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https://f1000research.com/articles/11-949/v1	18 Aug 22	{ "type": "Research Article", "title": "How mission-driven policies challenge traditional research funding systems", "authors": [ "Kaare Aagaard", "Maria Theresa Norn", "Andreas Kjær Stage", "Maria Theresa Norn", "Andreas Kjær Stage" ], "abstract": "For decades, public research funding systems have operated with the dual objectives of fostering research excellence on the one side and research contributing to innovation and growth on the other. These two objectives have to a large extent been pursued and institutionalized separately. Recently, a third objective has become increasingly prominent: to orient public research towards societal challenges through missions. This paper stresses that a precondition for achieving this new objective is successful coordination across the whole value chain of research and a more integrated and holistic approach to the design and implementation of funding policies. So far, limited attention has been paid to the risk that such coordination may be in conflict with dominant rationales underlying the current design of funding systems. In this study, we examine the challenges associated with the institutionalization of this emerging objective from both a theoretical and an empirical perspective. The theoretical analysis builds on historical institutionalism and argues that a partial conversion of the funding system as a whole is necessary for the new rationale to succeed. The empirical analysis focuses on two different national settings, the Danish and the Norwegian, and highlights challenges and tensions experienced by funding bodies responsible for operationalizing mission-driven research funding instruments, based on interviews with experts and key funding actors. We conclude that the key institutions in both national systems are attempting to adjust to the increasing political focus on missions through layering rather than processes of conversion, which we argue is necessary for funding organizations to successfully implement mission-driven policies. Finally, implications for the success of mission-driven policies are discussed.", "keywords": [ "research funding", "mission-driven policies", "funding bodies", "research policy", "innovation policy" ], "content": "Introduction\n\nThe science policy literature contains a number of attempts to identify and characterize different research policy ideas that have dominated different phases since World War II (see, e.g., Ruivo 1994; Elzinga and Jamison 1995; Stokes 1997; Guston 2000; Martin 2003; Aagaard and Mejlgaard 2020). The attempts have not least focused on the rationales for supporting public science and the way in which the relationship between the state and the scientific community should be organized. Three of the most dominant rationales can be labelled the ‘science push’ rationale, originally formulated in the report, Science: The Endless Frontier (Bush 1945), the ‘market-oriented’ rationale, drawing inspiration from the innovation systems literature (e.g., Lundvall 1992) but rooted in the demand pull model of innovation from the 1960s (Godin and Lane 2013), and the more recent ‘mission-driven’ rationale (e.g. Mazzucato 2018; Boon and Edler 2018). This latter ‘mission orientation’ is often loosely defined and closely interwoven with the related notion of ‘transformative innovation’ (e.g., Schot and Steinmueller 2018), but a broadly accepted minimum definition describes it as ‘a co-ordinated package of research and innovation policy and regulatory measures tailored specifically to address well-defined objectives related to a societal challenge’ (Larrue 2021b, 11).\n\nThese policy rationales have been turned into practical policy in a variety of ways over the last decades. Arguably, one of the most tangible and consequential manifestations of research and innovation policy rationales can be found in the design of funding systems and funding instruments. In other words, research funding can be seen as the operationalization of underlying policy rationales and as a direct link between policy on the one side and actual research activities, outputs, and impacts on the other. In this respect, funding mirrors the policy ambitions that governments hold for publicly funded research (Sörlin 2007).\n\nHence, this study builds on the observation that shifting policy rationales influence the design of funding systems. Based on a historical institutionalist approach, it examines challenges associated with institutionalizing the new mission-driven policy rationale within traditionally fragmented research funding systems.\n\nOther scholars have previously described the mission-driven policy rationale as being layered upon (rather than replacing) earlier science and innovation policy paradigms (Diercks, Larsen, and Steward 2019) given that all three rationales remain in use as arguments for policy intervention (Borrás and Edler 2020; Robinson and Mazzucato 2019). However, this paper argues that although new research and innovation policy rationales have largely been able to build on former dominant rationales, their institutionalization and, thus, their impact on research and innovation systems may entail profound conversion of the institutions and instruments used to pursue policy aims.\n\nFor a long period, the science push and market-oriented rationales were, to a large extent, institutionalized in separate institutions of, respectively, scientific excellence and innovation-oriented funding instruments. The process by which the market-oriented policy rationale was originally implemented could thus be fittingly described as ‘layering’, with different rationales organized side by side and enabled by additions to existing institutions (Thelen 2004).\n\nWe argue that the newer mission-driven policy rationale cannot be implemented by simply adding new institutions to existing ones but, rather, requires the redesign and repurposing of existing organizations and policy instruments. This is required partly because the complex, open-ended, and systemic characteristics of societal challenges demand a better coordinated policy approach drawing on the whole value chain of research and innovation as well as the full array of funding actors (Weber and Rohracher 2012; Grillitsch et al. 2019). Therefore, in historical institutional terms, the mission-driven rationale requires, not a relatively straightforward layering but a more challenging conversion of the entire funding system whereby ‘existing institutions are redirected to new purposes, driving changes in the role they perform and/or the functions they serve’ (Hacker 2004, 246).\n\nThe importance in the mission-driven rationale of directing policy instruments towards new ends and of achieving the necessary degrees of coordination among them has in itself been referred to as perhaps the most ‘wicked’ issue in policymaking (Kattel and Mazzucato 2018). Still, most of the literature merely highlights the need for better coordination but offers little insight into the concrete challenges of achieving coordination in funding systems that are traditionally fragmented.\n\nIn this study, we focus on the question of how to coordinate research funding and research efforts within a mission-oriented policy paradigm. Although representing only a subset of the policy instruments needed to realize the aims of mission-oriented policy, research funding is a crucial one given the importance of science for the development of effective solutions to many societal challenges. As we will argue, even within this subset of policy instruments, the coordination challenges related to the practical implementation of mission-oriented policies seem to be underestimated.\n\nFirst, we ask how the institutionalization of the mission-driven rationale can be characterized in a historical institutional perspective and what is the main challenge that can be expected in its implementation. Second, we explore how this emerging rationale is implemented in the national research funding systems of Denmark and Norway and investigate how experts and central research funding actors from these two systems view central challenges and barriers for a successful implementation.\n\nWhile the first part is mainly theoretical, the empirical exploration is based on a document- and interview-based examination of the Danish and Norwegian research funding systems. The two otherwise similar public research systems are interesting in a comparative perspective as they represent two distinctively different types of national research funding arrangements. While Norway has a broad and unified research council with a cross-cutting responsibility for the whole value chain of research, Denmark still has a system with a number of distinct and mutually independent public research funders.\n\nHowever, in recent years, both countries have pursued a challenge-driven approach to research funding aimed at addressing societal challenges and are currently transitioning to a formal mission-driven policy. In Denmark, a mission-driven policy was introduced in 2020 (with a singular focus on climate change and green transitions), while it is under development in Norway. Although challenge- and mission-driven policies are often used interchangeably in the literature (e.g., Mazzucato, Kattel, and Ryan-Collins 2020), we argue that the challenge-driven research policies in the two countries studied can be seen as a first generation of mission-driven policy, the implementation of which offers insight into the challenges likely to be faced in the institutionalization of the next generation. As such, insights into the challenges encountered in this process can help inform the further transition towards mission-driven funding strategies.\n\nIn the following, we, first, present a brief outline of the theoretical framework before examining the characteristics of the three policy rationales and how they might co-exist. We subsequently present our methods and data as well as the results of our empirical analysis. Finally, we discuss our findings, outline our conclusions, and consider their policy implications.\n\n\nTypes of gradual institutional change\n\nResearch funding systems are often portrayed as layered entities where new research policy rationales become institutionalized on top of existing ones and where balances between them change and evolve over time (Edqvist 2003; Lepori 2011; Aagaard 2017). A useful theoretical frame for examining such processes has been developed by Thelen (2004) within a historical institutional framework. Here, they challenge the concept of punctuated equilibrium, which seeks to explain institutional change as path dependency interrupted by sudden and revolutionary shifts. Instead, Streeck and Thelen propose an alternative and theoretically innovative framework, using an empirically based typology to highlight how institutions can evolve and change more gradually over time (see also Mahoney and Thelen 2010). This approach has proven useful in a number of cases and has, in a few instances, also been taken up by the innovation and science policy literature and by the literature on policy mixes (see, e.g., Howlett and Rayner 2007; Kern and Howlett 2009; Howlett and Rayner 2013; Aagaard 2017).\n\nThree types of gradual changes – layering, displacement, and conversion – are of particular interest in this analysis of co-existing research policy rationales and may help elucidate potential challenges to the implementation of policy changes. The first type, layering, involves ‘the grafting of new elements onto an otherwise stable institutional framework’ (Thelen 2004, 35). In contrast to more radical changes, layering does not initially include the creation or displacement of institutions but represents additions to existing ones (Thelen 2004). However, what is at first introduced as marginal correctives may over time lead to substantial change when additions sum up or when new elements grow at a faster pace than old ones. Displacement covers processes where the balance between various elements of existing institutions changes over time. A central mechanism at play here is differentiated growth, which occurs when some elements increase their market share at the expense of other elements and, thus, gradually alter the institutional balance (Streeck and Thelen 2005). Finally, conversion ‘occurs when rules remain formally the same but are interpreted and enacted in new ways’ (Mahoney and Thelen 2010, 10). In other words, the term captures situations where ‘existing institutions are redirected to new purposes, driving changes in the role they perform and/or the functions they serve.’ (Hacker 2004, 246).\n\nFurthermore, the typology indicates that different types of policy changes will likely meet different degrees of resistance. Typically, it is assumed that attempts to suddenly reform existing structures by radical changes will meet strong opposition and counter mobilization, while more gradual institutional transformation processes such as layering and displacement often have a better chance of success because they can be initiated without confronting change-resistant structures head on (Streeck and Thelen 2005: 19). However, although conversion processes are usually gradual as well, they are likely to meet resistance because they tend to challenge already existing institutions.\n\nIn the following sections, we will use this theoretical framework to investigate how evolving research policy rationales may be institutionalized in research funding systems. The core argument is that the process of layering is central to understand the way in which the science push and the market-oriented rationales have been institutionalized separately and the ways in which they have co-existed over time. However, in order to examine how the emerging mission-driven rationale can be institutionalized, we also need to bring in the notion of conversion. We elaborate on this argument in the following section.\n\n\nChanging policy rationales and their impact on institutional change in the research funding system\n\nAs alluded to earlier, the science and innovation policy literature offers a number of attempts to identify and categorize policy rationales. In the following, our focus is restricted to three of the most dominant rationales since World War II (see, e.g., Schot and Steinmüller 2018 for a similar distinction). The examination builds on previous work but also extends on this with a specific focus on research funding arrangements and the way in which the emerging mission-driven policy rationale may challenge existing institutions.\n\nNotice, however, that these ideal type policy rationales are unlikely to be found in their pure form in practical policy. Rather, we are likely to observe different balance points and degrees of separation between different rationales varying over time and across national contexts. Indeed, many different and even conflicting policy rationales can be identified at any given point in time, as rationales evolve – and dominating paradigms shift – over time (Skogstad 2011). Likewise, it is important to stress that aspects of recent policy rationales may have existed already in earlier periods. For instance, the mission-driven rationale is not new, as key aspects of this rationale were formulated early on, although in a quite different form (Foray, Mowery, and Nelson 2012; Ulnicane 2016; Robinson and Mazzucato 2019).\n\nUp until the 1980s, the dominating research policy rationale prescribed governments to provide universities with institutional funding for research with few strings attached (Martin 2003) or to channel funding through academically oriented research councils (Rip 1994; Sörlin 2007; Aagaard 2017). The policy objectives first and foremost found their rationale in the linear science push model that emerged out of the Vannevar Bush (1945) report Science: The Endless Frontier (Godin 2006). It rested on an underlying belief that if governments allocate money to basic research, societal benefits will eventually, but unpredictably, materialize and contribute to increased welfare and long-term economic growth (Cohen, Nelson and Walsh 2002; Schot and Steinmueller 2018). The science push linear model of innovation was further cemented by the successful application of chemistry and physics to war efforts during World Wars I and II, as well as by the rise of ‘Big Science’ during the interwar years, all of which opened up for additional funding and greater autonomy in basic science (Kline 1995).\n\nSeveral authors have described this model as the ‘traditional social contract for science’ (Van der Meulen 1998; Martin 2003). It involves extensive reliance on the internal mechanisms of science for quality assurance, significant individual and organizational discretion, and high, but largely unspecified, expectations that academic advancements will eventually create societal value (Aagaard and Mejlgaard 2020). Theoretically, the rationale also rests on economic research highlighting technological change as the main factor behind growth (Solow 1957) and stressing a market failure where private companies lack incentives to invest sufficiently in research (Nelson 1959).\n\nOverall, this rationale prescribes a clear division of labor between different actors. On the one side, public science is expected to seek advancement of knowledge without considering potential societal value. On the other, the private sector, is expected to transform the findings into innovations (Schot and Steinmueller 2018). Another key characteristic is that society should not interfere with the direction of research. Rather, the direction should solely be determined by internal priorities based on the perception that the self-organizing character of science automatically directs individual researchers towards the most promising and important topics (Polanyi 1962).\n\nWhile this rationale, in particular, was dominant for university research from World War II until the 1980s, some of the underlying ideas have seen a revival in the last two decades in the form of strengthened excellence orientation (see, e.g., the establishment of ERC and national equivalents).\n\nAlthough the science push rationale never disappeared, the underlying policy ideas became increasingly challenged from the 1960s and onwards. Where the traditional social contract provided basic researchers with great autonomy, the emerging policy rationale implied that in return for public funds, scientists should be held more directly accountable and should be guided towards addressing research problems of industrial and social relevance (Gulbrandsen and Smeby 2005). Initially, the science push model was supplemented by a demand pull model that emphasized the role of market demands (rather than internal priorities in science) in driving technological innovation (Godin and Lane 2013). This shift in perspective was brought about by increasing political dissatisfaction with the lack of direct and easily measurable pay-offs from investments in basic research (Wise 1985; Pavitt 2001).\n\nThe view was not only that a turn towards a global knowledge and innovation economy was taking place (Stehr 1994), but also that the linear model was too simple as a foundation for funding decisions (Kline and Rosenberg 1986; Aagaard 2017). In particular, a new understanding of the dynamics by which innovation occurs began to challenge the linear science push rationale and accentuated the need to consider feedback mechanisms and interdependencies. Universities therefore began to be perceived as key organizations that should contribute to national wealth creation by linking their work closely to the needs of the economy (Martin 2003; Etzkowitz and Leydesdorff 2000).\n\nThis market rationale comes in various forms. What is highlighted here can first and foremost be perceived as an exponent of the ‘innovation systems’ thinking of the 1990s (Lundvall 1992; Nelson 1993) stressing the need for strengthening networks, collaboration, and co-production to increase and accelerate the uptake and commercialization of science and to make universities themselves more entrepreneurial and professional. Expected results are more market-oriented outputs from universities (e.g., in the form of patenting and licensing of research outputs and spin-out companies) as well as broader effects on private firms’ innovation, turnover, growth in employment, and, ultimately, competitiveness. With this rationale, the previous idea of market failure was supplemented by ideas of institutional and interactional or ‘systemic’ failure as a barrier for productive interactions and positive societal impact (see, e.g., Bleda and del Río 2013). Hence, the clear separation of tasks between public science and private companies from the science push rationale was abandoned.\n\nInstead, the market-oriented rationale promoted the view that useful knowledge is generated through interaction among actors in national, regional, technological, or sectoral innovation systems. To the extent that the direction of research should be influenced through funding, it should be based on strategic assessments of medium- and long-term commercial potential. In relation to the question of how to fund research, this rationale has placed the responsibility for funding in dedicated agencies and/or strategic funding instruments that emphasize public-private collaboration.\n\nHowever, also the market-oriented rationale has become challenged over time. In particular, it has been argued that the lack of directionality and its focus on economic effects have created new problems and that current societal challenges can, at least partly, be linked to technological innovation with unintended side effects (e.g., Weber and Rohracher 2012; Diercks, Larsen, and Steward 2019). In other words, a strong market orientation may lead to societally undesirable priorities if not balanced against other considerations (Kallerud et al. 2013). There was also growing agreement that the market-oriented rationale was not sufficiently effective in fostering solutions to complex problems in society (e.g. Schot and Steinmueller 2018). In recent years, a different policy rationale has therefore been (re-)introduced seeking more explicitly to enable research to contribute to tackling societal challenges through, for instance, politically defined ‘missions’.\n\nWhile there may be many interdependencies and overlaps between societal and economic objectives, a key difference between the market-oriented rationale and the mission-driven rationale is that the latter involves much more direct steering of efforts towards specific objectives based on broad societal needs rather than narrow economic objectives indirectly steered by market demands (Diercks, Larsen, and Steward 2019). Mission-driven policy approaches therefore entail a strengthened effort by policymakers to shape the direction of scientific and technological advance (Weber and Rohracher 2012). Hence, with this rationale, the role of the state is changing from primarily supporting connectivity and learning within systems to shaping the direction and coordination of research and innovation activities.\n\nThis shift is most clearly expressed in the recent mission-driven policies of the European Union, addressing grand societal challenges and the UN Sustainable Development Goals (Mazzucato 2018). These policies define specific areas of societal concern and seek to tackle societal challenges such as food security, energy, and climate. Hence, the main objective of the emerging rationale is not to enhance national competitiveness but rather to solve global challenges (although the two objectives are often seen as complementary). Similarly, the main concern is not market failure or systemic failure but rather directional failure (Chataway et al. 2017). This directionality is expected to be based on social choices rather than economic potential (Schot and Steinmueller 2018). Finally, the mission-oriented rationale also differs in its emphasis on collaboration and division of labor both within the academic system and between the academic system and society. Broadly speaking, societal challenges are perceived as too complex to be addressed by single disciplines. Similarly, the perception is also that societal challenges cannot only be solved though collaboration between public science and private companies but requires multiple types of actors negotiating with different motivations and priorities towards social choices (Kallerud et al. 2013). This includes non-governmental organizations, philanthropic foundations, and social entrepreneurs, which are expected to catalyze innovation and, hereby, address problems that are insufficiently targeted by governments or the market (Kallerud et al. 2013).\n\nThe emerging mission-driven rationale not only distinguishes itself from the science push and the market-oriented rationales, but also from traditional mission-driven research policies of the 1950s to 1980s. These policies were typically characterized by goals determined by single government institutions, often fully funded and implemented by independent, dedicated agencies such as the Defense Advanced Research Projects Agency (DARPA) or NASA and centered on well-defined objectives requiring solutions of a scientific or technological nature. However, since challenges today are of a different nature to the challenges that inspired the Apollo program and the Manhattan Project, modern missions need to take new forms and should be funded differently (Nelson 1977; Ulnicane 2015; Boon and Edler 2018). Among other things, funding is expected to come not only from one dedicated agency, but rather from a variety of public and private sources targeting all research actors and the whole value chain of research (Mazzucato and Semieniuk 2017).\n\nMission-driven policies are closely interwoven with the notion of challenge-driven policies. Indeed, they are often used interchangeably, with challenges seen as the driving force for the formulation of missions (see, e.g., Mazzucato, Kattel, and Ryan-Collins 2020). However, we observe a change in the way in which policies are named and described since the beginning of the century: A shift from the introduction of challenge-oriented policies by the EU, and subsequently by several countries, to a more recent shift towards mission-driven policies, again pioneered by, among others, the EU but also seeping into national policy development.\n\nKey characteristics of the three policy rationales are summarized in Table 1.\n\nFrom the historical institutionalist perspective, it can be argued that traditional research funding systems largely adjusted to the introduction of the market-oriented rationale through a process of layering. This resulted in funding systems where the science push and market-oriented rationales could co-exist side by side but implemented through separate funding bodies or distinct funding instruments. This separation is observable in many countries and, such as in the EU research funding system, as exemplified by the division of labor between the European Research Council and the Horizon Framework Program.\n\nIn many countries, as in the EU, different independent funding organizations with distinct missions clearly linked to one of the two rationales have been established. As we will show in the empirical analysis, this is the case in Denmark. In other countries, such as Norway, we find a more unitary research funding system in which the traditional separation between predominantly science-oriented and market-oriented rationales is still present internally in the form of dedicated programs and instruments linked to one of the two rationales.\n\nTo a large extent, both types of systems have upheld this separation between the two rationales and pursued their objectives more or less independently of each other. However, the distinction is not entirely clear-cut. For instance, scientific excellence is typically invoked as one of the assessment criteria, also in market-oriented programs. Struggles between proponents of either rationale have to a large degree been about balances, displacement, and differential growth (see, e.g., Aagaard 2017 for an example of this development in a Danish context). However, although separation between the rationales has been the norm in many systems, the lack of integration has often been viewed as a problem. The attempt to establish effective coordination of the public research effort has therefore been a continuous concern for most governments over the years, but the general impression is that coming to grips with this task has been difficult (Skoie 2000).\n\nIn contrast, the main argument of this paper is that the emerging mission-driven rationale cannot be institutionalized separately if it is to succeed in its aims. This rationale demands a strong state-led directionality that cuts across the whole value chain of research and innovation, targets many different research performers, draws on multiple funding sources, and is based on broad social choices. It therefore depends on a more holistic, system-wide coordination, where different research areas, research types, and research projects all contribute towards the same ultimate goals. Accordingly, a general characteristic of modern mission-driven approaches is that they attempt to address what Weber and Rohracher have named ‘policy coordination failure’ (2012). This failure is attributed to lack of policy coordination across different systemic levels; lack of horizontal coordination between research, technology and innovation policy, sectoral policies, and cross-cutting policies; and lack of vertical policy coordination between ministries and implementing agencies.\n\nHowever, even if we restrict our focus to the research part of this wider system, it is clear that missions require a high degree of coordination. It is necessary to build a diverse but also coherent portfolio of projects and to make a continuous effort to evaluate the contribution from individual projects to the mission objectives in order to re-direct funding to other activities if necessary (Mazzucato 2018). This portfolio management approach is an argument for more proactive and flexible management of funded projects in which the managing organization relies on in-house capabilities to balance the risk of wasting resources on futile projects with the risk of writing off their unexpected value (Mazzucato 2018a).\n\nHence, where the market-oriented rationale could be layered unto and pursued largely separately from the science push rationale, the mission-driven rationale requires a more holistic funding approach where different elements are considered more as parts of a greater whole and coordinated as such. This leads to an increased demand for coordination and portfolio management. Rather than displacing institutions developed to serve science- and market-oriented rationales, mission-driven policies require existing research funding institutions and instruments to be adjusted to relatively high degrees of directionality in research funding and to new aims (e.g., aiming for broader societal effects rather than the realization of economic impacts). This is also likely to have implications for the criteria used to assess and select projects for funding. For instance, instruments that deploy mission-driven policies would likely include an assessment of the ability of proposed projects to contribute to solutions to a given societal challenge or mission, in addition to conventional assessment criteria related to, for instance, the scientific excellence and potential socio-economic impact of the proposed research (Normann et al. 2022).\n\nA shift towards the mission-driven rationale is also likely to require new means. This includes an increased need for coordination across actors and policy areas and portfolio management of grants within given thematic missions, as stated earlier. To a large extent, the mission-driven rationale must be integrated in already existing research funding systems – including institutions that have evolved to serve the science push rationale as well as those that deploy market-oriented instruments – and to provide both old and new funding instruments with a common direction. It also includes an increased need for funders to follow up on funded activities, monitoring their progress and contributions towards targeted societal missions in order to perform actual portfolio management (Normann et al. 2022).\n\nIn historical institutionalist terms, we therefore argue that what is required is (at least partially) a conversion of funding systems, where the existing institutions are re-directed to new purposes (Hacker 2004). However, these requirements of conversion may challenge institutions that have for long evolved to serve other policy rationales. Thus, the implementation of the mission-driven rationale may lead to tensions, symbolic implementation, or even resistance from engrained funders. In the following, such theoretically expected tensions are explored in two illustrative case studies of the Danish and Norwegian research funding systems.\n\n\nMethods\n\nThe present study consists of the hitherto theoretical analysis of the potential co-existence of three policy rationales and of a following empirical analysis of two selected national research funding systems. However, both the theoretical and the empirical analyses are relatively broad-brush examinations focusing on general policy rationale characteristics and general system-level funding features. Hence, the intention is not to give a detailed account of all aspects of the selected policy rationales or scrutinize the selected national funding systems. Rather, the aim is to highlight key features with implications for the way in which the different policy objectives may be pursued jointly or separately, as well as the challenges associated with a successful implementation of the mission-driven rationale. Accordingly, the empirical analysis is not an in-depth examination of concrete coordination mechanisms, but rather an exploration of expectations, perspectives, and viewpoints of key actors in the two selected systems.\n\nThe present study is part of the larger four-year project PROSECON: ‘Promoting the socio-economic impact of research – the role of funding practices’, which is funded by the Novo Nordisk Foundation. This overall project has influenced the selection of countries, funders, interviewees, and themes for the interview. More specifically, the study is linked to another study examining in detail how targeting is employed by research funders in relation to six selected research funding instruments – three responsive mode instruments and three instruments targeting both market objectives and societal challenges. This examination, including the interviews conducted for that study, feeds into the present study.\n\nAll respondents were informed of the aims of the study and the ways in which their personal data would be processed. Written informed consent was obtained from respondents.\n\nGiven that the study is based solely on interview data and the limited sensitivity of the data collected, the level of risk for human participants was deemed to be relatively low. As such, the authors did not apply for approval of the study from the university’s ethics committee.\n\nThe overall PROSECON project focuses on three countries: Denmark, Norway, and the Netherlands. However, in this specific study, we only compare Denmark and Norway. As argued by van der Meulen and Rip (1998), the intermediary level of funding organizations is populated differently in different countries, and this ‘ecology’ is likely to influence the direction, outcomes, and impacts of conducted research. The path dependency of these ecologies is also likely to influence the way in which new rationales become integrated in existing systems. In this study, we therefore selected the two most differing countries: Denmark, with a funding system consisting of multiple funding bodies with distinct aims and mandates, and Norway, with a broad and unified research council.\n\nIn this study, we restrict ourselves to an examination of the main public funding bodies operating at a national level, thus excluding domestic private funders and supranational funders. In addition, we focus on dedicated research funding organizations only, thus excluding research funding instruments in government ministries and agencies.\n\nVia publicly available documents from within each country, we identified the key public funders responsible for the allocation of competitive research funding. We mapped their aims, main characteristics, and key funding instruments in order to identify the funding bodies responsible for the main public mission-driven research funding instruments in each country. The selected funders are, for Denmark, the Independent Research Fund Denmark (IRFD) and the Innovation Fund Denmark (IFD), and, for Norway, The Research Council of Norway (RCN).\n\nFor each country, interviews with both administrative staff employed in the selected funding bodies and members of the boards were undertaken. All the interviewed board members were external, that is, not employed by the funding body but appointed to their role on the board. These interviews provided first-hand insight into the history, day-to-day management, and ongoing internal assessment and adjustment of the selected instruments. Five interviews were undertaken with representatives from IRFD and IFD, while three interviews were undertaken with RCN staff and board members.\n\nThe interview guide was developed by the authors for the purposes of this study and can be found in the Extended data (Norn et al. 2022). The guide was not validated through pilot testing but designed as a semi-structured interview guide, allowing the authors to adapt interview questions to the experiences and expertise of the respondents.\n\nThe aim of the interviews was to collect data on the funders’ perspective on their mission and overall aims as well as their role within the national research funding system. The interviews also explored the extent to which targeting efforts and mechanisms were determined by external actors (e.g., policymakers who allocate funding to be distributed by the funder) and the extent to which they were decided upon by the funders themselves. We also asked about issues related to coordination and portfolio management. This study in particular builds on the latter, but also draws on the remaining issues as background information.\n\nFinally, a background interview was undertaken with two academic scholars with great insight into European research funding systems and focusing on general challenges in relation to coordination of funding bodies or instruments and portfolio steering. In addition, we interviewed three representatives for the Dutch national research council, NWO, focusing on similar funding instruments. Although this paper focuses on the Danish and Norwegian cases, insights into the Dutch funding system contributed to the background knowledge for this present study.\n\nInterviews were undertaken during the COVID-19 pandemic. Due to travel and transport restrictions, all interviews were undertaken and recorded using Microsoft Teams. Two of the authors performed the interviews, and both these authors participated in all interviews. Interviews were subsequently transcribed by a research assistant, and data analysis was performed by the authors.\n\nThe interviews were conducted in early 2021. As such, the Danish government’s introduction of a green mission-driven research policy in late 2020 had not yet been implemented, while, as previously mentioned, a formal mission-driven policy was still under development in Norway. As such, the timing of the interviews allowed us to capture experiences and practices surrounding the implementation of the former generation of challenge-driven funding instruments in both countries, on the cusp of a transition to next-generation mission-driven instruments. The interview guides can be found in Extended data (Norn et al. 2022).\n\n\nThe Danish and Norwegian research funding systems\n\nThe empirical analysis consists of two sections. First, we examine the two national research funding systems with a focus on their institutional background as well as current configurations and mission ambitions. In the second section, we discuss key questions and challenges for the implementation of mission-driven research funding policies. The first section builds mainly on the document study, but is also informed by the interviews. It is vice versa for the second section.\n\nBackground\n\nSince the late 1960s, Denmark has had a traditional, academically oriented research council system, which, in spite of various reforms, has remained relatively unchanged in its basic structure. In addition, a ‘Centers of Excellence’-oriented funding organization was established in 1993 in the form of the Danish National Research Foundation (DNRF). The basic institutional funding configuration supporting the science push rationale has thus been rather stable over time.\n\nThe implementation of more market-oriented objectives, on the other hand, has been much more shifting and unstable. The first large-scale attempts to stimulate economic and wider societal impact came in the 1980s based on the emerging policy belief that industrial growth should be based on technologies such as information technology, biotechnology, and materials science (Aagaard 2011; Grønbæk 2001). This led to a strong growth in earmarked strategic program funding over the following years – mainly administered in special committees outside of the existing research council structure. During the 1990s, many of these long-term programs were replaced with more short-term and more narrowly defined programs. As a consequence, many strategic research areas have thus been lacking long-term stability and an overall strategic direction.\n\nIn 2001, a new Danish government initiated a restructuring of the public research funding system. The traditional academic research councils were subsumed under a new umbrella organization, the Independent Research Fund Denmark (IRFD), and three new market-oriented research funding organizations were established alongside the science push part of the system (consisting of IRFD and DNRF). The new market-oriented funding organizations included the Council for Technology and Innovation (established in 2002), the Strategic Research Council (established in 2004), and the Advanced Technology Foundation (established in 2005). This layering strategy subsequently opened up for differentiated growth, leading to displacement in favor of the market-oriented funders. In 2013, these three funding organizations were merged into a united organization labelled Innovation Fund Denmark (IFD). The result was a research funding system with a sharp demarcation between funders relying on the science push rationale and funders with a clear market-oriented rationale.\n\nCurrent system\n\nWhile the basic structure remains unchanged, this sharp demarcation has become a bit more blurred recently. On the one hand, IRFD has – in addition to its core mission to support and promote responsive mode research – been given the responsibility to fund politically defined thematic research from 2018 and onwards. On the other hand, IFD is more explicitly asked not only to support entrepreneurship, partnerships, and technologies that can be translated into viable businesses and stimulate growth and employment, but also to focus on solutions to key societal challenges and broader societal effects. A policy expectation has been that IFD needs to move from a one-by-one funding approach towards a more strategic and coherent allocation of funding.\n\nThese expectations were further reinforced when the Danish Government in September 2020 launched a new green transition research strategy with four concrete missions: carbon capture, green fuels (e.g., Power-to-X), climate-friendly agriculture and food production, and re-use and reduction of plastic waste (The Danish Government 2020). The strategy states that the government will support dialogue and collaboration among the central actors within the green transition sectors – including research funding organizations, the higher education and research institutions, and the private sector – to establish a clear direction and a more coherent effort across the whole value chain from basic research to commercialization. However, the policy instructions do not lay out more precisely how coordination and portfolio management can take place in relation to funding of this mission-driven research.\n\nA new funding instrument, InnoMissions, was introduced to support this transition towards green missions, which builds on, but extends, the former main instrument of IFD, ‘Grand Solutions’. Indeed, both IFD and Grand Solutions were created as by-products of a national innovation strategy introduced in 2012 that formally defined societal challenges as the aim of research and innovation policy (The Danish Government 2012). Alongside the development of IFD, the thematic funding instruments of IRFD were introduced. Thus, the current shift towards green missions in Danish research and innovation policy builds on almost a decade of experience with challenge-oriented research funding instruments.\n\nA recent report (Wohlert et al. 2021) offered recommendations for the implementation of a Danish mission-driven policy on green energy, underlining, among other things, the need to involve a broad range of societal actors to increase the likelihood that outputs from funded activities will be developed into effective technologies and approaches to mitigating the effects of climate change and supporting a green transition. The authors also call for increased and more effective coordination across relevant ministries and funding bodies. Similarly, an expert group reviewing the Danish science and innovation system pointed to the need to strengthen coordination across actors and instruments in the Danish system (European Commission 2019). Indeed, the authors of this report argued that such coordination was key to achieving innovation aims in Denmark but that past reforms had focused on minimizing the need for coordination instead of bolstering increasingly important links between actors and activities in the research and innovation system.\n\nBackground\n\nNorway established three research councils during the late 1940s, devoted to industrial needs and technological development, agriculture, and academic research, respectively. A council devoted to fisheries was added in 1972, while a fifth devoted to applied social sciences was established in 1987. By the late 1980s, Norway thus had a structure with a mixed but separated set of academic, technological development, and innovation-oriented councils. However, a perceived lack of coordination, excess administration, and lack of integration between basic and applied research led to a merger of the five councils into the broad and unitary Research Council Norway (RCN) in 1993 (Skoie 2000). The aim was to develop a comprehensive, simple, efficient, and well-coordinated funding organization to facilitate integration of basic and applied research and to foster interdisciplinarity (Skoie 2000). Hence, the new council was not merely to be an umbrella organization for councils attached to four different ministries and building on different policy rationales. It was to be a fully integrated council under one ministry (the Ministry of Education and Research) with an entirely new internal structure.\n\nFrom the beginning, RCN was divided into six non-disciplinary operational divisions, all integrating both basic research and innovation, but after an evaluation of the council in 2001 (Arnold et al. 2001), it was reorganized into three broader divisions. A main reason was that RCN still reproduced the fragmentation of its predecessor organizations. Furthermore, having 16 ministries providing it with funding and instructions without having significant internal ‘strategic’ resources made it difficult to fulfill stakeholders’ expectations and also created a heavy organizational and administrative load. However, many of these problems persisted, and RCN was therefore reorganized again in 2010. The new organization addressed the need for thematic and disciplinary expertise at the division board level and allowed RCN the possibility to strengthen its position in relation to the generation of national research and innovation strategies.\n\nCurrent system\n\nThroughout this period, RCN has stood out in a comparative perspective as one of the broadest and most unified national research councils in Europe. Unlike most other research funding agencies, RCN covers all research disciplines and sectors, including support of research-based innovation. A large share of all public R&D funding is channeled through RCN via a number of instruments, ranging from centers of excellence, infrastructure, and large thematic programs to business-oriented and user-driven projects. The Ministry of Research and Education and the Ministry of Trade, Industry and Fisheries are the most important contributors to RCN’s budget, but RCN administers funding from a total of 15 ministries.\n\nHowever, until recently, the different historical institutional backgrounds were still mirrored in the structure of the funding programs. Rather than fully integrated, it was a layered system, grounded in vastly different legacies and ways of thinking. According to critics, the result was too much silo thinking with ministries funding research only within their specific area of policy. This was also stated in a 2012 evaluation that highlighted difficulties with the coordination of research and innovation policy at the national level, stressing that a national strategy for research and innovation should be more than the sum of what 16 ministries want. In the same evaluation, it was stated that the responsive mode funding was to a large extent fenced off from the rest of the system. This science push part of the system was described as an ‘aggregation machine’ – responsively funding proposals but not with RCN acting as a change agent (Technopolis Group 2012).\n\nThis type of criticism eventually led to a major reorganization of RCN beginning in 2019. Most importantly, RCN established 15 portfolio boards under a single executive steering committee. Each portfolio board is responsible for making investments within a specified but relatively broadly defined thematic area. They are also responsible for monitoring investments within their respective portfolio area when investment decisions are made by other portfolio boards. Moreover, the portfolio boards advise the CEO of RCN on overall holistic follow-up of the portfolios within their area of responsibility and manage the budget funds they are allocated by RCN’s board.\n\nWith regard to the introduction of a mission-driven policy, Norway has not yet decided on concrete missions. It has, however, outlined a framework and formulated the principles on which a mission-driven approach should build as well as sought recommendations for the design of a Norwegian mission-driven innovation policy (Larrue 2021a; Normann et al. 2022). The ambition is to establish clearly directed missions that mobilize along the whole value chain of research and innovation, to utilize existing R&D instruments, to take advantage of active portfolio management to ensure stronger interaction across instruments, and to have a consistent and coherent coordination (Forskningsrådet 2020).\n\nWithin Norwegian research policy, targeting research at addressing societal challenges has long been a central rationale, which is why more targeted missions in a formal mission-driven policy would not represent a departure from prior policy objectives (Normann et al. 2022). This challenge-driven focus has been implemented in RCN in instruments such as the ‘Collaborative Projects to Meet Societal and Industry-Related Challenges’. The recent reorganization of RCN into portfolio boards was intended to strengthen the existing ability of the council to deliver on policy aims of promoting research that can deliver solutions to societal challenges.\n\nA recent research report presents recommendations for the Norwegian implementation of mission-driven policies and emphasizes the importance of mobilizing a broad set of actors across sectors and policy areas and the demands that this places on the ability of central institutions to coordinate mission-driven activities (Normann et al. 2022). Moreover, the authors of the report argue that the Norwegian system is hampered in this regard by a lack of tradition and mechanisms for coordination across ministries and sectors – particularly beyond the research funding system – although it has strong traditions for coordinating research funding within sectors (a similar conclusion is presented in Larrue 2021a). The same report suggests that mission orientation will require more portfolio management and follow-up monitoring of granted projects than practiced today in RCN.\n\nAs described above, both the Norwegian and Danish research funding systems have until recently been characterized by a rather sharp separation between programs or funding organizations based on the science push rationale on the one side and programs or funders adhering to the market-oriented rationale on the other. Despite important differences in organization (separated funding organizations vs. a unitary research council), the two funding systems may both be described as layered entities with limited integration across the two traditional rationales.\n\nAs mentioned earlier, although a societal challenges perspective has been implemented in research funding in both national systems in recent years, a formal mission-driven approach has only recently been introduced (in Denmark) and is still under consideration (in Norway). As such, examining experiences in both countries with challenge-driven research funding instruments, and how these have been institutionalized, provides a window into the challenges likely to be faced in the implementation of the next generation of mission-driven policies, which will come with strengthened expectations of coordination and portfolio management, and which we turn our attention to in the next section.\n\n\nResults: Challenges for a successful implementation of mission-driven policies\n\nAs described in earlier, mission-driven policies are likely to pose challenges to research systems that have evolved to mainly serve science push and market-oriented rationales, as they require existing research funding institutions and instruments to be adjusted to accommodate relatively high degrees of directionality in research funding to new aims, such as aiming for broader societal effects rather than the realization of economic impacts, and new means, including an increased need for coordination and portfolio management, but also an increased need to follow up on funded activities, monitoring their contributions towards the societal mission they are motivated by. This section builds mainly on interview material, but is also informed by the document study, and serves to illustrate key challenges encountered by the selected Danish and Norwegian research funders in their implementation of challenge-driven research policies.\n\nMission-driven policies involve a high degree of directionality in research funding, as funding is allocated to the pursuit of specific, politically prioritized missions.\n\nOne of the main challenges mentioned by the interviewees, related to the expectations of increased coordination at the project level and more active portfolio management at the strategic level, has to do with a perceived trade-off between directionality and quality. There is a general concern across all interviewees that increased directionality (which per definition narrows the calls) may harm the scientific quality and perhaps also the impact of the research investments. All interviewees thus emphasize that they do not only work actively to influence the political formulation of call texts to make sure that they are formulated as broadly as possible, but also subsequently seek to interpret them as broadly as possible.\n\nIRFD is a good example of this approach. First of all, IRFD seeks to stay as close as possible to the political formulation of themes and to avoid additional narrowing of calls. They strive to allow as many researchers from as many disciplines as possible to apply as well to give individual researchers a large degree of freedom in terms of motivating their project within the call. It was stressed that this approach is not a matter of disagreement with the priority of the politicians but that it was chosen out of a genuine concern for the quality. However, the IRFD representatives stress that the most important part of this work takes place before rather than after the political formulation of the call texts. Here, they try to influence the political process as much as possible to avoid narrow thematic priorities.\n\nAlso, IFD has traditionally tried to interpret not only the specific call texts, but also their legal basis as broadly as possible, and even to have an open call once a year. However, this has become increasingly difficult as almost all of their funding is now tied to green transition research and, often, to quite specific technologies. The interviewees from IFD sees this as an important constraint and fears that it will reduce the impact of the investments. In particular, they highlight the fact that the open calls have normally been a tool for filling in the holes between thematic calls and that these calls have enabled them to also support high-quality proposals that fall outside or in-between calls.\n\nThe same concern is found in the Norwegian context, where also the portfolio boards seek to make calls as broad as possible. Here, it is also stated in relation to the thematic calls that although RCN requires the highest possible quality, there is a clear trade-off. Accordingly, the interviewees stated that when you narrow down the thematic calls, you have less competition and, potentially, lower quality. However, while this concern is also present in Norway, it comes across as less pronounced than in Denmark – perhaps because applications can be reallocated to other calls by the portfolio boards.\n\nMission-driven policies differ from their counterparts grounded in a market-oriented rationale by aiming for broader societal effects rather than the realization of economic impacts such as growth in productivity, turnover, or employment among private firms.\n\nInterviewees mentioned that a more concrete challenge for an active portfolio steering is related to difficulties with formulating criteria that allow the funders to select projects based on how they fit into an overall portfolio. These difficulties are clearly linked to the trade-off described above. It was a general impression across the interviewees that coordination and steering may be possible in relation to the formulation of calls but that active portfolio management is very difficult in relation to the selection of specific projects. As stated in one of the expert interviews, if you consider using portfolio thinking in assessment or allocation decisions, you will immediately be asked to stick to the criteria described in the call. So, assessment panels can only take the overall portfolio of projects into account if the criteria for this are clearly spelled out beforehand.\n\nThere are also challenges in relation to the assessment of the formulated criteria, where broader impact or portfolio-oriented criteria are perceived as difficult to handle. Across most of the interviewees, it is stressed that scientific quality is often less problematic to assess than expected impact or fit with a mission-based strategy.\n\nFor IRFD, it is stated that there are no clear requirements as to how these impact statements are understood, evaluated, or weighted. In their thematic calls, they receive both very solution-oriented applications and basic research-oriented projects, and it is seen as difficult to determine the weights between project types in advance/as a generic form. In the same vein, the interviewees also highlighted that a good applicability dimension will never outweigh the scientific quality requirement. Only if projects are of identical scientific quality can other requirements be added to the overall assessment. It is academic quality understood as excellence or expected breakthroughs – not applicability potential – that is used to compare the different projects. Nonetheless, applicants have to account for the potential applicability perspective in their application for the thematic calls. For IFD, however, this trade-off is perceived somewhat differently. As stated by one of the interviewees, there is not necessarily full correspondence between what is good for science and what is good for society, but also here it is acknowledged that potential impact is difficult to assess – in particular when impact is viewed in a societal perspective rather than at a single firm level.\n\nAlso in the Norwegian interviews the same tension can be identified. Here, it is stated that it is the academic score of each project that constitutes the main criterion in the assessment. Additional criteria can be added in the call text. This could be that female PIs or hydrogen-related research should be prioritized. Hence, the opportunity to consider other criteria is present but only if it is included in the call description. In reality, however, this is difficult, and an interviewee mentioned that the portfolio board has had applications that they could not reject even though they did not really consider them appropriate. The reason was that they had not been sufficiently specific in their call description. Along the same lines, it is also underlined that the portfolio boards almost always follow the ranking of the projects from the administration and the assessment panels. The scores that the experts provide cannot be overturned or changed, so the boards have limited influence on the selection of concrete projects.\n\nThe assessment of projects according to RCN’s goals is still present but at another stage of the process. According to the interviewees, the most important function of the portfolio boards is to control the calls, that is, through portfolio planning. Here, they decide what portfolio should be prioritized and how calls can be angled in a given direction. This is where the thematic focus in the specific calls is decided.\n\nMission-driven policies call for new, or rather reinforced, mechanisms for funding research, including an increased need for coordination among actors (because of the complexity of the missions addressed), portfolio management (to ensure that the total portfolio of activities funded by the individual funder and, ideally, across funders contribute, as a whole, to the pursuit of the given mission), and an increased need to follow up on funded activities (to monitor their progress and contributions towards the societal mission they are motivated by).\n\nWith regard to coordination and portfolio management, all interviewees expressed uncertainty as to how efficiently this can take place in practice across programs and funding organizations.\n\nNot surprisingly, this challenge is perceived as most pronounced in a Danish context, where no mechanisms or traditions exist to ensure coordination across the research funding system as a whole, as confirmed by an expert panel review of the Danish research and innovation system (European Commission 2019). Hence, in a Danish context, it is not clear who should take this responsibility or how. As stated almost unanimously in the Danish interviews, there is no formalized coordination of who and what funding is provided for across the different funding organizations. While some forums for dialogue and coordination across the research funding system do exist, coordination within thematic areas is not on the agenda here.\n\nSeveral interviewees did, however, state that a stronger political push for coordination is expected, just as portfolio management is expected to become increasingly important. Several interviewees also stated that achieving such coordination will pose a great challenge, since there is very limited experience to draw on in the Danish system. This is to a large degree perceived to be a result of having a system with clearly distinct funding organizations where no one holds any de facto cross-cutting responsibility and where no mechanisms provide oversight over the thematic distribution of funding.\n\nThe interviews revealed that such coordination and portfolio management is only to a limited or no extent practiced within the individual Danish funding organizations. In IFRD, for instance, there is no portfolio management at all within thematic calls. As long as applications fall within the broad thematic area of a specific call, no further considerations of fit or complementarity play a role in the assessment or selection of projects. There is also very limited oversight of distribution of funding across different themes.\n\nIFD practices some degree of internal portfolio management, but this has an informal character and is mainly used as a tool to support the board. However, interviewees stress that criticism presented in previous evaluations implies that IFD will work more actively and in a more formalized way with portfolio management in the future. IFD also makes some attempts at facilitating wider coordination within the green research and innovation system, but this is an added mechanism established by their own initiative and not part of a formalized mission approach. More specifically, IFD has created a sounding board to which they have invited key stakeholders and actors in an attempt to become an innovation hub in Denmark, albeit this type of initiative is still closely linked to the market-oriented rationale.\n\nThe Norwegian system in turn has some of advantages over its Danish counterpart with regard to coordination and portfolio steering. First of all, the unitary structure of RCN offers better opportunities to align the overall approach and to secure an overview of the overall distribution of funding. These opportunities have not least been strengthened recently with the introduction of the portfolio boards. Portfolio management at the board level comes in different forms, with both a long-term plan for the portfolio and an ongoing portfolio analysis. First of all, there are some portfolio considerations over time with 1-4 specific calls each year in addition to the ongoing calls. These are based on a regular portfolio analysis.\n\nAccording to interviews, the portfolio boards were established to promote a more holistic way of thinking and to secure a better balance in the overall system, for instance, allowing for project proposals to be redistributed to other portfolio boards or programs. At least this is the case in principle. In practice, interviewees stated that the reorganization of RCN is still in a period of adjustment and learning and that historical institutional traditions and differences die hard, although they have been diluted in the current portfolio board setup. They stressed that the new organizational layer of the portfolio boards has been added to the traditional system and that it has not really found its final form yet.\n\nFinally, the experts interviewed express uncertainty about how such a coordinated portfolio approach may play out in practice in a less mature context as the public research system (in contrast to, for instance, portfolio management in a private company).\n\nAnother key challenge addressed by the funders interviewed relates to the perceived mission and identity of the funding organizations or specific programs. This is linked to the acknowledgement that a successful implementation of a mission-driven understanding of the mission-driven rationale will require the funders to partly rethink their role and mission. Many interviewees express a reluctance to do this, most pronounced by the responsive mode funders and most pronounced in Denmark, where the separation between individual funding agencies has also created a strong identity for each.\n\nIRFD states that their responsibility for thematic grants was a result of an amendment of the law, where this task was added to their legal obligations. Initially, there was great resistance to this task as it was perceived as a tool to steer the direction of their funding, which was previously entirely fenced off from political influence. A part of this resistance also has to do with a perception of the political system as being unable to identify the right priorities. For example, an interviewee stated that once the political system knows what is important, the world of research has already known this for 10 or 20 years. Along the same lines, it is also stated that IRFD has always had a strong commitment towards their own brand, which is responsive mode, curiosity-driven research. The main focus has been to protect and secure sufficient funds for the independent researcher-initiated research – not to support thematic priorities. To strengthen the quality of Danish research is also still perceived as the most important part of their legal obligation.\n\nA similar tension could be observed in relation to IFD. The amendment of the law that mandated IRFD to allocate thematic funding was actually a consequence of political dissatisfaction with the way in which IFD previously used their mandate. IFD felt that they were being constrained by very specific call texts and decided to interpret them more broadly. The rationale was that the narrow calls did not correspond with the reason for their existence. It was also stated that IFD has traditionally had a strong focus on the market-oriented rationale, which, in a Danish context, has been formulated with the slogan ‘from research to invoice’ (The Danish Government 2003). Here, the focus has mainly been whether it would be possible to create the right business case. However, the part with having to contribute to the solutions of great societal challenges did not take up much space. Assessments were primarily focusing on the single firm level and resulted in projects that may have been good for particular firms, but where the societal innovation potential would often disappear. However, it is also stated that this has improved recently.\n\nMore generally, it was also stated in the expert interviews that the research councils covered in this study were never designed to mimic, for instance, the strategic research councils in the US. They share few similarities with, for instance, DARPA or other organizations built to address specific missions. Hence, it is perceived as challenging to keep these councils working towards missions formulated at a higher policy level and targeting many different parts of the research system. The question from the experts is how to really identify such missions in a way so that you can use them to steer policy or funding allocation in a clear direction? Although the experts were positive towards the ambition, they were uncertain if it can really be done.\n\n\nConclusion\n\nFew disagree that public research needs to contribute to tackling grand societal challenges – not least climate change. Many also agree that traditional national research funding systems face difficulties when it comes to supporting this task. For these reasons, mission-driven approaches to research and innovation policies have gained popularity recently. However, it is important to scrutinize the underlying premises of these approaches and pinpoint aspects that may turn out as important challenges for a successful implementation. In this study, we have used a historical institutional framework to underline that a mission-driven societal challenges approach can hardly be implemented successfully through a traditional layering strategy but, rather, requires a (partial) conversion of already existing funding structures. Furthermore, we have also pointed to a number of challenges from both a theoretical and practical perspective: How can directionality and academic quality be balanced; how can sufficiently clear and operational criteria be formulated; who has the authority and oversight to make portfolio decisions across complex systems with many actors and many interests? None of these questions have yet been clearly answered in the two national systems, nor in the scholarly literature.\n\nNeither is it clear what the appropriate balances are between the different rationales. As argued by Larrue (2021a), mission-driven approaches are not a silver bullet that will solve all issues. While such approaches are relevant in specific conditions and for certain missions, they are not meant to fully substitute other types of more traditional policies: ‘They build on other instruments and there is still a need for open, non-thematic policy instruments in order to, for instance, provide generic scientific knowledge and raise the general level of business R&D investment across the board’ (Larrue 2021a, 7).\n\nFinally, it is also important to highlight the fact that resistance and path dependency are also likely to be found in the rest of the research system, which makes the task of achieving directionality and coordination even more complicated. In general, traditional research universities do not like the idea of having to act strategically and often do not acknowledge targeted research as ‘proper’ research. The same often goes for individual scientists who sit in the funders’ expert panels and so on. They may often function as important resisting forces against managers or policymakers who try to influence the direction of research.\n\nHowever, while it is clear that mission-driven approaches will interfere with the self-organizing dynamics of science and may limit competition based on traditional academic criteria, it is just as clear that a pure academic orientation does not necessarily align with broader societal needs. These aspects deserve a much more thorough discussion than we have seen so far if the research system should be able to lift this responsibility. If not, the mission-driven approach is likely to end up as little more than well-meaning intentions and big promises.\n\nThe interview data that support the findings of this study cannot be made publicly available since the contained human data cannot be sufficiently de-identified. However, the data can be shared upon reasonable request to co-author Maria-Theresa Norn via email (mtn@ps.au.dk), under the following conditions: full transcripts can only be shared under the condition that respondents give their written and informed consent to allow the authors to share their data with named third parties. Anonymized transcripts where all identifying details have been deleted or replaced can be shared upon request.\n\nOpen Science Framework: PROSECON Funder Study. https://doi.org/10.17605/OSF.IO/6PNKF (Norn et al. 2022).\n\nThis project contains the following extended data:\n\n- PROSECON Funder Study Interview Guide\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgements\n\nThe authors would like to thank Josefine Bjørnholm for assistance in the document study and in transcription of interview data. We are also grateful to our interviewees for engaging with us openly and enthusiastically and to Duncan Thomas, Barend van der Meulen, Aldo Geuna, and Taran Mari Thune for valuable comments on earlier versions of this manuscript.\n\n\nReferences\n\nAagaard K: Kampen om basismidlerne historisk institutionel analyse af basisbevillings-modellens udvikling på universitetsområdet i Danmark. Ph.d.-dissertation. Aarhus University.2011.\n\nAagaard K: The evolution of a national research funding system: Transformative change through layering and displacement. Minerva. 2017; 55(3): 279–297. Publisher Full Text\n\nAagaard K, Mejlgaard N: Dansk forskningspolitik efter årtusindskiftet. Aarhus:Aarhus University Press;2012.\n\nAagaard K, Mejlgaard N:Research Policy: Transformations and tensions. The Oxford Handbook of Danish Politics. Oxford:Oxford University Press;2020; (pp. 664–684).\n\nArnold E, Kuhlmann S, van der Meulen B : A singular Council: evaluation of the Research Council of Norway.2001.\n\nBleda M, del Río P : The Market Failure and the Systemic Failure Rationales in Technological Innovation Systems. Res. Policy. 2013; 42(5): 1039–1052. Publisher Full Text\n\nBoon W, Edler J: Demand, Challenges, and Innovation. Making Sense of New Trends in Innovation Policy. Sci. Public Policy. 2018; 45(4): 435–447. Publisher Full Text\n\nBorrás S, Edler J: The Roles of the State in the Governance of Socio-Technical Systems’ Transformation. Res. Policy. 2020; 49(5): 103971. Publisher Full Text\n\nBush V: Science: The Endless Frontier. Washington, D.C.:National Science Foundation;1945/1990.\n\nChataway J, Daniels C, Kanger L, et al.: Developing and enacting transformative innovation policy: a comparative study. Paper presented at the 8th International Sustainability Transitions Conference Downloaded on 14 July 2018. 2017.Reference Source\n\nCohen WM, Nelson RR, Walsh JP: Links and Impacts: The Influence of Public Research on Industrial R&D. Manag. Sci. 2002; 48: 1–23. Publisher Full Text\n\nDiercks G, Larsen H, Steward F: Transformative Innovation Policy: Addressing Variety in an Emerging Policy Paradigm. Res. Policy. 2019; 48(4): 880–894. Publisher Full Text\n\nEdler J, Boon WP: ‘The next generation of innovation policy: Directionality and the role of demand-oriented instruments’—Introduction to the special section. Sci. Public Policy. 2018; 45(4): 433–434. Publisher Full Text\n\nEdqvist O: Layered science and science policies. Minerva. 2003; 41(3): 207–221. Publisher Full Text\n\nElzinga A, Jamison A:Changing policy agendas in science and technology.Jasanoff S, et al., editors. Handbook of science and technology studies. London:Sage Publications;1995; pp. 572–597.\n\nEtzkowitz H, Leydesdorff L: The Dynamics of Innovation: From National Systems and 'Mode 2' to a Triple Helix of University-Industry-Government Relations. Res. Policy. 2000; 29(2): 109–123. Publisher Full Text\n\nEuropean Commission: Peer Review of the Danish R&I System Ten Steps, and a Leap Forward: Taking Danish Innovation to the next Level. Prepared by the independent experts C. Ketels (Chair), M.D. Hanouz (Rapporteur), J. Hunter, S. Kuhlmann and T. Raven. Peers: P. Heringa (Netherlands), U. Gabai (Israel), G. Marklund (Sweden), C. Palmberg (Finland). Horizon 2020 Policy Support Facility. 2019.Reference Source\n\nForay D, Mowery DC, Nelson RR: Public R&D and Social Challenges: What Lessons from Mission R&D Programs?. Res. Policy. 2012; 41(10): 1697–1702. Publisher Full Text\n\nForskningsrådet: Missions På Norsk. Presentation at \"Kunnskapsgrunnlagskonferansen 2020\". 2020. 25. november 2020.\n\nGodin B: The Linear Model of Innovation: The Historical Construction of an Analytical Framework. Sci. Technol. Hum. Values. 2006; 31(6): 639–667. Publisher Full Text\n\nGodin B, Lane JP: Pushes and Pulls: Hi(S) Tory of the Demand Pull Model of Innovation. Sci. Technol. Hum. Values. 2013; 38(5): 621–654. Publisher Full Text\n\nGrillitsch M, Hansen T, Coenen L, et al.: Innovation Policy for System-Wide Transformation: The Case of Strategic Innovation Programmes (SIPs) in Sweden. Res. Policy. 2019; 48(4): 1048–1061. Publisher Full Text\n\nGrønbæk D: Mellem politik og videnskab. PhD thesis from the Department of Political Science 2001/4. Copenhagen: University of Copenhagen.2001.\n\nGulbrandsen M, Smeby JC: Industry Funding and University Professors’ Research Performance. Res. Policy. 2005; 34(6): 932–950. Publisher Full Text\n\nGuston D: Between Politics and Science: Assuring the Integrity and Productivity of Research. Cambridge UK:Cambridge University Press;2000.\n\nHacker JS: Privatizing risk without privatizing the welfare state: The hidden politics of social policy retrenchment in the United States. Am. Polit. Sci. Rev. 2004; 98(2): 243–260. Publisher Full Text\n\nHowlett M, Rayner J: Design Principles for Policy Mixes: Cohesion and Coherence in ‘New Governance Arrangements’. Polic. Soc. 2007; 26(4): 1–18. Publisher Full Text\n\nHowlett M, Rayner J: Patching vs Packaging in Policy Formulation: Assessing Policy Portfolio Design. Politics and Governance. 2013; 1(2): 170–182. Publisher Full Text\n\nKallerud E, Klitkou A, Olsen DS, et al.: Dimensions of Research and Innovation Policies to Address Grand and Global Challenges. Eu/SPRI Forum Position Paper of the project ‘The Emergence of Challenge-Driven Priorities in Research and Innovation Policy (CPRI)’. 2013.\n\nKattel R, Mazzucato M: Mission-driven innovation policy and dynamic capabilities in the public sector. Ind. Corp. Chang. 2018; 27(5): 787–801. Publisher Full Text\n\nKern F, Howlett M: Implementing transition management as policy reforms: a case study of the Dutch energy sector. Policy. Sci. 2009; 42(4): 391–408. Publisher Full Text\n\nKivimaa P, Kern F: Creative destruction or mere niche support? Innovation policy mixes for sustainability transitions. Res. Policy. 2016; 45(1): 205–217. Publisher Full Text\n\nKline R: Construing ‘Technology’ as ‘Applied Science’: Public Rhetoric of Scientists and Engineers in the United States, 1880-1945. Isis. 1995; 86(2): 194–221.Reference Source\n\nKline S, Rosenberg N:An Overview of innovation.Landau R, Rosenberg N, editors. The Positive Sum Strategy: Harnessing Technology for Economic Growth. Washington, DC:National Academy of Sciences;1986.\n\nKuhlmann S, Rip A: Next-generation innovation policy and grand challenges. Sci. Public Policy. 2018; 45(4): 448–454. Publisher Full Text\n\nLarrue P: Mission-driven Innovation Policy in Norway: Challenges, Opportunities and Future Options. Paris:OECD Publishing;2021a. OECD Science, Technology and Industry Policy Papers, No. 104. Publisher Full Text\n\nLarrue P: The Design and Implementation of Mission-driven Innovation Policies: A New Systemic Policy Approach to Address Societal Challenges. Paris:OECD Publishing.;2021b. OECD Science, Technology and Industry Policy Papers, No. 100. Publisher Full Text\n\nLepori B: Coordination modes in public funding systems. Res. Policy. 2011; 40(3): 355–367. Publisher Full Text\n\nLogar N: Scholarly science policy models and real policy, RSD for SciSIP in US Mission Agencies. Policy. Sci. 2011; 44(3): 249–266. Publisher Full Text\n\nLundvall B-Å: National Innovation Systems: Towards a Theory of Innovation and Interactive Learning. London:Pinter Publishers;1992.\n\nMahoney J, Thelen K: Explaining Institutional Change: Ambiguity, Agency, and Power. Cambridge:Cambridge University PressPublisher Full Text\n\nMartin BR;The changing social contract for science and the evolution of the university.Geuna A, Salter AJ, Steinmueller WE, editors. Science and Innovation: Rethinking the Rationales for Funding and Governance. Cheltenham:Edward Elgar;2003.\n\nMazzucato M: Mission-driven innovation policies: challenges and opportunities. Ind. Corp. Chang. 2018; 27(5): 803–815. Publisher Full Text\n\nMazzucato M, Kattel R, Ryan-Collins J: Challenge-Driven Innovation Policy: Towards a New Policy Toolkit. J. Ind. Compet. Trade. 2020; 20(2): 421–437. Publisher Full Text\n\nMazzucato M, Semieniuk G: Public financing of innovation: new questions. Oxf. Rev. Econ. Policy. 2017; 33(1): 24–48. Publisher Full Text\n\nNelson RR: The Simple Economics of Basic Scientific Research. J. Polit. Econ. 1959; 67(3): 297–306. Publisher Full Text\n\nNelson RR: The Moon and the Ghetto: An Essay on Public Policy Analysis. New York:Norton;1977.\n\nNelson RR: National Innovation Systems: A Comparative Analysis. Oxford:Oxford University Press;1993.\n\nNormann HE, Scordato L, Solberg E, et al.: Målrettede Samfunnsoppdrag i Norge. Forskningsrapport; oppdragsgiver: Kunnskapsdepartementet 2022:7. NIFU-Rapport. Nordisk institutt for studier av innovasjon, forskning og utdanning (NIFU). 2022.Reference Source\n\nNorn MT, Aagaard K, Stage AK: PROSECON Funder Study. OSF. [Dataset].2022. Publisher Full Text\n\nOECD: New Mission-driven Policy Initiatives as Systemic Policies to Address Societal Challenges. Analytical Framework and Typology of Initiatives.2019.Reference Source\n\nPavitt K: Public Policies to Support Basic Research: What Can the Rest of the World Learn from US Theory and Practice? (And What They Should Not Learn). Ind. Corp. Chang. 2001; 10(3): 761–779. Publisher Full Text\n\nPolanyi M: The Republic of Science: Its Political and Economic Theory. Minerva. 1962; 1(1): 54–73. Publisher Full Text\n\nRip A: The republic of science in the 1990s. High. Educ. 1994; 28(1): 3–23. Publisher Full Text\n\nRuivo B: ‘Phases’ or ‘paradigms’ of science policy? Sci. Public Policy. 1994; 21(3): 157–164.\n\nRobinson DKR, Mazzucato M: The Evolution of Mission-driven Policies: Exploring Changing Market Creating Policies in the US and European Space Sector. Res. Policy. 2019; 48(4): 936–948. Publisher Full Text\n\nSchneider F, Buser T, Keller R, et al.: Research funding programmes aiming for societal transformations: ten key stages. Sci. Public Policy. 2019; 46(3): 463–478. Publisher Full Text\n\nSchot J, Steinmueller WE: Three Frames for Innovation Policy: R&D, Systems of Innovation and Transformative Change. Res. Policy. 2018; 47(9): 1554–1567. Publisher Full Text\n\nSkogstad G: Policy Paradigms, Transnationalism, and Domestic Politics . the Series “Studies in Comparative Political Economy and Public Policy.”. Toronto:University of Toronto Press;2011. Publisher Full Text\n\nSkoie H: Diversity and identity: the merger of five research councils in Norway. Sci. Public Policy. 2000; 27(2): 83–96. Publisher Full Text\n\nSolow RM: Technical Change and the Aggregate Production Function. Rev. Econ. Stat. 1957; 39(3): 312–320. Publisher Full Text\n\nSörlin S: Funding diversity: Performance based funding regimes as drivers of differentiation in Higher Education systems. High Educ. Pol. 2007; 20(4): 413–440. Publisher Full Text\n\nStehr N: Knowledge Societies. London:Sage Publications;1994.\n\nStilgoe J, Owen R, Macnaghten P: Developing a framework for responsible innovation. Res. Policy. 2013; 42(9): 1568–1580. Publisher Full Text\n\nStokes DE: Pasteur’s quadrant: Basic science and technological innovation. Washington, DC:Brookings Institution Press;1997.\n\nStreeck W, Thelen K, editors. Beyond continuity: Institutional change in advanced political economies. Oxford University Press;2005.\n\nTechnopolis Group: A Good Council? – Evaluation of the Research Council of Norway. Report commissioned by the Ministry of Education and Research of Norway.2012.Reference Source\n\nThe Danish Government: Nye Veje Mellem Forskning Og Erhverv – Fra Tanke Til Faktura.2003.Reference Source\n\nThe Danish Government: Danmark Løsningernes Land.2012.Reference Source\n\nThe Danish Government: Fremtidens grønne løsninger.2020.Reference Source\n\nThelen K: How institutions evolve: The political economy of skills in Germany, Britain, the United States, and Japan. Cambridge University Press;2004.\n\nUlnicane I: Broadening Aims and Building Support in Science, Technology and Innovation Policy: The Case of the European Research Area. J. Contemp. Eur. Res. 2015; 11(1): 19.\n\nUlnicane I: ‘Grand Challenges’ Concept: A Return of the ‘Big Ideas’ in Science, Technology and Innovation Policy? Int. J. Foresight Innov. Policy. 2016; 11(1–3): 5–21. Publisher Full Text\n\nUnited Nations: Transforming our world: the 2030 Agenda for Sustainable Development. Resolution adopted by the General Assembly. 2015.Reference Source\n\nVan der Meulen B: Science policies as principal–agent games: Institutionalization and path dependency in the relation between government and science. Res. Policy. 1998; 27(4): 397–414. Publisher Full Text\n\nVan der Meulen B, Rip A: Mediation in the Dutch science system. Res. Policy. 1998; 27(8): 757–769. Publisher Full Text\n\nWeber KM, Rohracher H: Legitimizing Research, Technology and Innovation Policies for Transformative Change: Combining Insights from Innovation Systems and Multi-Level Perspective in a Comprehensive ‘Failures’ Framework. Res. Policy. 2012; 41(6): 1037–1047. Publisher Full Text\n\nWise G: Science and Technology. Osiris. 1985; 1: 229–246. Publisher Full Text Reference Source\n\nWohlert J, Lind JK, Norn MT, et al.: Forskning Og Innovation Målrettet et Klimaneutralt Danmark. DEA Report. Copenhagen:The Think Tank DEA;2021.Reference Source" }	[ { "id": "176615", "date": "14 Jul 2023", "name": "Elvira Uyarra", "expertise": [ "Reviewer Expertise policy rationales", "policy mixes", "mission oriented policies", "public procurement" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe paper provides an interesting and welcome discussion on the implementation challenges of mission oriented policies.\nThe paper draws from interviews to key public funders in Norway and Denmark. The authors conducted overall 8 interviews. This does not seem a lot to sustain a paper and I wonder if they authors also conducted document analysis that they can also mention here? Further, there is little information about how the interviews were conducted, how long they were, what questions were asked and how the results were analysed. Again, the evidence used in the paper is rather thin and should be complemented with document analysis of policy reviews and evaluations. Further data sources should be acknowledged as a limitation.\nThe way the results are structured is not clear, why these headings? It does not seem to follow a clear conceptual framework. I think the paper would benefit from a final summary table synthesising the main insights/findings of the paper. Also some paragraphs are too short and schematic.\nI think the characterisation of the three rationales is a bit misleading, particularly the market driven and the mission driven. The market driven characterisation is not totally appropriate for the innovation system approaches as they reject the market failure rationale and have a key focus on institutions. I suggest using a different term. Similarly missions where used extensively as a rationale for S&T policy in the past as they authors say, before the so called ‘transformative missions’ of today. So a more nuanced term would also be appropriate.\nThe paper discusses at length the changing rationales of innovation policy but the idea of ‘rationales’ is taken for granted. See for instance Laranja et al (2007) and Flanagan et al. (2011) for a definition and discussion of policy and theoretical rationales and how change tends to occur in layers.\nI also feel that the paper could say a lot more about the governance challenges of mission oriented policy, including not just cross-ministry coordination but also vertical coordination.\nAll in all, I find the paper interesting as it captures a current debate in relation to the implementation of mission oriented policies, but the paper stays at very surface level in its analysis and conclusions.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "183083", "date": "07 Sep 2023", "name": "Steven Wooding", "expertise": [ "Reviewer Expertise Research on research", "funding systems", "research culture" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors suggest that there are now three objectives for scientific research: research excellence; innovation and growth; specific societal goals. They suggest there may be conflicts and challenges in trying to get a research system designed (or evolved) to address two of these goals to address specific societal goals. They examine these conflicts and how they manifest themselves when trying to build systems (institutionalising) this such a joint approach – both from a theoretical and through example. The authors argue that the existing systems in Denmark and Norway are reacting to the need to bring these missions together by ‘layering on’ new systems, however the authors suggest it is necessary to redesign the systems in order to achieve direction to address societal goals. They then consider the implications of these findings.\nThe authors do a good job of summarising the evolution of research funding systems through three phases – science led (where the public research system was largely allowed to pursue it’s own agenda); innovation led (where the public research system was expected to prioritise stimulating innovation and economic growth); and mission led (where the public research system is required to work in the service of societal agreed goals – such as carbon minimisation).\nAlongside this theoretical account they provide a clear explanation of how the funding systems in Denmark and Norway have evolved.\nThe authors also provide an interesting and thoughtful write up of their discussions with policy makers in the research systems of Denmark and Norway about how they are struggling to balance both the needs of an innovation-led and mission-led systems.\nMy concern is with the theoretical argument that innovation-led system necessarily needs a different set of institutional structures to a mission-led system and that the change required can only be brought about by conversion.\nI think the authors could easily address my concern by suggesting what we see in the evolution of funding system is an association between what systems are expected to accomplish (science, growth, mission) and how they are managed, and talking about how some of those associations my fit with the particular challenges of accomplishing different things. What I find less convincing is the suggestion that different things can _only_ be accomplished by the different institutionalised mechanisms they detail. Below I try to explain why I think this relationship could be an association rather than a requirement and try to extract some of the elements that I think drive the needs for institutional structures with different powers.\nI suggest that as funding systems have moved from science-led to innovation-led to mission-led there has been a parallel evolution of management approaches and that is why it appears that mission-led approaches use/need different institutional arrangements; there is no intrinsic reason why mission-led approaches require different approaches to innovation-led ones. And the more radical changes in institutional arrangements that are being suggested for mission-led research (increased directionality, for example) – could be just as useful for innovation-led research – it’s just such approaches have taken longer to appear and hence appear to be associated with the arrival of mission-led approaches.\nI think there are there is another way of breaking funding systems down into three types: Please see the PDF table here, or copy and paste the following URL into your browser https://f1000research.s3.amazonaws.com/linked/541468.Characteristics_table_-_Steven_Wooding.pdf.\n\nMy impression is that the authors assume a direct read across between these types the the stages of evolution they describe single characteristic = science-led; multi-characteristic = innovation-led and portfolio = mission-led; and this could often be the case, but I don’t think it is necessary. I think innovation-led research funding can include elements of portfolio decision making – ensuring that a full supply chain is developed, rather than just a breakthrough new material.\nI think it is these three types aspects that play a large role in determining the institutional structure – for multi-characteristic funding systems the administration needs to decide how to trade off/balance between the characteristics – this might be done by:\nLinear combination – proposals with highest combined score are funded\n\nThreshold requirement – only proposals that reach a threshold of scientific quality are funded\n\nRelevance mentored – all proposals above a threshold for potential impact are funded, but where they are below a threshold for quality, the funding agency puts in place collaborations or mentoring to increase their quality.\nThe last approach in particular requires the administration to take a much more hands on role in and do things that were previously seen as the role of the scientists.\nIn the third type of system – portfolio – the administration needs to take decisions to fund (or support) projects that are not seen as the ‘best’ but are allow the best portfolio to be constructed – which is often seen as an inappropriate role for a public funding system.\nSo I agree there are different types of system depending on what factors the system is trying to take into account – but I don’t agree that those types have to line up with the science-led; innovation-led and mission-led categories. I think there is a good case to be made that a portfolio approach could well be as valuable in innovation-led funding as it is in mission lead funding – or at least that it is a continuum.\nThis also brings in the aspect of institutionalisation – the authors argue that providing mission-led funding requires different aspects of institutionalisation (specifically adding conversion in addition to layering). I think this is a matter of extent rather than an absolute requirement – I can envisage a funding system with two government funders – one doing science-led funding and one providing innovation-led funding. To add mission-led funding it would be perfectly possible to add a new funder providing mission-led funding. It might be less effective – but I think the only way to tell that would be to examine systems where that had happened – I don’t think this paper provides a strong theoretical justification that it could not be done this way.\nI think the claims made by the authors about the requirements of different institutional systems need to be slightly softened – the theoretical arguments and empirical data is suggestive but I don’t think it is as black and white as it is presented. Particularly in Table 1 – I don’t think the characteristics in each row are necessarily segmented – I can envisage a funding system where ‘All funding sources’ are used for a ‘Market oriented’ system; and I can envisage a system where ‘Dedicated instruments/programs’ are used for ‘Mission driven’. The authors seem to be arguing that this is the _only_ ways such systems could be designed – whereas I’d be much more comfortable with a suggestion that this is the way these systems have tended to be designed in the path dependent history of funding systems that we have seen.\nHere is an example the authors give where more coordination has been called for in achieving innovation aims:\n“Similarly, an expert group reviewing the Danish science and innovation system pointed to the need to strengthen coordination across actors and instruments in the Danish system (European Commission 2019). Indeed, the authors of this report argued that such coordination was key to achieving innovation aims in Denmark but that past reforms had focused on minimizing the need for coordination instead of bolstering increasingly important links between actors and activities in the research and innovation system.”\nI think you could write these examples with ‘innovation-driven’ rather than mission-driven – where the ‘specific politically prioritized mission’ is growth – I’m not clear what is qualitatively different.\nAnd it just seems to be that mission driven directionality is a different type of directionality – I’m not sure why it is qualitatively different: ‘Mission-driven policies involve a high degree of directionality in research funding, as funding is allocated to the pursuit of specific, politically prioritized missions.’\n\n‘There is a general concern across all interviewees that increased directionality (which per definition narrows the calls) may harm the scientific quality and perhaps also the impact of the research investments.’\nI think the argument that new monitoring is needed for mission-led was also true for innovation-led (see impact case studies in the UK REF).‘It also includes an increased need for funders to follow up on funded activities, monitoring their progress and contributions towards targeted societal missions in order to perform actual portfolio management’.\nDetailed points\n‘layering’ seems like a badly picked word as what is described ‘the grafting of new elements onto an otherwise stable institutional framework’ – layering to me implies stacking of layers, ie adding something on top, whereas, the description suggests adding elements that may sit within the current system, and alongside previous elements – ‘grafting’ seems to me like a much better term. But I guess you are stuck with it – if it has previously been coined by someone else.\nIn the following paragraph it is not clear to me whether the authors think there has only been a change of language to describe the same thing, or whether they are suggesting there is a difference of definition between ‘challenge-driven’ and ‘mission-driven’: ‘Mission-driven policies are closely interwoven with the notion of challenge-driven policies. Indeed, they are often used interchangeably, with challenges seen as the driving force for the formulation of missions (see, e.g., Mazzucato, Kattel, and Ryan-Collins 2020). However, we observe a change in the way in which policies are named and described since the beginning of the century: A shift from the introduction of challenge-oriented policies by the EU, and subsequently by several countries, to a more recent shift towards mission-driven policies, again pioneered by, among others, the EU but also seeping into national policy development.’\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? No source data required\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "183064", "date": "08 Sep 2023", "name": "Alessandro Muscio", "expertise": [ "Reviewer Expertise Economics of science", "technology transfer", "innovation policy" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nI like the topic of the paper, but I was expecting more clarity in the actual discussion of the topic of research funding. As it stands, I believe that there are at least two main issues that need a much clearer discussion: the rationale of university funding; mission orientation. These two topics need to be better fitted in the European context, as the paper makes very little references about the relevant funding schemes, their fit with other European schemes, the current trends in European research policy.\nThe authors also need to be clearer about the current changes in the role of universities in societies. There are some megatrends shaping R&I in Europe. With the affirmation of the so-called knowledge economy, universities have grown in relevance, and so has research funding and its use as a policy tool. Therefore, it is just natural that mission-orientation in getting into play in universities. This process (that the authors are free to debate) is not clear in the paper.\nDETAILED COMMENTS\nThe authors state that: “Recently, a third objective has become increasingly prominent: to orient public research towards societal challenges through missions.” This is not completely true, or, to say the least, needs to be better framed. This role in delivering missions derives from a change in the role of universities in societies. This ongoing change in their pivotal role started some time ago (mid ‘80s?), at least from when local development policies have failed in delivering what they promised because they revealed to be too difficult to be implemented successfully. Universities were then rediscovered as engines of growth/change and hence alerted when the mission-oriented approach was implemented.\n\nThe paper makes no reference to the main instrument currently supporting mission-oriented policies in Europe: the RRF. Current funding of PhD programmes, research projects, etc. in many EU countries has to meet the directives of the RRF that, after the Covid pandemic, boosted the change in policy approach stressed by the authors. In this respect, the authors stress that: “the newer mission-driven policy rationale cannot be implemented by simply adding new institutions to existing ones but, rather, requires the redesign and repurposing of existing organizations and policy instruments”. I encourage the authors to reconsider their framework of analysis in the light of recent changes in European policy.\n\nThe literature review is weak in the area of university funding. Please consider whether the following references can help support the authors’ arguments. (Please see 1, 2, 3, 4, 5)\n\nGiven that the paper relies on a project specifically targeted at the promotion of the socio-economic impact of research, it seems strange that no mention is made about the limits of the interaction between social sciences and humanities and the hard sciences. The EU is particularly concerned about the scarce interaction between these two branches in EU programmes, despite all the efforts put in the creation of the SSH mission in Horizon 2020. See below.\n\nThe readers need more information about the interviews (number, stratification, etc.).\n\nThe survey could have been structured as a case study (e.g. see Yin, 1984 6; Eisenhardt, 2021 7). There is hardly any information about the development of the research question and about the choice of the interviewees. Maybe, few statements from them could have helped in building the arguments.\n\nMaybe, the addition of a table summarizing the key results of the qualitative responses (e.g. with the intensity of perceived issues measured in ***) could help the reader.\n\nThe conclusions are rushed, and little information is given about what other countries can learn from the case presented.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-949
https://f1000research.com/articles/11-945/v1	17 Aug 22	{ "type": "Case Report", "title": "Case Report: Treatment of porphyria cutanea tarda with low dose hydroxychloroquine", "authors": [ "Andrew Awad", "Alexander Nirenberg", "Rodney Sinclair", "Alexander Nirenberg", "Rodney Sinclair" ], "abstract": "Background: Porphyria cutanea tarda (PCT) is a complex metabolic disease resulting from altered activity of the enzyme uroporphyrinogen decarboxylase (UROD) in the liver resulting in accumulation of uroporphyrin. PCT presents as a blistering photodermatitis with skin fragility, vesicles, scarring and milia. Case: We report a case of PCT in a 67-year-old man with hemochromatosis (HFE) gene mutation who, following a major syncopal episode in response to venesection was commenced on low dose hydroxychloroquine. Conclusions: Low dose hydroxychloroquine provided a safe and effective alternative to venesection in this patient who was needle phobic.", "keywords": [ "Porphyria cutanea tarda", "hemochromatosis", "hydroxychloroquine" ], "content": "Introduction\n\nPorphyria cutanea tarda (PCT) is the most common type of porphyria and results from a decline of uroporphyrinogen decarboxylase (UROD), an enzyme involved in heme synthesis and resulting in accumulation of uroporphyrin.1 There are two types of PCT. Type 1 is an acquired disorder triggered by iron overload or viral infection. Type II is an autosomal-dominant genodermatosis.2 The cutaneous manifestations arise when cutaneous porphyrins absorb ultraviolet radiation (UV) and generate reactive oxygen species (ROS) that induce skin photosensitivity, sub-epidermal blistering, erosions, milia and scar formation.3 We present a case of a patient diagnosed with type 1 PCT and hemochromatosis, successfully treated with low dose hydroxychloroquine.\n\n\nCase report\n\nA 67-year-old Caucasian male, who worked as a plumber, presented with a two-month history of skin fragility and pruritic blisters on dorsal hands, spreading up the arms. He noted that broken blisters healed with firm little “white spots” and described lethargy and darkening of urine. For many years he had regularly consumed three cans of beer daily. Examination revealed intact blisters alongside numerous erosions over the hands and elbows and milia on inspection of the left hand (Figure 1). There was no forehead hypertrichosis.\n\nThe clinical differential diagnosis included hepatocutaneous porphyria and epidermolysis bullosa acquisita (EBA). Skin biopsy, blood, urinary and faecal porphyrins were performed and he was advised to reduce alcohol consumption and sun exposure.\n\nHistopathology revealed an intact sub-epidermal blister with minimal dermal inflammation (Figure 2). Haematological investigations demonstrated; C282Y hemochromatosis (HFE) gene mutation, mildly elevated liver function tests (LFTs) consistent with alcohol intake and elevated ferritin (756 μg/L). Hepatitis and HIV serology were negative. The porphyrin screen showed elevated urinary total porphyrin (3.4 μmol/L), uroporphyrin (3.2 μmol/L), faecal total porphyrin (330 μmol/L), Isocoprophyrin (125 μmol/L), plasma porphyrin (207 nmol/L) and red cell porphyrin (1.8 μmol/L rbc). The patient was referred for venesection but had a major syncopal episode and declined further venesection. Treatment was then commenced with oral hydroxychloroquine 5 mg daily (compounded extemporaneously) and up-titrated over six months to 200 mg daily. Within 12 months the PCT was in complete remission with normal LFTs and ferritin (462 μg/L) and hydroxychloroquine was ceased. The porphyrin screen showed normal levels of urinary total porphyrin (0.17 μmol/L), red cell porphyrin (0.41 μmol/L red cells) and plasma total porphyrin (13 nmol/L).\n\nIn the superficial dermis there are some thick-walled blood vessels, which stain for Periodic acid–Schiff (PAS). In the upper dermis there is a sparse lymphocytic infiltrate.\n\n\nDiscussion\n\nThe most common triggers for type 1 PCT are alcohol, environmental chemicals, hemochromatosis and viruses.2 Our patient possessed two of the above triggering factors (alcohol and hemochromatosis). Alcohol may trigger PCT by increasing iron absorption through dissociating iron from its binding proteins as well as directly inhibiting UROD.4 Hemochromatosis causes iron excess and can trigger PCT by catalysing ROS formation and increasing uroporphyrin concentration through direct oxidation of uroporphyrinogen and inhibition of UROD.1\n\nHydroxychloroquine increases porphyrin excretion in PCT and is as effective as phlebotomy with remission in 6–9 months.5 The HFE mutation type appears to be important in hydroxychloroquine therapeutic response, with homozygosity for the C282Y mutation resulting in treatment failure, but heterozygosity, as demonstrated in our case, did not.6 The use of compounded low-dose hydroxychloroquine minimised risk of acute toxicity and provided a safe and effective alternative to venesection in our patient. The dose was up-titrated until clinical remission was achieved. A limitation of this case report was the small sample size of only one patient.\n\n\nConclusions\n\nOral hydroxychloroquine provided a safe and effective alternative to venesection in this patient who was needle phobic.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nConsent\n\nWritten informed consent for publication of their clinical details and clinical images was obtained from the patient.", "appendix": "References\n\nRyan Caballes F, Sendi H, Bonkovsky HL: Hepatitis C, porphyria cutanea tarda and liver iron: an update. Liver Int. 2012; 32(6): 880–893. PubMed Abstract \| Publisher Full Text\n\nJalil S, Grady JJ, Lee C, et al.: Associations among behavior-related susceptibility factors in porphyria cutanea tarda. Clin. Gastroenterol. Hepatol. 2010; 8(3): 297–302.e1. PubMed Abstract \| Publisher Full Text\n\nHorner ME, Alikhan A, Tintle S, et al.: Cutaneous porphyrias part I: epidemiology, pathogenesis, presentation, diagnosis, and histopathology. Int. J. Dermatol. 2013; 52(12): 1464–1480. PubMed Abstract \| Publisher Full Text\n\nDoss MO, Kühnel A, Gross U: Alcohol and porphyrin metabolism. Alcohol Alcohol. 2000; 35(2): 109–125. Publisher Full Text\n\nSingal AK, Kormos-Hallberg C, Lee C, et al.: Low-dose hydroxychloroquine is as effective as phlebotomy in treatment of patients with porphyria cutanea tarda. Clin. Gastroenterol. Hepatol. 2012; 10(12): 1402–1409. Publisher Full Text\n\nStölzel U, Köstler E, Schuppan D, et al.: Hemochromatosis (HFE) gene mutations and response to chloroquine in porphyria cutanea tarda. Arch. Dermatol. 2003; 139(3): 309–313. PubMed Abstract" }	[ { "id": "156729", "date": "16 Dec 2022", "name": "Jordi To-Figueras", "expertise": [ "Reviewer Expertise Porphyria" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is an OK addition to the literature of PCT.\n\nThe authors should however clarify the haemochromatosis status. In the case report, they should indicate if the patient is heterozygous for the C282Y mutation (hence C282Y/WT?) and add the H63D status (WT/WT?). According to reviews (i.e. Kowdley et al. (2019)1), HFE status would be defined by a C282Y homozygous or C282Y/H63D compound heterozygous. Please clarify.\n\n'Case report' section: \"red cell porphyrin\" should read as \"red cell protoporphyrin\"; \"plasma porphyrin\" should read as \"plasma total porphyrin\".\nThe case the authors reported adds to the PCT literature. Even if venesection is considered a treatment of choice for PCT that has been empirically proven to reduce overproduction of porphyrins through reduction of hepatic iron depots, it is an invasive procedure. Needle phobia of the patient induced consideration of low-dose oral chloroquine as an alternative. And that simple and well-known regime induced remission even if haemochromatosis was suspected. The point is that, PCT being a benign disease, non-invasive treatments (chloroquine or oral antivirals when PCT is induced by HCV infection) should be preferred to venesection as a first choice.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Partly\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "172317", "date": "23 May 2023", "name": "Staffan Wahlin", "expertise": [ "Reviewer Expertise Liver diseases. Porphyria." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a short report about a fairly standard PCT patient who was successfully treated to reach clinical and biochemical remission. I have two main concerns:\nThe title of the report does not really reflect the content; \"low dose\" is true only in comparison with other non-PCT indications. In PCT, the recommended dose of hydroxychloroquine is 100 mg twice weekly (for chloroquine, 125 mg twice weekly). The reason for keeping the dose low is mainly a significant risk of hepatotoxicity in higher doses. Toxic retinopathy is also an issue. This case was treated with 5 mg daily uptrited to 200 mg daily. In a PCT context, that should be regarded as \"high dose\". The patient did ok with normal LFTs during the treatment period.\n\nPlease don't say that the patient had hemochromatosis. He had a HFE gene variant on one allele, he was heterozygous. The moderately elevated serum ferritin was more likely a result of alcohol overconsumption (>20 beer cans per week). His main risk factor was alcohol. The HFE mutation may have made him more vulnerable.\nSome details:\nIn Introduction: \"Type 1 is an acquired disorder triggered by risk factors such as iron overload...\"\n\nPorphyrins absorb mainly visible light around 405 nm (could be expressed as \"longer wavelength UVA and visible light around 405 nm\"). Saying UV radiation is misleading as it suggests that protection with UV blocking creams may help. They don't.\n\nUnits. Are umol/L standard in Australia? In Europe, nmol/L and, in the US, mcg/dL is standard/preferred. Check what is most appropriate for the journal.\n\nThe last sentence about the limitation is unnecessary.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Partly\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? No\n\nIs the case presented with sufficient detail to be useful for other practitioners? Partly", "responses": [] }, { "id": "172322", "date": "08 Jun 2023", "name": "Andrea Ricci", "expertise": [ "Reviewer Expertise Rare liver diseases", "iron overload disorders (hemochromatosis", "ferroportin disease", "hemoglobinopathies)", "porphyrias" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors report an interesting case report which reminds us that hydroxychloroquine is an effective treatment for PCT. This should be kept in mind for all those patients who cannot undergo phlebotomy (for instance, cirrhotic patients, or those affected by myelodysplastic disorders) even though the choice to use hydroxychloroquine should be always weighed against the risk of adverse events in patients who are already affected by a liver disease.\nI find this report clearly written and informative. However, a few points should be corrected/clarified:\nThis patient carried a heterozygous C282Y variant in the human homeostatic iron regulator protein (HFE) gene, which should be mentioned as such (not \"hemochromatosis\" gene, as there are several other genes - HJV, TFR2, etc. - which cause hemochromatosis). A C282Y heterozygous mutation is by no means sufficient to cause HFE-related hemochromatosis, which is mainly associated with a C282Y homozygous genotype. A compound heterozygous C282Y/H63D genotype may be regarded as a \"risk genotype\" for liver iron overload, but is not sufficient in itself to define \"classic\" HFE-related hemochromatosis. In sum, the authors should consider that the iron overload phenotype of their patient cannot be explained by his HFE genotype (I assume that the patient did not carry further pathogenic variants in this gene). Furthermore, they should report the patient's serum iron, transferrin, and transferrin saturation levels at baseline (both serum iron and transferrin saturation should be above the range of normality in a typical hemochromatosis patient, whereas serum transferrin should be normal/below range).\n\nDid the patient change his habits as to daily ethanol consumption? As the authors hint, this could be the main reason for his iron overload phenotype.\n\nIsocoproporphyrin is misspelled.\n\nThe patient did not undergo a liver biopsy, which is reasonable enough a choice, provided the hepatopathy he was affected by is reasonably diagnosed as alcohol-related. This should be specified somewhere in the text. If the authors think that alcohol use alone does not fully explain this patient's liver disease, they should clarify why other causes of hepatopathy (i.e. NAFLD, autoimmune, etc.) have not been investigated.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Partly\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Partly\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-945
https://f1000research.com/articles/11-943/v1	17 Aug 22	{ "type": "Case Report", "title": "Case Report: Clinical outcome of prolonged cord prolapse", "authors": [ "Muna Karki", "Bibhushan Neupane", "Lokendra Bata", "Shiba Bam", "Rama Ghimire", "Sujila Maharjan", "Bishnu Deep Pathak", "Bibhushan Neupane", "Lokendra Bata", "Shiba Bam", "Rama Ghimire", "Sujila Maharjan", "Bishnu Deep Pathak" ], "abstract": "Abstract:\nUmbilical cord prolapse is an uncommon obstetric emergency with high neonatal morbidity and mortality. It is a rare entity with incidence ranging from 0.1 to 0.6%. Timely recognition and immediate interventions are needed for better outcome. Here, we present a case of 28-year-old multigravida of term pregnancy with cord prolapse of seven hours following rupture of membrane. She was experiencing vaginal leakage in the absence of abdominal pain, and was referred from the peripheral health center with the provisional diagnosis of cord prolapse. She finally underwent emergency caesarean section with good neonatal outcome at tertiary care center.", "keywords": [ "umbilical cord", "prolapse", "obstetric", "neonatal" ], "content": "Introduction\n\nUmbilical cord prolapse (UCP) is the abnormal descent of the umbilical cord through the cervix or past the presenting part in the presence of ruptured membrane. The overall incidence of UCP ranges from 0.1-0.6 %.1 It is an infrequent and unpredictable obstetric emergency.2 It occurs more commonly in pregnancies with amniotic membrane rupture before labour.3 Delay of management is responsible for poor perinatal outcome.2 Therefore, timely recognition and intervention is needed to avoid neonatal morbidity and mortality.4 The cord prolapse to delivery time and delay in transfer to hospital are associated with unfavourable neonatal outcome.5\n\nHere, we present a case of 28-year multigravida of term pregnancy with cord prolapse of seven hours following rupture of membrane, who underwent an emergency caesarean section with good neonatal outcome. She was a referred case from a peripheral rural health centre.\n\n\nCase report\n\nA 28-year old Nepalese female, Hindu by religion and housewife with gravida four, parity one and living one at 38 weeks 6 days of gestation, a referred case from district level hospital, presented to our tertiary care centre with a diagnosis of premature rupture of membrane of 15 hours and cord prolapse of seven hours. She was well 15 hours before when she experienced vaginal leaking, not associated with pain in the abdomen. There was no history of fever or foul-smelling vaginal discharge. Her past four deliveries were uneventful.\n\nOn physical examination by the attending obstetrician, her uterus was of term size with longitudinal lie, cephalic presentation and the fetal head was free. There was no uterine contraction. The fetal heart rate as heard by fetal doppler was 150 beats per minute and was regular. On speculum examination, a glistening white structure was seen lying in the vagina as shown in Figure 1. Thus, the diagnosis of cord prolapse was confirmed. Complete blood count, C-reactive protein, urine routine/microscopic examination and high vaginal swab analyses were conducted.\n\nOn vaginal examination, the umbilical cord hanging by the side of the presenting part was wrapped with a gauze soaked with warm saline. One of the assistants wearing sterile glove placed a hand inside the patient’s vagina and lifted the presenting part. At the same time, the assistant palpated the cord and confirmed its presence by feeling pulsation of umbilical arteries. Then, Foley’s catheterization was done and approximately 200 ml of distilled water was infused into the urinary bladder. The patient was immediately taken to the operation theatre on trolley in exaggerated Sims position. Emergency caesarean section was then done. Intra-operative findings were that the placenta had already separated with retroplacental clots of 100 ml. Baby was cephalic, left occipito-anterior and placenta was in fundo-anterior position.\n\nThe outcome of caesarean section was a single alive male baby with birth weight of 3300 grams, cried immediately after delivery with Apgar score of 6/10 and 8/10 at one and five minutes respectively. The weight of placenta was 550 grams.\n\nOn second and third day postpartum, the patient had a few episodes of fever of maximum 102° F for which fever panel was sent and all came out to be within normal limits. She was kept under intravenous antibiotics for 48 hours (intravenous ceftriaxone 1 g 12 hourly and intravenous metronidazole 500 mg 8 hourly). C-reactive protein of baby was also sent for testing and came out to be negative. Patient was discharged on fifth day post-operative with afebrile period of > 24 hours and was followed up on seventh day for suture removal. Both mother and baby were fine.\n\n\nDiscussion\n\nUCP is a rare occurrence, and very little literature has reported on long duration of UCP. Incidence of cord prolapse ranges from one to six per 1000 pregnancies, and it is associated with high perinatal mortality, ranging from 23% to 27% in low-income countries and 6% to 10% in high-income countries.2 Risk factors for UCP include fetal malpresentation, fetal prematurity, multifetal gestation, polyhydramnios and spontaneous rupture of membrane.3 In our case, the associated risk factor was spontaneous rupture of membrane when the head was not engaged.\n\nIn a study by Lin MG et al., perinatal mortality was found to be significantly greater when prolapse occurred outside the hospital (38-40%) compared to within hospital (0-3%).6 Due to neonatal morbidity and mortality associated with UCP, rapid and decisive management is required. The guiding principle was to deliver the fetus as soon as possible. Cesarean section is the recommended mode of delivery.1\n\nIn a study by Li PC et al., they delivered a baby vaginally after 30 minutes of UCP, whereas in our case, we did a caesarean section.4 It is reported that the outcome of umbilical cord prolapse is good, if the baby is delivered within a half hour of diagnosis.5 However, in our case even after seven hours of cord prolapse, the neonatal outcome was good.\n\nIn a study by Murphy DJ et al., the authors concluded that Apgar scores were better with a shorter DDI (diagnosis of UCP to delivery interval) and babies delivered vaginally generally had shorter DDIs and better Apgar scores than those delivered through caesarean section.7 However, in our case, even though DDI was longer and the patient underwent a caesarean section, the baby was delivered with a good Apgar score.\n\nOne limitation of our study was that we lost to follow up the case on a long-term basis. In this case, we learned that the situation was very urgent and required immediate management. After the rupture of membrane, it is mandatory to do per vaginal examination to rule out cord prolapse. These types of cases need to be urgently referred from peripheral health centres to well-equipped hospitals early so that timely definitive management can be done.\n\n\nConclusions\n\nThe umbilical cord prolapse should be ruled out in a term pregnant woman presenting with ruptured membrane or persistent per vaginal discharge. These cases need to be recognized and managed as early as possible. They should be urgently referred to a well-equipped centre, where caesarean delivery service is available.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nConsent\n\nWritten informed consent for publication of the clinical details and clinical image has been obtained from the patient.", "appendix": "References\n\nUmbilical Cord Prolapse (Green-top Guideline No. 50): [cited 2021 Dec 5].Reference Source\n\nWong L, Kwan AHW, Lau SL, et al.: Umbilical cord prolapse: revisiting its definition and management. Am. J. Obstet. Gynecol. 2021 Oct 1 [cited 2021 Dec 5]; 225(4): 357–366. PubMed Abstract \| Publisher Full Text Reference Source\n\nDilbaz B, Ozturkoglu E, Dilbaz S, et al.: Risk factors and perinatal outcomes associated with umbilical cord prolapse. Arch. Gynecol. Obstet. 2006 Mar 15 [cited 2021 Dec 5]; 274(2): 104–107. PubMed Abstract \| Publisher Full Text\n\nLi PC, Ding DC: Vaginal delivery in a pregnant woman with cord prolapse, velamentous cord insertion, and fetal vertex presentation: A case report. Med (United States). 2018 Nov 1 [cited 2021 Dec 5]; 97(45): e13221. Publisher Full Text Reference Source\n\nNizard J, Cromi A, Molendijk H, et al.: Neonatal outcome following prolonged umbilical cord prolapse in preterm premature rupture of membranes. BJOG Int. J. Obstet. Gynaecol. 2005 Jun 1 [cited 2021 Dec 5]; 112(6): 833–836. PubMed Abstract \| Publisher Full Text\n\nLin MG: Umbilical cord prolapse. Obstet. Gynecol. Surv. 2006 Apr [cited 2021 Dec 5]; 61(4): 269–277. Publisher Full Text Reference Source\n\nMurphy DJ, MacKenzie IZ: The mortality and morbidity associated with umbilical cord prolapse. BJOG Int. J. Obstet. Gynaecol. 1995 Oct 1 [cited 2021 Dec 5]; 102(10): 826–830. PubMed Abstract \| Publisher Full Text" }	[ { "id": "247550", "date": "28 Feb 2024", "name": "Akmal El-Mazny", "expertise": [ "Reviewer Expertise Obstetrics Gynecology Infertility" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors concluded that umbilical cord prolapse should be ruled out in a term pregnant woman presenting with ruptured membrane or persistent per vaginal discharge. These cases need to be recognized and managed as early as possible.\n\nComments: Title: - Is appropriate for the content of the article. Abstract:- Represents a suitable summary of the work. Case:- The methods and results have been well explained. Conclusions:- Are justified on the basis of the study.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "268018", "date": "09 Sep 2024", "name": "Everett F. Magann", "expertise": [ "Reviewer Expertise I am a Maternal Fetal Medicine subspecialist and have rewritten a review of the diagnosis and management of umbilical cord prolapse" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAbstract: Needs more information - - How is \"provisional diagnosis\" defined, - Was an exam done, - Was there evidence of fetal heart rate abnormalities after rupture of the membranes?\nThis is unclear in the abstract and the case report.\nIt appears that the most unique aspect of this case report is the time from \"provisional diagnosis \" to delivery.\nThis might be a good opportunity to talk about methods used to assist when referral becomes necessary. From the 1920s until cesarean was proposed as treatment of choice, cord replacement was done if the segment of cord prolapse was < 25 cm, the cervix was dilated to 4 cm and present part could be elevated to -1 station.\nVaginal deliver could be considered if this is quicker than a cesarean , changing maternal position Trendelenburg or knee chest position, and filling the bladder with saline have all been suggested as methods to treat if immediate cesarean is not available.\n\nIs the background of the case’s history and progression described in sufficient detail? Partly\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Partly\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Partly\n\nIs the case presented with sufficient detail to be useful for other practitioners? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-943
https://f1000research.com/articles/11-941/v1	17 Aug 22	{ "type": "Brief Report", "title": "Inconclusive results of SARS-CoV2 RT-qPCR: To retest or not?", "authors": [ "Christian Ardianto", "Anastasia Venna", "Anita Devi K. Thantry", "Maria M M Kaisar", "Christian Ardianto", "Anastasia Venna", "Anita Devi K. Thantry" ], "abstract": "Background: Reverse transcription-quantitative PCR (RT-qPCR) is widely used to detect SARS-CoV-2 infections. A small proportion (3-5%) of the samples turn out to be inconclusive which are difficult to interpret and require repeat testing. Methods: This study utilizing RT-qPCR for SARS-CoV-2 collected data from the viral RNA extracted using Maccura Mag-Bind RNA from NPOP specimen, then amplified and quantified using Maccura SARS-CoV-2 Fluorescent PCR kit. The data with inconclusive interpretation and re-test results were selected and further analysed. Results: The retrospective analysis of 247 inconclusive samples that were retested was included in the study. Among the inconclusive results from the first test, 80% of samples which expressed SARS-CoV-2 N and E genes (without ORF1ab gene) turned out to be positive in the repeat test (p < 0.001), while 55% of samples that had only one gene expressed initially, were positive on repeat testing. The E gene was detected (without N and ORF1ab gene) in nine samples, of which seven were negative on re-testing. Conclusions: Our study suggests that it is beneficial to repeat the SARS-CoV-2 RT-qPCR test, especially when two genes are expressed, while detection of only E gene in the first test can be regarded as negative.", "keywords": [ "Inconclusive", "Possibly Positive", "RT-qPCR", "COVID-19", "SARS-CoV-2" ], "content": "Introduction\n\nCOVID-19, caused by the SARS-CoV-2 virus, was first isolated from an unexplained pneumonia case in 2019 in Wuhan, China, with the first case confirmed in Indonesia on 2 March 2020. COVID-19 has been fatal to a large number of patients worldwide, prompting the World Health Organization (WHO) to declare it as a pandemic on 11 March, 2020.1\n\nThe nucleic acid amplification test (NAAT) is currently the gold standard for SARS-CoV-2 detection, particularly reverse transcription-quantitative polymerase chain reaction (RT-qPCR). RT-qPCR with multiple targeted genes such as open reading frame 1ab (ORF1ab), nucleocapsid (N), and/or envelope (E) are commonly used for detection. The detection sensitivity of RT-qPCR ranges from 32 to 95% in clinical samples, depending on the specimen type being processed.2,3\n\nClear-cut positive or negative results are easy to interpret, whereas a small portion of samples (3-5% of all samples)4,5 with either only one gene detected or those with borderline cycle threshold (CT) values for any one of the genes are considered inconclusive (also referred to as “possibly positive” results). Several factors lead to inconclusive results, including inadequate sampling, a cold chain transport decline, poor viral transport medium (VTM) quality, insufficient sample storage, lack of amplification in internal control, or extraction failure.6 Inconclusive results are difficult to interpret and necessitate repeat testing, which increases laboratory cost, requires additional manpower, and delays reporting of result to the hospital or patient. Nonetheless, retesting of inconclusive RT-qPCR results is required for confirmation and decision-making regarding patient management strategy. Inconclusive cases might indicate the initial or late stage of COVID-19 infection7 which require a different patient management strategy, including isolation and testing approach. This study aims to estimate the value of retesting the inconclusive results and finding a better method of interpreting them in the first testing round itself, thereby reducing the need for unnecessary re-testing.\n\n\nMethods\n\nThis study used data from samples tested for SARS-CoV-2 by RT-qPCR at the COVID-19 Laboratory, Atma Jaya Catholic University of Indonesia, from September to November 2020. A retrospective study of the 14,609 SARS-CoV-2 RT-qPCR results during this period was carried. The study was approved by the Institutional Review Board of the School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia (AJCUI) under the approval number 07/06/KEP-FKIKUAJ/2022. This study was a retrospective study, which required no further consent from participants and has been waived by ethical committee. Viral RNA from nasopharyngeal and oropharyngeal swabs was extracted using Maccura Mag-Bind RNA (Maccura Biotechnology Co., Ltd., Chengdu, PRC) based on the magnetic-bead principle,8 and further amplified using a qRT-PCR kit (SARS-CoV-2 Fluorescent PCR, Maccura Biotechnology Co., Ltd., Chengdu, PRC) to detect ORF1ab gene (FAM), N gene (Cy5), and E gene (ROX) with Internal Control/IC (VIC) on CFX 96 Touch Thermal Cycler (Bio-Rad Laboratories). The amplification was done as per manufacturer’s instruction, with cycling conditions of 55°C for 15 minutes, 95°C for two minutes, followed by 40 cycles at 95°C for 15 seconds, 58°C for 35 seconds, and a final cycle at 40°C for 10 seconds. Through a quality control assessment, valid results were amplified and checked for whether they showed a typical smooth “S-shaped” curve above the threshold. The CT value results were analysed using Bio-Rad CFX Maestro software (V4.1.2433.1219). Based on the CT value analysis, a retest was conducted on the inconclusive samples using the same extraction and PCR kits used in the first round.\n\nThe positivity cut-off of the CT value was decided as less than or equal to 38 for both N and ORF1ab genes and less than or equal to 37 for E gene. The sample was categorized as positive if the ORF1ab gene was detected along with the N gene and/or E gene (based on the CT cut off). Negative result was confirmed if no genes were detected. Inconclusive results were classified into four groups based on gene(s) detected (as specified by the manufacturer): i) ORF1ab gene only (ORF1ab+), ii) N gene only (N+), iii) E gene only (E+), iv) both N and E (N+E+) gene detected but without ORF1ab gene. The inconclusive results were retested and categorized as positive if the targeted genes were detected within the CT cut-off value and negative if no gene was detected.\n\nStatistical analyses were performed using STATA version 14.1. Among the inconclusive group, frequencies and CT values of each gene from the first test were compared with the retest results (positive or negative) using the independent t-test and Chi-square test. Regarding the frequency of inconclusive groups, N+ and ORF1ab+ were compared using chi-square test and the reference was N+E+ group, whereas E+ group was compared using Fisher’s exact probability test because chi-square test assumptions were not met. The CT value of each gene in the inconclusive test was compared using the Mann-Whitney U test for all genes, except N gene of the N+E+ group which was compared using unpaired t-test as it showed normal distribution. CT value of each gene from the same sample was compared between the first test and retest using paired t-test for N gene of N+E+ group, while CT value of other genes were calculated using a Wilcoxon signed-rank test, because the distribution was not normal. A p-value less than 0.05 was defined as statistically significant.\n\n\nResults and discussion\n\nA total of 14,609 samples were processed using the Maccura Mag-Bind RNA viral RNA extraction kit and consecutively amplified using the Maccura SARS-CoV-2 Fluorescent PCR kit. Of the total samples tested, 11,220 (76.8%) samples were negative with 17.26% (2521) being positive, and 4.25% (621) of samples having invalid results, which were retested and further classified as positive, negative or inconclusive. A total of 247 samples were recorded as inconclusive, representing 1.69% of the total samples analysed (Figure 1a) which is much less than previously reported (4-5%).4,5 Inconclusive cases can be minimized, though unavoidable, as a small portion will always occur. Inconclusive results might happen due to aberrancies at multiple levels in the process of retesting; therefore, it is vital to evaluate all processes including sample collection, quality of VTM, sample transportation, sample storage prior to processing, RNA extraction or PCR process.6\n\n(a) Pie chart representing the total selected samples which consist of negative (dark grey), positive (light grey), invalid (grey) and inconclusive (red) shown in percentage (%). (b) A bar chart showing the stratification of inconclusive groups (actual cases numbers).\n\nThe stratification of the inconclusive groups in our study is represented in Figure 1b. The majority (65.59%) of the inconclusive samples were N+ (162), followed by ORF1ab+ and N+E+ inconclusive categories with 18.62% (46) and 12.15% (30), respectively. E+ contributes to nine samples (3.64%). The retesting of these inconclusive samples cleared 122 samples (49.39%) as positive and 126 samples (50.61%) as negative which is comparable with previous reports, in which 53.9% of inconclusive samples turned positive on repeat testing.9 Although false-negative results of SARS-CoV-2 RT-PCR are predicted to be around 28% to 39%,10 our study found that 126 out of 247 samples (51%) were false negative results.\n\nThis study also showed that when two genes (N+E+) were detected, the probability of positive result on retest was significantly higher (80%) (p-value = 0.001) than when only one gene was detected (ORF1ab+, N+ or E+ alone) (45.16%). Table 1 represents significant differences between N+E+ samples as compared to N+ only (p-value = 0.001), ORF1ab+ only (p-value = 0.002), and E+ (p-value = 0.003). Moreover, we observed that E+ in the first test had the least chance of turning positive on repeat testing. This observation could be explained by the fact that the E gene has specificity problems and is vulnerable to sample contamination.11–13 Overall, our data indicated that retesting inconclusive samples was beneficial, particularly when two genes were detected, but was ineffective when only E gene was detected.\n\n1 The result obtained from the first test.\n\n* Chi-square test.\n\n# Fisher’s exact probability test.\n\nWe investigated whether the CT values of inconclusive samples correlated with retested positive results. We observed that the CT value of the inconclusive samples could not predict the positivity following a retest since there were no significant differences between CT values of the inconclusive first test and positive retest result, as presented in Table 2. One possible explanation could be that the cut-off CT value is higher than 37, which correlates with a lower RNA load14; a major difference in borderline CT values was not observed in the positive versus the negative final result of the inconclusive samples tested.\n\n1 The result obtained from the first test.\n\n* Unpaired t-test.\n\n# Mann-Whitney U-test.\n\nWe further selected samples paired with final positive results (first and second test) of all inconclusive groups and compared both CT values as summarized in Table 3. Another interesting observation was that the CT value of the positive retest was significantly lower compared to the first test CT value for inconclusive samples. This finding suggests the importance of retesting inconclusive results in order to improve diagnosis accuracy.\n\n* Paired t-test.\n\n# Wilcoxon signed-rank test.\n\nThere were some potential aspects that could be assessed in the future research based on the results from our study. The lack of access to clinical and epidemiological data that could have aided in the analysis of this investigation was a major fallback. Additionally, this study used only one extraction kit and one PCR kit, contributing to consistent results. However, the inconclusive results might vary when using other kits. Further studies could be conducted to compare extraction and PCR kits, analyze the CT value in greater detail, or compare the results to those from another country or laboratory. In conclusion, most inconclusive samples expressed only the N gene, followed by only the ORF1ab gene, and both N and E genes together. When two genes were expressed in the first test, 80% of the inconclusive samples tested positive (p = 0.001) on the retest, compared to samples with only one gene expressed (45%). Detection of the E gene alone was found in nine samples, of which seven were negative in the retest. Retesting the inconclusive samples was beneficial, especially when two genes were expressed, but there was not much value in retesting when only the E gene was expressed. Altogether, our data might become a reference for similar investigations done in multiplexing targets of other pathogens.15\n\n\nData availability\n\nFigshare: Dataset_Inconlusive RT-qPCR_MK, https://doi.org/10.6084/m9.figshare.20306415v1.16\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgments\n\nWe thank Tria A. Widowati for her assistance in initial screening of the data and Helen Kristin for her technical support. The database of SARS-CoV-2 measurement using RT-qPCR that is used in this study was provided by the COVID-19 Laboratory Center of Atma Jaya Catholic University of Indonesia (AJCUI).\n\n\nReferences\n\nBaloch S, Baloch MA, Zheng T, et al.: The coronavirus disease 2019 (COVID-19) pandemic. Tohoku J. Exp. Med. 2020; 250(4): 271–278. PubMed Abstract \| Publisher Full Text\n\nGhoshal U, Vasanth S, Tejan N: A guide to laboratory diagnosis of Corona Virus Disease-19 for the gastroenterologists. Indian J. Gastroenterol. 2020 Sep 2; 39: 236–242. Publisher Full Text\n\nClerici B, Muscatello A, Bai F, et al.: Sensitivity of SARS-CoV-2 detection with nasopharyngeal swabs. Front. Public Health. 2021; 8: 1098.\n\nBhoyar RC, Jain A, Sehgal P, et al.: High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing. PLoS One. 2021 Feb 17; 16(2): e0247115. PubMed Abstract \| Publisher Full Text\n\nPujadas E, Ibeh N, Hernandez MM, et al.: Comparison of SARS-CoV-2 detection from nasopharyngeal swab samples by the Roche cobas 6800 SARS-CoV-2 test and a laboratory-developed real-time RT-PCR test. J. Med. Virol. 2020; 92(9): 1695–1698. Publisher Full Text\n\nBhattacharya S, Vidyadharan A, Joy VM: Inconclusive SARS-COV-2 reverse transcription-polymerase chain reaction test reports: Interpretation, clinical and infection control implications. J. Acad. Clin. Microbiol. 2020 Jan 1; 22(1): 59. Publisher Full Text\n\nFalasca F, Sciandra I, Di Carlo D, et al.: Detection of SARS-COV N2 gene: very low amounts of viral RNA or false positive? J. Clin. Virol. 2020 Dec 1; 133: 104660. PubMed Abstract \| Publisher Full Text\n\nMag-Bind RNA Extraction Kit. Maccura Biotechnology Co., Ltd.;2019.\n\nGreen DA, Zucker J, Westblade LF, et al.: Clinical performance of SARS-CoV-2 molecular tests. J. Clin. Microbiol. 2020 Jun 8; 58. PubMed Abstract \| Publisher Full Text\n\nYang S, Stanzione N, Uslan DZ, et al.: Clinical and epidemiologic evaluation of inconclusive COVID-19 PCR results using a quantitative algorithm. Am. J. Clin. Pathol. 2021 Mar 1; 155(3): 376–380. PubMed Abstract \| Publisher Full Text\n\nBenrahma H, Idrissa D, Imane S, et al.: Epidemiological description and analysis of RdRp, E and N genes dynamic by RT-PCR of SARS-CoV-2 in Moroccan population: Experience of the National Reference Laboratory (LNR)-UM6SS. medRxiv. 2020 Jan 1; 2020.06.18.20135137.\n\nLim YK, Kweon OJ, Kim HR, et al.: Clinical and epidemiologic characteristics of inconclusive results in SARS-CoV-2 RT-PCR assays. BMC Infect. Dis. 2021 Aug 21; 21(1): 851. PubMed Abstract \| Publisher Full Text\n\nBezier C, Anthoine G, Charki A: Reliability of real-time RT-PCR tests to detect SARS-Cov-2: A literature review. Int. J. Metrol. Qual. Eng. 2020; 11: 13. Publisher Full Text\n\nde la Calle C , Lalueza A, Mancheño-Losa M, et al.: Impact of viral load at admission on the development of respiratory failure in hospitalized patients with SARS-CoV-2 infection. Eur. J. Clin. Microbiol. Infect. Dis. 2021 Jun 1; 40(6): 1209–1216. PubMed Abstract \| Publisher Full Text\n\nEsteves LM, Bulhões SM, Branco CC, et al.: Diagnosis of human leptospirosis in a clinical setting: real-time PCR high resolution melting analysis for detection of leptospira at the onset of disease. Sci. Rep. 2018 Jun 15; 8(1): 9213. PubMed Abstract \| Publisher Full Text\n\nKaisar M, Ardianto C: Dataset_Inconclusive RT-qPCR_MK.xlsx. figshare. Dataset.2022. Publisher Full Text" }	[ { "id": "221903", "date": "15 Nov 2023", "name": "Kenji Ota", "expertise": [ "Reviewer Expertise Infectious diseases", "molecular diagnosis" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this retrospective study, the authors analyzed clinical RT-PCR result, trying to clarify the incidence and establish the measure to reduce inconclusive results. The purpose is relevant, however, the definition is ambiguous and the results cannot be generalized in present manuscript.\nMethods should be divided in subsection including sampling, RT-PCR, test protocol, cut-off determination. Since this study focuses on inconclusive results, the factors affecting the nucleic acid amplification test including swab type and viral transport media should be describe in detail. In addition, the process for determination different cut-pff value to different target needs explanation or citation.\nThe study protocol is not clearly described in Method until the readers reaches Results section (1st test, invalid results, 2nd test, inconclusive?). The review regarding Results awaits till Methods are clarified.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate? Yes\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] } ]	1	https://f1000research.com/articles/11-941
https://f1000research.com/articles/10-1260/v1	08 Dec 21	{ "type": "Method Article", "title": "Hobotnica: exploring molecular signature quality", "authors": [ "Alexey Stupnikov", "Alexey Sizykh", "Alexander Favorov", "Bahman Afsari", "Sarah Wheelan", "Luigi Marchionni", "Yulia Medvedeva", "Alexey Sizykh", "Alexander Favorov", "Bahman Afsari", "Sarah Wheelan", "Luigi Marchionni" ], "abstract": "A Molecular Features Set (MFS), is a result of a vast diversity of bioinformatics pipelines. The lack of a “gold standard” for most experimental data modalities makes it difficult to provide valid estimation for a particular MFS's quality. Yet, this goal can partially be achieved by analyzing inner-sample Distance Matrices (DM) and their power to distinguish between phenotypes. The quality of a DM can be assessed by summarizing its power to quantify the differences of inner-phenotype and outer-phenotype distances. This estimation of the DM quality can be construed as a measure of the MFS's quality. Here we propose Hobotnica, an approach to estimate MFSs quality by their ability to stratify data, and assign them significance scores, that allow for collating various signatures and comparing their quality for contrasting groups.", "keywords": [ "Molecular signature", "Distance Matrix", "Differential Gene Expression", "Gene Signature", "Rank statistics" ], "content": "Introduction\n\nA signature based on a predefined Molecular Features Set (MFS), which is designed to distinguish biological conditions or phenotypes from each other, is a crucial concept in bioinformatics and precision medicine. In this context, signatures typically originate from MFS from contrasting experimental data from two or more sample groups, which differ phenotypically. These MFS incorporate information on the differences between the groups. The nature of the MFS depends on the modality of the original data. For instance, the MFS provided by the Differential Gene Expression approach is a list of Differentially Expressed genes (DEG); Differential Methylation analysis provides Differentially Methylated Cytosines or regions (DMC and DMR) as MFS.\n\nA significant number of mutational, expression and methylation-based signatures have recently been published and they are actively used in research and translational medicine. Examples of expression-based signatures involve gene sets for clinical prognosis (e.g., PAM50,1 MammaPrint2), for pathways and gene enrichment analysis (e.g., MsigDB collections3), and for drug re-purposing (e.g., LINCS project4).\n\nDirect quality assessment for MFS is currently hardly possible, since there are no ‘gold standard’ datasets where active Molecular Features are explicitly known. In this manuscript, we propose a novel approach - Hobotnica, that allows for measurement of MFS quality by addressing the key property of the signature, namely, its quality for data stratification.\n\nHobotnica leverages the quality of distance matrices obtained from any source, in order to assess the quality of the MFS from any data modality compared to a random MFS. In this study, we demonstrate its application to transcriptomic signatures.\n\n\nMethods\n\nThe Hobotnica approach is as follows: For a given data set W and a given MFS (S) we derive the inter-sample distance matrix (DMSW). Then we assess the quality of DM (and, thus, of S) with a summarizing function (αDMS=αDMSY or by abuse of notation αDMS) where (Y) represents the labels of samples. In shorter notation,\n\nWe desire the function α to gauge if the inner-class samples are closer to each other than to outer-class samples. If no difference exists from one class to another, α must be close to zero and as the difference grows, α grows. In the ideal case of a perfect separation, α reaches its maximum at 1:\n\n• α∈01\n\n• α→1⇔ High groups stratification quality\n\n• α→0⇔ Low groups stratification quality\n\nUnder the null hypothesis of Hobotnica ((H0)), no significant difference exists between αS and the α of an equal-sized general random set. On the contrary, the alternative (HA) hypothesizes that S generates higher α than most random S′ of the same size. To estimate a null distribution for Hobotnica’s α, we applied a permutation test. As our default options, we use Kendall distance as the distance measure and Mann-Whitney-Wilcoxon test as the summarizing function.\n\nWhen instead of a single MFS a set of hypotheses H1:MFS1H2:MFS2…Hn:MFSn is in place, for each Molecular Feature Set MFSi corresponding Distance Matrix DMi can be generated, and than, in turn, particular value of the measure αi:\n\nThus, for every MFS MFSi from set of hypotheses H1:MFS1H2:MFS2…Hn:MFSn H-score αi may be computed, resulting in a set α1α2…αn. Comparing α values allows for corresponding Feature Sets qualities ranking and selecting the most informative Signatures for the Data D.\n\nTo validate our approach, we conducted three case studies.\n\nIn the first case study we extracted RNA-seq expression dataset for prostate cancer from the Cancer Genome Atlas (TCGA) on counts level.5 As MFSs, we recruited the C2 collection of molecular signatures from MSigDB,3,6 that contains a number of prostate-related gene sets. This way, every candidate MFS (gene set from the collection) produced its specific H-score.\n\nFor the second case study, we recruited the PAM50 molecular signature,7 which was designed for classifying various breast cancer subtypes, as MFS. Then, we applied it to several datasets containing these breast cancer subtypes.5,8–11\n\nIn the third case study, we explored H-scores delivered by various DGE approaches. We performed DGE analysis for two groups of mice samples with different response to MYC factor treatment (Mycfl/fl vs MycΔIE, ERT2 genotypes)12 with DESeq213 and edgeR.14\n\nThe top 100 genes for each method were then retrieved. In addition, we extracted a list of genes genes with the highest variance in expression, as well as a number of random gene sets.\n\nIn each case, the counts were normalised to counts per million (cpm). For every geneset an H-score and its p-value with BH15 correction were computed.\n\n\nResults\n\nProstate-related C2 gene sets clearly demonstrated highest H-score values and sufficient statistical significance (Table 1, Figure 1A), as well as data stratification (Figure 1B), which is expected for prostate cancer as opposed to control contrast. Gene sets not attributed to prostate cancer-related processes did not achieve statistically significant p-values (Table 1).\n\nH-scores for the PAM50 signature were evidently higher for all datasets in the second case study than those for random gene sets for the same datasets (Figure 2, Figure 1C). This implies that the PAM50 signature exhibits a high stratification quality for various breast cancer subtypes samples. PAM50-delivered H-scores also demonstrated highly statistically significant p-values (Table 2).\n\nIn the third case study, various DGE approaches resulted in gene sets that delivered significantly different H-scores (Figure 3). For this dataset, edgeR provided a signature with the best quality score, while DESeq2 still demonstrated a higher separation quality than that of random signatures. Genes with the highest variance showed lower scores compared to random gene sets. This result stresses the importance of the Hobotnica procedure to evaluate the quality of a particular DGE analysis.\n\n\nDiscussion\n\nHobotnica was designed to quantitatively evaluate MFS quality through their ability for data stratification, based on their inter-sample distance matrices, and to assess the statistical significance of the results. We demonstrated that Hobotnica can efficiently estimate the quality of a molecular signature in the context of expression data.\n\nThe suggested method can be used to evaluate various sorts of MFSs: those retrieved from DGE or DM analyses, Mutation/single nucleotide variation calling or pathways analysis, as well as data modalities of other types, that are suitable as differential problems.\n\nA possible application of Hobotnica is evaluating a particular model’s performance (e.g., DGE model) for a particular dataset. This will allow researchers to choose a method that delivers a signature with the best data stratification from a number of proposed approaches.\n\nAssessing H-score values for various lengths of the same set or signature can be explored with the proposed method, which will help to optimize MFS structure. Such procedures can be especially crucial in clinical applications.\n\n\nData availability\n\nNCBI Gene Expression Omnibus: Alternatively processed and compiled RNA-Sequencing and clinical data for thousands of samples from The Cancer Genome Atlas, https://identifiers.org/ncbiprotein:GSE62944\n\nNCBI Gene Expression Omnibus: Modeling precision treatment of breast cancer, https://identifiers.org/ncbiprotein:GSE48216\n\nNCBI Gene Expression Omnibus:Spatial proximity to fibroblasts impacts molecular features and therapeutic sensitivity of breast cancer cells influencing clinical outcomes, https://identifiers.org/ncbiprotein:GSE80333\n\nNCBI Gene Expression Omnibus: Next Generation Sequencing Analysis of Mycfl/fl and MycIE, ERT2 intestinal transcriptomes, https://identifiers.org/ncbiprotein:GSE155460\n\nAnalysis code\n\nAnalysis code available from: https://github.com/lab-medvedeva/Hobotnica-main\n\nArchived analysis code as at time of publication: https://doi.org/10.5281/zenodo.5656814\n\nLicense: GNU General Public License v2.0\n\n\nCompeting interests\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis work was supported by Ministry of Science and Higher Education of the Russian Federation (agreement no. 075-15-2020-899) and by the NIH grants R01DE027809 and P30CA006973.", "appendix": "Acknowledgements\n\nWe thank Frank Emmert-Streib, Leslie Cope and Elana Fertig for fruitful discussions.\n\n\nReferences\n\nParker JS, Mullins M, Cheang MCU, et al.: Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 2009; 27(8): 1160–1167. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCardoso F, van’t Veer LJ, Bogaerts J, et al.: 70-gene signature as an aid to treatment decisions in earlystage breast cancer. N. Engl. J. Med. 2016; 375(8): 717–729. Publisher Full Text\n\nSubramanian A, Tamayo P, Mootha VK, et al.: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. 2005; 102(43): 15545–15550. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLiu C, Jing S, Yang F, et al.: Compound signature detection on lincs l1000 big data. Mol. BioSyst. 2015; 11(3): 714–722. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRahman M, Jackson LK, Evan Johnson W, et al.: Alternative preprocessing of rna-sequencing data in the cancer genome atlas leads to improved analysis results. Bioinformatics. 2015; 31(22): 3666–3672. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLiberzon A, Subramanian A, Pinchback R, et al.: Molecular signatures database (MSigDB) 3.0. Bioinformatics. 05 2011; 27(12): 1739–1740. ISSN 1367-4803. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nParker JS, Mullins M, Cheang MCU, et al.: Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 2009; 27(8): 1160–1167. PubMed Abstract \| Publisher Full Text\n\nVarley KE, Gertz J, Roberts BS, et al.: Recurrent read-through fusion transcripts in breast cancer. Breast Cancer Res. Treat. 2014; 146(2): 287–297. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMarusyk A, Tabassum DP, Janiszewska M, et al.: Spatial proximity to fibroblasts impacts molecular features and therapeutic sensitivity of breast cancer cells influencing clinical outcomes. Cancer Res. 2016; 76(22): 6495–6506. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDaemen A, Griffith OL, Heiser LM, et al.: Modeling precision treatment of breast cancer. Genome Biol. 2013; 14(10): R110–R114. Publisher Full Text\n\nCostello JC, Heiser LM, Georgii E, et al.: A community effort to assess and improve drug sensitivity prediction algorithms. Nat. Biotechnol. 2014; 32(12): 1202–1212. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLuo Y, Yang S, Wu X, et al.: Intestinal MYC modulates obesity-related metabolic dysfunction. Nat. Metab. July 2021; 3(7): 923–939. PubMed Abstract \| Publisher Full Text\n\nLove MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for rna-seq data with deseq2. Genome Biol. 2014; 15(12): 1–21. Publisher Full Text\n\nRobinson MD, McCarthy DJ, Smyth GK: edger: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010; 26(1): 139–140. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBenjamini Y, Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological). 1995; 57(1): 289–300." }	[ { "id": "102280", "date": "20 Dec 2021", "name": "Roberto Malinverni", "expertise": [ "Reviewer Expertise Epigenetics. R-developrer" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this short article the authors present an R package called Hobotnica, whose purpose is to evaluate the goodness with which different methodologies can stratify the results presented as Molecular Feature Sets (MFS). With MFS the authors point to all those types of data as a result of different -omics techniques (such as expression, methylation, Mutation / single nucleotide variation calling or pathways analysis).\n\nMajor comments\nThe authors present three examples in which it is demonstrated how this approach is able to evaluate the effectiveness of MFS stratification, but the examples considered are all based on expression data. To verify the statements presented in the article, it would be useful to test the methodology on different data (for example methylation arrays). The approach chosen for this evaluation is based on the calculation and comparison of Distance Matrices (DM).\n\nThe example of figure 3 evaluates two different standard approaches for the analysis of RNAseq using Hobotnica and the H0 value as discriminant. It can be appreciated in this figure how the stratification quality of Deseq2 is decidedly more efficient than both random genes and top variant genes. Surprisingly, however, the H0 value calculated using the top 100 genes collected with edgeR is very similar to that calculated using random genes, this confused me. Authors should explain this similarity more in depth.\n\nThe data presented in this article do not seem to convince satisfactorily. The quality evaluation power obtained by applying Hobotnica does not seem to correspond to the premises made. While not in fact a slate on the methodology, my advice is to review the examples and try to improve in benchmarking, adding different types of data.\n\nIs the rationale for developing the new method (or application) clearly explained? Yes\n\nIs the description of the method technically sound? Partly\n\nAre sufficient details provided to allow replication of the method development and its use by others? Partly\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Partly", "responses": [ { "c_id": "8284", "date": "16 Aug 2022", "name": "Alexey Stupnikov", "role": "Author Response", "response": "The authors present three examples in which it is demonstrated how this approach is able to evaluate the effectiveness of MFS stratification, but the examples considered are all based on expression data. To verify the statements presented in the article, it would be useful to test the methodology on different data (for example methylation arrays). The approach chosen for this evaluation is based on the calculation and comparison of Distance Matrices (DM). We thank the Reviewer for this suggestion. Indeed, the method we propose is applicable for Molecular Feature Sets evaluation of different nature, yet in the manuscript we demonstrated its work only for Expression based data.To improve the manuscript in a way the Reviewer suggested , we have performed additional analysis on Methylation based data for several datasets. We added this case study to the Validation and Results sections and comments to the Discussion section. The example of figure 3 evaluates two different standard approaches for the analysis of RNAseq using Hobotnica and the H0 value as discriminant. It can be appreciated in this figure how the stratification quality of Deseq2 is decidedly more efficient than both random genes and top variant genes. Surprisingly, however, the H0 value calculated using the top 100 genes collected with edgeR is very similar to that calculated using random genes, this confused me. Authors should explain this similarity more in depth. The point the Reviewer mentions indeed raises concern. After thorough examination we identified a data analysis related problem that caused the wrong genes subset process and resulted in the incorrect depiction in the presented barplot. We have corrected this issue. The rest of our findings were not changed during our reevaluation and all the results hold. The results are depicted and Fig.5 in the current manuscript version. The data presented in this article do not seem to convince satisfactorily. The quality evaluation power obtained by applying Hobotnica does not seem to correspond to the premises made. While not in fact a slate on the methodology, my advice is to review the examples and try to improve in benchmarking, adding different types of data. To address the Reviewer’s comments on the evaluation made in the manuscript we conducted additional analysis and validation carried out for methylation data modality on several datasets, and improved and fixed validation for differential expression analysis. Now we feel that the argument and claims we make regarding the H-score are compelling and plausible." } ] }, { "id": "102284", "date": "05 Jan 2022", "name": "Shailesh Tripathi", "expertise": [ "Reviewer Expertise Data science", "Machine learning", "network analysis", "computational biology", "gene expression data analysis" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors present an approach called Hobotonica for quantitatively evaluating (by assigning H score) MFS quality for given sample labels. This approach could be useful for analyzing samples, for e.g., quality comparison, filtering out poor quality samples, and comparing different phenotypical conditions and experiments. It is important that the authors should discuss a reasonable H-score interpretation in terms of various implications of data quality/outcome related to experimental conditions, sample size, data preprocessing, and the complexity of biological systems reflecting the non-trivial correlation structure.\nI highlight some of the recommendations to be discussed in the paper:\nThe author should add simulation studies providing a realistic understanding and interpretation of the H score.\n\nHow is the current approach different from the clustering-based approach where the optimized number of clusters are compared to sample labels using rand-index (where a high rand score means the clustering solution and the sample labels are in agreement) or other measures.\n\nThe analysis should consider experimental conditions (data derived from multiple experiments representing the same phenotype), data preprocessing methods, sample size, and gene expression data covariance structure.\n\nHow does H-score vary with relation to the number of phenotype conditions and number of MFS. The authors should add analysis and interpretation of results:\nwhen MFS is differentially expressed genes. when MFS is randomly selected. When MFS is a predefined set (e.g., GO pathway).\n\nThe author should add accurate descriptions of all the notations used.\n\nAdd a definition of H-score.\n\nIs the rationale for developing the new method (or application) clearly explained? Partly\n\nIs the description of the method technically sound? Partly\n\nAre sufficient details provided to allow replication of the method development and its use by others? Yes\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Partly", "responses": [ { "c_id": "8285", "date": "16 Aug 2022", "name": "Alexey Stupnikov", "role": "Author Response", "response": "The author should add simulation studies providing a realistic understanding and interpretation of the H score. The Reviewer raises an important problem of parametric and nonparametric statistics. The nature of H-score distribution indeed was not discussed in detail. Yet, its distribution was not the focus of this study, for distribution of H-scores for randomly selected Molecular Feature Sets is only employed to compute empirical p-values. This procedure is nonparametric and, therefore, is not affected by the nature of H-score distribution. We agree the nonparametric nature of the statistic needs to be mentioned more explicitly in the manuscript, and add a paragraph to the Discussion section: “The non-parametric statistic used in the approach not only allows for MFS of various types (differential, predefined, etc.) and data modalities (expression, methylation, etc.), but also for different structure of contrasted samples groups (sample size, preprocessing methods, etc.)” How is the current approach different from the clustering-based approach where the optimized number of clusters are compared to sample labels using rand-index (where a high rand score means the clustering solution and the sample labels are in agreement) or other measures. We agree the difference of our approach from clustering-based methods was not mentioned explicitly. We have added a paragraph to the Methods section discussing the difference of our approach. “The proposed approach is different from existing metrics, such as often used Rand index and other clustering-based measures, as it allows one to avoid clustering procedure, that itself may be carried out with various approaches and parameters. In contract to clustering-based methods, H-scores directly reflects the sample stratification quality.” The analysis should consider experimental conditions (data derived from multiple experiments representing the same phenotype), data preprocessing methods, sample size, and gene expression data covariance structure. The dataset details the reviewer mentions are crucial for understanding a particular dataset’s structure, and it is correct that they may affect some types of analysis. However, since the nature of the statistic is nonparametric, the details do not affect our approach. We agree this point needs to be stressed explicitly in the manuscript, and add a paragraph in the Discussion section: “The non-parametric statistic used in the approach not only allows for MFS of various types (differential, predefined, etc.) and data modalities (expression, methylation, etc.), but also for different structure of contrasted samples groups (sample size, preprocessing methods, etc.)” The exploration of H-score distribution in relation to experimental conditions mentioned above certainly is an interesting fundamental question. However, it does not affect the practical implementation we introduce. Therefore, we believe that such study is beyond the scope of a current paper. How does H-score vary with relation to the number of phenotype conditions and number of MFS. The authors should add analysis and interpretation of results: when MFS is differentially expressed genes. when MFS is randomly selected. When MFS is a predefined set (e.g., GO pathway). The nature of MFS indeed may be quite different. For this reason we have performed and discussed the analysis of following MFS types: differentially expressed genes randomly selected genes MysigDB gene sets (predefined genesets) In the revised version of manuscript differentially methylated MFS are also considered. In this way, we feel the analysis and the interpretation the Reviewer suggested can be found in the manuscript. The author should add accurate descriptions of all the notations used. To address Reviewer’s comment we carefully checked the manuscript to ensure all introduced notations are defined and explained, and added a subsection to the Methods section for more detailed description of H-score. Add a definition of H-score. We agree the definition of the H-score statistic and notation we introduce should be expanded. To address Reviewer’s comment, we have added a subsection to the Methods section where we define H-score with more details." } ] } ]	1	https://f1000research.com/articles/10-1260
https://f1000research.com/articles/11-937/v1	16 Aug 22	{ "type": "Research Article", "title": "Overdose symptoms and positive affect in never-established smokers are moderated by nicotine patch type: A between-subjects experimental investigation", "authors": [ "David G. Gilbert", "Bryant M. Stone", "Norka E. Rabinovich", "David G. Gilbert", "Norka E. Rabinovich" ], "abstract": "Background: A growing number of studies have assessed the effects of acute nicotine on affect, cognition, and brain activity in never-established smokers in attempts to identify mechanisms by which nicotine promotes progression to dependence. However, these acute administration studies have not adequately addressed the problem of potential adverse side effects due to lack of tolerance, such as nausea, feelings of sickness, lightheadedness, and general negative affect and malaise – a term referred to as nicotine overdose events (NODEs). Thus, we report the first study to carefully characterize the prevalence, intensity, and effects of NODEs in never-established-smokers after acute nicotine administration. Methods: We compared the subjective effects of two different 7 mg nicotine patches that have different pharmacokinetics on never-established smokers (n = 67). One patch produces gradual increases in blood nicotine and the other produces more rapid increases in blood nicotine. Results: The findings suggest that in never-smokers, the lowest dose (7 mg) of rapid blood nicotine-rise patches are associated with a high prevalence of NODEs (45.83%) and decreased positive affect (PA) (54.17%) compared to a placebo patch (8.34% for NODEs and 33.34% for PA). The slow-rise patch did not significantly affect nicotine overdose symptoms or PA. Conclusions: Fast blood-rise nicotine patches may not be an ecologically valid method of nicotine delivery to never-smokers, while slow-rise nicotine patches, lower dose, and self-paced dosing may be more appropriate in this population. Findings also highlight the importance of the careful assessment of NODES in this population.", "keywords": [ "nicotine patch", "pharmacokinetics", "never-smokers", "overdose", "mood" ], "content": "Introduction\n\nA growing number of studies are administering nicotine to never-established smokers in attempts to assess the effects of nicotine that are independent of withdrawal alleviation (e.g., Duke et al., 2015; Hahn et al., 2020; reviewed by Heishman et al., 2010; Knott et al., 1999). However, there has been surprisingly little formal assessment of dose and pharmacokinetic factors that can result in aversive responses to nicotine. This potential for overdose is especially true in the case of non-smokers. It has long been known that excessive and rapidly administered acute doses can cause nicotine overdose events (NODEs), including malaise, nausea, sickness, dizziness, unpleasantness, negative affect, and vomiting (Nyberg et al., 1982) and that high and rapidly administered acute nicotine doses can result in NODEs even in nicotine-dependent individuals (Gilbert et al., 1992; Seyler et al., 1984, 1986). Very little attention has been given to the potentially confounding effects of NODEs in never-established smokers (for brevity never-smokers are those smoking fewer than 100 cigarettes in their life) administered nicotine by nicotine patch, gums, and other routes. Given that NODEs are likely to decrease positive affect (PA), increase negative affect, and divert attention away from appropriate task performance in studies assessing the effects of nicotine on attention and affect, it is critical that studies use means of nicotine administration that minimize NODEs if inferences concerning the inherent effects of self-administered nicotine are to be accurately characterized and to have ecological validity. The accurate characterization of the effects of acute nicotine administration on mood and other potentially rewarding effects is important because never-smokers are the only group that can progress to becoming smokers and it is important to understand motives for progression to smoker status. Nicotine enhances dopamine in brain reward-related regions, such as the nucleus accumbens, with PA-inducing effects that have been promoted by many as critical determinants of the development-dependent smoking (Volkow et al., 2019).\n\nThere are several reasons why the better characterization of different nicotine dosing products and regimens is critically important to understanding nicotine use and treatment of nicotine dependence via smoking and other means. For example, while high doses of blood nicotine resulting from the rapid smoking of two 2.4 mg nicotine cigarettes after overnight deprivation in habitual smokers lead to large increases in blood beta-endorphin (BE) concentrations, minimal or no increases have been observed after the smoking of normal-nicotine delivery cigarettes smoked at more normal rates (Gilbert et al., 1992, 1994). Of note, BE, like cortisol and adrenocorticotropic hormone (ACTH), have been found to correlate strongly with the degree of aversive symptoms (e.g., nausea, sickness, and unpleasantness) in such studies (Gilbert et al., 1992; Seyler et al., 1984, 1986) associated with the smoking of high nicotine-delivery (e.g., 2.4 mg) cigarettes. Self-reported NODEs (e.g., nausea, sickness, and unpleasantness) increased after smoking two 2.4 mg nicotine cigarettes in rapid succession and subjective distress was correlated with changes in blood BE and cortisol. However, more natural smoking of a single regular (1.0 mg) cigarette did not increase blood BE or cortisol or subjective distress in a study by Gilbert et al. (1992). Overall, these findings indicate the critical importance of dose in determining the effects of nicotine in smokers, but there is no characterization of the effects of these dosing parameters in never-smokers and non-smokers.\n\nNonetheless, because of the lack of formal assessment of NODEs in the previous studies in never-smokers, the present study assessed NODEs formally by questionnaire every 20 minutes beginning 20 minutes after patch application in an investigation designed to assess the effects of nicotine on mood and attentional processes in never-smokers. The present report first describes the prevalence and severity of NODEs during the two-hour period after patch administration for two different brands of 7 mg nicotine patches, one with slow-rise and one with a fast-rise blood nicotine concentration, with nominally the same 24-hour nicotine delivery but with different pharmacokinetic properties.\n\n\nMethods\n\nThis study was approved by the Southern Illinois University Carbondale (SIUC) Institutional Review Board, IRB protocol number: 99128, assurance number FWA00005334. The study was initially approved on January 25th, 2004, and data collection started shortly after approval on April 30th, 2004. The study ran until February 1st, 2006, and the IRB re-reviewed and approved the protocol on January 18th, 2006, as part of a standard procedure of updating active studies (i.e., no ethical breaches occurred). Participants consented to participate at the beginning of the study and were able to quit the study at any point. NODE symptoms resolved within 30 minutes of patch removal. Unlike previous studies that lacked a formal assessment of NODEs in never-smokers, we assessed NODEs every 20 minutes beginning 20 minutes after patch application in an investigation designed to assess the effects of nicotine on mood and attentional processes in never-smokers. The present report first describes the prevalence and severity of NODEs during the two-hour period after patch administration for two different brands of 7 mg nicotine patches, one with fast-rise (study phase 1) and one with a 7 mg slow-rise blood nicotine concentration (phase 2), with nominally the same 24-hour nicotine delivery but with different pharmacokinetic properties. The primary aim of the study initially was to assess the effects of acute nicotine on PA in never-smokers, but due to the unexpected modestly high prevalence of NODEs observed in our initial group of participants, our subsequent aims were extended to include the comparison of the subjective states of fast versus slow blood nicotine rise-time patches in never-smokers.\n\nParticipants were never-smokers (n = 67) between the ages of 18 and 47 years (Mage = 23.76; SD = 7.16; 50% female). The sample size was dependent on funding. Never-smokers were defined as those smoking fewer than 100 cigarettes in their life and none in last year (Klemperer et al., 2021). The age limits were used because of the legal age of smoking (18 years old) and potential health risks and limited relevance to smoking onset at older ages. Participants were recruited by adverts throughout the Midwestern University community. Phone and in-person screening interviews were used to assess inclusion and exclusion criteria. Exclusion criteria included reported use of psychoactive drugs or medications other than caffeine, marijuana, and alcohol, excessive alcohol use, aged less than 18 or more than 50 years, non-English speaking, atypical sleep cycles, and serious medical problems. Participants were instructed not to drink alcohol for the 12 hours preceding each of the experimental sessions and not to smoke or use marijuana or any other psychoactive substance for at least 72 hours prior to the session. Only those who adhered to these abstinence requirements were included in the data analysis. Some participants were removed because they reported significantly high nicotine overdose symptoms 20 min and 40 min post-patch application (n = 6), prior to the time of significant increases in blood nicotine concentration and therefore presumably due to minor illness or other non-nicotine causes. No participants experienced NODEs severe enough to withdraw their data from the study. A total of 27 participants received the fast-rise patch and 40 received the slow-rise patch.\n\nFeelings State Questionnaire (FSQ). Participants completed the FSQ developed by the author (Gilbert et al., 1992), a measure designed to assess the physical and affective effects of nicotine. The FSQ contains 14 10-point Likert items ranging from 1 = none to 10 = extreme. We used summated scores for the analyses. We used two of its subscales, 1) nicotine overdose symptoms (sick, dizzy, lightheaded, and nauseous) and 2) positive (happy and pleasantness). Previous research has shown that the FSQ is sensitive to experimental manipulations and correlates with measures of mood (Gilbert & Spielberger, 1987). The internal consistency of the four-item overdose scale at time one for the placebo session was acceptable, α = .680 and excellent for the PA scale, α = .914. The mean score on the nicotine overdose scale indicated low overall overdose symptoms (M = 2.07, SD = 2.43) and was normally distributed, γ = 1.10, κ = -.10. The mean score on the PA scale indicated moderate overall PA (M = 10.60, SD = 3.59) and was normally distributed, γ = -.34, κ = -.31.\n\nDuring phase 1 of the study, a 7 mg NicoDerm® CQ® rapid blood-nicotine rise patch was used because the series of NicoDerm® CQ® 21 mg, 14 mg, and 7 mg patches are one of the two most widely used brand of patch for smoking cessation in the USA (personal search of ClinicalTrials.gov) and because a number of previous studies by others had used either the 7 mg, 14 mg, or 21 mg NicoDerm® CQ® patch without reporting or apparently formally assessing NODEs (Barr et al., 2008; Potter & Newhouse, 2008; Wignall & de Wit, 2011). GlaxoSmithKline provided the patches. According to the findings of Gupta et al. (1995) NicoDerm® CQ® patches (i.e., fast-rise) reach 80% maximum blood nicotine concentrations about two hours after application, while the formulation of the Habitrol® patches (i.e., slow-rise) used at the time of the study reached 80% maximum blood nicotine concentrations about four hours after application. From one to two hours after application the NicoDerm® CQ® patch results in a blood nicotine concentration that is twice or more than that of the Habitrol® patch. It is important to note that the blood nicotine rise times for the “rapid-rise” patch patches are relatively faster than other patches and are still much slower than for other forms of over-the-counter nicotine administration, including lozenges, inhalers, e-cigarettes, and tobacco cigarettes (Shiffman et al., 2005).\n\nA MiniCO meter (Vitalograph, Lenexa, Kansas) was used to assess carbon monoxide concentrations prior to acceptance into the study and at the beginning of each of the two experimental sessions in order to help assure never-smoker status and abstinence from other smoked psychoactive substances. We used a cut-off of less than or equal to six parts per million.\n\nParticipants completed an orientation session during which they were informed of the nature of the study, signed an informed consent approved by the Carbondale Committee for Research on Human Subjects (protocol #99128), and completed a current and life-time retrospective version of the Time-line Followback for Tobacco, Drugs, and Substance Use (not used in the current study; Sobell & Sobell, 2000), the FSQ (Gilbert et al., 1992), a demographics questionnaire that assessed age and gender, and provided a carbon monoxide breath samples. Participants attended two experimental sessions during which they sat alone in a small experimental room that was electronically connected to a central control room. The control room contained a server computer for control of experimental tasks, video display units for monitoring each participant’s computer and behavior, and audio communications with each of the individual subject rooms. Participants earned monetary compensation for the completion of the study. Half of the never-smokers wore a nicotine patch on the first session and a placebo patch on the second session, while the other half had the reverse order of patches. The participants and the experimenters interacting with the participants were blind to the nicotine versus placebo status of the patches.\n\nExperimental sessions began between noon and 2:00 p.m. and lasted about 120 minutes. A minimum of one day and a maximum of seven days separated the practice sessions and each of the four experimental sessions. The nicotine or placebo patch was then applied. A researcher not involved in data collection or otherwise interacting with subjects provided the appropriate nicotine or placebo patch and kept a record of which patch was given. Neither the participant nor the researchers who gathered the data and interacted with the participant had any information about which patch was given.\n\nDuring phase 1 of the study (n = 27 participants) a 7 mg NicoDerm-CQ® (rapid blood-nicotine rise) patch was used because this is the most widely used brand of patch for smoking cessation and patch research in the USA. After the identification of a modest number of incidences of adverse reactions to the NicoDerm-CQ® patch, we switched to a slower blood nicotine rise patch in what we now label as phase 2 of the study that used all new participants (n = 40). To avoid nausea and other adverse effects of rapidly rising nicotine, we used a 7 mg Habitrol® patch that has a slower blood nicotine rise profile than the NicoDerm-CQ® patch. The active patches were purchased at a local pharmacy. The placebo patch was a 2” × 2” bandage. To minimize the ability of participants to differentiate between active and placebo patches by skin sensations (itching or irritation) we used a cover bandage with capsaicin cream. Both the active and placebo patches were placed in the center of a 6.5 cm × 7.0 cm cover bandage. Then, a small amount (.05 cc) of capsaicin .075% cream (Capzasin-HP7, Chattem, Inc) was applied to the Teflon-coated surface of the cover bandage, covering an area 5 mm wide immediately next to each of the edges of the bandage. Pilot testing demonstrated that this procedure eliminated the ability of subjects to detect differences between the active and placebo patch when applied. During the time after patch application, participants completed the FSQ starting 20 minutes after patch administration and every 20 minutes after for 100 minutes.\n\nWe analyzed the data using SPSS Statistics 27.0 (RRID:SCR_016479) (IBM Corporation, LLC, Armonk, NY, 2020). We conducted a 2 (patch type: slow-rise vs. fast-rise) × 2 (condition: placebo vs. nicotine) × 5 (time: 20 minutes vs. 40 minutes vs. 60 minutes vs. 80 minutes vs. 100 minutes) analysis of variance (ANOVA). We conducted one ANOVA for the overdose scale and one ANOVA for the PA scale using the Greenhouse-Geisser degrees of freedom correction to adjust for the false inflation of the effect size due to heterogeneity of variances. A Bonferroni correction for all post-hoc tests to control for family-wise error was used.\n\n\nResults\n\nAll 67 participants completed all five timepoints. There was a three-way interaction, F(2.14, 89.78) = 10.24, p < .001, ηp2 = .196, involving patch type, condition, and time (Stone, 2022). There were significant simple effects for the fast-rise patches between conditions at 60, 80, and 100 minutes after patch administrations, ps < .001 (see Figure 1). At these times after patch administration, individuals who used the fast-rise nicotine patch reported significantly more NODEs compared to when they received the placebo patch. For the PA scale, there was a three-way interaction, F(2.84, 119.31) = 3.19, p = .028, ηp2 = .071, such that there were significant simple effects for the fast-rise patches between conditions at 60, 80, and 100 minutes after patch administrations, ps < .016 (see Figure 2), such that individuals who used the fast-rise nicotine patch reported significantly less PA compared to when they received the placebo patch. There were no significant differences between the placebo patch and the slow-rise nicotine patch at any time points for either scale, ps > .396.\n\nMean NODE scores between the two patch types (slow-rise vs. fast-rise) by condition (nicotine vs. placebo patch) across the five time points in 20-minute intervals in a three-way ANOVA. The results show a large effect of NODEs between the fast-rise compared to the placebo conditions, where only the fast-rise patches caused significant NODEs. NODE, nicotine overdose event.\n\nMean PA scores between the two patch types (slow-rise vs. fast-rise) by condition (nicotine vs. placebo patch) across the five time points in 20-minute intervals in a three-way ANOVA. The results show a large effect of PA between the fast-rise compared to the placebo conditions, where only the fast-rise patches caused a significant reduction in PA. PA, positive affect.\n\nWe assessed the prevalence of NODEs by comparing baseline scores to that of T5. We used a mean score change of 2 points to determine which participants experienced NODEs or a reduction in PA. The findings suggest that in never-smokers, the lowest dose (7 mg) of rapid blood nicotine-rise patches are associated with a high prevalence of NODEs (45.83%) and decreased PA (54.17%) compared to a placebo patch (8.34% for NODEs and 33.34% for PA). Note that none of the items were significantly more endorsed than the others (i.e., these changes in NODEs and PA were not driven by a single item).\n\n\nDiscussion\n\nThe current investigation is to compare the subjective effects of two different commonly used nicotine patches in never-established-smokers. We found that never-smokers reported significantly more NODEs and less PA compared to placebo. These effects were not found in never-smokers who received the slow-rise nicotine patch during our two-hour assessment period. Never-smokers in the present study experienced adverse NODEs, such as nausea and feeling of sickness, when placed on the nicotine patch that produces a rapid increase in blood-nicotine concentration. Below we briefly address the potential implications of these findings, the limitations of the current study, and directions for future research.\n\nThe present findings are consistent with previous studies on habitual smokers that have shown that forcing regular smokers to consume nicotine more quickly than their typical rate can lead to nausea and even vomiting (e.g., Gilbert et al., 1992) smoke more intensely. For example, administering nicotine too quickly or in too high of doses can produce NODEs. There is a fine line between beneficial and distress-producing doses (Gilbert et al., 1992). Small differences in nicotine dosing (e.g., doubling the dose) can produce large differences in subjective and physiological effects (Gilbert et al., 1992) that make NODE-related findings ecologically invalid. Administering nicotine too quickly or in too high of doses can produce NODEs. Because habitual smokers typically do not experience NODEs when using nicotine, it is suggested that the doses of nicotine that produce NODEs may not be ecologically valid in many cases. The present results call into question the results of studies using fast-rise nicotine patches in non-smokers (e.g., Griesar et al., 2002; Sørensen et al., 2009). NODEs in nicotine research may interfere with the detection of potential reinforcing, affect-modulating, and attention-enhancing effects of nicotine and be correlated with abnormal neural and hormonal activity, limiting ecological validity.\n\nFor practical purposes, most laboratory studies of acute dosing effects in never-smokers use experimental sessions that last no more than half a day each, a period that included nicotine administration followed by mood and experimental tasks. In addition, blood nicotine level figures from the pharmacogenetics study (Gupta et al., 1995) show that fast-rise patches produce elevations at two hours that are twice as high as the slow-rise patches. However, eight hours after application the two patches produce equally high blood nicotine concentrations. The time trajectories of NODEs across this period are not known. Given that rapid tolerance develops to acute nicotine, it is not clear whether the slow-rise patches would ever produce a substantial prevalence of NODEs or for how long a duration NODEs would be sustained in rapid-rise participants. It would likely be fruitful to examine NODE time courses and to evaluate self-paced and other means of nicotine administration (e.g., electronic cigarettes or inhalers) in never-smokers. We believe that it is critically important for future acute administration studies to systematically assess NODEs using our measure or similar measure to help ensure that they are not adversely affecting study outcomes and conclusions.\n\nThe findings have a few limitations and future directions. First, we stopped data collection for the never-smokers who received the fast-rise nicotine patches because the patches were making the participants significantly sick (e.g., several participants felt they might vomit), something that we feared would prevent the accurate assessment of the effects of nicotine on PA. Thus, individuals were not randomized to the two patch types. However, it is important to note that the subjects were from the same larger subject pool (all recruitment procedures and acceptance criteria remained the same for the two samples), there was no recruitment break between the samples, and the two groups did not differ in terms of demographics.\n\nFurther, despite the dates of data collection occurring in the early 2000s, the results should not be affected by changing cultural factors since the data were collected. The NicoDerm and Habitrol patches are still being used in studies and sold over the counter. Thus, our findings are still relevant and may be even more relevant as researchers continue to use fast-rise patches with never-established smokers, despite the loss of ecological validity from the excessive presence of NODEs in their participants.\n\nIn conclusion, our findings make an important contribution to the literature in that they underline the oft-neglected importance of carefully and routinely characterizing NODEs because even subtle differences in dosing methods can lead to adverse effects on mood state. The first author noted this some 30 years ago in the case of experimental demands for high levels of smoking-delivered nicotine intake that result in NODEs in dependent smokers (Gilbert et al., 1992). Whatever the assessed subject group, it is critical that researchers to avoid using experimental demands that result in rapidly rising or high blood concentrations of nicotine that cause NODEs and altered cognitive and affective states.\n\n\nData availability\n\nOpen Science Framework: Overdose Symptoms and Positive Affect in Never-Established Smokers are Moderated by Nicotine Patch Type. https://doi.org/10.17605/OSF.IO/VS7JC (Stone, 2022).\n\nThis project contains the following underlying data:\n\n- Data.sav (spreadsheet data)\n\n- Labels.docx (codebook for spreadsheet data)\n\n- Feelings State Questionnaire.docx\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nBarr RS, Culhane MA, Jubelt LE, et al.: The effects of transdermal nicotine on cognition in nonsmokers with schizophrenia and nonpsychiatric controls. Neuropsychopharmacology 2008; 33(3): 480–490. PubMed Abstract \| Publisher Full Text\n\nDuke AN, Johnson MW, Reissig CJ, et al.: Nicotine reinforcement in never-smokers. Psychopharmacology 2015; 232(23): 4243–4252. PubMed Abstract \| Publisher Full Text\n\nGilbert DG, Spielberger CD: Effects of smoking on heart rate, anxiety, and feelings of success during social interaction. J. Behav. Med. 1987; 10(6): 629–638. PubMed Abstract \| Publisher Full Text\n\nGilbert DG, Meliska CJ, Welser R, et al.: Depression, personality, and gender influence EEG, cortisol, beta-endorphin, heart rate, and subjective responses to smoking multiple cigarettes. Personal. Individ. Differ. 1994; 16: 247–264. Publisher Full Text\n\nGilbert DG, Meliska CJ, Williams C, et al.: Subjective correlates of smoking-induced elevations of peripheral beta-endorphin and cortisol. Psychopharmacology 1992; 106: 275–281. Publisher Full Text\n\nGriesar WS, Zajdel DP, Oken BS: Nicotine effects on alertness and spatial attention in non-smokers. Nicotine Tob. Res. 2002; 4(2): 185–194. PubMed Abstract \| Publisher Full Text\n\nGupta SK, Okerholm RA, Eller M, et al.: Comparison of the Pharmacokinetics of Two Nicotine Transdermal Systems: Nicoderm and Habitrol. J. Clin. Pharmacol. 1995; 35(5): 493–498. PubMed Abstract \| Publisher Full Text\n\nHahn B, Shrieves ME, Olmstead CK, et al.: Evidence for positive allosteric modulation of cognitive-enhancing effects of nicotine in healthy human subjects. Psychopharmacology 2020; 237(1): 219–230. PubMed Abstract \| Publisher Full Text\n\nHeishman SJ, Kleykamp BA, Singleton EG: Meta-analysis of the acute effects of nicotine and smoking on human performance. Psychopharmacology 2010; 210(4): 453–469. PubMed Abstract \| Publisher Full Text\n\nIBM Corp: IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY:IBM Corp;Released 2020.\n\nKlemperer EM, Hughes JR, Callas PW, et al.: Tobacco and Nicotine Use Among US Adult “Never Smokers” in Wave 4 (2016-2018) of the Population Assessment of Tobacco and Health Study. Nicotine Tob. Res. 2021; 23(7): 1199–1207. PubMed Abstract \| Publisher Full Text\n\nKnott V, Bosman M, Mahoney C, et al.: Transdermal nicotine: Single dose effects on mood, EEG, performance and event-related potentials. Pharmacol. Biochem. Behav. 1999; 63(2): 253–261. Publisher Full Text\n\nNyberg G, Panfilov V, Sivertsson R, et al.: Cardiovascular effects of nicotine chewing gum in healthy non-smokers. Eur. J. Clin. Pharmacol. 1982; 23(4): 303–307. PubMed Abstract \| Publisher Full Text\n\nPotter AS, Newhouse PA: Acute nicotine improves cognitive deficits in young adults with attention-deficit/hyperactivity disorder. Pharmacol. Biochem. Behav. 2008; 88: 407–417. PubMed Abstract \| Publisher Full Text\n\nSeyler LE, Fertig J, Pomerleau O, et al.: The effects of smoking on ACTH and cortisol secretion. Life Sci. 1984; 34(1): 57–65. Publisher Full Text\n\nSeyler L, Pomerleau OF, Fertig JB, et al.: Pituitary hormone response to cigarette smoking. Pharmacol. Biochem. Behav. 1986; 24(1): 159–162. Publisher Full Text\n\nShiffman S, Fant RV, Buchhalter AR, et al.: Nicotine delivery systems. Expert Opin. Drug Deliv. 2005; 2(3): 563–577. Publisher Full Text\n\nSobell LC, Sobell MB: Instructions for filling out the Timeline Cigarette Use Calendar.2000. (accessed on February 2, 2009).Reference Source\n\nSørensen LT, Zillmer R, Ågren M, et al.: Effect of smoking, abstention, and nicotine patch on epidermal healing and collagenase in skin transudate. Wound Repair Regen. 2009; 17(3): 347–353. PubMed Abstract \| Publisher Full Text\n\nStone B: Overdose Symptoms and Positive Affect in Never-established Smokers Are Moderated by Nicotine Patch Type. OSF. [Dataset]. 2022. Publisher Full Text\n\nVolkow ND, Michaelides M, Baler R: The neuroscience of drug reward and addiction. Physiol. Rev. 2019; 99: 2115–2140. PubMed Abstract \| Publisher Full Text\n\nWignall ND, de Wit H : Effects of nicotine on attention and inhibitory control in healthy nonsmokers. Exp. Clin. Psychopharmacol. 2011; 19: 183–191. PubMed Abstract \| Publisher Full Text \| Free Full Text" }	[ { "id": "235760", "date": "13 Feb 2024", "name": "Bertrand Dautzenberg", "expertise": [ "Reviewer Expertise Smoking Vaping (former chaest physician)" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nReview F1000 RESEARCH\nOverdose symptoms and positive affect in never-established are moderated by nicotine patch type: A between- subjects experimental investigation [version 1 awaiting peer review] from David G. Gilbert , Bryant M. Stone, Norka E. Rabinovich\nThis paper describe in non-smokers (less 100 cigarettes in the life) the NODE (Nicotine tolerance and effect) and the decrease of PA (measured on positive affect scale) after use of a 7mg/24h patch or placebo using rapid or slow nicotine delivery (single use) The results are interesting, but the paper is confusing and need review for precision and clarification of the results.\nOn the period of the study : Data collection starts in April 30th 2004 and was submit in 2022 (Such 18 years delay need some explanation).\nNever-established smokers included :The tolerance of nicotine in non-current smoker was different in non-current smoker between those who never use of single cigarette and former smoker who dont smoke from several years (Respir Med Res. 2021 Nov:80:100844. doi: 10.1016/j.resmer.2021.100844. Epub 2021 Jun 7.).\nIt is not very clear among the 67 participants who have smoke some cigarettes and who have not smoke a single cigarette. (A decrease of NODEs and a greater stability of PA is anticipate in those who have smoke 1to 100 cigarette in the past vs never smokers). Authors need to provide theses results (if information available)\nHour of record of datas Authors report in introduction that the nicotine pic of nicotine is 2 hours (120 minutes) with the rapid nicotine delivery and 4 hours (240 minutes with standard speed of nicotine deliveryl®) . You report concern 20, 40, 60, 80 and 100 minutes, Please explain why you don’t report the monitoring of nicotine until the time of anticipated nicotine peak). In discussion page 7 you discuss 2 hours results but without figure. And discuss result according to the delay between end of monitoring (100 min) and the Peak (240 min for Habitrol®).\nA “phase 1” is describe with 27 inclusions, but you don’t report “phase 2”. Please clarify and explain that you report phase 1 , Pase1+2, but not phase 2 (if I have understand).\nLegend of figure 1: Please precise the number of participant (n=67) (If is not clear if all the 67 participants receive placebo patch, rapid and standard nicotine release , if not provide the numbers) Please precise that overdose symptoms (NODEs) in ordinate are the mean of the total score or of the mean of individual scores. The last sentence of the figure could be transfer to the text of the results.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "246955", "date": "28 Mar 2024", "name": "Noni Soeroso", "expertise": [ "Reviewer Expertise oncology and lung cancer" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this study, the researchers assessed the effects of acute nicotine on positive affect in never-smokers and compared the subjective states of fast versus slow blood nicotine rise-time patches in never-smokers. The study aimed to evaluate the effects of acute nicotine on positive affect using the Feelings State Questionnaire (FSQ) in never-smokers and compare the subjective states of fast versus slow blood nicotine rise-time patches in never-smokers. Finally, they found the prevalence of NODEs by comparing baseline and suggested that in never-smokers, the low dose of 7 mg of rapid blood nicotine-rise patches is associated with a high prevalence of NODES and decreased positive affect compared with the placebo patch.\nStrengths of the study: Overall, the abstract is clear and coherent in presenting the study’s purpose, methods, results, and conclusion. This is an experimental study with consecutive sampling. It provides essential information about the research and a clear conclusion.\nWeaknesses: This study had two arms that used a fast-rise patch and a slow-rise patch; unfortunately, the sample size of participants was not equal between the two groups. There is no result of the examination of blood nicotine concentrations of both patch applications after two hours or four hours after application; assessment only from NODEs and Feelings State Questionnaire (FSQ).\n\nIs the work clearly and accurately presented and does it cite the current literature? No\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "259948", "date": "16 Sep 2024", "name": "Ian Fearon", "expertise": [ "Reviewer Expertise Nicotine pharmacology", "biomarkers of exposure and of biological effect", "behavioural studies of nicotine use." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is an interesting paper examining the adverse consequences of nicotine administration among nicotine-naive individuals, and in particular whether the rate of administration affected and untoward effects of nicotine use. The study was well-conducted and concisely written up. The primary finding of the study was that the use of nicotine pouches which deliver nicotine rapidly was associated with adverse effects (nicotine overdose events) and decreased positive affect. In contrast, the use of pouches which contain the same amount of nicotine but deliver it more slowly was not associated with any such effects.\n\nThe topic of the paper is timely, given the ongoing debate regarding the effects of the use of nicotine and in particular of novel use forms such as electronic cigarettes and tobacco-free nicotine pouches. In this sense, the paper may provide useful information concerning adverse effects of acute nicotine product use. A strength of the paper is that it examines the effects of nicotine in nicotine-naïve individuals (never smokers, noting that at the time the study was conducted other forms of consumer nicotine (e-cigarettes, nicotine pouches) were not available to use. It’s weakness is perhaps the age of the data, with the study conducted in 2004. However, I feel that the data are still relevant given that physiological responses to nicotine would still be the same now as they were when the study was conducted.\n\nMajor comments\n\nI have no major comments\n\nMinor comments\n\nI have just a few minor comments.\n\n1. Although data collection occurred some time ago, I feel that the data and the study findings are still relevant. One thing I would like to see though is, how do these findings impact the work of those studying potential therapeutic uses of nicotine? For example, the work of Paul Newhouse (e.g., Andrews P et al, 2024 [Ref 1], Conley AC et al 2022 [Ref 2], and Vega JN et al, 2019 [Ref 3]), who is examining potential medicinal uses of nicotine aside from smoking cessation. Many of Dr. Newhouse’s studies have used the same transdermal nicotine patches route of administration as that used in the study presented in this paper, and so the data may be informative regarding safety aspects of studies using nicotine patches for transdermal nicotine administration.\n\n2. 1st paragraph of the Discussion: change 'is to compare' to 'was'.\n\n3. 2nd paragraph of the Discussion: at the end of the first sentence, the text 'smoke more intensely' can be deleted.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-937
https://f1000research.com/articles/11-430/v1	19 Apr 22	{ "type": "Research Article", "title": "Cytotoxicity of Peruvian propolis and Psidium guajava on human gingival fibroblasts, PBMCs and HeLa cells", "authors": [ "Pablo Alejandro Millones-Gómez", "Myriam Angélica De la Garza-Ramos", "Victor Hugo Urrutia-Baca", "Humberto Carlos Hernandez-Martinez", "David Alejandro Hernández Marín", "Carlos Alberto Minchón Medina", "Myriam Angélica De la Garza-Ramos", "Victor Hugo Urrutia-Baca", "Humberto Carlos Hernandez-Martinez", "David Alejandro Hernández Marín", "Carlos Alberto Minchón Medina" ], "abstract": "It is indisputable that every day it is demonstrated that natural products present diverse therapeutic benefits, which has boosted their incorporation within various products for clinical use. However, this must be accompanied by knowledge of their effect on cell lines to ensure their use is safe. The objective of this study was to evaluate the cytotoxic effect of two ethanolic extracts based on Peruvian natural products, on three human cell lines. Cervical cancer cell lines (HeLa), human gingival fibroblasts (HGF-1 - ATCC CRL-2014) (HGF-1) and peripheral blood mononuclear cells (PBMCs) were cultured and subsequently treated with preparations of ethanolic extracts of propolis (EEP) and Psidium guajava (EEG) from a concentration of 50 mg/mL to 0.024 mg/mL, by the 3-(4,5- dimethylthiazol-2-yl)-2,5-diphenyltetrazole bromide reduction assay. At a concentration of 0.24 mg/mL EEG, viability of 99.7±1.24%, 99.8±2.2% and 99.7±2.7% was observed in HeLa, HGF-1 and PBMCs, respectively; >90% cell viability values were observed with EPP at 0.024 mg/mL, with HGF-1 showing the highest viability (96.9±1.15%). A dose-dependent effect was observed for both extracts with a decrease in cell viability as concentrations increased (up to 50 mg/mL). EEP and EEG extracts at low concentrations do not show cytotoxicity in human cell lines, these findings are an advance in the preclinical evaluation on their safety and open a continuity to further studies for their potential applications in dentistry and medicine.", "keywords": [ "Cytotoxicity", "Viability", "Propolis", "Guava" ], "content": "Introduction\n\nSince time immemorial, man has tried to mitigate his ailments and prolong his life. This fact has been observed since there have been historical records, from civilization to civilization, until today.1 Even so, man in the 21st century has not been able to avoid death by limiting himself to mitigating symptoms of diseases and avoiding the development of others.1,2\n\nIn times when man only had at his disposal the resources that the planet gave him, he sought in these the tools to reduce physical pain and avoid death. Among the resources most exploited by different cultures throughout history are mineral, animal and vegetable resources. Until the middle of the 20th century, these were the therapeutic resources par excellence.2,3\n\nAmong the kingdoms of nature that contribute, to this day, to reducing symptoms and preventing diseases, the plant kingdom stands out.4 Plants, thanks to their marvelous and complex metabolism, constitute a true chemical arsenal. Of which only a third is currently known, considering the variety of existing species worldwide, without considering those species already extinct.3,4\n\nEach region of the world developed its own way of healing from medicinal plants, which is unique and characteristic since species endemic to regions were used.4 Over time, these local characteristic therapies came to form the so-called traditional medicine and, when being preserved by the native peoples, is sometimes called aboriginal or autochthonous medicine, as well as traditional or autochthonous recipes4 that group together uses, forms of preparation, administration, dosage, among other modern pharmacological parameters. This is because our therapeutic reality today is governed by synthetic chemistry, but what few people know is that these successful molecules that cure are nothing more than improved copies of chemical substances that nature spontaneously created.4\n\nOne of the most studied products is propolis,5 which is composed of approximately 50% to 55% resins and balsams, 30% to 40% wax, 10% to 15% essential oils, 5% pollen and 5% minerals.5 In its components we can mention that it has phenolic compounds: Flavonoids, flavones, isoflavones and flavonones in 50%,5 which inhibit bacteria and fungi.6 The amount of flavonoids confers the antibacterial power to propolis. This quantity depends on the flora surrounding the bee hives.5 Its antibacterial action mechanism is given by the inhibition of cell division, DNA disruption, disorganization of the cytoplasmic membrane and inhibition of cell wall synthesis, causing partial bacteriolysis and inhibiting protein synthesis.5,6\n\nGuava (Psidium guajava) is a fruit native to Central America and the Caribbean, belonging to the Myrtaceae family, distributed in the tropics and subtropics around the world. Guava fruits stand out among tropical fruits not only because of their good organoleptic characteristics (flavor and aroma) but also nutritionally, they are a source of vitamin A, B1, B3 and C, fiber, minerals such as potassium, calcium, iron and phosphorus.7 The guava also has a relevant content of lycopene, an important carotenoid with therapeutic properties, so it has been widely studied.7,8\n\nCytotoxic evaluation, as the main factor of biocompatibility, is determined by the cell cultures to be selected for in vitro toxicity testing.9 Continuous and real-time monitoring allows label-free assessment of cell proliferation, viability and cytotoxicity, revealing the physiological status of the cells.8 To evaluate the efficacy of natural products, it is not enough to measure their therapeutic effect, but one must be sure that they do not cause deterioration of constituent cells. The aim of this study was to evaluate the cytotoxic effect of ethanolic extracts of propolis and P. guajava on HELA cell lines, human gingival fibroblasts (HGF-1) and peripheral blood mononuclear (PBMCs) cells.\n\n\nMethods\n\nPropolis and P. guajava samples were collected by researchers in the Oxapampa valley, Pasco, Peru following the methodology described by Millones et al.5,8 and subsequently refrigerated until processed. After they were removed from refrigeration they were left for two hours to allow for them to reach room temperature. Once they had reached room temperature they were macerated Once room temperature was reached, they were macerated with a volume of 100 ml of absolute ethanol for every 10 grams of propolis sample, it was then left at room temperature for 24 hours. Then, the macerate was filtered using a 20 cm diameter glass funnel with sterile cotton; the filtered sample was collected in a glass refractory to finally be taken to an extraction hood so that the ethanol present in the extract evaporates completely and only a pasty mass remains. This step was performed two more times until the samples were observed to be discolored. Finally, they were stored in glass containers covered with aluminum foil to avoid degradation.10\n\nThe HeLa cell line (ATCC, Manassas, VA, USA) (RRID:CVCL_0058) was cultured in a Petri dish with a 35 mm diameter glass bottom (MatTek Corporation, Ashland, MA, USA, CAT#: P DCF OS 30). The cell line was cultured in Eagle’s Minimum Essential Medium (Gibco) with 4% PBS (phosphate buffered saline) at 37°C in 5% CO2 and 95% air.5 The cells were incubated for 30 min in 1 mL of dye solution in Hank’s Balanced Salt Solution (HBSS, Thermo Fisher Scientific)) (100 nM Mitotracker Red FM) at 37°C, 5% CO2. After incubation, the cells were washed three times with HBSS buffer.11\n\nHuman gingival fibroblasts (HGF-1 - ATCC CRL-2014) (HGF-1) were obtained from the American Type Culture Collection (ATCC) and cultured in Dulbecco’s modified Dulbecco’s medium containing glucose (DMEM; Sigma-Aldrich, St. Louis, MO, USA) supplemented with 4 mM L-glutamine (Sigma-Aldrich), 1% penicillin, streptomycin (Sigma-Aldrich) and 10% (vol/vol) heat-inactivated fetal bovine serum (FBS; Sigma-Aldrich). Cells were incubated at 37°C in a 5% CO2 atmosphere in an incubator (Cytomat 2C450S; Thermo Fisher Scientific), and were fed every 48 hours and subcultured every 5 days at a 1:3 ratio using trypsin-EDTA (0.05%; Sigma-Aldrich) for 3 minutes at 37°C.12\n\nPBMC cells were isolated by Ficoll density gradient centrifugation (TBD, Shanghai, China) and cultured in RPMI-1640 medium with 10% fetal bovine serum and placed in a humidified incubator (Thermo CO2 incubator, 311, USA) at 37°C, 5% CO2 and 95% humidity. The medium was changed once every 24 hours.13–16\n\nTo evaluate the cytotoxic effect, cell viability methodology was performed in microplate with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazole bromide (MTT).10 For this, confluent cell cultures of (80-100%) contained in 25 cm2 flasks were started, the medium was discarded using a 5mL serological pipette, two washes were performed to the cell layer with PBS solution (0.004% Ethylene diamine tetracetic acid), 1 mL of Trypsin-EDTA (0.05%) was immediately added and incubated at 37°C for 15 min. A 20 μL sample was taken and 20 μL of 0.4% trypan blue (Gibco, Carlsbad, CA, USA) was added to perform a cell count in a Neubauer chamber (Sigma-Aldrich, model: Bright-LineTM Hemacytometer, catalog number: Z359629) to adjust the cell concentration to 5×104 cells per reaction with Dulbecco’s Modified Eagle’s medium (d-MEM) supplemented with 10% fetal bovine serum. Then 50 μL of the cell suspension was seeded, incubated at 37° C, 5% CO2 in an incubator (Cytomat 2C450S; Thermo Fisher Scientific) until confluence was obtained (after 48 hours), then different concentrations of the natural products5 (50 to 0.024 mg/mL) were applied and the plates were incubated for 48 hours. Only d-MEM culture medium was used as a negative control and as a positive control.\n\nThe medium used was then discarded and the cell layer was washed with PBS solution (0.004% EDTA) and 50 μL of d-MEM culture medium was added.\n\nTo each well, 20 μL of MTT (5 mg/mL) was added to each culture and then the cultures were incubated for four hours. After this time, the medium was aspirated. 200 μL of dimethyl sulfoxide was added to dissolve the formazan crystals; the plate was left in agitation for 15 minutes microplate shaker (Lab-Line Instrument Inc. Melrose Park, IL) and shaken at 120 revolutions per minute to ensure complete dissolution. Finally, the plate was read at 570 nm on a Smart Spectophotometer plus reader (1705061, Bio-Rad, Hercules, CA, USA).\n\nThe experimental data were analyzed using nonlinear regression with the Gompertz model to evaluate the effect according to the concentration of the doses used, whose equation is given by:32\n\nWhere, y is the cell viability, x the administered concentration of each product (mg/mL), and α, β, and k are the parameters of the model. Comparison of the cytotoxic effect of propolis and P. guajava was performed using analysis of covariance, which in addition to the product includes the concentration administered. Graphical presentation was prioritized to highlight some analyses. The analyses were performed with Excel (Microsoft Corporation, US, 2019) (RRID:SCR_016137) and SPSS version 26 (IBM, US, 2019) (RRID:SCR_016479).\n\n\nResults\n\nThe cytotoxic effect of Peruvian propolis is shown in Figure 1, with high cell viability at concentrations of 0.24 mg/mL, reaching 1.120±0.012 HBA cells, 0.922±0.011 HGF-1 and 0.624±0.002 PBMCs cells, decreasing rapidly to 0.052±0.002, 0.051±0.001 and 0.055±0.001, respectively as concentrations increase up to 50 mg/mL. The estimated nonlinear Gompertz regression models were:\n\nThe cytotoxic effect of Peruvian propolis is shown in Figure 1, with high cell viability at concentrations of 0.24 mg/mL, reaching 1.120±0.012 Henrietta Lacks cells (HELA cells), 0.922±0.011 human gingival fibroblasts (HGF-1) and 0.624±0.002 peripheral blood mononuclear cells (PBMCs cells), decreasing rapidly to 0.052±0.002, 0.051±0.001 and 0.055±0.001, respectively as concentrations increase up to 50 mg/mL. The observed trend shows that cell growth decreases in a non-linear fashion as the dose of Peruvian propolis administered increases.\n\nOn the other hand, the cytotoxic effect of Peruvian P. guajava is shown in Figure 2, with high cell viability at concentrations of 0.24 mg/mL, reaching 1.190±0.015 HBA cells, 0.948±0.020 HGF-1 and 0.685±0.019 PBMCs cells. These decreased more slowly to 0.656±0.019, 0.165±0.020 and 0.099±0.002, respectively as concentrations increase up to 50 mg/mL. The estimated nonlinear Gompertz regression models were:\n\nThe cytotoxic effect of guajava is shown in Figure 2, with high cell viability at concentrations of 0.24 mg/mL, reaching 1.190±0.015 Henrietta Lacks cells (HELA cells), 0.948±0.020 human gingival fibroblasts (HGF-1) and 0.685±0.019 peripheral blood mononuclear cells (PBMCs cells). These decreased more slowly to 0.656±0.019, 0.165±0.020 and 0.099±0.002, respectively as concentrations increase up to 50 mg/mL. Similarly, the observed trend shows that cell growth decreases in a non-linear fashion as the dose of guajava administered increases.\n\nThe goodness of fit of the Gompertz curves to the cytotoxic effect on the cell lines of both products is shown by the coefficient of determination (R2), this value is above 90% for all curves.\n\nThe cytotoxic effect of propolis and P. guajava on the cell lines was compared using analysis of covariance, which are shown in Table 1. In each of the cell lines, differences in the cytotoxic effect between both products were observed (p<0.01 in each of the lines); likewise, the linear effect of the concentrations used for each of the products was observed (p<0.01 in each of the lines), even though the non-linear effect was verified by means of the Gompertz model.\n\nFigures 3-5 show the cytotoxic effect of propolis and P. guajava on the cell lines as a percentage of cell viability, established from the medium controls and Triton X-100, being notorious the differences in the effect between both products, as already shown.\n\nFigure 3 compares the cytotoxic effect of propolis and P. guajava concentrations and Triton X-100 on Henrietta Lacks cells (HELA cells) viability (%), showing the average and the corresponding standard deviations. With propolis, the growth of HELA cells remains in control with doses of 50-1,563 mg/mL, increasing very rapidly with smaller doses. In contrast, with guajava, cell growth is already more than 50% at doses of 50 mg/mL, growing rapidly, and reaching maximum levels at doses of 1,563 mg/mL or lower.\n\nThe growth of human gingival fibroblasts remains in control with propolis doses of 50-0.39 mg/mL, with rapid growth at lower doses; in contrast, with gujava, while at doses of 50 mg/mL cell growth was pc more than 10%, it begins to increase considerably up to doses of 0.781 mg/mL, at which it reaches maximum growths.\n\nThe growth of peripheral blood mononuclear cells (PBMCs cells) remains in control with propolis doses of 50-0.39 mg/mL, with rapid growth at lower doses; on the contrary, with guajava, although at a dose of 50 mg/mL cell growth was small, it begins to increase considerably up to doses of 0.195 mg/mL, at which it reaches maximum growth.\n\n\nDiscussion\n\nThe aim of this study was to evaluate the cytotoxic effect of ethanolic extracts of propolis and P. guajava on HELA cell lines, HGF-1 and PBMCs cells. The results showed high cell viability at concentrations of 0.24 mg/mL, decreasing rapidly as concentrations increased up to 50 mg/mL.\n\nThe cytotoxicity assay revealed that Peruvian propolis and guajava extracts at lower concentrations can work safely on the fibroblast cell line. However, it is important to recognize that since this is an in vitro assay, this value may vary if other types of cell lines are used. The results obtained in the cytotoxicity assay, add to the increasingly abundant information reported by other research groups that have wanted to address this issue but focusing on alcoholic extracts,17–19 and are therefore important. The content of phenols and flavonoids obtained in the aqueous extract of propolis is lower than that reported by other research groups20 however, it should be noted that the extraction methods were different and as mentioned, these are determinant for the preparation of the extract. To determine which methodology is more efficient, the same propolis sample should be used,21–24 due to the high variability in the composition that this product may have with respect to its region of origin.24\n\nAs for P. guajava, it showed similar toxicity in the three cell lines. Some studies report a higher amount of active metabolites in the peel with respect to guava pulp, and also report a better antioxidant capacity in vitro.24,25 With the cytotoxic effect shown in HeLa cells, the world list of plants with potential for cases of cervical neoplasia published is increased, the results obtained in the study contribute to corroborate the properties traditionally attributed to these plants and highlight species of the Peruvian medicinal flora as a source of substances for the treatment of cancer.25\n\nDespite the high cytotoxicity shown by most of the propolis samples against the cell lines studied, the samples also showed toxicity to HGF-1 culture. Ling et al.26 have also investigated the cytotoxicity of Brazilian red propolis extracts for two tumor cell lines (Hep-2 and HeLa) and for normal human embryonic epithelial kidney (Hek-293), also reporting a higher IC50 value for Hek-293 compared to the tumor cell lines.\n\nAlthough both propolis and guava seem to exert a potential on PBMCs cells, only a few studies have been performed in this field of research.27–30 Despite this, our preliminary data suggest that both products could present a modulatory action on the immune response opening perspectives for further research in this field.\n\n\nConclusions\n\nEEP and EEG at low concentrations do not show cytotoxicity in human cell lines and their effect is dose dependent. Our findings are an advance in the preclinical evaluation of natural extracts from Peru on their safety and open a continuity to further studies for their potential applications in dentistry and medicine. Despite our positive data, further study is required to evaluate the usefulness of these extracts.\n\n\nData availability\n\nMendeley: Cytotoxicity database. https://doi.org/10.17632/yt4h7h9cvv.131\n\nThis project contains the following underlying data:\n\n- citotoxicidad.sav (raw data)\n\nMendeley: Cytotoxicity database. https://doi.org/10.17632/yt4h7h9cvv.131\n\nThis project contains the following extended data:\n\n- database.xlsx (Processed data)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nShi QW, Li LG, Huo CH, et al.: Estudio sobre química medicinal natural y desarrollo de nuevos fármacos. Mentón. tradición Hierba. drogas. 2010; 41: 1583–1589.\n\nFabricant DS, Farnsworth NR: El valor de las plantas utilizadas en la medicina tradicional para el descubrimiento de fármacos. Reinar. Perspectiva de Salud. 2001; 109 Suppl 1: 69–75. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGao XM, Zhang TM, Zhang JR, et al.: Materia médica china. Pekín, China: China Press de Medicina Tradicional China; 2007.\n\nAlves RR, Rosa IM: Biodiversidad, medicina tradicional y salud pública: ¿Dónde se encuentran?. J. Etnobiol. etnificado. 2007; 3. PubMed Abstract \| Publisher Full Text\n\nMillones Gómez PA, Tay Chu Jon LY, Maurtua Torres DJ, et al.: Antibacterial, antibiofilm, and cytotoxic activities and chemical compositions of Peruvian propolis in an in vitro oral biofilm. F1000Res. 2021 Oct 27; 10: 1093. Reference Source\n\nZulhendri F, Felitti R, Fearnley J, et al.: The use of propolis in dentistry, oral health, and medicine: A review. J. Oral Biosci. 2021 Mar; 63(1): 23–34. PubMed Abstract \| Publisher Full Text\n\nMorais-Braga MF, Carneiro JN, Machado AJ, et al.: Psidium guajava L., from ethnobiology to scientific evaluation: Elucidating bioactivity against pathogenic microorganisms. J. Ethnopharmacol. 2016 Dec 24; 194: 1140–1152. PubMed Abstract \| Publisher Full Text\n\nMillones-Gómez PA, Maurtua-Torres D, Bacilio-Amaranto R, et al.: Antimicrobial Activity and Antiadherent Effect of Peruvian Psidium guajava (Guava) Leaves on a Cariogenic Biofilm Model. J. Contemp. Dent. Pract. 2020 Jul 1; 21(7): 733–740. PubMed Abstract \| Publisher Full Text\n\nLiu HC, Chiang CC, Lin CH, et al.: Anti-cancer therapeutic benefit of red guava extracts as a potential therapy in combination with doxorubicin or targeted therapy for triple-negative breast cancer cells. Int. J. Med. Sci. 2020 Apr 6; 17(8): 1015–1022. PubMed Abstract \| Publisher Full Text\n\nVerma UP, Gupta A, Yadav RK, et al.: Cytotoxicity of chlorhexidine and neem extract on cultured human gingival fibroblasts through fluorescence-activated cell sorting analysis: An in-vitro study. Eur. J. Dent. 2018; 12(3): 344–349. PubMed Abstract \| Publisher Full Text\n\nKnies KA, Li YV: Zinc cytotoxicity induces mitochondrial morphology changes in hela cell line. Int. J. Physiol. Pathophysiol. Pharmacol. 2021 Apr 15; 13(2): 43–51. PubMed Abstract\n\nPoggio C, Riva P, Chiesa M, et al.: Comparative cytotoxicity evaluation of eight root canal sealers. J. Clin. Exp. Dent. 2017 Apr 1; 9(4): e574–e578. PubMed Abstract \| Publisher Full Text\n\nRiedhammer C, Halbritter D, Weissert R: Peripheral Blood Mononuclear Cells: Isolation, Freezing, Thawing, and Culture. Methods Mol. Biol. 2016; 1304: 53–61. PubMed Abstract \| Publisher Full Text\n\nGrievink HW, Luisman T, Kluft C, et al.: Comparison of Three Isolation Techniques for Human Peripheral Blood Mononuclear Cells: Cell Recovery and Viability, Population Composition, and Cell Functionality. Biopreserv Biobank. 2016 Oct; 14(5): 410–415. PubMed Abstract \| Publisher Full Text\n\nPatarat R, Riku S, Kunadirek P, et al.: The expression of FLNA and CLU in PBMCs as a novel screening marker for hepatocellular carcinoma. Sci. Rep. 2021 Jul 21; 11(1): 14838. PubMed Abstract \| Publisher Full Text\n\nGuimarães R, Barros L, Dueñas M, et al.: Nutrients, phytochemicals and bioactivity of wild Roman chamomile: a comparison between the herb and its preparations. Food Chem. 2013; 136(2): 718–725. PubMed Abstract \| Publisher Full Text\n\nRao CV, Desai D, Rivenson A, et al.: Chemoprevention of colon carcinogenesis by phenylethyl-3-methylcaffeate. Cancer Res. 1995; 55(11): 2310–2315. PubMed Abstract\n\nLeu T-H, Maa M-C: The molecular mechanisms for the antitumorigenic effect of curcumin. Curr. Med. Chem. Anticancer Agents. 2002; 2(3): 357–370. PubMed Abstract\n\nTapiero H, Tew KD, Ba GN, et al.: Polyphenols: do they play a role in the prevention of human pathologies?. Biomed. Pharmacother. 2002; 56(4): 200–207. Publisher Full Text\n\nNagaoka T, Banskota AH, Tezuka Y, et al.: Selective antiproliferative activity of caffeic acid phenethyl ester analogues on highly liver-Metastatic murine colon 26-L5 carcinoma cell line. Bioorg. Med. Chem. 2002; 10(10): 3351–3359. PubMed Abstract \| Publisher Full Text\n\nPapathoma AS, Zoumpourlis V, Balmain A, et al.: Suppression of cell transformation and induction of apoptosis by caffeic acid phenethyl ester. Mol. Carcinog. 2001; 31(2): 83–89. Publisher Full Text\n\nEtzenhouser B, Hansch C, Kapur S, et al.: Mechanism of toxicity of esters of caffeic and dihydrocaffeic acids. Bioorg. Med. Chem. 2001; 9(1): 199–209. PubMed Abstract \| Publisher Full Text\n\nAkao Y, Maruyama H, Matsumoto K, et al.: Cell growth inhibitory effect of cinnamic acid derivatives from propolis on human tumor cell lines. Biol. Pharm. Bull. 2003; 26(7): 1057–1059. PubMed Abstract \| Publisher Full Text\n\nSilva EAJ, Estevam EBB, Silva TS, et al.: Antibacterial and antiproliferative activities of the fresh leaf essential oil of Psidium guajava L. (Myrtaceae). Braz. J. Biol. 2019; 79(4): 697–702. PubMed Abstract \| Publisher Full Text\n\nFernandes CC, Rezende JL, Silva EAJ, et al.: Chemical composition and biological activities of essential oil from flowers of Psidium guajava (Myrtaceae). Braz. J. Biol. 2021; 81(3): 728–736. PubMed Abstract \| Publisher Full Text\n\nLing T, Lang WH, Maier J, et al.: Cytostatic and Cytotoxic Natural Products against Cancer Cell Models. Molecules. 2019 May 26; 24(10): 2012. PubMed Abstract \| Publisher Full Text\n\nAmarante MK, Watanabe MA, Conchon-Costa I, et al.: The effect of propolis on CCL5 and IFN-γ expression by peripheral blood mononuclear cells from leishmaniasis patients. J. Pharm. Pharmacol. 2012 Jan; 64(1): 154–160. PubMed Abstract \| Publisher Full Text\n\nDos Santos Thomazelli APF, Tomiotto-Pellissier F, da Silva SS , et al.: Brazilian propolis promotes immunomodulation on human cells from American Tegumentar Leishmaniasis patients and healthy donors infected with L. braziliensis. Cell. Immunol. 2017 Jan; 311: 22–27. PubMed Abstract \| Publisher Full Text\n\nConte FL, Santiago KB, Conti BJ, et al.: Propolis from southeastern Brazil produced by Apis mellifera affects innate immunity by modulating cell marker expression, cytokine production and intracellular pathways in human monocytes. J. Pharm. Pharmacol. 2021 Mar 4; 73(2): 135–144. PubMed Abstract \| Publisher Full Text\n\nGoverna P, Cusi MG, Borgonetti V, et al.: Beyond the Biological Effect of a Chemically Characterized Poplar Propolis: Antibacterial and Antiviral Activity and Comparison with Flurbiprofen in Cytokines Release by LPS-Stimulated Human Mononuclear Cells. Biomedicines. 2019 Sep 21; 7(4): 73. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMillones Gómez P: Cytotoxicity database. Mendeley Data. 2022; V1. Publisher Full Text\n\nTjørve KMC, Tjørve E: The use of Gompertz models in growth analyses, and new Gompertz-model approach: An addition to the Unified-Richards family. PLoS One. 2017 Jun 5; 12(6): e0178691. PubMed Abstract \| Publisher Full Text" }	[ { "id": "135716", "date": "23 May 2022", "name": "Tania Valentina Rosales Cifuentes", "expertise": [ "Reviewer Expertise Natural products and microbiology" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nTitle: Its title is adequate, it consigns the most interesting part of the study referred to the cytotoxicity of propolis, using scientific terms keeping the coherence and sufficiency of the article's content.\nSummary: Although it is true that natural products are beneficial, there are few studies that mention the safety of the clinical use of the product. The article emphasizes the importance of knowledge of cell toxicity with a clear and precise explanation of the adequate concentration to avoid the cytotoxic effect.\nContent: The methods section is well explained, the cytotoxic assay of this study establishes which was the adequate procedure that provided the percentage of safe and reliable cell viability, being coherent with the results in Figure 1. I consider that establishing the detailed procedure as it is done in this study is important so that it is reproducible in future studies of regenerative medicine or tissue engineering.\nIntroduction: I appreciate the effort of the background search and its respective analysis, the introduction is very good, it makes a brief summary of the background making reference to the relevant medical literature, in the last paragraph it mentions the safety of the use of propolis without deterioration of the cells, I suggest, so that the reader can make a comparison and as interesting reading, to cite references 27 and 30, which are similar studies.\nResults: The results of this study are accurate, achieving the objective to avoid cytotoxicity in human cell lines, recognizing that the effect is dose-dependent. Based on the experience of the researchers evidenced in previous publications, it can be observed that a line of research continues in search of new active principles that can offer a promising pharmacological product based on natural products. Although it is true that this is a preliminary study as indicated by the authors, it is important to point out that future research could consider procedures based on flow cytometry to corroborate the results obtained in the present study.\nDiscussion: The background information showed the therapeutic benefits of natural products, with propolis standing out from the two products, for its antimicrobial, anti-inflammatory and antioxidant effects, among others; however, complementary studies are required to verify its safety in clinical use. The article specifies its strengths and limitations by mentioning which is the ideal concentration to avoid cytotoxicity and that the extracts of Peruvian propolis and guava at lower concentrations can work safely in the fibroblast cell line; however, the authors recognize that since this is an in vitro assay, this value may vary if other types of cell lines are used, making a discussion with other studies carried out; they also suggest that both products could present a modulating action on the immune response, opening perspectives for future research in this field.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "144832", "date": "09 Aug 2022", "name": "Orlando Torres Garcia", "expertise": [ "Reviewer Expertise Immunology and Immunogenetics", "microbiology." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this article, the authors evaluated the cytotoxic effect of ethanolic extracts of propolis and P. guajava on HELA cell lines, human gingival fibroblasts (HGF-1), and peripheral blood mononuclear cells (PBMC), finding cell viability more significant than 90% at concentrations equal to or less than 0.24 mg/mL and 0.024 mg/mL for EEG and EPP, respectively. Within this perspective, the authors infer potential applications in medicine and dentistry.\nMain comments:\nIn the study methodology, the authors use the HELA cell lines, human gingival fibroblasts (HGF-1), and peripheral blood mononuclear cells (PBMC); however, the reason for their selection they not mentioned in the text. I suggest the authors include some selection criteria for these cell lines used in work.\n\nTo determine the cytotoxicity, the authors use the ethanolic extracts of propolis and P. guajava at the concentration range of 0.024 to 50 mg/mL. What were the selection criteria for this range of concentrations?\n\nAlthough the document achieves the objective of determining the highest concentrations of the two ethanolic extracts at which cell viabilities more significant than 90% are observed, it would also be interesting to calculate the IC50 of each extract on each cell line.\nMinor comment:\nIn the last paragraph of the discussion, the authors state that their preliminary data suggest that both products could have a modulating action on the immune response. I suggest rethinking this inference because within the document's text, and mainly, neither in the objective nor in the methodology, and even less in the results, are not elements that allow this insinuation in the present study.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8636", "date": "24 Aug 2022", "name": "Pablo Millones Gómez", "role": "Author Response", "response": "In the study methodology, the authors use the HELA cell lines, human gingival fibroblasts (HGF-1), and peripheral blood mononuclear cells (PBMC); however, the reason for their selection they not mentioned in the text. I suggest the authors include some selection criteria for these cell lines used in work. We appreciate the reviewer's comments, the requested criteria were added to the methodology section. To determine the cytotoxicity, the authors use the ethanolic extracts of propolis and P. guajava at the concentration range of 0.024 to 50 mg/mL. What were the selection criteria for this range of concentrations? We appreciate the reviewer's comments, the requested information has been added. Although the document achieves the objective of determining the highest concentrations of the two ethanolic extracts at which cell viabilities more significant than 90% are observed, it would also be interesting to calculate the IC50 of each extract on each cell line. We appreciate the reviewer's comments. Although the IC50 is used in many cytotoxicity studies, the authors decided to use the criteria of Poggio et al. because we seek to continue with studies in the oral cavity. In the last paragraph of the discussion, the authors state that their preliminary data suggest that both products could have a modulating action on the immune response. I suggest rethinking this inference because within the document's text, and mainly, neither in the objective nor in the methodology, and even less in the results, are not elements that allow this insinuation in the present study. We appreciate the reviewer's comments. Changes were made within the last paragraph of the discussion." } ] } ]	1	https://f1000research.com/articles/11-430
https://f1000research.com/articles/11-935/v1	15 Aug 22	{ "type": "Research Article", "title": "Behaviour test in chronic brain ischemia rats: A bibliometric approach", "authors": [ "Tiwuk Susantiningsih", "Feda Makkiyah", "Maria Selvester Thadeus", "Tuty Rizkianti", "Hikmah Muktamiroh", "Muttia Amalia", "Yuni Setyaningsih", "Mila Citrawati", "Cut Fauziah", "Meiskha Bahar", "Aulia Chairani", "Yanti Harjono", "Agneta Irmarahayu", "Sri Wahyuningsih", "Fajriati Zulfa", "Tiwuk Susantiningsih", "Maria Selvester Thadeus", "Tuty Rizkianti", "Hikmah Muktamiroh", "Muttia Amalia", "Yuni Setyaningsih", "Mila Citrawati", "Cut Fauziah", "Meiskha Bahar", "Aulia Chairani", "Yanti Harjono", "Agneta Irmarahayu", "Sri Wahyuningsih", "Fajriati Zulfa" ], "abstract": "Background: Stroke causes severe disability and mortality. Despite the fact that the pathology of acute stroke is well understood, publication on chronic stroke is still limited. Because scarring of glia limits the recovery area of acute stroke and reorganization capacity is reduced, discovering new treatments for chronic stroke poses substantial obstacles. In stroke research, rodent models are commonly utilized, and behavior testing is a crucial tool. To measure stroke outcomes and translating rodent findings to therapeutic trials, selecting relevant behavioral tests that fit the study purpose is critical. Here, we aimed to look at the last decade’s publications highlighting behaviour tests on chronic stroke rats. Hopefully, we were able to give more information about the behaviour tests to facilitate the researchers’ choice of appropriate test. Methods: By using a bibliometric analysis, we hope to systematically discuss rodent behavior tests in chronic stroke research. Documents were extracted from the Scopus database in April 2022. Excel and VOSviewer 1.6.18 were used to conduct statistical and graphical analysis. Results: Research on \"behavioral test in chronic stroke rats\" has progressed quickly, although the researchers have yet to collaborate with each other. H. Millani was an active researcher and author who connected numerous researchers, according to documents and citation analysis. “Animals”, “brain ischemia”, “man”, “publication”, and “animal experiment” were all common keywords. The majority of the articles were from the United States and China. The Morris Water Maze test and the cylinder test were the most commonly used behavior tests. Conclusions Clinical applications and therapeutic effectiveness against stroke could be improved with more collaboration amongst authors. When using a behavior test, researchers need to think about which neurological deficiency is being addressed and whether the test covers long-term evaluation.", "keywords": [ "Bibliometric analysis", "Scopus", "Stroke", "chronic", "behaviour test", "rats" ], "content": "Introduction\n\nStroke causes severe disability and mortality. Moreover, stroke is considered the number one cause of disabilty and independency (Katan and Luft, 2018). Acute and subacute strokes have been targeted with medicines provided within 48 hours after onset, thanks to recent breakthroughs in stroke treatment. Thrombus breakdown using a tissue-type plasminogen activator (e.g, alteplase) within 4.5 hours of stroke onset or mechanical thrombectomy within six hours are two current treatment options. Both of these treatments, however, are only appropriate for a tiny percentage of patients, and not all of them work well (Wardlaw et al., 2014).\n\nDespite the fact that the mechanism of acute stroke is widely recognized, publication on chronic stroke is still limited. Because glial scars mark the location of brain injury and the capacity for reorganization may be substantially reduced, finding new treatments for chronic stroke poses significant challenges. In recent investigations, a paracrine effect has been proposed as a mechanism for improving recovery, implying that when surviving, neurons surrounding the infarction are adequately activated, and have the ability to change function in ways that improve brain function. Replacement of destroyed brain tissue and restoration of missing connections may be necessary for greater improvement and maybe complete recovery. This would necessitate the replacement of neuron, endothelial cells, astrocytes, and supportive cells. Some of these challenges are currently being investigated in animal models, with the expectation of progressing rapidly toward the objective of finding viable treatments for chronic stroke patients (Wechsler et al., 2018).\n\nIn stroke research, rodent models are commonly utilized and behavior testing is a crucial tool (Saré et al., 2021). Rodents have various advantages over other species, including quick reproduction, minimal maintenance costs, and more ethical acceptance (Ruan and Yao, 2020). However, rats and humans have quite different neurological behaviors and higher brain processes. Rodents, for example, may only perform tasks that imitate their natural responses, whereas human patients can have their neurological processes tested by answering questions and following directions. This makes determining the outcome of a stroke, particularly in terms of cognitive function and consciousness, problematic.\n\nIn measuring stroke outcome and translating rodent findings to therapeutic trials, selecting relevant behavioral tests that fit the study purpose is critical. Although 30-minute temporary middle cerebral artery occlusion (30-min tMCAO) generates consistent infarct in subcortical areas of rats’ brains, the behavioral tests such as the rotarod test, adhesive-removal test, or narrow beam test make it difficult to assess the subsequent neurological loss. The development of a quantitative evaluation method would aid in the development of a unique cerebral infarction therapy approach (Wakayama et al., 2007).\n\nHere, we’ll look at some of the recent publications that have focused on behavior testing in chronic stroke patients. Hopefully, we were able to provide additional information regarding the behavior test, allowing researchers to select the best test for their needs. A bibliometric analysis was used to examine global collaboration patterns, patterns in institutions and countries, as well as to determine trends in studies.\n\n\nMethods\n\nThe Scopus database was searched using the terms “behavior test” and “rats”, as follows: (ALL (“behaviour test”) OR TITLE-ABS-KEY (“behavioural outcomes”) AND TITLE-ABS-KEY (rats) OR TITLE-ABS-KEY (rodents) AND TITLE-ABS-KEY (“brain ischemia”) AND TITLE-ABS-KEY (chronic) OR TITLE-ABS-KEY (“chronic ischemic stroke”)). A total of eighteen papers were collected and analyzed bibliometrically.\n\nTo begin, Scopus search and retrieval results were used to examine the general information of the literature, which included the publication year, country of origin, organization, journal, and author. Following that, bibliometric and visual analysis were performed using the VOS viewer 1.6.18 software open source (https://www.vosviewer.com), including primary author, keyword, collaboration link, citation analysis, and co-citation analysis.\n\n\nResults\n\nFrom 1996 to 2022, the Scopus database contained 18 entries relating to “behaviour test in chronic stroke rats”. Three articles were excluded (Macaca article, a Chinese article we were unable to translate, mice-related articles). Figure 1A illustrates the annual publication trend. In 1996, there was only one publication, which then gradually increased year after year until it peaked in 2021 (four publications). The study “behaviour test in chronic stroke rats” received funding from 23 different sources. The National Natural Science Foundation of China (frequency: 4), the National Institute of Neurological Disorders and Stroke (frequency: 3), and the National Institutes of Health (frequency: 2) were the top three primary funding sources (frequency: 3) (Figure 1B).\n\nIn the 18 papers on “behaviour test in chronic stroke rats” that have been published so far, 12 nations and 49 organizations were identified. The top three countries/regions were China, the USA, and Brazil (Table 1 and Figure 2). With 99 citations, the USA led the pack, followed by Brazil with 63 and China with 52. With two papers and 62 citations, the Department of Neurology at the University of Texas at Houston Medical School in Houston, Texas, was the most productive (Table 1). There were six organizations that collaborated with each other during the publication and other organizations published by their own resource (Figure 3).\n\nA. Six-organizations connected to each other. B. Other organizations that worked alone for their publication.\n\nThe term “behavior test in chronic brain stroke of rats” was found in 14 journals. Table 2 shows that the top three journals published the same article multiple times. Behavioural Brain Research and Brain Research were the most popular journals. The JCR partitioning in all of the journals was higher (Q1 and Q2).\n\nIn “behavior test in chronic stroke rats,” 96 authors contributed to 18 papers. Milani H placed first (63 citations) with two papers, followed by J Aronowski, J. C Grotta, and R Strong (Figure 4A). The study “behaviour test in chronic stroke rats” had Milani H as the lead author. Figure 4B illustrates that collaboration amongst active authors in this subject is still lacking.\n\nA. Authors that collaborated in publications. B. Other authors that published independently.\n\nThe circle size denotes the number of occurrences of phrases in the subnetwork of keywords and graph, as shown in Figure 5. The top ten keywords were “animals”, “brain ischemia”, “male”, “article”, “animal experiment”, “animal model”, “rats”, “controlled study”, “animal behaviour”, “animal tissue” (Figure 5A). In the overlaid visualization (Figure 5B), the keywords “animal behaviour” were related to “middle cerebral artery occlusion”, “brain ischemia”, “cognitive function” and “sensorimotor function”. Figure 5C shows the keyword connected with cognitive dysfunction such as “tumor necrosis factor”, “metabolism”, and “inflammation”.\n\nA. The top ten keywords were “animals”, “brain ischemia”, “male”, “article”, “animal experiment”, “animal model”, “rats”, “controlled study”, “animal behaviour”, “animal tissue”. B. Keyword related animal behaviour. C. Keyword related cognitive function.\n\nThe most used test in the articles was the Morris Water Maze (Dhaliwal et al., 2021; Hei et al., 2018; Yao et al., 2021; Yan et al., 2021) and the second was the cylinder test (Huang et al., 2018; Lipsanen et al., 2011; Loris et al., 2017; Shaafi et al., 2019). Beam walking test (Lipsanen et al., 2011; Wang et al., 2021), forced swim test (FST), elevated zero maze (EZM), open field (OF), and object location test (OLT) (Soares et al., 2016) were also encountered (Table 3).\n\nThe Morris Water Maze (MWM) test was used in the majority of cases, with the cylinder test coming in second.\n\n\nDiscussion\n\nStroke causes long-term impairment that is sometimes accompanied by debilitating deficits, necessitating immediate treatment. Stroke patients commonly experience motor, sensory, and cognitive impairments, but therapeutic options are limited. Functional results in animal models, in addition to histology measurements, have provided vital information into the molecular basis of experimental stroke and future rehabilitation initiatives. Expanding the development of translational medicines necessitates the creation and use of tests that can identify behavioral impairments.\n\nSelecting relevant behavioral measures that meet the study goal is crucial when monitoring stroke outcome and transferring rodent findings into treatment trials. Although a 30-minute tMCAo generates consistent infarct in subcortical area in rats, behavioural tests like the rotarod test, adhesive-removal test, or narrow beam test make measuring the ensuing neurological damage difficult. The development of a new cerebral infarction therapy technique would benefit from the development of a quantitative evaluation method (Wakayama et al., 2007).\n\nChoosing the appropriate behaviour test in chronic stroke research is difficult since rats’ brains recover well, and even though infarct pathology still exists, behaviour test findings are comparable to normal rats. This is the component about which researchers should ponder long and hard before beginning their study. It’s crucial to use tests that are able to detect the neurological deficits to the injury to the brain and the treatments used. Due to the loss of limb function following a stroke, many tests focus on motor and sensory testing (Lipsanen et al., 2011; Makkiyah et al., 2021; Sun et al., 2016; Wakayama et al., 2007). Because learning and memory problems are frequent after a stroke, cognitive testing is particularly important for determining the full extent of the difficulties (Barros et al., 2009; Dhaliwal et al., 2021; Hei et al., 2018; Yao et al., 2021). As a result, it’s critical to have sensitive behavioural approaches for detecting the wide range of deficits that might arise after a stroke. By recording functional improvements over time, behavioral assessments can also be used to measure the efficiency of pharmacological and cell-replacement treatments.\n\nSince 1996, researchers have been using behaviour tests in chronic stroke patients, with a peak occurring in 2021. The literature was dominated by research from countries like the USA and China. In other areas of stroke research, such as the involvement of ferroptosis in stroke, a similar pattern emerged (Chen et al., 2021).\n\nThe MWM test, which is the most common test implemented in the literature has some limitations. It may be difficult to distinguish between a merely cognitive deficit and a possible sensorimotor insufficiency in tMCAO rats because of the unilateral ischemia impairment. There was no significant variation in swim speed or path length during the probing session, indicating that abilitity to swim did not have a role in the cognitive function deficit shown in tMCAO animals. As a result, while the water maze techniques used may provide useful assays for the efficacy of therapeutic interventions targeting the striatum area, other behavioural tests may be more appropriate for measuring rescue area or recovery in injured neocortex areas (Bingham et al., 2012).\n\nSensorimotor asymmetry is one of the most common signs of stroke, and it can be measured using a variety of behavioural tests, including cylinder test. After a central nervous system injury, the cylinder test was initially used to measure spontaneous forelimb motor performance. It has been used in many publications in research related to behaviour tests in chronic stroke rats (Barros et al., 2009; Huang et al., 2018; Lipsanen et al., 2011; Loris et al., 2017; Makkiyah et al., 2021; Shaafi et al., 2019). The cylinder task has been shown to be objective, simple to use and score, sensitive to chronic issues that other tests overlook, and has strong inter-rater reliability. Furthermore, no prior training is necessary, albeit baseline data is required to assess for pre-operative bias because some animals exhibit independent use of one limb on occasion (Schaar et al., 2010).\n\nAlthough this is the first bibliometric analysis of “behavior test in chronic stroke rats,” it does have some limitations.\n\nTo begin with, the retrieval date was 26 April, 2022, but the database is still being updated. There should be more coming articles after that retrieval date. Secondly, the Scopus database’s search phrases (ALL (“behavior test”) OR TITLE-ABS-KEY (“behavioural outcomes”) AND TITLE-ABS-KEY (rats) OR TITLE-ABS-KEY (rodents) AND TITLE-ABS-KEY (“brain ischemia”) AND TITLE-ABS-KEY (chronic) OR TITLE-ABS-KEY (“chronic ischemic stroke”) were utilized. There might be some articles that were not included with searching using different keywords. However, because Scopus is the most widely used database for bibliometric research, we feel our study represents the global situation and general trend for bibliometric analysis.\n\n\nConclusions\n\nClinical applications and therapeutic effectiveness against stroke could be improved with more collaboration amongst authors. When using a behavior test, researchers need to think about which neurological deficiency is being addressed and whether the test covers long-term evaluation.\n\n\nData (and Software) availability\n\nFigshare: bibliometric results of behaviour tests of chronic brain rats ischemia.xlsx, https://doi.org/10.6084/m9.figshare.19911172.v1 (Makkiyah and Susantiningsih, 2022).\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nAuthor contributions\n\nConceptualization: FD, TS, HM. Data collection and analysis: AI, MC. MA-formal analysis. CB, MB, AC, YH, AI, SW, FZ. methodology. Writing—original draft: YS, TR. Writing—review and editing: MST.", "appendix": "References\n\nBarros CA, Ekuni R, Moro MA, et al.: The cognitive and histopathological effects of chronic 4-vessel occlusion in rats depend on the set of vessels occluded and the age of the animals. Behav. Brain Res. 2009; 197(2): 378–387. PubMed Abstract \| Publisher Full Text\n\nBingham D, Martin SJ, Macrae IM, et al.: Watermaze performance after middle cerebral artery occlusion in the rat: The role of sensorimotor versus memory impairments. J. Cereb. Blood Flow Metab. 2012; 32(6): 989–999. PubMed Abstract \| Publisher Full Text\n\nChen Y, Long T, Xu Q, et al.: Bibliometric analysis of ferroptosis in stroke from 2013 to 2021. Front. Pharmacol. 2021; 12: 4132. Publisher Full Text\n\nDhaliwal N, Dhaliwal J, Singh A, et al.: Dimethyl fumarate attenuates 2-VO-induced vascular dementia via activating the Nrf2 signaling pathway in rats. Inflammopharmacology. 2021; 29(2): 537–547. PubMed Abstract \| Publisher Full Text\n\nHei Y, Chen R, Yi X, et al.: HMGB1 neutralization attenuates hippocampal neuronal death and cognitive impairment in rats with chronic cerebral hypoperfusion via suppressing inflammatory responses and oxidative stress. Neuroscience. 2018; 383: 150–159. PubMed Abstract \| Publisher Full Text\n\nHuang L, Lu J, Cerqueira B, et al.: Chronic oral methylene blue treatment in a rat model of focal cerebral ischemia/reperfusion. Brain Res. 2018; 1678: 322–329. PubMed Abstract \| Publisher Full Text\n\nKatan M, Luft A: Global Burden of Stroke. Global burden of stroke. 2018; 38(02): 208–211. Publisher Full Text\n\nLipsanen A, Hiltunen M, Jolkkonen J: Chronic ibuprofen treatment does not affect the secondary pathology in the thalamus or improve behavioral outcome in middle cerebral artery occlusion rats. Pharmacol. Biochem. Behav. 2011; 99(3): 468–474. Publisher Full Text\n\nLoris ZB, Pieper AA, Dietrich WD: The neuroprotective compound P7C3-A20 promotes neurogenesis and improves cognitive function after ischemic stroke. Exp. Neurol. 2017; 290: 63–73. PubMed Abstract \| Publisher Full Text\n\nMakkiyah F, Sadewo W, Nurrizka R: Comparative Dose of Intracarotid Autologous Bone Marrow Mononuclear Therapy in Chronic Ischemic Stroke in Rats. Open Access Macedonian Journal of Medical Sciences. 2021; 9(A): 233–243. Publisher Full Text\n\nMakkiyah F, Susantiningsih T: bibliometric results of behaviour tests of chronic brain rats ischemia.xlsx. figshare. Dataset. 2022. Publisher Full Text\n\nRewell SS, Churilov L, Sidon TK, et al.: Evolution of ischemic damage and behavioural deficit over 6 months after MCAo in the rat: Selecting the optimal outcomes and statistical power for multi-centre preclinical trials. PLoS One. 2017; 12(2): e0171688. PubMed Abstract \| Publisher Full Text\n\nRuan J, Yao Y: Behavioral tests in rodent models of stroke. Brain Hemorrhages. 2020; 1(4): 171–184. Publisher Full Text\n\nSaré RM, Lemons A, Smith CB: Behavior Testing in Rodents: Highlighting Potential Confounds Affecting Variability and Reproducibility. Brain Sci. 2021; 11(4): 522. PubMed Abstract \| Publisher Full Text\n\nSchaar KL, Brenneman MM, Savitz SI: Functional assessments in the rodent stroke model. Exp. Transl. Stroke Med. 2010; 2(1): 1–11. Publisher Full Text\n\nShaafi S, Sharifi-Bonab M, Ghaemian N, et al.: Early motor-behavioral outcome of ischemic stroke with ketogenic diet preconditioning: Interventional animal study. J. Stroke Cerebrovasc. Dis. 2019; 28(4): 1032–1039. PubMed Abstract \| Publisher Full Text\n\nSoares LM, De Vry J, Steinbusch HW, et al.: Rolipram improves cognition, reduces anxiety-and despair-like behaviors and impacts hippocampal neuroplasticity after transient global cerebral ischemia. Neuroscience. 2016; 326: 69–83. PubMed Abstract \| Publisher Full Text\n\nSun X, Zhou Z, Liu T, et al.: Fluoxetine enhances neurogenesis in aged rats with cortical infarcts, but this is not reflected in a behavioral recovery. J. Mol. Neurosci. 2016; 58(2): 233–242. Publisher Full Text\n\nWakayama K, Shimamura M, Sata M, et al.: Quantitative measurement of neurological deficit after mild (30 min) transient middle cerebral artery occlusion in rats. Brain Res. 2007; 1130: 181–187. PubMed Abstract \| Publisher Full Text\n\nWang A, Mi L, Zhang Z, et al.: Saikosaponin A improved depression-like behavior and inhibited hippocampal neuronal apoptosis after cerebral ischemia through p-CREB/BDNF pathway. Behav. Brain Res. 2021; 403: 113138. PubMed Abstract \| Publisher Full Text\n\nWardlaw JM, Murray V, Berge E, et al.: Thrombolysis for acute ischaemic stroke. Cochrane Database Syst. Rev. 2014; 7. Publisher Full Text\n\nWechsler LR, Bates D, Stroemer P, et al.: Cell therapy for chronic stroke. Stroke. 2018; 49(5): 1066–1074. Publisher Full Text\n\nYan N, Xu Z, Qu C, et al.: Dimethyl fumarate improves cognitive deficits in chronic cerebral hypoperfusion rats by alleviating inflammation, oxidative stress, and ferroptosis via NRF2/ARE/NF-κB signal pathway. Int. Immunopharmacol. 2021; 98: 107844. Publisher Full Text\n\nYao Z-H, Wang J, Yuan J-P, et al.: EGB761 ameliorates chronic cerebral hypoperfusion-induced cognitive dysfunction and synaptic plasticity impairment. Aging (Albany NY). 2021; 13(7): 9522–9541. PubMed Abstract \| Publisher Full Text" }	[ { "id": "147593", "date": "30 Aug 2022", "name": "Robert Sinurat", "expertise": [ "Reviewer Expertise Neurosurgery", "stem cell for stroke", "spinal diseases." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors analyzed the behavior test in chronic brain ischemic of rat models by a bibliometric approach. The authors have obtained how many articles were published in 1996 - 2022, who and from what country the author was, and how many times each article was cited by another author. The study is interesting, but the authors need to revise the manuscript.\n\nAlteplase and thrombectomy are treatment for ischemic stroke, not for hemorrhagic stroke. The authors cited from an older article about the outcome of the treatment (Wardlaw et al, 2014). It would be better to reveal the outcome of the procedures from more recent articles, such as research reported by Katherin T Mun(2022) title: Fragility index meta analysis of randomized controlled trials shows highly robust evidential strength for benefit of < 3 hours intravenous alteplase1.\n\nThe purpose of this study is the authors want to add information about the behavior test through bibliometric analysis, but it was not explained in detail what kind of information will be expected to be obtained through the results of this study.\nThe authors searched the articles from the Scopus database, and the number of articles obtained was eighteen papers. The authors are required to explain why they are limiting the source to only the Scopus database. If the sources were expanded the number of articles that can be analyzed will be raised.\n\nThe authors need to enlarge the text in the figures and improve the discussion section by interpreting each point of the results of the bibliometric analysis obtained from this study. It would be nice if the authors could use simpler sentences to make it easier to understand. For examples, the authors maybe can explain why the majority of the articles are from USA and China, why the MWM test was widely used, and how the results of this study helping the researchers to choose the kind of behavior test for their future study.\n\nThe authors need to conclude this study according to the results of their bibliometric analysis, and convey considerations for other prospective researchers on which test is more appropriate to use for research in chronic ischemic stroke rat models.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "239673", "date": "25 May 2024", "name": "Federica Marchiotto", "expertise": [ "Reviewer Expertise Neuroscience. I'm not an expert of bibliometric approaches", "so I'm able to assess only parts of this article." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article is about a bibliometric analysis on the most commonly used chronic stroke behavioral tests in rats. The authors show at first the published articles per year, the country of origin of the authors, the journals in which the articles have been published and the citations (to investigate if an author is comparing more times). Then, they analysed the tests and the MWM and the cylinder test resulted to be the most used tests. Milani H. is an active researcher in the field.\nThe conclusions are quite disconnected from the results, or, better, they are not following the findings.\nMoreover, the aim reported in the abstract is meaningly different from the aim written at the end of the introduction and from the discussion. This does not allow the reader to really understand the point of the article.\nThe cited behavioral tests are not explained: it is not explained the aim of these tests and why they are implied in the evaluation of chronic stroke behavioral impairments.\nIn general, the article is well structured and the figures, with their legends, are clear.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-935
https://f1000research.com/articles/11-931/v1	12 Aug 22	{ "type": "Research Article", "title": "Mathematical model analysis and numerical simulation of intervention strategies to reduce transmission and re-activation of hepatitis B disease", "authors": [ "Firaol Asfaw Wodajo", "Temesgen Tibebu Mekonnen", "Temesgen Tibebu Mekonnen" ], "abstract": "Background: Because of its asymptomatic nature, the Hepatitis B Virus (HBV) has become the most lethal and silent killer. In this research, we offer HBV virus transmission characteristics in the form of a mathematical model. We suggested and examined a seven-compartment compartmental nonlinear deterministic mathematical model for transmission dynamics with immigration and HBV reactivation after recovery, as well as control measures for Hepatitis B virus disease transmission. By considering the following facts and cases, this work will provide new knowledge. First, re-infection of HBV after liver transplantation, chemotherapy, and other therapies is one of the most essential aspects in HBV transmission, although reactivation of HBV was not taken into account in some compartmental models of HBV transmission. Furthermore, the exposure rate, immigration rate, and level of infectiousness of the chronic infective class were not given enough weight in the numerical assessment of the force of HBV infection. These facts influenced the development of our model. Methods: We demonstrated that the solution of the dynamical system under consideration is positive and bounded. The effective reproductive number that represents the epidemic indicator is generated from the biggest eigenvalue of the netgeneration matrix, and the model is examined qualitatively using differential equation stability theory. For disease-free and endemic equilibria, both local and global asymptotic stability criteria are determined. Results: A full explanation of the parameters and their numerical findings is presented and debated well based on the numerical simulation. Conclusions: According to the findings of this study, vaccination and treatment interventions play a critical role in reducing HBV transmission and reproduction. It has also been demonstrated that HBV reactivation contributes significantly to an increase in theinfective population, which boosts virus transmission, and that a combination of vaccination and treatment will be the most effective strategy for controlling HBV infection and reinfection after recovery.", "keywords": [ "Hepatitis B", "Effective reproduction number", "Global Stability", "Numerical Simulation" ], "content": "Introduction\n\nThe hepatitis B virus causes hepatitis B, an infectious disease that affects the liver (HBV). It is spread through contact with infectious blood, sperm, and other bodily fluids.1 Furthermore, it can be passed on from infected women to their infants at the moment of birth, or from family members to their children in early childhood.2 Because it is asymptomatic by nature, it develops complicated and can lead to chronic liver disease. People in this chronic stage are at a significant risk of dying from liver cirrhosis and cancer. Hepatitis B, on the other hand, is a liver infection caused by the HBV that can be prevented with a vaccine.3\n\nFor numerous decades, experts have paid close attention to the study of the hepatitis B virus. One of the reasons for this close scrutiny is a strong desire to learn everything there is to know about this lifethreatening virus and how it spreads and spreads. Risk of HBV also goes to healthcare workers who sustain accidental needle-stick injuries while caring for HBV infected people.4 Although it is asymptomatic and have ten times mode of transmission than HIV/AIDS, asafe and effective vaccine is available to prevent HBV infection.5 Another feature of HBV disease is that it might reactivate after malignancy, autoimmune disease, or organ transplantation immunosuppressive medication.\n\nIn the study of virus dynamics, mathematical modeling has proven to be the most effective method for understanding biological mechanisms and interpreting experimental results. To better understand the dynamics of HIV, HBV, and other virus infections, an early mathematical model for the basic dynamics of virus in vivo was devised and examined.6 Hepatitis B is a serious liver illness caused by the HBV, which is a major worldwide medical problem and the most frequent kind of viral hepatitis. It is found only in Asia and Africa.7 Around the world, around two billion people are asymptomatic or symptomatic of the virus, and approximately 360 million have the most severe infection.8\n\nIn 1990, 154 million people, or 2.9 percent of the global population, were migrants; however, the figure for 2013 was 3.2 percent,9 and these figures do not include undocumented migrants.\n\nThe United States, Canada, and a few other EU countries were among the top ten destinations for international migrants in 2013.10\n\nAccording to research on some African migrants in the United States, the proportion of people infected with HBV is ten times that of the host population. This is most likely due to a mix of factors, including a lack of understanding of diseases, risk factors, and symptoms, as well as a lack of access to healthcare and health information. According to studies, workers and displaced persons are 25 times more likely to die from liver disease than the general population.11,12 proposed a mathematical model for hepatitis B with migration. According to the findings, rigorous immigration rules such as screening and limiting the number of immigrants allowed into a given population could help curb the spread of the disease.\n\nReference 13 also analyzed the state of the art in modeling and anazing data received from hepatitis B virus infected individuals treated with antiviral medications. With more understanding and quantitative methods, it will be easier to test new medicines for antiviral and immune-modulating effects, and viral kinetic studies may eventually be used to predict long-term patient responses.12 Investigated the role of infectious immigrant epidemic models and immunization on disease patterns. This straightforward configuration takes into account the likelihood of acquired immunity with a focus on SIR and SIS models Class has been immunized.\n\nOne of the main goals of research into hepatitis B virus (HBV) infection is to enhance control and, eventually, eliminate the infection from the community. Mathematical models can be an effective tool in this strategy, allowing us to optimize the use of finite resources or simply to improve the effectiveness of infection control methods. To demonstrate the effects of climate change, Anderson and May employed a simple mathematical model.14 Reference 15 created mathematical models of HBV transmission dynamics and optimal vaccination and treatment control for both vertical and horizontal HBV transmission. However, they failed to account formigration effect and HBV reactivation following recovery and re-infection of the recovered group. In this study, we looked at re-infection, which occurs when previously healthy people get reinfected after undergoing liver transplantation and chemotherapy and are exposed to HBV and migration of population which is currently becoming harsh in increasing number of infected population of infectious disease in ones country.\n\n\nMathematical model formulation and assumptions\n\nSusceptible S(t), Vaccinated V(t), Exposed E(t), Acutely infected A(t), Chronically infected C(t), Treated T(t), and Recovered R are the seven compartments that the total population N(t) is divided into based on the epidemiological status of individuals.\n\ni) Recruitment into the population is either by birth or immigration.\n\nii) certain percentage of newborns and immigrants in the population were immunized against HBV infection at birth\n\niii) we considered loss of immunity in the case of vaccinated population\n\niv) force of infection incorporates contact rate, Probability of acquiring HBV infectious per contact with one infectious individual, and Level of infectiousness of chronically infected population.\n\nv) We considered re-activation of HBV after transplantation and chemotherapy.\n\nvi) Acutely infected individuals have probability to recover from HBV by natural immunity.\n\nvii) Disease induced death rate is assumed in chronically infected individuals.\n\nviii) The mixing in this model is homogeneous, that is, all susceptible individuals are equally likely to be infected by infectious individuals in case of contact.\n\nix) People in each compartment have equal natural death rate of μ.\n\nx) Migration of individuals is also considered as one of the contributing factor for transmission of HBV.\n\n\nCorresponding compartmental diagram\n\n\n\n\nCorresponding dynamical system\n\n\n\n\nMathematical analysis of the model\n\nUnder this section, we will check the positivity, boundedness, and existence of the solution of the model.\n\nTheorem 1 (Positivity)\n\nLet the initial data for the model be S0>0,V0>0,E0>0,A0>0,C0>0,T0>0,R0>0. Then, the solutions St,Vt,Et,At,Ct,Tt and Rt of the model will be remaining positive for all time t>0.\n\nProof: Let S0>0,V0>0,E0>0,A0>0,C0>0,T0>0,R0>0. Also, we assume that all the parameters are positive. To show this, we take these differential equations of the dynamical system given above and show that their solutions are non-negative as follows.\n\n1. Let us take the first differential equation\n\nAfter simplification, we get:\n\nSince any exponential function with positive coefficients and S0 are both positive and 1−θπ+1−ψΛ+τV+εRμ+cωφC+AN is also positive, we can conclude that St>0.\n\n2. Let us consider the second ordinary differential equation dVdt=θπ+ψΛ−τV−μV.\n\nThis equation is in the form of dydt+pxy=qx which is first-order linear differential equation with integrating factor I.F=e∫τ+μdt=eτ+μt\n\nSolution of dydt+pxy=qx is given by:y=1I.F∫I.F×qxdx\n\nSo, the solution of dVdt+τ+μV=θπ+ψΛ is given by:\n\nSince V0 is positive, any exponential function with positive coefficient is positive and θπ+ψΛτ+μ is also positive, then we can conclude that Vt>0.\n\n3. Let us consider the third ordinary differential equation\n\nAfter computing and simplification, we get:\n\nSince E0 is positive, any exponential function has range of positive real number and their product is positive and cωφC+ANS+γcωφC+ANRμ+c1+c2 is also positive, then we can conclude that Et>0.\n\n4. Let us consider the fourth differential equation\n\nComputation and simplification gives us:\n\nSince A0 is positive, any exponential function with positive coefficient is positive and c2Eδ2α+δ1α+μ is also positive, then we can conclude that At>0.\n\n5. Let us consider the fifth ordinary differential equation\n\nAfter some steps, we get:\n\nSince C0 is positive, any exponential function with positive coefficient is positive and c1E+δ2αAμ+d+σ is also positive, then we can conclude that Ct>0.\n\n6. Let us consider the sixth ordinary differential equation\n\nSimplification after some step yields:\n\nSince T0 is positive and any exponential function with positive coefficient is positive and σCφ1+μ is also positive, then we can conclude that Tt>0.\n\n7. Let us consider the seventh ordinary differential equation\n\nAfter computation and simplification, we get:\n\nSince R0 is positive, any exponential function with positive coefficient is positive and φ1T+δ1αAγcωφC+AN+ε+μ is also positive, then we can conclude that Rt>0.\n\nThis completes the proof of the theorem. Therefore, the solution of the model is positive.\n\nTheorem 2 (Boundedness)\n\nTo show the boundedness of the solution, we have to show lower bound and upper bound. But, initially, N0=N0>0,S0=S0>0,V0=V0>0,E0=E0>0,A0=A0>0,C0=C0>0,T0=T0>0,R0=R0>0\n\nThese initial conditions are considered as lower bounds. Now, we are going to show the upper bound. By taking the relation\n\nand differentiating both sides of the equation with respect to time, we get:\n\nIn the absence of mortality due to Hepatitis B virus, that is at d=0,\n\n⇒dNdt=V+π−μN, Integrating both sides give us:\n\n⇒−1μlnΛ+π−μN≤t+c which is simplified to\n\n⇒Λ+π−μN≥Ae−μt where e−μc=A=Constant\n\nBy applying the initial condition N0=N0, we get:\n\n⇒Λ+π−μN≥A which upon substitution in\n\nThen, −μN≥−Λ−π+Λ+π−μN0e−μt\n\nAs t→∞, the population size N→Λ+πμ since Λ+π−μN0e−μtμ→0, as t→∞.\n\nThis implies that 0≤N≤Λ+πμ. Thus, feasible solution set of the system equation of the model enters and remains in the region.\n\nTherefore, the basic model is well posed epidemiologically and mathematically. Hence, it is sufficient to study the dynamics of the basic model in Ω.\n\n\nDisease-free equilibrium point\n\nTo find the disease-free equilibrium (DFE), we equated the right-hand side of the model (1)-(7) to zero, evaluating it at E=A=C=T=0 and solving for the noninfected and noncarrier state variables. Therefore, the disease-free equilibrium is given by:\n\n\nEffective reproduction number\n\nWe calculate the basic reproduction number denoted by REff using the van den Driesch and Warmouth next-generation matrix approach from Ref. 16. The basic reproduction number is obtained by taking the largest (dominant) eigenvalue (spectral radius) of the matrix: FV−1=∂FiE0∂xj∂viE0∂xj−1, where Fi is the rate of appearance of new infection in compartmenti, vi is the transfer of infections from one compartment i to another, and E0 is the disease-free equilibrium point. The reproduction number REff of our HBV model is obtained by rearranging the differential equation of the dynamical system (1)-(7) above in terms of dXidt=Fi−vi=Fi−vi−−vi+.\n\nThen.\n\nThen,\n\nEigenvalues of FV−1 is given by:\n\nThen, the spectral radius (Effective reproduction number, REff) of FV−1 of our HBV model is:\n\n\nLocal stability analysis of the disease-free equilibrium point\n\nTheorem 3: The disease-free equilibrium point of the model (1)-(7) above is locally asymptotically stable if REff<1 and unstable ifREff<1.\n\nProof: The local stability of the disease-free equilibrium point of the system (1)-(7) can be studied from its Jacobian matrix at the disease-free equilibrium point E1=S0V0E0A0C0T0R0=Λ+πμ−Λψ+θπτ+μΛψ+θπτ+μ00000 and Routh-Hurwitz stability criteria. Then, the Jacobian matrix of the dynamical system (1)-(7) at E1=Λ+πμ−Λψ+θπτ+μΛψ+θπτ+μ00000 is given by:\n\nThen, the characteristic equation of the above Jacobian matrix is given by:\n\nLet m=τ+μ,f=cωSN,l=μ+c1+c2,g=δ1α+δ2α+μ,h=μ+d+σ,i=φ1+μ,j=ε+μ,k=cωφSN,p=δ2α,q=δ1α\n\nHere, it is obvious that, λ1,λ2,λ3,λ4,λ5 are all negative.\n\nTo check the remaining eigenvalues are negatives for the quadratic equation L2λ2+L1λ+L0=0\n\nLet us consider λ2+l+μ+kc1λ+ehg−fgφc1+c2h+φα+δ2+fεσc1φ1=0\n\nAssuming that L2=1, ,L1=l+μ+kc1, L0=−fgφc1+c2h+φαδ2+fεσc1φ1\n\nwe can apply Routh Hurwitz stability criteria since L2=1>0 both, L1 and L0 should be positive.\n\nNow, L1=l+μ+kc1>0 and\n\nHence, the last two eigenvalues are negatives if REff<1.\n\nThus, since all the eigenvalues are negatives, the disease-free equilibrium point of the HBV dynamical system (1)-(7) above is locally asymptotically stable if REff<1.\n\n\nGlobal stability of disease-free equilibrium point (DFEP)\n\nTheorem 3: The disease-free equilibrium point of the dynamical system (1)-(7) which is given by:\n\nE1=S0V0E0A0C0T0R0=Λ+πμ−Λψ+θπτ+μΛψ+θπτ+μ00000 of is globally asymptotically stable if REff≤1 otherwise unstable.\n\nProof: To show global stability of the DFEP, we applied Lyapunov function method as.6,17\n\nLet the Lyapunov function L:R+7→R+ is defined by:\n\nL=SVEACTR=α1S+α2E+α3A+α4C. Then,\n\nTaking the coefficients of S,E,A, andC are equal to zero, we get:\n\nPartial derivative in terms of S gives us: α11−θπ−1−ψΛ−μ=0.\n\nThis gives\n\nPartial derivative in terms of E gives us: −μ+c1+c2α2+c2α3+c1α4=0.\n\nPartial derivative in terms of A gives us: −cωS0Nα1+α2cωS0N−δ2α+δ1α+μα3+αδ2α4=0.\n\nPartial derivative in terms of C gives us: cωS0Nα1−α2cωS0N−μ+d+σα4=0.\n\nSince S≤S0, and from equations (8)-(11) solving for α2,α3 and α4 and after simplification, we get:\n\nSince S0N=τ+μ−μθτ+μ, and cωS0N=cωτ+μ−μθτ+μ,\n\n⇒dLdt=α2c2REff−1, since α2c2>0,\n\nThen, dLdt=α2c2REff−1≤0 where REff≤1 and dLdt=0 if and only if S=S1,E=E1,A=A1 and C=C1. Therefore, the largest compact invariant set in SEAC∈Ω1:dLdt=0 is the singleton E1 where E1 is the disease-free equilibrium point of the model (1)-(7).\n\nThus, by LaSalle’s invariance principle,18 it implies that the disease-free equilibrium point E1=Λ+πμ−Λψ+θπτ+μΛψ+θπτ+μ00000 is globally asymptotically stable in Ω1 if REff≤1 otherwise it is unstable.\n\n\nEndemic equilibrium points (EEP), E1\n\nLet the endemic equilibrium of our HBV model system (1)-(7) be denoted by E1 = (V∗,S∗,E∗,A∗,C∗,T∗,R∗). It is obtained by setting the right-hand side of each equation of our model (1)-(7) equal to zero and solving for the state variables in terms of the force of λ=cωφC+AN. That is:\n\nE1 = (V∗,S∗,E∗,A∗,C∗,T∗,R∗)\n\nThus, after some calculation, we get the endemic equilibrium point is given by:E1=V∗S∗E∗A∗C∗T∗R∗ where V∗=θπτ+μ;\n\nR∗=11−aε+σa1−θπ+τθπ+ψΛτ+μ, where:\n\n\nLocal stability analysis of the Endemic Equilibrium Point (EEP)\n\nThe disease-free equilibrium point of the model (1)-(7) above is locally asymptotically stable if REff<1 and unstable ifREff<1.\n\nTheorem 4: The endemic equilibrium point E1=S∗V∗E∗A∗C∗T∗R∗ of the HBV model, (1)-(7) is locally asymptotically stable (LAS) if Reff>1.\n\nProof: To show the local stability of the endemic equilibrium point, we use the method of the Jacobian matrix and Routh Hurwitz stability criteria. Then, the Jacobian matrix of the dynamical system (1)-(7) at the endemic equilibrium point E1. The Jacobean matrix, J(E1) of model (1)-(7) with respect to E1=S∗V∗E∗A∗C∗T∗R∗ at the endemic equilibrium point is:\n\na=τ+μ,b=μ+cωφC∗+A∗N,c=μ+c1+c2,d=δ1α+δ2α+μ,f=μ+d+σ,g=φ1+μ,h=(γcωφC∗+A∗N+ε+μ),j=cωS∗N,k=cωφS∗N,l=γcωφC∗+A∗N,m=cωφS∗N,n=cωS∗N,p=δ1α,r=γ+ε+μ,u=c1E∗\n\nThen, determinant of this Jacobian matrix is given by:\n\nAfter simplification and adjustments, we get:\n\nThen, we have: −a−λ−g−λ−r−λ−b−λA3λ3+A2λ2+A1λ+A0=0.\n\nHere, we get λ1=−a<0,λ2=−g<0,λ3=−r<0 or λ4=−b<0andA3λ3+A2λ2+A1λ+A0=0.\n\nWhere:\n\nA0=abh+cklu+cdfp+c2adhk=cωφγλ+ε+μτ+μREff+μ+c1+c2μ2μ+d+σREff+δ1αREff−1+γcωφλ+μREff+δ2αφc2REff−1, if REff>1. This implies that all the coefficients of the characteristic’s polynomial are positives if REff>1. Hence, the endemic equilibrium point of the dynamical system (1)-(7) is locally asymptotically stable.\n\n\nSensitivity analysis\n\nThe study of how the uncertainty in the output of a mathematical model or system might be partitioned and assigned to different sources of uncertainty in its inputs is known as sensitivity analysis. Sensitivity analysis may anticipate event outcomes given a certain set of factors, and an analyst can utilize this knowledge to understand how a change in one impacts the other variables or outcomes. A sensitivity analysis can isolate specific factors and display the range of possible outcomes. A sensitivity analysis is a tool for determining the robustness of trial findings by analyzing how changes in methodology, models, unmeasured variable values, or assumptions affect results.\n\nSince sensitivity analysis gives us best indication about parameters that contribute most and least to increasing of reproduction of the disease under investigation, we can see sensitivity indices of Reff to the fifteen different parameters in the model in the order from the most sensitive to least. From the sensitivity index of the model, it is shown that the most sensitive parameter is contact rate c whereas,the least sensitive parameter is τ, which is rate of waning of vaccination efficacy.\n\nDefinition: The normalized forward sensitivity index of Reff that depends differentiable on a ParameterP is defined by:\n\nThe parameter with higher magnitude is/are more influential. The sign of the sensitivity indices of Reff with respect to the parameters show the positive or negative impact of the parameter on Reff. That is, if the sign of the sensitivity indices is positive then the value of increase whenever the value of the parameter increases and if the sign of the sensitivity indices is negative then the value of Reff decrease whenever the value of the parameter increase.19\n\nTherefore, we calculated Sensitivity Index in terms of each parameter by using the parametric values from Table 1 above as follows.\n\nThe resulting sensitivity indices of Reff to the thirteen different parameters in the model are shown in the following table in the order from the most sensitive to least.\n\nSince sensitivity analysis gives us best indication about parameters that contribute most and least to increasing of reproduction of the disease under investigation, we can see sensitivity indices of REff to the fifteen different parameters in the model in the order from the most sensitive to least. Asit is illustrated on sensitivity index of the model in table above, it is shown that the most sensitive parameter that contributes to reproduction number of BV disease is contact rate c, whereas,the least sensitive parameter contributing to reproduction number is τ, which is rate of waning of vaccination efficacy.\n\n\nNumerical simulation and discussion\n\nIn order to discuss numerical analysis of both DFE and EEP of HBV disease, we used MATLAB numerical solver (ode45) with data from Table 1 and different initial conditions.\n\nFirst, consider the role of acute and chronic infectious individuals in disease transmission, as shown in Figure 2 below.\n\nWe calculated the basic reproduction number as:\n\nThis can be expressed in terms of:\n\nThis implies:\n\nwhere:\n\n-R0A− Reproduction number at Acute stage\n\n-R0C−Reproduction number at Chronic stage\n\nAcute hepatitis B infection can last up to six months (with or without symptoms), and infected people can transmit the virus to others during this time. The majority of people recover from an acute infection within three months. People are in a good mood at this time. However, it may take up to four months for the hepatitis B virus to be eliminated from the blood. Because the acute stage of HBV infection is asymptomatic, and acutely infected people have a higher viral load than chronically infected people. Individuals in the acute stage are more likely to infect others than those in the chronic stage, as illustrated graphically in Figure 2 by R0A > R0C.\n\nFigure 2 shows that an individual's basic reproduction number is greater in the acute stage than in the chronic stage. This implies that infectious individuals in the acute stage contribute significantly to infection transmission and keep the disease endemic in the population when compared to those in severe conditions (chronic stage) whose HBV status is well known and most of whom are expected to be treated (hospitalized).\n\nFigure 3 above is plotted with the effective reproduction numbers less than a unity in mind. It aided us in demonstrating that the infectious classes of our model decrease at Reff<1. Reff= 0.58 at c1 = 0.00157, c2 = 0.000643 with all other parameters as shown in Table 1. This figure confirms the diseasefree equilibrium point of the HBV model is globally asymptotically stable.\n\nFigure 4 depicts the plot of Reff<3.513 at c1 = 0.67, c2=0.281, with all other parameters listed in Table 1. It is clear from the simulation in Figure 4 that the HBV model endemic equilibrium point is globally asymptotically stable.\n\nFigure 5 shows that when the vaccination rate exceeds 0.81, the graph of reproduction number falls to zero. This confirms that subsequent vaccination of the population is critical in reducing HBV disease transmission.\n\nFigure 6 shows keeping the value of treatment rate σ greater than 0.67 makes reproduction number of HBV disease to decrease to zero. This shows the effectiveness of treatment in suppressing transmission of HBV disease.\n\nFigure 7 shows as the transfer rate from Exposed class to Acute infective class increases effective reproduction number of HBV increases. Then by keeping c2<0.451, it is possible to decrease effective reproduction number of HBV and transmission of the disease.\n\nAs it is understood from Figure 8, effective reproduction number is proportional to transfer rate from Exposed class to Chronically infective class. Then, by keeping c1<0.52, it is possible to control transmission of HBV.\n\nAs it is shown on Figure 9 above, when contact rate of HBV becomes greater than 0.337, then effective reproduction number of the HBV becomes greater than 1 meaning the disease becomes endemic in the society. To overcome the endemicity of the virus we should keep the contact rate less than 0.337 by preparing education campaign concerning transmission mechanism of the virus for the society.\n\nIt is known that migration of people from one place plays a vital role in transmission of infectious disease. Currently, the world is suffering from migration. So to control transmission of HBV in the world it is recommendable to decrease migration rate below 0.445 so as to make the virus not become endemic in the society.\n\nOn Figure 11, it is shown that when REff<1 and in the absence of re-infection rate,γ=0, exposed population decreases. This shows that absence of re-infection contributes to decrement of transmission of HBV and exposed population.\n\nAs it is shown on Figure 12, in the presence re-infection rateγ>0, population of exposed class increase when compared to that of in absence of re-infection. From this, we can understand that re-infection plays its vital role in increasing transmission rate of HBV and increment of infective population.\n\nAs illustrated in Figure 13, migration plays an important role in reducing the number of HBV susceptible people. As the migration rate increases from 0.02 to 0.9, the number of years required for the susceptible population to become zero decreases from seven to two. As a result of this, we can conclude that migration is one of the influential factors in the spread of HBV in society.\n\nAs a result, testing the immigrants allows us to control the virus's spread.\n\n\nConclusion\n\nIn this study, we developed a mathematical model of seven nonlinear differential equations on HBV that includes vaccination intervention for acute and chronic infective classes, treatment for chronic infective classes, and HBV reactivation after transplantation and chemotherapy. We demonstrated the model's solutions' positivity and boundedness. Reff was calculated and used to determine the conditions under which HBV could be transmitted and remained endemic in the population.\n\nAs a result, we demonstrated that diseasefree equilibrium points E0 are locally asymptotically stable when Reff<1. We also demonstrated that the HBVinfected population has three endemic equilibrium points E∗and is locally asymptotically stable when REff>1.\n\nThe diseasefree equilibrium points of the HBV model were determined using a global stability analysis whenever Reff<1. We used numerical simulation to investigate the effect of vaccination and treatment on HBV transmission. The most sensitive parameters of our model that can be controlled epidemiologically are the HBV contact rate,cand migration rate, ψ.\n\nAs a result, it is reasonable to recommend using HBV intervention strategies to reduce c to less than 0.337 and ψto less than 0.445.Vaccination and treatment are examples of intervention strategies.\n\n2.It is possible to reduce HBV transmission in society by increasing the sensitive parameters vaccination rate greater than 0.81 and treatment rate greater than 0.67. Furthermore, by lowering the reinfection rate to less than 0.25, it is possible to reduce the exposed population, which greatly contributes to the increase of acute and chronic infective populations that play a role in the transmission of HBV infection in society following liver transplantation and chemotherapy. Furthermore, by keeping migration less than 0.445 and reducing the number of untested immigrants, HBV transmission can be reduced.\n\n\nRecommendations\n\nIn this study, we observe that the effective reproduction number REff=3.513 is greater than one and this implies that the disease spreads in the community. Therefore, we want to draw the following recommendations to make the effective reproduction number less than one:\n\nContact rate, the one that contributes much to transmission of HBV should be made less than 0.337 by making education campaign and panel discussion with the society with the concerned virus. Vaccination rateθ should be made greater than 0.81, treatment rate σ should be greater than 0.67, migration rate should be kept below 0.445, the transfer rate from Exposed class to Acute infective class c2 should be less than 0.451, transfer rate from Exposed class to Chronically infective class c1 should be kept less than 0.52 so as to effective reproduction number less than one implying decrement of transmission of HBV and its re-activation.\n\n\nData availability\n\nThe authors used secondary data from related literatures published on the HBV transmission dynamics case and cited the source of their data in the references part.2,18,20–24", "appendix": "References\n\nRoche B, Samuel D, Gigou M, et al.: De novo and apparent de novo hepatitis B virus infection after liver transplantation. J Hepatol. 1997; 26: 517–526. PubMed Abstract \| Publisher Full Text\n\nThornley S, Bullen C, Roberts M: Hepatitis B in a high prevalence New Zealand population: a mathematical model applied to infection control policy. J Theor Biol. 2008; 254(3): 599–603. PubMed Abstract \| Publisher Full Text\n\nKassa SM, Ouhinou A: Epidemiological models with prevalence dependent endogenous self-protection measure. Math Biosci. 2011; 229(1): 41–49. PubMed Abstract \| Publisher Full Text\n\nLau GK, Yiu HH, et al.: Early is superior to deferred preemptive lamivudine therapy for hepatitis B patients undergoing chemotherapy. Gastroenterology. 2003; 125: 1742–1749. PubMed Abstract \| Publisher Full Text\n\nRinaldi F: Global stability results for epidemic models with latent period. IMA J Math Appl Med Biol 1990; 7: 69–75. PubMed Abstract \| Publisher Full Text\n\nAhmed F, Foster GR: Global hepatitis, migration and itsimpact on Western healthcare. Gut. 2010; 59(8): 1009–1011. PubMed Abstract \| Publisher Full Text\n\nWHO (World Health Organization): National Hepatitis B Needs Assessment; 2008. Williams R. Global Challenges In Liver Disease. J Hepatol. 2006; 44(3): 521–526.\n\nAhmed F, Foster GR: Global Hepatitis,Migration and its Impact on Western Healthcare, Baij Group Ltd and British. Soc Gastroenterol. 2010; 59(8): 1009–1011.\n\nGalbrain JW, Donnell JP, Franco R, et al.: National estimates of healthcare utilizationby individuals with hepatitis C virus infection in the United States. Clin Infect Dis. 2014; 59(6): 755–764. PubMed Abstract \| Publisher Full Text\n\nLequam M: A Mathematical Model Of The Dynamics For Anti-HBU Infection Treatment with Pegunterferon Alfa-2a. J Tempe. 2008; 1433–1436.\n\nGaff H, Schaefer E: Optimal control applied to vaccination and treatment strategies for various epidemiological models. Math Biosci Eng. 2009; 6: 460–492.\n\nRuy MR, Arthur L, Alan SP: Dynamics Of hepatitis B virus Infection. J. Microbes Infection. 2002; 4: 829–835. Publisher Full Text\n\nShim E: An epidemic model with infective immigrants and vaccination. M.Sc Thesis, University of British Columbia, Vancouver, BC, Canada.2004.\n\nAnderson RM, May RM: Infectious Diseases of Humans: Dynamics and Control. Oxford, UK:Oxford University Press;1991.\n\nKamyad AV, et al.: Mathematical Modeling of Transmission Dynamics and Optimal Control of Vaccination and Treatment for Hepatitis B Virus. Comput Math Methods Med. 2014; 2014: 1–15. Article ID 475451. PubMed Abstract \| Publisher Full Text\n\nLiang TJ, Baruch Y, Ben-Porath E, et al.: Hepatitis B virus infection in patients with idiopathic liver disease. Hepatology. 1991; 13: 1044–1051. PubMed Abstract\n\nRedheffer R: Volterra multipliers I. SIAM J Algebr Discret Methods. 1985; 6: 592–611. Publisher Full Text\n\nPang J, Cui A, Zhou X: Dynamical behavior of a hepatitis B virus transmission model with vaccination. J Theor Biol. 2010; 265(4): 572–578. PubMed Abstract \| Publisher Full Text\n\nvan den Driessche P , Watmough J: Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math Biosci. 2002; 180(1-2): 29–48. PubMed Abstract \| Publisher Full Text\n\nZhang T, et al.: Modeling and Analyzing the Transmission Dynamics of HBV Epidemic in Xinjiang, China.Publisher Full Text\n\nZou L, Zhang W, Ruan S: Modeling the transmission dynamics and control of hepatitis B virus in China. J Theor Biol. 2010; 262(2): 330–338. PubMed Abstract \| Publisher Full Text\n\nMedley GF, et al.: Hepatitis-B Virus endemicity, Catastrophic dynamics and Control. Nat Med. 2001; 7(5): 619–624. PubMed Abstract \| Publisher Full Text\n\nHu Z, Ma W, Ruan S: Analysis of SIR epidemic models with nonlinear incidence rate and treatment. Math Biosci. 2012; 238: 12–20. PubMed Abstract \| Publisher Full Text\n\nLau GK, et al.: Preemptive use of lamivudine reduces hepatitis B exacerbation after allogeneic hematopoietic stem cell transplantation. Hepatology. 2002; 36: 702–709. PubMed Abstract \| Publisher Full Text" }	[ { "id": "149579", "date": "27 Sep 2022", "name": "Mahmood Parsamanesh", "expertise": [ "Reviewer Expertise Mathematical modelling of infectious diseases." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAn epidemic model for HBV transmission dynamics was introduced in this paper. The model includes vaccination, treatment and re-infection. Infected people are considered in Acutely infected and Chronically infected classes. Stability of the equilibria and sensitivity analysis of the basic reproduction number have been given.\nAfter reading the manuscript, my comments are given below. Upon my observations I suggest major revision.\nThere are some typos error in the manuscript. For instance\nIntroduction, paragraph 2, line 2, it spreads and spreads --> it spreads, and line 4, asafe --> a safe, Bottom of the page 3, Recovered R --> Recovered R(t) page 5, some explanations about the force of infection should be given.\n\npage 5, analytic solution of S(t) has not been obtained correctly.\n\npage 5, in proof of positivity of S(t), why is the expression in parentheses positive? The positivity of V, R, C and A has not been proven yet. Similarly, this question is raised for positivity of the other variables.\n\npage 8, firstly substitutions yields to . Secondly, how this condition with implies ?\n\npage 9, in rearranging the differential equation of the dynamical system (1)-(7), more explanations about should be given. Moreover, before obtaining matrices F and V, the matrices and should be given.\n\npage 10, in statement of Theorem 3, and unstable if --> and it is unstable if\n\npage 10, the diagonal components in the determinant of the Jacobian matrix for obtaining the characteristic equation are wrong. All diagonal components should be subtracted by a .\n\npage 10, the component (2,4) in the determinant of Jacobian matrix has been dropped. Moreover, for convenience of readers please give more explanations for obtaining the characteristic equation .\n\npage 11, the Routh Hurwitz criteria has not been applied completely for negativity of the last two eigenvalues of the characteristic equation. Some conditions of this criteria have not been applied.\n\npage 11, the counter of theorems is wrong. Theorem 3 --> Theorem 4. “of” is redundant in “of is globally asymptotically stable if …”.\n\npage 11, please clarify the partial derivative in terms of S in proof.\n\npage 12, after relation (11), why do we have ?\n\npage 12, before applying LaSalle’s invariance principle, and and .\n\npage 13, and unstable if --> and it is unstable if\n\nBottom of the page 13, . All diagonal components in determinant should be subtracted by a . Also, please give more explanations for obtaining the characteristic equation.\n\npage 14, in proof of local stability of endemic point, some conditions of the Routh Hurwitz criteria have not been applied.\n\npage 15, second line after Table 1, BV disease --> HBV disease\n\nA single notation for the basic reproduction number should be used throughout the article. In section Numerical simulation and discussion, the notation has been used for the basic reproduction number while before that has been used for it.\n\nbottom of the page 16, -->\n\npage 22, after Figure 13, “2.” Is redundant.\n\nIn the article, the impact of re-infection on the introduced model has not been investigated such as it stated as a novelty of this work. It is expected that the its impact is considered on the basic reproduction number of the model as well as on the dynamics of the model.\n\nImportant: Please address all changes made in the manuscript exactly in the response comment and highlight them in the revised version.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? No source data required\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "150057", "date": "05 Oct 2022", "name": "Adnan Khan", "expertise": [ "Reviewer Expertise Mathematical Epidemiology" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors present and analyze a model for the transmission dynamics of Hepatitis B. The problem they address is relevant and interesting. In particular they want to study the effects of reinfection and rates of transmission at various stages of the disease.\n\nI have two major concerns:\nThe model itself is not well explained, for example recovered population can become susceptible again, this is in addition to the possibility of reinfection given by a pathway from the recovered to the exposed population sub group. The first pathway needs to be justified.\n\nFurther a detailed literature survey needs to be provided, there are many Hepatitis B transmission models in the literature. The authors may want to clarify the novelty of the model they present.\n\nPerhaps a more serious concern is that there are several and sometimes very basic mathematical errors, for example the proof of theorem 1 has elementary errors and is incorrect, moreover positivity and boundedness of such models can be proved in a relatively simple manner, and is standard in almost all papers using these models. Similarly the stability of the DFE does not require a complicated proof using Routh Hurwitz.\n\nThe authors need to seriously go through the work and rectify the mathematical errors and then resubmit the work.\n\nIn summary they authors have tackled an interesting problem, however there are serious deficiencies in the work, as outlined above.\n\nIs the work clearly and accurately presented and does it cite the current literature? No\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? No source data required\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-931
https://f1000research.com/articles/11-930/v1	12 Aug 22	{ "type": "Research Article", "title": "The impact of stress and its influencing factors among dentists during the COVID-19 pandemic in Kingdom of Bahrain", "authors": [ "Ali Ateeq", "Shaikha Ebrahim", "Rana Al-Ghatam", "Shaikha Ebrahim", "Rana Al-Ghatam" ], "abstract": "Background: It is well known that all medical professions are linked to work stress, including dentistry, which is seen as facing high risk due to the nature of the job, especially the working conditions. This study aimed to assess the impact of stress and its influencing factors among dentists during the coronavirus disease 2019 (COVID-19) pandemic in Bahrain. Methods: A cross-sectional survey was designed to assess the impact of stress and its influencing factors among Bahraini dentists. A total of 306 participants were randomly selected from 1489 registered professionals in the NHRA (National Health Regulatory Authority Bahrain). Results: Out of 306 participants invited in the survey, 253 responded. Overall, the participants reported moderate stress. All the variables of the study showed different effects, but the highest stressor with a strong correlation was “fear of social isolation” (FI) at the significance level of 0.01 (β= 0.393, t= 5.090, p < 0.05= (0.000) with f2 = 0.201 above 0.15 and less than 0.35, which was considered as a moderate effect size of approximately (20%), which strongly supported the hypothesis that researchers have proposed. Overall, the total effect for all stressors was 30 % which was considered as a moderate effect size. All hypotheses were supported except Burden of caring for patients → OUTCOME due to insufficient evidence. R² values of independent variables were above 95% for the variance of dentists’ outcomes, which is considered an excellent fit to the data as evidenced by the squared multiple correlations (R2 ) values for the dependent variables. Conclusions: The study is unique based on its findings that reveal the impact of stress among dentists. Moreover, the results of this study may serve as guidance for future monitoring of dental practitioners’ burnout, anxiety, and workload.", "keywords": [ "Covid-19", "Stress", "influencing factors", "Outcome", "Dentists" ], "content": "1. Introduction\n\nThe study of stress has received much scholarly attention, especially in the last two years, precisely during the coronavirus disease 2019 (COVID-19. However, the majority of stress-related studies cannot be thoroughly assessed. Notwithstanding, the study of depression, anxiety, and stress levels of physicians and healthcare workers has recently caught the attention of many researchers yet there is still scarce literature on this vital issue. The current research dwells on stress and its influencing factors among health workers, specifically dentists, in the Kingdom of Bahrain. Continuous stress and its consequences on dentists’ mental and social health are critical issues for medical researchers to address.1\n\nBahrain was not insulated from what was going on around the globe during the pandemic. More than a third of the population had experienced anxiety and other significant psychological impacts according to a study conducted in Bahrain in the year 2020.2\n\nIn fact, since the COVID-19 was discovered in Wuhan, its rapid spread in a short period of time, the enormous number of infected cases, and the unfortunate deaths were noted. These large numbers have created fear among the public, particularly among health workers (front liners), including doctors, nurses, and allied personnel. professionals.3\n\nMultiple studies have shown the negative consequences of the spread of COVID-19 and its related stress issues along with its substantial impact on the medical staff (nurses, doctors, and dentists). This continuous stress has led to post-traumatic stress symptoms and poor performance.4\n\nPrevious studies have reported that dental practitioners are not spared from stress and are affected as much as other health workers.5,6 However, this stress should be mitigated as much as possible to help reduce any stress-related physical and emotional consequences.\n\nThe study by Al-Zubair (2014) examined the stress experienced by dentists in Yemen. The results suggested that dentistry is a stressful profession due to many factors such as the nature of work conditions, handling uncooperative patients, dealing with an intense work schedule, the repetitive nature of the work plus fear and anxieties. A study conducted by Guostė Antanavičienė (2020)7 found that the most stressful factors were restrictions, work tension and responsibility, while least stressful were the value of work and life satisfaction. In fact, experts recommended that dentists should be encouraged to take stress management courses to have a healthier lifestyle.5\n\nQ1. Is there any impact between fear of social isolation and dentists’ outcome during the COVID-19 pandemic in Kingdom of Bahrain?\n\nQ2. Does discomfort caused by protective equipment affect the outcome of dentists during the COVID-19 pandemic in Kingdom of Bahrain?\n\nQ3. To what extent do difficulties and anxieties related to the measures taken to control the infection, affect the dentist’s outcome during the pandemic in the Kingdom of Bahrain?\n\nQ4. How does the burden of caring for patients affect the dentists’ performance outcome during the COVID-19 pandemic in Kingdom of Bahrain?\n\nThis research aims to assess the stress, influencing factors, and determinants affecting dentists’ practices outcomes during covid-19 in the Kingdom of Bahrain. The research objectives among others are as follows:\n\nO1. To examine the impact of fear of social isolation and dentists’ outcome during the COVID-19 pandemic in Kingdom of Bahrain.\n\nO2. To assess the effects of discomfort caused by personal protective equipment towards the dentists during the COVID-19 pandemic in the Kingdom of Bahrain.\n\nO3. To investigate the impacts of the measures taken to control the infection that affects dentists’ outcome during the COVID-19 pandemic in Kingdom of Bahrain.\n\nO4. To evaluate how the pandemic of COVID-19 has impacted the responsibilities of dentists in caring for patients essentially, in the Kingdom of Bahrain.\n\n\n2. Literature review\n\nIn general, stress harms both physical and mental health. But more specifically, stress harms physicians who are exposed to a high level of stress at work.8 Moreover, stress is not only harmful to mental and physical health but to social life as well.9 It could also strongly implicate the human body, such as the pathogenesis of coronary heart disease.10 Several studies have found that individuals who are reported with high levels of stress and tension are more likely to suffer from fatal diseases such as heart disease and psycho-emotional disorders, which ultimately affect their professional and social lives.11,12 Stress and tension affect the nervous system as well. The impacts of stress can be seen in terms of reduced focus levels at work, which can lead to other serious complications.\n\nIn recent years, an increasing number of studies have mentioned the negative impact of stress on healthcare workers during COVID-19. For instance, a study conducted by Ahmed et al. (2020) has analysed the data from 30 countries. The essence of this study was on how practitioners around the globe are in a constant state of anxiety and fear while working in their respective fields due to the COVID-19 pandemic’s impact on humanity.13 According to Stankovska et al. (2020), healthcare workers are mostly at high risk of getting coronavirus due to direct contact with patients.14 This often causes fear and panic among the medical staff, fear of the consequences of the virus when communicating with the family members, fear of isolation, and fear of transmitting the virus to their family members.\n\nThe researcher has claimed that doctors’ frequent medical errors are mostly due to high stress levels they are experiencing.15 Moreover, Nabil Mohsen Al-Zubair et al. suggested that the most influential source contributing to stress, which received the highest vote compared to the other stress factors, was the repetition of work or boredom.\n\nAnother study led by Myers (2014) argued that other stress factors are the strict work timing and the attendance issues among dentists.16 Plus, the workload issue has led to sleep disturbances. In addition, several studies conducted in several countries showed that dentists experiencing nervousness and burnout at work led to the deterioration of their psychological state.17,18\n\nPouradeli et al. (2016) mentioned that concentration at work during the COVID-19 pandemic was 66%, while time pressure was 65%. These statistics yet again highlighted some stress-causing factors amongst dentists.19 A similar study revealed that anxiety represented 35.1% in China, which was the highest factor other than sleep deprivation and depression.20 Stankovska et al. (2020) and Jarvis et al. (2020) noted that everyone was anxious of the risks of catching a potentially fatal new virus and might experience mental stress, anxiety, loneliness, depression; thus, dentists were the individuals who confronted this problem the most, when looking at the nature of their job.14,21\n\nRegarding the stress related to sex among dentists, a study conducted by Ahmed Arafa1 et al. (2021) claimed that more women were experiencing psychological disturbances compared to men. Therefore, the study was formulated to test the impact between stress dimensions as independent variables and the dentists’ performance outcome as the dependent variable. Consequently, these hypotheses are displayed in detail to ensure they achieve the objectives of the study. Therefore, this has led to the following hypothesis:\n\nThere is a significant positive impact between fear of social isolation and dentist outcome during the COVID-19 pandemic in Kingdom of Bahrain.\n\nThere is a significant positive impact between the discomfort caused by personal protective equipment on the dentist outcome during the COVID-19 pandemic in the Kingdom of Bahrain.\n\nThere is a significant positive impact caused by difficulties and anxieties related to infection control on the dentist outcome during the COVID-19 pandemic in the Kingdom of Bahrain.\n\nThere is a significant positive impact between the responsibilities of dentists in caring for patients essentially, in the Kingdom of Bahrain.\n\nFigure 1 shows the conceptual framework and hypotheses model for this work.\n\nBCP=Burden of caring for patients; DAIC=Difficulties and anxieties related to infection control; DCPE=Discomfort caused by protective equipment; FI=Fear of social isolation. Source: Author’s own Conceptual Framework and Hypotheses Model.\n\n\n3. Methodology\n\nExpedited ethics approval was received from the Research Crown Prince Center, BDF Hospital, Kingdom of Bahrain (approval no. BDF/R&REC/2021-625) in September 2021. All respondents were asked for written informed consent to participate before filling out the questionnaire.\n\nSeveral dentists in the Kingdom of Bahrain were requested to participate in an online study regarding stress and its influencing factors among dentists during the COVID-19 pandemic. A total of 306 respondents selected from a list of 1489 registered professionals in the NHRA (National Health Regulatory Authority Bahrain). A convenience sample of dentists was contacted to participate in this research22 A sample size of n=306 was considered sufficient for this study according to the table of Krejcie and Morgan 1970.23 In addition, a convenience sample of dentists was contacted to participate in this study.\n\nA cross-sectional survey was designed to assess the impact of stress and its influencing factors among Bahraini dentists. An online survey was conducted to minimise face-to-face communication as well as to accommodate to dental practitioners who work in different locations of hospitals and dental clinics in Bahrain. A web-based survey was created using Google forms and emailed to the dentists in Bahrain. Data was collected between the 8th of September 2021 and 10th of October 2021.\n\nTable 1 illustrates the correlation among research objectives, research questions, and related hypotheses (created by the researcher).\n\nThe quantitative approach was utilized in this study since it is more structured than the qualitative method. Hence, the data from the respondents were collected using the online questionnaire, which was more feasible during this pandemic. Both independent (BCP, DAIC,DCPE, FI) and dependent variables (Outcome) were measured using a five-point Likert scale ranging from (1) ‘Strongly Disagree’ (2) ‘Disagree’ (3) ‘Natural’ (4) ‘Agree’ (5) ‘Strongly Agree’.This research covers the respondents’ socio-demographic profile, including gender, age, education, experience, marital status, having a child. The exogenous variables have 24 questions measured by using an instrument developed by Kuo, F. L. et al. (2020),24 while the endogenous variables have 6 questions measured by using an instrument developed by Al-zubair et al. (2014).\n\nDescriptive analysis was done using the SPSS version 25 program to analyse the study data. The partial least squares SEM (PLS-SEM) was used to estimate complex cause-effect relationship models with the latent variables. The internal consistency (Cronbach’s alpha) of the exogenous and endogenous variables were 0.938, suggesting that the questionnaires were internally consistent. This study has five dimensions as presented in Table 2.\n\n\n4. Results\n\nFigure 2 illustrates the procedure of data gathering.\n\nOut of 306 participants included in the survey, 253 responded, giving a response rate of 83.6%.49 Overall, 30.8% were female, and 69.2% were male. The average mean and standard deviation in gender variable were 1.35±0.35. There were more men than women in the sample (69% vs 30.9%). Table 3 shows that the majority of the sample were aged between 45-50 years, which represented 39.9%. In contrast, 61.1% represented the rest of the age groups. The average mean and standard deviation in age were 2.72±0.96. In terms of experience, most dental practitioners who participated in the survey had over 20 years clinical experience. Over two-thirds of the surveyed dentists (69.2%) hold a bachelor’s degree. The average mean and standard deviation were 1.19 ±0.28. There were more bachelor’s degree holders than master’s degree holders in the sample (69.2.8% vs 3.8%). Regarding marital status, 81.1%. of respondents were married, and most of the participants had children (84.6%), while the rest (15.4%) did not have children. Table 4 shows the descriptive statistics for constructs. Tables 5 to 9 show the descriptive statistics for variables.\n\nActual range 1-5=5-point Likert scale (1) Strongly Disagree, (2) Disagree, (3) Natural, (4) Agree, to (5) Strongly Agree.\n\nThe findings reveal that the mean of all variables is greater than 2.80. This suggests that responders were aware of the impact of stress during the COVID-19 epidemic. According to Table 4, the most common stress factor was difficulties and anxieties towards infection risks. The mean score was 2.90±1.36, which was significantly higher than the rest of factors respectively, followed by fear of social isolation and the mean score was 2.87±1.14, which was the lowest standard deviation (SD) among the others. Both discomfort caused by personal protective equipment and outcome variables received nearly identical scores of 2.84±1.51 and 2.83±1.46. Finally, the burden of caring for patients had a mean of 2.81±1.72, which was the lowest mean and the highest SD among the other research dimensions.\n\nThe overall mean for all dimensions was 2.86±1.43. reflecting the existence of considerable acceptable variability within the data set. Figure 3 illustrates a simple bar graph representing mean of variable study.\n\nBCP=Burden of caring for patients; DAIC=Difficulties and anxieties related to infection control; DCPE=Discomfort caused by protective equipment; FI=Fear of social isolation; O=outcome.\n\nReliability measurement gives internal consistency in the measurement of the variable.25 The instrument’s reliability must be greater than 0.60 to be accepted.26,27 In this study, the researcher has conducted two types of reliability tests namely Cronbach’s alpha through SPSS 25 and composite reliability (C.R). The findings showed the reliability (Cronbach’s alpha) values were ranged from 0.997 to 0.745 while composite reliability (CR) values ranged from 0.997 to 0.974. The discriminant validity was achieved as the square root of AVE (0.990) and (0.852) was higher than the correlation value (0.50) between two latent construct.28 Furthermore, it implied that the model was free from any redundant items. Therefore, all values for composite reliability, Cronbach’s alpha, and AVE were significant and had met the required acceptance criteria. In general, Table 10 shows the characteristics of the three constructs used. The Cronbach’s alphas are greater than 0.7, and all composite reliability estimates higher than 0.9. This demonstrates a reasonable level of reliability thus, this finding has a good internal consistency that is fit and suitable for this study.29\n\nFigure 4 shows the path model result.\n\nConvergent validity refers to a level to which a set of variables converge in their measurement of a specific concept.30 The establishment and confirmation of convergent validity call for meeting specific criteria, including factors loadings, composite reliability (CR) as well as average variance extracted (AVE); these were all employed in a simultaneous manner as recommended by Hair et al. 2013.31 In doing so, the item loadings were observed and it was evident that the entire items were over 0.50 indicating acceptable levels (Hair et al., 2010). All the factor loadings in this study are significant at the significant level of 0.1.\n\nThe discriminant validity of the measures reveals how well items differ among constructs. Simply put, it confirms that the items that use various constructs do not overlap. As a result, all the variables have sufficient discriminant validity in this study that the AVE exceeds the correlation among variables. The results AVE for each variable have a greater correlation square of the given variable with any other variable. Table 12 below illustrates that the AVE’s square root for all variables is higher than the correlations between the variable and other variables in the model.\n\nThe R - squared value shows how much variance is explained by the independent variables for dependent variables. Consequently, a higher R2 value enhances the predictive ability of the structural model. Plonsky et al. (2018) recommended that R2 has to be larger than 0.75 to be deemed substantial, with adequate power above 0.25.32 In this study, the model indicated an excellent fit to the data as evidenced by the squared multiple correlations (R2) values for the dependent variables (Outcome): O (R2=0.992); as shown in Table 13 and Figure 5. Thus, the one latent variable of independents (IV) explained a substantial of variance for the outcome of dental practitioners (DV). Meanwhile, dependents variables have revealed that there were more than 98% of the variation for the impact of stress and influencing factors among dentists during the COVID-19 pandemic in Bahrain.\n\nThe main purpose of using effect size in this study is to measure the effect and relationship between variables. According to Cohen (1988), the effect size that should be less than 0.02 (0.02=small,0.15=medium, 0.35=high).33 From Table 14, the effect size of BCP, DAIC, DCPE are small meanwhile, the effect size of FI is medium. As illustrated in Table 14 and Figure 6, the effect of stress and influencing factors of stress among dentists during the COVID-19 pandemic in the Kingdom of Bahrain were calculated by the following formula:\n\nf2=above 0.35 is considered large effect size\n\nf2=ranging from 0.15 to 0.35 is considered medium effect size\n\nf2=between 0.02 to 0.15 is considered small effect size\n\nf2=values less than 0.02 are considered with no effect size\n\nf2=(R2 included – R2 excluded)/(1-R2 included)\n\nAs shown in Table 14 and Figure 6, the effect size of the burden of caring for patients (BCP) ranged between 0.02 to 0.15, which seemed a weak support for the hypothesis with limitation of small effect size, approximately 2.6%. While difficulties and anxieties related to infection control (DAIC) ranged between 0.02 to 0.15 was considered as small effect size, represented 3.5%. Similarly, discomfort caused by protective equipment (DCPE) was considered as a small effect. Finally, fear of social isolation (FI) had the strongest effect size among other independent variables. Its medium ranged was above 0.015 and less than 0.35 (represented 20%), which was considered as a medium-size effect according to Cohen’s criterion.35 In summary, all the variables of the studies have contributed considerable effects in varying proportions as the total effect size had a medium with a total average (29.8%). Therefore, there was a support for the proposed hypotheses with a high effect size rate.\n\nFollowing the confirmation of the goodness of the outer model, the researcher tested the hypothesised relationship among the constructs through Smart PLS 3.0, PLS Algorithm. R is an open-source software which could also be used. Figure 7 and Table 15 display the path coefficients and t-values that were obtained from the test.\n\nBCP=Burden of caring for patients; DAIC=Difficulties and anxieties related to infection control; DCPE=Discomfort caused by protective equipment; FI=Fear of social isolation.\n\n* Significant=p<0.05.\n\nTo ensure that the path coefficients are statistically significant, the current study has chosen the bootstrapping method integrated with Smart PLS3. The main purpose of using bootstrapping was to generate t-values coupled with each path coefficient, and as a subsequence, the p-values of the hypotheses were also generated, as displayed in Table 15. As shown in Table 15, it can be concluded that the burden of caring for patients (BCP) has negatively impacted the outcome at the significant level of 0.01 (β=-0.184, t=01.560, p=0.060). Additionally, the result rejected the hypothesis due to the t-value, which was less than 1.96, while the highest SD among the others and p>0.05. Moreover, dental practitioners did not support the burden of caring for patients as an independent variable and the outcome as the dependent variable. In other words, this result indicated that their priority was to taking care of the patient, despite the fatal risk they were exposed to during the COVID-19 pandemic. Apparently, the participants did not pay much attention thus implied the variable was not their primary concern. It became unnecessary to examine the impact of (BCP) on the stated impact as suggested by Hair et al.36 Furthermore, the researcher rejected alternate hypotheses and accepted null hypothesis instead, due to disapproving of the impact (BCP) on the outcome during the COVID-19.37 However, the impact between difficulties and anxieties related to infection control (DAIC) and the outcome as the dependent variable was supported at the level of significance of 0.01 (p<0.05, β=0.210, t=2.118, p=0.017). Meanwhile, the discomfort caused by protective equipment was supported by predictors of dental practitioners at the significance level of 0.01 (p<0.05, β=0.212, t=2.354, p=0.009). This result was found by another study which was conducted in Taiwan in 2020, which revealed that discomfort caused by protective equipment had a moderate stressor among another dimension of stressor investigated.38 Surprisingly, fear of social isolation revealed the strongest correlation with outcome among independent variables at the significance level of 0.01 (β=0.393, t=5.090, p<0.05 (0.000). Statistically, FI was considered the lowest SD among other dimensions, which enhanced researcher’s analysis. This result indicated that fear of social isolation revealed (FI) as one of the most important challenges and the most stressful for dental practitioners in Bahrain. Therefore, this result is in line with previous studies that supported healthcare workers such as dental practitioners did experience stress related to fear of social isolation, in fact they were even more stressful of the fear of having the infection spread to their family and relatives.38,39 All the relationships mentioned earlier were examined by using the PLS.3 bootstrapping method.\n\n\n5. Discussion\n\nThis study on stress and its influencing factors among dentists during the COVID-19 pandemic was conducted in the Kingdom of Bahrain, using a web-based structured questionnaire. As per findings, total stress was a moderate stress and fear of social isolation (FI) was ranked as the major stressor. Dentists generally perceived as experiencing a higher stress as compared to other types of medical staff. Difficulties and anxieties related to infection control (DAIC) and discomfort caused by protective equipment (DCPE) were the major stressor as well for the participants and affected negatively to their performance, while the burden of caring for patients (BCP) was the least stressful among all dimensions. Surprisingly, in this study, more than half (2.81±1.72) of participants agreed that they could cope with the high risk of stress as they believed in their responsibility of patient care; thus, the burden of caring for patients (BCP) variable was not supported by the participants thus it had the highest SD, with the lowest mean as well as lowest correlated among other independents variables as there was not a strong effect. Therefore, the hypothesis was rejected at insignificant level 0.01 (β=-0.184, t=01.560, p=0.060).\n\nFear of social isolation (FI) was the major stressor with a total effect off2 20% out of 30% among other stressors and had negatively affected the dentists’ performance. FI was seen as the most statistically significant stressor for participants due to reasons such as loneliness, being apart from their loved ones, causing their family to experience emotional and physical difficulties due to their absence. This result was consistent with the finding of Ahmed et al. (2020) who stated that 570 out of 655 participants (87 percent) were terrified of becoming infected with coronaviruses; thus, this is a sufficient justification to support that social isolation variable could be a source of constant fear and anxiety.5 Therefore, this construct has the strongest correlation and support hypotheses by participants.\n\nSimilar studies have reported that the presence of stress among healthcare workers could reflect in their performance negatively, thus leading to medical errors.40,41\n\nCompared to earlier studies, the current study found moderate stress levels among dentists in Bahrain.42 It was revealed that moderated stress reflected how dentists reacted to the apparently never-ending pandemics that plague the country these days.\n\nSince the beginning of the pandemic, the Bahraini authorities have taken many precautionary measures to mitigate the spread of the virus. For instance: taking strict measures such as wearing protective equipment for prolonged periods with extended working hours in some cases, thus caused a type of psychological pressure, discomfort, and tension among doctors.43 Other than that, it is important to note that the protective equipment may obstruct the work of the dentist, for instance, limited visibility. In addition, there are other accompanying factors, such as the fear of infection and the fear of home quarantine.44\n\nThe authorities could provide some incentives, either by recognising their sacrifice especially when exposing themselves to risks and complications their job can cause them, or by supporting them financially. These could help reduce stress among the dental practitioners as they pursue their challenging tasks with the incentives in mind. Another means to lower the stress levels is by reducing the working hours. In line with our findings, studies assessing the psychological impacts of the COVID-19 pandemic towards the public in Egypt showed that a lack of social and emotional support from family and relevant authorities led to worse psychological consequences compared to their counterparts. Arafa et al. (2020).40 A similar study conducted in China indicated that the attention and support automatically helped reduce anxiety and stress Cao et al.26 Similarly, data from a number of research, including a sample size of 1,400 family doctors from 12 European nations, found that 43% of sample respondents suffered from moderate stress and emotional exhaustion.45 This finding is consistent with the findings of the current study in Bahrain. It is proposed that these moderated stresses have reflected on how dental practitioners endured the long and uncertain period of the current epidemic.\n\nDental practitioners are believed to be under high stress due to the nature of their occupation and the high prevalence of burnout, anxiety, and stress. Therefore, it is recommended that the authorities should be supporting them emotionally and financially, and consider them as one of the most valuable professionals. Furthermore, it may be necessary to minimise working hours to help release the stress. Some studies assessing the psychological impacts of the COVID-19 pandemic on the public in Egypt showed that lack of social and emotional support from family and relevant authorities would cause worse psychological consequences compared with their counterparts from other professionals who were offered support.46 A similar study conducted in China indicated that the paid attention support helped reduce anxiety and stress.47 Similarly, findings from numerous studies comprised a sample size of 1,400 family physicians in 12 European countries; the study showed that 43% of sample respondents scored for stress and emotional exhaustion.48 Another important finding was that at least one-third of the physicians experienced tiredness, stress, and burnout; these results included a study which was done in the United Kingdom that had involved more than 500 physicians.28 As referred to the current study’s findings, this issue (stress among dentist) is crucial since it demonstrates the extent to which dentists are at risk during the pandemic, such as psychological discomfort, stress, and fear. In conclusion, the current study found that many dentists fear getting infected by their patients or co-workers; this was statistically confirmed by the fourth hypothesis, which concurred with the study conducted by Ahmed et al.5\n\nThis is the first study in the Kingdom of Bahrain investigating the impact of stress and its influences on dentists during COVID-19. However, we have identified many limitations in our research. Firstly, the outcome of this study is based on data collected from the dentists on the impact of stress during COVID-19 at one point in time. This study is based on cross-sectional data, which is limited in nature and lacks follow-up. This research could be more accurate if using a longitudinal approach to explain the complex relationship of the impact over a longer period. Additionally, the low response rate, a biased selection, and the fact that this study used only two variables with no mediation or moderator variables all serve as limitations. Despite these limitations, this study represents a large-scale study with validated measurements that provides a comprehensive understanding of stress and its influencing factors among dentists in Bahrain.\n\nIt is recommended that further studies utilise longitudinal approaches rather than cross-sectional plus other different analysis methods such as CFA and SEM techniques. It is recommended that future studies also include other countries, such as Arab countries in general, practically in GCC (Gulf Cooperation Council) countries. Another recommendation for future studies is to increase the sample size.\n\n\n6. Conclusion\n\nSince the early stage of the COVID-19 pandemic in Bahrain, the results have shown that dental practitioners are subjected to psychological and physical stress. Also, the dentist profession is reported to experience significantly high levels of tension. Furthermore, the fact that the healthcare workers, especially those who are directly in contact with sick patients face increased risk of contracting infectious diseases, poses more significant psychological stress. Moreover, stress and its influencing factors among dentists are a commonly serious issue that may tremendously impact the quality of their performance.\n\nAs a result, based on the high risks of stress that dentists face, policymakers in Bahrain’s Ministry of Health or associated parties should consider assessing dental professionals’ requirements from various perspectives, including physically, emotionally, and financially. Additionally, decreasing working hours during COVID-19 and enhancing dentists’ working circumstances to cope with this critical situation would substantially help minimise or prevent stress. This study is unique as it exposes the consequences of stress among dentists in the Kingdom of Bahrain.\n\n\nData availability\n\nDryad: The impact of stress and its influencing factors among dentists during the COVID-19 pandemic. https://doi.org/10.5061/d ryad.1g1jwstzq.49\n\nThis project contains the following underlying data:\n\n- Dataset\n\n- Codebook june 2022.docx\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "References\n\nAlzahem AM, Van der Molen HT, Alaujan AH, et al.: Stress amongst dental students: a systematic review. Eur. J. Dent. Educ. 2011; 15(1): 8–18. Publisher Full Text\n\nAlsalman A, Mubarak H, Aljabal M, et al.: The psychological impact of covid-19 pandemic on the population of bahrain. Acta Biomed. 2020; 91(4): e2020131–e2020137. PubMed Abstract \| Publisher Full Text\n\nWang C, Pan R, Wan X, et al.: Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int. J. Environ. Res. Public Health. 2020; 17(5): 1729. PubMed Abstract \| Publisher Full Text\n\nOkechukwu EC, Tibaldi L, La Torre G: The impact of COVID-19 pandemic on mental health of Nurses. La Clin. Ter. 2020; 17(15).\n\nAhmed MA, Jouhar R, Ahmed N, et al.: Fear and practice modifications among dentists to combat novel coronavirus disease (COVID-19) outbreak.2020. Publisher Full Text\n\nKhader Y, Al Nsour M, Al-Batayneh OB, et al.: Dentists’ awareness, perception, and attitude regarding COVID-19 and infection control: cross-sectional study among Jordanian dentist. JMIR Public Health Surveill. 2020; 6(2): e18798. PubMed Abstract \| Publisher Full Text\n\nAntanavičienė G, Monika Zaleckytė JN: Stress and associated factors among dentists. Stomatologija Baltic Dental and Maxillofacial Journal. 2020; 22(2): 44–48. PubMed Abstract\n\nClark LA: Mental health and clinical psychological science in the time of COVID-19: Challenges, opportunities, and a call to action. Am. Psychol. 2021; 76(3): 409–426. Publisher Full Text\n\nRuskin KJ, Ruskin AC, Musselman BT, et al.: COVID-19, Personal Protective Equipment, and Human Performance. Anesthesiology. 2021; 134: 518–525. PubMed Abstract \| Publisher Full Text\n\nO’Connor DB, Thayer JF, Vedhara K: Stress and health: A review of psychobiological processes. Annu. Rev. Psychol. 2021; 72: 663–688. PubMed Abstract \| Publisher Full Text\n\nClemente-Suárez VJ, Navarro-Jiménez E, Jimenez M, et al.: Impact of COVID-19 pandemic in public mental health: An extensive narrative review. Sustainability (Switzerland). 2021; 13(6): 1–21. Publisher Full Text\n\nCooper CL, Marshall J: Occupational Sources of Stress. From Stress to Wellbeing Volume 1. 2013; 1(1): 3–4. Publisher Full Text\n\nAhmed MA, Jouhar R, Ahmed N, et al.: actice Modifications among Dentists to Combat Novel Coronavirus Disease (COVID-19) Outbreak. Int. J. Environ. Res. Public Health. 2020; 17(8): 282.\n\nStankovska G, Memedi I, Dimitrovski D: CORONAVIRUS COVID-19 DISEASE, MENTAL HEALTH AND PSYCHOSOCIAL SUPPORT. Society Register. 2020; 4(2): 33–48. Publisher Full Text\n\nRomani M, Ashkar K: Burnout among physicians. Libyan J. Med. 2014; 9(1): 23556. PubMed Abstract \| Publisher Full Text\n\nPuriene A, Aleksejuniene J, Petrauskiene J, et al.: Occupational hazards of dental profession to psychological wellbeeing. Stomatologija, Baltic Dental and Maxillofacial Journal. 2007; 9: 72–78. PubMed Abstract\n\nFelton JS: Burnout as a clinical entity - its importance in health care workers. Occup. Med. 1998; 48(4): 237–250. PubMed Abstract \| Publisher Full Text\n\nLarbie J, Kemp M, Whitehead P: The Mental Health and Well-being of UK Dentists: A Qualitative Study About the BDA. British Dental Association. 2017; (August).Reference Source\n\nPouradeli S, Shahravan A, Eskandarizdeh A, et al.: Occupational Stress and Coping Be- haviours Among Dentists in Kerman, Iran. Sultan Qaboos Univ. Med. J. 2016; 16(3): e341–e346. PubMed Abstract \| Publisher Full Text\n\nHuang Y, Zhao N: Generalized Anxiety Disorder, Depres- Sive Symptoms and Sleep Quality during COVID-19 Outbreak in China.2020.\n\nJarvis GE, Jurcik T, Jarvis GE, et al.: Adapting mental health services to the COVID-19 pandemic: reflections from professionals in four countries. Couns. Psychol. Q. 2020;(July); 34: 649–675. Publisher Full Text\n\nNhra: Annual Report. 2020.Reference Source\n\nAli AAA: THE RELATIONSHIP BETWEEN ISLAMIC WORK ETHICS AND EMPLOYEE PERFORMANCE AMONG MEDICAL STAFF IN THE PUBLIC HEALTH SECTOR IN BAHRAIN: EMPLOYEE COMMITMENT AS MEDIATING VARIABLE.2022.\n\nKuo FL, Yang PH, Hsu HT, et al.: Survey on perceived work stress and its influencing factors among hospital staff during the COVID-19 pandemic in Taiwan. Kaohsiung J. Med. Sci. 2020; 36(11): 944–952. PubMed Abstract \| Publisher Full Text\n\nMohajan HK: Two criteria for good measurements in research: Validity and reliability. Annals of Spiru Haret University Economic Series. 2017; 17(4): 59–82. Publisher Full Text\n\nSekaran U, Bougie R: Research Methods for Business. 5th ed.United Kingdom:John Wiley & Son, Ltd.;2019.\n\nHair JF, Black WC, Babin BJ, et al.: Multivariate Data A. 2006; Vol 6.\n\nZainudin A: Structural Equation Modelling Using Amos Graphic. Shah Alam:Universiti Teknologi MARA Publication Centre (UPENA);2012.\n\nSarstedt M, Ringle CM, Hair JF: Partial Least Squares Structural Equation Modeling. Handbook of market research. 2017; 26(1): 1–40. Publisher Full Text\n\nHair JF, Black WC, Babin BJ: Multivariate Data Analysis: A Global Perspective, Pearson Education. 2010.\n\nHair JF, Ringle CM, Sarstedt M: Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance.2013.\n\nPlonsky L, Ghanbar H: Multiple regression in L2 research: A methodological synthesis and guide to interpreting R2 values. Mod. Lang. J. 2018; 102(4): 713–731. Publisher Full Text\n\nChung RM, Adeleke AQ, Ajibike WA: Journal of Business Management and CLIENT DELAY FACTORS AFFECTING BUILDING PROJECT PERFORMANCE AMONG KUANTAN MALAYSIAN CONSTRUCTION INDUSTRY: THROUGH PARTIAL LEAST SQUARE STRUCTURAL EQUATION MODELING. Journal of Business Management and Economic Research. 2020; 4(1): 38–55. Publisher Full Text\n\nSarstedt M, Ringle CM, Hair JF:Partial least squares structural equation modeling. In Handbook of Market Research. Cham:Springer International Publishing;2021. Publisher Full Text\n\nCohen J: Statistical Power Analysis for the Behavioral Sciences. 2nd ed.1988.\n\nHair JF, Black WC, Babin JB, et al.: Multivariate data analysis: A global perspective. 7th ed.Upper Saddle River, New Jersey:Pearson Education;2010.\n\nKelter R: Bayesian alternatives to null hypothesis significance testing in biomedical research: a non-technical introduction to Bayesian inference with JASP. BMC Med. Res. Methodol. 2020; 6(20): 1–12.\n\nKuo FL, Yang PH, Hsu HT, et al.: Survey on perceived work stress and its influencing factors among hospital staff during the COVID-19 pandemic in Taiwan. Kaohsiung J. Med. Sci. 2020; 36(11): 944–952. PubMed Abstract \| Publisher Full Text\n\nBuheji M, Jahrami H, Dhahi AS: Minimising Stress Exposure During Pandemics Similar to COVID-19. Int. J. Psychol. Behav. Sci. 2020; 10(1): 9–16. Publisher Full Text\n\nRomani M, Ashkar K: Burnout among physicians. Libyan J. Med. 2014; 9(1): 23556–23557. PubMed Abstract \| Publisher Full Text\n\nHarrison R, Lawton R, Perlo J, et al.: Emotion and Coping in the Aftermath of Medical Error: A Cross-Country Exploration. J. Patient Saf. 2015; 11(1): 28–35. PubMed Abstract \| Publisher Full Text\n\nLin XJ, Zhang CY, Yang S, et al.: Stress and its association with academic performance among dental undergraduate students in Fujian, China: A cross-sectional online questionnaire survey. BMC Med. Educ. 2020; 20(1): 1–9. PubMed Abstract \| Publisher Full Text\n\nOng JJY, Bharatendu C, Goh Y, et al.: Headaches Associated With Personal Protective Equipment – A Cross-Sectional Study Among Frontline Healthcare Workers During COVID-19. Headache. 2020; 60(5): 864–877. PubMed Abstract \| Publisher Full Text\n\nBizzoca ME, Campisi G, Lo ML: Covid-19 pandemic: What changes for dentists and oral medicine experts? A narrative review and novel approaches to infection containment. Int. J. Environ. Res. Public Health. 2020; 17(11). PubMed Abstract \| Publisher Full Text\n\nKumar S: Burnout and doctors: Prevalence, prevention and intervention. Healthcare (Switzerland). 2016; 4(3). PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nArafa A, Mohamed A, Saleh L, et al.: Psychological Impacts of the COVID-19 Pandemic on the Public in Egypt. Community Ment. Health J. 2021; 57(1): 64–69. PubMed Abstract \| Publisher Full Text\n\nCao W, Fang Z, Hou G, et al.: The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020; 287(112934): 112934. PubMed Abstract \| Publisher Full Text\n\nSharma A, Sharp DM, Walker LG, et al.: Stress and burnout in colorectal and vascular surgical consultants working in the UK National Health Service. Psycho-Oncology:Journal of the Psychological, Social and Behavioral Dimensions of Cancer. 2008; 17(6): 570–576. PubMed Abstract \| Publisher Full Text\n\nAteeq A, Ebrahim S, Al-Ghatam R: The impact of stress and its influencing factors among dentists during the COVID-19 pandemic. [Dataset] Dryad. 2022. Publisher Full Text" }	[ { "id": "205221", "date": "21 Sep 2023", "name": "Yuanita Lely Rachmawati", "expertise": [ "Reviewer Expertise Epidemiology", "Community Dentistry" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAbstract and Methods: The abstract stated that \"participants were randomly selected\". In the Methods section, \"A convenience sample of dentists was contacted to participate in this research\". Please explain more specifically the sampling design.\nResult: In Figure 2, there were 53 participants excluded, please explain the reason for being excluded. It is necessary to include in the text.\nMethods: The instruments used are developed by Kuo, F. L. et al. (2020), and Al-Zubair et al. (2014). Please explain thoroughly, whether those questionnaires are adapted directly or cross-adapted. If cross-adaptation is carried out, it is necessary to explain the validity and reliability of the questionnaire.\nReference: several reference needs to be adjusted related to the writing #4, 23, 33.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "11641", "date": "28 Jun 2024", "name": "Ali Ateeq", "role": "Author Response", "response": "I am very grateful to the reviewer for their feedback on my article. However, I kindly request that they provide specific scientific justifications for their claims regarding the flaws. As a data analyst with over 60 published scientific papers, I strive for the highest standards and would appreciate detailed feedback to address any concerns accordingly. Thank you. Dr.Ali Ateeq" } ] } ]	1	https://f1000research.com/articles/11-930
https://f1000research.com/articles/11-929/v1	12 Aug 22	{ "type": "Research Article", "title": "The effects of the ‘Our Love, Our Control’ online program on sexual health literacy (SHL) and behaviors in preventing unintended pregnancy and sexually transmitted diseases (STDs) among adolescents in agricultural areas during COVID-19 outbreak in Thailand", "authors": [ "Saowanee Thongnopakun", "Mereerat Manwong", "Yuvadee Rodjarkpai", "Aimutcha Wattanaburanon", "Sawitree Visanuyothin", "Saowanee Thongnopakun", "Yuvadee Rodjarkpai", "Aimutcha Wattanaburanon", "Sawitree Visanuyothin" ], "abstract": "Background: This quasi-experimental study aimed to determine the effects of the ‘Our Love, Our Control’ online program on sexual health literacy and behaviors during the COVID-19 situation in Thailand from February 2020 to September 2021. Methods: Multistage sampling resulted in 37 and 34 participants in the experimental and control groups, respectively. Data were collected by a self-administered questionnaire. Descriptive statistics, Fisher’s exact test/Chi-square test, and independent t-test/Mann-Whitney test were used to determine differences in sociodemographic variables between the experimental and control groups. Repeated measures of ANCOVA were used to compare the mean and 95% confidence intervals of the adjusted variables. Results: From the results, adolescents who had sexual intercourse experience had statistically significant differences at the eighth week of score for behaviors (23.92; 95% CI: 16.56; 31.29), and at the eighth and at the twentieth week of score for sexual health literacy (43.55; 95% CI: 28.10; 59.00; and 19.35; 95% CI: 0.23; 38.48, respectively). However, adolescents who had no sexual intercourse experience had statistically significant differences only at the eighth week of score for sexual health literacy. (11.20; 95% CI: 3.79; 18.61). Conclusions: These findings present a useful practical program to prevent unintended pregnancy and sexually transmitted diseases, especially in sexually active adolescents.", "keywords": [ "Sexual health literacy", "pregnancy", "sexually transmitted disease", "student", "health", "COVID-19" ], "content": "Introduction\n\nThe World Health Organization (WHO) defines ‘sexual health as a state of physical, emotional, mental and social well-being related to sexuality; it is not merely the absence of disease, dysfunction or infirmity’ (World Health Organization, 2006). Sexual health is an important concept to globally prevent sexually transmitted disease (STDs) and unintended pregnancy, which are worldwide challenges among adolescents (Douglas and Fenton, 2013; Forsyth and Rogstad, 2015; World Health Organization, 2018, 2021a; Centers for Disease control and Prevention, 2021).\n\nIn developing countries, unintended pregnancies among adolescents aged 15–19 years are estimated to be more than 10 million pregnancies per year (World Health Organization, 2020). The unintended pregnancy rate in Southeast Asia has been increasing, with the top three rates in Lao People’s Democratic Republic (PDR), Cambodia and Thailand (UNESCO, 2018). The unintended pregnancy rate in adolescents aged 15–19 years is 28.7 cases per 1,000 (Bureau of Reproductive Health, 2018), which leads not only to health complications, but also to socioeconomic consequences (World Health Organization, 2015). STDs directly impact sexual and reproductive health (World Health Organization, 2021b). Unintended pregnancies and STDs are caused by low contraception use rates and other factors (UNICEF, 2015), and sex education is a major approach to solving these problems (Kay, Jones, and Jantaraweragul, 2010; Aragão et al., 2018; Briñez, Panqueva, and Hinojos, 2019). Currently, the COVID-19 pandemic is a barrier to adolescents’ access to those services. Consequently, UNESCO suggests that digital health sources that provide easy accessibility, privacy protection, comfort and entertaining content should be used to improve sexual health in adolescents (UNESCO, 2021).\n\nA study in Thailand demonstrated that online media education is an effective method for preventing pregnancy in adolescents (Narkarat et al., 2021). Health literacy plays an essential role in promoting sexual health (Vamos et al., 2020; Massey et al., 2012; Fortenberry et al., 2001). Sexual health literacy is ‘the ability to understand preventive sexual health information to make informed choices, increase safe sex practices, and reduce sexual transmitted infection risk’ (Vamos et al., 2020). Another study in Thailand that applied health literacy and self-efficacy concepts in the intervention increased the intention and practice for pregnancy prevention (Thongnopakun, Pumpaibool, and Somrongthong, 2018b). There has been little research on online sexual health literacy interventions against pregnancy and STDs in adolescents during the COVID-19 pandemic. Adolescents seem to have good health and are likely to neglect sexual health, especially after exposure to sexually risky behaviors (Massey et al., 2012). Also, there was a province in the East region of Thailand which has the highest number of STDs (Department of Disease Control, 2019) including a high rate of unintended pregnancies. Therefore, the ‘Our Love, Our Control’ online program was conducted in this province, for edutainment, sexual health literacy (accessing, understanding, appraising and applying health-related information in healthcare) (Sørensen et al., 2012), and self-efficacy concepts. This study aims to determine the effects of the ‘Our Love, Our Control’ online program on sexual health literacy and behaviors among adolescents who had sexual intercourse experience and those who had none during the COVID-19 situation in Thailand.\n\n\nMethods\n\nThis quasi-experimental research was conducted in a province of the East region, Thailand during February 2020 to September 2021. The intervention took place from 12 February 2021 – 25 June 2021. The study aimed to determine the effects of the ‘Our Love, Our Control’ online program on sexual health literacy and behaviors among adolescents who had sexual intercourse experience and those who had none during the COVID-19 situation in Thailand. Edutainment, sexual health literacy and self-efficacy were principal concepts of the online program. The experimental group attended the online program; whereas the control group lived their usual lifestyle. Nonetheless, the control group received a manual for unintended pregnancy and sexually transmitted disease prevention at the end of the research.\n\nThe Ministry of Public Health disclosed that this province had a childbearing rate of 30.63 per 1,000 among 15–19-year-old teenagers. The top three rates per 1,000 were 48.45, 36.83, and 36.74 in the districts of this province. Epidemiologic reports revealed that this province had the highest rate of STDs in Thailand, with 107.8 per 100,000 among 15–24 year-olds (Department of Disease Control, 2019).\n\nThe population of this study was 4,653 adolescent eighth graders from 71 public schools in this province. Two districts with the highest rate of teenage pregnancy/STDs were purposively selected as the experiment and comparison areas. The distance between both districts was 94 kilometres, and they were similar in terms of population size, number of students in school, agricultural land, and rurality. The classrooms in those schools from which the study population was drawn were randomly selected. The participating students received prior permission from their parents.\n\nLemeshow’s model was used to formulate the sample sizes (Lemeshow and Stroh 1988) with a confidence interval (CI) of 95%. The significant level (α) was taken as 0.05 and the power was 0.80. The mean difference was 3.46. (Krinara, Ketvatimart, and Maneechot, 2013). The sample size had a 20% attrition rate (Thongnopakun, Pumpaibool, and Somrongthong, 2018b). In the experimental group, there were 37 adolescents. The inclusion criteria were as follows: 1) Thai nationality; 2) live in the area for at least three months; 3) receive parental allowance. The exclusion criteria were as follows: 1) unable to access a smartphone; 2) being pregnant (self-reported).\n\nA self-administered 30-minute questionnaire was given to both groups at baseline, eighth week, and twentieth week. The questionnaire consisted of four categories with 70 items as follows: 1). Sociodemographic characteristics (10 closed-ended questions, including sex, grade point average, religion, average income per day, daily sufficient income, parents’ marital status, co-living with others, and occupation of parent); 2). Attribute and pattern of sexual behaviors (15 closed-ended questions, including sexual orientation, having a boy or girl friend, sexual intercourse experiences, preventive pregnancy and STD history, consultation history about preventive pregnancy and STDs, and consequences of sexual intercourse); 3). Sexual health literacy (30 Likert’s scale questions with a total of 120 point, including accessibility of sexual health information and services, sufficient understanding of sexual health and services for practice, sexual health assessment, and decision making of sexual practice), which were mainly adapted from two studies (Sørensen et al., 2012; Ministry of Public Health, 2014); 4). Behaviors for preventing unintended pregnancy and STDs (15 Likert’s scale questions with a total of 60 point, including night life, watching pornographic media, self-management of sex drive, preventing unintended pregnancy and STDs, parental consultation about sexual health, which were mainly adapted from one study (Health Education Division Ministry of Public Health, 2014). A copy of the questionnaire can be found under Extended data (Manwong, 2022).\n\nIntervention (12 February 2021 – 25 June 2021)\n\nIn order to increase sexual health literacy, behaviors for preventing unintended pregnancy and STDs, the ‘Our Love, Our Control’ online program was created by the researcher team and stakeholders with approval from five experts of adolescent health and behavior based on edutainment, sexual health literacy and self-efficacy concepts. There were seven main activities: ‘clear by doctor’ (accessibility of sexual health information and services), ‘sex must know’ (sufficient understanding of sexual health and services for practice), ‘help!!! I am not ready’ (sufficient understanding of sexual health and services for practice, and decision making of sexual practice), ‘condom matter’ (sufficient understanding of sexual health and services for practice), ‘believable’ (sexual health assessment), ‘my value’ (decision making of sexual practice), and ‘my choice’ (decision making of sexual practice). There were two research assistants (RAs) who were public health graduates and have worked with adolescents for at least three years. They were trained in sexual health literacy, behaviors for preventing unintended pregnancy and STDs, research methodology, data collection skills and Facebook management by a main researcher during 28 January – 11 February 2021, two weeks before the recruitment process. The edutainment media was composed of animation, infographic, live modelling techniques, short movies, and an interview with a health expert. All edutainment media were implemented via Facebook using the following methods: independent online learning, group discussion, pair discussion, group assignment, game playing, independent practice, rewarding and recognizing. The activities were held once weekly for eight weeks, for an average of 50 minutes per activity. After that, seven main activities were repeated from the ninth to the twentieth week. A copy of the program guide can be found under Extended data (Manwong, 2022).\n\nFive experts in adolescent health and behavior from the Ministry of Education, Ministry of Public Health, and Ministry of Higher Education, Science, Research and Innovation validated the questionnaire via Google Forms and the online program. The questionnaire’s index of item objective congruence (IOC) was 0.94 and that of the online program was 0.80 (Rovinelli and Hambleton, 1976). After testing the questionnaire on 30 adolescents with similar characteristics to the participants, the Cronbach’s alpha coefficient (DeVellis, 2016) for each part was as follows: comfortable communication with parents about sexual issues was 0.90; social and environmental factors was 0.76; sexual health literacy was 0.89; and behaviors for preventing unintended pregnancy and STDs was 0.76. The online program was tested on 30 adolescents. They evaluated the program in seven activities by five-scale ratings as follows: 1) corrected content; 2) appropriate content; 3) understandable content; 4) updated content; 5) appropriate duration; 6) interest; 7) easily applying. The results showed that 95.6% strongly agreed and agreed with all seven activities. The online questionnaires were collected at baseline, eighth week, and twentieth week by sending QR code via ‘Our Love, Our Control’, closed Facebook group.\n\nAfter each participants entered their data via Google Forms, all individual data were exported into a CSV file. This CSV file was imported into SPSS. The data was validated, coded and analysed using SPSS (IBM SPSS version 23×86, Burapha University license). Sexual intercourse experience was coded as 1 for who had experience, and 0 who had no experience. In part three of the questionnaires, there were five levels of ‘sexual health literacy’ scores as follows; 0=strongly disagree , 1=disagree, 2=not sure, 3=agree, 4=strongly agree. In part 4 of the questionnaires, there were five levels of ‘behaviors for preventing unintended pregnancy and STDs’ scores as follows; 0=never, 1=rarely, 2=sometimes, 3=very often, 4=always. The total scores of two dependent variables as sexual health literacy and behaviors for preventing unintended pregnancy and STDs were analyzed for comparison. The frequency distributions, mean (SD), median (IQR), minimum and maximum for continuous variables, and numbers and percentages for categorical variables were used to examine the sociodemographic characteristics for each group. Fisher’s exact test or Chi-square test was used for categorical data. Independent t-tests or Mann-Whitney tests for continuous data were used to determine differences in sociodemographic variables between the experiment and control groups. A literature review indicated that sexual intercourse experience was associated with behaviors for preventing unintended pregnancy and sexual health literacy (Thongnopakun, Pumpaibool, and Somrongthong, 2018a). Therefore, the data were sub-grouped and analysed by sexual intercourse experiences. Repeated measures of ANCOVA were used to compare the mean with 95% CIs of the adjusted variables of marital status and co-living with others, adjusted at baseline, eighth week and twentieth week. Statistical significance was considered when the p-value was <0.05.\n\nEthical approval was granted by Burapha University with code number: IRB1-003/2021. The approval was made in accordance with the Helsinki Declaration on studies involving human subjects. The researcher informed the participants of the research procedure in a classroom. Each participant brought the consent form back home. The parents and participants signed the informed consent form of this research if they had a mutual agreement to participate. To protect their privacy, code names were utilized, and data was kept confidential.\n\n\nResults\n\nA total of 37 adolescents from the experimental group and 34 adolescents from the control group completed this study. Three adolescents in the control group quit the study due to the COVID-19 situation. A total of 71 adolescents participated in the final per protocol analysis.\n\nThe experimental demographic characteristics (sex, grade point average, religion, average income per day, daily sufficient income, and occupation of parent) was nearly similar to that of the control group. More than half were female. The average grade point was at least 3.00. All of them were Buddhist. The average daily income was 60 baths. Forty-seven to fifty-seven percent had sufficient daily income. More than half of the parents were agriculturists. Their sexual orientation was heterosexual, at more than 70%. There were differences in demographic variables between the experimental and control groups. In the experimental group, 40.5% of them had married parents, and 59.4% had divorced or separated parents. Conversely, in the control group 70.6% were married. Among those co-living with parents, 43.2% of the experimental group lived with parents and 37.8% lived with either mother/father. In the control group, 70.6% lived with their parents. The experimental group had higher experience of sexual intercourse than the control group. (Table 1). The full dataset can be found under Underlying data (Manwong, 2022).\n\na Fisher’s exact test.\n\nb Mann-Whitney test.\n\nThere was no difference in behaviors for preventing unintended pregnancy and STDs at baseline between the experimental group and the control group. After adjusting the variables of marital status and co-living with others at the eighth week of the program, the score of behaviors for preventing unintended pregnancy and STDs showed a significant statistical difference between the experimental group and the control group (mean difference: 23.92; 95% CI: 16.56; 31.29). However, there was no difference in these scores at the twentieth week (Table 2, and Figure 1) Sexual health literacy showed no statistically significant difference between the experimental group and the control group at baseline. The score for sexual health literacy was statistically significantly different between the experimental group and the control group at the eighth week of the program (mean difference: 43.55; 95% CI: 28.10; 59.00) and at the twentieth week of the program (mean difference: 19.35; 95% CI: 0.23; 38.48) after adjusting for marital status and co-living with others (Table 2, and Figure 3).\n\n* Statistically significant.\n\nThere were no differences in behaviors for preventing unintended pregnancy and STDs at baseline between the experimental group and the control group. After adjusting the variables of marital status and co-living with others at the eighth and twentieth week, the score of behaviors for preventing unintended pregnancy and STDs was not statistically significantly different between the experimental group and the control group (Table 2, and Figure 2). There was no statistically significant difference in sexual health literacy between the experimental group and the control group at baseline. The score for sexual health literacy was statistically significantly different between the experimental group and the control group at the eighth week of the program (mean difference: 11.20; 95% CI: 3.79; 18.61) after adjusting for marital status and co-living with others. However, there was no difference in these scores at the twentieth week between the groups (Table 2, and Figure 4).\n\n\nDiscussion\n\nThe results in adolescents who had sexual intercourse experience show that there are statistically significant differences at the eighth week of score for behaviors, and at the eighth week and the twentieth week of score for sexual health literacy. These findings demonstrate that the online program was effective and appropriate in improving behaviors and sexual health literacy for preventing unintended pregnancies and STDs. The online program involved adolescents and teachers using edutainment, media, self-efficacy concepts and various designed methods for the study. Therefore, this program may be appropriate for adolescents to prevent unintended pregnancies and STDs. The intervention in this study was consistent with the two studies that used visual media, watching a discussion between medical experts, infographic and animations (Graf and Patrick 2015; Narkarat et al., 2021). A study in Thailand also disclosed that applying different methods to modify behaviors was effective for pregnancy prevention (Thongnopakun, Pumpaibool, and Somrongthong, 2018b). During the follow up period, from the ninth to the twentieth week, the activities for increasing self-efficacy were not implemented in this study, such as brainstorming and group discussion. Moreover, communication was mostly in one direction (Feldman and Rosenthal, 2000; Koesten, 2004). Without activities for increasing self-efficacy, an insignificant difference in behavior scores was observed at the twentieth week between the experimental and the control groups. Although the average behavior score at the twentieth week in the experimental group was lower than that at the eighth week, the score was still higher than that of the baseline. During the COVID-19 lockdown, the score at the twentieth week of behaviors and sexual health literacy in the control group was higher than that at the eighth week. An increase in the score in the control group may be explained by 70.6% of the control group living with their parents. Living with parents gave them the opportunity to discuss sexual information with their parents and friends, which is supported by a post hoc analytic study that revealed that friends and family were common sources of sexual information (Graf and Patrick, 2015).\n\nThere was no difference in behaviors and sexual health literacy for preventing unintended pregnancy and STDs between the experimental group and the control group. Except for the experimental adolescents who had no sexual intercourse experience, there was a statistically significant difference in sexual health literacy scores at the eighth week compared to the control group. A study by Valois et al. (1999) observed that the number of sexual intercourse partners is associated with sexually risky behaviors. Therefore, adolescents who had sexual intercourse experience were aware that they had high sexual risk behaviors. Therefore, they may focus on improving their preventive behavior and sexual health literacy. In contrast, adolescents who have no sexual intercourse experience may not be aware of sexually risky behaviors or even gain sexual health literacy improvement.\n\n\nConclusion and recommendations\n\nThe ‘Our Love, Our Control’ online program on sexual health literacy and behaviors during the COVID-19 situation in Thailand was effective, especially among adolescents who had sexual intercourse experience. There were statistically significant improvements in behaviors and sexual health literacy to prevent unintended pregnancies and STDs. Therefore, this program behavior is novel and practical in the COVID-19 era to prevent unintended pregnancies and STDs, particularly in adolescents who have sexual intercourse experience living in rural areas. Policy makers should focus on the promotion of sexual health among adolescents using online programs during the COVID-19 pandemic. This study was a quasi-experiment that represents real-life research during the COVID-19 outbreak; however, this design may not fully control all enrolments. To generate the results of this study, context needs to be considered.\n\n\nData availability\n\nZenodo: The Effects of the ‘Our Love, Our Control’ Online Programe on Sexual Health Literacy (SHL) and Behaviors in Preventing Unintended Pregnancy and Sexually Transmitted Diseases (STDs) among Adolescents in Agricultural Areas during Coronavirus Disease 2019 (COVID-19) Situation in Thailand. https://doi.org/10.5281/zenodo.6646350 (Manwong, 2022).\n\nThis project contains the following underlying data:\n\n- 000 Data set our love our control F1000 030665.xlsx [Data set]\n\nThis project contains the following extended data:\n\n- 000 Program table our love our control 030665.pdf\n\n- 000 Questionnaire our love our control F1000 030665.pdf\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nAragão JM, Nunes F, do Amaral G , et al.: The use of Facebook in health education: perceptions of adolescent students. Rev. Bras. Enferm. 2018; 71: 265–271. Publisher Full Text\n\nBriñez DK, Rojas ÁH, Panqueva G, et al.: How Should I Teach Sex Education in Middle School? An Action Research Study on an ICT-Based Intervention. Qual. Rep. 2019; 24(2): 405–428.\n\nBureau of Reproductive Health: Thailand reproductive health database. Ministry of Public Health;2018. Accessed December 25.Reference Source\n\nCenters for Disease Control and Prevention: Information for Teens and Young Adults: Staying Healthy and Preventing STDs. Centers for disease control and prevention;2021. Accessed January 3.Reference Source\n\nDepartment of Disease Control: Annual report of bureau of AIDS TB and STIs 2019. Thailand.2019.\n\nDeVellis RF: Scale development: Theory and applications. Chapel Hill, USA:Sage Publications;2016; vol. 26.\n\nDouglas JM Jr, Fenton KA: Understanding sexual health and its role in more effective prevention programs. Public health reports (Washington, D.C.: 1974). 2013; 128 Suppl 1(Suppl 1): 1–4. PubMed Abstract \| Publisher Full Text\n\nFeldman SS, Rosenthal DA: The effect of communication characteristics on family members’ perceptions of parents as sex educators. J. Res. Adolesc. 2000; 10(2): 119–150. Publisher Full Text\n\nForsyth S, Rogstad K: Sexual health issues in adolescents and young adults. Clin. Med. (Lond.). 2015; 15(5): 447–451. PubMed Abstract \| Publisher Full Text\n\nFortenberry JD, McFarlane MM, Hennessy M, et al.: Relation of health literacy to gonorrhoea related care. Sex. Transm. Infect. 2001; 77(3): 206–211. Publisher Full Text\n\nGraf AS, Patrick JH: Foundations of life-long sexual health literacy. Health Educ. 2015; 115: 56–70. Publisher Full Text\n\nHealth Education Division Ministry of Public Health: Health Literacy Scale for Unwanted Pregnancy Prevention of Thai Female Adolescents. Nonthaburi:Ministry of Public Health;2014.\n\nKay NS, Jones MR, Jantaraweragul S: Teaching sex education in Thailand. The ICHPER-SD Journal of Research in Health, Physical Education, Recreation, Sport & Dance. 2010; 5(2): 10.\n\nKoesten J: Family communication patterns, sex of subject, and communication competence. Commun. Monogr. 2004; 71(2): 226–244. Publisher Full Text\n\nKongtragoul P, Ishikawa K, Ishii H: Metalaxyl Resistance of Phytophthora palmivora Causing Durian Diseases in Thailand. Horticulturae. 2021; 7(10): 375. Publisher Full Text\n\nKrinara P, Ketvatimart M, Maneechot M: The effects of nursing student- lead unplanned pregnancy prevention program on knowledge, attitude and intention to prevent unplanned pregnancy among early adolescents. The Journal of Boromarajonani College of Nursing, Nakhonratchasima. 2013; 19(2): 20–29.\n\nLemeshow S, Stroh G: Sampling techniques for evaluating health parameters in developing countries. National Academies;1988.\n\nMassey PM, Prelip M, Calimlim BM, et al.: Contextualizing an expanded definition of health literacy among adolescents in the health care setting. Health Educ. Res. 2012; 27(6): 961–974. Publisher Full Text\n\nManwong M: The Effects of the ‘Our Love, Our Control’ Online Program on Sexual Health Literacy (SHL) and Behaviors in Preventing Unintended Pregnancy and Sexually Transmitted Diseases (STDs) among Adolescents in Agricultural Areas during Coronavirus Disease 2019 (COVID-19) Situation in Thailand.2022. Publisher Full Text\n\nMinistry of Public Health: Health Literacy Scale for Unwanted Pregnancy Prevention of Thai Female Adolescents. Nonthaburi:2014.\n\nNarkarat P, Taneepanichskul S, Kumar R, et al.: Effects of mobile health education on sexual and reproductive health information among female school-going adolescents of rural Thailand [version 1; peer review: 2 approved]. F1000Res. 2021; 10(452). Publisher Full Text\n\nRovinelli RJ, Hambleton RK: On the use of content specialists in the assessment of criterion-referenced test item validity.1976.\n\nThongnopakun S, Pumpaibool T, Somrongthong R: The association of sociodemographic characteristics and sexual risk behaviors with health literacy toward behaviors for preventing unintended pregnancy among university students. J. Multidiscip. Healthc. 2018a; Volume 11: 149–156. PubMed Abstract \| Publisher Full Text\n\nThongnopakun S, Pumpaibool T, Somrongthong R: The effects of an educational program on knowledge, attitudes and intentions regarding condom and emergency contraceptive pill use among Thai female university students. J. Health Res. 2018b; 32(4): 270–278. Publisher Full Text\n\nSørensen K, Van den Broucke S, Fullam J, et al.: Health literacy and public health: a systematic review and integration of definitions and models. BMC Public Health. 2012; 12(1): 80. PubMed Abstract \| Publisher Full Text\n\nThongkaew S, Sukprasert P, Jatuporn C: Factors affecting decision making for purchasing durian in the eastern region of Thailand: A case study of consumers. KHON KAEN AGR. J. 2021; 45(4): 593–600.\n\nUNESCO: Addressing the patterns of child marriage, early union and teen pregnancy in Southeast Asia: A matter of urgency. Bangkok:UNESCO;2018. Accessed January 3.Reference Source\n\nUNESCO: Comprehensive sexuality educationin digital spaces – opportunities forformal education in Thailand. United Nations Educational, Scientific and Cultural Organization;2021. Accessed January 4.Reference Source\n\nUNICEF: Situation analysis of adolescent pregnancy in Thailand: Synthesis report 2015.2015. Accessed January 17.Reference Source\n\nValois RF, Oeltmann JE, Waller J, et al.: Relationship between number of sexual intercourse partners and selected health risk behaviors among public high school adolescents. J. Adolesc. Health. 1999; 25(5): 328–335. Publisher Full Text\n\nVamos CA, Thompson EL, Logan RG, et al.: Exploring college students’ sexual and reproductive health literacy. J. Am. Coll. Heal. 2020; 68(1): 79–88. PubMed Abstract \| Publisher Full Text\n\nWorld Health Organization: Defining sexual health: report of a technical consultation on sexual health, 28-31 January 2002. World Health Organization;2006.Reference Source\n\nWorld Health Organization: Global standards for quality health care services for adolescents. World Health Organization;2015.Reference Source\n\nWorld Health Organization: WHO recommendations on adolescent sexual and reproductive health and rights.2018.\n\nWorld Health Organization: Adolescent pregnancy. World Health Organization;2020. Last Modified March 28.Reference Source\n\nWorld Health Organization: Adolescent pregnancy.2021a.Reference Source\n\nWorld Health Organization: Sexually transmitted infections (STIs). World Health organization;2021b. Accessed December 3.Reference Source" }	[ { "id": "147524", "date": "06 Oct 2022", "name": "Bayu Anggileo Pramesona", "expertise": [ "Reviewer Expertise public health policy" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nOverall, this study has successfully presented the whole aspect of a well written article by providing adequate information in background, methods, results, and conclusion. However, I have the following responses to this manuscript:\nIn the abstract, in the methods section, if applicable, the authors may add the intervention which provided in both groups.\n\nSince one of the outcomes of this study was preventing unintended pregnancy, why the authors thought that they need to assess the respondents' sexual orientation? You have 3 homosexual respondents and 11 bisexuals as their sexual orientation. Why do you think it's necessary to include them as your respondents? Because homosexuals may only be interested in the same gender. Those who have bisexual orientation maybe still ok to be recruited as your sample, but, for those who have a homosexual orientation, is it still relevant to your \"preventing unintended pregnancy\" outcome?\n\nYour edutainment media was mostly using Facebook as a tool. How do you convince us that the outcomes revealed due to your intervention, because the information on this sexual related issue may not only be obtained from FB, the respondents may receive some information from outside? How do you control the samples in the intervention group to follow your intervention and convince us that your samples followed your intervention until the end of study?\n\nIn the discussion, the authors need to explain why there was no difference between the experimental group and the control group in scores at the twentieth week, and why in the 20th week, there was an increase in adjusted mean of behaviors for preventing unintended pregnancy and STDs (among adolescents who had sexual intercourse experience) for the control group, while the intervention group mean score was decreased.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "9128", "date": "22 Dec 2022", "name": "Mereerat Manwong", "role": "Author Response", "response": "1. \"In the abstract, in the methods section, if applicable, the authors may add the intervention which provided in both groups.\" Answer: Due to the limitation of word count in the abstract of this journal, the details of the intervention were in the manuscript. 2. \"Since one of the outcomes of this study was preventing unintended pregnancy, why the authors thought that they need to assess the respondents' sexual orientation? You have 3 homosexual respondents and 11 bisexuals as their sexual orientation. Why do you think it's necessary to include them as your respondents? Because homosexuals may only be interested in the same gender. Those who have bisexual orientation maybe still ok to be recruited as your sample, but, for those who have a homosexual orientation, is it still relevant to your \"preventing unintended pregnancy\" outcome?\" Answer: Based-on literature review of “Can Some Gay Men and Lesbians Change Their Sexual Orientation? 200 Participants Reporting a Change from Homosexual to Heterosexual Orientation” (Spitzer, 2003), there were 200 participants (143 males, 57 females) who reported at least some minimal change from homosexual to heterosexual orientation that lasted at least 5 years. Therefore, this study should not avoid to recruit homosexual. 3. \"Your edutainment media was mostly using Facebook as a tool. How do you convince us that the outcomes revealed due to your intervention, because the information on this sexual related issue may not only be obtained from FB, the respondents may receive some information from outside? How do you control the samples in the intervention group to follow your intervention and convince us that your samples followed your intervention until the end of study?\" Answer: That is why there was the control group to be compared with an experimental group in order to reduce the other effects. More than that, repeated measures of ANCOVA were used to analyze aiming to decrease effects of time and other variables, except the effect of the intervention in this study. 4. \"In the discussion, the authors need to explain why there was no difference between the experimental group and the control group in scores at the twentieth week, and why in the 20th week, there was an increase in adjusted mean of behaviors for preventing unintended pregnancy and STDs (among adolescents who had sexual intercourse experience) for the control group, while the intervention group mean score was decreased.\" Answer: Actually, there the discussion about that between line 6 to 11 in page 9, as following. “Although the average behavior score at the twentieth week in the experimental group was lower than that at the eighth week, the score was still higher than that of the baseline. During the COVID-19 lockdown, the score at the twentieth week of behaviors and sexual health literacy in the control group was higher than that at the eighth week. An increase in the score in the control group may be explained by 70.6% of the control group living with their parents. Living with parents gave them the opportunity to discuss sexual information with their parents and friends, which is supported by a post hoc analytic study that revealed that friends and family were common sources of sexual information (Graf & Patrick, 2015)”" } ] }, { "id": "256747", "date": "11 May 2024", "name": "Ratana Somrongthongh", "expertise": [ "Reviewer Expertise Public health and reproductive health" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIntervention: edutainment media were implemented via Facebook , how to ensure whether the participants were exposed to all packages of the intervention, how many pecentage of them did not completed the intervention pacakage. Discussion: need more discussion why there was no difference in the mean scores of sexual health behavior at the twentieth week between the groups.\nIntervention: Please describe more a bit on how to ensure the participants complied with the packages of the intervention Add more the limitation: such ass small sample size\nThe article is scientific valid, the research methodology the results presented is clear.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-929
https://f1000research.com/articles/11-928/v1	12 Aug 22	{ "type": "Systematic Review", "title": "Prevalence of COVID-19 vaccine hesitancy in students: A global systematic review", "authors": [ "Debendra Nath Roy", "Md. Mohabbot Hossen", "Mohitosh Biswas", "Ekramul Islam", "Md.Shah Azam", "Debendra Nath Roy", "Md. Mohabbot Hossen", "Mohitosh Biswas", "Ekramul Islam" ], "abstract": "Background: Examining the prevalence of coronavirus disease (COVID-19) vaccine hesitancy and understanding what motivates students to accept or reject a newly promoted vaccine has the potential in preventing rapid spread of infection and optimizing country-wide mass vaccination programs. This systematic review aimed to examine global COVID-19 vaccine hesitancy among students, and to identify an up-to-date and concise assessment of most common factors influencing vaccine acceptance and hesitancy around the world. Methods: A systematic search of peer-reviewed literatures indexed in reputable databases was performed. After obtaining the results via screening using PRISMA flow diagram, a total of 35 articles met the inclusion criteria and formed the basic structure of the study objectives. Results: The results revealed that, the worldwide pooled COVID-19 vaccine hesitancy rate was (x̅%)=29.8% (95% CI 23.37–36.23) among students. According to the country count assessment, the pooled vaccine hesitancy has been found to be ups and downs across the countries around the world such as (x̅%)=32% (95% CI 20.04–43.97) in Asia, (x̅%)=(28.11%, 95% CI 18.83–37.40) in the United States, (x̅%)=15.59% (95% CI 8.23–22.95) in Europe, (x̅%)=55.93% (95% CI 40.31–71.55) in Africa, (x̅%)=20.4% in North America, and (x̅%)=22.5% in multi-ethnic areas in the reported student’s COVID-19 vaccine hesitancy. In total, 10 key factors were identified. “Side effect” 45.41% (95% CI 29.68–61.14), “safety” 42.27% (95% CI 27.50–57.04), and “trust” 44.95%, (95% CI 26.51–63.39) were the overarching concerns in making students' vaccination decisions. Conclusions: The prevalence of COVID-19 vaccine hesitancy varied among the students; however, vaccine acceptance or refusal relies on several socio-psychological, societal, and vaccine related factors. This study helps the vaccine policy-makers and health stakeholders gain a better understanding of COVID-19 vaccination drive and design the vaccine promotion strategies. Health educational interventions could be the most preferred approach to improve student’s adherence and knowledge about the COVID-19 vaccination consequences.", "keywords": [ "COVID-19", "vaccine hesitancy", "acceptance", "students", "global" ], "content": "Introduction\n\nThe morbidity and mortality caused by coronavirus disease 2019 (COVID-19) has led to an unusual health burden across the countries and recognized as a global health warning, and it is not over yet. The World Health Organization (WHO) and public health expertise suggested non-pharmaceutical health measures and non-therapeutic managements for reducing rapid contamination of the novel coronavirus. Alongside, an unprecedented effort from the global scientific community has been paid to discover a new vaccine quickly because vaccines are the most promising and cost-effective health intervention that mitigates the viral infection. Noticeably, mass vaccination has proven its applicability in gradual silencing of pandemic and epidemic since last five decades.1 The Centers for Disease Control and Prevention (CDC) has declared vaccination as one of the ten public health achievements.2 However, the optimization of country-wide vaccination coverage largely depends on the vaccine acceptability among various population subgroups, particularly in students who are more vulnerable due to their active lifestyle and perception of invulnerability.\n\nDespite significant immunization advances in the 21st century around the world, there are still significant obstacles to COVID-19 vaccine in the vaccine- based intervention worldwide and one of which is hesitancy or low vaccine acceptance intention. Vaccine hesitancy is characterized by delay in accepting, hesitation, or rejection of vaccine despite the vaccination services being available.3 More specifically, vaccine hesitancy is expressed in “5C” sequences point to confidence, complacency, convenience, communication, and context.4 Accordingly, the World Health Organization declared the vaccine hesitancy as one of the top ten therapeutic challenges.5 Even prior to the pandemic vaccine hesitancy due to social and behavioral influences was identified as health threat5 and this concern is growing for COVID-19 vaccination because vaccine acceptance and hesitancy remarkably varied among various population sub-groups, with substantial regional variability.6\n\nWorldwide, the low vaccine uptake intention or hesitancy towards a particular vaccine has been recognized the most common phenomenon among the student groups in previous vaccination programs such as for influenza vaccination,7–11 human papilloma virus (HPV) vaccination,12–16 hepatitis B vaccinations,17,18 pertussis vaccinations,19 HIV vaccinations,20 measles vaccinations,21 and now COVID-19 vaccinations.22\n\nIn context of current COVID-19 pandemic, most of the review studies on vaccine hesitancy were conducted by analyzing the general population sample23–29 and few emphasized the regional locations.30–32 Although a study attempted to illustrate the COVID-19 vaccine hesitancy among health care student trainees;33 there is lack of evidence that concentrated to assess COVID-19 vaccine hesitancy among the students globally. Hence, this systematic review aimed to examine global COVID-19 vaccine hesitancy among students, and to identify an up-to-date and concise assessment of most common factors influencing vaccine acceptance and hesitancy around the world.\n\n\nMethods\n\nTo fine-tune the study objectives, we investigated the popular peer-reviewed databases for summarizing COVID-19 vaccine hesitancy among students. The Preferred Reporting Items for Systematic Reviews and Meta Analyses-(PRISMA) 2020 statement34 flow diagram was employed for screening procedure of databases as well as for the course of literatures selections. Four bibliographic databases (Pub Med, Embase, Science Direct and Google Scholar) were searched to retrieve studies related to COVID-19 vaccine hesitancy and acceptance among students.\n\nThe literature search inclusion criteria were the followings: 1) peer-reviewed articles published from four major databases; 2) quantitative survey studies involving student groups as sample population; 3) address the scope and principal aim of the study; 4) original research focused COVID-19 vaccine hesitancy; and 5) English language used in the publication. On the other hand, we track the following exclusion criteria: 1) unpublished manuscripts; 2) publication with lack of required original data; 3) students were not the sample population; 4) articles focused non-COVID-19 vaccine hesitancy; 5) publications other than original research; and 6) publication language was not English. The search period for the review spanned between November 2021 and December 2021.\n\nThe permission to conduct this review was obtained from “Ethical Review Committee” (IRC), Faculty of Biological Science and Technology, Jashore University of Science and Technology, Bangladesh. Since no clinical intervention was applied to the subject, the study was not required for ethical approval, although we informed the review matter to the IRC; however considering all issues the IRC opined not to require further approval.\n\nThe review protocol sets out the methods to be used in the review and provides an explicit plan. Decisions about the review question, inclusion criteria, search strategy, study selection, data extraction, quality assessment, data synthesis, and plans for dissemination was addressed by the authors collaboratively. The review protocol was further assessed by the IRC, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Bangladesh. Three major themes such as COVID-19 vaccine, vaccine hesitancy, and vaccine acceptance were used to develop search protocol. The key predictive items associated with vaccine hesitancy was conceptualized around COVID-19 vaccines in global perspectives.6 The search items we used in this study were adopted from the theory analysis of prior systematic analysis that evaluated non-COVID-19 vaccine hesitancy around the world35–40 The literature search for peer-reviewed articles was conducted by using the following keywords: (“novel coronavirus” OR “coronavirus 2019” OR “COVID 2019” OR “COVID19” OR “COVID-19” OR “SARS-CoV-2” OR “HCoV-19” OR “2019-nCoV” OR “severe acute respiratory syndrome corona virus 2”) AND (vaccine * OR immunization) AND (hesitancy * OR reluctance * OR acceptance) AND (student * OR educational sector). The Cochrane collaboration’s review team was formed for assessing the risk of biases and reports the assessment protocol that ensure the process become more accurate. The team attempted to identify, appraise, and synthesize all the empirical evidence that met pre-specified eligibility criteria. The first three independent reviewers conducted preliminary pilot study for screening of first 55 articles based on the titles and abstracts. The same reviewers independently performed screening of the titles and abstracts of all retrieved articles from selected databases. The potentially relevant articles were evaluated for full-text analysis prior to inclusion in the synthesis process. Disagreements raised in inclusion phase of review process were critically evaluated to attain consent. The fourth and fifth reviewer acted as an independent mediator for such disagreements which could not be resolved between first two reviewers. The critical appraisal of study outcomes was evaluated and the expected outcome measures of the study were COVID-19 vaccine hesitant population, associated factors, and the number of population identify the factors.\n\nMicrosoft excel data collection sheet was prepared by two authors. The sheet was critically evaluated, reviewed, and approved by third and fourth reviewer to chart the data from included articles. Qualitative method was employed to synthesize the study outcomes. The data were extracted by two authors independently while the third and fourth author reviewed the synthesized data placed in excel sheet. The filled data sheet comprised the key information included author (s) name, study type, study title, year of publication, sample size, population characteristics, study design, and the analytical approach used in the respective studies. Descriptive statistics described percentage and weighted frequencies the study samples. Mean (x̅), standard deviation (SD), and standard error (SE) were calculated to estimate 95% confidence interval (CI).\n\n\nResults\n\nThe initial search results retrieved 63 studies from the selected databases. Additionally 3 survey articles were identified from reference lists included in the review process. The search results also included letters, commentary, viewpoints, and conferences that needed to exclude from the review. The review process is shown in Figure 1. In the initial phase and before screening 4 duplicate articles, 3 commentaries, 2 letters, and 2 viewpoints were identified and took away from the procedure while 55 articles were screened. After careful screening the abstract, 6 articles were removed at the eligibility assessment step. The remaining 49 articles were analyzed for full-text; however, to comply with the study objectives the independent reviewer excluded 14 articles because these articles lack the required data. Finally, 35 peer-reviewed articles were selected to include in this study for rationalizing the study objectives. A collaborative editorial team led by the most senior author assesses the risk of associated biases which may occur in the included studies.\n\nMost of the studies included in this systematic review were carried out when the COVID-19 vaccination has started in the respective country context. The study reduced ambiguity in sample population selection and considered the risk of introducing spectrum bias when selecting study population. The highest number of the studies (n=9) that included in this study were carried out in the USA. From China, 6 studies were included; 3 studies were conducted in Italy, 1 study in France, India, Uganda, Israel, Egypt, Zambia, Poland, Kuwait, Jordan, Czech Republic, Lebanon, Kazakhstan, Nigeria, Saudi Arabia, Bangladesh, Canada, and Romania. One included study represented 22 country populations in multi-ethnicity. The participants were under-graduate and postgraduate students of diverse educational institutes and branches worldwide. Among these student diversities, 10 studies were conducted on university students, 9 studies were conducted on medical students, 7 studies were college students, 2 studies were dental students, 2 studies were nursing students and health care students of each, 1 study was carried out in combined sample of medical and nursing students, 1 multi-ethnic study represented combination of medical and dental students, 1 study conducted among pharmacy students and another 1 study was conducted among the international college students. The collaborative team evaluated individual synthesis for assessing the risk of reporting bias raised from missing values.\n\nThe overall vaccine hesitancy rate synthesized from eligible 35 articles41–75 is shown in Table 1. The percentage mean value of the hesitant students was (x̅ %)=29.80 (95% CI 23.37–36.23) and the mean respondents value was (x̅)=341.81 (95% CI 217.76–465.86) while the total population mean was (X)= 1290.58. The highest value of the percent hesitant was reported (xh)=75.6 (95% CI 73–78) and the lowest value reported 3 (95% CI 1–5) among the studied articles.\n\nTable 2 summarizes and describes the mode of distribution frequency of hesitancy rate around the world. In Asian countries, we analyzed 13 articles (n=13) in which the percentage mean value of the hesitant students was (x̅%)=32 (95% CI 20.04-43.97) and the mean respondents value was (x̅)=347.31 (95% CI 203.81–490.81) while the total population mean was (X)= 1288.77. The highest value of the percent hesitant was reported (xh)=75.6 (95% CI 73–78) and the lowest value was=(xl) 9.6 (95% CI 5.6–13.6) in Asian countries. The synthesized results obtained in the United States (n=9; x̅%=28.11, 95% CI 18.83-37.40;x̅=136.5, 95% CI 63.54–209.46;xh%= 47.5,95% CI 63.54–209.46; xl%=3, 95% CI 1–5 and X̅=511.3), in Europe (n=7; x̅%=15.59, 95% CI 8.23–22.95; x̅=413.29, 95% CI 216–824.42; xh%= 29, 95% CI 28–30; xl%=5.27, 95% CI 3–7; X̅=1883.86), in Africa (n=4; x̅%=55.93, 95% CI 40.31–71.55; x̅=444.75, 95% CI 85.12–804.38; xh%= 75, 95% CI 70–80; xl%=40, 95% CI 35–45; X̅=874.75), in North America (n=1; x̅%=20.4; x̅=259; xh%= 20.4; xl%=20.4; X̅=1269) and, in multi-ethnic areas (n=1; x̅%=22.5; x̅=1494; xh%= 22.5; xl%=22.5; X̅=6639).\n\nThe most frequently identified factors in vaccination decision are illustrated in Table 3. In total 10 potential factors were identified from our studied articles. Among these key factors “side effect” was identified from the highest count in 15 articles (n=15) in which the percentage mean value of the student respondents was (x̅%)=45.41 (95% CI 29.68–61.14), the mean respondents was (x̅)= 623.87 (95% CI 153.16–1094.58), and the total population mean was (X̅)= 1484.13. The highest value represented side effect reported (ch%)=96.8 (95% CI 96.3–97.7) while the lowest was (cl%)=1.15 (95% CI 1.15–1.95). The second highest count (n=13) was recognized for “safety” (n=13; x̅%=42.27 95% CI 27.50–57.04); x̅=451.92 95% CI 122.37–781.48; X̅=1285.62; ch%=84.3 95% CI 80.3–88.3; cl%=4.3 95% CI 3.8–4.8), followed by “trust” (n=9; x̅%=44.95, 95% CI 26.51–63.39; x̅=414.44, 95% CI -12.51–841.39; X̅=1189; ch%= 89, 95% CI 85-93–cl%=10.6, 95% CI 8.6–12.6), “information sufficiency” (n=6; x̅%=47.05 95% CI 25.45–68.65; āx̅=715.5, 95% CI 9.93–1421.07; X̅=1672.67; ch%= 77.3, 95% CI 72.3–82.3; cl%=16, 95% CI 11–21), “effectiveness” (n=6; x̅%=46.22, 95% CI 19.26–73.19; x̅=708.17, 95% CI 3.81–1412.53; X̅=991.17; ch%= 93.2 95% CI 92–94; cl%=10.2, 95% CI 7.2–13.2), “efficacy” (n=4; x̅%=24.97 95% CI -12.36–62.30; x̅=179.67, 95% CI -16.00–375.34; āX̅=1585.67; ch%=62.7 95% CI 58.7–66.7; cl%=1.6 95% CI 1.2–2), “vaccine mandate” (n=3; x̅%=52.7 95% CI 9.13–96.27; x̅=124.67 95% CI 16.13–233.21; X̅=217.33; ch%= 85, 95% CI 80–90; cl%=10.1, 95% CI 5.1–15.1), “social influence” (n=2; x̅%=33.98 95% CI -31.53 – 99.49; x̅=92 95% CI -55– 239; X̅=1668.5; ch%= 67.4, 95% CI 62.4–72.4; cl%=0.55, 95% CI 0.2 – 0.8), “conspiracy beliefs” (n=2; x̅%=17.15 95% CI 14.31–19.99; x̅=258 95% CI 156.08 – 359.92; X̅=1538.5; ch%= 18.6, 95% CI 16.6–20.6; cl%=15.7, 95% CI 13.7–17.7), and “religiosity” (n=1; x̅%=12.3; x̅=817; X̅=6639).\n\nIn Figure 2, we represented a graphical view of the overall study outcomes that we have extracted and summarized from included eligible articles.\n\n\nDiscussion\n\nThe COVID-19 pandemic not only has destroyed the economic development, health systems, and transport but also the education system was brutally affected worldwide. Despite a widespread discussion about the effect of pandemic on economy and health system, the catastrophic impact of lethal coronavirus on education system has yet to draw the attention of the world’s community to a large extent. Most developed nations have succeeded in overcoming the disastrous impact of this virus through the online transformation of their traditional education system and rapid vaccination coverage to the students because the ratio of vaccine coverage is comparatively higher in developed countries than that of developing nation.76 Vaccine hesitancy or vaccine refusal is not an old phenomenon; rather, it is dynamic and heterogeneous concept sharply regulated by multi-faceted events of socio-psychological, societal, and behavioral characteristics.35 Ensuring the equitable vaccine coverage among different population groups is facing challenges because public perceptions on vaccination may alter over time and disease backdrop.77 Even for national immunization programs, the psychological behaviors explaining vaccine uptake intention is almost similar as in pandemic crisis.78 Acceptability of a newly promoted vaccine is the prime indicator of a successful vaccination drive while at the same time vaccine may economically costly and the equal distribution would time consuming process.79 As such, synthesizing and summarizing the global COVID-19 vaccine hesitancy in student groups would be an effective step to formulate the strategies that boost mass vaccination programs by reducing COVID-19 vaccine hesitancy. This study thus investigated global COVID-19 vaccine hesitancy in students and explored the potential factors associated with it. During the early days of vaccination, a smear campaign was set out to embarrass the health policy makers and many groups intentionally aired different propaganda about vaccine origin and vaccines data. Consequently, globally, a significant portion of population in different geographical locations remained confused about whether they should accept or reject COVID-19 vaccine. Recently a systematic review reported that, 40% sample population had the hesitancy or refusal intention in accepting a COVID-19 vaccine.80 In our study, the pooled COVID-19 vaccination hesitancy rate was identified 30% among students globally. Since the selected study population was students, who are resourceful in accessing the updated vaccine information. Therefore, a relatively low hesitancy rate was observed in student’s cohort compared to the general population in prior study. Since 2014, hesitancy towards a particular vaccine has increased exponentially in more than 90% countries of the world.81 The current study findings indicated that, the overwhelming majority of the hesitant students need to integrate into mass vaccination process, otherwise global attempts to provide free vaccines may not be effective in preventing COVID-19 transmission and morbidity.\n\nSeveral factors potentially contributed to the vaccination decision and plays a role in individual’s behavior to refuse, delay, or accept vaccines reported in previous measles and pertussis outbreak82 and now for COVID-19 vaccination consequences6. This study deduced vaccine safety, side effects, and trust were the most common factors responsible for student’s COVID-19 vaccine acceptance and hesitancy. Several scientific studies explained previous vaccination progress reported same factors as the vaccine predictive concerns. For example, a comprehensive review synthesized data from 2,791 studies published between 1990 and 2019 concluded that, safety was the principal predictor of vaccine refusal alongside with disease severity, culture, and contextual determinants.83 In the same manner, side effects and safety were the primary considerations in vaccine receiving decision by the general people and health care professionals retrieved from 1,187 articles focused on global HPV and flu vaccinations.84 Similarly, Karafillakis and Larson (2017) argued that, among others vaccine safety and efficacy were the highest concerns in making vaccination decision since 2004 to 2014 among the English, French, and Spanish nations.85\n\nTrust plays a key role in modifying the public behaviors toward vaccine apprehension because restoring public trust would lead to COVID-19 vaccine confidence.86 When the public trusted that, the prospective vaccines would be safe and effective after inoculation vaccine confidence would be built. This growing confidence was the greatest forecaster in making vaccine uptake decision by the public.87 As a result, trust has been recognized as one of the most important predictors of vaccine acceptance in low and middle income countries.88 Alternatively, distrust of and misinformation about the vaccines, and the government agencies regarding the vaccination process significantly reduced the vaccine acceptance rate.89 Hence, building public trust and confidence in health systems would be the key solutions for reducing COVID-19 vaccine hesitancy. It is also important that, evidence-based information need to be provided by the independent expert groups for tracking and tackling of fake news about the vaccines already circulated to the general people.\n\nThis study addressed some limitations. The foremost limitation of this study was inadequate sample size, because we synthesized limited number of scholarly articles included in analytical estimation purpose. A lot of peer-reviewed articles have been published in the current COVID-19 vaccine context. As a result, there is a possibility for those articles in which the student participants might have been more accepting or hesitant than our included studies. Secondly, most of the analyzed articles were cross-sectional types, thus provided snapshots of hesitancy status in each country. Actually, it is absolutely challenging to predict in-spot vaccine perceptions among people because vaccine apprehension may depend on disease backdrop and it can alter over time.77 Thirdly, we have documented few selective factors of COVID-19 vaccine acceptance and hesitancy in students; however, this may differ from behavioral context. Due to the disease severity, perceived health risk, pandemic backdrop, and approval of new COVID-19 vaccines the possibility of temporal changes in factors associated with COVID-19 vaccinations would take place. Finally, there are some additional key factors including rumors90,91 observed in Asian continents were truly unidentified in this study.\n\nGiven the prevalence of vaccine hesitancy and potential influential factors of COVID-19 vaccinations, the educational policy makers should develop strategies that compliance with the adherence, attitude, and knowledge about vaccination consequences among the students group. This study acts as scientific evidence for initiating further predictive studies of COVID-19 vaccine acceptance and hesitancy among students by examining the association between vaccine acceptance and other explanatory variables. Since educational contents aimed to improve infectious disease awareness among students would be beneficial,92 hence the advancement of effective health education in a multi-disciplinary approach would be imperative to emphasize personal relevance of the disease and to improve vaccine related knowledge among the students. The authors believe that, the study findings largely benefits the health policy makers, stakeholders, and the vaccine promoters in different parts of the world to design an evidence-based vaccine promotion strategy seeking to influence the vaccination policy implication in pandemic and post pandemic era.\n\n\nConclusions\n\nSince COVID-19 vaccine availability does not guarantee uptake, so examining COVID-19 vaccine hesitancy among students and identifying the factors associated with vaccine acceptance and hesitancy is a fundamental task that must be undertaken to guarantee an effective immunization plan. This study investigated global COVID-19 vaccine hesitancy among the students and concluded that the vaccine hesitancy was higher in African countries followed by Asia, the United States and Europe. Although the prevalence of COVID-19 vaccine hesitancy varied among the higher education students globally; vaccine acceptance relies on several common factors related to socio-psychological and the vaccine itself. In this study, we identified 10 potential concerns related to vaccine uptake and refusal intention in students, among which side effect, safety, trust, and information sufficiency were the most prominent concerns of COVID-19 vaccination decision among students. Hence, the scientific community must ensure the safety confirmation, side-effect free remedy, rapid response against disease; provide long-term therapeutic benefit, and acquisition of required immunity to encounter the perceived challenges in successful vaccination programs. In addition, the manufacturers need to produce adequate vaccine doses and distributed vaccines equally across the countries. Public perceptions are likely to be changed as more vaccine related safety and efficacy data become largely available and convey the information to people through effective communication and trustworthy approach. COVID-19 vaccine information regarding side effects, safety, and efficacy as well as the communicative roles of the media is essential for improving vaccine trust among the students. Application of useful communication channels and educational interventions would contribute to remove anti-vaccination sentiments and rumors thereby enhancing vaccine uptake willingness among students. Effective policy directions for pandemic management and vaccination consequences in the academic curricula would shape and influence education community to enhance student’s health engagement in infectious disease awareness and vaccine readiness. Therefore, addressing COVID-19 vaccine hesitancy among students and enlisting the factors associated with vaccine acceptance and hesitancy is a fundamental assignment that must be undertaken to guarantee an immunization plan throughout the country. The study findings thus help the researchers, policymakers, and administrators gain a better understanding of vaccination drive among students and call for further implementation of multi-disciplinary educational intervention within the academic curricula.\n\n\nData availability\n\nNo data are associated with this article.\n\nFigshare: PRISMA checklist for ‘Prevalence of COVID-19 vaccine hesitancy in students: A global systematic review’. https://doi.org/10.6084/m9.figshare.20366712.93\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nConsent\n\nThe authors confirm that, we have obtained signed consent from the participants included in the graphical presentation (Figure 2) to exploit images in the article. Also, the graphical presentation contained no reproduced copyrighted materials from other sources while the image was self-generated by the authors.", "appendix": "Acknowledgements\n\nAll authors are greatly acknowledging to Dr. Koshor Mazumder, Department of Pharmacy, Jashore University of Science and Technology, Jashore, Bangladesh for the helpful comments and suggestions provided for the manuscript. Authors confirm that, this person agreed to be acknowledged in this section of the article.\n\n\nReferences\n\nMartin B: Vaccination education subordinated to campaigning.\n\nKoppaka R: Ten great public health achievements--United States, 2001-2010.2011.\n\nSoares P, Rocha JV, Moniz M, et al.: Factors associated with COVID-19 vaccine hesitancy. Vaccines. 2021 Mar; 9(3): 300. PubMed Abstract \| Publisher Full Text\n\nRazai MS, Oakeshott P, Esmail A, et al.: COVID-19 vaccine hesitancy: the five Cs to tackle behavioural and sociodemographic factors. J. R. Soc. Med. 2021 Jun 1; 114: 295–298. Publisher Full Text\n\nWorld Health Organization: Ten threats to global health in 2019. [cited 2022 March 29].Reference Source\n\nRoy DN, Biswas M, Islam E, et al.: Potential factors influencing COVID-19 vaccine acceptance and hesitancy: A systematic review. PLoS One. 2022 Mar 23; 17(3): e0265496. PubMed Abstract \| Publisher Full Text\n\nAbalkhail MS, Alzahrany MS, Alghamdi KA, et al.: Uptake of influenza vaccination, awareness and its associated barriers among medical students of a University Hospital in Central Saudi Arabia. J. Infect. Public Health. 2017; 10(5): 644–648. PubMed Abstract \| Publisher Full Text\n\nCheung K, Ho SMS, Lam W: Factors affecting the willingness of nursing students to receive annual seasonal influenza vaccination: A large-scale cross-sectional study. Vaccine. 2017; 35(11): 1482–1487. PubMed Abstract \| Publisher Full Text\n\nBednarczyk RA, Chu SL, Sickler H, et al.: Low uptake of influenza vaccine among university students: evaluating predictors beyond cost and safety concerns. Vaccine. 2015; 33(14): 1659–1663. PubMed Abstract \| Publisher Full Text\n\nBenjamin SM, Bahr KO: Barriers associated with seasonal influenza vaccination among college students. Influenza Research and Treatment. 2016; 2016: 1–5. PubMed Abstract \| Publisher Full Text\n\nHashmi S, D'Ambrosio L, Diamond DV, et al.: Preventive behaviors and perceptions of influenza vaccination among a university student population. J. Public Health. 2016; 38(4): 739–745. PubMed Abstract \| Publisher Full Text\n\nShetty S, Prabhu S, Shetty V, et al.: Knowledge, attitudes and factors associated with acceptability of human papillomavirus vaccination among undergraduate medical, dental and nursing students in South India. Hum. Vaccin. Immunother. 2019; 15(7-8): 1656–1665. PubMed Abstract \| Publisher Full Text\n\nPelullo CP, Esposito MR, Di Giuseppe G: Human papillomavirus infection and vaccination: knowledge and attitudes among nursing students in Italy. Int. J. Environ. Res. Public Health. 2019; 16(10): 1770. PubMed Abstract \| Publisher Full Text\n\nJuntasopeepun P, Suwan N, Phianmongkhol Y, et al.: Factors influencing acceptance of human papillomavirus vaccine among young female college students in Thailand. Int. J. Gynecol. Obstet. 2012; 118(3): 247–250. PubMed Abstract \| Publisher Full Text\n\nDonadiki E, Jiménez-García R, Hernández-Barrera V, et al.: Health Belief Model applied to non-compliance with HPV vaccine among female university students. Public Health. 2014; 128(3): 268–273. PubMed Abstract \| Publisher Full Text\n\nDonadiki EM, Jiménez-García R, Hernández-Barrera V, et al.: Knowledge of the HPV vaccine and its association with vaccine uptake among female higher-education students in Greece. Hum. Vaccin. Immunother. 2013; 9(2): 300–305. PubMed Abstract \| Publisher Full Text\n\nWibabara Y, Banura C, Kalyango J, et al.: Hepatitis B vaccination status and associated factors among undergraduate students of Makerere University College of Health Sciences. PLoS One. 2019; 14(4): e0214732. PubMed Abstract \| Publisher Full Text\n\nSajid M, Jamil M, Javed M: VACCINATION STATUS OF DENTAL STUDENTS OF MULTAN DENTAL COLLEGE MULTAN AGAINST HEPATITIS B VIRUS. Pakistan Oral & Dental Journal. 2018; 38(4): 513–515.\n\nBöhme M, Voigt K, Balogh E, et al.: Pertussis vaccination status and vaccine acceptance among medical students: multicenter study in Germany and Hungary. BMC Public Health. 2019; 19(1): 1–10. Publisher Full Text\n\nRavert RD, Zimet GD: College student invulnerability beliefs and HIV vaccine acceptability. Am. J. Health Behav. 2009; 33(4): 391–399. PubMed Abstract\n\nYörük S: Factors associated with childhood vaccine hesitancy and measles vaccine hesitancy among healthcare students. Nurs. Health Sci. 2020; 22(4): 1030–1037. PubMed Abstract \| Publisher Full Text\n\nAl-Mulla R, Abu-Madi M, Talafha QM, et al.: COVID-19 vaccine hesitancy in a representative education sector population in Qatar. Vaccines. 2021; 9(6): 665. PubMed Abstract \| Publisher Full Text\n\nBiswas M, Alzubaidi MS, Shah U, et al.: A scoping review to find out worldwide COVID-19 vaccine hesitancy and its underlying determinants. Vaccines. 2021; 9(11): 1243. PubMed Abstract \| Publisher Full Text\n\nSallam M: COVID-19 vaccine hesitancy worldwide: a concise systematic review of vaccine acceptance rates. Vaccines. 2021; 9(2): 160. PubMed Abstract \| Publisher Full Text\n\nAbdulmoneim SA, Aboelsaad IAF, Hafez DMH, et al.: Systematic Review and Meta-analysis on COVID-19 Vaccine Hesitancy. medRxiv. 2021.\n\nSalomoni MG, Di Valerio Z, Gabrielli E, et al.: Hesitant or not hesitant? A systematic review on global COVID-19 vaccine acceptance in different populations. Vaccines. 2021; 9(8): 873. PubMed Abstract \| Publisher Full Text\n\nCascini F, Pantovic A, Al-Ajlouni Y, et al.: Attitudes, acceptance and hesitancy among the general population worldwide to receive the COVID-19 vaccines and their contributing factors: A systematic review. EClinicalMedicine. 2021; 40: 101113. PubMed Abstract \| Publisher Full Text\n\nNehal KR, Steendam LM, Campos Ponce M, et al.: Worldwide vaccination willingness for COVID-19: a systematic review and meta-analysis. Vaccines. 2021; 9(10): 1071. PubMed Abstract \| Publisher Full Text\n\nHrynick T, Schmidt-Sane M, Ripoll S: Rapid review: vaccine hesitancy and building confidence in COVID-19 vaccination.2020.\n\nAw J, Seng JJB, Seah SSY, et al.: COVID-19 vaccine hesitancy—A scoping review of literature in high-income countries. Vaccines. 2021; 9(8): 900. PubMed Abstract \| Publisher Full Text\n\nKhubchandani J, Macias Y: COVID-19 vaccination hesitancy in Hispanics and African-Americans: a review and recommendations for practice. Brain, behavior, & immunity-health. 2021; 15: 100277. PubMed Abstract \| Publisher Full Text\n\nWang Y, Liu Y: Multilevel determinants of COVID-19 vaccination hesitancy in the United States: a rapid systematic review. Prev. Med. Rep. 2021; 25: 101673–101673. PubMed Abstract \| Publisher Full Text\n\nMustapha T, Khubchandani J, Biswas N: COVID-19 vaccination hesitancy in students and trainees of healthcare professions: A global assessment and call for action. Brain, Behavior, & Immunity-Health. 2021; 16: 100289. PubMed Abstract \| Publisher Full Text\n\nPage MJ, McKenzie JE, Bossuyt PM, et al.: The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021; 372: n71. PubMed Abstract \| Publisher Full Text\n\nLarson HJ, Jarrett C, Eckersberger E, et al.: Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: a systematic review of published literature, 2007–2012. Vaccine. 2014; 32(19): 2150–2159. PubMed Abstract \| Publisher Full Text\n\nJarrett C, Wilson R, O’Leary M, et al.: Strategies for addressing vaccine hesitancy–A systematic review. Vaccine. 2015; 33(34): 4180–4190. PubMed Abstract \| Publisher Full Text\n\nTruong J, Bakshi S, Wasim A, et al.: What factors promote vaccine hesitancy or acceptance during pandemics? A systematic review and thematic analysis. Health Promot. Int. 2021; 37. Publisher Full Text\n\nSchmid P, Rauber D, Betsch C, et al.: Barriers of influenza vaccination intention and behavior–a systematic review of influenza vaccine hesitancy, 2005–2016. PLoS One. 2017; 12(1): e0170550. PubMed Abstract \| Publisher Full Text\n\nDubé E, Gagnon D, MacDonald NE: Strategies intended to address vaccine hesitancy: Review of published reviews. Vaccine. 2015; 33(34): 4191–4203. PubMed Abstract \| Publisher Full Text\n\nDubé E, Laberge C, Guay M, et al.: Vaccine hesitancy: an overview. Hum. Vaccin. Immunother. 2013; 9(8): 1763–1773. PubMed Abstract \| Publisher Full Text\n\nJain J, Saurabh S, Goel AD, et al.: COVID-19 vaccine hesitancy among undergraduate medical students: results from a nationwide survey in India. medRxiv. 2021.\n\nRosental H, Shmueli L: Integrating Health Behavior Theories to Predict COVID-19 Vaccine Acceptance: Differences between Medical Students and Nursing Students. medRxiv. 2021:2021.05.18.21257416.\n\nAlali WQ, AlFouzan W, Aljimi D, et al.: Perception and awareness of COVID-19 among health science students and staff of Kuwait University: An online cross-sectional study. medRxiv. 2021. 2020.12.26.20248891.\n\nSallam M, Dababseh D, Eid H, et al.: Low COVID-19 vaccine acceptance is correlated with conspiracy beliefs among university students in Jordan. Int. J. Environ. Res. Public Health. 2021; 18(5): 2407. PubMed Abstract \| Publisher Full Text\n\nBai W, Cai H, Liu S, et al.: Attitudes toward COVID-19 vaccines in Chinese college students. Int. J. Biol. Sci. 2021; 17(6): 1469–1475. PubMed Abstract \| Publisher Full Text\n\nHamdan MB, Singh S, Polavarapu M, et al.: COVID-19 vaccine hesitancy among university students in Lebanon. Epidemiol. Infect. 2021; 149. Publisher Full Text\n\nGao X, Li H, He W, et al.: COVID-19 Vaccine Hesitancy Among Medical Students: The Next COVID-19 Challenge in Wuhan, China. Disaster Med. Public Health Prep. 2021; 1-6: 1–6. Publisher Full Text\n\nLi M, Zheng Y, Luo Y, et al.: Hesitancy toward COVID-19 vaccines among medical students in Southwest China: a cross-sectional study. Hum. Vaccin. Immunother. 2021; 17: 4021–4027. Publisher Full Text\n\nBolatov AK, Seisembekov TZ, Askarova AZ, et al.: Barriers to COVID-19 vaccination among medical students in Kazakhstan: development, validation, and use of a new COVID-19 Vaccine Hesitancy Scale. Hum. Vaccin. Immunother. 2021; 17: 4982–4992. Publisher Full Text\n\nJiang N, Wei B, Lin H, et al.: Nursing students’ attitudes, knowledge and willingness of to receive the coronavirus disease vaccine: A cross-sectional study. Nurse Educ. Pract. 2021; 55: 103148. PubMed Abstract \| Publisher Full Text\n\nWalker AN, Zhang T, Peng X-Q, et al.: Vaccine acceptance and its influencing factors: an online cross-sectional study among international college students studying in China. Vaccines. 2021; 9(6): 585.\n\nAlmalki MJ, Alotaibi AA, Alabdali SH, et al.: Acceptability of the COVID-19 vaccine and its determinants among university students in Saudi Arabia: a cross-sectional study. Vaccines. 2021; 9(9): 943. Publisher Full Text\n\nHossain ME, Islam MS, Ghose TK, et al.: COVID-19 vaccine acceptability among public university students in Bangladesh: Highlighting knowledge, perceptions, and attitude. Hum. Vaccin. Immunother. 2021; 17: 5089–5098. Publisher Full Text\n\nSilva J, Bratberg J, Lemay V: COVID-19 and influenza vaccine hesitancy among college students. J. Am. Pharm. Assoc. 2021; 61(6): 709–714.e1. PubMed Abstract \| Publisher Full Text\n\nManning ML, Gerolamo AM, Marino MA, et al.: COVID-19 vaccination readiness among nurse faculty and student nurses. Nurs. Outlook. 2021; 69(4): 565–573. PubMed Abstract \| Publisher Full Text\n\nLucia VC, Kelekar A, Afonso NM: COVID-19 vaccine hesitancy among medical students. J. Public Health. 2021; 43(3): 445–449. PubMed Abstract \| Publisher Full Text\n\nMascarenhas AK, Lucia VC, Kelekar A, et al.: Dental students’ attitudes and hesitancy toward COVID-19 vaccine. J. Dent. Educ. 2021; 85(9): 1504–1510. PubMed Abstract \| Publisher Full Text\n\nKelekar AK, Lucia VC, Afonso NM, et al.: COVID-19 vaccine acceptance and hesitancy among dental and medical students. J. Am. Dent. Assoc. 2021; 152(8): 596–603. PubMed Abstract \| Publisher Full Text\n\nSharma M, Davis RE, Wilkerson AH: COVID-19 vaccine acceptance among college Students: a theory-based analysis. Int. J. Environ. Res. Public Health. 2021; 18(9): 4617. PubMed Abstract \| Publisher Full Text\n\nTam CC, Qiao S, Li X: Factors associated with decision making on COVID-19 vaccine acceptance among college students in South Carolina. Psychol. Health Med. 2022/01/02 2022; 27(1): 150–161. PubMed Abstract \| Publisher Full Text\n\nKevin C: College students' COVID-19 vaccine hesitancy. Synnott, CK (2021) College Students' COVID-19 Vaccine Hesitancy The Journal of Higher Education Management. 2021; 36(2): 152–159.\n\nQiao S, Tam CC, Li X: Risk exposures, risk perceptions, negative attitudes toward general vaccination, and COVID-19 vaccine acceptance among college students in South Carolina. medRxiv. 2020; 2020.11.26.20239483.\n\nTavolacci MP, Dechelotte P, Ladner J: COVID-19 vaccine acceptance, hesitancy, and resistancy among university students in France. Vaccines. 2021; 9(6): 654. PubMed Abstract \| Publisher Full Text\n\nSzmyd B, Bartoszek A, Karuga FF, et al.: Medical students and SARS-CoV-2 vaccination: attitude and behaviors. Vaccines. 2021; 9(2): 128. Publisher Full Text\n\nBarello S, Nania T, Dellafiore F, et al.: ‘Vaccine hesitancy’among university students in Italy during the COVID-19 pandemic. Eur. J. Epidemiol. 2020; 35(8): 781–783. PubMed Abstract \| Publisher Full Text\n\nPastorino R, Villani L, Mariani M, et al.: Impact of COVID-19 pandemic on flu and COVID-19 vaccination intentions among university students. Vaccines. 2021; 9(2): 70. PubMed Abstract \| Publisher Full Text\n\nRiad A, Pokorná A, Antalová N, et al.: Prevalence and drivers of COVID-19 vaccine hesitancy among Czech university students: National cross-sectional study. Vaccines. 2021; 9(9): 948. Publisher Full Text\n\nBaccolini V, Renzi E, Isonne C, et al.: COVID-19 Vaccine Hesitancy among Italian University Students: A Cross-Sectional Survey during the First Months of the Vaccination Campaign. Vaccines. 2021; 9(11): 1292. PubMed Abstract \| Publisher Full Text\n\nBălan A, Bejan I, Bonciu S, et al.: Romanian Medical Students’ Attitude towards and Perceived Knowledge on COVID-19 Vaccination. Vaccines. 2021; 9(8): 854. PubMed Abstract \| Publisher Full Text\n\nKanyike AM, Olum R, Kajjimu J, et al.: Acceptance of the coronavirus disease-2019 vaccine among medical students in Uganda. Tropical medicine and health. 2021; 49(1): 1–11. Publisher Full Text\n\nMudenda S, Mukosha M, Meyer JC, et al.: Awareness and Acceptance of COVID-19 Vaccines among Pharmacy Students in Zambia: The Implications for Addressing Vaccine Hesitancy.2021.\n\nMustapha M, Lawal BK, Sha’aban A, et al.: Factors associated with acceptance of COVID-19 vaccine among University health sciences students in Northwest Nigeria. PLoS One. 2021; 16(11): e0260672. PubMed Abstract \| Publisher Full Text\n\nSaied SM, Saied EM, Kabbash IA, et al.: Vaccine hesitancy: Beliefs and barriers associated with COVID-19 vaccination among Egyptian medical students. J. Med. Virol. 2021; 93(7): 4280–4291. PubMed Abstract \| Publisher Full Text\n\nMant M, Aslemand A, Prine A, et al.: University students’ perspectives, planned uptake, and hesitancy regarding the COVID-19 vaccine: A multi-methods study. PLoS One. 2021; 16(8): e0255447. PubMed Abstract \| Publisher Full Text\n\nRiad A, Abdulqader H, Morgado M, et al.: Global prevalence and drivers of dental students’ COVID-19 vaccine hesitancy. Vaccines. 2021; 9(6): 566. PubMed Abstract \| Publisher Full Text\n\nWHO: Rich countries should donate vaccines, not use boosters. The Times of India. Jul 14, 2021.Reference Source\n\nXiao J, Cheung JK, Wu P, et al.: Temporal changes in factors associated with COVID-19 vaccine hesitancy and uptake among adults in Hong Kong: Serial cross-sectional surveys. Lancet Reg Health West Pac. 2022 Mar 29; 23: 100441. PubMed Abstract \| Publisher Full Text\n\nDetermann D, Korfage IJ, Lambooij MS, et al.: Acceptance of vaccinations in pandemic outbreaks: a discrete choice experiment. PLoS One. 2014; 9(7): e102505. PubMed Abstract \| Publisher Full Text\n\nMahoney RT, Krattiger A, Clemens JD, et al.: The introduction of new vaccines into developing countries: IV: global access strategies. Vaccine. 2007; 25(20): 4003–4011. Publisher Full Text\n\nRobinson E, Jones A, Daly M: International estimates of intended uptake and refusal of COVID-19 vaccines: A rapid systematic review and meta-analysis of large nationally representative samples. Vaccine. 2021; 39(15): 2024–2034. PubMed Abstract \| Publisher Full Text\n\nLane S, MacDonald NE, Marti M, et al.: Vaccine hesitancy around the globe: Analysis of three years of WHO/UNICEF Joint Reporting Form data-2015–2017. Vaccine. 2018; 36(26): 3861–3867. PubMed Abstract \| Publisher Full Text\n\nPhadke VK, Bednarczyk RA, Salmon DA, et al.: Association between vaccine refusal and vaccine-preventable diseases in the United States: a review of measles and pertussis. JAMA. 2016; 315(11): 1149–1158. PubMed Abstract \| Publisher Full Text\n\nSweileh WM: Bibliometric analysis of global scientific literature on vaccine hesitancy in peer-reviewed journals (1990–2019). BMC Public Health. 2020; 20(1): 1–15. Publisher Full Text\n\nYaqub O, Castle-Clarke S, Sevdalis N, et al.: Attitudes to vaccination: a critical review. Soc. Sci. Med. 2014; 112: 1–11. Publisher Full Text\n\nKarafillakis E, Larson HJ: The benefit of the doubt or doubts over benefits? A systematic literature review of perceived risks of vaccines in European populations. Vaccine. Sep 5 2017; 35(37): 4840–4850. Publisher Full Text\n\nVerger P, Dubé E: Restoring confidence in vaccines in the COVID-19 era. Expert Rev. Vaccines. 2020 Nov 1; 19(11): 991–993. PubMed Abstract \| Publisher Full Text\n\nQuinn SC, Jamison AM, An J, et al.: Measuring vaccine hesitancy, confidence, trust and flu vaccine uptake: Results of a national survey of White and African American adults. Vaccine. 2019; 37(9): 1168–1173. PubMed Abstract \| Publisher Full Text\n\nLarson HJ, Clarke RM, Jarrett C, et al.: Measuring trust in vaccination: A systematic review. Hum. Vaccin. Immunother. 2018; 14(7): 1599–1609. PubMed Abstract \| Publisher Full Text\n\nHalpin C, Reid B: Attitudes and beliefs of healthcare workers about influenza vaccination. Nurs. Older People. Mar 22 2019; 31(2): 32–39. Publisher Full Text\n\nKanozia R, Arya R: “Fake news”, religion, and COVID-19 vaccine hesitancy in India, Pakistan, and Bangladesh. Media Asia. 2021 Sep 17; 48(4): 313–321. Publisher Full Text\n\nRoy DN, Huda MN, Azam MS: Factor’s influencing COVID-19 vaccine acceptance and hesitancy among rural community in Bangladesh: a cross-sectional survey based study. Hum. Vaccin. Immunother. 2022 May 6; 18: 1–9. Publisher Full Text\n\nShareef LG, Al-Hussainy AF, Hameed SM: COVID-19 vaccination hesitancy among Iraqi general population between beliefs and barriers: An observational study. F1000Research. 2022 Mar 18; 11(334): 334. PubMed Abstract \| Publisher Full Text\n\nRoy D: PRISMA_2020_checklist. figshare. [Dataset].2022. Publisher Full Text" }	[ { "id": "147408", "date": "30 Aug 2022", "name": "ASM Monjur Al Hossain", "expertise": [ "Reviewer Expertise Pharmaceutics", "Topical drug delivery", "public health", "Fungal disease" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nRelevance of the study: In the actual context, the paper presents theoretical and practical importance. It is quite interesting the analysis of the global vaccine hesitancy rate and the ten concerns which determine the acceptance or hesitancy towards the Covid-19 vaccines among students globally.\n\nAbstract: Well organized and concisely stated the review outcomes.\n\nIntroduction – Informative and properly contextualized the current research gap. It summarized relevant research to provide context and to explain the findings to others.\n\nLiterature cited– Adequately cited with appropriate kinds of literature in the current context, hence, no missing or incomplete citations were found. Authors paid appropriate credit to ideas, concepts and data that have been published recently.\n\nMethodologically, I am convinced that the search protocol had drawn strictly. The choice to include key terms is specific and accurately derived has been cited from the existing theory and explained in the protocol development section.\nThe shared PRISMA 2020 checklist provided unique information necessary in the manuscript writing and all PRISMA 2020 critical items for a systematic review have been addressed.\nAlthough it would be good to include a large sample size in data; this review included 35 articles which are acceptable. However, one question can be opened up? If you use any tools to calculate 95% confidence please include? Additionally, you can add an Ethical permission letter as supplementary data.\n\nConclusion – Strategically reflected the study findings and suggested the recommendation effectively.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? Yes\n\nAre the conclusions drawn adequately supported by the results presented in the review? Yes", "responses": [] }, { "id": "189170", "date": "28 Nov 2023", "name": "Jomell M Santiago", "expertise": [ "Reviewer Expertise Education", "biological science", "social science", "science education" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe introduction should contain literature about vaccine hesitancy in a global or worldwide approach. As written in the introduction, only one stanza discusses this section which is not sufficient. Thus, it is recommended to increase the number of literature that will address or discuss this part since the center of this paper is about vaccine hesitancy worldwide.\n\nThe methods were fully explained all the sections were stated very well.\nIn the result, there were 63 studies from the selected databases and 35 articles chosen. Is the number of articles/sources enough to be the basis of the study? It is recommended (if possible) to add articles that will somehow cover the majority of the countries to establish vaccine hesitancy worldwide. For the discussion part, all the sections that must be explained were stated and discussed very well.\nThe conclusion should be reduced or stated in the very least statements as much as possible.\n\nUse proper formatting/style in writing the references. Include its doi or the link where it is derived.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? Not applicable\n\nAre the conclusions drawn adequately supported by the results presented in the review? Yes", "responses": [ { "c_id": "10669", "date": "29 Nov 2023", "name": "Debendra Roy", "role": "Author Response", "response": "Reviewer: The introduction should contain literature about vaccine hesitancy in a global or worldwide approach. Author response: Thanks for your valuable comments. We have conducted this study at the early phase of vaccination derive (between November 2021 and December 2021) and primarily focused on the students vaccine hesitancy globally. There was a lack of review on students’ COVID-19 vaccination decision, so we could not include maximum references highlighted COVID-19 vaccine reluctance in the introduction section. To rationalize the study’s outlined objectives, we incorporated many study (review) articles related to other vaccinations types (ref: 12-21) conducted on students perspectives. We strictly denied mentioning the research article as a citation in the introduction phase. I hope these numbers satisfy the study requirement. Reviewer: The methods were fully explained all the sections were stated very well. Author response: Thanks for your appreciation. Reviewer: In the result, there were 63 studies from the selected databases and 35 articles chosen. Is the number of articles/sources enough to be the basis of the study? It is recommended (if possible) to add articles that will somehow cover the majority of the countries. Author response: Thanks for your observation. Although we noticed many more relevant article currently; however, we have conducted this study at the early phase of vaccination derive (between November 2021 and December 2021). Limited number of articles published in the topic and this review was the first systematic review on students COVID-19 vaccine decision. We added a common key word “AND (student * OR educational sector)” with our used keywords during searching the literatures. As a result, we found limited number articles (63) in the search engine. Based on our inclusion criteria we were able to consider 35 articles included in the final analysis. Although there are many articles published recently, however given the study’s originality we would like to remain the same analysis. Reviewer: The conclusion should be reduced or stated in the very least statements as much as possible. Author response: Thanks for your suggestion. This is a global systematic review on students’ vaccination consequence, so we have incorporated some additional sentences in the conclusion part as a recommendation of the study outcome. We organized the writing content according to the guideline of the journal. Reviewer: Use proper formatting/style in writing the references. Include its doi or the link where it is derived. Author response: Thanks for your suggestion. This journal already published the references. So we believed that the writing met the standard of journal’s referencing style." } ] }, { "id": "189184", "date": "16 Sep 2024", "name": "Lakshit Jain", "expertise": [ "Reviewer Expertise Psychiatry", "Addiction Psychiatry" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAs someone for whom English is not their primary language, this reviewer understands the struggle in writing in a different language.\n\nThe article uses excessively ornate language with too many adjectives. Such language is more suited for an opinion piece or an editorial, not for a review article.\n\nAt certain places in the article Authors talk about specific countries, but at other places they transition to continents. Please adhere to one set of terminology.\n\nThe Authors write \"screening using PRISMA flow diagrams\" on multiple occasions. This is incorrect. One follows the PRISMA guidelines and uses the diagram to describe to the reader how the authors adhered to the guidelines.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? Yes\n\nAre the conclusions drawn adequately supported by the results presented in the review? Yes\n\nIf this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-928
https://f1000research.com/articles/11-925/v1	11 Aug 22	{ "type": "Research Article", "title": "Descriptive analysis of clinical and laboratory findings in relation to changes in SARS-CoV-2 viral dynamics and cyclic threshold: a retrospective, single center observational study in patients treated with Hydroxychloroquine/Azithromycin combination therapy", "authors": [ "Maha M. Alamri", "Edward B. Devol", "Anwar B. Al-Otaibi", "Faisal A. Albaiz", "Mayyadah H. Alabdely", "Sahar I. Althawadi", "Maysoon S. Mutabagani", "Fatimah S. Alhamlan", "Fahad A. Alrabiah", "Reem S. Almaghrabi", "Edward B. Devol", "Anwar B. Al-Otaibi", "Faisal A. Albaiz", "Mayyadah H. Alabdely", "Sahar I. Althawadi", "Maysoon S. Mutabagani", "Fatimah S. Alhamlan", "Fahad A. Alrabiah" ], "abstract": "Background: Cases of undiagnosed pneumonia have emerged, and sequencing of respiratory samples indicated the presence of SARS-CoV-2 causing COVID-19. Patients with higher viral load and lower Ct values tend to have progressive disease and severe lung injury. The objective of this study is to describe the clinical manifestation and disease outcomes of COVID-19 patients in relation to their Ct values. Methods: A retrospective, single center observational study was performed, including patients admitted to King Faisal Specialist Hospital and Research Centre (KFSH&RC) Riyadh between March 1st-29th, 2020 and have a confirmed diagnosis of COVID-19. The Ct value was identified to determine the viral load. All patients were treated according to KFSH&RC guidelines. Patients were divided into HCQ/AZI and non HCQ/AZI treated groups. Results: There were many days where Ct values were not available. An attempt at imputing information for missing Ct values was made using logic. The logic leads to an ordinal Ct score 1, 2, 3, or 4. As a result, complete Ct score profiles were available. There was no evidence of statistically significant difference between the two groups in regard to clinical severity, duration to negative test or changes in Ct values. Conclusion: There is little knowledge known to the time profile of Ct values and their relation to disease course of COVID-19. This study provides insight on how Ct values might be used to determine treatment efficacy. As it might be difficult to obtain Ct values at all times, this study provides an imputation method that may be used with conservative statistical assumptions for analyses of Ct profiles.", "keywords": [ "COVID-19", "Dynamics", "SARS-CoV-2", "Coronavirus", "PCR." ], "content": "Introduction\n\nIn December 2019, multiple cases of undiagnosed pneumonia emerged in China. Sequencing on respiratory samples indicated the presence of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) causing Coronavirus Disease 2019 (COVID-19).1–3\n\nThe main method of diagnosing COVID-19 is by the isolation of SARS-CoV-2 through Reverse Transcriptase Polymerase Chain Reaction (RT-PCR or PCR) nucleic amplification testing of respiratory samples.4 In a study done by Yu et al. the viral load predicted by the Cycle threshold (Ct) value was higher in sputum samples than nasopharyngeal and throat swabs. Patients who had an increasing viral load and lower CT values had a progressive disease and more severe lung injury.5,6 Furthermore patients with higher initial viral loads had worse outcomes and more prolonged viral shedding.7 The viral dynamics studied in 18 different patients resembled that of patients with influenza rather than SARS-CoV.8\n\nGiven the importance for early identification of patients with severe disease and that a low Ct value is proposed to be inversely proportional to disease severity,7 we aim to describe the different clinical manifestations and disease severities in relation to the initial and subsequent Ct values in patients who were admitted to King Faisal Specialist Hospital and Research Centre-Riyadh (KFSH&RC).\n\n\nMethods\n\nA retrospective, single center observational study was undertaken and included all patients who were admitted to KFSH&RC-Riyadh in one month in 2020 and had a confirmed diagnosis of COVID-19 based on a positive PCR taken from a respiratory sample. The study was approved by the policies and guidelines for clinical research at KFSH&RC and the KFSH&RC-Riyadh Institutional Review Board (IRB) (RAC # 2201054). As this is a retrospective study, consent to participate from patients was waived by the IRB.\n\nAll but two patients were followed for a total duration of 14 days after the initial diagnosis. Repeat PCR results were sought during data abstraction for days 3, 7, 10 and 14. The Ct value was identified on the obtained samples. All patients were treated according to KFSH&RC treatment guidelines (as detailed below).\n\nEpidemiological, demographic, clinical, laboratory, treatment administered, and outcome of the disease data were obtained from the patient’s electronic medical records. All data were entered in a password-protected database developed using the Research Electronic Data Capture (REDCap) version 9.4 software. The Ct values on admission and follow-up samples were obtained from the microbiology laboratory. As hydroxychloroquine (HCQ) and azithromycin (AZI) were one of the commonly used regimens for treatment, we divided our cohort into HCQ/AZI and non-HCQ/AZI treated groups.\n\nSample: Combined nasopharyngeal and throat swabs were collected from patients.\n\nCOVID-19 RNA extraction method: RNA was extracted utilizing Qiagen QIAamp® DSP Viral RNA Mini Kit or QIAamp® Viral RNA Mini Kit EZ1 following the manufacturer recommendations, utilizing 200 μL of sample and eluted with 60 μL of buffer.\n\nRNA amplification and detection: RealStar ® SARS-CoV-2 RT-PCR Kit RUO Altona was used for RNA detection and differentiation of lineage B-betacoronavirus (β-CoV) and SARS-CoV-2 specific RNA. Reagent system included an internal control and positive control for both targets, B-βCoV and SARS-CoV-2 following manufacturer recommendations. Tests were done on Rotor-Gene ® Q. Tests were reported as positive and negative accordingly. Each test was run into cycles and up to 45 cycles, and the Ct value was recorded according to the cycle for which the test became positive.\n\nAll patients admitted were treated according to hospital guidelines that had been revised and edited according to emerging evidence. Up to the time of writing, the hospital had issued six versions of COVID-19 treatment and management guidelines, the initial three versions were released at the time of data collection and analysis. The first guideline was issued on March 5th, 2020 followed by the second and third versions that were released on March 19th and 26th, 2020 respectively.\n\nAt first (and as per the Ministry of Health guidelines for Saudi Arabia), all patients who were eligible to be treated in KFSH& RC-Riyadh and who had a positive COVID-19 PCR were admitted to the hospital regardless of the presence or absence of symptoms.\n\nAll admitted patients had baseline lab tests requested including Complete Blood Count with Differential (CBCD), urea and electrolytes, creatinine, C-Reactive Protein (CRP), Liver Function Test (LFT), blood glucose, and ferritin level. Electrocardiograms (ECGs) were also conducted to look at the corrected QT interval prior to starting medications.\n\nMultiplex PCR using the QIAstat-Dx Respiratory SARS-CoV-2 Panel is intended for the detection and differentiation of nucleic acid from SARS-CoV-2 and multiple other respiratory viruses and atypical bacteria. In addition, if Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is needed, a BIOFIRE® RP2.1plus is used which detects SARS-CoV-2, MERS-CoV and other common respiratory pathogens and atypical bacteria.\n\nIn the latest revision, further investigations were added as the available literature suggested their correlation with disease severity and outcome. These included erythrocyte sedimentation rate (ESR), D-Dimer, Creatinine Kinase (CK), troponin, Lactate Dehydrogenase (LD) and haptoglobin. All patients had a baseline chest X-Ray, and those with an abnormal finding or those at high risk underwent Computed Tomography (CT) scan of the chest.\n\nIn the earliest guidelines issued, patients were divided according to the presence or absence of symptoms, and radiological evidence of pneumonia. Severity was indicated by the need for Intensive Care Unit (ICU) admission. Following the latest guideline, patients were categorized into four categories (asymptomatic, mild, moderate and severe infection) (Table 1).\n\n\n\n1. Respiratory rate of 30 breaths/min.,\n\n2. Arterial oxygen partial pressure to fractional inspiratory oxygen ratio (PaO2/FiO2) less than 300,\n\n3. More than 50% lung involvement on imaging within 24-48 hours,\n\n4. Critical respiratory failure requiring mechanical ventilation, septic shock or multi-organ dysfunction.\n\nIn the first guidelines, active treatment was given for patients with radiological evidence of pneumonia. Those patients were treated as community acquired pneumonia in addition to Lopinavir/Ritonavir +/- Ribavirin. Other treatment options were decided after discussion with an infectious disease (ID) physician. As the evidence evolved and as the roles of HCQ and AZI were thought to lead to favorable outcomes, hospital guidelines changed to include HCQ and AZI for all patients presenting with symptoms regardless of symptoms severity and presence or absence of pneumonia. The HCQ regimen involved a loading dose of 400 mg oral twice daily in the first day, followed by 200 mg orally every 12 hours for a duration of 6 days. AZI was given at a dose of 500 mg daily for 3 days. Lopinavir/Ritonavir were used if the above regimen was contraindicated. In the latest guidelines, Tocilizumab was added as a possible treatment for cytokine release syndrome. Its use was strictly prescribed by an ID physician and for patients who were admitted to the ICU with evidence of cytokine storm and elevated Interleukin (IL) 6. The recommended dose was 4-8 mg/kg and repeated after 12 hours if the response for the 1st dose was poor and to a maximum of two doses.\n\nIn this study, a confirmed case is defined as a patient with at least one positive PCR test for COVID-19. Cure is defined as a single negative COVID-19 PCR test. Persistent disease is defined as a positive PCR on day 14 following the initial positive test or sometime afterwards. A high risk patient is any patient who is positive for COVID-19 and has any of the following comorbidities: Age above 60 years, lung disease, cancer, cardiovascular or cerebrovascular disease, renal or liver disease, diabetes, hypertension, immunocompromising conditions (Human Immunodeficiency Virus (HIV), post solid organ or hematopoietic stem cell transplant, on active chemotherapy or receiving an immunomodulator or immunosuppressant therapy), or pregnancy.\n\nData were entered in an electronic database system – REDCap version 9.4. Over 300 data items were abstracted from the medical records for each included patient. JMP/SAS software (version 15.0) and Cytel (StatXact version 6.0 and LogXact version 6.0) were used for data analysis. Data were summarized using mean (+/− standard deviation) or median (with interquartile range) for continuous data. Categorical data were summarized using frequencies and percentages. All analysis methods are available and could be reproduced with R, a freely available software platform.\n\nPatients were divided into two groups - a group receiving a hydroxychloroquine-based regimen and the second group receiving a regimen not including hydroxychloroquine. The Ct values were compared between the two groups and correlated with disease severity and outcome with a Spearman’s correlation coefficient. Cure, persistent disease and death were the three main outcome categories. Comparisons between the two treatment groups were evaluated with nonparametric methods (Wilcoxon Rank Sum Test) given the small numbers and inability to evaluate distributional requirements. Time-to-event analyses were also carried out with the Kaplan-Meier technique.\n\n\nResults\n\nDuring the study time period, 35 subjects had presented to the KFSH&RC-Riyadh and for whom sufficient follow-up information was available (21 women and 14 men). In total, 28 patients were considered at presentation mild (stage B), 5 were moderate (stage C), and 2 were asymptomatic (stage A). The average age was 49.9±21.9 years. Comorbidities were observed in 68.6% of the cases. All patients had tested positive for SARS-CoV-2 by PCR. Table 2 shows the disease severity progression through the course of 14 days following admission. Table 3 presents symptoms that developed sometime during the course of infection.\n\n* 2 patients were followed for 10 days instead of 14 days.\n\nThere were nine different treatment profiles administered across the 35 subjects when considering the seven different drugs used during the course of illness – HCQ, AZI, Kaletra, Ribavirin, Tocilizumab, IVIG, and other. Of interest is to differentially identify from among the 35 study subjects those who were given the combination of HCQ and AZI as their initial treatment from those who were not given this combination as their initial treatment. The schematic in Figure 1 depicts the course of treatments received by each of the 35 subjects and how it was decided into which of the two treatment groups each was assigned post-hoc. It is seen that 21 (60%) pateints were given HCQ and AZI as their initial treatment. Henceforth, this treatment group will be referred to as the HCQ/AZI group. Those subjects not in the HCQ/AZI treatment group will be denoted the HCQ/AZI¯ group.\n\nTable 4 displays a comparison of baseline characteristics between the two treatment groups. There was no significant difference in age and gender between the two groups. The frequency of individuals with a past history of smoking in the HCQ/AZI group was significantly less in the HCQ/AZI¯ group. No differences were observed in the radiological findings or vital signs between the two groups. Among the baseline laboratory values, ALT was lower in the HCQ/AZI group. Table 5 displays a comparison of the baseline clinical severity of the two treatment groups; there is no statistically significant difference in the two.\n\nTable 6 shows a comparison for the number of days to reach negative RT-PCR results between the two treatment groups. From the table it can be seen that 7 of the 21 HCQ/AZI-treated subjects remained positive for 14 days after admission whereas 12 were able to reach a negative status within that time period. There were 2 subjects not fully followed for 14 days post-admission for whom a conclusion could not be reached. Moreover, 9 of the 14 HCQ/AZI¯-treated subjects remained positive for 14 days after admission, whereas 5 were able to reach a negative status within that time period. Considered as two ordered multinomial distributions, the two columns did not show a statistically significant difference between the two treatment groups (p = 0.1571) with respect to the time to reach negativity. Figure 2 presents a time-to-negativity actuarial chart for the two treatment groups with no statistically significant difference in the two curves.\n\n* subjects were followed for less than 14 days.\n\nThe Ct values ranged from a minimum of 11.44 to a maximum of 38.35 across the 5 time points (days 0, 3, 7, 10, and 14), across the two treatment groups, and during the 14 days. There were many days among the 35 subjects for which Ct values were not available (i.e. a PCR test was not carried out). These missing results presented a challenge in trying to evaluate the relative Ct profiles between the two treatment groups. It was noted however that, although the Ct value was missing, a positivity/negativity indication was often present in the medical record when the Ct value was missing. Among those missing both the Ct value and an indication of positivity/negativity, a clinical severity stage value (A, B, C, D, or dead) was present for each of the 5 days. Using this information together with whatever Ct values were present, an attempt at imputing information for missing Ct values was made using the following logic. The logic lead to an ordinal Ct score 1, 2, 3, or 4 for each subject for each of the 5 days (0, 3, 7, 10, and 14), and it will be referred to as the Ct score. The methodology includes the following five steps:\n\n1. Ct values were firstly regarded as falling within one of four categories:\n\n• Less than 20 as category 1, scored 1;\n\n• At least 20 to less than 30 as category 2, scored 2;\n\n• At least 30 to less than 40 as category 3, scored 3;\n\n• At least 40 as category 4, scored 4.\n\nNote that, even though a Ct value of 40 or more was not seen among the 35 subjects, this category was conceptualized to accommodate a Ct value for a subject who reached a negative RT-PCR test or a status of no disease.\n\n2. For each day when a subject’s Ct value was available, a score (as described in #1 above) was assigned to the Ct score.\n\n3. It was noted that a Ct value was present (i.e. not missing) on day 0 for all 35 subjects. It was therefore the case that a true Ct based score was able to be assigned to each subject’s day 0.\n\n4. For all but 8 of the subjects, at least one Ct value was available at one of the follow-up days (3, 7, 10, or 14). In those situations, a linearly interpolated (assuming the 5 days 0, 3, 7, 10, and 14 as equidistant) score was assigned. Reassuringly, for every interpolation, the value was consistent with the associated clinical severity stage.\n\n5. In addition to the 8 subjects for whom no Ct values subsequent to day 0 were available, there were 16 subjects who had a subsequent Ct value but were missing day 14, i.e. for which interpolation was not possible based on an endpoint Ct value (two boundary endpoints being required in order to interpolate). That is, there were 24 subjects for whom it was necessary to rely on the positivity/negativity result or the clinical severity stage in order to impute a Ct score. The following was inferred:\n\n• For 12 subjects, a score of 4 could be assigned as on the days subsequent to their last Ct value, they were recorded as being RT-PCR negative;\n\n• For 3 subjects, a score of 1 could be assigned as they either died or they were at stage D;\n\n• For 5 subjects, a score of 4 could be assigned to day 14 as a result of a negative RT-PCR, and intermediate interpolations were then made (e.g. scores of 2 or 3 as appropriate);\n\n• For 2 subjects, there was no information on positivity/negativity on the days when the Ct value was missing, but the clinical severity stage strongly suggested the score (scores of 2 and 3 were imputed);\n\n• For 2 subjects both treated with HCQ/AZI, too little information was available, and an inference could not be made, and they were not included in this analysis.\n\nIn the end, as a result of the above, a complete Ct score profile was available for 33 of the 35 subjects. A breakdown of these profiles separately for the two treatment groups is as shown in Tables 7 and 8. In reviewing the tables, it can be seen that there are 12 unique Ct score profiles for those treated with HCQ/AZI¯, and 14 unique Ct score profiles for those treatment with HCQ/AZI. It was found that 5 of the profiles from Table 7 were the same as 5 of the profiles from Table 8, i.e. 18 unique profiles of Ct scores across all subjects. The 18 profiles are presented in Table 9 and ranked in order of favorability, where a more favorable outcome is one for which a higher score is reached earlier. A rank of 1 is the least favorable profile and larger ranks assigned to a profile indicate a more favorable one. A rank-based comparison was performed on these two sets of the ranks, and the results suggested no statistically significant difference in the two treatment groups (HCQ/AZI median rank: 11; HCQ/AZI¯ median rank: 5.5; p = 0.2212 (Kruskal-Wallis)) with respect to the time to a recovering Ct value.\n\nTable 10 describes the change in disease severity from admission to day 14. One patient was classified at admission with stage A and then his disease developed at day 14 to stage D. Around 36% of the patients presented with mild (stage B) severity and then lessened to asymptomatic (stage A). In total, 7 patients presented with mild stage then they were tested negative by day 14. Table 11 provides an overall comparison of the clinical severity on day 14 between the two treatment groups with no statistically significant difference between the two (p > 0.05).\n\n* Note that the above table involves 33 subjects (two subjects were followed for less than 14 days – one initially stage B and one initially stage C).\n\nSeveral lab tests were carried out on the study subjects during admission (Table 12). These included hemoglobin, creatinine, D-dimer, CD4, IgG, and others. From among the lab tests the following were found to significantly relate to disease severity at admission: D-dimer, troponin, LD, C4, absolute CD8 (p < 0.05).\n\n\nDiscussion\n\nThe current study involves subjects presenting early in the COVID-19 pandemic and much knowledge about the virus and the ensuing disease has been generated since the time of these subjects’ presentations. However, there is still relatively little new knowledge related to the time profile of Ct values and their potential value in understanding the course of disease. This study aims to add some related insights and particularly how treatment efficacy (here a comparison of HCQ and AZI) may be able to be evaluated based on Ct values. Additionally, the study recognizes the challenges associated with timely RT-PCR testing and always documenting the Ct values and proposes an imputation method that may be used with conservative statistical assumptions for analyses of Ct profiles. There are several limitations of this study. It is a retrospective study that has a small sample size and was conducted in a single center.\n\nIn this study, a treatment regimen of HCQ and AZI was identified for 21 of 35 subjects testing positive for SARS-Cov2 and admitted to a single tertiary care hospital early in the COVID-19 pandemic.\n\nThis study presents the follow-up information gathered on the patients for up to 14 days after admission, specifically days 0 (admission), 3, 7 10, and 14. Of particular interest for the follow-up was the clinical staging of COVID-19 and the Ct value from the RT-PCR. Ct values were scored as 1, 2, 3, or 4 based on the value of the Ct being below 20, 20-30, 30-40, or 40 or more. The follow-up Ct value was not consistently available at each of the four follow-up timepoints following admission, and imputation of missing Ct scores (1-4) was made using an algorithm based on coincident clinical stage and interpolation. Recognizing the assumptions associated with the designed imputation scheme, a conservative, nonparametric (i.e. rank-based) method was used for comparing the two treatment groups with respect to outcomes. A validation study of this method is going to follow.\n\nThe patients treated with the HCQ and AZI were similar to those not treated with respect to all demographic, clinical, radiological, and laboratory features with the exception of a higher rate of smoking history among those treated with HCQ and AZI. The follow-up profiles of the two groups were compared with respect to improvement trends (i.e. improving clinical staging and improving Ct scores). There was no evidence of any difference in the sets of profiles for the two treatment groups.\n\n\nData availability\n\nDryad: SARS-CoV-2 Viral dynamics, https://doi.org/10.5061/dryad.15dv41nwm.9\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "Competing interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nSu S, Wong G, Shi W, et al.: Epidemiology, Genetic Recombination, and Pathogenesis of Coronaviruses. Trends Microbiol 2016; 24: 490–502. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLu R, Zhao X, Li J, et al.: Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 2020; 395: 565–74. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHuang C, Wang Y, Li X, et al.: Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395: 497–506. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLiu R, Han H, Liu F, et al.: Positive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020. Clin Chim Acta 2020; 505: 172–5. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nYu F, Yan L, Wang N, et al.: Quantitative Detection and Viral Load Analysis of SARS-CoV-2 in Infected Patients. Clin Infect Dis 2020. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLiu Y, Yang Y, Zhang C, et al.: Clinical and biochemical indexes from 2019- nCoV infected patients linked to viral loads and lung injury. Sci China Life Sci 2020; 63: 364–74. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLiu Y, Yan L, Wan L, et al.: Viral dynamics in mild and severe cases of COVID-19Dysregulation of immune response in patients with COVID-19 in Wuhan, China Chuan. Lancet Infect Dis 2020; 2019: 2019–20. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nZou L, Ruan F, Huang M, et al.: SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients. N Engl J Med 2020; 382: 1177–9. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAlamri M: SARS-CoV-2 Viral dynamics. Dryad, [Dataset]. 2022. Publisher Full Text" }	[ { "id": "179429", "date": "03 Jul 2023", "name": "Reza Zolfaghari Emameh", "expertise": [ "Reviewer Expertise SARS-CoV-2" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript entitled “Descriptive analysis of clinical and laboratory findings in relation to changes in SARS-CoV-2 viral dynamics and cyclic threshold: a retrospective, single center observational study in patients treated with Hydroxychloroquine/Azithromycin combination therapy “ was reviewed carefully.\nThe study was performed in March 2020 and three years have been passed since then. The subjects such as HCQ/AZI treatment protocols, have been published many times. In addition, hydroxychloroquine has been banned by the World Health Organization (WHO) in treatment of COVID-19. Finally, there is no novelty in this manuscript.\nAs the result, the manuscript is not acceptable.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] } ]	1	https://f1000research.com/articles/11-925
https://f1000research.com/articles/11-29/v1	11 Jan 22	{ "type": "Research Article", "title": "Pre-Clinical Study: Immunohistochemical evaluation of matrix metalloproteinase-13 on rabbit (Oryctolagus cuniculus) socket healing after application of platelet-rich fibrin with and without hydroxyapatite", "authors": [ "Meta Maulida Damayanti", "Meike Rachmawati", "Meike Rachmawati" ], "abstract": "Background: Tissue engineering technology has been used globally and proven to accelerate wound healing. This study aimed to analyse the effect of adding hydroxyapatite (HA) as a scaffold to platelet-rich fibrin (PRF) as a growth factor in accelerating the wound healing process as seen from the expression of matrix metalloproteinase-13 (MMP-13). Methods: This research is an animal experiment conducted on 18 rabbits (Oryctolagus cuniculus). Rabbits were randomly divided into the following three groups of treatment: (G1) the application of PRF group, (G2) the application of PRF+HA group and (C) the control group without any application. Furthermore, each treatment group was split randomly into three groups of observation time. Periodontal tissue biopsy was performed to analyse the histopathological features that were examined on the basis of the level of MMP-13 immunoexpression. Results: MMP-13 immunoexpression in the PRF+HA group showed better histoscore results, indicating a substantial reduction in MMP-13 values compared with other groups. The healing process was shown to increase with increasing observation time (p<0.05), and the PRF+HA group outperformed the PRF and control groups. On day 3, MMP-13 exhibited a dark brown colour of Immunohistochemistry (IHC), which indicated an increase in the expression value of MMP-13 in the early stages of healing, namely, inflammation. On day 14, light brown IHC was seen, especially in group 2, as a reference that the remodeling process had begun. Conclusions: This study indicates that the application of HA can accelerate the socket healing process by decreasing the level of immunoexpression of MMP-13. HA is an alloplastic material that has inherent bioactive properties that support osteoconduction, which functions as a scaffold in the form of a fibrin matrix that can bind MMPs so that it can accelerate the wound healing process.", "keywords": [ "Socket Healing", "Matrix Metalloproteinases-13", "Platelet-Rich Fibrin", "Hydroxyapatite" ], "content": "Introduction\n\nTooth extraction is one of the most common treatment procedures in dentistry. This procedure may cause resorption of the alveolar bone, gingival recession around the extraction area and periodontal abnormality and may also result in an aesthetic problem because of post-extraction anatomical and physiological changes.1,2 The wound healing process is influenced by various molecules, inflammation mediators, integrins, growth factors and matrix metalloproteinases (MMPs). MMPs has a function in every phase of wound healing by making modifications to the wound matrix, enabling cell migration essential in the remodeling process. Furthermore, MMPs are responsible for collagen degradation, and tissue engineering is one of the treatment options for regenerating periodontal tissues and alveolar bone. Progenitor cells, scaffolds, and growth factors are three essential components of tissue engineering.3,4\n\nMMP-13 has an important role in the early diagnosis of arthritis by analysing its pathological activity on the basis of histopathological features.5 Fibroblast cells are abundant in the stroma, and these cells play a role in making the extracellular matrix (ECM) function properly. During the wound healing, inflammatory, proliferative and remodeling stages, fibroblasts adapt to their environment and respond to and emit signals locally. At the time of injury, fibroblasts can replace the injured tissue. During pathological conditions, the ECM is produced in excess, and collagen is deposited irregularly, often leading to irreversible organ dysfunction or a disfiguring appearance.6\n\nBone grafts are used to replace and regenerate the lost bone. Scaffolding materials studied have been widely employed to stimulate bone growth. A promising scaffold must have biomaterials similar to the original bone structure.7 Platelet concentrates, such as platelet-rich fibrin (PRF), are utilised in different clinical fields, particularly in a medical procedure involving the mouth and jaws, the concentrates contain a high concentration of growth factors, which are essential in wound healing, particularly bone regeneration. Thus, they are considered as another treatment adjuvant.8–12 Research that utilised platelets as growth factor therapy has affirmed that the use of PRF is better in wound healing compared with platelet-rich plasma (PRP), which is seen from various diagnostic tools.11 In dentistry, PRF has proven to accelerate wound healing.13\n\nHydroxyapatite (HA) is a fundamental part of hard tissues, namely, bones and teeth. HA (Ca10(PO4)6(OH)2) is a material to assist with bone regeneration, it has great biocompatibility, does not cause unnecessary inflammation phenomena. It is non-poisonous, has great osteoconduction, it also has a high affinity for binding with other materials, and is a manufactured material generally utilised in medication and dentistry.11,14 In addition, HA can be employed as a scaffold in bone tissue regeneration. Growth factors and scaffold products induce the release of inflammatory molecules and mediators, such as tumour necrosis factor-alpha (TNF-α), interleukin (IL)-1, IL-6 and MMP-13, to render a better catabolic effect on chondrocyte metabolism and to speed up the inflammatory process.15 Scaffold functions as an early ECM essential for cell proliferation, migration and differentiation, while growth factor has a vital role in the wound healing process, an acute tissue response to trauma and several cell physiological processes. This study aimed to analyse the effect of adding HA as a scaffold to PRF as a growth factor in accelerating the wound healing process as observed from the expression of MMP-13.\n\n\nMethods\n\nAll experimental procedures involving animals were conducted in accordance with ARRIVE guidelines 2.0 on the care and use of laboratory animals to ameliorate any suffering for the animals.16 The treatment of the experimental animals was according to the regulations regarding the convention on international trade in endangered species of wild fauna and flora. A research proposal containing research procedures was submitted to the ethics committee and passed the ethical committee issued by the University of Padjadjaran Bandung, Indonesia (Number: 132/UN6.C1.3.2/KEPK/PN/2017).\n\nThis analytic, quantitative research used an animal experimental laboratory design, and a post-test-only control group study design was conducted. The sample size was determined using the Mead equation formula calculation. Subjects were 18 rabbits (Oryctolagus cuniculus) chosen according to the following: healthy, good inferior anterior teeth and 300–400 g of weight. The animals were not selected on the basis of sex and age because they did not affect the treatment. The study employed three treatment groups and three observation times. The treatment groups were as follows: the control group (C), the PRF group (G1) and the PRF+HA group (G2), and the observation times were the following Day 3, Day 7 and Day 14 based on the inflammation, proliferation and remodeling phases of the healing process. Each animal obtained different treatments with distinct observation times. The experimental animals were randomly divided into three treatment groups and then split into three groups on the basis of the time of observation. Each group was marked on the back area using markers (C, G1 and G2) and placed in a different cage according to the time of observation. Cage A for Day 3, B for Day 7 and C for Day 14.\n\nAfter subject selection, a rabbit adaptation was performed for 7 days, and all the animals fasted for 12 hours before tooth extraction. Thereafter, tooth extraction was performed, PRF was applied, and then HA was added. A commercial brand of HA, which is commonly used in dentistry treatment, was chosen for this study. During the experimental period, all the experimental animals were given standard feeds and cages met the ethical standards. All the research conditions and procedures were recorded daily by the team in their logbooks. Details such as group allocations, preparations, treatment, and data collection and analysis were duly noted.\n\nThree millilitres of homologous blood was acquired in sterile cylinders from the ear cartilage of each rabbit. From that point onward, the blood was quickly centrifuged at 3200 rpm (1600 g) for 10 minutes. The blood was isolated into three layers, and the top layer was separated from the other layers by transferring to another centrifugation tube and then was centrifuged again at 3200 rpm (1600 g) for 15 minutes.10,17\n\nExtraction was performed under anaesthesia (ketamine and xylazine) to relieve pain. During the extraction process, the experimental animals were conditioned as comfortably as possible and were put to sleep on a support board. The enclosed action area was not visible to other experimental animals. Further, the tooth extraction was executed with labial and lingual luxation movements using pedodontic forceps for the inferior anterior region with the principle of minimal injury. After the extraction, the socket was irrigated using a 0.09% saline solution and was drained using a sterile tampon. The socket was filled with PRF (G1) and PRF+HA (G2), and nothing was given to the control group. After the application was made, the wound was closed with simple stitches using a 3.0 silk stitches thread and a curved needle with a simple interrupted suture method. The periodontal tissue biopsy specimens were taken on the basis of the observation time (Days 3, 7 and 14). Termination was conducted before taking the specimens using ketamine at a dose of 200 mg/kg rabbit body weight. The limitation of this study is that, after tooth extraction, intervention was executed on the basis of the treatment group, and then simple stitches was performed. However, stitches can loosen up if the experimental animal is too active in moving its teeth and tongue, even making the stitches to come off.\n\nImmunohistochemical tests were performed to analyse the immunoexpression of MMP-13. The current research used an MMP-13 primary antibody kit, a labelled streptavidin-biotin (LSAB) secondary antibody kit, polyclonal antibody (MyBioSource, Cat# MBS837431, RRID: AB_2895530), and positive control of breast cancer. The immunoexpression of MMP-13 appeared to be positive when the connective tissue/stromal fibroblast around was brown in colour by looking at the distribution and intensity. Histoscore/final score is the multiplication of distribution with intensity, and the values for the distribution are as follows: 4 = cells positive > 75%, 3 = cells positive 51%–75%, 2 = cells positive 25%–50% and 1 = cells positive < 25%. The value for intensity is 0 = no colour, 1 = current colour, weak (light brown), 2 = present colour, moderate (brown) and 3 = present colour, strong (dark brown).10,18,19 This research was conducted in Laboratory Pathology Anatomy Hasan Sadikin General Hospital Bandung, Indonesia, and the immunoexpression scores of MMP-13 were evaluated by a qualified pathologist.\n\nData analysis was conducted using the Statistical Package for Social Science (SPSS) software (IBM SPSS Statistics, RRID:SCR_019096). Normal distribution data analysis was performed using the Shapiro–Wilk test if normally distributed, and parametric tests were performed. The evaluation of MMP-13 among the groups and observation times was performed statistically with the Kruskal–Wallis test. All the data were uploaded to the repository.20–22\n\n\nResults\n\nThe addition of HA to PRF displayed faster wound healing in the socket. The total histoscore in group 2 was lower than that in group 1 and the control group. Table 1 shows differences in MMP-13 immunoexpression between groups. Histoscore Days 7 and 14 had a significant difference (p < 0.05). On the third day, the MMP-13 values were the same in all the groups. On Day 7, the MMP-13 value began to decrease, where group 2 showed a significant decrease. On Day 14, it was observed that MMP-13 had a lower histoscore, especially in group 2.\n\n* Median value (range).\n\nThe brown staining addresses the showed antigen, while the blue colour was the counterstain of the cores. Socket healing featured MMP-13 protein in the cytoplasm of the stromal fibroblast cells. In addition, the undeniable levels of MMP-13 protein were solely in the cytoplasm of the fibroblast cells in all the groups for day 3 [Figure 1 (A), (D) and (G)]. The light brown colour on fibroblast represented the low IHC staining of the MMP-13 expression (Days 7 and 14 and groups 1 and 2) [Figure 1 (F), (H) and (I)]. The brown colour on the fibroblast represented the moderate IHC staining of MMP-13 expression (B), (C) and (E). The large and small image inserts exhibited the portion of each treatment group and the observation time at magnifications 100× and 400×. Furthermore, administration platelets increased the MMP-13 expression in line with HA levels. The histopathological picture showed the expression of MMP-13 with a dark brown appearance in the stromal fibroblast area, which was evenly distributed in all areas with strong intensity (A, D and G). In contrast to the IHC picture, which looked light brown, especially in pictures (F) and (I), it displayed a reduced distribution and intensity (see Figure 1).22\n\n(A) control group day 3; (B) control group day 7; (C) control group day 14; (D) group 1 day 3; (E) group 1 day 7; (F) group 1 day 14; (G) group 2 day 3; (H) group 2 day 7; (I) group 2 day 14.\n\nTable 2 showed that administration of PRF and PRF+HA could reduce MMP-13 levels during the observation time. There was a significant difference in examination between observation times. Of all group, group 2 saw a significant difference based on the healing time.\n\n* Based on Kruskal Wallis test.\n\n\nDiscussion\n\nThe present study validated that MMP-13 could determine healing activities. Hydroxyapatite is the primary mineral aspect of vertebrate bones and teeth, and it's far a good cloth for growing as a simple, efficient, and environmentally pleasant approach of forming biofunctional scaffolds and implant coatings with sizeable biocompatibility, bioactivity, mechanical strength, and the cap potential to feature as a drug delivery system.23\n\nThis preclinical study confirmed the hypothesis that the application of HA in post-extraction socket healing can accelerate the healing process and decrease the level of MMP-13 immunoexpression based on the stages of wound healing, namely the stages of inflammation, proliferation, and progression. On Day 3, MMP-13 was highly expressed, proving that up to 4–5 days after an injury, there will be an inflammation phase. On the next day, the expression began to decrease, especially in group 2, meaning that HA could accelerate the work of growth factors in the wound healing process. On Day 14, there was a decrease in expression, indicating that the inflammatory process was finished and that tissue regeneration or the stages of proliferation and progression began. In this study, there was a significant difference based on the observation time from Day 3 to Day 14.\n\nThis result related to the theory that growth factors are an important part of the bone restoration response delivery system and delivering exogenous growth factors to the injured site improves healing outcomes significantly. Scaffold systems have the potential to provide safer, simpler bone regeneration therapies than the systems currently utilised within the clinic.24 Platelets and growth factors comprise a scaffold component in the form of a fibrin matrix that could increase the bioactivity of inflammatory mediators to accelerate wound healing. Platelets and leukocyte cytokines are essential in biomaterial biology, and the fibrin matrix that supports it is the determining factor responsible for increasing the potential use of PRF. The primary source of angiogenesis is derived from fibrin gel. The fibrin matrix supports injured tissues, which affects the metabolism of epithelial cells and fibroblasts. Additionally, PRF acts as a physiological fibrin matrix, functioning as cell stems and allowing the remodeling of fibrin into being more dense connective tissue resistant. Therefore, the PRF membrane simultaneously increases the angiogenesis and the thickness or closure of the epithelium necessary for cutaneous healing. In this way, the use of platelet concentrate autologous is a promising application in the field of periodontal tissue regeneration and the alveolar bone that can be utilised in clinical circumstances that require quicker healing.25\n\nMMP-13 has been widely used as a marker and therapy in the medical field. MMP-13, an important member of the MMPs family, performs well-measured functions through degradation of type II collagen in articular cartilage and bone in osteoarthritis, concerns the molecular metastases of oral cancer, and should alter vasculogenic mimicry and endothelial-dependent vessel formation in large cell lung cancer.26–28 Similar studies using the expression of MMP-13 have proven that MMP-13 plays a role in every phase of wound healing by making modifications to the wound matrix, enabling cell migration essential in the remodeling process. MMPs are responsible for collagen degradation. Tissue engineering is one of the helpful endeavours in recovering periodontal tissues and alveolar bone. The three fundamental parts in tissue engineering are progenitor cells, scaffolds and growth factors. Proteinases play an essential role in wound healing by controlling cell-grid connections and the accessibility of bioactive particles. In the research conducted by Toriseva M. et al. (2012), the role of matrix MMP-13 on granulation tissue development was significantly reduced in mice. Granulation tissue in MMP-13/− mice exhibited delayed myofibroblast organisation, an increased microvascular density and an almost complete absence of large vessels. In addition, the gene expression profile identified genes that were differentially expressed in the granulation tissue of MMP-13/− mice involved in biological functions, including inflammatory response, angiogenesis, cell movement, cell growth, proliferation and proteolysis. This study exhibited the role of MMP-13 in wound healing by organising cell exercises that are significant in the growth and maturation of granulation tissues, including myofibroblast work, inflammation, angiogenesis and proteolysis.29\n\nHA applications are widely used for wound healing, even the modifications continue to be developed. Hassan HH, et al. (2021) states that following compositional modification, cellulose acetate nanofibers containing modified HA for wound healing utilization demonstrated a high degree of response with proliferation and growing behaviors.30 Samadian HA, et al. (2018) used HA modification dressing that resulted in the highest collagen synthesis, re-epithelialization, neovascularization, and cosmetic appearance, according to histological and histomorphometric examinations of the wounds.31 Wardhana AS, et al. use ellagic-hydroxyapatite acid to promotes osteogenesis in bone defects by increasing the amounts of osteoblasts and therefore the expression of osteoprotegerin and osteocalcin.32 HA is a scaffold that can bond with MMPs and reduce its activities in vitro. Secretion and MMP activities are regulated well, and in normal tissues, MMP is expressed on a fundamental level. If the tissue remodeling phase is necessary, such as in wound healing, MMP can be expressed and activated easily. A few diverse cell types communicated MMPs inside the skin (keratinocytes, fibroblasts, endothelial cells and inflammatory cells, such as monocytes, lymphocytes and macrophages). MMP expression can be prompted to see different signs, including cytokines, hormones and contact with other cell types or with ECM.3 MMP-13 cleaves Connective Tissue Growth Factor (CTGF) and releases deliveries a few parts, which are more strong than the parent particle to actuate fibrosis.33\n\nThe study's limitation is that the evaluation was done solely by looking at the level of MMP-13 immunoexpression. Further research will be required to assess the changes in the alveolar bone using intra-oral radiographic examination. Further research can also be carried out with a longer observation period to estimate the expression of other molecular markers of the periodontal tissue and alveolar bone and are also needed to confirm the effective dose of the biomaterial used when ready for use in human clinical trials.\n\n\nConclusion\n\nIn conclusion, the administration of PRF and HA was capable of reducing the MMP-13 expression that significantly accelerate the socket healing process. This study that used platelet concentrates as growth factors and hydroxyapatite as scaffold is the best combination and can be utilised as an alternative therapy. Moreover, hydroxyapatite is an alloplastic material that has inherent bioactive properties that support osteoconduction, can bind MMPs, and showed faster healing results based on the observation time as documented by immunohistochemistry.\n\n\nAuthor contributions\n\nMMD and MR conceived the plan of this research. MMD wrote the manuscript. MMD analysed the data and made the figures. MMD edited the manuscript. MMD is responsible for research in the animal laboratory, MR did the analysis of MMP-13 evaluation, and MMD supervised the whole research. All authors revised and approved the manuscript for final submission.\n\n\nData availability\n\nFigshare: Underlying data for ‘Pre-Clinical Study: Immunohistochemical evaluation of matrix metalloproteinase-13 on Rabbit (Oryctolagus cuniculus) socket healing after application of platelet-rich fibrin with and without hydroxyapatite’\n\nHistopathological of IHC MMP-13\n\nhttps://doi.org/10.6084/m9.figshare.16529847.22\n\nThis project contains the following underlying data:\n\n= MMP-13 C 3 100×.tiff (immunoexpression of MMP-13 control group in Day 3 observation at 100× magnification).\n\n= MMP-13 C 3 400×.tiff (immunoexpression of MMP-13 control group in Day 3 observation at 400× magnification).\n\n= MMP-13 C 7 100×.tiff (immunoexpression of MMP-13 control group in Day 7 observation at 100× magnification).\n\n= MMP-13 C 7 400×.tiff (immunoexpression of MMP-13 control group in Day 7 observation at 400× magnification).\n\n= MMP-13 C 14 100×.tiff (immunoexpression of MMP-13 control group in Day 14 observation at 100x magnification).\n\n= MMP-13 C 14 400x.tiff (immunoexpression of MMP-13 control group in Day 14 observation at 400× magnification).\n\n= MMP-13 PRF 3 100×.tiff (immunoexpression of MMP-13 PRF group in Day 3 observation at 100× magnification).\n\n= MMP-13 PRF 3 400×.tiff (immunoexpression of MMP-13 PRF group in Day 3 observation at 400× magnification).\n\n= MMP-13 PRF 7 100×.tiff (immunoexpression of MMP-13 PRF group in Day 7 observation at 100× magnification).\n\n= MMP-13 PRF 7 400×.tiff (immunoexpression of MMP-13 PRF group in Day 7 observation at 400× magnification).\n\n= MMP-13 PRF 14 100×.tiff (immunoexpression of MMP-13 PRF group in Day 14 observation at 100× magnification).\n\n= MMP-13 PRF 14 400×.tiff (immunoexpression of MMP-13 PRF group in Day 14 observation at 400× magnification).\n\n= MMP-13 PRF+HA 3 100×.tiff (immunoexpression of MMP-13 PRF+HA group in Day 3 observation at 100× magnification).\n\n= MMP-13 PRF+HA 3 400×.tiff (immunoexpression of MMP-13 PRF+HA group in Day 3 observation at 400× magnification).\n\n= MMP-13 PRF+HA 7 100×.tiff (immunoexpression of MMP-13 PRF+HA group in Day 7 observation at 100× magnification).\n\n= MMP-13 PRF+HA 7 400×.tiff (immunoexpression of MMP-13 PRF+HA group in Day 7 observation at 400× magnification).\n\n= MMP-13 PRF+HA 14 100×.tiff (immunoexpression of MMP-13 PRF+HA group in Day 14 observation at 100× magnification).\n\n= MMP-13 PRF+HA 14 400×.tiff (immunoexpression of MMP-13 PRF+HA group in Day 14 observation at 400× magnification).\n\nFigshare: Histoscore of IHC MMP-13\n\nhttps://doi.org/10.6084/m9.figshare.16531398.20\n\nThis project contains the following underlying data:\n\n= Histoscore C PRF PRF+HA (Multiplication of distribution and intensity of MMP-13 among group: control, PRF, and PRF+HA)\n\n= Histoscore C 3, 7, 14 (Multiplication of distribution and intensity of MMP-13 in control group based on observation time)\n\n= Histoscore PRF 3, 7, 14 (Multiplication of distribution and intensity of MMP-13 in PRF group based on observation time)\n\n= Histoscore PRF+HA 3, 7, 14 (Multiplication of distribution and intensity of MMP-13 in PRF+HA group based on observation time)\n\n= Histoscore 3, 7, 14 (Multiplication of distribution and intensity of MMP-13 among group based on observation time)\n\nFigshare: ARRIVE checklist for ‘Pre-Clinical Study: Immunohistochemical evaluation of matrix metalloproteinase-13 on Rabbit (Oryctolagus cuniculus) socket healing after application of platelet-rich fibrin with and without hydroxyapatite’\n\nhttps://doi.org/10.6084/m9.figshare.16640299.16\n\nThis project contains the following underlying data:\n\n= ARRIVE guidelines checklist full\n\nFigshare: Figure of Table for ‘Pre-Clinical Study: Immunohistochemical evaluation of matrix metalloproteinase-13 on Rabbit (Oryctolagus cuniculus) socket healing after application of platelet-rich fibrin with and without hydroxyapatite’\n\nhttps://doi.org/10.6084/m9.figshare.16641181.34\n\nThis project contains the following underlying data:\n\n= Table 1 (Table of histoscore difference of MMP-13 between groups)\n\n= Table 2 (Table of differentiation of each treatment groups by observation times on Day 3, Day 7, and Day 14)\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "Acknowledgements\n\nThe authors would like to thank to the Laboratory Department of Pathology Anatomy Hasan Sadikin General Hospital Bandung, Laboratory Biomedical Faculty of Medicine University of Islam Bandung, and special copyeditor.\n\n\nReferences\n\nCohen N, Cohen-Lévy J: Healing processes following tooth extraction in orthodontic cases. J Dentofac Anom Orthod. 2014; 17(3). Publisher Full Text\n\nPagni G, Pellegrini G, Giannobile WV, et al.: Postextraction Alveolar Ridge Preservation: Biological Basis and Treatments. Senel FC, editor. Int J Dent. 2012; 2012: 151030. PubMed Abstract \| Publisher Full Text\n\nCaley MP, Martins VLC, O’Toole EA: Metalloproteinases and Wound Healing. Adv Wound Care. 2015 Apr 1; 4(4): 225–234. PubMed Abstract \| Publisher Full Text\n\nAlzahrani AA, Murriky A, Shafik S: Influence of platelet rich fibrin on post-extraction socket healing: A clinical and radiographic study. Saudi Dent J. 2017; 29(4): 149–155. PubMed Abstract \| Publisher Full Text Reference Source\n\nLi H, Wang D, Yuan Y, et al.: New insights on the MMP-13 regulatory network in the pathogenesis of early osteoarthritis. Arthritis Res Ther. 2017; 19(1): 1–12. Publisher Full Text\n\nDick MK, Miao JH, Limaiem F: Histology, fibroblast. StatPearls; 2020.\n\nPolo-Corrales L, Latorre-Esteves M, Ramirez-Vick JE: Scaffold design for bone regeneration. J Nanosci Nanotechnol. 2014; 14(1): 15–56. Publisher Full Text\n\nAnitua E, Murias-Freijo A, Alkhraisat MH, et al.: Clinical, radiographical, and histological outcomes of plasma rich in growth factors in extraction socket: a randomized controlled clinical trial. Clin Oral Investig. 2015; 19(3): 589–600. PubMed Abstract \| Publisher Full Text\n\nAlbanese A, Licata ME, Polizzi B, et al.: Platelet-rich plasma (PRP) in dental and oral surgery: from the wound healing to bone regeneration. Immun Ageing. 2013; 10(1): 23. PubMed Abstract \| Publisher Full Text\n\nPreeja C, Arun S: Platelet-rich fibrin: Its role in periodontal regeneration. Saudi J Dent Res. 2014; 5(2): 117–122. Publisher Full Text Reference Source\n\nYelamali T, Saikrishna D: Role of Platelet Rich Fibrin and Platelet Rich Plasma in Wound Healing of Extracted Third Molar Sockets: A Comparative Study. J Maxillofac Oral Surg. 2015; 14(2): 410–416. PubMed Abstract \| Publisher Full Text\n\nZhang Y, Ruan Z, Shen M, et al.: Clinical effect of platelet-rich fibrin on the preservation of the alveolar ridge following tooth extraction. Exp Ther Med. 2018; 15(3): 2277–2286. PubMed Abstract \| Publisher Full Text\n\nMiron RJ, Fujioka-Kobayashi M, Bishara M, et al.: Platelet-rich fibrin and soft tissue wound healing: a systematic review. Tissue Eng Part B Rev. 2017; 23(1): 83–99. Publisher Full Text\n\nKrishnan V, Bhatia A, Varma H: Development, characterization and comparison of two strontium doped nano hydroxyapatite molecules for enamel repair/regeneration. Dent Mater. 2016; 32(5): 646–659. Publisher Full Text Reference Source\n\nHu Q, Ecker M: Overview of MMP-13 as a Promising Target for the Treatment of Osteoarthritis. Int J Mol Sci. 2021; 22(4): 1742. PubMed Abstract \| Publisher Full Text\n\nDamayanti M, Rachmawati M: ARRIVE guidelines checklist full.2021. Reference Source\n\nAbdullah BJ, Atasoy N, Omer AK: Evaluate the effects of platelet rich plasma (PRP) and zinc oxide ointment on skin wound healing. Ann Med Surg. 2019; 37: 30–37. PubMed Abstract\n\nNugraha HK, Muljanti M, Hernaningsih Y, et al.: Platelet rich plasma preparation protocols: a preliminary study. Indones J Trop Infect Dis. 2012; 3(2): 104–107. Publisher Full Text\n\nSalaün M, Peng J, Hensley HH, et al.: MMP-13 In-Vivo Molecular Imaging Reveals Early Expression in Lung Adenocarcinoma. PLoS One. 2015 Jul 20; 10(7): e0132960. PubMed Abstract \| Publisher Full Text\n\nDamayanti M, Rachmawati M: MMP-13 histoscore results based on treatment group and observation time.2021. Reference Source\n\nDamayanti M: Data of Nutritional Satatus and Affecting Factors.2021. Reference Source\n\nDamayanti M, Rachmawati M: Histopatological of periodontal tissue with IHC MMP-13.2021. Reference Source\n\nSzcześ A, Hołysz L, Chibowski E: Synthesis of hydroxyapatite for biomedical applications. Adv Colloid Interface Sci. 2017; 249: 321–330. Publisher Full Text\n\nNyberg E, Holmes C, Witham T, et al.: Growth factor-eluting technologies for bone tissue engineering. Drug Deliv Transl Res. 2016; 6(2): 184–194. PubMed Abstract \| Publisher Full Text\n\nBansal M, Kumar A, Puri K, et al.: Clinical and histologic evaluation of platelet-rich fibrin accelerated epithelization of gingival wound. J Cutan Aesthet Surg. 2016; 9(3): 196. PubMed Abstract \| Publisher Full Text\n\nWan Y, Li W, Liao Z, et al.: Selective MMP-13 inhibitors: promising agents for the therapy of Osteoarthritis. Curr Med Chem. 2020; 27(22): 3753–3769. PubMed Abstract \| Publisher Full Text\n\nHuang S-H, Law C-H, Kuo P-H, et al.: MMP-13 is involved in oral cancer cell metastasis. Oncotarget. 2016; 7(13): 17144. PubMed Abstract \| Publisher Full Text\n\nLi Y, Sun B, Zhao X, et al.: MMP-2 and MMP-13 affect vasculogenic mimicry formation in large cell lung cancer. J Cell Mol Med. 2017; 21(12): 3741–3751. PubMed Abstract \| Publisher Full Text\n\nToriseva M, Laato M, Carpén O, et al.: MMP-13 Regulates Growth of Wound Granulation Tissue and Modulates Gene Expression Signatures Involved in Inflammation, Proteolysis, and Cell Viability. PLoS One. 2012 Aug 7; 7(8): e42596. PubMed Abstract \| Publisher Full Text\n\nElsayed MT, Hassan AA, Abdelaal SA, et al.: Morphological, antibacterial, and cell attachment of cellulose acetate nanofibers containing modified hydroxyapatite for wound healing utilizations. J Mater Res Technol. 2020; 9(6): 13927–13936. Publisher Full Text\n\nSamadian H, Salehi M, Farzamfar S, et al.: In vitro and in vivo evaluation of electrospun cellulose acetate/gelatin/hydroxyapatite nanocomposite mats for wound dressing applications. Artif cells, Nanomedicine, Biotechnol. 2018; 46(sup1): 964–974. Publisher Full Text\n\nWardhana AS, Nirwana I, Budi HS, et al.: Role of Hydroxyapatite and Ellagic Acid in the Osteogenesis. Eur J Dent. 2021; 15(01): 8–12. Publisher Full Text\n\nGeorge J, Tsutsumi M, Tsuchishima M: MMP-13 deletion decreases profibrogenic molecules and attenuates N-nitrosodimethylamine-induced liver injury and fibrosis in mice. J Cell Mol Med. 2017; 21(12): 3821–3835. PubMed Abstract \| Publisher Full Text\n\nDamayanti M, Rachmawati M: Figure of Table.2021. Reference Source" }	[ { "id": "119475", "date": "07 Feb 2022", "name": "Niswati Fatmah Rosyida", "expertise": [ "Reviewer Expertise biomaterial", "orthodontic tooth movement" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\n1. Abstract:\n- Kindly rewrite the conclusion in the abstract, because the conclusion is different from the result of this study.\n2. Method:\n- Kindly mention the production company of the material used.\n-\"The animals were not selected on the basis of sex and age because they did not affect the treatment\". Kindly comment on this statement. Please add the literature which proves that statement.\n- Please mention the reason not to control the age of animals?\n- Kindly describe the preparation of PRF+HA. Mention the formulation of PRF and PRF+HA which were used in this study, the concentration of each material, the dosage, and dosage form.\n- \"...the immunoexpression scores of MMP-13 were evaluated by a qualified pathologist.\" - please describe how intra-examiner calibrations were measured.\n-\"...if normally distributed, and parametric tests were performed. The evaluation of MMP-13 among the groups and observation times was performed statistically with the Kruskal–Wallis test\". Please add the reason for using a nonparametric test (Kruskal Wallis).\n3. Results:\n- Kindly revise the legend of the table.\n- Please add an asterisk or similar sign to highlight where there are significant differences between the groups.\n- Kindly revise the legend of the table. Add the information of magnification.\n4. Discussion:\n- \"...there was a significant difference based on the observation time from Day 3 to Day 14.\" - kindly add literature in paragraph two of the discussion which strengthens this result.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8599", "date": "01 Aug 2022", "name": "META DAMAYANTI", "role": "Author Response", "response": "We want to thank the invited reviewer for their valuable comments and suggestions. We feel that the scientific value of our manuscript has increased significantly. This revised version of the manuscript includes the following significant adjustment as suggested by the reviewer. We have proofread the manuscript a couple of times. Thank you for your review. I have just submitted version 2. To answer point-by-point: Abstract: - Kindly rewrite the conclusion in the abstract, because the conclusion is different from the result of this study. A revised abstract about the conclusion has been added in the new versions. Method: - Kindly mention the production company of the material used. References for the product of material used have been added in the revised version. Also, we generated and utilized the commonly used product. -\"The animals were not selected on the basis of sex and age because they did not affect the treatment\". Kindly comment on this statement. Please add the literature which proves that statement. Thank you for making us aware of this. We followed your suggestion, and we added this to the script. As in all studies here, we mentioned that gender had no effect because we assumed no hormonal influence on oral wound healing. However, I will add gender-specific criteria because our study used male and adult animal models. However, for age, we have revised it by adding an age range as an inclusion criterion. - Please mention the reason not to control the age of animals? Thanks for mentioning this. I missed a clear statement of inclusion criteria, and a more detailed age range will also be corrected. - Kindly describe the preparation of PRF+HA. Mention the formulation of PRF and PRF+HA which were used in this study, the concentration of each material, the dosage, and dosage form. Thank you for letting us know that this explanation has gotten lost somehow. The methodology has been clarified, such as formulations of PRF and PRF+HA, the concentration of each material, the dosage, and the dosage form used in the study. Materials and methods have been described more accurately as suggested in the new versions. - \"...the immunoexpression scores of MMP-13 were evaluated by a qualified pathologist.\" - please describe how intra-examiner calibrations were measured. Evaluation by a qualified pathologist has been described as well as how intra-examiner calibration is measured, including several points to address the importance of this research study evaluation method. -\"...if normally distributed, and parametric tests were performed. The evaluation of MMP-13 among the groups and observation times was performed statistically with the Kruskal–Wallis test\". Please add the reason for using a nonparametric test (Kruskal Wallis). In the revised text, we have corrected the error of the normal to abnormal distribution, so that a non-parametric test with the Kruskal-Wallis test was performed. Because in this study we want to examine differences in stratified groups. Additions suggested by reviewers have also been added detailed in the methods section. Results: - Kindly revise the legend of the table. Thank you for your detailed comment. We replaced the revised table in the new version paper. - Please add an asterisk or similar sign to highlight where there are significant differences between the groups. Thank you for the suggestions. We have been adding a similar sign to highlight significant differences between the groups and are now uniform throughout the manuscript to increase readability. - Kindly revise the legend of the table. Add the information of magnification. The legend of the table and information on magnification has been fully addressed in the revised text. Discussion: - \"...there was a significant difference based on the observation time from Day 3 to Day 14.\" - kindly add literature in paragraph two of the discussion which strengthens this result. The comment in the discussion section to strengthen the result has been addressed in the revised text by providing more literature." } ] }, { "id": "142579", "date": "04 Jul 2022", "name": "Joao Vitor dos Santos Canellas", "expertise": [ "Reviewer Expertise Evidence-based dentistry", "Systematic reviews", "meta-analysis", "clinical trials", "and Platelet-rich fibrin." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors make quite an effort trying to evaluate in a preclinical study the use of PRF with and without HA in socket healing. However, there are some points that need clarification. Comments:\n\nThe title and the abstract of this study are appropriate, direct, and descriptive.\n\nThe authors reported that the sample size was determined using the Mead equation. However, they should describe how the sample size was determined exactly, including the values used to achieve the sample of 18 rabbits. Small sample sizes may make it difficult to determine if the outcome is a true finding or a type II error.\n\nThe authors reported that the animals were randomly divided into three groups, but they did not explain the method used to assign rabbits interventions. Bias arising from the randomization process can occur if the method of allocation is not adequately or not truly random.\n\nImportant differences among commercial HA result from chemical proprieties and the manufacturing process. Authors should detail what HA was used in this research. Many studies reported that two similar alloplastic biomaterials could produce different clinical results.\n\nAuthors should remove the sentence “…The limitation of this study is that, after tooth extraction, intervention was executed on the basis of the treatment group, and then simple stitches was performed. However, stitches can loosen up if the experimental animal is too active in moving its teeth and tongue, even making the stitches to come off.’’ From the method section. This information should be included in the discussion section.\n\nA detailed description must be reported in all studies related to PRF to increase the transparency of research. Please, provide the centrifugation device used, as well as the rotor angulation, radius at the clot, and tube characteristics. Each of mentioned parameters may influence regeneration success.\n\nBias in the measurement of the outcomes can occur when the researcher involved in outcome analysis is not blind to the assigned interventions. Please inform if the qualified pathologist was blinded. If not, include this information in the study limitation paragraph.\n\nAuthors use a surrogated outcome, \"MMP-13 immunoexpression” to evaluate alveolar changes after tooth extraction. Discuss the limitations of this examination and other possible limitations of the present preclinical study.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8598", "date": "01 Aug 2022", "name": "META DAMAYANTI", "role": "Author Response", "response": "The authors thank reviewer for the excellent review of the paper and for the in-depth suggestions made to improve the quality of the article. The followings are the responses to the recommendations of the reviewer. The valuable suggestions and corrections are incorporated cautiously, and the paper is made more transparent while revising the manuscript. All changes have been made in response to the reviewer. I have just submitted version 2. Furthermore, to answer point-by-point: The authors reported that the sample size was determined using the Mead equation. However, they should describe how the sample size was determined exactly, including the values used to achieve the sample of 18 rabbits. Small sample sizes may make it difficult to determine if the outcome is a true finding or a type II error. The exact determined sample has been updated as suggested to avoid an error. This approach further allowed us to reduce the required number of animals according to the principle of the three R’s (replacement, reduction, and refinement) and ARRIVE 2.0 guidelines for animal handling. The authors reported that the animals were randomly divided into three groups, but they did not explain the method used to assign rabbits interventions. Bias arising from the randomization process can occur if the method of allocation is not adequately or not truly random. We applied simple random sampling to divide into three groups of treatment and then three groups of observation time. Randomization processes for the animal study have been described in greater detail in the new version manuscript. Important differences among commercial HA result from chemical proprieties and the manufacturing process. Authors should detail what HA was used in this research. Many studies reported that two similar alloplastic biomaterials could produce different clinical results. We agree that there are differences between commercial HA. Because we already have experience with HA. We use HA material with the brand that is most often used by dentists today, namely a modification made from the Gama-Cha brand. We recognize the limitations of the ingredients, and we agree that further research is needed to see how commercial HA administration differs from homemade biocompatible products. Authors should remove the sentence “…The limitation of this study is that, after tooth extraction, the intervention was executed on the basis of the treatment group, and then simple stitches was performed. However, stitches can loosen up if the experimental animal is too active in moving its teeth and tongue, even making the stitches to come off.’’ From the method section. This information should be included in the discussion section. We have deleted the sentences regarding the statement above. We agree with the comment that it should be removed. This aspect has consequently been removed from the text, and more explained in the discussion section. A detailed description must be reported in all studies related to PRF to increase the transparency of research. Please, provide the centrifugation device used, as well as the rotor angulation, radius at the clot, and tube characteristics. Each of mentioned parameters may influence regeneration success. Thank you for your helpful report. Your suggestions have allowed us to improve our manuscript and present our data more accurately. We will add to the new version paper, and more detailed documentation will also be provided. Bias in the measurement of the outcomes can occur when the researcher involved in outcome analysis is not blind to the assigned interventions. Please inform if the qualified pathologist was blinded. If not, include this information in the study limitation paragraph. Thank you for your comment. Blind observers (pathologists) assigned random areas of IHC photographed using a Leica microscope without knowing the group identity on histopathology slides. We added this more detailed explanation to the materials and methods section. Revisions have been included in the revised text. Authors use a surrogated outcome, \"MMP-13 immunoexpression” to evaluate alveolar changes after tooth extraction. Discuss the limitations of this examination and other possible limitations of the present preclinical study. The limitations of this examination and other possible limitations of the present preclinical study have been included in the revised text." } ] } ]	1	https://f1000research.com/articles/11-29
https://f1000research.com/articles/11-923/v1	11 Aug 22	{ "type": "Research Article", "title": "Analysis of hydroxychloroquine adverse events in COVID-19 patients reported throughout Iraqi pharmacovigilance center in VigiBase™: A study based on WHO database", "authors": [ "Yasir A. Noori", "Inam S. Arif", "Manal M. Younus", "Mohammed Mahmood Mohammed", "Inam S. Arif", "Manal M. Younus", "Mohammed Mahmood Mohammed" ], "abstract": "Background: Hydroxychloroquine is a long-used medication, most commonly used to treat and prevent malaria, that also has anti-inflammatory and antiviral characteristics. Therefore, specialists have shown interest in the underlying mechanism of its antiviral activity. In vitro experiments have demonstrated its efficiency against SARS coronavirus, and in vitro and in vivo research on coronavirus disease 2019 (COVID-19) is being conducted. We aimed to investigate reports on adverse events of hydroxychloroquine submitted to the Iraqi Pharmacovigilance Centre and compare the incidence of these reported adverse events in Iraq to globally reported cases during the COVID-19 pandemic in 2020 using information component (IC)025 values. Methods: The reported adverse events of hydroxychloroquine to the national Pharmacovigilance database, VigiBase™ a WHO global database of reported potential side effects of medicinal products, were investigated qualitatively (age, sex, and severity) and quantitatively (using IC025) as a measure of the existence of new/altered safety information associated with hydroxychloroquine. Results: A total of 132 reports were found, with women representing 37.1% and men representing 60.6% of cases, while the rest were unidentified, with the predominant age groups ranging from 18–44 years old accounting for 47.4% of cases. The most reported adverse events were upper (17%) and lower abdomen pain (21%), nausea (14%), diarrhea (13%), and electrocardiogram (ECG) QT prolongation (13%). There were 44 different drug-adverse reaction pairings in which the adverse reaction reports included more than one event. The IC025 value for the most widely reported adverse events showed a positive comparable value for upper (2/0.3) and lower abdominal pain (1.8/-0.0), palpitation (1.6/-0.4), and dyspepsia (1.1/0.6). There was a decreased value for IC025 in cases of ECG QT prolongation (3.5/5), diarrhea (0.3/0.8), abdominal discomfort (0.1/2), and oral fungal infection (-0.4/0.6). Conclusions: The IC025 helped determine the higher reporting rate of adverse events compared to the average global rates.", "keywords": [ "COVID-19", "World Health Organization", "VigiBase", "Hydroxychloroquine", "pharmacovigilance", "adverse events" ], "content": "Introduction\n\nThe coronavirus disease 2019 (COVID-19) pandemic began in Wuhan, China, in December 2019. High body temperature, dry cough, headache, dyspnea, and diarrhea were all symptoms of this viral illness. The earliest occurrences of these symptoms were linked to a food market in Wuhan, China. Since then, some cases have developed into severe respiratory distress, with an approximate death rate of 2%.1–4 The global impact of the SARS-CoV-2 pandemic has been unprecedented, prompting the scientific community to investigate all potential remedies.5 Because hydroxychloroquine (HCQ) has previously been shown to be successful in the treatment and prevention of SARS-CoV,6 and because COVID-19 is similar to SARS-CoV, many investigators have advocated HCQ as a possible therapeutic drug.7 HCQ is a medication used in the treatment and prevention of malaria and autoimmune diseases such as rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE).8 In vitro investigations suggest that HCQ inhibits SARS-CoV-2 infection and multiplication.9–11 HCQ has antiviral action through entrance inhibition, replication inhibition, or immunological manipulation.12,13 Endosomal antigen processing is altered by HCQ, and innate and adaptive immune responses are modulated.14,15 This reduces the production of pro-inflammatory cytokines such as TNF-α, IL-1, and IL-6.\n\nFurthermore, HCQ optimizes endothelial function and suppresses the prothrombotic condition. These characteristics may benefit people with severe COVID-19.16 In patients with malaria or autoimmune disorders, the most common adverse effects of HCQ encompass gastrointestinal distress (vomiting, diarrhea, stomach cramps), skin rash, headache, dizziness, and ophthalmic toxicity. In addition, these medications may potentially induce significant adverse effects such as arrhythmia, bronchospasm, angioedema, and seizures.17 Cardio-toxicity is the most devastating adverse effect of HCQ therapy in severely infected COVID-19 patients. A double-blind clinical study from Brazil revealed that medication dose may be a contributor in HCQ cardiotoxicity.18 The purpose of this research was to examine the adverse events related to HCQ administration (alone or in combination with other medicines) in COVID-19 patients in Iraq to determine any new/altered safety information connected to HCQ.\n\n\nMethods\n\nThis was a descriptive analysis of the potential adverse events of HCQ during its use in the COVID-19 pandemic; data were collected from VigiBase™, the world’s most extensive database of more than 20 million Individual Case Safety Reports (ICSRs) submitted by members of the World Health Organization (WHO) Program for International Drug Monitoring since 1968, as well as the risk of multiple adverse events co-occurring. Sweden’s Uppsala Surveillance Centre (UMC) creates and maintains this database. VigiLyze™ was used to retrieve the reaction outcome, disproportionality measure (information component (IC)025 value), and other relevant variables. VigiLyze is a data mining and analytics tool developed for VigiBase. In addition, national centers like the Iraqi Pharmacovigilance Centre may gather adverse effects of medications and vaccines from users, healthcare personnel, and regulated pharmaceutical corporations using the e-Reporting module. E-Reporting enables the user or healthcare professional to generate, evaluate, and report adverse effects from anywhere with an internet connection using their smartphone or other devices. The reported side effects will be instantaneously accessible in VigiFlow™ as adverse event reports for further assessment.\n\nThe IC measures the disproportionality among observed and predicted reporting of adverse drug event pairing. A positive IC value implies that a specific drug adverse event combination is reported more often than expected based on all entries in the database. On the other hand, a negative IC value indicates that the drug adverse events pairing is recorded less often than predicted. The greater the IC value, the more the combination stands out from the background. The IC025 value is the lowest limit of the IC’s % credibility interval. The credibility interval indicates the stability of a particular IC value: the smaller the gap, the greater the stability.19\n\nDescriptive statistics were used to analyze the data for this investigation. This research did not include any individual case evaluations. IBM SPSS Statistics (RRID: SCR 016479) version 27 software for Microsoft Windows was employed throughout the statistical analysis procedure.\n\nThe Institutional Ethical Committee excluded this research from ethics consideration since it is based on secondary data analysis and does not include any direct interaction with human participants.\n\n\nResults\n\nThe Iraqi Pharmacovigilance Centre reviewed and recorded 132 episodes of adverse events related to HCQ use in VigiBase over 2020 in the COVID-19 pandemic; the study involved 132 ICSRs, all cases were qualitatively screened, 49 reports were found for women, which accounted for 37.1% of cases, while 80 reports were found for men (60.6% of cases), and three unknown reports 2.3% were found. The age group of affected patients varied from 28 days to 75 years, as seen in Figure 1.\n\nHCQ, hydroxychloroquine.\n\nAzithromycin is the most often documented co-reported active component with HCQ, with 45 reports as suspected/interacting and five as a concomitant, totaling 50 reports (37.9% of cases). Oseltamivir has 29 suspected/interacting reports and seven concomitant reports, for a total of 36 reports (27.3%), paracetamol has one report as suspect/interacting and 21 reports as a concomitant, for a total of 22 reports (16.7%). Centrum (an American brand of multivitamins) has one report as suspected/interacting, and 20 reports were simultaneous, for a total of 21 reports (15.7%). Enoxaparin has three reports as questioned/interacting and nine as a concomitant, 12 reports in total (9.1%). Bromhexine received no reports as suspected/interacting and 10 reports as a concomitant, for a total of 10 reports (7.6%). Meropenem has four reports as suspected/interacting and four as a concomitant, eight reports in total. Clopidogrel has five reports as suspected/interacting and one as a concomitant, total of six reports (4.5%). In a quantitative assessment of the Iraqi database, the Iraqi Pharmacovigilance Centre found 44 combinations involving 177 adverse medication reactions for patients who took HCQ in various dosage strengths throughout 2020. There were 13 instances of QT prolongation on an electrocardiogram (ECG), 17 cases of upper abdominal pain, 21 cases of abdominal pain, nine cases of palpitation, five cases of dyspepsia, 13 cases of diarrhea, four cases of abdominal discomfort, 14 cases of nausea, and two cases of oral fungal infection. Many side effects, such as upper abdominal discomfort, palpitation, and dyspepsia, are more prevalent in Iraqi records than in foreign cases. The severity of these responses was assessed at 48%. Cardiac arrest, abdominal pain, fatigue, gastroesophageal reflux disease, diarrhea, headache, and dyspepsia were among the co-reported side effects as presented in Table 1.\n\nThe Iraqi number of observed cases was compared to the expected data in VigiBase for Iraq and the global registry, as well as the Iraq-IC025/Global-IC025 ratio, sex, severity, and patient age were enlisted in Table 2.\n\n\nDiscussion\n\nFindings from this study demonstrate how a medication’s safety profile depends on how it is administered. When administered outside of its marketing authorization, any medicine, even one that is well-known and is thought to be understood, may show higher frequent and serious adverse effects than anticipated. To guarantee patient safety, spontaneous reporting and pharmacovigilance are crucial in informing healthcare providers of possible issues.20 This research found that within the first wave of the pandemic, off-label use of HCQ in patients with COVID-19 has been related to greater reporting than in the preceding years. Adverse drug reactions (ADRs) are generally predicted and are stated in the French summary of product features for PLAQUENIL®, as previously documented in a study by P. Lory et al.21 Abdominal pain and QT prolongation were the most widely reported ADRs in individuals taking HCQ for the treatment of COVID-19, which agrees with the most consistently encountered ADRs recognized by Zekarias et al., throughout an evaluation of 2,573 reports on COVID-19-specific therapies from VigiBase.22 High dosages of the antimalarial23 and concomitant treatment with azithromycin have been associated with a greater risk of significant side effects. Furthermore, the HCQ pharmacokinetics are distinguished by their prolonged half-life and a large volume of dispersion.24 The most remarkable findings are the relatively high proportion of cardiac ADRs (ECG QT prolonged = 3.5/5 of overall ICSRs), which demonstrate that HCQ may directly damage the myocardium and cause cardiac rhythm disturbances. The relatively high incidence of toxicosis also explains the low therapeutic window of HCQ.25 The current findings further reveal that the cardiac signal (QT prolongation, arrhythmias, etc.) seen with HCQ in COVID-19 patients was previously prevalent in inflammatory arthritis or SLE patients.26,27 According to Funck-Brentano et al.,28 there are several potential causes for the elevated risk of cardiac toxicity. The first one could be connected to how SARS-CoV-2 affects the heart. In reality, individuals with coronavirus infections are more likely to have drug-induced rhythm abnormalities due to frequent hypokalemia and fever, which exacerbates the effects of drug-induced cardiac channel blocking.\n\nFurthermore, elevated IL-6 levels following infection may contribute to the QT prolongation brought on by inflammation. According to Guo et al., myocardial damage linked to cardiac dysfunction and arrhythmias was seen in almost 30% of COVID hospitalized patients in a Chinese hospital. There is a strong correlation between these cardiac lesions and fatal results.29 Additionally, COVID-19 patients often received large dosages of HCQ in addition to other medications that cause QT prolongation (including azithromycin). HCQ and azithromycin were combined in 80% of the interaction situations, and the QT interval was lengthened in every single one. Other medications that interact with HCQ in a potentiating or additive way, such as spiramycin, fluoroquinolones, antivirals, or antidepressants, have also been linked to heart harm. Cardiac toxicity (QT prolongation, heart failure, and cardiac arrest) was the cause of the seven recorded fatalities during the COVID era. Our research points up several instances when a “drug interaction” with HCQ might negatively impact the heart.\n\nOur investigation has some limitations and strengths, despite the inevitable biases of such research (under-reporting, absence of extensive information on dosages and exposure period in VigiBase, use of HCQ in simultaneous rheumatic or autoimmune illnesses, and not just COVID-19). Nevertheless, the findings have significant strengths: we utilized the world’s biggest pharmacovigilance database, which includes over 90% of people worldwide, to identify and analyze possible safety signals during the COVID-19 pandemic outbreak. These worldwide database results strengthen the external validity of our findings. Furthermore, unlike clinical trials, dealing with this data from VigiBase enables us to be in the setting of real-world practice. Data from the real world that were not analyzed in clinical trials allow for outcomes’ applicability.\n\n\nConclusions\n\nThe events reported to the Iraqi pharmacovigilance center include the concurrent use of other drugs, making it difficult to verify whether HCQ is responsible for these adverse effects. According to WHO global data, most of these impacts have minor differences. However, several have negative correlations, indicating that the predicted number of cases is greater than the actual number. In addition, some of the reported side effects, such as upper abdominal discomfort, abdominal pain, palpitations, and dyspepsia, showed a significant difference in IC025 between cases reported in Iraq and those reported internationally. This adverse effect may influence patient adherence; however, it seldom affects their use.\n\n\nData availability\n\nThe raw data created and analyzed throughout the present research are still not publicly accessible due to commitments between data providers to the database utilized (VigiBase™) and the database administrator. National Iraqi pharmacovigilance center provides data to VigiBase, while the Uppsala Monitoring Centre serves as the holder in its position as a WHO cooperating center for worldwide drug monitoring. The dataset generated during the current study is not publicly available as it contains proprietary information that the authors acquired through a license. Information on how to obtain it and reproduce the analysis is available from the corresponding author on request for personal non-reproducible use to the following email address: yasiralkashab99@yahoo.com.", "appendix": "Acknowledgments\n\nThe authors express gratitude to the Iraqi Pharmacovigilance Centre for facilitating their access to VigiBase™.\n\n\nReferences\n\nBurki T: Outbreak of coronavirus disease 2019. Lancet Infect. Dis. 2020; 20(3): 292–293. PubMed Abstract \| Publisher Full Text\n\nBonyan FA, Shareef LG, Al-waily A, et al.: COVID-19 clinical characteristics and outcomes in 60 hospitalized Iraqi patients-Case series. Med. Sci. 2020; 2251–2258.\n\nShareef LG, Fawzi Al-Hussainy A, Majeed HS: COVID-19 vaccination hesitancy among Iraqi general population between beliefs and barriers: An observational study [version 2; peer review: 2 approved]. F1000Res. 2022; 11: 334. PubMed Abstract \| Publisher Full Text\n\nSabah Khalid S, Mohamed Ali Z, Shareef LG: Levels of cardiac troponin-T and LDL-C to HDL-C ratio of hospitalized COVID-19 patients: A case-control study [version 1; peer review: awaiting peer review]. F1000Res. 2022; 11: 860. Publisher Full Text\n\nSiddique A, Shahzad A, Lawler J, et al.: Unprecedented environmental and energy impacts and challenges of COVID-19 pandemic. Environ. Res. 2021; 193: 110443. PubMed Abstract \| Publisher Full Text\n\nRoldan EQ, Biasiotto G, Magro P, et al.: The possible mechanisms of action of 4-aminoquinolines (chloroquine/hydroxychloroquine) against Sars-Cov-2 infection (COVID-19): A role for iron homeostasis? Pharmacol. Res. 2020; 158: 104904. PubMed Abstract \| Publisher Full Text\n\nPastick KA, Okafor EC, Wang F, et al.: Hydroxychloroquine and chloroquine for treatment of SARS-CoV-2 (COVID-19). Oxford University Press US;2020.\n\nSingh AK, Singh A, Shaikh A, et al.: Chloroquine and hydroxychloroquine in the treatment of COVID-19 with or without diabetes: A systematic search and a narrative review with a special reference to India and other developing countries. Diabetes Metab. Syndr. Clin. Res. Rev. 2020; 14(3): 241–246. PubMed Abstract \| Publisher Full Text\n\nYao X, Ye F, Zhang M, et al.: In vitro antiviral activity and projection of optimized dosing design of hydroxychloroquine for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clin. Infect. Dis. 2020; 71(15): 732–739. PubMed Abstract \| Publisher Full Text\n\nWang M, Cao R, Zhang L, et al.: Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res. 2020; 30(3): 269–271. PubMed Abstract \| Publisher Full Text\n\nLiu J, Cao R, Xu M, et al.: Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro. Cell discovery. 2020; 6(1): 1–4. PubMed Abstract \| Publisher Full Text\n\nOscanoa TJ, Romero-Ortuno R, Carvajal A, et al.: A pharmacological perspective of chloroquine in SARS-CoV-2 infection: An old drug for the fight against a new coronavirus? Int. J. Antimicrob. Agents. 2020; 56(3): 106078. PubMed Abstract \| Publisher Full Text\n\nShareef LG, Abdulwahab SM: Trends in covid-19 therapeutic modalities: A narrative literature. Eur J Pharm Med Res. 2020; 7: 757–767.\n\nHashem AM, Alghamdi BS, Algaissi AA, et al.: Therapeutic use of chloroquine and hydroxychloroquine in COVID-19 and other viral infections: A narrative review. Travel Med. Infect. Dis. 2020; 35: 101735. PubMed Abstract \| Publisher Full Text\n\nMeyerowitz EA, Vannier AGL, Friesen MGN, et al.: Rethinking the role of hydroxychloroquine in the treatment of COVID-19. FASEB J. 2020; 34(5): 6027–6037. PubMed Abstract \| Publisher Full Text\n\nMiranda S, Billoir P, Damian L, et al.: Hydroxychloroquine reverses the prothrombotic state in a mouse model of antiphospholipid syndrome: role of reduced inflammation and endothelial dysfunction. PLoS One. 2019; 14(3): e0212614. PubMed Abstract \| Publisher Full Text\n\nYam JCS, Kwok AKH: Ocular toxicity of hydroxychloroquine. Hong Kong Med. J. 2006; 12(4): 294–304. PubMed Abstract\n\nGautret P, Lagier J-C, Parola P, et al.: Clinical and microbiological effect of a combination of hydroxychloroquine and azithromycin in 80 COVID-19 patients with at least a six-day follow up: A pilot observational study. Travel Med. Infect. Dis. 2020; 34: 101663. PubMed Abstract \| Publisher Full Text\n\nBate A, Lindquist M, Edwards IR, et al.: A Bayesian neural network method for adverse drug reaction signal generation. Eur. J. Clin. Pharmacol. 1998; 54(4): 315–321. PubMed Abstract \| Publisher Full Text\n\nSultana J, Crisafulli S, Gabbay F, et al.: Challenges for drug repurposing in the COVID-19 pandemic era. Front. Pharmacol. 2020; 11: 588654. PubMed Abstract \| Publisher Full Text\n\nLory P, Lombardi J, Lacroix C, et al.: Comparative study of the adverse event profile of hydroxychloroquine before and during the Sars-CoV2 pandemic. Therapies. 2022; 77(3): 301–307. PubMed Abstract \| Publisher Full Text\n\nZekarias A, Watson S, Vidlin SH, et al.: Sex differences in reported adverse drug reactions to COVID-19 drugs in a global database of individual case safety reports. Drug Saf. 2020; 43(12): 1309–1314. PubMed Abstract \| Publisher Full Text\n\nCortegiani A, Ingoglia G, Ippolito M, et al.: A systematic review on the efficacy and safety of chloroquine for the treatment of COVID-19. J. Crit. Care. 2020; 57: 279–283. PubMed Abstract \| Publisher Full Text\n\nCavalcanti AB, Zampieri FG, Rosa RG, et al.: Hydroxychloroquine with or without azithromycin in mild-to-moderate Covid-19. N. Engl. J. Med. 2020; 383(21): 2041–2052. PubMed Abstract \| Publisher Full Text\n\nVinetz JM, Clain J, Bounkeua V, et al.: Chemotherapy of malaria. The pharmacological basis of therapeutics. 2011; 12: 1383–1418.\n\nChorin E, Dai M, Shulman E, et al.: The QT interval in patients with COVID-19 treated with hydroxychloroquine and azithromycin. Nat. Med. 2020; 26(6): 808–809. PubMed Abstract \| Publisher Full Text\n\nYazdany J, Kim AHJ: Use of hydroxychloroquine and chloroquine during the COVID-19 pandemic: what every clinician should know. American College of Physicians. 2020; 172: 754–755. Publisher Full Text\n\nFunck-Brentano C, Nguyen LS, Salem J-E: Retraction and republication: cardiac toxicity of hydroxychloroquine in COVID-19. Lancet. 2020; 396(10245): e2–e3. PubMed Abstract \| Publisher Full Text\n\nGuo T, Fan Y, Chen M, et al.: Cardiovascular implications of fatal outcomes of patients with coronavirus disease 2019 (COVID-19). JAMA Cardiol. 2020; 5(7): 811–818. PubMed Abstract \| Publisher Full Text" }	[ { "id": "247330", "date": "21 Feb 2024", "name": "Srikanth Umakanthan", "expertise": [ "Reviewer Expertise Infectious diseases (COVID19)", "histopathology", "molecular genetics", "Oncopathology and Haematology." ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe study is on an interesting topic, the authors have tried to provide a good intention study and manuscript. However, I have serious limitations as indicated below for this manuscript. Abstract: Provide specific background information pertaining to your study. Methods needs to be more elaborated. Introduction: HCQ was initially withdrawn from use to treat COVID19 due to certain specific toxicities, that information needs to be mentioned here. The reason for selecting VigiBase and VigiLyze needs to be mentioned. Indicate the reasons for selecting qualitative and quantitative measures in your study, How were the other variables excluded (the rationale behind the selection needs to be mentioned) Results and methodology are very concise. This section forms the core of the study, and the authors need to elaborate a lot of information in their manuscript. This includes the questionnaire, if pilot study was conducted, the reasons for selecting and quantifying variables into dependent and independent types, the role of bias and how it was minimized, how HCQ was selected compared to other mentioned drugs like Azithro, PCT, Centrum, the study had more of males and less of females this reason needs to be indicated., if neonate/child was included in the study was there a specific consent obtained, the figures and tables are very simple(the authors need to be more experimental in providing detailed results in graphical form), the statistical analysis is lacking in major sections. Many references listed are of 2020, this needs to be updated with the most recent literature studies.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-923
https://f1000research.com/articles/11-920/v1	10 Aug 22	{ "type": "Review", "title": "Lessons from Indonesia, a country with highest COVID-19 mortality rate in the world: dissecting multiple aspects", "authors": [ "Muhammad Miftahussurur", "Camilia Metadea Aji Savitri", "Langgeng Agung Waskito", "Yudith Annisa Ayu Rezkitha", "Inge Dhamanti", "Diah Indriani", "Bagong Suyanto", "Raissa Virgy Rianda", "Yoshio Yamaoka", "Camilia Metadea Aji Savitri", "Langgeng Agung Waskito", "Yudith Annisa Ayu Rezkitha", "Inge Dhamanti", "Diah Indriani", "Bagong Suyanto", "Raissa Virgy Rianda", "Yoshio Yamaoka" ], "abstract": "COVID-19 has been infecting every continent and Indonesia had suffered greatly as it ranked first for confirmed cases in Southeast Asia region with almost 100,000 deaths. We summarized Indonesian population demographic, socio-behavior, multiple government policy and public health interventions contributed to the high mortality. Although the virulence of COVID-19 strain was found to be similar as other countries, it might be inaccurate due to the low amount of sequenced genome and publicly accessible data of the virus’ strain. As Indonesia recorded higher testing number than WHO’s target, there were imbalances of testing capacity between capital cities and remote areas, hence the actual case number would be larger. The availability of healthcare facilities and skilled healthcare workers were also dispersed unequally, causing Indonesian health systems near collapsing. Moreover, individual sense of urgency and hazard of the pandemic were low, as shown by the low compliance of wearing masks and social distancing. Even though Indonesia was unprepared early in the pandemic, currently these systems are being improved. Indonesia has experienced an extensive problem in conquering the pandemic, hence, the country needed a comprehensive approach from the government, citizens, even private sectors to cease the pandemic.", "keywords": [ "COVID-19", "intervention", "disease burden", "mortality" ], "content": "Introduction\n\nCoronavirus disease 2019 (COVID-19) had been declared a pandemic by World Health Organization (WHO) on January 30th 2020. It kept spreading worldwide, despite different continents separated by oceans.1 Few coronaviruses came with mild symptoms, upon exception was severe acute respiratory syndrome coronavirus (SARS-CoV) which infects more than 8,000 people in China during 2002-2003 and Middle East respiratory syndrome (MERS) coronavirus (MERS-CoV) in 2012, infected 2494 people and claimed lives of 858 in Saudi Arabia.2\n\nWorldwide confirmed cases was a staggering 196 million with more than 4 million deaths.3 Indonesia held second position only to India in Southeast Asia. Last known confirmed cases were more than three million alongside almost 100,000 deaths. With numbers growing every day, Indonesia’s case fatality rate (CFR) had reached 2.8%, higher than worldwide which is 2.2%. The CFR had been worse early in the pandemic, reaching 9% on April. COVID-19 infection had claimed myriad of lives, from the tip of Sumatera through remote islands of Molucca and Papua.4\n\nHost, agent, and environment interactions were crucial in the progression of infectious disease. Therefore, high mortality rates should be dissected from multiple aspects.5 Epidemiological assessment may be relevant to understand the patterns of transmission.6 From host side, it has been a mystery whether population characteristic and behavior contribute to the continuation of the disease. The recognition of disease’s contributing factor might give an insight to government policies. With better policies, countries would be able to control one variable in infection management. In this review, we will discuss COVID-19 infection in Indonesia thoroughly, from its genealogy, demography, to health policies and capabilities of healthcare resources. Some information will be our original investigation. These data support our hypothesis regarding the reason behind the worse condition in Indonesia.\n\nAmong Southeast Asia nation countries, Indonesia was leading for confirmed cases.7 Indonesia had crossed the one million mark on January 26th, 2021. Daily addition of confirmed cases ranged around 30,000 cases, currently around 30,000-40,000.4 Highest record of new confirmed cases of 56,757 people had been reported on July 15th. Moreover, Indonesia had the highest deaths of almost 100,000 people.8 As of August 1st 2021, Indonesia had more than 3.4 million confirmed cases with more than 500,000 active cases.4 Currently, the case progression is soaring.\n\nThe distribution of cases varied across the country. With 34 provinces and population of 240 million, each province had different demographic, infrastructures, and socioeconomic conditions. Jakarta, the capital city of Indonesia held most cases of more than 260,000, followed by West Java, East Java, Central Java, and South Sulawesi. The capital counted 2,487 cases per 100,000 people, the highest in the country. On the other hand, East Java held first position for deaths of 7,805 people (6.92% deaths out of all confirmed cases).9 It seemed higher case number did not align with higher population; even though larger population made more potential hosts for the virus,10 since Jakarta was not the most populated city. However, it is the province with the highest population density of 16,704 people per km2, therefore, with higher density and mobility, is a promoting factor for COVID-19 transmission.11\n\nStudies from India12 and Algeria13 concluded that case number grew as urban density climbs. Provinces in Indonesia had different result, nevertheless. There were few provinces with higher cases amidst less population density and vice versa. This paradox could stem from the uneven availability of diagnostic tools in some areas, while many lived in remote ones. Even though Indonesia had tested more than 300,000 people,14 almost half originated from Jakarta alone. This phenomenon revealed testing imbalances in other 33 provinces. Moreover, there were vague sources whether the number stands for one person-one testing or one person tested more than once. Therefore, adequate availability of diagnostic tools across country to equalize testing coverage is essential. Adequate diagnosis would help isolate and contain the disease.\n\nThe SARS-CoV-2 genome is a single stranded positive-sense RNA.15 This virus has ~30Kb in size, 38% of GC ratio and composed of 13-15 open reading frames (ORFs). It has 11 protein-coding genes with 12 expressed proteins among the constructed ORFs. The ORFs arrangement is very similar with SARS-CoV and MERS-CoV.16,17 It is arranged as replicase and protease (1a-1b), followed by major S, E, M and N protein in a typical 5′-3′ order. These protein products play an essential role in pathogenesis, attachment, fusion, and survival in host cells.\n\nRecent universally-used classification methods for SARS-CoV-2 are Nextstrain,18 GISAID19 clades and PANGO lineages.20 Both Nextstrain and GISAID described a broad-brush characterization of globally available databases, whereas pangolin lineages aimed at the outbreak sources in a dynamic manner.20 The latter grant access to create variants based on several occurred mutations, currently referred as Variants of Interest (VOI) and Variant of Concern (VOC) by WHO and CDC. VOCs had evidence to high transmissibility or virulence with reduction of neutralization ability through vaccination or natural immunity and evade detection. The VOI solely reported as genetic marker that might be correlated to some characteristic that VOC has, with evidence of increased case proportion.21\n\nIndonesian SARS-CoV-2 had currently deposited 2,549 genomes in GISAID. Indonesian SARS-CoV-2 had VOI of Eta (5 genomes), Iota (2 genomes) and Kappa (2 genomes). As for VOC were Delta (382 genomes) and Alpha (49 genomes). The Delta variant or B.1.617.2 lineage were predominantly found especially in sequences submitted after April 2021. It is characterized by spike mutations of T19R, G142D, Δ157-158, L452R, T478K, D614G, P681R, and D950N.22 The prime feature of this variant is its high transmissibility, potential reduction in neutralization by some EUA monoclonal antibody and potential post-vaccination immunity reduction.23,24 Therefore, Delta might be responsible for Indonesia’s current second wave, as it is also reported as the main cause of second wave in India.21 Alpha variant, first emerged in England, is the second most predominant in Indonesian SARS-CoV-2. It is characterized by seven missense mutations (N501Y, A570D, D614G, P681H, T716I, S982A, D1118H) and three deletions in spike (69/70del and 144del).22 Therefore, dissemination of these variants in Indonesia might be due to the lack of international travel restrictions.\n\nThe accelerated number of sequenced viruses is essential for genome surveillance to understand circulating viruses in population. However, it only covered for less than 1% of total cases in Indonesia. As the available genome sequencing equipment are centralized in capital cities, the tiny proportion of virus collected might lead to the misinterpretation of current circulating virus. Therefore, increased availability of genome sequencing equipment or divergent distribution for viral DNA transport across country is crucial.\n\nCOVID-19 had brought substantial changes on how people lived. One underlying factor was the perceived the risk of getting infected.25 Moreover, proper knowledge of COVID-19 and awareness for WHO recommendations were equally essential.26 Case numbers in Indonesia are proliferating, owing to not only multiple violations of preventive measures, but also a lack of social construct of COVID-19 to begin with. Some even concluded COVID-19 as a harmless disease.27\n\nSince there is no definitive treatment available, the government had implemented multiple preventive measures. However, data from the Indonesian government stated that only 29% of all cities nationwide had >90% docility to wear masks. Restaurants were the primary place where people do not wear masks, followed by private housing and public places. The social-distancing compliance also had similar results with gym, home, and tourist attractions as places where people do not socially distanced.28 This phenomenon can be attributed to the lenient implementation of these measures, complemented by the lack of knowledge and awareness. On the contrary, a study of a student population in China found that 75% considered wearing masks when going outside is beneficial for themselves, even when the pandemic is over.25\n\nStudies have found health behavior to be influenced by perceived severity and susceptibility of COVID-19.29–31 One study found older people regarded themselves as more susceptible to the disease,30 while other study found older people worried less than younger ones.32 Awareness to the disease was more emphasized by highly educated people. Older and educated people lean more towards comply with precautionary measures.30 In addition, adherences to precautionary measures were found to be correlated with trust in the government, probably due to the validity of information they have given.33 Indonesians had low confidence in the government in COVID-19 management, which might be the reason why there was low compliance on preventive measures nationwide.34,35 As fear of the disease is associated with motivation of engaging to behavioral change,36 broadening the sense of crisis and awareness of COVID-19 are imperative, with the expectation of increased awareness in Indonesians.\n\nIndonesia had been preparing for COVID-19 since January, by assembling referral hospitals, strict supervision in entry routes (airports, harbors, roads), and performing detection in risky cities with direct access to China. Early on, non-pharmaceutical interventions (NPIs) were applied to inhibit transmissions. Individual measures include hand hygiene, usage of mask, social distancing, isolation, quarantine for contacts, and avoidance of crowded places. Environmental measures could be achieved by well ventilated rooms and routine cleaning of surfaces exposed to public. Community measures include restricting access to public places which were not essential to daily life.37 Moreover, task forces were formed,38 hospitals for COVID-19 were added, school and public prayer places were closed. Despite of NPIs, WHO recommended detection and isolation of infected individuals, contact tracing, treatment regimen, and travel measures regulation.26\n\nIn April, large-scale social restrictions were applied at multiple cities in Indonesia, with protocol to close schools, offices, public places as well as restriction of public transportation. Massive scale of social distancing would have the largest impact, especially when combined with other interventions.39 Measures were taken as cluster cases have been reported in confined and crowded places such as shopping malls, offices, public transportations, and hospitals. Moreover, several officials in some countries were diagnosed with COVID-19 after participating in public gatherings without masks.40\n\nEarly intervention was essential to suppress transmission before overwhelming healthcare resources.39 China did a lockdown policy after the virus was identified. It appeared to be effective, showed by flattened curve, considering it has high population density. China’s first wave lasted only for 20 days, while majority of countries lasted over 40 days. Countries with shorter first wave includes South Korea, which also has strict lockdown policies.41 Unfortunately, restrictions in Indonesia did not seem to flatten the curve. The failure was probably due to its short duration and inability to maintain the policy persistently. Hence, transmission could rebound, potentially at the scale in which no interventions had been implemented.39\n\nWhile Indonesia was incapable to implement prolonged mass social restrictions, combination of case isolation, self-quarantine, and social distancing can be alternatives.39 Most of Indonesia’s cluster cases occurred in office settings, raising concern whether health protocols in workplaces are effective.42 As of 9th November 2020, the highest number of cluster cases was held by Indonesian Ministry offices of 1,935 cases; with Ministry of Transportation (332 cases) and Health Ministry (314 cases) in first and second, followed by private offices (1,533 cases).43\n\nMore flexible interventions to compensate economic burden can be done if high-risk groups are carefully protected.44 Indonesian government had enforced vaccination for population at risk, with the hope for a fully vaccinated country. However, doubts circulating the vaccine efficiency shadowed the program. As of February 3rd 2021, only 600,000 healthcare workers out of the 1.5 million have been vaccinated.45 Even though vaccination had started, citizens will require mask for months or even years to come, since asymptomatic COVID-19 spread was a huge issue early on. Moreover, vaccine needed time to develop immunity.\n\nGovernment policy had gravitated toward the lenient way. The name might have changed but there were voids in implementation. Enforcement of these policies, both as an example by government officials and citizens, is paramount, considering Indonesia’s new record cases every day. However, the longer the pandemic, more strain were put on healthcare, hence, more burden will arise in various sectors.\n\nOne year to the pandemic and yet, definitive treatment has not available although vaccines showed promising results. Lack of resources complicates the capability to provide adequate testing, setting up isolation wards, and providing critical care.26 Indonesia had 2,813 hospitals with various accreditation and ownership status.46 From those, government have appointed 940 COVID-19 referral hospitals and even requested non-referral hospitals to provide service to COVID-19 patients.\n\nHospitals around the world have been overwhelmed by the pandemic beyond their available reserves. The field assessment of pandemic preparedness conducted in fifteen provinces identified gaps in the healthcare system, such as the availability of ICUs and other facilities in the event of increased cases.47 In September 2020, the community health centers and ambulances were struggling to refer patients to temporary hospitals in Jakarta.48 Meanwhile in January 2021, the occupancy rate of referral hospitals in Jakarta entered critical points at 95%.49\n\nDuring the pandemic, temporary hospitals were the solution because they were cheaper and easier to build and run.50 It had significantly improved diagnosis, admission, and treatment.51 Protocols and procedures needed to be developed as soon as the hospital operates. Moreover, healthcare workers (HCWs) and staffs needed training in infection control to ensure safe, high-quality, and efficient service51 because rapid redesign and redeployment of health system around the world created environment that threaten patient safety and to some extent, promote the development of harmful malpractices.52 Most of the participants in our study described that hospitals need to adjust the hospital service flow, add infrastructures, carry out screening at emergency departments, apply zoning areas, and cohort COVID-19 patients. We also found types of administrative errors, delayed referral and care, prescription errors, and misdiagnoses. Delayed care has been identified more than other accidents. Administrative errors were found higher in field or temporary hospitals while delayed treatment were found at all types of hospitals.\n\nDespite the availability of healthcare facilities, WHO has been raising concern for scarcity of HCWs worldwide, especially in developing countries. Contributing factors are poor remuneration and working conditions, completed with pandemic situation.53 In Indonesia, more than 200 healthcare workers’ lives have been taken by COVID-19. With a very low doctor to population ratio; only 1:250,000. Deceased doctors cannot be replaced easily since the experience will not match up. Each hospital had different strategies to manage this problem, for example, by using medical, nursing and midwifery apprentices. At temporary hospitals in Jakarta and Surabaya, HCWs were recruited by Ministry of Health or sent by organizations or Indonesian Police Force.\n\nNew infectious disease outbreaks challenged HCWs due to insufficient knowledge of the emerging threat. In addition, ensuring adequate access to skilled HCWs especially in rural and remote communities is a challenge considering disparities in both areas.53 Most hospitals in Indonesia had provided adequate training or sent their HCWs to major cities to train with the government. Only one participant reported that HCWs there did not receive any training. However, that hospital developed Standard Operational Procedure (SOP) to be followed.\n\nSkilled HCWs needed to be equipped with appropriate personal protective equipment (PPEs) as they are notably at risk for COVID-19 infection. Higher number of infection were contributed by long shifts; owing to increased number of patients and staff shortages, and excessive fatigue which weakened the immune system.54 However, as infection progressed, availability of PPE becomes an issue.53 Mask prices increased aggressively, some people even stole or fought for mask in some regions.55 A member of a District-Government Hospital in Indonesia reckoned wearing raincoats and triple cloth masks as a PPE replacement. Furthermore, in other hospitals, HCWs would only wear PPE when required to go inside the isolation room.\n\nWhen Indonesia was faced with the scarcity of PPE early in the pandemic, there were many community movements involving housewives, disabled community, and university students to produce PPE.56–58 However, these good intentions raised the question of standardization, as some PPEs did not comply with WHO requirements and were provided directly to health care or HCWs. As a result, it was questionable not only the comfort, but also the efficacy in preventing transmission. Providing HCWs with proper training in patient care and hospital management complemented with adequate PPEs could reduce the burden of the pandemic in our healthcare facilities.\n\n\nConclusion\n\nCOVID-19 pandemic is a global burden including in Indonesia. With proper strategies to overcome the pandemic, it could reduce the number of transmissions which lead to lower case fatality rate. As known, Indonesia had a high case fatality rate with total death more than 1 million. With low number of sequence available, it is difficult to trace the viral mutations that occur in Indonesia. The disparities of healthcare facilities to diagnose and treat patients between urban and rural region expands the problem. Moreover, the awareness and knowledge of the disease is inadequate in majority of Indonesian citizen. The problem is extensive. Hence, it needs a comprehensive approach from the government, citizens, even private sectors to cease the pandemic.\n\n\nData availability\n\nNo data are associated with this article.\n\n\nAuthor contribution\n\nMiftahussurur M: Conceptualization, Writing – Original Draft, Writing – Review & Editing; Savitri, CAM: Formal Analysis, Writing – Original Draft; Waskito LA: Formal Analysis, Writing – Original Draft; Rezkitha YAA: Data Curation, Writing – Original Draft; Dhamanti I: Data Curation, Writing – Review & Editing; Indriani, D: Data Curation, Writing – Original Draft; Suyanto B: Formal Analysis, Writing – Review & Editing; Rianda, RV: Data Curation, Writing – Original Draft; Yamaoka Y: Conceptualization, Writing – Review & Editing.", "appendix": "References\n\nAhn DG, Shin HJ, Kim MH, et al.: Current status of epidemiology, diagnosis, therapeutics, and vaccines for novel coronavirus disease 2019 (COVID-19). J. Microbiol. Biotechnol. 2020; 30(3): 313–324. Publisher Full Text\n\nPascarella G, Strumia A, Piliego C, et al.: COVID-19 diagnosis and management: a comprehensive review. J. Intern. Med. 2020; 288(2): 192–206. Publisher Full Text\n\nWorld Health Organization: WHO Coronavirus Disease (COVID-19) Dashboard, Global Situation.2021.\n\nThe Indonesian Task Force for COVID-19: Perkembangan COVID-19 per Hari. Kemenkes. 2021.\n\nTosepu R, Gunawan J, Effendy DS, et al.: Correlation between weather and Covid-19 pandemic in Jakarta, Indonesia. Sci. Total Environ. 2020; 725: 138436. PubMed Abstract \| Publisher Full Text\n\nByass P: Eco-epidemiological assessment of the COVID-19 epidemic in China, January–February 2020. Glob. Health Action. 2020; 13(1): 1760490. PubMed Abstract \| Publisher Full Text\n\nMinistry of Health of the Republic of Indonesia: Recent Situation on COVID-19 in Indonesia.2021.\n\nWHO SEARO ES: Weekly Situation Report Week 3 of 2021.2021; January(November): 1–7.\n\nBurhan E, Susanto AD, Nasution SA, et al.: Guidelines for COVID-19 Management.2020.\n\nJamshidi S, Baniasad M, Niyogi D: Global to USA county scale analysis of weather, urban density, mobility, homestay, and mask use on COVID-19. Int. J. Environ. Res. Public Health. 2020; 17(21): 1–17.\n\nEryando T, Sipahutar T, Rahardiantoro S: The Risk Distribution of COVID-19 in Indonesia: A Spatial Analysis. Asia-Pacific J. Public Heal. 2020; 32(8): 450–452. PubMed Abstract \| Publisher Full Text\n\nBhadra A, Mukherjee A, Sarkar K: Impact of population density on Covid-19 infected and mortality rate in India. Model Earth Syst. Environ. 2021; 7(1): 623–629. PubMed Abstract \| Publisher Full Text\n\nKadi N, Khelfaoui M: Population density, a factor in the spread of COVID-19 in Algeria: statistic study. Bull. Natl. Res. Cent. 2020; 44(1).\n\nMinistry of Health of the Republic of Indonesia: Indonesia’s COVID-19 Data Analysis.2020.\n\nWu F, Zhao S, Yu B, et al.: A new coronavirus associated with human respiratory disease in China. Nature. 2020 Mar; 579(7798): 265–269. PubMed Abstract \| Publisher Full Text\n\nRota PA, Oberste MS, Monroe SS, et al.: Characterization of a novel coronavirus associated with severe acute respiratory syndrome. Science (80-). 2003 May; 300(5624): 1394–1399. Publisher Full Text\n\nLu R, Wang Y, Wang W, et al.: Complete genome sequence of Middle East respiratory syndrome coronavirus (MERS-CoV) from the first imported MERS-CoV case in China. Genome Announc. 2015; 3(4): e00818–e00815. Publisher Full Text\n\nHadfield J, Megill C, Bell SM, et al.: NextStrain: Real-time tracking of pathogen evolution. Bioinformatics. 2018 Dec; 34(23): 4121–4123. PubMed Abstract \| Publisher Full Text\n\nElbe S, Buckland-Merrett G: Data, disease and diplomacy: GISAID’s innovative contribution to global health. Glob. Challenges. 2017 Jan; 1(1): 33–46. PubMed Abstract \| Publisher Full Text\n\nRambaut A, Holmes EC, O’Toole Á, et al.: A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology. Nat. Microbiol. 2020 Nov; 5(11): 1403–1407. PubMed Abstract \| Publisher Full Text\n\nCDC: SARS-CoV-2 Variant Classifications and Definitions.2021.\n\nLazarevic I, Pravica V, Miljanovic D, et al.: Immune Evasion of SARS-CoV-2 Emerging Variants: What Have We Learnt So Far?. Viruses. 2021 Jun; 13(7): 1192. Publisher Full Text\n\nAllen H, Vusirikala A, Flannagan J, et al.: Increased household transmission of COVID-19 cases associated with SARS-CoV-2 Variant of Concern B.1.617.2: a national case-control study. Public Health England (PHE). 2021; 12: 100252. Publisher Full Text\n\nDeng X, Garcia-Knight MA, Khalid MM, et al.: Transmission, infectivity, and antibody neutralization of an emerging SARS-CoV-2 variant in California carrying a L452R spike protein mutation. medRxiv Prepr. Serv. Heal. Sci. 2021 Mar. 2021.03.07.21252647.\n\nShamshiripour A, Rahimi E, Shabanpour R, et al.: How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago. Transp. Res. Interdiscip. Perspect. 2020; 7: 100216. Publisher Full Text\n\nMaqbool A, Khan NZ: Analyzing barriers for implementation of public health and social measures to prevent the transmission of COVID-19 disease using DEMATEL method. Diabetes Metab. Syndr. Clin. Res. Rev. 2020; 14(5): 887–892. PubMed Abstract \| Publisher Full Text\n\nMatthewman S, Huppatz K: A sociology of Covid-19. J. Sociol. 2020; 56(4): 675–683. Publisher Full Text\n\nThe Indonesian Task Force for COVID-19: Health Protocol Monitoring in Indonesia. Vol. January 20.2021.\n\nHarper CA, Satchell LP, Fido D, et al.: in the COVID-19 Pandemic.2021; 1875–1888.\n\nAnaki D, Sergay J: Predicting health behavior in response to the coronavirus disease (COVID-19): Worldwide survey results from early March 2020. PLoS One. 2021; 16(1 January): e0244534–e0244516. PubMed Abstract \| Publisher Full Text\n\nOlapegba PO, Chovwen CO, Ayandele O, et al.: Fear of COVID-19 and Preventive Health Behavior: Mediating Role of Post-Traumatic Stress Symptomology and Psychological Distress. Int. J. Ment. Health Addict. 2021; 1–12. PubMed Abstract \| Publisher Full Text\n\nBarber SJ, Kim H: COVID-19 Worries and Behavior Changes in Older and Younger Men and Women. J. Gerontol. - Ser. B Psychol. Sci. Soc. Sci. 2021; 76(2): E17–E23. Publisher Full Text\n\nWeismüller B, Schweda A, Dörrie N, et al.: Different Correlates of COVID-19-Related Adherent and Dysfunctional Safety Behavior. Front. Public Heal. 2021; 8(January): 1–10. Publisher Full Text\n\nKairoot R, Ersya MP: Analysis of the Level of Public Trust in the Implementation of the Covid-19 Handling Policy by the Kubung District, Indonesia. J. Civ. Educ. 2021; 4(4). Reference Source\n\nMufti M, Gatara AAS, Afrilia A, et al.: Analysis of Public Trust Measurement in the Government: Strength for Community-Based COVID-19 Handling. Lp2M. 2020: 1–13. Reference Source\n\nFrounfelker RL, Santavicca T, Li ZY, et al.: COVID-19 Experiences and Social Distancing: Insights From the Theory of Planned Behavior. Am. J. Health Promot. 2021; 35(8): 1095–1104. PubMed Abstract \| Publisher Full Text\n\nGarcia LP, Duarte E: Nonpharmaceutical interventions for tackling the COVID-19 epidemic in Brazil. Epidemiol e Serv saude Rev do Sist Unico Saude do Bras. 2020; 29(2): e2020222.\n\nMinistry of Manpower of Republic Indonesia: Regulations of the Ministry of Menpower regarding COVID-19 Prevention in Companies and Business Continuity Plan.2020.\n\nFerguson N, Laydon D, Nedjati-Gilani G, et al.: Report 9 - Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand\|Faculty of Medicine\|Imperial College London. Imperial College COVID Response Team; 2020.\n\nMinistry of of Foreign Affairs: Republic of Indonesia Government Policy Regarding the COVID-19 Outbreak.April 2020.\n\nSun Z, Zhang H, Yang Y, et al.: Impacts of geographic factors and population density on the COVID-19 spreading under the lockdown policies of China. Sci. Total Environ. 2020; 746(666): 141347. Publisher Full Text\n\nThe Jakarta Post: Health Ministry largest virus hotbed in Jakarta.2020.\n\nJakarta Provincial Government: COVID-19 Cluster Transmission in Jakarta.2020.\n\nStedman M, Davies M, Lunt M, et al.: A phased approach to unlocking during the COVID-19 pandemic—Lessons from trend analysis. Int. J. Clin. Pract. 2020; 74(8): 1–7.\n\nMeters W o: Reported case and death by territory.2021.\n\nMinistry of Health. PTM prevalence reduction and AKI-AKN reduction through the filling of infrastructure facilities in health services facilities. 2019.\n\nWorld Health Organization: Field assessment of COVID-19 pandemic preparedness and response capacity in 15 provinces.2020.\n\nThe Jakarta Post: Indonesian health system might collapse soon: COVID-19 task force.2020.\n\nTempo: COVID-19 Referral Hospitals in Jabodetabek 95% Full: ARSSI.2021.\n\nZhu W, Wang Y, Xiao K, et al.: Establishing and managing a temporary coronavirus disease 2019 specialty hospital in Wuhan, China. Anesthesiol. J. Am. Soc. Anesthesiol. 2020; 132(6): 1339–1345. Publisher Full Text\n\nJamil KF, Winardi W, Yufika A, et al.: Knowledge of coronavirus disease 2019 (COVID-19) among healthcare providers: A cross-sectional study in Indonesia. Asian Pac. J. Trop. Med. 2020; 13(9): 402. Publisher Full Text\n\nArmitage R, Nellums LB: Whistleblowing and patient safety during COVID-19. Vol. 24, EClinicalMedicine. Lancet Publishing Group; 2020; 100425.\n\nMbunge E: Effects of COVID-19 in South African health system and society: An explanatory study. Diabetes Metab. Syndr. Clin. Res. Rev. 2020; 14(6): 1809–1814. Publisher Full Text\n\nAğalar C, Öztürk ED: Protective measures for covid-19 for healthcare providers and laboratory personnel. Turkish. J. Med. Sci. 2020; 50(SI-1): 578–584. Publisher Full Text\n\nWang J, Pan L, Tang S, et al.: Mask use during COVID-19: A risk adjusted strategy. Environ. Pollut. 2020; 266(January): 115099. PubMed Abstract \| Publisher Full Text\n\nMaida AN, Qurani B: PKM Menjahit Busana Alat Pelindung Diri (APD) dan Masker Untuk Pencegah Covid-19 pada Ibu-Ibu Rumah Tangga di Kec. Biringkanaya Kota Makassar. Seminar Nasional Pengabdian Kepada Masyarakat. 2020.\n\nRofiah SK, Zuchdi MZ, Rieuwpassa DO, et al.: Workshop and Training on Making Personal Protective Equipment during the COVID-19 Pandemic as a Form of Empowering Persons with Disabilities. 1st International Conference on Information Technology and Education (ICITE 2020). Atlantis Press; 2020; p. 374–80.\n\nFaslih A, Jaya SN, Al-Ikhsan A, et al.: Sinergitas Masyarakat pada Pembuatan Alat Pelindung Diri Tepat Guna Dalam Rangka Pencegahan dan Pengendalian Penyebaran Covid-19 di Wilayah Provinsi Sulawesi Tenggara. J. Pengabdi Masy Ilmu Terap. 2020; 2(2): 7–16. Publisher Full Text" }	[ { "id": "190603", "date": "04 Aug 2023", "name": "Osaretin Christabel Okonji", "expertise": [], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nGeneral comment\nThank you for the opportunity to review this paper, the manuscript titled “Lessons from Indonesia, a country with the highest COVID-19 mortality rate in the world: dissecting multiple aspects” is an interesting topic but the manuscript needs further improvement. There are several issues that need to be addressed as a way to improve this manuscript. The authors need to update the manuscript. I have included comments to improve the manuscript further.\nTitle of manuscript\nPlease revise the title of the manuscript not clear.\nAbstract\nThe abstract needs improvement, it needs to be succinctly written with focus on the topic.\n\nPlease include when the first case of COVID-19 was detected in the country. Also, briefly include the region most affected in the country.\n\n100,000 deaths – As of when? Please indicate a date after this, and update to recent figures. Recently, more than 160,000 deaths have been recorded in the country as of August 1st 2023.\n\nPlease check the second and third line, not clear in the abstract and should be the last part of the abstract (We summarized Indonesian population demographic, socio-behavior, multiple government policy and public health interventions contributed to the high mortality).\nKeywords\nPlease include other key words such as Coronavirus, Pandemic, Epidemiology, Indonesia\nIntroduction\nThis section needs to be re-worked, as many of the issues raised here needs to be updated. It will be good for the authors to discuss the COVID-19 epidemiology in Indonesia.\n\nPlease correct the sentence and check the reference- which infects more than 8,000 people in China during 2002-2003 and Middle East respiratory syndrome (MERS) coronavirus (MERS-CoV) in 2012, infected 2494 people and claimed lives of 858 in Saudi Arabia.2\n\nNot clear- confirmed cases of what ? (Worldwide confirmed cases was a staggering 196 million with more than 4 million deaths). Update the reference.\n\nSecond paragraph -Please update the world-wide COVID-19 cases and death to recent figures and indicate the date.\n\nSecond paragraph- Please update Indonesia COVID-19 cases and deaths to recent figures with date -Currently over 6 million cases and more than 160, 000 deaths have been reported as of August 1, 2023.\n\nSecond paragraph- Not clear, April when? (The CFR had been worse early in the pandemic, reaching 9% on April).\n\nSecond paragraph- Please highlight the regions most affected.\n\nRephrase, not clear, what data? Please revise the sentence – (These data support our hypothesis regarding the reason behind the worse condition in Indonesia).\n\nPlease include when the first, second and third wave of COVID-19 occurred in Indonesia.\n\nAlso include the regions where most cases and deaths occurred.\n\nPlease include the variant driving the COVID-19 wave in the country- Delta variant\n\nThe introduction is poorly written, more explicit details are necessary.\n\nIt will be good to include a table or a graph to show COVID-19 cases and mortality in the different Province in the country.\n\nNot much is discussed about the risk factors for COVID-19 mortality in the paper.\n\nPrevalence and distribution across provinces\nAdd COVID-19 to the title of this section\n\nFirst paragraph- Please update the whole information to recent figures and succinctly described it. The information here was 2 years ago- August 2021.\n\nThe second and third paragraph should be updated, the authors cited 2020 and 2021 articles. Most of the information stated should be updated.\nGenealogy and viral mutation\nThis section is not necessary in a paper like this.\nGovernment policy and Healthcare resources\nThese sections need improvement. Please succinctly write these two sections.\n\nHow did Indonesian population, demographic, socio-behavior, multiple government policy and public health interventions contributed to the high mortality? This was the intention of the authors when they were writing this paper. Not much is discussed about the aforementioned factors in the manuscript.\n\nI believe the review will not be complete without the issue of how the Indonesian population demographics, socio-behaviour, government policy and public health intervention influenced the COVID-19 mortality rate in the context of a developing country being discussed.\n\nAlso, it will be good for the authors to discuss the different prevalence of pre-existing comorbidity, healthcare capacity in responding to the pandemic, and socio-economic characteristics. Did all of these factors influence the mortality rate in the country?\n\nPlease include a section for recommendations\n\nInclude health system strengthening and improved resource allocation to ensure improved health outcomes for vulnerable population…..\n\nAdd other important recommendations\nConclusion\nThis is not true, please correct or delete- As known, Indonesia had a high case fatality rate with total death more than 1 million.\n\nCheck this sentence- With low number of sequence available, it is difficult to trace the viral mutations that occur in Indonesia.\n\nThe conclusion needs improvement. It will be good to include a summary of the key findings of the study in the conclusion section.\n\nThe manuscript needs extensive revision for language and grammar.\nReferences\nInclude more references particularly recent references. See example below.\nSurendra H, Paramita D, Arista NN, Putri AI, Siregar AA, Puspaningrum E, Rosylin L, Gardera D, Girianna M, Elyazar IRF. Geographical variations and dist rict-level factors associated with COVID-19 mortality in Indonesia: a nationwide ecological study. BMC Public Health. 2023 Jan 14;23(1):103. doi: 10.1186/s12889-023-15015-0. PMID: 36641453; PMCID: PMC9840537.\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? No", "responses": [] }, { "id": "202113", "date": "04 Sep 2023", "name": "Kevin T Kavanagh", "expertise": [ "Reviewer Expertise Patient safety and infectious diesease." ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAfter reviewing the updated paper, I am sorry to report that I do not feel it is acceptable to be indexed in its present form. The article is too long, not focused and has extraneous information. In addition, there are a number of areas where the English syntax and wording is awkward. In addition, there are questions of the validity of the data.\n\nThe authors state, “Some information will be our original investigation. These data support our hypothesis regarding the reason behind the worse condition in Indonesia.” This needs either a reference or the original investigation methods and results need to be presented in a structured form in the manuscript.\nSome of the specific concerns are as follows:\n\nExtraneous information:\nSecond paragraph introduction: “It kept spreading worldwide, despite different continents separated by oceans.” This is to be expected with air travel and the statement does not need a reference.\n\nThird paragraph in the introduction. “Epidemiological assessment may be relevant to understand the patterns of transmission.” This again goes without saying. It may even be viewed as a false statement since epidemiology assessment “is” relevant.\n\nThe Genealogy and Viral Mutation section does not add to the manuscript. Most of the information the authors present does not directly relate to the manuscript’s assertions. The exact amino sequences of the mutations of various strains and the classification methods just confuse the topic. The authors should just present a timeline with the various strains Indonesia was exposed to, and then compare this to relevant other countries.\nAwkward Syntax:\nThird paragraph in the introduction. “Therefore, high mortality rates should be dissected from multiple aspects.”\n\nSecond paragraph in the Introduction. “Some information will be our original investigation” should state “Some information will be from our original investigation”\n\nMisstatements and Inaccurate/Outdated Information.\nTitle: Indonesia does not have the highest mortality rate in the world.\nSecond paragraph in the introduction. “Few coronaviruses came with mild symptoms” The common cold is a coronavirus, this is a common infection with mild symptoms.\n\nThis should read: “Most coronaviruses have mild symptoms, with a few exceptions exemplified by …”\n\nThird paragraph in the Introduction. “…it has been a mystery whether population characteristics and behavior contribute to the continuation of the disease”. This statement is false. It is not a mystery if these are contributing factors. What the factors are and the degree to which they impact the disease certainly needs further study, but no one doubts population characteristics and behavior will have an impact on disease spread.\n\nFourth paragraph: The authors state Indonesia “was” leading, but when did this happen? Next sentence, the authors state “currently around 30,000 to 40,000”, but the reference is from 2021. The next sentence states July 15th, but no year is given. In the next sentence the authors state Indonesia has deaths of almost 100,000 cases. However, Worldometer1 has the cases for Indonesia at almost 162 thousand. In the last sentence, it states cases are soaring but Worldometer shows the case rate is currently flat.\n\nIn the conclusion it states that Indonesia had over 1 million deaths. This is in error.\n\nClarity needs to be added:\n\nThroughout the paper, there is an attempt to trace the history of the pandemic in Indonesia. Dates are often given as months and days but omitting the years. This causes confusion and makes the data provided lose context. For example: In the Government Policy Section it states, “since January” but no date is given. In the second paragraph in this Section, it states “In April” but again no year is given. In the second paragraph of the Introduction the authors state that the CFT reached 9% in April, but no year is given. In addition, the authors need a reference for the 9% data point.\n\nI do not feel the Authors made their case:\nBut most importantly, I do not feel the authors have made their case that Indonesia has had a response much worse than the rest of the world or even Southeast Asia. According to Worldometer, the county’s deaths per 1 million population is at a lower rate than Japan, South Korea and Taiwan. The discussion of comparing wave or surge length on the top of page 5 makes little sense. Surges were described as lasting 20 days in China and over 40 days in other countries. However, many view the data from China having low reliability and as illustrated by Worldometer the length of surges has been much longer than 40 days. The reporting aberrations in the various countries confound the data and weaken the author’s case.\n\nHowever, the authors need to present data regarding excess rates of death. A source for this in the mid portion of the pandemic was published in the Lancet.2 ( PMID: 35279232 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8912932/ )\n\nIn the Lancet publication. data shows that the excess mortality rate from 2020 to 2021 in Indonesia was 140.7 far above the average of 90.8 in Southeast Asia. This data supports the authors contention that early in the pandemic Indonesia lagged behind the response in neighboring countries. However, current data from Worldometer suggests that this situation has changed since countries such as South Korea, Australia and Japan had their major surges in 2022.\n\nThus, if the article was rewritten, shortened, additional data added with is accurately related to a timeline, one might be able to conclude that in the initial pandemic Indonesia fared worse than other countries, but those countries could not maintain their mitigation strategies indefinitely. This resulted in these countries experiencing late pandemic surges and possibly overtaking Indonesia in deaths per 1 million population.\n\nReferences:\n\nCOVID - Coronavirus Statistics - Worldometer (worldometers.info) https://www.worldometers.info/coronavirus/\n\nCOVID-19 Excess Mortality Collaborators. Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21. Lancet. 2022 Apr 16;399(10334):1513-1536. doi: 10.1016/S0140-6736(21)02796-3. Epub 2022 Mar 10. Erratum in: Lancet. 2022 Apr 16;399(10334):1468. PMID: 35279232; PMCID: PMC8912932.\n\nIs the topic of the review discussed comprehensively in the context of the current literature? No\n\nAre all factual statements correct and adequately supported by citations? No\n\nIs the review written in accessible language? Partly\n\nAre the conclusions drawn appropriate in the context of the current research literature? No", "responses": [] } ]	1	https://f1000research.com/articles/11-920
https://f1000research.com/articles/11-919/v1	10 Aug 22	{ "type": "Case Report", "title": "Case Report: A rare case of choledochal cyst", "authors": [ "Wasiq Bin Tariq", "Anu Radha Twayana", "Neela Sunuwar", "Azwar Anjum", "Sulav Deo", "Sushil Rayamajhi", "Amit Singh", "Wasiq Bin Tariq", "Neela Sunuwar", "Azwar Anjum", "Sulav Deo", "Sushil Rayamajhi", "Amit Singh" ], "abstract": "Background: Choledochal cysts are dilated portions of the biliary tract that account for 1% of all benign biliary diseases. It is prevalent among Asian and female populations and the incidence is 1:100,000–150,000. Among the different types, only 15–35% of all choledochal cysts are type IV cysts, with type I being the most common representing 50–80%. Clinical presentation and therapy of biliary cysts (BC) differ depending on the type. Case: We present a case of a 2-year-old male who presented with non-specific symptoms of multiple episodes of vomiting. Laboratory investigations revealed raised alkaline phosphatase and gamma-glutamyl transpeptidase. His symptoms of acute pancreatitis were resolved with conventional therapy. Ultrasonography of the abdomen showed intra and extra-hepatic cystic biliary tree dilatation suggestive of choledochal cyst Type IV A. Conclusions: Choledochal cysts present with clinical features varying with age and anatomical variants and can pose challenges in management that can be addressed by surgery to avoid further complications.", "keywords": [ "biliary cysts", "biliary drainage", "cholangiography", "choledochal cyst type 4", "hepaticojejunostomy" ], "content": "Introduction\n\nCholedochal cysts are intrahepatic, extra hepatic or both biliary tree dilatations. The incidence in the Western population is 1 in 100,000–150,000 live births; in Asian populations, 1 in 1,000–13000,1,2 Japan has two-thirds of all cases. There is predominance in the female population, which is more common in the first decade. Type I is the most common.3 Overall, 80% of cases are infants and young children.4 Clinicopathological characteristics vary depending on their age. Abdominal discomfort, jaundice, and an abdominal mass are the most common symptoms in children. Adults, on the other hand, frequently present with biliary or infectious problems and are more likely to progress to choledocholithiasis and malignant transformation.2 Infants tend to present with painless jaundice, hepatomegaly, and acholic stools, a condition mistaken for biliary atresia, hepatic fibrosis, or cirrhosis. Ultrasonography, endoscopic retrograde cholangiopancreatography (ERCP) and magnetic resonance cholangiopancreatography (MRCP) are diagnostic techniques.4 Complete cyst excision and laparoscopic Roux-en-Y hepaticojejunostomy is safe for both infants and children.2\n\n\nCase report\n\nA 2-year-old Asian male child presented with generalized abdominal pain, fever and excessive vomiting for one week. He was not icteric at any point in time. Abdominal examination revealed epigastric tenderness and guarding. There was no other notable medical history. No reports of biliary cysts in family members could be identified. Further laboratory investigations were done, which revealed a cholestatic pattern in serum liver test (raised alkaline phosphatase and gamma glutamyl transpeptidase). His amylase and lipase levels were increased, and the child was diagnosed and treated for acute pancreatitis. His symptoms improved with conventional treatment. The child was kept nil per oral and given intravenous fluids. Later on, ultrasonography of the abdomen was done, which showed both intra and extra hepatic cystic biliary tree dilatation suggestive of choledochal cyst Type IV A, an incidental finding along with soft stones or sludge in the common bile duct (Figure 1). Despite the fact that computerized tomography (CT) or magnetic resonance imaging (MRI) would have been the next step in the workup, the parents denied further investigation due to financial reasons. In addition, a genetic study of the patient and family could not be conducted. The child’s parents were advised about the necessity for surgery, which included a partial hepatectomy for removal of the intrahepatic section of the cyst and repair with a broad hilar Roux-en-Y hepaticojejunostomy. However, due to financial constraints, they refused surgery.\n\n\nDiscussion\n\nCholedochal cysts are congenital cystic expansions of the ductus choledochal, the “common channel” that opens into the duodenal lumen. There are five types according to the Todani’s classification (Figure 2).4\n\nThis figure has been reproduced from Giha et al.,9 under a CC BY-NC-ND 4.0 license.\n\nThe symptoms are non-specific, such as recurring upper abdominal pain, malaise with nausea and vomiting, which can also be found in biliary tract colic, bile duct abnormalities, or other gastro-intestinal ailments, delaying proper diagnosis.5 Most recent research indicate that nausea, vomiting, and abdominal pain are the most prevalent presenting symptoms in older children (1–18 years of age at presentation), while abdominal mass is predominate in newborns (1 year of age at presentation).6 Similar to the previous studies, the toddler we are reporting on came with a similar finding of multiple episodes of nausea and vomiting and abdominal pain refractory to symptomatic treatment. Furthermore, Badebarin et al.,6 Hung et al.,3 and Fumino et al.7 discovered that abdominal pain was more prevalent in older children than in infants. The study also found that the pattern of choledochal cyst presentation changes from infancy to older children. Infants were more likely than older children to develop nausea, vomiting, and stomach discomfort.\n\nThe diagnosis of choledochal cyst is readily established by ultrasound or computed tomography abdomen.8 Similarly, due to recurrent episodes of vomiting, an ultrasound abdomen was advised for the case we are presenting, which revealed both intra and extra hepatic cystic biliary tree dilatation suggestive of choledochal cyst Type IV A along with soft stones or sludge in common bile duct, an incidental finding.\n\nThe standard treatments for a symptomatic choledochocele are laparotomy, duodenotomy, and excision of the choledochocele in the sense of internal marsupialization, potentially accompanied with sphincteroplasty. Since the mid-1980s, successful endoscopic therapy, such as endoscopic sphincterotomy or endoscopic cyst excision with a diathermy loop, has been described with increasing regularity.5\n\nThere are some limitations to this case study. To begin with, this is a single case, and the finding is unrelated to genetic factors, i.e., it is a spontaneous occurrence. Second, we could not include operation and postoperative details. The child’s parents were advised about the necessity for surgery, however, due to financial constraints, they refused surgery. As a result, the possible predictive factors for postoperative outcomes and complications are unknown. The examination of varied clinical manifestations in the setting of newborns and older children is, nevertheless, a remarkable strength of the current study. Our observations of choledochal cyst symptoms and laboratory abnormalities in this toddler could aid in early detection of the condition and the prevention of late consequences.\n\n\nConclusions\n\nIn conclusion, choledochal cysts are a rare finding. Between childhood and adolescence, the pattern of choledochal cyst presentation changes. An abdominal mass is more common in infants, whereas nausea, vomiting, and stomach pain are more common in older children. Surgeons should be aware of the likelihood of anatomical variants in choledochal cysts that fall outside of the standard classification and be prepared for the challenge of management, which may be addressed with careful dissection and correct excision, avoiding additional complications.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nConsent\n\nWritten informed consent for publication of their clinical details and clinical images was obtained from the family of the patient.", "appendix": "References\n\nSato M, Ishida H, Konno K, et al.: Choledochal cyst due to anomalous pancreatobiliary junction in the adult: sonographic findings. Abdom. Imaging. 2001; 26(4): 395–400. PubMed Abstract \| Publisher Full Text\n\nLee HK, Park SJ, Yi BH, et al.: Imaging Features of Adult Choledochal Cysts: a Pictorial Review. Korean J. Radiol. 2009; 10(1): 71–80. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHung MH, Lin LH, Chen DF, et al.: Huang CS. Choledochal cysts in infants and children: experiences over a 20-year period at a single institution. Eur. J. Pediatr. 2011; 170(9): 1179–1185. PubMed Abstract \| Publisher Full Text\n\nTigabie W, Tesfay H, Tamrat D, et al.: Unusual variant of choledochal cyst in a child: A case report, in Tertiary Specialized Hospital, Ethiopia. Int. J. Surg. Case Rep. 2020; 75: 117–121. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWeißer M, Bennek J, Hörmann D: Choledochocele - A Rare Cause of Necrotising Pancreatitis in Childhood. Eur. J. Pediatr. Surg. 2000; 10(04): 258–264. PubMed Abstract \| Publisher Full Text\n\nBadebarin D, Aslanabadi S, Teimouri-Dereshki A, et al.: Different clinical presentations of choledochal cyst among infants and older children: A 10-year retrospective study. Medicine (Baltimore). 2017; 96(17): e6679. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFumino S, Ono S, Kimura O, et al.: Diagnostic impact of computed tomography cholangiography and magnetic resonance cholangiopancreatography on pancreaticobiliary maljunction. J. Pediatr. Surg. 2011; 46(7): 1373–1378. PubMed Abstract \| Publisher Full Text Reference Source\n\nReed MK, Williams JE, DuBois JJ: Choledochal cyst of the proximal common pancreaticobiliary channel. Pediatr. Surg. Int. 1995; 10: 553–556. Publisher Full Text\n\nGiha S, Redondo Y, Quintero G: Quiste de colédoco: diagnóstico y manejo intraoperatorio. Pediatría. 2016; 49(2): 64–67. 0120-4912. Publisher Full Text" }	[ { "id": "147153", "date": "11 Aug 2022", "name": "Bishayeeta Shrestha", "expertise": [ "Reviewer Expertise Maxillofacial Pathology", "Immunohistochemistry", "medical education" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe background seems incomplete. The author could have added the uniqueness of the cases (why your case is unique), the treatment and outcome (why this wasn't possible due to patient's factor should have been included in background).\nAquedate description was included regarding the diagnostic approaches and treatment plan. But the case report had its own limitation as treatment wasn't possible.\nSufficient discussion was included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment. Case presented with sufficient detail to be useful for other practitioners\n\nIs the background of the case’s history and progression described in sufficient detail? Partly\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Partly\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "260825", "date": "08 May 2024", "name": "Simone Maurea", "expertise": [ "Reviewer Expertise Abdominal diagnostic imaging" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis interesting clinical case report describes a pediatric patient with choledochal cyst for which the imaging diagnosis is fundamental; the authors illustrate that the patient was evaluated with ultrasound (US),CT and MRI, but only US images are provided.\nMajor Point: The role of MRCP should be underlined in the discussion section illustrating the possibility to use two technical types of MRCP, the static hydrographic T2-weighted sequence with radial or volumetric scanning and the dynamic post-contrast T1-weighted fat-suppressed sequence using liver specific gadolinium chelates (Multihance or Primovist). In this regard, while the static MRCP depicts all anatomic structures with fluid content, the dynamic MRCP is able to detect only fluid structures corresponding to bile drainage such as a choledochal cyst for which the imaging diagnosis is reached with this methodological approach.\nMinor Point: The following references should be cited since report the two technical types of MRCP: 1. Maurea S, et. al., 2009 (ref 1). 2. Maurea S, et. al., 2010 (ref 2) 3. Maurea S, et. al., 2011 (ref 3)\n\nIs the background of the case’s history and progression described in sufficient detail? Partly\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Partly\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-919
https://f1000research.com/articles/11-915/v1	09 Aug 22	{ "type": "Research Article", "title": "The role of personality traits and engagement factors towards the use of paid stickers in personal communication messages", "authors": [ "Sudaporn Sawmong" ], "abstract": "Background: The research investigated the personality traits and engagement factors that influence the use of paid stickers in personal communication. The study was driven by the increasing significance of stickers such as emoticons and emojis in online dialogues. The study was hinged on the Theory of the big five personality traits; neuroticism, extraversion, openness to experience, agreeableness and conscientiousness. The study tested seven hypotheses to ascertain the effect of personality traits and engagement factors towards the utilization of paid stickers in personal communication. Methods: The research applied the quantitative survey research design, where primary data was collected from respondents that had experience in using emojis and emoticons in their communications. The data was collected from respondents in Bangkok, Thailand using a structured questionnaire between May 14, 2022, and May 31, 2022.\n\nResults: The results from 391 respondents indicated that conscientiousness, extraversion, openness, and neuroticism influence perceived enjoyment, while perceived enjoyment and perceived ease of use have a significant and positive influence on the intention to use paid stickers. Two elements of engagement, interactive engagement, and personal engagement were used to assess the influence of engagement parameters on the behavioral intention to use paid stickers. The intention to employ paid stickers in personal messages was found to be strongly and favorably influenced by these two engagement characteristics. Conclusions: The study recommends that the creators of stickers, emoticons, and emojis should consider user personality features, sticker engagement, sticker simplicity of use, and the personal delight of users in the creative and communication process. The study concludes that perceived enjoyment and perceived ease of use have a large and favorable impact on the use of paid stickers. The study's main limitation was that it focused on one area of social media. This must be taken into account when applying the findings.", "keywords": [ "Personality Traits", "Paid Stickers", "Emoticons", "Personal Messages", "Emojis" ], "content": "Introduction\n\nEmoticons and emojis are used to create stickers, which are among the instruments that may aid enhance communications. Emoji, emoticons, and stickers increase the social inclinations and complexity of online dialogues and communication.1 Emoticon usage has changed with time, obtaining supplementary purposes. Widely praised for compensating for the absence of prosodic and gestural clues in textual emoticons, they portray emotion and simulate nonverbal indicators like winks and tongues hanging out that traditionally signify flirting and joking behaviors when done offline. While face-to-face communication is restricted online, it may be used to communicate emotions or transmit meanings and substitute for the lack of nonverbal indicators.2 Emoticons are becoming more widely accepted as a system of punctuation for indicating utterance emotion and therefore are gaining grammatical significance.\n\nSimilarly, users' large number of emoticons when the internet was introduced has dwindled over time to only a few that are seldomly used—for example, the open-mouth laugh, the grin, the wink, the frown, and the tongue sticking out. This decrease is also in line with changes in offline language. Wang et al.,3 point out that emojis may also do functions that emoticon can’t, like riffing on other graphics and narrating occurrences, as they can “keep a conversational link; conclude a conversational thread; amuse and establish new interpretations” (p.4). Emoji have a bigger influence on readers’ impressions of a writer's mood and devotion than emoticons, owing to their increased vividness. Emojis, which are emoticons in the shape of icons, came later. Tang and Hew4 state that character emoticons and moving emoticons have become popular, known as stickers. People may use stickers to convey their feelings, ideas, and intentions more interactively. Social networking services (SNSs), personal messengers, and marketing all employ stickers.\n\nA personal messenger may communicate with a single person or a group of individuals, but a social networking site can communicate with unlimited users. Stickers are mostly utilized as a means of communication in this environment. De Seta and Biaoqing5 highlights that their usage conveys nonseriousness, frivolity, and funny purposes more abstractly. Stickers have become commonplace at the utterance-final position, where they generally appear, as markers of the user's expressive intent, such as highlighting or downplaying the power of the utterance and indicating its tone. According to Tang and Hew,6 tone marking, also known as illocutionary force, is a more abstract, ‘bleached’ function than communicating emotion or nonverbal conduct. It also entails an expansion of the emoji's original meaning so that a smiling face may now convey not just pleasure or a good mood but also pragmatic connotations like honesty, tolerance, and civility. Personal messenger users consider stickers more helpful, fascinating, entertaining, simple, and casual than emoticons.\n\nNumerous businesses utilize stickers to advertise their goods to customers. They employ stickers to build their brand emblems, pique people's attention, and urge consumers to learn about their companies.4 The objective of using stickers varies depending on the context in which they are used. WhatsApp, WeChat, Facebook Communication, Skype, Line, BBM, QQ Messenger, Telegram, and KakaoTalk are just a few personal messenger apps. Because several personal messengers provide emojis, emoticons, and stickers freely, the emoji and sticker industry is seldom supported.7 However, companies like KakaoTalk and Line Creators have developed sticker markets where users can purchase and gift stickers.\n\nThe LINE Store is filled with free and premium stickers created by authorized groups, designers, and several LINE customers. Even though 70% of Line customers rarely purchase e-stickers, 74.5% have used sponsored e-stickers.8 Customers adore these personalized e-stickers because they are free and because the design is original and vibrant. Including both a brand image and a product image in the interface style of LINE stickers unintentionally delivers sponsor imagery to consumers’ brains to be absorbed, even if it is the customer's initial interaction with the collection of stickers. Therefore, learning ways to build meaningful branded9 stickers is a significant problem for marketers to enhance the efficacy of LINE sticker marketing initiatives. Iqbal10 informs that in 2020, LINE made $1.51 billion in income, largely from advertising. LINE is used by approximately 224 million individuals once a month, with 86 million in Japan. In 2020, LINE users transacted about $15 billion on the service. Mobile marketing media's interactive and entertaining character may positively impact brands and customer behavior.\n\nSimilarly, from 2021, Kakao has offered a subscription option that allows users to utilize all stickers for a set monthly fee. The sticker market is growing, and the subscription service includes a sticker suggestion feature.11 According to Jobst,12 Kakao's yearly revenue was roughly 6.1 trillion South Korean Won in 2021, up from around 4.2 trillion earned before. Lee and Lee7 clarifies out that several variables are likely to influence sticker purchases; however, only a few research studies have looked at the factors that influence sticker purchases. As a result, it's important to consider the numerous diverse elements that influence sticker purchases.\n\nThis section describes the literature review and hypotheses of the role of personality traits and engagement factors towards the use of paid stickers in personal communication, including the theory of the big five personality traits, as well as the application of the Technology Acceptance Model in investigating the research problem.\n\nSeveral variables are likely to influence sticker purchases. However, just a few researchers have looked at the variables that influence sticker purchases. As a result, it's important to consider the numerous diverse elements that influence sticker purchases. Personality is among the variables that reveal a customer's unique characteristics, and it's often discussed regarding product and service buying and preference.13 Various elements influence personal differences, including personality, developmental stage, needs, and attitudes, which are more constant over time and across contexts than other aspects. Investigating the effects of nature on individual service use patterns or preferences will help with the most long-term and stable customization. According to Dainas and Herring,14 personality is widely utilized in business and psychology studies to identify attitudes and actions, and personality is a significant predictor of customer beliefs and attitudes in information management studies. When it comes to stickers, individuals buy them to use their communication in messages strongly tied to their purpose.\n\nMany modern personality theories suggest that there are five essential dimensions to personality, designated the Big Five personality traits. The Big Five personality traits (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) are a psychological research framework that relates to a particular propensity expressed through intra-psychic characteristics.15–16 The traits are defined as natural inclinations; the actions they incline one to vary across tasks, social environments, and timeframes, but they are all consistent with the trait. Because the items are mainly context-invariant, the assessments of the five qualities are frequently decontextualized.15 Because it may reflect many systems of personality description in a shared framework, the Big Five personality traits perform an integrative function.17 These five characteristics have been studied and evolved, and while each has received a lot of attention, scholars have not always agreed on how to define the different traits. The five personality trait tests determine where an individual falls in the range of each of the five qualities. Each attribute assesses a distinct facet of human personality:\n\nNeuroticism\n\nAnxiety, self-consciousness, aggression, and mental illness are all symptoms of neuroticism.15 The outcomes of neuroticism research vary by field. First, those with high neuroticism seem to have a pessimistic view of technology's utility. Şahin et al.,16 infers that people with high neuroticism see technological growth as dangerous and unpleasant, so neuroticism negatively connects with technology's perceived utility. In a virtual reality team setting, neuroticism is positively connected with technological communication anxiety, so an individual with high neuroticism is concerned about prospective obligations and events.17 Furthermore, using new or old technology in novel ways creates circumstances in which future effects are unknown. However, Goreis and Voracek18 are of the opinion that individuals exhibit a distinct pattern while participating in online interactions, for instance, on social networking sites or shopping, instead of experimenting with new technologies or employing cooperative technologies. Individuals with high neuroticism seek knowledge, network, and make their products available on the internet to escape the strain of face-to-face engagement.19 The utilization of social services is positively associated with neuroticism. Individuals with a high degree of neuroticism are more likely to begin blogging as a digital expression. Finally, individuals with high neuroticism do not appear to be resistant to new technologies or features.\n\nExtraversion\n\nSocial, outgoing, active, and warm interpersonal interactions define extraversion.20 Buecker et al.,20 further explains that energy, spontaneity, dominance, and sociability are more extroverted, while introverted people are regarded as sluggish, restrained, contemplative, and silent. According to previous studies, those with high extroversion are more active in adopting technology. Extraversion is linked to a desire to utilize a software platform constructively.18 Extraversion had a favorable influence on behavioral intention. The study by Şahin et al.,16 on the link between instructors’ personalities and their behavioral intention. Extraversion predicts the perceived utility of a virtual reality team and the desire to employ one. In the literature, though, inconsistent outcomes have been documented. Extraversion concerns external sources; hence, it entails superior performance while engaging with people or accomplishing group activities.21 Since it was passive information technology, such individuals could not connect with others via the learning system, resulting in a negative association. From this perspective, it may be inferred that talking with people through SNSs or messengers is significantly connected with extraversion. Furthermore, extraverted persons love social attention and thrill-seeking hobbies. They also have a low level of emotional arousal.\n\nOpenness to experience\n\nNikčević et al.,19 state that curiosity, inventiveness, inquisitiveness, and aesthetic sensitivity are all characteristics of openness to experience. People that are open to new experiences and beliefs actively seek them out. Openness studies have shown a variety of outcomes. According to several studies, openness is linked to a desire to utilize technology. Openness, for instance, is a personality quality that impacts the desire to work with a virtual reality group. Openness is linked to a good desire to utilize technology. On the other hand, openness had no bearing on the desire to utilize technology; it only impacted perceived ease of use (PEU). Furthermore, openness has little impact on the use of mobile applications. Şahin et al.,16 claimed that the mobile applications they utilized in their research diminished openness since many people widely adopted them. A more open person is more inclined to take chances to succeed. As a result, if many individuals have already adopted a service or technology, it is no longer a risky position. Most individuals use stickers and messengers daily, and openness is not anticipated to take a motivational role in using or purchasing stickers.\n\nAgreeableness\n\nAccording to Buecker et al.,20 kindness, helpfulness, being thoughtful, and being altruistic toward others are characteristics of an agreeable personality. Agreeableness is linked to interpersonal connections. Individuals that are agreeable are socially oriented and want a sense of belonging. Stajkovic et al.,15 adds that agreeable individuals want social value when utilizing social networking sites; therefore, pleasant individuals are socially driven toward assisting and collaborating with others. Numerous research has shown a link between agreeableness and perceived usefulness when utilizing technology.21 When working with new technology, friendly individuals are more responsive and collaborative, and they strive to find the good elements. Furthermore, if technology facilitates cooperation in completing tasks and job completion, it will be significantly linked to agreeability.22 Individuals with a high agreeableness use stickers to show pleasant feelings toward others. Emojis representing blushing cheeks are associated with agreeableness because blushing is a signal that promotes favorable social relationships. As a result, persons with high agreeableness will want to participate in more emotional interactions, and stickers are an excellent tool. As a result, it was expected that persons with a high agreeability would utilize stickers to convey their feelings better and demonstrate closeness.\n\nConscientiousness\n\nPeople who have high conscientiousness follow the rules, exercise self-control, and put in a lot of effort.23 The link between conscientiousness and social media usage has been studied in certain research. More conscientious people are less likely to actively engage in social media and those who are more conscientious show more remorse when they share improper content.24 When they use SNSs, they look for content that has monetary worth. Individuals with strong conscientiousness are tight with themselves and encourage online learning activities while rejecting online pleasure pursuits. They shun leisure applications since they are ineffective or bothersome for mobile apps. Individuals use stickers for various purposes, but the fundamental goal of personal messengers is to interact. Individuals with high conscientiousness will utilize stickers for this reason if stickers increase the productivity of the discussion. The phrase complement motive is linked to precise communication and emphasizing delivery, which is important for enhancing conversation performance.18 Individuals with high conscientiousness, according to,24 are strict with themselves and prefer online learning activities while rejecting online pleasure pursuits. As a result, we hypothesized that a high level of conscientiousness would be connected with a desire to complete sentences.\n\n(H1): The big five personality traits (at least three of which) have a significant and positive influence on perceived enjoyment of paid stickers.\n\n(H2): The big five personality traits (at least three of which) have a significant and positive influence on the perceived usefulness of paid stickers.\n\nPersonal and interactive engagements have been investigated in associated academic areas like sociology, psychology, and organizational behavior, but it has not been emphasized lately in the marketing sector. Researchers in marketing have begun to look at the topic, particularly in the service and mobile settings.25 Zainuddin et al.,26 reiterates that consumer engagement is widely thought to depend on connections between the engagement subject and the engagement object, even though studies have yet to agree on consumer engagement. According to several academics, interactive engagement has behavioral, cognitive, and emotional elements. Liu et al.,13 specifically developed a measuring instrument for personal messenger interactive engagement, referring to these three characteristics as cognitive processing, attachment, and activation. These dimensions are theoretically, and an empirically distinct notion, which implies their nomological networks, may vary, and their determinants, consequences, and moderators may or may not be the same.25 Furthermore, they play distinct functions in different circumstances, resulting in variable degrees of participation.\n\n(H3): Interactive engagement has a significant and positive influence on the behavioral intention to use paid stickers\n\n(H4): Personal engagement has a significant and positive influence on the behavioral intention to use paid stickers\n\nThe technology acceptance model (TAM) originated with a curiosity about the elements that influence people's acceptance or rejection of information technology.27 The TAM has been investigated in terms of motivation. Salloum et al.,28 state that extrinsic motivation is a kind of it, and perceived usefulness and proposed an integrated technology adoption model that includes intrinsic motivation via pleasure. According to research, employing perceived pleasure to quantify intrinsic motivation, extrinsic and intrinsic incentives promote sustained SNS use.29 Many researchers have tried to explain motivational aspects using the TAM, although the questions posed in this research deal with abstract dimensions. Estriegana et al.,30 looked at the distinctiveness of learning and the incentives linked with environmental aspects on the internet, indicating that particular motivations are more contextual than generic. The use of stickers in personal messengers has its own set of peculiarities. They are mainly available online, are simple to use, and are handy. The latter is a common feature of social networking sites.\n\nPerceived enjoyment effect on behavioral intention\n\nIndividuals’ intrinsic drive to utilize a system is perceived as delightful,31 Sukendro et al.,31 stated that consumers generally accept emerging technologies and techniques since they may bring intrinsic perks like entertainment, enjoyment, etc. A few earlier studies have only studied the association between perceived enjoyment and behavioral intentions.32 Chao33 states that enthusiasm, pleasure, and other factors of perceived enjoyment have a substantial impact on behavioral intention. Users who have a positive attitude about new technology will be more likely to utilize the new application. The time of usage is connected to pleasure or perceived enjoyment. Pleasure and excitement will raise anticipation, hence affecting behavioral intention.\n\n(H5): Perceived enjoyment has a significant and positive influence on the behavioral intention to use paid stickers\n\nPerceived ease of use effect on behavioral intention\n\n‘Ease of use’ is described as a person's view that using new technology relieves them of strain.34 Sun and Gao35 suggested that perceived ease of use is a system that is considered simple to grasp, analyze, or operate, causing buyers to plan to purchase online. Lin et al.,36 reiterates that consumers’ perceptions of the ease of use and adaptability of stickers’ impact customers’ motives towards behavioral intention. Perceived ease of use is related to behavioral intention.\n\n(H6): Perceived ease of use has a significant and positive influence on the behavioral intention to use paid stickers\n\nPerceived usefulness effect on behavioral intention\n\nThe extent to which an individual feels that implementing a strategic approach would help them achieve more success is perceived usefulness.37 Chao33 defines perceived usefulness as how humans feel that employing a given system would increase their work performance. When it comes to perceived usefulness, people typically inquire about how technology helps them increase their efficiency, profitability, and efficacy.35 Customers’ perceptions of stickers’ usefulness are regarded as an innovative feature that aids in developing more efficient methods for measuring consumers’ behavioral engagement.\n\n(H7): Perceived usefulness has a significant and positive influence on the behavioral intention to use paid stickers\n\n\nMethods\n\nThis study was approved by the Research Ethics Committee of King Mongkut's Institute of Technology Ladkrabang, Thailand with study number EC-KMITL_65_077. The Ethics Committee granted the study an exemption waiver in line with the Declaration of Helsinki, ICH Guidelines for Good Clinical Practice, and other international guidelines for human research protection. We confirm that all respondents gave their informed consent voluntarily. The questionnaire did not include any information that might be used to identify respondents. They could also refuse to answer any question that they felt invaded their privacy. Participants were promised that any freely submitted information in the course of this study would be treated confidentially, including any information that could reveal their identity. Written informed consent was obtained in the first stage of the questionnaire section before respondents are exposed to the questionnaire questions proper.\n\nThe study was a survey research design focused on investigating the role of personality traits and engagement factors in using paid stickers in personal communication such as in Messengers. The research relied on primary data collected from a representative sample of the respondents. The study population was the people who use stickers such as emoticons and emojis in their online conversations. Therefore, the population of the study was quite large. The people in Bangkok city were considered suitable for sampling to determine the sample size. The questionnaire was developed in English and hosted online using Google Forms; a campaign was run requesting people take part in the survey on social media platforms including Facebook, LINE, Instagram, Twitter, and Whatsapp. Users on these platforms that fit the study criteria were encouraged to complete the survey. The target sample size was 600 respondents, and 473 people answered the questionnaire. Before respondents are taken to the main questionnaire, they gave their written consent to participate in the study with the undertaken that their data will be kept confidential, and that the questions do not involve a personally identifying questions. Respondents were also informed that they had the option of exiting the study at any point they are not comfortable with the nature of the questions being asked. After cleaning the data from respondents, including removing those with incomplete answers or illegible responses, 391 responses were considered suitable for data extraction for the study. The survey was conducted between May 14, 2022, and May 31, 2022.\n\nThe questionnaire was divided into two main sections; the first section was used to produce information about the demographic data of the respondents, while the second section was used to elicit responses to the research hypotheses.64 The first section of the demographic data covered the gender, age, education, employment and income of the respondents and their use of paid stickers. The section had seven questions, while the second section had 54 questions covering the study hypotheses. Extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience had six questions each, while perceived ease of use, perceived usefulness, perceived enjoyment, purchase intention, and interactive engagement had four questions each. The scales and the variables are summarized in Table 1. Prior to the main study survey, a pilot study was undertaken to test the reliability of the research instrument by administering the questionnaire to 30 respondents from May 14–16, 2022. The pilot study was hosted using Google Forms and shared with participants using Facebook and the Line app. Once the target sample (30) was achieved, the pilot study was discontinued. The final survey did not contain these initial respondents. This made it possible for the author to evaluate the appropriateness and readability of each questionnaire item. The pilot study was consistent with the intent of the research thus no changes were required to the questionnaire.\n\nThe data was collected using a 5-point Likert scale on a questionnaire. his contained scales ranging from 1 to 5, with 1 indicating ‘strongly disagree’ and 5 indicating ‘strongly agree’.63–64 The researcher made certain that the questionnaire did not include any options that could divulge personal or identifying information. The study participants stayed anonymous as a result of this. Several strategies were used to analyze the data. The first phase was data cleaning, which included eliminating missing data, identifying and deleting outliers, and removing any numbers that did not appear to be consistent with the rest of the data. This was followed by descriptive statistics, which entails computing the characteristics of the data's variables, such as mean, mode, median, standard deviation, percentiles, skewness, kurtosis, and maximum and minimum values. Normality tests, correlation descriptive statistics, validity and reliability testing, and confirmatory factor analysis were among the diagnostic tests used. Utilizing AMOS version 26, Structural Equation Modeling (SEM) was used to evaluate the study's hypotheses.\n\nThe study variables were developed from a critical literature review and applicable theoretical frameworks.56 The personal traits used in the study were obtained from the big five personality traits, which include neuroticism,45–46 extraversion,38–39 openness to experience,40–45 agreeableness,40–41 and conscientiousness.42–45 The engagement factors were represented by personal engagement and interactive engagement. The Technology Acceptance Model provided four additional variables: perceived enjoyment,47,50–51 perceived ease of use,44,47 perceived usefulness,48–49 and behavioral intention to use.50–52 Among these variables, perceived enjoyment and usefulness were the mediating variables; behavioral intention was a dependent variable, while others were independent variables, this is summarized in Table 1. The applied conceptual framework is presented in Figure 1.\n\nVarious techniques were adopted in the process of data analysis. The first was evaluating the model's suitability and fitness of the study variables in the proposed conceptual framework. This was done using reliability and validity techniques, including Composite Reliability (CR), Average Variance Extracted (AVE), Cronbach's alpha, and factor loadings. The measurement of the proposed research model was conducted using convergent validity, discriminant validity, and internal consistency. For composite reliability, the indicator threshold was supposed to be above or equal to 0.7 based on the recommendations of Hair et al.,.57 The model's fitness was evaluated using confirmatory factor analysis (CFA) with various indicted being tested. The Partial Least Square Structural Equation Modeling (PLS-SEM) was utilized in the analysis of the proposed hypothesis.\n\nIn research projects, establishing trustworthiness entails establishing the reliability of the research process. Credibility refers to the qualitative researcher's belief in the accuracy of the study's findings. To be believed, the researchers had to show that data collection and analysis were done in a specific, constant, and detailed method by documenting, standardizing, and revealing the techniques of analysis in sufficient detail to allow the reader to evaluate whether the process was plausible. In the sections above, the entire research process has been explained in detail including, method of data collection, time frame of data collection, method of analysis, and the triangulation method used in the analysis to robustly analyze the data,\n\n\nResults\n\nThe first analysis was to evaluate the demographic characteristics of the respondents. The results indicated in Table 2 show for the gender, females were the majority (54%) while males were the minority (46%). Considering the age variable, the majority age group was 21 – 30 years, followed by 31 – 40 years then 18 – 20 years, and then the least were over than 60+ years. Most of the respondents had a bachelor’s degree (34%) while the least represented were those with postgraduate degrees (17%) In terms of occupation, about 27% of the respondents were company employees, while the unemployed accounted for the least numbber of respondents with about 11%. When assessing the income of the respondents, those earning between 20,000 Bahts and 30,000 Bahts constituted over 24% of the respondents while those earning less than 10,000 Bahts were the least with about 14% of the respondents. For the ‘how often the respondents used the sticker’ variable, the majority was 11 – 20 times, followed by those who have used stickers and emoticons 21 – 30 times. For the frequency of purchase of the sticker, minority respondents indicated 11 – 20 times, followed by 21 – 30 times and the least was 40+ times.\n\nThe measurement of the proposed research model was conducted using convergent validity, discriminant validity, and internal consistency. For composite reliability, the indicators threshold was supposed to be above or equal to 0.7.57 From the presented results, it was found that the composite reliability results ranged from 0.701 to 0.922 which were all within the required threshold. The internal consistency of the measurement model was evaluated using Cronbach's alpha coefficients and the average variance extracted (AVE). The required threshold for Cronbach's alpha is at least 7.0 which indicate to be acceptable, good, or excellent. The results for Cronbach's alpha ranged from 0.729 to 0.937 which confirms that the indicators were within the required threshold.57–58 Considering the AVE, the required threshold, according to Ramaya et al.,59 and Hair et al.,57 should be 0.5 or greater. From the results, the AVE ranged from 0.553 to 0.762, which satisfied the required threshold. These findings confirmed that the measurement model’s internal consistency, validity, and reliability were satisfactory and within the required threshold.\n\nThe fitness of the model was also evaluated by checking the fit indices of the model which demonstrated the goodness of fit of the proposed model. From the goodness of fit tests done using confirmatory factor analysis, it was found that GFI = 0.942, NFI = 0.951, CFI = 0.963, TLI = 0.968, RFI = 0.945, AGFI = 0.863, RMR = 0.048, RMSEA.096, SRMR = 0.0456, and the Chi-square/df = 2.901 as shown in Figure 2 and Table 3. These figures depicted a satisfactory fitness based on the thresholds recommended by.60–62\n\nThe goal of this study was to see how personality traits and engagement factors influenced the use of paid stickers in personal messages, such as emoticons and emojis. The results tabulated in Table 4 indicated that four of the big five personality traits significantly and positively influence perceived enjoyment (conscientiousness β = 0.144, p<0.000; extraversion β = 0.170, p<0.000; openness β = 0.205, p<0.000; neuroticism β = 0.544, p<0.000). This confirmed H1 that big five personality traits (at least three) have a significant and positive influence on perceived enjoyment of paid stickers. The results also indicated that three of the big five personality traits significantly and positively influence perceived usefulness (agreeableness β = 0.198, p=0.000; openness β = 0.275, p<0.000; neuroticism β = 0.380, p<0.000). As a result, H2 was supported that the big five personality traits (at least three) have a significant and positive influence on the perceived usefulness of paid stickers. The path coefficient between interactive engagement and the behavioral intention was positive and significant (β = 0.415, p<0.000) confirming H3 that interactive engagement has a significant and positive influence on the behavioral intention to use paid stickers.\n\nThe path coefficient between personal engagement and the behavioral intention was positive and significant (β = 0.143, p<0.000) confirming H4 that personal engagement has a significant and positive influence on the behavioral intention to use paid stickers. The path coefficient between perceived enjoyment and the behavioral intention was positive and significant (β = 0.262, p<0.000) confirming H5 that perceived enjoyment has a significant and positive influence on the behavioral intention to use paid stickers. The path coefficient between perceived ease of use and the behavioral intention was positive and significant (β = 0.326, p<0.000) confirming H6 that perceived ease of use has a significant and positive influence on the behavioral intention to use paid stickers.\n\n\nDiscussion\n\nThe objective of this research was to investigate the role of personality traits and engagement factors in influencing the use of purchased or paid-for stickers in personal communication messages. To evaluate the personality traits, the big five personality traits were used – neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. The results indicated that these factors were significant influencers of the perceived enjoyment and perceived usefulness of the use of paid-for stickers. Considering the specific aspects, conscientiousness, extraversion, openness, and neuroticism influence perceived enjoyment when using paid stickers in personal messages. These findings echo that of Ali24 who indicated that individuals with strong conscientiousness are tight with themselves and encourage online learning activities while rejecting online pleasure pursuits. Nikčević et al.,19 observed that openness is linked to a desire to utilize technology. According to Goreis and Voracek,18 those with high extraversion are more active in adopting technology as well as the desire to utilize a software platform constructively.\n\nIn a similar breath, agreeableness, openness, and neuroticism have a significant influence on the perceived usefulness of paid stickers in personal messages. These findings are in line with that of Buecker et al.,,20 who indicated that individuals that are agreeable are socially oriented and want a sense of belonging. Agreeable individuals want social value when utilizing social networking sites; therefore, pleasant individuals are socially driven toward assisting and collaborating with others. Similarly, Goreis and Voracek18 pointed out that individuals with high neuroticism seek knowledge, network, and make their products available on the internet to escape the strain of face-to-face engagement.\n\nThe effects of engagement factors on the behavioral intention to use paid stickers on personal communication messages were evaluated using two aspects, interactive engagement, and personal engagement. These two engagement factors were found to significantly and positively influence the intention to use paid stickers in personal messages. This implied that the engagement aspects such as psychological connection, pleasurable emotional state, sense of pride, ability to express oneself, express emotions, and sense of empowerment associated with paid stickers in personal messages increases their uses. Liu et al.,13 agreed with these conclusions, stating that personal comunication messages interactive engagement is associated with connections between the engagement subject and the engagement object, even though studies have yet to agree on consumer engagement.\n\nIn addition, the technology acceptance model factors were used to evaluate their influence on the behavioral intention to use paid stickers in personal messages. The factors used were perceived enjoyment, perceived usefulness, and perceived ease of use. The results indicated that perceived enjoyment and perceived ease of use have a significant and positive influence on the intention to use paid stickers such as emoticons and emojis in personal messages. It implied that enjoyment aspects such as feeling good, enjoyable, and interesting feelings while using stickers are important in their use. As well, as perceived ease of use aspects such as ease of using, ability to become skillful, and ability to clearly understand if important for the behavior towards adopting paid stickers in personal messages. These findings were supported by Lin et al.,,36 who claimed that consumers’ perceptions of the ease of use and adaptability of stickers impact customers’ motives towards behavioral intention. Additionally, Chao33 stated that enthusiasm, pleasure, and other factors of perceived enjoyment have a substantial impact on behavioral intention to adopt and use the technology. When the users perceive the technology as enjoyable, they tend to use it more often.\n\nThis study has both theoretical and managerial implications. Considering the theoretical implications, the study has contributed significantly to the available literature regarding the adoption and use of paid stickers in personal messages. As mentioned in the literature, there is a dearth of scholarship about the issue under examination in the study. Another theoretical contribution is that the study has proposed a new conceptual framework, which could be considered in future studies. The conceptual framework is a hybrid of three models, the Technology Acceptance Model, the Big Five Personality Traits Model, and the Personal Engagement Model. The three models were combined to evaluate how their inherent factors influence the behavior intention to use paid stickers in personal messages. Considering the managerial implications, several recommendations could be made for the people in the business of developing and selling stickers such as emojis and emoticons; the study recommends that the five personality traits should be considered in developing stickers, as they influence user enjoyment, which is a critical factor in the use of stickers such as emojis and emoticons. Secondly, developers should consider the ability of the stickers to have personal engagement and interactive engagement, as this would enhance the connection between the persons communicating. Additionally, enjoyment factors such as feeling good, enjoyable, and interesting feelings while using stickers are important in their use, as well as ease of using, ability to become skillful, and ability to clearly understand.\n\n\nConclusions\n\nFrom the study, several conclusions could be developed, regarding the role of personality traits and engagement factors in the use of paid stickers in personal communication messages. The first conclusion to mention is that this developed and adopted an extended study model, which combined three theories – personality trait theory under the big five personality traits, the TAM theory, and the personal engagement factors. The framework led to insightful results regarding the use of paid stickers on personal messages. The study concludes that four personality traits - conscientiousness, extraversion, openness, and neuroticism - influence perceived enjoyment. Additionally, agreeableness, openness, and neuroticism have a significant influence on the perceived usefulness of paid stickers in personal messages. Considering the personal engagement factors, this research concludes that both interactive engagement and personal engagement are important factors in determining the behavior intention to use paid stickers in personal messages. The research also concludes that perceived enjoyment and perceived ease of use have a significant and positive influence on the intention to use paid stickers such as emoticons and emojis in personal messages. The limitation of the study was that it specifically focused on one aspect of social media, the paid stickers such as emoticons and emojis. This fact needs to be recognized in the application of the results. Another limitation is that the study was carried out in Thailand, specifically in Bangkok city. This brought about the geographical limitation which should be considered in the application of the results.\n\n\nData availability\n\nFigshare: Paid sticker article datasets. https://doi.org/10.6084/m9.figshare.19964480.v5.63\n\nThe project contains the following underlying data:\n\n• Paid Sticker Article Datasets.xls. (Anonymised raw data responses to the survey).\n\nFigshare: Paid sticker article datasets. https://doi.org/10.6084/m9.figshare.20217719.v3.64\n\nThis project contains the following extended data:\n\n• Survey form.pdf. (Paid sticker questionnaire used in this study).\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nKonrad A, Herring SC, Choi D: Sticker and emoji use in Facebook Messenger: Implications for graphicon change. J. Comput.-Mediat. Comm. 2020; 25(3): 217–235. Publisher Full Text\n\nKimura-Thollander P, Kumar N: Examining the global language of emojis: designing for cultural representation. Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1–14).\n\nWang Y, Li Y, Gui X, et al.: Culturally-embedded visual literacy: A study of impression management via emoticon, emoji, sticker, and meme on social media in China. Proceedings of the ACM on Human-Computer Interaction. 2019; 3(CSCW): 1–24.\n\nTang Y, Hew KF: Emoticon, emoji, and sticker use in computer-mediated communication: A review of theories and research findings. Intl. J. Comm. 2019; 13: 2457–2483.\n\nDe Seta G: Biaoqing: The circulation of emoticons, emoji, stickers, and custom images on Chinese digital media platforms. First Monday. 2018; 23. Publisher Full Text\n\nTang Y, Hew KF:Emoticon, emoji, and sticker use in computer-mediated communications: Understanding its communicative function, impact, user behavior, and motive. New media for educational change. Singapore:Springer; 2018; (pp. 191–201).\n\nLee SY, Lee SW: Social media use and job performance in the workplace: The effects of facebook and kakaotalk use on job performance in South Korea. Sustainability. 2020; 12(10): 4052. Publisher Full Text\n\nSteinberg M: LINE as super app: Platformization in East Asia. Social Med.+ Soc. 2020; 6(2): 2056305120933285.\n\nRiadi I, Sunardi S, Rauli ME: Live forensics analysis of line app on proprietary operating system. Kinetik: Game Tech., Inform. Sys., Comput. Netw., Comput., Electr. & Contr. 2019; 4: 305–314. Publisher Full Text\n\nIqbal M: Line Revenue and Usage Statistics (2022). Business of Apps. 2022. Accessed on 8 May, 2022.Reference Source\n\nJung B, Kim H, Lee SHS: The impact of belongingness and graphic-based emoticon usage motives on emoticon purchase intentions for MIM: An analysis of Korean KakaoTalk users. Online Inform. Rev. 2021; 46: 391–411. Publisher Full Text\n\nJobst N: Annual revenue of Kakao Corporation from 2013 to 2021. Statista. 2022. Accessed on 15 March, 2022.Reference Source\n\nLiu L, Liu X, Cheng S, Li K: Research on relationship between the comprehension and usage of emoticons. Paper presented at the International Joint Conference on Information, Media and Engineering (ICIME). 2018; pp. 55–60. IEEE.\n\nDainas A, Herring SC:Interpreting emoji pragmatics.Xie C, Yus F, Haberland H, editors. Internet Pragmatics: Theory and Practice. 2021; pp. 107–144.Reference Source\n\nStajkovic AD, Bandura A, Locke EA, et al.: Test of three conceptual models of influence of the big five personality traits and self-efficacy on academic performance: A meta-analytic path-analysis. Pers. Individ. Dif. 2018; 120: 238–245. Publisher Full Text\n\nŞahin F, Karadağ H, Tuncer B: Big five personality traits, entrepreneurial self-efficacy and entrepreneurial intention: A configurational approach. Intl. J. Entrepre. Behav. & Res. 2019; 25: 1188–1211. Publisher Full Text\n\nOshio A, Taku K, Hirano M, et al.: Resilience and Big Five personality traits: A meta-analysis. Pers. Individ. Dif. 2018; 127: 54–60. Publisher Full Text\n\nGoreis A, Voracek M: A systematic review and meta-analysis of psychological research on conspiracy beliefs: Field characteristics, measurement instruments, and associations with personality traits. Front. Psychol. 2019; 10: 205. PubMed Abstract \| Publisher Full Text\n\nNikčević AV, Marino C, Kolubinski DC, et al.: Modelling the contribution of the Big Five personality traits, health anxiety, and COVID-19 psychological distress to generalized anxiety and depressive symptoms during the COVID-19 pandemic. J. Affec. Disord. 2021; 279: 578–584. PubMed Abstract \| Publisher Full Text\n\nBuecker S, Maes M, Denissen JJ, et al.: Loneliness and the Big Five personality traits: A meta–analysis. Euro. J. Personal. 2020; 34(1): 8–28. Publisher Full Text\n\nAllen MS, Walter EE: Linking big five personality traits to sexuality and sexual health: A meta-analytic review. Psych. Bullet. 2018; 144: 1081–1110. PubMed Abstract \| Publisher Full Text\n\nJayawickreme E, Zachry CE, Fleeson W: Whole trait theory: An integrative approach to examining personality structure and process. Pers. & Individ. Diff. 2019; 136: 2–11. Publisher Full Text\n\nPletzer JL, Bentvelzen M, Oostrom JK, et al.: A meta-analysis of the relations between personality and workplace deviance: Big Five versus HEXACO. J. Vocat. Behav. 2019; 112: 369–383. Publisher Full Text\n\nAli I: Personality traits, individual innovativeness and satisfaction with life. J. Innova. & Knowl. 2019; 4: 38–46. Publisher Full Text\n\nKaryda M, Wilde D, Kjærsgaard MG: Narrative physicalization: Supporting interactive engagement with personal data. IEEE Comput. Graph. & Applicat. 2020; 41(1): 74–86.\n\nZainuddin Z, Shujahat M, Haruna H, et al.: The role of gamified e-quizzes on student learning and engagement: An interactive gamification solution for a formative assessment system. Comp. & Edu. 2020; 145: 103729. Publisher Full Text\n\nRahimi B, Nadri H, Afshar HL, et al.: A systematic review of the technology acceptance model in health informatics. Appl. Clin. Inform. 2018; 9(03): 604–634.\n\nSalloum SA, Alhamad AQM, Al-Emran M, et al.: Exploring students’ acceptance of e-learning through the development of a comprehensive technology acceptance model. IEEE Access. 2019; 7: 128445–128462. Publisher Full Text\n\nRafique H, Almagrabi AO, Shamim A, et al.: Investigating the acceptance of mobile library applications with an extended technology acceptance model (TAM). Comput. & Edu. 2020; 145: 103732. Publisher Full Text\n\nEstriegana R, Medina-Merodio JA, Barchino R: Student acceptance of virtual laboratory and practical work: An extension of the technology acceptance model. Comput. & Edu. 2019; 135: 1–14. Publisher Full Text\n\nSukendro S, Habibi A, Khaeruddin K, et al.: Using an extended Technology Acceptance Model to understand students’ use of e-learning during Covid-19: Indonesian sport science education context. Heliyon. 2020; 6(11): e05410. PubMed Abstract \| Publisher Full Text\n\nScherer R, Siddiq F, Tondeur J: The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Comput. & Edu. 2019; 128: 13–35. Publisher Full Text\n\nChao CM: Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Front. Psychol. 2019; 10: 1652. PubMed Abstract \| Publisher Full Text\n\nLang C: Perceived risks and enjoyment of access-based consumption: Identifying barriers and motivations to fashion renting. Fash. & Text. 2018; 5(1): 1–18.\n\nSun Y, Gao F: An investigation of the influence of intrinsic motivation on students’ intention to use mobile devices in language learning. Edu. Tech. Res. & Develop. 2020; 68(3): 1181–1198. Publisher Full Text\n\nLin CW, Lin YS, Liao CC, et al.: Utilizing technology acceptance model for influences of smartphone addiction on behavioural intention. Math. Probl. Engr. 2021; 2021: 1–7. Publisher Full Text\n\nDedeoglu BB, Bilgihan A, Ye BH, et al.: The impact of servicescape on hedonic value and behavioral intentions: The importance of previous experience. Intl. J. Hosp. Manag. 2018; 72: 10–20. Publisher Full Text\n\nWatson D, Clark LA:Extraversion and its positive emotional core. Handbook of Personality Psychology. Hogan R, Johnson JA, Briggs SR, editors.New York, NY:Academic Press;1997; 767–793.\n\nThomas K: Dimensions of Personality: Introduction to Psychology. Hove, United Kingdom:Routledge;2021; 373–416.\n\nJacques PH, Garger J, Brown CA, et al.: Personality and virtual reality team candidates: the roles of personality traits, technology anxiety and trust as predictors of perceptions of virtual reality teams. J. Bus. Manag. 2009; 15: 143–157.\n\nXu R, Frey RM, Fleisch E, et al.: Understanding the impact of personality traits on mobile app adoption–insights from a large-scale field study. Comput. Hum. Behav. 2016; 62: 244–256. Publisher Full Text\n\nSeidman G: Self-presentation and belonging on Facebook: how personality influences social media use and motivations. Pers. Individ. Dif. 2013; 54: 402–407. Publisher Full Text\n\nChua YP, Chua YP: Do computer-mediated communication skill, knowledge and motivation mediate the relationships between personality traits and attitude toward Facebook? Comput. Hum. Behav. 2017; 70: 51–59. Publisher Full Text\n\nLiu D, Campbell WK: The big five personality traits, big two metatraits and social media: a meta-analysis. J. Res. Pers. 2017; 70: 229–240. Publisher Full Text\n\nDevaraj S, Easley RF, Crant JM: Research note—how does personality matter? Relating the five-factor model to technology acceptance and use. Inf. Syst. Res. 2008; 19: 93–105. Publisher Full Text\n\nTackett JL, Lahey BB:Neuroticism. The Oxford Handbook of the Five Factor Model. Widiger TA, editor.New York, NY:Oxford University Press;2017.\n\nPark SY, Nam M-W, Cha S-B: University students’ behavioral intention to use mobile learning: Evaluating the Technology Acceptance Model. Brit. J. Edu. Tech. 2012; 43: 592–605. Publisher Full Text\n\nJoo YJ, So HJ, Kim NH: Examination of relationships among students’ self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Comput. & Edu. 2018; 122: 260–272. Publisher Full Text\n\nRabaa’i AA: The use of UTAUT to investigate the adoption of e-government in Jordan: a cultural perspective. Intl. J. Bus. Inform. Sys. 2017; 24(3): 285–315.\n\nLakhal S, Khechine H, Pascot D: Student behavioural intentions to use desktop video conferencing in a distance course: integration of autonomy to the UTAUT model. J. Comput. in High. Edu. 2013; 25(2): 93–121. Publisher Full Text\n\nBing Tan P: Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan. SAGE Open. 2013; 3: 215824401350383–215824401350312. Publisher Full Text\n\nKhechine H, Lakhai S, Pascot D, et al.: UTAUT model for blended learning: the role of gender and age in the intention to use webinars. Interd. J. E-Learn. & Learn. Obj. 2014; 10: 33–52.\n\nHarter JK, Schmidt FL, Hayes TL: Business-unit-level relationship between employee satisfaction, employee engagement, and business outcomes: a meta-analysis. J. Appl. Psychol. 2002; 87(2): 268–279. PubMed Abstract \| Publisher Full Text\n\nMacey WH, Schneider B: The meaning of employee engagement. Industr. Org. Psychol. 2008; 1(1): 3–30. Publisher Full Text\n\nEldor L, Harpaz I: A process model of employee engagement: The learning climate and its relationship with extra-role performance behaviors. J. Organiz. Behav. 2016; 37(2): 213–235. Publisher Full Text\n\nKang H, Park Y, Shin Y, et al.: What Makes Consumers’ Intention to Purchase Paid Stickers in Personal Messenger? The Role of Personality and Motivational Factors. Front. Psychol. 2022; 12: 1–19. PubMed Abstract \| Publisher Full Text\n\nHair JF, Ringle CM, Sarstedt M: PLS-SEM: Indeed a silver bullet. J. Market. Theor. & Pract. 2011; 19(2): 139–152. Publisher Full Text\n\nIngenhoff D, Buhmann A: Advancing PR measurement and evaluation: Demonstrating the properties and assessment of variance-based structural equation models using an example study on corporate reputation. Publ. Rel. Rev. 2016; 42(3): 418–431. Publisher Full Text\n\nRamayah T, Cheah J, Chuah F, et al.: Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0: An updated and practical guide to statistical analysis. Malaysia:Pearson;2018.\n\nByrne BM: Structural equation modeling with Mplus: Basic concepts, applications, and programming. New York:Routledge;2013.\n\nByrne BM: Structural equation modeling with AMOS, EQS, and LISREL: Comparative approaches to testing for the factorial validity of a measuring instrument. Intl. J. Test. 2001; 1(1): 55–86. Publisher Full Text\n\nCollier JE: Applied structural equation modeling using AMOS: Basic to advanced techniques. Milton Park:Routledge;2020.\n\nSawmong S: Paid sticker article datasets. figshare. [Dataset].2022. Publisher Full Text\n\nSawmong S: Paid sticker survey. figshare. [Dataset].2022. Publisher Full Text" }	[ { "id": "146997", "date": "26 Aug 2022", "name": "Babita Singla", "expertise": [ "Reviewer Expertise Marketing and Retail" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nI have reviewed this article in detail. It investigates the personality traits and engagement factors that affect the use of paid stickers in personal communication. The factors researched included conscientiousness, extraversion, openness, neuroticism, and ease of use. The use of paid stickers in personal communication was found to be majorly influenced by perceived ease of use and perceived enjoyment.\n\nIn this report, the author adopted the Technology Acceptance Model (TAM) and the Theory of big five personality traits and developed the conceptual framework and hypothesis on its basis. The theoretical background and empirical literature have been well established.\n\nThe author used structural equation modeling (SEM) with satisfactory results on the measurement model – including reliability, validity, and goodness of fit tests.\n\nFrom a critical review of the article, I am of the view that the manuscript satisfies the required threshold for publication. However, I have several comments have been made regarding this manuscript, and have been summarized below. These comments do not require revisions, and the article can be indexed in its current form.\nMain comments:\nThe article has adequately discussed the limitations of the study. However, it has not given a direction for future research. I believe that based on these limitations, the article could have highlighted the recommendations that could be considered by future researchers.\n\nThe article has a major strength in that it has attached the data and model used. Therefore, the findings of the research are verifiable, and the reliability and validity examined\n\nAnother notable aspect is that references, almost all of them are recent ones (previous five years). This is very commendable as it displays the time relevance of the article's findings\n\nSpecific comments\n\nIn the introduction, the background of the topic is well introduced. As well, I was able to clearly identify the problem of the study.\n\nHowever, I did not find a statement that clearly states the objective/purpose of the study. It is always advisable to state the objective of the study in addition to the problem statement\n\nThe results presentation is empirically satisfactory\n\nThe discussion of the results has been done adequately. The findings of the article were compared with previous findings, with adequate citations. I find this commendable\n\nFor the model measurement, it is usually a good practice to present the findings of the model fitness on a table, alongside their threshold, and a column indicating whether the threshold has been achieved or not\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "146999", "date": "30 Aug 2022", "name": "William Philip Wall", "expertise": [ "Reviewer Expertise Business Management", "Strategic Management", "Entrepreneurship", "Startups", "Angel Investment", "Renewable Energy", "Sustainable Development." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article investigates the personality traits and engagement factors affecting the use of paid stickers in messaging. Based on the research study, the use of paid stickers in communication messages significantly influenced by perceived enjoyment and perceived ease of use.\n\nAuthors have used multiple theories including Technology Acceptance Theory (TAM) and Big Five Personality Traits to develop the research framework and conducted an empirical analysis.\n\nAuthor has comprehensively covered the background and literature review section.\n\nAnalysis have been performed using Reliability, Validity, Confirmatory Factor Analysis and Structural Equation model. The indices of all the models shows the excellent fit.\n\nWith my expertise in the business management discipline, I would like to endorse my recommendation to consider its indexation; however, some of the optional improvements are recommended which can be considered by Author.\n\nMain comments:\n\nIn the article, there are no directions of future research for the other researchers to contribute their results from different environments.\n\nThe article has comprehensively covered the implications and contributions, and conclusion section which gives a complete visibility to its readers about the importance of paid stickers in communication messages.\n\nThe respondent’s data furnished along with the article testifies the study conducted in authentic, and legit.\n\nAlso, the results, and discussion section provides the comprehensive information about the article’s findings and relating the results from the international studies.\n\nSpecific comments\n\nAuthor have detailed the information about the introduction and background of the topic. Also, detailing about the problems of the research study has made it convenient for readers easy understanding.\n\nAuthor can also consider incorporating the research objectives to bring it more clarity.\n\nThe article has comprehensively interpreted the results.\n\nThe discussion section has comprehensively covered the information relating it with previously conducted research studies and also studies conducted internationally highlighting the findings.\n\nAlso, the tabulated illustration of research findings provides its readers an opportunity to determine the hypotheses tested significant.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-915
https://f1000research.com/articles/8-1618/v1	10 Sep 19	{ "type": "Research Article", "title": "Statistical models for the deterioration of kidney function in a primary care population: A retrospective database analysis", "authors": [ "Jason L Oke", "Benjamin G Feakins", "Iryna Schlackow", "Borislava Mihaylova", "Claire Simons", "Chris A O'Callaghan", "Daniel S Lasserson", "F D Richard Hobbs", "Richard J Stevens", "Rafael Perera", "Jason L Oke", "Iryna Schlackow", "Borislava Mihaylova", "Claire Simons", "Chris A O'Callaghan", "Daniel S Lasserson", "F D Richard Hobbs", "Richard J Stevens", "Rafael Perera" ], "abstract": "Background: Evidence for kidney function monitoring intervals in primary care is weak, and based mainly on expert opinion. In the absence of trials of monitoring strategies, an approach combining a model for the natural history of kidney function over time combined with a cost-effectiveness analysis offers the most feasible approach for comparing the effects of monitoring under a variety of policies. This study aimed to create a model for kidney disease progression using routinely collected measures of kidney function. Methods: This is an open cohort study of patients aged ≥18 years, registered at 643 UK general practices contributing to the Clinical Practice Research Datalink between 1 April 2005 and 31 March 2014. At study entry, no patients were kidney transplant donors or recipients, pregnant or on dialysis. Hidden Markov models for estimated glomerular filtration rate (eGFR) stage progression were fitted to four patient cohorts defined by baseline albuminuria stage; adjusted for sex, history of heart failure, cancer, hypertension and diabetes, annually updated for age. Results: Of 1,973,068 patients, 1,921,949 had no recorded urine albumin at baseline, 37,947 had normoalbuminuria (<3mg/mmol), 10,248 had microalbuminuria (3–30mg/mmol), and 2,924 had macroalbuminuria (>30mg/mmol). Estimated annual transition probabilities were 0.75–1.3%, 1.5–2.5%, 3.4–5.4% and 3.1–11.9% for each cohort, respectively. Misclassification of eGFR stage was estimated to occur in 12.1% (95%CI: 11.9–12.2%) to 14.7% (95%CI: 14.1–15.3%) of tests. Male gender, cancer, heart failure and age were independently associated with declining renal function, whereas the impact of raised blood pressure and glucose on renal function was entirely predicted by albuminuria. Conclusions: True kidney function deteriorates slowly over time, declining more sharply with elevated urine albumin, increasing age, heart failure, cancer and male gender. Consecutive eGFR measurements should be interpreted with caution as observed improvement or deterioration may be due to misclassification.", "keywords": [ "Kidney Function Decline", "Chronic Kidney Disease (CKD)", "Estimated Glomerular Filtration Rate (eGFR)", "Proteinuria", "Hidden Markov Model (HMM)", "Primary Care", "Clinical Practice Research Datalink (CPRD)" ], "content": "Introduction\n\nThe National Institute for Health and Care Excellence recommend monitoring kidney function using estimated glomerular filtration rate (eGFR) in people with, or at risk of, chronic kidney disease (CKD)1. The guideline suggests increasing the intensity of monitoring according to the current level of eGFR and albumin-creatinine ratio, stating that monitoring should be tailored according to i) the underlying cause of CKD and ii) past patterns of eGFR and albumin-creatinine ratio, comorbidities, changes to treatments such as reninangiotensin-aldosterone system antagonists, inter-current illness and whether the patient has chosen conservative management of CKD. One of the objectives of monitoring eGFR is to detect progression of CKD, which could precede end-stage renal disease (ESRD). ESRD is associated with substantial morbidity and mortality, with cardiovascular disease mortality rates 10 to 30 times higher in patients on dialysis than in the general population2. Yet, kidney function declines slowly with age and ESRD is rare, even for people with moderately impaired renal function (eGFR 30–59 ml/min/1.73m2). In a study of 58,000 people with CKD stage 3 who were followed for 10 years, the cumulative incidence was 40 per 1,000 people3. It follows that recommendations to monitor everyone annually or more frequently in a community setting for progressive kidney function loss will have a poor yield. Furthermore, as eGFR is a noisy measurement, with a within-person coefficient of variation estimated to be approximately 5.5%4, it is likely two consecutive eGFR measurements may appear to indicate declining renal function when underlying renal function is stable (false positive), or stable renal function when underlying renal function has deteriorated (false negative). Finally, it is arguable as to whether there are any actions that can be taken to halt the deterioration of renal function if progressive CKD is found, as there is currently very little evidence that “catching” CKD early produces any benefit5.\n\nThere have been no trials of screening or monitoring for CKD6 and recommendations for how frequently monitoring should take place are based on expert opinion. In the absence of trials, an approach combining a model for the natural history of kidney function over time combined with a cost-effectiveness analysis offers the most feasible approach for comparing the effects of monitoring under a variety of policies. The aim of this study was to create a model for kidney disease progression using routine measures of kidney function. Our approach simultaneously estimates the true rate of kidney function loss and the probability of misclassification that inevitably occurs from using eGFR. Our study is conducted in a general primary care population and our results will be useful in guiding future recommendations for the timing of monitoring eGFR in primary care.\n\n\nMethods\n\nThe protocol for this research was approved by the Independent Scientific Advisory Committee of the Medicines and Healthcare Products Regulatory Agency (protocol number 14_150R). Ethical approval for observational research using the Clinical Practice Research Datalink with approval from the Independent Scientific Adisory Committee has been granted by a National Research Ethics Service committee (Trent Multi Research Ethics Committee, REC reference number 05/MRE04/87).\n\nWe used the UK Clinical Practice Research Practice Datalink (CPRD)7 to construct an open cohort of adults (≥18 years of age) registered at practices deemed to have “acceptable” patient records (termed “up-to-standard” in CPRD). We included patient records starting from 1 April 2005, post-dating the publication of the Kidney Disease Outcomes Quality Initiative (KDOQI) guidelines for the classification of CKD in 20028 and the introduction of Quality and Outcomes Framework targets in UK primary care in 2004. The study end date was 31 March 2014. Eligible patients had to be registered with their practice for a minimum of 12 months before study entry to ensure adequate recording of baseline covariates. We excluded patients who, in the 12 months before study entry, were pregnant, were receiving dialysis, or were living kidney donors or recipients. Follow-up ended at the study end date, unless preceded by the date of death, transfer out of CPRD, the last available linked data, or (where applicable) pregnancy, renal transplantation/donation, or dialysis.\n\nTo model decline in kidney function, hidden Markov models (HMMs)9–13 were fitted to four patient cohorts defined by baseline albuminuria stage: 1) no albuminuria measurement (unmeasured), 2) normoalbuminuria (<3 mg/mmol), 3) microalbuminuria (3–30 mg/mmol), and 4) macroalbuminuria (>30 mg/mmol). Models were adjusted for sex, heart failure, cancer, hypertension and diabetes, and annually updated age.\n\nThe HMMs comprised two components, a multi-state model governing the ‘true’ underlying progression of CKD, and a second model for the probability of misclassification to allow for the variability in eGFR. The underlying model for CKD was parametrised as uni-directional, in which true kidney function could only deteriorate over time (no spontaneous improvement). The outcome was eGFR stage based on the criteria used for the diagnosis of CKD, i.e. G1–G5. We combined stages G1 and G2 for the purposes of improving model fit. Death from any cause was assumed to be an absorbing state. A representation of the HMMs is depicted in Figure 1.\n\nArrows indicate permitted (instantaneous) transitions. The numbers in brackets depict the estimated glomerular filtration rate ranges (in ml/min/1.732) associated with each stage.\n\nThe HMMs were specified so that it was possible for misclassification to occur in neighbouring eGFR categories. Hence, for a person with true GFR >60 ml/min/1.73m2 we specified the model so that a single measurement of eGFR could fall within a G3a or G3b category due to measurement error and biological variation, but not G4 or G5. For a person with true eGFR in stage G3b, a single measurement of eGFR could be misclassified as either G1/2, G3a, G4 or G5. Death was the only state assumed to be always classified correctly.\n\nTo assess model fit, we used a split-sample approach. Although this is a weak procedure for low-variance methods, such as the Cox proportional hazards model or logistic regression, it is useful for a model that can be over-parametrised or exhibit convergence issues (such as a HMM). We split the data using pseudo-random numbers into equal size training and testing data sets. The model was fit in the training data set and then used to predict trajectories of eGFR for patients in the testing data set, based on their measurement times and covariates. Calibration plots were used to compare the predicted and observed proportion of tests falling within each eGFR category over time. Annual transition rates for kidney function loss and death from any cause were estimated from the model, along with the misclassification probabilities and transition rate multipliers for age, sex, heart failure and cancer, and presented as state model diagrams. The models were used to estimate the probability of progression to a higher stage within six, 12 or 36 months, along with the probability that an eGFR test taken at that time would detect the change (true positive), and the probability that a change in eGFR stage would occur in a person in whom true kidney function had not changed (false positive), for all cohorts for baseline stages G3a and G3b; see Supplementary Tables S18–21 (Extended data)14.\n\nFinally, we estimated global misclassification probabilities for the four cohorts using the Viterbi algorithm15 to find the underlying sequence of true eGFR stages with the highest probability given the observed sequence. Assuming the state predicted by the model was the truth, we calculated the proportion of times the observed state was a lower stage than predicted (under-grading) and the proportion of times the observed was a higher stage than predicted (over-grading), and then added these together to calculate the total number of misclassified tests across cohorts.\n\nAll analyses were performed in R version 3.6.1 (“Action of the Toes”)16, with HMMs fit using version 1.6.7 of the msm package17. Scripts used in these analyses are available (see Software availability )18.\n\n\nResults\n\nThe initial data set comprised 3,338,526 patients. A total of 1,365,458 patients whose records contained fewer than three eGFR tests were excluded, leaving 1,973,068 patients eligible for analysis: 1,921,949 without a urine albumin test on record, 37,947 with normoalbuminuria (<3 mg/mmol), 10,248 with microalbuminuria (3–30 mg/mmol), and 2,924 with macroalbuminuria (>30 mg/mmol). Each of the four cohorts were split into two halves and nominated as training and testing data sets. Due to the computational demands of the statistical method used, we randomly selected a sub-cohort of 50,000 patients to fit the model in the cohort without a urine albumin test on record. Summary statistics of patient characteristics from the four cohorts are presented in Table 1.\n\nSix state continuous time HMMs adjusted for sex, heart failure, cancer, hypertension and diabetes, and annually updated age were fit on the four training data sets. Hypertension and diabetes were subsequently removed from the models as they were unable to predict eGFR stage progression or death. All models converged to their respective maximum likelihood estimates, with positive definitive Hessian matrices permitting confidence interval estimation for all parameters. Intensity, transition and misclassification matrices for these models are given in Supplementary Tables S2–13 (Extended data)14.\n\nFigure 2 shows the annual transition and misclassification probabilities for a woman, aged 60, without heart failure or a previous diagnosis of cancer and with no urine albumin test on record. The figure shows that if kidney function is normal (G1/G2) then the probability of her true kidney function deteriorating to stage G3a in one year is estimated to be 1.1%. The probability that a single eGFR test will be misclassified as G3a is 2.9%, while the probability that it will correspond to her true stage is 97.1%. The probability that this woman dies within a year is estimated to be 0.7%. The probability that her kidney function remains in this category is 98.2%. If the woman is one year older then transition probabilities should be multiplied by 1.08 for kidney function and 1.09 for death. For example, the annual transition probability from stage G3b, is 1.0% for a 60 year old woman, but 1.0 × 1.0810 = 2.16% for a 70 year old woman and × 1.0820 = 4.66% for woman who is 80 years old. Multipliers in which the confidence interval overlapped “no effect” are set to 1.00.\n\nProbabilities are based on a woman aged 60, without heart failure or a previous diagnosis of cancer.\n\nFigure 3 represents annual transitions for a woman with the same characteristics, but who has had her urine albumin tested and found to be in the normoalbuminuric range. Corresponding annual transition probabilities for kidney function are nearly twice that of an equivalent woman without a urine albumin test on record. Respective transition rates to death from each stage are also higher, illustrating that this cohort represents women in poorer health. Misclassification probabilities and transition probability multipliers are broadly similar to Figure 2.\n\nProbabilities are based on a woman aged 60, without heart failure or a previous diagnosis of cancer.\n\nFigure 4 and Figure 5 show results for women with micro- and macroalbuminuria, respectively. Kidney function transition probabilities are higher, as are annual transition probabilities for death. Fewer transition multipliers are significant for these cohorts but this probably reflects the smaller cohort sizes and correspondingly reduced statistical power.\n\nProbabilities are based on a woman aged 60, without heart failure or a previous diagnosis of cancer.\n\nProbabilities are based on a woman aged 60, without heart failure or a previous diagnosis of cancer.\n\nTable 2 shows the results from applying the Viterbi algorithm to the four cohorts. Under-grading of eGFR stage occurs more often than over-grading in all cohorts but over-grading tends to increase for cohorts having urine albumin tests. In total, 12.1% (11.9–12.2%) of all tests done in the unmeasured urine albumin cohort are misclassified, 13.1% (13.0–13.3%) in patients with normoalbuminuria, 14.5% (14.2–14.8%) in patients with microalbuminuria, and 14.7% (14.1–15.3%) in patients with macroalbuminuria.\n\n95% confidence intervals shown in brackets.\n\nMean sojourn time, i.e. the average time spent in each state, decreased with increasing severity of eGFR and albuminuria stage (Table 3). One exception was for macroalbuminuric patients in eGFR stage G5, for whom the mean sojourn time was greater than for microalbuminuric patients in eGFR stage G5. However, few patients were present in the more severe diseases states and the 95% confidence intervals of the two estimates substantially overlap.\n\n95% confidence intervals shown in brackets.\n\n\nDiscussion\n\nWe have developed a statistical model for kidney function monitoring over time, using a large clinical database of longitudinal kidney function measurements from an unselected primary care cohort. This model takes into account that observed kidney function is measured with error and uses statistical methodology to estimate the underlying ‘true’ rate of progression. We stratified our models by albuminuria stage in accordance with the findings of previous studies that showed that urine albumin excretion is a significant risk factor for the progression of CKD and the development of ESRD19–21. Our analyses suggest that kidney function declines more rapidly in men than in women, independent of other risk factors. Existing evidence for differences in the rates of progression between men and women is conflicting3,22,23. Our analysis supports the observations of others, that men are over-represented in the latter stages of CKD24, with our model predicting a slower progression of kidney disease for women in the unmeasured urine albumin and normoalbuminuria cohorts. The fact that women are over-represented at CKD stage 3 may be due to the fact that women tend to live longer than men.\n\nWe estimated the probability of misclassification conditioning on true eGFR stage. A consistent pattern is seen across the different baseline urine albumin levels and by eGFR stage. Our model suggests that on average, change in underlying kidney function is slow with mean sojourn times in stage G3a and G3b being between 15 and 25 years for patients without elevated urine albumin. Given the slow rate of change and the high chance that observed eGFR misclassifies the true eGFR stage, frequent testing of eGFR in these populations will inevitably lead to the detection of more spurious change than real change.\n\nWe assessed whether our models of kidney disease progression would be improved by adjusting for clinical characteristics that were a priori considered to be associated with increased risk, and therefore, faster progression. Our analysis did not support the notion that diabetes, hypertension, peripheral vascular disease, ischaemic heart disease, stroke or transient ischaemic attack are independently associated with deterioration of kidney function once albuminuria stage and updated eGFR are accounted for. We conclude that conditioning on eGFR stage and urine albumin levels, knowledge of diabetes status is less important, but we cannot rule out that our study may be under-powered to detect small but real effects on transition rates.\n\nA major strength of this study is that we have taken a very large and unselected sample of patients from a database that has been shown to be representative of the wider UK population7. Our model for progression takes into account multiple stages of kidney function and the competing risk of death from any cause. We have also employed a method that takes into account that eGFR is observed with error, and simultaneously estimates true underlying eGFR25. This means that we can estimate misclassification probabilities and evaluate the effects of different monitoring strategies. We used a split-sample approach to assess for potential over-fitting and the internal validity of the model.\n\nOur study has a number of limitations. Our data was not collected for the purpose of conducting a study about modelling progression of kidney function. As a consequence, we do not know the reasons tests were conducted, and for many patients, records were incomplete and examination times were irregular. The extent to which this could bias our findings is unclear as it depends on our understanding of the examination scheme used by the doctors. We recognise three potential mechanisms for these tests to occur in a primary care setting. A significant number of creatinine tests will be ‘random’ with respect to the kidney function, because they would have been ordered as part of a routine check-up and not specifically to monitor or diagnose kidney disease. This could be a result of the co-reporting of serum creatinine as part of ‘test batches’ in which other biomarkers would have been of primary interest, or because serum creatinine may have been requested prior to the initiation of a potentially nephrotoxic drug. For some patients, the timing of the next measurement will have been influenced by the current kidney function level. This is likely to have happened if the purpose of the test is to monitor CKD and current clinical guidelines are followed1. This mechanism has been referred to as ‘doctor’s care’ in the literature. The third scenario is when a patient initiates the timing of their test themselves, so called ‘patient self-selection’. Of the three scenarios, we consider the self-selection scenario possible but less likely than the other schemes due to the asymptomatic nature of kidney function loss in all but the end-stages of the disease. Grüger et al.26 showed that estimated transition rates are only biased under the “patient self-selection” examination schemes and transition rate estimates are unbiased if inefficient under doctor’s care scheme. In the case of random timing, the estimates are both efficient and unbiased.\n\nWe attempted to include a state to represent transient and acute loss of kidney function (acute kidney injury) as this is a contributing factor to CKD, but the addition of this non-absorbing state with pathways back to each state resulted in over-parametrisation of the model. Furthermore, data on urine albumin, body mass index and ethnicity is missing in a large number of patients in CPRD. To overcome this, we created a sub-group of patients in whom urine albumin was not recorded. The omission of ethnicity in this model is a limitation as kidney function decline is considered to differ between ethnic groups. We were not able to adjust our models for ethnicity, as historically, ethnicity has been poorly recorded in CPRD.\n\nIt is likely that once a patient’s kidney function has been observed in stage 4 or 5, they are referred to specialist care, with subsequent kidney function testing occurring outside the CPRD database. Hence, these patients’ records are missing from our study, which potentially explains why transition rates slow down rather than increase, as might be expected. In a study of electronic health records data from Pennsylvania, a similar model was fit to eGFR records, and reported that transition probabilities between kidney function stages generally increased as stage increased for all but stage 325. Even so, our model calibrates well with reports of progression to ESRD from different stages. For example, Tangri et al.27 reported that three from 2,014 people with CKD stage 3 at baseline progressed to ESRD after three years of follow-up. Assuming this population contained an equal proportion of people with CKD stage 3a and 3b, then our model, based on the unmeasured urine albumin cohort, would predict that just one person would reach stage 5 after three years. Using the model for patients with normoalbuminuria, it would be three people. From the same study, 22 of 826 people progressed from stage 4 at baseline to kidney failure after three years. Our models predict 25 people with unmeasured urine albumin and 46 people with normoalbuminuria would reach stage 4. In a study reporting on sex differences in CKD progression, the rate of ESRD per 100 person-years was 3.1 in women and 3.8 in men. Based on our model for patients with normoalbuminuria our equivalent estimates are 1.9 and 2.3, but 2.07 and 2.13 for patients with microalbuminuria and 3.0 and 3.2 for patients with macroalbuminuria. Our study shows that kidney function deteriorates slowly in most patients with average sojourn times in decades rather than years. Whilst eGFR is widely used to measure kidney function we estimate that the potential for misclassification is large and clinically relevant, with implications for monitoring for rapid kidney function loss or pharmacovigilance. For example, of 1,741 people with CKD stage 3 recruited for a study from 32 primary care practices in the UK28, 496 were in remission at baseline (although qualifying at the recruitment stage) and of these, 157 were back to CKD stage 3 at one year, with a further 132 returning to stage 3 CKD by five years. This type of pattern is consistent with our model, in which underlying kidney function only deteriorates but is observed with error. If our model is correct, then it is clear to see how monitoring CKD periodically will confuse and might lead to inappropriate action.\n\n\nConclusions\n\nWe have developed a model to predict decline in kidney function and used it to assess different monitoring strategies and screening programmes. The model takes into account stage progression and test error, which were recently identified as important for future economic evaluations of CKD testing29. Future work in this field could look to validate this model in another primary care population, ideally one in which patients are followed throughout including stages 4 and 5.\n\n\nData availability\n\nThe data used in this study are not publicly available and were obtained under licence. The terms of this license do not permit us to share the data. However, those wishing to replicate our analysis in this database can apply directly to the Medicines and Healthcare Products Regulatory Agency (MHRA) for access to the CPRD, at enquiries@cprd.com. The conditions under which the MHRA will grant access are beyond our control, but are explained at https://www.cprd.com/research-applications.\n\nFigshare: Statistical models for the deterioration of kidney function in a primary care population: A retrospective database analysis (Extended Data). https://doi.org/10.6084/m9.figshare.9741611.v114.\n\nThis project contains the following extended data:\n\nExtended Data.pdf (document containing Tables S1–20 and Figures S1–5)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nSoftware availability\n\nSource code available from: https://github.com/OxPrimaryCareStats/egfr-decline/tree/v1.0.0\n\nArchived source code at time of publication: https://doi.org/10.5281/zenodo.337711318\n\nLicense: MIT License", "appendix": "Acknowledgements\n\nWe would like to thank Alice Fuller and Dr Sarah Lay-Flurrie for their hard work in providing much of the initial data management for this project.\n\n\nReferences\n\nNational Institute for Health and Care Excellence: Chronic kidney disease in adults: assessment and management: Clinical guideline [CG182]. Technical report, National Institute for Health and Care Excellence, 10 Spring Gardens, London, SW1A 2BU. 2014. Reference Source\n\nWeiner DE, Tighiouart H, Amin MG, et al.: Chronic kidney disease as a risk factor for cardiovascular disease and all-cause mortality: a pooled analysis of community-based studies. J Am Soc Nephrol. 2004; 15(5): 1307–15. PubMed Abstract \| Publisher Full Text\n\nEriksen BO, Ingebretsen OC: The progression of chronic kidney disease: a 10-year population-based study of the effects of gender and age. Kidney International. 2006; 69(2): 375–382. PubMed Abstract \| Publisher Full Text\n\nLamb E, Brettell EA, Cockwell P, et al.: The eGFR-C study: accuracy of glomerular filtration rate (GFR) estimation using creatinine and cystatin C and albuminuria for monitoring disease progression in patients with stage 3 chronic kidney disease--prospective longitudinal study in a multiethnic population. BMC Nephrol. 2014; 15: 13. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSpence D: Bad medicine: chronic kidney disease. BMJ. 2010; 340: c3188. PubMed Abstract \| Publisher Full Text\n\nFink H, Ishani A, Taylor B, et al.: Screening for, monitoring, and treatment of chronic kidney disease stages 1 to 3: a systematic review for the U.S. Preventive Services Task Force and for an American College of Physicians Clinical Practice Guideline. Ann Intern Med. 2012; 156(8): 570–581. PubMed Abstract \| Publisher Full Text\n\nHerrett E, Gallagher AM, Bhaskaran K, et al.: Data resource profile: Clinical Practice Research Datalink (CPRD). Int J Epidemiol. 2015; 44(3): 827–836. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNational Kidney Foundation: K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis. 2002; 39(2 Suppl 1): S1–266. PubMed Abstract\n\nBaum L, Petrie T: Statistical Inference for Probabilistic Functions of Finite State Markov Chains. Ann Math Stat. 1966; 37(6): 1554–1563. Publisher Full Text\n\nBaum L, Eagon J: An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology. Bull Am Math Soc. 1967; 73(3): 360–363. Publisher Full Text\n\nBaum L, Sell G: Growth transformations for functions on manifolds. Pac J Math. 1968; 27(2): 211–227. Publisher Full Text\n\nBaum L, Petrie T, Soules G, et al.: A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains. Ann Math Stat. 1970; 41(1): 164–171. Publisher Full Text\n\nBaum L: An inequality and associated maximization technique in statistical estimation of probabilistic functions of a markov process. Inequalities. 1972; 3: 1–8. Reference Source\n\nOke JL, Feakins B, Schlackow I, et al.: Statistical models for the deterioration of kidney function in a primary care population: A retrospective database analysis (Extended Data). 2019; 8. http://www.doi.org/10.6084/m9.figshare.9741611.v1\n\nViterbi A: Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Trans Inf Theory. 1967; 13(2): 260–269. Publisher Full Text\n\nR Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2019. Reference Source\n\nJackson CH: Multi-state models for panel data: The msm package for R. J Stat Softw. 2011; 38(8): 1–29. Publisher Full Text\n\nFeakster: Oxprimarycarestats/egfr-decline: Initial release. 2019. http://www.doi.org/10.5281/zenodo.3377113\n\nChang WX, Arai S, Tamura Y, et al.: Time-dependent risk factors associated with the decline of estimated GFR in CKD patients. Clin Exp Nephrol. 2016; 20(1): 58–70. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nInaguma D, Imai E, Takeuchi A, et al.: Risk factors for CKD progression in Japanese patients: findings from the Chronic Kidney Disease Japan Cohort (CKD-JAC) study. Clin Exp Nephrol. 2017; 21(3): 446–456. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCoresh J, Heerspink HJL, Sang Y, et al.: Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies. Lancet Diabetes Endocrinol. 2019; 7(2): 115–127. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRicardo AC, Yang W, Sha D, et al.: Sex-Related Disparities in CKD Progression. J Am Soc Nephrol. 2019; 30(1): 137–146. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNeugarten J, Acharya A, Silbiger SR: Effect of gender on the progression of nondiabetic renal disease: a meta-analysis. J Am Soc Nephrol. 2000; 11(2): 319–329. PubMed Abstract\n\nGlassock R, Winearls C: Screening for CKD with eGFR: doubts and dangers. Clin J Am Soc Nephrol. 2008; 3(5): 1563–1568. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLuo L, Small D, Stewart WF, et al.: Methods for estimating kidney disease stage transition probabilities using electronic medical records. EGEMS (Wash DC). 2013; 1(3): 1040. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGrüger J, Kay R, Schumacher M: The validity of inferences based on incomplete observations in disease state models. Biometrics. 1991; 47(2): 595–605. PubMed Abstract \| Publisher Full Text\n\nTangri N, Inker LA, Hiebert B, et al.: A Dynamic Predictive Model for Progression of CKD. Am J Kidney Dis. 2017; 69(4): 514–520. PubMed Abstract \| Publisher Full Text\n\nShardlow A, McIntyre NJ, Fluck RJ, et al.: Chronic Kidney Disease in Primary Care: Outcomes after Five Years in a Prospective Cohort Study. PLoS Med. 2016; 13(9): e1002128. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSutton AJ, Breheny K, Deeks J, et al.: Methods Used in Economic Evaluations of Chronic Kidney Disease Testing - A Systematic Review. PLoS One. 2015; 10(10): e0140063. PubMed Abstract \| Publisher Full Text \| Free Full Text" }	[ { "id": "53695", "date": "11 Sep 2019", "name": "Dorothea Nitsch", "expertise": [ "Reviewer Expertise Renal epidemiology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors used CPRD records to inform a multistate model on progression of kidney disease. They appropriately considered that there could be measurement error and allowed for this to some extent.\n\nThey used outcome variables that have not been validated for incident analyses in CPRD(dialysis/transplantation).\nThe underlying model for 'true' but unobserved kidney disease assumed that kidney disease could only get worse over time but not better - but this is not supported by actual data which suggest that transient decreases can improve over time and may not necessarily need to be permanent (though such changes may be a risk marker for later decline). Here the authors should discuss more about the chronicity assumption within the CKD definition and how they parametrised this in their data.\nThen there was a model for measurement error, but this seems to be a static model, i.e. assuming that measurement error does not vary over time - did I understand this correctly? Because over time in the UK the way creatinine gets measured and reported has changed dramatically during the study period. This change in reporting of calibrated creatinines in effect hides progression over time when crude analyses are used as different labs shifted to calibration and reporting of creatinine to IDMS at different points in time - thereby shifting the entire creatinine distribution down by 5% over the years prior to 2014 (i.e. hiding a decrease in kidney function over time).\nDid the authors recalculate eGFR from the creatinines (which then requires some thought about time-dependent measurement error which varies by lab and time) - or use reported eGFRs (which then means they lost a lot of measurements based on thresholds with informative missingness as eGFR does not get reported uniformly - some labs only report values in a range of >15 and <60, others report up to 90ml/min/1.73m2)? Dependent on whether the authors used creatinine or eGFR they have discussed further biases in their design and explicitly allow for such biases in their model.\nThen there is the overall study design which is a somewhat odd cohort as it is dependent on having three or more eGFR (or creatinine?) tests and that is not representative of the general population - the survey and CPRD validated prevalence of reduced eGFR in the UK population is about 6% and here the numbers are much higher (3-7 fold depending on albuminuria category) simply because these represent an enriched sample as GPs had a reason to test more than once but indeed three times. Does this enriched sample really represent 'a model for kidney disease progression'? The authors should discuss this and whether people who should have been tested but weren't tested may be a high risk group. The sample here represents a group of patients who engage with the health service but the people who progress in truth may be not fully captured. This needs to be discussed more.\nThere were real financial reasons for testing e.g. annual testing for diabetes (started in 2004), and less so for other illnesses, but risk factors for CKD determine testing rates and especially repeat testing as reported by the UK National CKD Audit, and there is some understanding from this audit how testing schemes are carried out. So I would disagree with \"A major strength of this study is that we have taken a very large and unselected sample of patients from a database that has been shown to be representative of the wider UK population\" as stated in the discussion - this is a selected sample and not representative of what happens overall in terms of kidney function decline as not all are tested the same way. I would have stratified by underlying comorbidity and not simply adjusted for it.\nI totally agree with the authors about the selective loss to follow-up with loss of people who are managed by other specialities including renal in secondary care.\n\nOverall this is an interesting analysis, but more work is needed to convince me that this model should be used for economic modelling.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8572", "date": "22 Aug 2022", "name": "Benjamin Feakins", "role": "Author Response", "response": "Reviewer: They used outcome variables that have not been validated for incident analyses in CPRD (dialysis/transplantation). Authors: We did not model or attempt to estimate the incidence of dialysis or transplantation. We have included patients who would be candidate for dialysis or transplantation (patients with stage 4/5 CKD), but we censored patients at the first code relating to dialysis or transplantation from hospital or GP records. Moreover, we excluded patients with history of renal replacement therapy. It is unlikely that a significant number of patients would have received either dialysis or renal replacement therapy without there being a code to identify it in the data. Reviewer: The underlying model for 'true' but unobserved kidney disease assumed that kidney disease could only get worse over time but not better - but this is not supported by actual data which suggest that transient decreases can improve over time and may not necessarily need to be permanent (though such changes may be a risk marker for later decline). Here the authors should discuss more about the chronicity assumption within the CKD definition and how they parametrised this in their data. Authors: It is true that kidney function, albeit measured by an imperfect test (e.g., eGFR) has been observed to improve and whilst this might be true, observed improvements in kidney function could also be as a result of measurement error or intervention. For simplicity, and with the agreement of the clinicians on the paper (DL and CO’C), we thought the unidirectional model for true underlying kidney function to be biologically plausible. We did perform a sensitivity analysis in which we allowed underlying kidney function to spontaneously (without intervention) improve. We concluded that this model did not fit the data as well as the progression only model. We have added the following text to the eighth paragraph of the Discussion section: “The assumption that true underlying kidney function only deteriorates with age is a fundamental part of the model and further research could investigate alternative models for underlying kidney progression and their impact monitoring recommendations.” Reviewer: Then there was a model for measurement error, but this seems to be a static model, i.e. assuming that measurement error does not vary over time - did I understand this correctly? Because over time in the UK the way creatinine gets measured and reported has changed dramatically during the study period. This change in reporting of calibrated creatinines in effect hides progression over time when crude analyses are used as different labs shifted to calibration and reporting of creatinine to IDMS at different points in time - thereby shifting the entire creatinine distribution down by 5% over the years prior to 2014 (i.e. hiding a decrease in kidney function over time). Authors: This is a valid point, relating to a problem we have encountered in routine health record data sets. However, we feel that this issue is likely to have minimal impact to our study, as apart from the last 3.25 years, our data pre-dates the use of IDMS as the changes took place in 2010. Furthermore, we conducted this study in an open cohort (CRPD-Vision) that has been decreasing in size (https://doi.org/10.1136/bmjopen-2017-020738), further attenuating the pool of potentially affected tests. Reviewer: Did the authors recalculate eGFR from the creatinines (which then requires some thought about time-dependent measurement error which varies by lab and time) - or use reported eGFRs (which then means they lost a lot of measurements based on thresholds with informative missingness as eGFR does not get reported uniformly - some labs only report values in a range of >15 and <60, others report up to 90ml/min/1.73m2)? Dependent on whether the authors used creatinine or eGFR they have discussed further biases in their design and explicitly allow for such biases in their model. Authors: In this study, we used all testing sources available to obtain eGFR, including pre-derived eGFR values. Unfortunately, the data source used provides no information on the techniques used to measure serum creatinine levels or to estimate eGFR. We also no longer have access to this data. Hence, we cannot say whether the calculation of a particular eGFR value was performed using laboratory methods or via an estimating equation in a GP practice. However, we estimated the overwhelming majority of eGFR values from raw serum creatinine values. Hence, any bias present from the use of pre-derived eGFR values is likely to be minimal. The method we used to calculate eGFR from serum creatinine was the CKD-EPI equation. We are aware that better method for the calculation of eGFR exist, however, the one we used would have been the one predominantly in use in UK clinical practice throughout the study period. Reviewer: Then there is the overall study design which is a somewhat odd cohort as it is dependent on having three or more eGFR (or creatinine?) tests and that is not representative of the general population - the survey and CPRD validated prevalence of reduced eGFR in the UK population is about 6% and here the numbers are much higher (3-7 fold depending on albuminuria category) simply because these represent an enriched sample as GPs had a reason to test more than once but indeed three times. Does this enriched sample really represent 'a model for kidney disease progression'? The authors should discuss this and whether people who should have been tested but weren't tested may be a high risk group. The sample here represents a group of patients who engage with the health service but the people who progress in truth may be not fully captured. This needs to be discussed more. Authors: The requirement of three serum creatinine tests was imposed to establish a reliable baseline eGFR status (requiring two tests) and to estimate change over time. We concede that the population present in this sample is not representative of a general UK population so much as a UK general practice population, and we have amended the wording of the fourth paragraph of the Discussion section of the manuscript to reflect this. This reads: “Inclusion into the study was conditional upon having three or more serum creatinine measurements, but creatinine is commonly measured in UK general and not necessarily for the purpose of monitoring kidney function or diagnosing kidney disease.” … and later in the eighth paragraph of the Discussion section: “Our study design means that we would also miss patients with ESRD who had not engaged in primary care.” The degree to which this could bias our results is open to some conjecture, and we have also made such comments in the Discussion section of the manuscript. Furthermore, others [Gruger J et al., 1991] who have studied the underlying mechanisms for requesting kidney function testing have concluded that the only mechanism by which testing may bias estimates of transition rates is that of patient-driven testing, which we feel is possible, but unlikely. Reviewer: There were real financial reasons for testing e.g. annual testing for diabetes (started in 2004), and less so for other illnesses, but risk factors for CKD determine testing rates and especially repeat testing as reported by the UK National CKD Audit, and there is some understanding from this audit how testing schemes are carried out. So I would disagree with \"A major strength of this study is that we have taken a very large and unselected sample of patients from a database that has been shown to be representative of the wider UK population\" as stated in the discussion – this is a selected sample and not representative of what happens overall in terms of kidney function decline as not all are tested the same way. I would have stratified by underlying comorbidity and not simply adjusted for it. Authors: When we wrote the section of text in question, we were referring to the non-selected nature of any one individual appearing in the dataset, i.e., their presence was only determined through virtue of their general practice opting into the database. However, as per our previous response, the population used in this study is still representative of a GP patient cohort, which is the setting in which we anticipate these results to be generalised. We have endeavoured to ensure that our study population was as non-specific as possible, but he nature of our study meant that patients needed to have creatinine measures present in their medical history for us to draw any kind of inference on their kidney function decline. We would also add that, contrary to the reviewer’s comments, we have stratified our analysis by the factors most important in determining the rate of kidney function decline, being the initial albuminuria stage. This is in line with the findings of other studies in this area [Chang WX et al., 2016; Inaguma D et al., 2017; Coresh J et al., 2019]." } ] }, { "id": "69718", "date": "28 Aug 2020", "name": "Lawrence Hunsicker", "expertise": [ "Reviewer Expertise Nephrology", "Epidemiology", "Statistics", "Clinical trial design", "performance", "and analysis." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors of this manuscript report on the long-term rate of progression of chronic kidney disease (CKD) in a very large cohort of UK general practice patients followed as part of the Clinical Practice Research Datalink in the time between 1 April 2005 and 31 March 2014. Progression of kidney disease over each patient's course was assessed as the rate of progression from one stage to the next across the six currently standard KDOQI/KDIGO \"stages\" of renal insufficiency (Stages 1, 2, 3a, 3b, 4, and 5), which are defined by ranges of estimated glomerular filtration rate (eGFR). The rate of progression from one stage to the next was modeled as a Hidden Markov Model, which assumes that subjects are at \"true\" eGFR stages at each evaluation point, but that these stages may be misclassified based on random error of the eGFR estimate, so that the \"observed\" transitions may be misidentified. The overall conclusions of the authors are: a) that progression of renal disease to renal failure occurs quite slowly in general, with only a small fraction of patients that progress to kidney failure, and b) that progression of kidney disease as evidenced by [exclusive] use of progression in the KDOQI/KDIGO Stage of CKD, though generally reflective of the average course of kidney disease in the community, is associated with significant error when applied to an individual. Though the authors don't say this, the implication is that use of their analysis may not be very helpful in establishing guidelines as to in whom, and at what repeated intervals, eGFR determinations would be cost effective.\nThe major strength of this study is the almost unique test bed offered by access to the data of almost 2,000,000 UK qualified general practice patients from Clinical Practice Research Datalink with \"up-to-standard\" data collection. Given the choice of analytic method, the authors' analysis is technically entirely competent. The assumptions and methods are well described. The results are clearly explained and put in appropriate context in the Discussion Section. The major limitation of the available data is that patients with the more advanced Stages of kidney disease are likely to have been referred to specialist providers, so that data on the more advanced stages of kidney disease, where progression is generally both more rapid and more clinically important, are more limited and more susceptible to bias. The authors clearly acknowledge this. Further, the issue addressed by this manuscript is potentially important, at least from a health economics point of view. Current policy recommendations uniformly encourage periodic assessment of renal function \"in people with, or at risk of, chronic kidney disease (CKD).\" But as noted above, in general kidney disease progresses quite slowly and only a small minority of subjects even with documented kidney disease ever progress to chronic renal failure. There is almost no empirical data upon which to make any data-based recommendation about in whom or how often the \"periodic assessments\" should be done.\n\nBut the choice of analytic method is subject to criticism. The continuous variable eGFR may range from over 100 (mL/min/1.73 M2) to close to 0. The reduction of this range of values to a classification with 6 levels is associated with massive information loss. Markov models deal with chances of transition from one state to another, and all members of one state are considered to be interchangeable, so that a patient with an eGFR of 100 (at Stage 1/2 with the combination of these two stages) is treated as equivalent to one with an eGFR of 62. But surely the chance of progression from an eGFR of 100 to an eGFR < 60 (Stage 3a) is much lower than the chances of progression from a value of 62 to < 60 . Similarly, it is intuitively likely (though not at all certain) that a subject with a history of rapid loss of eGFR in the past will have more rapid progression in the future. But with a Markov model, all history is lost, and only the current stage, and not the prior history is taken into account. Given the huge amount of information available for this analysis, the inefficiency of the hidden Markov model may be overcome in the analysis of the overall community estimates of rate of progression. But these results will be of almost no use in prediction of the progression of kidney disease in the individual patient. And it is the individual patient's progress, not the average rate of progression in the community, that we are trying to clarify in recommending individual testing eGFR and setting repeat testing intervals.\n\nAn alternative approach would have been to use a hierarchical (\"mixed\") analytic method (or perhaps even better, joint analysis combining the hierarchical analysis with a time to event analysis for ESRD and death) to evaluate the overall community rate of progression while estimating the distribution of individual rates of progression. Mixed models deal automatically with the problem that eGFR is measured with error (whether due to variability of the underlying \"true\" GFR, error due to the misestimation of GFR by eGFR -- up to 35% CKD Stage misclassification using the CKD-Epi formula: Levey et al. (2009)1, error due to the underlying determination of serum creatinine (Scr) which is increased at low levels of Scr because of its inverse relationship with eGFR, or variability in timing of the underlying measurements of serum creatinine). Mixed methods also permit specification of alternative models of change over time, permitting exploration of the hypotheses that progression is not linear. They would also facilitate development of time dependent models, allowing input of changes to patient's diabetes, hypertension, and cancer status over time, rather than limiting those variables to the baseline analysis. Most important, this sort of analysis might permit identification of the subset of individuals for whom the risk of progression is the highest -- that might be most benefited by careful follow-up of eGFR, and might give better guidance as to cost-effective testing intervals.\nThe authors' choice of analytic methods in this analysis should be put into perspective. The authors were evidently motivated to undertake this analysis so that cost-effectiveness studies could be done specifically in terms of the KDOQI/KDIGO CKD staging mechanism -- presumably to make it easier to develop easily followed guidelines for testing frequency. (See the authors' comment and reference 29 in their final Conclusion.) If the authors felt constrained by these requirements, they have performed a reasonable, if inefficient, analysis. But they and the authors of reference 29 might have done better to request and perform a more efficient analysis using the underlying eGFR data rather than the derived CKD Stages to develop their model, and then abstracted stage specific recommendations from the more efficient model, rather than the other way around.\n\nIn sum, the analysis as performed using the specified analytic model was competently done, and the overall conclusions are justified - that the rate of progression of renal insufficiency is slow on average, and that dependence on this model would be associated with potentially significant error. But these limited conclusions don't exclude the possibility that more clinically reliable and useful data might be obtained by use of a method that didn't throw away so much of the available data.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8573", "date": "22 Aug 2022", "name": "Benjamin Feakins", "role": "Author Response", "response": "Reviewer: The authors of this manuscript report on the long-term rate of progression of chronic kidney disease (CKD) in a very large cohort of UK general practice patients followed as part of the Clinical Practice Research Datalink in the time between 1 April 2005 and 31 March 2014. Progression of kidney disease over each patient's course was assessed as the rate of progression from one stage to the next across the six currently standard KDOQI/KDIGO \"stages\" of renal insufficiency (Stages 1, 2, 3a, 3b, 4, and 5), which are defined by ranges of estimated glomerular filtration rate (eGFR). The rate of progression from one stage to the next was modeled as a Hidden Markov Model, which assumes that subjects are at \"true\" eGFR stages at each evaluation point, but that these stages may be misclassified based on random error of the eGFR estimate, so that the \"observed\" transitions may be misidentified. The overall conclusions of the authors are: a) that progression of renal disease to renal failure occurs quite slowly in general, with only a small fraction of patients that progress to kidney failure, and b) that progression of kidney disease as evidenced by [exclusive] use of progression in the KDOQI/KDIGO Stage of CKD, though generally reflective of the average course of kidney disease in the community, is associated with significant error when applied to an individual. Though the authors don't say this, the implication is that use of their analysis may not be very helpful in establishing guidelines as to in whom, and at what repeated intervals, eGFR determinations would be cost effective. Authors: We disagree. We believe our model (unlike others that assume the observed eGFR is equal to true eGFR) permits analysis that correctly considers the misclassification that commonly occurs when monitoring kidney function using estimated GFR. This is important because when a person is misclassified into a higher stage treatment may represent a cost but provide less benefit than expected and in the opposite scenario a misclassification into a lower stage (false negative) would not incur costs from direct treatment but would render the patient at a higher risk for longer. Attempts to model the cost-effectiveness of monitoring without taking this into account are potentially misleading. The work presented in this manuscript formed part of a wider research project, which is intended to assess the cost effectiveness of kidney function monitoring. The health economics study using the outputs from this paper can be found at https://doi.org/10.1371/journal.pmed.1003478. The Health and Technology Assessment programme this work feeds into can be found at https://www.journalslibrary.nihr.ac.uk/programmes/pgfar/RP-PG-1210-12003. Reviewer: The major strength of this study is the almost unique test bed offered by access to the data of almost 2,000,000 UK qualified general practice patients from Clinical Practice Research Datalink with \"up-to-standard\" data collection. Given the choice of analytic method, the authors' analysis is technically entirely competent. The assumptions and methods are well described. The results are clearly explained and put in appropriate context in the Discussion Section. The major limitation of the available data is that patients with the more advanced Stages of kidney disease are likely to have been referred to specialist providers, so that data on the more advanced stages of kidney disease, where progression is generally both more rapid and more clinically important, are more limited and more susceptible to bias. The authors clearly acknowledge this. Further, the issue addressed by this manuscript is potentially important, at least from a health economics point of view. Current policy recommendations uniformly encourage periodic assessment of renal function \"in people with, or at risk of, chronic kidney disease (CKD).\" But as noted above, in general kidney disease progresses quite slowly and only a small minority of subjects even with documented kidney disease ever progress to chronic renal failure. There is almost no empirical data upon which to make any data-based recommendation about in whom or how often the \"periodic assessments\" should be done. Authors: We would like that thank the Reviewer for the very positive comments and we agree that patients with more advanced stages of kidney disease might have been referred to specialist care. We would like to emphasise that the main aim of this study was estimate the rate of progression of kidney function decline before they enter end-stage renal disease, requiring specialist care. Therefore, there is a plethora of data, on which to make data-based recommendations regarding the frequency of periodic assessments. Tables S17–20 show that where such recommendations have been made, these have ‘only’ been for patients in eGFR stages G3a and G3b. Patients in these stages are still monitored within primary care, as opposed to specialist care. Moreover, as general practices are financially incentivised by the Quality and Outcomes Framework (QOF) to monitor such patients, there is no shortage of data for these patients as demonstrated in Table 1. Furthermore, it’s also worth noting that Table 1 represents the baseline values for patients from an open cohort spanning the years 2005–2014. During this time, there were two substantial changes to QOF that increased the frequency of serum creatinine and proteinuria testing—one in 2006 and another in 2009. The effect of these changes can be seen in Figure 3. This figure shows that serum creatinine testing increased in subjects with CKD stages ≥2 from 2005 to 2008, where it reached a new plateau, and proteinuria testing increased in subjects with CKD stages ≥4 from 2008 to 2010, where it too reached a new plateau. A significant number of patients would have entered our study cohort prior to these dates, making Table 1 a poor reflection of the general quality of the testing data https://doi.org/10.1136/bmjopen-2018-028062. This figure shows that serum creatinine testing increased in subjects with CKD stages ≥ 2 from 2005 to 2008, where it reached a new plateau, and proteinuria testing increased in subjects with CKD stages ≥ 4 from 2008 to 2010, where it too reached a new plateau. A significant number of patients would have entered our study cohort prior to these dates, making Table 1 a poor reflection of the general quality of the testing data. Reviewer: But the choice of analytic method is subject to criticism. The continuous variable eGFR may range from over 100 (mL/min/1.73 m2) to close to 0. The reduction of this range of values to a classification with 6 levels is associated with massive information loss. Markov models deal with chances of transition from one state to another, and all members of one state are considered to be interchangeable, so that a patient with an eGFR of 100 (at Stage 1/2 with the combination of these two stages) is treated as equivalent to one with an eGFR of 62. But surely the chance of progression from an eGFR of 100 to an eGFR < 60 (Stage 3a) is much lower than the chances of progression from a value of 62 to < 60. Similarly, it is intuitively likely (though not at all certain) that a subject with a history of rapid loss of eGFR in the past will have more rapid progression in the future. But with a Markov model, all history is lost, and only the current stage, and not the prior history is taken into account. Given the huge amount of information available for this analysis, the inefficiency of the hidden Markov model may be overcome in the analysis of the overall community estimates of rate of progression. But these results will be of almost no use in prediction of the progression of kidney disease in the individual patient. And it is the individual patient's progress, not the average rate of progression in the community, that we are trying to clarify in recommending individual testing eGFR and setting repeat testing intervals. Authors: The Reviewer is correct in stating that the Markov assumption means that each subject’s transition to a more severe eGFR stage depends only upon their current stage. We agree that this assumption may be an oversimplification of reality, as it would be likely that an individual who has progressed rapidly through previous stages will continue to do so, and vice versa. As for the reviewers point about likelihood of progression being different if eGFR was 100 vs 62 ml/min/1.73m2, we do not disagree that progression to a next stage would be different, but we would emphasise the problem of knowing what true eGFR is. For example, someone in whom true eGFR is 80 ml/min/1.73m2, their observed eGFR could be anywhere between 70 and 90 ml/min/1.73m2. So, by categorising eGFR into six levels there is some loss in information, but we have a more robust inference. We strongly disagree that these models will be almost of no use. Our models provide average progression times conditional on eGFR stage and presence of albuminuria, and other co-morbidities, e.g., heart failure. The same problem would exist for mixed effect models in as much as you can only provide aggregated rates of decline. We have added the following paragraph to the Discussion section: “We could be criticised for using an approach that categorises kidney function rather than a method that models continuous eGFR, such as generalised linear mixed models. This is because categorisation can lead to loss of information and reduced statistical power. However, such information loss is typically small when the number of categories is large [Altman D and Royston P, 2006], as was the case in our study. Furthermore, the use of categories that naturally aligned with clinically meaningful eGFR stages added to the interpretability of our findings. In addition, HMMs assume that all individuals within a state are interchangeable, and that the chance of progression to subsequent states depends only on the current state. This assumption may not hold if a patient whose kidney function has previously rapidly declined continues along this trajectory. To mitigate this, we have included updated risk factor information in our model and stratified by baseline albuminuria status. Further research could include assessing the impact of the Markov assumption on predicting kidney function decline using HMMs.” Reviewer: An alternative approach would have been to use a hierarchical (\"mixed\") analytic method (or perhaps even better, joint analysis combining the hierarchical analysis with a time to event analysis for ESRD and death) to evaluate the overall community rate of progression while estimating the distribution of individual rates of progression. Mixed models deal automatically with the problem that eGFR is measured with error (whether due to variability of the underlying \"true\" GFR, error due to the misestimation of GFR by eGFR -- up to 35% CKD Stage misclassification using the CKD-Epi formula: Levey et al. (2009)1, error due to the underlying determination of serum creatinine (Scr) which is increased at low levels of Scr because of its inverse relationship with eGFR, or variability in timing of the underlying measurements of serum creatinine). Mixed methods also permit specification of alternative models of change over time, permitting exploration of the hypotheses that progression is not linear. They would also facilitate development of time dependent models, allowing input of changes to patient's diabetes, hypertension, and cancer status over time, rather than limiting those variables to the baseline analysis. Most important, this sort of analysis might permit identification of the subset of individuals for whom the risk of progression is the highest -- that might be most benefited by careful follow-up of eGFR and might give better guidance as to cost-effective testing intervals. Authors: The reviewer is correct, there are alternative statistical models to the approach we led with in this paper. Our initial intention was to model eGFR (or log eGFR) using mixed effect models, but we decided against it for two reasons: the trajectories of eGFR are not linear or necessarily even monotonic in time; more flexible modelling is limited by the fact that for many people only a few eGFR measurements existed in their health record. The models that we did fit did not meet the assumptions of normality implicit in the random effects approach and this, we believe, led to poor predictive performance of these models. It is possible that in an alternative data set, it would be possible to fit these models, but this was not our experience using routinely collected GP data. We would like to stress that we used updated covariates in all the HMMs used in this study and did not condition on only the baseline values of these. Reviewer: The authors' choice of analytic methods in this analysis should be put into perspective. The authors were evidently motivated to undertake this analysis so that cost-effectiveness studies could be done specifically in terms of the KDOQI/KDIGO CKD staging mechanism -- presumably to make it easier to develop easily followed guidelines for testing frequency. (See the authors' comment and reference 29 in their final Conclusion.) If the authors felt constrained by these requirements, they have performed a reasonable, if inefficient, analysis. But they and the authors of reference 29 might have done better to request and perform a more efficient analysis using the underlying eGFR data rather than the derived CKD Stages to develop their model, and then abstracted stage specific recommendations from the more efficient model, rather than the other way around. Authors: The reviewer is not entirely correct. This model was one part of a larger funded project which included a cost-effectiveness study using the outputs from this model, but it is not true that we felt or were constrained by this. Our initial plan was to model eGFR as a continuous measure, but we did not for reasons explained in the previous response. We feel the objective of our work is quite the opposite to the reviewer and we would prioritise models than fit clinical practice over and above statistical efficiency. Reviewer: In sum, the analysis as performed using the specified analytic model was competently done, and the overall conclusions are justified - that the rate of progression of renal insufficiency is slow on average, and that dependence on this model would be associated with potentially significant error. But these limited conclusions don't exclude the possibility that more clinically reliable and useful data might be obtained by use of a method that didn't throw away so much of the available data. Authors: We disagree with the assertion made by the reviewer that our method “threw so much of the data away”. We agree that categorisation can result in loss of information, but this is most likely to occur when continuous measures are split in two (dichotomisation) and applied to small data sets. The thresholds for categorisation should also not be defined post-hoc. Neither of these are true in our case. To cite Altman and Royston “using multiple categories (to create an “ordinal” variable) is generally preferable to dichotomising. With four or five groups the loss of information can be quite small, but there are complexities in analysis” (see https://doi.org/10.1136/bmj.332.7549.1080). Moreover, we have provided calibration plots in Figures S1–4 that demonstrate the accuracy of the predictions made by the models." } ] } ]	1	https://f1000research.com/articles/8-1618
https://f1000research.com/articles/11-366/v1	30 Mar 22	{ "type": "Research Article", "title": "Mapping accessibility to oral health care in coastal India – A geospatial approach using a geographic information system (GIS)", "authors": [ "Prajna Pramod Nayak", "Soham Mitra", "Jagadeesha B. Pai", "Ramprasad Vasthare Prabhakar", "Nandita Kshetrimayum", "Prajna Pramod Nayak", "Soham Mitra", "Ramprasad Vasthare Prabhakar", "Nandita Kshetrimayum" ], "abstract": "Background: It is imperative to have a thorough assessment of the existing distribution of oral healthcare facilities and understand potential accessibility when planning for expansion of oral health services. In the present study, an attempt to measure geographic accessibility to oral healthcare, by locating the availability of dental practitioners in the coastal districts of Karnataka state, India using a geographical information system (GIS), has been made. Methods: For the study, data on public and private oral health centres were collected for the three coastal districts of Karnataka state, India. Population and income data were collected, along with geographic attributes (latitudes and longitudes) of the practitioners' addresses. Descriptive statistical analyses and dentist-to-population ratios (D:P) were calculated. Correlation between the number of clinics with population and D:P with per capita income were analyzed using Pearson's correlation coefficient. Chi-square test applied to analyze any association between D:P and urbanization. Results: Among 340 clinics, 8.5% are public and 91.5% are private clinics catering to a population of 4,704,179. Average D:P for the three coastal districts is 1:13,836. There is an uneven urban-rural distribution of dentists with lower D:P in rural areas. Rural population in four taluks have only one dentist for over a lakh population. Six taluks have only one dentist for every 50000 – 100000 population in rural areas. Six rural areas had only public centers to cater to their oral health.\n\nConclusions: From the study, it is concluded that oral health services were concentrated in areas with higher annual income per-capita, increased urbanization and population density.", "keywords": [ "Geographic Information Systems", "spatial analysis", "geographic accessibility", "oral health services." ], "content": "Introduction\n\nHealth For All has become a corner-stone of public health, ever since the International Conference on Primary Healthcare and declaration of Alma Ata in 1978. Health for all is not just being free from diseases; it is a promise for the provision of basic services to every single person in the world. Right to healthcare is a basic human necessity and includes dental healthcare within its umbrella of holistic cares.1\n\nOne of the principles of primary health care is to provide social equity universally. The word equity refers to just and fair distribution of health care services all around the globe.1 There is a special emphasis on providing access, which is people’s ability to avail healthcare related services as and when they are needed.2 Access to healthcare has an important role to play in the overall health system, in reducing the burden of disease.2 Access to health care has two important geographical perspectives:\n\n1. Accessibility (potential of approach) – how conveniently a particular service can be approached and the means of accessing the facility; and\n\n2. Utilization (actual frequency of approach) – actual use of services at hand.\n\nIt is very well acknowledged that, the healthcare based resources need to be planned in a specific way that, they are utilized to the maximum.3 They need to be located conveniently for the majority of the population to be able to access them. It is also important to accommodate for different growth rates of different geographic areas and population clusters. Some areas are dynamic and mutate, evolve and grow with time. This uneven growth rate of population clusters is straining an already stressed utility provision system. The prime objective for healthcare providers is to have an adequate road map during the establishment of new healthcare centres so that it caters to maximum number of people.3\n\nGiven the above criteria, geographic information system (GIS) based accessibility interpretation is the most scientific and succinct method that can be used to calculate the extent to which geographical access is obtained.4,5 In short, GIS is the ‘digitization of cartogram’. It is a modern information system with capabilities of accepting, recording, analysing, managing and presenting the spatial referenced data (that is, the data is linked to a geographic location).6 It uses data that is attached to a unique location (geo-referencing) to create a multi-tier map showing individual attributes that can be superimposed. GIS allows and aids in cartographical representation and comparison of data that can be used in formulating better and focused healthcare plans. Pictorial representation of statistical data is much more lucid and easier to interpret in comparison to other formats of data representation.7 Density maps/Heat maps aid in finding density of health centres, cases, vectors, risk factors, etc. Kernel density calculates the density of features in a neighbourhood and around those features, per unit area, in a raster format. It can be used with both the point and line data.7\n\nIn terms of geographical extent, India enjoys the position of being the seventh largest country worldwide, with a population of 1.3 billion. In India, dental healthcare is provided by a combination of private sector and public institutions. As one of the major signatories of the United Nations (UN) charter for health, India is committed to provide basic dental health provision, starting at the level of Community Health Centres. Since the inception of India’s first dental college in Kolkata in the year 1920, it has been an uphill task to train sufficient number of dentists to meet the demands of an ever growing population. Annual government funding for health services is meagre 1.6% of our total GDP, with no separate allocation for oral health.8 With 22% of the population living below poverty line, providing basic dental health services is a mammoth task.9\n\nCoastal Karnataka includes the districts of Udupi, Dakshina Kannada and Uttara Kannada in the South Western part of India. This area has its own ethnic population and customs and boasts of a population of roughly 4.7 million, spread over an area of 18730 square kilometre. The settlements vary greatly from commercial and urban clusters of Mangalore to inaccessible villages of Dandeli. This uneven distribution of population, and living standards warrants individual surveys for planning. It is hence imperative to have a thorough assessment of the existing distribution of oral healthcare facilities and understand potential accessibility when planning for expansion of oral health services. We hypothesized that dentists are concentrated to areas with high population density, easy geographic access and a higher wealth distribution.\n\nHence, this study aimed to map and calculate objectively, spatial accessibility to the oral health care facilities in coastal districts of Karnataka state, India: Udupi, Uttara Kannada and Dakshina Kannada, and its association with population density and socio-economic conditions. Objectives were:\n\n1. to analyze the geographic distribution of private and public dental healthcare providers with respect to population, per-capita income and urbanization, in GIS environment;\n\n2. to identify the poorly served areas in the three coastal districts of Karnataka and\n\n3. to investigate any association between oral health care services and socio-economic conditions.\n\n\nMethods\n\nThe three coastal districts of Karnataka stretch to a length of 435 km and a width of 225 km. These Districts are further divided into administrative sub-units known as taluks. There are a total of 1807 villages in 20 Taluks of these 3 Districts. We chose administrative districts as our geographical regions, since these match the population census files in the same format, as required for geo-mapping and analysis of geographical data. This cross-sectional study was conducted over a duration of twelve weeks between September and November 2020.\n\nIndian oral health care delivery system comprises predominantly of a private sector and a smaller public sector. Data on the public and private oral health centres were collected.\n\nPublic health care centers: Oral health delivery in public sector is integrated into the existing network of public hospitals in India and is organized in a hierarchy based on administrative units and population size. Oral healthcare is provided by Community Health Centres (CHC’s), district hospitals and government teaching institutions spread across the country. The address of each of these centers with dental clinics were obtained from the official portal of Karnataka State Health Ministry.10\n\nPrivate dental clinics: Private delivery system has been the predominant format of care in India. There is no official database maintained for the private dental clinics in our country. Therefore, the addresses were obtained from the largest dental non-governmental organization in India (Indian Dental Association branches of the three districts). We also hand-searched for any other private clinics through Google Search and advertisements.\n\nTeaching Dental Hospitals: Addresses of all the private dental schools with attached tertiary hospitals available in these districts were also included.\n\nTo test for accuracy of the geocoded dental practices, 2% of all practices with geocoding were chosen randomly and tested with Google Maps and open street maps and further web searched to attest to the authenticity of the data.\n\nPopulation based statistics were obtained from the most recent National Census of India (2011).11 Urban-rural divide of the population was obtained from Primary Census Abstract Data Highlights of Karnataka.12\n\nPer-capita income at the district level was extracted from India Human Development Survey II (2011-12).13\n\nThe geographic extent of the study area is from 15.5252°N to 12.8437°N latitude and 74.0852°E to 75.2479°E longitude covering an area of 18,931 square km. Geo-coding of the all the public and private oral health care services were completed by plotting on the free access geo-coding website from Google (OpenStreetMap). Geographic attributes (latitudes and longitudes) were then designated to the practitioners’ addresses with 90% being at the level of the building. Exclusion of duplicate addresses were done. After recording and cleaning, database files were transferred to the Quantum Geographic Information Systems (QGIS version 3.14, QGIS Development Team, GNU General Public License, Essen, Germany), with World Geodetic System 1984 (WGS 84) standard of coordinate referencing for geo-mapping.\n\nThe extracted data sets were then transferred to Microsoft Excel 2010. Descriptive statistical analyses (including number of dental practices within each district) and dentist-to-population ratios (D:P) were calculated. Correlation between the number of dental clinics with population and D:P with per capita income were analyzed using Pearson’s Correlation coefficient. Chi-square test was applied to analyze any association between D:P and urbanization.\n\n\nResults\n\nWe located 340 clinics functioning currently in the 20 taluks of the 3 districts, 29 (8.5%) of which are public and 311 (91.5%) are private clinics and cater to a population of 4,704,179.28 Overall, there are 255 (75%) urban and 85 (25%) rural clinics in the three districts as shown in Table 1.\n\nAmong the 11 taluks in Uttara Kannada, almost all (n=9) have less than 10 clinics and 10-20 clinics in 3 taluks. In contrast, one taluk each of Udupi and Dakshina Kannada districts have 40-50 clinics as shown in Table 2.\n\nAverage D:P for the three coastal districts is 1:13,836. Udupi district has lowest D:P of 1:10801, followed by Dakshina Kannada with ratio of 1: 12742 and Uttara Kannada with highest D:P of 1: 21450. Taluk-wise ratios showed lowest D:P in Mangalore taluk (1:9656) while Mundgod has the highest D:P (1:53087). Mangalore has the highest number of dental clinics (N=103), of which 96 (93.2%) were private clinics, which is also the taluk with highest per-capita income. Likewise, Mundgod taluk that has highest D:P (1:53087) has lowest per-capita income as shown in Table 3.\n\nFigure 1 gives the geo-map for the three coastal districts. Bourgeoning of private dental clinics and dental schools in a few areas is distinctly evident. Out of 340 clinics in the three districts, 103 were situated in Mangalore taluk. Further, Mangalore taluk alone houses five dental schools of the total seven dental schools in three districts. Uttara Kannada district does not have any dental schools.\n\nThere is an uneven urban-rural distribution of dentists with lower D:P in rural areas. Rural population in four taluks have only one dentist for over a lakh population. Six taluks have only one dentist for every 50000 – 100000 population in rural areas. Six rural areas had only public centers to cater to their oral health. Highest concentration of dental schools was seen in Dakshina Kannada district, with four schools in Mangalore taluk. Uttara Kannada district has no dental schools, in spite of being the biggest district of the three (Table 3). Identification of poorly served areas in the three coastal districts of Karnataka was facilitated with the aid of heat maps/density maps as shown in Figure 2.\n\nSignificant positive correlation is seen between taluk-wise population and number of dental clinics (Pearson’s correlation coefficient = 0.984) and also with D:P and per-capita income (Pearson’s correlation coefficient = -0.548). Chi-square test applied to determine association between D:P and urbanization is found to be significant (p < 0.000).\n\n\nDiscussion\n\nUniversal healthcare facilities are one of the pillars of the healthcare planning process. Access to healthcare is different from the geographic accessibility, in that, the former encompasses both:\n\n1. spatial components (availability and accessibility) and\n\n2. aspatial components (acceptability and affordability).\n\nHence, in our study we tried to measure geographic accessibility by locating the availability of dental practitioners in the coastal districts of Karnataka using GIS. A geographic information system (GIS) is a computerized system, that is created to analyse and display geographically referenced information as a layered map 6. According to Padminee K et al., Karnataka has the largest number of Dental practitioners for any state in India (34,768).14 For our work, geo-coordinates of the public and private oral health centres were collected and this data was used for GIS analysis using the open-source software, QGIS 3.14.\n\nIn the present study the average D:P was 1:12836. This is in accordance with the national D:P of 1:10,271.15 World Health Organization (WHO) recommendations state the ideal dentist to population ratio should be 1:7500.16 The above data is in sync with that of other developing countries. In India there are more than 300 dental colleges with 24,000 dental graduates adding to the pool every year. This ratio is similar to the studies conducted by Periera I et al. and Hosny G et al. in Srilanka and Egypt, respectively,16,17 but more than that of the study conducted by Omogunloye OG et al.18 but much lesser than the ratio reported in studies conducted in Australia and the United States (US).19,20\n\nThere is a severe misallocation of dentists in terms of urban and rural distribution. A high proportion of dental professionals are concentrated in the urban agglomerations. Only a small Indian population of 15 – 20% have access to dental health services through national schemes. The average per capita public health funding for a year in India is a meagre 2.6$.14\n\nAccording to the current study, a meagre 25% of the dental practitioners were practicing in the rural areas, serving 37.2% of coastal population, making D:P in the rural areas to 1: 39,401. This is very similar to the national estimates of rural D:P of 1:30,000.15 This contrasts with an urban D:P of 1:6859. These values are very similar to the national urban D:P of 1:4,000.15 This distribution pattern is common to many countries. Brazil and Taiwan (as developing nations) report an average D:P of 1:735 and 1:1603, respectively, but show uneven distribution between urban and rural areas.21,22 The solution for this uneven distribution lies in bringing all dentists under the umbrella of primary health-care system. In India, providing dental care starts at the level of community health centers. Employment of dental manpower at the primary health center level can help reduce this burden. The dental practitioner to population ratio has markedly improved from 1:301,000 in the 1960s to 1:9992 in the present times and yet, the state-wise distribution of dentists is disproportionate.23\n\nPublic health centers are providing affordable oral care services, but the services are very limited. This in turn, compels the people to consult private health care facilities, resulting in excessive expenditures. This situation is the same as in other developing countries like Nepal, Taiwan and Brazil.21–23 In Nepal the current ratio is 1:16000 according to a population report by Central Bureau of Statistics. Only 8% of dentists work in public sector, and these values are even lower in comparison to countries like Denmark and South Africa. Though the ratio has improved to 1:24000 in 2010 from 1:120000 in 2000, it is much lesser when compared to countries like Singapore and United Kingdom.24 These countries provide holistic dental care via the National Health Service and have a strong network of public health centres for all its citizens.25\n\nSince the 1990s, there has been a boom in the number of dental schools, most of which are private. At present, 86% of all Indian dental schools are private colleges. We observed dissimilarity in the distribution of dental schools across the region. Four dental schools, all private, are located in a single taluk, with one district devoid of any dental schools. Privatization increases the divide between rich and poor, boosting the facilities richest while driving the poor to further penury.25 This should not be acceptable to a civilized society. This wave of privatization has side-lined access to universal oral health services and has alienated the underprivileged.26\n\nThe results of our study confirm the hypothesis that dentists are concentrated to areas with high population density, easy geographic access and a higher wealth distribution. This disparity in distribution of oral healthcare amongst the districts of Coastal Karnataka is similar to that of other countries, with dental services being more easily found in the large cities and along the coastal areas.6,22\n\nOur study has some limitations. Comprehensive data on the dental clinics were not available. Many countries around the world have an annually updated database of dentists in both private and public and sectors. The Indian database is substantially inadequate in this regard. For this study we collected all the data on private dental clinics via the registered dentists under Indian Dental Association. We also hand searched for any private clinics via Google search engine. The latest population data available to us was that of the National Census 2011, whereas, the dental clinics data is updated to 2019 and hence, there are possibilities of overestimation of clinics/D:P ratio.\n\n\nConclusion\n\nFrom our study, we came to the conclusion that oral health services were concentrated in areas with higher annual income per-capita, increased urbanization and population density. The same were unevenly spread across coastal districts. Rural population in four taluks have only one dentist for over a lakh population. Most of the rural areas have only public centres to cater to their oral health. Private clinics are unevenly distributed. Also, we could identify the poorly served areas in the three districts. Shockingly, the share of funds allocated for public healthcare provision is only 1% of the total GDP. Moreover, India lacks a separate and specific allocation for dental health. In the last financial India spent only 6% of its total GDP towards healthcare.27\n\nAll the above mentioned problems can be solved with appropriate government support in key areas. Meticulous planning of survey data comprising of geographical distribution parameters and economic status of the surrounding population can give an accurate representation of the ease of accessibility of treatment.\n\n\nData availability\n\nOpen Science Framework: https://doi.org/10.17605/OSF.IO/A8SNJ.28\n\nLicense: Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "References\n\nWho called to return to the declaration of alma-ata. Accessed: 2022-02-2. Reference Source\n\nBlack M, Ebener S, Aguilar PN, et al.: Using gis to measure physical accessibility to health care. World Health Organization; 2004; 3–4.\n\nRanasinghe N, Kruger E, Tennant M: School dental service in sri lanka: geo-spatial analysis of access to oral health care. Int. J. Paediatr. Dent. 2018; 28(5): 490–496. PubMed Abstract \| Publisher Full Text\n\nPhotis YN: Disease and health care geographies: Mapping trends and patterns in a gis. Health Sci. J. 2016; 10(3): 1.\n\nMokgalaka H: Gis-based analysis of spatial accessibility: an approach to determine public primary healthcare demand in metropolitan areas. Master’s thesis, University of Cape Town.2015.\n\nNor Faezah M, Bohari EK, John J, et al.: Analysis of dental services distribution in malaysia: a geographic information systems–based approach. Int. Dent. J. 2019; 69(3): 223–229.\n\nNayak PP, Pai JB, Singla N, et al.: Geographic information systems in spatial epidemiology: Unveiling new horizons in dental public health. J. Int. Soc. Prev. Community Dent. 2021; 11(2): 125–131. PubMed Abstract \| Publisher Full Text\n\nDemand for grants 2020-21 analysis: Health and family welfare: 2021. Accessed: 2021-03-24. Reference Source\n\nNational health profile 2019: 2019. Accessed: 2021-03-24. Reference Source\n\nDistrict wise hospital details with facilities: 2017. Accessed: 2020-09-02. Reference Source\n\nPopulation enumeration data (final population): 2011. Accessed: 2020-09-12. Reference Source\n\nPrimary census abstract data highlights karnataka: Series 30: 2011. Accessed: 2020-09-12. Reference Source\n\nIndia human development survey ii (2011-12): 2012. Accessed: 2020-09-12.Reference Source\n\nKrishnan Padminee RA, Lakshmi K, Kumar PDM, et al.: Geographic disproportions in dental workforce distribution and its impact on oral disease burden: An indian perspective. SRM Journal of Research in Dental Sciences. 2020; 11(2): 76. Publisher Full Text\n\nVundavalli S: Dental manpower planning in india: current scenario and future projections for the year 2020. Int. Dent. J. 2014; 64(2): 62–67. Publisher Full Text\n\nPerera I, Kruger E, Tennant M: Gis as a decision support tool in health informatics: spatial analysis of public dental care services in sri lanka. Journal of Health Informatics in Developing Countries. 2012; 6(1).\n\nHosny G, Sayed S, Tantawi M, et al.: Evaluation of accessibility of dental services using geographic information system. Sci. Afric. J. Sci. Issues. 2015; 3: 763–767.\n\nOmogunloye OG, Tijani OA, Abiodun EO, et al.: Geospatial distribution and utilization of dental facilities in lagos state.2016.\n\nTennant M, Kruger E: A national audit of a ustralian dental practice distribution: do all a ustralians get a fair deal?. Int. Dent. J. 2013; 63(4): 177–182. PubMed Abstract \| Publisher Full Text\n\nVoinea-Griffin A, Solomon ES: Dentist shortage: an analysis of dentists, practices, and populations in the underserved areas. J. Public Health Dent. 2016; 76(4): 314–319. PubMed Abstract \| Publisher Full Text\n\nMartin ASS, Chisini LA, Martelli S, et al.: Distribution of dental schools and dentists in brazil: an overview of the labor market. Rev. Abeno. 2018; 18(1): 63–73.\n\nCheng F-C, Chang JY-F, Lin T-C, et al.: Dentist manpower development and geographical distribution of dentists in taiwan. J. Dent. Sci. 2020; 15(2): 121–131. Publisher Full Text\n\nJaiswal AK, Srinivas P, Suresh S: Dental manpower in india: changing trends since 1920. Int. Dent. J. 2014; 64(4): 213–218. Publisher Full Text\n\nShrestha RM, Shrestha S, Kunwar N: Dentists in nepal: a situation analysis. J. Nepal Health Res. Counc. 2017; 15(2): 187–192. PubMed Abstract \| Publisher Full Text\n\nSaliba NA, Moimaz SAS, Garbin CAS, et al.: Dentistry in brazil: its history and current trends. J. Dent. Educ. 2009; 73(2): 225–231. PubMed Abstract \| Publisher Full Text\n\nRamanarayanan V, Janakiram JJC, Krishnakumar K: Oral health care system analysis: A case study from india. J. Family Med. Prim. Care. 2020; 9(4): 1950–1957. PubMed Abstract \| Publisher Full Text\n\nNational oral health policy: 2021. Accessed: 2021-09-12.Reference Source\n\nNayak PP, Mitra S, Pai JB, et al.: Mapping accessibility to oral health care in coastal India – A geospatial approach using Geographic Information System (GIS).2022, February 14. Publisher Full Text" }	[ { "id": "135730", "date": "16 May 2022", "name": "Patrick Calvano Küchler", "expertise": [ "Reviewer Expertise Geographic Information Systems", "Health Geography" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn the present study, an attempt was made to measure geographic accessibility to oral health in the Indian state of Karnataka. The proposal was to use geoprocessing methods and tools available in open source geographic information systems to analyze the spatial distribution of oral health facilities in public and private spheres in urban and rural regions. Geographically, the data used were latitude and longitude extracted from the addresses, which made it possible to geocode the data using OpenStreetMap as a basis. Descriptive statistical analyzes were performed with the creation of one main index: the dentist-population ratio D:P, in addition to its correlations with per capita income and number of clinics where Pearson's correlation coefficient was used.\nIn addition to the location map of the oral health units, a density index map was produced. I believe that the authors could better explore the geoprocessing tools in future work, producing layer overlays or even thematic maps with the D:P index for each district, which would make it possible to carry out a deeper discussion of the results, making the research more relevant. I believe that the contribution of this article to the scientific society is important, with an impact on public health management, where it became evident that the understanding of spatial distributions is essential for a broad understanding of society, producing information that support decisions in the public health management.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "145194", "date": "28 Jul 2022", "name": "Arun Pallathadka", "expertise": [ "Reviewer Expertise I specialize in GIS", "Spatial Analysis", "Spatial Statistics", "Urban Geography", "and Sustainability." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis work uses GIS methods to analyze accessibility to dental services in 20 taluks of 3 districts in Karnataka, India. The authors have geocoded dental practitioner locations using open resources such as Google Maps and OpenStreetMap, and have further relied on density mapping and Pearson's correlation to report their findings. Overall, this work has merit, especially in highlighting the urban-rural divide in dental service accessibility in India. While the authors have shown promising potential in the area of geographic information system (GIS) applications, I note that there are sections in this manuscript that could be improved. Following are my comments for improvement:\nIn the introduction section, the authors introduce healthcare accessibility well but do not discuss the state of knowledge on dental care accessibility. Discuss previous works summarizing what similar studies (global, regional, local) have found. I have added references that may be helpful to the authors.\n\nI would recommend not using 1 sentence paragraphs in the manuscript. For example, \"socioeconomic data\" has only one sentence. You can either add a few more sentences to such subsections or combine them into a single section under appropriate headings.\n\nI would strongly encourage the authors to include a site map showing the location of the three districts with all the major cities clearly shown, and then also show a Karnataka map (with just district boundaries) within the Indian map (state boundaries only). Include the Arabian sea.\n\nRevise Fig. 1 with the following changes:\n\n- Fix the legend heading, i.e., \"Selected_points\" is unnecessary. Figures should be clean without underscores. - Under three districts on the legend, it is not clear what the blue polygon represents as it stands without a label.\n\n- I would also include a very light base map of neighboring districts and the Arabian Sea for reference.\n\nIn the methods, briefly describe what technique (E.g., Kernel) / tool (E.g., Point Density tool) was used for density/heat mapping analysis.\n\nIt is not clear what software was used to run Pearson and Chi-square tests. Please include the appropriate citations.\n\nI am not sure this paragraph fits into the scope of discussion. It would better fit in the methods section or perhaps even the introduction section where the study area is described.\n\" Hence, in our study we tried to measure geographic accessibility by locating the availability of dental practitioners in the coastal districts of Karnataka using GIS. A geographic information system (GIS) is a computerized system, that is created to analyse and display geographically referenced information as a layered map 6. According to Padminee K et al., Karnataka has the largest number of Dental practitioners for any state in India (34,768).14 For our work, geo-coordinates of the public and private oral health centres were collected and this data was used for GIS analysis using the open-source software, QGIS 3.14.\"\n\nIn your limitations, also acknowledge the differences that may exist in dental service preferences among urban and rural populations. This applies to both dentist and patient behaviors.\n\nIn your conclusion section, refer to the sentence I have provided below. The statement is too strong/broad. Perhaps, rephrase to state how these problems can be better addressed with appropriate government support, along with support from private and non-governmental stakeholders.\n\n\"All the above mentioned problems can be solved with appropriate government support in key areas.\"\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8616", "date": "08 Aug 2022", "name": "Jagadeesha Pai B", "role": "Author Response", "response": "Response to Reviewers 05.08.2022 Respected Reviewers, We would like to thank you for the opportunity to make revisions in our manuscript entitled “Mapping accessibility to oral health care in coastal India – A geospatial approach using a geographic information system”. We would also like to thank the reviewer for his comments and suggestions on our manuscript. We have responded to each comment by the reviewer below: Comment: In the introduction section, the authors introduce healthcare accessibility well but do not discuss the state of knowledge on dental care accessibility. Discuss previous works summarizing what similar studies (global, regional, local) have found. I have added references that may be helpful to the authors. Response to reviewers: We have now added that, sir Changes done on page number: Page No. 4 Comment: I would recommend not using 1 sentence paragraphs in the manuscript. For example, \"socioeconomic data\" has only one sentence. You can either add a few more sentences to such subsections or combine them into a single section under appropriate headings. Response to reviewers: We have now done that sir Changes done on page number: Page number 5 Comment: I would strongly encourage the authors to include a site map showing the location of the three districts with all the major cities clearly shown, and then also show a Karnataka map (with just district boundaries) within the Indian map (state boundaries only). Include the Arabian sea. Response to reviewers: Location map is included sir Changes done on page number: Page number 5 Comment: Revise Fig. 1 with the following changes: - Fix the legend heading, i.e., \"Selected_points\" is unnecessary. Figures should be clean without underscores. - Under three districts on the legend, it is not clear what the blue polygon represents as it stands without a label. - I would also include a very light base map of neighboring districts and the Arabian Sea for reference. Response to reviewers: Modification has been incorporated sir and map is modified, sir Changes done on page number: Page number 9 Comment: In the methods, briefly describe what technique (E.g., Kernel) / tool (E.g., Point Density tool) was used for density/heat mapping analysis. Response to reviewers: The method we used is Kernel Density Estimation and same has been explained. Changes done on page number: Page No. 9 Comment: It is not clear what software was used to run Pearson and Chi-square tests. Please include the appropriate citations. Response to reviewers: We have now mentioned sir Changes done on page number: Page No. 6 Comment: I am not sure this paragraph fits into the scope of discussion. It would better fit in the methods section or perhaps even the introduction section where the study area is described. \" Hence, in our study we tried to measure geographic accessibility by locating the availability of dental practitioners in the coastal districts of Karnataka using GIS. A geographic information system (GIS) is a computerized system, that is created to analyse and display geographically referenced information as a layered map 6. According to Padminee K et al., Karnataka has the largest number of Dental practitioners for any state in India (34,768).14 For our work, geo-coordinates of the public and private oral health centres were collected and this data was used for GIS analysis using the open-source software, QGIS 3.14.\" Response to reviewers: Sir, we usually start with a small introductory paragraph in Discussion. Justifying the reason for conducting the study. Comment: In your limitations, also acknowledge the differences that may exist in dental service preferences among urban and rural populations. This applies to both dentist and patient behaviors. Response to reviewers: We have now added sir. Changes done on page number: Page No. 10 Comment: In your conclusion section, refer to the sentence I have provided below. The statement is too strong/broad. Perhaps, rephrase to state how these problems can be better addressed with appropriate government support, along with support from private and non-governmental stakeholders. \"All the above mentioned problems can be solved with appropriate government support in key areas.\" Response to reviewers: We have now rectified sir Changes done on page number: Page No. 11 We hope to have carried out revisions to the satisfaction of the reviewer. Please let us know if more revisions are required. Regards" } ] } ]	1	https://f1000research.com/articles/11-366
https://f1000research.com/articles/11-471/v1	28 Apr 22	{ "type": "Research Article", "title": "Prevalence of responsible research practices among academics in The Netherlands", "authors": [ "Gowri Gopalakrishna", "Jelte M. Wicherts", "Gerko Vink", "Ineke Stoop", "Olmo R. van den Akker", "Gerben ter Riet", "Lex M. Bouter", "Jelte M. Wicherts", "Gerko Vink", "Ineke Stoop", "Olmo R. van den Akker", "Gerben ter Riet", "Lex M. Bouter" ], "abstract": "Background: Traditionally, research integrity studies have focused on research misbehaviors and their explanations. Over time, attention has shifted towards preventing questionable research practices and promoting responsible ones. However, data on the prevalence of responsible research practices, especially open methods, open codes and open data and their underlying associative factors, remains scarce. Methods: We conducted a web-based anonymized questionnaire, targeting all academic researchers working at or affiliated to a university or university medical center in The Netherlands, to investigate the prevalence and potential explanatory factors of 11 responsible research practices. Results: A total of 6,813 academics completed the survey, the results of which show that prevalence of responsible practices differs substantially across disciplines and ranks, with 99 percent avoiding plagiarism in their work but less than 50 percent pre-registering a research protocol. Arts and humanities scholars as well as PhD candidates and junior researchers engaged less often in responsible research practices. Publication pressure negatively affected responsible practices, while mentoring, scientific norms subscription and funding pressure stimulated them. Conclusions: Understanding the prevalence of responsible research practices across disciplines and ranks, as well as their associated explanatory factors, can help to systematically address disciplinary- and academic rank-specific obstacles, and thereby facilitate responsible conduct of research.", "keywords": [ "Responsible conduct of research", "Responsible research practices", "Research integrity", "Open science" ], "content": "Introduction\n\nThe basis of sound public policy relies on trustworthy and high-quality research. This trust is earned by being transparent and performing research that is relevant, ethically sound and of robust methodological quality. Researchers and their research institutions can accomplish this by promoting responsible research practices (RRPs) and by discouraging questionable research practices (QRPs) and research misconduct.1 To this end, solid, empirical knowledge on the adoption of RRPs and their underlying explanatory factors is paramount.\n\nThere has been a clear rise in publications and efforts aimed at promoting research integrity in recent years,1–8 including pleas for the adoption and promotion of open science and other RRPs aimed at increasing the trustworthiness of research through increased transparency. In particular, open methods (e.g. preregistration of study protocols), open codes (for data analysis), open data (following the FAIR principles9) and open access (rendering publications available at no cost for users) play an important role.4\n\nA number of explanatory factors such as scientific norms subscription, fair distribution of resources, rewards and recognitions (i.e. organizational justice), perceived pressures researchers face (e.g. competition, work, publication and funding pressures), and support by mentors have been suggested to be important in fostering high-quality research.10–12 So far however, the body of research on research integrity has focused largely on how to minimize QRPs but not so much on empirical evidence to foster RRPs. These studies typically have a narrow disciplinary scope covering few possible explanatory factors.10–17\n\nThe National Survey on Research Integrity (NSRI)18 was designed to take a balanced, research-wide approach to report on the prevalence of RRPs, QRPs and research misconduct, in addition to exploring the potential explanatory factors associated with these behaviors in a single survey. The NSRI targeted the entire population of academic researchers in The Netherlands, across all disciplinary fields and academic ranks.\n\nThe objectives of the NSRI were:\n\n1) to estimate prevalence of RRPs, QRPs and research misconduct, and\n\n2) to study the association between possible explanatory factors and RRPs, QRPs and research misconduct.\n\nIn this paper we focus on the prevalence of RRPs and the explanatory factors that may help or hinder responsible conduct of research. Elsewhere we report on QRPs, research misconduct and their associative explanatory factors.19\n\n\nResults\n\nA total of 63,778 emails were sent out (Figure 1) and 9,529 eligible respondents started the survey. Of these, 2,716 stopped the survey prematurely and 6,813 completed the survey. The response could only be reliably calculated for the eight supporting institutions (Figure 1a, Extended data20) and was 21.1%.\n\nExtended data: Table 1a gives a breakdown of all respondents stratified by background characteristics.20 Male and female respondents were fairly equally split among the respondents. For the natural and engineering sciences, women accounted for 24.9% of respondents. In the highest academic rank of associate and full professors, women made up less than 30% of respondents (Table 1a, Extended data20). Nearly 90% of all respondents are engaged in empirical research and about half (48%) come from the eight supporting institutions. Respondents from supporting and non-supporting institutions were fairly evenly distributed across disciplinary fields and academic ranks except for the natural and engineering sciences where less than one in four (23.5%) came from supporting institutions.\n\nPhD candidates and junior researchers had the lowest scale score for work pressure (3.9) compared to the other ranks (Table 1b, Extended data20). Postdocs and assistant professors reported the highest scale scores for publication pressure (4.2), funding pressure (5.2), and competitiveness (3.7), and the lowest scores for peer norms (4.1) and organizational justice (4.1) compared to the other ranks (Table 1b, Extended data20).\n\nRespondents from the arts and humanities had the highest scale scores for work pressure (4.8), and competitiveness (3.8) and the lowest scale scores for mentoring and organizational justice (3.5 and 3.9, respectively) (Extended data: Table 1b20). The scientific norms scale scores were similar across all disciplines and academic ranks. The scores on the peer norms scale were consistently lower than the scientific norms scores across disciplines and ranks.\n\nThe five most prevalent RRPs (i.e. with a Likert scale score of 5, 6 or 7) had a prevalence range of 86.4% to 99% (Table 1; Figure 2, Extended data20). Fair ordering of authorships (RRP 3) and preregistration of study protocols (RRP 6) showed the largest percentage differences between the Life and Medical Sciences and the Arts and Humanities (RRP 3: 75.7 vs 91.6% and RRP 6: 50.8% versus 30.2%). PhD candidates and junior researchers (74.2%) reported the lowest prevalence for RRP3 on fair allocation of authorships compared to associate and full professors (90.9%).\n\nExtended data: Table 2 shows the discipline- and academic rank-specific prevalence of “not applicable” (NA) answers on the 11 RRPs.20 Arts and Humanities scholars reported the highest prevalence of NA for nine out of the 11 RRPs. Similarly, across ranks, PhD candidates and junior researchers displayed the highest prevalence of NAs on nine out of the 11 RRPs.\n\nThe four open science practices had an overall prevalence ranging from 42.8% to 75%: (i) following the FAIR principles (RRP 4: 75%); (ii) Publishing open access (RRP 8: 72.6%); (iii) Providing underlying data, computer codes, or syntaxes (RRP 10: 47.2%) and (iv) Preregistration of study protocols (RRP 6: 42.8%) (Table 1).\n\nSurprisingly, the Arts and Humanities scholars had the highest prevalence for RRP 4 on following FAIR principles (84.6%). However, a closer look at RRP 4, reveals that this discipline also had the highest percentage of NA for RRP 4 (27.5%) (Extended data: Table 220). Life and Medical Sciences had the highest prevalence (50.8%) and the Arts and Humanities the lowest (30.2%) for preregistration of study protocols (RRP 6), where nearly 70% (67.8%) of the arts and humanities scholars rated RRP 6 as not applicable (Table 2, Extended data20). Arts and Humanities scholars had the lowest prevalence (59.1%) and the Life and Medical Sciences the highest (75.1%) for publishing open access (RRP 8) (Table 1).\n\nTable 2a shows the results of the linear regression analysis for the five background characteristics while Table 2b shows the linear regression results for the explanatory factor scales.\n\n* Two subscales (Distributional and Procedural Organizational Justice) were merged due to high correlation. Extended data: Table 4 shows the correlation of all the explanatory factor scales. Bold figures are statistically significant.\n\nTable 2a shows that the Arts and Humanities scholars had a significantly lower overall RRP mean score (-0.51; 95% CI -0.59, -0.42). Similarly, doing non-empirical research was associated with a significantly lower overall RRP mean score (-0.49; 95% CI -0.57, -0.42). Interestingly, females had a significantly lower RRP mean score than males (-0.07; 95% CI -0.12, -0.02). Being a PhD candidate or junior researcher was associated with a significantly lower overall RRP mean (-0.31; 95% CI -0.37, -0.25).\n\nOne standard deviation increase on the publication pressure scale was associated with a significant decrease in overall RRP mean score (-0.05; 95% CI -0.08, -0.02) (Table 2b). An increase of one standard deviation in the following five explanatory factor scales was associated with higher overall RRP mean, namely: (i) responsible mentoring (0.15; 95% CI 0.11, 0.18); (ii) funding pressure (0.14; 95% CI 0.11, 0.17); (iii) scientific norms subscription (0.13; 95% CI 0.10, 0.15); (iv) likelihood of QRP detection by collaborators (0.05; 95% CI 0.02, 0.08); and (v) work pressure (0.03; 95% CI 0.01, 0.06).\n\n\nDiscussion\n\nWe found that overall RRP prevalence ranged from 42.8% to 99% with open science practices at the lower end (42.8% to 75%). The Arts and Humanities scholars had the lowest prevalence of preregistration of study protocols and open access publication. This disciplinary field also had the highest prevalence of NAs (nine out of the 11 RRPs), as did the PhD candidates and junior researchers. Arts and Humanities scholars, as well as PhD candidates and junior researchers, were associated with a significantly lower overall RRP mean score, as was doing non-empirical research and being female in gender.\n\nPublication pressure was associated with lower overall RRP mean score while responsible mentoring, funding pressure, scientific norms subscription, likelihood of QRP detection by collaborators and work pressure were associated with higher RRP mean scores.\n\nThe results of our regression analysis suggest that publication pressure might lower RRPs, although the effect was modest. This finding complements what we found for QRPs, where publication pressure was associated with a higher odds of engaging frequently in at least one QRP.19 These results suggest that lowering publication pressure may be important for fostering research integrity.\n\nOur findings regarding scientific norms and peer norms subscription are noteworthy.10,12 These scales have previously been validated and used in a study among 3,600 researchers of different disciplines in the United States of America.12,21 In that study, respondents reported higher scientific norms subscription when asked about the norms a researcher should embrace, but they perceived the actual adherence to these norms by their peers to be lower. Our results corroborate these findings.12\n\nPrevious authors have made calls to institutional leaders and department heads to pay increased attention to scientific norms subscription within their research cultures.12,22 Our regression analysis findings reinforce these calls to revive subscription to the Mertonian scientific norms.21\n\nMentoring was associated with a higher overall RRP mean score and was aligned with a similar study by Anderson et al.17 Interestingly, a lack of proper supervision and mentoring of junior co-workers was the third most prevalent QRP respondents reported in our survey.19 This finding was also reported in another recent survey among researchers in Amsterdam23 which suggests that increased efforts to improve mentoring and supervision may be warranted within research institutions.\n\nIn our QRP analysis of the NSRI survey results, likelihood of detection by reviewers was significantly associated with less misconduct, suggesting that reviewers, more than collaborators, are important in QRP detection.24 However, for RRPs, the reverse seems to be true: collaborators may be more important for fostering RRPs than reviewers.\n\nTo our surprise, we found that work pressure and funding pressure both had a small but significant association with higher RRP mean scores. One plausible explanation may be that adhering to RRPs requires a slower, more meticulous approach to performing research.\n\nWe found that scholars from the Arts and Humanities, as well as PhD candidates and junior researchers, reported RRPs more often as “not applicable”. We were unable to differentiate whether this is because these open science RRPs are truly not applicable or if these practices are simply not yet recognized as standard responsible practices in this discipline and rank. While it can be argued that not all open science practices, particularly those relating to the sharing of data and codes, are relevant for the non-empirical disciplines such as the Arts and Humanities,25,26 practices like preregistration of study protocols, publishing open access and making sources, theories and hypotheses explicit and accessible, seem relevant for most types of research, empirical or not.\n\nArts and Humanities scholars reported the highest work pressure and competitiveness, and the lowest organizational justice and mentoring support. While our sample size for this disciplinary field was relatively small (n = 636), the finding of lower organizational justice in this discipline is consistent with a recent study.24 Our regression analysis shows that Arts and Humanities scholars had significantly lower overall RRP mean scores as well as the highest prevalence of “not applicables” for nine out of the 11 RRPs. Research integrity efforts have largely focused on the biomedical, and social and behavioural sciences.27 However, these results point to a need to better understand responsible research practices that may be disciplinary field-specific, namely to the Arts and Humanities discipline.\n\nWe found that PhD candidates and junior researchers had the lowest prevalence across all RRPs and were associated with the lowest overall RRP mean score. A recent Dutch survey of academics, as well as our own survey, point to inadequate mentoring and supervision of junior co-workers as a prevalent QRP.19,28 This seems to underline a clear message: adequate mentoring and supervision of PhD candidates and junior researchers appears to be consistently lacking and may be contributing to lower prevalence of RRPs in this rank.\n\nWomen had a slightly lower, yet statistically significant, overall RRP mean score. While it has been previously reported that men engage in research misbehavior more than women,19,23,29 our finding of lower RRP engagement for women has not been reported earlier and is a finding we hope to explore in the qualitative discussions planned in the next phase of our project.\n\nThe email addresses of researchers affiliated to non-NSRI-supporting institutions were web-scraped from open sources. Therefore, we are unable to credibly verify if the scraped email addresses matched our eligibility criteria for NSRI participation. Hence, we calculated the response based only on the eight supporting institutions. The 21.1% response was within the range of similar research integrity surveys.24,30 Given this response, one may question the representativeness of the NSRI sample to its target population, i.e. all academic researchers in The Netherlands. Unfortunately, there are no reliable numbers at the national level that match our study’s eligibility criteria. Therefore, we cannot assess our sample’s representativeness even for the five background characteristics. Nevertheless, we believe our results to be valid as our main findings align well with the findings of other national and international research integrity surveys.12,17,22,24,31\n\nA limitation of our analysis concerns recoding NA answers into “never” for the multiple linear regressions, since there is a difference between not committing a behaviour because it is truly not applicable and intentionally refraining from doing so. Our analyses may therefore underestimate the occurrence of true, intentional RRPs.\n\nThe NSRI is the largest research integrity survey in academia to-date to look at both prevalence of RRPs as well as the largest range of explanatory factors in a single study across disciplinary fields and academic ranks.\n\n\nMethods\n\nThis study was performed in accordance with guidelines and regulations from Amsterdam University Medical Centers and the Declaration of Helsinki. In addition, the Ethics Review Board of the School of Social and Behavioral Sciences of Tilburg University approved this study (Approval Number: RP274). The Dutch Medical Research Involving Human Subjects Act (WMO) was deemed not applicable to this study by the Institutional Review Board of the Amsterdam University Medical Centers (Reference Number: 2020.286).\n\nThe full NSRI study protocol, ethics approvals, complete data analysis plan and final dataset can be found on Open Science Framework.32 Below we summarize the salient study features.\n\nThe NSRI was a cross-sectional study using a web-based anonymized questionnaire. All academic researchers working at or affiliated to at least one of 15 universities or seven university medical centers (UMCs) in The Netherlands were invited by email to participate. To be eligible, researchers had, on average, to do at least eight hours of research-related activities weekly, belong to Life and Medical Sciences, Social and Behavioural Sciences, Natural and Engineering sciences, or the Arts and Humanities, and had to be a PhD candidate or junior researcher, postdoctoral researcher or assistant professor, or associate or full professor.\n\nThe survey was conducted by a trusted third party, Kantar Public,33 which is an international market research company that adheres to the ICC/ESOMAR International Code of standards.2,34 Kantar Public’s sole responsibility was to send the survey invitations and reminders by email to our target population and send the anonymized dataset at the end of the data collection period to the research team.\n\nUniversities and UMCs that supported NSRI supplied Kantar Public with the email addresses of their eligible researchers. Email addresses for the other institutes were obtained through publicly available sources, such as university websites and PubMed.\n\nResearchers’ informed consent was sought through a first email invitation which contained the survey link, an explanation of NSRI’s purpose and its identity protection measures. Starting the survey after this section on informed consent implied written consent. Consenting invitees could therefore immediately participate in the survey thereafter. NSRI was open for data collection for seven weeks, during which three reminder emails were sent to non-responders, at a one- to two-week interval period. Only after the full data analysis plan had been finalized and preregistered on the Open Science Framework32 did Kantar Public send us the anonymized dataset containing individual responses.\n\nNSRI comprised four components: 11 QRPs, 11 RRPs, two research misconduct questions on falsification and fabrication (FF) and 12 explanatory factor scales (75 questions). The survey started with a number of background questions to assess eligibility of respondents. These included questions on one’s weekly average duration of research-related work, one’s dominant field of research, academic rank, gender and whether one was conducting empirical research or not.32\n\nAll respondents, regardless of their disciplinary field or academic rank, were presented with the same set of RRPs, QRPs and research misconduct questions on FF. These questions referred to the last three years in order to minimize recall bias. The 11 RRPs were adapted from the Dutch Code of Conduct for Research Integrity 201811 and a survey among participants of the World Conferences on Research Integrity.35 The first author of this manuscript created the initial formulations of the RRPs which covered study design, data collection, reporting, open science practices, conflicts of interest and collaboration. These 11 RRP formulations were reviewed and agreed upon in two rounds: first within the NSRI core research team, and subsequently by an external group of multidisciplinary experts who formed the NSRI Steering Committee.18 All 11 RRPs had a seven-point Likert scale ranging from 1 = never to 7 = always, in addition to a “not applicable” (NA) answer option.\n\nThe explanatory factors scales were based on psychometrically tested scales in the research integrity literature and focused on action-ability. Twelve were selected: scientific norms, peer norms, perceived work pressure, publication pressure, pressure due to dependence on funding, mentoring (responsible and survival), competitiveness of the research field, organizational justice (distributional and procedural), and likelihood of QRP detection by collaborators and reviewers.10–12,18,21,22,35–37 Some of the scales were incorporated into the NSRI questionnaire verbatim, others were adapted for our population or newly created (see Extended data: Table 5).\n\nFace validity of the NSRI questionnaire was tested in several ways. The QRP-related questions underwent extensive focus group testing in the instrument development stage of the project. Both the QRPs and RRPs were further refined through several rounds of discussions with the core research team, with the project’s Steering Committee and with an independent expert panel set up to review the entire questionnaire. Preliminary pilot testing was conducted for some of the explanatory factor scales, listed in Extended Data Table 5 along with the results of the factor analysis (factor loadings), whereas others were re-used from validated instruments, also detailed in Table 5 (Extended data).20 Explanatory factor scales that are indicated as having been piloted will be reported on in future publications. In addition, internal consistency was tested and is reported as Cronbach’s Alpha in Extended Data Table 1b. Inter-rater reliability was not applicable as the survey was self-administered; however test-retest reliability was not tested. Finally, the NSRI questionnaire’s comprehensibility was pre-tested in cognitive interviews with 18 academics from different ranks and disciplines.38 In summary, the comments centered around improvement in layout, such as the removal of an instructional video on the RR technique which was said to be redundant, improvement in the clarity of the instructions, and recommendations to emphasize certain words in the questionnaire by using different fonts for improved clarity. The full report of the cognitive interview can be accessed at the Open Science Framework.32\n\nWe used “missingness by design” to minimize survey completion time. Thus, each invitee received one of three random subsets of 50 explanatory factor items from the full set of 75 (see Table 5, Extended data20). All explanatory factor items had seven-point Likert scales. In addition, the two perceived likelihood of QRP detection scales, the procedural organizational justice scale and the funding pressure scale had a NA answer option. There was no item non-response option as respondents had to either complete the full survey or withdraw.\n\nWe report on RRPs both in terms of prevalence and overall RRP mean. We operationalized prevalence as the proportion of participants that scored 5, 6 or 7 among the participants that deemed the RRP at issue applicable. Mean scores of individual RRPs only consider respondents that deemed the RRP to be applicable. In the multiple linear regression analysis, overall RRP mean was computed as the average score on the 11 RRPs, with the not-applicable scores recoded to 1 (i.e., “never”). Extended data: Figures 2a to 2e show the distribution of responses, including the “not-applicable” category for the 11 RRPs.20 The associations of the overall RRP mean with the five background characteristics (Extended data: Table 1a20) and the explanatory factor scales were investigated with multiple linear regression.39\n\nFor the multivariate analyses of the explanatory factor scales, we used z-scores computed as the first principal component of the corresponding items.31 Missing explanatory factor item scores due to ‘not applicable’ answers were replaced by the mean z-score of the other items of the same scale. Multiple imputation with mice in R31 (version 4.0.3) was employed to deal with the missingness by design. Fifty complete data sets were generated by imputing the missing values using predictive mean matching.40,41 The linear regression models were fitted to each of the 50 data sets, and the results combined into a single inference. To incorporate uncertainty due to the nonresponse, the inferences were combined according to Rubin’s Rules.42 All models contained all explanatory scales and the five background characteristics. The full statistical analysis plan, and analysis codes were preregistered on the Open Science Framework32 including the following pre-specified subgroup analyses: field by rank, publication pressure by rank, funding pressure by rank, competition by disciplinary field, and detection (by reviewers or by collaborators) by disciplinary field.\n\nRespondents’ identities were protected in accordance with the European General Data Protection Regulations (GDPR) and corresponding legislation in The Netherlands. In addition, we had Kantar Public conduct the survey to ensure that the email addresses of respondents were never handled by the research team. Kantar Public did not store respondents’ URLs and IP addresses. Only a fully anonymized dataset was sent to the research team upon closure of data collection and preregistration of the statistical analysis plan. Finally, we conducted analyses at aggregate levels only (i.e., across disciplinary fields, gender, academic ranks, whether respondents conducted empirical research, and whether they came from NSRI supporting institutions).\n\n\nData availability\n\nOpen Science Framework (OSF): National Survey on Research Integrity, https://doi.org/10.17605/OSF.IO/2K549.43\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nAuthors' contributions\n\nConceptualization: GtR, JMW, LMB\n\nMethodology: GG, GtR, GV, IS, JMW, LMB\n\nInvestigation: GG, JMW, OvdA\n\nVisualization: GG, GtR, GV, IS, JMW, LMB, OvdA\n\nFunding acquisition: GtR, LMB\n\nProject administration: GG, LMB\n\nSupervision: GG, GtR, LMB\n\nWriting – original draft: GG\n\nAll authors reviewed and edited the manuscript.", "appendix": "Acknowledgments\n\nThe authors wish to thank the NSRI Steering Committee members (Guy Widdershoven, Herman Paul, Joeri Tijdink, Sonja Zuijdgeest, Corrette Ploem) for their support. In addition, we wish to thank Sara Behrad, Frank Gerritse, Coosje Veldkamp, Brian Martinson and Melissa Anderson for their contributions.\n\n\nReferences\n\nNational Academy of Sciences, National Academy of Engineering, Institute of Medicine, Committee on Science and Engineering and Public Policy & Panel on Scientific Responsibility and the Conduct of Research. Responsible science - Ensuring the integrity of the research process: volume 1. Washington, DC: The National Academies Press; 1992. Reference Source\n\nSteneck N, Mayer T, Anderson MS: Singapore statement on research integrity. Singapore: 2010. Reference Source\n\nShaw DM, Ten Thomas C : simple rules for protecting research integrity. PLoS Comput. Biol. 2015; 11: e1004388. PubMed Abstract \| Publisher Full Text\n\nMoher D, et al.: The Hong Kong Principles for assessing researchers: Fostering research integrity. PLoS Biol. 2020; 18: e3000737. PubMed Abstract \| Publisher Full Text\n\nMejlgaard N, et al.: Research integrity: nine ways to move from talk to walk. Nature. 2020; 586: 358–360. PubMed Abstract \| Publisher Full Text\n\nHiney M: Briefing paper on research integrity: what it means, why it is important and how we might protect it. Science Europe; 2015. Reference Source\n\nCommittee on Responsible Science, Committee on Science Engineering Medicine and Public Policy, Policy and Global Affairs & National Academies of Sciences Engineering and Medicine. Fostering integrity in research. The National Academies Press; 2017.\n\nALLEA - All European Academies: The european code of conduct for research integrity (revised edition). Berlin: 2017.\n\nWilkinson MD e a: The FAIR guiding principles for scientific data management and stewardship. Scientific Data. 2016; 3: 160018. PubMed Abstract \| Publisher Full Text\n\nMerton RK: The sociology of science: theoretical and empirical investigations. University of Chicago Press; 1973.\n\nKNAW, NFU, NOW, TO2-federatie, Vereniging Hogescholen, VSNU: Netherlands code of conduct for research integrity. The Netherlands: 2018. Publisher Full Text\n\nAnderson MS, Martinson BC, De Vries R: Normative dissonance in science: results from a national survey of U.S. scientists. J. Empir. Res. Hum. Res. Ethics. 2007; 2: 3–14. PubMed Abstract \| Publisher Full Text\n\nXie Y, Wang K, Kong Y: Prevalence of research misconduct and questionable research practices: a systematic review and meta-analysis. Sci. Eng. Ethics. 2021; 27: 41. PubMed Abstract \| Publisher Full Text\n\nDe Vries R, Anderson MS, Martinson BC: Normal misbehavior: scientists talk about the ethics of research. J. Empir. Res. Hum. Res. Ethics. 2006; 1: 43–50. PubMed Abstract \| Publisher Full Text\n\nBonn NA, Pinxten W: Advancing science or advancing careers? Researchers’ opinions on success indicators. PLoS One. 2021; 16: e0243664. PubMed Abstract \| Publisher Full Text\n\nAnderson MS, Ronning EA, De Vries R, et al.: The perverse effects of competition on scientists’ work and relationships. Sci. Eng. Ethics. 2007; 13: 461–637.\n\nAnderson MS, et al.: What do mentoring and training in the responsible conduct of research have to do with scientists' misbehavior? Findings from a national survey of NIH-funded scientists. Acad. Med. 2007; 82: 853–860. PubMed Abstract \| Publisher Full Text\n\nNational Survey on Research Integrity: 2020. Reference Source\n\nGopalakrishna G, ter Riet G , Vink G, et al.: Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in The Netherlands. PLoS One. 2022; 17(2): e0263023. PubMed Abstract \| Publisher Full Text\n\nGopalakrishna G, et al.: NSRI Supplementary Materials. OSF. 2022. Publisher Full Text\n\nAnderson MS, Ronning EA, De Vries R, et al.: Extending the Mertonian norms: scientists’ subscription to norms of research. J. High. Educ. 2010; 81: 366–393. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMartinson BC, Crain AL, De Vries R, et al.: The importance of organizational justice in ensuring research integrity. J. Empir. Res. Hum. Res. Ethics. 2010; 5: 67–83. PubMed Abstract \| Publisher Full Text\n\nFang FC, Bennett JW, Casadevall A: Males are overrepresented among life science researchers committing scientific misconduct. Am. Soc. Microbiol. 2013; 4: e0064012. Publisher Full Text\n\nHaven TL, Tijdink JK, Martinson BC, et al.: Perceptions of research integrity climate differ between academic ranks and disciplinary fields: Results from a survey among academic researchers in Amsterdam. PLoS One. 2019; 14: e0210599. PubMed Abstract \| Publisher Full Text\n\nSeverin A, Egger M, Eve MP, et al.: Discipline-specific open access publishing practices and barriers to change: an evidence-based review. F1000 Res. 2018; 7(1925) Publisher Full Text\n\nKnöchelmann M: Open Science in the Humanities, or: Open Humanities?. MDPI. 2019; 7(65). Publisher Full Text\n\nBonn NA, Pinxten W: A decade of empirical research on research integrity: what have we (not) looked at?. J. Empir. Res. Hum. Res. Ethics. 2019; 14: 338–352. PubMed Abstract \| Publisher Full Text\n\nHaven TL, et al.: Researchers’ perceptions of research misbehaviours: a mixed methods study among academic researchers in Amsterdam. Res. Integr. Peer Rev. 2019; 4: 25. PubMed Abstract \| Publisher Full Text\n\nCharness G, Gneezy U: Strong evidence for gender differences in risk taking. J. Econ. Behav. Organ. 2012; 83: 50–58. Publisher Full Text\n\nFanelli D: How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data. PLoS One. 2009; 4: e5738. PubMed Abstract \| Publisher Full Text\n\nvan Buuren S , Groothuis-Oudshoorn K: mice: multivariate Imputation by chained equations in R. J. Stat. Softw. 2011; 45: 1–67. Publisher Full Text\n\nNational Survey on Research Integrity on Open Science Framework (OSF): 2020. Reference Source\n\nKantar Public: 2020. Reference Source\n\nESOMAR: Kantar signs up to ICC/ESOMAR international code globally - inks new membership deal focused on employee development.2020. Reference Source\n\nBouter LM, Tijdink JK, Axelsen N, et al.: Ranking major and minor research misbehaviors: results from a survey among participants of four World Conferences on Research Integrity. Res. Integr. Peer Rev. 2016; 1: 17. PubMed Abstract \| Publisher Full Text\n\nNavarro MLA, Mas MB, Jiménez AML: Working conditions, burnout and stress symptoms in university professors: Validating a structural model of the mediating effect of perceived personal competence. Span. J. Psychol. 2010; 13: 284–296. PubMed Abstract \| Publisher Full Text\n\nHaven TL, de Goede MEE , Tijdink JK, et al.: Personally perceived publication pressure: revising the Publication Pressure Questionnaire (PPQ) by using work stress models. Res. Integr. Peer Rev. 2019; 4: 7. PubMed Abstract \| Publisher Full Text\n\nMiller K, Willson S, Chepp V, et al.: Cognitive interviewing methodology. Hoboken, New Jersey: John Wiley & Sons, Inc; 2014.\n\nCruyff MJLF, Van den Hout ADL, Van der Heijden PGM: The analysis of randomized-response sum score variables. J. R. Stat. Soc. Series B Stat. Methodol. 2008; 70: 21–30.\n\nRubin DB: Statistical matching using file concatenation with adjusted weights and multiple imputations. J. Bus. Econ. Stat. 1986; 4: 87–94.\n\nLittle RJA: Missing-data adjustments in large surveys (with discussion). J. Bus. Econ. Stat. 1988; 6: 287–296.\n\nRubin DB: Multiple imputation for nonresponse in surveys. John Wiley & Sons; 1987; vol. 76. .\n\nGopalakrishna G, Wicherts JM, Bouter L, et al.: National Survey on Research Integrity - Just Science Pilot.2020, September 29. Publisher Full Text" }	[ { "id": "136272", "date": "16 May 2022", "name": "Elisabeth M. Bik", "expertise": [ "Reviewer Expertise Scientific integrity" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis manuscript is the second publication derived from a large questionnaire sent out to universities and academic medical centers in the Netherlands. While the first paper (PLOS ONE 2022, DOI: 10.1371/journal.pone.0263023; henceforth: \"PONE22\"1) focused on questions and answers related to questionable research practices (QRP) and research misconduct, this manuscript reports on the survey part related to responsible research practices (RRP).\nThis study found a negative correlation between pressure to publish and RRP, whereas its counterpart PONE22 found a positive correlation between publication pressure and QRP. Both findings are important because they strongly suggest that the increasing pressure put on scholars to publish might lead to less RRP and more QRP and science misconduct. In addition, the paper finds a correlation between the lack of adequate mentoring of junior researchers and a lower prevalence of RRPs.\nThe two papers nicely complement each other, but since they both refer to the same questionnaire, there is a lot of textual and data overlap. One might argue that keeping both parts of the study together in one publication would have been a better strategy because by splitting up these papers, parts of this manuscript read as redundant and not novel. While in some cases - such as in the methods - this might be acceptable, some other parts - such as the introduction and results - should be checked for identical or very similar phrases. Some specific examples of such similarities are noted below.\nStrengths of this paper are the scale and anonymity of the survey, the focus on both good as well as bad practices (in combination with the PONE22 paper), and the analysis of multiple science disciplines and influencing factors. This paper nicely builds upon and extends on previous surveys on research integrity and misconduct, and offers a view of the factors that drive researchers to choose between good or bad practices. This study and its PONE22 companion could and should be used for future roadmaps on how to best structure academic research.\n\nSpecific comments\nIntroduction: the first two sentences are (nearly) identical to those of PONE22. Could they be worded a bit differently?\n\nResults - \"A total of 63,778 emails were sent out (Figure 1) and 9,529 eligible respondents started the survey.\" Figure 1 is the same as in PONE22 - the authors could just leave this sentence and add reference 19 for more details.\n\nResults. \"The response could only be reliably calculated for the eight supporting institutions (Figure 1a, Extended data20) and was 21.1%.\" - This sentence was not clear. Does this refer to the institutions (8 out of 22 invited institutions) that provided the email addresses, as mentioned in PONE22? Does the 21.1% refer to the number of invited vs completed surveys or institutions? A similar statement was found in PONE22, but there it was 21.2%.\n\nThe whole first part of the results \"Descriptive analyses\" seems nearly identical to that in PONE22. To prevent a partial duplication of already published results, it might be better to just give a short summary here, and refer to reference 19.\n\nResults: Table 1: In the description of RRP1, check \"finan1bcial\"\n\nResults. In the paragraph starting with \"The four open science practices\" perhaps chance 75% to 75.0% to match the number of digits to the other reported percentages.\n\nDiscussion. The sentence starting with \"In our QRP analysis of the NSRI survey results..\" refers to an older survey, reference 24. Should this not be reference 19, PONE22? Perhaps the authors could check.\n\nDiscussion. Could the authors perhaps define the difference between publication pressure and work pressure? I was not sure what was meant by these or how they were related to questions in the survey. This is particularly relevant since these two factors had opposite effects on RRPs. Perhaps this should be better defined in the results or here in the discussion?\n\nDiscussion: The last paragraphs, starting with \"The email addresses of researchers...\" are nearly identical to those in PONE22. Could the authors please rewrite these?\n\nMethods: Again, large chunks of the text here are similar to those in PONE22. I am not sure how much textual similarity in the Methods would be acceptable for F1000, but it might still be needed to partially rewrite these and refer to reference 19.\n\nMethods: Could the authors check the part starting with \" The explanatory factors scales were based...\"? The second sentence seems to talk specifically about QRPs, and might not be applicable for this paper.\n\nThis is very minor, but the text switched between \"behavior\" and \"behaviour\" and its derivatives.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8421", "date": "08 Aug 2022", "name": "Gowri Gopalakrishna", "role": "Author Response", "response": "We thank the reviewer for these comments. With respect to the similarities between both manuscripts, we have modified parts of the Introduction, Results and Discussion sections to emphasize the differences between this manuscript and PONE22 more. The specific changes are outlined in detail below against each of the reviewer comments. As the reviewer correctly points out both manuscripts, this and PONE22, are complementary to each other. Whilst the PONE22 article reports on the fabrication and falsification (FF) and questionable research practices (QRPs), this manuscript presents the responsible research practice questions (RRPs) from the National survey on Research Integrity (NSRI) and the association between each explanatory factor and the overall RRP mean score. Because both PONE22 and this manuscript report on data of the NSRI the Methods sections are indeed quite similar. We did consider the option of combining both papers into one but decided against this for the following reasons: Much of the research integrity literature has focused on negative research behaviours (i.e. QRPs and misconduct) and hardly on the empirical evidence around RRPs and the factors that may be associated with them. Combining both papers may dilute the emphasis on the RRPs which we felt warranted in line with the discussions that increasingly center around rewarding responsible research practices and open science. Combining both papers into one would have complicated a focused discussion considerably given the large number of descriptive as well as regression-based findings. We also believed that two separate papers with clear cross-references would make the NSRI findings more assessable than everything piled in one lengthy piece. For descriptive results on the explanatory factors which are similar in both papers, we have now made a reference to PONE22 in this manuscript to avoid repetition. Specific comments Introduction: the first two sentences are (nearly) identical to those of PONE22. Could they be worded a bit differently? Author Response: Thank you for this comment. We have changed the introduction such that it now begins with the following paragraph “There has been a clear rise in publications and efforts aimed at promoting research integrity in recent years, including pleas for the adoption and promotion of open science and other RRPs aimed at increasing the trustworthiness of research through increased transparency. In particular, open methods (e.g. preregistration of study protocols), open codes (for data analysis), open data (following the FAIR principles) and open access (rendering publications available at no cost for users) play an important role” Results - \"A total of 63,778 emails were sent out (Figure 1) and 9,529 eligible respondents started the survey.\" Figure 1 is the same as in PONE22 - the authors could just leave this sentence and add reference 19 for more details. Author Response: Thank you for this comment. While we agree this part of the results is the same as in PONE22, we feel it is important to explicitly mention these results so a reader can immediately have the response proportion of our survey without needing to look up this important information in another publication. Results. \"The response could only be reliably calculated for the eight supporting institutions (Figure 1a, Extended data20) and was 21.1%.\" - This sentence was not clear. Does this refer to the institutions (8 out of 22 invited institutions) that provided the email addresses, as mentioned in PONE22? Does the 21.1% refer to the number of invited vs completed surveys or institutions? A similar statement was found in PONE22, but there it was 21.2%. Author Response: Thank you for spotting this error in the decimal point. The figure should be 21.1% and refers to the same percentage explained in Figure 1a of the extended data reference 20. This is derived by dividing total number of eligible individuals who opened the survey invitation (4414) by the total number of individuals who were invited from the 8 supporting institutions. We have further clarified by this by changing the following sentence to read as: “The response could only be reliably calculated for the eight supporting institutions (Figure 1a, Extended data20) and was 21.1%. This percentage was derived by dividing total number of eligible individuals who opened the survey invitation (4414) by the total number of individuals who were invited from the eight supporting institutions (20,879).” The whole first part of the results \"Descriptive analyses\" seems nearly identical to that in PONE22. To prevent a partial duplication of already published results, it might be better to just give a short summary here, and refer to reference 19. Author Response: We have replaced this first paragraph as suggested with the following sentence: Extended Data Table 1a describes the distribution of survey respondents by gender, disciplinary field, engagement in empirical research and if they were from a supporting institution or not. Extended Data Table 1b describes the distribution of the explanatory factor scales by disciplinary field and academic rank. The full description of these distributions can be read at Gopalakrishna et al19 . Results: Table 1: In the description of RRP1, check \"finan1bcial\" Author Response: This should have been “financial” and is now corrected. Results. In the paragraph starting with \"The four open science practices\" perhaps change 75% to 75.0% to match the number of digits to the other reported percentages. Author Response: We have changed the percentage to read as 75.0% Discussion. The sentence starting with \"In our QRP analysis of the NSRI survey results..\" refers to an older survey, reference 24. Should this not be reference 19, PONE22? Perhaps the authors could check. Author Response: Thank you for spotting this mistake. The reference should be 19 as mentioned and is now corrected. Discussion. Could the authors perhaps define the difference between publication pressure and work pressure? I was not sure what was meant by these or how they were related to questions in the survey. This is particularly relevant since these two factors had opposite effects on RRPs. Perhaps this should be better defined in the results or here in the discussion? Author Response: We now make this distinction more clearly in the Methods section where we have included the following sentences: “With respect to the explanatory factor scale on work pressure, this can be defined as “the degree to which an academic has to work fast and hard, has a great deal to do, but with too little time” while publication pressure can be defined as the degree to which an academic feels s/he has to publish in high-prestige journals in order to have a sustainable career (Karasek & Theorell, 1990),” Extended data Table 620 provides the full list of questions we included in the questionnaire.” Discussion: The last paragraphs, starting with \"The email addresses of researchers...\" are nearly identical to those in PONE22. Could the authors please rewrite these? Author Response: We have modified these paragraphs as requested. They now read as follows: “The response proportion for this survey could only reliably be calculated for the eight supporting institutions and this was 21.1%19. This is within the range of other research integrity surveys 24,30. Since there were no reliable numbers at the national level that match our study’s eligibility criteria, we were unable to assess our sample’s representativeness including the five background characteristics. Despite this limitation, we believe our results to be valid as our main findings corroborate the findings of other national and international research integrity surveys 12,17,22,24,31. A limitation in our analysis concerns the recoding of the NA answers into “never” for the multiple linear regressions. We expect our analyses reported in this manuscript to be an underestimation of the occurrence of true intentional RRPs as a result of this re-coding. Because our recoding of NA into “never” cannot distinguish between not committing a behavior because it is truly not applicable versus intentionally refraining from doing so, our analyses may therefore underestimate the occurrence of true, intentional RRPs. The NSRI is the one of the largest and most comprehensive research integrity surveys in academia to-date which to study prevalence of RRPs and the potential explanatory factors that may be associated with these behaviours in a single study across disciplinary fields and academic ranks.” Methods: Again, large chunks of the text here are similar to those in PONE22. I am not sure how much textual similarity in the Methods would be acceptable for F1000, but it might still be needed to partially rewrite these and refer to reference 19. Author Response: Thank you for this comment. We feel it is appropriate for there to be textual similarity in the Methods as this is the same survey and hence using the same methods as in PONE22 with the important exception that this manuscript reports on a different dataset from the survey namely that on the prevalence and associative factors relating to the responsible research practices. Methods: Could the authors check the part starting with \" The explanatory factors scales were based...\"? The second sentence seems to talk specifically about QRPs, and might not be applicable for this paper. Author Response: This is making reference to the two explanatory factor scales namely, likelihood of QRP detection by collaborators and likelihood of QRP detection by reviewers. As such they are not making reference to the PONE22 QRP paper but to two of the twelve explanatory factor scales which are named as such. This is very minor, but the text switched between \"behavior\" and \"behaviour\" and its derivatives. Author Response: Thank you for pointing this out. We have checked the manuscript to ensure behavior is spelled consistently." } ] }, { "id": "137500", "date": "27 May 2022", "name": "Dorothy Vera Margaret Bishop", "expertise": [ "Reviewer Expertise Psychology", "Neuropsychology", "Language", "Reproducibility" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nSummary This is the 2nd paper reporting results from the National Survey on Research Integrity in the Netherlands (NSRI), this time with a focus on frequency of, and drivers of responsible research practices (RRPs). The previous study reported on questionable research practices and a future report will consider the associations between the two. This seems a reasonable way to divide up the report of findings. The authors report that frequency of RRPs varies with discipline and they conduct a pre-registered regression analysis to look at predictors of RRPs. I evaluated this work without looking at the existing reviewer report, in order to give an independent opinion.\nEvaluation This is a substantial piece of work; the survey materials that the authors have developed are impressive and they home in on key constructs for tackling issues around responsible research. It was particularly impressive that the researchers achieved the support of many research institutions in the Netherlands. This is a rich dataset, which is openly available to other researchers, greatly enhancing its value.\nI have many suggestions for improvement, however, as I think the value and comprehensibility of the work could be enhanced. Since the F1000 model requires reviewers to give approval in order for the work to be indexed, I will note which points I see as most important to achieve that.\n\n1. Response rate.\nA major limitation of this study is the low response rate (20%). The authors mention this in the Discussion and note that their response rate is comparable to other studies of this kind. That is certainly true (in fact, it is a relatively high rate!), and I sympathise, having had similar experiences in studies of this kind I've been involved in. Nevertheless, it really limits the conclusions one can draw, especially if there is no information about how this self-selection bias affected who responded. The authors note that they cannot assess the sample's representativeness even for the five background characteristics, but \"Nevertheless, we believe our results to be valid as our main finding align well with the findings of other national and international research integrity surveys\". But those other surveys suffer from the same problem: self-selection bias. Given that one of the goals of the study is to assess the prevalence, there is serious potential for biased estimates. If we have a lot of studies all with the same bias, we are in serious danger of creating illusory validity. I have two suggestions for starting to address this:\nAt least for the institutions who supported the survey, gather information on the numbers of academics at the institution who fall into each discipline, and the number who fall into each academic rank. Even if these numbers are approximate, and do not describe the specific sample targeted here, they would be helpful for giving some idea about response rates in each cell of a discipline x academic rank table. Supplementary Table 1a gives some information on those completing the survey but does not actually report discipline x academic rank, which I think is an important feature (as indicated by Table 2a). I do not see it as essential to do this, as I appreciate it may be difficult to gather this information, but it would be very useful. If it is not possible to do it, maybe flag up the importance to gather this information upfront in future surveys.\n\nDiscuss possible strategies for achieving better response rates in future surveys. An obvious one is incentives. I could not find any information about this in the paper, but in supplementary materials, I note the survey takes 20-25 minutes to complete. A survey that does not incentivise people to respond is going to be problematic because anyone who is busy and/or regards the subject of the survey uninteresting or irrelevant won't reply, and these people may have given different responses to those who do respond. Probably the most cost-effective way of incentivising people is to offer a lottery with one or more high-stakes prizes - e.g. enter people into a prize draw with the chance to win one of five prizes of €1000. It's possible ethics committees would object, but I think the case for doing this is very strong - and it could be argued it is unethical to do a study that is likely to give biased findings. The most ethical solution would be to offer each respondent an adequately motivating reward (comparable to minimum wage rate) for the time spent completing the survey. With a potential pool of 60K respondents, this would get very expensive, but the research would be more valid with a smaller pool of representative academics, than with a large pool of unrepresentative people. I think some discussion of this issue, perhaps combined with some discussion of point (2) below, would be easy to incorporate in a revision and worth doing.\n\n2. Arts and humanities\nOn the one hand, it is good to include arts and humanities. But on the other hand, they frequently responded NA, and one can see why. Around 1/3 of respondents were not doing empirical research. The wording of questions to refer to 'open science', 'scripts', and 'data' is not ideal for this field. In my experience, academics in this area can get pretty irritated and feel they are having scientific practices imposed on them. The survey also has questions on adherence to 'scientific norms' - again, that wording is really not appropriate language for people in arts and humanities. 'Scholarly norms' would be better. Open access publishing has been a thorny issue in the humanities, especially in areas where the main output is a monograph, and there may be no funds to pay for open access. (Indeed, lack of funds for open access may be a limiting factor in other disciplines and failure to ask about that is one limitation of an otherwise very well-motivated and comprehensive survey). My inclination would be to remove the Arts and Humanities subgroup from the analysis, as they are so very different in many respects, and I suspect the survey lacks face validity for many in those disciplines. (Of course, given that the authors have provided their data and scripts, it would be straightforward for other interested scholars to do this, so I don't insist on this as a condition for giving peer reviewer approval).\n3. Pre-registration\nI found the pre-registration status of the paper confusing. A link, https://osf.io/2k549, is provided under Data Availability, but that refers to a Belgian pilot study. I think that is probably just an error, but it was extremely confusing and I wasted time wading through that material looking for details of the current questionnaire. Then under 'statistical analysis' I found 'The full statistical analysis plan, and analysis codes were preregistered on the Open Science Framework', and a link to an OSF page that contains data, materials, and analysis scripts, https://osf.io/ehx7q/. This material is well-organised and reasonably easy to navigate, but it does not appear to have been formally pre-registered, in the sense of having a fixed date-stamped version and I could not find a document with the data analysis plan.\nI did find data-analysis.rmd, which says \"This document contains the analyses as described in NSRI data analysis plan - VERSION 7 - 20120126.docx\", but I could not find that document on the OSF. Apologies if I missed it: hopefully this can be made more prominent, as this is a key aspect for evaluating the analysis. This is an essential point.\n4. Skewed data.\nFor many of the items, data are skewed - in effect, these are items which amount to asking whether the respondent approves of motherhood and apple pie - everyone strongly agrees. I noticed at least one item (I did not check all), in the opposite direction, and this was one which perhaps should have been reverse scored - item F27 - most people responded 1. Some brief discussion of how this might affect results would be warranted - e.g. how does the restriction of range on some scales affect the regression coefficients?\n5. Treatment of NA responses.\nWe are told that for the regression analysis NA was coded as 1. The justification for this is questionable. My general sense is that it would be preferable to have a smaller sample for whom the survey items were valid (i.e. where NA was not used), rather than to shoehorn all respondents into an analysis which might give a misleading picture.\nIt would be reassuring to readers if the analysis could be repeated by excluding all participants who responded NA, to check how this influenced findings. I see this as essential for clarifying the results.\n6. Difficulty in getting the sense of the main findings.\nThe underlying motivation for this work includes identification of potential explanatory factors for RRPs, presumably so interventions can be designed to modify these. Yet I could get no sense of how useful various explanatory factors would be, because data are reported largely as regression coefficients and confidence intervals, with the predictors shown on a z-score scale, which I think is derived from a principal component analysis. This would make it difficult for anyone else to use the same survey and try to replicate the results in a new sample - that would be easier if an average score from sets of items were used as an independent variable.\n\nMinimally, a measure of effect size, such as percentage of variance explained, would be useful. I had to go to Supplementary Materials to find more detail of basic results of interest, and when I did that there were some anomalies - see point j below. It is a very large and complex dataset and I appreciate that the authors did not want to overwhelm readers with information. Nevertheless, I feel they have gone too far in the direction of economical presentation so that the reader has less of an immediate sense of what the results mean. This is not helped by having Methods placed after Results (see point a below).\nI was interested, for instance, in understanding more about the unexpected association between work pressure/funding pressure and RRPs. I didn't really understand the authors' explanation 'adherence to RRPs requires a slower, more meticulous approach' - I can see that might increase work pressure because there is more to do, but it wasn't so clear for funding pressure. Why would increased funding pressure increase RRPs? Perhaps funders are these days demanding that evidence of RRPs is shown in proposals? What's interesting though is that some might leap on this finding to justify putting more pressure on researchers, with some kind of 'more pain, more gain' argument. Of course, they could be right! This gets right to the heart of research culture: in the past, many disciplines had a 'survival of the fittest' approach with ECRs - there was an implicit ethos that research was tough, that putting pressure on ECRs would select for the best researchers, with less committed researchers dropping out. If the most committed are also those who adopt new, open practices, then you might get this kind of association. I'm not advocating this as an explanation, which is completely against current ideas of nurturing ECRs to get the best from them! But it is important to get a more detailed picture of what is going on here.\nAccordingly, I wrote a little script to explore this finding and this suggests that it's a complex picture with the effect influenced by the combination of Field and Rank, as well as Empirical Research. It also looked as if the association was at least in part driven by the NA responders doing non-empirical research. If I am able to attach figures I'll do so, but otherwise, here is the code, where the data is just the first imputed dataset, d50[[1]].\nmyplot <- ggplot(mydat, aes(x=WorkPress, y=RRP_ave, color=Research)) +\n\ngeom_point(shape=1, size=.5)+\n\ngeom_smooth(method=lm) myplot<- myplot + facet_grid(Field ~ Rank) The plots can be viewed on Github: https://github.com/oscci/miscellaneous/blob/master/FundPress.pdf https://github.com/oscci/miscellaneous/blob/master/WorkPress.pdf\n\nAssuming my plots are accurate, I'd be very cautious about making any general claims about the impact of either Work Pressure or Publication Pressure on the adoption of RRPs.\nI don't regard it as essential for the authors to add such plots, but I would like to see some discussion of the possible variation across disciplines/ranks, and the substantive importance of the effect sizes in real life.\n\nMore minor points\na. I dislike the practice of putting Methods at the end of the paper. I see it as symptomatic of a tendency that the authors want to avoid - treating methods as less important than results. I can't make sense of the results until I have seen the methods. In fact, numerous questions occurred as I read the Results, which then were answered at the end of the paper. So please put this important material in its rightful place, after the introduction.\nb. The file codebook.rmd does not run. The variable v is length 143, whereas descriptions and values are length 139, so they won't combine in a data frame. Ideally, we just need a document file with this information (I tried the html file, but it did not give sensibly formatted output; a simple .csv would be best). (I'm sure this is easily fixed)\nc. It would be good to have a table showing the breakdown of numbers in each cell formed by cross-classifying by discipline and academic rank. Some information is available on 2-way cross-classification in the supplementary tables, but it is not enough.\nd. p 3, end of Introduction; 'associative' change to 'associated'\ne. Mention how long the survey took to complete: I eventually found this in the online material, but it would be better in text.\nf. p 3. It seems odd to say that there were 6813 completed surveys out of 63,778 emails and then describe a 21% response rate. I assume this reflects the fact that for nonsupporting institutions, you do not know if emails were correct? Just a word of explanation is needed here.\ng. Is Extended Data the same as Supplementary Materials? I assume it is and refers to the material I found at this link: https://osf.io/w9vhc/.\nh. Why is Supplementary Table 1b not in the main text? This seems like key information from the survey, which readers will want to have readily available without needing to open supplementary documents from a link.\ni. Similarly, I felt that to get a sense of the data, I needed to see the items corresponding to the scales shown in Supplementary Table 1b. These should be included in the main text.\nj. Supplementary Figure 2 would also be worth including in the main text, but it needs a key indicating what each of the RRP codes is. The order of the codes seems different from the order in which each RRP is mentioned in the Tables. This figure illustrates the skew that I mentioned that affects especially Scientific Norms (I assume RRP1?) and RRP9 and RRP11. I tried to work out which scales were RRP9 and RRP11 by looking for scales with means above 5 (since most responses in Fig 2 are 6 and 7 for these scales), but there weren't any others than Scientific Norms, so this again is confusing and needs clarifying. I eventually worked it out by comparing the main paper Table 1 and the Supplementary material, but I am still confused as to why the mean scores for F9 and F11 are not higher in Supplementary Table 1b.\nk. I recommend being more cautious in the use of causal language, e.g. talking of 'explanatory factors'. This is observational rather than experimental data, based on self-report, and it is possible that there are subject-specific factors that lead to specific kinds of responses on the 'dependent' variables and also affect reporting of 'independent' predictors. In effect, any reporting biases by participants are confounded with both independent and dependent measures. The difficulty in assigning causality is apparent in the authors' own explanation of why work pressure predicts RRPs - this could actually be because adoption of RRPs makes more work.\nThe results are still of interest but need to be reported with appropriate cautions.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8425", "date": "08 Aug 2022", "name": "Gowri Gopalakrishna", "role": "Author Response", "response": "We thank the reviewer for these suggestions. We have already tried to gather data on the five background variables for the eight supporting institutions, but this proved difficult as some institutions had deleted the dataset they specially generated for our survey by the time we made this request (ie shortly after the survey collection closed in Nov 2020) or did not have this data that specifically matched the definitions we used in our survey. For example academic rank category we had a number of different ranks which were not always synonymous to how these institutions categorized their staff. We have therefore chosen to address this concern of the reviewer by flagging the importance of gathering this type of information upfront for future surveys. Discussion section now includes the following sentences: “Nonetheless, we believe having solid data on the representativeness of our survey respondents in terms of our overall target population is vital. While this was unavailable at both the national level and within the supporting institutions, it is imperative that future surveys collect such data prior to the survey start.” Discuss possible strategies for achieving better response rates in future surveys. An obvious one is incentives. I could not find any information about this in the paper, but in supplementary materials, I note the survey takes 20-25 minutes to complete. A survey that does not incentivise people to respond is going to be problematic because anyone who is busy and/or regards the subject of the survey uninteresting or irrelevant won't reply, and these people may have given different responses to those who do respond. Probably the most cost-effective way of incentivising people is to offer a lottery with one or more high-stakes prizes - e.g. enter people into a prize draw with the chance to win one of five prizes of €1000. It's possible ethics committees would object, but I think the case for doing this is very strong - and it could be argued it is unethical to do a study that is likely to give biased findings. The most ethical solution would be to offer each respondent an adequately motivating reward (comparable to minimum wage rate) for the time spent completing the survey. With a potential pool of 60K respondents, this would get very expensive, but the research would be more valid with a smaller pool of representative academics, than with a large pool of unrepresentative people. I think some discussion of this issue, perhaps combined with some discussion of point (2) below, would be easy to incorporate in a revision and worth doing. Author Response: Thank you for raising this relevant point. We did explore with our international advisors and steering committee of the NSRI the issue of incentives. However, we decided against this for several reasons. Firstly, the literature (a selection of which is provided below this response) and our experts we consulted were divided on the usefulness of incentives to higher the response rate. Secondly, incentivizing would likely not adequately address the issue of selection bias and may even possibly exacerbate it. There is evidence suggesting if incentives are to be used, they should be offered to all participants, unconditionally in order to be effective which in our study was not feasible due to the sample size. Finally, because of our strict privacy measures, handing out incentives to responders only was not a feasible option as we didn’t know who the responders were. We, therefore, chose to focus our efforts to increase participation by 1. drafting an attractive, yet succinct personalized invitation letter to each of the 63,778 participants in our target group 2. clearly outlining the importance of this survey, and how its outcome would help shape the research integrity climate for Netherlands and beyond, 3.ensuring strict privacy protection measures in the design of the survey (detailed in our methods section), 4. developing a reasonably short, easy to answer questionnaire suitable for a laptop and other handheld devices, 5.testing the online survey layout and usability through cognitive testing, 6.conducting a broad media campaign consisting of advertising the survey on social media and news outlets (university newsletters, national newspapers, national and international academic news magazines, personalized email invitations on a last name basis), 7.sending 3 reminders over a seven week period. Literature: Göritz, Anja. (2006). Incentives in Web Studies: Methodological Issues and a Review. International Journal of Internet Science. 1; Göritz, A. S., & Neumann, B. P. (2016). The longitudinal effects of incentives on response quantity in online panels. Translational Issues in Psychological Science, 2(2), 163–173. https://doi.org/10.1037/tps0000071 Suzer-Gurtekin, Z. Tuba, Mahmoud ElKasabi, Mingnan Liu, James M. Lepkowski, Richard Curtin, and Rebecca McBee. 2016. “Effect of a Pre-Paid Incentive on Response Rates to an Address-Based Sampling (ABS) Web-Mail Survey.” Survey Practice 9 (4). https://doi.org/10.29115/SP-2016-0025. Evans, J.R. and Mathur, A. (2018), \"The value of online surveys: a look back and a look ahead\", Internet Research, Vol. 28 No. 4, pp. 854-887. https://doi.org/10.1108/IntR-03-2018-0089 2. Arts and humanities On the one hand, it is good to include arts and humanities. But on the other hand, they frequently responded NA, and one can see why. Around 1/3 of respondents were not doing empirical research. The wording of questions to refer to 'open science', 'scripts', and 'data' is not ideal for this field. In my experience, academics in this area can get pretty irritated and feel they are having scientific practices imposed on them. The survey also has questions on adherence to 'scientific norms' - again, that wording is really not appropriate language for people in arts and humanities. 'Scholarly norms' would be better. Open access publishing has been a thorny issue in the humanities, especially in areas where the main output is a monograph, and there may be no funds to pay for open access. (Indeed, lack of funds for open access may be a limiting factor in other disciplines and failure to ask about that is one limitation of an otherwise very well-motivated and comprehensive survey). My inclination would be to remove the Arts and Humanities subgroup from the analysis, as they are so very different in many respects, and I suspect the survey lacks face validity for many in those disciplines. (Of course, given that the authors have provided their data and scripts, it would be straightforward for other interested scholars to do this, so I don't insist on this as a condition for giving peer reviewer approval). Author Response: We thank the reviewer for this valuable comment. The reviewer is right in pointing out that certain terms used in the survey may be less applicable to the Arts and Humanities including certain Open Science practices such as open access for specific fields and open sharing of data, syntaxes and codes. However, we wish to point out that many of the RRPs (about 7 of the 11) are not exclusionary to the Arts and Humanities for example RRP 2 “ I took steps to correct errors in my published work whenever I and/or peers provided valid reasons for such a correction”, RRP 5 “I kept a comprehensive record of my research decisions throughout my studies”, RRP 9 “When making use of other people’s ideas, procedures, results and text in my publications, I cited the source accurately in accordance with the standards of my discipline”. We did strive to have face validity of our survey instrument by including a sample of researchers from all four disciplinary fields including the Arts and Humanities in our focus group sessions, in the cognitive testing of the survey instrument (see Methods section, subheading survey instrument) and in our Steering Committee. Whilst we agree that some of the RRPs may truly be not applicable to this discipline, this would not be the case for the majority of the RRPs studied. Because this field is especially understudied in the field of research integrity, we feel it is all the more important to not exclude this group from our results but rather prompt a debate on why this discipline may be so different and that we need greater understanding of this discipline in the research integrity, responsible research and open science debates. Excluding this group from our analysis and study will not help the dialogue on the need for better understanding of the challenges and knowledge production methods in this discipline. 3. Pre-registration I found the pre-registration status of the paper confusing. A link, https://osf.io/2k549, is provided under Data Availability, but that refers to a Belgian pilot study. I think that is probably just an error, but it was extremely confusing and I wasted time wading through that material looking for details of the current questionnaire. Then under 'statistical analysis' I found 'The full statistical analysis plan, and analysis codes were preregistered on the Open Science Framework', and a link to an OSF page that contains data, materials, and analysis scripts, https://osf.io/ehx7q/. This material is well-organised and reasonably easy to navigate, but it does not appear to have been formally pre-registered, in the sense of having a fixed date-stamped version and I could not find a document with the data analysis plan. I did find data-analysis.rmd, which says \"This document contains the analyses as described in NSRI data analysis plan - VERSION 7 - 20120126.docx\", but I could not find that document on the OSF. Apologies if I missed it: hopefully this can be made more prominent, as this is a key aspect for evaluating the analysis. This is an essential point. Author Response: Thank you for your meticulous checking of the links provided under Data availability. We have corrected the link under Data Availability with the correct link: https://osf.io/dp6zf/.This should have been the correct link listed which when clicked takes you to several subfolders. The data analysis plan can be found under the subfolder: “NSRI Data Analysis > OSF Storage (United States)>NSRI Questionnaire, Raw Data & NSRI Data Analysis Plan. The NSRI Data Analysis Plan is a pdf document which is time stamped as 2021-08-03 03:11PM. 4. Skewed data. For many of the items, data are skewed - in effect, these are items which amount to asking whether the respondent approves of motherhood and apple pie - everyone strongly agrees. I noticed at least one item (I did not check all), in the opposite direction, and this was one which perhaps should have been reverse scored - item F27 - most people responded 1. Some brief discussion of how this might affect results would be warranted - e.g. how does the restriction of range on some scales affect the regression coefficients? Author Response: All scales have been recoded - when applicable - such that they measure in the same direction. In the case for F27 which measures the question: “Publication pressure sometimes leads me to cut corners.” Here, most respondents did respond with a “1” indicating “never” reflecting that most respondents did not tend to favor cutting corners. On skewness and its probably effect on coefficients, this was carefully checked by our statisticians to ensure skewness did not affect our regression coefficients. 5. Treatment of NA responses. We are told that for the regression analysis NA was coded as 1. The justification for this is questionable. My general sense is that it would be preferable to have a smaller sample for whom the survey items were valid (i.e. where NA was not used), rather than to shoehorn all respondents into an analysis which might give a misleading picture. It would be reassuring to readers if the analysis could be repeated by excluding all participants who responded NA, to check how this influenced findings. I see this as essential for clarifying the results. Author Response: Thank you for this comment. We wish to clarify that the “not applicable” values are bonafide missing values. While we understand removing them may seem semantically intuitive, there are valid statistical and procedural reasons why we chose to replace these values with the lowest observed category (1 = Never). Please allow us to explain these here: First, the recoding of “not applicable” to 1 is part of our pre-registered data analysis plan. Second, we did run extensive sensitivity analyses to study the validity of our pre-registered choice. Based on these analyses we concluded that our pre-registered choice is the most valid solution to this issue in this data set i.e. we deliberately chose recoding NAs into 1 as we know the direction of any potential bias: it underestimates the true effect, thereby limiting the statistical power of our analysis. Despite this we still found some effects.These sensitivity analyses can be found in the OSF data analysis folder> subfolder entitled “Figures and Tables> Table 3 Regressions”: https://osf.io/ehx7q/. Third, replacing “not applicable” with the value 0 is not a bonafide value that could have been observed. Using non-bonafide constants to fill in missing values is unreliable and statistically invalid. As such filling in zero would underestimate any parameters to a much greater extent than using a bonafide observed value would. We believe inducing such deliberate bias would therefore be undesirable. Fourth, coding “not applicables” as zero yields a positive correlation between QRP and RRP in a confirmatory factor analysis. This is counterintuitive and not in line with theoretical, nor practical expectations. Coding the “not applicables” as 1 (or any other bonafide observed value, for that matter) yields an expected negative correlation between the factors QRP and RRP. Lastly, the validity of our pre-registered data analysis plan with respect to the “not applicable” has been confirmed by two independent replications on two different data structures reference: De Koning and Van der Sluis (2021). Modeling not applicable answers when data are incomplete. Master Thesis. Utrecht University. To ensure this is also explained in the Limitations section of the manuscript, we have included this change in the Discussion section: “We have studied other recodes of the NA answers and remain confident that our preregistered choice yields inferences that do not ignore the non-random distributions of the NA answers and do not violate theoretical and practical expectations about the relation between RRP and other studied practices.” 6. Difficulty in getting the sense of the main findings. The underlying motivation for this work includes identification of potential explanatory factors for RRPs, presumably so interventions can be designed to modify these. Yet I could get no sense of how useful various explanatory factors would be, because data are reported largely as regression coefficients and confidence intervals, with the predictors shown on a z-score scale, which I think is derived from a principal component analysis. This would make it difficult for anyone else to use the same survey and try to replicate the results in a new sample - that would be easier if an average score from sets of items were used as an independent variable. Minimally, a measure of effect size, such as percentage of variance explained, would be useful. I had to go to Supplementary Materials to find more detail of basic results of interest, and when I did that there were some anomalies - see point j below. It is a very large and complex dataset and I appreciate that the authors did not want to overwhelm readers with information. Nevertheless, I feel they have gone too far in the direction of economical presentation so that the reader has less of an immediate sense of what the results mean. This is not helped by having Methods placed after Results (see point a below). I was interested, for instance, in understanding more about the unexpected association between work pressure/funding pressure and RRPs. I didn't really understand the authors' explanation 'adherence to RRPs requires a slower, more meticulous approach' - I can see that might increase work pressure because there is more to do, but it wasn't so clear for funding pressure. Why would increased funding pressure increase RRPs? Perhaps funders are these days demanding that evidence of RRPs is shown in proposals? What's interesting though is that some might leap on this finding to justify putting more pressure on researchers, with some kind of 'more pain, more gain' argument. Of course, they could be right! This gets right to the heart of research culture: in the past, many disciplines had a 'survival of the fittest' approach with ECRs - there was an implicit ethos that research was tough, that putting pressure on ECRs would select for the best researchers, with less committed researchers dropping out. If the most committed are also those who adopt new, open practices, then you might get this kind of association. I'm not advocating this as an explanation, which is completely against current ideas of nurturing ECRs to get the best from them! But it is important to get a more detailed picture of what is going on here. Author Response: Thank you for raising this valid important concern. We agree that these findings must be interpreted with caution given the cross sectional nature of our study. We have emphasized this by including a sentence in the Discussion section on this topic which reads as follows “However, given the cross sectional nature of our study, these findings do not indicate causality and must be interpreted with caution” Assuming my plots are accurate, I'd be very cautious about making any general claims about the impact of either Work Pressure or Publication Pressure on the adoption of RRPs. I don't regard it as essential for the authors to add such plots, but I would like to see some discussion of the possible variation across disciplines/ranks, and the substantive importance of the effect sizes in real life. Author Response: Thank you for this thorough analysis on this issue, However, please allow us to explain why the proposed procedure may be cause for concern. Our analysis are based on the pooled inferences obtained after multiple imputation. We use Rubin’s rules (See reference 42, pp. 76) to properly combine parameter estimates and correctly calculate the corresponding variances. Looking at a single imputed data set and interpreting the effects of that set can be dangerous and may lull the analyst into a false sense of discovery . For example, re-running the code snippet on the next imputed data set yields different plots, with different trends and interactions. This is indicative of the sampling and missing data uncertainty in the analysis problem. Rubin’s rules take the maximum likelihood estimate over the imputed sets and increase the variance about the estimates (i.e. the square of the standard error) accordingly. The procedure we followed ensures that the variability and likelihood of the obtained inference after pooling is properly incorporating the missing data and parameter uncertainty associated with the problem. Having said this, we do agree that making general claims that may imply causality is to be avoided. In that light we have included the following sentence at the end of our Discussion section as follows: “Even so, it is important to emphasize that this is a cross-sectional study and therefore does not imply causality.” More minor points I dislike the practice of putting Methods at the end of the paper. I see it as symptomatic of a tendency that the authors want to avoid - treating methods as less important than results. I can't make sense of the results until I have seen the methods. In fact, numerous questions occurred as I read the Results, which then were answered at the end of the paper. So please put this important material in its rightful place, after the introduction. Author Response: We have moved Methods such that it appears after Introduction. The file codebook.rmd does not run. The variable v is length 143, whereas descriptions and values are length 139, so they won't combine in a data frame. Ideally, we just need a document file with this information (I tried the html file, but it did not give sensibly formatted output; a simple .csv would be best). (I'm sure this is easily fixed) Author Response: This discrepancy in length is now fixed and can be viewed here: https://osf.io/2yhpq/ It would be good to have a table showing the breakdown of numbers in each cell formed by cross-classifying by discipline and academic rank. Some information is available on 2-way cross-classification in the supplementary tables, but it is not enough. Author Response: We have included an extra Supplementary Table 1b showing the proportion of respondents by discipline and rank in the supplementary files which can be directly viewed here https://osf.io/wju6e/ p 3, end of Introduction; 'associative' change to 'associated' Author Response: Thank you. We have made this change. Mention how long the survey took to complete: I eventually found this in the online material, but it would be better in text. Author Response: We have included the following sentence in Methods: “We used “missingness by design” to minimize survey completion time resulting in a total of 20 minutes on average for completion” p 3. It seems odd to say that there were 6813 completed surveys out of 63,778 emails and then describe a 21% response rate. I assume this reflects the fact that for non-supporting institutions, you do not know if emails were correct? Just a word of explanation is needed here. Author Response: We have included a reference to Supplementary Figure 1a which provides the reader with a full and detailed explanation on how we derived the 21% response proportion. The changes made now read as follows: “This percentage was derived by dividing total number of eligible individuals who opened the survey invitation (4414) by the total number of individuals who were invited from the eight supporting institutions (20879). Extended Figure 1a20 provides a detailed explanation of this calculation” Is Extended Data the same as Supplementary Materials? I assume it is and refers to the material I found at this link: https://osf.io/w9vhc/. Author Response: Yes, this is correct. Extended Data is how F1000 refers to supplementary materials. Why is Supplementary Table 1b not in the main text? This seems like key information from the survey, which readers will want to have readily available without needing to open supplementary documents from a link. Author Response: In our previous submission of this work to a different journal, there were restrictions on the number of tables and figures allowed in the main text as well as word limits, hence we had to make choices on the most important Tables and Figures and results to discuss. As part of this we moved Table 1b to extended data which we prefer to leave as is given F1000 whilst not having a Figures and Table limit does have a word limit which we are already at. Similarly, I felt that to get a sense of the data, I needed to see the items corresponding to the scales shown in Supplementary Table 1b. These should be included in the main text. Given the length of our manuscript, including Supplementary 1b which is already rather large to also now show all items per scale we felt would make the Table even larger and cumbersome. We, therefore, included it as a supplementary table.As for the items in each scale, these are presented Supplementary Table 5 to make it easier for the reader to digest all the information we have included in the entire manuscript. Supplementary Figure 2 would also be worth including in the main text, but it needs a key indicating what each of the RRP codes is. The order of the codes seems different from the order in which each RRP is mentioned in the Tables. This figure illustrates the skew that I mentioned that affects especially Scientific Norms (I assume RRP1?) and RRP9 and RRP11. I tried to work out which scales were RRP9 and RRP11 by looking for scales with means above 5 (since most responses in Fig 2 are 6 and 7 for these scales), but there weren't any others than Scientific Norms, so this again is confusing and needs clarifying. I eventually worked it out by comparing the main paper Table 1 and the Supplementary material, but I am still confused as to why the mean scores for F9 and F11 are not higher in Supplementary Table 1b. Author Response: We wish to clarify that the eleven RRPs (dependent variables) shown in Supplementary Figure 2 are NOT the explanatory factor scales (independent variables). It appears that perhaps there was some confusion in the review with RRPs no. 1-11 (as shown in supplementary Figure 2) and with the 10 explanatory factors scales shown in supplementary Table 1b.Scientific Norm Subscription for example which the reviewer makes reference to is not an RRP but one of the 10 explanatory factor variables. Figure 2 show the distribution of respondent answers on the Likert answer scale and not of the explanatory factor scales. I recommend being more cautious in the use of causal language, e.g. talking of 'explanatory factors'. This is observational rather than experimental data, based on self-report, and it is possible that there are subject-specific factors that lead to specific kinds of responses on the 'dependent' variables and also affect reporting of 'independent' predictors. In effect, any reporting biases by participants are confounded with both independent and dependent measures. The difficulty in assigning causality is apparent in the authors' own explanation of why work pressure predicts RRPs - this could actually be because adoption of RRPs makes more work. Author Response: Thank you for this comment. We have included a sentence at the end of the Discussion to this effect which reads as follows: “Even so, it is important to emphasize that this is a cross-sectional study and therefore does not imply causality.”" } ] } ]	1	https://f1000research.com/articles/11-471
https://f1000research.com/articles/10-374/v1	11 May 21	{ "type": "Method Article", "title": "satuRn: Scalable analysis of differential transcript usage for bulk and single-cell RNA-sequencing applications", "authors": [ "Jeroen Gilis", "Kristoffer Vitting-Seerup", "Koen Van den Berge", "Lieven Clement", "Jeroen Gilis", "Kristoffer Vitting-Seerup" ], "abstract": "Alternative splicing produces multiple functional transcripts from a single gene. Dysregulation of splicing is known to be associated with disease and as a hallmark of cancer. Existing tools for differential transcript usage (DTU) analysis either lack in performance, cannot account for complex experimental designs or do not scale to massive scRNA-seq data. We introduce satuRn, a fast and flexible quasi-binomial generalized linear modelling framework that is on par with the best performing DTU methods from the bulk RNA-seq realm, while providing good false discovery rate control, addressing complex experimental designs and scaling to scRNA-seq applications.", "keywords": [ "RNA-seq", "single-cell transcriptomics", "splicing", "differential transcript usage", "statistical framework", "satuRn" ], "content": "Introduction\n\nStudying differential expression (DE) is one of the key tasks in the downstream analysis of RNA-seq data. Typically, DE analyses identify expression changes on the gene level. However, the widespread adoption of expression quantification through pseudo-alignment,1,2 which enables fast and accurate quantification of expression at the transcript level, has effectively paved the way for transcript-level analyses. Here, we specifically address differential transcript usage (DTU) analysis, one type of transcript-level analysis that studies the change in relative usage of transcripts/isoforms within the same gene. DTU analysis holds great potential: previous research has shown that most multi-exon human genes are subject to alternative splicing and can thus produce a variety of functionally different isoforms from the same genomic locus.3–5 The dysregulation of this splicing process has been reported extensively as a cause for disease,6–9 including several neurological diseases such as frontotemporal dementia, Parkinsonism and spinal muscular atrophy, and is a well-known hallmark of cancer.10\n\nIn this context, full-length single-cell RNA-Seq (scRNA-seq) technologies such as Smart-Seq211 and Smart-Seq312 hold the promise to further increase the resolution of DTU analysis from bulk RNA-seq data towards the single-cell level, where differences in transcript usage are expected to occur naturally between cell types. However, only a few bespoke DTU methods have been developed for scRNA-seq data and they lack biological interpretation. Indeed, methods specifically developed for scRNA-seq data are either restricted to exon/event level13,14 analysis (e.g. pinpointing exons involved in splicing events), or they can only pinpoint DTU genes without unveiling the actual transcripts that are involved.15 Interestingly, many DTU methods for bulk RNA-seq do provide inference at the transcript level and their performance has already been extensively profiled in benchmark studies.16–18 Based on a subset of the simulated RNA-seq dataset from Love et al.18 (see Methods), we show the performance of six DTU tools; DEXSeq,19 DoubleExpSeq,20 DRIMSeq,21 edgeR diffSplice,22 limma diffSplice23 and NBSplice24 (Figure 1A). DEXSeq and DoubleExpSeq have a higher performance than the other methods. In addition, we observe that most methods, and DRIMSeq in particular, fail to control the false discovery rate (FDR) at its nominal level, which is in line with previous reports.16–18\n\nA: Performance evaluation on the simulated bulk RNA-Seq dataset from Love et al.18 Each curve displays the performance of each method by evaluating the sensitivity (true positive rate, TPR) with respect to the false discovery rate (FDR). The three circles on each curve represent working points when the FDR level is set at nominal levels of 1%, 5% and 10%, respectively. The circles are filled if the empirical FDR is equal or below the imposed FDR threshold. DEXSeq and DoubleExpSeq clearly have the highest performances. Note that most methods, and DRIMSeq in particular, fail to control the FDR at its nominal level. B: Scalability with respect to the number of cells in a scRNA-Seq dataset. While all other methods scale linearly with an increasing number of cells, DEXSeq scales quadratically. As such, DEXSeq cannot be used for the analysis of large bulk and scRNA-Seq datasets. For all sample sizes, the number of transcripts in the datasets were set at 30.000. Note that NBSplice needed to be omitted from this analysis as it fails to converge on datasets with a large proportion of zero counts (see below). C: Scalability with respect to the number of transcripts in a scRNA-Seq dataset. While all other methods scale linearly with an increasing number of cells, BANDITS scales quadratically. Moreover, BANDITS failed to run on our system for datasets with 7.500 transcripts or more. As such, it had to be omitted from panels A and B. A performance and scalability evaluation of BANDITS on datasets with an (artificial) lower number of transcripts is provided as Extended data figures S1 and S3.25\n\nIn order to assess DTU in single-cell applications, however, these bulk RNA-seq DTU tools should scale to the large data volumes generated by full-length scRNA-seq platforms, which can profile the transcriptome of several thousands of cells26–28 in a single experiment. In Figure 1B, we evaluate the required computational time in function of the number of sequenced libraries for a two-group DTU analysis for 30,000 transcripts on a subset of the scRNA-seq dataset from Chen et al.29 In spite of its good performance, the popular tool DEXSeq already required more than five hours to analyze two groups of 32 cells and clearly does not scale to large bulk nor scRNA-seq datasets.\n\nIn addition, DTU methods should allow for the analysis of datasets with large numbers of (unique) transcripts. The number of transcripts that are typically assessed depends on the coverage of the RNA-seq experiment and the adopted filtering criteria in the data analysis workflow. As the coverage of RNA-seq experiments has increased rapidly over the past few years and can be expected to continue expanding, scalability towards large numbers of transcripts will be essential to enable a transcriptome-wide view on the isoform usage changes. In Figure 1C, we perform a DTU analysis across a range of transcripts in a two-group comparison with 16 cells each, using the dataset from Chen et al. Here, we observed that the DTU tool BANDITS30 scales particularly poorly to large numbers of transcripts. More specifically, BANDITS did not complete the DTU analysis on the dataset with 7.500 transcripts within 137 hours on our system (see Methods); therefore, larger analyses were omitted. As such, BANDITS had to be omitted from the analyses shown in Figures 1A and 1B. For a performance and scalability evaluation of BANDITS on datasets with an (artificial) lower number of transcripts, we refer to Extended data figures S1 and S3.25\n\nBesides scalability, several other issues arise when porting bulk RNA-seq DTU tools towards scRNA-seq applications. Indeed, modelling scRNA-seq data often requires multifactorial designs, for instance when comparing expression levels across multiple cell types between multiple treatment groups. Accounting for multiple covariates, however, is not implemented in BANDITS, NBSplice and DoubleExpSeq, jeopardizing their utility for (sc-)RNA-seq DTU analysis. Another issue arises with the large numbers of zero counts in scRNA-seq data, which seems to be particularly problematic for NBSplice that fails to converge if the gene-level count of any of the samples or cells is zero. As such, NBSplice could not be evaluated in Figures 1B and 1C.\n\nAltogether, many of the existing DTU analysis tools are not well suited to analyze large bulk RNA-seq and full-length scRNA-seq datasets, leaving the great potential of these data largely unexploited. In light of these shortcomings we developed satuRn, which is an acronym for Scalable Analysis of differential Transcript Usage for RNa-seq data, a novel method for DTU analysis that (i) is highly performant, (ii) provides a good control of the false discovery rate (FDR) (iii) scales seamlessly to the large data volumes of contemporary (sc-)RNA-seq datasets, (iv) allows for modelling complex experimental designs, (v) can deal with realistic proportions of zero counts and (vi) provides direct inference on the biologically relevant transcript level. In brief, satuRn adopts a quasi-binomial (QB) generalized linear model (GLM) framework. satuRn provides direct inference on DTU by modelling the relative usage of a transcript, in comparison to other transcripts from the same gene, between groups of interest. To stabilize the estimation of the overdispersion parameter of the QB model, we borrow strength across transcripts by building upon the empirical Bayes methodology as introduced by Smyth et al.23 In order to control the number of false positive findings, an empirical null distribution is used to obtain the p-values, which are corrected for multiple testing with the FDR method of Benjamini and Hochberg.31 Our method is implemented in an R package available at https://github.com/statOmics/satuRn and will be submitted to the Bioconductor project.\n\n\nMethods\n\nAs input, satuRn requires a matrix of transcript-level expression counts, which may be obtained either through pseudo-alignment using kallisto1 or salmon,2 or by classical alignment-based tools followed by transcript-level quantification (e.g. STAR32,33 and RSEM34). Let Ygti denote the observed expression value for a given transcript t = 1, … , Tg of gene g = 1, ..., G in cell or sample i = 1, … , n. The total expression of gene g in sample i can then be expressed as\n\ni.e. by taking the sum of expression values for all Tg transcripts belonging to gene g in sample i. The usage of transcript t in sample or cell i can then be estimated as\n\nNext, we adopt a quasi-binomial (QB) generalized linear modelling (GLM) strategy to model DTU. As opposed to canonical maximum likelihood models, this quasi-likelihood modelling strategy only requires the specification of the first two moments of the response distribution, i.e. the mean and the variance. We define the mean of the QB model as\n\nIn this notation, ηgti is the expected probability of observing transcript t within the pool of transcripts (1, … , Tg) belonging to gene g in sample i and, as such, corresponds to its expected usage for that sample. We model πgti using a logit link function, where βt is a p x 1 column vector of regression parameters modelling the association between the average usage and the covariates for transcript t. Finally, XiT is a row in the n x p design matrix X that corresponds with the covariate pattern of sample i, with p the number of parameters of the mean model, i.e. the length of vector βt.\n\nThe variance of the QB model can be described as\n\nwith Yg.iπgti1−πgti the canonical variance of the binomial distribution and πgt a transcript-specific overdispersion parameter to describe additional variance in the data with respect to the binomial variance. We adopt the empirical Bayes procedure from Smyth et al.,23 as implemented in the squeezeVar function of the limma Bioconductor R package, to stabilize the estimates of πgt by borrowing information across transcripts, which is adopted in the default edgeR quasi-likelihood workflow for bulk RNA-seq data.22,35 Note that stabilizing the dispersion estimation is particularly useful in datasets with a small sample size.\n\nTaken together, the quasi-binomial thus allows us to model the log-odds of drawing a particular transcript t from the pool of transcripts in the corresponding gene g across samples. The intercept also has an interpretation of a log-odds and the remaining mean model parameters are log-odds ratios, which may thus be interpreted in terms of differential transcript usage. We adopt t-tests that are computed based on the log-odds ratio estimates of the QB model and the posterior variance, as obtained from the empirical Bayes procedure. P-values are computed assuming a t-distribution under the null hypothesis with posterior degrees of freedom calculated as the sum of the residual degrees of freedom and the prior degrees of freedom from the empirical Bayes procedure.\n\nFor bulk analyses, the implementation of satuRn as described above provides a high performance and a good control of the FDR. However, for single-cell datasets we observed that our inference is too liberal (see Extended data25 figure S10), which could suggest that the theoretical null, the t-distribution, is no longer valid. Indeed, in large-scale inference settings, failure of the theoretical null distribution is often observed. Efron36 (Chapter 6) describes four reasons why the theoretical null distribution may fail; failed mathematical assumptions, correlation across features (transcript expression), correlation across subjects (samples or cells), and unobserved confounders in observational studies. To avoid these issues, Efron proposes to exploit the massive parallel data structure of omics datasets to empirically estimate the null distribution of the test statistics.37 To this end, Efron converts the test statistic to z-scores, which should follow a standard normal distribution under the theoretical null, and then proposes to approximate the empirical null distribution with a normal distribution with unknown mean (μ∗) and standard deviation (σ∗), which can be estimated by maximum likelihood on a subset of the test statistics near zero.\n\nAs such, we first convert the two-sided p-values to z-scores according to\n\nwith Φ the cumulative distribution function for the standard normal distribution, pgt the original two-sided p-value indicating the statistical significance of differential usage of transcript t from gene g between the conditions of interest, sign(S) the sign of the t-test statistic S and zgt the resulting z-score. Next, we adopt the maximum likelihood procedure, implemented in the locfdr function of the locfdr R package from CRAN,38 to estimate the mean μ∗ and standard deviation σ∗of the empirical null distribution. Based on these estimates, we recompute the z-scores and corresponding p-values as follows\n\nFinally, the resulting (empirical) p-values are corrected for multiple testing with the FDR method of Benjamini and Hochberg.31 As opposed to the original p-values that were calculated based on the theoretical null distribution for the t-statistics, we found that this procedure allows for a better FDR control in single-cell applications.\n\nTable 1 provides a brief description of the DTU methods that were included in the performance benchmarks of this paper. For more details, we refer to the Extended data and the respective original publications. Note that all methods were run in R3.6.1 using default settings.\n\nColumns 1 to 5 respectively display the name of each method, the package version used, a brief description of each method, the test statistic used for inference on differential transcript usage, and whether the method can handle complex designs, e.g., to incorporate additional covariates such as batch effects. All packages are available from Bioconductor 3.10. Acronyms; NB: negative binomial, GLM: generalized linear model, LRT: likelihood ratio test, DB: double binomial, DM: Dirichlet-multinomial.\n\nWe adopted two different strategies for filtering transcripts in each of the RNA-seq datasets in the performance benchmarks.\n\nThe first filtering strategy uses the filterByExpr function implemented in edgeR.39 This filtering strategy only retains transcripts that have at least an expression level of min.count counts-per-million (CPM, calculated as the number of read counts divided by the total number of reads in the dataset and multiplied by one million) in at least n samples or cells. In addition, the sum of the CPM of the transcript across all cells or samples must be at least min.total.count. For the bulk RNA-seq datasets, we use the default settings (min.count = 10, n = min(10, 0.7sample size of the smallest group in the comparison) and min.total.count = 10). For the scRNA-seq datasets, the settings are adjusted to; min.count = 1 (as requiring a transcript to be expressed in all single-cells is a stringent criterium), n = 0.5sample size of the smallest group in the comparison and min.total.count = 0. In addition, if only one transcript of a gene passes this filtering criterion, it is omitted from the analysis, as DTU analysis is meaningless when only one transcript is retained. As such, we specifically set the parameters to generate a very lenient filtering criterium.\n\nThe second filtering strategy uses the dmFilter function implemented in DRIMSeq.21 This filter is more stringent and specifically designed for DTU analysis. The filtering process can be thought of as proceeding in three steps. Let ns be the number of samples or cells in the smallest group. The first step requires the transcripts to have a count of at least 10 in at least ns samples. The second filtering step requires the transcript to make up at least 10% of the total count of its corresponding gene in at least ns samples. The third filtering step removes all transcripts for which the corresponding gene has a count below 10 in any of the samples or cells in the dataset. Again, if only one transcript of a gene passes this filtering criterion, it is omitted from the analysis.\n\nTo evaluate the performance of the different DTU analysis methods, we first adopt three simulated bulk RNA-seq datasets from previous publications: the simulated dataset from Love et al.18 (dataset 1) and both the Drosophila melanogaster (dataset 2) and Homo sapiens (dataset 3) simulation studies from Van den Berge et al..40 All three datasets were generated based on parameter values obtained from real RNA-seq samples, to mimic real RNA-seq data as close as possible.\n\nNotably, there is a subtle difference in how DTU is introduced between the two simulation frameworks. For dataset 1, the origin of DTU is twofold: On the one hand, DTU was specifically introduced by swapping the transcript-per-million (TPM) abundances between two expressed isoforms. On the other hand, DTU was also obtained as a consequence of introducing DTE, where a single expressed isoform was induced to be differentially expressed at a certain log fold change, which leads to DTU if this transcript belongs to a gene expressing multiple isoforms. For datasets 2 and 3, there is only one source of DTU. The number of differentially used transcripts within a gene was sampled ranging from a minimum of two up to a random number drawn from a binomial distribution with size equal to the number of transcripts and success probability 1/3. DTU was introduced by swapping the TPM abundances between the differentially used transcripts. As such, the latter framework allows for differential usage of multiple transcripts of the same gene, which is not possible with the framework used for generating dataset 1. Additionally, dataset 1 uses salmon2 (version 1.1.0) for estimating transcript-level abundances, whereas datasets 2 and 3 were quantified with kallisto1 (version 0.46.0).\n\nWe evaluate the performance of the different DTU methods on real bulk RNA-seq data, by subsampling a homogeneous set of samples from the large bulk RNA-seq dataset available from the Genotype-Tissue Expression (GTEx) consortium41 release version 8. Nine datasets were generated non-parametrically. More specifically, we first selected samples from adrenal gland tissue that were extracted with the RNA extraction method “RNA Extraction from Paxgene-derived Lysate Plate Based”. From the remaining samples we subsampled nine datasets, comprising three repeats for each of three sample sizes; 5 versus 5, 20 versus 20 and 50 versus 50 samples. Next, DTU is artificially introduced with the swapping strategy that is described in the bulk simulation study paragraph of the Methods section of this paper. The GTEx data was quantified with RSEM34 version 1.3.0.\n\nWe evaluate the performance of the different DTU methods on real scRNA-seq datasets. These scRNA-seq datasets were generated non-parametrically by subsampling a homogeneous set of cells from three real scRNA-seq datasets,26,29,42 after which DTU is artificially introduced by the swapping strategy that is described in the bulk simulation study paragraph of the Methods section of this paper.\n\nFor the dataset of Chen et al.,29 which was used to construct Figures 4 and the Extended data figure S7,25 we selected a homogeneous population of cells by considering only the EpiStem cells of female mice, resulting in a dataset of 120 cells. From this homogeneous population of cells, we then subsampled six datasets, comprising three repeats for each of two sample sizes: 20 versus 20 and 50 versus 50 cells. Next, DTU was artificially introduced with the swapping strategy that is described in the bulk simulation study paragraph of the Methods section of this paper. Finally, we adopted either edgeR or DRIMSeq for filtering.\n\nThe other two scRNA-seq datasets were generated analogously. For the dataset of Tasic et al.,42 which was used to construct Figure S8 (Extended data25), we selected a homogeneous population of cells by considering only the Lamp5 cells in the anterior lateral motor cortex of mice without any eye conditions, resulting in a dataset of 897 cells. After introducing DTU, we randomly subsampled 20, 75 or 200 cells from each group. For the dataset of Darmanis et al.,26 which was used to construct Extended data figure S9, we selected the immune cells that clustered together in tSNE cluster 8 of the original publication, resulting in a dataset of 248 cells. After introducing DTU, we randomly subsampled 20, 50 or 100 cells from each group.\n\nWe perform a DGE analysis on a subset of the Tasic single-cell dataset,42 i.e. between different the cell types originating from the ALM and VISp regions of the glutamatergic L5 IT subclass. We use the quasi-likelihood method of edgeR43 to model the gene expression profiles and additionally adopt the edgeR glmTreat function to test differential expression against a log2-fold change threshold (log2-fold change = 1). Statistical significance was evaluated at the 5% FDR level.\n\nWe assess the performance of different DTU methods on a bulk simulation dataset with scatterplots of the true positive rate (TPR) versus the false discovery rate (FDR), according to the following definitions:\n\nwhere FN, FP and TP denote the numbers of false negatives, false positives and true positives, respectively. The FDR-TPR curves are constructed using the Bioconductor R package ICOBRA version 1.14.0.44\n\nThe scalability benchmark was run on subsets of the Chen scRNA-seq dataset,29 which contains 617 cells in total. For the scalability benchmark with respect to the number of cells in the dataset, we randomly subsample a certain number of cells (8, 16, 32, 64, 128 or 256 cells per group) from the dataset (without introducing DTU or selecting specific homogeneous cell populations). Next, we filter this subsample using the edgeR-based filtering criterion. This was done to remove very lowly abundant transcripts, which may otherwise cause problems in the parameter estimation procedure. From the remaining transcripts, we randomly subsampled to a total of 30,000 transcripts before running the DTU analysis. To allow for a scalability benchmark of BANDITS, which scales poorly to the number of transcripts (Figure 5B), we also generated a dataset with only 1,000 transcripts (see Extended data figure S125).\n\nFor the scalability benchmark with respect to the number of transcripts, we randomly sampled two groups of 16 cells from the dataset. After applying the edgeR-based filter, we sampled eight distinct numbers of transcripts: 1,000, 2,000, 5,000, 10,000, 15,000, 20,000, 25,000, 30,000 and 35,000 prior to the DTU analysis. All scalability benchmarks were run on a single core of a virtual machine with an Intel(R) Xeon(R) CPU E5-2420 v2 (2.20GHz, Speed: 2200 MHz) processor and 30GB RAM.\n\n\nResults\n\nWe first evaluate the performance of our novel DTU method, satuRn, on publicly available simulated and real bulk RNA-seq data, as well as on real scRNA-seq data. In general, we found that the performance of satuRn was at least on par with the performances of the best tools from the literature. In addition, our method controls the FDR closer to the nominal level, on average. Second, we show that satuRn scales towards the large data volumes generated by contemporary bulk and single-cell RNA-seq experiments, allowing for a transcriptome-wide analysis of datasets consisting of several thousands of cells, in only a few minutes. Finally, we analyze a large full-length scRNA-seq case study dataset, where we obtain highly relevant biological results on isoform-level changes between cell types that would have remained obscured in a canonical differential gene expression (DGE) analysis.\n\nTo evaluate the performance of satuRn, we adopt three simulated bulk RNA-seq datasets from previous publications. Dataset 1 was obtained from Love et al.18 and contains two groups of 12 samples each, which we subsample without replacement to evaluate 3vs3, 6vs6 and 10vs10 two-group comparisons. Datasets 2 and 3 are the Drosophila melanogaster and Homo sapiens simulation studies from Van den Berge et al.40 and Soneson et al.,17 which both contain two groups of five samples each. In brief, all datasets were constructed by generating sequencing reads based on parameters that are estimated from real bulk RNA-seq data. DTU between groups of samples was artificially introduced in the data, prior to the quantification of expression using either Salmon2 (dataset 1) or kallisto1 (dataset 2 and 3). Notably, there are some methodological differences between the simulation framework of dataset 1 and that of datasets 2 and 3 with respect to the read generation and the simulation of DTU signal (see Methods). In terms of transcript filtering, we adopt two different strategies as implemented by edgeR43 and DRIMSeq,21 which correspond to a lenient and more stringent filtering, respectively (see Methods).\n\nThe result of the performance evaluation of satuRn with respect to other DTU methods on the three simulated bulk datasets is displayed in Figure 2 Figure 2A shows the average performance over three 6 versus 6 subsamples for dataset 1, after filtering with edgeR. Figures 2B and 2C display the performance on datasets 2 and 3 after edgeR filtering, respectively. In all three datasets, satuRn outperforms NBSplice, edgeR diffsplice and limma diffsplice. Intriguingly, the performance of DRIMSeq varies strongly between the three datasets. This discrepancy may be explained by the different strategies for generating reads and introducing DTU between dataset 1, and, datasets 2 and 3 (see methods). We furthermore find the performance of satuRn is on par with the best performing tools from the literature, DEXSeq and DoubleExpSeq. In addition, both satuRn and DoubleExpSeq provide a stringent control of the FDR, while DEXSeq and DRIMSeq are often too liberal, as reported previously.18\n\nEach curve visualizes the performance of each method by displaying the sensitivity of the method (true positive rate, TPR) with respect to the false discovery rate (FDR). The three circles on each curve represent working points when the FDR level is set at nominal levels of 1%, 5% and 10%, respectively. The circles are filled if the empirical FDR is equal or below the imposed FDR threshold. The performance of satuRn is on par with the best tools from the literature, DEXSeq and DoubleExpSeq, for all datasets. In addition, our method consistently controls the FDR close to its imposed nominal FDR threshold.\n\nWe also evaluated the effects of sample size and different filtering criteria on the performance of the different DTU methods (see Extended data25 figures S2, S3, S4 and S5). Neither sample size nor filtering criterion had a profound impact on the ranking of the performances of the different DTU methods; satuRn, DEXSeq and DoubleExpSeq remain the best performing methods overall. In addition, we studied the impact of using either raw count estimates or normalized abundance estimates (scaledTPM, see Methods) as input data for the DTU algorithms. We observed a slightly higher performance in all datasets when providing raw abundance estimates, except for Dataset 1 from Love et al.18 All performance evaluations in the body of this publication therefore were generated with raw count estimates as input data, except for Figure 2, panel A. For a full overview on the effects of sample size, filtering criteria and data input type, we refer to Figures S2 and S9 of the Extended data.\n\nWhile simulation studies are common for evaluating the performance of DE analysis methods, there is currently no consensus on the simulation strategy that best mimics real (sc)RNA-seq data. In addition, simulation frameworks typically generate data according to parametric assumptions on the data-generating mechanism, thus potentially favoring DE methods that adopt similar distributional assumptions in their statistical model.40 An alternative procedure is to non-parametrically modify a real dataset. Here, we obtained different subsamples from the large bulk RNA-seq dataset available from the Genotype-Tissue Expression (GTEx) consortium,41 generating nine datasets in total, i.e. three repeats for each of three sample sizes; 5 versus 5, 20 versus 20 and 50 versus 50 samples. We then artificially introduced DTU in these data by swapping transcript usages between groups of samples (see Methods for details). Again, we adopt two different filtering strategies as implemented by edgeR43 and DRIMSeq21 (see Methods).\n\nThe results of the performance evaluation of satuRn on the real bulk datasets upon edgeR filtering is displayed in Figure 3. In agreement with the results obtained from the simulated bulk RNA-seq study, we observe that the performance of satuRn is on par with DEXSeq and DoubleExpSeq. Again, satuRn provides a conservative FDR control. While the FDR control of DoubleExpSeq is good overall, it appears to become too liberal with increasing sample size. In this evaluation, DRIMSeq performs poorly, in contrast to simulated bulk RNA-seq datasets 2 and 3, but in line with the performance evaluation on the simulated bulk RNA-seq dataset 1. Note that DEXSeq, DRIMSeq and NBSplice were omitted from the analysis of the largest dataset (50 versus 50 samples), as these methods do not scale to such large datasets (Figure 1). Adopting the DRIMSeq-based filtering did not have a qualitative impact on the performance (Extended data figure S625).\n\nEach curve visualizes the performance of each method by displaying the sensitivity of the method (true positive rate, TPR) with respect to the false discovery rate (FDR). The three circles on each curve represent working points when the FDR level is set at nominal levels of 1%, 5% and 10%, respectively. The circles are filled if the empirical FDR is equal or below the imposed FDR threshold. The performance of satuRn is on par with the best tools from the literature, DEXSeq and DoubleExpSeq. In addition, satuRn consistently controls the FDR close to its imposed nominal FDR threshold, while DoubleExpSeq becomes more liberal with increasing sample sizes. Note that DEXSeq, DRIMSeq and NBSplice were omitted from the larger comparison, as these methods do not scale to large datasets (Figure 1).\n\nFinally, we evaluate the performance of satuRn on single-cell RNA-seq data. As with the real bulk analysis, the single-cell datasets were generated by subsetting from three different real scRNA-seq datasets26,29,42 (see Methods). Again, we subsampled three repeats of different sample sizes, artificially introduced DTU with the swapping strategy and applied either the edgeR- or DRIMSeq-based filtering criterium (see Methods for details).\n\nBy subsampling the Chen et al.29 dataset, we generated three repeats of two sample sizes, i.e. 20 versus 20 and 50 versus 50 cells. The results of the performance evaluation of satuRn on this dataset upon edgeR filtering is displayed in Figure 4. The performance of satuRn is slightly better than that of the best tool from the literature, DoubleExpSeq. As compared to the evaluations on bulk data, we observe a performance drop for DEXSeq relative to satuRn and DoubleExpSeq. This, in combination with its poor scalability (Figure 1), greatly compromises the use of DEXSeq for the analysis of scRNA-seq data. satuRn again provides a stringent control of the FDR, while the inference of DoubleExpSeq is too liberal, again becoming more problematic for larger sample sizes. Adopting the DRIMSeq filter did not have a qualitative impact on the performances (Extended data figure S725). The results of the performance evaluations on the other two scRNA-seq datasets26,42 are in strong agreement with the results displayed here, with satuRn performing at least on par with DoubleExpSeq and satuRn additionally controlling the FDR around the nominal level (Extended data figures S8 and S9).\n\nEach curve visualizes the performance of each method by displaying the sensitivity of the method (true positive rate, TPR) with respect to the false discovery rate (FDR). The three circles on each curve represent working points when the FDR level is set at nominal levels of 1%, 5% and 10%, respectively. The circles are filled if the empirical FDR is equal or below the imposed FDR threshold. The performance of satuRn is on par with the best tools from the literature, DEXSeq and DoubleExpSeq. In addition, our method provides a stringent control of the FDR, while DoubleExpSeq becomes more liberal with increasing sample sizes (see also Extended data figure S625). Note that DEXSeq and DRIMSeq were omitted from the two largest comparisons, as these methods do not scale to large datasets (Figure 1). NBSplice was omitted from all comparisons, as it does not converge on datasets with many zeros, such as scRNA-Seq datasets.\n\nNotably, we found that the theoretical null distribution of the test statistics from satuRn failed to provide good FDR control in single-cell analyses (Extended data figure S1025). To obtain proper p-values with satuRn in single-cell applications, we therefore estimate the null distribution of the test statistic empirically (see Methods, satuRn paragraph). Note, that the use of the empirical null distribution in our bulk RNA-seq benchmarks does not affect the results because no deviations of the theoretical null distribution occur. However, the empirical null resulted in much improved FDR control in scRNA-seq datasets (Extended data figure S10). We therefore adopt the empirical null estimation as the default setting in satuRn. As such, all satuRn results in this publication are relying on the empirical null strategy. As a final remark, we likewise attempted to improve the FDR control of DoubleExpSeq. However, in all analyses with DoubleExpSeq we observed a large spike of p-values equal to 1, which poses a problem when estimating the empirical null distribution (Extended data figure S11). Therefore, this strategy could not be used to improve the FDR control of DoubleExpSeq.\n\nWe performed a computational benchmark of satuRn to investigate its scalability with respect to the number of samples/cells and the number of transcripts in an RNA-seq dataset. All scalability benchmarks were run on a single core of a Linux machine with an Intel(R) Xeon(R) CPU E5-2420 v2 (2.20GHz, Speed: 2200 MHz) processor and 30GB RAM. The results are displayed in Figure 5.\n\nLeft panel: it is clear that DRIMSeq and especially DEXSeq scale very poorly with the number of cells in the dataset. Right panel: Detailed plot of the remaining methods. satuRn scales linearly with increasing numbers of cells, with a slope that is comparable to that of limma diffsplice. As such, satuRn is able to perform a DTU analysis on a dataset with two groups of 256 cells each and 30,000 transcripts in less than three minutes. For all sample sizes, the number of transcripts in the datasets were set at 30,000. Note that NBSplice was not included in this analysis as it fails to converge on datasets with a large proportion of zero counts. B: Runtime with respect to the number of transcripts in a scRNA-Seq dataset. Left panel: DEXSeq, DRIMSeq and especially BANDITS scale poorly to the number of transcripts in the dataset. Right panel: Detailed plot of the remaining methods. satuRn scales linearly with increasing numbers of transcripts, but with a steeper slope than edgeR diffsplice, DoubleExpSeq and limma diffsplice. The number of cells in the dataset was set fixed to two groups of 16 cells. All scalability benchmarks were run on a single core.\n\nFigure 5A displays the scalability with respect to the number of cells in the dataset, while keeping the number of transcripts in the dataset fixed at 30,000. From the left panel, it is clear that DRIMSeq and especially DEXSeq scale very poorly with the number of cells in the dataset, which was already shown in Figure 1B. In the right panel, we focus on the four remaining methods. satuRn scales linearly with increasing numbers of cells, with a slope comparable to limma diffsplice. As such, satuRn is able to perform a DTU analysis on a dataset with two groups of 256 cells each and 30,000 transcripts in less than three minutes. Note that BANDITS30 was not included in this benchmark, as it does not scale to datasets with this many transcripts. For a performance and scalability evaluation of BANDITS on datasets with a lower number of transcripts, we refer to Extended data figure S1.25 NBSplice was also omitted as it fails to converge on datasets with a large proportion of zero counts.\n\nFigure 5B shows the scalability with respect to the number of transcripts in the dataset, while keeping the number of cells in the dataset fixed to two groups of 16 cells. As shown in Figure 1C, BANDITS, DEXSeq and DRIMSeq scale poorly to datasets with many transcripts. From the right panel, satuRn scales linearly with increasing numbers of transcripts, albeit with a steeper slope than edgeR diffsplice, DoubleExpSeq and limma diffsplice. Note, that the scalability of DTU analyses can be improved through parallelization, if this is allowed by the underlying algorithm. Parallel execution is implemented in satuRn and in all methods from the literature that were discussed in this manuscript, except for DoubleExpSeq and NBSplice.\n\nAltogether, we find that while several methods for DTU analysis exist, none are optimally suited for analyzing single-cell datasets. DRIMSeq, NBSplice, edgeR diffsplice and limma diffsplice have a much lower overall performance in our benchmarks. DEXSeq does not scale to large datasets. Finally, DoubleExpSeq does not support experimental designs that require an analysis with multiple additive effects, e.g. randomized complete block designs and designs where batch-effect correction is required, which are essential for many practical scRNA-Seq analysis settings.45 In addition, it fails to control the FDR at the desired level, especially with increasing sample sizes.\n\nWe use satuRn to perform a DTU analysis on a subset of the single-cell (SMART-seq211) RNA-seq dataset from Tasic et al.42 In addition, we analyze the same dataset with DoubleExpSeq and limma diffsplice, which are the only other DTU methods that scale to large scRNA-seq datasets and have a reasonable performance in our benchmarks. In the original publication, the authors studied differential gene expression between cell types originating from two areas at distant poles of the mouse neocortex; the primary visual cortical area (VISp), which processes sensory information with millisecond timescale dynamics46–48 and the anterior lateral motor cortex (ALM), which displays slower dynamics related to short-term memory, deliberation, decision-making and planning.49,50 Based on marker genes, Tasic et al.42 assigned all of the 23,822 cells from the scRNA-seq dataset to one of three cell classes; glutamatergic (excitatory) neurons, GABAergic (inhibitory) neurons or non-neuronal cells. The authors then further classified the neuronal cells into several subclasses based on their dominant layer of dissection and projection patterns (through a retrograde labelling experiment). Finally, these subclasses are further classified into cell types based on the expression of specific marker genes.\n\nIn their original DGE analysis, Tasic et al.42 obtained the largest number of differentially expressed genes between the cell types originating from the ALM and VISp regions of the glutamatergic L5 IT subclass (2,739 cells in total), where L5 refers to layer-of-dissection 5 and IT refers to the intratelencephalic projection type. Here, we first perform a DGE analysis with an edgeR-based workflow (see Methods) on the same comparisons between L5 IT cell types that were assessed by Tasic et al. Table 2 shows the number of differentially expressed genes between the groups of interest in column 4.\n\nNext, we perform a DTU analysis for the same cell types using satuRn. In column 5 of Table 2, we display the number of differentially used transcripts for each comparison. We also show the number of unique genes in which we find evidence for changes in usage of at least one transcript (column 6). While the number of differentially used transcripts is lower than the number of differentially expressed genes in each of the contrasts, we did identify differentially used transcripts in all contrasts of interest. Most interestingly, we observe that the overlap between the differentially expressed genes and the genes in which we found evidence for DTU is very limited (Table 2, column 7). This shows that the information obtained from our DTU analyses are orthogonal to the results from the canonical DGE analyses, which has been reported previously for simulated bulk data.18\n\nThe first three columns indicate the comparisons between ALM (column 2) and VISp (column 3) cell types, respectively. Column 4 indicates the number of differentially expressed genes as identified with an edgeR analysis. Column 5 displays the number of transcripts that satuRn flagged as differentially used. Column 6 shows the number of unique genes in which satuRn finds evidence of differential usage of at least one transcript. Column 7 displays the absolute number of genes that overlap between columns 4 and 6.\n\nWe perform a gene set enrichment analysis (GSEA51) on the three comparisons with most DE genes and most genes with evidence for DTU (comparisons 5, 6 and 7). Similar gene ontology categories are returned for the set of DGE genes and the set of DTU genes, with many of the enriched processes being biologically relevant in the context of this case study. Enriched gene sets include the gene ontology classes, synapse, neuron projection, synaptic signaling and cell projection organization. This shows that the complementary information brought by the DTU analysis is indeed biologically relevant. For an extensive overview of the GSEA of the set of DGE genes and genes with evidence of DTU in comparisons 5, 6 and 7, we refer to the Extended data.25\n\nTo display the utility of satuRn for identifying and visualizing DTU transcripts in scRNA-seq datasets, we focus on comparison #6 of the DTU analysis and discuss the gene P2X Purinoceptor 4 or P2rx4 (Ensembl ID ENSMUSG00000029470), alsb gene which is part of a family of purinergic receptors that have been implicated in functions such as learning, memory and sleep. In the DGE analysis, no evidence for differential expression of P2rx4 was found at the gene level (FDR-adjusted p-value = 1). By contrast, in our DTU analysis the transcripts of P2xr4 displayed the highest statistical evidence for differential usage within the set of transcripts that could be assigned to the ontology class ‘neuron projection’.52 The mean usage of transcript ENSMUST00000081554 is estimated to be 28.9% in Tnc cells and 75.9% in Hsd11b1 Endou cells (FDR-adjusted p-value = 1.22E-13). For transcript ENSMUST00000195963, the transcript usage changes from 58.2% in Tnc cells and 16.6% in Hsd11b1 Endou cells (FDR-adjusted p-value = 1.79E-10). For the third transcript of P2rx4 that was assessed in our DTU analysis, ENSMUST00000132062, we found no statistical evidence for DTU (FDR-adjusted p-value = 0.534). In Figure 6, we show the output for the visualization of the transcript usages for P2rx4 as obtained from satuRn. Interestingly, the majority transcript in the Tnc cell type, ENSMUST00000195963, is not protein coding.53 By contrast, the majority transcript in the Hsd11b1 Endou cell type, ENSMUST00000081554, is coding for the P2X purinoceptor protein (UniProt ID Q9Z256). As such, the changes in transcript usage between both cell types represent actual biological differences in the functionality of the gene products, which may be relevant to the process of neuron projection. This functional difference would have remained obscured when only performing a canonical DGE analysis.\n\nEach panel shows transcript usage or gene expression across cells of the Tnc and Hsd11b1 cell types. For the transcript-level figures, the size of each datapoint is weighted according to the total expression of the gene in that cell, i.e. the gene counts per cell. The yellow diamonds indicate the estimated mean usage of a transcript for each cell type, as estimated by satuRn. The cyan and dark green diamonds indicate mean and median gene expression levels per cell type, respectively. The two top panels display the transcript usage across cells of the Tnc and Hsd11b1 Endou cell types of transcripts ENSMUST00000081554 and ENSMUST00000195963, respectively. The proportion of usage of the former transcript is clearly higher in Hsd11b1 Endou cells, while the latter transcripts is most abundant in Tnc cells. For the third transcript, ENSMUST00000132062 (bottom left panel) there is no evidence for differential usage between both cell types. In addition, there is no evidence for differential expression of P2rx4 on the gene level (bottom right panel). DTU and DGE significance levels are indicated in the figure headers.\n\nWe also analyzed the case study dataset with limma diffsplice.23 When running limma diffsplice with default settings, a large number of DTU transcripts was returned (Extended data figure S1225) and we observe that the p-values were shifted towards smaller values (Extended data figures S13 and S14). Therefore, we adopted the same empirical null strategy as implemented in satuRn to post-process the results. While this dramatically decreased the number of significant DTU transcripts, limma diffsplice still identified more transcripts (i.e. true or false positives) than our method. However, when we inspected the transcripts that were highly ranked in the top DTU list of limma diffsplice but lowly ranked in our top list, we found that most of these transcripts either originate from genes that are lowly expressed, or they are transcripts with a large fraction of zero counts (i.e. zero expression in a large percentage of cells). Limma diffsplice thus claims differential usage more often for transcripts that only contain little information for assessing DTU. This is depicted in Figure 7.\n\nLeft panel: Boxplots on the average gene-level count for the DTU genes identified by the respective methods. Transcripts uniquely identified by satuRn originate from genes that have a much higher gene-level count (averaged over cells) as compared to transcripts uniquely identified by limma diffsplice. Note that the y-axis is displayed on a log10 scale. Right panel: Violin plots indicating the fraction of cells in which the transcripts are expressed. Transcripts uniquely identified by satuRn are expressed, on average, in a much larger fraction of the cells. Conversely, transcripts identified as DTU uniquely by limma diffsplice often have no expression in a large fraction of the cells. The dark green diamond indicates the median fraction of cells in which the DTU transcripts are expressed.\n\nThis behavior can be expected. Limma diffsplice tests for DTU by comparing the log-fold change in expression of transcript t with the average log-fold change in the expression of all transcripts belonging to the same gene as transcript t. As such, limma diffsplice does not incorporate any information on the absolute gene expression levels. In contrast, our quasi-binomial GLM framework models the log-odds of drawing a particular transcript t from the pool of transcripts in the corresponding gene. As a consequence, transcripts belonging to lowly expressed genes are correctly considered less informative in satuRn and are thus less likely to be picked up. For example, in Figure 8A, we show that while our method estimates a mean usage of 7% in Tnc cells and 26% in Hsd11b1 Endou cells (indicated by the gold diamond), the transcript is not identified as differentially used, given the low abundance of the corresponding gene and the highly variable single-cell level observations.\n\nEach panel shows transcript usage across cells of the Tnc and Hsd11b1 cell types. The size of each datapoint is weighted according to the total expression of the corresponding gene in that cell, i.e. the total gene count per cell. The yellow diamonds indicate the estimated mean usage of a transcript for each cell type, as estimated by satuRn. The cyan diamonds indicate the mean transcript expression levels per cell type. The header of each panel indicates the FDR-adjusted p-value and the rank of the DTU finding in the top lists by limma diffsplice and satuRn analyses. Panel A: Transcript uniquely identified as differentially used by limma diffsplice. The DTU claim by limma is driven by the difference in mean transcript usage between cell types. Given the low abundance of the corresponding gene and the highly dispersed single-cell level observations, satuRn does not identify the transcript as differentially used. Panel B: Transcript uniquely identified as differentially used by satuRn. Even though the mean difference in transcript usage between cell types is estimated to be 3%, satuRn claims significance given that the difference is stably supported by many cells with high gene-level expression levels. Panel C: Transcript uniquely identified as differentially used by limma diffsplice. The DTU claim by limma is driven by the raw mean difference in transcript usage between cell types. In contrast, satuRn takes into account that the Hsd11b1 Endou cells expressing the transcript at 0% usage have low gene-level count. The size of the dots (which represent individual cells) is weighted according to the total expression of the gene in that cell, i.e. the total gene count per cell. The yellow diamonds indicate the estimated mean usage of a transcript for each cell type, as estimated by satuRn. The cyan diamonds indicate the raw mean transcript usage levels per cell type.\n\nConversely, by looking at the transcripts that were highly ranked in our DTU list but lowly ranked in the top list of limma, we observe that our model is more likely to capture small changes in transcript usage that are stable across all cells and belong to genes that are highly expressed. An example of such a transcript is shown in Figure 8B. satuRn estimates a mean usage of 3% in Tnc cells and 6% in Hsd11b1 Endou cells. While this is only a minor change in transcript usage, satuRn still identifies this transcript as differentially used because the gene is highly expressed and the small change in usage is supported by a large number of cells. In case such small differences in usage are not considered biologically meaningful, it is possible to set a threshold on the minimal desired difference. Finally, by not taking into account gene abundances, limma is more influenced by outlying observations that have a low gene-level abundance (Figure 8C). Indeed, DTU claims by limma are driven by differences in raw mean usages of transcripts. In Figure 8C, the raw mean usage of the transcript is 77% in Tnc cells and 45% in Hsd11b1 Endou cells, as indicated by the cyan diamonds. By contrast, the mean usage estimate by satuRn, which takes into account that the Hsd11b1 Endou cells expressing the transcript at 0% usage have low gene-level count, is 83% for Tnc cells and 75% for Hsd11b1 Endou cells, as indicated by the gold diamonds.\n\nWe therefore argue that, given the above observations, the transcripts identified by satuRn should be considered more reliable, as they generally originate from genes containing more information for assessing DTU.\n\nWe additionally analyzed the dataset by Tasic et al. with DoubleExpSeq.20 DoubleExpSeq identified a large number of DTU transcripts in all eight comparisons between cell types, ranging from 335 to 4580 DTU transcripts (Extended data figure S1225). This is consistent with our performance benchmarks, which already suggested that DoubleExpSeq becomes overly liberal in single-cell datasets with a large number of cells (Figures 4, Extended data figures S7, S8 and S9). We therefore expect many of these transcripts to correspond to false positives. Furthermore, this is reflected in the pathological distribution of p-values obtained by DoubleExpSeq, where p-values have a tendency to be small and therefore the analysis too liberal (Extended data figure S15). Furthermore, as discussed in the benchmark studies, we could not adopt the empirical null strategy to improve the FDR control of DoubleExpSeq. Again, a large number of p-values equal 1 poses a problem for estimating the empirical null distribution (Extended data figure S16).\n\nWhile the results of DoubleExpSeq are likely to be overly liberal, the ranking of the transcripts (based on the p-values of the DTU analysis) might still be reasonable. In Figure 9 we observe a large overlap between the top 200 transcripts identified by satuRn in comparison #6 of the case study and the top 200 transcripts of DoubleExpSeq in that comparison. This overlap is considerably smaller with a limma diffsplice analysis.\n\nWe observe that in the set of the top 200 transcripts identified by satuRn, 149 transcripts overlap with the top 200 list from DoubleExpSeq. In the top 200 list of limma diffsplice, 108 transcripts are present that were not in the top lists of satuRn or DoubleExpSeq.\n\nFinally, we note that while DoubleExpSeq could still be used in this case study given the simple factorial design (using a single factor to assign each cell to a cell type), DoubleExpSeq cannot be used in multifactorial designs, for instance to compare expression levels across multiple cell types between multiple samples or treatment groups.\n\n\nDiscussion\n\nIn this manuscript, we have proposed satuRn, a new software tool for DTU analysis. satuRn adopts a quasi-binomial GLM framework and obtains direct inference on DTU by modelling the relative usage of a transcript, in comparison to other transcripts from the same gene, between conditions of interest. We evaluated the performance of satuRn with respect to seven other DTU methods on three simulated bulk RNA-seq datasets, a real bulk RNA-seq dataset and three real scRNA-seq datasets. These benchmarks underscored the strong performance of satuRn, as well as its ability to control the FDR close to the nominal level. In addition, we showed that satuRn scales seamlessly to the large data volumes that are produced in contemporary (sc-)RNA-seq experiments. Furthermore, given the underlying GLM framework, our method can handle complex experimental designs that are commonplace in scRNA-seq experiments. Finally, satuRn can extract biologically relevant information from a large scRNA-seq dataset that would have remained obscured in a canonical DGE analysis.\n\nSince most sequencing reads map to multiple transcripts, quantification tools such as Salmon or kallisto only provide an estimate of the expected number of fragments originating from each transcript. Incorporating quantification uncertainty has recently been shown to improve results in differential expression analysis of single-cell RNA-seq datasets.54 Currently, satuRn and all other DTU methods discussed in this manuscript, except for BANDITS,30 neglect the uncertainty on this abundance estimate. BANDITS models the abundance uncertainty; however, it had a markedly lower performance than our method in our benchmark evaluation (Extended data figure S125).\n\nOne challenge common to all DTU methods is that the power to detect differentially used transcripts depends strongly on the quality of the scRNA-seq dataset. This becomes clear when comparing the performances for the three different scRNA-seq benchmarks in this manuscript. The performances on the Darmanis26 dataset (Extended data figure S9) are markedly lower than the performances on the other two datasets (Figure 4 and Extended data figure S8). A closer inspection of the Darmanis dataset showed that, after filtering, the transcript-level counts matrix contains a much larger percentage of zero counts than the other datasets. We also more frequently observed the scenario where the expression level of a gene could be attributed to a single isoform. This effectively causes the transcript usage to appear binary, with either 0% or 100% usages of a certain transcript. We argue that while this may reflect the true underlying biology, for instance through the process of transcriptional bursting,30 it is more likely to be a technical artefact as a consequence of more shallow sequencing, given the lower percentage of binary usage profiles in the Chen and Tasic datasets. The supposedly binary expression of transcripts due to coverage-dependent bias and the use of more stringent filtering criteria to reduce this bias has already been comprehensively reported by Najar et al.57\n\nWe conclude with the following recommendations for DTU analysis from an applied perspective. In case of small bulk RNA-seq datasets, satuRn, DEXSeq and DoubleExpSeq can be used interchangeably. In case of datasets with more complex designs that require the DTU model to incorporate additional covariates, e.g. batch effects, DoubleExpSeq cannot be used. For single-cell datasets, using DEXSeq will become infeasible in terms of scalability and DoubleExpSeq may give overly liberal results. As such, we recommend satuRn for performing DTU analyses in large bulk and single-cell RNA-seq datasets.\n\n\nData availability\n\nZenodo: Datasets associated with this publication https://doi.org/10.5281/zenodo.4439415.58\n\nThis project contains the following underlying data:\n\n- Case_study.zip (Transcript-level expression count matrix Tasic_caseStudy_transcript_counts.Rds and corresponding metadata files Tasic_metadata_1.xlsx and Tasic_metadata_2.csv of a subset of the dataset by Tasic et al.42)\n\n- Performance_Chen.zip (Transcript-level expression matrices Chen_counts.Rds and Chen_scaledTPM.Rds, as well as the corresponding metadata file Chen_metadata.csv of the dataset by Chen et al.29)\n\n- Performance_Darmanis.zip (Transcript-level expression count matrix Darmanis_counts.Rds and the corresponding metadata file Darmanis_metadata.Rdata of the dataset by Darmanis et al.26)\n\n- Performance_Dmelanogaster.zip (Dmelanogaster_kallisto is a folder containing the full output of the quantification of the Dmelanogaster dataset40 as quantified with kallisto1 version 0.46.0. The corresponding metadata can be retrieved from Dmelanogaster_metadata_1.txt and Dmelanogaster_metadata_2.txt.)\n\n- Performance_GTEx.zip (Transcript-level expression matrices GTEx_counts.gz and GTE_scaledTPM.gz, as well as the corresponding metadata file GTEx_metadata.txt of the GTEx dataset.41)\n\n- Performance_Hsapiens.zip (Hsapiens_kallisto is a folder containing the full output of the quantification of the Hsapiens dataset40 as quantified with kallisto1 version 0.46.0. The corresponding metadata can be retrieved from Hsapiens_metadata_1.txt and Hsapiens_metadata_2.txt.)\n\n- Performance_Love.zip (Love_kallisto is a folder containing the full output of the quantification of the dataset by Love et al.18 as quantified with salmon2 version 0.1.0. The corresponding metadata can be retrieved from Love_metadata.rda. Effective transcript length estimates for BANDITS30 are available from Love_eff_len.rds.\n\n- Performance_Tasic.zip (Transcript-level expression matrices Tasic_counts.Rds and Tasic_scaledTPM.Rds, as well as the corresponding metadata files Tasic_metadata_1.xlxs and Tasic_metadata_2.csv of a subset of the dataset by Tasic et al.42)\n\n- Scalability_analysis.zip (Several.Rdata files containing the scalability results of the different DTU tools on datasets of different sizes.)\n\nIn addition, all folders except Scalability_analysis.zip contain intermediate DTU analysis results that are available as.Rdata files or, in the case of Case_study.zip, .Rds files. Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\nZenodo: Extended data for satuRn publication https://doi.org/10.5281/zenodo.4672628.25\n\nThis project contains the following extended data:\n\n- Supplementary_Figures.pdf: The supplementary figures to the satuRn publication, including figure captions.\n\n- DTU_Methods_Detail.pdf: A.pdf text file that describes the different DTU tools that were included in our benchmarks in greater detail as compared to the description in our main publication. For even higher detail, we refer to the respective original publications.\n\n- GSEA_MSigDB.xlsx: The output of the Gene Set Enrichment Analyses (GSEA) for the case study of our publication as generated by the online MSigDB platform.\n\nLicense: Data are available under the terms of the CC-BY 4.0 license.\n\n\nSoftware availability\n\nSource code available from: https://github.com/statOmics/satuRn\n\nArchived source code at time of publication: https://doi.org/10.5281/zenodo.4656084.59\n\nLicense: Data are available under the terms of the CC-BY 4.0 license.\n\nCode to reproduce analyses and figures available from: https://github.com/statOmics/satuRnPaper\n\nArchived analysis code at time of publication: https://doi.org/10.5281/zenodo.4655310.60\n\nLicense: Data are available under the terms of the CC-BY 4.0 license.", "appendix": "Acknowledgements\n\nThe authors would like to thank Milan Malfait for his suggestions and comments throughout this project. We also note that an earlier version of this article can be found in bioRxiv. 61\n\n\nReferences\n\nBray NL, Pimentel H, Melsted P, et al.: Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 2016; 34: 525–527. PubMed Abstract \| Publisher Full Text\n\nPatro R, Duggal G, Love MI, et al.: Salmon: fast and bias-aware quantification of transcript expression using dual-phase inference. Nat. Methods. 2017; 14: 417–419. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWang ET, et al.: Alternative isoform regulation in human tissue transcriptomes. Nature. 2008; 456: 470–476. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPan Q, Shai O, Lee LJ, et al.: Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat. Genet. 2008; 40: 1413–1415. PubMed Abstract \| Publisher Full Text\n\nTrapnell C, et al.: Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 2010; 28: 511–5. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKelemen O, et al.: Function of alternative splicing. Gene. 2013; 514: 1–30. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWard AJ, Cooper T: The pathobiology of splicing. J. Pathol. 2010; 220: 152–163. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWang GS, Cooper TA: Splicing in disease: Disruption of the splicing code and the decoding machinery. Nat. Rev. Genet. 2007; 8: 749–761. PubMed Abstract \| Publisher Full Text\n\nHallegger M, Llorian M, Smith CWJ: Alternative splicing: Global insights. FEBS J. 2010; 277: 856–866. PubMed Abstract \| Publisher Full Text\n\nOltean S, Bates DO: Hallmarks of alternative splicing in cancer. Oncogene. 2014; 33: 5311–5318. PubMed Abstract \| Publisher Full Text\n\nPicelli S, et al.: Full-length RNA-seq from single cells using Smart-seq2. Nat. Protoc. 2014; 9: 171–181. PubMed Abstract \| Publisher Full Text\n\nHagemann-Jensen M, et al.: Single-cell RNA counting at allele and isoform resolution using Smart-seq3. Nat. Biotechnol. 2020; 38: 708–714. PubMed Abstract \| Publisher Full Text\n\nKatz Y, Wang ET, Airoldi EM, et al.: Analysis and design of RNA sequencing experiments for identifying isoform regulation. Nat. Methods. 2010; 7: 1009–1015. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHuang Y, Sanguinetti G: BRIE: Transcriptome-wide splicing quantification in single cells. Genome Biol. 2017; 18: 1–11. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWelch JD, Hu Y, Prins JF: Robust detection of alternative splicing in a population of single cells. Nucleic Acids Res. 2016; 44. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLiu R, Loraine AE, Dickerson JA: Comparisons of computational methods for differential alternative splicing detection using RNA-seq in plant systems. BMC Bioinformatics. 2014; 15: 1–16. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSoneson C, Matthes KL, Nowicka M, et al.: Isoform prefiltering improves performance of count-based methods for analysis of differential transcript usage. Genome Biol. 2016; 17: 1–15. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLove MI, et al.: Swimming downstream: statistical analysis of differential transcript usage following Salmon quantification. F1000Res. 2018; 1–61. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAnders S, Reyes A, Huber W: Detecting differential usage of exons from RNA-seq data. Genome Res. 2012; 22. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRuddy S, Johnson M, Purdom E: Shrinkage of dispersion parameters in the binomial family, with application to differential exon skipping. Ann. Appl. Stat. 2016; 10: 690–725. Publisher Full Text\n\nNowicka M, Robinson MD: DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics. F1000Res. 2016; 5: 1356. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nChen Y, Mccarthy D, Ritchie M, et al.: edgeR: differential expression analysis of digital gene expression data. User’s Guid. 2019.\n\nSmyth GK: Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray. Stat. Appl. Genet. Mol. Biol. 2006; 3.\n\nMerino GA, Fernández EA: Differential splicing analysis based on isoforms expression with NBSplice. J. Biomed. Inform. 2020; 103. PubMed Abstract \| Publisher Full Text\n\nGilis J, Vitting-seerup K, Van den Berge K, et al.: Extended data for the satuRn publication. Zenodo Version 1.0.1. 2021. Publisher Full Text\n\nDarmanis S, et al.: Single-cell RNA-Seq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma. Cell Rep. 2017; 21: 1399–1410. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nShalek AK, et al.: Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature. 2014; 510: 363–369. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPetropoulos S, et al.: Single-Cell RNA-Seq Reveals Lineage and X Chromosome Dynamics in Human Preimplantation Embryos. Cell. 2016; 167: 285. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nChen G, et al.: Single-cell analyses of X Chromosome inactivation dynamics and pluripotency during differentiation. Genome Res. 2016; 26: 1342–1354. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTiberi S, Robinson MD: BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty. Genome Biol. 2020; 21: 1–13. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBenjamini Y, Hochberg Y: Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B. 1995; 57: 289–300.\n\nDobin A, et al.: STAR: Ultrafast universal RNA-seq aligner. Bioinformatics. 2013; 29: 15–21. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLund SP, Nettleton D, McCarthy DJ, et al.: Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates. Stat. Appl. Genet. Mol. Biol. 2012; 11. PubMed Abstract \| Publisher Full Text\n\nLi B, Dewey CN: RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011; 12: 323. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMcCarthy DJ, Chen Y, Smyth GK: Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 2012; 40: 4288–4297. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nEfron B: Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction. Institute of Mathematical Statistics Monographs. Cambridge University Press.2010. Publisher Full Text\n\nEfron B: Large-scale simultaneous hypothesis testing: The choice of a null hypothesis. J. Am. Stat. Assoc. 2004; 99: 96–104. Publisher Full Text\n\nEfron B, Turnbull BB, Narasimhan B: Locfdr: Computes Local False Discovery Rates. R Packag. Version 1. 2011.Reference Source\n\nChen Y, Lun ATL, Smyth GK: From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline. F1000Res. 2016; 5, 1438. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVan den Berge K, Soneson C, Robinson MD, et al.: stageR: A general stage-wise method for controlling the gene-level false discovery rate in differential expression and differential transcript usage. Genome Biol. 2017; 18, 1–14. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGTEx Consortium: The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 2013; 45(580–585). PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTasic B, et al.: Shared and distinct transcriptomic cell types across neocortical areas. Nature. 2018; 563: 72–78. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRobinson MD, McCarthy DJ, Smyth GK: edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2009; 26: 139–140. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSoneson C, Robinson MD: iCOBRA: open, reproducible, standardized and live method benchmarking. Nat. Methods. 2016; 13: 283. PubMed Abstract \| Publisher Full Text\n\nKang HM, et al.: Multiplexed droplet single-cell RNA-sequencing using natural genetic variation. Nat. Biotechnol. 2018; 36: 89–94. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDurand S, et al.: A comparison of visual response properties in the lateral geniculate nucleus and primary visual cortex of awake and anesthetized mice. J. Neurosci. 2016; 36: 12144–12156. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCardin JA, Kumbhani RD, Contreras D, et al.: Cellular mechanisms of temporal sensitivity in visual cortex neurons. J. Neurosci. 2010; 30: 3652–3662. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLiu H, Agam Y, Madsen JR, et al.: Timing, Timing, Timing: Fast Decoding of Object Information from Intracranial Field Potentials in Human Visual Cortex. Neuron. 2009; 62, 281–290. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGuo ZV, et al.: Maintenance of persistent activity in a frontal thalamocortical loop. Nature. 2017; 545: 181–186. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGuo ZV, et al.: Flow of cortical activity underlying a tactile decision in mice. Neuron. 2014; 81: 179–194. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSubramanian A, et al.: Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. U. S. A. 2005; 102: 15545–15550. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCarbon S, et al.: AmiGO: Online access to ontology and annotation data. Bioinformatics. 2009; 25: 288–289. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nYates AD, et al.: Ensembl 2020. Nucleic Acids Res. 2020; 48: D682–D688. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVan Buren S, et al.: Compression of quantification uncertainty for scRNA-seq counts. bioRxiv. 2020; 2020.07.06.189639. PubMed Abstract \| Publisher Full Text\n\nFujita K, Iwaki M, Yanagida T: Transcriptional bursting is intrinsically caused by interplay between RNA polymerases on DNA. Nat. Commun. 2016; 7: 1–10. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBrian M, van Oudenaarden A: Using noise to understand gene regulation. Science (80-.). 2012; 336, 183. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNajar CFBA, Yosef N, Lareau LF: Coverage-dependent bias creates the appearance of binary splicing in single cells. Elife. 2020; 9: 1–23. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGilis J, Vitting-seerup K, Van den Berge K, et al.: Datasets associated with the publication of the ‘satuRn’ R package. Zenodo Version 1.0.2. 2021. Publisher Full Text\n\nGilis J, Vitting-Seerup K, Van den Berge K, et al.: Source code of the ‘satuRn’ R package at the time of publication (snapshot satuRn v0.99.7). Zenodo Version 1.0.0. 2021. Publisher Full Text\n\nGilis J, Vitting-seerup K, Van den Berge K, et al.: Source code for the publication of the ‘satuRn’ R package. Zenodo Version 1.0.0. 2021. Publisher Full Text\n\nGilis J, Vitting-Seerup K, Van Den Berge K, et al.: satuRn: Scalable Analysis of differential Transcript Usage for bulk and single-cell RNA-sequencing applications. bioRxiv. 2021. Publisher Full Text" }	[ { "id": "85874", "date": "10 Jun 2021", "name": "Marek Cmero", "expertise": [ "Reviewer Expertise Bioinformatics", "method development", "transcriptomics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nGilis et al. present satuRn, a novel method for performing differential transcript usage analysis on bulk and single-cell RNA-seq data. The approach improves upon existing methods through computational scalability and support for multifactorial experimental designs, while also tightly controlling FDR rates for bulk and single-cell experiments. The authors demonstrate performance using simulated, as well as real bulk and single-cell RNA-seq data, showing that satuRn performs on par with the best available approaches, while controlling the FDR and scaling favourably to large numbers of cells and transcripts.\n\nThe paper is well written, logical and easy to follow. The experimental methodology and results are sound and well presented. The authors have also done a great job with the software. I was able to install satuRn and run the vignette without any difficulty.\n\nThe following points would help improve the manuscript:\nThe manuscript cites support for multifactor experimental designs as a key advantage of satuRn, however, this is not demonstrated. A small case study experiment with a multifactor experimental design, perhaps using the Tasic et al. data, would be helpful in illustrating this feature.\n\nThe authors benchmark satuRn's scalability on scRNA data, however, not on bulk RNA-seq (although competing methods are benchmarked on bulk data in Figure 1). While this is computationally less challenging, it would be helpful for the authors to also show satuRn’s scalability on bulk RNA-seq, for instance, using the Love et al. data as in Figure 1.\n\nThe Discussion notes that performance on different scRNA datasets is affected by the percentage of zero counts: It would be helpful if the authors could show the zero count distributions in the three different scRNA data sets to illustrate this.\n\nIt can be quite difficult to compare across the FDR-TPR curves when assessing performance using the different filters and abundance estimation methods. Perhaps for a subset of the comparisons and only showing the best performing tools, the authors could consider adding a set of simplified figures that compares the different filtering/counting approaches on a single plot per tool.\n\nThe authors state that performance of raw abundance estimates was better in all data sets, except for the Love et al. data., which is presumably due to the simulation methodology. Do the authors have any insights into why this dataset performed better using pseudo-alignments?\n\nThe quantification methodology of the scRNA data is not described in the methods and should be included.\n\nIn the two sections describing the real bulk and real single-cell study data, the authors refer to the ‘swapping strategy’ described in the Methods. However, two different swapping strategies are detailed. Please clarify.\n\nIn the ‘Performance assessment’ section, the acronym FDP is not spelled out.\n\nPanels A-C in Figure 8 are missing labels.\n\nIt would be helpful if the authors could explain the null distribution histograms a bit more, i.e. what the green and blue lines, red triangles and highlighted distributions show.\n\nIs the rationale for developing the new method (or application) clearly explained? Yes\n\nIs the description of the method technically sound? Yes\n\nAre sufficient details provided to allow replication of the method development and its use by others? Partly\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "8563", "date": "07 Sep 2022", "name": "Jeroen Gilis", "role": "Author Response", "response": "We are grateful for the comments and suggestions of both reviewers, which have markedly improved the readability of the manuscript and have led to several additional analyses and findings. We here first summarise the major and minor changes to the manuscript and then address the reviewer-specific comments point-by-point: Major changes: We include a case study analysis on single-cell RNA-seq data with a more complex multifactor experimental design. We first show that including additional covariates to the differential transcript usage (DTU) analysis affects the ranking of transcripts in the resulting top list as compared to an analysis without these covariates. Second, we use the more complex model to identify covariate-specific changes in DTU. We include a case study that performs a differential usage analysis at the level of equivalence classes. We qualitatively compare results between a transcript-level and equivalence class-level analysis on the same data, highlighting the advantages and disadvantages of both analyses. We included a short case study on differential exon usage on a small bulk RNA-seq dataset, comparing satuRn with DEXSeq. We elaborate on the effect of data sparsity and filtering on the benchmark performances of the different DTU tools. We additionally summarize the key characteristics of the different datasets. We elaborate on the comparison between using raw counts or scaledTPM abundances in the context of DTU analyses. We assess the performance of DTU methods as a function of the strength of the induced DTU signal as introduced by the swapping strategy in our performance benchmarks. We additionally include a scalability analysis of the different DTU tools on bulk RNA-seq data. Minor changes: We discuss the discrepancy of the performance benchmark results between the dataset from Love et al. and the other datasets. We add information on the quantification strategies for the single-cell RNA-seq datasets. We make more explicit which strategies were used for introducing DTU signal in the different datasets that were used for benchmarking the DTU methods. We clarify the acronym FDP. We labeled the panels of Figure 8. In addition, we provided labels to Figure 6 and adapted the captions accordingly. We provide a more detailed description of the null distribution histograms in the Extended data figures. We clarify that, by default, satuRn adopts the testing strategy that is based on the empirical null distribution, but that users could opt for working with the unadjusted p-values as well. We clarify that we did not perform stage-wise testing adjustment in any of the analyses presented in the manuscript. We aimed to improve the layout of the performance curves. Response to comments Reviewer 1: We have followed the reviewer’s suggestion of including a case study analysis with a multifactor experimental design. We reanalysed the single-cell study from Tasic et al. but we now include a main effect for cell type, gender, and the continuous covariate age, as well as an interaction effect between cell type and gender. In this analysis, we first show that including these additional covariates affects the ranking of transcripts in the resulting top list as compared to our original unadjusted analysis. Second, we assessed the interaction effect to prioritise transcripts for which the DTU between cell types differs according to gender. Here, we highlight a transcript that displays strong evidence for DTU between cell types in female mice, but not in male mice. The analysis has been included in the manuscript as a new paragraph, “Analyses with complex experimental designs”, under the Results section and includes the new Figure 10. We have followed the reviewer’s suggestion of including an additional scalability benchmark on bulk data. We performed the benchmark on the GTEx dataset and not the Love dataset (as was suggested by the Reviewer), because the latter only contains 24 samples. The results of the benchmark are in line with those of the single-cell scalability benchmark, with DEXSeq and DRIMSeq being markedly slower than the other methods. When directly comparing the scalability between the bulk and single-cell data on equally sized subsets, we found limited differences in scalability between the data types, except for DEXSeq. DEXSeq scales considerably better on bulk data than on single-cell data, suggesting that the estimation of the GLM parameters is slower when the data are sparse. However, since the scalability profile of DEXSeq is quadratic with respect to the number of cells/samples in the data, it is still infeasible to adopt DEXSeq in bulk datasets with many samples. The discussion of the results has been added to the “Scalability benchmark” paragraph of the Results section. Figures of the scalability profiles on bulk data have been included in the Extended data, Figures S20 and S21. In the third comment, the question was raised as to how the performance of the different DTU methods is affected by the percentage of zero counts in the data. This relates to a comment raised by reviewer #2, who requested “to show [DTU] benchmarks with less stringent criteria to assess how the presence of many zeros affect [the performance of] each method”. We therefore address these comments jointly. We provide Extended data Table S1 containing relevant summary statistics for the different datasets, including the number of features retained after filtering, as well as Figure S32 that visualizes some of the sparsity related properties of the datasets (e.g., library size, fraction zeros per cell). These clearly show that the Darmanis et al. dataset, for which the performance was lowest for each DTU method, is by far the sparsest dataset in our benchmark analyses. Second, we explored how differences in sparsity between the different datasets are reflected in the performance benchmarks. To this end, we construct FDR-TPR curves where the genes (not individual transcripts) have been stratified based on the percentage of zero counts. For each dataset, we thus assess the performance on three strata of genes, i.e., for genes that have a low (< 25%), middle (25-50%) or high (> 50%) percentage of zero counts in their corresponding transcript-level count matrices. All the transcripts of the gene get stratified in this gene-level stratum. The results of this performance benchmark have been included in the Extended data, Figures S30 and S31. As expected, we observe that performances are higher when there is a low percentage of zero counts, uniformly across all datasets and for all methods. Second, performances on genes with high percentage zero counts increase strongly when the number of cells increases (comparison between the bottom rows of Figures S30 and S31). Third, some methods seem more sensitive than others against sparse data. In particular, the performance of DEXSeq on the Tasic et al. 20v20 dataset and the Chen et al. 20v20 dataset (Figure S30) is on par with the performance of satuRn and DoubleExpSeq for the strata with a low or middle percentage of zeros, but markedly lower for the stratum with the highest percentage of zeros. As such, the performance gain of satuRn and DoubleExpSeq over DEXSeq in these datasets can be largely attributed to a better performance on transcripts of lowly abundant genes. Note that this is in line with the performance of DEXSeq being on par with satuRn and DoubleExpSeq on bulk data. In addition to Extended data Figures S30-S32 and Table S1, we included a discussion of these results in the Discussion section of the manuscript (third paragraph). We have followed the reviewer’s suggestion of including simplified figures that compare the different filtering and counting approaches on a single plot per tool. These figures have been included as Extended data Figures S10-S13 and are discussed in the “Performance on simulated bulk RNA-seq datasets” paragraph in the Results section of the manuscript. These figures show more clearly that neither sample size nor the filtering strategy had a profound impact on the ranking of the performances of the different DTU methods; satuRn, DEXSeq and DoubleExpSeq remain the best performing methods overall. However, we did find that the effects of filtering and counting differ between the different datasets. For the Love et al. simulated bulk dataset, filtering more stringently strongly improves performance. In addition, both performance and FDR control are much better when using scaledTPM abundances, as compared to using counts. The strong positive effect of using scaledTPM abundances are only observed for this dataset, which we will discuss in more detail in our response to the next comment of the reviewer. For the simulated bulk datasets by Van den Berge et al., we also observe a positive effect of stringent filtering. The difference between scaledTPM and raw count abundances is negligible. For the real datasets, a quite different pattern is observed. For the GTEx bulk dataset and the single-cell datasets by Tasic et al. and Chen et al., the effects of filtering are limited and using counts performs slightly better than using scaledTPM abundances. Finally, stringent filtering had a strong positive impact on performance on the Darmanis et al. dataset. Note that this dataset is by far the sparsest dataset in our benchmarks (Extended data Figure S32 and Table S1). The differences in performance between scaledTPM and raw count abundances are small. Taken together, using scaledTPM abundances is only beneficial in the simulations by Love et al., for reasons we explain in below. Therefore, we recommend using raw counts abundances. With respect to filtering, the more stringent DRIMSeq filtering strategy only seems beneficial in simulated data and in very sparse single-cell data. Thus, for bulk data and regular single-cell data the lenient edgeR filtering strategy seems sufficient to increase the signal-to-noise ratio. In our hands, the use of scaledTPM abundances instead of raw counts was indeed only beneficial in the simulated dataset by Love et al. As suggested by the reviewer, this is indeed due to the simulation methodology. Love et al. introduced DTU either by swapping TPM abundances or by introducing a fold change in transcript expression in one group of samples, again on TPM abundances. However, when back-transforming the swapped TPM abundances to count abundances, the transcript lengths were not swapped. Hence, the simulation strategy can induce differences in the total count for a gene, which in turn may alter the usage of all (target and off-target) transcripts in that gene when raw counts are used as an input, which gives rise to many false positives in off-target transcripts of DTU genes. When introducing DTU by swapping raw counts (real bulk and single-cell evaluations), we could expect spurious signal in analyses on the TPM scale for the same reason. However, the difference between the raw count and TPM analyses was much less pronounced, which was also the case for the Van den Berge et al. simulation approach. We have included this as a remark in the “Performance on simulated bulk RNA-seq datasets” paragraph in the Results section of the manuscript. The quantification methodology for the single-cell RNA-seq data was indeed missing and has now been included in the “Real single-cell study” paragraph of the Methods section as follows: “The datasets from Chen et al.29 and Tasic et al.42 were quantified using Salmon v1.1.0, whereas the dataset from Darmanis et al.26 was quantified with Salmon v0.8.2 as obtained from Soneson et al.43.” We agree with the reviewer that it previously unclear which swapping strategy was used in the “real bulk study” and “real single-cell study” paragraphs of the Methods section. In both cases, DTU is artificially introduced by swapping raw transcript counts between groups of samples, which we now explicitly mention in both paragraphs. We have now spelled out the acronym FDP in the “Performance assessment” paragraph of the Methods section, and defined it as follows: “The FDR is the expected value of the false discovery proportion (FDP), which is the ratio of the number of false positives over the total number of positives.” As requested, we labeled the panels of Figure 8. In addition, we provided labels to Figure 6 and adapted the captions accordingly. We agree with the reviewer that the null distribution histograms in the Extended data Figures S14, S15, S24 and S26 required further explanation. We have included this information in the caption of Figure S14 and referred to that information in the captions of Figures S15, S24 and S26. The update caption of Figure S14 reads as follows: “The z-scores corresponding to the null transcripts are expected to follow a standard normal distribution (mean = 0, standard deviation = 1). This corresponds well with the maximum likelihood estimates (MLE) for the mean and variance of the empirical null distribution (mean = -0.002, standard deviation = 1.029) as obtained with the locfdr package. In brief, these estimates are obtained by assuming that the z-scores of all transcripts follow a mixture distribution, where the z-scores of the null transcripts are expected to follow a normal distribution and the z-scores of the DTU transcripts follow some other distribution. Two models are fitted to the z-scores. The blue dashed curve is a normal distribution that is fitted to the mid 50% of the z-scores, which are assumed to originate from null genes, thus representing the estimated empirical null component densities. The MLE and central matching estimates (CME) for the mean and standard deviation of the estimated empirical null distribution are provided in the caption at the bottom of the plot. Finally, the green solid curve represents the estimated marginal density across all z-scores and is obtained by fitting a spline model to the histogram counts.” To avoid confusing the reader with concepts that are not required for the paper, we have omitted the explanation of the yellow triangles on the locfdr figures. In brief, the locfdr package returns local fdr values for each transcript. The FDR is a set property, i.e., the expected fraction of false positives in the set that is returned. Efron (2010) showed that the FDR can also be interpreted as a posterior probability, i.e., the posterior probability that a random feature in the set that is returned is a false positive. Unlike the FDR, the local fdr of a feature is the posterior probability that this individual feature is a false positive, so it relates to a single specific null hypothesis of this specific feature and not to a set of null hypotheses. Efron (Ann. Stat. 2007) defined 0.2 as a useful cutoff for the local fdr and argues that a 0.2 cutoff for the local fdr often corresponds with a conventional FDR of 0.05. Efron showed that the FDR can also be interpreted as the average local fdr over the set that is returned as significant, i.e., the features with a local fdr < 0.2. The conventional FDR over this set can be estimated by taking the sample average of the local fdr of the features that are returned, and is bound to be much smaller than 0.2. The triangles on the locfdr plot indicate cut points for the z-scores; z-scores that are more extreme than the triangles will result in a local FDR estimate that is smaller than 0.2." } ] }, { "id": "85196", "date": "21 Jun 2021", "name": "Alejandro Reyes", "expertise": [ "Reviewer Expertise Bioinformatics", "Computational Biology", "Drug Discovery" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors propose a new method to test for differences in transcript usage for both bulk RNA-seq and single-cell RNA-seq data. The manuscript is clear and the method is sound and well explained. The authors provide an excellent implementation of their method as a Bioconductor package whose vignette is easy to follow. The main advantage and novelty of satuRn is that it scales well with very large samples, which is a limitation of some of the best performing methods in literature. Below are a couple of suggestions to provide more context to the DTU events on the benchmarks, assess to what extent DTU for single cells might be a limitation and a couple of requests for clarifications in the manuscript.\nThe transcript swapping strategy seems quite powerful to benchmark DTU methods. This strategy is probably introducing DTU of different magnitudes. It would be highly informative if the authors can assess the performance of the different methods as a function of the strength of the induced DTU. How is the performance of satuRn and the other tools across different ranges of DTU induction?\n\nThe authors describe a strategy to calculate p-values based on t-test on the estimated log-odds transcript ratios. They also describe that this strategy is too liberal for scRNA-seq analyses and provide an alternative approach that converts these p-values to z-scores and use locfdr to estimate an empirical null distribution. Based on the paper and the vignette, it was unclear to me which strategy is followed for bulk RNA-seq analyses? Does the user have the possibility of choosing which strategy to use?\n\nThe filtering strategy for scRNA-seq datasets is very stringent (at least 1 count in 50% of the cells) and might result in mostly highly expressed genes/transcripts. How many genes can be tested for DTU after such thresholds are applied in real scRNA-seq data? It would also be very informative to show benchmarks with less stringent criteria to assess how the presence of many zeros affect each method.\n\nGiven that most scRNA-seq protocols only sequence the 3’ end of transcripts, it might be unfeasible to reliably estimate transcript expression (this is discussed in Ntranos et al. (20191)). Examples would be when the transcripts are not distinguishable from the 3’ends alone. The authors should consider testing their approach and benchmarks at the level of transcript compatibility counts.\n\nI found unclear whether stageR applied by default (as I understand from the vignette)? If so, I think it is important to apply stageR to all the methods tested in the benchmarks to distinguish the performance of saturn vs satuRn + stageR.\n\nThe authors describe the applicability of their method for differential transcript usage. However, as I understand the model, it could also be used for differential exon usage, or groups of reads supporting an alternative splicing event (counts from alternative splicing event A counts from event B, or intron clusters as in leafcutter, etc). I think the authors could showcase these examples to expand the applications of their model.\n\nIn most ROC curves it’s a bit hard to distinguish each different line due to over plotting.\n\nIs the rationale for developing the new method (or application) clearly explained? Yes\n\nIs the description of the method technically sound? Yes\n\nAre sufficient details provided to allow replication of the method development and its use by others? Yes\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Partly", "responses": [ { "c_id": "8564", "date": "07 Sep 2022", "name": "Jeroen Gilis", "role": "Author Response", "response": "We are grateful for the comments and suggestions of both reviewers, which have markedly improved the readability of the manuscript and have led to several additional analyses and findings. We here first summarise the major and minor changes to the manuscript and then address the reviewer-specific comments point-by-point: Major changes: We include a case study analysis on single-cell RNA-seq data with a more complex multifactor experimental design. We first show that including additional covariates to the differential transcript usage (DTU) analysis affects the ranking of transcripts in the resulting top list as compared to an analysis without these covariates. Second, we use the more complex model to identify covariate-specific changes in DTU. We include a case study that performs a differential usage analysis at the level of equivalence classes. We qualitatively compare results between a transcript-level and equivalence class-level analysis on the same data, highlighting the advantages and disadvantages of both analyses. We included a short case study on differential exon usage on a small bulk RNA-seq dataset, comparing satuRn with DEXSeq. We elaborate on the effect of data sparsity and filtering on the benchmark performances of the different DTU tools. We additionally summarize the key characteristics of the different datasets. We elaborate on the comparison between using raw counts or scaledTPM abundances in the context of DTU analyses. We assess the performance of DTU methods as a function of the strength of the induced DTU signal as introduced by the swapping strategy in our performance benchmarks. We additionally include a scalability analysis of the different DTU tools on bulk RNA-seq data. Minor changes: We discuss the discrepancy of the performance benchmark results between the dataset from Love et al. and the other datasets. We add information on the quantification strategies for the single-cell RNA-seq datasets. We make more explicit which strategies were used for introducing DTU signal in the different datasets that were used for benchmarking the DTU methods. We clarify the acronym FDP. We labeled the panels of Figure 8. In addition, we provided labels to Figure 6 and adapted the captions accordingly. We provide a more detailed description of the null distribution histograms in the Extended data figures. We clarify that, by default, satuRn adopts the testing strategy that is based on the empirical null distribution, but that users could opt for working with the unadjusted p-values as well. We clarify that we did not perform stage-wise testing adjustment in any of the analyses presented in the manuscript. We aimed to improve the layout of the performance curves. Response to comments Reviewer 2: The swapping strategy will indeed induce DTU signal of different magnitudes. We followed the reviewer’s suggestion of assessing the performance of the different methods as a function of the strength of the induced signal. Specifically, we have included four additional figures in the Extended data (Figures S16-S19), corresponding to the four benchmarks that used swapping, where we stratify FDR-TPR curves based on the strength of the induced DTU signal. As an estimate for the strength of the signal, we take the difference in the empirical average transcript usage between the two groups of cells/samples. The empirical usage was computed by dividing the transcript-level count with the corresponding gene-level count in each cell/sample. Based on this metric, the FDR-TPR curves are stratified in 6 categories: a difference in transcript usage between groups of 0-10%, 10-20%, 20-30%, 30-40%, 40-50% and 50-100%. A brief discussion of the results is included in the “Performance on real single-cell data” paragraph of the Results section of the manuscript. First, as expected, the ability of all methods to detect DTU decreases when the strength of the DTU signal decreases. Second, the difference of transcript usage that can be correctly detected is dependent on the data: small differences in transcript usage can be more easily detected in bulk data as compared to single-cell data, likely owing to the larger sequencing depth and lower variability of bulk datasets. Third, inference improves for all strata when the number of cells or samples increases. Fourth, we observed in all benchmark datasets that satuRn and DoubleExpSeq are more successful in detecting small differences as compared to the other methods. As such, the performance gain of satuRn and DoubleExpSeq in the overall results (without stratification) can be attributed to picking up DTU with smaller effect sizes. As a final note, having different transcript-level filtering procedures (edgeR filter versus DRIMSeq filter) did not affect these findings. Adopting scaledTPM abundances instead of raw counts did not affect the results, either (results not shown). In the second comment, the reviewer asked if satuRn by default uses the empirical null strategy to improve FDR control, if this is also the case in bulk analyses and if this is tunable by the user. By default, we indeed always use the strategy that relies on the empirical null distribution, both for single-cell and bulk datasets. The empirical null strategy improved the FDR control in single-cell data and performed on par in bulk data, as shown in Extended data Figure S14. However, it is possible for the user to use the “raw” p-values and FDR instead, as they are also provided in the output of the testDTU function. The empirical null strategy being the default is discussed at the end of the “Performance on real single-cell data” paragraph of the Results section of the manuscript. However, in the Bioconductor vignette, we indeed failed to explicitly mention which strategy we are using. We have now added this information to the vignette, where we now also more explicitly describe the output of the testDTU function, i.e., the fact that both the raw and empirical p-values are returned and can both be used for downstream analysis (see the updated vignette at https://statomics.github.io/satuRn/articles/Vignette.html). In the third comment, the reviewer requests to assess the effect of filtering and data sparsity on the performance of the different DTU tools. This relates to a comment also raised by reviewer #1, who requested to assess how the performance of the different DTU methods is affected by the percentage of zero counts in the data and if we could display some of the sparsity related summary statistics and distributions of the different benchmark datasets. We therefore address these comments jointly. We first provide a table (Extended data Table S1) containing relevant summary statistics for the different datasets, including the number of features retained after filtering in the different datasets, as well as a figure (Figure S32) that visualizes some of the sparsity related properties of the datasets (e.g., library size, fraction zeros per cell). These clearly show that the Darmanis et al. dataset, for which the performance was lowest for each DTU method, is by far the sparsest dataset in our benchmark analyses. Second, we explored how differences in sparsity between the different datasets are reflected in the performance benchmarks. To this end, we construct FDR-TPR curves where the genes (not individual transcripts) have been stratified on the percentage of zero counts. For each dataset, we thus assess the performance on three strata of genes, i.e., for genes that have a low (< 25%), middle (25-50%) or high (> 50%) percentage of zero counts in their corresponding transcript-level count matrices. All the transcripts of the gene get stratified in this gene-level stratum. The results of this performance benchmark have been included in the Extended data, Figures S30 and S31. As expected, we observe that performances are higher when there is a low percentage of zero counts, uniformly across all datasets and for all methods. Second, performances on genes with high percentage zero counts increase strongly when the number of cells in the data increases (comparison between the bottom rows of Figures S30 and S31). Third, some methods seem more sensitive than others against sparse data. In particular, the performance of DEXSeq on the Tasic et al. 20v20 dataset and the Chen et al. 20v20 dataset (Figure S30) is on par with the performance of satuRn and DoubleExpSeq for the strata with a low or middle percentage of zeros, but markedly lower for the stratum with the highest percentage of zeros. As such, the performance gain of satuRn and DoubleExpSeq over DEXSeq in these datasets can be largely attributed to a better performance on the sparsest part of the data. Note that this is in line with the performance of DEXSeq being on par with satuRn and DoubleExpSeq on bulk data. In addition to Extended data Figures S30-S32 and Table S1, we included a discussion of these results in the Discussion section of the manuscript (third paragraph). We have followed the reviewer’s suggestion of including an additional case study in the manuscript that performs a differential usage analysis on transcript compatibility counts (TCCs), sometimes referred to as equivalence class (EC) counts. More specifically, we have performed an EC-level analysis on the dataset of Tasic et al., which was also used for the transcript-level case study, allowing us to qualitatively compare the results of both analyses. This additional analysis led to several novel insights which we describe detail in paragraph “Case study on transcript compatibility counts” of the Results section and discuss in the fourth paragraph of the Discussion section of the manuscript. In addition, Figure S27 was added to the Extended data. We here attempt to briefly summarise the key outcomes of the analysis. First, we display the number of differentially used transcripts and equivalence classes in eight comparisons between cell types in Table 3. The extent to which transcript-level and EC-level results correspond differs between the different comparisons. For several comparisons, there is a clear discrepancy between the number of differentially used transcripts and equivalence classes (Table 3, columns 4 and 6) and in the number of unique genes in which evidence for differential usage was observed (Table 3, columns 5 and 7). The overlap between the genes found in the transcript-level and the TCC-level analysis ranges from 53% (54/102) in comparisons 6 and 8 to 100% in comparison 3. For comparison 6 (53% overlap), we investigate the genes identified by both analyses. For some genes that are identified in both analyses, there is a strong agreement between the transcript-level and EC-level results. One example is the gene Pde4d. As depicted in Figure 11, there is a one-to-one concordance in the usage profiles of the equivalence classes and the transcripts. In other words, for this gene, the EC-level analysis is sufficient to obtain the same qualitative results as the transcript-level analysis. This is highly interesting, as the TCCs require only a fraction of the time to compute compared to the transcript-level counts, and they have no quantification uncertainty. However, for most other genes in which DU was identified in both analyses, the comparison between transcript and EC results is more ambiguous, as ECs often do not allow to pinpoint the responsible transcript(s) driving their observed DU. We demonstrate this by investigating the gene P2rx4. Four P2rx4 equivalence classes passed feature-level filtering, which we will denote with EC1-EC4. EC1 uniquely corresponds to transcript ENSMUST00000195963, and both the transcript and TCC are found to be differentially used in their respective analyses (Extended data Figure S27, panel A). The other ECs correspond to two, three and four different transcripts, respectively (Extended data Figure S27, panel A). For EC2 and EC3, strong evidence for differential usage was found. For EC4, there was no evidence for differential usage. However, based on these ECs alone, it would not be possible to unambiguously attribute these changes to single transcripts, complicating the biological interpretation. In the Discussion, we therefore conclude that biological interpretation of equivalence classes that correspond to multiple transcripts of a gene remains challenging. Currently, functional interpretation will therefore be limited to pinpointing genes with differential usage of a certain equivalence classes, without being able to link this to a functional effect at the transcript- or protein level. Finally, we note that while an analysis on scRNA-seq data from droplet protocols (like Chromium 10X) where the transcripts are not distinguishable from the 3’ ends alone would also be very interesting, we did not include such analysis in this manuscript. In our opinion, an extensive benchmarking of the different DTU tools on such data would be required and is out of the scope of this manuscript. The reviewer asked if we by default use the stage-wise testing procedure stageR in a satuRn analysis workflow. We do not apply stageR by default. Hence, all results from the paper are generated without stage-wise testing to allow for a fair comparison between the methods. We did not systematically compare results for all methods with and without stageR, as this would further increase (double) the number of benchmarks in this paper. In addition, it is not an integral part of any DTU method and the utility of stageR in a DTU setting has been demonstrated previously in the original stageR publication of Van den Berge et al. However, conceptually, a stage-wise testing procedure makes sense in the context of DTU and should result in increased statistical power for all DTU methods. In this context, stageR has also been included in the downstream analysis of DTU methods in the F1000research workflow paper by Love et al. (https://doi.org/10.12688/f1000research.15398.3). We only included stageR as a downstream analysis method in our package vignette, where we wanted to showcase how to use stageR in the downstream analysis of satuRn output. We have now specifically stated in the vignette that this is an optional step. We have followed the reviewer’s suggestion of including an additional case study in the manuscript that performs a differential usage analysis at the level of exons. To briefly showcase this, we adopted the differential exon usage (DEU) analysis using the data from the DEXSeq vignette, i.e., we perform the same DEU analysis as the DEXSeq vignette using both DEXSeq and satuRn. This analysis has been included in the “Case study on exon-level counts” paragraph in the Results section of the manuscript. In addition, we added Figures S28 and S29 to the Extended data. Compared to the original DEXSeq analysis, satuRn identified fewer differentially used exons between the two experimental groups, with three statistically significant findings at 5% FDR for satuRn compared to 19 significant findings with DEXSeq. While we did not benchmark satuRn and DEXSeq on exon-level data, this could correspond to DEXSeq being overly liberal in transcript-level bulk analyses, especially with small sample sizes (Figure 2 and Extended data Figure S2). More importantly, however, the ranking of the exons based on their respective p-values is almost identical between the two methods (Extended data Figure S28). Again, this is supportive of a similar performance of DEXSeq and satuRn on small bulk RNA-Seq datasets, albeit with a different type 1 error rate. In Extended data Figure S29, we additionally demonstrate how satuRn can be used to visualise changes in the usage of exons. Finally, the reviewer request to improve the layout of the performance curves to reduce overplotting. Given that the performances of most methods are very close, this was not trivial. First, we did not want to reduce the range of the x-axis, as this would remove some of the FDR working points for the more liberal tools. Second, we prefer displaying the entire curve over only displaying the curve between the FDR working points of 0.01 and 0.1, which is also often done in this context. However, the latter strategy does not allow for displaying early mistakes, i.e., false positives with a very low FDR. Therefore, we aimed to accommodate the comment by reducing the size of the FDR working points, making the curves slightly thinner and by increasing the size of some of the plots." } ] } ]	1	https://f1000research.com/articles/10-374
https://f1000research.com/articles/11-579/v1	26 May 22	{ "type": "Research Article", "title": "Usefulness of vaccine boosters for Covid-19 in Italy and in UK and comparison between in intensive care admissions and deaths of vaccinated and unvaccinated patients. Surprises and implications", "authors": [ "Marco Alessandria", "Claudio Simion", "Alberto Donzelli", "Claudio Simion", "Alberto Donzelli" ], "abstract": "Background: There is insufficient clarity about the different outcomes between unvaccinated and vaccinated people hospitalized with Covid-19, with reference to the variables “Intensive Care Unit” and “Deaths”. Moreover, it is unclear the real effectiveness of the vaccine boosters on the risks of infection and Covid-19 deaths, beyond the first few months after the booster. To verify the hypotheses that repeated vaccinations might expose to a progressively greater risk of severe Covid-19, and of a growing weakening of the immune response, primarily against infection, as the distance from the booster dose increases. Methods: Through an analysis of the official Italian data we calculated significant differences, percentage variations and trends in the variables “Intensive Care Units” and “Deaths” in hospitalized patients among four groups with different vaccination status, and between the Unvaccinated and Vaccinated groups. Through analyses of the UK Security Agency data in the weekly COVID-19 vaccine surveillance reports we explored the vaccine effectiveness against SARS-CoV-2 infections and against COVID-19 deaths in relation to the time elapsed from the booster doses. Results: Repeated vaccinations seem to expose the recipients to a growing risk of severe Covid-19, and fewer vaccinations might be enough to protect persons at greater risk. The vaccine effectiveness against infection vanished and reversed in the medium term, and vaccinated persons with three doses become increasingly more infected versus unvaccinated persons. Conclusions: The starting hypotheses have been supported, together with the need to combine carefully rethought vaccination campaigns with the implementation of other strategies, with the achievement of a healthy living and working environment, healthy lifestyles, and effective, safe and sustainable care.", "keywords": [ "Covid-19 vaccinations", "first second dose of Covid-19 vaccination", "Covid-19 booster vaccination", "Covid-19 vaccination and Intensive Care Unit admission", "Covid-19 vaccination and deaths in hospitalized patients", "vaccinations and SARS-CoV-2 infections", "repeated vaccinations and long-term immune response" ], "content": "Introduction\n\nMost Italian mainstream media emphasize the success of the Covid-19 vaccination campaign, following the information provided by the Istituto Superiore di Sanità (ISS). However, there is insufficient clarity about the different outcomes between unvaccinated and vaccinated people hospitalized with Covid-19, with reference to the variables “Intensive Care Unit (ICU)” and “Deaths”. Moreover, it is unclear the real effectiveness of the vaccine boosters on the risks of infection and of Covid-19 death in a period of time not limited to the first months after the booster.\n\nThe effects of repeated vaccinations on lowering the risk of disease have been shown for other infectious diseases.\n\nIn the Canadian influenza season 2014 – 2015 repeated vaccinations increased the risk of medically attended A(H3N2) disease up to 50% versus unvaccinated people.1 Similar results were also shown in Italy, where most participants had received repeated doses,2 and in Michigan, where the influenza vaccine effectiveness was lower in subjects vaccinated in both the current and prior season in all age groups. On the contrary, in subjects with no evidence of prior vaccination, the vaccine effectiveness was higher for all age groups.3 Moreover, the dose-response relationship, calculated with adjusted geometric mean fold rise (MFR) after influenza vaccination, seems to be inversely related to the number of prior vaccinations, with higher protection without prior vaccination and lower protection in subjects up to four prior vaccination.4\n\nSome authors provide two hypotheses as potential explanation of these phenomena. The first is the Antigenic Distance hypothesis, meaning that variation in repeated vaccine effectiveness (VE) is due to differences in antigenic distances among vaccine strains and between the vaccine strains and the epidemic strain in each outbreak; if antibody titer is high for more than a year, it has the potential to negatively interfere with a subsequent revaccination if the antigenic similarity between the prior season vaccine strain and the epidemic strain is high.5 The second is the Original Antigenic Sin (OAS), meaning that the immunity response to the previous met viral strain permanently shapes itself in order to boost the antibody production to related strain.6\n\nMoreover, it seems that the hypothesis based entirely on the antibody response to a unique viral antigen is not enough, but it is likely that the adaptive immune response to other virus components might contribute.7 In fact, a recent study suggests that the presence of pre-existing non-spike cross-reactive memory T cells protects the SARS-CoV-2-naïve contacts from infection.8\n\nAlthough many important questions related to the mechanism of OAS remain unanswered,9 it seems that the effectiveness of the current vaccine will be higher in people not previously vaccinated, or if the previous vaccine strain cross-reacts minimally with the current vaccine strain, even with no close match to the circulating strain.6\n\nMoreover, it has been hypothesized that anti-COVID-19 vaccinations, too frequently or too close repeated, could weaken the immune response or damage the immune system itself.\n\nThe aim of this study is to verify significant differences, percentage variations and trends in the ICU and Deaths variables, in the hospitalized population among four groups: an Incomplete Cycle (IC – defined as all reported cases with a confirmed diagnosis of SARS-CoV-2 virus infection, occurring at least 14 days after the first dose – in subjects who have received a two-dose vaccine course – or, within 14 days days after administration of the second dose10) group, a double dose since less than 4 months (2D<4) group, a double dose more than 4 months ago (2D>4) group, and a third dose (3D) group.\n\nFurthermore, we aim to verify significant differences, percentage variations and trends in the same variables between the Unvaccinated (UV) and Vaccinated (V) groups.\n\nWe hypothesize that repeated vaccinations might expose the recipients to a progressively greater risk of Covid-19, included severe diseases, and that fewer vaccinations might be enough to protect the subjects at greater risk.\n\nFinally, we have verified the hypothesis of a progressive weakening of the immune response as the time elapsed from the booster dose increased, analyzing the data published weekly by the UK Security Agency in the COVID-19 vaccine surveillance reports.\n\n\nMethods\n\nThe official data relating to Covid-19 Hospitalizations, ICU and Deaths between Unvaccinated and Vaccinated (and their subgroups: IC, 2D<4, 2D>4, 3D) were collected from the ISS bulletins starting by January 14, 2022 until February 18, 2022. For the variable Deaths data were collected starting from January 21, 2022 because the division between <4 and >4 months started from this date.\n\nThe reference populations among the bulletins were never aligned with the observation period of all 3 variables taken into consideration. Therefore, it was necessary to proceed with this alignment considering the “median date” of the observation period of each variable and using the populations of the previous bulletins whose reference date coincided with the median date.\n\nThe observation period of one month allowed us to carry out analyzes on populations stable enough, despite the changes of parts of the population among the groups (</> 5 months, </> 4 months, and third doses).\n\nRates/1,000 were calculated for both total events and for each group on the “Intensive Care Unit (ICU)” and “Deaths” variables.\n\nThe rates of the variable “ICU” were calculated on the hospitalized population, while the rates of the variable Covid-19 “Deaths” were calculated on the hospitalized population added to the ICU population. The reason for this choice is based on the fact that the number of deaths was higher than the number of accesses to ICU.\n\nThe calculation of the variation in the rates rate variations was carried out according to the formula:\n\nTo compare the Unvaccinated group and Vaccinated group, data of IC, 2D<4, 2D>4 and 3D were aggregated and was calculated the total rate of Vaccinated group. The reason for this choice is that the ISS considers Unvaccinated even people “… vaccinated with either the first dose or single-dose vaccine within the 14 days prior to diagnosis.” (although, in our opinion, this can introduce a bias and a systematic error).10\n\nThe VIVALDI Study11 showed a marginally greater hazard ratio for PCR-positive infection among vaccinated people after first dose of BNT162b2 vaccine within 7-13 days compared to unvaccinated people. This evidence seems supported by data from Qatar in the two weeks following the first dose, mostly for asymptomatic infections.12,13 This phenomenon might be related to a post-vaccination fall in neutrophil and lymphocyte.14,15\n\nData published weekly by the UK Security Agency in the COVID-19 vaccine surveillance reports were analyzed from the time the majority of the population (>30 million people) received the third dose, in order to verify the immune response as the time elapsed from the booster dose increased, calculating the ratio of deaths of unvaccinated versus vaccinated persons with at least 3 doses.\n\nA non-parametric statistic was used after performing the Shapiro – Wilk normality test, inasmuch the distribution of the rates of the variables considered (“Intensive Care Unit” and “Deaths”) do not show a normal distribution.\n\nThe Kruskal-Wallis test with Dunn’s post-hoc test was used to compare Incomplete Cycle (IC), double dose <4 months (2D<4), double dose >4 months (2D>4) and third doses (3D) groups, while the Mann-Whitney test was used to compare Unvaccinated (UV) and Vaccinated (V) groups.\n\nFor the descriptive statistic, data were processed using Excel, while for the inferential statistic was used GraphPad Prism 5 software (GraphPad Software, Inc., USA); the “p” significance level was fixed at <0.05.\n\n\nResults\n\n\n\na. Intensive Care Unit (ICU) variable\n\nStatistical significant difference (p=0.0001) was observed among groups. Pairwise comparisons using Dunn’s test indicated that IC group was significantly different from the 3D group and 2D>4m. The 2D<4m group was significantly different by the 2D>4m.\n\nThe trend of 3D group is growing with an increase of the 253.3%, while the trend of 2D>4m is degrowing with a decrease of the 39.7%. The trend of IC group and 2D<4m are overlapping and show a decrease respectively of 45.5% and 13.9% (Figure 1 and Table 1).\n\nb. Deaths variable\n\nStatistical significant difference (p=0.001) was observed among groups. Pairwise comparisons using Dunn’s test indicated that IC group was significantly different from the 2D>4m. The 2D<4m group was significantly different by the 2D>4m group.\n\nThe trend of 3D group and 2D>4m are growing with an increase respectively of the 416 % and 3.5%. The trend of IC group and 2D<4m are overlapping and show an increase respectively of 39.9% and 49.8% (Figure 2 and Table 2).\n\n\n\na. ICU variable\n\nStatistical significant difference (p=0.0087) was observed between groups. The trend of UV group and V are both degrowing with an decrease of 51.1% and 12.8% respectively (Figure 3 and Table 3).\n\nb. Deaths variable\n\nStatistical significant difference (p=0.0159) was observed between groups. The trend of UV and V groups are both growing with an increase of 9.5% and 53.2% respectively (Figure 4 and Table 4).\n\nThe reports of COVID-19 vaccine surveillance, weekly published by the UK Security Agency, show a clear trend towards an increase in infections in vaccinated persons versus not vaccinated persons per 100,000, compared in each of eight age classes: under 18, 18 to 29, 30 to 39, 40 to 49, 50 to 59, 60 to 69, 70 to 79, 80 or over. Indeed, the Week 36 of 2021 showed an unbalancement in age classes from 40 to 79 years, in which COVID-19 cases in vaccinated exceeded those in not vaccinated persons, although the entire column of vaccinated persons still outnumbered (-17,2%) the column of not vaccinated.\n\nIn the following weeks the COVID-19 cases among the vaccinated persons continued to increase more than proportionally, until in Week 43 the ratio was reversed, with more COVID-19 cases among the vaccinated persons (+2,5% overall). Thereafter, the relative increases among the vaccinated persons were always higher than those in their counterpart, up to Week 2 of 2022, when the excess reached +91%. From Week 3 of 2022 the tables published in the reports show the comparison only between unvaccinated versus vaccinated persons “with at least 3 doses”, with an attenuated excess of cases temporarily in vaccinated (+24%). However, in the following weeks the excess of cases has continued incessantly: +32%, +35%, +48%, +70%, +100%, +133%, +162%, to reach +186% in Week 11.\n\nIn the weeks when more than half of the English people have received the vaccine booster (from Week 3 of 2022 onwards),19 the Week 3 shows a death rate of unvaccinated 9.4 times than the one of the vaccinated persons, while Week 11 shows a rate unvaccinated/vaccinated persons only about 1.6 (Table 5).\n\n\nDiscussion\n\nThe aim of this study was to understand the impact of the Covid-19 vaccine boosters in the ICU and Deaths variables and to compare the weight of the Unvaccinated and Vaccinated groups in the same variables.\n\nThe results support our hypothesis.\n\nIn fact, the Kruskal-Wallis test used to compare IC, 2D<4, 2D>4, 3D groups have shown that, from the comparison between the rates, a single dose is already associated with reduced access to ICU and Deaths, and that the third doses are associated with increased accesses in ICU and Deaths, with an overall increase of 253% and 416% respectively, unlike the second doses and incomplete cycles (IC), which recorded decreases up to 45 % for ICU and increases up to 49.8% for Deaths.\n\nMoreover, the 2D>4m are associated with significantly greater values than the IC and 2D<4m both in the ICU and Deaths variables. However, on the whole, the 2D>4m show a progressive and continuous decrease over time up to levels almost comparable for the ICU variable to the 3D values (which instead seem to worsen constantly); instead, in Deaths variable the 2D>4m show a slight rise during the considered period.\n\nOverall, the 2D <4m do not seem to improve ICU accesses and deaths, if compared to the single doses (IC) and, moreover, they show a trend over time similar to the IC group.\n\nThe Mann-Whitney test was used to compare Unvaccinated (UV) and Vaccinated (V) groups shows that, overall, the UV group has significantly higher ICU accesses, but it shows a sharp declining trend over the whole period considered (-51%), while the V group shows only a 13% decrease.\n\nThere is an overlap of values between UV and V groups in the last bulletin of the period considered for the ICU variable; instead, the Deaths variable shows a progressive divergence of values throughout the considered period.\n\nIn contrast to the ICU variable, the deaths in the UV group are significantly lower than those in V group, with an increase of 9.5% over the considered period, while the increase in the V group is 53.2%.\n\nThe hypothesis of a progressive weakening of the immune response with the increase of the time from the booster dose is supported by the data in the weekly publications of the UK Security Agency - COVID-19 vaccine surveillance reports.\n\nIn fact, such a clear trend not only argues for the waning of the 3rd dose effectiveness in preventing SARS-CoV-2 infection, but also for a possible, progressive worsening of the immune response.\n\nNote that the Authors of the UK Security Agency Report always repeat that: “Comparing case rates among vaccinated and unvaccinated populations should not be used to estimate vaccine effectiveness against COVID-19 infection. Vaccine effectiveness (VE) has been formally estimated from a number of different sources and is summarised on pages 4 to 15 in this report.” However, the four cohort studies mentioned in the Report in the paragraph “Effectiveness against infection”11,16–18 have a short follow-up, ranging on average from 45 to 80 days, during the so-called honeymoon between the vaccine and the vaccinated persons. In this period the protection is at its maximum, also against the infection, and it is before the beginning of its rapid decline. Moreover, these inconsistent arguments of the Report authors do not stand up to comparison with the very strong and linear trend of increasing infections in vaccinated individuals shown by the weekly data, albeit unadjusted.\n\nIt is not enough. Looking at the weeks when more than half of the English people have received the vaccine booster (from Week 3 of 2022 onwards),19 it is detectable a clear trend to an attenuation of the VE even towards deaths, because in Week 3 the death rate of unvaccinated was 9.4 times the vaccinated rate, while in the Week 10 the rate unvaccinated/vaccinated was only about 1.4 (Table 5). The rate in week 11, nearly 1.6, might be an interruption of this trend, or an effect of chance, or an interference with the (temporary?) effects of the fourth dose, reported only from 9 March 2022.19\n\nThe usual explanation is to acknowledge a progressive attenuation of the VE against the infection (although for now, despite mounting evidence,12,13,20–22 most main stream researchers are far from admitting a VE negativization in the medium period, in comparison to the unvaccinated persons). But, together, the typical narrative states definitely that the VE remains very good against a severe or critical COVID-19. Unfortunately, the data in Table 5 show a clear trend towards an attenuation of the VE even for deaths, and the data should call into question the strategy of repeated, continuous vaccine boosters. Other strategies as well should be debated and studied in depht and implemented, from allowing natural infections (as Icelandic Public Healthcare is proposing,23 in the setting of a mild dominant variant such as Omicron), to implementation of safer environments,24–26 healthy lifestyles,27–32 and reasonably effective, safe and sustainable early care.33–37\n\n\nConclusion\n\nThe results do not provide support to vaccination campaigns with multiple and repeated doses (and related obligations), both because of the doubtful advantage of subsequent doses, and because of the suspicion that the repeated stimulation of the immune system with this type of vaccine may expose the vaccinated people to an increased risk of serious disease.\n\nThe negative effect of this uninterrupted vaccination campaign seems to affect particularly the age groups that the campaign aims to protect; moreover, the net benefits declared for the younger are not evident.\n\nIn addition to continuing researching for better vaccines, it would be time to implement different strategies as well, to tackle this and other pandemics: from the achievement of a healthy living and working environment, to healthy lifestyles, to accessible early, safe and sustainable care.\n\n\nData availability\n\nAs the data are not owned by the authors, it is not possible to upload the data to a repository. Data analysed will be available in an accessible form by contacting the corresponding author.\n\n15/1/2022: https://www.epicentro.iss.it/coronavirus/bollettino/Bollettino-sorveglianza-integrata-COVID-19_12-gennaio-2022.pdf\n\n22/1/2022: https://www.epicentro.iss.it/coronavirus/bollettino/Bollettino-sorveglianza-integrata-COVID-19_19-gennaio-2022.pdf\n\n29/1/2022: https://www.epicentro.iss.it/coronavirus/bollettino/Bollettino-sorveglianza-integrata-COVID-19_26-gennaio-2022.pdf\n\n5/2/2022: https://www.epicentro.iss.it/coronavirus/bollettino/Bollettino-sorveglianza-integrata-COVID-19_2-febbraio-2022.pdf\n\n12/2/2022: https://www.epicentro.iss.it/coronavirus/bollettino/Bollettino-sorveglianza-integrata-COVID-19_9-febbraio-2022.pdf\n\n19/2/2022: https://www.epicentro.iss.it/coronavirus/bollettino/Bollettino-sorveglianza-integrata-COVID-19_16-febbraio-2022.pdf", "appendix": "References\n\nSkowronski DM, Chambers C, Serres D, et al.: Serial Vaccination and the Antigenic Distance Hypothesis: Effects on Influenza Vaccine Effectiveness During A(H3N2) Epidemics in Canada, 2010-2011 to 2014-2015. J. Infect. Dis. 2017; 215(7): 1059–1099. PubMed Abstract \| Publisher Full Text\n\nRizzo C, Bella A, Alfonsi V, et al.: Influenza vaccine effectiveness in Italy: Age, subtype-specific and vaccine type estimates 2014/15 season. Vaccine. 2016 Jun 8; 34(27): 3102–3108. PubMed Abstract \| Publisher Full Text\n\nOhmit SE, Petrie JG, Malosh RE, et al.: Influenza vaccine effectiveness in the community and the household. Clin. Infect. Dis. 2013 May; 56(10): 1363–1369. PubMed Abstract \| Publisher Full Text\n\nThompson MG, Naleway A, Fry AM, et al.: Effects of Repeated Annual Inactivated Influenza Vaccination among Healthcare Personnel on Serum Hemagglutinin Inhibition Antibody Response to A/Perth/16/2009 (H3N2)-like virus during 2010-11. Vaccine. 2016 Feb 10; 34(7): 981–988. PubMed Abstract \| Publisher Full Text\n\nSmith DJ, Forrest S, Ackley DH, et al.: Variable efficacy of repeated annual influenza vaccination. Proc. Natl. Acad. Sci. U. S. A. 1999 Nov 23; 96(24): 14001–14006. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLewnard JA, Cobey S: Immune History and Influenza Vaccine Effectiveness. Vaccines (Basel). 2018 May 21; 6(2): 28. PubMed Abstract \| Publisher Full Text\n\nBelongia EA, Skowronski DM, McLean HQ, et al.: Repeated annual influenza vaccination and vaccine effectiveness: review of evidence. Expert Rev. Vaccines. 2017 Jul; 16(7): 1–14. PubMed Abstract \| Publisher Full Text\n\nKundu R, Narean JS, Wang L, et al.: Cross-reactive memory T cells associate with protection against SARS-CoV-2 infection in COVID-19 contacts. Nat. Commun. 2022 Jan 10; 13(1): 80. PubMed Abstract \| Publisher Full Text\n\nZhang A, Stacey HD, Mullarkey CE, et al.: Original Antigenic Sin: How First Exposure Shapes Lifelong Anti-Influenza Virus Immune Responses. J. Immunol. 2019 Jan 15; 202(2): 335–340. PubMed Abstract \| Publisher Full Text\n\nDonzelli A, Alessandria M, Orlando L: Comparison of hospitalizations and deaths from COVID-19 2021 versus 2020 in Italy: surprises and implications. F1000Res. 2021 Sep 24; 10: 964. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nShrotri M, Krutikov M, Palmer T, et al.: Vaccine effectiveness of the first dose of ChAdOx1 nCoV-19 and BNT162b2 against SARS-CoV-2 infection in residents of long-term care facilities in England (VIVALDI): a prospective cohort study. Lancet Infect. Dis. 2021 Nov; 21(11): 1529–1538. PubMed Abstract \| Publisher Full Text\n\nChemaitelly H, Tang P, Hasan MR, et al.: Waning of BNT162b2 Vaccine Protection against SARS-CoV-2 Infection in Qatar. N. Engl. J. Med. 2021 Dec 9; 385(24): e83. Epub 2021 Oct 6. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAbu-Raddad LJ, Chemaitelly H, Bertollini R: National Study Group for COVID-19 Vaccination. Waning mRNA-1273 Vaccine Effectiveness against SARS-CoV-2 Infection in Qatar. N. Engl. J. Med. 2022 Mar 17; 386(11): 1091–1093. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMuturi-Kioi V, Lewis D, Launay O, et al.: Neutropenia as an Adverse Event following Vaccination: Results from Randomized Clinical Trials in Healthy Adults and Systematic Review. PLoS One. 2016 Aug 4; 11(8): e0157385. PubMed Abstract \| Publisher Full Text\n\nMunyer TP, Mangi RJ, Dolan T, et al.: Depressed lymphocyte function after measles-mumps-rubella vaccination. J. Infect. Dis. 1975 Jul; 132(1): 75–78. PubMed Abstract \| Publisher Full Text\n\nPritchard E, Matthews PC, Stoesser N, et al.: Impact of vaccination on SARS-CoV-2 cases in the community: a population-based study using the UK’s COVID-19 Infection Survey. medRxiv 2021: 2021.04.22.21255913 COVID-19 vaccine surveillance report – week 11 56.\n\nHall VJ, Foulkes S, Saei A, et al.: COVID-19 vaccine coverage in health-care workers in England and effectiveness of BNT162b2 mRNA vaccine against infection (SIREN): a prospective, multicentre, cohort study. Lancet. 2021.\n\nMenni C, Klaser K, May A, et al.: Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID-19 Symptom Study app in the U K: a prospective observational study. Lancet Infect. Dis. 2021; 21: 939–949. PubMed Abstract \| Publisher Full Text Reference Source\n\nNordström P, Ballin M, Nordström A: Risk of infection, hospitalisation, and death up to 9 months after a second dose of COVID-19 vaccine: a retrospective, total population cohort study in Sweden. Lancet. 2022 Feb 26; 399(10327): 814–823. Epub 2022 Feb 4. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFabiani M, Puopolo M, Morciano C, et al.: Italian Integrated Surveillance of covid-19 study group and Italian covid-19 Vaccines Registry group. Effectiveness of mRNA vaccines and waning of protection against SARS-CoV-2 infection and severe covid-19 during predominant circulation of the delta variant in Italy: retrospective cohort study. BMJ. 2022 Feb 10; 376: e069052. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHansen CH, Schelde AB, Moustsen-Helm IR, et al.: Vaccine effectiveness against SARS-CoV-2 infection with the Omicron or Delta variants following a two-dose or booster BNT162b2 or mRNA-1273 vaccination series: A Danish cohort study. medRxiv 2021.12.20.21267966. Publisher Full Text\n\nDorabawila V, Hoefer D, Bauer UE, et al.: Effectiveness of the BNT162b2 vaccine among children 5-11 and 12-17 years in New York after the Emergence of the Omicron Variant. medRxiv 2022.02.25.22271454. Publisher Full Text\n\nhttp\n\nWu X, Nethery RC, Sabath MB, et al.: Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. Sci. Adv. 2020 Nov 4; 6(45): eabd4049. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFiasca F, Minelli M, Maio D, et al.: Associations between COVID-19 Incidence Rates and the Exposure to PM2.5 and NO2: A Nationwide Observational Study in Italy. Int. J. Environ. Res. Public Health. 2020 Dec 13; 17(24): 9318. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDi Ciaula A, Bonfrate L, Portincasa P, et al.: Nitrogen dioxide pollution increases vulnerability to COVID-19 through altered immune function. Environ. Sci. Pollut. Res. Int. 2022 Feb 8. Epub ahead of print. PubMed Abstract \| Publisher Full Text\n\nda Silveira MP , da Silva Fagundes KK , Bizuti MR, et al.: Physical exercise as a tool to help the immune system against COVID-19: an integrative review of the current literature. Clin. Exp. Med. 2021 Feb; 21(1): 15–28. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSallis R, Young DR, Tartof SY, et al.: Physical inactivity is associated with a higher risk for severe COVID-19 outcomes: a study in 48 440 adult patients. Br. J. Sports Med. 2021 Oct; 55(19): 1099–1105. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPopkin BM, Du S, Green WD, et al.: Individuals with obesity and COVID-19: A global perspective on the epidemiology and biological relationships. Obes. Rev. 2020 Nov; 21(11): e13128. Epub 2020 Aug 26. Erratum in: Obes Rev. 2021 Oct; 22(10): e13305. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDemasi M: COVID-19 and metabolic syndrome: could diet be the key?. BMJ Evid Based Med. 2021 Feb; 26(1): 1–2. Epub 2020 Jul 10. Free Full Text Publisher Full Text \|\n\nFarsalinos K, Barbouni A, Poulas K, et al.: Current smoking, former smoking, and adverse outcome among hospitalized COVID-19 patients: a systematic review and meta-analysis. Ther. Adv. Chronic Dis. 2020 Jun; 25(11): 2040622320935765. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPatanavanich R, Glantz SA: Smoking Is Associated With COVID-19 Progression: A Meta-analysis. Nicotine Tob. Res. 2020 Aug 24; 22(9): 1653–1656. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nReis G, Dos Santos Moreira-Silva EA, Silva DCM, et al.: TOGETHER investigators. Effect of early treatment with fluvoxamine on risk of emergency care and hospitalisation among patients with COVID-19: the TOGETHER randomised, platform clinical trial. Lancet Glob. Health. 2022 Jan; 10(1): e42–e51. Epub 2021 Oct 28. Erratum in: Lancet Glob Health. 2022 Feb 24. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nChoudhury IM, Shabnam N, Ahsan T, et al.: Effect of 1% Povidone Iodine Mouthwash/Gargle, Nasal and Eye Drop in COVID-19 patient. Bioresearch Communications-(BRC). 2021; 7(1): 919–923. Dhaka, Bangladesh. Publisher Full Text Reference Source\n\nHasan ZT, Atrakji DMQYMAA, Mehuaiden DAK: The Effect of Melatonin on Thrombosis, Sepsis and Mortality Rate in COVID-19 Patients. Int. J. Infect. Dis. 2022 Jan; 114: 79–84. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPawar KS, Mastud RN, Pawar SK, et al.: Oral Curcumin With Piperine as Adjuvant Therapy for the Treatment of COVID-19: A Randomized Clinical Trial. Front. Pharmacol. 2021 May 28; 12: 669362. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRavichandran R, Mohan SK, Sukumaran SK, et al.: Indomethacin Use for Mild & Moderate hospitalised Covid-19 patients: An open label randomized clinical trial, Medrxiv.Publisher Full Text" }	[ { "id": "139174", "date": "07 Jun 2022", "name": "Gokhan Tut", "expertise": [ "Reviewer Expertise COVID-19 immunology" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nMajor comments and concerns\n\nThe authors have not stratified their data at all, simply looking at whole populations just based on how many vaccines participants have had is not enough. The analysis would need to be redone with multivariate analysis corrections for age, sex, time after vaccination and ethnicity at the very least.\n\nThe quality of the figures is not up to standard and a Y-axis should be provided in the longitudinal subfigures. We should be able to understand the data by looking at the figures and legends alone.\n\"The VIVALDI Study11 showed a marginally greater hazard ratio for PCR-positive infection among vaccinated people after first dose of BNT162b2 vaccine within 7-13 days compared to unvaccinated people.\"\nIn this study, this was not significantly different - authors should either remove this reference or state that the difference seen was not statistically significant in the VIVALDI study.\n\n\"The trend of 3D group is growing with an increase of the 253.3%, while the trend of 2D>4m is degrowing with a decrease of the 39.7%. The trend of IC group and 2D<4m are overlapping and show a decrease respectively of 45.5% and 13.9%\"\n\nIs this statistically significant on the longitudinal graph? Again, this should be checked for every figure.\n\"The reason for this choice is that the ISS considers Unvaccinated even people “… vaccinated with either the first dose or single-dose vaccine within the 14 days prior to diagnosis.” (although, in our opinion, this can introduce a bias and a systematic error).\"\nI do not understand this sentence. It takes at least 14 days for the immune response to mature, therefore only counting those after 14 days of vaccination will provide the true response to vaccination. Days 1-14 the immune response is not yet complete.\n\n\"Indeed, the Week 36 of 2021 showed an unbalancement in age classes from 40 to 79 years, in which COVID-19 cases in vaccinated exceeded those in not vaccinated persons, although the entire column of vaccinated persons still outnumbered (-17,2%) the column of not vaccinated.\"\nThe authors would need to adjust the analysis to account for the larger number of vaccinated donors in this cohort.\n\nThe fundamental conclusions drawn from the analysis would need to be revisited after the multivariant analysis corrections have been implemented.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [ { "c_id": "8525", "date": "12 Aug 2022", "name": "Marco Alessandria", "role": "Author Response", "response": "Reviewer:The authors have not stratified their data at all, simply looking at whole populations just based on how many vaccines participants have had is not enough. The analysis would need to be redone with multivariate analysis corrections for age, sex, time after vaccination and ethnicity at the very least. Response The ISS official bulletins do not provide all the data and variables needed to implement a multivariate logistic analysis, nor the ISS itself has carried out a multivariate analysis. To comply to your suggestion, we asked the ISS all the needed data to perform this analisys, but the reply was: “… for privacy reasons we are not authorized to provide individual or detailed data as you requested. In any case, if deemed useful, you may consult the page https://www.epicentro.iss.it/coronavirus/aggiornamenti, where the ISS weekly bulletins are stored…”. So we have had to limit our analysis to a non-parametric comparison between groups. Anyhow, we consider that, if a multivariate analysis had brought relevant added value, the ISS itself would have probably implemented it, having all the information. Anyway, we believe that proposing considerations and opening a debate about the ISS data as they are presented, highlighting the emerging trends in those data, might be better than giving up, in absence of information to carry out a more appropriate analysis. For completeness, we performed the non-parametric statistical analysis for all age groups, inserting them in a file entitled \"Supplementary Material\" and sent to the editor for publication on the site. Reviewer: The quality of the figures is not up to standard and a Y-axis should be provided in the longitudinal subfigures. We should be able to understand the data by looking at the figures and legends alone. Response The Figures are produced by the statistical software and meet accuracy standards. As you suggested, longitudinal sub-figures have been corrected by adding the Y axis and the description of the axes. Reviewer: \"The VIVALDI Study11 showed a marginally greater hazard ratio for PCR-positive infection among vaccinated people after first dose of BNT162b2 vaccine within 7-13 days compared to unvaccinated people.\" In this study, this was not significantly different - authors should either remove this reference or state that the difference seen was not statistically significant in the VIVALDI study. Response You are correct. We have added in the text that in the VIVALDI Study the difference is not statistically significant, but that it shows a tendency consistent with the results of other studies, with a mRNA vaccine or even with an inactivated COVID-19 vaccine (CoronaVac): see references. - Craig C. Thinking beyond behavioural change as an explanation for increased COVID post vaccination. BMJ 26 March 2021. Rapid response to: Covid-19: Stronger warnings are needed to curb socialising after vaccination, say doctors and behavioural scientists - BMJ 2021; 372 doi: https://doi.org/10.1136/bmj.n783 (Published 19 March 2021) - U.S. Food and Drug Administration. Emergency Use Authorization (EUA) for an Unapproved Product Review Memorandum. https://www.fda.gov/media/144416/download Hitchings MDT, Ranzani OT, Scaramuzzini Torres MS, et al. Effectiveness of CoronaVac among healthcare workers in the setting of high SARS-CoV-2 Gamma variant transmission in Manaus, Brazil: A test-negative case-control study. Lancet Reg Health Am 2021 Sep;1:100025. doi: 10.1016/j.lana.2021.100025. Epub 2021 Jul 25. Reviewer: The trend of 3D group is growing with an increase of the 253.3%, while the trend of 2D>4m is degrowing with a decrease of the 39.7%. The trend of IC group and 2D<4m are overlapping and show a decrease respectively of 45.5% and 13.9%\" Is this statistically significant on the longitudinal graph? Again, this should be checked for every figure. Response All the significance of the percentage variation were calculated according to the methods described in the text. Reviewer: \"The reason for this choice is that the ISS considers Unvaccinated even people “… vaccinated with either the first dose or single-dose vaccine within the 14 days prior to diagnosis.” (although, in our opinion, this can introduce a bias and a systematic error).\" I do not understand this sentence. It takes at least 14 days for the immune response to mature, therefore only counting those after 14 days of vaccination will provide the true response to vaccination. Days 1-14 the immune response is not yet complete. Response We agree that the full potential of a vaccination can be seen after 14 days from the injection. This is a correct vaccine-oriented perspective. We disagree with the way of setting up the groups by the ISS. In order to appropriately compare the groups, the subjects constituting them should have similar characteristics, as much as possible. In our opinion, it could be useful to separate the subjects vaccinated within 14 days, placing them in a separate group because, if they are aggregated in a single group together with the unvaccinated, they might alter the features of the entire group in an unpredictable way. Moreover, from a safety and person-oriented perspective, it could be useful to separate unvaccinated persons from the subjects who have received the first dose, even in the first 14 days from the inoculation. Reviewer: \"Indeed, the Week 36 of 2021 showed an unbalancement in age classes from 40 to 79 years, in which COVID-19 cases in vaccinated exceeded those in not vaccinated persons, although the entire column of vaccinated persons still outnumbered (-17,2%) the column of not vaccinated.\" The authors would need to adjust the analysis to account for the larger number of vaccinated donors in this cohort. Response Your point is correct. Indeed, the UK Health Security Agency compared eight (about) ten-year classes rates (per 100,000) among persons vaccinated with 2 doses and persons not vaccinated. In addition we have now implemented also a standardization based on the age structure of the English population. This has lead to minor changes in the numbers of the previous version, that we have corrected in the text." } ] } ]	1	https://f1000research.com/articles/11-579
https://f1000research.com/articles/10-377/v1	12 May 21	{ "type": "Systematic Review", "title": "A systematic review of the case findings, testing and management of COVID-19", "authors": [ "Dewi Susanna", "Dian Pratiwi", "Sang Gede Purnama", "Dian Pratiwi", "Sang Gede Purnama" ], "abstract": "Background: Mass testing and adequate management are essential to terminate the spread of coronavirus disease 2019 (COVID-19). This testing is due to the possibility of unidentified cases, especially ones without COVID-19 related symptoms. This review aimed to examine the outcome of the existing studies on the ways of identifying COVID-19 cases, and determine the populations at risk, symptom and diagnostic test management of COVID-19. Methods: The articles reviewed were scientific publications on the PubMed, Science Direct, ProQuest, and Scopus databases. The keywords used to obtain the data were COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and case detection, case management or diagnostic test. We applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Population, Intervention, Control and Outcomes (PICO) approaches. Results: A total of 21 articles from 13 countries met the inclusion criteria and were further analyzed qualitatively. However, 62% of the articles used a rapid antibody test for screening rather than a rapid antigen test. According to the rapid antigen test, 51.3% were positive, with men aged above 50 years recording the highest number of cases. Furthermore, 57.1% of patients were symptomatic, while diagnostic tests' sensitivity and specificity increased to 100% in 14 days after the onset. Conclusions: Real-time polymerase chain reaction (RT-PCR) is recommended by the World Health Organization for detection of COVID-19. Suppose it is unavailable, the rapid antigen test is used as an alternative rather than the rapid antibody test. Diagnosis is expected to be confirmed using the PCR and serological assay to achieve an early diagnosis of COVID-19, according to disease progression, gradual rapid tests can be used, such as rapid antigen in an earlier week and antibody tests confirmed by RT–PCR and serological assay in the second week of COVID-19.", "keywords": [ "COVID-19", "SARS-CoV-2", "case detection mechanism", "case finding", "case management", "diagnostic test" ], "content": "Introduction\n\nThe outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known as coronavirus disease 2019 (COVID-19). This outbreak started in Wuhan Hubei, China, in early December 20191. Presently, an exponential increase in infection cases has been continuously reported in various countries, although vaccinations now accompany this.\n\nCoronaviruses are a group of RNA viruses that cause various respiratory, gastrointestinal, and neurological diseases with mild and severe symptoms in humans and animals. There are at least two types with severe symptoms: Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS). COVID-19, which SARS-CoV-2 causes, is a new type of disease that humans have never identified before. Furthermore, it is regarded as a zoonotic disease (an animal disease transmitted to humans). SARS has been reported in several studies to be transferred from civets to humans while MERS is contacted from camels. Meanwhile, the particular animal source of COVID-19 transmission is still unknown2.\n\nThe governments of various countries have created several services to handle and prevent the spread of COVID-19. Furthermore, several steps have been taken, such as the rapid purchase of test kits, additional health facilities to accommodate patients, laboratories capable of examining blood specimens, human resources, equipment, infrastructure, etc. It is presumed that these additions can suppress the number of positive cases. Patients with symptoms are immediately tested and treated or even monitored; however, the number of positive cases is still increasing.\n\nThe strategies for the prevention and control of COVID-19 include increasing epidemic surveillance, quarantining the infection source, speeding up the diagnosis of suspected cases, optimizing close contact management, constricting the prevention and control of outbreaks. The strategies also prevent possible epidemic rebounds by immediate quarantine of individuals in close contact of positive cases and strengthening community prevention and control measures3. However, early and accurate case findings are necessary to maximize these efforts. Therefore, it is important to review the results of existing studies on finding cases, determine the population at risk, determine diagnostic tests, and provide facilities including human resources and tools to prevent Covid-19 transmission to ending this pandemic.\n\nDue to the influence of COVID-19, several studies have recently been conducted because the pandemic is complex in many aspects of life4–6. The complexity is attributed to the crises experienced in the national health, economic, education, cultural, sports, and social systems6, apart from the drug and vaccine candidates5. The occurrence and development of SARS-CoV-2 depend on the interaction between the virus and the individuals' immune system7. Therefore, its treatment requires special analyses for case findings and management of COVID-19 cases. Presently, there is a controversy over the use of rapid tests and screening for new cases. For instance, Indonesia's government is yet to decide whether rapid tests need to be continued or stopped.\n\nThis review aimed to examine the outcome of the existing studies on the ways of identifying COVID-19 cases, determining the populations at risk, symptom and diagnostic test management of COVID-19.\n\n\nMethods\n\nA systematic review was conducted to identify articles that describe the diagnostic, identification, and management of SARS-CoV-2 and COVID-19 cases. The review is reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines8.\n\nThis review received ethical approval from the Research and Community Engagement Ethical Committee of Faculty of Public Health, Universitas Indonesia Number: Ket-198/UN2.F10.D11/PPM.00.02/2020.\n\nOriginal studies published in open-access journals before 1 August 2020 in English during the COVID-19 pandemic were included. Studies had to include rapid COVID-19 tests and screening. Closed access articles, audio, communication, reviews, reports, perspectives, case studies, surveys, clinical and molecular papers, mathematical modelling, and diagnostic procedures were excluded from this review.\n\nA systematic search was conducted in four databases, specifically SCOPUS, Science Direct, ProQuest and PubMed. The keywords used to obtain data from Science Direct included COVID-19/COVID/coronavirus 2019 OR SARS-CoV-2 AND rapid test OR rapid diagnostic test AND screening.\n\nFor Scopus, the following search was used: ((TITLE-ABS-KEY (covid-19) OR TITLE-ABS-KEY (covid) OR TITLE-ABS-KEY (coronavirus 2019) OR TITLE-ABS-KEY (sars-cov-2) AND TITLE-ABS-KEY (rapid AND test) OR TITLE-ABS-KEY (covid AND diagnostic AND test) AND TITLE-ABS-KEY (screening)).\n\nThe search used for Science Direct was \"COVID-19\" OR COVID OR \"coronavirus 2019\" OR \"SARS-CoV-2\" AND (\"rapid test\" OR \"rapid diagnostic test\") screening. The ProQuest used covid-19 OR covid OR (coronavirus 2019) OR (sars-cov-2) AND (rapid test) OR (rapid diagnostic test) AND (screening).\n\nThe search used for PubMed was ((((covid-19) OR (covid) OR (coronavirus 2019) OR (SARS-CoV-2)) AND (rapid test)) OR (rapid diagnostic test)) AND (screening)))).\n\nThe initial screening was conducted for articles between 1 December 2019 and 31 July 2020. All the authors recorded and reviewed the collected articles. Furthermore, DS determined the study design, time frame, and criteria for the included studies to retrieve the articles and process the data. Importantly, DS retrieved the data from SCOPUS and Science Direct databases, while DP from ProQuest and PubMed databases as SGP's suggestion. The identified articles' information was imported into Excel worksheets and Mendeley Desktop, where duplicates between databases were removed. DS, DP, and SGP separately reviewed the titles to eliminate analysis that does not meet the inclusion criteria before reviewing the title and the abstract. Moreover, DS and DP accessed the full-text articles for the eligibility criteria. In case there were differences in the number of articles obtained, the two authors re-checked the articles again using the same criteria until the same articles are selected. The final decision of articles included was after DS and DP. All authors discussed the variables to assess the full paper using PICOS to determine the study questions. The PICOS's assessment used include 1) Population, 2) Intervention: The diagnostic tests for COVID-19, 3) Comparison: the method of the test and antigen or antibody results, and 4) Outcome: The antibody or antigen tests. Any discrepancies were resolved through consensus via a virtual meeting.\n\nQuality assessment for the selected articles was performed using a modified checklist9 that consisted of seven questions. If the answer of the question is ‘yes’, the value will be ‘1’, while if the answer is ‘no’, the value will be ‘0’. Each article will have a total value, then scored (in %) by calculating the total value divided by the total number of question, then multiplied by 100.\n\nThe score grouped into three scoring (in %) = total score divided by the total number of question, then multiplied by 100; then categorized as ‘good’ (68–100%), satisfactory (34–67%), and bad (0–30%), as shown in Table 1 (as an attachment).\n\nScoring (in %) = total score divided by the total number of question, then multiplied by 100; then categorized as good (68–100%), satisfactory (34–67%), and bad (0–30%)\n\nAll authors designed the variables to be described in the matrix and the topics discussed. The differences in the case detection method of the articles could be a source of bias. To minimize the biases, this review determined and selected the same variables (screening, symptoms, and diagnostic tests; at least an article had one of the following epidemiological parameters regarding COVID-19 or SARS-CoV-2: (i) signs and symptoms, (ii) types of test, (iii) case findings, (iv) screening and testing for COVID-19, (v) procedures for managing positive cases, or (vi) interventions or treatments.). The diagnostic test of each article was different after-time onset. Therefore, the authors used the limit after onset both less and more than 14 days (after onset ≤ 14 days and > 14 days).\n\nThe outcome of the analysis was displayed in a matrix containing the author's name, title, date of research, country of origin of the article, method, and results. Another table included the symptoms, incubation period, method of case finding, diagnostic tests, and type of examination in a more detailed manner. Management identification was based on the type of intervention, care, and treatment.\n\nDescriptive synthesis conducted in the textual description of findings and presented in all tables. A narrative synthesis was undertaken for analysis based on the topics selected. The issues raised included high-risk group, case findings, symptoms of COVID-19 patients, diagnostic test, and the potential strengths and weaknesses of this review, are shown in Table 1. The average quality score was 87.1% and ranged from 71.4% to 100%.\n\n\nResults\n\nBased on the four databases, 152 titles were obtained, with 21 studies included in the review. Figure 1 provides an overview of the articles included. There were 21 eligible articles conducted between December 2019 and 31 July 2020 from 13 countries, including France, the United States of America, Italy, Singapore, Chile, Germany, Taiwan, South Korea, Austria, Bulgaria, Japan, Spanish, and Brazil (Table 2).\n\nCOVID-19:coronavirus disease 2019\n\nELISA : Enzyme linked immunosorbent assay\n\nIgA : Immunoglobulin A\n\nIgG : Immunoglobulin G\n\nIgM : Immunoglobulin M\n\nSARS-CoV-2: severe acute respiratory syndrome coronavirus 2\n\nEach country has its reasons and policies for adopting the coronavirus screening method. Besides polymerase chain reaction (PCR), antigen and antibody tests, there are various tests for detecting the virus, such as the use of clinical immunoassays. An immunoassay is a biomedical test for measuring molecules' presence in a solution through the use of antibodies or antigens10.\n\nA rapid test is the screening method for detecting COVID-19 that shows the results quickly, specifically between a few minutes to a maximum of one hour. The methods in Table 3 are divided into two, namely the antigen and antibody rapid tests. The rapid antigen test is used to detect a viral protein (antigen) and is detected when the virus is actively replicating. Conversely, the rapid antibody test is used to detect antibodies or immunoglobins produced by the body against the virus. According to Table 3, showing the screening tests used in the studies, 62% of the articles (13/21) adopted the rapid antibody and antigen tests, for mostly males aged over 50 years. The rapid antigen test results showed that 51.3% were positive, as shown in Table 3.\n\nLegend: NA= Not Available\n\nThe terms for COVID-19 patients are divided into several groups, namely patients under monitoring or confirmed cases without symptoms11. The clinical manifestations of COVID-19 patients have a broad spectrum, ranging from lack of symptoms to mild illnesses, pneumonia, severe pneumonia, and septic shock. In Table 4, the symptoms were divided into two groups, namely typical and atypical. Typical symptoms are the most frequently reported clinical manifestations. The virus enters through the nose and mouth and attacks the respiratory tract with typical symptoms, namely fever > 38°C and cough12. Conversely, atypical symptoms are clinical manifestations originating from organs other than the lungs. The reactive results from patients examined by the rapid test showed that 42.9% were asymptomatic or lacked available data. In comparison, 57.1% were symptomatic, with typical symptoms such as fever, cough, respiratory syndrome, sore throat, pneumonia, loss of taste and smell, and atypical symptoms including malaise, nausea, gastrointestinal disorders, headaches, and fatigue, as shown in Table 4.\n\nLegend: NA= Not Available\n\nThe rapid test is verified through a diagnostic test to confirm the patients' status, whether positive or negative. Real-time polymerase chain reaction (RT-PCR) testing of SARS-CoV-2 has become a standard method for direct diagnosis. Currently, RT-PCR is used to diagnose COVID-19 by detecting genetic material of the coronavirus13. Serologic and immunological tests such as ELISA (enzyme linked immunosorbent assay), POC or LFA (point-of-care lateral flow assay), and CLIA (chemiluminescence immunoassay) complement RT-PCR examinations in screening and diagnosis of COVID-19.\n\nMeanwhile, the POC or LFA is a type of rapid examination for diagnosing infectious diseases and the results are shown within minutes, permitting quick decisions regarding the patients' care. POC also extends its testing to communities and populations that do not have easy access to health care14. ELISA is an analytical biochemical test that is used to evaluate the presence of an antigen or antibody in a sample. It is useful in the determination of serum antibody concentration15. CLIA is the assay for detection antibodies against the SARS-CoV-2 nucleoprotein (Np) in serum or plasma.\n\nOnly 11 articles out of 21 titles provided sensitivity or specificity data (Table 5a and Table 5b). At 14 days after symptom onset, the test results were in IgG, IgM, and IgA (antibody) values, because at that particular time-point, antibodies have formed. Immunoglobin M (IgM) tends to increase within 3–14 days after infection and is replaced by Immunoglobin G (IgG) for 7 to 15 days, which tends to remain detectable for months. Meanwhile, immunoglobin A (IgA) is usually used to diagnose disorders in the immune system and detect mucosal secretions such as saliva. The sensitivity indicates the ability of the test to show a positive result. Therefore, the higher the test sensitivity, the greater the positive test results, and the lesser the number of false negatives.\n\nSpecificity indicates a test's ability to show a negative result for individuals who do not have the virus. Therefore, the higher it is, the more negative test results, or the fewer false positives16. Overall, the sensitivity and specificity tend to be accurate or have high values after 14 days of onset with 100 for all immunoassay assays, as shown in Table 5a and Table 5b.\n\nSe: sensitivity\n\nSp: specificity\n\nRT-PCR : Real time-polymerase chain reaction\n\nELISA: Enzyme-linked immunosorbent assay\n\nPOC LFA: Point-of-care lateral flow assay\n\nCLIA: Chemiluminescence immunoassay\n\nNA=Not available\n\n\nDiscussion\n\nIndonesia's government implemented a Rapid Test policy to accelerate the early detection of confirmed cases, both among health workers and other high-risk groups. However, this test has drawbacks because positive results are only obtainable among individuals with COVID-19 antibodies in their blood, which are generally formed on the seventh day after infection. Consequently, there is a possibility of the result being negative but does not mean that the individual is not infected. This occurrence is since the antibodies are yet to be formed; therefore, repetition is needed. The implementation of the rapid test is intended for individuals that are at risk. However, in this current condition, mass testing could be carried out considering the number of infected people without symptoms that have not received treatment and monitoring, which are all sources of transmission.\n\nThe elderly and individuals with pre-existing medical conditions such as high blood pressure, heart and lung disorders, diabetes, and cancer are at greater risk of experiencing severe COVID-19 symptoms38. Furthermore, travelers and individuals who have had close contact with infected individuals and medical personnel39. Therefore, surveillance for this group needs to be carried out daily with active case finding through screening for signs and symptoms and checking body temperature39. Based on gender distribution, males are presumed to be associated with a higher prevalence of active smoking40. It is suspected that there is an increase in ACE2 receptor expression in smokers, people with hypertension, and diabetes mellitus40,41.\n\nThe COVID-19 pandemic has been driven by cross-border human mobility and region-specific COVID-19 susceptibilityy42. The diagnosis of new cases is inseparable from early precautions2. One method of how a diagnosis is carried out is via screening. During the COVID-19 pandemic, screening at airports has been a priority due to its spread in 113 countries globally, which allegedly started in Wuhan (China). Initially, it was only a thermal test developed into a quarantine system at airports or ports. While active screening at airports is still an effective method for detecting new diseases, it does not provide 100% efficacy in case detection43 because there are passive cases that are yet reported at health services.\n\nSurveillance activities may be either passive or active. In passive surveillance, the health department passively receives reports of suspected injury or illness. Conversely, epidemiologists actively seek out cases of disease44. The detection of passive cases is triggered by patients seeking to be treated by doctors working in health facilities. Meanwhile, active screening detects 80% and 20% of imported and passive cases, respectively43.\n\nThe active case findings under rapid tests in the community, for instance, in Indonesia, are currently being carried out by inviting individuals to various designated places, such as the health office, stadium, village centers, markets, and schools. South Korea adopted a test kit from SD Biosensor to carry out mass testing in its country as a preventive. This test has proven to be a practical rapid screening step, consequently reducing the death rate. However, this rapid test is also supported by the PCR test with free drive-through service. The test kit's performance is influenced by several factors, such as the period of emergence of symptoms, the concentration of virus in the specimen, quality and method of processing, and the reagent formulation in test kit45.\n\nThe terms for COVID-19 patients are divided into several groups, namely patients under monitoring (ODP) or close contacts, patients under supervision (PDP) or suspected cases, and patients without symptoms (OTG) or confirmed cases without symptoms11. The clinical manifestations of COVID-19 have a broad spectrum, ranging from asymptomatic, mild symptoms, pneumonia, severe pneumonia, acute respiratory distress syndrome (ARDS), sepsis to septic shock. Approximately 80% of cases have been classified as mild or moderate, 13.8% as severe, and over 6.1% as under critical condition46. These manifestations usually appear within 2 to 14 days after exposure and common signs include acute respiratory symptoms such as fever, cough, and difficulty breathing. In severe cases, COVID-19 symptoms include pneumonia, ARDS, kidney failure, and even death. The severity of symptoms is influenced by the immune system, age, certain comorbidities such as hypertension, diabetes mellitus, asthma, heart disease, obesity, and some habits such as smoking, lack of exercise, and staying in poorly ventilated rooms47.\n\nThe incubation period from when the virus was initially contracted to manifesting the first symptoms is usually 5 to 7 days (or within the range of 4–14 days). Current infection diagnosis relies on tests to detect the virus in various bodily fluids. Previous infections are confirmed through blood tests, and negative tests presume immunity to re-infection, although the duration and effectiveness of this protection are still unknown48.\n\nLaboratory-based molecular tests for detecting SARS-CoV-2 in the respiratory specimens are the current reference standard used to diagnose COVID-19, although serological immunoassays are rapidly being developed49. One example of detection used respiratory specimens was conducted in Independent and Assisted Living Community for Older Adults —Seattle, Washington42. The detection of SARS-CoV-2 using nasopharyngeal swabs was carried out twice, precisely day-one and seven, on the staff members. The positive cases in the first round were isolated immediately using personal protective equipment irrespective of whether they showed no symptoms. Furthermore, in the second round, positive cases were also discovered among the people who did not have symptoms initially. This analysis needs to be carried out because positive cases are bound to be found in the housing of a group of elderly or nursing homes. Therefore, this examination need not be carried out only once42. IgM detection and IgA detection were possible from days 3 to 6 after the onset of the symptoms, while IgG starts to emerge from days 10 to 1850. Consequently, rapid antibody test is not recommended by the World Health Organization (WHO) as the primary basis for diagnosis. Therefore, serologically negative patients still need to be observed and re-examined to be confirmed51.\n\nThis study reported that all COVID-19 tests are effective when carried out in accordance with their purpose and objectives. However, not all studies reviewed have a similar pattern. Therefore only a few were compared. Meanwhile, the cost of rapid testing was not discussed, which varies widely and allows for differences in the examinations' quality.\n\n\nConclusion\n\nThe elderly and individuals with pre-existing medical conditions such as high blood pressure, heart and lung disorders, diabetes, and cancer are at greater risk of experiencing severe COVID-19 symptoms. Finding new COVID-19 cases during this pandemic situation is extremely necessary to aid early detection with proper and mass surveillance. Therefore, treatments can be quickly administered and the source of transmission reduced. Tests for COVID-19 are generally divided into two, namely targeting the virus RNA and protein. The PCR method is targeted for RNA, while rapid tests for antigens and antibodies are targeted for proteins. The accuracy of these tests is supported by the sampling method from the incubation, emergence of symptoms, and healing period. Furthermore, the exposed individuals' contact history or positive case is also a significant factor determining sampling time with the appropriate type of test. The WHO recommends a rapid antigen test as an alternative supposing PCR is not available, therefore interfering with the handling of COVID-19 patients and the pandemic response process52. Meanwhile, the rapid antigen test is effective when the number of cases is high because it detects virus material directly after symptoms. The result is known faster than the PCR test, compared to the rapid antibody test that increases in the second and third weeks after the onset of symptoms. Therefore, the order starts from the PCR test, then supposing it is unavailable, the rapid antigen test serves as an alternative when compared with the antibody test. However, the diagnosis should be confirmed using the PCR. Based on this study, the accuracy of most diagnostic tests such as RT-PCR, ELISA, POC LFA, CLIA, CEFA, and MIA sensitivity and specificity is increased in the late phase (> 14 days) after the onset of symptoms. This accuracy is helpful in the identification of individuals that have been exposed to COVID-19. To achieve an early diagnosis of COVID-19, according to disease progression, gradual rapid tests can be used, such as rapid antigen in an earlier week and antibody tests confirmed by RT–PCR and serological assay in the second week of COVID-19.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\nFigshare: PRISMA checklist for 'A systematic review on the case findings and management of COVID-19; in the link https://doi.org/10.6084/m9.figshare.13586081.v18\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgments\n\nThe authors would like to thank to the Directorate of Research and Development Universitas Indonesia for supporting the financial through Grant No NKB-2605/UN2.RST/HKP.05.00/2020. The authors also gratefully acknowledge the Library of Universitas Indonesia for providing the databases used in this review.\n\n\nReferences\n\nLim J, Jeon S, Shin HY, et al.: Case of the index patient who caused tertiary transmission of coronavirus disease 2019 in Korea: The application of lopinavir/ritonavir for the treatment of COVID-19 pneumonia monitored by quantitative RT-PCR. J Korean Med Sci. 2020; 35(6): e79. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKemenkes RI: PEDOMAN PENCEGAHAN DAN PENGENDALIAN CORONAVIRUS DISESASE (COVID-19). 2020; 1–214. Reference Source\n\nXu TL, Ao MY, Zhou X, et al.: China's practice to prevent and control COVID-19 in the context of large population movement. Infect Dis Poverty. 2020; 9(1): 115. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nEl‐Taliawi OG, Hartley K: The COVID-19 crisis and complexity: A soft systems approach. J Contingencies Cris Manag. 2020; 1468–5973.12337. Publisher Full Text\n\nShariare MH, Parvez MAK, Karikas GA, et al.: The growing complexity of COVID-19 drug and vaccine candidates: challenges and critical transitions. J Infect Public Health. 2020; 14(2): 214–220. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBratianu C: Toward understanding the complexity of the COVID-19 crisis: A grounded theory approach. Manag Mark. 2020; 15(s1): 410–423. Publisher Full Text\n\nLi X, Geng M, Peng Y, et al.: Molecular immune pathogenesis and diagnosis of COVID-19. J Pharm Anal. 2020; 10(2): 102–108. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSusanna D: A systematic review on the case findings and management of COVID-19. figshare. Dataset. 2021. http://www.doi.org/10.6084/m9.figshare.13586081.v1\n\nSchenck R, Blaauw D, Viljoen K: Enabling factors for the existence of waste pickers: A systematic review. Soc Work (South Africa). 2016; 52(1): 35–53. Publisher Full Text\n\nYetisen AK, Akram MS, Lowe CR: Paper-based microfluidic point-of-care diagnostic devices. Lab Chip. 2013; 13(12): 2210–2251. PubMed Abstract \| Publisher Full Text\n\nBNPB: Gugus tugas percepatan penanganan covid-19. 2020; 1–39. Reference Source\n\nWHO: WHO COVID-19 : Case Definitions. 2020; 2020. Reference Source\n\nJawerth N: How is the COVID-19 Virus Detected using Real Time RT-PCR? 2020; 1–6. Reference Source\n\nCDC: Symptoms of Coronavirus ( COVID-19 ). 2020; 316475. Reference Source\n\nMedline: Screening and diagnosis for HIV How the Test is Performed. 2020; 11–14. Reference Source\n\nGede IW, Eka A, Epid M, et al.: UJI DIAGNOSTIK DAN SKRINING. 2016.\n\nKimball A, Hatfield KM, Arons M, et al.: Asymptomatic and Presymptomatic SARS-CoV-2 Infections in Residents of a Long-Term Care Skilled Nursing Facility — King County, Washington, March 2020. MMWR Morb Mortal Wkly Rep. 2020; 69(13): 377–381. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLorenzo D, Carrisi C: COVID-19 exposure risk for family members of healthcare workers : An observational study. Int J Infect Dis. 2020; 98: 287–289. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTuaillon E, Bolloré K, Pisoni A, et al.: Detection of SARS-CoV-2 antibodies using commercial assays and seroconversion patterns in hospitalized patients. J Infect. 2020; 81(2): e39–e45. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDemey B, Daher N, François C, et al.: Dynamic profile for the detection of anti-SARS-CoV-2 antibodies using four immunochromatographic assays. J Infect. 2020; 81(2): e6–e10. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSun Y, Koh V, Marimuthu K, et al.: Epidemiological and Clinical Predictors of COVID-19. Clin Infect Dis. 2020; 71(15): 786–792. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMargiotti K, Cupellaro M, Emili S, et al.: Evaluation of A Rapid IgM-IgG Combined Antibody Test for SARS-CoV-2 Infection : Single Italian Center Study. Am J Infect Dis. 2020; 16(2): 85–88. Publisher Full Text\n\nPorte L, Legarraga P, Vollrath V, et al.: Evaluation of a novel antigen-based rapid detection test for the diagnosis of SARS-CoV-2 in respiratory samples. Int J Infect Dis. 2020; 99: 328–333. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWu JL, Tseng WP, Lin CH, et al.: Four point-of-care lateral flow immunoassays for diagnosis of COVID-19 and for assessing dynamics of antibody responses to SARS-CoV-2. J Infect. 2020; 81(3): 435–442. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCho J, Kang SH, Park HC, et al.: Hemodialysis with Cohort Isolation to Prevent Secondary Transmission during a COVID-19 Outbreak in Korea. J Am Soc Nephrol. 2020; 31(7): 1398–1408. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNepogodiev D, Bhangu A, Glasbey JC, et al.: Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study. Lancet. 2020; 396(10243): 27–38. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWeidner L, Gänsdorfer S, Unterweger S, et al.: Quantification of SARS-CoV-2 antibodies with eight commercially available immunoassays. J Clin Virol. 2020; 129: 104540. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDöhla M, Boesecke C, Schulte B, et al.: Rapid point-of-care testing for SARS-CoV-2 in a community screening setting shows low sensitivity. Public Health. 2020; 182: 170–172. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAzzi L, Carcano G, Gianfagna F, et al.: Saliva is a reliable tool to detect SARS-CoV-2. J Infect. 2020; 81(1): e45–e50. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTsaneva-damyanova D: SARS-CoV-2 : seroepidemiological pattern in northeastern Bulgaria. Biotechnol Biotechnol Equip. 2020; 34(1): 441–446. Publisher Full Text\n\nBanerjee A, Ray S, Vorselaars B, et al.: Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population. Int Immunopharmacol. 2020; 86: 106705. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLiu A, Li Y, Huang Y, et al.: Antibody responses against SARS-CoV-2 in COVID-19 patients. J Med Virol. 2020; 93(1): 144–148. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nZhou W, Xu X, Chang Z, et al.: The dynamic changes of serum IgM and IgG against SARS-CoV-2 in patients with COVID-19. J Med Virol. 2020; 93(2): 924–933. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKaneko S: Clinical validation of an immunochromatographic SARS-Cov-2 IgM/IgG antibody assay with Japanese cohort. J Med Virol. 2021; 93(1): 569–572. PubMed Abstract \| Publisher Full Text\n\nYu H, Sun B, Fang Z, et al.: Distinct features of SARS-CoV-2-specific IgA response in COVID-19 patients. Eur Respir J. 2020; 56(2): 2001526. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nde la Iglesia J, Fernández-Villa T, Fegeneda-Grandes JM, et al.: Concordance between two rapid diagnostic tests for the detection of antibodies against SARS-CoV-2. Semergen. 2020; 46 Suppl 1: 21–25. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSotgiu G, Barassi A, Miozzo M, et al.: SARS-CoV-2 specific serological pattern in healthcare workers of an Italian COVID-19 forefront hospital. BMC Pulm Med. 2020; 20(1): 203. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWHO: COVID-19 : vulnerable and high risk groups. 2020; 1–6.\n\nKementerian Kesehatan Republik Indonesia: PEDOMAN PENCEGAHAN DAN PENGENDALIAN CORONAVIRUS DISESASE (COVID-19). REV-5. (Aziza Listiana; Aqmarina Adistiqah; Insan Maulidiah, ed.). Jakarta: Kementerian Kesehatan RI; 2020; Accessed January 8, 2021. Reference Source\n\nCai H: Sex difference and smoking predisposition in patients with COVID-19. Lancet Respir Med. 2020; 8(4): e20. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFang L, Karakiulakis G, Roth M: Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection? Lancet Respir Med. 2020; 8(4): e21. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRoxby AC, Greninger AL, Hatfield KM, et al.: Detection of SARS-CoV-2 Among Residents and Staff Members of an Independent and Assisted Living Community for Older Adults — Seattle, Washington, 2020. MMWR Morb Mortal Wkly Rep. 2020; 69(14): 416–418. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSookaromdee P, Wiwanitkit V: Imported Novel Coronavirus Infections: Observation on Active and Passive Case Detection in Thailand. Popul Health Manag. 2021; 24(1): 149. PubMed Abstract \| Publisher Full Text\n\nJamison DT, Breman JG, Measham AR, et al.: Disease Control Priorities in Developing Countries 2nd Edition. Second edi. Washington DC: The International Bank for Reconstruction and Development / The World Bank; 2006; Accessed December 28, 2020. Reference Source\n\nWorld Health Organization: Manual for the Laboratory Diagnosis and Virological Surveillance of Influenza. Malta; 2011. Reference Source\n\nWHO: Report of the WHO-China Joint Mission on Coronavirus Disease 2019 ( COVID-19 ). 2020; 2019: 16–24. Reference Source\n\nNadia: KESIAPAN KEMENKES DALAM MENGHADAPI OUTBREAK NOVEL CORONAVIRUS ( 2019-nCoV ). 2020.\n\nBeeching NJ, Fletcher TE, Beadsworth MBJ: Covid-19 : testing times. Rapid near patient testing for both current and past infections is urgently required. BMJ. 2020; 369: m1403. PubMed Abstract \| Publisher Full Text\n\nCheng MP, Papenburg J, Desjardins M, et al.: Diagnostic Testing for Severe Acute Respiratory Syndrome-Related Coronavirus 2: A Narrative Review. Ann Intern Med. 2020; 172(11): 726–734. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGuo L, Ren L, Yang S, et al.: Profiling Early Humoral Response to Diagnose Novel Coronavirus Disease (COVID-19). Clin Infect Dis. 2020; 71(15): 778–785. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWHO: Laboratory testing for coronavirus disease 2019 ( COVID-19 ) in suspected human cases. 2020; 2019. Reference Source\n\nWHO (World Health Organization): Saran Penggunaan Tes Imunodiagnostik Di Fasyankes ( Point of Care ) Untuk COVID-19. 2020. Reference Source" }	[ { "id": "94254", "date": "04 Oct 2021", "name": "Sonu Menachem Maimonides Bhaskar", "expertise": [ "Reviewer Expertise COVID-19", "Public Health", "Epidemiology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is an interesting review of the case findings, testing, and management of COVID-19. The article needs substantial revision for its content. Here are some general comments for the authors to consider:\nIn the Abstract, the authors state \"This review aimed to examine the outcome of the existing studies on the ways of identifying COVID-19 cases...\", please revise this to \"..examine the variations in COVID-19 diagnostic testing and clinical characteristics across various studies.\". The study doesn't provide data on management protocols or on the outcomes.\n\nThe Discussion lacks a concrete summary. Please summarise the findings relevant to this systematic review.\n\nTable 1 should be provided as a part of the Results.\n\nIn Table 2, the data on clinical characteristics, such as risk factors, COVID-19 severity, etc., are not provided and could be included. Moreover, please change the legend of Table 2 to \"Clinical and demographic characteristics of studies included in the systematic review\".\n\nIn the Discussion, \"High-risk group\" section, the authors make statements that are not appropriately referenced and lacks context from the standpoint of the overall findings of this review.\n\nThe authors discuss the symptoms in Table 4; however, several studies have not reported on various symptoms or data is simply not available?\n\nThe authors conclude \"The elderly and individuals with pre-existing medical conditions such as high blood pressure, heart and lung disorders, diabetes, and cancer are at greater risk of experiencing severe COVID-19 symptoms.\". But this is not supported by the findings of this study. The authors didn't examine these associations in this systematic review.\n\nThe Conclusion and Discussion need substantial revision focussing on the findings of this systematic review only. The accuracy of rapid antigen tests remains debatable, therefore, unless not available, RT-PCR should be preferred as the first-line strategy.\n\nThe authors need to expand upon the statistical analysis, as in what descriptive statistics were used for subgroup analyses.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Partly\n\nIs the statistical analysis and its interpretation appropriate? Partly\n\nAre the conclusions drawn adequately supported by the results presented in the review? No", "responses": [ { "c_id": "7510", "date": "02 Feb 2022", "name": "Dewi Susanna", "role": "Author Response", "response": "Dear editor and reviewer, Here are our responses to the reviewer comments and suggestions: 1. In the Abstract, the authors state, \"This review aimed to examine the outcome of the existing studies on the ways of identifying COVID-19 cases...\", please revise this to \"..examine the variations in COVID-19 diagnostic testing and clinical characteristics across various studies.\". The study doesn't provide data on management protocols or on the outcomes. Author Responses: The aim of this abstract and the last part of the introduction was revised as follows: The review aimed to examine the variations in COVID-19 diagnostic testing and clinical characteristics across various studies 2. The Discussion lacks a concrete summary. Please summarise the findings relevant to this systematic review. Author Responses: The revision of the Discussion is as follows: a. The section High-Risk Group was changed with Commorbidies and added for the new Discussion: Comorbidities: COVID-19 patients with other comorbidities such as chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), hypertension, cancer, diabetes, HIV, chronic kidney disease can cause a high risk of death. Comorbidities cause COVID-19 patients to be more at risk of increased morbidity and mortality 42-45. A cohort study in Jakarta also found a higher risk of death with comorbid patients than those without, the risk increasing sixfold among patients <50 years of age 46. Therefore, comorbidities can exacerbate COVID-19 infection 47. Here are the added references, so the reference list must be reordered. 41. Ejaz H, Alsrhani A, Zafar A, Javed H, Junaid K, Abdalla AE, et al. COVID-19 and comorbidities: Deleterious impact on infected patients. J Infect Public Health [Internet]. 2020 Dec 1 [cited 2021 Nov 27];13(12):1833–9. Available from: https://pubmed.ncbi.nlm.nih.gov/32788073/ 42. Sanyaolu A, Okorie C, Marinkovic A, Patidar R, Younis K, Desai P, et al. Comorbidity and its Impact on Patients with COVID-19. SN Compr Clin Med. 2020;2(8):1069–76. 43 Fathi M, Vakili K, Sayehmiri F, Mohamadkhani A, Hajiesmaeili M, Rezaei-Tavirani M, et al. The prognostic value of comorbidity for the severity of COVID-19: A systematic review and meta-analysis study. PLoS One [Internet]. 2021;16(2 February):1–25. Available from: http://dx.doi.org/10.1371/journal.pone.0246190 44. Surendra H, Elyazar IR, Djaafara BA, Ekawati LL, Saraswati K, Adrian V, et al. Clinical characteristics and mortality associated with COVID-19 in Jakarta, Indonesia: A hospital-based retrospective cohort study. Lancet Reg Heal - West Pacific [Internet]. 2021;9:100108. Available from: https://doi.org/10.1016/j.lanwpc.2021.100108 45. Klein F. Risikofaktor Komorbiditäten bei COVID-19- Erkrankung. Pneumologie. 2020;74(10):640. b. The findings were summarised to relevant review: The last part of the Discussion summarised the review as follows: Various screening methods are used to detect COVID-19, such as rapid antigen and antibody tests. Early diagnosis of COVID-19 requires gradual tests such as a screening test by conducting a rapid antigen test a week earlier and an antibody test that needs to be confirmed by RT-PCR and serological tests in the second week of COVID-19. Based on this study, the accuracy of most diagnostic tests such as RT-PCR, ELISA, POC LFA, CLIA, CEFA, and MIA the sensitivity and specificity increased in the late phase (>14 days) after the onset of symptoms. This accuracy helps identify individuals who have been exposed to COVID-19. 3. Table 1 should be provided as a part of the Results. Author Responses: Table 1 moved to the results. It is put after Figure 1. 4. In Table 2, the data on clinical characteristics, such as risk factors, COVID-19 severity, etc., are not provided and could be included. Moreover, please change the legend of Table 2 to \"Clinical and demographic characteristics of studies included in the systematic review\". Author Responses: The legend of Table 2 is replaced with: “Clinical and demographic characteristics of studies included in the systematic review” 5. In the Discussion, \"High-risk group\" section, the authors make statements that are not appropriately referenced and lacks context from the standpoint of the overall findings of this review: Author Responses: The section High-Risk Group was changed with Comorbidities and the Discussion added information as shown in responses No. 2.b above. 6. The authors discuss the symptoms in Table 4; however, several studies have not reported on various symptoms or data is simply not available? Author Responses: The characteristics of the symptoms shown are following the results of the journals reviewed. 7. The authors conclude \"The elderly and individuals with pre-existing medical conditions such as high blood pressure, heart and lung disorders, diabetes, and cancer are at greater risk of experiencing severe COVID-19 symptoms.\". But this is not supported by the findings of this study. The authors didn't examine these associations in this systematic review. Author Responses: The findings: \"The elderly and individuals with pre-existing medical conditions such as high blood pressure, heart and lung disorders, diabetes, and cancer are at greater risk of experiencing severe COVID-19 symptoms” was deleted since it is not supported by the data and the authors did not measure the associations. 8. The Conclusion and Discussion need substantial revision focussing on the findings of this systematic review only. The accuracy of rapid antigen tests remains debatable; therefore, unless not available, RT-PCR should be preferred as the first-line strategy. Author Responses: ‘The accuracy of rapid antigen tests remains debatable; therefore, RT-PCR should be preferred unless not available as the first-line strategy’ was put in the first line of the conclusion. 9. The authors need to expand upon the statistical analysis, as in what descriptive statistics were used for subgroup analyses: Author Responses: The authors did not use statistical analysis, for instance, a meta-analysis, because quantitative data such as Odds ratio, p-value, etc. were not supported in the articles selected." } ] } ]	1	https://f1000research.com/articles/10-377
https://f1000research.com/articles/9-1263/v1	22 Oct 20	{ "type": "Method Article", "title": "An R-based reproducible and user-friendly preprocessing pipeline for CyTOF data", "authors": [ "Helena L. Crowell", "Stéphane Chevrier", "Andrea Jacobs", "Sujana Sivapatham", "Tumor Profiler Consortium", "Bernd Bodenmiller", "Mark D. Robinson", "Stéphane Chevrier", "Andrea Jacobs", "Sujana Sivapatham", "Bernd Bodenmiller", "Mark D. Robinson" ], "abstract": "Mass cytometry (CyTOF) has become a method of choice for in-depth characterization of tissue heterogeneity in health and disease, and is currently implemented in multiple clinical trials, where higher quality standards must be met. Currently, preprocessing of raw files is commonly performed in independent standalone tools, which makes it difficult to reproduce. Here, we present an R pipeline based on an updated version of CATALYST that covers all preprocessing steps required for downstream mass cytometry analysis in a fully reproducible way. This new version of CATALYST is based on Bioconductor’s SingleCellExperiment class and fully unit tested. The R-based pipeline includes file concatenation, bead-based normalization, single-cell deconvolution, spillover compensation and live cell gating after debris and doublet removal. Importantly, this pipeline also includes different quality checks to assess machine sensitivity and staining performance while allowing also for batch correction. This pipeline is based on open source R packages and can be easily be adapted to different study designs. It therefore has the potential to significantly facilitate the work of CyTOF users while increasing the quality and reproducibility of data generated with this technology.", "keywords": [ "CyTOF", "Preprocessing", "Normalization", "Debarcoding", "Compensation", "Gating", "Batch correction", "Reproducibility" ], "content": "Introduction\n\nOver the past decade, mass cytometry (CyTOF) has advanced our understanding of a wide range of cellular processes, particularly in the field of immunology and tumor biology1,2, by enabling the simultaneous measurement of 40+ parameters at the single cell level. Currently, mass cytometry is transitioning from an exploratory research approach toward a diagnostic tool used in clinical laboratories and this transition is associated with an increased need for standardization3. Various studies have already suggested improvements on the experimental workflows to increase the robustness of mass cytometry data by working with frozen antibody cocktails or by including shared reference samples in each independent experiment to enable for batch correction4,5. Similarly, advanced downstream analyses benefit from the large number of analysis tools and algorithms implemented in R, which allow for fully reproducible analyses6.\n\nBetween data generation and downstream data analysis, data preprocessing is a multi-step procedure required to convert raw FCS files into data objects that can be input to downstream statistical analysis and visualization7. Upon data collection, the first step consists in concatenating files from sequential CyTOF runs and removing events of the acquisition with unstable signal, which are usually caused by uneven flow rate or introduction of air in the fluidic system. As a second step, CyTOF data need to be corrected for time dependent signal drift, which is mostly due to cone contamination, mass calibration drift or loss of detector sensitivity over time. This correction is performed by acquiring metal tagged polystyrene beads together with the cell suspension, where bead signals can be used as a reference to normalize the cell signals8. Another potential artefact in CyTOF data is due to signal spillover between channels. Although lower than what is usually observed in fluorescent flow cytometry, spillover in mass cytometry can still account for up to 4% of the signal in some channels and needs to be corrected using signal compensation9. Sample barcoding prior to staining is a common approach used in mass cytometry to combine multiple samples in a single experiment to minimize experimental variation due to staining and CyTOF acquisition. In this case, individual cells have to be assigned to their respective sample via a process called single cell debarcoding10. In large studies where samples are collected over a long period of time by different users, on different machines or at different sites, an important step is to correct for batch effects, which can be achieved by including a shared control sample in each independent batch11,12. Finally, only live, intact single cells are relevant for the downstream analysis. Beads, doublets, debris and dead cells are excluded by gating on scatter plots7.\n\nEach step of the preprocessing pipeline requires expert decisions to determine the best parameters to achieve an optimal signal correction and cell selection. Moreover, all the chosen parameters should be recorded for reproducibility purposes. Despite these requirements, many current preprocessing pipelines still rely on switching between platforms that include, for example, MATLAB applications and (at least partially) closed source online platforms (e.g., Cytobank13). This approach necessitates uploading the data to different platforms and carrying out certain steps in a purely manual fashion, which makes it time-consuming and difficult to reproduce. This is particularly limiting in a clinical setting, where reproducibility and large-scale data analysis are required. Thus, we propose a semi-automated R-based preprocessing pipeline for CyTOF data that is: i) fully reproducible; ii) includes quality checks and, iii) has limited need for supervision once the original setup has been made. This pipeline is developed around an updated version of CATALYST, an R package designed for preprocessing and differential analysis of mass cytometry data9,14. This new version of CATALYST is based on Bioconductor’s SingleCellExperiment class, the standard for high dimensional single cell data analysis. This pipeline can easily be adapted to each CyTOF user’s needs and will accelerate CyTOF data preprocessing while improving the quality of mass cytometry data generated.\n\nThe data used in this pipeline were generated in the context of the Tumor Profiler project, a multi-center observational study investigating the relevance of different innovative technologies, including CyTOF, imaging mass cytometry, single-cell DNA and RNA sequencing, as well as ex vivo drug testing to improve the diagnostic of advanced cancer patients15.\n\nThe samples of interest included blood samples and tumor biopsies collected at the University Hospital Zurich in spring 2020. These samples were assessed by mass cytometry in the context of a set of references including commercially available cell lines, PBMCs from healthy donors and PHA activated PBMCs. PBMCs from patients and healthy donors were collected based on a ficoll gradient16, and tumor samples were dissociated as previously described17. Once in single-cell suspension, all samples were stained for 5 min on ice with Cell-ID TM Cisplatin-194Pt (#201194, Fluidigm) to identify dead cells and subsequently fixed with PFA 1.6% (#15710, Electron Microscopy Sciences). Samples were stored as dry pellet at −80° C until CyTOF measurement.\n\nThe dataset used in this study was obtained from a single CyTOF run containing nine references, three blood samples and three tumor samples barcoded with a 20-well barcoding plate17. Reference samples were selected to contain positive and negative populations for each marker included in the study’s antibody panel. This design was chosen to enable for quality control and batch correction across independent experiments based on quantile scaling as described in Schuyler et al.11. After barcoding, pooled cells were stained at 4 degree for 1h with a 40-Ab panel designed to perform an in-depth characterization of the samples’ immune compartment. DNA intercalation was performed with a 1h room temperature incubation in Cell-ID Intercalator-Ir (#201192B, Fluidigm). Finally, the cell suspension was diluted 1:10 in Maxpar® Cell Acquisition Solution (#201240, Fluidigm) and 10% of EQ Four Element Calibration Beads (#201078, Fluidigm), and acquired on a HeliosTM upgraded CyTOF 2 system at a flow rate of 150 events per second.\n\nThroughout this workflow, we will make use of a set of metadata for standard preprocessing steps (normalization, debarcoding and compensation), as well as various quality controls. An overview of the metadata used is given in Table 1. All data used are provided as underlying data18.\n\nMost data used and returned throughout this workflow are kept in an object of Bioconductor’s SingleCellExperiment (SCE) class from the SingleCellExperiment package19. This data structure can store all single-cell related data (measurement data and transformations thereof; cell, feature and experiment-wide metadata; dimensionality reductions), allowing for synchronized and thus less error-prone data manipulation.\n\nThe key component of SCEs are matrix-like assays, where rows are features (targets) and columns are observations (cells), that store the measurement data and any data derived thereof. Metadata associated with cells are stored under colData, feature metadata under rowData, and any experiment-wide metadata may be stored in the metadata slot. Lastly, the SCE can store an arbitrary number of dimensionality reductions under reducedDims. For a more detailed description of usage and structure of SCEs, we refer to the SingleCellExperiment package’s documentation.\n\n\nResults\n\nThe pipeline presented here describes all steps required to process raw mass cytometry data to a state where the user may proceed with downstream analyses (e.g., dimensionality reduction, differential analysis, trajectory inference). The process includes the concatenation of the individual acquisitions, the exclusion of part of the acquisition with unstable signal, the correction for time-dependent signal drift via bead normalization, the correction for signal spillover via compensation, the selection of cells of interest via automated gating, and the correction for batch effects. The workflow is exemplified on data obtained from three successive CyTOF acquisitions of 15 barcoded samples mixed with calibration beads.\n\nWe use CATALYST9 to perform key preprocessing steps, including: concatenation, normalization, debarcoding and compensation; openCyto20 and flowWorkspace21 for gating; ggplot222 and ggcyto23 for visualization; flowCore24 and dplyr25 for data accession and manipulation; and mvtnorm to compute polygonal live gates. Thus, our workflow is limited to the following dependencies:\n\n\n\nBesides standard preprocessing steps, we include quality control (QC) steps to assess CyTOF sensitivity, staining efficacy, and cell yield; these rely on results from previous runs (n > 7) as a reference. For consistent visualization, we define a common plotting theme for boxplots that are used to compare the current to previous acquisitions:\n\n\n\nBy default, flowCore’s read.FCS() function, which underlies read.flowSet() for reading in a set of FCS files, transforms channel intensities and removes events with extreme values. To omit this behavior, we recommend reading in files with arguments transformation = FALSE and truncate_max_range = FALSE; by default, files will be read in by CATALYST’s prepData() function with these settings.\n\nAs described above, the SCE class allows the keeping of multiple data transformations in a single object. Thus, when applying a transformation to arrive at expression-like data, we can store the transformed data in a separate assay without overwriting the raw ion count data. In this way, any data generated and used throughout preprocessing (e.g., normalized, compensated or batch-corrected counts and their arcsinh-transformed counterparts) can be in principal retained, and written to intermediate FCS files for backup or quality control outside of R. However, it is worth noting that this procedure could lead to a shortage of memory for large datasets, in which case overwriting the data at each step is advisable; if not specified otherwise, CATALYST overwrites by default.\n\nA SCE can be constructed using CATALYST’s prepData() function, which accepts a path to a directory with one or many FCS files, a character vector of FCS filenames, a single or list of flowFrame(s), or a https://bioconductor.org/packages/3.11/bioc/html/flowCore.html (flowCore package24). By default (transform = TRUE), an arcsinh-transformation with cofactor = 5 is applied to the input (count) data, and the resulting expression matrix is stored in the exprs assay slot of the output SCE:\n\n\n\n\n\nInitially, our SCE has two assays containing dual ion counts (assay counts) and cofactor-5 arcsinh-transformed counts (assay exprs). The cofactor used for transformation is stored inside the object’s internal metadata (int_metadata(sce)$cofactor), and the FCS file of origin for each cell under cell metadata column sample_id (accessible via colData(sce)$sample_id or, equivalently, sce$sample_id). In our dataset, FCS files correspond to acquisitions rather than biological samples. Thus, we rename the cell metadata variable sample_id to file_id to avoid ambiguity:\n\n\n\nThe total number of cells across all acquisitions corresponds to the number of columns in the SCE (ncol(sce)). We can summarize the number of cells in each file by tabulating the file_ids:\n\n\n\n\n\nIn both mass and flow cytometry, each feature has both a channel and target associated with it. As can be seen from printing the sce variable above, prepData() defaults to using targets as rownames (when available). We can retrieve each feature’s measurement channel using the channels() accessor, and use channel metals and masses to extract the indices of features that are relevant to different preprocessing steps. Namely, we assign channels measuring DNA to the variable dna, and channels for live gating (one DNA channel and cisplatin) to live:\n\n\n\nHigh quality data generation requires a stable signal throughout the acquisition. Various issues can lead to signal change over time, including unstable flow rate, introduction of air or introduction of metal contamination in the system. These changes in signal intensity can vary in terms of duration and intensity, and can affect all or only a subsets of channels simultaneously. In order to detect regions of the acquisition affected by signal instability, we display the signal for selected channels as a function of time in a scatter plot (Figure 1).\n\n\n\nBins are colored by cell density; y-axis corresponds to cofactor-5 arcsinh-transformed dual counts.\n\nIn this particular experiment, we do not observe time-related signal instability. In case part of the acquisition should be excluded, this could be done by manually gating on the region with stable signal, and subsequent subsetting to only retain cells that fall within the gate’s boundaries (argument pop = \"+\"). Vice versa, it is possible to select a region with unstable signal, and remove it from the SCE object (pop = \"-\"). For the sake of completeness, we include how a region of unstable signal could be excluded via manual gating:\n\n\n\nIn the case of mass cytometry, signal drift during acquisition due to a progressive loss of sensitivity must be accounted and normalized for. A widely established strategy is to mix samples with polystyrene beads embedded with metal lanthanides, allowing monitoring of instrument performance throughout data acquisition8. These beads are in turn used to estimate and correct for the signal’s time drift. When independent experiments have to be analyzed in the same context, variation due to changes in instrument performance over time combined with intervals between scheduled maintenance have to be taken into account as well. In this case, the bead signal should be normalized to a set of reference beads from an earlier acquisition. This ensures that different experiments are normalized to the same level, independent of the CyTOF’s sensitivity.\n\nA MATLAB tool to perform normalization outside of R was available until recently at nolanlab/beadnormalization; current R implementations are available through CATALYST and premessa. CATALYST provides an extension of bead-based normalization as described by Finck et al.8, with automated identification of bead singlets (used for normalization), as well as of bead-bead and cell-bead doublets (to be removed), thus eliminating the need for manual gating. This is implemented as follows:\n\n1. beads are initially identified as those events that have their highest signals in the bead channels\n\n2. cell-bead doublets are removed by applying a separation cutoff on the distance between the lowest bead and highest non-bead channel signal\n\n3. events passing all vertical gates defined by the lower bounds of bead signals are removed (these include bead-bead and bead-cell doublets)\n\n4. bead-bead doublets are removed by applying a default median ± 5 mad rule to events identified in step 2; the remaining bead events are used for normalization\n\nThe above procedure is carried out by a single function, normCytof(), which takes as input a SCE and a set of arguments that control the normalization parameters and output format. Here, we specify beads = \"dvs\", corresponding to DVS Science beads (lanthanides Ce140, Eu151, Eu153, Ho165, Lu175). Secondly, we provide the path to a set of reference beads that are used to compute baseline intensities for normalization (argument norm_to). Lastly, we set overwrite = FALSE to retain both raw and normalized data, and remove_beads = TRUE to exclude bead and doublet events:\n\n\n\n\n\nWhen remove_beads = TRUE (the default), normCytof() will return a list of three SCEs containing filtered, bead and remove events, respectively, as well as two ggplot objects:\n\n\n\n\n\nThe first SCE (res$data) contains the filtered data with additional assay slot \"normed\" housing normalized expressions. The remaining two SCEs are data subsets that contain any events identified as beads (slot beads) and all removed events (including beads, bead-bead and bead-cell doublets; slot removed), respectively; thus, the beads themselves are a subset of the removed events. Here, we compare the number and percentage of cells contained in each subset:\n\n\n\n\n\nAs a first quality control plot, res$scatter (Figure 2) renders scatter plots of bead channels (x-axis) versus DNA (y-axis), where events identified as beads as well as their expression range are highlighted in color; bead events should have low DNA intensity (since they are not cells) and high intensities across all bead channels.\n\nEvents identified as beads are colored in blue; for each bead channel, expression ranges across all bead events are indicated as rectangular gates. Events were downsampled to at most 10,000 for visualization.\n\nSecondly, res$lines (Figure 3) displays smoothed median bead intensities before and after normalization; these typically decrease with time prior to normalization, and should be approximately constant and centered around the baseline after normalization. In our dataset, normalization is performed based on previously acquired reference beads. Thus, baseline values correspond to the reference bead’s mean bead channel intensities. As shown in Figure 3, the bead channel levels are considerably lower after normalization, indicating higher sensitivity in the current run. Importantly, the slight decrease in signal over time is no longer present after normalization.\n\nIn order to assess the sensitivity of the CyTOF during acquisition and identify potential issues that would have remained undetected during the tuning of the instrument, we compute the mean bead channel counts across events identified as beads (res$beads subset). A logical vector of which channels correspond to beads is stored under rowData column bead_ch, which we can use to subset the counts assay to include bead channels only.\n\n\n\nTo assess the measurement sensitivity during the current run, we compare the mean bead channel counts computed above to those obtained from 12 previously acquired runs available in metadata table ref_bead_counts.csv. The resulting boxplot (Figure 4) shows that the current run’s sensitivity is relatively high, but well in the range of previous runs.\n\n\n\nBoxplot comparing the mean dual ion counts (y-axis) across bead channels (x-axis) obtained for the current run (red crosses) to those from 12 previsouly acquired reference runs (boxes).\n\nAfter normalization, we overwrite the input dataset with the filtered subset that no longer includes bead events, or bead-bead and bead-cell doublets:\n\n\n\nIn mass cytometry, samples are often labeled with unique sample-specific barcodes and pooled together for processing and measurement, an approach termed multiplexing26. The most widely used barcoding scheme is based on Zunder et al.10, and relies on binary palladium-based mass-tag cell barcoding. Here, each sample i = 1, ..., n is either positive or negative for each of m palladium isotopes, resulting in an m-choose-k barcoding scheme, where k is the number of positive barcodes. For example, labeling of three out of six palladium isotopes will result in n-choose-k = 6-choose-3 = 20 unique barcodes. In order to recover the individual samples for further analysis, the pooled dataset is debarcoded (or deconvoluted) computationally.\n\nThe single cell debarcoding (SCD) algorithm first sorts each cell’s barcode intensities to assign preliminary barcode IDs such that a cell is assigned to the barcode population for which its barcode intensities are highest. Next, intensities within each barcode population are scaled using the 95th expression quantiles, and thereby brought to a comparable scale. Finally, events whose separation between highest negative and lowest positive barcode intensity is below a threshold value (separation cutoff) are left unassigned.\n\nIn the initial SCD algorithm, sample yields are determined by a single global cutoff on the separation between positive and negative barcode populations. Naturally, this procedure is suboptimal when yields as a function of the applied cutoff do not decline simultaneously. To optimize cell yields in such cases, CATALYST provides an option to automatically estimate or specify sample-specific separation cutoffs.\n\nThe SCD algorithm is implemented in CATALYST as a three-step procedure: i) preliminary barcode assignment (assignPrelim()); ii) automated estimation of sample-specific separation cutoffs (estCutoffs()); and, iii) application of cutoffs to arrive at final barcode assignments (applyCutoffs()).\n\nFor our dataset, a 6-choose-3 = 20 barcoding scheme was used (Figure 5). Five barcodes were unused (empty_1-5), resulting in 15 samples (9 references, 6 samples of interest). We first read the corresponding debarcoding_scheme.csv into R:\n\nRows correspond to palladium isotopes (barcode channels), columns to barcode identifiers (samples). Each sample is negative (white) or positive (grey) for 3 out of 6 barcode channels, resulting in 20 unique barcode combinations.\n\n\n\nDuring this first debarcoding step, each event is preliminarily assigned to a barcode according to its top-k expressed barcode channels. Here, events whose expression is highest for a combination of barcode channels that does not appear in the debarcoding scheme (bc_key) will be given barcode ID 0 (for “unassigned”). Thus, we can remove empty barcodes from the bc_key variable such that events assigned to these barcodes are left unassigned from the start. Alternatively, one could perform debarcoding using the non-subsetted key, and filter out empty barcodes downstream.\n\n\n\nFor preliminary barcode assignment, we use CATLAYST’s assignPrelim() function, providing the input data (sce) and debarcoding scheme (bc_key). If not specified otherwise, assignPrelim() will default to using the exprs assay slot (argument assay). Because we ran normCytof() with overwrite = FALSE, this assay contains arcsinh-transformed raw counts; we set assay = \"normexprs\" in order to use the normalized values instead:\n\n\n\nIn the returned SCE, feature metadata (rowData) column is_bc indicates whether or not a channel corresponds to a barcode channel:\n\n\n\nFor each event, barcode identifiers are stored in colData column bc_id. After this preliminary round of assignment, 57980/337525 events (17.18%) have been left unassigned:\n\n\n\nFurthermore, for each cell, the barcode channel expressions are scaled relative to the 95th expression percentiles of its respective barcode population. The scaled data is stored in assay slot scaled. Based on these scaled barcode channel intensities, a separation value is computed as the distance between highest negative and lowest positive barcode channel; separations are stored in colData column delta.\n\nTo decide on separation cutoffs, we consider yields upon debarcoding as a function of the applied cutoff (Figure 6). Commonly, this function will be characterized by an initial weak decline, where doublets are excluded, and subsequent rapid decline in yields to zero. In-between, low numbers of counts with intermediate barcode separation give rise to a plateau. Ideally, the applied separation cutoffs should provide a balance between high cell yield and low assignment uncertainty, marking the approximate midpoint of the yield function’s plateau region.\n\n\n\nShown is the distribution of barcode population separations (histogram) and cell yields by sample (lines) as a function of the applied separation cutoff. Left axis corresponds to cell yield in percent; right axis to the total number of cells.\n\nInstead of a single global cutoff, we estimate a sample-specific cutoff to account for barcode population yields that decline in an asynchronous fashion. To this end, we fit both a linear and a three-parameter log-logistic model to each yield function. For the linear fit, we estimate the cutoff as the value for which yields have declined to 50%. For the log-logistic fit, we compute the cutoff as the value for which there is minimal yield decline by minimizing each yield function’s 1st derivative. For each barcode, the final cutoff estimate is computed as the mean of both estimates, weighted with the goodness (residual sum of squares) of each fit (see Methods for details). Thus, the choice of thresholds for the distance between negative and positive barcode populations is: i) automated and ii) independent for each barcode. Nevertheless, reviewing barcode-specific yield plots and, in rare cases, refining the estimated separation cutoffs is advisable (see Figure 7).\n\nCutoff estimation is performed by CATALYST’s estCutoffs() function, which takes as input a SCE as returned by assignPrelim(); that is, preliminary barcode assignments are required to estimate separation cutoffs. estCutoffs() will store sample-specific cutoff estimates under metadata slot sep_cutoffs, but will leave barcode assignments unchanged.\n\n\n\nWe can visually inspect the estimated cutoffs using plotYields() with argument which specifying the barcode ID of interest (Figure 7). In our example, the cutoff estimate nicely marks the midpoint of the yield function’s plateau or, equivalently, the valley between peaks of cell yields. To decrease the stringency of the applied cutoff, and thus increase the resulting cell yield, we could set the sample’s cutoff to e.g. 0.1. Vice versa, a more stringent cutoff of e.g. 0.2 would decrease the cell yield but yield a purer population.\n\nAs an alternative to inspecting the cutoff estimate for each sample in R, we could specify which = bc_ids to obtain a list of yield plots for all barcodes; the generated set of plots may be written to a single PDF file via providing plotYields() with an out_path to allow for easy reviewing of the separating cutoffs currently stored within the object.\n\n\n\nShown is the distribution of barcode population separations (histogram) and cell yields (line) for the sample as a function of the applied separation cutoff. Left axis corresponds to cell yield in percent; right axis to the total number of cells.\n\nBesides a cutoff on the separation between positive and negative barcode populations, to trim outliers, the SCD algorithms applies an additional cutoff on the Mahalanobis distance (argument mhl_cutoff), a metric that quantifies the distance of a given event to the expression distribution of the barcode population it has been assigned to.\n\nIn Figure 6, we can observe that population yields decline synchronously with increasing separation cutoffs, and that we might consider applying a global separation cutoff, e.g., at ∼ 0.15. For this data, yields are in fact similar, independent of whether we apply sample-specific cutoffs or a single global one. Nevertheless, applying sample-specific cutoffs is recommended in order to maximize cell yields while minimizing uncertainty in barcode assignments.\n\n\n\nAfter debarcoding, we compare the number of events assigned to each barcode population before and after applying separation cutoffs, and filter out events that have been left unassigned (barcode ID 0). As shown in Figure 8, after applying the separation cutoffs, the number of unassigned cells (0) increases, while the number of cells assigned to each barcoding well decreases. We also observe a higher decrease in assigned cells for tumor samples, which underwent a dissociation process and contain more debris. Conversely, highly viable cell lines and PBMCs have a higher recovery yield.\n\n\n\n\n\nMass cytometry utilizes heavy metals (usually from the lanthanide series) as reporters to label antibodies. As a result, channel crosstalk originating from spectral overlap and autofluorescence is significantly less pronounced in mass cytometry compared to flow cytometry. Yet, spillover due to abundance sensitivity, isotopic impurities, and oxide formation still exists, giving rise to artefactual signal that can impede data interpretability.\n\nA combined experimental-computational pipeline to correct for spillover in mass cytometry data has been proposed by Chevrier et al.9 and is implemented in the CATALYST package. In brief, compensation is achieved via the following three-step approach outlined here (see for details).\n\n1. Identification of single positive populations via deconvolution of single-stained beads (assignPrelim(), estCutoffs(), applyCutoffs()).\n\n2. Estimation of a spillover matrix (SM) from the populations identified (computeSpillmat()).\n\n3. Compensation via multiplication of measurement intensities by the SM’s inverse, the compensation matrix (compCytof()).\n\nWe will apply a pre-acquired spillover matrix (metadata file spillover_matrix.csv). Thus, we enter at step 3, which involves only compensating the input dataset using CATALYST’s compCytof() function. By default, compCytof() will reuse the cofactor stored in int_metadata(sce)$cofactor for computing arcsinh-transformed data from the compensated counts, thus applying the same transformation as during data preparation and normalization:\n\n\n\nTo visually inspect how compensation affects signal intensities, we can generate scatter plots pre- and post-compensation; an exemplary pair of channels is shown in Figure 9. In such a plot, we can observe a slight positive association between the signals of spill-affected channels, which should be removed upon compensation.\n\n\n\nMany events acquired in mass cytometry may in fact be debris, doublets or dead cells, and should be filtered out through a gating step. Here, we suggest a strategy that first applies an elliptical gate on cell events, defined as double positive for the DNA channels Ir191/Ir193. This allows the exclusion of debris and doublets. As a second step, we discard cells that are positive for the dead cell marker Pt194.\n\nThese two steps are performed using the openCyto R package20, and the resulting gates are visualized on scatter plots of the channels subjected to gating using ggcyto23. For consistent visualization, we again define a common plotting theme for scatter plots of channels chs that include the gating boundaries for the specified gate_id:\n\n\n\nIn order to apply sample-specific gates, we first convert the SCE into a flowSet with a separate frame for each sample (argument split_by = \"bc_id\"). As gating should be performed on expression-like data (not ion counts), we further specify assay = \"exprs\" to retain the arcsinh-transformed assay slot. Thirdly, since conversion from SCE to flowCore data structures requires matrix transposition (rows correspond to targets in the SCE, but to events in flowFrame/Sets), we retain only those channels that are relevant when gating of (live) cells: DNA and dead channels, whose indices are stored in variables dna and live.\n\n\n\nWe apply an elliptical gate (gating_method = \"flowClust.2d\") to exclude the two lowest density percentiles (quantile = 0.98). Because the input gating set contains a separate frame for each barcode, the gate will be computed separately for each sample.\n\n\n\nWe use ggcyto to produce scatter plots of the DNA channels, with geom_gate(\"cells\") to visualize the gates computed above (Figure 10):\n\n\n\nThe wrapper function .live_gate() defines a polygonal gate comprised of a line and a bivariate standard normal density Z, such that cells pass gating when i) their expression is within the qth quantile of Z; and, ii) their expression falls below a line parameterized by intercept i and slope s. In this way, the gate is centered around the expression peak, while excluding cells whose dead channel intensities increases with DNA content.\n\n\n\nIn contrast to the cell gates above, we apply live gates with sample-specific gating parameters. To this end, we specify a list l containing quantiles q, intercepts i and slopes s for each sample. These parameters are updated iteratively to remove dead cells while retaining cell yields as high as possible. After manual adjustments, we arrive at the following sample-specific gating parameters (Figure 11).\n\n\n\nWe display the yield of \"cell\" and \"live\" gates on each samples to quickly assess the cell losses occurring at the two gating steps (Figure 12). As expected the \"cell\" gate leads to a systematic loss of around 1% of cells across all the samples. The \"live\" gate leads to a stronger reduction of cell yield in the tumor samples, consistent with the fact that those samples, which underwent enzymatic dissociation, contain more dead cells.\n\n\n\nFor each barcode ID (x-axis), frequencies are relative to the total number of cells in the population before gating; bars are colored by gate ID.\n\nWe extract a logical vector indicating whether a given event is included in or excluded by the \"live\" gate applied above by applying gh_pop_get_indices to each sample in gs. Secondly, we extract the cell indices from gs and subset the SCE to keep only cells that passed the \"live\" gate.\n\n\n\nFinally, we can again visualize scatter plots of dead channels against DNA as a quality control for the retained subset of cells (Figure 13).\n\nHaving completed the standard preprocessing steps, we proceed to investigate how the current run compares to prior acquisitions in terms of the number of cells in each reference and sample, and the expression levels of each target. Large parts of the metadata generated by now may no longer be needed, and unnecessarily increases output file sizes for large-scale datasets. Therefore, we will retain only two key cell metadata variables: file_ids containing the FCS filename each cell originates from, and bc_ids containing the barcode population assignments. We secondly rename these variable to make the following quality control steps more intuitive.\n\n\n\nIn the debarcoding scheme used for deconvolution of the multiplexed samples (Section Debarcoding), barcode identifiers were chosen to contain all information relevant for each sample. This setup allows us to extract sample metadata directly from the bc_ids. Alternatively, and especially for more complex experimental designs, this information could be stored in a separate metadata table. Such a table could then be used to match the bc_ids with the listed samples, and add arbitrary metadata information (e.g., batch, patient ID, treatment).\n\nIn our example, barcode identifiers include each sample’s type (CellLine, PBMC or Tumor), group (R for reference or S for sample of interest), and replicate number; and follow a consistent naming scheme: . We can easily extract these components and store them in the SCE’s cell metadata (colData):\n\n\n\n\n\nAs a first quality control, we compare the cell counts of each reference sample (R) to those obtained from 7 previous runs (Figure 14). Since the references are obtained from pre-barcoded aliquots of cells, the number of reference cells acquired gives direct information regarding the cell yield throughout the whole experiment: From cell barcoding to acquisition on the CyTOF. As shown in Figure 10, the current run has a lower yield compared to average run. This observation is consistent across all references measured.\n\n\n\nBoxplot comparing the reference cell counts obtained for the current run (red crosses) to those from 7 previsouly acquired runs.\n\nSecondly, we compare the cell counts for the 4 samples of interest (2 PBMC, 2 tumor samples) to the number of cells recorded for 14 tumor and PBMC samples each (28 reference samples in total) acquired in previous runs (Figure 15). This step provides a first quality assessment of the samples of interest. Here, samples with too few cells will be less reliable, and potentially less representative of the original tissue, making conclusions from downstream analyses more difficult to draw.\n\n\n\nBoxplot comparing the sample cell counts obtained for the current run (red crosses) to those from 7 previsouly acquired runs.\n\nAs the third and final quality control, we compare the 98th expression quantiles across all targets of interest over the pooled references to those obtained from 8 previously acquired runs available in metadata table ref_marker_levels.csv (Figure 15). We chose the 98th percentile to account for the fact that some populations are rare, and we are particularly interested in assessing signal stability for positive cells rather than the median of the population. Since the pooled references are identical from one run to another, this gives a direct indication of the current run’s staining efficacy and enables early identification of antibody degradation over time.\n\n\n\nBoxplot comparing the mean marker expression obtained for the current run (shown in red) to those from 8 previsouly acquired runs.\n\nEach CyTOF run contains the same set of references. Similar to the approach used by Schuyler et al.11, we use these references as anchors to calculate a channel-specific correction factor by dividing the 98th percentile measured in the current run by the average 98th percentile obtained across the first seven runs of the project. The signal observed in each channel for the samples of interest is then divided by these correction factors derived from the reference samples (Figure 16).\n\n\n\n\nDiscussion\n\nIn this workflow, we have presented a pipeline for reproducible and highly-automated preprocessing of CyTOF data, based on an updated version of CATALYST. Our pipeline covers four standard steps: Normalization for signal time-drift using bead standards (Section Normalization), single-cell deconvolution of multiplexed samples (Section Debarcoding), correction for spillover via compensation (Section Compensation), and gating for live cells (Section Gating). Moreover, we have included various quality control steps that compare the current acquisition to a set of reference data (Section Quality control). These steps ensure that measurement sensitivity, gating cell yields, sample cell counts, and expression levels lie within the expected range.\n\nA key advantage of both using and developing Bioconductor packages is that they utilize common data structures, thereby greatly facilitating interaction between them. For example, many of the data structures used in scRNA-seq data analysis have only become established relatively recently. Meanwhile, the cytometry community has been relying on the FCS file format for data storage, and flowCore’s flowFrame/flowSet as well as flowWorkspace’s GatingSet classes for computational analyses. While there exists a lot of infrastructure around these data structures, they impede method development for newly emerging standards, and act as a barrier for interpolation of analyses across currently developed packages. This is particularly visible in the context of other fast growing single-cell data types such as scRNA-seq data analysis, where most current methods are being developed around Bioconductor’s SingleCellExperiment class. To name just two examples, an extensive collective of visualization tools for SCEs is available through scater27, including a variety of dimensionality reduction methods; and methods for differential abundance (DA) analysis (to detect subpopulations that are differently abundant between conditions) and differential state (DS) analysis (to test for subpopulation-specific expression changes across conditions) are implemented in diffcyt28.\n\nThe SCE class allows storing multiple assays that can, for example, contain raw counts, expression-like data obtain upon arcsinh-transformation, as well as any intermediate data matrices obtained after normalization, compensation and batch correction. Moreover, any event (cell) and feature (marker) metadata generated in the process can be added to the object’s colData/rowData, alongside an arbitrary number of dimensionality reductions. Thus, SCEs present an overall more compact and less error-prone data structure for both preprocessing and downstream analysis when compared to storing the various data matrices or metadata in separate variables, which would have to be combined for certain computations, separately subsetted and saved to independent outputs.\n\nThere is an obvious benefit for the mass cytometry community to take advantage of these new infrastructure developments. However, it is equally important to maintain backward compatibility with well-established standards in the field. For example, it can be desirable to write out intermediate outputs (FCS files) after each proprocessing step, or make use of available tools that build around flowCore’s flowFrame and flowSet classes, or other classes derived thereof (e.g., flowWorkspace’s GatingSet). Thus, while CATALYST’s transition to a more recent and an arguably advantageous data structure is motivated by the ability to leverage many existing and newly-developed tools, a complete dismissal of the large infrastructure that is available in the realm of cytometry data analysis is impossible at this time. To facilitate conversion between SCEs and conventional cytometry data structures, CATALYST provides the sce2fcs() function, which allows the user to specify which assay data to retain, whether to drop or keep available cell metadata and dimensionality reductions, and (optionally) to split the input dataset by a non-numeric variable (to, e.g., export each sample to a separate FCS file).\n\nAlthough the current version of this pipeline constitutes a comprehensive approach to generate high-quality data for downstream analysis, further developments could be added in the future. In particular, it could be useful to implement an automated way of identifying and removing part of the data with unstable signal, similar to the approach proposed by flowClean29, an R package designed to exclude fluorescent anomalies in flow cytometry data. Given that selection of anomalies in the dataset by the user is subjective, or that they may be altogether undetectable by eye, the advantage of such an approach would be to further standardize the process while decreasing manual work.\n\nRecently, batch normalization has become of increased importance in order to enable integration of datasets acquired at different times, by different users and on different instruments. Here, we use scaling normalization where references are used as anchors to correct all samples included in the analysis in a channel specific way, similar to the strategy proposed by Schuyler et al.11. While this approach requires a well-defined experimental procedure where references with positive and negative subsets for each marker have to be included in each acquisition, it does not make any assumptions on sample compositions. Thus, since the dataset used in this pipeline was acquired on the same instrument and stained with the same frozen antibody panel as previous acquisitions, scaling by expression quantiles provides an efficient way to correct for batch effects. To increase the flexibility of batch correction in cases where the experimental variation is higher, CATALYST could integrate different methods that have the potential to increase batch correction efficiency. For example, CytoNorm12 computes quantiles for every metacluster and for every marker after aggregation of control samples from each batch. Such an approach could be more appropriate in cases where the references’ expression distributions are less aligned. An alternative method, CytofRUV30, exploits the concept of pseudo-replicates to remove unwanted variation (RUV) between proteins and cells. Here, cells are grouped into subpopulations using FlowSOM31 clustering. Groups of cells present across all batches are considered to be pseudo-replicates, and their deviation (residuals) from the average signal across batches is used to estimate and correct for the batch effects.\n\nAlthough various methods to correct for batch effects in both the presence and absence of references have been proposed, a systematic comparison of batch correction tools for mass cytometry data is missing. Thus, whether the approach used in this study to align batches on the basis of shared references is the most accurate remains unresolved.\n\nOur pipeline is entirely R-based and does not rely on switching between platforms. Thus, it omits the need for heavy data transfers between online cloud services, graphical user interfaces (GUI), and programming environments for different parts of preprocessing and downstream analysis. As a result, each step in the analysis is fully reproducible and any parameters used throughout can be easily modified and documented. This transition from manual, GUI-based to largely automated, programmatic data processing is indispensable for clinical and other large-scale studies, where sample throughput is high and reproducibility ever so important.\n\nSince its first submission to Bioconductor in 2017, CATALYST has undergone continuous maintenance and development. The most noteworthy changes include implementation of a comprehensive visualization suite based on Nowicka et al.14’s workflow for differential discovery; and, the transition from custom data structures to using Bioconductor’s SingleCellExperiment class for differential analysis with Bioconductor v3.11, and for preprocessing with v3.12. Taken together, these developments have transformed CATALYST into a one-stop tool for cytometry data analysis, enabling both data preprocessing and in-depth downstream analysis.\n\n\nMethods\n\nIdentification of bead events. Commonly, bead events are identified by manual gating on scatter plots of DNA vs. bead channels where DNA show be low, and expression should be high across all bead channels. Instead, we propose a programmatic way to identify beads that includes detection of bead-bead and cell-bead doublets.\n\nOur normalization strategy leverages the already established SCD algorithm for preliminary tagging of events as beads. In this context, the debarcoding scheme is a 2×(2+m) matrix (Figure 17). Here, columns correspond to the two DNA channels and m barcode channels; rows correspond to barcodes 0 (no bead) and 1 (is bead), where non-bead events are positive for DNA channels only (barcode 11000. . . ), while bead events are negative for DNA and positive for all bead channels (barcode 00111. . . ):\n\nRows correspond to barcodes, columns to DNA and bead channels. Each barcode is either positive (grey) or negative (blank) for a given channel; cells (barcode 11000...) are positive for DNA and negative for bead channels, bead events (barcode 00111...) are negative for DNA and positive for bead channels.\n\nUpon initially assignment of bead events, we apply a median ± n median absolute deviation (MAD) rule to remove low- and high-signal events from the bead population used for estimating normalization factors. As n decreases, bead populations become more narrow and bead-bead doublets are excluded. The extent to which bead populations are trimmed can be adjusted via argument trim (default 5).\n\nNotably, slight over-trimming does not affect normalization. It is therefore recommended to choose a trim value that is small enough to assure removal of doublets at the cost of reduced bead population sizes.\n\nCorrecting for signal-decrease over time. To correct for the effect of event acquisition time on signal intensity, we follow the method proposed by Finck et al.8. In essence, bead intensities are smoothed using a median sliding-window with width k (default 500 bead events). At each timepoint, the slope of a line with intercept zero is computed my minimizing the squared error between smoothed bead and mean bead intensities (= baseline). Alternatively, a reference set of beads from which to compute the baseline can be provided. Slopes for non-bead timepoints are obtained via constant interpolation of these slopes. Here, large slopes correspond to significant deviation from the baseline, and small slopes indicate that the signal is already similar to the baseline. Thus, raw bead counts are normalized by multiplication with the fitted slopes at each timepoint.\n\nPreliminary barcode assignment. The debarcoding process commences by assigning each event a preliminary barcode ID. This requires specification of a binary barcoding scheme (or debarcoding key)\n\n\n\nwhere i = 1, ..., n is the barcode index, j = 1, ..., m a barcode channel, and n, m denote the number of unique barcodes and barcoding channels, respectively. Further, let ki denote the number of positive barcoding channels for barcode i: ki=∑j=1mbij.\n\nIf ki = k ∀ i = 1, ..., n (i.e., every barcode has the same number of positive barcoding channels), the k channels with the highest signal in a given event are considered to be positive, the remaining m − k to be negative. The separation δ of positive and negative events is then defined as the difference between the kth highest and (m − k)th lowest scaled intensity for that event.\n\nSeperation cutoff estimation. When the separation between positive and negative barcoding channels is low, we cannot be confident in the barcode assignment.\n\nFor the estimation of cutoff parameters, we consider yields upon debarcoding as a function of the applied cutoffs. Commonly, this function will be characterized by an initial weak decline, where doublets are excluded, and subsequent rapid decline in yields to zero. In between, low numbers of counts with intermediate barcode separation give rise to a plateau. To facilitate robust estimation, we fit a linear and a three-parameter log-logistic function32 to the yields function with drc’s LL.R function33 (Figure 18). As an adequate cutoff estimate, we target a point that marks the end of the plateau regime and on-set of yield decline to appropriately balance confidence in barcode assignment and cell yield.\n\nWe define the linear model cutoff estimate cLM as the value for which the cell yield Y has declined to half of the initial Yield β0:\n\n\n\nwhere β0, β1 are the intercept and slope of the linear model fit, respectively.\n\nWe define the log-logistic model cutoff estimate cLLM as the value for which the log-logistic function’s decline is minimized relative to its value:\n\n\n\nThe final cutoff estimate c is defined as the weighted mean between these estimates:\n\n\n\nwhere w is the goodness of the linear fit relative to the log-logistic fit:\n\n\n\nBar graphs represent the distribution of cells relative to the barcode distance, dotted line scorresponds to yield upon debarcoding as a function of the applied separation cutoff. The yield curve is fitted with a linear regression (blue) and a three parameter log-logistic function (red). The final cutoff estimate (black dashed line) is defined as the mean of estimates derived from both fits, weighted with the goodness of the respective fit.\n\nRetrieval of real signal. As in conventional flow cytometry, we model spillover linearly, with the channel stained for as predictor, and spill-effected channels as response. Thus, the intensity observed in a given channel j are a linear combination of its real signal and contributions of other channels that spill into it. Let I denote the (unknown) real and J the observed signal. Further, let sij be the proportion of channel j signal that is due to channel i, and wj the set of channels that spill into channel j. Then\n\n\n\nIn matrix notation, measurement intensities may be viewed as the convolution of real intensities and a spillover matrix SM=(sij)∈ℝ+n×p, where n denotes the number of samples (cells) and p the number of features (channels): J = I · SM. The real signal I can then be retrieved via:\n\n\n\nwhere SM−1 is termed compensation matrix (CM).\n\nWhile mathematically exact, the solution to this equation will yield negative values, and does not account for the fact that ion counts are strictly non-negative. A computationally efficient way to adress this is to instead use non-negative linear least squares (NNLS), which optimizes the least squares criterion under the constraint of non-negativity:\n\n\n\nTo solve for I, we apply the Lawson-Hanson algorithm34,35 for NNLS implemented in the nnls package.\n\nSpillover estimation. Because any signal not in a single stain experiment’s primary channel j results from channel crosstalk, each spill entry sij can be approximated by the slope of a linear regression with channel j signal as the response, and channel i signals as the predictors, where i ∈ wj. computeSpillmat() offers two alternative ways for spillover estimation (Figure 19).\n\nThe default method approximates this slope with the following single-cell derived estimate: Let i+ denote the set of cells that are possitive in channel i, and sijc be the channel i to j spill computed for a cell c that has been assigned to this population. We approximate sijc as the ratio between the signal in unstained spillover receiving and stained spillover emitting channel, Ij and Ii, respectively. The expected background in these channels, mj− and mi−, is computed as the median signal of events that are i) negative in the channels for which spill is estimated (i and j); ii) not assigned to potentionally interacting channels; and, iii) not unassigned, and subtracted from all measurements:\n\n\n\nEach entry sij in SM is then computed as the median spillover across all cells c ∈ i+:\n\n\n\nIn a population-based fashion, as done in conventional flow cytometry, sij is computed as the slope of a line through the medians (or trimmed means) of stained and unstained populations, mj+ and mi+, respectively. Background signal is computed as above and subtracted, according to:\n\n\n\nIn a population-based setting (left), spillover is estimated as the slope of a line through the centers of positive (red) and negative (blue) populations. In a single-cell based setting (right), slopes are computed independently for each cell in the positive population, and spillover is estimated as their median.\n\nOn the basis of their additive nature, spill values are estimated independently for every pair of interacting channels. Hereby, we take into account only interactions that are sensible from a chemical and physical point of view: M ± 1 channels (abundance sensitivity), M + 16 channels (oxide formation), and channels measuring isotopes (impurities; Figure 20).\n\nIncluded are only interactions that are sensible from a chemical and physical point of view: adjacent mass channels (abundance sensitivity), +16 mass channels (oxidation), and channels measuring isotopes (impurities).\n\nAlternatively, interactions = \"all\" will compute a spill estimate for all n · (n − 1) possible interactions, where n denotes the number of measurement parameters. Estimates falling below the threshold specified by th will be set to zero. Lastly, note that diagonal entries sii = 1 for all i ∈ 1, ..., n, so that spill is relative to the total signal measured in a given channel.\n\n\nData availability\n\nThe CyTOF data as well as all metadata required to run the full pipeline presented herein are available from Figshare as well as the Tumor Profiler website at https://tu-pro.ch/download/catalyst.\n\nFigshare: An R-based reproducible and user-friendly preprocessing pipeline for CyTOF data. https://doi.org/10.6084/m9.figshare.c.5063984.v118\n\nThis project contains the following underlying data:\n\nCyTOF_acquisition_1-3.fcs (40-Ab panel CyTOF data of 2 blood and 2 tumor samples, and 9 reference samples selected to contain positive and negative populations for each marker included in the study’s Ab-panel. Samples were multiplexed with a 20-well barcoding plate, and obtained from a single run provided as 3 FCS files.)\n\nnormalization_beads.fsc (Beads identified using CATALYST during the normalization step of a previous CyTOF run. – Used as reference beads to correct for changes in signal sensitivity over time across multiple CyTOF runs.)\n\nref_bead_counts.csv (A table of mean dual counts for the six different bead channels (columns) obtained from 12 previous acquisitions (rows). – Used as a reference to assess the measurement sensitivity for the current run.)\n\ndebarcoding_scheme.csv (A binary barcoding scheme of 6-choose-3 = 20 barcodes with columns corresponding to barcode channel masses (101, 104, 105, 106, 108, 110) and rows corresponding to barcodes (7 empty, 9 references, 2 PBMC and 2 tumor samples) – Used for single-cell deconvolution of multiplexed of samples.)\n\nspillover_matrix.csv (A spillover matrix calculated with CATALYST from beads single-stained with each of the 40 antibodies included in the panel used in this study. The matrix contains, for each measurement channel (rows), the percentage of signal received by all other channels (columns). – Used for correction of spillover.)\n\nref_cell_counts.csv (A table of the number of cells measured in 7 previous acquisitions, each including 4 cell line, 3 PBMC and 2 tumor references samples (63 samples in total). – Used to asses reference sample cell yields in the current in comparison to previous runs.)\n\nsample_cell_counts.csv (A table of the number of cells measured in 7 previous acquisitions, each including 2 PBMC and 2 tumor samples each (28 samples in total). – Used to asses sample cell yields in the current in comparison to previous runs.)\n\nref_marker_levels.csv (A table of the 98th expression percentiles for each target (columns) across 7 previous acquisitions (rows). – Used to assess the staining efficiency of the current run.)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nSoftware availability\n\nAnalyses were run in R v4.0.036, with Bioconductor v3.1137, and all software packages used throughout this workflow are publicly available through the Comprehensive R Archive Network (https://cran.r-project.org) or the Bioconductor project (http://bioconductor.org). Specific package versions are captured in the following session information:\n\n\n\n\n\n\nConsent\n\nWritten informed consent for publication of the tumor and blood samples was obtained from the patients (BASEC-Nr.2018-02050, approved by the Kantonal Ethics Commisions of Zurich and Basel).", "appendix": "Acknowledgments\n\nThe authors would like to acknowledge support from the Biobank team of the Department of Dermatology at University Hospital Zurich, who provided us with the samples used in this study.\n\n\nAuthor Information\n\nHCL and SC contributed equally to the scientific content of this article and share first authorship. MDR and BB act as co-senior authors.\n\n\nFootnotes\n\n1Cantonal Hospital Baselland, Medical University Clinic, Rheinstrasse 26, 4410 Liestal, Switzerland\n\n2ETH Zurich, Department of Biology, Wolfgang-Pauli-Strasse 27, 8093 Zurich, Switzerland\n\n3ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058 Basel, Switzerland\n\n4ETH Zurich, Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 1-5/10, 8093 Zurich, Switzerland\n\n5ETH Zurich, Department of Computer Science, Institute of Machine Learning, Universitätstrasse 6, 8092 Zurich, Switzerland\n\n6ETH Zurich, Department of Health Sciences and Technology, Otto-Stern-Weg 3, 8093 Zurich, Switzerland\n\n7ETH Zurich, NEXUS Personalized Health Technologies, John-von-Neumann-Weg 9, 8093 Zurich, Switzerland\n\n8F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070 Basel, Switzerland\n\n9F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070 Basel, Switzerland\n\n10Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany\n\n11Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Grenzacherstrasse 124, 4070 Basel, Switzerland\n\n12Roche Pharmaceutical Research and Early Development, Roche Innovation Center Munich, Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany\n\n13Roche Pharmaceutical Research and Early Development, Roche Innovation Center Zurich, Wagistrasse 10, 8952 Schlieren, Switzerland\n\n14Swiss Institute of Bioinformatics, Zurich, Switzerland\n\n15University Hospital Basel and University of Basel, Department of Biomedicine, Hebelstrasse 20, 4031 Basel, Switzerland\n\n16University Hospital Basel and University of Basel, Department of Surgery, Brustzentrum, Spitalstrasse 21, 4031 Basel, Switzerland\n\n17University Hospital Basel, Brustzentrum & Tumorzentrum, Petersgraben 4, 4031 Basel, Switzerland\n\n18University Hospital Basel, Brustzentrum, Spitalstrasse 21, 4031 Basel, Switzerland\n\n19University Hospital Basel, Centre for Neuroendocrine & Endocrine Tumours, Spitalstrasse 21/Petersgraben 4, 4031 Basel, Switzerland\n\n20University Hospital Basel, Department of Information- and Communication Technology, Spitalstrasse 26, 4031 Basel, Switzerland\n\n21University Hospital Basel, Gynecological Cancer Center, Spitalstrasse 21, 4031 Basel, Switzerland\n\n22University Hospital Basel, Institute of Medical Genetics and Pathology, Schönbeinstrasse 40, 4031 Basel, Switzerland\n\n23University Hospital Basel, Spitalstrasse 21/Petersgraben 4, 4031 Basel, Switzerland\n\n24University Hospital Zurich, Biomedical Informatics, Schmelzbergstrasse 26, 8006 Zurich, Switzerland\n\n25University Hospital Zurich, Clinical Trials Center, Rämistrasse 100, 8091 Zurich, Switzerland\n\n26University Hospital Zurich, Department of Dermatology, Gloriastrasse 31, 8091 Zurich, Switzerland\n\n27University Hospital Zurich, Department of Pathology and Molecular Pathology, Schmelzbergstrasse 12, 8091 Zurich, Switzerland\n\n28University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland\n\n29University Hospital and University of Zurich, Department of Neurology, Frauenklinikstrasse 26, 8091 Zurich, Switzerland\n\n30University of Bern, Department of BioMedical Research, Murtenstrasse 35, 3008 Bern, Switzerland\n\n31University of Zurich, Department of Quantitative Biomedicine, Winterthurerstrasse 190, 8057 Zurich, Switzerland\n\n32University of Zurich, Institute of Molecular Life Sciences, Winterthurerstrasse 190, 8057 Zurich, Switzerland\n\n33University of Zurich, Services and Support for Science IT, Winterthurerstrasse 190, 8057 Zurich, Switzerland\n\n34University of Zurich, VP Medicine, Künstlergasse 15, 8001 Zurich, Switzerland\n\n\nReferences\n\nSimoni Y, Chng MHY, Li S, et al.: Mass cytometry: a powerful tool for dissecting the immune landscape. Curr Opin Immunol. 2018; 51: 187–196. PubMed Abstract \| Publisher Full Text\n\nSpitzer MH, Nolan GP: Mass Cytometry: Single Cells, Many Features. Cell. 2016; 165(4): 780–791. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBehbehani GK: Applications of Mass Cytometry in Clinical Medicine: The Promise and Perils of Clinical CyTOF. Clin Lab Med. 2017; 37(4): 945–964. PubMed Abstract \| Publisher Full Text\n\nSchulz AR, Baumgart S, Schulze J, et al.: Stabilizing Antibody Cocktails for Mass Cytometry. Cytometry A. 2019; 95(8): 910–916. PubMed Abstract \| Publisher Full Text\n\nHartmann FJ, Babdor J, Gherardini PF, et al.: Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy. Cell Rep. 2019; 28(3): 819–831.e4. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPalit S, Heuser C, de Almeida GP, et a: Meeting the Challenges of High-Dimensional Single-Cell Data Analysis in Immunology. Front Immunol. 2019; 10: 1515. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nOlsen LR, Leipold MD, Pedersen CB, et al.: The anatomy of single cell mass cytometry data. Cytometry A. 2019; 95(2): 156–172. PubMed Abstract \| Publisher Full Text\n\nFinck R, Simonds EF, Jager A, et al.: Normalization of mass cytometry data with bead standards. Cytometry A. 2013; 83(5): 483–494. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nChevrier S, Crowell HL, Zanotelli VRT, et al.: Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry. Cell Syst. 2018; 6(5): 612–620.e5. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nZunder ER, Finck R, Behbehani GK, et al.: Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm . Nat Protoc. 2015; 10(2): 316–333. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSchuyler RP, Jackson C, Garcia-Perez JE, et al.: Minimizing Batch Effects in Mass Cytometry Data. Front Immunol. 2019; 10: 2367. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVan Gassen S, Gaudilliere B, Angst MS, et al.: CytoNorm: A Normalization Algorithm for Cytometry Data. Cytometry A. 2020; 97(3): 268–278. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKotecha N, Krutzik PO, Irish JM: Web-based analysis and publication of flow cytometry experiments. Curr Protoc Cytom. 2010; Chapter 10: Unit10.17. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNowicka M, Krieg C, Crowell HL, et al.: CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets [version 3; peer review: 2 approved]. F1000Res. 2019; 6: 748. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nIrmisch A, Bonilla X, Chevrier S, et al.: The Tumor Profiler Study: Integrated, multi-omic, functional tumor profiling for clinical decision support. medRxiv. 2020. Publisher Full Text\n\nChevrier S, Zurbuchen Y, Cervia C, et al.: A distinct innate immune signature marks progression from mild to severe COVID-19. bioRxiv. 2020. Publisher Full Text\n\nChevrier S, Levine JH, Zanotelli VRT, et al.: An Immune Atlas of Clear Cell Renal Cell Carcinoma. Cell. 2017; 169(4): 736–749.e18. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCrowell H, Chevrier S, Jacobs A, et al.: An r-based reproducible and user-friendly preprocessing pipeline for cytof data. 2020. Reference Source\n\nLun A, Risso D, Korthauer K: SingleCellExperiment: S4 classes for single cell data. R package version. 2018; 1. Publisher Full Text\n\nFinak G, Frelinger J, Jiang W, et al.: OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis. PLoS Comput Biol. 2014; 10(8): e1003806. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFinak G, Jiang M: FlowWorkspace: Infrastructure for representing and interacting with gated and ungated cytometry data sets. R package version. 2018; 3. Publisher Full Text\n\nWickham H: ggplot2: Elegant Graphics for Data Analysis. Springer, 2016. Reference Source\n\nVan P, Jiang W, Gottardo R, et al.: ggCyto: next generation open-source visualization software for cytometry. Bioinformatics. 2018; 34(22): 3951–3953. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHahne F, LeMeur N, Brinkman RR, et al.: flowCore: a Bioconductor package for high throughput flow cytometry. BMC Bioinformatics. 2009; 10(1): 106. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWickham H, Francois R, Henry L, et al.: dplyr: A grammar of data manipulation. R package. 2015.\n\nBodenmiller B, Zunder ER, Finck R, et al.: Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nat Biotechnol. 2012; 30(9): 858–867. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMcCarthy DJ, Campbell KR, Lun ATL, et al.: Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R. Bioinformatics. 2017; 33(8): 1179–1186. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWeber LM, Nowicka M, Soneson C, et al.: diffcyt: Differential discovery in high-dimensional cytometry via high-resolution clustering. Commun Biol. 2019; 2: 183. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFletez-Brant K, Špidlen J, Brinkman RR, et al.: flowClean: Automated identification and removal of fluorescence anomalies in flow cytometry data. Cytometry. 2016; 89(5): 461–471. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTrussart M, Teh CE, Tan T, et al.: CytofRUV: Removing unwanted variation to integrate multiple CyTOF datasets. bioRxiv. 2020. Publisher Full Text\n\nVan Gassen S, Callebaut B, Van Helden MJ, et al.: FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data. Cytometry A. 2015; 87(7): 636–645. PubMed Abstract \| Publisher Full Text\n\nFinney DJ: Probit analysis. J Pharm Sci. 1971; 60(9): 1432.\n\nRitz C, Baty F, Streibig JC, et al.: Dose-Response Analysis Using R. PLoS One. 2015; 10(12): e0146021. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLawson CL, Hanson RJ: Solving least squares problems prentice-hall. Prentice Hall, Englewood Cliffs, NJ. 1974. Reference Source\n\nLawson CL, Hanson RJ: Solving Least Squares Problems. SIAM, Philadelphia, PA. 1995. Reference Source\n\nR Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2019. Reference Source\n\nHuber W, Carey VJ, Gentleman R, et al.: Orchestrating high-throughput genomic analysis with Bioconductor. Nat Methods. 2015; 12(2): 115–121. PubMed Abstract \| Publisher Full Text \| Free Full Text" }	[ { "id": "73591", "date": "05 Nov 2020", "name": "Marie Trussart", "expertise": [ "Reviewer Expertise I work in Bioinformatics and especially in the normalization and batch correction of CyTOF datasets." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript is presenting an updated version of the CATALYST package for preprocessing Cytof data. It is well detailed with several examples and has been updated based on the Bioconductor SingleCellExperiment class. Every step of preprocessing is clearly stated and illustrated to guide the user on the different steps to process their data. Also, new quality checks are being reviewed to explore the quality of the data. I provided below some feedback to make the manuscript clearer and some suggestions to address some issues I encountered:\nIt will be useful to define clearly what are the differences between successive acquisitions, single CyTOF run and batch.\n\nThe different samples and runs listed through the different examples could be better presented with a table containing all runs and samples. In the data description, it explains that \"The dataset used in this study was obtained from a single CyTOF run containing nine references, three blood samples and three tumor samples barcoded with a 20-well barcoding plate\". However in the quality checks section; additional data is being analyzed which makes it confusing, coming from additional runs, sometimes from 7 runs or other times from 8 runs.\n\nBatch alignment: Could you provide an additional plot showing the effect of applying this correction factor? How are you assessing the performance of your batch alignment method?\n\nargument norm_to in the normCytof() function: give explanations on how it being computed when giving reference beads, especially how does it compute the new baseline, does it takes into account both the beads from the reference and current by averaging both? Can it be used to normalize data from different batches? If so how does it deal with distinguishing times and ordering the beads and time which would be similar in separated batches?\n\nFigure 4: Could you please give more explanations on how to assess run sensitivity and how does the user decide what is acceptable and what is not? Also, you need to load the library(reshape2) to run this part.\n\nThe wrap_plots function is missing here.\n\nI got an error when running the QC on reference cell counts. \"Error: Can't combine `1$CellLine_R1` and `2$CellLine_R1` .\"\n\nMinor comments:\nWhen running the code using the data provided, the directory name should be modified to \"CyTOF_acquisition_1-3.FCS/\" instead of data fcs <- list.files(\"CyTOF_acquisition_1-3.FCS/\", \"acquisition\", full.names = TRUE) Also, it should be specified that the directory name containing all the data should be called \"data\" and it refers to the directory name, or an alternative is to have the local directory \".\" instead of data like in here: # specify path to reference beads ref_beads <- file.path(\".\", \"normalization_beads.fcs\")\n\nIntroduction: \"an important step is to correct for batch effects, which can be achieved by including a shared control sample in each independent batch11,12 \" Add CytofRUV reference mentioned in the discussion.\n\n\"In our example, barcode identifiers include each sample’s type (CellLine, PBMC or Tumor), group (R for reference or S for sample of interest), and replicate number; and follow a consistent naming scheme: We can easily extract these components and store them in the SCE’s cell metadata (colData)\". The example selected is not the best one, as it not showing any differences between the 6 first row.\n\nThere is a typo in the legend of some figures like figure 17: \"previously\" acquired runs.\n\nIs the rationale for developing the new method (or application) clearly explained? Yes\n\nIs the description of the method technically sound? Yes\n\nAre sufficient details provided to allow replication of the method development and its use by others? Partly\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "8417", "date": "08 Aug 2022", "name": "Helena Crowell", "role": "Author Response", "response": "It will be useful to define clearly what are the differences between successive acquisitions, single CyTOF run and batch. Indeed, the meaning behind the concepts of successive acquisitions, single CyTOF run and batch was not fully clear and these terms were not used in a consistent way. A “CyTOF run” corresponds to an independent experiment where samples are stained and acquired simultaneously on the CyTOF. We replaced the term run with experiment to clarify the meaning. Each CyTOF experiment corresponds to one “batch” and this term is used to refer to the batch correction which is performed on the different CyTOF experiments. The data from a single CyTOF experiment are usually acquired over multiple “successive acquisitions”, each leading to the generation of a single FCS file. We also made the use of these terms consistent throughout the paper. The different samples and runs listed through the different examples could be better presented with a table containing all runs and samples. In the data description, it explains that \"The dataset used in this study was obtained from a single CyTOF run containing nine references, three blood samples and three tumor samples barcoded with a 20-well barcoding plate\". However in the quality checks section; additional data is being analyzed which makes it confusing, coming from additional runs, sometimes from 7 runs or other times from 8 runs. The pipeline described in this paper was designed to preprocess CyTOF data acquired over a long period of time with a focus on ensuring data consistency over time. The aim of the workflow is to guide the readers through the preprocessing steps required to convert FCS files obtained in a given CyTOF experiment to a format suitable for downstream analysis, while presenting key quality checks to ensure the reliability of the data generated in the experiment of interest. Therefore, the whole analysis is based on a dataset obtained from a single CyTOF experiment, which is benchmarked against data acquired during a preparatory phase. For consistency reasons, we included now systematically the data from seven previous CyTOF experiments to benchmark the data of the CyTOF experiment preprocessed in this paper. Batch alignment: Could you provide an additional plot showing the effect of applying this correction factor? How are you assessing the performance of your batch alignment method? The batch alignment presented in this paper is based on a linear scaling based on a percentile, using references as anchoring points, similar to a previously published method (Schuyler et al, 2019). To assess the performance of our batch alignment method, we have now included a figure to compare the expression distributions before and after batch correction (including their 98th percentiles and those of the references). As intended, 98th percentiles align with the references’ upon correction, while expression distributions remain virtually unchanged. argument norm_to in the normCytof() function: give explanations on how it being computed when giving reference beads, especially how does it compute the new baseline, does it take into account both the beads from the reference and current by averaging both? Normalization using reference beads follows the methodology originally introduced in Finck et al. (2013): The baseline is computed as the mean intensity of the reference beads only, not including the current experiment. Would the average be taken over both, intensities would not be aligned between current and reference experiment. While the statement “[...] We provide the path to a set of reference beads (argument `norm_to`) that are used to compute baseline intensities for normalization” explains this only briefly, we believe that the method is well established and readers should refer to the original publication for more detail. Can it be used to normalize data from different batches? If so how does it deal with distinguishing times and ordering the beads and time which would be similar in separate batches? Yes, certainly. The normalization aims at correcting the signal time-drift due to progressive loss of sensitivity during acquisition. This is a technical effect that is independent of batch effects, and should be accounted for regardless of whether or not batch effects are present: these should be corrected for downstream analysis. Events from different FCS files (independent of whether these are different acquisitions of the same experiment or batches) are concatenated. How event times are dealt with depends on prepData()’s input arguments. When by_time = TRUE, files are ordered according to their acquisition time (stored under each flowFrame’s $BTIM description field). Otherwise, they are kept in the order provided by the input metadata table (argument md). Figure 4: Could you please give more explanations on how to assess run sensitivity and how does the user decide what is acceptable and what is not? Instrument sensitivity is an important parameter that should be closely monitored. This parameter is assessed during the tuning but those data cannot be easily exported and compared between experiments. The aim was to take advantage of the beads, which are run together with the samples to report on instrument sensitivity. Figure 3 provides key information regarding how the sensitivity evolves during the run, while the point of Figure 4 is to show how the average sensitivity evolves from one experiment to another. Instrument sensitivity varies from machine to machine and deciding what is acceptable will depend on the requirements of the users. The point of this plot was to offer an option for the user to easily identify in case the sensitivity is getting low compared to previous experiments, and to make a link between the quality of the data generated in a specific experiment with the sensitivity of the instrument. Also, you need to load the library(reshape2) to run this part. Yes, thank you for catching this; we’ve added reshape2 to the list of dependencies, and it is now loaded along the other required libraries. The wrap_plots function is missing here. Yes, thank you for catching this; we’ve added patchwork to the list of dependencies, and it is now loaded along the other required libraries. I got an error when running the QC on reference cell counts. \"Error: Can't combine `1$CellLine_R1` and `2$CellLine_R1`.\" True, thank you; I could reproduce this with the current R and package versions. It has been fixed by converting the ‘run’ object of class ‘table’ to call ‘integer’ using c(). Minor comments: When running the code using the data provided, the directory name should be modified to \"CyTOF_acquisition_1-3.FCS/\" instead of data: fcs <- list.files(\"CyTOF_acquisition_1-3.FCS/\", \"acquisition\", full.names = TRUE) We are not sure we understand this comment. ‘list.files(path, pattern, …)’ expects the first argument to be a directory (where the FCS files are located), not the file names themselves (“xxx.FCS”). Also, it should be specified that the directory name containing all the data should be called \"data\" and it refers to the directory name, or an alternative is to have the local directory \".\" instead of data like in here: # specify path to reference beads ref_beads <- file.path(\".\", \"normalization_beads.fcs\") Thank you, yes, we forgot to mention that in the presented code all data used throughout the workflow is expected to sit inside a “data” subdirectory relative to where the .Rmd file is being run. We have now added a note explaining this in the 2nd paragraph under “Results”. Introduction: \"an important step is to correct for batch effects, which can be achieved by including a shared control sample in each independent batch\" Add CytofRUV reference mentioned in the discussion. We updated the reference to CytofRUV to the new version of the manuscript published in eLife and added it to the introduction. \"In our example, barcode identifiers include each sample’s type (CellLine, PBMC or Tumor), group (R for reference or S for sample of interest), and replicate number; and follow a consistent naming scheme: We can easily extract these components and store them in the SCE’s cell metadata (colData)\". The example selected is not the best one, as it not showing any differences between the 6 first row. True. We have modified the example to sample 10 unique ‘sample’ entries (= type_group) for which to display the ‘colData’. There is a typo in the legend of some figures like figure 17: \"previously\" acquired runs. Thanks for pointing out this typo, which was corrected in the corresponding figures." } ] }, { "id": "73588", "date": "01 Dec 2020", "name": "Felix Hartmann", "expertise": [ "Reviewer Expertise Single cell proteomics", "Mass Cytometry", "Immunology", "Stem Cell biology" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn their manuscript, Crowell & Chevrier et al. present a novel workflow to preprocess mass cytometry (CyTOF) datasets in R. The presented pipeline is a useful update on earlier publications and packages, including the authors' CATALYST package which is clearly stated. Overall, I find this to be a valuable tool that brings together different functionalities into a unified workflow that enables reproducible and comprehensive preprocessing of this data type. The different steps and approaches are well described and illustrated. Especially, the inclusion of a functionality to perform live cell gating without having to switch platforms is much appreciated, although its current implementation could be improved:\nGating on cells: Cells are first identified using an elliptical gate to exclude the two lowest density percentiles. Firstly, this plot relies on two DNA channels (whose information is likely redundant) and wasn’t directly applicable to alternative DNA stains (e.g. rhodium). Furthermore, I am wondering whether this approach might exclude for example a fraction of cycling cells or preferentially exclude cell types or states with increased chromatin accessibility and therefore higher DNA signal?\n\nGating on live cells: The approach suggested by the authors worked well on my test data, however, it takes a while to manually adjust values for every file to fit the gates closely to the data. While I see the value of automating this step, I also think that some manual gating could simplify the process and further increase downstream data quality. Potentially, the authors could adopt an approach like the gate_draw function from the CytoRSuite library.\n\nCompensation: The workflow includes compensation as a preprocessing step which the authors have shown in separate publications to improve data quality, but which is currently not routinely performed by many researchers working using mass cytometry. I, therefore, assume that most users of this pipeline would be relying on published spillover matrices that reflect estimates of isotope purity and oxidation. While I agree with the usefulness of this function, I believe that adding additional quality control functions could improve acceptance of and trust in this approach. For example, in flow cytometry, overcompensation is often easily spotted by the occurrence of overly negative values, however, using their NNLS approach this is not readily apparent in compensated mass cytometry data. It would be very helpful to have a quality metric that would alert users to such potential issues introduced by the compensation step.\n\nIn addition, testing this pipeline on some in-house generated data, a few minor issues occurred which should be addressed:\nWhile this might only be needed in rare cases, a function to rename channels and potentially match these names across multiple fcs files could enhance the adaptability of this package. In my test case, conflicting channel names prevented the import of the files into the workflow. In other cases, it might help to match channel names between batches. The authors could look to the premessa package for inspiration.\n\nThe authors have incorporated various options for DNA channels which is much appreciated. My test data had been stained with a rhodium intercalator. Specifying this worked well, only the res$scatter function seems to ignore this choice and instead seems to default to iridium DNA intercalators.\n\nSample specific debarcoding is appreciated. Figure 6 and the plotYields function return a debarcoding percentage. I believe this percentage refers to percent of initial assignments, but it is not specifically stated. It might be helpful to get a feeling of the percentage of cells (out of total cells) that are assigned after refining the initial assignments.\n\nIs the rationale for developing the new method (or application) clearly explained? Yes\n\nIs the description of the method technically sound? Yes\n\nAre sufficient details provided to allow replication of the method development and its use by others? Yes\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "8418", "date": "08 Aug 2022", "name": "Helena Crowell", "role": "Author Response", "response": "Gating on cells: Cells are first identified using an elliptical gate to exclude the two lowest density percentiles. Firstly, this plot relies on two DNA channels (whose information is likely redundant) and wasn’t directly applicable to alternative DNA stains (e.g. rhodium). Furthermore, I am wondering whether this approach might exclude for example a fraction of cycling cells or preferentially exclude cell types or states with increased chromatin accessibility and therefore higher DNA signal? The first gating step is indeed performed on two DNA channels which contains redundant information. However, this approach is commonly used in the mass cytometry field to exclude debris and cell doublets. By modifying the quantile and the target value defining the center of the ellipse, the user can control how many cells are excluded from the gate and ensure that most cycling cells are kept in the analysis. To gate on alternative DNA stains, a different pair of channels could be assigned to the “dna” variable in the corresponding code chunk. In the case of a single DNA channel, a one-dimensional gating (i.e., thresholding) could be applied (as opposed to the currently used elliptical gate). We have added a comment mentioning this to the text under “Gating on cells”. Gating on live cells: The approach suggested by the authors worked well on my test data, however, it takes a while to manually adjust values for every file to fit the gates closely to the data. While I see the value of automating this step, I also think that some manual gating could simplify the process and further increase downstream data quality. Potentially, the authors could adopt an approach like the gate_draw function from the CytoRSuite library. Indeed, the approach depicted in this paper works well in cases where a limited number of samples are included in a run and when the live/dead cell profile is well defined and consistent between samples. The process can indeed be tedious when hundreds of samples are included in a run or when the live/dead cell profile is more complex. In the latter case, including a function similar to gate_draw function from CytoRSuite could be helpful. However, we here aimed at proposing an automated pipeline; manual gating would defeat this purpose. As a side note: We have attempted applying CytoRSuite, however, encountered several confusing issues that we’ve been unable to resolve: The CytoRSuite site (https://dillonhammill.github.io/CytoRSuite) lists a GH repository that no-longer exists; we could find an installable version at https://github.com/gfinak/cytoRSuite (is this the same?) but ‘drawGate()’ gave an error that we have not been able to resolve; meanwhile, any of CytoRSuite, cytoRSuite and cytoSuite (from which the latter has been forked) have not been changed in 4 years. Taken together, this gave us the feeling that the tool is no longer maintained and likely to be inapplicable with current versions of R and Bioconductor. Of course, there may be other tools available at this point for manual gating, and we leave it to the user to incorporate these into their workflow should that be of interest. A possible strategy then might be to i) perform manual gating and export the resulting gates into a table (gating scheme); ii) apply that scheme in an automated fashion (e.g., using the code we presented); and, iii) do manual adjustments to refine gates according to the current experiment. Compensation: The workflow includes compensation as a preprocessing step which the authors have shown in separate publications to improve data quality, but which is currently not routinely performed by many researchers working using mass cytometry. I, therefore, assume that most users of this pipeline would be relying on published spillover matrices that reflect estimates of isotope purity and oxidation. While I agree with the usefulness of this function, I believe that adding additional quality control functions could improve acceptance of and trust in this approach. For example, in flow cytometry, overcompensation is often easily spotted by the occurrence of overly negative values, however, using their NNLS approach this is not readily apparent in compensated mass cytometry data. It would be very helpful to have a quality metric that would alert users to such potential issues introduced by the compensation step. These are all very good points and legitimate concerns. As indicated in the original paper, the spillover matrix used to compensate mass cytometry data should be calculated based on the antibodies included in the panel. We should stress here that, based on the single-stained bead acquisition approach presented in the original paper, the experimental procedure required to generate a compensation matrix is fairly straightforward and can be achieved rapidly. Using a previously published spillover matrix is a risky strategy, which can indeed lead to inaccurate compensation. The user should instead first run the compensation in classic mode and perform a visual inspection to ensure no overcompensation can be detected before using the NNLS method. This is a valuable option to avoid this specific type of artefact. Automating this step is a good suggestion, but is out of the scope of this publication and comes with some disadvantages. The risk we see is that this process could be imperfect and potentially misleading for the user. Indeed, such an approach would only identify overcompensation in channels where a single positive population is present but not in the case of a double positive population. In other words, it will highly depend on the user’s data type. Furthermore, it would not identify under-compensated signals. As a consequence, providing an approach to alert users of potential issues would likely be imperfect and could give a wrong impression that the data are correctly compensated if no alert is raised, which is not necessarily the case. Moreover, to the best of our knowledge, such an approach also doesn’t exist in fluorescent flow cytometry, most likely due to the fact that ensuring accurate compensation on a fully stained data set is a challenging task. We should also mention that the spillover coefficients in mass cytometry rarely exceed 4% and therefore the consequences of a slight over or under-compensation are less important in mass cytometry than in flow cytometry. Minor comments: While this might only be needed in rare cases, a function to rename channels and potentially match these names across multiple fcs files could enhance the adaptability of this package. In my test case, conflicting channel names prevented the import of the files into the workflow. In other cases, it might help to match channel names between batches. The authors could look to the premessa package for inspiration. We very much appreciate this comment as we have encountered various discrepancies between panels, especially in long-term projects. To date, we have used a custom R script to i) read in files separately; ii) fix panels according to a reference file (i.e., removing/adding additional/missing channels); and, iii) write out a new set of FCS files with concordant panels. However, this solution is suboptimal as it leads to a duplication of files (or, in case the original files were overwritten, the process would no longer be reproducible). Similarly, a GUI solution (as ‘premessa’) would defeat the purpose of providing an automated, reproducible preprocessing solution. Thus, taken together, we propose (and have now implemented) the following strategy: > ‘prepData’ now exposes additional arguments to be passed to ‘flowCore::read.FCS’ via ‘...’ > ‘read.FCS’ provides an argument ‘channel_alias’: “an optional ‘data.frame’ used to provide the alias of the channels to standardize and solve the discrepancy across FCS files. [...]” > independent of whether or not this option is used, ‘prepData’ will check whether panels (FCS channel names) match between files: in case of any discrepancy, the newly added ‘fix_chs’ argument will be used to determine how to resolve discrepancies “all” will keep all channels (i.e., the union across files); any missing channels will be added to the respective samples, and a channels x samples matrix is stored in the object to track which channels were present in which samples originally “common” will keep shared channels (i.e., the intersection across files); any other channels will be dropped from the respective files ‘prepData’ will, in any case, return a ‘SingleCellExperiment’, i.e., no altered FCS files or ‘flowFrame’s will be written out / returned The authors have incorporated various options for DNA channels which is much appreciated. My test data had been stained with a rhodium intercalator. Specifying this worked well, only the res$scatter function seems to ignore this choice and instead seems to default to iridium DNA intercalators. We thank the reviewer for noticing this. Indeed, while the workflow allows for specification of the DNA channels used (via variable ‘dna’), these were fixed internally in CATALYST’s ‘normCytof()’ function. We have added an additional argument to allow passing custom DNA channel masses (default ‘dna = c(191, 193)’ for Ir191/3; for Rh103, the argument would be ‘dna = 103’ instead); the output scatter plot of DNA vs. bead intensities (‘res$scatter’) is now generated based on the first matching DNA channel (see updated ‘?normCytof’ documentation). Sample specific debarcoding is appreciated. Figure 6 and the plotYields function return a debarcoding percentage. I believe this percentage refers to percent of initial assignments, but it is not specifically stated. It might be helpful to get a feeling of the percentage of cells (out of total cells) that are assigned after refining the initial assignments. That is correct: As in the original Finck et al. outputs (a MATLAB application), yields (left-hand y-axis) correspond to the proportion of cells that would be retained upon applying a given cutoff (x-axis). In Figure 8, we compare the absolute barcode population sizes before vs. after debarcoding. Analogously, it would be straightforward for users to generate such a barplot from cell counts obtained when applying various thresholding schemes (e.g., no filtering compared to global vs. sample-specific separation cutoffs)." } ] } ]	1	https://f1000research.com/articles/9-1263
https://f1000research.com/articles/5-43/v1	08 Jan 16	{ "type": "Method Article", "title": "How to put plant root uptake into a soil water flow model", "authors": [ "Xuejun Dong" ], "abstract": "The need for improved crop water use efficiency calls for flexible modeling platforms to implement new ideas in plant root uptake and its regulation mechanisms. This paper documents the details of modifying a soil infiltration and redistribution model to include (a) dynamic root growth, (b) non-uniform root distribution and water uptake, (c) the effect of water stress on plant water uptake, and (d) soil evaporation. The paper also demonstrates strategies of using the modified model to simulate soil water dynamics and plant transpiration considering different sensitivity of plants to soil dryness and different mechanisms of root water uptake. In particular, the flexibility of simulating various degrees of compensated uptake (whereby plants tend to maintain potential transpiration under mild water stress) is emphasized. The paper also describes how to estimate unknown root distribution and rooting depth parameters by the use of a simulation-based searching method. The full documentation of the computer code will allow further applications and new development.", "keywords": [ "Computer simulation", "Richards’ equation", "Root growth", "Soil water balance", "Transpiration", "Uptake compensation", "Water stress" ], "content": "Introduction\n\nIncreased biomass and yield of agricultural crops hinges on improved efficiency of root water uptake1,2. Biophysical mechanisms responsible for the improved uptake efficiency in turn rely on linkages between plant physiological processes and the physics of soil water movement; the development of the latter has been well illustrated in 3,4 and 5. Research literature in this and closely related areas has been profound in past decades, though roughly two categories of approach can be identified: one that is mechanistic and one that is phenomenological in nature. The mechanistic approach has improved our understanding of the soil-root interactions by identifying major resistances and driving forces of water flow from soil to roots3,4, as well as the scale-dependent interactions and geometry among soil organisms responsible for water and nutrient uptake6,7. Yet effective mechanistic modeling needs a large amount of empirical data support, which can not always be met due to various factors constraining research activities. On the other hand, an intuitive, phenomenological approach can be implemented with less empirical data support. Examples of this latter approach may include constraining root water uptake capacity by soil water potential8, by root length distribution9–11, and through additional modifications of the root uptake sensitivity to local soil water potential and root density12–16, which allows compensated uptake to maintain potential transpiration17,18.\n\nOne of the major goals of agronomic management for increased water use efficiency is to channel water loss through transpiration19. This to some extent can be aided by the compensated root uptake, which has been implemented in software such as HYDRUS (http://www.pc-progress.com/en/Default.aspx?hydrus-1d) through the use of a threshold root uptake adaptation factor, whereby reduced water uptake in water-stressed parts of the root zone is fully compensated for by increased uptake in other soil regions where water is available20.\n\nHowever, root water uptake compensation has been implemented in different studies using different models, which naturally calls for the flexibility of implementation of various forms of the compensation mechanism in root uptake studies. The first objective of this paper is to show that this flexibility can be obtained by using a water flow model extended from an original model as described in 5. This extended model was used in generating numerical solutions of water flow problems in 16.\n\nThe second objective of this paper is to provide a tool for quantifying plant water uptake under conditions where information of root depth and distribution pattern is not known. This is relevant to agricultural applications as fine root information remains difficult to obtain despite the progress made in advanced underground sensing21. We take advantage of inverse modeling, similar to 22 and 10, to find optimal solutions of unknown root parameters based on good measurement of soil water content, which can be obtained through the use of various soil moisture sensors. Despite excellent documentation of the methods for solving the soil water flow equations relevant to agricultural water management3,5, the author has not seen a paper documenting the details of how to put the root uptake component into a soil water flow model, as well as providing the details of a search-based optimization procedure for root parameter estimation.\n\n\nMethods\n\nThe one dimensional Richards equation of soil water flow in the vertical direction can be written as\n\n\n\nwhere h is water pressure head (m), t is time (s), z space (m, positive downward and soil surface as zero), K hydraulic conductivity (m/s) and c=∂θ∂h. The reason why there is a negative sign in Equation 1 is that, when we take the space derivative for the gravity potential head z, namely, in ∂z/∂z, the values in the numerator change in the opposite direction as that in the denominator: gravity head always decreases downwards but our chosen space z increases downwards.\n\nThe model described by Equation 1 does not consider a sink of plant root water uptake. It can be solved using the implicit finite difference method as described by 5. Here is a summary of key points with a few intuitive comments. Let’s for now assume surface fluxes as precipitation, irrigation, or surface evaporation. As Equation 1 considers soil water dynamics both in space (vertical axis) and time, we need to properly discretize the equation considering both space and time. Here we let all h’s that take space derivatives be approximated using values at the old (t = n) and the new (t = tn+1) times, but let K’s be approximated in old time (t = n). All other variables not taking partial derivatives are to be approximated in the old time. Assume the vertical axis is equally divided by Δz, to approximate Equation 1 at z = zi and tn+1 = tn+Δt, we have the following formula to use:\n\n\n\nAnother interesting aspect of Equation 2 is that the space index for K is shifted to the upper edge of each of the blocks, while the index of h or θ is located at the center of the blocks. This is the characteristic of the block-centered finite difference scheme and it will enable the calculation of fluxes between two adjacent soil layers, or blocks, as seen in the right sub-figure of Figure 1, which is based on Figure 5–13 of Warrick’s book (on page 195). In Figure 1, we reinforce the idea that, similar to the situation of conductivity, K, the index for flux density also is located at the edge of the blocks. Intuitively, this makes sense, because in the head-based equation of soil water flow, K and J have the same unit (both are in m/s). As a result, we can compare the magnitude of K and J directly. For example, if the water conductivity of the surface soil is similar to the rate of precipitation, we can roughly say that all the rain water would have time to fully infiltrate into the soil before ponding on the soil surface.\n\nA. Pressure heads and water conductivities are indexed differently. B. Highlight of one internal block. Modified based on Figure 5–13 of 5.\n\nThe terms of the implicit scheme can be collected to form a tridiagonal system of linear equations, with the water potentials for the new time (starred) arranged at the left side and those for the old time on the right side of the equation. Then, terms for different space segments can be collected to form the following equation:\n\n\n\nwhich can be written in matrix form as\n\n\n\nEquation 4 is called tridiagonal because, for the coefficient of the nz by nz square matrix, the elements are all zero except for those located along the three diagonals. From Equation 4, we can see that A1 = Cnz = 0. Actually, values of the coefficients on the left side of Equation 4 should be determined considering the boundary conditions at the soil surface and at the bottom of the root zone.\n\nDetailed solution procedures of the above model “Austere-Layered\" (hereafter referred to as AL.f) are provided in 5. Here in order to let this soil water flow model simulate root uptake, the following new components have been added: (a) dynamic root growth, (b) non-uniform root distribution and water uptake, (c) effect of water stress on plant water uptake, and (d) soil evaporation. Following Warrick’s original model, the extended model (ALS.f) was also programmed using Fortran 77. See https://zenodo.org/record/42663. To facilitate further development, variables (array variables and non-array variables) used in the original program AL.f, as well the extended program ALS.f, are listed in Supplementary material 1 (in four tables). The subroutine SINK() in ALS.f encapsulates various options for root uptake mechanisms. Similar to some other external subroutines, such as THOMAS(), variables inside the subroutine are local, so that they are not listed in the tables of Supplementary material 1. In the following we document major changes made to the program ALS.f:\n\nThe model AL.f was modified to include the flux update scheme proposed by 23 and was applied in program a2&3.for of 5. The main idea is summarized in the following (variables referred to are included in ALS.f):\n\n• Assume we use the flux upper boundary condition (B_TYPE= 2). At each new time step, the old hydraulic conductivities and soil water capacities are used to find the needed coefficients for solving the tridiagonal system of equations. However, the surface flux is temporarily not considered (C2=0). Then, these coefficients are provided to the Thomas subroutine to find the updated pressure head (HSTAR). The trial soil water content at the new time (THETA) is found using the newly computed conductivities based on values of HSTAR as well as the surface flux.\n\n• The trial value of THETA is accepted only if the soil water content at a depth interval, or that for intervals immediately adjacent to this current depth interval, is unsaturated. In such a case, the soil water retention curve is used to update the new pressure head H based on the trial value of THETA.\n\n• Otherwise, the trial value of THETA is rejected, the value of HSTAR is accepted as the updated value for H, and the updated THETA is computed from the soil water retention curve based on HSTAR.\n\nDetailed information regarding the root uptake sink term is included in Supplementary material 2. In particular, Equation 1 of Supplementary material 2 illustrates the importance of four water pressure heads for root uptake: h1 marks the anaerobiosis point; h4 the pressure head at permanent wilting point, and h2 and h3 marks the range of pressure head for optimal root uptake. Here we refer to h3 as the ending water potential for optimal uptake, because root uptake starts to reduce when the soil water potential becomes lower than this point. As different plants might have different sensitivity to a mild water stress, it is useful to test the model’s sensitivity to h3.\n\nFollowing 14 and 24, h3 may be assumed as h31=−11 m for a slow transpiration of Tp1=1 mm day−1 and h32=−5 m for a fast transpiration of Tp2=5 mm day−1. We tested two more possibilities of the h3 values, namely, (h31,h32)=(−14,−8) m, and (h31,h32)=(−16,−10), for (Tp1,Tp2)=(1,5)mm day−1. We also assumed that h3 changed in a linear fashion for intermediate transpiration rates between Tp1=1 and Tp2=5 mm day−1), using different h31 and h32 values:\n\n\n\nwhere a=(h31−h32)/(Tp1−Tp2). This change is reflected in the new subroutine HTHREE, as shown in ALS.f. This (Equation 5) is another form of Equation 2 of Supplementary material 2 but with variable h31 and h32.\n\nThe extended program ALS.f also allows testing different root uptake functions with or without compensation mechanisms, such as those demonstrated in 14,15,25. In particular, in subroutine SINK(), the model by 12 is used when ICPS= 1; a function by 9 is used when ICPS= 3; and the compensation function of 14 (in combination with Wu’s function) is used when ICPS= 2. The normalized root density function (Lnrd) of 9 has four parameters:\n\nThe extended program ALS.f also allows testing different root uptake functions with or without compensation mechanisms, such as those demonstrated in 14,15,25. In particular, in subroutine SINK(), the model by 12 is used when ICPS= 1; a function by 9 is used when ICPS= 3; and the compensation function of 14 (in combination with Wu’s function) is used when ICPS= 2. The normalized root density function (Lnrd) of 9 has four parameters:\n\n\n\nwhere zr = z/Zr(t) is the normalized root density at time t with Zr(t) the maximum rooting depth (m) at time t. The coefficients R1 through R4 represent experimentally fitted values for wheat, with R1 = 2.21, R2 = -3.72, R3 = 3.46, and R4 = -1.87 according to 9. The compensation function proposed by 14 at time t has the following form:\n\n\n\nwhere Si is the actual water uptake from ith soil depth increment, αi is the reduction function for this ith depth increment, Lnrd,i the normalized root density function for the ith depth increment, Δzi the thickness (m) of the ith depth increment, and λ is a fitting parameter varying from 0.01 to 2.0 according to 14.\n\nIn order to cope with situations in which the information of rooting depth and root distribution pattern is unknown, the program ALS.f was converted into a subroutine and is callable by a searching main program, ALSS.f, which is available at https://zenodo.org/record/42702. This conversion was quite straight forward in Fortran 77 in that we only did three things: (a) we deleted parameters BETA and ZRMAX from the parameter listing; (b) we converted the program ALS.f from a main program to a subroutine using 2 input dummy variables BETA and ZRMAX and 7 output dummy variables; and (c) we let this subroutine be called multiple times using different values of true BETA and true ZRMAX from arrays BETAS() and ZRMAX() within the main program unit and made sure that only the values of selected 7 variables were returned to the main program after each run but all the other information from within the subroutine ALS() is lost.\n\nThe provided two Fortran programs, ALS.f and ALSS.f, can be run from one of the freely available compilers, such as g95 (http://www.g95.org/). A short introduction of how to install and use g95 to a PC under Window XP or Windows 7 can be found at: http://www.ems.psu.edu/~young/meteo473/Bootcamp/g95Instructions.pdf\n\nTo run ALS.f and ALSS.f, the following input information is needed (see Supplementary material 3):\n\n• Soil physical properties and in particular soil water retention curve and saturated hydraulic conductivity. The exact format of data structure is shown in the supplementary data file ALS.DAT, which follows the template provided by 5. A method for predicting soil water retention curves based on easily measured soil texture and bulk density data is illustrated in 26.\n\n• Initial soil water content profile. This must be provided and put to exact format as shown in supplementary data file INITF.DAT, following the template provided by 5. The measured soil water content must be interpolated so that every depth increment of soil has a water content value in it. One method of data interpolation is outlined in 16 using routines provided in 27 and 28.\n\n• Measured terminating soil water content. This can be the measured soil water content on last day of simulation and must be entered in the format as shown in TERMF.DAT of Supplementary material 3. No interpolation is needed for this file.\n\n• Daily weather data. Daily evapo-transpiration rate, daily average air temperature, daily rainfall, relatively humidity, as well as leaf area index, must be entered in data file WEA2.DAT in the order as shown in the data file. Daily leaf area index can be interpolated based on field measured result, as shown in 16.\n\nThere are four output files from ALS.f (Supplementary material 3):\n\n• OUTS.DAT – Mirrors output from AL.f of 5.\n\n• OUTS2.DAT – Daily soil water potential and water contents for interested soil depths.\n\n• INFS.DAT – Mirrors output from AL.f of 5.\n\n• WUE.DAT – Summary of daily cumulative water loss.\n\nThere are seven output files from ALSS.f. They provide the following information based on particular realization of combinations of root distribution shape factor BETAS and the maximum rooting depth ZRMAXS (Supplementary material 3):\n\n• ARD.DAT – Average relative discrepancy between measured and simulated soil water content throughout the simulation period.\n\n• C_AEVA.DAT – Cumulative soil evaporation throughout the simulation period.\n\n• C_ATRA.DAT – Cumulative transpiration throughout the simulation period.\n\n• WBELOW.DAT – Amount of water to deep drainage out of the specified root zone. This was inherited from AL.f\n\n• WADD.DAT – Amount of water added to the system. This was also inherited from AL.f\n\n• BIGI.DAT – Cumulative infiltration. This was also inherited from AL.f\n\n• PCTDIF.DAT – Percent difference in water balance, defined in 5 as (BIGI-WADD)/WADD*100.\n\nThe main difference between the output files of ALS.f and those of ALSS.f is that the outputs from the former are a summary of water balance from the simulation of soil water balance based on one set of root parameters (rooting depth and shape factors), while those from the latter (ALSS.f) contain the simulation outcomes using many sets of root parameters (see next section for further details).\n\n\nUse cases\n\nPrograms ALS.f and ALSS.f in their current forms were customized to simulate the soil water dynamics for 111 days from May 14 to September 1, 2009. This is reflected both in the programs and the input data files. To use the model in other locations and other durations, appropriate changes must be made both in a few parameters of the programs and input data files. The two potential uses of the programs are outlined in the following:\n\n• If root distribution parameter BETA and maximum rooting depth ZRMAX are known, then program ALS.f may be used to simulate soil water dynamics with root uptake. Make sure to provide updated values for the major parameter values, such as JMATUR (Julian day number of growth maturity), JTHAW (Julian day number of growth initiation), BETA, and ZRMAX.\n\n• If root distribution parameter BETA and maximum rooting depth ZRMAX are unknown, then it is recommended to first use ALSS.f to find the optimal values for BETA and ZRMAX before using ALS.f to simulate soil water dynamics. Before running ALSS.f, three things must be done:\n\n1. Check to see if the current value of h3 (see Equation 1 of Supplementary material 2) is correct by changing, if necessary, the value of parameter IHTH (current default value is set to 1, meaning (h31,h32)=(−11,−5)). See the preamble of subroutine SINK() for two other options.\n\n2. Check to see if the parameter of ICPSN is correctly specified. currently, the default value is 1, meaning to use Ojha’s compensation function. Setting the value of ICPSN to 2 will switch to Li’s compensation function, and a value of 3 will invoke Wu’s uptake function (without compensation).\n\n3. Check the nested DO LOOPs structure to adjust the admissible values for index variable II (currently it is set to have 16 different values for BETA) and JJ (currently it is set to have 22 different values for ZRMAX). At the same time, the following lines in the main program of ALSS.f must be changed to be compatible with the range of index values in the nested DO LOOPS.\n\n\n\n• Finally, it is recommended to put both the program files and the required input data files in the same folder before running the programs.\n\n\nSummary\n\nWhile plant root water uptake has been implemented in commercial software packages, very few researchers have found the time to document important details of how root uptake can be included in a soil water flow model. This paper tries to fill this knowledge gap by using a simple computer program aided with sample input data sets. Specifically, we modified and extended a soil water flow model of 5 to include plant root water uptake capability. We showed that the extended program has the flexibility of considering different sensitivity of root uptake, as well as different water uptake mechanisms. We also modified the model to search for optimal root parameters based on measured soil water content data. This is relevant for new application in that field data of root development usually is expensive and sometimes difficult to obtain, and the utilization of a searching-based modeling approach will help to identify root parameters for improved water balance characterization, which in turn may help to identify ways to improve crop water use efficiency under field conditions. No menu-driven user interface is provided but the author believes that, under some circumstances of knowledge discovery, it is more efficient to work directly with a well-structured computer program, such as the one described in this paper, than relying on a packaged one.\n\n\nSoftware availability\n\nALS.f is available from: https://zenodo.org/record/42663\n\nALSS.f is available from: https://zenodo.org/record/42702\n\nALS.f archived source code as at the time of publication: http://dx.doi.org/10.5281/zenodo.4266329\n\nALSS.f archived source code as at the time of publication: http://dx.doi.org/10.5281/zenodo.4270230\n\nLicense: Academic free license (\"AFL\") v.3.0 http://opensource.org/licenses/afl-3.0.php", "appendix": "Competing interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis paper is part of North Dakota Agricultural Experiment Station project ND6149 and Texas A&M AgriLife Research Hatch project TEX09574, both funded by the USDA NIFA.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nThe author thanks Bob Patton, Paul and Anne Nyren and Lyle Prunty at North Dakota State University for fruitful collaboration leading to this paper.\n\n\nSupplementary material\n\nSupplementary material 1. Definition of variables used in the computer programs ALS.f.\n\nThis file contains four tables documenting the variables used in AL.f (Supplementary Tables 1 and 3) and those added in ALS.f (Supplementary Tables 2 and 4).\n\nClick here to access the data.\n\nSupplementary material 2. More details about the root uptake term.\n\nThis file documents details of the water uptake term as used in the extended Fortran program ALS.f. It is useful for those who are curious about how the water extraction term is specified in the model.\n\nClick here to access the data.\n\nSupplementary material 3. Data files for ALS.f and ALSS.f.\n\nThis includes (a) four input data files common to ALS.f and ALSS.f, (b) four Output files from ALS.f (OUTS.DAT, OUTS2.DAT, INFS.DAT, WUE.DAT), (c) seven output files from ALSS.f (ARD.DAT, C_AEVA.DAT, C_ATRA.DAT, WBELOW.DAT, WADD.DAT, BIGI.DAT, PCTDIF.DAT).\n\nClick here to access the data.\n\n\nReferences\n\nCampbell GS, Diaz R: Simplified soil-water balance models to predict crop transpiration. In F. R. Bidinger and C. Johansen, editors, Drought research priorities for the dryland tropics. International Crops Institute for the Semi-Arid Tropics, Parancheru, A. P. 502 324, India, 1988; 15–26. Reference Source\n\nPassioura JB, Angus JF: Improving productivity of crops in water-limited environments. In D. L. Sparks, editor, Advances in Agronomy. Elsevier Science, USA, 2010; 106: 37–75. Publisher Full Text\n\nCampbell GS: Soil Physics with Basic: Transport Models for Soil–Plant Systems. Developments in Soil Science 14. Elsevier, New York, 1985. Reference Source\n\nHopmans JW, Bristow KL: Current capabilities and future needs of root water and nutrient uptake modeling. In D. L. Sparks, editor, Advances in Agronomy. Elsevier Science, USA, 2002; 77: 103–183. Publisher Full Text\n\nWarrick AW: Soil Water Dynamics. Oxford University Press, 2003. Reference Source\n\nRoose T, Schnepf A: Mathematical models of plant-soil interaction. Philos Trans A Math Phys Eng Sci. 2008; 366(1885): 4597–4611. PubMed Abstract \| Publisher Full Text\n\nLeitner D, Schnepf A, Klepsch S, et al.: Comparison of nutrient uptake between three-dimensional simulation and an averaged root system model. Plant Biosystem. 2010; 144(2): 443–447. Publisher Full Text\n\nFeddes RA, Kowalik PJ, Zaradny H: Simulation of field water use and crop yield. Center for Agricultural Publishing and Documentation, Wageningen, The Netherlands, 1978. Reference Source\n\nWu J, Zhang R, Gui S: Modeling soil water movement with water uptake by roots. Plant Soil. 1999; 215(1): 7–17. Publisher Full Text\n\nZuo Q, Zhang R: Estimating root-water-uptake using an inverse method. Soil Sci. 2002; 167(9): 561–571. Publisher Full Text\n\nZuo Q, Jie F, Zhang R, et al.: A generalized function of wheat’s root length density distributions. Vadose Zone J. 2004; 3: 271–277. Reference Source\n\nOjha CS, Rai AK: Nonlinear root water uptake model. J Irrig Drain Eng. 1996; 122(4): 198–201. Publisher Full Text\n\nAdiku SG, Rose CW, Braddock RD, et al.: On the simulation of root water extraction: examination of a minimum energy hypothesis. Soil Sci. 2000; 165(3): 226–236. Publisher Full Text\n\nLi KY, De Jong R, Boisvert JB: An exponential root water uptake model with water stress compensation. J Hydrol. 2001; 252(1–4): 189–204. Publisher Full Text\n\nYadav BK, Mathur S, Siebel MA: Soil moisture dynamics modeling considering the root compensation mechanism for water uptake by plants. J Hydrol Eng. 2009; 14(9): 913–922. Publisher Full Text\n\nDong X, Patton BD, Nyren AC, et al.: Quantifying root water extraction by rangeland plants through soil water modeling. Plant Soil. 2010; 335(1): 181–198. Publisher Full Text\n\nHeinen M: Compensation in root water uptake models combined with three-dimensional root length density distribution. Vadose Zone J. 2014; 13(2). Publisher Full Text\n\nVerma P, Loheide SP, Eamus D, et al.: Root water compensation sustains transpiration rates in an Australian woodland. Adv Water Resour. 2014; 74: 91–101. Publisher Full Text\n\nBodner G, Nakhforoosh A, Kaul HP: Management of crop water under drought: A review. Agron Sustain Dev. 2015; 35(2): 401–442. Publisher Full Text\n\nSimunek J, Hopmans JW: Modeling compensated root water and nutrient uptake. Ecol Model. 2009; 220(4): 505–521. Publisher Full Text\n\nJayawickreme DH, Jobbágy EG, Jackson RB: Geophysical subsurface imaging for ecological applications. New Phytol. 2014; 201(4): 1170–1175. PubMed Abstract \| Publisher Full Text\n\nMusters PA, Bouten W: A method for identifying optimum strategies of measuring soil water contents for calibrating a root water uptake model. J hydrol. 2000; 227(1–4): 273–286. Publisher Full Text\n\nKirkland MR, Hills RG, Wierenga PJ: Algorithms for solving Richards’ equation for variably saturated soils. Water Resour Res. 1992; 28(8): 2049–2058. Publisher Full Text\n\nYang D, Zhang T, Zhang K, et al.: An easily implemented agro-hydrological procedure with dynamic root simulation for water transfer in the crop-soil system: validation and application. J Hydrol. 2009; 370(1–4): 177–190. Publisher Full Text\n\nLai CT, Katul G: The dynamic role of root-water uptake in coupling potential to actual transpiration. Adv Water Resour. 2000; 23(4): 427–439. Publisher Full Text\n\nDong X, Patton BD: Predicting soil water retention curves based on particle-size distribution using a Minitab macro. Afr J Soil Sci. 2015; 3(1): 079–085. Reference Source\n\nDoughty S: Solve It: Computer Aided Mathematics for Science and Engineering. Gulf Publishing Company, 1995. Reference Source\n\nHanna OT, Sandall OC: Computational Methods in Chemical Engineering. Prentice Hall PTR, 1995. Reference Source\n\nDong X: A plant root water uptake model. Zenodo. 2015. Data Source\n\nDong X: A program for searching optimal root parameters in plant water uptake modeling. Zenodo. 2015. Data Source" }	[ { "id": "11896", "date": "04 Feb 2016", "name": "Brijesh K Yadav", "expertise": [], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe text is nicely written and I have few minor comments as described below.Some references order is not cited correctly. For example the compensation function in equation 7 is proposed by \"15\" instead of the cited reference is number \"14\". Similaraly the rest of the citation numbers needs to be corrected. The author has shown the moisture flow equation (Eqn 1) without the sink term. Since the focus of this article is on plant root uptake, so sink term should be included in all the governing equations along with their discrete form.The figure 1 can be improved to make it more readable.", "responses": [ { "c_id": "8513", "date": "07 Sep 2022", "name": "Xuejun Dong", "role": "Author Response", "response": "Thank you for the interesting comments! This paper attempts to provide a further documentation to an earlier paper by Dong et al. (Plant and Soil, 335:181-198, 2010). The focus is on providing details on computer implementation of the model. For completeness, several supplemental files, data sets, and computer code, are provided. I understand it can be difficult for the reader to switch back and forth between the main paper and the supplemental files. But I hope this way of presentation will save space and avoid repeating published material. For examples of how the choices of model parameters influence the results, one can refer to the paper of Dong et al. (2010), in which a number of scenarios of varying soil physical and root parameters are discussed in detail. Also, one may refer to the conference paper by Dong at al (2013), in which the same model was applied to simulate soil water flow in a heavily grazed pasture (cited in the paper). In this paper, a direct comparison of this model against some other models is not done. I leave it for a future effort. Yes, I have included a sink term for all major equations. Also, some further discussions on the sink terms are provided. Finally, Figure 1 has been re-drawn." } ] }, { "id": "11894", "date": "24 Oct 2016", "name": "Jun Fan", "expertise": [], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIt is an interesting topic and the text is well written but it is requested some program experience. It is a technical report not fully a scientific paper. It gave sufficient detail information about this model and also some relative programs. If a plant root uptake model with plant growth process which can report LAI or other parameters for ET calculation was put to Soil water flow model, this is more useful. If some cases can be tested and compared with other models, it will make user to use it easily. I fully agreed that it can be published as so far and give more opportunities to test it.", "responses": [ { "c_id": "8514", "date": "07 Sep 2022", "name": "Xuejun Dong", "role": "Author Response", "response": "Thanks for the insightful comments! Yes, I agree it is not a typical research paper, but one documenting methodical details of a previously published paper. The dynamics of root and LAI growth are considered in the model, although not in a mechanistic manner in which the growth of roots and leaves are dynamically linked to the local weather and soil water availability. Again, the focus is on describing in detail the computer implementation procedure, along with explanation of important concepts, but lacks a direct comparison with other published models. As noted above, I hope the further comparisons can be achieved in future work." } ] }, { "id": "16853", "date": "11 Nov 2016", "name": "Hirotaka Saito", "expertise": [], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article entitled \"How to put plant root uptake into a soil water flow model\" by Dong is in general well written and technically sound. However when I read this manuscript, I just found it a bit difficult to read as most relevant information such as Feddes function was in a supplemental file. There were no examples in the manuscript either. In my opinion, if the author is providing a tool to evaluate root water uptake, several examples (more than one) need to be included in the manuscript; for example how the choice the model affect soil water dynamics. This fact really makes it difficult to evaluate the manuscript.\nThere should be a sink term, S, that is used to account for root water uptake in Eq (1).\n\nFigure 1 needs to be upgraded. They get blurred.", "responses": [ { "c_id": "8515", "date": "07 Sep 2022", "name": "Xuejun Dong", "role": "Author Response", "response": "Thanks for the encouraging comments; your suggestions are accepted. I inspected references #14 and #15 and made corrections about the source of Eqn (14). In this case, I think both #14 and #15 should be acknowledged, since they provide different insights to the same problem. I added the sink term to all governing equations. Also, a clear figure has been provided to replace the blurred Figure 1 in the previous submission." } ] } ]	1	https://f1000research.com/articles/5-43
https://f1000research.com/articles/11-904/v1	05 Aug 22	{ "type": "Systematic Review", "title": "Cytotoxic T-lymphocyte associated-protein-4 +49A/G-allele (rs231775) single nucleotide polymorphisms are associated with acute allograft renal transplantation rejection: A multilevel modelling of meta-analysis", "authors": [ "Besut Daryanto", "Athaya Febriantyo Purnomo", "Athaya Febriantyo Purnomo" ], "abstract": "Background: Acute renal transplant rejection is believed to be an immunological phenomenon and is one of the most serious consequences of transplantation as a treatment for end-stage renal illness. In recent decades, numerous research has been conducted to investigate the relationship between cytotoxic T-lymphocyte antigen 4 +49A/G (CTLA-4 +49A/G) single nucleotide polymorphisms (SNPs) with the likelihood of rejection; nevertheless, the results are still controversial, and inconsistency has been documented among investigations. Consequently, the purpose of the present investigation was to conduct a study on the relation between CTLA-4 +49A/G polymorphism and risk of transplant rejection. Methods: The study was reported based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Retrospective and prospective analytical randomized control trial (RCTs) published prints from Embase, PubMed, Cochrane, and Web of science were included to the study in accordance with the PRISMA guidelines. The search was conducted on February 2nd, 2022, using the search term (cytotoxic-T-lymphocyte-antigen-4 OR CTLA-4) AND (gene polymorphism OR single nucleotide polymorphisms OR allele OR alleles OR genotype OR genotypes) AND (renal OR kidney) AND (transplant OR transplantation) AND (acute rejection). Results: The CTLA-4 G-allele/GG-genotype was more likely to be related to renal transplantation rejection risk. It was found with odds ratio (OR) in overall analysis of G vs. A-allele was 1.22 (95%CI 1.05-1.42; p-value=0.01) and the OR of GG vs. AG+AA-genotype was 1.47 (95%CI 1.14-1.89; p-value=0.003). However, the AA-genotype was not associated with renal transplantation rejection risk. The interesting finding in this study was the association of the SNPs and rejection of renal transplantation was especially found in Asian sub-analysis. Conclusions: Consequently, the CTLA-4 G-allele/GG-genotype is related to the likelihood of rejection in patients underwent renal transplantation.", "keywords": [ "gene polymorphism", "renal transplant rejection", "cytotoxic T-lymphocyte associated protein 4 (CTLA-4)" ], "content": "Introduction\n\nHigh mortality and morbidity rates are still the main issues in end-stage renal disease (ESRD), and it increases healthcare utilization.1 There are several options directed for renal replacement therapy as ESRD treatment, which are hemodialysis (HD), continuous-ambulatory peritoneal-dialysis (CAPD), and renal transplantation. For now, renal transplantation is the gold standard treatment for ESRD.1,2 Renal transplantation is still the best method option for treatment for ESRD due to better quality of life, the modifiable morbidity rate, promising survival rates, and the greatest impacts in daily basis activities in spite of the rejection risks as one of the complications.3,4\n\nPresently, renal transplantation is the most effective treatment for end-stage renal illness, because it preserved individuals with ESRD’s lives.2 However, the big issue of renal transplantation is acute rejection in some recipient cases, which diminishes the quality of the donated kidney.2 Renal transplantation rejection can consequently decrease the renal physiological function and become a threat to a patient’s life. Therefore, it is essential to investigate factors that aggravate transplantation rejection.\n\nCytotoxic T-lymphocyte antigen-4 (CTLA-4), is a regulatory molecule that inhibits T-cell effector action after first costimulatory signal activation.3,4 CTLA-4 has been implicated in acute renal transplantation rejection etiology, according to available dataset.3 The CTLA-4 +49A/G single nucleotide polymorphism (SNPs) involves a shift from the A to the G-allele that leads to several complicated sequences that jeopardize the next transcription-translation phase of DNA. CTLA-4 is a key CTLA variation, and current findings indicate that the CTLA-4 +49A/G SNPs increases the likelihood of rejection. Previous meta-analysis has been conducted to evaluate the association between the CTLA-4 +49A/G SNPs and the incidence of renal transplantation rejection.4 Nonetheless, there was no assessment of the nature of polymorphism, which included Hardy-Weinberg equilibrium in order to exclude the chance of polymorphism influenced by evolution, moreover only limited studies were included. This study was conducted to determine if the CTLA-4 +49A/G SNPs were connected with the incidence of renal transplantation rejection by compiling a large number of previously published papers.\n\n\nMethods\n\nThe study was reported based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines.5 The search was conducted on February 2nd, 2022. Retrospective and prospective analytical randomized control trials (RCTs) published prints from Embase, PubMed, Cochrane, and Web of science were included in accordance with the PRISMA guideline and thoroughly analyzed using a random or fixed effect model regarding to its heterogeneity. These datasets were populated with the retrieval approach “(cytotoxic-T-lymphocyte-antigen-4 OR CTLA-4) AND (gene polymorphism OR single nucleotide polymorphisms OR allele OR alleles OR genotype OR genotypes) AND (renal OR kidney) AND (transplant OR transplantation) AND (acute rejection).” The extra reports were discovered using the citations found in the selected papers.\n\nStudies included had quantitative data of renal transplantation rejection genotype that had the cases of acute rejection and non-acute rejection comparison data; and adequate data on the distribution of the CTLA-4 +49A/G genotype was required. We also include retrospective or prospective studies, randomized trials, that provided sufficient data of odds ratio (OR) 95% confidence interval (CI). The thirteen studies that were included are shown in Figure 1. Other studies than those stated before were excluded.\n\nWe also measured the Hardy-Weinberg Equilibrium (HWE) formula (X2>3.84 indicated as deviation from HWE) as described by Rodriguez et al. 2009.6 Two reviewers (BD and AFP) worked independently at first to screen each record and each report retrieved, then reviewers discussed to achieve consensus. Any disagreement toward the included studies was resolved by consensus.\n\nTwo reviewers (BD and AFP) performed the literature selection and gathered the data from electronic databases that accumulated into a dataset qualified study that collected: the first author, the year of publication, the ethnicity, and patient-control proportions for CTLA-4 +49A/G genotyping into Microsoft Excel v2013. Using the distribution of the associated genotypes, the occurrence of the G-allele in CTLA-4 +49A/G were computed. The outcomes were compared, and differences were addressed via discussion.\n\nApplication of Review Manager version 5 (Cochrane Library, UK) was utilized to compute the available dataset from the included studies. The dataset included in the software was firstly collected in Microsoft Excel. Model of random effect was applied when p-value in heterogeneity test was <0.05. For dichotomous data, results were reported using OR, and 95% CI was also computed. Overall analysis needed p-value <0.05 to be interpreted as statistically significant. I2 was utilized for heterogeneity between the included studies as well.\n\n\nResults\n\nThis meta-analysis included 13 out of 15 papers7–21 investigating the relationship between CTLA-4 +49A/G SNPs and renal transplantation rejection risk. The data were extracted, and the occurrence of the G-allele of CTLA-4 +49A/G in the groups was determined. Table 1 presents the characteristics of the studies. These 13 studies included 959 patients with acute rejection and 2069 controls with non-acute rejection.\n\nAs shown in Figure 2 and Table 2, in the overall analysis (OR=1.22, 95% CI:1.05-1.42, P=0.001), the CTLA-4 +49A/G G-allele was shown to be related to an increased risk of acute rejection after renal transplantation in this meta-analysis. In contrast, the A-allele seemed to be related with protective effect toward acute rejection risk. For renal transplantation, the presence of the GG-genotype (OR=1.47, 95% CI:1.14-1.89, P=0.003) increased the risk of acute rejection, as shown in Figure 3 and Table 2. However, the AA-genotype did not seem to protect against the acute rejection associated with transplantations (OR=0.87, 95% CI:0.69-1.09, P=0.21). This meta-analysis found that the CTLA-4 +49A/G SNPs were not linked to an increased risk of acute rejection in African or Caucasian ethnicities, according to multilevel modelling of analyses (Table 2). However, the CTLA-4 +49A/G G-allele was related with renal transplantation rejection risk among Asian populations, as shown in Figure 4 (OR=1.55, 95% CI:1.16-2.06, P=0.003; Table 2), but not in the general population. The GG-genotype was also linked to an increased risk of acute rejection after the analysis, as shown in Figure 5 (OR=1.91, 95% CI:1.29-2.84, P=0.001) and Table 2.\n\nCI: confidence interval; P: P-value; I2: heterogeneity.\n\n* P<0.05.\n\nCI: confidence interval; P: P-value; I2: heterogeneity.\n\nCI: confidence interval; P: P-value; I2: heterogeneity.\n\nCI: confidence interval; P: P-value; I2: heterogeneity.\n\n\nDiscussion\n\nThis meta-analysis found a connection between the CTLA-4 +49A/G G-allele/GG-genotype and the increased prevalence of acute renal transplantation rejection, with more prominent emphasis of evolution influence exclusion in the genetic polymorphism study. Additionally, we tested for publication bias and found that the CTLA-4 +49A/G SNPs had no influence on an increased incidence of acute renal rejection in general populations. The association of CTLA-4 +49A/G SNPs and acute renal rejection risk was shown to be strong. After further investigation, we discovered no association between the CTLA-4 +49A/G SNPs and the incidence of the rejection in the African and Caucasian population. Caucasians and Africans were underrepresented in the included studies. Therefore, further research about the role of the polymorphism among different ethnicities is necessary to be done.\n\nIntriguingly, we discovered that the G-allele and GG-genotype were both linked to risk of renal transplantation rejection in Asians. It means that the G-allele and GG-genotype seemed to be a risk factor for acute rejection in Asian populations, according to this study. However, further research is needed to examine the link between the two variables. Our findings seemed to be quite stable in certain respects. Meta-analysis studied by Duan et al.22 found that the G-allele was related with a higher risk of acute rejection after renal transplantation, but not with the GG-genotype and the AA-genotype in the general population. However, a limitation of the previous paper was not classifying cases into ethnic subgroups, also the previous publication was not validated by the Hardy-Weinberg equilibrium that explains evolution theory influences that need to be excluded in order to make sure the SNPs occurred actually came from the patient’s case itself.\n\nAccording to Zhu et al.,23 the CTLA-4 +49A/G SNPs were not related with the incidence of renal transplant rejection in general populations. In a meta-analysis of nine studies, Gao et al.24 found that the G-allele and GG-genotype were related with acute renal rejection risks in Asian populations and in general populations. As a consequence of the increased number of studies included in our meta-analysis (13 included studies), our findings were more vigorously updated than those from the prior meta-analyses, also the use of HWE analysis provides more valid results in terms of polymorphism study. CTLA-4 +49A/G SNPs, particularly the G-allele/GG-genotype, were associated with acute renal rejection risk in Asian ethnicity and overall populations, according to our findings. Because of a wide range of issues including linguistic bias, a small sample size, poor statistical power and heterogeneity of recruited patients, as well as a variety of research designs and varied therapies, the findings should be taken with a grain of salt.\n\n\nConclusions\n\nTo summarize, the findings of the conducted meta-analysis indicate that the CTLA-4 +49A/G SNPs, particularly the G-allele/GG-genotype, were related with the acute rejection, increased risk in renal transplantation cases of Asian ethnicity and global populations. But in spite of that, further association research is necessary to better elucidate this.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nReporting guidelines\n\nFigshare: PRISMA checklist and flow diagram for ‘Cytotoxic T-lymphocyte associated-protein-4 +49A/G-allele (rs231775) Single Nucleotide Polymorphisms was corresponded with acute allograft renal transplantation rejection: a multilevel modelling of meta-analysis’. https://doi.org/10.6084/m9.figshare.20124215.25\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nDesai N, Rahman M: Nephrology update: end-stage renal disease and renal replacement therapy. FP Essent. 2016; 444: 23–29. PubMed Abstract\n\nArze Aimaretti L, Arze S: Preemptive renal transplantation-the best treatment option for terminal chronic renal failure. Transplant Proc. 2016; 48: 609–611. PubMed Abstract \| Publisher Full Text\n\nBuchbinder E, Hodi FS: Cytotoxic T lymphocyte antigen-4 and immune checkpoint blockade. J Clin Invest. 2015; 125: 3377–3383. PubMed Abstract \| Publisher Full Text\n\nKolacinska A, Cebula-Obrzut B, Pakula L, et al.: Immune checkpoints: cytotoxic T-lymphocyte antigen 4 and programmed cell death protein 1 in breast cancer surgery. Oncol Lett. 2015; 10: 1079–1086. PubMed Abstract \| Publisher Full Text\n\nMoher D, Liberati A, Tetzlaff J, et al.: Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009; 339: b2535. PubMed Abstract \| Publisher Full Text\n\nRodriguez S, Gaunt TR, Day IN: Hardy-Weinberg equilibrium testing of biological ascertainment for Mendelian randomization studies. Am J Epidemiol. 2009; 169(4): 505–514. PubMed Abstract \| Publisher Full Text\n\nDmitrienko S, Hoar DI, Balshaw R, et al.: Immune response gene polymorphisms in renal transplant recipients. Transplantation. 2005; 80: 1773–1782. Publisher Full Text\n\nWisniewski A, Kusztal M, Magott-Procelewska M, et al.: Possible association of cytotoxic T-lymphocyte antigen 4 gene promoter single nucleotide polymorphism with acute rejection of allogeneic renal transplant. Transplant Proc. 2006; 38: 56–58. PubMed Abstract \| Publisher Full Text\n\nGorgi Y, Sfar I, Abdallah TB, et al.: CTLA-4 exon 1 (+49) and promoter (-318) gene polymorphisms in renal transplantation. Transplant Proc. 2006; 38: 2303–2305. PubMed Abstract \| Publisher Full Text\n\nGendzekhadze K, Rivas-Vetencourt P, Montano RF: Risk of adverse post-transplant events after renal allograft transplantation as predicted by CTLA-4 + 49 and TNF-alpha -308 single nucleotide polymorphisms: a preliminary study. Transpl Immunol. 2006; 16: 194–199. PubMed Abstract \| Publisher Full Text\n\nHaimila K, Turpeinen H, Alakulppi NS, et al.: Association of genetic variation in inducible costimulator gene with outcome of renal transplantation. Transplantation. 2009; 87: 393–396. PubMed Abstract \| Publisher Full Text\n\nKrichen H, Sfar I, Jendoubi-Ayed S, et al.: Genetic polymorphisms of immunoregulatory proteins in acute renal allograft rejection. Transplant Proc. 2009; 41: 3305–3307. PubMed Abstract \| Publisher Full Text\n\nKusztal M, Koscielska-Kasprzak K, Drulis-Fajdasz D, et al.: The influence of CTLA-4 gene polymorphism on long-term renal allograft function in Caucasian recipients. Transpl Immunol. 2010; 23: 121–124. PubMed Abstract \| Publisher Full Text\n\nRuhi C, Sallakci N, Ersoy F, et al.: The relation between CTLA-4 single nucleotide polymorphisms and acute rejection in renal transplantation. NDT Plus. 2010; 3(Suppl 3): iii524–iii525.\n\nKim HJ, Jeong KH, Lee SH, et al.: Polymorphisms of the CTLA-4 gene and renal transplant rejection in Korean patients. Transpl Immunol. 2010; 24: 40–44. PubMed Abstract \| Publisher Full Text\n\nDomanski L, Bobrek-Lesiakowska K, Kloda K, et al.: The impact of rs231775 (+49AG) CTLA-4 gene polymorphism on transplanted renal function. Ann Transplant. 2012; 17: 29–35. PubMed Abstract \| Publisher Full Text\n\nGao JW, Guo YF, Fan Y, et al.: Polymorphisms in cytotoxic T lymphocyte associated antigen-4 influence the rate of acute rejection after renal transplantation in 167 Chinese recipients. Transpl Immunol. 2012; 26: 207–211. PubMed Abstract \| Publisher Full Text\n\nCanossi A, Aureli A, Delreno F, et al.: Influence of cytotoxic T-lymphocyte antigen-4 polymorphisms on acute rejection onset of cadaveric renal transplants. Transplant Proc. 2013; 45: 2645–2649. PubMed Abstract \| Publisher Full Text\n\nMisra MK, Kapoor R, Pandey SK, et al.: Association of CTLA-4 gene polymorphism with end-stage renal disease and renal allograft outcome. J Interferon Cytokine Res. 2014; 34: 148–161. PubMed Abstract \| Publisher Full Text\n\nRuhi C, Sallakci N, Yegin O, et al.: The influence of CTLA-4 single nucleotide polymorphisms on acute renal allograft rejection in Turkish patients. Clin Transplant. 2015; 29: 612–618. PubMed Abstract \| Publisher Full Text\n\nSlavcheva E, Albanis E, Jiao Q, et al.: Cytotoxic T-lymphocyte antigen 4 gene polymorphisms and susceptibility to acute allograft rejection1. Transplantation. 2001; 72(5): 935–940. PubMed Abstract \| Publisher Full Text\n\nDuan Z, Zhang Y, Pan F, et al.: Association between CTLA-4 gene polymorphisms and acute rejection of renal transplantation: a metaanalysis. J Nephrol. 2012; 25: 996–1002. PubMed Abstract \| Publisher Full Text\n\nZhu CL, Huang Q, Liu CH, et al.: Polymorphisms in the cytotoxic T-lymphocyte antigen 4 gene and acute rejection risk in transplant recipients. Mol Biol Rep. 2012; 39: 8701–8708. PubMed Abstract \| Publisher Full Text\n\nGao JW, Zhou ZH, Guo SC, et al.: A deeper understanding of the association between CTLA-4 + 49A/G and acute rejection in renal transplantation: an updated meta-analysis. Ren Fail. 2015; 37: 165–174. PubMed Abstract \| Publisher Full Text\n\nDaryanto B, Purnomo AF: Cytotoxic T-lymphocyte associated-protein-4 +49A/G-allele (rs231775) Single Nucleotide Polymorphisms was corresponded with acute allograft renal transplantation rejection: a multilevel modelling of meta-analysis. Figshare. [Dataset].2022." }	[ { "id": "146723", "date": "31 Aug 2022", "name": "Yuki Nakagawa", "expertise": [ "Reviewer Expertise kidney transplant sorgen", "ABO incompatible kidney transplantation" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a meta-analysis review of the association between cytotoxic T-lymphocyte antigen 4 +49A/G (CTLA-4 +49A/G) single nucleotide polymorphisms (SNPs) and the risk of kidney transplant rejection. It was systematically analyzed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, resulting in a more accurate survey. It is interesting to note that the Asian subanalysis and SNP associations show that the G/GG genotype was associated with the risk of rejection. However, 54% of his Asian SNPs were GG type, 39% GA type, and 7% AA type. On top of that, it is necessary to re-evaluate whether this result is effective.\nThe ratio of single nucleotide polymorphism events by race was posted in the background of the target cases.\n\nDepending on the number of subjects, the credibility of whether or not Asians can say the relationship between SNP GG type and rejection will come out.\n\nImpaired absorption and metabolism of immunosuppressants (FK) is often observed in SNP GG type. We would like you to discuss the relevance of immunosuppressive drugs in this meaningful data on rejection.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required.\n\nAre the conclusions drawn adequately supported by the results presented in the review? Partly", "responses": [ { "c_id": "9637", "date": "15 May 2023", "name": "Besut Daryanto", "role": "Author Response", "response": "Thank you for your input Prof. Absolutely, whether that 54% of this SNPs is effective should be interrogated further. However by this study, we could actually see there was an association related to that. In order to take the next step of validating the SNPs toward the functionality and phenotype of the patients even more in the next studies. This could be an interesting further research field in order to explore more of the reasons and flows. The relevance of immunosuppressive drugs in the context of patients with specific genotypes, such as those carrying GG genotype single nucleotide polymorphisms (SNPs), can be crucial in understanding the incidence of rejection in kidney transplantation. Genetic variations, such as SNPs, can affect how individuals metabolize or respond to certain medications, including immunosuppressive drugs. For example, the CYP3A5 gene, which is responsible for the production of the CYP3A5 enzyme, plays an important role in the metabolism of calcineurin inhibitors like tacrolimus, a commonly used immunosuppressive drug in kidney transplantation. There is a well-known SNP in this gene, CYP3A5*3 (rs776746), where the non-expresser allele (G) results in reduced enzyme activity. Individuals with the GG genotype exhibit lower enzyme activity, leading to higher blood levels of tacrolimus at a given dose compared to those with other genotypes (e.g., AG or AA). As a result, GG individuals may require lower doses of tacrolimus to achieve the same therapeutic effect and avoid toxic side effects. The relevance of genotyping for SNPs, like the one mentioned above, lies in its potential to personalize immunosuppressive therapy. By identifying patients with specific genotypes that influence drug metabolism or response, clinicians can tailor dosing regimens and therapeutic strategies to minimize the risk of rejection and adverse side effects. This approach is known as pharmacogenomics and can significantly improve the outcomes of kidney transplantation. In summary, the relevance of immunosuppressive drugs in the context of patients with GG genotype SNPs is to understand how these genetic variations can impact drug metabolism or response. By identifying such variations, personalized immunosuppressive therapy can be designed to minimize the risk of rejection and optimize transplant outcomes. As this would be beneficial and applied in this study reviewed." } ] }, { "id": "146722", "date": "22 Feb 2023", "name": "Nurul Cholifah Lutfiana", "expertise": [ "Reviewer Expertise Medicine" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe strength of this paper is the meta-analysis in terms of effect estimates. This paper revealed the association not only of the overall population but also based on ethnicity, therefore although it seems to give significance to overall population, the interesting part is that only Asian sub-group has significant association, not for Caucasian and African. This meta-analysis was thoroughly and systematically reviewed using the PRISMA Guideline. The research question builds a good sense of the issue, on how the inconsistency of each findings, especially in SNPs study in renal transplantation, still have a hazy conclusion. Therefore the gap of inconsistency in the literature was well overcome by the explanation of further analysis using multilevel modelling.\nThe search strategy was comprehensive by searching the published prints from trusted resources for the field. The authors highlight the keywords they used in the study, and all the processes were well described and illustrated in a PRISMA flow diagram. The results are well presented, because they are summarized in tables, and illustrated in forest plots as it is the basic necessity for meta-analysis. The authors described how they discovered that the G-allele and GG-genotype were both linked to risk of renal transplantation rejection in Asians. They also highlight the prior report lacked a classification of patients into ethnic categories. In addition, the previous article was not evaluated by the Hardy-Weinberg equilibrium, which describes evolution theory factors that must be ruled out to ensure that the SNPs observed originated from the patient's instance\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? Yes\n\nAre the conclusions drawn adequately supported by the results presented in the review? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-904
https://f1000research.com/articles/11-901/v1	04 Aug 22	{ "type": "Research Article", "title": "Next-generation sequencing (NGS) reveals low-abundance HIV-1 drug resistance mutations among patients experiencing virological failure at the time of therapy switching in Uganda", "authors": [ "Maria Magdalene Namaganda", "Hakim Sendagire", "David Patrick Kateete", "Edgar Kigozi", "Moses Luutu Nsubuga", "Fred Ashaba Katabazi", "Jupiter Marina Kabahita", "Fredrick Elishama Kakembo", "Stephen Kanyerezi", "Barbara Castelnuovo", "Andrew Kambugu", "Isaac Ssewanyana", "Chris Okirya", "Susan Nabadda", "Moses Joloba", "Gerald Mboowa", "Maria Magdalene Namaganda", "David Patrick Kateete", "Edgar Kigozi", "Moses Luutu Nsubuga", "Fred Ashaba Katabazi", "Jupiter Marina Kabahita", "Fredrick Elishama Kakembo", "Stephen Kanyerezi", "Barbara Castelnuovo", "Andrew Kambugu", "Isaac Ssewanyana", "Chris Okirya", "Susan Nabadda", "Moses Joloba" ], "abstract": "Background: The emergence and spread of antiretroviral drug resistant HIV-1 variants is one of the major factors associated with therapeutic failure in persons living with HIV (PLWH) as it jeopardizes the efforts to reduce the progression to AIDS. Whereas Sanger sequencing is the most appropriate conventional method for HIV drug resistance testing, it has limited capacity to detect low-abundance variants. This study assessed the suitability of next generation sequencing (NGS) to reveal low-abundance HIV-1 drug resistance mutations amongst patients experiencing virological failure at the time of therapy switching in Uganda. Methods: Archived blood samples previously collected from 60 PLWH were used in this study. Briefly HIV viral RNA was extracted and performed targeted NGS of portions of both the HIV protease and reverse transcriptase genes on the illumina MiSeq. For performance comparison, Sanger sequencing was also performed for all the samples targeting the highlighted genes. The sequence data generated was analyzed using HyDRA bioinformatics pipeline, accompanied by the Stanford HIV drug resistance database, to annotate and report drug resistance mutations/variants. Results: Out of the 60 samples, 58 passed preliminary quality control and were considered for subsequent analysis—of which 38/58 (65.5%) registered low-abundance HIV drug resistance variants. Overall, 757 variants from the NGS data and 90 variants from the Sanger data were identified. The most prevalent minority variants included; K65R (65.5%), K14R (63.8%), K45R (63.8%), L63P (63.8%), I15V (63.8%), K70R (60.3%), V77I (60.3%), L283I (60.3%), G16E (58.6%) and L282C (58.6%). Conclusion: An estimated 65.5% of the sampled population harbors low-abundance HIV-1 variants, most of which are associated with virological failure, and consequently antiviral drug resistance. NGS suitably detects drug resistance mutations even at frequencies below 20% of the viral quasi species that are occasionally missed by Sanger sequencing.", "keywords": [ "HIV", "Drug resistance testing", "Low-abundance (minority) variants", "Sanger sequencing", "Next-generation sequencing", "Sanger sequencing" ], "content": "Introduction\n\nThe widespread emergence and transmission of HIV drug resistance (HIV-DR) may jeopardize the success of the currently recommended first-line antiretroviral therapy (ART) regimens in sub-Saharan Africa (SSA) (Phillips et al., 2017). The initial ART regimen generally consists a combination of two nucleoside reverse transcriptase inhibitors (NRTIs) usually lamivudine/abacavir (3TC/ABC) or tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) plus a drug from one of the three classes: a non-nucleoside reverse transcriptase inhibitor (NNRTI); usually efavirenz (EFV) or nevirapine (NVP), an integrase strand transfer inhibitor (INSTI) or a protease inhibitor (PI) (De Clercq, 2013). Additional data has shown to support the use of Dolutegravir/lamivudine (DTG/3TC) for initial treatment of some people with HIV (Cahn et al., 2020).\n\nRecently, there has been reported existence of HIV drug resistance to both classes of first line drugs mentioned above, with reported genotypic variations. Predominantly, the prevalence of pre-treatment NNRTI resistance has been eye-catching in African populations, with notable ranges of 8% in Cameroon, and close to 15% in Uganda (de Waal et al., 2018). In 2018, the WHO recommended use of DTG in first line ART as there was increasing prevalence of pre-treatment drug resistance to most NNRTIs, especially in sub-Saharan Africa (Siedner et al., 2020). This was supported by international data documenting the presence of low-abundance variants, in addition to the known variants, among people on antiretroviral drugs. However, the policy stated that the urgency of the transition would largely depend on the country-specific prevalence of NNRTI resistance (Phillips et al., 2018a). The policy was not based on locally available data and as such calls for validation, particularly in our Uganda population—given that such in depth analyses can avail a baseline guidance on whether a patient living with HIV has a mutated form of the virus that does respond to ART or not (Clutter et al., 2016).\n\nSeveral mechanisms including phenotypic and genotypic methods have been employed to offer options for HIV drug susceptibility testing. These methods include conventional HIV-1 genotyping techniques as well as Next generation sequencing approaches, that may as well be used to elaborate predominant viral quasispecies in the population (Smyth et al., 2012). The conventional HIV-1 genotyping assays, including Sanger sequencing, have to date been employed as the gold standard for HIV-DR testing although limited to only detecting HIV-1 variants present at frequencies above approximately 20% of the viral quasispecies. Such limitations lead to the collective failure of such approaches to exclusively detect low-levels of HIV-1 variants (with frequencies lower than 20% of viral quasispecies)—even when the viral species harbor HIV-DR mutations (Lee et al., 2020). Low-abundance variants, also known as minority variants, are usually present in small proportions of the virus populations, and have been reported to have a significant association with increased virological failure for first-line nucleoside reverse transcriptase inhibitors (NRTI) and NNRTI based regimens (Mbunkah et al., 2020). This type of drug resistance has been proven to be selected under the appropriate pressure of ART onto the virions during the course of treatment. And with the advent of deep (next-generation) sequencing, unlike the conventional methods, it is very possible to detect drug resistant HIV-1 variants at low frequencies, below 20% of the viral population (Simen et al., 2009). This study therefore aimed at utilizing NGS deep sequencing and correspondent bioinformatics pipelines to detect low-abundance drug resistance HIV-1 variants amongst patients on first line regimen combinations, with reported virological failure in Uganda, at the time of therapy switching.\n\n\nMethods\n\nThis was a retrospective quantitative cross-sectional study that analyzed 60 archived blood samples received at the National Health Laboratory and Diagnostic Services (NHLDS), a department of the Ugandan Ministry of Health (MoH), between June 2020 and October 2020. These samples had been collected from PLWH on first line ART in Uganda that were found to have virological failure defined as non-suppressed repeat (2nd) viral load of ≥1,000 copies/ml, performed consecutively within at least three months of each other, following enhanced adherence support of up to three months. The patients were on combinations; TDF+3TC+EFV, TDF+3TC+DTG, AZT+3TC+EFV, ABC+3TC+EFV AZT+3TC+NVP, ABC+3TC+DTG and ABC+3TC+LPV/r among children as reported.\n\nApprovals to use archived samples were sought from NHLDS, Department of Immunology and Molecular Biology, NHLDS-Research and Ethics Committee (REC), Makerere University School of Biomedical Sciences Research and Ethics Committee (SBSREC, Reference SBS-2021-56), as well as the Uganda National Council of Science and Technology (UNCST, Reference HS743ES).\n\nSamples were obtained from NHLDS, a reference laboratory for HIV viral load testing in Uganda and transported to the Genomics and Molecular Biology Laboratory at the Department of Immunology and Molecular Biology, Makerere University College of Health Sciences.\n\nTotal viral RNA was extracted from 60 archived samples using the QIAmp viral RNA extraction kit according to the manufacturer’s protocol (Qiagen, USA). Total viral RNA extracted was used as template in reverse transcription PCR to obtain cDNA using SuperScript III Reverse transcriptase double stranded cDNA synthesis kit following the manufacturer’s instructions (Thermo Fisher, USA). PCR targeting a contiguous region of the HIV-1 pol gene of interest in routine HIVDR, the protease gene (codon 1-99) and amino terminus of reverse transcriptase codon (1-320) was performed. For quality control, the subsequent amplicons were analyzed by gel electrophoresis through 1.5% (w/v) agarose gels. Gels were stained with ethidium bromide and bands visualized under UV; lanes of 1 kbp DNA ladder marker (New England Biolabs, UK).\n\nGenomic libraries were prepared using the Illumina Nextera XT library preparation kit following manufacturer’s instruction (Illumina, San Diego, USA). Quality of the prepared libraries was assessed with the Agilent Tape Station system using the D1000 High sensitivity ScreenTape assay and reagents (Agilent Technologies, USA). Libraries were sequenced using the Illumina MiSeq V3 cartridge following the manufacturer’s protocol (Illumina, San Diego, USA) at Genomics and Molecular Biology Laboratory at Makerere University College of Health Sciences.\n\nTo validate NGS data, sanger sequencing, a gold standard for HIV drug resistance testing was performed on the same samples. Briefly, PCR was performed targeting the reverse transcriptase and protease genes to generate Amplicons of 1200bp for each sample. The amplicons were then purified using the ExoSAP-ITTM kit and sequenced using the Big dye terminator v3.1 cycle sequencing kit according to the manufacturer’s protocol (Applied Biosystems, USA). Targeted sequencing for the HIV selected regions was run using the Applied Biosystems (ABI) SeqStudio Genetic Analyzer machine at the Genomics and Molecular Biology Laboratory, Dept. of Immunology & Molecular Biology, Makerere University College of Health Sciences.\n\nRaw sequence data in FASTQ file format were assessed for quality using FASTQC and MULTIQC software tools (Andrews, 2017/2022) that produced reports in html format about the quality of the sequences. Low-quality bases, very short reads and any adapter sequences were therefore trimmed off and removed using Trim galore tool (Babraham Bioinformatics, 2019). Using the HyDRA pipeline, an annotated reference-based bioinformatics pipeline, the generated NGS data was analyzed to determine the genotypes of HIV-1 drug resistance mutations. The annotated HXB2 sequence was used for reference mapping by Bowtie2, and stringent data quality assurance and variant calling to identify HIVDR associated mutations based on the World Health Organization (WHO) list for surveillance of transmitted HIVDR. All HIVDR mutations found in the pol gene; protease (PR), reverse transcriptase (RT), were reported according to classifications outlined in the Stanford surveillance drug resistance mutation list (WHO, 2020).\n\nAfter performing all the quality checks, good quality reads were considered for the downstream analyses. Calling of the low abundance HIV-1 variants and annotation was performed using the HyDRA pipeline in the command-line to detect HIVDR mutations. The FASTQ files were analyzed to release files in aavf format, an output of HyDRA pipeline from Quasitools. The aavf report provides a compact summary of the amino acid variation obtained by conceptual translation of the NGS read pileup across the examined region of the HIV genome. It also contains information on the frequencies of matching codons (wild type or mutant), quality of the variant calling as well as the coverage of relevant loci and it is based on the variant call format (vcf) standard that has been universally adopted for recording nucleotide variants. The main output of HyDRA was a drug resistance report which used the Stanford HIVDB mutations when reporting. All HIV DR mutations found at a frequency above 1%, a default setting under minimum AA frequency were listed in the report. A summary report of HIVDR mutations identified in each sample was downloaded in the form of a CSV file and viewed in Excel.\n\nOutput data from Sanger sequencing in. ab1 file format was transformed using a custom script into fasta files that were also queried against the Stanford HIV drug resistance database for identification of major drug resistance mutations for each antiretroviral drug. This unveiled the drug resistant variants from the Sanger sequence data. For comparison, custom bash scripts were written to sort drug resistant mutations from both the Sanger dataset and NGS dataset. Thereafter, unique and common mutations were extracted from both datasets. The main objective of the comparison was to identify mutations of clinical significance that were missed by Sanger sequencing but captured by NGS.\n\n\nResults\n\nA total of 58 samples passed preliminary quality control, and were successfully analyzed in this study. Among the participants, 43 (74.1%) were females and 15 (25.9%) were males with an average age of 32 years. These patients had all been on first line regimens for a period of at least 6 months where 37 (63.8%) of them were on TDF-3TC-EFV. Other ART combinations were TDF-3TC-DTG (10.3%), ABC-3TC-DTG (1.7%), AZT-3TC-NVP (12.1%), AZT-3TC-EFV (1.7%), ABC-3TC-EFV (3.4%) and ABC-3TC-LPV/r (6.9%) as summarized in Figure 1.\n\nSequence data was obtained from the two genes targeted in the routine monitoring of HIV drug resistance testing, namely the reverse transcriptase (RT) and protease (PR) genes. Sequence data of these genes provided information on three classes of drugs namely, NRTI, NNRTI and PI class. Overall, a total of 782 variants were identified; 757 variants from the NGS data, 90 variants from the Sanger sequencing data whereas 65/782 (8.3%) of the variants were shared between NGS and Sanger datasets. Additionally, it was observed that Sanger Sequencing was able to detect 25 variants that were not identified by NGS, whereas NGS data revealed 692 variants that were not detected by Sanger sequencing. See Table 1 below.\n\nFrom the NGS datasets, all variants detected at a frequencies of 20% and above within the viral quasispecies were categorized as majority, whereas all those detected at a frequency less than 20% but greater than or equal to 1% of the viral quasispecies are categorized as minority variants (Silver et al., 2018); therefore from the current study, 563/757 (74.4%) of the NGS identified variants were categorized as minority variants. The 563 minority variants were distributed variably with some mutations appearing more frequently than others. Such variants appeared in 65.5% (38/58) of the sampled population—some of which variants included HIV-DR mutations. Overall, the most prevalent minority variants present in the analyzed samples included; K65R in 38/58 (65.5%), K14R in 37/58 (63.79%), K45R in 37/58 (63.79%), L63P in 37/58 (63.79%), and I64V in 37/58 (63.79%). Additionally, I15V was identified in 60.3% (35/58), K70R in 60.3% (35/58), V77I in 60.3% (35/58), and L283I in 60.3% (35/58), G16E in 60.3% (35/58). Some of the least prevalent minority mutations found in only one (0.02%) of the analyzed samples are A71V, C67W, D25G, D30N, E21D, G16W, G27E, H69L, I15M, I50F and I64L. Others are listed in the supporting file HDR-Supp.zip.\n\nIt was also observed and important to note that a mutation categorized as a minority variant in one sample can be also identified as a more frequent variant in another sample. There was purposive selection of 15 most prevalent mutations from the analyzed samples and their positions in the corresponding genes were also highlighted in Table 2.\n\n* Denotes the most prevalent low-abundance drug resistance variant located at position 65 of the pol gene. Other high frequency low-abundance drug resistance variants are also summarized in the Table 2 above.\n\nAll variants are summarized in the supporting files HDR-Supp.zip.\n\nThis study also identified some minority variants of clinical importance that were highly prevalent in the analyzed samples but were missed by Sanger sequencing. Figure 2 shows some unusual mutations that have not been reported previously as well as the presence of drug resistance mutation. These included; K14R, K45R, L63P, I64V, I15V, L83I, V77I. Other than the drug resistant mutations, there were also several unusual mutations whose clinical significance is still unknown and they could be nominated for diagnostic targets, drug resistance targets, drug targets and so on.\n\nThe histograms highlighted in grey indicate usual (previously reported) mutations and whereas the ones highlighted in red indicate unusual (not reported before) mutations. A blue dot above the histograms indicates presence of a drug resistance mutation.\n\n\nDiscussion\n\nAffordable, sensitive, and scalable technologies are needed for monitoring antiretroviral treatment (ART) success with the goal of eradicating HIV-1 infection in low resource settings. For instance, in recent years, conventional HIV-1 genotyping assays, including Sanger sequencing have been the standard approaches for HIV- DR testing in sub-Saharan Africa (Manyana et al., 2021). Being the gold standard, Sanger sequencing is still able to detect HIV-DR mutations of clinical relevance as well as drug resistance, even though it is mainly limited by relatively high sequencing costs and low-throughput, henceforth evidently failing to detect the low-levels of HIV-1 variants—with reported frequencies lower than 20% of viral quasispecies—which scenario may well harbor HIV-DR mutations as reported (Lee et al., 2020). These low-abundance variants, also known as minority variants, usually present as minority members of the virus populations, and thus cannot be easily detected. With such challenges of inadequate/inaccurate detection, some studies recommend the usage of high throughput sequencing technologies (Slatko et al., 2018; Manyana et al., 2021). This study therefore aimed at utilizing NGS deep sequencing approaches, and correspondent bioinformatics pipelines, to detect low-abundance drug resistance HIV-1 variants amongst patients on first line regimen combinations, with reported virological failure in Uganda, at the time of therapy switching. The study population included patients on first-line regimen with virological failure where most participants (58.6%) were on TDF, 3TC, and EFV combination; that is, two NRTIs and one NNRTI. This regimen was common for HIV treatment in many countries as reported (Gregson et al., 2016). Sequence data was obtained from the two genes targeted in the routine monitoring of HIV drug resistance testing, namely the reverse transcriptase (RT) and protease (PR) genes. These genes provide information on three classes of drugs; NRTI, NNRTI and PI class. Overall, 782 variants were identified; 757 variants from the NGS data, 90 variants from the Sanger sequencing data whereas 65/782 (8.3%) of the variants were shared between NGS and Sanger datasets. The study further observed that Sanger Sequencing was able to detect 25 variants that were not identified by NGS, whereas NGS revealed 692 variants that were not detected by Sanger sequencing. This elaborates that NGS being a deep sequencing high-throughput detects more variants compared to Sanger sequencing as observed by previous studies (Taylor et al., 2019; Schenkel et al., 2016). The current study further reports 563 (74.4%) minority variants observed within the 757 total variants identified by NGS. This elaborates that NGS is able to detect approximately 74.4% of the minority variants present above a cutoff of 1% of the viral quasispecies. The 563 minority variants were dispersed unproportionally, with some mutations appearing more frequent than others. Such variants were observed in 65.5% (38/58) of the sampled population amongst the study participants—some of which variants included HIV-DR mutations. Several reports have elucidated the presentation of similar minority variants in different populations as reported (Nicot et al., 2012; Capobianchi et al., 2013; Wensing et al., 2019). The current study also highlights the most prevalent minority variants, which included; K65R in 38/58 (65.5%), K14R in 37/58 (63.79%), K45R in 37/58 (63.79%), L63P in 37/58 (63.79%), and I64V in 37/58 (63.79%). The mutation K65R, that also presents the highest prevalence in the current study, is one of the low-abundance drug resistance mutations conferring resistance to at least one class of drugs—and within the NRTI class. However in other studies, this mutation has been categorized as a relatively rare drug resistance conferring variant that causes loss of drug susceptibility of HIV-1 to most NRTIs (tenofovir, didanosine, abacavir and stavudine), with exception to zidovudine (Brenner & Coutsinos, 2009). And essentially, even though there are limited studies that have focused on understanding the incidences of minority variants more so in sub-Saharan Africa, the outstanding prevalence of K65R perfectly relates to findings in a few researches conducted in different geographical regions in HIV high burdened areas. In Israel, there was a reported high incidence of K65R is the analyzed population (Turner et al., 2009); in West Africa, particularly Togo, there was evidence of a high prevalence of K65R (Dagnra et al., 2011); whereas within the Resistance Monitoring study, a multicenter prospective observational cohort of HIV-1-infected adults who received ART in routine circumstances at 13 clinical sites in Kenya, Nigeria, South Africa, Uganda, Zambia, and Zimbabwe—also reported a significant incidence of K65R amongst samples collected from participants (Sigaloff et al., 2011). Other studies conducted in Southern Africa have elucidated significant occurrences of K65R as a key variant amongst HIV-1 positive individuals experiencing virological failure (Skhosana, 2015; Etta et al., 2017). Accordingly, in the current study, it should be noted that K65R remains the most important and significant variant identified. The results from the study findings also elaborate that there is observed co-existence of mutations amongst the analyzed samples, which findings strongly compare with other research that observed co-existence of variants, most notably K65R with S68G. The alteration S68G, has been reported to partially restore the replication defect associated with K65R as reported (Parikh et al., 2006). Additionally, the variants K14R and K70R were observed to be housed, each at a frequency of 60.3% of all the samples analyzed. The variant K14R is a single nucleotide variant that has been reported to confer no resistance to the most important ART drugs (Descamps et al., 2009), whereas K70R has been categorized as a classical Thymidine Analog mutation (TAM) known to cause intermediate-level resistance to AZT, and possibly low-level resistance to d4T and TDF (Quintana & José, 2013; Hachem et al., 2020). The current study also observed several nonpolymorphic mutations from the analyzed data as categorized by the HIV Stanford database. Such variants include; P225H, G190A, M46I, M46L, K70Q, K70N, K70S, K70T, K101E, and L100I—that are categorically believed not to occur in absence of therapy, contrary to the polymorphic mutations that occur frequently in viruses not exposed to selective drug pressure (Shafer & Schapiro, 2008; WHO, 2020). It should also be noted that the mutation P225H is an EFV-selected variant that occasionally occurs in combination with K103N. This results in synergistic reduction of susceptibility to NVP, EFV and DOR (Kouamou et al., 2021). As well, another reported mutation G190A has been associated with high-level resistance to NVP and intermediate resistance to EFV (Yang et al., 2015), whereas K101E is a primary accessory mutation that causes intermediate resistance to NVP and RVP, low-level resistance to EFV, and potentially low-level resistance to ETR as reported (Wu et al., 2015). The mutations M46I and M46L are relatively non-polymorphic Protease inhibitor-selected mutations, associated with reduced susceptibility to PIs with an exception of DRV, as reported (Watera et al., 2021). The mutations K70E and K70G are known to cause low-level resistance to TDF, ABC, 3TC and FTC, and also increase susceptibility to AZT (Siller et al., 2021). Other identified mutations included K70Q, K70N, K70S and K70T, that are rare non-polymorphic NRTI-selected mutations relating to resistance profiles of K70E and K70G described herein above. Earlier studies elaborated that the mutation L100I usually occurred in combination with K103N even though there is evidence that such variants may cause high level resistance to NVP and EFV (Soriano & de Mendoza, 2002). Other than the drug resistant conferring variants, there were also several unusual mutations whose clinical significance is still unknown and they could be nominated and validated as potential diagnostic targets, drug resistance targets, and so on. For instance, the present study has also unveiled a number of minority variants of clinical importance that were highly prevalent in the analyzed samples. These included; K14R, K45R, L63P, I64V, I15V, L83I, V77I among others as summarized in the supporting files HDR-Supp.zip.\n\n\nConclusion\n\nNext Generation Sequencing approaches can confidently reveal low-abundance drug resistance variants (minority variants) in populations of HIV-1 resistant individuals that have been reported to have virological failure. NGS, due to its high throughput data is able to detect low abundance variants as low as 1% of the viral quasispecies. This has been a limitation of the conventional Sanger sequencing that is currently considered the gold standard for HIV-DR testing. It is therefore vital that patients experiencing virological failure are tested using NGS as Sanger misses most of the low abundance variants that are of clinical significance. The frequency of drug resistance varies among individuals suggesting that discrete viral populations have different levels of genetic diversity. An estimated 65.5% of the sampled population harbored low-abundance HIV-1 variants, most of which are associated with virological failure, and consequently antiviral drug resistance.\n\nThe current Ministry of Health consolidated guidelines for prevention and treatment of HIV in Uganda recommended transition to use of DTG-based regimens as first line ART regimen; a combination of two NRTIs plus Dolutegravir (TDF+3TC+DTG) following concern over increasing prevalence of NNRTI resistance in people on ART in low-income and middle-income countries (MoH, 2018). According to a study on cost-effectiveness of public health options in presence of pre-treatment NNRTI drug resistance in sub-Saharan Africa, the urgency of transition would depend largely on the country specific prevalence of NNRTI resistance (Phillips et al., 2018b). During sample collection for the current study in 2020, 37/58 (63.8%) of the participants were still on TDF+3TC+EFV.\n\n\nData availability\n\nZenodo. Next generation sequencing reveals low-abundance HIV-1 drug resistance mutations among patients experiencing virological failure at the time of therapy switching in Uganda, DOI: https://doi.org/10.5281/zenodo.6326916 (Namaganda et al., 2022).\n\nThis project contains the following underlying data:\n\n- Zenodo. Raw reads and assembly files https://doi.org/10.5281/zenodo.6326915\n\n- Zenodo. Analysis files DOI https://doi.org/10.5281/zenodo.6619076\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nAuthor contributions\n\nConceptualization: Maria Magdalene Namaganda, Hakim Sendagire, Gerald Mboowa, Edgar Kigozi, Barbara Castelnuovo, David Patrick Kateete, Moses L Joloba.\n\nFunding Acquisition: Gerald Mboowa, Maria Magdalene Namaganda.\n\nSample Acquisition: Hakim Sendagire, Susan Nabadda, Isaac Ssewanyana, Chris Okirya.\n\nRNA Extraction: Maria Namaganda, Moses Luutu Nsubuga, Ashaba Fred.\n\nLibrary preparation and Sequencing: Maria Namaganda, Moses Luutu Nsubuga, Ashaba Fred, Edgar Kigozi.\n\nBioiformatics Analysis: Maria Magdalene Namaganda, Gerald Mboowa, Stephen kanyerezi, Fredrick Elishama Kakembo, Jupiter Marina Kabahita.\n\nManuscript writing: All authors have given final approval of the version to be published.", "appendix": "Acknowledgments\n\nThe Samples were collected and received from Uganda National Health Laboratory and Diagnostic Services Department of the Uganda Ministry of Health under a grant to Hakim Sendagire, from the World Bank supported East African Public Health Laboratory Networking Project (EAPHLNP).\n\nA special thanks to the Nurturing Genomics and Bioinformatics Research Capacity in Africa (BRECA grant number #1U2RTW010672) for the Bioinformatics training provided to many of the authors on this publication.\n\nResearch reported in this publication was supported by the Fogarty International Center of the National Institutes of Health under Award Number D43TW009771. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.”\n\nWe thank HEPI-SHSSU and MAPRONANO-ACE for the additional funding towards this study.\n\n\nReferences\n\nAgilent Technologies: TapeStation Automated Electrophoresis for DNA & RNA Quality Control\|Agilent. 2013.Reference Source\n\nAndrews S: FastQC. 2022. (Original work published 2017).Reference Source\n\nApplied BiosystemsTM : BigDyeTM Terminator v3.1 Cycle Sequencing Kit. n.d. Retrieved February 18, 2022.Reference Source\n\nBabraham Bioinformatics: Babraham Bioinformatics—Trim Galore!. 2019.Reference Source\n\nBrenner BG, Coutsinos D: The K65R mutation in HIV-1 reverse transcriptase: Genetic barriers, resistance profile and clinical implications. HIV Ther. 2009; 3(6): 583–594. PubMed Abstract \| Publisher Full Text\n\nCahn P, Madero JS, Arribas JR, et al.: Durable Efficacy of Dolutegravir Plus Lamivudine in Antiretroviral Treatment-Naive Adults With HIV-1 Infection: 96-Week Results From the GEMINI-1 and GEMINI-2 Randomized Clinical Trials. J. Acquir. Immune Defic. Syndr. 2020; 83(3): 310–318. PubMed Abstract \| Publisher Full Text\n\nCapobianchi MR, Giombini E, Rozera G: Next-generation sequencing technology in clinical virology. Clin. Microbiol. Infect. 2013; 19(1): 15–22. Publisher Full Text\n\nClutter DS, Jordan MR, Bertagnolio S, et al.: HIV-1 drug resistance and resistance testing. Infect. Genet. Evol. 2016; 46: 292–307. PubMed Abstract \| Publisher Full Text\n\nDagnra AY, Vidal N, Mensah A, et al.: High prevalence of HIV-1 drug resistance among patients on first-line antiretroviral treatment in Lomé, Togo. J. Int. AIDS Soc. 2011; 14(1): 30–30. PubMed Abstract \| Publisher Full Text\n\nDe Clercq E:Chapter Nine—The Nucleoside Reverse Transcriptase Inhibitors, Nonnucleoside Reverse Transcriptase Inhibitors, and Protease Inhibitors in the Treatment of HIV Infections (AIDS).De Clercq E , editor. Advances in Pharmacology. Academic Press;2013; Vol. 67: pp. 317–358. Publisher Full Text\n\nde Waal R , Lessells R, Hauser A, et al.: HIV drug resistance in sub-Saharan Africa: Public health questions and the potential role of real-world data and mathematical modelling. J. Virus Erad. 2018; 4: 55–58. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDescamps D, Lambert-Niclot S, Marcelin A-G, et al.: Mutations associated with virological response to darunavir/ritonavir in HIV-1-infected protease inhibitor-experienced patients. J. Antimicrob. Chemother. 2009; 63(3): 585–592. PubMed Abstract \| Publisher Full Text\n\nEtta EM, Mavhandu L, Manhaeve C, et al.: High level of HIV-1 drug resistance mutations in patients with unsuppressed viral loads in rural northern South Africa. AIDS Res. Ther. 2017; 14(1): 36. PubMed Abstract \| Publisher Full Text\n\nGregson J, Tang M, Ndembi N, et al.: Global epidemiology of drug resistance after failure of WHO recommended first-line regimens for adult HIV-1 infection: A multicentre retrospective cohort study. Lancet Infect. Dis. 2016; 16(5): 565–575. PubMed Abstract \| Publisher Full Text\n\nHachem AA, Hariri EH, Mansour A, et al.: Human Immunodeficiency Virus type 1 Drug Resistance Mutations in Patients Failing Antiretroviral Therapy in Lebanon from 2009 to 2013. Int. J. Clin. Res. 2020; 1(1): 113–123. Publisher Full Text\n\nIllumina: Nextera XT DNA Library Prep Kit\|Sequence small genomes, plasmids, cDNA. 2019. Reference Source\n\nKouamou V, Ndhlovu CE, Katzenstein D, et al.: Rapid HIV-1 drug resistance testing in a resource limited setting: The Pan Degenerate Amplification and Adaptation assay (PANDAA). Pan Afr. Med. J. 2021; 40: 57. PubMed Abstract \| Publisher Full Text\n\nLee ER, Parkin N, Jennings C, et al.: Performance comparison of next generation sequencing analysis pipelines for HIV-1 drug resistance testing. Sci. Rep. 2020; 10(1): 1634. PubMed Abstract \| Publisher Full Text\n\nLi S, Ouyang J, Zhao B, et al.: The S68G polymorphism is a compensatory mutation associated with the drug resistance mutation K65R in CRF01_AE strains. BMC Infect. Dis. 2020; 20(1): 123. PubMed Abstract \| Publisher Full Text\n\nManyana S, Gounder L, Pillay M, et al.: HIV-1 Drug Resistance Genotyping in Resource Limited Settings: Current and Future Perspectives in Sequencing Technologies. Viruses. 2021; 13(6): 1125. PubMed Abstract \| Publisher Full Text\n\nMbunkah HA, Bertagnolio S, Hamers RL, et al.: Low-Abundance Drug-Resistant HIV-1 Variants in Antiretroviral Drug-Naive Individuals: A Systematic Review of Detection Methods, Prevalence, and Clinical Impact. J. Infect. Dis. 2020; 221(10): 1584–1597. PubMed Abstract \| Publisher Full Text\n\nMoH: Consolidated Guidelines for Prevention and Treatment of HIV in Uganda\|Ministry of Health Knowledge Management Portal. 2018.Reference Source\n\nNamaganda MM, Sendagire H, Mboowa G, et al.: Impact of next-generation sequencing (NGS) on HIV-1 drug resistance testing among patients experiencing virological failure at the time of therapy switching in Uganda.2022. Publisher Full Text\n\nNew England Biolabs (UK) Ltd—/:n.d. Retrieved April 16, 2022.Reference Source\n\nNicot F, Saliou A, Raymond S, et al.: Minority variants associated with resistance to HIV-1 nonnucleoside reverse transcriptase inhibitors during primary infection. J. Clin. Virol. 2012; 55(2): 107–113. PubMed Abstract \| Publisher Full Text\n\nPhillips AN, Cambiano V, Nakagawa F, et al.: Cost-effectiveness of public-health policy options in the presence of pretreatment NNRTI drug resistance in sub-Saharan Africa: A modelling study. Lancet HIV. 2018a; 5(3): e146–e154. PubMed Abstract \| Publisher Full Text\n\nPhillips AN, Cambiano V, Nakagawa F, et al.: Cost-effectiveness of public-health policy options in the presence of pretreatment NNRTI drug resistance in sub-Saharan Africa: A modelling study. Lancet HIV. 2018b; 5(3): e146–e154. PubMed Abstract \| Publisher Full Text\n\nPhillips AN, Stover J, Cambiano V, et al.: Impact of HIV Drug Resistance on HIV/AIDS-Associated Mortality, New Infections, and Antiretroviral Therapy Program Costs in Sub–Saharan Africa. J. Infect. Dis. 2017; 215(9): 1362–1365. PubMed Abstract \| Publisher Full Text\n\nQiagen Q: QIAamp Viral RNA Kits. 2013.Reference Source\n\nQuintana B, José G: Mechanistic insights into the role of secondary mutations of HIV-1 reverse transcriptase in the acquisition of antiretroviral drug resistance. 2013.Reference Source\n\nSchenkel LC, Kerkhof J, Stuart A, et al.: Clinical Next-Generation Sequencing Pipeline Outperforms a Combined Approach Using Sanger Sequencing and Multiplex Ligation-Dependent Probe Amplification in Targeted Gene Panel Analysis. J. Mol. Diagn. 2016; 18(5): 657–667. Publisher Full Text\n\nShafer RW, Schapiro JM: HIV-1 Drug Resistance Mutations: An Updated Framework for the Second Decade of HAART. AIDS Rev. 2008; 10(2): 67–84. PubMed Abstract\n\nSiedner MJ, Moorhouse MA, Simmons B, et al.: Reduced efficacy of HIV-1 integrase inhibitors in patients with drug resistance mutations in reverse transcriptase. Nat. Commun. 2020; 11(1): 5922. PubMed Abstract \| Publisher Full Text\n\nSigaloff KCE, Hamers RL, Wallis CL, et al.: Unnecessary Antiretroviral Treatment Switches and Accumulation of HIV Resistance Mutations; Two Arguments for Viral Load Monitoring in Africa. J. Acquir. Immune Defic. Syndr. 2011; 58(1): 23–31. PubMed Abstract \| Publisher Full Text\n\nSiller A, Jebain J, Jinadatha C, et al.:Mechanisms of Retroviral Resistance.Tyring SK, Moore SA, Moore AY, editors. Overcoming Antimicrobial Resistance of the Skin. Springer International Publishing;2021. pp. 75–90. Publisher Full Text\n\nSilver N, Paynter M, McAllister G, et al.: Characterization of minority HIV-1 drug resistant variants in the United Kingdom following the verification of a deep sequencing-based HIV-1 genotyping and tropism assay. AIDS Res. Ther. 2018; 15(1): 18. PubMed Abstract \| Publisher Full Text\n\nSimen BB, Simons JF, Hullsiek KH, et al.: Low-Abundance Drug-Resistant Viral Variants in Chronically HIV-Infected, Antiretroviral Treatment–Naive Patients Significantly Impact Treatment Outcomes. J. Infect. Dis. 2009; 199(5): 693–701. PubMed Abstract \| Publisher Full Text\n\nSkhosana L: High Prevalence of the K65R Mutation in HIV-1 Subtype C Infected Patients Failing Tenofovir-Based First-Line Regimens in South Africa. 2015. Publisher Full Text\n\nSlatko BE, Gardner AF, Ausubel FM: Overview of Next-Generation Sequencing Technologies. Curr. Protoc. Mol. Biol. 2018; 122(1): e59. PubMed Abstract \| Publisher Full Text\n\nSmyth RP, Davenport MP, Mak J: The origin of genetic diversity in HIV-1. Virus Res. 2012; 169(2): 415–429. Publisher Full Text\n\nSoriano V, de Mendoza C : Genetic mechanisms of resistance to NRTI and NNRTI. HIV Clin. Trials. 2002; 3(3): 237–248. Publisher Full Text\n\nTaylor T, Lee ER, Nykoluk M, et al.: A MiSeq-HyDRA platform for enhanced HIV drug resistance genotyping and surveillance. Sci. Rep. 2019; 9: 8970. PubMed Abstract \| Publisher Full Text\n\nThermo Fisher:n.d. Retrieved April 16, 2022.Reference Source\n\nTurner D, Shahar E, Katchman E, et al.: Prevalence of the K65R resistance reverse transcriptase mutation in different HIV-1 subtypes in Israel. J. Med. Virol. 2009; 81(9): 1509–1512. PubMed Abstract \| Publisher Full Text\n\nWatera C, Ssemwanga D, Namayanja G, et al.: HIV drug resistance among adults initiating antiretroviral therapy in Uganda. J. Antimicrob. Chemother. 2021; 76(9): 2407–2414. PubMed Abstract \| Publisher Full Text\n\nWensing AM, Calvez V, Ceccherini-Silberstein F, et al.: 2019 Update of the Drug Resistance Mutations in HIV-1. Topics in Antiviral Medicine. 2019; 27(3): 111–121. PubMed Abstract\n\nWHO: WHO SDRM List—HIV Drug Resistance Database. 2020.Reference Source\n\nWu H, Zhang X-M, Zhang H-J, et al.: In Vitro Selection of HIV-1 CRF08_BC Variants Resistant to Reverse Transcriptase Inhibitors. AIDS Res. Hum. Retrovir. 2015; 31(2): 260–270. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nYang C, Yang S, Li J, et al.: Genetic Diversity and Drug Resistance Among Antiretroviral Treatment-Failed Individuals from 2010 to 2012 in Honghe, China. AIDS Res. Hum. Retrovir. 2015; 31(8): 822–829. PubMed Abstract \| Publisher Full Text" }	[ { "id": "170857", "date": "23 May 2023", "name": "Pascal O. Bessong", "expertise": [ "Reviewer Expertise HIV drug resistance", "antimicrobial resistance", "global health" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nBackground: The authors generated HIV polymerase sequences, by Sanger and Next generation sequencing (Illumina MiSeq) methods. The complete protease (99 amino acids) and about 320 amino acids of reverse transcriptase were examined for drug resistance resistance related mutations. The goal of the study was to compare the level of detection of minority drug resistance related variants of the two sequencing methods. Overall, more drug resistant variants were detected with NGS than with Sanger.\n\nComments: It is well established that that NGS is superior in the detection of minority HIV drug resistant variants than Sanger sequencing. So, it is not clear why the authors thought a different observation was likely with the study population employed. It is important to address this caveat to give a rational purpose for the study in the setting as described.\n\nWhat was the source specimen for total viral RNA? Plasma or blood?\n\nIt would be nice to see some statistical comparative analysis of the resistance variants across the two sequencing approaches. I think investigators would like to know the viral genotypes harboring the resistance related mutations observed.\nIt would read better to say an estimated 65.5% of the sampled population harbored low-abundance HIV-1 resistant variants, most of which are associated with virologic failure. This is because mutations may lead to antiviral drug resistance and subsequently virologic failure. (since in this context, virologic failure does not lead to antiviral drug resistance, it is the other way round instead). This logic should be reflected in the concluding line in the abstract and in the conclusion section of the main text.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-901
https://f1000research.com/articles/11-897/v1	04 Aug 22	{ "type": "Systematic Review", "title": "Industry 4.0 solutions for preventive engine maintenance: a systematic review", "authors": [ "Christian Fauska", "Jaroslava Kniežová", "Jaroslava Kniežová" ], "abstract": "Background: Industry 4.0 is about to revolutionize engine maintenance and support systems with predictive and analytical technologies. Available academic research probes into different expert technologies but lacks a comprehensive overview of available standards and their interaction Methods: The study conducts a systematic review based on the PRISMA Concept 2020 to provide a systematic overview on articles empirically analyzing technologies for maintenance and repair using industry 4.0 technologies. Results: The review identifies four key development fields of industry 4.0 solutions for preventive engine maintenance and repair: sensor equipment, digital networks, technology integration and augmented behavior. All four technologies can be intertwined to implement industry 4.0 based solutions in the industry shopfloor. A cycle model illustrating this is derived. Conclusions: Industry 4.0 based maintenance and repair in the shopfloor is a promising technological development field but further research is required to utilize the individual technologies consistently and integrate them into a comprehensive digital shopfloor environment.", "keywords": [ "Industry 4.0", "maintenance engineering", "preventative maintenance", "shop floor control", "smart factory" ], "content": "Introduction\n\nThe integration of digital intelligence into products, machines, and equipment in the form of cyber-physical systems requires the adaptation and reconfiguration of production processes (BMI, 2020). Industry 4.0 is an umbrella term applied to the intelligent networking of machines and industrial processes with the aid of information and communication technology (BMI, 2021) and has been formulated as a catchword for industrial development programs of the German government and OECD (OECD, 2017). The autonomous, computer-assisted interaction and communication of industrial machinery, in brief, smart factory designs, promise to dynamize and modularize production, optimize logistics, monitor and control production processes, individualize outputs to customer requirements and define sustainable product lifecycles (BMI, 2021).\n\nPredictive industrial maintenance refers to all processes of monitoring, analysis, and amendment applied before machinery or digital processes fail to retain and grant their full functionality (Zhong et al., 2017; Oztemel and Gursev, 2020). To integratedigital self-optimizing industry 4.0 elements in industrial production processe a paradigm shift of the maintenance and support process chain is required. At the same time industry 4.0 technologies promise to revolutionize maintenance and repair systems for industrial production (Reinhart, 2017, 409). To avoid downtime and bottlenecks in autonomous production networks, preventive maintenance is mandatory, intelligent digital technologies could enable industrial production systems to self-organize and self-implement their maintenance processes (Oztemel and Gursev, 2020).\n\nIndustry 4.0 is also, undoubtedly, a fashionable buzzword and a series of publications in preventive industrial maintenance use it (Sony & Naik, 2019; Bongomin et al., 2020). However, a comprehensive overview of relevant preventive maintenance approaches does not yet exist. Integration of the fragmented digitalized solutions for preventive maintenance as postulated by the industry 4.0 principle, is outstanding. Earlier reviews (Zhong et al., 2017; Oztemel and Gursev, 2020; Çınar et al., 2020; Bueno, Filho, and Frank, 2020) in industry 4.0 technologies are more general, i.e. not specialized in preventive maintenance and accordingly provide no in-depth data on the above points.\n\n\nMethods\n\nThis study uses a systematic review of empirically proven technologies to develop an integrative model of preventive maintenance applicable and adjustable to diverse industries using industry 4.0 standards.\n\nFirst eligibility criteria for study consideration have to be specified: The review includes publications in English language in academic peer-reviewed journals, as well as conference papers published since the initial public discussion of the term industry 4.0 in 2017. Studies published as working papers or final theses in a university context as well as books and book contributions are excluded since these are not peer-reviewed. Publications in languages beyond English and publications not available in full text have to be excluded, to ensure a detailed analysis of the content.\n\nSecond information sources the considered articles are retrieved from, have to be specified: to ensure the academic focus of results the study focuses on academic databases. Three major academic data bases are searched for relevant contributions: Web of Science, Scholar Google and Ebscohost. The search was done in June 2021 and the review thus considers publications until 2021.\n\nA homogenous research strategy is applied across all three databases. It uses the following uniform keyword combination to retrieve appropriate studies: “industry 4.0” AND “preventive maintenance” OR “preventive repair” AND empirical. The research is limited to the period 2017 to 2021 to ensure topicality of results in the dynamically evolving field of research. Only studies discussing the issues of preventive maintenance or preventive repair in an industry 4.0 context and within the framework of an empirical study are retained for further evaluation. The titles of the initially retrieved 127 studies are screened manually for relevance to the review. After removal of 52 duplicate or not eligible studies 75 studies remain. Based on a scan of study abstracts 22 studies are deselected for content reasons. 53 studies remain to be sought for retrieval but only 25 studies are openly available in full text from the databases. Textual analysis is done for these studies. Due to lacking applicability four further studies are excluded, six evaluated studies contain no new information. A total of 15 studies were included in the final review. Figure 1 shows the PRISM flowchart (Fauska, 2022).\n\nThe data interpretation process is based on a methodology suggested by Webster and Watson (2002). No software is required for this method. First the studies are catalogued in table form in alphabetical order of authors in the form of a content matrix. It summarizes discussed technologies, fields of application, potentials, limitations, and success factors of the respective technologies (Box 1). The textual evaluation (presented in section “Results”) is then organized by order of technologies and adopt a classification described in Deloitte (2017) and Çınar et al. (2020). Tt includes the sections “sensor equipment”, digital networks, technology integration and augmented behavior. Each section describes a technological subject field of predictive maintenance and repair. All four technological fields interact as shown in the section “discussion”.\n\nThe described review method avoids important biases of literature-based research, namely reporting, selection and interpretation biases by applying a coherent set of rules for study retrieval, selection and interpretation. However, some potential biases remain: Since there is only one coder in the person of the author, subjective biases and errors cannot fully be excluded. Further databases and key word combinations could deliver further results however cannot be considered here due to limitations in publication length.\n\n\nResults\n\nPredictive maintenance systems rely on predictive information to organize maintenance requirements (Jardine, Lin, and Banjevic, 2006), which is (1) gathered from decentral sensor equipment, (2) collected and integrated into digital networks, managed and evaluated in operation centred which rely on (3) technology integration and (4) augmented behaviour (Çınar et al., 2020):\n\n(1) Smart sensors collect machine-internal or external information to detect and inform on equipment status and status changes (Çınar et al., 2020). Sensors collect maintenance information at the level of individual machines and dispose of usually wireless network connections, to feed in time series data on the central network (Jung et al., 2017; Wang et al., 2020). Smart monitoring technology integrates various types of sensors and pieces of information to conclusive longitudinal data strands and profiles (Zhong et al., 2017).\n\n(2) Digital (wireless) networks are applied to interconnect technological appliances, transfer and store data (Çınar et al., 2020). Smart machinery could shortly be able to survey its performance and repair status based on status and operation protocols and self-inform on repair requirements (Saxby, Cano-Kourouklis, and Viza, 2020). Big data i.e. time series data of smart sensor units are automatically collected, analyzed, and integrated to develop an action schedule (Lee et al., 2019; Powell, 2018).\n\n(3) Technology integration refers to data management and accumulation in the Internet of Things and uses artificial intelligence to process and analyze data (Çınar et al., 2020; Leyh, Martin, and Schäffer, 2017). By integrating machinery data, a maintenance plan for the equipment is designed automatically which considers interdependencies and common maintenance requirements (Jung et al., 2017). Linear (regularly moving) assets place particular inspection and maintenance challenges that could be solved by automated robots operating digital data self-reliantly (Seneviratne et al., 2018). Degradation analysis is supported by contingent and reliable data streams (Zhonget al., 2017).\n\n(4) Augmented behavior refers to virtual computing and service applications administering the machine-human interface (Çınar et al., 2020). Preventive maintenance and repair information provides a reliable data basis for operative human repair and exchange activities (Saxby, Cano-Kourouklis, and Viza, 2020). Chen et al. (2017) see the key action field for preventive maintenance to be the level of data application. The analysis of data gathered from diverse sensor networks is integrated using a data mining strategy and enable active maintenance processes. Augmented reality applications enable humans to understand and control maintenance processes (Longo, Nicoletti, and Padovano, 2017; Bueno et al., 2020),\n\nIntegrating these points and referring to the Total Quality Management “Plan – Do- Check- Act” cycle (Johnson, 2002) a circular model for the integration and use of industry 4.0 technology to preventive maintenance processes results:\n\n\nDiscussion\n\nIn the following discussion the opportunities, limitations and success factors of preventive maintenance using industry 4.0 technologies are discussed controversially.\n\nPreventive engine maintenance offers huge technical and economic potentials: Smart machinery self-diagnoses emerging problems even on a remote basis (Oztemel and Gursev, 2020), provides decision support for operators (Oztemel and Gursev, 2020) and predicts system failure to design an immediate process of routine and extraordinary checks (Chen et al., 2017; Rosin et al., 2020). Real-time information gathering and monitoring enable timely intervention in case of failure risk and the planning ahead of routine maintenance jobs (Lee et al., 2019). Repair equipment and staff are ordered and organized regarding process flows. Maintenance intervals and life cycle management are optimized by structured scheduling (Zhong et al., 2017; Wang et al., 2020). Structured maintenance information helps to diminish production failure due to machinery shortcomings and increases productivity (Saxby, Cano-Kourouklis, and Viza, 2020).\n\nSmart active repair prevents downtimes and organizes repair and maintenance processes so that process flows run undisturbed, which reduces the transaction costs of operation (Wang et al., 2020). Accident prevention becomes more effective due to early failure diagnosis (Wang et al., 2020). Technical replacement impacts and costs can be reduced by comprehensive intervention planning (Lee et al., 2019). Intelligent augmented reality systems could be applied to enhance human understanding of maintenance requirements and schedules (Longo, Nicoletti & Padovano, 2017; Powell et al., 2018).\n\nOn the other hand, the technology requires further development: Expert knowledge is indispensable to adapt smart repair routines to complex production architectures individually (Chen et al., 2017). Initial capital investments are significant and usually, external experts are required to get and keep the system running (Lee et al., 2019; Seneviratne et al., 2018). Repair processes are frequently not possible without human interventions, e.g. when components must be changed physically (Longo, Nicoletti, and Padovano, 2017). Intersections between human activity and digital processes have to be designed (Longo, Nicoletti, and Padovano, 2017). Complex maintenance routines are prone to potential failure and human intervention could become difficult for lack of understanding of error causes and potential remedies. To date, test samples for preventive smart maintenance are small and available for individual industries and applications only (Lee et al., 2019). The net cost effects of smart preventive maintenance accordingly are not well documented and no general application standards are available (Saxby, Cano-Kourouklis, and Viza, 2020).\n\nTo develop sustainable preventive maintenance concepts in single factory industry 4.0 environments relevant data has to be identified and integrated into a database for machine learning models to gather the necessary information (Çınar et al., 2020). Workshop equipment has to be renewed and intense cooperation with IT experts is necessary (Jung et al., 2017). Businesses should document this knowledge carefully (Chen et al., 2017) to keep track of and monitor self-organizing routines and intervene in case of errors. Data security issues have to be considered for sustainable operationality (Çınar et al., 2020).\n\nIn the future, industry 4.0 maintenance applications could be augmented by cloud-based data, big data streaming and management systems (Sahal, Ali, and Breslin, 2020), which integrate information across various industrial units on share platforms, deselect redundant information and condense relevant data. These applications could provide reliable data sets to predict and plan maintenance processes for similar units (Zhong et al., 2017).\n\n\nConclusions\n\nHuge initial investments into a comprehensive ICT grid are required to comprehensively collect all necessary repair and maintenance data and evaluate these data (Sahal, Ali, and Breslin, 2020) based on joint information models (Jung et al., 2017).\n\nFurther inter-industry research is desirable to augment knowledge on the efficiency of smart maintenance in an industry 4.0 environment and to develop general industry standards.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nReporting guidelines\n\nFIGSHARE: PRISMA checklist and flowchart:\n\nhttps://doi.org/10.6084/m9.figshare.20363727.v1 (Fauska, 2022)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Appendices\n\n\n\n\nReferences\n\nBMI (Bundesministerium für Wirtschaft und Energie): Industrie 4.0, Innovationen für die Produktion von morgen.2020. Accessed May 22, 2022.Reference Source\n\nBMI (Bundesministerium für Wirtschaft und Energie): Was ist Industrie 4.0?2021. Accessed June 11, 2021.Reference Source\n\nBongomin O, Yemane A, Kembabazi B, et al.: Industry 4.0 disruption and its neologisms in major industrial sectors: A state of the art. J. Eng. 2020; 2020: 1–45. Publisher Full Text\n\nBueno AF, Filho MG, Frank AG: Smart production planning and control in the Industry 4.0 context: A systematic literature review. Comput. Ind. Eng. 2020; 149: 106774. Publisher Full Text\n\nChen B, et al.: Smart factory of industry 4.0: Key technologies, application case, and challenges. IEEE Access. 2017; 6: 6505–6519. Publisher Full Text\n\nÇınar ZM, et al.: Machine learning in predictive maintenance towards sustainable smart manufacturing in industry 4.0. Sustainability. 2020; 12(19): 8211. Publisher Full Text\n\nDeloitte: Making Maintenance Smarter. New York, NY, USA:Deloitte University Press;2017. Accessed June 11, 2021.Reference Source\n\nFauska C: PRISM Checklist and flowchart - Industry 4.0 solutions for preventive engine maintenance. figshare. [Reporting guidelines].2022. Publisher Full Text\n\nJardine AKS, Lin D, Banjevic D: A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mech. Syst. Signal Process. 2006; 20(7): 1483–1510. Publisher Full Text\n\nJohnson CNThe benefits of PDCA. Qual. Prog. 2002; 35(5): 120.Reference Source\n\nJung K, et al.: A reference activity model for smart factory design and improvement. Prod. Plan. Control. 2017; 28(2): 108–122. Publisher Full Text\n\nLee SM, Lee DH, Kim YS: The quality management ecosystem for predictive maintenance in the Industry 4.0 era. Int. J. Qual. Innov. 2019; 5(1): 1–11. Publisher Full Text\n\nLeyh C, Martin S, Schäffer T: Industry 4.0 and Lean Production—A matching relationship? An analysis of selected Industry 4.0 models. 2017 Federated Conference on Computer Science and Information Systems (FedCSIS). IEEE;2017. Publisher Full Text\n\nLongo F, Nicoletti L, Padovano A: Smart operators in industry 4.0: A human-centred approach to enhance operators’ capabilities and competencies within the new smart factory context. Comput. Ind. Eng. 2017; 113(2017): 144–159. Publisher Full Text\n\nOECD: OECD Digital Economy Outlook 2017.2017.Reference Source\n\nOztemel E, Gursev S: Literature review of Industry 4.0 and related technologies. J. Intell. Manuf. 2020; 31(1): 127–182. Publisher Full Text\n\nPowell D, et al.:Towards digital lean cyber-physical production systems: Industry 4.0 technologies as enablers of leaner production. IFIP International Conference on Advances in Production Management Systems. Cham:Springer;2018. Publisher Full Text\n\nPRISMA 2020: Checklist.2020. Accessed May 22, 2022.Reference Source\n\nReinhart G: Handbuch Industrie 4.0: Geschäftsmodelle, Prozesse, Technik. Carl Hanser Verlag GmbH Co KG;2017.\n\nRosin F, et al.: Impacts of Industry 4.0 technologies on Lean principles. Int. J. Prod. Res. 2020; 58(6): 1644–1661. Publisher Full Text\n\nSahal R, Breslin JG, Ali MI: Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case. J. Manuf. Syst. 2020; 54(2020): 138–151. Publisher Full Text\n\nSaxby R, Cano-Kourouklis M, Viza E: An initial assessment of Lean Management methods for Industry 4.0. TQM J. 2020; 32: 587–601. Publisher Full Text\n\nSeneviratne D, et al.: Smart maintenance and inspection of linear assets: An Industry 4.0 approach. Acta Imeko. 2018; 7. Publisher Full Text\n\nSony M, Naik S: Key ingredients for evaluating Industry 4.0 readiness for organizations: a literature review. BIJ. 2019; 27(7): 2213–2232. Publisher Full Text\n\nWang N, et al.: An active preventive maintenance approach of complex equipment based on a novel product-service system operation mode. J. Clean. Prod. 2020; 277(2020): 123365. Publisher Full Text\n\nWebster J, Watson RT: Analyzing the past to prepare for the future: Writing a literature review. MIS Q. 2002: xiii–xxiii.Reference Source\n\nZhong RY, et al.: Intelligent manufacturing in the context of industry 4.0: a review. Engineering. 2017; 3(5): 616–630. Publisher Full Text" }	[ { "id": "168705", "date": "14 Apr 2023", "name": "Ari Setiawan", "expertise": [ "Reviewer Expertise Production Systems", "Flexible Manufacturing Systems (FMS)", "Smart Factory", "Maintenance." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe title of this paper is Industry 4.0 solutions for preventive ENGINE maintenance: a systematic review. The keyword that made me interested was the word: engine. At first I thought that the word “engine” in this title refers to an object of the engine in mechanical equipment. However, this makes me doubt whether (1) the engine as an object of the prime mover in mechanical equipment or (2) as an “engine” of maintenance activities.\nTherefore I would like to give more comments for this article as the Major points:\nThis article discusses a systematic review as the first step in a series of research. However there has been no explanation in the background section regarding the importance of implementing and developing industry 4.0 solutions for preventive engine maintenance. Meanwhile in this article, the assessment is more emphasized on industrial issues.\n\nThe use of the word engine in the title leads to an ambiguous perception as to whether the engine in question is the prime mover of a mechanical device or vehicle, or the engine of maintenance activities. Therefore it needs further explanation in the introduction and also choose a more appropriate word for the title of the article.\n\nThe research questions in this article are not explained and make the research has no objective.\n\nThe method used is the PRISMA Statement 2020 which in my opinion can be used as a systematic review. However a more detailed discussion is needed to explain the development of the Smart preventive maintenance cycle.\n\nNeed to add more references which in my opinion there are at least more than 35 articles related to the topics discussed.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Partly\n\nIs the statistical analysis and its interpretation appropriate? Not applicable\n\nAre the conclusions drawn adequately supported by the results presented in the review? Yes", "responses": [] }, { "id": "154083", "date": "16 Nov 2023", "name": "Mita Mehta", "expertise": [ "Reviewer Expertise Corporate Governance", "Digital innovation", "HR" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nQ1 Are the rationale for, and objectives of, the Systematic Review clearly stated?\n\nWhile Authors have tried to look into the solutions suggestive through engine maintenance by undertaking systematic review; the PRISM concept it is still not coming clear from the Article writing skills the clear purpose of doing the research. Though Fig 1 clearly mentions the keyword selection so How part is clear but not Why.\nQ4 Are the conclusions drawn adequately supported by the results presented in the review?\nDiscussions and conclusions seems unsynchronized with results and even in results. Authors can explain the review outcomes derived through PRISMA.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Partly\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? Not applicable\n\nAre the conclusions drawn adequately supported by the results presented in the review? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-897
https://f1000research.com/articles/11-893/v1	04 Aug 22	{ "type": "Research Article", "title": "Adverse COVID-19 vaccination effects in Finnish patients with Ménière’s disease: a cross-sectional study", "authors": [ "Eldre Beukes", "Vinaya Manchaiah", "Nora Pyykkö", "Ilmari Pyykkö", "Vinaya Manchaiah", "Nora Pyykkö", "Ilmari Pyykkö" ], "abstract": "Background: The association between reporting adverse coronavirus disease 2019 (COVID-19) vaccination effects and those with a history of audiovestibular difficulties is unknown. The aim of this research is therefore to investigate adverse vaccination effects in adults with a history of Ménière’s disease. Specifically, the incidence of adverse effects, the factors associated with those reporting adverse effects and the relationship between the reporting of audiovestibular and other adverse effects. Methods: A mixed-methods exploratory cross-sectional survey study design was used. Data were collected from 333 members of the Finnish Ménière Association. The survey was designed to obtain demographic information that may be associated with having adverse effects or not, vaccination-specific information and adverse vaccination effects. Both health and audiovestibular adverse events were identified. Data analysis included comparing those reporting and not reporting adverse vaccination effects. Results: The mean age was 63 years with 81% being female. Of the 327 respondents who had one of the COVID-19 vaccinations (Comirnatry/ Pfizer, Astra Zeneca, or Moderna), 203 (62%) reported no adverse effects. The type of or number of vaccinations were not related to the reporting of adverse effects. The most frequently reported adverse effects were injection site tenderness (38%), arm pain (21%), fever (15%) and headaches (15%). Post-vaccination tinnitus and vertigo (both 7%) were the most frequently reported audiovestibular-related symptoms, followed by aural fullness (6%) and hearing loss (4%). Those reporting previous pre-vaccination vertigo were more likely to have post-vaccination vertigo. The presence of post-vaccination tinnitus, hearing loss, and aural fullness, predicted the presence of post-vaccination vertigo. Conclusions: A small proportion of patients with a history of Ménière’s disease may experience adverse post-vaccination effects. Further research is required to explore whether adverse post-vaccination audiovestibular effects are more prevalent in those with a history of otological disorders compared with the general population.", "keywords": [ "Ménière’s disease", "COVID-19 vaccination", "COVID-19", "audiovestibular", "vertigo", "hearing loss", "tinnitus" ], "content": "Introduction\n\nThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in more than five million deaths after two years of the coronavirus disease 2019 (COVID-19) pandemic.1 Many patients with COVID-19 infections fully recover, however, a proportion experience long-term symptoms including pulmonary, cardiovascular, nervous system and psychological effects.2 Evidence for the association between COVID-19 infection and audiovestibular symptoms such as hearing loss, tinnitus and vertigo has furthermore been identified.3,4\n\nTo reduce the risk of receiving COVID-19 infection, vaccines were developed, and global vaccination implementation recommended.5 Several vaccines are approved for use and proven effective, however, post-vaccination adverse effects are also reported.6 The most common reported adverse effect are pain at the site of injection, fatigue, and headache, which generally are mild and resolve within a few days.7 Adverse audiovestibular effects such as sudden hearing loss, have also been reported in case studies or larger groups, such as sudden sensorineural hearing loss,8,9 tinnitus,10,11 and dizziness.12,13 Although recovery is often reported and incidence rates appear similar to those in the general population (e.g., Formeister et al.14; Tseng et al.15).\n\nAs with COVID-19 infection, there may be certain populations who are more at risk for developing adverse post-vaccination effects. One group may be those with pre-existing audiovestibular problems, such as patients with Ménière’s disease who experience hearing loss, tinnitus and vertigo. A study by Wichova, Miller and Derbery16 identified that 11 out of 30 patients reporting post-vaccination hearing-related symptoms had previous otologic diagnoses, including six patients with Ménière’s disease. As this possible association deserves further attention, the current study was undertaken with the aim of investigating adverse post-vaccination effects in patients with pre-existing Ménière’s Disease. The specific aims were to (i) identify the incidence of adverse effects, (ii) explore the factors associated with those reporting adverse effects, and (iii) identify the relationship between the reporting of audiovestibular and other adverse effects.\n\nThe Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies17 was used to report the methods and results of the survey (see Extended data26).\n\n\nMethods\n\nA mixed-methods exploratory cross-sectional survey study design was used to find out about vaccinations taken and possible side effects.\n\nThis study was conducted by the Union of Finnish Ménière Association sending a questionnaire by email to the members of the Union of Finnish Ménière Association, who had a registered email address. The Union of Finnish Ménière Association is a charitable organization consisting of eight regional Ménière Associations and the main aim of the Union is to coordinate and organize peer support for Ménière patients offered by the local associations. The Union administers centrally the above-mentioned member register, and the register adheres to the GDPR (General Data Protection Regulation) of the EU. The data collection was completely voluntary and non-invasive and therefore by Finnish law did not require formal ethical committee approval, as confirmed by the Finnish law authorities (ETENE). The study was approved on 9 September 2021 by the internal ethics board of the Union of Finnish Ménière Association and was carried out according to the principles expressed in the Declaration of Helsinki. The anonymized data set was provided to the research team.\n\nParticipants provided online written, informed consent for participation by confirming they understood how their data would be used and what the study entailed.\n\nThe survey questions were developed jointly by the study authors (IP, NP) and FMF (Finnish Ménière Federation). The survey included demographic questions (i.e., gender, age, and presence of vertigo prior to the vaccination), vaccination related questions (i.e., number of COVID-19 vaccinations received, type and date of the vaccinations), and adverse vaccination effects (i.e., vertigo, imbalance, drop attacks [Tumarkin’s otolithic Crisis]), hearing loss, aural fullness, tinnitus, sinus symptoms, headaches, arm pain and/or fever). Respondents were asked to report symptoms that appeared within three weeks after vaccinations. There was also the option to include descriptions and provide more information regarding the symptoms experienced. All the questions, except the descriptions were mandatory, and participants could not continue unless they answered prior questions. This may have reduced the numbers completing the full questionnaire.\n\nThe eligibility criteria included adults aged 18 years or older who provided written electronic informed consent. The survey was distributed via email to members of the FMF who were above 18 years, who were assumed to have a history of Ménière’s disease, and who had a registered email address, which accounts for 75% of their members. The survey was lunched on October 10th, 2021 and closed on October 28th, 2021. Reporting bias was minimized by allowing anonymous responses and carefully wording to be non-leading where possible.\n\nAll analyses were completed in the Statistical Package for Social Sciences (SPSS) version 26.0. Significance was set to p ≤ .05, two-tailed. All the data was, thus using completer’s analysis. As all the questions were mandatory, there was no missing data, except for comment boxes.\n\nPost-hoc tests were Bonferroni corrected for multiple comparisons. Continuous data are expressed as mean and standard deviation (SD). Categorical data are shown as percentages and frequencies. Initial analysis involved all the respondents (n = 333). To evaluate the vaccination effect, those who did not have the vaccination were removed (n = 6).\n\nSubgroups were compared for those not reporting post-vaccination adverse effects and those reporting general post-vaccination effects (e.g., fever, arm pain, headaches) and those reporting vertigo-related effects (e.g., vertigo, falls, imbalance). The independent-samples t-test were used for continuous variables and the Chi-squared test for categorical variables together with adjusted standardized residual values during post-hoc testing. Spearman’s rho correlations (categorical variables) were used to estimate the strength of association between reporting vertigo-related problems and other post-vaccination-related effects. Correlation strength was categorized as very weak (.00 to .19) weak (.20 to .39), moderate (.40 to .59), strong (.60 to.79) and very strong (.80 to 1.0). Following this, hierarchical linear multiple regression models were performed with vertigo-related problems as the dependent variable and other post-vaccination-related effects as predictor variables. Due to the categorical data dummy variables were used. Qualitative data from the open questions were analyzed separately using inductive content analysis to supplement the quantitative analyses.\n\n\nResults\n\nA total of 333 participants responded to the survey from an estimated 550 participants (60% response rate). The mean age was 63 years (SD: 11 years) with an unequal gender divide with 81% being female and 19% being male as seen in Table 1, partly representing the higher incidence of Ménière’s Disease in women.18 There were 31% reporting no history of vertigo prior to the vaccination and 69% reporting either constant (6%), episodic (47%) or a mixture of constant and episodic vertigo (16%). Those reporting no vertigo had a higher mean age (65 SD: 10 years) than those reporting constant (63 SD: 13 years) or episodic vertigo (62 SD: 12 years) or a mixture of constant and episodic vertigo (60 SD: 11 years). This may represent the progression of the Ménière’s disease that those that are older were in the later stages and hence having fewer symptoms. This indicated a significant relationship between age and type of vertigo reported (r = -.19, p = 0.002). Of those responding, 327 (98%) had the first, 313 (94%) had the second and 12 (4%) had the third vaccination as seen in Figure 1. The majority were vaccinated with Comirnaty (Pfizer/BioNTech) (69%) followed by Oxford- Astra Zeneca (15%) and then Moderna (8%) vaccinations.\n\nOf the 327 who were vaccinated, 203 (62%) reported no vaccination adverse effects and 124 (38%) reported post-vaccination adverse effects. The most common adverse effect was injection site tenderness (38%), followed by arm pain (21%), fever (15%) and headaches (15%) as seen in Figure 2. Although differences in symptom reporting was observed, such as less fever reported by those with Comirnaty (10%) compared to those Astra Zeneca (30%) and Moderna (33%) no significant correlations were found between the symptom reported and type of vaccination received. From the open-ended responses (see supplementary information S2) most of these symptoms were short lived, expected and mild as described by these example responses: “Mild pain at the injection site that disappeared the next day,” “Mild fever the next day after the first vaccination,” and “A headache that lasted 1 day.” Post-vaccination tinnitus and vertigo (both 7%) were the most frequently reported audiovestibular-related symptoms, followed by aural fullness (6%) and hearing loss (4%).\n\nCorrelation coefficients provided represent Spearman’s correlations between the symptom and type of vaccination received.\n\nTable 1 compares those reporting and not reporting general post-vaccination adverse effects. There were no significant associations regarding those having effects or not, based on the type of vaccination received. Age differences were present as those having vaccination effects were significantly older. Gender differences were also seen as significantly fewer females (33%) had adverse effects compared with those with no effect (67%). Significantly more males (55%) had effects compared to those with no effects (45%). The time of vaccination had no effect, except for the second vaccination, significantly fewer respondents vaccinated in April-June experienced adverse effects (55%) compared with those without effects in this period (45%). Spearman’s correlations investigated the effect of the vaccination type and the presence of symptoms. The only weak positive correlation was for local arm pain being higher for those with the Moderna injection (although this is a smaller sample: 10 not having pain and 17 having pain). Those receiving Astra Zeneca and Moderna were less likely to report injection pain.\n\nOf the 327 who were vaccinated, 281 (86%) reported no vertigo, imbalance, swaying or drop attacks and 46 (14%) reported at least one vertigo-related post-vaccination symptom as seen in Table 2. Of these 23 (7%) reported one symptom and 23 (7%) reported two or more symptoms. There were no gender effects and no differences found related to the type of vaccination received. Those who were younger were significantly more likely to report vertigo and imbalance post-vaccination. There were also significant differences based on the presence of pre-vaccination vertigo-related problems as those reporting previous pre-vaccination vertigo were more likely to have post-vaccination vertigo. The strength of this relationship was a small positive relationship (r = .16, p = .005). When looking at the group reporting vertigo as the largest vestibular complaint (n = 23), there were no significant difference between this group and those not reporting vertigo as seen in the last column of Table 2.\n\nThere was a positive relationship between experiencing post-vaccination vertigo and experiencing post-vaccination tinnitus, hearing loss, aural fullness, headaches, and rhinitis as seen in Table 3. The correlation was strong for tinnitus, moderate for hearing loss and aural fullness and weak for headaches and rhinitis. Hierarchical linear multiple regression analysis was carried out to investigate the ability of the presence of these adverse effects to predict the presence of post-vaccination vertigo (see Table 3). All the available effects were used in the model. The model significantly improved the ability to post-vaccination vertigo and imbalance [F(8, 318) = 34.21, p = 0.001*] and 46% (Adjusted R2 = 0.63) of the variance was explained by the presence of these symptoms. Removing the non-significant variables did not improve the model. The variables making significant predictors regarding the presence of post-vaccination vertigo and imbalance were tinnitus (β = .50, p < 0.001), aural fullness (β = .19, p < 0.001), rhinitis (β = .14, p = 0.003) as seen in Table 3.\n\nFrom the open-ended responses it was very difficult to identify if some participants were describing vaccination-related effects or general pre-vaccination effects due to vague comments such as “Hearing problems in my right ear,” Constant feeling of pressure,” or “headaches.” A summary of the number of open-ended responses for each symptom and information regarding the onset, duration and vaccination dosage where available is available in Underlying data. The onset of vertigo and unsteadiness was between 12 hours to two and a half weeks post-vaccination. Where reported, the duration was between a few hours to two weeks. Effects were reported for either of the vaccination doses and at times both the first and second doses. Some patients reported that they felt that their symptoms were exacerbated by the stress during the pandemic and not necessarily the vaccination.\n\n\nDiscussion\n\nThe aim of the current study was to investigate adverse post-vaccination effects for 333 Finnish patients with an assumed history of Ménière’s disease due to recruitment through the FMF. Of the 327 who were vaccinated, 203 (62%) reported no adverse vaccination effects and 124 (38%) reported one or more adverse effect. The most common effect was injection site tenderness (38%), followed by arm pain (21%), fever (15%) and headaches (15%). Those reporting effects were more likely to be older or to be males. This is in contrast to adverse vaccination effect being higher in the female population in the general public as reported in previous studies.19 It may be that the gender imbalance of the sample size is affecting these results and they should thus be interpreted with caution. Some vaccination reports have found no age effects20 whereas others have found that young age was correlated with more effects.21 For the second vaccination, significantly fewer effects were reported for those vaccinated in April-June 2020. When comparing those who reported adverse effects and those who did not, there were no significant differences base on the type of vaccination received.\n\nOf those vaccinated, 15% reported at least one adverse audiovestibular symptom. Post-vaccination tinnitus and vertigo (both 7%) were the most frequently reported audio-vestibular symptoms, followed by aural fullness (6%) and hearing loss (4%). There were no gender or vaccination type effects but those with previous vertigo problems and younger adults were more likely to report vertigo-related problems. From the reports the symptoms appeared to resolve within two weeks of onset, although not all participants reported the duration of the effects. There was also no clear pattern as to which vaccination could result in more effects and for one group of people it was one vaccination while others reported adverse effects after both the second and third vaccinations. These results are different to those reported by Wichova et al.16 who found that 30 (3%) of their sample of 1,325 patients reported audiovestibular effects, with hearing loss (83%) being most frequently reported, followed by tinnitus (50%), dizziness (27%) and vertigo (17%) although evidence of a correlation was not found. A further interesting difference was that the onset of audiovestibular problems was 10 days post-vaccination, which appears similar to the present study reporting onset between 12 hours to 2.5 weeks post-vaccination. Both studies suggested that previous otologic diagnoses may result in a higher incidence of post-vaccination adverse effects. A further study by Ciorba et al.22 reported a higher incidence of post-vaccination vertigo (.96%) compared with tinnitus (.11%) in Italy. Formeister et al.14 found that the incidence of sudden sensorineural hearing loss was similar post-vaccination to that expected in the general population. Further systematic reviews are required to identify wider audiovestibular adverse post-vaccination effects due to these difference across studies.\n\nIn the present study, experiencing post-vaccination tinnitus, hearing loss, and aural fullness predicted the presence of post-vaccination vertigo (explaining 46% of the variability). This indicates that likelihood that post-vaccination vertigo is more likely in the presence of other post-vaccination effects. The effect of stress during the pandemic was noted by numerous participants as contributing to their audiovestibular problems as previously found.23 Ensuring support for such individuals is available, is required.\n\nOverall, the current exploratory study has highlighted that a small proportion of patients with a history of Ménière’s disease may experience adverse post-vaccination effects. These individuals may be more hesitant to undergo vaccinations, particularly if they had an adverse effect for one of the vaccination dosages. Further robust studies to explore this effect is required, together with systematic reviews to pool what is known regarding post-vaccination audiovestibular effects. Further research is also required to explore whether adverse post-vaccination audiovestibular effects are more prevalent in those with a history of otological disorders compared with the general population.\n\nThere were numerous limitations that should be considered when interpreting the results. Firstly, there is possible sampling bias as those responding to the survey may be patients more likely to have had post-vaccination effects. The sample was not well balanced due to an unequal gender divide, which may have affected results, although Ménière’s disease is known to be more prevalent in females.18 The survey could have been improved to ask specific questions regarding the onset, duration and dosage linked to the adverse effects. Vertigo-related problems are also frequently experienced during cardiac problems. Post-vaccination vertigo could be associated with cardiovascular problems24 and other non-auditory health conditions this association should be accounted for in future studies. Looking at the impact of comorbid health conditions on adverse vaccination effects is also required. Associations between other health conditions and audiovestibular symptom have been previously reported. Pyykkö et al.25 for instance identified that vestibular syncope (sudden and transient loss of consciousness) was associated with Tumarkin attacks, migraine and history of ischemic heart disease and history of cerebrovascular disease). It is also important to establish if there are any associations regarding previous COVID-19 infections and adverse vaccination effects. Further studies and systematic reviews are encouraged to identify the incidence and mechanisms of adverse audiovestibular vaccination effects.\n\n\nData availability\n\nFigshare: COVID 19 vaccine in Ménière's disease, https://doi.org/10.6084/m9.figshare.19519801.26\n\nThis project contains the following underlying data:\n\n- COVID vaccine in MD for repository.xslx (raw data).\n\nFigshare: COVID 19 vaccine in Ménière's disease, https://doi.org/10.6084/m9.figshare.19519801.26\n\nThis project contains the following extended data:\n\n- Finnish_MD COVID Vaccination Questionnaire\n\n- English_MD COVID Vaccination Questionnaire\n\n- S 1S1 The STROBE Checklist\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgements\n\nWe would like to thank Nina Kallunki from the Finnish Ménière Federation for help with recruitment and data transfer and control for this study. Our thanks is extended to all the participants of this study for their time give to do the survey.\n\n\nReferences\n\nWorld Health Organization: COVID-19 weekly epidemiological update, edition 79, 15 February 2022.2022.\n\nWorld Health Organization (WHO), A clinical case definition of post COVID-19 condition by a Delphi consensus:2021. Retrieved October 6, 2021.Reference Source\n\nLough M, Almufarrij I, Whiston H, et al.: Revised meta-analysis and pooled estimate of audio-vestibular symptoms associated with COVID-19. Int. J. Audiol. 2021; 1–5. Advance online publication. PubMed Abstract \| Publisher Full Text\n\nBeukes E, Ulep AJ, Eubank T, et al.: The Impact of COVID-19 and the Pandemic on Tinnitus: A Systematic Review. J. Clin. Med. 2021; 10(13): 2763. PubMed Abstract \| Publisher Full Text\n\nKupferschmidt K: Despite obstacles, WHO unveils plan to distribute vaccine. Science (New York, N.Y.). 2020; 369(6511): 1553. PubMed Abstract \| Publisher Full Text\n\nXing K, Tu XY, Liu M, et al.: Efficacy and safety of COVID-19 vaccines: a systematic review. Zhongguo dang dai er ke za zhi = Chinese Journal of Contemporary Pediatrics. 2021; 23(3): 221–228. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKaur RJ, Dutta S, Bhardwaj P, et al.: Adverse Events Reported From COVID-19 Vaccine Trials: A Systematic Review. Ind. J. Clin. Biochem. 2021; 36(4): 427–439. PubMed Abstract \| Publisher Full Text\n\nJeong J, Choi HS: Sudden sensorineural hearing loss after COVID-19 vaccination. International Journal of Infectious Diseases: IJID: Official Publication of The International Society for Infectious Diseases. 2021; 113: 341–343. PubMed Abstract \| Publisher Full Text\n\nTsetsos N, Poutoglidis A, Vlachtsis K, et al.: Sudden Sensorineural Hearing Loss Following the Second Dose of COVID-19 Vaccine. Cureus. 2021; 13(8): e17435. PubMed Abstract \| Publisher Full Text\n\nKahn B, Apostolidis SA, Bhatt V, et al.: Multisystem Inflammation and Organ Dysfunction After BNT162b2 Messenger RNA Coronavirus Disease 2019 Vaccination. Crit. Care Explor. 2021; 3(11): e0578. PubMed Abstract \| Publisher Full Text\n\nParrino D, Frosolini A, Gallo C, et al.: Tinnitus following COVID-19 vaccination: report of three cases. Int. J. Audiol. 2021; 61: 526–529. PubMed Abstract \| Publisher Full Text\n\nGee J, Marquez P, Su J, et al.: First Month of COVID-19 Vaccine Safety Monitoring - United States, December 14, 2020-January 13, 2021. MMWR Morb. Mortal. Wkly Rep. 2021; 70(8): 283–288. PubMed Abstract \| Publisher Full Text\n\nGianfredi V, Minerva M, Casu G, et al.: Immediate adverse events following COVID-19 immunization. A cross-sectional study of 314,664 Italian subjects. Acta bio-medica: Atenei Parmensis. 2021; 92(S6): e2021487. PubMed Abstract \| Publisher Full Text\n\nFormeister EJ, Chien W, Agrawal Y, et al.: Preliminary Analysis of Association Between COVID-19 Vaccination and Sudden Hearing Loss Using US Centers for Disease Control and Prevention Vaccine Adverse Events Reporting System Data. JAMA Otolaryngol. Head Neck Surg. 2021; 147(7): 674–676. PubMed Abstract \| Publisher Full Text\n\nTseng WP, Wu JL, Wu CC, et al.: Seroprevalence Surveys for Anti-SARS-CoV-2 Antibody in Different Populations in Taiwan With Low Incidence of COVID-19 in 2020 and Severe Outbreaks of SARS in 2003. Front. Immunol. 2021; 12: 626609. PubMed Abstract \| Publisher Full Text\n\nWichova H, Miller ME, Derebery MJ: Otologic Manifestations After COVID-19 Vaccination: The House Ear Clinic Experience. Otol. Neurotol. 2021; 42(9): e1213–e1218. PubMed Abstract \| Publisher Full Text\n\nAltman DG, Egger M, Pocock SJ, et al.: The Strengthening the Reporting of Observational Studies in Epidemiology [STROBE] statement: guidelines for reporting observational studies. Gac. Sanit. 2008; 22(2): 144–150.\n\nCorazzi V, Ciorba A, Skarżyński PH, et al.: Gender differences in audio-vestibular disorders. Int. J. Immunopathol. Pharmacol. 2020; 34: 205873842092917. Publisher Full Text\n\nCuschieri S, Borg M, Agius S, et al.: Adverse reactions to Pfizer-BioNTech vaccination of healthcare workers at Malta's state hospital. Int. J. Clin. Pract. 2021; 75(10): e14605. PubMed Abstract \| Publisher Full Text\n\nAl Khames Aga QA, Alkhaffaf WH, Hatem TH, et al.: Safety of COVID-19 vaccines. J. Med. Virol. 2021; 93(12): 6588–6594. PubMed Abstract \| Publisher Full Text\n\nCoggins S, Laing ED, Olsen CH, et al.: Adverse effects and antibody titers in response to the BNT162b2 mRNA COVID-19 vaccine in a prospective study of healthcare workers. medRxiv: the preprint server for health sciences. 2021; 2021.06.25.21259544. Publisher Full Text\n\nCiorba A, Bianchini C, Caranti A, et al.: Incidence of Audiological Adverse Effects Induced by COVID-19 Vaccines: A Preliminary Study. Ear Nose Throat J. 2021; 1455613211048975. Advance online publication. PubMed Abstract \| Publisher Full Text\n\nBeukes EW, Baguley DM, Jacquemin L, et al.: Changes in Tinnitus Experiences During the COVID-19 Pandemic. Front. Public Health. 2020; 8: 592878. PubMed Abstract \| Publisher Full Text\n\nBasnet A, Ojha SK, Jha SK, et al.: Cardiovascular Complication following Covishield Vaccination in Nepal: A Case Report. JNMA J. Nepal Med. Assoc. 2021; 59(240): 805–807. PubMed Abstract \| Publisher Full Text\n\nPyykkö I, Manchaiah V, Zou J, et al.: Vestibular syncope: A disorder associated with drop attack in Ménière's disease. Auris Nasus Larynx. 2018; 45(2): 234–241. PubMed Abstract \| Publisher Full Text\n\nManchaiah V: COVID 19 vaccine in Ménière's disease. figshare. [Dataset].2022. Publisher Full Text" }	[ { "id": "148131", "date": "27 Oct 2022", "name": "Hari Prakash P", "expertise": [], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript aims to explore the post vaccination adverse effect on individuals with Meniere’s disease. The authors have done a survey on Finnish population using questionnaire and contrasted the subgroup with the predominantly aural symptoms versus other symptoms. The authors found that the vertigo, tinnitus, and hearing loss were the most common symptoms post vaccination. Presence of tinnitus, hearing loss and aural fullness predicted the post vaccination vertigo. Overall, the study is well designed and executed. Statistics were appropriate. The study is important now since, Corona vaccination can have various adverse effect and individuals with Meniere’s disease could have some serious audio-vestibular consequence. The study should be appreciated for including a large sample of Meniere’s disease. Following are some minor clarifications that can be addressed to improve understanding of the paper.\nIf current medication history for group is available, it could be added to the results and see if it has an interaction with these side effects.\n\nIt would be good add a justification if any for relating symptoms up to three weeks as a post vaccination adverse effect, also, some places it is given as 2.5 weeks, please clarify in the paper.\n\nThe English MD vaccination questionnaire has number of places where it is mentions “coronary vaccination”, it could be check whether it is a typo, or do they mean something else?\n\nRhinitis related aural symptoms like fullness, tinnitus, and hearing loss could it be confounder to infer the effects of vaccine on Meniere’s disease?\n\nIs there any literature on audio vestibular symptoms in general population? If so, it is worth discussing in the discussion to compare how audio-vestibular symptoms in Meniere’s population differ from general population.\n\nIt would be interesting to know why the older individuals have higher chance of audio vestibular symptoms.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "153971", "date": "14 Nov 2022", "name": "Habib Georges Rizk", "expertise": [ "Reviewer Expertise Neurotology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe study is clear and well done. There are limitations to the study and the authors acknowledge them. However the study results do give the clinician some answers to better counsel Meniere's disease patients when they ask abut the vaccination. Patients with prevaccination episodes are at higher risk to develop vertigo post vaccination\nWhat is the Finnish meniere federation and how is it different from union of Finnish meniere association?\n\nWas there a reason why the authors shows three weeks as the timeline after vaccination that they enquired about? Any literature cited that most side effects of vaccinations are typically within three weeks? If not please explain the rationale\n\nWhy did the authors lump constant vertigo and episodic vertigo together and then look at episodic vertigo only? Did they attempt to separate them like they classified the prevaccination symptoms?\n\n\"There were no gender or vaccination type effects but those with previous vertigo problems and younger adults were more likely to report vertigo-related problems.\" I don't see an odds ratio calculated with confidence intervals\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "153973", "date": "28 Nov 2022", "name": "Sun-Uk Lee", "expertise": [ "Reviewer Expertise Neurotology", "neuro-ophthalmology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors investigated the adverse reaction of COVID-19 vaccination among MD patients through a questionnaire survey. I personally read it with great interest and was convinced this report can provide a novel and robust message for neurotologists. However there are some issues that should be answered and addressed clearly.\nI believe it would be better to focus on the audiovestibular side effects. It seems more appealing considering the readership rather than reporting all the other systemic miscellaneous side effects. Otherwise, how about describing the audiovestibular side effects upfront in the result and discussion, and showing the other systemic adverse reactions in the latter section?\nIn addition, the authors cannot be sure whether those side effects come specifically from the COVID-19 vaccination or just from ‘the vaccination’, since MD patients often report aggravation of their symptoms following other vaccinations, too. I understand that this issue cannot be answered given the study design, but it should be covered in the discussion at least, and acknowledged as a limitation of this study.\nAnother major drawback of this study is that the authors associated the adverse reaction as a whole. Instead, the symptoms should be compared for each individual, not as a whole. Since MD has a episodic nature – not like other systemic symptoms that can be monophasic to occur just after vaccination --, the association cannot be decided unless those were compared for each individual. The fact that those with frequent vertigo spell also experience frequent adverse reactions indicates that it may be not because of the vaccination but rather due to uncontrolled MD, per se.\nBesides, due to its questionnaire-based study design, there may be heterogenous patients included, and the baseline nature of MD cannot be assessed, such as early vs. burnt-out, unilateral vs bilateral, which may give further information and in-depth discussion.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-893
https://f1000research.com/articles/10-1061/v1	18 Oct 21	{ "type": "Research Article", "title": "The effect of ingestion of red dragon fruit extract on levels of malondialdehyde and superoxide dismutase after strenuous exercise in rats (Rattus norvegicus)", "authors": [ "Gusbakti Rusip", "Syafrudin Ilyas", "I. Nyoman Ehrich Lister", "Chrismis N. Ginting", "Syafrudin Ilyas", "I. Nyoman Ehrich Lister", "Chrismis N. Ginting" ], "abstract": "Background: Prolonged activation of skeletal muscles causes a decrease in the production of fatigue. Exercise with strenuous intensity causes an increase in Reactive Oxygen Species (ROS). An increase in free radicals causes oxidative stress resulting in damage to cell function to mitochondrial dysfunction, and fatigue. This study aimed to determine the antioxidant potential of red dragon fruit (RDF) to delay fatigue due to oxidative stress, which improves cell function in mitochondria. Methods: 25 male rats (Rattus norvegicus) aged three months were divided into five groups: Group K1 was N.A. (No Activity) but drinking and eating; Group K2 performed strenuous exercise without RDF treatment; Groups 3, 4, and 5 (P1, P2 and P3, respectively) performed strenuous exercise and were treated with 75 mg kg-1.bw, 150 mg kg-1.bw, and 300 mg kg-1.bw of RDF extract, respectively. The exercise for the rats involved intense swimming for 20 minutes every day, four days a week for 31 days. Malondialdehyde (MDA) was measured with the ELISA and histopathology for muscle soleus and lung tissue. Results: Strenuous exercise followed by RDF extract ingestion was compared for fatigue in terms of duration and time; before (24.55±1.38 minute) and after (95.31±7.82 minute) and led to a significant difference of 39% (p<0.01). The study also compared MDA before and after RDF extract ingestion in the K2 vs. the P1 group (p<0.05). At the same time, P2 differed more significantly (p<0.01). This indicated a spread of free radicals and featured histopathological damage of muscle cells. However, ingestion of RDF extract leads to improvement of soleus muscle cells; thus, repairs cell function, delaying fatigue. Conclusion: This study confirmed that strenuous exercise, which causes an increase in ROS, intensifies free radicals with RDF extract ingestion and declines oxidative stress, repairing cell function and delaying fatigue.", "keywords": [ "Red Dragon Fruit (RDF)", "Strenuous exercise", "MDA", "Improve function cell", "Fatigue" ], "content": "Introduction\n\nIncreased frequency, intensity, and duration of regular physical exercise improves performance and delays fatigue in daily work.1,2 All living things, except those that are anaerobic, require oxygen to produce energy efficiently. Oxygen is an essential component of cellular metabolism. Exercise causes an increase in oxygen consumption by 10-12 times in the body, causing oxidative damage to the lipids of various tissues.3–7 Moderate to high-intensity exercise can result in an increase in reactive oxygen species (ROS), free radicals in the body, which is characterized by an increase in malondialdehyde (MDA), and a decrease in superoxide dismutase (SOD) which is an endogenous antioxidant to suppress excess of free radicals. Several studies showed that reactive oxygen species (ROS) formed due to tissue hypoxia during muscle contraction have an adaptive physiological role during physical exercise. Light to moderate amount of ROS is formed during moderate-intensity activities to increase endogenous antioxidants, preventing oxidative stress in the body.8,9 Oxidative stress is an imbalance between free radicals and antioxidants. Endogenous antioxidants cannot neutralize free radicals if they are formed excessively.8 Oxidative stress causes damage to muscle cells and lungs, known as oxidative damage. It is the breakdown of biomolecules that make up cells due to reactions with free radicals.10 Strenuous physical exercise will increase the growth of the free radicals found in muscle and liver tissue 2 to 3 times in experimental animals, which also will increase ROS. As a defence action, the body will be countered by the endogenous antioxidant system,11 which is known as oxidative stress. This can be seen based on the ability of antioxidants in the tissue to neutralize ROS,12 particularly the antioxidants produced by the body known as endogenous antioxidants that come from outside or exogenous antioxidants. These antioxidants come from food, such as fruit. Red dragon fruit (RDF) has been proven to protect the tissue from damage caused by ROS in the body.8,9,13 This study aimed to examine the impact of strenuous exercise on changes in MDA and SOD with RDF extract (Hylocereus polyrhizus) treatment to improve muscle and lung tissue and to delay fatigue in rats (Rattus norvegicus).\n\n\nMethods\n\nAnimal models, particularly rodents, are widely used in biological sciences, and the findings of animal research are traditionally projected to human response similar to physiological stimuli.14 This article was reported in line with the ARRIVE guidelines. The study was a randomized post-test-only control group approved by the Animal Research Ethics Committee, Department of Biology - Faculty of Mathematics and Science, Universitas Sumatera Utara (approval number 0005/KEPH-FMIPA/2020).\n\nThe subjects of this research consisted of 25 male rats (Rattus Norvegicus), aged three months with an average weight of 200 g. The subjects were obtained from the Animal House Unit of the Biology laboratory, Universitas Sumatera Utara, Medan, Indonesia. All of the subjects were sustained and maintained in groups in experimental animal cages in the laboratory. The cages were made of plastic (30 × 20 × 10 cm) and covered with fine wire mesh. The cage base was covered with rice husk as thick as 0.5-1 cm that was replaced every day during the research. The room light was controlled strictly at day and night for 12 hours, respectively. The temperature room and humidity were adjusted to a normal range of 25–27°C. The subjects were fed with standard rat pellets and provided with enough drinking water.\n\nThe experimental method in the laboratory was applied with a proper experimental design and randomized post-test-only control group. Simple random sampling was implemented with the experimental animals being divided into five groups (5 rats/group): Group K1 was N.A. (no activities) and no RDF (Negative control); Group K2 was without being treated with RDF or NRDF (No RDF) subjected to strenuous exercise (Positive control); the other three groups performed strenuous exercise and consisted of Group P1 treated with 75 mg kg−1.bw; Group P2 with 150 mg kg−1.bw; and Group P3 with 300 mg kg−1.bw of RDF extract.\n\nThe strenuous exercise given to all rats involved a morning swim between 08 – 09 AM for 20 minutes a day three times a week for four weeks.15 The rats were treated with RDF extract every day for four weeks respectively at half an hour before the strenuous exercise. All rats completed the strenuous exercise test. At the end of the study, the results were obtained in the fourth week of exercise testing until the maximum exercise was swimming until almost drowning.\n\nOne of the biomarkers of oxidative stress is a high level of malondialdehyde (MDA) and decreased SOD activity due to excessive lipid peroxidation processes in cells. One way to control excessive oxidative stress is by consuming antioxidants from food (exogenous antioxidants); one source of exogenous antioxidants is RDF, which consists of Group P1 treated with 75 mg kg−1.bw; Group P2 with 150 mg kg−1.bw; and Group P3 with 300 mg kg−1.bw of RDF extract. The consumption of RDF extract suppresses the increase in free radicals due to strenuous exercise. It increases SOD, an endogenous antioxidant, so oxidative stress does not occur, and repair mitochondrial cell function has fatigue delaying effect.\n\nThe RDF extract obtained from farmers in Indonesia was peeled, washed, cut into small pieces, and dried in the drying cabinet. Then, the fruit was blended using a blender.\n\nThe RDF extract was isolated with a maceration method using 96% ethanol, which had been distilled as much as ten times the weight of RDF. RDF powder was stored in a container with 96% ethanol (ratio 1:7, fruit powder: ethanol) and then soaked for three days. After that, the RDF powder was filtered and sealed. The RDF collected in a container was macerated and then processed with a rotary evaporator at 45°C until the extract was thickened. The same process was repeated for three days until the remaining ethanol reached 96%. The less thickened extract was then evaporated in a water bath until a thick extract of 100 mg of red dragon fruit was obtained. Then, it was gently ground using a pestle and mortar. After that, 0.5% carboxymethylcellulose (CMC) Na solution was slowly added and ground until it became homogeneous. Finally, the suspension was added to a 10 mL measuring flask until it reached the marked line. The allocation of RDF extract, a dosage of 75 mg kg−1.bw, for instance: a rat with a weight of 200 g took 1,5 ml RDF extract suspension. Dosage of 150 mg kg−1.bw was taken with 3 ml extract suspension, while the dosage of 300 mg kg−1.bw was taken with 6 ml extract suspension.\n\nThe soleus muscle and lung tissue were analysed to discover degrees of damage with Hematoxylin Eosin (H&E) staining. The muscle tissues were stored in pots filled with formalin, and then histopathology of the muscle tissues and lungs was conducted. The preparations were observed under a microscope with 400× magnification. From the microscopic picture, changes in the muscle cells and lung tissue would be able to be seen.\n\nAll of the rats completed the strenuous exercise course. They experienced maximal physical activity, i.e., swimming, until they almost drowned. Blood for MDA was taken consecutively, and the MDA was assessed with enzyme-linked immune sorbent assay (ELISA) method and spectrophotometry with a wavelength of 450 nm. The assessment was done by using Mouse Malondialdehyde Elisa Kit, Brand Bioassay TL, catalog: EO625Mo for MDA levels. The SOD level was determined using the equation obtained from the standard curve.16–18 The muscle tissue was taken through biopsy to analyze degree of degree with H&E staining.\n\nNormality was assessed with Shapiro-Wilk test (p > 0.05). Data Analysis was done by one-way analysis of variance (ANOVA) to indicate the effect of treatments for each group. The data were analysed with SPSS version 25 software and presented in tabulated and graphical forms as means and standard deviation. Significant differences were determined at p < 0.05. The Post Hoc Bonferroni test was conducted after the significant results were obtained.\n\nThe animal subjects' research was performed according to the ethical standards by the Animal Research Ethics Committees/AREC, Faculty Mathematics and Natural Sciences Universitas Sumatera Utara, Indonesia (approval number 0005/KEPH-FMIPA/2021).\n\n\nResults\n\nDuring consumption of the antioxidant RDF extract, all rats were accustomed to reducing stress-related disorders and seemed to be in good condition. No rats were poisoned, and there were no deaths in the experiment period.\n\nA normality test indicated that the data are normally distributed (Table 1).\n\nThe results of One-Way ANOVA test for groups K2, P1, P2, and P3 showed significant differences (Table 2). It is known that the measurement of MDA levels is a marker for assessing the increase in free radical production in rats treated with physical activity.\n\nMDA expression (Table 2 and Figure 1) was decreased after treatment with RDF extract (0.4191 vs 0.5471 vs 0.3120 vs 0.3159 vs 0.2531 μg/dL). The P3 group had the lowest score compared to the other groups. This study showed a significant reduction between groups. The relationship between the provision of antioxidants after treatment with RDF extract is that the administration of exogenous antioxidants helps suppress the spread of free radicals in the body because antioxidants can come from within the body (endogenous) or come from outside the body (exogenous), simultaneously suppressing free radicals due to exercise.\n\nNote: The different notation letters on the bar graph are significantly different (p < 0.05).\n\nThe study results compared the MDA of rats after ingestion of RDF extract, which was tested with the Post Hoc test - Bonferroni. In the K2 vs. P1 group, there was a significant difference of p < 0.05, the K2 vs. P2 group had a significant difference of p < 0.05, and the K2 vs. P3 group had an increased significant difference of p < 0.01.\n\nThe free radicals in the body are balanced with endogenous defence mechanisms, and the body will produce antioxidants with an anti-free radical effect. In this study, the K2 group performed physical activity and SOD levels were 0.4632 ± 0.2449 ng/mL. There was an increase in SOD levels in the K1 group (0.8647 ± 0.1744 ng/mL) that did not perform physical activity. The increase in SOD continued with RDF extract treatment in groups K1 (1.3499 ± 0.1359 ng/mL), P2 (1.9370 ± 0.0236 ng/mL) and P3 (1.9521 ± 0.0239 ng/mL). The three groups were given RDF treatment and showed significant differences (p < 0.05), analysed with the One-Way ANOVA test (Table 3 and Figure 2).\n\nNote: The different notation letters on the bar graph are significantly different (p < 0.05).\n\nThe histopathological examination were observed under a microscope. It was seen that in group K1 changes in muscle and lung tissue did not occur. Ingroup K2 the changes were very significant, and many inflammatory cells and necrosis were observed in both the muscles and lungs. In contrast to P1, the P2 and P3 groups showed a decrease in inflammatory cells. In addition, in these two groups compared to P1, the lungs in the intra-alveolar and the alveolar sacs were dilated, and tissue repair was shown by the hyalinization process. Results showed changes in free radicals that could damage tissue in the positive control group K2. In contrast, the histopathological features of the P1, P2, P3 groups showed lung tissue and muscle cell repair, after being given RDF (Figures 3 and 4).\n\nArrow yellow: inflammatory cells, Arrow red: necrosis.\n\nNote: Red arrow = inflammatory cells; SIA = interalveolar septum, KA = alveolar sac.\n\n\nDiscussion\n\nFree radicals in the skeletal muscles cause muscle fatigue. The free radicals significantly reduce muscle strength, contributing to muscle fatigue during prolonged training.7,19,20 The role of oxidants in muscle fatigue has been investigated in various animal models in vitro and situ during exercise. Oxidants are detectable in muscle at low levels during rest and at higher levels during contractions. RNS depress force production but do not appear to cause fatigue of healthy muscle. In contrast, muscle-derived ROS contribute to fatigue because loss of function can be delayed by ROS-specific antioxidants.21–23 A study showed that exogenous antioxidants derived from food to capture ROS slowed down muscle fatigue, and enzymatic and nonenzymatic antioxidants delayed muscle fatigue during contraction. In the study, the subject characteristics have been standardized in accordance with WHO, adjusted to the provisions of the criteria24–26 in the Research Guideline for Evaluating the Safety and Efficacy of Herbal Medicines.\n\nIn skeletal muscles, antioxidants are enzymatic (e.g., Glutathione peroxidase (GPx) and catalase) and nonenzymatic (for example, GSH, uric acid, bilirubin, vitamin E, vitamin C, etc.) function as an integrated antioxidant complex that acts to capture ROS.27,28 These intracellular antioxidants are usually present in cells, cytoplasm, and organelles (for example, mitochondria) whose role is to protect muscle fibres from damage caused by ROS.27,29–31 Endogenous free radicals are formed as a normal response to the chain reaction of respiration in the body. The free radicals in the body are balanced by an endogenous defence system mechanism,32 in which the body produces antioxidants that have an anti-free radical effect. One of the endogenous antioxidants is SOD, which is the body's first line of defence against ROS activation.8 When the level of ROS rises beyond the endogenous defence capacity, oxidative instability, known as oxidative stress, occurs.9,29 Oxidative stress conditions due to free radicals will cause lipid peroxidation of cell membranes and damage cell membrane organization. One of the biomarkers of oxidative stress is a high level of MDA33 and decreased SOD activity due to excessive lipid peroxidation processes in cells.9 One way to control excessive oxidative stress is by consuming antioxidants from food (exogenous antioxidants).34 One source of exogenous antioxidants is RDF that can be found in Indonesia.\n\nIn this study, the endogenous antioxidants in the body were superoxide dismutase (SOD), and they are unable to neutralize free radicals. This condition results in an imbalance of free radicals and antioxidants, leading to oxidative damage, as reported in previous studies.35 Unstabilized oxidative stress produces free radicals, which can damage muscle tissue and lungs and cause impaired cell function, which is involved in muscle fatigue. RDF treatment can increase SOD significantly (P < 0.05) and function as a good source of several natural antioxidants, such as betalain, polyphenols, and ascorbic acid, as evidenced in previous studies.36,37 During strenuous exercise, the increase in ROS formation during contractile activity is directly related to increased oxygen consumption. This condition results in a 50 or 100 fold increase in mitochondrial activity in the formation of superoxide in skeletal muscle during aerobic contraction.38,39 An increase in oxidative stress, as observed, leads to an increase in lipid peroxidation accompanied by a decline in SOD level activity, as the antioxidants are given depending on the dose affect the increase in SOD levels.28 This improvement in oxidative status suggests that the natural antioxidants in the extract with high doses were responsible for delaying fatigue in this study, as reported in previous studies.40,41 In this study, it was found that the higher the dose given, the greater the SOD, as shown in group P3 that was on treatment so that this SOD level could neutralize free radicals. The SOD enzyme is the first defence system against free radicals. Thus, moderate-intensity regular exercise has been shown to increase antioxidant defences by increasing the activity of endogenous antioxidant enzymes, such as SOD, glutathione peroxidase, and catalase.42,43 These enzymes can suppress or inhibit the formation of free radicals by breaking the chain reaction so that the product is more stable. This process is known as the antioxidant chain-breaking reaction.\n\nRDF is rich in antioxidants, such as phenol and flavonoid compounds. Phenolic compounds that function as antioxidants neutralize free radicals and peroxide radicals to inhibit lipid oxidation effectively. Flavonoids are exogenous antioxidants that are beneficial in preventing cell damage due to oxidative stress. Its role is to donate hydrogen ions to neutralize the toxic effects from free radicals due to exercise. RDF consumption can also increase the VO2max value.44\n\nAnthocyanin is one type of flavonoid widely found in dragon fruit,45 which is able to improve mitochondrial function by influencing free radicals. Anthocyanins can suppress the occurrence of lipid peroxidation as an inflammatory response due to free radicals, thereby suppressing the production of MDA.46\n\nAn increase in the free radicals in the body causes an imbalance between oxidants and antioxidants. This condition leads to oxidative stress. The earliest known and widely studied cell or tissue mechanism is lipid peroxidation. RDF extract contains anthocyanin pigments which function as antioxidants.18,47,48 Anthocyanins can play a role in inhibiting free radicals that occur due to strenuous exercise. This study examined the provision of RDF extract comprising anthocyanins, one of the types contained in flavonoids, which provides a response to inflammation in the muscles and lung tissue. The presence of anthocyanins repairs damaged tissue so that physiological mitochondrial function returns, as anthocyanins can suppress the occurrence of lipid peroxidation and suppress MDA production so that MDA levels decrease.49,50 Anthocyanins can quickly bind metal ions to form a stable anthocyanin-metal complex. This means that anthocyanins bind to the transitioned ion metal to prevent highly toxic and reactive hydroxyl reactions. In the end, anthocyanins can suppress lipid peroxidation and suppress MDA production to reduce MDA levels.\n\n\nConclusions\n\nStrenuous exercise causes an increase in ROS, resulting in increased free radical levels, leading to oxidative stress to occur. Ingesting RDF extracts suppresses the increase. The group that was given RDF doses of 150 mg, and 300 mg performed better than the group with a dose of 75 mg in responding to oxidative stress with strenuous exercise. RDF extract dose resulted in decreased oxidative stress, repaired muscle and lung tissue, so that cell function returned physiologically, which delayed fatigue.\n\n\nData availability\n\nFigshare: Datasets, https://doi.org/10.6084/m9.figshare.15074544.v5.51\n\nThis project contains the following underlying data:\n\n- MDA RAT.xls ( MDA levels for all groups)\n\n- SOD RAT 23 Maret 21.xls (SOD levels for all groups)\n\n- Table HEnew.docx (scoring for microscopy results)\n\nFigshare: ARRIVE checklist for ‘The effect of ingestion of Red dragon fruit extract on levels of malondialdehyde and superoxide dismutase after strenuous exercise in rats (Rattus norvegicus)’, https://doi.org/10.6084/m9.figshare.15074544.v5.51\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nGruet M, Temesi J, Rupp T, et al.: Stimulation of the motor cortex and corticospinal tract to assess human muscle fatigue. Neurosci. 2013; 231: 384–399. PubMed Abstract \| Publisher Full Text\n\nTaylor JL, Amann M, Duchateau J, et al.: Neural Contributions to Muscle Fatigue: From the Brain to the Muscle and Back Again.2016; 48: 2294–2306. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDillard CJ, Litov RE, Savin WM, et al.: Effects of exercise, vitamin E, and ozone on pulmonary function and lipid peroxidation. J. Appl. Physiol. Respir. Environ. Exerc. Physiol. 1978; 45(6): 927–932. PubMed Abstract \| Publisher Full Text\n\nViña J, Gomez-Cabrera MC, Lloret A, et al.: Free radicals in exhaustive physical exercise: Mechanism of production, and protection by antioxidants. IUBMB Life. 2000; 50(4-5): 271–277. Publisher Full Text\n\nDekkers JC, Van Doornen LJP, Kemper HCG: The role of antioxidant vitamins and enzymes in the prevention of exercise-induced muscle damage. Sports Med. 1996; 21(3): 213–238. PubMed Abstract \| Publisher Full Text\n\nHalliwell B, Gutteridge JM:Celullar respons to oxidative stress: adaptation damage repair, senescence and death.Halliwell B, Gutteridge JM, editors. Free Radicals in Biology and Medicine. Oxford University Press;5 th ed.2015; 254–338. Publisher Full Text\n\nMoopanar TR, Allen DG: Reactive oxygen species reduce myofibrillar Ca2+ sensitivity in fatiguing mouse skeletal muscle at 37°C. J. Physiol. 2005; 564(1): 189–199. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGomez-Cabrera M, Domenech E, Viña J: Moderate exercise is an antioxidant: Upregulation of antioxidant genes by training. Free Radic. Biol. Med. 2008; 44: 126–131. PubMed Abstract \| Publisher Full Text\n\nBerzosa C, Cebrián I, Fuentes-Broto L, et al.: Acute exercise increases plasma total antioxidant status and antioxidant enzyme activities in untrained men. J. Biomed. Biotechnol. 2011; 2011: 1–7. Publisher Full Text\n\nKregel KC, Zhang HJ: An integrated view of oxidative stress in aging: Basic mechanisms, functional effects, and pathological considerations. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2007; 292(1): R18–R36. Publisher Full Text\n\nAtsumi T, Iwakura I, Kashiwagi Y, et al.: Free radical scavenging activity in the nonenzymatic fraction of human showing saliva: A Simple D P P H assay the effect of Physical exercise. Antioxid. Redox Signal. 1999; 1(4): 537–546. PubMed Abstract \| Publisher Full Text\n\nWilson DO, Johnson P: Exercise modulates antioxidant enzyme gene expression in rat myocardium and liver. J. Appl. Physiol. 2000; 88: 1791–1796. PubMed Abstract \| Publisher Full Text\n\nRimbach G, Hohler D, Fischer A, et al.: Methods to assess free radicals and oxidative stress in biological system. ArchAnimNutr. 1999; 52(August 2013): 203–222. Publisher Full Text\n\nGoutianos G, Tzioura A, Kyparos A, et al.: The rat adequately reflects human responses to exercise in blood biochemical profile: A comparative study. Physiol. Rep. 2015; 3(2): e12293. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSchwiebert R, Ang J, Chang C: The Laboratory Mouse - Breeding. Singapore:NUS;2007; Schwiebert, R., Ang, J. & Chang, C. (2007) The Laboratory Mouse - Breeding. Singapore, NUS, Singapore, NUS.\n\nStathopulos PB, Rumfeldt JAO, Karbassi F, et al.: Calorimetric analysis of thermodynamic stability and aggregation for Apo and Holo amyotrophic lateral sclerosis-associated Gly-93 mutants of superoxide dismutase. J. Biol. Chem. 2006; 281(10): 6184–6193. Publisher Full Text\n\nSentman ML, Granström M, Jakobson H, et al.: Phenotypes of mice lacking extracellular superoxide dismutase and copper- and zinc-containing superoxide dismutase. J. Biol. Chem. 2006; 281(11): 6904–6909. Publisher Full Text\n\nJaafar RA, Abdul Rahman ARB, Mahmod NZC, et al.: Proximate analysis of dragon fruit (hylecereus polyhizus). Am. J. Appl. Sci. 2009; 6(7): 1341–1346. Publisher Full Text\n\nVasilaki A, Mansouri A, Van Remmen H , et al.: Free radical generation by skeletal muscle of adult and old mice: effect of contractile activity. Aging Cell. November 2005; 5: 109–117. PubMed Abstract \| Publisher Full Text\n\nRichardson RS, Noyszewski EA, Kendrick KF, et al.: Myoglobin O2 desaturation during exercise: Evidence of limited O2 transport. J. Clin. Invest. 1995; 96(4): 1916–1926. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFerreira LF, Reid MB: Muscle-derived ROS and thiol regulation in muscle fatigue. J. Appl. Physiol. 2008; 104(3): 853–860. PubMed Abstract \| Publisher Full Text\n\nKozlov AV, Szalay L, Umar F, et al.: Skeletal muscles, heart, and lung are the main sources of oxygen radicals in old rats. Biochim. Biophys. Acta Mol. basis Dis. 2005; 1740(3): 382–389. PubMed Abstract \| Publisher Full Text\n\nReid MB, Haack KE, Franchek KM, et al.: Reactive oxygen in skeletal muscle. I. Intracellular oxidant kinetics and fatigue in vitro. J. Appl. Physiol. 1992; 73(5): 1797–1804. PubMed Abstract \| Publisher Full Text\n\nWHO: Research Guidelines for Evaluating the Safety and Efficacy of Herbal Medicine. 1993.\n\nWHO: General Guidelines for Methodologies on Research and Evaluation of Traditional Medicine World Health Organization. Geneva:WHO;2000.\n\nWHO: WHO Guidelines on Good Manufacturing Practice (GMP) for Herbal Medicine. 2007.Reference Source\n\nPowers SK, Ji LL, Kavazis AN, et al.: Reactive oxygen species: Impact on skeletal muscle. Compr. Physiol. 2011; 1(April): 941–969. Publisher Full Text\n\nKayode OT, Kayode AAA, Nwonuma CO: Alcoholic bitters modulates sex hormones and some biochemical parameters of testicular function in male wistar rats [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Res. 2018; 7: 1–9. Publisher Full Text\n\nPowers SK, Jackson MJ: Exercise-induced oxidative stress: Cellular mechanisms and impact on muscle force production. Physiol. Rev. 2008; 88(4): 1243–1276. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKurepa J, Shull TE, Smalle JA: Quercetin feeding protects plants against oxidative stress. F1000Res. 2016; 5(May): 2430. Publisher Full Text\n\nHubert SM, Athrey G: Energy metabolism and sources of oxidative stress in wooden breast - a review [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Res. 2020; 9(319): 1–15. Publisher Full Text\n\nNovita Sari H, Amelia R: Red dragon fruit (hylocereus polyrhizus) extract decreases lactic acid level and creatine kinase activity in rats receiving heavy physical exercise. Open Access Maced J Med Sci. 2019; 7(14): 2232–2235. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTsikas D: Assessment of lipid peroxidation by measuring malondialdehyde (MDA) and relatives in biological samples: Analytical and biological challenges. Anal. Biochem. 2017; 524: 13–30. PubMed Abstract \| Publisher Full Text\n\nReid MB: Redox modulation of skeletal muscle contraction: what we know and what we don’t. J. Appl. Physiol. 2001; 90(Feb): 724–731. PubMed Abstract \| Publisher Full Text\n\nCaramori G, Papi A: Oxidants and asthma. Thorax. 2004; 59(2): 170–173. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMachha A, Achike FI, Mustafa AM, et al.: Quercetin, a flavonoid antioxidant, modulates endothelium-derived nitric oxide bioavailability in diabetic rat aortas. Nitric Oxide Biol. Chem. 2007; 16(4): 442–447. PubMed Abstract \| Publisher Full Text\n\nWoo KK, Ngou FH, Ngo LS, et al.: Stability of betalain pigment from red dragon fruit (Hylocereus polyrhizus). Am. J. Food Technol. 2011; 6(2): 140–148. Publisher Full Text\n\nKarazis A, Powers S: Impact of exercise, reactive oxygen and reactive nitrogen species on tumor growth. Exerc Energy Balanc Cancer. 2013; 1–239. Publisher Full Text\n\nKang SW, Rhee SG, Chang TS, et al.: 2-Cys peroxiredoxin function in intracellular signal transduction: Therapeutic implications. Trends Mol. Med. 2005; 11(12): 571–578. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAnand Swarup KRL, Sattar MA, Abdullah NA, et al.: Effect of dragon fruit extract on oxidative stress and aortic stiffness in streptozotocin-induced diabetes in rats. Pharm. Res. 2010; 2(1): 31–35. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSumardika IW, dan Jawi IM : Department of Pharmacology, Medical School, Udayana University. J Ilm Kedokt Med. 2014; 36(September): 19–24.Reference Source.\n\nGusbakti R, Mukti SS: Effects of moderate intensity exercise on glutathione peroxidase activity and VO 2 max in elderly women. Maced J Med Sci. 2020; 8((A)(25)): 230–233. Publisher Full Text\n\nMiyata M, Kasai H, Kawai K, et al.: Changes of urinary 8-hydroxydeoxyguanosine levels during a two-day ultramarathon race period in Japanese non-professional runners. Int. J. Sports Med. 2008; 29: 27–33. Publisher Full Text\n\nPrakoso LO, Yusmaini H, Thadeus MS, et al.: Perbedaan efek ekstrak buah naga merah (Hylocereus polyrhizus) dan ekstrak buah naga putih (Hylocereus undatus) terhadap kadar kolesterol total tikus putih (Rattus norvegicus). J Gizi dan Pangan. 2017; 12(3): 195–202. Publisher Full Text\n\nJamilah B, Shu CE, Kharidah M, et al.: Physico-chemical characteristics of red pitaya (hylocereus polyrhizus) peel. Int. Food Res. J. 2011; 18(1): 279–286.Reference Source.\n\nMiguel MG: Antioxidant activity of medicinal and aromatic plants. A review. Flavour. 2009; 25(November): 291–312. Publisher Full Text\n\nStintzing FC, Carle R: Functional properties of anthocyanins and betalains in plants, food, and in human nutrition. Trends Food Sci. Technol. 2004; 15(1): 19–38. Publisher Full Text\n\nWu LC, Hsu HW, Chen YC, et al.: Antioxidant and antiproliferative activities of red pitaya. Food Chem. 2006; 95(2): 319–327. Publisher Full Text\n\nHarahap NS, Lelo A, Purba A, et al.: The effect of red-fleshed pitaya (Hylocereus polyrhizus) on heat shock protein 70 and cortisol expression in strenuous exercise induced rats [version 1; peer review: 1 approved with reservations]. F1000Res. 2019; 8: 1–12. Publisher Full Text\n\nSingh G, Pachouri UC, Khaidem DC, et al.: Mitochondrial DNA Damage and Diseases. F1000Res. 2015; 4: 176–177. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRusip G: Datasets. figshare. Dataset. 2021. Publisher Full Text" }	[ { "id": "127975", "date": "29 Mar 2022", "name": "Farzaneh Taghian", "expertise": [ "Reviewer Expertise Sport and nutrition" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe author evaluated the effect of ingestion of red dragon fruit extract on levels of malondialdehyde and superoxide dismutase after strenuous exercise in rats. I think this study was informative and practical.\nHowever, there are some comments to improve this study:\nIn the Introduction section explain red dragon fruit in detail.\n\nThe grouping is not clear. Describe it. What is N, A, or RDF? Completely explain the grouping.\n\nStudy design is not suitable. The author has to explain the standard condition of the rats and grouping.\n\nWrite the commercial name of the kits, catalog number.\n\nThe grammar and writing is poor\n\nWrite the protocol of Hematoxylin Eosin (H&E) staining\n\nThe quality of the image is poor.\n\nIs the work clearly and accurately presented and does it cite the current literature? No\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [ { "c_id": "8055", "date": "07 Apr 2022", "name": "Prof Gusbakti Rusip", "role": "Author Response", "response": "We would like to thank the reviewer for the time and willingness to assess the quality of our manuscript. In the new version of our manuscript, suggested changes in all sections have been added according to the reviewer’s recommendation. It has been a great delight to receive your very nice and professional comments. Kindest regards, Prof Dr Gusbakti Rusip, MD, Sp.KKLP,AIFM, Department Physiology, University Prima Indonesia Introduction: One source of natural antioxidants is red dragon fruit peel (Hylocereus polyrhizus). Red dragon fruit peel (1 mg/kg) can inhibit 83.48% of free radicals. Red dragon fruit peels has antioxidant activity (IC50 = 43,836 microgram/mL). The antioxidants of red dragon fruit peel are higher than in its flesh. Red dragon fruit peel contains natural antioxidant compounds in phenolic or polyphenolic. It has antioxidant activity of flavones, flavonols, isoflavones, catechins and kalkon. Red dragon fruit peel also contains betacyanin. Betacyanin is part of the pigment betalains and has antioxidant properties (neutralizing free radicals). Betacyanin of red dragon fruit peel including phenolic compounds. Phenolic derivatives or polyphenols (as antioxidants) stabilize free radicals by supplementing lack of electrons possessing free radicals and inhibiting the occurrence of chain reactions from free radical formation. Methods and Materials: In this study, we used 25 three-month-old male rats with an average weight of 200 g. The rats were obtained from the Animal House Unit of the Biology Laboratory, Universitas Sumatera Utara, Indonesia. All rats were maintained in groups in experimental animal cages in the laboratory. The cage (30 cm,20 cm, 10 cm) was made of plastic and covered with fine wire mesh. The cage base was covered with rice husks with a thickness of 0.5–1 cm, which was replaced every day during the study. The room light was controlled to deliver a 12 h light/12 h dark cycle, the temperature was set to 25–27 °C, and the room's humidity was adjusted to a normal range of 35–50%. The rats were fed standard rat pellets and given tap water ad libitum. Design study: We used an in vitro experimental method with a true experimental design and a randomised post-test for the control group. Simple random sampling was used to categorise the laboratory rats into five groups as follows: group K1 with no activity and no RDF; group K2 subjected to strenuous exercise without RDF (Red Dragon Fruit); and groups P1, P2, and P3 subjected to strenuous exercise and treated with 75, 150, and 300 mg kg−1 body weight of RDF extract, respectively. It is easy to find RDF in the fruit market, acquired from farmers in Indonesia, peeled, washed, cut into small pieces, and then dried in a drying cabinet. Next, the fruit was blended using a blender, and the extract was obtained by the maceration method with 96% ethanol, which was distilled by 10 times the weight of RDF. The RDF powder was stored in a container with 96% ethanol (ratio of 1:7, fruit powder: ethanol) and then soaked for 3 d. The RDF was macerated using a rotary evaporator at 45 °C until the extract thickened. The macerated RDF was extracted using 96% ethanol. The remaining extract was then evaporated in a water bath until a thick extract was obtained. Next, 100 mg RDF extract was weighed and crushed using a pestle and mortar. Subsequently, carboxymethylcellulose Na solution (0.5% w/v) was slowly added until a homogeneous extract was obtained, and the resulting volume was 10 mL. This final RDF extract was administered to the rats at appropriate dosages; specifically, rats weighing 200 g were fed 1.5, 3.0, or 6.0 mL of the RDF extract suspension, which corresponded to doses of 75, 150, or 300 mg kg−1 body weight, respectively. Analysis of blood samples: rats performed strenuous exercise until they reached their maximum effort (i.e., swimming until they almost drowned). At this time, blood samples were sequentially taken to analyse malondialdehyde (MDA) and SOD using the enzyme-linked immune sorbent assay (ELISA) method with spectrophotometry at a wavelength of 450 nm. The mouse malondialdehyde ELISA kit (Brand Bioassay TL, catalog: EO625Mo) was used to analyse the MDA levels. The SOD kit ( Brand Bioassay TL, catalog: EO168Ra) Rat super Oxidase Dimutase ELISA kit was determined using the equation obtained from the standard curve. Histopathological study muscle and lung tissue samples were collected by performing a biopsy to determine the degree of muscle damage based on haematoxylin and eosin (H&E) staining. The soleus muscle tissues of the rats were collected and fixed with 10% formalin for 24 h. The muscle and lung tissues were embedded in paraffin, sectioned to a 4 μm thickness, and stained via H&E staining. The stained sections were then examined under a light microscope (400X magnification) with 10 fields of view to determine the degree of damage concerning inflammatory cells and necrosis. The examination was conducted by a pathologist blinded to the applied treatment." } ] }, { "id": "137352", "date": "07 Jun 2022", "name": "Ermita I. Ibrahim Ilyas", "expertise": [ "Reviewer Expertise Exercise Physiology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis study was quite informative. There are some suggestions to improve this article:\nThe title should be in accordance with the result of the study.\n\nAbstract should be rewritten since there were information missed in the methods, results and conclusion. Please refer to the main body of the manuscript.\n\nThe introduction also needs to be rewritten to make it clear, focused and concise to the aim of the study. Authors have to provide a comprehensive description\nMethods:\nStudy design has to explain the grouping of the rats with proper terms.\n\nExperimental procedures in the main manuscript were different than in the abstract.\n\nOutcome: authors mentioned about repair mitochondrial cell function has fatigue delaying effect. However, authors did not analyse or measure the mitochondria function and fatigue duration and time.\nResults:\nWrite complete legends of the figures including clear explanation of the sign.\n\nExplain how to determine the improvement of lung and muscle cells (histopathological change in muscle and lung tissue) in the rats supplemented by RDF.\n\nHow to determine the fatigue? Authors mentions the fatigue delay with no data showing this.\nDiscussion:\nRewrite to make it systematic, focused and clear to provide a comprehensive report.\nConclusion:\nMy answer to the question, \"Are the conclusions drawn adequately supported by the results?\" is 'No' because the conclusion of the manuscript was not written adequately from the result of the study. My suggestion is that they have to write the conclusion based on all the parameters they analyzed.\n\nConclusion in the abstract: \"This study confirmed that strenuous exercise that causes an increase in ROS intensifies free radicals with RDF extract ingestion and declines stress oxidative, repairing cell function and delaying fatigue.\"\n\nMy suggestion for Conclusion in the abstract:\n\"This study confirmed that strenuous exercise causes an increase in ROS intensifies free radicals shown by MDA increase and SOD decrease, and with RDF extract ingestion MDA decrease and SOD increase showed RDF declines stress oxidative, and 300 mg kg-1.bw of RDF extract showed better result compared to other doses. The decrease of oxidative stress, showed improvement of muscle and lung tissue injuries.\"\n\nConclusion in the main body of the manuscript: \"Strenuous exercise causes an increase in ROS, resulting in increased free radical levels, leading to oxidative stress to occur. Ingesting RDF extracts suppresses the increase. The group was given RDF doses of 150 mg, and 300 mg performed better than 75 mg in responding to oxidative stress with strenuous exercise. This condition results in decreased oxidative stress, repaired muscle and lung tissue, so that cell function returned physiologically, which delayed fatigue.\"\nMy suggestion for Conclusion in the main body of manuscript: \"Strenuous exercise causes an increase in ROS, resulting in increased free radical levels, leading to oxidative stress to occur shown by MDA increase and SOD decrease. Ingesting RDF extracts suppresses the increase of oxidative stress. The group that was given RDF doses of 150 mg and 300 mg performed better than 75 mg in responding to oxidative stress. The decrease of oxidative stress, showed improvement of muscle and lung tissue injuries.\"\n\nNote:\n\nThe manuscript's language and grammar should undergo a thorough proofreading.\n\nAuthors should rewrite the manuscript based on reviewer’s suggestions.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [ { "c_id": "8405", "date": "30 Jun 2022", "name": "Prof Gusbakti Rusip", "role": "Author Response", "response": "It has been a great sense of delight to receive your very friendly and professional comments. We want to thank the reviewer for the time and willingness to assess the quality of our manuscript. In the new version, our manuscript suggested changes in all sections have been added according to the reviewer's recommendation. Kindest regards, Prof Dr Gusbakti Rusip, MD, Sp.KKLP, AIFM, Department Physiology, University Prima Indonesia Introduction One source of natural antioxidants is red dragon fruit peel (Hylocereus polyrhizus). Red dragon fruit peel (1 mg/kg) is able to inhibit 83.48% of free radicals. Red dragon fruit peels has antioxidant activity (IC50 = 43,836 microgram/mL). The antioxidant of red dragon fruit peel is higher than its flesh. Red dragon fruit peel contains a natural antioxidant compound of phenolic or polyphenolic. It has antioxidant activity of flavones, flavonols, isoflavones, catechins and kalkon. Red dragon fruit peel also contains betacyanin. Betacyanin is part of the pigment betalains and has antioxidant properties (neutralizing free radicals). Betacyanin of red dragon fruit peel, including phenolic compounds. Phenolic derivatives or polyphenols (as antioxidants) stabilize free radicals by supplementing lack of electrons possessing free radicals and inhibiting the occurrence of chain reactions from free radical formation. Methods and materials In this study, we used 25 three-month-old male rats with an average weight of 200 g. The rats were obtained from the Animal House Unit of the Biology Laboratory, Universitas Sumatera Utara, Indonesia. All rats were maintained in groups in experimental animal cages in the laboratory. The cage (30 cm, 20 cm, 10 cm) was made of plastic and covered with fine wire mesh. The cage base was covered with rice husks with a thickness of 0.5–1 cm, which was replaced daily during the study. The room light was controlled to deliver a 12h light/12h dark cycle, the temperature was set to 25–27 °C, and the room's humidity was adjusted to a normal range of 35–50%. The rats were fed standard rat pellets and given tap water ad libitum. Design study We used an in vitro experimental method with an actual experimental design and a randomised post-test for the control group. Simple random sampling was used to categorise the laboratory rats into five groups as follows: group K1 with no activity and no RFP; group K2 subjected to strenuous exercise without RDF (Red Dragon Fruit); and groups P1, P2, and P3 subjected to strenuous exercise and treated with 75, 150, and 300 mg kg−1 body weight of RDF extract, respectively. In the fruit market, it is easy to find RFP fruit acquired from farmers in Indonesia, peeled, washed, cut into small pieces, and then dried in a drying cabinet. Next, the fruit was blended using a blender, and the extract was obtained by the maceration method with 96% ethanol, which was distilled by ten times the weight of RDF. The RDF powder was stored in a container with 96% ethanol (ratio of 1:7, fruit powder: ethanol) and then soaked for 3 d. The RDF was macerated using a rotary evaporator at 45 °C until the extract thickened. The macerated RDF was extracted using 96% ethanol. The remaining extract was evaporated in a water bath until a thick extract was obtained. Next, 100 mg RDF extract was weighed and crushed using a pestle and mortar. Subsequently, carboxymethylcellulose Na solution (0.5% w/v) was slowly added until a homogeneous extract was obtained, and the resulting volume was 10 mL. This final RFP extract was administered to the rats at appropriate dosages; specifically, rats weighing 200 g were fed 1.5, 3.0, or 6.0 mL of the RFP extract suspension, corresponding to doses of 75, 150, or 300 mg kg−1 body weight, respectively. Analysis of blood samples All rats performed strenuous exercise until they reached their maximum effort (i.e., swimming until they almost drowned). At this time, blood samples were sequentially taken to analyse malondialdehyde (MDA) and SOD using the enzyme-linked immune sorbent assay (ELISA) method with spectrophotometry at a wavelength of 450 nm. The mouse malondialdehyde ELISA kit (Brand Bioassay TL, catalog: EO625Mo) was used to analyse the MDA levels. The SOD kit (Brand Bioassay TL, catalog: EO168Ra) Rat super Oxidase Dismutase ELISA kit was determined using the equation obtained from the standard curve. Histopathological study Muscle and lung tissue samples were collected by performing a biopsy to determine the degree of muscle damage based on haematoxylin and eosin (H&E) staining. The soleus muscle tissues of the rats were collected and fixed with 10% formalin for 24 h. The muscle and lung tissues were embedded in paraffin, sectioned to a 4 μm thickness, and stained via H&E staining. The stained sections were then examined under a light microscope (400' magnification) with 10 fields of view to determine the degree of damage concerning inflammatory cells and necrosis. The examination was conducted by a pathologist who was blinded to the applied treatment." }, { "c_id": "8406", "date": "28 Jun 2022", "name": "Prof Gusbakti Rusip", "role": "Author Response", "response": "We would like to thank the reviewer for the time and willingness to assess the quality of our manuscript. In the new version, the suggested changes in all sections have been added according to the reviewers recommendation. It has been a great sense of delight to receive your very nice and professional comments. Kindest regards, Prof Dr Gusbakti Rusip, MD, Sp.KKLP,AIFM, Department Physiology, University Prima Indonesia The title should be in accordance with the result of the study. We agree that we have adjusted the results of the study. Abstract should be rewritten since there were information missed in the methods, results and conclusion. Please refer to the main body of the manuscript. The manuscript has been revised and has been completed. The introduction also needs to be rewritten to make it clear, focused and concise to the aim of the study. Authors have to provide a comprehensive description. The manuscript has been revised and has been completed. Methods: Study design has to explain the grouping of the rats with proper terms. Experimental procedures in the main manuscript were different than in the abstract. It has been revised according to the research objectives and has been perfected. Outcome: authors mentioned about repair mitochondrial cell function has fatigue delaying effect. However, authors did not analyse or measure the mitochondria function and fatigue duration and time. Mitochondrial function analysis has not been analyzed, the research is in progress. Results: Write complete legends of the figures including clear explanation of the sign. We have fixed it in the revised article. Explain how to determine the improvement of lung and muscle cells (histopathological change in muscle and lung tissue) in the rats supplemented by RDF. Monitoring the repair of muscle and lung cells seen from the number of inflammatory cells and necrosis then examined under a light microscope (400x magnification) with ten fields of view to ascertain the degree of damage with respect to inflammatory cells and necrosis seen in Fig share table HE. How to determine the fatigue? Authors mentions the fatigue delay with no data showing this. The results of this study are that we write down the time of fatigue before and after giving Red Dragon Fruit after we have entered the data on the results of the comparison. Discussion: Rewrite to make it systematic, focused and clear to provide a comprehensive report. We have systematically improved and completed several discussions for the perfection of the article. Conclusion: My answer to the question, \"Are the conclusions drawn adequately supported by the results?\" is 'No' because the conclusion of the manuscript was not written adequately from the result of the study. My suggestion is that they have to write the conclusion based on all the parameters they analyzed. We have adjusted the conclusion to the topic, we found the results of our research." } ] } ]	1	https://f1000research.com/articles/10-1061
https://f1000research.com/articles/11-892/v1	04 Aug 22	{ "type": "Research Article", "title": "Managing the effect of magnetic resonance imaging pulse sequence on radiomic feature reproducibility in the study of brain metastases", "authors": [ "Drew Mitchell", "Samantha Buszek", "Benjamin Tran", "Maguy Farhat", "Jodi Goldman", "Lily Erickson", "Brandon Curl", "Dima Suki", "Sherise D. Ferguson", "Ho-Ling Liu", "Suprateek Kundu", "Caroline Chung", "Drew Mitchell", "Samantha Buszek", "Benjamin Tran", "Maguy Farhat", "Jodi Goldman", "Lily Erickson", "Brandon Curl", "Dima Suki", "Sherise D. Ferguson", "Ho-Ling Liu", "Suprateek Kundu" ], "abstract": "Background: Despite the promise of radiomics studies, their limited reproducibility has hindered meaningful clinical translation. Variability in study designs as well as image acquisition and processing contribute to unreproducible radiomic results. This work’s purpose was to (i) quantitatively compare variability of radiomic features extracted from 2-D spin echo (SE) and 3-D spoiled gradient echo (SPGR) T1-weighted post-contrast magnetic resonance (MR) images of brain metastases acquired within the same patient in a single imaging session, and (ii) provide a framework to inform data acquisition for reproducible radiomics studies. Methods: A retrospective cohort of 29 patients with pathologically-confirmed brain metastases and contrast-enhanced T1-weighted MR images acquired using 2-D SE and 3-D SPGR sequences within one exam was identified. Metastases were segmented twice by different physicians using semi-automated methods. Radiomic features were extracted using PyRadiomics for 264 preprocessing variable combinations. Lin’s concordance correlation coefficient (CCC) was computed between features extracted from images acquired by both pulse sequences and different tumor segmentations. Results: We provided general recommendations to improve MR-based radiomic feature reproducibility by clustering and identifying low-concordance features and processing variables. Median CCC between 2-D SE and 3-D SPGR (measuring feature agreement between pulse sequences) was greater for fixed bin count intensity discretization (0.76 versus 0.63) and specific high-concordance features (0.74 versus 0.53). Applying all recommendations improved median CCC from 0.51 to 0.79. Median CCC between contours (measuring feature sensitivity to inter-observer variability) was higher for 2-D SE (0.93 versus 0.86) but improved to 0.93 for 3-D SPGR after low-concordance feature exclusion. Conclusions: The following recommendations are proposed to improve reproducibility: 1) Fixed bin count intensity discretization for all studies, 2) for studies with 2-D and 3-D datasets, excluding high-variability features from downstream analyses, 3) when segmentation is manual or semi-automated, using only 2-D SE images or excluding features susceptible to segmentation variability.", "keywords": [ "Magnetic resonance imaging", "radiomics", "reproducibility", "brain metastases" ], "content": "Introduction\n\nIt is estimated that 20% of cancer patients develop brain metastases, and prognosis following metastasis to the brain is generally poor.1 Surgical resection, whole-brain radiation therapy, and stereotactic radiosurgery are the most prevalent treatments and are necessary to extend survival, preserve neurologic function, and provide palliative care.2 Magnetic resonance imaging (MRI) plays a critical role in the diagnosis and treatment of brain metastases. Several different pulse sequences are routinely employed in the detection and monitoring of brain metastases, and their effectiveness for these purposes has been the subject of several studies.3–6 In particular, post-contrast T1-weighted images can be acquired in a number of ways, commonly including 2-D conventional spin echo (SE) and 3-D spoiled gradient echo (SPGR). Generally, 2-D SE acquisitions provide images with better lesion conspicuity, whereas SPGR can be acquired more easily with thin slices in 3-D, allowing better detection of small metastases.7 A recent consensus recommendation for imaging brain metastases includes post-contrast T1-weighted acquisitions with both of these pulse sequences.8\n\nDespite the valuable role of MRI in imaging brain metastases, some clinical questions that determine course of treatment, such as differentiation between tumor progression and radiation necrosis or determination of metastatic tumor type, are difficult or impossible to answer by evaluating MR images with the human eye. Radiomics aims to completely characterize data contained in an image or region of interest (ROI) by using dozens to hundreds of different radiomic features that each capture some characteristic of the image or ROI. Radiomics confers several potential advantages: radiomic features may capture image characteristics that are nearly or completely invisible to the human eye, features can quantitatively capture image characteristics that otherwise require qualitative evaluation, and radiomics can be employed in automatic tools to augment clinical decision making. One of the principal applications of radiomic features is to train machine learning classifiers that can assist clinical decisions.9 Several studies demonstrate the feasibility of such tools in cases such as patient outcomes in non-small cell lung cancer.10\n\nThere are several important applications of radiomics for brain metastases in particular. One such application is training machine learning classifiers to distinguish between tumor progression and radiation necrosis, particularly in patients who have undergone Gamma Knife radiosurgery.11–13 One study used radiomic features as a prognostic factor to predict effectiveness of Gamma Knife radiosurgery in brain metastases.14 Another important application exists in cases where brain metastases are detected before diagnosing the primary cancer. In these cases machine learning classifiers have been trained on radiomic feature data to predict metastatic tumor type.15,16\n\nWhile radiomics studies have already yielded exciting findings and these tools have many promising applications, there are concerns about the reproducibility of radiomics studies due to the range of possible study designs and the inherent variability in radiomic features as a function of imaging modality, acquisition parameters, scanner, image preprocessing methods, and feature definitions.17 Several studies have addressed these concerns in computed tomography (CT)18,19 and positron emission tomography (PET). The Image Biomarker Standardization Initiative (IBSI) has worked to standardize radiomic features across several imaging modalities, including MRI, CT, and PET20 and has also published a manual in which consensus-based recommendations and guidelines for radiomics are presented, as well as a general radiomics image processing scheme.21 A recent review of repeatability and reproducibility studies of radiomic features in cancer patients found good representation of CT and PET images, however, relatively few investigated MR-based radiomic features. Furthermore, repeatability and reproducibility investigations have been limited to a small number of cancer types, with types such as non-small cell lung cancer (NSCLC) being dominant in the literature.22 None addressed brain metastases. The need for standardization of MR-based radiomic features in particular is well understood,23 and there have been several suggestions for bringing uniformity to radiomics study workflows.21,24 It is critical to understand the variability of MR-based radiomic features in order to identify which will be reliable for downstream applications, such as machine learning classifiers. As recently as 2016, a review by Yip and Aerts found no investigations of MR-based radiomic feature repeatability, highlighting the need for such work.25\n\nIn the intervening time, several studies have begun to address important questions about the variability of MR-based radiomic features. In a mathematical phantom, Ford et al. investigated MR-based radiomic feature variability as a function of pulse sequence parameter selection,26 and Bologna et al. studied feature robustness to various acquisition parameters in a digital phantom.27 In MRI phantoms, Mayerhoefer et al. investigated how radiomic feature variability responded to variations in acquisition parameters, including the number of acquisitions, repetition time, echo time, sampling bandwidth, and spatial resolution.28 Rai et al. performed a multicenter evaluation of MRI-based radiomic feature reproducibility in phantoms,29 Wong et al. studied longitudinal acquisition repeatability of features on an American College of Radiology MRI phantom,30 and Lee et al. used a test-retest scheme to quantify repeatability of radiomic features in an MRI radiomics phantom while varying acquisition parameters across multiple scanners.31 Finally, in human images, one recent test-retest study investigated repeatability of MR-based radiomic features in glioblastoma across several preprocessing approaches,32 one examined the sensitivity of radiomic features to inter-observer variability in apparent diffusion coefficient maps in cervical cancer,33 and another compared intensity normalization and discretization methods for gadolinium-enhanced T1-weighted and T2-weighted fluid-attenuated inversion recovery series in glioma patients.34 Recent MRI studies have also been performed in patients with Alzheimer’s,35 multiple sclerosis,35 lachrymal gland tumors,36 breast lesions,36 and glioblastoma multiform,37,38 as well as healthy volunteers.35,39–41 Many preprocessing variables have been studied, including contrast weighting,40 resolution,40 acceleration,40,41 gray level discretization,36,38 statistical normalization,35,38 and bias field correction,37 all of which affect the repeatability and reproducibility of extracted radiomic features.\n\nMany studies of MR-based radiomic features have been test-retest repeatability studies,30,38–41 which typically minimize dataset heterogeneity in order to exclusively isolate the intra-scanner variability of radiomic features. However, several previous studies have pointed out the need for balance between dataset homogeneity, which results in low noise in order not to mask any radiomic signature, and heterogeneity, which offers increased generalizability for application to real-world datasets.42–44 Previous studies have addressed some practical concessions that must be made to real-world dataset quality. Many concluded that one of the best options to standardize results from multi-center studies or retrospective cases is to perform preprocessing prior to feature extraction and determine the stable features.27,42 Given the prevalence of this pragmatic approach, best practices must be determined for radiomics studies in these real-world conditions as well as in studies with highly controlled datasets.\n\nThe purpose of this work was to both (i) quantitatively compare the variability of radiomic features extracted from 2-D SE and 3-D SPGR MR images of brain metastases acquired within the same patient in a single imaging session to determine the impact of image acquisition on the identified radiomic features, and (ii) to provide a framework to use these results to inform data acquisition and processing to improve the reliability and reproducibility of radiomics studies. Consensus recommendations for acquiring post-contrast T1-weighted images using both pulse sequences are relatively recent, and many imaging protocols and existing datasets include only one post-contrast T1-weighted acquisition. With this unique dataset, it is critical to understand the variability of radiomic features extracted from both acquisition types, especially for retrospective studies where heterogeneous imaging data is often unavoidable. Furthermore, this information impacts the design of imaging protocols for future studies and the selection of appropriate radiomic data where data from both acquisitions are available. We consider this study to be innovative because it addresses a key aspect of reproducibility in MRI radiomics studies: the sensitivity of features to the input imaging data acquisition parameters. To our knowledge, no previous studies have compared variability of radiomics features derived from different common MR pulse sequences in human imaging data. Based on this data, we provide general recommendations for the design of reproducible radiomics studies, and the extended data can be used to guide study design in more specific cases.\n\n\nMethods\n\nThe study protocol (PA17-0374_MOD008) was approved by the MD Anderson Office of Human Subjects Protection. Ethical approval and consent from participants were waived by the committee. A retrospective cohort was identified consisting of 225 patients treated with Gamma Knife for brain metastasis who subsequently developed radiological/clinical progression and required surgical resection of the same lesion. MR imaging was performed on multiple 1.5T and 3T General Electric MR scanners prior to surgical resection, after which brain metastases were confirmed via pathology. Patients were excluded who did not have T1-weighted post-contrast images acquired by both 2-D SE and 3-D SPGR in a single exam, resulting in 29 patients. T1-weighted post-contrast images were acquired after application of gadobutrol (Gadavist, Bayer Healthcare) with a dose of 0.1 mmol/kg body weight. Within the same exam, T1-weighted post contrast images were acquired using 2-D SE after contrast injection, followed by 3-D SPGR. Standard in-line reconstruction provided by the vendor was used, and no acceleration was employed. Table 1 shows characteristics of these 29 cases, and Table 2 lists scanners and pulse sequence parameter ranges for the two T1-weighted post-contrast acquisitions.\n\nIn total, 29 cases had T1-weighted post-contrast images acquired by both 2-D spin echo and 3-D spoiled gradient echo pulse sequences in the same exam prior to surgical resection.\n\n1 Field of view.\n\n2 Slice thickness.\n\n3 Slice spacing.\n\nTumor volumes were contoured by experienced physicians using the treatment planning system RayStation. In patients with multiple lesions, the contoured lesion was the same one ultimately surgically resected. The enhancing volume in both T1-weighted post-contrast images (2-D SE and 3-D SPGR) was contoured via semi-automated methods using tools available in RayStation and adjusted manually as necessary. The tumor volume on each image was contoured twice by different physicians in order to examine the variability introduced through segmentation. Contour similarity was evaluated using Dice similarity coefficient (DSC). Example images and tumor segmentations are shown in Figure 1.\n\nIn total, 29 patients with brain metastases were included in this study. Each patient had two images (2-D SE and 3-D SPGR), and each tumor volume was segmented by two different physicians, resulting in 58 images and 116 segmentations of the tumor volumes that were analyzed. Radiomic features were extracted using PyRadiomics, which adheres to the image biomarker standardization initiative (IBSI) definitions of features.45 For each combination of preprocessing variables, 105 radiomic features were extracted from several classes, including shape, first order, gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), gray level size zone matrix (GLSZM), gray level dependence matrix (GLDM), and neighboring gray tone difference matrix (NGTDM). These features are listed in Table 3 under their respective classes along with abbreviations for the full feature names used in figures for readability.\n\nSeveral preprocessing variables were investigated, including spatial normalization, 2-D or 3-D radiomic feature extraction, intensity discretization, and image filters. Spatial normalization resolutions included 0.4297 × 0.4297 × 5 mm, 1 × 1 × 5 mm, 3 × 3 × 3 mm, and 1 × 1 × 1 mm. Both 2-D and 3-D radiomic features were extracted, where 3-D features consider voxels from adjacent slices to be neighboring for purposes of feature computations, and 2-D features only consider neighboring voxels within the same slice. Intensity discretization performed on original images included both fixed bin count and fixed bin width methods. Fixed bin counts of 16, 32, 64, 128, and 256 and fixed bin widths of 16, 32, 64, 128, and 256 were considered. This resulted in a total of 264 preprocessing scenarios and 30,624 different feature extractions. In addition to original images, radiomic features were extracted from filtered images. Filters included Laplacian of Gaussian (sigma = 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0 mm) and wavelet (LLH, LHL, LHH, HLL, HLH, HHL, HHH, LLL). Intensity normalization was also performed using square, square root, logarithm, exponential, and gradient scales.\n\nLin’s concordance correlation coefficient (CCC) was used to determine concordance between radiomic feature values extracted from the two acquisition types. CCC is defined between two variables X and Y as\n\nwhere ρ is the correlation coefficient between X and Y, σx and σy are the standard deviations of X and Y, respectively, and μx and μy are the means of X and Y, respectively.\n\nCCC was computed between values of each radiomic feature extracted from the 2-D SE series and those extracted from the 3-D SPGR series for all 264 combinations of preprocessing variables. Kernel density estimates were performed to compare the distribution of CCC among all radiomic features between each combination of preprocessing methods.\n\nCCC was also computed between values of each radiomic feature extracted from the first segmentation of the tumor volume and those from the second segmentation of the same tumor volume. CCC was calculated for each radiomic feature, combination of preprocessing methods, and acquisition type. Kernel density estimates were again performed to compare the distribution of CCC among all radiomic features between each different acquisition type and combination of preprocessing methods.\n\nGeneral recommendations for radiomic study design were given based on patterns of concordance. Exclusion was suggested for filters or preprocessing variable combinations with consistently low concordance or highly variable concordance between 2-D SE and 3-D SPGR extractions. Low concordance suggests these features, filters, and preprocessing variables are likely unreliable in heterogeneous datasets where both 2-D SE and 3-D SPGR pulse sequences were used. Features with consistently low concordance between extractions from the different lesion segmentations were likewise recommended for exclusion in studies in which segmentation variability was present.\n\nA Kolmogorov-Smirnov (K-S) test was performed between radiomic feature values computed from 2-D SE images and those from 3-D SPGR images to assess whether the two distributions were significantly different. K-S tests were repeated to test for distribution differences in each radiomic feature and each different combination of preprocessing variables. Levene’s test for equality of variances was also performed on the same data to determine whether significant differences in variability were present.\n\n\nResults\n\nResults are provided for two scenarios: (i) concordance between radiomic features extracted from 2-D SE and from 3-D SPGR acquisitions, which measures feature agreement between pulse sequences, and (ii) concordance between radiomic features extracted from contours drawn by two different observers on (iia) 2-D SE or (iib) 3-D SPGR images, which captures feature sensitivity to inter-observer variability. For each of these scenarios, there were 105 radiomic features and 264 combinations of preprocessing decisions to consider. Our recommendations for radiomic study design are provided based on broad patterns of concordance displayed in these features and processing combinations, a subset of which is displayed in the following figures. These recommendations are presented in the form of flowcharts, and the quantitative effects of each study design decision are summarized graphically.\n\nThe extended data can also inform more specific decisions in the design of MR acquisitions and analysis by using the concordance of radiomic features for pulse sequences, contouring methods, and preprocessing methods of interest. The complete set of results can be found divided into several figures in the extended data. Alternatively, these data can be viewed as single next-generation clustered heat maps (NG-CHM) via an interactive viewer at https://www.ngchm.net using the provided NG-CHM files for CCC between features from 2-D SE and 3-D SPGR data, CCC between different lesion segmentations on 2-D SE data, and CCC between different lesion segmentations on 3-D SPGR data.46,47 The interactive NG-CHMs allow the convenient visualization of the results in their entirety in order to provide further information with which to support the design of radiomics studies.\n\nCCC was computed between radiomic feature values extracted from 2-D SE and 3-D SPGR images. A value of 1 indicates perfect concordance, -1 indicates perfect discordance, and 0 indicates complete absence of concordance. Figure 2 shows the clustered heat map of CCC values computed for 2-D radiomic features extracted from original images and various preprocessing combinations, including spatial normalization to voxel sizes of 0.4297 × 0.4297 × 5 mm (vs435), 1 × 1 × 5 mm (vs15), 3 × 3 × 3 mm (vs33), and 1 × 1 × 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256). Figure 3 contains the clustered CCC values for 3-D radiomic features in the same combinations. Table 4 lists features with consistently high concordance between values extracted from 2-D SE and 3-D SPGR images. Heat maps of CCC values computed for filtered images, including Laplacian of Gaussian (LoG) with sigma values ranging from 0.5 mm to 5 mm and wavelet (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL), as well as square, square root, logarithm, exponential, and gradient normalization, are included in the extended data. Kernel density estimates of CCC distributions are also computed and displayed in the extended data for all combinations of spatial normalization and intensity discretization in original images.\n\nPreprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).\n\nPreprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).\n\nTwo-sample K-S goodness of fit tests were performed between radiomic feature values extracted from 2-D SE images and those from 3-D SPGR images for each radiomic feature and combination of preprocessing methods. Figures 4 and 5 show clustered binary heat maps of 2-D and 3-D features, respectively, and combinations of preprocessing methods for which the K-S test resulted in p < 0.05, indicating rejection of the null hypothesis that the two sets of radiomic feature values were from the same distribution. Similarly, Levene’s test for equality of variances was performed between radiomic feature values extracted from 2-D SE images and those from 3-D SPGR images for each radiomic feature and combination of preprocessing methods. These results are included in the extended data.\n\nPreprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).\n\nPreprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).\n\nBy hierarchically clustering CCC for each feature and preprocessing variable, low-concordance combinations can be identified and recommended for exclusion in future radiomics studies employing both pulse sequences in the acquisition of T1-weighted post-contrast images in order to improve reproducibility. Figure 6 summarizes recommendations for radiomic feature extraction from T1-weighted post-contrast images acquired by mixed pulse sequences, and Figure 7 groups CCC values to show the effects of each recommendation. The median CCC between features extracted from images acquired by 2-D SE and 3-D SPGR for recommended combinations of features and preprocessing variables was 0.79, compared to a median CCC of 0.51 for those combinations that are not recommended.\n\nThis flowchart assumes an existing dataset with post-contrast T1-weighted images and provides suggestions for selecting pre-processing and feature extraction parameters.\n\nDSC was used to measure the similarity of ROIs delineated by two different physicians. On 2-D SE images, mean DSC was 0.9072 and standard deviation was 0.0574. On 3-D SPGR images, mean DSC was 0.9067 and standard deviation was 0.0456. This suggests good overall agreement between segmentation, which is suitable for assessing feature sensitivity to inter-observer variability. CCC was also computed between radiomic feature values extracted from two different segmentations of the tumor volume on 2-D SE images and separately on 3-D SPGR images. Figure 8 shows the clustered heat map of CCC values computed for original 2-D SE images and differing preprocessing combinations, including spatial normalization to varying voxel sizes, bin counts for relative intensity discretization, and bin widths for absolute intensity discretization. Figure 9 shows the same for 3-D features and original 3-D SPGR images. Table 5 lists the features with consistently low concordance between values extracted from the two segmentations on 3-D SPGR images. Results for 2-D SE and 3-D SPGR LoG- and wavelet-filtered images, as well as square, square root, logarithm, exponential, and gradient normalizations, are provided in extended data. Kernel density estimates of these CCC distributions from 2-D SE and 3-D SPGR images are computed and displayed in the extended data for all combinations of spatial normalization and intensity discretization in original images.\n\nPreprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).\n\nPreprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).\n\nFor each radiomic feature and combination of preprocessing methods, two-sample K-S goodness of fit tests were performed between radiomic feature values extracted from two different segmentations of the tumor volume on 2-D SE images and separately on 3-D SPGR images. Only 12 total combinations of features and preprocessing methods from both 2-D SE and 3-D SPGR images resulted in K-S tests with p < 0.05, indicating rejection of the null hypothesis that the two sets of radiomic feature values are from the same distribution. Detailed figures are shown in the extended data. Similarly, Levene’s test for equality of variances was performed between radiomic feature values extracted from the two sets of tumor volume segmentations for each radiomic feature, each combination of preprocessing methods, and both 2-D SE and 3-D SPGR images. Seventeen features that consistently met the Levene's test significance threshold (p < 0.05) between two different lesion segmentations on 3-D SPGR series are listed in Table 6. Detailed results are again provided in extended data.\n\nLow-concordance combinations of features and preprocessing variables were again identified and recommended for exclusion from future studies by hierarchically clustering CCC values for all combinations. Figure 10 summarizes recommendations for radiomic feature extraction from T1-weighted post-contrast images based on variability introduced by lesion segmentation methods, and Figure 11 groups CCC values to show the effects of each recommendation made. The median CCC between features extracted from two different lesion segmentations was 0.93 for images acquired by 2-D SE and 0.86 for images acquired by 3-D SPGR. By applying additional recommendations to feature extraction from 3-D SPGR data, median CCC of recommended features and preprocessing variables was increased to 0.93.\n\nThis flowchart assumes an imaging protocol with post-contrast T1-weighted images is being designed before data collection and provides suggestions for selecting pulse sequence and pre-processing and feature extraction parameters.\n\n\nDiscussion\n\nThis study compared the resulting MR-based radiomic features between two common T1-weighted MR pulse sequences (2-D SE and 3-D SPGR) for brain metastases imaging that were acquired in the same patient during the same imaging study. It highlights the impact of image acquisition and processing on the identified radiomic features by investigating feature variability as a function of pulse sequence, spatial normalization, 2-D or 3-D feature extraction, intensity discretization, image filters, and inter-observer variability in segmentation. Repeatability and reproducibility studies of radiomic features are necessary to assess the generalizability of radiomics applications. For example, machine learning classifiers trained on radiomic features may not be generalizable to other datasets if training is performed with features that perform poorly in repeatability or reproducibility metrics. Repeatability and reproducibility studies also contribute to the future design and standardization of high-quality, reliable radiomics studies. For these reasons, repeatability and reproducibility studies of radiomic features are increasingly necessary.\n\nThe images in this study were not acquired with uniform pulse sequence parameters. A previous study found that the sensitivity of second-order texture features to variation in acquisition parameters increases non-uniformly with spatial resolution across features. However, it also determined that variations in acquisitions such as number of acquisitions, repetition time, echo time, and slice bandwidth did not significantly affect results of pattern discrimination above certain spatial resolution thresholds, and it identified GLCM features as the most robust to variability introduced in datasets with lower or heterogeneous spatial resolutions.28 Because many radiomic features are likely dependent on acquisition parameters, one review of feature repeatability and reproducibility studies recommends performing benchmarking studies on datasets with heterogeneous acquisition variables, such as slice thickness, acquisition protocols, multiple scanner manufacturers, and multiple institutions.22\n\nIn these results, the fixed bin count intensity discretization method for original images generally displays greater CCC between 2-D and 3-D sequences than the fixed bin width method (Figures 2 and 3). This result reaffirms the widespread preference for relative discretization methods when processing MR images. Fixed bin methods introduce some normalization to images for which intensity units are arbitrary and contrast is important.21 Features with consistently high concordance between 2-D SE and 3-D SPGR series are listed in Table 4. Some features, such as large area emphasis, large area high gray level emphasis, and zone variance from the GLSZM class, demonstrated high variability in concordance between 2-D SE and 3-D SPGR series. For these features, concordance may be sensitive to preprocessing variables but generally may not be robust to variation in acquisition parameters or pulse sequence. In a mathematical phantom, Ford et al. determined that radiomic features varied significantly between SE and SPGR pulse sequences,26 which is supported by these results.\n\nWhen considering features extracted from filtered images, the LoG filter, for all tested values of sigma, generally resulted in greater concordance between 2-D SE and 3-D SPGR sequences than other filters (Figures S-1 and S-2). In particular, normalization to square, square root, exponential, and gradient scales resulted in very poor concordance between 2-D SE and 3-D SPGR features (Figures S-3 and S-4), so these are generally not recommended in heterogeneous datasets.\n\nFor spatial normalization, kernel density estimates of CCC distributions among radiomic features (Figure S-12) show that 2-D radiomic features extracted at the non-isotropic resolutions (0.4297 × 0.4297 × 5 mm and 1 × 1 × 5 mm) possess higher concordance as a whole between 2-D SE and 3-D SPGR features. 3-D radiomic features extracted at non-isotropic resolutions possess lower concordance as a whole, which is expected since this eliminates rotational invariance of features. For this reason, this combination is not recommended, and in-plane computation of radiomic features should be employed for non-isotropic spatial normalization. For both 2-D and 3-D radiomic feature extraction, the isotropic resolutions (3 × 3 × 3 mm and 1 × 1 × 1 mm) showed lower concordance as a whole between 2-D SE and 3-D SPGR. This suggests a significant penalty to agreement between features from the two sequences as a result of interpolation between slices.\n\nFrom the two-sample K-S tests, several features met the significance threshold (p < 0.05) for being sampled from different distributions (Figures 4 and 5). This suggests that these features should be treated with caution, as they may not be robust to differences between the acquisition parameters and pulse sequences. Several of the same features met the significance threshold (p < 0.05) in Levene’s test for equality of variances (Figures S-17 and S-18). Additional features displayed statistically significantly different variances between 2-D SE and 3-D SPGR features but did not reach significance for the K-S test. These features may be more stable for images acquired with one pulse sequence compared to the other.\n\nNearly all features and combinations of preprocessing methods demonstrated very high concordance between the two segmentations drawn by different physicians on the 2-D SE images (Figures 8, S-21, S-22, S-23, S-24, and S-25). This is encouraging as it indicates that almost all features were robust to inter-observer variability in segmentation of the tumor volume. Likewise, most features and combinations of preprocessing methods showed high concordance between segmentations on 3-D SE images as well (Figures 9 and S-26). However, several features yielded consistently low concordance between observers (Table 5). This indicates that these features may be poor choices for applications trained on data acquired with 3-D SPGR sequences, as they likely are not robust to inter-observer variability during segmentation. Similar features displayed low concordance for filtered 3-D SPGR images (Figures S-27, S-28, S-29, and S-30). Again, most features demonstrated very low concordance for square, square root, exponential, and gradient normalization scales, suggesting that these are not reliable methods for processing MR images for feature extraction. As a whole, fixed bin width methods resulted in greater concordance between the two segmentations for 3-D SPGR series (Figures 9, S-32, S-37, and S-38). This might be explained by the inclusion or exclusion of voxels at the segmentation boundaries having less impact on the bins into which interior voxels fall for fixed bin widths than for fixed bin counts. Still, it is unlikely to be advantageous to sacrifice the normalizing effect of fixed bin count methods for MR data for better robustness to inter-observer variability from segmentation. If fix bin width intensity discretization is used, it is important to include an appropriate intensity normalization method in image pre-processing.34\n\nFor 2-D SE data, spatial normalization did not appear to have a significant impact on agreement between features extracted from the two segmentations (Figures S-33, S-35, and S-36). For 3-D SPGR data, only the 3 × 3 × 3-mm spatial normalization appeared to perform consistently poorly compared to the other resolutions tested (Figures S-34, S-37, and S-38). This resolution results in a significant amount of averaging of the original image data, and therefore loss of feature concordance is unsurprising.\n\nFor two-sample K-S tests between feature values from the two segmentations, only six features and preprocessing methods met the significance threshold (p < 0.05) for being sampled from different distributions for 2-D SE data (Figures S-39 and S-40), and six features and preprocessing methods met the significance threshold for 3-D SPGR data (Figures S-41 and S-42). However, a few features from the 2-D SE data met the significance threshold (p < 0.05) for Levene’s test for equality of variances (Figures S-43 and S-44), including long run high gray level emphasis and long run low gray level emphasis from the GLRLM class and large area high gray level emphasis, large area low gray level emphasis, and small area low gray level emphasis from the GLSZM class. Several more features from the 3-D SPGR data consistently met this significance threshold (Figures S-45 and S-46). This suggests that features extracted from 2-D SE images are generally more robust to inter-observer variability during segmentation than those from 3-D SPGR images. This may result from better lesion conspicuity or higher signal-to-noise ratio (SNR) in 2-D SE acquisitions. The features listed above may suffer instability in 3-D SPGR images as a result variability introduced during segmentation of the tumor volume.\n\nThe results from this study are summarized into a series of recommendations that are shown as flowcharts in Figures 6 and 10. Figure 6 walks through decisions for an existing dataset with post-contrast T1-weighted images and provides suggestions for selecting pre-processing and feature extraction parameters. For T1-weighted post-contrast images acquired by both SE and SPGR sequences, fixed bin count intensity discretization is strongly recommended, non-isotropic spatial normalization with comparable in-plane resolution and 2-D radiomic feature extraction are potentially beneficial, and exclusion of low-concordance feature groups, such as certain wavelet filters (HLH, HHL, and HHH) and square root, logarithm, and exponential normalization, is strongly recommended. Figure 7 demonstrates the effect of each individual recommendation and the cumulative impact of all recommendations. The strong recommendations above resulted in substantial improvement in CCC, and the potential recommendations resulted in more modest improvement.\n\nFigure 10 considers decisions involved in designing an imaging protocol with post-contrast T1-weighted images before data collection and provides suggestions for selecting pulse sequences. For any segmentation with significant variability, especially manual or semi-automated methods, 2-D SE acquisitions are strongly preferred to reduce sensitivity to inter-observer variability. Fixed bin count intensity discretization and exclusion of low-concordance feature groups, such as HHL and HHH wavelet filters and square root and logarithm normalization, are strongly recommended for 2-D SE data. If 3-D SPGR acquisitions are included, fixed bin width intensity discretization may potentially reduce feature sensitivity to segmentation variability but requires appropriate intensity normalization. Exclusion of low-concordance features in Table 5 results in a comparable distribution of CCC values to those obtained from segmentations on images from 2-D SE acquisitions, so this is strongly recommended. Figure 11 again compares the effects of each individual decision in this process and the cumulative effect of all recommendations if 3-D SPGR acquisitions are included.\n\nSome limitations to this work warrant further study. Although the sample set was small, the goal of this study was to leverage a unique dataset to compare the effect of two pulse sequences within the same patient and same tumors imaged in the same scanner in a single imaging session on the resulting radiomic features. Given that consensus recommendations on brain metastases protocols that include both 2-D SE and 3-D SPGR T1+C acquisitions are relatively recent,8 we are unlikely to be able to assemble a larger dataset similar to this one retrospectively. Over 85% of patients from the original cohort were rejected because they did not have both T1-weighted post-contrast series in the same exam. Second, the scanner models and acquisition parameters were not uniform across patients included in this study. In typical test-retest studies, dataset heterogeneity is often considered to be a weakness. Because this study does not strictly compare identical measurements, but rather concordance of similar measurements, we believe increased generalizability better protects against dataset variable dependence in the results. Several previous studies have pointed out the need for balance between dataset homogeneity, which affords low noise in order to detect radiomic signatures, and heterogeneity, which offers increased generalizability for application to real-world datasets.42–44 However, it is important to note potential drawbacks of dataset heterogeneity. Third, the main goal of this study was to study feature concordance between two different pulse sequences in brain metastasis imaging, but several additional variables affect reproducibility, such as intensity normalization, and would be useful to focus on in future work. These variables introduce additional considerations, such as white matter segmentation dependence, effects on image texture, and tumor size-dependent distortion.34,35 Finally, it would be useful to complete the picture of brain metastasis imaging protocols by investigating other commonly employed sequences, such as T2 FLAIR.\n\n\nConclusions\n\nMR-based radiomic features that demonstrate high concordance between values extracted from images acquired with different pulse sequences may be more reliable and robust inputs to feature-based models that assist with clinical decision making. Similarly, those with high concordance between feature values extracted from different tumor volume segmentations may be more stable against variability introduced during segmentation. Fixed bin count intensity discretization demonstrated higher concordance between features extracted from 2-D SE and 3-D SPGR images, which agrees with common recommendations for MR-based radiomic feature extraction. Non-isotropic spatial normalization was found to have higher concordance between features extracted from 2-D SE and 3-D SPGR images. This study found that the 2-D SE pulse sequence was more robust to inter-observer variability in tumor volume segmentation than the 3-D SPGR pulse sequence. We use these results to provide comprehensive recommendations for preprocessing in future radiomics studies with heterogeneous imaging data.\n\n\nData availability\n\nFigshare: Extended Data for Managing the Effect of Magnetic Resonance Imaging Pulse Sequence on Radiomic Feature Reproducibility in the Study of Brain Metastases, https://doi.org/10.6084/m9.figshare.c.6039128.v1.48\n\nThis project contains the following underlying data:\n\n• pulsesequences_ccc_ngchm.ngchm. (The complete set of results for CCC between features from 2-D SE and 3-D SPGR data. These data can be viewed as a single next-generation clustered heat map (NG-CHM) via an interactive viewer at https://www.ngchm.net. The interactive NG-CHMs allow the convenient visualization of the results in their entirety in order to provide further information with which to support the design of radiomics studies, e.g. selection of pulse sequences, contouring methods, and preprocessing methods of interest.)\n\n• segmentation_2dse_ccc_ngchm.ngchm. (The complete set of results for CCC between different lesion segmentations on 2-D SE data. These data can be viewed as a single next-generation clustered heat map (NG-CHM) via an interactive viewer at https://www.ngchm.net. The interactive NG-CHMs allow the convenient visualization of the results in their entirety in order to provide further information with which to support the design of radiomics studies, e.g. selection of pulse sequences, contouring methods, and preprocessing methods of interest.)\n\n• segmentation_3dspgr_ccc_ngchm.ngchm. (The complete set of results for CCC between different lesion segmentations on 3-D SPGR data. These data can be viewed as a single next-generation clustered heat map (NG-CHM) via an interactive viewer at https://www.ngchm.net. The interactive NG-CHMs allow the convenient visualization of the results in their entirety in order to provide further information with which to support the design of radiomics studies, e.g. selection of pulse sequences, contouring methods, and preprocessing methods of interest.)\n\n\nData that cannot be shared\n\nThe following data cannot be shared due to restrictions on data sharing in the IRB protocol. Individuals may contact the corresponding author to apply for access to the data, which will be granted upon IRB approval.\n\n• 29 T1-weighted post-contrast image series acquired by 2-D spin echo sequences.\n\n• 29 T1-weighted post-contrast image series acquired by 3-D spoiled gradient echo sequences.\n\nFigshare: Extended Data for Managing the Effect of Magnetic Resonance Imaging Pulse Sequence on Radiomic Feature Reproducibility in the Study of Brain Metastases. https://doi.org/10.6084/m9.figshare.c.6039128.v148\n\nThis project contains the following extended data:\n\n• Figure S-1.tif. (Figure S - 1. Heat map of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from Laplacian of Gaussian (LoG) filtered 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and LoG filter sigma values from 0.5 mm to 5.0 mm in increments of 0.5 mm.)\n\n• Figure S-2.tif. (Figure S - 2. Heat map of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from Laplacian of Gaussian (LoG) filtered 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and LoG filter sigma values from 0.5 mm to 5.0 mm in increments of 0.5 mm.)\n\n• Figure S-3.tif. (Figure S - 3. Heat map of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from wavelet filtered and square normalized 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and low- and high-pass wavelet filter combinations (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL).)\n\n• Figure S-4.tif. (Figure S - 4. Heat map of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from wavelet filtered and square, square root, logarithm, exponential, and gradient normalized 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and low- and high-pass wavelet filter combinations (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL).)\n\n• Figure S-5.tif. (Figure S - 5. Heat map with clustering of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from original 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256). Dendrograms are displayed on both axes.)\n\n• Figure S-6.tif. (Figure S - 6. Heat map with clustering of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from original 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256). Dendrograms are displayed on both axes.)\n\n• Figure S-7.tif. (Figure S - 7. Heat map with clustering of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from Laplacian of Gaussian (LoG) filtered 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and LoG filter sigma values from 0.5 mm to 5.0 mm in increments of 0.5 mm. Dendrograms are displayed on both axes.)\n\n• Figure S-8.tif. (Figure S - 8. Heat map with clustering of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from Laplacian of Gaussian (LoG) filtered 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and LoG filter sigma values from 0.5 mm to 5.0 mm in increments of 0.5 mm. Dendrograms are displayed on both axes.)\n\n• Figure S-9.tif. (Figure S - 9. Heat map with clustering of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from wavelet filtered and square normalized 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and low- and high-pass wavelet filter combinations (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL). Dendrograms are displayed on both axes.)\n\n• Figure S-10.tif. (Figure S - 10. Heat map with clustering of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from wavelet filtered and square, square root, logarithm, exponential, and gradient normalized 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and low- and high-pass wavelet filter combinations (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL). Dendrograms are displayed on both axes.)\n\n• Figure S-11.tif. (Figure S - 11. Kernel density estimates (KDE) of concordance correlation coefficient (CCC) distributions between radiomic feature values extracted from 2-D SE and 3-D SPGR images. Subplots group together distributions computed from various intensity discretization methods, including fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-12.tif. (Figure S - 12. Kernel density estimates (KDE) of concordance correlation coefficient (CCC) distributions between radiomic feature values extracted from 2-D SE and 3-D SPGR images. Subplots group together distributions computed from 2-D and 3-D radiomic feature extraction with various spatial normalization methods, including voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11).)\n\n• Figure S-13.tif. (Figure S - 13. Number of radiomic features extracted from original images with concordance correlation coefficient (CCC) falling into various ranges. CCC is computed between radiomic features values extracted from 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and 2-D (f2d) or 3-D (f3d) feature extraction.)\n\n• Figure S-14.tif. (Figure S - 14. Number of radiomic features extracted from original images with concordance correlation coefficient (CCC) falling into various ranges. CCC is computed between radiomic features values extracted from 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256), and 2-D (f2d) or 3-D (f3d) feature extraction.)\n\n• Figure S-15.tif. (Figure S - 15. Binary heat map with clustering of 2-D radiomic features and preprocessing combinations for which p < 0.05 from Kolmogorov-Smirnov test computed between radiomic feature values extracted from 2-D SE and 3-D SPGR images. The dendrogram grouping features is displayed. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-16.tif. (Figure S - 16. Binary heat map with clustering of 3-D radiomic features and preprocessing combinations for which p < 0.05 from Kolmogorov-Smirnov test computed between radiomic feature values extracted from 2-D SE and 3-D SPGR images. The dendrogram grouping features is displayed. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-17.tif. (Figure S - 17. Binary heat map of 2-D radiomic features and preprocessing combinations for which p < 0.05 from Levene's test for equality of variances computed between radiomic feature values extracted from 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-18.tif. (Figure S - 18. Binary heat map of 3-D radiomic features and preprocessing combinations for which p < 0.05 from Levene's test for equality of variances computed between radiomic feature values extracted from 2-D SE and 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-19.tif. (Figure S - 19. Binary heat map with clustering of 2-D radiomic features and preprocessing combinations for which p < 0.05 from Levene's test for equality of variances computed between radiomic feature values extracted from 2-D SE and 3-D SPGR images. The dendrogram grouping features is displayed. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-20.tif. (Figure S - 20. Binary heat map with clustering of 3-D radiomic features and preprocessing combinations for which p < 0.05 from Levene's test for equality of variances computed between radiomic feature values extracted from 2-D SE and 3-D SPGR images. The dendrogram grouping features is displayed. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-21.tif. (Figure S - 21. Heat map of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from two different lesion segmentations on original 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-22.tif. (Figure S - 22. Heat map of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from two different lesion segmentations on Laplacian of Gaussian (LoG) filtered 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and LoG filter sigma values from 0.5 mm to 5.0 mm in increments of 0.5 mm.)\n\n• Figure S-23.tif. (Figure S - 23. Heat map of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from two different lesion segmentations on Laplacian of Gaussian (LoG) filtered 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and LoG filter sigma values from 0.5 mm to 5.0 mm in increments of 0.5 mm.)\n\n• Figure S-24.tif. (Figure S - 24. Heat map of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from two different lesion segmentations on wavelet filtered and square normalized 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and low- and high-pass wavelet filter combinations (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL).)\n\n• Figure S-25.tif. (Figure S - 25. Heat map of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from two different lesion segmentations on wavelet filtered and square, square root, logarithm, exponential, and gradient normalized 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and low- and high-pass wavelet filter combinations (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL).)\n\n• Figure S-26.tif. (Figure S - 26. Heat map of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from two different lesion segmentations on original 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-27.tif. (Figure S - 27. Heat map of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from two different lesion segmentations on Laplacian of Gaussian (LoG) filtered 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and LoG filter sigma values from 0.5 mm to 5.0 mm in increments of 0.5 mm.)\n\n• Figure S-28.tif. (Figure S - 28. Heat map of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from two different lesion segmentations on Laplacian of Gaussian (LoG) filtered 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and LoG filter sigma values from 0.5 mm to 5.0 mm in increments of 0.5 mm.)\n\n• Figure S-29.tif. (Figure S - 29. Heat map of concordance correlation coefficient (CCC) between 2-D radiomic feature values extracted from two different lesion segmentations on wavelet filtered and square normalized 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and low- and high-pass wavelet filter combinations (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL).)\n\n• Figure S-30.tif. (Figure S - 30. Heat map of concordance correlation coefficient (CCC) between 3-D radiomic feature values extracted from two different lesion segmentations on wavelet filtered and square, square root, logarithm, exponential, and gradient normalized 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), and low- and high-pass wavelet filter combinations (LLH, LHL, LHH, HLL, HLH, HHL, HHH, and LLL).)\n\n• Figure S-31.tif. (Figure S - 31. Kernel density estimates (KDE) of concordance correlation coefficient (CCC) distributions between radiomic feature values extracted from two different lesion segmentations on 2-D SE images. Subplots group together distributions computed from various intensity discretization methods, including fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-32.tif. (Figure S - 32. Kernel density estimates (KDE) of concordance correlation coefficient (CCC) distributions between radiomic feature values extracted from two different lesion segmentations on 3-D SPGR images. Subplots group together distributions computed from various intensity discretization methods, including fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-33.tif. (Figure S - 33. Kernel density estimates (KDE) of concordance correlation coefficient (CCC) distributions between radiomic feature values extracted from two different lesion segmentations on 2-D SE images. Subplots group together distributions computed from 2-D and 3-D radiomic feature extraction with various spatial normalization methods, including voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11).)\n\n• Figure S-34.tif. (Figure S - 34. Kernel density estimates (KDE) of concordance correlation coefficient (CCC) distributions between radiomic feature values extracted from two different lesion segmentations on 3-D SPGR images. Subplots group together distributions computed from 2-D and 3-D radiomic feature extraction with various spatial normalization methods, including voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11).)\n\n• Figure S-35.tif. (Figure S - 35. Number of radiomic features extracted from original images with concordance correlation coefficient (CCC) falling into various ranges. CCC is computed between radiomic features values extracted from two different lesion segmentations on 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and 2-D (f2d) or 3-D (f3d) feature extraction.)\n\n• Figure S-36.tif. (Figure S - 36. Number of radiomic features extracted from original images with concordance correlation coefficient (CCC) falling into various ranges. CCC is computed between radiomic features values extracted from two different lesion segmentations on 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256), and 2-D (f2d) or 3-D (f3d) feature extraction.)\n\n• Figure S-37.tif. (Figure S - 37. Number of radiomic features extracted from original images with concordance correlation coefficient (CCC) falling into various ranges. CCC is computed between radiomic features values extracted from two different lesion segmentations on 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and 2-D (f2d) or 3-D (f3d) feature extraction.)\n\n• Figure S-38.tif. (Figure S - 38. Number of radiomic features extracted from original images with concordance correlation coefficient (CCC) falling into various ranges. CCC is computed between radiomic features values extracted from two different lesion segmentations on 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256), and 2-D (f2d) or 3-D (f3d) feature extraction.)\n\n• Figure S-39.tif. (Figure S - 39. Binary heat map of 2-D radiomic features and preprocessing combinations for which p < 0.05 from Kolmogorov-Smirnov test computed between radiomic feature values extracted from two different lesion segmentations on 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-40.tif. (Figure S - 40. Binary heat map of 3-D radiomic features and preprocessing combinations for which p < 0.05 from Kolmogorov-Smirnov test computed between radiomic feature values extracted from two different lesion segmentations on 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-41.tif. (Figure S - 41. Binary heat map of 2-D radiomic features and preprocessing combinations for which p < 0.05 from Kolmogorov-Smirnov test computed between radiomic feature values extracted from two different lesion segmentations on 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-42.tif. (Figure S - 42. Binary heat map of 3-D radiomic features and preprocessing combinations for which p < 0.05 from Kolmogorov-Smirnov test computed between radiomic feature values extracted from two different lesion segmentations on 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-43.tif. (Figure S - 43. Binary heat map of 2-D radiomic features and preprocessing combinations for which p < 0.05 from Levene's test for equality of variances computed between radiomic feature values extracted from two different lesion segmentations on 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-44.tif. (Figure S - 44. Binary heat map of 3-D radiomic features and preprocessing combinations for which p < 0.05 from Levene's test for equality of variances computed between radiomic feature values extracted from two different lesion segmentations on 2-D SE images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-45.tif. (Figure S - 45. Binary heat map of 2-D radiomic features and preprocessing combinations for which p < 0.05 from Levene's test for equality of variances computed between radiomic feature values extracted from two different lesion segmentations on 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\n• Figure S-46.tif. (Figure S - 46. Binary heat map of 3-D radiomic features and preprocessing combinations for which p < 0.05 from Levene's test for equality of variances computed between radiomic feature values extracted from two different lesion segmentations on 3-D SPGR images. Preprocessing combinations include spatial normalization to voxel sizes of 0.4297 x 0.4297 x 5 mm (vs435), 1 x 1 x 5 mm (vs15), 3 x 3 x 3 mm (vs33), and 1 x 1 x 1 mm (vs11), intensity discretization to fixed bin counts of 16 (bc16), 32 (bc32), 64 (bc64), 128 (bc128), and 256 (bc256), and intensity discretization to fixed bin width of 16 (bw16), 32 (bw32), 64 (bw64), 128 (bw128), and 256 (bw256).)\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "Acknowledgements\n\nThe authors would like to thank David Jaffray, Ph.D. for constructive criticism of the manuscript.\n\n\nReferences\n\nAchrol AS, Rennert RC, Anders C, et al.: Brain metastases. Nat. Rev. Dis. Primers. 2019; 5: 1. Publisher Full Text\n\nBrastianos PK, Curry WT, Oh KS: Clinical discussion and review of the management of brain metastases. JNCCN J. Natl. Compr. Cancer Netw. 2013; 11(9): 1153–1164. Publisher Full Text\n\nDowns RK, Bashir MH, Ng CK, et al.: Quantitative contrast ratio comparison between T1 (TSE at 1.5T, FLAIR at 3T), magnetization prepared rapid gradient echo and subtraction imaging at 1.5T and 3T. Quant. Imaging Med. Surg. 2013; 3(3): 141–146. PubMed Abstract \| Publisher Full Text\n\nFurutani K, Harada M, Mawlan M, et al.: Difference in enhancement between spin echo and 3-dimensional fast spoiled gradient recalled acquisition in steady state magnetic resonance imaging of brain metastasis at 3-T magnetic resonance imaging. J. Comput. Assist. Tomogr. 2008; 32(2): 313–319. PubMed Abstract \| Publisher Full Text\n\nGraves MJ: Pulse sequences for contrast-enhanced magnetic resonance imaging. Radiography. 2007; 13(SUPPLL. 1): e20–e30. Publisher Full Text\n\nMirowitz SA: Intracranial lesion enhancement with gadolinium: T1-weighted spin-echo versus three-dimensional fourier transform gradient-echo MR imaging. Radiology. 1992; 185(2): 529–534. PubMed Abstract \| Publisher Full Text\n\nKakeda S, Korogi Y, Hiai Y, et al.: Detection of brain metastasis at 3T: Comparison among SE, IR-FSE and 3D-GRE sequences. Eur. Radiol. 2007; 17(9): 2345–2351. PubMed Abstract \| Publisher Full Text\n\nKaufmann TJ, Smits M, Boxerman J, et al.: Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases. Neuro-Oncology. 2020; 22(6): 757–772. PubMed Abstract \| Publisher Full Text\n\nZhou M, Scott J, Chaudhury B, et al.: Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches. Am. J. Neuroradiol. 2018; 39(2): 208–216. PubMed Abstract \| Publisher Full Text\n\nFave X, Zhang L, Yang J, et al.: Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer. Sci. Rep. 2017; 7(1): 1–11. PubMed Abstract \| Publisher Full Text\n\nArtzi M, Bressler I, Ben BD: Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis. J. Magn. Reson. Imaging. 2019; 50(2): 519–528. PubMed Abstract \| Publisher Full Text\n\nPeng L, Parekh V, Huang P, et al.: Distinguishing True Progression From Radionecrosis After Stereotactic Radiation Therapy for Brain Metastases With Machine Learning and Radiomics. Int. J. Radiat. Oncol. Biol. Phys. 2018; 102: 1236–1243. PubMed Abstract \| Publisher Full Text\n\nZhang Z, Yang J, Ho A, et al.: A predictive model for distinguishing radiation necrosis from tumour progression after gamma knife radiosurgery based on radiomic features from MR images. Eur. Radiol. 2018; 28: 2255–2263. PubMed Abstract \| Publisher Full Text\n\nHuang CY, Lee CC, Yang HC, et al.: Radiomics as prognostic factor in brain metastases treated with Gamma Knife radiosurgery. J. Neuro-Oncol. 2020; 146(3): 439–449. PubMed Abstract \| Publisher Full Text\n\nKniep HC, Madesta F, Schneider T, et al.: Radiomics of brain MRI: Utility in prediction of metastatic tumor type. Radiology. 2019; 290(3): 479–487. PubMed Abstract \| Publisher Full Text\n\nOrtiz-Ramon R, Larroza A, Arana E, et al.: A radiomics evaluation of 2D and 3D MRI texture features to classify brain metastases from lung cancer and melanoma. Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS. 2017; 2017: 493–496. PubMed Abstract \| Publisher Full Text\n\nRizzo S, Botta F, Raimondi S, et al.: Radiomics: the facts and the challenges of image analysis. Eur. Radiol. Exp. 2018; 2(1): 36. PubMed Abstract \| Publisher Full Text\n\nShafiq-Ul-Hassan M, Zhang GG, Latifi K, et al.: Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels. Med. Phys. 2017; 44(3): 1050–1062. PubMed Abstract \| Publisher Full Text\n\nBerenguer R, Del Rosario P-JM, Canales-Vázquez J, et al.: Radiomics of CT features may be nonreproducible and redundant: Influence of CT acquisition parameters. Radiology. 2018; 288(2): 407–415. PubMed Abstract \| Publisher Full Text\n\nZwanenburg A, Vallières M, Abdalah MA, et al.: The image biomarker standardization initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology. 2020; 295(2): 328–338. PubMed Abstract \| Publisher Full Text\n\nZwanenburg A, Leger S, Vallières M, Löck S: Image biomarker standardisation initiative.2016. Publisher Full Text\n\nTraverso A, Wee L, Dekker A, et al.: Repeatability and Reproducibility of Radiomic Features: A Systematic Review. Int. J. Radiat. Oncol. Biol. Phys. 2018; 102(4): 1143–1158. PubMed Abstract \| Publisher Full Text\n\nMolina D, Pérez-Beteta J, Martínez-González A, et al.: Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. PLoS One. 2017; 12(6): e0178843–e0178814. PubMed Abstract \| Publisher Full Text\n\nvan Timmeren JE , Cester D, Tanadini-Lang S, et al.: Radiomics in medical imaging—“how-to” guide and critical reflection. Insights Imaging. 2020; 11(1): 91. PubMed Abstract \| Publisher Full Text\n\nYip SSF, Aerts HJWL: Applications and limitations of radiomics. Phys. Med. Biol. 2016; 61(13): R150–R166. PubMed Abstract \| Publisher Full Text\n\nFord J, Dogan N, Young L, et al.: Quantitative Radiomics: Impact of Pulse Sequence Parameter Selection on MRI-Based Textural Features of the Brain. Contrast Media Mol. Imaging. 2018; 2018: 1–9. PubMed Abstract \| Publisher Full Text\n\nBologna M, Corino V, Mainardi L: Technical Note: Virtual phantom analyses for preprocessing evaluation and detection of a robust feature set for MRI-radiomics of the brain. Med. Phys. 2019; 46(11): 5116–5123. PubMed Abstract \| Publisher Full Text\n\nMayerhoefer ME, Szomolanyi P, Jirak D, et al.: Effects of MRI acquisition parameter variations and protocol heterogeneity on the results of texture analysis and pattern discrimination: An application-oriented study. Med. Phys. 2009; 36(4): 1236–1243. PubMed Abstract \| Publisher Full Text\n\nRai R, Holloway LC, Brink C, et al.: Multicenter evaluation of MRI-based radiomic features: A phantom study. Med. Phys. 2020; 47(July): 3054–3063. PubMed Abstract \| Publisher Full Text\n\nWong OL, Ji Y, Zhou Y, et al.: Longitudinal acquisition repeatability of MRI radiomics features: An ACR MRI phantom study on two MRI scanners using a 3D T1W TSE sequence. Med. Phys. 2021; 48(3): 1239–1249. PubMed Abstract \| Publisher Full Text\n\nLee J, Steinmann A, Ding Y, et al.: Radiomics feature robustness as measured using an MRI phantom. Sci. Rep. 2021; 11(1): 1–14. PubMed Abstract \| Publisher Full Text\n\nShiri I, Hajianfar G, Sohrabi A, et al.: Repeatability of radiomic features in magnetic resonance imaging of glioblastoma: Test–retest and image registration analyses. Med. Phys. 2020; 47(9): 4265–4280. PubMed Abstract \| Publisher Full Text\n\nTraverso A, Kazmierski M, Welch ML, et al.: Sensitivity of radiomic features to inter-observer variability and image pre-processing in Apparent Diffusion Coefficient (ADC) maps of cervix cancer patients. Radiother. Oncol. 2019; 143: 88–94. PubMed Abstract \| Publisher Full Text\n\nCarré A, Klausner G, Edjlali M, et al.: Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics. Sci. Rep. 2020; 10(1): 12315–12340. PubMed Abstract \| Publisher Full Text\n\nShinohara RT, Sweeney EM, Goldsmith J, et al.: Statistical normalization techniques for magnetic resonance imaging. NeuroImage Clin. 2014; 6: 9–19. PubMed Abstract \| Publisher Full Text\n\nDuron L, Balvay D, Vande PS, et al.: Gray-level discretization impacts reproducible MRI radiomics texture features. PLoS One. 2019; 14(3): e0213459–e0213414. PubMed Abstract \| Publisher Full Text\n\nMoradmand H, Aghamiri SMR, Ghaderi R: Impact of image preprocessing methods on reproducibility of radiomic features in multimodal magnetic resonance imaging in glioblastoma. J. Appl. Clin. Med. Phys. 2020; 21(1): 179–190. PubMed Abstract \| Publisher Full Text\n\nHoebel KV, Patel JB, Beers AL, et al.: Radiomics repeatability pitfalls in a scan-rescan mri study of glioblastoma. Radiol. Artif. Intell. 2021; 3(1): e190199. PubMed Abstract \| Publisher Full Text\n\nPandey U, Saini J, Kumar M, et al.: Normative Baseline for Radiomics in Brain MRI: Evaluating the Robustness, Regional Variations, and Reproducibility on FLAIR Images. J. Magn. Reson. Imaging. 2021; 53(2): 394–407. PubMed Abstract \| Publisher Full Text\n\nEck B, Chirra PV, Muchhala A, et al.: Prospective Evaluation of Repeatability and Robustness of Radiomic Descriptors in Healthy Brain Tissue Regions in vivo Across Systematic Variations in T2-Weighted Magnetic Resonance Imaging Acquisition Parameters. J. Magn. Reson. Imaging. 2021; 54(3): 1009–1021. PubMed Abstract \| Publisher Full Text\n\nKim M, Jung SC, Park JE, et al.: Reproducibility of radiomic features in SENSE and compressed SENSE: impact of acceleration factors. Eur. Radiol. 2021; 31(9): 6457–6470. PubMed Abstract \| Publisher Full Text\n\nShur JD, Doran SJ, Kumar S, et al.: Radiomics in oncology: A practical guide. Radiographics. 2021; 41(6): 1717–1732. PubMed Abstract \| Publisher Full Text\n\nKeek SA, Leijenaar RT, Jochems A, et al.: A review on radiomics and the future of theranostics for patient selection in precision medicine. Br. J. Radiol. 2018; 91(1091): 20170926. PubMed Abstract \| Publisher Full Text\n\nKumar V, Gu Y, Basu S, et al.: Radiomics: The process and the challenges. Magn. Reson. Imaging. 2012; 30(9): 1234–1248. PubMed Abstract \| Publisher Full Text\n\nvan Griethuysen JJM , Fedorov A, Parmar C, et al.: Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Res. 2017; 77(21): e104–e107. PubMed Abstract \| Publisher Full Text\n\nBroom BM, Ryan MC, Stucky M, et al.: Interactive Clustered Heat Map Builder: An easy web-based tool for creating sophisticated clustered heat maps. F1000Res. 2020; 8: 1750. PubMed Abstract \| Publisher Full Text\n\nBroom BM, Ryan MC, Brown RE, et al.: A galaxy implementation of next-generation clustered heatmaps for interactive exploration of molecular profiling data. Cancer Res. 2017; 77(21): e23–e26. PubMed Abstract \| Publisher Full Text\n\nMitchell D: Extended Data for Managing the Effect of Magnetic Resonance Imaging Pulse Sequence on Radiomic Feature Reproducibility in the Study of Brain Metastases. figshare. [Dataset].2022. Publisher Full Text" }	[ { "id": "180248", "date": "02 Aug 2023", "name": "Nguyen Quoc Khanh Le", "expertise": [ "Reviewer Expertise Artificial intelligence", "bioinformatics", "medical informatics", "radiomics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis study aims to address the limited reproducibility of radiomics studies and provides recommendations to improve the reproducibility of radiomic features extracted from brain metastases on magnetic resonance imaging (MRI). While the study offers some valuable insights, there are a few major concerns to consider:\nThe study is based on a retrospective cohort of only 29 patients. A small sample size raises concerns about the generalizability and statistical power of the findings. It is important to acknowledge the limitations of a small sample and discuss the potential impact on the reliability and applicability of the recommendations provided.\n\nThe study does not mention whether the recommendations were validated or tested on an independent dataset. External validation is crucial to assess the generalizability and effectiveness of the proposed recommendations beyond the specific cohort used in the study. Including an external validation step would strengthen the reliability and relevance of the recommendations.\n\nThe study focuses on variability in image acquisition and processing as sources of unreproducible radiomic results. However, other factors such as inter-reader variability and inter-scanner variability are also known to impact reproducibility. It would be valuable to discuss and consider these additional factors in the framework for reproducible radiomics studies.\n\nThe study focuses primarily on the technical aspects of improving reproducibility in radiomic features. While this is important, the study does not address the clinical impact or utility of these features. It would be beneficial to discuss how the improved reproducibility of radiomic features can enhance clinical decision-making or patient outcomes.\n\nAlthough the study provides recommendations for improving reproducibility, it does not discuss the practical implementation challenges or potential barriers that may arise when applying these recommendations in real-world clinical settings. Addressing implementation considerations would enhance the practicality and feasibility of the proposed framework.\n\nWhile the study provides recommendations, it does not thoroughly discuss the limitations and potential drawbacks associated with implementing these recommendations. It is important to acknowledge and address potential limitations, such as the trade-offs between reproducibility and the potential loss of information or clinical relevance.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-892
https://f1000research.com/articles/11-564/v1	24 May 22	{ "type": "Brief Report", "title": "Productivity of mother pigs is lower in countries that still confine them in gestation crates", "authors": [ "Cynthia Schuck-Paim", "Wladimir J. Alonso", "Wladimir J. Alonso" ], "abstract": "Background: For decades, pig farmers have used gestation crates — small metal enclosures about two feet wide — to confine pregnant sows (female breeding pigs). Gestation crates physically restrain sows for most of their life, preventing them from walking or even turning around. Millions of females are still housed in these systems. Growing societal concern about animal welfare has been pressuring the industry for change, with recent legislation in the European Union and California restricting the use of crates. Still, the notion that gestation crates negatively affect sow welfare has been challenged by producers in regions where crates are widely used, who argue that, by facilitating health monitoring and preventing aggression, crates lead to lower sow mortality and higher piglet outputs per sow. We address these claims by comparing sow mortality and performance across countries with different housing systems. Methods: To this end, we use publicly available data from InterPig, a network of pig production economists in 17 countries that provides internationally harmonized methods for meaningful comparisons of national production data. Results: The results show that sow mortality is significantly higher, and annual pig production per sow significantly lower, in those countries where gestation crates are still the norm compared to countries in the European Union, where use of gestation crates is restricted to up to four weeks after insemination. Conclusions: Claims of higher mortality and reduced productivity per sow in crate-free systems are not substantiated by this data. This evidence should be considered in policies affecting the welfare of breeding pigs.", "keywords": [ "pig", "sows", "gestation crates", "confinement", "animal welfare" ], "content": "Introduction\n\nFor decades, pig production has relied on the use of gestation crates (also referred to as gestation stalls) — small metal enclosures about two feet wide — to confine pregnant sows (female breeding pigs). Gestation crates physically restrain sows for most of their life, preventing them from walking, turning around or extending their limbs fully1 (Figure 1). They are linked to several welfare and health problems, such as pressure sores, ulcers, and abrasions, poorer cardiac function and immune-competence.2–5 Most female breeding pigs around the globe are still housed in these systems.\n\nPhases are ordered horizontally, from left to right, representing the passage of time. Except for the gestation and farrowing cycles (which are experienced five to six times by an average sow), enclosure widths roughly coincide with the duration of the corresponding phase. The thickness of lines underneath production phases is proportional to the time of life spent at each phase.\n\nHowever, growing societal concern about animal welfare6,7 has been pressuring the industry for change. For example, with over 1 million European Union (EU) citizens supporting the EU citizens’ initiative ‘End the Cage Age’, the European Commission committed to present legislative proposals to prohibit the confinement of female pigs in gestation crates at any moment of their lives.8 In California, similar legislation only allows confinement in enclosures providing a minimum of 24 square feet of usable floorspace per breeding pig.9\n\nStill, the notion that gestation crates negatively affect sow welfare is often challenged in countries and regions where crates are still widely used. The industry argues that, by facilitating health monitoring and preventing aggression, crates lead to lower sow mortality and higher piglet outputs per sow.10 For example, according to the National Pork Producers Council (USA), crate-free housing “increases sow mortality, reduces litter sizes, and reduces productivity”.10\n\nAlthough mortality and productivity are not necessarily good indicators of welfare (sick individuals may be kept alive for a long time),11 we explore these claims by comparing sow mortality and performance across countries in which different housing systems are used.\n\n\nMethods\n\nWe use publicly available data from InterPig, a network of pig production economists in 17 countries that provides internationally harmonized methods for meaningful comparisons of national production costs and performance indicators.12,13 InterPig data are widely used by stakeholders in the swine industry, enabling assessment and comparison of sow productivity and mortality among countries with different policies regarding the housing of gestating pigs with an industry-validated dataset.\n\nWe analyzed sow mortality per year and number of pigs sold annually per sow. The latter parameter is very informative of sow productivity, being compounded by several factors: pigs born alive per litter, litters per sow per year and cumulative mortality of pigs over the production cycle (pre-weaning, rearing and finishing mortality). We used the last five years (2015–2019) of data on annual sow mortality and number of pigs sold annually per sow, as made available in the annual reports of the Agriculture and Horticulture Development Board (AHDB) and the Brazilian Agricultural Research Corporation (EMBRAPA). Data was used as provided in the reports, with no data points excluded. The underlying data is available at the Open Science Framework repository.14\n\nCountries were grouped in three housing categories: (1) countries where gestation crates for housing sows are still the norm (United States, Canada, Brazil), (2) countries where gestation crates are restricted to (up to) the first four weeks of pregnancy (Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Hungary, Ireland, Italy, Netherlands, Spain) following a 2013 EU Directive, and (3) countries where gestation crates are entirely banned (Sweden and United Kingdom, where stalls were banned in 1994 and 1999, respectively).\n\nWe also investigated the extent to which potential differences in sow mortality and productivity among housing groups were statistically significant. To this end, we used a general linear model (GLM) having sow mortality and productivity as response variables, housing group as a fixed categorical variable and year as a co-variate. Group means were compared with Tukey’s post-hoc test. To standardize the distribution of residuals, sow productivity values were log-transformed and mortality data were square-root arcsine transformed. Analyses were conducted using Minitab v. 21.1.1. P-values are two-tailed.\n\n\nResults and conclusions\n\nFigure 2 shows mean values (± SEM) of sow productivity and mortality for each housing group, which have both increased over the five years (GLM, effect of year: F1,85=9.05, P=0.003 and F1,85=3.34, P=0.071, respectively). While many factors are expected to affect sow productivity and mortality, including the degree of commitment to national policies and legislation, Figure 2 clearly shows that sow mortality is not greater in crate-free systems. On the contrary, higher sow mortality is observed in those countries where gestation crates are still the norm (GLM: F2,85=5.06, P=0.009, effect of housing group) compared to those countries where crates have been restricted to four weeks after insemination (Tukey’s test, P=0.006). Likewise, there were significant differences in productivity among the housing groups (GLM: F2,85=5.99, P=0.004), with annual pig production per sow being significantly lower in countries where the use of gestation crates prevails compared to those where crates are restricted (Tukey’s test, P=0.012).\n\nData from 17 countries belonging to the InterPig network, divided in three groups: (1) countries where gestation crates are the norm (Red: USA, Canada, Brazil), (2) gestation crates are restricted to (up to) the first four weeks of pregnancy (Black: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Hungary, Ireland, Italy, Netherlands, Spain), and (3) gestation crates are entirely banned (Blue: Sweden, United Kingdom (UK)). In the UK, data up to 2018 reflects a blend of indoor and free-range systems, and in 2019 indoor systems only. The patterns do not change if Brazil is removed from group 1.\n\nThese results are in line with evidence showing that improving maternal welfare improves disease resistance, resilience and survival of piglets.3,4,15 Importantly, they clearly speak against the notion that sow mortality is inherently higher, or productivity lower, in crate-free production. As observed in the transition of laying hens to cage-free systems,11 variability in sow mortality might be observed during any transition from one housing system to another, though it is expected to decrease rapidly as farmers gain experience with the newly adopted systems.11\n\nChanges towards crate-free housing are currently underway in many countries and affect millions of pigs annually. The present findings should be considered to guide debate on policies and legislation affecting the welfare of breeding pigs.\n\n\nData availability\n\nOpen Science Framework: Productivity of mother pigs is lower in countries that still confine them in gestation crates. https://doi.org/10.17605/OSF.IO/G4DK214\n\nThis project contains the following underlying data:\n\n• DataSowMortalityProductivity.xlsx (Data on sow mortality and pigs sold per sow per year, from 2015 to 2019, for 17 countries in the InterPig Network)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nRhodes RT, Appleby MC, Chinn K, et al.: A comprehensive review of housing for pregnant sows. J. Am. Vet. Med. Assoc. 2005; 227: 1580–1590. PubMed Abstract \| Publisher Full Text\n\nMarchant-Forde JN: Housing and Welfare of Sows during Gestation. Livestock Behavior Research Unit. Factsheet. 2010; USDA-ARS-MWA: 1–3.\n\nLiu X, Song P, Yan H, et al.: A Comparison of the Behavior, Physiology, and Offspring Resilience of Gestating Sows When Raised in a Group Housing System and Individual Stalls. Animals. 2021; 11. Publisher Full Text\n\nAlbernaz-Gonçalves R, Olmos Antillón G, Hötzel MJ: Linking Animal Welfare and Antibiotic Use in Pig Farming—A Review. Animals. 2022; 12: 216. PubMed Abstract \| Publisher Full Text\n\nThe Humane Society of the United States (HSUS). Welfare Issues with Gestation Crates for Pregnant Sows. 2013. Report No. 25.\n\nRyan EB, Fraser D, Weary DM: Public Attitudes to Housing Systems for Pregnant Pigs. PLoS One. 2015; 10: e0141878. PubMed Abstract \| Publisher Full Text\n\nYunes MC, von Keyserlingk M , Hötzel MJ: Restricting the ability of sows to move: a source of concern for some Brazilians. Anim. Welf. 2018; 27: 379–392. Publisher Full Text\n\nEuropean Commission: Communication from the Commission on the European Citizens’ Initiative (ECI) ‘End the Cage Age’. 2021 (June). Reference: C(2021)4747. Directorate-General for Health and Food Safety.\n\nCalifornia Department of Food and Agriculture: Animal Health and Food Safety Services. Proposition 12, Farm Animal Confinement. Chapter 10 of Division 2 of Title 3 of the California Code of Regulations.2021.\n\nPetition to the Supreme Court of the United States: National Pork Producers Association (NPCC) v Karen Ross. Petition for a Writ of Certiorari. 2021 (Sep). Report No.: 21. 102549231.\n\nSchuck-Paim C, Negro-Calduch E, Alonso WJ: Laying hen mortality in different indoor housing systems: a meta-analysis of data from commercial farms in 16 countries. Sci. Rep. 2021; 11: 3052. PubMed Abstract \| Publisher Full Text\n\nAgriculture and Horticulture Development Board (AHDB): Pig cost of production in selected countries (2015-2019).2022.\n\nBrazilian Agricultural Research Corporation (EMBRAPA): Custos de produção de suínos (2015-2019) nos países da rede InterPIG. Comunicado Técnico. 539; 548; 554; 565; 580.\n\nSchuck-Paim C: Productivity of mother pigs is lower in countries that still confine them in gestation crates. OSF. 2022. [Dataset]. Publisher Full Text\n\nMerlot E, Meunier-Salaün M-C, Peuteman B, et al.: Improving maternal welfare during gestation has positive outcomes on neonatal survival and modulates offspring immune response in pigs. Physiol. Behav. 2022; 249: 113751. PubMed Abstract \| Publisher Full Text" }	[ { "id": "142487", "date": "04 Jul 2022", "name": "Elodie Merlot", "expertise": [ "Reviewer Expertise I am a researcher in the field of animal sciences at the National Research Institute for Agriculture", "Food and Environment (INRAE)", "France. I have published more than 50 scientific papers on the evaluation", "using physiological and behavioral tools", "of the effects of various husbandry practices and housing systems on the health and welfare of pigs." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIs the work clearly and accurately presented and does it cite the current literature?\nThe work is very clearly presented. It cites some current literature as well as documents from governmental, European or non-governmental organizations. However, besides literature dealing with the most severe health problems generated in sows, a few other articles could have been cited as well in the introduction, for example dealing with the behavioral effects of rearing loose or crated sows during gestation, which are relevant indicators to asses sow welfare. (for example, Boyle et al, 2002, Appl Anim Behav Sci 76:119-134; Jang et al, 2017, Livestock Sci 199:37-45; Zhou et al, 2014, Animal, 8: 1162-1169)\nIs the study design appropriate and does the work have academic merit?\nThis is a very brief study involving a limited amount of data, which fits with the scope of a report for F1000Research. It is based on the analysis of two variables (the sow mortality rate and pigs sold annually per sow), and the data have been collected by others (data are accessible freely on internet in reports edited by the Agriculture and Horticulture Development Board). However, looking at the data available in the AHDB report, I am not convinced that the two most relevant variables were chosen by authors, nor that the report would have been too long if some additional variables had been analyzed here.\n\nIndeed, except in cases of prenatal imprinting (which may occur here), the further away from the birth, the more the effects of gestation tend to be diluted by other life events (potential biases) that have occurred since. Thus, the number of sold pigs per sow could have been influenced by many other factors than crating the pregnant mothers, and which would have influenced the life of pigs in between. This limitation is compounded by the fact that the number of countries included in the study is unbalanced in the 3 groups that are compared and biased in terms of geographic distribution. This increases the likelihood that uncontrolled confounding factors will influence the result observed here.\n\nThe number of weaned pigs per sow could have been studied also to enrich the study. Although it is of less economic interest than the number of pigs sold per sow, it is of greater biological interest. Indeed, the number of weaned pigs is particularly relevant because it is highly correlated with pre-weaning mortality, and most mortality in pig production occurs before weaning. Don’t you think that this 3rd variable could be added to your study?\nAre sufficient details of methods and analysis provided to allow replication by others?\nThe nature of the data used could be described more accurately. It could be specified, because it is not obvious for non specialists, that culled sows are not included in the mortality rate. Culling rate and sow longevity are unfortunately not available in the AHDB report, but this information would have been very interesting for this study.\n\nIt should be also very briefly explained how the number of pigs sold annually per sow is calculated/standardized. In some farms/countries, pigs are raised in the same farm until slaughter age, in some others they are sold to fattening farms after weaning. These variations make the comparison between countries uneasy.\n\nWhat Interpig is needs to be explained, so that the reader can get an idea of the reliability of the data produced by this organization. It might be indicated that InterPig belongs to the Agriculture and Horticulture Development Board (AHDB), which is not a public statistic institute, but receive national data from “production economists” working in various public or private technical institutes…\nIf applicable, is the statistical analysis and its interpretation appropriate?\nThe statistical result is clear. However, the results are based on the comparison between a group of 3 countries (using gestation crate), a group of 12 countries (using crates only for a few weeks at the beginning of gestation), and lastly a group of 2 countries having sows loose for all gestation. This is not an optimal design to perform a general linear Model (2 and 3 countries in groups are too small numbers for this kind of statistical model). A non-parametric test would have been more adequate, and whatever the statistical model used, the discussion must mention the limit of the small number of countries. When a group contains 2 or 3 countries, an uncontrolled factor influencing the variable of interest in one of these countries can influence dramatically the outcome of the statistical result.\nAre all the source data underlying the results available to ensure full reproducibility?\nYes\nAre the conclusions drawn adequately supported by the results?\nEuropean breeders now commonly recognized the absence of negative effect of loose housing on the technical-economic results of sows. Therefore, I support the conclusion of this paper, but I am not sure that the data presented here are irrefutable proof. As mentioned above, I think that the limitations and possible biases of the study should be mentioned. The grouping of countries that has been done leads to compare countries blocking or not their pregnant sows, but it compares at the same time American countries with European countries. These regions do not have the same animal genetics, the same climate, the same sources of feed, the same size of farms, etc. There are many confounding factors that can lead to an erroneous conclusion. Some of these possible biases must be cited in the discussion.\n\nThe results for UK and Switzerland, which have fully loose sows during gestation, might be discussed in one or two lines as well.\nOther minor comments:\nThe area and size of pens and crates must be indicated in units of the universal measurement system (meters).\n\nIn the second paragraph of the introduction, it is necessary to specify, for more clarity, that in the European Union, the individual crates are already prohibited during a period beginning four weeks after the mating and ending one week before the date planned for the farrowing.\n\nIn the legend of figure 2, it is not clear why authors also tried to analyze the data after removing Brazil from group 1. Since they did not remove it after all, is it useful to keep this comment? If yes, please provide some more explanations.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate? No\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8601", "date": "04 Aug 2022", "name": "Cynthia Schuck-Paim", "role": "Author Response", "response": "We would like to thank Dr. Merlot for the insightful comments and helpful suggestions. In the revised version we have addressed all the points made, as well as thoroughly checked the Report for greater clarity. REVIEWER: \"The work is very clearly presented. It cites some current literature as well as documents from governmental, European or non-governmental organizations. However, besides literature dealing with the most severe health problems generated in sows, a few other articles could have been cited as well in the introduction, for example dealing with the behavioral effects of rearing loose or crated sows during gestation, which are relevant indicators to asses sow welfare. (for example, Boyle et al, 2002, Appl Anim Behav Sci 76:119-134; Jang et al, 2017, Livestock Sci 199:37-45; Zhou et al, 2014, Animal, 8: 1162-1169)\" AUTHORS: We thank Dr. Merlot for the suggestions, additional references on the behavioral effects of the rearing system have been incorporated in the revised version. REVIEWER: \"This is a very brief study involving a limited amount of data, which fits with the scope of a report for F1000Research. It is based on the analysis of two variables (the sow mortality rate and pigs sold annually per sow), and the data have been collected by others (data are accessible freely on internet in reports edited by the Agriculture and Horticulture Development Board). However, looking at the data available in the AHDB report, I am not convinced that the two most relevant variables were chosen by authors, nor that the report would have been too long if some additional variables had been analyzed here. Indeed, except in cases of prenatal imprinting (which may occur here), the further away from the birth, the more the effects of gestation tend to be diluted by other life events (potential biases) that have occurred since. Thus, the number of sold pigs per sow could have been influenced by many other factors than crating the pregnant mothers, and which would have influenced the life of pigs in between. This limitation is compounded by the fact that the number of countries included in the study is unbalanced in the 3 groups that are compared and biased in terms of geographic distribution. This increases the likelihood that uncontrolled confounding factors will influence the result observed here. The number of weaned pigs per sow could have been studied also to enrich the study. Although it is of less economic interest than the number of pigs sold per sow, it is of greater biological interest. Indeed, the number of weaned pigs is particularly relevant because it is highly correlated with pre-weaning mortality, and most mortality in pig production occurs before weaning. Don’t you think that this 3rd variable could be added to your study?\" AUTHORS: Dr. Merlot is correct in that many factors other than the housing system affect performance and welfare. In the revised version we include such a discussion. Regarding the choice of parameters investigated, we now justify it more clearly, explaining that in this Brief Report our main goal is to explore whether the specific claims often made by industry representatives - which concern piglet output per sow and sow mortality (e.g., “...the California Department of Food and Agriculture has considered that use of loose housing systems may lead to “lower piglet output per animal and increased breeding pig mortality”) - are factually valid. The report thus focuses on the parameter of greater interest from the producers’ perspective, examining whether their claims are justified (“the number of pigs sold annually per sow is of greater economic interest than the compounding factors cited, hence it is the parameter of choice in economic assessments of the impact of sow housing reforms”). Additionally, and although we concur with the reviewer that the number of weaned pigs per sow is a variable of biological interest, the dataset for this variable seems to be incomplete, with missing data for Canada in some of the years. REVIEWER: \"The nature of the data used could be described more accurately. It could be specified, because it is not obvious for non specialists, that culled sows are not included in the mortality rate. Culling rate and sow longevity are unfortunately not available in the AHDB report, but this information would have been very interesting for this study.\" AUTHORS: We thank Dr. Merlot for the suggestion, we now clarify this point in the revised version (“Sow mortality is represented by the percentage of sows that die on the farm during the year. The Interpig network does not provide estimates of sow culling rates”) REVIEWER: \"It should be also very briefly explained how the number of pigs sold annually per sow is calculated/standardized. In some farms/countries, pigs are raised in the same farm until slaughter age, in some others they are sold to fattening farms after weaning. These variations make the comparison between countries uneasy.\" AUTHORS: Thank you once more. The revised version now explains that “We analyzed the number of pigs sold annually per sow and sow mortality per year. The former parameter is very informative of sow productivity, being compounded by several factors: pigs born alive per litter, litters per sow per year and mortality of pigs over the production cycle [pigs sold/sow/year = pigs weaned/sow/year * ((100-rearing mortality)/100) * ((100-finishing mortality)/100), where pigs weaned/sow/year = pigs born alive per litter * litters/sow/year * ((100-pre-weaning mortality)/100)].” REVIEWER: \"What Interpig is needs to be explained, so that the reader can get an idea of the reliability of the data produced by this organization. It might be indicated that InterPig belongs to the Agriculture and Horticulture Development Board (AHDB), which is not a public statistic institute, but receive national data from “production economists” working in various public or private technical institutes…\" AUTHORS: Indeed, such an explanation was missing. The revised version reads “We use publicly available data from InterPig, a network managed by the Agriculture and Horticulture Development Board (AHDB, a board of producers and other stakeholders in the UK farming industry), which collects farm and sector data from production economists in 17 countries to provide internationally harmonized methods for meaningful comparisons of national production indicators. ….. InterPig data are used predominantly for cost comparisons across countries…)”. REVIEWER: \"The statistical result is clear. However, the results are based on the comparison between a group of 3 countries (using gestation crate), a group of 12 countries (using crates only for a few weeks at the beginning of gestation), and lastly a group of 2 countries having sows loose for all gestation. This is not an optimal design to perform a general linear Model (2 and 3 countries in groups are too small numbers for this kind of statistical model). A non-parametric test would have been more adequate, and whatever the statistical model used, the discussion must mention the limit of the small number of countries. When a group contains 2 or 3 countries, an uncontrolled factor influencing the variable of interest in one of these countries can influence dramatically the outcome of the statistical result.\" AUTHORS: Dr. Merlot is right in that such a small sample size in two of the groups is not ideal. However, because of (1) the nature of the response variables, (2) the fact that non-parametric tests are necessarily associated with too much loss of information when data points are ranked and (3) they are unable to combine categorical (housing group) and continuous (year) predictors, their use is very limited in this case. GLM procedures have been shown to be very robust to handle unbalanced designs (Grafen & Hails, 2002. Modern Statistics for the Life Sciences. OUP). We have now included a more thorough description of the test results (Table 1). Importantly, the statistical results reflect accurately the data patterns shown in Figure 2. REVIEWER: \"European breeders now commonly recognized the absence of negative effect of loose housing on the technical-economic results of sows. Therefore, I support the conclusion of this paper, but I am not sure that the data presented here are irrefutable proof. As mentioned above, I think that the limitations and possible biases of the study should be mentioned. The grouping of countries that has been done leads to compare countries blocking or not their pregnant sows, but it compares at the same time American countries with European countries. These regions do not have the same animal genetics, the same climate, the same sources of feed, the same size of farms, etc. There are many confounding factors that can lead to an erroneous conclusion. Some of these possible biases must be cited in the discussion. The results for UK and Switzerland, which have fully loose sows during gestation, might be discussed in one or two lines as well.\" AUTHORS: We agree that such a discussion is needed, hence include it in the revised version (“Naturally, many are the factors that can influence the number of pigs sold per sow and sow mortality other than the crating of pregnant mothers. They include differences in environmental factors, genetics, nutrition, the type of feeding system, building design, farm size, and management. Given existing differences in these parameters across the country groups, it is not possible to establish a causal association between the lower mortality, or greater productivity, and restrictions on crate use. For example, all countries where crates are still the norm are in the American continent, whereas those where they were partially banned are in Europe, where factors such as genetics, management, farm sizes and climate differ. Similarly, results for countries where gestation crates were completely banned (UK and Sweden) are likely influenced by factors such as the inclusion of data for outdoor systems in the UK and the ban of farrowing crates in Sweden. The influence of factors other than crating is particularly likely given the small number of countries both in the CRATE and BANNED groups.”) REVIEWER: \"The area and size of pens and crates must be indicated in units of the universal measurement system (meters).\" AUTHORS: Areas and sizes are now indicated using the metric system. REVIEWER: \"In the second paragraph of the introduction, it is necessary to specify, for more clarity, that in the European Union, the individual crates are already prohibited during a period beginning four weeks after the mating and ending one week before the date planned for the farrowing.\" AUTHORS: Such a clarification has been added, thank you for the suggestion. REVIEWER: \"In the legend of figure 2, it is not clear why authors also tried to analyze the data after removing Brazil from group 1. Since they did not remove it after all, is it useful to keep this comment? If yes, please provide some more explanations.\" AUTHORS: The comment was removed, thank you for the suggestion. We thank Dr. Merlot for the time and relevant comments, which we hope to have addressed satisfactorily. Yours sincerely, Cynthia Schuck-Paim and Wladimir Alonso" } ] }, { "id": "142491", "date": "12 Jul 2022", "name": "Keelin O’Driscoll", "expertise": [ "Reviewer Expertise Animal welfare", "pig performance and management" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nGeneral comments I understand that this is a brief report, but there should be reference somewhere to the confounding factors and limitations of the results, as requested in the instructions for authors. For starters, there are only 2 countries in the ‘total ban’ category, and both of these have systems that differ significantly from those typically used in the other categories (e.g. lots of outdoor sows in the UK, Sweden requires nesting material, ban on farrowing crates etc.). It is misleading not to mention these other significant system differences, as well as the fact there is no mention of the possibility of the effect of typical genetics of the countries in the various categories. The description of the statistical analysis and outputs are not written clearly. I suggest the authors consult with a statistical colleague/expert to help them with this. Details below.\nAbstract\nIn the abstract, there is not enough information in the methods or information either as to which years of data were used.\nIntroduction\nIn the second paragraph, it would be useful to state that gestation crates are already banned in the EU (after 28 days), not just that there is pressure from the public to ban crates in the future.\n\nIn the final paragraph, I think it is valid to explore the claims even from the perspective of actual performance, as well as welfare – if the producers in countries where gestation crates are asking to weigh up the performance aspects of sows relative to their welfare, it is important to determine whether their claims re performance are actually valid (as well as using mortality and performance as a proxy for welfare).\nMaterials and methods\nFirst paragraph: I understand your meaning, but to people not familiar with Interpig data the impression is that it is primarily used for sow metrics, whereas it is much more extensive than that.\n\nSecond paragraph. State the years you used in the first sentence, as it will make the paragraph more concise. Why did you not use data from 2020, or prior to 2015?\n\nI don’t understand why you used data from AHDB (Agriculture and Horticulture Development Board) and EMBRAPA (Brazilian Agricultural Research Corporation) when you state earlier that you are using Interpig data. Why use these sources as well?\n\nFigure 1. I suggest you use ‘a’, ‘b’, ‘c’ for the different aspects of the figure (e.g. ‘a’ for the pie chart) to make it a bit easier to follow.\n\nFourth paragraph: Why do you state you \"We ‘also’ investigated the extent to which potential differences in sow mortality and productivity among housing groups were statistically significant\" How does this differ to what is described in the first paragraph?\n\nYear should not be a covariate as there are less than 6 levels, it would be better treated as a fixed effect. Tukeys is an adjustment of calculated p-values, not a test in its own right.\nResults and conclusions\nPage 4: Evidently year was not included as a covariate, because if it was then there would be no lsmeans for each year for each category. In L2 of the results, I don’t understand what the 2 different tests results refer to – one is the effect of year, what is the other one?\n\nPage 5:\nLine 1: There is no need to include ‘GLM’ in the parentheses, as you have already stated that is the test used.\n\nLine 3: Which pair-wise comparison are you referring to – is it where crates are the norm, vs where crates are allowed partially? Same for the last sentence in the paragraph. There is no need to refer to ‘Tukeys test’ as it is not a test. You could instead label the categories more concisely (e.g. USED, PARTIAL, BANNED) and then state clearly which comparison you are referring to in the text, followed by the P-value in the parentheses.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate? Partly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8602", "date": "04 Aug 2022", "name": "Cynthia Schuck-Paim", "role": "Author Response", "response": "We would like to thank Dr. O’Driscoll for the very helpful comments and suggestions, addressed below. REVIEWER: \"I understand that this is a brief report, but there should be reference somewhere to the confounding factors and limitations of the results, as requested in the instructions for authors. For starters, there are only 2 countries in the ‘total ban’ category, and both of these have systems that differ significantly from those typically used in the other categories (e.g. lots of outdoor sows in the UK, Sweden requires nesting material, ban on farrowing crates etc.). It is misleading not to mention these other significant system differences, as well as the fact there is no mention of the possibility of the effect of typical genetics of the countries in the various categories.\" AUTHORS: Thank you for the suggestions. We agree such a discussion was missing, and have now incorporated it in the revised version (“...many are the factors that can influence the number of pigs sold per sow and sow mortality other than the crating of pregnant mothers. They include differences in environmental factors, genetics, nutrition, the type of feeding system, building design, farm size, and management. Given existing differences in these parameters across the country groups, it is not possible to establish a causal association between the lower mortality, or greater productivity, and restrictions on crate use. For example, all countries where crates are still the norm are in the American continent, whereas those where they were partially banned are in Europe, where factors such as genetics, management, farm sizes and climate differ. Similarly, data on the annual number of pigs sold per sow in the two countries where gestation crates were completely banned (UK and Sweden) are likely influenced by factors such as the inclusion of data for outdoor systems in the UK. The influence of factors other than crating is particularly likely given the small number of countries both in the CRATE and BANNED groups.)” REVIEWER: \"The description of the statistical analysis and outputs are not written clearly. I suggest the authors consult with a statistical colleague/expert to help them with this. Details below.\" AUTHORS: Thank you. We have now expanded the explanation and justification for the analyses, and include a table (Table 1) with the complete outputs of the analyses. REVIEWER: \"In the abstract, there is not enough information in the methods or information either as to which years of data were used.\" AUTHORS: The abstract has been revised to include further information on the methods. REVIEWER: \"In the second paragraph, it would be useful to state that gestation crates are already banned in the EU (after 28 days), not just that there is pressure from the public to ban crates in the future.\" AUTHORS: Thanks, this information has been now incorporated into the introduction. REVIEWER: \"In the final paragraph, I think it is valid to explore the claims even from the perspective of actual performance, as well as welfare – if the producers in countries where gestation crates are asking to weigh up the performance aspects of sows relative to their welfare, it is important to determine whether their claims re performance are actually valid (as well as using mortality and performance as a proxy for welfare).\" AUTHORS: We now clarify that we are exploring whether the specific claims made by producers are factually valid (regarding mortality and performance), that we are measuring the performance indicator of greater economic interest to producer, and address more thoroughly the extent to which mortality and performance are good proxies of welfare (“It is important to highlight that mortality and productivity are not necessarily good indicators of welfare. Although higher death rates can indicate poorer health in morbid animals, mortality fails to capture the impact of non-fatal outcomes of disease, injury and deprivations on welfare (what makes animals suffer is not necessarily what kills them) [13]. There is also no necessary correlation between welfare and productivity. Management and genetic selection for higher productivity can in fact be linked with a higher likelihood of behavioral disorders and production diseases (diseases that become more prevalent or severe in proportion to the potential productivity of the system) [20,21]. For example, hyperprolific sows often experience a higher incidence of farrowing complications, such as postpartum dysgalactia and retention of placenta [14]...”) REVIEWER: \"First paragraph: I understand your meaning, but to people not familiar with Interpig data the impression is that it is primarily used for sow metrics, whereas it is much more extensive than that.\" AUTHORS: Thank you for raising this point. We now clarify that InterPig is a “network managed by the Agriculture and Horticulture Development Board (AHDB, a board of producers and other stakeholders in the UK farming industry), which collects farm and sector data from production economists in 17 countries to provide internationally harmonized methods for meaningful comparisons of national production indicators” and, importantly, that “InterPig data are used predominantly for cost comparisons across countries”. REVIEWER: \"Second paragraph. State the years you used in the first sentence, as it will make the paragraph more concise. Why did you not use data from 2020, or prior to 2015?\" AUTHORS: In the revised version of this Brief Report the choice of years is justified more thoroughly, explaining that “To reflect the most recent statistics, we used the last five years of publicly available data”, and that the year 2020 was not used because, for one of the variables (sow mortality), “data for 2020 is only available for seven of the 17 countries”. Data prior to 2015 was not used since “data on the number of pigs sold per sow annually is described in the AHDB annual reports for the period 2015-2020” only. REVIEWER: \"I don’t understand why you used data from AHDB (Agriculture and Horticulture Development Board) and EMBRAPA (Brazilian Agricultural Research Corporation) when you state earlier that you are using Interpig data. Why use these sources as well?\" AUTHORS: Thank you for the opportunity to clarify the use of sources. We now explain that InterPig is “a network managed by the Agriculture and Horticulture Development Board (AHDB)”, and that “Interpig data on the number of pigs sold per sow annually is described in the AHDB annual reports”. We also explain that “Sow mortality statistics, as collected by the Interpig network, have been made publicly available in the reports of the Brazilian Agricultural Research Corporation (a member institution)”. REVIEWER: \"Figure 1. I suggest you use ‘a’, ‘b’, ‘c’ for the different aspects of the figure (e.g. ‘a’ for the pie chart) to make it a bit easier to follow.\" AUTHORS: Thank you, the suggestion has been incorporated into Figure 1. REVIEWER: \"Fourth paragraph: Why do you state you \"We ‘also’ investigated the extent to which potential differences in sow mortality and productivity among housing groups were statistically significant\" How does this differ to what is described in the first paragraph?\" AUTHORS: Thanks for catching this inconsistency, it has been corrected now. REVIEWER: \"Year should not be a covariate as there are less than 6 levels, it would be better treated as a fixed effect. Tukeys is an adjustment of calculated p-values, not a test in its own right.Page 4: Evidently year was not included as a covariate, because if it was then there would be no lsmeans for each year for each category. In L2 of the results, I don’t understand what the 2 different tests results refer to – one is the effect of year, what is the other one?\" AUTHORS: Given the continuous nature of the predictor year, and its consistent effect across years, having it fit as a continuous predictor (1 degree of freedom) makes it more sensitive than fitting it as a categorical variable (Grafen). We have now included a table with the complete output of the statistical analyses, which we hope to have clarified what each test result refers to. REVIEWER Page 5: \"Line 1: There is no need to include ‘GLM’ in the parentheses, as you have already stated that is the test used.\" AUTHORS: Thank you, it has been removed. REVIEWER Line 3: \"Which pair-wise comparison are you referring to – is it where crates are the norm, vs where crates are allowed partially? Same for the last sentence in the paragraph. There is no need to refer to ‘Tukeys test’ as it is not a test. You could instead label the categories more concisely (e.g. USED, PARTIAL, BANNED) and then state clearly which comparison you are referring to in the text, followed by the P-value in the parentheses.\" AUTHORS: The groups have been relabeled accordingly, and the comparisons clarified. Thank you once more for the time and detailed comments, which we hope to have addressed satisfactorily. Yours, Cynthia Schuck-Paim and Wladimir Alonso" } ] } ]	1	https://f1000research.com/articles/11-564
https://f1000research.com/articles/10-344/v1	05 May 21	{ "type": "Software Tool Article", "title": "target: an R package to predict combined function of transcription factors", "authors": [ "Mahmoud Ahmed", "Deok Ryong Kim", "Mahmoud Ahmed" ], "abstract": "Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the factor ChIP experiment and the signed statistics from gene expression profiling with factor perturbation. We further extend BETA to integrate two sets of data from two factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two factors, which were found to be, on average, more cooperatively regulated.", "keywords": [ "transcription-factors", "DNA-binding", "gene-expression", "r-package", "bioconductor", "workflow" ], "content": "Introduction\n\nThe binding of a transcription factor to a genomic region (e.g., gene promoter) can have the effect of inducing or repressing its expression Latchman1. The binding sites can be identified using ChIP experiments. High through-put ChIP experiments produce hundreds or thousands of binding sites for most factors Johnson et al.2. Therefore, methods to determine which of these sites are true targets and whether they are functional or not are needed Ucar et al.3. On the other hand, perturbing the transcription factor by over-expression or knockdown and measuring the gene expression changes provide valuable information on the function of the factor Tran et al.4. Methods exist to integrate the binding data and the factor perturbation gene expression to predict the real target regions (e.g., genes)5,6. This article presents a workﬂow for using the target package to integrate binding and expression data to predict the shared targets and the combined function of two transcription factors.\n\nTo illustrate the utility of this workﬂow, we applied it to binding and expression data of the transcription factors YY1 and YY2. We asked whether the two factors cooperate or compete on their shared targets in HeLa cells.\n\n\nMethods\n\nR version: R version 4.0.3 (2020-10-10)\n\nBioconductor version: 3.11\n\nWe developed an open-source R/Bioconductor package target to implement BETA for predicting direct transcription factor targets from binding and expression data. The details of the algorithm were described here Wang et al.6. In addition, our implementation extends BETA to apply for factor combinations (Ahmed et al.7). Brieﬂy, factor potential binding sites are identified by ChIP-sequencing and gene expression under factor perturbation by microarrays or sequencing. The distances between the peaks and the transcription start sites are used to calculate the peak scores. The sum of the scores of the individual peaks in a certain region of interest is the region’s regulatory potential. A signed statistics (fold-change or t-statistics) from the differential gene expression of the factor perturbation is used to estimate the factor function. The product of the ranks of the regulatory potential and the signed statistics is the final rank of the regions.\n\nTo predict the combined function of two factors, two sets of data are required. The overlapping peaks are the potential binding sites. The product of the two signed statistics is the factor function. When the two factors agree in the direction of the regulation of a region where they both bind, they could be said to cooperate on this region. When the sign is opposite, they could be said to regulate that region competitively.\n\nThe package leverages the Bioconductor data structures such as GRanges and DataFrame to provide fast and flexible computation on the data Huber et al.8. Similar to the original python implementation, the input data are the identified peaks from the ChIP-Seq experiment and the expression data from RNA-Seq or microarrays perturbation experiment. The final output is the peaks associated with the factor binding and the predicted direct targets. We use the terms peaks to refer to the GRanges object that contains the coordinates of the peaks. We use the term region to refer to a similar object that contains the information on the regions of interest; genes, transcripts, promoter regions, etc. In both cases, any number of additional information on the ranges can be added to the object as metadata.\n\nThe algorithm was implemented in R (>=3.6) and should be able to run on any operating system. Libraries required for running the workﬂow are listed and loaded below. Alternatively, a docker image is available with R and the libraries installed on an Ubuntu image: https://hub.docker.com/r/bcmslab/target_flow.\n\n\n\n\nUse case\n\nYY1 and YY2 belong to the same family of transcription factors. YY1 is a zinc finger protein that directs deacetylase and histone acetyltransferases of the promoters of many genes. The binding of YY1 to the regulatory regions of genes results in the induction or repression of their expression. YY2 is a parloge of YY1. Similarly, it is a zinc finger protein with both activation or repression functions on its targets. Using the target analysis, we will attempt to answer the following questions. Do the two transcription factors share the same target genes? What are the consequences of the binding of each factor on its targets? If the two factors share binding sites, what is the function of the binding of the two factors to these sites?\n\nTo answer these questions, we use publicly available datasets to model the binding and gene expression under the transcription factors perturbations (Table 1). This dataset was obtained in the form of differential expression between the two conditions from KnockTF. The first dataset is gene expression profiling using microarrays of YY1/YY2 knockdown and control HeLa cells. The binding sites of the factors in HeLa cells were determined using two ChIP-Seq datasets. The ChIP peaks were obtained in the form of bed files from ChIP-Atlas. Finally, we used the USSC hg19 human genome to extract the genomic annotations.\n\nBrieﬂy, we first prepared the three sources of data for the target analysis. Then we predict the specific targets for each individual factor. Third, we predict the combined function of the two factors on the shared target genes. Finally, we show an example of a motif analysis of the competitively and cooperatively regulated targets.\n\nThe ChIP peaks were downloaded in the form of separate bed files for each factor. We first locate the files in the data/ directory and load the files using import.bed. Then the data is transformed into a suitable format, GRanges. The resulting object, peaks, is a list of two GRanges items, one for each factor.\n\n\n\nThe differential expression data were downloaded in tabular format. After locating the files in data/, we read the files using read_tsv and select and rename the relevant columns. The resulting object, express, is a list of two tibble items.\n\n\n\nThe knockdown of either factor in HeLa cells seems to change the expression of many genes in either direction (Figure 1A&B). Moreover, the changes resulting from the separate knockdown of the factors are correlated (Figure 1C). These observations suggest that many of the regulated genes are shared targets of the two factors, or they respond similarly to their perturbation of either factor.\n\nGene expression was compared between transcription factors knockdown and control HeLa cells. The fold-change and p-values of (A) YY1- and (B) YY2-knockdown are shown as volcano plots. (C) Scatter plot of the fold-change of the YY1- and YY2-knockdown.\n\n\n\nThe gene information in express is recorded using the gene SYMBOLS. They need to be mapped to the EN-TREZIDS before extracting the genomic coordinates. To do that, we use the org.Hs.eg.db to map between the identifiers. Next, we use the TxDb.Hsapiens.UCSC.hg19.knownGene to get the genomic coordinates for the transcripts and resize them to 100kb upstream from the transcription start sites.\n\n\n\nThe resulting object, genome, from the previous step is a tibble that shares the column gene_id with the expression data express. Now the two objects can be merged. The merged object, regions, is similarly a tibble containing genome and expression information of all common genes.\n\n\n\nThe standard target analysis includes identifying associated peaks using associated_peaks and direct targets using direct_targets. The inputs for these functions are the objects peaks and regions from the previous steps in addition to the column names for regions regions_col or the region and the statistics column stats_col, which is the fold-change in this case. The resulting objects are GRanges for the identified peaks assigned to the regions ap or the ranked targets. Several columns are added to the metadata objects of the GRanges to save the calculations.\n\n\n\nTo determine the dominant function of a factor, we divide the targets by the direction of the effect of knock-down of the factor on the expression of the target and show the regulatory potential of the target on these groups. We use the empirical distribution function (ECDF) to show the fraction of targets with a specified regulatory potential or less. Because the ranks rather than the absolute value of the regulatory potential are used, the lower the value, the higher the potential. Then the groups of targets can be compared to each other or a theoretical distribution.\n\n\n\nThe scores of the individual peaks are a decreasing function of the distance from the transcription start sites— the closer the factor binding site from the start site, the lower the score. The distribution of these scores is very similar for both factors (Figure 2A). The ECDF of the down-regulated of YY1 is higher than that of up-and none-regulated targets (Figure 2B). Therefore, the absence of YY1 on its targets results in aggregate in their downregulation. If indeed these are true targets, then we expect YY1 to induce their expression. The opposite is true for YY2, where more high-ranking targets are up-regulated by the factor knockdown (Figure 2C).\n\n\n\nBindings peaks of the transcription factors in HeLa cells were determined using ChIP-Seq. Distances from the transcription start sites and the transformed distances of the (A) YY1 and YY2 peaks are shown. The regulatory potential of each gene was calculated using target. Genes were grouped into up, none or down regulated based on the fold-change. The emperical cumulative distribution functions (ECDF) of the groups of (C) YY1 and (D) YY2 targets are shown at each regulatory potential value.\n\nTo formally test these observations, we use the Kolmogorov-Smirnov (KS) test. The distributions of the two groups are compared for equality. If one lies on either side of the other, then they must be drawn from different distributions. Here, we compared the up and down-regulated functions for both factors (Table 2). In both cases, the distributions of the two groups were significantly different from one another.\n\nUsing target to predict the shared target genes and the combined function of the two factors is a variation of the previous analysis. First, the shared/common peaks are generated using the overlap of their genomic coordinates, subsetByOverlaps. Second, Instead of one, two columns for the differential expression statistics, one for each factor is needed; these are supplied to the argument stats_col in the same way. Here, common_peaks and both_regions are the main inputs for the analysis functions.\n\n\n\n\n\n\n\n\n\nThe output of associated_peaks is the same as before. direct_targets is the same, but the stat and the stat_rank carry the product of the two statistics provided in the previous step and the rank of that product.\n\nThe output can also be visualized the same way. The targets are divided into three groups based on the statistics product. When the two statistics agree in the sign, the product is positive. This means the knockdown of either transcription factor results in the same direction change in the target gene expression. Therefore, the two factors would cooperate if they bind to the same site on that gene. The reverse is true for targets with oppositely signed statistics. On these targets, the two factors would be expected to compete for inducing opposing changes in the expression.\n\n\n\nThe common peak distances and scores take the same shape (Figure 3A). The two factors seem to cooperate on more of the common target than any of the two other possibilities (Figure 3B). This observation can be tested using the KS test. The curve of the cooperative targets lies above that of none and competitively regulated targets (Table 3).\n\n\n\nShared bindings sites of YY1 and YY2 in HeLa cells were determined using the overlap of the individual factor ChIP-Seq peaks. (A) Distances from the transcription start sites and the transformed distances of the shared peaks are shown. The regulatory interaction of each gene was calculated using target. Genes were grouped into cooperatively, none or competitively regulated based on the the product of the fold-changes from YY1- and YY2-knockdown. (B) The emperical cumulative distribution functions (ECDF) of the groups of targets are shown at each regulatory potential value.\n\n\n\nAny number of downstream analyses can be performed on the final output. For example, we could apply binding motif analysis to the groups of regulated targets. In this example, all the motif analysis itself is handled by the BCRANK package Ameur et al.12. Here, we explain how to prepare the input from the shared peaks and target objects produced in the last step.\n\nFirst, we extract the transcript IDs of the targets in their respective groups. Then the peaks assigned to these targets are ordered and sliced.\n\n\n\nThe input for bcrank is a fasta file with the sequence of the regions to look for frequent motifs. We used the BSgenome.Hsapiens.UCSC.hg19 to extract the sequences of the common peaks in the competitive and cooperative target groups. The sequences are first written to a temporary file and feed to the search function.\n\n\n\nThe sequences in the search path of the regions of interest are shown in (Figure 4). In the competitively regulated regions, one sequence was more frequent than all other sequences. By contrast, no sequence was uniquely frequent in the regions of cooperative targets.\n\n\n\nThe number of occurances of the sequences in the search path in the regions of (A) competitively and (B) cooperatively regulated regions.\n\nThe most frequent motifs in the two groups are shown as seq logos using the seqLogo package (Figure 5).\n\n\n\nThe weight matrices of the most frequent motifs in the (A) competitively and (B) cooperatively regulated regions were calculated and shown as seq logos. y-axis represents the information content at each position. The size of each letter represents the frequency in which the letter occure at that position.\n\n\nSummary\n\nIn this article, we present a workflow for predicting the direct targets of a transcription factor by integrating binding and expression data. The target package implements the BETA algorithm ranking gene targets based on the distance of the ChIP peaks of the transcription factor in the genes and the differential expression of the factor perturbation. To predict the combined function of two factors, two sets of data are used to find the shared peaks and the product of their differential expression.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nSoftware availability\n\nSoftware available from: https://doi.org/doi:10.18129/B9.bioc.target\n\nSource code available from: https://github.com/MahShaaban/target\n\nArchived source code as at time of publication: https://doi.org/doi:10.18129/B9.bioc.target13\n\nLicense: GPL-3", "appendix": "Acknowledgments\n\nWe thank all lab members for the discussion and comments on the early drafts of the article.\n\n\nReferences\n\nLatchman DS: Transcription factors: Bound to activate or repress. Trends Biochem Sci. 2001; 26(4): 211–3. PubMed Abstract \| Publisher Full Text\n\nJohnson DS, Mortazavi A, Myers RM, et al.: Genome-wide mapping of in vivo protein-DNAinteractions. Science. 2007; 316(5830): 1497–502. PubMed Abstract \| Publisher Full Text\n\nUcar D, Beyer A, Parthasarathy S, et al.: Predicting functionality of protein-DNA interactions by integrating diverse evidence. Bioinformatics. 2009; 25(12): i137–44. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTran LM, Brynildsen MP, Kao KC, et al.: gNCA: A framework for determining transcription factor activity based on transcriptome: Identiﬁability and numerical implementation. Metab Eng. 2005; 7(2): 128–41. PubMed Abstract \| Publisher Full Text\n\nSubramanian A, Tamayo P, Mootha VK, et al.: Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005; 102(43): 15545–15550. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWang S, Sun H, Ma J, et al.: Target analysis by integration of transcriptome and ChIP-seq data with BETA. Nat Protoc. 2013; 8(12): 2502–15. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAhmed M, Min DS, Kim DR: Integrating binding and expression data to predict transcription factors combined function. BMC Genomics. 2020; 21(1): 610. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHuber W, Carey VJ, Gentleman R, et al.: Orchestrating high-throughput genomic analysis with Bioconductor. Nat Methods. 2015; 12(2): 115–121. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nChen L, Shioda T, Coser KR, et al.: Genome-wide analysis of YY2 versus YY1 target genes. Nucleic Acids Res. 2010; 38(12): 4011–4026. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMichaud J, Praz V, Faresse VJ, et al.: HCFC1 is a common component of active human CpG-island promoters and coincides with ZNF143, THAP11, YY1, and GABP transcription factor occupancy. Genome Res. 2013; 23(6): 907–16. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWu XN, Shi TT, He YH, et al.: Methylation of transcription factor YY2 regulates its transcriptional activity and cell proliferation. Cell Discov. 2017; 3: 17035. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAmeur A, Rada-Iglesias A, Komorowski J, et al.: Identification of candidate regulatory SNPs by combination of transcription-factor-binding site prediction, SNP genotyping and haploChIP. Nucleic Acids Res. 2009; 37(12): e85. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAhmed M: target: Predict Combined Function of Transcription Factors. R package version 1.4.0, 2020. Publisher Full Text" }	[ { "id": "94695", "date": "18 Oct 2021", "name": "Shulan Tian", "expertise": [ "Reviewer Expertise Genomics", "bioinformatics", "epigenomics", "data science", "etc" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAhmed and Kim developed an R package to implement the binding and expression target analysis (BETA) package and extend the application to cases involving two transcription factors. The package predicts the potential target genes for binding sites from individual TFs or shared binding sites from two factors. There are some major concerns that need to be addressed.\n\np4: YY1 is a zinc finger protein that directs deacetylase and histone acetyltransferases of the promoters of many genes.\nThis is misleading. While YY1 binds preferentially to the promoter regions, it also binds to enhancers. YY1 binds to both and facilitates the structural interactions between regulatory elements [see Cell. 20171]. YY2 also binds to both promoters and enhancers [see Proc Natl Acad Sci U S A. 20162]. It should be \"directs histone deacetylase and acetyltransferases to ..\"\n\nYY1 and YY2 have been well studied in terms of their regulatory roles. Both have dual activating and repressive roles in regulating target gene expression, with a lot of overlap between their binding sites. How about two factors both with overall activating roles? Are there public data available to better demonstrate the applications of this package?\n\nThe R code in the manuscript is obsolete. It will be great to make the coding workflow consistent with the one that is available in bioconductor. For example, I can't find the data files mentioned in the manuscript when the target package was installed from bioconductor. Clearly lay out the strength to implement an R version vs. the original python version [described by Wang et al. 3] will be helpful, like what the authors described in the bioconductor documentation. Also, emphasize the low- or high-level functions implemented here are beneficial to general users who don't have comprehensive programming background.\n\nThe authors illustrate how to identify the target genes for the shared binding sites between two TFs. How about the gene targets of the factor-unique binding sites?\n\nThe authors set the maximum peak-to-gene TSS distance at 100kb, which is fine for the purpose of demonstration. Practically, the authors may want to provide recommendations or suggestions to the external users, since this is a very critical parameter. Based on the chromatin interaction data and co-accessibility data, peaks can target genes over a much larger distance. Alternatively, provide the option to incorporate topologically associating domains data, which will improve the detection of regulatory interactions.\n\np6: Because the ranks rather than the absolute value of the regulatory potential are used, the lower the value, the higher the potential\nBased on the original paper of the BETA package [Figure 2], genes were ranked based on their regulatory potential score (from high to low), it should be \"the lower the rank, the higher the regulatory potential\"?, Please check\nSimilarly on P7: The scores of the individual peaks are a decreasing function of the distance from the transcription start sites— the closer the factor binding site from the start site, the lower the score.\nBased on the original paper of the BETA package [Table], this should be \"the closer the factor binding site to the start site, the higher the score\"? Please check.\n\nThe authors need to check spelling and grammar more carefully and try to make it more readable. Below are some of the examples:\np3: Therefore, methods to determine which of these sites are true targets [should be true binding sites]\np3: A signed statistics (fold-change or t-statistics)\np4: YY2 is a parloge of YY1 [a paralog of YY1]\np4: This dataset was obtained in the form of differential expression between the two conditions from KnockTF [need citation]\np4: ChIP-Atlas, no citation\np4: USSC hg19 [UCSC hg19]\np5: Figure 1, The fold-change [knockdown/control?]\np5: EN-TREZIDS [Entrez IDs]\nP5: resize? them to 100kb upstream from the transcription start site [extend to 100kb...]\np12: In Summary section: based on the distance of the ChIP peaks of the transcription factor in the genes and the differential expression of the factor perturbation.\nbased on the distances of the ChIP peaks of the transcription factor relative to the TSSs of the genes\ntwo sets of data are used to find the shared peaks and the product of their differential expression\ntwo sets of data are used to find the shared peaks and the rank product of their differential expression statistics?\nTable 2. two-sided [two.sided]\nFigure 2 legend: Figure 2A: the same color was used to represent both YY1 and YY2 data. Figure 2C should be Figure 2B. Figure 2D should be Figure 2C YY1 and YY2 targets are shown at each regulatory potential value. the x-axis is the rank, not the regulatory potential value itself the same for Figure 3, the x-axis is the rank of regulatory interaction\nFigure 3 legend: what are the transformed distances of the shared peaks? Need to explain whether it represents % of distance occurances [occurrences]\nFigure 5 legend: weight matrices, position weight matrices seq logos, sequence logos the letter occure at that position, occurs at that position\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Partly\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Partly\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "7358", "date": "10 Nov 2021", "name": "Mahmoud Ahmed", "role": "Author Response", "response": "We would like to thank the reviewers for their effort and thoughtful comments. We addressed each point separately We corrected the above sentence and added another sentence to mention that the YY1 binds to the enhancer regions of many of its targets. Since this package aims to model the combined function of two factors from separate datasets, the data presented in the manuscript fit the goal well. That is, we want to see whether using data generated separately but in the same biological system we could suggest the true gene targets of the two factors. First by modeling the regulatory potential of each on the shared targets and then by considering the effect of their knockdown on the expression of the same targets. The data we used in this article is available from Figshare (and not in the package). We added a chunk of code to the manuscript to download the data from the source. This workflow article focuses on the steps to perform the analysis enabled by the package. It is not intended to be a substitute for reading the package documentation for users who are interested in the low-level functions. The code in section \"Predicting gene targets of individual factors\" does predict the targets of the individual transcription factors on their unique binding sites and the results are presented in Figure 2. This model is based on the idea that the regulatory potential of a given factor decreases with the distance from the transcription start sites. It is not clear to use whether this holds at very large distances or for regulators other than transcription factors. Therefore we used the distance recommended by the original paper and left the decision to the user to make depending on their case. Users can define their regions of interest in any way they like, for example, using TADs. Here, we used the simplest case of extracting TSSs and including stretches of the up and down streams. We corrected the sentence referred to above. We corrected the sentence referred to above and revised the manuscript for typos and grammatical errors." } ] }, { "id": "97730", "date": "08 Nov 2021", "name": "Mireia Ramos-Rodríguez", "expertise": [ "Reviewer Expertise Genomics and Regulatory Genomics", "Bioinformatics", "R and Bioconductor." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this paper, Ahmed and Kim present the target R package, which implements the BETA algorithm and extends its functionality to predict combined targets and functions of two different transcription factors (TF). By using transcription factor binding data (ChIP-seq) and gene expression data when the TF is perturbed, they are able to predict the gene targets of a single or a pair of TFs.\nThis paper raised some major concerns that need to be addressed by the authors:\nRegarding the actual package code, the distance calculation doesn’t measure the actual distance between peaks and TSS. The code of your find_distance() function subtracts the peak center from the region center to obtain the distance between these two features. This is not the same as the distance from the peak to the TSS, which is what this variable should be measuring according to your text “The scores of individual peaks are decreasing function of the distance from the transcription start sites”, your vignette “find_distance: calculate the distance between the peaks and the regions of interest, e.g. transcription start sites (TSS).” and the original method publication “∆ is the exact distance between a binding site and the TSS”. An easy way to fix this is to provide different arguments for peak and regions “how”, so the user can for example select how_peaks=”center” and how_regions=”end”. In the specific case of the code you show in this paper, those parameters would return the actual distances between peaks and TSS.\n\nRelated to the previous point, the parameter downstream in the function promoters() is set to 200 by default, so the width of the regions you are generating in the first chunk of code in page 6 actually have a width of 100,200bp. You should set this argument to 0 to actually obtain 100kb windows upstream of TSS.\n\nYY1 and YY2 might not be the best examples to use for extracting conclusions on gene targets and the combined action of both TFs. Besides YY1 activity as a TF, it can also interact with chromatin modifiers and direct them to specific regions of the genome 1. It has also been identified as a structural factor that regulates the formation and DNA loops 2. Thus, the changes in gene expression observed when perturbing this TF might not all be associated with its activity as a TF, which is the main focus of this package.\n\nThe section on the binding motif analysis is quite interesting in terms of what to do after performing the analysis with the R target package. However, I think it would be interesting to develop it a little bit more, maybe associate the sequences present in the different groups of regulated targets to actual transcription factors to see if there is a common regulatory pathway to these targets.\n\nRegarding the general text, and specifically the section “Predicting gene targets of individual factors”, I feel that the description of the main package functionality is too technical and not very informative. The authors describe all the arguments that can be provided to the different functions and the object classes that come out of them, but this description is already in the package manual. Instead of talking about the arguments and object classes, I would briefly describe what they do and how they do it, so readers can easily follow the methods without the need to read the original BETA publication or the package vignette.\n\nRelated to point 3, the datasets used in this paper are different from the ones used in the vignettes and included within the package and I wasn’t able to find it on the GEO site either. I would recommend providing this data either within the package or in the docker image they already created. This would facilitate the reproduction of the results presented in this paper.\n\nThe authors keep referring to transcription factors as “factors”, which might induce confusion when reading the article. They write “Transcription Factors” (or the abbreviation TF) to differentiate them from the broad and diverse meanings of “factors”.\n\nWhen revising the vignette I noticed that it’s missing the steps for preparing the data gene expression data, specifically the set to create windows upstream of TSS. When they load the gene expression object with (data(\"real_transcripts\")) the windows are already present. This is misleading for users that are following the vignette as they might miss this specific step and they will not be able to get the correct results when reproducing it with their own data.\n\nIn page 5, the authors mention that the changes in expression resulting from separate KD of YY1 and YY2 are correlated, but they do not provide any statistical test to confirm this. They should at least perform a correlation test and show the p-value to make this affirmation.\n\nThere are some sentences in the text that are difficult to understand. The authors should rewrite them to ensure that the readers can follow the text. Some examples are:\n\nMissing citations for “KnockTF” and “ChIP-Atlas” in p.4.\n\n“We used the USSC hg19 human genome” [p. 4], should be “UCSC”.\n\n“We first locate the files in the data/ directory” [p. 4], shouldn’t it be “save”?\n\n“They respond similarly to their perturbation of either factor” [p.5] should be “the perturbation”.\n\n“They need to be mapped to the EN-TREZIDS” [p.5] should be “ENTREZ IDs”\n\n“get the genomic coordinates for the transcripts and resize them to 100kb upstream” [p.5]. The authors should rephrase this, as they are not resizing the transcripts but rather generating 100kb windows upstream of their TSS.\n\n“we divide the targets by the direction of the effect of knock-down of the factor on the expression of the target” [p.6]. The authors should rephrase this sentence, as it is very long and difficult to follow.\n\n“The ECDF of the down-regulated of YY1 is higher than that [...]”. This whole paragraph it’s difficult to understand, the authors should rephrase it.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Partly\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Partly\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "7405", "date": "10 Nov 2021", "name": "Mahmoud Ahmed", "role": "Author Response", "response": "The solution referred to by the reviewer is already implemented in the find_distance function as an argument called how which defaults to 'center'. This is a link to the code (https://github.com/MahShaaban/target/blob/9c6f869d794cfaff63310c5f79cea1e1095e2198/R/functions.R#L47). I chose this as default since it would be neutral to the peak width. But of course, in a different use case, the user might be interested in the distance from the 'start' or 'end' of the peak. We revised the text to state the correct downstream and upstream distances as pointed out by the reviewer. We are aware of these facts. We would like to argue that using these transcription factors is still suitable. In fact, one of the main goals of the package is to distinguish between the direct targets of transcription factors and the ones that change indirectly, hence the reliance on both gene expression and peak binding. However, the definition of target here might be broadened to include cases like the ones pointed to by the reviewer. The goal of this section, as correctly pointed out by the reviewer, is to give an example of further analysis of the target package output. There is a number of further analysis that could be performed using the found motifs, but it is beyond the purpose of this workflow article to get into. We revised the section to briefly describe what each function does and how. We added to the revised version of the manuscript a chunk of code to download the dataset. We revised the text to use \"transcription factor\" instead of just \"factor\", when appropriate. The data object real_transcripts is made up of the test data provided by BETA. The original files are too large to be included in the R package. The processing is script is part of the package though, `inst/extdata/make-data.R` We calculated the correlation coefficient for the fold-change of YY1 and 2 and added it to the text. We revised the text to correct the errors and rephrase difficult sentences." } ] } ]	1	https://f1000research.com/articles/10-344
https://f1000research.com/articles/11-222/v1	24 Feb 22	{ "type": "Correspondence", "title": "Lupeol and pristimerin do not inhibit activation of the human sperm CatSper Ca(2+)-channel", "authors": [ "Anders Rehfeld", "Christian Marcus Pedersen" ], "abstract": "Opposing findings have been published on the regulation of the sperm-specific Ca2+ channel CatSper (cation channel of sperm) in human sperm cells by the plant triterpenoids lupeol and pristimerin. While the original study on this topic found these triterpenoids to act as potent inhibitors of human CatSper, subsequent studies have failed to replicate such an inhibitory effect. It has been suggested that these issues could in part be due to purity issues and/or batch variation between the plant-derived extracts of lupeol and pristimerin obtained for the studies. The aim of this study was to elucidate this controversy by investigating the batches of lupeol and pristimerin used in our previous study with state-of-the-art 1H-, 13C- and 2D-nuclear magnetic resonance (NMR) methods to reveal potential purity and/or batch variation issues. When comparing the NMR-spectra obtained from 1H-NMR and 13C-NMR with previously published NMR-spectra for lupeol and pristimerin, we could confirm that both the lupeol and pristimerin batch were ≥95 % pure. These results confirm the validity of the findings in our previous study for lupeol and pristimerin, showing that lupeol and pristimerin do not inhibit activation of CatSper in human sperm. In conclusion, using 1H-, 13C- and 2D-NMR methods, we confirm that the lupeol and pristimerin batches used in our previous study were ≥95 % pure and thereby fail to identify any purity issues and/or batch variation that could explain the observed inability of lupeol and pristimerin to inhibit activation of CatSper in human sperm.", "keywords": [ "Fertility", "CatSper", "Male reproduction", "Lupeol", "Pristimerin", "Sperm function" ], "content": "\n\nThe putative inhibitory action of the two plant triterpenoids lupeol and pristimerin on the activation of the human sperm CatSper Ca(2+)-channel has recently been debated in the scientific literature. The original study on this subject (Mannowetz et al., 2017) indicated that these triterpenoids act as very potent and efficacious inhibitors of progesterone-activated CatSper-currents in human sperm cells with IC50-values in the lower nM range, and a follow-up study by the same research group confirmed the inhibitory action of pristimerin on progesterone-induced Ca(2+)-influxes via CatSper through measurements in the principal piece of the flagellum in single human sperm cells (Mannowetz et al., 2018).\n\nIn contrast to these findings, two studies from independent research groups failed entirely to replicate any inhibitory action for neither lupeol nor pristimerin on progesterone-induced Ca(2+)-influxes through CatSper in populations of human sperm cells (Brenker et al., 2018; Rehfeld, 2020) and progesterone-activated CatSper-currents in single human sperm cells (Brenker et al., 2018), even when exposing the sperm cells to lupeol and pristimerin at much higher µM concentrations.\n\nThe complete failure of these studies to replicate the findings from (Mannowetz et al., 2017; Mannowetz et al., 2018) is highly concerning since a patent has been filed (Lishko & Mannowetz, 2018) and a company (YourChoice Therapeutics, CA, US) has been formed based on the original discovery by (Mannowetz et al., 2017; Mannowetz et al., 2018) that lupeol and pristimerin act as potent inhibitors of human CatSper and could thus potentially be used as novel male and female contraceptives.\n\nSince the publication of the most recent study on this matter (Rehfeld, 2020), the corresponding author was contacted by researchers who questioned the validity of the results presented in the study for lupeol and pristimerin, i.e., the inability to reproduce the inhibitory action of these triterpenoids on human CatSper, and suggested that the failure to identify such an inhibitory effect on human CatSper could be due to purity issues and/or batch variation between the plant-derived extracts of lupeol and pristimerin obtained for the study from Cayman Chemicals (MI, USA).\n\nAlthough Cayman Chemicals stated that the lupeol and pristimerin batches were delivered with a purity of ≥98 %, we fully agreed with these researchers that it would be good scientific conduct and of general interest of the field of human sperm physiology to examine the two stocks solutions used in (Rehfeld, 2020), i.e., a 5 mM pristimerin dimethylsulfoxid (DMSO) stock and a 1 mM lupeol ethanol stock, using state-of-the-art 1H-, 13C- and 2D-nuclear magnetic resonance (NMR) methods (Bruker 500 MHz Ultrashield Plus equipped with a CryoProbe, Bruker, Germany) to reveal potential purity and/or batch variation issues in these stocks.\n\nTo prepare the stocks for the NMR-measurements, we first evaporated the ethanol from the lupeol stock, removed the DMSO from the pristimerin stock using an evaporation system (V-10 evaporator, Biotage, Sweden), and exchanged the solvent for both triterpenoids to deuterated chloroform (CDCl3). The raw NMR data can be found as Underling data (Rehfeld, 2022a). When comparing the NMR-spectra obtained on the two stocks from 1H-NMR and especially 13C-NMR (see Extended data (Rehfeld, 2022b)) with previously published NMR-spectra for lupeol and pristimerin (Espindola et al., 2018; Shwe et al., 2019), we could confirm that Cayman Chemicals had indeed provided us with batches containing lupeol and pristimerin, respectively. Furthermore, the NMR-data showed that both lupeol and pristimerin were ≥95 % pure (Extended data (Rehfeld, 2022b)), despite the prolonged storage at -20 °C since conducting the experiments for (Rehfeld, 2020).\n\nTaken together, the results provided here confirms the validity of the findings in our previous study for lupeol and pristimerin (Rehfeld, 2020), i.e., that the two plant triterpenoids lupeol and pristimerin do not inhibit activation of CatSper in human sperm. The findings in (Rehfeld, 2020) are therefore still in line with the observations by (Brenker et al., 2018) and still contradicting the putative inhibitory action of lupeol and pristimerin on human CatSper described in (Mannowetz et al., 2017; Mannowetz et al., 2018).\n\nIn conclusion, using state-of-the-art 1H-, 13C- and 2D-NMR methods, we confirm here that the lupeol and pristimerin stocks used in (Rehfeld, 2020) were ≥95 % pure and thereby fail to identify any purity issues and/or batch variation that could explain the observed inability of these triterpenoids to inhibit activation of CatSper in human sperm.\n\n\nData availability\n\nFigshare. Raw 1H-, 13C- and 2D-NMR data for lupeol and pristimerin in MestReNova (Mnova) format. https://doi.org/10.6084/m9.figshare.19181087.v1 (Rehfeld, 2022a).\n\nData are available under the terms of the Creative Commons Zero \"No rights reserved\" data waiver (CC0 1.0 Public domain dedication).\n\nRaw 1H-, 13C- and 2D-NMR data for lupeol and pristimerin in MestReNova (Mnova) format are also available at the BMRbig repository, part of the Biological Magnetic Resonance Data Bank (BMRB), with ID: BMRbig35, https://bmrbig.org/released/bmrbig35.\n\nFigshare: Supplementary file 1. https://doi.org/10.6084/m9.figshare.19134488.v1 (Rehfeld, 2022b).\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nBrenker C, Schiffer C, Wagner IV, et al.: Action of steroids and plant triterpenoids on CatSper Ca2+ channels in human sperm. Proc Natl Acad Sci U S A. 2018; 115(3): E344–E346. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nEspindola LS, Dusi RG, Demarque DP, et al.: Cytotoxic Triterpenes from Salacia crassifolia and Metabolite Profiling of Celastraceae Species. Molecules. 2018; 23(6): 1494. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLishko PV, Mannowetz N: Contraceptive use of triterpenoids. World Intellectual Property Organization. 2018. Reference Source\n\nMannowetz N, Miller MR, Lishko PV: Regulation of the sperm calcium channel CatSper by endogenous steroids and plant triterpenoids. Proc Natl Acad Sci U S A. 2017; 114(22): 5743–5748. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMannowetz N, Mundt N, Lishko PV: Reply to Brenker et al.: The plant triterpenoid pristimerin inhibits calcium influx into human spermatozoa via CatSper. Proc Natl Acad Sci U S A. 2018; 115(3): E347–E348. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRehfeld A: Revisiting the action of steroids and triterpenoids on the human sperm Ca2+ channel CatSper. Mol Hum Reprod. 2020; 26(11): 816–824. PubMed Abstract \| Publisher Full Text\n\nRehfeld A: NMR dataset of Lupeol and Pristimerin. figshare. Dataset. 2022a. http://www.doi.org/10.6084/m9.figshare.19181087.v1\n\nRehfeld A: Supplementary file 1.docx. figshare. Dataset. 2022b. http://www.doi.org/10.6084/m9.figshare.19134488.v1\n\nShwe HH, Win KK, Moe TT, et al.: Isolation and Structural Characterization of Lupeol from the Stem Bark of Diospyros ehretioides Wall. IEEE-SEM. 2019; 7(8): 140–144. Reference Source" }	[ { "id": "125363", "date": "02 Mar 2022", "name": "João Ramalho-Santos", "expertise": [ "Reviewer Expertise Sperm physiology", "male and female infertility", "reproductive and stem cell biology." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nMy comments have to do with the fact that, while the topic is very worthwhile, this is not exactly (in my view) a straightforward Correspondence. The steps are as follows:\nOriginally a paper is published in Proceedings of the National Academy of Sciences of the United States of America (PNAS) in 2017 showing that Lupeol and pristimerin strongly inhibits the CatSper channel, the implication being that they could be used in male contraception, and apparently a company was formed with that in mind.\n\nIn 2018 (also in PNAS) other authors question this data suggesting that there are, in fact, no effects.\n\nThe original 2017 authors contest this, stand by their results and suggest that their data is valid and that the negative results are based on monitoring different things. Sample purity is not mentioned in this exchange.\n\nIt should be noted that none of the authors of this correspondence were involved in this controversy, the first author did work with the team that published the 2018 paper, and confirmed the absence of results with CatSper not being inhibited by Lupeol and pristimerin in a 2020 Molecular Human Reproduction (MHR) paper.\nIn this correspondence the authors perform NMR spectra to show that Lupeol and pristimerin are as pure as possible, and that the absence of inhibition of CatSper is therefore a true result. One authors is an expert on sperm (and CatSper in particular), the other on chemical structures, so I have no issues with the data here at all. However, I doubt that this will in any meaningful way solve the contradiction. Using other batches of Lupeol and pristimerin might be a possibility, or at least framing the discussion a bit more thoroughly and discussing/updating the issues raised in the 2018 exchange, that, as stated, never mention sample purity. But I do respect the authors not wanting to do this, as they were not part of those papers.\n\nIs the rationale for commenting on the previous publication clearly described? Partly\n\nAre any opinions stated well-argued, clear and cogent? Yes\n\nAre arguments sufficiently supported by evidence from the published literature or by new data and results? Partly\n\nIs the conclusion balanced and justified on the basis of the presented arguments? Partly", "responses": [ { "c_id": "7919", "date": "04 Mar 2022", "name": "Anders Rehfeld", "role": "Author Response", "response": "I fully agree with the reviewer in his comment that this is not a straightforward Correspondence. I would have preferred to be able to publish all my data on this issue as a Letter to the original PNAS paper, but unfortunately, there was a 6-month limit to submit such Letters to articles in PNAS and I did not have any data ready within that timeframe. My way into writing this Correspondence was this: I read the original 2017 PNAS paper and was very excited about the novel CatSper-inhibitor compounds Lupeol and Pristimerin, which seemed to be highly potent and efficacious compared to other known CatSper-inhibitors. I therefore ordered these compounds to use them in my own studies as CatSper-inhibitors. I received Lupeol and Pristimerin, diluted them according to the recommendation of the vendor and started testing them in my own experimental setup. However, I could not identify any inhibitory effects of the compounds on CatSper in human sperm cells. Puzzled, I contacted the authors of the original 2017 PNAS paper to discuss what I might have done wrong. The authors of the original 2017 PNAS paper suggested me to test Lupeol and Pristimerin prepared at different stock concentrations in different solvents, with or without sonication, as well as from different vendors. However, in the end I could still not observe any inhibition of human CatSper in my assay. At this point I decided to re-examine both the two triterpenoids, Lupeol and Pristimerin, and the steroids investigated in the original 2017 PNAS paper using my own experimental setup. This collected work is what I published in the 2020 Molecular Human Reproduction paper. After publishing this 2020 Molecular Human Reproduction paper, I was contacted per e-mail by researchers who questioned the validity of the results presented in the study for Lupeol and Pristimerin, and suggested that my failure to identify inhibitory effects on human CatSper could be due to purity issues and/or batch variation between the plant-derived extracts of Lupeol and Pristimerin obtained for the study. As the reviewer states, this purity issue was not mentioned in the 2018 PNAS exchange. I had to agree with the researchers that this could of course be true and something that I should have investigated before submitting the 2020 Molecular Human Reproduction paper. I thus contacted, Christian Marcus Pedersen, a chemical scientist from the chemical department at the University of Copenhagen, and asked him to perform nuclear magnetic resonance analyses of the Lupeol and Pristimerin stocks I used for the 2020 Molecular Human Reproduction study. Christian Marcus Pedersen performed nuclear magnetic resonance analyses of my Lupeol and Pristimerin batches and thankfully both compounds were present at high purity, even despite the prolonged storage at -20 °C since conducting the experiments for the 2020 Molecular Human Reproduction paper. At this point I simply wanted to share these additional important data, which I thought were highly relevant for the discussion of the putative inhibitory effects of Lupeol and Pristimerin on human CatSper. Unfortunately, it was not possible for me to simply add these nuclear magnetic resonance data to the 2020 Molecular Human Reproduction paper, why I had to identify another journal to get the data published, accessible, and citable to other researchers of the human sperm physiology field. Luckily Correspondence articles at F1000 Research were suitable for exactly this. Of note, I believe that I discussed several issues raised in the 2018 PNAS exchange quite thoroughly in the 2020 Molecular Human Reproduction paper, e.g., the claim that Ca2+-signals must be recorded specifically from the principal piece of the flagellum only to be able to observe an inhibitory effect on CatSper in human sperm cells, which did not agree with my observations using the other CatSper-inhibitor RU1968. However, if other reviewers also suggest this, we can of course update our Correspondence to discuss the issues raised in the 2018 PNAS exchange more thoroughly. I fully agree with the reviewer that this Correspondence may not solve this controversy. However, in a recent review article “Natural Products with Potential for Nonhormonal Male Contraception” (J. Nat. Prod. 2021, 84, 2762−2774), they also discuss the controversy regarding the action of Lupeol and Pristimerin on human CatSper, and state the following: “These contradictory findings suggest a need for further studies to confirm the action or lack of action of the plant triterpenoids on the CatSper channel. The conflicting results also demonstrate the difficulties in reproducibility of results, which is often a barrier to studies of natural compounds in general.”. I believe that we are following up on this exact suggestion with this Correspondence and I hope it will be helpful for solving the issue and reaching consensus in the human sperm physiology field at some point. In the end, my hope is that other researchers reading our Correspondence will obtain Lupeol and Pristimerin themselves and test these compounds for effects on CatSper in human sperm cells in their own lab and hopefully at some point publish their findings like we have done here. This will be the only way to solve this controversy in my opinion." }, { "c_id": "8473", "date": "02 Aug 2022", "name": "Anders Rehfeld", "role": "Author Response", "response": "As the other reviewers also suggest that we discuss the issues raised in the 2018 PNAS exchange, we have now update our Correspondence manuscript to address these issues more thoroughly." } ] }, { "id": "129824", "date": "13 Apr 2022", "name": "Tao Luo", "expertise": [ "Reviewer Expertise Male infertility" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nDifferent research groups showed contradictory results on whether plant triterpenoids, lupeol and pristimerin, inhibit the activation of CatSper. It has been suggested that these issues could in part be due to purity issues and/or batch variation between the plant-derived extracts of lupeol and pristimerin obtained for the studies.\nThis manuscript aimed to elucidate this controversy by investigating the batches of lupeol and pristimerin used in their previous study using state-of-the-art 1H-, 13C- and 2D-nuclear magnetic resonance (NMR) methods. The authors confirm that the lupeol and pristimerin batches used in their previous study were ≥95 % pure. Therefore, they concluded that the purity issues and/or batch variation could not explain the inability of lupeol and pristimerin to inhibit activation of CatSper in human sperm found in their previous study. The opinions stated are well-argued, clear and cogent. The arguments were sufficiently supported by evidence from the new data.\nHowever, the manuscript did not discuss or respond to the other two important issues argued by Mannowetz et al. 2018:\nAn electrical driving force of 20 mV generated from a holding potential of −80 to −100 mV, as shown by Brenker et al. 2018, is neither enough to reliably assess inward CatSper currents nor to estimate “fold current increase”.\n\nIf it is of interest to study CatSper-mediated calcium influx into spermatozoa, individual principle pieces (PPs) as regions of interest must be analyzed.\nIf these issues are addressed, the controversy may be better elucidated.\n\nIs the rationale for commenting on the previous publication clearly described? Yes\n\nAre any opinions stated well-argued, clear and cogent? Yes\n\nAre arguments sufficiently supported by evidence from the published literature or by new data and results? Yes\n\nIs the conclusion balanced and justified on the basis of the presented arguments? Yes", "responses": [ { "c_id": "8474", "date": "02 Aug 2022", "name": "Anders Rehfeld", "role": "Author Response", "response": "We have now addressed these two issues in the discussion of the updated manuscript." } ] }, { "id": "129827", "date": "04 May 2022", "name": "Huafeng Wang", "expertise": [ "Reviewer Expertise sperm", "CatSper", "ion channel", "electrophysiology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe effects of lupeol and pristimerin on human CatSper have aroused a controversy since two PNAS papers were published from different groups (Mannowetz et al., 2017 and Brenker et al., 2018). This manuscript was aiming to uncover a potential possibility for a better explanation by examining the purity of lupeol and pristimerin, together with their previous work (Molecular Human Reproduction, 2020). It is believed the data in this manuscript was solid and convincing. However, is the lupeol and pristimerin tested in this manuscript from same batch with the other two groups? If not, it would be great to test those from the two groups individually, even though the purity was not mentioned in this controversy (Mannowetz et al., 2018 and Brenker et al., 2018).\n\nIs the rationale for commenting on the previous publication clearly described? Yes\n\nAre any opinions stated well-argued, clear and cogent? Partly\n\nAre arguments sufficiently supported by evidence from the published literature or by new data and results? Partly\n\nIs the conclusion balanced and justified on the basis of the presented arguments? Partly", "responses": [ { "c_id": "8475", "date": "02 Aug 2022", "name": "Anders Rehfeld", "role": "Author Response", "response": "We have now contacted these groups to offer them NMR-analyses of their lupeol and pristimerin batches." } ] } ]	1	https://f1000research.com/articles/11-222
https://f1000research.com/articles/11-884/v1	02 Aug 22	{ "type": "Research Article", "title": "Physical, psychological, academic, and sexual abuse of university students in five Latin American countries: characteristics and association with student satisfaction: a cross-sectional study", "authors": [ "Christian R. Mejia", "Diego J. Castro", "Naysha Torrejon", "Jhosselyn I. Chacon", "Lorena Fernandez-Espindola", "Isaac Martinez-Cornejo", "Diego J. Castro", "Naysha Torrejon", "Jhosselyn I. Chacon", "Lorena Fernandez-Espindola", "Isaac Martinez-Cornejo" ], "abstract": "Background: A high rate of student abuse has been reported in various studies; however, few studies substantiate the seriousness of the issue in Latin American contexts. This study aimed to characterize the abuse of university students in five Latin American countries and its association with student satisfaction.\n\nMethods: An analytical transversal study was conducted, in which 2,141 undergraduate students from Paraguay, Ecuador, Colombia, Venezuela, and Panama were surveyed. A validated questionnaire was applied to evaluate four types of abuse (Cronbach's Alpha: 0.90): psychological, physical, academic, and sexual. In addition, students’ perception of satisfaction of four items in the university environment (Cronbach's Alpha: 0.85) was also analyzed.\n\nResults: It was found that the older students were, the more dissatisfied they were with “logistics” (aPR: 1.02; 95% CI: 1.00-1.04; p-value; 0.014) and the top-third segment of those who perceived “sexual abuse” were more dissatisfied with the teaching provided by their universities (aPR: 1.23; 95% CI: 1.00-1.52; p-value: 0.048). Moreover, those who were most dissatisfied with the agreements were part of the top-third segment of those who perceived sexual abuse (aPR: 1.16; 95% CI: 1.03-1.32; p-value: 0.016) and those in the country of Panama were less dissatisfied with “agreements” (RPa: 0.70; 95% CI: 0.66-0.073; p-value<0.001). The countries of Colombia (aPR: 0.08; IC95%: 0.01-0.59; p-value: 0.014) and Panama (aPR: 0.57; 95% CI: 0.52-0.64; p-value<0.001) were less dissatisfied with investigation programs.\n\nConclusions: The perception of ‘sexual abuse’ was the only risk factor statistically associated with dissatisfaction with teaching and agreements.", "keywords": [ "Physical Abuse", "Sex Offenses", "Students", "Latin America." ], "content": "Introduction\n\nStudying in higher educational institutions is a rigorous and demanding process. During this period students face many challenges; however, they sometimes come across additional obstacles that they should not be facing. The most prevalent of these is abuse. Abuse impacts academic performance and the sense of satisfaction students feel towards their universities. Multiple studies have demonstrated this. In one such study that was conducted on medical students in Peru, it was concluded that abuse could have consequences for students, their academic performance and, even their future as professionals.1 However, these are not the only negative consequences, as other studies have shown that the abuse of university students is associated with Burnout syndrome,2 alcohol consumption,3 and post-traumatic stress.4\n\nThese consequences shed light on the importance of this issue, since university students are frequently subjected to various forms of psychological, physical, academic, and sexual abuse, as evidenced by a study conducted at the University of Manizales-Colombia, where 71% of the students faced at least one type of abuse.5 Another study conducted at the Universidad Nacional San Luis Gonzaga de Ica-Perú showed that the most frequent type of abuse was psychological (97%), followed by academic (87%), physical (63%), and sexual (21%).6 These types of abuse are also correlated with overall satisfaction with the university. In Mexico, teachers' treatment of their students is reported to be the most important factor in any evaluation of their work.7\n\nThe treatment of students seems to be more prevalent in developing countries. Reports from UK show that the quality of teaching, organization, and management are the most important factors in determining a student’s satisfaction.8 A study conducted in Spain showed that teaching, academic reputation, sports activities, and international programs are the most influential variables in student satisfaction.9 However, in Latin America the context is different from that of developed countries, which can influence students’ decision to stay in college.10 Therefore, the objective of this research is to characterize the types of abuse experienced among university students across five Latin American countries and its association with student satisfaction.\n\n\nMethods\n\nAn analytical cross-sectional study was conducted, in which information was collected by surveying undergraduate university students from Paraguay, Ecuador, Colombia, Venezuela, and Panama during November 2017. The survey collected demographic data from the respondents, data regarding the different forms of abuse that they were subjected to, and data on the degree of general satisfaction they felt with their higher education institution. This survey used Likert – type responses and was available through Google Forms. Non-probability sampling was used to attain a minimum sample size of 2,029 (calculated from a previous pilot study, where the minimum difference was found to be 36% and 39%, a statistical power of 80%, and a confidence level of 95% for a single sample).\n\nData collected from undergraduate students who were attending higher education institutions and agreed to voluntarily participate in the research from Paraguay, Ecuador, Colombia, Venezuela, and Panama were included in the study. Surveys that were duplicated or did not meet the study criteria were excluded (less than 3% exclusion). The survey was an open survey distributed via email, WhatsApp, and Facebook messenger.\n\nThe present study was inspired from a test conducted in a Peruvian student population, in which the main study variables were the following four types of abuse: psychological, academic, physical, and sexual.6 The authors used a scale developed by Munayco-Guillen et al. called “Questionnaire of Perception of Mistreatment in the Medical Student” was composed of three sections; 1) Sociodemographic and educational characteristics; 2) Perception of mistreatment according to four components: (a) psychological mistreatment (8 items), (b) physical mistreatment (3 items), (c) academic mistreatment (4 items) and (d) sexual mistreatment (8 items); 3) Place where mistreatment had taken place, reporting the mistreatment and reasons for not reporting the mistreatment. For this study we also considered all the variables of the scale. The Cronbach’s alpha of the survey was 0.8.6 In addition, the different forms of satisfaction that students perceived in terms of university logistics, teacher training, university agreements, and activities related to undergraduate research were collected using the Likert Scale (very satisfied, satisfied, indifferent, dissatisfied, and very dissatisfied). The Likert type response was used because it was suggested by the authors of the instrument validation.\n\nThe reliability of all questions was corroborated by Cronbach's Alpha statistical test, which yielded a result of 0.89. The positive mistreatment was considered for university students who were part of the top-third segment in terms of the total score obtained in each of the four aspects (this was contrasted with those who fell under the remaining two thirds).\n\nFinally, in addition to the variables already mentioned, we collected demographic information including age, gender (female or male), university (private or public), university career, year of study, and country of residence (according to the five already mentioned). A copy of the questionnaire can be found in the Extended data.39\n\nA database was created using the MS Excel program (Windows 2016 version), data was then reviewed, and cleaned before statistical analysis. Stata version 14 was used to analyze the data, and a descriptive analysis of the categorical variables was performed using absolute and relative frequencies. In addition, bivariate and multivariate regression analyses were performed to estimate the magnitude of association of the variables of interest. Graphics were used to show distribution (box and whiskers charts) (see Figure 2). Generalized linear models were used (with the Poisson family, log-link function, models for robust variances, and adjusting for the respondent's location) to obtain adjusted prevalence ratios, 95% confidence intervals, and p-values, which were statistically significant.\n\nThe study was approved by the ethics committee of the Hospital Nacional Docente Madre Niño San Bartolomé (Lima-Peru). Ethical approval number: [0665-2017-OADI-HONADOMANI-SB]. Anonymity of participants was respected throughout, and the survey didn’t request names, addresses, or any information that could be a source of identification. Furthermore, before statistical analysis, data was codified to be deidentified. Every participant was informed about study objectives, and they gave their written consent before take part of the study. Because the study was conducted virtually, written consent was requested as an option to check at the beginning of the survey. The participant could decide to take part or refuse to fill out the survey without having provided any prior information.\n\n\nResults\n\n3500 people were invited to take part in the project. Of these, 800 did not meet the inclusion criteria and were withdrawn during quality control. Of the remainder, 559 participants who met the inclusion criteria but did not complete the questionnaire were withdrawn. 2,141 students surveyed in Latin America, the highest percentages of dissatisfaction were found for the activities related to “undergraduate research” category of the survey: 12% very dissatisfied and 18% dissatisfied. Percentages of students who were dissatisfied with “agreements” were as follows: 10% very dissatisfied and 22% dissatisfied, and dissatisfaction with “logistics of their university” accounted for 9% (very dissatisfied) and 18% (dissatisfied) (Figure 1). The full results of the survey can be found under Underlying data.39\n\nThe box and whiskers charts show that the median dissatisfaction score was higher than the satisfaction score in all four cases of type of abuse experienced: psychological (Figure 2A), physical (Figure 2B), academic (Figure 2C), and sexual (Figure 2D).\n\nNote: The higher the score, the more abuse.\n\nMultivariate regression analysis showed that the older the person, the more dissatisfaction was felt with “logistics” (aPR: 1.02; 95% CI: 1.00-1.04; p-value: 0.014); moreover, those in the upper tertile level of the section of students who perceived sexual abuse were more dissatisfied with the “teaching provided by universities” (aPR: 1.23; 95% CI: 1.00-1.52; p-value: 0.048) (Table 1).\n\n* This variable was analyzed in its quantitative format. Adjusted prevalence ratios (95% confidence intervals) and p-values were obtained using generalized linear models (with the Poisson family, log-link function, models for robust variances, and adjusting for the respondent’s location).\n\nIn another multivariate analysis, it was found that those who felt the greatest sense of dissatisfaction with the university agreements also belonged to the top-third segment of those who perceived sexual abuse (aPR: 1.16; 95% CI: 1.03-1.32; p-value: 0.016), and students in the country of Panama were less dissatisfied with “the agreements” (aPR: 0.70; 95% CI: 0.66-0.073; p-value <0.001). Students from Colombia (aPR: 0.08; 95% CI: 0.01-0.59; p-value: 0.014) and Panama (aPR: 0.57; 95% CI: 0.52-0.64; p-value <0.001) were least dissatisfied with “the research.” Both models were adjusted for other types of abuse, sex, age, type of university, and location of the respondent (Table 2).\n\n* This variable was analyzed in its quantitative format. Adjusted prevalence ratios (95% confidence intervals) and p-values were obtained using generalized linear models (with the Poisson family, log-link function, models for robust variances, and adjusting for the respondent’s location).\n\n\nDiscussion\n\nThe abuse faced by university students is an alarming issue worldwide. Its high prevalence is recorded by many studies. One study, which was conducted among university students across three medical schools in Thailand, found that 63% of students reported they had experienced some form of abuse at university.11 The issue has gained greater importance following the increased media exposure of gender-based discrimination.12 It must be remembered that abuse has different devastating consequences on students’ lives such as, hampered academic performance,1,13 the consumption of harmful substances,3 affects on health,2,4 and affects on their decisions regarding their future professional training.14\n\nThe present study reveals that the various types of abuse (physical, psychological, academic, and sexual) are directly related to the degree of satisfaction perceived by university students in their higher education centers. These findings have been corroborated by similar studies and suggest a growing issue that cannot go unnoticed.15–19 This leads us to believe that interventions are needed to mitigate abuse and its consequences, so that student welfare can be improved, and students can get the most out of the learning process.\n\nOn the other hand, this research found that a higher degree of dissatisfaction was associated with the agreements that each university offers to their students to improve their education as well as the opportunities in terms of undergraduate research. This corroborates a study conducted in higher education institutions across the Toluca Valley, which found that students in public universities show less satisfaction with the university agreements offered to them by their universities in terms of job opportunities or educational institutions, as opposed to students in private higher education institutions.20 Another study conducted at the University of Castile in Spain showed that student satisfaction was related to “the agreements” that provided opportunities for student exchange programs in order to strengthen their university experience.9 In other studies, it was not uncommon for universities in Latin American countries to account for low scientific production by medical students due to the lack of specific strategies to promote undergraduate research.21 This is important because university quality is reduced when they do not offer agreements with other universities, and there are few opportunities to carry out research training activities.22–24\n\nIn addition, students who were dissatisfied with “teaching” and with “the agreements” also had a greater perception of sexual abuse. This is a serious issue; at the University of Manizales-Colombia, 29% of all medical students reported at least one perceived event of sexual abuse.5 Similar results were observed in studies conducted on medical interns at the National Polytechnic Institute in Mexico,25 and on students in other medical and dental schools.1,6,26 However, these are not the only studies that highlight the importance of the topic; a study on nursing students also corroborated this with similar results.27–29 Thus, it can be concluded that the perception of sexual abuse is directly proportional to dissatisfaction, suggesting that this is a topic that should be given more attention in future studies. This is a problem that has not been explored in a large population, and it is therefore recommended that university authorities and rectors in each country take preventive and remedial measures to tackle it.\n\nFurther, our study found that the older the student, the more dissatisfaction there was with the logistics of their university. This result corroborates two studies: one included undergraduate students from five private universities in Bangladesh30 and the other included graduate students from China, India, Indonesia, and Thailand.31 Both studies correlated age with degree of satisfaction, including logistical satisfaction. Conversely, there are studies that conclude that although dissatisfaction is linked to the logistical services offered by the university, student age is not considered a relevant factor. These results were reproduced in two more studies, one of which was conducted at the Universidad Autónoma de Tamaulipas, where 27% of all students were dissatisfied with university logistics.7 The other study was conducted at the Universidad Autónoma de Nayarit, where 41% of students were satisfied with the logistical services provided by their university.32 Similar results were also found among university students in Chile, Mexico, and Colombia.33–36 A study conducted on psychology graduates from three universities in Chile found a high degree of satisfaction with university logistics.37 These results highlight that more research is required on this issue, since the factors that directly intervene in logistical satisfaction are not clear. This is important because university welfare is related to the quality of logistics implemented by each university, which in turn influences academic satisfaction and performance (confirmed by a study conducted at the Universidad Autónoma de San Luis Potosí38).\n\nDespite what has been described above, the present study found that Panamanian university students were less satisfied with “the agreements” offered by their universities. This could be related to their multiple links with universities and other first-world institutions, which other higher education centers do not have, as shown by a study conducted in higher education institutions in the Toluca Valley.20 In addition, students from countries such as Colombia and Panama have shown less dissatisfaction with the research conducted at their campuses, which could be related to the greater support provided to students in their institutions to encourage undergraduate publication.\n\nIt is important to mention that this study has certain limitations. The results cannot be extrapolated to all students in the countries mentioned in this study as no random sampling and/or multiple levels of stratification were undertaken. However, the results are nonetheless very valuable since for the first time, they shed light on the abuse faced by students and the association with their level of perceived satisfaction, in a wide and diverse Latin American student population. It has already been established that this research is contextual in nature; therefore, university institutions should carry out longitudinal research to measure the causality of the different aspects of satisfaction.\n\nBased on the results, it is concluded that there is a relationship between some aspects of student satisfaction and the abuse that they may have received. The older the student, the more they were dissatisfied with the logistics. Those who were in the upper third percentile of those who perceived sexual abuse had greater dissatisfaction with the teaching given by the universities, and were most dissatisfied with university agreements. The country that was most satisfied with the “agreements” of its institution was Panama. In turn, Panama and Colombia were satisfied with the research conducted at their universities.\n\n\nData availability\n\nZenodo: Physical, psychological, academic, and sexual abuse of university students in five Latin American countries: characteristics and association with student satisfaction, https://doi.org/10.5281/zenodo.6228828.39\n\nThis project contains the following underlying data:\n\n- Base_Satisf-y-maltrato-en-est_Diego-Naysha.xlsx (full results from survey)\n\nThis project contains the following extended data:\n\n- Survey.pdf\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgments\n\nTo the student Franco Rodríguez, for the assistance he provided in the writing of the manuscript.\n\n\nReferences\n\nMejia CR, Quiñones-Laveriano DM, Chacón JI, et al.: Factores socioeducativos asociados a la percepción de maltrato en estudiantes de medicina peruanos. Rev Cuba Educ Medica Super. 2018; 32(1): 74–84.Reference Source\n\nCook AF, Arora VM, Rasinski KA, et al.: The Prevalence of Medical Student Mistreatment and Its Association With Burnout. Acad Med. 2014; 89(5): 749–754. PubMed Abstract \| Publisher Full Text\n\nDeHart T, Longua-Peterson J, Richeson JA, et al.: A Diary Study of Daily Perceived Mistreatment and Alcohol Consumption in College Students. Basic Appl Soc Psych. 2014; 36(5): 443–451. Publisher Full Text\n\nHeru A, Gagne G, Strong D: Medical Student Mistreatment Results in Symptoms of Posttraumatic Stress. Acad Psychiatry. 2009; 33(4): 302–306. PubMed Abstract \| Publisher Full Text\n\nBermeo JL, Castaño-Castrillón JJ, López-Román A, et al.: Abuso académico a estudiantes de pregrado por parte de docentes de los programas de Medicina de Manizales, Colombia. Rev la Fac Med. 2016; 64(1): 9–19. Publisher Full Text\n\nMunayco-Guillén F, Cámara-Reyes A, Muñoz-Tafur LJ, et al.: Características del maltrato hacia estudiantes de medicina de una Universidad pública del Perú. Rev Peru Med Exp Salud Publica. 2016; 33(1): 58–66. PubMed Abstract \| Publisher Full Text\n\nSalinas-Gutiérrez A, Martínez-Camblor P: Principales factores de satisfacción entre los estudiantes universitarios. Rev Int Ciencias Soc y Humanidades. 2007; 17(1): 163–192.\n\nBurgess A, Senior C, Moores E: A 10-year case study on the changing determinants of university student satisfaction in the UK. PLoS One. 2018; 13(2): e0192976–e0192915. PubMed Abstract \| Publisher Full Text\n\nResino J, González J, Montero E, et al.: Calidad de vida universitaria: Identificación de los principales indicadores de satisfacción estudiantil. Rev Educ. 2013; (362): 458–484. Publisher Full Text\n\nDos Santos M: Calidad y satisfacción: el caso de la Universidad de Jaén. Rev la Educ Super. 2016; 45(178): 79–95. Publisher Full Text\n\nPitanupong J, Sathaporn K: The Prevalence and Factors Associated with Mistreatment Perception among Thai Medical Students in a Southern Medical School. Siriraj Med J. 2019; 71(4): 310–317. Publisher Full Text Reference Source\n\nHill KA, Samuels EA, Gross CP, et al.: Assessment of the Prevalence of Medical Student Mistreatment by Sex, Race/Ethnicity, and Sexual Orientation. JAMA Intern. Med. 2020; 180(5): 653–665. PubMed Abstract \| Publisher Full Text\n\nFranco-Cedeño F, Osorio-Sánchez A, Cervantes-Molina P: Relación entre el bienestar psicológico, rendimiento académico y acoso en los estudiantes universitarios. Univ y Soc. 2018; 10(3): 134–141.Reference Source\n\nStratton TD, McLaughlin MA, Witte FM, et al.: Does Students’ Exposure to Gender Discrimination and Sexual Harassment in Medical School Affect Specialty Choice and Residency Program Selection? Acad Med. 2005; 80(4): 400–408. PubMed Abstract \| Publisher Full Text\n\nAkanni DWMM, Adjadohoun SBMG, Damien BG, et al.: Mistreatment of students and associated factors in the Faculty of Medicine of Parakou in 2018. Pan Afr Med J. 2019; 34: 1–11. Publisher Full Text\n\nJaramillo-Sandoval DA, Yanez-Gallardo R: Impacto emocional en estudiantes de pedagogía ante eventos de maltrato en la práctica profesional. Lib Psicol. 2015; 21(2): 245–252.\n\nPeres MFT, Babler F, Arakaki JNL, et al.: Mistreatment in an academic setting and medical students’ perceptions about their course in São Paulo, Brazil: A cross-sectional study. Sao Paulo Med. J. 2016; 134(2): 130–137. PubMed Abstract \| Publisher Full Text\n\nWang C, Dong X, Yang J, et al.: Sexual violence experienced by male and female Chinese college students in Guangzhou. Inj Prev. 2015; 21(1): e99–e104. PubMed Abstract \| Publisher Full Text\n\nPhillips SP, Webber J, Imbeau S, et al.: Sexual Harassment of Canadian Medical Students: A National Survey. EClinicalMedicine. 2019; 7: 15–20. PubMed Abstract \| Publisher Full Text\n\nAlvarez-Botello J, Martha E, Salinas C, et al.: Estudio de la Satisfacción de los Estudiantes con los Servicios Educativos brindados por Instituciones de Educación Superior del Valle de Toluca. Rev Iberoam sobre Calidad, Efic y Cambio en Educ. 2014; 13(2): 5–26.\n\nGonzales-Saldaña J, Chavez-Uceda T, Lemus-Arteaga K, et al.: Producción científica de la facultad de medicina de una universidad peruana en SCOPUS y Pubmed. Educ Medica. 2018; 19: 128–134.Reference Source\n\nGonzález R, Tinoco MÁ, Torres VH: Análisis de la satisfacción de la experiencia universitaria de los egresados en 2015 de la Universidad de Colima. Paradig Económico. 2016; 59–84.Reference Source\n\nBlanco N, Herrera D, Reyes Y, et al.: Dificultades en el desarrollo de las habilidades investigativas en los estudiantes de Medicina. EduMeCentro. 2014; 6(1): 98–113.\n\nRivera-García CG, Espinosa-Manfugás J, Valdés-Bencomo Y: La investigación científica en las universidades ecuatorianas: Prioridad del sistema educativo vigente. Rev Cuba Educ Super. 2017; 36(2): 113–125.\n\nFuentes-Unzueta R, Manrique-Nava C, Domínguez-Márquez O: Condiciones generales de los estudiantes de medicina de la generación 2010 durante su internado rotatorio de pregrado en la escuela superior de medicina del Instituto Politécnico nacional. Acta Bioeth. 2015; 21(1): 29–36. Publisher Full Text\n\nGarbin CAS, Zina LG, Garbin AJI, et al.: Sexual harassment in Dentistry: Prevalence in dental school. J Appl Oral Sci. 2010; 18(5): 447–452. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNava BR, Mariscal SLR, Estrada JRO: La percepción del maltrato de las y los estudiantes nayaritas en las carreras universitarias de medicina y enfermería. Un primer acercamiento Waxapa. 2013; 5(9): 20–30.\n\nPonce R Magnitud de exposición de violencia en alumnos de enfermería en diferentes escenarios. 2015; 6(1): 1–11\n\nÇelebioĝlu A, Akpinar RB, Küçükoĝlu S, et al.: Violence experienced by Turkish nursing students in clinical settings: Their emotions and behaviors. Nurse Educ Today. 2010; 30(7): 687–691. Publisher Full Text\n\nAkareem HS, Hossain SS: Determinants of education quality: what makes students’ perception different? Open Rev Educ Res. 2016; 3(1): 52–67. Publisher Full Text\n\nArambewela R, Hall J, Zuhair S: Student Satisfaction: Impact of Age and Gender on Satisfaction Among International Postgraduate Students from Asia. Deakin Research Online. 2007; 15(3): 15–18.\n\nJiménez A, Terriquez B, Robles F: Evaluación de la satisfacción académica de los estudiantes de la Universidad Autónoma de Nayarit. Rev Fuente. 2011; 6(6): 46–56.\n\nRomán-Fuentes JC, Franco-Gurría RT, Gordillo-Martínez ÁE: Satisfacción estudiantil sobre servicios recibidos en la universidad: Percepción de egresados. Rev Int Adm Finanz. 2015; 8(3): 103–112.\n\nDe la Fuente MH, Navarro MM, Riquelme MJR: Análisis de la satisfacción universitaria en la facultad de Ingenería de la Universidad de Talca. Ingeniare. 2010; 18(3): 350–363. Publisher Full Text\n\nCandelas C, Gurruchaga M, Mejias A, et al.: Medición de la satisfacción estudiantil universitaria: Un estudio de caso en una institución Mexicana. Iberoam. J Ind Eng. 2013; 9(5): 261–274.\n\nCarlos J, Schmalbach V: Análisis de la calidad en el servicio y satisfacción de los estudiantes de Ciencias Económicas de la Universidad de Cartagena mediante un modelo de ecuaciones estructurales. Redie. 2011; 13: 108–122.\n\nEspinoza-Díaz ÓG, González-Fiegehen LE, Loyola-Campos JI: Evaluación de la satisfacción de titulados de la carrera de psicología en Chile. Innovación educativa. 2018; 18: 171–192.\n\nGómez D, Martínez E, Recio R, et al.: Lealtad, satisfacción y rendimiento académico en los estudiantes de la UASLP-UAMZM. Sophia. 2013; 9: 1–17.\n\nMejia CR, Castro D, Torrejon N, et al.: Physical, psychological, academic, and sexual abuse of university students in five Latin American countries: characteristics and association with student satisfaction - Survey and database.2021. Publisher Full Text" }	[ { "id": "196973", "date": "05 Sep 2023", "name": "Viann Nguyen-Feng", "expertise": [], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nOverall comments:\nThe authors successfully conducted an ambitious study examining four abuse types (physical, psychological, academic, sexual) among university students across five Latin American countries. The study is important in shedding light on such abuse experiences among students in countries that are typically underrepresented in the literature. My comments below primarily focus on providing enough information to replicate the study; defining terminology in a more trauma-informed, inclusive manner; and directly connecting the writing to the study’s specific research question. I appreciate the opportunity to review this manuscript.\nDetailed comments:\nAbstract:\nBriefly describing the term “’logistics’” would be helpful so that the reader can be informed of the constructs of interest from reviewing the abstract alone.\n\nReconsider the use of quotations around the term “’sexual abuse,’” as the quotes might appear invalidating to students’ experiences. Similarly, please reconsider referencing such abuse experiences as student “perceptions” throughout the manuscript. Perhaps “report of sexual abuse” or another phrase would be more supportive of students’ reported experiences.\n\nPlease specify the comparator when the authors state “less dissatisfied.” Less dissatisfied than whom or what?\nIntroduction:\nReconsider describing abuse as an “obstacle,” as the term might appear minimizing to some survivor-victims given that broad range of non-abuse stressors that are typically referenced with the term “obstacle.”\n\n“The most prevalent of these is abuse.” > Could the authors please provide a citation?\n\n“The treatment of students seems to be more prevalent in developing countries.” > I encourage the authors to soften this statement, given the limited cross-cultural research that would provide empirical support for the statement.\n\nConsider being more specific when noting that countries are “developed” or not. Do the authors mean “economically developed” or another metric of development?\nMethods:\nDesign and population: Could the authors please include a citation for the previous pilot study mentioned?\n\nSelection of participants: More detail would be helpful here. How many universities in each country participated? How were students targeted/recruited within each university? Who did the recruiting (faculty, staff, peers/students)? What did the recruitment advertisements say? What were the specific inclusion/exclusion criteria? The last question is particularly important given that nearly a quarter of participants did not meet inclusion criteria.\n\nData collection: Could the authors please clarify the sample on which this alphas were determined as well as the items/subscale/scale that were considered? The Questionnaire of Perception of Mistreatment in the Medical Student seems to have a number of distinct subscales in which between-subscale internal consistency would not be needed. Briefly defining these subscales and including sample items would also be helpful. For instance, how is “academic mistreatment” defined?\n\nData collection: How did the authors decide to use terciles as cut-points?\n\nData collection: In this section and throughout the manuscript, please review verbiage to ensure that gender identity and sex assigned at birth are not conflated and that response options themselves (e.g., “male”) are not described as a standalone variable, as the latter dismisses minoritized identities.\n\nData analysis: Slightly more details about the models are needed. For instance, the term “variables of interest” does not quite explicate the specific predictors and outcomes that were input into the various regression models. Please clarify these variables, as doing so would also allow the reader to understand other analytic decisions, such as why a Poisson distribution was selected.\n\nConsider moving Figure 1 prior to Figure 2 in the text.\nResults:\nProviding a definition for the constructs of interest (particularly “agreements” and “logistics”) earlier in the paper would allow the reader to more easily interpret the results.\n\nHow come Paraguay was selected as the comparator country? Rationale for this would be helpful earlier in the manuscript.\nDiscussion:\nReferencing gender-based discrimination only in the discussion appears out of place. If the authors wish to keep its mention in, some expansion on this topic and its explicit connection to the study objectives would be helpful.\n\nDiscussion of prior literature appears strong in this section. Although the cited literature discusses some of the present study’s constructs of interest, connections to abuse itself are missing and warrants further connection given that abuse is critical to the present study’s research question.\n\nThe limitations section needs to be expanded, as only one limitation is mentioned.\n\nThe concluding paragraph is clear and concise although excludes how the findings relate to abuse. Given that abuse is critical to the present study’s research question, connections to abuse warrant being mentioned in the concluding paragraph.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-884
https://f1000research.com/articles/11-664/v1	16 Jun 22	{ "type": "Research Article", "title": "Prospects for using charity lotteries in social marketing", "authors": [ "Sergey Evgenievich Barykin", "Svetlana Bozhuk", "Nelli Kozlova", "Nataliia Krasnostavskaia", "Reena Mehta", "Stepan Vinokurov", "Inga Nimenia", "Irina Vasilievna Kapustina", "Elena Naumova", "Natalia Dedyukhina", "Svetlana Bozhuk", "Nelli Kozlova", "Nataliia Krasnostavskaia", "Reena Mehta", "Stepan Vinokurov", "Inga Nimenia", "Irina Vasilievna Kapustina", "Elena Naumova", "Natalia Dedyukhina" ], "abstract": "Background: The purpose of this work is to study the prospects of using charity lotteries as a marketing tool for involving consumers and employees in charitable activities. Methods: The research methodology is based on the principles of the theory of planned behavior by Ajzen. Results: The study confirmed that behavioral intention is correlated with actual behavior. Subjective norms factors have the most significant influence on behavioral intention. Conclusions: Correlation analysis allowed us to establish a weak effect of socio-demographic characteristics (Age, Gender, Capital Status, Ownership of Home, Educational Qualification, Employment, Annual Income) on behavior. The experience of participating in the lottery in the past also turned out to be insignificant. There is reason to believe that Russian consumers' decision to participate in the charity lottery is impulsive or due to pressure from their surroundings.", "keywords": [ "social marketing", "CSR", "charity lotteries", "consumer behavior", "theory of planned behavior" ], "content": "Introduction\n\nIn Russia, charity as a type of social activity of the population has existed for a long time, but charity lotteries are rarely used.\n\nCharitable organizations, whose purpose is to accumulate funds for gratuitous assistance, cannot have the funds necessary for the prize fund due to legislative regulation. Thus, charity lotteries in Russia can be commercial organizations that carry out long-term cooperation with a charitable foundation.\n\nPractice shows that a commercial organization uses charitable events within the corporate social responsibility (CSR) policy framework to create new value for the consumer. Companies can also involve their employees in charity events, which affects the morale of the team. Thus, holding a charity lottery serves the goals of both the internal and external strategy of the organization.\n\nVolunteer movement (providing action assistance), charitable fundraising (financial aid), and charity lotteries are usually considered options for involving people in philanthropic projects. Compared with other ways of attracting people to charity projects, Charity lotteries have a dual perception. On the one hand, charity lotteries are perceived as entertainment and even gambling. On the other hand, charity lotteries have a more motivating nature, encouraging an essential potential win. A volunteer movement or charitable fundraising requires high motivation in charitable, social, and environmental projects. Participation in the charity lottery does not require significant efforts from the participants. The winner gets a prize, the losers – the opportunity to participate in an essential social campaign.\n\nIn Russia, there is a practice of holding charity lotteries. An excellent example is the charity projects “Help and Win” and “Your Star”, conducted by the joint-stock company (JSC) “Russian Railways” and the public joint stock corporation (PJSC) “Aeroflot”. Passengers are invited to purchase a charity card and win a prize. The beneficiary of this lottery is the charitable foundation “Lifeline”. Currently, due to the spread of coronavirus disease (COVID-19), the sale of postcards and other non-food items on flights is suspended. The “Lifeline” foundation assesses the experience of using charity lotteries as positive; the funds received provide treatment for 70 seriously ill children a year. However, the matter of the effectiveness of the lottery as a fundraising method remains open. Currently, disposable income levels in developing countries remain low. The lottery can be attractive to consumers with its potential benefits.\n\nThe purpose of this work is to identify the prospects for using charity lotteries as a marketing tool for involving consumers and employees in charitable activities. During the study, the following objectives were set: to identify the level of consumer awareness of charity lotteries; to identify the factors that most determine the behavior of participants in charity lotteries; to define what is the position of consumers about charity lotteries, to find out whether charity lotteries create additional value for consumers.\n\n\nMethods\n\nInternational studies of countries by level of charity take into account the respondent’s actions over the past month (monetary donations, volunteer activities, any help to a stranger who needed it), the number of people involved in providing charitable assistance (in %), as well as the general attitude of the people of the country to charity and volunteer activities. These studies reflect the attitude that characterizes people’s behavior to a greater extent. In our opinion, the evaluation of the charity index serves the purpose of tracking changes, helping to determine the dynamics of social achievements and comparing their activities with the best practices of other countries. However, for this study, this evaluation mechanism seems too narrow. It reflects the consequences, not the reasons for the attitude to charity. It does not consider the impact of business strategy on the involvement of consumers and employees in charity events. Therefore, the theoretical basis for our research was in socially responsible marketing tools and consumer behavior.\n\nBased on the research review, it can be concluded that the current social image is an integral part of organizational strategies in developed countries. The authors also support the claims of many researchers that the social responsibility of an organization contributes to its competitiveness. Attention to the effectiveness of social responsibility and its impact on the organization’s competitiveness gave impetus to a detailed study of consumer behavior and their reaction to various social projects. It should be understood that consumers are significant stakeholders for the organization. Therefore, their position on social responsibility can exert pressure on the organization’s decisions.\n\nFor a perception of charitable activities to be appropriately formed, it is necessary to understand the nature of the attitude of consumers and other interested parties to philanthropic events. This research perspective remains relevant for developing countries, as CSR practices are not sustainable. A focus on CSR activities as a source of self-oriented value for consumers provides an opportunity for marketers to create differentiation and augment what is a dominant emphasis on other-oriented value in CSR research (Peloza and Shang 2011; Azmat and Ha 2013; Anadol et al. 2015).\n\nParminder Kaur investigated consumers’ perception of the social responsibility of organizations, taking into account their desire to purchase a product, and notes that there is a positive relationship between consumer confidence, which is the result of the CSR of the company, and the intention to purchase its product (Kaur 2013).\n\nK. B. Bello, A. and K. Md Nor conclude the willingness of consumers to reward socially responsible companies with positive reviews. Consumers’ reaction to CSR can manifest itself in the form of trust, a higher perceived quality of service, increased customer satisfaction and loyalty, purchase intentions, and an increase in the share of purchases (Bello et al. 2021).\n\nConsumer expectations motivate marketers to incorporate social considerations into their marketing practices and communicate about those actions (Castaldo et al. 2009; Chernev and Blair 2015; Golob et al. 2015; Chaudary et al. 2016). Although studies show that perception of CSR toward community has a substantial influence on consumers’ attitude when considering purchases in the distant or indefinite future, the impact of such information on purchases shortly (for example, at the time of purchase) will be quite insignificant (Brown and Dacin 1997; Carrigan and Attalla 2001; Tian et al. 2011; Becker-Olsen 2014). In these situations, the consumer is more influenced by factors such as brand availability or specific functional attributes of products. If consumers believe that a company which is engaged in socially responsible activities produces outcomes which are worse for the market than firms that do not worry about social responsibilities, then information about social responsibility will not bring the desired effect (Rivera et al. 2016; Wan et al. 2016; Schill and Godefroit 2021).\n\nSankar Sen and C. B. Bhattacharya note that consumers in company assessments are more sensitive to negative information about CSR than positive; moreover, all consumers react negatively to negative news, whereas positive information receives a positive reaction only from those consumers who themselves are involved in solving social problems (Sen and Bhattacharya 2001).\n\nThe theoretical analysis allowed us to make some generalizations. Participation in charity events, including charity lotteries, has the potential to create additional value for the company and has an impact on the formation of its social image in the eyes of both consumers and employees, as well as other stakeholders (Bhattacharya et al. 2009; Semeijn et al. 2014; Lu et al. 2015; Du and Sen 2016; Gürlek et al. 2017; Afzali and Kim 2021). However, the issue of choosing tools for involving consumers in charitable activities is poorly considered (de Los Salmones et al. 2005). The World Charity Index considers only two options - financial assistance (giving money to strangers or donations) and volunteering. The potential of the charity lottery as a tool for involving consumers and employees in charitable activities remains unclear (Hildebrand et al. 2017; Chen McCain et al. 2019; Li et al. 2021).\n\nThe potential of charitable events to create additional value is the subject of applied research. Analysis of research data carried out by the British Research Institute of Public Relations, Mail. Ru Corporation, and Russian Public Opinion Research Center (VTsIOM), the Charity Fund “Gift of Life (Podari Zhizn’)” allowed to identify the factors that determine the attitude to charity in general.\n\nThe British Research Institute of Public Relations conducted a study on the importance of charity for households in a sample consisting of 2,070 adults. The study revealed popular forms of participation in charity: shopping in charity shops, visiting charitable institutions, or events organized by a charitable organization. Among the factors determining the attitude to charity, gender and age were noted. An interesting result was the absence of a linear relationship between income and participation in charity.\n\nThe Mail. Ru Corporation and Russian Public Opinion Research Center (VTsIOM) conducted a study called “Attitudes towards Charity in Russia”, which examined the opinions of 1,500 respondents aged 18 to 60 living in large Russian cities. The barriers to charity identified in the study in Russia are distrust of charitable organizations (49% of respondents) and lack of money for charity (48% of respondents).\n\nThe incentive to participate in a charity event is the availability of detailed information about the action. In addition, the support of their family members and close and familiar friends is essential to users. The third incentive for respondents was the availability of various bonuses for charity. Thus, the nature of charity lotteries’ motivation helps get a positive reaction to the event.\n\nThe charity fund “Gift of Life (Podari Zhizn’)” surveyed 1,434 donors and 1,600 people who are not involved in charitable activities. The study revealed that the factors of the gender and age of respondents influenced their charity training. Education and income level also matter. Philanthropists most often are motivated in their actions. These are purposeful people who want to solve society’s problems through collective action.\n\nEmpirical studies have provided valuable information about many factors that determine people’s attitude to charity in general. There is reason to believe that the factors of awareness, the emotional coloring of the charity project, the opinions of the immediate environment, and the norms of behavior recommended by the external environment and socio-demographic characteristics are causal factors determining the reaction to the charity lottery. However, there is no direct evidence that the identified trends persist for charity lotteries.\n\nThe methodology of studying people’s attitudes and their willingness to participate in the lottery is based on the principles of the Theory of Planned Behavior by Ajzen (TPB) (Ajzen and Fisbbein 1974; Ajzen 1991). TPB defines a person’s behavior as the result of their conscious decision to act in a certain way (Ajzen 2012, 2015; Barbera and Ajzen 2020; Bosnjak et al. 2020). The strengths of the TPB methodology are that it applies to various forms of behavior, takes into account a small range of influencing factors, and is easy to use. Therefore, TPB has received substantial research support (al Jarah and Emeagwali 2017; Miller 2017; Gupta 2021).\n\nAccording to the theory of planned behavior, the choice of a person’s conscious decision is determined by three factors: attitude to behavior (Aact), subjective norms (SN) and perceived behavioral control (PBC). Together they form behavioral intention (BI) (Ajzen 2012) (Figure 1). The factors of the TPB model were supplemented, taking into account empirical studies. The complete list of factors is shown in Table 1. The “behavior (B)” factor was considered an influential factor.\n\nTwo types of seven-point scales are used in the questions: a semantic differential (for Aact) and an evaluation scale with the points: 1 = Strongly Disagree, 2 = Disagree, 3 = Slightly Disagree, 4 = Neutral, 5 = Slightly Agree, 6 = Agree, and 7 = Strongly Agree.\n\nThe main hypotheses:\n\nH1 – the stronger the attitude towards behavior (Aact), the stronger the behavioral intention (BI).\n\nH2 – the greater the perceived behavioral control (PBC), the stronger the behavioral intention (BI).\n\nH3 – the stronger the subjective norms (SN), the stronger the behavioral intention (BI).\n\nH4 – the stronger the valuable belief in luck/karma, the stronger the behavioral intention (BI).\n\nH5 – the greater the normative beliefs (NB), the stronger the behavior behavioral intention (BI).\n\nH6 – behavioral intention (BI) is correlated with actual behavior (B).\n\nA Structural Equation Modeling (SEM) approach was selected to analyze the cause-effect relationships among constructs used in the study.\n\n\nResults\n\nThe sample was 355 people (Barykin 2022). The respondents’ age distribution: arithmetic mean - 24.8 years, median - 21 years, total span - 49 years, standard deviation - 8.2 years. Gender distribution: male - 159 people (44.8% of respondents); female - 196 people (52.2% of respondents).\n\nAbout 11% of respondents have already participated in charity lotteries. About 9% of respondents participated in charity lotteries at least once in the last year. Only 40% of respondents had an idea about the existence of such lotteries.\n\nHowever, the survey showed that if the respondents knew that such an event was taking place, 48% of the respondents would participate.\n\nCorrelation analysis made it possible to establish a weak influence of socio-demographic factors (Age, Gender, Marital Status, Ownership of Home, Educational Qualification, Employment, Annual Income) on behavior. In further analysis, these factors were not considered when constructing the model.\n\nThe construct Experience (Exper) was insignificant and was excluded from further analysis. Variables P6 (construct PBC) and S10 (construct SN) were also removed from other research.\n\nThe results of the adjusted confirmatory factor analysis (CFA) are shown in Table 2.\n\nThe results of the CFA are the basis for building a structural model (SEM), which is used to test hypotheses. The structural modeling and hypothesis testing results are presented in Figure 2 and Table 3.\n\n\nDiscussion\n\nThe quality of the resulting model leaves much to be desired for predicting the behavior of Russian consumers. R2 is low, i.e., some critical factors seem to be missing. It may be necessary to use more surface scales to measure variables.\n\nMost of the research hypotheses were not confirmed. However, the influence of SN on BI was confirmed. The BI has been proven to determine the resulting behavior. However, there are quite a few factors that explain Intention. Statistical analysis of individual factors shows their connection with intention and directly with the resulting behavior. Therefore, it is not possible to separate the direct influence of these factors on behavior from the power of intentions.\n\nIt can be assumed that people are guided by more general motives for charity (Romani et al. 2013; Hildebrand et al. 2017), while answers to questions regarding pragmatic reasons and specific values (winning, government benefits, beliefs about lotteries in general) turn out to be insignificant. It can be doubted that there is a rational internal motivation to participate in charity. Studies (Norgaard 2006; Slote 2013; Cappelen et al. 2018) show that the structure of donations usually speaks in favor of the desire to avoid negative emotions, superstitious fears, and judgment, rather than in favor of the desire to help solve problems.\n\n\nConclusions\n\nThe study showed that Russian consumers are not aware of charity lotteries. The potential of charity lotteries to engage consumers in charity remains unclear. The study has established that subjective norms define behavioral intention. Behavioral intention is correlated with actual behavior. There is reason to believe that Russian consumers make decisions about charity either impulsively (as opposed to buying clothes online) or under pressure from their environment.\n\nThe Russian specificity of charity shows the importance of trust in a charity project. Charity lottery as a form of entertainment does not build trust. The trust factor is also related to the declared informal norms of behavior and public control, which are formed by cultural traditions and the media. Russian cultural traditions favor charity donations over lotteries.\n\n\nData availability\n\nFigshare: Questionnaire Prospects for Using Charity Lotteries, https://doi.org/10.6084/m9.figshare.19726942.v1 (Barykin 2022).\n\nThis project contains the following underlying data:\n\n• Questionnaire Prospects for Using Charity Lotteries.xlsx (questionnaire responses for the study on prospects for using charity lotteries in social marketing)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nEthical approval and consent\n\nApproval was obtained from Peter the Great St. Petersburg Polytechnic University Institutional Review Board (Approving Number F-1-Q1-2022). An informed consent form was used to obtain consent from the participants of this study. All participants voluntarily took part in this study.", "appendix": "Acknowledgments\n\nWe are thankful to the Ministry of Science and Higher Education of the Russian Federation for the financial support of this project.\n\n\nReferences\n\nAfzali H, Kim SS: Consumers’ responses to corporate social responsibility: The mediating role of csr authenticity. Sustainability (Switzerland). 2021; 13: 1–13. Publisher Full Text\n\nAjzen I: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991; 50: 179–211. Publisher Full Text\n\nAjzen I: Martin fishbein’s legacy: The reasoned action approach. Ann. Am. Acad. Pol. Soc. Sci. 2012; 640: 11–27. Publisher Full Text\n\nAjzen I: Consumer attitudes and behavior: the theory of planned behavior applied to food consumption decisions. Italian Rev. Agric. Econ. 2015; 70: 121–138. Publisher Full Text\n\nAjzen I: TPB Questionnaire Construction 1 CONSTRUCTING A THEORY OF PLANNED BEHAVIOR QUESTIONNAIRE.\n\nAjzen I, Fisbbein M: Factors Influencing Intentions and the Intention-Behavior Relation. Hum. Relat. 1974; 27: 1–15. Publisher Full Text\n\nal Jarah A , Emeagwali OL: Corporate social responsibility and behavioral intention: The moderator effect of contextual factors: A meta-analytic examination. Soc. Responsib. J. 2017; 13: 678–697. Publisher Full Text\n\nAnadol Y, Youssef MA, Thiruvattal E: Consumer reaction towards corporate social responsibility in United Arab Emirates. Soc. Responsib. J. 2015; 11: 19–35. Publisher Full Text\n\nAzmat F, Ha H: Corporate Social Responsibility, Customer Trust, and Loyalty-Perspectives from a Developing Country. Thunderbird Int. Bus. Rev. 2013; 55: 253–270. Publisher Full Text\n\nla Barbera F , Ajzen I: Control interactions in the theory of planned behavior: Rethinking the role of subjective norm. Eur. J. Psychol. 2020; 16: 401–417. PubMed Abstract \| Publisher Full Text\n\nBarykin S: data for Prospects for Using Charity Lotteries calculations.xlsx. figshare. Dataset. 2022. Publisher Full Text\n\nBecker-Olsen K: The CSR Conundrum: understanding consumer response to Corporate Social Responsibility.2014; pp 149–174\n\nBello KB, Jusoh A, Md Nor K: Relationships and impacts of perceived CSR, service quality, customer satisfaction and consumer rights awareness. Soc. Responsib. J. 2021; 17: 1116–1130. Publisher Full Text\n\nBhattacharya CB, Korschun D, Sen S: Strengthening stakeholder-company relationships through mutually beneficial corporate social responsibility initiatives. J. Bus. Ethics. 2009; 85: 257–272. Publisher Full Text\n\nBosnjak M, Ajzen I, Schmidt P: The theory of planned behavior: Selected recent advances and applications. Eur. J. Psychol. 2020; 16: 352–356. PubMed Abstract \| Publisher Full Text\n\nBrown TJ, Dacin PA: The company and the product: Corporate associations and consumer product responses. J. Mark. 1997; 61: 68–84. Publisher Full Text\n\nCappelen A, Cappelen C, Kuhnle S, et al.: How to retrench the welfare state: Attitudes in the general population. Soc. Policy Adm. 2018; 52: 862–879. Publisher Full Text\n\nCarrigan M, Attalla A: The myth of the ethical consumer – do ethics matter in purchase behaviour? J. Consum. Mark. 2001; 18: 560–578. Publisher Full Text\n\nCastaldo S, Perrini F, Misani N, et al.: The missing link between corporate social responsibility and consumer trust: The case of fair trade products. J. Bus. Ethics. 2009; 84: 1–15. Publisher Full Text\n\nChaudary S, Zahid Z, Shahid S, et al.: Customer perception of CSR initiatives: Its antecedents and consequences. Soc. Responsib. J. 2016; 12: 263–279. Publisher Full Text\n\nChen McCain S-L, Lolli JC, Liu E, et al.: The relationship between casino corporate social responsibility and casino customer loyalty. Tour. Econ. 2019; 25: 569–592. Publisher Full Text\n\nChernev A, Blair S: Doing well by doing good: The benevolent halo of corporate social responsibility. J. Consum. Res. 2015; 41: 1412–1425. Publisher Full Text\n\nde Los Salmones MDMG , Crespo AH, del Bosque IR : Influence of corporate social responsibility on loyalty and valuation of services. J. Bus. Ethics. 2005; 61: 369–385. Publisher Full Text\n\nDu S, Sen S: Challenging Competition with CSR: Going Beyond the Marketing Mix to Make a Difference. GfK Marketing Intelligence Review. 2016; 8: 18–23. Publisher Full Text\n\nGolob U, Podnar K, Jancic Z: The Importance of Values Motivation and Expectations for Consumers’ Responses to Corporate Social Responsibility.2015; p. 11.\n\nGupta V: Validating the theory of planned behavior in green purchasing behavior. SN Bus. Econ. 2021; 1. Publisher Full Text\n\nGürlek M, Düzgün E, Uygur SM: How does corporate social responsibility create customer loyalty? the role of corporate image. Soc. Responsib. J. 2017; 13: 409–427. Publisher Full Text\n\nHildebrand D, Demotta Y, Sen S, et al.: Consumer responses to corporate social responsibility (CSR) contribution type. J. Consum. Res. 2017; 44: 738–758. Publisher Full Text\n\nKaur P: The Effect Of CSR On Consumer’s Buying Behavior. Int. J. Innov. Res. Dev. 2013; 2: 317–323.\n\nLi J, Chen Y, Qing Q: Differentiated consumer responses to corporate social responsibility domains moderated by corporate social responsibility perceptions: A Kano model-based perspective. Corp. Soc. Responsib. Environ. Manag. 2021; 28: 1606–1619. Publisher Full Text\n\nLu T, Wei X, Li K: Consumer responses to corporate social responsibility programs. Nankai Bus. Rev. Int. 2015; 6: 364–380. Publisher Full Text\n\nMiller Z: The Enduring Use of the Theory of Planned Behavior. Hum. Dimens. Wildl. 2017; 22: 583–590. Publisher Full Text\n\nNorgaard K: “People Want to Protect Themselves a Little Bit”: Emotions, Denial, and Social Movement Nonparticipation. Sociol. Inq. 2006; 76: 372–396. Publisher Full Text\n\nPeloza J, Shang J: How can corporate social responsibility activities create value for stakeholders? A systematic review. J. Acad. Mark. Sci. 2011; 39: 117–135. Publisher Full Text\n\nRivera JJ, Bigne E, Curras-Perez R: Effects of Corporate Social Responsibility perception on consumer satisfaction with the brand\|Efectos de la responsabilidad social corporativa sobre la satisfacción del consumidor con la marca. Span. J. Mark. - ESIC. 2016; 20: 104–114. Publisher Full Text\n\nRomani S, Grappi S, Bagozzi RP: Explaining Consumer Reactions to Corporate Social Responsibility: The Role of Gratitude and Altruistic Values. J. Bus. Ethics. 2013; 114: 193–206. Publisher Full Text\n\nSchill M, Godefroit D: Consumer responses to environmental corporate social responsibility and luxury. J. Serv. Mark. ahead-of-print.2021. Publisher Full Text\n\nSemeijn J, Schenkel M, Ghijsen P, et al.: Consumer appreciation of forms of Corporate Social Responsibility Knowledge Management, Management Innovation and High Performance Organizations in an Emerging Market View project Two forthcoming articles on supply chain flexibility and one on supplier development View project Nord Van Kessel Canon Global Consumer appreciation of forms of Corporate Social Responsibility.2014. Publisher Full Text\n\nSen S, Bhattacharya C: Does Doing Good Always Lead to Doing Better? Consumer Reactions to Corporate Social Responsibility. J. Mark. Res. 2001; 38: 225–243. Publisher Full Text\n\nSlote M: Egoism and Emotion. Philosophia. 2013; 41: 313–335. Publisher Full Text\n\nTian Z, Wang R, Yang W: Consumer Responses to Corporate Social Responsibility (CSR) in China. J. Bus. Ethics. 2011; 101: 197–212. Publisher Full Text\n\nWan L, Poon P, Yu C: Consumer reactions to corporate social responsibility brands: the role of face concern. J. Consum. Mark. 2016; 33: 52–60.Ajzen.SchmidtFestschrift2012.pdf. Publisher Full Text" }	[ { "id": "141076", "date": "29 Jun 2022", "name": "Yuriy Yu Shvets", "expertise": [ "Reviewer Expertise self economy" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nDear authors, thank you so much for giving me the opportunity to read and review your work.\n1. This work aims to identify the prospects for using charitable lotteries as a marketing tool to involve consumers and employees in charitable activities. However, in the research methodology, the authors do not specify what interpretation of involvement they use in the study of participation in a charity lottery does not require significant efforts from the participants.\n2. The authors set themselves the task of determining whether the charity lottery creates additional value for consumers. What is the potential for creating additional value for consumers in charitable lotteries themselves?\n3. The authors' conclusions did not reflect consumers’ attitudes to charitable lotteries as a gambling game. This point needs to be elaborated.\n4. In the theoretical framework, the authors discuss the issue of consumer confidence in organizations that carry out activities within the framework of corporate social responsibility. It would be appropriate to explain how this problem is reflected in the observed variables.\n5. Is there a barrier to charity in the form of a lottery if consumers have doubts about the good faith of the lottery organizer? Need a bit more explanation on this.\n6. Factors of awareness of consumer behavior by what variables were measured? Need to elaborate.\n7. What additional factors, according to the authors, should be measured additionally to improve the quality of the forecast of consumer behavior about charitable lotteries?\n8. How do the authors plan to measure the effectiveness of the lottery as a method of raising funds? This point is important to be discussed in the manuscript.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "141077", "date": "29 Jun 2022", "name": "Muhammad Mohsin", "expertise": [ "Reviewer Expertise OK" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe title is interesting, and I can see merit in the paper, however I have few suggestions to improve the paper and some revisions should be made before indexing.\nThe introduction section is written well and composed very well. However, a good intro presentation should be precise. The introduction needs to be more structured in terms of current citation from reputed journals.\nAlthough the overall language of the manuscript is good and acceptable, a few grammatical and typo issues have been observed.\nThe authors partially define the amount of literature that has been carried out and where does gap persist in this area of filed. Additionally, the literature review is too short. I suggest using summary on which you reviewed the literature. Also, it would be nice to summarize the main gaps in the literature that your paper should fill, because it should be clear.\nBetter to add a summarizing paragraph at the end of the introduction showing the relationship between prospects for using charity lotteries in social marketing. Overall, this section contains enough explanation however the proposed model should be compared with some popular models to measure Prospects for using charity lotteries in social marketing.\nThe result and discussion sections have been presented in good structure. The result section should be compared with current and relevant citations. Again, the closing paragraph of the results can add to conclude the technical findings. Authors are suggested to improve the conclusion section since it is broadly handled and should be very concrete for describing the results followed by the policy. I would suggest a separate policy section after the conclusion. I hope my comments will help to improve the paper before publication, however, its policy implication section briefly deals with the suggestions and policy implications, which is an essential part of the description of the conclusion section.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-664
https://f1000research.com/articles/11-278/v1	04 Mar 22	{ "type": "Opinion Article", "title": "Making European performance and impact assessment frameworks glocal", "authors": [ "Ana M.P. Melo", "Sofia Oliveira", "Jorge S. Oliveira", "Corinne S. Martin", "Ricardo B. Leite", "Sofia Oliveira", "Jorge S. Oliveira", "Corinne S. Martin", "Ricardo B. Leite" ], "abstract": "Sustainability of research infrastructures (RIs) is a big challenge for funders, stakeholders and operators, and the development and adoption of adequate management tools is a major concern, namely tools for monitoring and evaluating their performance and impact. BioData.pt is the Portuguese Infrastructure of Biological and Portuguese node of the European Strategy Forum on Research Infrastructures \"Landmark\" ELIXIR. The foundations of this national research infrastructure were laid under the “Building BioData.pt” project, for four years. During this period, performance and impact indicators were collected and analysed under the light of international guidelines for assessing the performance and impact of European research infrastructures produced by the European Strategy Forum on Research Infrastructures, the Organisation for Economic Co-operation and Development and the EU-funded RI-PATHS project. The exercise shared herein showed that these frameworks can be adopted by national RIs, with the necessary adaptations, namely to reflect the national landscape and specificity of activities, and can be powerful tools in supporting the management of RIs. “Not everything that counts can be counted, and not everything that can be counted, counts”. Albert Einstein, Theoretical physicist and Nobel Prize winner", "keywords": [ "biological data", "FAIR", "research management", "open science", "performance and impact indicators", "research infrastructures", "socio-economic impact" ], "content": "Introduction\n\nThe long-term sustainability of Research Infrastructures (RIs) is of great importance to the European Strategic Forum on Research Infrastructures (ESFRI) and the European Union more broadly, as shown by calls for RIs to demonstrate their economic and wider benefit to society.1 For the Organisation for Economic Co-operation and Development (OECD), sustainability is also a major concern as RIs represent an increasingly large share of research investment by national governments.2 As a result, recent years have seen the emergence of a number of frameworks (ESFRI, OECD and that developed by the EU-funded RI-PATHS project) to guide RIs in their journeys to demonstrate performance and impact, going beyond simply scientific impact, and considering public value more generally.\n\nBioData.pt is the Portuguese Infrastructure of Biological Data and the Portuguese node of ELIXIR. In this study, the goal was to consider three frameworks for impact and performance evaluation (ESFRI, OECD and RI-PATHS) in relation to existing indicators maintained by the BioData.pt project, from now on referred to as “Building BioData.pt”, funded via the Portuguese state budget and European structural funds. From this, we expected to gain a more systematic, structured, and deeper understanding of the performance and impact of this national-level RI, and to use this new knowledge to inform its further development towards long-term sustainability. Beyond the qualitative assessment itself, this exercise aimed to document a process that may help national nodes of distributed European RIs to understand the impact of their activities, to inform stakeholders, policy makers and funders, as well as to improve their operations and increase their visibility, and overall prestige. In addition, it aimed to assess the relevance and adequacy of the indicators used by BioData.pt. It is expected that our findings, including lessons learned, will be useful to other similar public-funded RIs, which are often working with limited resources and do not have the means to fund repeated impact evaluations by specialized consultancies.\n\nAlthough BioData.pt is the Portuguese Infrastructure of Biological Data and the Portuguese Node of the ESFRI Landmark ELIXIR (a pan-European research infrastructure for life science data, Ref. 3), it relies on fixed-term project funds to operate. A historical note of BioData.pt and the Portuguese Node of ELIXIR is depicted in Figure 1.\n\nIn 2010, a Portuguese researcher from IGC (Instituto Gulbenkian de Ciência) at the European Bioinformatics Institute was challenged to participate in the onset of ELIXIR and create the Portuguese Node of this, yet to be, research infrastructure. In 2011, a first step was done, by creating the Portuguese bioinformatics woody plants platform followed by the creation of BioData.pt – Portuguese Biological Data Network, to operate the Portuguese Node of ELIXIR (ELIXIR PT), in 2013. In the same year, the ELIXIR, an intergovernmental organisation bringing together life science resources from across Europe, namely, databases, software tools, training materials, cloud storage and supercomputers, was founded. In 2014, the Foundation for Science and Technology, on behalf of the Portuguese Government, signed the ELIXIR Consortium Agreement, by which Portugal adhered to ELIXIR and, in 2016, a collaboration agreement between INESC-ID (Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento) and ELIXIR was signed, creating the Portuguese Node of this pan-European infrastructure. The merger between BioData.pt and ELIXIR PT was formalized in 2018 and, very recently, already in 2021, the BioData.pt Association was founded as the legal entity of this RI.\n\nSince 2017, the development and early operation of BioData.pt have been funded through a €2.7M project grant to last for four years, to lay the foundation of this RI. The “Building BioData.pt” project involved 11 beneficiaries and 81 participants, many of which providing in-kind expertise on computing, bioinformatics and data management to a range of end-users, as well as building and operating the infrastructure itself. Of the project budget, 33% was used to hire human resources and 57% to purchase equipment, mostly computing resources to assemble the nationally distributed computing infrastructure. The remainder was used in the adaptation of buildings to host the computing infrastructure or to deliver training. “Building BioData.pt” was structured as shown in Table 1.\n\n\nMethods\n\nBased on the simplified RI-PATHS approach, which classifies indicator types in activity (concrete activities to be carried out within the scope of the project, visible to the public and under full control of the organization), outcome (short-term direct results of each activity, not under direct control of the organization) and impact (transformative effects of the activity on its target audience and beyond, in the mid to long term),4 a “BioData.pt Monitoring and Evaluation Matrix” (B-MEM) (Figure 2, Ref. 5) and supporting guidelines were developed to facilitate the onset of evaluation processes, by the BioData.pt infrastructure. This simple and participatory approach allowed project managers to view and document, for the first time, the 10 working groups (or work packages) (Table 1) of “Building BioData.pt” in terms of activities, outcomes and impact, and align these with the overarching objectives of the project. In a second stage, the existing “Building BioData.pt” indicators, which had been maintained during the four years of grant execution, were categorized as activity, outcome and impact indicators, and assigned to the most relevant RI-PATHS impact area.\n\nThis matrix, internally developed during the BioData.pt project, was used to understand and document project working groups in terms of activities, outcomes and impact.\n\nEach existing “Building BioData.pt” indicator, which could be quantitative or qualitative by nature, was documented and cross-checked against those compiled by the RI-PATHS project, and the OECD and ESFRI frameworks.\n\nFinally, the “Building BioData.pt” indicators were assessed against several sets of strategic objectives relevant to research infrastructures and their work: those of BioData.pt (as an organization), those of the current ELIXIR Scientific Programme,6 those of the Portuguese National Roadmap of Research Infrastructures,7 those of EOSC8 and, finally, those of the United Nations Sustainable Development Goals.9 This was done to gain insights into the relevance of BioData.pt in these broader contexts.\n\nA visualization method was used to better document the relevance of the retrieved indicators, considering the national context, and the global environment of BioData.pt mission. A stacked column chart was generated entirely using the Rstudio software version 2021.09.0.351 and ggplot2 version 3.3.5,10 specifically using the ggplot() function, due to the complexity of the graphic. The fct_reorder() function of forcats version 0.5.1 was used to reorder indicators according to their relevance, in decreasing order.\n\n\nImplementation and impact analysis\n\nThe first step was the description of the “Building BioData.pt” project working groups, in terms of activities, outcomes and impact, and their alignment with its two overarching objectives, using the BioData.pt Impact Assessment Matrix (B-MEM) and the respective guidelines. Working groups (WG) 1 to 5 were dedicated to domain specific activities which, overall, aimed to build the BioData.pt Research Communities, and their expected outcomes were data curation, integration and availability for domain-specific areas with impact in enhancing the quality of scientific research by promoting the FAIR principles. The global activity of WGs 6, 7, 9 and 10 was to set up the Support to Research Communities, having three outcome/impact lines: 1) a fully available computational infrastructure for data analysis/better and more extensive computing resources; 2) promotion of capacity-building in bioinformatics and research data management in the national research community/improved research efficiency & effectiveness and human capital; and 3) overall management of RI and operation of the Portuguese Node of ELIXIR/strengthened RI long-term sustainability. Both “Research Communities” and “Support to Research Communities” were developed under the objective “Strengthening research, technological development and innovation”. The second objective “Enhancing research knowledge transfer from academy to industry” was served by the activity Industry & Entrepreneurship, developed by WG8, delivering promotion of knowledge transfer to industry to bring an added value to companies’ data and an industrial ecosystem of companies aware/beneficiary of bioinformatics and research data management as outcome and impact, respectively.\n\nYet with the help of the B-MEM, the “Building BioData.pt” project and Infrastructure reports were mined for indicators that would relate to those compiled by the ESFRI, OECD and RI-PATHS frameworks. Table 2 shows one example of this implementation, performed for the activity “Research Communities”, in relation to RI-PATHS. In detail, for this activity, we were able to find indicators of two types, activity and outcome, distinctly distributed by three of four impact areas, Human Resources, Economic and Innovation and Societal/Social. For each type of indicator identified, the indicator itself, the evidence for confirmation and method for description is listed. For instance, under the objective “Strengthening research, technological development and innovation”, in the activity “Research Communities”, the activity indicator Number of publications is identified by direct evidence (e.g., from Web of Science) and the method for collecting evidence is counting the number of publications. The full dataset of BioData.pt project indicators classified following the RI-PATHS approach can be accessed.11\n\nB-MEM follows the RI-PATHS approach, thus segmenting indicator types in Activity, Outcome or Impact, and requiring further description of the Evidence and Method used for indicator collection. WG (Working Group) 1 – Plants, WG2 – Marine Resources, WG3 – Systems biology, WG4 – Neurosciences, WG5 – Yeastract.\n\nThis exercise was repeated using the impact assessment frameworks of ESFRI and OECD. These approaches cover more explicitly the so-called scientific impact, of which some indicators, like Number of publications and Number of Citations, are also covered in the Human Resources area of the RI-PATHS approach.\n\nA summary of RI-PATHS’ indicator types produced by “Building BioData.pt” (Table 3) shows that the different activities of the project, “Research Communities”, “Support to Research Communities” and “Industry and Entrepreneurship”, encompassing its 10 working groups had impact in all four RI-PATHS areas, namely, Human Resources, Economic and Innovation, Social/Societal and Policy, the working groups that provide “Support to Research Communities” having the broader socio-economic impact.\n\nA- activity; O- outcome; I- impact; Tick – indicator or proxy found; n/a – not applicable. WG (Working Group) 1 – Plants, WG2 – Marine Resources, WG3 – Systems biology, WG4 – Neurosciences, WG5 – Yeastract, WG6 – Common Infrastructure, WG7 – Training, WG8 – Industry & Entrepreneurship, WG9 – Bioinformatics Support and WG10 – Project Management & Dissemination.\n\nThe indicators of “Building BioData.pt” identified in the ESFRI list corroborated the previous finding that the activities with broader impact were those dedicated to the “Support of Research Communities” (Table 4). The detailed information for this exercise is available for consultation.11 In addition, “Building BioData.pt” generated indicators for all ESFRI’s areas and covered all indicators except number 14 (number of publicly available data sets used externally).\n\nTick – indicator or proxy found; n/a – not applicable. WG (Working Group) 1 – Plants, WG2 – Marine Resources, WG3 – Systems biology, WG4 – Neurosciences, WG5 – Yeastract, WG6 – Common Infrastructure, WG7 – Training, WG8 – Industry & Entrepreneurship, WG9 – Bioinformatics Support and WG10 – Project Management & Dissemination.\n\nThe analysis of “Building BioData.pt” indicators using the OECD framework (Table 5) also corroborated the broad impact of the project, by retrieving indicators for all impact areas. In this case, the scientific impact produced by the activities of “Research Communities” assumes particular relevance. Nonetheless, as for the previous frameworks, the activities related to “Support to Research Communities” have a wider impact. The full dataset of this analysis can be consulted.11\n\nTick - indicator or proxy found; n/a - not applicable. WG (Working Group) 1 - Plants, WG2 - Marine Resources, WG3 - Systems biology, WG4 - Neurosciences, WG5 - Yeastract, WG6 - Common Infrastructure, WG7 - Training, WG8 - Industry & Entrepreneurship, WG9 - Bioinformatics Support and WG10 - Project Management & Dissemination.\n\nThe indicators generated by “Industry and Entrepreneurship” activities could find matches or proxies in the lists of the three impact assessment approaches, with greater emphasis, as expected, in the Economic and Innovation impact areas, enriching the project with a translational dimension.\n\nOverall, this analysis showed that the activities carried out to accomplish the “Building BioData.pt” overarching objectives of “Strengthening research, technological development and innovation” and “Enhancing research knowledge transfer from academy to industry” covered the broad range of impact areas foreseen for European Research Infrastructures. This not only puts this RI of the National Roadmap aligned with sibling international counterparts, but also suggests that BioData.pt is well aligned with ELIXIR, bringing to the national scientific system the state-of-the-art topics of computing, bioinformatics and data management, addressed by this ESFRI Landmark.\n\nFinally, the relevance of the retrieved indicators was ascertained, considering the national context and the global environment of the BioData.pt mission. Arbitrary units (A.U.) were attributed to the alignment of each indicator with the objectives/goals of the BioData.pt (4.5 A.U.), ELIXIR (2 A.U.), National Roadmap of Research Infrastructures (2 A.U.), EOSC (1 A.U.) and the Sustainable Development Goals - SDG (0.5 A.U.). A cutoff was established at 6.5 A.U., a score that could only be reached if an indicator matched BioData.pt goals and, at least, those of ELIXIR or the National Roadmap of Research Infrastructures, to which BioData.pt is bound by a formal relationship. Alignment with EOSC and SDG was sought to assess the chosen indicators in agreement with the main European trends in open science and the goals for global development, respectively (Figure 3). The full dataset of this analysis can be consulted.12\n\nArbitrary units (AU). Dashed line - cutoff point.\n\n\nDiscussion\n\nOf the 102 indicators compiled as potentially relevant to RIs by the RI-PATHS project, 25 indicators were monitored during “Building BioData.pt”, scattered in all impact areas, suggesting the broad socio-economic impact of BioData.pt. RI-PATHS also proposes a set of pathways that should be taken into consideration when assessing the socio-economic impact of specific project activities. For instance, pathways 5 - Learning and training by using RI facilities and services, 9 - Provision of specifically curated/edited data, and 11 - Creating and shaping scientific networks and communities could be applied in the monitoring the impact of BioData.pt training activities (e.g., “Ready for BioData Management?”), the CorkOak DB portal13 and the consolidation of our Communities and Platforms, in a multidisciplinary network to identify gaps in computing data management and bioinformatics for the life sciences and build solutions. In these cases, around 50% alignment with the primary indicators of each referred pathway was observed, while only 25% alignment was detected when all BioData.pt project indicators were compared with the overall indicators list. These findings emphasize the need to adjust global performance and impact indicators to the particular context of a national project (e.g., with a wide scope that covered simultaneously Enabling Science, Problem-Solving, and Science and Society, in the case of the establishment of a national RI) or to a particular activity with a narrower scope (e.g., a training program, a community, a data portal).\n\nOf the 21 indicators compiled by the ESFRI framework, 20 were monitored by “Building BioData.pt”. The missing indicator, Number of publicly available data sets used externally, relates to the optimisation of data use and is a relevant indicator for a RI like BioData.pt. Although BioData.pt has publicly available datasets (e.g., Pheno and CorkOakDB13), it does not currently maintain indicators to demonstrate how these are being used externally. This difficulty also intricates with the fact that there is still a long way to go in the formal acknowledgement of RI services by its users, which is harder when the goods provided are intangible and sometimes provided by third parties. In the future, this topic should be addressed by putting in place a tracking system.\n\nFinally, out of the 58 indicators compiled by the OECD framework, 32 were monitored by “Building BioData.pt”, 18 belonging to Scientific Impact and Training and Education, emphasizing the importance of these areas into BioData.pt.\n\nThe three frameworks considered in this study were comprehensive enough to accommodate all indicators maintained during “Building BioData.pt”, in spite of the fact that these were tailored according, for instance, to its specific national context, mission and role as a national node of a European RI.14 In addition, considering absent indicators may also prove useful to bring our attention to untracked activities that are relevant to the mission of a RI.\n\nThe vast majority of the ESFRI, OECD and RI-PATHS indicators identified in Building BioData.pt surpassed the 6.5 A.U. in our scoring exercise, indicating that, this project was well aligned with current thinking around the performance and impact of RIs. This also reflects the natural integration of BioData.pt in the European and Portuguese research landscape. Furthermore, alignment with the EOSC goals was also very frequently observed underlining the commitment of BioData.pt with the best practices of FAIR data management and open science. It was interesting to observe the overlap between BioData.pt and SDG objectives, suggesting that national RIs, as likely their European counterparts, can give a valuable contribution to global sustainable development, and are thus a public good. Below the cutoff, three indicators contributing to the strategic objectives of the BioData.pt infrastructure were identified that did not align with the priorities of ELIXIR or the National RoadMap of Research Infrastructures. These were the number of employees and the income from commercial activities and the number of entities paying for service. Although these indicators are not directly related to the mission of BioData.pt, they may assume a very relevant role for its long-term sustainability and thus, perhaps both the National Roadmap for Research Infrastructures and ELIXIR would like to consider this information when revising their priorities.\n\n\nFinal remarks\n\nThe monitoring of RIs performance and impact through indicators can be powerful in strategic management not only for continuous monitoring but also to inform future steps at the level of funders, optimization of processes and visibility by users and citizens.15,16 Although highly qualified consultants are available to provide such service, national RIs are typically underfunded, and thus cannot support the cost. It is thus critical to establish simple and participatory methods to be implemented by the RI staff with oversight from the management team.\n\nFrom this study, it is clear that the approaches developed by ESFRI, OECD and RI-PATHS are very useful and adaptable to the national context. It is also clear that special attention should be given to the national and thematic context of the activities under assessment.\n\nOverall, there is a strong alignment of “Building BioData.pt” with the mission of a research infrastructure as foreseen by ESFRI. The major flaw recognised under this study, respecting the difficulty to control external use and acknowledgement of RI assets, such us datasets, may need a collective solution to be addressed in the future.\n\nThis exercise was done backwards to provide lessons for the future, where ex ante the areas where impact aims to be achieved, the different types indicators for each activity to be collected, as well as the methods for capturing should be documented.\n\nIn this scope, the methodology used to assess the relevance of the indicators maintained during “Building BioData.pt” (Figure 3) can be useful to adapt the selection of indicators to a specific context, taking into account the mission and goals of the RI, and also those of national and international organizations and global initiatives composing the landscape where the RI develops its work and aims to have impact. To successfully assess performance and impact of RIs it is also very important to set up processes where the staff should be involved already from the planning stage, such as the BioData.pt monitoring and evaluation matrix (Figure 2).\n\n\nData availability\n\nZenodo: Mapping Building BioData.pt Indicators against the performance and impact assessment frameworks for research infrastructures of OECD, ESFRI and RI-PATHS project, https://doi.org/10.5281/zenodo.5828310.11\n\nZenodo: Relevance of “Building BioData.pt” indicators identified in ESFRI (E), OECD (O) and RI-PATHS (R) impact assessment frameworks, https://doi.org/10.5281/zenodo.5828295.12\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nEuropean Strategy Forum on Research Infrastructures Long-Term Sustainability Working Group: Long-Term Sustainability of Research Infrastructures. Dipartimento di Fisica - Università degli Studi di Milano; October 2017. 978-88-901562-8-1. Reference Source\n\nDirectorate for Science, Technology and Innovation, Committee for Scientific and Technological Policy: Strengthening the Effectiveness and Sustainability of International Research Infrastructures. Organisation for Economic Co-operation and Development.2017. Reference Source\n\nHarrow J, Drysdale R, Smith A, et al.: ELIXIR: providing a sustainable infrastructure for life science data at European scale. Bioinformatics. 2021; 37(16): 2506–2511. PubMed Abstract \| Publisher Full Text\n\nHelman A, Barberis M, Vignetti S, et al.: Deliverable 5.1. Socio-Economic Impact Assessment Framework. Research Infrastructure imPact Assessment paTHwayS (RI-PATHS). European Union’s Coordination and Support Action project (contract 777563).2020; 70 pp. Reference Source\n\nVal SB, Faria D, Contreiras SM, et al.: Impact Assessment of Node Activities Canvas ELIXIR Portugal. Figshare.2020. Publisher Full Text\n\nHeads of Nodes, Platform and Community Leaders, Technical and Training Coordinators and members of the various Working Groups: ELIXIR 2019–23 Scientific Programme.2018. Reference Source\n\nFundação para a Ciência e a Tecnologia: Portuguese Roadmap of the Research Infrastructures.2020. 978-972-667-357-6. Reference Source\n\nEuropean Commission, Directorate-General for Research and Innovation: European Open Science Cloud (EOSC) strategic implementation plan. Publications Office; 2019. Publisher Full Text\n\nUnited Nations: Transforming Our World: The 2030 Agenda for Sustainable Development.Reference Source\n\nWickham H: ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag; 2016. 978-3-319-24277-4.\n\nMelo AMP, Oliveira S, Oliveira J, et al.: Mapping Building BioData.pt Indicators against the performance and impact assessment frameworks for research infrastructures of OECD, ESFRI and RI-PATHS project.2022. Publisher Full Text\n\nMelo AMP, Oliveira S, Oliveira J, et al.: Relevance of “Building BioData.pt” indicators identified in ESFRI (E), OECD (O) and RI-PATHS (R) impact assessment frameworks.2022. Publisher Full Text\n\nArias-Baldrich C, Silva MC, et al.: CorkOakDB - The Cork Oak Genome Database Portal. Database. 2020; 2020. PubMed Abstract \| Publisher Full Text\n\nReid A, Griniece E, Angelis J: Evaluating and Monitoring the Socio-Economic Impact of Investment in Research Infrastructures.2015. Publisher Full Text\n\nTurpen PB, Hockberger PE, Meyn SM, et al.; Metrics for Success: Strategies for Enabling Core Facility Performance and Assessing Outcomes. J. Biomol. Tech. 2016; 27(1): 25–39. PubMed Abstract \| Publisher Full Text\n\nMartin C, Repo S, Márquez J, et al.: Demonstrating public value to funders and other stakeholders—the journey of ELIXIR, a virtual and distributed research infrastructure for life science data. Ann. Public Cooperative Econ. 2021; 92: 497–510. Publisher Full Text" }	[ { "id": "126306", "date": "29 Mar 2022", "name": "Eugénio Campos Ferreira", "expertise": [ "Reviewer Expertise Systems Biology", "Bioinformatics", "Research management and assessment" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAn interesting opinion article on the performance and impact of the Biodata.pt, the Portuguese node of the ESFRI landmark ELIXIR, the European Research Infrastructure for life science. A significant coverage of indicators was compiled based on 3 frameworks: 20 out of 21 ESFRI indicators, 32 out of 58 OECD, ESFRI, OECD, RI-PATHS projects, 25 out of 102 RI-PATHS project indicators.\nThe main strengths of the article are related to the use of wide-spectrum frameworks created for the analysis of pan-European and global research infrastructures to a national (Portuguese) research Infrastructure, with ad hoc adaptations to reflect the national landscape and specificity of activities. The article also underlines the possibility of conducting a backward exercise able to prospect recommendations for the future, determine areas where impact aims are to be achieved, the indicators for each activity to be collected, as well as the methods for capturing should be documented.\nA few remarks:\nThe title “Making European performance and impact assessment frameworks glocal” does not allow inferring the content of the typescript. Although the article is inserted in the ELIXIR gateway, I suggest that reference be made to the performance and impact of BioData.pt according to the addressed frameworks (ESFRI, OECD, RI-PATHS project).\n\nOne last note: the quote “Not everything that counts can be counted, and not everything that can be counted, counts”, is frequently incorrectly attributed to Albert Einstein. Probably comes from a paper published in 1963 by the sociologist, William Bruce Cameron (Cullis 20171).\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nAre arguments sufficiently supported by evidence from the published literature? Yes\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Yes", "responses": [ { "c_id": "8577", "date": "02 Aug 2022", "name": "Ana Melo", "role": "Author Response", "response": "Dear Dr Ferreira, Thank you for reading our article and making suggestions that contributed to its improvement. The measures taken to address your concerns are described below your points: The title “Making European performance and impact assessment frameworks glocal” does not allow inferring the content of the typescript. Although the article is inserted in the ELIXIR gateway, I suggest that reference be made to the performance and impact of BioData.pt according to the addressed frameworks (ESFRI, OECD, RI-PATHS project). The authors have modified the title of the article. One last note: the quote “Not everything that counts can be counted, and not everything that can be counted, counts”, is frequently incorrectly attributed to Albert Einstein. Probably comes from a paper published in 1963 by the sociologist, William Bruce Cameron (Cullis 20171). The authors have confirmed and modified the attribution of this quote. Yours sincerely, Ana Portugal Melo" } ] }, { "id": "126307", "date": "06 Apr 2022", "name": "Enrico Guarini", "expertise": [ "Reviewer Expertise Financial management and governance in government and not-for-profit settings", "Performance Management", "Management of Research Infrastructures" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper examines how the international frameworks developed for the monitoring and evaluation of performance and impact of research infrastructures (RIs) can be adopted by national RIs to support its management. This is done by presenting the results of a four-year project of collecting and analyzing performance indicators carried out during the development of the Portuguese Infrastructure of Biological Data (BioData.pt) as the national node of an international RI (ELIXIR). The authors focus on three performance measurement frameworks developed for RIs (ESFRI, OECD, and RI-PATHS) and empirically assess how the combination of suggested performance indicators can be applied at the operational level to assess the impact of the organization. Within this perspective, the authors aim to contribute to developing useful tools for RI management.\nThe article is clear and well written, however, it needs improvement. Our main point is that the authors could better discuss the management implications of their findings. Below we present our main points and suggestions:\n\nFirstly, the authors focus from the beginning on the process of development of the national node - the ‘Building BioData.pt’ project - paying scarce attention in the Discussion section to the operational phase, for example, which indicators can also be relevant for the permanent organization/node itself rather than for the project phases. We would encourage the authors to clarify this from the beginning since the abstract seems to propose general implications for RI management. We would like to see some reflections at a general level (maybe also in the conclusions).\n\nOne major point that needs further specification is, first of all, the adaptability of the three frameworks at the national node level. The authors present a list of 77 retrieved indicators out of 181 from the three frameworks. It is still not clear why some indicators were more relevant than others, and why many of the proposed indicators were excluded. The authors need to better clarify if this was related to the need to adjust the impact indicators to the context of the project, to the construction stage of the RI, to the national goals/strategy, or to data availability. Thus, the authors need to discuss in more detail how the case studied and the findings might affect the generalisability of the results. In other words, the issue of adaptation from ‘global’ to ‘local’ needs to be better addressed (in the discussion/conclusion).\n\nAnother point that requires further specification is not only the relation between the indicators and the national context/strategy but also the managerial implications of collecting and using these indicators. Apart from the issue of collecting data from third parties, we think that the process of staff engagement in the measurement process should be discussed further. For example, the authors could consider the opportunity to provide more insights into how the participatory approach was conducted and received by the staff. The engagement of team members in performance measurement could be an important aspect to be emphasised as a management implication.\n\nIn the ‘Methods section,’ the authors report the results of scoring of indicators to assess their alignment with national and international goals. No information is provided about the method and reliability of the scoring process. Moreover, it is not clarified what is meant here with the concept of ‘alignment’.\n\nSince the article focuses on RIs, we would encourage the authors to include it in the title.\n\nMinor comments:\n\nTable 1. To improve readability, we would suggest adding a label ‘Activity’ to refer to “Research Communities”, “Support to Research Communities”, and “Industry engagement”, and a label ‘Objectives’ to refer to “Strengthening research, technological development and innovation\" (WGs 1, 2, 3, 4, 5, 6, 7, 9, 10), and to “Enhancing research knowledge transfer from academy to industry” (WG8).\n\nTable 1. WG9 is missing.\n\nTable 1. The activity “Industry Engagement” is mentioned as “Industry and Entrepreneurship” in the ‘Implementation and impact analysis’ section.\n\nMethods. Clarify the years during which the measurement process was conducted.\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nAre arguments sufficiently supported by evidence from the published literature? Yes\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Partly", "responses": [ { "c_id": "8578", "date": "02 Aug 2022", "name": "Ana Melo", "role": "Author Response", "response": "Dear Drs Lavitrano and Guarini, The authors have read thoroughly read your appreciation of this article and proceeded to the necessary modifications. We are very grateful for your analysis and think that it helped us to improve the quality of the article. In detail: Firstly, the authors focus from the beginning on the process of development of the national node - the ‘Building BioData.pt’ project - paying scarce attention in the Discussion section to the operational phase, for example, which indicators can also be relevant for the permanent organization/node itself rather than for the project phases. We would encourage the authors to clarify this from the beginning since the abstract seems to propose general implications for RI management. We would like to see some reflections at a general level (maybe also in the conclusions). A paragraph was added to the discussion to suggest a set of indicators that can be relevant for the operational stage of BioData.pt, as a mature infrastructure. One major point that needs further specification is, first of all, the adaptability of the three frameworks at the national node level. The authors present a list of 77 retrieved indicators out of 181 from the three frameworks. It is still not clear why some indicators were more relevant than others, and why many of the proposed indicators were excluded. The authors need to better clarify if this was related to the need to adjust the impact indicators to the context of the project, to the construction stage of the RI, to the national goals/strategy, or to data availability. Thus, the authors need to discuss in more detail how the case studied and the findings might affect the generalisability of the results. In other words, the issue of adaptation from ‘global’ to ‘local’ needs to be better addressed (in the discussion/conclusion). The discussion was reformulated to address and clarify the adaptability of the frameworks to the national node level, and the criteria to discriminate and attribute relevance to the indicators. Overall, the discussion section is now more detailed and emphasises the issue of adaptation from ‘global’ to ‘local’ needs. Another point that requires further specification is not only the relation between the indicators and the national context/strategy but also the managerial implications of collecting and using these indicators. Apart from the issue of collecting data from third parties, we think that the process of staff engagement in the measurement process should be discussed further. For example, the authors could consider the opportunity to provide more insights into how the participatory approach was conducted and received by the staff. The engagement of team members in performance measurement could be an important aspect to be emphasised as a management implication. The managerial implications of using the selected indicators are described, and the process of staff engagement is documented including recommendations for future assessments. In the ‘Methods section,’ the authors report the results of scoring of indicators to assess their alignment with national and international goals. No information is provided about the method and reliability of the scoring process. Moreover, it is not clarified what is meant here with the concept of ‘alignment’. The methods section was modified to clarify the concept of \"alignment\" and further information about the method and scoring process was included. Since the article focuses on RIs, we would encourage the authors to include it in the title. The title was modified accordingly. Minor comments: Table 1. To improve readability, we would suggest adding a label ‘Activity’ to refer to “Research Communities”, “Support to Research Communities”, and “Industry engagement”, and a label ‘Objectives’ to refer to “Strengthening research, technological development and innovation\" (WGs 1, 2, 3, 4, 5, 6, 7, 9, 10), and to “Enhancing research knowledge transfer from academy to industry” (WG8). The table was modified accordingly. Table 1. WG9 is missing. The table was modified accordingly. Table 1. The activity “Industry Engagement” is mentioned as “Industry and Entrepreneurship” in the ‘Implementation and impact analysis’ section. The table was modified accordingly. Methods. Clarify the years during which the measurement process was conducted. This information was added to the methods. We expect that now you will find the article acceptable for publication. Yours sincerely, Ana Portugal Melo" } ] } ]	1	https://f1000research.com/articles/11-278
https://f1000research.com/articles/10-952/v1	21 Sep 21	{ "type": "Study Protocol", "title": "The Wessex Fit-4-Cancer Surgery Trial (WesFit): a protocol for a factorial-design, pragmatic randomised-controlled trial investigating the effects of a multi-modal prehabilitation programme in patients undergoing elective major intra–cavity cancer surgery", "authors": [ "Malcolm West", "Andrew Bates", "Chloe Grimmett", "Cait Allen", "Richard Green", "Lesley Hawkins", "Helen Moyses", "Samantha Leggett", "Denny Z H Levett", "Sally Rickard", "Judit Varkonyi-Sepp", "Fran Williams", "Stephen Wootton", "Matthew Hayes", "Micheal P W Grocott", "Sandy Jack", "Malcolm West", "Andrew Bates", "Cait Allen", "Richard Green", "Lesley Hawkins", "Helen Moyses", "Samantha Leggett", "Denny Z H Levett", "Sally Rickard", "Judit Varkonyi-Sepp", "Fran Williams", "Stephen Wootton", "Matthew Hayes", "Micheal P W Grocott", "Sandy Jack" ], "abstract": "Background: Surgical resection remains the primary curative treatment for intra-cavity cancer. Low physical fitness and psychological factors such as depression are predictive of post–operative morbidity, mortality and length of hospital stay. Prolonged post-operative morbidity is associated with persistently elevated risk of premature death. We aim to investigate whether a structured, responsive exercise training programme, a psychological support programme or combined exercise and psychological support, delivered between treatment decision and major intra-cavity surgery for cancer, can reduce length of hospital stay, compared with standard care. Methods: WesFit is a pragmatic, 2x2 factorial-design, multi-centre, randomised-controlled trial, with planned recruitment of N=1560. Participants will be randomised to one of four groups. Group 1 (control) will receive usual pre-operative care, Group 2 (exercise) patients will undergo 2/3 aerobic, high-intensity interval training sessions per week supervised by personal trainers. Group 3 (psychological support) patients are offered 1 session per week at a local cancer support centre. Group 4 will receive both exercise and psychological support. All patients undergo baseline and pre-operative cardiopulmonary exercise testing, complete self-report questionnaires and will be followed up at 30 days, 12 weeks and 12 months post-operatively. Primary outcome is post-operative length-of-stay. Secondary outcomes include disability-adjusted survival at 1-year postoperatively, post-operative morbidity, and health-related quality of life. Exploratory investigations include objectively measured changes in physical fitness assessed by cardiopulmonary exercise test, disease-free and overall mortality at 1-year postoperatively, longer-term physical activity behaviour change, pre-operative radiological tumour regression, pathological tumour regression, pre and post-operative body composition analysis, health economics analysis and nutritional characterisation and its relationship to post-operative outcome. Conclusions: The WesFit trial will be the first randomised controlled study investigating whether an exercise training programme +/- psychological intervention results in improvements in clinical and patient reported outcomes in patients undergoing major inter-cavity resection of cancer. ClinicalTrials.gov registration: NCT03509428 (26/04/2018)", "keywords": [ "Surgery", "Prehabilitation", "Cardiopulmonary Exercise Test", "Exercise", "Physical activity", "Psychological", "Wellbeing", "Neoadjuvant", "Chemotherapy", "Chemoradiotherapy", "Outcome" ], "content": "Introduction\n\nThe number of new cancer cases per year is expected to rise to 23.6 million by 2030. Depending on the cancer cohort, major curative cancer surgery is associated with post-operative morbidity in up to 50% of gastrointestinal cancer patients and up to 60% in pancreatic cancer patients especially after neoadjuvant cancer treatments.1–3 Improved surgical, oncological and anaesthetic techniques, enhanced recovery pathways and perioperative care have delivered consistent improvements in length of hospital stay, in-hospital morbidity and readmission rates after major surgery. However, over half of patients over the age of 60 years after major abdominal surgery live with reduced functional capacity, physical fitness and quality of life (QoL), with a significant proportion never regaining pre-operative fitness or independent living.4,5 Our group and others have described the association between reduced pre-operative physical fitness6–11 (and its decline with neoadjuvant cancer treatments) and poor post-operative outcomes in upper and lower gastrointestinal cancer patients. Furthermore, we have reported on the associations between reduced physical fitness and reduced mitochondrial function,12 QoL13,14 and physical activity15 after cancer treatments before surgery.\n\nCancer prehabilitation is a novel process that occurs between the time of cancer diagnosis and continues throughout the cancer treatment pathway. The time before cancer diagnosis and surgery is an emotionally salient time where patients are receptive to changes in behaviour regarding their nutrition, fitness and psychological coping. Physical fitness, nutritional and psychological multimodal prehabilitation are targeted, tailored interventions with the aim to prevent, minimise and/or rescue the severity of anticipated treatment-related impairments that may cause significant disability when recovering from major cancer surgery.16 Given the multi-system impact of cancer and its treatment(s), prehabilitation interventions have adopted a ‘multimodal approach’, that may be defined as the incorporation of two or more intervention components specifically selected for their potential cumulative or synergistic effects on health outcomes. Reviews of prehabilitation in surgical oncology identify many limitations in the current evidence, yet acknowledge encouraging findings including improved fitness, endurance time, length of hospital stay, surgical complication rates, and health-related QoL with prehabilitation interventions.17–26 Recently, multinational consensus statements jointly from Macmillan Cancer Support, the Royal College of Anaesthetists and the National Institute for Health Research in the United Kingdom,27 Exercise and Sports Science Australia28,29 and the Academy of Medical Royal Colleges in the United Kingdom30 aim to advance the care provision, inform a change in policy, inform service provision, and implement a practice to benefit people living with cancer. Specifically, effective prehabilitation using multimodal physical activity, exercise, nutrition and psychological support, underpinned by behaviour change support, to improve cancer outcomes is advocated. Thus far the evidence is mostly based on uni-modal interventions, for example exercise interventions to improve physical fitness and post-operative complications20,22,31–34 and respiratory interventions to improve pulmonary specific morbidity,26 however literature utilising multimodal interventions (mostly exercise and nutrition) to improve outcomes is now emerging.18,19,35,36\n\nTo date exercise prehabilitation trials have focused on in-hospital training with little consideration for sustainable models of delivery. There has also been a lack of inclusion of behavioural science to facilitate engagement and longer-term behaviour change post-surgery. Furthermore, increasingly, evidence suggests that psychological factors impact physiological and psychological outcomes in both the short and long term, with implications for recovery from surgery, QoL and re-attainment of independent living.37 A systematic review of psychological prehabilitation before cancer surgery suggests such interventions can positively impact QoL and psychological outcomes (such as distress and anxiety). However prehabilitation studies including a psychological component have tended to be small, therefore, an evaluation of a psychological intervention together with an exercise intervention as part of a multimodal prehabilitation programme in cancer patients is urgently needed.23\n\n\nProtocol\n\nThe Wessex Fit-4 Cancer Surgery trial (WesFit) is a multi-centre, 2 × 2 factorial design, randomised-controlled, single blind, phase III clinical trial designed to compare the effect of structured prehabilitation programmes, against standard pre-operative care on patient outcome following major intra-cavity surgery for cancer (Figure 1). Participant recruitment, assessment and intervention are organised by NHS Hospital trusts who oversee referral to our community partners in local gymnasiums (exercise and behaviour change intervention) and Cancer Support centres (psychological intervention). The trial was registered with clinicaltrials.gov (NCT03509428) on April 26th, 2018. This protocol follows the SPIRIT guidelines – see Reporting guidelines.56\n\nMDT: multidisciplinary team, CPET: cardiopulmonary exercise test, SREPT: structured responsive exercise training programme, WHODAS: World Health Organisation Disability Adjusted Survival.\n\nPrimary objective: investigate whether a multimodal exercise, and psychological support prehabilitation programme, performed in a community-based setting prior to major cancer surgery, (± neoadjuvant cancer treatments) will result in a clinically significant difference (1-day reduction) in post-operative in-hospital length of stay) when compared to a control group.\n\nSecondary objectives: investigate whether the WesFit programme performed prior to major cancer surgery ± neoadjuvant cancer treatments:\n\ni. Improves disability free survival as measured by World Health Organisation (WHO) Disability Adjusted Survival v2.0\n\nii. Improves post-operative morbidity38 as measured by post-operative morbidity score (POMS) and Clavien-Dindo-Demartines (CD)39/comprehensive complication index (CCI) scores40\n\niii. Improves health related QoL as measured by EQ-5D-5L41 and EORTC-QLQ-C30.42\n\nExploratory objectives include:\n\ni. Improve overall survival and disease-free at one-year post-surgery\n\nii. Improve selected cardiopulmonary exercise test (CEPT) physiological variables\n\niii. Improve long-term physical activity behaviour\n\niv. Demonstrate cost effectiveness determined by health economics analysis\n\nv. Improve radiological markers of body composition\n\nvi. Improve radiological tumour regression grade (TRG)\n\nvii. Improve pathological tumour regression grade (yTRG)\n\nviii. Improve psychological outcomes including confidence to self-manage illness, anxiety and depression.\n\nix. Improve body composition measured by computer tomography and bioelectrical impedance analyses\n\nx. Improve nutritional and micronutrient status measured by micronutrient blood analysis\n\nPatients will be eligible for WesFit if they are over 18 years old and are scheduled to have major, intra-cavity cancer surgery with a curative intent. These are defined as thoracic, colorectal (including anal and neuroendocrine tumours), oesophagogastric (including neuroendocrine tumours), urological (including prostate, bladder and renal tumours), head and neck (including nasopharyngeal, laryngeal, pharyngeal and oral) and hepatobiliary (including pancreatic, gall bladder and neuroendocrine tumours). Treatment includes surgery alone or surgery combined with cancer treatments (including but not limited to neoadjuvant chemotherapy, chemoradiotherapy or immunotherapies). All patients deemed by the multidisciplinary team (MDT) as potentially curable or undergoing neoadjuvant cancer treatments with curative intent prior to restaging and surgery will be included.\n\nExclusion criteria includes patients with a tumour that is considered surgically non-resectable, having absolute or relative contraindications to completing a CPET,43 patients unable to perform CPET due to other coexisting acute illness or conditions (e.g. lower limb dysfunction), patients declining surgery or planned neoadjuvant treatment, if their weight exceeds 160 kg and patients unable to give informed consent.\n\nConsecutive, potentially eligible patients will be identified at MDT meetings and approached with patient information sheets at surgical/oncological outpatient clinic appointments. If the patient chooses to participate in this trial, they will undergo a screening CPET. This constitutes part of standard clinical care in some NHS hospitals. Once reviewed by a senior clinician, final eligibility is confirmed, and written informed consent can be obtained for trial participation.\n\nPatients will be randomised 1:1:1:1 to one of four groups. The study design is a 2 x 2 factorial design. The randomisation will be performed using ALEATM from FormsVision, an online software not under the control of the study team. Patients will be randomised by ALEATM by minimisation to the multimodal interventions or the control arm and stratified according to tumour type, hospital site, gender, neoadjuvant cancer therapy and age. Group 1 is control (routine care), group 2 is exercise alone, group 3 is psychological support alone and group 4 is a multimodal exercise, and psychological support.\n\nWesFit began recruitment in April 2018 and at the time of publishing was paused due to coronavirus disease 2019 (COVID-19) lockdown restrictions.\n\nExercise intervention: The exercise-training programme is consistent with the FITT principle (frequency, intensity, time and type), as advised by a panel of international experts and patient representatives. The exercise intervention has been shown by our group to be safe, feasible and tolerable in locally advanced rectal cancer patients following neoadjuvant chemoradiotherapy.31,39 Patients will participate in a prescribed, supervised, aerobic high-intensity interval, structured, responsive, exercise training programme (SRETP) on an electronically-braked cycle ergometer (Ergoselect Cloud bike). Participants will undertake 3-sessions per week (2-sessions per week if undergoing neoadjuvant treatments), from recruitment to surgical resection. These will occur within community gymnasia, unless precluded by safety concerns due to clinical condition. High-risk patients can exercise within a hospital setting. The high-intensity interval training (HIIT) comprises of an initial 5 minutes of unloaded pedalling. This is followed by 3 minutes at moderate intensity and 2 minutes at severe intensity. Moderate intensity exercise refers to the patient’s power output at 80% of oxygen uptake (VO2) at the anaerobic threshold, (80%AT) derived at baseline CPET. Severe exercise intensity occurs at the patient’s power output, at 50% of the difference between the VO2 at AT and VO2 Peak (50%∆) also accounting for 2/3 of the ramp work rate. These 5-minute intervals will be repeated 6 times, followed by 5 minutes of unloaded pedalling. The entire session lasts for 40 minutes. If the patient is receiving neoadjuvant treatment the entire session lasts for 30 minutes, with the 5-minute intervals repeated 4 times rather than 6 times. The full exercise programme is reported according to the Template for Intervention Description and Replication (TIDiER) checklist for exercise. The checklist is available in Extended data.56\n\nAs part of the exercise intervention personal trainers delivering the supervised exercise intervention will receive training in behaviour change support in the form of Healthy Conversation Skills (HCS). HCS is a brief intervention, developed to equip health and social care practitioners with the skills to support improvements in diet and physical activity in their patients/clients.44 Informed by principles of motivational interviewing and social cognitive theory it is an empowering, client-centred, solution-focused approach to support behaviour change. Self-efficacy, a central construct of Bandura’s social cognitive theory,45 describes a person’s belief in their abilities to perform a given task. Self-efficacy is also considered to be a prerequisite to an individual experiencing a sense of control. Evidence suggests that self-efficacy is a mediator of exercise behaviour in clinical populations and a predictor of exercise adherence.46 See Table 1 for included behaviour change techniques as per the behaviour change technique taxonomy.47 Personal trainers work with participants throughout the intervention to increase motivation, self-efficacy and support planning for continued unsupervised exercise after surgery. Personal trainers have telephone consultations at three and six months after surgery to support long-term engagement in independent physical activity. The behaviour change intervention is reported according to the TIDiER checklist in Extended data.56\n\nPsychological support: Psychological support will be provided in the form of counselling. Counselling will be delivered by counsellors experienced in working with people affected by cancer. Counsellors are members of the British Association of Counselling and Psychotherapy with a minimum qualification of a Diploma in Counselling and Psychotherapy. The processes reflect the best practice currently delivered by cancer support centre staff. Participants will be offered weekly one-to-one consultations lasting up to 1 hour, allowing them to explore any issues/concerns they are experiencing, including (but not limited to) ways of coping with their reaction to cancer, family and relationship issues, anxiety and distress. After each session, counsellors will complete a checklist indicating counselling techniques used. The psychological support intervention is reported according to the TIDiER checklist in Extended data.56\n\nAdherence will be monitored throughout the trial. The trial team will receive automatic uploads of exercise adherence from the card- and cloud-based systems and attendance (or not) at counselling sessions will be logged.\n\nControl group: The control group will receive routine pre- and post-operative care with additional assessments common to all groups, but no intervention outside of routine care.\n\n\nOutcome measures\n\nBaseline assessment will occur as close as possible to the MDT treatment decision. All patients repeat assessments immediately prior to surgery. Patients undergoing neoadjuvant cancer treatment (e.g. chemoradiotherapy for locally advanced rectal cancer patients) will undergo repeat CPET every 4-weeks (depending on site availability), in order to assess continued eligibility and to moderate training intensities according to physiological adaptation. Post-operative assessment occurs during hospital admission, at 30 days post-surgery, at 6- and 12- weeks post-surgery and 12-months post-surgery. The schedule of observations and procedures can be found in the Extended data.56\n\n\nPrimary outcome\n\nLength of stay is defined as the number of days a patient stays in hospital following surgery. It is calculated by subtracting the date of surgery from the date of discharge. The date of surgery is defined as day 0 of a patient’s post-operative hospital stay.\n\n\nSecondary outcomes\n\n\n\ni. World Health Organisation Disability Adjusted Survival 2.0 (WHODAS 2.0) - The 36 item WHODAS 2.0 questionnaire will be completed at baseline, prior to surgery, day-30, week-12 and 12-months following date of surgery.\n\nii. Post-operative morbidity will be determined by the post-operative morbidity survey (POMS),48 the highest in-hospital morbidity achieved according to the Clavien-Dindo-Demartines (CD) score39 and the comprehensive complication index (CCI) score.40 Patients’ POMS will be characterised on day 3, 5, 7 and 15, while patient remains hospitalised. The POMS 18-item survey will be used to address nine domains of postoperative morbidity (pulmonary, infectious, renal, gastrointestinal, cardiovascular, neurological, wound complication, haematological and pain). On day of discharge, patient’s surgical complications (if any) will be graded using the CD classification of surgical complications This classification is used to assess overall hospital morbidity following surgical procedures. Patients are graded as 0 (no complications) or Grade I-V based on the level of complication, including the number of organ system involvement. Grade V is defined as death of a patient. A record of the CCI – an update of the CD classification will also be collected.\n\niii. Health related QoL will be assessed using the EQ-5D-5L40 and the EORTC-QLQ-C30.41 EQ-5D-5L is a standardised measure of health status which provides a simple, generic measure of health for clinical and economic appraisal. There are 5 domains (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) each with 5 levels of health. It also includes a visual analogue scale which asks the respondent to rate their health from 0 (worst imaginable) to 100 (best imaginable health). Cancer specific, health-related QoL will be measured using the EORTC-QLQ-C30. This EORTC-QLQ-C30 measures physical, role, emotional, social and cognitive functioning, as well as global QoL and three symptoms; fatigue, pain and nausea/vomiting. For all scales scores range from 0-100. For global and functional scales higher scores reflect favorable QoL, whereas higher symptom scales score indicate more symptoms.\n\n\nExploratory outcomes\n\n\n\ni. Overall and disease-free survival at 1-year post-surgery\n\nii. VO2 at AT (anaerobic threshold), VO2 at peak, and VE-VCO2 slope. Other CPET variables will be reported and analysed as per previous publications.8,12,32,38\n\niii. Radiological makers of body composition will be measured from routine abdominal computed tomography (CT) scans at L3.48,49\n\niv. Radiological tumour downsizing/sizing/regression will be assessed using CT, magnetic resonance imaging (MRI) and positron emission tomography (PET) scans for all patients including those who have received neoadjuvant treatments. Clinical radiological tumor, node and metastasis (TNM) and tumour specific regression scores (RECIST50) will be recorded after each clinical scan (baseline and re-staging).\n\nv. Body composition will be measured using bioelectrical impedance analysis at baseline, immediately before surgery and at 6- and 12-weeks after surgery using the supplied SECATM body composition analyser MBCA 515 weighing scale.\n\nvi. Patients will undertake assessments through the trial in order to characterise nutritional status and relate to post-operative outcome, response to the trial interventions and response to neoadjuvant cancer treatments.\n\nvii. Objective physical activity levels will be determined in a sub-sample of participants by ActiGraphTM GT9X link activity sensor, worn for 5 complete days, following baseline CPET, +/-during cancer therapies and at 12-weeks and 12-months following surgery.\n\nviii. Quality-adjusted life years (QALY) will be used as a measure of health outcome for economic evaluation, incorporating both the quantity and the quality of patients’ lives. The EQ-5D-5L will be used to evaluate QALYs to evaluate both the morbidity gains and the mortality impact of prehabilitation in cancer patients.51\n\nix. Anxiety and depression will be measured using the hospital anxiety and depression scale (HADS).52\n\nx. Self-efficacy (confidence) to self-manage chronic disease (SEMCD), will be measured using the Lorig SEMCD scale.53\n\nxi. Patient activation will be measured using the PAM (patient activation measure).54\n\n\nProcess evaluation\n\nQualitative in-depth semi-structured interviews will be conducted with patients enrolled in the trial and professionals involved in the delivery of the trial at two time points. Interviews of up to 1 hour will be conducted either face to face at a location convenient to the participant or by telephone depending on preference. A researcher with experience in qualitative interviewing and who is not part of intervention delivery will conduct the interviews. Firstly, patients from all arms of the study (N = 12) and key stakeholders; personal trainers, research nurses and counsellors (N = 5) will be interviewed regarding their experiences of the trial once the first 30 patients have reached 12 weeks post-surgery. The sample size is pragmatic based on the time and resource available early in the trial and will provide an opportunity for the research team to reflect on the experiences of patients and professionals involved in the trial, identifying barriers and facilitators to trial processes and implementation (professionals) and trial experiences (patients). If any amendments to the trial are deemed necessary, a substantial amendment will be submitted to the ethics committee and Health Research Authority (HRA) for approval.\n\nFollowing completion of the trial structured interviews will be conducted with 25 patients (with representation from all 4 study arms) to understand patient experience of the trial and subsequent behaviour change. The sample size is will allow for purposive sampling with sampling characteristics including a range of age, sex, disease type, and whether or not they received neoadjuvant treatments. Interviews will also be conducted with stakeholders involved in the delivery of the trial, to include personal trainers, counsellors, research nurses (including other research team members) and members of clinical care teams, commissioners and cancer centre staff (N = 15). These interviews will seek to understand the barriers and facilitators to the implementation of the trial into clinical practice and within the community setting. All interviews will be audio-recorded, transcribed verbatim managed through NVIVO software (v12) and analysed using thematic analysis with an inductive approach. Normalisation process theory will inform data collection and analysis.55\n\n\nEstimation of sample size\n\nFrom previous studies, the median length of stay in the control group is estimated to be 7 days. To detect a clinically meaningful difference of a (significance level to detect a hazard ratio of 1.17 when the control group median in-patient time is 7 days) 1 day reduction in LOS with 85% power, alpha = 0.05, a sample size of 1560 participants will need to be recruited over 3 years, with a one year follow-up period. The sample size allows for a 20% drop-out.\n\nSample size calculations for 2×2 designs are based on the two main comparisons (i.e. exercise vs. no exercise and psychological support vs. no support). The trial sample size is the larger of these 2 comparisons, so in this case, the sample size calculation is powered on the psychological support comparison. The sample size calculation assumes that there is no interaction between the interventions.\n\n\nStatistical analysis plan\n\nDescriptive statistics will be used to summarise the baseline demographic and clinical variables. For continuous variables, if the data are normally distributed, the mean and standard deviation will be calculated. If the data are not normally distributed, the median and interquartile range will be calculated. For categorical or binary variables, these will be summarised as frequency and percentage of total. There will be a variety of data consistency and quality checks performed at various stages of the data capture process, e.g. regular calibration and monitoring of measuring instruments, use of control standards in assays. All extreme values (mean +/- 3* standard deviation) and improbable values, as defined by clinical opinion will be investigated. In depth descriptions of these procedures exist in the trials data management plan, data management procedure and the data validation plan (code book) held by the sponsor. Outcomes assessors and statisticians will be blinded to trial arm until completion of analysis.\n\nWe will summarise, by group, any patients who were randomised, but did not have surgery, and reasons (i.e. death or withdrawal). We will also summarise by group the time between randomisation and surgery. Competing-risks survival regression will be used to model length of hospital stay. This allows for the fact that the participant may die in hospital, thus preventing the occurrence of the event of interest (discharge from hospital). As the time between randomisation and surgery will vary between participants, this will be included in the model. A multivariate model analysis will also be performed adjusting for clinically prognostic factors including age, gender, tumour type, T-stage and neoadjuvant treatment (yes/no). As a secondary analysis, we will perform the above including an interaction term in the model in order to test whether the effect of exercise differs according to whether psychological support is provided or not, although it is recognised that the power to detect any significant interactions in this number of patients will be low.\n\n\n\ni. WHODAS total score, and each category score (cognition, mobility, self-care, interpersonal relationships, life activities and participation in society) will be summarised by intervention group at baseline, 30 days, 12 weeks and 12 months using mean (standard deviation) or median (interquartile range) depending on the normality of data.\n\nii. Disability free survival will be assessed by identifying whether the patient has a WHODAS score less than 25% at 1-year post surgery, and will be compared between treatment groups using logistic regression. A multivariate analysis may be performed adjusting for clinically prognostic factors, as specified for the primary endpoint.\n\niii. The Clavien-Dindo complication score is an ordinal variable with classification grades I, II, IIIa, IIIb, IVa, IVb, V. The wilcoxon-mann-whitney test will be used to compare between groups. If appropriate, ordinal logistic regression will be used to perform an analysis adjusted for important prognostic variables. The CCI score provides a measure of overall morbidity over the whole period following an intervention, which is reflected on a scale from 0 (no complication) to 100 (death). Data will be checked for Normality and summarised using mean (SD) or median (IQR) as appropriate. If the scores are normally distributed, a t-test will be used to compare groups, and linear regression modelling may be considered in order to adjust for baseline characteristics. For non-normal data, we will check whether logistic transformation improves normality. If not, the wilcoxon-mann-whitney test will be used. The proportion of patients with post-operative morbidity according to POMS will be summarised in each of the nine domains by intervention group/day. Due to the repeated nature of the data, mixed modelling will also be considered.\n\niv. The EQ 5D subscales and overall Health scale will be tabulated at each timepoint (baseline, pre-surgery, week-12 and 12-months post-surgery). Linear mixed modelling will be performed with overall health scale as the outcome variable, and intervention group and baseline health scale as explanatory variables to investigate the effect of intervention considering all timepoints. This will be repeated for the EORTC-QLQ-C30 global health score, and mixed effects ordered logistic regression will be considered for analysis of subscales.\n\n\nPatient and public involvement\n\nPatient and public involvement has been included throughout. As part of the development of WesFit 2 focus groups and 1 interview were conducted with patients who had been encouraged to exercise prior to cancer treatment including: an individual who had undergone exercise in a community setting following general practitioner (GP) referral, a focus group (N = 12) of patients and carers who had taken part in clinical trials conducted by University Hospital Southampton (UHS) NHS Foundation Trust where they had performed in-hospital exercise training and a focus group (N = 2) of patients and cares who had attended the ‘Fit 4 surgery’ school at UHS. This informed the design of the trial such as the inclusion of support from personal trainers after surgery and the most appropriate language used to communicate the psychological element of the trial. These discussions also informed the managed process of community referral with links to the clinical teams clearly visible to patients to ensure they felt safe. Three patient representatives are included in the trial management group. They review and revise all patient facing documentation and trialled completion of all patient reported outcome measures. They were also consulted regarding the burden of the trial on participants. They will also help inform and facilitate future dissemination plans.\n\n\nEthics and dissemination\n\nThe trial was initially authorised by London – Westminster Research Ethics Committee (REC reference 18/LO/0129) on 06/03/2018. Before a patient is randomised to the WesFit Trial, written informed consent will be obtained. When obtaining consent from a patient, the trial and the patient information sheet will be introduced in full. Written confirmation that the patient has given their consent to participate in the trial will be recorded by member of the research team according to local practice.\n\nThe chief investigator and trial sponsor will have access to the full dataset. Generalisable results will be published in scientific journals, incorporated into multi-disciplinary society guidelines and presented at cross-disciplinary international scientific conferences, patient groups, cancer charities and NIHR strategic partners.\n\n\nMonitoring and trial management\n\nUniversity Hospital Southampton NHS Foundation Trust is acting as sponsor for this trial. The sponsor will ensure that all regulatory policies adhered to in line with GCP and phamacovigilance policies. Day to day trial management, including site set-up, training and urgent consideration of safety concerns, will be the responsibility of the chief investigator. The trial management group will meet monthly and oversee the day to day running of the WesFit trial.\n\nA project board will be responsible for all governance and finance frameworks and have oversight of the study conduct and management. The board will have an independent chair and consist of representatives from the sponsor, patient groups and study partners.\n\n\nData collection, quality and storage\n\nData will be collected and stored on password protected databases by trial personnel, who are trained in good clinical practice (GCP) and the General Data Protection Regulation (GDPR). Local Principle Investigators will be responsible for ensuring data accuracy and will complete a signed delegation log. Patient reported outcome measures will be completed on paper or using the electronic case report form (ALEATM) depending on patient preference. All patient reported outcome data will be entered into the electronic case report form (ALEATM) and data validation will take place according to the procedures set out in the data management plan and data validation plan. Clinical data will be collected from patients’ medical records and entered directly into the electronic case report form (ALEA™) with data validation taking place as per the above statement. Prior to any statistical analysis, all variables will be checked for the number of missing values, impossible values and improbable values. Impossible and improbable values will be defined by clinical opinion. Improbable values will also include values that are outside three standard deviations of the mean value. Any questions regarding the data will go back to the data manager. Descriptive statistics will be calculated for all variables, and distributional assumptions will be checked.\n\nData collected prior to participant withdrawal or deviation from the protocol will be included, unless participant withdraws consent for its use. Electronic copies of the case report form will be transferred using secure nhs.net email accounts, with data encrypted to ensure anonymity. All procedures for handling, storing, destroying and processing data will be compliant with the Data Protection Act 2018.\n\nAll trial documentation and data will be archived centrally by the sponsor at the end of trial in a purpose designed facility for ten years in accordance with regulatory requirements. Access to these archives will be restricted to authorised personnel. Electronic data sets will be stored indefinitely.\n\n\nData monitoring committee\n\nAn external, independent Data Monitoring Committee (DMC) will be convened on instruction of the CI and co-investigators on behalf of the project board. It will be made up of experts in the field who are not engaged in any trial activity. The DMC will be responsible for safeguarding the interests of the study participants and assuring the integrity and credibility of the clinical trial.\n\n\nSafety reporting\n\nAll adverse events are to be recorded in the relevant case report form. Adverse events during CPET are reported to the chief investigator, and adverse events during exercise training (pain and muscle soreness) or psychological support sessions (mental health concerns) are reported to the trial coordinator by the instructor/counsellor and recorded in the relevant case report form by the research physiologist/nurse. Fatal or life-threatening serious adverse events (SAEs) are reported within 24 hours of the local site becoming aware of the event. The SAE form documents the nature of the event, date of onset, severity, corrective therapies given, outcome and causality (that is, unrelated, unlikely, possibly, probably, or definitely). Questions concerning adverse event reporting are directed to the chief investigator in the first instance.\n\n\nConclusion\n\nThe Wessex Fit-4-Cancer Surgery trial will be the first pragmatic, robustly conducted randomised controlled study investigating whether a structured and responsive multi-modal exercise training programme +/- psychological intervention will result in a reduced hospital length of stay, improved disability-free survival, reduced in-hospital complications and improved health-related QoL for patients undergoing major inter-cavity resection of cancer.\n\n\nData availability\n\nNo data are associated with this article.\n\nUniversity of Southampton Institutional Repository: The Wessex Fit-4-Cancer Surgery Trial (WesFit): a protocol for a factorial-design, pragmatic randomised-controlled trial investigating the effects of a multi-modal prehabilitation programme in patients undergoing elective major intra–cavity cancer surgery. https://doi.org/10.5258/SOTON/D1790.56\n\nThis project contains the following extended data:\n\n- Appendix_3_TIDiER_checklist_for_healthy_conversation_skills_.docx.\n\n- Appendix_2_TIDiER_checklist_for_exercise.docx\n\n- Appendix_4-TIDiER_checklist_for_psychological_support_.docx\n\n- Appendix_5_and_6.docx (Schedule of observations and procedures for primary surgical pathway; and schedule of observations and procedures for neoadjuvant cancer treatment pathway)\n\n- WesFit_readme1.txt\n\nUniversity of Southampton Institutional Repository: SPIRIT checklist for ‘The Wessex Fit-4-Cancer Surgery Trial (WesFit): a protocol for a factorial-design, pragmatic randomised-controlled trial investigating the effects of a multi-modal prehabilitation programme in patients undergoing elective major intra–cavity cancer surgery’. https://doi.org/10.5258/SOTON/D1790.56\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nHo C, Kleeff J, Friess H, et al.: Complications of pancreatic surgery. HPB. 2005; 7: 99–108. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGoense L, Meziani J, Ruurda JP, et al.: Impact of postoperative complications on outcomes after oesophagectomy for cancer. BJS. 2019; 106: 111–9. PubMed Abstract \| Publisher Full Text\n\nMcDermott FD, Heeney A, Kelly ME, et al.: Systematic review of preoperative, intraoperative and postoperative risk factors for colorectal anastomotic leaks. Br J Surg. 2015 Apr; 102(5): 462–79. PubMed Abstract \| Publisher Full Text\n\nStabenau HF, Becher RD, Gahbauer EA, et al.: Functional Trajectories Before and After Major Surgery in Older Adults. Ann Surg. 2019; 268(6): 911–7. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLawrence VA, Hazuda HP, Cornell JE, et al.: Functional independence after major abdominal surgery in the elderly. J Am Coll Surg. 2004 Nov; 199(5): 762–72. PubMed Abstract \| Publisher Full Text\n\nMoran J, Wilson F, Guinan E, et al.: Role of cardiopulmonary exercise testing as a risk-assessment method in patients undergoing intra-abdominal surgery: A systematic review. Br J Anaesth. 2016; 116(2): 177–91. PubMed Abstract \| Publisher Full Text\n\nJack S, West MA, Raw D, et al.: The effect of neoadjuvant chemotherapy on physical fitness and survival in patients undergoing oesophagogastric cancer surgery. Eur J Surg Oncol. 2014 Oct; 40(10): 1313–20. PubMed Abstract \| Publisher Full Text\n\nWest MA, Parry MG, Lythgoe D, et al.: Cardiopulmonary exercise testing for the prediction of morbidity risk after rectal cancer surgery. Br J Surg. 2014; 101(9): 1166–72. PubMed Abstract \| Publisher Full Text\n\nWest MA, Loughney L, Barben CP, et al.: The effects of neoadjuvant chemoradiotherapy on physical fitness and morbidity in rectal cancer surgery patients. Eur J Surg Oncol. 2014 Nov; 1(11): in press. PubMed Abstract \| Publisher Full Text\n\nWest MA, Lythgoe D, Barben CP, et al.: Cardiopulmonary exercise variables are associated with postoperative morbidity after major colonic surgery: A prospective blinded observational study. Br J Anaesth. 2014; 112(4): 665–71. PubMed Abstract \| Publisher Full Text\n\nWest M, Asher R, Browning M, et al.: Validation of preoperative cardiopulmonary exercise testing-derived variables to predict in-hospital morbidity after major colorectal surgery. Br J Surg. 2016; 103: 744–52. PubMed Abstract \| Publisher Full Text\n\nWest MA, Loughney L, Lythgoe D, et al.: The effect of neoadjuvant chemoradiotherapy on whole-body physical fitness and skeletal muscle mitochondrial oxidative phosphorylation in vivo in locally advanced rectal cancer patients - An observational pilot study. PLoS One. 2014; 9(12): 1–15. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBurke S, Wurz A, Bradshaw A, et al.: Physical activity and quality of life in cancer survivors: A meta-synthesis of qualitative research. Cancers (Basel). 2017; 9(5): 1–29. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBurke SM, Brunet J, Sabiston CM, et al.: Patients’ perceptions of quality of life during active treatment for locally advanced rectal cancer: The importance of preoperative exercise. Support Care Cancer. 2013; 21(12): 3345–53. PubMed Abstract \| Publisher Full Text\n\nLoughney L, West MA, Dimitrov BD, et al.: Physical activity levels in locally advanced rectal cancer patients following neoadjuvant chemoradiotherapy and an exercise training programme before surgery: a pilot study. Perioper Med. 2017; 6(3): 1–8. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSilver JK, Baima J: Cancer prehabilitation: An opportunity to decrease treatment-related morbidity, increase cancer treatment options, and improve physical and psychological health outcomes. Am J Phys Med Rehabil. 2013; 92(8): 715–27. PubMed Abstract \| Publisher Full Text\n\nvan Rooijen SJ, Engelen MA, Scheede-Bergdahl C, et al.: Systematic review of exercise training in colorectal cancer patients during treatment. Scand J Med Sci Sport. 2018; 28(2): 360–70. PubMed Abstract \| Publisher Full Text\n\nGillis C, Buhler K, Bresee L, et al.: Effects of nutritional prehabiliation, with and without exercise on outcomes of patients who undergo colorectal surgery: A systematic review and meta-analysis. Gastroenterology. 2018; 155: 391–410. PubMed Abstract \| Publisher Full Text\n\nMinnella EM, Bousquet-Dion G, Awasthi R, et al.: Multimodal prehabilitation improves functional capacity before and after colorectal surgery for cancer: a five-year research experience. Acta Oncol (Madr). 2017; 56(2): 295–300. PubMed Abstract \| Publisher Full Text\n\nBarberan-Garcia A, Ubré M, Roca J, et al.: Personalised Prehabilitation in High-risk Patients Undergoing Elective Major Abdominal Surgery: A Randomized Blinded Controlled Trial. Ann Surg. 2018; 267(1): 50–6. PubMed Abstract \| Publisher Full Text\n\nTreanor C, Kyaw T, Donnelly M: An international review and meta-analysis of prehabilitation compared to usual care for cancer patients. J Cancer Surviv. 2018; 12(1): 64–73. PubMed Abstract \| Publisher Full Text\n\nPiraux E, Caty G, Reychler G: Effects of preoperative combined aerobic and resistance exercise training in cancer patients undergoing tumour resection surgery: A systematic review of randomised trials. Surg Oncol. 2018 Sep; 27(3): 584–94. PubMed Abstract \| Publisher Full Text\n\nTsimopoulou I, Pasquali S, Howard R, et al.: Psychological Prehabilitation Before Cancer Surgery: A Systematic Review. Ann Surg Oncol. 2015 Dec; 22(13): 4117–23. PubMed Abstract \| Publisher Full Text\n\nHeldens AFJM, Bongers BC, Lenssen AF, et al.: The association between performance parameters of physical fitness and postoperative outcomes in patients undergoing colorectal surgery: An evaluation of care data. Eur J Surg Oncol. 2017 Nov; 43(11): 2084–92. PubMed Abstract \| Publisher Full Text\n\nLoughney L, West M, Kemp G, et al.: Exercise interventions for people undergoing multimodal cancer treatment that includes surgery. Cochrane Database Syst Rev. 2018; 12. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHughes MJ, Hackney RJ, Lamb PJ, et al.: Prehabilitation Before Major Abdominal Surgery: A Systematic Review and Meta-analysis. World J Surg. 2019. PubMed Abstract \| Publisher Full Text\n\nMacmillan, National institute for health research, Anaesthetists R college of: Principles and guidance for prehabilitation within the management and support of people with cancer.2019.\n\nTurner J, Marthick M, Murnane A, et al.: Consensus statement on the role of accredited exercise physiologists in the treatment of cancer: A guide for all health professionals involved in the care of people with cancer.2017.\n\nCormie P, Atkinson M, Bucci L, et al.: Clinical Oncology Society of Australia position statement on exercise in cancer care. Med J Aust. 2018; 1. PubMed Abstract \| Publisher Full Text https://www.mja.com.au/journal/2018/209/6/clinical-oncology-society-australia-position-statement-exercise-cancer-care\n\nExercise: The miracle cure and the role of the doctor in promoting it. Academy of Medical Royal Colleges. 2015.\n\nWest M, Loughney L, Lythgoe D, et al.: Effect of prehabilitation on objectively measured physical fitness after neoadjuvant treatment in preoperative rectal cancer patients: a blinded interventional pilot study. Br J Anaesth. 2015 Oct; 114(2): 244–51. PubMed Abstract \| Publisher Full Text\n\nvan Rooijen SJ, Engelen MA, Scheede-Bergdahl C, et al.: Systematic review of exercise training in colorectal cancer patients during treatment. Scand J Med Sci Sports. 2017; (April): 8–13. PubMed Abstract \| Publisher Full Text\n\nDoherty AFO, West M, Jack S, et al.: Preoperative aerobic exercise training in elective intra-cavity surgery: a systematic review.2013: 1–11. PubMed Abstract \| Publisher Full Text\n\nValkenet K, Van De Port IGL, Dronkers JJ, et al.: The effects of preoperative exercise therapy on postoperative outcome: A systematic review. Clin Rehabil. 2011; 25(2): 99–111. PubMed Abstract \| Publisher Full Text\n\nJanssen TL, Steyerberg EW, Langenberg JCM, et al.: Multimodal prehabilitation to reduce the incidence of delirium and other adverse events in elderly patients undergoing elective major abdominal surgery: An uncontrolled before-and-after study.2019: 1–16. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMinnella EM, Awasthi R, Loiselle SE, et al.: Effect of Exercise and Nutrition Prehabilitation on Functional Capacity in Esophagogastric Cancer Surgery: A Randomized Clinical Trial. JAMA Surg. 2018; 153(12): 1081–9. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLevett DZH, Grimmett C: Psychological factors, prehabilitation and surgical outcomes: evidence and future directions. Anaesthesia. 2019; 74: 36–42. PubMed Abstract \| Publisher Full Text\n\nGrocott MPWW, Browne JP, Van der Meulen J, et al.: The Postoperative Morbidity Survey was validated and used to describe morbidity after major surgery. J Clin Epidemiol. 2007 Sep; 60(9): 919–28. PubMed Abstract \| Publisher Full Text\n\nCLavien Dindo Dindo D, Demartines N, Clavien PA: Classification of surgical complications: A new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004; 240(2): 205–13. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSlankamenac K, Graf R, Barkun J, et al.: The comprehensive complication index: a novel continuous scale to measure surgical morbidity. Ann Surg. 2013 Jul; 258(1): 1–7. PubMed Abstract \| Publisher Full Text\n\nHerdman M, Gudex C, Lloyd A, et al.: Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011; 20(10): 1727–36. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAaronson NK, Ahmedzai S, Bergman B, et al.: The European Organization for Research and Treatment of Cancer QLQ-C30: A Quality-of-Life Instrument for Use in International Clinical Trials in Oncology. J Natl Cancer Inst. 1993; 85(5): 365–76. PubMed Abstract \| Publisher Full Text\n\nLevett DZH, Jack S, Swart M, et al.: Perioperative cardiopulmonary exercise testing (CPET): consensus clinical guidelines on indications, organization, conduct, and physiological interpretation. Br J Anaesth. 2018; 120(3): 484–500. PubMed Abstract \| Publisher Full Text\n\nAdam LM, Jarman M, Barker M, et al.: Use of healthy conversation skills to promote healthy diets, physical activity and gestational weight gain: Results from a pilot randomised controlled trial. Patient Educ Couns. 2020 Jun; 103(6): 1134–42.PubMed Abstract \| Publisher Full Text\n\nBandura A: ISocial foundations of thought and action: A social cognitive theory . NJ1. England: Englewood Cliffs; 1986.\n\nMcAuley E, Blissmer B: Self-efficacy determinants and consequences of physical activity. Exerc Sport Sci Rev. 2000 Apr; 28(2): 85–8. PubMed Abstract\n\nMichie S, Richardson M, Johnston M, et al.: The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013; 46(1): 81–95. PubMed Abstract \| Publisher Full Text\n\nMourtzakis M, Prado CMM, Lieffers JR, et al.: A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl Physiol Nutr Metab. 2008; 33(5): 997–1006. PubMed Abstract \| Publisher Full Text\n\nMartin L, Birdsell L, MacDonald N, et al.: Cancer cachexia in the age of obesity: Skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol. 2013; 31(12): 1539–47. PubMed Abstract \| Publisher Full Text\n\nEisenhauer EA, Therasse P, Bogaerts J, et al.: New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur J Cancer. 2009; 45(2): 228–47. PubMed Abstract \| Publisher Full Text\n\nWhitehead SJ, Ali S: Health outcomes in economic evaluation: The QALY and utilities. Br Med Bull. 2010; 96(1): 5–21. PubMed Abstract \| Publisher Full Text\n\nSinger S, Kuhnt S, Gotze H, et al.: Hospital anxiety and depression scale cutoff scores for cancer patients in acute care. Br J Cancer. 2009 Mar; 100(6): 908–12. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLorig KR, Sobel DS, Ritter PL, et al.: Effect of a self-management program on patients with chronic disease. Eff Clin Pract. 2001; 4(6): 256–62. PubMed Abstract\n\nHibbard JH, Mahoney ER, Stockard J, et al.: Development and testing of a short form of the patient activation measure. Health Serv Res. 2005 Dec; 40(6 I): 1918–30. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMurray E, Treweek S, Pope C, et al.: Normalisation process theory: A framework for developing, evaluating and implementing complex interventions. BMC Med. 2010; 8. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGrimmett C: The Wessex Fit-4-Cancer Surgery Trial (WesFit): a protocol for a factorial-design, pragmatic randomised-controlled trial investigating the effects of a multi-modal prehabilitation programme in patients undergoing elective major intra–cavity cancer surgery.University of Southampton;[Dataset]. 2021. Publisher Full Text" }	[ { "id": "101805", "date": "22 Dec 2021", "name": "Aron Onerup", "expertise": [ "Reviewer Expertise Prehabilitation with exercise before colorectal cancer surgery." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors have planned a rational and interesting study. I have some suggestions for the authors to consider in order to optimize the output from their efforts and some minor comments on the text:\nThe authors write in the conclusions in the abstract that this is the first RCT of its kind. I do not find this to be correct, and I do not find it to be necessary. Carli et al.1 have evaluated multimodal rehabilitation before colorectal cancer surgery. I would consider the main strength of this study is that it includes high-intensity training, a large sample size, and clinically relevant outcomes.\n\nThe authors have performed several previous studies on the association between fitness and outcomes after surgery. It would be interesting if the authors could provide a pathophysiological rationale for the study with preliminary observational results on the association between both fitness and physical activity and postoperative outcomes in order to motivate the chosen outcomes, rather than a list of previous studies. This could also include more recent articles, e.g. the SR by Steffens et al.2 and the article by Onerup et al.3.\n\nFor colorectal cancer surgery, I would say that there are three well-performed RCTs where the effect of exercise has been evaluated for clinically relevant outcomes: Barberan-Garcia et al.4, Carli et al.1, and our pragmatic RCT recently reported, Onerup et al.5. I suggest the authors add these articles to the background since it has some common elements with the current study, albeit with a higher intensity (interesting) intervention in the current study.\n\nGiven the results from Barberan-Garcia et al.4, Onerup et al.5, and Onerup et al.3, it is reasonable to believe that the exercise intervention will have the most effect on non-surgical morbidity, e.g. cardiovascular complications, pulmonary complications, and possibly infections, etc. Have the authors considered focusing on, or at least measuring, these outcomes rather than general outcomes (length of hospital stay and CCI) mostly driven by surgical complications, where it is less probable that the intervention will have an effect? I fear that the authors risk missing a large portion of the effect with their chosen outcome measures.\n\nI appreciate the pragmatic design. Have the authors considered rating the pragmatic design using the tool described in BMJ?\n\nRegarding randomisation, I understand it as 4 treatment groups, stratified for: tumor type (8 alternatives), hospital site (unknown number), gender (2 alternatives), neoadjuvant therapy (≥2 alternatives), and age (≥2 alternatives). This gives me at least 4x8x2x2x2=256 x the number of hospitals strata. Suddenly the planned sample size sounds relatively small. When adding the wide spectrum of postoperative recovery for the various tumor types, I wonder if the authors consider the sample size to be large enough to find clinically relevant differences. Will the population be analyzed as one cohort or as different cohorts depending on tumor type?\nIn conclusion, the authors should be commended for performing the described study and I hope that my suggestions/questions may improve the outcome of the study.\n\nIs the rationale for, and objectives of, the study clearly described? Yes\n\nIs the study design appropriate for the research question? Yes\n\nAre sufficient details of the methods provided to allow replication by others? Yes\n\nAre the datasets clearly presented in a useable and accessible format? Yes", "responses": [ { "c_id": "8540", "date": "02 Aug 2022", "name": "Chloe Grimmett", "role": "Author Response", "response": "Thank you for the review and apologies for the delay in replying. We were not aware that replies to your comments were still outstanding, please accept our sincere apologies. 1) We have removed the 'first' in the abstract and concentrated on the high-intensity rehabilitation as the novelty in this study. 2) We have included the suggested references, thank you, and have elaborated more on the data in the introduction. 3) We have included a section on recent RCTs recommended showing illustrating mixed outcomes in high-quality trials. 4) Indeed, the reviewer is right. The primary outcome measure is a commissioner-driven metric along with all the patient-reported outcome metrics (WHO-DAS, EQ-5D, etc.) and will give us an in-depth understanding of heath economical endpoints which are imperative for service delivery in this area. Complications will be measured in 3 ways (Clavien-Dindo, POMS 18-item, and CCI). POMS-18 items measured on days 3, 5, 7, and 15 will ensure capture of complications in nine distinct domains including but not restricted to complications shown to be improved by prehab in the various RCTs we included in the introduction. 5) No, unfortunately, we were unaware that such a tool existed. WesFit is currently actively recruiting, so we are unable to change our trial methodology at this stage. 6) Indeed, the strata are significant, however, such a large pragmatic trial also needs to be deliverable. Increasing the number of patients to account for each stratum would make this trial unfeasible. We feel that the sample size calculation we undertook is adequate. As described, the sample size was based on the two main comparisons (i.e. exercise vs. no exercise and psychological support vs. no support). The trial sample size is the larger of these two comparisons, so in this case, the sample size calculation is powered on the psychological support comparison. The sample size calculation assumes that there is no interaction between the interventions. The population will be analysed as one cohort." } ] }, { "id": "96567", "date": "21 Feb 2022", "name": "Celena Scheede-Bergdahl", "expertise": [ "Reviewer Expertise Prehabilitation", "cancer", "exercise", "inflammation" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis study protocol is nicely put together, by researchers who are obviously very knowledgeable about the area and have experience conducting studies in this field.\nIt is very thorough but the only point where I can see where an expansion would be beneficial is the limitation of \"cross contamination\". Given that information regarding multimodal prehabilitation is widely accessible and compelling, how would the researchers account for those randomized into the control, exercise only or psychological support only groups from participating in their own versions of \"multimodal prehabilitation\"?\n\nThis is always worthwhile discussion when we aim to elucidate the various contributing factors to a multimodal approach.\n\nIs the rationale for, and objectives of, the study clearly described? Yes\n\nIs the study design appropriate for the research question? Yes\n\nAre sufficient details of the methods provided to allow replication by others? Partly\n\nAre the datasets clearly presented in a useable and accessible format? Yes", "responses": [ { "c_id": "8543", "date": "02 Aug 2022", "name": "Chloe Grimmett", "role": "Author Response", "response": "Thank you for the review and apologies for the delay in replying. We were not aware that replies to your comments were still outstanding, please accept our sincere apologies. Thank you for your kind comments. Control group contamination is a real issue, but luckily not seen in any of our cohorts. The reason being is that the control groups also benefit from activity advice, nutrition advice, and surgery school which are all standard of care. In our smaller cohorts we have given patients activity monitors to objectively measure patients’ activity and statistically account for it if contamination is seen; however, it was felt that this cohort was too large to undertake this in our usual manner. With that said, however, one of our exploratory outcomes will be to look for control group contamination using a sub-sample of participants recruited to all four groups. We will be undertaking this by a five-day objectively measured in-depth analyses of activity (repeatable over three time points) as we have done on our smaller cohorts (all referenced). Moreover, we have explored this in other cohorts and we have found that even if patients improve PA, unfortunately, this doesn’t translate to improvement in fitness or even outcome. This, we think, is down to the nature of the high-interval training programme which cannot be substituted for an improvement in PA." } ] } ]	1	https://f1000research.com/articles/10-952
https://f1000research.com/articles/10-1277/v1	14 Dec 21	{ "type": "Research Article", "title": "Validity of automated audiometry for hearing examination in patients with multidrug-resistant tuberculosis", "authors": [ "Nyilo Purnami", "Rian W. Palandeng", "Soedarsono -", "Dhany Arifianto", "In Seok Moon", "Rian W. Palandeng", "Soedarsono -", "Dhany Arifianto", "In Seok Moon" ], "abstract": "Background: The objective of this study was to test the validity of automated audiometry as a method of hearing examination in patients with multidrug-resistant tuberculosis.\nMethods: This was a cross-sectional comparative study with a retrospective approach, using patient medical records. Patients with multidrug-resistant tuberculosis (MDR-TB) were recruited based-on medical records that met the inclusion and exclusion criteria at the Pulmonology outpatient unit, then referred to the Otorhinolaryngology outpatient unit of the Dr. Soetomo Academic Medical Center. The subjects’ hearing function was measured with two different devices (automated audiometer and conventional audiometer) before being given anti-tuberculosis drug therapy (aminoglycoside injection) as ototoxicity monitoring from July to December 2019 period. Sensitivity and specificity analysis was used to assess the validity of the test. Results: A total of 36 patients (72 ears) were included. The comparison test results using the Mann-Whitney test showed that there were significant differences between automated audiometry and conventional audiometry in both ears. Analysis values were: sensitivity 80-97%, specificity 37-96%, positive predictive value 74-98%, and negative predictive value 59-96%. Conclusions: Automated audiometry is valid for use as a method of hearing examination and monitoring in patients with multidrug-resistant tuberculosis.", "keywords": [ "multidrug-resistant tuberculosis", "ototoxicity", "audiometry" ], "content": "Introduction\n\nMultidrug-resistant tuberculosis (MDR-TB) is tuberculosis (TB) resistant to isoniazid and rifampicin, with or without resistance to other anti-TB drugs.1 The World Health Organization (WHO) recommendations for multidrug-resistant tuberculosis (MDR-TB) include 8+ months of an aminoglycoside treatment such as kanamycin or amikacin or capreomycin. Aminoglycosides can produce significant side effects, including irreversible ototoxicity.2,3 The incidence of ototoxicity due to administration of aminoglycosides varies from 7% to 90%. Ototoxicity in MDR-TB patients is sensorineural and can be detected early by monitoring the hearing threshold periodically until the patient is recovered. Ototoxicity starts at high frequencies so that hearing techniques at high frequency are more sensitive to detect cochlear damage compared to methods that can only measure at standard frequencies (≤8000 Hz).4,5\n\nInitial hearing screening - at least air conduction (AC) - should be done on all patients who will start anti-tuberculosis drug therapy, especially aminoglycosides. Audiometry is a procedure to test one's listening ability at various sound frequencies and is used to identify hearing loss. This procedure is carried out using an electronic device called an audiometer to get the value of AC and bone conduction (BC). Not all audiometers can assess BC, so audiometry as auditory screening only requires AC values. MDR-TB patients with normal audiogram results can continue using anti-TB injections.6,7\n\nConventional audiometry is a gold standard examination to assess hearing loss. This procedure is carried out in a soundproof booth to determine the hearing threshold, which is the lowest pure tone that someone can still hear at a specific frequency, from 250 to 8000 Hz. The audiometer consists of a sound intensity control knob, a frequency control knob, headphones to assess AC and BC.8 Not all hospitals have soundproof chambers for this examination, and they are not recommended for MDR-TB patients because of the small size of the chamber. There is also less air circulation so they can cause shortness of breath and disturb concentration.6,7\n\nAutomated audiometry is an audiometer device that, in its use, does not require a soundproof booth; or in other words, automated audiometry is a portable audiometer that can be used in an open space. There is an active noise monitoring feature that functions to monitor the high level of background noise when conducting audiometry, making it possible to pause the test until the background noise level returns to low.9,10\n\nAutomated audiometry needs to be assessed for validity, and research in Indonesia has never been done. The purpose of this study was to prove the validity of automated audiometry as a method of hearing examination in patients with multidrug-resistant tuberculosis.\n\n\nMethods\n\nThis research was a cross-sectional comparative study with a retrospective approach. The subjects of this study were patients with MDR-TB in the Pulmonology outpatient unit Dr. Soetomo Academic Medical Center, who were referred to the otorhinolaryngology outpatient clinic for examination of hearing function, before starting the anti-tuberculosis drug therapy (aminoglycoside injection) as monitoring of ototoxicity during the period from July to December 2019. Data were retrieved from medical records that met the inclusion and exclusion criteria. Inclusion criteria were new MDR-TB patients who performed two kinds of hearing examination using conventional audiometry as the gold standard of hearing assessment and automated audiometry which can measure at high frequencies. Exclusion criteria were patients with incomplete medical record data.\n\nAutomated audiometry uses the KUDUwave audiometer (model KUDUwave Prime), which can measure at frequencies from 250 Hz to 16 000 Hz. The patient uses headphones in an open space of the Pulmonology outpatient department with a noise level of 60 dB and is asked to press a button when a tone is heard. Conventional audiometry uses the Interacoustics AD226 audiometer, which can measure at frequencies of 125 Hz to 8000 Hz. The patient uses headphones in a soundproof chamber at the Pulmonology outpatient department with a noise level of 28 dB, and asked to press a button when a tone is heard. Calibration of the two audiometers is done routinely. Examination with automated audiometry and conventional audiometry from medical record data in this study was carried out by competent medical personnel.\n\nData obtained from the medical records included air conduction (AC) results from conventional audiometry and automated audiometry examinations. Other data recorded included sex, age, results of an otoscopy examination, pure tone average (PTA), and the degree of hearing loss based on ear count. The automated audiometry examination results were compared with conventional audiometry results that were calculated at all frequencies. The subsequent analysis with IBM SPSS Statistics 25.0 uses a 2 × 2 table, with the output in sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Comparative analysis of automated audiometry and conventional audiometry using the Mann Whitney test.\n\nEthical clearance was obtained from the Ethical Committee of Dr. Soetomo Hospital, Surabaya, Indonesia (approval number 1858/KEPK/111.2020). Written informed consent was obtained from all individuals included in this study, after being given an explanation of the examinations to be carried out.\n\n\nResults\n\nBased on data from medical records, the results of hearing tests using two methods were compared: (i) automated audiometry examination conducted in the open field of a Pulmonology outpatient department, (ii) conventional audiometry performed in a soundproof room as the gold standard of hearing function examination. Data were obtained from 36 patients (72 ears) in the study period. There were 21 male patients (58.33%) and 15 female patients (41.67%).31\n\nThe youngest MDR-TB patient was 18 years old, while the oldest was 85 years old. The largest age group was 45 to 54 years, with 13 patients (36.11%). The results of the otoscopy examination in 36 patients (72 ears) showed all normal tympanic membranes (Table 1).\n\nConventional audiometry examination obtained normal hearing with an average of 19.26 ± 4.42 dB, mild hearing loss with an average of 29.52 ± 3.39 dB, moderate with an average of 45.62 ± 3.92 dB, moderate to severe with 62.50 ± 4.68 dB, and severe hearing loss with an average of 81.25 ± 12.37 dB (Table 2).\n\nSD = standard deviation.\n\nAutomated audiometry examination results obtained normal hearing with an average of 16.93 ± 5.34 dB, mild hearing loss with an average of 31.67 ± 4.21 dB, moderate with an average of 50.78 ± 4.11 dB, moderate to severe degree with the average was 59.37 ± 0.88 dB and severe degree with an average of 87.50 ± 2.89 dB (Table 3).\n\nSD = standard deviation.\n\nThe normality test results showed that the data were not normally distributed, so to find out significant differences between the two examinations, the Mann-Whitney test was used. The results showed significant differences (p < 0.05) between automated audiometry and conventional audiometry in both ears (Table 4).\n\nThe automated audiometry test results compared with conventional audiometry results as the gold standard, obtained a sensitivity of 80-97%, specificity 37-96%, positive predictive value (PPV) 74-98%, and negative predictive value (NPV) 59-96% (Table 5).\n\nPPV = positive predictive value; NPV = negative predictive value.\n\n\nDiscussion\n\nThe limitation of this study is that high frequencies (8000-16000 Hz) data collection of the automated audiometry was not carried out. The distribution of sex in this study found more male than female patients, consisting of 21 males (58.33%) and 15 females (41.67%). These results are consistent with research in China where 1154 MDR-TB incidents comprised 777 males and 377 females.11 MDR-TB is more frequent in males, a fact that is supported by research in Rawalpindi, Pakistan, that reports MDR-TB is more dominant in males with 23 cases than in females with 15 cases.12 However, a study in Ethiopia stated that the risk of MDR-TB decreases by 14% in males compared to females.13\n\nAnother study in Surakarta reported MDR-TB cases in 50 males and 26 females.14 The reason for this is not yet known, but could be due to male mobility or exposure due to social interactions is higher than female and non-compliance of a male patient in consuming anti-TB drugs.15 A study about the risk of multidrug- or rifampicin-resistance in males versus females stated that there was no evidence of either sex being more at risk of MDR-TB.16 The age characteristic of the youngest MDR-TB patients is 18 years, while the oldest is 85 years. The most populous age group was 45 to 54 years with 13 patients (36.11%). The average age of patients with MDR-TB was 43.44 years. Research in China reports that the most populous age group of MDR-TB patients is 31-45 years, with as many as 383 patients.11 Other studies in Mali report as many as 134 of 214 MDR-TB patients, including in the age group ≤40 years.17 A study in Gujarat reported that majority of MDR-TB patients were aged between 40 to 50 years.18 Age groups between 24-50 were found more in this study, probably because of its higher activity than other age groups.\n\nThe comparison test results using the Mann-Whitney test showed significant differences between automated audiometry and conventional audiometry in both ears. Research on the accuracy and efficiency of automated audiometry reports that automated audiometry is a stable, accurate, and time-efficient method for evaluating adult hearing status with normal hearing and hearing loss.19 Research in South Africa stated that there is no significant difference between conventional audiometry and automated audiometry.20 Several reports included in a systematic review indicated that automated audiometry using the method of adjustment (Békésy sweep or Békésy fixed frequency method) generally yields lower (i.e., better) thresholds compared with manual audiometry.21–26\n\nOther studies report that conventional audiometry and audiometry hearing threshold results show a small difference.27 Studies in primary school children aged 6-10 years in South Africa report that automated audiometry can correctly identify 87.5% of hearing loss detected using conventional audiometry.28 Another study in industry reported that the difference in the hearing threshold between automated audiometry and conventional audiometry was less than 5 dB.29 The difference in the results of the two examinations in this study was probably due to the difference in the frequency of the two devices used and the different conditions (fatigue, shortness of breath) of patients with MDR-TB when examined.\n\nThe automated audiometry results against the conventional audiometry results obtained 80-97% sensitivity, specificity 37-96%, positive predictive value 74-98%, and negative predictive value 59-96%. Research evaluating the sensitivity and specificity of automated audiometry reports that automated audiometry has a high sensitivity, ranging from 86-100% and specificity of 78-100%. Positive predictive value is around 89-91%, and negative predictive value is about 89-100%, indicating that automated audiometry can be used to identify hearing loss.30 The results in this study were obtained according to the reference. The background noise level of a non-soundproofed room does not affect the accuracy of the hearing threshold value obtained using automated audiometry.\n\n\nConclusions\n\nThis study shows that automated audiometry is a valid method of hearing examination and monitoring in patients with multidrug-resistant tuberculosis with normal hearing or hearing loss. Automated audiometry does not require a soundproof booth, rather can be performed in an open space. An active noise monitoring feature monitors the high level of background noise when conducting audiometry, making it possible to pause the test until the background noise level returns to low.\n\n\nData availability\n\nFigshare: Validity of automated audiometry for hearing examination in patients with multidrug-resistant tuberculosis. https://doi.org/10.6084/m9.figshare.17129123.31\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nPaul R: The threat of multidrug-resistant tuberculosis. J. Global Infect. Dis. 2018; 10(3): 119–120. PubMed Abstract \| Publisher Full Text\n\nHeysell SK, Ahmed S, Rahman MT, et al.: Hearing loss with kanamycin treatment for multidrug-resistant tuberculosis in Bangladesh. Eur. Respir. J. 2018; 51(3): 1–3.\n\nGamboa I, Sousa PC, Duarte D, et al.: Amikacin ototoxicity: case report and literature review. Otolaryngology Online Journal. 2018; 8(4): 1–5.\n\nPeterson L, Rogers C: Aminoglycoside-induced hearing deficits - a review of cochlear ototoxicity. S. Afr. Fam. Pract. 2015; 57(2): 77–82. Publisher Full Text\n\nGanesan P, Schmiedge J, Manchaiah V, et al.: Ototoxicity: a challenge in diagnosis and treatment. J. Audiol. Otol. 2018; 22(2): 59–68. PubMed Abstract \| Publisher Full Text\n\nChallenge TB: Guide to detect and manage hearing loss during the management of drug-resistant tuberculosis.2019. Accessed February 1, 2020. Reference Source\n\nChallenge TB: Audiometry in the management of drug-resistant tuberculosis.2017. Accessed February 1, 2020. Reference Source\n\nAmerican Speech Language Hearing Association: Guidelines for manual pure-tone threshold audiometry.2019. Accessed February 1, 2020. Reference Source\n\nShojaeemend H, Ayatollahi H: Automated audiometry: a review of the implementation and evaluation methods. Healthc. Inform. Res. 2018; 24(4): 263–275. PubMed Abstract \| Publisher Full Text\n\nStorey KK, Munoz K, Nelson L, et al.: Ambient noise impact accuracy of automated hearing assessment. Int. J. Audiol. 2014; 53(10): 730–736. PubMed Abstract \| Publisher Full Text\n\nLu Z, Jiang W, Zhang J, et al.: Drug resistance and epidemiology characteristics of multidrug-resistant tuberculosis patients in 17 provinces of China. PLoS One. 2019; 14(11): 1–14. Publisher Full Text\n\nRafique A, Dastgir M, Jamalullah M, et al.: Streptomycin associated hearing loss in patients treated for multidrug resistant tuberculosis. Isr. Med. J. 2012; 4(3): 139–142.\n\nAlemu A, Bitew ZW, Diriba G, et al.: Risk factors associated with drug-resistant tuberculosis in Ethiopia: a systematic review and meta-analysis. Authorea. 2021; 1: 1–12. Publisher Full Text\n\nPamungkas P, Rahardjo SS, Murti B: Evaluation of multidrug resistant tuberculosis predictor index in Surakarta, Central Java. J. Epidemiol. Public Health. 2018; 03(2): 263–276. Publisher Full Text\n\nSoeroto AY, Pratiwi C, Santoso P, et al.: Factors affecting outcome of longer regimen multidrug-resistant tuberculosis treatment in West Java Indonesia: a retrospective cohort study. PLoS One. 2021; 16(2): 1–13. Publisher Full Text\n\nMcQuaid CF, Horton KC, Dean AS, et al.: The risk of multidrug- or rifampicin-resistance in males versus females with tuberculosis. Eur. Respir. J. 2020; 56(3): 1–14.\n\nBaya B, Achenbach CJ, Kone B, et al.: Clinical risk factors associated with multidrug-resistant tuberculosis (MDR-TB) in Mali. Int. J. Infect. Dis. 2019; 81: 149–155. PubMed Abstract \| Publisher Full Text\n\nBhardwaj M, Shah KV: A cross-sectional study to correlate demographic and clinical profile of multi-drug resistant tuberculosis patients in a tertiary hospital. IP Indian J. Immunol. Respir. Med. 2021; 6(2): 80–85. Publisher Full Text\n\nSwanepoel DW, Mngemane S, Molemong S, et al.: Hearing assessment-reliability, accuracy, and efficiency of automated audiometry. Telemed. J. E Health. 2010; 16(5): 557–563. PubMed Abstract \| Publisher Full Text\n\nMahomed F, Swanepoel DW, Eikelboom RH, et al.: Validity of automated threshold audiometry: a systematic review and meta-analysis. Ear Hear. 2013; 34(6): 745–752. PubMed Abstract \| Publisher Full Text\n\nMaiya PS, Kacker SK: Comparison of threshold between pure tone and Bekesy audiometry. Silent Wld. 1973; 8: 16–20.\n\nRobinson DW, Whittle LS: A comparison of self-recording and manual audiometry: some systematic effects shown by unpractised subjects. J. Sound Vib. 1973; 26: 41–62. Publisher Full Text\n\nErlandsson B, Håkanson H, Ivarsson A: Comparison of the hearing threshold measured by manual pue-tone and by self-recording (Békésy) audiometry. Audiology. 1979; 18: 414–429. PubMed Abstract \| Publisher Full Text\n\nHarris DA: Microprocessor, self-recording and manual audiometry. J. Aud. Res. 1979; 19: 159–166. PubMed Abstract\n\nFrampton MC, Counter RT: A comparison of self recording audiometry in naval establishments and clinical audiometry in a hospital setting. J. Roy. Nav. Med. Serv. 1989; 75: 99–104. PubMed Abstract \| Publisher Full Text\n\nIshak WS, Zhao F, Stephens D: Test-retest reliability and validity of Audioscan and Békésy compared with pure tone audiometry. Audiol. Med. 2011; 9: 40–46. Publisher Full Text\n\nJones CGB, Eikelboom RH, Swanepoel DW, et al.: Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a soundtreated environment. Int. J. Audiol. 2016; 55(9): 507–513. PubMed Abstract \| Publisher Full Text\n\nMahomed AF, Swanepoel DW, Eikelboom RH: Diagnostic hearing assessment in schools: validity and time efficiency of automated audiometry. J. Am. Acad. Audiol. 2016; 27: 42–48.\n\nMeinke DK, Norris JA, Flynn BP, et al.: Going wireless and booth-less for hearing testing in industry. Int. J. Audiol. 2017; 56: 41–51. PubMed Abstract \| Publisher Full Text\n\nSkjonsberg A, Heggen C, Jamil M, et al.: Sensitivity and specificity of automated audiometry in subjects with normal hearing or hearing impairment. Noise & Health A Bimonthly Inter-disciplinary International Journal. 2019; 21(98): 1–6. Publisher Full Text\n\nPurnami N: Validity of automated audiometry for hearing examination in patients with multidrug-resistant tuberculosis. figshare. Dataset. 2021. Publisher Full Text" }	[ { "id": "115235", "date": "02 Feb 2022", "name": "Herman A. Jenkins", "expertise": [ "Reviewer Expertise I am Chair of an Otolaryngology-Head and Neck Surgery Department in the USA with expertise in hearing and balance disorders and monitoring both." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAccess and therefore expense of providing standard audiometry testing is often difficult, particularly in developing countries with areas of limited access. This manuscript compares standard audiometry with an automated form. The latter does not require sound dampened facilities or great expense. The investigators compared the two and demonstrated that, while the automated testing was less predictive of hearing level, it was within a range to make it feasible for situations not allowing sophisticated setup. The authors have used a small, but valid sample and the conclusions that they have drawn are valid. Monitoring in conditions as drug resistance or chemotherapy is important and the use of automated testing provided sufficient information to validate the hearing level without requiring expensive set up. I would recommend indexing the manuscript as is.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "7773", "date": "03 Feb 2022", "name": "Nyilo Purnami", "role": "Author Response", "response": "Thank you very much." } ] }, { "id": "123563", "date": "13 Apr 2022", "name": "Jackie L. Clark", "expertise": [ "Reviewer Expertise Teleaudiology", "pediatric audiology", "electrophysiology", "large scale community based hearing screenings", "hearing aid fitting and dispensing." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThough there are a number of studies over the past number of years across the globe with similar findings. I only have a few minor concerns: the authors indicated that there were significant threshold differences between the automated vs conventional audiometry; and conclusion suggests that the automated audiometry is a valid method of hearing examination. The significant differences may be statistically different, and though they don't appear with the limited data available, there is no clinically significant difference between the two conditions.\nThe other concern is that the automated audiometry was completed in a relatively hostile environment. The manufacturer suggests that while a sound booth is not necessary, it IS necessary to find an auditorily and visually quiet space. If the system were used appropriately (i.e. in an environment without visual and auditory competition) the findings may have revealed less difference between the two conditions. It is important to keep in mind that the advantage of the automated audiometry is the capability of task shifting to an assistant so that the audiologist can work on more advanced measures in the clinic. The noise suppression system within the automated system optimizes the assessment outcomes.\nThank you for the opportunity of reviewing this interesting manuscript.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8566", "date": "09 Aug 2022", "name": "Nyilo Purnami", "role": "Author Response", "response": "\"The authors indicated that there were significant threshold differences between the automated vs conventional audiometry; and conclusion suggests that the automated audiometry is a valid method of hearing examination.\" I Agree, in here the authors want to test the validity of automated auditory as method hearing examination because there are already differences in the regulation of the examination, namely without the use of canamicyn injection. it is hoped that automated auditory can be used \"The significant differences may be statistically different, and though they don't appear with the limited data available, there is no clinically significant difference between the two conditions\" Because the research is limited in time, we using patient medical records in a six month period. There is no clinically significant different because patient and equipment limitations. \"The manufacturer suggests that while a sound booth is not necessary, it IS necessary to find an auditorily and visually quiet space.\" An active noise monitoring feature monitors the high level of background noise when conducting audiometry, making it possible to pause the test unlit the background noise level. But thank you for suggestions, may be the next research we will consider carefully about manufacturer suggest. \"If the system were used appropriately (i.e. in an environment without visual and auditory competition) the findings may have revealed less difference between the two conditions. It is important to keep in mind that the advantage of the automated audiometry is the capability of task shifting to an assistant so that the audiologist can work on more advanced measures in the clinic. The noise suppression system within the automated system optimizes the assessment outcomes.\" The advantage of this examination is that it provides benefits and convenience to an assistant so that the audiologist can work on more advanced measures in the clinic." } ] } ]	1	https://f1000research.com/articles/10-1277
https://f1000research.com/articles/11-879/v1	02 Aug 22	{ "type": "Case Report", "title": "Case Report: Role of transesophageal echocardiography in a patient with an initially misdiagnosed acute pulmonary embolism", "authors": [ "Mohamed Aziz Daghmouri", "Maroua Oueslati", "Mohamed Amine Tarhouni", "Olfa Faten", "Sameh Zakhama", "Lotfi Rebai", "Maroua Oueslati", "Mohamed Amine Tarhouni", "Olfa Faten", "Sameh Zakhama", "Lotfi Rebai" ], "abstract": "Background: For the diagnosis of acute pulmonary embolism, chest computerized tomography (CT) angiography is considered as the gold standard. However, echocardiography could be useful especially in cases of high suspicion with normal CT scan or for patient with hemodynamic instability. Case presentation: We present a case of a 47-year-old man admitted to the intensive care unit with a diagnosis of respiratory failure and hemodynamic instability 24 hours after closed fracture of the right leg. Before his admission, a thoracic CT angiography was done but did not show any sign of acute pulmonary embolism. During the first hours, he presented a bad evolution with a respiratory status which failed to respond to high dose of vasopressor, oxide nitric and ventilatory support. Therefore, due to the poor echocardiographic window, transesophageal echocardiography examination was done in emergency. It revealed high-probability diagnosis of massive pulmonary embolism based on right ventricular dysfunction and the presence of thrombus in the right pulmonary artery. Anticoagulant therapy (non-fractioned heparin) was administrated immediately achieving a favorable clinical outcome with rapid withdrawal of dobutamine, nitric oxide and norepinephrine. Conclusions: This case illustrates the fundamental role of transesophageal echocardiography in a critically ill patient with shock due to high-probability pulmonary embolism. Echocardiography allows the initiation of adequate treatment without further delay.", "keywords": [ "Acute pulmonary embolism", "transesophageal echocardiography", "transthoracic echocardiography", "CT chest angiography" ], "content": "Introduction\n\nPulmonary embolism (PE) can be difficult to diagnose especially in critical ill patients who are hemodynamically unstable notably if the classic symptoms of PE are absent1. However, many cases of PE are diagnosed in an emergency context2. Echocardiography could be considered a useful technique at the bedside in critical care settings for the diagnosis of PE, especially as it is difficult to diagnose using other techniques2. That is why, we present this case of massive pulmonary embolism diagnosed by the combined use of transthoracic echocardiography (TTE) and transesophageal echocardiography (TEE) due to the poor transthoracic window. TEE was useful in ruling out differential diagnoses and finding signs in favor of the diagnosis of PE, which allowed the initiation of adequate treatment without further delay. The aim of this case report was to highlight the pivotal role of TEE in the diagnosis of PE in a hemodynamically unstable patient especially when his mobilization to the radiology department was difficult to achieve.\n\n\nCase presentation\n\nA 47-year-old north-African man working as an engineer, with no relevant medical history, previous treatments or toxic habits (tobacco, alcohol) was admitted to hospital with a diagnosis of isolated closed fracture of his right leg due to a road accident (he was struck by a motor vehicle). At the time of admission, he was conscious, without any neurological alterations, or hemodynamic and respiratory disorders.\n\n24 hours after admission, the patient suddenly presented a change in his level of consciousness (confusion with Glasgow come scale of 12). He was tachypneic (30 breaths/min) with an oxygen saturation of 94% with a non-rebreather mask. Lung auscultation showed conserved vesicular murmur with bilateral basal crackles. He was tachycardic (heart rate 120 beats/min) and presented a hypotension (blood pressure was 80/40 mmHg). He was not febrile and did not present any cutaneous sign. A 12-lead electrocardiogram showed only a sinusal tachycardia without other signs of acute coronary syndrome or right heart strain. The patient was immediately treated with crystalloid fluid infusion and bolus of epinephrine. After that, a brain scan was done which did not show signs of post traumatic abnormalities, in addition to thoracic CT angiography which did not show any sign of acute pulmonary embolism (Figure 1).\n\nTherefore, he was transferred in emergency to the intensive care unit (ICU) and due to his bad evolution, he was intubated and required mechanical ventilation. Arterial acid-base balance at that time showed fraction of inspired oxygen 100%, pH 7.15, partial pressure of oxygen 86 mmHg, partial pressure of carbon dioxide 52 mmHg, bicarbonates 24 mmol/L, base excess -15, lactic acid 2.5 mmol/L and oxygen saturation 93%. Laboratory findings showed hemoglobin 10g/dl, leukocytes 6.103/mm3, lymphopenia, creatinine 1.5 mg/dl, troponin T 34 µg/L, pro-BnP 400 pg/ml and procalcitonin < 0.05. His respiratory status failed to respond to high-dose of vasopressor and ventilatory support so nitric oxide was introduced in addition to continued infusion of cisatracurium. Chest radiography showed bilateral infiltrate (Figure 2).\n\nIn order to determine the real cause of this instability, TTE was performed however we obtained poor quality images, so it was necessary to do a TEE which was performed by an experiment anesthesiologist. TEE demonstrated a dilated and dysfunctional right ventricle (RV) with a hypertrophic dysfunctional left ventricle (LV). The right atrium (RA) was also severely dilated with a patent foramen oval and septum bowing (Figure 3). The RV end-diastolic diameter to LV end-diastolic diameter ratio was 1.2 suggesting RV pressure overload. RV dilatation led to functional tricuspid regurgitation as the tricuspid annulus enlarged. There was a pulmonary arterial hypertension with a pulmonary artery systolic pressure of 70–80 mmHg. Initially, there was no evidence of a thrombus either in the pulmonary arteries or on the right side of the heart. Due to global heart failure and the low-cardiac-output state, dobutamine was used with the doses of 3–5 µg/kg/min. However, after 24 hours, a control TEE showed an evident thrombus in the right pulmonary artery which was dilated (Figure 4). Massive pulmonary embolism was suspected but we could not confirm it by other complementary test because the unfavorable hemodynamic situation of the patient prevented his transfer. Anticoagulant therapy (non-fractioned heparin) was administrated immediately achieving a favorable clinical outcome with rapid withdrawal of dobutamine, nitric oxide and cisatracurium. No follow up information about the patient was available.\n\n\nDiscussion\n\nThis case highlights the crucial role of echocardiography in ICU for patients with severe shock due to massive pulmonary embolism associated to an unfavorable hemodynamic situation. In addition, like another similar case published in literature, it illustrates the value of TEE over TTE for those who have poor transthoracic window secondary to some clinical situation (supine position or mechanical ventilation)1.\n\nPulmonary embolism can be difficult to diagnose particularly for patients in ICU who are sedated or on mechanical ventilation because key symptoms are absent (dyspnea, chest pain and syncope). For the diagnosis of PE, pulmonary angiography and spiral CT is the gold standard with a sensitivity of 83% and a specificity of 96% according to the PIOPED II trial3. However, in our scenario, the CT angiography performed initially did not show any sign of acute pulmonary embolism despite the high probability of PE and this could be explained by the occurrence of artifacts or secondary migration of subsegmental thrombosis. So echocardiography was useful in order to rule out some differential diagnoses which caused this hemodynamic instability (tamponade, aortic dissection, hypovolemia…) according to the guidelines of European Society of Cardiology4.\n\nVignon et al. showed that TEE helped in 98% of clinical decisions in a critical care population so it has higher impact on patient care than TTE which provided adequate images in only 38% of cases5. Concerning the confirmation of PE, TEE has 70% sensitivity and 81% specificity6. In the context of PE, TEE usually shows indirect signs like RV dilatation (RV end-diastolic diameter/LV end-diastolic diameter ratio > 0.9) and exclude other causes7. In addition, serial assessment of RV size, determination of RV systolic pressure and inferior vena cava assessment could be performed in patients with massive PE. Although, thrombus may be seen in some cases. According to Pruszczyk et al.8, the central pulmonary arteries including the proximal lobar branches on both sides could be precisely visualized by biplane TEE. Only the proximal left pulmonary artery is difficult to assess because it is shielded by the left main bronchus. But a perimural artifact may be potentially misinterpreted as thrombus especially when it is present in the right pulmonary artery9.\n\nSignificant hemodynamic instability is present in 8% of patient with acute pulmonary embolism. The main cause is acute right ventricular failure which increases mortality from 15% to 42%10. That is why, TEE could be useful for analyzing response to medical interventions such as fluid and drug therapy. It could also be helpful for monitoring RV function and pulmonary artery systolic pressure especially if thrombolytics or anticoagulant were administrated11.\n\n\nConclusion\n\nWe reported this case in order to show the fundamental role of TEE in ICU especially when the transthoracic window is poor. TEE allows the initiation of adequate treatment without further delay, by avoiding unnecessary mobilization of an unstable patient to perform CT chest angiography and can lead to a better clinical outcome. Although, TEE has some limitations like the cost of the equipment or the inability to place a probe (esophagectomy, esophageal diverticula or varices), complication rates from TEE use are fairly low at 0.2%12. In addition, it has been demonstrated to have a steep learning curve and that physicians could successfully perform focused TEE assessments with a high retention rate after 6 weeks of 4-hour simulation workshop13.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nConsent\n\nWritten informed consent for publication of their clinical details and clinical images was obtained from the patient.", "appendix": "Acknowledgements\n\nAn earlier version of this article can be found on Authorea (doi: 10.22541/au.161467284.43760460/v1).\n\n\nReferences\n\nMiranda-Bacallado J, Izquierdo-Gómez MM, García-Niebla J, et al.: Role of echocardiography in a patient with suspected acute pulmonary embolism: a case report. J Med Case Rep. 2019; 13(1): 37. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFields JM, Davis J, Girson L, et al.: Transthoracic Echocardiography for Diagnosing Pulmonary Embolism: A Systematic Review and Meta-Analysis. J Am Soc Echocardiogr. 2017; 30(7): 714–723.e4. PubMed Abstract \| Publisher Full Text\n\nStein PD, Fowler SE, Goodman LR, et al.: Multidetector Computed Tomography for Acute Pulmonary Embolism. N Engl J Med. 2006; 354(22): 2317–27. PubMed Abstract \| Publisher Full Text\n\nKonstantinides SV, Meyer G, Becattini C, et al.: 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS): The Task Force for the diagnosis and management of acute pulmonary embolism of the European Society of Cardiology (ESC). Eur Heart J.. 2020; 41(4): 543–603. PubMed Abstract \| Publisher Full Text\n\nVignon P, Mentec H, Terré S, et al.: Diagnostic accuracy and therapeutic impact of transthoracic and transesophageal echocardiography in mechanically ventilated patients in the ICU. Chest. 1994; 106(6): 1829–34. PubMed Abstract \| Publisher Full Text\n\nKline JA, Johns KL, Colucciello SA, et al.: New diagnostic tests for pulmonary embolism. Ann Emerg Med. 2000; 35(2): 168–80. PubMed Abstract \| Publisher Full Text\n\nTorbicki A, Perrier A, Konstantinides S, et al.: Guidelines on the diagnosis and management of acute pulmonary embolism: the Task Force for the Diagnosis and Management of Acute Pulmonary Embolism of the European Society of Cardiology (ESC). Eur Heart J. 2008; 29(18): 2276–315. PubMed Abstract \| Publisher Full Text\n\nPruszczyk P, Torbicki A, Kuch-Wocial A, et al.: Visualization of the central pulmonary arteries by biplane transesophageal echocardiography. Exp Clin Cardiol. 2001; 6(4): 206–10. PubMed Abstract \| Free Full Text\n\nBedet A, Razazi K, May F, et al.: Transesophageal echocardiography for pulmonary embolism diagnosis in the intensive care unit: artifact in three dimensions. Intensive Care Med. 2017; 43(2): 261–2. PubMed Abstract \| Publisher Full Text\n\nZhao S, Friedman O: Management of Right Ventricular Failure in Pulmonary Embolism. Crit Care Clin. 2020; 36(3): 505–15. PubMed Abstract \| Publisher Full Text\n\nPorter TR, Shillcutt SK, Adams MS, et al.: Guidelines for the Use of Echocardiography as a Monitor for Therapeutic Intervention in Adults: A Report from the American Society of Echocardiography. J Am Soc Echocardiogr. 2015; 28(1): 40–56. PubMed Abstract \| Publisher Full Text\n\nKallmeyer IJ, Collard CD, Fox JA, et al.: The safety of intraoperative transesophageal echocardiography: a case series of 7200 cardiac surgical patients. Anesth Analg. 2001; 92(5): 1126–30. PubMed Abstract \| Publisher Full Text\n\nArntfield R, Pace J, McLeod S, et al.: Focused transesophageal echocardiography for emergency physicians-description and results from simulation training of a structured four-view examination. Crit Ultrasound J. 2015; 7(1): 27. PubMed Abstract \| Publisher Full Text \| Free Full Text" }	[ { "id": "277859", "date": "27 May 2024", "name": "David Dudzinski", "expertise": [ "Reviewer Expertise Echocardiography (transthoracic and transesophageal)", "appropriate use criteria", "critical care cardiology", "pulmonary embolism and right heart" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a case report of a post-trauma patient with hemodynamic and respiratory instability wherein transesophageal echocardiography was performed toward identifying thrombus-in-transit.\nSeveral clinical parameters are uncertain in the current version (and this analysis also reviewed the earlier version of the article referenced). First, how was written informed consent able to be obtained if no follow up information about the patient was available? Unclear from the vignette is whether there was concurrent fat embolism syndrome given antecedent long bone trauma and change in consciousness, though the authors are likely attempting to address this by excluding cutaneous findings however all elements of the Bergmann triad are not required for that diagnosis. The lung imaging windows are poor quality but do suggest other contributors to the pathophysiology besides only pulmonary emboli, and these are not explained.\n\nAdditionally, the vignette strongly suggests right to left interatrial shunting as another mechanism but does not discuss. What artifacts on the CT are referred to as explanation for negative pulmonary embolism CT? Figure 1 does not show optimal windows to exclude proximal pulmonary embolism. Videos would be the ideal modality to provide for Figure 3 and 4. Perimural artifact is referenced as a limitation of TEE in assessment of the right pulmonary artery yet the image quality of Figure 4 is insufficient to assess this; color Doppler would also be useful, as would biplane or 3D. Additionally the caption \"apdte\" in Figure 4 remains unclear. What does a \"high-probability\" TEE mean when thrombus-in-transit was ostensibly visualized?\n\nBasic parameters to strengthen the vignette would include laboratory value reference ranges, explaining why the patient was anemic (related to long bone trauma?), characterization of the patient's oximetry with respect to possible shunt and ventilator settings, and correction of various grammar and phrases including \"oxide nitric\" \"bilateral consendation\" \"experiment anesthesiologist\" and \"control TEE\".\nIf there was high suspicion would not unfractionated heparin be administered empirically? Given thrombus-in-transit, would interventional strategy be considered or recommended?\nLastly, I agree echocardiography can have a role in elucidating the differential diagnosis, however this case report may overweight the role of transesophageal echocardiography (I would not characterize its role as fundamental), especially as regards PE, given inability to visualize the left pulmonary artery generally. The standards of which physicians should perform transesophageal echocardiography and after what training remain under debate.\n\nIs the background of the case’s history and progression described in sufficient detail? Partly\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? No\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? No\n\nIs the case presented with sufficient detail to be useful for other practitioners? Partly", "responses": [] }, { "id": "293558", "date": "24 Jun 2024", "name": "Casper Falster", "expertise": [ "Reviewer Expertise Ultrasound and venous thromboembolism." ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThank you for letting me review this case report highlighting the important utility of ultrasound in suspected pulmonary embolism.\nThe manuscript by Daghmouri MA et al is generally well written. However, I have a few concerns which I believe should be addressed prior to acceptance.\nBelow you will find my comments regarding each part of the manuscript.\nAbstract:\n\n1. Under \"case presentation\" you write that the patients presents with a diagnosis of respiratory failure and hemodynamic instability. I suggest framing it as \"symptoms\" of respiratory failure instead or just \"admitted to the intensive care unit due to respiratory failure and hemodynamic instability...\"\n2. Instead of \"bad evolution\" consider using the phrase \"clinical deterioration\"\n\nIntroduction:\n\n3. For this section, I would like to propose the following recent reviews instead of reference 1 and 2.\nWe recently published this review in Lancet Haematology, which compares 13 guidelines recommendations on diagnosis of PE, also including hemodynamic instability and the role of ultraound: Falster C et al (2023 [ref - 1]) : https://pubmed.ncbi.nlm.nih.gov/37804848/\nFurther, while Fields and colleagues provided a nice review on diagnostic accuracy of cardiac ultrasound in 2017, this recent meta-analysis is more comprehensive and only includes studies in which PE was already suspected, making the study population more representative of your case: Falster C et al (2022 [ref - 2]) : https://pubmed.ncbi.nlm.nih.gov/34497138/\nNotably, the meta-analysis reports a specificity of 100% of right heart thrombi. Underscoring your approach.\n\nCase presentation:\n\n4. Was there any suspicion of DVT at the time of hospital admission? Any ultrasound performed?\n5. Could you elaborate which ECG-signs of right heart strain you assessed for? especially presence of S1Q3T3, iRBBB and T-wave inversions in V1-V4 are (although not very sensitive or specific) associated with a worse outcome in present PE.\n6. For those using other references of arterial blood gas (i.e. in Denmark, we use kPa instead of mmHg for partial pressures. Could you add the converted metrics in a paranthesis or at least indicate if the pressure were elevated or lowered.\n7. Why did you obtain poor quality images using TTE? Supine position only? High BMI? Low quality scanner etc.?\n8. A TR gradient of 70-80mmHg seems high for an acute PE. While his RV might be able to generate such pressures given his young age, could there be any other causes of pulmonary hypertension? For instance previous PEs giving rise to CTEPH which now has an acute component? Indeed, it is also somewhat curious that his clinical status declines that rapidly without any central emboli. Perhaps you could add some considerations on this topic in the discussion. Kurzyna et. al. has published research suggesting that the TR gradient is rarely above 60mmHg in acute PE with an otherwise unconditioned RV (cited in the Thorax review - see 60/60-sign). - Kurzyna M et al (2002 [ref - 3])\n9. What do you mean by dysfunctional LV? In cases of massive PE, LV preload is severely reduced, rendering the LV hyperdynamic. Was this the case? If there was presence of for instance regional hypo- or akinesia, this should be elaborated further.\n10. You describe the hemodynamic situation as unfavorable. Could you elaborate? If the patient was hemodynamically unstable tPA should be initiated along with heparinization according to most guidelines (see the Lancet Haematology review). What were your considerations at this point?\n\nDiscussion:\n\n11. Besides TEE, venous compression ultrasound showing a DVT is also recommended for diagnosis of PE by multiple medical societies (see Lancet Haematology review). Consider discussing this point as well. Especially considering that your patient had a fracture, this risk of substantian residual DVT is high and since a transit thrombus was only present at your follow-up TEE, it suggests that you could have diagnosed PE earlier by assessing his deep veins.\n12. The term \"spiral CT\" is somewhat outdated. I suggest using the description CT pulmonary angiography instead.\n\n13. Which CT-scanner was available at your insitution? Is it possible that the patient suffered from profound peripheral embolization which could be acknowledged by a state-of-the-art apparatus?\n\n14. You state that TEE has a sensitivity of 70% and specificity of 81%. Please elaborate. Is this overall regardless of which sign of RV strain you assess for or does this pertain to RV dilation alone etc.?\n\nOnce again thank you for sending me this case report which I enjoyed reading and found thoroughly interesting.\nI look forward to reading the revised version.\n\nIs the background of the case’s history and progression described in sufficient detail? Partly\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Partly\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Partly\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-879
https://f1000research.com/articles/11-506/v1	09 May 22	{ "type": "Research Article", "title": "Analysis of contact tracing surveillance for COVID-19 among healthcare workers in secondary referral hospital, Indonesia", "authors": [ "Tri Pudy Asmarawati", "Tintin Sukartini", "Ardhena Ekasari", "Devi Rahma Sofia", "Nurul Kamariyah", "Dwiki Novendrianto", "Putri Yuliasari", "Kuswantoro Rusca P", "Joel Rey Acob", "Choirina Windradi", "Bagus Aulia Mahdi", "Okla Sekar Martani", "Esthiningrum Dewi Agustin", "Tri Pudy Asmarawati", "Ardhena Ekasari", "Devi Rahma Sofia", "Nurul Kamariyah", "Dwiki Novendrianto", "Putri Yuliasari", "Kuswantoro Rusca P", "Joel Rey Acob", "Choirina Windradi", "Bagus Aulia Mahdi", "Okla Sekar Martani", "Esthiningrum Dewi Agustin" ], "abstract": "Background: Healthcare workers (HCWs) are more vulnerable to COVID-19 infection. Tracing and screening cases among healthcare workers are essential to overcome the spread of COVID-19. We held surveillance at the second-referral hospital in Surabaya, Indonesia, to inspect the associating factors of infected HCWs. Methods: From 776 HCWs, we conducted a structured retrospective review of all COVID-19-confirmed HCWs and ones having contact with COVID-19 patients between February-July 2021. We associated general characteristics (i.e age, gender, working sites, etc) of the sample with the positive cases, analyzed the vaccination status, then did bivariate and multivariate regression logistic analyses to determine related factors putting HCWs at risk for COVID-19 infection.\n\nResults: Bivariate analysis significantly revealed that 72.86% patients had a close contact (OR = 2.61; p<0.05), with medical staffs as the most frequent source (85.71%; OR = 2.19; p=0.033), for > 15 minutes contact duration (90%; OR = 1.1; p<0.05). Healthcare workers wearing proper PPE (N-95 and face shields) were significantly less exposed to COVID-19 (OR = 0.47; p<0.05; and OR = 0.46; p<0.05). Even fully-vaccinated samples were still prone to infection. (OR=1.25; p= 0.042). Common symptoms consisted of fever, rhinorrhea, sore throat, and vomiting (p=0.025l p=0.002; p<0.05; p=0.002). Multivariate regression logistic analysis disclosed that the use of N95 masks, contact duration >15 minutes, and the vaccine were the most influential factors (aOR = 1.72. 95% CI (1.029-2.88); aOR = 3.92. 95% CI (1.75-8.78); aOR = 0.39. 95% CI (0.13-0.82 )) Conclusions: Close contact, lack of compliance in wearing N95 masks, and unvaccinated status are risk factors for COVID-19 exposure to HCWs; thus, to achieve maximum prevention of intra-hospital transmission, the use of N-95 masks, contact avoidance, and vaccination, along with immediate tracing and strict health-protocols are all compulsory.", "keywords": [ "contact tracing", "infectious diseases", "surveillance", "COVID-19", "healthcare workers" ], "content": "Introduction\n\nCOVID-19 has initiated worldwide outbreak inevitably threatening healthcare workers. High transmission rate of SARS-CoV-2 poses healthcare workers at risk whenever they are in contact with infected patients.1,2 Globally, healthcare workers (HCWs) constitute nearly 7% of all COVID-19 cases.2 A prospective cohort study of a large healthcare worker population in the USA and UK revealed more than three times higher risk of infection amongst HCWs than the general population.3 In developing countries, the more HCWs get infected, the more disrupted health system will be.\n\nSeveral factors, e.g work department in hospital, duration of exposure, and PPE use have been shown to correlate with the risk of COVID-19 transmission.1,4,5 However, many studies have reported the effectiveness of vaccine in reducing the incidence of hospitalized infections. Nevertheless, the SARS-CoV-2 mutation and various antibody put HCWs at risk for breakthrough infection, even after being fully vaccinated.6–8 Therefore, comprehensive contact tracing has become one of the critical strategies by governments to ensure healthcare workers’ and patients’ safety.9\n\nContact tracing is a crucial mechanism for breaking the chain of infectious diseases by identifying, quarantining, and monitoring contacts of infected individuals.10 Contact tracing surveillance ensures detailed information about confirmed and suspected cases in the community. The growth of incidence can be controlled through effective contact tracing. More practical ways are needed to perform the screening and tracing process.11 Digital applications or platforms have an excellent potential in implementing those steps efficiently without direct physical contact with infected individuals.12–14\n\nInfected HCWs commonly complain of fever, cough, shortness of breath, and sore throat. A study in Malaysia on tracing HCWs showed that the prevalence of healthcare workers infected with COVID-19 was around 0.3%.15 In Indonesia, a study by Soebandrio et al. in Jakarta showed that of all 1201 healthcare workers, 7.9% were infected with regular symptoms such as cough, malaise, fever, shore throat, runny nose, and myalgia.16\n\nSince the pandemic is not yet over, we aim to portray the tracing system of COVID-19 staff in one of the teaching hospitals in Indonesia as a preliminary study to develop a mobile-based application as an innovation for the contact tracing process. We inspect and analyze several factors associated with COVID-19-confirmed HCWs.\n\n\nMethods\n\nThis study was conducted in a COVID-19 secondary referral hospital in Surabaya, Universitas Airlangga Hospital, Indonesia. In January 2021, Indonesia was in the middle of the first COVID-19 wave. The incidence declined from February until May and rose again in June-August 2021 as the second wave attacked.17 Data in this study were collected retrospectively from the contact tracing surveillance database during February-June 2021 and associated general characteristics (i.e age, gender, working sites, etc) of the sample with the positive cases, regardless of the vaccination status (complete or incomplete). The database was composed of the online questionnaire filled out by healthcare workers suspected of having COVID-19 exposure during their work and signed informed consent prior to the study. It was developed and modified from a previous study database for specific healthcare workers.18,19 Universitas Airlangga Hospital Ethical Committee had approved this study with the ethical clearance number: 174/KEP/2021.\n\nContact tracing was conducted by the Infection Prevention and Control Team. HCWs exposed to COVID-19-confirmed patients without appropriate personal protective equipment (PPE) were asked to fill in an online questionnaire to determine close contact with a confirmed case. The questionnaire comprised of the name, age, ward unit, date of contact, duration of contact, surrounding environment (indoor or outdoor), the physical distance between staffs, and PPE use. The use of personal protective equipment (PPE) refers to the National Guideline Recommendation.20,21 The criteria for close contact were as follows: 1) If there was contact with the asymptomatic COVID-19 case two days before tested positive; 2) Contact with symptomatic COVID-19 case two days before symptoms appear; 3) Contact duration>15 minutes with a distance of ≤ 1.8 meters without proper PPE. Staff considered to have had close contact underwent quarantine and nasopharyngeal/oropharyngeal swab for SARS-CoV-2 detection (Figure 1).\n\nWorking areas were stratified to: 1) Low risk: green zone (non-COVID-19 ward, management office); 2) Intermediate risk: yellow zone (non-COVID-19 ICU, emergency triage, emergency unit); 3) High risk: red zone (COVID-19 ward and outpatient clinic).\n\nContact tracing data will be shown as descriptive studies, including characteristics of HCWs such as gender, age, unit, and symptoms. We analyzed the data using SPSS version 24 (Chicago. Illinois. USA; RRID: SCR_002865). We analyzed general characteristics, including age, gender, working sites, close contact, contact duration, vaccination status, and other, then correlate them with infected HCWs. To calculate the risk value, we used chi-square in the two-category group. A simple logistic regression test was used to analyze the group of more than two categories. We carried out multivariate logistic regression analysis to see the interaction of factors from the characteristics of the sample, use of PPE, and vaccine status on the risk of COVID-19 infection in health care workers.\n\n\nResults\n\nThere were 75.8% staffs filling out the surveillance form during the second wave which was thrice higher than at the end of the first wave. Sixty percent participants had close contact with infected persons during the second wave (see Table 1).\n\nSeventy staffs were tested positive for COVID-19. Most of them were female, aged between 25-34, and living in Surabaya. Confirmed patients having close contact reached 72.86% (OR = 2.61; p < 0.05) mostly for >15 minutes (90%) (OR = 1.1; p < 0.05) and with medical staff as the most frequent source (85.71%) (OR = 2.19; p = 0.033). Mostly, infected HCWs developed symptoms within 10 days (98.57%). Most of them had shifts in the non-covid ward (42.86%). Risk assessment showed that most of them were at intermediate one (72.86%). Patients with both positive and negative results for COVID-19 had been previously vaccinated (OR = 3.19; p < 0.05). Even confirmed patients mostly had complete doses of COVID-19 vaccines (OR =1.25; p < 0.05) (see Table 2).\n\n† p<0.05.\n\n# Chi-square test.\n\n* Simple logistic regression test.\n\nBelow we present the distribution of personal protective equipment (PPE). HCWs who wore N95 masks and face shields were not likely to be positive (OR = 0.47; p = 0.003 and OR = 0.46; p = 0.025, respectively). On the other hand, patients that did not wear the PPE tended to be positive for COVID-19, although insignificant (see Table 3).\n\n† p < 0.05.\n\nConfirmed patients mostly were symptomatic (62.86%) (OR = 3.92; p < 0.05). They experienced cough (17.14%) (OR = 1.82; p = 0.074), rhinorrea (15%) (OR = 2.56; p = 0.002), fever (10%) (OR = 2.59; p = 0.025), sore throat (32.86%) (OR = 2.9; p < 0.05), and cephalgia (7.14%)(OR = 1.93; p = 0.183). They neither experienced dyspnea nor anosmia. Meanwhile, symptomatic HCWs with negative swab results presented with cough (10.20%), sore throat (14.31%), rhinorrhea (9.63%), and fever (4.11%) (see Table 4).\n\n† p < 0.05.\n\nMultivariat regression logistic analysis for HCWs risk factors showed that the use of N95 masks, contact duration > 15 minutes, and the vaccine was the most influential factor (aOR = 1.72. 95% CI (1.029-2.88); aOR = 3.92. 95% CI (1.75-8.78); aOR = 0.39. 95% CI (0.13-0.82))(see Table 5).\n\n† p<0.05.\n\n\nDiscussion\n\nPneumoniae outbreak caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have caused pneumonia coronavirus disease (COVID-19), which spread rapidly throughout the world.22 SARS-CoV-2 infection can be asymptomatic or cause mild to critical symptom.23 The nature of the spread of the SARS-CoV-2 virus is still unclear, but what can be known is that prevention of its spread is related to demographic dynamics, population attitudes, and preventive measures. The outbreak in the Hunan area brought prevention movements in the form of non-pharmacological measures, restrictions on mobilization, screening of travelers, isolation, contact tracing, and quarantine.24\n\nA study by Yan Ge et al., illustrates that men were found more prevalent to have close contact with COVID-19 patients. Multivariable analysis based on age, sex, duration of contact, and contact setting on the incubation period, a person is more at risk of being infected with COVID-19 after 1-3 days of exposure to symptomatic COVID-19 patient (ARR [adjusted relative risk], 3.4; 95% CI, 1.9-5.8) or day 0 and 2 days after their index patient’s symptom onset (ARR, 2.8; 95% CI, 1.5-5.0). The highest risk occurs both in the home setting and outside the home. Still, in the family cluster, this complaint will manifest 2-3 days after exposure.25\n\nThe common transmission modes are conversation, eating in groups, direct contact in a closed room within close distance, in-hospital care, living together in one house, and sharing a vehicle. Multivariable analysis showed that family members had an ARR of 8.1 (95% CI, 5.9-11.4), contact with the same patient, and an ARR of 6.0 (95% CI, 1.7-21.0) compared to other distribution models such as conversation, sharing vehicles, and being in the same space. HCWs exposed to confirmed patients had lower scores than others but not statistically significant risk of COVID-19 (ARR, 0.4; 95% CI, 0.1-1.7).25\n\nThree retrospective cohort studies evaluated risk factors for the occurrence of COVID-19 in HCWs exposed to COVID-19. Seventy-two exposed people (clinicians and nurses) in Wuhan, China, had acute complaints. The median age of the subjects was 31 years, and 69% of HCWs were female; PCR-confirmed COVID-19 occurred in 38.9% (28 of 72 HCWs). These HCWs worked at high-risk areas (relative risk [RR], 2.13 [CI, 1.45 to 3.95]), poor hand washing before and after patient contact (RR, 3.10 [CI, 1.43 to 3.95]). 6.73] and 2.82 [CI, 1.11 to 7.18], respectively), long working hours (log-rank p = 0.02), and inappropriate use of PPE (RR, 2.82 [CI, 1.11 to 7.18]). Some procedures such as endotracheal tube removal, cardiopulmonary resuscitation, fiberoptic bronchoscopy, and sputum suction are not associated with an increased risk of infection. Infected family members also tend to be the source of transmission for HCWs indicating that transmission can happen outside the hospital as well (RR, 2.76 [CI, 2.02 to 3.77]).26 But our study showed that most of HCWs get infected after having contact with other medical staffs rather than patients, yet multivariate analysis revealed that the risk was not significant.\n\nThe Centers for Disease Control and Prevention (CDC) defines a person as close contact if the face-to-face distance is less than six feet, had contact two days before someone is COVID-19 confirmed, with a total duration of contact for 15 minutes. People who have had close contact are supposed to do the nasopharyngeal swab at least five days after close contact, isolate, and wear a mask as a measure to prevent transmission.27\n\nA meta-analysis study resulted in lower virus spread after applying 1 m distancing between people than < 1 m (n = 10 736, pooled adjusted odds ratio [aOR] 0.18, 95% CI 0.09 to 0.38; risk difference [RD] –10.2%, 95% CI –11.5 to –7.5; moderate certainty); because distance provides protection (change in relative risk [RR] 2.02 per m; interaction p = 0.041; moderate certainty). Face masks provided adequate protection by reducing the risk of infection (n = 2647; aOR 0.15, 95% CI 0.07 to 0.34, RD –14.3%, –15.9 to –10.7; low certainty), with more substantial power on HCWs using N95 or similar respirators than disposable surgical masks (e.g., reusable 12–16-layer cotton masks; p = 0.090; posterior probability >95%, low certainty). Goggle users also benefited from infection protection by reducing the risk of infection (n = 3713; aOR 0.22, 95% CI 0.12 to 0.39, RD –10.6%, 95% CI –12.5 to –7.7; low certainty).28\n\nIn Indonesia, a study from Soebandrio et al. showed that six COVID-19 confirmed HCWs did aerosols procedure, and half of them did not use N95 masks. One of those six cases was hospitalized with pneumonia (16.7%).16 Furthermore, our study disclosed that a lot of HCWs who did not wear any N95 mask, had close contact for duration > 15 minutes tested positive. This finding was supported by multivariate analysis showing its high significance for duration > 15 minute and wear N95 mask.\n\nIn Malaysia, of 1174 HCWs, 17 HCWs were tested positive for COVID-19 (12 HCWs had work-related exposure and 5 HCWs had community exposure–close contact) tested positive for COVID-19 presenting with fever (p < 0.001) and respiratory symptoms–cough (p = 0.003), shortness of breath (p = 0.015) and sore throat (p = 0.002).15\n\nIn Indonesia, the most common clinical findings in infected were cough (61.6%), malaise (52.1%), fever (45.2%), sore throat (45.2%), headache (45.2%), runny nose (30.1%) and muscle pain (30.1%). Further analysis showed that respiratory and extra-pulmonary manifestation could also appear. People in the age group >50 years tend to present with more complains than ones in age group <29 years.16\n\nA study from Atnafie et al. showed that HCWs aged 25–34 years had 80 times lower risk than those aged 18–24 years (aOR = 0.20, 95% CI = 0.041–0.96). HCWs aged 35–44 years had 87 times lower risk than subjects aged 18–24 years (aOR = 0.13, 95% CI = 0.02–0.86). Furthermore, HCWs living in the same house with more than six members are four times more prone to COVID-19 than those with < 3 members (aOR = 3.77, 95% CI = 1.07–13.26). Long working experience increases awareness for COVID-19 infection. HCWs who have worked 21–30 years have a lower risk of infection than those who have only worked for one year (AOR = 0.01, 95% CI = 0.01–0.06).29 Our data showed that the age group of HCWs is not related to the risk of COVID-19 infection.\n\nDuring the Delta wave, of 488 unvaccinated participants wit median follow-up of 43 days (IQR = 37–69 days; total = 24,871 days) 19 people were infected with SARS-CoV-2 (94.7% symptomatic). On the other hand, 2,352 subjects were fully vaccinated during a median follow-up of 49 days (IQR = 35–56 days; total = 119,218 days) and 24 people were infected with SARS-CoV-2 (75.0% symptomatic). Adjusted VE during this wave was 66% (95% CI = 26%–84%) compared to previous period [91% (95% CI = 81%–96%)].30\n\nIn the period of December 14th, 2020–August 14th, 2021, complete vaccination with COVID-19 vaccines was 80% effective in preventing infection among HCWs.30 Soegiarto et al examined total dose inactivated virus vaccination in health workers in Indonesia and disclosed that even fully vaccinated still had a breakthrough infection.8 Our study showed similar result that the vaccined HCWs still have a risk to be infected.\n\nCompilation from our study at a secondary hospital in Surabaya showed that close contact (72.86%; OR = 2.61; p < 0.05), contact source from medical staff (85.71%; OR = 2.19; p = 0.033), and contact duration > 15 minutes (90%; OR = 1.1; p < 0.05) showed significant differences. Similar to previous studies, PPE (N95 and face shields) was evidently found effective in reducing the (OR = 0.47; p < 0.05; and OR = 0.46; p < 0.05, respectively). In the meantime, bivariate analysis determined that both vaccinated HCWs (OR = 3.2; p = 0.001) and fully-vaccinated HCWs (OR = 1.25; p = 0.042) still had the risk of infection. Multivariate regression logistic analysis showed that the use of N95 masks, contact duration >15 minutes, and the vaccination were the most influential factor [aOR = 1.72; 95% CI (1.029-2.88); aOR = 3.92; 95% CI (1.75-8.78); aOR = 0.39. 95% CI (0.13-0.82)].\n\nOur study comes with some limitations. We did the test simultaneously resulting in biased result—positive result in one work area, negative in another. Furthermore, we could not clearly identify the exposures leading to infection as an observational study. Data on PPE use were limited, self-reported, and did not include specifics on each item used (i.e sub-optimal handwash). This study also did not consider family members who also had the infection. Therefore, other factors can be examined in further research.\n\n\nConclusion\n\nOur study shows that close contact with COVID-19 patients, not wearing N95 masks, and not getting vaccinated are risk factors for HCWs to get infected with COVID-19. Therefore, adherence to N-95 masks, close contact avoidance, and complete vaccination are all mandatory. Proper and rapid testing is undoubtedly another key strategy in minimizing the spread of infection.\n\n\nData availability\n\nFigshare: Repository Data of Analysis of Contact Tracing Surveillance for COVID-19 among Healthcare Workers in Secondary Referral Hospital, Indonesia, https://doi.org/10.6084/m9.figshare.19625196.v4.31\n\nFigshare: Repository Data of Analysis of Contact Tracing Surveillance for COVID-19 among Healthcare Workers in Secondary Referral Hospital, Indonesia, https://doi.org/10.6084/m9.figshare.19625196.v4.31\n\nThis project contains the following extended data:\n\n- Research instrument dr. TPD.docx\n\n- dr. TPD - Informed Consent.docx\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgment\n\nWe deliver our gratitude to Universitas Airlangga Hospital for supporting this research.\n\n\nReferences\n\nRosser JI, Tayyar R, Giardina R, et al.: Case-control study evaluating risk factors for SARS-CoV-2 outbreak amongst healthcare personnel at a tertiary care center. Am. J. Infect. Control. 2021; 49(12): 1457–1463. PubMed Abstract \| Publisher Full Text\n\nWan KS, Tok PSK, Yoga Ratnam KK, et al.: Implementation of a COVID-19 surveillance programme for healthcare workers in a teaching hospital in an upper-middle-income country. PLoS One. 2021; 16(4): e0249394. PubMed Abstract \| Publisher Full Text\n\nNguyen LH, Drew DA, Graham MS, et al.: Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Health. 2020; 5(9): e475–e483. PubMed Abstract \| Publisher Full Text\n\nZheng C, Hafezi-Bakhtiari N, Cooper V, et al.: Characteristics and transmission dynamics of COVID-19 in healthcare workers at a London teaching hospital. J. Hosp. Infect. 2020; 106(2): 325–329. PubMed Abstract \| Publisher Full Text\n\nAsmarawati TP, Arifianto MV, Hadi U, et al.: Healthcare Associated COVID-19 Transmission: Strategies to prevent. New Armen. Med. J. 2020; 14.\n\nBergwerk M, Gonen T, Lustig Y, et al.: Covid-19 Breakthrough Infections in Vaccinated Health Care Workers. N. Engl. J. Med. 2021; 385(16): 1474–1484. PubMed Abstract \| Publisher Full Text\n\nBruxvoort KJ, Sy LS, Qian L, et al.: Effectiveness of mRNA-1273 against delta, mu, and other emerging variants of SARS-CoV-2: test negative case-control study. BMJ (Clinical research ed). 2021; 375: e068848. PubMed Abstract \| Publisher Full Text\n\nSoegiarto G, Wulandari L, Purnomosari D, et al.: Hypertension is associated with antibody response and breakthrough infection in health-care workers following vaccination with inactivated SARS-CoV-2. [Observational Study]. In press. 2022. Publisher Full Text\n\nWhitelaw S, Mamas MA, Topol E, et al.: Applications of digital technology in COVID-19 pandemic planning and response. Lancet Digital Health. 2020; 2(8): e435–e440. PubMed Abstract \| Publisher Full Text\n\nBreeher L, Boon A, Hainy C, et al.: A Framework for Sustainable Contact Tracing and Exposure Investigation for Large Health Systems. Mayo Clin. Proc. 2020; 95(7): 1432–1444. PubMed Abstract \| Publisher Full Text\n\nKim R, Nachman S, Fernandes R, et al.: Comparison of COVID-19 infections among healthcare workers and non-healthcare workers. PLoS One. 2020; 15(12): e0241956. PubMed Abstract \| Publisher Full Text\n\nGreiner AL, Angelo KM, McCollum AM, et al.: Addressing contact tracing challenges-critical to halting Ebola virus disease transmission. Int. J. Infect. Dis. 2015; 41: 53–55. PubMed Abstract \| Publisher Full Text\n\nGowda G, Holla R, Ramraj B, et al.: Contact Tracing and Quarantine for Covid 19: Challenges in community surveillance. Indian J. Community Health. 2020; 32(2 (Supp)): 306–308. Publisher Full Text\n\nGarg S, Bhatnagar N, Gangadharan N: A Case for Participatory Disease Surveillance of the COVID-19 Pandemic in India. JMIR Public Health Surveill. 2020; 6(2): e18795. PubMed Abstract \| Publisher Full Text\n\nMoreland NJ, Wan KS, Tok PSK, et al.: Implementation of a COVID-19 surveillance programme for healthcare workers in a teaching hospital in an upper-middle-income country. PLoS One. 2021; 16(4): e0249394. PubMed Abstract \| Publisher Full Text\n\nSoebandrio A, Kusumaningrum T, Yudhaputri FA, et al.: COVID-19 prevalence among healthcare workers in Jakarta and neighbouring areas in Indonesia during early 2020 pandemic. Ann. Med. 2021; 53(1): 1896–1904. PubMed Abstract \| Publisher Full Text\n\nSatgas: Satuan Tugas Penanganan, Covid: Peta Sebaran COVID-19 Januari-Agustus 2021\|Satgas Penanganan COVID-19 2021.Reference Source\n\nAsmarawati TP, Suryantoro SD, Rosyid AN, et al.: Predictive Value of Sequential Organ Failure Assessment (SOFA), Quick Sequential Organ Failure Assessment (qSOFA), Acute Physiology and Chronic Health Evaluation (APACHE II), and New Early Warning Signs (NEWS-2) Scores Estimate Mortality of COVID-19 Patients Requiring Intensive Care Unit (ICU). [Original Article]. In press. 2022.\n\nAsmarawati TP, Rosyid AN, Suryantoro SD, et al.: The clinical impact of bacterial co-infection among moderate, severe and critically ill COVID-19 patients in the second referral hospital in Surabaya. F1000Res. 2021; 10: 113. Publisher Full Text\n\nSatari HI: Petunjuk teknis alat pelindung diri (APD). Direktorat Jendral Pelayanan Kesehatan Kementrian Kesehatan Republik Indonesia.2020; (4).\n\nKemenkes: Petunjuk Resmi Penggunaan APD. Jakarta: Kementerian Kesehatan Republik Indonesia; 2020 April 2020.\n\nZhao H, Lu X, Lun W, et al.: Transmission dynamics of SARS-CoV-2 in a mid-size city of China. BMC Infect. Dis. 2021; 21(1): 793–799. PubMed Abstract \| Publisher Full Text\n\nLauer SA, Grantz KH, Bi Q, et al.: The incubation period of coronavirus disease 2019 (CoVID-19) from publicly reported confirmed cases: Estimation and application. Ann. Intern. Med. 2020; 172(9): 577–582. PubMed Abstract \| Publisher Full Text\n\nSun K, Wang W, Gao L, et al.: Transmission heterogeneities, kinetics, and controllability of SARS-CoV-2. Science (New York, N.Y.). 2021; 371(6526). PubMed Abstract \| Publisher Full Text\n\nGe Y, Martinez L, Sun S, et al.: COVID-19 Transmission Dynamics among Close Contacts of Index Patients with COVID-19: A Population-Based Cohort Study in Zhejiang Province, China. JAMA Intern. Med. 2021; 181(10): 1343–1350. PubMed Abstract \| Publisher Full Text\n\nChou R, Dana T, Buckley DI, et al.: Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers; A Living Rapid Review. Ann. Intern. Med. 2020; 173(2): 120–136. PubMed Abstract \| Publisher Full Text\n\nCDC: How to Determine a Close Contact for COVID-19. CDC; 2022.\n\nChu DK, Akl EA, Duda S, et al.: Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet. 2020; 395(10242): 1973–1987. Publisher Full Text\n\nAtnafie SA, Anteneh DA, Yimenu DK, et al.: Assessment of exposure risks to COVID-19 among frontline health care workers in Amhara Region, Ethiopia: A cross-sectional survey. PLoS One. 2021; 16(4 April): e0251000–e0251014. PubMed Abstract \| Publisher Full Text\n\nFowlkes A, Gaglani M, Groover K, et al.: Effectiveness of COVID-19 Vaccines in Preventing SARS-CoV-2 Infection Among Frontline Workers Before and During B.1.617.2 (Delta) Variant Predominance — Eight U.S. Locations, December 2020-August 2021. MMWR Recomm. Rep. 2021; 70(34): 1167–1169. PubMed Abstract \| Publisher Full Text\n\nAsmarawati TP, Sukartini T, Ekasari A, et al.: Repository Data of Analysis of Contact Tracing Surveillance for COVID-19 among Healthcare Workers in Secondary Referral Hospital, Indonesia. figshare. [Dataset].2022. Publisher Full Text" }	[ { "id": "140548", "date": "28 Jun 2022", "name": "Pasquale Stefanizzi", "expertise": [ "Reviewer Expertise Vaccine", "epidemiology", "infectious disease" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis research presents key elements and reduces ambiguities in current healthcare infection's risk evaluation and impact of tracing activity. This draft does not completely deliver on these dimensions, and requires minor revisions to achieve its intended purpose. The goal of the study is represented by the mobile-based application used to link between COVID19 diagnosis and healthcare workers risk factor.\nIntroduction: Authors correctly express the general concept of tracing and screening cases among healthcare workers and the importance of protecting healthcare workers to protect frail patients. It's useful to add a comparison with a European hospital in line 7 e.g. (Vimercati L, De Maria L, Quarato M, Caputi A, et al. 2021)1\n\nThe study was carried out in the period February-July 2021 - so the benefit of vaccination in reducing the incidence of COVID19 in this period can be reported; so I suggest comparison with the impact of the HW vaccination in an Italian hospital in the same period (line 8) - e.g. (Stefanizzi P, Martinelli A, Ferorelli D, Soldano S, et al. 2021)2. You could try to estimate the effectiveness of vaccine in your sample.\n\nMethods and results: it's a retrospective study and the database was composed of the online questionnaire; the analysis aims to evaluate distribution and risk factors of COVID-19 exposure. Information bias probably are reported in database.\n\nData of quarantine (how long) can be further clarified. Probably the average and median time interval between contact and reporting symptoms can be reported\n\nAuthors correctly underline the limits of that study that affected the quality of final results (family members, contacts outside the workplace, use of DPI); also the limits of contact tracing in epidemic control can be discussed in the last paragraph of the discussion - this article can be an important comparison - (Piasecki T, Mucha PB, Rosińska M. 2021)3\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-506
https://f1000research.com/articles/10-1238/v1	03 Dec 21	{ "type": "Opinion Article", "title": "Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR", "authors": [ "Robert M. Waterhouse", "Anne-Françoise Adam-Blondon", "Donat Agosti", "Petr Baldrian", "Bachir Balech", "Erwan Corre", "Robert P. Davey", "Henrik Lantz", "Graziano Pesole", "Christian Quast", "Frank Oliver Glöckner", "Niels Raes", "Anna Sandionigi", "Monica Santamaria", "Wouter Addink", "Jiri Vohradsky", "Amandine Nunes-Jorge", "Nils Peder Willassen", "Jerry Lanfear", "Robert M. Waterhouse", "Anne-Françoise Adam-Blondon", "Donat Agosti", "Petr Baldrian", "Bachir Balech", "Erwan Corre", "Robert P. Davey", "Henrik Lantz", "Graziano Pesole", "Christian Quast", "Frank Oliver Glöckner", "Niels Raes", "Anna Sandionigi", "Monica Santamaria", "Wouter Addink", "Jiri Vohradsky", "Amandine Nunes-Jorge", "Nils Peder Willassen" ], "abstract": "Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth’s biodiversity.", "keywords": [ "Bioinformatics", "Genomics", "Sequencing", "Data Management", "Data Standards", "Genetic Resources", "Taxonomy" ], "content": "Introduction\n\nBiological diversity represents the full spectrum of the variety of organisms on Earth, at genetic, species, and ecosystem levels, created over millions of years of evolution. Biodiversity is also essential for life itself, for the sustainability of varied communities of interdependent and interacting species at all scales. Anthropocentrically, biodiversity forms the foundation of ecosystem services that are indispensable for human well-being and a healthy planet. Whilst biodiversity is naturally constantly changing, increasingly unsustainable pressures resulting from human activities mean that this variety is currently being lost like never before. Recognising the threat to humanity that this decline poses, governments and international organisations have responded with strategies to protect and restore biodiversity, such as the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES 2021). These and other initiatives also recognise the important roles that genetic and genomic data can play in biodiversity assessment, monitoring, conservation, and restoration, to ensure the long-term health of ecosystem services (Hoban et al. 2020). This requires infrastructures that make it easier for scientists to exchange knowledge and agree on best practices, as well as to find, share, and connect increasingly large and diverse datasets. As an intergovernmental organisation that develops services and technical solutions to integrate and coordinate life science resources from across Europe, ELIXIR recognises that connecting molecular sequence data with biodiversity research infrastructures will be critical to support global efforts to prevent further declines of biodiversity.\n\nBiodiversity sequencing and research infrastructure initiatives\n\nOne of the aims of biodiversity research infrastructures is to compile and maintain comprehensive lists of all known species of organisms including their spatio-temporal distributions on Earth, normally within a taxonomic framework and usually with additional associated metadata. Prominent examples that bring together information from multiple sources include the Catalogue of Life (CoL) (Roskov et al. 2020), the Global Biodiversity Information Facility (GBIF 2021), the Environmental Research Infrastructures Community (ENVRI 2021), the Ocean Biodiversity Information System (OBIS 2021), the Encyclopedia of Life (Parr et al. 2014), and the Distributed System of Scientific Collections (DiSSCo 2021). For example, GBIF aims to map diversity in space and time based on natural science collection records, sequence data, biodiversity surveys, human and machine observations, and species lists. The taxonomic frameworks are built from sources of published records such as the Biodiversity Heritage Library and the Biodiversity Literature Repository (BLR), with ongoing efforts to standardise data and make them machine readable and citable (Agosti & Egloff 2009; Penev et al. 2012; Bénichou et al. 2019). Biodiversity research infrastructures also encompass biobanks (genebanks or seed banks) for conserving genetic resources, of major crops and their wild relatives e.g. collated by Genesys (Genesys 2021), of livestock breeds managed by the Domestic Animal Diversity Information System (DAD-IS 2021), or of microbes in the context of food and agriculture or health e.g. managed by the Microbial Resource Research Infrastructure (MIRRI 2021).\n\nMolecular data collection initiatives are equally as varied, aiming to collate growing amounts of DNA and RNA sequence data, often also employing a taxonomic framework and collecting sample metadata. Notable examples include the principally archival International Nucleotide Sequence Database Collaboration (INSDC) (Arita et al. 2021) comprising the DNA DataBank of Japan (DDBJ), the European Nucleotide Archive (ENA), and the United States National Center for Biotechnology Information (NCBI) GenBank, as well as the China National GeneBank DataBase (Wang et al. 2019). More specialised initiatives focus on e.g. ribosomal RNA collections (Glöckner et al. 2017; Santamaria et al. 2018; Nilsson et al. 2019), microbiome resources (Mitchell et al. 2020), or metagenomics sequence data (Meyer et al. 2019).\n\nThese examples help to formulate more formal definitions: (i) molecular sequence data collection initiatives are producing and collating reference catalogues of genetic and genomic biodiversity on Earth; and (ii) biodiversity research infrastructures are capturing knowledge from scientific collections, observations, and the literature, and building resources of biodiversity information for all Earth’s organisms. Here we identify opportunities to connect these biodiversity sequence collection initiatives and research infrastructures in a standardised and scalable manner that will greatly enhance the utility of both by facilitating data-to-knowledge research.\n\nExpanding collections of molecular sequence data\n\nNew technologies and falling sequencing costs are greatly improving the diversity of species sampling through the acquisition of increasing amounts of molecular data. This has led to a growing number of large-scale sequencing data generation initiatives with increasingly ambitious sampling aims covering eukaryotes, prokaryotes, and viruses (Table 1). For example, the Earth BioGenome Project (EBP 2021) aims to coordinate the sequencing and characterisation of the genomes of all eukaryotic life, with a vision of creating a new foundation for biology that will deliver solutions for understanding ecosystems, protecting biodiversity, and benefiting human welfare (Lewin et al. 2018). This involves developing and agreeing on standards for all protocols from specimen collection and identification through to sequencing, assembly, annotation, and analysis. Initiatives are typically geographically or taxonomically focused, such as the Darwin Tree of Life (DToL 2021) project in Britain and Ireland, The European Reference Genome Atlas initiative (ERGA 2021), the Vertebrate Genomes Project (VGP) (Rhie et al. 2020), the i5k Arthropod Genomes Initiative (i5K Consortium 2013), the 10KP Plant Genomes Project (Cheng et al. 2018), and others (Table 1).\n\nA non-exhaustive list of active international projects and umbrella initiatives covering many species and producing (meta) genomes, (meta) transcriptomes, and/or DNA barcodes, with public data deposition.\n\nMicrobe-focused sequencing initiatives benefit from much smaller genomes, but this is countered by orders of magnitude greater species diversity, most of which remains uncatalogued. Pioneering efforts such as the Genomic Encyclopedia of Bacteria and Archaea (GEBA) aim to systematically fill gaps in the phylogeny and to sequence type strains (Whitman et al. 2015; Mukherjee et al. 2017). Others apply metagenomics approaches and are driven more by ecosystem ecology than phylogeny, including the Earth Microbiome Project (EMP) (Gilbert et al. 2014), Tara Oceans (Sunagawa et al. 2020) and other marine surveying projects. Many are driven by the impacts of microbes on human health, e.g. the Global Microbial Identifier (GMI) consortium (Aarestrup et al. 2012) collates genomic information of microorganisms linked to epidemiological data for bacteria, viruses, parasites, and fungi, and the Human Microbiome Project that focuses on host-microbiome interactions (iHMP Research Network Consortium 2019). Similarly, the Global Virome Project aims to improve understanding of the diversity and ecology of viral threats (Carroll et al. 2018).\n\nIn addition to reference genomes, collections of sequence data are growing through DNA barcoding initiatives that define standardised molecular marker(s) for species identification, e.g. cytochrome c oxidase I (COX1) for metazoans, internal transcribed spacer (ITS) for fungi, 16S rRNA for bacteria, and ribulose-1,5-bisphosphate carboxylase/oxygenase (rbcL), maturase K (matK), and ITS for plants. The main reference libraries include the Barcode of Life Data (BOLD) System (Ratnasingham & Hebert 2007) and the International Barcode of Life (iBOL) (Adamowicz et al. 2017). Ongoing barcoding efforts, such as the iBOL consortium’s BIOSCAN programme (Hobern 2020), continue to expand molecular sequence data collection to speed up species discovery as well as exploring species interactions and tracking their dynamics. Together, these sequence data generation initiatives aim to produce molecular catalogues with associated metadata of the entirety of Earth’s biodiversity.\n\nMetadata standards requirements for use in biodiversity research\n\nMany sequencing initiatives have and will continue to produce molecular data in the form of reference-quality genomes, complete transcriptomes, and lineage-tailored DNA barcode libraries. In terms of tangible outcomes for biodiversity knowledge, these data represent a rapidly growing comprehensive molecular ‘lookup table’ for species identification. To ensure accuracy, species must be correctly identified and recorded during sample collection and referenced to a taxonomic backbone (e.g. NCBI or GBIF), with subsequent management of reference or voucher information, and publishing with the respective voucher and taxon identifiers. To this end, sample vouchering experience from museums such as the Smithsonian has been vital in driving standards development through collaborative initiatives such as the Global Genome Biodiversity Network (GGBN) (Droege et al. 2016). These efforts helped to extend data models for classical specimens, e.g. Darwin Core (Wieczorek et al. 2012) and Access to Biological Collections Data (ABCD) (Holetschek et al. 2012), in order to build a new data model for molecular sequence data. One of the key roles of initiatives like the Earth BioGenome Project and others (Table 1) is to coordinate the development of protocols and standards for sample collection and metadata capture in line with such data models, building on established reporting standards that aim to make genomic data discoverable, e.g. developed by the genomic standards consortium (Field et al. 2014).\n\nIn the context of infraspecific diversity conserved in plant, forest, and animal genetic resources, several projects are developing common recommendations and metadata standards to improve the conservation and sustainable use of these resources, e.g. GenRes Bridge (GenResBridge 2021), DivSeek (DivSeek 2021), and FAANG (FAANG 2021). Metagenomics projects also recognise the importance of developing data standards for describing essential steps, including sampling, sequencing, data analysis, archiving, and dissemination (ten Hoopen et al. 2017). Across the board, tools that make metadata management easier, such as the COPO platform for brokering collaborative open omics data (Shaw et al. 2020), are helping to ensure that data are increasingly Findable, Accessible, Interoperable, and Reusable (FAIR) (Wilkinson et al. 2016). These examples highlight the challenges involved as well as the importance of developing and applying community standards to comprehensively describe the sources of molecular sequence data collections. Good metadata management is critical to enable biorepositories to collect and preserve Earth’s genetic and genomic biodiversity in molecular sequence collections, while making it both available to and usable by researchers worldwide.\n\nBenefits of connecting sequencing data to biodiversity research infrastructures\n\nData management frameworks aim to connect data generation initiatives to biodiversity research infrastructures in order to accelerate and expand the capabilities of existing species quantification and monitoring efforts. To achieve a unified global record of species populations in space and time, two principal Essential Biodiversity Variables (EBVs), species abundance and distribution, are required (Jetz et al. 2019). To detect critical and potentially long-lasting biodiversity change, additional EBVs need to be prioritised such as allelic diversity, survival rates, ecosystem heterogeneity, phenology, range dynamics, size at first reproduction, and body mass index (Schmeller et al. 2018; Kissling et al. 2018). Taxonomically annotated molecular catalogues of Earth’s biodiversity provide the means to scale up data collection of species and community EBVs that can be extrapolated from sequencing georeferenced samples. DNA barcoding has proven to be a cost-effective way of providing a model for integrating genomic data resources and biodiversity catalogues. For example, connecting GBIF with the UNITE database, a fungi-focused DNA barcoding resource (Nilsson et al. 2019), enables spatial and temporal surveying even for ‘dark taxa’ without any physical specimens or resolved taxonomic names (Ryberg & Nilsson 2018). Another example is the DNA barcode reference library of Canadian invertebrate fauna, which is supported by voucher specimens, digital images, and DNA extracts, with sequences deposited at GenBank and BOLD, and specimen data contributed to GBIF as Darwin Core records (deWaard et al. 2019).\n\nBeyond barcodes, employing the MGnify resource (Mitchell et al. 2020) to perform taxonomic assignments of microbiome sequencing data, the European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) and GBIF teamed up to facilitate the generation of sequence-based occurrence records from georeferenced European Nucleotide Archive (ENA) samples as standardised Darwin Core sampling-event datasets (Schigel et al. 2019). Facilitating these processes is important to ensure that DNA-derived data are made discoverable through biodiversity platforms and thus increase the value of sequences with associated coordinates and timestamps (Andersson et al. 2020). These examples show that making such connections can (i) extend traditional sampling methods of observing, capturing, or extracting, to massively scaled-up sampling using metagenomics or environmental DNA (eDNA) techniques; and (ii) transform traditional expert identification approaches into super-fast molecular species identification using progressively more comprehensive reference sequence databases. To realise these benefits, the future will therefore increasingly need to combine new sequencing technologies and bioinformatics data models for molecular sequence data management with field ecology to match metagenomics or eDNA data to reference genomic species libraries.\n\nMutually beneficial outcomes for sequence collections and biodiversity infrastructures\n\nFor biodiversity research to exploit the full value of data from molecular sequence collection initiatives, it is clear that robust and reproducible approaches to data integration are required. Ongoing efforts to coordinate traditional biodiversity infrastructures exemplify how developing common standards and practices enhance interoperability and value. For example, the DiSSCo research infrastructure works towards the digital unification of all European natural science collections (DiSSCo 2021), and the Consortium of European Taxonomic Facilities (CETAF 2021) brings together collections from museums, botanic gardens, and others, with a research focus on taxonomy and systematic biology. Such digitalisation and standardisation greatly facilitate the task of connecting sequence collections and biodiversity research infrastructures, exemplified by recent GBIF-UNITE and GBIF-EBI collaborations (Andersson et al. 2020).\n\nAs well as accelerating and expanding the capabilities of existing biodiversity quantification and monitoring efforts, molecular data can support biodiversity research more widely. For example, by helping to extend, refine, and update catalogues of known species, particularly for microbes and fungi but also other groups such as insects where possibly 80% of species remain to be discovered (Stork 2018), known as ‘dark’ biodiversity. Reciprocally, traditional biodiversity data and resources can help inform detailed annotations of sequence collections, linking data to knowledge about species biology and ecosystem compositions. One way this corpus of data from an estimated 500 million scholarly publications including all known species and their taxonomy, can be made FAIR-compliant is through the BLR (Agosti et al. 2019) and its reuse by GBIF. Thus by making the connections, decades of accumulated learning can transform into new and refined knowledge supported by molecular data, greatly advancing data-to-knowledge research.\n\nHere we outline current technical capabilities with respect to the tools and other resources that support the molecular components of biodiversity informatics, and present four use case examples focused on (i) sequence-informed taxonomies; (ii) ocean metagenomics; (iii) agricultural food security genetics; and (iv) global fungal diversity. These illustrate current efforts and resources to link sequence collections with biodiversity infrastructures. They inform strategies for developing national biodiversity programmes, while also highlighting key gaps that need to be addressed. Together with other examples, they help to formulate recommendations for closer integrations through ELIXIR and other infrastructures that will shape the future of biodiversity research.\n\nELIXIR is an intergovernmental European organisation that brings together life science resources including databases, software tools, training materials, cloud storage and supercomputers, to connect and unite infrastructures vital for scientific research (ELIXIR 2021a). It coordinates, integrates, and sustains bioinformatics resources across its member states, enabling users in academia and industry to access services that support scientists to exchange expertise and develop best practices, as well as to find and share the accumulating volumes of data being generated by publicly funded research. ELIXIR services (i.e. resources for users), platforms (i.e. technical domains for implementation), and communities (i.e. use cases) aim to develop and provide solutions to manage life sciences data of increasing quantity and complexity, with robust bioinformatics infrastructures and the best tools and training to drive innovation. These principles also apply to the growing field of biodiversity informatics, and it is thus timely to begin to identify the key life sciences resources, from both within the established ELIXIR infrastructures and beyond, which are required to effectively support biodiversity research. This includes the acquisition, analysis, and archival of molecular sequence data, and their integration with other biodiversity-related data and resources.\n\nAs this is a rapidly moving field, rather than listing these resources in a static table herein, we provide a contextualised list on the ELIXIR services website: https://elixir-europe.org/services/biodiversity. Over time, this portfolio of biodiversity informatics resources and services will be reviewed and extended to reflect the status quo, bringing visibility to existing infrastructures as well as stimulating initiatives to address key gaps and improve integration. Many demonstrate how ELIXIR already acts as an infrastructure to support the integration of molecular and other biodiversity-related data, as elaborated in the four different use cases detailed below. The current range of identified resources includes those that enable deposition and archival of molecular data as well as facilitating access to and retrieval of biodiversity-relevant data. This extends to software, workflows, and computing resources for data analysis, for improving data interoperability, and for using molecular data to address key questions in biodiversity. It incorporates access to training for researchers coming from diverse backgrounds, and advocates FAIR data principles of findability, accessibility, interoperability, and reusability as a cornerstone of any infrastructure that supports the integration of molecular and other biodiversity-related data.\n\nIn addition, wider assistance and guidance to help with Life Science data management, can also be found in the ELIXIR Research Data Management Kit (RDMkit 2021), an online guide containing good data management practices applicable to research projects from the beginning to the end.\n\n\nUse cases: Integrating sequence collections and biodiversity infrastructures\n\nHere we describe four use cases that demonstrate how biodiversity-relevant bioinformatics resources are being used to connect and integrate sequencing data with biodiversity-related research infrastructures to enhance interoperability and value. The use cases cover a broad spectrum with a common theme of showing examples of how these tools and other resources are used in order to process, analyse, and archive molecular sequencing data, within the broader context of biodiversity-related data generation and research. Use case 1 examines taxonomies, the key roles they play in biodiversity research, and the interdependence of molecular data and taxonomic references. Use case 2 turns to metagenomics data and the exploration of the hidden diversity of the world’s oceans. Use case 3 highlights genetics and genomics resources and initiatives for food security and agriculture. Finally, use case 4 details efforts to describe and understand the patterns of global distributions and diversity of fungi using molecular data. Although by no means exhaustive, these use cases provide clear examples of key life science tools and resources supporting biodiversity informatics through the integration of molecular and other biodiversity-related data to facilitate global efforts to protect and restore biodiversity.\n\nCreating a comprehensive taxonomy linked with unique taxonomic identifiers (taxIDs) concerns mainly an efficient interoperability function in molecular biodiversity studies such as DNA barcoding and metabarcoding, phylogeny inference, genomics, and data retrieval. Occurrence and taxonomic data such as those present in the GBIF taxonomic backbone (Figure 1a) provide the opportunity to summarise the geographical distribution of included taxa and more recently the described taxa supplied by BLR (Agosti et al. 2019). However, such data are not necessarily linked to unique taxIDs across repositories and might include several synonyms that also remain unlinked. The same issue can be encountered in the CoL (Roskov et al. 2020) resource where the most recent recognised taxonomy, when covered, is reported (Figure 1b). It is important to note that not all these taxonomic entries have associated molecular sequence data where many of them originate from classical biodiversity studies. In this context, while seeking a new experimental design for molecular characterisation of specific organisms, the absence of unique identifiers (i.e. taxIDs) represents an important issue in collecting the most comprehensive information related to the organisms of interest. This may be due to several reasons including the presence of synonymous names, taxa with the same scientific names but with different taxonomic classifications, the splitting of well-established species leading to the nomination of new and different taxa, e.g. European Grass Snake (Kindler et al. 2017), or evidence-based renaming of species, such as the fungus that causes ash dieback (Baral et al. 2014), requiring additional needed legacy information to track the recent changes in taxonomic classifications and link them efficiently to a reference taxonomy.\n\nA schematic representation of the primary molecular and taxonomy data resources illustrating how they are interconnected to support the development of comprehensive taxonomies linked with unique taxonomic identifiers (taxID). Specifically, each NCBI taxID is associated with a molecular sequence in (a) the NCBI and ENA primary databases which feed (b) the GBIF taxonomy backbone. (c) CoL informs both the NCBI taxonomy and GBIF with new or updated taxa names taking information from third party specialised resources. Finally, (d) literature data are used to extract taxonomic names and treatments to enhance and update NCBI taxonomy, GBIF and CoL through the Biodiversity Literature Repository and TreatmentBank. ‘XX’ indicates taxon or other specialised resources. Lines with arrows indicate data sharing efforts. Dashed lines with red arrows indicate that only a part of data is shared with the destination resources. Blue boxes highlight machine annotation and yellow boxes indicate human curation. NCBI, United States National Center for Biotechnology Information; ENA, European Nucleotide Archive; GBIF, Global Biodiversity Information Facility; CoL, Catalogue of Life.\n\nThe NCBI taxonomy database (Federhen 2012; Schoch et al. 2020) offers well-structured taxonomic classification reports in which ‘synonyms’ and ‘equivalent names’ are linked to the unique taxID of the main taxon scientific name (Figure 1a). In particular, the release of February 10th 2021 contains 179,314 declared synonyms and 1,180 scientific names with more than one taxonomic path or rank. For instance, Diplura is the scientific name of both order and genus ranks, Centipeda is a genus name belonging to plants and firmicutes, and Taenidia is a Coleoptera subgenus and a genus name belonging to plants. As noted above, the lack of molecular sequence data for many established taxa means that they currently have no corresponding NCBI taxIDs. This represents the gap between the NCBI taxonomy and other repositories or backbones such as CoL and GBIF (Figure 1b and c). In addition, other molecular sequence collections, such as BOLD, contain entries with related taxonomic information sometimes not yet incorporated into the NCBI taxonomy and consequently lacking unique NCBI taxIDs.\n\nAn important way to enhance the completeness of the taxonomy information is to merge and harmonise such information coming from different sources. A good example in this context is the EukMap platform developed within the UniEuk project (Berney et al. 2017). It is an open-source software currently oriented to protist taxonomy management, but it can be deployed by other communities adapting it to their needs. The platform adopts an online open collaboration concept for expert driven curation able to link state-of-the-art phylogeny-based taxonomy with genetic information. As such, taxonomists are encouraged to propose updates or corrections to the taxonomy using the platform. Proposals are then validated by community experts to feed into the official release of the UniEuk taxonomic framework with the goal of pushing these changes to the common taxonomy resources such as the NCBI (Schoch et al. 2020) and SILVA (Quast et al. 2012).\n\nMore generally, a solution for taxonomic name integration is included in the published literature (Figure 1d). All these names including their history are documented in the huge, daily growing corpus of highly structured taxonomic literature, comprising well over 100M pages of printed or more recently electronically published literature, dating back to the origin of modern taxonomy in 1753 and 1758 for plants and animals respectively (Linné & Salvius 1753, 1758). Each taxonomic name is accompanied by a taxonomic treatment with a description and/or diagnosis, notes on behaviour, distribution, vernacular names, and citations of previous treatments or synonyms. The latter functions not only similar to a bibliographic citation for articles, for which a Digital Object Identifier (DOI) can be mined, but can also be typed, for example by creating a synonym (see e.g. the original description of the honey bee Apis mellifera by Linnaeus (Linnaeus 1758). In this last issue, text mining techniques would play an important role in collecting the relevant information from scientific literature to update the knowledge needed to resolve such ambiguity. For example, Plazi (Plazi 2021) extracted over 370,000 taxonomic treatments and data therein including taxonomic treatment citations (Miller et al. 2015). These data are FAIR and reused by GBIF and accessible through Plazi’s application Synospecies, providing access to the taxonomic names and synonyms as linked open data. They are also submitted once a day to NCBI, albeit only data covering organisms already present in the database, and thus morphological based species without molecular sequence depositions are discarded.\n\nAn additional source of information on taxon names used in scientific publications falls outside taxonomic treatments, such as linked supplementary data tables (e.g. listing all sequenced specimens with their corresponding taxonomic names and accession numbers), or a list of species or molecular taxonomic units identified from a metabarcoding survey (Figure 1d). Clearly the advantages of having access to the taxonomic treatments and to the structured data tables embedded in the scientific papers, as this allows understanding the reasoning for creating a new species name or synonym, are numerous. This also provides access to cited specimens, permits the discovery of advanced species/taxa interactions such as viral hosts or plant pollinators, and promotes the development of a harmonised and complete list of taxonomic names tagged by unique taxIDs.\n\nBiodiversity data derived from marine metagenomics datasets have grown substantially during the last years and can serve as an excellent example of how molecular sequence data have expanded the insight and understanding of microbial biodiversity in the marine environment. Before the establishment of ELIXIR (Harrow et al. 2021) and the Marine Metagenomics Community (MMC 2021), there was a lack of standards on how to process the data and deposit metagenomic and metagenomic-derived data into appropriate databases. As one of the first steps to address these gaps, the MMC published best practices (ten Hoopen et al. 2017) that served as a foundation for a community standard to enable reproducibility and better sharing of metagenomic data along with comprehensive sampling metadata. As a part of the work, the community built and benchmarked analysis pipelines, established domain-specific reference databases and established better procedures for deposition of metagenomic data.\n\nAn example project that has been very successful in using molecular sequence data to inform and enrich our understanding of biodiversity is the work undertaken by the Tara Ocean Foundation (TARA 2021). Within this project, several major studies have been undertaken since 2009 using molecular sequencing techniques to characterise the life of the world’s oceans. Tara Oceans has advanced our knowledge of all microbial kingdoms of life present in the ocean, from bacteria to small eukaryotes, as well as viruses (e.g. 150,000 eukaryotic taxa in the epipelagic ocean at 90% unknown, nearly 200,000 new double-stranded DNA viruses). The approach uses meta-barcoding, metagenomic and meta-transcriptomic data sequencing (Sunagawa et al. 2020) to generate large numbers of raw sequence reads derived from organisms present in water samples. The Ocean Gene Atlas (Villar et al. 2018) is a web service to explore the biogeography of marine genes (Figure 2) based on sequence similarities and consists of the Tara Ocean Microbiome - Reference Gene Catalog database (OM-RGC) and the Marine Atlas of Tara Ocean Unigenes (MATOU) (Sunagawa et al. 2015; Tara Oceans Coordinators et al. 2018). The OM-RGC contains 46 million bacterial/archaeal genes, generated from metagenome raw data, while MATOU contains 117 million eukaryotic genes, generated from the metatranscriptome raw data. The raw data from Tara Oceans has also been submitted to MGnify - a free to use resource for analysis, visualisation and discovery of metagenomic, metatranscriptomic, amplicon and assembly datasets (Mitchell et al. 2020). Approximately 1,300 samples in eight studies have so far been analysed in MGnify, including 370 metatranscriptome and metagenome samples. Of these, 1,189 amplicon events have been registered in GBIF, giving rise to more than 750,000 biogeography occurrences (GBIF 2018). The sequence datasets analysed in MGnify are stored in the European Nucleotide Archive (ENA) and re-used in other marine reference databases such as METdb, a genomic reference database dedicated to micro-eukaryotic species, containing 348 organisms and 463 strains of micro-eukaryotic species derived from transcriptome sequence data (Niang et al. 2020).\n\nA simplified flowchart of the processing steps of information from the Tara Oceans datasets (metagenomics, metatranscriptomics, and amplicons) to integrate data with primary and secondary resources and other biodiversity platforms as GBIF and WoRMS. Processing of sequence data from oceanic water samples using informatics tools and services connects them with taxonomic information and links them to knowledge about species biology and ecosystem variables. PR2, pr2-primers: an 18S rRNA primer database for protists; SILVA, an on-line resource for quality checked and aligned ribosomal RNA sequence data; ITSoneDB, a collection of eukaryotic ribosomal RNA Internal Transcribed Spacer 1 (ITS1) sequences; UniProt, the universal protein resource of sequence and functional information; ENA, European Nucleotide Archive; MGnify, the microbiome analysis resource; OGA, Ocean Gene Atlas; OBA, Ocean Barcode Atlas; GBIF, Global Biodiversity Information Facility; WoRMS, the World Register of Marine Species; MetDB, a genomic reference database for marine species; MAR databases, a collection of richly annotated and manually curated contextual and sequence resources for marine species.\n\nThe metagenome-assembled genomes (MAGs) generated from analyses of shotgun sequenced samples in MGnify have been included in the MAR databases (Klemetsen et al. 2018), a collection of richly annotated and manually curated contextual (metadata) and sequence databases for marine prokaryote species. Context is captured through ensuring compliance with the Genomic Standards Consortium (Field et al. 2014) recommendations for Minimum Information about any (x) Sequence (MIxS) standards, an overarching framework of sequence metadata (Yilmaz et al. 2011). These resources are accessible through the Marine Metagenomics Portal (MMP 2021), with the MarRef containing nearly 1,000 complete microbial genomes, and MarDB hosting more than 13,000 non-complete genomes. The MAR database entries are cross-referenced with ENA and the World Register of Marine Species (WoRMS) (Vandepitte et al. 2018) records to ease the access to additional and curated metadata. The data from the Tara Oceans project also provides links to several other databases such as UniProt (The UniProt Consortium 2019), a high-quality curated database of protein sequences and functional information, SILVA (Quast et al. 2012), a database for ribosomal RNA (rRNA) genes used for phylogenetic reconstruction, PR2 (Vaulot et al. 2021) a reference database of 18S rRNA protist sequences carefully curated by experts from each taxonomic group in the context of EukRef project, and ITSoneDB (Santamaria et al. 2018), a specialised collection of ribosomal RNA Internal Transcribed Spacer 1 (ITS1) sequences aimed at the taxonomic identification of eukaryotes. The Ocean Barcode Atlas (OBA) is a web service designed to explore the biodiversity and biogeography of marine organisms at planetary scale for Tara Oceans and other marine metabarcode datasets (Vernette et al. 2021).\n\nFigure 2 illustrates how raw environmental sequence data derived from oceanic water samples are processed, annotated, and re-used, applying informatics tools and services to connect them with taxonomic information that helps link the data to knowledge about species biology and ecosystem variables. These sequence datasets therefore serve as a measure to determine diversity and abundance in a specific habitat, provide a means to quantify declines in biodiversity and climate change, and allow for efficient comparisons of datasets, e.g. time-series experiments, in environmental or species monitoring programmes.\n\nOther large-scale projects to analyse ocean biodiversity have also been undertaken in recent years, including the Malaspina expedition (Duarte 2015), Ocean Sampling Day initiatives (Kopf et al. 2015), the Antarctic Circumnavigation Expedition (ACE 2021), and the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition (MOSAiC 2021). On the one hand, the large and growing variety of observations taken during oceanic sampling (Gorsky et al. 2019) have posed many data management challenges. On the other hand, facing these challenges means that the field of marine metagenomics has paved the way towards better capturing, processing, and managing of samples and their metadata. In parallel to these studies addressing diversity issues at the global ocean scale, smaller spatial scale studies addressing temporality issues have emerged (including classical diversity data, genomic data, and imaging data) on enhanced marine genomic observatories (Bourlat et al. 2013; Davies et al. 2014). More generally, increasingly integrative approaches to diversity analysis are now favoured by the marine research community (Canonico et al. 2019; Collins et al. 2020). Although marine metagenomics is relatively mature as a field, there are still many issues that need attention. There is a need to implement standardised procedures for processing and analysing datasets, including best practices for assembly, binning and annotation. Furthermore, the quality of reference databases, integration of new omics data, specific data warehouses, and long-term data management services are issues that warrant careful attention, e.g. in the context of moving from biodiversity snapshots to large-scale monitoring and discovery.\n\nAdaptation of agriculture has been based on fitting crop varieties and breeds to their production system, which includes farming systems and their natural environments. This has led after initial domestication to the development of a large diversity of varieties and breeds adapted to local farming conditions but also to diverse usage and consumer demands. With the specialisation and industrialisation of production systems after the Second World War, this high intraspecific diversity has started to decline all over the world and is now threatened in many cases (Pilling, Bélanger & Hoffmann 2020b). Important initiatives to catalogue and conserve this diversity in large ex situ collections or with participatory in situ approaches have grown in parallel with a global governance under the auspices of the United Nations Food and Agriculture Organisation (FAO) (Pilling, Bélanger, Diulgheroff, et al. 2020a). The global objectives of these initiatives are to secure this biodiversity as the indispensable foundation of sustainable food production systems (Smale & Jamora 2020), highlighted in the EU Biodiversity 2030 Strategy, the EU Green Deal, and the UN Sustainable Development Goal 2.5 (Zero hunger - maintain the genetic diversity of seeds, cultivated plants and farmed and domesticated animals and their related wild species). The global collections of genetic resources, comprising ~5.4 million plant accessions from over 50,000 species and over 7,800 local breeds (Pilling, Bélanger, Diulgheroff, et al. 2020a), are managed by a large number of stakeholders. Plant genetic resources are conserved in more than 700 genebanks from 103 countries and 17 regional or international research centres (Pilling, Bélanger, Diulgheroff, et al. 2020a), that contribute to international catalogues of genetic resources such as the European Search Catalogue for Plant Genetic Resources (EURISCO) (Weise et al. 2017) and the European Farm Animal Biodiversity Information System (EFABIS) at the European level and the Domestic Animal Diversity Information System (DAD-IS 2021) and GENESYS (Genesys 2021) at the international level (Figure 3; (FAO 2010)). Another possibility for archiving data on collections of genetic resources is to use the GBIF portal, which is often carried out in parallel as an alternative that does not require any clearance by governmental agencies (Figure 3; e.g. datasets at GBIF from The Netherlands Centre for Genetic Resources, (Menting 2020)).\n\nIn the green box at the bottom, the information systems used to manage the data collected and curate it. Some of these information systems are maintained by ELIXIR nodes in their national infrastructures. The data can then regularly be submitted and updated in international archives. The list of Genetic Resource accessions are archived in the European Search Catalogue for Plant Genetic Resources (EURISCO) and the European Farm Animal Biodiversity Information System (EFABIS) after clearance by National Focal Points appointed by country governments and then collected by global information systems, Genesys and the Domestic Animal Diversity Information System (DAD-IS). They can also archive their datasets at GBIF without any clearance. Genotyping and genomic data are archived in ELIXIR deposition databases and Core Data Resources (EMBL-EBI ENA, EVA and BioSamples). Brokering platforms such as COPO, can be used to facilitate data submission to international archives. ELIXIR has also contributed to a global standard for a RESTful application programming interface (API) focused on plant data, BrAPI, that is progressively implemented on the main plant information systems to allow automatic access to standardised data. GBIF, Global Biodiversity Information Facility; ENA, European Nucleotide Archive; EVA, European Variation Archive.\n\nSince the 1980s, collections of accessions have been genotyped with a set of fast-evolving techniques, mainly to understand crops and breed evolution since domestication and for the identification of adaptive traits, e.g. (Wilkinson et al. 2013; Brozynska et al. 2016; Mascher et al. 2019). Sequence variation has also proved useful and is increasingly used for monitoring current maintained genetic diversity, e.g. detection of redundancy in collections, or assessment of threat levels facing small populations of breeds, forest trees or crop wild relatives (Bélanger et al. 2019). International archives have been developed to store sequence variation data, such as dbSNP (Sherry et al. 2001) focused on Sequence Nucleotide Polymorphisms (SNPs) or the European Variation Archive (EVA 2021) launched more recently to store any type of sequence variant that can be expressed in Variant Call Format (VCF) (Figure 3). Companion archives can be used to track the accession identifiers and collection provenance (BioSamples and BioStudies at EMBL-EBI or BioProjects at NCBI) while the reference genomes used for the detection of the variations must be stored in the INSDC archives prior to the submission of variation data (Figure 3).\n\nA key challenge to be addressed in the context of biodiversity genetics and genomics for food and agriculture rests with the identification of the accessions of genetic resources and their consistency across the catalogues and molecular archives. Breeds or crop variety names that are critical information for linking data obtained on genetic resources to previous knowledge are also a challenge for interoperability due to misspelling, homonyms and synonyms over time, and across regions and borders. Given that reference genome sequences, sequence variation data and catalogues of accessions of genetic resources are usually managed by separate groups, they often end up in different silos with poor or no interoperability. This also affects the interoperability of the data once submitted to international archives, which is still not a routine practice. It is therefore currently not possible to automatically obtain the genetic variation data associated with a given panel of accessions selected in a catalogue of genetic resources or reciprocally, to retrieve all known information on the origin of the accessions (country of origin, type of material, etc.) associated with a variant found in EVA or dbSNP. For crops, the United Nations FAO recently recommended adding a DOI to the three fields of the MultiCrop Passport Data standards that have ensured the unique identification of accessions to date (species name, holding institution name, and the accession identifier provided by the holding institute) and developed a dedicated service (GLIS: the Global Information System on Plant Genetic Resources for Food and Agriculture, Figure 3) to support the adoption of this new practice by genebanks. The communities working on crops, farm animals and forest trees are also actively working with EMBL-EBI to develop dedicated specifications for the metadata associated with the data archived in ENA and EVA and in particular to ensure that they track identifiers associated with accessions of genetic resources. In this context it is important to take into account the possible different scales at which the genetic resources are collected, i.e. an individual for most crops, and populations for breeds and most forest trees. Reciprocally, mechanisms for capturing and updating in genebank catalogues the identifiers associated with the samples that were genotyped or sequenced are needed (see e.g. in relation with domestic animals biological resources: IMAGE 2021). These challenges are not necessarily unique to biodiversity genetics and genomics for food and agriculture, but they particularly highlight efforts required to informatically process and connect sequence data with sample metadata.\n\nThe GlobalFungi Database (GlobalFungi 2021) exemplifies efforts to connect sequencing data to biodiversity research infrastructures and advance data-driven research. Fungi play key roles in all terrestrial ecosystems, primarily as decomposers of organic matter but also as pathogens or symbionts. Long-standing scientific interests in describing and understanding the patterns of global distributions and diversity of fungi mean that sequencing initiatives have led to an accumulating wealth of fungal molecular data from various geographical regions, ecosystems, and habitats. Large-scale studies focusing on soil fungi have used metabarcoding analysis to examine the ecological drivers and biogeographic patterns of fungal community composition and diversity (Tedersoo et al. 2014; Egidi et al. 2019). However, coordinated global sampling at sufficient spatial and taxonomic resolution remains largely unfeasible for individual research studies. Instead, a meta-approach is needed to collect, collate, categorise, and centralise existing data using infrastructures that can continue to gather and include new and future genetic and genomic datasets. The GlobalFungi Database was established as a platform to address these needs by providing public access to published data on fungal community composition obtained by next-generation-sequencing approaches through a web-based interface that promotes FAIR principles and allows various queries and visualisations of the results (Větrovský et al. 2020). Release version 3.0 contains over 1100 million observations of fungi from 367 manually curated studies with over 36,000 samples and 213 million ITS sequence variants (Figure 4). GlobalFungi allows searching for specific sequence variants, fungal genera, species, and molecular species (called ‘species hypotheses’) by performing BLASTn sequence searches and querying the local MySQL database. Annotation of taxa is based on UNITE, the database of fungal molecular taxa compiled using direct sequencing of known fungal species and environmental sequencing of targeted barcodes (Nilsson et al. 2019). GlobalFungi contains data from high-throughput sequencing efforts including local abundance of fungi and complete sampling metadata, and allows querying of samples by location searches on maps or through the studies where they were published. These are complemented with extensive climatic data for sample locations retrieved from the CHELSA (Climatologies at High resolution for the Earth’s Land Surface Areas) database (Karger et al. 2017). The GlobalFungi Database aims to continue to grow by adding more records and by motivating the community to submit new datasets to help build the resource for research on the systematics, biogeography, and ecology of fungi.\n\nGlobalFungi enables searches for specific sequence variants, fungal genera, species, and molecular species (called ‘species hypotheses’) by performing BLASTn sequence searches and querying a local MySQL database. Annotation of taxa is based on UNITE, the database of fungal molecular taxa. Samples can be queried by searching on maps or through the studies where they were published. Climatic data for sample locations are retrieved from the CHELSA (Climatologies at High resolution for the Earth’s Land Surface Areas) database. ITS, Internal Transcribed Spacer; GPS, Global Positioning System.\n\nThe utility of such a centralised resource connecting sequencing data to biodiversity research infrastructures is demonstrated generally through the characterisation of global patterns of fungal biodiversity (Větrovský et al. 2019) or predicting the global biodiversity of fungi (Baldrian et al. 2021) and specifically through the ability to identify fungi that are carried across continents along with introduced plants (Vlk et al. 2020). Moreover, the metadata-rich resource helped to show that symbiotic fungi are more vulnerable to climate change than pathogens and that climate change thus represents a considerable threat for forestry production, agriculture, and food security (Větrovský et al. 2019). Beyond community diversity and biogeography patterns, the distributions of individual fungal species are particularly important, e.g. for phytopathogenic fungi that may severely affect yields of agricultural crops such as the Fusarium pathogen of bananas (Dale et al. 2017). Exploiting the GlobalFungi Database, mycologists, ecologists, or global climate change scientists are able to link fungal occurrence and diversity data with the panel of collected metadata, allowing for the characterisation of key environmental factors that are driving fungal diversity. Such studies can be performed at different geographic levels, from country scales to biomes of the entire world, and for all identifiable fungal communities or for selected ecosystem compartments. Collating these data involves manual curation of information from published studies (367 studies in the latest release), but metadata heterogeneity means that attributes extracted from the publications that are common across the database are limited to just Longitude, Latitude, Continent, Sample type, Biome, Sampling year, Primers used, and pH, while additional metadata only exist for some of the studies. Nevertheless, these resources bring together different data types to enable assessments of fungal diversity across the globe and tracking of individual species or genera, leading to the development of a more comprehensive understanding of the biogeography of fungal diversity. Importantly, this also facilitates assessments of potential threats faced by fungal communities and the ecosystems of which they form such a vital part.\n\n\nInforming strategies for large-scale national biodiversity programmes\n\nNow that large-scale regional, national, and global biodiversity genomics projects are a reality, it is vital to capitalise on the lessons learned and best practices developed through initiatives such as the example use cases presented above. The greatest impact that genetic and genomic data can have on biodiversity assessments, monitoring, conservation, and restoration will only be realised with the support of infrastructures that facilitate the finding, sharing, and connecting of increasingly large and diverse datasets. This requires efforts at all levels to be put into practice from the start, informing strategies for biodiversity programmes to ensure that the data they generate are findable and interoperable. A huge amount of data is being produced globally, and whilst the situation is improving with respect to open access for sequencing data at least, much of this data is still not made available to the research community with adherence to the FAIR principles. By developing strategies and supporting infrastructures that make this easier and scalable, usability and impact will be greatly extended: a major goal of ELIXIR. National biodiversity sequencing efforts can be a useful opportunity to demonstrate how project-wide strategies for harmonisation and standardisation of FAIR data can be put to good effect.\n\nThe primary products of these programmes, the assembled genomes and their corresponding annotations, are the fundamental building blocks that modern computational comparative approaches exploit to learn about the biology and evolution of the species (Zoonomia Consortium 2020). These benefit from and build on accumulated knowledge from field and wet lab research compiled by biologists working on their organisms of interest and documenting experiment details and sample information. This species, experiment, and sample metadata is vital to contextualise the production of a genome and its annotation, and even more so when subsequently exploiting these resources, e.g. through gene expression analysis and interpretation using transcriptomic and other techniques.\n\nStandardisation is essential for the successful scaling up of these initiatives. Whilst the superset of metadata used to describe biological entities and processes might be ever-expanding, metadata about the provenance of samples can be reduced to a subset of ‘core’ terms that reflect descriptions that are fundamental to the downstream contextualisation of a given sequence. For example, the Darwin Tree of Life project (DToL 2021) is a large programme that aims to understand the biodiversity of the British Isles, by sequencing the DNA of all the animals, plants, fungi, and protists, comprising approximately 60,000 species. As a partner of the Earth BioGenome Project (Lewin et al. 2018), DToL has worked with sample collectors who are, or collaborate with, taxonomic experts to develop a core standard for sample metadata collection alongside Standard Operating Procedures for physical preservation of samples and subsequent sequencing. The breadth of the genomes that will be produced from the wide array of habitats, collection methods, and variety of recorded traits across taxonomic groups is a key challenge in terms of ensuring compliance with these standards.\n\nDToL is also undertaking widespread DNA barcoding of specimens. DNA barcoding contributes to rapid identification of biological material and, in terms of cost-benefit, knowing when to barcode and/or genome sequence a specimen could be seen to be a balancing act when considering how to efficiently make assessments of biodiversity. As noted in Use Case 1, barcoding provides a fast and cost-effective technical process to ascertain a provenance trail for a given organism with respect to its taxonomic lineage, an essential part of biodiversity studies. This becomes increasingly important where taxonomic identification is still uncertain due to conflicting or a lack of information, i.e. where an expert identification results in naming differences, lack of defined lineages of less well-studied organisms within the taxonomy databases, and discrepancies with taxonomic identifier allocation services such as the NCBI. As part of DToL, specific metadata schemas are being prepared to assist with the collection of standardised barcoding data alongside methodologies to automate taxonomic identification based on amplicon sequences. Data management tools incorporate and link the deposited sample metadata and the subsequent genomes in the EMBL-EBI Biosamples and ENA databases, respectively, and will also submit to BOLD.\n\nOther national projects focus on within species diversity rather than between species. The national Swedish conifer programme to sequence the Norway spruce and Scots pine genomes serves as an example of what can be done with a well-assembled and annotated genome (Nystedt et al. 2013). Around 75% of Sweden’s area is covered with forest, and much of this is conifer. To improve production and to inform a sustainable forestry practice, the genomes will serve as a basis for a massive resequencing effort where thousands of individuals are sequenced using short read technologies. This will in turn be used to study population structure, and tens of thousands of individuals with known phenotypes will be genotyped. These phenotypes can then be coupled to genotypes and used to improve productivity and to create varieties more adapted to climate change. This also opens up the possibility of pangenomics, an area that is growing in popularity and usefulness, especially in the context of food security highlighted by use case 3, and particularly for crop and livestock improvement (Tao et al. 2019; Khan et al. 2020; Danilevicz et al. 2020; Della Coletta et al. 2021). To fully exploit the massive amounts of sequence data produced, they will need to be deposited with carefully annotated metadata, and stable identifiers that are coupled with phenotypic information.\n\nWhilst the DToL and the Swedish conifer projects are at different ends of the spectrum in terms of breadth and depth, they highlight direct commonalities. They both comprise important first steps for future biodiversity studies, i.e. they develop fundamental genomic baselines on which to build future comparisons amongst organisms and populations through resequencing efforts. However, differences in sampling, naming conventions, sequencing dataset quality and coverage, and annotation quality can all lead to barriers to uptake within the FAIR data ecosystem. By using standardised methods and tools for metadata and data capture and processing, one of the key gaps in biodiversity data management is fulfilled and directly coupled to efforts to produce sequencing and barcoding data based on consistent rich metadata about the biological material from which data are derived. Technical tools, including COPO (Shaw et al. 2020), an ELIXIR roadmapped data brokering resource, are being employed to aid consistent deposition of project-compliant data and metadata in DToL and other upcoming national and international programmes. The aim is to provide a comprehensive overview of the history of the sample, evidence for its characterisation, and its genome which is ready to be used for annotation and further study.\n\nThe DToL and the Swedish conifer projects here serve as examples, in many respects paving the way for emerging initiatives such as the European Reference Genome Atlas (ERGA 2021). Being able to link the sampled biological material to the metadata about the collection process, the identification strategy, the sequence data, and subsequent metrics for assembly, and finally the annotation, will fill crucial gaps in FAIR data delivery in these projects. In this way, the coordination of infrastructure alongside coordination of sampling and characterisation processes based on metadata specifications is a powerful way of linking FAIR data to the methodologies that communities use to undertake biodiversity research and discovery.\n\n\nCommon challenges faced when connecting molecular sequence and biodiversity research infrastructures\n\nThe four use cases and examples of large-scale national biodiversity programmes outlined above present different aspects of how infrastructures can be involved in and support biodiversity studies. They represent data and knowledge ecosystems of connected and complementary information systems. The technical solutions to overcoming data integration challenges are often somewhat domain-specific. Nevertheless, analogies can be drawn amongst the different steps taken to address specific challenges, revealing common gaps in tools and infrastructures focused on taxonomy, metadata, and community services. Cross-domain recognition of these gaps is important to ensure coordinated efforts to address priority issues that will facilitate continued commitments to open science and increased usability of biodiversity related data in support of increased research efficiency.\n\nThe informatics processes designed to connect information from biodiversity research infrastructures with molecular sequence data collections are often hindered by the inconsistent use of taxIDs across collaborating partners. For molecular sequence data, taxIDs are issued by NCBI but only for taxa where sequences have been deposited, whereas biodiversity infrastructures often employ their own distinct sets of taxIDs. Missing and non-matched taxIDs give an incomplete and inconsistent view of currently documented taxa, which greatly decreases the power of computational analyses and severely limits cross-infrastructure interoperability. Conflicting and/or not regularly updated taxonomies employed by the different infrastructures further hinder interoperability, promoting the building of data silos by distinct research communities. Furthermore, different names are currently accepted (able to be processed) by the different infrastructures, and synonym lists are not complete or not compatible. A similar situation exists for agricultural catalogues of genetic resources, where accessions, lines, and samples may be assigned conflicting identifiers by different laboratories. Moreover, the names of breeds and varieties to which they belong are not standardised, meaning that when data are shared or archived their future reuse can be limited by the uncertainty of their origins. The information necessary to address these issues exists, but is difficult to obtain as it essentially implies determining the provenance of a name. It is trapped in the collective wisdom of experts and their publications, and thus must first be extracted, e.g. using text-mining and expert curation, and then fed into reference taxonomic infrastructures with stable backbones and fully traceable identifiers. However, this does not extend well to metagenomics-focused research where ‘dark taxa’ vastly outnumber described diversity, and thus pose additional challenges in the context of defining and employing interoperable identifiers. Communities recognise that taxonomies are not static because our ever-improving understanding of life on Earth necessitates constant revisions. They also recognise that gaps created by failing to develop and support harmonisation initiatives are holding back advances in biodiversity research.\n\nComprehensive and accurate recording of metadata are critical for data reuse and interoperability, but they require considerable extra efforts and cannot be rigidly enforced. They not only enable the tracing of the origins of samples or sample-derived molecular data, but they also provide the necessary context to be able to link these to other relevant data. The scope of such other relevant data could cover taxonomy, ecology and life history, climatology, biogeography, essential and extended sets of biodiversity variables, and much more, but only if the data can be correctly linked. The use cases outlined above highlight just how heterogeneous metadata can be across different research domains, but also how important it is to be able to maintain correct links in order to achieve meaningful research outputs. Metadata is particularly important in the context of connecting molecular sequence data to biodiversity research infrastructures, especially with expanding collections of molecular sequence data and efforts to build reference genomic species libraries. Although a suite of relevant metadata standards exist, e.g. Darwin Core (Wieczorek et al. 2012) for species observations, specimens, samples, and related information, and MIxS for Minimum Information about any (x) Sequence (Yilmaz et al. 2011), they are not used consistently and different standards are adopted by different infrastructures. This is a common problem, as research communities and projects differ with respect to how they set the balance between achieving (i) maximal data accessibility - encouraging data submissions by requiring minimal metadata standards, and (ii) maximal data findability, interoperability, and reusability - by requiring much more comprehensive cataloguing of metadata at the risk of discouraging data submissions. A common challenge is the lack of well-defined comprehensive checklists before embarking on sample collections. Efforts to develop these would mean that the appropriate metadata can be captured during the experiment, rather than retrospectively having to determine the key attributes and recover their values from heterogeneous sources. The examples presented above highlight how consistently capturing at least sample provenance can facilitate some retrospective metadata harvesting, but the challenges of doing so remain considerable. Despite general commonalities amongst standards for the whole data lifecycle: data collection, data processing, analysis, annotation, curation, and data deposition, communities recognise that metadata standards are not ‘one-size-fits-all’ because the great variety of research projects means that some degree of flexibility is required. They also recognise the important added value of investing in comprehensive metadata collection. Practically however, the heterogeneity of current solutions limits communities’ abilities to fully exploit the accumulating data to advance biodiversity research.\n\nAnother common challenge across research communities is the lack of comprehensive and dedicated support to help scientists work towards better compliance with FAIR principles. Researchers who are designing and carrying out the sampling and experiments are not necessarily trained with the technical know-how to ensure good data management. In larger consortia there is often more scope for such support, but this has been historically largely responsive rather than being fully integrated from the early planning stages. Funding agencies are increasingly requiring detailed planning on standards for metadata collection, collation, aggregation, dissemination, and archiving, but implementing such plans remains challenging. For individual researchers, this process often constitutes a barrier that prevents their data being made available in the most useful way to the rest of the scientific community. The use cases above highlight some examples of communities that are building brokering services to meet their own needs, but these probably reflect the exception rather than the rule. Brokering services support researchers by maintaining a technical infrastructure for aiding and automating data submission. For example, the Integrated Publishing Toolkit (IPT 2021) is a free open-source software used to publish and share biodiversity datasets through the GBIF network. Even when such data brokering tools exist for specific communities, users still need support to ensure that they are using the systems correctly: selecting the right standards; employing the right formats; obtaining useful feedback when metadata is not collected properly or missing; and most importantly, a human support mechanism that fits with their domain. The next step, integrating data across different research domains, is often where the greatest metadata loss occurs. If a host resource cannot accommodate certain data types or structures, these remain with the submitter and risk being lost altogether even if provenance is recorded. Proactive communities have recognised many of these challenges and developed brokering tools to meet specific needs, and more generally it is clear that without such supporting services the end-value of the data for biodiversity research is greatly diminished. With the scaling up of production of high-quality sequence data collections and biodiversity research datasets, communities also recognise that ensuring high standards achieved normally through manually curating metadata will not be possible without efficient brokering. This remains practically challenging in many cases as developing and maintaining such dedicated support services to assist researchers with FAIR data brokering is rarely prioritised.\n\n\nRecommendations for closer integrations that will shape the future of biodiversity research\n\nOur survey of approaches by which molecular technologies help inform understanding of biodiversity aimed to identify opportunities and priorities to aid strategic thinking. This highlights the emerging critical importance of making use of molecular data to advance understanding of biodiversity in its broadest terms. The four use cases clearly demonstrate that molecular data are now increasingly and routinely used to inform diverse questions on taxonomies, diversity and abundance of microorganisms, the interface with the human food chain, and to increase our understanding of organisms in a wider ecological sense. Also evident is the rapid change in scale, both in terms of foundational whole genomes and derived data, which is creating related challenges across the use cases and more widely in the field. To that end, we therefore make the following recommendations, which we believe are essential for the wider field of biodiversity research to benefit from the vast quantity of molecular data that will be generated in the coming years:\n\nFirst and foremost, the key infrastructures in the molecular domain such as ELIXIR, should seek to form strong collaborations with those that span the biodiversity domain, such as (but not limited to) GBIF, DiSSCo, CETAF, ENVRI, CoL, BLR and OBIS. This will be required to meet the challenges associated with the steep scaling up of molecular approaches for the study of biodiversity. Infrastructures should build Communities of Practice that create standards and alignment across the two domains of science. This will support research aimed at discovering, monitoring, characterising, and understanding biodiversity, but also many other areas of research and innovation in the life sciences using genetic diversity as a basis. Infrastructures can benefit from the experience of ELIXIR to independently build solutions to meet specific community needs but maintain interoperability with existing resources. A significant step in this direction will be via a Horizon 2020 funded project to build the Biodiversity Community Integrated Knowledge Library (BiCIKL). This will bring together a cross-disciplinary set of infrastructures, spanning molecular, taxonomic, literature, museum, and others into a single community focused on addressing biodiversity-related data challenges.\n\nTo address shortcomings in the way taxonomies are handled between the biodiversity and molecular domains we should adopt a common linked data resource. Building on existing resources, taxonomy methodologies need to bridge the gap between identifiers in the molecular domain (e.g. taxID) and taxonomic names in the biodiversity domain, in a manner that is harmonised across repositories. This would provide tools to deal with synonyms and updates, it would enable better understanding of the meaning of a taxonomic name through access to taxonomic treatments, and it would facilitate annotations and links with external data. Harmonisation would also provide researchers with access to a comprehensive and consistent overview of known or accepted taxa names as a proxy of the current state of existing biodiversity to be characterised. This needs to cover all branches of life and be able to accommodate emerging potential species currently only known from sequencing-based studies.\n\nTo facilitate links across the biodiversity and molecular domains we should develop a consistent set of interoperable metadata standards that are fit-for-purpose and fully integrated into the research lifecycle. This will allow for the connected tracking of accessions, vouchers, and samples with a rich wealth of information captured about their origins (localisation, biome, etc.), and with publications synthesising the emerging knowledge. This has to be associated with a set of technical standards and tools to facilitate data and metadata collection, formatting, and curation, with brokering services to guide the process to completion. Responding to such needs, the ELIXIR Research Data Management Kit (RDMkit 2021) offers guidance on life sciences data management practices applicable to metadata in biodiversity-related research. Finally, and recognising that standards as described here are only useful if they are widely used, we recommend there is a rigorous drive towards their universal adoption via data brokering and deposition platforms and via publication of results in the scientific literature.\n\nAs the rate of acquisition grows, and molecular data are increasingly recognised as a common resource with multiple downstream applications, data management solutions need to scale accordingly. It is clear that from barcodes to reference genomes, sequencing hundreds of thousands of species in the near future will generate the foundational data for most biodiversity molecular studies for decades to come. Efficient data management will require national and international investments to build and sustain the required infrastructures. Upscaling the approaches for standardised and common methods for metadata capture, sequence analysis and annotation, as well as curation and archival, is critical if the data are to be re-used as widely as possible at a large scale and across domains. In addition, when operating at this scale, and across many geographies, it is essential now that the core resources are designed to be sustained in the long term.\n\nContinued community-driven development of the analysis tools and services required to take full advantage of the accumulating data should be actively supported. Methods for the analysis of molecular data integrated with biodiversity-related data will continue to evolve and improve, so adopting a fixed approach to data analysis is not a realistic option. Instead, development should proceed in an environment that encourages innovation while building on and connecting to existing tools and services. To achieve this in an efficient manner that benefits the entire community, bioinformatics methods development needs to follow the recommendations on FAIR software (Katz et al. 2021). To encourage this, we should prioritise the establishment of dedicated recommendations and guidelines for best practices in developing bioinformatics tools and services for biodiversity research. For example, workflows used to analyse biodiversity-related data should be containerised and made easily accessible through BioContainers (da Veiga Leprevost et al. 2017) or within cloud computing infrastructures. These efforts can benefit from and should build on the ELIXIR tools ecosystem (ELIXIR 2021b) that aims to help communities find, register and benchmark software tools, while maintaining information standards for these tools, and producing, adopting and promoting best practices for their development.\n\nTo encourage and enable the adoption of these recommendations by the end-user communities, we should build common training, capacity building, and outreach activities. This needs to cover all stages of the processes involved, from sampling to data processing and analysis. Training ensures dissemination of the developed tools, resources, and standards to the scientific community and engagement feeds back into refinements and new initiatives to better serve community needs. Sustained support for training connects infrastructure developers like data engineers, service providers, and software developers, with infrastructure users producing and analysing biodiversity-related data. The rewards from prioritising training are evident from the experiences of the ELIXIR Training Platform, through which researchers are empowered with the skills and confidence to use the relevant tools and services and contribute to their continued development.\n\nThis survey represents a step in the direction of identifying common challenges and opportunities with respect to how molecular technologies can help inform understanding of biodiversity. The use cases described above show how different research communities are developing initiatives to connect molecular sequence data collections with biodiversity research infrastructures. They represent just a small fraction of ongoing initiatives spanning a wide range of biodiversity studies, some more and others less aware of each other’s activities. Research communities should be proactive in communicating their needs and the solutions to meet them, thereby encouraging cross-community development of tools and resources that multiply benefits and avoid redundancies. The ELIXIR contextualised portfolio of biodiversity informatics resources and services provides a starting point to bringing visibility to existing infrastructures as well as stimulating improved integration. In order to better understand the challenges concerning emerging technologies, scaling up workflows, and ensuring that standards evolve in a coherent manner, we recommend that the community develops a curated, shared, and public understanding of the different types of emerging data, dataflows, repositories, and portals that are necessary to steward up-to-date, comprehensive, complete, and interoperable reference datasets on biodiversity. Such a catalogue of use cases would be a natural output of the Communities of Practice described above in our recommendation on improved collaborations. Through such community-driven initiatives, core sets of standards, approaches, and techniques should be defined that provide all researchers with the means to address critical biodiversity questions by taking advantage of well-connected molecular sequence and biodiversity research infrastructures.\n\n\nData availability\n\nNo data are associated with this article.", "appendix": "Acknowledgements\n\nThe authors would like to acknowledge the important contribution made by Dr Corinne Martin, ELIXIR, who provided critical independent expert review of the manuscript during its preparation.\n\n\nReferences\n\nAgosti D, Egloff W: Taxonomic information exchange and copyright: the Plazi approach. BMC. Res. Notes 2009. 2009; 2(53). Publisher Full Text\n\nAarestrup FM, et al.: Integrating Genome-based Informatics to Modernize Global Disease Monitoring, Information Sharing, and Response. Emerg. Infect. Dis. 2012; 18: e1–e1. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nACE: ACE Expedition – A better understanding of Antarctica.2021. (Accessed February 24, 2021). Reference Source\n\nAdamowicz SJ, Hollingsworth PM, Ratnasingham S, et al.: International Barcode of Life: Focus on big biodiversity in South Africa Cristescu, ME, editor. Genome. 2017; 60: 875–879. PubMed Abstract \| Publisher Full Text\n\nAgosti D, et al.: Biodiversity Literature Repository (BLR), a repository for FAIR data and publications. Biodivers. Inf. Sci. Stand. 2019; 3: e37197. Publisher Full Text\n\nAgosti D, Egloff W: Taxonomic information exchange and copyright: the Plazi approach. BMC. Res. Notes. 2009; 2: 53. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAndersson A, et al.2020. Publishing sequence-derived data through biodiversity data platforms.Publisher Full Text\n\nArita M, Karsch-Mizrachi I, Cochrane G: The international nucleotide sequence database collaboration. Nucleic Acids Res. 2021; 49: D121–D124. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBaldrian P, Větrovský T, Lepinay C, et al.: High-throughput sequencing view on the magnitude of global fungal diversity. Fungal Divers. 2021. in press. Publisher Full Text\n\nBaral H-O, Queloz V, Hosoya T: Hymenoscyphus fraxineus, the correct scientific name for the fungus causing ash dieback in Europe. IMA Fungus. 2014; 5: 79–80. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBélanger J, Pilling D: FAO, Commission on Genetic Resources for Food and Agriculture: The state of the world’s biodiversity for food and agriculture. 2019. (Accessed February 22, 2021). Reference Source\n\nBénichou L, Gerard I, Chester C, et al.: The European Journal of Taxonomy: Enhancing taxonomic publications for dynamic data exchange and navigation. Biodivers. Inf. Sci. Stand. 2019; 3: e37199. Publisher Full Text\n\nBerney C, et al.: UniEuk: Time to Speak a Common Language in Protistology!. J. Eukaryot. Microbiol. 2017; 64: 407–411. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBiCIKL. Reference Source\n\nBourlat SJ, et al.: Genomics in marine monitoring: New opportunities for assessing marine health status. Mar. Pollut. Bull. 2013; 74: 19–31. PubMed Abstract \| Publisher Full Text\n\nBrozynska M, Furtado A, Henry RJ: Genomics of crop wild relatives: expanding the gene pool for crop improvement. Plant Biotechnol. J. 2016; 14: 1070–1085. PubMed Abstract \| Publisher Full Text\n\nCanonico G, et al.: Global Observational Needs and Resources for Marine Biodiversity. Front. Mar. Sci. 2019; 6: 367. Publisher Full Text\n\nCarroll D, et al.: The Global Virome Project. Science. 2018; 359: 872–874. PubMed Abstract \| Publisher Full Text\n\nCETAF: CETAF – Consortium of European Taxonomic Facilities\|EXPLORING AND DOCUMENTING DIVERSITY IN NATURE.2021. (Accessed November 1, 2020). Reference Source\n\nCheng S, et al.: 10KP: A phylodiverse genome sequencing plan. GigaScience. 2018; 7: 1–9. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCollins JE, et al.: Strengthening the global network for sharing of marine biological collections: recommendations for a new agreement for biodiversity beyond national jurisdiction Blasiak, R, editor. ICES J. Mar. Sci. 2020; 78: 305–314. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDAD-IS: Domestic Animal Diversity Information System. Domest. Anim. Divers. Inf. Syst. DAD-IS. 2021. (Accessed October 26, 2020). Reference Source\n\nDale J, et al.: Transgenic Cavendish bananas with resistance to Fusarium wilt tropical race 4. Nat. Commun. 2017; 8: 1496. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDanilevicz MF, Tay Fernandez CG, Marsh JI, et al.: Plant pangenomics: approaches, applications and advancements. Curr. Opin. Plant Biol. 2020; 54: 18–25. PubMed Abstract \| Publisher Full Text\n\nDavies N, et al.: The founding charter of the Genomic Observatories Network. GigaScience. 2014; 3: 2. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDella Coletta R, Qiu Y, Ou S, et al.: How the pan-genome is changing crop genomics and improvement. Genome Biol. 2021; 22: 3. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\ndeWaard JR, et al.: A reference library for Canadian invertebrates with 1.5 million barcodes, voucher specimens, and DNA samples. Sci. Data. 2019; 6(308): 308. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDiSSCo: The Distributed System of Scientific Collections. DiSSCo; 2021. (Accessed October 26, 2020). Reference Source\n\nDivSeek: DivSeek International Network - A Global Community Driven Not-for-Profit Organization. DivSeek Intl.; 2021. (Accessed October 26, 2020). Reference Source\n\nDroege G, et al.: The Global Genome Biodiversity Network (GGBN) Data Standard specification. Database (Oxford). 2016 Oct 2; 2016: baw125. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDToL: Darwin Tree Of Life.2021. (Accessed June 19, 2020). r\n\nDuarte CM: Seafaring in the 21St Century: The Malaspina 2010 Circumnavigation Expedition. Limnol. Oceanogr. Bull. 2015; 24: 11–14. Publisher Full Text\n\nEBP: Earth BioGenome Project. Earth Biog. Proj.; 2021. (Accessed April 7, 2021). Reference Source\n\nEgidi E, et al.: A few Ascomycota taxa dominate soil fungal communities worldwide. Nat. Commun. 2019; 10: 2369. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nELIXIR: ELIXIR\|A distributed infrastructure for life-science information.2021a. (Accessed December 14, 2020). Reference Source\n\nELIXIR: ELIXIR Tools Platform. ELIXIR; 2021b. (Accessed May 10, 2021). Reference Source\n\nENVRI: ENVRI: Environmental Research Infrastructures Community. ENVRI Community; 2021. (Accessed May 10, 2021). https://envri.eu/\n\nERGA: The European Reference Genome Atlas (ERGA) initiative. Genome Atlas Eur. Biodivers. 2021. (Accessed May 10, 2021). Reference Source\n\nEVA: The European Variation Archive.2021. (Accessed December 14, 2020). Reference Source\n\nFAANG: A Global Network - Functional Annotation of Animal Genomes (FAANG). Funct. Annot. Anim. Genomes FAANG Proj. - Coord. Int. Action Accel. Genome Phenome. 2021. (Accessed October 26, 2020). Reference Source\n\nFAO: The second report on the state of the world’s plant genetic resources for food and agriculture. Rome: Commission on Genetic Resources for Food and Agriculture, Food and Agriculture Organization of the United Nations; 2010.\n\nFederhen S: The NCBI Taxonomy database. Nucleic Acids Res. 2012; 40: D136–D143. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nField D, et al.: Genomic Standards Consortium Projects. Stand. Genomic Sci. 2014; 9: 599–601. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGBIF: Amplicon sequencing of Tara Oceans DNA samples corresponding to size fractions for protists.2018. Publisher Full Text\n\nGBIF: GBIF: The Global Biodiversity Information Facility (2020) What is GBIF?. GBIF; 2021. (Accessed June 17, 2020). Reference Source\n\nGenesys: Genesys.2021. (Accessed October 26, 2020). Reference Source\n\nGenResBridge: GenRes Bridge.2021. (Accessed October 26, 2020). Reference Source\n\nGilbert JA, Jansson JK, Knight R: The Earth Microbiome project: successes and aspirations. BMC Biol. 2014; 12: 69. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGlobalFungi: GlobalFungi.2021. (Accessed December 23, 2020). Reference Source\n\nGlöckner FO, et al.: 25 years of serving the community with ribosomal RNA gene reference databases and tools. J. Biotechnol. 2017; 261: 169–176. PubMed Abstract \| Publisher Full Text\n\nGorsky G, et al.: Expanding Tara Oceans Protocols for Underway, Ecosystemic Sampling of the Ocean-Atmosphere Interface During Tara Pacific Expedition (2016–2018). Front. Mar. Sci. 2019; 6: 750. Publisher Full Text\n\nHarrow J, et al.: ELIXIR-EXCELERATE: establishing Europe’s data infrastructure for the life science research of the future. EMBO J. 2021; 40: e107409. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHoban S, et al.: Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biol. Conserv. 2020; 248: 108654. Publisher Full Text\n\nHobern D: BIOSCAN: DNA barcoding to accelerate taxonomy and biogeography for conservation and sustainability Adamowicz, S, editor. Genome. 2021; 64: 161–164. PubMed Abstract \| Publisher Full Text\n\nHoletschek J, et al.: The ABCD of primary biodiversity data access. Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology 2012; 146(4): 771–779. Publisher Full Text\n\nten Hoopen P , et al.: The metagenomic data life-cycle: standards and best practices. GigaScience. 2017; 6: 1–11. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\ni5K Consortium: The i5K initiative: advancing arthropod genomics for knowledge, human health, agriculture, and the environment. J. Hered. 2013; 104: 595–600. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\niHMP Research Network Consortium: The Integrative Human Microbiome Project. Nature. 2019; 569: 641–648. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nIPBES: The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). IPBES; 2021. (Accessed May 6, 2021). Reference Source\n\nIMAGE: Innovative Management of Animal Genetic Resources.2021. (Accessed July 9, 2021). Reference Source\n\nIPT: The Integrated Publishing Toolkit.2021. (Accessed March 22, 2021). Reference Source\n\nJetz W, et al.: Essential biodiversity variables for mapping and monitoring species populations. Nat. Ecol. Evol. 2019; 3: 539–551. PubMed Abstract \| Publisher Full Text\n\nKarger DN, et al.: Climatologies at high resolution for the earth’s land surface areas. Sci. Data. 2017; 4: 170122. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKatz DS, Gruenpeter M, Honeyman T: Taking a fresh look at FAIR for research software. Patterns. 2021; 2: 100222. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKhan AW, et al.: Super-Pangenome by Integrating the Wild Side of a Species for Accelerated Crop Improvement. Trends Plant Sci. 2020; 25: 148–158. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKindler C, et al.: Hybridization patterns in two contact zones of grass snakes reveal a new Central European snake species. Sci. Rep. 2017; 7: 7378. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKissling WD, et al.: Towards global data products of Essential Biodiversity Variables on species traits. Nat. Ecol. Evol. 2018; 2: 1531–1540. PubMed Abstract \| Publisher Full Text\n\nKlemetsen T, et al.: The MAR databases: development and implementation of databases specific for marine metagenomics. Nucleic Acids Res. 2018; 46: D692–D699. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKopf A, et al.: The ocean sampling day consortium. GigaScience. 2015; 4: 27. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLewin HA, et al.: Earth BioGenome Project: Sequencing life for the future of life. Proc. Natl. Acad. Sci. 2018; 115: 4325–4333. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLinnaeus CApis mellifera Linnaeus, 1758, spec. nov.1758. Publisher Full Text\n\nvon Linné C , Lars S Caroli Linnaei … Species plantarum: exhibentes plantas rite cognitas, ad genera relatas, cum differentiis specificis, nominibus trivialibus, synonymis selectis, locis natalibus, secundum systema sexuale digestas…. Holmiae:Impensis Laurentii Salvii. 1753. Reference Source\n\nvon Linné C , Lars S: Caroli Linnaei…Systema naturae per regna tria naturae: secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis. Holmiae:Impensis Direct. Laurentii Salvii. 1758. Reference Source\n\nMascher M, et al.: Genebank genomics bridges the gap between the conservation of crop diversity and plant breeding. Nat. Genet. 2019; 51: 1076–1081. PubMed Abstract \| Publisher Full Text\n\nMenting F: Centre for Genetic Resources, the Netherlands. PGR passport data. 2020. Publisher Full Text\n\nMeyer F, et al.: MG-RAST version 4—lessons learned from a decade of low-budget ultra-high-throughput metagenome analysis. Brief. Bioinform. 2019; 20: 1151–1159. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMiller J, et al.: Integrating and visualizing primary data from prospective and legacy taxonomic literature. Biodivers. Data J. 2015; 3: e5063. Publisher Full Text\n\nMIRRI: The pan-European Microbial Resource Research Infrastructure.2021. (Accessed October 26, 2020). Reference Source\n\nMitchell AL, et al.: MGnify: the microbiome analysis resource in 2020. Nucleic Acids Res. 2020; gkz1035. Publisher Full Text\n\nMMC: Marine Metagenomics Community. ELIXIR; 2021. (Accessed February 24, 2021). Reference Source\n\nMMP: Marine Metagenomics Portal.2021. (Accessed March 24, 2021). Reference Source\n\nMOSAiC: MOSAiC Expedition. MOSAiC Exped; 2021. (Accessed February 24, 2021). Reference Source\n\nMukherjee S, et al.: 1,003 reference genomes of bacterial and archaeal isolates expand coverage of the tree of life. Nat. Biotechnol. 2017; 35: 676–683. PubMed Abstract \| Publisher Full Text\n\nNiang G, et al.: METdb: A genomic reference database for marine species.2020. Publisher Full Text\n\nNilsson RH, et al.: The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Res. 2019; 47: D259–D264. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNystedt B, et al.: The Norway spruce genome sequence and conifer genome evolution. Nature. 2013; 497: 579–584. PubMed Abstract \| Publisher Full Text\n\nOBIS: Ocean Biodiversity Information System.2021. (Accessed May 10, 2021). Reference Source\n\nParr CS, et al.: The Encyclopedia of Life v2: Providing Global Access to Knowledge About Life on Earth. Biodivers. Data J. 2014; 2: e1079. Publisher Full Text\n\nPenev L, et al.Implementation Of Taxpub, An Nlm Dtd Extension For Domain-Specific Markup In Taxonomy, From The Experience Of A Biodiversity Publisher.2012. Publisher Full Text\n\nPilling D, Bélanger J, Diulgheroff S, et al.: Global status of genetic resources for food and agriculture: challenges and research needs: Global status of genetic resources for food and agriculture. Genet. Resour. 2020a; 1: 4–16. Publisher Full Text\n\nPilling D, Bélanger J, Hoffmann I: Declining biodiversity for food and agriculture needs urgent global action. Nat. Food. 2020b; 1: 144–147. Publisher Full Text\n\nPlazi: Plazi: an association supporting and promoting the development of persistent and openly accessible digital taxonomic literature.2021. (Accessed February 24, 2021). Reference Source\n\nQuast C, et al.: The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2012; 41: D590–D596. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRatnasingham S, Hebert PDN: Bold: The Barcode of Life Data System. Mol. Ecol. Notes. 2007; 7: 355–364. Reference SourcePubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRDMkit: RDMkit The ELIXIR Research Data Management Kit.2021. (Accessed April 5, 2021). Reference Source\n\nRhie A, et al.: Towards complete and error-free genome assemblies of all vertebrate species. Nature. 2021 Apr; 592(7856): 737–746. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRoskov Y, et al.: Catalogue of Life - 2019 Annual Checklist. Cat. Life 2019 Annu. Checkl. 2020. (Accessed May 13, 2020). Reference Source\n\nRyberg M, Nilsson RH: New light on names and naming of dark taxa. MycoKeys. 2018; 30: 31–39. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSantamaria M, et al.: ITSoneDB: a comprehensive collection of eukaryotic ribosomal RNA Internal Transcribed Spacer 1 (ITS1) sequences. Nucleic Acids Res. 2018; 46: D127–D132. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSchigel D, et al.: Going Molecular: Sequence-based spatiotemporal biodiversity evidence in GBIF. Biodivers. Inf. Sci. Stand. 2019; 3: e37036. Publisher Full Text\n\nSchmeller DS, et al.: A suite of essential biodiversity variables for detecting critical biodiversity change: EBVs and critical biodiversity change. Biol. Rev. 2018; 93: 55–71. PubMed Abstract \| Publisher Full Text\n\nSchoch CL, et al.: NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database. 2020; 2020: baaa062. Publisher Full Text\n\nShaw F, et al.: COPO: a metadata platform for brokering FAIR data in the life sciences. F1000Res. 2020; 9: 495. Publisher Full Text\n\nSherry ST, et al.: dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001; 29: 308–311. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSmale M, Jamora N: Valuing genebanks. Food Secur. 2020; 12: 905–918. Publisher Full Text\n\nStork NE: How Many Species of Insects and Other Terrestrial Arthropods Are There on Earth?. Annu. Rev. Entomol. 2018; 63: 31–45. Publisher Full Text\n\nSunagawa S, et al.: Structure and function of the global ocean microbiome. Science. 2015; 348: 1261359–1261359. PubMed Abstract \| Publisher Full Text\n\nSunagawa S, et al.: Tara Oceans: towards global ocean ecosystems biology. Nat. Rev. Microbiol. 2020; 18: 428–445. Publisher Full Text\n\nTao Y, Zhao X, Mace E, et al.: Exploring and Exploiting Pan-genomics for Crop Improvement. Mol. Plant. 2019; 12: 156–169. PubMed Abstract \| Publisher Full Text\n\nTARA: The Tara Ocean Foundation. Fond. Tara Océan.2021. (Accessed December 7, 2020). Reference Source\n\nTara Oceans Coordinators: A global ocean atlas of eukaryotic genes. Nat. Commun. 2018; 9: 373. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTedersoo L, et al.: Global diversity and geography of soil fungi. Science. 2014; 346: 1256688. PubMed Abstract \| Publisher Full Text\n\nThe UniProt Consortium: UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 2019; 47: D506–D515. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVandepitte L, et al.: A decade of the World Register of Marine Species – General insights and experiences from the Data Management Team: Where are we, what have we learned and how can we continue? Hejnol, A, editor. PLOS ONE. 2018; 13: e0194599. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVaulot D, Geisen S, Mahé F, Bass D: pr2-primers: an 18S rRNA primer database for protists. bioRxiv. 2021. Publisher Full Text\n\nda Veiga Leprevost F , et al.: BioContainers: an open-source and community-driven framework for software standardization Valencia, A, editor. Bioinformatics. 2017; 33: 2580–2582. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVernette C, et al.: The Ocean barcode atlas: A web service to explore the biodiversity and biogeography of marine organisms. Mol. Ecol. Resour. 2021; 21: 1347–1358. Publisher Full Text 1755–0998.13322.\n\nVětrovský T, et al.: A meta-analysis of global fungal distribution reveals climate-driven patterns. Nat. Commun. 2019; 10: 5142. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVětrovský T, et al.: GlobalFungi, a global database of fungal occurrences from high-throughput-sequencing metabarcoding studies. Sci. Data. 2020; 7: 228. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVillar E, et al.: The Ocean Gene Atlas: exploring the biogeography of plankton genes online. Nucleic Acids Res. 2018; 46: W289–W295. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVlk L, et al.: Alien ectomycorrhizal plants differ in their ability to interact with co-introduced and native ectomycorrhizal fungi in novel sites. ISME J. 2020; 14: 2336–2346. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWang B, et al.: The China National GeneBank─owned by all, completed by all and shared by all. Yi Chuan Hered. 2019; 41: 761–772. Publisher Full Text\n\nWeise S, Oppermann M, Maggioni L, et al.: EURISCO: The European search catalogue for plant genetic resources. Nucleic Acids Res. 2017; 45: D1003–D1008. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWhitman WB, et al.: Genomic Encyclopedia of Bacterial and Archaeal Type Strains, Phase III: the genomes of soil and plant-associated and newly described type strains. Stand. Genomic Sci. 2015; 10: 26. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWieczorek J, et al.: Darwin Core: An Evolving Community-Developed Biodiversity Data Standard Sarkar, IN, editor. PLoS One. 2012; 7: e29715. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWilkinson MD, et al.: The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016; 3: 160018. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWilkinson S, et al.: Signatures of Diversifying Selection in European Pig Breeds Visscher, PM, editor. PLoS Genet. 2013; 9: e1003453. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nYilmaz P, et al.: Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications. Nat. Biotechnol. 2011; 29: 415–420. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nZoonomia Consortium: A comparative genomics multitool for scientific discovery and conservation. Nature. 2020; 587: 240–245. PubMed Abstract \| Publisher Full Text \| Free Full Text" }	[ { "id": "115285", "date": "05 Jan 2022", "name": "Donald Hobern", "expertise": [ "Reviewer Expertise Biodiversity informatics including management of taxonomic and DNA barcode data", "use of data in taxonomy", "ecology and agriculture." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper addresses probably the most significant opportunity for data-driven innovation and transformation in taxonomy, biogeography, ecology, conservation and biosecurity, with major implications for sustainability and food security.\nThe paper is well structured and clearly demonstrates the potential and challenges. I've divided my comments as follows: 1) clarifications of detail (minor) in regard to some of the referenced initiatives, 2) a few major initiatives that are highly relevant but not referenced, 3) suggestions to make the text clearer and more readable.\nI use page numbers from the PDF version downloadable on 4 January 2022.\nClarifications of detail\nPage 4: The preferred abbreviation for Catalogue of Life is now (since 2021) fully capitalised (COL).\nPage 4: \"The taxonomic frameworks are built ...\" - this seems to refer specifically to GBIF's taxonomic framework, so perhaps replace \"The\" with \"Its\". More importantly, by far the largest contribution to GBIF's framework is COL (see https://data-blog.gbif.org/post/gbif-backbone-taxonomy/) - this provides the major structure and other published resources (including BLR) augment it.\nPage 6 - \"The main reference libraries include ...\" - BOLD is the main reference library that supports iBOL. iBOL is not a separate library. I recommend rewriting \"and the International Barcode of Life\" as \"maintained by the International Barcode of Life\".\nPage 6 - \"(e.g. NCBI or GBIF)\" - as noted above, COL is the core of the GBIF backbone and is used in many other contexts. It may be better to reference \"(NCBI, COL or GBIF)\".\nPage 7 - \"For example, connecting GBIF with the UNITE database\" - Note that GBIF has integrated both BOLD and UNITE in this way - both now contribute molecular OTUs (in BOLD's case BINs) that appear as part of the GBIF taxonomic framework.\nPage 7 - \"Reciprocally, traditional biodiversity data and resources can help inform\" - while this is true, it is not clear how the authors expect the benefits to be developed in this direction. Navigation from molecular data to a corpus of knowledge about associated taxa is relatively simple to achieve, but the published literature is insufficiently structured or parsed to support meaningful inference to support machine-driven analysis of genetic and genomic data.\nPage 8 - \"The NCBI taxonomy database\" - The listed number of synonyms is important, but should be put in context of the current version of COL including 1.95 million accepted species names and another 2 million synonyms.\nPage 10 - \"An additional source of information on taxon names\" - It is important to highlight the scale and diversity of information resources and datasets relating to biodivesity, but these are so heterogeneous that it is unhelpful to treat them monolithically. Lumping them together leaves taxonomic identifiers as the only possible connection point. In practice, the field of biodiversity informatics needs to digest these resources into digital objects that fall into more precise classes (specimen, ecosystem, species, gene, sampling event, trait, etc.).\nPage 13 - Figure 3 caption - \"They can also archive their datasets at GBIF without any clearance.\" - Unless I am missing something, this would be better expressed as \"publish their datasets to GBIF\" since GBIF does not currently assume responsibility for archival of data published to the network (although such archival often de facto occurs).\nPage 16 - \"Missing and non-matched taxIDs give an incomplete and inconsistent view\" - All that is written here is true, but an associated and often neglected issue is the uncertainty associated with taxonomic identifications. A name may be correctly interpreted according to a perfect taxonomic framework, while all the time being based on misidentification. This aspect overlays everything written here and needs to be acknowledged. Of course, this is also a key area in which the fusion of genetic/genomic and other data can bring big benefits. Ideally taxonomic type specimens will end up serving as anchor points not only for morphological descriptions but also as DNA vouchers that can be used to label the corresponding molecular OTUs and validate field-collected data.\nPage 17 - \"Efforts to develop these would mean that the appropriate metadata can be captured during the experiment\" - True, but it is important that we distinguish clearly within the metadata between elements co-collected with the sample of interest and elements added subsequently via interpolation, look-up, etc.\nPage 17 - \"Even when such data brokering tools exist for specific communities\" - Another source of difficulty is inconsistent rigor in defining or interpreting even widely adopted standards. Mapping data from different studies will involve compromises and ambiguities that may not be apparent either to those sharing the data or to consumers of the data.\nPage 18 - \"Metadata needs to be better standardised and universally adopted\" - It may be worthwhile to clarify the scope of what is intended by \"metadata\" - FAIR data standards should include consideration of data structures and packaging models to ensure that users can correctly find and interpret all elements. This is more complex than adopting vocabulaties, etc.\nPage 18 - \"Bioinformatics tools and services for biodiversity research need to be prioritised\" - It may be worthwhile to acknowledge that we do not need monolithic solutions here. We need minimum information standards, stable identifiers and provenance information, good generalisable packaging mechanisms and a software ecosystem that assists with point-to-point or data-class to data-class transformations. Satellite imagery may be a good analogy. Downstream consumers need well-referenced products such as NDVI - these become the components of interest for other more targeted applications. In the same way, we may be best off focusing on a modular approach - develop robust taxonomic frameworks and associated tools, map molecular hypotheses against these frameworks, ensure that data from samples can be consumed as Darwin Core Occurrences and Events, etc.\nOther initiatives\nPage 7 - \"Ongoing efforts to coordinate traditional biodiversity infrastructures\" - As well as the initiatives referenced in this paragraph, GBIF and partners have organised two global conferences, each leading to a publication focused on building such coordination (Hobern et al. 2012, Hobern et al. 2019). The later event led to the call for an alliance for biodiversity knowledge (https://www.biodiversityinformatics.org/) which is highly relevant to this paper as an umbrella for cross-infrastructure collaborations. The alliance is also applicable to page 18 \"Biodiversity-related and molecular-focused infrastructures need to collaborate\".\nPage 8 - Use case 1, paragraph 1 - A topical collection of six papers has recently been published in Organisms Diversity and Evolution from work carried out under the auspices of IUBS. This collection specifically explores the need for a shared taxonomic framework and makes proposals for the required collaboration (Towards a global list of accepted species, see here). Citations for all six papers provided. This is especially applicable to page 18 \"Taxonomies need to be aligned and harmonised across domains\".\nReadability\nIt may be a relatively minor issue, but many sentences throughout the document are unnecessarily hard to read because the central ideas are delayed to the end of the sentence and/or a passive voice is unnecessarily used. For example, in the abstract, consider rewriting \"As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player\" as \"ELIXIR plays a key role as a research infrastructure that develops services and technical solutions that help integrate and coordinate life science resources across Europe\". I found I needed to re-read several passages a few times to get their sense. In almost all cases, the concepts were correct and important, but obscured by word order.\nPage 8 - use case 1 seems in particular need of a rewrite to improve clarity. The first sentence, (\"Creating a comprehensive taxonomy linked ...\") does not make sense and certainly needs to be rewritten.\n\nPage 11 - \"The MAR database entries are cross-referenced with ENA and the World Register of Marine Species (WoRMS) (Vandepitte et al. 2018) records\" - no need for the word \"records\".\nPage 11 - \"On the one hand, the large and growing variety of observations taken during oceanic sampling (Gorsky et al. 2019) have posed many data management challenges.\" - \"has posed\".\nPage 13 - \"Long-standing scientific interests\" - \"interest\".\nPage 15 - \"This species, experiment and sample metadata\" - may be clearer as \"This metadata on species, experimennts and samples\".\nPage 18 - \"It is clear that from barcodes to reference genomes, sequencing hundreds of thousands of species in the near future will generate the foundational data for most biodiversity molecular studies for decades to come.\" - this sentence is awkward and could be rewritten.\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nAre arguments sufficiently supported by evidence from the published literature? Yes\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Yes", "responses": [ { "c_id": "8534", "date": "01 Aug 2022", "name": "Jerry Lanfear", "role": "Author Response", "response": "This paper addresses probably the most significant opportunity for data-driven innovation and transformation in taxonomy, biogeography, ecology, conservation and biosecurity, with major implications for sustainability and food security. The paper is well structured and clearly demonstrates the potential and challenges. I've divided my comments as follows: 1) clarifications of detail (minor) in regard to some of the referenced initiatives, 2) a few major initiatives that are highly relevant but not referenced, 3) suggestions to make the text clearer and more readable. I use page numbers from the PDF version downloadable on 4 January 2022. Response: We thank the reviewer for recognising the importance of this Opinion Piece and especially for the detailed constructive feedback that has undoubtedly helped to improve the manuscript substantially. Clarifications of detail Page 4: The preferred abbreviation for Catalogue of Life is now (since 2021) fully capitalised (COL). Response: Updated to COL throughout, including in Figure 1. Page 4: \"The taxonomic frameworks are built ...\" - this seems to refer specifically to GBIF's taxonomic framework, so perhaps replace \"The\" with \"Its\". More importantly, by far the largest contribution to GBIF's framework is COL (see https://data-blog.gbif.org/post/gbif-backbone-taxonomy/) - this provides the major structure and other published resources (including BLR) augment it. Response: Updated accordingly. Page 6 - \"The main reference libraries include ...\" - BOLD is the main reference library that supports iBOL. iBOL is not a separate library. I recommend rewriting \"and the International Barcode of Life\" as \"maintained by the International Barcode of Life\". Response: Updated accordingly. Page 6 - \"(e.g. NCBI or GBIF)\" - as noted above, COL is the core of the GBIF backbone and is used in many other contexts. It may be better to reference \"(NCBI, COL or GBIF)\". Response: Updated accordingly. Page 7 - \"For example, connecting GBIF with the UNITE database\" - Note that GBIF has integrated both BOLD and UNITE in this way - both now contribute molecular OTUs (in BOLD's case BINs) that appear as part of the GBIF taxonomic framework. Response: Our second example in this section (Canadian invertebrate fauna) presents a specific case of how BOLD integrates with GBIF, so although somewhat implicit this integration is already noted and we prefer to leave it as it is rather than expand this section. Page 7 - \"Reciprocally, traditional biodiversity data and resources can help inform\" - while this is true, it is not clear how the authors expect the benefits to be developed in this direction. Navigation from molecular data to a corpus of knowledge about associated taxa is relatively simple to achieve, but the published literature is insufficiently structured or parsed to support meaningful inference to support machine-driven analysis of genetic and genomic data. Response: We agree that currently there are many challenges that still need to be overcome to achieve this and have edited the text to reflect this as a future goal rather than a current reality. Page 8 - \"The NCBI taxonomy database\" - The listed number of synonyms is important, but should be put in context of the current version of COL including 1.95 million accepted species names and another 2 million synonyms. Response: For context we have added this after the reference to Figure 1. Page 10 - \"An additional source of information on taxon names\" - It is important to highlight the scale and diversity of information resources and datasets relating to biodivesity, but these are so heterogeneous that it is unhelpful to treat them monolithically. Lumping them together leaves taxonomic identifiers as the only possible connection point. In practice, the field of biodiversity informatics needs to digest these resources into digital objects that fall into more precise classes (specimen, ecosystem, species, gene, sampling event, trait, etc.). Response: Although this case study is focused on taxonomy we agree that highlighting the role of digital objects is important and have updated the text accordingly. Page 13 - Figure 3 caption - \"They can also archive their datasets at GBIF without any clearance.\" - Unless I am missing something, this would be better expressed as \"publish their datasets to GBIF\" since GBIF does not currently assume responsibility for archival of data published to the network (although such archival often de facto occurs). Response: Updated accordingly. Page 16 - \"Missing and non-matched taxIDs give an incomplete and inconsistent view\" - All that is written here is true, but an associated and often neglected issue is the uncertainty associated with taxonomic identifications. A name may be correctly interpreted according to a perfect taxonomic framework, while all the time being based on misidentification. This aspect overlays everything written here and needs to be acknowledged. Of course, this is also a key area in which the fusion of genetic/genomic and other data can bring big benefits. Ideally taxonomic type specimens will end up serving as anchor points not only for morphological descriptions but also as DNA vouchers that can be used to label the corresponding molecular OTUs and validate field-collected data. Response: This is indeed a very important point that we did not address specifically, we have added “Taxon misidentifications” to this section to highlight this while not going into details to try to keep this section on common challenges concise, instead adding a sentence to the use case 1 section earlier to elaborate this point. Page 17 - \"Efforts to develop these would mean that the appropriate metadata can be captured during the experiment\" - True, but it is important that we distinguish clearly within the metadata between elements co-collected with the sample of interest and elements added subsequently via interpolation, look-up, etc. Response: We agree with this distinction and have updated the text to include this important point. Page 17 - \"Even when such data brokering tools exist for specific communities\" - Another source of difficulty is inconsistent rigor in defining or interpreting even widely adopted standards. Mapping data from different studies will involve compromises and ambiguities that may not be apparent either to those sharing the data or to consumers of the data. Response: We agree that even within domains (between studies) there are ambiguities and have updated the text to specifically mention this before considering cross-domain issues. Page 18 - \"Metadata needs to be better standardised and universally adopted\" - It may be worthwhile to clarify the scope of what is intended by \"metadata\" - FAIR data standards should include consideration of data structures and packaging models to ensure that users can correctly find and interpret all elements. This is more complex than adopting vocabulaties, etc. Response: We agree that data structures and packaging models are also important for FAIR. However, here we focus on metadata solely as an information collection, standardisation and curation mechanism, as this is a vital first step in how knowledge is represented within a biodiversity project, i.e. sample collection metadata as defined in the Darwin Tree of Life. Data structures and packaging models are primarily concerned with the consumption of biodiversity data, and if the metadata provided at the outset is high quality and standardised, downstream tools and APIs can be varied yet still remain FAIR. We modified the text to clarify the focus here on the first steps in the process of metadata collection. Page 18 - \"Bioinformatics tools and services for biodiversity research need to be prioritised\" - It may be worthwhile to acknowledge that we do not need monolithic solutions here. We need minimum information standards, stable identifiers and provenance information, good generalisable packaging mechanisms and a software ecosystem that assists with point-to-point or data-class to data-class transformations. Satellite imagery may be a good analogy. Downstream consumers need well-referenced products such as NDVI - these become the components of interest for other more targeted applications. In the same way, we may be best off focusing on a modular approach - develop robust taxonomic frameworks and associated tools, map molecular hypotheses against these frameworks, ensure that data from samples can be consumed as Darwin Core Occurrences and Events, etc. Response: We had hoped to have conveyed this with phrases such as “adopting a fixed approach to data analysis is not a realistic option” and “development should proceed in an environment that encourages innovation while building on and connecting to existing tools and services”. Describing these concepts with the suggested term “modular approach” works well to reinforce these ideas, so we have taken this on board and updated the paragraph to more clearly reflect this message. Other initiatives Page 7 - \"Ongoing efforts to coordinate traditional biodiversity infrastructures\" - As well as the initiatives referenced in this paragraph, GBIF and partners have organised two global conferences, each leading to a publication focused on building such coordination (Hobern et al. 2012, Hobern et al. 2019). The later event led to the call for an alliance for biodiversity knowledge (https://www.biodiversityinformatics.org/) which is highly relevant to this paper as an umbrella for cross-infrastructure collaborations. The alliance is also applicable to page 18 \"Biodiversity-related and molecular-focused infrastructures need to collaborate\". Response: These are indeed important syntheses of efforts to build such coordination, we have updated both paragraphs to highlight the relevance of the alliance for cross-infrastructure collaborations. Page 8 - Use case 1, paragraph 1 - A topical collection of six papers has recently been published in Organisms Diversity and Evolution from work carried out under the auspices of IUBS. This collection specifically explores the need for a shared taxonomic framework and makes proposals for the required collaboration (Towards a global list of accepted species, see here). Citations for all six papers provided. This is especially applicable to page 18 \"Taxonomies need to be aligned and harmonised across domains\". Response: We agree that this topical collection exemplifies many of the issues faced in this domain and have now specifically mentioned this in the text. Readability It may be a relatively minor issue, but many sentences throughout the document are unnecessarily hard to read because the central ideas are delayed to the end of the sentence and/or a passive voice is unnecessarily used. For example, in the abstract, consider rewriting \"As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player\" as \"ELIXIR plays a key role as a research infrastructure that develops services and technical solutions that help integrate and coordinate life science resources across Europe\". I found I needed to re-read several passages a few times to get their sense. In almost all cases, the concepts were correct and important, but obscured by word order. Response: We have been through the text and specifically identified sentences that would benefit from rearrangements as suggested to improve readability. Page 8 - use case 1 seems in particular need of a rewrite to improve clarity. The first sentence, (\"Creating a comprehensive taxonomy linked ...\") does not make sense and certainly needs to be rewritten. Response: There are two aspects in a single authoritative list. Going forwards a single list seems obvious, as proposed by Garnett and colleagues the way to go. However, all the legacy data requires a list to include all the synonyms, misidentifications, spelling variants and in order to decide, access to the respective taxonomic treatments. To clarify we use the language used by Garnett et al. that introduces the set of six IUBS commissioned papers mentioned above. Page 11 - \"The MAR database entries are cross-referenced with ENA and the World Register of Marine Species (WoRMS) (Vandepitte et al. 2018) records\" - no need for the word \"records\". Response: Fixed. Page 11 - \"On the one hand, the large and growing variety of observations taken during oceanic sampling (Gorsky et al. 2019) have posed many data management challenges.\" - \"has posed\". Response: Fixed. Page 13 - \"Long-standing scientific interests\" - \"interest\". Response: Fixed. Page 15 - \"This species, experiment and sample metadata\" - may be clearer as \"This metadata on species, experimennts and samples\". Response: Agree, updated. Page 18 - \"It is clear that from barcodes to reference genomes, sequencing hundreds of thousands of species in the near future will generate the foundational data for most biodiversity molecular studies for decades to come.\" - this sentence is awkward and could be rewritten. Response: Agreed, we have re-worked this sentence for clarity." } ] }, { "id": "119683", "date": "31 Mar 2022", "name": "Anders Andersson", "expertise": [ "Reviewer Expertise Microbial ecology and evolution. Bioinformatics." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe opinion article by Waterhouse et al. \"Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR\" goes through a number of use cases on how biodiversity information from DNA sequencing data can be integrated into biodiversity platforms and also highlights challenges related to this. Towards the end, the authors, as the title promises, provide some recommendations on what type of infrastructure initiatives should be funded, to help the biodiversity field overcome the challenges.\nThis paper has many good points and the authors have pinpointed several of the caveats of integrating molecular data with biodiversity platforms. And it also provides some concrete advice on projects/initiatives to overcome the obstacles. But the paper is extremely long - 28 pages - and sometimes difficult to read. For example, it took me five attempts to grasp the meaning of this sentence: “Our survey of approaches by which molecular technologies help inform understanding of biodiversity aimed to identify opportunities and priorities to aid strategic thinking”. And the following sentence doesn't provide much aid: \"This highlights the emerging critical importance of making use of molecular data to advance understanding of biodiversity in its broadest terms.”. I would thus recommend the authors simplify the text a bit. Likewise, I think the paper would benefit from being shortened, otherwise, there is a risk many readers will never reach the recommendations at the end (which, given the title, is probably the main point of this opinion paper).\nHere some specific suggestions (page numbers refer to the pdf version of the article):\nAbstract: \"To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity.\" -> (I suggest) \"Here we survey approaches by which molecular technologies help inform understanding of biodiversity, in order to identify opportunities, highlight priorities, and aid strategic thinking.\"\nAbstract: “Increasing knowledge of marine biodiversity” -> “increasing knowledge of marine biodiversity”\np. 3: “at genetic, species, and ecosystem” -> “at population, community and ecosystem levels” (all those levels involve genetics)\np. 3: “millions of years of evolution” -> “billions of years of evolution” (life on Earth arose 3-4 billion years ago)\np. 4: \"These examples help to formulate more formal definitions: (i) molecular sequence data collection initiatives are producing and collating reference catalogues of genetic and genomic biodiversity on Earth; and (ii) biodiversity research infrastructures are capturing knowledge from scientific collections, observations, and the literature, and building resources of biodiversity information for all Earth’s organisms. Here we identify opportunities to connect these.\"\n- I find the definition (i) incomplete: in addition to producing reference catalogues (e.g. genomes or marker genes) they, importantly, also contain sequencing datasets from the field that hold information on species occurrences (and sometimes intra-specific diversity) in samples (i.e. metagenomic and metabarcoding datasets). The description of MGnify on page 7 illustrates this. Maybe this is what is meant by \"collating\" but that was not clear to me.\nTable 1: Add GTDB (https://gtdb.ecogenomic.org/)\np. 6: Add a brief description of GTDB, for example to the first paragraph of page 6. GTDB is rapidly establishing itself as the standard for cataloguing prokaryotic diversity and a good example of how (meta)genomics can aid in improving taxonomies.\np. 8: \"In this context, while seeking a new experimental design for molecular characterisation of specific organisms, the absence of unique identifiers (i.e. taxIDs) represents an important issue in collecting the most comprehensive information related to the organisms of interest.\"\n- This sentence has unclear meaning to me, what is meant by \"new experimental design\" here?\np. 18: “These efforts can benefit from and should build on the ELIXIR tools ecosystem (ELIXIR 2021b) that aims to help communities find, register and benchmark software tools, while maintaining information standards for these tools, and producing, adopting and promoting best practices for their development.”.\n- I'm not really in favour of using the term \"should\" here. There are other examples of software tool collaborations that fulfil the FAIR requirements such as the nf-core collaboration (https://nf-co.re/) with pipelines/tools used by thousands of researchers and many sequencing facilities.\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nAre arguments sufficiently supported by evidence from the published literature? Yes\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Yes", "responses": [ { "c_id": "8535", "date": "01 Aug 2022", "name": "Jerry Lanfear", "role": "Author Response", "response": "The opinion article by Waterhouse et al. \"Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR\" goes through a number of use cases on how biodiversity information from DNA sequencing data can be integrated into biodiversity platforms and also highlights challenges related to this. Towards the end, the authors, as the title promises, provide some recommendations on what type of infrastructure initiatives should be funded, to help the biodiversity field overcome the challenges. This paper has many good points and the authors have pinpointed several of the caveats of integrating molecular data with biodiversity platforms. And it also provides some concrete advice on projects/initiatives to overcome the obstacles. But the paper is extremely long - 28 pages - and sometimes difficult to read. For example, it took me five attempts to grasp the meaning of this sentence: “Our survey of approaches by which molecular technologies help inform understanding of biodiversity aimed to identify opportunities and priorities to aid strategic thinking”. And the following sentence doesn't provide much aid: \"This highlights the emerging critical importance of making use of molecular data to advance understanding of biodiversity in its broadest terms.”. I would thus recommend the authors simplify the text a bit. Likewise, I think the paper would benefit from being shortened, otherwise, there is a risk many readers will never reach the recommendations at the end (which, given the title, is probably the main point of this opinion paper). Response: We thank the reviewer for noting the positive points and for the constructive criticisms with respect to addressing readability issues, also noted by reviewer 1. We have made simplifications and rephrased complex statements to more clearly convey the main messages. Regarding the length, we recognise that describing the four use cases in the manuscript adds substantially to the overall content, but we believe these details are necessary as they provide the basis from which to develop meaningful recommendations. We agree that the recommendations are the main point of the paper, and we believe that many readers will be inclined to focus on this section along with one or two of the use cases most closely aligned with their own research fields. Thus, while attempting to be more concise throughout the manuscript we would prefer not to dramatically shorten or discard any particular section. We have also rephrased the two sentences highlighted here to improve readability. Here some specific suggestions (page numbers refer to the pdf version of the article): Abstract: \"To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity.\" -> (I suggest) \"Here we survey approaches by which molecular technologies help inform understanding of biodiversity, in order to identify opportunities, highlight priorities, and aid strategic thinking.\" Response: Agree, updated. Abstract: “Increasing knowledge of marine biodiversity” -> “increasing knowledge of marine biodiversity” Response: fixed p. 3: “at genetic, species, and ecosystem” -> “at population, community and ecosystem levels” (all those levels involve genetics) Response: Agree that the proposed formulation is better, updated. p. 3: “millions of years of evolution” -> “billions of years of evolution” (life on Earth arose 3-4 billion years ago) Response: Agree, updated. p. 4: \"These examples help to formulate more formal definitions: (i) molecular sequence data collection initiatives are producing and collating reference catalogues of genetic and genomic biodiversity on Earth; and (ii) biodiversity research infrastructures are capturing knowledge from scientific collections, observations, and the literature, and building resources of biodiversity information for all Earth’s organisms. Here we identify opportunities to connect these.\" - I find the definition (i) incomplete: in addition to producing reference catalogues (e.g. genomes or marker genes) they, importantly, also contain sequencing datasets from the field that hold information on species occurrences (and sometimes intra-specific diversity) in samples (i.e. metagenomic and metabarcoding datasets). The description of MGnify on page 7 illustrates this. Maybe this is what is meant by \"collating\" but that was not clear to me. Response: We agree that the definition should be more clearly broadened to encompass other sequencing datasets and have updated the text accordingly. Table 1: Add GTDB (https://gtdb.ecogenomic.org/) Response: The examples provided in Table 1 are focused on international projects and umbrella initiatives producing (meta) genomes, (meta) transcriptomes, and/or DNA barcodes. GTDB seems to fit more the profile of a consumer of such data and therefore we do not think it represents an example of the type of project we wish to highlight here. p. 6: Add a brief description of GTDB, for example to the first paragraph of page 6. GTDB is rapidly establishing itself as the standard for cataloguing prokaryotic diversity and a good example of how (meta)genomics can aid in improving taxonomies. Response: We agree that this is a good example and we have added GTDB in the discussion of microbe-focused sequencing initiatives. p. 8: \"In this context, while seeking a new experimental design for molecular characterisation of specific organisms, the absence of unique identifiers (i.e. taxIDs) represents an important issue in collecting the most comprehensive information related to the organisms of interest.\" - This sentence has unclear meaning to me, what is meant by \"new experimental design\" here? Response: Indeed, ‘new experimental design’ could be misleading, we have rephrased to improve clarity p. 18: “These efforts can benefit from and should build on the ELIXIR tools ecosystem (ELIXIR 2021b) that aims to help communities find, register and benchmark software tools, while maintaining information standards for these tools, and producing, adopting and promoting best practices for their development.”. - I'm not really in favour of using the term \"should\" here. There are other examples of software tool collaborations that fulfil the FAIR requirements such as the nf-core collaboration (https://nf-co.re/) with pipelines/tools used by thousands of researchers and many sequencing facilities. Response: Indeed the use of “should” here was meant to echo the sentiment above relating to “building on and connecting to existing tools and services” but as it could be misinterpreted we have reworded to remove ambiguity." } ] } ]	1	https://f1000research.com/articles/10-1238
https://f1000research.com/articles/10-1014/v1	06 Oct 21	{ "type": "Review", "title": "Culling and mortality of dairy cows: why it happens and how it can be mitigated", "authors": [ "Diniso Simamkele Yanga", "Ishmael Festus Jaja", "Diniso Simamkele Yanga" ], "abstract": "The United Nations estimates that the global population will total 9.7 billion in 2050. Rapid population growth pose a significant obstacle to achieving the Sustainable Development Goals, particularly eradicating hunger and poverty. In view of the expanding population growth, food production ideally should triple to prevent massive food shortages. Sustainable food and nutrition security is the focal point of the dairy industry. Dairy production plays a pivotal role in addressing and advancing global food and nutrition security. It serves as a major source of protein, calcium, and phosphorus in many families in developing countries with a fast-growing population. Consequently, the dairy industry is expected to grow by approximately 26% in the next 10 years and produce an estimated 1077 million tonnes of milk by 2050. However, the growth and distribution of the dairy industry is limited by many factors such as culling and mortality of dairy cows. Several studies highlight reproduction failures, old age, poor milk yield, diseases (mastitis, lameness, and dystocia), and heat stress as some reasons for culling of dairy cows. Hence, this review highlights the factors influencing culling and mortality in dairy production farms, and discusses mitigating measures to limit culling.", "keywords": [ "Milk production", "culling", "mortality", "dairy animals", "lameness", "mastitis" ], "content": "Introduction\n\nGlobally, the growth and distribution of the dairy industry is anticipated to rise by 26% within the next 10 years.1 In some countries like South Africa, there has been a steady growth of 4.8% in 2018 and 3.0% in 2017.2 There is an expected production of 1077 million tonnes of milk by 2050.3 The projected rise will be escalated by, but not limited to, the rapid growth of the maize production industry, which supplies the dairy industry with feed. The availability and access to nutritious dairy products will also increase with the industry's growth and distribution. Increased availability and access will aid in enhancing food security, especially in developing continents. However, the demand for milk and milk-related products far exceeds the current supply of milk and milk-related products and also exceeds the expected 26% rise.1,4,5 For instance, South Africa experiences a 3,500,000 litre milk deficit every year.6 In 2016, South Africa contributed 0.5% to the overall global milk production.7 The general imbalance in the demand and supply of milk is mainly due to the escalating global population growth.4\n\nAmong many factors influencing milk quantities and qualities, culling and mortality of cows have been highlighted as significant dairy industry constraints. Culling is mainly divided into voluntary and involuntary culling. Involuntary culling accounts for most reasons why dairy animals are removed from production.8–10 Culling is also regarded as a damage control and preventative strategy in which the farmer eliminates cows that carry undesired traits and defects.10 Culling also aids incorporating replacement heifers (the availability of a replacement heifer with superior potential influences the decision to cull a cow regardless of other factors10) and maintaining an optimum herd size. Dairy cows can be removed during production, such as the lactation stage, and culling records are essential in drafting a herd health program.9,11 Culling, to some extent, mitigates mortality as cows that are injured or prone to diseases are most likely to be eliminated through market channels, such as sales and auctions. Documenting the factors responsible for culling helps to identify several problems affecting the farm from cow-level to herd-level and from a managerial to economic point of view.8,10,12–15 Understanding culling rates and related factors is of utmost importance as it is often associated with managerial expertise.8,15 At the herd level, culling is influenced by several factors such as replacement heifers plan, milk quotas, and market prices of milk and beef.15,16 The most common reasons for culling at cow-level includes old age, diseases (udder and legs), metabolic diseases or disorders, respiratory diseases, infectious and non-infectious diseases, illness, injury, infertility, and accidents.17,18 There are several studies conducted in several countries in the world on culling effects and culling factors except in Africa.19–22 There is limited, or lack thereof, information on the culling strategies and rates in Africa. Hence, this review seeks to highlight the factors responsible for culling and mortality in dairy farms.\n\n\nLiterature search\n\nStudies covering any of the factors responsible for culling and mortality in dairy production farms were targeted and included in this review. These studies did need not be addressing the factor in relation to culling and mortality per se to be included in the review. Peer-reviewed literature were identified using databases such as WHO Library Information Systems (WHOLIS), Web of Science, Science Direct, Google Scholar, Scopus, and Norwegian Register for Scientific Journals, Series and Publishers (NSD). Other databases searched were MEDLINE (NLM), Agriculture, Biology and Environmental Sciences (Clarivate Analytics), and PubMed Central (NLM). In addition, grey literature was searched using Google search engine. The following terms were used: culling, culling and mortality, dairy production, dairy industry, diseases, dairy animals, diseases of dairy production, predisposing factors of diseases in dairy production, lameness and associated factors. Also, we searched lists and citations of related studies. Various articles were identified and thoroughly read to extract common factors responsible for culling and mortality in dairy animals. The causative factors were grouped into several classes: udder-related (mastitis) reproduction, production, growth and leg factors, sales, health, and miscellaneous factors.8 The search focused on both commercial and communal dairy farms. A summary of the studies included in this article can be found in Table 1.\n\n\nMajor factors responsible for culling and mortality\n\nAnimal diseases are responsible for a significant loss of production in dairy production farms. Diseases are seldom planned for, some cannot be eradicated, some are zoonotic, and hence they present a fatal risk to the whole herd and public health. Furthermore, some animal diseases are too costly to treat,11,32 hence are further regarded as indirect causes of poor milk yield because sick animals lose appetite and are mostly depressed, and as such cannot yield the expected quantity of milk.11,33 Important considerations are made before a decision to cull is taken, such as the physiological status of the cow, genetic variability and adaptability, and milk production potential.34 Diseases have a direct influence on the culling and mortality rates of dairy cows.11 Some of these diseases include bovine neosporosis caused by Neospora caninum, which affects intensive dairy production. In addition, other common diseases or disorders that play an important role in culling decisions include milk fever, lameness, dystocia, udder deformities, ketosis, metritis, and mastitis.\n\nBovine neosporosis\n\nBovine neosporosis causes abortions, stillbirths, and drops in milk production amongst dairy cows worldwide.32 As such, a cow that has been diagnosed with Neospora caninum is culled from the herd. A study conducted in Senegal reported that sero-positive cows, when not culled, require more inseminations during breeding season than sero-negative cows resulting in more costs incurred.32 It is, therefore, to a certain degree, logical and cost-effective to cull cows that are sero-positive for neosporosis.\n\nMilk fever and ketosis\n\nDuring early lactation, first 30 days, there is a high culling rate due to milk fever.11 It has also been reported that milk fever also contributes to lactation culling, especially late lactation after 240 days.11 The other disease of interest that has been identified as a causative agent for culling and mortality of dairy cows is ketosis. Ketosis refers to an energy imbalance in the cow in terms of the demand and available energy for the cow.11,32 This disease requires a high level of management as it has resulted in the culling of many cows during late lactation.11 Cows with ketosis are culled because they tend to disrupt the breeding process and, in some cases, results in infertility.11 However, the effect of ketosis on culling of dairy cows has not been concluded as different studies have contradicting reports in terms of the risk level. Contrary to earlier studies, it has been reported that ketosis can be easily managed and has no effect on milk yield after 30 days in milk thus invalidating ketosis as a major factor responsible for culling.35\n\nMastitis\n\nMastitis is the most significant disease of economic importance in the dairy industry. In clinical mastitis cases, the udder is characterised by inflammation, pain (the cow refuses to be milked), discolouration of milk, watery and bloody milk, flakes or clots to purulent exudate, and reddish discolouration of the skin and swelling of the udder.11,36–38 The disease has been responsible for the culling of many dairy cows during the first and second lactation with a risk ratio of 1.9.11 Evidence from many recent studies shows that mastitis increases the risk of culling in dairy cows.11,39,40 The prevalence of mastitis varies with the cow’s stage of lactation; heifers are more susceptible to clinical mastitis immediately after calving.21,41 Furthermore, cows that exhibit recurrence of clinical mastitis are most likely to be culled than first-time casualties as they become a liability to the farm.42\n\nMastitis in dairy cows, at any milk production stage, may be induced by one pathogen or a combination of many pathogens.20 Mastitis cases are classified in terms of the origin of the pathogen, i.e. contagious pathogens and environmental pathogens.43 Examples of contagious pathogens are Staphylococcus aureus, Streptococcus agalactiae, Corynebacterium bovis and Mycoplasma species.37,38,43,44 Contagious pathogens are mainly found in the cow’s intra-mammary glands. They are transmitted from one cow to another through milking machines, flies, and milking operators’ hands.43 Environmental pathogens originate from the cow’s surroundings and are transmitted into the cow through the teat during contact with contaminated water, contaminated bedding, and contaminated soil.43,44 Examples of environmental pathogens are Escherichia coli, Streptococcus uberis, Streptococcus dysgalactiae and Klebsiella species.\n\nThe severity of infection caused by these pathogens varies, and depends on the stage of lactation, lactation number, age of the cow, and the type of breed.20 These mechanical dynamics present a risk of lesions or alteration of the teat end, inducing subclinical mastitis in the process.44 Gram-negative pathogens are accountable for clinical mastitis in high-producing multiparous cows.45\n\nIn terms of cost, mastitis is a disease of economic importance in dairy farms as it directly influences the milk quality and quantity42,45 which, when compromised, have significant financial implications.41,42 Mastitis-related economic losses in a dairy farm include costs of medication, veterinarian costs, labour costs, loss of quality (drop in butterfat content), discarded milk, culling and occurrence of other diseases.46 These economic losses depend on the type of production system; an intensive system incurs more costs due to the high-input production methods whereas an extensive system incurs the least costs. The economic losses also vary on the type of mastitis: clinical mastitis (associated with acute cases) and subclinical cases (chronic cases). In recent studies, economic losses due to mastitis have ranged from 2369.72 Rand (120 Euros) to 2765 Rand/cow/year (140 Euros).46,47 In a study conducted in the Netherlands, there was approximately 107 kg and 336 kg of milk per lactating cow lost due to subclinical mastitis and clinical mastitis, respectively.47 It is evident that clinical mastitis results in severe milk production losses even though it is associated with acute cases. Milk production losses also include discarded milk due to contamination, whether thrown away or fed to the calves.48 In the first 30 days of a lactation study, discarded milk accounted for 5.7% of direct costs incurred in a dairy farm per case of clinical mastitis, approximately R450.00 (US$25) per case.48 In the same study, veterinary costs were responsible for only 1% of the total direct costs due to mastitis. A similar trend was reported in similar studies.46–48\n\nMastitis further causes significant losses through reproductive disruptions which, when they occur, means that the farmer is most likely forced to cull the cow.11,20,49 Replacement heifers’ susceptibility and high incident rate to clinical mastitis peri-partum presents the farm with substantial financial losses in terms of medical costs and drop in milk yield.21\n\nLameness is a paramount indicator of animal welfare; this is because lameness is a condition that is commonly associated with pain.50–52 In the United States, lameness is noted as a significant contributor to the culling of dairy cows.53 For dairy farmers, lameness is a sensitive subject because it imposes serious financial losses, as such culling becomes an alternative. Lameness is also sensitive to dairy farmers as it may be associated with the farm’s poor detection of locomotion defects.50 In the United Kingdom, one study reported the prevalence of lameness as 36.5% in 205 dairy farms.50 The study further emphasised that cases of lameness vary with seasons and environment in which the cows are exposed. There are more cases of lameness in spring.54 Lameness is closely associated with an intensive milk production system, in which the cows are subjected to standing for long periods on a concrete floor, and imbalanced diets that solely are formulated to enhance milk production yet predispose the cow to lameness.52\n\nA study conducted in New Zealand reported that lameness is closely correlated to reproductive failures. In cases where lameness affects reproductive performance, such cows have increased chances of being culled.30 This further buttresses that reproductive failures are mainly responsible for the culling decision in many dairy farms.9,23,25 Lameness is most common in multiparous cows, especially cows that are in third or higher parity. Therefore, lameness coincides with peak production of the dairy cows, which is tricky for a farmer as replacement heifers would not immediately meet production levels required.8,30 Lameness can be in the form of claw ulcers which are closely associated with milk yield or production performance.31 Lameness is considered as a disease of economic importance as, upon occurrence, it affects the whole lactation period of the cow. As a result, culling due to lameness is a rationally taken decision in most cases. Lameness is a disease of economic importance in dairy farms; it significantly reduces milk yield.50,59 Milk yield is the currency of a dairy farm. Thus, any loss in milk yield has a monetary value attached to it. Consequently, a cow with a persisting lameness case is at high risk of being culled. Lameness has also been closely linked to poor fertility amongst dairy cows.53 Poor fertility is a major factor responsible for culling.25 One of the effects of lameness is delayed ovarian cycles, which disrupt the breeding cycle53 and eventually induce poor reproductive performance.31 Dairy cows with a reduced reproductive performance are immediately culled from the dairy farm.15 There is a positive correlation between delayed ovarian cycle and body condition losses, ketosis, and puerperal disturbances. Also, veterinary costs associated with the treatment and management of lameness increase the cost of managing and running dairy farms.30 Furthermore, sub-optimal treatment of lameness results in high lameness recurrence cases.30\n\nThe various factors that induce lameness are environment, management, the cow (breed, stage of lactation, age), and nutrition.51 Furthermore, environmental factors such as grazing pastures, type of housing, and concrete surfaces are other predisposing factors of lameness.50 Specifically, concrete surface is closely associated with hoof lesions.50,55 There are more lameness (claw disorders) incidences amongst dairy cows that are housed indoors (concrete floors) than those that are under pasture-based systems, whereby they are frequently susceptible to small rocks, wire and metal.52 A damaged hoof and joint stiffness impair a dairy cow’s locomotion,31 directly affecting the cow’s feeding patterns. It is precisely for this reason that farmers must pay close attention to claw health. Impaired locomotion is more evident amongst Holstein-Friesland because of their high milk yield pedigree.56 Bony changes in the pedal bone accounted for the increased vulnerability to the lameness of old dairy cows.30\n\nThe nutritional disorder closely associated with lameness is clinical and subclinical ruminal acidosis.51 Discrepancies in herd management often lead to nutrition disorders such as systemic or metabolic acidosis.31 A concentrate diet fed with limited functional fibres results in reduced chewing, so the cow produces a limited quantity of buffering saliva, resulting in a drop of the rumen pH.57 Hence the blood becomes acidic from too much acid being absorbed from the rumen into the blood, leading to acidosis.\n\nAcidic blood cannot carry as much oxygen and cow’s feet, being at the farthest points of the cow’s body, receive the least oxygen.57,58 The lack of supply of blood causes the release of histamine, a vasodilator, and arterial constrictor. The sensitive tissues lining the outside wall of the hoof and coffin bone cause ulcers, pain, and haemorrhages associated with laminitis.57,58\n\nSeveral studies have reported a very close association between reproductive failures and high culling rates.9,15,23 Reproductive failures have been closely linked to the age at first calving. Early age at calving improves reproductive performance.17 Conception status is considered the key influencer in culling a cow.11 Reproduction failures, specifically missing conception or failure to deliver the calf, are a leading global factor that causes the culling of dairy animals.9,13,23,25 Cows that generally fail to conceive from a single service tend to have lengthy calving intervals.29 Such cows that are costly to the farm, as a result, have a high probability of being culled than the cows that readily conceive.\n\nHeat stress\n\nHeat stress negatively interferes with production and reproduction dynamics. Hence it is of economic importance in the dairy production industry.60–62 The oestrus cycle and the conception rate of dairy cows are key factors that affect breeding outcomes in a particular breeding season. During periods of heat stress, cows are seldom likely to show signs of oestrus or heat, which is a further indication of decreased amounts of reproductive hormones in the blood.63 Without signs of oestrus, the farmer does not know that a cow should be artificially inseminated or be bred, and when a cow does not get inseminated, the cow cannot conceive a pregnancy. Besides, heat stress disrupts the embryo's development by significantly reducing the cow’s dry matter intake, which is a critical component of gestating dairy cows.64 It further distorts embryo development by inhibiting the functioning of dominant follicles and oocytes, thus rendering them unable to breed successfully.\n\nInfertility\n\nThe goal of any breeding program should be to have 90-95% of cows bred in a 65-day breeding season.65 Often, this is not the case due to nutritional and non-nutritional factors. Factors causing infertility and animals showing a diminished or absent capacity to produce viable offspring are removed from the breed stock.65 In a study conducted in France, infertility (26.1%) was the most frequent cause for culling than low milk yield.25 In the same study, more than 50% of other reasons were health-related such as lameness.50 Poor fertility is a global dairy production challenge that has caused the culling of many dairy cows. For instance, in one study investigating culling in 50 dairy herds in England, poor fertility was responsible for 37% of culling.28 A review conducted in Southern Africa amongst smallholder dairy farms mentioned that contributing factors to infertility includes inadequate housing facility, poor nutrition and improper health management systems.66 Infertility results in poor herd growth, a decrease in replacement of heifers, and generally low farm productivity66; hence it is logical to cull infertile cows as they become a liability to the farm. The unavailability of replacement heifers limits voluntary culling in which the farmer has the prerogative to cull dairy cows.17,18 It further results in the retention of older cows even when the milk yield is declining.\n\nParity\n\nPrevious studies have shown a relationship between parity and the culling rate of cows.67,68 An increase in parity is often associated with a continuous drop in culling frequency, with the highest culling rate at parity 1 to 3.67 Animals in parity 1 to 3 produce more milk than animals in the other parities. Hence, culling dairy cows between first parity and third parity is a costly exercise for dairy farms because it is a stage whereby cows are producing more milk.18,67 Udder morphological disorder is one of the leading predisposing factors for culling across parities.8,23,25 However, culling due to udder problems is more evident during the fourth to sixth parity, where it accounts for almost 50% as a reason to cull. In contrast, reproductive failures are the main factors that lead to culling in second and third parities.29 Parity presents a significant risk for culling, especially to Holstein-Friesian, more than other dairy breeds.29 The first and second parity are two vulnerable stages in the cow’s production life as it is exposed to cases of mastitis and ketosis.11 It is in these stages that culling due to ketosis is frequently reported.\n\nCulling based on age varies with farm management styles/plans, herd size, and milk yield prowess.17 There is an association between herd size and age at culling, in which the smallest herd size had the oldest age at culling.17 Several studies have reported fewer incidences of culling due to age. Therefore, this low incidence rate of culling due to age is hypothetically an indicator of a lack of potential for longevity and lengthy productivity amongst dairy cows. The availability of replacement heifers and mean milk yield by the seasoned cow strongly dictates the age of culling.17,69\n\nIn a commercial dairy farm, it is expected that a cow that is not yielding the anticipated quantities of milk is culled. Hence, it could be assumed that low producing cows are at high risk of culling as milk is the primary product. However, previous studies have reported that high producing cows are most likely to be culled than low producing cows due to the complications associated with high levels of production.18,42 Complications such as recurrent milk fever and abortion are common reasons high milk producers are often culled.12,18,67 Poor milk yield has been attributed to age, clinical mastitis and recurrent mastitis, and breed types. On the other hand, a rise in the culling rate of cows has often associated with an increase in milk yield.42 There is no clear scientific explanation of this correlation between culling and high producing cows. However, several reports have highlighted that high milk yield is a contributing factor to the culling of dairy cows.12,13,24,25 In addition to the ambiguity of why high milk producers are culled, there is a negative correlation between mastitis (a common reason for culling dairy cows) and high milk production.12 The closest reasoning or influence to the culling of high producing cows is abortion cases, especially in Holstein breeds. Another reason for culling high producing cows is a significant drop in milk production. The decline in milk yield is influenced by age, nutrition, and diseases.12,29\n\n\nMitigation strategies to limit culling and mortality of dairy cows\n\nCulling of dairy cows is not always an indication of adversities on the farm. For instance, dairy cows can be voluntarily culled to maintain herd size and generate profit from the sale of the surplus cows or heifers. Also, the culling of dairy cows is inevitable. It cannot be wholly eradicated; however, some factors that influence involuntary culling, such as reproduction failures and diseases, can be prevented or mitigated.\n\nReproduction failures, to some extent, can be avoided through sound management practices and upgrades like improving heat detection and efficient artificial insemination.27 Even so, heat detection by a farmer cannot be as instinctive and accurate70 as it could be when performed by the bull; hence there should be regular training and updating for this activity where artificial insemination is practised.71\n\nAlso, one of the major contributors to reproductive failure is pathogens, such as Brucella abortus, which results in infertility and abortion. Therefore, surveillance of this pathogen needs to be prioritised at all stages of gestation. Different laboratory tests should be conducted because a serological test may yield negative results, whereas a culture test and a more sophisticated molecular test may be positive.72 Thus, it is not recommended to rely on one type of test.\n\nIn addition, the feasibility of age (15 months old) at first insemination needs to be investigated. This is because the farm's economic reasons often influence the decision to inseminate at an early age.73 More minor details such as matching the bull’s body frame with the 15 month old heifer are overlooked, and cases of dystocia are encountered.74\n\nA systematic recording system of health records may help minimise misdiagnosis and premature culling of dairy cows. An earlier study alluded that an improved recording system should provide an epidemiological baseline for each health factor that may tamper with dairy cow’s production and reproduction performance.16 This is essential considering that the decision to cull dairy cows voluntarily is the farmer’s prerogative.12,75 The reliance on farmers' context to voluntarily cull a dairy cow may be subjective; hence, a systematic recording system is necessary. Systematic recording promotes the evaluation of regular health disorders. Also, data derived from a systematic recording system should be the basis of breeding plans to improve the longevity of dairy cows.16\n\nThe performance of dairy cows is mainly influenced by genetics and the environment, particularly nutrition and management. Genetic evaluation and prediction of cow survival should form part of management strategies to lower culling and mortality rates.76 However, genetic evaluation and selection should not only revolve around the milk production potential of the cow.68 Genetic evaluation throughout the heifer rearing stage should also be prioritised to help predict cow survival. Genetic evaluation at the heifer level may limit premature culling and eliminate important traits as some functional traits are cumulative even though they have low heritability.76\n\nOver the years, selection for mainly milk production has proven unsustainable, especially with high producing dairy cows being reported as highly susceptible to mastitis, lameness and reduced length of reproductive life.30 Also, when semen is selected, physical characteristics, such as good leg and feet, and condition of the genitals, precedes other considerations such as cow survival.70\n\nFurthermore, the influence of heat stress on dairy cows varies with breeds and stages of production because there are genetic traits of heat tolerance that vary with breeds.63 Previous attempts to cross-breed indigenous cattle breeds with the exotic breed to mitigate heat stress have, however, resulted in reduced milk yield.3,61 However, the level of reduction of milk yield due to cross-breeding is not extensively documented. As such, it is unclear whether this drop is of any significance.\n\nHigh ambient temperatures directly adversely influence the productivity of the cows to the extent that they can even contribute to the mortality of the cows.19,77 This is because animals respond to high temperatures by reducing feed intake, altering respiration rate, and increasing water intake to facilitate cooling. This might have a limited impact over a single day or two during a hot summer’s day. However, under prolonged periods of high temperatures, the drop in feed intake becomes highly unsustainable, resulting in a decrease in milk yield volumes.3,61 Hence, establishing shelters and shades around the farm would provide great relief to dairy cows and consequently reduce culling and mortality rates.\n\n\nConclusion and recommendation\n\nReproduction failures have been singled out as the most common factor responsible for culling dairy cows in different countries. It is closely followed by production performance and mastitis as leading contributors to the decision to cull dairy cows. Dairy animals are culled because they are poor milk producers; even high milk producers are also culled due to abortion, lameness, and idiopathic reasons. As much as culling and mortality of dairy cows are inevitable, there is a need to revisit and revise dairy farming strategies, starting with the selection process and genetic evaluation. Functional traits should be considered if sustainability is to be achieved by the industry.\n\n\nData availability\n\nNo data is associated with this article.", "appendix": "References\n\nAgriculture Research Council:Economic Outlook Report XXIV. www.arc.agric.za. Accessed: June 18, 2019;2018 [cited 2019 Jun 18].Reference Source\n\nMilk SA: Lactodata November 2019. Lactodata. Pretoria. Accessed: 2019-02-18;2019; Vol. 22.\n\nMelissa Rojas-Downing M, Pouyan Nejadhashemi A, Harrigan T, et al.: Climate change and livestock: Impacts, adaptation, and mitigation. Clim Change. 2017 [cited 2019 Nov 7]; 16: 145–163. Publisher Full Text\n\nThornton PK: Livestock production: recent trends, future prospects. Philos Trans R Soc B Biol Sci. 2010 [cited 2019 Jun 9]; 365: 2853–2867.Reference Source\n\nAgriculture Research Council: Economic outlook report XXII. Accessed: June. 18, 2019;2017 [cited 2019 Jun 18].Reference Source\n\nLemmer W: Spring Outlook: Absa Agribusiness report. Accessed: June.24, 2019; www.absa.co.za. 2018 [cited 2019 Jun 24].Reference Source\n\nMilk Producers Organisation: Agriculture sector on path to recovery. Accessed: Feb. 05, 2019. www.mpo.co.za. 2017 [cited 2019 Feb 5].Reference Source\n\nCompton CWR, Heuer C, Thomsen PT, et al.: Invited review: A systematic literature review and meta-analysis of mortality and culling in dairy cattle. J Dairy Sci. 2017, Jan [cited 2019 Feb 6]; 100(1): 1–16. PubMed Abstract \| Publisher Full Text Reference Source\n\nOrpin PG, Esslemont RJ: Culling and Wastage in Dairy Herds: An Update on Incidence and Economic Impact in Dairy Herds in the UK. Leicestershire. Accessed: July. 02, 2019.;2016 [cited 2019 Jul 2].Reference Source\n\nWakchaure R, Ganguly S, Para PA, et al.: A review on disposal (culling and mortality) of cattle. J Lab Life Scs. 2015; 1(2): 8–16.\n\nGröhn YT, Eicker SW, Ducrocq V, et al.: Effect of diseases on the culling of Holstein dairy cows in New York State. J Dairy Sci. 1998 Apr 1 [cited 2019 Jul 19]; 81(4): 966–978. PubMed Abstract \| Publisher Full Text\n\nBascom SS, Young AJ: A Summary of the Reasons Why Farmers Cull Cows. J Dairy Sci. 1998 Aug 1 [cited 2019 Feb 20]; 81(8): 2299–2305. PubMed Abstract \| Publisher Full Text Reference Source\n\nHadley GL, Wolf CA, Harsh SB: Dairy Cattle Culling Patterns, Explanations, and Implications. J Dairy Sci. 2006 Jun 1 [cited 2019 Jun 3]; 89(6): 2286–2296. PubMed Abstract \| Publisher Full Text Reference Source\n\nArmengol R, Fraile L: Descriptive study for culling and mortality in five high-producing Spanish dairy cattle farms (2006–2016). Acta Vet Scand. 2018 Dec 28 [cited 2019 Apr 4]; 60(1): 45. Publisher Full Text\n\nHaine D, Delgado H, Cue R, et al.: Culling from the herd’s perspective—Exploring herd-level management factors and culling rates in Québec dairy herds. Prev Vet Med. 2017 Nov 1 [cited 2019 Feb 6]; 147: 132–141. PubMed Abstract \| Publisher Full Text Reference Source\n\nBeaudeau F, Seegers H, Ducrocq V, et al.: Effect of health disorders on culling in dairy cows: a review and a critical discussion. Ann Zootech. 2000 Jul; 49(4): 293–311. Publisher Full Text\n\nAdamczyk K, Makulska J, Jagusiak W, et al.: Associations between strain, herd size, age at first calving, culling reason and lifetime performance characteristics in Holstein-Friesian cows. Anim Consort. 2016; 11(2): 327–334. PubMed Abstract \| Publisher Full Text\n\nWeigel KA, Palmer RW, Caraviello DZ: Investigation of Factors Affecting Voluntary and Involuntary Culling in Expanding Dairy Herds in Wisconsin using Survival Analysis. J Dairy Sci. 2003 Apr [cited 2019 Jul 16]; 86(4): 1482–1486. PubMed Abstract \| Publisher Full Text Reference Source\n\nBiffani S, Bernabucci U, Vitali A, et al.: Short communication: Effect of heat stress on nonreturn rate of Italian Holstein cows. J Dairy Sci. 2016; 99(7): 5837–5843. PubMed Abstract \| Publisher Full Text\n\nHertl JA, Schukken YH, Bar D, et al.: The effect of recurrent episodes of clinical mastitis caused by gram-positive and gram-negative bacteria and other organisms on mortality and culling in Holstein dairy cows. J Dairy Sci. 2011 Oct [cited 2019 Sep 13]; 94(10): 4863–4877. PubMed Abstract \| Publisher Full Text Reference Source\n\nCompton CWR, Heuer C, Parker K, et al.: Epidemiology of Mastitis in Pasture-Grazed Peripartum Dairy Heifers and Its Effects on Productivity. J Dairy Sci. 2007 Sep [cited 2019 Sep 30]; 90(9): 4157–4170. PubMed Abstract \| Publisher Full Text Reference Source\n\nEdwards-Callaway LN, Walker J, Tucker CB: Culling Decisions and Dairy Cattle Welfare During Transport to Slaughter in the United States. Front Vet Sci. 2019 Jan 18 [cited 2019 Jun 14]; 5: 343. PubMed Abstract \| Publisher Full Text \| Free Full Text Reference Source\n\nKerslake JI, Amer PR, O’Neill PL, et al.: Economic costs of recorded reasons for cow mortality and culling in a pasture-based dairy industry. J Dairy Sci. 2018 Feb 1 [cited 2019 Jun 3]; 101(2): 1795–1803. PubMed Abstract \| Publisher Full Text Reference Source\n\nKuczaj M, Zielak A, Blicharski P: Reasons for the culling of Polish Holstein-Friesian cows in a high yield herd. Med Weter. 2008 [cited 2019 May 6]; 64(10): 51–630. Publisher Full Text Reference Source\n\nSeegers H, Beaudeau F, Fourichon C, et al.: Reasons for culling in French Holstein cows. Prev Vet Med. 1998 Oct 9 [cited 2019 Jul 2]; 36(4): 257–271. PubMed Abstract \| Publisher Full Text Reference Source\n\nMaher P, Good M, More S: Trends in cow numbers and culling rate in the Irish cattle population, 2003 to 2006. Ir Vet J. 2008 Dec 1 [cited 2019 Jul 2]; 61(7): 455.Reference Source\n\nDe Vries A, Olson JD, Pinedo PJ: Reproductive risk factors for culling and productive life in large dairy herds in the eastern United States between 2001 and 2006. J Dairy Sci. 2010 Feb [cited 2019 Jul 2]; 93(2): 613–623. PubMed Abstract \| Publisher Full Text Reference Source\n\nEsslemont RJ, Kossaibati MA: Culling in 50 dairy herds in England. Vet Rec. 1997 Jan 11 [cited 2019 Jul 16]; 140(2): 36–39. PubMed Abstract \| Publisher Full Text Reference Source\n\nPinedo PJ, Daniels A, Shumaker J, et al.: Dynamics of culling for Jersey, Holstein, and Jersey × Holstein crossbred cows in large multibreed dairy herds. J Dairy Sci. 2014 May 1 [cited 2019 Jul 19]; 97(5): 2886–2895. PubMed Abstract \| Publisher Full Text\n\nMason W: Association between age and time from calving and reported lameness in a dairy herd in the Waikato region of New Zealand. N Z Vet J. 2017 [cited 2019 Jul 19]; 65(3): 163–167. PubMed Abstract \| Publisher Full Text\n\nHultgren J, Manske T, Bergsten C: Associations of sole ulcer at claw trimming with reproductive performance, udder health, milk yield, and culling in Swedish dairy cattle. Prev Vet Med. 2004 Apr 16 [cited 2019 Aug 21]; 62(4): 233–251. PubMed Abstract \| Publisher Full Text Reference Source\n\nKamga-Waladjo AR, Gbati OB, Kone P, et al.: Seroprevalence of Neospora caninum antibodies and its consequences for reproductive parameters in dairy cows from Dakar–Senegal, West Africa. Trop Anim Health Prod. 2010 Jun 9 [cited 2019 Jul 18]; 42(5): 953–959. PubMed Abstract \| Publisher Full Text Reference Source\n\nRajala-Schultz PJ, Gröhn YT: Culling of dairy cows. Part III. Effects of diseases, pregnancy status and milk yield on culling in Finnish Ayrshire cows. Prev Vet Med. 1999 Aug 23 [cited 2019 Apr 4]; 41(4): 295–309. PubMed Abstract \| Publisher Full Text\n\nBeaudeau F, Seegers H, Ducrocq V, et al.: Effect of health disorders on culling in dairy cows: A review and a critical discussion. Anim Res. 2000 Jul 1 [cited 2021 Jun 28]; 49(4): 293–311. Publisher Full Text\n\nGröhn YT, Rajala-Schultz PJ, Allore HG, et al.: Optimizing replacement of dairy cows: Modeling the effects of diseases. Prev Vet Med. 2003 Sep 30; 61(1): 27–43. PubMed Abstract \| Publisher Full Text\n\nIslam M, Islam M, Islam M, et al.: Prevalence of Subclinical Mastitis in Dairy Cows in Selected Areas of Bangladesh. Bangladesh J Vet Med. 2012; 9(1): 73–78.\n\nSumon S, Ehsan M, Islam M: Subclinical mastitis in dairy cows: somatic cell counts and associated bacteria in Mymensingh, Bangladesh. J Bangladesh Agric Univ. 2017; 15(2): 266–271.\n\nMarimuthu M, Faez F, Jesse A, et al.: Prevalence and antimicrobial resistance assessment of subclinical mastitis in milk samples from selected dairy farms. Am J Anim Vet Sci. 2014 [cited 2019 Apr 15]; 9(1): 65–70. Publisher Full Text Reference Source\n\nGera S, Guha A: The Indian journal of animal sciences. Indian J Animal Sci. (India). Indian Council of Agricultural Research. Accessed: 2019-05-26;2011 [cited 2019 May 26].Reference Source\n\nHumayun Kabir M, Ershaduzzaman M, Giasuddin M, et al.: Prevalence and identification of subclinical mastitis in cows at BLRI Regional Station. J Adv Vet Anim Res. 2017 [cited 2019 May 9]; 4(3): 295–300. Publisher Full Text\n\nNaqvi SA, Nobrega DB, Ronksley PE, et al.: Invited review: Effectiveness of precalving treatment on postcalving udder health in nulliparous dairy heifers: A systematic review and meta-analysis. J Dairy Sci. 2018; 101(6): 4707–4728. PubMed Abstract \| Publisher Full Text\n\nJamali H, Barkema HW, Jacques M, et al.: Invited review: Incidence, risk factors, and effects of clinical mastitis recurrence in dairy cows. J Dairy Sci. 2018 Jun 1 [cited 2019 Sep 13]; 101(6): 4729–4746. PubMed Abstract \| Publisher Full Text Reference Source\n\nDufour S, Labrie J, Jacques M, et al.: The Mastitis Pathogens Culture Collection. Am Soc Microbiol. 2019; 8: 1. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNeijenhuis F, Barkema HW, Hogeveen H, et al.: Relationship Between Teat-End Callosity and Occurrence of Clinical Mastitis. J Dairy Sci. 2001; 84(12): 2664–2672. PubMed Abstract \| Publisher Full Text\n\nSchukken YH, Hertl J, Bar D, et al.: Effects of repeated gram-positive and gram-negative clinical mastitis episodes on milk yield loss in Holstein dairy cows. J Dairy Sci. 2009 Jul [cited 2019 Sep 13]; 92(7): 3091–3105. Publisher Full Text Reference Source\n\nHuijps K, Lam TJ, Hogeveen H: Costs of mastitis: facts and perception. J Dairy Res. 2008 Feb 29 [cited 2019 Aug 22]; 75(1): 113–120. PubMed Abstract \| Publisher Full Text Reference Source\n\nvan Soest FJS, Santman-Berends IMGA, Lam TJGM, et al.: Failure and preventive costs of mastitis on Dutch dairy farms. J Dairy Sci. 2016 Oct 1; 99(10): 8365–74. PubMed Abstract \| Publisher Full Text\n\nRollin E, Dhuyvetter KC, Overton MW: The cost of clinical mastitis in the first 30 days of lactation: An economic modeling tool. Prev Vet Med. 2015 Dec 1; 122(3): 257–264. PubMed Abstract \| Publisher Full Text\n\nBar D, Tauer LW, Bennett G, et al.: The Cost of Generic Clinical Mastitis in Dairy Cows as Estimated by Using Dynamic Programming. J Dairy Sci. 2008 Jun [cited 2019 Sep 13]; 91(6): 2205–2214. PubMed Abstract \| Publisher Full Text Reference Source\n\nBarker ZE, Leach KA, Whay HR, et al.: Assessment of lameness prevalence and associated risk factors in dairy herds in England and Wales. J Dairy Sci. 2010 Mar 1 [cited 2019 Apr 5]; 93(3): 932–941. PubMed Abstract \| Publisher Full Text\n\nRanjbar S, Rabiee AR, Gunn A, et al.: Identifying risk factors associated with lameness in pasture-based dairy herds. J Dairy Sci. 2016; 99(9): 7495–7505. Publisher Full Text\n\nHernandez-Mendo O, von Keyserlingk MAG, Veira DM, et al.: Effects of Pasture on Lameness in Dairy Cows. J Dairy Sci. 2007 Mar 1 [cited 2019 Sep 13]; 90(3): 1209–1214. PubMed Abstract \| Publisher Full Text Reference Source\n\nGarbarino EJ, Hernandez JA, Shearer JK, et al.: Effect of lameness on ovarian activity in postpartum Holstein cows. J Dairy Sci. 2004 Dec 1; 87(12): 4123–4131. PubMed Abstract \| Publisher Full Text\n\nBarnes AP, Rutherford KMD, Langford FM, et al.: The effect of lameness prevalence on technical efficiency at the dairy farm level: An adjusted data envelopment analysis approach. J Dairy Sci. 2011 Nov; 94(11): 5449–5457. Publisher Full Text\n\nBergsten Cr: Effects of Conformation and Management System on Hoof and Leg Diseases and Lameness in Dairy Cows. Vet Clin North Am Food Anim Pract. 2001; 17(1): 1–23. PubMed Abstract \| Publisher Full Text\n\nAdams AE, Lombard JE, Fossler CP, et al.: Associations between housing and management practices and the prevalence of lameness, hock lesions, and thin cows on US dairy operations. J Dairy Sci. 2017 Mar 1 [cited 2019 Aug 22]; 100(3): 2119–2136. PubMed Abstract \| Publisher Full Text Reference Source\n\nde Ondarza MB : Nutrition and management. Deval milk production.com. Accessed: 2020-04-11;2001.\n\nStone WC: Nutritional approaches to minimize subacute ruminal acidosis and laminitis in dairy cattle. J Dairy Sci. 2004 Jul 1; 87(SUPPL. 1): E13–E26. Publisher Full Text\n\nAmory JR, Barker ZE, Wright JL, et al.: Associations between sole ulcer, white line disease and digital dermatitis and the milk yield of 1824 dairy cows on 30 dairy cow farms in England and Wales from February 2003-November 2004. Prev Vet Med. 2008 Mar 17 [cited 2020 Mar 23]; 83(3–4): 381–391. PubMed Abstract \| Publisher Full Text\n\nPolsky L, von Keyserlingk MAG : Invited review: Effects of heat stress on dairy cattle welfare. J Dairy Sci. 2017; 100(11): 8645–57. PubMed Abstract \| Publisher Full Text\n\nRavagnolo O, Misztal I: Genetic Component of Heat Stress in Dairy Cattle, Parameter Estimation. J Dairy Sci. 2000; 83(9): 2126–2130. Publisher Full Text\n\nJordan ER: Effects of Heat Stress on Reproduction. J Dairy Sci. 2003; 86: E104–E114. Publisher Full Text\n\nWest JW: Effects of heat-stress on production in dairy cattle. J Dairy Sci. 2003; 86(6): 2131–2144. PubMed Abstract \| Publisher Full Text\n\nSt-Pierre NR, Cobanov B, Schnitkey G: Economic losses from heat stress by US livestock industries1. J Dairy Sci. 2003; 86(SUPPL. 1). Publisher Full Text\n\nNavarre CB: Infertility in cattle. Animal Health Notes. Accessed: 2020-04-11.2010;\n\nBanda LJ, Kamwanja LA, Chagunda MGG, et al.: Status of dairy cow management and fertility in smallholder farms in Malawi. Trop Anim Health Prod. 2012 Apr 19 [cited 2019 Jul 18]; 44(4): 715–727. PubMed Abstract \| Publisher Full Text Reference Source\n\nChiumia D, Chagunda MGG, MacRae AI, et al.: Predisposing factors for involuntary culling in Holstein-Friesian dairy cows. J Dairy Res. 2013; 80(1): 45–50. PubMed Abstract \| Publisher Full Text\n\nPritchard T, Coffey M, Mrode R, et al.: Genetic parameters for production, health, fertility and longevity traits in dairy cows. Animal. 2013 Jan 1; 7(1): 34–46. PubMed Abstract \| Publisher Full Text\n\nNor NM, Steeneveld W, Hogeveen H: The average culling rate of Dutch dairy herds over the years 2007 to 2010 and its association with herd reproduction, performance and health. J Dairy Res. 2014; 81(1): 1–8. PubMed Abstract \| Publisher Full Text\n\nMulu M, Adane M, Moges N: Review on process, advantages and disadvantage of artificial insemination in cattle. Int J Vet Sci Anim Husb. 2018; 3(6): 8–13.Reference Source\n\nMohammed A: Artificial Insemination and its Economical Significancy in Dairy Cattle: Review. Int J Res Stud Microbiol Biotechnol. 2018; 4(1). Publisher Full Text\n\nGomo C, Musari S, De Garine-Wichatitsky M, et al.: Detection of Brucella abortus in Chiredzi district in Zimbabwe. Onderstepoort J Vet Res. 2012 Feb 2 [cited 2019 Jul 19]; 79(1): 5. PubMed Abstract \| Publisher Full Text Reference Source\n\nCabrera VE: Economics of fertility in high-yielding dairy cows on confined TMR systems. Anim Consort. 2014 [cited 2021 Jun 28], SUPPL. 1; 8: 211–221. PubMed Abstract \| Publisher Full Text Reference Source\n\nFon Tebug S, Kasulo V, Chikagwa-Malunga S, et al.: Smallholder dairy production in Northern Malawi: production practices and constraints. Trop Anim Health Prod. 2011 [cited 2019 Jun 8]; (44): 55–62. PubMed Abstract \| Publisher Full Text Reference Source\n\nMohammadi GR, Sedighi A: Reasons for culling of Holstein dairy cows in Neishaboor area in northeastern Iran. Iran J Vet Res. 2009; 10(3): 278–282.\n\nPritchard T, Coffey M, Mrode R, et al.: Understanding the genetics of survival in dairy cows. J Dairy Sci. 2013 May 1; 96(5): 3296–3309. PubMed Abstract \| Publisher Full Text\n\nBernabucci U, Biffani S, Buggiotti L, et al.: The effects of heat stress in Italian Holstein dairy cattle. J Dairy Sci. 2014 Jan [cited 2019 Sep 14]; 97(1): 471–486. PubMed Abstract \| Publisher Full Text Reference Source" }	[ { "id": "96317", "date": "28 Oct 2021", "name": "Emmanuel Okechukwu Njoga", "expertise": [ "Reviewer Expertise Veterinary Science and Public Health" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper is well written and scientifically sound. The topic addressed important livestock diseases that are prevalent in South Africa, and also provided the disease control measures. Once the issues raised below are addressed, this paper will be approvable without reservations.\nIntroduction\nFirst paragraph, 6th sentence: rewrite to read \"The increased availability and access will enhance food security...\".\nSecond paragraph, 8th sentence: replace \"point “with \"points\".\nLiterature Search\nTable 1:\n\nA review paper on the causes of mortality and culling in dairy cows in South Africa should identify, mention, discuss/review the causes in Africa first before comparing or mentioning the causes in other continents. The local problems/causes in Africa may be different from that of other continents and hence need to be discussed. If the causes are the same globally, then it should be listed in the table so that it will be evident to the scientific community.\nTherefore, the authors should include published papers from Africa in the Table. Some suggested ones are included here, for South Africa,1 2 Ethiopia,3 4 Nigeria,5 Kenya, 6 and Senegal.7\nMajor Factors for Culling\nDiseases: the authors could include brucellosis as this is a major problem in the dairy industry. The zoonotic and economic (production loss) importance of it need to be discussed.\nMilk fever and ketosis: can the authors provide few lines on the pathogenesis/pathophysiology of ketosis? This might aid readers in their understanding of the condition, especially among those outside the field of veterinary and animal sciences.\nMastitis: third paragraph, what do the authors mean by “mechanical dynamics\"?\nCan any of the pathogens listed be zoonotically transmitted via the handling of an infected cow or the drinking of contaminated and unpasteurized milk?\nLameness: fourth sentence, replace \"sensitive” with \"importance\". Second paragraph: lameness is not a disease but a condition.\nHeat stress: third sentence, delete \"pregnancy “so that the sentence reads \"... can not conceive\".\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? Yes", "responses": [ { "c_id": "8024", "date": "01 Aug 2022", "name": "Ishmael Jaja", "role": "Author Response", "response": "We thank you for taking time to read our paper. The comments and input by reviewers have greatly improved our paper, for this we are grateful. Reviewer 1 S/N Reviewer’s comment Authors’ response Line number 1. First paragraph, 6th sentence: rewrite to read \"The increased availability and access will enhance food security...\". The 6th sentence has been corrected and written as per advice (p31) 2. Second paragraph, 8th sentence: replace \"point “with \"points\". Point has been edited to points (p58) 3. Table 1: A review paper on the causes of mortality and culling in dairy cows in South Africa should identify, mention, discuss/review the causes in Africa first before comparing or mentioning the causes in other continents. The local problems/causes in Africa may be different from that of other continents and hence need to be discussed. If the causes are the same globally, then it should be listed in the table so that it will be evident to the scientific community. Therefore, the authors should include published papers from Africa in the Table. Some suggested ones are included here, for South Africa,1 2 Ethiopia,3 4 Nigeria,5 Kenya, 6 and Senegal.7 An African perspective of culling and mortality has been duly incorporated in the work and table has been updated. (p86, 119) 4. Diseases: the authors could include brucellosis as this is a major problem in the dairy industry. The zoonotic and economic (production loss) importance of it need to be discussed. Brucellosis has been added and discussed in the review paper as per the reviewer’s advice. (p111-124) 5. Milk fever and ketosis: can the authors provide few lines on the pathogenesis/pathophysiology of ketosis? This might aid readers in their understanding of the condition, especially among those outside the field of veterinary and animal sciences. Brief pathogenesis of both milk fever and ketosis has been added to the review as per advice. (p127-172) 6. Mastitis: third paragraph, what do the authors mean by “mechanical dynamics\"? The paragraph has been rephrased thus removing mechanical dynamics. (p183) 7. Lameness: fourth sentence, replace \"sensitive” with \"importance\". Sensitive has been replaced with importance/ important. (p226, 227) 8. Second paragraph: lameness is not a disease but a condition. In instances whereby, lameness has been referred to as a disease instead of condition, corrections have been made. (p223) 9. Heat stress: third sentence, delete \"pregnancy “so that the sentence reads \"... can not conceive\". Pregnancy has been removed (p287)" } ] }, { "id": "116136", "date": "12 Jan 2022", "name": "Thankgod Onyiche", "expertise": [ "Reviewer Expertise Veterinary science with more emphasis on parasitilogy" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIntroduction\nThis section can be further improved by highlighting and citing adequate literature on the current needs and demands for milk, not only using South Africa as reference, but other countries from different regions within Africa and the rest of the world.\nIn line 2, page 3, could you kindly presents the statistics for the growth rate for 2017 at 3.9% before that of 2018 at 4.8%\nLiterature search\nIt will be interesting for the authors to clearly state the search outcome from each of the databases used. For example, web of science (n=36). To allow for reproducibility, it will be good if the authors presents this search strategy using the standard protocol for the key terms used in the searches to be in inverted commas: for example, “Culling”. If Boolean operators were used when searching in the databases, then the authors could kindly state this: for example, “AND”, “OR”.\nCould they also provide additional information on the date where they last search was carried out. Articles are being published daily, and potential readers should be made sure that the search was conducted properly and adequately, so that no article was erroneously left out.\n\nDiseases\nWith respect to diseases, to ensure orderly presentation of thoughts, the authors should discuss the various diseases broadly under two headings; infectious and non-infectious causes. Under the infectious causes, neosporiasis, mastitis etc. can be discussed.\nIn your discussion for bovine neosporiasis, ketosis and milk fever, I would like to see a more in depth discussion, the present treatment is too short.\nIn the last line of page 5, the expression “A similar trend was reported in similar studies” should be rephrased.\nIn the general discussion of economic losses due to mastitis, the authors must be consistent in terms of the currency value: for example, some of the losses were expressed in Euros while others was in US dollars. This should be standardised. Nonetheless, I appreciate that the base was in South Africa rand.\nOn page 7, under the sub theme “infertility”, the expression “Factors causing infertility and animals showing a diminished...' requires elaboration. What factors cause infertility? Please clarify.\nDue to paucity of studies in Africa on factors responsible for culling and mortality in farm animals, I will like to see how the authors relate their findings from studies in the western world to most probably what we have in Africa and the likely reasons why studies on this subject matter has not been published or brought to the front burner in this field.\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? Yes", "responses": [ { "c_id": "8025", "date": "01 Aug 2022", "name": "Ishmael Jaja", "role": "Author Response", "response": "We thank you for taking time to read our paper. The comments and input by reviewers have greatly improved our paper, for this we are grateful. To Reviewer 2 S/N Reviewer’s comment Authors’ response Line number 1. This section can be further improved by highlighting and citing adequate literature on the current needs and demands for milk, not only using South Africa as reference, but other countries from different regions within Africa and the rest of the world. The section has been further improved with statistics and trends from other African countries. (p39-45) 2. In line 2, page 3, could you kindly presents the statistics for the growth rate for 2017 at 3.9% before that of 2018 at 4.8%. Statistics for the growth from previous years have been included in the paragraph. (p27, 28) 3. It will be interesting for the authors to clearly state the search outcome from each of the databases used. For example, web of science (n=36). To allow for reproducibility, it will be good if the authors presents this search strategy using the standard protocol for the key terms used in the searches to be in inverted commas: for example, “Culling”. If Boolean operators were used when searching in the databases, then the authors could kindly state this: for example, “AND”, “OR”. The authors appreciate the advice and promise to opt for systematic review in the future in which the suggested approach will be in effect. We, however, wish to keep this work as a traditional literature synthesis. N/A 4 Could they also provide additional information on the date where they last search was carried out. Articles are being published daily, and potential readers should be made sure that the search was conducted properly and adequately, so that no article was erroneously left out. The authors appreciate the advice and promise to opt for systematic review in the future in which the suggested approach will be in effect. We, however, wish to keep this work as a traditional literature synthesis. N/A 5. With respect to diseases, to ensure orderly presentation of thoughts, the authors should discuss the various diseases broadly under two headings; infectious and non-infectious causes. Under the infectious causes, neosporiasis, mastitis etc. can be discussed. In your discussion for bovine neosporiasis, ketosis and milk fever, I would like to see a more in depth discussion, the present treatment is too short. The diseases have been divided into infectious and non-infectious diseases. Pathophysiology of the suggested diseases has been added to provide with more in-depth information. (p103, 125) 6. In the last line of page 5, the expression “A similar trend was reported in similar studies” should be rephrased. The expression has been revised. (p216) 7. In the general discussion of economic losses due to mastitis, the authors must be consistent in terms of the currency value: for example, some of the losses were expressed in Euros while others was in US dollars. This should be standardised. Nonetheless, I appreciate that the base was in South Africa rand. The currency for the losses due to culling has been corrected throughout the document. (p208 - 217) 8. On page 7, under the sub theme “infertility”, the expression “Factors causing infertility and animals showing a diminished...' requires elaboration. What factors cause infertility? Please clarify. Factors contributing infertility are covered. 311-315 9. Due to paucity of studies in Africa on factors responsible for culling and mortality in farm animals, I will like to see how the authors relate their findings from studies in the western world to most probably what we have in Africa and the likely reasons why studies on this subject matter has not been published or brought to the front burner in this field. An account has been given at the end of the conclusion and recommendation. (p427-430)" } ] } ]	1	https://f1000research.com/articles/10-1014
https://f1000research.com/articles/11-871/v1	29 Jul 22	{ "type": "Research Article", "title": "Risk factors of non-specific low back pain in a rural community of Bangladesh: A case-control study", "authors": [ "Md. Abu Shahin", "Rijwan Bhuiyan", "Rowsan Ara", "Md. Nazrul Islam", "Minhaj Rahim Choudhury", "Syed Atiqul Haq", "Mohammad Mostafa Zaman", "Rijwan Bhuiyan", "Rowsan Ara", "Md. Nazrul Islam", "Minhaj Rahim Choudhury", "Syed Atiqul Haq", "Mohammad Mostafa Zaman" ], "abstract": "Background: Data pertaining to risk factors of nonspecific low back pain (NSLBP) among rural Bangladeshi is scarce. This study explored the risk factors associated with NSLBP among rural Bangladeshi adults. Methods: A community-based study was done in Sonargaon Upazila of Narayanganj district of Bangladesh. A total of 343 NSLBP patients were recruited as cases, based on the Bangla version of Community oriented program for control of rheumatic diseases (COPCORD) questionnaire. An equal number of age and sex matched subjects without any rheumatic disease were recruited from the same community. A total of 15 probable factors were analyzed. Age-sex adjusted univariate and age-sex with 13 risk factors adjusted multivariate conditional logistic regression analyses were done. Results: The mean age of the participants was 33.1 years old (standard deviation: 9.5). Out of 13 risk factors, history of chronic disease (OR 2.0, 95% CI 1.2 – 3.4), prolonged sitting (OR 4.6, 95% CI 2.0 – 11.0), squatting (OR 7.2, 95% CI 3.2 – 16.0), bending of the waist (OR 3.7, 95% CI 1.8 – 7.6), regular lifting or carrying a heavy load (OR 9.2, 95% CI 2.2 – 39.7), prolonged standing (OR 5.8, 95% CI 1.9 – 17.7), occupation related to strenuous physical activity (OR 0.2, 95% CI 0.1 – 0.8), overweight (body mass index >=25 kg/m2) (OR 3.1, 95% CI 1.8 – 5.2) and depression (OR 2.2, 95% CI 1.4 – 3.6) were found to be significantly associated with NSLBP. Conclusions: The study generated knowledge on associated risk factors for NSLBP in rural people of Bangladesh that may facilitate an evidence-based intervention for the target group.", "keywords": [ "Risk factors", "nonspecific low back pain", "rural", "COPCORD", "Bangladesh" ], "content": "Introduction\n\nLow back pain (LBP) has become one of the major public health challenges1 because of its high prevalence2 and association with years lived with disability,3 job absenteeism4 and declining overall quality of life for decades. It imposes a significant medical burden and economic expense as well.5 Evidence support that most people have to suffer symptoms of back pain at some point in their lives.6 The prevalence of LBP in low- and middle-income countries (LMICs) has been identified as high.7 The national level survey of Bangladesh reported that the prevalence of LBP was 18.6%.8 However, in most of the (85%) cases a specific diagnosis of LBP cannot be obtained, as there are no recognizable pathologies such as infection, tumor, osteoporosis, fracture, structural deformity, and inflammatory diseases responsible for LBP. Such cases are referred to as non-specific low back pain (NSLBP).9,10 The prevalence of NSLBP was reported to be 6.6, 9.9 and 9.2% in the rural, urban slum and urban affluent community, respectively, in another small-scale study.11\n\nAlthough the causes of NSLBP is unknown, but there are some known factors (modifiable or non-modifiable) that are associated with NSLBP. Addressing those factors are the primary concern to prevent NSLBP.12,13 Data pertaining to risk factors of NSLBP among rural Bangladeshi is scarce. This study explored the risk factors associated with NSLBP among rural Bangladeshi adults.\n\n\nMethods\n\nThis study adhered to the Declaration of Helsinki, and we assured that the data would be used for scientific research only. Participants were informed in detail about the nature of the study. Spontaneous written consent was taken from the participants and Bangla informed consent form was attached with the questionnaire. Each participant enjoyed the right to participate or refuse to participation. They could withdraw their participations from the study at any stage by contacting the principal investigator and citing their ID number or name. Data taken from the participants were regarded as confidential and kept locked under the principal investigator. The participant’s data were kept anonymous in datasets and were tracked by using unique ID numbers. If any study subject became sick during the survey, proper advice and clinical management was given. Ethical clearance was obtained from the Ethical Review Committee of Bangabandhu Sheikh Mujib Medical University (BSMMU) in 2011 (Memo number: BSMMU/2011/6045) before starting data collection.\n\nThis case control study was carried out during the period of June to September 2011 at Sonargaon Upazila, Narayanganj district, consisting of 19 small villages located approximately 35 km from the capital city. The data collection period was from July to August 2011. Due to the presence of some industries nearby this predominant rural area had some influence of urbanization. There were a diverse range of occupations represented, including agricultural workers, weavers, garment workers, salesmen, and so on. All adults aged 18 years old or above from both sexes were considered as eligible population.\n\nAll the eligible adults of the study area were requested to attend the satellite Community oriented program for control of rheumatic diseases (COPCORD) camp according to a roster. Out of 5,005 eligible adults aged 18 years old and above, 4,850 participated in the camp and the other 155 were non-responsive. At the camp, a Bangla version of the World Health Organization (WHO)-International League of Associations for Rheumatology (ILAR) COPCORD Core English questionnaire was administered by the field enumerators.14,15 By using WHO-ILAR COPCORD questionnaire, 1,315 patients were identified who had any rheumatic condition and the rest of the 3,535 patients had no rheumatic conditions. Those who were identified as rheumatic patients, of them 494 had LBP and they were sent to the rheumatologists. The rest of the 821 patients had rheumatic conditions other than LBP and were excluded from the study. Among the 494 LBP patients, 343 were clinically diagnosed as NSLBP patients using Asia Pacific League of Associations for Rheumatology (APLAR)-COPCORD questionnaire for NSLBP16 by rheumatologists and considered as cases for the study. NSLBP is defined as low back pain not attributable to a recognizable, known specific pathology (e.g., infection, tumor, osteoporosis, lumbar spine fracture, structural deformity, inflammatory disorder, radicular syndrome, or cauda equina syndrome).17 To avoid any potential source of bias the diagnosis of NSLBP was made by exclusion of specific pathology with proper history taking, physical examination, imaging and sometimes opinion of expert rheumatologists. In case of any diagnostic difficulties investigators discussed among themselves to decide. Sometimes assistance of radiological investigations was taken. Those who had NSLBP but also had co-morbid illnesses such as symptomatic bronchial asthma, ischemic heart disease and intellectual disability were excluded. The rest of the 151 patients had LBP due to secondary causes and were excluded from the study.\n\nFrom the patients who had no rheumatic conditions as confirmed by WHO-ILAR COPCORD questionnaire (n=3,535), 343 were recruited as controls of the study by matching with sex and age with ±5 years. A second recall of those who did not report to the camp was done to finally declare them as non-respondents. Details of the selection process is given in Figure 1. Questionnaires, blank consent forms and study information can be found as Extended data.18\n\nWHO-ILAR COPCORD: World Health Organization-International League of Associations for Rheumatology Community oriented program for control of rheumatic diseases. APLAR-COPCORD: Asia Pacific League of Associations for Rheumatology-Community oriented program for control of rheumatic diseases.\n\nWe used community specific APLAR-COPCORD questionnaire validated by Siddiqui et al.16\n\nHistory of chronic disease: Respondents were asked whether they are currently taking any medication for diabetes and/or hypertension, or have they ever been said to have raised blood glucose or blood pressure by any physician or qualified health care worker. If they said ‘yes’ to any of the above two then they were considered as having a history of chronic disease.16\n\nHistory of trauma: Respondents were asked whether they had any major accident/physical trauma over the last 12 months.16\n\nProlonged continuous sitting: Respondents were asked whether they have to sit for ≥ 2 hours/day continuously irrespective of their daily activities or occupation over the last 12 months. Such as desk workers, driver, tailors.16\n\nSquatting: Respondents were asked whether they have to squat or sit bending knee for ≥ 1 hours/day continuously irrespective of their daily activities or occupation over the last 12 months. Such activities include sitting without stool/floor or yard scraping/wiping/cooking etc.16\n\nBending of waist: Respondents were asked whether they have to bend their waist for ≥ 1 hours/day continuously irrespective of their daily activities or occupation over the last 12 months. Such as agricultural work (without lifting weight), manual weeding, gardening, fishing, laundering, cobbling, potter, blacksmith, weaving, manual brick crushing, carpenter, plasterer, corpse worker, manual brick maker, coppersmith etc.16\n\nRegular lifting or carrying heavy load: Respondents were asked whether they have to lift or carry heavy load regularly irrespective of their daily activities or occupation over the last 12 months. Such as porters, day laborer, construction worker, agriculture work, lifting water filled jar, cultivation in hilly land, peddler, tea plucking, industrial worker, brick crushing etc.16\n\nProlong standing: Respondents were asked whether they have to stand for ≥ 2 hours/day continuously irrespective of their daily activities or occupation over the last 12 months. Such as seals man, nurse, street vendor, barber, security guards, bus helper/conductors, traffic police, teacher, receptionist, health worker, etc.16\n\nDepression: Depression in respondents was measured using the General Health Questionnaire (GHQ-12)19 consisting of 12 items, each of which is evaluated by four indices. The GHQ-12 has satisfactory reliability with good sensitivity and specificity. Four-point Likert scoring method was used. Scoring ranged from 0 to 36. A score of >15 was considered as depressed.\n\nData were analyzed using Epi Info 7 software (RRID:SCR_021682). The sociodemographic characteristics and risk variables were presented in terms of numbers and percentages. Age and body mass index were described using the mean and standard deviation. A total of 12 factors such as, ‘age’, ‘sex’, ‘history of chronic disease’, ‘history of trauma’, ‘prolonged continuous sitting ≥ 2 hours/day’, ‘squatting ≥ 1 hour/day’, ‘bending of waist ≥ 1 hour/day’, ‘regular lifting or carrying heavy load’, ‘prolong standing ≥ 2 hours/day’, ‘Strenuous physical activity’, ‘overweight (body mass index ≥ 25 Kg/m2)’, and ‘depression’ were examined for their relationship with NSLBP. The risk factors were identified using conditional logistic regression analyses and are shown as odds ratios with 95% confidence intervals. All missing data were dropped from the analysis. STROBE checklist for case-control study was followed to prepare the manuscript.20\n\n\nResults\n\nAmong the 686 participants, 343 were cases (have NSLBP) and 343 were controls (no rheumatic diseases). The mean age of the participants was 33.2 years old (standard deviation: 9.4). Over two-thirds (69.1%) were women, four in 10 (40%) had no formal education and around 91% were married. Around 11% of participants had an occupation related to various laborious work and more than one-fifth (21%) used any form of tobacco (Table 1).21\n\n P < 0.05.\n\n** P < 0.01.\n\na All the risk factors mentioned in the table were entered into the model simultaneously age and sex were entered as matching variables.\n\nb Diabetes and hypertension.\n\nc Desk workers, driver, tailors etc.\n\nd Sitting without stool or on floor or yard scraping/swapping floor/cooking etc.\n\ne Agricultural work (without lifting weight), manual weeding, gardening, fishing, laundering, cobbling, potter, blacksmith, weaving, manual brick crushing, carpenter, plasterer, corpse worker, manual brick maker, coppersmith etc.\n\nf Salesman, nurse, street vendor, barber, security guards, bus helper/conductors, traffic police, schoolteacher, etc.\n\ng Cultivator, day laborer, mason, rickshaw/van driver or any other hard worker.\n\nh General Health Questionnaire (GHQ-12): score ≤15 normal and >15 depressed out of 36.\n\nOverall, 23% of participants had a history of chronic disease and around 3.4% had a history of trauma. One in every 10 were involved in prolonged continuous sitting (>2 hours/day) and six out of 10 individuals engaged in prolonged squatting position (≥1 hour/day). More than one-fifth (22%) were bent at the waist at least 1 hour/day. Around 5% and 8% were involved in regular lifting or carrying heavy load and prolonged standing (at least 2 hours/day), respectively. Over a quarter (31%) were overweight (body mass index ≥25 kg/m2). Around one-third reported experiencing ‘distress’ in general health question (GHQ-12) (Table 1).\n\nFrom the univariate analysis (age-sex matched) 11 of the 13 risk factors, such as education (OR 1.7, 95% CI 1.2 – 2.4), marital status (OR 3.3, 95% CI 1.6 – 6.7), history of chronic disease (OR 3.3, 95% CI 2.2 – 5.1), history of trauma (OR 5.7, 95% CI 1.7 – 19.3), prolonged continuous sitting (OR 1.7, 95% CI 1.0 – 2.7), squatting (OR 2.3, 95% CI 1.5 – 3.7), bending of waist (OR 1.9, 95% CI 1.3 – 2.8), regular lifting or carrying heavy load (OR 2.7, 95% CI 1.2 – 5.7), prolonged standing (OR 2.1, 95% CI 1.1 – 3.8), overweight (body mass index ≥25 kg/m2) (OR 2.7, 95% CI 1.8 – 3.9) and depression (OR 2.0, 95% CI 1.4 – 2.9) were found to be significantly associated. However, after adding 13 other risk factors to the statistical model, nine risk factors were found to be significantly associated with NSLBP. These were history of chronic disease (OR 2.0, 95% CI 1.2 – 3.4), prolonged sitting (OR 4.6, 95% CI 2.0 – 11.0), squatting (OR 7.2, 95% CI 3.2 – 16.0), bending of waist (OR 3.7, 95% CI 1.8 – 7.6), regular lifting or carrying heavy load (OR 9.2, 95% CI 2.2 – 39.7), prolonged standing (OR 5.8, 95% CI 1.9 – 17.7), occupation related to strenuous physical activity (OR 0.2, 95% CI 0.1 – 0.8), overweight (body mass index ≥25 kg/m2) (OR 3.1, 95% CI 1.8 – 5.2) and depression (OR 2.2, 95% CI 1.4 – 3.6) were found to be significantly associated with NSLBP (Table 1).\n\n\nDiscussion\n\nIn this community-based case control study, several risk factors were found to be associated with LBP. Several studies reported LBP as one of the most common causes of hospital visits and the leading cause of work absences.3 Multiple studies worked with different cohorts suffering from LBP and reported causal relationships.2 The prevalence of NSLBP was 6.6–9.2% in different communities of Bangladesh.11 There are many proposed risk factors associated with LBP in the general population.22\n\nLBP is a common problem in diabetic patients in terms of intensity, frequency and functional level of disability.23 The current study observed that chronic diseases, such as diabetes mellitus and hypertension, had an increased risk of developing NSLBP. LBP in diabetic individuals may be due to diabetic neuropathy, resulting in symptoms such as pain, tingling, or numbness. It is a problem that may affect as many as 50% of people with diabetes and can lead to chronic back pain.24 In addition, acute trauma can contribute the development of LBP.25 Its contribution can be up to 7%. Our findings in the present study are also similar in nature.\n\nVarious body postures like prolonged sitting, standing, bending of waist, pulling/pushing, frequent weightlifting have been revealed as statistically significant risk factors for back pain.26 One study showed body positions like sitting more than 2 hours per day, squatting more than 30 minutes are associated with LBP.27 Bidassie et al., found that work-related postures like prolonged squatting or bending of the waist were significantly associated with LBP.28 Occupational exposure is a highly preventable risk factor common in working populations with high physical loading on the back and possibly also high psychosocial strain.29 Studies reporting on manual material handling, such as lifting and carrying loads without mechanical assistance, have shown them as risk factors for LBP.30 The meta-analysis and subsequent pooled risk estimates demonstrated that intensity and frequency of lifting were significantly associated with annual incidence of LBP.31 Another study has also shown that workers who perform repetitive weightlifting experienced LBP more frequently.32 In this study, we also found that regular lifting or load carrying were significantly associated with LBP. This association may be due to repeated heavy lifting, or a sudden awkward movement that can strain back muscles and spinal ligaments. A previous study found that prolonged standing without freedom to sit was associated with LBP.33 In this study, we also found that prolonged standing >2 hours were significantly associated with LBP.\n\nA previous study found that LBP is more common in jobs that require heavy physical activity.34 Different studies have found significant relationships between body mass index and LBP.35 This study also found a significant association between obesity and LBP. Pain may be because the pelvis of an obese individual is pulled forward, and thus the lower back becomes strained. A strained lower back will produce symptoms such as pain, soreness, and tightness.36 Another study done on work history and work environment factors showed that work dissatisfaction and life stress were important factors influencing LBP prevalence.37–39 In this study we found that subjects with evidence of psychological distress had a higher risk of developing NSLBP.\n\nTo the best of our knowledge, so far, our study is the first community-based case-control study on NSLBP conducted in Bangladesh. This study attempted to cover all possible aspects of etiological factors. Age and sex matched cases and control subjects were enrolled. Culturally adapted and validated tools were used. However, this study also has weaknesses. The study area was selected purposively and its proximity to the BSMMU may not represent rural Bangladeshi population at large. Furthermore, the population was selected purposively. Performing imaging was very difficult because the diagnostic centers were far away from the study area, and we were limited by fund constraints. Thus, X-rays were only performed in a few of the cases.\n\n\nConclusions\n\nIn this study, some risk factors were found to be strongly associated with LBP, including history of trauma, history of chronic disease, and prolonged continuous sitting, squatting, bending, standing, regular lifting and carrying load. While some variables were weakly associated with NSLBP, such as marital status, vigorous physical activity and obesity. Some factors were not associated with LBP, including religion status, smoking history, and previous history of cesarean section. The results of this study generated knowledge about different risk factors associated with NSLBP and open up possibilities for evidence-based intervention programs to prevent the development of NSLBP. A non-communicable disease control program may finally help to reduce the burden of NSLBP in the community.\n\n\nData availability\n\nZenodo: Risk Factors of Non-specific Low Back Pain in a Rural Community of Bangladesh. https://doi.org/10.5281/zenodo.6709850.21\n\nZenodo: Risk Factors of Non-specific Low Back Pain in a Rural Community of Bangladesh (extended data). https://doi.org/10.5281/zenodo.6824159.18\n\nThis project contains the following extended data:\n\n- Questionnaire Part 1.pdf\n\n- Questionnaire Part 2.pdf\n\n- Questionnaire Part 3.pdf\n\n- Copcord Ph I English.pdf\n\n- Copcord Ph II English.pdf\n\n\nReporting guidelines\n\nZenodo: STROBE checklist for ‘Risk factors of non-specific low back pain in a rural community of Bangladesh: A case-control study’. https://doi.org/10.5281/zenodo.6823445.20\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "Acknowledgements\n\nWe acknowledge the local health administrations of the survey area, local people of the survey area, and the participants of the survey.\n\n\nReferences\n\nBuchbinder R, van Tulder M , Öberg B, et al.: Low back pain: a call for action. Lancet. 2018 Jun; 391(10137): 2384–2388. Publisher Full Text\n\nHoy D, Bain C, Williams G, et al.: A systematic review of the global prevalence of low back pain. Arthritis Rheum. 2012 Jun; 64(6): 2028–2037. Publisher Full Text\n\nVos T, Flaxman AD, Naghavi M, et al.: Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012 Dec; 380(9859): 2163–2196. PubMed Abstract \| Publisher Full Text\n\nDriscoll T, Jacklyn G, Orchard J, et al.: The global burden of occupationally related low back pain: estimates from the Global Burden of Disease 2010 study. Ann. Rheum. Dis. 2014 Jun; 73(6): 975–981. PubMed Abstract \| Publisher Full Text\n\nHoy D, March L, Brooks P, et al.: The global burden of low back pain: estimates from the Global Burden of Disease 2010 study. Ann. Rheum. Dis. 2014 Jun; 73(6): 968–974. PubMed Abstract \| Publisher Full Text\n\nFatoye F, Gebrye T, Odeyemi I: Real-world incidence and prevalence of low back pain using routinely collected data. Rheumatol. Int. 2019 Apr; 39(4): 619–626. PubMed Abstract \| Publisher Full Text\n\nSharma S, McAuley JH: Low Back Pain in Low- and Middle-Income Countries, Part 1: The Problem. J. Orthop. Sports Phys. Ther. 2022 May; 52(5): 233–235. PubMed Abstract \| Publisher Full Text\n\nZahid-Al-Quadir A, Zaman MM, Ahmed S, et al.: Prevalence of musculoskeletal conditions and related disabilities in Bangladeshi adults: a cross-sectional national survey. BMC Rheumatology. 2020 Dec; 4(1): 69–69. PubMed Abstract \| Publisher Full Text\n\nO’Sullivan P: Diagnosis and classification of chronic low back pain disorders: Maladaptive movement and motor control impairments as underlying mechanism. Man. Ther. 2005 Nov; 10(4): 242–255. PubMed Abstract \| Publisher Full Text\n\nMaher C, Underwood M, Buchbinder R: Non-specific low back pain. Lancet. 2017 Feb; 389(10070): 736–747. Publisher Full Text\n\nHaq SA, Darmawan J, Islam MN, et al.: Prevalence of rheumatic diseases and associated outcomes in rural and urban communities in Bangladesh: a COPCORD study. J. Rheumatol. 2005 Feb; 32(2): 348–353. PubMed Abstract\n\nSidiq M, Alenazi W, Kashoo FZ, et al.: Prevalence of non-specific chronic low-back pain and risk factors among male soldiers in Saudi Arabia. PeerJ. 2021 Oct; 9: e12249–e12249. PubMed Abstract \| Publisher Full Text\n\nManchikanti L: Epidemiology of low back pain. Pain Physician. 2000 Apr; 3(2): 167–192. PubMed Abstract \| Publisher Full Text\n\nIslam ME, Ahmed S, Shahin MA, et al.: Cross-cultural adaptation and validation of revised WHO-ILAR-COPCORD core English questionnaire translated to Bangla. Int. J. Rheum. Dis. 2021 Sep; 24(9): 1153–1166.\n\nWHO-ILAR: Community Oriented Programme for Control of Rheumatic Diseases.\n\nSiddiqui MNA, Islam MN, Haq SA, et al.: Development of APLAR-COPCORD Core Questionnaire for Identification of Risk Factors for Non Specific Low Back Pain. TAJ: Journal of Teachers Association. 2018 Nov; 24(2): 85–90. Publisher Full Text\n\nNordin M, Balagué F, Cedraschi C: Nonspecific Lower-back Pain. Clin. Orthop. Relat. Res. 2006 Feb; 443: 156–167. Publisher Full Text\n\nShahin MA, Bhuiyan R, Ara R, et al.: Risk Factors of Non-specific Low Back Pain in a Rural Community of Bangladesh (extended data). [Dataset]. Zenodo.2022. Publisher Full Text\n\nLiang Y, Wang L, Yin X: The factor structure of the 12-item general health questionnaire (GHQ-12) in young Chinese civil servants. Health Qual. Life Outcomes. 2016 Dec; 14(1): 136–136. Publisher Full Text\n\nShahin MA, Bhuiyan R, Ara R, et al.: STROBE Checklist of Risk factors of non-specific low back pain in a rural community of Bangladesh: A case-control study. [Dataset]. Zenodo.2022. Publisher Full Text\n\nShahin MA, Bhuiyan R, Ara R, et al.: Risk Factors of Non-specific Low Back Pain in a Rural Community of Bangladesh. [Dataset]. Zenodo.2022. Publisher Full Text\n\nHartvigsen J:Risk factors for low back and neck pain: an introduction to clinical epidemiology and review of commonly suspected risk factors. Principles and practice of chiropractic. 3rd ed.New York:McGraw-Hill;2005; p. 471–478.\n\nEivazi M, Abadi L: Low back pain in diabetes mellitus and importance of preventive approach. Health Promot. Perspect. 2012; 2(1): 80–88.\n\nRinaldo L, McCutcheon BA, Gilder H, et al.: Diabetes and Back Pain: Markers of Diabetes Disease Progression Are Associated With Chronic Back Pain. Clinical Diabetes. 2017 Jul; 35(3): 126–131. PubMed Abstract \| Publisher Full Text\n\nHincapié CA, Cassidy JD, Côté P: Is a history of work-related low back injury associated with prevalent low back pain and depression in the general population? BMC Musculoskelet. Disord. 2008 Dec; 9(1): 22–22. PubMed Abstract \| Publisher Full Text\n\nDave VR, Khanpara HJ, Shukla RP, et al.: Risk factors of occupation related back pain and neck pain among patients attending tertiary care hospital, Ahmedabad, India. J. Prev. Med. Hyg. 2019 Dec; 60(4): E419–E427.\n\nSweetman BJ, Anderson JAD, Dalton ER: The relationships between little-finger mobility, lumbar mobility, straight-leg raising, and low-back pain. Rheumatology. 1974; 13(4): 161–166. PubMed Abstract \| Publisher Full Text\n\nBidassie B, McGlothlin JD, Mena I, et al.: Evaluation of lifestyle risk factors and job status associated with back injuries among employees at a mid-western university. Appl. Ergon. 2010 Jan; 41(1): 106–114. PubMed Abstract \| Publisher Full Text\n\nPunnett L, Prüss-Ütün A, Nelson DI, et al.: Estimating the global burden of low back pain attributable to combined occupational exposures. Am. J. Ind. Med. 2005 Dec; 48(6): 459–469. PubMed Abstract \| Publisher Full Text\n\nAstrand NE: Medical, psychological, and social factors associated with back abnormalities and self reported back pain: a cross sectional study of male employees in a Swedish pulp and paper industry. Occup. Environ. Med. 1987 May; 44(5): 327–336. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCoenen P, Gouttebarge V, van der Burght ASAM , et al.: The effect of lifting during work on low back pain: a health impact assessment based on a meta-analysis. Occup. Environ. Med. 2014 Dec; 71(12): 871–877. PubMed Abstract \| Publisher Full Text\n\nBergquist-Ullman M, Larsson U: Acute Low Back Pain in Industry: A Controlled Prospective Study with Special Reference to Therapy and Confounding Factors. Acta Orthop. Scand. 1977 Dec; 48(sup170): 1–117. PubMed Abstract \| Publisher Full Text\n\nTissot F, Messing K, Stock S: Studying the relationship between low back pain and working postures among those who stand and those who sit most of the working day. Ergonomics. 2009 Nov; 52(11): 1402–1418. PubMed Abstract \| Publisher Full Text\n\nAmorim AB, Simic M, Pappas E, et al.: Is occupational or leisure physical activity associated with low back pain? Insights from a cross-sectional study of 1059 participants. Braz. J. Phys. Ther. 2019 May; 23(3): 257–265. PubMed Abstract \| Publisher Full Text\n\nTaylor ED, Theim KR, Mirch MC, et al.: Orthopedic Complications of Overweight in Children and Adolescents. Pediatrics. 2006 Jun; 117(6): 2167–2174. PubMed Abstract \| Publisher Full Text\n\nIbrahimiKacuri D, Murtezani A, Rrecaj S, et al.: Low Back Pain and Obesity. Med. Arch. 2015; 69(2): 114–114.\n\nTucer B, Yalcin BM, Ozturk A, et al.: Risk factors for low back pain and its relation with pain related disability and depression in a Turkish sample. Turk. Neurosurg. 2009 Oct; 19(4): 327–332. PubMed Abstract\n\nHung CI, Liu CY, Fu TS: Depression: An important factor associated with disability among patients with chronic low back pain. Int. J. Psychiatry Med. 2015 Apr; 49(3): 187–198. Publisher Full Text\n\nFeyer AM, Herbison P, Williamson AM, et al.: The role of physical and psychological factors in occupational low back pain: a prospective cohort study. Occup. Environ. Med. 2000 Feb; 57(2): 116–120. PubMed Abstract \| Publisher Full Text \| Free Full Text" }	[ { "id": "164964", "date": "17 Mar 2023", "name": "Abhay Bang", "expertise": [ "Reviewer Expertise Mother and child health", "Tribal Health", "Alcohol and Tobacco control", "Musculoskeletal diseases", "Youth training towards social change making", "Low back pain." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nWe congratulate the authors for conducting a much-needed study addressing a disease that is a significant public health issue.\nSummary of the article: A community-based case-control study was conducted in 2011, with non-specific low back pain as cases and age and gender-matched controls. Cases to control ratio is 1:1. Selection and exclusion criteria of the cases and controls are mentioned. Exposure variable ascertainment is appropriate with variables like chronic diseases, history of trauma, prolonged sitting and standing, squatting, bending at the waist, tobacco use, overweight, distress, strenuous physical activity, and carrying a heavy load. Study population aged between 18-55 years. The odds ratio from conditional logistic regression is significantly higher among the cases than the controls establishing the risk factors of non-specific low back pain.\nThe methods and analysis provided have some gaps:\nThe sample size calculation for the study is not mentioned.\n\nCo-morbid conditions like bronchial asthma and ischemic heart diseases are excluded in selecting cases. However, these conditions can also contribute to chronic illness in any individual.\n\nIn the exposure ascertainment variable, “Depression” is measured using General Health Questionnaire 12; the same is mentioned the table one results. In the textual interpretation of results, the term 'distress' is used. The terms 'depression' and 'distress' are used interchangeably. GHQ 12 measures nonpsychotic mental health problems associated with depression, anxiety, somatic symptoms, and social dysfunction, indicating psychological distress.\n\nThe comprehensive clinical examination used to diagnose the cases is commendable. Use of radiological investigation when in need might have led to nonuniformity in the diagnosis. Laboratory tests were not used to identify secondary causes of low back pain.\n\nStatistical analysis and its interpretation:\nIn table one, the variable “Occupation related to strenuous physical activity” Odds Ratio is 0.2 [0.1-0.8] for the laborious job against the reference of Other jobs [non-laborious jobs]. In the textual interpretation part of the results, the authors have presented laborious jobs needing strenuous physical activity as one of the risk factors of non-specific LBP.\nAn odds ratio of less than one indicates that the exposure variable is protective against the outcome or negates the variable being the risk factors. For example, the odds ratio of 0.2, interpreted as strenuous physical activity, is not a risk factor for non-specific back pain compared to non-laborious jobs. Authors must check the possibility of a typo or suitably discuss the results and interpretation.\n\nSome odd Features need explanations:\n\nHow was a participation rate of 97% (4850/5005) achieved especially of the asymptomatics?\n\nWhy was publication delayed, when the data were collected in 2011?\n\nThe age group {33 years, SD 9.5] is lower than expected. Backache is more common in old age.\n\nNearly 10% is the prevalence of LBP in this community [494 cases of LBP], which is much lesser than 18% in Bangladesh [as mentioned in the Introduction].\n\nAmong the listed authors, four have contributed only to writing, reviewing, and editing. If they did not play any role in planning, data collection, or analysis - are they eligible to be included as the authors?\n\nHow was the list of population size (5,005) selected? What is the source of the numbers?\n\nIf feasible, there are additional pointers for authors to incorporate for the better utility of the peers interested in the topics:\nTo mention the severity of the low back pain and the strength of its association with the risk factors.\n\nAs the occupation and activities indulged are diverse across the age groups, subgroup analysis of different age groups can help plan interventions targeting the specific risk factors.\n\nSimilarly, gender-based subgroup analysis helps to identify risk factors gender specific. The number of risk factors per individual helps understand the severity and existence of multiple risk factors in a single individual and their relationship with the severity of low back pain.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "297348", "date": "30 Jul 2024", "name": "Solomon Berhanu Mogas", "expertise": [ "Reviewer Expertise I have experience and interest on chronic disease", "epidemiological and public health researches" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe issue raised in the manuscript is a significant public health importance condition A community based age-sex matched case control study was conducted in a rural community of Bangladesh to assess the risk factors of non-specific LBP in 2011. The study was conducted in 2011 but, submitted for publication is too late, which is after more than 10 years. the literatures used must consider the time variation and some lacks these issue. The findings were not interpreted well and the discussion needs detail and specific approach for separate factors to show the possible explanation and implication of the factors. Overall, the importance of considering the paper for indexing is not significant due to late for submission for publication. There might be a lot change in those time periods.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-871
https://f1000research.com/articles/11-870/v1	29 Jul 22	{ "type": "Research Article", "title": "Prevalence of Fabry disease in Iraq", "authors": [ "Mohammed Younus Naji Al Atbee", "Ali Abdulmajid Dyab Allawi", "Safa E. Almukhtar", "Jawad Ibrahim Rasheed", "Faten Abdulghani Hammoudi", "Hala Sami Tuama", "Mohammed Esam Mohammed Al Baldawi", "Hasan Al Farhan", "Ala Sh. Ali", "Ali Abdulmajid Dyab Allawi", "Safa E. Almukhtar", "Jawad Ibrahim Rasheed", "Faten Abdulghani Hammoudi", "Hala Sami Tuama", "Mohammed Esam Mohammed Al Baldawi", "Hasan Al Farhan", "Ala Sh. Ali" ], "abstract": "Background: Fabry disease occurs due to mutations in the α-galactosidase A (GLA) gene present in the X-chromosome, which results in α-galactosidase A (α-GAL A) enzyme deficiency, leading to the intracellular accumulation of glycosphingolipids like globotriaosylceramide (Gb3). It involves multiorgan dysfunction, particularly affecting kidneys, heart, and central and peripheral nervous system. We intended to evaluate the prevalence of Fabry disease in various regions of Iraq along with the clinical manifestations. Methods: This cross-sectional multi-center study was conducted in Iraq with 1148 patients with variable presentations from January 2018 to June 2022. The demography, patient medical and family history were recorded. Routine clinical investigations were performed along with some specific assessments. Lysosomal α-GAL A enzyme activity was determined using the dried blood spot test followed by tandem mass spectrometry, where values between 200–2000 pmol/spot20 h were considered normal. Any patient with α-GAL A activity <100 pmol/spot20h was sent for genetic testing for confirmation of the diagnosis. Statistical analysis of data involved Pearson’s chi-squared test. Results: In total, 17 patients had Fabry disease, with a 16:1 male:female ratio. The disorder was predominant in the 10–30-year age group. Renal dysfunction was the dominant clinical manifestation (82.3%), followed by peripheral neuropathy (35.3%), angiokeratoma (29.4%), corneal verticillate (23.5%), and left ventricular hypertrophy (17.6%). The prevalence of Fabry disease was highest in north Iraq, followed by middle and south regions. Conclusions: A prompt and timely diagnosis of Fabry disease is the cornerstone for preventing complications, especially renal and cardiac involvement.", "keywords": [ "Fabry disease", "α-galactosidase A", "angiokeratoma", "proteinuria", "renal insufficiency", "left ventricular hypertrophy" ], "content": "Introduction\n\nFabry disease is a hereditary disorder that encompasses the clinical and the pathologic indications of the alpha-galactosidase A (α-GAL A) enzyme deficiency, which results in the intracellular deposition of neutral glycosphingolipids. An aberration in the alpha-galactosidase-A gene (GLA-gene), found on the long arm of the X-chromosome (Xq22.1), is responsible for the disease.1\n\nThis disease leads to the progressive intralysosomal deposition of globotriaosylceramide (Gb3), also known as ceramide trihexoside (CTH), in different cell types and body fluids, with red blood cells (RBCs) being an exception. Globotriaosylceramide accumulation is predominantly high in the diseased kidney. An important component of the plasma membranes and the membranes of the intracellular organelles are the glycosphingolipids. The intracellular transportation of glycosphingolipids is mediated by apolipoproteins. The accumulated glycosphingolipids in Fabry disease and those found in normal tissues are similar.2,3\n\nClassic Fabry disease is defined as a clinically heterogeneous sand multisystem disorder that involves the kidneys, heart, and central and peripheral nervous systems.3,4 Predictably, Fabry disease being an X-linked disorder, severe clinical presentations have been identified in hemizygous males, while heterozygous females express widely variable but usually less severe disease course.3–5 The initial signs in affected males become apparent in childhood and early adolescence; the symptoms comprise of parenthesis accompanied by episodic pain attacks in the hands and feet. The disease course is variable, which commonly leads to chronic kidney disease during 30–60 years of age. In women, severe Fabry disease can result due to considerable inactivation of the X chromosome where the normal α-Gal A allele is located.4,5 Although early renal defect involves an impaired ability to concentrate urine, the nephropathy of Fabry disease arises around age 30 and typically manifests as mild to moderate proteinuria, and occasionally with microhematuria; however, nephrotic syndrome is uncommon.5–7 A high concentration of glycosphingolipids is present in the urine, which appears as oval fat bodies with a Maltese cross configuration when viewed under a polarizing microscope.7,8 Renal function deteriorates gradually, and hypertension and chronic kidney disease develop during 40–50 years of age. Although mild renal involvement is commonly observed in heterozygous women, few of them may develop chronic kidney disease.9\n\nLight microscopy shows noticeable glomerular changes, in addition to irregularities in the tubular epithelium and vessels. The enlarged glomerular visceral epithelial cells obtained during processing contain glycosphingolipids that appear as small, clear vacuoles. These vacuoles may be present in the epithelial cells of the distal convoluted tubule and loop of Henle and the parietal epithelial cells; however, they are rarely found in the proximal tubular epithelial cells, mesangial cells, and glomerular endothelial cells. These irregularities result in increasing segmental and global glomerulosclerosis.8,10,11 Additionally, vacuoles are reported in the endothelial cells and the smooth muscle cells of arteries and arterioles. Abundant inclusions were observed within the lysosomes, especially within the visceral epithelial cells under electron microscopy. Typically, the inclusions, also known as the myelin figures, are round and composed of concentric layers of dense material that are separated by clear spaces. These concentric layers arranged in parallel are known as zebra bodies. Although inclusions are present in heterozygous women, their number is less in comparison to the affected men. Typical inclusion bodies are observed in the renal tubular cells.12–14 In all likelihood, the progression of Fabry nephropathy to chronic kidney disease results from two parallel processes, such as visceral epithelial cell defect and progressive impairment of arteriolar flow. The former causes proteinuria and subsequently visceral epithelial cell detachment and necrosis, resulting in capillary loop collapse and segmental sclerosis, whereas the development of the latter due to impingement of enlarging endothelial cells on vascular lumina results in ischemic glomerular damage.9,14\n\nWe conducted a multi-center study in Iraq to evaluate the prevalence of Fabry disease in patients with variable presentations.\n\n\nMethods\n\nWe conducted a cross-sectional multi-center study in Iraq with 1148 patients with variable presentations from June 2018 to June 2022. This study planned to recruit as many participants as possible with suspected features of this rare disease to cover all centers in our country and to overcome all issues of selection bias. The study was conducted in all the dialysis units of the Iraqi governorates and outpatient clinics, including nephrology, cardiology, pediatric, dermatology, and neurology. This study included patients with at least one of the following indications: positive or suspected family history of renal disease, suspected angiokeratomas, unexplained peripheral neuropathy, proteinuria, or cardiovascular disease, and children and adolescent on hemodialysis.\n\n\n\na) Hepatitis B or hepatitis C viral infection\n\nb) Diabetes mellitus\n\nc) Children with inter-current illness like severe gastroenteritis or decompensated heart failure\n\nd) Patients with sepsis\n\nThe demography of the study population was recorded, which included patient age, gender, and case history. The medical and family histories of all the recruited patients were carefully noted, including evidence for acroparesthesia and hypohidrosis (sweating abnormalities).\n\nWe recruited multi-center patients from different age 6-75 years from nephrology centers, cardiac centers, pediatrics hospital, dermatologic centers, neurology centers in different governorates (north, middle and south of Iraq). We screened depending on medical records and direct examination for each issue for following clinical features in all recruited patients:\n\n• Intermittent episodes of burning pain in the extremities (acroparesthesias)\n\n• Cutaneous vascular lesions (angiokeratomas)\n\n• Diminished perspiration (hypo- or anhidrosis)\n\n• Characteristic corneal and lenticular opacities.\n\n• Abdominal pain, nausea, and/or diarrhea of unknown aetiology in young adulthood or any symptoms consistent with irritable bowel syndrome.\n\n• Left ventricular hypertrophy (LVH) of unknown aetiology, particularly in young adults.\n\n• Arrhythmias of unknown aetiology, particularly in young adults.\n\n• Stroke of unknown aetiology at any age.\n\n• Chronic kidney disease (CKD) and/or proteinuria of unknown aetiology.\n\n• Multiple renal sinus and/or renal pelvis cysts discovered incidentally.\n\n• Recurrent hand pain (painful crisis) in children.\n\nMoreover, clinical assessment and routine examinations, such as complete blood count, serum creatinine, serum potassium, blood urea, and urinalysis, were performed. The assessment done using formal assessments for all patients including:\n\n• Full family history of renal disease and premature cardiac disease.\n\n• Careful physical examination, looking for angiokeratomas, telangiectasias, hypo- or anhydrosis, corneal opacities by doing formal slit lab exam, edema or lymphedema, abnormal cardiac examination (evidence of LVH, arrhythmia).\n\n• Routine laboratory tests to evaluate kidney function such as creatinine, urinalysis with examination of the urine sediment, and spot urine protein-to-creatinine ratio.\n\n• With kidney involvement, urine microscopy may reveal oval fat bodies (degenerating tubular epithelial cells with lipid inclusions).\n\nIn addition, electrocardiography, echocardiography, nerve conduction, neurologic assessment, skin angiokeratomas, slit-lamb examination, formal audiology assessment, ophthalmologic evaluation, and α-GALA enzyme assay was performed. We measure leukocyte alpha-galactosidase A (alpha-Gal A) activity as the initial diagnostic assay. Dried blood spot (DBS) test was conducted for the screening of Fabry disease. In this test, four blood spots were placed on a filter paper (Sigma-Aldrich/ USA, Cat. No.:1450-045-8) and dried at room temperature. The α-GAL A activity was measured using tandem mass spectrometry (AB SCIEX Pte. Ltd. /USA, DH Tech. Dev. Pte. Ltd., Cat. No.:IVD-0355724MKT), where values between 200–2000 pmol/spot20 h were considered normal. This diagnosis is confirmed if there is a decrease or absence of α-GALA activity in the dry blood leukocytes. A lysosomal enzyme activity assay <200 pmol/spot20h is suggestive of Fabry disease with clinical correlation. Any patient with α-GAL A activity <100 pmol/spot20h was sent for genetic testing for confirmation of the diagnosis. Genetic testing should then be performed. Genetic testing in this setting facilitates diagnosis and genetic counselling in the patient's family (particularly in females)15–17 and further genetic assessment. The assessment done over different days. These measures were assessed both from medical records evaluation of patients.\n\nBlood samples of all the patients were collected by applying a blood drops, drawn by lancet from the finger, on a special dry paper (Sigma-Aldrich/USA, Cat. No.: 8.294.0004A) (Figure 1). Then, it was sent to the advanced genetic clinical research lab of Univ.-Prof. Dr. Berthold Streubel in Vienna, Austria and to the Laboratory of Metabolism, University Medical Center Hamburg, Germany by DHL from Iraq. Dried blood spot (DBS) test was conducted for the screening of Fabry disease. In this test, four blood spots were placed on a paper and leave dried at room temperature.\n\nThe α-GAL A activity was measured using tandem mass spectrometry, where values between 200–2000 pmol/spot20 h were considered normal. This diagnosis is confirmed if there is a decrease or absence of α-GALA activity in the dry blood leukocytes. A lysosomal enzyme activity assay <200 pmol/spot20h is suggestive of Fabry disease with clinical correlation. Any patient with α-GAL A activity <100 pmol/spot20h was sent for genetic testing for confirmation of the diagnosis.\n\nMolecular testing include several approaches include single-gene testing, multi-gene testing, or comprehensive genomic testing. In this study, multi-gene testing was preferable to use because of multifactorial aetiology of disease. First, the GLA sequence is analyzed; if no pathogenic variant is found, then gene-targeted determined. We invited all patient from different centers to proceed to did dry blood spot paper testing. The information about testing include (Official symbol: GLA; Gene ID: 2717; and Reference sequence: NM_000169.2 (ENST00000218516)). The DNA extraction from Dried Blood Spot; PCR amplification and sequencing of all coding exons and flanking intronic regions were done automated by (PCR thermocycler model Verriti, thermofisher company, USA). All samples were sent to ARCHIMEDlife for PCR testing.\n\nTargeted analysis for the p.Ala143Pro and IVS4+919G>A pathogenic variants were performed.\n\nMentioned in the test ARCHIMEDlife used a NM_000169.2 for GLA gene ID 2717 as reference sequence for comparison or more scientific term (Alignment) with Human genome HGVS 37. Variants are described according to den Dunnen et al. (2016).18 Common benign variants in the gene may have been identified but have not been included in this report. Mosaicism cannot be excluded. Because of their complexity and their potential implications for other family members, all genetic tests should be accompanied by genetic counseling in accordance with local legislation.\n\nWritten informed consent was obtained from all participants. The Medical Ethical Committee at the College of Medicine, University of Basrah, approved this study (1st on 11/06/2018; ID: 2018-00287712 and 2nd on 04/03/2021; ID: 2021-03040818 because the first approval got lost in transport.\n\nData were coded before entering them on the computer. The data is presented as the total number as well as in percentage. SPSS software version 20 (RRID:SCR_019096) was used to perform statistical analysis. Pearson’s chi-squared test was used for determining the statistically significant differences among variables, which was indicated by a p-value < 0.05.\n\n\nResults\n\nA total of 1148 patients were enrolled for this multi-center, cross-sectional study conducted across various regions in Iraq.22 After clinical investigation, it was confirmed that 17 of the patients had α-GAL A deficiency (Fabry disease), with each presenting varied clinical symptoms.\n\nTable 1 demonstrates the distribution of Fabry disease according to the gender of the patients. Of the confirmed cases, 16 were male (94.1%) and only one female (5.9%). Comparison of the control group (having normal α-GAL A enzyme level) with the patients showed no statistical difference (p=0.5; Pearson’s chi-square value=0.38).\n\nTable 2 shows the distribution of patients with Fabry disease according to age. It was observed that the maximum number of patients belonged to the 10–30 years age group (12 patients; 70.6%), followed by 3 patients in the 31–50 years age group (17.6%). The <10 years and >50 years age groups consisted of only one patient (5.9% of the total Fabry cases each). Patients with enzyme deficiency and the patients with normal enzyme level showed a statistically significant difference (p=0.003; Pearson’s chi-square value=13.8).\n\nTable 3 shows the distribution of patients based on their clinical presentations after the genetic confirmation of the Fabry disease. As expected, renal dysfunction (proteinuria with or without renal insufficiency) was the most common clinical presentation, with 14 out of the 17 confirmed cases (82.3%) showing renal involvement. Ten cases had chronic kidney disease (stage 1–4;eGFR >15 ml/min/1.73 m2) while the other 4 were undergoing hemodialysis (eGFR <15 ml/min/1.73 m2). This was followed by neurological involvement, where 6 patients (35.3%) showed peripheral neuropathy. The other clinical manifestations included angiokeratoma (5 patients; 29.4%), left ventricular hypertrophy (3 patients; 17.6%), and corneal verticillate (4 patients; 23.5%).\n\nNext, we compared the distribution of the various clinical presentations with the control group. As shown in Table 4, renal involvement was found in 1120 patients, of which 1106 patients had normal α-GAL A level, while 14 patients had enzyme deficiency, and hence confirmed Fabry disease. All the confirmed cases had proteinuria with or without renal insufficiency. The confirmed cases showed a statistically significant difference with the control group (p=0.0001; Pearson’s chi-square value=16.7).\n\nIn contrast to renal involvement where 1120 patients out of total 1148 patients turned out to be positive for renal dysfunction, cardiac involvement was found in only 37 patients. The number of patients with normal enzyme level was 34 while only 3 patients were confirmed to have Fabry disease (Table 5). These patients suffered from left ventricular hypertrophy. The patients with left ventricular hypertrophy and the control group exhibited statistically significant difference (p=0.001; Pearson’s chi-square test=11.5).\n\nThen, the distribution of neurological involvement was studied among the patients with and without α-GAL A enzyme deficiency (Table 6). Neurological involvement was not found in many patients; there were 7 positive and 1141 negative cases. Out of the total 7 positive cases with peripheral neuropathy, 6 patients had confirmed Fabry disease. The confirmed cases and the control group showed statistically significant difference (p=0.0001; Pearson’s chi-square value=324.5).\n\nFinally, as shown in Table 7, the distribution of dermatological involvement in Fabry disease was studied. In this case, a small number of patients were found to be positive for angiokeratoma, and all those patients had confirmed Fabry disease. The difference between the confirmed cases and the control group was found to be statistically significant (p=0.0001; Pearson’s chi-square value=267).\n\nIn addition to the comparison of the clinical presentation between the confirmed Fabry disease group and the control group, we also compared the prevalence of this disease in various regions of Iraq, namely north, middle, and south Iraq. As shown in Table 8, although the maximum number of recruited patients (975) were from middle of Iraq, the maximum number of confirmed cases were from the northern region of Iraq (8 cases; 47%), followed by 6 cases from the middle region of Iraq (35.3%), and 3 cases form south of Iraq (17.7%). A statistically significant difference was observed between the confirmed cases from north of Iraq and the control group (p=0.0001; Pearson’s chi-square value=44.3).\n\n\nDiscussion\n\nA total of 1148 patients with variable presentations were enrolled for a multi-center, cross-sectional study to realize the prevalence of Fabry disease in Iraq. Fabry disease results due to the deficiency or absence of the lysosomal enzyme α-GAL, whose function is to breakdown glycolipids, which leads to the continuous build-up of Gb3, and consequently, cell abnormalities and organ dysfunction. In this study, lysosomal α-GAL A activity was determined by tandem mass spectrometry, and any patient with α-GAL A activity <100 pmol/spot*20h was sent for genetic testing for the confirmation of the diagnosis.\n\nInterestingly, in our study, only 17 cases were confirmed to have Fabry disease, out of which 16 were male (94.1%) and only one female (5.9%). This skewed gender ratio is explained by Fabry disease being inherited X-linked disorder.1 Men inherit only one X-chromosome, and if the GLA mutation is present on that X-chromosome, they will be affected with the disorder. On the other hand, women have two X-chromosomes. Therefore, the expression of the mutated gene may be reduced or masked by the normal gene on the other X-chromosome.1\n\nSince this was a multi-center study, the regions were distributed as north, middle, south Iraq. The regional distribution of patients with Fabry disease included 8 cases from the north of Iraq (47%), 6 cases from the middle region (35.3%), and 3 cases from south Iraq (17.7%). There was a statistically significant difference between the confirmed cases from the north of Iraq and the control group (p=0.0001).\n\nThe clinical manifestations of Fabry disease in the confirmed cases included angiokeratoma (5; 29.4%), peripheral neuropathy (6; 35.3%), left ventricular hypertrophy (3; 17.6%), proteinuria with and without renal insufficiency (14; 82.3%), and corneal verticillate (4; 23.5%). Furthermore, the age distribution of patients with Fabry disease was as follows: one patient was below 10 years of age (5.9%), 12 patients belonged to the 10–30 years age group (70.6%), 3 patients belonged to 31–50 years age group (17.6%), and only one was >50 years of age (5.9%). Considering the age distribution, a statistically significant difference was observed between the confirmed cases with α-GAL A deficiency and the control cases without enzyme deficiency (p=0.003). The distribution of renal involvement (proteinuria with or without renal insufficiency) in patients with Fabry disease demonstrated a statistically significant difference with the control group (p=0.003). This could be explained by the striking glomerular changes that occur in the glomerular visceral epithelial cells. These cells become enlarged and become packed with small, clear vacuoles enclosing the glycosphingolipid.6,10 A progressive decrease in renal function is due to the progressive accumulation of Gb3 in the kidneys, particularly in the endothelial cells, smooth muscle cells, and podocytes, leading to segmental and global glomerulosclerosis.6,10\n\nCardiac diseases are common in Fabry patients owing to the deposition of Gb3 in all cardiac tissues. Heart diseases like heart enlargement typically left ventricular hypertrophy leads to arrhythmia, hypertrophic cardiomyopathy, and heart failure. Similar to renal dysfunction, a statistically significant difference was observed between patients with cardiac involvement (left ventricular hypertrophy) and the control group (p=0.001). This is consistent with the results of the study by Baptista et al.19 It should be mentioned that the etiology of left ventricular hypertrophy is difficult to distinguish from the other heart diseases using the common cardiac imaging methods, especially echocardiography.19\n\nAnother common clinical manifestation of Fabry disease includes peripheral neuropathy (neurological involvement) that may present as neuropathic pain, reduced warm and cold sensation, and gastrointestinal disturbances. In our study, 41.2% of the patients with α-GAL A deficiency suffered from peripheral neuropathy. There was a statistically significant difference between the confirmed cases and the control groups (p=0.0001). A progressive lysosomal accumulation of glycolipids in the neural cells affects the small, unmyelinated nerve fibers, which manifests as neural myopathy, mostly at a young age.\n\nDermatological involvement was also observed in few of the patients with α-GAL A deficiency. In our study, 29.4% of the confirmed cases had angiokeratoma, which was found to be statistically significant compared to the control group (p=0.0001). In the early stages, reddish to dark blue skin rashes/lesions appear, mostly in the area between the hips and the knees. Angiokeratomas are benign cutaneous vascular lesions characterized by dilated thin-walled blood vessels lying in the upper dermis, associated with an epidermal reaction like hyperkeratosis.20\n\nAlthough ophthalmological manifestations do not generally result in significant visual impairment, they are important as some manifestations serve as disease markers and have prognostic and diagnostic implications.21 In our study, 23.5% of the patients presented with corneal verticillate, which is the most typical ocular symptom in Fabry disease.\n\nThe strength of this study are firstly this is firstly time multi-centers study for rare disease in Iraq and give special recognition for doctors to screening for this genetic disease.\n\nThe limitations are small sample size, and the genetic testing done only for female with highly suspected Fabry disease and male with deficient alpha GAL A enzyme.\n\n\nConclusions\n\nThis study suggested the screening of all patients with a positive or suspected family history of renal disease, suspected angiokeratoma, unexplained peripheral neuropathy, unexplained proteinuria, unexplained cardiovascular disease, as well as children and young hemodialysis patients. It has been established that the early diagnosis of Fabry disease is the cornerstone for the prevention of multiorgan complications, especially renal and cardiac complications. There is a need for effective treatment beyond the palliative and symptomatic care usually provided by the clinicians. Since multiorgan dysfunction is involved, the patients require an individually tailored comprehensive and multidisciplinary treatment approach that includes specific therapies targeting abnormal substrate accumulation and adjuvant therapies that address end-organ damage. Thus, the initiation of enzyme replacement therapy using recombinant human α-GAL A (agalsidase) is of utmost importance for the treatment of Fabry disease. Hitherto, there has been no comparable substitute to enzyme replacement therapy for this damaging, progressive disease till date. It is crucial for future research to focus on the development of protocols for the early diagnosis of Fabry disease. Moreover, effective enzyme protocols are required for the reversal, maintenance, and prevention of the fundamental pathology of the disorder, especially for children and patients with cardiac diseases and compromised renal function.\n\n\nData availability\n\nZenodo: FABRY disease. https://doi.org/10.5281/zenodo.6879922.22\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nDesnick RJ, Ioannou YA, Eng CM: Valle DL, Antonarakis S, Ballabio A, et al., editors. α-Galactosidase A deficiency: Fabry disease. New York:McGraw-Hill; 2001; pp. 3733–3774. Publisher Full Text\n\nGarman SC, Garboczi DN: The molecular defect leading to Fabry disease: structure of human alpha-galactosidase. J. Mol. Biol. 2004; 337: 319–335. PubMed Abstract \| Publisher Full Text\n\nGermain DP: Fabry disease. Orphanet J. Rare Dis. 2010; 5: 30. PubMed Abstract \| Publisher Full Text\n\nMehta A, Ricci R, Widmer U, et al.: Fabry disease defined: baseline clinical manifestations of 366 patients in the Fabry Outcome Survey. Eur. J. Clin. Investig. 2004; 34: 236–242. PubMed Abstract \| Publisher Full Text\n\nMacDermot KD, Holmes A, Miners AH: Anderson-Fabry disease: clinical manifestations and impact of disease in a cohort of 60 obligate carrier females. J. Med. Genet. 2001; 38: 769–775. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nIchinose M, Nakayama M, Ohashi T, et al.: Significance of screening for Fabry disease among male dialysis patients. Clin. Exp. Nephrol. 2005; 9: 228–232. PubMed Abstract \| Publisher Full Text\n\nRolfs A, Bottcher T, Zschiesche M, et al.: Prevalence of Fabry disease in patients with cryptogenic stroke. Lancet. 2005; 366: 1794–1796. Publisher Full Text\n\nEng CM, Banikazemi M, Gordon RE, et al.: A Phase 1/2 clinical trial of enzyme replacement in Fabry disease: Pharmacokinetic, substrate clearance, and safety studies. Am. J. Hum. Genet. 2001; 68: 711–722. PubMed Abstract\n\nTerryn W, Cochat P, Froissart R, et al.: Fabry nephropathy: Indications for screening and guidance for diagnosis and treatment by the European Renal Best Practice. Nephrol. Dial. Transplant. 2013; 28: 505–517. PubMed Abstract \| Publisher Full Text\n\nTahir H, Jackson LL, Warnock DG: Antiproteinuric therapy and Fabry nephropathy: Sustained reduction in proteinuria in patients receiving enzyme replacement therapy with agalsidase-beta. J. Am. Soc. Nephrol. 2007; 18: 2609–2617. Publisher Full Text\n\nKosch M, Koch HG, Oliveira JP, et al.: Enzyme replacement therapy administered during hemodialysis in patients with Fabry disease. Kidney Int. 2004; 66: 1279–1282. PubMed Abstract \| Publisher Full Text\n\nDesnick RJ, Brady R, Barranger J, et al.: Fabry disease, an under-recognized multisystemic disorder: Expert recommendations for diagnosis, management, and enzyme replacement therapy. Ann. Intern. Med. 2003; 138: 338–346. PubMed Abstract \| Publisher Full Text\n\nYoung-Gqamana B, Brignol N, Chang HH, et al.: Migalastat HCl reduces globotriaosylsphingosine (Lyso-Gb3) in Fabry transgenic mice and in the plasma of Fabry patients. PLoS One. 2013; 8: e57631. PubMed Abstract \| Publisher Full Text\n\nGiugliani R, Wldek S, Germain DP, et al.: A Phase 2 study of migalastat hydrochloride in females with Fabry disease: Selection of population, safety and pharmacodynamic effects. Mol. Genet. Metab. 2013; 109: 86–92. PubMed Abstract \| Publisher Full Text\n\nDiagnostic strategy for Females suspected of Fabry Disease, Poster Presentation, WORLDSymposium. Orlando USA:Feb. 2020.\n\nBalendran S, Oliva P, Sansen S, et al.: Diagnostic strategy for females suspected of Fabry disease. Clin. Genet. 2020; 97(4): 655–660. PubMed Abstract \| Publisher Full Text\n\nStiles AR, Zhang H, Dai J, et al.: A comprehensive testing algorithm for the diagnosis of Fabry disease in males and females. Mol. Genet. Metab. 2020; 130(3): 209–214. PubMed Abstract \| Publisher Full Text\n\nden Dunnen JT , Dalgleish R, Maglott DR, et al.: HGVS Recommendations for the Description of Sequence Variants: 2016 Update. Hum. Mutat. 2016 Jun; 37(6): 564–569. PubMed Abstract \| Publisher Full Text\n\nBaptista A, Pedro M, Sílvia L, et al.: Screening for Fabry Disease in Left Ventricular Hypertrophy:Documentation of a Novel Mutation. Arq. Bras. Cardiol. 2015; 105: 139–144. PubMed Abstract \| Publisher Full Text\n\nAnderson W: A case of “angio-keratoma”. Br. J. Dermatol. 1898; 10: 113–117. Publisher Full Text\n\nSodi A, Ioannidis A, Pitz S:Chapter 26, Ophthalmological manifestations of Fabry disease.Mehta A, Beck M, Sunder-Plassmann G, editors. Fabry disease: perspectives from 5 years of FOS. Oxford:Oxford PharmaGenesis; 2006.\n\nAl Atbee MYN: FABRY disease [Data set]. Zenodo.2022. Publisher Full Text" }	[ { "id": "149609", "date": "13 Sep 2022", "name": "‪Fellype de Carvalho Barreto", "expertise": [ "Reviewer Expertise Nephrology", "rare genetic disorders", "Fabry disease." ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is an important study that investigated the prevalence of Fabry disease among a wide variety of patients with suspicious clinical characteristics for Fabry disease in Iraq. The manuscript requires great improvement in order to make the study bloom.\nYou will find below my main considerations and suggestions:\nThe introduction should be focused on the importance of screening for Fabry disease among a high-risk population. It is equally relevant to address that rare genetic diseases need to be included in our differential diagnosis. These strategies may offer the patients the opportunity of an early diagnosis, more potential benefits of the pathogenetic treatment, and avoid the diagnostic odyssey that most patients still face.\n\nMeasuring only the α-GAL A enzyme activity is not considered an adequate methodology to screen for Fabry disease in women. Women may have Fabry disease even in the presence of normal levels of enzymatic activity due to skewed X-inactivation. Hence, the study may have missed some cases of Fabry disease among females. This limitation needs to be addressed in the discussion.\n\nIt is important to add the data on the level of the enzymatic activity of each patient rather than only classifying patients as presenting normal or abnormal enzymatic levels. The pathogenic genetic variants that were identified need to be shown as well. Patients with GVUS may present a slight decrease in enzymatic activity and the diagnosis of Fabry disease is uncertain.\n\nHow many patients have classic and late-onset phenotypes?\n\nIt is important to report the prevalence of Fabry disease and the clinical and demographic characteristics according to the subtype of the study population, i.e. the prevalence of Fabry disease among patients with LVH, among cryptogenic stroke, and so on. Presenting data this way would highlight the importance of screening for Fabry disease among the high-risk population, as well as would possibly identify a subset of the population that deserves more attention that are still neglected.\n\nIt is well recognized that, on average, five new cases of Fabry disease are diagnosed among the relatives of an index case. Was family screening performed? Please discuss the importance of family screening as a tool to identify new cases at a younger age.\n\nWhy were hepatitis B, hepatitis C, and diabetes considered exclusion criteria?\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "346305", "date": "18 Dec 2024", "name": "Saida Ortolano", "expertise": [ "Reviewer Expertise Biochemist", "expert in Fabry Disease" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe present article analyzes the prevalence of Fabry disease in Iraq, a region in which this disease has been poorly studied, and therefore the article is of interest. However, there are important lacks in data reporting and interpretation which should be addressed to make this study scientifically sound. Here are some advises for article revision: Introduction: Authors says that \"accumulated glycosphingolipids in Fabry disease and those found in normal tissues are similar\". What do they mean for similar? Concentration of glycosphingolipids is not similar in Fabry versus healthy controls, while qualitatively these sphingolipids are of course substrate that are naturally present in the body. Authors also says \" In women, severe FD can result due to the considerable inactivation of the X chromosome, where the normal alpha-Gal A allele is located\" probably they should say: In women, severe FD can result due to the considerable inactivation of the normal allele of GLA in the X chromosome, since both alleles are present in somatic cells and the severity of the disease is correlated with the percentage of inactivation of the wild type allele. Finally, cardiac involvement in FD, should be at least mentioned in the introduction as a very common consequence of the pathology. Methods: genetic molecular testing of GLA description is confused. First author says that they selected a multigene sequencing strategy, then they describe a methodologic approach used for Sanger sequencing, it is difficult to understand what method was actually selected. Also it is stated that targeted analysis for the p.Ala143Pro and the IVS4+919G>A pathogenic variant was performed. Why these two variants? There are no common mutations in FD and more than 1000 variants known. Are these two mutations common in the region? Are these the variants that were prevalently identified? Results: the identified genetic variants should be disclosed, for complete description of the study, to know whether they are new variants or variants that were already associated to classic or late onset FD and to exclude that the author identified variants of unknown significance. Also, the prevalence of FD that is reported is quite high, even considering that the study was done in risk populations. Is any of the 17 patients been identified in the context of a family study? Was genetic testing performed in all the females of the families of the index cases, in spite of the activity values? In page 5, authors suggest that genetic counselling is particularly important for females, however it is equally important for men, who can also transmit the disease to next generation and who will obligatorily transmit the mutation to all their daughters. Discussion: Authors justify the low number of identified female patients because of the X-linked pattern of inheritance of the disease, however the main cause for this is the methodologic approach selected for the screening. The cut off activity value as selection method leads to the exclusion of all the females that have normal enzyme activity in the blood, but may present considerable level of wild type allele X inactivation in target tissue, so the false negative rate in female could be high. The X-linked inheritance leads to usually milder manifestations in females, but not in a lower frequency of inheritance of the mutation, indeed all the female, who are descendants of a male with FD, will always present the mutation.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-870
https://f1000research.com/articles/11-869/v1	29 Jul 22	{ "type": "Opinion Article", "title": "Community-driven ELIXIR activities in single-cell omics", "authors": [ "Paulo Czarnewski", "Ahmed Mahfouz", "Raffaele A. Calogero", "Patricia M. Palagi", "Laura Portell-Silva", "Asier Gonzalez-Uriarte", "Charlotte Soneson", "Tony Burdett", "Barbara Szomolay", "Pavankumar Videm", "Hans-Rudolf Hotz", "Irene Papatheodorou", "John M. Hancock", "Björn Grüning", "Wilfried Haerty", "Roland Krause", "Salvador Capella-Gutierrez", "Brane Leskošek", "Luca Alessandri", "Maddalena Arigoni", "Tadeja Rezen", "Alexander Botzki", "Polonca Ferk", "Jessica Lindvall", "Katharina F. Heil", "Naveed Ishaque", "Eija Korpelainen", "Ahmed Mahfouz", "Raffaele A. Calogero", "Patricia M. Palagi", "Laura Portell-Silva", "Asier Gonzalez-Uriarte", "Charlotte Soneson", "Tony Burdett", "Barbara Szomolay", "Pavankumar Videm", "Hans-Rudolf Hotz", "Irene Papatheodorou", "John M. Hancock", "Björn Grüning", "Wilfried Haerty", "Roland Krause", "Salvador Capella-Gutierrez", "Brane Leskošek", "Luca Alessandri", "Maddalena Arigoni", "Tadeja Rezen", "Alexander Botzki", "Polonca Ferk", "Jessica Lindvall", "Katharina F. Heil" ], "abstract": "Single-cell omics (SCO) has revolutionized the way and the level of resolution by which life science research is conducted, not only impacting our understanding of fundamental cell biology but also providing novel solutions in cutting-edge medical research. The rapid development of single-cell technologies has been accompanied by the active development of data analysis methods, resulting in a plethora of new analysis tools and strategies every year. Such a rapid development of SCO methods and tools poses several challenges in standardization, benchmarking, computational resources and training. These challenges are in line with the activities of ELIXIR, the European coordinated infrastructure for life science data. Here, we describe the current landscape of and the main challenges in SCO data, and propose the creation of the ELIXIR SCO Community, to coordinate the efforts in order to best serve SCO researchers in Europe and beyond. The Community will build on top of national experiences and pave the way towards integrated long-term solutions for SCO research.", "keywords": [ "Single cell", "multi-omics", "spatial transcriptomics", "FAIR", "data analysis", "data standards", "training", "computing infrastructure" ], "content": "Introduction\n\nSingle-cell omics (SCO) is an umbrella term that encompasses multiple technologies that are able to profile various omic modalities at the single-cell level. These high-throughput single-cell approaches have rapidly become the method of choice over traditional bulk methods which average data across a population of cells. Single-cell approaches are better suited for characterizing many biological phenomena and exploring cellular heterogeneity such as characterisation of rare cell types and diverse cell states. Besides single-cell/nucleus RNA sequencing,1–4 SCO approaches include nuclear epigenetic profiling such as chromatin accessibility,5 histone profiling,6 DNA methylation,7 chromatin conformation8 as well as high throughput single-cell proteomics.9 Recent developments allow simultaneous profiling of two or more of the aforementioned modalities,10 opening up unprecedented opportunities to study diverse processes such as development, gene expression dynamics, tissue heterogeneity and disease pathogenesis. More recently, several approaches have been developed to deliver spatial resolution of single cell expression within tissues, adding another layer of complexity. While several grand challenges in exploratory data analysis remain,11 a parallel issue is the provision of infrastructure to support such analysis in the rapidly developing field.\n\nNew SCO profiling technologies are mushrooming, and new analysis methods are published weekly (Figure 1a). As the scale and modality of data sets grow, new computational methods are required. The data also need to be stored and annotated in a standardized manner in order to enable their reuse. This in turn adds an extra challenge and makes it hard for most institutes to handle alone, and calls for international collaboration on training, tools, compute, data, interoperability and standardization in SCO.\n\n(a) Current count of articles using SCO technologies and cumulative number of cells sequenced and deposited in public databases. (b) Number of tools developed specifically to work with SCO. (c) Most common SCO molecular profiling technologies mentioned in publications. (d) Top 15 most targeted categories for software development in SCO. (e) Number of tools developed for SCO, split by which scripting languages are used. Data were taken from public databases.34,74 See the Data and Software Availability section for details.\n\nELIXIR, the European infrastructure for life sciences data, brings Europe’s national centers and core bioinformatics resources into a single, coordinated infrastructure.12 This intergovernmental organization currently has 23 Nodes, and facilitates collaboration between its member institutes and researchers with two intersecting organizational groupings: Platforms and Communities. ELIXIR Platforms (Data, Interoperability, Tools, Compute and Training) provide services, and ELIXIR Communities identify the needs of domain- or technology-specific research around a theme. There are currently 13 Communities ranging from Metabolomics and Proteomics to Federated Human Data and Galaxy.\n\nMany ELIXIR Nodes already have single-cell facilities, and others are setting them up. The Nodes are facing a huge demand for single-cell data analysis and training, and some knowledge transfer between the Nodes already exists. Examples of past data analysis courses co-organized by ELIXIR Nodes are listed in Table 1. The Nodes have also co-organized workshops to discuss FAIR data management and best training practices for SCO. Together, 17 ELIXIR Nodes proposed to create the ELIXIR SCO Community to connect these grass-roots efforts and strengthen European and international cohesion in SCO.\n\nTutorial training style refers to teaching bioinformatics by following pre-made sequential analysis steps with code. PBL training style refers to teaching using project-based learning, where students develop their own analysis code to solve analysis tasks. All courses listed below were taught in English.\n\n\nLandscape of SCOs\n\nSingle-cell omics technologies have seen widespread adoption since its announcement as Nature Method of the Year in 2013.13 The most widely used SCO technologies are single-cell RNA-seq, single-nucleus RNA-seq, and single-cell ATAC-seq. The early days of these technologies were dominated by heterogeneous implementations of handling, preparation and sequencing protocols,14 which left its mark in the large number of software tools that had been developed, which in part led to lack of standardization of data and metadata. In recent years, we have seen a number of technology providers prevail for instrumentation (e.g. Fluidigm, 10x Genomics), reagents (e.g. ThermoFisher, QiaGen, Roche), and sequencing (e.g. Illumina, MGI, ONT and PacBio). This has led to the community converging around a few workflows based around the popular 10x Genomics Chromium and SmartSeq chemistries (Figure 1c), which have been exploited for large scale sequencing efforts such as the Human Cell Atlas (HCA)15 and Human BioMolecular Atlas (HuBMAP),16 that, in turn, have resulted in large investments into solving the sample handling, data integration and data management problems underpinning the vast array of data being generated.\n\nWhile it has been a decade since the SCO technologies have taken the center stage in unraveling bio-molecular heterogeneity, technology developers are far from stagnant and we are seeing rapid evolution of these technologies. We witness the adoption of single-cell genomics (e.g. MissionBio Tapestri) and some progress in the field of single-cell proteomics.17 Single-cell multimodal omics was announced as Nature Method of the Year 2019.10 These assays provide multiple readouts that can be used to define cells. For example, antibody profiling (e.g. CITE-seq18) allows scientists to contextualize novel cell types and states in the context of well-established cell biology markers; immune repertoire profiling can also link how transcriptional profiles of immune cells differ based on the receptor specificity19; true multimodal omics such as simultaneous profiling of chromatin accessibility, DNA methylation and transcriptomics (e.g. scNMT-seq20) allows us to also decipher the regulatory changes that underpin the transcriptional landscape of cells.\n\nIn 2020, spatially resolved transcriptomics (SRT) was announced as Nature Method of the Year.21 These technologies fall under three broad areas of laser capture microscopy combined with single-cell sequencing (e.g. GeoMX DSP, Tomo-seq), in situ capture arrays (e.g. ST, Visium, Slide-seq, HDST), and image-based single-molecule expression quantifications (e.g. in situ sequencing,8 seqFISH+,22 Molecular Cartography,23 MERFISH24). Despite its youth, there are over 20 SRT profiling technologies,25 which are also expanding into other omics modalities, such as proteomics (e.g. CODEX26) and metabolomics.27 However, the community quickly realized the potential of this technology and early efforts were pushed by the Chan Zuckerberg Initiative to harmonize the field by funding efforts such as StarFish,28 a platform to uniformly process raw single molecule SRT data, and the SpaceTX consortium, which aim to benchmark and harmonize data from various SRT platforms and analytics methods. Efforts to make comprehensive cell atlases available to the community now facilitate more single-cell study designs to include perturbation and lineage tracing experiments (e.g. via CRISPR29–33).\n\nWhile the standards for scRNA-seq have by-and-large converged, the extension of single-cell technologies to new modalities and experimental setups places even more emphasis on establishing adaptable and extensible standards.\n\nThere is a large number of single-cell analysis methods and tools available that cover a wide range of analysis steps. In January 2022, the scRNA-tools database recorded nearly 1,200 tools divided over more than 30 categories (Figure 1b and d).34 Computational and analytical challenges in single-cell genomics have been discussed extensively.11,35 The analysis steps vary depending on the modality of single-cell data. For the most widely used modality, transcriptomic data, the community has converged on a consensus regarding the analysis steps.36 Yet, even some foundational steps remain active areas for research, such as how to normalize scRNA-seq data37–39 or how best to perform differential expression analysis.40,41 Also, annotation of cell types varies drastically between studies, with many resorting to ad hoc decisions. A complete atlas of all cell types would be required to improve the standardization of cell-type nomenclature and ontologies (e.g. Cell Ontology, UBERON).42 Scientists analyzing SCO data need to have sufficient information on the strengths and limitations of the available analysis tools in order to select the most suitable ones for their data and purpose. However, systematic comparison of these tools is challenging, especially given the ever-increasing number of methods and their parameter combinations.\n\nStudies have identified essential guidelines for benchmarking computational methods43–49 and reviewed published benchmarking studies of computational tools for omics data, highlighting the advantages and limitations of benchmarking across various domains of the life sciences.50 Systematic benchmarking frameworks can enable crowdsourcing and community challenges, which have been a successful means for fostering community creativity and expertise to address open problems.51 In a concerted effort to address “grand challenges” for the SCO community,11 the Open Problem in Single-Cell Analysis group52 is devising competitions to address those challenges, e.g. the Multimodal Single-Cell Data Integration competition (NeurIPS 2021).\n\nDespite community efforts, the major challenges facing SCO benchmarking studies are the lack of appropriate experimental data and/or realistic simulated data that can be used for benchmarking, as well as the lack of agreed-upon measures to evaluate different methods. There is also a need for a common platform to conduct benchmark studies. The Open Problems NeurIPS challenge provides a leading example for evaluating methods using common datasets, performance metrics, as well as providing a compute infrastructure to run these methods. However, there is still a need for platforms that allow for continuous update of results as new tools and/or metrics become available and to dynamically respond to the needs of individual communities within the life sciences.\n\nCurrently available tools and pipelines differ in their usability. While the majority require programming knowledge, several pipelines provide GUIs for users without programming experience (e.g. Galaxy, Chipster).53,54 Most tools are available as R and Python packages or as a collection of scripts on GitHub (Figure 1e). To keep up with the technology developments, these methods and tools are continuously updated. Yet, maintaining tools and providing support is often challenging for research groups. Interoperability between methods and tools is limited despite efforts by popular packages such as Seurat55 to provide wrappers around other tools. However, frequent updates to tools to keep up with technology developments (e.g. updating single-cell objects to cater for multi-modal data) limits interoperability, emphasizing the importance of a concerted effort to address robust data and metadata standards.\n\nThe major factor in realizing interoperability is the definition and adoption of robust data format standards. While more than 1,000 SCO tools exist, there is broad acceptance of widely adopted raw data standards (e.g. FASTQ, FAST5, BAM, CRAM) and convergence to a few processed data formats (e.g. tab-separated files, AnnData, HDF5, loom, SingleCellExperiment, Seurat). The data formats and structures employed by some of the most popular tools for SCO data analysis55,56 have had to change to adapt to new technologies that rendered previous formats inadequate. While these changes in data formats are frustrating for maintaining data analysis workflows, they are necessary for keeping up to date with the rapid technological developments in this field. This places a strong emphasis on planning to adapt to changes by employing extensible structures that do not break the chain of backwards compatibility.\n\nFurthermore, metadata standards and minimal reporting guidelines enable the appropriate archiving and subsequent reuse of SCO data. For some specific library construction or sequencing technologies, provision of platform specific metadata is routine and standardized (e.g. for the 10x Chromium), however additional care is required for in-house solutions and for reporting metadata for other parts of the experimental design. Establishing the Minimum INformation about a SEQuencing Experiment (MINSEQE) guideline was an important achievement for reporting metadata for sequencing data.57 Recently the Minimum Information about a Single-Cell Experiment (minSCe) guidelines were established,58 which defines 48 attributes that describe the biosource, isolation method, protocols, library construction, sequencing assay, raw data files and sequences, and cell- and sample-associated information derived from data analysis. However, as we move towards atlasing entire organisms and the rapid emergence of spatially resolved SCO technologies, further refinement of these minimal reporting standards is required to allow for describing common landmarks to facilitate integration of reference maps at differing scales into a single common framework, e.g. through the adoption of the Common Coordinate Framework59 that aims to uniquely and reproducibly define any location in the human body. A major consequence of establishing robust metadata standards is that they facilitate the establishment of SCO portals that provide access to uniformly processed data from a wide variety of SCO studies (e.g. the EBI Single Cell Expression Atlas, the Broad Single Cell Portal, and the HCA Data Portal). Such portals rely on accurate and sufficient metadata to enable appropriate processing of SCO data from a wide variety of studies in a uniform way.\n\nGiven the fast pace of technological developments in the SCO field, the community has identified that both adaptability and extensibility are key considerations in defining sustainable standards. This has been achieved in the field of medical imaging with the Digital Imaging and Communications in Medicine (DICOM) format,60 which has been constantly extended and updated without breaking backwards compatibility for nearly 30 years. However, this level of flexibility was only achieved by the third version of the DICOM standard, 10 years after its initial inception, and it was a concerted effort between medical and trade associations. Part of the successful adoption of the DICOM format is that despite all major medical imaging players having their own proprietary formats, they provide an interface to the DICOM format. In order for the SCO community to reach a similar level of interoperability as has been achieved in medical imaging, technology providers and tool developers should also either adopt the most common standards in the SCO community, or provide interfaces to them. While it is not clear how the current landscape of SCO data and metadata standards will stand the test of time, some aspects that will determine their success with be their ability to adapt to change (e.g. through using extensible formats such a JSON), used of controlled nomenclature (e.g. utilising ontologies for defining attributes), and adopting versioning (e.g. semantic versioning).\n\nUpskilling life scientists to analyze SCO data is a moving target, given the fast development of the field. The cutting edge analysis methods for SCO data tend to be rather computationally complex, making them harder to grasp for life scientists who typically lack a solid background in mathematics, statistics and machine learning and often R/Python skills too.\n\nTrainers, on the other hand, find themselves updating training materials constantly and, in general, struggle to keep up with the fast development of new analysis methods in order to choose what to teach. To make things worse, often only a small fraction of their working time is dedicated to training, or training is offered on a voluntary basis on top of their workload. It is therefore not surprising that even though single-cell courses are offered by several ELIXIR Nodes, many flavors of SCO are not yet covered. For example, courses on single-cell epigenetic, multi-omics as well as image-based spatially resolved SCOs are still rare. The demand for training continues to grow, but the lack of competent experts with enough training experience and time available is a major bottleneck in scaling up training provision. While pedagogical train-the-trainer (TtT) courses61,62 can empower experts to feel more comfortable to teach, the constant evolution of the SCO field can intimidate newcomers.\n\nThere are also more practical hurdles: the analysis of single-cell data requires a sophisticated computational environment with many tools and their dependencies, often requiring high-end computational resources. These environments have to be ready-to-go or at least easy to set up, and reproducible across heterogeneous hardware infrastructure, allowing the participants to re-run the practical and to analyze their (probably much larger) own data in their own setting. It is also challenging to find good training datasets that are small enough to be run in a class but meaningful enough to prove the concepts.\n\n\nAlignment with ELIXIR Platforms and Communities\n\nThe ELIXIR SCO Community will bring together current efforts and produce guidelines and training. It creates a communication channel to exchange experiences, collect user requests and feedback and push for standards. Given its needs for training, tools, compute, data and interoperability, the SCO Community aligns well with all the ELIXIR Platforms. It also has synergies with the ELIXIR Human Data Communities and the Galaxy Community, as well as some ELIXIR Focus Groups like Cancer Data and FAIR Training.\n\nUpskilling scientists in SCO data analysis and standards lies at the heart of the ELIXIR SCO Community, and particular efforts will be made to make the training scalable and FAIR in coordination with the ELIXIR Training platform (Table 2).\n\n\n\n• Provide training in data analysis and standards to complement ELIXIR Nodes activities.\n\n• Create an ELIXIR SCO website, with a dedicated training section for easy discovery.\n\n• Create a catalog of SCO video lectures and tutorials for self-study and asynchronous learning with links to training resources which enable anyone to learn SCO data analysis independently of time and place.\n\n• Organize workshops for SCO data analysis trainers for exchanging ideas about best practices, methods and datasets.\n\n• Collaborate with the ELIXIR Train-the-Trainer programme to provide pedagogical techniques for trainers.\n\n\n\n• Perform periodic reviews of methods for registration in bio.tools.\n\n• Provide a public Slack channel to exchange information about software benchmarks and datasets for benchmarking.\n\n• Explore OpenEBench for benchmarking SCO data analysis methods.\n\n• Collect and curate datasets for benchmarking.\n\n• Provide ready-made containers, Conda recipes and Notebooks with popular SCO software environments.\n\n\n\n• Keep the Compute Platform up to date with the computing needs of SCO data analysis.\n\n\n\n• Define requirements of a framework for an efficient, effective and flexible single cell omics FAIR data and metadata standards.\n\n• Disseminate knowledge of and promote standards in preparation for creation of ELIXIR core data resources.\n\n\n\n• Collaborate with TeSS, ELIXIR’s Training Portal, to establish a well-curated ELIXIR SCO training portal, listing national and international bodies, web resources and upcoming training events.\n\n• Keep training resources up to date.\n\n\n\n• Benchmarking and reproducibility: develop several software benchmarks within the OpenEBench infrastructure.\n\n• Develop cloud-deployable analysis pipelines for SCO data and make them available also through Galaxy and Chipster for non-programming scientists.\n\n• Provide long-term cloud-based solutions for making tools open and FAIR.\n\n\n\n• Benchmark, update and optimize tools to run as efficiently as possible across different ELIXIR computing nodes.\n\n\n\n• Support existing efforts for aggregating and disseminating related metadata standards, e.g. from ArrayExpress, the HCA and further efforts.\n\n• Establish a user forum to restructure and unify data structure of sequencing, spatial and image data across SCO.\n\n• Encourage all data generators to ensure their data is available from an ELIXIR core data resource.\n\n• Leverage EMBL-EBI connections to the HCA Data Coordination Platform to broker the HCA data to ELIXIR core data resources and deposition resources.\n\nThe SCO Community will ensure that training materials and expertise are shared efficiently and following FAIR and open research principles.63,64 We will collaborate with ELIXIR’s Training Portal TeSS65 to establish a well-curated SCO training portal, listing national and international training providers, web resources and upcoming training events. To help the current trainers and encourage new ones, we will annotate training materials with appropriate metadata, curate training datasets, provide detailed explanation on how to run courses, and share best practices and best ways to teach the more advanced concepts. In order to identify SCO areas which lack sufficient training, we will participate in designing the annual training gap survey by the Training Platform, and also perform more detailed SCO training surveys if needed. We will regularly host trainer workshops targeting the areas identified as lacking sufficient training to exchange experiences and discuss materials.\n\nAnyone should be able to learn about SCO data analysis independently of time and place. To make the training scalable, lectures and video tutorials will be recorded for asynchronous learning, and combined into modular eLearning courses. Resources will be gathered and annotated on a single site for easy discovery. In addition to organizing training in SCO data analysis and standards to complement ELIXIR Nodes activities, we will provide training in best practices for trainers (TtT) to increase the number of expert trainers.\n\nThe course software installation challenge will be addressed together with the ELIXIR Tools Platform, as described below, using Conda environments, containers and Notebooks. Both Galaxy66 and Chipster54 offer specific training access and a comprehensive collection of training materials. There is no setup required, and the same environment is available when analyzing one’s own data after the course.\n\nSCO data analysis typically requires a large number of tools and their dependencies. The installation challenge can be eased by providing Conda environments67 and containers68 for SCO, in alignment with the work developed in the Tools Platform’s Packaging, containerisation and deployment activity. Also, RStudio or Jupyter Lab based SCO Notebooks can be made to support courses and self-study. The Community will develop cloud-deployable analysis pipelines for SCO data and make them available also through the web-based Galaxy Single Cell Omics, Galaxy Human Cell Atlas project, and Chipster analysis platforms for researchers lacking programming skills. The analysis pipelines will be deposited in WorkflowHub69 for easy discovery, re-use and assessment.\n\nThe SCO Community will take several actions to address the aforementioned challenges in benchmarking. Liaising with data analysis experts, we will carefully curate data collections suitable for addressing specific tasks within the SCO data analysis workflow (e.g. multi-modal data integration, deconvolution of bulk data). For this, we will survey the landscape of existing benchmarking studies and identify the datasets they used and how they were evaluated. Whenever possible, our focus will be on real datasets rather than simulated ones, given the bias introduced by simulated data towards methods using the same underlying model. In order to address the lack of agreed-upon performance metrics to evaluate different types of methods, we will collect and curate existing metrics, and develop/suggest new measures when necessary (Table 2).\n\nRegarding the need for a common platform to conduct benchmark studies, we will explore using OpenEBench.70 This ELIXIR benchmarking platform offers a flexible computational framework that allows individual communities to design and perform their benchmarking experiments. Communities are responsible for defining the reference datasets and the evaluation metrics and designing and developing evaluation workflows. Software developers are then able to use these workflows to evaluate their tools against the reference datasets, and the computed metrics are compiled, analyzed and publicly exposed in tables and visualizations. The results of the evaluation are then used by the community or any other OpenEBench user to decide which is the most suitable tool to do their analysis. The SCO Community will provide guidelines for the setup of single-cell benchmarking experiments. The guidelines have to cover three topics: 1) the scope of the benchmark, 2) the evaluation metrics that will be used to measure the performance of the tools and 3) the reference or gold standard datasets. The SCO Community will establish a benchmarking environment for SCO data analysis tools within the OpenEBench infrastructure, to facilitate a variety of community-driven challenges to address the diversity of the SCO applications.\n\nThe SCO community will perform periodic reviews of highly performant and rapidly adopted methods for registration in the bio.tools catalogue. To this end we will work closely also with the EDAM ontology to define single-cell specific keywords, which will help us not only to annotate the tools but also tag courses in TeSS.\n\nThe computing resource requirements of SCO data analysis increase constantly as the scale and modality of the data sets grow. The discussion between the SCO Community and the ELIXIR Compute Platform is therefore vital to ensure sufficient resources. The Community will also benefit from the Compute Platform’s Container Orchestration task, which will allow execution of containerised software tools and workflow workloads supporting public and sensitive data across ELIXIR Nodes. The ELIXIR Authentication and Authorisation Infrastructure (AAI) will be supported in the context of sensitive SCO data and whenever controlled access will be needed, we count on learning from the HCA’s experience on this matter.\n\nThe ELIXIR SCO Community will promote the development and usage of standards of metadata and file formats to ensure reproducibility of analyses and data reuse across biological and bioinformatics research communities. We will support existing efforts for aggregating and disseminating related metadata standards, e.g. from ArrayExpress, the HCA and further efforts. This is particularly important for emerging spatially resolved data, for which we aim to investigate efficient and scalable reporting structures, in line with current efforts in imaging and omics databases (Table 2).\n\nAn important consideration for sensitive human data is the General Data Protection Regulation (GDPR). To comply with the GDPR, raw human sequencing data deposited in EGA is protected and requires approval of the Data Access Committee Officer (DACO) as well as Data Transfer Agreements (DTA) outlining the conditions for allowing access to sensitive data. However, there is heterogeneous interpretation of the GDPR across Europe, and to facilitate this there have been a number of nationally Federated EGAs being established. Other non-human raw sequencing data would be deposited in ENA and would not be subject to these restrictions.\n\nThe ELIXIR SCO Community will encourage all data generators to ensure their data is available from an ELIXIR core data resource, or is deposited with a suitable ELIXIR core deposition resource, wherever possible, to ensure maximum data reuse and long term sustainability of all SCO data across the broader community. Via connections to key ELIXIR resources at EMBL-EBI (ENA, EGA, ArrayExpress and BioSamples database), we will promote discussions with these data resources to encourage the adoption and development of standards, where needed, to support the rapid pace of technology change in the single-cell field. We will leverage EMBL-EBI connections to the HCA Data Coordination Platform to broker the HCA data to ELIXIR core data resources and deposition resources.\n\n\nAlignment with other European and global SCO initiatives\n\nThe SCO Community will bring together data standardization efforts across Europe and combine them with global collaborations. The EMBL-EBI Node is a member of the global HCA community, whose mission is to create comprehensive reference maps of all human cells as a basis for both understanding human health and diagnosing, monitoring, and treating disease.15 It is also involved in the NIH-supported HuBMAP consortium,16 which develops tools to create an open, global atlas of the human body at the cellular level. The EMBL-EBI has already led an international effort to define the first guidelines for metadata standards of scRNA-seq experiments,58 involving members of the HCA and HuBMAP data platforms. As SCO techniques develop, we expect these guidelines to evolve to enable reproducible analysis of other methods, such as scATAC-seq, CITE-seq, single-cell HiC, to name a few.\n\nImportantly, the ELIXIR SCO Community will align its activities with the LifeTime FET initiative,71 which combines single-cell multi-omics technologies with artificial intelligence and machine learning in order to revolutionize healthcare by tracking, understanding, and treating human cells during diseases. The LifeTime consortium includes over 90 research institutes and 70 supporting companies across Europe. Scientists from some of ELIXIR Nodes belong to both the LifeTime initiative and the SCO Community, thereby providing a direct link between them.\n\nWhile HCA, HuBMAP and LifeTime focus on human cells, it is important to note that SCO technologies are used for different organisms, and thereby the ELIXIR SCO Community is not limited to human research. For example, the EMBL-EBI is also involved in the Fly Cell Atlas consortium.72\n\nThe training activities of the SCO Community will be enriched by collaboration with the Global Organization for Bioinformatics Learning, Education and Training (GOBLET).73 GOBLET’s mission is to cultivate the global bioinformatics trainer community, set standards and provide high-quality resources to support learning, education and training. The emerging SCO Community and GOBLET co-organized a global workshop for single-cell RNA-seq data analysis trainers in 2021. Sharing information about different training approaches, materials and datasets was considered very useful by the participants, and follow-up workshops are planned.\n\nFinally, the SCO Community is discussing with the emerging SCO Community of Australian BioCommons, which is currently collecting user needs and finding solutions to the challenges identified, similar to us.\n\n\nConclusions\n\nThe SCO paradigm represents a revolution in the life sciences that pushes the boundaries of what can be explored, creating both new opportunities and challenges. We are witnessing increasing numbers of individual- and multi-omics modalities, and spatio-temporally resolved read outs. Both the rapid pace of advancement and adoption indicate that SCO will become the new normal in the life sciences. In the past five years, many ELIXIR Nodes have been working to assemble resources with the goal of developing future-proof guidelines and infrastructure as well as delivering training to SCO scientists. Here, we defined key goals at different infrastructural areas in order to create the ELIXIR SCO Community (Table 2) to ultimately strengthen current and foster new collaborations, and establish sustainable European and global frameworks for SCO research.\n\nData on scientific publications on SCO and number of cells sequenced was obtained from the Single-cell studies database.74 Data on SCO tools was taken from the publicly available repository of the scRNA-tools database.34\n\n\nAuthor contributions\n\nPC, PMP, IP, TB, JL, KH and EK conceptualized the study. PC performed data curation and visualization. KH performed project administration. PC, AM, RAC, PMP, LPS, AGU, LA, SCG, BS, MA, NI and EK wrote the original draft of the manuscript. PC, AM, PMP, LPS, AGU, CS, BS, PV, H-RH, BL, JMH, BG, WH, RK, TR, AB, PF, KH, NI, and EK reviewed and edited the manuscript.", "appendix": "Acknowledgments\n\nWe would like to thank several members of ELIXIR Nodes for useful discussions and input: Ana Melo (PT), Andrei Zinovyev (FR), Åsa Björklund (SE), Celia van Gelder (NL), Ernesto Picardi (IT), Philip Lijnzaad (NL), Jan Korbel (DE), Joaquin Dopazo (ES) Loredana Le Pera (IT), Priit Adler (EE), Ricardo Leite (PT), Silvie Fexova (EMBL-EBI), Ståle Nygård (NO), Victoria Dominguez del Angel (FR).\n\n\nReferences\n\nLacar B, Linker SB, Jaeger BN, et al.: Nuclear RNA-seq of single neurons reveals molecular signatures of activation. Nat. Commun. 2016 Apr; 7: 11022. PubMed Abstract \| Publisher Full Text\n\nTang F, Barbacioru C, Wang Y, et al.: mRNA-Seq whole-transcriptome analysis of a single cell. Nat. Methods. 2009 May; 6(5): 377–382. PubMed Abstract \| Publisher Full Text\n\nPicelli S, Björklund ÅK, Faridani OR, et al.: Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat. Methods. 2013 Nov; 10(11): 1096–1098. PubMed Abstract \| Publisher Full Text\n\nZheng GXY, Terry JM, Belgrader P, et al.: Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 2017 Jan 16; 8(1): 14049. PubMed Abstract \| Publisher Full Text\n\nBuenrostro JD, Wu B, Litzenburger UM, et al.: Single-cell chromatin accessibility reveals principles of regulatory variation. Nature. 2015 Jul; 523(7561): 486–490. PubMed Abstract \| Publisher Full Text\n\nAngermueller C, Clark SJ, Lee HJ, et al.: Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat. Methods. 2016 Mar; 13(3): 229–232. PubMed Abstract \| Publisher Full Text\n\nLuo C, Keown CL, Kurihara L, et al.: Single Cell Methylomes Identify Neuronal Subtypes and Regulatory Elements in Mammalian Cortex. Science. 2017 Aug; 357(6351): 600–604. PubMed Abstract \| Publisher Full Text\n\nNagano T, Lubling Y, Stevens TJ, et al.: Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. Nature. 2013 Oct; 502(7469): 59–64. PubMed Abstract \| Publisher Full Text\n\nBandura DR, Baranov VI, Ornatsky OI, et al.: Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal. Chem. 2009 Aug; 81(16): 6813–6822. PubMed Abstract \| Publisher Full Text\n\nZhu C, Preissl S, Ren B: Single-cell multimodal omics: the power of many. Nat. Methods. 2020 Jan; 17(1): 11–14. Publisher Full Text\n\nLähnemann D, Köster J, Szczurek E, et al.: Eleven grand challenges in single-cell data science. Genome Biol. 2020 Feb; 21(1): 31. Publisher Full Text\n\nHarrow J, Hancock J; ELIXIR-EXCELERATE Community et al.: ELIXIR-EXCELERATE: establishing Europe’s data infrastructure for the life science research of the future. EMBO J. 2021 Mar 15 [cited 2022 Feb 2]; 40(6). Publisher Full Text\n\nMethod of the Year 2013. Nat. Methods. 2014 Jan; 11(1): 1–1. Publisher Full Text\n\nSvensson V, Vento-Tormo R, Teichmann SA: Exponential scaling of single-cell RNA-seq in the past decade. Nat. Protoc. 2018 Apr; 13(4): 599–604. PubMed Abstract \| Publisher Full Text\n\nRegev A, Teichmann SA, Lander ES, et al.: The Human Cell Atlas. Elife. 2017 Dec; 6: e27041. PubMed Abstract \| Publisher Full Text\n\nHuBMAP Consortium: The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. Nature. 2019 Oct; 574(7777): 187–192. PubMed Abstract \| Publisher Full Text\n\nVistain LF, Tay S: Single-Cell Proteomics. Trends Biochem. Sci. 2021 Aug 1; 46(8): 661–672. Publisher Full Text\n\nStoeckius M, Hafemeister C, Stephenson W, et al.: Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods. 2017 Sep; 14(9): 865–868. PubMed Abstract \| Publisher Full Text\n\nRedmond D, Poran A, Elemento O: Single-cell TCRseq: paired recovery of entire T-cell alpha and beta chain transcripts in T-cell receptors from single-cell RNAseq. Genome Med. 2016 Dec; 8(1): 80. PubMed Abstract \| Publisher Full Text\n\nClark SJ, Argelaguet R, Kapourani C-A, et al.: scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat. Commun. 2018 Dec; 9(1): 781. PubMed Abstract \| Publisher Full Text\n\nMethod of the Year 2020: spatially resolved transcriptomics. Nat. Methods. 2021 Jan; 18(1): 1–1. PubMed Abstract \| Publisher Full Text\n\nEng C-HL, Lawson M, Zhu Q, et al.: Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. Nature. 2019 Apr; 568(7751): 235–239. PubMed Abstract \| Publisher Full Text\n\nLee JH, Daugharthy ER, Scheiman J, et al.: Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues. Nat. Protoc. 2015 Mar; 10(3): 442–458. PubMed Abstract \| Publisher Full Text\n\nXia C, Fan J, Emanuel G, et al.: Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression. Proc. Natl. Acad. Sci. U. S. A. 2019 Sep; 116(39): 19490–19499. PubMed Abstract \| Publisher Full Text\n\nMoses L, Pachter L: Museum of Spatial Transcriptomics. Bioinformatics. 2021 May [cited 2022 Jan 25]. Publisher Full Text\n\nGoltsev Y, Samusik N, Kennedy-Darling J, et al.: Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging. Cell. 2018 Aug; 174(4): 968–981.e15. PubMed Abstract \| Publisher Full Text\n\nRappez L, Stadler M, Triana S, et al.: SpaceM reveals metabolic states of single cells. Nat. Methods. 2021 Jul; 18(7): 799–805. PubMed Abstract \| Publisher Full Text\n\nPerkel JM: Starfish enterprise: finding RNA patterns in single cells. Nature. 2019 Aug; 572(7770): 549–551. PubMed Abstract \| Publisher Full Text\n\nSmith RH, Chen Y-C, Seifuddin F, et al.: Genome-Wide Analysis of Off-Target CRISPR/Cas9 Activity in Single-Cell-Derived Human Hematopoietic Stem and Progenitor Cell Clones. Genes. 2020 Dec; 11(12): 1501. PubMed Abstract \| Publisher Full Text\n\nten Hacken E , Clement K, Li S, et al.: High throughput single-cell detection of multiplex CRISPR-edited gene modifications. Genome Biol. 2020 Dec; 21(1): 266. PubMed Abstract \| Publisher Full Text\n\nYang L, Chan AKN, Miyashita K, et al.: High-resolution characterization of gene function using single-cell CRISPR tiling screen. Nat. Commun. 2021 Dec; 12(1): 4063. PubMed Abstract \| Publisher Full Text\n\nZafar H, Lin C, Bar-Joseph Z: Single-cell lineage tracing by integrating CRISPR-Cas9 mutations with transcriptomic data. Nat. Commun. 2020 Dec; 11(1): 3055. PubMed Abstract \| Publisher Full Text\n\nDixit A, Parnas O, Li B, et al.: Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens. Cell. 2016 Dec 15; 167(7): 1853–1866.e17. PubMed Abstract \| Publisher Full Text\n\nZappia L, Phipson B, Oshlack A: Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database. Schneidman D, editor. PLoS Comput. Biol. 2018 Jun; 14(6): e1006245. PubMed Abstract \| Publisher Full Text\n\nStegle O, Teichmann SA, Marioni JC: Computational and analytical challenges in single-cell transcriptomics. Nat. Rev. Genet. 2015 Mar; 16(3): 133–145. PubMed Abstract \| Publisher Full Text\n\nLuecken MD, Theis FJ: Current best practices in single-cell RNA-seq analysis: a tutorial. Mol. Syst. Biol. 2019 Jun [cited 2022 Feb 3]; 15(6): e8746. PubMed Abstract \| Publisher Full Text\n\nLytal N, Ran D, An L: Normalization Methods on Single-Cell RNA-seq Data: An Empirical Survey. Front. Genet. 2020 Feb; 11: 41. PubMed Abstract \| Publisher Full Text\n\nHafemeister C, Satija R: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol. 2019 Dec 23; 20(1): 296. PubMed Abstract \| Publisher Full Text\n\nLause J, Berens P, Kobak D: Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data. Genome Biol. 2021 Sep 6; 22(1): 258. PubMed Abstract \| Publisher Full Text\n\nSoneson C, Robinson MD: Bias, robustness and scalability in single-cell differential expression analysis. Nat. Methods. 2018 Apr; 15(4): 255–261. Publisher Full Text\n\nSquair JW, Gautier M, Kathe C, et al.: Confronting false discoveries in single-cell differential expression. Nat. Commun. 2021 Sep 28; 12(1): 5692. PubMed Abstract \| Publisher Full Text\n\nOsumi-Sutherland D, Xu C, Keays M, et al.: Cell type ontologies of the Human Cell Atlas. Nat. Cell Biol. 2021 Nov; 23(11): 1129–1135. PubMed Abstract \| Publisher Full Text\n\nTran HTN, Ang KS, Chevrier M, et al.: A benchmark of batch-effect correction methods for single-cell RNA sequencing data. Genome Biol. 2020 Dec; 21(1): 12. PubMed Abstract \| Publisher Full Text\n\nSaelens W, Cannoodt R, Todorov H, et al.: A comparison of single-cell trajectory inference methods. Nat. Biotechnol. 2019 May; 37(5): 547–554. PubMed Abstract \| Publisher Full Text\n\nTian L, Dong X, Freytag S, et al.: Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments. Nat. Methods. 2019 Jun; 16(6): 479–487. Publisher Full Text\n\nAbdelaal T, Michielsen L, Cats D, et al.: A comparison of automatic cell identification methods for single-cell RNA sequencing data. Genome Biol. 2019 Dec; 20(1): 194. PubMed Abstract \| Publisher Full Text\n\nHou W, Ji Z, Ji H, et al.: A systematic evaluation of single-cell RNA-sequencing imputation methods. Genome Biol. 2020 Dec; 21(1): 218. PubMed Abstract \| Publisher Full Text\n\nLuecken MD, Büttner M, Chaichoompu K, et al.: Benchmarking atlas-level data integration in single-cell genomics. Nat. Methods. 2022 Jan; 19(1): 41–50. PubMed Abstract \| Publisher Full Text\n\nWeber LM, Saelens W, Cannoodt R, et al.: Essential guidelines for computational method benchmarking. Genome Biol. 2019 Jun; 20(1): 125. PubMed Abstract \| Publisher Full Text\n\nMangul S, Martin LS, Hill BL, et al.: Systematic benchmarking of omics computational tools. Nat. Commun. 2019 Mar; 10(1): 1393. PubMed Abstract \| Publisher Full Text\n\nMeyer P, Saez-Rodriguez J: Advances in systems biology modeling: 10 years of crowdsourcing DREAM challenges. Cell Syst. 2021 Jun 16; 12(6): 636–653. Publisher Full Text\n\nCZI: Open Problems in Single Cell Analysis. Open Problems in Single Cell Analysis. [cited 2021 Dec 2].Reference Source\n\nAfgan E, Baker D, Batut B, et al.: The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res. 2018 Jul; 46(W1): W537–W544. PubMed Abstract \| Publisher Full Text\n\nKallio MA, Tuimala JT, Hupponen T, et al.: Chipster: user-friendly analysis software for microarray and other high-throughput data. BMC Genomics. 2011 Dec; 12(1): 507. PubMed Abstract \| Publisher Full Text\n\nHao Y, Hao S, Andersen-Nissen E, et al.: Integrated analysis of multimodal single-cell data. Cell. 2021 Jun; 184(13): 3573–3587.e29. PubMed Abstract \| Publisher Full Text\n\nWolf FA, Angerer P, Theis FJ: SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 2018 Feb 6; 19(1): 15. PubMed Abstract \| Publisher Full Text\n\nBrazma A, Ball C, Bumgarner R, et al.: INSEQE: Minimum Information about a high-throughput Nucleotide SeQuencing Experiment - a proposal for standards in functional genomic data reporting.2012 Jun 1 [cited 2022 Feb 6].Reference Source\n\nFüllgrabe A, George N, Green M, et al.: Guidelines for reporting single-cell RNA-seq experiments. Nat. Biotechnol. 2020 Dec; 38(12): 1384–1386. PubMed Abstract \| Publisher Full Text\n\nRood JE, Stuart T, Ghazanfar S, et al.: Toward a Common Coordinate Framework for the Human Body. Cell. 2019 Dec 12; 179(7): 1455–1467. PubMed Abstract \| Publisher Full Text\n\nBest DE, SCH Md, Bennett WC, et al.:Update of the ACR-NEMA digital imaging and communications in medicine standard. Medical Imaging VI: PACS Design and Evaluation. SPIE; 1992 [cited 2022 Feb 5]. p. 356–61. Publisher Full Text\n\nVia A, Attwood TK, Fernandes PL, et al.: A new pan-European Train-the-Trainer programme for bioinformatics: pilot results on feasibility, utility and sustainability of learning. Brief. Bioinform. 2019 Mar; 20(2): 405–415. PubMed Abstract \| Publisher Full Text\n\nMorgan SL, Palagi PM, Fernandes PL, et al.: The ELIXIR-EXCELERATE Train-the-Trainer pilot programme: empower researchers to deliver high-quality training. F1000Res. 2017 Aug; 6: 1557. Publisher Full Text\n\nWilkinson MD, Dumontier M, Aalbersberg IJ, et al.: The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016 Mar; 3(1): 160018. PubMed Abstract \| Publisher Full Text\n\nGarcia L, Batut B, Burke ML, et al.: Ten simple rules for making training materials FAIR. PLoS Comput. Biol. 2020 May 21; 16(5): e1007854. PubMed Abstract \| Publisher Full Text\n\nBeard N, Bacall F, Nenadic A, et al.: TeSS: a platform for discovering life-science training opportunities. Bioinformatics. 2020 May 1; 36(10): 3290–3291. PubMed Abstract \| Publisher Full Text\n\nBatut B, Hiltemann S, Bagnacani A, et al.: Community-Driven Data Analysis Training for Biology. Cell Syst. 2018 Jun 27; 6(6): 752–758.e1. Publisher Full Text\n\nGrüning B, Dale R, Sjödin A, et al.: Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat. Methods. 2018 Jul; 15(7): 475–476. Publisher Full Text\n\nda Veiga LF , Grüning BA, Alves Aflitos S, et al.: BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15; 33(16): 2580–2582. Publisher Full Text\n\nGoble C, Soiland-Reyes S, Bacall F, et al.: Implementing FAIR Digital Objects in the EOSC-Life Workflow Collaboratory. Zenodo. 2021 Mar [cited 2022 Feb 9]. Reference Source\n\nCapella-Gutierrez S, de la Iglesia D , Haas J, et al.: Lessons Learned: Recommendations for Establishing Critical Periodic Scientific Benchmarking. bioRxiv. 2017 [cited 2022 Feb 4]; p. 181677. Publisher Full Text\n\nRajewsky N, Almouzni G, Gorski SA, et al.: LifeTime and improving European healthcare through cell-based interceptive medicine. Nature. 2020 Nov; 587(7834): 377–386. PubMed Abstract \| Publisher Full Text\n\nLi H, Janssens J, De Waegeneer M, et al.: Fly Cell Atlas: a single-cell transcriptomic atlas of the adult fruit fly. Genomics. 2021 Jul [cited 2022 Jan 13]. Publisher Full Text\n\nAttwood TK, Atwood TK, Bongcam-Rudloff E, et al.: GOBLET: the Global Organisation for Bioinformatics Learning, Education and Training. PLoS Comput. Biol. 2015 Apr; 11(4): e1004143. PubMed Abstract \| Publisher Full Text\n\nSvensson V, da Veiga BE , Pachter L: A curated database reveals trends in single-cell transcriptomics. Database. 2020 Jan 1; 2020: baaa073. PubMed Abstract \| Publisher Full Text" }	[ { "id": "221768", "date": "24 Nov 2023", "name": "Xiao-Yang Zhao", "expertise": [ "Reviewer Expertise Single-cell omics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nSingle-Cell Omics (SCO) Community is recently launched in ELIXIR, representing the field of single-cell and spatial omics. In this Whitepaper, Czarnewski and colleagues summarized the current status and dilemmas of single-cell multi-omics (up until January 2022), and elaborated on some of the outstanding contributions made by the ELIXIR SCO community in helping to solve challenges in training, interoperability, standardisation, benchmarking, and computational resources. The author also clarified plans for the next few years. Overall, community-driven ELIXIR activities in single-cell omics are in great demand, the work done by colleagues in the SCO community is well planned and promising. This paper is well organized and written. Here, I have some suggestions that may help the European and even global scientific researchers to understand the SCO community and platform and participate in it. At the same time, some concerns need to be addressed.\nMajor:\nSingle-cell sequencing is currently one of the most commonly used and advantageous technologies in life science research. While there is always a long time lag between the publication and application of new tools, could SCO community invite the main creative team of new tools directly participates in the community, to make training and revolution faster.\n\nA virtuous cycle organization always needs a certain incentive mechanism. On the one hand, it encourages more experts to participate in training and dissemination; on the other hand, it encourages researchers to participate in learning and integration. Please describe some of your organization’s efforts or related implementation plans on the incentive mechanism?\n\nThese is little specific and detailed SCO community use cases throughout this paper, making it hard to understand how SCO community solves challenges. As the author stated, data output is mushrooming, how to quickly evaluate the quality of data, and how to compare and integrate data from different sources? Can authors take this as an example to briefly describe a specific case in the SCO community?\n\nIs it possible to join forces with large life science journal publishers and science funding agencies to evaluate new technologies in unpublished articles or application forms? Of course, strict confidentiality must be maintained.\n\nIt has been more than a year since the author submitted the first version article. Can you further summarize the relevant development progress, such as high-resolution spatial transcriptome technology and third-generation sequencing technology?\nMinor:\nPlease summarize the current status and challenges in data integration of NGS and third-generation sequencing.\n\nGenome annotation is iterating, and genome reference changing has a great impact on analysis. How should we solve these difficulties?\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nAre arguments sufficiently supported by evidence from the published literature? Yes\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Partly", "responses": [] }, { "id": "221769", "date": "15 Dec 2023", "name": "Feng Zhu", "expertise": [ "Reviewer Expertise Bioinformatics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nPaulo Czarnewski et al. provided an overview of the current state of single-cell omics (SCO) development as of January 2022, encompassing data, publications, and tools. They summarized the limitations in data storage, annotation, and tool utilization. Additionally, they discussed the future plans of the ELIXIR SCO community, aiming to enhance the overall landscape of single-cell research through personnel training, tool benchmarking, and computational platform construction, among other methods. It has the potential to benefit researchers in related fields and deserves publication. However, there are certain aspects that may warrant consideration.\n1. The community may facilitate the better utilization of these tools or algorithms by undertaking two aspects of work. Firstly, organizing competitions targeting key algorithmic challenges to appropriately compare the tools, enabling researchers to understand how to select the most suitable ones. Secondly, requesting tool or algorithm providers to participate in the competitions while also providing user instructions and simplifying the operational complexity as much as possible, so as to truly assist the majority of researchers.\n2. Single-cell omics has rapidly evolved and now encompasses single-cell transcriptomics, single-cell proteomics, single-cell metabolomics, and more. When establishing communities, it may be beneficial to maintain a certain level of independence among these different branches of omics, as researchers in different omics fields may face distinct challenges.\n3. Will the training sessions only be open to European researchers? Are there any restrictions based on other regions or ethnicities?\n4. Perhaps the authors could update the statistical information in Figure 1, as nearly two years have passed since January 2022.\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nAre arguments sufficiently supported by evidence from the published literature? Yes\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-869
https://f1000research.com/articles/11-228/v1	24 Feb 22	{ "type": "Software Tool Article", "title": "The Neuroimaging Data Model Linear Regression Tool (nidm_linreg): PyNIDM Project", "authors": [ "Ashmita Kumar", "Albert Crowley", "Nazek Queder", "JB Poline", "Satrajit S. Ghosh", "David Kennedy", "Jeffrey S. Grethe", "Karl G. Helmer", "David B. Keator", "Albert Crowley", "Nazek Queder", "JB Poline", "Satrajit S. Ghosh", "David Kennedy", "Jeffrey S. Grethe", "Karl G. Helmer", "David B. Keator" ], "abstract": "The Neuroimaging Data Model (NIDM) is a series of specifications for describing all aspects of the neuroimaging data lifecycle from raw data to analyses and provenance. NIDM uses community-driven terminologies along with unambiguous data dictionaries within a Resource Description Framework (RDF) document to describe data and metadata for integration and query. Data from different studies, using locally defined variable names, can be retrieved by linking them to higher-order concepts from established ontologies and terminologies. Through these capabilities, NIDM documents are expected to improve reproducibility and facilitate data discovery and reuse. PyNIDM is a Python toolbox supporting the creation, manipulation, and querying of NIDM documents. Using the query tools available in PyNIDM, users are able interrogate datasets to find studies that have collected variables measuring similar phenotypic properties. This, in turn, facilitates the transformation and combination of data across multiple studies.\nThe focus of this manuscript is the linear regression tool which is a part of the PyNIDM toolbox and works directly on NIDM documents. It provides a high-level statistical analysis that aids researchers in gaining more insight into the data that they are considering combining across studies. This saves researchers valuable time and effort while showing potential relationships between variables. The linear regression tool operates through a command-line interface integrated with the other tools (pynidm linear-regression) and provides the user with the opportunity to specify variables of interest using the rich query techniques available for NIDM documents and then conduct a linear regression with optional contrast and regularization.", "keywords": [ "Linear Regression", "Neuroimaging", "PyNIDM", "Neuroimaging Data Model", "Machine Learning" ], "content": "Introduction\n\nThe Neuroimaging Data Model (NIDM) (Keator et al. 2013; NIDM Working Group; Maumet et al. 2016) (Neuroimaging Data Model, RRID:SCR_013667) was started by an international team of volunteers to create specifications for describing all aspects of the neuroimaging data lifecycle. NIDM is built upon the PROV Standard (Moreau et al. 2008; “PROV-Overview”). It consists of three specifications: Experiment, Results, and Workflow. Using sematic web techniques (“Semantic Web - W3C”), these specifications were envisioned to capture information on all aspects of the neuroimaging data lifecycle, producing graphs linking each result’s artifact with the workflow that produced it and the data used in the computation. These graphs can be serialized into a variety of text-based formats (NIDM documents), and with the capabilities of the semantic web, can be used to link datasets together through annotations with terms from formal terminologies, complete data dictionaries of study variables, and linkage of study variables to broader concepts. These annotations provide a critical capability to aid in reproducibility and replication of studies, as well as data discovery in shared resources. The NIDM-Experiment model consists of a simple project-session-acquisition hierarchy which can be used to describe both the content and metadata about experimental studies and derived (e.g., regional brain volume, mass-univariate functional brain analysis) neuroimaging data. It has been used to describe many large publicly-available human neuroimaging datasets (e.g. ABIDE (Di Martino et al. 2014), ADHD200 (Milham et al. 2011), CoRR (Zuo et al. 2014) (Consortium for Reliability and Reproducibility, RRID:SCR_003774), OpenNeuro (“OpenNeuro”) (OpenNeuro, RRID:SCR_005031) datasets) along with providing unambiguous descriptions of the clinical, neuropsychological, and imaging data collected as part of those studies.\n\nPyNIDM (PyNIDM) (PyNIDM, RRID:SCR_021022) v3.9.5 is a Python toolbox under active development that supports the creation, manipulation, and query of NIDM documents. It is open-source and hosted on GitHub, distributed under the Apache License, Version 2.0 (“Apache License, Version 2.0”). PyNIDM consists of tools to work with NIDM documents such as conversion from BIDS (Gorgolewski et al. 2016), graph visualization, serialization format conversion, merging and query. Querying of NIDM documents is supported using a command-line RESTful (Ravan et al. 2020) interface (i.e. pynidm query) which executes SPARQL (“SPARQL Query Language for RDF”) queries. Using the query functionality and the NIDM document semantics, users can quickly identify datasets that measured similar properties and may be combined for further investigation.\n\nBeyond the existing tools that have been written to support NIDM documents, some high-level statistical analysis tools are needed to provide investigators with an opportunity to gain more insight into data they may be interested in combining for a complete scientific investigation. Combining datasets collected across different studies is not a trivial task. It requires both a complete, unambiguous description of the data and how it was collected, along with a varying number of transformations to align, where possible, disparate data. The process of transforming data is often quite time-consuming and therefore understanding whether the identified datasets, at a high level, might have some interesting relationships prior to committing to a full scientific study is prudent. Here we report on a tool that provides such capabilities; namely, a simple linear modeling tool supporting NIDM documents and integrated into the existing PyNIDM suite of tools.\n\nWhile tools and libraries for statistics and machine learning algorithms are numerous, there are none that can be directly applied to NIDM documents. The linear regression algorithm presented here allows scientists studying the human brain to easily find relationships between variables across datasets while retaining the provenance present in NIDM documents. The algorithm has the ability to query for specific variables or across similar variables from different studies using concept annotations on the variables. It then provides the user with the ability to construct arbitrary linear models on those data, supporting interactions between variables, contrasts of learned parameter sets, and L1 and L2 regularization (Nagpal 2017). There is no comparable tool for this use case.\n\n\nMethods\n\nThe linear regression tool, nidm_linreg, uses the PyNIDM query functionality to aggregate data in NIDM documents serialized using the standard Terse Resource Description Framework (RDF) Triple Language (TURTLE) (“RDF 1.1 Turtle”), a common semantic-web serialization format that is both structured for ease of use with computers and relatively easy for humans to read. Researchers have the ability to construct custom models based on their scientific goals. The source code is available on Zenodo and full details can be found in the Software Availability statement (Keator et al. 2021).\n\nThus, nidm_linreg is a machine learning algorithm that can work on complex datasets described using the NIDM linked-data format, while being reasonably easy to use. Researchers have the ability to conduct a preliminary analysis to understand if it is worth the effort to pursue combining datasets and doing the transformations necessary to integrate those datasets. One can quickly determine if there are high-level relationships in the datasets and look at the different weights to decide what variables may warrant further study.\n\nThe tool provides a simple command-line user interface (Figure 1) based on the “Click” Python library (“Welcome to Click — Click Documentation (8.0.X)”) which integrates the linear regression module with existing PyNIDM tools (e.g. pynidm linear-regression, pynidm query, pynidm convert, etc.).\n\nTo use the tool, the user runs the command pynidm linear-regression with a variety of required and optional parameters. The first parameter, “-nl”, is a comma- separated list of NIDM serialized TURTLE files, each representing a single dataset or a collection site within a multi-site research project or multiple datasets (Figure 2). A useful set of NIDM documents describing publicly-available neuroimaging data from the ABIDE, ADHD200, and CoRR studies along with datasets in the OpenNeuro database can be found on GitHub (D. Keator) The next parameter, “-model” provides the user with the ability to construct a linear model using notation found in popular statistics packages (e.g., R statistical software (Ripley 2001) (R Project for Statistical Computing, RRID:SCR_001905)). The syntax follows the scheme “dependent variable (DV) = independent variable 1 (IV1) + independent variable 2 (IV2) + … + IVX”. To encode interactions between IV1 and IV2 in the above example, one can use the common “” syntax: “DV = IV1 + IV2 + IV1IV2”.\n\nTo determine what variables or data elements are available from a set of NIDM documents, the first step is to use “pynidm query” to do a data element search of the NIDM documents. From this search, the user can see what data elements are available in the selected NIDM documents and understand some details of those data elements (e.g., ranges, categories, data type, etc.). After performing the data elements query of the NIDM documents and selecting independent and dependent variables of interest, one proceeds with constructing the linear model with the pynidm linear-regression tool.\n\nIn the example shown in Figure 2, we have first run a pynidm query operation on the NIDM documents and identified four variables of interest: supratentorial brain volume (fs_000008), diagnostic group (DX_GROUP), performance IQ (PIQ_tca9ck), and age. The model specified establishes the relationship between the DV, brain volume, and the IVs, diagnostic group, performance IQ, and age. In this example, fs_000008 is the fixed unique identifier (UUID) of the supratentorial brain volume computed with the FreeSurfer software (Fischl 2012) (FreeSurfer, RRID:SCR_001847) using the original Magnetic Resonance Imaging (MRI) structural scans of the brain. This particular UUID is fixed because it identifies a specific brain region and measurement computed with the FreeSurfer software and will not change across datasets that derive brain volume measurements with FreeSurfer. DX_GROUP is the name of the study-specific variable describing the diagnostic group assigned to participants. PIQ_tca9ck is the performance IQ measure collected on study participants and is the UUID created for this data element when the NIDM documents were created for this dataset. Note, this particular UUID is not guaranteed to be the same across NIDM documents from different studies. Finally, “http://uri.interlex.org/ilx_0100400” is the age of the participants using a URL form to reference a concept describing the high-level measure of age which has been used to annotate the variables measuring age across studies. Here we use a concept URL that has been mapped to each dataset’s separate variables that store the age of participants. By using the concept URL, we avoid the complexity of different variable names being used to store consistent information (e.g., age) across datasets.\n\nThis example shows that one can select data elements from the NIDM documents for linear regression using three specific forms: (1) using the UUID of the objects in the NIDM graph documents; (2) using the distinct variable name from the original dataset, also stored as metadata in the NIDM graph documents; (3) using a high-level concept that has been associated with specific variables described by the concept across datasets, used to make querying across datasets with different variable names but measuring the same phenomenon easier. We support these three distinct forms of selecting data elements to enable distinct usage patterns. Some investigators will use NIDM documents of their internal studies and want to be able to reference data elements using their study-specific variable names. Other investigators may want to use variables from different studies and thus the variable names are unlikely to be the same; thus, we support the use of selecting variables based on high-level concepts. In practice, users will not often mix forms of referring to data elements within the same model, but we show it here to make evident the flexibility of the tool.\n\nThe optional “-contrast” parameter allows one to select one or more IVs to contrast the parameter estimates for those IVs. The contrast variable in this example is “DX_GROUP” which describes the diagnostic group of each participant. Our tool supports multiple methods of coding treatment variables (e.g., treatment coding (Figure 3), simple coding, sum coding, backward difference coding, and Helmert coding) as made available by the Patsy Python library (Brooke 1923). The user can select multiple independent variables to contrast and/or contrasts on interactions. The results of the treatment coding contrast applied in Figure 2 can be seen in Figure 3.\n\nThe optional “-r” parameter allows the user to select L1 (Lasso) or L2 (Ridge) regularization implemented in scikit-learn (Varoquaux et al. 2015) (scikit-learn, RRID:SCR_002577). In either case, regularizing prevents the data from being overfit, potentially improving model generalizability and demonstrating which variables have the strongest relationships with the dependent variable. The regularization weight is iteratively determined across a wide range of regularization weightings using 10-fold cross-validation, selecting the regularization weight yielding the maximum likelihood.\n\nThere are error checks within the code to make sure the researcher has feedback on why a model cannot run, whether it is because there are not enough data points or because one or more variables could not be found in one or more of the NIDM documents. This makes the experience as simple as possible for the user, which is important, as our intended audience for these tools are investigators who may have no prior experience with the semantic web and/or NIDM documents.\n\nIn the example shown in Figure 4, we have first run a pynidm query operation on the NIDM documents and identified 4 variables of interest: fs_003343, age, sex, and group. Here, fs_003343 is the fixed unique identifier (UUID) of the left hippocampus volume while age, sex, and group are names of the study-specific variables concerning the age of the participant at the time of the study, the gender, and the group the participant was in. The model specified establishes the relationship between the DV, left hippocampus volume, and the IVs, group, age, and sex. However, in this case, we also encode interactions between age and sex and age and group, as denoted by the asterisks. Also, in this model, we have used multiple IVs to contrast the parameter estimates for those IVs. The contrast variables are age and group. Finally, L2 regularization is selected for regularization.\n\nThe results of the Helmert coding contrast can be seen in Figure 5.\n\n\nOperation\n\nThe data must be in a NIDM document(s) to be used with this tool. Data can be transformed into a NIDM document directly from BIDS or tabular data files using the PyNIDM tools “bidsmri2nidm” and “csv2nidm”. Once data is transformed into NIDM, the user only needs to have a functional installation of PyNIDM and access to a terminal window or similar command-line processing tool with a functional version of Python 3. Once the user specifies the parameters, data is aggregated from the NIDM files, re-structured for the linear regression algorithm, and parameter estimates learned using ordinary least squares and returning either a printout or output file of the various coefficients and summary statistics.\n\n\nConclusions\n\nIn this work, we have designed a linear regression tool that works on linked-data NIDM documents in support of understanding relationships between variables collected across studies. This tool helps scientists evaluate relationships between data prior to fully integrating datasets for hypothesis testing which may require considerable time and resources. In our initial evaluations, this tool has shown utility for these use cases. In future work, we are creating additional machine learning tools allowing users to cluster data in a similar fashion to the linear regression tool presented here. Further, the NIDM community is working on additional functionality for the PyNIDM toolkit that transforms the value representations of the variables selected for modeling to be consistent across all NIDM documents used in the model. These transformations are made using the detailed data dictionaries included in the NIDM documents. This functionality will be included in the PyNIDM query application programmers’ interface (API) and will be immediately available to the linear regression tool presented here.\n\n\nSoftware availability\n\nSource code available from: https://github.com/incf-nidash/PyNIDM/blob/master/nidm/experiment/tools/nidm_linreg.py\n\nArchived source code at time of publication: v3.9.5, https://doi.org/10.5281/zenodo.4635287 (Keator et al., 2021)\n\nLicense: Apache License, Version 2.0", "appendix": "References\n\nApache License, Version 2.0: Copyright 2022, The Apache Software Foundation.Reference Source\n\nBrooke MC: Patsy. The Psychological Clinic 1923; 15(1-2): 41–43. PubMed Abstract\n\nConsortium for Reliability and Reproducibility (CoRR) — Consortium for Reliability and Reproducibility (CoRR) Documentation. http\n\nDi Martino A, Yan C-G, Li Q, et al.: The Autism Brain Imaging Data Exchange: Towards a Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism. Molecular Psychiatry 2014; 19(6): 659–667. PubMed Abstract \| Publisher Full Text\n\nFischl B: FreeSurfer. NeuroImage 2012; 62: 774–781. PubMed Abstract \| Publisher Full Text\n\nGorgolewski K, Auer T, Calhoun V, et al.: The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Scientific Data 2016; 3: 160044. PubMed Abstract \| Publisher Full Text\n\nKeator D: simple2_NIDM_examples: ReproNim simple2 NIDM Files for ABIDE/ADHD200 Available from Datalad. Github.Reference Source\n\nKeator D, et al.: incf-nidash/PyNIDM: PyNIDM tools v3.7.6 (dev) (v3.7.6). Zenodo 2021. Publisher Full Text\n\nKeator DB, Helmer K, Steffener J, et al.: Towards Structured Sharing of Raw and Derived Neuroimaging Data across Existing Resources. NeuroImage 2013; 82(November): 647–661. PubMed Abstract \| Publisher Full Text\n\nMaumet C, Auer T, Bowring A, et al.: Sharing Brain Mapping Statistical Results with the Neuroimaging Data Model. Scientific Data 2016; 3(December): 160102. PubMed Abstract \| Publisher Full Text\n\nMilham MP, Buitelaar J, Castellanos FX, et al.: ADHD200.2011. Reference Source\n\nMoreau L, Ludäscher B, Altintas I, et al.: Special Issue: The First Provenance Challenge. Concurrency and Computation: Practice & Experience 2008; 20(5): 409–418. Publisher Full Text\n\nNagpal A: L1 and L2 Regularization Methods. Towards Data Science 2017. October 13, 2017. Reference Source\n\nnidm_linreg: Github.Copyright 2017-202, INCF-NIDASH developers.Reference Source\n\nNIDM Working Group: NIDM. Copyright 2018, NIDM Working Group.Reference Source\n\nOpenNeuro: Copyright 2022, Stanford Center for Reproducible Neuroscience.Reference Source\n\nPROV-Overview: Copyright 2013, W3C.Reference Source\n\nPyNIDM: Github. Copyright 2017-2020, INCF-NIDASH developers.Reference Source\n\nRavan J, Person DY, Packer J, et al.: What Is REST.2020. May 31, 2020. Reference Source\n\nRDF 1.1 Turtle: Copyright 2008-2014, W3C.Reference Source\n\nRipley BD: The R Project in Statistical Computing. MSOR Connections 2001; 1(1): 23–25. Publisher Full Text\n\nSemantic Web - W3C: Copyright 2015, W3C.Reference Source\n\nSPARQL Query Language for RDF: Copyright 2006-2007, W3C.Reference Source\n\nVaroquaux G, Buitinck L, Louppe G, et al.: Scikit-Learn. GetMobile Mobile Computing and Communications 2015; 19(1): 29–33. Publisher Full Text\n\nWelcome to Click — Click Documentation (8.0.X): Copyright 2014, Pallets.Reference Source\n\nZuo X-N, Anderson JS, Bellec P, et al.: An Open Science Resource for Establishing Reliability and Reproducibility in Functional Connectomics. Scientific Data 2014; 1(December): 140049. PubMed Abstract \| Publisher Full Text" }	[ { "id": "125517", "date": "08 Apr 2022", "name": "Adam G. Thomas", "expertise": [ "Reviewer Expertise Neuroimaging", "Neuroscience", "Computer Science", "Data Science" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors have written about the nidm_linreg tool which is a linear regression tool that is now a part of the PyNIDM software. nidm_linreg was added because PyNIDM did not have a tool like this in its suite yet. The tool’s design and the paper’s focus on usage are both very thorough. This software tool article is likely of interest to PyNIDM and other members of the neuroimaging community. We have the following comments and concerns about the software and the paper:\nEchoing the concern expressed in Dec 2021 in the PyNIDM GitHub issue 309 (https://github.com/incf-nidash/PyNIDM/issues/309), it is bad practice to install Python packages outside of dependency management functionality. The nidm_linreg.py tool currently tries to quietly install 4 packages using pip if they are not present in the Python environment. This will likely cause problems and/or confusion for the user. A safe and reproducible way to provide the end-user with the dependencies they need is to provide a requirements.txt file with the repository which lets users use a specific version of the expected package dependencies. https://pip.pypa.io/en/stable/reference/requirements-file-format/\n\nWe ran the commands on the GitHub README.md (with some necessary modifications) to install and test PyNIDM (see below). pytest returned several errors and warnings (on two different platforms) that should be corrected:\nconda create -n pynidm_py3 python=3 git clone https://github.com/incf-nidash/PyNIDM.git cd PyNIDM pip install -e . pytest [snip] = 4 failed, 24 passed, 14 skipped, 3 warnings, 36 errors in 35.41s ==\n\nRunning the commands as-written in Figures 2 and 4 did not work. We cloned the simple2_NIDM_examples repository (https://github.com/dbkeator/simple2_NIDM_examples) and tried to use the data within, but we were only able to run one of the example commands successfully.\nThis felt insufficient to evaluate the reproducibility of the tool. The authors should provide commands, script, or a container such that users can reproduce the same outputs presented in the paper.\n\nThe Methods section “Implementation and use cases” covers a blend of those two things where we think it would read better to see a focused section on Implementation and a focused section on Use cases. The Implementation section could discuss the design decisions and software architecture as well as planned support. Most of the current content could move over to a Use cases section covering a use case or two (as it does now).\n\nThe paper mentioned there are “error checks” built into the tool, but no examples are shown. Including a sentence about the kinds of errors being checked for would be another useful addition.\n\nThe reference for the Patsy Python Library (Brooke 1923).on page 5 of the PDF (Methods section, 8th paragraph) is incorrect.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? No\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Partly", "responses": [ { "c_id": "8172", "date": "29 Jul 2022", "name": "Ashmita Kumar", "role": "Author Response", "response": "Thank you for your feedback on our tool. We appreciate your thoroughness and will ensure to make the required changes. To your first point, we will make sure that our package requirements are presented to the user before installation instead of using a quiet install. To your second point, while we are unsure why the error appeared, we are looking into it and attempting to reproduce it. We will be sure to address it in our next version. To your third point, we will make sure to provide a way for users to replicate the outputs in the paper by providing more specifics on how we obtained them. To your fourth point, we will separate the two sections and add to our Implementation section in our next version. To your fifth point, the error checks built in include data validation for type and quantity of that data, which we will explain in more detail. To your final point, we will try to find the correct citation. Thank you for taking the time to make this review, and we are sorry for the length of time it has taken to respond. We really appreciate it." } ] }, { "id": "125519", "date": "11 Apr 2022", "name": "Karsten Specht", "expertise": [ "Reviewer Expertise Neuroimaging", "methods development", "reliability measures" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this software tool article, the authors describe a tool that allows high-level statistical analysis for combining studies that follow the Neuroimaging Data Model (NIDM) framework. The tool is/will be part of the PyNDIM toolbox.\nIn general, this appears as a very useful tool that a larger community might want to use. However, the article is phrased and organized in a way that this might not happen. The audience of the current manuscripts is almost exclusively the NDIM community that is involved in developing the tools, but it is not directed to potential users. The main problem is, in my view, that the level of explanation and description of the tool is very minimalistic. Of course, all important aspects and relevant tools are mentioned, but only as keywords with the appropriate references. My main concern is that readers not entirely familiar with all aspects and methods incorporated into this tool will not get its importance and relevance.\nI would like to see just a few more sentences describing the key elements in a revised version. For example, readers unfamiliar with the PROV standard or the semantic web technique are already lost after the third sentence. And the introduction continues like that. For example, the “L1 and L2 regularization” is just thrown in on the first page, assuming that every reader immediately gets its relevance, but a more relevant discussion follows much later.\nSimilarly, I would have expected a more detailed description of the implementations in the section that is called “implementation and use cases”, but this section is mainly on “use cases” and very little on implementation.\nSo, in summary, I think a revised version of this article would benefit from just a few more describing lines so that this very relevant tool generates interest in a broader audience.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Partly\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "8173", "date": "29 Jul 2022", "name": "Ashmita Kumar", "role": "Author Response", "response": "Thank you for the time you have taken to review this paper. We will add more specifics to make it more accessible to potential users, defining our implementation, data structures, and technique in more detail. We apologize for the time it has taken to respond, but rest assured we are working to address it in our next version." } ] } ]	1	https://f1000research.com/articles/11-228
https://f1000research.com/articles/11-865/v1	29 Jul 22	{ "type": "Research Article", "title": "Proximate analysis of the high phytochemical activity of encapsulated Mandai cempedak (Artocarpus champeden) vinegar prepared with maltodextrin and chitosan as wall materials", "authors": [ "Anton Rahmadi", "Siti Nurjannah", "Yulian Andriyani", "Maghfirotin Marta Banin", "Miftakhur Rohmah", "Nur Amaliah", "Kartika Sari", "Aswita Emmawati", "Siti Nurjannah", "Yulian Andriyani", "Maghfirotin Marta Banin", "Miftakhur Rohmah", "Nur Amaliah", "Kartika Sari", "Aswita Emmawati" ], "abstract": "Background: Mandai cempedak vinegar (MCV) is a fermented vinegar produced from the inner skin of cempedak (Artocarpus champeden), which contains antioxidants classified as flavonoids, phenols, and tannins. These bioactive compounds are sensitive to heat and prone to oxidative damage. Therefore, an encapsulation process is proposed to protect the bioactive compounds. This study aimed to design a potential scaling-up formulation of spray-dried encapsulated MCV based on Total Soluble Solid (TSS) with the addition of maltodextrin and chitosan, followed by determining the nutrition and phytochemical values of the formulation. Methods: The formulation employed maltodextrin to achieve TSS of 15, 20, and 25 ºBrix as the primary wall material treatment factor. The second factor was chitosan as auxiliary wall material at 1, 2, and 3% (w/w of maltodextrin). Products were spray-dried at 100 ºC inlet temperature and 80 ºC outlet temperature. Analyses of nutrition, flavonoid, phenol, and tannin were conducted in triplicate for each encapsulated product. Results: The 15 ºBrix of TSS from maltodextrin with 1% chitosan emerged as the best-encapsulating material, giving 7.54% moisture, 0.75% ash, 0.42% protein, 0.35% fat, and 90.94% carbohydrate content, resulting in a phytochemical activity equivalent to 9.13 mg Catechin Equivalent kg-1, 69.61 mg Gallic Acid Equivalent kg-1, and 25.04 mg Tannic Acid Equivalent kg-1. Compared to maltodextrin, the chitosan generally contributed less to the proximate, flavonoid, phenol, and tannin content of the encapsulated MCV. Conclusions: The best formulation contained maltodextrin at 15 ºBrix of TSS and 1% chitosan. Maintaining optimum TSS was a key to producing consistent encapsulated MCV with high phytochemical activity.", "keywords": [ "chitosan", "maltodextrin", "mandai cempedak vinegar", "spray drying", "total soluble solids" ], "content": "Introduction\n\nMandai cempedak is a traditional food fermented from the inner skin of cempedak (Artocarpus champeden), technologically processed with the addition of a bacterial starter containing Lactic Acid Bacteria (LAB).1 The liquid separated from mandai cempedak solids is named mandai cempedak vinegar (MCV). MCV is produced twice as much as the weight of the solid part during fermentation. MCV developed in our design is a by-product of mandai cempedak fermentation with Lactobacillus casei as a starter.1–3 Mariana et al.4 show that MCV can reduce cholesterol levels in mice after 14 days of intervention. In addition, MCV contains bioactive, i.e., lactic acid, flavonoid compounds, and saponins. These substances may reduce cholesterol levels.5,6\n\nMCV is easily degraded during storage because of its content. The changes include oxidation of phenol and evaporation of volatile compounds. In addition, the liquid form of MCV is affected by environmental factors, i.e., temperature, oxygen, humidity, light, and other unfavorable conditions during the storage process.7,8 Therefore, the technology has been developed to protect the active compounds in MCV by converting MCV into encapsulated form. Encapsulation is the process of protecting, enclosing, or trapping the core material (liquid, gas, and solid particles) in a solid shell in the form of coating material for controlled release, immobilization, protection, or isolation of core material.9\n\nThe composition of coating materials can affect the characteristics of the resulting encapsulated product.10 This study used maltodextrin and chitosan as wall and auxiliary coating materials in producing encapsulated MCV. It is essential to maintain the stability of the Total Soluble Solid (TSS) value in the encapsulation process.11 As customarily observed from natural products,12 MCV has a tiny but inconsistent amount of soluble solids. Hence, maltodextrin contributes to TSS as a primary controlling factor for wall material.13 Maltodextrin is used because it has a high solubility in water, high viscosity, low price, and can maintain the stability of polyphenol compounds in a formulation.14,15\n\nThe auxiliary coating material used in this study is chitosan. Chitosan is non-toxic and biodegradable with some antimicrobial properties, benefiting product shelf life extension.16,17 In addition, chitosan is a biocompatible amino polysaccharide capable of forming ionic or covalent bonds with crosslinking agents and forming networks where the active compounds can be retained.18 These properties are helpful for encapsulation material of various active ingredients, enveloping bioactive compounds, and reducing oxidation.17,19 As a result, chitosan is widely used as an encapsulation agent for sensitive core materials in the pharmaceutical industry, such as lipophilic drugs,20 vitamin D2,21 ampicillin,22 and olive oil extract.23 However, chitosan is expensive. Therefore, it is used as auxiliary material in this research.\n\nSpray drying may be applied to encapsulate bioactive material from MCV because the short contact time with the medium and the high evaporation rate results in a high-quality product compared to conventional drying methods.24 As a result, the spray drying technique is relatively easy to apply in the scaling-up process for volatile or non-volatile oils and flavor encapsulation. In addition, the production cost is relatively low compared to other available technologies.25,26\n\nThis research aims to design a potential scaling-up formulation of spray-dried encapsulated MCV based on maltodextrin equivalent to specified TSS with the addition of chitosan. The experimental parameters include proximate values (moisture, ash, protein, fat, and carbohydrate contents) and phytochemical characteristics (flavonoid, tannin, and phenol). The encapsulation of MCV is expected to be a new niche seasoning flavor with the additional advantage of high bioactive capacity.\n\n\nMethods\n\nThe process of making MCV is described by Mariana et al.4 The cempedak was obtained from the traditional markets in Samarinda, East Kalimantan, Indonesia. The inner cempedak skin was cut into small pieces, cleaned with running water, and then boiled with a ratio of 1:2 (w/v) cempedak and water at 100°C for five minutes to remove the sap. The cempedak skin was then cooled to achieve room temperature (28±3°C) in a closed jar. The boiling procedure was repeated twice. The boiled cempedak skin was then placed in a sterile container, and boiled potable water was added (2:1 v/w). LAB starter was added at 4% (v/v) and was aseptically stirred until evenly distributed. The mandai cempedak was fermented for 14 days at 5-8°C (stored in the refrigerator). Subsequently, the mandai cempedak was crushed with a blender and filtered with a clean cloth. The filtered MCV was then centrifuged at 3000 revolutions per minute (RPM) for 15 minutes. The supernatant was collected and stored at 5-8°C.\n\nMCV encapsulation was carried out using a spray dryer (locally built by Maxer Sterile - Malang, Indonesia, with a capacity of 0.5-5 liter/hour, electric heating of 13 kilowatts, automatic temperature control, a yield of 8-12%, and moisture content of 3-7%). Each batch consisted of 500 mL MCV. The treatment used in the encapsulation of MCV was maltodextrin equivalent to TSS 15, 20, 25 °Brix and chitosan (1, 2, 3% w/w of maltodextrin). About 500 mL MCV and a specified maltodextrin content by TSS value were homogenized. The intended Brix value was achieved by adding maltodextrin in a stepwise manner. TSS was measured by a hand refractometer (Brix scale: 0 to 32% Brix, Automatic Temperature Compensation Range: 10-30°C) at room temperature of 28±3°C. The range of maltodextrin addition was 70-170 g, corresponding to 15 – 25 °Brix. Chitosan was added according to the treatment with concentrations of 1, 2, and 3% by weight of the maltodextrin used. The mixtures were spray-dried with the condition of 100°C inlet temperature and 80°C outlet temperature. The obtained encapsulated MCV was stored at -20±3°C for further analysis.\n\nThe water content analysis was carried out by referring to the modified Lindani27 method regarding the number of samples and the time of sample testing. A total of 0.5 grams of sample was put into the moisture analyzer (OHAUS MB 125), then the sample was flattened on a pan, and the instrument was closed again. The moisture was measured as per recommended method by the manufacturer. The results obtained were then recorded.\n\nThe measurement of ash content used the Andarwulan et al.28 method. The inorganic residue formed by burning off the organic matter of the sample in a muffle furnace at 550±50°C for four hours was referred to as ash. A pre-heated crucible was filled with 2 g of the sample. The crucible was placed in a muffle furnace at 550±50°C for four hours or until whitish-grey ash was formed. After that, the crucible was placed in the desiccator and weighed.\n\nCrude protein is calculated by multiplying the nitrogen content of the food by a factor of 6.25. This number is used because most protein contains 16% nitrogen. The Kjeldahl method is used to determine crude protein.29 Digestion, distillation, and titration are all part of the process.30 About 2 g of the material was weighed carefully in a Kjeldahl flask. About 25 ml of 97% sulfuric acid to the flask and 1 g of Kjeldahl tablet (containing Na2SO4 96.5%, CuSO4 1.5%, Se 2.0%) (Merck, USA) were added. Heat was slowly applied in a fume cupboard to avoid excessive frothing, then digestion continued for 45 minutes, or until the digesta became transparent pale green. The digesta was allowed to cool before adding 100 ml of distilled water. The digesta was rinsed 2-3 times before adding the digesting flask to the bulk. Distillation: Markham distillation device was used for distillation. The digesta was taken 10 ml of the digest to boil in the distillation equipment after heating it. About 10 ml sodium hydroxide (10 mol/l) (Merck, USA) was added to avoid ammonia loss. Five drops of methyl red indicator (0,1 % in ethanol) (Sigma-Aldrich, USA) were distill-filtered into 50 ml of 2% boric acid (Merck, USA). Titration: The alkaline ammonium borate was directly titrated with 0.1N HCl (Merck, USA). The volume of acid used was recorded as the titer value. The amount of acid used was factored into the formula, yielding %N.\n\nConstant: Nitrogen molecular weight 14,008 g/mol; Conversion factor: 6,25\n\nCrude lipid was determined using the Soxhlet extraction technique (Association of Official Analytical Chemists, 2005).31 First, the lipid content of the sample (2 g) was extracted using 100 mL of petroleum ether. Then, the mixture was filtered, and its lipid content was collected in a pre-weighed (W1) clean beaker. After that, exhaustive lipid extraction was done on the same sample with 100 mL of n-hexane (Fulltime, China) for 24 h. It was then filtered and decanted into a beaker (W1). Next, the lipid content was concentrated to dryness in a steam bath and oven-dried at 40–60 °C, and the beaker was reweighed (W2). Finally, the percentage of lipid was calculated.\n\nWhere:\n\nW1=Weight of sample (g)\n\nW2=Weight of fat flask without fat (g)\n\nW3=Weight of fat flask with fat (g)\n\nThe carbohydrate content was calculated by subtracting the total crude protein, ash, and crude fat from the total dry matter.32\n\nThe total flavonoid content was determined.33 Encapsulated MCV was weighed at 1 mg and then dissolved in 10 mL of 95% ethanol (SmartLab, Indonesia). A total of 0.7 mL of distilled water was added to the encapsulation and dissolved in ethanol. Then, about 0.1 mL of 5% NaNO2 (Sigma-Aldrich, USA) was added to the mixture. After five minutes, 0.1 mL of 10% AlCl3 (Sigma-Aldrich, USA) was added. After six minutes, 0.5 mL of 1 M NaOH (Merck, USA) was added. All ingredients were mixed with a vortex evenly, then incubated for 10 minutes. The absorbance value was detected at a wavelength of 510 nm (Biospectrometer, Eppendorf, Germany). The results obtained were plotted against the catechin (Sigma-Aldrich, USA) standard curve prepared similarly. Total flavonoid was expressed as milligrams of catechin equivalent per kilogram dry weight extract.\n\nMeasurement of total phenol was conducted.34,35 About 0.3 g encapsulated MCV was carefully dissolved in 10 mL of ethanol and distilled water (1:1 ratio). About 0.2 mL of the extract solution was pipetted and added with 15.8 mL of distilled water and 1 mL of Folin-Ciocalteu 50% (v/v) reagent (Merck, USA). The solution was allowed to stand for eight minutes, and then 3 mL of 5% (w/v) Na2CO3 (Sigma-Aldrich, USA) was added. Then the solution was allowed to stand for two hours in the dark at room temperature (28±3°C). The absorbance value was detected at a wavelength of 725 nm (BioSpectrometer, Eppendorf, Germany). The absorbance value was plotted against a gallic acid (Sigma-Aldrich, USA) standard curve prepared similarly. Total phenol was expressed in milligrams of gallic acid equivalent per kilogram dry weight extract.\n\nThe total tannin was calculated.36 A total of 0.5 g of encapsulated MCV was macerated in 10 mL of diethyl ether (Merck, USA) for 20 hours, then filtered, and the residue obtained was boiled with 100 mL of distilled water for two hours, then allowed to cool. About 0.1 mL of the cold sample was added with 0.1 mL of Folin-Ciocalteu reagent (Merck, USA) and vortexed, added with 2 mL of 2% Na2CO3 (Sigma-Aldrich, USA), and vortexed again. The absorbance value was detected at a wavelength of 760 nm (BioSpectrometer, Eppendorf, Germany) after being incubated for 30 minutes at room temperature (28±2°C). The results obtained were plotted against a tannic acid (Sigma-Aldrich, USA) standard curve prepared similarly. Thus, the total tannin content was expressed in milligrams tannic acid per kilogram extract.\n\nThe experimental design used in this study was a factorial, completely randomized design with nine treatments and two replications. This study consisted of two factors, namely maltodextrin equivalent to TSS (15, 20, 25 °Brix) and chitosan (1, 2, 3% w/w maltodextrin), as shown in Table 1.\n\nThe data obtained from the chemical and phytochemical tests were analyzed using variance analysis at a 5% significance level using a GraphPad Prism (v9.2), but can also be analyzed using any open-source statistical software, including the freely available R. If the variance test shows a significant treatment effect, the variance analysis was continued with the Tukey test.\n\n\nResult and discussion\n\nMoisture content is an important parameter determining dry products’ quality, such as dry encapsulation. The lower moisture content makes the product protected from bacterial and fungal spoilage.37 The moisture content of the MCV encapsulated product in this study ranged from 5.31 ± 1.00% to 10.45 ± 0.85% (see Table 2 and Underlying data67). The TSS treatment and the interaction between the two factors had a significant effect (p<0.05) on the moisture content of the encapsulated MCV product. In contrast, the chitosan treatment showed no significant effect (p>0.05). However, TSS treatments showed a significantly different effect on moisture content. The 15 °Brix treatment group generally produced more moisture content than the 20 °Brix treatment group. The higher the TSS used in the encapsulation process, the lower the percentage of moisture content (Table 2).\n\nAccording to Marte et al.,38 the higher the total solids dried to a certain extent, the higher the evaporation rate, causing lesser moisture content. Hayati et al.39 stated that maltodextrin used in quantities could reduce the moisture content of the encapsulated results.\n\nAt TSS 25 °Brix, the encapsulated MCV experienced an increase in moisture content. Different total solids influence the increase in moisture content. The high total solids are related to the drying rate during spray drying.40 However, a high concentration of maltodextrin causes coagulation.41 As a result, the water molecules that will diffuse are blocked by larger maltodextrin molecules and cause a decrease in the drying rate, thus causing the moisture content to increase.41\n\nChitosan has no significant effect on the moisture content of the encapsulated MCV product. However, chitosan has a humidifying effect, retaining moisture during the spray drying. Moreover, chitosan can slow down the crystallization process during spray drying.42\n\nThe ash content of the MCV encapsulated product in this study ranged from 0.25±0.35% to 1.25±0.35% (see Table 2 and Underlying data67). The treatment and interaction of TSS and chitosan had no significant effect on the ash content of the encapsulated MCV product. The highest ash content value was obtained in the TSS 20 °Brix treatment with 1% chitosan, and the lowest ash content was found in the TSS 25 °Brix treatment with 2% chitosan.\n\nAsh content is usually pointing to the total minerals in a material. The ash content of the MCV encapsulated product showed no significant difference. The non-significance values happened because the raw material in MCV was used in the same concentration. Siregar et al.43 concluded ash content of the mandai cempedak product per 100 g of dry matter was 4.3%. The low ash content obtained is because MCV is a derivative product of the mandai. Caez and Jaraba44 reported 0.43% ash content in mango juice microencapsulated with maltodextrin compared to other encapsulated products. Minerals are not significantly affected by chemical and physical treatments during processing.45 For example, specific mineral ions can be oxidized in the presence of oxygen, but their final concentrations were not significantly affected.46\n\nThe crude protein content in this study ranged from 0.42±0.02% to 0.70±0.05% (see Table 2 and Underlying data67). The treatment of TSS and chitosan and the interaction between the two factors significantly affected the protein content of the Encapsulated MCV. The TSS and chitosan treatments have significantly different effects. The highest protein content was obtained from the TSS 20 °Brix treatment with 2% chitosan, and the lowest protein content was obtained from the TSS 15 °Brix treatment with 1% chitosan. The TSS treatment of 15 and 20 °Brix showed no significant difference, but protein levels decreased in TSS 25 °Brix. The value explains that the higher the total solids used in the Encapsulated MCV, the lower the protein content of the powder produced.\n\nProteins consist of long chains of amino acids bound to each other by peptide bonds. Amino acids consist of carbon, oxygen, hydrogen, and nitrogen.47 The decrease in protein content in the processing of MCV encapsulated products is also due to the spray drying method used, which causes the particles to come into direct contact with high temperatures, which allows the denaturation process to occur. For example, Anandharamakrishnan et al.48 reported that protein denaturation by the spray drying method could occur even at an outlet temperature of 60°C.\n\nThe higher the chitosan concentration in the processing of the encapsulated MCV, the higher the protein content of the powder produced. Commercial chitosan contains 0.48% protein, so there may be an increase in protein due to the higher amount of chitosan added.49 Conversely, a concentration of 3% chitosan showed a decrease in protein levels. This was because chitosan concentration was too high, making chitosan insoluble. This situation causes a crack in the encapsulation wall so that the compound can diffuse out through the gap formed.50\n\nFats are compounds formed from the esterification reaction between fatty acids and glycerol. The use of high temperatures in fats will cause the double bonds in the fat to break, breaking the fat into glycerol and fatty acids.51 The crude fat content value of the encapsulated MCV in this study ranged from 0.35% to 0.85% (see Table 2 and Underlying data67). The treatment of TSS and chitosan and the interaction between the two factors significantly affected the fat content of the encapsulated MCV. The highest fat content was obtained from the TSS 25 °Brix treatment with 3% chitosan, and the lowest fat content was obtained from the TSS 15 °Brix treatment with 1% chitosan. The fat content of the encapsulated MCV increased with the increasing amount of TSS and chitosan used.\n\nThe higher the maltodextrin and chitosan, the higher the fat content of the encapsulated MCV. Therefore, the rehydration of the sample may occur in a small amount. However, it affects the total weight of the fat tested. Maurer et al.52 stated that rehydration might affect the fat content measurement. Since the fat content of encapsulated MCV is less than 1%, the minute increase in fat concentration affects the statistical calculation.\n\nThe fat content in cempedak fruit is less than 2%, so the fat content produced in encapsulated MCV is also insignificant.53 On the other hand, the low-fat content provides advantages for the drying process and extends the shelf life.54,55\n\nIn this study, the carbohydrate content of the encapsulated MCV was determined by the by-difference method. Major nutrients that affect carbohydrate levels include protein, fat, moisture, and ash content.56 In this study, the carbohydrate content values ranged from 87.59±0.23% to 90.94±0.16% (see Underlying data67). The maltodextrin equivalent to TSS and chitosan treatments and their interactions had no significant effect on the carbohydrate content of the encapsulated MCV.\n\nThe carbohydrate content of cempedak fruit is 84-87%, so the carbohydrate content dominates the encapsulated MCV.53 This is also possible because of maltodextrin and chitosan’s combined carbohydrate content. Maltodextrin is a saccharide polymer generally obtained from the hydrolysis of corn starch with acids or enzymes.55 Chitosan is a non-toxic amino polysaccharide obtained from chitin through a complete deacetylation process.18 In this study, the carbohydrate content of the MCV encapsulated product was not significantly different, only slightly influenced by the increase in wall material concentration. In another report, the carbohydrate content in the encapsulated gac fruit did not change with the addition of auxiliary material.57\n\nBefore the spray drying, the total flavonoid content in MCV was 11.4 mg Catechin Equivalent (CE) kg-1. The flavonoid content of encapsulated MCV varies with maltodextrin and chitosan. The total flavonoid value of the MCV encapsulated product ranged from 6.99±1.08 mg CE (Catechin Equivalent) kg-1 to 9.13±0.89 mg CE kg-1 (see Table 3 and Underlying data67). The highest flavonoid content was found in encapsulated product with 15 °Brix TSS and 1% chitosan, the encapsulation with the lowest concentration of wall material. The encapsulation concentration influenced the flavonoid content in purple sweet potato in another research.58 The binding of flavonoid by the encapsulated matrix caused the product with a higher encapsulated concentration to bind more flavonoid.58 As a result, an increase in the concentration of the encapsulant causes a decrease in flavonoid levels.\n\nThe treatment of TSS and chitosan and their interactions had no significant effect on the total flavonoid of the Encapsulated MCV. The increase in maltodextrin and chitosan showed no significant difference in the total value of encapsulated flavonoid. The use of maltodextrin and chitosan can protect flavonoid compounds well because they have properties that can prevent oxidation.41,59\n\nThe initial total phenol content in MCV was 103.31 mg GAE (Gallic Acid Equivalent) kg-1. The total phenol value of the MCV encapsulated product in this study ranged from 56.93±0.52 mg GAE kg-1 to 83.13±0.92 mg GAE kg-1 (see Table 3 and Underlying data67). The treatment of maltodextrin and chitosan and their interactions had a significant effect on the total value of the encapsulated product of MCV. Each treatment of TSS and chitosan and their interactions gave significantly different effects. The highest total phenol was obtained from 15 °Brix TSS treatment with 3% chitosan, and the lowest total phenol was obtained from 20 °Brix TSS treatment with 2% chitosan.\n\nThe highest total phenol was obtained from the 15 °Brix TSS treatment, and the lowest was accepted from the 20 °Brix TSS treatment. The higher the total solids, the total encapsulated phenol tends to decrease. Safithri et al.60 stated that the more total solids used in functional drinks based on red betel leaf extract (Piper crocatum) in maltodextrin as coating material, the lower the total coated phenol. In addition, encapsulation materials such as maltodextrin and chitosan coat bioactive compounds in the form of phenol compounds.61 When tested with phenol reagents, not all bioactive components can react, resulting in under-valued measurement.62 The oxidation process causes this total degradation of phenol due to heat treatment during spray drying activities.63 This can be related to changes in the molecular structure that cause a decrease in reactivity. In addition, the possibility of a reduction of total phenol levels is due to the formation of phenol-protein complexes or decomposition of phenol compounds and changes in chemical structure due to pressure and temperature.63\n\nThe highest total phenol was obtained from 3% chitosan treatment, and the lowest was accepted from 1% chitosan treatment. The use of higher concentrations of chitosan can encapsulate more phenolic compounds. The trend is also following the research of Kistriyani et al.,59 which states that the higher the chitosan content, the higher the binding ability to protect phenolic compounds. Belscak-Cvitanovic et al.64 showed that chitosan as an encapsulant was very effective in safeguarding bioactive compounds, slowing their release profile, and increasing encapsulation efficiency. Encapsulation efficiency is calculated based on the number of polyphenols encapsulated. Encapsulation efficiency is related to the particles’ morphological characteristics and heat resistance. Therefore, chitosan can protect the encapsulated active compounds.\n\nThe total tannin content in MCV was 33.63 mg TAE (Tannic Acid Equivalent) kg-1. The total tannin value of the MCV encapsulated product in this study ranged from 13.12±0.89 mg TAE kg-1 to 26.67±0.64 mg TAE kg-1 (see Table 3 and Underlying data67). The highest total tannin was found in 15 °Brix TSS treatment with 2% chitosan. The treatment of maltodextrin and chitosan and their interactions significantly affected the total tannin of the encapsulated MCV.\n\nThe highest total tannin was found in the 15 °Brix TSS treatment, and the lowest was obtained from the 20 °Brix TSS treatment. The increase in TSS at various concentrations of maltodextrin and chitosan causes the total tannin content to be lower. The increasing TSS affects the movement of volatile components to the dried droplet surface.50 According to Rosenberg et al.,65 the concentration of total solids affects the viscosity and decreases the volatile components.\n\nThe more the addition of chitosan to various TSSs, the higher the total encapsulated tannin. Therefore, the ability of chitosan to protect the tannin compounds in the product to be dried by the spray drying process is more significant. Chitosan protects essential compounds contained in materials such as bioactive components, including tannin, because chitosan has a solid binding capacity to coated bioactive components.66 The concentration of 3% chitosan showed a decrease, and this happened because chitosan was given in large quantities so that the chitosan became insoluble. Ali et al.50 stated that increasing the higher chitosan concentration could cause chitosan to become insoluble. This condition results in cracks in the crust so that the bioactive components diffuse out through the gaps formed.\n\n\nConclusions\n\nMaltodextrin and chitosan treatment significantly affected moisture, protein, and fat contents. Chitosan has a humidifying effect and can slow down the crystallization process during spray drying. In addition, a high concentration of maltodextrin causes coagulation; water molecules that will diffuse are blocked by larger maltodextrin molecules and cause a decrease in the drying rate, thus causing the moisture content to increase. The decreased protein content is due to the spray drying method used. However, the higher the chitosan concentration, the higher the protein content of the powder produced because commercial chitosan contains 0.48% protein, the more chitosan used, the higher the protein content. On the other hand, the higher the maltodextrin and chitosan, the higher the fat content, and the rehydration of the sample may occur in a small amount. Total flavonoid, phenol, and total tannin were related to maltodextrin equivalent to TSS and chitosan treatment. The best phytochemical concentrations of encapsulated MCV were produced from 15 °Brix TSS with 1% chitosan. Encapsulated MCV product with this treatment has 7.54% moisture, 0.75% ash, 0.42% protein, 0.35% fat, 90.94% carbohydrate contents, giving bioactive capacities equivalent to 9.13 mg CE kg-1, 69.61 mg GAE kg-1, and 25.04 mg TAE kg-1.\n\n\nData availability\n\nOpen Science Framework: MCV encapsulation treatment. https://doi.org/10.17605/OSF.IO/3AQSW.67\n\nThis project contains the following underlying data:\n\n▪ MCV encapsulation treatment.csv (sample code/key and treatment).\n\n▪ Ash content.csv (replication and average ash on MCV encapsulation).\n\n▪ Ash_data for graphs with GraphPad.csv (ash percentage data on MCV encapsulation for graphing with GraphPad Prism).\n\n▪ Ash_Ordinary one-way ANOVA Results with GraphPad.csv (results of data analysis with ANOVA using GraphPad Prism).\n\n▪ Ash_Multiple comparisons with GraphPad.csv (data analysis with Tukey’s multiple comparisons test using Graphpad Prism).\n\n▪ Carbohydrate Content.csv (replication and average carbohydrate on MCV encapsulation).\n\n▪ Carbohydrate _data for graphs with GraphPad.csv (carbohydrate percentage data on MCV encapsulation for graphing with GraphPad Prism).\n\n▪ Carbohydrate _Ordinary one-way ANOVA Results with GraphPad.csv (results of data analysis with ANOVA using GraphPad Prism).\n\n▪ Carbohydrate _Multiple comparisons with GraphPad.csv (data analysis with Tukey’s multiple comparisons test using Graphpad Prism).\n\n▪ Fat content.csv (replication and average fat on MCV encapsulation).\n\n▪ Fat_data for graphs with GraphPad.csv (fat percentage data on MCV encapsulation for graphing with GraphPad Prism).\n\n▪ Fat_Ordinary one-way ANOVA Results with GraphPad.csv (results of data analysis with ANOVA using GraphPad Prism).\n\n▪ Fat_Multiple comparisons with GraphPad.csv (data analysis with Tukey’s multiple comparisons test using Graphpad Prism).\n\n▪ Flavonoid content.csv (replication and average flavonoid on MCV encapsulation).\n\n▪ Flavonoid_data for graphs with GraphPad.csv (flavonoid percentage data on MCV encapsulation for graphing with GraphPad Prism).\n\n▪ Flavonoid_Ordinary one-way ANOVA Results with GraphPad.csv (results of data analysis with ANOVA using GraphPad Prism).\n\n▪ Flavonoid_Multiple comparisons with GraphPad.csv (data analysis with Tukey’s multiple comparisons test using Graphpad Prism).\n\n▪ Moisture Content.csv (replication and average moisture on MCV encapsulation).\n\n▪ Moisture_data for graphs with GraphPad.csv (moisture percentage data on MCV encapsulation for graphing with GraphPad Prism).\n\n▪ Moisture_Ordinary one-way ANOVA Results with GraphPad.csv (results of data analysis with ANOVA using GraphPad Prism).\n\n▪ Moisture_Multiple comparisons with GraphPad.csv (data analysis with Tukey’s multiple comparisons test using Graphpad Prism).\n\n▪ Phenols content.csv (replication and average phenols on MCV encapsulation).\n\n▪ Phenols_data for graphs with GraphPad.csv (phenols percentage data on MCV encapsulation for graphing with GraphPad Prism).\n\n▪ Phenols_Ordinary one-way ANOVA Results with GraphPad.csv (results of data analysis with ANOVA using GraphPad Prism).\n\n▪ Phenols_Multiple comparisons with GraphPad.csv (data analysis with Tukey’s multiple comparisons test using Graphpad Prism).\n\n▪ Protein content.csv (replication and average protein on MCV encapsulation).\n\n▪ Protein_data for graphs with GraphPad.csv (protein percentage data on MCV encapsulation for graphing with GraphPad Prism).\n\n▪ Protein_Ordinary one-way ANOVA Results with GraphPad.csv (results of data analysis with ANOVA using GraphPad Prism).\n\n▪ Protein_Multiple comparisons with GraphPad.csv (data analysis with Tukey’s multiple comparisons test using Graphpad Prism).\n\n▪ Tannin content.csv (replication and average tannin on MCV encapsulation).\n\n▪ Tannin_data for graphs with GraphPad.csv (tannin percentage data on MCV encapsulation for graphing with GraphPad Prism).\n\n▪ Tannin_Ordinary one-way ANOVA Results with GraphPad.csv (results of data analysis with ANOVA using GraphPad Prism).\n\n▪ Tannin_Multiple comparisons with GraphPad.csv (data analysis with Tukey’s multiple comparisons test using Graphpad Prism).\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "References\n\nRahmadi A, Sari K, Khairiyah N, et al.: Bacterial Population and Chemical Characteristics of Fermented Mandai cempedak with Starter Induction. Microbiol. Indonesia. 2018; 12(3): 83–91. Publisher Full Text\n\nRahmadi A, Sari K, Sitohang S, et al.: Profil perubahan populasi BAL, pH, kadar flavonoid, dan Potensi aktivitas antioksidan dari fermentasi mandai cempedak higienis tanpa garam. Semin. Nas. PATPI. 2017, October.\n\nRahmadi A, Sari K, Handayani F, et al.: Modulation Of Phenolics Substances and Antioxidant Activity In Mandai cempedak By Unsalted Spontaneous and Lactobacillus casei Induced Fermentation. J. Teknol. dan Ind. Pangan. 2019; 30(1): 75–82. Publisher Full Text\n\nMariana RA, Syahrumsyah H: Pengaruh Pemberian Cuka Mandai Terhadap Kadar Kolesterol Total, Lipoprotein dan Trigliserida Pada Mencit (Mus musculus) Dengan Induksi Kuning Telur. J. Trop. AgriFood. 2020; 2(1): 45–52. Publisher Full Text\n\nHasibuan R: Efektifitas Pemberian Soyghurt Terhadap Penurunan Kadar Kolesterol Dalam Darah Mencit (Mus musculus) Dengan Jum;ah Bakteri Asam Laktat Dan Suhu Inkubasi Yang Optimum. J. Ilm. PANNMED (Pharmacist, Anal. Nurse, Nutr. Midwivery, Environ. Dent.). 2019; 9(2): 138–145. Publisher Full Text\n\nSutjiatmo AB, Sukandar EY, Sinaga R, et al.: Efek Antiokolesterol Ekstrak Etanol Daun Creme (Phyllanthus acidus (L.) Skeels) Pada Tikus Wistar Betina. Kartika J. Ilm. Farm. 2013; 1(1): 1–7.\n\nKhairullah Mohammed N, Tan C, Abd Manap Y, et al.: Process conditions of spray drying microencapsulation of Nigella sativa oil. Powder Technol. 2017; 315: 1–14. Publisher Full Text\n\nDeng M, Deng YY, Dong L, et al.: Effect of Storage Conditions on Phenolic Profiles and Antioxidant Activity of Litchi Pericarp. Molecules. 2018; 23: 2276. PubMed Abstract \| Publisher Full Text\n\nVladisavljević GT, Holdich RG: Encapsulation. Encycl. Member. 2016. Publisher Full Text\n\nSiregar TM, Kristanti C: Mikroenkapsulasi Senyawa Fenolik Ekstrak Daun Kenikir (Cosmos caudatus K.). J. Apl. Teknol. Pangan. 2019; 8(1): 31–37.\n\nPantastico EB:Fisiologi Pasca Panen. Universitas Gadjah Mada, Yogyakarta. Yogyakarta:Universitas Gadjah Mada;1986.\n\nKhuenpet K, Charoenjarasrerk N, Jaijit S, et al.: Investigation of suitable spray drying conditions for sugarcane juice powder production with an energy consumption study. Agric. Nat. Resour. 2016; 50(2): 139–145. Publisher Full Text\n\nMaherawati M, Hartanti L: The Properties of Aloe Vera Powder using Cassava Maltodextrin as Carrier Agents. J. Ind. Has. Perkeb. 2019; 14(2): 44. Publisher Full Text\n\nKane SN, Mishra A, Dutta AK: Preface: International Conference on Recent Trends in Physics (ICRTP 2016). J. Phys. Conf. Ser. 2016; 755(1): 011001. Publisher Full Text\n\nKha TC, Nguyen MH, Roach PD: Effects of spray drying conditions on the physicochemical and antioxidant properties of the Gac (Momordica cochinchinensis) fruit aril powder. J. Food Eng. 2010; 98(3): 385–392. Publisher Full Text\n\nKurniasih RA, Darmadji P, Pranoto Y: Pemanfaatan Asap Cair terenkapsulasi Maltodekstrin-Kitosan Sebagai Pengawet Ikan Cakalang (Katsuwonus pelamis). J. Teknol. Has. Pertan. 2016; 9(1): 9–16. Publisher Full Text\n\nRaza ZA, Khalil S, Ayub A, et al.: Recent developments in chitosan encapsulation of various active ingredients for multifunctional applications. Carbohydr. Res. 2020; 492(December): 108004. PubMed Abstract \| Publisher Full Text\n\nEstevinho BN, Rocha F, Santos L, et al.: Microencapsulation with chitosan by spray drying for industry applications - A review. Trends Food Sci. Technol. 2012; 31(2): 138–155.\n\nBakry AM, Abbas S, Ali B, et al.: Microencapsulation of Oils: A Comprehensive Review of Benefits, Techniques, and Applications. Compr. Rev. Food Sci. Food Saf. 2016; 15(1): 143–182. PubMed Abstract \| Publisher Full Text\n\nRibeiro AJ, Neufeld RJ, Arnaud P, et al.: Microencapsulation of Lipophilic Drugs in Chitosan-Coated Alginate Microspheres. Int. J. Pharm. 1999; 187(1): 115–123. PubMed Abstract \| Publisher Full Text\n\nShi X, Tan T: Preparation of Complex Chitosan Microcapsule and Its Application In Controlled Release of Vitamin D2. Biomaterials. 2002; 23(1): 4469–4473. PubMed Abstract \| Publisher Full Text\n\nAnal AK, Stevens WF, Remuñán-López C: Ionotropic Cross-Linked Chitosan Microspheres For Controlled Release of Ampicillin. Int. J. Pharm. 2006; 312(1–2): 166–173. PubMed Abstract \| Publisher Full Text\n\nKosaraju SL, D’ath L, Lawrence A: Preparation and Characterisation of Chitosan Microspheres For Antioxidant Delivery. Carbohydr. Polym. 2006; 64(2): 163–167. Publisher Full Text\n\nGong Z, Zhang M, Mujumdar A, et al.: Spray drying and agglomeration of instant bayberry powder. Dry. Technol. 2008; 26(1): 116–121.\n\nReineccius GA: The spray drying of food flavors. Dry. Technol. 2004; 22(6): 1289–1324. Publisher Full Text\n\nJafari SM, Assadpoor E, He Y, et al.: Encapsulation Efficiency of Food Flavours and Oils During Spray Drying. Dry. Technol. 2008; 26(7): 816–835. Publisher Full Text\n\nLindani A: Perbandingan Pengukuran Kadar Air Metode Moisture Analyzer Dengan Metode Oven Pada Produk Biskuit Sandwich Cookies Di PT. Mondelez Indonesia Manufacturing. Skripsi:IPB University;2016.\n\nAndarwulan N, Kusnandar F, Herawati D: Analisis Pangan. Jakarta:Dian Rakyat;2011.\n\nJiang B, Tsao R, Li Y, Miao M: Food Safety: Food Analysis Technologies/Techniques.Van Alfen NK , editor. Encyclopedia of Agriculture and Food Systems. Oxford:Academic Press;2014; 273–288. Publisher Full Text\n\nSudarmadji S, Haryono B, et al.: Analisa Bahan Makanan dan Pertanian. Yogyakarta:Liberty;2010.\n\n[AOAC] Association of Official Analytical Chemists: Official Methods of Analysis of AOAC International. 18th ed.Gaithersburg:AOAC International;2005.\n\nWinarno FG: Kimia Pangan dan Gizi. Jakarta:Gramedia Pustaka Utama;1986.\n\nZou Y, Lu Y, We D: Antioxidant activity of a flavonoid-rich extract of Hypericum perforatum L. in vitro. J. Agric. Food Chem. 2004; 52(16): 5032–5039. PubMed Abstract \| Publisher Full Text\n\nMu’nisa A, Wresdiyati T, Kusumorini N., et al.: Aktivitas Antioksidan Ekstrak Daun Cengkeh. J. Vet. 2013; 13(3): 272–277.\n\nNurhayati KS, Harjono: Pengaruh Konsentrasi Natrium Benzoat dan Lama Penyimpanan Pada Kadar Fenolat Total Pasta Tomat. Indones. J. Chem. Sci. 2012; 1(2).\n\nMalangngi L, Sangi M, Paendong J: Penentuan Kandungan Tanin dan Uji Aktivitas Antioksidan Ekstrak Biji Buah Alpukat (Persea americana Mill.). J. MIPA. 2012; 1(1): 5.\n\nPurnomo W, Khasanah LU, Anandito BK: Pengaruh Ratio Kombinasi Maltodekstrin, Karagenan dan Whey Terhadap Karakteristik Mikroenkapsulan Pewarna Alami Daun Jati (Tectona Grandis L. F.). J. Apl. Teknol. Pangan. 2014; 3(3): 121–129.\n\nAlcantara Marte Y, Alcantara Marte Y, Tejada AE, et al.: Effect of different concentrations of pulverized mesocarp of Citrus paradisi Macf. on the bromatological characteristics of spray-dried lemon juice powder. Food Sci. Nutr. 2018; 6(5): 1261–1268. PubMed Abstract \| Publisher Full Text\n\nHayati FG, Dewi AK, Nugrahani RA, et al.: Pengaruh Konsentrasi Maltodekstrin Terhadap Kadar Air Dan Waktu Melarutnya Santan Kelapa Bubuk (Coconut Milk Powder) Dalam Air. J. Teknol. 2015; 7(1): 55–60.\n\nDjaafar TF, Santoso U, Ariestyanta A: Pengaruh Penambahan Maltodekstrin dan Suhu Inlet Spray Dryer terhadap Karakteristik Fisiko-Kimia Bubuk Sari Kerandang (Canavalia virosa). Agritech. 2018; 37(3): 334. Publisher Full Text\n\nSantoso BD, Ananingsih VK, Soedarini B, et al.: Pengaruh Variasi Maltodekstrin dan Kecepatan Homogenisasi Terhadap Karakteristik Fisikokimia Enkapsulat Butter Pala (Myristica fragrans Houtt) Dengan Metode Vacuum Drying. J. Teknol. Has. Pertan. 2020; 13(2): 94. Publisher Full Text\n\nEdrisi Sormoli M: Imtiaz Ul Islam M, and Langrish TAG: The effect of chitosan hydrogen bonding on lactose crystallinity during spray drying. J. Food Eng. 2012; 108(4): 541–548. Publisher Full Text\n\nSiregar MTP, Kusdiyantini E, Rukmi MI: Isolasi Dan Karakterisasi Bakteri Asam Laktat Pada Pangan Fermentasi Mandai. Biologi. 2014; 3(2): 40–48.\n\nFuentes KMC, Castro NJ: Microencapsulación del Jugo de Mango (Mangifera indica L.) para la Obtención de un Concentrado con la Utilización de Maltodextrina como Material Pared. Thesis.2012; 1–85.\n\nRamadhia M, Kumalaningsih S, Santoso I: The Making of Aloe vera Powder (Aloe vera L.) with Foam-mat Drying Method. J. Teknol. Pertan. 13(2): 125–137.\n\nLenaerts S, Van Der Borght M, Callens A, et al.: Suitability of microwave drying for mealworms (Tenebrio molitor) as an alternative to freeze-drying: Impact on nutritional quality and color. Food Chem. 2018; 254(January): 129–136. Publisher Full Text\n\nAlmatsier S: Prinsip Dasar Ilmu Gizi. PT Gramedia Pustaka Utama. Jakarta. Jakarta:Gramedia Pustaka Utama;2009.\n\nAnandharamakrishnan C, Rielly CD, Stapley AGF: Effects of process variables on the denaturation of whey proteins during spray drying. Dry. Technol. 2007; 25(5): 799–807. Publisher Full Text\n\nKaimudin M, Leonupun MF: Characterization Chitosan From Waste Leather with Shrimp Process Using Different Bleaching and Deacetylation. Maj. BIAM. 2016; 01(12): 1–7.\n\nAli DY, Darmadji P, Pranoto Y: Optimasi Nanoenkapsulasi Asap Cair Tempurung Kelapa Dengan Response Surface Methodology Dan Karakterisasi Nanokapsul. J. Teknol. dan Ind. Pangan. 2014; 25(1): 23–30.\n\nMamuaja CG: Lipida. Unsrat Press;2017; 1–119.\n\nMaurer AJ, Baker RC, Vadehra DV: Factors Affecting the Drying, Stability, and Rehydration of Freeze-Dried Chicken Meat. Poult. Sci. 1973; 52(2): 784–792. Publisher Full Text\n\nGopinathan M, Yusof YA, Pui LP: Effects of Different Drying Methods on the Physicochemical and Antioxidant Content of “Cempedak” (Artocarpus Integer L.) Powder. J. Food Process. Preserv. 2020; 44. Publisher Full Text\n\nHermanto S, Muawanah A, Wardhani P: Analisis Tingkat Kerusakan Lemak Nabati dan Lemak Hewani Akibat Proses Pemanasan. J. Kim. Val. 2012; 1(6): 262–268.\n\nSamantha SC, Bruna ASM, Adriana RM, et al.: Drying by spray drying in the food industry: Micro-encapsulation, process parameters and main carriers used. Afr. J. Food Sci. 2015; 9(9): 462–470. Publisher Full Text\n\nwa ode Irmayanti H, Asyik N: Analisis Organoleptik dan Proksimat Biskuit Berbahan Dasar Ubi Jalar (Ipomea batatas L) dan Kacang Hijau (Phaseolus radiatus L). J. Sains Dan Teknol. Pangan. 2017; 2(2): 413–424.\n\nAngkananon W, Anantawat V: Effects of Spray Drying Conditions on Characteristics, Nutritional Value and Antioxidant Activity of Gac Fruit Aril Powder. Rev. Integr. Bus. Econ. 2015; 4: 1–11.\n\nAhmed M, Akter MS, Lee JC, et al.: Encapsulation by spray drying of bioactive components, physicochemical and morphological properties from purple sweet potato. LWT - Food Sci. Technol. 2010; 43(9): 1307–1312. Publisher Full Text\n\nKistriyani L, Fauziyyah F, Rezeki S: Profil Release Enkapsulasi Antosianin, Flavonoid dan Fenolik pada Kulit Semangka Menggunakan Metode Spray Drying. Eksergi. 2020; 17(2): 33. Publisher Full Text\n\nSafithri M, Indariani I, Yuliani R: Effect of Microencapsulation Techniques on Physical and Chemical Characteristics of Functional Beverage Based on Red Betel Leaf Extract (Piper crocatum). J. Kim. Sains dan Apl. 2020; 23(8): 276–282. Publisher Full Text\n\nAfandi FA: Pengaruh Nanoenkapsulasi terhadap Mutu Sensori, Fisikokimia, dan Fisiologiaktif Minuman Fungsional Berbasis Kumis Kucing (Orthosiphon aristatus BI. Miq), master thesis, Fakultas Teknologi Pertanian, Institut Pertanian Bogor, Bogor.2014.\n\nNallamuthu I, Devi A, Khanum F: Chlorogenic acid-loaded chitosan nanoparticles with sustained release property, retained antioxidant activity and enhanced bioavailability. Asian J. Pharm. Sci. 2015; 10(3): 203–211. Publisher Full Text\n\nYuliawaty ST, Susanto WH: Pengaruh Lama Pengeringan dan Konsentrasi Maltodekstrin Terhadap Karakteristik Fisik Kimia dan Organoleptik Minuman Instan Daun Mengkudu (Morinda citrifolia L). J. Pangan dan Agroindustri. 2015; 3(1): 41–51.\n\nBelšćak-Cvitanović A, Stojanovic R, Manojlovic, et al.: Encapsulation of polyphenolic antioxidants from medicinal plant extracts in alginate-chitosan system enhanced with ascorbic acid by electrostatic extrusion. Food Res. Int. 2011; 44(4): 1094–1101. Publisher Full Text\n\nRosenberg M, Kopelman IJ, Talmon Y: Factors Affecting Retention in Spray-Drying Microencapsulation of Volatile Materials. J. Agric. Food Chem. 1990; 38(5): 1288–1294. Publisher Full Text\n\nSaloko S, Sulastri Y, Kadir A: Enkapsulasi Gula Semut Aren Menggunakan Kitosan dan Maltodekstrin. Pro Food (Jurnal Ilmu dan Teknol. Pangan). 2021; 7(1).\n\nRahmadi A, Banin MM, Rohmah M: MCV encapsulation treatment. Data. 2022, April 15. Publisher Full Text" }	[ { "id": "171418", "date": "03 May 2023", "name": "Gülay Baysal", "expertise": [], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis manuscript is research on “Proximate analysis of the high phytochemical activity of encapsulated Mandai cempedak (Artocarpus champeden) vinegar prepared with maltodextrin and chitosan as wall materials”. I would like to say that the research is unacceptable without minor revision. Comments are as follows:\nThe authors should add the pre-treatments in the ash analysis to the first part of the experimental phase.\n\nPlease explain in detail all auxiliary chemicals used in the analysis by specifying their specific properties in the material section.\n\nNumber all of the formulas used in protein, fat and carbohydrate analysis and define references for each one separately.\n\nPlease discuss and interpret the following sentence in detail: “Minerals are not significantly affected by chemical and physical treatments during processing.45 For example, specific mineral ions can be oxidized in the presence of oxygen, but their final concentrations were not significantly affected...\"\n\nPlease specify the encapsulation efficiency ratio in the following sentence:\n“Encapsulation efficiency is calculated based on the number of polyphenols encapsulated.\"\n\nMinor grammatical errors in English need to be corrected.\n\nIn the introduction section, add a brief analysis of the research findings on chitosan and its encapsulation as a paragraph. The following 2 articles will help you: Baysal, Olcay & Günneç (2023)1 & Baysal et al., (2022)2.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "263519", "date": "20 May 2024", "name": "Faith Seke", "expertise": [ "Reviewer Expertise Food chemistry" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe introduction can be improved; the author should include more information to motivate why they chose to use maltodextrin and chitosan, as well as the choice of encapsulation method. Maltodextrin has a high glycemic index, can you justify the final maltodextrin concentration you used in your experiment, and how sure are you that, that concentration will be suitable for all consumers, especially diabetic consumers. A key is needed under the tables, illustrating what is F1, F2, F3 etc There are no statistical denotations (a,b,c) on the Ash and carbohydrate (Table 2), and flavonoids (Table 3) columns; are you assuming that there is no significant difference between the treatments? Also, tell us what is happening with the statistics, normally, an illustrative statement should be provided under the tables. The conclusion can be improved, what are your recommendations based on the results of this study?\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-865
https://f1000research.com/articles/11-864/v1	29 Jul 22	{ "type": "Research Article", "title": "An exploration of trends and future directions in sustainability performance: A bibliometric analysis of Scopus database", "authors": [ "Kai Han Yang", "Ai Chin Thoo", "Ai Chin Thoo" ], "abstract": "Background: Current global economic activities are increasingly being perceived as unsustainable. With the Sustainable Development Goals (SDGs) statement in 2015, sustainability performance has received significant attention. Thus, it is necessary to better understand the topics of interest and expand cooperation networks to advance studies in integrated efforts. The present bibliometric research intends to assess worldwide research tendency in sustainability performance. Methods: We conducted an extensive bibliometric analysis of published academic articles on sustainability performance (SP) from 1997 to 2021. We reviewed, retrieved, and analysed 3680 papers published in Scopus. Specifically, VOSviewer software was used to conduct document co-authorship and co-occurrence analyses and burst detection analyses. Results: The outcomes reveal that since 1997, the sum of publications has been on the rise steadily. About a third of all global papers on sustainability performance were produced by researchers from the United States and Australia, outnumbering the remaining 138 countries/territories. Furthermore, the ten most prolific authors of sustainability performance are all from universities. Haapala, Karl R. and Murat Kucukvar were the most influential authors found, based on the total publication number of sustainability performance. Conclusions: The bibliometric analysis was conducted to identify the trends in the area of sustainability performance. Therefore, this study identified a significant research gap for future study of practitioners and researchers. The social sustainability and the relationship between the material flow analysis and sustainability performance should be noted. In addition, only the Scopus database has been considered due to its academic prestige. The database includes a large number of articles on sustainability performance. Therefore, the analysis was limited to the Scopus database only. However, other databases, such as Web of Science, Google Scholar, and MedLine, can be used for future research. These can also be used in combination.", "keywords": [ "Sustainability performance", "Scopus database", "bibliometric analysis", "co-citation analysis", "co-occurrence analysis" ], "content": "Introduction\n\nAccording to the World Meteorological Organization, the period 2015–2020 was the warmest on record, with global climate change increasing by 0.2 percent compared to 2011–20151,2. The 20% increase in global carbon emissions was among the factors contributing to this change, which was also higher than 410 parts per million (ppm) at the end of 20202. However, the concentration of the major greenhouse gases showed a continuous increase in 2020. A similar trend showed through carbon dioxide (CO2) concentration as in previous years could amount to 414 ppm or higher in 20212. In 2018, across the world, an overall US$166 billion economy loss and 55.3 Giga tera (Gt) of carbon dioxide (CO2) equivalent emissions were attributed to 831 critical phenomena associated with climate3. Sustainable development has become a universal concern across countries following the increasing socio-environmental issues, including climate change, pollution, and multiple health issues due to pollution4.\n\nIn 2015, all United Nations (U.N.) member states implemented Sustainable Development Goals (S.D.G.s) to eradicate poverty, provide protection to the earth, and achieve prosperity by 20305. In the period of sustainable development, all organisations are recommended to enhance perceptiveness in achieving sustainable development objectives associated with social well-being, economic prosperity, and environmental preservation6. Notably, sustainability performance helps organisations obtain a competitive advantage in the market that is progressing towards a greener economy, achieve significant financial gains, and attract customers to assure long-term profitability7,8.\n\nTherefore, sustainability performance has been under close attention by researchers, scholars, and practitioners. Furthermore, a considerable number of papers and special journal issues are available, covering a wide range of themes related to sustainability performance9–11. However, very few studies concerning the bibliometric analysis of sustainability performance form global perspective using VOSviewer. VOSviewer is a tool to carry out bibliometric analysis, which is helpful to comprehend the research topic status12. Additionally, this study used Scopus as a source of data mining. Scopus is the biggest database of abstracts and citations, with 1.4 billion citations and 16 million researcher information13. The Web of Science (WoS) and Scopus databases are remarkably overlapped in terms of journal indexing14. As a result, employing Scopus aims to cover a broader range of topics.\n\nIn conclusion, this study aims to conduct a bibliometric analysis of sustainability performance from 1997 to 2021. It intends to identify the trend of publication of papers in the said area, identify the prolific contributors in sustainability performance, analyze co-authorship of different researchers and nations, and analyze the co-occurrence of author keywords. This study will help scholars, policymakers, and industry grasp the research tendency in sustainability performance and identify the orientations for their research.\n\n\nSustainability performance\n\nThe concept of sustainable development has aroused more and more academic interest over the past decade due to the increasing environmental crises, inclusive of climatic variations, contamination and substantial health crises derived from contamination4. The concept of sustainable development denotes the present generation’s capability of fulfilling necessities without jeopardizing the development of our offspring15,16. Such a concept has three pivotal elements (society, environment, and economy) when it comes to producing commodities4,17.\n\nThe leading research focus currently emphasizes sustainability performance. According to 18, sustainability performance benefits from economic, social, and environmental coordination. Eventually, it fulfils stakeholders’ necessities, enhances profit, competitiveness, and organizations’ resilience in the short and long term. Numerous research (e.g. 17,19–21) has identified sustainability performance dimensions, such as environmental, economic, and society-level performances, called triple bottom line (TBL). The TBL, including economic benefit, ecological environment, and social responsibility, do not exist independently as a link to associate them. For example 22 argued that organizations highlighting TBL could achieve better economy-wise performances in contrast to those highlighting 1 or 2 aspects23,24. Higher economic gains encourage organisations to adopt better social responsibility25. Organisations with robust economic strength can splurge additional money on treating pollution, offer advantages to the society and enhance the employees’ well-being26,27. Hence, sustainable development performance can be evaluated as per the economy, society, and environmental influences28.\n\nThe performance of sustainable development herein primarily denotes that corporations should manufacture on the foundation of the entire TBL. Furthermore, enterprises should minimize the expenditure, uplift consumers’ contentment, decrease discontentment, focus on developing green packaging, diminish unnecessary deliveries, and use environmentally friendly materials to minimize environmental impacts. Hence, sustainable development performance can be evaluated as per the economy, society, and environmental influences28.\n\n\nMethods\n\nIn this study, bibliometric analysis was used as a research method. Bibliometric analyses are a quantification method assisting in identifying and analysing data correlated with keywords, their associations, the number of papers published within a certain time limit and their citations29,30. 31 employed this strategy, and other studies have used a similar methodology, such as 32–34, with Gaur and Kumar providing an in-depth assessment (2018).\n\nFigure 1 depicts how to collect the articles for bibliometric analysis. The subsections that follow explain each of the stages shown in Figure 1.\n\nFirst, the research theme of sustainability performance was defined. Furthermore, this study aims to explore worldwide research tendency in sustainability performance to identify gaps and make research recommendations. Based on the research question and objectives, the article searching keywords were established. The full search strategy, retrieved by topic = “sustainability performance” or “triple bottom line” or “TBL”. The timespan is 1997–2021, and the retrieval time was 13 October 2021.\n\nThe present paper was based on the Scopus database core collection to guarantee the data’s scientific and completeness. Scopus is the largest database of abstracts and citations, with 1.4 billion citations and 16 million author data35. The Scopus database is superior to similar alternatives since it indexes approximately 70% more sources36. It gives more thorough coverage of the newest literature, according to 37.\n\nAfter the research searching keywords were chosen, the inclusion criteria (IC) were constructed. There were four criteria for inclusion:\n\nIC1: To include papers containing the research subject, which was “sustainability performance”, and the research premises/objective should match the paper’s objective.\n\nIC2: To include papers that eliminated letters, duplications, book reviews, editorials, conference proceedings and unpublished research.\n\nIC3: To include only papers within the analysis time (1997 – 2021).\n\nIC4: To include papers that limited the research fields (called “subject area” in databases) to environmental science, engineering, commercial activities, economy and society-wise research, and decision-making sciences.\n\nThe inclusion criteria contributed to the selection of articles, with only those that met all of them being chosen.\n\nPosterior to the initial search, we completed screening practically and methodologically to guarantee the correlation of literature, during which it needed to involve ⩾ 1 keyword aforementioned in the topics, abstracts, keywords. Our team completed the initial selection for approximately 5428 literature and afterwards discussed the outcomes to generate consensus. Subsequently, we reviewed the entire databases and checked associations via reading the abstracts when necessary. As a result, the 3687 articles were identified through Search Filters 1 (SF1), which read the title, abstract, and keywords. Only articles that demonstrated potential for achieving the four inclusion criteria cleared SF1 (IC1, IC2, IC3 and IC4). Afterwards, there were 3680 articles retrieved after full reading (SF2). The procedure of study inclusion and record exclusion was presented in Table 1. Please note that the full list of included studies is available in Underlying data.\n\nAfter data selection, there were a total of 3680 articles extracted for analysis. Furthermore, with the fast advancement of data mining, informational analyses and graphics rendering techniques, it’s probable to utilise computers to study substantial literature data and complete data expression via visualising data results38. This research will use this kind of bibliometric analysis tool, VOSviewer, to perform a quantitative analysis of the relevant literature39.\n\nVan Eck and Waltman of Leiden University in the Netherlands created VOSviewer, a program for constructing and visualizing econometrical networks. It’s capable of creating a corresponding knowledge map, identifying the research area’s knowledge base, and providing the most up-to-date progress in related research, as well as frontier hotspots, evolution paths, and future development trends in sustainability performance research, all of which are intended to serve as references and a foundation for future research38.\n\n\nResults and discussion\n\nAs presented by Figure 2, for the period of almost 24 years, 3680 papers were published, given the limitations in the search string. The results obtained from the preliminary analysis revealed that the oldest publication was dated 1997. The trends of the quantity of the literature witnessed relatively low before the year 2001. However, it increased gradually from then on, which showed there would be more documents to pour into the literature on sustainability performance. It may have been due to the increasing environmental crises, climatic variations, contamination and substantial health problems derived from contamination, and the fact that the concept of sustainable development had been widely accepted among the industries4. In addition, almost 400 publications were published in each of the last three years. It reflects that this trend will also grow by the rapidly increasing rate, which shows the importance of the topic of sustainability performance.\n\nTable 2 presents the ten most productive authors in sustainability performance from five nations: the United States (4 authors), Canada (3 authors), China (1 author), Norway (1 author), and Qatar (1 author). The first publications ranged between 2009–2015, where five authors were the first authors, three were co-authors, and two were the last authors. Although there isn’t any rule pertaining to author sequence, the first author is often related to the most contribution. Also, the affiliations of authors displayed that sustainability performance studies were mainly conducted in the university.\n\nNote = TP: Total Publication/ TC: Total Citation\n\nAs shown in Table 2, Haapala, Karl R. can be seen as the most prolific researcher in the field of sustainable performance, having produced the most papers, which is 25. Also, this study checked the hottest research topic of the ten most prolific authors in the last five years. The research of Haapala mainly focuses on sustainable manufacturing issues in recent years. Conversely, only Haapala focuses on sustainable manufacturing areas among the top ten prominent researchers. At the same time, material flow analysis is the most popular research topic among the top ten contributing authors, including Kucukvar, Tatari, Shen and Egilmez. The second most popular research topic is the green supply chain, which was investigated by three authors, involving Searcy, Svensson and Badurdeen. Authors Hewage and Sadiq, with the identical study field of life cycle assessment, co-authored a report entitled “Sustainability assessment of flooring systems in the city of Tehran: An AHP-based life cycle analysis”.\n\nThe literature review should be a valid approach to identify the conceptual content of the research area and guide further studies40, whereas identifying the most tightly associated and essential research is pivotal for the bibliography. The top 10 sustainability performance-associated journals are presented in Table 3. As shown in Table 3, the top 10 most prolific journals are owned by five publishers. Four of the top ten journals were published by Elsevier. The most prolific journal was the Journal of Cleaner Production, with 9658 papers covering 299% of the overall publications. The Journal of Cleaner Production has been cited in many papers, which can explain why the CiteScore is remarkably high. As is known to all, the CiteScore can impact authors’ decision-making in selecting journals suiting their original and note-worthy works. Also, after investigation, the Journal of Cleaner Production strongly connects to clean manufacturing, environmental challenges, and sustainable development.\n\nNote = TP: Total Publication/ TC: Total Citation\n\nIn addition, as shown in Table 3, the top ten journals are nearly all of excellent quality (as they are all SCI or SCIE), such as the social science citation index or science citation index expanded, except for the Sustainability Switzerland. Also, the CiteScore of Sustainability Switzerland is low. But the Sustainability Switzerland is still among the top two most productive journals. That might be because the authors consider the CiteScore and take into account if the journal can deliver research to appropriate readers and facilitate the development of the research area. Sustainability Switzerland is mainly related to sustainability and sustainable development. Therefore, CiteScore ought not to be considered the only measure. Aside from CiteScore, researchers should consider whether the publication can convey research to the appropriate academics and accelerate the relevant research field development.\n\nTable 4 presents the top 15 most prolific nations facilitating the increase of sustainability performance studies across the globe. Approximately 38% of the international research were from the United States and Australia, revealing that both nations are pivotal for developing sustainability performance studies. The United States was the leading nation with 867 articles, covering 26% of the overall articles across the world. With one-half of the United States’ overall articles, Australia was the second most prolific nation. However, Oregon State University’s total publication (TPi) was comparable to that of the University of Queensland, albeit slightly lower than that of Universiti Teknologi Malaysia. As a result, having the most productive academic institution may not be synonymous with being the most productive country.\n\n*Note = Abbreviation: TPc - Total Publications of a Given Country/ TPi - Total Publications of a Given Academic Institution/S.C.P. - Single-Country Publications\n\nBesides, only India (73.2%) had over 2/3 single-country publications (S.C.P.) among the 15 countries. This indicated that India has a more vital intra-country collaboration than other countries. Additionally, China was the nation with the least S.C.P. with 37.0%, in which 101 out of 273 articles were associated with several affiliations from 43 diverse nations. Furthermore, China has more total publications than India, which indicates that international collaboration should be a focus. As shown in Figure 3, outcomes of co-authorship revealed that America was the most affiliated nation, linked to 53 nations/territories. Moreover, the United States produced the most publications, with the total number of publications ranking first. Therefore, international collaboration might contribute to producing more publications. The government needs to formulate flexible and steady policies to sustain transnational collaborations.\n\nThe URL below can be utilized to open Figure 3 in VOSviewer39: https://bit.ly/3vZdPU7\n\nThe analyses of the knowledge development track in the study field can assist scholars in comprehensively capturing the development trend of the study field, forecasting the developmental tendency, and offering scholars more research targets. In past research, certain scholars utilized quantitative computation on the foundation of the occurrence frequency or co-occurrence frequency of words or phrases, which delineate the study. As per the association strength between topic words, they clustered them and drew a net of subject topics in diverse periods’ atlases to identify the development path of the study field38.\n\nAs shown in Figure 4, there are 7634 author keywords documented, amongst which 6006 (78.7%) were merely utilized once, 782 essential words (10.2%) were utilized twice, and 276 (3.6%) were utilized three times. After re-labelling synonymical single words and congenerical phrases, 420 keywords reached the liminal value of minimal five occurrences for VOSviewer. In the map, the term ‘sustainability’ was the most popular keyword with 878 occurrences and 337 associations with other keywords. In addition, our team discovered the utilization of general terms like “organizational sustainability” (8 occurrences, 12 links), “corporate sustainability” (129 occurrences, 112 links) and ‘triple bottom line’ (22 occurrences, 29 links).\n\nThe URL below can be utilized to open Figure 4 in VOSviewer39: https://bit.ly/ 3bsitk4.\n\nThe critical concept of sustainable development includes three pivotal components, including society, environment, and economic development41. In Figure 4, keywords associated with ‘social sustainability, ‘economic sustainability’ and ‘environmental sustainability’ were repeated 31, 69 and 70 times, respectively. This result suggests that the researchers overlooked the social sustainability aspect. Although, some researchers indicated that corporations and commercial activities shouldn’t merely highlight the economy-wise sustainable development. The other aspects should be taken into consideration as well because they are equally essential42–44.\n\nKeywords that address challenges within sustainability performance by inner or outer factors were discovered as well, e.g., ‘green supply chain’ was reported 21 times and often cooccurred with ‘reverse logistics’. Furthermore, green manufacturing, green purchasing and green packaging, three elements of the green supply chain, were identified as the factor for influencing reverse logistics45. But there have been no academics researching the effect of other elements of the green supply chain on reverse logistics, which provided a research gap for future study. On the other hand, material flow analysis is the most popular research topic among the top ten contributing authors. Nevertheless, no streams of keyword occurrence were observed in the review, which linked material flow analysis and sustainable development performance.\n\nAs per the number of research and author keyword occurrences, positive associations were discovered between the outputs of the subtheme search and the centric theme search. For example, it is shown that the manufacturing industry was the most commonly seen application with 1149 papers in Scopus and 28 occurrences in VOSviewer. This was followed by the construction industry (700 papers and 21 occurrences), food industry (593 papers and 11 occurrences), automotive industry (371 papers and 7 occurrences), agriculture industry (362 papers and 7 occurrences), and oil and gas industry (246 papers and 6 occurrences).\n\nIn fact, the manufacturing sector is a cornerstone of economic development, which is pivotal for economy-wise sustainability, and it serves as a major contributor to the Gross Domestic Product (G.D.P.), employment rates and export percentage of countries around the world. However, the rapid development of manufacturing has caused substantial waste, overuse of various resources and overconsumption of energy46. Also, achieving sustainability performance helps manufacturing organizations to attain a competitive advantage in the market that is moving towards a greener economy and achieving significant financial gains while attracting customers to assure long term profitability47. As a result, an increasing number of academics and practitioners are incorporating sustainability into the manufacturing industry, and the manufacturing industry has become the focus of research.\n\nFurthermore, Figure 5 showed that most publications related to the manufacturing industry, construction industry, food industry, automotive industry and agriculture industry came from the U.S.A. except on the agriculture industry. Australia is the primary focus of research into the agriculture industry’s sustainability performance. The reason for it could be linked to Australia’s economy and culture. The agricultural sector is vital for Australia’s economic and cultural development. In this country, about 65% of overall production is exported, which accounts for about 14% of the overall exportation value in Australia48. Also, in general, the U.K. was amongst the top five nations that publish research on all sustainability performance applications. Other nations like China, Australia, Malaysia, India, Netherlands and Italy were listed in diverse applications of sustainability performance and merely once.\n\nThe outcome may not cover all sustainability performance-associated research on Scopus by restricting the search of “sustainability performance” within titles, abstracts, and content. That’s because certain scholars didn’t refer to their systems as sustainability performance but instead utilized diverse terms. Research in the future should contrast the outputs from several databases like Scopus and Web of Sciences. The search outcomes from Web of Science, for example, automatically demonstrate the most popular research via the ‘hot paper’ function, which remains absent in Scopus. Such a function demonstrates that pivotal research was recognized quickly after publication, which is reflected via a fast and remarkable citation number. Utilizing bibliometric analyses via several data sources will facilitate more systematic research.\n\n\nConclusions\n\nThe present paper aims to help researchers and practitioners grasp the research tendency in sustainability performance and find the underlying orientations for further studies. As per academic database outputs, bibliometric analyses are a mechanical method to grasp the international research tendency in certain study fields. Such a method can distinguish a bibliometric analysis report from a review study mainly aimed at summarizing the latest development, problems, and future orientations of specific topics. Although there are certain limitations, this research is still vital for sustainability performance researchers.\n\nFirstly, the outcomes herein reveal that the sustainability performance field has witnessed remarkable advancement recently. Publications have been increasing over the past ten years and are anticipated to increase progressively. Secondly, according to the findings of this study, the academics who focus on sustainability performance-related research are all university professors. Moreover, when publishing the article, the authors should not only consider the CiteScore but also take into account if the journal can deliver research to appropriate readers and facilitate the development of the research area. Furthermore, the study identified countries and academic institutions with solid international and internal cooperation (e.g., U.S.A. and India). Those international and internal collaborations are a treasure for scholars to expand their studies. However, the fact that some countries and regions lack international collaboration and specialized policies to support collaboration should be noted.\n\nFinally, this paper found the research trend for academics. There are three elements of sustainability performance, however, social sustainability has been somewhat overlooked, and this should be noted. Likewise, the association of material flow with sustainable development performance, which offers future orientations for scholars, practitioners and investigators in future studies on sustainability performance, ought to be extensively researched. Moreover, merely co-authorship and cooccurrence analyses were completed via the VOSviewer. Thereby, more tools, like co-citation and bibliographical coupling of the program, can be utilized. Because sustainability performance is important across the globe, the sustainability performance research boundaries are expected to expand progressively, and more thrilling topics will definitely emerge.\n\n\nData availability\n\nDryad: An Exploration of Trends and Future Directions in Sustainability Performance. https://doi.org/10.5061/dryad.8kprr4xqx49.\n\nThis project contains the following underlying data:\n\nScopus.csv (articles from 1997–2010).\n\nScopus_(1).csv (articles from 2010–2021).\n\n[insert license statement].", "appendix": "References\n\nM. M. O. World Meterological Organization (WMO): Global climate in 2015-2019: Climate change accelerates. 2019. Reference Source\n\nM. M. O. World Meterological Organization (WMO): The state of the global climate 2020. 2020. Reference Source\n\nZhang C, Cai W, Liu Z, et al.: Five tips for china to realize its co-targets of climate mitigation and sustainable development goals (SDGs). Geography and Sustainability. 2020; 1(3): 245–249. Publisher Full Text\n\nKhan SAR, Zhang Y, Kumar A, et al.: Measuring the impact of renewable energy, public health expenditure, logistics, and environmental performance on sustainable economic growth. Sustainable Development. 2020; 28(4): 833–843. Publisher Full Text\n\nPradhan P, Costa L, Rybski D, et al.: A systematic study of sustainable development goal (sdg) interactions. Earth’s Future. 2017; 5(11): 1169–1179. Publisher Full Text\n\nTsalis TA, Malamateniou KE, Koulouriotis D, et al.: New challenges for corporate sustainability reporting: United nations’ 2030 agenda for sustainable development and the sustainable development goals. Corp Soc Responsib Environ Manag. 2020; 27(4): 1617–1629. Publisher Full Text\n\nMorioka SN, Bolis I, Evans S, et al.: Transforming sustainability challenges into competitive advantage: Multiple case studies kaleidoscope converging into sustainable business models. J Clean Prod. 2017; 167: 723–738. Publisher Full Text\n\nEngida TG, Rao X, Berentsen PBM, et al.: Measuring corporate sustainability performance- the case of european food and beverage companies. J Clean Prod. 2018; 195: 734–743. Publisher Full Text\n\nSeuring S: A review of modeling approaches for sustainable supply chain management. Decis Support Syst. 2013; 54(4): 1513–1520. Publisher Full Text\n\nLuthra S, Mangla SK, Shankar R, et al.: Modelling critical success factors for sustainability initiatives in supply chains in indian context using grey-dematel. Production Planning & Control. 2018; 29(9): 705–728. Publisher Full Text\n\nSafdar N, Khalid R, Ahmed W, et al.: Reverse logistics network design of e-waste management under the triple bottom line approach. J Clean Prod. 2020; 272:122662. Publisher Full Text\n\nLiu W, Bai E, Liu L, et al.: A framework of sustainable service supply chain management: A literature review and research agenda. Sustainability. 2017; 9(3): 421. Publisher Full Text\n\nFranceschini F, Maisano D, Mastrogiacomo L: Empirical analysis and classification of database errors in scopus and web of science. J Inform. 2016; 10(4): 933–953. Publisher Full Text\n\nAghaei Chadegani A, Salehi H, Yunus M, et al.: A comparison between two main academic literature collections: Web of science and scopus databases. Asian social science. 2013; 9(5): 18–26. Publisher Full Text\n\nHelleno AL, de Moraes AJI, Simon AT: Integrating sustainability indicators and lean manufacturing to assess manufacturing processes: Application case studies in brazilian industry. J Clean Prod. 2017; 153: 405–416. Publisher Full Text\n\nOrji IJ: Examining barriers to organizational change for sustainability and drivers of sustainable performance in the metal manufacturing industry. Resour Conserv Recycl. 2019; 140: 102–114. Publisher Full Text\n\nAhmad S, Wong KY, Rajoo S: Sustainability indicators for manufacturing sectors: A literature survey and maturity analysis from the triple-bottom line perspective. Journal of Manufacturing Technology Management. 2019; 30(2): 312–334. Publisher Full Text\n\nAhi P, Searcy C, Jaber MY: Energy-related performance measures employed in sustainable supply chains: A bibliometric analysis. Sustainable Production and Consumption. 2016; 7: 1–15. Publisher Full Text\n\nZubir AFM, Habidin NF, Conding J, et al.: The development of sustainable manufacturing practices and sustainable performance in malaysian automotive industry. J Econ Sustain Dev. 2012; 3(7): 130–138. Reference Source\n\nRosen MA, Kishawy HA: Sustainable manufacturing and design: Concepts, practices and needs. Sustainability. 2012; 4(2): 154–174. Publisher Full Text\n\nVinodh S, Joy D: Structural equation modeling of sustainable manufacturing practices. Clean Techn Environ Policy. 2012; 14(1): 79–84. Publisher Full Text\n\nCarter C, Rogers DS: A framework of sustainable operations management: Moving toward new theory. International Journal of Physical Distribution and Logistics Management. 2008; 38(5): 360–387. Publisher Full Text\n\nMirkouei A, Haapala KR, Sessions J, et al.: A mixed biomass-based energy supply chain for enhancing economic and environmental sustainability benefits: A multi-criteria decision making framework. Appl Energy. 2017; 206: 1088–1101. Publisher Full Text\n\nMoktadir MA, Ali SM, Rajesh R, et al.: Modeling the interrelationships among barriers to sustainable supply chain management in leather industry. J Clean Prod. 2018; 181: 631–651. Publisher Full Text\n\nMota B, Gomes MI, Carvalho A, et al.: Towards supply chain sustainability: economic, environmental and social design and planning. J Clean Prod. 2015; 105: 14–27. Publisher Full Text\n\nCao M, Zhang Q: Supply chain collaboration: Impact on collaborative advantage and firm performance. Journal of Operations Management. 2011; 29(3): 163–180. Publisher Full Text\n\nLi Y, Zhao X, Shi D, et al.: Governance of sustainable supply chains in the fast fashion industry. European Management Journal. 2014; 32(5): 823–836. Publisher Full Text\n\nChopra S, Meindl P: Supply chain management:strategy, planning, and operation. Boston: Pearson, 2016; 31(7): 144–144. Reference Source\n\nEvren S, Kozak N: Bibliometric analysis of tourism and hospitality related articles published in turkey. Anatolia. 2014; 25(1): 61–80. Publisher Full Text\n\nMuñoz Leiva F, Porcu L, del Barrio-García S, et al.: Discovering prominent themes of integrated marketing communication research from 1991 to 2012: A co-word analytic approach. Int J Advert. 2015; 34(4): 678–701. Publisher Full Text\n\nDe Sousa Jabbour ABL, Ndubisi NO, Seles BMRP: Sustainable development in asian manufacturing smes: Progress and directions. Int J Prod Econ. 2020; 225: 107567. Publisher Full Text\n\nJabbour CJC: Environmental training in organisations: From a literature review to a framework for future research. Resour Conserv Recycl. 2013; 74: 144–155. Publisher Full Text\n\nMariano EB, Sobreiro VA, Rebelatto DADN: Human development and data envelopment analysis: A structured literature review. Omega. 2015; 54: 33–49. Publisher Full Text\n\nSeuring S, Müller M: From a literature review to a conceptual framework for sustainable supply chain management. J Clean Prod. 2012; 16(15): 1699–1710.\n\nSheeraz MI, Ahmad UNU, Nor KM: What makes articles cited highly? an analysis of top 100 highly cited articles on organizational citizenship behavior. FWU Journal of Social Sciences. 2021; 15(1): 90–104. Reference Source\n\nBrzezinski M: Power laws in citation distributions: evidence from scopus. Scientometrics. 2015; 103(1): 213–228. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHarzing AW, Alakangas S: Google scholar, scopus and the web of science: a longitudinal and cross-disciplinary comparison. Scientometrics. 2016; 106(2): 787–804. Publisher Full Text\n\nMeng L, Wen KH, Brewin R, et al.: Knowledge atlas on the relationship between urban street space and residents’ health—a bibliometric analysis based on vosviewer and citespace. Sustainability. 2020; 12(6): 2384. Publisher Full Text\n\nWaltman L, van Eck NJ, Noyons ECM: A unified approach to mapping and clustering of bibliometric networks. J Inform. 2010; 4(4): 629–635. Publisher Full Text\n\nRaghuram S, Tuertscher P, Garud R: Mapping the field of virtual work: a co-citation analysis. Information Systems Research. 2010; 21(4): 983–999. Reference Source\n\nBeske P, Land A, Seuring S: Sustainable supply chain management practices and dynamic capabilities in the food industry: A critical analysis of the literature. Int J Prod Econ. 2014; 152: 131–143. Publisher Full Text\n\nSeuring S, Müller M: From a literature review to a conceptual framework for sustainable supply chain management. J Clean Prod. 2008; 16(15): 1699–1710. Publisher Full Text\n\nMandal S: Towards a new framework for sustainable supply chain management. Int J Manuf Mater Mech Eng. 2013; 3(3): 1–12. Publisher Full Text\n\nHossan Chowdhury MM, Quaddus MA: Supply chain sustainability practices and governance for mitigating sustainability risk and improving market performance: A dynamic capability perspective. J Clean Prod. 2021; 278: 123521. Publisher Full Text\n\nHsu CC, Tan KC, Mohamad Zailani SH: Strategic orientations, sustainable supply chain initiatives, and reverse logistics: Empirical evidence from an emerging market. International Journal of Operations & Production Management. 2016; 36(1): 86–110. Publisher Full Text\n\nAbdul-Rashid SH, Sakundarini N, Raja Ghazilla RA, et al.: The impact of sustainable manufacturing practices on sustainability performance: Empirical evidence from Malaysia. International Journal of Operations & Production Management. 2017; 37(2): 182–204. Publisher Full Text\n\nCankaya SY, Sezen B: Effects of green manufacturing and eco-innovation on sustainability performance. Journal of Manufacturing Technology Management. 2019; 99(6): 154–163.\n\nAustralian Government: Agricultural trade. 2020.\n\nYang K, Thoo AC: An exploration of trends and future directions in sustainability performance. Dryad, Dataset. 2022. http://www.doi.org/10.5061/dryad.8kprr4xqx" }	[ { "id": "199402", "date": "16 Oct 2023", "name": "Francisco Jesús Gálvez-Sánchez", "expertise": [ "Reviewer Expertise environmental sustainability", "circular economy", "CSR and social sustainability." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nDear authors, I appreciate the opportunity to review the manuscript entitled \"An exploration of trends and future directions in sustainability performance: A bibliometric analysis of Scopus database”, which proposes a bibliometric analysis of scientific production on sustainability performance, based on the Scopus database, and presenting the main authors, institutions, countries, journals and thematic analysis.\nNext, I review the content of the manuscript, as well as make some minor contributions that I hope will be well considered by the authors, as well as contribute to improving the original version of the manuscript:\nIn my opinion, sections 1 and 2 would fit better together. As it is fundamentally a theoretical analysis, it would be better structured if once the authors substantiate the meteorological changes that have been taking place over the last few years, and just afterwards describe the concept of sustainability performance. This would further help readers understand the rationale for the research. Following this, the research gap should be addressed, which is not discussed much in the current version, beyond the description of the concepts. At the end of this section, I think it would be appropriate to dedicate a final paragraph to describe the final structure of the manuscript, something that is often useful for readers to identify the most relevant sections of the manuscript.\n\nThe methods section is quite complete. The authors justified the selected database, the methodological procedure applied, the software used and the inclusion criteria. However, in the latter, the authors could be more careful and provide some additional justification for the reasons why they applied these criteria, including some additional bibliographic references if necessary to support their decisions. Additionally, in the study limitations section, reference should be made to this, that is, that part of the scientific production was not considered as a consequence of the inclusion criteria used, especially in the case of the type of documents.\n\nThe results section, in my opinion, is also quite complete. The bibliometric indicators used are the most common in this type of study. However, I think there are two issues that can go deeper. (A) In the analysis of publication trends, the authors talk about the growth of academic literature, although they do not discuss in depth the causes that could cause it. In my opinion, reviewing the dates of the main international political agendas on sustainability would help to better explain the changes in the growth trend of publications over time. (B) The co-occurrence section is too weak. One of the fundamental contributions of bibliometric studies is to explain how the different topics within the line of research emerged over time. Here, I feel the authors were lax and could add much more value to their research by putting a little more effort into it.\n\nThe limitations section of the study, in my opinion, would be better placed in the conclusions section.\n\nThe conclusion section is too weak. The authors basically make a brief summary of their results. It is very important to highlight the main contributions of this research, how it has contributed to generating new theoretical (and perhaps practical) knowledge, or, among other issues, for whom and why the new available knowledge is valuable.\n\nIn general terms, I show my appreciation to the researchers, since they carried out a research work that I consider to be relevant, current and innovative. However, I feel they should spend a little more time explaining these recommendations so that the research really has a big impact for future readers.\nAll the best.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] }, { "id": "228113", "date": "22 Dec 2023", "name": "Norsiah Hami", "expertise": [ "Reviewer Expertise Technology management", "Sustainable performance", "Sustainable manufacturing" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn overall, this manuscript is good and interesting. However, there is no discussion on the validation process of the instrument or data. In addition, the argument that \"there have been no academics researching the effect of other elements of the green supply chain on reverse logistics, which provided a research gap for future study\" is questionable. Reverse logistic was considered as one of the element of green supply chain in many previous studies.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "211468", "date": "26 Jan 2024", "name": "Qaisar Iqbal", "expertise": [ "Reviewer Expertise Sustainable Development", "Leadership", "Sustainable HRM", "SMEs" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nI appreciate your hard work. Yet, I have noted a few discrepancies and would recommend you fix all these in the revised draft.\nIn the draft, it is written \"To include only papers within the analysis time (1997 – 2021).\nFollowing your inclusion criteria, I found that few names such Ahmad, N.H. (13), Iqbal, Q. (13), Choi, Y. (10) were supposed to be in the top productive author's list but are missing. More recently, there is also a review paper about leadership-sustainable performance which is also missing in your draft.\nRelevant research papers are shared here for fixing of these issues in the revised draft: Piwowar-Sulej and Iqbal (20231); Lin et al. (20222).\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "269824", "date": "07 May 2024", "name": "Raghavendran Sivasubramanian", "expertise": [ "Reviewer Expertise Wastewater treatment", "Aerobic sludge", "Linear regression statistics", "Algae biodiesel", "Advanced reduction process", "Environmental Sustainability" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nVerdict: Accepted, with modifications. This article reviews the updates on sustainability practices and points the directions that the existing journals have progressed since 1997. The reviewer has reservations on this article.\nThis paper is written with a lot of efforts! Very detail-oriented and well-explained. However, this paper does not add any real value for the already existing knowledge.\n\nMethods in Abstract needs to be rewritten:\n“This article reviewed more than 3500 papers that are published in Scopus where document co-authorship, co-occurrence analyses and burst detection analyses were analyzed using VOSviewer software.”\n\nThe Result section in the Abstracts is not really needed. They do not present a scientific understanding/ presentation. They need to be re-written by keeping information really needed for scientific understanding. Introduction:\n“According to the World Meteorological Organization, the period 2015–2020 was the warmest on record, with global climate change increasing by 0.2 percent compared to 2011–2015.” – Please provide the temperature values. Paragraph 3 needs to be completely re-written. The authors have jumped to a new segment without connecting the dots way too soon. The entire paragraph feels out of place.\n\nThe referencing in this paper is bad. When citing a source, please add the authors’ names in text.\n“According to Ahi and Jaber (18)” – Page 3 “For example, Carter and Rogers (22)” – Page 3 “De Sousa Jabbour et al (31) employed this strategy, and other studies (32-24) have used a similar methodology. Provide a reference for Gaur and Kumar (2018).\n\nWhy are the timespan chosen from 1997 and not before that? Remove the sentences: “Scopus is the largest database of abstracts and citations, with 1.4 billion citations and 16 million author data35. The Scopus database is superior to similar alternatives since it indexes approximately 70% more sources36. It gives more thorough coverage of the newest literature, according to 37.” It is just an advertisement for Scopus! Remove the first paragraph in Process of selecting articles. It is unnecessary. Remove the second paragraph in Data Analysis method. It is unnecessary. Remove the Most Influential Authors section. The Literature Development Trends may not be needed at all! The reason for increase from 2001 was because the area became easy to publish. The factor influence is debatable.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] } ]	1	https://f1000research.com/articles/11-864
https://f1000research.com/articles/11-862/v1	29 Jul 22	{ "type": "Systematic Review", "title": "The global prevalence and association between the risk of myocarditis and mRNA-based COVID-19 vaccination: A network meta-analysis", "authors": [ "Mohammad Rohman", "Jonny Karunia Fajar", "Gatot Soegiarto", "Laksmi Wulandari", "Muhammad Anshory", "Muhammad Ilmawan", "Dewi Marlysawati", "Yeni Purnamasari", "Andy Pranata Kusuma", "Anisa Asmiragani", "Dimas Adhiatma", "Andi Permana", "Erwin Alexander Pasaribu", "Helnida Anggun Maliga", "Yuri Pamungkas", "Putu Wina Margarani Puteri", "Vebri Anita Sinaga", "Dedy Setiawan", "Effika Nurningtyas Putri", "Eliza Techa Fattima", "Olivia Listiowati Prawoto", "Rina Safitri", "Roma Yuliana", "Kholisotul Hikmah", "Yama Sirly Putri", "Laili Nurzaidah", "Lianto Lianto", "Meiliana Dwi Cahya", "Muhammad Ikhsan", "Ibrahim Ibrahim", "Anggara Dwi Samudra", "Fredo Tamara", "Dessy Aprilia Kartini", "Aditya Indra Mahendra", "Kuldeep Dhama", "Harapan Harapan", "Laksmi Wulandari", "Muhammad Anshory", "Muhammad Ilmawan", "Dewi Marlysawati", "Yeni Purnamasari", "Andy Pranata Kusuma", "Anisa Asmiragani", "Dimas Adhiatma", "Andi Permana", "Erwin Alexander Pasaribu", "Helnida Anggun Maliga", "Yuri Pamungkas", "Putu Wina Margarani Puteri", "Vebri Anita Sinaga", "Dedy Setiawan", "Effika Nurningtyas Putri", "Eliza Techa Fattima", "Olivia Listiowati Prawoto", "Rina Safitri", "Roma Yuliana", "Kholisotul Hikmah", "Yama Sirly Putri", "Laili Nurzaidah", "Lianto Lianto", "Meiliana Dwi Cahya", "Muhammad Ikhsan", "Ibrahim Ibrahim", "Anggara Dwi Samudra", "Fredo Tamara", "Dessy Aprilia Kartini", "Aditya Indra Mahendra", "Kuldeep Dhama", "Harapan Harapan" ], "abstract": "Background: Cases of myocarditis development have been reported after administration of messenger ribonucleic acid (mRNA)-based coronavirus disease (COVID-19) vaccines. However, the reports vary among the studies, and the types of mRNA vaccines with potential to cause myocarditis remain unidentified. The objective was to assess the cumulative prevalence of myocarditis and determine the association between myocarditis and mRNA-based COVID-19 vaccination. Methods: We performed a network meta-analysis by searching articles in PubMed, Scopus, and Web of Science. Information on the prevalence of myocarditis after the mRNA-based COVID-19 vaccination was collected from each study. Analysis was performed by calculating the pooled prevalence rate, and the association was determined using the Z-test. Data networking was performed using the Bayesian method. Results: A total of 18 papers was included in our analysis. We found that the cumulative prevalence of myocarditis was 1.7, 1.9, 1.2, and 1.1 per 100,000 population after vaccination with different types of mRNA-based COVID-19 vaccines, namely all mRNA COVID-19 vaccines, BNT162b1, mRNA-1273, and the combination of BNT162b1 and mRNA-1273, respectively. Moreover, the results revealed that BNT162b1 vaccination increased the risk of myocarditis by 1.64- and 1.71-folds compared to mRNA-1273 and the combination of BNT162b2 and mRNA-1273, respectively. Similar risks of developing myocarditis were observed after mRNA-1273 and the combination of BNT162b1 and mRNA-1273 vaccination. Conclusions: Our findings suggest the cumulative prevalence of myocarditis after mRNA-based COVID-19 vaccination with maximum prevalence was observed after BNT162b2 administration. BNT162b2 was associated with a higher risk of developing myocarditis than the other mRNA-based COVID-19 vaccines.", "keywords": [ "Myocarditis", "side effect", "vaccination", "mRNA", "COVID-19" ], "content": "Introduction\n\nSince early 2021, the COVID-19 vaccination program has been initiated in many regions.1 The program involves administration of several types of COVID-19 vaccines such as inactivated, protein subunits, messenger ribonucleic acid (mRNA)-based, and vector vaccines.2 It is widely known that a vaccine development usually requires 10-15 years before it is ready to use in human subjects. Moreover, it undergoes various steps including antigen identification and production, non-clinical (animal) testing, clinical trials (phase I-III), filing and licensing, and surveillance However, the vaccine development process for COVID-19 was completed in approximately a year. The fact that the COVID-19 pandemic resulted in very high mortality rates globally, led to an urgent need for the vaccine, which explains the short duration of vaccine development.3,4 However, this rapid process probably led to unfolding of various side effects gradually.5 Of all the available vaccines, mRNA-based COVID-19 vaccines have been associated with maximum side effects.6\n\nmRNA vaccines have been investigated for several infectious diseases such as Cytomegalovirus, Zika virus, Human Metapneumovirus, Respiratory Syncytial Virus, Influenza, Chikungunya, and Rabies.7 Of these viruses, some serious side effects like toxic epidermal necrolysis were reported in the case of mRNA Rabies vaccine.8 Similarly, the mRNA-based COVID-19 vaccine also showed some minor side effects such as pain or redness at the site of injection, fatigue, fever, headache, nausea or vomiting, chest pain, and shortness of breath.9 Additionally, some fatal side effects such as acute kidney injury, anemia, and myocarditis have been reported.10 Of these, myocarditis is the most life-threatening condition due to associated high mortality rates (25%-56%).11 Various observational studies and case reports and series have shown the occurrence of myocarditis after mRNA-based COVID-19 vaccine administration;10,12–29 however, the findings vary across the studies. In the current scenario, global prevalence rate of myocarditis post mRNA-based COVID-19 vaccination should be established precisely, and the types of vaccines associated with this condition should be identified. Therefore, the present study aimed to assess the global prevalence and association between the risk of myocarditis and mRNA-based COVID-19 vaccination, using a networking meta-analysis approach.\n\n\nMethods\n\nA meta-analysis following the protocols of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA)30 was conducted. The PRISMA checklist in our present study was provided in the supplementary files.31 To analyze our study objectives, a systematic search was conducted in PubMed, Scopus, and Web of Science and the required data were retrieved to calculate the cumulative prevalence and effect estimates.\n\nEligibility criteria were defined prior to the systematic search. The inclusion criteria for study sources were as follows: (1) Assessed the prevalence of myocarditis after mRNA-based COVID-19 vaccination and (2) provided the required information to calculate the prevalence and effect estimates. Reviews, commentaries, letters to the editor, and double publications were excluded from the study sources.\n\nA systematic search was conducted in PubMed, Scopus, and Web of Science between January and February 2022; as of 3 February 2022 3rd, data collection was finished. Before searching for the primary outcomes, we searched for the type of mRNA-based COVID-19 vaccines involved in our study. The keywords adapted from medical subject headings used were as follows: [“mRNA COVID-19 vaccine” or “BNT162b1” or “Pfizer” or “mRNA-1273” or “Moderna”], [“Myocarditis” or “side effect”], and [“COVID-19” or “Coronavirus disease-19”]. The systematic search was limited to English language and original articles. In case of double publications, only studies with larger sample sizes were included. Moreover, a systematic search of the reference list of relevant systematic reviews was conducted to collect additional articles. Subsequently, the data of interest from the selected articles were extracted and included: (1) first author name, (2) publication year, (3) study design, (4) type of mRNA-based COVID-19 vaccines, (5) trade name of the vaccines, and (6) the incidence of myocarditis after mRNA-based COVID-19 vaccination. Two independent investigators (JKF and MI) performed the systematic search and extracted the data. Prior to performing the systematic search and data extraction, the assessments and ratings given by independent investigators were analyzed using the kappa agreement. Agreement was established if the coefficient of kappa agreement was greater than the p-value.\n\nBefore their inclusion in our analysis, the articles were assessed for quality using the Newcastle-Ottawa scale (NOS)32 with score ranging from 0 to 9. A score of 7-9, 4-6, and 0-3 indicated that the papers were of high, moderate, and low quality, respectively. Low-quality articles were excluded from the analysis. Using a pilot form, quality assessment was performed by two independent authors (JKF and MI) and any discrepancies were resolved through discussion.\n\nThe primary outcomes were cumulative prevalence and risk of myocarditis after mRNA-based COVID-19 vaccination. To identify the potential mRNA-based COVID-19 vaccines, an initial evaluation of the available data in PubMed, Scopus, and Web of Science was performed. We found that BNT162b1 (Pfizer) and mRNA-1273 (Moderna) were suitable for our analysis. Myocarditis cases data were retrieved according to the International Classification of Diseases, Tenth Revision (ICD-10) as follows: I40.0 (infectious myocarditis), I40.1 (isolated myocarditis), I40.8 (other acute myocarditis), I40.9 (acute myocarditis), I41 (myocarditis in diseases classified elsewhere), I51.4 (myocarditis unspecified), or B33.22 (viral myocarditis).\n\nBefore analyzing the data, potential publication bias and heterogeneity across the studies were assessed. Publication bias was determined using an Egger test, with a p-value ˂ 0.05 indicating a trend towards publication bias. Heterogeneity among studies was evaluated using the Q test with a p-value ˂ 0.10 suggesting heterogeneity and that a random effect model should be applied for data analysis; otherwise, fixed-effects model were be used. The cumulative prevalence of myocarditis after mRNA-based COVID-19 vaccination was determined using a single-arm meta-analysis with the dichotomous covariate method by calculating the event per sample size from each study. The effect estimate was presented as (logit) event rate. The analysis was performed using R software (RStudio version 4.1.1, MA, US). Confidence in Network Meta-Analysis (CINEMA 1.9.1, Bern, Switzerland) software was used to outline the network diagram of the comparison of the risk of myocarditis among patients administered with different types of mRNA-based COVID-19 vaccines. The effect estimate was presented in a forest plot as the pooled odd ratio and 95% confidence interval (OR 95% CI).\n\n\nResults\n\nWe collected 997 potential papers from the database and 16 papers from the reference list of related systematic reviews. Of these, 22 papers were excluded owing to the duplication of data and 942 papers owing to irrelevant topics. Subsequently, we included 49 full-text review papers. From these, 12 reviews, 16 case reports, and three papers were excluded owing to insufficient data. Finally, a total of 18 papers were analyzed to determine the cumulative prevalence and risk of myocarditis after mRNA-based COVID-19 vaccination.10,16–29 The process of article selection is shown in Figure 1 and the characteristics of the included papers are summarized in Table 1.\n\nThe data analysis revealed that the prevalence of myocarditis after mRNA-based COVID-19 vaccination was 859 cases in a population of 51,826,799 (logit event rate: ˗10.70; 95% CI: ˗11.24, ˗ 10.16) (Figure 2A). In subgroup analyses, the prevalence of myocarditis was 643 cases in a population of 33,088,209 (logit event rate: ˗10.61; 95% CI: ˗11.29, ˗9.93) (Figure 2B) after BNT162b1 (Pfizer) vaccination, 126 cases in a population of 10,710,913 (logit event rate: ˗10.13; 95% CI: ˗12.62, ˗7.64) (Figure 2C) after mRNA-1273 (Moderna) vaccination, and 90 cases in a population of 8,027,677 (logit event rate: ˗11.23; 95% CI: ˗12.44, ˗10.02) (Figure 2D) after combined vaccination with BNT162b1 and mRNA-1273. A summary of the cumulative prevalence of myocarditis after the mRNA-based COVID-19 vaccination is outlined in Table 2.\n\nA). All type of mRNA COVID-19 vaccines. B). Pfizer mRNA COVID-19 vaccines. C). Moderna mRNA COVID-19 vaccines. D). The combination of Pfizer and Moderna.\n\nThe indirect comparison (Figure 3A) revealed that the use of BNT162b1 vaccination increased the risk of myocarditis by 1.63-folds compared to mRNA-1273 vaccination (OR: 1.63; 95% CI: 1.35, 1.97; p < 0.0001). Moreover, BNT162b1 was associated with an increased risk of myocarditis compared to the combination of BNT162b1 and mRNA-1273 vaccines (OR: 1.71; 95% CI: 1.37, 2.13; p < 0.0001). mRNA-1273 and the combination of BNT162b1 and mRNA-1273 showed a similar risk of developing myocarditis (OR: 1.05; 95% CI: 0.80, 1.38; p = 0.7270). A summary of the indirect comparison of the risk of myocarditis associated with different mRNA-based COVID-19 vaccines is presented in Table 3 and the network is illustrated in Figure 3B.\n\nHeterogeneity was observed in all the models of analysis. Therefore, we used a random-effects model. Egger’s test was used to assess the potency of bias among the studies. Our pooled analyses revealed no publication bias (Table 2).\n\n\nDiscussion\n\nOur findings revealed that the pooled prevalence rate of myocarditis after mRNA-based vaccination was 1.7 cases per 100,000 population. Specifically, it was 1.9, 1.2, and 1.1 cases per 100,000 population after BNT162b1, mRNA-1273, and combination of BNT162b1 and mRNA-1273 vaccination, respectively. Our study is the first meta-analysis to report the prevalence of myocarditis after administration of different types of mRNA-based COVID-19 vaccines. Previously, a total of four meta-analyses in this context were conducted.33–36 However, these reports are limited to the crude prevalence rate and did not investigate different types of mRNA-based COVID-19 vaccinations. According to these reports the cumulative prevalence rate of myocarditis after mRNA-based COVID-19 vaccination was 1.2-11.9 per 100,000 population,35,36 which is consistent with our findings. In our study, we included a larger sample size; therefore, the present study might provide a better insight into the precise prevalence rate.\n\nWe also reported that BNT162b1 vaccination was associated with 1.6 and 1.7-folds higher risk of developing myocarditis compared to mRNA-1273 and the combination of BNT162b1 and mRNA-1273 vaccines, respectively. On the other hand, mRNA-1273 and the combination of BNT162b2 and mRNA-1273 shared similar risks of developing myocarditis. The underlying mechanism by which BNT162b1 vaccination leads to a higher risk of developing myocarditis remains debatable. Briefly, the principle of mRNA-based COVID-19 vaccination is to produce viral-mRNAs that can encode the perfusion stabilized full-length spike protein, a protein involved in the interaction with ACE2 receptors to infect the target cells. The production of antibodies with high affinity to spike protein may inhibit the interaction between spike protein and ACE2 receptors and therefore may provide protection against COVID-19 infection.37 Spike proteins of SARS-COV-2 have a molecular weight of 180-200 kDa.38 On the other hand, myocardial cells consist of actin and myosin proteins. These proteins have a molecular weight of 100-250 kDa.39 In the theory of cross-immunity, it is known that two different proteins with similar molecular weights, defined as molecular mimicry, may trigger cross-immunity.40–43 Therefore, due to the similar molecular weights of spike protein of SARS-COV-2 and actin-myosin, the antibodies may attack latter proteins in myocardial cells as well, resulting in development of myocarditis eventually. Moreover, studies also revealed that BNT162b1 consisted of highly purified ss-5-capped mRNA, and mRNA-1273 consisted of synthesis of ss-5-capped mRNA. The capability of spike protein production was reported higher in BNT162b1 than mRNA-1273.44,45 Furthermore, previous studies have also reported myocarditis in patients with COVID-19; however, the evidence of whether the myocarditis was caused by the direct infection or the systematic inflammation is not clear.46 On the other hand, a study found that COVID-19 patients with myocarditis showed no signs of injury in electrocardiography and echocardiography, indicating that myocardial damage was a result of systemic inflammation and not direct infection.47 This possible mechanism might explain the findings of our study, which indicate that the immunization with BNT162b1 had higher risk of developing myocarditis compared to other mRNA-based COVID-19 vaccines.\n\nOur study is the first networking meta-analysis to report the prevalence rate and risk of myocarditis after mRNA-based COVID-19 vaccination. We revealed that immunization with BNT162b1 had the highest prevalence rate and risk of developing myocarditis compared to other mRNA-based COVID-19 vaccinations. Our findings may contribute to the development of a COVID-19 immunization policy. If an mRNA-based COVID-19 vaccine needs to be selected, we recommended the use of mRNA-1273 or the combination of mRNA-1273 and BNT162b1 over the use of BNT162b1 alone. Further investigations are required to assess the specific mechanism underlying association of BNT162b1 vaccine with high-risk of myocarditis compared to other mRNA-based COVID-19 vaccines. On the other hand, the knowledge of patients on the side effect of mRNA COVID-19 vaccination should be investigated to assess the willingness for COVID-19 vaccination.48–51\n\nOur study had several important limitations. First, the potential confounding factors that might contribute to the development of myocarditis (e.g., infection due to common causative agents such as Coxsackie virus, group A streptococci, chlamydia, or Trypanosoma cruzi) were not included in the analysis.52 Second, the small prevalence of myocarditis after mRNA-based COVID-19 vaccination impeded the calculation of the precise prevalence and risk association. Third, the design of the included papers in our study was dominated by a retrospective study; therefore, further investigations with better study designs are required. Fourth, the proportion of myocarditis cases in each study was unequal. Fifth, the majority of papers in our analysis assessed BNT163b1 and the number of papers assessing mRNA-1273 was insufficient. Therefore, there is a possibility that calculation bias would have existed.\n\n\nConclusions\n\nOur study revealed that the prevalence of myocarditis after mRNA-based COVID-19 vaccination was 1.7 cases per 100,000 population, and BNT162b1 was associated with the highest prevalence rate compared to other mRNA-based COVID-19 vaccines. BNT162B1 vaccination is also associated with a higher risk of myocarditis than other mRNA-based COVID-19 vaccines. Based on these results, we recommend the use of mRNA-1273 vaccine over the BNT162B1 vaccine.\n\n\nData availability\n\nFigshare: Supplementary files: The global prevalence and association between the risk of myocarditis and mRNA-based COVID-19 vaccination: A network meta-analysis, https://doi.org/10.6084/m9.figshare.19768498.v2.31\n\n\nReporting guidelines\n\nFigshare: PRISMA checklist for “The global prevalence and association between the risk of myocarditis and mRNA-based COVID-19 vaccination: A network meta-analysis”, https://doi.org/10.6084/m9.figshare.19768498.v2.31\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nAuthor contribution\n\nIdea/concept: MSR, JKF. Design: MSR, GS, JKF, LW. Control/supervision: MSR, GS, LW, MA, KD, HH. Data collection/processing: MI, DM, YP, APK, AA, DA, AP, EAP, HAM, YP, DA, PWMP, VAS, DS, ENP, ETF, OLP, RS, RY, KH, YSP, LN, LL, MDC, MI, II, ADS, FT, DAK, AIM. Extraction/Analysis/interpretation: JKF, MI. Literature review: MSR, JKF, MI. Writing the article: MSR, JKF, MI. Critical review: MSR, GS, LW, MA, KD, HH. All authors have critically reviewed and approved the final draft and are responsible for the content and similarity index of the manuscript.", "appendix": "Acknowledgements\n\nWe thank Lembaga Pengelola Dana Pendidikan (LPDP) Republic of Indonesia for supporting this project.\n\n\nReferences\n\nBagcchi S: The world's largest COVID-19 vaccination campaign. Lancet Infect. Dis. 2021; 21: 323. PubMed Abstract \| Publisher Full Text\n\nKaur SP, Gupta V: COVID-19 Vaccine: A comprehensive status report. Virus Res. 2020; 288: 198114. PubMed Abstract \| Publisher Full Text\n\nBaud D, Qi X, Nielsen-Saines K, et al.: Real estimates of mortality following COVID-19 infection. Lancet Infect. Dis. 2020; 20: 773. PubMed Abstract \| Publisher Full Text\n\nSingh JA, Upshur REG: The granting of emergency use designation to COVID-19 candidate vaccines: implications for COVID-19 vaccine trials. Lancet Infect. Dis. 2021; 21: e103–e109. PubMed Abstract \| Publisher Full Text\n\nMenni C, Klaser K, May A, et al.: Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID Symptom Study app in the UK: a prospective observational study. Lancet Infect. Dis. 2021; 21: 939–949. PubMed Abstract \| Publisher Full Text\n\nRiad A, Hockova B, Kantorova L, et al.: Side Effects of mRNA-Based COVID-19 Vaccine: Nationwide Phase IV Study among Healthcare Workers in Slovakia. Pharmaceuticals (Basel). 2021; 14. PubMed Abstract \| Publisher Full Text\n\nChaudhary N, Weissman D, Whitehead KA: mRNA vaccines for infectious diseases: principles, delivery and clinical translation. Nat. Rev. Drug Discov. 2021; 20: 817–838. PubMed Abstract \| Publisher Full Text\n\nAlberer M, Gnad-Vogt U, Hong HS, et al.: Safety and immunogenicity of a mRNA rabies vaccine in healthy adults: an open-label, non-randomised, prospective, first-in-human phase 1 clinical trial. Lancet. 2017; 390: 1511–1520. PubMed Abstract \| Publisher Full Text\n\nAlamer E, Alhazmi A, Qasir NA, et al.: Side Effects of COVID-19 Pfizer-BioNTech mRNA Vaccine in Children Aged 12-18 Years in Saudi Arabia. Vaccines (Basel). 2021; 9. Publisher Full Text\n\nBarda N, Dagan N, Ben-Shlomo Y, et al.: Safety of the BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Setting. N. Engl. J. Med. 2021; 385: 1078–1090. PubMed Abstract \| Publisher Full Text\n\nKuhl U, Schultheiss HP: Myocarditis: early biopsy allows for tailored regenerative treatment. Dtsch. Arztebl. Int. 2012; 109: 361–368. PubMed Abstract \| Publisher Full Text\n\nAbu Mouch S, Roguin A, Hellou E, et al.: Myocarditis following COVID-19 mRNA vaccination. Vaccine. 2021; 39: 3790–3793. PubMed Abstract \| Publisher Full Text\n\nHabib MB, Hamamyh T, Elyas A, et al.: Acute myocarditis following administration of BNT162b2 vaccine. IDCases. 2021; 25: e01197. PubMed Abstract \| Publisher Full Text\n\nDeb A, Abdelmalek J, Iwuji K, et al.: Acute Myocardial Injury Following COVID-19 Vaccination: A Case Report and Review of Current Evidence from Vaccine Adverse Events Reporting System Database. J. Prim. Care Community Health. 2021; 12: 21501327211029230.\n\nRosner CM, Genovese L, Tehrani BN, et al.: Myocarditis Temporally Associated With COVID-19 Vaccination. Circulation. 2021; 144: 502–505. PubMed Abstract \| Publisher Full Text\n\nChoe YJ, Yi S, Hwang I, et al.: Safety and effectiveness of BNT162b2 mRNA Covid-19 vaccine in adolescents. Vaccine. 2021.\n\nDiaz GA, Parsons GT, Gering SK, et al.: Myocarditis and Pericarditis After Vaccination for COVID-19. JAMA. 2021; 326: 1210–1212. PubMed Abstract \| Publisher Full Text\n\nFarahmand R, Trottier CA, Kannam JP, et al.: Incidence of Myopericarditis and Myocardial Injury in Coronavirus Disease 2019 Vaccinated Subjects. Am. J. Cardiol. 2022; 164: 123–130. Publisher Full Text\n\nGurdasani D, Bhatt S, Costello A, et al.: Vaccinating adolescents against SARS-CoV-2 in England: a risk-benefit analysis. J. R. Soc. Med. 2021; 114: 513–524. PubMed Abstract \| Publisher Full Text\n\nHause AM, Gee J, Baggs J, et al.: COVID-19 Vaccine Safety in Adolescents Aged 12-17 Years - United States, December 14, 2020-July 16, 2021. MMWR Morb. Mortal. Wkly Rep. 2021; 70: 1053–1058. PubMed Abstract \| Publisher Full Text\n\nHusby A, Hansen JV, Fosbol E, et al.: SARS-CoV-2 vaccination and myocarditis or myopericarditis: population based cohort study. BMJ. 2021; 375: e068665. Publisher Full Text\n\nKim HW, Jenista ER, Wendell DC, et al.: Patients With Acute Myocarditis Following mRNA COVID-19 Vaccination. JAMA Cardiol. 2021; 6: 1196–1201. PubMed Abstract \| Publisher Full Text\n\nMevorach D, Anis E, Cedar N, et al.: Myocarditis after BNT162b2 mRNA Vaccine against Covid-19 in Israel. N. Engl. J. Med. 2021; 385: 2140–2149. PubMed Abstract \| Publisher Full Text\n\nMontgomery J, Ryan M, Engler R, et al.: Myocarditis Following Immunization With mRNA COVID-19 Vaccines in Members of the US Military. JAMA Cardiol. 2021; 6: 1202–1206. PubMed Abstract \| Publisher Full Text\n\nNygaard U, Holm M, Bohnstedt C, et al.: Population-based Incidence of Myopericarditis After COVID-19 Vaccination in Danish Adolescents. Pediatr. Infect. Dis. J. 2022; 41: e25–e28. PubMed Abstract \| Publisher Full Text\n\nPerez Y, Levy ER, Joshi AY, et al.: Myocarditis Following COVID-19 mRNA Vaccine: A Case Series and Incidence Rate Determination. Clin. Infect. Dis. 2021. Publisher Full Text\n\nSimone A, Herald J, Chen A, et al.: Acute Myocarditis Following COVID-19 mRNA Vaccination in Adults Aged 18 Years or Older. JAMA Intern. Med. 2021; 181: 1668–1670. PubMed Abstract \| Publisher Full Text\n\nSingh A, Khillan R, Mishra Y, et al.: The safety profile of COVID-19 vaccinations in the United States. Am. J. Infect. Control. 2022; 50: 15–19. PubMed Abstract \| Publisher Full Text\n\nWitberg G, Barda N, Hoss S, et al.: Myocarditis after Covid-19 Vaccination in a Large Health Care Organization. N. Engl. J. Med. 2021; 385: 2132–2139. PubMed Abstract \| Publisher Full Text\n\nPage MJ, McKenzie JE, Bossuyt PM, et al.: The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021; 372: n71. Publisher Full Text\n\nFajar J: Supplementary files: The global prevalence and association between the risk of myocarditis and mRNA-based COVID-19 vaccination: A network meta-analysis. Figshare. 2022; 1: 1. Publisher Full Text\n\nStang A: Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur. J. Epidemiol. 2010; 25: 603–605. PubMed Abstract \| Publisher Full Text\n\nFazlollahi A, Zahmatyar M, Noori M, et al.: Cardiac complications following mRNA COVID-19 vaccines: A systematic review of case reports and case series. Rev. Med. Virol. 2021; e2318. PubMed Abstract \| Publisher Full Text\n\nMatta A, Kunadharaju R, Osman M, et al.: Clinical Presentation and Outcomes of Myocarditis Post mRNA Vaccination: A Meta-Analysis and Systematic Review. Cureus. 2021; 13: e19240. Publisher Full Text\n\nWang M, Wen W, Zhou M, et al.: Meta-Analysis of Risk of Myocarditis After Messenger RNA COVID-19 Vaccine. Am. J. Cardiol. 2022; 167: 155–157. Publisher Full Text\n\nCordero A, Cazorla D, Escribano D, et al.: Myocarditis after RNA-based vaccines for coronavirus. Int. J. Cardiol. 2022; 353: 131–134. PubMed Abstract \| Publisher Full Text\n\nAnand P, Stahel VP: Review the safety of Covid-19 mRNA vaccines: a review. Patient Saf. Surg. 2021; 15: 20. PubMed Abstract \| Publisher Full Text\n\nHuang Y, Yang C, Xu XF, et al.: Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19. Acta Pharmacol. Sin. 2020; 41: 1141–1149. PubMed Abstract \| Publisher Full Text\n\nGovindan S, Sarkey J, Ji X, et al.: Pathogenic properties of the N-terminal region of cardiac myosin binding protein-C in vitro. J. Muscle Res. Cell Motil. 2012; 33: 17–30. PubMed Abstract \| Publisher Full Text\n\nCusick MF, Libbey JE, Fujinami RS: Molecular mimicry as a mechanism of autoimmune disease. Clin. Rev. Allergy Immunol. 2012; 42: 102–111. PubMed Abstract \| Publisher Full Text\n\nMahendra AI, Fajar JK, Harapan H, et al.: Porphyromonas gingivalis vesicles reduce MDA-LDL levels and aortic wall thickness in high fat diet induced atherosclerosis rats. Artery Res. 2018; 23: 20–27. Publisher Full Text\n\nWardhani SO, Fajar JK, Nurarifah N, et al.: The predictors of high titer of anti-SARS-CoV-2 antibody of convalescent plasma donors. Clin. Epidemiol. Glob. Health. 2021; 11: 100763. PubMed Abstract \| Publisher Full Text\n\nWardhani SO, Fajar JK, Wulandari L, et al.: Association between convalescent plasma and the risk of mortality among patients with COVID-19: a meta-analysis. F1000Res. 2021; 10: 64. PubMed Abstract \| Publisher Full Text\n\nFang E, Liu X, Li M, et al.: Advances in COVID-19 mRNA vaccine development. Signal Transduct. Target. Ther. 2022; 7: 94. PubMed Abstract \| Publisher Full Text\n\nPark JW, Lagniton PNP, Liu Y, et al.: mRNA vaccines for COVID-19: what, why and how. Int. J. Biol. Sci. 2021; 17: 1446–1460. PubMed Abstract \| Publisher Full Text\n\nLi B, Yang J, Zhao F, et al.: Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin. Res. Cardiol. 2020; 109: 531–538. PubMed Abstract \| Publisher Full Text\n\nDeng Q, Hu B, Zhang Y, et al.: Suspected myocardial injury in patients with COVID-19: Evidence from front-line clinical observation in Wuhan, China. Int. J. Cardiol. 2020; 311: 116–121. PubMed Abstract \| Publisher Full Text\n\nHarapan H, Anwar S, Bustaman A, et al.: Community Willingness to Participate in a Dengue Study in Aceh Province, Indonesia. PLoS One. 2016; 11: e0159139. PubMed Abstract \| Publisher Full Text\n\nMudatsir M, Anwar S, Fajar JK, et al.: Willingness-to-pay for a hypothetical Ebola vaccine in Indonesia: A cross-sectional study in Aceh. F1000Res. 2019; 8: 1441. Publisher Full Text\n\nFajar JK, Harapan H: Socioeconomic and attitudinal variables associated with acceptance and willingness to pay towards dengue vaccine: a systematic review. Arch. Clin. Infect. Dis. 2017; 12. Publisher Full Text\n\nPrihatiningsih S, Fajar JK, Tamara F, et al.: Risk factors of tuberculosis infection among health care workers: A meta-analysis. Indian J. Tuberc. 2020; 67: 121–129. PubMed Abstract \| Publisher Full Text\n\nCooper LT Jr: Myocarditis. N. Engl. J. Med. 2009; 360: 1526–1538. PubMed Abstract \| Publisher Full Text" }	[ { "id": "305292", "date": "04 Oct 2024", "name": "Yen-Ching Lin", "expertise": [ "Reviewer Expertise Clinical medicine" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn the various articles discussing the relationship between Covid-19 mRNA vaccines and myocarditis, there is considerable heterogeneity in research methods. These differences include the methods of post-vaccine myocarditis surveillance in different countries (active or passive), whether medical records of cases have been re-examined, the diagnostic criteria for myocarditis, the duration post-vaccination during which adverse events are still considered related to the vaccination, and whether cases include pericarditis, among others. How did you address these issues to integrate the data and perform a meta-analysis? If the pooled data have high heterogeneity, the results of the meta-analysis may be distorted.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? Partly\n\nAre the conclusions drawn adequately supported by the results presented in the review? Partly\n\nIf this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable", "responses": [] } ]	1	https://f1000research.com/articles/11-862
https://f1000research.com/articles/10-840/v1	20 Aug 21	{ "type": "Research Article", "title": "Faculty readiness for online teaching at Imam Abdulrahman Bin Faisal University during the COVID-19 crisis: a cross-sectional study", "authors": [ "Muneerah B. Almahasheer", "Abdullah Al Rubaish", "Abdullah Alkadi", "Mahmoud A. Abdellatif", "Vijaya Ravinayagam", "Assaf, Wael Fateh", "Palanivel Rubavathi Marimuthu", "Nuhad A. Alomair", "Muneerah B. Almahasheer", "Abdullah Al Rubaish", "Abdullah Alkadi", "Mahmoud A. Abdellatif", "Vijaya Ravinayagam", "Assaf, Wael Fateh", "Palanivel Rubavathi Marimuthu" ], "abstract": "Background: The outbreak of the COVID-19 pandemic has affected the education sector around the world. In order to control the spread of the virus, eLearning practice has been introduced in Saudi higher education. Such online communication has become an important tool to narrow the teaching practice gap. This study assessed the characteristics of eLearning and distance learning and the inclination of Imam Abdulrahman BinFaisal University (IAU) faculty members in terms of skills, and managing classes and tests using online learning tools.\nMethods: A QuestionPro questionnaire with 22 questions on eLearning experience, training experience, and skills and knowledge in the educational process of IAU teaching faculty was conducted through the online university e-mail domain. The questionnaire was sent to the IAU’s teaching faculty. The questionnaire’s reliability was studied using Cronbach’s α coefficient. The criterion value was statistically studied using the KMO (Kaiser-Meyer-Olkin) and Bartlett’s test. The variables associated with the present survey model were analysed using Structural Equation Modelling (SEM).\nResults: The study showed positive responses and readiness (skills and abilities) and the effectiveness of IAU’s faculty members to perform e-learning activities during COVID-19. IAU faculty received a strong positive response, and the respondents were also impressed with and agreed on trainer knowledge, session management, communication and expertise on training topics.\nConclusions: The positive response indicates the readiness of IAU to provide the necessary support (tools, information and updates) required for a successful online educational process.", "keywords": [ "COVID-19", "Education", "Faculty readiness", "Administration", "Remote working." ], "content": "Introduction\n\nCoronavirus disease 2019 (COVID-19) derived from a mutated zoonotic virus tends to cause respiratory infections with variable severity (Tay et al., 2020). The pandemic disease initially started in Wuhan city, China and then spread severely, affecting Western countries. The infection rate and number of deaths are increasing at alarming rates around the globe. The main source of this rapid spread is attributed to the infection and replication ability of the virus in the upper respiratory tract without any symptoms. In the case of a single cough or sneeze, millions of microdroplets containing the virus are generated. COVID-19 has infected approximately 16 million people and caused the death of approximately 600,000 individuals worldwide. The global economic losses due to forced lockdowns around the globe to contain the spread of the virus have been estimated to be 9 trillion US dollars. In the U.S., more than 4 million people have been infected; and in the Kingdom of Saudi Arabia (KSA), the cases of infection and deaths are increasing steadily. The transmission rate from infected people was found to be higher than that of the influenza virus with reproductive numbers between 1.4 and 2.5. In the KSA, to date (08.04.21), the total number of cases is 394,952 with 6,719 deaths and 381,189 recoveries (https://www.worldometers.info/coronavirus/).\n\nTo contain the spread of this viral infection, strict social distancing, quarantine and rapid testing are suggested to control the COVID-19 crisis (Giordano et al., 2020). Inadvertently, the important role of information technology has been felt in higher education (Ayers, 2004; Carr-Chellman & Duchastel, 2000). Saudi Arabia has initiated several measures to actively control and manage the virus. In order to fight against COVID-19, as per Saudi government instructions, the Ministry of Education has taken several actions without affecting the quality of the education system.\n\nImam Abdulrahman Bin Faisal University (IAU) is a leading university promoting academic and advanced scientific research in the Eastern Region. IAU has various graduate courses and branches. The university started with the College of Medicine and College of Architecture and provides strong health care services through the establishment of King Fahd University Hospital. The IAU campus and its 21 colleges spread across various places of the Eastern Province with student enrolment is currently approximately 45,000 students. In order to control the spread of COVID-19, the KSA suspended all onsite activities of universities and initiated digital-based distance learning and remote working strategies. Based on the World Health Organization and Ministry of Health guidance, certain orders were issued such as staying home, working from home, being safe, and maintaining good hygiene. In the case when going out is a necessity, social distancing (2 m) should be maintained. The sudden health crisis affected the educational sectors and inflicted a long-term financial revision state pertaining to online education.\n\nWeb-based advanced learning tools for online teaching have long been considered a prime importance for student coaching (Beaudoin, 1990; Beaudoin 1998; Cohn, 2002; Zhang et al., 2020). Therefore, in response to government mandated quarantine and remote working, IAU swiftly moved to online teaching (March, 2020). Fortunately, various technological updated measures have already been recommended based on the KSA’s Vision 2030 (https://ndu.gov.sa/en/). Accordingly, several technological readiness measurements have been implemented by IAU. The advancement of the digital age with computer-based information technology was well realized, leading to the establishment of the Deanship of E-Learning and Distance Learning in 2010. Since then, the evolution of the eLearning processes of universities worldwide has been constantly upgraded and developed for teaching, distance learning programmes, training and services (Dhawan, 2020). The IAU’s mission to integrate such digital technology aims to provide effective eLearning teaching, provide distance learning services and deliver support in e-courses. The goal is to provide an e-learning platform to on- and off-campus students and expand the technology from universities to integrate regions and spread across the KSA.\n\nCurrently, the digital platform that IAU uses is the Blackboard eLearning management system. The Deanship of E-Learning and Distant Learning lab at IAU is integrated with advanced high-performance IOS computers (Mac), Windows, platforms, visual viewers, studios, and soundproof capsules (to view and recording services). The presence of a digital lab enables interactive sessions, displays, video meetings, lectures, workshops, training sessions, uploading data in the Blackboard system and recording. IAU has advanced eLearning digital management facilities.\n\nThe aim of this study was to analyse the significant role of the digital system and evaluate the readiness of IAU faculty members to transition to online teaching during COVID-19 using survey-based methods.\n\n\nMethods\n\nThe questionnaire was intended to study the level of eLearning experience among the faculty members of IAU. Considering the abrupt changes in teaching mode during this pandemic situation, a questionnaire could effectively predict the characteristics and management of the advantages of e-learning by faculty members. The study was conducted from 8th March to 12th March 2020.\n\nThe study was approved by the Institutional Review Board (Standing Committee for Research Ethics on Living Creatures) with reference no. IRB-2020-17-148). Completion of the questionnaire by faculty members was taken as consent to participate.\n\nThis study was conducted at Imam Abdulrahman Bin Faisal University (IAU), which is located in the Eastern Region of Saudi Arabia. All faculty members (N=2227) of IAU who were involved in online teaching during the COVID-19 crisis in the 2019–2020 academic year were considered the population of this study, as only these faculty members used and experienced IAU e-learning facilities. Access to QuestionPro by external (non-IAU) persons was prohibited; therefore, only IAU teaching faculty were included. Nonteaching staff/faculty of IAU were excluded. In order to address potential sources of bias, the population of this study only included faculty members.\n\nA QuestionPro questionnaire with 22 questions on eLearning experience, training experience and skills and knowledge in the educational process of IAU faculty was implemented. Questionnaire was sent to participants using their university e-mail with a link to the questionnaire. The faculty members had to use their university email and password to log into the questionnaire via Blackboard dashboard. A specified time duration of 14 days to respond to the questionnaire was given to potential respondents. Two follow-up emails were sent that included reminders regarding answering the questionnaire.\n\nThe questionnaire was created through four brainstorming meetings with higher education experts and faculty members.\n\nThree sections were included in the questionnaire, which aimed to evaluate: (section 1) the overall eLearning experience using Blackboard; (section 2) the skills and training provided to IAU faculty members to use eLearning; and (section 3) the management of classes and tests using the online learning tools. Section 1 had 8 items, section 2 had 9 items and section 3 had 4 items (total 21 items). The last item (22) was ‘How satisfied are you with our services’. Each item was a statement, and the answers respondents could choose from were as follows: strongly agree (marked as 1 in the data), agree (2), true sometimes (3), disagree (4), and strongly disagree (5).\n\nDescriptive statistics were applied to reveal the level of eLearning experience among the faculty members of IAU. The internal consistency of the questionnaire was assessed using Cronbach’s alpha reliability test. Confirmatory factor analysis (CFA) with the principal component method was used to determine the construct validity of the questionnaire used. Furthermore, structural equation modelling (SEM) analysis was conducted using the AMOS (Analysis of Moment Structures) software 2020 to study the adequacy of the e-learning variables involved in the questionnaire. Pearson’s correlation was also used to examine the relationship between the e-learning variables and the faculty’s overall satisfaction. Besides, the effect of e-learning variables on the faculty’s overall satisfaction was evaluated using multiple regression analysis. All statistical analyses were conducted using SPSS version 22.0 at a 5% significance level. Pearson’s correlation was also used to examine the relationship between the e-learning subgroups and interactions. There were no missing data to address in this study.\n\n\nResults\n\nOut of the 2227 potential responses, 634 completed responses were received (response rate, 28.5%).\n\nCronbach’s alpha was used as a benchmark to study the reliability of the questionnaire (Schakib-Ekbatan et al., 2019). The reliability value of Cronbach’s α coefficient ranges from 0.00–1.00. In the present study, the reliability of the statistics on the eLearning questionnaire using Cronbach’s α coefficient was found to be 0.940. This indicates that the questionnaire achieved a reliable standard of high consistency.\n\nFaculty’s perception of eLearning variables could be graded as ‘‘Good’’ (mean, 89.15; variance, 153.168; std. dev., 12.376). Cronbach’s alpha for each section was as follows: section 1 (evaluation of overall e-learning experience), 0.874; section 2 (training received), 0.940; and section 3(applying skills and knowledge in the educational process through eLearning), 0.872.\n\nEFA on the 21-item questionnaire was 0.943, with a significance level of 0.000 with Bartlett’s test. The dimensionality of the instrument was analysed using CFA. KMO value (KMO=0.943) and Bartlett’s test of sphericity (value=10061.978, p<0.05) demonstrated that the raw data were suitable for the application of factor analysis (Table 1).\n\nThe common communalities of the instrument used are presented in Table 2; all the items had a value greater than 0.50, which indicated that the quality of the measurement was satisfactory.\n\nTable 3 shows the percentage of responses for each statement. The faculty’s perception of the quality of eLearning experience at IAU was found to be high (Table 4). A positive correlation existed between the eLearning variables that indicate an overall satisfaction with the provided services (Table 5). The results of the factor loadings on the eLearning scale showed that all items had values greater than 0.5, which indicated that the survey’s quality was satisfactory (Table 6).\n\n** Correlation is significant at the 0.01 level (2-tailed)\n\nIn this study, SEM analysis resulted in the model depicted in Figure 1, and the following characteristics: n=634, df=184, chi-squared=966.286, and p=0.000 (<0.05). Therefore, it is concluded that the proposed SEM model used in this study adequately fits the sample data representing IAU faculty members. The results of the relationship between each item and the proposed three dimensions show that the path coefficient between each item and the proposed 21-item questionnaire is positive and significant (p-value<0.05). The results show that there is a positive significant relationship between each item and the proposed three dimensions ranging from 0.290 to 1.339, which is given in Table 7. In this study, the Normed Fit Index (NFI), Relative Fit Index (RFI), Incremental Fit Index (IFI), Tucker-Lewis Index (TLI) and Comparative Fit Index (CFI) values of 0.905, 0.892, 0.922, 0.911, and 0.922, respectively, were highly consistent, suggesting that the proposed model represented an adequate fit to the data (Table 8). The CFI=1 (>0.082) (Table 4) and the Root Mean Square Error of Approximation (RMSEA) for the proposed model are equal to 0.0001 (p-value<0.05) (Table 9–Table 11), which indicates that the model has a good fit. This finding is supported by a study by Bryne (2009), which stated that the NFI, RFI, IFI, TLI and CFI range from 0 to 1, with values closer to 1 being indicative of a good fit. In conclusion, SEM analysis showed that the items observed under the proposed four dimensions are acceptable to measure the experience of eLearning working by IAU faculty members during the COVID-19 outbreak.\n\nNote: Significant at the 0.05 level\n\nSignificant at the 0.05 level\n\n\nDiscussion\n\nIAU promotes leadership qualities, encourages and supports high-end basic and applied research activities (medicine, arts and sciences, and computing), and enhances researcher skills with state-of-the-art facilities. IAU has students and faculty members from different cities and regions. During onsite/traditional classes, the chance for infection and spread is high among students due to mingling. The online management and workload assessment of faculty are critical for strategic balance (Conceição & Lehman, 2011; Davies et al., 2005). This study was conducted to evaluate eLearning variables from the perspective of IAU faculty members using a questionnaire. The questionnaire’s reliability was studied using Cronbach’s α coefficient. The criterion value was statistically studied with KMO (Kaiser-Meyer-Olkin) and Bartlett’s test. The results indicated that all the items had a value greater than 0.50, which indicated that the quality of the measurement was satisfactory.\n\nIn the first section of the questionnaire, the eLearning experience of faculty was evaluated. The faculty members were asked about their experience using Blackboard, training, and applying their learned skills and knowledge through eLearning. Bower et al. (2001) stated that online distance education requires effective training sessions and a change in the pedagogical approach. In addition, such a web-based teaching approach requires certain preassessment measures to ensure the validity and results (Buchanan, 1999; Carnevale, 2004; Schifter, 2000a; Schifter, 2000b). Our results show a unanimous level of satisfaction of faculty members using the Blackboard eLearning tool. In the first instance, the ease of using Blackboard received mostly positive responses of ‘strongly agree’ (50.3%) and ‘agree’ (38.7%), indicating a higher proportion of faculty members with a strong commitment to the online working mode of action. Broadcasting and recording lectures via Zoom using Blackboard received mostly ‘strongly agree’ (59.3%) and ‘agree’ (33.4%) responses. Very few responded ‘true sometimes’ (6.2%), ‘disagree’ (1.1%) and ‘totally disagree’ (0.0%). The positive responses of respondents indicate the ease of using the Blackboard platform to provide course lessons using menu items and conducting Zoom classes with students through built content options. In the case of Blackboard collaboration (virtual classroom), the ‘true sometimes’ (32.5%) responses increased, similar to the ‘strongly agree’ (33.1%) and ‘agree’ (30.8%) responses. Impressively, the disagreement response still has a lower proportion (<4%). An increase in ‘true sometimes’ indicates that respondents have some reluctance or reservation of using Blackboard as a video tutoring platform. Conducting online tests using this software was found to be easier as most respondents positively agreed (58.5%). In total, 26.8% of respondents answered ‘true sometimes’ while few disagreed (11.2%) and strongly disagreed (3.5%). Faculty members expressed positive agreement and strong satisfaction with the provided technical support (strongly agree, 49.8%; agree, 34.5%). Less than 4% expressed disagreement, while 12% responded ‘true sometimes’. Furthermore, stronger agreement was given by faculty members for the easy contact, responses and services provided by technical support assistance.\n\nThe second section of the questionnaire was related to the experience of the training received. Cho & Berge (2002) reported that a major barrier in distance training is administrative, technical experts and the infrastructure system. However, in the present study, a strong positive response was given to training experience. Respondents were also impressed and agreed on the trainer’s knowledge expertise on training topics. Strong affirmative statements were recorded for the trainer’s session management and the way they handled participants’ questions. Similarly, the trainer’s ability to communicate with trainees and the level of discussion received strong positive responses. Training experience using the Zoom platform, training time and training materials received positive responses. For the overall training sessions, approximately 7–15% of respondents expressed the statement of ‘true sometimes’ while very few provided negative responses.\n\nThe third section of the questionnaire was related to the application of skills and knowledge in the educational process through eLearning at IAU. Substantial positive responses with 47.3% of respondents answering ‘strongly agree’ and 42.7% answering ‘agree’ indicated that the organized training was consistent with faculty’s job goals. Similarly, the faculty revealed that they were able to apply the learned experience during their educational process (agreement of 43.7% and 43.8%, respectively). A high percentage of respondents agreed that training also contributed to developing specific skills that can boost their success in the workplace and accepted that they would also promote this training course to their colleagues. Overall, the faculty members expressed satisfaction with the provided Blackboard service.\n\nThe level of perception of faculty members with respect to eLearning experience at IAU was found to be impressively high with a mean score higher than 4 (Table 4). A positive correlation exists between eLearning variables that indicates an overall satisfaction with the provided services (Table 5). The results of the factor loadings on the eLearning scale showed that all items had values greater than 0.5, which indicated that the survey’s result quality was satisfactory (Table 6). The observed positive results of eLearning experience can be correlated to several IAU training initiatives offered to faculty members through the Deanship of Academic Development (DAD). Key training program approaches to online classes are classified into short training programmes, intensive training programmes and material resource support. The professional development training programme involves improving competency in teaching/learning, lecture preparations and mentorship training programmes. Training topics are based on assessment, surveys, reports to the Deanship of Quality and Accreditation (DQAA), student course evaluations, faculty, academic program evaluations, benchmarking teaching and learning practices, trainer questionnaires, and DAD forum recommendations. In addition, the training content materials were updated in the training portal on Blackboard and IAU website (DAD, 2020).\n\nMainly, the key strategy points focus on faculty online communication skills, leadership skills, conceptual thinking, learning as a team, teaching in a creative way, interpersonal student communication skills, deep learning, lecture planning, an artistic teaching approach and class management.\n\nA faculty professional development series was conducted by IAU. The topics was related on utilizing educational technology and teaching methods. The framework includes theoretical backed interactive sessions, using technological tools to improve student engagement, motivating the students by improving the learning environment and intellectual concept activities, improving competency and fluency in English, microteaching (teaching through practice), metacognition (higher-order thinking), effective questioning strategies, avoiding common teaching mistakes, flipped classrooms (instructional strategy), knowing students’ learning styles and welcoming students on the first day of class.\n\nThe professional training for faculty also includes improving effective assessment and evaluation skills. The module covers the different types of concepts, methods, types and concepts based on assessment. Increasing questioning, thinking skills, teaching strategies and question paper setting tend to improve higher-order thinking capabilities. Faculty members are guided to use performance-based assessment and portfolios; improve the capability of analysing test results; establish question items to motivate higher-order thinking; assess project work and lab-based learning; and improve soft skills such as emotional intelligence, team-based work, interactions, metacognition skills and leadership. Furthermore, faculty members are trained on grading practices, effective rubrics and constructive feedback.\n\nImportantly, a survey finding by Bonk (2002) stated that faculty members should be trained for online teaching in the online world. Considering such recommendations, the development series focused on mentoring benefits, improving oral communications, and 21st century skills (collaboration, critical thinking, communications, creativity, and emotional intelligence) in higher education. Training includes assessing new learning and teaching strategies, similar to the COVID-19 pandemic situation; and how to publish in journals related to education. The module comprises observation of classroom behaviours and interactions and the promotion of learning through activities. Faculty members were taught strategies for formulating key principles of critical thinking and student engagement. The adult learning concept and principles were taught to be applied in knowledge transfer from classroom to actual work settings, as seen in the current pandemic situation. The concept of self-efficacy from the perspective of faculty and department was the focus. Similarly, preventing faculty burnout during adverse situations such as COVID-19 and different strategies to overcome faculty burnout are taught.\n\nSEM was used to evaluate the experience of eLearning at IAU. This model has been effectively used to analyse the structural variables in educational-based research (Jansson et al., 2019). Based on the survey study, a model was constructed using SEM analysis (Figure 1). The SEM study showed that items studied under the proposed three dimensions are acceptable for measuring the eLearning experience of IAU faculty members during the COVID-19 pandemic. Overall, the modules were found to be effective in the present situation and able to continue the practice of teaching and learning in the online mode of action. The expressed eLearning satisfaction level by faculty and online trainings adopted by IAU can be an effective strategy to combat online teaching challenges.\n\n\nConclusion\n\nThe COVID-19 pandemic presents an unprecedented challenge in higher education. This study explored faculty readiness for online teaching during the COVID-19 crisis at IAU. The survey responses by the faculty indicate their high satisfaction using eLearning tools. The Blackboard online teaching software tool, recording lectures using the Zoom platform, virtual classrooms and online tests received strong positive responses. Faculty responded positively to the technical and training support rendered by IAU. Overall, the study found that the eLearning training and modules provided by IAU were effective in the present pandemic situation.\n\n\nData availability\n\nFigshare: E-learning datasheet of Faculty readiness for online teaching at Imam Abdulrahman Bin Faisal University during the COVID-19 crisis: a cross-sectional study, https://doi.org/10.6084/m9.figshare.14406434 (Almahasheer et al., 2021).\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nAlmahasheer MB, Al-Rubaish AM, Alkadi A, et al.: Faculty readiness for online teaching at Imam Abdulrahman Bin Faisal University during the COVID-19 crisis: a cross-sectional study. figshare. Dataset. 2021. http://www.doi.org/10.6084/m9.figshare.14406434.v1\n\nAyers EL: The Academic Culture and the IT Culture: Their Effect on Teaching and Scholarship. EDUCAUSE. 2004; 39: 48–2. Reference Source\n\nBeaudoin M: The Instructor’s Changing Role in Distance Education. The American Journal on Distance Education. 1990; 4(2): 21–9. Reference Source\n\nBeaudoin M: A New Professoriate for the New Millennium. Deosnews. 1998; 8(5). Reference Source\n\nBonk CJ: Online Teaching in an Online World” Education at a Glance: United States Distance Learning Association (USDLA). Journal. 2002; 16(1).\n\nBower BL: Distance Education: Facing the Faculty Challenge. IV(II), Summer 2001 State University of West Georgia, Distance Education enter. 2001. Reference Source\n\nBryne BM: Structural equation modeling with AMOS basic concepts, applications, and programming. 2nded New York, NY: Taylor and Francis Group; 2009. Reference Source\n\nBuchanan EA: Assessment Measures: Pre-Test for Successful Distance Teaching and Learning? Online Journal of Distance Learning Administration. Winter 1999 State University of West Georgia, Distance Education Center. 1999; 2(4). Reference Source\n\nCarnevale D: Professors Seek Compensation for Online Courses. Chronicle of Higher Education: Information Technology. 2004; 50(49): A27. Reference Source\n\nCarr-Chellman A, Duchaste lP: The Ideal Online Course. British Journal of Educational Technology. 2000; 31. Reference Source\n\nCho SK, Berge ZL: Overcoming Barriers to Distance Training and Education. EModerators. Journal. 2002; 16(1). Reference Source\n\nCohn ER: Instant Messaging in Higher Education: A New Faculty Development Challenge. Indiana University – Purdue University Fort Wayne online papers. 2002. Reference Source\n\nConceiçãoS CO, Lehman RM: Managing Online Instructor Workload: Strategies for Finding Balance and Success. San Francisco, 2011; CA: Jossey-Bass. Reference Source\n\nCuschieri S: The STROBE guidelines. Saudi J Anaesth. 2019; 13(Suppl 1): S31–S34. Publisher Full Text\n\nDavies A, Ramsay J, Lindfield H, et al.: Building learning communities: foundations for good practice. British Journal of Educational Technology. 2005; 36(4): 615–28. Publisher Full Text\n\nDAD: Training Content in Teaching and Learning. Deanship of Academic Development website, visited. 2020.\n\nDhawan S: Online Learning: A Panacea in the time of COVID-19 Crisis. Journal of Educational Technology. 2020; 49(1): 5–22. Publisher Full Text\n\nGiordano G, Blanchini F, Bruno R: Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy. Nat Med. 2020; 26(6): 855–860. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nJansson A, Sundblad GB, Lundvall S, et al.: Assessing Students’ Perceived Learning and Contentment in Physical Education: A Scale Development Study and Structural Equation Modeling Analysis. Measurement in Physical Education and Exercise Science. 2019; 23(1): 1–11. Publisher Full Text\n\nSchifter CC: Compensation Models in Distance Education. Online Journal of Distance Learning Administration, III(I), Spring 2000 State University of West Georgia, Distance Education Center. 2000a.\n\nSchifter CC: Faculty Participation in Asynchronous Learning Networks: a Case Study of Motivating and Inhibiting Factors. Journal of Asynchronous Learning Networks. 2000b; 4(1). Publisher Full Text\n\nSchakib-Ekbatan K, Lechner S, Schweiker M: Reliability of an Item Set Assessing Indoor Climate in Offices—Results From Field Studies and Laboratory Research Front. Built Environ. 2019; 5: 117. Publisher Full Text\n\nTay MZ, PohCMRénia L, et al.: The trinity of COVID-19: immunity,inflammation and intervention. Nat Rev Immunol. 2020; 20(6): 363–374. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nZhang W, Wang Y, Yang L, et al.: Suspending Classes Without Stopping Learning: China’s Education Emergency Management Policy in the COVID-19 Outbreak. J Risk Financial Manag. 2020; 13: 55. Publisher Full Text" }	[ { "id": "92444", "date": "04 Oct 2021", "name": "Shahul Hameed Pakkir Mohamed", "expertise": [ "Reviewer Expertise Musculoskeletal physical therapy" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nComments on: Faculty readiness for online teaching at IAU during the COVID-19 crisis.\nThe demographic details are missing in the table and in the interpretation of the results?\n\nIt is better to add a table relationship between demographic data (such as academic rank, age, years of teaching experience, attendance of training courses, etc...) of faculty members and their e-learning experience, received training information, and applied skills and knowledge?\n\nWhat type of sampling was used in this study?\n\nWhat are the challenges or barriers the faculty members at the IAU have met while using Blackboard?\n\nWhat are the limitations, suggestions, and recommendations in the study?\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "7563", "date": "21 Jan 2022", "name": "Nuhad Abdullah Alomair", "role": "Author Response", "response": "The demographic details are missing in the table and in the interpretation of the results? Response: The aim of the study is to analyse only the significant role of the digital system and evaluate the readiness of IAU faculty members to transition to online teaching during COVID-19 using survey-based methods. Hence, the authors have not collected the demographic data of the IAU faculty members. However, the authors stated that the demographic data of faculty members can be included in further research in the Limitations and Recommendations Section. Limitations and Recommendations This study is restricted to the faculty members of a single public university, and future work can be conducted with the enclosure of all Saudi universities. In further research, the demographic data of faculty members can be included. Further, the relationship between demographic variables of faculty members (such as age, gender, nationality, highest educational qualification, current designation, and work experience) and their e-learning experience, training, and applying skills and knowledge in the educational process through e-learning can be revealed in future studies. Besides, the difference in overall satisfaction among faculty members concerning their demographic variables can also be studied. It is suggested to study the influence of demographic variables on overall faculty satisfaction with the e-learning process at their respective universities. A qualitative or quantitative research can be further carried out with Saudi faculty members to reveal the challenges or barriers facing faculty members while using Blackboard. This study also recommends that higher education administrators frame and execute uniform regulations to improve teaching faculty’s satisfaction with Blackboard. It is better to add a table relationship between demographic data (such as academic rank, age, years of teaching experience, attendance of training courses, etc...) of faculty members and their e-learning experience, received training information, and applied skills and knowledge? Response: The aim of the study is to to analyse the significant role of the digital system and evaluate the readiness of IAU faculty members to transition to online teaching during COVID-19 using survey-based methods. Hence, the authors did not analyze the relationship between demographic data of faculty members and their e-learning experience, received training information, and applied skills and knowledge. However, the authors stated that the relationship between demographic data of faculty members and their e-learning experience, received training information, and applied skills and knowledge can be revealed in future studies in the Limitations and Recommendations Section. The description is provided as follows: Limitations and Recommendations This study is restricted to the faculty members of a single public university, and future work can be conducted with the enclosure of all Saudi universities. In further research, the demographic data of faculty members can be included. Further, the relationship between demographic variables of faculty members (such as age, gender, nationality, highest educational qualification, current designation, and work experience) and their e-learning experience, training, and applying skills and knowledge in the educational process through e-learning can be revealed in future studies. Besides, the difference in overall satisfaction among faculty members concerning their demographic variables can also be studied. It is suggested to study the influence of demographic variables on overall faculty satisfaction with the e-learning process at their respective universities. A qualitative or quantitative research can be further carried out with Saudi faculty members to reveal the challenges or barriers facing faculty members while using Blackboard. This study also recommends that higher education administrators frame and execute uniform regulations to improve teaching faculty’s satisfaction with Blackboard. What type of sampling was used in this study? Response: In this study, convenience sampling technique was applied. The description is provided in the Methods section as follows: Methods Participants This study was conducted at Imam Abdulrahman Bin Faisal University (IAU), which is located in the Eastern Region of Saudi Arabia. A convenience sampling was used in this study. All faculty members (N=2227) of IAU who were involved in online teaching during the COVID-19 crisis in the 2019–2020 academic year were considered the population of this study, as only these faculty members used and experienced IAU e-learning facilities. What are the challenges or barriers the faculty members at the IAU have met while using Blackboard? Response: The aim of the study is to analyse the significant role of the digital system and evaluate the readiness of IAU faculty members to transition to online teaching during COVID-19 using survey-based methods. Hence, the authors did not reveal the challenges or barriers the faculty members at the IAU have met while using Blackboard. This valuable point of the reviewer has been included in the Limitations and Recommendations Section for further research. The description is provided as follows: Limitations and Recommendations This study is restricted to the faculty members of a single public university, and future work can be conducted with the enclosure of all Saudi universities. In further research, the demographic data of faculty members can be included. Further, the relationship between demographic variables of faculty members (such as age, gender, nationality, highest educational qualification, current designation, and work experience) and their e-learning experience, training, and applying skills and knowledge in the educational process through e-learning can be revealed in future studies. Besides, the difference in overall satisfaction among faculty members concerning their demographic variables can also be studied. It is suggested to study the influence of demographic variables on overall faculty satisfaction with the e-learning process at their respective universities. A qualitative or quantitative research can be further carried out with Saudi faculty members to reveal the challenges or barriers facing faculty members while using Blackboard. This study also recommends that higher education administrators frame and execute uniform regulations to improve teaching faculty’s satisfaction with Blackboard. What are the limitations, suggestions, and recommendations in the study? Response: As advised, the authors have included the Limitations and Recommendations Section in the manuscript. The description provided in the manuscript is given below: Limitations and Recommendations This study is restricted to the faculty members of a single public university, and future work can be conducted with the enclosure of all Saudi universities. In further research, the demographic data of faculty members can be included. Further, the relationship between demographic variables of faculty members (such as age, gender, nationality, highest educational qualification, current designation, and work experience) and their e-learning experience, training, and applying skills and knowledge in the educational process through e-learning can be revealed in future studies. Besides, the difference in overall satisfaction among faculty members concerning their demographic variables can also be studied. It is suggested to study the influence of demographic variables on overall faculty satisfaction with the e-learning process at their respective universities. A qualitative or quantitative research can be further carried out with Saudi faculty members to reveal the challenges or barriers facing faculty members while using Blackboard. This study also recommends that higher education administrators frame and execute uniform regulations to improve teaching faculty’s satisfaction with Blackboard." } ] } ]	1	https://f1000research.com/articles/10-840
https://f1000research.com/articles/11-856/v1	28 Jul 22	{ "type": "Opinion Article", "title": "Five future concerns for women’s health", "authors": [ "Sophie Harman" ], "abstract": "The coronavirus disease 2019 (COVID-19) pandemic has brought the world’s attention to the gendered impacts of health emergencies of women. This offers a critical opportunity to advance our understanding of the gendered impacts of healthcare and to improve health outcomes for women around the world. However, to do so we need to be mindful of five future challenges: 1. the continued impact of COVID-19; 2. attacks on women’s health and the need for gender equality; 3. understanding women’s health needs everyday, not just during emergencies; 4. not seeing female leadership as a quick fix; and 5. holding global institutions to account.", "keywords": [ "Women's Health", "Gender", "COVID-19", "Politics" ], "content": "Introduction\n\nThe COVID-19 pandemic finally woke the world up to realising health emergencies had profound impacts on women because of gender norms and inequalities.1 Research into the myriad ways in which these impacts have been felt across politics, economics, and society is being produced across the globe.2 This research is feeding into evidence-based policy in newly formed or refreshed women and gender teams in leading global health organisations from the World Health Organisation to the Bill and Melinda Gates Foundation.3 Frameworks and guidelines as to how governments, the private sector, and international institutions can mainstream gender into their prevention and response plans are freely available to anyone who wants them.4\n\nShould another health emergency arise, we have the evidence to say how women will be affected, clear guidelines as to how to minimise the impact of emergencies on women, and crucially, an expectation that women are no longer an after-thought in, and that gendered inequalities cut across, pandemic preparedness and response. More than that, the impact of COVID-19 on women means gender is no longer an after-thought in thinking through all contemporary global health challenges in the world. A lens on how health issues affect people differently due to gender norms must be fundamental to how we deliver better health for all. However, knowing this and having the evidence of what to do is the easy bit. The tricky part is sustaining the effort. We have to be attentive to five concerns in 2022.\n\nThe world is divided between those who are vaccinated and those who are not. For those who are vaccinated, COVID-19 is something to be attentive to but thought of in the past tense. Those who are not vaccinated may similarly be keen to put the pandemic in the past, but without access to the greatest protection against the virus there is a huge inequality in who gets to move on. 5\n\nAn understandable focus on how to integrate a gender lens into future pandemic preparedness and post-pandemic recovery must be balanced against sustained interventions to ensure the world is vaccinated. Vaccines are a feminist issue.6 Access to vaccines draw on transnational feminist solidarity and ideas of equality across the world. Moreover, vaccine delivery and uptake rests on the army of labour of female health care workers across the world. Our first concern for the future of women’s health is therefore to ensure all women around the world are vaccinated against the world, and that the women doing the vaccination are free from violence at work.7\n\nWith every advance on women’s rights comes backlash.8 A growing prominence of women’s health needs and the gendered impacts of health emergencies and pandemics will similarly be met with backlash.9 This backlash may be insidious questions such as ‘what about men?’ or ‘why does everything have to be about women?’ or ‘what about race or class?’ These questions are rarely intended to focus on these important points and sources of inequality: they are always about silencing women and/or asking questions about gender.\n\nInsidious questions mark a deeper unease, and in some cases resistance to anything to do with gender. This can be because the term gender confuses people, and often people can be resistant to what they don’t understand. Understanding takes effort and in some cases makes you confront how you see things and live your life. This can also be a deliberate form of ‘strategic ignorance’10 in not wanting to understand for a political purpose.\n\nA more serious concern is a deliberate backlash against gender and so-called ‘gender ideology.’11 This has little to do with a misunderstanding or an unwillingness to engage. It is a direct attempt by politicians to seize the gender equality agenda to their own ends, while completely disregarding the power systems that make the lives of men, women, and non-binary people unequal. Critics of ‘gender ideology’ tend to sit on the populist right.12 They hold firm that gender is an affront to family values and traditional ways of life. This is a clear political tactic – it is used to appeal to the past and ‘tradition’ as a means of gaining votes in periods of uncertainty. However it has serious ramifications for women’s health. Where anti-gender ideology comes, repression against women’s sexual and reproductive health rights is sure to follow. We saw this in Poland, we saw this in Brazil, and we have now seen this in America with the overturning of Roe vs Wade.\n\nIf you have worked in women’s health in the last two years you may think everyone was on board with the pursuit of gender equality as a means of better health for all. You would be very wrong. The opposite is true: if anything, women’s right to health is under greater attack that it has been in the last 50 years.\n\nThere is a high risk that when an issue gets attention because of its connection to a health emergency, everything about that issue becomes about the emergency. This is what we call emergency exceptionalism in global health security: when an issue attains specialised status precisely because it is linked to an emergency.13 Exceptional status leads to additional funding and political will which in turn ensures it becomes one of the biggest health priorities in the world. This process is then circular: the more in which something is a priority, the more funding and political status afforded to it, and the more exceptional it becomes.\n\nThe risk with women and health is that the seismic impact and attention towards COVID-19 means that there is only attention, money, and concern for the impact of health emergencies on women, rather than women’s health more broadly. This is a problem. Making an issue exceptional within women’s health – women and health emergencies – leads to distortion of funds and attention away from other issues such as the leading causes of death of women in the world14. Health emergencies cause a huge short and long term burden on women around the world, but they are not the leading cause of death of women. These are: 1. ischaemic heart disease; 2. stroke; 3. chronic obstructive pulmonary disease; 4. lower respiratory infections; and 5. Alzheimer’s disease and other dementias.15 Alzheimer’s disease and other dementias is the biggest growth in cause of death, and kills more women than men.16\n\nA day to day concern for women around the world is malnutrition. One of the biggest health concerns for women is they are overweight or underweight. And this is getting worse. 2020 saw a severe food shortage and an increase in hunger, particularly in low and middle income countries. These changes were undoubtedly linked to the pandemic. However the future outlook remains bleak with climate change and global consumption habits continuing to impact on hunger around the world, and new challenges such as the war in Ukraine and sanctions against Russia heavily impacting on global food supply. More women go hungry than men. According to the UN’s The State of Food Security and Nutrition in the World Report, ‘for every 10 food-insecure men, there were 11 food-insecure women in 2020.’17 Hunger is a fundamental problem for the future of women’s health.\n\nA focus on the gendered impacts of health emergencies on women should not detract but be in addition to work on fighting these five leading causes of death of women. There is a risk that should a focus on the gendered impacts of health emergencies attain exceptional status, this will follow the path of other ‘exceptional’ health issues and cause huge distortions in women’s health away from other health programs. Advocates of women’s health need to be mindful of this trap and not repeat the past mistakes of global health security.\n\nOne way of making governments, international organisations, and private companies take women’s issues more seriously is to include women at every level of governance, including the top table. The logic being more women leads to greater diversity of thought and experience as to what it is live as a woman. Leading researchers such as Global Health 50/50 and campaigners such as Women in Global Health have done pioneering work in this area: identifying the extent of under-representation of women, and the absurdity of it. As Women in Global Health argue, health is ‘Delivered by women, led by men.’18 Health is different to other areas of international development in that women are ‘conspicuously invisible’19 – they are conspicuous across the health sector and make up the majority of healthcare workers in the world, but are invisible in policies, strategies, and across leadership.\n\nIncreased representation of women is a good in itself. However, it is not the end point of achieving gender equality in global health. There is a risk that institutions will point to their women quotas as evidence that they ‘do’ gender equality and therefore don’t have to do much else. This is a problem for four reasons. First, it puts a lot of onus and responsibility on women to effect change. This increases their workload and burden. Second, it assumes that these women want to do this work or have an inherent commitment to gender equality by virtue of being women. It fundamentally overlooks the diversity of women’s experiences in the world. Third, it shifts attention away from the gaps in the institution’s wider work. It is a classic deflection tactic. Finally, it puts all the emphasis on the individual without a wider commitment to structural change within a sector or institution. Greater representation of women and women in leadership is great. It is not an end point.\n\nGetting institutions to sign on to commitments towards gender equality is one thing. But the formal and informal ways in which this plays out is another. For example, institutions may be happy to talk about gender with regard to HIV/AIDS or COVID-19 but not road traffic accidents. Commitment to gender equality can also often rest with key individuals with the power and leverage to support these initiatives. This creates a set of problems: a lack of critical mass to galvanise and build institutional support and change, and an absence of progress should an individual leave the institution. Finally, there is institutional fatigue. People like to sign up to equality and justice initiatives when the world is looking at them, but then rapidly shift to the next issue or lose interest. Think about how quickly the narrative around #metoo and Black Lives Matter moved on. When this happens the gender equality advocate who was so desperately engaged by leadership, and most probably put on the front of their website for a month, becomes side-lined, and worse, a nuisance.\n\nExternal partners and friendly critics need to hold institutions to account on their promises. More than that, we need to push them to do more. For example, sex disaggregated data across the policies and programmes of the World Health Organisation (WHO) would be amazing. But data alone is not enough in the same way representation is not enough. We need to keep pushing for more. If we think we’re pushing too hard, we’re just getting through.\n\n\nData availability\n\nNo data are associated with this article.", "appendix": "Footnotes\n\n1 Sophie Harman, Threat not solution: gender, global health security and COVID-19, International Affairs, Volume 97, Issue 3, May 2021, Pages 601–623, https://doi.org/10.1093/ia/iiab012.\n\n2 Gender and COVID-19, ‘Resources’ https://www.genderandcovid-19.org/resources-page/ (accessed June 2022).\n\n3 WHO. ‘Gender, Equity, and Human Rights’ https://www.who.int/teams/gender-equity-and-human-rights/about (accessed June 2022); Bill and Melinda Gates Foundation, ‘Gender Equality’ https://www.gatesfoundation.org/our-work/programs/gender-equality/gender-equality (accessed June 2022).\n\n4 Gender and COVID-19, ‘Toolkits’ https://www.genderandcovid-19.org/resource_type/toolkit/ (accessed June 2022).\n\n5 Harman S, Erfani P, Goronga T, et al. Global vaccine equity demands reparative justice — not charity. BMJ Global Health 2021;6:e006504.\n\n6 Priti Krishtel, ‘Why vaccine equity is a feminist issue’ Ms Magazine, 23rd August 2021, https://msmagazine.com/2021/08/23/covid-vaccine-equity-feminist-women-girls-education-violence/ (accessed June 2022).\n\n7 Sophie Harman et al. ‘COVID-19 vaccines and women’s security’ The Lancet 2021; 397(10272): 357-358.\n\n8 Susan Faludi, Backlash: the undeclared war against women London: Vintage Random House; 1992.\n\n9 Susan Faludi, Backlash: the undeclared war against women.\n\n10 Linsey McGoey, The Unknowers: how strategic ignorance rules the world. London: Zed Books; 2019.\n\n11 Elżbieta Korolczuk and Agnieszka Graff, ‘Gender as “Ebola from Brussels”: The Anticolonial Frame and the Rise of Illiberal Populism’\n\nSigns: Journal of Women in Culture and Society 2018; 43(4): 797-821.\n\n12 Elżbieta Korolczuk and Agnieszka Graff, 2018, ‘Gender as “Ebola from Brussels”: The Anticolonial Frame and the Rise of Illiberal Populism’; Sara E Davies, Sophie Harman, Securing Reproductive Health: A Matter of International Peace and Security, International Studies Quarterly, Volume 64, Issue 2, June 2020, Pages 277–284, https://doi.org/10.1093/isq/sqaa020.\n\n13 Sara E Davies, Sophie Harman, Securing Reproductive Health: A Matter of International Peace and Security, International Studies Quarterly, Volume 64, Issue 2, June 2020, Pages 277–284, https://doi.org/10.1093/isq/sqaa020.\n\n14 Sara E Davies, Sophie Harman, Securing Reproductive Health: A Matter of International Peace and Security, International Studies Quarterly, Volume 64, Issue 2, June 2020, Pages 277–284, https://doi.org/10.1093/isq/sqaa020.\n\n15 WHO. 2020. ‘Leading causes of death and disability’ https://www.who.int/data/stories/leading-causes-of-death-and-disability-2000-2019-a-visual-summary (accessed June 2022).\n\n16 WHO. 2020. ‘Leading causes of death and disability’ https://www.who.int/data/stories/leading-causes-of-death-and-disability-2000-2019-a-visual-summary (accessed June 2022).\n\n17 WHO. (2021). https://www.who.int/news/item/12-07-2021-un-report-pandemic-year-marked-by-spike-in-world-hunger (accessed June 2022).\n\n18 WHO. (2019). Delivered by women, led by men: a gender and equity analysis of the global health and social workforce. World Health Organization. https://apps.who.int/iris/handle/10665/311322.\n\n19 Sophie Harman (2016) Ebola, gender and conspicuously invisible women in global health governance, Third World Quarterly, 37:3, 524-541, DOI: https://doi.org/10.1080/01436597.2015.1108827." }	[ { "id": "155122", "date": "16 Dec 2022", "name": "Marta Schaaf", "expertise": [ "Reviewer Expertise Sexual and reproductive health and rights", "governance", "accountability", "human rights" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAbstract:\nThe abstract refers to the gendered impacts of healthcare; this is not addressed in the paper itself.\nIntroduction:\n\nWould not use \"thinking through\" twice in the same paragraph.\n\nSeems to equate women with gender. Were there explorations of masculinity, risk-taking, assumptions about work and family support, and COVID-19? If not, it may not be fair to say that 'gender is no longer an after-thought\".\n1. We are not post-pandemic\nSeems to imply that vaccination is the only and the most important tool. Morbidity and mortality are rising among the vaccinated as new variants develop.\n\n\"Access to vaccines draw on transnational feminist solidarity and ideas of equality across the world. Moreover, vaccine delivery and uptake rests on the army of labour of female health care workers across the world. Our first concern for the future of women’s health is therefore to ensure all women around the world are vaccinated against the world.\"\nThere are multiple typos in these sentences, e.g. 'army of labour of female HCWs'; 'women around the world are vaccinated against the world...' - The first sentence doesn't have a typo but I don't understand what it means. Do you mean civil society movements promoting access to vaccines draw on transnational feminist solidarity?\n\n2. Lots of the world...\n\"These questions are rarely intended to focus on these important points and sources of inequality: they are always about silencing women and/or asking questions about gender.\"\nThat is a very strong statement. In the context of BLM and the significant racial disparities in COVID mortality rates, saying that asking questions about race and class is always about silencing women is a very strong statement that I disagree with and one I urge you to reconsider. It is easy to interpret as discounting the notion of intersectionality.\n\n\"they hold firm that gender is an affront\" - I know the word 'gender' by definition is about a social construct, but it might be helpful to your readers to be more specific about what you mean.\n\n\"We saw this in Poland, we saw this in Brazil...\" - Again, some greater specificity for your readers would be helpful.\n\nAgain, I am not sure about the conventions of this particular publication, but greater specificity and/or citations on the statement \"under greater attack than (not that) it has been in the last 50 years\" would be helpful.\n\nOn the causes of death, would it strengthen your argument to point to some of the SDH drivers of these? So besides inequalities in health research and health care access, there are issues around exposure to risk factors.\n\nYou mention overweight but your examples are all on underweight. Given the growing attention to the social construction and impact of overweight, I would delete it, since you don't explore it further.\n4. Seize the moment...\nOne other criticism of counting women in leadership positions that you might consider is whether or not women's representation is representative. In other words, to what extent are women of color, women from the Global South, women with disabilities etc. present? You acknowledge some positive impact of representation, presumably, this representation should extend to all groups of women, not just those who already hold comparatively more power.\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nAre arguments sufficiently supported by evidence from the published literature? Partly\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-856
https://f1000research.com/articles/11-854/v1	28 Jul 22	{ "type": "Review", "title": "Understanding floral biology for CRISPR-based modification of color and fragrance in horticultural plants", "authors": [ "Zulqurnain Khan", "Asim Razzaq", "Tahmina Sattar", "Aftab Ahmed", "Sultan Habibullah Khan", "Muhammad Zubair Ghouri", "Asim Razzaq", "Tahmina Sattar", "Aftab Ahmed", "Sultan Habibullah Khan", "Muhammad Zubair Ghouri" ], "abstract": "The global market of a total 42.4 billion US dollars of ornamental plants owes its worth to the color and fragrance associated with these plants. A lot of work has been done to understand the physiological, biochemical, genetic, and environmental factors responsible for the development of color and fragrance in flowers. The aim of these studies about the floral biology was to achieve the desired characters by manipulating all these factors to fulfill the changing demand of the global market. While, modifying flower color and fragrance, scientists moved from the traditional breeding methods to the comparatively modern genetic engineering techniques, yet limitations in results always remained a big issue for researchers. However, genome editing tools look promising to achieve the desired level of efficiency to modify the color and fragrance in the flowers. This review gives insight into the significance of floral characters, molecular factors responsible for these characters and applications of modern genome editing technologies for desirable modification.", "keywords": [ "Genome Editing", "Flower Color", "Frangrance", "Genetic Modification", "Plant Transformation" ], "content": "1. Introduction\n\nEsthetics and the appreciation of beauty are among the basic instincts of human beings, and ornamental plants are the purest form of natural esthetics. Humans have been breeding these plants for thousands of years in order to develop desired characteristics. Besides aesthetics, they have many economic, environmental and health benefits (Hall & Dickson, 2011; Hall & Hodges, 2011). Cut flowers, lawn grasses, palms, bedding plants, shrubs, and trees are some of the main categories of these ornamental plants. Among them, 4000 non-woody species have been commercialized so far (Pompelli, De Brito, Otoni, & Guerra, 2007). We believe it is justified to say that all value and mystique of ornamentals are directly or indirectly associated with their color and fragrance.\n\nFlower color could be regarded as the most important feature of flowering plants (Zhao & Tao, 2015). Besides esthetics, specific flower color is also responsible for entomophily (Brouillard & Cheminat, 1988; Davies, Albert, & Schwinn, 2012). Furthermore, flower color has a major impact on the commercial value and consumer selection (Berghage & Wolnick, 2000). Flower color is determined by three classes of pigments: flavonoids, carotenoids, and betalains (Grotewold, 2006; Tanaka, Katsumoto, Brugliera, & Mason, 2005). It can be classified on the basis of either color depth or coloration (Nakayama, Tanikawa, Morita, & Ban, 2012). Flavonoids are the most abundant among these pigments and nearly six thousand such pigments have been reported in the literature (Hichri et al., 2011). They can be divided chiefly into co-pigments (e.g., flavanones, flavones, and chalcones) and anthocyanins (e.g., petunidin, pelargonidin, and cyanidin) (Barb, Werner, & Griesbach, 2008).\n\nAnthocyanins are regarded as the major pigments for determining flower color and its intensity (Aida et al., 2000a; Hanumappa et al., 2007; Katsumoto et al., 2007), giving characteristic orange, pink, purple, red, violet and blue colors to the flowers of different plant species (Forkmann, 1991; Gutterson, 1995). Around 1000 such pigments have been identified so far (Yoshida, Mori, & Kondo, 2009). Besides having a function in coloration, anthocyanin has also been found playing an antioxidative role by protecting the plant from free radicals produced as a result of various stresses (Chalker-Scott, 1999; Harborne & Williams, 2000; He et al., 2011; Steyn, Wand, Holcroft, & Jacobs, 2002; Teppabut, Oyama, Kondo, & Yoshida, 2018). Anthocyanidins (anthocyanin without sugars) have three main classes: pelargonidin (orange to brick red), cyanidin (red to pink) and delphinidin (purple to blue) (Hanumappa et al., 2007; Yoshida et al., 2009). Moreover, the intensity of color is also related to the concentration of anthocyanins (Tanaka, Sasaki, & Ohmiya, 2008).\n\nCarotenoids give a range of orange and yellow colors (Gutterson, 1995). Besides providing color, they have also an important role in photosynthesis, prevention from free radicals and entomophily (Bradshaw Jr & Schemske, 2003; Fang et al., 2008; Jo et al., 2016; Ruban et al., 2007).\n\nThe fragrance is a collective, complex and unpredictable trait of flower (Cherri-Martin, Jullien, Heizmann, & Baudino, 2007), produced by the products of several biosynthetic pathways within the plant. These products are low molecular weight volatiles (Croteau & Karp, 1991). More than 1700 such volatiles have been identified by the scientists (Ishizaka, 2018) and their function has been characterized in different flowers, like roses (Flament, Debonneville, & Furrer, 1993; Shalit et al., 2004), petunia (Schuurink, Haring, & Clark, 2006), gentians (Lee, Sugawara, Yokoi, & Takahata, 2010), lilies (Kong, Sun, Pan, & Zhang, 2012) and carnations (Clery, Owen, Chambers, & Thornton-Wood, 1999; Kishimoto, Nakayama, Yagi, Onozaki, & Oyama-Okubo, 2011; Schade, Legge, & Thompson, 2001). These volatiles are mainly derived from three pathways: the terpenoid pathway, the phenylpropanoid/benzenoid pathway and the fatty acids pathway (Knudsen, Eriksson, Gershenzon, & Ståhl, 2006; Vainstein, Lewinsohn, Pichersky, & Weiss, 2001). Mostly these pathways are overlapping with each other and also with the pathways involved in color production (Croteau & Karp, 1991; Zvi et al., 2008).\n\nPhenylpropanoids arise from phenylalanine and its synthesis is catalyzed by an enzyme called phenylalanine ammonia-lyase (PAL) (Dudareva & Pichersky, 2006c; Vainstein et al., 2001). It consists of number of secondary metabolites and those secondary metabolites which are volatiles, have a specific chemical configuration (Dudareva & Pichersky, 2006c). While benzenoids arise from trans-cinnamic acid through a side branch of general phenylpropanoid pathway (Boatright et al., 2004). Phenylpropanoids and benzenoids also originate from shikimic acid through shikimate pathway (Baldermann, Yang, Sakai, Fleischmann, & Watanabe, 2009). Besides having a role in fragrance, this class is also involved in plant defense (Dixon et al., 2002). A lot of studies have been performed to study the regulation of benzenoids pathway in various flowering plants (Boatright et al., 2004; Schuurink et al., 2006; van Schie, Haring, & Schuurink, 2006).\n\nTerpenes are from the largest class of plant volatiles, mainly consist of monoterpenes (linalool, caryophyllene, limonene, farnesene, myrcene etc.) and are produced by the terpenoid pathway from a five-carbon compound called isopentenyl diphosphate, whose biosynthesis is catalyzed by various mono- and sesquiterpene synthases (Blowers & Dudareva, 2006; Trapp & Croteau, 2001). Terpenes also have a role in insect attraction and plant defense mechanism (Dewick, 2002).\n\nFatty acid derivatives form the second largest class of plant volatiles and are derived from membrane lipids through lipogenase pathway with the involvement of lipogenase enzymes (Gutiérrez, 2009). The shikimate pathway provides precursors for the biosynthesis of primary metabolites such as aromatic amino acids and folic acid. The shikimate pathway is a metabolic bridge between primary and secondary metabolism with regard to the regulation of AAA biosynthesis (Tzin & Galili, 2010). The regulation of the shikimate pathway has been studied extensively (Maeda & Dudareva, 2012; Tzin, Galili, & Aharoni, 2001).\n\nFloral fragrance enhances the esthetic and commercial value of ornamental plants (Dudareva & Pichersky, 2006a; Noman et al., 2017; Pichersky, Noel, & Dudareva, 2006). It is an important trait for flowers to attract bees and other pollinators for the successful pollination (Dudareva & Pichersky, 2000; Pellmyr & Thien, 1986; Piechulla & Pott, 2003; Tholl, 2006; Vainstein et al., 2001). It also has a role in providing insect resistance and pathogen protection to flower (Dudareva, Klempien, Muhlemann, & Kaplan, 2013; Dudareva & Pichersky, 2008). Modifying the floral fragrance of an ornamental will surely help to enhance its value (Pompelli et al., 2007).\n\nInterestingly, the floral fragrance does not remain the same throughout the season or even throughout the day. Circadian rhythm has been found to control this trait for example, petunia and gentian were found to be more fragrant in the night (Verdonk et al., 2005). There are various studies mentioning the impact of circadian rhythm on fragrance (Helsper, Davies, Bouwmeester, Krol, & van Kampen, 1998; Hendel-Rahmanim, Masci, Vainstein, & Weiss, 2007; Kolosova, Gorenstein, Kish, & Dudareva, 2001; Simkin et al., 2004). Availability of light, production of certain hormones, climatic factors, developmental stage of the flower and time of activity of pollinator are the major factors affecting this rhythmic emission of fragrance (Cna'Ani et al., 2015; Dudareva et al., 2000; Dudareva & Pichersky, 2006b; Jakobsen & Olsen, 1994). Floral color and fragrance are the most important factors of prime esthetic value to attract the customers and industry. Modification in the color and fragrance may have huge impact in scientific and economic terms.\n\n\n2. Synthesis and regulation of flower color and fragrance\n\nStructural and regulatory genes of flower color determine the color type and its intensity (Nakatsuka, Nishihara, Mishiba, & Yamamura, 2005). Many genes related to pigment biosynthesis in ornamental plants have been discovered so far.\n\nGenes encoding 3GTs in snapdragon were characterized (Martin, Prescott, Mackay, Bartlett, & Vrijlandt, 1991). The role of the AmAS1 gene in yellow flower color in snapdragon was confirmed in 2000 (Nakayama et al., 2000). Moreover, genes related to floral pigments were found in various other ornamentals like lily and morning glory flowers (Yamagishi, 2013; Zufall & Rausher, 2003). A chromoplast-specific, carotenoid-associated gene (OgCHRC) was characterized in oncidium Gower Ramsey (Chiou, Wu, & Yeh, 2008). UDP-glucose: anthocyanin 5-O-glucosyltransferase (5GT), having a role in gentiodelphin accumulation in petals conferring blue color, was characterized from blue gentian (Nakatsuka et al., 2008c). The chalcone synthase (CHS) gene was found in in tree peony (Zhou, Wang, & Peng, 2011). Anthocyanin methyltransferase (AMT), and glutathione S-transferase (GST) were found to have a role in the anthocyanin biosynthesis pathway in carnations (Tanaka, 2012). Dual colors in petunia petals were related to the post-transcriptional gene silencing of CHS genes (Yamagishi, 2013). Similarly, VwF3′5′H, VwDFR and VwANS genes were found to play role in flower color patterns in pansy petals (Li, Wang, Sun, & Shang, 2014). The F3H, DFR, ANS and 3GT genes play a role in purple–red pigmentation were found in in tree peony (Shi et al., 2015). In the ornamental tree peony, PsDFR and PsANS were found to be related to anthocyanin biosynthesis (Zhao, Tang, Hao, & Tao, 2015). The impact of floral color and inflorescence genes interaction on the creation of floral color and type in ornamental sunflower was discovered in 2016 (Cvejić, Jocić, & Mladenović, 2016). The flavonol synthase gene (FLS) and Fh3GT1 were found to have a role in anthocyanin biosynthesis in the tree peony (Sun et al., 2017; Zhao, Wei, Liu, & Tao, 2016). Genes related to color intensity in peony were found (Gao, Yang, Liu, Yang, & Hu, 2016). The role of RrFLS, RrDFR and RrF3′H genes in petal color of rose was found in 2018 (Li et al., 2018). CpurFLS1 and CpurFLS2 were isolated from cyclamen and have a role in flavonol synthesis (Akita, Kitamura, Mikami, & Ishizaka, 2018).\n\nVarious transcriptional factors associated with the pigments biosynthesis and regulation has been identified in different ornamentals. Members of the R2R3-MYB gene family were identified as the key activators of the flavonoid pathway and were isolated from various ornamentals (Davies et al., 2012; Morita, Saitoh, Hoshino, Nitasaka, & Iida, 2006; Naing & Kim, 2018; Yamagishi, Shimoyamada, Nakatsuka, & Masuda, 2010). The R2R3-MYB transcription family was found to control pigmentation pattern in petunias (Albert et al., 2011). Likewise, MYB and bHLH transcription factors were found to be related to anthocyanin pigmentation in various ornamental flowers (Nakatsuka et al., 2008a; Schwinn et al., 2014). 50 differentially expressed transcription factors involved in flavonoid biosynthesis in the tree peony were discovered in 2015 (Shi et al., 2015).\n\nSo, there is a long list of discovered transcriptional factors involved in flower color formation and regulation process not only in ornamentals but also in other crops (Hichri et al., 2011).\n\nBesides genomics and proteomics, several physical and chemical factors like metal ions, vacuolar pH, temperature, biotic and abiotic stresses, and hormones have been found having a great impact on the color formation process in petals (Chandler & Tanaka, 2007; Lai, Yamagishi, & Suzuki, 2011; Takeda, 2006; Tatsuzawa, Tanikawa, & Nakayama, 2017; Tsuma et al., 2014; Weiss, 2000; Winkel-Shirley, 2002). All of these factors must be kept in mind while manipulating the flower color otherwise desired results could not be achieved, as occurred in case of failure of the attempt to create blue carnation in spite of successful transfer of F35H′ gene due to inappropriate vacuolar pH (Holton et al., 1993).\n\nVarious genes related to the volatile production have been discovered in various ornamental species like in snapdragon these genes were identified: S-adenosyl-L-methionine:benzoic acid carboxyl methyl transferase (Dudareva et al., 2000), S-adenosyl-L-methionine: salicylic acid carboxyl methyl transferase (Negre, Kolosova, Knoll, Kish, & Dudareva, 2002), myrcene synthase (Dudareva et al., 2003), and terpene synthases (Nagegowda, Gutensohn, Wilkerson, & Dudareva, 2008).\n\nWhile in roses: orcinol O-methyl transferase (Lavid et al., 2002), germacrene D synthase (Guterman et al., 2002), OOMT1 and OOMT2 (Guterman et al., 2002), geraniol/citronellol acetyl transferase (Shalit et al., 2003), RhAAT1 (Shalit et al., 2003), RcOMT1 and RcOMT2 (Wu et al., 2003), and phloroglucinol O-methyltransferase (POMT) (Wu et al., 2004), and RhPAAS (Farhi et al., 2010).\n\nIn petunia: S-adenosyl-L-methionine: benzoic acid/salicylic acid carboxyl methyl transferase (Negre et al., 2003), benzoyl-coenzyme A:benzyl alcohol/phenylethanol benzoyl transferase (Boatright et al., 2004), phenylacetaldehyde synthase (PAAS) (Kaminaga et al., 2006b), and PhCM1 (Colquhoun et al., 2010b).\n\nIn Clarkia breweri: (S)-linalool synthase (Dudareva, Cseke, Blanc, & Pichersky, 1996), S-adenosyl-L-methionine (SAM):(iso) eugenol O-methyl transferase (Wang, Dudareva, Bhakta, Raguso, & Pichersky, 1997), iso-eugenol O-methyltransferase (IEMT) (Wang & Pichersky, 1998), acetyl-coenzyme A:benzyl alcohol acetyltransferase (Dudareva, D’auria, Nam, Raguso, & Pichersky, 1998), S-adenosyl-L-methionine:salicylic acid carboxyl methyl transferase (Ross, Nam, D'Auria, & Pichersky, 1999), benzoyl-coenzyme A:benzyl alcohol benzoyl transferase (D'Auria, Chen, & Pichersky, 2002).\n\nFinally, in Hedychium spp., two terpene synthase genes were found (HcTPS7 and HcTPS8) (Yue, Yu, & Fan, 2014).\n\nBesides structural genes, transcriptional factors’ role in fragrance biosynthesis has been also studied (Colquhoun & Clark, 2011). A few such transcriptional factors have been discovered in ornamentals like MYB transcriptional factors in roses (Yan et al., 2011). ODORANT1, EMISSION OF BENZENOIDS II (EOBII), ODO1 from petunia (Spitzer-Rimon et al., 2012; Spitzer-Rimon et al., 2010; Van Moerkercke, Galván-Ampudia, Verdonk, Haring, & Schuurink, 2012; Verdonk et al., 2005) and ODORANT1 from lilies (Yoshida, Oyama-Okubo, & Yamagishi, 2018).\n\n\n3. Methods to improve flower color and fragrance\n\nA detailed account of successful attempts of flower color and fragrance modification in ornamental plants using various techniques has been provided in the Table 1.\n\nBreeding tools have been used to bring modifications in the flower color of ornamentals; for example, interspecific hybridization has been used to modify the flower color in Ornithogalum spp. (Griesbach, Meyer, & Koopowitz, 1993).\n\nSome of the random mutation tools have also been applied to achieve flower color modification in ornamentals such as the application of various sugars (sucrose, mannose, glucose) to peonies affecting flower color and anthocyanin biosynthesis (Zhang et al., 2015); white–purple color variant violets were obtained by colchicine treatment (Seneviratne & Wijesundara, 2007); magnesium treatment increased anthocyanin accumulation in four different ornamentals (Nissim-Levi, Ovadia, Forer, & Oren-Shamir, 2007; Venkatachalam & Jayabalan, 1994) used gamma radiations to realise mutations in zinnia flowers.\n\nAfter a long era of ignorance of fragrance traits, finally, progress was made on selecting ornamental varieties, not for agronomic or color traits but for fragrance traits; for example, in 2013, an effort was made to enhance the benzenoid diversity in carnations by crossing it with wild dianthus (Dianthus hungaricus) (Kishimoto et al., 2013). The resultant hybrid carnations were found to have a relatively diverse fragrant compounds’ profile than their parents.\n\nA relatively new mutation tool, ion beam radiation, has been also used to change the flower color by deposition of high energy through ion beams (heavy charged particles); inducing epigenetic changes (as suggested by: (Nakayama et al., 2012)) or creating double-strand breaks in DNA (Hoglund, 2000) with a low probability of DNA repairing (Goodhead, 1995). It has been induced successfully to induce flower color mutants in ornamentals like geraniums (Yu et al., 2016), Torenia spp. (Miyazaki et al., 2006), chrysanthemum (Matsumura et al., 2010), and cyclamen (Ishizaka, Kondo, & Kameari, 2012; Kondo et al., 2009). This technique has also been used in combination with other techniques like tissue culture (Matsumura et al., 2010) or by pretreatment of the sample with potential mutants (Hase, Okamura, Takeshita, Narumi, & Tanaka, 2010).\n\nNot only the desired gene but also many other genes get interchanged during hybridization, so backcrosses must be made to somehow get close to the desired level of the trait (Hammond, 2004). We can just either knock-out a gene through these methods or interchange them but, unlike genome editing tools, we cannot introduce the desired gene into the target organism, so we are limited by the genome of our target organism and dependent on the genes only naturally present in parent plants (Nishihara & Nakatsuka, 2010; Tanaka et al., 2005). Secondly, unlike genome editing techniques, all of these mutation-inducing methods are non-precise, random and have not much science involved in them. Some problems with being dependent on the mutation breeding to modify plants were identified (Shibata, 2008).\n\nIon beam radiation although yielded some successful results and could be termed as “new infatuation” for the mutation breeders. But compromising randomness over precision would not be a good choice. Some precision in this method was attempted by using it in accordance with pre-discovered genomic data (Tanaka, 2012), to make it look more “scientific” but it still remains a hit and trial method in which one performing it is not sure that either the target gene or trait would be targeted or not.\n\nReintroducing genes in antisense or sense orientation to induce genetic transformation is one of the oldest and outdated techniques in genetic engineering of ornamentals. In antisense suppression, an antisense RNA (having sequence complementary to the target RNA) blocks the target RNA by binding to it via base pairing, thus resulting in the knock-down of that particular gene (extensively reviewed by: (Green, Pines, & Inouye, 1986). It all started in 1988 with antisense CHS gene producing mutant (white) color in petunias (Van der Krol et al., 1988). Later on, it was extended to many other ornamentals, targeting various genes involved in floral pigment biosynthesis and regulation like CHS (Elomaa et al., 1993; Hanumappa et al., 2007), FLS (Nielsen et al., 2002), F3′5′H (Boase et al., 2010; Ueyama et al., 2006), F3H (Zuker et al., 2002), and DFR (Aida et al., 2000a).\n\nWhile, in sense/co-suppression, transgenes, aimed at overexpressing a particular gene, tend to knock down the targeted endogenous gene. The exact phenomenon of its working is still unknown; however, many possibilities exist, like epistatic interaction or RNA–duplex DNA interaction (as discussed by: (Van der Krol et al., 1990)) and its effectivity is dependent on many other factors like transgene sequence and promoter (Que, Wang, English, & Jorgensen, 1997). This technique was discovered accidentally in 1990 when CHS was tried to overexpress to enhance anthocyanin biosynthesis and instead it blocked it (Napoli, Lemieux, & Jorgensen, 1990). Since then it was implied in other ornamentals like petunia (Van der Krol et al., 1990), Torenia spp. (Aida et al., 2000b; Suzuki et al., 2000), chrysanthemum (Courtney-Gutterson et al., 1994), and others (reviewed by: (Gutterson, 1995)).\n\nWe have found only one modification being reported so far in which antisense suppression of flavanone 3-hydroxylase gene in Carnation resulted in the modification in fragrance due to the production of benzoic acid (Zuker et al., 2002).\n\nGenome modification techniques were rendered useful to overcome the genetic limitation of the plants not allowing having the colors out of a specific range (Chandler & Sanchez, 2012). We were able to introduce novel genes related to floral pigment biosynthesis and regulation, naturally not present in that ornamental. The first example of the color modification through this method was the generation of the color mutant in petunia through activating pelargonidin biosynthesis in it by transfer of A1 gene from maize into it (Meyer, Heidmann, Forkmann, & Saedler, 1987). Similarly, pelargonidin accumulation in Osteospermum spp. was achieved by the introduction of the DFR gene (Seitz et al., 2007). The most famous example is the creation of blue roses. Rose does not have a naturally blue color due to the lack of delphinidin biosynthesis. Scientists downregulated the native DFR gene of rose and took the F3′5′H from pansy and the DFR gene from iris and transferred it to rose resulting in blue roses (Katsumoto et al., 2007). Further, a yellow-colored petunia was generated by introducing the CHR gene into it (Davies, Bloor, Spiller, & Deroles, 1998). Further, pink-colored Torenia spp. and magenta-colored roses have been achieved by the introduction of DFR and anthocyanin 3′,5′-O-methyltransferase (A3′5′OMT) genes into them, respectively (Nakamura, Fukuchi-Mizutani, Miyazaki, Suzuki, & Tanaka, 2006).\n\nThe first case of fragrance modification using gene transfer was the production of S-linalyl-b-D-glucopyranoside in petunia after the transfer of the linalool synthase gene from Clarkia breweri into it (Lücker et al., 2001). Similar gene transfer from Clarkia breweri into carnation resulted in the production of trans-linalool oxide in the transgenic carnation (Lavy et al., 2002). However, fragrance modification remained undetectable for humans.\n\nRose alcohol acetyltransferase (RhAAT) gene transfer to petunia resulted in the accumulation of phenyl ethyl acetate and benzyl acetate in transgenic petunia (Guterman et al., 2006). Similarly, the transfer of Clarkia breweri benzyl alcohol acetyltransferase (BEAT) into lisianthus resulted in the enhancement of benzyl acetate in the transgenic plant (Aranovich et al., 2007).\n\nIntroduction of production of Anthocyanin Pigment1 (Pap1) from arabidopsis in P. hybridia and rose resulted in enhancement of phenylpropanoid/benzenoid and terpenoid compounds in the transgenic petunia and rose and thus modification was detectable by the human nose (Zvi et al., 2008, 2012). Genetic transformation tools have enabled scientists to perform cross-species gene transfer like a petunia plant was transformed with feedback-insensitive bacterial DAHPSf 3-deoxy-diarabino-heptulosonate 7-phosphate synthase enzyme (AroG*) gene which resulted in the enhanced formation of phenylalanine, tyrosine, and tryptophan in petunia and thus enhancing its fragrance (Oliva et al., 2015).\n\nAs far as the method of gene transfer is related, no doubt we are no more limited by the genome of our target plant. However, the limitation is that we can perform just a gene transfer and in order to create a mutant in which we have to target a specific gene knock out, the only option will be genome editing tools, as RNAi and other PTGS tools just perform a knockdown (which too not up to 100% as discussed below). Specifically when it comes to fragrance modification using gene transfer we have several short comes. Floral fragnance production is complex phenomenon. Introduction of a gene (producing particular volatile) may not give significant results due to lack of specific substrate or enzyme necessary to catalyze its production in that transgenic plant or due to accumulation of that volatile in the undesirable location or due to no proper storage facility. Moreover, this kind of volatile production will also have to compete with the other volatiles which are essential for development and growth (As discussed by: (Dudareva & Pichersky, 2006c)).\n\nSecondly, unlike as in case of genome editing techniques, the integration of transferred gene in the host genome is at a random location. This location has an impact on the expression of that gene due to the chromosomal position effect. Also, this randomly induced gene can disrupt the functioning of neighbor genes (as discussed by: (SonGSTad, Petolino, Voytas, & Reichert, 2017)). These concerns have to be addressed while approving a GM variety, making the regulation process very lengthy. While in case of genome editing, we have targeted knock-ins in the host genome, thus eliminating these unwanted problems and reducing the time required for its regulation (Pfeiffer et al., 2018).\n\nRNAi technology, whose idea came from (Napoli et al., 1990), bought a revolution in the whole scenario of not only floral color modification but also in the whole agriculture industry (Yogindran & Rajam, 2015). Scientists started preferring it over antisense and sense technology because of its potential and efficiency (Nakamura et al., 2006). RNAi is a post-transcriptional gene silencing technique in which double-stranded RNA gets cleaved into small interfering RNAs, which further degrade targeted mRNA (Angaji et al., 2010). It has been used to induce targeted color mutations in ornamentals. Like in Torenia spp. to produce white-colored flowers (Fukusaki et al., 2004b; Nakamura et al., 2006) or in gentian to produce white, blue and magenta-colored flowers (Nakatsuka et al., 2008b; Nakatsuka et al., 2010). Liliales spp. and petunia flower colors were also altered using RNAi (Kamiishi et al., 2012; Keykha, Bagheri, Moshtaghi, Bahrami, & Sharifi, 2016).\n\nTalking about fragrance modification in ornamentals using RNAi, we have seen examples in petunia only. These too were mostly focused on reducing the expression of a certain volatile and most of them were just performed to verify the involvement of a certain gene in the formation of a particularly volatile. In petunia, the BPBT gene was suppressed using RNAi and resulted in the reduced production of benzyl benzoate in transgenic petunia (Orlova et al., 2006). In another experiment, RNAi suppression of the PhMYB4 transcriptional factor in petunia resulted in the increased production of FVBP (floral volatile benzenoid/phenylpropanoid) compounds in transgenic petunia (Colquhoun et al., 2010a). In P. hybrida, downregulation of ODO1 transcriptional factor using RNAi resulted in the reduced production of benzoic acid (Verdonk et al., 2005). The knockdown of the PhBSMT gene resulted in the elimination of methyl benzoate in transgenic petunia (Underwood et al., 2005). In another experiment, the knockdown of the Arogenate Dehydratase1 (ADT1) gene resulted in the reduced level of shikimate and benzenoid in petunia (Maeda et al., 2010). RNAi-mediated silencing of the PhPAAS gene resulted in the termination of phenylacetaldehyde production (Kaminaga et al., 2006b). The PhcFAT gene was suppressed using RNAi and it resulted in the elimination of isoeugenol in the transgenic petunia plants (Dexter et al., 2007).\n\nNo doubt RNAi is a powerful tool to induce genome modifications, but it is a post-transcriptional genome silencer and it has been found difficult to restrict such tools only to the intended target (Hanumappa et al., 2007). RNAi is not efficient for plants having multiple copies of the same gene in their genome; if we knock down one gene, other genes continue to express (Shikata & Ohme-Takagi, 2008). While in the case of genome editing tools, we can use multiplex genome editing to solve this problem efficiently. Just like the case of mutation tools in RNAi, we are limited by the genome of our targeted organism. Further, we can neither perform a 100% knock out using RNAi (Angaji et al., 2010) nor introduce or activate desired genes in our target (Unniyampurath, Pilankatta, & Krishnan, 2016), making it inferior to genome editing tools.\n\nFor ornamental modification, from using selective breeding to the usage of genetic engineering now we have entered the era of genome modification.\n\nAlthough conventional breeding and genome engineering tools were being used for the improvement of crops and things were going on, there was an urge among the scientists to have a technology which can perform crop improvement with great precision. This dream came true in the form of genome editing tools. These tools comprising of zinc finger nucleases (ZFN), transcription activator-like effector nucleases (TALENs), and the Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated system (CRISPR) (Figure 2) can be harnessed not only to knock out a specific gene by creating a double stand break (DSB) (Haun et al., 2014; Shan, Zhang, Chen, Zhang, & Gao, 2015), but also to knock in a gene at a specific location in the target genome (Cai et al., 2009; J Li et al., 2016; Miki, Zhang, Zeng, Feng, & Zhu, 2018). Back in 2011, these genome editing methods were named as the method of the year by the nature journal (Baker, 2011). These genome editing tools are not limited to just perform knock-ins and knockouts by binding with an endonuclease domain only instead ZFN, TALE and Cas9 proteins can be paired with various other effector domains besides endonucleases to achieve the activation, repression or epigenome modification at the desired location (Khan, Khan, Mubarik, & Ahmad, 2018).\n\nThe DSB created by these genome editing tools is repaired by the host endogenous repair machinery either through homology-directed repair (HDR) or non-homologous end joining (NHEJ). In HDR, DSB is repaired by copying the information from a template DNA which could be from the sister chromatid or we can artificially provide that template DNA and thus performing a targeted knock-in. While in the absence of a template DNA, DSB is repaired through non-homologous end joining (NHEJ). It produces INDELs (insertions, deletions) thus leading to frameshift mutations and ultimately knocking out gene at the target loci (Lieber, 2010; Puchta, 2004; Symington & Gautier, 2011; Wyman & Kanaar, 2006).\n\n3.5.1 ZFN\n\nZFN (zinc finger nuclease) is the first to be created among the targeted genome editing tools back in 1994 (Kim & Chandrasegaran, 1994). It consists of a zinc finger protein domain bound with a FokI endonuclease domain (Durai et al., 2005). FokI endonuclease cleaves the site upon dimer formation due to the binding of ZF proteins with the specific target sequence thus creating a double stand break there (Weeks, Spalding, & Yang, 2016). One monomer of ZF protein is specific for three DNA bases. So an array of zinc finger proteins is made according to the target sequence (Sovová, Kerins, Demnerová, & Ovesná, 2016). Most of the time, this DSB is usually repaired through the NHEJ pathway (Mishra & Zhao, 2018). Platforms like Oligomerized Pool Engineering (OPEN) and Context Dependent Assembly (CODA) are available for the ZFN assembly (Sander et al., 2010; Zhang et al., 2010).\n\nSo far it has been used in crops like soybean (Curtin et al., 2011) and tobacco (Schneider et al., 2016; Wright et al., 2005).\n\nThis tool was useful but a bit costly and complex (in terms of designing) and also to an extent, its target sites were limited (Nemudryi, Valetdinova, Medvedev, & Zakian, 2014).\n\n3.5.2 TALENS\n\nAddressing some of the complexity and high cost associated with ZFN, TALEN was created (Joung & Sander, 2013). Just like ZFN it also consists of two components, one is TALE protein and the other is a FokI nuclease domain, which is fused with the TALE proteins (Christian et al., 2010; Weeks et al., 2016). TALE is basically the infectious protein injected by Xanthomonas spp. bacteria into its host plant and thus recruiting host genome for its own benefit (Boch & Bonas, 2010; Bonas, Stall, & Staskawicz, 1989; Scholze & Boch, 2011). They have a translocational domain for moving, binding domain for binding at the specific target site and a transcription activator domain for activating the expression of that target host gene (Khan, Khan, Mubarik, Sadia, & Ahmad, 2017).\n\nTALE proteins consist of a repeat of 33–35 amino acids. This specific sequence of amino acid remains conserved in all TALE proteins except the amino acids at positions 12 and 13, known as repeat variable di-residues (RVDs), these amino acids are different in every TALE protein and each RVD specifically binds with one DNA base (Deng et al., 2012). HD, NG, NI, and NN specify for C, T, A and G/A respectively (Boch et al., 2009; Moscou & Bogdanove, 2009). Thus, every monomer of TALE protein binds with one specific nucleotide and TALENS can be assembled using this information. Designing of TALENS is less complex as compared to that of ZFNs (Petersen & Niemann, 2015). Modular assembly (T. Li et al., 2011) and Golden gate assembly (Cermak et al., 2011) are used most of the time by scientists for the designing and assembly of TALEs and TALEN. Furthermore, (Khan et al., 2017) had excellently reviewed the available tools and methods for the assembly and designing of TALEs and TALENs. TALEN has been successfully used to modify the genome of many crops like rice (T. Li, Liu, Spalding, Weeks, & Yang, 2012; Shan et al., 2015), potato (Clasen et al., 2016), tobacco (Mahfouz et al., 2011), barley (Wendt et al., 2013), wheat (Y. Wang et al., 2014), maize (Char et al., 2015), and tomato (Lor, Starker, Voytas, Weiss, & Olszewski, 2014).\n\n3.5.3 CRISPR\n\nBack in 2012, the invention of CRISPR appeared as a revolutionary tool in the field of genome editing (Jinek et al., 2012). It is a kind of immune system named CRISPR/Cas which is found widely among archaea and bacteria (Barrangou, 2013; Barrangou et al., 2007; Makarova et al., 2015). When a bacteriophage attacks bacterium, the bacterial Cas9 endonuclease protein cleaves the phage DNA into small fragments and integrates them in the CRISPR locus. Upon transcription, that locus forms CRISPR RNAs (crRNAs) which gets paired with its complementary trans-activating crRNA (tracrRNA). And this complex guides the Cas9 protein in identification and cleavage of invading foreign nucleic acid (Datsenko et al., 2012; Jinek et al., 2012; Van Der Oost, Westra, Jackson, & Wiedenheft, 2014).\n\nThe CRISPR tool used for genome editing has two components: Cas9 protein and a sgRNA (single guide RNA), which is a chimera of trRNA and crRNA. A sequence of 3–5 nucleotides known as protospacer adjacent motif (PAM) must be present downstream to target DNA for the binding of and cleavage by CRISPR complex at that location. In case of Streptococcus pyogenes-derived CRISPR-Cas system, this sequence is 5′-NGG. Cleavage is made by the Cas9 protein at three base pairs (bp) upstream to the PAM sequence (Jinek et al., 2012; Schaeffer & Nakata, 2015).\n\nThe construct for CRISPR-Cas can be delivered via conventional gene transfer methods. However, the scientists prefer to use the transient gene expression. Because, firstly, stable gene transfer methods are laborious one and secondly, in these methods the trans-gene, coding for our synthetic nuclease, will get integrated into the host genome. No doubt it will segregate in the progeny, and we will select only those plants which do not express that trans-gene but it makes whole process so laborious. Instead, we can use transient gene expression, as we have the aim of creating knock out at desired location, once it has been created than we do not need the expression of that gene. We can even perform genome editing via CRISPR without even using a trans-gene; sgRNA–Cas9 ribonucleoprotein complexes are delivered directly to the target organisms where they perform cleavage at the target location and then get degraded by the enzymatic machinery of that organism (As reviewed by: (Pfeiffer, Quetier, & Ricroch, 2018)). This trans-gene free method has been used recently in maize (Svitashev, Schwartz, Lenderts, Young, & Cigan, 2016), and bread wheat (Liang et al., 2017).\n\nCRISPR-Cas9 mediated genome editing has been used in many crops so far like tobacco (Li et al., 2013; Nekrasov, Staskawicz, Weigel, Jones, & Kamoun, 2013), wheat (Wang et al., 2014), tomato (Brooks, Nekrasov, Lippman, & Van Eck, 2014; Ito, Nishizawa-Yokoi, Endo, Mikami, & Toki, 2015; Pan et al., 2016; Shimatani et al., 2017), rice (Feng et al., 2013; Wang et al., 2016), and maize (Char et al., 2017; Feng et al., 2016, 2018; Shi et al., 2017).\n\nNo doubt, CRISPR has much improved the overall efficiency of genetic manipulation experiments but still off targets remained a great hurdle for achieving the ideal level of results. Different variants of Cas proteins like Cas12 (Zetsche et al., 2015) and Cas13 (Abudayyeh et al., 2016) have been utilized to overcome this problem. A detailed comparison of these variants with other genome editing tools have been provided in the Table 2.\n\nPrime editing and base editing are relatively a fresh arrival in the toolkit of genome editing to tackle the off targets issue. Base editing is a technique involving irreversibly changing a single base in the whole genome. It can be very useful for manipulating single base mutation related properties or diseases, without producing unwanted double stand breaks in the DNA (Komor, Kim, Packer, Zuris, & Liu, 2016) converted Cytosine (C) into Thymine (T) by first using cytidine deaminase to convert C into Uracil (U). Consequent changing in the complementary strand through DNA repair mechanism resulted in the final conversion of G:U into A:T.\n\nThere are some reports of off targeting caused by Cytosine based base editing (Jin et al., 2019; Zhou et al., 2019). However, to further increase the efficiency of base editing, various amendments including addition of Uracil N-glycosylase (UGI), Gam protein (Komor et al., 2017) and POBEC3A (eA3A) (Gehrke et al., 2018) have been made so far. Also, to increase the target sites, various variants of Cas proteins have been used with base editing machinery (Hua, Tao, & Zhu, 2019; Wang et al., 2020). The unintended modification in RNA by base editing complex was also reported, which can be reduced by using deaminases (Zhou et al., 2019).\n\nBase editing has been used for genome manipulation in various plants including wheat (Li et al., 2018; Zhang et al., 2019; Zong et al., 2018; Zong et al., 2017), rice (Hua, Tao, Yuan, Wang, & Zhu, 2018; Jingying Li, Sun, Du, Zhao, & Xia, 2017; Lu & Zhu, 2017; Yan et al., 2018; Zong et al., 2017), arabidopsis (Chen et al., 2017), tomato (Shimatani et al., 2017), maize (Zong et al., 2017) and potato (Zong et al., 2018). However, we still wait for the first ever report for genome editing in ornamentals for fragrance and color using base editing.\n\nThe newest member in the family of genome editing tools is prime editing. It was reported back in 2019 (Anzalone et al., 2019). It not only overcomes the off-targeting issue of base editing but also it can perform all 12 kinds of base-to-base conversions, including four transition mutations and eight transversion mutations (Anzalone et al., 2019). The complex consists of a prime editing guide RNA (peg-RNA), a reverse transcriptase domain (RT domain) and a Cas9 protein. The Cas9 in it does not produces a double strand break at the target areas instead it produces a nick in a single strand, thus avoiding the complex aftermath of double strand breaks. The peg-RNA contains the sequence needed to be introduced at the target place. Upon attachment of prime editing complex at targeted sequence, Cas 9 produces a nick in the PAM containing DNA strand and the primer binding site (PBS) of peg-RNA hybridizes with it and RT produces the desired DNA strand using the sequence provided by peg-RNA (Anzalone et al., 2019).\n\nPrime editing technology is relatively new, and it promises a lot of potential for genome editing in not only ornamentals but also other plants.\n\nGenome editing tools have been successfully used to modify various fruits and ornamental species (Karkute, Singh, Gupta, Singh, & Singh, 2017). But, so far in the case of ornamentals, very little progress has been made for various reasons, like lack of whole-genome sequencing in most of the ornamentals and not having proper information about the exact pathways of many volatiles associated with these traits, especially flower fragrance. The lack of research is mainly due to the fact that there are thousands of ornamental flowers and the market value of one variety as a single is very low while modification and then regulation of modified plants require a lot of money and time.\n\nIn genome editing tools, only CRISPR has been used to harvest color modification in ornamentals, maybe due to the simplicity in its designing (Cong et al., 2013). Whereas, no attempt to modify floral fragrance in ornamentals using genome editing tools has been made.\n\nTorenia spp., Japanese morning glory, and P. hybridia have been reported to have modified color using CRISPR. In Japanese morning glory knockout of carotenoid cleavage dioxygenase (CCD4) using the CRISPR/Cas9 system resulted in the pale-yellow colored flowers (Watanabe, Oda-Yamamizo, Sage-Ono, Ohmiya, & Ono, 2018). While knockdown of dihydroflavonol-4-reductase-B (DFR-B) gene in Japanese morning glory using CRISPR/Cas9 system yielded white-colored flowers instead of purple (Watanabe et al., 2017), While in Torenia spp., knock out of flavanone 3-hydroxylase (F3H) gene resulted in the creation of pale blue colored flowers (Nishihara, Higuchi, Watanabe, & Tasaki, 2018) and similarly in P. hybridya flavanone 3-hydroxylase (F3H) was knockdown using CRISPR/Cas9 system (Subburaj et al., 2018).\n\n\n4. Concluding remarks\n\nThe modifications done in ornamentals using antisense, sense or RNAi technology were most of the times proved to be unstable and reversible. So, in the future usage of genome editing tools for genetic modifications can be proved worthy. Several ways could be adopted to bring stable modifications in ornamentals using genome editing tools. Like, 3,5-dimethoxytoluene (DMT) contributes a significant part in Tea rose scent (Scalliet et al., 2008) and OOMT1 and OOMT2 were found playing role in DMT formation (Scalliet et al., 2008). So, by precisely knocking out or knocking down these enzymes using genome editing tools, we can have a modified form of fragrance in these flowers. Similarly, upregulation of ODO1 (Verdonk et al., 2005), having a role in the shikimate pathway, using CRISPRa will be promising for enhancing fragrance in it.\n\nMonoterpenes constitute a major part of rose fragrance. GPP is found to be the precursor of monoterpenes. Similarly, GGPP was found to be the precursor of polyterpenes (Magnard et al., 2015). So, by enhancing the production of GPPPs and CaGGPPs (enzymes catalyzing productions of GPP and GGPP respectively) using CRISPRa, an enhance in the rose fragrance is expected which will be commercially beneficial.\n\nGeraniol is also a significant part of rose fragrance. An enzyme RhNUDX1 was found to be a precursor of geraniol formation in roses (Magnard et al., 2015). The upregulation of this enzyme, using CRISPRa, is expected to enhance fragrance in roses.\n\nChrysanthemum has carotenoids but they have white-colored flowers because they have a carotenoid degrading enzyme called carotenoid cleavage dioxygenase (CCD4) (Ohmiya, Kishimoto, Aida, Yoshioka, & Sumitomo, 2006). By precise targeting of CCD4 through genome editing tools, we can yield carotenoid related colors in this flower.\n\nThe blue color of the gentian is found to be due to anthocyanins (Nakatsuka et al., 2008c). So, by precise targeting of anthocyanidin glucosyltransferase through genome editing tools, we can expect a noble color formation in gentian flowers.\n\nLikewise, Tiger Lilly has b-carotene based carotenoids (Deli, 1999). So, by targeting enzymes involved in the b-carotene formation like lycopene B-cylose, a significant change in the flower color is expected.\n\nOrnamental plants are under continuous threat from pests; be it aphids (Peronti and Sousa-Silva, 2002), bugs (Wheeler and Henry, 1976), whiteflies (Simala et al., 2009), sawflies (Miles, 1962) or moths (Evenden, 2009). The future work on ornamentals could be directed towards using genome editing tools for decreasing the infestation of pests on ornamental plants. It can be started from analyzing the parameters which are considered by these pests for attacking an ornamental. Recently, we have seen that knocking down PDS gene of carotenoid pathway resulted in less growth of caterpillars on the modified plants (Zheng et al., 2010). Similarly, other important genes involved in the color and fragrance formation in ornamental plants can be targeted via genome editing tools and we can have less infestation of these harmful insects.\n\nAnother effective method for color modification using genome editing tools could be knock out/knockdown of transcriptional factors associated with regulation and synthesis of various floral pigments. Many such have been identified in various ornamentals (Davies et al., 2012; Morita et al., 2006; Naing & Kim, 2018; Nakatsuka et al., 2008a; Schwinn et al., 2014; Shi et al., 2015; Yamagishi et al., 2010).\n\nShikimate pathway is the precursor to the phenyl propaniod pathway (Herrmann & Weaver, 1999). So, any precise disturbance induced in the enzymes of this pathway like TYRB or PDT using genome editing tools could result in the disturbance of phenylpropanoid leading to a significant change in both color and fragrance. Apart from these possible editions, many other ways are waiting to be explored.\n\nWe are optimistic that in the future scientists would be successful in exploring more and more paradigms behind the formation of flower color and fragrance. As color and fragrance formation is a complex phenomenon and we had already seen that manipulation of the genes, involved in pigments biosynthesis, negatively affected the other traits of the plant besides color (Van Der Meer, Stam et al. 1992; Li, Zhang et al. 2013). So only a healthy cooperation between fields of structural and functional genomics along with transcriptomics and bioinformatics can open new dimensions in the identification and then efficient genome editing of the factors producing color and fragrance in ornamental plants.\n\nThe prime editing and base editing will be the frontline tools to achieve subtle fragrance and color modifications. Also, the future optimization of prime editing and base editing complexes will play a decisive role in determining their part in the advancement of ornamental industry.\n\nAs in the future we will be equipped with more efficient genome editing tools and genome modification would be easier than ever, a close eye should be kept on the possible repercussions of these modifications. The modification in the color and fragrance of ornamentals will lead to the change in the selection pattern of their pollinators and their pests. It would be necessary then to be clear in the objectives of genome editing. The economic gain at the cost of ecological disruption will be proven nothing but an illusion.\n\nIn the end, the issue of regulation of gene-edited crops would be worth discussing. As apart from the aforementioned reasons, scientists were moving towards genome editing tools because these tools were out of the jurisdiction of regulatory authorities of genetically modified crops. However, the Court of Justice of the European Union (ECJ) recent ruling that all gene-edited crops should be regulated under the same laws as genetically modified organisms are being regulated, can be a huge set back to the prospering industry of gene-edited ornamentals. The demand for minimizing regulatory procedures at-least for the non-food plants, especially the ornamentals, can now be heard louder than ever.\n\n\nData availability\n\nNo data are associated with this article.\n\n\nAuthor contributions\n\nZ.K. planned the manuscript outline. A.R. and T.S. wrote the draft and created the figures and tables. S.H.K., A.A., Z.A. and A.A.K. revised and proofread the manuscript. All authors read and approved the final manuscript.", "appendix": "References\n\nAbudayyeh OO, Gootenberg JS, Konermann S, et al.: C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector. Science. 2016; 353(6299): aaf5573. PubMed Abstract \| Publisher Full Text\n\nAida R, Yoshida K, Kondo T, et al.: Copigmentation gives bluer flowers on transgenic torenia plants with the antisense dihydroflavonol-4-reductase gene. Plant Sci. 2000a; 160(1): 49–56. PubMed Abstract \| Publisher Full Text\n\nAida R, Kishimoto S, Tanaka Y, et al.: Modification of flower color in torenia (Torenia fournieri Lind.) by genetic transformation. Plant Sci. 2000b; 153(1): 33–42. Publisher Full Text\n\nAkita Y, Kitamura S, Mikami R, et al.: Identification of functional flavonol synthase genes from fragrant wild cyclamen (Cyclamen purpurascens). J. Plant Biochem. Biotechnol. 2018; 27(2): 147–155.\n\nAlbert NW, Lewis DH, Zhang H, et al.: Members of an R2R3-MYB transcription factor family in Petunia are developmentally and environmentally regulated to control complex floral and vegetative pigmentation patterning. Plant J. 2011; 65(5): 771–784. PubMed Abstract \| Publisher Full Text\n\nAngaji S, Hedayati SS, Hosein R, et al.: Application of RNA interference in plants. Plant Omics. 2010; 3(3): 77.\n\nAnzalone AV, Randolph PB, Davis JR, et al.: Search-and-replace genome editing without double-strand breaks or donor DNA. Nature. 2019; 576(7785): 149–157. PubMed Abstract \| Publisher Full Text\n\nAranovich D, Lewinsohn E, Zaccai M, et al.: Post-harvest enhancement of aroma in transgenic lisianthus (Eustoma grandiflorum) using the Clarkia breweri benzyl alcohol acetyltransferase (BEAT) gene. Postharvest Biol. Technol. 2007; 43(2): 255–260. Publisher Full Text\n\nBaker M: Gene-editing nucleases. Nature Publishing Group;2011; 9. : 23–26. Publisher Full Text\n\nBaldermann S, Yang Z, Sakai M, et al.: Volatile constituents in the scent of roses. Floric. Ornam. Biotechnol. 2009; 3(1): 89–97.\n\nBarb JG, Werner DJ, Griesbach RJ: Genetics and biochemistry of flower color in stokes aster. J. Am. Soc. Hortic. Sci. 2008; 133(4): 569–578. Publisher Full Text\n\nBarrangou R: CRISPR-Cas systems and RNA-guided interference. Wiley Interdiscip. Rev. RNA. 2013; 4(3): 267–278. Publisher Full Text\n\nBarrangou R, Fremaux C, Deveau H, et al.: CRISPR provides acquired resistance against viruses in prokaryotes. Science. 2007; 315(5819): 1709–1712. PubMed Abstract \| Publisher Full Text\n\nBerghage R, Wolnick D: Consumer color preference in New Guinea impatiens. HortTechnology. 2000; 10(1): 206–208. Publisher Full Text\n\nBlowers A, Dudareva N: Modification of floral scent in flowering plants. Google Patents;2006.\n\nBoase MR, Lewis DH, Davies KM, et al.: Isolation and antisense suppression of flavonoid 3', 5'-hydroxylase modifies flower pigments and colour in cyclamen. BMC Plant Biol. 2010; 10(1): 107. PubMed Abstract \| Publisher Full Text\n\nBoatright J, Negre F, Chen X, et al.: Understanding in vivo benzenoid metabolism in petunia petal tissue. Plant Physiol. 2004; 135(4): 1993–2011. PubMed Abstract \| Publisher Full Text\n\nBoch J, Bonas U: Xanthomonas AvrBs3 family-type III effectors: discovery and function. Annu. Rev. Phytopathol. 2010; 48: 419–436. PubMed Abstract \| Publisher Full Text\n\nBoch J, Scholze H, Schornack S, et al.: Breaking the code of DNA binding specificity of TAL-type III effectors. Science. 2009; 326(5959): 1509–1512. Publisher Full Text\n\nBonas U, Stall RE, Staskawicz B: Genetic and structural characterization of the avirulence gene avrBs3 from Xanthomonas campestris pv. vesicatoria. Mol. Gen. Genet. MGG. 1989; 218(1): 127–136. PubMed Abstract \| Publisher Full Text\n\nBradshaw H Jr, Schemske DW: Allele substitution at a flower colour locus produces a pollinator shift in monkeyflowers. Nature. 2003; 426(6963): 176–178. Publisher Full Text\n\nBrooks C, Nekrasov V, Lippman ZB, et al.: Efficient gene editing in tomato in the first generation using the clustered regularly interspaced short PALindromic repeats/CRISPR-associated9 system. Plant Physiol. 2014; 166(3): 1292–1297. PubMed Abstract \| Publisher Full Text\n\nBrouillard R, Cheminat A: Flavonoids and plant color. Prog. Clin. Biol. Res. 1988; 280: 93–106.\n\nCai CQ, Doyon Y, Ainley WM, et al.: Targeted transgene integration in plant cells using designed zinc finger nucleases. Plant Mol. Biol. 2009; 69(6): 699–709. PubMed Abstract \| Publisher Full Text\n\nCermak T, Doyle EL, Christian M, et al.: Efficient design and assembly of custom TALEN and other TAL effector-based constructs for DNA targeting. Nucleic Acids Res. 2011; 39(12): e82–e82. PubMed Abstract \| Publisher Full Text\n\nChalker-Scott L: Environmental significance of anthocyanins in plant stress responses. Photochem. Photobiol. 1999; 70(1): 1–9. Publisher Full Text\n\nChandler SF, Sanchez C: Genetic modification; the development of transgenic ornamental plant varieties. Plant Biotechnol. J. 2012; 10(8): 891–903. Publisher Full Text\n\nChandler S, Tanaka Y: Genetic modification in floriculture. Crit. Rev. Plant Sci. 2007; 26(4): 169–197. Publisher Full Text\n\nChar SN, Neelakandan AK, Nahampun H, et al.: An Agrobacterium-delivered CRISPR/Cas9 system for high-frequency targeted mutagenesis in maize. Plant Biotechnol. J. 2017; 15(2): 257–268. PubMed Abstract \| Publisher Full Text\n\nChar SN, Unger-Wallace E, Frame B, et al.: Heritable site-specific mutagenesis using TALEN s in maize. Plant Biotechnol. J. 2015; 13(7): 1002–1010.\n\nChen Y, Wang Z, Ni H, et al.: CRISPR/Cas9-mediated base-editing system efficiently generates gain-of-function mutations in Arabidopsis. Sci. China Life Sci. 2017; 60(5): 520–523. PubMed Abstract \| Publisher Full Text\n\nCherri-Martin M, Jullien F, Heizmann P, et al.: Fragrance heritability in hybrid tea roses. Sci. Hortic. 2007; 113(2): 177–181. Publisher Full Text\n\nChiou C-Y, Wu K, Yeh K-W: Characterization and promoter activity of chromoplast specific carotenoid associated gene (CHRC) from Oncidium Gower Ramsey. Biotechnol. Lett. 2008; 30(10): 1861–1866. PubMed Abstract \| Publisher Full Text\n\nChristian M, Cermak T, Doyle EL, et al.: Targeting DNA double-strand breaks with TAL effector nucleases. Genetics. 2010; 186(2): 757–761. PubMed Abstract \| Publisher Full Text\n\nClasen BM, Stoddard TJ, Luo S, et al.: Improving cold storage and processing traits in potato through targeted gene knockout. Plant Biotechnol. J. 2016; 14(1): 169–176. PubMed Abstract \| Publisher Full Text\n\nClery RA, Owen NE, Chambers SF, et al.: An investigation into the scent of carnations. J. Essent. Oil Res. 1999; 11(3): 355–359. Publisher Full Text\n\nCna'Ani A, Muehlemann JK, Ravid J, et al.: Petunia× hybrida floral scent production is negatively affected by high-temperature growth conditions. Plant Cell Environ. 2015; 38(7): 1333–1346. PubMed Abstract \| Publisher Full Text\n\nColquhoun TA, Clark DG: Unraveling the regulation of floral fragrance biosynthesis. Plant Signal. Behav. 2011; 6(3): 378–381. Publisher Full Text\n\nColquhoun TA, Kim JY, et al.: PhMYB4 fine-tunes the floral volatile signature of Petunia× hybrida through PhC4H. J. Exp. Bot. 2010a; 62(3): 1133–1143. PubMed Abstract \| Publisher Full Text\n\nColquhoun TA, Schimmel BC, Kim JY, et al.: A petunia chorismate mutase specialized for the production of floral volatiles. Plant J. 2010b; 61(1): 145–155. PubMed Abstract \| Publisher Full Text\n\nCong L, Ran FA, Cox D, et al.: Multiplex genome engineering using CRISPR/Cas systems. Science. 2013; 339(6121): 819–823. Publisher Full Text\n\nCourtney-Gutterson N, Napoli C, Lemieux C, et al.: Modification of flower color in florist's chrysanthemum: production of a white–flowering variety through molecular genetics. Bio/Technology. 1994; 12(3): 268–271. PubMed Abstract \| Publisher Full Text\n\nCroteau R, Karp F: Perfume: Art, Science and Technology. Muller PM, Lamparsky D, edtors.Blackie Academic and Professional;London:1991.\n\nCurtin SJ, Zhang F, Sander JD, et al.: Targeted mutagenesis of duplicated genes in soybean with zinc-finger nucleases. Plant Physiol. 2011; 156(2): 466–473. PubMed Abstract \| Publisher Full Text\n\nCvejić S, Jocić S, Mladenović E: Inheritance of floral colour and type in four new inbred lines of ornamental sunflower (Helianthus annuus L.). J. Hortic. Sci. Biotechnol. 2016; 91(1): 30–35. Publisher Full Text\n\nDatsenko KA, Pougach K, Tikhonov A, et al.: Molecular memory of prior infections activates the CRISPR/Cas adaptive bacterial immunity system. Nat. Commun. 2012; 3: 945. PubMed Abstract \| Publisher Full Text\n\nD'Auria JC, Chen F, Pichersky E: Characterization of an acyltransferase capable of synthesizing benzylbenzoate and other volatile esters in flowers and damaged leaves of Clarkia breweri. Plant Physiol. 2002; 130(1): 466–476.\n\nDavies KM, Albert NW, Schwinn KE: From landing lights to mimicry: the molecular regulation of flower colouration and mechanisms for pigmentation patterning. Funct. Plant Biol. 2012; 39(8): 619–638. PubMed Abstract \| Publisher Full Text\n\nDavies KM, Bloor SJ, Spiller GB, et al.: Production of yellow colour in flowers: redirection of flavonoid biosynthesis in Petunia. Plant J. 1998; 13(2): 259–266. Publisher Full Text\n\nDeli J: Isolation of capsanthin 5, 6-epoxide from Lilium tigrinum. Acta Bot. Hung. 1999; 42: 105–110.\n\nDeng D, Yan C, Pan X, et al.: Structural basis for sequence-specific recognition of DNA by TAL effectors. Science. 2012; 335(6069): 720–723. PubMed Abstract \| Publisher Full Text\n\nDewick PM: Medicinal natural products: a biosynthetic approach. John Wiley & Sons;2002.\n\nDexter R, Qualley A, Kish CM, et al.: Characterization of a petunia acetyltransferase involved in the biosynthesis of the floral volatile isoeugenol. Plant J. 2007; 49(2): 265–275. PubMed Abstract \| Publisher Full Text\n\nDixon RA, Achnine L, Kota P, et al.: The phenylpropanoid pathway and plant defence—a genomics perspective. Mol. Plant Pathol. 2002; 3(5): 371–390. PubMed Abstract \| Publisher Full Text\n\nDudareva N, Pichersky E: Biochemical and molecular genetic aspects of floral scents. Plant Physiol. 2000; 122(3): 627–634. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDudareva N, Pichersky E: Biology of floral scent. CRC press;2006a.\n\nDudareva N, Pichersky E: Floral scent metabolic pathways: their regulation and evolution Biology of floral scent. CRC Press;2006b; 69–92.\n\nDudareva N, Pichersky E: Metabolie engineering of floral scent of ornamentals. J. Crop Improv. 2006c; 18(1-2): 325–346. Publisher Full Text\n\nDudareva N, Pichersky E: Metabolic engineering of plant volatiles. Curr. Opin. Biotechnol. 2008; 19(2): 181–189. PubMed Abstract \| Publisher Full Text\n\nDudareva N, Cseke L, Blanc VM, et al.: Evolution of floral scent in Clarkia: novel patterns of S-linalool synthase gene expression in the C. breweri flower. Plant Cell. 1996; 8(7): 1137–1148. PubMed Abstract\n\nDudareva N, D’auria JC, Nam KH, et al.: Acetyl-CoA: benzylalcohol acetyltransferase–an enzyme involved in floral scent production in Clarkia breweri. Plant J. 1998; 14(3): 297–304. Publisher Full Text\n\nDudareva N, Klempien A, Muhlemann JK, et al.: Biosynthesis, function and metabolic engineering of plant volatile organic compounds. New Phytol. 2013; 198(1): 16–32. Publisher Full Text\n\nDudareva N, Martin D, Kish CM, et al.: (E)-β-Ocimene and myrcene synthase genes of floral scent biosynthesis in snapdragon: function and expression of three terpene synthase genes of a new terpene synthase subfamily. Plant Cell. 2003; 15(5): 1227–1241. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDudareva N, Murfitt LM, Mann CJ, et al.: Developmental regulation of methyl benzoate biosynthesis and emission in snapdragon flowers. Plant Cell. 2000; 12(6): 949–961. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDurai S, Mani M, Kandavelou K, et al.: Zinc finger nucleases: custom-designed molecular scissors for genome engineering of plant and mammalian cells. Nucleic Acids Res. 2005; 33(18): 5978–5990. PubMed Abstract \| Publisher Full Text\n\nElomaa P, Honkanen J, Puska R, et al.: Agrobacterium-mediated transfer of antisense chalcone synthase cDNA to Gerbera hybrida inhibits flower pigmentation. Bio/Technology. 1993; 11(4): 508–511. Publisher Full Text\n\nEvenden ML: Biology of Caloptilia fraxinella (Lepidoptera: Gracillariidae) on ornamental green ash, Fraxinus pennsylvanica (Oleaceae). Can. Entomol. 2009; 141(1): 31–39.\n\nFang J, Chai C, Qian Q, et al.: Mutations of genes in synthesis of the carotenoid precursors of ABA lead to pre-harvest sprouting and photo-oxidation in rice. Plant J. 2008; 54(2): 177–189. PubMed Abstract \| Publisher Full Text\n\nFarhi M, Lavie O, Masci T, et al.: Identification of rose phenylacetaldehyde synthase by functional complementation in yeast. Plant Mol. Biol. 2010; 72(3): 235–245. PubMed Abstract \| Publisher Full Text\n\nFeng C, Su H, Bai H, et al.: High-efficiency genome editing using a dmc1 promoter-controlled CRISPR/Cas9 system in maize. Plant Biotechnol. J. 2018; 16(11): 1848–1857. PubMed Abstract \| Publisher Full Text\n\nFeng C, Yuan J, Wang R, et al.: Efficient targeted genome modification in maize using CRISPR/Cas9 system. J. Genet. Genomics. 2016; 43(1): 37–43. PubMed Abstract \| Publisher Full Text\n\nFeng Z, Zhang B, Ding W, et al.: Efficient genome editing in plants using a CRISPR/Cas system. Cell Res. 2013; 23(10): 1229–1232. PubMed Abstract \| Publisher Full Text\n\nFlament I, Debonneville C, Furrer A: Volatile constituents of roses. In “Bioactive Volatile Compounds from Plants. Paper presented at the ACS Symposium Series.1993.\n\nForkmann G: Flavonoids as flower pigments: the formation of the natural spectrum and its extension by genetic engineering. Plant Breed. 1991; 106(1): 1–26. Publisher Full Text\n\nFukusaki E-i, Kawasaki K, et al.: Flower color modulations of Torenia hybrida by downregulation of chalcone synthase genes with RNA interference. J. Biotechnol. 2004a; 111(3): 229–240. PubMed Abstract \| Publisher Full Text\n\nFukusaki E-i, Kawasaki K, Kajiyama S, et al.: Flower color modulations of Torenia hybrida by downregulation of chalcone synthase genes with RNA interference. J. Biotechnol. 2004b; 111(3): 229–240. PubMed Abstract \| Publisher Full Text\n\nGao L, Yang H, Liu H, et al.: Extensive transcriptome changes underlying the flower color intensity variation in Paeonia ostii. Front. Plant Sci. 2016; 6: 1205. Publisher Full Text\n\nGehrke JM, Cervantes O, Clement MK, et al.: An APOBEC3A-Cas9 base editor with minimized bystander and off-target activities. Nat. Biotechnol. 2018; 36(10): 977–982. PubMed Abstract \| Publisher Full Text\n\nGoodhead D: Molecular and cell models of biological effects of heavy ion radiation. Radiat. Environ. Biophys. 1995; 34(2): 67–72. Publisher Full Text\n\nGreen PJ, Pines O, Inouye M: The role of antisense RNA in gene regulation. Annu. Rev. Biochem. 1986; 55(1): 569–597. Publisher Full Text\n\nGriesbach R, Meyer F, Koopowitz H: Creation of new flower colors in Ornithogalum via interspecific hybridization. J. Am. Soc. Hortic. Sci. 1993; 118(3): 409–414. Publisher Full Text\n\nGrotewold E: The genetics and biochemistry of floral pigments. Annu. Rev. Plant Biol. 2006; 57: 761–780. PubMed Abstract \| Publisher Full Text\n\nGuterman I, Shalit M, Menda N, et al.: Rose scent: genomics approach to discovering novel floral fragrance–related genes. Plant Cell. 2002; 14(10): 2325–2338. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGuterman I, Masci T, Chen X, et al.: Generation of phenylpropanoid pathway-derived volatiles in transgenic plants: rose alcohol acetyltransferase produces phenylethyl acetate and benzyl acetate in petunia flowers. Plant Mol. Biol. 2006; 60(4): 555–563. PubMed Abstract \| Publisher Full Text\n\nGutiérrez AMB: Studies on fragrance, vase life and ethylene regulation of volatile production in rose flowers. University of Florida;2009.\n\nGutterson N: Anthocyanin biosynthetic genes and their application to flower color modification through sense suppression. HortScience. 1995; 30(5): 964–966. Publisher Full Text\n\nHall CR, Dickson MW: Economic, environmental, and health/well-being benefits associated with green industry products and services: A review. J. Environ. Hortic. 2011; 29(2): 96–103. Publisher Full Text\n\nHall CR, Hodges A: Economic, environmental and well-being benefits of lifestyle horticulture. Chronica Horticulturae. 2011; 51(4): 5–8.\n\nHammond J: Current status of genetically modified ornamentals. Paper presented at the XI International Symposium on Virus Diseases of Ornamental Plants 722.2004.\n\nHanumappa M, Choi G, Ryu S, et al.: Modulation of flower colour by rationally designed dominant-negative chalcone synthase. J. Exp. Bot. 2007; 58(10): 2471–2478. Publisher Full Text\n\nHarborne JB, Williams CA: Advances in flavonoid research since 1992. Phytochemistry. 2000; 55(6): 481–504. PubMed Abstract \| Publisher Full Text\n\nHase Y, Okamura M, Takeshita D, et al.: Efficient induction of flower-color mutants by ion beam irradiation in petunia seedlings treated with high sucrose concentration. Plant Biotechnol. 2010; 27(1): 99–103. Publisher Full Text\n\nHaun W, Coffman A, Clasen BM, et al.: Improved soybean oil quality by targeted mutagenesis of the fatty acid desaturase 2 gene family. Plant Biotechnol. J. 2014; 12(7): 934–940. PubMed Abstract \| Publisher Full Text\n\nHe Q, Shen Y, Wang M, et al.: Natural variation in petal color in Lycoris longituba revealed by anthocyanin components. PLoS One. 2011; 6(8): e22098. PubMed Abstract \| Publisher Full Text\n\nHelsper JP, Davies JA, Bouwmeester HJ, et al.: Circadian rhythmicity in emission of volatile compounds by flowers of Rosa hybrida L. cv. Honesty. Planta. 1998; 207(1): 88–95. Publisher Full Text\n\nHendel-Rahmanim K, Masci T, Vainstein A, et al.: Diurnal regulation of scent emission in rose flowers. Planta. 2007; 226(6): 1491–1499. PubMed Abstract \| Publisher Full Text\n\nHerrmann KM, Weaver LM: The shikimate pathway. Annu. Rev. Plant Biol. 1999; 50(1): 473–503. Publisher Full Text\n\nHichri I, Barrieu F, Bogs J, et al.: Recent advances in the transcriptional regulation of the flavonoid biosynthetic pathway. J. Exp. Bot. 2011; 62(8): 2465–2483. PubMed Abstract \| Publisher Full Text\n\nHoglund EB, Carlsson J, Stenerlow B, et al.: DNA damage induced by radiation of different linear energy transfer: initial fragmentation. Int. J. Radiat. Biol. 2000; 76(4): 539–547. PubMed Abstract \| Publisher Full Text\n\nHolton TA, Brugliera F, Lester DR, et al.: Cloning and expression of cytochrome P450 genes controlling flower colour. Nature. 1993; 366(6452): 276–279. PubMed Abstract \| Publisher Full Text\n\nHua K, Tao X, Zhu JK: Expanding the base editing scope in rice by using Cas9 variants. Plant Biotechnol. J. 2019; 17(2): 499–504. PubMed Abstract \| Publisher Full Text\n\nHua K, Tao X, Yuan F, et al.: Precise A· T to G· C base editing in the rice genome. Mol. Plant. 2018; 11(4): 627–630. PubMed Abstract \| Publisher Full Text\n\nIshizaka H: Breeding of fragrant cyclamen by interspecific hybridization and ion-beam irradiation. Breed. Sci. 2018; 68(1): 25–34. PubMed Abstract \| Publisher Full Text\n\nIshizaka H, Kondo E, Kameari N: Production of novel flower color mutants from the fragrant cyclamen (Cyclamen persicum× C. purpurascens) by ion-beam irradiation. Plant Biotechnol. 2012; 12(0116): a.\n\nIto Y, Nishizawa-Yokoi A, Endo M, et al.: CRISPR/Cas9-mediated mutagenesis of the RIN locus that regulates tomato fruit ripening. Biochem. Biophys. Res. Commun. 2015; 467(1): 76–82. PubMed Abstract \| Publisher Full Text\n\nJakobsen HB, Olsen CE: Influence of climatic factors on emission of flower volatiles in situ. Planta. 1994; 192(3): 365–371. Publisher Full Text\n\nJin S, Zong Y, Gao Q, et al.: Cytosine, but not adenine, base editors induce genome-wide off-target mutations in rice. Science. 2019; 364(6437): 292–295. Publisher Full Text\n\nJinek M, Chylinski K, Fonfara I, et al.: A programmable dual-RNA–guided DNA endonuclease in adaptive bacterial immunity. Science. 2012; 337(6096): 816–821. PubMed Abstract \| Publisher Full Text\n\nJo YD, Kim Y-S, Ryu J, et al.: Deletion of carotenoid cleavage dioxygenase 4a (CmCCD4a) and global up-regulation of plastid protein-coding genes in a mutant chrysanthemum cultivar producing yellow petals. Sci. Hortic. 2016; 212: 49–59. Publisher Full Text\n\nJoung JK, Sander JD: TALENs: a widely applicable technology for targeted genome editing. Nat. Rev. Mol. Cell Biol. 2013; 14(1): 49–55. PubMed Abstract \| Publisher Full Text\n\nKamiishi Y, Otani M, Takagi H, et al.: Flower color alteration in the liliaceous ornamental Tricyrtis sp. by RNA interference-mediated suppression of the chalcone synthase gene. Mol. Breed. 2012; 30(2): 671–680. Publisher Full Text\n\nKaminaga Y, Schnepp J, et al.: Phenylacetaldehyde synthase from Petunia hybrida is a biofunctional enzyme that catalyzes the efficient coupling of phenylalanine decarboxylation to phenylalanine oxidation. J. Biol. Chem. 2006a; 281(33): 23357–23366. PubMed Abstract \| Publisher Full Text\n\nKaminaga Y, Schnepp J, Peel G, et al.: Plant phenylacetaldehyde synthase is a bifunctional homotetrameric enzyme that catalyzes phenylalanine decarboxylation and oxidation. J. Biol. Chem. 2006b; 281(33): 23357–23366. PubMed Abstract \| Publisher Full Text\n\nKarkute SG, Singh AK, Gupta OP, et al.: CRISPR/Cas9 mediated genome engineering for improvement of horticultural crops. Front. Plant Sci. 2017; 8: 1635. PubMed Abstract \| Publisher Full Text\n\nKatsumoto Y, Fukuchi-Mizutani M, Fukui Y, et al.: Engineering of the rose flavonoid biosynthetic pathway successfully generated blue-hued flowers accumulating delphinidin. Plant Cell Physiol. 2007; 48(11): 1589–1600. PubMed Abstract \| Publisher Full Text\n\nKeykha F, Bagheri A, Moshtaghi N, et al.: RNAi-induced silencing in floral tissues of Petunia hybrida by agroinfiltration: a rapid assay for chalcone isomerase gene function analysis. Cell. Mol. Biol. 2016; 62(10): 26–31. PubMed Abstract\n\nKhan Z, Khan SH, Mubarik MS, et al.: Targeted Genome Editing for Cotton Improvement. Past, Present and Future Trends in Cotton Breeding. 2018: 11. Publisher Full Text\n\nKhan Z, Khan SH, Mubarik MS, et al.: Use of TALEs and TALEN technology for genetic improvement of plants. Plant Mol. Biol. Report. 2017; 35(1): 1–19. Publisher Full Text\n\nKim Y-G, Chandrasegaran S: Chimeric restriction endonuclease. Proc. Natl. Acad. Sci. 1994; 91(3): 883–887. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKishimoto K, Nakayama M, Yagi M, et al.: Evaluation of wild Dianthus species as genetic resources for fragrant carnation breeding based on their floral scent composition. J. Jpn. Soc. Hortic. Sci. 2011; 80(2): 175–181. Publisher Full Text\n\nKishimoto K, Yagi M, Onozaki T, et al.: Analysis of scents emitted from flowers of interspecific hybrids between carnation and fragrant wild Dianthus species. J. Jpn. Soc. Hortic. Sci. 2013; 82(2): 145–153. Publisher Full Text\n\nKnudsen JT, Eriksson R, Gershenzon J, et al.: Diversity and distribution of floral scent. Bot. Rev. 2006; 72(1): 1–120. Publisher Full Text\n\nKolosova N, Gorenstein N, Kish CM, et al.: Regulation of circadian methyl benzoate emission in diurnally and nocturnally emitting plants. Plant Cell. 2001; 13(10): 2333–2347. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKomor AC, Kim YB, Packer MS, et al.: Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature. 2016; 533(7603): 420–424. PubMed Abstract \| Publisher Full Text\n\nKomor AC, Zhao KT, Packer MS, et al.: Improved base excision repair inhibition and bacteriophage Mu Gam protein yields C: G-to-T: A base editors with higher efficiency and product purity. Sci. Adv. 2017; 3(8): eaao4774. PubMed Abstract \| Publisher Full Text\n\nKondo E, Nakayama M, Kameari N, et al.: Red-purple flower due to delphinidin 3,5-diglucoside, a novel pigment for Cyclamen spp., generated by ion-beam irradiation. Plant Biotechnol. 2009; 26(5): 565–569. Publisher Full Text\n\nKong Y, Sun M, Pan H-T, et al.: Composition and emission rhythm of floral scent volatiles from eight lily cut flowers. J. Am. Soc. Hortic. Sci. 2012; 137(6): 376–382. Publisher Full Text\n\nLai Y-S, Yamagishi M, Suzuki T: Elevated temperature inhibits anthocyanin biosynthesis in the tePALs of an Oriental hybrid lily via the suppression of LhMYB 12 transcription. Sci. Hortic. 2011; 132: 59–65. Publisher Full Text\n\nLavid N, Wang J, Shalit M, et al.: O-methyltransferases involved in the biosynthesis of volatile phenolic derivatives in rose petals. Plant Physiol. 2002; 129(4): 1899–1907. PubMed Abstract \| Publisher Full Text\n\nLavy M, Zuker A, Lewinsohn E, et al.: Linalool and linalool oxide production in transgenic carnation flowers expressing the Clarkia breweri linalool synthase gene. Mol. Breed. 2002; 9(2): 103–111. Publisher Full Text\n\nLee J, Sugawara E, Yokoi S, et al.: Genotypic variation of volatile compounds from flowers of gentians. Breed. Sci. 2010; 60(1): 9–17. Publisher Full Text\n\nLi C, Zong Y, Wang Y, et al.: Expanded base editing in rice and wheat using a Cas9-adenosine deaminase fusion. Genome Biol. 2018; 19(1): 59. PubMed Abstract \| Publisher Full Text\n\nLi J, Meng X, Zong Y, et al.: Gene replacements and insertions in rice by intron targeting using CRISPR-Cas9. Nat Plants. 2016; 2: 16139. PubMed Abstract \| Publisher Full Text\n\nLi J, Sun Y, Du J, et al.: Generation of targeted point mutations in rice by a modified CRISPR/Cas9 system. Mol. Plant. 2017; 10(3): 526–529. Publisher Full Text\n\nLi J-F, Norville JE, Aach J, et al.: Multiplex and homologous recombination–mediated genome editing in Arabidopsis and Nicotiana benthamiana using guide RNA and Cas9. Nat. Biotechnol. 2013; 31(8): 688–691. PubMed Abstract \| Publisher Full Text\n\nLi Q, Wang J, Sun H-Y, et al.: Flower color patterning in pansy (Viola× wittrockiana Gams.) is caused by the differential expression of three genes from the anthocyanin pathway in acyanic and cyanic flower areas. Plant Physiol. Biochem. 2014; 84: 134–141. PubMed Abstract \| Publisher Full Text\n\nLi T, Huang S, Zhao X, et al.: Modularly assembled designer TAL effector nucleases for targeted gene knockout and gene replacement in eukaryotes. Nucleic Acids Res. 2011; 39(14): 6315–6325. PubMed Abstract \| Publisher Full Text\n\nLi T, Liu B, SPALding MH, et al.: High-efficiency TALEN-based gene editing produces disease-resistant rice. Nat. Biotechnol. 2012; 30(5): 390–392. PubMed Abstract \| Publisher Full Text\n\nLi Z, Zhao M, Jin J, et al.: Anthocyanins and their biosynthetic genes in three novel-colored Rosa rugosa cultivars and their parents. Plant Physiol. Biochem. 2018b; 129: 421–428. PubMed Abstract \| Publisher Full Text\n\nLiang Z, Chen K, Li T, et al.: Efficient DNA-free genome editing of bread wheat using CRISPR/Cas9 ribonucleoprotein complexes. Nat. Commun. 2017; 8: 14261. PubMed Abstract \| Publisher Full Text\n\nLieber MR: The mechanism of double-strand DNA break repair by the nonhomologous DNA end-joining pathway. Annu. Rev. Biochem. 2010; 79: 181–211. PubMed Abstract \| Publisher Full Text\n\nLor VS, Starker CG, Voytas DF, et al.: Targeted mutagenesis of the tomato PROCERA gene using transcription activator-like effector nucleases. Plant Physiol. 2014; 166(3): 1288–1291. Publisher Full Text\n\nLu Y, Zhu J-K: Precise editing of a target base in the rice genome using a modified CRISPR/Cas9 system. Mol. Plant. 2017; 10(3): 523–525. PubMed Abstract \| Publisher Full Text\n\nLücker J, Bouwmeester HJ, Schwab W, et al.: Expression of Clarkia S-linalool synthase in transgenic petunia plants results in the accumulation of S-linalyl-β-d-glucopyranoside. Plant J. 2001; 27(4): 315–324. PubMed Abstract \| Publisher Full Text\n\nMaeda H, Dudareva N: The shikimate pathway and aromatic amino acid biosynthesis in plants. Annu. Rev. Plant Biol. 2012; 63: 73–105. Publisher Full Text\n\nMaeda H, Shasany AK, Schnepp J, et al.: RNAi suppression of Arogenate Dehydratase1 reveals that phenylalanine is synthesized predominantly via the arogenate pathway in petunia petals. Plant Cell. 2010; 22(3): 832–849. PubMed Abstract \| Publisher Full Text\n\nMagnard J-L, Roccia A, Caissard J-C, et al.: Biosynthesis of monoterpene scent compounds in roses. Science. 2015; 349(6243): 81–83. PubMed Abstract \| Publisher Full Text\n\nMahfouz MM, Li L, Shamimuzzaman M, et al.: De novo-engineered transcription activator-like effector (TALE) hybrid nuclease with novel DNA binding specificity creates double-strand breaks. Proc. Natl. Acad. Sci. 2011; 108(6): 2623–2628. PubMed Abstract \| Publisher Full Text\n\nMakarova KS, Wolf YI, Alkhnbashi OS, et al.: An updated evolutionary classification of CRISPR–Cas systems. Nat. Rev. Microbiol. 2015; 13(11): 722–736. PubMed Abstract \| Publisher Full Text\n\nMartin C, Prescott A, Mackay S, et al.: Control of anthocyanin biosynthesis in flowers of Antirrhinum majus. Plant J. 1991; 1(1): 37–49. PubMed Abstract \| Publisher Full Text\n\nMatsumura A, Nomizu T, Furutani N, et al.: Ray florets color and shape mutants induced by 12C5+ ion beam irradiation in chrysanthemum. Sci. Hortic. 2010; 123(4): 558–561. Publisher Full Text\n\nMeyer P, Heidmann I, Forkmann G, et al.: A new petunia flower colour generated by transformation of a mutant with a maize gene. Nature. 1987; 330(6149): 677–678. PubMed Abstract \| Publisher Full Text\n\nMiki D, Zhang W, Zeng W, et al.: CRISPR/Cas9-mediated gene targeting in Arabidopsis using sequential transformation. Nat. Commun. 2018; 9(1): 1967. PubMed Abstract \| Publisher Full Text\n\nMiles HW: The sawflies that infest ornamental plants. Sci. Hortic. 1962; 16: 22–30.\n\nMishra R, Zhao K: Genome editing technologies and their applications in crop improvement. Plant Biotechnol. Rep. 2018; 12(2): 57–68. Publisher Full Text\n\nMiyazaki K, Suzuki K-I, Iwaki K, et al.: Flower pigment mutations induced by heavy ion beam irradiation in an interspecific hybrid of Torenia. Plant Biotechnology. 2006; 23(2): 163–167. Publisher Full Text\n\nMorita Y, Saitoh M, Hoshino A, et al.: Isolation of cDNAs for R2R3-MYB, bHLH and WDR transcriptional regulators and identification of c and ca mutations conferring white flowers in the Japanese morning glory. Plant Cell Physiol. 2006; 47(4): 457–470. PubMed Abstract \| Publisher Full Text\n\nMoscou MJ, Bogdanove AJ: A simple cipher governs DNA recognition by TAL effectors. Science. 2009; 326(5959): 1501–1501. PubMed Abstract \| Publisher Full Text\n\nNagegowda DA, Gutensohn M, Wilkerson CG, et al.: Two nearly identical terpene synthases catalyze the formation of nerolidol and linalool in snapdragon flowers. Plant J. 2008; 55(2): 224–239. PubMed Abstract \| Publisher Full Text\n\nNaing AH, Kim CK: Roles of R2R3-MYB transcription factors in transcriptional regulation of anthocyanin biosynthesis in horticultural plants. Plant Mol. Biol. 2018; 98(1-2): 1–18. PubMed Abstract \| Publisher Full Text\n\nNakamura N, Fukuchi-Mizutani M, Miyazaki K, et al.: RNAi suppression of the anthocyanidin synthase gene in Torenia hybrida yields white flowers with higher frequency and better stability than antisense and sense suppression. Plant Biotechnol. 2006; 23(1): 13–17. Publisher Full Text\n\nNakamura N, Fukuchi-Mizutani M, et al.: Generation of pink flower varieties from blue Torenia hybrida by redirecting the flavonoid biosynthetic pathway from delphinidin to pelargonidin. Plant Biotechnology. 2010; 27(5): 375–383. Publisher Full Text\n\nNakamura N, Katsumoto Y, et al.: Flower color modification in Rosa hybrida by expressing the S-adenosylmethionine: anthocyanin 3′, 5′-O-methyltransferase gene from Torenia hybrida. Plant Biotechnol. 2015; 32(2): 109–117. Publisher Full Text\n\nNakatsuka T, Haruta KS, Pitaksutheepong C, et al.: Identification and characterization of R2R3-MYB and bHLH transcription factors regulating anthocyanin biosynthesis in gentian flowers. Plant Cell Physiol. 2008a; 49(12): 1818–1829. PubMed Abstract \| Publisher Full Text\n\nNakatsuka T, Mishiba K-I, Abe Y, et al.: Flower color modification of gentian plants by RNAi-mediated gene silencing. Plant Biotechnol. 2008b; 25(1): 61–68. Publisher Full Text\n\nNakatsuka T, Mishiba K-I, Kubota A, et al.: Genetic engineering of novel flower colour by suppression of anthocyanin modification genes in gentian. J. Plant Physiol. 2010; 167(3): 231–237. PubMed Abstract \| Publisher Full Text\n\nNakatsuka T, Nishihara M, Mishiba K, et al.: Temporal expression of flavonoid biosynthesis-related genes regulates flower pigmentation in gentian plants. Plant Sci. 2005; 168(5): 1309–1318. Publisher Full Text\n\nNakatsuka T, Sato K, Takahashi H, et al.: Cloning and characterization of the UDP-glucose: anthocyanin 5-O-glucosyltransferase gene from blue-flowered gentian. J. Exp. Bot. 2008c; 59(6): 1241–1252. PubMed Abstract \| Publisher Full Text\n\nNakayama M, Tanikawa N, Morita Y, et al.: Comprehensive analyses of anthocyanin and related compounds to understand flower color change in ion-beam mutants of cyclamen (Cyclamen spp.) and carnation (Dianthus caryophyllus). Plant Biotechnol. 2012; 12(0102): a.\n\nNakayama T, Yonekura-Sakakibara K, Sato T, et al.: Aureusidin synthase: a polyphenol oxidase homolog responsible for flower coloration. Science. 2000; 290(5494): 1163–1166. PubMed Abstract \| Publisher Full Text\n\nNapoli C, Lemieux C, Jorgensen R: Introduction of a chimeric chalcone synthase gene into petunia results in reversible co-suppression of homologous genes in trans. Plant Cell. 1990; 2(4): 279–289. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNegre F, Kish CM, Boatright J, et al.: Regulation of methylbenzoate emission after pollination in snapdragon and petunia flowers. Plant Cell. 2003; 15(12): 2992–3006. PubMed Abstract \| Publisher Full Text\n\nNegre F, Kolosova N, Knoll J, et al.: Novel S-adenosyl-L-methionine: salicylic acid carboxyl methyltransferase, an enzyme responsible for biosynthesis of methyl salicylate and methyl benzoate, is not involved in floral scent production in snapdragon flowers. Arch. Biochem. Biophys. 2002; 406(2): 261–270. PubMed Abstract \| Publisher Full Text\n\nNekrasov V, Staskawicz B, Weigel D, et al.: Targeted mutagenesis in the model plant Nicotiana benthamiana using Cas9 RNA-guided endonuclease. Nat. Biotechnol. 2013; 31(8): 691–693. PubMed Abstract \| Publisher Full Text\n\nNemudryi A, Valetdinova K, Medvedev S, et al.: TALEN and CRISPR/Cas genome editing systems: tools of discovery. Acta Naturae (англоязычная версия). 2014; 6(3 (22)): 19–40. Publisher Full Text\n\nNielsen K, Deroles SC, Markham KR, et al.: Antisense flavonol synthase alters copigmentation and flower color in lisianthus. Mol. Breed. 2002; 9(4): 217–229. Publisher Full Text\n\nNishihara M, Nakatsuka T: Genetic engineering of novel flower colors in floricultural plants: Recent advances via transgenic approaches Protocols for in vitro propagation of ornamental plants. Springer;2010; 325–347.\n\nNishihara M, Higuchi A, Watanabe A, et al.: Application of the CRISPR/Cas9 system for modification of flower color in Torenia fournieri. BMC Plant Biol. 2018; 18(1): 331. PubMed Abstract \| Publisher Full Text\n\nNissim-Levi A, Ovadia R, Forer I, et al.: Increased anthocyanin accumulation in ornamental plants due to magnesium treatment. J. Hortic. Sci. Biotechnol. 2007; 82(3): 481–487.\n\nNoman A, Aqeel M, Deng J, et al.: Biotechnological advancements for improving floral attributes in ornamental plants. Front. Plant Sci. 2017; 8: 530. Publisher Full Text\n\nOhmiya A, Kishimoto S, Aida R, et al.: Carotenoid cleavage dioxygenase (CmCCD4a) contributes to white color formation in chrysanthemum petals. Plant Physiol. 2006; 142(3): 1193–1201. PubMed Abstract \| Publisher Full Text\n\nOliva M, Ovadia R, Perl A, et al.: Enhanced formation of aromatic amino acids increases fragrance without affecting flower longevity or pigmentation in Petunia× hybrida. Plant Biotechnol. J. 2015; 13(1): 125–136. PubMed Abstract \| Publisher Full Text\n\nOrlova I, Marshall-Colón A, Schnepp J, et al.: Reduction of benzenoid synthesis in petunia flowers reveals multiple pathways to benzoic acid and enhancement in auxin transport. Plant Cell. 2006; 18(12): 3458–3475. PubMed Abstract \| Publisher Full Text\n\nPan C, Ye L, Qin L, et al.: CRISPR/Cas9-mediated efficient and heritable targeted mutagenesis in tomato plants in the first and later generations. Sci. Rep. 2016; 6: 24765. PubMed Abstract \| Publisher Full Text\n\nPellmyr O, Thien LB: Insect reproduction and floral fragrances: keys to the evolution of the angiosperms? Taxon. 1986; 35(1): 76–85.\n\nPeronti AL, Sousa-Silva CR: Aphids (Hemiptera: Aphidoidea) of ornamental plants from São Carlos, São Paulo state, Brazil. Rev. Biol. Trop. 2002;50(1): 137–144.\n\nPetersen B, Niemann H: Molecular scissors and their application in genetically modified farm animals. Transgenic Res. 2015; 24(3): 381–396. PubMed Abstract \| Publisher Full Text\n\nPfeiffer M, Quetier F, Ricroch A: Genome Editing in Agricultural Biotechnology Advances in Botanical Research. vol. 86:2018; Elsevier: 245–286.\n\nPichersky E, Noel JP, Dudareva N: Biosynthesis of plant volatiles: nature's diversity and ingenuity. Science. 2006; 311(5762): 808–811. PubMed Abstract \| Publisher Full Text\n\nPiechulla B, Pott MB: Plant scents—mediators of inter-and intraorganismic communication. Planta. 2003; 217(5): 687–689. PubMed Abstract \| Publisher Full Text\n\nPompelli M, De Brito G, Otoni W, et al.: Biotechnologies for ornamental plants: some insights to the Brazilian productive chain. International Journal of Horticultural Science. 2007; 13(1): 51–59. Publisher Full Text\n\nPuchta H: The repair of double-strand breaks in plants: mechanisms and consequences for genome evolution. J. Exp. Bot. 2004; 56(409): 1–14. PubMed Abstract \| Publisher Full Text\n\nQue Q, Wang H-Y, English JJ, et al.: The frequency and degree of cosuppression by sense chalcone synthase transgenes are dependent on transgene promoter strength and are reduced by premature nonsense codons in the transgene coding sequence. Plant Cell. 1997; 9(8): 1357–1368. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRoss JR, Nam KH, D'Auria JC, et al.: S-adenosyl-L-methionine: salicylic acid carboxyl methyltransferase, an enzyme involved in floral scent production and plant defense, represents a new class of plant methyltransferases. Arch. Biochem. Biophys. 1999; 367(1): 9–16. PubMed Abstract \| Publisher Full Text\n\nRuban AV, Berera R, Ilioaia C, et al.: Identification of a mechanism of photoprotective energy dissipation in higher plants. Nature. 2007; 450(7169): 575–578. PubMed Abstract \| Publisher Full Text\n\nSander JD, Maeder ML, Reyon D, et al.: ZiFiT (Zinc Finger Targeter): an updated zinc finger engineering tool. Nucleic Acids Res. 2010; 38(suppl_2): W462–W468. PubMed Abstract \| Publisher Full Text\n\nScalliet G, Piola F, Douady CJ, et al.: Scent evolution in Chinese roses. Proc. Natl. Acad. Sci. 2008; 105(15): 5927–5932. PubMed Abstract \| Publisher Full Text\n\nSchade F, Legge RL, Thompson JE: Fragrance volatiles of developing and senescing carnation flowers. Phytochemistry. 2001; 56(7): 703–710. PubMed Abstract \| Publisher Full Text\n\nSchaeffer SM, Nakata PA: CRISPR/Cas9-mediated genome editing and gene replacement in plants: transitioning from lab to field. Plant Sci. 2015; 240: 130–142. PubMed Abstract \| Publisher Full Text\n\nSchneider K, Schiermeyer A, Dolls A, et al.: Targeted gene exchange in plant cells mediated by a zinc finger nuclease double cut. Plant Biotechnol. J. 2016; 14(4): 1151–1160. PubMed Abstract \| Publisher Full Text\n\nScholze H, Boch J: TAL effectors are remote controls for gene activation. Curr. Opin. Microbiol. 2011; 14(1): 47–53. PubMed Abstract \| Publisher Full Text\n\nSchuurink RC, Haring MA, Clark DG: Regulation of volatile benzenoid biosynthesis in petunia flowers. Trends Plant Sci. 2006; 11(1): 20–25. Publisher Full Text\n\nSchwinn KE, Boase MR, Bradley JM, et al.: MYB and bHLH transcription factor transgenes increase anthocyanin pigmentation in petunia and lisianthus plants, and the petunia phenotypes are strongly enhanced under field conditions. Front. Plant Sci. 2014; 5: 603. Publisher Full Text\n\nSeitz C, Vitten M, Steinbach P, et al.: Redirection of anthocyanin synthesis in Osteospermum hybrida by a two-enzyme manipulation strategy. Phytochemistry. 2007; 68(6): 824–833. PubMed Abstract \| Publisher Full Text\n\nSeneviratne K, Wijesundara D: First African violets (Saintpaulia ionantha H. Wendl.) with a changing colour pattern induced by mutation. American. J. Plant Physiol. 2007; 2(3): 233–236. Publisher Full Text\n\nShalit M, Guterman I, Volpin H, et al.: Volatile ester formation in roses. Identification of an acetyl-coenzyme A. Geraniol/citronellol acetyltransferase in developing rose petals. Plant Physiol. 2003; 131(4): 1868–1876. PubMed Abstract \| Publisher Full Text\n\nShalit M, Shafir S, Larkov O, et al.: Volatile compounds emitted by rose cultivars: fragrance perception by man and honeybees. Isr. J. Plant Sci. 2004; 52(3): 245–255. Publisher Full Text\n\nShan Q, Zhang Y, Chen K, et al.: Creation of fragrant rice by targeted knockout of the Os BADH 2 gene using TALEN technology. Plant Biotechnol. J. 2015; 13(6): 791–800. PubMed Abstract \| Publisher Full Text\n\nShi J, Gao H, Wang H, et al.: ARGOS 8 variants generated by CRISPR-Cas9 improve maize grain yield under field drought stress conditions. Plant Biotechnol. J. 2017; 15(2): 207–216. PubMed Abstract \| Publisher Full Text\n\nShi Q, Zhou L, Wang Y, et al.: Transcriptomic analysis of Paeonia delavayi wild population flowers to identify differentially expressed genes involved in purple-red and yellow petal pigmentation. PLoS One. 2015; 10(8): e0135038. PubMed Abstract \| Publisher Full Text\n\nShibata M: Importance of genetic transformation in ornamental plant breeding. Plant Biotechnol. 2008; 25(1): 3–8. Publisher Full Text\n\nShikata M, Ohme-Takagi M: The utility of transcription factors for manipulation of floral traits. Plant Biotechnol. 2008; 25(1): 31–36. Publisher Full Text\n\nSimala M, Milek TM, Korić B: Whitefly species (Hemiptera: Aleyrodidae) recorded on imported ornamental plants in Croatia from 2005–2008. Zbornik predavanj in referatov. 2009; 9: 389–396.\n\nShimatani Z, Kashojiya S, Takayama M, et al.: Targeted base editing in rice and tomato using a CRISPR-Cas9 cytidine deaminase fusion. Nat. Biotechnol. 2017; 35(5): 441–443. PubMed Abstract \| Publisher Full Text\n\nSimkin AJ, Underwood BA, Auldridge M, et al.: Circadian regulation of the PhCCD1 carotenoid cleavage dioxygenase controls emission of β-ionone, a fragrance volatile of petunia flowers. Plant Physiol. 2004; 136(3): 3504–3514. PubMed Abstract \| Publisher Full Text\n\nSongstad DD, Petolino J, Voytas DF, et al.: Genome editing of plants. Crit. Rev. Plant Sci. 2017; 36(1): 1–23. Publisher Full Text\n\nSovová T, Kerins G, Demnerová K, et al.: Genome editing with engineered nucleases in economically important animals and plants: state of the art in the research pipeline. Curr. Issues Mol. Biol. 2016; 21(21): 41–62.\n\nSpitzer-Rimon B, Farhi M, Albo B, et al.: The R2R3-MYB –like regulatory factor EOBI, acting downstream of EOBII, regulates scent production by activating ODO1 and structural scent-related genes in petunia. Plant Cell. 2012; 24(12): 5089–5105. PubMed Abstract \| Publisher Full Text\n\nSpitzer-Rimon B, Marhevka E, Barkai O, et al.: EOBII, a gene encoding a flower-specific regulator of phenylpropanoid volatiles' biosynthesis in petunia. Plant Cell. 2010; 22(6): 1961–1976. PubMed Abstract \| Publisher Full Text\n\nSteyn W, Wand S, Holcroft D, et al.: Anthocyanins in vegetative tissues: a proposed unified function in photoprotection. New Phytol. 2002; 155(3): 349–361. PubMed Abstract \| Publisher Full Text\n\nSubburaj S, Jeon Y-S, Tu L, et al.: CRISPR/Cas9-mediated Mutagenesis of the Flavanone 3-hydroxylase (F3H) Locus in the Petunia× hybrida. 한국원예학회학술발표요지. 2018: 178–178.\n\nSun W, Meng X, Liang L, et al.: Overexpression of a Freesia hybrida flavonoid 3-O-glycosyltransferase gene, Fh3GT1, enhances transcription of key anthocyanin genes and accumulation of anthocyanin and flavonol in transgenic petunia (Petunia hybrida). In Vitro Cell. Dev. Biol. Plant. 2017; 53(5): 478–488. Publisher Full Text\n\nSuzuki K-I, Xue H-M, Tanaka Y, et al.: Flower color modifications of Torenia hybrida by cosuppression of anthocyanin biosynthesis genes. Mol. Breed. 2000; 6(3): 239–246. Publisher Full Text\n\nSvitashev S, Schwartz C, Lenderts B, et al.: Genome editing in maize directed by CRISPR–Cas9 ribonucleoprotein complexes. Nat. Commun. 2016; 7: 13274. PubMed Abstract \| Publisher Full Text\n\nSymington LS, Gautier J: Double-strand break end resection and repair pathway choice. Annu. Rev. Genet. 2011; 45: 247–271. Publisher Full Text\n\nTakeda K: Blue metal complex pigments involved in blue flower color. Proceedings of the Japan Academy, Series B. 2006; 82(4): 142–154. Publisher Full Text\n\nTanaka A: Targeted mutation breeding of flower color by taking advantage of ion-beam irradiation and genomic information. Plant Biotechnology. 2012; 29(3): 191–192. Publisher Full Text\n\nTanaka Y, Katsumoto Y, Brugliera F, et al.: Genetic engineering in floriculture. Plant Cell Tissue Organ Cult. 2005; 80(1): 1–24. Publisher Full Text\n\nTanaka Y, Sasaki N, Ohmiya A: Biosynthesis of plant pigments: anthocyanins, betalains and carotenoids. Plant J. 2008; 54(4): 733–749. PubMed Abstract \| Publisher Full Text\n\nTatsuzawa F, Tanikawa N, Nakayama M: Red-purple flower color and delphinidin-type pigments in the flowers of Pueraria lobata (Leguminosae). Phytochemistry. 2017; 137: 52–56. Publisher Full Text\n\nTeppabut Y, Oyama K-I, Kondo T, et al.: Change of Petals′ Color and Chemical Components in Oenothera Flowers during Senescence. Molecules. 2018; 23(7): 1698. PubMed Abstract \| Publisher Full Text\n\nTholl D: Terpene synthases and the regulation, diversity and biological roles of terpene metabolism. Curr. Opin. Plant Biol. 2006; 9(3): 297–304. PubMed Abstract \| Publisher Full Text\n\nTrapp SC, Croteau RB: Genomic organization of plant terpene synthases and molecular evolutionary implications. Genetics. 2001; 158(2): 811–832. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTsuma M, Ito A, Mizuta D, et al.: Effect of anthocyanin profile and petal pH on flower coloration in evergreen azalea. Paper presented at the XXIX International Horticultural Congress on Horticulture: Sustaining Lives, Livelihoods and Landscapes (IHC2014): 1104.2014.\n\nTzin V, Galili G: New insights into the shikimate and aromatic amino acids biosynthesis pathways in plants. Mol. Plant. 2010; 3(6): 956–972. PubMed Abstract \| Publisher Full Text\n\nTzin V, Galili G, Aharoni A: Shikimate pathway and aromatic amino acid biosynthesis. e LS. 2001.\n\nUeyama Y, Katsumoto Y, Fukui Y, et al.: Molecular characterization of the flavonoid biosynthetic pathway and flower color modification of Nierembergia sp. Plant Biotechnology. 2006; 23(1): 19–24. Publisher Full Text\n\nUnderwood BA, Tieman DM, Shibuya K, et al.: Ethylene-regulated floral volatile synthesis in petunia corollas. Plant Physiol. 2005; 138(1): 255–266. PubMed Abstract \| Publisher Full Text\n\nUnniyampurath U, Pilankatta R, Krishnan M: RNA Interference in the age of CRISPR: will CRISPR interfere with RNAi? Int. J. Mol. Sci. 2016; 17(3): 291. PubMed Abstract \| Publisher Full Text\n\nVainstein A, Lewinsohn E, Pichersky E, et al.: Floral fragrance. New inroads into an old commodity. Plant Physiol. 2001; 127(4): 1383–1389. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nVan der Krol AR, Lenting PE, Veenstra J, et al.: An anti-sense chalcone synthase gene in transgenic plants inhibits flower pigmentation. Nature. 1988; 333(6176): 866–869. Publisher Full Text\n\nVan der Krol AR, Mur LA, Beld M, et al.: Flavonoid genes in petunia: addition of a limited number of gene copies may lead to a suppression of gene expression. Plant Cell. 1990; 2(4): 291–299. PubMed Abstract \| Publisher Full Text\n\nVan Der Oost J, Westra ER, Jackson RN, et al.: Unravelling the structural and mechanistic basis of CRISPR–Cas systems. Nat. Rev. Microbiol. 2014; 12(7): 479–492. PubMed Abstract \| Publisher Full Text\n\nVan Moerkercke A, Galván-Ampudia CS, Verdonk JC, et al.: Regulators of floral fragrance production and their target genes in petunia are not exclusively active in the epidermal cells of petals. J. Exp. Bot. 2012; 63(8): 3157–3171. PubMed Abstract \| Publisher Full Text\n\nvan Schie CC , Haring MA, Schuurink RC: Regulation of terpenoid and benzenoid production in flowers. Curr. Opin. Plant Biol. 2006; 9(2): 203–208. PubMed Abstract \| Publisher Full Text\n\nVenkatachalam P, Jayabalan N: New flower colour mutants evolved through gamma irradiation in Zinnia elegANS Jacq. J. Mendel. 1994; 11: 35.\n\nVerdonk JC, Haring MA, van Tunen AJ , et al.: ODORANT1 regulates fragrance biosynthesis in petunia flowers. Plant Cell. 2005; 17(5): 1612–1624. PubMed Abstract \| Publisher Full Text\n\nWang F, Wang C, Liu P, et al.: Enhanced rice blast resistance by CRISPR/Cas9-targeted mutagenesis of the ERF transcription factor gene OsERF922. PLoS One. 2016; 11(4): e0154027. PubMed Abstract \| Publisher Full Text\n\nWang J, Pichersky E: Characterization ofS-Adenosyl-l-Methionine:(Iso) eugenolO-Methyltransferase Involved in Floral Scent Production inClarkia breweri. Arch. Biochem. Biophys. 1998; 349(1): 153–160. Publisher Full Text\n\nWang J, Dudareva N, Bhakta S, et al.: Floral Scent Production in Clarkia breweri (Onagraceae)(II. Localization and Developmental Modulation of the Enzyme S-Adenosyl-L-Methionine:(Iso) Eugenol O-Methyltransferase and Phenylpropanoid Emission). Plant Physiol. 1997; 114(1): 213–221. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWang M, Xu Z, Gosavi G, et al.: Targeted base editing in rice with CRISPR/ScCas9 system. Plant Biotechnol. J. 2020; 18: 1645–1647. PubMed Abstract \| Publisher Full Text\n\nWang Y, Cheng X, Shan Q, et al.: Simultaneous editing of three homoeoalleles in hexaploid bread wheat confers heritable resistance to powdery mildew. Nat. Biotechnol. 2014; 32(9): 947–951. PubMed Abstract \| Publisher Full Text\n\nWatanabe K, Kobayashi A, Endo M, et al.: CRISPR/Cas9-mediated mutagenesis of the dihydroflavonol-4-reductase-B (DFR-B) locus in the Japanese morning glory Ipomoea (Pharbitis) nil. Sci. Rep. 2017; 7(1): 10028. PubMed Abstract \| Publisher Full Text\n\nWatanabe K, Oda-Yamamizo C, Sage-Ono K, et al.: Alteration of flower colour in Ipomoea nil through CRISPR/Cas9-mediated mutagenesis of carotenoid cleavage dioxygenase 4. Transgenic Res. 2018; 27(1): 25–38. PubMed Abstract \| Publisher Full Text\n\nWeeks DP, SPALding MH, Yang B: Use of designer nucleases for targeted gene and genome editing in plants. Plant Biotechnol. J. 2016; 14(2): 483–495. Publisher Full Text\n\nWeiss D: Regulation of flower pigmentation and growth: multiple signaling pathways control anthocyanin synthesis in expanding petals. Physiol. Plant. 2000; 110(2): 152–157. Publisher Full Text\n\nWendt T, Holm PB, Starker CG, et al.: TAL effector nucleases induce mutations at a pre-selected location in the genome of primary barley transformants. Plant Mol. Biol. 2013; 83(3): 279–285. PubMed Abstract \| Publisher Full Text\n\nWinkel-Shirley B: Biosynthesis of flavonoids and effects of stress. Curr. Opin. Plant Biol. 2002; 5(3): 218–223. Publisher Full Text\n\nWheeler AG, Henry TJ: Biology of the honeylocust plant bug, Diaphnocoris chlorionis, and other mirids associated with ornamental honeylocust. Ann. Entomol. Soc. Am. 1976; 69(6): 1095–1104.\n\nWright DA, Townsend JA, Winfrey RJ Jr, et al.: High-frequency homologous recombination in plants mediated by zinc-finger nucleases. Plant J. 2005; 44(4): 693–705. Publisher Full Text\n\nWu S, Watanabe N, Mita S, et al.: The key role of phloroglucinol O-methyltransferase in the biosynthesis of Rosa chinensis volatile 1, 3, 5-trimethoxybenzene. Plant Physiol. 2004; 135(1): 95–102. PubMed Abstract \| Publisher Full Text\n\nWu S, Watanabe N, Mita S, et al.: Two O-methyltransferases isolated from flower petals of Rosa chinensis var. spontanea involved in scent biosynthesis. J. Biosci. Bioeng. 2003; 96(2): 119–128. PubMed Abstract \| Publisher Full Text\n\nWyman C, Kanaar R: DNA double-strand break repair: all's well that ends well. Annu. Rev. Genet. 2006; 40: 363–383.\n\nYamagishi M: How genes paint lily flowers: regulation of colouration and pigmentation patterning. Sci. Hortic. 2013; 163: 27–36. Publisher Full Text\n\nYamagishi M, Shimoyamada Y, Nakatsuka T, et al.: Two R2R3-MYB genes, homologs of petunia AN2, regulate anthocyanin biosyntheses in flower tePALs, tePAL spots and leaves of Asiatic hybrid lily. Plant Cell Physiol. 2010; 51(3): 463–474. PubMed Abstract \| Publisher Full Text\n\nYan F, Kuang Y, Ren B, et al.: Highly efficient A· T to G· C base editing by Cas9n-guided tRNA adenosine deaminase in rice. Mol. Plant. 2018; 11(4): 631–634. PubMed Abstract \| Publisher Full Text\n\nYan H, Zhang H, Wang Q, et al.: Isolation and identification of a putative scent-related gene RhMYB 1 from rose. Mol. Biol. Rep. 2011; 38(7): 4475–4482. PubMed Abstract \| Publisher Full Text\n\nYogindran S, Rajam MV: RNAi for crop improvement Plant biology and biotechnology. 2015; Springer: 623–637.\n\nYoshida K, Mori M, Kondo T: Blue flower color development by anthocyanins: from chemical structure to cell physiology. Nat. Prod. Rep. 2009; 26(7): 884–915. PubMed Abstract \| Publisher Full Text\n\nYoshida K, Oyama-Okubo N, Yamagishi M: An R2R3-MYB transcription factor ODORANT1 regulates fragrance biosynthesis in lilies (Lilium spp.). Mol. Breed. 2018; 38(12): 144. Publisher Full Text\n\nYu L-X, Li W-J, Du Y, et al.: Flower color mutants induced by carbon ion beam irradiation of geranium (Pelargonium× hortorum, Bailey). Nucl. Sci. Tech. 2016; 27(5): 112. Publisher Full Text\n\nYue Y, Yu R, Fan Y: Characterization of two monoterpene synthases involved in floral scent formation in Hedychium coronarium. Planta. 2014; 240(4): 745–762. PubMed Abstract \| Publisher Full Text\n\nZetsche B, Gootenberg JS, Abudayyeh OO, et al.: Cpf1 is a single RNA-guided endonuclease of a class 2 CRISPR-Cas system. Cell. 2015; 163(3): 759–771. PubMed Abstract \| Publisher Full Text\n\nZhang C, Fu J, Wang Y, et al.: Glucose supply improves petal coloration and anthocyanin biosynthesis in Paeonia suffruticosa ‘Luoyang Hong’cut flowers. Postharvest Biol. Technol. 2015; 101: 73–81. Publisher Full Text\n\nZhang F, Maeder ML, Unger-Wallace E, et al.: High frequency targeted mutagenesis in Arabidopsis thaliana using zinc finger nucleases. Proc. Natl. Acad. Sci. 2010; 107(26): 12028–12033. PubMed Abstract \| Publisher Full Text\n\nZhang R, Liu J, Chai Z, et al.: Generation of herbicide tolerance traits and a new selectable marker in wheat using base editing. Nature plants. 2019; 5(5): 480–485. PubMed Abstract \| Publisher Full Text\n\nZhao D, Tao J: Recent advances on the development and regulation of flower color in ornamental plants. Front. Plant Sci. 2015; 6: 261. Publisher Full Text\n\nZhao D, Tang W, Hao Z, et al.: Identification of flavonoids and expression of flavonoid biosynthetic genes in two coloured tree peony flowers. Biochem. Biophys. Res. Commun. 2015; 459(3): 450–456. PubMed Abstract \| Publisher Full Text\n\nZhao D-Q, Wei M-R, Liu D, et al.: Anatomical and biochemical analysis reveal the role of anthocyanins in flower coloration of herbaceous peony. Plant Physiol. Biochem. 2016; 102: 97–106. PubMed Abstract \| Publisher Full Text\n\nZheng SJ, Snoeren TA, Hogewoning SW, et al.: Disruption of plant carotenoid biosynthesis through virus‐induced gene silencing affects oviposition behaviour of the butterfly Pieris rapae. New Phytol. 2010; 186(3): 733–745.\n\nZhou C, Sun Y, Yan R, et al.: Off-target RNA mutation induced by DNA base editing and its elimination by mutagenesis. Nature. 2019; 571(7764): 275–278. PubMed Abstract \| Publisher Full Text\n\nZhou L, Wang Y, Peng Z: Molecular characterization and expression analysis of chalcone synthase gene during flower development in tree peony (Paeonia suffruticosa). Afr. J. Biotechnol. 2011; 10(8): 1275–1284.\n\nZong Y, Song Q, Li C, et al.: Efficient C-to-T base editing in plants using a fusion of nCas9 and human APOBEC3A. Nat. Biotechnol. 2018; 36(10): 950–953. PubMed Abstract \| Publisher Full Text\n\nZong Y, Wang Y, Li C, et al.: Precise base editing in rice, wheat and maize with a Cas9-cytidine deaminase fusion. Nat. Biotechnol. 2017; 35(5): 438–440. PubMed Abstract \| Publisher Full Text\n\nZufall RA, Rausher M: The genetic basis of a flower color polymorphism in the common morning glory (Ipomoea purpurea). J. Hered. 2003; 94(6): 442–448. PubMed Abstract \| Publisher Full Text\n\nZuker A, Tzfira T, Ben-Meir H, et al.: Modification of flower color and fragrance by antisense suppression of the flavanone 3-hydroxylase gene. Mol. Breed. 2002; 9(1): 33–41. Publisher Full Text\n\nZvi MMB, Negre-Zakharov F, Masci T, et al.: Interlinking showy traits: co-engineering of scent and colour biosynthesis in flowers. Plant Biotechnol. J. 2008; 6(4): 403–415. PubMed Abstract \| Publisher Full Text\n\nZvi MMB, Shklarman E, Masci T, et al.: PAP1 transcription factor enhances production of phenylpropanoid and terpenoid scent compounds in rose flowers. New Phytol. 2012; 195(2): 335–345. PubMed Abstract \| Publisher Full Text" }	[ { "id": "149552", "date": "22 Nov 2022", "name": "Muhammad Azam", "expertise": [ "Reviewer Expertise Horticulture/Pomology/Molecular biology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIt is a very interesting review regarding the \"Understanding floral biology for CRISPR-based modification of color and fragrance in horticultural plants\". Authors has compiled all the previous research in a very good manner. However there are suggestions to improve this review for readers interest.\nIt is suggested to improve the Figure 1a to 4, all abbreviations should be mentioned in the figure.\n\nThe authors did not mention figure 1a-d in the text and there is no proper information about these figure in the manuscript.\n\nAuthor need to redraw all figures.\n\nFigure 1b shows some arrows, but there is no description below.\n\nSome words are broken in the boxes in all figures which seems not good.\n\nThe authors should also give some information about the new genes which are important in different crops but are ignored regarding floral biology and future work should be carried out to improve the crop performance or resistance against changing climate conditions.\n\nAuthor also suggested to add some studies regarding suppression of volatile compound for the control of some destructive pests during flowering or fruit maturation period in horticulture crops as well as color base transformation to other fruits or vegetables.\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? Partly", "responses": [] }, { "id": "169049", "date": "17 Apr 2023", "name": "Albert Chern Sun Wong", "expertise": [ "Reviewer Expertise Plant biotechnology", "plant tissue culture", "plant physiology", "CRISPR/Cas9", "molecular biology", "cereals", "crop improvement" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe review article titled 'Understanding floral biology for CRISPR-based modification of color and fragrance in horticultural plants' summarized various key research in floral color and fragrance, which identified gene targets that could potentially be modified to enhance flower appearances in horticultural plants. Gene targets involved in the synthesis and regulation of flower color and fragrance and molecular techniques are extensively listed in the review. However, the review article can be further improved with the following suggestions:\nFigures 1a-d are not mentioned in the article. These figures are only useful if they are mentioned in-text. For the benefit of readers who are not experts in these fields, it is recommended to explain each of the figures with appropriate captions, explaining each abbreviation and/or arrows used in the figures, and carefully format text within figures so that they are aligned correctly.\n\nAlternatively, these figures should be removed if the authors agree the effort to revise them are more than their usefulness for this article.\n\nSeveral gene and protein names are not clearly explained at their first mention. For example, in section 2.1, 3GTs is first mentioned, but no full name is stated.\n\nFigure 2 needs to be revised. Several misspellings are present in figure. Alternatively, similar figure could be obtained from published sources with appropriate permission granted from authors and publishers.\n\nTable 2 do not require excessive self-citation for each row. Instead, I would suggest adding that citation in the caption if the table was adapted from the cited book chapter.\n\nIn-text references and the reference list are not consistent throughout the article. These need to be revised for consistency throughout. For example, in the first paragraph of the introduction, in-text citation (Pompelli, De Brito, Otoni, & Guerra, 2007) listed all authors but the corresponding reference in the reference list did not and replaced the last author name with et al. instead. In section 2.4, the in-text citation (Negre, Kolosova, Knoll, Kish, & Dudareva, 2002) listed all five authors, but the corresponding reference in the reference list only listed the first 3 authors followed by et al. It is recommended to use a standardized referencing guide (such as APA style), listing up to 2 authors and use et al. thereafter in the in-text citations and list all authors in the reference list.\n\nPlease combine some of the sentences in the same section where appropriate to make article concise and clear.\nIn addition to the above suggestions, I suggest revising the article writing style as many sections are written in a very casual and conversational way. The use of the word 'we' in the article is unnecessary, and in some cases incorrect.\nThe authors could add further value to their article by discussing some of the potential consequences of editing some of the genes to alter flower color. For example, the edit of the FSH gene altered flower color in Torenia spp., but it should be noted that altering a key gene such as FSH could potentially affect other processes such as abiotic stresses defenses.\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-854
https://f1000research.com/articles/11-353/v1	23 Mar 22	{ "type": "Review", "title": "The genomic and clinical features of the COVID-19 Omicron variant: a narrative review", "authors": [ "Decsa Medika Hertanto", "Henry Sutanto", "Maria Inge Lusida", "Kuntaman Kuntaman", "Djoko Santoso", "Decsa Medika Hertanto", "Henry Sutanto", "Maria Inge Lusida", "Kuntaman Kuntaman" ], "abstract": "Coronavirus disease 2019 (COVID-19) is a major cause of morbidity and mortality worldwide. Since late November 2021, the Omicron variant has emerged as the primary cause of COVID-19 and caused a huge increase in the reported incidence around the world. To date, 32-34 spike mutations have been reported to be present in the Omicron variant, 15 of which were located in the receptor-binding domain that interacts with the cell surface of the host cells, while the rest were located in the N-terminal domain and around the furin cleavage site. Recent studies have suggested that those mutations could have a major role in the transmissibility and pathogenicity of the Omicron variant. Additionally, some mutations might contribute to the change of viral tropism of this novel variant. Here, we aim to discuss the recent reports on the transmissibility and severity of the Omicron variant from both the genetic and clinical perspectives. Afterward, we also take the chance to deliver our personal view on the topic.", "keywords": [ "COVID-19", "pandemic", "SARS-CoV-2", "Omicron variant", "emerging disease", "global health", "virus", "genome", "mutation" ], "content": "Introduction\n\nCoronavirus disease 2019 (COVID-19) has been a major cause of morbidity and mortality worldwide since December 2019. Up to February 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 400 million people and contributed to the death of more than 5.5 million individuals around the world. Intriguingly, after more than 2 years of its existence, the infection rate remains high, and the pandemic has not been resolved. Following the devastating impacts of the B.1.617.2 (Delta) variant, predominantly in health and socioeconomic sectors, there was a high expectation that the viral disease could be tamed by the rapid, collaborative and evolutionary development of COVID-19 vaccines. Indeed, the massive vaccination program in several countries has successfully reduced the fatality of the disease and together with the implementation of strict public health and social control measures (PHSCM), the infection rate could also be lowered.1–4 For example, in the United States (US), COVID-19 vaccines reduced the overall attack rate (i.e., number of new cases during specified time interval divided by the total population at start of time interval) in vaccinated individuals by 4.4% on day 300 from the start of vaccination (9% in the unvaccinated group vs. 4.6% in the vaccinated group), as well as the rate of hospitalization, intensive care unit (ICU) occupancy, incidence of major adverse events and mortality.1 Despite the reported effectivity decline of BNT162b2 and ChAdOx1 vaccines against the Delta variant (10–13% and 16% lower than B.1.1.7 (Alpha) variant, respectively),5 vaccination was proven to remain effective in reducing infection and accelerating viral clearance,2 as well as lowering mortality caused by the Delta variant.4\n\nHowever, a glimpse of hope to end the pandemic was once again challenged by the presence of the new COVID-19 B.1.1.529 (a.k.a. Omicron) variant. Since its first reported appearance in South Africa in November 2021, it has rapidly taken the attention of experts around the world. A few days after its appearance, the World Health Organization (WHO) immediately classified Omicron as a Variant of Concern (VoC). Since then, it has vastly spread from Africa to Europe, then Asia, Australia and America (Figure 1). Since early January 2022, the Omicron variant has become the major COVID-19 variant in most countries (Table 1)6,7 and contributed to the rise of COVID-19 incidence from ~600,000 new cases in late November 2021 to ~3.5 million cases in late January 2022.\n\n\nThe genomic basis of the Omicron variant and the predicted effects of its mutations\n\nA study conducted based upon the genome sequencing data of 108 samples collected from patients infected with the Omicron variant8 revealed that this variant possessed 61-64 mutations, 54 of which were single nucleotide polymorphisms (SNPs). Of those, 34 mutations were positioned at the spike (S) proteins and 32 of those spike mutations were non-synonymous, which means that the mutations alter the amino acid sequences.8 Importantly, the mutations in the Omicron variant were reported to be present in all three key regions in the spike of SARS-CoV-2: The receptor binding domain (RBD), N-terminal domain (NTD) and furin cleavage site (FCS). Overall, 15 of the spike mutations were located in the RBD, a region that is responsible for the viral attachment to the cell surface (Table 2).\n\na was reported by Ma et al.8 and\n\nb was reported by the United States Centers for Disease Control and Prevention (CDC). The mutations that are potentially suitable for Omicron screening are marked by (#). This was assessed based on the exclusivity of these mutations for Omicron variant (present in >95% of Omicron (and sub-lineage) sequences and present in <1% of recent non-Omicron sequences) according to the Communicable Diseases Genomics Network (CDGN) per 20 December 2021 (FCS = furin cleavage site; NTD = N-terminal domain; RBD = receptor binding domain).\n\nMutations in RBD\n\nAs displayed in Table 2, the N501Y mutation that converts amino acid asparagine to tyrosine at position 501 was identified in the Omicron variant. This particular mutation enhanced the binding affinity of the RBD to angiotensin converting enzyme type-2 (ACE2) receptor in the surface of the host cell.9 As a consequence, the Omicron variant could have a stronger attachment to the host cells than some of the other COVID-19 variants, fostering its transmissibility. Meanwhile, the mutation Q498R (converting glutamine to arginine at position 498) of the RBD alone negatively affected the protein stability and binding. However, due to its known epistatic effect with N501Y, the combination of both mutations was shown to increase the affinity of the RBD to ACE2 receptor by 4-fold.10 Of note, the N501Y mutation was also identified in other COVID-19 variants (e.g., C.1.2, Alpha, Beta and Gamma), but not Q498R. In addition to their effect on the binding affinity to ACE2 receptor, Omicron-associated mutations in the RBD could also promote the escape from existing neutralizing antibodies. In the study done by Cao et al.,11 the effect of Omicron-associated mutations in the RBD region on neutralizing antibodies was assessed using a high throughput yeast display screening. As the result, K417N, G446S, E484A and Q493R mutations assisted the virus to evade neutralizing antibodies, especially the ones which epitope overlapped with the ACE2 binding motif (epitope group A-D). Also, there was evidence that G339D, S371L and N440K mutations of the RBD could facilitate the virus evasion from other neutralizing antibodies (epitope group E-F). Overall, of the 247 antibodies tested, 85% were evaded by Omicron, suggesting the potentially low efficacy of preexisting neutralizing antibodies against the Omicron variant.11\n\nMutations in NTD\n\nSeveral mutations in the NTD region were shown to have significant effect on viral infectivity and the modulation of immune evasion. For example, the del69-70 boosted the infectivity of the Alpha variant through the elevation of cleaved spike incorporation into virions.12 Conversely, T95I mutation that was previously identified in the B.1.617.1 variant seems not to be substantially involved in immune evasion due to its location outside of the antigenic supersite.13 Interestingly, two cases of BNT162b2 and mRNA-1273 vaccines breakthrough infection were reported in COVID-19 patients harboring T95I mutation of the NTD, as well as the del142-144 mutation of the NTD and D614G mutation of the FCS, indicating the possible contribution of those mutations on viral immune escape.14 Meanwhile, evidence of a marked (4-16-fold) reduction of neutralizing capacity of COVID-19 convalescent sera against a recombinant vesicular stomatitis virus carrying SARS-CoV-2 spike protein with Y145D mutation was also reported.15\n\nMutations in FCS\n\nThe FCS region has been shown to be a key part of SARS-CoV-2 pathogenesis and severity. For instance, a mutant lacking FCS (ΔPRRA) displayed a reduced replication rate in a human respiratory cell line.16 Meanwhile, in regard to Omicron-associated mutations, the H655Y and N679K mutations which are located proximal to the FCS, and the P681H mutation of the FCS could enhance the SARS-CoV-2 spike cleavage and increase the transmissibility of the Omicron variant. Moreover, the P681H mutation, which was previously identified in the B.1.1.7 (Alpha) variant, was demonstrated to facilitate the viral resistance against innate immunity (i.e., interferon-β) in lung epithelial cells.17 Yet, another study on this particular mutation did not find any notable change on the spike cleavage, viral entry or intercellular spreading.18 Next, the D614G mutation, a common mutation found in existing COVID-19 variants, increased viral replication in human lung epithelia and respiratory tract by fostering the virion stability and infectivity. Moreover, it increased the viral load in the upper respiratory tract, thereby promoting viral transmission.19 However, it is important to note that the effect of such mutations on Omicron pathogenicity may differ from what was reported in previous COVID-19 variants due to distinct interactions among variant-associated mutations.\n\nThe change of viral tropism in the Omicron variant is also important to scrutinize. A recent UK-based study showed that the Omicron variant was strongly associated with symptoms from upper respiratory tract more than the lower respiratory tract.20 This could be explained by the presence of two Omicron-specific mutations: N764K and N856K. Those mutations were shown to produce cleavage sites for subtilisin-kexin isozyme-1/site-1 protease (SKI-1/S1P) serine protease predominantly situated in the upper airway. Such cleavage sites are important to cleave viral envelope glycoproteins, which modulate SARS-CoV-2 replication and pathogenesis.21 Indeed, the Omicron variant was shown to replicate faster in the bronchus than in the lung parenchyma.22 Another study also highlighted that despite the similar viral replication in human nasal epithelial cultures, the Omicron variant demonstrated lower replication in lower respiratory and pulmonary cells than the Delta variant.23 Additionally, Omicron spike protein has a lower S1/S2 cleavage efficiency than the Delta variant and Omicron tends to avoid cells expressing a high level of transmembrane protease, serine 2 (TMPRSS2). This was due to Omicron’s failure in exploiting the TMPRSS2 that promotes cell entry via plasma membrane fusion. As a consequence, the cell entry of the Omicron variant was largely mediated through the endocytic pathway.23,24 The fact that SKI-1/S1P was also present in pulmonary macrophages21 could suggest the potential consequences of N764K and N856K mutations on the host innate immunity. Nevertheless, more studies are needed to confirm this notion.\n\n\nWhat can we tell from the Ct value of patients with the Omicron variant?\n\nReal-time reverse transcription polymerase chain reaction (rtRT-PCR) or quantitative RT-PCR (qRT-PCR) is a gold-standard diagnostic tool for identifying SARS-CoV-2, the causative agent of COVID-19. This method usually detects ≥ 2 genes of SARS-CoV-2, including ORF1ab/RdRp, N and E.25 At present, due to the increasing incidence of Omicron variant infection, S gene with S gene target failure (SGTF) is frequently used as an indicator for screening of the Omicron variant. Most reported Omicron variant sequences include a deletion in the S gene, which can cause an SGTF in some PCR assays.\n\nCycle threshold (Ct) is the thermal cycle number at which the amplified DNA that shows as a fluorescent signal exceeds and thus passes the threshold for positivity. A higher Ct value means that the tool requires more copy numbers to reach the positivity threshold, indicating a lower viral concentration in the specimens. Conversely, the lower the Ct level the greater the amount of identified target ribonucleic acid (RNA) in the sample. A recent study assessing the real-time (RT) qPCR data from 10,324 specimens and comparing 97 Omicron against 107 Delta variant infections reported that the Ct values was higher for Omicron infections than for Delta infections (Omicron: Ct 23.3 vs. Delta: Ct 20.5), suggesting a lower peak viral RNA of the Omicron variant. Moreover, the clearance phase for Omicron was shorter while the clearance rate was similar with the Delta variant.26 Similarly, studies conducted in France also reported a significantly higher Ct value for Omicron infection than the non-Omicron variants.27,28 These findings suggest that the high transmissibility of the Omicron variant might not be due to a high viral load in the upper respiratory tract, despite the presence of D614G mutation which was known to increase viral replication in the upper respiratory tissue.19 Thus, at present, the cause of a higher Ct value in Omicron variant infection than other variants, including Delta, remains unclear.\n\n\nClinical features of the Omicron variant\n\nA recent observational study conducted in Texas, US, from late December 2021 to early January 2022 reported that the Omicron variant displayed some different clinical patterns than its predecessors.29 Compared to patients infected by Alpha and Delta variants, these patients were younger and predominantly female. The number of patients requiring hospitalization was significantly lower in Omicron than in Alpha and Delta variant infections (19.8% vs. 54.6% and 43.1%, respectively). Of those who were hospitalized, the average length of stay was significantly shorter in Omicron than Alpha and Delta (3.2 days vs. 5.1 days and 5.4 days, respectively). Moderate to severe cases (e.g., number of patients requiring extracorporeal membrane oxygenation [ECMO], mechanical ventilation and high-flow oxygenation) and mortality were also lower in Omicron infection. As expected, while Alpha and Delta variants affected mostly the unvaccinated individuals, the Omicron variant proportionally infected both the unvaccinated (44.1%) and vaccinated people (55.9%).29 These findings and comparable results from other studies30,31 confirm the hypothesis that the Omicron variant causes less severe disease, resulted in a lower hospitalization rate. Importantly, the fact that Omicron caused an increased mRNA vaccine (i.e., BNT162b2 and mRNA-1273) breakthrough incidence29 needs to be swiftly responded to by speeding up the vaccination booster campaign. The third vaccine (booster) dose has been shown to rescue and broaden the viral neutralization.32–35 A study comparing the mRNA vaccines effectiveness on 16,087 Omicron versus 4,261 Delta cases revealed that the second dose vaccine effectiveness against the Delta variant reduced from 89% to 80% after 240 days. Interestingly, against the Omicron variant, the second dose vaccine effectiveness was only 36% at day 7-59 and completely diminished after 180 days. However, the third dose (booster) vaccination recovered the vaccine effectiveness against the Delta and Omicron variants to 97% and 61% after day 7, respectively.35 Therefore, booster vaccination is expected to be beneficial to tackle this emerging COVID-19 variant.\n\nTable 3 lists the reported clinical symptoms associated with Omicron variant infection.36–41 In most studies, upper respiratory symptoms (e.g., runny or stuffy nose, sneezing, cough and sore throat) dominated, while the lower respiratory complaint (e.g., shortness of breath) was identified in less than 20% of patients infected by the Omicron variant. Non-respiratory symptoms, such as fatigue, headache, muscle pain and fever, were also seen in some patients, although the number varies between studies. Importantly, COVID-19-pathognomonic symptoms, such as anosmia and ageusia, were only observed in a limited number of patients across studies (less than 25%). Overall, this observation is consistent with the abovementioned viral tropism of the Omicron variant.\n\n* Multiple symptoms could be reported by one person (UK = United Kingdom; USA = United States of America).\n\nNevertheless, it is also crucial to acknowledge that although studies have shown compelling evidence of a less severe disease and a lower hospitalization due to Omicron infection, the high transmissibility of this variant might still impact the healthcare system readiness and increase the absolute number of hospitalization.42 These conditions would cause a severe delay on the non-COVID-19 patient care and might result in bigger indirect consequences than we expected. Also, the effect of the Omicron variant in immunocompromised individuals, and patients with concomitant diseases and comorbidities (e.g., diabetes mellitus) is still unknown. In general, these individuals have an impaired immune response against infections, a condition that favors Omicron and other COVID-19 variants. Nonetheless, the effect of Omicron on this special population is yet to be explored.\n\n\nHighlights\n\nOverall, the genomic profile of the Omicron variant hinted a high affinity to ACE2 receptor, a high transmissibility and a likelihood to evade neutralizing antibodies,23 either from the previous vaccination32,43 or prior infection(s).44 This evidence suggests the need for Omicron-specific vaccines, which could provide a better protection against the disease than the currently available COVID-19 vaccines. Indeed, an Omicron-based vaccine is currently being studied in a clinical trial to evaluate the safety, tolerability and immunogenicity in healthy adults. In addition, the fact that the Omicron variant had a lower predisposition to damage lower respiratory tract and pulmonary tissue could indicate its potentially lower severity than its predecessors (e.g., Delta variant). Indeed, the less severe feature of Omicron has been seen in several observational studies. Nonetheless, the consequences of this variant on special populations (e.g., individuals with altered immune response, diabetes mellitus or advanced age) remain to be elucidated.\n\nAlso, it is important to highlight that in a recent statement, WHO’s Technical Advisory Group on SARS-CoV-2 Virus Evolution (TAG-VE) has raised a concern regarding Omicron sublineage BA.2. To date, several Omicron sublineages have been identified (e.g., BA.1, BA.1.1., BA.2 and BA.3) and each of them exhibits different mutations than the others. For the past few weeks, globally, the proportion of BA.2 sublineage has been increasing relative to BA.1. Initial data regarding this subvariant suggested that Omicron sublineage BA.2 was more transmissible than BA.1, with a reproduction rate of 1.4 times higher than BA.1.45 It was also more replicative in human nasal epithelial cells. Moreover, the pathogenicity and the ability to evade neutralizing antibodies were reported to be higher in BA.2 Omicron sublineage.45 In addition, the absence of del69-70 mutation of NTD in BA.2 could significantly lower the identifiability of this subvariant in some PCR assays.\n\nRegardless, implementing an effective PHSCM could still be beneficial to limit person-to-person transmission of Omicron variant. The application of well-fitting mask, imposing strict physical distancing, cough etiquette and hand hygiene, as well as avoiding crowds remain vital. The WHO has already advised to enhance surveillance with rapid testing, cluster investigations, contact tracing and quarantine, as well as case isolation to cut the chain of transmission. Only by a collaborative effort, the COVID-19 pandemic could be brought to an end.\n\n\nData availability\n\nNo data are associated with this article.", "appendix": "Acknowledgements\n\nAn earlier version of this article can be found on https://www.preprints.org/ (doi: 10.20944/preprints202202.0224.v1).\n\n\nReferences\n\nMoghadas SM, Vilches TN, Zhang K, et al.: The Impact of Vaccination on Coronavirus Disease 2019 (COVID-19) Outbreaks in the United States. Clin. Infect. Dis. 2021; 73(12): 2257–2264. PubMed Abstract \| Publisher Full Text\n\nSinganayagam A, Hakki S, Dunning J, et al.: Community transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated individuals in the UK: a prospective, longitudinal, cohort study. Lancet Infect. Dis. 2022; 22(2): 183–195. PubMed Abstract \| Publisher Full Text\n\nNg OT, Koh V, Chiew CJ, et al.: Impact of Delta Variant and Vaccination on SARS-CoV-2 Secondary Attack Rate Among Household Close Contacts. Lancet Reg. Health West Pac. 2021; 17: 100299. PubMed Abstract \| Publisher Full Text\n\nSheikh A, Robertson C, Taylor B: BNT162b2 and ChAdOx1 nCoV-19 Vaccine Effectiveness against Death from the Delta Variant. N. Engl. J. Med. 2021; 385(23): 2195–2197. PubMed Abstract \| Publisher Full Text\n\nPouwels KB, Pritchard E, Matthews PC, et al.: Effect of Delta variant on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK. Nat. Med. 2021; 27(12): 2127–2135. PubMed Abstract \| Publisher Full Text\n\nDong E, Du H, Gardner L: An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect. Dis. 2020; 20(5): 533–534. PubMed Abstract \| Publisher Full Text\n\nKhare S, Gurry C, Freitas L, et al.: GISAID's Role in Pandemic Response. China CDC Wkly. 2021; 3(49): 1049–1051. PubMed Abstract \| Publisher Full Text\n\nMa W, Yang J, Fu H, et al.: Genomic perspectives on the emerging SARS-CoV-2 omicron variant. Genomics Proteomics Bioinformatics. 2022. Publisher Full Text\n\nLiu Y, Liu J, Plante KS, et al.: The N501Y spike substitution enhances SARS-CoV-2 infection and transmission. Nature. 2022; 602(7896): 294–299. PubMed Abstract \| Publisher Full Text\n\nZahradnik J, Marciano S, Shemesh M, et al.: SARS-CoV-2 variant prediction and antiviral drug design are enabled by RBD in vitro evolution. Nat. Microbiol. 2021; 6(9): 1188–1198. PubMed Abstract \| Publisher Full Text\n\nCao Y, Wang J, Jian F, et al.: Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies. Nature. 2021; 602: 657–663. PubMed Abstract \| Publisher Full Text\n\nMeng B, Kemp SA, Papa G, et al.: Recurrent emergence of SARS-CoV-2 spike deletion H69/V70 and its role in the Alpha variant B.1.1.7. Cell Rep. 2021; 35(13): 109292. PubMed Abstract \| Publisher Full Text\n\nMcCallum M, Walls AC, Sprouse KR, et al.: Molecular basis of immune evasion by the Delta and Kappa SARS-CoV-2 variants. Science. 2021; 374(6575): 1621–1626. PubMed Abstract \| Publisher Full Text\n\nHacisuleyman E, Hale C, Saito Y, et al.: Vaccine Breakthrough Infections with SARS-CoV-2 Variants. N. Engl. J. Med. 2021; 384(23): 2212–2218. PubMed Abstract \| Publisher Full Text\n\nHaslwanter D, Dieterle ME, Wec AZ, et al.: A Combination of Receptor-Binding Domain and N-Terminal Domain Neutralizing Antibodies Limits the Generation of SARS-CoV-2 Spike Neutralization-Escape Mutants. MBio. 2021; 12(5): e0247321. PubMed Abstract \| Publisher Full Text\n\nJohnson BA, Xie X, Bailey AL, et al.: Loss of furin cleavage site attenuates SARS-CoV-2 pathogenesis. Nature. 2021; 591(7849): 293–299. PubMed Abstract \| Publisher Full Text\n\nLista MJ, Winstone H, Wilson HD, et al.: The P681H mutation in the Spike glycoprotein confers Type I interferon resistance in the SARS-CoV-2 alpha (B.1.1.7) variant. bioRxiv 2021:2021.11.09.467693.\n\nLubinski B, Fernandes MHV, Frazier L, et al.: Functional evaluation of the P681H mutation on the proteolytic activation of the SARS-CoV-2 variant B.1.1.7 (Alpha) spike. iScience. 2022; 25(1): 103589. PubMed Abstract \| Publisher Full Text\n\nPlante JA, Liu Y, Liu J, et al.: Spike mutation D614G alters SARS-CoV-2 fitness. Nature. 2021; 592(7852): 116–121. PubMed Abstract \| Publisher Full Text\n\nVihta K-D, Pouwels KB, Peto TE, et al.: Omicron-associated changes in SARS-CoV-2 symptoms in the United Kingdom. medRxiv 2022:2022.01.18.22269082.\n\nMaaroufi H: The N764K and N856K mutations in SARS-CoV-2 Omicron S protein generate potential cleavage sites for SKI-1/S1P protease. bioRxiv 2022:2022.01.21.477298.\n\nHui KPY, Ho JCW, Cheung MC, et al.: SARS-CoV-2 Omicron variant replication in human bronchus and lung ex vivo. Nature. 2022. PubMed Abstract \| Publisher Full Text\n\nMeng B, Abdullahi A, Ferreira I, et al.: Altered TMPRSS2 usage by SARS-CoV-2 Omicron impacts tropism and fusogenicity. Nature. 2022. Publisher Full Text\n\nZhao H, Lu L, Peng Z, et al.: SARS-CoV-2 Omicron variant shows less efficient replication and fusion activity when compared with Delta variant in TMPRSS2-expressed cells. Emerg Microbes Infect. 2022; 11(1): 277–283. PubMed Abstract \| Publisher Full Text\n\nvan Kasteren PB , van der Veer B , van den Brink S , et al.: Comparison of seven commercial RT-PCR diagnostic kits for COVID-19. J. Clin. Virol. 2020; 128: 104412. PubMed Abstract \| Publisher Full Text\n\nHay JA, Kissler SM, Fauver JR, et al.: Viral dynamics and duration of PCR positivity of the SARS-CoV-2 Omicron variant. medRxiv 2022:2022.01.13.22269257.\n\nSofonea MT, Roquebert B, Foulongne V, et al.: From Delta to Omicron: analysing the SARS-CoV-2 epidemic in France using variant-specific screening tests (September 1 to December 18, 2021). medRxiv 2022:2021.12.31.21268583.\n\nSentis C, Billaud G, Bal A, et al.: SARS-CoV-2 Omicron variant, lineage BA.1, is associated with lower viral load in nasopharyngeal samples compared to Delta variant. medRxiv 2022:2022.02.02.22269653.\n\nChristensen PA, Olsen RJ, Long SW, et al.: Signals of Significantly Increased Vaccine Breakthrough, Decreased Hospitalization Rates, and Less Severe Disease in Patients with Coronavirus Disease 2019 Caused by the Omicron Variant of Severe Acute Respiratory Syndrome Coronavirus 2 in Houston, Texas. Am. J. Pathol. 2022. PubMed Abstract \| Publisher Full Text\n\nMaslo C, Friedland R, Toubkin M, et al.: Characteristics and Outcomes of Hospitalized Patients in South Africa During the COVID-19 Omicron Wave Compared With Previous Waves. JAMA. 2022; 327(6): 583–584. PubMed Abstract \| Publisher Full Text\n\nEspenhain L, Funk T, Overvad M, et al.: Epidemiological characterisation of the first 785 SARS-CoV-2 Omicron variant cases in Denmark, December 2021. Euro Surveill. 2021; 26(50) PubMed Abstract \| Publisher Full Text\n\nAccorsi EK, Britton A, Fleming-Dutra KE, et al.: Association Between 3 Doses of mRNA COVID-19 Vaccine and Symptomatic Infection Caused by the SARS-CoV-2 Omicron and Delta Variants. JAMA. 2022; 327: 639–651. PubMed Abstract \| Publisher Full Text\n\nPerez-Then E, Lucas C, Monteiro VS, et al.: Neutralizing antibodies against the SARS-CoV-2 Delta and Omicron variants following heterologous CoronaVac plus BNT162b2 booster vaccination. Nat. Med. 2022. PubMed Abstract \| Publisher Full Text\n\nSchmidt F, Muecksch F, Weisblum Y, et al.: Plasma Neutralization of the SARS-CoV-2 Omicron Variant. N. Engl. J. Med. 2022; 386(6): 599–601. PubMed Abstract \| Publisher Full Text\n\nBuchan SA, Chung H, Brown KA, et al.: Effectiveness of COVID-19 vaccines against Omicron or Delta symptomatic infection and severe outcomes. medRxiv 2022:2021.12.30.21268565.\n\nBrandal LT, MacDonald E, Veneti L, et al.: Outbreak caused by the SARS-CoV-2 Omicron variant in Norway, November to December 2021. Euro Surveill. 2021; 26(50). PubMed Abstract \| Publisher Full Text\n\nYoung B, Fong S-W, Chang ZW, et al.: Comparison of the clinical features, viral shedding and immune response in vaccine breakthrough infection by the Omicron and Delta variants. Research Square. 2022.\n\nTeam CC-R: SARS-CoV-2 B.1.1.529 (Omicron) Variant - United States, December 1-8, 2021. MMWR Morb. Mortal. Wkly Rep. 2021; 70(50): 1731–1734. Publisher Full Text\n\nMaisa A, Spaccaferri G, Fournier L, et al.: First cases of Omicron in France are exhibiting mild symptoms, November 2021-January 2022. Infect. Dis. Now. 2022. PubMed Abstract \| Publisher Full Text\n\nMenni C, Valdes A, Polidori L, et al.: A Comparison of Symptom Prevalence, Severity and Duration in the SARS-CoV-2 Omicron Versus Delta Variants Among Vaccinated Individuals from the ZOE COVID Study. SSRN. 2022. Publisher Full Text\n\nHajjo R, AbuAlSamen MM, Alzoubi HM, et al.: The Epidemiology of Hundreds of Individuals Infected with Omicron BA.1 in Middle-Eastern Jordan. medRxiv 2022:2022.01.23.22269442.\n\nUlloa AC, Buchan SA, Daneman N, et al.: Early estimates of SARS-CoV-2 Omicron variant severity based on a matched cohort study, Ontario, Canada. medRxiv 2022:2021.12.24.21268382.\n\nCollie S, Champion J, Moultrie H, et al.: Effectiveness of BNT162b2 Vaccine against Omicron Variant in South Africa. N. Engl. J. Med. 2022; 386(5): 494–496. PubMed Abstract \| Publisher Full Text\n\nAltarawneh HN, Chemaitelly H, Hasan MR, et al.: Protection against the Omicron Variant from Previous SARS-CoV-2 Infection. N. Engl. J. Med. 2022. PubMed Abstract \| Publisher Full Text\n\nYamasoba D, Kimura I, Nasser H, et al.: Virological characteristics of SARS-CoV-2 BA.2 variant. bioRxiv 2022:2022.02.14.480335." }	[ { "id": "141228", "date": "18 Jul 2022", "name": "Leyi Wang", "expertise": [ "Reviewer Expertise Virology", "Molecular Diagnostics", "SARS-CoV-2" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe genomic and clinical features of the COVID-19 Omicron variant: a narrative review. (Hertanto et al.)\nSummary:\nThe ongoing COVID-19 pandemic is a major cause of worldwide mortality and morbidity. The review manuscript by Hertanto et al. looks at the Omicron variant that first emerged in South Africa in November of 2021 and how it became a Variant of Concern relatively quickly. This review paper is split into two parts, the first covers the genomic basis of the Omicron variant and the second part looks at the clinical features of the same variant.\nMajor comments:\nWhat we find lacking in this review is that authors fail to introduce the readers to any basic background of Omicron. There are phylogenetic studies that point to the suggestion that the Omicron variant likely diverged early on from other SARS-CoV-2 strains. Examination of the whole genome has indicated that the Omicron variant can be classified into two different lineages, BA.1 and BA.2. Maybe more could have been presented on this earlier rather than at the end in the highlights section of the paper. If this is a narrative review, the hope is that an overall picture of the subject is presented. We find that this is lacking in this narrative.\nThe major focus of the section on the genomic bases of the Omicron variant is on the mutations that are present in the 3 key regions of the spike of SARS-CoV-2: the receptor binding domain, the N-terminal domain and the furin cleavage site. There are more than just the mutations found in these three regions that account for the mutations present in the Omicron variant. The authors do not cover these mutations or their effect.\nThe first sentence in Mutations in RBD section: \"As displayed in Table 2, the N501Y mutation that converts amino acid asparagine to tyrosine at position 501 was identified in the Omicron variant\", is slightly misleading. On first read, it implies that this mutation was identified first in the Omicron variant. This mutation has been identified in other variants, and this is represented five sentences later in the same paragraph.\nOn the section titled: What can we tell from the Ct value of patients with the Omicron variant? : While the authors present that Omicron variant samples had a higher Ct value compared to other variant samples, there is nothing notable to take away from this section. The authors do not highlight any key point as to what having a higher Ct value means for the Omicron variant.\n\nMinor Comments:\nTable 2: Reported mutations in S-protein of the Omicron variant. This table was not helpful and did not contribute anything to the review. All the mutations identified in the Omicron variant should have been presented, not just the ones in the RBD, NTD and Furin Cleavage site. Legend for Table 2 mentions the mutations that are potentially suitable for Omicron screening but no where in the body of the text is there mention of using the mutations for screening purposes.\nClinical features of the Omicron variant:\nFor this section of the paper, the authors highlight the different clinical patterns observed in the Omicron variant compared to its predecessors. This section is written and presented very well. Being able to read some comparisons between the Omicron, Alpha and Delta variant was a plus and helped accomplish the author’s goal. With the presentation of the Omicron came asymptomatic and symptomatic variant infection. It would be a nice touch if the authors mentioned something notable about this occurrence.\nThe data presented in Table 3 might have been better served if presented in graph/chart form. It would have had a better impact if that data was presented differently.\nSummary:\nOverall, this review is missing in many areas. There is no new scientific information that is presented. There are other reviews, (1: Omicron genetic and clinical peculiarities that may overturn SARS-CoV-2 pandemic: a literature review; 2: Literature review of Omicron: A grim reality amidst COVID-19) that give a good understanding of the Omicron variant and the impact on the COVID-19 pandemic.\nReferences:\nArora, S.; Grover, V.; Saluja, P.; Algarni, Y.A.; Saquib, S.A.; Asif, S.M.; Batra, K.; Alshahrani, M.Y.; Das, G.; Jain, R.; et al. Literature Review of Omicron: A Grim Reality Amidst COVID-19. Microorganisms 2022, 10, 451. https://doi.org/10.3390/microorganisms10020451\nKupperschmidt, K. Where did ‘weird’ Omicron come from? Science, Vol 374, Issue 6572, Dec 2021. https://doi.org/10.1126/science.acx9754\nSujan Poudel, Angela Ishak, Javier Perez-Fernandez, Efrain Garcia, Darwin A. León-Figueroa, Luccio Romaní, D. Katterine Bonilla-Aldana, Alfonso J. Rodriguez-Morales. Highly mutated SARS-CoV-2 Omicron variant sparks significant concern among global experts – What is known so far? Travel Medicine and Infectious Disease,Volume 45, 2022, 102234, ISSN 1477-8939, https://doi.org/10.1016/j.tmaid.2021.102234.\nTiecco, G.; Storti, S.; Degli Antoni, M.; Focà, E.; Castelli, F.; Quiros-Roldan, E. Omicron Genetic and Clinical Peculiarities That May Overturn SARS-CoV-2 Pandemic: A Literature Review. Int. J. Mol. Sci. 2022, 23, 1987. https://doi.org/10.3390/ijms23041987\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? Partly", "responses": [ { "c_id": "8565", "date": "28 Jul 2022", "name": "Djoko Santoso", "role": "Author Response", "response": "The ongoing COVID-19 pandemic is a major cause of worldwide mortality and morbidity. The review manuscript by Hertanto et al. looks at the Omicron variant that first emerged in South Africa in November of 2021 and how it became a Variant of Concern relatively quickly. This review paper is split into two parts, the first covers the genomic basis of the Omicron variant and the second part looks at the clinical features of the same variant. First, we would like to thank the Referee(s) for the time and willingness to review our manuscript, as well as for the critical assessment, which we believe has improved our manuscript significantly. Here, we address the comments and concerns raised by the Referee(s) point-by-point: Major comments: What we find lacking in this review is that authors fail to introduce the readers to any basic background of Omicron. There are phylogenetic studies that point to the suggestion that the Omicron variant likely diverged early on from other SARS-CoV-2 strains. Examination of the whole genome has indicated that the Omicron variant can be classified into two different lineages, BA.1 and BA.2. Maybe more could have been presented on this earlier rather than at the end in the highlights section of the paper. If this is a narrative review, the hope is that an overall picture of the subject is presented. We find that this is lacking in this narrative. We thank the Referee(s) for these excellent and useful suggestions. Previously, we did not include the phylogenetics of the Omicron variant because at the time of writing, it was not yet clear whether it had its own clade or shared some connections with the preexisting COVID-19 variants. In this revised version, we added a paragraph discussing the phylogenetics of the Omicron variant reported by previous studies. Similarly, regarding the BA.1 and BA.2 classifications, at the time of the writing (January 2022), BA.1 was the dominating subvariant, whereas BA.2 just began to rise. As the consequence, we provided a warning at the end of the original manuscript to highlight the potential hazard of this BA.2 subvariant. At present (6 months later), we clearly see that BA.2 took over the domination from BA.1 and as suggested, we have now added some discussion about the existing Omicron subvariants / sublineages (not only BA.1 and BA.2, but also BA.3, BA.4, BA.5 and XE subvariants). In general, we fully agree that ideally, in our narrative review, we should be able to capture the overall picture of the subject of interest, which is Omicron variant in our case. However, the rapid development and progression of the disease, as well as the rapid changing information about this variant make it difficult to cover everything simultaneously. Employing the unique feature of F1000 Research (which allow us to submit updated versions of our manuscript), we hope to be able to keep this review live and updated, should we find new information regarding the Omicron variant in the future. The major focus of the section on the genomic bases of the Omicron variant is on the mutations that are present in the 3 key regions of the spike of SARS-CoV-2: the receptor binding domain, the N-terminal domain and the furin cleavage site. There are more than just the mutations found in these three regions that account for the mutations present in the Omicron variant. The authors do not cover these mutations or their effect. Again, thank you for this meticulous observation. Indeed, we originally focused only on the spike protein mutations because the spike region was the most studied part of the virus (due to its importance in the binding to ACE2 receptor and cell invasion) and the S-protein mutations were the ones that were heavily linked with the clinical features of the SARS-CoV-2 variants, including the Omicron variant. As reported by early papers about this variant, the mutations in RBD, NTD and FCS could be associated with the transmission, pathogenicity and immune response of the virus. However, we agree with the Referee(s) that several other mutations are now discovered outside of this region, including the ones in the NSP and ORF regions. Therefore, we have added a paragraph discussing this aspect as well in our revised manuscript. The first sentence in Mutations in RBD section: \"As displayed in Table 2, the N501Y mutation that converts amino acid asparagine to tyrosine at position 501 was identified in the Omicron variant\", is slightly misleading. On first read, it implies that this mutation was identified first in the Omicron variant. This mutation has been identified in other variants, and this is represented five sentences later in the same paragraph. Thanks for this correction regarding the semantics of “identify”. Since the Referee(s) feel that the word “identified” could be misleading, we want to avoid similar misunderstanding in the future. Therefore, we have replaced “identified” with “detected” in the revised manuscript and introduce the associated information “Of note, the N501Y mutation was also identified in other COVID-19 variants (e.g., C.1.2, Alpha, Beta and Gamma)” right after the sentence. On the section titled: What can we tell from the Ct value of patients with the Omicron variant? : While the authors present that Omicron variant samples had a higher Ct value compared to other variant samples, there is nothing notable to take away from this section. The authors do not highlight any key point as to what having a higher Ct value means for the Omicron variant. Thank you for the critics regarding this Ct section. With all due respect, allow us to disagree with the Referee(s) on this particular point. We believe that there are some important insights can be obtained from this section that the Ct value of the Omicron variant was higher than Delta, despite the higher transmissibility of the Omicron variant. A higher Ct value indicates lower viral loads in the sample taken (normally from the upper respiratory tract) and this was contradictory with the rapid spreading of the Omicron variant. Taking into account the results of previous studies, we suggest that the Omicron variant might be using another way to increase its transmissibility, rather than increasing the viral loads in the upper airways. This was also confirmed by a recent study by Laitman and colleagues which concluded that the rapid dissemination of the Omicron variant was not attributed to higher nasal viral loads as compared to prior variants. Minor Comments: Table 2: Reported mutations in S-protein of the Omicron variant. This table was not helpful and did not contribute anything to the review. All the mutations identified in the Omicron variant should have been presented, not just the ones in the RBD, NTD and Furin Cleavage site. Legend for Table 2 mentions the mutations that are potentially suitable for Omicron screening but no where in the body of the text is there mention of using the mutations for screening purposes. As mentioned above, we previously focused on the S-protein mutations because they were more heavily studied than other mutations outside of the spike region. In response to the Referee(s) comment, we now added new figures displaying the site of the mutations outside and inside of the spike region that we obtained from The Stanford University Coronavirus Antiviral and Resistance Database. We hope that these figures are informative and suffice. We believe that research is still ongoing, thus it could be that some newly discovered mutations associated with the Omicron variant will be subsequently reported in the future. Regarding the legend for Table 2, we have now removed the text regarding “…potentially suitable for Omicron screening” since it is not relevant anymore to be included. Clinical features of the Omicron variant: For this section of the paper, the authors highlight the different clinical patterns observed in the Omicron variant compared to its predecessors. This section is written and presented very well. Being able to read some comparisons between the Omicron, Alpha and Delta variant was a plus and helped accomplish the author’s goal. With the presentation of the Omicron came asymptomatic and symptomatic variant infection. It would be a nice touch if the authors mentioned something notable about this occurrence. This is a very interesting and useful comment. We have now added a new paragraph comparing the reported clinical characteristics of the Omicron vs. Delta vs. Alpha vs. Gamma variants. Of note, COVID-19 symptoms are heterogeneous and could be influenced by gender, race, ethnic, environmental factors, comorbidities etc., so head-to-head comparisons between two or more distinct studies have to be carefully interpreted. Regarding the asymptomatic vs. symptomatic, as per the definition, there is no symptom reported in the “asymptomatic” individuals, therefore we could not compare it with the clinical characteristics of the symptomatic patients. However, the study by Laitman and colleagues for example, revealed that the Ct value in the symptomatic individuals were lower than the asymptomatic ones (which we believe might not be too surprising that higher viral loads may induce overt disease). Additionally, the fact that some patients were asymptomatic or mildly affected by the virus could be associated with an increasing herd immunity in the population. Nevertheless, a quantitative calculation of herd immunity is needed to confirm the notion. The data presented in Table 3 might have been better served if presented in graph/chart form. It would have had a better impact if that data was presented differently. We sincerely thank the Referee(s) for this suggestion. However, we believe that a table is more appropriate to display the exact number and percentage, as done by the original studies. To provide a clearer overall data regarding the most reported symptoms of the Omicron variant, we now calculated and added the approximate mean percentage from 6 studies that we included in this manuscript. Summary: Overall, this review is missing in many areas. There is no new scientific information that is presented. There are other reviews, (1: Omicron genetic and clinical peculiarities that may overturn SARS-CoV-2 pandemic: a literature review; 2: Literature review of Omicron: A grim reality amidst COVID-19) that give a good understanding of the Omicron variant and the impact on the COVID-19 pandemic. We wholeheartedly appreciate the efforts made by the Referee(s) and we fully agree that our narrative review is still far from perfection. We are confident that following the revision, our manuscript has improved significantly and we hope that it can be approved by the Referee(s). Indeed, the nature of a narrative review does not allow us to add new scientific information. Per definition (https://libguides.csu.edu.au/review/Traditional), a narrative or traditional literature review is a comprehensive, critical and objective analysis of the current knowledge on a topic. Therefore, most journals prohibit adding original data into a narrative review. This is clearly different than a meta-analysis that uses a more quantitative approach on a more specific and focused topic of interest. The abovementioned reviews about the Omicron variants are nice examples and we believe that our revised manuscript can complement those reviews." } ] } ]	1	https://f1000research.com/articles/11-353
https://f1000research.com/articles/11-852/v1	28 Jul 22	{ "type": "Study Protocol", "title": "The burden of BRCA1 and BRCA2 gene mutations among Vietnamese women and their associated factors: A protocol for a systematic review and meta-analysis", "authors": [ "Phuc Thai Tran", "Duc Quang Tran", "Chi Thi Quynh Vu", "Quang Ngoc Phan", "Anh Thi Thu Nguyen", "Phuc Thai Tran", "Chi Thi Quynh Vu", "Quang Ngoc Phan", "Anh Thi Thu Nguyen" ], "abstract": "Background: BReast CAncer gene (BRCA)1 and BRCA2 mutation carriers are frequently provided genetic counselling. A precise estimation of the prevalence of BRCA gene mutations is essential to provide an appropriate risk prediction. However, the data in Vietnam is ambiguous and include unreliable risk factors from individual studies. Hence, the objective of this protocol is to provide a method to synthesize evidence pertaining to the proportion of BRCA mutations among Vietnamese women and their risk factors for cancer. Methods: PRISMA-P was followed in developing and reporting this protocol. From the databases' inception until June 2023, a comprehensive search will be undertaken in electronic PubMed and Scopus databases. In two stages, title/abstract screening and full-text screening, two independent authors will assess all retrieved articles for inclusion. This review includes papers providing the relevant results reflecting the prevalence of BRCA gene mutations in Vietnamese women who are at least 18 years old with or without cancer. Predefined selection criteria will be used to establish each publication's eligibility. Using the Newcastle-Ottawa Scale and Cochrane Risk of Bias tools, the quality of included studies will be assessed, and overall evidence quality will be appraised using the GRADE approach. All pertinent data from the included articles will be entered into an Excel spreadsheet for meta-analysis, which will be imported into Rstudio. Meta-analyses using random effects will be used to obtain the pooled percentages. The chi-squared test and I2 parameter will be used to evaluate heterogeneity. Publication bias will be investigated visually using funnel plots for asymmetry and Egger's statistical tests. Conclusions: Based on the prevalence of BRCA muations and its associated comprehensive and specific risk factors, we hope our findings will provide a reference for future strategies to build an effective treatment plan and manage the risk of cancer development. Registration: PROSPERO (CRD42022340152; 30 June 2022).", "keywords": [ "Vietnam", "Breast cancer", "Ovarian cancer", "BRCA1", "BRCA2" ], "content": "Introduction\n\nA significant risk of getting breast cancer and ovarian cancer is posed to women with a pathogenic germline mutation in either the BReast CAncer gene (BRCA)1 and BRCA2 gene, which was discovered in the 1990s.1 For women with a BRCA1 pathogenic variation, the cumulative lifetime risk of breast cancer varies from 40–87%, and the risk of ovarian cancer ranges from 16–68%. Women with a BRCA2 pathogenic variation have a comparable risk, with a lifetime breast cancer risk of 27–84% and ovarian cancer risk of 11–30%.2 In 2020, an estimated 2.3 million women will be diagnosed with breast cancer, leading to the death of 685,050 people worldwide. There were 7.8 million women who had been diagnosed with breast cancer in the last five years as of the end of 2020, making it the most common disease globally.3 Although it is far less frequent than breast cancer, ovarian cancer is the eighth most prevalent form of cancer in women and the 18th most prevalent form of cancer overall. There were around 300,000 new cases of ovarian cancer diagnosed in 2018, and almost 200,000 deaths were attributed to the illness.4 Among them, approximately 10% of breast cancers are inherited and may be traced back to germline mutations in breast cancer susceptibility genes, most notably in the BRCA1 and BRCA2 genes.5 In comparison, the figure is much higher among those diagnosed with ovarian cancer—approximately 15%.6\n\nIn population, it is well established that the BRCA frequency varies significantly. For instance, compared to the general population, which has an inherited mutation rate of 0.2–0.3%, Ashkenazi Jews make up roughly 2.0% of those with a deleterious variation in either BRCA1 or BRCA2. While in the United States, the prevalence of BRCA1 has been reported as high as 11.1%, the prevalence in Japan was just 2.6%.7 Because there is a wide range of estimates, it may be difficult for physicians to choose which one to use.\n\nIn Vietnam, the cancer burden has been steadily increasing over the last 30 years, with approximately 165,000 new cancer cases and 115,000 cancer-related deaths occurring annually. The age-adjusted cancer death rate in Vietnam is 104 per 100,000 people, which ranks 57 internationally.8 The epidemiology of BRCA mutations in Vietnamese communities is plagued by a lack of high-quality data and studies devoted to it, even though the incidence of breast cancer is on the rise, with an estimated 21,555 new cases and 9,345 deaths every year. At the same time, ovarian cancer had 1,404 cases and 923 fatalities per year (ranked 21st) in 2020.9\n\nAnalysis of the BRCA1 and BRCA2 genes is becoming more popular as a method for detecting pathogenic variations in the context of both preventative and therapeutic concerns. Access to BRCA tumour testing in a timely manner is becoming more significant in the therapeutic field to identify cancer patients who may benefit from therapy with poly (ADP-ribose) polymerase (PARP) inhibitor (PARPi).10 Although the test is highly recommended by professional groups such as the Society of Gynecologic Oncology (SGO) and the National Comprehensive Cancer Network (NCCN)11; however, in Vietnam, the availability of such genetic testing is severely restricted because of the exorbitant cost, as well as a shortage of properly equipped labs and well-trained healthcare professionals.12\n\nFurthermore, no comprehensive statistics about the prevalence of BRCA1 and BRCA 2 gene mutations in Vietnam women are available. Consequently, our study aims to fill this knowledge gap by systematic review and meta-analysis of all the available evidence on the prevalence of BRCA1 and BRCA2 gene mutations among Vietnamese women, including in hospitals and the community.\n\n\n\n1. What is the pooled prevalence of the BRCA1 and BRCA2 gene mutations in the Vietnamese female population, including in-hospital and community?\n\n2. Which risk factors of Vietnamese women should prompt a physician to perform a BRCA gene test for the client/patient?\n\nOur overall objective is to assist physicians and researchers in better understanding the prevalence of BRCA1 and BRCA2 gene mutations and their related risk factors in Vietnamese women. Future research efforts may better guide therapeutically relevant goals.\n\n\nMethods\n\nThis procedure is carried out in accordance with the standards provided by Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P) for systematic review protocols13 and the completed checklist can be found under Reporting Guidelines.20 This protocol for a systematic review has been submitted to the PROSPERO database for registration (CRD42022340152; 30 June 2022). The PRISMA guidelines14 and the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines15 will be used to construct a systematic review and meta-analysis procedure for this study.\n\nWe will enlist the assistance of a genetic consultant and a librarian with extensive expertise in conducting systematic reviews to formulate our search strategy. An exhaustive computerized search of PubMed (RRID:SCR_004846) and Scopus (RRID:SCR_022559) databases from the beginning of the database systems to June 2023 will provide relevant research on the incidence of mutations in BRCA1 and BRCA2. In these database searches, we will use the specified query or the appropriate search technique for the database. The scope of the searches will be restricted to English language and human studies only. We do not aim to look for previously unreleased content or manuscripts. Our searches were based on a combination of key phrases and index terms (MeSH and Emtree). The following terms will be used for the search strategy (in all fields): “Vietnam”, “Vietnamese”, “women”, “female”, “breast cancer”, “breast carcinoma”, “mammary cancer”, “breast tumor”, “ovarian cancer”, “ovarian tumors”, “ovarian carcinomas”, “brca1”, “brca2”, “brca” with the cognitive logical operators “AND” and “NOT” are utilized for the purpose of efficiently finding publications. Table 1 provides comprehensive search algorithms for all databases.\n\nUsing the Mendeley Data (RRID:SCR_002750) online bibliography management application, we will collect, arrange, and export citations from the aforementioned databases. Duplicates will be detected and eliminated. The remaining citations will be considered for research selection.\n\nTypes of studies\n\nOnly peer-reviewed publications and all research designs to determine the frequency of BRCA1 and/or BRCA2 gene mutations in Vietnamese women will be included; while, case studies, literature reviews, systematic reviews, editorials, letters, and dissertations will not be included in this review.\n\nTypes of participants\n\nStudies that include Vietnamese women who are at least eighteen years old will be eligible for inclusion.\n\nTypes of comparison/exposure\n\nStudies investigating individual characteristics, cancer diagnoses (if any), and pathogenic mutations in BRCA1 and BRCA2 genes are considered eligible. The primary risk of this review will be on patient characteristics that have the potential to serve as risk factors or predictive variables for a future aggravation or malignancy, or cancer development.\n\nTypes of outcome measures\n\nWe will incorporate the original papers that include the proportion of Vietnamese women who have BRCA1/BRCA2 gene mutations in order to diagnose/to robustly diagnose cancer disease (e.g., breast cancer, ovarian cancer and other relevant cancers) or to estimate the risk of developing these cancers.\n\nSelection of studies for inclusion in the review\n\nThe first step will be to create an online sheet in Microsoft Excel (RRID:SCR_016137) for data extraction that can be shared among the team members. After that, we will run a pilot test with five articles chosen randomly and use the results to fine-tune the data extraction form appropriately. Two independent reviewers will evaluate the abstracts of all identified studies. Possible studies include articles that will be collected in full text for further evaluation. We will reach out to the authors to inquire about ambiguous points and request clarification. Disputes over inclusion will be resolved by consensus; if this is not feasible, we intend to bring in a third author who would then make a decision.\n\nThese could consist of, but are not limited to, the following:\n\n• Study characteristics (e.g., names of the authors, the publishing year, the journal, and the research design, hospital or community);\n\n• Demographic characteristics (e.g., age, education, profession, socioeconomic status, beginning menstrual cycles early, entering menopause later);\n\n• Prevalence of BRCA gene mutations (e.g., BRCA1, BRCA2 and both mutations);\n\n• Oncogenic mutations in BRCA1 and BRCA2 genes (e.g., type of genetic analysis method, BRCA variants, novel variant, distribution of pathogenic variants);\n\n• Cancer-related characteristics of the patients (e.g., type of cancer, age at diagnosis of cancer, cancer stage, tumour size);\n\n• Various health-related factors (e.g., smoking, co-morbidities, Body Mass Index, radiation treatment, exposure to diethylstilbestrol, genetic cancer predisposition syndromes);\n\n• Included in this research are those looking at various cancer risk factors, and family history is one of them. The family includes all relatives (parents, siblings, or other biological family members). Registers, medical records, or self-reported information are potential sources for obtaining data on family history. Cancer in the family history should be considered for any cancer, including but not limited to cancer diagnosed at a younger age, particular forms of cancer, relatives who have been diagnosed with two or more cancers or multiple cases of cancer, and relatives that have previously been shown to be carriers of cancer-causing mutations.\n\nUsing a tool that has already been pre-piloted, the essential data will be retrieved to an online sheet in Microsoft Excel Online. The data will be gathered separately by the two authors.\n\nFor observational studies, the included articles will be evaluated using the Newcastle Ottawa Scale (NOS),16 and for randomized controlled trials (RCTs), the Cochrane Risk of Bias (RoB) tool17 will be utilized. Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria18 will be used to grade the quality and strength of the evidence. Both evaluations will be conducted independently by two authors. The first five included studies will be evaluated, and inconsistencies in the assessment will be discussed before reviewing the remainder of the included research to ensure the two authors make equivalent risk assessments. In circumstances when there is disagreement, reaching a consensus will be accomplished via discussion.\n\nOur narrative synthesis of the results from the included studies will be framed around the characteristics of the subjects, the distribution of probable predictors and outcomes. When applicable, ranges, means (standard deviations) or medians (interquartile ranges), and frequencies (%) will be included in summary statistics. The extracted data will be loaded into RStudio (RRID:SCR_000432) software (version 2022.02.1 Build 461) with “meta” (RRID:SCR_019055), “metafor” (RRID:SCR_003450), and “ggplot2” (RRID:SCR_014601) packages for analysis. Using a random-effects model, the pooled prevalence estimate of BRCA1 gene mutation/BRCA2 gene mutation/both mutations in Vietnamese women will be calculated. The existence of statistical heterogeneity will be evaluated by the Cochrane’s Q statistic (with P<0.10 indicating the presence of statistically significant heterogeneity).19 In addition, the I2 statistic will be used to gauge the degree of statistical heterogeneity among the research (low, medium, and high heterogeneity, respectively, are defined by values of 25, 50, and 75%). If adequate data are available, we will conduct subgroup analyses based on the individual and family factors to identify plausible sources of heterogeneity and to study their effect on the prevalence of BRCA gene mutations. The examination of a funnel plot for signs of asymmetry and the use of Egger’s test will be used to determine the existence of publication bias in the analyses. If P<0.05, we will consider the possibility of publication bias to be present.\n\nThere is no need for ethical approval for this systematic review.\n\nAn earlier version of this article can be found on Research Square (https://doi.org/10.21203/rs.3.rs-1818425/v1).\n\nThis project is still in progress. Given the scarcity of relevant publications, searching for potential information sources such as grey databases are presently underway to carry out this systematic evaluation.\n\n\nDiscussion\n\nContextually, there is a paucity of national cancer screening programs and a shortage of infrastructure to deal with the rapidly expanding cancer treatment demands in Vietnam. Moreover, although legislative frameworks are in place for cancer control in Vietnam, there is still a lack of suitable financial and governance structures to support long-term cancer prevention and treatment plan. Therefore, the immediate requirement for enhanced cancer screening programs, enhanced risk stratification at clinical decision points, and the determination of the optimal timing for genetic testing concerning surgical decision-making in breast/ovarian cancer patients who carry the BRCA gene mutations are all issues that require urgent attention.\n\nTo the best of our knowledge, this systematic review and meta-analysis will be the first to synthesize the data from separate studies to derive reliable estimates of the prevalence of BRCA gene mutations and its related factors among Vietnamese women with and without a cancer diagnosis. Based on our findings, the general public and healthcare practitioners will also have a heightened awareness of the significance of genetic testing and risk management for individuals who possess germline mutations.\n\n\nData availability\n\nNo data are associated with this article.\n\n\nReporting guidelines\n\nFigshare: PRISMA-P checklist for ‘The burden of BRCA1 and BRCA2 gene mutations among Vietnamese women and their associated factors: A protocol for a systematic review and meta-analysis’. https://doi.org/10.6084/m9.figshare.20308413.20\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "References\n\nArmstrong K, Weiner J, Weber B, et al.: Early adoption of BRCA1/2 testing: who and why. Genet. Med. Off. J. Am. Coll. Med. Genet. 2003; 5(2): 92–98. Publisher Full Text\n\nKuchenbaecker KB, Hopper JL, Barnes DR, et al.: Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers. JAMA. 2017 Jun; 317(23): 2402–2416. Publisher Full Text\n\nWorld Health Organization: Breast cancer.2021 [cited 2022 Jun 17].Reference Source\n\nBray F, Ferlay J, Soerjomataram I, et al.: Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018 Nov; 68(6): 394–424. PubMed Abstract \| Publisher Full Text\n\nTorres D, Bermejo JL, Rashid MU, et al.: Prevalence and Penetrance of BRCA1 and BRCA2 Germline Mutations in Colombian Breast Cancer Patients. Sci. Rep. 2017; 7(1): 4713. PubMed Abstract \| Publisher Full Text\n\nNorquist BM, Harrell MI, Brady MF, et al.: Inherited Mutations in Women With Ovarian Carcinoma. JAMA Oncol. 2016 Apr 1; 2(4): 482–490. PubMed Abstract \| Publisher Full Text\n\nSharma P, Klemp JR, Kimler BF, et al.: Germline BRCA mutation evaluation in a prospective triple-negative breast cancer registry: implications for hereditary breast and/or ovarian cancer syndrome testing. Breast Cancer Res. Treat. 2014 Jun; 145(3): 707–714. PubMed Abstract \| Publisher Full Text\n\nWorld Health Organization: Cancer in Viet Nam. World Health Organization (WHO) Representative Office for Vietnam;2022 [cited 2022 Jun 7].Reference Source\n\nThe International Agency for Research on Cancer (IARC): GLOBOCAN 2020. Vietnam.2021.Reference Source\n\nGrafodatskaya D, O’Rielly DD, Bedard K, et al.: Practice guidelines for BRCA1/2 tumour testing in ovarian cancer. J. Med. Genet. 2022 Apr 6; jmedgenet-2021-108238.Reference Source\n\nBerliner JL, Fay AM, Cummings SA, et al.: NSGC practice guideline: risk assessment and genetic counseling for hereditary breast and ovarian cancer. J. Genet. Couns. 2013 Apr; 22(2): 155–163. PubMed Abstract \| Publisher Full Text\n\nNakamura S, Kwong A, Kim S-W, et al.: Current Status of the Management of Hereditary Breast and Ovarian Cancer in Asia: First Report by the Asian BRCA Consortium. Public Health Genomics. 2016; 19(1): 53–60. PubMed Abstract \| Publisher Full Text\n\nShamseer L, Moher D, Clarke M, et al.: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015 Jan; 349: g7647. Publisher Full Text\n\nMoher D, Liberati A, Tetzlaff J, et al.: Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009 Jul 21; 339: b2535. PubMed Abstract \| Publisher Full Text Reference Source\n\nStroup DF, Berlin JA, Morton SC, et al.: Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000 Apr; 283(15): 2008–2012. PubMed Abstract \| Publisher Full Text\n\nWells GA, Shea B, O’Connell D, et al.: The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Oxford:2000.\n\nHiggins JPT, Altman DG, Gøtzsche PC, et al.: The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011 Oct; 343: d5928. PubMed Abstract \| Publisher Full Text\n\nBerkman ND, Lohr KN, Ansari MT, et al.: Grading the strength of a body of evidence when assessing health care interventions: an EPC update. J. Clin. Epidemiol. 2015 Nov 1; 68(11): 1312–1324. PubMed Abstract \| Publisher Full Text\n\nHiggins JPT, Thompson SG: Quantifying heterogeneity in a meta-analysis. Stat. Med. 2002 Jun; 21(11): 1539–1558. PubMed Abstract \| Publisher Full Text\n\nTran D, Tran P, Vu C, et al.: PRISMA-P checklist. [Dataset]. figshare.2022. Online resource. Publisher Full Text" }	[ { "id": "273060", "date": "13 Jun 2024", "name": "Weang Kee Ho", "expertise": [ "Reviewer Expertise systematic review" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis protocol aims to synthesize evidence regarding the proportion of BRCA mutations and associated risk factors. However, the current protocol lacks clarity on several key aspects, including the review objective, target populations (e.g., type of cancer, healthy or affected individuals, or both), inclusion criteria (e.g., types of studies considered), and the intended meta-analysis for this review (e.g., random model and why). Below are major considerations to enhance the protocol's clarity and provide a more focused objective:\nClarify Target Populations: Clearly define whether the review will include studies on specific cancer types, healthy individuals, affected individuals, or a combination of these groups. Specify the rationale for including each population and how do they help to address the research questions. Specify Inclusion Criteria: Outline the specific types of studies that will be considered for inclusion. This should include criteria such as study design (e.g., randomized controlled trials, cohort studies, case-control studies) and population characteristics (e.g., healthy or cancer patients). For instance, how do these studies or target populations help to address research questions, particularly RCTs and healthy women? Detail the Meta-Analysis Plan: Provide a comprehensive plan for the meta-analysis, including the statistical methods to be used and how data will be analysed. Currently, it is not clear if author’s intention is to pool the prevalence of mutations only or both prevalence and risk factors. If so, how do authors intend to include healthy individuals in the analyses? Justify the choice of the meta-analysis model. Search Strategy: The search will include studies published until June 2023. Given that this review is not yet published and the status is ongoing, will the authors be updating the search? Clarify Protocol Statements:\nWide Range of Estimates: Clarify what estimates are being referred to and for what purpose. For example, \"Because there is a wide range of estimates of BRCA mutation prevalence, it may be difficult for physicians to choose which one to use.\" Risk Factors Prompting BRCA Testing: Clarify the meaning of \"Which risk factors of Vietnamese women should prompt a physician to perform a BRCA gene test for the client?\" Is the review aiming to provide guidance on which risk factors should trigger BRCA testing? Is this the expected finding implication, such as population-specific clinical criteria?\n\nIs the rationale for, and objectives of, the study clearly described? Partly\n\nIs the study design appropriate for the research question? Yes\n\nAre sufficient details of the methods provided to allow replication by others? No\n\nAre the datasets clearly presented in a useable and accessible format? Not applicable", "responses": [] } ]	1	https://f1000research.com/articles/11-852
https://f1000research.com/articles/11-843/v1	27 Jul 22	{ "type": "Research Article", "title": "Reverse order law for outer inverses and Moore-Penrose inverse in the context of star order", "authors": [ "Umashankara Kelathaya", "Manjunatha Prasad Karantha", "Umashankara Kelathaya" ], "abstract": "The reverse order law for outer inverses and the Moore-Penrose inverse is discussed in the context of associative rings. A class of pairs of outer inverses that satisfy reverse order law is determined. The notions of left-star and right-star orders have been extended to the case of arbitrary associative rings with involution and many of their interesting properties are explored. The distinct behavior of projectors in association with the star, right-star, and left-star partial orders led to several equivalent conditions for the reverse order law for the Moore-Penrose inverse.", "keywords": [ "Generalized inverses", "Outer inverses", "Moore-Penrose inverse", "Reverse order law", "Star order" ], "content": "Introduction\n\nGiven any invertible matrices A and B, it is well-known that (AB)−1 = B−1A−1. This property is often called reverse order law for the invertible matrices. This law is easily extended for the invertible elements from an associative ring with identity. This notion has been well studied in the literature and it is known that the analogue is not true in the case of generalized inverses, unless there are certain additional conditions. Several researchers came up with many necessary as well as sufficient conditions for the reverse order law to hold in the case of different generalized inverses. Ivan Erdelyi in 1966 discussed reverse order law for Moore-Penrose inverses of complex matrices in the context of partial isometries1. Greville, in his celebrated paper2, gave several equivalent conditions for the reverse order law for Moore-Penrose inverse of matrices over complex field. He proved that given two complex matrices A and B with AB defined, the reverse order law (AB)† = B†A† holds if and only if the equations A†ABBA = BBA and BB†AAB = AAB are satisfied, which is equivalent to the column space inclusions 𝒞 (BBA) ⊆ 𝒞 (A) and 𝒞 (AAB) ⊆ 𝒞 (B). Here, the notations † and * denote the Moore-Penrose inverse and conjugate transpose, respectively. Motivated by this paper, Hartwig discussed equivalent conditions for triple reverse order law for Moore-Penrose inverses (see, 3) and Y. Tian discussed equivalent conditions for multiple reverse order law for Moore-Penrose inverses of complex matrices (see, 4).\n\nThe reverse order law for Moore-Penrose inverses in the context of elements from an associative ring with involution was studied previously5. Also, it has been extended to different generalized inverses including group inverse, Drazin inverse, core inverse, Drazin Moore-Penrose (DMP) inverse and pseudo core inverse, of matrices over a field, operators on Hilbert space, and elements of rings. Interested readers may refer to 4, 6–10 and the references therein.\n\nAnother notion of our concern is the star order, introduced by M. P. Drazin in 197811. In the beginning of 90’s, J. K. Baksalary and S. K. Mitra considered weaker conditions than those considered by Drazin and introduced left-star and right-star orders12. Benitez et al.,13 discussed some equivalent conditions for reverse order law for group inverse and Moore-Penrose inverse in terms of sharp and star partial orders, respectively, where most of his results assume that one of the matrices under consideration is Equal Projector (EP).\n\nIn the present paper, one of our main focuses is to study the reverse order law for Moore-Penrose inverses of arbitrary elements, which need not be EP, in terms of different partial orders. While exploring the extension of reverse order law for the class of outer inverses, it may be noted that an outer inverse of given element is not uniquely established, unlike in the cases of inverse, Moore-Penrose inverse and group inverses. So, a natural question arises is that whether every outer inverse (ab)= of ab could be written as gbga for some outer inverses gb of b and ga of a. In case the answer is affirmative, then verify if\n\nholds. While answering these questions, a few noteworthy properties of right-star, left-star and star partial orders are studied. Further, we give some equivalent conditions for the reverse order law for Moore-Penrose inverse in terms of different star partial orders.\n\n\nPreliminaries\n\nThroughout our discussion, 𝒜 denotes an associative ring, need not be with unity unless indicated otherwise. We use the notations a, b, c, ... for the elements of a ring and A, B, C, ... for matrices under discussion. Let a ∈ 𝒜. If there exists a g ∈ 𝒜 satisfying aga = a, then a is said to be regular and g is called a generalized inverse (or simply a g-inverse) of a. An arbitrary g-inverse of a is denoted by a−. If there exists a g ∈ 𝒜 satisfying gag = g, then such a g is called an outer inverse of a. An arbitrary outer inverse of a is denoted by a=. A generalized inverse, which is also an outer inverse, is called a reflexive generalized inverse and an arbitrary reflexive generalized inverse of a is denoted by ar−. A commuting reflexive generalized inverse of a is called the group inverse of a and it is denoted by a#. It is unique whenever it exists. The classes {a−}, {a=}, and {ar−} denote the class of all g-inverses, outer inverses and reflexive g-inverses of a, respectively. For basic notions of generalized inverses in the context of matrices we refer the readers to 14, 15, and 16.\n\nAn involution ‘’ of a ring 𝒜 is an anti-automorphism whose square is identity; i.e.\n\nInvolution ‘’ is said to be proper (see 11) if for all a, b ∈ 𝒜,\n\nA proper -ring is a ring equipped with a proper involution ‘’. A ring is said to be regular ring if all of its elements are regular. A -regular ring is a regular ring with involution ‘’ such that aa = 0 ⇒ a = 0. Observe that the involution is proper if and only if aa = 0 ⇒ a = 0 holds. An important consequence of this property of involution is the -cancellation law.\n\nAn element a is said to satisfy left (right) -cancellation law if aax = aay ⇒ ax = ay (xaa* = yaa* ⇒ xa = ya). Element a is said to be -cancellable if it satisfies both left and right -cancellation laws.\n\nFor an associative ring 𝒜 with involution '' and a ∈ 𝒜, consider the following four equations:\n\nAn element g satisfying the equations {i, j, ...} ⊆ {1, 2, 3, 4}, is called {i, j, ...}-inverse of a and the class of all {i, j, ...}-inverses of a is denoted by {a{i, j,...}}. An element g ∈ 𝒜 satisfying all of (1), (2), (3) and (4), if exists, is unique and is called the Moore-Penrose inverse of a. The existence of Moore-Penrose inverse for the elements of a -regular ring was proved by Kaplansky17, almost at the same time that Penrose18 proved the existence in the case of matrices. The Moore-Penrose inverse of an element a is denoted by a†. We will use the notation 𝒜† to denote the set of all elements of 𝒜 having Moore-Penrose inverse. Note that the elements of 𝒜† are -cancellable.\n\nAn element a is Hermitian if a = a, and it is an idempotent if a2 = a. Hermitian idempotents are called projectors. If a† is the Moore-Penrose inverse of a, then both aa† and a†a are projectors.\n\nThe right annihilator ao of an element a ∈ 𝒜 is the set {x ∈ 𝒜 : ax = 0} and the left annihilator oa is the set {y ∈ 𝒜 : ya = 0}. If 1 ∉ 𝒜, then the right annihilator (1 − a)o is defined as {x ∈ 𝒜 : x = ax} and the left annihilator o(1 − a) = {y ∈ 𝒜 : y = ya} (see 19). For any a, b ∈ 𝒜, we write a≃csb (a≃rsb) if the principal right (left) ideals generated by a and b coincide. We say that a and b are space equivalent if both a≃csb and a≃rsb are true. In such a case we write a≃spb.\n\nThe sum a + b is written as a ⊕ b (⊕ refers to direct sum) if a𝒜 ∩ b𝒜 = {0} and 𝒜a ∩ 𝒜b = {0}. If so is the case, then we say that a and b are disjoint. We refer to 19, 20, and 21 for more details on the above notions.\n\nThe minus partial order is helpful in discussing many of the properties of star partial order. For the initial works on minus partial order, one may refer to 21–23.\n\nDefinition 1 (Minus Partial Order21,22). The minus partial order is a relation, denoted by ≤−, defined on set of all regular elements of 𝒜 by a ≤− b if there exists a g-inverse g of a such that ag = bg and ga = gb.\n\nFor the proof of the following theorem, see 24 and 25.\n\nTheorem 2 (Right-left Symmetry24,25). Let 𝒜 be an associative ring with unity and let a, b, c ∈ 𝒜 such that a = b + c is regular. Then the following statements are equivalent.\n\n(i) b ≤− a\n\n(ii) b𝒜 ⊕ c𝒜 = a𝒜\n\n(iii) b𝒜 ∩ c𝒜 = {0} = 𝒜b ∩ 𝒜c\n\n(iv) 𝒜b ⊕ 𝒜c = 𝒜a\n\n(v) c ≤− a\n\n(vi) b ∈ a𝒜 ∩ 𝒜a and {a−} ⊆ {b−}\n\n(vii) c ∈ a𝒜 ∩ 𝒜a and {a−} ⊆ {c−}.\n\nNote that the theorem holds even in the case of an associative ring without unity, provided a, b, c are regular.\n\nDefinition 3 (Star Order11). Let 𝒜 be an associative ring with involution ‘’ and a, b ∈ 𝒜. The relation ≤ defined by a ≤* b if aa = ab and aa* = ba* is called star order on 𝒜. If a ≤* b, then we say that the element a is dominated by b under star order.\n\nDrazin, in 11 noticed that the relation star order defined on a -semigroup is a partial order. He pointed out that if the Moore-Penrose inverses of a and b exist, then,\n\nand\n\nHe also noted that\n\nDefinition 4. A partial order ≤2 on a set S2 is said to be dominated by a partial order ≤1 defined on set S1 if S2 ⊆ S1 and for a, b ∈ S2,\n\nNote that the minus partial order dominates the star partial order (as seen from (5)).\n\n\nReverse order law for outer inverses\n\nIn this section we probe if the reverse order law mentioned in the earlier section holds. In the following lemma, we observe that the inclusion {(ab)=} ⊆ {b=a=} always holds.\n\nLemma 5. For a, b ∈ 𝒜, we have\n\nProof. Given an outer inverse gab of ab, note that gaba is an outer inverse of b and bgab is an outer inverse of a. Further, we have gab = gab(ab)gab = (gaba)(bgab) ∈ {b=a=}, proving (8). Hence the lemma.\n\nUnfortunately, the reverse of inclusion appearing in (8) need not be true. We have a counter example in the matrix case. For A=[1236] and B=[2211], consider GA=[1000] and GB=[0100], which are outer inverses of A and B, respectively. Note that GBGA=[0100] is not an outer inverse of AB=[81648], as we have\n\nThis proves that {B=A=} ≠ {(AB)=}.\n\nIn 26 and 27, the authors presented necessary and sufficient conditions for {B{1,2,3}A{1,2,3}} ⊆ {(AB){1,2,3}} in the case of matrices and bounded linear operators on Hilbert spaces, respectively. An equivalent condition for the inclusion {B{1,2}A{1,2}} ⊆ {(AB){1,2}} is given in 28 for bounded linear operators on complex Hilbert spaces.\n\nNow, our interest in this section is to characterize the subset of {b=a=}, which equals to {(ab)=}, where a, b ∈ 𝒜.\n\nTheorem 6. Let 𝒜 be any associative ring and let a, b ∈ 𝒜. Then,\n\nwhere a1 = agaa ≤− a and b1 = bgbb ≤− b.\n\nProof. Note that outer inverse of any element is a regular element in the ring, and if x is any regular element in 𝒜, then x ∈ x𝒜 ∩ 𝒜x.\n\nNow consider any gab ∈ {(ab)=}. As noted earlier in the Lemma 5, we have gab = gababgab in the form of gbga, where gb = gaba ∈ {b=} and ga = bgab ∈ {a=}. Now,\n\nThe proof of ga𝒜 = b1𝒜 is similar. From the definition of a1, it is verified that ga is a generalized inverse of a1. Further, we get a1ga = aga and gaa1 = gaa, proving that a1 ≤− a. b1 ≤− b is similarly proved.\n\nNow to prove (9) and the theorem, consider ga ∈ {a=} and gb ∈ {b=} satisfying 𝒜gb = 𝒜a1 or ga𝒜 = b1𝒜. Now consider the case of 𝒜gb = 𝒜a1, whereas the other case similar. Since gb and a1 are regular elements, we have gb, a1 ∈ 𝒜gb = 𝒜a1 and therefore, a1bgb = a1 and gaabgb = gaa. Now, using the same we get\n\nproving that gbga ∈ {(ab)=}.\n\nRemark 1. Note that the set {gbga : ga ∈ {a=}, gb ∈ {b=}, such that 𝒜gb = 𝒜a1 or ga𝒜 = b1𝒜} does not determine exact class of pairs of outer inverses (ga, gb) of a and b whose product determine {(ab)=}. It may be noted in each of the cases (i) ga𝒜 ⊂ b1𝒜 (ii) b1𝒜 ⊂ ga𝒜 (iii) 𝒜a1 ⊂ 𝒜gb (iv) 𝒜gb ⊂ 𝒜a1, we get\n\nTherefore, determining the exact class of (ga, gb) determining {(ab)=} remains to be a problem to probe.\n\nLet 𝒜 be an associative ring with involution ‘’. Then, we have the following corollary.\n\nCorollary 7. Given elements a, b ∈ 𝒜, if ga and gb are reflexive g-inverses of a and b, respectively, satisfying any of the cases (a) ga𝒜 ⊂ b𝒜 (b) b𝒜 ⊂ ga𝒜 (c) 𝒜a ⊂ 𝒜gb (d) 𝒜gb ⊂ 𝒜a, then gbga∈{(ab)r−}. Further, we have the following.\n\n(i) In the case of (a) or (c) and if ga is a {1, 2, 3}-inverse of a, then we have\n\n\n\n(ii) In the case of (b) or (d) and if gb is a {1, 2, 4}-inverse of b, then we have\n\n\n\n(iii) If a†, b† exists and a𝒜 ⊂ b𝒜, then we have\n\n\n\n(iv) If a†, b† exists and b𝒜 ⊂ a𝒜, then we have\n\n\n\n(v) If a†, b† exist and a≃csb, then (ab)† exists, in which case\n\n\n\nProof. In the cases of (a), (b), (c), and (d) we have bgbga = ga, gaab = b, abgb = a, and gbgaa = gb, respectively. Now, by direct substitution it is easily verified that gbga is a reflexive generalized inverse of ab.\n\nIf ga ∈ a{1,2,3} and the condition (a) or (c) is satisfied, then abgbga = aga proving that gbga ∈ {(ab){1,2,3}}. Hence, (i) is proved.\n\nSimilarly, if gb ∈ a{1,2,4} and the condition (b) or (d) is satisfied, then we have gbgaab = gbb proving gbga ∈ {(ab){1,2,4}} and (ii).\n\nProof of (iii) and (iv) are consequences of (i) and (ii), respectively, since a†≃spa.\n\nProof of (v) is an immediate consequence of (iii) and (iv).\n\nLet A and B be any two complex matrices with AB defined. According to Corollary 7 (v), we have (AB)† = B†A† if ℛ(A) = ℛ(B), where ℛ(X ) denotes the row space of X. However, the converse need not be true. For example, if\n\nthen (AB)†=[0100] = B†A†. But ℛ(B) ≠ ℛ(A).\n\n\nLeft-star and right-star orders\n\nIn the present section, we extend the notions of left-star and right-star orders to the case of elements from an associative ring with involution. These notions were originally defined in the matrix case by Baksalary and Mitra in 12. As noted earlier, Drazin proved that the star order is a partial order on a proper -semigroup and hence on a proper -ring (see 11).\n\nFollowing the matrix case, we shall now define the left-star and right-star orders in the context of associative rings with involution.\n\nDefinition 8. For a, b ∈ 𝒜, we say that a is dominated by b under left-star order, and denote a ≤l* b if aa = ab, a ∈ a𝒜 and a𝒜 ⊆ b𝒜. We say that a is dominated by b under right-star order, and denote a ≤r* b if aa* = ba, a ∈ 𝒜a and 𝒜a ⊆ 𝒜b.\n\nBaksalary and Mitra in 12 showed that the right-star and left-star orders are partial orders on the class of matrices over complex field. In the case of rings, clearly these relations are reflexive. Further, if a ≤l b and b ≤l* c, then we have aa = ab = ac, since a = xb* for some x and bb = bc. Thus, the the relation ≤l* is transitive and preorder on ring 𝒜. Additionally, if a or b is left -cancellable and a ≤l b and b ≤l* a, then a = b. For the proof, consider the case of a being left -cacellable. Then, aa = ab ⇒ a = b, since b = ax for some x and a ∈ a𝒜. Hence, we have the following theorem.\n\nTheorem 9. Let 𝒜 be an associative ring with involution ‘’. Then the relation ≤l* (≤r) is a partial order on the class of left -cancellable (right -cancellable) elements. In particular, if 𝒜 is a proper -ring, then ≤l* and≤r* are partial orders on 𝒜.\n\nNow, we shall proceed to prove some of the basic properties of left-star ordering. Analogous results for the right-star order can be obtained in the similar manner.\n\nTheorem 10. Let 𝒜 be an associative ring and let a ∈ 𝒜 be left -cancellable. Then the following statements hold.\n\n(i) a ≤l b ⇔ a* ≤r* b\n\n(ii) If p is a projector and a ≤l p, then a is also a projector.\n\n(iii) If p and q are projectors, then the following are equivalent.\n\n(a) p ≤l* q\n\n(b) p𝒜 ⊆ q𝒜\n\n(c) 𝒜p ⊆ 𝒜q\n\n(d) p ≤r* q\n\n(e) p ≤* q\n\n(f) p ≤− q\n\n(iv) If q is a projector, then a ≤l* q ⇔ a ≤r* q ⇔ a ≤* q ⇔ a ≤− q.\n\nProof. Note that (i) follows from the properties of involution ‘’.\n\nFrom the hypothesis of (ii), we have aa = ap = pa and a ∈ a𝒜 ⊆ p𝒜. Therefore, a = pa = aa proving that a is a projector. This proves (ii).\n\nThe equivalences of (a)-(f) in (iii) are easily verified using the properties of projectors.\n\nProof of (iv) follows from the statements (ii) and (iii).\n\nNow, for a, b, c ∈ 𝒜†, we make the following observations.\n\n(i) a ≤l* b ⇔ a† ≤l* b† and a ≤r* b ⇔ a† ≤r* b†: If a ≤l* b, then aa = ab, a ∈ a𝒜 and a𝒜 ⊆ b𝒜. So, aa = ba and 𝒜a† = 𝒜a* ⊆ 𝒜b* = 𝒜b†. Then, we have bb†a = a and a†bb† = a†. Thus, a† ∈ 𝒜. Also, a†a = a†b = b(a†) and hence,\n\n\n\nFurther,\n\n\n\nThus, a† ≤l* b†. Converse part follows by the uniqueness of Moore-Penrose inverse and the fact that (a†)† = a. A similar argument will prove the second equivalence.\n\n(ii) a ≤l* b ⇔ aa† = ab† (a ≤r* b ⇔ a†a = b†a): Follows by noting that aa† = ab† is equivalent to (10) and (11).\n\n(iii) If a ≤l* b, then b† is a {1,3}-inverse of a (If a ≤r* b, then b† is a {1,4}-inverse of a): From (ii) above, it follows that ab† is Hermitian. Also, postmultiplying aa† = ab† by a, we get that b† is a g-inverse of a.\n\n(iv) If a ≤l* b (or a ≤r* b), then (bb†a)† = a†bb† and (ab†b)† = b†ba†: If a ≤l* b, then we have a𝒜 ⊆ b𝒜, 𝒜a† ⊆ 𝒜b†, a†𝒜 ⊆ b†𝒜 (refer (i) above) and hence, 𝒜a ⊆ 𝒜b. From the first two inclusions, we get that bb†a = a and a†bb† = a† proving that (bb†a)† = a†bb†. The last two inclusions imply the equations b†ba† = a† and ab†b = a proving that (ab†b)† = b†ba†.\n\n(v) ≤l* and ≤r* are partial orders on 𝒜†: Evidently, ≤l* is reflexive. Suppose that a ≤l* b and b ≤l* c. Then a = (a†)aa = (a†)ab = aa†b = b as it follows from b𝒜 ⊆ a𝒜 that aa†b = b. Hence the anti-symmetry. Now for some a.b, c ∈ 𝒜, suppose that a ≤l* b and b ≤l* c. Then aa = ab and bb = bc with a𝒜 ⊆ b𝒜 ⊆ c𝒜. Now,\n\n\n\nas it follows from a𝒜 ⊆ b𝒜 that bb†a = a. Hence, ≤l* is transitive, which proves that ≤l* is a partial order.\n\n(vi) The minus order dominates the left-star and right-star orders: Suppose that a ≤l* b. Then a†a = a†b and a𝒜 ⊆ b𝒜. So, a = aa†b and a = bb−a for any g-inverse b− of b. Hence, a ∈ b𝒜 ∩ 𝒜b. Also,\n\n\n\nand hence {b−} ⊆ {a−}. Now, from Theorem 2 it follows that a ≤− b.\n\n(vii) If a ≤* b, then b† is a {1,3,4}-inverse of a and b†ab† = a†: The proof that b† is a {1,3,4}-inverse of a follows from the equivalence given in (6). Further, using the same equivalence, we get that b†ab† = b†aa† = a†aa† = a†.\n\nFrom (7), we have a† ≤* b†. In fact, if g is a {1,3,4}-inverse of a, then\n\n\n\nand similarly, a†(a†)* = g(a†). Hence, a† ≤ g. Therefore, we have\n\n\n\nwhere the minimum is with respect to the star order (see Theorem 211).\n\n(viii) If c ≤* a, then c† is a {2,3,4}-inverse of a: The proof follows by (5). From (7), we have c† ≤* a†. In fact, it is true that h ≤* a† for any {2,3,4}-inverse h of a. Thus, we have\n\n\n\nwhere the maximum is with respect to the star order (Theorem 211).\n\n(ix) The following implication follows from (5),\n\n\n\nIf a ≤* b and c = b − a, then by (12) and Theorem 2 it follows that b = a ⊕ c. Moreover, b† exists if and only if a† and c† exist, in which case,\n\n\n\nThis can be seen as follows: If a ≤* b, then ac = ab − aa = 0, which implies a†c = 0. Similarly, ca† = 0, ac† = 0, and c†a = 0.\n\n\nThe reverse order law for Moore-Penrose inverse\n\nThe projectors play a prominent role in obtaining several equivalent conditions for the reverse order law for Moore-Penrose inverse. They have distinct properties associated with the star order, a few of which are discussed in 29. In this section, we shall note a few more interesting behaviors of projectors associated with star, left-star and right-star orders. An important observation in proving our main theorem is the following fact: For a projector p, we have pa ≤r a (ap ≤l* a) if and only if pa ≤* a (ap ≤* a).\n\nLemma 11. Let 𝒜 be an associative ring with involution ‘’ and let p be a projector. For any a ∈ 𝒜, the following are equivalent.\n\n(i) (pa)(pa) = a(pa)\n\n(ii) paa ∈ o(p − 1)\n\n(iii) p commutes with aa\n\n(iv) paa is Hermitian\n\n(v) pa ≤* a\n\nIn particular, if a ∈ 𝒜a, then\n\nProof. Note that (i)⇒(ii), (ii)⇒(iii), and (iii)⇒(iv) are obvious.\n\nEvidently, (pa)(pa) = (pa)a. Now, pa(pa)* = p(pa)a* = paa* = a(pa). This proves (iv)⇒(v).\n\nNow, (14) follows from the definition of star order, equivalence of (i) and (v), and by noting that a ∈ 𝒜a implies that pa ∈ 𝒜pa, as p is idempotent.\n\nSymmetrically, we have the following result.\n\nLemma 12. Let 𝒜 be an associative ring with involution ‘’ and let p be a projector. For any a ∈ 𝒜, the following are equivalent.\n\n(i) (ap)(ap) = (ap)a\n\n(ii) aap ∈ (1 − p)o\n\n(iii) p commutes with aa\n\n(iv) aap is Hermitian\n\n(v) ap ≤ a\n\nIn particular, if a ∈ a𝒜, then\n\nLemma 13. Let 𝒜 be an associative ring with involution ‘’ and let a ∈ 𝒜. If p is a projector commuting with a, then pa ≤ a and ap ≤* a.\n\nProof. Follows by noting that the hypothesis implies statement (iii) of Lemma 11 as well as Lemma 12.\n\nNow we prove the main theorem of the present paper. The equivalence of statements (i) and (vii) is discussed in 2 and in 21 and the equivalence of (i) and (vi) is proved in 30. However, our proof is in the general setting of Lemma 11 and Lemma 12, which use the properties of projectors.\n\nTheorem 14. Let 𝒜 be a proper -ring. For a, b ∈ 𝒜†, the following are equivalent.\n\n(i) (ab)† = b†a†\n\n(ii) (a†ab)† = b†a†a and (abb†)† = bb†a†.\n\n(iii) a†ab ≤r b and bb† ≤l* a\n\n(iv) (a†ab)(a†ab)* = b(a†ab)* and (abb†)(abb†) = (abb†)a\n\n(v) a†abb* ∈ o(a†a − 1) and aabb† ∈ (1 − bb†)o\n\n(vi) a†abb = bba†a and aabb† = bb†aa\n\n(vii) a†abb and aabb† are Hermitian\n\n(viii) a†ab ≤ b and abb† ≤* a\n\nProof. (i)⇒(ii) can be verified by direct substitution. Conversely, premultiplying a†ab(b†a†a)a†ab = a†ab by a and postmultiplying (b†a†a)a†ab(b†a†a) = b†a†a by a†, we get abb†a†ab = ab and b†a†abb†a† = b†a†, respectively. Also, we have abb†a† = abb†(bb†a†) and b†a†ab = (b†a†a)a†ab. Hence, abb†a† and b†a†ab are Hermitian. Thus, we have (ab)† = b†a†, proving (ii)⇒(i). This proves (i)⇔(ii).\n\nThe equivalence of the statements (iii)-(viii) will follow from the Lemma 11 and Lemma 12 noting that a†a and bb† are projectors. It remains to prove that (i)⇔(viii).\n\n(i)⇔(viii): Evidently, (a†ab)a†ab = ba(a†)a† ab = (ba†a)b = (a†ab)b.\n\nPremultiplying ba = b†a†ab(ab)* by abbb, we get\n\nTaking u = bba* and v = a†abba, we note that uu = uv = vu = vv = abba†abba* and hence u = v, since ‘’ is a proper involution. That is, bba* = a†abba. Therefore, we get\n\nwhich proves that a†ab ≤* b. Proof of other inequality is symmetric.\n\nConversely, we have that b† and a† are {1,3,4}-inverses of a†ab and abb†, respectively. Hence, b†a†ab and abb†a† are Hermitian. Also, premultiplying a†abb†a†ab = a†ab by a, we get abb†a†ab = ab.\n\nFurther, 𝒜 (a†ab)* ⊆ 𝒜b* = 𝒜b†, gives\n\nPremultiplying by b†(b†)* and post-multiplying by a†, we get\n\nproving (i).\n\nFrom (i)⇔ (ii) of Theorem 14, we have (a†ab)† = b†a†a and (abb†)† = bb†a† if and only if the reverse order law for Moore-Penrose inverse holds. Further from (i)⇔(viii) and (7), we have (ab)† = b†a† if and only if (a†ab)† ≤* b† and (abb†)† ≤* a†. Hence, we have the following corollary.\n\nCorollary 15. Let 𝒜 be a proper -ring and let a, b ∈ 𝒜†. Then the following are equivalent.\n\n(i) (ab)† = b†a†\n\n(ii) b†a†a ≤l b† and bb†a† ≤r* a†\n\n(iii) (b†a†a)(b†a†a) = (b†a†a)b† and (bb†a†)(bb†a†)* = a†(bb†a†)\n\n(iv) (b†)b†a†a ∈ (a†a − 1)o and bb†a†(a†)* ∈o (1 − bb†)\n\n(v) a†a(b†)b† = (b†)b†a†a and a†(a†)bb† = bb†a†(a†)\n\n(vi) a†a(b†)b†and a†(a†)bb†are Hermitian\n\n(vii) b†a†a ≤* b† and bb†a† ≤* a†\n\nFrom Theorem 14, we have that a†ab ≤r* b and abb† ≤l* a if and only if the reverse order law (ab)† = b†a† holds. The equivalence fails to exist if we interchange the left-star and right star orders. However, one of the implications is true and the same is proved in the following theorem.\n\nTheorem 16. Let 𝒜 be a proper -ring. Let a, b ∈ 𝒜 be such that a† and b† exist. Then,\n\nProof. We have, (a†ab)(a†ab) = ba(a†)a†ab = ba†ab = (a†ab)b. Further, taking u = a†ab and v = bb†a†ab, we get uu = uv = vu = vv = ba†ab.\n\nThus,\n\nwhich proves that a†ab ≤l* b. Proof of other inequality is symmetric.\n\nRemark 2. The converse of the above theorem need not be true in general. For example, if\n\nthen\n\nso that\n\nClearly, A†AB ≤l* B and ABB† ≤r* A. But\n\nFrom Lemma 11 and Lemma 12, we have that a†ab ≤r* b implies a†ab ≤* b and abb† ≤l* a implies abb† ≤* a. It is not true in general that a†ab ≤* b whenever a†ab ≤l* b and that abb† ≤* a whenever abb† ≤r* a. The following lemma gives a sufficient condition for this result to hold.\n\nTheorem 17. Let 𝒜 be a proper -ring and let a, b ∈ 𝒜†. Suppose (ab)† = b†a†. Then, a†ab ≤l b implies a†ab ≤* b and abb† ≤r* a implies abb† ≤* a.\n\nProof. Since a†ab𝒜 ⊆ b𝒜 , we have\n\nas desired. The second implication can be proved similarly.\n\nThe proof of the following theorem is immediate from Theorem 14 and Lemma 13, noting that a†a and bb† are projectors commuting with b and a, respectively. This theorem shows that only two commutative relations out of four, given by Erdelyi in (Theorem 11) are sufficient for the reverse order law.\n\nTheorem 18. Let 𝒜 be a proper *-ring and let a, b ∈ 𝒜 be such that a† and b† exist. If both a(bb†) = (bb†)a and b(a†a) = (a†a)b are true, then (ab)† = b†a†.\n\n\nConclusions\n\nIn the present paper, the reverse order law for outer inverses is discussed. The notions of left-star and right-star orderings are extended to the case of associative rings with involution and several properties of the same are discussed. Also, necessary and sufficient conditions—in terms of star, left-star and right-star orders—for the reverse order law for Moore-Penrose inverse are given. The discussion on left-star and right-star partial orderings appears to help in further study of relation between star partial order and column space decomposition of matrices. Further, it has been noted in Theorem 10 that, in the class of all projectors the star, left-star, right-star and minus orders are all equivalent. The classification of elements of associative rings for which any two or more orders are equivalent seems to be an interesting problem to explore and the same will be presented in the subsequent papers.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.", "appendix": "References\n\nErdelyi I: On the ``Reverse Order Law'' Related to the Generalized Inverse of Matrix Products. Journal of the Association for Computing Machinery. 1966; 13(3): 439–443. Publisher Full Text\n\nGreville TNE: Note on the Generalized Inverse of a Matrix Product. Journal of the Society for Industrial Applications of Mathematics. 1966; 8(4): 518–521. Publisher Full Text\n\nHartwig RE: The reverse order law revisited. Linear Algebra Appl. 1986; 76: 241–246. Publisher Full Text\n\nTian Y: Reverse order laws for the generalized inverses of multiple matrix products. Linear Algebra Appl. 1994; 211: 85–100. Publisher Full Text\n\nKoliha JJ, Djordjević D, Cvetković D: Moore–Penrose inverse in rings with involution. Linear Algebra Appl. 2007; 426(2–3): 371–381. Publisher Full Text\n\nCao C, Zhang X, Tang X: Reverse order law of group inverses of products of two matrices. Appl Math Comput. 2004; 158(2): 489–495. Publisher Full Text\n\nCvetković-Ilić DS, Pavlović V: A comment on some recent results concerning the reverse order law for {1, 3, 4}-inverses. Appl Math Comput. 2010; 217(1): 105–109. Publisher Full Text\n\nShinozaki N, Sibuya M: The reverse order law (AB)− = B−A−. Linear Algebra Appl. 1974; 9: 29–40. Publisher Full Text\n\nWang X, Yu A, Li T, et al.: Reverse order laws for the Drazin inverses. J Math Anal Appl. 2016; 444(1): 672–689. Publisher Full Text\n\nWerner HJ: When is B− A− a generalized inverse of AB? Linear Algebra Appl. 1994; 210: 255–263. Publisher Full Text\n\nDrazin MP: Natural structures on semigroups with involution. Bull Amer Math Soc. 1978; 84(1): 139–141. Publisher Full Text\n\nBaksalary JK, Mitra SK: Left-star and right-star partial orderings. Linear Algebra Appl. 1991; 149: 73–89. Publisher Full Text\n\nBenitez J, Liu X, Zhong J: Some results on matrix partial orderings and reverse order law. Electronic Journal of Linear Algebra. 2010; 20: 254–273. Publisher Full Text\n\nBen-Israel A, Greville TNE: Generalized inverses: Theory and applications. 2nd ed. Canadian Mathematical Society, 1974. Reference Source\n\nRadhakrishna Rao C, Mitra SK, Mitra JK: Generalized inverse of matrices and its applications. John Wiley & Sons, Inc, 1971. Reference Source\n\nManjunatha Prasad K: An introduction to generalized inverse. In: Bapat, R. B., Kirkland, S., Manjunatha, Prasad, K., Puntanen, S. (editors), Lectures on matrix and graph methods. Manipal University Press, 2012; 43–60. Reference Source\n\nKaplansky I: Any orthocomplemented complete modular lattice is a continuous geometry. Ann Math. 1955; 61(3): 524–541. Publisher Full Text\n\nPenrose R: A generalized inverse for matrices. Mathematical Proceedings of the Cambridge Philosophical Society. 1955; 51(3): 406–413. Publisher Full Text\n\nHartwig RE: Block generalized inverses. Arch Rational Mech Anal. 1976; 61: 197–251. Publisher Full Text\n\nNashed ZM, Votruba GF: A unified operator theory of generalized inverses. In: Nashed, Zuhair M. (editor), Generalized inverses and applications. Academic Press, Inc., 1976; 1–109. Publisher Full Text\n\nHartwig RE: How to partially order regular elements. Japanese J Math. 1980; 25(1): 1–13. Reference Source\n\nSubramonian Nambooripad KS: The natural partial order on a regular semigroup. Proc Edinb Math Soc. 1980; 23(3): 249–260. Publisher Full Text\n\nBlackwood B, Jain SK, Prasad KM, et al.: Shorted operator relative to a partial order in a regular ring. Comm Algebra. 2009; 37(11): 4141–4152. Publisher Full Text\n\nJain SK, Manjunatha Prasad K: Right-left symmetry of aℛ ⊕ bℛa = (a + b)ℛ in regular rings. J Pure Appl Algebra. 1998; 133(1–2): 141–142. Publisher Full Text\n\nBapat RB, Jain SK, Karantha MP, et al.: Outer inverses: Characterization and applications. Linear Algebra Appl. 2017; 528: 171–184. Publisher Full Text\n\nXiong Z, Zheng B: The reverse order laws for {1,2,3}- and {1,2,4} - inverses of a two-matrix product. Appl Math Lett. 2008; 21(7): 649–655. Publisher Full Text\n\nLiu X, Wu S, Cvetković-Ilić DS: New results on reverse order law for {1,2,3}- and {1,2,4}- inverse of bounded operators. Math Comput. 2013; 82(283): 1597–1607. Publisher Full Text\n\nCvetković-Ilić DS, Nikolov J: Reverse order laws for reflexive generalized inverse of operators. Linear Multilinear Algebra. 2015; 63(6): 1167–1175. Publisher Full Text\n\nHartwig RE, Drazin MP: Lattice properties of the ∗-order for the complex matrices. J Math Anal Appl. 1982; 86(2): 359–378. Publisher Full Text\n\nBouldin R: The pseudo-inverse of a product. SIAM J Appl Math. 1973; 24(4): 489–495. Publisher Full Text" }	[ { "id": "146946", "date": "21 Oct 2022", "name": "Balaji Ramamurthy", "expertise": [ "Reviewer Expertise Linear algebra" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe reverse order law in the case of matrix inverses i.e., (AB) −1 = B−1A−1 is well known in the literature. But the same is not true when the inverses are replaced by generalized inverses. However, in the case of rectangular matrices the reverse order law could be extended by replacing the inverses by Moore-Penrose inverse subject to some necessary and sufficient conditions. When we consider the elements over an associative ring many tools which are available in the context of matrices, like rank, column space and row space are missing and hence the study of reverse order law for non-invertible elements is an interesting problem.\nIn the present paper, the authors study the reverse order law extended for outer inverses and Moore-Penrose inverses of the elements from associative ring using the minus partial order and the star order. These techniques are quite innovative and interesting.\nIn the first two sections authors provide detailed introduction and preliminary results required to discuss the rest of the developments.\nIn the third section the authors characterized the class of pairs of outer inverses satisfying the extended reverse order law. Interestingly, the theory of minus partial order plays an important role in obtaining this characterization.\nIn the fourth section the authors introduce and study left-star partial order and right-star partial order for the elements from associative ring. The interesting properties of these partial orders are effectively use in the Section 5 to obtain necessary and sufficient conditions on the elements for the Moore-Penrose inverses of those elements satisfying reverse order law.\nAll the results obtained in this paper are mathematically correct and interesting. The examples and counter examples discussed in this paper help in understanding the subject. I strongly recommend this paper for indexing.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "169472", "date": "25 Apr 2023", "name": "Mehsin Jabel Atteya", "expertise": [ "Reviewer Expertise Algebra", "Quantum Group", "Ring Theory." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAt the beginning, the counter examples and examples which are used in this article assist in understanding the specific points. During this paper, the authors provide background information about this subject in the introduction with preliminary results which are used to discuss the rest of the developments.This information is written in the first two sections. While the characterized the class of pairs of outer inverses which satisfy the extended reverse order law. Additionally, interestingly, the theory of minus partial order plays an important role in obtaining this characterization, in the third section. In the fourth and fifth sections, the authors posted necessary and sufficient relations on the elements for the Moore-Penrose inverses of those elements satisfying reverse order law. Also, they introduce and study left-star partial order and right-star partial order for the elements from associative ring. Finally, all the results which harvested in this paper are mathematically correct and interesting for more researchers. strongly recommend this paper for publishing.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-843
https://f1000research.com/articles/11-552/v1	20 May 22	{ "type": "Systematic Review", "title": "A systematic review of retinoic acid in the journey of spermatogonium to spermatozoa: From basic to clinical application", "authors": [ "Ria Margiana", "Cennikon Pakpahan", "Mulyoto Pangestu", "Ria Margiana", "Mulyoto Pangestu" ], "abstract": "Background: Retinoic acid plays an essential role in testicular development and functions, especially spermatogenesis. We have reviewed the role of retinoic acid from basic (molecular) to clinical application. Methods: A search was conducted in the online database including PubMed, Google Scholar, and Scopus for English studies published in the last eight years about this issue. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines in assessing the studies we are going to investigate. Results: Studies indicated that retinoic acid plays an essential role during pluripotent stem cell migration and lineage commitment, cell differentiation, apoptosis, stem cell number regulation, and maturation arrest in spermatogenic cells. Retinoic acid can also affect related protein expression and signaling pathways at different stages of spermatogenesis. Four studies have applied retinoic acid to humans, all of them in the single-arm observational study. The results look promising but need further research with more controlled study methods, randomization, and large samples. Conclusions: This current systematic review emphasizes a novel retinoic acid mechanism that has not been well described in the literature previously on its functions during the first seven days of spermatogenesis, leading to new directions or explanations of male infertility cause and treatments as a part of reproductive health care.", "keywords": [ "retinoic acid", "spermatozoa", "male infertility", "reproductive health care", "clinical application", "stem cell" ], "content": "Introduction\n\nThe process of spermatogenesis is highly complex and involves the production of spermatogonia after the primary male sperm cells undergo meiosis.1 The spermatogonia cells produce spermatocytes which further divide into secondary spermatocytes during meiosis I. The whole process of spermatogenesis takes 72 days in humans and occurs in seminiferous tubules. The process begins with the mitotic division of diploid spermatogonium.1,2 After primary and secondary spermatocytes divide into spermatids, they form a sperm cell, which is a mature spermatozoon.3 Recent studies have discovered that retinoic acid (RA) facilitates spermatogonia differentiation, suggesting its role in male infertility.3 Therefore, the rationale for this review is to provide the efficacy and the role of RA in infertility among males. Moreover, infertility among the male population is debatable and keeps attracting future studies. Subsequently, infertility treatment falls in the subset of andrology, implying that studies involving the impairment of spermatogenesis resulting from vitamin deficiency,3 among other molecular factors, are of scientific concern.3\n\nTo date, there are few reports on the role of RA in male reproduction and spermatogenesis.4 This review discusses several important aspects of the intricate relationship between RA and spermatogenesis, including its synthesis, metabolism, distribution of nuclear receptors and known effects on spermiogenesis during cell differentiation and infertility.\n\nThe review has two primary purposes: to assess the available literature on the role of RA on the spermatogenesis process from the spermatogonium to the spermatozoa. As a second point of discussion, this review examines the significance of RA in treating male infertility, emphasizing spermatogenesis.\n\n\nMethods\n\nWe conducted a search on the application of RA in a clinical setting in humans. The researcher searched the most relevant studies on Google Scholar, PubMed, and Scopus. These databases include peer-reviewed journals that focus on molecular and advanced medicine and other health-related topics. The search yielded a sufficient number of results without looking through registrations or reference lists.\n\nThe search strategy employed in the review process included keywords, truncation, and Boolean operators. The first approach used keywords that summarized the study’s topic. The keywords used in the search followed the phrase searching approach. For example, “what is the role of RA in spermatogenesis.” The second strategy used for the search comprised the truncation method. The researcher used the truncation (asterisk) plan to save time. In this case, truncation was focused on finding the study’s population. For example, spermat* was used to find spermatogenesis, spermatogonium, spermatozoa. Boolean operators such as “AND, OR, and NOT” were used to narrow, broaden and exclude specific phrases, respectively. For example, the reviewer used a secondary search such as “retinoic acid AND spermatogenesis” to generate accurate studies. We use this keyword to provide wide literature about basic sciences or molecular aspects of RA in spermatogenesis. Meanwhile, to find articles obtaining the clinical use of vitamin A in humans, we used the keywords “retinoic acid” AND “male infertility” AND “experimental study” OR “clinical trial”.\n\nWe collected data using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline.39 All studies had to meet the following requirements: (1) randomized clinical trial (experimental study), or cohort observational with single-arm study; (2) written in English; (3) examining sperm parameters as output; (4) the study’s full text was available. Studies that did not meet the following criteria were eliminated: (1) the study was not designed in an experimental study or cohort observational; instead, it was designed in the form of a case study; (2) duplicate studies; (3) studies that are not available in full text, main data, or data related to RA administration and sperm parameters; (4) the use of a language other than English; (5) no human subjects were used in the research; (6) articles that are in the form of an abstract or literature review.\n\nWe carried out separate electronic searches and retrieved information that matched the terms we were looking for independently. Then we collected together the search results we got into one file. RM and CP conducted critical appraisals one by one on studies that matched our inclusion criteria. We discussed any difficulties that surfaced during the search that produced uncertainty with the other writers. The first author’s name, the year of publication, the study design, the place of origin, the sample size, the sample criteria, the outcomes (sperm parameters, physical examination hormone levels, living birth), and the results were found. All of this information was gathered from each study. We contacted the article’s corresponding author if the required information was absent. We didn’t do quantitative analysis because each study’s statistical analysis was different.\n\nThe quality of the studies included in this review was assessed using the Newcastle-Ottawa quality evaluation scale (NOQS). This scale is used to assess the quality of observational studies in order to compile a thorough systematic review. All the included studies were assessed for three crucial components: selection of participants, comparability, and the outcome. The maximum total score for this assessment is nine. In terms of quality, the studies were graded as high (9 stars), medium (7-8 stars), or low (less than 7 stars) available from OHRI.\n\n\nResults\n\nUsing the PRSIMA flowchart39 (Figure 1), we searched the keywords on three databases, including Google Scholar, Scopus, and PubMed databases, we extracted the information about the role of RA in spermatogenesis and the clinical application of RA in humans as a part of infertility treatment. For the clinical application in humans, we found 200 studies relevant to our keywords. Following that, 100 studies were shown to be duplicates. We identified seven potentially relevant papers after screening for English, human research, semen parameters outcomes, and experimental or observational analytic study. Three of the seven studies did not meet our requirements because they do not provide sperm analysis outcomes in clinical settings. Finally, four studies were included in this review (Table 1).5–8\n\n* Study quality was determined using the Newcastle-Ottawa quality evaluation scale (NOQS) score on the observational study. This scale assesses the study through three aspects, namely selection (recruitment), comparability, and exposure.\n\nThe four studies that met our criteria were single-arm observational studies. Two are from the USA, one is from Turkey, and one is from Egypt. The sample group of two studies participating were men who used RA as part of the acne vulgaris treatment. However, there is also one study explicitly conducted on men with azoospermia. The total sample involved in this systematic review is 148 samples. All studies examined semen analysis as an output parameter to assess the success of therapy. However, some consider pregnancy and live birth one of the study outputs. More detailed results from the retrieval study are in Table 1.\n\n\nDiscussion\n\nThe use of RA as a treatment option in male infertility is still limited. The findings from the review show that RA plays a significant role in the spermatogenesis process. Spermatogenesis refers to how spermatogonia develop into mature spermatozoa and constitutes several developmental stages.1 The signal transduction of retinoic acid-binding receptors (RAR) is crucial in this process. This process also involves a series of transcriptional events regulated by various factors such as RAR, which control the initiation of the meiotic process from spermatogonium to primary spermatocytes and control the morphological transformation from round spermatids to elongated spermatozoa.1\n\nOf note, RA is a derivative of vitamin A, and it plays an essential role in spermatogenesis. During spermatogenesis, retinoic acid receptor gamma (RARγ) activates the expression of three genes: luciferase, Crypto, and RAR-related orphan receptor gamma-t (ROR_gamma-t).4 Both luciferase and ROR_gamma-t bind together to activate androgen receptor (AR) functions. AR triggers the expression of 41 genes implicated in spermatogenesis, such as Bos1. Bos1 encodes an enzyme called β-Hydroxysteroid Dehydrogenase Type 1, promoting testosterone synthesis.9 Testosterone is essential for spermatozoa development into mature sperm cells. Furthermore, RA also regulates both hormone and gene expressions.10\n\nRA is essential for the proper development of the adult male’s reproductive system. RA is involved in Sertoli cells differentiation, after which it regulates the later steps of spermatogenesis through the maintenance of germ cell proliferation and differentiation.11 Furthermore, RA promotes the meiotic process by inducing pachytene arrest in the first meiotic prophase.12 The spermatogonium goes on a long journey to mature spermatozoa. During this process, immature germ cells undergo differentiation and transformation by RA in each stage. RA is a derivative of vitamin A, synthesized from chemicals such as retinal that are ingested or formed from other vitamins already present within the body.12\n\nCritically, RA plays an essential role in development, growth and differentiation throughout life. Importantly, for gonadal function and sperm production, in particular, RA is required for spermatogonia to differentiate into spermatozoa.13,14 Retinoic acid receptor alpha (RARα) and beta (RARβ) are specific receptors found in the testes, both of which have a pivotal role in spermatogenesis. Mutations of RARα have been reported to cause male infertility.15,16 Scholars evaluated the effect of RA on spermatogenesis and RAR expression in mice models with defective RA signalling.15,16 They discovered that mice with depleted RA receptors showed a decrease in overall fertility and testicular weight as well as numerous defects such as failure to grow seminiferous tubules, less mature sperm cells, and decreased RAR expression.\n\nIn the mammalian testis, RA is one of the most important inducers of spermatogenesis.17 In humans, the spermatogenesis process takes 72 days, and RA initiates the undifferentiated spermatogonia. However, it is important to note that RA is produced in the fetal testis, particularly at the mesonephros during the fetal period. RA can prevent meiosis during the fetal period because of CYP26B1 (a metabolizing enzyme of RA) produced by the Sertoli cells.17 Therefore, this implies that RA regulates meiotic divisions in spermatogenesis when in action. It ensures that the spermatogenesis process (I-XII) occurs without interference, resulting in haploid spermatid formation.17 The formed haploid spermatid then becomes spermatozoa, which occurs due to morphological changes in the spermatogenic epithelium.17 Figure 2 below shows the role of RA in the stages of spermatogenesis.\n\nRA plays a role in the process of spermatogenesis. All-trans retinol will enter the cytoplasm and be converted into 4-oxo-retinoic acid as the final product of metabolism. Spermatogonia will utilize this product in the phases of mitosis and meiosis to become spermatozoa (a). In addition, the involvement of RA in spermatogenesis involves several proteins, one of which plays an active role is stimulated by retinoic acid gene 8 (Stra8) together with retinoic acid receptor alpha (RAR-α), Plzf (promyelocytic leukemia zinc finger), Spalt-like 4 (SALL4), and e-KIT. These proteins are dominantly involved in transforming the Apr spermatogonia into intermediate spermatogonia. The absence these proteins interaction with RA may cause the process of mitosis to discontinue (b). RAR-α: retinoic acid receptor alpha, Stra8: stimulated by retinoic acid gene 8, Plzf: promyelocytic leukemia zinc finger, SALL4: Spalt-like 4, RARE: retinoic acid response elements, RXR: retinoid X receptors, RXRE: retinoid X receptors elements.\n\nAt the start of the cycle, the concentration of RA is low because of the effects of enzymatic inhibitors, especially from stage I-III. The source of RA in this process includes the germ and Sertoli cells.17 The ALDH1A1 and ALDH1A2 catalyse the RA production, increasing concentration from stage VII-VIII. During the VII-VII, a transition occurs from Aa1 to A1 spermatogonia, in which RA induces the process of meiosis. The bidding process occurs at the peak of RA synthesis, where it binds with RAR to activate the downstream expression of genes such as Stra8.17\n\nIt has been reported that RA plays a crucial role in promoting meiosis progression, spermatid differentiation and spermiation among male gonad cells.18–22 In this present systematic review, the retinol-binding protein gene emerged using quantitative real-time polymerase chain reaction (qRT-PCR) analysis and investigated two critical regulatory mechanisms in germ cells: the differentiation and apoptosis of germ cells.19,23 The results demonstrated that retinol-binding protein (RBP) mRNA expression was upregulated in the RA group compared with the control group after exposure to RA. The systematic review results suggest that RA plays an essential role in regulating testicular function by increasing RBP levels through multiple pathways and processes.\n\nRA is required for the normal growth and development of spermatozoa. Spermatogonium and spermatocyte development require RA signalling, while spermatozoa only use endogenous metabolite concentrations.24–28 The requirement for retinoids in sperm development, and their ability to restore male fertility when topically administered, highlights the importance of these metabolites during spermatogenesis.\n\nRA is a small hydrophilic signal molecule that plays a role at the earliest stages of spermatogenesis to regulate the expression of factors involved in differentiation and proliferation, like SOX9 or DAZL.24–27,29–30 RA participates in class switching during meiosis and maintains pluripotency and proliferation of stem cells through these essential factors.\n\nRA is required for the initial stages of spermatogenesis. It is required to transition a spermatogonium to a primary spermatocyte and again from a primary spermatocyte to a secondary spermatocyte.31–36 RA also plays a role in the maturation of spermatozoa, as mutagenesis at specific sites in the RAR prevents the proper maturation of spermatozoa.\n\nRA is required to develop spermatogonia from its precursors to germ cells during fetal development. Once the adult testis has been established, RA becomes redundant for spermatogonia’s continued survival and proliferation.32 In rodents, it was observed that nutritional deprivation could lead to an up-regulation of retinoid synthesis in adult testes.32\n\nRetinoid acid deficiency during prenatal development or after birth can lead to male infertility. It was previously believed that retinoids were no longer needed for male fertility once the adult testis had developed and been established.36 Still, research has shown that when nutrition is low in adult rodents, a retinoid cycle is restored.36–38 Overall, RA plays an essential role in controlling fertility due to its effects on regulating spermatogenesis through modulating testosterone-dependent gene expression during development via retinoid X receptors.\n\nUnderstanding the great role of RA in the process of spermatogenesis, RA may have a big impact on clinical improvement of male infertility.\n\nRegarding the use of RA in treating male infertility, the four studies that we included conducted trials in men with oligospermia (three studies) and azoospermia (one study). Two studies were conducted on patients with acne vulgaris,7,8 and it is known that isotretinoin is the treatment of choice for acne. All three studies consistently reported changes in semen parameters in terms of concentration, motility, and morphology.7,8 Of these three studies, one examined hormone levels and reported no changes.7 Then there was one study that reported whether the effect of using RA gave changes to the ultra-microscopic structure of sperm but found no significant differences.8\n\nIn a study using patients with azoospermia, the use of RA was reported by some participants to produce sperm after several weeks of using RA.5 In this study, a surgical sperm retrieval procedure was also carried out. The results found a change in the profile of germ cells in the testes where sperm was collected. This sperm was used in an assisted reproductive technology program with an intracytoplasmic injection procedure, there was one pregnancy, and live birth was successful.5 The results of this study indicate that the use of RA affects the process of spermatogenesis, which may have stopped earlier.\n\nThe results of this study support the hypothesis of the role of RA in modulating and initiating the process of spermatogenesis from division to differentiation as we described earlier; however, these studies seem weak in explaining whether these changes occur due to a single role of RA or other factors. Several of these studies have attempted to select samples with biased factors such as smoking, alcohol consumption, and history of genitourinary surgery. However, to get better results in looking at the clinical use of RA in male infertility cases, a randomized clinical control design is the most appropriate. However, this information can be used as a pilot study for further clinical trials, especially to get the most appropriate dose and duration of use.\n\n\nConclusion\n\nRA plays an essential role in activating and modulating the process of spermatogenesis so that mitosis can continue to the final stage of meiosis. The role of RA molecularly in the process of spermatogenesis seems to have a very vital role. However, this argument is still unclear as the use of RA in treatment has not consistently provided a significant effect. Large randomized and blinded studies are needed to prove the benefit of RA in treating male infertility.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\nFigshare: PRISMA checklist and flowchart for ‘A Review of Retinoic Acid in The Journey of Spermatogonium to Spermatozoa: From Basic to Clinical Application’ https://doi.org/10.6084/m9.figshare.19404020.v2.39", "appendix": "Acknowledgements\n\nWe thank Patricia S. Kandar for her help in designing the figure that we include in this article.\n\n\nReferences\n\nMuciaccia B, Boitani C, Berloco BP, et al.: Novel Stage Classification of Human Spermatogenesis Based on Acrosome Development. Biol. Reprod. 2013 Sep 1; 89(3): 60. PubMed Abstract \| Publisher Full Text\n\nNya-Ngatchou JJ, Arnold SLM, Walsh TJ, et al.: Intratesticular 13-cis retinoic acid is lower in men with abnormal semen analyses: a pilot study. Andrology. 2012 Nov 29; 1(2): 325–331. PubMed Abstract \| Publisher Full Text\n\nTsampoukas G, Gkeka K, Dellis A, et al.: Vitamins as primary or adjunctive treatment in infertile men with varicocele: A systematic review. Arab. J. Urol. 2021 May 29; 19(3): 264–273. PubMed Abstract \| Publisher Full Text\n\nBusada JT, Geyer CB: The Role of Retinoic Acid (RA) in Spermatogonial Differentiation1. Biol. Reprod. 2016 Jan 1; 94(1): 10. PubMed Abstract \| Publisher Full Text\n\nAmory JK, Charles H, Muller TJW: Isotretinoin for the treatment of nonobstructive azoospermia: a pilot study. Asian J. Androl. 2021; 23(March): 537–540. Publisher Full Text\n\nAmory JK, Ostrowski KA, Gannon JR, et al.: Isotretinoin administration improves sperm production in men with infertility from oligoasthenozoospermia: a pilot study. Andrology. 2017; 5(6): 1115–1123. PubMed Abstract \| Publisher Full Text\n\nÇinar L, Kartal D, Ergin C, et al.: The effect of systemic isotretinoin on male fertility. Cutan. Ocul. Toxicol. 2016; 35(4): 296–299. PubMed Abstract \| Publisher Full Text\n\nEyada M, Mostafa R, Mahgoub S, et al.: Effect of systemic isotretinoin on semen parameters and sperm ultrastructure in male patients treated for acne vulgaris: An electron microscope study. Human Andrology. 2020; 10(1): 1–9. Publisher Full Text\n\nLi X, Long X-Y, Xie Y-J, et al.The roles of retinoic acid in the differentiation of spermatogonia and spermatogenic disorders. Clinica Chimica Acta; International Journal of Clinical Chemistry. 2019 Oct 1 [cited 2022 Jan 6]; 497: 54–60. PubMed Abstract \| Publisher Full Text\n\nTeletin M, Vernet N, Ghyselinck NB, et al.: Roles of retinoic acid in germ cell differentiation. Curr. Top. Dev. Biol. 2017 Jan 1; 125: 191–225. Publisher Full Text\n\nHiggins JPT, Altman DG, Gotzsche PC, et al.: The Cochrane Collaboration’s tool for assessing the risk of bias in randomized trials. BMJ. 2011 Oct 18; 343(oct18 2): d5928–d5928. PubMed Abstract \| Publisher Full Text Reference Source\n\nWang YJ, Jia GX, Yan RG, et al.: Testosterone-retinoic acid signaling directs spermatogonial differentiation and seasonal spermatogenesis in the Plateau pika (Ochotona curzoniae). Theriogenology. 2019 Jan 1; 123: 74–82. PubMed Abstract \| Publisher Full Text\n\nMacejova D, Toporova L, Brtko J: The role of retinoic acid receptors and their cognate ligands in reproduction in a context of triorganotin based endocrine-disrupting chemicals. Endocr. Regul. 2016 Jul 1; 50: 154–164. PubMed Abstract \| Publisher Full Text\n\nKasimanickam VR, Kasimanickam RK, Dernell WS: Dysregulated microRNA clusters respond to retinoic acid and CYP26B1 inhibitor-induced testicular function in dogs. PLoS One. 2014 Jun 9; 9(6): e99433. PubMed Abstract \| Publisher Full Text\n\nChoy JT, Eisenberg ML: Male infertility as a window to health. Fertil. Steril. 2018 Oct 1; 110(5): 810–814. Publisher Full Text\n\nSingh V, Joshi M, Singh K, et al.: Wnt signaling in spermatogenesis and male infertility. CRC Press; 2019 Nov 6.\n\nAmini Mahabadi J, Karimian M, Aghighi F, et al.: Retinoic acid and 17β-estradiol improve male germ cell differentiation from mouse-induced pluripotent stem cells. Andrologia. 2020 Mar; 52(2): e13466. PubMed Abstract \| Publisher Full Text\n\nBrtko J, Dvorak Z: Natural and synthetic retinoid X receptor ligands and their role in selected nuclear receptor action. Biochimie. 2020 Dec 1; 179: 157–168. PubMed Abstract \| Publisher Full Text\n\nTan H, Wang JJ, Cheng SF, et al.: Retinoic acid promotes the proliferation of primordial germ cell-like cells differentiated from mouse skin-derived stem cells in vitro. Theriogenology. 2016 Feb 1; 85(3): 408–418. PubMed Abstract \| Publisher Full Text\n\nCunningham TJ, Duester G: Mechanisms of retinoic acid signaling and its roles in organ and limb development. Nat. Rev. Mol. Cell Biol. 2015 Jan 5; 16(2): 110–123. PubMed Abstract \| Publisher Full Text\n\nForbes CM, Flannigan R, Schlegel PN: Spermatogonial stem cell transplantation and male infertility: Current status and future directions. Arab. J. Urol. 2018 Mar; 16(1): 171–180. PubMed Abstract \| Publisher Full Text\n\nMalivindi R, Rago V, De Rose D, et al.: Influence of all-trans retinoic acid on sperm metabolism and oxidative stress: Its involvement in the physiopathology of varicocele-associated male infertility. J. Cell. Physiol. 2018 Dec 1 [cited 2022 Mar 1]; 233(12): 9526–37. PubMed Abstract \| Publisher Full Text\n\nMinkina A, Lindeman RE, Gearhart MD, et al.: Retinoic acid signaling is dispensable for somatic development and function in the mammalian ovary. Dev. Biol. 2017 Apr 15; 424(2): 208–220. PubMed Abstract \| Publisher Full Text\n\nHogarth C: Retinoic acid metabolism, signaling, and function in the adult testis. Sertoli cell biology. Academic Press; 2015 Jan 1 (pp. 247–272). Publisher Full Text\n\nKasimanickam VR: Expression of retinoic acid-metabolizing enzymes, ALDH 1A1, ALDH 1A2, ALDH 1A3, CYP 26A1, CYP 26B1 and CYP 26C1 in canine testis during postnatal development. Reprod. Domest. Anim. 2016 Dec; 51(6): 901–909. PubMed Abstract \| Publisher Full Text\n\nPeng J, Shen L, Chen J, et al.: discovery of cryptorchidism: Decreased retinoic acid in the testicle. Saudi Pharm. J. 2016 May 1; 24(3): 279–285. PubMed Abstract \| Publisher Full Text\n\nLong C, Zhou Y, Shen L, et al.: Retinoic acid can improve autophagy through the depression of the PI3K-Akt-mTOR signaling pathway via RARα to restore spermatogenesis in cryptorchid infertile rats. Genes Dis. 2021 Apr 2. Publisher Full Text\n\nEskandari N, Moghaddam MH, Atlasi MA, et al.: The combination of retinoic acid and estrogen can increase germ cell gene expression in mouse embryonic stem cells derived from primordial germ cells. Biologicals. 2018 Nov 1; 56: 39–44. PubMed Abstract \| Publisher Full Text\n\nGaldon G, Atala A, Sadri-Ardekani H: In-vitro spermatogenesis: how far from clinical application?. Curr. Urol. Rep. 2016 Jul; 17(7): 1–2. Publisher Full Text\n\nLarose H, Shami AN, Abbott H, et al.: Gametogenesis: A journey from inception to conception. Curr. Top. Dev. Biol. 2019 Jan 1; 132: 257–310. PubMed Abstract \| Publisher Full Text\n\nNoman MAA, Kyzer JL, Chung SSW, et al.: Retinoic acid receptor antagonists for male contraception: current status†. Biol. Reprod. 2020 Jul 15; 103(2): 390–399. PubMed Abstract \| Publisher Full Text\n\nWu Y, Wang T, Zhao Z, et al.: Retinoic Acid-Induced Protein 14 (Rai14) is dispensable for mouse spermatogenesis. PeerJ. 2021 Feb 19 [cited 2022 Mar 1]; 9: e10847. PubMed Abstract \| Publisher Full Text\n\nGewiss R, Topping T, Griswold MD: Cycles, waves, and pulses: Retinoic acid and the organization of spermatogenesis. Andrology. 2020 Jul 1 [cited 2022 Mar 1]; 8(4): 892–897. PubMed Abstract \| Publisher Full Text\n\nLuo Y, Xie L, Mohsin A, et al.: Efficient generation of male germ-like cells derived during co-culturing of adipose-derived mesenchymal stem cells with Sertoli cells under retinoic acid and testosterone induction. Stem Cell Res. Ther. 2019 Mar 13; 10(1): 91. PubMed Abstract \| Publisher Full Text\n\nXie Y, Wei B-H, Ni F-D, et al.: Conversion from spermatogonia to spermatocytes: Extracellular cues and downstream transcription network. Gene. 2021 Jan 5 [cited 2022 Mar 1]; 764: 145080. PubMed Abstract \| Publisher Full Text\n\nYucel C, Arslan FD, Ekmekci S, et al.: Protective effect of all-trans retinoic acid in cisplatin-induced testicular damage in rats. The World Journal of Men’s Health. 2019 May 1; 37(2): 249–256. PubMed Abstract \| Publisher Full Text\n\nPeer NR, Law SM, Murdoch B, et al.: Germ Cell-Specific Retinoic Acid Receptor α Functions in Germ Cell Organization, Meiotic Integrity, and Spermatogonia. Endocrinology. 2018 Aug 6 [cited 2021 Jan 22]; 159(9): 3403–20. PubMed Abstract \| Publisher Full Text\n\nZheng Y, Lei Q, Jongejan A, et al.: The influence of retinoic acid-induced differentiation on the radiation response of male germline stem cells. DNA Repair. 2018 Oct 1 [cited 2022 Mar 1]; 70: 55–66. PubMed Abstract \| Publisher Full Text\n\nPakpahan C: PRISMA_2020_checklist.docx. figshare.2022. Publisher Full Text" }	[ { "id": "141380", "date": "12 Jul 2022", "name": "Abiodun Mathias Emokpae", "expertise": [ "Reviewer Expertise Reproductive Health studies", "human nutrition and sickle cell nephropathy." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe study reviewed the roles of RA in modulating and initiating the process of spermatogenesis from primitive cells division, differentiation to matured/functional spermatozoa. RA is involved in the modulation of testosterone dependent gene expression through retinoid receptors and Sertoli cell differentiation. It also reviewed the clinical application of RA in the treatment of male infertility. It also explained the possible mechanisms of action of RA in the process of spermatogenesis. It is a well written paper but requires minor modifications: Keywords should be derived via MeSH on Demand and abbreviations like ALDH1A and CYP may be written in full on first use. The article should be accepted (appropriate) with minor correction.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? Not applicable\n\nAre the conclusions drawn adequately supported by the results presented in the review? Yes", "responses": [] }, { "id": "142851", "date": "22 Jul 2022", "name": "Binarwan Halim", "expertise": [ "Reviewer Expertise reproductive endocrinology", "andrology", "embryology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThanks to the authors for trying to make a systematic review of the role of retinoic acid in spermatogenesis. Besides being involved in the role of modulation of gene expression, it can also be applied clinically as the treatment of male infertility. Overall, it was very well written, from the methods through the end of the paper.\nHowever, I think this study requires minor revision, as it should need to mention the pharmacokinetic and dynamic role of tretionoin administration, as well as its concentration in the testicles.\nAfter the minor revision, this article should be appropriate for indexing.\n\nAre the rationale for, and objectives of, the Systematic Review clearly stated? Yes\n\nAre sufficient details of the methods and analysis provided to allow replication by others? Yes\n\nIs the statistical analysis and its interpretation appropriate? Yes\n\nAre the conclusions drawn adequately supported by the results presented in the review? Yes", "responses": [ { "c_id": "8559", "date": "27 Jul 2022", "name": "Cennikon Pakpahan", "role": "Author Response", "response": "Thank you for your suggestions in enriching the information in this paper. We try to revise according to your requests. We think we have explained the dynamic role part in the previous version in the discussion part. While for pharmacokinetics and concentration of retinoic acid in testes, we have added it in the discussion section." } ] } ]	1	https://f1000research.com/articles/11-552
https://f1000research.com/articles/11-462/v1	26 Apr 22	{ "type": "Research Article", "title": "Appraisal on patient compliance and factors influencing the daily regimen of anti-tubercular drugs in Mangalore city: A cross-sectional study", "authors": [ "Rohith Motappa", "Tuba Fathima", "Himani Kotian", "Tuba Fathima", "Himani Kotian" ], "abstract": "Background: Globally, India is the country with the highest tuberculosis (TB) burden with respect to the number of new cases occurring each year. Annual incident cases of TB in India accounts for more than 25% of total TB morbidity and mortality worldwide. Several factors have been associated with the adherence of TB medication, which can be broadly classified as patient/personal, social, structural and health service. The aims of the present study were to determine the compliance to daily regimen of directly observed treatment, short-course (DOTS) therapy among TB patients registered at the Tuberculosis Unit (TU) of Mangalore and to identify the factors influencing non-compliance for treatment. Methods: A cross sectional study was performed. The study sample was drawn from the TUs, General Hospital, Mangalore, after taking permission from District TB Officer. The names and addresses of TB patients were collected from treatment cards. The TB patients were approached at their homes/DOTS centers/Primary Health Centre’s (PHCs) with the help of senior treatment supervisors. Results: It was found that patients positive for human immunodeficiency virus (HIV) were more likely to be non-adherent, which was statistically significant. Amongst the participants, 66 (33%) were diabetic and 28.8% of them were found to be non-adherent. The proportion of non-adherence was 27 times higher in those with poor patient provider relationships. Patients who reported to have side effects of TB medication were 5.23 times more likely to be non-adherent. Conclusions: Advice on routine consultation with the health care facility, adherence to treatment regimen and education about its benefits should be the prime focus of providing health education to all TB patients, both at the individual and community levels.", "keywords": [ "Tuberculosis", "Daily Regimen", "Compliance" ], "content": "Introduction\n\nTuberculosis (TB) is a rampant infectious disease caused by the bacteria, Mycobacterium tuberculosis. It is one of the most important socioeconomic global diseases with a high mortality rate.\n\nGlobal estimation shows around 10.0 million (range, 8.9–11.0 million) people fell ill with TB in 2019, a number that has also been declining very slowly in recent years according to the Global tuberculosis report 2020 by World Health Organization (WHO) (Accessed on 28-11-2021).\n\nGlobally TB is the 13th leading cause of death and the second leading infectious killer after COVID-19 (above human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS)) according to WHO (Accessed on 28-11-2021). India accounts for more than one-fourth of total TB cases and deaths worldwide. A total of 2.8 million new cases and 470,000 deaths due to TB, were reported in 2018, according to WHO global report.1,2\n\nNational and international efforts over the last few decades regarding the prevention of TB, and its early diagnosis and treatment have been guided by the directly observed treatment, short-course (DOTS) strategy and followed by the Stop TB strategy. Recently, the WHO End TB strategy highlighted global targets, including: i) To decrease TB deaths by 90%; ii) to reduce incident cases by 80% by 2030 and iii) to ensure that there is no family burden due to TB costs.1 To individuals diagnosed with TB, the DOTS strategy involves the delivery of a standard short course of drugs lasting six months for new patients and eight months for retreatment patients.3\n\nThe Supreme Court of India in February 2017 directed that all new patients should be administered a daily regimen of TB drugs. Under the new daily drug regimen, TB patients will be given fixed-dose combinations, three or four drugs in specific dosages in a single pill, on a daily basis. The patient under the new regimen will have a reduced pill burden, as instead of seven tablets, patients need to consume only two or three tablets, according to their weight band.4,5\n\nDaily regimens recommended by WHO have been shown to be highly effective for both preventing and treating TB, however poor adherence to anti-TB medication is a major barrier in its global control. Nearly 20-50% of patients fail to complete therapy and as TB is a rampant communicable disease, this leads to prolonged infectiousness, drug resistance, relapse, and death.6,7\n\nSeveral factors have been associated with the adherence of TB medication, which can be broadly classified as social, structural, health service and patient/personal.5\n\nTB is mainly a disease of the poor in a country like India. Low income and poor living conditions, including overcrowding, contribute to the economic and structural factors.4\n\nTB can also interfere with the mental health of an individual. Many studies report a high prevalence of psychiatric issues among patients with drug-resistant TB, which significantly correlates with severity and duration of the disease and can also be associated with poorer adherence to anti-TB treatment.1,8–10\n\nStigmatization has elicited a lot of self-denial among TB patients, hence the non-adherence. Families with low literacy level believe that merely associating with TB patients may cause them to have the disease and may create differences of opinion in the household about providing support to the patients, thereby leading to non-adherence. Also, discrimination on the basis of the disease at healthcare facilities may sometimes exacerbate the problem with adherence to drug-taking behavior.11\n\nNon-compliance to therapy leads to resurgence and persistence of TB and is regarded as an important cause of the development of multidrug-resistant (MDR)-TB and relapse. Hence, this study focused on compliance rates of anti-TB regimen and to determine factors associated with eventual non-compliance (Global tuberculosis report 2020). The aims and objectives of this study were to determine the compliance of daily regimen of DOTS therapy among TB patients registered at the Tuberculosis Unit (TU) of Mangalore, and to identify the factors influencing non-compliance for the treatment among the same group of patients.\n\n\nMethods\n\nThis was a cross-sectional study that took place from 15th July 2021 to 15th September 2021.\n\nThe study was approved by the Institutional Review Board of Yenepoya Ethics Centre 2 (Protocol number-YEC2/770) and performed in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from participants.\n\nMultiple TUs attached to the Designated Microscopy Centre in Government Hospital located in Mangalore were selected. This study was undertaken in those TUs. TB cards were used to approach the TB patients.\n\nSelected Primary Health Centre’s (PHCs) of Mangalore city and Wenlock district hospital in Dakshina Kannada district.\n\nFrom previous studies, it was found that the compliance rate among TB patients is 50%. Considering 5% level of significance and 7% absolute precision around the specified rate, the minimum sample size recommended for the present study was calculated by the following formula:\n\n*(To round off, this study only included 200 participants)\n\n\n\n1. The sputum positive pulmonary TB patients (18 years and above) registered in three TU, who were on treatment.\n\n2. Patients who had been on anti-TB drugs for at least three weeks of treatment.\n\n\n\n1. Patients who were critically ill.\n\n2. Pregnant and lactating women.\n\n3. If the patient couldn’t be found after two consecutive home visits.\n\nThe study sample was drawn from the TU, General Hospital, Mangalore, after taking permission from the District TB Officer. The names and addresses of sputum-positive TB patients were collected from treatment cards. The TB patients were approached at their homes/DOTS centers/PHCs with the help of senior treatment supervisors. The study purpose was explained participants at the time of the interview. They were informed that, their participation in the study was voluntary and that they could withdraw from the study at any point of time. Maintenance of confidentiality about data and findings was assured to the participants and their consent was obtained.6\n\nA semi-structured, pretested questionnaire was developed and administered to individuals who were on treatment, with modifications relevant to local conditions.12 The pilot study was performed on 20 people for pretesting. Statistical validation for the questionnaire was done by Cronbach’s Alpha (<0.7).\n\nThe questionnaire consisted of three parts:\n\ni) Socio-demographic variables.\n\nii) Knowledge and attitude factors leading to non-adherence with anti-TB treatment (WHO Global tuberculosis report 2019; Accessed on 28-11-2021).\n\niii) Factors contributing to non-adherence of anti-TB treatment.\n\nData were entered in Microsoft Excel 2016 (Microsoft Excel, RRID:SCR_016137) and analyzed using SPSS version 25 (IBM SPSS Statistics, RRID:SCR_019096). Data were interpreted in proportions and percentages, and Chi-square and P-values were obtained. Odds ratio values were obtained, and logistic regression analysis was performed to determine the likelihood of the factors involved in DOTS compliance in TB patients.\n\n\nResults\n\nTable 1 represents the socio-demographic details of the study participants.13 Out of the 200 participants included in our study, 118 (59%) were men and 82 (41%) were women. Amongst the male and female participants, 30.5% and 32.9% were found to be non-adherent, respectively, and when compared regarding compliance, the difference was not statistically significant.\n\na significant values; TB, tuberculosis; MDR, multidrug-resistant.\n\nA total of 39 (19.5%) of the participants belonged to the 28-25 age group, whereas the majority of the population were above the age of 49. Amongst them, 38.5% of the participants who were 18-25 years old and 30.7% who were over the age of 49 were non-adherent and this was found to be statistically insignificant.\n\nThis study showed that 135 (67.5%) of the participants had a monthly income of less than 5000 rupees and 65 (32.5%) earned more than 5000 rupees per month, of which 34.8% of the participants with income less than 5000 and 24.6% of those with income more than 5000 were found to be non-adherent. When they were compared with adherence, this difference was not statistically significant.\n\nA total of 67 (33.5%) of the patients received education up to middle school and 69 (34.5%) of them had high school education. Almost 8% of the study participants received no education and 47% of these participants were non-adherent. When the educational status of the patients was compared with that of the compliance, the difference was found to be statistically significant (p=0.003).\n\nOur study showed that 147 (73.5%) of the participants followed Hinduism, 31 (15.5%) followed Islam and 22 (11%) followed Christianity. Of the patients following Hinduism, Islam and Christianity, 32%, 32.3% and 27.3% were found to be non-adherent, respectively. In comparison with the compliance of these patients, the difference was not statistically significant.\n\nA total of 134 (67%) of the patients belonged to a nuclear family and 12.5% lived in a three-generation family. A total of 29.1% of the patients belonging to a nuclear family and 40% of those living in a three-generation family were found to be non-adherent and when compared regarding compliance, the difference was not statistically significant.\n\nAmongst our study participants, 51 (25%) were unemployed, 47 (23.5%) were housewives and 64 (32%) were reported to be skilled workers. A total of 47.1% of the unemployed, 36.2% of the housewives and 20.3% of the skilled workers were non-adherent to the TB regimen. In comparison with the compliance, there was no statistical significance.\n\nA total of 178 (89%) of the patients belonged to category 1 and the remaining 11% were category 2 patients. A total of 30.3% of patients in category 1 and 40.9% of patients in category 2 were non-adherent. There was no statistical significance when these were compared with the compliance. A total of 18% of the participants suffered from MDR TB, of which 31.5% were non-adherent.\n\nThe site of TB was pulmonary in 132 (66%) of the patients and extra pulmonary in 22 (11%) of them. It was found that 31.1% of the patients with pulmonary TB and 31.3% suffering from extra pulmonary TB were non-adherent. The difference was statistically insignificant regarding the compliance.\n\nTable 2 represents knowledge and attitude factors contributing to the poor compliance of anti-TB treatment. A total of 80 (40%) participants knew the correct causes of TB and 120 (60%) did not know the correct cause. Amongst them, 15% of the participants who knew the correct causes and 43.5% of them who did not know were found to be non-adherent. When compared in regards to the compliance, the difference was found to be statistically significant (p<0.001).\n\na significant values; TB, tuberculosis.\n\nA total of 130 (65%) of the patients knew the exact mechanisms of the spread of TB and 70 (35%) of them did not know the correct mechanism. Of the people who knew the exact mechanism of spread, 20.8% were found to be non-adherent and 51.4% of the patients who did not know the mechanism were non-adherent. A total of 36% of the patients knew how to prevent TB. However, 64.5% of the study participants had no knowledge about side effects of TB drugs. These values were found to be statistically significant (p<0.001).\n\nParticipants who knew the names of the TB drugs were 40 (2%), while 160 (80%) did not know the names. Amongst them, 17.5% of the participants who knew the exact names and 35% of the ones who did not know the names were non-adherent. When this was compared with the compliance, the difference was found to be statistically significant (p=0.037).\n\nA total of 156 (78%) participants were aware of the daily regimen and 22% had no awareness. A total of 21.2% of the participants who were aware of the daily regimen and 68.2% of those who were not aware, were found to be non-adherent. In regard to the compliance, these data were found to be statistically significant. Informants reported that the medication for the patients was given by the family members or treatment facilitators (health workers). The reason for being unaware of the regimen was found to be illiteracy.\n\nAs presented in Table 3, it was found that 4% of the study population who were HIV positive were non-adherent, which was statistically significant (p=0.002).\n\na significant values; TB, tuberculosis; HIV, human immunodeficiency virus; HCW, healthcare worker.\n\nAmongst the participants, 66 (33%) were diabetic and 28.8% of them were found to be non-adherent. A total of 31.4% of the study population who had reported a history of smoking and 32.7% of the study participants who had reported alcohol intake gave a history of non-adherence. None of the variables in comparison with the compliance, showed any statistical significance.\n\nA total of 180 (90%) of the patients reported to have a good patient provider relationship. Only 25% of them were found to be non-adherent. But 90% of the patients with a poor patient provider relationship were non-adherent and this difference regarding compliance was statistically significant (p<0.001).\n\nA total of 91% of the patients reported no financial burden for transportation to the nearest hospital, which was also found out to be significant. A total of 43% of the study population experienced side effects of TB drugs, of which 51.2% were found to be non-adherent. This was found to be significant (p<0.001).\n\nRegarding reasons for interruption to taking medication, variables such as feeling depressed, being sick, treatment course being long and the feeling that the drugs seem ineffective were found to be significant (Table 4).\n\na significant values.\n\nA total of 77 (38.5%) participants complained about being depressed and anxious since the disease was confirmed, of which 49.4% of them were found to be non-adherent, which was statistically significant (p<0.001).\n\nIt was found that 3% of patients cited being busy with other work, and among them 83.3% were non-adherent to TB medication. This was statistically significant (p=0.013).\n\nA total of 63 (31.5%) of participants complained about the treatment course being long, among them 55.6% were found to be non-adherent. A total of 74 (37%) of the patients feared the pill burden and 56.8% of them were non-adherent. Both these were found to be statistically significant (p<0.001).\n\nA logistic regression was applied to ascertain the effects of the aforementioned variables in the likelihood of the participants being non-compliant to the TB regimen (Table 5). Non-adherence was 4.8 times higher in participants who did not know about the etiology of TB, 3.37 times higher in those who did not know the correct mechanism of the spread of TB, 11.57 times higher in those who believed that the disease was incurable, 2.5 times higher in patients who did not know the names of the TB drugs and 7.9 times higher in those who did not have an awareness of the daily regimen.8\n\na significant values; TB, tuberculosis; HIV, human immunodeficiency virus.\n\nNon-adherence was found to be 27 times higher in patients with poor patient provider relationship, 5.23 times higher in patients who reported to have side effects of TB medication, 9.22 times higher in participants who did not receive support from their family during the treatment duration and 6.14 times higher in patients who weren't satisfied with the treatment at the health center (WHO).\n\nNon-adherence was 3.8 times higher in participants who complained about feeling depressed and anxious since the disease was confirmed, 11.72 times higher in patients who were busy with other work and 4.3 times higher inpatients whose appetite was influenced after taking TB medication. Participants who regarded the treatment course to be long and the ones who feared the pill burden were 4.8 and 6.5 times more likely to be non-adherent to the treatment, respectively (WHO).\n\n\nDiscussion\n\nOverall adherence was not up to the mark, as expected. Due to the unprecedented pandemic of COVID-19, which played a significant role in the non-adherence habits of the study participants.14\n\nThe present study showed that non-adherence was quite high in male participants who were predominantly unemployed. These findings were equivalent to a study done by Fang et al.15\n\nPatients who were from urban areas and had education until middle school were found to have greater percentages of non-adherence. These findings were similar to a study performed by Mekonnen and Azagew.16\n\nKnowledge about TB played a very important role in the rates of adherence. It was noted that a large proportion of the TB patients answered incorrectly about the aetiology of TB, modes of transmission and prevention methods, reflecting the poor basic knowledge about TB (Global tuberculosis report 2020). A previous study conducted by Krasniqi et al.17 showed a similar result.\n\nMoreover, factors such as awareness about the long duration of the treatment and adverse effects of daily dosages, have played an important part in adherence to treatment (Global tuberculosis report 2020).\n\nHIV status was significantly associated with non-adherence, with 32% of HIV-positive patients being non-adherent. The reason for this could be attributed to the pill burden caused by antiretroviral therapy (ART) itself. These findings were concurrent with a previous study done by Naing et al.18 The strategies to provide better anti-TB treatment to HIV-positive patients must be stressed upon in the programmes, since the number of HIV-positive patients who die due to TB is very high (Global tuberculosis report 2019).\n\nAll HIV-positive patients should be administered drugs under the direct supervision of health authorities. Educating people about the association between TB and HIV is of great importance (Global tuberculosis report 2019).\n\nMany patients shared their view regarding the economic burden of TB treatment. Poverty plays an etiological role for TB disease and the cost of treatment amplifies economic hardships and reduces adherence. Studies performed by Mauch et al.19 showed that cash incentives with food and transportation can improve treatment success rate.2\n\nNearly 22% of the study participants who were experiencing side effects of the TB treatment were found to be non-adherent and it was significantly associated. These results indicated the importance of health education and counselling on the importance of continuing TB treatment until declared cured. Similar results were found in a study done by Kigozi et al.20\n\nA total of 31.5% of the participants expressed psychological stress after the diagnosis was made and many opined regarding the need for psychological support during treatment.8 High prevalence of depression and anxiety in patients with TB contributing to the state of non-adherence is evident from other studies.17 Psychosocial support improves treatment success rates and this in turn increases TB treatment adherence. TB diagnosis itself may be emotionally taxing on the patients. Collaboration of psycho-emotional care with TB treatment may help patients better face the challenges leading to non-adherence.21\n\nThe analysis of TB compliance yielded a significant association with patients who considered the treatment course to be long, who deemed the drugs to be ineffective and who reported their appetite being reduced after anti-TB drugs. These variables demonstrate a link between major influencing factors for treatment adherence. Although, alcohol use, smoking, regular supply of drugs and distance from health care facility have been associated with high risk of treatment default as per the literature (Global tuberculosis report 2020), these variables did not reflect the increased risk for TB treatment non-adherence in our study.\n\n\nConclusions\n\nIn this qualitative assessment of non-adherence, it was revealed that treatment adherence was not satisfying. Intense health education and health awareness programs for TB patients, so they can be focused to adhere and motivate compliance towards TB treatment should be done at the individual and family level (Global tuberculosis report 2020). Regular follow-up to health care centres and provision to information about the advantages and safety profile of drugs must be encouraged. Also, importance should be given to raise the satisfaction of patients with medical personnel and health services and establishing a regular monitoring system to identify patients with high risk for non-adherence should be initiated.\n\n\nData availability\n\nFigshare: Data- Excel Sheet (Questionnaire results of the participants), https://doi.org/10.6084/m9.figshare.1911348813\n\nFigshare: Questionnaire final (English).docx (Questionnaires used to collect the findings of the study), https://doi.org/10.6084/m9.figshare.1917474512\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nPachi A, Bratis D, Moussas G, et al.: Psychiatric morbidity and other factors affecting treatment adherence in pulmonary tuberculosis patients. Tuberc Res Treat. 2013; 2013: 1–37. Publisher Full Text\n\nPark K: Chapter 5, Epidemiology of Communicable Diseases. Park's textbook of preventive and social medicine. 25th ed.Pune: M/s Banarsidas Bhanot; 2019; p. 188–189.\n\nMunro SA, Lewin SA, Smith HJ, et al.: Patient adherence to tuberculosis treatment: a systematic review of qualitative research. PLoS Med. 2007 Jul 24; 4(7): e238. PubMed Abstract \| Publisher Full Text\n\nChaudhuri AD: Recent changes in technical and operational guidelines for Tuberculosis control programme in India - 2016: A paradigm shift in tuberculosis control. J Assoc Chest Physicians. 2017; 5: 1–9. Publisher Full Text\n\nMandal PK, Mandal A, Bhattacharyya SK: Comparing the Daily Versus the Intermittent regimens of the Anti-Tubercular Chemotherapy in the Initial Intensive Phase in Non-HIV, Sputum Positive, Pulmonary Tuberculosis Patients. Journal of Clinical and Diagnostic and Diagnostic Research: JCDR. 2013; 7(2): 292–295.\n\nBurkhart PV, Sabaté E: Adherence to long-term therapies: evidence for action. J. Nurs. Scholarsh. 2003; 35(3): 207. Publisher Full Text\n\nCuneo WD, Snider DE Jr: Enhancing patient compliance with tuberculosis therapy. Clin. Chest Med. 1989 Sep; 10(3): 375–380. Publisher Full Text\n\nVega P, Sweetland A, Acha J, et al.: Psychiatric issues in the management of patients with multidrug-resistant tuberculosis. Int. J. Tuberc. Lung Dis. 2004 Jun; 8(6): 749–759. PubMed Abstract\n\nNatani GD, Jain NK, Sharma TN: Depression in tuberculosis patients: correlation with duration of disease and response to anti-tuberculous chemotherapy. Indian J. Tuberc. 1985; 32(4): 195–198.\n\nPanchal SL: Correlation with duration and depression in TB patients in rural Jaipur district. Int J Pharm. Bio. Sci. 2011; 2(2): B.263.\n\nSariem C, Nanlir Z, Banwat S, et al.: Factors influencing tuberculosis medication adherence: A cognitive intervention in a resource limited setting. World J. Pharm. Pharm. Sci. 2019; 3: 1912–1920.\n\nMotappa R: Questionnaire final (English).docx. figshare. Dataset. 2022. Publisher Full Text\n\nMotappa R: Data- Excel Sheet. figshare. Dataset. 2022. Publisher Full Text\n\nJaiswal S, Sharma H, Joshi U, et al.: Non-adherence to anti-tubercular treatment during COVID-19 pandemic in Raipur District Central India. The Indian Journal of Tuberculosis. Tuberculosis Association of India. 2021. Published by Elsevier B.V.\n\nFang XH, Shen HH, Hu WQ, et al.: Prevalence of and Factors Influencing Anti-Tuberculosis Treatment Non-Adherence Among Patients with Pulmonary Tuberculosis: A Cross-Sectional Study in Anhui Province, Eastern China. Med Sci Monit. 2019 Mar 14; 25: 1928–1935. PubMed Abstract \| Publisher Full Text\n\nMekonnen HS, Azagew AW: Non-adherence to anti-tuberculosis treatment, reasons and associated factors among TB patients attending at Gondar town health centers, Northwest Ethiopia. BMC. Res. Notes. 2018 Oct 1; 11(1): 691. PubMed Abstract \| Publisher Full Text\n\nKrasniqi S, Jakupi A, Daci A, et al.: Tuberculosis Treatment Adherence of Patients in Kosovo. Tuberculosis Research and Treatment. 2017; 2017: 1–8. PubMed Abstract \| Publisher Full Text\n\nNaing NN, D'Este C, Isa AR, et al.: Factors contributing to poor compliance with anti-TB treatment among tuberculosis patients. Southeast Asian J. Trop. Med. Public Health. 2001 Jun; 32(2): 369–382. PubMed Abstract\n\nMauch V, Bonsu F, Gyapong M, et al.: Free tuberculosis diagnosis and treatment are not enough: patient cost evidence from three continents. Int. J. Tuberc. Lung Dis. 2013 Mar; 17(3): 381–387. Publisher Full Text\n\nKigozi G, Heunis C, Chikobvu P, et al.: Factors influencing treatment default among tuberculosis patients in a high burden province of South Africa. Int. J. Infect. Dis. 2017 Jan; 54: 95–102. PubMed Abstract \| Publisher Full Text\n\nAibana O, Dauria E, Kiriazova T, et al.: Patients' perspectives of tuberculosis treatment challenges and barriers to treatment adherence in Ukraine: a qualitative study. BMJ Open. 2020 Feb 2; 10(1): e032027. PubMed Abstract \| Publisher Full Text" }	[ { "id": "135917", "date": "06 Jun 2022", "name": "Poonam Naik", "expertise": [ "Reviewer Expertise Operational Research", "Tuberculosis", "Geriatric health", "Epidemiology", "Public Health" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe research study findings are important to understand the factors influencing compliance/ adherence to daily treatment regimes.\nThe author may give more details on the following aspects:\nSampling method followed to select the sites and selection of study participants.\n\nOperational definitions followed for certain important terminologies such as: adherence/non adherence, patient provider relation.\n\nDiscussion may include the strengths of the study and limitations of any implications for the program.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8347", "date": "27 Jul 2022", "name": "Rohith Motappa", "role": "Author Response", "response": "Thank you for taking your valuable time for reviewing this article. I have incorporated the following changes in the manuscript based on your suggestions. 1- The sampling method was followed to select the sites and selection of study participants. Response- With the ongoing pandemic of covid-19, convenient sampling was done to select the multiple tuberculosis units in Mangalore. All the TB patients registered in those Tuberculosis Units were included in the study. TB cards were used to approach those patients. The TB patients were approached at their homes/DOTS centers/PHCs with the help of senior treatment supervisors. 2- Operational definitions followed for certain important terminologies such as adherence/non-adherence, and patient-provider relation. Response- Adherence - Patients who not had missed even a single prescribed dose of TB drug were deemed as Adherent Non–Adherence - Patients who had missed at least one prescribed dose of TB drug were deemed as Non-Adherence Patient-Provider Relationship- For differentiating between Good Patient-Provider relationships and Poor Patient-Provider relationships, we used 3 key traits of Health workers toward the patients, namely: Empathy towards the patients Effective communication with the patients and Shared decision-making regarding testing, treatment, and follow-up. If all the 3 traits were deemed as satisfied by patients, they were categorized as Good Patient-Provider relationships, and even if one trait were not up to the mark according to the patients, it was categorized as Poor Patient-Provider relationships 3- Discussion may include the strengths of the study and limitations of any implications for the program. Response - Strengths of the study This study was done during the Covid-19 pandemic when all the resources and logistics were deviated towards curbing Covid-19 infection. With significant numbers indicating the non-adherence in our study, these study findings showcase that no matter which pandemic might arise, Tuberculosis cannot be brushed aside With all the States and UTs working hard toward eliminating TB by 2025, these study findings can provide an insight as to where we stand and how we can improve. Limitations of the study As this study was done in Mangalore, these findings cannot be generalized for the Pan-India assumption This study considered the TB patients on the whole, without taking any details about the resistance patterns. Prevalence of non-adherence would have been even more comprehensible if we had taken the history of resistance towards any of the anti-tubercular drugs." } ] }, { "id": "142666", "date": "18 Jul 2022", "name": "Aniwada Elias Chikee", "expertise": [ "Reviewer Expertise Every area in medical science or Public Health with a bias on TB", "HIV and substance use" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nTITLE\nIs this compliance or adherence as all write up and tables were on adherence?\n\nSuggested title \"Appraisal on patient adherence to and factors influencing the daily regimen of anti-tubercular drugs in Mangalore city: A cross-sectional study\".\nABSTRACT\nMethods - include the study tool [Questionnaire], test statistics used [Chi square and Logistic regression], level of significance [p < 0.05].\n\nResult: It was found that non-adherence was more among; HIV positive (...%), Diabetics (28.8%), etc. Identified predictors of non- adherence were; having side effects 5.23 (confidence interval), etc.\n\nConclusion: There was poor adherence among...Advice on routine...\n\nKey words: Remove \"compliance\" and use \"adherence\".\nMAIN BODY Introduction\nRemove all accessed to reference section after conclusion e.g., (accessed on 28-11-21)\n\nRemove Global tuberculosis report 2020 to reference section.\n\nThe statement can read \"according to WHO, global estimation shows...\"\n\nChange 'Non-compliance' to 'Non-adherence' and 'compliance rate' to 'adherence rate'.\n\nRemove (Global tuberculosis report 2020) and insert reference in superscript (all in last paragraph).\nMethods\nMake Ethical consideration a subheading and include, \"The study purpose was explained participants at the time of the interview. They were informed that, their participation in the study was voluntary and that they could withdraw from the study at any point of time. Maintenance of confidentiality about data and findings was assured to the participants and their consent was obtained.\" in the section.\nStudy population\n\nNB these were patients NOT YUs.\n\nMove Inclusion and exclusion criteria to this section. Suggestion: These were TB patients that accessed care during period of study.\n\nInclusion criteria 1. The sputum positive pulmonary TB patients (18 years and above) registered in three TU, who were on treatment. 2. Patients who had been on anti-TB drugs for at least three weeks of treatment.\nExclusion criteria 1. Patients who were critically ill. 2. Pregnant and lactating women. 3. If the patient couldn’t be found after two consecutive home visits.\nStudy site\nI would additionally state the nature of facilities e.g., Is this for TB alone or involved in other activities, days of TB activities, TB patient load/attendance. number and distribution of TUs in Mangalore.\n\nChange heading \"sampling\" to sample size.\n\nWhy use 7% instead of 5% or 10%?\n\nThe create separate heading for sampling.\nSampling\nNB - How were TB patients selected? E.g., simple random sampling, systematic, convenience, snowballing etc.\n\nThe study sample was drawn from the TU, General Hospital, Mangalore, after taking permission from the District TB Office.\nStudy tools before methodology\nRemove \"pilot study\" and only use \"pretesting\" as pilot study was not done. These do not mean same thing.\n\nRemove accessed and WHO Global tuberculosis report.\n\nChange \"Factors contributing to non-adherence of anti-TB treatment\" to \"reasons for non-adherence to anti-TB treatment\". NB - Factors are derived by crosstabulation or bivariate and followed by multivariate analysis.\n\nChange \"methodology\" to \"Data collection method\".\n\nThe names and addresses of sputum-positive TB patients were collected from treatment cards. The TB patients were approached at their homes/DOTS centers/PHCs with the help of senior treatment supervisors. They were interviewed using questionnaires.\nStatistical analysis\nChi-square was used for associations of characteristics of TB patients and adherence to treatment. Binary Logistic Regression was used to determine predictors/likelihood of adherence to TB treatment. Level of significance was at p < 0.05\n\nRESULTS\nReduce reports tables. Report the findings and leave off its complements as they are seen in the table. E.g., highest age, highest income, education etc for adherent and non adherent.\n\nTable 1 change \"Socio-demographic factors.' to \"characteristics of TB patient based on adherence\". Remove \"a\" in superscript for non significant values.\n\nTable 2 change \"Knowledge and attitude factors contributing to poor compliance with anti-TB treatment\" to \"knowledge and attitude of TB patient based on adherence\". Remove \"a\" in superscript for non significant values.\n\nTable 3 change \"Factors contributing to non-adherence to anti-TB treatment\" to\" Reasons for non adherence to to anti-TB treatment\"\". Remove \"a\" in superscript for non significant values.\n\nTable 5 Change \"Logistic regression detailing the adherence\" to \" knowledge and attitude factors predicting or influencing adherence to anti-TH treatment\".\n\nNB - Remove columns with value and percentages. You do not use it at stage of multivariate analysis.\n\nDo similar analysis for characteristics of the patients - Title will be \"Characteristics of patients predicting or influencing adherence to anti-TH treatment\".\n\nNB; Always mention reference group in reporting regression, e.g., \"Non-adherence was found to be 27 times higher in patients with poor patient provider relationship than those who do not\".\nDISCUSSION\nRemove all those citation in bracket and use superscript for corresponding number at reference section.\n\nAlways state findings in studies you are making comparison for easy appreciation by readers. E.g., \"These findings were equivalent to a study done by Fang et al.15 which reported that...\".\n\nState reasons for your findings or why different from previous studies\n\nInclude implication of some of your findings\nCONCLUSION\nRemove qualitative assessment for you did quantitative study.\n\nRemove Global tuberculosis report 2020 . You do not reference in the conclusion.\n\nBe specific on areas, it is not satisfying.\n\nRecommendation should be based on findings.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] }, { "id": "142668", "date": "19 Jul 2022", "name": "Ganesh Kumar Saya", "expertise": [ "Reviewer Expertise Maternal and child health", "occupational health", "spiritual health" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nComments:\nIn the results section of the abstract, please add more findings relevant to the study objectives.\n\nThe introduction may be further strengthened by adding studies carried out on TB- drug adherence during the COVID pandemic.\n\nConclusions should be based on the study findings. Specific recommendations based on the study findings may be included.\n\nDo include the limitations of the study.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-462
https://f1000research.com/articles/11-718/v1	29 Jun 22	{ "type": "Correspondence", "title": "Mechanistic contribution of CaV3.2 calcium channels to trigeminal neuralgia pathophysiology not clarified", "authors": [ "Wolfgang Liedtke" ], "abstract": "Trigeminal neuralgia (TN) is a rare, yet debilitating trigeminal pain disorder, with jolts of supramaximal-debilitating pain in one or more of the three trigeminal branches. Familial TN is now recognized, with a recent report describing several human genetic polymorphisms. One affected gene is the voltage-gated calcium channel, CaV3.2 (CACNA1H), with 19 polymorphisms first described. A recent study in PAIN by Gambeta-et-al (DOI:10.1097/j.pain.0000000000002651) is entitled \"CaV3.2 calcium channels contribute to trigeminal neuralgia \". Here, I call into question their claim. My main arguments are 1)-3): 1) Gambeta-et-al studied 4/19 mutations reported in heterologous cellular expression, with two mutations showing gain-of-function of CaV3.2, two mutations not showing gain-of-function. Therefore the exemplary picks of familial TN-associated CaV3.2 mutations do not show a uniform change of channel function, such as gain-of-function. 2) In Gambeta-et-al, one gain-of-function mutation, CaV3.2(G563R) was directed to mouse trigeminal ganglion (TG) neurons, and their resulting hyperexcitability was demonstrated. A critical control of a non-gain-of-function channel was not included here, it was unclear whether neurons were separated by sex, and human sensory neurons were not used. Importantly, it is not clear that TG neurons are the critical cellular site of CaV3.2 mutations. 3) Gambeta-et-al used CaV3.2-/- pan-null knockout mice. Human TN-associated CaV3.2 mutations were not over-expressed. They used a infraorbital nerve constriction injury and measured facial heat hyperalgesia. CaV3.2-/- show a pain phenotype similar to control, yet are not affected by a CaV3-inhibitory compound, Z944. My argument is that when starting with TN-associated human mutations, use of a trigeminal neuropathic pain model is of limited value, and that human mutations have to be expressed against a mouse null background. Re thermal cue, Gambeta-et-al failed to study cold-evoked pain which is a TN clinical hallmark. Thus, Gambeta-et-al's 2022 PAIN-paper offers little new mechanistic evidence why CaV3.2 polymorphisms are associated with trigeminal neuralgia.", "keywords": [ "trigeminal neuralgia - CaV3.2 ion channel - channelopathy - pain - CACNA1H gene - familial trigeminal neuralgia" ], "content": "\n\nIn “CaV3.2 calcium channels contribute to trigeminal neuralgia” the authors state “TN is a debilitating syndrome […] Understanding the pathophysiology of TN is needed to provide new targets for therapeutic intervention.” (Gambeta et al. 2022).—No disagreements here.\n\nWhether their recent paper (Gambeta et al. 2022) indeed makes constructive progress on this front as claimed should be open for discussion. In this Correspondence I am asking for readers’ consideration whether data as reported and authors’ discussion of these data can indeed support their claim. In view of Dong et al. (2020), where polymorphisms in the CACNA1H gene were reported by Dong et al. as associated with familial trigeminal neuralgia, the lead question of “And what is new?” has to be asked, with particular focus on how findings by Gambeta et al. provide new mechanistic understanding of this debilitating pain condition in affected families. In other words, if a CACNA1H polymorphism carrier patient with trigeminal neuralgia asks their doctor “So tell me, doctor, why do I—and my family members—have these terrible jolts of pain, how does it really work?”; can they get a more rationally-based answer as a result of Gambeta et al.’s study?\n\nPresented data appear the result of dedicated physiologic, animal behavior, neurocellular, molecular biology and biochemical experimentation. However, results as presented simply to do not support the tendered claims and conclusions.\n\nGambeta et al. has three subsections, (i) directed expression of mutant CaV3.2 channels in heterologous cellular systems, (ii) directed expression of CaV3.2(G563R) in trigeminal ganglion sensory neurons, (iii) mouse studies using CaV3.2−/− pan-null knockout mice and a CaV3-selective chemical inhibitor, Z944. With regards to (i), there is non-congruence whether there is gain-of-function of the interrogated variants, or not. For (ii), the assumption that trigeminal ganglion sensory neurons are the critical cellular players in trigeminal neuralgia of CaV3.2 polymorphisms is unfounded. Only one variant is tested, not in human sensory neurons. With (iii), a model for trigeminal neuropathic pain after peripheral branch injury is used, and CaV3.2 mutations are not tested.\n\nThus, in terms of pathophysiology of trigeminal neuralgia we are left where we were before publication of Gambeta et al.’s recent paper in PAIN, perhaps scratching our heads more re the roles of CaV3.2 ion channels.\n\nWith regards to some critical detail:\n\nThe human genetic findings from Dong et al. (2020) are the starting point. As ion channels with some supporting evidence to their role in pathologic pain, CaV3.2 channels are legitimate targets for exploration of their mechanistic contribution to trigeminal neuralgia. How did the authors arrive at the four variants selected, out of a choice of 19? Ideally all variants should be interrogated by a validated first-pass screen, which is not asking too much at n=19. Any selection should be based on non-biased criteria, such as selecting polymorphisms from various subdomains of the molecule, representing equitably how the changes are distributed over the sequence (in case they do). The authors start with an arbitrary selection of mutations that then reveal channel function different from wildtype. Importantly, there is no unifying direction apparent in terms of the different-from-wildtype phenotype as presented. These data, taken in ensemble, indicate that the interrogated CaV3.2 channel mutations differ from wildtype, for each mutation in a different manner, with two of the mutations showing similar gain-of-function for peak current density. Importantly, the two other mutations do not reveal such a phenotype. It follows that lack of a specific explanatory electrophysiologic phenotype in half of interrogated channel mutations means that the detected gain-of-function in the other two CaV3.2 mutations is simply unclear with regard to their mechanistic impact on trigeminal neuralgia.\n\nThen one of the CaV3.2 gain-of-function channels is directed for expression in adult mouse trigeminal ganglion sensory neurons, evoking hyperexcitablity. However, the authors used mouse trigeminal ganglion sensory neurons, not human neurons, the latter a feasible experimental platform with stronger translational impact, especially for a paper with wider visibility, published in PAIN. The presented result is interesting, but lacking a critical control, namely at least one of the CaV3.2 mutations that did not reveal a gain of function. Importantly, how relevant is the examination of trigeminal ganglion sensory neurons with directed expression of CaV3.2(G563R)? How certain are we that trigeminal ganglion sensory neurons are the critical cellular site for CaV3.2 mutations to contribute to trigeminal neuralgia? Findings in nerve injury, as presented here for infraorbital nerve, or as referenced for DRG-peripheral nerve injury, do not exclude other cellular lineages as critical sites of action for CaV3.2 mutations: glial cells could also be involved such as peripheral glia, namely Schwann cells (ganglionic and peripheral) and satellite cells, and central glia, namely astrocytes, microglia and even oligodendroglia. Besides trigeminal ganglion sensory neurons, there are trigeminal nucleus spinalis pain relay neurons where CaV3.2 is also expressed, possibly also in glial cells that co-function with these neurons. In which cell lineage CaV3.2 expression is critical is simply unknown in trigeminal neuralgia. Last but not least, trigeminal ganglion sensory neurons were derived from “5–7-week-old mice”—of which sex? Directed expression of a human trigeminal neuralgia-associated CaV3.2 mutation to trigeminal sensory neurons is at least as relevant for the experimental objective of Gambeta et al. as for their mouse in-vivo studies, yet for culture of trigeminal ganglion sensory neurons they were not conducting the experiments in a sex-separate manner as they did for mouse in-vivo experiments.\n\nNow, onto the in vivo model. The authors have included several qualifier statements why infraorbital nerve constriction injury (CION) is not trigeminal neuralgia. These qualifiers are not wrong, but starting with human genetic polymorphisms that were detected in trigeminal neuralgia, NOT trigeminal neuropathic pain, dictates use of a more validated model, not of a marginally relevant model. Which outcomes of CION research have improved mechanistic understanding and clinical care of trigeminal neuralgia?\n\nCan some cases of familial trigeminal neuralgia be reduced to a CaV3.2 channelopathy? If so, this would allow us to then translate from the infrequent genetic alteration toward the more frequent sporadic disease, sticking with the same target, CaV3.2. The animal data presented by Gambeta et al. do not pertain to this concept. They are disjointed because none of the human CaV3.2 mutations were introduced into the mouse, for a dedicated interrogation against a CaV3.2−/− background. As presented, there is simply a complete lack-of-connect between mouse data and human CaV3.2(mutant) physiology data.\n\nOf the mouse data presented, the biggest red flag, peculiarly left uncommented, is that CaV3.2−/− pan-null mice show a highly similar nocifensive behavioral response to CION as do wildtype control mice! Non-injured pain behavior is less sensitive in CaV3.2−/− mice, meaning there is a measurable effect on the trigeminal pain system, depending on presence/absence of CaV3.2. This finding can be interpreted as a “positive control” that the engineered CaV3.2 null mutation affects trigeminal pain processing for one of the measured parameters. But then the pain phenotype in terms of nocifensive behavior in CaV3.2−/− is indistinguishable from wildtype in response to CION!\n\nThe documented different response to compound Z944—analgesic in wildtype for 30–60 min, complete lack of effect in CaV3.2−/− mice—should prompt dedicated follow up studies to this interesting starting point, such as sensory neuron-specific knockdown of CaV3.2. But considering this result in the context of the other presented data, it follows that we do not understand trigeminal neuralgia pathophysiology better, and arguably we are also left confused in terms of contributions of CaV3.2 channels to trigeminal peripheral nerve constriction injury.\n\nMoreover, the authors present hypersensitivity caused by CION as measured by heat avoidance. Clinically, in the context of trigeminal nerve pain, cold pain, e.g. as can be evoked by the slightest drafts of (cold) air, is a striking hallmark of the human disease which apparently the authors did not consider.\n\n\nData availability\n\nThere are no data associated with this article.", "appendix": "References\n\nDong W, Jin SC, Allocco A, et al.: Exome Sequencing Implicates Impaired GABA Signaling and Neuronal Ion Transport in Trigeminal Neuralgia. iScience. 2020; 23(10): 101552. PubMed Abstract \| Publisher Full Text\n\nGambeta E, Gandini MA, Souza IA, et al.: CaV3.2 calcium channels contribute to trigeminal neuralgia. Pain. 2022. PubMed Abstract \| Publisher Full Text" }	[ { "id": "142603", "date": "21 Jul 2022", "name": "Nicholas A. Veldhuis", "expertise": [ "Reviewer Expertise We each have >12 years experience in analgesic drug discovery utilising a range of pre-clinical pain models including migraine" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis correspondence provides a perspective on a recent publication by Gambeta et al, in the journal PAIN, entitled “CaV3.2 calcium channels contribute to trigeminal neuralgia”.\n\nOverall, the critique captures and distills all of the key findings made by Gambeta et al. and relates them to a prior human study where polymorphisms in the CACNA1H gene were reported. By doing so it asks readers to consider “what is new” and whether findings in this study progress our mechanistic understanding of how CACNA1H polymorphisms contribute to trigeminal neuralgia.\n\nThe author raises pertinent and valid concerns, within the context of the clinical relevance, which no doubt has limited the mechanistic insight and translational impact of the study. This includes choice of the most appropriate and clinically relevant pain model, rationale behind selection of which missense mutations to assess (i.e. selected sites in only a single domain), sex-specific differences, the methods to assess function (e.g. comparing gain and loss of function on a null background, or lack of a cold pain model) and failure to consider the potential contribution of CaV3.2 expressed by other cell types that drive pain.\n\nHowever, recognizing the expectations of a leading specialized journal such as PAIN, and the formative nature of this work, we suggest it would be useful to moderate some of these arguments and provide further constructive feedback, to benefit the authors of this specific study and for future consideration by others attempting related studies:\n\nThe comment about justifying the choice of these 4 particular mutants makes sense, but we suggest that author should equally justify screening all 19 mutants by pointing to any related studies in PAIN or equivalent calibre journals where a similarly comprehensive approach has been taken;\n\nComments about the lack-of-connect between mouse data and the human CaV3.2 physiology data would be nicely supported by suggesting logical follow up experiments. This may include assessment using a mouse model expressing the mutant human CaV3.2 or WT human channel, and/or determining specific roles through neuronal vs global deletion.\n\nFinal paragraph: Rather than stating that the authors simply did not consider the need to comment about the deficiencies of the study with respect to cold pain models, we suggest appending some constructive comments to this paragraph about how the study could have been improved if this had been added.\n\nIs the rationale for commenting on the previous publication clearly described? Yes\n\nAre any opinions stated well-argued, clear and cogent? Yes\n\nAre arguments sufficiently supported by evidence from the published literature or by new data and results? Partly\n\nIs the conclusion balanced and justified on the basis of the presented arguments? Yes", "responses": [ { "c_id": "8560", "date": "27 Jul 2022", "name": "Wolfgang Liedtke", "role": "Author Response", "response": "I am grateful to the reviewer for their careful appreciation of my comment, for their highly informed and constructive feedback. The reviewer's suggestions have been very helpful for revision of the ms. Specifically, in response: \"The comment about justifying the choice of these 4 particular mutants makes sense, but we suggest that author should equally justify screening all 19 mutants by pointing to any related studies in PAIN or equivalent calibre journals where a similarly comprehensive approach has been taken;\" Three exemplary studies are now referenced. \"Comments about the lack-of-connect between mouse data and the human CaV3.2 physiology data would be nicely supported by suggesting logical follow up experiments. This may include assessment using a mouse model expressing the mutant human CaV3.2 or WT human channel, and/or determining specific roles through neuronal vs global deletion.\" The logical follow up experiments are now explicitly spelled out, as suggested. \"Final paragraph: Rather than stating that the authors simply did not consider the need to comment about the deficiencies of the study with respect to cold pain models, we suggest appending some constructive comments to this paragraph about how the study could have been improved if this had been added.\" Constructive comments, as suggested by the reviewer, are now appended to this paragraph." } ] } ]	1	https://f1000research.com/articles/11-718
https://f1000research.com/articles/11-377/v1	31 Mar 22	{ "type": "Software Tool Article", "title": "Introducing the Task Switching Game: a paradigm for neuroimaging and online studies", "authors": [ "Danielle L. Kurtin", "Dr. Matthew Jaquiery", "Dr. Tibor Auer", "Prof. Adam Hampshire", "Dr. Ines R. Violante", "Dr. Matthew Jaquiery", "Dr. Tibor Auer", "Prof. Adam Hampshire", "Dr. Ines R. Violante" ], "abstract": "While writing this abstract I received an email, which I promptly answered. When I returned my attention to the abstract, I struggled to regain my flow of writing. In order to understand this deficit in performance associated with switching from one task to another, or \"switch cost\", cognitive neuroscientists use task switching paradigms to recreate similar experiences. However, many researchers may be familiar with the difficulties that accompany modifying an established paradigm to suit their experimental design, or even the challenge of creating a new, unvalidated paradigm to perturb a particular aspect of cognitive function. This software tool article introduces a novel task switching paradigm for use and adaptation in online and neuroimaging task switching studies. The paradigm was constructed with a flexible, easily-adapted framework that can accommodate a variety of designs. This paradigm utilizes three psychometrically opposed but visually similar tasks- the Digit Span, the Spatial Span, and the Spatial Rotation. In two Use Cases we demonstrate the reliable nature of overall task performance and the dependence of switch costs on certain task parameters. This task framework can be adapted for use across different experimental designs and environment, and we encourage researchers to modify the task switching game for their experiments.", "keywords": [ "task switching", "experimental design", "software", "cognitive task", "switch cost" ], "content": "Introduction\n\nSwitch costs are defined as the deficit in task performance incurred when switching between one task and another.1,2 Behavioral switch costs are observed when comparing successive trials in which participants switch between tasks to those where the same task was repeated. This switch cost can be viewed as a result of the increasing demand on executive function incurred by restructuring one mental “task set” (the goals, rules, and attentional focus unique to one task) to a different one.3,4 Put simply, switch costs may be a result of interference in cognitive restructuring processes. Neuroimaging studies classify the reconfiguration process as a result of the changes in brain network activity and functional connectivity that reflect the changes in task set.5,6 The neural correlates of each task set may be considered the brain state unique to each task set.\n\nMany studies have investigated how unique, overlapping, dissociable, and predicative these brain states are.7–10 To determine how unique the brain states for each task set are, Soreq et al built a classifier that identifies which working memory task a participant was completing based on their brain states.11 They showed that behaviorally distinct aspects of working memory mapped to distinct but densely overlapping patterns of activity and connectivity within the brain, known as the multiple demand cortex.12,13 The differing mental processing characteristics that underpin participant’s task performance are known as psychometric characteristics,14 and three tasks used in Soreq et al’s study- the Digit Span, Spatial Span, and Spatial Rotation- maximized the psychometric distance across orthogonal factors- visuospatial reasoning and verbal reasoning.15 Though all tasks recruited the multiple demand cortex, brain states could be separated according to the working memory processes recruited by each task, showing a high correspondence among behavioral constructs and resulting working memory subprocesses.11,16,17\n\nThis invites the follow-up question “How does the brain reconfigure between these different brain states?” The literature here is sparser, with a lack of studies that model how neural networks reconfigure when transitioning from one discrete task to another (referred to as “set switching” or “context switching”18). In future studies we hope to characterize the trajectory neural networks take to effectively switch between tasks. Therefore, we created a cued task switching paradigm that aims to generate a behavioral and physiological switch cost for use in experiments that will characterize, model, and modulate the switch cost. We chose three psychometrically opposed tasks from Soreq et al11 to force distinct reconfiguration from one brain state to the next. Two versions of the task exist- one is written in JavaScript to collect behavioral data online, and the other is written in Python for use in neuroimaging studies. These versions are designed to be highly similar to one another. We describe both in detail below, then present the results of two pilot studies. The pilot studies aimed to evaluate whether the paradigm is within an optimal difficulty range, and whether the task creates a switch cost in reaction time or accuracy.\n\n\nMethods\n\nIn this section, we first provide a description of each of the three tasks’ features. Then, we detail how the overall task is compiled, and what sections may be modified to suit different experimental designs.\n\nThe cued task switching paradigm switches between three tasks- a Spatial Rotation, Spatial Span, and Digit Span task. Variants of these tasks have been created and implemented over the years.19,10 The essential components of each task are clarified below.\n\nAll tasks use a similar stimuli presentation and response framework to reduce visual and motor confounds. Stimuli are created using normed pixel units, and the screen angle is standardized to reduce color variation across devices. Stimuli are presented on a 6x6 grid in the middle of the screen. To ensure the tasks are visually similar, each task’s stimulus grid flashes cells and contain numbers, even if not strictly necessary for the task. After presentation is complete, the stimulus grid disappears, and three answer grids appear in a row across the screen. One of the answer grids contains the correct answer, and the other two have one of the cells from the correct answered shifted, meaning two of the three grids’ answers are incorrect by one cell (Figure 1).\n\nThis depiction represents the task described in the manuscript, but all components shown can be changed to suit the needs of other experiments.\n\nDigit Span measures verbal working memory capacity. In this task, a sequence of 6 numbers within a shaded box on the stimulus grid appears one after another. One of the three answer grids will contain the correct sequence of numbers, and the other two will be correct except for one digit. This is a variant of the WAIS-R intelligence test that evaluates working memory.19 Spatial Span tests visuospatial working memory capacity. 6 squares flash digits appearing in a random sequence, one after another, in the stimulus grid. The correct answer grid will display the same sequence of numbers that flashed in the stimulus grid, while the other two display a sequence that is incorrect by one cell. Finally, Spatial Rotation measures the ability of the participant to mentally rotate objects in memory. Similar to the Spatial Span, shaded cells appear one after another, though in this task the previous cells continue to flash with each new addition. The resulting end stimulus is a flashing grid of 6 cells. The answer grids contain a 90, 180, or 270-degree rotation of the final grid, with two of the three answer grids incorrect by one cell. Gifs showing trials of each task can be found here: https://github.com/daniellekurtin/task_switching_paradigm/tree/master/TaskGifs.\n\nWe describe the implementation of the task switching paradigm as created for our experimental use, rather than the software package as a whole. We provide the software package as an example of how it may be implemented and used for an experiment.\n\nRunning the main.py script initiates an implementation of the task switching paradigm. The paradigm consists of blocks composed of a sequence of tasks. Each task is composed of a run of trials. Trials consist of stimuli and answer grids (Figure 1). Runs are set up so that the last run on one block continues as the first run on another block. For example, if the last run within a block consists of 9 trials of Digit Span, then the break could occur on trial 7, and after the break, the remaining two trials would be the first two trials of the next block. This approach maximizes the number of task switches in each block while keeping the number of runs balanced across each of the three task types. The main.py implementation begins with a popup to record participant and session information (taskSwitching.participant_gui.py). After the popup is dismissed, a scanner sync process is initiated, creating a Pythonic interface for neuroimaging experiments. Then main.py constructs a demo that participants may play multiple times to ensure their familiarity with how to play the tasks. The demo’s parameters are set by taskSwitching.ExperimentTaskSwitch class (and its parent taskSwitching.Experiment class), with trials determined by main.py. Then, main.py constructs a new task blueprint using the default parameters set by taskSwitching.ExperimentTaskSwitch class. If desired, implementations may specify the types of tasks the paradigm will switch between, the length of the cue cards, the number of trials per task, the duration of each stimuli, and more, as demonstrated in the tutorial construction. A pseudorandomized list of trials, runs, and blocks are constructed based on the provided specifications, ensuring there are an equal number of switches for each task type. Each task’s trials are instances of classes unique to each task type: taskSwitching.TrialDigitSpan, taskSwitching.TrialSpatialSpan, and taskSwitching.TrialSpatialRotation. Parameters may be set at the Experiment, Component, Trial, or specific trial task level, with the later parameters overriding earlier ones where there are conflicts. Values that can be set in this way include how stimuli and answers are created and displayed, and for how long.\n\nTrials are instances of Components, and cue cards, instructions, and breaks are also components. taskSwitching. Components include the following: taskSwitching.ComponentRest determines the rest screen; taskSwitching.ComponentStart is the screen before participants begin the task switching game; taskSwitching.ComponentInfoCard creates the cue cards that prompt a task switch; and taskSwitching.ComponentTrialGap fixes the screen that appears between trials.\n\nAs aforementioned, trials consist of stimuli and their answer grids, which are constructed according to the taskSwitching.Grid class. Finally, as the task is played, information is saved to a.csv file. What is saved and the file format is set by the taskSwitching.Experiment class.\n\nThis task is executable in a Pythonic environment. Touch events (i.e., participant’s responses) can be collected via button box, through keyboard strokes, and by mouse clicks. Responses minimize motor confounds through requiring a single button press or click to select an answer grid for all three tasks. We will now describe the workflow and design features for both the neuroimaging and online versions.\n\nThe paradigm begins with a participant GUI that requires entering the participant ID, age, gender, and session ID (fields can be adjusted depending on specific study needs). Participants then play a demo that includes each of the tasks at least once. The demo includes performance feedback: after participants select an answer grid, a green box will highlight either the correct answer grid, or the space it would occupy. This gives participants a better understanding of how well they comprehend the task’s rules. After a loading screen the participant is presented with a cue card stating they may press any button on the button box to begin. Once a button is pressed, the first cue card is presented, followed by the first trial of that task. After the first stimulus is finished, there is a variable delay before participant responses are enabled. Participants then have a window to respond. Once the participant selects their answer grid, the other two disappear, and the first answer grid is held on the screen for the remainder of the response window. This serves two purposes. First, by eliminating the other answer grids, we provide feedback that their answer has been recorded, preventing repetitive button presses. Second, we eliminate the potential for participants to compare their answer to the other answer girds. Once the trial is over, there is a variable intertrial interval (e.g. 100 to 1100 msec) to introduce a jitter. The jitter is used to improve reliability of fMRI signals, and increase the spatio-temporal resolutions.20 The number of trials per run range is modifiable (5-10 might be a reasonable number for fMRI experiments). Once the task is complete, a cue card stating “Next Task: [Digit Span/Spatial Span/Spatial Rotation]” is displayed to indicate which task is next. There are no task repeats (i.e., if the previous task was the Digit Span, the next would be either the Spatial Span or Spatial Rotation). The duration of the cue card is a random choice of either 0.5 or 4.0 seconds, though the number of cue cards and their length can be varied. This enables future investigation into the effects of short vs long cue presentation on neural network dynamics and task performance. After the trials within the block are complete, a break occurs (though the presence and/or duration of a break can be modified). The break screen contains a centered fixation cross, and a countdown until the task restarts. Once all blocks are complete, the task quits, and data is saved in a.csv file. Participant reaction time is computed as the difference between when they submit an answer and when a response was enabled for that trials. Reaction time is measured in seconds with hundred-millionths period precision.\n\nOur version of the task switching paradigm is hosted on the University of Surrey’s web servers. The university servers serve three main functions: enabling participants to access and play the task, recording their performance, and storing “task blueprints” (Figure 2). These “task blueprints” are pre-compiled sessions (the order of tasks, the number of trials per task, etc), and are the same as the tasks generated locally. Uploading the task blueprints is simple, and reduces the burden on the server. These blueprints are created using serve−trial−sequences.py, with dependencies and scripts used to communicate among servers located in the www folder of the paradigm’s repository. Participants access the task from the link http://www.task-switching-game.surrey.ac.uk. They are walked through a tutorial with written instructions and accompanying animations. Participants then play the same demo described in the above section. After the demo, participants are invited to either play it again, or continue on to the main task. Once they continue, they read an ethics statement and fill out consent checklists and their participant information (participant ID, age, sex). Next, they receive the instruction to “Press next to begin.” At this stage the online version of the task is as the neuroimaging version, except it consists of one, 20-minute long block, and answer selection is done using the mouse (the task is configured to work using a keyboard, mouse, or button box).\n\nParticipants accessed the task using a link that can be opened via web browsers using either a mobile device or computer (though we specified we prefer that participants used a computer).\n\n\nUse Case 1: Online study\n\nThe study was advertised on SONA, a participant recruitment and experiment management system that connects participants to ongoing studies. Participants could sign up and play the task switching game, and were awarded course credit for completion. All participants gave informed consent. This study was conducted with ethical approval by the University of Surrey Ethics Committee.\n\nParameters for this use case are as follows:\n\n• Delay from stimulus end to participant response window: 0.15 s\n\n• Participant response window: 3.0 s\n\n• Block break: 120.0 s\n\n• Response mode: mouse\n\n• Inter-trial interval: 100-1100 msec\n\n• Cue card length: 0.5 or 4.0 s\n\n• Number of trials per occurrence: 6-9 trials\n\n• Range of trials: 176-187\n\nData analysis was conducted using the .csv file output by the online task in a MATLAB environment. Non-normally distributed performance data was normalized by computing the z-score with a center of zero and one standard deviation. Generalized linear mixed effects models and ttests assessed the influence of task type and occurrence on performance. Occurrence refers to the number of times a participant has played a task. For example, if the task starts with a Digit Span, then switches to the Spatial Rotation, then back to the Digit Span, the occurrences would be 1, 1, 2.\n\nData cleaning The total number of online participants was n=87, with a mean age of 19.68, and all participants were university students. We removed any sessions with less than 100 trials (n=7). There were no participants that had >20% omissions in any task. We removed participants that performed below chance level for any task (n=19), leaving us with a final cohort of 61 participants (n=52 females). Each participant had an average of 178.9 trials (sd=12.37) overall.\n\nOverall performance-reaction time and accuracy Performance was evaluated using accuracy and mean reaction time (MRT) (Table 1). Kolgov-Smirnov tests show both accuracy (D(1509)=0.55, p≤0.0001) and MRT (D(10909)=1, p≤0.0001) are non-normally distributed, and were thus normalized.\n\nThere was a significant effect of task type on accuracy (F[2,1503]=10.8, p=2.1e-05). Post-hoc T-tests show each task’s accuracy is significantly different than the others, with Digit Span performing 12.6% and 4.8% better than Spatial Span (t(502)=-9.6, p=3.1e-20) and Spatial Rotation (t(502)=-3.6, p=3.7e-04) respectively, (Figure 3A). Spatial Rotation performance was 7.8% higher than Spatial Span performance (t(502)=-6.1, p=5.5e-11). There was no significant effect of occurrence on accuracy (F[1,1503]=2.6, p=0.10) (Figure 3B).\n\nThe top and bottom edges of the grey boxes represent the 25th and 75th percentiles, with the mean being the white dot. Extension of the whiskers limits outliers. A kernel density estimate of the data provides the edges to the violin plot, and individual data points are dark blue. ∗ denotes significance at p≤0.05 after Bonferroni correction for multiple comparisons.\n\nThere was a significant effect of occurrence on MRT (F[1,1481]=8.4, p=0.004) (Figure 3D). A Bland-Altman plot was created to investigate whether the effect of occurrence was a result of unreliable RT recording or learning effects. There are no remarkable effects on the data, as shown in the (Figure 4A). There was no significant effect of task type on MRT (F[2,1481]=0.1, p=0.92) (Figure 3C).\n\nPlots show the mean (solid line), 95% confidence limits (dashed lines), and the data points (blue points).\n\nSwitch Cost There is a significant overall switch cost in accuracy (t(1447)=3.0, p=0.003) (Figure 5A) but not MRT (t(811)=0.85, p=0.39) (Figure 5B). Because there is an effect of task type on accuracy, we looked at whether there was an effect of switch on each task’s performance. After Bonferroni correction for multiple comparisons, there is a significant switch cost in Spatial Span (F[1,120]=7.4, p=0.008) and Spatial Rotation (F[1,120]=7.4, p=0.007) accuracy, but not Digit Span (F[1,120]=0.25, p=0.62) Figure 5C-E).\n\nThe top and bottom edges of the grey boxes represent the 25th and 75th percentiles, with the mean being the white dot. Extension of the whiskers limits outliers. A kernel density estimate of the data provides the edges to the violin plot, and individual data points are dark blue. ∗ denotes significance at p≤0.05 after Bonferroni correction for multiple comparisons.\n\nWe also sought to determine whether switch cost was influenced by switch type- the six possible combinations of how one task may switch to another. For example, a switch from Digit Span to Spatial Span is one switch type, and vice versa, another. We found a significant effect of switch type (F[1,425]=6.8, p=0.009) on accuracy but not MRT (F[1,405]=1.3, p=0.26). Post-hoc ttests found no significant differences in accuracy per switch type after Bonferroni corrections for multiple comparisons.\n\nIn this first online pilot of the task switching paradigm we found task type influenced accuracy. The better performance in the Digit Span compared to the Spatial Span is not surprising. A study of 44,600 participants playing a range of cognitive tasks online found that, when playing the Digit Span, the average number of stimuli remembered by participants is 7, whereas the average number of stimuli remembered for the Spatial Span is 6.19 This means that, using our 6x6 grid, the number of stimuli to retain for the Digit Span is well within the abilities of our population. The discrepancy in performance between the Digit Span and Spatial Rotation is less clear. However, in a previous study comparing performance between working memory tasks that greatly resemble the Digit Span and Spatial Rotation, performance on the Digit Span analog was significantly better than their analog visuospatial task.21 Finally, the difference in performance between the Spatial Span and the Spatial Rotation may be a result of participant’s ability to form effective strategies for each task. A study by Gardony et al investigated mental rotation tasks and found that, as difficulty increased, cognitive strategies shifted in order to meet the demands of the task.22 Participants playing the Spatial Span can more easily rely on recognition strategies than in the Spatial Rotation, where participants not only need to recall patterns, but perform a mental rotation of the patterns as well. The additional demands of the Spatial Rotation task may have resulted in the discrepancy between Spatial Span and Spatial Rotation performance.\n\nWe found an influence of occurrence on MRT. The greatest difference in MRT per occurrence is between occurrence 1 and 7. MRT in occurrence 7 is 6% faster than during occurrence 1; a marginal improvement over the duration of the experiment.\n\nThe switch cost in accuracy, but not reaction time, demonstrates a partial success of our aim to create a task switching paradigm that forces a behavioral switch cost. The presence of switch costs in accuracy, but not reaction time, may be a function of the response window imposed on participants. A study by Hughes et al found that switch accuracy fell 29% by introducing a response time window,23 but this switch cost did not extend to reaction time. Our response window of three seconds is likely enough to induce a time pressure on participants, as well as the added switch cost in accuracy, but not reaction time. The explicit cues informing participants a switch is about to occur may have reduced the behavioral switch cost. A study by Merian also using a random, cued, task switching paradigm reported a smaller switch cost than the switch cost observed in a study by Monsell without random task switches.1,24 Tornay and Milan compared the two studies and hypothesized that the cue for a change in task gives participants time to suppress the current task set. This initiates the cognitive restructuring process of task switching, thus increasing participants’ ability to quickly reconfigure to the demands of the new task.4 Our cue card intervals of 0.5 and 4.0 seconds were likely long enough to allow participants to suppress the currently active task set when the cue card is shown. This preparatory process may decrease the switch cost, but not the cognitive restructuring process of switching. We did not collect neuroimaging data for this study, but we plan to in the future, and will investigate this arm of research.\n\nDue to an error in the data collection process, we were unable to assess how the variation in cue card presentation length effected participant’s performance. Because of the potentially significant influence this variability may have had on participant’s performance, we standardized the cue card length from 4.0 seconds to 0.5 seconds, and conducted a second round of data collection. The results from this second use case are detailed below.\n\n\nUse Case 2: Online study with standardized cue card length\n\nAs a result of our inability to calculate the impact of cue card length on MRT and accuracy, we standardized the cue card length to be 0.5 seconds. Our data collection and analysis were conducted using the same methods as above.\n\nData cleaning The total number of online participants was n=40, and all participants were university students. We removed any sessions with less than 100 trials (n=4). We also removed participants that had >20% omissions in any task (n=0), participants that performed below chance level for any task (n=3), leaving us with a final n=33 (n=31 females) Each participant had an average of 182 trials (sd = 3.35) overall.\n\nOverall performance-reaction time and accuracy Accuracy and MRT were used to evaluate performance (Table 2). Kolgov-Smirnov tests show both accuracy (D(825)=0.55, p=4.4e-215) and MRT (D(825)=1, p≤0.0001) are non-normally distributed.\n\nThere was a significant effect of task type (F[1,819]=3.1, p=0.047) (Figure 5A), but not occurrence (F[1,819]=0.01, p=0.94) (Figure 6B), on accuracy. Post-hoc T-tests show each task’s accuracy is significantly different than one another, with Digit Span performing 14.9% and 5.5% better than Spatial Span (t(274)=-5.6, p=4.9e-08) and Spatial Rotation (t(274)=-3.4, p=7.8e-04), respectively. Spatial Rotation performance was 9.34% higher than Spatial Span performance (t(274)=-9.1, p=2.3e-17).\n\nThe top and bottom edges of the grey boxes represent the 25th and 75th percentiles, with the mean being the white dot. Extension of the whiskers limits outliers. A kernel density estimate of the data provides the edges to the violin plot, and individual data points are dark blue. ∗ denotes significance at p≤0.05 after Bonferroni correction for multiple comparisons.\n\nThere was a significant effect of occurrence on MRT (F[1,813]=12.0, p=0.0006) (Figure 6D). A Bland-Altman plot was created to investigate whether the effect of occurrence was a result of unreliable RT recording or learning effects. There are no remarkable effects on the data, as shown in the (Figure 4B). There was no significant effect of task type on MRT (F[2,813]=0.39, p=0.67) (Figure 6C).\n\nSwitch cost There is no significant switch cost in accuracy (t(791)=-0.69, p=0.49) (Figure 7A) or MRT (t(469)=-0.34, p=0.73) (Figure 7B). There was no significant effect of switch type on accuracy (F[1,229]=0.01, p=0.92).\n\nExtension of the whiskers limits outliers. A kernel density estimate of the data provides the edges to the violin plot, and individual data points are dark blue.\n\nThis online pilot sought to evaluate performance on the task switching paradigm and see how the standardization of cue cards influenced performance.\n\nThere was high similarity between the first and second pilot, with both pilots showing an effect of occurrence on MRT and task type on accuracy. However, the switch cost in the Spatial Span and Spatial Rotation observed in the first pilot was not present in the second. The loss of switch cost is surprising, especially given that the cue card length was standardized to 0.5 seconds as opposed to 4.0 second, suggesting that switch costs may by driven by a longer cue card.\n\nThis is supported by a task switching study by Periánez and Barcelo25 that studied the role of exogenous (cues) and endogenous (task-set activation) in the behavior and EEG markers of switch costs. Their experimental paradigm randomly varied the cue-trial interval (CTI) between participants as either 800 or 2000 ms. They found that the shorter CTI did not consistently lead to a greater switch cost, and in fact, influenced a cue-switch benefit. The results from our study are similar- Use Case 1, which had CTIs of either 500 ms or 4000 ms, exhibited a greater switch cost than in Use Case 2, which solely had CTIs of 500 ms. Their EEG results suggest this phenomena may be a result of reduced P3 activity that arises from an interplay between time-dependent endogenous (anticipatory task set reconfiguration) and exogenous (cue) factors. We suggest future studies utilize the neuroimaging compatibility of our task switching paradigm to replicate this finding.\n\nThis task contains two visual confounds. First, in the Spatial Span and Digit Span the boxes disappear after the initial presentation; in the Spatial Rotation, they build upon one another. The resulting end image is a visually more complex image. This confound is unavoidable due to the nature of the Spatial Rotation task. Second, the stimuli in the Digit Span present in half the time as the stimuli for the Spatial Span and Spatial Rotation, 0.25 seconds as opposed to 0.50 seconds, respectively. This difference was implemented after rounds of piloting the task, where it was noticed the Digit Span was markedly easier than the other two tasks. By reducing the stimulus presentation time we increase the difficulty of the Digit Span, making it more comparable to the other two tasks. This is important, as cognitive load influences the brain network activity and connectivity within a task.26 Future researchers are encouraged to modify these parameters as it suits their task. The task switching paradigm was built with flexibility in mind, so it may be easily adapted to various experimental designs.\n\n\nConclusions\n\nSearching for “task switching paradigms” reveals a staggering amount of task designs, theories, and neuroimaging data. The quantity and heterogeneity of experimental designs address specific facets of switch costs, and by proxy, cognitive function. The authors are not aware of an existing framework that can be adapted easily to suit the demands of different experiments, leaving researchers to either re-use old tasks or create entirely new ones to suit their experimental designs. We needed to construct a novel task switching paradigm, and chose to create one within a framework that can be adapted to suit the needs of different experiments. Here we introduce a flexible software package to create task switching paradigms. It can accommodate nuanced designs within a stable and robust framework for on or offline studies, and is compatible with neuroimaging methods. The task switching paradigm does induce minimal switch costs, but efforts are underway to improve the switch cost.\n\n\nData availability\n\nRepository: Task Switching Paradigm. https://github.com/daniellekurtin/task_switching_paradigm with an MIT license.\n\nThis project contains the following underlying data:\n\n• rawdata_pilot4.csv. (Data downloaded from the task server for Use Case 1.)\n\n• rawdata_pilot5.csv. (Data downloaded from the task server for Use Case 2.)\n\nData are available under the terms of the repository’s MIT license.\n\n\nSoftware availability\n\nSource code available from: https://github.com/daniellekurtin/task_switching_paradigm with an MIT license.\n\n\nCompeting interests\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nIRV and TA were funded by the BBSRC (Ref: BB/S008314/1). DK was funded by the Vice Chancellor Studentship at the University of Surrey. MJ was funded by the Medical Research Council (Ref: 17/18_MSD_661552).", "appendix": "Acknowledgements\n\nWe would like to thank Henry Hebron for his guidance in creating the figures in this manuscript.\n\n\nReferences\n\nRogers RD, Monsell S: Costs of a predictible switch between simple cognitive tasks. J. Exp. Psychol. Gen. 1995; 124(2): 207–231. Publisher Full Text\n\nJersild AT: Mental set and shift. Arch. Psychol. 1927.\n\nVandierendonck A, Liefooghe B, Verbruggen F: Task switching: interplay of reconfiguration and interference control. Psychol. Bull. 2010; 136(4): 601–626. PubMed Abstract \| Publisher Full Text\n\nTornay FJ, Milán EG: A more complete task-set reconfiguration in random than in predictable task switch. The Quarterly Journal of Experimental Psychology Section A. 2001; 54(3): 785–803. PubMed Abstract \| Publisher Full Text\n\nYeung N, Nystrom LE, Aronson JA, et al.: Between-task competition and cognitive control in task switching. J. Neurosci. 2006; 26(5): 1429–1438. Publisher Full Text\n\nDosenbach NUF, Visscher KM, Palmer ED, et al.: A core system for the implementation of task sets. Neuron. 2006; 50(5): 799–812. PubMed Abstract \| Publisher Full Text\n\nLorenz R, Violante IR, Monti RP, et al.: Dissociating frontoparietal brain networks with neuroadaptive bayesian optimization. Nat. Commun. 2018; 9(1): 1–14. Publisher Full Text\n\nShi Y, Wolfensteller U, Schubert T, et al.: When global rule reversal meets local task switching: The neural mechanisms of coordinated behavioral adaptation to instructed multi-level demand changes. Hum. Brain Mapp. 2018; 39(2): 735–746. PubMed Abstract \| Publisher Full Text\n\nHampshire A, Daws RE, Neves ID, et al.: Probing cortical and sub-cortical contributions to instruction-based learning: Regional specialisation and global network dynamics. NeuroImage. 2019; 192: 88–100. PubMed Abstract \| Publisher Full Text\n\nSoreq E, Leech R, Hampshire A: Dynamic network coding of working-memory domains and working-memory processes. Nat. Commun. 2019; 10(1): 1–14. Publisher Full Text\n\nSoreq E, Violante IR, Daws RE, et al.: Neuroimaging evidence for a network sampling theory of individual differences in human intelligence test performance. Nat. Commun. 2021; 12(1): 1–13. Publisher Full Text\n\nDuncan J, Owen AM: Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends Neurosci. 2000; 23(10): 475–483. PubMed Abstract \| Publisher Full Text\n\nFedorenko E, Duncan J, Kanwisher N: Broad domain generality in focal regions of frontal and parietal cortex. Proc. Natl. Acad. Sci. 2013; 110(41): 16616–16621. PubMed Abstract \| Publisher Full Text\n\nDeary IJ: Psychometric intelligence differences and brain function. Novartis Foundation Symposium. Wiley Online Library; 2000; pages 58–72.\n\nHitch GJ, Allen RJ, Baddeley AD: Attention and binding in visual working memory: Two forms of attention and two kinds of buffer storage. Atten. Percept. Psychophys. 2020; 82(1): 280–293. PubMed Abstract \| Publisher Full Text\n\nBaddeley A: Exploring the central executive. The Quarterly Journal of Experimental Psychology Section A. 1996; 49(1): 5–28. Publisher Full Text\n\nBaddeley AD, Hitch GJ, Allen R: A multicomponent model of working memory. Working memory: State of the science. 2020: 10–43. Publisher Full Text\n\nKim C, Cilles SE, Johnson NF, et al.: Domain general and domain preferential brain regions associated with different types of task switching: A meta-analysis. Hum. Brain Mapp. 2012; 33(1): 130–142. PubMed Abstract \| Publisher Full Text\n\nHampshire A, Highfield RR, Parkin BL, et al.: Fractionating human intelligence. Neuron. 2012; 76(6): 1225–1237. PubMed Abstract \| Publisher Full Text\n\nWatanabe M, Bartels A, Macke JH, et al.: Temporal jitter of the bold signal reveals a reliable initial dip and improved spatial resolution. Curr. Biol. 2013; 23(21): 2146–2150. Publisher Full Text\n\nHubber PJ, Gilmore C, Cragg L: Mathematics students demonstrate superior visuo-spatial working memory to humanities students under conditions of low central executive processing load.2019.\n\nGardony AL, Eddy MD, Brunyé TT, et al.: Cognitive strategies in the mental rotation task revealed by eeg spectral power. Brain Cogn. 2017; 118(0): 1–18. PubMed Abstract \| Publisher Full Text\n\nHughes MM, Linck JA, Bowles AR, et al.: Alternatives to switch-cost scoring in the task-switching paradigm: Their reliability and increased validity. Behav. Res. Methods. 2014; 46(3): 702–721. PubMed Abstract \| Publisher Full Text\n\nMeiran N: Reconfiguration of processing mode prior to task performance. J. Exp. Psychol. Learn. Mem. Cogn. 1996; 22(6): 1423–1442. Publisher Full Text\n\nPeriáñez JA, Barceló F: Updating sensory versus task representations during task-switching: Insights from cognitive brain potentials in humans. Neuropsychologia. 2009; 47(4): 1160–1172. PubMed Abstract \| Publisher Full Text\n\nCocchi L, Halford GS, Zalesky A, et al.: Complexity in relational processing predicts changes in functional brain network dynamics. Cereb. Cortex. 2014; 24(9): 2283–2296. PubMed Abstract \| Publisher Full Text" }	[ { "id": "129896", "date": "19 May 2022", "name": "Frini Karayanidis", "expertise": [ "Reviewer Expertise Cognitive control processes", "task-switching paradigm", "cognitive ageing", "behavioural and EEG measures. I do not have sufficient expertise to evaluate the software code." ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper presents a well-motivated objective – to design and make available a well-controlled task-switching paradigm that can be used in multiple contexts (eg., imaging and online studies) and with different groups. This will facilitate the comparison of findings across studies and participant groups.\nThe authors put substantial effort into making the three tasks similar in visual presentation and response requirements, so that differences between them can be attributed to different cognitive processes rather than sensory or motor processes. They select three visual tasks that have previously established psychometric properties and focus on digit span, spatial span, and spatial rotation, with a multiple-choice response format (i.e., given 3 options and have to select the correct response). The design includes short blocks of trials (7-10 trials) on the same task. Each block begins with a cue card that indicates which task will be performed. Task order is pseudorandomised, as the same task is not repeated across two blocks. The duration of the cue card is variable, the duration of each target card is not specified, but the response grid appears after variable delay. Once the participant selects one of the three options, the others disappear and after another variable interval, the next trial appears. The first data set shows significant accuracy and RT differences between tasks, and a significant ‘switch cost’ on accuracy but not RT. The second data set is run with a fixed cue duration (0.5 secs) and the effect of the task is found again, but no ‘switch cost’ in either accuracy or RT.\nThe paper is generally very well-written, and the data are clearly presented with good quality, analytical figures. However, I found that there are many weakly justified decisions in the paradigm development that question whether the paradigm can produce data comparable to the vast volume of task-switching literature available and therefore weaken the potential impact of the paper. My concerns are mainly related to the fact that the design of the task-switching paradigm, the choice of tasks, the timing parameters, the response options, and the conditions are not consistent with any of the multiple paradigm structures available. Moreover, the paradigm itself did not produce robust switch effects, which questions its usefulness as a task-switching paradigm.\nThere are many well-established variants of the task-switching paradigm (e.g., Grange and Houghton1, Jamadar et al.2, Karayanidis and McKewen3). These produce somewhat different ways to measure switch costs and additional measures of interest. The paradigm used here is probably most similar to that used by Allport et al.4, but with significant differences to make comparisons difficult. The paper does not actually specify how ‘switch cost’ is measured. An example trial sequence is: Task A: 1 2 3 4 5 6 7, Task B: 1 2 3 4 5 6 7 8 Task C: 1 2 3 4 5 6 7, etc. I can only assume that trial 1 in each block is considered the ‘switch’ trial. However, it’s not clear which of the other trials are used as the ‘repeat’ trial, e.g., is it trial 2, the average of all other trials, etc. This will impact the value of the repeat trial, and therefore switch cost estimation.\nAllport and Wylie5 showed that these paradigms produce both switch and restart costs, as the first trial of each block produces poorer performance whether the task switches or not. Without occasional repeat blocks, e.g., Task A A B C C B A, it is impossible to differentiate between the switch and restart costs. In addition, this paradigm does not allow estimation of mixing cost (the difference between repeat trials in a single-task vs a mixed-task block), a measure that has been found to be more sensitive to variability in some groups (e.g., ageing, see Karayanidis and McKewen3, Karayanidis et al.6).\nAnother major concern is the timing parameters. The paradigm includes very slow trials – the exact inter-trial interval is not specified but appears to be in the order of seconds – and substantial jitter. Monsell and colleagues7,8 have shown that timing, jitter, etc can result in measurable changes in outcomes. Ruge et al.9 reviewed the fMRI task-switching literature and concluded that timing variations used to adapt the paradigm to fMRI timing can significantly impact the cognitive control processes being activated.\nFinally, the tasks themselves are very different from the tasks typically used in task-switching paradigms. In previous studies, tasks tend to involve a simple visual stimulus (e.g., letter, number, shape) that requires a 2-choice decision with a discrete response associated with that decision on each trial (e.g., is the letter a vowel or a consonant, press left for vowel, right for consonant). Here, the stimulus is a matrix and different types of exemplars appear over time. So, the stimulus involves a sequence of processes that evolve over time (how long?). The response is not the result of a discrete decision associated with that target. It involves the outcome of a process of comparing three different matrices against the representation of the stimulus held in working memory and selecting which is the closest match. The set of cognitive operations involved is very different to those in typical task-switching paradigms, and the memory-related operations are likely to drown out any effects of task-switching that only apply to the first trial of each block. This may account for the weak switch effects reported. Moreover, any such task-switching processes are not tightly timed to an event (e.g., cue) so will not be readily targeted by event-related fMRI or EEG measures. In addition, this paradigm is likely to produce a lot of motion, especially eye movements, which may create artefacts for fMRI as well as EEG.\nOverall, the aim of the paper is sound, the approach well-executed, and the concept of designing paradigms that can be used across platforms and labs is highly commendable. The paradigm appears suited to investigating the cognitive and neural processes engaged by three different visual attention tasks – spatial span, digit span and visual rotation. However, in my opinion, it is not suited to measuring the cognitive and neural processes involved in task-switching.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Partly\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? No\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? No", "responses": [ { "c_id": "8538", "date": "27 Jul 2022", "name": "Danielle Kurtin", "role": "Author Response", "response": "Response to Prof Frini Karyanadis’s Peer Review Report Prof Karyanadis provided a thorough summary of our manuscript and its intent to introduce a novel task switching paradigm for use in online or neuroimaging studies. She captured the careful design we implemented to reduce visual and motor confounds, the discrete nature of the visual working memory tasks the paradigm switches among, as well as the results of our two Use Cases. We thank her for the careful reading of the manuscript and for the valuable comments. We appreciate her main concerns centre around our task design and how it diverges from existing literature, the task’s timing, the study’s results, and considerations on how we define and evaluate switch costs. We have addressed Prof Karyanadis’s concerns in our new version of the manuscript and have responded to each concern below. Our paradigm’s design is different from the existing literature Our task’s different experimental design draws three concerns from Prof Karyanadis - that its novelty and difference make comparison to existing literature difficult, that its design cultivates memory-related processes rather than switching processes, and that switch events are not tightly timed to a cue. In this section, we address each concern in turn. We understand Prof Karyanadis’s concern that it may be difficult to compare our paradigm to existing task switching literature that utilizes standard task switching frameworks. This paradigm is intentionally different from most task switching paradigms so one can study research questions traditional task switching paradigms are not well-suited to investigating – in our case, evaluating the neural correlates of large set shifts. In the likely event there are other researchers who also need a new paradigm to meet the needs of their research question, we created our paradigm in an easily modifiable framework so that fewer entirely new paradigms need to be created. We acknowledge we may not have made this paradigm’s differences and their impact clear enough. To ensure readers are aware that results from our experiment may not generalize to task switching studies with more standard designs, we have added the following sentences (in bold) to the Introduction: \"This invites the follow-up question “How does the brain reconfigure between these different brain states?” The literature here is sparser, with a lack of studies that model how neural networks reconfigure when transitioning from one discrete task to another (referred to as “set switching” or “context switching” (Kim et al 2012). In future studies we hope to characterize the trajectory neural networks take to effectively switch between tasks. Therefore, we created a cued task switching paradigm that aims to generate a behavioral and physiological switch cost for use in experiments that will characterize, model, and modulate the switch cost. We chose three psychometrically opposed tasks from Soreq et al (2021) to force distinct reconfiguration from one brain state to the next. Rather than switching between stimulus response mappings or rules, our task switches between entire task sets, similar to Allport et al (1994). Yet our task differs from to Allport's set-shifting task by shifting among different, psychometrically opposed working memory tasks, rather than rules or stimuli within a task. These differences were introduced with the aim of inducing large set shifts observable by fMRI, where future studies may explore how neural networks reconfigure to meet the demands of different working memory tasks.\" We have also added another sentence in the Limitations section, to ensure readers consider the difference in our paradigms to most others in their interpretation of results and application of this paradigm to other studies: \"Finally, our task differs from most variants of task switching paradigms, and this should be taken into consideration when comparing results from this task to literature using different paradigms.\" Prof Karyanadis’s second point centres around a concern that the paradigm probes memory, rather than switch-related processes. We agree that these shifts in working memory processes are different than the common 2-choice decision tasks, both in terms of the number of cognitive operations required and the three, rather than two, response options. Nevertheless, we intentionally switch between three psychometrically opposed working memory tasks because we wanted to investigate the neural correlate of large set shifts, which could not be possible using more standard task switches, such as stimulus-response or rule switches. Regarding Prof Karyanadis’s third point that there is not an event to which we can identify the task switch events, we would like to highlight that our Cue Cards precede each switch, and are timed cues by which we can localize task switching events. Figure 1 provides a visual depiction of how a Cue Card precedes a set of trials that build into a run of a task before another Cue Card announces a switch to the next run of trials of a different task. Task timing We understand Prof Karyanadis has two concerns regarding task timing, with the first being that we do not specify a precise intertrial interval (ITI). We do not specify a specific ITI because, as described in the Neuroimaging studies section, the ITI varies randomly between 100 to 1100 msec. Should future researchers wish to change this, the task was created to be easily customizable, and we remark in several places that all task parameters (such as the ITI) can be changed to suit the researcher. Second, we understand Prof Karyanadis’s concern about the influence the variable ITI exerts on cognitive control processes or fMRI analysis. To ensure readers are aware of the impact of adding a variable ITI, we have included the following sentence: “For online studies, we recommend researchers include a jitter-induced delay related regressor in models of BOLD activity, and remove jitter during offline studies as recommended by [1] for response-cue trial intervals.” in the Neuroimaging study section. Study results We acknowledge Prof Karyanadis is unsure whether a task switching paradigm qualifies as such if it does not induce switch effects. As with any study, the results are the one aspect of an experiment that cannot be controlled. We argue that the absence of positive results does not invalidate the design of the paradigm. We also would like to highlight that we did pilot our work to identify suitable task parameters that induce a switch cost. Before conducting any Use Cases, we determined which parameters would ensure above-chance and below-ceiling performance in each task. For example, literature has shown most healthy young adults can remember 7 digits in a digit span [2], but we use 6x6 grids for the working memory tasks, meaning that the number of stimuli participants are asked to remember for the digit span should be within their ability. Early piloting showed that, when 6 stimuli were presented at the standard 0.5 seconds per stimuli, participants exhibited ceiling effects. We, therefore, shortened the stimuli presentation time for digit span stimuli to 0.25 seconds, with the intent to standardize performance across tasks. With these parameters, we began conducting Use Case 1. In Use Case 1, the cue cards preceding each task were either 4.0 or 0.5 seconds. We observed a switch cost in accuracy but not reaction time, and, based on literature showing short cue cards induce switch costs [3][4], we chose to standardize our cue card duration to 0.5 seconds in an attempt to induce a switch cost in both accuracy and reaction time. Though we did not observe a switch cost after standardizing our cue card duration, in our discussion for the second Use Case we suggest that our negative results may be due to an interplay between endogenous, preparatory processes and exogenous, cue-driven processes [5]. Because of the customizable nature of the paradigm, we encourage future researchers to pilot the task using parameters (cue cards, length of time stimuli are presented, the number of tasks, etc) suitable for their experiment and assess the presence of a switch cost. Switch costs We thank Prof Karyanadis for identifying that we did not fully specify how we measure switch cost. We have clarified this in the manuscript in the Use Case 1 section as follows: “Switch task types are defined as the first trial after a switch between tasks, and stay trial types are all other trials.” We appreciate that our task design does not permit a comparison of switch vs restart costs, nor mixing costs, and how this may have influenced our ability to induce switch costs. We have added the following sentences to our Limitations section to make this clearer to readers: “Though the piloting of this task was performed with healthy control participants, future researchers may want to assess differences between healthy control and patient populations. Mixing costs may be more sensitive to between-group variability [6], and one limitation of our task structure is that it does not permit the exploration of mixing costs. Moreover, the current design did not allow repeats blocks of the same task (for example, this order would not occur: Digit Span, Spatial Span, Spatial Span, Spatial Rotation), and therefore cannot investigate the difference in switch vs restart costs [7]. Future researchers are invited to adapt the paradigm’s design to allow repeat task blocks, to investigate switch vs restart costs, and explore whether introducing mixed-task blocks induces switch costs not seen in this version of the paradigm.” Finally, to make it abundantly clear to readers that our paradigm does not consistently introduce a switch cost, we have included the following sentence at the end of the Software Tool Article’s Introduction: “The pilot studies observe that, though the two versions of the task do not consistently induce a switch cost, the paradigm operates within an optimal difficulty range, and participants do not exhibit learning effects. Though our task does not produce traditional switch costs, we believe this paradigm is useful given its highly adaptable, multi-modal, open-source nature.”. We hope this response addresses Prof Karyanadis’s concerns surrounding our Software Tool Article Manuscript. We appreciate her insight, and the changes we have made as a result of her review have improved and strengthened the manuscript. References: [1] Ruge H, Jamadar S, Zimmermann U, Karayanidis F: The many faces of preparatory control in task switching: reviewing a decade of fmri research. Human brain mapping. 2013; 34(1):12–35 [2] Hampshire A, Highfield RR, Parkin BL, et al.: Fractionating human intelligence. Neuron. 2012; 76(6): 1225–1237 [3] Monsell S, Mizon GA: Can the task-cuing paradigm measure an endogenous task-set reconfiguration process? Journal of Experimental Psychology: Human perception and performance. 2006; 32.3(493). [4] Schneider DW, Logan GD: Task-switching performance with 1: 1 and 2: 1 cue–task mappings: Not so different after all. Journal of Experimental Psychology: Learning, Memory, and Cognition. 2011; 37(2):405. [5] Periáñez JA, Barceló F: Updating sensory versus task representations during task-switching: Insights from cognitive brain potentials in humans. Neuropsychologia. 2009; 47(4): 1160–1172. [6 Karayanidis F, Whitson LR, Heathcote A, Michie PT: Variability in proactive and reactive cognitive control processes across the adult lifespan. Frontiers in psychology. 2011; 2:318. [7] Allport DA, Wylie GR: Task-switching, stimulus-response bindings, and negative priming. In S. Monsell and J. Driver (Eds.), Control of cognitive processes: Attention and performance XVIII. Cambridge, MA: MIT Press. 2000. 35-70" } ] } ]	1	https://f1000research.com/articles/11-377
https://f1000research.com/articles/10-789/v1	11 Aug 21	{ "type": "Research Article", "title": "Sea grapes powder with addition of tempe rich in collagen: An anti-aging functional food", "authors": [ "Happy Kurnia Permatasari", "Fahrul Nurkolis", "Christopherous Diva Vivo", "Sutamara Lasurdi Noor", "Rahmawati Rahmawati", "Son Radu", "Hardinsyah Hardinsyah", "Nurpudji Astuti Taslim", "Nelly Mayulu", "Defny Silvia Wewengkang", "Mury Kuswari", "Siti Chairiyah Batubara", "William Ben Gunawan", "Maizer Said Nahdi", "Christopherous Diva Vivo", "Sutamara Lasurdi Noor", "Rahmawati Rahmawati", "Son Radu", "Hardinsyah Hardinsyah", "Nurpudji Astuti Taslim", "Defny Silvia Wewengkang", "Mury Kuswari", "Siti Chairiyah Batubara", "William Ben Gunawan", "Maizer Said Nahdi" ], "abstract": "Background: This study aimed to determine the potential anti-aging effects of sea grapes and tempe (Fermented soybeans) collagen particle size, by measuring the activities of anti-glycation, antioxidant and tyrosinase inhibitors. Methods: Collagen was isolated from sea grapes and tempe freeze dried powder and treated with different NaOH concentrations (0.10 M; 0.20 M; 0.30 M), and CH3COOH 1 M solution, separately. The collagen particle size was adjusted by stirring at 1000 rpm for 5 and 10 hours. 2,2-diphenyl-1-picrylhydrazyl (DPPH) was used to measure the antioxidant activity, and L-tyrosine and L-DOPA (l-3,4-dihydroxyphenylalanine) were used as a marker of tyrosine inhibition. Results: The collagen treated with 0.10 M NaOH produced the highest collagen yield (11.65%), and largest particle size (2455 nm). Additionally, this collagen, when treated for 5 hours, exhibited 24.70% antioxidant activity, 62.60% anti-glycation, 8.97% L-tyrosine, and 26.77% L-Dopa inhibition activities. Meanwhile, the collagen treated for 10 hours had a 9.98% antioxidant activity, 41.48% anti-glycation, 7.89% L-tyrosine, and 2.67% L-Dopa inhibition activity. Conclusion: Sea grapes and tempe collagen powder treated with 0.10 M NaOH and stirred for 5 hours, as functional foods have anti-aging properties.", "keywords": [ "Ageing", "antioxidant", "sea grapes", "tempe", "functional food" ], "content": "Introduction\n\nUnhealth diet and excessive exposure to UV (ultra-violate) light can cause premature skin aging, leading to excess melanin production (hyperpigmentation), and darker patches (depigmentation) (Saeedi et al., 2019). Excessive UV light exposure can trigger oxidative stress, causing damage and apoptosis in skin cells. Oxidative stress occurs due to the increased intercellular levels of reactive oxygen species (ROS), which play an important role in pathogenesis of aging and chronic disorders (Peñalver et al., 2020; Park, 2013; Park et al., 2004). Consumption of high antioxidant functional foods in recent years has become popular as they can reduce oxidative stress damage. The presence of hydroxyl groups in antioxidant compounds acts as hydrogen donors to stabilize and prevent the formation of new ROS (Pereira et al., 2009).\n\nIn some Asian countries, such as Malaysia, Indonesia, and the Philippines, sea grapes or Caulerpa racemosa, which are edible marine macroalgae, are believed to be functional foods or nutraceuticals packed with antioxidant properties that can delay or prevent premature skin aging (Eren et al., 2019; Schumacker, 2015; Peñalver et al., 2020; Tanna et al., 2020; Yep et al., 2019; Pakki et al., 2020). Studies have explored several bioactive components in sea grapes, such as bioactive peptides, fibers (polysaccharides), polyphenols, flavonoids, antioxidants, and their distinctive compounds caulerpin (Cao et al., 2021; Yang et al., 2015; Yep et al., 2019). In line with this, sea grapes extract tested in diabetic rats indicated a lowering effect on glucose levels, reduced aspartate aminotransferase, and alanine aminotransferase activities, and a had a hepatoprotective effect (Qudus et al., 2020).\n\nSimilar to sea grapes, tempe (Fermented soyabeans), which is a local Indonesian food and known worldwide as a functional food, also has a high antioxidant activity (Kadar et al., 2020; Mani & Ming, 2017).\n\nPremature aging can be exacerbated by an unhealthy diet as well. High glucose levels at the presence of limited insulin can trigger the glycation process, whereby glucose is attached to the proteins, lipids, and DNA of the skin, producing Advanced Glycation End-products (AGEs) (Hantzidiamantis & Lappin, 2019; Kim et al., 2017). Consequently, AGEs can deactivate the antioxidants, attack collagen, and elastyn, leaving the skin to lose moisture, become wrinkled, dull, and prone to damage and premature aging (Gill et al., 2019). Consumption of antioxidants and collagen, such as those found in sea grapes and tempeh, can inhibit AGEs (Aubry et al., 2020; Kadar et al., 2020; Yang et al., 2015).\n\nTyrosinase inhibition is another useful way of avoiding depigmentation. Tyrosinase transforms tyrosin to 3,4-dihydroxyphenylalanine (DOPA), then transforms DOPA to dopakuinone; which results in melanin at the end of the process (Pillaiyar et al., 2017). As such this study aimed to determine the anti-aging potential effect of sea grapes and tempe collagen powder, by analyzing the activities of anti-glycation, antioxidant and tyrosinase inhibitors.\n\n\nMethods\n\nSea grapes (Caulerpa racemosa) were rinsed and cleaned with the use of CO2 free water. The soybean-based tempe is mixed with sea grapes (0.25:1) with a blender, and frozen at the −22°C for 12 hours. Samples were dried with the use of freezer dryer (LyovaporTM L-200) for 24 hours, which resulted in 0.3-0.5 mm powder.\n\nThe determination of water content was based on the Association of Official Analytical Chemists (AOAC) drying method (Thermogravimetry) (Latimer, 2019) (Table 1), and the content was calculated by using the following formula:\n\nW0 = Weight of empty cup\n\nW1 = Weight of the cup + initial sample (before heating in the oven)\n\nW2 = Weight of cup + initial sample (after cooling in desiccator)\n\nThe procedure for determining the ash content was also with the use of the AOAC method (Latimer, 2019), and the content was calculated by using the following formula:\n\nCollagen from sea grapes and tempe powder is isolated by treating the samples (ready-to-eat dry products) with three variations of NaOH concentrations (0.10 M; 0.20 M; 0.30 M) with a ratio of 1:10 (w/v), for 48 hours. The samples were then dried with the use of a freeze dryer (Lyovapor ™ L-200) and treated with 1 M CH3COOH solution at a ratio of 1:10 (w/v), for 24 hours. Whatman filter paper (Grade 1) was used to obtain the filtrate. Lastly, the collagen obtained was once again dried with a freeze dryer.\n\nThe optimal NaOH treated collagen is dissolved with distilled water (1:2 (v/v)) and spun for 5 and 10 hours with a magnetic stirrer (1000 rpm) to establish size transformation. The size of the particles was measured by using the Particle Size Analyzer (PSA), and the antioxidant activity was tested with DPPH Assay (2,2-diphenyl-1-picrylhydrazyl), antiglycation, and tyrosinase inhibitors.\n\nThe enzyme-linked immunosorbent assay (ELISA, Sigma #CS0790) was used to determine the antioxidant activity of DPPH (Batubara et al., 2015). 100 μL of each sample along with 100 μL of DPPH (0.3 mM) was added to the 96-well microplate and incubated for 30 minutes in a dark room. The absorbance was measured by using an ELISA reader at a wavelength of 517 nm (Underlying data) (Nurkolis, 2021). The antioxidant activity is calculated as follows:\n\nA0 = Absorbance of blank\n\nA1 = Absorbance of standard or sample\n\nThe anti-glycation measurement (Table 2) was carried out as previously described (Povichit et al., 2010) (Underlying data) (Nurkolis, 2021). All the test solutions were incubated at 60°C for 40 hours. After incubation, the aliquots (100 μL) were pipette into a 96-well plate. The relative amount of glycated Bovine Serum Albumin (BSA) was measured using a fluorometer at an excitation wavelength of 370 nm, and emission of 440 nm.\n\nThe tyrosinase enzyme inhibitory activity was measured as previously described (Batubara et al., 2015). L-tyrosine and L-DOPA (l-3,4-dihydroxyphenylalanine) were used as substrates (MyBioSource #MBS9301852), and kojic acid as positive controls (Table 5) (Underlying data) (Nurkolis, 2021). Samples were dissolved with dimethyl sulfoxide (DMSO) as stock solution. The concentration variant was prepared by dissolving collagen with a phosphate buffer (pH of 6.5). A total of 70 μL of solution along with 30 μL of tyrosinase enzyme (Sigma, 333 units mL-1 in phosphate buffer solution was added) was pippeted into the 96-well plate, and the mixture was incubated for 5 minutes. To this mixture, 110 μL of substrate (L-tyrosine 2 mM) was added and incubated at 37°C for 30 minutes. The absorbance was measured at a wavelength of 492 nm, by using the microplate reader (Spectrophotometer).\n\n\nData analysis\n\nStatistical analyses were performed by using SPPS 26.0 for the Windows version. The differences between samples are analysed based on the antioxidant activity, anti-glycation activity, and tyrosinase inhibition activity tests. The data obtained from three replications (triples) were analyzed by ANOVA at 95% CI (p < 0.05). The result is defined as significant if the p-value is < 0.05.\n\n\nResults\n\nTable 1 shows the triplicate process resulted in 3.42 (± 1.05%) water content and 2.65 (± 0.50%) ash content.\n\nCollagen yield obtained by each concentration is shown in Table 3. The isolation with NaOH 0.10 M produced the highest collagen yield (p < 0.05), this showed that there was a significant difference in the yield of the three variations of NaOH and CH3COOH treatment. Levenes’ test of homogeneity of variants was p = 0.397 (p > 0.05).\n\nParticle Size Analyzer (PSA) was used to determine the collagen particles size. The collagen yields ranged from 1012 nm to 2455 nm, with the highest DPPH and glycation inhibitions at 2455 nm (11.74% and 62.76%, respectively) (Table 4). In addition to producing significantly different yields, different treatments across the three samples were also significantly different in the particles size (p = 0.000), with p > 0.05 homogeneity. The collagen with the largest particle size of 2455 nm was obtained from 0.10 M NaOH treatment for 5 hours (Table 4).\n\n* Shows significant difference at p = 0.05.\n\nThe 0.10 M NaOH treatment for 5 hours, resulted in 24.70% and 62.60% antioxidant and anti-glycation activities, respectively (Table 4). However, treatment with 0.10 M NaOH for 10 hours resulted in 9.98% antioxidant and 41.48% anti-glycation activities. Additionally, treatment with 0.10 M NaOH for 5 hours inhibited 8.97% of L-tyrosine and 26.77% of L-Dopa activities (Table 5).\n\n* Shows significant difference at p = 0.05.\n\n\nDiscussion\n\nBased on the ash and water content analysis, the powder made from sea grapes and tempe is considered safe to consume, based on the Indonesia National Standard (SNI) No. 01-4320-1996 regulations for food in powder form or powder extract (3% maximum water content). Moreover, pre-treatment was done to remove the non-collagen proteins, as well as assessing the amount of pure collagen proteins in the final product. Collagen is usually insoluble in alkaline solutions, however, NaOH treatment is commonly used in the collagen extraction process as it can significantly minimize collagen loss, compared to other alkaline solutions (Liu et al., 2015). In this study collagen from sea grapes and tempe powder treated with 0.10 M NaOH produced the highest yield, which showed the effectiveness of the extraction process. As indicated by Potaros and colleagues, the difference in yield can be caused by the extraction method, such as the concentration of a solution in the non-collagen protein separation process, and the type of material used (Potaros et al., 2009). Therefore, treatment with variations of NaOH concentration could affect the collagen yields (%), particle size, DPPH inhibition (%) and anti-glycation produced (%).\n\nThe collagen particle measurements in this study ranged from 1012 to 2455 nm (Table 4), which was too large to be considered as nanoparticles (10-1000nm) (Mohanraj & Chen, 2007). Therefore, further optimization was carried out in order to reduce the collagen particle size of the 0.10 M NaOH treatment, through stirring for 5 or 10 hours. It is necessary to reduce the particle size in order to increase its absorption by the digestive system (Mohanraj & Chen, 2007). In a study by Mohanrja et al., reducing the particle size should be through the hydrolysis process, and not by a mechanical process such as stirring, as it can re-solidify or coagulate the collagen (Mohanraj & Chen, 2007). However, the hydrolysis process was avoided in this study, as it might have broken down other important compounds, such as antioxidants. Mechanical stirring for 5 hours, resulted in almost 2-fold reduction in the size of the collagen particles. However, stirring for 10 hours did not reduce the particle size due to the reasons described by Mohanraj et al. (2007).\n\nThe treatment with 0.10 M NaOH (Table 4), produced the largest particle size with the highest anti-glycation activity compared to other concentrations, however, its antioxidant activity was lower compared to 0.30 M NaOH. The percentage of antioxidants produced is similar to commercial collagen (IC50), which is greater than the result in the study by Fauzi (2018). At 0.10 M NaOH treatment with 5 hours had a better anti-glycation activity than at 10 hours. The resulting anti-glycation activity was higher when compared to the 17.74% activity of the collagen produced in Fauzi dissertation research (Fauzi, 2018).\n\nExcessive melanin production or hyperpigmentation caused by exposure to excessive UV rays can lead to dark skin or depigmentation (Saeedi et al., 2019). Tyrosine inhibition can reduce excessive melanin production, which can prevent skin damage. The results of this study showed that treating L-tyrosine and L-DOPA substrates for 5 hours had a greater tyrosinase enzyme inhibitory activity, compared with treatment for a longer period (Table 5) (Figure 1). In the Fauzi study, commercial collagen did not show tyrosinase enzyme inhibitory activity at 1000 mg/L and exhibited lower activity than the collagen obtained in the present study (Fauzi, 2018).\n\nSea grapes and tempe powder combined with a variety of food additives can be used by manufacturing companies as functional foods or anti-aging nutraceuticals, by NaOH (0.10 M) and CH3COOH (1 M) treatment at 1000 rpm for 5 hours (Figure 1). However, this in vitro pilot study has the potential to be a basic reference for pre-clinical research. Further trials are needed to determine the continued efficacy of this study.\n\n\nConclusion\n\nSea grapes and tempe collagen powder as functional foods or nutraceuticals have anti-aging properties. Based on the anti-glycation, anti-tyrosinase and antioxidant activities, the collagen of this powder treated with 0.10 M NaOH for 5 hours, has the most optimal anti-aging effect. Manufacturers seeking to produce anti-aging food products rich in collagen can use this method for determining the optimal powder formulation, however extensive trials are still needed to further analyze its clinical effects.\n\n\nData availability\n\nFigshare: Sea grapes powder with addition of tempe rich in collagen: An anti-aging functional food.\n\nDOI: https://doi.org/10.6084/m9.figshare.15072597.v3 (Nurkolis, 2021).\n\nThe project contains the following underlying data:\n\n• Raw data: Water and ash content, antioxidant activity, glycation inhibition activity, particle size, anti-tyrosinase activity of the collagen. The chemical composition of the solution in the anti-glycation activity test.\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).\n\n\nAuthor contributions\n\nAll authors contributed to the writing and revision of this article; and all authors have read and approved the final manuscript. H. K. P. and F. N. gathered study ideas, designed the experiments, analyzed data, and compiled manuscripts. N. A. T., H. H., N. S., M. K., S. R., R. R. and N. M. analyzed and interpreted data and critically revised the manuscript. The F. N., S. L. N., D. S. W. and H. K. P. conducted experiments, analyzed biochemistry, and critically revised the manuscript. N. M., S. C. B., W. B. G., and C.D.V., implemented experimental protocols, assisted in statistical analysis, interpreted data, and critically revised manuscripts. All writers read and approve the final manuscript.", "appendix": "Acknowledgement\n\nWe thank State Islamic University of Sunan Kalijaga; Faculty of Medicine-Brawijaya University and all of contributors for their outstanding help in formatting the paper. I would also like to express my gratitude to Prof. Ir. Hardinsyah, MS., Ph.D. (as President of the Federations of Asian Nutrition Societies; President of the Food and Nutrition Society of Indonesia; and Chair of Southeast Asia Probiotics Scientific and Regulatory Experts Network), and Prof. Dr. Nurpudji A Taslim, MD., MPH.,Sp.GK(K) (Chair of Indonesian Clinical Nutrition Physician Association), and also to Nindy Sabrina, S.Gz., M. Sc. who has provided comments, suggestions, and input in the research and writing of this paper, as well as the motivation he has given the writers to keep the passion for research during the pandemic.\n\n\nReferences\n\nAseervatham GSB, Sivasudha T, Jeyadevi R, et al.: Environmental factors and unhealthy lifestyle influence oxidative stress in humans--an overview. Environ Sci Pollut Res Int. 2013; vol. 20, no. 7: pp. 4356–4369. PubMed Abstract \| Publisher Full Text\n\nAubry L, De-Oliveira-Ferreira C, Santé-Lhoutellier V, et al.: Redox Potential and Antioxidant Capacity of Bovine Bone Collagen Peptides towards Stable Free Radicals, and Bovine Meat Lipids and Proteins. Effect of Animal Age, Bone Anatomy and Proteases-A Step Forward towards Collagen-Rich Tissue Valorisation. Molecules (Basel, Switzerland). 2020; 25(22), 5422. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBatubara I, Julita I, Darusman LK, et al.: Flower Bracts of Temulawak (Curcuma xanthorrhiza) for Skin Care: Anti-acne and Whitening Agents. Procedia Chem. Jan. 2015; 14: 216–224. Publisher Full Text\n\nCao M, Li Y, Famurewa AC, et al.: Antidiabetic and Nephroprotective Effects of Polysaccharide Extract from the Seaweed Caulerpa racemosa in High Fructose-Streptozotocin Induced Diabetic Nephropathy. Diabetes Metab Syndr Obes. 2021; 14: 2121–2131. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nEren B, Tuncay Tanrıverdi S, Aydın Köse F, et al.: Antioxidant properties evaluation of topical astaxanthin formulations as anti-aging products. J. Cosmet. Dermatol. Feb. 2019; 18(1): 242–250. PubMed Abstract \| Publisher Full Text\n\nFauzi S: Hidrolisat Kolagen Kulit Ikan Tuna Sirip Kuning (Thunnus albacares) sebagai anti penuaan2018. Accessed: Apr. 10, 2021. Reference Source\n\nGill V, Kumar V, Singh K, et al.: Advanced glycation end products (AGEs) may be a striking link between modern diet and health Biomolecules. MDPI AG; Dec. 01, 2019; vol. 9, no. 12. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHantzidiamantis PJ, Lappin SL: Physiology Glucose. StatPearls Publishing; 2019.\n\nKadar AD, Astawan M, Putri SP, et al.: Metabolomics-Based Study of the Effect of Raw Materials to the End Product of Tempe—An Indonesian Fermented Soybean. Metabolites. Sep. 2020; 10(9): 367. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKim C-S, Park S, Kim J: The role of glycation in the pathogenesis of aging and its prevention through herbal products and physical exercise. J. Exerc. Nutr. Biochem. Sep. 2017; 21(3): 55–61. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLatimer G: Official Methods of Analysis of AOAC INTERNATIONAL, 21st Edition. AOAC Int. 2019; no. 2019, pp. 2019–2022. Accessed: Mar. 28, 2021. Reference Source\n\nLiu D, et al.: Effects of alkaline pretreatments and acid extraction conditions on the acid-soluble collagen from grass carp (Ctenopharyngodon idella) skin. Food Chem. Apr. 2015; 172: 836–843. PubMed Abstract \| Publisher Full Text\n\nMani V, Ming LC: Tempeh and Other Fermented Soybean Products Rich in Isoflavones. Fermented Foods in Health and Disease Prevention. Elsevier Inc; 2017, pp. 453–474. Publisher Full Text\n\nMohanraj VJ, Chen Y: Nanoparticles - A review. Trop. J. Pharm. Res. Jul. 2007; 5(1): 561–573. Publisher Full Text\n\nNurkolis F: Sea grapes powder with addition of tempe rich in collagen - Potential as an anti-aging functional food.xlsx. figshare. Dataset. 2021. Publisher Full Text\n\nPakki E, Tayeb R, Usmar U, et al.: Effect of orally administered combination of Caulerpa racemosa and Eleutherine americana (Aubl) Merr extracts on phagocytic activity of macrophage. Res. Pharm. Sci. Aug. 2020; 15(4): 401–409. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPark S, et al.: L-Ascorbic acid induces apoptosis in acute myeloid leukemia cells via hydrogen peroxide-mediated mechanisms. Int. J. Biochem. Cell Biol. Nov. 2004; 36(11): 2180–2195. PubMed Abstract \| Publisher Full Text\n\nPark S: The effects of high concentrations of vitamin C on cancer cells Nutrients. MDPI AG; Sep. 09, 2013; vol. 5, no. 9. pp. 3496–3505. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPeñalver R, Lorenzo JM, Ros G, et al.: Seaweeds as a Functional Ingredient for a Healthy Diet. Mar Drugs. 2020; 18(6): 301. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPereira D, Valentão P, Pereira J, et al.: Phenolics: From Chemistry to Biology. Molecules. Jun. 2009; 14(6): 2202–2211. Publisher Full Text \| Free Full Text\n\nPillaiyar T, Manickam M, Namasivayam V: Skin whitening agents: Medicinal chemistry perspective of tyrosinase inhibitors J Enzyme Inhib Med Chem. Taylor and Francis Ltd; 2017; vol. 32, no. 1. pp. 403–425. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPotaros T, Raksakulthai N, Runglerdkreangkrai J, et al.: Characteristics of Collagen from Nile Tilapia (Oreochromis niloticus) Skin Isolated by Two Different Methods2009. Accessed: Apr. 10, 2021. Reference Source\n\nPovichit N, Phrutivorapongkul A, Suttajit M, et al.: Antiglycation and antioxidant activities of oxyresveratrol extracted from the heartwood of artocarpus lakoocha roxb. Maejo Int. J. Sci. Technol. 2010; 4(3): 454–461. Accessed: Apr. 07, 2021. Reference Source\n\nQudus A, Aroyehun B, et al.: Bioprospecting Cultivated Tropical Green Algae, Caulerpa racemosa (Forsskal) J. Agardh: A Perspective on Nutritional Properties, Antioxidative Capacity and Anti-Diabetic Potential. Foods. Sep. 2020; 9(9): 1313. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSaeedi M, Eslamifar M, Khezri K: Kojic acid applications in cosmetic and pharmaceutical preparations. Biomed Pharmacother. Elsevier Masson SAS; Feb. 01, 2019; vol. 110, pp. 582–593. PubMed Abstract \| Publisher Full Text\n\nSchumacker PT: Reactive Oxygen Species in Cancer: A Dance with the Devil Cancer Cell. Cell Press; Feb. 09, 2015; vol. 27, no. 2. pp. 156–157. PubMed Abstract \| Publisher Full Text\n\nTanna B, Yadav S, Mishra A: Anti-proliferative and ROS-inhibitory activities reveal the anticancer potential of Caulerpa species. Mol. Biol. Rep. Oct. 2020; 47(10): 7403–7411. PubMed Abstract \| Publisher Full Text\n\nYang P, et al.: Bioactive constituents from the green alga Caulerpa racemosa. Bioorganic Med. Chem. Jan. 2015; 23(1): 38–45. PubMed Abstract \| Publisher Full Text\n\nYap WF, Tay V, Tan SH, et al.: Decoding antioxidant and antibacterial potentials of Malaysian green seaweeds: Caulerpa racemosa and caulerpa lentillifera. Antibiotics. Sep. 2019; 8(3). PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nZhang S, Duan E: Fighting against Skin Aging: The Way from Bench to Bedside Cell Transplant. SAGE Publications Ltd; May 01, 2018; vol. 27, no. 5. pp. 729–738. PubMed Abstract \| Publisher Full Text \| Free Full Text" }	[ { "id": "119984", "date": "31 Jan 2022", "name": "Yasuyuki Irie", "expertise": [ "Reviewer Expertise Pharmacology and Nutritional Science" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors aimed to determine the anti-aging potential effect of sea grapes and tempe collagen powder, by analyzing the activities of anti-glycation, antioxidant and tyrosinase inhibition. In general, the article clearly and accurately presented the data and their interpretations citing the current literature.\nAs a in vitro pilot study, the study design is appropriate and the study has academic merit. Although I am not a specialist for food processing, the methods seem to be appropriate and can be replicated by other researchers. All the source data underlying the results available to ensure full reproducibility. The conclusions were drawn adequately and supported by the results.\nOne of the new findings they presented in this study is the development of a method to optimize the collagen particle size. Therefore, it is necessary to fully explain the significance of optimizing collagen particle size and the previous studies. That is the comment for the inquiry \"Is the work clearly and accurately presented and does it cite the current literature?\"\nIn the last part of the abstract, the authors assert that \"Sea grapes and tempe collagen powder treated with 0.10M NaOH and stirred for 5 hours, as functional foods have anti-aging properties.\" However, as stated in the last part of the Discussion in the text, this study was an \"in vitro pilot study,\" and it cannot be concluded that functional foods have anti-aging properties. Therefore, the wording of the abstract should be changed appropriately. That is the comment for the inquiry \"Are the conclusions drawn adequately supported by the results?\"\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/10-789
https://f1000research.com/articles/11-434/v1	19 Apr 22	{ "type": "Research Article", "title": "Adverse drug reactions to the three doses of the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) mRNA-1273 vaccine in a cohort of cancer patients under active treatment of a tertiary hospital in Madrid, Spain", "authors": [ "Javier David Benitez Fuentes", "Alicia de Luna Aguilar", "Alejandro Francisco Jimenez Ortega", "Paloma Flores Navarro", "Jorge Bartolomé Arcilla", "Elvira Baos Muñoz", "Alberto Delgado-Iribarren García-Campero", "Sara Gil Useros", "Ignacio Martinez Capella", "Laura Llorente Sanz", "Macarena Torrego Ellacuría", "Pedro Pérez Segura", "Alicia de Luna Aguilar", "Alejandro Francisco Jimenez Ortega", "Paloma Flores Navarro", "Jorge Bartolomé Arcilla", "Elvira Baos Muñoz", "Alberto Delgado-Iribarren García-Campero", "Sara Gil Useros", "Ignacio Martinez Capella", "Laura Llorente Sanz", "Macarena Torrego Ellacuría", "Pedro Pérez Segura" ], "abstract": "Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines efficacy and safety have been tested in phase 3 studies in which cancer patients were not included or were underrepresented. Methods: The objective of this study is to evaluate the safety profile of the mRNA-1273 vaccine across cancer patients and its relationship to patients’ demographics. This retrospective cohort study included patients 18-years or older with solid malignancies receiving active treatment in our hospital who had received the three-dose schedule of the mRNA9 1273 vaccine and whose side effects after each dose were recorded. Patient electronic medical records were reviewed retrospectively to collect data between April 19, 2021, and December 31, 2021. Patients with documented previous infection by SARS-Cov-2 were excluded from the study. Results: A total of 93 patients met the inclusion criteria. Local adverse drug reactions (ADRs) were reported more frequently after the first and second dose than after the third (41.9%, 43% and 31.1% of the patients respectively), while systemic ADRs followed the opposite pattern (16.1%, 34.4% and 52.6% of the patients respectively). We found a statistically significant association between sex and systemic ADRs after the third dose. Cochran-Armitage test showed a statistically significant linear trend, p = 0.012, with a higher Eastern Cooperative Oncology Group (ECOG) score associated with a lower proportion of patients suffering from systemic side effects. A logistic regression showed that women had 5.79 times higher odds to exhibit systemic ADRs after the third dose (p=0.01) compared to males. Increasing age was associated with a decreased likelihood of exhibiting ADRs (p=0.016). Conclusion: The mRNA-1273 vaccine shows a tolerable safety profile. The likelihood of ADRs appears to be associated with gender and age. Its association with ECOG scores is less evident. Further studies are needed to elucidate this data in cancer patients.", "keywords": [ "COVID-19", "mRNA-1273 Vaccine", "SARS-CoV-2", "Safety", "Cancer", "Oncology" ], "content": "Introduction\n\nIn December 2019, cases of pneumonia of unknown aetiology related to a seafood market were found in Wuhan, China. A previously unknown betacoronavirus was isolated from human epithelial cells, it was named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the disease it causes coronavirus disease 2019 (COVID-19). The virus spread exponentially through Hubei province in China, affecting the whole country afterwards and then the rest of the world.1 In January 2020 the World Health Organization (WHO) declared an international emergency after the expansion of the virus to other countries, infecting 10,000 people and provoking 200 deaths.2 On 11th March, following a further increase in the number of cases outside China and the number of countries affected, the WHO declared COVID-19 a pandemic.3 COVID-19 has shown a wide variety of symptoms and a broad spectrum of severity.4 SARS-CoV-2 infection has been associated with worse clinical outcomes in patients with cancer, with an estimated mortality of 30% in hospitalized cancer patients and 60% in cancer patients admitted to the Intensive Care Unit.5–7 Patient care in this population was disrupted during the pandemic due to the emergency situation. In many cases surgeries and cancer medical treatments were delayed to prevent cancer patients from getting the infection.8 Due to the emergency generated by the pandemic several research projects involving vaccines against SARS-CoV-2 were started. In December 2020 the Food and Drug Administration (FDA) issued the first Emergency Use Authorization for the BNT162b2 vaccine after it was found to be safe and efficient in preventing COVID-19 in the general population, followed shortly by the mRNA-1273 vaccine.9 Patients receiving systemic immunosuppressants or immune modifying drugs within six months of screening were excluded from the clinical trials,10,11 thus leaving cancer patients behind in the research for a vaccine against SARS-CoV-2. However, despite the lack of evidence in this population, cancer patients were prioritized for the administration of the SARS-CoV-2 vaccine.12 In Spain cancer patients started vaccination in April 2021.\n\nThere are few studies showing the safety of mRNA-1273 vaccine in solid cancer patients.\n\nIn this study we describe and analyse the safety profile of the mRNA-1273 vaccine in a cohort of 93 cancer patients in cancer treatment in a tertiary hospital in Madrid, Spain.\n\n\nMethods\n\nThe Comité de Ética del Medicamento e Investigación Clínica (Ethics Committee) of Hospital Clínico San Carlos approved the project with the code: 22/033-E. The Comité de Ética del Medicamento e Investigación Clínica (Ethics Committee) of Hospital Clínico San Carlos deemed the necessary requirements for appropriateness of the protocol in relation to the objectives of the study were met, the informed consent waiver was considered adequate, the procedure foreseen for the handling of personal data was adequate. The ethical precepts formulated in the Declaration of Helsinki of the World Medical Association for medical research on human beings and its subsequent revisions are complied with, as well as those required by the applicable legal regulations according to the characteristics of the study.\n\nThis observational retrospective study included patients with solid tumours receiving anticancer treatment at the outpatient facility of the Hospital Clínico San Carlos Medical Oncology service in Madrid, Spain. We included all the patients vaccinated with the complete three-dose schedule mRNA-1273 vaccine that were on active anticancer therapy and had complete available information about the date of each vaccination dose and side effects for each of the three doses in electronic medical records.\n\nWe selected the patients vaccinated with the complete three-dose schedule mRNA-1273 vaccine from the Preventive Medicine and Public Health Department database. This database was linked with the Medical Oncology Department patient database selecting all oncology patients under active treatment who were in the previous database. From these subjects we selected the ones that had information about the appearance or absence of adverse drug reactions (ADRs) after each dose of the vaccine available in electronic medical records. Patients who had a documented SARS-CoV-2 infection or a positive SARS-CoV-2 serology test collected during routine clinical practice in the 7 days prior to the first mRNA-1273 vaccine dose were excluded.\n\nAdditional clinical information was abstracted from the electronic medical records, including age, sex, performance status (using Eastern Cooperative Oncology Group (ECOG) performance status score),13 cancer type, cancer stage and cancer therapy. Patient electronic medical records were reviewed retrospectively to collect the information regarding the previous parameters between the dates April 19, 2021, and December 31, 2021. Authors belonging to Medical Oncology Department had complete access to all electronic medical records available from the patients.\n\nECOG performance status score describes the level of functioning in terms of the ability to selfcare, daily activity, and physical ability of the patients. ECOG 0 patients are fully active. ECOG 1 patients are not able to perform physically demanding activity but are ambulant and able to perform occupations of light nature. ECOG 2 patients are ambulant, up for more than 50% of waking hours, and capable of all personal care, but are unable to perform any work activities. ECOG 3 patients can perform only limited self-care and are bedridden or confined to a chair for more than half of waking hours. ECOG 4 patients are completely incapacitated, unable to perform any self-care and totally confined to a bed or chair. ECOG 5 patients are dead.13\n\nCancer type was divided in seven groups: thoracic malignancies, breast cancer, head and neck cancer, gastrointestinal malignancies, gynaecological malignancies, and others (malignancies that did not belong to any of the previous groups).\n\nCancer stage was divided in metastatic, patients with malignant lesions in locations organs distant from where the primary tumour is, and the rest, defined as localized.\n\nCancer therapy was divided in chemotherapy, targeted therapy, immunotherapy and combined therapy (any combination of the previous treatments).\n\nThe primary end point of this study was ADRs after each dose of mRNA-1273 vaccine. ADRs were categorized as local adverse reactions which included pain, swelling, rash and itchiness at the site of infection and systemic adverse reactions. Systemic adverse reactions reported by patients were fever (defined as body temperature equal or above 38°C), headache, myalgia, malaise, nausea, arthralgia, chills, adenopathies, urticaria, asthenia and cough.\n\nData was analysed with IBM SPSS v.25. For descriptive purposes, categorical variables were represented by absolute and relative frequencies and quantitative variables were represented by central and dispersion measures. In order to ascertain the relationship between nominal independent variables (sex, heavily treated status and past story of systemic adverse drug reactions) we performed a chi-squared test (all expected cell frequencies were greater than five) followed by a Cramér’s V test. For ordinal variables (ECOG performance status score)14 we performed a Cochran-Armitage test of trend. Significance was tested with an alpha value of 0,05. No multiplicity correction was applied. To test the value as predictors of true baseline variables (age, sex and ECOG performance status) we fitted a binomial logistic regression to ascertain the effects of age, sex and ECOG score on the likelihood that participants have systemic adverse events after the third dose (hereinabove described). We used a Box-Tidwell procedure to evaluate the linear relationship between the logit of the outcome and continuous variables. Following a Bonferroni correction, statistical significance was accepted hen p < 0.0071. Age was included as a continuous variable, sex as a dichotomous variable, being male considered as reference, and ECOG scores were included as categorical variables, with a score of 0 considered the reference.\n\n\nResults\n\nData was retrieved from electronic medical records on the 31st of December. In total 93 patients were eligible for the current analysis.18 Patient demographic, cancer, and therapy characteristics included are summarized in Table 1.\n\nThe number of ADRs categorized as local and systemic after the first, the second and the third vaccine dose are shown in Figure 1. Local ADRs included pain, swelling, rash and itchiness at the site of infection. We can observe that systemic ADRs have a clearly increasing trend while local ADRs have a discrete downward trend.\n\nAfter the first, second and third dose 41.9%, 43% and 31.1% of the patients respectively reported a local ADR, while systemic ADRs were increasingly reported after each dose (16.1%, 34.4% and 52.6% of the patients respectively).\n\nThe ADRs occurring after the first, the second and the third vaccine dose are described in Figures 2–4 respectively. The most common ADR after the first dose was local reaction with a marked difference compared with systemic ADRs. After the second dose the most frequent ADR was still local reaction, but systemic were becoming increasingly important. After the third dose we can observe that local ADR is less common and takes second place after fever and that the rest of systemic effects are increasingly frequent.\n\nNo severe ADRs requiring hospitalization occurred in this population. No new SARS-CoV-2 infections occurred in this population during the period studied.\n\nThere was a statistically significant association between sex and systemic adverse reactions after the third dose, χ2(1) = 14.620, p ≤ 0.01. The association was moderate (Cramer's V = 0.390). We didn’t find a statistically significant association between heavily treated status and systemic adverse reactions after the third dose, χ2(1) = 0.063, p = 0.802. The association was small (Cramér's V = 0.05).\n\nRegarding adverse reactions after previous vaccine doses, there was not a statistically significant association between systemic adverse reactions after the first dose and after the third one, χ2(1) = 1.897, p = 0.168, and the association between the variables small, Cramér's V = 0.172. On the other hand, we found a statistically significant association between systemic adverse reactions after the second dose and systemic adverse reactions after the third dose, χ2(1) = 12.886, p < 0.001. The association was moderate, Cramér's V = 0.372.\n\nThe Cochran-Armitage test of trend showed a statistically significant linear trend, p = 0.012, with a higher ECOG score associated with a lower proportion of patients suffering from systemic side effects. The scores tested were ECOG 0 (n = 56), ECOG 1 (n = 30), ECOG 2 (n = 7), and the proportion of patients suffering a side effect was 0.643, 0.4 and 0.286, respectively.\n\nAge was found to be linearly related to the logit of the dependent variable. The area under the ROC curve was 0.783 (95% CI, 0.688 to 0.878) (Figure 5), which is at the upper level of an acceptable level of discrimination according to.16 The logistic regression model was statistically significant, χ2(4) = 25.641, p < .0005. The model explained 32.2% (Nagelkerke R2) of the variance in systemic adverse events after the third dose and correctly classified 72.0% of cases. Sensitivity was 82%, specificity was 60.5%, positive predictive value was 70.6% and negative predictive value was 74.2%.\n\nOnly two variables were statistically significant: age and sex (as shown in Table 2). Women had 5.79 times higher odds to exhibit systemic adverse events after the third dose compared to males. Increasing age was associated with a decreased likelihood of exhibiting adverse events. ECOG score was not statistically significant but a trend towards a diminished likelihood of systemic adverse reactions with higher ECOG score compared to ECOG 0.\n\nAbbreviations: B logarithmic regression slope, SE standard error, degrees of freedom, OR odds ratio, CI confidence interval.\n\nRegarding the variable Sex, male was considered the reference. Regarding the variable ECOG, ECOG 0 was considered the reference.\n\n\nDiscussion\n\nAmong completed and ongoing trials of SARS-CoV-2 vaccines there is scarce information regarding safety and efficacy of these vaccines in solid cancer patients. Patients receiving systemic immunosuppressants or immune modifying drugs within six months of screening were excluded from the major vaccine trials.9,11\n\nIn the phase 3 clinical trial of the mRNA-1273 SARS-CoV-2 vaccine, the mRNA-1273 group showed 84.2% of local ADRs after the first dose and 88.6% after the second dose. Systemic ADRs in the mRNA-1273 group occurred in 54.9% of patients after the first dose and 79.4% of patients after the second. Fever, headache, and myalgia were the most common systemic ADRs.11 In our population we observed both less local and systemic ADRs than in the healthy population from this trial.\n\nOnly a few studies report on the safety profile of the COVID-19 vaccines in cancer patients, fewer report data specifically about the mRNA-1273 vaccine safety profile in this population, and none of them about the third dose.\n\nIn a study from the Massachusetts General Hospital Cancer Center, in patients vaccinated with mRNA-1273, BNT162b2 and Ad26.COV2.S, the frequency of local or systemic ADRs was highest in the mRNA-1273 recipients; 233 of 288 (81%) had an ADR. Systemic ADRs were more common after the second dose of the vaccine. The most common systemic ADR was fatigue.15\n\nIn another study from the Netherlands four cohorts were studied, one made of individuals without cancer (cohort A), cancer patients treated with immunotherapy (cohort B), cancer patients treated with any type or combination of cytotoxic chemotherapy (cohort C) and cancer patients treated with chemoimmunotherapy (cohort D). No major adverse events of grade 3 or worse happened in any participant in cohort A. In the rest of the cohorts, serious adverse events occurred in 2% of 137 patients in cohort B, in 2% of 244 patients in cohort C, and in 1% of 163 patients in cohort D. Only four events (two of fever and one each of diarrhoea and febrile neutropenia) were potentially related to vaccination. Systemic ADRs were more common after the second dose with myalgia, headache, chills, and fatigue being the most common. No vaccine related deaths were reported.16\n\nIn another study from Italy in patients with solid malignancies undergoing radiotherapy treatment, 5% of patients after the first dose and 26% after the second dose reported grade 2 ADRs. After the first dose 0% reported grade 4 ADRs and only 4% reported them after the second dose. In this study we can also observe the increasing trend of systemic ADRs with the second dose.17\n\nIn all these studies we observe an increasing trend of systemic ADRs. Our study is, to our knowledge, the only one evaluating the safety profile of each of the three doses of mRNA-1273 vaccine in cancer patients. Our study confirms the increasing frequency of systemic ADRs after each dose. In a scenario where the start of the administration of the fourth dose in cancer patients is near, we expect that this trend will be maintained in the fourth dose. We have also observed an association of ADRs with gender and age, which could help us predict subgroups at greater risk of ADRs in the event of more doses of the vaccine.\n\nThis study has some important limitations. (1) The retrospective nature of the study makes it more prone to error, making measurements less precise. (2) The small population in this study and its characteristics do not represent the general cancer patient population and makes it difficult to generalize the results, thus external validity can be compromised. (3) The absence of a healthy control group makes it difficult to reach conclusions.\n\n\nConclusion\n\nAlthough based on a small number of patients and limited by the observational nature of the study, the mRNA-1273 vaccine shows a tolerable safety profile in this cohort of cancer patients similar to the non-oncologic population. No severe ADRs requiring hospitalization occurred in this population. The likelihood of ADRs appears to be associated with gender and age. The likelihood of systemic ADRs after the third dose appears to be associated with systemic ADRs after the second dose. There appears to be a trend towards more systemic and less local ADRs with every consecutive dose of the vaccine. Its association with ECOG performance score is less evident. To date this is the first study evaluating the safety profile of the three doses of mRNA-1273 vaccine.\n\n\nData availability\n\nDryad: Adverse drug reactions to the three doses of the SARS-COV-2 mRNA-1273 vaccine in a cohort of cancer patients of a tertiary hospital. https://doi.org/10.5061/dryad.cnp5hqc6d.18\n\nThis project contains the following underlying data:\n\n• ADRs_mRNA-1273_database_excel.xlsx (database with all the individual anonymized data regarding the parameters analysed in this article)\n\n• README.docx (document with the explanation of the data used in the database)t\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "References\n\nZhu N, et al.: A Novel Coronavirus from Patients with Pneumonia in China, 2019. N. Engl. J. Med. 2020; 382(8): 727–733. PubMed Abstract \| Publisher Full Text\n\nMahase E: China coronavirus: WHO declares international emergency as death toll exceeds 200. BMJ (Clinical research ed.). Jan. 2020; 368(m408): 31. PubMed Abstract \| Publisher Full Text\n\nCucinotta D, Vanelli M: WHO Declares COVID-19 a Pandemic. Acta Bio-medica: Atenei Parmensis. 19 Mar. 2020; 91(1): 157–160. PubMed Abstract \| Publisher Full Text\n\nGuan W-J, et al.: Clinical Characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med. 2020; 382(18): 1708–1720. PubMed Abstract \| Publisher Full Text\n\nDesai A, et al.: Mortality in hospitalized patients with cancer and coronavirus disease 2019: A systematic review and meta-analysis of cohort studies. Cancer. 2021; 127(9): 1459–1468. PubMed Abstract \| Publisher Full Text\n\nNadkarni AR, et al.: Mortality in Cancer Patients With COVID-19 Who Are Admitted to an ICU or Who Have Severe COVID-19: A Systematic Review and Meta-Analysis. JCO Glob. Oncol. 2021; 7: 1286–1305. PubMed Abstract \| Publisher Full Text\n\nLee LY, et al.: COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study. Lancet (London, England). 2020; 395(10241): 1919–1926. PubMed Abstract \| Publisher Full Text\n\nSchrag D, et al.: Oncology Practice During the COVID-19 Pandemic. JAMA. 2020; 323(20): 2005–2006. Publisher Full Text\n\nPolack FP, et al.: Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine. N. Engl. J. Med. 2020; 383(27): 2603–2615. Publisher Full Text\n\nModerna COVID-19 Vaccine Emergency Use Authorization Amendment Review Memorandum. US Food and Drug Administration. 18 October 2021. Accessed 27 February 2022. Reference Source\n\nBaden LR, et al.: Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine. N. Engl. J. Med. 2021; 384(5): 403–416. PubMed Abstract \| Publisher Full Text\n\nRibas A, et al.: Priority COVID-19 Vaccination for Patients with Cancer while Vaccine Supply Is Limited. Cancer Discov. 2021; 11(2): 233–236. PubMed Abstract \| Publisher Full Text\n\nOken MM, et al.: Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am. J. Clin. Oncol. 1982; 5(6): 649–655. PubMed Abstract \| Publisher Full Text\n\nHosmer DW, et al.: Applied Logistic Regression. Wiley; 2013.\n\nNaranbhai V, et al.: Immunogenicity and Reactogenicity of SARS-CoV-2 Vaccines in Patients With Cancer: The CANVAX Cohort Study. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2022; 40(1): 12–23. Publisher Full Text\n\nOosting SF, et al.: mRNA-1273 COVID-19 vaccination in patients receiving chemotherapy, immunotherapy, or chemoimmunotherapy for solid tumours: a prospective, multicentre, non-inferiority trial. Lancet Oncol. 2021; 22(12): 1681–1691. PubMed Abstract \| Publisher Full Text\n\nScoccianti S, et al.: Acute tolerance of Moderna mRNA-1273 vaccine against COVID-19 in patients with cancer treated with radiotherapy. Lancet Oncol. 2021; 22(9): 1212–1214. PubMed Abstract \| Publisher Full Text\n\nFuentes B, David J, et al.: Adverse drug reactions to the three doses of the SARS-COV-2 mRNA-1273 vaccine in a cohort of cancer patients of a tertiary hospital, Dryad, [Dataset].2022. Publisher Full Text" }	[ { "id": "135138", "date": "03 May 2022", "name": "Manushak Avagyan", "expertise": [ "Reviewer Expertise Childhood cancer", "cancer epidemiology", "childhood cancer registration", "cancer registries." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript presents a detailed assessment of the mRNA-1273 vaccine's safety profile in 93 cancer patients and its link to their demographics. In view of the paucity of knowledge on data about the safety and efficacy of the vaccines among cancer patients, this is a potentially valuable contribution to knowledge. However, the manuscript needs adjustments to be ready for indexing in F1000Research, as covered in the following specific comments.\nOverall, the work might benefit from greater literature support; consider updating with the latest publications concerning vaccination safety in cancer patients.\nTitle:\nThe title is lengthy yet self-explanatory.\n\nAbstract:\nThe abstract and overarching objectives are clear. The methodology is not thorough and the analysis is not clear from the appropriate section. The main outcomes are clear, and the conclusions are relevant to the aim.\n\nKeywords:\nPlease consider including a keyword that addresses adverse reactions in addition to safety.\n\nIntroduction:\nThe broad description section at the beginning could be improved, particularly the first six sentences, which should be shortened and summarized into 2-3 sentences and present more about the characteristics of oncology patients, as well as a presentation about other vaccine-related information among cancer patients.\n\nThe use of a hyperlink at the end of the introduction does not seem proper by highlighting one sentence.\n\nThere is a need for references for the pre-last phrase concerning a few studies indicating vaccination safety among cancer patients.\n\nConsider removing the patient count from the final line of the introduction, while describing the aim of the study.\n\nMethods:\nMove the ethical considerations to the end of the methods section.\n\nPlease specify the time period under investigation. The methodology section (it's clearly specified in the abstract) does not specify which dates were verified for recruitment since there are dates in the middle of the paragraph discussing data collecting for additional variables.\n\nIn the methods section, please define the term \"heavily treated.\"\n\nIf you find it feasible, an extra step for the study would be to use a logistic regression model and evaluate the model's fit to the data.\n\nResults:\nThe reported findings are based on the analysis mentioned in the methodology section.\n\nHaving subheadings in the results section can improve.\n\nConsider mentioning the full date in the first sentence of the results section.\n\nPage 7: a. The second paragraph, which discusses the relationship between various doses and the subsequent systemic response, might be articulated clearly in the first opening phrase. b. The presentation of the findings in the third paragraph might be improved. c. In the fourth paragraph, the first two phrases need clarification.\n\nDiscussion:\nIn the discussion section, only three new references are provided, and further comparisons and references are needed; this might be updated with new research released in 2022.\n\nTables:\nIn Table 1, the word \"SD\" appears twice in the second row.\n\nTable 2 might be improved by deleting unnecessary information generated during analysis and presenting a clearer and more focused table, with the main values being OR, P, and CI, and the rest could be discarded.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8546", "date": "26 Jul 2022", "name": "Javier David Benitez Fuentes", "role": "Author Response", "response": "In the 2nd version, I am submitting the following has been addressed: Abstract: The abstract and overarching objectives are clear. The methodology is not thorough and the analysis is not clear from the appropriate section. The main outcomes are clear, and the conclusions are relevant to the aim. Response: Methodology and results description has been improved. Keywords: Please consider including a keyword that addresses adverse reactions in addition to safety. Response: Done Introduction: The broad description section at the beginning could be improved, particularly the first six sentences, which should be shortened and summarized into 2-3 sentences and present more about the characteristics of oncology patients, as well as a presentation about other vaccine-related information among cancer patients. Response: Done The use of a hyperlink at the end of the introduction does not seem proper by highlighting one sentence. Response: Editors from the journal suggested this format. There is a need for references for the pre-last phrase concerning a few studies indicating vaccination safety among cancer patients. Response: Done Consider removing the patient count from the final line of the introduction, while describing the aim of the study. Response: Done Methods: Move the ethical considerations to the end of the methods section. Response: Done Please specify the time period under investigation. The methodology section (it's clearly specified in the abstract) does not specify which dates were verified for recruitment since there are dates in the middle of the paragraph discussing data collecting for additional variables. Response: Done In the methods section, please define the term \"heavily treated.\" Response: Done If you find it feasible, an extra step for the study would be to use a logistic regression model and evaluate the model's fit to the data. Response: Clarified by the biostatistician Results: The reported findings are based on the analysis mentioned in the methodology section. Having subheadings in the results section can improve. Response: Done Consider mentioning the full date in the first sentence of the results section. Response: Done Page 7: a. The second paragraph, which discusses the relationship between various doses and the subsequent systemic response, might be articulated clearly in the first opening phrase. Response: Done b. The presentation of the findings in the third paragraph might be improved. Response: Done c. In the fourth paragraph, the first two phrases need clarification. Response: Done Discussion: In the discussion section, only three new references are provided, and further comparisons and references are needed; this might be updated with new research released in 2022. Response: Done Tables: In Table 1, the word \"SD\" appears twice in the second row. Response: Erased Table 2 might be improved by deleting unnecessary information generated during analysis and presenting a clearer and more focused table, with the main values being OR, P, and CI, and the rest could be discarded. Response: Done" } ] } ]	1	https://f1000research.com/articles/11-434
https://f1000research.com/articles/11-496/v1	05 May 22	{ "type": "Study Protocol", "title": "Acute Kidney Injury associated with \"Triple whammy\" combination: a protocol for a systematic review.", "authors": [ "Dulce Maria Calvo Barbado", "Luis Carlos Saiz Fernández", "Leire Leache Alegría", "Maria Concepción Celaya Lecea", "Marta Gutiérrez-Valencia.", "Luis Carlos Saiz Fernández", "Leire Leache Alegría", "Maria Concepción Celaya Lecea", "Marta Gutiérrez-Valencia." ], "abstract": "Background: “Triple whammy” (TW) refers to the simultaneous use of diuretics, renin-angiotensin-aldosterone system inhibitors and nonsteroidal anti-inflammatory drugs (NSAIDs). To date, the risk of developing acute kidney injury (AKI) associated to this combination has not been deeply investigated. The objectives are to analyze the incidence of AKI associated to the exposure to “triple whammy” including all NSAIDs versus non-exposure to this combination. Secondarily, the risk of hospitalization, severe adverse events, requirement of renal replacement therapy and mortality will be assessed. Also, the incidence of AKI associated to the exposure to “triple whammy” versus non-exposure will be analyzed, including only metamizole as NSAID.\n\nMethods: A systematic literature search of intervention studies and analytical observational studies will be conducted in the Cochrane Library, Medline and EMBASE, among others. AKI 12 months after the last prescription of the triple combination will be the main outcome. Relative frequencies, risk of bias and certainty of evidence will be analyzed. Additionally, sensitivity and subgroup analyses will be performed.\n\nResults: Once this systematic review has been completed, the results are expected to provide an estimate of the risk associated with this triple combination and the renal variables, in addition to new guidance on the renal treatment of patients potentially receiving triple therapy. Conclusions: This is intended to be the first systematic review of observational studies to analyse TW combination and AKI's risk based on well-validated epidemiological databases exploring drug safety issues.", "keywords": [ "Acute kidney injury", "triple whammy", "diuretics", "Angiotensin-Converting Enzyme Inhibitors", "Angiotensin II Type 1 Receptor Blockers", "Non-Steroidal Anti-Inflammatory Agents", "metamizole", "dipyrone" ], "content": "List of abbreviations\n\nAECI: Angiotensin-Converting Enzyme Inhibitors\n\nAKI: Acute Kidney Injury\n\nARB: Angiotensin II Type 1 Receptor Blockers,\n\nGRADE: Grading of Recommendations, Assessment, Development and Evaluation\n\nKDIGO: Kidney Disease Improving Global Outcomes\n\nNSAID: Non-steroidal anti-inflammatory drugs\n\nROBINS-I: Risk Of Bias In Non-randomized Studies of Interventions\n\nWHO: World Health Organization\n\n\nBackground\n\nThe term “triple whammy” corresponds to the simultaneous use of diuretics, antihypertensive inhibitors of the renin system angiotensin (Angiotensin-Converting Enzyme Inhibitors (ACEi) or Angiotensin II Type 1 Receptor Blockers (ARB) and non-steroidal anti-inflammatory drugs (NSAIDs).1 These groups of drugs affect kidney function through different mechanisms such as producing hypovolemia, and reduction of glomerular filtration rate and glomerular perfusion.2\n\nThis combination of drugs has been correlated with an increased incidence of Acute Kidney Injury (AKI).2 In this sense, Loboz et al. found a significant association between the number of drugs components of the triple therapy and the deterioration of renal function, established as an increase of serum creatinine or reduction of creatinine clearance.3 Specifically, the triple association has been associated with an increase of about 30% in the risk of AKI.4,5 Furthermore, in the case-control study carried out by Lapi et al. it was concluded that the risk of developing AKI was higher during the first 30 days of treatment with the triple therapy.6\n\nAKI has important social and economic consequences. There is a wide variation in prevalence (1-25%) and mortality (15-60%) estimates for AKI due to the existence of multiple pathology definitions.7 In economic terms, the cost associated with AKI is around 5% of the hospital budget and 1% of total health expenditure, due to an increase in hospital stay, intensified monitoring and dialysis requirements.8,9\n\nIn Spain, there has been an exponential increase in the number of hospitalizations with diagnosis of AKI over time.10 The number of hospitalizations for AKI in 1997 was 15,885, reaching 207,287 hospitalizations in 2015.10 Iavecchia et al. found that 54.1% of the hospitalizations were related to drugs that were diuretics and ones that acted on the renin-angiotensin system.11 García Camín et al. showed that the incidence of out-of-hospital AKI due to drugs considered in the “triple whammy” association was 3.4 cases per 1,000 consumers/year, with a mortality of 11.3% during hospital admission and 38.7% at 12 months. In addition, an average avoidable cost of 214,604 euros per 100,000 inhabitants/year was estimated.12\n\nScientific evidence of the “triple whammy” combination effect from studies is scarce. The initial review of the literature provides three nested case control studies conducted in the United Kingdom,4 Canada,6 and the United States.13 Descriptive, cross-sectional, and retrospective studies in Australia3,14 and Japan.5 Only three investigations carried out in Spain have been identified,12,15,16 of which only two analyzed the incidence of AKI, mortality and costs associated with “triple whammy”. The third study analyzed the effect of pharmaceutical interventions on the frequency of prescription of the combination therapy.\n\nTwo Pharmacovigilance studies conducted in France have also provided information on this association and the risk of AKI.17,18\n\nIn contrast with other countries, metamizole is used largely for pain management in Spain. Safety data from the WHO international database VigiAccess contains 23,582 reports of adverse reactions related to metamizole. Of these, 534 (2.3 %) affect the renal and urinary system, with 197 (37.6 %) corresponding to acute renal failure and 112 to related terms (21%), 57% reports related to metamizole come from Europe.17 The European database of suspected adverse reactions (Eudravigilance) contained 9,906 reports with metamizole up to June 2020, of which 25.2% come from Spain. In total, 5.3% of the reports corresponded to reactions affecting the renal and urinary system, of which 261 (49.4%) were recorded as acute renal failure, and 26 (4.9%) reported severe reactions.17\n\nDespite these reported data, there is no strong evidence showing that metamizole relates to a lower risk of AKI compared to other types of NSAIDs. To date, studies examining the effect of metamizole in combination with diuretics and ACE inhibitors/ARBs on the risk of developing AKI have also not been conducted. Therefore, it is particularly relevant to determine the actual impact of metamizole on kidney function.\n\nReview question: Do patients exposed to the “triple whammy” combination with/without metamizole have a higher risk of AKI compared those not exposed to the “triple whammy” combination?\n\nThe main objective is to analyze the incidence of AKI associated to the exposure versus non-exposure of the “triple whammy” combination.\n\n\nMethods\n\nThis protocol has been registered with PROSPERO international prospective register of systematic reviews (registration number CRD42020213680) and has been reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) 2015 statement (See Reporting Guidelines).18\n\nThe methodology of this review is according to the Cochrane Handbook for Systematic Review of Interventions.19\n\n\nEligibility criteria\n\nClinical trials and analytical observational studies assessing the risk of AKI or morbidity-mortality associated with the “triple whammy” combination will be included. Priority will be given to randomized controlled trials, but non-randomized controlled trials, controlled before-after studies, historically controlled studies, cohort studies and case-control studies will also be considered for inclusion. In order to be included, studies must have analyzed the primary outcome or at least one secondary outcome. There will be no restrictions regarding the publication date, setting and languages. Animal studies will be excluded.\n\nPatients ≥ 18 years will be included. Patients with any type of cancer, except from basal cell carcinoma, will be excluded.\n\nExposure to the “triple whammy” combination will be analyzed. The combination refers to the simultaneous use of at least one diuretic of any class, plus ACEI or ARB or aliskiren plus NSAIDs.\n\nNo exposure to the “triple whammy” combination.\n\nAcute Kidney Injury (AKI) will be the main outcome. Secondary outcome variables will be the following: hospitalization due to AKI, serious adverse events, mortality within 30 days after AKI, mortality from any cause and requirement of kidney replacement therapy. Events (primary and secondary outcomes) within 12 months after the last prescription of the triple combination will be considered, except for mortality within 30 days after AKI.\n\nThe definitions of AKI used in the different studies will be accepted to determine the occurrence of AKI. In the case of studies that do not provide a certain AKI definition, the definition established by Kidney Disease Improving Global Outcomes (KDIGO) will be adopted.\n\nAccording to the criteria established by KDIGO, AKI is defined as an increase in serum creatinine of 26 micromol/liter (0.3 mg/dl) or more within 48 hours, or a 50% or greater increase in serum creatinine known or suspected to have occurred in the last 7 days or a drop in urine output to less than 0.5 ml/kg/hour for more than 6 hours in adults, plus 25% of the estimated glomerular filtrate value in the last 7 days.20–23\n\nA systematic search of the literature will be conducted through the following sources: Cochrane Library, Medline, Epistemonikos, EMBASE, Scopus, Web of Science, CINAHL, Latin American and Caribbean Health Sciences Literature (LILACS) Bireme and Scientific Electronic Library Online (Scielo).\n\nPrimary studies will be identified through the ClinicalTrials.gov database, the Spanish Clinical Trials Registry (REEC), the EU Clinical Trials Registry, the EU post-authorization study registry (ENCePP), and the International Clinical Trials Registry Platform (ICTRP) of the World Health Organization. A search in PROSPERO will be carried out to identify completed and/or ongoing reviews. In addition to the electronic database search, citation tracking (checking reference lists of all included and excluded studies) will be performed to search for other relevant articles and to identify additional trials and studies. References from reviews, clinical practice guidelines and position papers from health care institutions or organizations will be accessed.\n\nThe strategy will be built with the following keywords and boolean operators for the initial question:\n\n((“Angiotensin-Converting Enzyme Inhibitors” [Mesh]) OR (Angiotensin-Converting Enzyme Inhibitors [Pharmacological Action]) OR (Angiotensin Receptor Antagonists [Mesh]) OR (Angiotensin II Type 1 Receptor Blockers [Mesh])) AND ((Diuretics [Mesh]) OR (Diuretics [Pharmacological Action])) AND ((Anti-Inflammatory Agents, Non-Steroidal [Pharmacological Action]) OR (Anti-Inflammatory Agents, Non-Steroidal [Mesh]) OR (Dipyrone [Mesh]) OR (Metamizole magnesium [Supplementary Concept])) OR (“triple whammy”)) AND (“Acute Kidney Injury” [Mesh]).\n\nTwo independent reviewers will carry out the selection of papers based on the title, keywords and abstract, and eligibility criteria. The full text of each paper considered for inclusion will be obtained. If the information relevant to the inclusion criteria is not available in the abstract or if the title is relevant but the abstract is not available, the full text of the report will be obtained. Discrepancies will be resolved by discussion or by a third author if necessary. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses' statement) flowchart of included and excluded articles will be prepared.\n\nTwo reviewers will independently extract the data from the included trials with a previously prepared data extraction form. Differences between authors will be resolved by consensus and the participation of a third author, if necessary. The data extraction form will include descriptive information of the included studies (general data, eligibility, inclusion and exclusion criteria, methodology used, and assessment of risk of bias) and information on primary and secondary outcomes. Microsoft Access and Microsoft Excel will be used to organize and analyze the data of individual participants. If it is deemed necessary to complete the information, the authors will be contacted for additional data. Whenever possible, analyses will be carried out using the individual data from the included studies.\n\nAcute Kidney Injury (AKI) occurring 12 months after the last prescription of the triple combination, or “triple whammy” will be the main outcome.\n\n\n\n1. Hospitalization for AKI\n\n2. Serious adverse events: Any unfortunate medical event that may occur during treatment with a drug but does not necessarily have a causal relationship with that treatment. In this case, the coincidence in time occurs without any suspicion of a causal relationship. The serious event of those that cause death, threaten the life of the patient, produce permanent or substantial disability, require hospitalization or prolong the time of hospitalization, produce congenital anomalies or malignant processes.\n\n3. Mortality within 30 days after Acute Kidney Injury: only deaths occurring within 30 days after the AKI that must have occurred in the year following the exposure to the triple whammy will be considered.\n\n4. Mortality from any cause.\n\n5. Kidney replacement.\n\nRisk of bias will be evaluated for each study using for randomized clinical trials, the Cochrane Risk of Bias 2 (RoB 2) tool, according to the method described in the Cochrane Handbook for Systematic Reviews of Interventions version 6.0,19 the ROBINS-I tool24 and Newcastle-Otawa Scale.25 The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) methodology26 will be applied to evaluate the quality of the evidence for the main and secondary outcomes. A funnel plot will be carried out in the case of having 10 or more studies for each of the variables, in order to evaluate the possible existence of publication bias.\n\nData synthesis and analysis will be performed using (RevMan, RRID:SCR_003581) version #5.4. Exposure to the “triple whammy” combination (regardless of whether the NSAID is metamizole or another drug) will be considered for the main analysis. The secondary analysis will consider exposure to the triple whammy combination in which the NSAID is metamizole.\n\nRandomized and non-randomized clinical trials will be analyzed separately. In addition, non-randomized studies will be analyzed separately according to the specific study design.\n\nRelative frequencies will be used to compare the incidence or the frequency of the event among the patients exposed and not exposed to the triple combination. The risk ratio (RR) or odds ratio (OR), with their corresponding 95% confidence interval, will be used. The Chi2 and the I2 statistics will be used to describe the heterogeneity. Indication of substantial heterogeneity will be I2 >60%.\n\nWhen substantial heterogeneity (I2 value greater than 60%) is found, the pooled effect estimator will not be provided; in this case, a narrative description of the results will be provided. With respect to observational studies, if both unadjusted and adjusted effect estimates are reported, the adjusted effects will be preferred.\n\nQualitative results should be presented in a narrative form.\n\nSubgroup analyses will be carried out for the following populations: patients over 75 years; patients with previous chronic renal failure; patients with cardiovascular disease.\n\nSensitivity analyses will be performed excluding studies with high risk of bias and including only those studies that used KDIGO's definition of AKI.\n\n\nDiscussion\n\nBeyond the individual well-known renal action of diuretics, AECI, ARB and NSAID, the effect of the combination and its potential association with the risk of AKI still needs to be explored. On the other hand, there is not much evidence on the use of metamizole and its risk. This systematic review will provide updated evidence relative to the risk of AKI and “triple whammy”. As a result, the project is expected to provide a new strategy to decrease the risk of renal injury in patients potentially using this triple combination.\n\nThis is a protocol for a systematic review and any amendment will be reported by updating the submitted protocol at PROSPERO (an international and prospective register of systematic reviews) and will be reported in the final manuscript. There is a plan to disseminate all results by means of a subsequent publication, which will be part of the evidence to support a nested case-control study on triple whammy and AKI in Spain.\n\nTo the best of our knowledge, there is a lack of high-quality data on this topic, which makes this research particularly timely.\n\n\nConclusion\n\nAKI is a growing global disease that causes major morbidity and death and has significant resource consequences. The concurrent use of nephrotoxic medications raises the risk of AKI. Based on their pharmacological mechanism, simultaneous administration of diuretics, antihypertensives such as RASI, and NSAIDs or metamizole, known as “triple whammy”, may be linked to AKI. To our knowledge, this is the first systematic review of case-control studies to analyse the “triple whammy” combination and AKI's risk based on well-validated epidemiological databases exploring drug safety issues. The evidence generated by this study can be used as a basis for future studies in order to better understand the risk of AKI and triple therapy combinations. These future studies could explore other confounding factors such as dose, individual’s pharmacokinetics, existence of arteriosclerosis, salt consumption, other medicines, and genetic polymorphisms in enzymes.\n\n\nData availability\n\nNo data are associated with this article.\n\n\nReporting guidelines\n\nOpen Science Framework: PRISMA-P checklist for ‘Acute Kidney Injury associated with “Triple whammy” combination: a protocol for a systematic review’.\n\nCalvo Barbado, Dulce Maria (2022): PRISMA-P 2015 checklisthalffull20032022.docx. figshare. Journal contribution. https://doi.org/10.6084/m9.figshare.19501465.v1.18\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).\n\n\nAuthor contributions\n\nDulce Maria Calvo: Formal analysis (lead) writing – original draft (lead); investigation (lead), methodology (equal); review and editing (equal); guarantor (lead). Luis Carlos Saiz: Formal analysis (supporting), investigation (supporting), methodology (equal); writing – original draft (supporting); review and editing (equal). Leire Leache Alegría: Methodology (equal); writing – original draft (supporting); review and editing (equal). Maria Concepción Celaya: Conceptualization (lead); methodology (equal); review and editing (equal). Marta Gutiérrez Valencia: Methodology (equal); writing – original draft (supporting); review and editing (equal).", "appendix": "References\n\nThomas MC: Diuretics, ACE inhibitors and NSAIDs--the triple whammy. Med. J. Aust. 2000; 172(4): 184–185. PubMed Abstract \| Publisher Full Text\n\nPrieto-Garcia L, Pericacho M, Sancho-Martinez SM, et al.: Mechanisms of triple whammy acute kidney injury. Pharmacol. Ther. 2016; 167(p44, 7905840): 132–145. PubMed Abstract \| Publisher Full Text\n\nLoboz KK, Shenfield GM: Drug combinations and impaired renal function – the ‘triple whammy’. Br. J. Clin. Pharmacol. 2005; 59(2): 239–243. PubMed Abstract \| Publisher Full Text\n\nDreischulte T, Morales DR, Bell S, et al.: Combined use of nonsteroidal anti-inflammatory drugs with diuretics and/or renin-angiotensin system inhibitors in the community increases the risk of acute kidney injury. Kidney Int. 2015; 88(2): 396–403. Publisher Full Text\n\nKunitsu Y, Isono T, Hira D, et al.: Chronic Effects on Kidney Function by «Triple Whammy» (Combination of Renin and Angiotensin Type Inhibitor, Diuretic Drug and Nonsteroidal Anti-inflammatory Drug). Yakugaku Zasshi. 2019; 139(11): 1457–1462. PubMed Abstract \| Publisher Full Text\n\nLapi F, Azoulay L, Yin H, et al.: Concurrent use of diuretics, angiotensin converting enzyme inhibitors, and angiotensin receptor blockers with non-steroidal anti-inflammatory drugs and risk of acute kidney injury: nested case-control study. BMJ. 2013; 346: e8525. Publisher Full Text\n\nLameire NH, Bagga A, Cruz D, et al.: Acute kidney injury: an increasing global concern. Lancet. 2013; 382(9887): 170–179. PubMed Abstract \| Publisher Full Text\n\nChertow GM, Burdick E, Honour M, et al.: Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J. Am. Soc. Nephrol. 2005; 16(11): 3365–3370. Publisher Full Text\n\nVandijck DM, Oeyen S, Decruyenaere JM, et al.: Acute kidney injury, length of stay, and costs in patients hospitalized in the intensive care unit. Acta Clin. Belg. 2007; 62(suppl 2): 341–345. Publisher Full Text\n\nConsulta Interactiva del SNS: [cited 14 June 2020]. Reference Source\n\nIavecchia L, Cereza García G, Sabaté Gallego M, et al.: Drug-related acute renal failure in hospitalised patients. Nefrologia. 2015; 35(6): 523–532. PubMed Abstract \| Publisher Full Text\n\nGarcia Camin RM, Cols M, Chevarria JL, et al.: Acute kidney injury secondary to a combination of renin-angiotensin system inhibitors, diuretics and NSAIDS: “The Triple Whammy”. Nefrología (English Edition). 2015; 35(2): 197–206. PubMed Abstract \| Publisher Full Text Reference Source\n\nTownsend RR, Cohen DL: Use of diuretics with ACE inhibitors or angiotensin receptor blockers and NSAIDs increases the risk of acute kidney injury. Evid.-Based Med. 2013; 18(6): 232–233. Publisher Full Text Reference Source\n\nMangoni AA, Kholmurodova F, Mayner L, et al.: The Concomitant Use of Diuretics, Non-Steroidal Anti-Inflammatory Drugs, and Angiotensin-Converting Enzyme Inhibitors or Angiotensin Receptor Blockers (Triple Whammy), Extreme Heat, and In-Hospital Acute Kidney Injury in Older Medical Patients. Adv. Ther. 2017; 34(11): 2534–2541. PubMed Abstract \| Publisher Full Text Reference Source\n\nArrufat-Goterris G, do Pazo-Oubiña F , Malpartida-Flores M, et al.: Pharmaceutical intervention to reduce the iatrogenic risk associated with the triple whammy combination. Aten. Primaria. 2017; 49(3): 150–155. PubMed Abstract \| Publisher Full Text\n\nCongreso 2016 de la Sociedad Española de Farmacéuticos de Atención Primaria. SEFAP. Reference Source\n\nOracle BI Interactive Dashboards - DAP. Reference Source\n\nBarbado C, Maria D: PRISMA-P 2015 checklisthalffull20032022.docx. figshare. Journal Contribution. 2022. Publisher Full Text\n\nHiggins JP, Thomas J, Chandler J, et al.: Cochrane handbook for systematic reviews of interventions. John Wiley & Sons; 2019.\n\nBellomo R, Ronco C, Kellum JA, et al.: Acute renal failure - definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit. Care. 2004; 8(4): R204–R212. PubMed Abstract \| Publisher Full Text\n\nMehta RL, Kellum JA, Shah SV, et al.: Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury. Crit. Care. 2007; 11(2): R31. PubMed Abstract \| Publisher Full Text\n\nGroup KDIGO (KDIGO) AKIW: KDIGO clinical practice guideline for acute kidney injury. Kidney Int. Suppl. 2012; 2(1): 1–138.\n\nRecommendations\|Acute kidney injury: prevention, detection and management\|Guidance\|NICE. NICE. Reference Source\n\nSterne JA, Hernán MA, Reeves BC, et al.: ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016; 355. Publisher Full Text Reference Source\n\nOliveras Boté I: Evaluación e incorporación del riesgo de sesgo de estudios no experimentales en revisiones sistemáticas y metaanálisis [Ph.D. Thesis]. TDX (Tesis Doctorals en Xarxa). Universitat Autònoma de Barcelona.2018. Reference Source\n\nSanabria AJ, Rigau D, Rotaeche R, et al.: Sistema GRADE: metodología para la realización de recomendaciones para la práctica clínica. Aten. Primaria. 2015; 47(1): 48–55. PubMed Abstract \| Publisher Full Text" }	[ { "id": "142589", "date": "21 Jul 2022", "name": "Antònia Agustí Escasany", "expertise": [ "Reviewer Expertise Pharmacovigilance and pharmacoepidemiology." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAcute Kidney Injury associated with \"Triple whammy\" combination: a protocol for a systematic review. Calvo Barbado DM, Saiz Fernández LC, Leache Alegría L, Celaya Lecea MC and Gutiérrez-Valencia. M\nThe authors will perform a systematic review to calculate the incidence of AKI (Acute Kidney Injury) associated with triple whammy treatment apart from other secondary objectives. In the review clinical trials and also observational studies are going to to be included without any restriction regarding the publication date, setting and languages. The methodology of the review is correct and the authors provide with sufficient details in order to be able to replicate the results by others.\nThe only comments I have are the following:\nI do not know why the authors have chosen 12 twelve months as the period to consider the main and the secondary objectives of the study.\n\nI agree to include in the review the different kind of design studies (clinical trials and the observations ones) and analysed them according to the design of the studies, but I think it could be quite a lot of work.\n\nIs the rationale for, and objectives of, the study clearly described? Yes\n\nIs the study design appropriate for the research question? Yes\n\nAre sufficient details of the methods provided to allow replication by others? Yes\n\nAre the datasets clearly presented in a useable and accessible format? Not applicable", "responses": [ { "c_id": "8561", "date": "09 Aug 2022", "name": "Dulce Maria Calvo Barbado", "role": "Author Response", "response": "Dear Reviewer, Thanks for your comments and review process. Regarding your comments, maybe it is something that we will need to clarify in our protocol. We refer \"Events (primary and secondary outcomes) within 12 months after the last prescription of the triple combination will be considered\", due to AKI is not to be measured \"at\" 12 months but \"in\" the 12 months following the end of exposure to TW. We sought to extend the AKIs not only to the time patients are exposed, but also to the following 12 months (beyond 12 months we interpret the AKI as not being due to previous exposure). Maybe we need to clarify more in our protocol to be understand better for readers. Regarding your second comments, we agree that it will be a lot of work, but thinking that it is a safety problem, observational studies can be a proper way to do it. Again we are thankful for your comments and will take in mind. Dulce Maria Calvo" } ] } ]	1	https://f1000research.com/articles/11-496
https://f1000research.com/articles/11-828/v1	26 Jul 22	{ "type": "Review", "title": "Plant tissue culture challenges in Ethiopia and alternative options for low-cost media", "authors": [ "Kasahun Amare", "Geleta Dugassa", "Geleta Dugassa" ], "abstract": "Plant tissue culture (PTC) is the cultivation of any part of a plant in nutritionally defined media under an aseptic and controlled environment, regardless of season and weather. The application of PTC leads to the mass propagation of varietal, high-quality seedlings of ornamental plants, medicinal plants, plantation crops, fruit trees, and forest trees. PTC technology, on the other hand, is more expensive in developing nations, such as Ethiopia, than traditional propagation methods such as seeds, cuttings, grafting, and so on. As a result, it is critical to take steps to cut production costs and explore alternate choices for present PTC obstacles (budget restrictions, procedural and operational matters, and unfortunate interactions and partnerships). In order to lower the unit cost of crop production, cost-effective procedures and the optimal utilization of equipment are required. This can be accomplished by increasing the efficiency of processes and optimizing resource allocation. Gelling agents, macro and micronutrients, equipment, carbon sources, and the utilization of bioreactors, which can minimize space, energy, and labor needs, can all be replaced to lower production costs. Therefore, these alternative options are recommended as a workaround to the problems and are briefly described in this document.", "keywords": [ "Alternatives", "Biotechnology", "Ethiopia", "Low-cost" ], "content": "1. Introduction\n\nThe growth of plant organs, tissues, cells, or protoplasts in specially formulated nutritional media under sterile and well-controlled light, temperature, and humidity conditions is known as plant tissue culture (PTC) (George et al., 2008; Twaij et al., 2020). PTC is a remarkable biotechnological tool that has applications in vegetable propagation and improvement, disease elimination, herbicide resistance, salinity tolerance, incorporation of high nutrient content, genetically improved plants, and conservation of endangered plant species, and soon usage of this technology will increase further (Naik et al., 2020; Twaij et al., 2020).\n\nWith the increasing demand for agricultural, forestry, and horticultural products, the demand for hybrid crops and high-quality, high-yielding, disease-free planting material has increased dramatically in recent decades (Kadam et al., 2018). Due to these factors, the PTC market was valued at USD382.305 million in 2020 and is projected to grow to USD895.006 million by 2030, with a compound annual growth rate of 8.5 percent from 2021 to 2030 (Srivas & Sumant, 2021).\n\nTo meet market demand and provide farmers with planting material, production must be plentiful. However, one of the major disadvantages of PTC is the high cost of culture media (carbon source, gelling agents, and growth regulators), facilities, and high relative humidity inside the culture vessel causes hyperhydricity, somaclonal variation, energy, and labor, which limit the expansion of the techniques and hamper their implementation (George et al., 2008; Chen, 2016; Espinosa-Leal et al., 2018).\n\nDue to high manufacturing costs, even small and medium-sized laboratories with limited resources cannot take advantage of the potential benefits of PTC technology (Naik et al., 2020). The poorest countries, including Ethiopia, have missed these opportunities due to a lack of understanding, economic reputation, and legal constraints related to spending (Getnet et al., 2016; Abrar et al., 2019). The cost of producing the medium can be as much as 30-35% of the cost of producing micropropagated plants (Gitonga et al., 2010). Electricity costs can account for up to 60% of tissue culture production costs, and labor costs can account for up to 70% (Espinosa-Leal et al., 2018). In addition to high media and others such as inadequate funding and poor management practices, lack of qualified staff, inadequate infrastructure, and poor facilities, staff turnover/brain drain are serious bottlenecks for PTC (George & Manuel, 2013; Abbebaw et al., 2021).\n\nThese difficulties have been solved by the development of reliable, inexpensive tissue culture methods that do not compromise plant quality. Chemicals, media, energy, labor, and capital costs are important factors in production. Alternative materials such as gelling agents (isabugol, sago, cassava starch, barley starch, and bulla) can be substituted for agar as a solidifying agent. In addition, carbon sources such as table sugar, potatoes, cane juice, sugar cubes, and brown sugar have already been documented worldwide (Naik et al., 2020). Other possibilities for lowering production cost includes liquid media, reusable glass beads and bioreactors, can be mentioned (Daud et al., 2011; Espinosa-Leal et al., 2018). Furthermore, there is a huge demand to develop scale-up systems and automation to reduce the intensive labor need as well as the production cost in PTC (Aladele et al., 2012). In this case, this paper aims to review the current challenges of PTC in the development of various low-cost alternatives in Ethiopia.\n\n\n2. PTCs in Ethiopia and current status\n\nIn Ethiopia, biotechnology is covered by seven institutions with a total of 24 branches that deal with various stages of biotechnology research/education and development, including tissue culture, molecular markers, embryo transfer, immunology, vaccines, diagnostic kit development, epidemiology, and genetic diversity. Among those PTC is the most extensively utilized method in agricultural biotechnology (Abraham, 2009; Kassa, 2011). This valuable training area has been initiated in universities and colleges since the 1980s and 1990s at Addis Ababa University initiated joint research and training programs in biotechnology with Swedish Universities. The programs made it possible to train staff members in agricultural biotechnology and industrial biotechnology and to establish a modest facility (Wandui et al., 2013; Abebaw et al., 2021).\n\nOther Ethiopian universities have begun graduate and undergraduate biotechnology training programs, following Addis Ababa University's examples such as Gonder University (undergraduate program); Haramaya University (master’s degree program); Jimma University (master’s degree program), Arba Minch University (master’s degree program), and Bahir Dar University (master’s degree program), Mekelle University and Mekelle Institute of Technology (undergraduate program) and others (Broek & Rensink, 2021).\n\nHowever, a broader and more concerted tissue culture research program was instituted by the Ethiopian Institute of Agricultural Research, which in 2000 launched a broader and more coordinated tissue culture research program focusing on micropropagation, optimization of tissue culture protocol, and virus elimination in economically important horticultural crop species, including banana, cardamom, grapevine, citrus, garlic, potato, geranium, enset, coffee, pineapple, black pepper, sweet potato, cassava, Aframomum corrorima and other high-value crops (Abraham, 2009; Wandui et al., 2013; Abebaw et al., 2021; Seyoum et al., 2021).\n\nRegional agricultural research institutes such as Amhara Regional Agriculture Research Institute (Bahir Dar Tissue Culture Laboratory), Southern Nations, Nationalities and People Region Agricultural Research Institute (Areka Agricultural Research Center), Oromia Regional Agriculture Research Institute (Adami Tulu Agricultural Research Center), and the Tigray Regional Agriculture Research Institute (Mekelle Agricultural Research Center) have made significant advances in tissue culture (Abebaw et al., 2021).\n\nIn addition, tissue culture activities are also carried out by private companies; for example, VCI was active until 2017 but was shut down, as was Narus Biotechnology, which appears to have ceased operations. Waginos Biotech is still operational but is more focused on ornamental crops for the local market and small seed potato crops. Tigray Biotechnology Center, Dessie Tissue Culture Center, and Bahir Dar Tissue Culture Enterprise play a role in the commercialization and dissemination of research outputs to stakeholders (Wandui et al., 2013; Abrar et al., 2019; Abebaw et al., 2021). The most active private plant tissue laboratory is the Bahir Dar PTC, which produces approximately 500,000 plantlets annually (Broek & Rensink, 2021).\n\nCurrently, there is fertile ground in Ethiopia to take advantage of the potential benefits that can come from biotechnology, particularly tissue culture. Some of the micropropagation efforts came to results and commenced to solve the prevailing shortage of planting material (Seyoum et al., 2021). Most production-oriented plant tissue initiatives in the mid-2010s were geared toward expanding large-scale semipublic sugarcane plantations. Most of the seedlings produced in the various laboratories were concentrated in these new plantations; the Tigray Biotechnology Center alone had a production capacity of 40 million, and the Dessie Tissue Culture Center had 20 million plantlets to supply this market (Abebaw et al., 2021; Broek & Rensink, 2021). Between 2009 and 2019, the government had a plan to expand the area covered by state sugar cane cultivation by more than 330,000 hectares and to boost annual sugar production from 2.25 to 4.1 million tons. The program implemented several new sugar plantations, including in the Omo Valley. As a result, Ethiopia increased sugar cane production to 1.5 million tons in 2019. However, limited expansion is currently taking place, putting pressure on PTC labs (Hamza & Alebjo, 2017; Broek & Rensink, 2021; Seyoum et al., 2021).\n\n\n3. The major challenges of PTC\n\nDeveloping nations, including Ethiopia, are not getting the potential benefits from modern biotechnological tools and products. Even if PTC activities started three decades ago in Ethiopia, particularly in public and private research centers and public universities, they have not reached the commercial level to date (Getnet et al., 2016). Therefore, in the Ethiopian context, this sector is an emerging subject both as an academic subject and as an industrial application with its emerging application prospects. This is evidenced by the introduction of undergraduate courses, funding for new university-level laboratories, and approval for young start-ups in biotechnology sectors (Hanumanthaiah & Alemu, 2021). A limited investigation and academic institutes in Ethiopia are engaged in basic, advanced and related research areas in biotechnology with limitations in tools, techniques, and management as well as financial constraints (Abebaw et al., 2021; Hanumanthaiah & Alemu, 2021). At the same time, these developments pose challenges for pioneering biotechnological research and development in terms of lack of funding and supplies in government institutions, low management autonomy in maintenance, technical and administrative problems, limited capacities, improper networking and collaborations leading to material and technological results, and financial difficulties (Hanumanthaiah & Alemu, 2021).\n\nIn addition, finding skilled workers for the plant tissue laboratory is the greatest challenge. The work in the labs is tedious and requires dedication. University graduates (Bachelor) do not want to work as normal workers in laboratories. In addition, prices for inputs are increasing; in particular, the chemicals needed to produce the media and growth hormones, equipment cost, and energy sources remain a challenge (Baidiyavadra et al., 2019; Abebaw et al., 2021; Broek & Rensink, 2021).\n\nTo fully achieve the potential of tissue culture in Ethiopia, answers to these constraints are required. Intervention methods to address these concerns would undoubtedly necessitate a collaborative effort by a number of persons and institutions, which should be backed up by suitable national and regional governments (Abebaw et al., 2021). The Ethiopian government has publicly expressed its interest in the commercialization of agricultural biotechnology as a tool to achieve food security in the country as directed by the prime minister's office to stakeholders (Seyoum et al., 2021). The government recently established a national biotechnology roadmap, which will design and implement policies and strategies for modern biotechnology, prioritizing the agricultural sector. To this end, public universities, research institutes, and some private companies play a promising role in producing a skilled labor force and have started research in biotechnology (Abrar et al., 2019; Abebaw et al., 2021). In other cases, alternative options for culture media, such as cane molasses, cane juice, banana extract, and coconut water, are good alternatives to high-quality sucrose to reduce mean costs (Getnet et al., 2016).\n\nPublic awareness is the last step toward the acceptance and application of the technology in practice. Nonetheless, it is believed that the public is generally less supportive of animal biotechnology applications than plant biotechnology applications, possibly reflecting spiritual attitudes and literacy impact (Abbebaw et al., 2021). However, the obstacle to plant biotechnology is public acceptance of genetically modified crops, as the technology can be controversial and questionable. Farmers have also expressed their concerns. Farmers are particularly concerned about the requirement for qualified workers to carefully nurture PTC seedlings in nurseries, as well as a variety of other unusual growth procedures that stymie PTC's economic viability (Bandewar et al., 2017).\n\nTherefore, since PTC is a part of plant biotechnology, it is important to be introduced to the young generation to encourage their positive attitudes, which ultimately lead to human capital and public awareness in the field (Moid et al., 2021). In addition, the restriction can be avoided by raising awareness through the organization of training, workshops, national seminars, conferences, demonstrations, and dissemination of the information to the public through television, radio interviews, and other mass media (Hanumanthaiah & Alemu, 2021).\n\nHigh national investments have set the foundation for the development of national and international firms in nations where biotechnology has taken hold. The strong backdrop of national research and development, as well as the introduction of special budgets to stimulate the rise of commercial biotechnology, were two of the key factors for the early birth of biotechnology in industrialized countries. Various governments place a high priority on biotechnology development and provide adequate funding for research and development. For example, Lithuania (29%), Austria (3.3%), Germany (2.8%), and the Russian Federation (1%) spent by the fiscal year of 2020 on the research and development of biotechnology companies. Research and development by biotechnology companies as a proportion of the indicator for the country's research focuses on modern biotechnology (OECD, 2021).\n\nIn FY2019-20, the Ethiopian government funded ETB 0.16 billion for the Ethiopian Institute of Biotechnology, which can be distributed to available departments (Ethiopia’s 2019 Budget document). However, there are public and private biotechnology laboratories in Ethiopia, funded by government and nongovernment sources. Some of the labs are for tissue culture, and others are for molecular biology. Therefore, the fund is not as sufficient to undergo plant biotechnology tasks as needed. Due to fund limitations, research and development carried out by Ethiopia's private sector are limited (Abebaw et al., 2021; Broek & Rensink, 2021). In general, it appears that the level of funding required to get a biotechnology program on track and the level of sustained funding required for subsequent operations are generally underestimated (Hanumanthaiah & Alemu, 2021).\n\nThe available financial resources are still too low to allow countries to engage effectively in cutting-edge activities. While they are coordinated and managed by public research institutions, most laboratories and/or institutions heavily rely on external funding from development partners that may not satisfy our needs. Equally challenging is the low level of private sector participation in biotechnology research and development. In some cases, links with the local private sector are either weak or nonexistent (Abebaw et al., 2021; Broek & Rensink, 2021; Seyoum et al., 2021).\n\nDue to the high costs associated with this, long-term planning is required when allocating resources to make optimal use of the infrastructure setup. Medium-term depletion of funds or limited operating budgets was the cause of poor performance, reducing profits to a fraction of what was expected (Abebaw et al., 2021).\n\nPrevious studies have proven that there can be no national economic growth without adequate investment in the appropriate technologies. Investment in unsuitable technology is a real solution to major national challenges such as job creation and poverty alleviation. This is obvious in countries that have welcomed and absorbed biotechnology in previous technological revolutions and are now implementing it on a massive scale (Aladele et al., 2012).\n\nTherefore, four separate steps must be recognized in the funding process to enable the full functionality of an established facility. 1) Funding to establish the physical laboratory space large enough to house the extensive instrumentation associated with this equipment-intensive technology. 2) Funding to purchase the critical mass of equipment needed for molecular work. 3) Funding to cover operational costs of expensive reagents, renewable consumables, and technical support. 4) Funding to fund specific research projects for the period necessary to obtain results. With proper financial planning that includes sustainable funding; our labs can become more productive.\n\nThe lack of adequately qualified science, technology, and support personnel severely impedes the application of biotechnology in developing countries, including Ethiopia. Most service personnel do not have the necessary scientific background to use the new technology. Therefore, further training of the staff is urgently required to enable the use of new technologies. The Ethiopian government recently created a national biotechnology roadmap that prioritizes the agricultural sector to design and implement policies and strategies related to advanced biotechnology. To this end, national universities, research institutes, and some private companies play a promising role in developing a skilled workforce (Abebaw et al., 2021; Hanumanthaiah & Alemu, 2021).\n\nPTC is one of the plant biotechnology disciplines that necessitate a time-consuming procedure. 1) medium preparation, dispensing, and discarding; 2) container washing, handling, and transportation; 3) autoclaving; (4) pruning and transplanting of plants and explants; 5) capping and uncapping; 6) removal and disposal of dead and contaminated plants; 7) acclimatization, equipment, and room sterilization; 8) recording of activities and labeling on culture vessels; and 9) surveillance (Abebaw et al., 2021).\n\nIn affluent countries, labor is a significant expense at PTC. On the other hand, developing-country labor is often cheaper, which is a significant advantage. Labor accounts for 40% of a tissue culture facility's production costs, 10% for supplies, 20% for overhead, and 30% for sales, general, and administrative operations, according to a typical cost profile (Datta et al., 2017). In the EU, however, labor can account for 60-70% of the cost of in vitro plants (Savangikar, 2004).\n\nAnother bottleneck in PTC is the scarcity of supportive staff for the repair and maintenance of equipment. There is currently a shortage of trained technicians to maintain advanced equipment, so it is necessary to frequently request repairs from foreign manufacturing companies. The challenge after training our workforce is managed to avoid losing our skilled workforce (Abebaw et al., 2021; Hanumanthaiah & Alemu, 2021). This is also the current challenge of PTC laboratories present in Ethiopia. For example, Abebaw et al. (2021) reviewed the country's existing laboratories and found a shortage of well-trained and experienced tissue culture personnel and high staff turnover; regrettably, skills for the maintenance and repair of tissue culture equipment are also limited.\n\nFurthermore, many entrepreneurs enter commercial PTCs without sufficient knowledge of tissue culture. To be successful, entrepreneurs must have a basic understanding of the factors that affect plant growth, how plants respond to culture, and how to manipulate plant growth. A solid foundation for plant operations enables entrepreneurs at PTC to change processes to maintain high plant yields. To have such knowledge at PTC, there should be a system for the entrepreneurs to enter a college center. However, in Ethiopia, the number of tissue culture courses offered at public universities is limited (Seyoum et al., 2021).\n\nTo overcome the scarcity of manpower, it is advised that there should be a system that encourages students to attend prestigious universities and research centers with scholarships as an important way to gain access to new knowledge. Other forms of collaboration, such as technology transfer and alliances are also needed.\n\nTo reduce staff turnover/brain drain, after an efficient recruitment process has been developed to hire the best people, whatever is necessary should be done to retain them. Employees need a living wage to pay for food, shelter, and other basic needs, and this is achieved by providing significant incentives. Attractive incentives can help reduce staff turnover while encouraging employees to be more loyal and productive (Sawyer, 2019).\n\nA tissue culture facility can use a variety of low-cost options to simplify operations and cut costs. Equipment and buildings with a preparation room, transfer room, culture or growth room, hardening and weaning area, soil growing area (greenhouses, plastic tunnels), packaging and shipping area, and associated facilities such as an office and chemical storage area, containers, and extras are all physical components of a typical PTC facility. The size of a tissue culture facility's physical components is determined by its functional requirements or production volume (George & Manuel, 2013).\n\nEthiopian government-owned PTC laboratories are characterized by adequate infrastructure, and these are a serious bottleneck and were exacerbated by unreliable utility services (electricity and water supply). Furthermore, low efficiency at different steps in the tissue culture process resulted in very low productivity due to the multiplicative effect of the low facility (Abbebaw et al., 2021). Therefore, finding a reliable solution to such problems requires adequate funding to provide and maintain adequate facilities to operate. The management of assets and personnel must be aligned to the desired level of production.\n\nThe lack of active biotechnology networks and a regional network may be considered one factor limiting the development of biotechnology in agriculture. To date, research collaborations have usually been established either by individual institutions with specialized laboratories abroad for specific projects or with plant-based networks (Brook & Mastewal, 2018). Ethiopian entered into a few partnerships with some organizations involved in agricultural biotechnology in a fragmented way; for example, the Open Forum on Agricultural Biotechnology is one of the agricultural research collaborators with Ethiopia and other countries, such as Kenya, Burkina Faso, Ghana, Nigeria, Tanzania and Uganda (Rock & Schurman, 2020). Another example of partnerships and collaborations in the country is the Addis Ababa University Institute of Biotechnology with the Swedish University of Agricultural Sciences. Networks are built based on common areas of interest; they facilitate the joint development of training programs and research projects, as well as student exchanges and research stays (Brook & Mastewal, 2018).\n\nThere seems to be an urgent need for Ethiopia to join as many large-scale plant-based research networks as possible, particularly those involving other developing countries of comparable economic status and interests in plant research. In addition, the establishment of a regional network is necessary for the sustainable development of biotechnology. Critical to the success of this network would be support for the FAO Global Plant Biotechnology Programme, which aims to strengthen plant biotechnology institutions in developing countries.\n\nGenerally, the weak collaborative linkages and/or partnership among the different stakeholders along with the tissue culture development and the delivery pipeline is considered the bottleneck for the advancement of PTC research centers, universities, and private laboratories should create a very good platform and collaboration that enables solving the key challenges (Seyoum et al., 2021).\n\nIn high-tech laboratories, PTC has become a standard method of plant propagation. However, as compared to traditional propagation methods such as seeds, cuttings, grafting, and so on, the production costs of conventional tissue culture are quite high (Suman, 2017). Traditional PTC has been utilized for decades; nevertheless, the expensive cost of tissue culture production is a disadvantage for laboratories with limited resources, especially in developing nations (George & Manuel, 2013). The high cost of primary production prevents PTC from being adopted on a big scale. As a result, it is critical to take steps to lower production costs. In order to lower the unit cost of crop production, cost-effective techniques and optimal equipment utilization are required. This can be accomplished through increasing the efficiency of processes and optimizing resource allocation (Suman, 2017).\n\n\n4. Low-cost PTC options\n\nThe adoption of procedures and the use of equipment to minimize the unit cost of plantlets and overall plant output is known as inexpensive tissue culture technology. Low-cost alternatives should lower production costs without affecting micropropagule or plant quality. Cost savings are obtained with low-cost technologies by enhancing process efficiency and making better use of resources. In many developing nations, inexpensive tissue culture technology is a top goal in agriculture, horticulture, forestry, and floriculture to provide high-quality planting material at affordable prices (George & Manuel, 2013).\n\nSeveral low-cost alternatives can be used to simplify various operations and reduce costs in a tissue culture facility. The physical components of a typical PTC facility include equipment and buildings with a prep room, a transfer room, a culture or growing room, a hardening and settling area, a soil growing area (greenhouses, plastic tunnels), a packing and shipping area, and associated facilities such as a warehouse an office and chemical store, containers and supplies. The size of the physical components of a tissue culture facility depends on its functional requirements or production volume (George & Manuel, 2013).\n\nThe costs of constructing and managing tissue culture facilities are high, and in developing nations, they are typically non-existent. Facility setup costs and unit production costs of micro propagated plants are high in developing nations, and the return on investment is typically disproportionate to the technology's potential economic benefits. Electricity, for example, is significantly cheaper in industrialized countries, and the supply is far more reliable than in underdeveloped countries. The same is true for micropropagation culture vessels, media, chemicals, equipment, and instruments. To minimize the cost of plant micropropagation, alternatives to expensive inputs and infrastructure must be identified and created (Savangikar 2004; Purohit et al., 2011).\n\nSeveral factors can influence the success of micropropagation, including the efficacy of surface sanitation, the type of culture medium used, and how browning symptoms are handled. As a result, explants must be handled aseptically with sterilized tools; nonetheless, disinfecting chemicals were previously utilized to destroy any germs that may have been present, particularly on the outside of the explants. The reasons of microbial contamination in tissue cultures have been explained in a variety of ways (Abass, 2013). The approach utilized to sterilize the explants, instruments, and equipment could be one cause. In tissue culture, the most prevalent issues are improper procedures and insufficient disinfectant levels. External contamination of explants from contaminated tools, equipment, and personnel in media preparation and culture is also a hazard (Abass, 2013; Rahayu et al., 2019; Emoghene et al., 2020).\n\nOne of the most important steps in PTC is surface sterilization of explants. Explants simply need to be surface sterilized by treatment with a disinfectant solution at acceptable concentrations for a defined amount of time; living materials should not lose their biological activity during sterilization, and only impurities should be removed; (Oyebanji et al., 2009). Sodium hypochlorite (NaOCl), calcium hypochlorite Ca (ClO)2, mercuric chloride (HgCl2), silver nitrate (AgNO3), and hydrogen peroxide (H2O2) are some of the most commonly utilized sterilants (Rahayu et al., 2019).\n\nAs a result, the sterilizing process is made simple, quick, and economical by using locally available bleach or berekina (Oyebanji et al., 2009). As a result, standardizing both the concentration and exposure time for local bleach (berekina) for surface sterilization of sugarcane explants helps to sterilize explants at a lower cost and in a safer manner (Mekonnen et al., 2013).\n\nTopically prepared bleaching solution (JIC with 3.5% sodium hypochlorite) at time intervals between 20 and 45 minutes of surface sterilization of seeds and excised embryos of cowpea, rice, and sorghum explants resulted in a zero percent reduction in bacterial and fungal contamination (Oyebanji et al., 2009). Additionally, sterilization of sweet potato nodule cuttings with JIK (commercial bleach) at 40% v/v containing 1.5% sodium hypochlorite for 20 min prevented microbial contamination (Ogero et al., 2011). Similarly, Mekonnen et al. (2013) devised a safer and less expensive approach for surface sterilization of sugarcane explants using berekina instead of mercuric chloride as a surface sterilant. For surface disinfection of cane shoot tips, berekina with 5% chlorine active for 25 minutes of exposure was shown to be the best combination. Ayele & Tefera (2018) developed an inexpensive sterilization technique for the in vitro initiation of vanilla using the locally available sterilant berekina with 5% active chlorine treatment for 25 minutes and achieved an 82% contamination-free culture with a survival rate of 80% of plant regeneration.\n\nThe autoclaves (laboratory sterilizers) developed for laboratory sterilization applications make processes safer, simpler, more accurate, more reproducible, and more validatable. However, an electric autoclave is expensive; it requires a long heat-up time, electricity, special maintenance, and the risk of electrocution. Therefore, this can be replaced by pressure cookers, which are cheap, efficient, can use any heat source, are easy to maintain, and are safe by attaching a wire mesh to their base (Ahloowalia & Prakash, 2004). Contamination is not detected when media and equipment have been sterilized using a pressure cooker (Naik et al., 2020).\n\nSeveral types of culture vessels are used in PTC culture laboratories, such as laboratory-specific culture jars, Erlenmeyer flasks, magenta bottles, or screw-capped test tubes and Petri dishes during the induction stage, but larger vessels were used when transferring explants for multiplication and elongation (Ahloowalia & Prakash, 2004). Traditional tissue culture vessels may cost at least USD2.90 per piece. To reduce the costs in PTC, locally available glass jars that are used for food canning can be used in place of traditional tissue culture vessels. Hence, at least 85% of the cost could be reduced by using locally available jars. These potential alternatives can therefore find wide acceptability in developing countries that practice micropropagation (Silvosa-Millado et al., 2020).\n\nBioreactors are vessels used to culture vast amounts of cells, tissues, or organs in liquid media. A growing variety of plants have shown numerous significant advantages over traditional semisolid micropropagation, including increased propagation rates and reduced space, energy, and labor costs. Increased interest in the usage of fluid systems, in general, in general, has been fueled by these cost-cutting benefits (Levin & Tanny, 2004). As a result, when used in conjunction with a traditional laboratory, they can be appealing to developing countries looking to build new or expand existing plant culture facilities. Traditional culture tanks offer less precise control of plant growth, gas exchange, illumination, medium movement, temperature, and pH than bioreactors (Adelberg, 2016).\n\nThe ability to scale up in a faster time frame, lower production costs, and automated control of physical and chemical conditions during the growth phase of PTCs is the main welfares of consuming a bioreactor culture method for propagation of economically significant plants (Aladele et al., 2012). However, there are numerous drawbacks to using bioreactors in micropropagation due to a variety of issues. Contamination, a lack of procedures and production methods, increased hyperhydricity, foaming issues, shear stress, and the release of growth inhibiting chemicals from the cultures are just a few of the issues. Because liquid systems have more challenging contamination problems and a lack of problem-solving knowledge than semisolid growth media, they are more dangerous and demand more competence. As a result, in many impoverished nations, bioreactors are not a cost-effective solution. Labor expenses, production capacity, crops to be propagated, contamination rate, and energy and cost savings potential are all factors to consider (Levin & Tanny, 2004; George & Manuel, 2013).\n\nLight plays a crucial role in the growth and development of in vitro plant culture. It is a powerful source for photosynthesis and physiological processes to produce secondary metabolites. Among the many factors that contribute to plant growth, light is one of the most important obstacles to effective in vitro plant growth (Vu et al., 2020). Typically, light intensity is set between 50 and 100 mol m-2 s-1 of photosynthetically active radiation, but photosynthetic photon fluxes as low as 5 or as high as 150 mol m-2 s-1 have been reported, depending on the species and application (Phillips & Garda, 2019).\n\nBecause of the importance of light for plant growth, laboratories that affect plant tissues often consume a large amount of artificial light electricity. Artificial light generates heat that must be dissipated by cooling, and the fan further contributes to the electrical load. Therefore, switching the lighting method from artificial to natural light is a crucial cost-effective option in tissue culture. Light is a very expensive and ineffective method in tissue culture technology. In developing countries, electricity costs can account for up to 60% of production costs. In addition, its constant supply and power supply cause major problems (George & Manuel, 2013; Vu et al., 2020).\n\nWhile the need for electrical power is essential, adopting low-cost options can reduce production costs. The alternative of using natural light as a light source for micropropagation systems has been reported in various studies to reduce power and capital costs as well as to improve plant quality. For example, the use of light-emitting diodes in micropropagation can reduce electricity prices by 50 to 75% compared to traditional lighting systems. This is done by replacing artificial light with natural light (George & Manuel, 2013; Vu et al., 2020).\n\nGlass-distilled water is commonly used in tissue culture, with many laboratories using double distilled water (Phillips & Garda, 2019). The use of ion-exchange columns has been criticized for the release of a variety of organic contaminants during the process (True, 1914). However, ion exchange columns easily supply water to many laboratories and are widely used in Europe. For example, Ahloowalia and Prakash (2004) reported that double distilled water is the main component of all tissue culture media and is considered free of ions and impurities.\n\nHowever, distilled water produced through electrical distillation is expensive and adds to the cost of tissue culture; hence, alternative, cheaper water sources that could reduce the cost of the media without altering the composition are needed. Tap water (free from heavy metals and contaminants) can be substituted for distilled water to lower the cost of the medium. Tap water after autoclaving can be used in small facilities rather than distilled water. Reverse osmosis water can be used for stock solutions and hormone preparations, and distilled water can be used for media preparation to reduce the cost most effectively. It is also used for washing plants before sterilization and for added sterilants for cleaning. Table bottled water from the supermarket can also be used as a low-cost alternative (Naik et al., 2020). Rainwater, river water, and water from other natural sources were considered to be more beneficial to their experimental sites than distilled water, and natural waters were often used to ensure that plant behavior was considered normal (True, 1914).\n\nAs a result, much research has been done to reduce the cost of double-distilled water. Raghu et al. (2007) reported that using tap water for tissue culture did not affect in vitro plant growth. Saraswathi et al. (2016) reported that for banana micropropagation, three types of water (reverse osmosis water, drilled well water, and simple distilled water) were evaluated to reduce media preparation costs. Water costs were reduced by 86% by using inexpensive replacement water (reverse osmosis water, artesian well water) instead of double-distilled water. Similarly, Sunandakumari et al. (2004) reported that media prepared with tap water differed from media prepared with double distilled water in terms of in vitro sprout induction in Mentha piperita.\n\nFor semisolid and solid media, a typical PTC medium includes a base solution containing major and minor minerals, a carbon source (sucrose), vitamins, growth regulators, and a gelling agent (Bhojwani & Dantu, 2013). However, there is an ongoing search for alternatives for the culture medium components to lower plant micropropagation expenses. The major goal is to substitute nutritive solutions derived from less expensive sources for macro- and micronutrients, sugars, and gelling agents (Montenegro et al., 2014). These are the key variables that contribute to the high production costs.\n\nWe can considerably lower the cost of tissue culture by adopting low-cost alternatives, allowing it to be practiced by the common farmer. Using low-cost alternatives, tissue culture plant manufacturing costs can be decreased by 50-90 percent. Foliar nutrients have been used in the in vitro culture of Cattleya sp., seed culture of Arabidopsis thaliana, fertilizers for Laelia anceps micropropagation, and numerous commercial foliar fertilizers in the micropropagation of Solanum tuberosum have been reported (Montenegro et al., 2014).\n\nThe gelling agent is another ingredient of PTC media. Agar is one of the most commonly used gelling agents in the preparation of culture media, but it is also one of the most expensive. Alternatives such as cassava starch, wheat flour, semolina, potato starch, rice powder, sage, bulla, and others have allegedly been used to generate inexpensive and accessible media for commercial in vitro plant production (Mohamed et al., 2010). In the case of the root-initiating MS medium, some other ingredients, such as sawdust, peanut hulls, rice husks, coconut pulp, and coir, were used instead of agar (Das & Gupta, 2009).\n\n4.6.1 Low-cost options for gelling agent\n\nCulture growth and shoot or root formations are greatly affected by the physical instability of the medium. Gelling agents are often added to the medium to increase its viscosity, thereby keeping the tissues of plants and organs above the surface of the medium (Ahloowalia & Prakash, 2004). The rigidity of the medium greatly affects the growth of the cultured tissue. A wide range of gelling agents used in plant culture media are available on the market, including agar, agarose, and gellan gum sold under trade names such as Phytagel, Gelrite, and GelGro (Ahloowalia & Prakash, 2004; Franklin & Franco, 2021).\n\nAgar has been widely used as a medium for microorganisms and PTC since it was introduced as a gelling agent over 100 years ago. It is a polysaccharide derived from red algae and the family Rhodophyceae. It is used as a universal gelling agent for preparing semisolid and solid media for PTC. The concentration of agar used in the medium depends on its purity and productivity. It is usually applied at 0.6-0.8% (w/v) (Franklin & Franco, 2021). It is the most expensive component of the PTC medium and usually contributes to increased medium viscosity at 70% of the medium cost (Naik et al., 2020). The almost exclusive use of agar leads to overfishing of its source. Due to the exorbitant price of tissue culture grade agar, attempts have been made to find suitable alternative gelling agents that are economically feasible and readily available locally (Khan et al., 2012).\n\nRecently, various inexpensive sources, such as potato flour, rice, barley, wheat, enset flour/bulla, and corn flour, have also been used individually or in combination as gelling agents with varying degrees of success (Mohamed et al., 2010; Ayenew et al., 2012; Khan et al., 2012). It has also been found that the combination of laundry starch, potato starch, and semolina in a 2:1:1 ratio reduces the cost of the gelling agent by more than 70% (Prakash, 1993).\n\nBulla: Bulla is a processed starch or dough from Enset. It is a byproduct of making kocho when the waste and pulp are pressed, separating the liquid. The starch that separates from the liquid concentrates into a white powder.\n\nBulla was first used for the micropropagation of pineapple (Ananas comosus) in place of agar at 80 g/L. The results showed that production costs were reduced up to 76% (Ayenew et al., 2012). Another report from the same year found that replacing agar with 60-100 g/L of bulla could reduce the cost of micropropagation of vanilla planifolia by 50-72.5% (Mengesha et al., 2012). Similarly, for cassava meristems, culture bulla at 80 g/L reduced costs by 86% when combined with 60 g/L bulla + 2 g/L agar, and 70 g/L bulla + 1 g/agar saved a cost of 65-75% (Ayalew et al., 2017).\n\nIn addition to replacing traditional agar, bullas have been found to increase root length compared to traditional agar. This may be due to the carbon content. However, bulla is less transparent, and contamination is difficult to detect (Ayenew et al., 2012; Mengesha et al., 2012; Ayalew et al., 2017). Similarly, other types of starches may exhibit such greening or darkening properties, e.g., Saraswathi et al. (2016) reported that three gelling agents were used, and greening (10%-20%) was observed in a medium with corn flour.\n\nIsubgol: Isubgol is extracted from the seeds of the Plantago ovata of the Plantain family. The effect of Isubgol's skin is solely due to the presence of large amounts of mucus in the skin. Similar to agar, ibugor mucus is colloidal and polysaccharide-like, consisting primarily of xylose, arabinose, galacturonic acid, rhamnose, and galactose. The slimy husks from Plantago ovata have been successfully used as a gelling material for tissue culture media. The price of “Isubgolhusk” is cheaper than that commonly used as agar because the price of the gelling agent in the PTC medium has been reduced by approximately 47.5% (Khan et al., 2012).\n\nThis has been evidenced by different previous reports. For instance, replacing the commonly used solidifying agent agar (0.8%) with Isbugor (1.5%) produced a much similar response to agar for callus formation in sugarcane in vitro propagation (Dhawale et al., 2021). In another report by Ullah et al. (2015), isabgol at 30 g/L was the optimal cost-effective gelling agent for the best growth of shoots, leaves, and roots of orchids (Dendrobium Sonia). Similarly, Isabgol-based medium enhanced the initial establishment of shoot tips in ‘Udhayam’ and ‘Rasthali’ banana cultivars, and the combination of Sago and Isabgol was found to be a better gelling agent for many crops, including banana. The effectiveness of these alternative gelling agents might have been due to their high mucilage content (>30%) or their polysaccharide and colloidal nature (Saraswathi et al., 2016).\n\nPotato, barley, and corn starch: Starch is the cheapest alternative among the alternative gelling agents in PTC, and its use may reduce costs. Nevertheless, starch is hydrolyzed by plant amylolytic enzymes during in vitro tissue culture (Lima et al., 2011). To evaluate this situation, Amlesom et al. (2021) examined three alternative low-cost corn, potato, and barley starches at 50 g/L as a solidifying substitution for commercial agar for the micropropagation of potato. It has been found that substituting agar with alternative starches showed a significant reduction in the cost of a solidifying agent. The highest cost reduction was observed from 61-66%, implying that using both corn and potato starches can be reliable and cost-effective gelling agents for the micropropagation of potatoes.\n\nSago starch: Sago starch is a complex polysaccharide that serves as a storage product in a variety of plants. It contains a small number of sugars, fiber, protein, calcium, and other minerals. Sago, unlike agar, can be used as a gelling agent and as a carbohydrate component in nutrient media (Datta et al., 2017).\n\nSago, as a gelling agent, had a significant influence on shoot proliferation and in vitro rooting of ginger, turmeric, and banana. Sago at 70 g/L gave proper solidification and normal culture growth in ginger and turmeric micropropagation (Prakash, 1993). Similarly, medium solidified with sago at 80 g/L was found to be superior to commercial grade agar for the micropropagation of banana in terms of shoot length, several leaves, shoot diameter, several primary roots, plantlet diameter, and fresh weight, and it reduced the media cost by 69.69% (Prabhuling, et al., 2014). However, beyond the better performance of sago in the medium, it may reduce visibility to check for fungal growth under in vitro conditions (Saraswathi et al., 2016).\n\nAdditionally, the utilization of glass beads has potential. Glass beads provide a good substratum for plant tissues that grow well in a liquid media, with the added benefit of reuse, lowering the input cost by removing the use of a solidifying agent in every cycle (Pant, 2016).\n\n4.6.2 Low-cost options for macro- and micro-nutrients\n\nPlant tissue and organs produced in vitro on synthetic media provide the nutrients required for growth and development. Plant propagation via tissue culture is impacted by the type of media utilized. Because plants require considerable amounts of inorganic elements, they are referred to as major plant nutrients. N, P, Ca, P, Mg, and S are the main elements. Micronutrients, on the other hand, are elements that are required in little amounts (Fe, Cu, Zn, B, Mo, Mn, and Cl) (Purohit et al., 2011; George & Manuel, 2013; Ayalew et al., 2017; Phillips & Garda, 2019).\n\nLocally available fertilizers at appropriate concentrations can be used as a low-cost source of nutrients for PTC. The conventional sources of MS media were replaced by mixed nutrients containing both macro- and micronutrients for sweet potato micropropagation. MS nutrients were substituted with locally available fertilizers as a macronutrient (monopotassium phosphate, potassium fertilizer, Epsom salt, and ammonium quarry salt) and micronutrients (Stanes Iodised Microfood®) using 30 g/L table sugar as a source of carbon. The low-cost medium was significantly cheaper than the MS medium, with reductions of 87.8%, 68.6%, and 97.1% for macronutrients, micronutrients, and carbon sources, respectively (Ogero et al., 2011). Ogero et al. (2012) found that replacing MS salt medium with locally available foliar feed “Easygro vegetative fertilizer” comprising both macro- and micronutrients resulted in a low-cost cassava micropropagation strategy. The usage of Easy Grows led in a 96.7% cost decrease. Similarly, alternative sources to MS macronutrients included ammonium fertilizer, potassium fertilizer, Epsom salt, monopotassium phosphate, and calcination, while Stanes Iodized Microfood® was used as an alternative to MS micronutrients for cassava micropropagation, resulting in a 93% cost savings (Kidulile et al., 2018).\n\nHydro Agri’s fertilizer is also another alternative option to replace MS media salts for micropropagation of cassava, and the full substitution of the media with commercially available nutrients resulted in a cost reduction of 93.1% compared to the traditional media (Naik et al., 2020). In addition, palm oil mill effluent is a free and nontoxic material that contains valuable macronutrients required for plant growth. It consists of high total nitrogen sources that increase the composting period efficiency by degrading the cellulose and hemicellulose components of empty fruit bunches. In addition, the organic nutrient constitution in palm oil mill effluent and empty fruit bunch is desirable by the plant, which can reduce the usage of inorganic fertilizer as part of environmental protection. A 100 mL palm oil mill effluent solution with 100 mL molasses was found to be more cost-effective than the synthetic MS basal salt medium. Thus, this will also minimize the production cost of the clonal plant without compromising the quality of regeneration produced (Nadirah et al., 2019).\n\n4.6.3 Low-cost options for carbon source\n\nIn vitro, plant cells, tissues, and organ cultures are not fully autotrophic, necessitating the use of carbohydrates in culture media to maintain osmotic potential and provide energy and carbon for developmental processes such as shoot proliferation, root induction and emission, embryogenesis, and organogenesis, all of which are energy-intensive developmental processes in plant biology (Yaseen et al., 2013).\n\nTherefore, the addition of suitable carbonaceous materials as an energy source is imperative. In plant cell culture media, sucrose is mainly used as an energy source. Sucrose is partially broken down into fructose and glucose during autoclaving. Sucrose also acts as an osmoticum in the medium. Generally, 20-40 grams of sucrose is added to each liter of liquid medium. Starches are also used in some medium formulas both as the support substance and energy source. Sucrose has been reported to act as a morphogenetic trigger in the formation of accessory buds and branching of adventitious roots (George et al., 2008). Consequently, sucrose is among the media components that are routinely used in PTC. However, the unavailability and the prohibitive cost of laboratory-grade sucrose are among the major constraints of PTC laboratories found in developing countries (Rukundo et al., 2012).\n\nAs a result, instead of tissue culture-grade sucrose, commercially available table sugar was employed. This resulted in lower medium costs without sacrificing micropropagation rate or plant quality (Venkatasalam et al., 2013). Furthermore, adding cane molasses, banana extract, and coconut water to basal media has been discovered to be a suitable choice for lowering medication prices. These substrates provide not only energy but also vitamins and inorganic ions, which are essential for growth.\n\nAlternative energy sources for micropropagation of various plant species have been documented in numerous researches. Using locally available alternatives the energy cost for potatoes TC was reduced by 34 to 51% (Demo et al., 2008). Table sugar at 30 g/L could stimulate banana plantlet growth to the same extent as laboratory sucrose at 30 g/L. As a result, table sugar is advised for banana micropropagation to lower the cost of in vitro plantlets. Plantlets grown on table sugar culture medium, on the other hand, were shown to be weaker than counterparts grown on laboratory grade sucrose culture medium (Rukundo et al., 2012).\n\nMekonnen et al. (2014) developed an inexpensive protocol that can use table sugar 6% half MS for rooting and 4% table sugar for sprout propagation instead of expensive sucrose 6% with half MS and 3% sucrose for sprout propagation. Therefore, to let developing countries such as Ethiopia benefit from PTC technology, using such locally available and economically justifiable resources instead of expensive resources is the best alternative. Identifying cheap or low-cost alternative gelling and carbon sources will significantly reduce production costs by 90-97% (Mengesha et al., 2021; Datta et al., 2017). In addition, using vermicompost 50 g/L+ table sugar 30 g/L, wheat flour, and coconut water reduces production costs by 58 to 97% (Kadam et al., 2018; Rasal-Monir, 2018).\n\n\n5. Conclusion\n\nPTC is considered to be a mass propagator of agriculturally important crops within a finite period regardless of the season. However, its application is hampered by the costs required to carry out the activities. Therefore, various developing countries, including Ethiopia, suffer from the high costs of media, facilities, and skilled labor, as well as adequate funding, staff turnover, and government policies, which pose the greatest challenges for PTC in developing countries. To meet these challenges, various scientists have searched for solutions in the past. One solution that scientists are recommending for developing countries to use PTC applications is to replace low-cost media alternatives, gelling agents, locally available culture vessels, natural light, tap water, table sugar as a carbon source, and others. Furthermore, the government should pay attention to adequate funding for the PTC sectors in the country, train employees, provide incentives to reduce staff turnover, and focus on expanding laboratory facilities to promote the technology and use it effectively.\n\n\nData availability\n\nThere are no underlying data associated with this article.", "appendix": "References\n\nAbass MH: Microbial contaminants of date palm (Phoenix dactylifera L.) in Iraqi tissue culture laboratories. Emirates Journal of Food and Agriculture. 2013; 25: 875–882. Publisher Full Text\n\nAbebaw YM, Tobiaw DC, Abate BA, et al.: Plant Tissue Culture Research and Development in Ethiopia: A Case Study on Current Status, Opportunities, and Challenges. Advances in Agriculture. 2021; 2021: 1–12. Publisher Full Text\n\nAbraham A: Agricultural biotechnology research and development in Ethiopia. African Journal of Biotechnology. 2009; 8(25).\n\nAbrar T, Temam Z-H, Redwan W: Current Status and Opportunities of Plant Tissue Culture in Ethiopia.2019; 5: 19–28.\n\nAdelberg J: Bioreactors and “smart vessels” for large-scale propagation. IX International Symposium on in vitro Culture and Horticultural Breeding 1187. 2016, March; (pp. 123–138).\n\nAhloowalia BS, Prakash J: Physical components of tissue culture technology. Low cost options for tissue culture technology in developing countries 2004; 17.\n\nAladele SE, Okere AU, Jamaldinne E, et al.:The science of plant tissue culture as a catalyst for agricultural and industrial development in an emerging economy. Recent advances in plant in vitro culture. IntechOpen;2012.\n\nAmlesom WS, Mehari T, Saleh BK: Evaluation of Different Starches as Gelling Agents for Micropropagation of Potato. The Journal of Agricultural Science. 2021; 13(5): 144. Publisher Full Text\n\nAyalew M, Vellaiyappan S, Gebre W: Micropropagation of cassava [Manihot esculenta Crantz] using bulla flour [Ensete Ventricosum [Welw.], Cheesman] as an alternative source of agar in plant tissue culture media. International Journal of Research Studies in Science, Engineering and Technology. 2017; 4: 23–34.\n\nAyele YZ, Tefera W: Low cost sterilization technique and in vitro initiation of vanilla (Vanilla planifolia Andr.). Journal of Agricultural Science and Food Research. 2018; 1–6.\n\nAyenew B, Mengesha A, Tadesse T, et al.: Ensete ventricosum (Welw.) Cheesman: a cheap and alternative gelling agent for pineapple (Ananas comosus var. smooth cayenne) in vitro propagation. Journal of Microbiology, Biotechnology and Food Sciences. 2012; 2021: 640–652.\n\nBaidiyavadra DA, Muralidharan CM, Sharma KM: Fresh date production in Kachchh (India): Challenges and future prospects. Medicinal Plants-International Journal of Phytomedicines and Related Industries. 2019; 11(3): 218–227. Publisher Full Text\n\nBandewar SV, Wambugu F, Richardson E, et al.: The role of community engagement in the adoption of new agricultural biotechnologies by farmers: the case of the Africa harvest tissue-culture banana in Kenya. BMC Biotechnology. 2017; 17(1): 1–11. Publisher Full Text\n\nBhojwani SS, Dantu PK:Culture Media. Plant Tissue Culture: An Introductory Text. India:Springer;2013; (pp. 27–37).\n\nBroek J, Rensink T: Market Research Plant Propagation Material Sector In Ethiopia. Addis Abeba:Resilience;2021.\n\nBrook L, Mastewal M: Bilateral cooperation with Ethiopia a Proposal for training and research partnership between Institute of Biotechnology (IOB), Addis Ababa University (AAU) and the Swedish University of Agricultural Sciences (SLU): 2018-2023.2018.\n\nChen C: Cost analysis of plant micropropagation of Phalaenopsis. Plant Cell, Tissue and Organ Culture (PCTOC). 2016; 126(1): 167–175. Publisher Full Text\n\nDas A, Gupta SN: Use of low cost resources for banana micropropagation. Indian Journal of Horticulture. 2009; 66(3): 295–300.\n\nDatta SK, Chakraborty D, Janakiram T: Low cost tissue culture: an overview. The Journal of Plant Science Research. 2017; 33(2): 181–199.\n\nDaud N, Taha RM, Noor NNM, et al.: Provision of low cost media options for in vitro culture of Celosia sp. African Journal of Biotechnology. 2011; 10(80): 18349–18355.\n\nDemo P, Kuria P, Nyende AB, et al.: Table sugar as an alternative low cost medium component for in vitro micropropagation of potato (Solanum tuberosum L.). African Journal of Biotechnology. 2008; 7(15).\n\nDhawale RN, Patwari LV, Sharma KM, Bharose AA: Admixture of Isubgol Husk together with agar as gelling agent for sugarcane callus induction.2021.\n\nEmoghene BO, Idu M, Eke CR, et al.: Effects of different sterilization regimes & growth regulators on micropropagation of female date Palm (Phoenix dactylifera L.). Nigerian Journal of Biotechnology. 2020; 37(1): 159–168.\n\nEspinosa-Leal CA, Puente-Garza CA, García-Lara S: In vitro plant tissue culture: means for production of biological active compounds. Planta. 2018; 248(1): 1–18. PubMed Abstract \| Publisher Full Text\n\nFranklin VF, Franco V: Gelling agents and their role in plant tissue culture - Lab Assocciates. Lab Associates. 2021, December 13. Retrieved March 14, 2022, fromReference Source\n\nGeorge EF, Hall MA, De Klerk GJ: Plant propagation by tissue culture. 3rd ed.The Netherland:The Back Ground Springer;2008.\n\nGeorge P, Manuel J: Low cost tissue culture technology for the regeneration of some economically important plants for developing countries. International Journal of Agriculture, Environment and Biotechnology. 2013; 6(Special Issue): 703–711.\n\nGetnet B, Bantte K, Diro M: Table Sugar as Low Cost Option and its Concentration Effect on Shoot Multiplication of Sugarcane (Saccharum officinarum L.) Genotypes. Advances in Crop Science and Technology. 2016; 04(248): 2. Publisher Full Text\n\nGitonga NM, Ombori O, Murithi KSD, et al.: Low technology tissue culture materials for initiation and multiplication of banana plants. African Crop Science Journal. 2010; 18(4).\n\nHamza TA, Alebjo AL: Sugarcane (Saccharum Officinarum L) tissue culture in Ethiopia: opportunities for Ethiopia’s sugar industries. International Journal of Scientific & Technology Research. 2017; 6(8): 398–406.\n\nHanumanthaiah P, Alemu AC: Plant Biotechnology in Ethiopia: Current Status, Opportunities And Challenges. Plant Cell Biotechnology and Molecular Biology. 2021; 22(13&14): 136–156.\n\nKadam DD, Chhatre AA, Lavale SA, et al.: Low-cost alternatives for conventional tissue culture media. International Journal of Current Microbiology and Applied Sciences. 2018; 7(4): 2523–2529. Publisher Full Text\n\nKassa GD: The potential of biotechnology in Ethiopia: Present situation and expected development. Food and Chemical Toxicology. 2011; 49(3): 685–689. PubMed Abstract \| Publisher Full Text\n\nKhan S, Al Maruf A, Aktera S, et al.: Admixture of Isubgol husk together with conventionally used agar as gelling agent for Potato and Stevia regeneration. Bangladesh Journal of Scientific and Industrial Research. 2012; 47(2): 161–166. Publisher Full Text\n\nKidulile CE, Alakonya AE, Ndunguru JC, et al.: Cost effective medium for in vitro propagation of Tanzanian cassava landraces. African Journal of Biotechnology. 2018; 17(25): 787–794. Publisher Full Text\n\nLevin R, Tanny G: Bioreactors as a low cost option for tissue culture. Low cost options for tissue culture technology in developing countries. 2004; 47.\n\nLima GPP, da Silva Campos RA , Willadino LG, Camara TJ, et al.: Polyamines, gelling agents in tissue culture, micropropagation of medicinal plants and bioreactors. sn. 2011.\n\nMekonnen T, Diro M, Sharma M: An alternative safer and cost effective surface sterilization method for sugarcane (Saccharum officinarum L.) explants. African Journal of Biotechnology. 2013; 12(44): 6282–6286. Publisher Full Text\n\nMekonnen T, Diro M, Sharma M, et al.: Protocol optimization for in vitro mass propagation of two sugarcane (Saccharum officinarum L.) clones grown in Ethiopia. African Journal of Biotechnology. 2014; 13(12).\n\nMengesha A, Ayenew B, Tadesse T: Energy sources affect in vitro propagation and subsequent acclimatization of Ananas comosus, var. smooth cayenne plants. Journal of Microbiology, Biotechnology and Food Sciences. 2021; 2021: 2372–2376.\n\nMengesha A, Ayenew B, Gebremariam E, et al.: Micro-Propagation of Vanilla planifolia using Enset (Ensete ventricosum (Welw, cheesman)) starch as a gelling agent. Current Research Journal of Biological Sciences. 2012; 4(4): 519–525.\n\nMohamed MAH, Alsadon AA, Al Mohaidib MS: Corn and potato starch as an agar alternative for Solanum tuberosum micropropagation. African Journal of Biotechnology. 2010; 9(1).\n\nMoid MM, Alam NASS, Rasidi IZAN, et al.:Development of STEM tissue culture module in promoting plant biotechnology. Journal of Physics: Conference Series. IOP Publishing;2021, May; (Vol. 1882, No. 1, p. 012159). Publisher Full Text\n\nMontenegro-Juárez FE, Rojas-Idrogo C, Quevedo-Calle D, et al.: Efecto del sulpomag y complejos orgánicos como sustitutos parciales del medio de cultivo de micropropagación de Musa sp. cv. Cavendish. Agronomía Costarricense. 2014; 38(1): 147–159.\n\nNadirah MNA, Awal A, Azma YN, et al.:POME: An alternative nutrient source for bio-organic plant tissue culture media. IOP Conference Series: Earth and Environmental Science. IOP Publishing;2019, September; (Vol. 327, No. 1, p. 012029).\n\nNaik R, Bhushan A, Gupta RK, et al.: Low Cost Tissue Culture Technologies in Vegetables: A Review. International Journal of Biochemistry Research and Review. 2020; 29(9): 66–78. Publisher Full Text\n\nOECD: Key biotechnology indicators. OECD;2021. Retrieved March 31, 2022, fromReference Source\n\nOgero KO, Gitonga NM, Mwangi M, et al.: A low-cost medium for sweet potato micropropagation. African Crop Science Conference Proceedings. 2011.\n\nOgero KO, Gitonga NM, Mwangi M, et al.: Cost-effective nutrient sources for tissue culture of cassava (Manihot esculenta Crantz). African Journal of Biotechnology. 2012; 11(66): 12964–12973. Publisher Full Text\n\nOyebanji OB, Nweke O, Odebunmi O, et al.: Simple, effective and economical explant-surface sterilization protocol for cowpea, rice and sorghum seeds. African Journal of Biotechnology. 2009; 8(20).\n\nPant M: A minimal cost micropropagation protocol for Dianthus caryophyllus L. a commercially significant venture.2016.\n\nPhillips GC, Garda M: Plant tissue culture media and practices: an overview. In Vitro Cellular & Developmental Biology-Plant. 2019; 55(3): 242–257. Publisher Full Text\n\nPrabhuling G, Mastiholi AB, Kerutagi MG: Low-cost gelling agents for micropropagation of banana (Musa acuminate) cv.'Grande Naine'. International Journal of Plant Sciences (Muzaffarnagar). 2014; 9(1): 46–51.\n\nPrakash S: Production Of Ginger and Turmeric Through Tissue Culture Methods And Investigations Into Making Tissue Culture Propogation Less Expensive.1993.\n\nPurohit SD, Teixeira da Silva JA, Habibi N: Current approaches for cheaper and better micropropagation technologies. International Journal of Plant Developmental Biology. 2011; 5: 1–36.\n\nRaghu AV, Martin G, Priya V, et al.: Low cost alternatives for the micropropagation of Centella asiatica. Journal of Plant Sciences. 2007; 2(6): 592–599. Publisher Full Text\n\nRahayu ES, Widiatningrum T, Herlina L, et al.:The optimal sterilizing compound and culture medium in Elaeocarpus grandiflorus L. in vitro shoot induction. Journal of Physics: Conference Series. IOP Publishing;2019, October; (Vol. 1321, No. 3, p. 032040).\n\nRasal-Monir MD: Low Cost Media for in Vitro Regeneration of Gynura procumbens (Lour.) Merr (Doctoral dissertation, Department of Horticulture, Sher-E-Bangla Agricultural University, Dhaka-1207).2018.\n\nRock J, Schurman R: The complex choreography of agricultural biotechnology in Africa. African Affairs. 2020; 119(477): 499–525. Publisher Full Text\n\nRukundo P, Ulinzwenimana C, Uwase F, et al.: Comparative study of effects of table sugar, laboratory grade sucrose and mannitol on growth of banana plantlets under in vitro conditions. Rwanda Journal. 2012; 28: 76–83.\n\nSaraswathi MS, Uma S, Kannan G, et al.: Cost-effective tissue culture media for large-scale propagation of three commercial banana (Musa spp.) varieties. The Journal of Horticultural Science and Biotechnology. 2016; 91(1): 23–29. Publisher Full Text\n\nSavangikar VA: Role of low cost options in tissue culture. In Low cost options for tissue culture technology in developing countries. Proceedings of a Technical Meeting organized by the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture. 2004, February; (pp. 11–15).\n\nSawyer K: 30 Employee Incentives for Lowering Turnover Rate. Deputy.2019, February 12.Retrieved March 17, 2022, fromReference Source\n\nSeyoum H, Ayano A, Menges B: Current State and Development of Micro Propagation of Selected High Value Crops in Ethiopia: A Review. American Journal of Life Sciences. 2021; 9(4): 81–91. Publisher Full Text\n\nSilvosa-Millado CSC, Dejan ACM, Asumbrado MJLC, et al.: Alternative materials for plumule initiation and callus induction of coconut (Cocos nucifera L.) cv. Laguna Tall.2020.\n\nSrivas A, Sumant O: Plant Tissue Culture Market Statistics\|Industry Forecast - 2030. Allied Market Research. 2021. Retrieved March 11, 2022, fromReference Source\n\nSuman S: Plant tissue culture: A promising tool of quality material production with special reference to micropropagation of banana. Biochemical and Cellular Archives. 2017; 17(1): 1–26.\n\nSunandakumari C, Martin KP, Chithra M, et al.: Rapid axillary bud proliferation and ex vitro rooting of herbal spice, Mentha piperita L.2004.\n\nTrue RH: The harmful action of distilled water. American Journal of Botany. 1914; 1: 255–273. Publisher Full Text\n\nTwaij BM, Jazar ZH, Hasan M: Trends in the use of tissue culture, applications and future aspects. International Journal of Plant Biology. 2020; 11(1): 8385. Publisher Full Text\n\nUllah MA, Uddin MI, Puteh AB, et al.: Alternative gelling agents for in vitro propagation of orchid (Dendrobium sonia). JAPS: Journal of Animal & Plant Sciences. 2015; 25(3).\n\nVenkatasalam EP, Sood R, Sharma AK, et al.: Development of low cost technology for in vitro mass multiplication of potato (Solanum tuberosum L.). African Journal of Agricultural Research. 2013; 8(49): 6375–6382.\n\nVu TN, Tran QT, Tong QC, et al.: Development of a solar/LED lighting system for a plant tissue culture room. Journal of Vietnamese Environment. 2020; 12(2): 142–147. Publisher Full Text\n\nWandui C, Masiga E, Francis M, et al.:2013. Situational Analysis of the Current State of Tissue Culture Application in the Eastern and Central Africa Region. Kampala. Reference Source\n\nYaseen M, Ahmad T, Sablok G, et al.: Role of carbon sources for in vitro plant growth and development. Molecular Biology Reports. 2013; 40(4): 2837–2849. PubMed Abstract \| Publisher Full Text" }	[ { "id": "204125", "date": "25 Sep 2023", "name": "Marimuthu Somasundaram Saraswathi", "expertise": [ "Reviewer Expertise Tissue culture", "mutation breeding", "molecular biology and genetic resources management" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThough the low cost options have been covered comprehensively in this review, it needs revisions in the following areas.\nIn all places, wherever you have mentioned about cost reduction, it should be in terms of % reduction as against control or the standard practice.\n\nThe scientific names should always be in italics.\n\nThe term in vitro should be italicised.\n\nIt is very poorly written, they are advised to proofread the article.\n\nReferences\nFranklin and Franco, 2021 in page No.10 4.6.1. last but one line. In the references, the retrieved date is not required as it cause confusion of 2022 or 2021\nAbebaw et al. (2021) is the right spelling and in Page 3, 4th para last line it has been wrongly spelled as Abbebaw. Hence this may be corrected please.\nReferences formatting is not uniform, this may be re-checked please.\nPlease find an annotated pdf with further corrections here.\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nIs the review written in accessible language? Partly\n\nAre the conclusions drawn appropriate in the context of the current research literature? Yes", "responses": [] }, { "id": "228304", "date": "16 Feb 2024", "name": "Dr. Nurul Izzati Osman", "expertise": [ "Reviewer Expertise Plant Tissue Culture", "Phytochemistry", "Pharmacognosy" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\n(1) Suggestion: Concrete reference/supporting studies are required for certain claims/statements in the manuscript, for example: -\"University graduates (Bachelor) do not want to work as normal workers in laboratories\". -\"Furthermore, adding cane molasses, banana extract, and coconut water to basal media has been discovered to be a suitable choice for lowering medication prices \"\n(2) Some of the references cited don't reflect the statement mentioned in the manuscript, for example: -\"In other cases, alternative options for culture media, such as cane molasses, cane juice, banana extract, and coconut water, are good alternatives to high-quality sucrose to reduce mean costs (Getnet et al., 2016)\". Getnet et al., 2016 research is on table sugar, not cane juice, banana extract etc.\n(3) Delete repeated words: \"Increased interest in the usage of fluid systems, in general, in general, has been fueled by these cost-cutting benefits...\"\n(4) Suggestion: Incorporate latest/recent findings and references for classic reference, for example: \"Rainwater, river water, and water from other natural sources were considered to be more beneficial to their experimental sites than distilled water, and natural waters were often used to ensure that plant behavior was considered normal (True, 1914).\"\n(5) For this study, what was the impact on micropropgated plants? The implication for the quality of yields and products must be highlighted. \"Water costs were reduced by 86% by using inexpensive replacement water (reverse osmosis water, artesian well water) instead of double-distilled water.\"\n(6) Why adequate infrastructure is a serious bottleneck?: \"Ethiopian government-owned PTC laboratories are characterized by adequate infrastructure, and these are a serious bottleneck ...\"\n(7) No space between Ca and (ClO)2. Please check.\n(8) Revise the sentence: \"Explants simply need to be surface sterilized by treatment with a disinfectant solution at acceptable concentrations for a defined amount of time; living materials should not lose their biological activity during sterilization, and only impurities should be removed; (Oyebanji et al., 2009).\"\n(9) Revise the sentences. Twice 'As a result' in a consecutive order in one paragraph. \"As a result, the sterilizing process is made simple, quick, and economical by using locally available bleach or berekina (Oyebanji et al., 2009). As a result, standardizing both the concentration and exposure time...\"\n(10) There is a reference that cannot be accessed: Abbebaw et al. 2021. Is it similar to Abebaw et al. 2021?\n(11) Suggestion: It is good if the facts and figures regarding the demand for PTC-produced plants in Ethiopia are included in the review, and how many are successfully met with the current status of PTC in Ethiopia to depict the challenges of PTC.\nGeneral comment: Please check the sentence structures of the whole manuscript, the currentness, and suitability of the references cited.\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nIs the review written in accessible language? Partly\n\nAre the conclusions drawn appropriate in the context of the current research literature? Yes", "responses": [] }, { "id": "215945", "date": "16 Sep 2024", "name": "Jaindra Nath Tripathi", "expertise": [ "Reviewer Expertise Plant tissue culture and Plant Transformation", "Genome editing" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript is well written, focusing on plant tissue culture challenges in Ethiopia and suggesting how to reduce the cost using alternative options. I agree with the authors to use low-cost options to reduce the cost. it is very difficult to buy all the tissue culture consumables from international companies in developing countries like Ethiopia and other African countries.\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Yes\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-828
https://f1000research.com/articles/11-827/v1	26 Jul 22	{ "type": "Research Article", "title": "A retrospective cohort study on effects of antenatal steroids on respiratory morbidity for term elective caesarean sections in South Asian women", "authors": [ "Madura Jayawardane", "Indunil Piyadigama", "Uthpala Chandradeva", "Indunil Piyadigama", "Uthpala Chandradeva" ], "abstract": "Background Respiratory distress (RD) is higher among newborns born by caesarean section (CS) compared to vaginal delivery. Royal College of Obstetricians and Gynaecologists recommend steroid administration for CS prior to 39 weeks. Effectiveness of steroids for neonatal RD at term is inconclusive. The racial differences are yet to be studied.\nMethods A single center retrospective cohort study was conducted in Colombo, Sri Lanka from December 2016 to February 2019. All mothers delivered by CS between 37+0 and 38+6 weeks were included. Mothers with severe maternal hypertension, fetal rhesus sensitization, intrauterine infection, multiple pregnancies and who received steroids at a prior gestation were excluded. Cohort was subdivided according to administration of intramuscular dexamethasone prior to CS. Primary outcomes measured were RD, admissions to neonatal intensive care unit (NICU) and special care baby unit (SCBU). Neonatal infections and maternal duration of hospital stay were recorded as secondary outcome measures.\nResults 560 patients were included. 23.2% of patients received antenatal corticosteroids. Incidence of RD, NICU admissions and SCBU admissions in the study cohort was 10%, 0.9%, and 2.7% respectively. Relative risk for developing RD in the steroid group compared to non-steroid group was 2.67 (95CI 1.64-4.35). 4.6% of the steroid group and 3.3% of the non-steroid group needed to be admitted to the NICU/SCBU (p=0.464). A significantly higher number of babies in the steroid group needed IV antibiotics. The average number of days the mothers were admitted to the hospital was 2.45 days (SD+/- 1.424) for steroid group and 1.4 days (SD+/- 0.856) for the non-steroid group (p < 0.001).\nConclusions There is a significant increase in the respiratory morbidity in the dexamethasone administered south Asian mothers at term prior to CS. However, this effect has no clinical significance since the admissions to NICU and SCBU were not significantly different.", "keywords": [ "Dexamethasone", "term", "elective caesarean", "respiratory distress", "RDS" ], "content": "Introduction\n\nGestational age is the most important risk factor for respiratory distress (RD) in the newborn. As gestation increases, neonatal respiratory morbidity decreases. The incidence of respiratory distress (RD) exponentially decreases from 12.9/1000 to 1.1/1000 for vaginal deliveries prior to 39 weeks compared to vaginal deliveries from 39+0 weeks onwards (Zanardo et al. 2004). It has also been shown that caesarean section (CS) is an independent risk factor for respiratory morbidity with an odds ratio (OR) of 2.3 (95% confidence interval (CI) 2.1–2.6) compared to vaginal delivery (Gerten et al. 2005). Therefore, American College of Obstetricians and Gynecologists (Guidelines for Perinatal Care, 5th edition, p 148) and National Institute for Health and Care Excellence recommends avoiding all planned CS, if possible, before 39 weeks of gestation. However, this is not practical in many instances. 30-80% of planned CS are carried out prior to 39 weeks of gestation due to various reasons such as maternal medical problems, fetal indications and convenience, across the world (Tita et al. 2011).\n\nRD is defined as signs of breathing difficulties in the neonate. In term RD is reported in up to 7% of newborns (Edwards, Kotecha, and Kotecha 2013). RD leads to admission to a special care baby unit (SCBU) and neonatal intensive care unit (NICU), separation from the mother, and in turn secondary problems with ICU care as well as long term complications like asthma with a very high cost of overall management (Jain and Dudell 2006). Transient tachypnoea of the newborn (TTN), respiratory distress syndrome (RDS), congenital pneumonia and meconium aspirations syndrome (MAS) are some of the common causes that can lead to respiratory distress at term.\n\nRDS is primarily a condition that occurs due to surfactant deficiency in the preterm. Antenatal steroids had been a revolutionary treatment for preterm birth (before 34+0 weeks) as this reduces respiratory problems, intraventricular haemorrhage (IVH) and necrotizing enterocolitis (NEC) and improves the overall neonatal health and decreases mortality rates (McGoldrick et al. 2020).\n\nIn the term infant respiratory distress appears to have different pathophysiology based on retention of physiological fluids in the lungs (Hopkins 2015). Traditionally it was thought that vaginal delivery squeezes fluid out of the lungs during delivery. Current evidence suggests that lung epithelial sodium channels (ENaC) play a crucial role in the alveolar fluid drainage (Jain and Dudell 2006). Catecholamine increases the activity of ENaCs, which may explain the reduction in respiratory complications in labour (Brown et al. 1983). ENaCs are also directly regulated by glucocorticoids (Venkatesh and Katzberg 1997). After exposure of 4 to 24 hours glucocorticoids increase the number of ENaCs and their function through genomic effects. Additionally, glucocorticoids increase the responsiveness of ENaCs to catecholamines and thyroid hormones.\n\nSince the Antenatal Steroids for Term Caesarean Section (ASTECS) trial demonstrating the protective effect of betamethasone on respiratory morbidity in term newborns (P. Stutchfield, Whitaker, and Russell 2005), Royal College of Obstetricians and Gynaecologist (RCOG) recommend corticosteroids be administered for all planned caesareans before 38+6 weeks of gestation.\n\nSteroid administration is a relatively safe procedure. However, steroids can lead to transient suppression of the maternal-fetal production of Adrenocorticotropic hormone (ACTH), Dehydroepiandrosterone sulfate (DHEA-S) and circulating estradiol (Ogueh et al., 1999). Fetal problems such as impaired growth, transient hypoglycemia, childhood poor school performance, increased vulnerability to stress related diseases and metabolic illness in later life have been reported in some studies (Haviv, Said, and Mol 2019). Maternal hyperglycemia, pain associated with intramuscular injections and additional hospital visits or increased stay duration are some of the other recognized complications (Kalra, Kalra and Gupta, 2014).\n\nAdministering steroids is a common procedure where clinicians are challenged frequently. Sotiriadis et al. concludes that more quality studies are needed due to a bias of the current studies on steroid for term CS. Also, the Cochrane review questioned the clinical significance of steroid administration given the low event rates of significant respiratory morbidity (Sotiriadis et al. 2018). There is conflicting evidence for using steroids at term for preventing respiratory morbidity. Haviv et al. in their review do not recommend steroid administration for early term deliveries given the potential risk weighing against the benefits (Haviv, Said, and Mol 2019), and the American, Canadian, Australian and New Zealand societies do not recommend steroids at term. There can be racial differences in effect of steroids on neonatal respiratory complications at term with Asians having relatively less RD compared to Caucasians (Nada et al., 2016). These effects in south Asian pregnancies are yet to be studied.\n\n\nMethods\n\nA retrospective cohort study was conducted to look for the effects of corticosteroid administration for respiratory morbidity in Sri Lankan neonates delivered by elective caesarean section (ELCS) between 37 and 38+6 weeks.\n\nAll the CS prior to February 2019, in University Obstetrics and Gynaecology Unit, Colombo South Teaching Hospital (Prof-unit CSTH) were assessed for eligibility. Prof-unit CSTH was chosen for the study for several reasons. This is a teaching unit which practices RCOG guidance. There are five practicing consultants with differing opinions on term steroid administration and therefore it was easier to recruit groups with and without corticosteroid administration. The neonatal care is provided by a single unit and therefore diagnosis and admission criterion were similar for all the neonates.\n\nMothers undergoing ELCS between 37 and 38+6 weeks of gestation were included for the study. Pregnancies complicated with severe maternal hypertension, severe fetal rhesus sensitization, and evidence of intrauterine infection (maternal temperature, cardiotocographic finding of tachycardia or fetal distress, meconium-stained liquor at delivery), those who received steroids due to other indications up to 36 weeks of gestation and multiple pregnancies and any intrapartum CS were excluded. On average Prof-unit CSTH has about 200 deliveries a month. The CS rate of the unit is about 30% with nearly half being ELCS. This accounts for about 30 ELCS a month. Due to strict inclusion and exclusion criteria, we could recruit about 20 patients a month for the study. The neonatal policies of the unit were changed in late 2016. Therefore, recruiting was done only up to December 2016.\n\nThe data from bed head tickets, which were traced from the archives in the record room, were extracted by a research assistant on to a data collection sheet. Data collection was carried out from April to September 2019. One research assistant who was not involved with the research protocol development or the management of the patients was used to eliminate observer bias. Maternal demographic data were collected including age, parity and previous and current medical problems, gestational age at CS, surgical details, and postoperative complications. Maternal corticosteroid administration was recorded. All neonatal information including birth weight, gender, and Apgar scores were recorded. Primary outcomes measured were RD and admissions to NICU and SCBU. The data key for the variables is shown in Table 1.\n\nNeonatal records were used to arrive at the diagnosis of RD. RD in the newborn was diagnosed in the presence of at least one of the following criteria: respiratory rate of 60/min or more, increased respiratory effort (subcostal recessions, xiphoid retraction, suprasternal in-drawing), nasal flaring, expiratory grunting and cyanosis (Flidel-Rimon and Shinwell, 2005). Neonatal infections, medical interventions, and duration of hospital stay were recorded as secondary outcome measures.\n\nThe cohort was analyzed in two groups. Group 1 consisted of mothers who received IM dexamethasone 12mg, two doses 12 hours apart within a week from delivery up to 24 hours prior to the delivery. Group 2 consisted of mothers who did not receive corticosteroids in the antenatal period. Analysis was done using IBM SPSS version 25 in February 2021. Relative risks for developing complications were analyzed and Pearson’s chi-square test was used to compare the independent and dependent categorical variables. A sensitivity analysis using binary logistic regression model was used to look for the confounders. There were no missing data for exposure or the outcomes since the records were obtained from bead head tickets.\n\nEthical approval was granted by the University of Sri Jayewardenepura ethical review committee on 30/05/2017 (application number 35/17). The ethical review committee concluded that since the data extracted are retrospective without any patient identification details it was not necessary to obtain written consent from the patients.\n\n\nResults\n\n560 patients were included in the study (Piyadigama, 2022). Amongst the study cohort 130 (23.2%) patients received antenatal corticosteroids.\n\nAverage gestation age of delivery was 38 weeks for both the groups. Average birth weights of steroid and non-steroid groups were 2.951kg and 2.924kg respectively. There was no significant difference in parity, pregnancy complications and birth weights within the groups. However, there was a significant difference in the gestation age at delivery between the two groups with a slightly advanced gestation in the non-steroid group. 46.2% women in the steroid group and 40.3% of women in the non-steroid group included in the sample had delivered between 37 to 37+6 weeks. 53.8% of women of steroid group and 59.7 % of women of non-steroid group had delivered at 38-38+6 weeks (p=0.238) (Table 2).\n\nIncidence of RD, NICU admissions and SCBU admissions in the study cohort was 10% (56), 0.9% (5), 2.7% (15) respectively. There was a significantly higher incidence of RD of 19.2% in the steroid group compared to 7.2% in non-steroid group (p<0.001). NICU and SCBU admissions were needed by 4.6% (6) in steroid group and 3.3% (14) in non-steroid group without a significant difference (p=0.464). There was a 2.67 times higher risk of respiratory morbidity in the steroid administered group compared to non-steroid group (Table 3).\n\nA significantly higher number of babies in the steroid group needed intravenous antibiotics. On average the number of days these mothers remained in the hospital was 2.45 days (SD 1.424) for steroid group and 1.4 days (SD 0.856) for the non-steroid group. The hospital stay was significantly higher in the steroid group (p < 0.001) (Table 3).\n\nAmongst the neonates who developed primary outcomes (respiratory complications), the mean birth weight was 3.104kg (SD ±0.463) in the steroid group and 2.833kg (SD ±0.574) in the non-steroid group. The gestational age at delivery was 265.2 (SD ±4.523) days and 264.5 (SD ±3.741) days respectively (Table 4). There was no significant difference in the birth weights and gestational age at delivery amongst the neonates with respiratory complications (Table 5).\n\nA logistic regression was performed to ascertain the effects of steroid administration and gestational age at the delivery. The model explained 6.7% (Nagelkerke R2) of the variance in respiratory distress and correctly classified 90.0% of cases. Neonates exposed to steroids were 3.03 times more likely to exhibit RD than neonates who were not exposed to steroids. Increasing gestational age at delivery was associated with a 0.93 times reduction in respiratory distress.\n\nWhen considering the indications for admission to NICU and SCBU the RDS and TTN were recorded as the primary indications for admission in 2 (33.3%) neonates in the steroid group and 10 (71.4%) neonates in the non-steroid group. There was no significant difference in respiratory complications being the primary indication for admission amongst the two groups (p=0.112) (Table 5).\n\n\nDiscussion\n\nOur findings conclude that there is no protective benefit of maternal dexamethasone administration at term prior to CS. Some studies have demonstrated protective effects of steroids at term. The Antenatal Steroids for Term Caesarean Section (ASTECS) trial was one of the first studies to show beneficial effects of steroids. The relative risk of admission to special care baby unit with respiratory distress was 0.46 (95%CI 0.23-0.93) in favor of the steroid administration (P. Stutchfield, Whitaker, and Russell 2005). The Cochrane review in 2018, looking at four large randomized controlled trials was also able to demonstrate the beneficial effects of corticosteroids at term by reducing respiratory distress syndrome. However, it was concluded that the evidence of these studies are of low quality (Sotiriadis et al. 2018).\n\nSeveral studies have failed to demonstrate protective effects of steroids on respiratory morbidity of newborns delivered by CS at term (de la Huerga López et al. 2019; Nooh et al. 2018). An observational study done in Oman looking at RDS in neonates delivered at term by ELCS which included 650 patients showed 2.5% RDS prevalence in the overall study sample. There was no significant difference in the respiratory morbidity with and without dexamethasone administration in this study (3.7% vs. 2.1%; p = 0.340) (Al Riyami et al. 2020).\n\nThe use of steroid at term and the effect on different ethnicities is not yet sufficiently studied. The ASTECS study identifies race as a contributory factor for steroid effects. However, the study was not powered enough to analyze these effects (P. Stutchfield, Whitaker, and Russell 2005). Although western studies have shown a beneficial effect of term steroid administration, studies with Arabic and Egyptian pregnant women have failed to demonstrate this (Al Riyami et al. 2020; Nooh et al. 2018). Our study, looking at South Asians, also could not show beneficial effects of steroids.\n\nA recent Sri Lankan study in a tertiary care hospital reported the RD prevalence as 8.2% for all newborns delivered at term (Gamhewage et al. 2020). International literature also reports similar incidences (Edwards, Kotecha, and Kotecha 2013). In our study the prevalence of overall respiratory morbidity was 10%, in keeping with these findings.\n\nOur study showed a significantly higher rate of respiratory morbidity in the steroid administered group which has not been reported in any other studies. Although the reported respiratory morbidity was higher in the steroid group, there was no significant difference in admission to SCBU or NICU. Asian mothers are more prone for glycemic problems in pregnancy (Chen et al. 2019). Dexamethasone can lead to transient changes in blood sugar levels. In turn this can affect the newborn which may not have enough time for equilibrate its blood sugar levels since delivery occurs within 24 to 48 hours of steroids. Neonatal hypoglycemia is a known complication associated with steroids (Thevathasan and Said 2020). This may explain the transient increase in RD in the steroid group without needing further interventions. In fact, the ASTECS study showed higher rates of admissions to special care unit without respiratory complications in the betamethasone administered group. However, the reasons for these admissions and neonatal glycemic levels were not reported.\n\nGamhewage et al. looked at different causes of RD in a Sri Lankan tertiary care hospital and found out TTN, congenital pneumonia, MAS and neonatal sepsis without pneumonia were the major contributors in descending order (Gamhewage et al. 2020). Therefore, neonatal infections seem to play a larger role than RDS for RD at term in the Sri Lankan setup. A significant proportion of neonates in the steroid administered group in our study receiving IV antibiotics may reflect this phenomenon. Increasing the hospital stay can have various adverse effects on surgical patients, especially increasing their risk of acquired hospital infections. The steroid administered group had a longer hospital stay needing at least 24 to 48 hours prior to the planned surgery. The mechanism of congenital pneumonia and early neonatal infections without ruptured membranes is difficult to explain. Neonatal antibiotics administration was a secondary finding of the study and we have not collected sufficient data to test if neonatal infections were the cause for higher RD in the steroid administered group.\n\nWe used IM dexamethasone 12mg, 2 doses with a 12-hour gap. Some of the studies have used IM betamethasone 12mg two doses with a 24 hour gap (P. R. Stutchfield et al. 2013) while most of the others have used IM dexamethasone 24mg with two or three divided doses withing a 24 hour period (Ahmed, Sayed Ahmed, and Mohammed 2015; Nooh et al. 2018; Nada et al. 2016). Both these steroids are structurally similar fluorinated compounds. However, there are differences in structure of these and therefore effects in vitro. Because of the acetate included, betamethasone has longer half-life compared to dexamethasone (Thevathasan and Said 2020). Dexamethasone has demonstrated stronger non-genomic effects. When comparing the effects of the two medications on preterm infants betamethasone seems to have better respiratory outcomes with a larger reduction of RDS (Feldman et al. 2007) whereas dexamethasone administered had more effect on reducing IVH (Nooh et al. 2018). The effect of different formulations of steroids on term respiratory morbidity had not yet been assessed but should be considered in future research.\n\nOur study was a retrospective analysis which helped to get a larger sample within a limited time. However due to the design there was loss of information. Observer bias also was unavoidable. There were multiple confounders leading to outcomes which we have not separately analyzed. The primary outcomes were dependent on diagnosis already made by clinicians at the time of delivery rather than looking at different clinical or radiological features individually. Therefore, different causes for RD could not be analyzed.\n\nWe recommend further evaluation of the effect of dexamethasone administration in term pregnancies of south Asian mothers prior to CS. Prospective studies or randomized control trials of high quality are needed. Also, it may be beneficial to compare the effects of dexamethasone versus betamethasone in term respiratory morbidity prevention. Looking at neonatal infections and hypoglycemia may give further insight to the subject.\n\n\nConclusions\n\nThere is a significant increase in the respiratory morbidity in the dexamethasone administered group with a RR of 2.67 (1.64-4.35). However, this is not clinically significant since the NICU and SCBU admissions are not significantly different with or without steroid administration [RR-1.42 (0.56-3.62)].\n\n\nData availability\n\nDryad: A Retrospective Cohort Study on Effects of Antenatal Steroids on Respiratory Morbidity for Term Elective Caesarean Sections in South Asian Women https://doi.org/10.5061/dryad.g79cnp5qs (Piyadigama, 2022).\n\nThis project contains the following files:\n\n- Dexamethasone_final_data_set.sav (raw data file)\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).\n\n\nAuthor contributions\n\nIP, MJ, UC contributed to the concept, data collection, analysis and writing up of the manuscript.", "appendix": "Acknowledgments\n\nWe thank all the health staff involved in the care for the study cohort.\n\n\nReferences\n\nAhmed MR, Ahmed WAS, Mohammed TY: Antenatal Steroids at 37 Weeks, Does It Reduce Neonatal Respiratory Morbidity? A Randomized Trial. J. Matern. Fetal Neonatal Med. 2015; 28(12): 1486–1490. PubMed Abstract \| Publisher Full Text\n\nBrown MJ, Olver RE, Ramsden CA, et al.: Effects of Adrenaline and of Spontaneous Labour on the Secretion and Absorption of Lung Liquid in the Fetal Lamb. J. Physiol. 1983; 344(November): 137–152. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nChen L, Shi L, Zhang D, et al.: Influence of Acculturation on Risk for Gestational Diabetes among Asian Women. Prev. Chronic Dis. 2019; 16(12): 1–10. PubMed Abstract \| Publisher Full Text\n\nEdwards MO, Kotecha SJ, Kotecha S: Respiratory Distress of the Term Newborn Infant. Paediatr. Respir. Rev. 2013; 14(1): 29–37. Publisher Full Text\n\nFeldman DM, Carbone J, Belden L, et al.: Betamethasone vs Dexamethasone for the Prevention of Morbidity in Very-Low-Birthweight Neonates. Am. J. Obstet. Gynecol. 2007; 197(3): 284.e1–284.e4. PubMed Abstract \| Publisher Full Text\n\nFlidel-Rimon O, Shinwell ES: Respiratory Distress in the Term and Near-term Infant. NeoReviews. 2005; 6(6): e289–e297. Publisher Full Text\n\nGamhewage NC, Jayakodi H, Samarakoon J, et al.: Respiratory Distress in Term Newborns: Can We Predict the Outcome?. Sri Lanka Journal of Child Health. 2020; 49(1): 30–34. Publisher Full Text\n\nGerten KA, Coonrod DV, Curtis Bay R, et al.: Cesarean Delivery and Respiratory Distress Syndrome: Does Labor Make a Difference?. Am. J. Obstet. Gynecol. 2005; 193(3 SUPPL.): 1061–1064. Publisher Full Text\n\nHaviv HR, Said J, Mol BW: The Place of Antenatal Corticosteroids in Late Preterm and Early Term Births. Semin. Fetal Neonatal Med. 2019; 24(1): 37–42. PubMed Abstract \| Publisher Full Text\n\nHopkins J: “Tachypnea,” no. patient 7.2015.\n\nde la Huerga López A , Alonso MS, Jiménez APJ, et al.: Antenatal Corticosteroids and Incidence of Neonatal Respiratory Distress after Elective Caesarean Section in Late Preterm and Term Neonates. Anales de Pediatría (English Edition). 2019; 91(6): 371–377. PubMed Abstract \| Publisher Full Text\n\nJain L, Dudell GG: Respiratory Transition in Infants Delivered by Cesarean Section. Semin. Perinatol. 2006; 30(5): 296–304. PubMed Abstract \| Publisher Full Text\n\nKalra S, Kalra B, Gupta Y: ‘Glycemic management after antenatal corticosteroid therapy’, North American journal of medical sciences. Medknow Publications & Media Pvt Ltd. 2014; 6(2): 71–76. PubMed Abstract \| Publisher Full Text\n\nMcGoldrick E, Stewart F, Parker R, et al.: Antenatal Corticosteroids for Accelerating Fetal Lung Maturation for Women at Risk of Preterm Birth. Cochrane Database Syst. Rev. 2020; 12(2). PubMed Abstract \| Publisher Full Text\n\nNada AM, Shafeek MM, El Maraghy MA, et al.: Antenatal Corticosteroid Administration before Elective Caesarean Section at Term to Prevent Neonatal Respiratory Morbidity: A Randomized Controlled Trial. Eur. J. Obstet. Gynecol. Reprod. Biol. 2016; 199: 88–91. PubMed Abstract \| Publisher Full Text\n\nNooh AM, Abdeldayem HM, Arafa E, et al.: Does Implementing a Regime of Dexamethasone before Planned Cesarean Section at Term Reduce Admission with Respiratory Morbidity to Neonatal Intensive Care Unit? A Randomized Controlled Trial. J. Matern. Fetal Neonatal Med. 2018; 31(5): 614–620. PubMed Abstract \| Publisher Full Text\n\nOgueh O, et al.: Effect of antenatal dexamethasone therapy on maternal plasma human chorionic gonadotrophin, oestradiol and progesterone. Hum. Reprod. 1999b; 14(2): 303–306. PubMed Abstract \| Publisher Full Text\n\nPiyadigama I: A retrospective cohort study on effects of antenatal steroids on respiratory morbidity for term elective Caesarean sections in South Asian women. Dryad, Dataset. 2022. Publisher Full Text\n\nAl Riyami N , Al Hadhrami A, Al Lawati T, et al.: Respiratory Distress Syndrome in Neonates Delivered at Term-Gestation by Elective Cesarean Section at Tertiary Care Hospital in Oman. Oman Med. J. 2020; 35(3): e133–e149. Publisher Full Text\n\nSotiriadis A, Makrydimas G, Papatheodorou S, et al.: Corticosteroids for Preventing Neonatal Respiratory Morbidity after Elective Caesarean Section at Term. Cochrane Database Syst. Rev. 2018; 2018(8): CD006614. PubMed Abstract \| Publisher Full Text\n\nStutchfield PR, Whitaker R, Gliddon AE, et al.: Behavioural, Educational and Respiratory Outcomes of Antenatal Betamethasone for Term Caesarean Section (ASTECS Trial). Arch. Dis. Child. Fetal Neonatal Ed. 2013; 98(3): F195–F200. PubMed Abstract \| Publisher Full Text\n\nStutchfield P, Whitaker R, Russell I: Antenatal Betamethasone and Incidence of Neonatal Respiratory Distress after Elective Caesarean Section: Pragmatic Randomised Trial. Br. Med. J. 2005; 331(7518): 662–664. PubMed Abstract \| Publisher Full Text\n\nThevathasan I, Said JM: Controversies in Antenatal Corticosteroid Treatment. Prenat. Diagn. 2020; 40(9): 1138–1149. PubMed Abstract \| Publisher Full Text\n\nTita ATN, Lai Y, Landon MB, et al.: Timing of Elective Repeat Cesarean Delivery at Term and Maternal Perioperative Outcomes. Obstet. Gynecol. 2011; 117(2 Pt 1): 280–286. PubMed Abstract \| Publisher Full Text\n\nVenkatesh VC, Katzberg HD: Glucocorticoid Regulation of Epithelial Sodium Channel Genes in Human Fetal Lung. Am. J. Physiol. Lung Cell. Mol. Physiol. 1997; 273(1): L227–L233. Publisher Full Text\n\nZanardo V, Simbi AK, Franzoi M, et al.: Neonatal Respiratory Morbidity Risk and Mode of Delivery at Term: Influence of Timing of Elective Caesarean Delivery. Acta Paediatrica, International Journal of Paediatrics. 2004; 93(5): 643–647. PubMed Abstract \| Publisher Full Text" }	[ { "id": "279636", "date": "27 Jun 2024", "name": "Annie Mcdougall", "expertise": [ "Reviewer Expertise Global maternal and newborn health", "public health", "preterm birth", "ACS" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nFor Authors: We have reviewed for indexing of the article: A retrospective cohort study on effects of antenatal steroids on respiratory morbidity for term elective caesarean sections in South Asian women. The authors report findings from a retrospective cohort study of mothers undergoing elective caesarean section between 37+0 and 38+6 weeks’ gestation, at one facility in Sri Lanka. They report incidence of respiratory distress, neonatal intensive case unit (NICU) and special care baby unit (SCBU) in neonates born at term to mothers receiving antenatal corticosteroids. They found no protective effect of corticosteroids, and respiratory distress was significantly worse in infants exposed to ACS. While this topic is of interest, there are several concerns that must be addressed before being approved for indexing.\n\nMajor comments:\n\nAuthors stated that there were no missing data for exposure or the outcomes of interest since the records were obtained from bed head tickets. Is it reasonable to expect that every bed head ticket had complete data with no gaps? Were only complete bed head tickets selected to be included in the study? Later, in the discussion , the authors note that ‘However due to the design there was loss of information’. This needs further explanation and for there to be consistency throughout the manuscript on missing data.\n\nPlease clarify the exact dates of the recruitment period, and include a flow chart of participants recruitment.\n\nA more detailed explanation is needed in the discussion about why steroids may make respiratory distress worse, as reported by the authors. Please discuss possible mechanisms. For example: about lung liquid reabsorption with thinning tissue with ACS and TTN as described here: Erin V McGillick et al. (2022 [ref - 1]) https://pubmed.ncbi.nlm.nih.gov/35813383/\n\nMinor comments:\n\nAbstract:\n\nUnder ‘Methods’ subheading of the abstract, clarify whether the study included all mothers delivered by CS, or only those with planned/elective CS\n\nKeywords:\n\nSuggest adding ‘pregnancy’ and ‘antenatal corticosteroids’\n\nIntroduction:\n\nParagraph 1, Line 2: use acronym RD as already mentioned in line 1. No need to spell out acronym twice. Use RD throughout manuscript following first use. Reference needed for ‘Gestational age is the most important risk factor for RD’. Reference needed for ‘RD is defined as signs of breathing difficulties in the neonate’.\n\nParagraph 2: ‘In term pregnancies, RD is reported…’ Paragraph 3: can authors clarify whether they are defining preterm birth as before 34+0 weeks? Suggest clarifying the definition of preterm birth (using the WHO definition), and make clearer what the current evidence suggests for use of antenatal corticosteroids before 34 weeks or 37 weeks?\n\nParagraph 6: suppression of ACTH, DHEA-S and estradiol is mentioned, but need to include further explanation of what the impact of this is.\n\n‘…common procedure where clinicians are challenged frequently’ – this sentence is not clear and needs clarification ‘…more quality studies are needed due to a bias of the current studies…’ – this needs further explanation. What bias is this referring to?\n\nMethods:\n\nParagraph 1: All CS prior to February 2019 were assessed for eligibility. Please state how far back the records were included? Add month and year that records were first assessed.\n\nParagraph 3: ‘One research assistant…was used to eliminate observer bias’ – this is unclear.\n\nParagraph 4: Duration of hospital stay was recorded as a secondary outcome – was this for the mother, neonate, or both?\n\nParagraph 6: Change ‘bead’ to ‘bed’ head tickets Table 1. Data Key appears to only include the key for some variables?\n\nResults:\n\nRCOG guidelines recommend antenatal corticosteroids for all planned CS before 38+6 weeks gestation, but only 23.2% of patients received antenatal corticosteroids. Provide explanation on why this is the case.\n\nParagraph 1: state how many patients did not received antenatal corticosteroids. Paragraph 6: How much of an increase in gestational age at delivery was associated with a 0.93 times reduction in RD? Number of days?\n\nTable 2: present mean gestational age at delivery as weeks+days not days.\n\nTable 2 includes number and percentage of mothers with pregnancy induced hypertension. However, women with severe maternal hypertension were excluded from the study. Please clarify.\n\nDiscussion:\n\nInsufficient discussion as to why conflicting findings have occurred among different studies on the possible benefits of ACS administration at term prior to CS. Paragraph 8: ‘…due to the design there was loss of information’ – explain what information was lost, and the impact of this on the analysis and findings.\n\nConclusions\n\nProvide an overall conclusion on the findings of this study. Are the findings conclusive or are there next steps/remaining evidence gaps that should be pursued?\n\nData Availability:\n\nUnable to open supplementary material ‘Dexamethasone_final_data_set.sav’.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-827
https://f1000research.com/articles/10-698/v1	30 Jul 21	{ "type": "Research Article", "title": "Low back pain and associated risk factors among medical students in Bangladesh: a cross-sectional study", "authors": [ "Shabbir Ahmed Sany", "Taukir Tanjim", "Md Ikbal Hossain", "Taukir Tanjim", "Md Ikbal Hossain" ], "abstract": "Background: Low back pain (LBP) is one of the leading causes of disability worldwide. Different studies showed the high prevalence of LBP among medical students. However, no study has been conducted on Bangladeshi medical students to estimate the prevalence of LBP. This study evaluated the prevalence, characteristics, and associated risk factors of LBP among medical students in Bangladesh. Methods: A cross-sectional study was conducted from October to December 2020 among randomly selected 270 medical students and medical interns in Faridpur Medical College, Bangladesh, using an online questionnaire. In data analysis, chi-square test and binary logistic regression were performed, and a p-value of < 0.05 was regarded as statistically significant. Results: A total of 207 participants responded fully to the survey, and were included in the analysis. The mean age of the participants was 22.36 ± 1.915 years. The point, 6-month, and 12-month prevalence of LBP was 25.6%, 46.9%, and 63.3%, respectively. In most participants, LBP was localized (53.2%), recurrent (64.9%), undiagnosed (70.8%), affected for a short period (55%), and relieved without receiving any treatment (60.4%). Participants who had a significantly higher 12-month prevalence of LBP included females (72.2% vs 52.2%), with BMI >25 kg/m2 (73.2% vs 56.7%), those who performed physical activity at low to moderate frequency (72.4% vs 29.5%), those who spent > 6 hours/day by sitting (71.3% vs 45.3%), and those who did not have enough rest time (92.7% vs 56%). Ergonomic features of chairs, such as having back support, adjustable back support, and adjustable sitting surface, significantly (p < 0.05) influenced the outcomes. Conclusion: The prevalence of LBP among medical students in Bangladesh was high, and most of the risk factors associated with the high prevalence of LBP were modifiable. Hence, LBP can be prevented by implementing preventive strategies and providing ergonomic training and physical activity facilities.", "keywords": [ "Bangladesh", "Low back pain", "Medical students", "Prevalence", "Risk factors." ], "content": "Introduction\n\nLow back pain (LBP) is considered the single leading cause of disability-related musculoskeletal conditions globally.1–3 Researchers showed that 70-80% of people suffer from LBP at least once in their lifetime2,4 and 18% of the people suffer from LBP at any given time.5 The healthcare-related costs due to LBP are increasing; hence it is becoming a burden in developed countries, as well as in low-income and middle-income countries.3\n\nIndividuals of all ages, including young people and students, can be affected by LBP.6–9 Medical students are at high risk of developing LBP as they have highly demanding curricula that facilitate a sedentary lifestyle, stressful routines, fewer sleeping hours, long hours of study, hospital training, and classes.5,9,10 It is therefore essential to identify the potential risk factors that lead to LBP at an early phase of their career. Prolonged exposure to these risk factors increases wear and tear of the back and consequently rises the injury rate in older age that leads to recurrent and chronic LBP.11–13 Moreover, Burton et al.14 addressed the modification of risk factors as the most crucial prevention strategy of LBP. However, very few studies5,6,10,15–20 have been conducted that evaluated the prevalence and potential risk factors associated with LBP among medical students. These studies showed a high prevalence of LBP. However, regarding the associated risk factors, the findings were inconsistent.\n\nIn Bangladesh, every year, approximately 10,500 students are admitted to 37 public, 70 private, and six armed forces medical colleges.21 To achieve an MBBS (Bachelor of Medicine and Surgery) degree in Bangladesh, students must study for at least five years, and after graduation, they have to complete a compulsory one-year training at the medical college hospital as medical interns. Hence, more than 50,000 students are studying MBBS courses in Bangladesh at any given time. Despite the high number of this specific vulnerable population, no study has been conducted to evaluate the prevalence of LBP among Bangladeshi medical students. Therefore, we aimed to conduct this study to determine the prevalence of LBP and its characteristics and identify the risk factors associated with LBP among medical students of a typical public medical college in Bangladesh.\n\n\nMethods\n\nThis cross-sectional study was conducted on MBBS students (first year to final year) and medical interns in Faridpur Medical College from October to December 2020. Every year, around 120 students are admitted to this medical college; hence typically, there are about 600 students and 120 medical interns in the medical college at any given time.\n\nThe study’s sample size was calculated as 251 using OpenEpi version 3.1, assuming 47.5% as the estimated prevalence rate22 at a 95% confidence level with 5% precision. Because of the possibility of sample loss, the final sample size was determined as 270. Forty-five students from each batch (1st year to 5th year) and 45 medical interns were selected randomly by lottery method using their roll number. The study was reported following the STROBE guidelines for reporting observational studies.23\n\nAn online, standardized, self-administrated questionnaire24 was used for data collection. The questionnaire was in English language and had three sections. Different sections of the questionnaire were adapted from the minimal dataset reported by Deyo et al.,25 and the questionnaires that were validated and used in previous studies.26,27\n\nSection 1 contained five questions related to socio-demographic data, including gender, age, height, weight, and educational level. Body mass index (BMI) was calculated as weight (in kg) divided by height squared (in meters). In Section 2, lifestyle-related questions, such as exercise frequency, smoking habits, total sitting time in a day (in hours), type of activity mostly done in a day, and availability of enough rest time, were inquired. In addition, the ergonomic characteristics (availability of back support, adjustable back support, adjustable sitting surface) of participants’ chairs were also assessed in that section. To determine the prevalence of LBP at different time points, participants were asked whether they suffered from LBP during the survey, the last 6 months, and the last 12 months (dichotomous scale, Yes/No) in Section 3. This section also included data regarding the first appearance, causes, and aggravating factors of LBP; duration and episode of LBP in the last 12 months; the presence of associated leg pain; and type of received treatment.\n\nThe questionnaire was piloted on 15 students before administration in the study to confirm the appropriateness and understandability of questions. The questionnaire was modified according to the feedback, and the responses from the pilot study were not included in the main study.\n\n\n\n• Point prevalence: Presence of LBP at the time of the survey.\n\n• 6-month prevalence: Had at least one episode of LBP in the last 6 months.\n\n• 12-month prevalence: Had at least one episode of LBP in the last 12 months.\n\nDependent variable:\n\n• Low back pain (LBP): LBP is the pain, muscle tension, or stiffness localized below the costal margin and above the inferior gluteal folds with or without leg pain.28\n\nIndependent variables:\n\n• Body mass index (BMI): the weight in kilograms, divided by height in meters squared.29\n\n• Aggravating factors of LBP: The activities that cause the low back symptoms to recur.\n\n• Exercise: A controlled, structured, and repetitive subset of physical activity with an ultimate or intermediate objective to improve or maintain physical fitness.30\n\nWe used the online survey software from Google Drive to conduct the survey and record the responses. The weblink of the questionnaire was sent to selected participants via email with a cover letter that informed the objective of the study and assurance confidentiality of the responses. Participants’ full consent was taken before collecting the data, and they had the right to withdraw anytime without completing the questionnaire. We did not offer any incentives or rewards for participation.\n\nAfter receiving responses from the participants, the accuracy and completeness were checked manually, and data were cleaned when required. All statistical analyses were performed by using IBM Statistical Package for Social Sciences (SPSS) Version 26. Descriptive statistics were calculated, and the continuous variables were summarized as mean and standard deviation, whereas the categorical variables were summarized as frequency and percentage. Bivariate analysis using the chi-square test was performed to evaluate the variables associated with LBP at different time points. In addition, binary logistic regression was applied to determine the relative odds of occurrence of LBP in the last 12 months due to the presence of a particular factor. The results were presented with an adjusted odds ratio (OR) and confidence intervals for 95% (95% CI). All statistical analysis was set at a 5% level of significance (p < 0.05).\n\nPermission was taken from the Ethical Review Committee (ERC) of the institute.\n\n\nResults\n\nA total of 223 subjects responded to the survey, with a response of 82.59%. However, 16 participants did not complete the survey fully; hence they were excluded. Eventually, 167 medical students and 40 medical interns participated entirely in the study and were included in the analysis. Breakdown of the students was: 31 (15%) in the first, 31 (15%) in the second, 30 (14.5%) in the third, 35 (16.9%) in the fourth, and 40 (19.3%) in the final year of MBBS course (Figure 1).\n\nAmong all participants, 44.4% were males, and 55.6% were females. The mean age of the participants was 22.36 ± 1.915 years, ranging between 19 and 27 years. Based on the mean age, participants were divided into ≤ 21, 22 – 24, and ≥ 25 age groups. Regarding weight, participants were divided into two groups, namely, below normal to normal weight (BMI ≤ 25 kg/m2) and above normal weight (BMI > 25 kg/m2). Three out of five participants (61.4%) had BMI ≤ 25 kg/m2.\n\nThe frequency of physical activity was categorized into three groups: Low level (< 4 times/month), moderate level (1-4 times/week), and high level (≥ 5 times/week). Among all participants, almost half (45.4%) performed a low level of physical activity, the majority (83.1%) were non-smokers, nearly half (48.3%) reported that they performed most of their daily activities by sitting, more than two-thirds (69.1%) of participants spent ≥ 6 hours/day in sitting, and four out of five participants (80.2%) had enough rest time. Moreover, the majority (76.3%) used chairs with back support, almost two-thirds (65.2%) used chairs with nonadjustable back support, and more than half (55.6%) used chairs without an adjustable sitting surface (Table 1).\n\nThe point, 6-month, and 12-month prevalence of LBP was 25.6%, 46.9%, and 63.3%, respectively. Nearly two-thirds (65.9%) of participants with LBP informed that they suffered the first episode of LBP after being admitted in medical, while only 5.5% experienced it during the internship. 35.1% of participants reported that they experienced only one episode of LBP, whereas 35.1% experienced 2–3 episodes, and 29.8% experienced more than three episodes in the previous 12 months. More than half of the respondents (55%) had a short duration (1 – 7 days) of LBP, while 8.4% reported they had LBP every day in the past year.72\n\nAs for causes or diagnosis of LBP, the majority (70.8%) reported no diagnosis, therefore had non-specific LBP. More than half of the participants (53.2%) reported no associated leg pain, while 31.2% reported radiated leg pain. Regarding aggravating factors, more than half of the participants (55.2%) reported that LBP worsened when they maintained a static position for a long time followed by bending or twisting (18.8%), lifting any object (8.4%), sudden movement (5.2%), performing repetitive tasks (3.2%) and non-specific (9.1%). Three-fifths of the participants (60.4%) reported their pain relieved without taking any specific treatment while the remaining received different medications in the form of opioid analgesics (22.1%), exercise therapy (9.1%), steroid injection (1.3%), both opioid and exercise therapy (5.2%), and opioid with steroid injection (1.9%) (Table 2).\n\nBivariate analysis showed no significant association between LBP and age groups (p > 0.160) or the education level of participants (p > 0.161) regardless of the time of occurrence (Table 1).\n\nIn contrast, the 6-month and 12-month prevalence of LBP were significantly correlated with gender or being overweight. The number of females with LBP was more than the number of males with LBP during the survey (20.7% vs 29.6%, p = 0.144), in the last 6 months (38% vs 53.9%; p = 0.023) and in the last 12 months (52.2% vs 72.2%; p = 0.003). In addition, participants with BMI > 25 kg/m2 reported the presence of LBP more frequently than the participants with BMI ≤ 25 kg/m2 during survey (22.8% vs 30%), in the past 6 months (39.4% vs 58.8%) and in the last 12 months (56.7% vs 73.8%) (Table 1).\n\nIn the logistic regression analysis, females were 2.3 times more likely to had LBP compared to males (OR: 2.378, 95% CI: 1.334 – 4.236; p = 0.003), and the participants with BMI > 25 kg/m2 were around two times at higher risk of developing LBP than the participants with BMI ≤ 25 kg/m2 (OR: 2.146, 95% CI: 1.167 – 3.947; p = 0.014) in the last 12 months (Table 3).\n\nAccording to the bivariate analysis, the factors that significantly contributed to LBP occurrence in the last 6 months and 12 months were frequency of physical activity, total sitting time per day, availability of rest time, and type of activity mostly done in a day. However, the point prevalence of LBP was significantly correlated with only physical activity and the type of activity mostly done in a day. Results demonstrated that the respondents who performed a high frequency of physical activity, those who spent < 6 hours per day by sitting, those who had enough rest time, and those who did not perform any specific task for a long time had the least prevalence of LBP in all time points compared to their counterparts (Table 1).\n\nResults of logistic regression analysis showed that the participants who performed moderate and low frequency of physical activity were 6.275 times (OR: 6.275, 95% CI: 2.721 – 14.474; p < 0.005), and 6.237 times (OR: 6.237, 95% CI: 2.831 – 13.738, p < 0.005) more likely to develop LBP in last 12 months than the participants who performed a high frequency of physical activity, respectively. Moreover, the odds of LBP were nearly 1.5 times higher among smokers than non-smokers (OR: 1.693, 95% CI: 0.678 – 4.226; p = 0.259), more than three times higher among participants who spent ≥ 6 hours in sitting than those spent < 6 hours (OR: 3.003, 95% CI: 1.629 – 5.533; p < 0.005), and almost 10 times higher among the subjects who had insufficient rest time than those who had enough rest time (OR: 9.943, 95% CI: 2.951 – 33.500; p < 0.005). In addition, the participants who did most of the activity in a day by sitting, standing, or walking, and bending were about 7.2 times (OR: 7.250, 95% CI: 3.660 – 14.359; p < 0.005), 1.6 times (OR: 1.670, 95% CI: 0.585 – 4.772; p = 0.338) and 4.5 times (OR: 4.455, 95% CI: 0.847 – 23.429; p = 0.078) more likely to suffer from LBP in last year compared to the participants who did not perform any activity in a specific position for a long time, respectively (Table 3).\n\nBivariate analysis revealed that the prevalence of LBP, regardless of the time of occurrence, was significantly correlated with the presence of back support, adjustable back support, and adjustable sitting surface of participants’ chairs. Results showed that the participants who had chairs with back support, adjustable back support, and adjustable sitting surface had a lower LBP prevalence than their counterparts (Table 1).\n\nFurther analysis showed that the 12-month prevalence of LBP was about 2.5 times higher among participants who used chairs without back support (OR: 2.414, 95% CI: 1.150 – 5.071; p = 0.020), nearly 5.5 times higher among participants who used chairs without adjustable back support (OR: 5.591, 95% CI: 2.998 – 10.428; p < 0.005), and almost 3.7 times higher among participants who used chairs without adjustable sitting surface (OR: 3.714, 95% CI: 2.049 – 6.732; p < 0.005) compared to their respective reference group (Table 3).\n\n\nDiscussion\n\nThe results of our study indicated that almost half (46.9%) and two-thirds (63.3%) of the participants experienced LBP in the past 6 months and 12 months, respectively, while 25.6% reported LBP at the time of the survey. Compared to this study, 12-month prevalence of LBP was lower among the medical students in Pakistan (38.6%),15 China (40.1%),16 the US (42.8%),17 Malaysia (46.1%),18 India (47.5%),6 Austria (53.4%),10 Serbia (59.5%),5 Brazil (59.9%),19 Saudi Arabia (61.4%),20 and was higher among the medical students in Turkey (96.4%).31 The discrepancy in the LBP prevalence could be from some factors, including the variation of faculty year of study, academic curriculum, methodological heterogenicity, mode of data collection, cross-cultural factors, and subjective perception of pain.32,33\n\nAge\n\nAge is considered one of the risk factors of LBP. Several studies have stated that the prevalence of LBP increases with age,7,34 although some studies revealed that the prevalence of LBP was higher among younger nurses than older nurses.35–37 Contrary to these findings, our study demonstrated no significant relationship between age and prevalence of LBP, which is comparable with several studies.38,39\n\nSex\n\nResults showed that females had a significantly higher prevalence of LBP than males, which was consistent with several studies.5,8,27,40,41 Males are structurally, anatomically, and physiologically different from females, and researchers asserted that females have lower pain thresholds and higher sensitivity to pain than males.42,43 For these reasons, females are more likely to report LBP than males. Although, some studies did not reveal any significant association between LBP prevalence and gender.6,16,18,38,41\n\nWeight\n\nRegarding the participant’s weight, our study showed participants with BMI > 25 kg/m2 had a higher prevalence of LBP than the participants with BMI ≤ 25 kg/m2, which is comparable with the findings of a meta-analysis by Shiri et al.44 and a study by Webb et al.45 Researchers showed that as weight increases, it creates higher pressure on the intervertebral disc and other spine structures, consequently triggers pain.46 However, few studies did not find any association between weight and LBP prevalence.7,31,38,41\n\nYear of study\n\nSeveral studies demonstrated a significant correlation between the year of study with musculoskeletal pain (MSP), including LBP among medical students.9,18,19,41 Two of these studies revealed an increased association of year of study with LBP,9,19 while others found that LBP prevalence was higher among third-year medical students.41,47 Amelot et al.41 stated that the third year is the first clinical year; hence, students might find it challenging to organize their schedule between theoretical lessons and hospital internships, which consequently causes psychological disturbance and LBP. In addition, Aggarwal et al.6 revealed that the prevalence of LBP increased with each class year, although the relationship was not significant. They mentioned workload, prolonged standing during clinical classes, and psychological factors as the reasons for that trend.6 However, the results of our study indicated that the second year students had a higher prevalence of LBP than others. The reason could be that the second year students need to appear for their first professional exam, and at that time, different factors, including more study hours, stress, and psychological imbalance, could evoke LBP. In contrast, few studies did not find any association between MSP prevalence, including LBP, and study year among medical students.15,20,38,39\n\nSmoking\n\nShiri et al.48 found the correlation between smoking habits and LBP prevalence in their meta-analysis, and they reported that smokers and ex-smokers had a higher prevalence of LBP than non-smokers. Other studies also revealed that medical students who smoked were more likely to suffer LBP.38,49 In contrast, our study revealed no association between smoking habit and LBP prevalence at any time point, in accordance with other studies.9,15,16,20,22,50 This discrepancy could be for the low number of smokers as it can be inferred that studies with less than 10% prevalence of smoking did not find any association between smoking habits and LBP prevalence. Moreover, research showed a positive relationship between the risk of LBP and smoking dose.51 Our study did not assess the intensity of smoking and the duration of exposure to the habit.\n\nSitting time\n\nProlonged sitting is another risk factor of LBP52,53 as it increases spinal compression load and dysfunction of paraspinal muscles.54,55 Nyland and Grimmer53 affirmed that ‘a sitting and looking down position’ was a potential risk factor of LBP, and studies demonstrated a positive correlation between staying in a sitting position for a long time and LBP.31,38,56 Our study revealed that participants who spent ≥ 6 hours sitting had a significantly higher prevalence of LBP than participants who spent < 6 hours sitting. Conversely, Hartvigsen et al.,57 Spyropoulos et al.,27 and Tavares et al.39 reported no association between sitting time and LBP prevalence.\n\nPhysical activity\n\nGenerally, medical students remain busy with their classes and hospital visits, making their life sedentary. A study on medical students of Delhi showed that only one-third of the medical students performed the recommended amount of physical activity.58 Physical exercise or regular sports practice are encouraged in different studies as it helps to minimize the rate of LBP prevalence and effective for primary and secondary prevention of LBP.59 The findings of our study demonstrated a significant relationship between the prevalence of LBP and frequency of physical activity, which was supported by previous studies.5,41 Moreover, The American College of Sports Medicine recommended that to promote and maintain health, physical activity should be performed for at least 30 minutes at moderate intensity with a minimum frequency of 5 days/week.60,61 The findings of our study were in line with this recommendation as the participants who performed high frequency (≥ five days/week) of physical activity had a significantly lower prevalence of LBP than those who performed low or moderate frequency (< five days/week) of physical activity. However, several studies did not reveal any significant association between physical activity and LBP prevalence among medical students.6,19,27,31,49\n\nWe found that in the majority of cases (64.9%), LBP was recurrent, and more than half (55%) of the participants had a short annual duration (1–7 days) of LBP which was consistent with previous studies on Greek public office workers,27 and nursing students and graduate nurses.26 That indicated the high chance of LBP recurrence and chronicity in the future. In addition, most of the participants (53.2%) had localized LBP, and 31.2% reported radiated leg pain, which was consistent with several studies.62,63\n\nEl-soud et al.63 found that LBP remained undiagnosed in most cases. In agreement with that result, our study also revealed that 70.8% of the subjects had LBP without a diagnosis. Regarding treatment, the majority (60.4%) of participants reported they did not seek any medication for their symptoms, which is comparable with the findings of studies from Wong et al. (65.9%),62 Hafeez et al. (64.5%)49 and Falavigna et al. (67.3%).19 Moreover, maintaining a specific posture, including standing and sitting, for a long time was the most cited (55.2%) aggravating factor for LBP in our study. In agreement with our finding, previous studies64 also reported LBP mostly worsened after prolonged standing/sitting.\n\nHestbaek et al.65 claimed that the lifetime prevalence of LBP increases markedly between 12 and 22 years of age. Our study came to the same conclusion as we found that 28.7% and 65.7% of participants had LBP before commencing their medical studies and during medical studies, respectively; and more than half (50.4%) of the participants who had LBP in the last 12 months aged ≤ 22 years. That indicated the importance of implementing the LBP prevention strategies before or at the beginning of the medical course.\n\nIndividuals suffering from different musculoskeletal pains due to prolonged sitting are recommended to use ergonomically sound chairs as the chair directly influences body alignment or posture.66,67 Researchers concluded that scarcity of knowledge, understanding, or application of ergonomics’ basic principles and rules could lead to LBP.68 Moreover, it is vital to adjust the height of the sitting surface of the chair to meet individual biomechanical requirements so that they can use the desk with ease without aggravating the spine.69,70 Our results showed that the participants who used chairs with back support, adjustable back support, and the adjustable sitting surface had a significantly lower prevalence of LBP compared to their counterparts at all time points. However, previous studies did not show any significant association between LBP prevalence and using a chair with back support27,49 or using a chair with an adjustable sitting surface.27 Whereas Mohsen et al.71 and Spyropoulos et al.27 demonstrated that LBP prevalence could be lowered using chairs with back support.\n\nThis study was the first study that evaluated the prevalence of LBP among Bangladeshi medical students, and the response rate of the study was satisfactory. However, our study has some limitations that should be acknowledged. First, as we included students from only one medical college, the outcomes may not fully represent the situation for all medical students in Bangladesh. Second, the study outcomes relied solely on the self-administrated questionnaire, and we did not perform any medical tests to confirm the presence of LBP. Therefore, information bias and subject bias cannot be ruled out. Moreover, the difficulty in recalling arises the possibility of over-or underreporting of LBP as participants reported the presence of LBP in the last one year, which entirely depended on the participants’ memory. Finally, as it was a cross-sectional study, the exposure to risk factors and outcomes were evaluated concurrently. Hence, we showed only the relationship but could not establish any evidence of the causal association between exposure and LBP occurrence.\n\n\nConclusion\n\nThe overall results of our study demonstrated the high prevalence of LBP among Bangladeshi medical students and indicated the necessity of formulating and implementing comprehensive preventive strategies. The majority of the risk factors are modifiable. Hence, initiatives can be taken to inspire them to avoid those risk factors, which could improve medical students’ and future doctors’ overall health and quality of life. Students should be encouraged to perform the recommended amount of physical activity by providing education and facilities and reserving a couple of hours exclusively for exercise and sports activities. Moreover, education on ergonomics and providing sound ergonomic chairs to the students could help minimize LBP prevalence.\n\nIn this study, we included students only from one medical college. Future studies should be undertaken with a larger sample size by including students from more than one medical college. Epidemiological longitudinal studies should be conducted to confirm the association of risk factors with LBP.\n\n\nData availability\n\nMendeley Data: Low back pain and associated risk factors among medical students in Bangladesh: A cross-sectional study. https://doi.org/10.17632/mfky2jttwp.3.72\n\nThe project contains the following underlying data:\n\n• Raw dataset.xlsx\n\nMendeley Data: Low back pain and associated risk factors among medical students in Bangladesh: A cross-sectional study. https://doi.org/10.17632/mfky2jttwp.3.72\n\nThe project contains the following extended data:\n\n• Course Evaluation – Google Forms.pdf\n\n• STROBE Checklist.doc\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgments\n\nThe authors are indebted to the study participants. The authors’ special gratitude to all batch captains of FMC and supervisors of the study.\n\n\nReferences\n\nVos T, et al.: Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016; 388: 1545–1602. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMaher C, Underwood M, Buchbinder R: Non-specific low back pain. Lancet. 2017; 389: 736–747. PubMed Abstract \| Publisher Full Text\n\nHartvigsen J, et al.: What low back pain is and why we need to pay attention. Lancet. 2018; 391: 2356–2367. PubMed Abstract \| Publisher Full Text\n\nNguyen TH, Randolph DC: Nonspecific low back pain and return to work. Am. Fam. Physician. 2007; 76. PubMed Abstract\n\nVujcic I, et al.: Low Back Pain among Medical Students in Belgrade (Serbia): A Cross-Sectional Study. Pain Res. Manag. 2018; 2018. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAggarwal N, Anand T, Kishore J, et al.: Low back pain and associated risk factors among undergraduate students of a medical college in Delhi. Educ. Heal. Chang. Learn. Pract. 2013; 26: 103–108. PubMed Abstract \| Publisher Full Text\n\nNordin NAM, Singh DKA, Kanglun L: Low back pain and associated risk factors among health science undergraduates. Sains Malaysiana. 2014; 43: 423–428.\n\nSmith DR, Leggat PA: Prevalence and distribution of musculoskeletal pain among Australian medical students. J. Musculoskelet. Pain. 2007; 15: 39–46. Publisher Full Text\n\nAlgarni AD, et al.: The Prevalence of and Factors Associated with Neck, Shoulder, and Low-Back Pains among Medical Students at University Hospitals in Central Saudi Arabia. Pain Res. Treat. 2017; 2017. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMoroder P, Runer A, Resch H, et al.: Low back pain among medical students. Acta Orthop. Belg. 2011; 77: 88–92. PubMed Abstract\n\nBrennan G, Shafat A, Donncha C, et al.: Lower back pain in physically demanding college academic programs: A questionnaire based study. BMC Musculoskelet. Disord. 2007; 8: 1–8. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHarreby M, Neergaard K, Hesselsoe G, et al.: Are radiologic changes in the thoracic and lumbar spine of adolescents risk factors for low back pain in adults?: A 25-year prospective cohort study of 640 school children. Spine (Phila. Pa. 1976). 1995; 20: 2298–2302. PubMed Abstract \| Publisher Full Text\n\nG B: The incidence of back pain and headache among Swedish school children. Qual. Life Res. 1994; 3(Suppl 1). PubMed Abstract \| Publisher Full Text\n\nBurton AK, Clarke RD, McClune TD, et al.: The natural history of low back pain in adolescents. Spine (Phila. Pa. 1976). 1996; (21): 2323–2328. PubMed Abstract \| Publisher Full Text\n\nHaroon H, Mehmood S, Imtiaz F, et al.: Musculoskeletal pain and its associated risk factors among medical students of a public sector university in Karachi, Pakistan. J. Pak. Med. Assoc. 2018; 68: 682–688. PubMed Abstract\n\nSmith DR, Wei N, Ishitake T, et al.: Musculoskeletal disorders among Chinese medical students. Kurume Med. J. 2005; 52: 139–146. PubMed Abstract \| Publisher Full Text\n\nKennedy C, Kassab O, Gilkey D, et al.: Psychosocial factors and low back pain among college students. J. Am. Coll. Heal. 2008; 57: 191–196. PubMed Abstract \| Publisher Full Text\n\nAlshagga MA, et al.: Prevalence and factors associated with neck, shoulder and low back pains among medical students in a Malaysian Medical College. BMC Res. Notes. 2013; 6. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFalavigna A, et al.: Increased prevalence of low back pain among physiotherapy students compared to medical students. Eur. Spine J. 2011; 20: 500–505. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDighriri Y, et al.: Prevalence and associated factors of neck, shoulder, and low-back pains among medical students at Jazan University, Saudi Arabia: A cross-sectional study. J. Fam. Med. Prim. Care. 2019; 8: 3826. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nList of medical colleges in Bangladesh - Wikipedia. http\n\nAggarwal N, Anand T, Kishore J, et al.: Low back pain and associated risk factors among undergraduate students of a medical college in Delhi. Educ. Heal. Chang. Learn. Pract. 2013; 26: 103–108. PubMed Abstract \| Publisher Full Text\n\nvon E E, et al.: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J. Clin. Epidemiol. 2008; 61: 344–349. PubMed Abstract \| Publisher Full Text\n\nSany SA, Tanjim T, Hossain MI: Low back pain and associated risk factors among medical students in Bangladesh: A cross-sectional study.2021; vol. 3. Reference Source\n\nDeyo RA, et al.: Report of the NIH task force on research standards for chronic low back pain. J. Pain. 2014; 15: 569–585. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMitchell T, O’Sullivan PB, Burnett AF, et al.: Low back pain characteristics from undergraduate student to working nurse in Australia: A cross-sectional survey. Int. J. Nurs. Stud. 2008; 45: 1636–1644. PubMed Abstract \| Publisher Full Text\n\nSpyropoulos P, et al.: Prevalence of low back pain in Greek public office workers. Pain Physician. 2007; 10: 651–660. PubMed Abstract\n\nChou R: Low back pain (chronic). BMJ Clin Evid. 2010; 2010. PubMed Abstract \| Free Full Text\n\nNuttall FQ: Body mass index: Obesity, BMI, and health: A critical review. Nutr Today. 2015; 50: 117–128. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCaspersen C, Powell K, Gregory C: Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985;Mar-Apr; 100(2): 126–31. US Natl. Libr. Med. 100 (2), 126–131 (1985). PubMed Abstract \| Free Full Text\n\nYucel H, Torun P: Incidence and Risk Factors of Low Back Pain in Students Studying at a Health University. Bezmialem Sci. 2016; 4: 12–18. Publisher Full Text\n\nFatoye F, Gebrye T, Odeyemi I: Real-world incidence and prevalence of low back pain using routinely collected data. Rheumatol Int. 2019; 39: 619–626. PubMed Abstract \| Publisher Full Text\n\nLeggat PA, Smith DR, Clark MJ: Prevalence and correlates of low back pain among occupational therapy students in Northern Queensland. Can. J. Occup. Ther. 2008; 75: 35–41. PubMed Abstract \| Publisher Full Text\n\nGhilan K, et al.: Low back pain among female nurses in Yemen. Int. J. Occup. Med. Environ. Health. 2013; 26(605–614). PubMed Abstract \| Publisher Full Text\n\nYassi A, et al.: The epidemiology of back injuries in nurses at a large Canadian tertiary care hospital: Implications for prevention. Occup. Med. (Chic. Ill). 1995; 45: 215–220. PubMed Abstract \| Publisher Full Text\n\nKarahan A, Kav S, Abbasoglu A, et al.: Low back pain: Prevalence and associated risk factors among hospital staff. J. Adv. Nurs. 2009; 65: 516–524. PubMed Abstract \| Publisher Full Text\n\nBelay MM, Worku A, Gebrie S, et al.: Epidemiology of low back pain among nurses working in public hospitals of Addis Ababa, Ethiopia. East Cent. African J. Surg. 2016; 21: 113. Publisher Full Text\n\nIlic I, et al.: Prevalence and correlates of low back pain among undergraduate medical students in Serbia, a cross-sectional study. PeerJ. 2021; 9: e11055. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTavares C, Salvi CS, Nisihara R, et al.: Low back pain in Brazilian medical students: a cross-sectional study in 629 individuals. Clin. Rheumatol. 2019; 38: 939–942. PubMed Abstract \| Publisher Full Text\n\nSikiru L, Shmaila H: Prevalence and risk factors of low back pain among nurses in Africa: Nigerian and Ethiopian specialized hospitals survey study. East Afr. J. Public Health. 2009; 6(22–25). PubMed Abstract \| Publisher Full Text\n\nAmelot A, et al.: Low Back Pain among Medical Students: A Burden and an Impact to Consider! Spine (Phila. Pa. 1976). 2019; (44): 1390–1395. PubMed Abstract \| Publisher Full Text\n\nKeriri HM: Prevalence and risk factors of low back pain among nurses in operating rooms, Taif, Saudi Arabia.2013; (1). PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMakris UE, Fraenkel L, Han L, et al.: Epidemiology of restricting back pain in community-living older persons. J. Am. Geriatr. Soc. 2011; 59: 610–614. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nShiri R, Karppinen J, Leino-Arjas P, et al.: The association between obesity and low back pain: A meta-analysis. Am. J. Epidemiol. 2010; 171: 135–154. PubMed Abstract \| Publisher Full Text\n\nWebb R, et al.: Prevalence and Predictors of Intense, Chronic, and Disabling Neck and Back Pain in the UK General Population. Spine (Phila. Pa. 1976). 2003; (28): 1195–1202. PubMed Abstract \| Publisher Full Text\n\nAndrusaitis SF, Oliveira RP, Barros Filho TEP: Study of the prevalence and risk factors for low back pain in truck drivers in the state of São Paulo, Brazil. Clinics. 2006; 61: 503–510. PubMed Abstract \| Publisher Full Text\n\nAlshagga MA, et al.: Prevalence and factors associated with neck, shoulder and low back pains among medical students in a Malaysian Medical College. BMC Res. Notes. 2013; 6. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nShiri R, Karppinen J, Leino-Arjas P, et al.: The Association between Smoking and Low Back Pain: A Meta-analysis. Am. J. Med. 2010; 123. PubMed Abstract \| Publisher Full Text\n\nHafeez K, et al.: Back pain - are health care undergraduates at risk? Iran. J. Public Health. 2013; 42: 819–825. PubMed Abstract \| Free Full Text\n\nAlShayhan FA, Saadeddin M: Prevalence of low back pain among health sciences students. Eur. J. Orthop. Surg. Traumatol. 2018; 28: 165–170. PubMed Abstract \| Publisher Full Text\n\nAlkherayf F, Wai EK, Tsai EC, et al.: A. C. Daily smoking and lower back pain in adult Canadians: the Canadian Community Health Survey. J. Pain Res. 2010; 3(155). PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLis AM, Black KM, Korn H, et al.: Association between sitting and occupational LBP. Eur Spine J. 2007; 16: 283–298. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNyland LJ, Grimmer KA: Is undergraduate physiotherapy study a risk factor for low back pain? A prevalence study of LBP in physiotherapy students. BMC Musculoskelet. Disord. 2003; 4: 1–12. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nCallaghan JP, McGill SM: Low back joint loading and kinematics during standing and unsupported sitting. Ergonomics. 2001; 44: 280–294. PubMed Abstract \| Publisher Full Text\n\nSolomonow M, et al.: Muscular dysfunction elicited by creep of lumbar viscoelastic tissue. J. Electromyogr. Kinesiol. 2003; 13: 381–396. PubMed Abstract \| Publisher Full Text\n\nDiaz-Caballero AJ, Gómez-Palencia IP, Díaz-Cárdenas S: Ergonomic factors that cause the presence of pain muscle in students of dentistry. Med. Oral Patol. Oral Cir. Bucal. 2010; 15. PubMed Abstract\n\nHartvigsen J, Leboeuf-Yde C, Lings S, et al.: Review Article: Is sitting-while-at-work associated with low back pain? A systematic, critical literature review. Scand J Public Health. 2000; 28: 230–239. PubMed Abstract\n\nAnand T, Tanwar S, Kumar R, et al.: Knowledge, attitude, and level of physical activity among medical undergraduate students in Delhi. Indian J. Med. Sci. 2011; 65: 133–142. PubMed Abstract \| Publisher Full Text\n\nHenchoz Y, Kai-Lik So A: Exercise and nonspecific low back pain: A literature review. Joint Bone Spine. 2008; 75: 533–539. PubMed Abstract \| Publisher Full Text\n\nBennett GG, Wolin KY, Puleo EM, et al.: Awareness of national physical activity recommendations for health promotion among US adults. Med. Sci. Sports Exerc. 2009; 41: 1849–1855. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGarber CE, et al.: Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Med. Sci. Sports Exerc. 2011; 43: 1334–1359. Publisher Full Text\n\nWong T, Teo N, Kyaw M: Prevalence and Risk Factors Associated with Low Back Pain Among Health Care Providers in a District Hospital. Malaysian Orthop. J. 2010; 4: 23–28. Publisher Full Text\n\nEl-Soud AMA, El-Najjar AR, El-Fattah NA, et al.: Prevalence of low back pain in working nurses in Zagazig University Hospitals: an epidemiological study. Egypt. Rheumatol. Rehabil. 2014; 41: 109–115. Publisher Full Text\n\nJohnson O, Edward E: Prevalence and Risk Factors of Low Back Pain among Workers in a Health Facility in South–South Nigeria. Br. J. Med. Med. Res. 2016; 11: 1–8. Publisher Full Text\n\nHestbaek L, Leboeuf-Yde C, Kyvik KO: Is comorbidity in adolescence a predictor for adult low back pain? A prospective study of a young population. BMC Musculoskeletal Disorders. 2006; 7. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAarås A, Horgen G, Bjørset HH, et al.: Musculoskeletal, visual and psychosocial stress in VDU operators before and after multidisciplinary ergonomic interventions. A 6 years prospective study - Part II. Appl. Ergon. 2001; 32: 559–571. PubMed Abstract \| Publisher Full Text\n\nVan Niekerk SM, Louw QA, Hillier S: The effectiveness of a chair intervention in the workplace to reduce musculoskeletal symptoms. A systematic review. BMC Musculoskeletal Disorders. 2012; 13: 145. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGopinadh A, et al.: Ergonomics and musculoskeletal disorder: As an occupational hazard in dentistry. J. Contemp. Dent. Pract. 2013; 14: 299–303. PubMed Abstract \| Publisher Full Text\n\nOffice Chair: How to Reduce Back Pain?Reference Source\n\nChapter 4: Body Alignment, Posture, And Gait. Reference Source\n\nMakhsous M, Lin F, Hendrix RW, et al.: Sitting with adjustable ischial and back supports: Biomechanical changes. Spine (Phila. Pa. 1976). 2003; 28: 1113–1121. PubMed Abstract \| Publisher Full Text\n\nSany SA, Tanjim T, Hossain MI: Low back pain and associated risk factors among medical students in Bangladesh: A cross-sectional study. Mendeley Data. Publisher Full Text" }	[ { "id": "93460", "date": "27 Sep 2021", "name": "Mohammad Mostafa Zaman", "expertise": [ "Reviewer Expertise Epidemiology of NCD risk factors", "rheumatic disorders" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nLBP is a common problem in Bangladesh and elsewhere. Data for medical students are lacking. This survey has been done among students of a medical college in Bangladesh (Faridpur Medical College). The manuscript will contribute to LBP prevention measures in the medical profession. However, there are points of concern:\n1. Abstract\nThe objective was to evaluate the prevalence. The authors have not done any evaluation. \"Evaluated\" could be replaced by \"determined\".\n\n70.8% were undiagnosed is not correct; the authors have not diagnosed LBP patients that were not diagnosed before.\n\n2. Introduction\nThe literature review is incomplete. National survey findings have been published in 2020, I do not see it in the review. For example, Zahid-Al-Quadir et al.1 reported the burden of LBP in the general population, and the introduction could build on this and the discussion could also benefit from adding this.\n3. Methods\nSample size calculation is based on an Indian study, which is very high. Prevalence in Bangladesh is much lower. There was another COPCORD study that reported LBP among other rheumatic disorders.\n\nLogistic regression analysis was done for a 12-month recall period, which has a potential of recall bias; this could be done for point prevalence.\n\nEthical clearance has been obtained from the institute. Which institute?\n4. Results\nThe results described have many digits after the decimal point; these could be up to one decimal point. No message will be lost by removing extra decimal points.\n\nDividing a small number of students (207) into so many age and educational groups is meaningless. There are hardly any points of implications by age and educational years, the differences in education and age are obviously very narrow. The message of the study could be generated for one group only. At best, the results could be presented for male and female, and students and interns.\n\nProviding both CIs and P-values is redundant information. The authors could put esoteric marks against significant CIs (Table 3).\n5. Discussion\nThe discussion is quite long. There are so many subheadings used because authors have discussed all variables under study. They could highlight the main points of the message that the study transmits to the readers. For example, years cannot be changed or intervened separately but it has a lengthy description.\n\nThe last paragraph under the Conclusion is a repetition of the limitations mentioned above; this could be deleted.\n6. Reference\nReference 72 is a duplication of reference 24.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "7759", "date": "08 Feb 2022", "name": "Shabbir Ahmed Sany", "role": "Author Response", "response": "Thank you for giving us the opportunity to submit a revised draft of our manuscript. We appreciate the time and effort you have dedicated to providing your valuable feedback on the manuscript. We are grateful to you for your insightful comments on our paper. We have been able to incorporate changes to reflect most of your suggestions. Here is a point-by-point response to the reviewers' comments and concerns. Abstract: The objective was to evaluate the prevalence. The authors have not done any evaluation. \"Evaluated\" could be replaced by \"determined\". Response: Thank you for your suggestion. We have replaced the word 'evaluated' with 'determined.' 70.8% were undiagnosed is not correct; the authors have not diagnosed LBP patients that were not diagnosed before. Response: We agree with this comment. 70.8% were non-specific LBP rather undiagnosed. We have corrected it. Introduction: The literature review is incomplete. National survey findings have been published in 2020, I do not see it in the review. For example, Zahid-Al-Quadir et al.1 reported the burden of LBP in the general population, and the introduction could build on this and the discussion could also benefit from adding this. Response: Thank you for your suggestion. We have made the changes as you suggested. Methods: Sample size calculation is based on an Indian study, which is very high. Prevalence in Bangladesh is much lower. There was another COPCORD study that reported LBP among other rheumatic disorders. Response: Thank you for pointing this out. However, the prevalence of LBP is relatively higher among the people involved with health professions. Physiotherapists in Bangladesh, for instance, had a 60.8% prevalence of LBP, which is higher than other professions [1]. Moreover, our study was the first study that determined LBP prevalence among Bangladeshi medical students. Therefore, we calculated the sample size based on an Indian study as the Bangladeshi medical students have relatively similar curriculum, clinical class exposure, study load, and social and cultural demographics as Indian medical students. Logistic regression analysis was done for a 12-month recall period, which has a potential of recall bias; this could be done for point prevalence. Response: You have raised an important point here. However, determining risk factors was one of the study's primary objectives; we opted to do logistic regression analysis for 1-year prevalence instead of point prevalence despite the potential of recall bias. Point prevalence could be too short a period to conclude the effect of exposure of any particular risk factor. Ethical clearance has been obtained from the institute. Which institute? Response: Thank you for pointing this out. We have corrected it. The ethical Permission was taken from the Ethical Review Committee (ERC) of Faridpur Medical College. Results: The results described have many digits after the decimal point; these could be up to one decimal point. No message will be lost by removing extra decimal points. Response: Agree. We have incorporated your suggestion throughout the manuscript. Dividing a small number of students (207) into so many age and educational groups is meaningless. There are hardly any points of implications by age and educational years, the differences in education and age are obviously very narrow. The message of the study could be generated for one group only. At best, the results could be presented for male and female, and students and interns. Response: Thank you for your comment. However, previous studies showed a significant association between medical students' age and education years and LBP prevalence. For this reason, we wanted to observe it among Bangladeshi medical students, and we divided the students into three age groups and academic years. We found that the 2nd year medical students had a higher prevalence of LBP, although the difference was not significant. Providing both CIs and P-values is redundant information. The authors could put esoteric marks against significant CIs (Table 3). Response: Thank you for pointing this out. We have modified Table 3 as you suggested. Discussion: The discussion is quite long. There are so many subheadings used because authors have discussed all variables under study. They could highlight the main points of the message that the study transmits to the readers. For example, years cannot be changed or intervened separately but it has a lengthy description. Response: Thank you for your suggestion. We have made the changes as you suggested. The last paragraph under the Conclusion is a repetition of the limitations mentioned above; this could be deleted. Response: We have deleted the line as you suggested. Reference: Reference 72 is a duplication of reference 24. Response: Thank you for pointing this out. We have corrected it. [1] R. Mondal, R. C. Sarker, S. Akter, P. C. Banik, and S. K. Baroi, “Prevalence of low back pain and its associated factors among physiotherapists in Dhaka city of Bangladesh in 2016,” J. Occup. Heal. Epidemiol., vol. 7, no. 2, pp. 70–74, 2018." } ] }, { "id": "95514", "date": "18 Oct 2021", "name": "Matthew Chiwaridzo", "expertise": [], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThank you for the opportunity to review this interesting manuscript.\nAlthough the study addresses an interesting research question for Bangladesh, and perhaps other countries, there is more detail that I would like to see in the introduction and methods sections, as well as integration of a few additional references and concepts throughout the manuscript. As such, this manuscript will require minor revisions to meet the criteria for indexing.\nAs the research design is observational, the authors are commended for applying the STROBE guidelines (available via the equator network at http://www.equator-network.org/reporting-guidelines/).\nIntroduction\nThis paper needs to strongly emphasise its unique contribution to the literature base in the context of what other authors have already researched and reported with regards to low back pain among medical students. LBP among medical students or generally university students is a well-researched area globally with studies from India, Pakistan, China, USA, Brazil, South Africa, Zimbabwe, Austria, and Malaysia.\n\nThe theoretical perspective to the problem is narrow in light of the many studies that have been conducted to answer the research question the authors are posing. Admittedly, the authors pointed many studies reporting a high prevalence of LBP among medical students from elsewhere.\n\nThe authors should briefly describe the results of some of the referenced studies in the background so that we can understand the theoretical background of this study.\nWhat was the prevalence of LBP among medical students from other studies? Which type of LBP was investigated and how was the investigation carried out? Where were these studies carried out and how do the results of these few studies mentioned in the background apply or not apply to the Bangladesh medical students’ situation? What factors affect the extrapolation of results? In what way are medical students from Bangladesh different from medical students from other countries like India, Pakistan for example?\n\nThe authors should also highlight the contextual background underpinning the conduction of the study in Bangladesh, Faridpur Medical College.\nWhat prompted the authors to want to do this study? What local problem justifies this study? What was observed by the authors among medical students in Bangladesh strongly justifying the need for this study?\n\nI commend the authors for giving us a brief narration of the MBBS programme but more can be added to show how exposed the students are to LBP and what exposes them. How is that exposure so unique to the Bangladeshis?\n\nThe authors are reminded that a statement like this “…no study has been conducted to evaluate the prevalence of LBP among Bangladeshi medical students” is not a sound and adequate justification. What is the problem now that has prompted an investigation into the prevalence of LBP and associated factors among medical students in Bangladesh particularly in the setting the study was conducted? Identification of the specific problem in Bangladesh makes the study uniquely different from similar studies conducted elsewhere.\n\nProvide a hint on the significance of this study in your context.\nMethods\nClearly provide details of the psychometric properties of the LBP questionnaire used in the study. How was the questionnaire tested for reliability and logical validity against the set objectives?\n\nKindly reference your operational variables such as point prevalence.\n\nNot clear whether the authors are addressing non-specific or specific LBP, acute vs chronic until the results section.\n\nReference 6 is the same as reference 22. Kindly check and address.\n\nFor Sample size calculation: Which recall period (point, 6-month or 12-month) was used for the estimation of the sample size? Kindly provide a justification for adopting a prevalence figure from the following study by Aggarwal et al., 20171 to inform your sample size calculation.\n\n“Because of the possibility of sample loss, the final sample size was determined as 270”: Be clear how that was arrived at.\n\nDid the authors check the continuous variables for normality first, and if so what tests were used?\n\nClarify the Inclusion and exclusion criteria of the participants.\n\nThe Ethical approval number from the “institute” should be provided.\nResults\nYour final sample size was less than the calculated minimum sample size?\n\nThe use of a flow chart is commendable.\n\nStatistical analysis is appropriate and well explained.\nDiscussion and conclusion\nMay I suggest removing sub-headings in the discussion section for clarity.\n\nThe first paragraph of the discussion should summarise the main findings from the study addressing the main research question.\n\nDiscuss briefly your findings on the association between age and LBP as they contrasted many findings from the literature.\n\nStudy limitations are well explained.\n\n“The overall results of our study demonstrated the high prevalence of LBP among Bangladeshi medical students and indicated the necessity of formulating and implementing comprehensive preventive strategies”: May I suggest you expand briefly on the possible preventative strategies based on your study findings. This is the most important part of this study. What can be done to curtail the problem of LBP among medical students given contextual information and study results?\n\nReferences\n\nLack of consistency in referencing style in the reference list.\n\nReferences 6 and 22 duplicated.\n\nAdd URL links for internet-derived references and dates accessed.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "7760", "date": "08 Feb 2022", "name": "Shabbir Ahmed Sany", "role": "Author Response", "response": "Thank you for giving us the opportunity to submit a revised draft of our manuscript. We would like to thank you for your insightful comments on the paper, as these comments led us to improve the quality of the manuscript. We took into consideration all comments and concerns in the paper. Detailed responses are given below: Introduction: Thank you for your valuable suggestion. We have made some changes as you suggested, especially we described the necessity of conducting the current study. Although several studies have been conducted globally to determine the prevalence of LBP, the results were inconsistent. Particularly regarding the risk factors, the results were contradictory as the socio-demographic factors of participants, study design, and exposure to risk factors were not the same. Therefore, this study was conducted to estimate the prevalence of LBP among medical students of Bangladesh. The results of this study will help to better know about the risk factors and their impact. We can also compare the results with other studies which will help to examine the validity of evidence and take initiatives to prevent LBP. We have also included the studies that determined LBP prevalence among medical students of different countries. Methods: The questionnaire was piloted on 15 students before administration in the study to confirm the validity and reliability. The reference for the definition of operational variables was included. Determining the acute vs. chronic, non-specific vs. specific LBP was not the study's primary aim. We just showed the percentage of participants who had non-specific and specific LBP. Test of Normality for continuous variables was not performed as we categorized the continuous variables for analysis. We included the inclusion and exclusion criteria briefly as you suggested. No formal ethical approval was required from the institution; hence, no approval number was provided. The intuition requires formal ethical approval for clinical trials involving human participants. We followed the STROBE guidelines. The checklist of the STROBE guidelines can be found at the Mendeley data repository1. Results: A flow chart was included as 'Figure 1', which demonstrated the different phases of the study. Two hundred twenty-three participants responded, and then 16 were excluded as they did not respond fully. Therefore, a total of 207 respondents were included for analysis. Discussion and conclusion: Changes were made where you suggested. Some sub-headings were removed for clarity. The association between age and prevalence of LBP was discussed under the subheading titled 'Socio-demographic factors and LBP prevalence.' The preventive measure was discussed briefly. It would have been better to expand it. However, in the case of our study, it seems slightly out of scope. Future studies involving medical students with more than one medical college are warranted for better evidence and giving the appropriate recommendation for implementing preventive measures. References: The correction was done as you suggested. The reference style was autogenerated by using Mendeley software. Later it was published following the journal’s formatting style. 1. Sany, Shabbir Ahmed; Tanjim, Taukir; Hossain, Md Ikbal (2021), “Low back pain and associated risk factors among medical students in Bangladesh: A cross-sectional study”, Mendeley Data, V4, doi: 10.17632/mfky2jttwp.4." } ] } ]	1	https://f1000research.com/articles/10-698
https://f1000research.com/articles/11-309/v1	14 Mar 22	{ "type": "Case Report", "title": "Case Report: Mitral valve obstruction by metastatic malignant phyllodes tumor", "authors": [ "Chamtouri Ikram", "Amdouni Nesrine", "Kaddoussi Rania", "Ahlem Bellalah", "Kortas Chokri", "Achour Asma", "Joober Sameh", "Maatouk Faouzi", "Amdouni Nesrine", "Kaddoussi Rania", "Ahlem Bellalah", "Kortas Chokri", "Achour Asma", "Joober Sameh", "Maatouk Faouzi" ], "abstract": "Cardiac metastases from phyllodes tumors (PTs) are rare. Herein, we report a case of a 37-year-old female patient with a history of borderline breast PTs, admitted to the cardiology department for acute cardiac failure revealing concomitant cardiac and pulmonary metastases of malignant PTs. Cardiac metastasis occurred through direct extension from pulmonary metastasis to the left atrium via the right inferior pulmonary vein, causing severe mitral valve obstruction. Although the metastasis was surgically removed, the patient had an uncommon complication, which led to acute heart failure and huge relapse resulting in her death.", "keywords": [ "Breast cancer", "cardiac metastasis", "mitral stenosis", "acute heart failure" ], "content": "List of abbreviations\n\nCT: computed tomography\n\nLA: left atrium\n\nLSPV: left superior pulmonary vein\n\nMRI: magnetic resonance imaging\n\nPts: Phyllodes tumors\n\nTTE: trans thoracic echocardiography\n\n\nBackground\n\nPhyllodes tumors (PTs) represent a rare category of breast neoplasm, with a prevalence accounting for <1% of all breast tumors.1 PTs predominantly occur in women aged 35-50 years,2 and they range from benign to malignant forms according to the histological features.3 Malignant PTs account for 16% to 30% of all PTs and they have an inherent recurrence and/or metastasis potential.4,5 Cardiac metastases are more frequent than primary cardiac tumors.6 Herein, we report a case of concomitant cardiac and pulmonary metastases of malignant PTs, causing severe mitral valve obstruction.\n\n\nCase report\n\nA 37-year-old Maghrebian female patient was presented to the cardiology department due to complaints of dyspnea, progressing over one month. She had a dry cough and had been resistant to symptomatic treatment. The patient was diagnosed with borderline breast PTs ten years earlier, which was treated by surgical excision. Upon examination, her dyspnea was classified as class IV on the New York Heart Association Functional Classification with orthopnea. Her transcutaneous oxygen saturation was 92%, and pulmonary auscultation revealed bibasilar crackles. Additionally, the patient’s chest x-ray showed a homogeneous opacity located in the basal part of the right lung. Transthoracic echocardiography (TTE) revealed 5 × 4 cm homogenous mass occupying nearly all the left atrium (LA), resulting in severe mitral valve obstruction (mean gradient = 17 mmHg) (Figure 1).\n\nLV: left ventricle, MV: mitral valve, RV: right ventricle.\n\nA second huge mass compressed the right atrium posterior wall. Following respiratory stabilization, transesophageal echocardiography confirmed TTE results and revealed an extended mass into LA via the right inferior pulmonary vein (RIPV) (Figure 2). Cardiac computed tomography (CT) revealed a large (100 × 70 × 100) mediastino-pulmonary mass extending to LA via RIPV (Figure 3).\n\nThe Cardiac magnetic resonance imaging (MRI) results showed low signal on T1-weighted imaging and high signal on T2-weighted imaging of the mediastino-pulmonary mass (Figure 4). The patient accepted to undergo an urgent mass resection surgery to avoid total mitral valve obstruction and sudden death. The histological study of the resected mass confirmed the metastatic spread of malignant PTs to LA (Figure 5). The patient was discharged from the hospital after having an echocardiographic check-up, which demonstrated no residual tumor. However, three months after the surgery, she died from a huge relapse of mediastinal mass with tracheal invasion.\n\n\nDiscussion\n\nPTs or cystosarcoma is a rare breast neoplasm.1 These types of tumors are commonly manifested in the breast tissue and are usually benign; however, they might rarely be malignant.2,3 A malignant tumor has a potential to metastasize to distant organs, such as lung, bone, and liver.8 Our case revealed concomitant pulmonary and cardiac metastases, which is unusual, and it is associated with poor prognosis. It has been reported that cardiac invasion could be caused by hematogenous spread, direct extension, or via the lymphatic route.9 In the case of this patient, direct extension from pulmonary metastasis to RIPV is the probable route of metastasis. Reported cases of cardiac metastasis are mostly located in the right heart with the possibility of right ventricle outflow tract obstruction.10 To the best of our knowledge, this is the first case of LA location, complicated by severe mitral obstruction and acute heart failure. The clinical expression of cardiac metastasis is mainly dependent on the tumor burden and location.6 As in the case of our patient, cardiac metastasis can manifest with dyspnea and chest pain, or it can be asymptomatic. Previously, malignant cardiac metastasis had poor prognosis and very rare cases were identified at autopsy.11 However, advances in imaging tools such as echocardiography allows for detection and confirmation of intra-cardiac mass and eventual valve or cavity obstruction. However, echocardiography is limited in the differentiation between PTs, myxoma, fibroadenoma, and thrombus.11 In our case, echocardiography revealed severe mitral obstruction by an intra-LA mass. Cardiac CT and MRI provide multiple views in different axes with a precision of limits as well as intra, and extra cardiac extension, thus allowing a better distinction between the thrombus and other masses.12 The results of the echocardiography, cardiac CT, and MRI for our patient confirmed the intra and extra cardiac location of the tumor and its LA access from RIPV to the mitral valve. Therapeutic approaches, including chemotherapy, radiotherapy, and hormonal therapy are still controversial.7 The surgical excision of cardiac metastasis from a malignant PTs was described in few reports.13 This type of intervention could be an urgent life-saving therapeutic strategy in case of right ventricle outflow obstruction or mitral obstruction, and it can also improve the patient’s quality of life in the short term, as it was in our case.14,15 However, intra-operative mass manipulation could cause tumor dissemination, thus leading to a risk of further metastasis development.11,16 This may explain the hudge relapse of mediastinal mass with tracheal invasion in our patient. In this case report the major limitations were the delay in diagnosing cardiac and pulmonary metastases and the lack of immunohistochemical analysis of the tumor.\n\n\nConclusion\n\nCardiac metastases from PTs are rare. Tumor surgical excision might be indicated to avoid sudden death and to improve the patient’s quality of life despite the extremely unfavorable prognosis. Nevertheless, urgent surgical removal could be unavoidable in case of valve obstruction. Early diagnosis and immunohistological analysis of PTs, especially the malignant type, is imperative given that there is little effective treatment for metastatic disease.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nAuthor contributions\n\nNA, AA and AB were actively involved in data collection and processing. IC and RK were involved in manuscript preparation. CK, SJ and FM were involved in manuscript reviewing. All authors have read and approved the manuscript.\n\n\nConsent\n\nA written informed consent was received from the patient’s brother.", "appendix": "References\n\nParker SJ, Harries SA: Phyllodestumors. Postgrad. Med. J. 2001; 77: 428–435. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nJing P, Wei B, Yang X: Phyllodestumor of the breastwithnippledischarge: A case report. Medicine (Baltimore). 2018; 97: e13767. PubMed Abstract \| Publisher Full Text\n\nZhang Y, Kleer CG: PhyllodesTumor of the Breast: Histopathologic Features, Differential Diagnosis, and Molecular/Genetic Updates. ArchPatholLab Med. 2016; 140: 665–671.\n\nRosenfeld JC, DeLaurentis DA, Lerner H: Cystosarcoma phyllodes. Diagnosis and management. Cancer Clin. Trials. 1981; 4: 187–193. PubMed Abstract\n\nJones AM, Mitter R, Poulsom R, et al.: mRNA expression profiling of phyllodes tumours of the breast: identification of genes important in the development of borderline and malignant phyllodes tumours. Phyllodes. Tumour Consortium. J. Pathol. 2008; 216: 408–417. Publisher Full Text\n\nBussani R, De-Giorgio F, Abbate A, et al.: Cardiac metastases. J. Clin. Pathol. 2007; 60(1): 27–34. PubMed Abstract \| Publisher Full Text\n\nTelli ML, Horst KC, Guardino AE, et al.: Phyllodes tumors of the breast: natural history, diagnosis, and treatment. J. Natl. Compr. Cancer Netw. 2007; 5: 324–330. Publisher Full Text\n\nKessinger A, Foley JF, Lemon HM, et al.: Metastatic cystosarcoma phyllodes: a case report and review of the literature. J. Surg. Oncol. 1972; 4: 131–147. Publisher Full Text\n\nSchoen FJ, Berger BM, Guerina NG: Cardiac effects of non cardiac neoplasms. Cardiol. Clin. 1984; 2: 657–670. Publisher Full Text\n\nNakatsu T, Koshiji T, Sakakibara Y, et al.: Pulmonary artery obstruction due to a metastatic malignant phyllodes tumor of the breast. Gen. Thorac. Cardiovasc. Surg. 2010; 58(8): 423–426. PubMed Abstract \| Publisher Full Text\n\nGarg N, Moorthy N, Agrawal SK, et al.: Delayed cardiac metastasis from phyllodes breast tumor presenting as cardiogenic shock. Tex Heart Inst. J. 2011; 38: 441–444.\n\nChiles C, Woodard PK, Gutierrez FR, et al.: Metastatic involvement of the heart and pericardium: CT and MR imaging. Radiographics. 2001; 21: 439–449. Publisher Full Text\n\nYa'qoub L, Larson S, Deedy M, et al.: Treatment of recurrent isolated right atrial metastatic cavitary mass frombreast cancer with radiation therapy: A case report and review of literature. Echocardiography. 2018; 35: 1680–1683. Publisher Full Text\n\nYoshidaya F, Hayashi N, Takahashi K, et al.: Malignant phyllodes tumor metastasized to the right ventricle: a case report. Surg. Case Rep. 2015; 1: 121.\n\nChachques JC, Argyriadis PG, Latremouille C, et al.: Cardiomyoplasty:ventricular reconstruction aftertumorresection. J. Thorac. Cardiovasc. Surg. 2002; 123: 889–894. Publisher Full Text\n\nGoh CH, Lim YP, Su JW, et al.: Cardio pulmonary thrombo embolism of epithelioid angiosarcoma arising from malignant phyllodes tumour of the breast. J. Clin. Pathol. 2014; 67: 450–454. PubMed Abstract \| Publisher Full Text" }	[ { "id": "139615", "date": "15 Jun 2022", "name": "Hassen Ibn Hadj Amor", "expertise": [ "Reviewer Expertise Cardiology" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is an excellent case report of a young patient presenting with dyspnea class IV on the New York Heart Association functional classification, including a cascade of exploration including Transthoracic echocardiography, Transesopheagal echocardiography, CT-scan and cardiac magnetic resonance imaging as well as the histological study, concluded that the mitral valve was obstructed by a metastatic malignant phyllodes tumor. The patient required emergency valve surgery with the particularity of preserving the native valve and removing only the metastatic mass (urgent life-saving therapeutic strategy). It is a very rare cause of mitral obstruction where only the histological examination allowed to differentiate it with certainty.\nThe iconography is well done. Discussion is sufficient with a good review of the literature\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "140668", "date": "01 Jul 2022", "name": "Chien-Liang Fang", "expertise": [ "Reviewer Expertise breast and plastic surgery" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a rare case of mitral valve obstruction by metastatic malignant phyllodes tumor. They provide clear and complete images for a complete preoperative assessment and they can keep patients alive for more than three months after surgery for such a severe mitral valve obstruction. They did a great job but this case report still needs further revision and correction.\nIn the abstract:\nThe authors write “we report a case of a 37-year-old female patient with a history of borderline breast PTs”, please add previous breast PT surgery treatments. “The patient had an uncommon complication”, please mention the complication.\nIn the report itself:\n“The patient was diagnosed with borderline breast PTs ten years earlier, which was treated by surgical excision.” Which breast, tumor size, skin involvement, safe margin of surgical resection, recurrence or not? What is the operation of metastatic malignant phyllodes tumor resection, including resection of mitral valve or cardiac tissue, lung resection (lobectomy) or debulking surgery? Reconstruction or not? “The patient was discharged from the hospital after having an echocardiographic check-up, which demonstrated no residual tumor.” Please show the echocardiographic image. “Three months after the surgery, she died from a huge relapse of mediastinal mass with tracheal invasion.”, please show the CT image. In discussion, I could find more than a dozen articles on metastatic malignant phyllodes tumor of the heart, please summarize and discuss the differences between your case and theirs. There are many errors in the references, please correct them.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Partly\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [ { "c_id": "8506", "date": "25 Jul 2022", "name": "IKRAM CHAMTOURI", "role": "Author Response", "response": "Dear editorial board Thank you for giving me the opportunity to submit a revised draft of my manuscript. We have highlighted the changes within the manuscript. Here is a point-by-point the response to the reviewers’ comments. In the abstract: 1. The authors write “we report a case of a 37-year-old female patient with a history of borderline breast PTs”, please add previous breast PT surgery treatments Response: changes made in the new version 2. The patient had an uncommon complication”, please mention the complication. Response: mediastinal location of metastasis In the report itself: 1.“The patient was diagnosed with borderline breast PTs ten years earlier, which was treated by surgical excision.” Which breast, tumor size, skin involvement, safe margin of surgical resection, recurrence or not? Response: Tumor size was 8 x7 x5 cm, removed surgically with no skin involvement and safe margin of resection (added in the new version) 2. What is the operation of metastatic malignant phyllodes tumor resection, including resection of mitral valve or cardiac tissue, lung resection (lobectomy) or debulking surgery? Reconstruction or not? Response: Surgery consisted on total intra cardiac metastasis resection with mitral valve conservation and right pneumonectomy without reconstruction.( added in the new version) 3. “The patient was discharged from the hospital after having an echocardiographic check-up, which demonstrated no residual tumor.” Please show the echocardiographic image. Response: no echocardiographic image was available 4. “Three months after the surgery, she died from a huge relapse of mediastinal mass with tracheal invasion.”, please show the CT image. Response: CT image added in the new version 5. In discussion, I could find more than a dozen articles on metastatic malignant phyllodes tumor of the heart, please summarize and discuss the differences between your case and theirs. Response: changes were made in the new version 6.There are many errors in the references, please correct them. Response: errors were corrected" } ] } ]	1	https://f1000research.com/articles/11-309
https://f1000research.com/articles/11-143/v2	25 Jul 22	{ "type": "Research Article", "title": "Effectiveness and safety profile of mesenchymal stem cell secretome as a treatment for severe cases of COVID-19: a randomized controlled trial", "authors": [ "Murdani Abdullah", "Jeanne Adiwinata Pawitan", "Cosphiadi Irawan", "Rahyussalim -", "Dita Aditianingsih", "Isabella Kurnia Liem", "Robert Sinto", "Adityo Susilo", "Mira Yulianti", "Raden Rara Diah Handayani", "Irandi Putra Pratomo", "Erlina Burhan", "Triya Damayanti", "Heri Wibowo", "Ismail Hadisoebroto Dilogo", "Hary Sakti Muliawan", "Mia Elhidsi", "Murdani Abdullah", "Jeanne Adiwinata Pawitan", "Cosphiadi Irawan", "Rahyussalim -", "Dita Aditianingsih", "Isabella Kurnia Liem", "Robert Sinto", "Mira Yulianti", "Raden Rara Diah Handayani", "Irandi Putra Pratomo", "Erlina Burhan", "Triya Damayanti", "Heri Wibowo", "Ismail Hadisoebroto Dilogo", "Hary Sakti Muliawan", "Mia Elhidsi" ], "abstract": "Background: Mesenchymal stem cells (MSCs) are known to have immunomodulatory, anti-inflammatory, anti-apoptotic, and angiogenesis effects that are useful for relieving inflammation, recovery, and protection of lung tissues in COVID-19 patients. Secretome, a secretory product of MSCs, has several advantages over MSCs. We conducted a study to investigate secretomes’ effectiveness and safety profile as a treatment for severe COVID-19. Methods: A double-blind, multicenter, randomized, placebo-controlled trial was conducted between February 2021 and July 2021 in three top COVID-19 referral hospitals in the Greater Jakarta area, Indonesia. Eligible subjects (n=40) were randomized in a 1:1 ratio to an intervention group (n=20) and a control group (n=20). The primary outcome of this study was the changes in inflammatory markers and the ratio of inflammatory to anti-inflammatory markers. The secondary outcomes of this study included clinical outcome, laboratory outcome, radiological outcome, RT-PCR result conversion, and safety profile of MSC secretome. Results: Our analysis showed that on the 14th day after placebo administration, IL-6 level in the control group was significantly increased [4.110 (2.403–12.820) at baseline to 13.320 (2.958–33.285) on the 14th day after intervention, p=0.017]. The IL-6/IL-10 ratio in the control group was significantly increased (p=0.036) on the 14th day after placebo administration. We also found that most of the subjects who received placebo had high levels of IL-6 and ferritin (p=0.043) on the seventh day after the intervention. However, we found no significant differences in inflammatory marker levels on the seventh day and 14th day after intervention between both groups. There was no adverse event reported. There were no significant differences in the laboratory outcome, radiology outcome, RT-PCR result conversion, and safety profiles between both groups. Conclusions: MSC secretome can control inflammation in patients with severe COVID-19 and has a good safety profile. MSC secretome is a promising treatment modality for severe COVID-19.", "keywords": [ "COVID-19", "secretome", "mesenchymal stem cell", "cytokine", "inflammation mediators" ], "content": "Background\n\nThe spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has caused a global COVID-19 pandemic.1 The severity of COVID-19 varies from mild to severe.2 The clinical symptoms of mild and moderate COVID-19 patients, include fever, myalgia, fatigue, and dyspnea, whereas acute respiratory distress syndrome (ARDS) and multiple organ failure usually develop in severe COVID-19 patients.2,3 Multiple organ failure in COVID-19 can be induced by SARS-CoV-2 infection to target organs expressing ACE2 receptor or by the cytokine storms.3,4\n\nIncreased levels of inflammatory mediators in the blood of COVID-19 patients are related to the severity of COVID-19.5,6 Patients with severe or critical COVID-19 have immune response dysfunction.7 Patients with severe COVID-19 have a higher increase in pro-inflammatory and anti-inflammatory cytokines than patients with moderate COVID-19.5,6 Kong et al. (2020) in their study stated that there was an increase in levels of VEGF, TNF-alpha, SCF, LIF, IL-2, IL-4, IL-6, IL-8, IL-10, IL -15, IL-17A, IL-18, IL-1beta, and IFN-gamma in severe and critical COVID-19 patients.8 An excessive immune response and overproduction of inflammatory cytokine lead to cytokine storms which induce cytokine release syndrome (CRS).2,9 Excessive release of cytokine and chemokines in cytokine release syndrome (CRS) can lead to multi-organ failure, which increases the disease severity, length of stay, and mortality rate.3,9\n\nCurrently, there is no definitive therapy used to treat COVID-19 and its immunologic complications.2,10 Immunosuppressive and immunomodulatory agent is considered as a treatment of immunologic complications in COVID-19.10 Mesenchymal stem cells (MSCs) are known to have immunomodulatory, anti-inflammatory, anti-apoptotic, and angiogenesis effects that are useful for relieving inflammation, recovery, and protection of lung tissues in COVID-19 patient.4,11 Several studies suggest that mesenchymal stem cells are useful in the treatment of COVID-19.12,13 A clinical trial in Indonesia showed that COVID-19 patients who received MSCs therapy had a greater decrease in the pro-inflammatory cytokine IL-6 and ferritin compared to patients who did not receive MSCs therapy. In addition, the administration of MSCs therapy was also beneficial in increasing the survival rate of COVID-19 patients.12 Another study stated that COVID-19 patients had PaO2/FiO2 ratio and radiological improvement after the administration of UC-MSCs.13\n\nMSC are known to secrete bioactive compound that have the same effects as MSC, called secretome.11 A case series on the use of MSC secretome in patients with severe COVID-19, reported that 3 patients with severe COVID-19 had clinical, radiological, and laboratory improvements after the administration of MSC secretome.14 In addition, the use of MSC secretome as a cell-free therapy has wide advantages compared to MSC as cell-based therapy.11,15 MSC secretome has less tumorigenicity effect, less immunogenicity effect, low risk of emboli formation, and low risk of infection transmission.4,16 Other advantages of MSC secretome as cell-free COVID-19 therapy, include cost-effective, can be produced in large quantities, ready to used, easy storage with maintaining product potency, and feasibleness in clinical practice.4,11,16 Thus, MSC secretome is a new strategy for the treatment of COVID-19.17 Therefore, we conducted a study to investigate the effectiveness and safety profile of MSC secretomes as a treatment for severe COVID-19.\n\n\nMethods\n\nThis study was a double-blind, multicenter, randomized, placebo-controlled trial of MSC secretome in severe COVID-19 patients.\n\nThe subjects who participated in this study were 40 subjects. The subjects were recruited from Dr. Cipto Mangunkusumo Hospital, Universitas Indonesia Hospital, and Persahabatan National Respiratory Hospital, in the Greater Jakarta area, Indonesia. The recruitment was conducted from February 2021 until July 2021. The subjects who participated in this study had met the inclusion and exclusion criteria. The inclusion criteria were 1) All individuals aged 18–65 years old, 2) Confirmed positive for COVID-19 based on real-time reverse-transcription polymerase chain reaction (RT-PCR) examination on throat/sputum/bronchoalveolar lavage (BAL) swab specimen, 3) Categorized as severe or moderate-to-severe cases of COVID-19 patients, 4) Not intubated on admission, 5) Patients were given standard COVID-19 therapy, 6) Agree to participate and sign the informed consent. Severe COVID-19 was described according to the national guideline released by the Indonesian Ministry of Health, complying with the one released by WHO.18 Moderate to severe COVID-19 criteria was described by COVID-19 pneumonia along with the presence of at least one of the following: sequential organ failure assessment (SOFA) score ≥5.65, body mass index ≥35, D-dimer >1 μg/mL, prothrombin time >13.6 seconds, thrombocytopenia (<100000/mL), INR >1.8, C-reactive protein >25, procalcitonin >0.5 ng/mL, lymphopenia (<1.5×109/L), neutrophil-lymphocyte ratio >3.3, or classified as a highrisk group [aged 60 years old, have comorbidity (diabetes, hypertension, lung diseases, and/or asthma), and/or long-term use of steroid]. The exclusion criteria were 1) a pre-existing history of allergy to penicillin, streptomycin, and amphotericin B, 2) a pre-existing cancerous illness, 3) currently participating in other intervention studies, 4) had participated in other intervention studies within the last three months.\n\nEligible subjects (n=40) were randomized in a 1:1 ratio to receive MSC secretome in the intervention group (n=20) or to receive placebo in the control group (n=20). Subjects were randomized with blocks, block sizes of 4, and two groups (intervention and control) using a randomization software (Sealed Envelope) by an independent statistician. Study preparations were prepared by a third party who had no involvement with patient care and data collection. All investigators, treating clinicians, and subjects were blinded.\n\nMSC secretome was produced and supplied by Stem Cells Medical Technology, Integrated Service Unit of Faculty of Medicine, Universitas Indonesia – Dr. Cipto Mangunkusumo, Jakarta, Indonesia. The secretome used in this study was derived from the fifth passage of the umbilical cord MSCs. The secretome has passed the quality control stage, sterility, and protein content test.\n\nPrior to the intervention, examination of clinical symptoms and vital signs, laboratory test, inflammation marker test, chest radiograph, and RT-PCR for SARS-CoV-2 were performed on subjects. Subjects in the intervention group (n=20) received MSC secretome and COVID-19 standard therapy. Meanwhile, subjects in the control group (n=20) received placebo (NaCl 0.9%) and COVID-19 standard therapy. MSC secretome was given once at a dose of 15 mL per administration dissolved in 100 mL of normal saline. Secretome was given intravenously for 60 minutes. COVID-19 standard therapy given to both groups were based on the national protocol for COVID-19 therapy.18\n\nPrimary outcomes\n\nThe primary outcome of this study was the effect of mesenchymal stem cell secretome on the level of inflammatory markers. The inflammatory markers assessed in this study were interleukin 6 (IL-6), interleukin 10 (IL-10), leukemia inhibitory factor (LIF), vascular endothelial growth factor (VEGF), and ferritin. Examination of inflammatory markers was performed before the intervention and repeated on the seventh and 14 days after the intervention. Parameters analyzed were changes in inflammatory markers and the ratio of inflammatory to anti-inflammatory markers.\n\nSecondary outcomes\n\nThe secondary outcomes of this study included clinical outcome, laboratory outcome, radiological outcome, RT-PCR result conversion, and safety profile of MSC secretome. Laboratory parameters, radiological imaging, RT-PCR examination for SARS-CoV-2 data before and after intervention (maximum 14 days after the intervention) were obtained. Side effects, infusion reaction, allergic reaction, secondary infection, adverse event, and renal function test were assessed during hospitalization and maximum of 14 days after the intervention.\n\nInflammatory markers were assessed using peripheral venous whole blood samples. Whole blood samples were collected on day 0 (immediately before intervention), on the seventh day after intervention, and on the 14th day after intervention. After collection, vacuum tubes were inserted into primary (zip-lock plastic), secondary (thermos), and tertiary pack (cool box containing ice pack) for transportation.\n\nAll data in this study were analyzed using SPSS software, V.25.0 (IBM). Analyses of categorical variables were calculated using the Chi-squared test or using Fisher’s exact test. Analyses of unpaired continuous variables were calculated using independent-samples Mann–Whitney U test for non-normally distributed data or independent-samples T-test for normally distributed data. Analyses of paired continuous variables were calculated using paired T-test for normally distributed data or Wilcoxon test for non-normally distributed data.\n\n\nResults\n\nFrom 18 February 2021 to 9 July 2021, 786 were screened for eligibility. The patient screening was carried out in three hospitals in Jakarta Greater area, Indonesia. A total of 745 patients who did not meet the inclusion criteria were determined ineligible. There was one patient who met the inclusion criteria but could not participate in this study due to being intubated before the intervention. 40 eligible subjects were randomized into two groups in a 1:1 ratio. 20 subjects in the intervention group receive secretome – MSC and COVID-19 standard therapy. Meanwhile, 20 subjects in the control group received placebo and COVID-19 standard therapy. After the intervention, whole blood samples were collected two times (on the seventh day and 14th day after intervention) to assess the inflammation markers’ level. The recruitment of the subjects is described in Figure 1.\n\nThis study analyzed 40 subjects and assigned 20 subjects to the intervention group and 20 subjects to the control group. There were no significant differences in the baseline characteristics of the subjects between the intervention and control groups. The average age of subjects in the intervention group was 51.25 years old, whereas the average age of subjects in the control group was 49.9 years old. Most of the subjects in both groups were 40–60 years old. The majority of subjects in both groups were obese. Besides obesity, heart disease was the most common comorbidity in the intervention group. Meanwhile, in the control group, hypertension became the most common comorbidity after obesity. A total of seven subjects in the intervention group had ≥4 comorbidities, while the number of subjects in the control group who had ≥4 comorbidities was 1 (5%) subject. Characteristics of the subject are presented in Table 1.\n\n* p-values were calculated by Chi-squared test.\n\n p-values were calculated by Fisher’s exact test because there are cells with expected count < 5.\n\n* p-values were calculated by Mann–Whitney test.\n\n**** p values were calculated by independent-samples T test for normally distributed data of continuous variables.\n\nThe inflammatory markers level in the intervention and control groups were assessed on day 0 (before intervention), the seventh day, and 14th day after intervention. Both groups had a comparable baseline levels of inflammatory markers. On the seventh day after intervention, the median values of IL-6, IL-10, LIF, and ferritin in the intervention group were lower than the control group. Meanwhile, the median value of VEGF in the intervention group was higher than the control group. There were no significant differences in inflammatory markers level on the seventh day and 14th day after intervention between both groups. However, the IL-6 marker in the control group was significantly increased on the 14th day after intervention (n=8) compared to the IL-6 marker before intervention (n=20) [4.11 (2.4025–12.82) at baseline to 13.32 (2.9575–33.285), p=0.017]. The baseline and after intervention levels of inflammatory markers are presented in Table 2.\n\n* p-values were calculated using Wilcoxon signed rank test.\n\n** p-values were calculated using paired T-test.\n\nThe ratio of inflammation marker level for each time point is presented in Figure 2. The ratio of inflammation marker is obtained by dividing subjects’ inflammation marker level at time point 1 by the same inflammation marker level at time point 2. Although the ratio of inflammation marker level for some inflammation markers (IL-6, IL-10, VEGF) in the control group tend to be more varied and have higher medians, there were no significant differences in the inflammation marker level ratio on the seventh day to day 0, 14th day to the seventh day, and 14th day to day 0 between both groups.\n\nNote that the ratios of inflammation markers on IL-6, IL-10, and VEGF in the control group tend to be more varied. The median ratio of IL-6 and VEGF also tend to be higher in the control group. There is no significant difference between both groups.\n\nAnalysis of pro-inflammatory (IL-6 and ferritin) and anti-inflammatory (IL-10) mediators, is presented in Figure 3. IL-6 and IL-10 is presented in the ratio form (Figure 3A). The ratio value was made based on the quotient between IL-6 and IL-10. We analyzed the changes in the IL-6/IL-10 ratio on day 0 (before intervention), the seventh day, and 14th day after intervention (Figure 1). In the control group, there was a significant increase in the IL-6/IL-10 ratio (p = 0.036) on the 14th day after the intervention compared to before the intervention. In contrast, in the intervention group, there was no increase in the IL-6/IL-10 ratio.\n\nA) Ratio of IL-6/IL-10 on Day 0 (Before Intervention), the seventh day, and the 14th day After Intervention. The IL-6/IL-10 ratio is increasing within 14 days after intervention in the control group. B) Relationship Between IL-6 and Ferritin on the seventh day After Intervention. Most of the subjects in the control group were distributed in the P-3 (high level of IL-6 and ferritin).\n\nThe interaction between high and low ferritin levels and high and low IL-6 levels on the seventh day was shown in the form of a scatter graph categorized into 4 panels (Figure 3B). The scatter graph shows that the proportion of subjects from the control group is mostly distributed in panel-3 (P-3) where P-3 describes the category of high IL-6 levels and high ferritin levels and is significantly larger than the intervention group (p = 0.043). Meanwhile, in the intervention group, most of the subjects were distributed in panel-1 (category of low IL-6 levels and low ferritin levels) and panel-4 (category of high IL-6 levels and low ferritin levels).\n\nPrior to the intervention, most of the subjects, 10 subjects in the intervention group and 12 subjects in the control group, had oxygen saturation >95% using a high-flow nasal cannula. Meanwhile, after the intervention, 10 subjects in the intervention group and eight subjects in the control group had oxygen saturation >95% at room temperature. In this study, there were four subjects from the intervention group and two subjects from the control group who reported using a ventilator after the intervention. There were no differences in oxygen saturation and supplementation between the intervention and control group (before intervention p=0.640, after intervention p=0.883).\n\nThe post-intervention laboratory parameters for the intervention and control groups are shown in Table 3. Both groups had comparable laboratory parameters at baseline. Both groups also had comparable levels of post-intervention laboratory parameters, except chloride levels (p=0.035). There was no significant difference in the post-intervention levels of other laboratory parameters between both groups.\n\n* p-values were calculated by Mann–Whitney test for non-normally distributed data of continuous variables.\n\n** p values were calculated by independent-samples T test for normally distributed data of continuous variables.\n\nConversion of RT-PCR results for SARS-CoV-2, from positive to negative, occurred in 8 subjects in the intervention group and 11 subjects in the control group. RT-PCR results of two subjects in the intervention group and seven subjects in the control group converted to negative within ≤14 days. Meanwhile, RT-PCR results for the other six subjects in the intervention group and four subjects in the control group converted to negative within >14 days. There were no significant differences in the number of RT-PCR conversions between the intervention group and control groups (p=0.238).\n\nThe proportions of lung lesion area and chest radiography score before and after intervention in the intervention and control groups are presented in Figure 4A and B. The intervention and control groups had comparable baseline values for lung lesion area proportions and brixia scores. There were no significant differences in the median value of lung lesion area proportion and brixia scores between both groups before the intervention. After the intervention, the median value of the lung lesion area proportion and brixia score in the intervention group was lower than in the control group. There were no significant differences in the median value of lung lesion area proportion and brixia scores between both groups after the intervention. We analyzed the ratio of lung lesion area proportion and chest radiography score after the intervention to before the intervention. The lung lesion area proportion ratio was made based on the quotient between lung lesion area proportion after the intervention and before the intervention. Meanwhile, brixia score ratio was made based on the quotient between brixia score after the intervention and before the intervention. The ratios oflung lesion area proportion and brixia score after the intervention to before the intervention are presented in Figure 4C. After the intervention, there was a decrease in the lung lesion area proportion and brixia score, both in the intervention and control groups. There were no significant differences in both groups.\n\nA) The proportions of lung lesion area before and after intervention in the intervention and control groups. Blue boxes represent proportions of lung lesion area before intervention, and res boxes represents proportions of lung lesion area after intervention. The median proportions of lung lesion area after intervention was decreased in both groups (deeper in intervention group), but not statistically significant. B) The chest radiography score (Brixia score) before and after intervention in the intervention and control groups. Blue boxes represent Brixia score before intervention and red boxes represents Brixia score after intervention. The median Brixia score after intervention was decreased in both groups (deeper in intervention group), but not statistically significant. C) The ratio of lung lesion area proportion and chest radiography score, after the intervention to before the intervention.\n\nA total of seven deaths were reported in this study, four deaths from the intervention group and three deaths from the control group. Six deaths occurred during the study period (within 14 days after intervention). Meanwhile, one death from the control group occurred near to study observation period (18th day after intervention). There were no significant differences in the number of deaths between the intervention and control groups (4 versus 3, p=1.00). The length of illness in this study was calculated from the onset of symptoms of COVID-19 until the patient recovers. The median value of the length of illness in the intervention group was lower than the control group, but not statistically significant [19 (14.25–23.75) versus 21.5 (19.25–27,25), p=0.068, respectively].\n\n\nDiscussion\n\nBased on the previous studies, MSCs are known to inhibit the release of inflammatory mediators and exert immunosuppressive effects through immune system regulation.19,20 Saleh et al. (2021) conducted a study on five severe COVID-19 patients who were treated by Wharton's jelly-derived mesenchymal stem cells, and the results were a decrease in IL-6 and VEGF levels and an increase in IL-10 levels after the intervention.21 Another study conducted by Adas et al. (2021) stated that there were a decrease in IL-6 and ferritin levels and an increase in VEGF levels on the seventh day after the intervention with Wharton's jelly-derived mesenchymal stem cells in critically ill COVID-19 patients.22\n\nAnalysis of IL-6 levels in our study showed that the median value of IL-6 in the intervention group was lower than the control group, both on the seventh day and 14th day after the intervention. The IL-6 marker in the control group was significantly increased on the 14th day after the intervention compared to the IL-6 marker before intervention (p=0.017). Meanwhile, analysis of ferritin levels in our study showed that the median value of ferritin on the seventh day and 14th day after intervention in the intervention group was lower than in the control group. Ferritin levels on the seventh day and 14th day after the intervention were decreased compared to ferritin levels before the intervention, both in the secretome and control groups. However, there was no significant difference between both groups. In our study, it was also found that on the seventh day after the intervention, most of the subjects who received placebo had high levels of IL-6 and ferritin (p=0.043). These results indicate that mesenchymal stem cell secretomes have a role in suppressing the inflammatory process in severe COVID-19. IL-6 is known as a pro-inflammatory cytokine produced in the blood by leukocytes and can be produced in injured tissue by endothelial cells, fibroblasts, or alveolar epithelial cells. Merza et al. (2021) in their study hypothesized that increased levels of IL-6 in severe COVID-19 patients were caused by alveolar epithelial cells inflammatory response due to alveolar epithelial cells injury by SARS-CoV-2.6 In addition, ferritin was a marker of systemic inflammation and can be used to determine the prognosis of COVID-19 patients.5,23 Chen et al. (2020) in their study stated that severe COVID-19 patients had higher ferritin levels than moderate COVID-19 patients, indicating the inflammatory process was higher in severe COVID-19 patients.5 Many previous studies have shown that administration of mesenchymal stem cells is beneficial in reducing levels of inflammatory markers, such as IL-6 and ferritin.20,21\n\nAnalysis of IL-10 levels in our study showed that the median value of IL-10 on the seventh day after the intervention in the intervention group was lower than in the control group, but there was no significant difference between both groups. In addition, there was a decrease in IL-10 levels on the 14th day after the intervention compared to IL-10 levels before the intervention in the secretome and control groups, and there was no significant difference between both groups. Our study also analyzed the changes in the IL-6/IL-10 ratio on day 0 (before intervention), the seventh day, and 14th day after intervention (Figure 2). The IL-6/IL-10 ratio describes the inflammatory potential in COVID-19. A high level of IL-6/IL-10 ratio indicated an increase of inflammatory potential. In the control group, there was a significant increase in the IL-6/IL-10 ratio (p = 0.036) on the 14th day after the intervention compared to before the intervention. In contrast, in the intervention group, there was no increase in the IL-6/IL-10 ratio. These results indicate that the administration of secretome is able to control the inflammation in COVID-19. IL-10 is known as an anti-inflammatory cytokine that can suppress inflammatory reaction.6 Chen et al. (2020) in their study stated that in most cases of severe COVID-19, there was an increase level of proinflammatory cytokines (IL-6) and anti-inflammatory cytokines (IL-10), and the levels of IL-6 and IL-10 in severe COVID-19 patients were significantly higher compared to moderate COVID-19 patients.5 This indicates the relationship between the severity of COVID-19 and the incidence of cytokine storms in COVID-19. Mesenchymal stem cell therapy from the umbilical cord in severe and critical COVID-19 patients has an effect on the profile of proinflammatory and anti-inflammatory cytokines. Zhang et al. (2021) in their case report stated that there was a significant downward trend in IL-6 and IL-10 after infusion of hUCMSC at a dose of 6.4×107 twice in critically ill COVID-19 patients.24 This supports the results of our study.\n\nAnalysis of VEGF levels in our study showed that there was a decrease in VEGF levels on the seventh and 14th days after the intervention compared to before the intervention, both in the secretome and control groups and there was no significant difference between both groups. In addition, the median value of VEGF on the 14th day after intervention in the intervention group was lower than in the control group, but there was no statistically significant difference between both groups. VEGF is one of the growth factors associated with the severity of COVID-19. VEGF levels were found to be significantly higher in critically ill COVID-19 patients compared to severe patients.8 Elevated VEGF levels are common in acute inflammatory and hypoxic conditions. Saleh et al. (2021) in their study stated that there was a gradual decrease in VEGF levels after Wharton’s Jelly – MSCs administration.21 These results were appropriate with the results in our study.\n\nAnalysis of LIF levels in our study showed that the median value of LIF in the intervention group on the seventh day and 14th day after the intervention was lower than in the control group. In addition, LIF levels on the seventh day and 14th day after the intervention were relatively the same as LIF levels before the intervention, both in the secretome and control groups. LIF is an inflammatory mediator that protects the lung during pneumonia. LIF is required to repair and regenerate alveolar epithelial cells during pneumonia due to COVID-19. LIF also prevents vascular leakage due to the inflammatory process.25 Quinton et al. (2012) in their study stated that low levels of LIF during pneumonia can cause lung injury. The results of their study stated that the administration of anti-LIF caused an increase in the ratio of the wet lung to the dry lung compared to the control group.26 Study conducted by Dilogo et al. (2021) stated that there was an increase in LIF in most subjects who received MSC on the seventh day after the intervention.12\n\nThe severity of COVID-19 varies, ranging from asymptomatic, mild symptoms, severe symptoms with respiratory failure and death.27 In our study, 7 (17.5%) deaths were reported, 4 (10%) deaths occurred in the intervention group and 3 (7.5%) deaths occurred in the control group. Six deaths occurred during the study period (within 14 days after intervention). Meanwhile, one death from the control group occurred near the study's observation period (died on day 18 after the intervention). There was no significant difference in the number of deaths in the intervention group, compared with the control group. The mortality rate in our study was lower than in the other study. Dilogo et al. (2021) in their study in critically ill COVID-19 patients stated that 10 (25%) deaths occurred in the MSC group and 16 (45%) deaths occurred in the control group.12 Another study in critically ill COVID-19 patients conducted by Adas et al. (2021) stated that there were three deaths (30%) in the MSC group and six deaths (60%) in the control group.22\n\nIn our study, we reported that in the intervention group there were two subjects who died had ≥4 comorbidities (10%), one subject who died had three comorbidities (5%), and one other subject had one comorbidity (5%). Meanwhile, in the control group, one subject who died had two comorbidities (5%), one subject who died had one comorbid (5%), and one other subject had no comorbid (5%). The comorbidities have a role in the mortality of COVID-19 patients. Wang et al. (2020) in a retrospective observational study stated that there were 116 patients who died from a total of 293 COVID-19 patients. Wang et al. (2020) also stated that most death cases in COVID-19 occurred in COVID-19 patients who had comorbidities. The study stated that 44 (37.9%) COVID-19 patients who died had ≥2 comorbidities and 36 (31%) of COVID-19 patients who died had one comorbid.27 Another study conducted by Dilogo et al. (2021) also stated that in both the MSC group and the control group, most deaths cases in COVID-19 critically ill patients occurred among patients who had ≥2 comorbids.12 This shows that there is a relationship between the number of comorbidities and mortality in COVID-19 patients. The difference in the number of comorbidities between the intervention and control groups is a factor that needs to be considered in determining the success of secretome therapy in this study.\n\nThis study has several limitations. The limited number of subjects in this study is one of the factors that can affect the insignificance of the results in this study. In addition, the number of doses, frequency of administration, and time of administration of secretome are also factors that need to be studied further to determine the efficacy of secretome therapy. The results of this study are also expected to be the basis for further studies regarding the implementation of the use of mesenchymal stem cell secretomes as a COVID-19 therapy.\n\n\nConclusions\n\nOur study showed a significant increase of inflammation markers in the control group on the 14th day after the intervention, compared to the intervention group. The ratio of inflammatory to anti-inflammatory markers on the seventh and 14th days after intervention also did not increase in the intervention group. On the seventh day after intervention, most of the subjects in the control group also had significantly high IL-6 levels and high ferritin levels. There is no adverse event reported. MSC secretome is a safe and promising treatment modality for severe COVID-19.\n\n\nDeclarations\n\nThis study has received ethical approval from The Ethics Committee of the Faculty of Medicine, University of Indonesia – Dr. Cipto Mangunkusumo Hospital with protocol number 20-07-0811 on 10th August 2020. All study participants or participants’ family have given their written informed consent regarding their participation and data publication in this study.\n\nThis study was registered in clinicaltrials.gov (NCT05122234).\n\n\nData availability\n\nOSF: “Effectiveness and Safety Profile of Mesenchymal Stem Cell Secretomes as a Treatment for Severe Cases of COVID-19”, https://doi.org/10.17605/OSF.IO/NUAVY.28\n\nThis project contains the following file:\n\n• Study Raw Data.xlsx\n\nOSF: CONSORT checklist for ‘Effectiveness and safety profile of mesenchymal stem cell secretomes as a treatment for severe cases of COVID-19: a randomized controlled trial’, https://doi.org/10.17605/OSF.IO/NUAVY.28\n\nData are available under the licence of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nCompeting interests\n\nMurdani Abdullah, Ismail Hadisoebroto Dilogo, Jeanne Adiwinata Pawitan, Cosphiadi Irawan, Rahyussalim, Dita Aditianingsih, Isabella Kurnia Liem, Robert Sinto, Adityo Susilo, Mira Yulianti, Raden Rara Diah Handayani, Erlina Burhan, Triya Damayanti, Irandi Putra Pratomo, Herry Wibowo stated that there were no competing interests.", "appendix": "Acknowledgments\n\nWe thank to Indonesian Ministry of Research and Technology/National Research and Innovation Agency through COVID-19 Research and Innovation Consortium Program for supporting this research.\n\n\nReferences\n\nCucinotta D, Vanelli M: WHO Declares COVID-19 a Pandemic. Acta Bio. Medica Atenei Parm. 2020 Mar 19; 91(1): 157–160.\n\nHu B, Huang S, Yin L: The cytokine storm and COVID-19. J. Med. Virol. 2021 Jan; 93(1): 250–256. PubMed Abstract \| Publisher Full Text\n\nMokhtari T, Hassani F, Ghaffari N, et al.: COVID-19 and multiorgan failure: A narrative review on potential mechanisms. J. Mol. Histol. 2020 Dec; 51(6): 613–628. PubMed Abstract \| Publisher Full Text\n\nMahajan A, Bhattacharyya S: A brief review on potential application of mesenchymal stem cell and secretome in combating mortality and morbidity in COVID-19 patients. Biom. J. 2021 Feb; 44(1): 63–73. Publisher Full Text\n\nChen G, Wu D, Guo W, et al.: Clinical and immunological features of severe and moderate coronavirus disease 2019. J. Clin. Invest. 2020 Apr 13; 130(5): 2620–2629. PubMed Abstract \| Publisher Full Text\n\nMerza MY, Hwaiz RA, Hamad BK, et al.: Analysis of cytokines in SARS-CoV-2 or COVID-19 patients in Erbil city, Kurdistan Region of Iraq. Koval M, editor. PLoS One. 2021 Apr 29; 16(4): e0250330. PubMed Abstract \| Publisher Full Text\n\nFeng Y, Ling Y, Bai T, et al.: COVID-19 with Different Severities: A Multicenter Study of Clinical Features. Am. J. Respir. Crit. Care Med. 2020 Jun 1; 201(11): 1380–1388. PubMed Abstract \| Publisher Full Text\n\nKong Y, Han J, Wu X, et al.: VEGF-D: a novel biomarker for detection of COVID-19 progression. Crit. Care. 2020 Dec; 24(1): 373. PubMed Abstract \| Publisher Full Text\n\nQue Y, Hu C, Wan K, et al.: Cytokine release syndrome in COVID-19: a major mechanism of morbidity and mortality. Int. Rev. Immunol. 2021 Feb 22; 1–14. PubMed Abstract \| Publisher Full Text\n\nSoy M, Keser G, Atagündüz P, et al.: Cytokine storm in COVID-19: pathogenesis and overview of anti-inflammatory agents used in treatment. Clin. Rheumatol. 2020 Jul; 39(7): 2085–2094. PubMed Abstract \| Publisher Full Text\n\nChouw A, Milanda T, Sartika CR, et al.: Potency of Mesenchymal Stem Cell and Its Secretome in Treating COVID-19. Regen Eng Transl Med. 2021 Mar 10 [cited 2021 Nov 11]; 1–12. PubMed Abstract \| Publisher Full Text\n\nDilogo IH, Aditianingsih D, Sugiarto A, et al.: Umbilical cord mesenchymal stromal cells as critical COVID -19 adjuvant therapy: A randomized controlled trial. Stem Cells Transl. Med. 2021 Sep; 10(9): 1279–1287. PubMed Abstract \| Publisher Full Text\n\nMeng F, Xu R, Wang S, et al.: Human umbilical cord-derived mesenchymal stem cell therapy in patients with COVID-19: a phase 1 clinical trial. Signal Transduct. Target. Ther. 2020 Dec; 5(1): 172. PubMed Abstract \| Publisher Full Text\n\nPutra A, Widyatmoko A, Ibrahim S, et al.: Case series of the first three severe COVID-19 patients treated with the secretome of hypoxia-mesenchymal stem cells in Indonesia. F1000Res. 2021 Mar 22; 10: 228. Publisher Full Text\n\nPraveen Kumar L, Kandoi S, Misra R, et al.: The mesenchymal stem cell secretome: A new paradigm towards cell-free therapeutic mode in regenerative medicine. Cytokine Growth Factor Rev. 2019 Apr; 46: 1–9. Publisher Full Text\n\nAbbasi-Malati Z, Roushandeh AM, Kuwahara Y, et al.: Mesenchymal Stem Cells on Horizon: A New Arsenal of Therapeutic Agents. Stem Cell Rev. Rep. 2018 Aug; 14(4): 484–499. PubMed Abstract \| Publisher Full Text\n\nBanimohamad-Shotorbani B, Farajpour H, Sefat F, et al.: Efficacy of mesenchymal stromal cells and cellular products in improvement of symptoms for COVID-19 and similar lung diseases. Biotechnol. Bioeng. 2021 Jun; 118(6): 2168–2183. PubMed Abstract \| Publisher Full Text\n\nKementerian Kesehatan RI: Pedoman Pencegahan dan Pengendalian Coronavirus Disease. (Covid-19) Revisi 5. Jakarta: Kementerian Kesehatan RI;\n\nTang L, Jiang Y, Zhu M, et al.: Clinical study using mesenchymal stem cells for the treatment of patients with severe COVID-19. Front. Med. 2020 Oct; 14(5): 664–673. PubMed Abstract \| Publisher Full Text\n\nShu L, Niu C, Li R, et al.: Treatment of severe COVID-19 with human umbilical cord mesenchymal stem cells. Stem Cell Res Ther. 2020 Dec; 11(1): 361. PubMed Abstract \| Publisher Full Text\n\nSaleh M, Vaezi AA, Aliannejad R, et al.: Cell therapy in patients with COVID-19 using Wharton’s jelly mesenchymal stem cells: a phase 1 clinical trial. Stem Cell Res Ther. 2021 Dec; 12(1): 410. PubMed Abstract \| Publisher Full Text\n\nAdas G, Cukurova Z, Yasar KK, et al.: The Systematic Effect of Mesenchymal Stem Cell Therapy in Critical COVID-19 Patients: A Prospective Double Controlled Trial. Cell Transplant. 2021 Jan 1; 30: 096368972110249. PubMed Abstract \| Publisher Full Text\n\nHussein AM, Taha ZB, Gailan Malek A, et al.: D-Dimer and Serum Ferritin as an Independent Risk Factor for Severity in COVID-19 Patients. Mater Today Proc. 2021 Apr; S2214785321028583; PubMed Abstract \| Publisher Full Text\n\nZhang Q, Huang K, Lv J, et al.: Case Report: Human Umbilical Cord Mesenchymal Stem Cells as a Therapeutic Intervention for a Critically Ill COVID-19 Patient. Front. Med. 2021 Jul 8; 8: 691329. PubMed Abstract \| Publisher Full Text\n\nMetcalfe SM: COVID-19 lockdown: de-risking exit by protecting the lung with leukaemia inhibitory factor (LIF). Med. Drug Discov. 2020 Jun; 6: 100043. Publisher Full Text\n\nQuinton LJ, Mizgerd JP, Hilliard KL, et al.: Leukemia Inhibitory Factor Signaling Is Required for Lung Protection during Pneumonia. J. Immunol. 2012 Jun 15; 188(12): 6300–6308. PubMed Abstract \| Publisher Full Text\n\nWang Z, Ye D, Wang M, et al.: Clinical Features of COVID-19 Patients with Different Outcomes in Wuhan: A Retrospective Observational Study. Xu Z, editor. Biomed. Res. Int. 2020 Oct 5; 2020: 1–10. Publisher Full Text\n\nAbdullah M: Effectiveness and Safety Profile of Mesenchymal Stem Cell Secretomes as a Treatment for Severe Cases of COVID-19. OSF. 2022 [cited 2022 Jun 1]. osf.io/rdc9a." }	[ { "id": "336476", "date": "19 Nov 2024", "name": "Chenxiao Wang", "expertise": [ "Reviewer Expertise respiratory immunology", "preclinical study." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe study titled Effectiveness and safety profile of mesenchymal stem cell secretome as a treatment for severe cases of COVID-19 by Abdullah et al. is a randomized, double-blind, multicenter, placebo-controlled trial aimed at assessing the effectiveness and safety of mesenchymal stem cell (MSC) secretome for severe COVID-19 patients. The trial involved 40 participants, divided into an intervention group receiving MSC secretome and a control group receiving a placebo, with both groups also receiving standard COVID-19 therapy. The primary outcome assessed was the change in inflammatory markers, and secondary outcomes included clinical, laboratory, and radiological outcomes, as well as safety and RT-PCR conversion rates.\nThe article provides an in-depth analysis of the potential benefits of MSC secretome as a cell-free therapy for severe COVID-19, highlighting its immunomodulatory and anti-inflammatory properties. However, there are a few questions that need to be further discussed.\n1. Minor point: Is the study design appropriate and is the work technically sound?\nPartly. While the study design is appropriate for the research question, employing a randomized, double-blind, and placebo-controlled approach, a more specific explanation on the administration route is needed: The secretome of mesenchymal stem cells (MSCs) is a collection of substances released by MSCs into their surrounding environment and it is believed to be released and work locally in the lung. In this study, the authors chose the i.v. treatment. This needs more explanation and discussion.\n2. Minor point: In the reference No.8, It states, \"Compared to the severe group, critical cases were of significantly older ages and showed higher white blood cell counts and neutrophil counts. Levels of VEGF-D, TNF-α, SCF, LIF, IL-2, IL-4, IL-6, IL-8, IL-10, IL-15, IL-17A, IL-18, IL-1β, and IFN-γ were significantly higher in the critical group than in the severe group.\" In a word, the reference paper shows the difference between two COVID severities rather than COVID and non-COVID patients as the authors cited in the background part. Please revise.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "358402", "date": "24 Jan 2025", "name": "Mutiara Indah Sari", "expertise": [ "Reviewer Expertise Genetics", "Immunology", "Metabolism" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis randomized controlled trial studies the effectiveness and safety profile of mesenchymal stem cell (MSC) secretome on severe COVID-19. The variables examined include IL-6, IL-10, LIF, VEGF and ferritin levels as well as laboratory parameters, RT-PCR conversion rates, chest radiography parameters, and mortality.\nThere are a few points that need to be considered:\n- For both the abstract and the main text, consider using a different term from “intervention” for the placebo treatment of the control group to avoid confusion between the control and intervention group.\n- In the abstract, the results section needs to describe more about the effects of secretome on the intervention group, compared to the control group.\n- In the discussion section of the main text, please elaborate on the mechanism of secretome that leads to the different outcome between the intervention group and the control group. As secretome contains numerous molecules, describe how the dominant molecule in the administered secretome affects the overall outcome.\n- In the conclusion section of the main text, as the aim of this study is to investigate the effectiveness and safety profile of MSC secretome as a treatment for severe COVID-19, compare the biomarker levels of the intervention group to the control group.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "349922", "date": "06 Feb 2025", "name": "Usha Rani Kandula", "expertise": [ "Reviewer Expertise Nursing research and administration" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe study is well-presented, and citing current literature. The randomized controlled design is appropriate and methodologically sound. Detailed methods and statistical analyses are provided for replication. Source data availability ensures reproducibility. Conclusions are well-supported by results, demonstrating the effectiveness and safety of mesenchymal stem cell secretome for severe COVID-19 cases.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	2	https://f1000research.com/articles/11-143
https://f1000research.com/articles/10-1087/v1	26 Oct 21	{ "type": "Research Article", "title": "Autism spectrum disorder in architecture perspective: a review of the literature and bibliometric assessment of research indexed in Web of Science", "authors": [ "Reham Moniem Ali", "Deema Faisal Al-Saleh", "Khadeeja M N Ansari", "Hala A. El-Wakeel", "Mai Ibrahim Shukri", "Reham Moniem Ali", "Hala A. El-Wakeel", "Mai Ibrahim Shukri" ], "abstract": "Purpose:\nThe primary objective of this research paper was to explore the current state-of-the-art research on autism spectrum disorder from a designer's perspective. An increasing number of scholarly publications in this discipline have urged researcher interest in this topic; however, there is still a lack of quantitative analysis. Therefore, this paper aims to analyze global research output on autism spectrum disorder from a designer's perspective during 1992–2021. Methodology: A bibliometric method was employed to analyze the published literature from 1992–2021. 812 papers were downloaded from the Web of Science core collection for analysis focused on annual growth of literature, prolific authors, authorship pattern, productive organizations, countries, international collaboration, literature trends by keyword analysis, and identifying the funding agencies. Various bibliometrics and scientometrics software were used to analyze the data, namely Bibexcel, Biblioshiny, and VOS viewer. Results: There were 812 research papers published in 405 sources during 1992–2021. 2019 was noted as the most productive year (NP=101), and 2014 received the highest number of citations (TC=6634). Researchers preferred to publish as journal articles (NP=538; TC=24922). The University of Toronto, Canada, was identified as a productive institution with 42 publications and 5358 citations. The USA was the leading producing country with 433 publications, and most of the researchers publish their work in the journal \"Scientific Reports\" (NP=16). The word \"autism\" (NP=257) and \"architecture\" (NP=165) were the most frequently used keywords in autism research.", "keywords": [ "Autism", "Autism Spectrum disorder", "Bibliometrics", "Scientometric", "Architecture", "Relevant source", "Web of science." ], "content": "Introduction\n\nAutism spectrum disorder (ASD) is a complicated neurological disorder that until now has been inscrutable. The population of individuals on the spectrum worldwide is increasing due to the increased awareness. As their numbers grow, professionals in many fields started studying their ASD cases to provide them with a better life (Hauptman et al., 2019). Individuals on the spectrum are part of a growing population usually ignored in design despite the current tendency to create designs that focus on persons with special needs. There are binding recommendations and laws on designing buildings that respect physical disabilities, and the field is rich in design applications for physical needs (Sánchez et al., 2011). By contrast, there is utter indifference towards the person with mental health disabilities. The built environment can cause extra confusion, which leads to a negative impact on children with ASD. Environmental and behavioral research has profoundly influenced the practice of interior architecture. Architects and interior architects are responsible for providing an inclusive built environment to improve the quality of life, especially for people with special needs (Kopec, 2012).\n\nA vast amount of literature has been published on autism in medical and psychological journals over the years. However, few studies from an architectural and interior architecture perspective have been published. Recently, architects have become interested in finding out the relationship between environment and autistic behavior to provide a suitable environment and support wellbeing. Today's literature is based on disability studies, environmental behavior studies, environmental design considerations, and guidelines to address behavioral aspects for autistic children. This study will cover this knowledge gap, and the literature review will progress from the general concept of autism to focus on autism and the physically built therapeutic environment.\n\n\nLiterature review\n\nASD is a neurodevelopmental condition that affects children from a young age. It is marked by functional impairment in social communication, limited interests, and repetitive habits, as well as hypersensitivity to touch, vision, taste, or sound in certain people. Autistic disorder, high-functioning autism (HFA), Asperger syndrome (AS), pervasive developmental disorder-not otherwise specified (PDD-NOS), and atypical autism are all diagnostic terminology that has previously been employed. ASD is expected to affect one out of every 88 children in the United States, with one out of every 56 boys being affected. (Taghizadeh et al., 2015)\n\nThe diagnosis rates for ASD have increased sharply worldwide in the last 40 years compared with other disabilities. The environment plays a role in human behavior. ASD children have sensory processing difficulties, which create challenges in understanding the surrounding environment, thus affecting their behaviors negatively (Sánchez et al., 2011).\n\nPallasmaa (2005) diagnosed with ASD, said: 'I confront the city with my body.' The interaction between a person and their environment produces many physical and mental challenges for ASD. Therefore, the built environment is an important factor that significantly inﬂuences, directly and indirectly, individuals' behavior. ASD children are a special case, which should be defined to help them access space and inhabit it. Two issues must be considered to understand the impact of the environment on the development of one's life (Horne, 1997):\n\n1- The identification of the physical environment in its material and symbolic context.\n\n2- The impact of the environment on one's behavior and how people perceive themselves and their surroundings.\n\nAutistic people have difﬁculties in processing the information from the physical environment through their senses, and they are forced to exert more effort to understand it. The difficulty in understanding provokes frustration and erratic behavior.\n\nA vast amount of literature has been published on autism in medical and psychological journals over the years. However, few studies from an architectural perspective have been published even though the role of the sensory environment in autistic behavior has been an issue of debate since Leo Kanner first defined the disorder in 1943 (Kanner, 1943). Recently, architects have become interested in finding out about the relationship between environment and autistic behavior to provide a suitable environment and support wellbeing.\n\nFew interior designers and architects have yet started to define codes and guidelines as a design solution for ASD to build autism-friendly surroundings that support users with ASD and prepares them to face other environments. The designer's approach is usually to compare between children with ASD and without through their behaviors to find the differences in their needs in the environment (Delmolino & Harris, 2012). Environmental and behavioral research has profoundly influenced architecture, and there is a growing need and trend towards user-centered and evidence-based design research.\n\nMany human–environment interaction research conducted by environmental psychologists have focused on the environment's psychological factors rather than the physical setting. This section will clarify the relationship between autism and the environment.\n\n1- Human ecosystem (HES)\n\nIn 1992, Guerin defined the Human ecosystem (HES) theory model in a learning environment to understanding autistic behavior. The variables in this progress are related to the specific model components:\n\na. HO, human organism: gender, age, number of children, and the level of diagnosing\n\nb. DE, designed environment: control of entry and exit (safety/security); classroom configuration and adaptability to make changes; lighting (artificial light/daylight); acoustics/noise; thermal comfort (temperature, humidity, ventilation, i.e. indoor air quality); wayfinding; building; FF&E (furnishings, fixtures, and equipment) materials and finishes (color, pattern) (Kopec, 2012; Martin & Guerin, 2010).\n\nc. NE, natural environment: access to daylight and natural ventilation, as well as green space and/or water (i.e. landscape elements).\n\nd. SE, social environment: visual, auditory, and physical communication method, as well as communication and interaction among children and caregivers in the same physical area.\n\n2- Performance prediction model (PPM)\n\nThe performance prediction model (PPM) describes the transactions between the users and their physical environment through the behavior. Also, understand how the physical environment affects user variables by observing behavior. In addition, clarify the interaction between the three components to lead to universal design principles. Even though this model is not explicitly created for ASD children, the research can be applied to users with different personal characteristics or functional abilities. This model consists of three main components (user variables, behavior, and environment). The variables in this progress are related to these specific components:\n\na. User abilities: individual characteristics and functional abilities.\n\nb. Task outcome: behavior and experiential.\n\nc. Physical environment: physical characteristics, organization, and ambience.\n\nd. Universal design: equitable use, flexibility in use, simple and intuitive, perceptible information, tolerance for error, low physical effort and size and space for approach and use.\n\nThis model is used as a guide for the designer in designing different types of the physical environment for different users because it helps to categorize the users according to their characteristics, which are:\n\n• Cognitive abilities: include all complex mental function prosses to make an action, for example, decision-making and planning (ICF illustration library, 2021)\n\n• Social and communication: include all components of the communication process with others by using different devices and methods to deliver or perceive massages (World Health Organization, 2017)\n\n• Sensory functions: includes touch, smell, visual, and hearing systems (ICF illustration library, 2021)\n\n• Mobility: the ability to manage body movements such as changing body position or location, carrying objects, performing physical activities (ICF illustration library, 2021)\n\nThe characteristics of autism are varied in intensity, degree, and amount and manifest differently from person to person and over time. The common characteristics associated with ASD are loosely based on the DSM-5, common features of ASD, and PMM on ASD.\n\n1. Cognitive abilities\n\n2. Social and communication interaction\n\n3. Sensory function\n\n4. Activity performance\n\nThere is limited research on how environments may affect behavior and be designed to meet the needs of those with ASD. Also, there is a lack of information on the experience of spaces and perceptions by people with autism. This research will try to fill this missing gap and help with understanding the interaction between children with ASD and their physical environment.\n\n3- Theoretical underpinnings of design\n\nInterior designers concentrate on the design of the interior environment with the requirements of the person who will be inhabiting the space as the driving force behind all design decisions. Human factors, lighting, occupant wellbeing and performance, post-occupancy evaluation, research, theories about the relationship between human behavior and the designed environment, and universal design are among the ten knowledge areas covered by the 'Human Environment Needs: Research and Application' (HEN) category.\n\nExperts on ASD consider that the first six years of school, from preschool to sixth grade, are important in reaching children and laying the groundwork for their lifelong learning and general well-being. Even when daily activities are meticulously organized, classrooms attended by children with ASD, or other children are highly dynamic, unpredictable environments. Because of this instability, examining the architecture of classroom space in schools where children with ASD attend from preschool to sixth grade is difficult. However, the framework identified by (Guerin, 1992), which recognized the interaction of the human organism (HO), the BTE, the natural environment (NE), and the behavioral environment (BHE).\n\n\nResearch questions\n\n1) What are the annual research trends of autism in architecture during 1992–2021?\n\n2) What are the most important types of research in autism?\n\n3) Which authors are the most prolific, and what is the authorship trend in autism research?\n\n4) What are the most relevant journals in journals in autism?\n\n5) What are the most important organizations and counties in autism?\n\n6) What are the most used keywords of autism in the field of architecture?\n\n7) What are the most global collaborative countries producing scientific literature on autism?\n\n8) What are the most cited documents and cited references in autism?\n\n9) What the most influential funding agencies?\n\n\nResearch methodology\n\nStatistical techniques are used to analyze different types of publications such as books, conferences, journal articles, etc., known as bibliometrics. Scientometrics is the sub-field of bibliometrics that studies quantitative means of investigation, scholarly publishing practices, publishing trends, trend topics, etc. This study, therefore, applies the scientometric method to ASD in the architecture field. The required literature in autism retrieved from Web of Science (as of 4th June 2021).\n\nThe following search query involved in the Web of Science database (Clarivate Analytics, 2020)\n\n• TOPIC: \"autism\"\n\n• Refined by: TOPIC: \"architecture\"\n\n• Further refined by language: English\n\n• Timespan: All years. Indexes: SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, ESCI.\n\n812 documents have been retrieved (Figure 1) for final analysis during 1992–2021. All the research data was downloaded in BibTeX, Tab-Delimited (win), plain text, and analyzed with Microsoft Excel (RRID:SCR_016137; Google Sheets (RRID:SCR_017679) is an open access alternative) and Scientometric and bibliometrics tools, namely Bibexcel (Persson et al., 2009), Biblioshiny (Aria & Cuccurullo, 2017), and VOSviewer (van Eck & Waltman, 2010).\n\n\nResults and discussion\n\nFrom 1992 to 2021, 405 sources were contributed by 5088 authors with 812 papers in autism. Single authored documents were 61 papers; hence authors in autism produce more research in collaboration. The average number of years of publications is 5.74, the average number of citations per document 43.21, and the average number of citations per year per document 5.711. 36,654 references have been consulted to produce 812 research papers. The number of documents per author is 0.16, authors per document are 6.27, Co-authors per document is 8.16, and the collaboration index is 6.71.\n\nThe first research paper on autism was recorded in 1992 with 382 citations (no publication indexed in 1993, 1995, 1996, 1997, and 2003), similar results reported by (Kumar et al., 2021). Though the research output gradually increases, but shallow up until 2012. The autism research increased markedly after 2013, noticeably more than 50 papers appeared every year after 2013. The year 2019 was the most successful in term of the number of the article (NP=101), followed by the year 2016 and 2017, in which the second highest number of research papers published, coincidently the year 2018 and 2020 have equal number published articles (NP=84) and the year 2021 have 35 papers with 19 citations. The highest number of citations received in 2014 (TC=6634) for 53 publications, followed by the year 2011 (TC=4078) for 31 papers and the year 2010 (TC=3108, TP=34) (Table 1).\n\nNP=Number of Publication TC=Total Number of Citations\n\nThe journal articles (NP=537) were the most preferred form, which agrees with (Rahaman et al., 2021b). The review found a second preferred form (NP=142), followed by proceedings papers (NP=71) and then meeting abstract (NP=17). Other documents were minor in the list, published only three papers each. On the other hand, the articles also received the highest number of total cations (24922), followed by review (TC=8916) (Table 2).\n\nNP=Number of Publication *TC=Total Number of Citations\n\nIt is evident that the top ten organizational productivity ranges between 25 to 42 publications (Table 3). The University of Toronto is the leading organization in autism research (NP=42), followed by Vanderbilt University (NP=37), University of California, Los Angeles (NP=35), Yale University (NP=33), and Massachusetts General Hospital (NP=30). Harvard Medical School (NP=25) identified as the minor producer of research in the top ten list. Interestingly, most of the listed organization are in the USA (9 organizations), and one organization from Canada. Stanford University was the most cited organization (TC=6686) for 28 publications, followed by Yale University (TC=6059) for 33 research in autism.\n\nMoreover, it is found that the top eight countries produced over 50 research papers (Table 4). Only two countries have over 100 articles on autism. The USA had outstanding research output in autism with 433 publications and 27124 citations, followed by the UK (118 publications, 7569 citations), Canada (79 publications, 6816 citations), China (72 publications, 3339 citations), and France (60 publications, 3304 citations). The analyses reveal that half of the research in autism contributed by the USA that received the highest number of citations (TC=27124) for 433 publications, followed by the UK with 7569 citations with 118 publications, and Canada with 6816 citations and 79 publications. Australia managed minimum citation (TC=2048) in the list with 46 publications.\n\nAll the top ten sources have more than 12 publications; coincidentally, six sources (American Journal of Human Genetics, American Journal of Medical Genetics Part B-Neuropsychiatric Genetics, Biological Psychiatry, Molecular Autism, Molecular Psychiatry, Neuron) produced 12 publications each. Scientific Reports (Nature Publishing Group) was considered the most relevant source with 14 publications and 203 citations, followed by Nature Neuroscience (Nature Publishing Group) with 14 publications and 1986 citations and Human Molecular Genetics and Plos One with 13 publications each and 1015 and 371 citations, respectively. The analysis reveals that most of the sources belongs to the Q1 category (eight sources), and two in Q2 category. The highest impact factor journal in the list was Nature Neuroscience (JIF=20.07), followed by Neuron (JIF=14.41) and Molecular Psychiatry (JIF=12.38) (Table 5).\n\nNP=Number of Publication TC=Total Number of Citations JIF=Journal impact factor **Q=Quartile\n\nInterestingly, we found that of 347 sources identified in autism spectrum research, only two were from the field of architecture, namely Archnet-Ijar International Journal of Architectural Research (NP=3, TC=5) and Architectural Design (NP=1, TC=2).\n\nThis analysis reveals that the article range of authors varied between nine and 12. Five authors (Devlin B, Geschwind DH, Scherer SW, State MW, and Wang Y) emerged as the most prolific authors with 13 publications each, 4383, 3409, 3338, 3662, and 333 citations, respectively. Buxbaum JD (Icahn School of Medicine at Mount Sinai) found as the second highest prolific author with 13 publications and 2970 citations, followed by Bourgeron T, Eichler EE, and Li Y with 11 publications and 2142, 1944, and 568 citations, respectively. Casanova MF (University of South Carolina School of Medicine) noted as the least contributed authors in the top ten list with nine publications and 361 citations. Devlin B (Mount Sinai School of Medicine) was the most cited author with 4383 citations for 13 publications, followed by Geschwind DH with 3409 citations for 13 publications, and Wang Y (Carnegie Mellon University) managed only 333 citations for 13 publications. The table also shows that the most prolific authors belong from the USA (7 authors), followed by Canada, France, and China. (Table 6).\n\nNP=Number of Publication *TC=Total Number of Citations\n\nThe Figure 2 illustrated the pattern of authorship in autism literature. It was clear from the figure that the authorship pattern ranged from single to two hundred and forty-seven. The analysis reveals that collaborative research is more prominent among the research of autism over the study period. The top six authorship patterns produced over 50 publications in the field. Three authorship patterns (NP=123) contributed a maximum article in autism, followed by two authorship (NP=120), four authorship (NP=93), five authorship (NP=79), single authorship (NP=61), and six authorship (NP=56). The authorship of 27, 36, 38, 39, 40, 42, 46, 56, 58, 65, 67, 73, 86, 88, 118, 125, 146, and 247 each contributed only single publications in autism. The results also showed that two authorship patterns received the highest number of citations (TC=4775), followed by five authorship (TC=3296) and Three authorship (TC=3071). Rahaman conducted a similar type of authorship pattern analysis (Rahaman et al., 2021a).\n\nFigure 3 shows analysis of all keywords that have been used in autism research during 1992–2021. The results showed that 3848 keywords appeared in autism research. To map the co-occurrence of all the keywords, minimum of 15 occurrences of keywords were considered for analysis. Out of 3848 keywords, only 79 keywords met the thresholds, and all 79 selected keywords are clustered in Figure 4 with 1737 links and total link strength (5557). The size of the ball indicates a strong network of keywords, with each color representing a distinct cluster.\n\nCluster 1 comprises 31 keywords (abnormalities, activation, adolescents, adults, architecture Asperger-syndrome, autism, autism spectrum disorder, autism spectrum disorders, behavior, brain, childhood, children, classification, connectivity, cortex, diagnostic interview, fMRI, functional connectivity, high-functioning autism, human cerebral-cortex, meta-analysis, networks, organization, patterns, pervasive developmental disorders, sleep, spectrum disorder, spectrum disorders, white-matter, and young-children).\n\nCluster 2 has 22 keywords (association, bipolar disorder, copy number variation, disorder, genes, genetic architecture, genetics, genome-wide association, heritability, identification, individuals, linkage, mutations, phenotype, prevalence, psychiatric-disorders, reveals, risk, schizophrenia, spectrum, susceptibility, and variants).\n\nCluster 3 includes 19 keywords (brain-development, copy number variants, copy-number variation, de-novo mutations, disease, disorders, epilepsy, evolution, expression, gene, intellectual disability, mechanisms, mental-retardation, network, neurodevelopmental disorders, neurons, prefrontal cortex, protein, and structural variation).\n\nCluster 4 has seven keywords (fragile x syndrome, fragile-x-syndrome, gene-expression, mental-retardation protein, mouse model, rett-syndrome, and synaptic plasticity).\n\nThe top ten keywords were autism (frequency=257), architecture (165), autism spectrum disorder (127), children (123), schizophrenia (92), autism spectrum disorders (91), de-novo mutations (86), Risk (73), brain (59) and expression (freq.=55) had weighty number of occurrence with strong total link strength.\n\nFigure 4 shows four alternative typologies of themes that can be visualized using a thematic map. The thematic parameter considered as, title selected for field, minimum number of words selected 80 and Unigram selected for graph.\n\nThe basic theme: Autism spectrum which represented by cluster 1 (autism, spectrum, disorder, children, brain, network, functional, connectivity, based, analysis, sleep, neural, developmental, learning, networks, structural, reveals, system, approach, design, matter, review, robot, resting, control, developing and white).\n\nThe motor theme: architecture human in cluster 2 (architecture, human, gene, syndrome, social, development, cortical, protein, autistic, model, synaptic, fragile, neuronal, cognitive, ASD, altered, behavior, mental, mice, role, cortex, expression, function, visual, cell, mouse, processing, and activity.\n\nNiche theme: genetic disorder placed in cluster 3 (disorders, genetic, variants, risk, schizophrenia, neurodevelopmental, genes, psychiatric, rare, common, de, genetics, novo, genomic, related, mutations, copy, disease, mechanisms, and sequencing).\n\nEmerging or declining theme: study genome represented by cluster 4 (study, genome, association, wide and evidence).\n\nThe top ten papers (Table 7) have more than 300 citations, published between 2007 and2015. \"Large-scale brain networks and psychopathology: a unifying triple network model\" (2011) by Menon V, published in Trends Cogn Sci was the topmost cited paper (1425 citations) (Menon, 2011), followed by \"Synaptic, transcriptional and chromatin genes disrupted in autism\" (2014) by De Rubeis S, appeared in \"Nature\" (1220 citations) (De Rubeis et al., 2014), \"The contribution of de novo coding mutations to autism spectrum disorder\" (2014) by Iossifov I, published in Nature (1118 citations) (Iossifov et al., 2014), \"Mapping autism risk loci using genetic linkage and chromosomal rearrangements\" (2007) by Szatmari (999 citations) (Szatmari et al., 2007). \"Dendritic spine pathology in neuropsychiatric disorders\" (2011) by Penzes (838 citations) (Penzes et al., 2011), and \"A genome-wide scan for common alleles affecting risk for autism\" was the least cited paper among the top ten (393 citations) (Anney et al., 2010). It was noticeable that half of the top ten cited papers were published by Nature Publishing Group. The article entitled \"Synaptic, transcriptional and chromatin genes disrupted in autism\" (De Rubeis et al., 2014) has the highest total citations per year (152.50).\n\nN/TC=Normalized total citation\n\nTable 8 explained the most top ten cited references in autism research. It is clear from the table that all listed references received more than 50 citations. Article entitled \"Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci\" (2015) by Sanders SJ, appeared in 'Neuron' was the most cited ( TC=92) reference in autism research (Sanders et al., 2015), followed by an article named 'Synaptic, transcriptional and chromatin genes disrupted in autism (2014) by De Rubeis S with 91 citations (De Rubeis et al., 2014), 'and 'The contribution of de novo coding mutations to autism spectrum disorder' (2014) by Lossifov I with 91 citations and appeared in the journal Nature (Iossifov et al., 2014). The cited references 'De novo gene disruptions in children on the autistic spectrum (2012) by Iossifov I published in 'NEURON' was the most diminutive receiver of citation with 61 TC (Iossifov et al., 2012).\n\nThere are only four funding agencies from the top 10 list which funded more than 100 research papers (Table 9). National Institutes of Health renowned as leading funding agency (313 publications, 23087 citations), followed by the United States Department of Human Health Services (313 publications, 22759 citations), the National Institute of Mental Health (182 publications, 16164 citations), European Commission (111 publications, 8476 citations), and National Institute of Child Health Human Development (66 publications, 7927 citations). The Wellcome Trust appeared as the least influential funding agency among the top ten (36 publications, 3959 citations). The USA was dominant in the top ten list (six funding agencies), followed by the UK (three funding agencies) and one agency from the EU.\n\nThe most dominant country collaborations were the USA and United Kingdom (51 publications), followed by the USA and Canada (43 publications), the USA and China (38 publications), the USA and Italy (26 publications), and the USA and the Netherlands (26 publications). The USA with Sweden collaboration (19 publications) was listed at the bottom of the top ten list. It was interesting to show that the USA collaborated with nine countries (the UK, Canada, China, Italy, the Netherlands, Germany, France, Australia, and Sweden). The UK followed this with two countries (the USA and Canada). (Figure 5).\n\n\nConclusion\n\nThe purpose of this study considered to completely overview the published literature on ASD in the architecture field. However, no other bibliometric analysis has been done from 1992 to 2021 that comprehensively evaluates and summarizes the literature, progress, and future directions of this key sub-area of ASD. Moreover, researchers investigating ASD can use the findings of this study to build techniques that are specific to the themes that are currently being researched (by consulting the visualization of analysis of this study). They can also discover the most influential publications, authors, and journals in this field to uncover research gaps and fresh discoveries. Here are few noteworthy predictions and emerging trends (from this study in terms of ASD in architecture research) and future insights. In conclusion, this study contributed to identify that there is very limited research has been done in ASD in field of architecture, the researchers should focus and consider this area of research. The results also direct us to conduct more academic research in this area.\n\n\nData availability\n\nZenodo: Underlying data for 'autism spectrum disorder in architecture perspective: A review of the literature and bibliometric assessment of research indexed in Web of Science'. https://doi.org/10.5281/zenodo.5080242\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nAnney R, Klei L, Pinto D, et al.: A genome-wide scan for common alleles affecting risk for autism. Hum Mol Genet. 2010; 19(20): 4072–4082. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAria M, Cuccurullo C: bibliometrix: An R-tool for comprehensive science mapping analysis. J Informetr. 2017; 11(4): 959–975. Publisher Full Text\n\nClarivate Analytics: Web of Science.2020. Reference Source\n\nCourchesne E, Pierce K, Schumann CM, et al.: Mapping Early Brain Development in Autism. Neuron. 2007; 56(2): 399–413. PubMed Abstract \| Publisher Full Text\n\nDe Rubeis S, He X, Goldberg AP, et al.: Synaptic, transcriptional and chromatin genes disrupted in autism. Nature. 2014; 515(7526): 209–215. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDelmolino L, Harris SL: Matching Children on the Autism Spectrum to Classrooms: A Guide for Parents and Professionals. J Autism Dev Disord. 2012; 42(6): 1197–1204. PubMed Abstract \| Publisher Full Text\n\nDi Martino A, Yan CG, Li Q, et al.: The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol Psychiatry. 2014; 19(6): 659–667. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGaugler T, Klei L, Sanders SJ, et al.: Most genetic risk for autism resides with common variation. Nat Genet. 2014; 46(8): 881–885. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGuerin B: BEHAVIOR ANALYSIS AND SOCIAL PSYCHOLOGY: A REVIEW OF LANA’S ASSUMPTIONS OF SOCIAL PSYCHOLOGY1. J Exp Anal Behav. 1992; 58(3): 589–604. Publisher Full Text\n\nHauptman M, Stierman B, Woolf AD: Children With Autism Spectrum Disorder and Lead Poisoning: Diagnostic Challenges and Management Complexities. Clin Pediatr (Phila). 2019; 58(6): 605–612. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHorne R: Representations of medication and treatment: Advances in theory and measurement. In: Perceptions of Health & Illness, London: Psychology Press, 1997; 520. Reference Source\n\nICF illustration library: ICF illustration library. 2021. Reference Source\n\nIossifov I, O’Roak BJ, Sanders SJ, et al.: The contribution of de novo coding mutations to autism spectrum disorder. Nature. 2014; 515(7526): 216–221. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nIossifov I, Ronemus M, Levy D, et al.: De novo gene disruptions in children on the autistic spectrum. Neuron. 2012; 74(2): 285–299. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKanner L: Autistic disturbances of affective contact. Nervous Child. 1943; 2: 217–250. Reference Source\n\nKopec DA: Environmental psychology for design. Fairchild Books. learning-therapy cluster.jpg. 2012. Reference Source\n\nKumar S, Joshi M, Rahaman MS, et al.: Research Productivity on Human Migration in the Himalayan Region during 1947-2019: A Bibliometric Study. Library Philosophy and Practice (e-Journal). 2021; 4909. Reference Source\n\nMarshall CR, Noor A, Vincent JB, et al.: Structural variation of chromosomes in autism spectrum disorder. Am J Hum Genet. 2008; 82(2): 477–488. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMartin CS, Guerin D: The interior design profession’s body of knowledge and its relationship to health: safety: and welfare. Council for Interior Design Accreditation. 2010. Reference Source\n\nMenon V: Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci. 2011; 15(10): 483–506. PubMed Abstract \| Publisher Full Text\n\nNeale BM, Kou Y, Liu L, et al.: Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature. 2012; 485(7397): 242–245. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nO’Roak BJ, Vives L, Girirajan S, et al.: Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature. 2012; 485(7397): 246–250. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPallasmaa J: The Eyes of the Skin: Architecture and the Senses. John Wiley & Sons. 2005. Reference Source\n\nPenzes P, Cahill ME, Jones KA, et al.: Dendritic spine pathology in neuropsychiatric disorders. Nat Neurosci. 2011; 14(3): 285–293. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPersson O, Danell R, Schneider JW: How to use Bibexcel for various types of bibliometric analysis. In: Celebrating scholarly communication studies: A Festschrift for Olle Persson at his 60th Birthday. ed. F Åström, R Danell, B Larsen, J Schneider. International Society for Scientometrics and Informetrics. 2009. Reference Source\n\nPinto D, Pagnamenta AT, Klei L, et al.: Functional impact of global rare copy number variation in autism spectrum disorders. Nature. 2010; 466(7304): 368–372. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nRahaman MS, Abdel Magid IM, Ahmad S, et al.: Scientometric Profile of the Imam Abdulrahman Bin Faisal University : A leading University of Eastern Province, Saudi Arabia. Libr philos pract. 2021a; 1–23. Reference Source\n\nRahaman MS, Kumar S, Ansari KMN, et al.: Twenty-five years of global research publications trends of novel coronavirus: A scientometrics assessment. Libr philos pract. 2021b; 1–17. Reference Source\n\nSánchez PA, Vázquez FS, Serrano LA: Tourism and the Built Environment. Architectural Tourism. 2011; 7–56. Publisher Full Text\n\nSanders SJ, He X, Willsey AJ, et al.: Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci. Neuron. 2015; 87(6): 1215–1233. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSanders SJ, Murtha MT, Gupta AR, et al.: De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature. 2012; 485(7397): 237–241. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSebat J, Lakshmi B, Malhotra D, et al.: Strong association of de novo copy number mutations with autism. Science (New York, N.Y.). 2007; 316(5823): 445–449. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSzatmari P, Paterson AD, Zwaigenbaum L, et al.: Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nature Genetics. 2007; 39(3): 319–328. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nTaghizadeh N, Davidson A, Williams K, et al.: Autism spectrum disorder (ASD) and its perioperative management. Paediatr Anaesth. 2015; 25(11): 1076–1084. PubMed Abstract \| Publisher Full Text\n\nvan Eck NJ, Waltman L: Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010; 84(2): 523–538. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWorld Health Organization: WHO Strategic Communications Framework. World Health Organization, 2017; 56. Reference Source" }	[ { "id": "97972", "date": "01 Nov 2021", "name": "Peter Kokol", "expertise": [ "Reviewer Expertise Computer science", "bibliometrics", "machine learning", "health informatics" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors performed an interesting bibliometric study. They focused mainly on quantitative aspects of the research on autism-related architectural design. However, the paper should be amended in some aspects to make it more informative for readers and to make the study repeatable.\nFirst, the introduction and the literature review should be extended with a description of bibliometrics, evidence of its successful use (and the reason why they selected bibliometrics as a knowledge synthesis method), the bibliometrics tools used should be shortly described and their use in the study stated more clearly. There are already some bibliometrics studies on autism and other disabilities already published, authors should point to them in the literature review and connect their research to already performed studies (they should also compare their results to results of similar studies in the discussion section).\nIn the results section, they should point out which bibliometric tool was used to produce them. The results should also be extended with qualitative aspects, actually, the discussion is mostly missing. What is the meaning of the results, who can use them, and for what purpose. In the conclusion, authors mention that research gaps, research directions could be derived from their results, but the readers could benefit much more if the authors themselves will reveal hot topics, gaps, directions, etc. Authors should describe revealed clusters from keywords analysis in more detail. They should use thematic or content analysis to name and describe clusters, point to relevant literature, etc.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8362", "date": "25 Jul 2022", "name": "Deema Al-Saleh", "role": "Author Response", "response": "Comment of reviewer: The authors performed an interesting bibliometric study. They focused mainly on quantitative aspects of the research on autism-related architectural design. However, the paper should be amended in some aspects to make it more informative for readers and to make the study repeatable. Authors Response: Done, the authors have worked more on the dataset and amended the annual literature growth table 1 to compare the literature growth in general with literature growth from the architectural and designers' perspective. Comment of reviewer: First, the introduction and the literature review should be extended with a description of bibliometrics, evidence of its successful use (and the reason why they selected bibliometrics as a knowledge synthesis method), the bibliometrics tools used should be shortly described and their use in the study stated more clearly. There are already some bibliometrics studies on autism and other disabilities already published, authors should point to them in the literature review and connect their research to already performed studies (they should also compare their results to results of similar studies in the discussion section). Authors Response: Done, the introduction and the literature review have been extended and previous bibliometric studies included and compared the results. In the results section, they should point out which bibliometric tool was used to produce them. The results should also be extended with qualitative aspects, actually, the discussion is mostly missing. What is the meaning of the results, who can use them, and for what purpose. In the conclusion, authors mention that research gaps, research directions could be derived from their results, but the readers could benefit much more if the authors themselves will reveal hot topics, gaps, directions, etc. Authors should describe revealed clusters from keywords analysis in more detail. They should use thematic or content analysis to name and describe clusters, point to relevant literature, etc. Authors Response: Done, all the issues raised have been addressed." } ] }, { "id": "101414", "date": "15 Dec 2021", "name": "Hashem Hussein Al-Attas", "expertise": [ "Reviewer Expertise I have enough knowledge in the field of bibliometric and scientometric studies." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors have collected an exclusive dataset from Web of Science using quantitative methodology. The bibliometric method to map the global research publication on autism spectrum disorder in architecture perspective, definitely contributes to the field and other researchers. It can help them decide the most productive country, journals, organization, pattern of authorship, most important author keywords, research themes, and new international collaboration. The analyses, results, and interpretation display interesting and beneficial data. Moreover, quality of the text is good. There are a few unnecessary capitalizations in the sentences, but ignorable. Overall the paper represents valuable information regarding autism spectrum disorder in architecture research.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/10-1087
https://f1000research.com/articles/11-815/v1	22 Jul 22	{ "type": "Case Report", "title": "Case Report: Ovarian fibroma: typical presentation with Meigs’s Syndrome", "authors": [ "Dipesh Upreti", "Dipesh Kumar Rohita", "Shailendra Kumar Yadav", "Niku Thapa", "Niku Thapa" ], "abstract": "Meigs’s syndrome is characterized by a triad of ovarian fibroma, ascites, and pleural effusion which can be managed surgically. Pleural effusion and ascites are usually transudative. Ovarian fibroma is an uncommon tumor. We herein report a case of Meigs’s syndrome in a 61-year-old woman who presented with complaints of abdominal pain for two-three months along with decreased appetite and constipation. On examination, there was decreased air entry in the right side of the chest, generalized abdominal distention, and a firm irregular mass was felt which was mobile and extending from upper border of symphysis pubis to just above the umbilicus on abdominal palpation. Chest X ray showed right sided pleural effusion, ultrasonogram (USG) abdominal and pelvis showed gross ascites, and a very large complex right ovarian cyst was confirmed by computed tomography (CT) scan. She underwent staging laparotomy with total abdominal hysterectomy, bilateral salpingo-oophorectomy and omental resection for biopsy. Biopsy showed right ovarian fibroma.", "keywords": [ "Ascites", "fibroma", "oophorectomy", "pleural effusion" ], "content": "Introduction\n\nMeigs syndrome is defined as the triad of benign ovarian tumor, especially ovarian fibroma with ascites and pleural effusion that resolves after tumor resection.1 It occurs as a result of increased capillary permeability thought to be a result of vascular endothelial growth factor (VEGF) production. Pleural effusions are usually right-sided because the transdiaphragmatic lymphatic channels are larger in diameter on the right.2 The pleural effusion as well as accompanying ascites are typically transudative. Meigs syndrome is also seen in cases like large, cystic leiomyomas or other benign ovarian tumors, thecoma, cystadenoma or granulosa cell tumor.3 Ovarian fibromas constitute 2 to 5% of all ovarian tumors and Meigs syndrome occurs in just 1% of these tumors indicating rarity of this clinical condition.4 Though diagnosis is possible preoperatively with ultrasound and magnetic resonance imaging (MRI), a high index of suspicion may be important as it radiologically and clinically mimics ovarian malignancy.5 This case is described for its rarity in presentation and clinical confusion in diagnosis.\n\n\nCase report\n\nThis was a case of 61-year-old, post-menopausal, Asian housewife, para four living three woman, presenting with abdominal distension for two to three months along with decreased appetite and constipation. She had a history of abdominal mass suspected of being ovarian malignancy for two years prior, for which she had not undergone any treatment due to personal difficulties. She experienced no vomiting and abdominal pain. She was former smoker and a known case of diabetes mellitus.\n\nOn examination, general condition was fair with no pallor, edema, lymphadenopathy or any signs of dehydration. Vitals were stable. On respiratory examination, decreased air entry was observed on the right side. Cardiovascular examination was normal. On abdomen examination, an irregular firm mass could be felt which was mobile and extending from the upper border of symphysis pubis to just above the umbilicus. The mass was mobile and non tender on palpation. Speculum examination showed normal cervix with rectocele. Vaginal examination showed an anteverted uterus with fullness felt in all the fornices separate from uterus.\n\nChest X-ray showed blunting of right costophrenic angle suggesting pleural effusion (Figure 1). Ultrasound of abdomen and pelvis revealed gross ascitis, huge complex right ovarian cyst (Figures 2, 3), confirmed by CT abdomen and pelvis as malignant ovarian tumor (Figures 4, 5). Ascitic tapping showed transudative nature of fluid, cancer antigen 125 (CA-125) was 84.6 U/ml and carcinoembryonic antigen (CEA) and lactate dehydrogenase (LDH) were normal.\n\nChest X-ray showing right sided pleural effusion.\n\nUltrasound of the abdomen and pelvis showing ovarian cyst and ascites.\n\nUltrasound of the abdomen and pelvis showing ovarian cyst and ascites.\n\nCT scan of the abdomen and pelvis showing the complex ovarian cysts.\n\nCT scan of the abdomen and pelvis showing the complex ovarian cyst.\n\nShe underwent staging laparotomy with total abdominal hysterectomy, bilateral salphingo-oophorectomy and omental resection for biopsy. There were six litres of straw-colored ascitic fluid with right ovarian hard mass with irregular surface of 15 × 10 cm on laparotomy (Figures 6, 7). Uterus, left ovary and cervix were normal. Omentum, bowel, liver, and peritoneal surface were normal. She was diagnosed with stage I C ovarian tumor. Her post-operative period after laparotomy with total abdominal hysterectomy and bilateral salphingo-oopherectomy was uneventful Biopsy report showed right ovarian fibroma. She recovered well and was living a comfortable life on follow up.\n\nGross surgical specimen showing right ovarian hard mass with irregular surface of 15 × 10 cm2.\n\nGross surgical specimen showing right ovarian hard mass with irregular surface of 15 × 10 cm2.\n\n\nDiscussion\n\nOvarian fibromas are the most common hormonally inactive sex cord stromal tumor variants that usually occur in perimenopausal and menopausal women.6 They represent only 4% of all ovarian neoplasms and are the least common major subtype of ovarian cancer. Meigs’s Syndrome occurs in just 1% of these cases. Although Meigs’s Syndrome is extremely rare, it is known to produce pleural effusion and ascites. Because several conditions are linked to the development of these common indications, the correct diagnosis and treatment are frequently missed.7 The cause of Meigs’s condition is still unknown. Ascites are a common symptom of ovarian tumors, and numerous causes have been proposed, including tumor torsion and restriction of venous drainage. According to laboratory investigations, the fluid collected in most but not all cases is transudate. The chest and abdomen fluids are identical in all patients.8 Peritoneal cytology, tumour markers, and other signs of malignant pathology may be confusing. Hence, laparotomy is essential for the correct identification of ovarian tumours.9 Due to the rarity of this condition, this is a diagnosis of exclusion but should be considered as soon as ovarian malignancy is excluded. The presentation in our case was similar where a long-standing ovarian mass presented with ascitis and pleural effusion.\n\n\nConclusions\n\nOvarian fibromas are uncommon sex cord stromal tumor commonly seen in post menopausal women. Ovarian fibroma could be a possibility in cases of ovarian tumors with ascitis and pleural effusion, especially when longstanding.\n\n\nPatient consent\n\nWritten and informed consent was obtained from the patient for the purpose of publication. The patient consented to their data being published.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.", "appendix": "References\n\nSaha S, Robertson M: Meigs’ and Pseudo-Meigs’ syndrome. Australas J Ultrasound Med. 2012 Feb; 15(1): 29–31. PubMed Abstract \| Publisher Full Text\n\nKrenke R, Maskey-Warzechowska M, Korczynski P, et al.: Pleural Effusion in Meigs’ Syndrome—Transudate or Exudate? Medicine (Baltimore). 2015 Dec 1; 94: e2114. PubMed Abstract \| Publisher Full Text\n\nLiao Q, Hu S: Meigs’ Syndrome and Pseudo-Meigs’ Syndrome: Report of Four Cases and Literature Reviews. J Cancer Ther. 2015; 06(04): 293–298. Publisher Full Text\n\nMohammed SA, Kumar A:Meigs Syndrome. StatPearls. Treasure Island (FL):StatPearls Publishing;2022 [cited 2022 May 21].Reference Source\n\nRouzier R, Berger A, Cugnenc PH: Meigs’ syndrome: is it possible to make a preoperative diagnosis? J Gynecol Obstet Biol Reprod (Paris). 1998 Sep; 27(5): 517–522. PubMed Abstract\n\nHorta M, Cunha TM: Sex cord-stromal tumors of the ovary: a comprehensive review and update for radiologists. Diagn Interv Radiol. 2015; 21(4): 277–286. PubMed Abstract \| Publisher Full Text\n\nMurayama Y, Kamoi Y, Yamamoto H, et al.: Meigs’ syndrome mimicking heart failure with preserved ejection fraction: a case report. BMC Cardiovasc Disord. 2020 Oct 7; 20(1): 436. PubMed Abstract \| Publisher Full Text\n\nLatta RJ, Lee PDK: Meigs’ syndrome in a young woman. J Adolesc Health Care. 1981 Jun 1; 1(4): 313–315. PubMed Abstract \| Publisher Full Text\n\nAbad A, Cazorla E, Ruiz F, et al.: Meigs’ syndrome with elevated CA125: case report and review of the literature. Eur J Obstet Gynecol Reprod Biol. 1999 Jan 1; 82(1): 97–99. PubMed Abstract \| Publisher Full Text" }	[ { "id": "233450", "date": "04 Mar 2024", "name": "Irene Iavarone", "expertise": [ "Reviewer Expertise Gynecologic oncology", "gynecology", "endometriosis", "Reproductive Medicine" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nI read with great interest the present Manuscript which falls within the aim of the Journal. In my honest opinion, the topic is interesting enough to attract the readers’ attention. Methodology is accurate and conclusions are supported by the data analysis. Nevertheless, authors should clarify some points and improve the discussion citing relevant and novel key articles about the topic. For all those reasons, I suggested performing the minor revisions.\n- Authors may specify whether they performed either peritoneal or pleural cytology;\n- Please clarify the Follow-Up time in the Case Report section;\n- In Discussion, Authors should parallel their findings with novel evidence about the topic. Please consider: (ref-1)\n- The Authors have not adequately highlighted the strength and limitations of the study. I suggest better specifying those points.\n\nIs the background of the case’s history and progression described in sufficient detail? Partly\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Partly\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Partly\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "262936", "date": "07 May 2024", "name": "Bijal Patel", "expertise": [ "Reviewer Expertise Gynecologic Oncology" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nCase report Review\n\nAbstract 1. Biopsy showed right….. Query - Do you mean the final histopathology ?\nCase report 2. Examination Ascitic fluid showed transudative…. Query - Kindly mention: - Was ascitic fluid sent for cytology? - Was a pleural fluid tapping done and sent for cytology? - Why was LDH done among the tumor markers?\n3. She was diagnosed with stage IC ovarian tumor….. Query - How has this stage been assigned?\n4. Biopsy report showed right ovarian fibroma…. Query - Was it the final Histopathology report? - Kindly elaborate whether this diagnosis was made on the gross and microscopic features … if so please include the microscopic pictures also and also mention description of microscopy including the atypical cells and mitotic rate. - Was any immunohistochemistry done… if so please mention.\n\nDiscussion 5. Laparotomy is essential for correct….. Query - Pathological diagnosis also plays a role… kindly discuss on those features and how it can be differentiated from fibrosarcoma and mitotically active ovarian fibroma\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "233449", "date": "29 May 2024", "name": "Heera Shenoy", "expertise": [ "Reviewer Expertise endocrine" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe abstract has been written well. The case presentation is in detail and well described. Images are apt and adequate.Discussion is short and could have been elaborated including pathophysiology, differential diagnosis and the options with counselling part. Pseudo meigs and the investigative approach could have been included and the clinical orientation need be established.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-815
https://f1000research.com/articles/11-811/v1	21 Jul 22	{ "type": "Case Report", "title": "Case Report: posterior approach with sub-laminar wiring as management of comminuted fracture of the odontoid process of the axis", "authors": [ "Carlos Novondo", "César Alas-Pineda", "Clarisa L. Reyes-Guardado", "Kristhel Gaitán-Zambrano", "Carlos Novondo", "Clarisa L. Reyes-Guardado", "Kristhel Gaitán-Zambrano" ], "abstract": "Background: Odontoid fractures (OF) account for 5-18% and 10-19% of all injuries at C2 and in the cervical region, respectively. According to the Anderson and D'Alonzo classification, there are three main types of OF: Type I, II and III. Most cases involving OF of the axis by high impact trauma result in death. Case presentation: A 21-year-old male patient, with comminuted OF caused by a high impact traffic accident. On admission, the patient reported moderate to severe pain in the posterior craniocervical junction, with significant limitation to lateral rotation of the head and severe cervical muscle spasm. There was evidence of comminuted OF of C2 without apparent displacement in the cervical region. The patient underwent surgery via a posterior approach with double sub-laminar wiring between C1 and C2. The procedure was considered to be completely resolutive with no postoperative complications or sequelae, with total recovery of the patient's functionality. Discussion: The posterior approach is a viable option when the anterior approach is not possible due to the nature of the comminuted fracture and risks of complications, even when it involves a degree of compromise in the rotation of the C1-C2 joint. OF is a medical emergency, requiring individualized treatment tailored to the characteristics of the patient. There are currently no standardized treatment guidelines for OF.", "keywords": [ "case report", "cervical axis vertebra", "odontoid process" ], "content": "List of abbreviations\n\nC1: first cervical vertebra\n\nC2: second cervical vertebra\n\nOF: odontoid fracture\n\n\nBackground\n\nThe odontoid process of the second cervical vertebra is a bony projection arising from the vertebral body of C2. It functions as a fulcrum for the lateral rotation of the ring of C1 or atlas over the body of the axis.1\n\nTraumatic axis injury is a common cervical spine injury, accounting for more than 20% of cervical fractures. The odontoid process of C2 is the main site of axis injury. Odontoid fracture (OF) accounts for 5-18% of C2 injuries, and 10-19% of all fractures in the cervical region.2 Multiple axis fractures account for only 1% of cervical spine fractures.3\n\nThe etiology of OF varies according to the patient’s age; in young people, the main cause is high-impact trauma, such as traffic accidents, sports injuries, or falls from great heights. In older people, it is the result of low-impact trauma that usually occurs when slipping and falling on the same plane of support4,5 and pathologies that compromise bone density.6\n\nHyperflexion of the spine is the most frequent mechanism of injury; it induces anterior displacement of the odontoid process of the axis. Hyperextension causes posterior displacement.7 Lateral flexion movements, compression or rotational forces are also mechanisms that cause OF.8,9\n\nThere are no standardized treatment guidelines for OF. Therapeutic options should be individualized to the patient's characteristics, experience and the surgeon's available resources. Conservative treatment includes external immobilization and use of devices including rigid collar or halo vest immobilization.5,10 Surgical treatment includes anterior fixation/posterior fixation. However, the most efficient treatment strategy is still under debate.11\n\nThe traumatism in the odontoid process of C2 was treated conservatively until 1910, when posterior fixation with wires began to be used as a surgical treatment, a procedure that has evolved since it was first described by Mixter and Osgood.9,12\n\nThe aim of this case report was to describe the surgical experience and favorable evolution in the treatment of a young patient with multiple OF of the axis, in which early age of presentation and causative mechanism in most cases are the cause of death. After surgery, the patient had no sequelae, with return to work and full recovery of quality of life.\n\n\nClinical presentation\n\nA 21-year-old male patient, from an urban area, with no prior pathological, pyscho-social, or past intervention history of interest, suffered high impact trauma in a motorcycle rollover road accident. He was transferred while unconscious to the emergency department of a private hospital for stabilization. He was later referred to the Hospital Militar del Norte in San Pedro Sula, Honduras, for further specialized treatment.\n\nHe was admitted to the emergency room wearing a rigid Philadelphia-type cervical collar and the initial evaluation revealed a Glasgow Coma Scale score of 15, no respiratory distress, and isochoric pupils. Intentional neurological examination showed a motor strength of 5/5 on the Daniels scale in all four extremities, and non-referred neurosensory alterations. Ecchymosis on the head and multiple abrasions on the body were present. On admission, the patient reported moderate to severe pain in the posterior craniocervical junction, with significant limitation to lateral rotation of the head and severe cervical muscle spasm. There were no signs of spinal cord compression. Blood biometry and blood chemistry studies were within normal parameters. Cerebral tomography revealed no abnormalities in encephalic structures, and cervical tomography evidenced comminuted OF of C2 without apparent displacement in the cervical region (Figure 1).\n\nOn day four hospitalization, a posterior surgical approach was performed due to comminution of the odontoid process of C2, a determining factor that contraindicated an anterior approach with an odontoid screw. Due to the patient's economic limitations, and lack of medical insurance to cover the costs of a posterior transpedicular screw system and lateral mass screws, we opted for sub-laminar wiring.\n\nThe patient was taken to the operating room, placed prone with the head in neutral position, and approached by the midline, exposing occipital bone, C1, C2 and C3. Double sub-laminar wiring was performed between C1 and C2 with 0.7-mm orthopedic cerclage wire. Autologous graft was harvested from the patient's left iliac crest. First, decortication of the C2 laminae and the posterior arch of C1 was performed. Bilateral simple wiring was closed and later, bilateral autologous bone graft wiring was performed (Figures 2, 3).\n\nThe patient left the operating room wearing a Philadelphia collar, extubated, with no motor deficit. He was transferred to the intermediate intensive care unit for monitoring. He was prescribed antibiotic coverage for two days and discharged on postoperative day two.\n\nThe use of a collar was indicated for three months after the procedure. However, the patient only used it for one week, but there were no complications during recovery. In functional terms, recovery was considered successful despite an approximately 50% decrease in cervical range of motion, which is within the expected range in C1-C2 fusion. Two control appointments were made with cervical tomography at three- and six-months post-operation (Figure 4). The patient made a total recovery without sequelae, with return to work and preserved quality of life.\n\n\nDiscussion\n\nFracture of the second cervical vertebra (C2) is the most common cervical spine injury in the geriatric population, accounting for 69% of cases with 36% in young adults.4,5 Our patient belongs to the minority group of those affected, who usually die as soon as the accident occurs in high-impact trauma or later during stabilization.\n\nAutopsy studies of patients killed in road traffic accidents have revealed that a significant proportion of mortality is attributed to fractures of the cervical region; axis fractures account for approximately 25–71% of fatalities.13 Neurological deficits occur in 8.5% of cases, and 2.4% of mortality is due to neurological deficits. A low percentage of patients with neurological injury are transported to the hospital in time.5 This patient suffered a comminuted fracture at cervical level in a high-impact road accident while riding a motorcycle, with transient loss of consciousness and no neurological deficit, and survived for subsequent stabilization and transfer without motor impairment.\n\nThe neurological risk associated with OF of C2 is potentially fatal, due to the proximity to the spinal cord, and the mobility of the atlantoaxial joint, which greatly increases the risk of instability. For these reasons, the associated morbidity and mortality is high.2,14\n\nC2 fractures can be subdivided into odontoid, Hangman's, and atypical fractures. OF account for approximately one-third of all cervical spine fractures, constituting 18% of cases in the general population and more than 50% in adults over 80 years of age.5,11\n\nAnderson and D’Alonzo (1974) classified the OFs of C2 into three main types: type I, which are oblique fractures in the apical region of the odontoid process; type II occurring at the junction of the odontoid process with the vertebral body; and type III, which are fractures that pass through the vertebral body.2,5,14 Type II OFs are the most frequent. Likewise, Hadley et. al propose an infrequent subtype of fracture: type IIA, which is characterized by comminuted fragments at the base of the vertebral body.5 The patient suffered a type IIA OF, which is why it is considered a peculiar case in the literature, with an atypical presentation of OF.\n\nAccording to recommendations of Ryken TC (2013), for the initial management of non-displaced OF type I, type II and type III OF, external cervical immobilization is recommended. In contrast, type II and III fractures with displacement ≥5 mm and commutation of the odontoid require surgical intervention for stabilization and fusion of the lesion.15\n\nSurgical intervention is indicated for unstable OFs associated with neurological risk and when non-union ranges are high.8 Recently, surgical treatment of these fractures has increased, due to faster mobilization, higher fusion rates, potential reduction in mortality, and preservation of C1-C2 joint motion.10\n\nThere are multiple options for fusion of the C1-C2 joint: screws to the lateral masses of C1, transpedicular screws to C2, and translaminar screws and posterior wires. The primary goal in performing any of the procedures is to align and stabilize the upper cervical spine.16\n\nThe C1-C2 complex allows 50% of cervical spinal rotation and 10° of flexion-extension and 50° axial rotation. Therefore, fusion of these segments will undoubtedly cause permanent loss of this movement. The anatomy and location of this complex along with the transfer of kinetic energy contribute to a wide variety of fractures.11,17 The technique of choice was the posterior approach, which involves the loss of lateral rotation of the atlantoaxial joint. The patient was informed of the potential sequelae and agreed to undergo the surgical procedure, judging that the benefits outweigh the surgical risks. The condition of the ligaments is the most important factor in the selection of treatment. The main elements that guide surgical treatment are the involvement of the ligamentous complex at the occipito-cervical junction, in the atlantoaxial complex, and in the complex between the second and third cervical vertebrae.18 Despite the integrity of the articular ligamentous complex, we decided to intervene surgically because of the instability and potential neurological risk caused by the OF.\n\nThe posterior approach consists of achieving stabilization and fusion with wire and bone graft from the iliac crest, which requires that the posterior arch of C1 and C2 are intact.10 The procedure provides strong bony fixation, with a high healing rate. However, the sacrifice of atlantoaxial rotational function is unavoidable.19 It is a viable option when the anterior approach is contraindicated in comminuted fracture, unfavorable antero-posterior fracture plane angulation, or rupture of the transverse ligament of C1-C2.19\n\nC1-C2 fusion can be performed to stabilize OFs; however, this involves compromising rotational function.5 Among the techniques of C1-C2 fusion with sub-laminar wire, the Gallie technique is one of the most commonly used, involving the use of a bone graft fixed by means of a sub-laminar wire below the spinous process of C2 and around the arch of C1.5,13 When performing the posterior approach, a variant of the technique was used in which the graft was placed over the arch of C1 above the laminae of C2. Unlike Gallie's technique, double bone grafting and bilateral double wiring were used.\n\nTransarticular fixation of C1-C2 with screws was a method introduced by Magerl and Seemann, which provides superior fixation to posterior wiring techniques and a greater range of rotational stiffness. In contrast, transarticular fixation cannot be performed in cases of fixed subluxation of C1 and C2 or where the vertebral artery follows an aberrant trajectory. The technique described by Harms addresses these limitations by inserting bilateral screws into the lateral masses of C1 and pedicles of C2.5 A limitation of the treatment process was the lack of medical insurance to cover the bilateral screw system, since it is not a procedure available within the public services of the country, and the patient’s economic condition prevented its application. Therefore, a surgical option that did not incur additional economic costs was used.\n\n\nConclusion\n\nOF is a medical emergency, due to its proximity to vital structures; it represents a high mortality rate when caused by high-impact mechanisms. The posterior approach is a viable option when the anterior approach is not possible due to the comminuted nature of the fracture and the risks of complications, even though it involves some degree of compromise in the rotation of the C1-C2 joint.\n\n\nConsent for publication\n\nWritten informed consent was obtained from the patient for publication of this case report and any accompanying images.\n\n\nData availability\n\nPatient’s files and datasets used to support the findings of this study are restricted by the ethics committee of the “Universidad Católica de Honduras” to protect the privacy of clinical data. Data are available to investigators who comply the criteria for access to confidential data under request to the ethics committee. Requests for access to these data should be directed to César Alas: cesar_alas10@hotmail.com.\n\nFigshare. CARE checklist. DOI: https://doi.org/10.6084/m9.figshare.20057225.v1", "appendix": "References\n\nTubbs RS, Hallock JD, Radcliff V, et al.: Ligaments of the craniocervical. J. Neurosurg. Spine. 2011 Jun; 14(6): 697–709. Publisher Full Text\n\nSan Lee L, Araya Ramirez E, Gonzales DE: Fractura de odontoides y tipos de tratamiento quirúrgicos. Revista Médica Sinergia. 2021; 6(1): e544. Publisher Full Text\n\nShinbo J, Sameda.: Simultaneous anterior and posterior screw fixation confined to the axis for stabilization of a 3-part fracture of the axis (odontoid, dens, ang hangman fracture). Neurosurg. Spine. 2014; 20(1): 265–269. PubMed Abstract \| Publisher Full Text\n\nRobinson AL, Möller A, Robinson Y, et al.: C2 Fracture Subtypes, Incidence, and Treatment Allocation Change with Age: A Retrospective Cohort Study of 233 Consecutive Cases. Biomed. Res. Int. 2017; 2017(1): 1–7. PubMed Abstract \| Publisher Full Text\n\nCarvalho AD, Figueiredo J, Schroeder GD, et al.: Odontoid Fractures: A Critical Review of Current Management and Future Directions. Clin. Spine Surg. 2019 Oct; 32(8): 313–323. Publisher Full Text\n\nIvancic PC: Odontoid Fracture Biomechanics. Spine. 2014; 39(24): E1403–E1410. Publisher Full Text\n\nClark CR, White AA 3rd: Fractures of the dens. A multicenter study. J. Bone Joint. Surg. 1985 Dec; 67(9): 1340–1348. PubMed Abstract \| Publisher Full Text\n\nSteltzlen C, Lazennec JY, Catonnéa Y, et al.: Unstable odontoid fracture: Surgical strategy. Orthop. Traumatol. Surg. Res. 2013 September; 99(5): 615–623. Publisher Full Text\n\nKorres DS, Boscainos P, Kouyialis M: Fracturas del axis. Rev. Ortop. Traumatol. 2005 Noviembre; 49(49): 463–473. Publisher Full Text\n\nMunakomi S, Tamrakar K, Chaudhary PK, et al.: Anterior single odontoid screw placement for type II odontoid fractures: our modified surgical technique and initial results in a cohort study of 15 patients. F1000Res. 2016 Jul 13; 5(1): 1681. PubMed Abstract \| Publisher Full Text\n\nBakhsh A, Alzahrani A, Aljuzair AH, et al.: Fractures of C2 (Axis) Vertebra: Clinical Presentation and Management. Int. J. Spine Surg. 2020 Dec; 14(6): 908–915. PubMed Abstract \| Publisher Full Text\n\nMixter SJ, Osgood RB: Traumatic lesions of the atlas and axis. Ann. Surg. 1910; 51(1): 193–207. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPryputniewicz DM, Hadley MN: Axis Fractures. Neurosurgery. 2010 March; 66(1): A68–A82. Publisher Full Text\n\nDorado E, Ruiz M, Magaña C, et al.: Fractura de la apófisis odontoide. BoletÍn Galego de Medicina Legal e Forense. 2019 Enero; (25): 79–83.\n\nRyken TC, Hadley MN, Aarabi B, et al.: Management of Isolated Fractures of the Axis. Neurosurgery. 2013; 72(1): 132–150. PubMed Abstract \| Publisher Full Text\n\nLarsen AG, Grannan BL, Koffie RM, et al.: Atlantoaxial Fusion Using C1 Sublaminar Cables and C2 Translaminar Screws. Oper. Neurosurg. (Hagerstown). 2018 Jun 1; 14(6): 647–653. PubMed Abstract \| Publisher Full Text\n\nKepler CK, Vaccaro AR, Flesichman AN, et al.: Treatment of Axis Body Fractures. A Systematic Review. J. Spinal Disord. Tech. 2015; 30: 442–456. PubMed Abstract \| Publisher Full Text\n\nMolinari JW, Molinari RW, Khera A, et al.: Functional outcomes, morbidity, mortality and fracture healing in 58 consecutive patients with geriatric odontoid fracture treated with cervical collar or posterior fusion. Global Spine J. 2013; 3(1): 21–31. PubMed Abstract \| Publisher Full Text\n\nYuan S, Wei B, Tian Y, et al.: The comparison of clinical outcome of fresh type II odontoid fracture treatment between anterior cannulated screws fixation and posterior instrumentation of C1-2 without fusion: a retrospective cohort study. J. Orthop. Surg. Res. 2018 Jan 8; 13(1): 3–10. PubMed Abstract \| Publisher Full Text" }	[ { "id": "281479", "date": "29 May 2024", "name": "Bartosz Godlewski", "expertise": [ "Reviewer Expertise spine surgery" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn the presented case, the patient required surgery using a posterior approach. The authors properly planned the surgical treatment. The presented fracture of the odontoid of C2 was not suitable for direct screw fixation from anterior approach. A slightly historical surgical technique was used, but with effective treatment results. Older applicable surgical techniques include a group of procedures done to produce fusion of the posterior arcs of C1 and C2 (by Galie, Brooks and Jenkins methods using wires or hooks of different types). Currently, C1-C2 stabilization using screws is more often performed, such as the popular Harms technique. This method allows for better stability and bone fusion. However, it is a technique that requires more surgical experience and is not performed by everyone, and knowledge of older techniques may still be helpful in everyday clinical practice.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-811
https://f1000research.com/articles/10-1312/v1	23 Dec 21	{ "type": "Research Article", "title": "Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada", "authors": [ "Eliseos J. Mucaki", "Ben C. Shirley", "Peter K. Rogan", "Eliseos J. Mucaki", "Ben C. Shirley" ], "abstract": "Introduction: This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. Methods: COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections. Daily cases were aggregated according to designated forward sortation area (FSA), and postal codes (PC) in municipal regions Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county. Hotspots were identified with area-to-area tests including Getis-Ord Gi, Global Moran’s I spatial autocorrelation, and Local Moran’s I asymmetric clustering and outlier analyses. Case counts were also interpolated across geographic regions by Empirical Bayesian Kriging, which localizes high concentrations of COVID-19 positive tests, independent of FSA or PC boundaries. The Geostatistical Disease Epidemiology Toolbox, which is freely-available software, automates the identification of these regions and produces digital maps for public health professionals to assist in pandemic management of contact tracing and distribution of other resources. Results: This study provided indicators in real-time of likely, community-level disease transmission through innovative geospatial analyses of COVID-19 incidence data. Municipal and provincial results were validated by comparisons with known outbreaks at long-term care and other high density residences and on farms. PC-level analyses revealed hotspots at higher geospatial resolution than public reports of FSAs, and often sooner. Results of different tests and kriging were compared to determine consistency among hotspot assignments. Concurrent or consecutive hotspots in close proximity suggested potential community transmission of COVID-19 from cluster and outlier analysis of neighboring PCs and by kriging. Results were also stratified by population based-categories (sex, age, and presence/absence of comorbidities). Conclusions: Earlier recognition of hotspots could reduce public health burdens of COVID-19 and expedite contact tracing.", "keywords": [ "COVID-19", "epidemiology", "geostatistics", "space-time analysis", "kriging", "infectious diseases" ], "content": "Introduction\n\nMany critical elements of disease epidemiology were unknown during the early stages of the COVID-19 pandemic. This included the case fatality rate, at what point during the natural history of the disease was it most transmissible (before, during or after the onset of symptoms), the frequencies of asymptomatic presentation of positive cases, and the duration of infectivity.1 Quarantining, social distancing, and isolation of infected populations were quickly recognized as effective public health measures. Without implementation of these measures in Ontario, COVID-19 patients presenting with severe disease would have exceeded available hospital capacity.2 Delayed testing and the sheer numbers of infected individuals often precluded comprehensive contact tracing.3 Indeed, COVID-19 testing was limited in many regions within Canada early in the pandemic, as was the availability of necessary resources (e.g., intensive care units, nursing and other clinical personnel, personal protective equipment).4,5 Limited resources must be adequately allocated to those locations where the rates of transmission of COVID-19 are high and where the highest numbers of infected individuals reside. This highlights the need for an effective, systematic way of tracking concentrations of this disease after community-level transmission. We address the persistence of geographic disease hotspots as a potential sentinel for efficient distribution of sparse resources.\n\nThe SARS-CoV-2 virus spreads by person-to-person contact, especially through respiration.6 Geographic epidemiology can be a key factor for the prevention of disease spread, as it can be used to monitor disease progression (or regression) and manage allocation of medical resources. Geostatistical methods have been utilized to map communicable diseases such as influenza-like diseases,7 dengue fever,8 cholera,9 legionellosis and shigellosis, among others.10 Various geostatistical analyses have been used in the surveillance of COVID-19 spread across the globe,11–17 often with the geo-spatial software, ArcGIS (ESRI).18 Other available tools for geostatistical epidemiology include SaTScanTM,19 GeoDa,20 and R statistical software environment,21 however these were not used in the present study because of their requirement to input disease background levels, which was not relevant for COVID-19. Available case data analyzed has been typically aggregated at the municipal11,16 or county level,13,14,22 however higher resolution spatial analyses has been limited as finer granularity for the distribution of COVID-19 cases has often been lacking.16,18 We performed geostatistical area-to-area analyses as well as interpolation of COVID-19 cases within six municipalities of the Canadian province of Ontario (Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto and Windsor/Essex region) distributed at the level of individual forward sortation areas (FSA) and postal codes (PCs). Area-to-area analyses were performed on COVID-19 case data at the provincial level by FSA, a geographical unit which can encompass hundreds of PCs. Each PC comprises an average of 19 households (Statistics Canada, 2006).\n\nThe success of short-term COVID-19 geostatistical studies at the county level early in the pandemic22 suggested that hotspots and localized concentrations of infected individuals could be delineated more precisely with epidemiological data collected with higher granularity. The present analysis evaluates the three major waves of COVID-19 infection to date in Ontario, allowing for the observation of trends and commonalities between waves. We utilized ArcGIS to carry out multiple area-to-area geostatistical tests, including Getis-Ord Gi hotspot analysis (Figure 1),23,24 Cluster and Outlier analysis (Figures 2A and 2B; Anselin Local Moran's I25), and Spatial Autocorrelation (Figures 2C and 2D; Global Moran’s I26). Hotspots were also inferred from spatially-interpolated counts by kriging and represented as topographic contour maps27,28 utilizing the ArcGIS geographic information system. Area-to-Area Gi* analysis finds regions with a high disease burden (i.e., model for community-driven spread), but does not inform how these cases are distributed throughout the region. PC-level point-to-point analyses (e.g., kriging) can be employed to provide context of how cases cluster and identify localized hotspots, where cases are concentrated in a single PC and independent of the disease burden of the FSA it is within (Figure 3). The Getis-Ord Gi* local statistic identifies regions with high disease burden with high, spatially clustered COVID-19 case counts (a local sum) relative to the rest of the province.23 Space-time Gi* analysis also uses this statistic to find hotspots that are both spatially and temporally clustered with other neighboring features (Figure 1D). Cluster and Outlier analysis identifies high-case regions that are geospatially clustered with other neighboring regions with a similar rate of cases (high-case clusters; Figure 2A), or those with neighboring regions with significantly lower COVID-19 case counts (high-case outliers; Figure 2B). The Global Moran’s I index determines if the distribution of cases is clustered, dispersed, or random within a region.26 The Moran’s I index is positive for spatially clustered cases between postal codes, which is compared to the expected value (i.e., if the spatial relationship was random) to compute a z-score and significance level. Kriging is a geostatistical interpolation method which predicts values over a non-sampled region by analyzing a subset of locations with known values.28 As a combination of geostatistical methods were applied to daily COVID-19 case data at the provincial [FSAs] and municipality [PCs] level for >450 days, efficient scripts were necessary to automate these analyses.\n\nCase counts aggregated at the centroids of FSAs or PCs over daily- or multi-day windows are compared to cases in neighboring FSAs or PCs and evaluated with geostatistical tests. These spatial relationships are defined by modeling spatial interactions between the FSA or PC being evaluated and the neighbors being tested. The panels describing these interactions indicate: (A) The fixed distance band weighs all neighbors within a specified distance equally, (B) The inverse distance band is based on distance decay where neighbors further from the target feature is weighted less relative to closer neighbors, (C) K-Nearest Neighbors constructs a spatial relationship which assesses a feature with a specified number of its most proximate neighbors based on centroid distances (here, N = 3), (D) Space-Time integration defines feature relationships in terms of both a space (fixed distance) and a time window. Features that are proximate to one another in space and time are analyzed together, as relationships are assessed relative to the location and time stamp of the target feature. Area-to-area geostatistical tests used include Gi* analysis, Cluster and Outlier analysis, and Spatial Autocorrelation.\n\nThe Global and Local Moran’s I statistics determine whether the numbers of cases in different PCs or FSAs in a region are distinct from one another or are related. Local Moran’s I (also known as Cluster and Outlier analysis) computes a Moran’s I value, or spatial autocorrelation, between counts within sets of FSAs or PCs. Global Moran’s I evaluates the overall case clustering in a region. Panels shown indicate these relationships in Leamington FSA N8H: A) A positive local Moran’s I index indicates that the regions neighboring N8H 3V5 has similar attributes (a high-case cluster; pink dot). B) A negative local Moran’s I index demonstrates that cases the region surrounding the target are dissimilar (a high-case outlier in N8H 3V8; red dot). C) The Global Moran’s I (Spatial Autocorrelation) index demonstrates whether cases are clustered, dispersed, or randomly distributed. In this example, cases were significantly clustered from Dec. 21 to 23, 2020 (p = 0.03; p-value signifies whether the null hypothesis [a random distribution] can be rejected). D) The case distribution was not significantly clustered on Dec. 2 to 4, 2020 (p = 0.7).\n\nKriging estimates case counts by interpolating unsampled regions between counts at known locations. Panels indicate: (A) Topographic contours were generated by Empirical Bayesian kriging (EBK) when analyzing PC-level case data in Windsor (Dec. 18 to 20, 2020) and interpolate different case levels within the region; (B) EBK uses empirical semivariograms which describe the correlations between the distance separating a pair of locations with COVID-19-positive individuals, ‘h’, and their corresponding semivariance ‘γ’. Larger values of γ indicate lower spatial autocorrelation between numbers of cases. A semivariogram model fits a curve through γ vs. distance that predicts γ at unsampled locations between known data points. The ‘Power’ semivariogram (B, top) is a parabolic mathematical model based on distance, while the Thin Plate Spline semivariogram (B, bottom) is a non-rigid model that passes exactly through bins of paired locations (grouped by distance and direction; blue crosses) while minimizing surface curvature. Red lines represent the median of the distribution of semivariogram models.\n\nThese geostatistical tools were used to identify and krige COVID-19 hotspots, clusters, and outliers within Ontario at a high level of granularity. With the results of these analyses, we can ask questions regarding the distribution of hotspots relative to others in both time and space. For example, this study evaluates significant levels of COVID-19 over a series of consecutive days which we term ‘streaks’. This allowed us to determine the true size and persistence of hotspots, compare and contrast geostatistical analyses of COVID-19 waves highlighting recurrent hotspots and clusters of PCs with high case counts. We also investigated the order in the progression of infection across a region in a statistically robust way. Empirical Bayesian Kriging (EBK) identified concentrations of COVID-19 that transcended the boundaries of FSAs and PCs. Ultimately, consistency between the results obtained by these different approaches reinforces the conclusions that might be drawn from them based on implementation as independent geostatistical tests.\n\n\nMethods\n\nCOVID-19 cases from March 26th, 2020 to June 25th, 2021 at the FSA (Ontario-wide) and PC-level (for 6 populated areas: Hamilton, Kitchener/Waterloo, London Ottawa, Toronto, and Windsor, including Essex county) were evaluated using ArcGIS Desktop 10.7 [ESRI] with the Geostatistical Analyst extension. Daily cases compiled by FSA were evaluated with Cluster and Outlier analysis, Gi* ‘hotspot’ analysis, and with space-time integrated Gi* analysis. Cluster and Outlier analysis computes a Local Moran’s I index score for each feature. A positive score indicates that a feature is clustered with other similar high-case count regions, while a negative index indicates that a feature is an outlier. The z-score and p-value indicates the statistical significance of the index value. A false discovery rate (FDR) correction was applied to this and Gi* analysis, which changes the threshold of significance of p-value ≤0.05 to a reduced value within the 95% confidence interval [C.I.], thereby accounting for multiple testing and spatial dependency. Z-scores are also determined in Gi* analysis, with higher positive scores indicating greater clustering of cases in a region. Space-time Gi* analysis was based on a single day interval but incorporated temporal trends based on the days preceding and subsequent to each date. We set a minimum threshold of 10 confirmed cases for an FSA to be considered significant by these three approaches, as this threshold was found to provide reliable and conservative detection of known hotspots using the Gi* test. Over two thirds of FSAs with ≥10 cases between March 1st and Sept. 24th, 2020 were found to be significant by Gi* [99% C.I.] using both a fixed and inverse distance metric (Extended data,29 Section 1 - Figure S1). Spatial relationships were evaluated to determine which distance metric best reflected the relationship between the test location and its surrounding FSAs by fixed distance (all FSAs within a given threshold distance [10km] are equally weighted with the test FSA), inverse distance (FSAs closer to the test FSA are weighted more highly), and by K Nearest Neighbors (KNN; comparing counts in the test FSA and its closest K neighbors).\n\nPC-level case data (binned over 3-day sliding windows) for each municipality were evaluated by Spatial Autocorrelation (Global Moran’s I), Cluster and Outlier analysis, and EBK. Spatial Autocorrelation used FDR correction to account for multiple testing; it was not applied for PC-level Cluster and Outlier analysis due a limitation of the method in high-case count regions where all locations were deemed non-significant. The KNN distance metric was used to define the spatial relationship between features (with K = 3) for all PCs, including those with zero cases. PCs with ≥6 cases were reported if deemed significant by Cluster and Outlier analysis. This is consistent with case minimums used in other COVID-19 geostatistical studies.13,14 Kriging generates a topographic contour map of the number of COVID-19 cases interpolated over the evaluated region, as indicated below.\n\nCOVID-19 testing data compiled by ICES contained metadata on tested individuals, such as gender, age, and relevant predicate health conditions. To identify geospatially significant cases in these groups, case data was stratified by gender (Male: 241,393; Female: 247,152; those without gender information were ignored), by age (≥65 years old: 63,746; <65 years: 424,854), and by presence or absence of at least one chronic health condition (187,242; includes chronic asthma, congestive heart failure, chronic obstructive pulmonary disease, dementia, hypertension and/or diabetes). 301,358 patients were without one of these conditions. Individuals with these conditions are grouped as an “at-risk population”, consistent with provincial terminology. These case subsets were then evaluated with Gi* (FSA-level), Spatial Autocorrelation, Cluster and Outlier analysis and kriging (PC-level).\n\nResults from PC-level Cluster and Outlier analysis were further analyzed with a program script to identify significantly, highly clustered PCs over consecutive periods (i.e., termed high-case cluster “streaks”; Local_Morans_Analysis.Recurrent_Clustered_PC_Identifier.pl; see Data Availability section30). We also identified which of these PC streaks occurred in close proximity (Local_Morans_Analysis.Clustered_Streak_Pairing_Program.pl) based on the neighbors of each postal code from PC centroid data (neighbors identified by Ontario_City_Closest_Postal_Code_Identification.pl; see FSA and PC boundary files subsection). Directional network graphs which visualize the interconnectivity of these paired high-case cluster streaks were created in MATLAB using built-in digraph and plot functions, where each edge (the connection between two PCs) represents a single pair of PCs with nearly concomitant or overlapping streaks.\n\nSoftware automation was required to computationally evaluate daily and windowed case data over 16 months at the geographic resolution of FSAs and PCs across multiple cities with different geostatistical tests. Using the ArcPy package (ESRI), which enables Python programs to access ArcGIS’s geoprocessing tools and extensions, program scripts were developed to perform geostatistical analyses across Ontario. These scripts set conditional variables which define the spatial relationship used (fixed, inverse or KNN), the threshold distance (or for KNN, the number of neighbors of the target feature), the distance method (how distances were calculated; set to ‘Euclidean’), row standardization (set to ‘none’), and whether FDR correction was used (applied to FSA-level Gi* and Cluster and Outlier analysis, and PC-level Spatial Autocorrelation analysis). ArcPy scripts read in case data (in tabular format), iterated sequentially through each date skipping those without positive cases, applied the associated geostatistical tool, and converted the output into text files. Tabular output was subsequently filtered by removing PCs without cases to avoid producing outputs of prohibitive size.\n\nAdditional ArcPy scripts imported and visualized the results from Gi, kriging and Cluster and Outlier analysis onto maps displayed in the ArcGIS system. These scripts label regions above the prerequisite case minimums to identify the location (FSA or PC) and case count, symbolize the results, i.e., to assign a colour to a location which represents its significance based on the analysis performed, and convert the map to a PNG formatted image. To image results of kriging analyses, program scripts simultaneously visualized the locations of COVID-19 cases and the kriging layer by setting transparency to 30%. The extent of the region visualized was defined manually in ArcGIS prior to generation of map images.\n\nThese processes were then integrated and streamlined in a software package named the Geostatistical Epidemiology Toolbox (see Data Availability section30), which is accessed through the ArcMap graphical user interface. This resource provides the same geostatistical operations and map imaging developed for this project in a simplified, user-friendly environment. This toolbox bundles manual pre-processing, analysis, and post-analytical steps into a set of linked, uninterrupted workflows. For example, tabular case data is converted into shapefiles and, optionally, the ArcGIS window is aligned to the city of interest when performing map imaging. The user-defined parameters for these operations are set through an interface entirely within ArcMap, which then allows a series of tasks to be carried out automatically. No prior Python programming knowledge is required. While the toolbox was designed to evaluate COVID-19 case data in Ontario, the software can be easily modified to accommodate other Canadian provinces and, with additional effort, other countries. To enable kriging functionality within the toolbox, the Advanced Geostatistical Analyst module is required to be installed in ArcMap as well as access to PC and FSA boundary shapefiles. These shapefiles are also required for PC-level Local Moran’s I and Global Moran’s I analyses. This package is not bundled with any of the program scripts developed to evaluate geostatistical output (beyond data imaging), however these are provided in the accompanying Zenodo archive.30 The toolbox is distributed under the GNU General Public License v3.0.\n\nAccess to anonymized Ontario COVID-19 test results through the ICES Research and Analytic Environment (RAE) was obtained through Applied Health Research Questions (AHRQ) project #P0950.096 approved by the Ontario Ministry of Health and Long-Term Care (MOHLTC). ICES collects health care data for analysis and evaluation of the health system. Ontario-wide COVID-19 data tables maintained in ICES were pre-processed to ensure that only the chronologically first laboratory-confirmed viral RNA polymerase chain reaction (PCR) SARS-CoV-2 test of a specific individual was counted (while repeat infections occur, these are assumed to be significantly less frequent). PCs associated with each positive case were cross-referenced to their respective FSA (derived from the 2016 Canadian Census boundary file from Statistics Canada) to identify and filter out invalid entries. The PCs provided were sourced from the OLIS (Ontario Laboratories Information System) and the RPDB (Registered Persons) databases. The OLIS postal code was more likely to relate to a current address and was therefore prioritized. However, it is also the most error prone. Reasons for rejection include blank entries, invalid FSAs (e.g., out of province FSA), or intentional masking. The RPDB PC was used if the OLIS PC was rejected. Entries where both PCs were invalid were rare (<0.1% of all unique positive cases). Non-residents or those ineligible for the Ontario Health Insurance Plan (OHIP) are also not included. Cases were separately aggregated by FSAs and PCs, then converted into tables structured as rows (FSA or PC count) by columns (date) as input to ArcGIS Desktop. Cases were based on the date of sampling, rather than when test results were reported, to more accurately reflect the inception of infections.\n\nAs of June 2021, three separate and distinct waves of COVID-19 cases have been recognized in Ontario (and elsewhere). We delineated the inception and termination dates of each wave from the rates of change in infection rates (cases/day2) using the second derivative of daily case counts. Stochasticity in day-to-day variation due to testing and case reporting caused fluctuations in changes of daily counts, even when averaging cases over multiple consecutive days. Consecutive dates without fluctuations in counts (between -10 and +10 cases/day2) were rare. Therefore, dates were selected where the second derivative remained between -10 and +10 cases/day2 immediately preceding rapid increases in cases that defined inception of a wave, or after infections ceased decreasing in counts, defining termination of a wave. The first wave (1) was found to span from March 26th to June 16th, 2020, second wave (2) began on September 25th, 2020 and continued until February 14th, 2021, and the third wave (3) covered March 17th to June 23rd, 2021.\n\nOf the geostatistical methods tested, PC-level counts of infected individuals were the most geospatially resolved granular COVID-19 case data. Many PCs comprise of small geographic areas with low population densities. This made them more prone to the effects of day-to-day stochasticity in patient ascertainment and laboratory reporting, especially when case counts were low. To address this, PC-level case data was also aggregated over multi-day sliding windows, effectively smoothing out this source of variation. Although 3 and 7-day windows were initially analyzed, longer windows were not as useful for determining the inception of hotspots, a goal of this analysis, and were eventually discounted. 3-day windows have been used in other geostatistical studies of COVID-19.13,14\n\nAccess to, pre-processing and geostatistical analysis of COVID-19 daily cases and associated metadata required the RAE computer system at ICES. To ensure patient privacy, ICES stipulated that the counts in all FSAs and/or PCs exhibiting between 1 and 5 daily COVID-19 cases be masked. We modified counts of FSAs meeting these criteria and assessed their impact on the geostatistical analysis. Gi analysis of ground truth case data was compared with the analysis of two modified FSA-level case datasets (where all instances of between 1 and 5 case counts were either converted to a single count or randomized between 1 and 5). More than one third of the locations that were deemed significant hotspots by Gi* from actual case counts (from March 1st to September 24th, 2020) were not flagged when locations were masked and assigned a count of 1; greater than one half were missed when case counts were randomized (Extended data,29 Section 1 - Table S1). Discordant hotspots identified from actual vs. masked case counts were reduced in FSAs with high-case counts (≥10) but were nevertheless unacceptably frequent (14% or 28% discordant, respectively, by masking low case counts as 1 or by randomization). We concluded that errors introduced by masking count values precluded analysis of masked data and required all work to be carried out within the RAE computing environment.\n\nShapefiles which store geospatial data [points, lines or polygons] with related attribute information and depict the 2016 census geographic boundaries of FSAs across Canada were obtained from Statistics Canada. PC boundary shapefiles created by DMTI (“DMTI_2019_CMPCS_LocalDeliveryUnitsRegion.shp”) were accessed through the Scholar's Geoportal at the University of Western Ontario. These files were used to compute latitude/longitude coordinates of the centroid for each FSA and PC (with the ArcGIS “Calculate Geometry” function), to validate PCs provided for each individual in the COVID-19 test dataset, and to convert spatial interpolation maps (such as those generated by kriging) into machine-readable text files (using ArcGIS “Intersection” function between the spatial map and with each boundary file). The ArcGIS “Split by Attribute” function was used to limit PC boundary files to the province of Ontario. This was necessary, both because data from other provinces were not available, and because of system limitations affecting processing and memory requirements for large geographic regions.\n\nMinor discrepancies between the FSA and PC boundary files were identified which had little or no impact on our geostatistical analysis. Nearly 9% of all PCs in Ontario overlapped multiple FSAs. Most of these PCs were present in multiple locations and occurred in rural areas. Approximately 2.7% of PCs intersected with an incorrect FSA, which was likely the result of asynchronous creation of the corresponding shapefiles. These locations rarely contained many COVID-19 cases as only 11 PCs had >5 cases over any 3-day span in 2020, including: N9H 0E3 (Windsor, ON) which overlaps with the FSA N9G; N8N 0B3 (Tecumseh, ON) which overlaps the bordering FSA N8R, and M3H 5V9 (Toronto, ON) which intersected with neighboring FSA M3J. These discrepancies might impact the interpolation of cases in FSAs based on kriging analysis. Since the discrepant PCs were typically found on the border of FSAs, these conflicts had minimal effect on kriging accuracy.\n\nKriging estimates case counts in unsampled regions by interpolation between counts at known locations. These values are spatially correlated with degree of separation from centroids of PCs or FSA with known cases. A topographic contour map is generated which illustrates the interpolated case levels within the analyzed region. The spatial distribution of the disease outbreak was determined for Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county by kriging analysis of PC-level COVID-19 case data over consecutive, overlapping 3-day windows. Kriging was also performed for other municipalities bordering Toronto (Ajax, Brampton, Markham, Mississauga, Pickering, Richmond Hill and Vaughan; see results in Extended data,29 Section 3). Only PCs with ≥1 case were included in this analysis, as locations without confirmed cases were found to severely depress kriging signals. Several types of kriging (Ordinary, Universal, Simple and EBK) were evaluated for accurate detection of high case clusters in municipalities with high and moderate population densities (Toronto and London, respectively). Contour maps generated by EBK best matched regions of known cases used for analysis. Ordinary and Universal kriging yielded similar results for locations with high case counts (≥50) but lacked the sensitivity of EBK in regions with moderate cases. Simple kriging failed to define most contours correctly, regardless of case count. Therefore, EBK was chosen for all kriging analyses presented in this study.\n\nSemivariograms describe how the distances separating COVID-19 positive individuals and the semivariance of counts at these locations are correlated. The best model that fits this relationship using empirically defined distance data was used to predict COVID-19 count levels at unsampled locations between the centroids of FSAs or PCs. Semivariogram models assessed included Power, Linear, Thin Plate Spline (TPS), Whittle, Exponential, K-Bessel. Kriging parameters for these models were considered, such as sector type, search radius, neighborhood type and the number of neighbors considered for each location. Through empirical testing, the ‘Power’ semivariogram model (based on a parabolic relationship to distance between locations) was chosen based on interpolated values that best represented actual case counts in low/moderately dense populations (Extended data,29 Section 1 - Figure S2A). Accuracy was maximized when interpolated values were based on three neighboring locations with known counts. However, the performance of the ‘Power’ semivariogram to interpolate high-case regions in Toronto, which exhibited the highest case counts of any municipality, failed to model some localized hotspots. The TPS semivariogram model, a non-rigid representation that passes exactly through points while minimizing surface curvature, performed best in this densely populated region (Extended data,29 Section 1 - Figure S2B). Power-based kriging contours were generally larger, while TPS-based kriging contours were smaller, bifurcated and more frequent. TPS, in some instances, generated kriging artifacts that did not correlate with known hotspots. Increasing the numbers of neighbors to 5 reduced the occurrence of these artifacts without negatively impacting the accuracy of the contour map. Consequently, we chose to evaluate cities with low-to-moderate population densities (Hamilton, Kitchener/Waterloo, London, Ottawa and Windsor/Essex) with the ‘Power’ semivariogram model (3 neighbors), whereas the Toronto metropolitan area was evaluated with the TPS semivariogram model (5 neighbors). All other EBK parameters were defaulted to those provided by the ArcGIS Advanced Geostatistics toolbox.\n\nWe have previously demonstrated that circumscribing the boundaries of analyzed regions by specifying these locations with zero counts improves kriging accuracy, especially at locations proximate to boundaries.31 This approach was used in the present study of interpolated COVID-19 cases for each municipality in Ontario. Municipal borders were derived by combining all PCs associated with the region of interest. The optimal densities and distances of the zero-count buffer circumscribing municipalities by programmatically generating boundaries. Distances between the boundary to the city border were varied from 0.1, 0.5, 2, and 5km, and densities between locations of 0.05, 0.25, 0.5 and 1km. Kriging analysis was iterated for each of these defined zero-count borders, and the kriging layers generated were compared to the original kriging results. The location of each kriging contour properly coincided with regions of high case counts, regardless of the shape and density of the zero-count boundary locations. Raising the boundary density consistently increased the COVID-19 case value interpolated of a high-case region while simultaneously reducing the total area of the kriging contours around the region, regardless of semivariogram model used. This effect was less prominent in regions with higher density of cases (i.e., Toronto), and in regions further from the city boundaries (as the kriging contours exhibited consistent shape and magnitude >6km away from the city boundary). Considering these observations, we chose to use a moderate value for each parameter (0.5km density and 1km distance from the city boundary). The kriging tool in the Geostatistical Epidemiology Toolbox, however, automatically generates these boundaries 1km from the selected border with 250m of distance between each location.\n\nKriging analysis generates a series of shapefiles containing contour maps that define the interpolated level of COVID-19 cases of a region. An ArcPy script intersected map contours derived from kriging and either FSA or PC boundary files, which associated each kriging-derived case count with these locations. The results of these intersections were displayed as distinct contour distributions (or kriging ‘symbologies’): one for instances with a wider range of inferred case count levels (0-1, 1-5, 5-10, 10-15 … 35-40, 40-50, >50 cases), and another for low densities of inferred cases, which was discriminated by single counts (0-1, 1-2 … 9-10, >10 cases). In compliance with ICES’s reporting criteria, we defined any interpolated value >5 cases (either ≥5-6 or ≥5-10 contour, depending on the symbology type used) as significant, and display PC or FSA designations for only these locations. The intersected area (m2) between contours and the corresponding FSA or PC was determined to compute the size of localized hotspots (e.g., the total area of the FSA or PC considered significant by kriging).\n\n\nResults\n\nChanges in the distribution of COVID-19 infections over time were evaluated through geostatistical analysis within both FSAs and PCs. PC-level analysis can map COVID-19 spread at a finer resolution, which more precisely identifies hotspots concentrated within individual postal codes (e.g., a localized hotspot). Area-to-area geostatistical analysis of cases in FSAs is better suited when COVID-19 cases are distributed across the entire FSA (e.g., an area with high disease burden by community-driven spread; Figure 4), rather than when cases are concentrated in a single location. This method does not, however, provide any information regarding the overall distribution of cases within the FSA. Spatial Autocorrelation analysis (Global Moran’s I) was therefore performed to identify FSAs where COVID-19 cases are clustered at the PC-level (potential evidence of disease transmission). These geostatistical methods combine analyses of COVID-19 cases at multiple levels of resolution, facilitating interpretation of the case distribution throughout the province.\n\nThe FSA M5V in the entertainment district of Toronto was identified as a hotspot relative to the rest of Ontario by the Gi* test over 14 days in September 2020 (case counts ≥6, with five days exhibiting at least 10 cases [Sept. 10th, 13th, 20th, 22nd, 23rd]). These cases were distributed across 71 separate PCs in M5V. A heat map generated with the Kernel Density function within the Spatial Analyst Toolbox of ArcGIS shows the relative density of postal codes with cases (blue dots), weighted by the number of days in which each individual postal code had ≥1 case (N = 118 cases total). Kriging analysis did not identify localized hotspots during this period, as none of the PCs exceeded 3 cases.\n\nSignificant FSA hotspots were assessed by Gi* through comparison of cases within KNNs, a fixed distance, or by weighted inverse distance. During the first wave of COVID-19, when testing was not fully established across the province, FSAs with the minimum number of cases considered significant hotspots (≥10) were less common, and fewer FSAs met these criteria (78 to 94%; Extended data,29 Section 1 - Table S2). Later, fixed distance comparisons identified more FSAs with significantly higher disease burden than other metrics (53% of all FSAs in wave 3 versus 24% for KNN3 and versus 13% with inversely weighted FSAs; Extended data,29 Section 1 - Table S2). We prioritized the standard Gi* analysis which utilized KNN (where K = 3) in this study, as it is moderately stringent (compared to results using the fixed and inverse distance metrics) and is unaffected by the shape of FSAs (which can be quite variable when comparing rural and urban areas).\n\nSpace-time Gi* analysis consistently called FSAs with ≥10 cases as significant in waves 2 and 3 (>91% and 95%, respectively; Extended data,29 Section 1 - Table S2). This approach identified nearly twice as many FSAs as significant versus to standard Gi* comparing neighbors up to the same fixed distance (Extended data,29 Section 1 - Table S2). FSAs deemed significant hotspots by space-time Gi* were tested against many more neighbors (<10km) relative to FSAs that were not hotspots (averaging 59 and 17 neighbors, respectively). This revealed a bias in significant FSA hotspots towards smaller, densely organized FSAs (which were typically urban), while those that did not achieve significance were often rural, covering larger areas and exhibiting lower COVID-19 counts. Additionally, 98% of the FSAs flagged were also significant hotspots on the days prior and subsequent to the central date in each window. This was uncommon in FSAs that were not determined to be significant hotspots (6%). Temporal trends in the distribution of COVID-19 cases and potential transmission were also identified by Cluster and Outlier analysis of PCs that persisted across a consecutive series of dates (referred to as high-case cluster ‘streaks’; described later in the Results section).\n\nComparison of kriging and Cluster and Outlier analysis of PC-level case data revealed that the same statistically significant PCs were often identified by both approaches on the same dates (March 26th to December 28th, 2020; ≥6 cases). A PC was considered significant by Cluster and Outlier analysis if the location was deemed a high-case cluster or outlier with an FDR-correction with 95% confidence, or if ≥5 cases were interpolated within it by kriging. This comparison finds that both approaches are consistent in municipalities with lower overall case counts such as Hamilton (65.2% concordance; N = 66 PCs found significant by cluster/outlier analysis), Kitchener/Waterloo (85.1% concordance; N=47), London (69.0% concordance; N = 29), and Windsor/Essex (85.0% concordance; N = 160) (Extended data,29 Section 1 - Table S3). The two methods showed <50% correlation to each other when evaluating cases in Ottawa (45.0% concordance; N = 211) and Toronto (49.7% concordance; N = 529). Nearly all discordant PCs were interpolated to have between 1-5 cases (i.e., marginally discordant). Kriging analysis commonly identified high-case outliers more often than high-case clusters. In Hamilton, 70% of high-case outliers but only 29% of high-case clusters were also found significant by kriging (N = 59 and 7, respectively). Similar patterns were observed for all regions evaluated except Windsor/Essex, where overlap between kriging and high-case clusters and outliers were comparable (83% and 96% [N = 138 and 22], respectively; Extended data,29 Section 1 - Table S3).\n\nAs incidence rates of COVID-19 have fluctuated since its initial appearance in Canada, the following geostatistical analyses have been stratified by periods with significant infectious burden, which provides a common frame of reference. We organize the analyses according to the three periods (or waves) with maximal occurrence of COVID-19 infections, where wave 1 extended from March 26th to June 16th, 2020, wave 2 from September 25th, 2020 to February 14th, 2021, and wave 3 from March 17th to June 23rd, 2021. The intervening periods between waves 1 and 2 and waves 2 and 3 are designated as inter-waves 1-2 and 2-3, respectively.\n\nKriging analysis of COVID-19 cases in this wave identified significant localized hotspots in Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex (all localized hotspots are identified in Extended data,29 Section 2). High disease burden FSAs (those flagged by Gi* analysis) were often found to include localized hotspots (>50% of flagged FSAs in cities evaluated; Extended data,29 Section 1 - Table S4). Localized hotspots (regions within contours exceeding significant interpolated count levels) were most frequently identified within high disease burden FSAs in Ottawa during the first COVID-19 wave (84%; Extended data,29 Section 1 - Table S4). However, kriging also identified 34 additional localized hotspots within FSAs on dates within this period, suggesting that significant COVID-19 events occur that are missed by Gi* analysis. Due to its high density, kriging analysis of cases in Toronto using the Power semivariogram (used in analysis of all other cities) was found to have poor overlap with Gi* analysis (only 31.6% of significant FSAs contained a localized hotspot). The overlap between kriging and Gi* test results was significantly improved using the TPS semivariogram (increased to 60.9%), and this was therefore used for all subsequent kriging analyses of Toronto. PC clustering was uncommon during this wave (<15% of FSAs flagged by Gi* and/or kriging were clustered). The exception was London where 27% of localized hotspots occurred in clustered FSAs [N = 11], and the majority of cases were often localized to a single PC in other cities that were analyzed (Extended data,29 Section 1 - Table S4).\n\nCOVID-19 outbreaks frequently affected residents of long-term care residences during this wave. Geostatistical analyses confirmed the ability to identify these outbreaks. For example, an outbreak in a nursing home in Toronto in early April 2020 (M8V; Lakeshore Lodge) was identified by kriging, while the FSA in which it occurred was also significant by Gi* analysis (Figure 5A). A different outbreak in Toronto in April 2020 (M2K; Extendicare Bayview nursing home) was also detected by kriging analysis, but the FSA in which it was found was not a significant hotspot by Gi* (Figure 5B; it was significant only using a fixed distance metric of ≥20km). Similarly, the FSA K1J (Ottawa, ON) was only significant by Gi* using an inverse distance weighted test, despite a mid-April 2020 outbreak in the Rothwell Heights assisted living community which was identified by kriging (Figure 5C). In each of these instances, the interpolation of cases by kriging were similar to actual case counts in these FSAs. This was consistent with the concentration of cases within a single PC (a frequent occurrence in the first COVID-19 wave; Extended data,29 Section 1 - Table S4).\n\nFSAs exhibiting high-disease burden by Gi* analysis were identified with localized hotspots by kriging or as having significant case clusters by Spatial Autocorrelation. Panels indicate cases in all PCs within FSAs (A) M8V (B) M2K, and (C) K1J, which were amalgamated over 3-day sliding windows and masked (red line indicates actual case counts; privacy consideration require dates with fewer than 5 cases to be masked as zero). Kriging interpolated the number of cases over these FSAs (blue line), which closely approximates true case counts when counts are high. Green asterisks indicate dates where at least one day within a 3-day window was significant by Gi; purple crosses indicate significantly clustered cases within PCs.\n\nLocalized hotspots identified by kriging comprise a narrow range of PCs in each FSA. The area of interpolated contours that overlapped FSAs with significant disease burdens (by Gi analysis) was compared to the total area of all corresponding FSAs. COVID-19 cases were highly localized, as the highest value contour (where kriging interpolates the greatest number of cases) constituted only a small portion of the total FSA area (Extended data,29 Section 1 - Figure S3). While hotspots found by kriging often coincide temporally with Gi* results (Extended data,29 Section 1 - Table S4), the interpolated hotspots contain fewer cases relative to the entire FSA, since the maxima of kriging contours cover only a portion of the overlapping FSA. The overall area indicated as significant by kriging overlaps a greater fraction of the FSA area, but still covers a fraction of its area (<10% in the majority of cases). Compared to the other COVID-19 waves, however, kriging analysis of cases during this wave tended to span a larger area of each FSA (Extended data,29 Section 1 - Figure S3A). This appears to be consistent with higher transmissibility (which, we speculate, may be related to lower levels of immunity during this period).\n\nCOVID-19 case counts were stratified into three categories: biological sex (males vs. females), age (exceeding vs. below 65 years old), and overall health (presence or absence of at-risk, pre-existing comorbidities). Stratified PC-level case counts were evaluated by Cluster and Outlier analysis across all waves (Table 1). In the first wave, the frequency of high-case outliers (a high-case PC with few cases amongst its immediate neighbors) is biased towards older, at-risk populations (Table 1A). Across all municipalities, PCs were flagged nearly 5-fold more often in the older population (305 and 62 PCs were identified as a high-case outlier on different dates in this wave, respectively). A similar pattern was observed in at-risk vs healthy populations (321 and 31 high-case outlier PCs, respectively), which is not surprising due to the significant overlap between the elevated age and groups with at-risk comorbid diagnoses. High-case clusters were identified less often, but also showed this pattern, which is likely related to the high frequency of outbreaks in long-term care homes during this period (Table 1B). Windsor/Essex was an exception to this trend, since the frequencies of PCs designated as high-case outliers were comparable among both age and comorbidity groups (20 vs 17 for older vs younger populations, 19 and 17 for at-risk vs. healthy populations; Table 1A). The frequency of high-case clusters/outliers identified by sex-stratification varied by the region analyzed (e.g., more high-case outliers were identified in the female population in Toronto, in contrast within the male population in Windsor/Essex).\n\n1 Interwaves 1-2 and 2-3 are displayed as ‘1-2’ and ‘2-3’, respectively.\n\n2 PCs identified as a high-case outlier on a particular 3-day interval with ≥6 cases when analyzing stratified case data.\n\nFor each subheading, the number of PCs with stratification bias, if any, are indicated.\n\n1 Interwaves 1-2 and 2-3 are displayed as ‘1-2’ and ‘2-3’, respectively.\n\n2 PCs identified as a high-case cluster on a particular 3-day interval with ≥6 cases when analyzing stratified case data.\n\nFor each subheading, the number of PCs with stratification bias, if any, are indicated.\n\nThe first COVID-19 wave ended approximately two months after the imposition of public health prohibitions on mobility, limits on assembly, and social distancing (i.e., a lockdown) in Ontario. June 16th, 2020 defined the start of interwave 1-2, a period of much lower COVID-19 incidence than the preceding 2 ½ months. Fewer FSAs exhibited high disease burden by Gi* analysis (39.7% of those called in wave 1, despite the duration of interwave 1-2 being longer; Extended data,29 Section 1 - Table S2). Despite the overall decrease in cases province-wide, the frequency of FSAs in the Windsor/Essex region that were designated hotspots by both Gi* and kriging analysis increased relative to the preceding wave (Extended data,29 Section 1 - Table S4). This was due to multiple outbreaks in the Essex County FSAs in Leamington [N8H] and Kingsville [N9Y] (Extended data,29 Section 1 - Figure S4). These outbreaks were publicly documented in guest farm workers, which is reflected by the Cluster and Outlier analysis of stratified case data (a strong bias of high-case clusters and outliers in healthy males <65 years in Windsor/Essex; Extended data,29 Section 1 - Table S4). These same locations were correlated with interpolated kriging contour maxima and often consisted of isolated single PCs (Table 1). However, there were instances where the interpolated count values exceeded the actual case count (i.e., N8H, June 22-26th, 2020; Extended data,29 Section 1 - Figure S4B) due to concurrent high case counts from neighboring FSAs (i.e., N0P 2J0; Extended data,29 Section 1 - Figure S4C) bleeding into these contours from a single PC.\n\nFSAs with high disease burden were more frequent within the second wave (Extended data,29 Section 1 - Table S2). Even when accounting for its longer duration, there was a >10-fold increase in FSAs with high disease burden based on the Gi* test. The distribution of cases was more widespread across each FSA, as COVID-19 testing became more reliable and pervasive. Localized hotspots were detected less frequently within FSAs with high disease burden, i.e., significant FSAs by Gi* analysis overlapped less often with significant kriging contours in all municipalities except Windsor/Essex (Extended data,29 Section 1 - Table S4). Additionally, interpolated case counts by kriging tended to be less than actual FSA case counts, due to dispersion of cases across more PCs. Most municipalities contained more FSAs with localized hotspots that were not significant by Gi* analysis. Increased case counts across the province during this wave increased the significance threshold for Gi* analysis. This decreased the likelihood that FSAs in municipalities with moderate population densities were designated significant hotspots. For example, FSAs within Kitchener/Waterloo and London were not significant COVID-19 hotspots during wave 2 (Extended data,29 Section 1 - Table S4). Hotspots in these regions were coincident with maximum contour levels interpolated by kriging. PCs had a greater proportion of high-case clusters and/or outliers in younger and healthy populations, in contrast with wave 1 (Table 1). The reduction of COVID-19 outbreaks (i.e., hotspots) in long-term care homes during this period was supported by reduced statistical significance of counts at these locations relative to increased background case counts across the province.\n\nLocalized hotspots detected in PCs by kriging were more frequent in Hamilton, London, Ottawa, Toronto and Windsor/Essex during this wave than in the preceding one (Extended data,29 Section 1 - Table S4). For example, an interpolated hotspot in the N5Y FSA (London) with significant cases over consecutive 3-day intervals (December 19-21 and December 20-22, 2020; Figure 6) represents a ‘streak’, since kriging analysis interpolated cases over this FSA throughout the previous week (however, it was below the kriging threshold for significance). This hotspot encompasses a 2 building apartment complex that was publicized on December 29 by the local health authorities as a COVID-19 hotspot, two weeks after it was first detected by kriging.32 While the interpolated case count is lower than the total count in this FSA on this date (N=33, other cases are present at other locations), this hotspot encompasses only 4% of the FSA by area. Other localized hotspots during this wave are depicted (e.g. in Leamington ON; Extended data,29 Section 1 - Figure S5) and catalogued in Extended data,29 Section 2.\n\n(A) Geostatistical analysis of the FSA N5Y (London, ON) identifies a significant localized hotspot from Dec. 19th to the 22nd. Although significant, estimates from kriging were lower than actual case counts. (B) The kriging contour of a localized hotspot (yellow) interpolated with ≥5 cases encompasses 4% of the FSA area. Dots indicate PCs at least 1 case, however only those with ≥6 cases are labelled (with PC identifier/case count).\n\nSignificant clustering of cases in PCs in close proximity based on Spatial Autocorrelation analysis may be distinct from other tests that identify localized hotspots. Spatially clustered localized COVID-19 hotspots may not be confined within the same region of an FSA. For example, FSA M1P (Toronto) from Nov. 1-3 to Nov. 3-5, 2020 exhibited significant case clustering based on Gi* analysis. However, a localized hotspot identified within this FSA during this time did not overlap this cluster (Extended data,29 Section 1 - Figure S6A). A neighboring FSA M1C showed significant spatially correlated cases within the same timeframe (Nov. 6-8, 2020), however localized hotspots were not detected in this FSA (Extended data,29 Section 1 - Figure S6B). No PC within this FSA had ≥6 cases during this period. This illustrates how combining Spatial Autocorrelation, Gi* and kriging analyses can improve the interpretation of asymmetric COVID-19 case distributions.\n\nThe interval between the end of wave 2 and inception of wave 3 was short (~31 days), however by comparison with interwave 1-2, the case counts were considerably higher (averaging 1134 and 154 per day, respectively). Thus, a far greater number of high disease burden FSAs were identified during this period (1.9 and 4.7-fold more often compared to wave 1 and interwave 1-2, respectively; Extended data,29 Section 1 - Table S2). However, most of these occurred in Toronto and Windsor/Essex regions only (Extended data,29 Section 1 - Table S4).\n\nThe frequencies of high disease burden FSAs in waves 2 and 3 were comparable upon adjusting for duration of each wave (Extended data,29 Section 1 - Table S2). The regions detected by geostatistical analyses were different. High disease burden FSAs implicated in Hamilton and Kitchener/Waterloo by Gi* analysis were significantly more frequent compared to the preceding wave, while FSAs within Toronto were less often significant (Extended data,29 Section 1 - Table S4). By contrast, localized hotspots within FSAs were generally less frequent than in wave 2, most notably in the Windsor/Essex region which contained 389 localized hotspots in wave 2, but 80 in wave 3 (Extended data,29 Section 1 - Table S4).\n\nHigh-case clusters and outliers were seldomly identified in older (≥65) populations in wave 3 and interwave 2-3 (Table 1). Similarly, there is a considerable decrease in the number of case clusters/outliers in at-risk populations relative to previous waves. For example, analysis of at-risk populations in Windsor/Essex identified 116 PCs as a high case outlier on a particular date during wave 2, but only 2 in wave 3 (Table 1A). These observations may be related to effectiveness of vaccination, based on the initial prioritization of older and at-risk cohorts for immunization.\n\nCOVID-19 distributions were evaluated by Cluster and Outlier analysis to identify neighboring PCs with high concentrations of cases. PCs deemed part of a high-case cluster that were clustered over contiguous date ranges were then identified. These PCs were recognized as clustered over the duration of a time “streak”, which by definition, allows for a single day in which the PC was either not clustered or did not meet the minimum case count threshold of ≥6 cases within the 3-day sliding window. PCs that were part of a high-case cluster, but did not meet the case threshold, were not reported. This analysis identified 20 unique PCs with one or more high-case cluster streaks in Hamilton, 5 in Kitchener/Waterloo, 10 in London, 24 in Ottawa, 216 in Toronto, and 19 in Windsor/Essex (Extended data,29 Section 1 - Table S5). Streaks were uncommon in Kitchener/Waterloo and London, as PCs in these cities rarely fulfilled the minimum case threshold. Most streaks were shorter than 4 sliding window periods, indicating that the most frequent streaks were brief due the large number of single day discontinuities from case reporting patterns and ascertainment bias. For these reasons, ≤3-day bins were not considered evidence of a streak. However, 37 streaks longer than 3 days were interpreted to indicate persistent infections at the same locations. Streaks with more than 3 consecutive high-case clusters were uncommon in wave 1, with M6M 2J5 (West Park Long Term Care Center) as the only example of a streak exceeding 3 days. The lack of other locations with persistent infections may be related to inconsistent case reporting which was hampered by limited testing during this period.4,33\n\nWe sought evidence of COVID-19 transmission by identifying pairs of PCs with high case counts that were adjacent to one another by both distance and time. In Figure 7A, we analyzed PCs and their 10 closest neighbors, where streaks were either concurrent, consecutive, or separated by short gaps within the same wave. Concurrent streaks of neighboring PC pairs spanned at least 3 and as many as 29 days in Hamilton, Ottawa, Toronto, and Windsor/Essex (Table 2). There were a greater number of discontinuous streaks across all municipalities, with gaps separating streaks in neighboring PCs varied from short to long intervals (Extended data,29 Section 1 - Table S6). During the second wave, many pairs of PCs were comprised of neighboring apartment buildings, for example, within Toronto FSA M4H. Other long concurrent paired streaks (exceeding 1 week in duration) occurred in Toronto PCs M1R 1S9 and M1R 1T1, M1L 1K9 and M1L 1L1 (both PC pairs in North York, Toronto), and L0R 1C0 with its neighbors in Hamilton (Table 2). Pairs of concurrent streaks in close proximity did not occur during wave 1, since streaks were uncommon during this time. However, many neighboring PCs were both found to be clustered both spatially and temporally during interwave 1-2 and waves 2 and 3 (Extended data,29 Section 1 - Table S6). While not concurrent, neighboring PC pairs in rural Essex county were clustered within 10 days of one another during interwave 1-2 (N0P 2L0, N0P 2P0 and N0R 1B0). This is confirmed by publicly reported outbreaks in agriculture facilities of this region during this time. During wave 2, 56 unique pairs of streaks were identified in neighboring PCs in Toronto (18 clustered concurrently, another 14 within a week of one other), 4 pairs in Hamilton (2 concurrent), 1 in London (concurrent), 4 in Ottawa (1 concurrent) and 14 in Windsor/Essex (10 concurrent; all involve PCs in Essex county). There were fewer incidences of streaks during the third wave, which may be related to the effectiveness of vaccination efforts which limit transmission (Figure 7B). During wave 3, we identified an additional 30 pairs of PCs with streaks in Toronto (7 are clustered concurrently, and an additional 4 pairs are offset by 1 week), and 6 in Hamilton (3 concurrent, and another pair offset by 2 days). Interestingly, 9 of the same PC pairs in Toronto clustered during the third wave were also flagged during the second wave, which could be an indication of an undetected reservoir of COVID-19 that persisted in this population during interwave 2-3. These pairs of PCs occurred in the Toronto neighbourhoods of East York (M4H 1J4 and M4H 1J5), Scarborough (M1H 2Y7 and M1H 2E9), North York (M1R 1T1 and M1R 1S9; M6M 5B3 and M6M 5B7), and Etobicoke (M9C 1G7 and M9C 1G6; M9V 3S6 and M9V 4A4; M9V 3S6 and M9V 4M1; M9V 4A4 and M9V 4M1; M9W 6L4 and M9W 6A7).\n\nPairs of neighboring PCs with high-case count clusters were identified by Cluster and Outlier analysis. Panels show: (A) parameters measured in PC pairs that were elements of significant high-case clusters over multiple consecutive days (allowing for a single day gap), termed “streaks”; (B) characteristics of neighboring pairs of PCs with multi-day streaks in close proximity in Toronto (of ten closest neighbors based on distance between centroids) during waves 2 (top) and 3 (bottom). Wave 1 is not indicated because streaks were infrequent. Each point represents a pair of PCs, with color codes (see legend) indicating ranges of total number of cases in both, the X axis indicates the duration between PC pairs (with negative values representing number of days of overlap between end of first PC streak and beginning of the second), and the Y axis indicates spatial distance between PCs constituting the pair.\n\nWe examined evidence for likely community spread of COVID-19 between infected individuals in different pairs of neighboring PCs. This involved determining the distances separating them, the duration between streaks in the respective PCs, the total case counts among PC pairs during these streaks, and then assessing the significance of these characteristics. During waves 2 and 3 in Toronto, paired concurrent or consecutive streaks in such PCs were common (Figure 7B). Frequencies of these PC pairs were negatively correlated with the duration of the gap between the end of a streak in one member of the pair and the beginning of the other (r = −0.57 and -0.50 for waves 2 and 3, respectively). To assess the significance of these results, a multinomial logistic regression model was derived from (1) the total number of cases in each pair of PCs over the course of both streaks (classified as either <25, between 25 and 49, or ≥50 cases), (2) the duration or gap (in days) separating streaks in a pair of PCs, and (3) the distances between the centroids of both PCs. The duration between streaks was significantly shorter for PC pairs with ≥50 cases relative to those with <25 cases (p = 0.0005 and 0.0141 for waves 2 and 3, respectively, using the Wald two-tailed z-test on the coefficients of the model). The same relationship was also significant when comparing streaks in pairs of PCs with ≥50 cases and those with 25-49 cases (p = 0.0015 and 0.0277 for waves 2 and 3, respectively). Total case counts and time between streaks in a pair of PCs were also inversely correlated (r = −0.41 in both waves 2 and 3), which is consistent with disease transmission between adjacent PCs being more common when cases were more abundant. These parameters were also inversely correlated (r = −0.13 and -0.17, respectively) in Ottawa and Windsor/Essex, but under less stringent criteria that allowed ≥6 cases for only one of the PCs in a pair on a single day. The relationship between distance between PCs and total number of cases was not significant by the regression model in either of these waves. Increasing the number of PC neighbors considered over a larger range of distances did not alter this result (Extended data,29 Section 1 - Figure S7). However, upon dividing groups of neighboring PCs thresholded according to average quartile values (distance [182m] and average gap between streaks [17.5 days]) distance between neighbors was significant when combined with the degree to which they coincided temporally. Below average duration between streaks and distance separating PCs were 2.8-fold more likely to exhibit ≥50 cases than all other PC pairs (p = 0.002 by Mantel-Haenszel chi square test). Transmission of higher levels of COVID-19 between pairs of PCs is supported by abbreviated intervals between streaks and their proximity to one another.\n\nMultiple paired PC streaks in Toronto were tightly grouped within a single neighborhood over a short period of time (Extended data,29 Section 1 - Table S6). Directional network diagrams were created to illustrate the connectivity and temporal relationships between these and other paired high-case cluster streaks in close proximity (Extended data,29 Section 1 - Figures S8 and S9 for waves 2 and 3, respectively). The preponderance of paired streaks were bimodal (9 paired streaks where only two neighbors interact [Extended data,29 Section 1 - Figure S8D], of which 17 occurred in wave 3 [Extended data,29 Section 1 - Figure S9A]), and in close succession (≤7 days between streaks). Multi-node networks involving ≥3 postal codes occurred in 3 distinct neighborhoods in wave 2, and another three neighborhoods within wave 3. These neighborhoods were often comprised of multiple adjacent apartment buildings, and rarely occurred in low-density residential areas. The PCs where streaks tended to coincide were often proximate to facilities where communities may have congregated (grocery stores, schools, parks, or religious sites). We investigated whether the participation of many PCs in a multi-node network was a result of higher case counts during a streak (which would suggest an increased probability of transmission between these locations). However, bimodal networks of two PCs with recurrent high case counts were not rare (e.g., >100 cases within a 9-day streak in M1R 1T1), so other factors are necessary to explain why some PCs form multi-node networks. Furthermore, the average numbers of cases within streaks in bimodal networks and multi-node networks were comparable (18.8 and 17.0 cases per streak, respectively).\n\nIn some instances, PCs began to accrue cases prior to their inclusion in significant clusters of PCs or reaching the minimum numbers of cases to be designated a COVID-19 hotspot (M4H 1K1, M4H 1K2, M4H 1K4, M4H 1L1, M4H 1L6, and M4H 1L7). These PCs were nevertheless elements of the M4H FSA streak. Similarly, M4H 1L3 and M4H 1L4 were elements of a cluster containing M4H 1J4 on Nov. 8-10, 2020, at least 2 weeks prior to the occurrence of the corresponding multi-day streaks. Consecutive streaks within a set of clustered PCs in Etobicoke (M9V 3S6, M9V 3Z8, M9V 4A4, M9V 4A9, M9V 4M1, M9V 4P1, and M9V 5G9; centroids were all within 0.63km of one another) occurred between mid-October and late December 2020 (Figure 8B). M9V 5G9 is separated from the other PCs by a wooded area, but all are close to a major thoroughfare, Kipling Avenue. A striking directional acyclic network of COVID-19 cases involved 7 adjacent PCs whose streaks occurred concurrently and were occurred nearly consecutively along Bathurst Street, Toronto (M2R 1Z2, M2R 1Z7, M2R 1Z8, M2R 1Z9, M2R 2A1, M2R 1Z6, M2R 2Y2; within 0.57km of one another; Figure 8C). Curiously, the order of occurrence of COVID-19 infections among these PCs consistently followed a southerly direction along Bathurst Street.\n\nDirectional acyclic graphs (left) organize adjacent high-case clustered PC streaks within the same FSAs ordered according to their occurrence. Panels indicate PCs within (A) M4H and (B) M9V in Toronto during wave 2. Each connection (or ‘edge’) linking two PCs represents a pair of clustered streaks occurring within 30 days of each other (all significant PC pairs are indicated in Extended data,29 Section 1 - Table S6). Labels on each edge indicate the duration (in days) separating adjacent PC pairs and the number of cases which occurred in the combined streaks (“dates.cases”). Negative values, when present, indicate the number of overlapping days of concurrent streaks in pairs of PCs. Arrows indicate the temporal order of these paired streaks (from earlier to the later streak). Maps (right) show the physical locations of each PC within the corresponding networks\n\nThe multi-node networks during wave 3 consisted of only three postal codes (M3C, M9V, M9W; Extended data,29 Section 1 - Figure S9A). Increasing the number of neighbors (by relaxing distance constraints, from 10 to 30 PCs) for these PC networks results in multi-node networks that were previously identified as bimodal (M4H, M4C, and M4X; Extended data,29 Section 1 - Figure S9B). This procedure also resulted in four additional bimodal pairs of PCs in wave 2 (Extended data,29 Section 1 - Figure S8D); however, the total number of PCs comprising the multi-node networks in wave 2 was unchanged (Extended data,29 Section 1 - Figures S8A-C).\n\n\nDiscussion\n\nGeostatistical analysis revealed the locations and relationships between COVID-19 hotspots, utilizing daily postal code-level case data in Ontario Canada from March 26th, 2020 through June 25th, 2021 (including Gi, Spatial Autocorrelation, Clustering and Outlier analyses and interpolation by kriging). Previous efforts to integrate geostatistical and epidemiological data have not investigated COVID-19 at this level of geographic and temporal resolution. This approach more precisely localized COVID-19 hotspots, and enabled early detection of disease clusters, which could be exploited to prevent or limit further spread at or close to these hotspots. Concurrent or consecutive neighboring hotspots classified as persistent high-case clusters were flagged as possible evidence of disease transmission.\n\nThe COVID-19 epidemic in Ontario has been classified into three distinct waves of infections.34 The recurrence of successive waves shortly after easing of public health measures strongly motivated development and implementation of novel strategies that anticipate the locations and timing of future hotspots. Network analysis demonstrated that these locations may form nuclei from which subsequent local outbreaks arise. COVID-19 clusters were considerably diminished in the older at-risk population during the third wave 3, most likely, because of province-wide vaccination compliance, which resulted in lower mortality in long-term care residences during this period.\n\nThe techniques implemented in this study could prove useful to assist with contact tracing of infectious diseases, which may be challenging to carry out in a timely fashion once community spread has already occurred. Contact tracing has been vital to identify potential sources of viral transmission from infected cases. Successful contact tracing is impacted by incomplete collection of information, specifically interviewees who provide imprecise information, omit critical interactions, or who are uncooperative.35 The directional acyclic network graphs presented are consistent with transmission between individuals residing in multiple PCs in close proximity to each other. These tools could assist tracing investigations by focusing resources on the most likely locations where interactions between infected and uninfected persons occur. It may be possible to exploit observations of COVID-19 infections at consecutive, neighboring PCs to anticipate the occurrence and locations of subsequent infections. This was exemplified by the progression of cases along PCs on Bathurst Street, Toronto in wave 2 (Figure 8C). We suggest that these and similar patterns may be useful as features along with cellular phone mobility data from dates preceding the appearance of future hotspots for predictive machine learning models. Accuracy in predicting the timing of future hotspots, however, would be influenced by the lag between date of infection and presentation of symptoms and by compliance of symptomatic individuals in seeking testing. Application of geostatistical analyses and other technologies36 may overcome the challenges posed by non-compliance or erroneous COVID-19 information from infected persons.\n\nWe also identified persistent, clustered postal codes that recurred between waves. Neighboring PCs comprising high-case clusters over a series of consecutive or overlapping dates were proposed as evidence of COVID-19 transmission. Nine PC pairs across 4 separate regions in Toronto were flagged in both waves 2 and 3, which were suggestive of recurrence. Without viral sequencing data, it is not possible to unequivocally establish whether these local outbreaks were independent events or due to re-emergence of the same infection from a low-level reservoir of asymptomatic or persistent mild infections during interwave 2-3. The same type of analysis did not yield evidence of inter-wave COVID-19 transmission in the other municipalities evaluated. Because of their comparatively lower population densities and smaller geographic size, it is less likely that the case thresholds required to define a COVID-19 hotspot within a 3-day window can be met in other Ontario municipalities. Increasing the aggregation of cases from 3- to 7-day sliding windows might improve detection of likely COVID-19 transmission in these areas.\n\nUnlike traditional geostatistical epidemiology, we did not determine the likelihoods of hotspots based on simulations of random distributions of the same number of cases in the analyzed region,14,37 since background levels of COVID-19 were undetectable prior to the pandemic. Therefore, performing geostatistical tests on positive COVID-19 cases is valid statistically. FSA-level analysis on population-normalized case counts (cases per 100,000; where FSAs with <100 individuals were not analyzed) was also performed (March to November 2020).29 Analyses could not be normalized by population densities (cases per 100,000) since these data are not publicly available for individual PCs. However, the smallest geographic units defined by Statistics Canada, termed Dissemination Areas, encompass an average of 15 postal codes (consisting of 400-700 persons).38,39\n\nA seroprevalence study of COVID-19 antibodies in Canada has suggested that infection rates were up to 3-fold higher than detected by RT-PCR testing during the first wave.33 Similar studies have also indicated underreporting in the U.S.40 and Europe.41,42 This included asymptomatic and untested symptomatic infected individuals41 or who received negative results.43 Our study assumes that the geographic and temporal distribution of unrecognized infections trends similarly with known cases. However, nonuniformity in the distribution of asymptomatic and undetected cases across Ontario could have altered the detection or localization of hotspots. It seems likely that significant hotspots detected by geostatistical methods that also fulfill minimum case count thresholds would seem to be less likely to present as false positives or be incorrectly localized.\n\nSome geostatistical functions (e.g., Gi and Cluster and Outlier analysis) could be computed rapidly (within seconds for a single day analysis), while others (e.g., intersection of kriging contours PC boundaries) required up to 10 minutes per date analyzed on the ICES research computing system. In order to scale these computations over the duration of this project, it was critical to automate analyses for Provincial and multiple Municipal jurisdictions for timely generation and interpretation of these results. In April 2021, the sponsor of our AHRQ project requested an analysis of recent COVID-19 count and location data (January-March 2021). We automated kriging of localized hotspots in Toronto, Windsor/Essex, Ottawa and London within 5 days from the receipt of the request. This entailed performing the software analysis, imaging the results as maps, and interpreting these results. The rapid turnaround of geostatistical analysis of ongoing infectious diseases could have practical value for time-sensitive, critical public health management decisions. These programs have been made as a publicly available package, reformatted as a user-friendly toolbox in ArcMap (the Geostatistical Epidemiology Toolbox).30\n\nFSA-level geospatial tests, such as Gi, did not reveal the distributions of COVID-19 infections, a limitation of this approach. We attempted to mitigate this by integrating the results of multiple geostatistical methods at different levels of resolution (e.g., Spatial Autocorrelation determined if cases were clustered at the PC-level). The locations of individuals in the same FSAs and PCs were aggregated at the centroids of their respective boundaries. However, boundary shapes and areas covered by different FSAs or PCs can vary, even though the total populations within each are more similar. Rural FSAs can be larger than urban counterparts and are occasionally non-contiguous (e.g., the FSA N0P). While close proximity of COVID-19 positive individuals in high-density municipalities is more consistent with transmission, it was nevertheless feasible to detect hotspots in rural regions. However, high concentrations of cases are required to find statistically significant hotspots in these regions. Since we use PC centroids to assign cases, this also affects the contours defined by kriging analysis of rural regions. These are limitations of the imposed boundaries of FSAs and PCs and not of the geostatistical tests used. Due to privacy considerations imposed by data providers, we could not perform kriging analysis on exact locations of COVID-infected individuals. Kriging interpolation can overlap multiple FSAs (Extended data,29 Section 1 - Figure S10), which can be advantageous over area-to-area geostatistical tests, as hotspots in close proximity that cross an FSA boundary could be missed with these tests. However, FSAs with few or no cases that are adjacent to a local hotspot could mistakenly be implicated. We account for this by ignoring FSAs without case counts, however this effect can still impact interpolation accuracy. For example, the interpolated case count for the FSA N8H in late June 2020 was much higher than the ground truth (Extended data,29 Section 1 - Figure S4B). Over the same period, 109 cases were reported over a 3-day period within N0P 2J0, which is immediately north of N8H. The high-case kriging contour detecting this event intersects the boundary of N8H, thus causing this discrepancy (Extended data,29 Section 1 - Figure S4C).\n\nIn late 2020, Ontario announced prioritization of COVID-19 vaccinations beginning with those with the highest risk of contracting severe illness. The subsequent group included individuals residing in hotspot communities.44 These hotspots were identified in FSAs with the highest counts per 100,000 population. However, cases are not always uniformly distributed within FSAs with high disease burden (Figure 4). This study illustrates the importance of identifying hotspots at a higher resolution and describes how this level of precision provides targeted information about transmission that is often not feasible with FSA-level analyses. To minimize high rates of community transmission in the future, we suggest that targeted vaccination campaigns focus on highly constrained, localized hotspots with high case counts at the earliest possible juncture (rather than broadly across a region or FSA). For example, a hotspot in London was detected by kriging over several weeks at levels below our pre-selected interpolated case thresholds (Figure 6). The results of this analysis surpassed these thresholds approximately one week before it was publicly revealed. Thus, targeting can achieve the necessary precision and at an earlier stage with these methods. Smaller targeted locations may also facilitate communication, promote compliance and implementation of individual public health measures.\n\n\nData availability\n\nZenodo: Zenodo Archive for ‘Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada, http://doi.org/10.5281/zenodo.5585812.29\n\nThis project contains the following underlying and extended data, organized across 4 sections. Section 1 and 2 contain extended data, and Sections 3 and 4 contains the data files containing and the map image files displaying the underlying statistics from the various geostatistical analyses performed in this study.\n\nZenodo: Zenodo Archive for ‘Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada’: http://doi.org/10.5281/zenodo.5585812.29\n\nThis project contains the following extended data:\n\n• Section 1 – An Excel document containing 6 additional tables described in this study which provide summary statistics of various geostatistical tests (“Section 1 – Tables S1-S4”) and lists all identified single and paired high-case cluster streaks (“Section 1 – Tables S5-S6”). This section also contains 10 additional figures referred to in the manuscript (“Section 1 – Figures S1-S10”) with a Word document which describe them. Figure legends are as follows:\n\n○ Figure S1. Case Count of FSAs by Frequency. Histograms indicate the frequency in which an FSA in (A) Ontario and (B) Toronto were reported to have ≥X COVID-19 cases (where X is the value on the X-axis) on a specific day from March 1st to September 24th, 2020 (blue columns). Gi analysis identified which FSAs were significant hotspots by comparing them with neighboring FSAs at a fixed distance (indicated with red bars) and inversely weighted distances (indicated with green bars), at a threshold of <50km. A large fraction of FSAs in Ontario and Toronto contained fewer than 8 cases and were not statistically significant. Over two thirds of FSAs with at least 10 cases were significant by the Gi* test at a 99% confidence level.\n\n○ Figure S2. Evaluation of Kriging Semivariogram Models. Interpolation by different semivariogram models was evaluated using kriging to determine which model best approximated true case counts in regions of moderate-to-high population densities. The two best performing models chosen were ‘Power’ and ‘Thin Plate Spline’ (TPS). Each point in this figure represents PCs with ≥1 COVID-19 case and PCs with ≥6 cases have been labelled [PC/case count]). Panel (A): Kriging analysis of Hamilton (moderate-density of cases) indicates Power-modeled kriging (left) shows smooth fit to the actual case distribution compared to TPS, which is discontinuous (right). Panel (B): In Toronto (high-density of cases), interpolation with the ‘Power’ model more frequently under-estimated actual case counts, whereas the TPS model derived case counts that more precisely resembled the actual distribution of cases.\n\n○ Figure S3. Histograms of the Fraction of FSAs Overlapped by Significant Kriging Contours. The percent overlap of the areas covered by kriging-derived contours and the corresponding FSAs were computed by area for all FSAs flagged by Gi* analysis. Panels depict (A) wave 1, (B) interwave 1-2, (C) wave 2, (D) interwave 2-3, and (E) wave 3. Histograms illustrate the distribution of the fraction of each FSA that is geographically intersected with either the highest interpolated kriging contour level (left) or kriging contours interpolating at least 5 (right).\n\n○ Figure S4. Hotspots Localized within High Disease Burden Regions. The distribution of COVID-19 cases within the FSAs (A) N9Y (Kingsville, ON) and (B) N8H (Leamington, ON) during interwave 1-2 was evaluated by kriging, Spatial Autocorrelation and Gi* analysis. Kriging-interpolated case values (blue line) were similar to actual case counts (red line). COVID-19 outbreaks within these FSAs were often identified by Gi* analysis (green asterisks), however the distribution of cases within these regions were infrequently found to be spatially clustered (purple crosses). Panel (C) indicates Power-based kriging contours can be large in regions with low population densities due to the distribution of cases. Interpolation of cases within N8H from June 22nd to June 26th, 2020 exceeded than actual counts due to the contribution of a high-case postal code in a neighboring FSA (N0P), with the resultant kriging contour intersecting both FSAs.\n\n○ Figure S5. A Localized Hotspot in Leamington, Ontario. PC-level COVID-19 case data of the FSA: N8H (Leamington, ON) on consecutive dates in December 2020 evaluated by kriging interpolation (blue line), testing for significance by Spatial Autocorrelation (purple crosses) and Gi* analysis (green asterisk). B) Map contours and distribution of cases. Small circles in this region represent PCs with one or more cases from December 21st to the 23rd, 2020. The maximal kriging contour was coincident with the hotspot in PC N8H 3V5 during this window.\n\n○ Figure S6. Spatial Clustering and the Identification of Localized Hotspots. Spatial autocorrelation analysis identifies clusters of postal codes with high case counts within FSAs. Panels (A) displays significantly clustered cases in Toronto FSA M1P from Nov. 3-5, 2020. This region was also significant by Gi* and contained a localized hotspot consisting of 8 cases (M1P 4V6). Each dot represents a postal code with at least 1 but fewer than 6 cases. (B) Cases in M1C were also significantly clustered from Nov. 6-8, 2020, but no hotspots were identified. Topographic contours indicate kriging-interpolated case counts.\n\n○ Figure S7. Contiguous or Consecutive Toronto Paired Streaks considering 50 Closest Neighbors. High-case postal code clusters were identified by Cluster and Outlier analysis (Local Moran’s I). High-case cluster streaks (PCs significant over multiple consecutive days, allowing for a single day gap) were identified and paired to other streaks within close proximity (considering 50 closest neighbors based on distance between PC centroids). Each point represents a paired PC streak with colors representing the total number of cases in both, the X axis indicates the duration between PC pairs (with negative values representing degree of overlap between end of first streak and beginning of the other), and the Y axis indicates spatial distance between the centroids of each PC forming a pair. All paired streaks are illustrated, regardless of wave.\n\n○ Figure S8. Directional Acyclic Graph Network of Clustered Streaks in Toronto during Wave 2. Directional networks identify streaks of clustered high-case counts (≥6 cases for each date evaluated) in close spatial and temporal proximity. Each connection (or edge) represents two neighboring PCs, where the value preceding the decimal represents the days separating pairs of streaks followed by the total number of cases in both (“dates.cases”). The arrows represent the order in which streaks occur in the pair of PCs. The left and right panels indicate the same network, based on either the 10 or 30 closest neighbors, respectively. Maps indicate the locations of PCs within the network (middle). The panels highlight different networks in neighborhoods according to the FSA: in which they occur: (A) M4H, (B) M9V and (C) M2R. Although increasing the number of neighbors considered for pairing added new edges, novel postal codes were not introduced. (D) Networks only connecting streaks between a single pair PCs are indicated.\n\n○ Figure S9. Directional Networks of COVID-19 Clustering Streaks in Toronto during Wave 3. Directional networks illustrate the relationship between PCs with consecutive COVID-19 clustering (i.e., streaks) in Toronto during Wave 3 of the COVID-19 epidemic, considering the (A) 10 closest and (B) 30 closest neighboring PCs for each streak. Simple networks involving two or three PCs were common and exhibited recurrent transmission between nodes. Increasing the number of allowable neighbors considered increased network complexity, including those not previously seen during Wave 2 (M3C, M4C and M4X). Networks for Wave 3 are less complex compared to those in Wave 2, possibly due to the increase of vaccinated individuals within the population.\n\n○ Figure S10. Overlap of Localized Hotspots with Multiple FSAs. Kriging contours can overlap multiple FSAs. While the kriging semivariogram model selected can affect their frequency, contours which intersect ≥2 FSAs can occur with either method. Panel A includes: a TPS-based kriging contour which intersected 9 separate FSAs in Toronto, and panel B shows a power-based kriging contour which interpolated ≥10 cases over 6 unique FSAs in London.\n\n• Section 2 – All localized hotspots (identified through kriging analysis) catalogued for each municipality evaluated are provided in this section. Each data file lists the FSA containing the localized hotspot, the size of this hotspot (% by area), the 3-day window in which it was observed, the interpolated and true case values on this date, and whether the FSA was also significant by Gi* analysis (on any of the 3 days analyzed).\n\nZenodo: Zenodo Archive for ‘Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada’: http://doi.org/10.5281/zenodo.5585812.29\n\nThis project contains the following underlying data:\n\n• Section 3 – All output files from the geostatistical tests performed in this study are provided in this section. This includes the output from Ontario-wide FSA-level Gi* and Cluster and Outlier analyses, and PC-level Cluster and Outlier, Spatial Autocorrelation, and kriging analysis of 6 municipal regions. Kriging analysis output files are also provided for 7 municipalities immediately surrounding Toronto. This section also contains data files from our analyses of stratified case data (by age, gender, and at-risk condition). All coordinates presented in these data files are given in “PCS_Lambert_Conformal_Conic” format. Case values between 1-5 were masked (appear as “NA”).\n\n• Section 4 – Sets of image files which map the results of our geostatistical analyses onto a map of Ontario or within the municipalities evaluated are provided. This includes: kriging analysis (PC-level), Local Moran's I Cluster and Outlier analysis (FSA and PC-level), normal and space-time Gi* analysis, and all images for all analyses performed on stratified data (by age, gender, and at-risk condition).\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nSoftware availability\n\nA second Zenodo repository (https://doi.org/10.5281/zenodo.567597930) provides all program files pertaining to the (Geostatistical analysis software package to be used in ArcGIS), as well as all other scripts described in this manuscript. This code is available under the terms of the GNU General Public License v3.0.\n\n\nFunding\n\nData acquisition and computing facilities used in this study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC). Data and information compiled were also provided by MOH. This study was also supported by the Ontario Health Data Platform (OHDP), a Province of Ontario initiative to support Ontario's ongoing response to COVID-19 and its related impacts. The work described was funded and performed under a contribution agreement between the Innovation for Defence Excellence and Security (IDEaS) program at the Department of National Defence and CytoGnomix. The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources. No endorsement by ICES, OHDP, its partners, or the Province of Ontario is intended or should be inferred.", "appendix": "Acknowledgements\n\nThe authors acknowledge advice from Dan Lizotte at Western University. ICES personnel: Refik Saskin, Minnie Ho, Diana An, and Ryan Godinho, Kamil Malikov and his staff at MOH, and Regine Lecocq at the Department of National Defence IDEaS program are recognized for their support and facilitation of this project.\n\n\nReferences\n\nAnderson RM, Heesterbeek H, Klinkenberg D, et al.: How will country-based mitigation measures influence the course of the COVID-19 epidemic?. Lancet. 2020; 395: 931–934. PubMed Abstract \| Publisher Full Text\n\nBarrett K, et al.: Estimation of COVID-19–induced depletion of hospital resources in Ontario, Canada. CMAJ Can. Med. Assoc. J. 2020; 192: E640–E646. Publisher Full Text\n\nGardner BJ, Kilpatrick AM: Contact tracing efficiency, transmission heterogeneity, and accelerating COVID-19 epidemics. PLoS Comput. Biol. 2021; 17: e1009122. PubMed Abstract \| Publisher Full Text\n\nDetsky AS, Bogoch II: COVID-19 in Canada: Experience and Response. JAMA. 2020; 324: 743–744. Publisher Full Text\n\nGovernment of Canada, O. of the A. G. of C: Report 10—Securing Personal Protective Equipment and Medical Devices.2021. Reference Source\n\nLiu J, et al.: Community Transmission of Severe Acute Respiratory Syndrome Coronavirus 2, Shenzhen, China, 2020. Emerg. Infect. Dis. 2020; 26: 1320–1323. PubMed Abstract \| Publisher Full Text\n\nCarrat F, Valleron AJ: Epidemiologic Mapping using the “Kriging” Method: Application to an Influenza-like Epidemic in France. Am. J. Epidemiol. 1992; 135: 1293–1300. PubMed Abstract \| Publisher Full Text\n\nDesjardins MR, Whiteman A, Casas I, et al.: Space-time clusters and co-occurrence of chikungunya and dengue fever in Colombia from 2015 to 2016. Acta Trop. 2018; 185: 77–85. PubMed Abstract \| Publisher Full Text\n\nAli M, et al.: Application of Poisson kriging to the mapping of cholera and dysentery incidence in an endemic area of Bangladesh. Int. J. Health Geogr. 2006; 5: 45. PubMed Abstract \| Publisher Full Text\n\nGreene SK, Peterson ER, Kapell D, et al.: Daily Reportable Disease Spatiotemporal Cluster Detection, New York City, New York, USA, 2014–2015. Emerg. Infect. Dis. 2016; 22: 1808–1812. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAzevedo L, Pereira MJ, Ribeiro MC, et al.: Geostatistical COVID-19 infection risk maps for Portugal. Int. J. Health Geogr. 2020; 19: 25. PubMed Abstract \| Publisher Full Text\n\nBriz-Redón Á, Serrano-Aroca Á: A spatio-temporal analysis for exploring the effect of temperature on COVID-19 early evolution in Spain. Sci. Total Environ. 2020; 728: 138811. PubMed Abstract \| Publisher Full Text\n\nDesjardins MR, Hohl A, Delmelle EM: Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters. Appl. Geogr. Sevenoaks Engl. 2020; 118: 102202. PubMed Abstract \| Publisher Full Text\n\nHohl A, Delmelle EM, Desjardins MR, et al.: Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States. Spat. Spatio-Temporal Epidemiol. 2020; 34: 100354. PubMed Abstract \| Publisher Full Text\n\nJia JS, et al.: Population flow drives spatio-temporal distribution of COVID-19 in China. Nature. 2020; 582: 389–394. PubMed Abstract \| Publisher Full Text\n\nKim S, Castro MC: Spatiotemporal pattern of COVID-19 and government response in South Korea (as of May 31, 2020). Int. J. Infect. Dis. 2020; 98: 328–333. PubMed Abstract \| Publisher Full Text\n\nOnovo AA, et al.: Using Supervised Machine Learning and Empirical Bayesian Kriging to reveal Correlates and Patterns of COVID-19 Disease outbreak in sub-Saharan Africa: Exploratory Data Analysis.2020. 2020.04.27.20082057. PubMed Abstract\n\nFatima M, O’Keefe KJ, Wei W, et al.: Geospatial Analysis of COVID-19: A Scoping Review. Int. J. Environ. Res. Public Health. 2021; 18: 2336. PubMed Abstract \| Publisher Full Text\n\nKulldorff M and ; Information Management Services Inc SaTScanTM v8.0: Software for the spatial and space-time scan statistics. 2009.\n\nAnselin L, Syabri I, Kho Y: GeoDa: An Introduction to Spatial Data Analysis. Geogr. Anal. 2006; 38: 5–22. Publisher Full Text\n\nR Core Team: R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2018.\n\nRogan PK, Mucaki EJ: Geostatistical Analysis of SARS-CoV-2 Positive Cases in the United States.2020. Reference Source\n\nGetis A, Ord JK: The Analysis of Spatial Association by Use of Distance Statistics. Geogr. Anal. 1992; 24: 189–206. Publisher Full Text\n\nOrd JK, Getis A: Local Spatial Autocorrelation Statistics: Distributional Issues and an Application. Geogr. Anal. 1995; 27: 286–306. Publisher Full Text\n\nAnselin L: Local Indicators of Spatial Association—LISA. Geogr. Anal. 1995; 27: 93–115. Publisher Full Text\n\nBoots BN, Getis A: Point Pattern Analysis. Newbury Park, CA: Sage Publications; 1998.\n\nGribov A, Krivoruchko K: Empirical Bayesian kriging implementation and usage. Sci. Total Environ. 2020; 722: 137290. PubMed Abstract \| Publisher Full Text\n\nKrivoruchko K: Empirical Bayesian Kriging.2012. Reference Source\n\nMucaki EJ, Shirley BC, Rogan PK: Zenodo Archive for ‘Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada’.2021. Publisher Full Text\n\nShirley BC, Mucaki EJ, Rogan PK: Software archive for ‘Likely community transmission of COVID-19 infections at neighboring, persistent hotspots in Ontario, Canada’.2021. Publisher Full Text\n\nRogan PK, et al.: Meeting radiation dosimetry capacity requirements of population-scale exposures by geostatistical sampling. PLoS One. 2020; 15: e0232008. PubMed Abstract \| Publisher Full Text\n\nMiddlesex-London Health Unit: Outbreak Declared as More Than 40 Cases Reported at Apartment Complex — Middlesex-London Health Unit.2020. Reference Source\n\nSaeed S, et al.: SARS-CoV-2 seroprevalence among blood donors after the first COVID-19 wave in Canada. Transfusion (Paris). 2021; 61: 862–872. PubMed Abstract \| Publisher Full Text\n\nDetsky AS, Bogoch II: COVID-19 in Canada: Experience and Response to Waves 2 and 3. JAMA. 2021; 326: 1145–1146. Publisher Full Text\n\nGarry M, Hope L, Zajac R, et al.: Contact Tracing: A Memory Task With Consequences for Public Health. Perspect. Psychol. Sci. J. Assoc. Psychol. Sci. 2021; 16: 175–187. PubMed Abstract \| Publisher Full Text\n\nCOVID-19 National Emergency Response Center, Epidemiology & Case Management Team, Korea Centers for Disease Control & Prevention: Contact Transmission of COVID-19 in South Korea: Novel Investigation Techniques for Tracing Contacts. Osong. Public Health Res. Perspect. 2020; 11: 60–63. PubMed Abstract \| Publisher Full Text\n\nKulldorff M: Prospective time periodic geographical disease surveillance using a scan statistic. J. R. Stat. Soc. Ser. A Stat. Soc. 2001; 164: 61–72. Publisher Full Text\n\nStatistics Canada: Dissemination area: Detailed definition.2018. Reference Source\n\nStatistics Canada: Dissemination Area Reference Maps, by Census Tracts, for Census Metropolitan Areas and Census Agglomerations.2021. Reference Source\n\nJones JM, et al.: Estimated US Infection- and Vaccine-Induced SARS-CoV-2 Seroprevalence Based on Blood Donations, July 2020-May 2021. JAMA. 2021; 326: 1400–1409. PubMed Abstract \| Publisher Full Text\n\nByambasuren O, et al.: Comparison of seroprevalence of SARS-CoV-2 infections with cumulative and imputed COVID-19 cases: Systematic review. PLoS One. 2021; 16: e0248946. PubMed Abstract \| Publisher Full Text\n\nGrant R, et al.: SARS-CoV-2 population-based seroprevalence studies in Europe: a scoping review. BMJ Open. 2021; 11: e045425. PubMed Abstract \| Publisher Full Text\n\nCharlton CL, et al.: Pre-Vaccine Positivity of SARS-CoV-2 Antibodies in Alberta, Canada during the First Two Waves of the COVID-19 Pandemic. Microbiol. Spectr. 2021; 9: e0029121.\n\nOntario Ministry of Health: COVID-19: Guidance for Prioritization of Phase 2 Populations for COVID-19 Vaccination.2021. Reference Source" }	[ { "id": "129168", "date": "05 Apr 2022", "name": "Lorant Foldvary", "expertise": [ "Reviewer Expertise geodesy", "gravimetry", "geoinformatics" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nBrief Report:\nQ: Is the work clearly and accurately presented and does it cite the current literature? A: The work is clearly and accurately presented, but the citation of the relevant literature is incomplete. For example, on page 3, in the Introduction: \"Various geostatistical analyses have been used in the surveillance of COVID-19 spread across the globe\" Relevant examples are missing such as Földváry (2021)1 but most essential referring to the solution at Johns Hopkins University.2.\nQ: Is the study design appropriate and does the work have academic merit? Yes, the study design is fine, the academic merit, and the scientific value is notably high.\n\nQ: Are sufficient details of methods and analysis provided to allow replication by others? A: The used methods are fine, this is the strength of the study. Since the analysis is performed on commercially available software, the study might be replicated if the used data is accessible.\nQ: If applicable, is the statistical analysis and its interpretation appropriate? A: Yes, the statistical analysis are fine, the interpretation of the results is reasonable!\nQ: Are all the source data underlying the results available to ensure full reproducibility? A: The information on the source data in the manuscript is a bit confusing. Accordingly, improvement of this section is suggested (see the next paragraph). The data and software availability is provided, this content seems to be fine, although the reviewer has no capacity to check on the full reproducibility.\n\nOn the source data: At distinct locations of the text some information on the data is provided, e.g. in the Geostatistical analysis subchapter of the Methods chapter (page 4) says: \"COVID-19 cases from March 26th, 2020 to June 25th, 2021 at the FSA (Ontario-wide) and PC-level (for 6 populated areas: Hamilton, Kitchener/Waterloo, London Ottawa, Toronto, and Windsor, including Essex county) were evaluated using ArcGIS Desktop 10.7 [ESRI] with the Geostatistical Analyst extension\". It is followed by the first information on the data (page 6, the same subchapter) by indicating that \"COVID-19 testing data compiled by ICES contained metadata on tested individuals, such as gender, age, and relevant predicate health conditions\", and only later, at the subchapter titled Preparation of Ontario COVID-19 case data from ICES (page 7), we get the introduction of the data source. Somehow the introduction of the data source should be provided more consistently, maybe in a separate chapter before \"Methods\" titled \"Data\". The importance of the data for any geostatistical study is essential since the quality and the reliability of the data validates the conclusions.\nQ: Are the conclusions drawn adequately supported by the results? A: Conclusions and interpretations of the results are adequately drawn.\nAdditional detailed comment: Page 6, Methods: \"COVID-19 testing data compiled by ICES contained metadata on tested individuals, such as gender, age, and relevant predicate health conditions.\" This is the first appearance of the abbreviation ICES, please provide here the full name of the organization!\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8547", "date": "21 Jul 2022", "name": "Peter Rogan", "role": "Author Response", "response": "Comment #1: The work is clearly and accurately presented, but the citation of the relevant literature is incomplete. For example, on page 3, in the Introduction: \"Various geostatistical analyses have been used in the surveillance of COVID-19 spread across the globe\" Relevant examples are missing such as Földváry (2021) but most essential referring to the solution at Johns Hopkins University (Dong et al., 2020). Response: We now cite Földváry et al. (2021) in the Introduction of our manuscript, as suggested by the reviewer. We have omitted Dong et al. (2020), as the web resource described in this study simply displays the location of official COVID-19 counts across the world. This paper focuses on literature that performs geostatistical analyses of the distribution of COVID-19 cases beyond simple counts (e.g. disease spread directionality). Comment #2: The information on the source data in the manuscript is a bit confusing. Accordingly, improvement of this section is suggested (see the next paragraph). The data and software availability is provided, this content seems to be fine, although the reviewer has no capacity to check on the full reproducibility. On the source data: At distinct locations of the text some information on the data is provided, e.g. in the Geostatistical analysis subchapter of the Methods chapter (page 4) says: \"COVID-19 cases from March 26th, 2020 to June 25th, 2021 at the FSA (Ontario-wide) and PC-level (for 6 populated areas: Hamilton, Kitchener/Waterloo, London Ottawa, Toronto, and Windsor, including Essex county) were evaluated using ArcGIS Desktop 10.7 [ESRI] with the Geostatistical Analyst extension\". It is followed by the first information on the data (page 6, the same subchapter) by indicating that \"COVID-19 testing data compiled by ICES contained metadata on tested individuals, such as gender, age, and relevant predicate health conditions\", and only later, at the subchapter titled Preparation of Ontario COVID-19 case data from ICES (page 7), we get the introduction of the data source. Somehow the introduction of the data source should be provided more consistently, maybe in a separate chapter before \"Methods\" titled \"Data\". The importance of the data for any geostatistical study is essential since the quality and the reliability of the data validates the conclusions. Response: We agree that the description of the data source should come before our description of the geostatistical methods used to analyze it. We have reordered the sections “Preparation of Ontario COVID-19 case data from ICES” and “FSA and PC Boundary Files,” which now appear before the “Geostatistical analysis” subsection of the Methods section. Comment #3: Page 6, Methods: \"COVID-19 testing data compiled by ICES contained metadata on tested individuals, such as gender, age, and relevant predicate health conditions.\" This is the first appearance of the abbreviation ICES, please provide here the full name of the organization! Response: ICES was previously an abbreviation for the ‘Institute for Clinical Evaluative Sciences', but is no longer. ICES is now the proper legal name of the organization (see: https://www.ices.on.ca/About-ICES/New-name-and-logo). Our agreement with ICES and representatives from ICES requested that the former abbreviation should not be included in the manuscript." } ] }, { "id": "129170", "date": "08 Apr 2022", "name": "Christine Tedijanto", "expertise": [ "Reviewer Expertise Infectious disease epidemiology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors present a thorough geospatial analysis of COVID-19 cases in Ontario, Canada. In this work, they explore a number of different global and local clustering methods in order to demonstrate (1) the importance of higher resolution data to monitor and control COVID-19 and (2) potential transmission between hotspots. They find alignment between the different clustering approaches and evidence of neighboring areas experiencing high case burdens at similar times, implying transmission between communities. In general, I thought the analyses were interesting, but the work could be made more impactful by streamlining the text and focusing on a clearer through line.\n\nFor readers who may not be familiar with Ontario, FSAs, and PCs, it may be helpful to include additional background material such as (1) a map of Ontario showing the location of the six municipalities (and FSAs, if possible) of interest, (2) the number of FSAs/PCs and their approximate population sizes, and (3) overall case counts in your municipalities of interest in each of the waves and interwave periods.\n\nThe motivation behind the subgroup analyses (sex, age, health conditions) was not clear to me. It seems like clusters within each subgroup would tend to appear simply where the highest number of individuals in each subgroup reside, and I’m not sure we would expect the transmission to occur along subgroup lines (for example, we might expect younger family members to transmit to older ones rather than transmission occurring between older individuals). Please explain the reasoning and implications of this analysis further; it may be more suitable in the Extended Data as it seems less relevant to the overall conclusions of the manuscript.\n\nI found it difficult to distinguish between the space-time Gi* and the “streak” analyses. How do they relate to one another? Is there any additional information gained from the space-time Gi* analysis?\n\nPlease describe in more detail the approach that was used to evaluate the kriging and semivariogram models. Why do you think the models performed differently in Toronto compared to other cities? In addition, please clarify – were PCs with 0 cases also excluded as neighbors (i.e., were neighbors in the kriging analysis restricted to neighbors with cases >=1)?\n\nIs there a way to incorporate uncertainty in the kriging analysis? I would also be cautious about using the term “significant” to describe areas with interpolated counts >5, as this may be mistaken for statistical significance.\n\nI thought the graphs in Figure 8 were a bit challenging to interpret. Visually, it may help to arrange the points similarly to how they are geographically located and/or to change the length of the edges in proportion to the duration separating adjacent pairs (the current label).\n\nI would like further discussion about how the authors see these analyses being applied, especially in real-time. For example, the first paragraph of the Discussion says that this method “enabled early detection of disease clusters” – please provide additional evidence of this from the analyses. Additionally, based on the authors’ experience of applying many different methods, are there specific ones that the authors would recommend for real-time use (or public health practice in general)?\n\nMinor comments:\nIn the second paragraph of the introduction, the authors include R in a list of tools that were not used because they require background levels, but R is very general software with packages that may be used without disease background levels. I would consider removing it from this list.\n\nIn my opinion, some sections of the methods may be moved to the Extended Data (e.g. paragraphs beginning “Additional ArcPy scripts…” and “These processes were then integrated…”) for conciseness. Tables 1 and 2 may also be better suited to the Extended Data.\n\nPlease clarify the paragraph about FSAs with case counts <5 – was it possible to analyze these FSAs without masking, just within a separate computing environment? It was not clear to me whether they were masked or not in the final analysis.\n\nIn the fourth paragraph of the results, why were comparisons between kriging and the cluster/outlier methods restricted to March 26 to December 28, 2020?\n\nIn Figure 3B, what do the blue crosses represent? I thought they represented the observed data, in which case I would have expected the same blue crosses in the top and bottom panel. Please clarify.\n\nPlease provide additional information on the “relative density” metric in Figure 4. Is there a reason this particular area and time were highlighted in this figure? It may be interesting to show a hotspot that occurred during a wave rather than in a time window with low disease burden.\n\nIf possible, please combine all resources into one repository.\n\nI did not see underlying data in any of the linked repositories. If the underlying data cannot be publicly shared, please provide a statement describing how the data may be accessed.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8548", "date": "21 Jul 2022", "name": "Peter Rogan", "role": "Author Response", "response": "Major Comment #1: ...it may be helpful to include additional background material such as (1) a map of Ontario showing the location of the six municipalities (and FSAs, if possible) of interest, (2) the number of FSAs/PCs and their approximate population sizes, and (3) overall case counts in your municipalities of interest in each of the waves and interwave periods. Response: We agree that including regional statistics and maps of the areas being studied would be beneficial to the manuscript. We have therefore chosen to append this information to Table 1A of the manuscript, as the structure of the table was well suited for it. The first column of Table 1 includes a map of lower Ontario with the location of each region of interest, as well as maps of each region indicating their boundaries. We also include the population, the area (km2) and the number of FSAs and PCs in each region analyzed. We have also added a new column which gives an estimate of the number of cases present in each region (the sum of cases from individual FSAs associated with the region of interest), divided by waves. These case numbers are estimated, since our contract with ICES has ended, and they have removed our access to actual case data. Thus, any dates in which case data was masked (i.e. the FSA had between 1-5 cases on a particular date) were considered to be a single case by this calculation (which is indicated in the footer of Table 1). Major Comment #2: The motivation behind the subgroup analyses (sex, age, health conditions) was not clear to me. It seems like clusters within each subgroup would tend to appear simply where the highest number of individuals in each subgroup reside, and I’m not sure we would expect the transmission to occur along subgroup lines (for example, we might expect younger family members to transmit to older ones rather than transmission occurring between older individuals). Please explain the reasoning and implications of this analysis further; it may be more suitable in the Extended Data as it seems less relevant to the overall conclusions of the manuscript. Response: The identification of COVID-19 clusters according to these subgroups was specifically requested by the Ontario Ministry of Health. There was interest in identifying differences in how COVID-19 cases were distributed across our regions of interest. This has merit since clustering of a particular subgroup was often correlated with known events occurring in those locations, e.g. high-case clusters of COVID-19 in predominantly young males in rural regions of Windsor/Essex reflecting outbreaks in migrant farm worker communities at this time). We have not moved this analysis (including Table 1) to the extended data. The analysis we describe does not imply that transmission is occurring between or within subgroups. Nonetheless, the distribution of cases by subgroup was of particular interest to the Ontario Ministry of Health. It did not reflect the geographic bias in the residence of subgroup members. We have therefore added the following to the end of the fourth paragraph of Results subsection “Wave 1” (page 17, paragraph 1 without markup): “This stratified analysis itself does not provide insight into the mode of COVID-19 transmission, that is, the development of a hot spot consisting of a particular subgroup does not indicate that viral transmission occurred exclusively between members of the particular subgroup.” Major Comment #3: I found it difficult to distinguish between the space-time Gi* and the “streak” analyses. How do they relate to one another? Is there any additional information gained from the space-time Gi* analysis? Response: Space-time Gi* analysis and Cluster and Outlier ‘streaks’ are indeed two separate analyses. Results using space-time Gi* analysis (built-in to ArcGIS) is provided at the start of the Results. We found that space-time Gi* analysis was generally uninformative, as the analysis called nearly all regions with high numbers of cases (>10 at the FSA level) as statistically significant (>90% in most waves). Therefore, we did not pursue it further. However, this was not explicitly stated, so we have added the following statement to the aforementioned Results paragraph: “As the vast majority of regions were flagged by this approach (>90%), we did not gain any insight from this space-time analysis.” We then investigated temporal trends using Cluster and Outlier analyses of “streaks” of consecutive days that particular locates were deemed hotspots. analysis This is a form of “space-time” analysis, but is completely independent of any functional tests built into ArcGIS. We aren't aware of any prior description of this method. We have modified the text to clarify that this was completely separate from space-time Gi* analysis (page 14, paragraph 2): “Instead, we evaluated temporal trends in the distribution of COVID-19 cases and identified potential transmission using Cluster and Outlier analysis of PCs that persisted across a consecutive series of dates (referred to as high-case cluster ‘streaks’; described later in the Results section).” Major Comment #4: Please describe in more detail the approach that was used to evaluate the kriging and semivariogram models. Why do you think the models performed differently in Toronto compared to other cities? In addition, please clarify – were PCs with 0 cases also excluded as neighbors (i.e., were neighbors in the kriging analysis restricted to neighbors with cases >=1)? Response: (A) In the second paragraph of Methods subsection “Empirical Bayesian Kriging analysis”, we describe our reasoning for prioritizing the Power and TPS semivariograms for low/medium and high case density regions, respectively. Some detail was excluded due to the overall length of the manuscript. To further elaborate, we chose to evaluate all available kriging semivariogram options in ArcGIS in moderate (London, ON) and high (Toronto, ON) density regions across several dates in Waves 1 and 2 of the COVID-19 pandemic. Each semivariogram was tested under various setting conditions (sector type [1 or 4 sectors], search radius [the optimal radius determined by ArcGIS software, that value halved and that value doubled], neighborhood type [smooth or standard] and the number of neighbors considered for each location [5, 10, 15]). The kriging contours generated were converted to polygons in order to perform an ‘intersect’ in ArcGIS between these contours and PCs, and from this intersection, the values interpolated by kriging were compared to true case counts. The Power semivariogram generally modeled counts better in low and medium-density municipal regions. Although TPS often performed well, it produced artifact contours in regions without cases, as described in the Methods (“TPS, in some instances, generated kriging artifacts that did not correlate with known hotspots”). However, the Power semivariogram model was sometimes inferior to TPS, with PCs having high case counts were being missed. Thus, we used TPS in Toronto, considering only 5 neighbors which minimized the kriging artifacts without sacrificing accuracy. This observation was supported by a chi-square test, whereby kriging interpolation with the TPS semivariogram utilizing ≥10 neighbors was frequently significantly different than ground truth (e.g. 72% of dates in Wave 2 were significantly different [p<0.05] when considering 10 neighbors) This did not happen when considering 5 neighbors (p>0.05 for all dates in Waves 1 and 2). This analysis justifies our selection for the number of neighbors parameter when performing kriging, and this analysis is now briefly described in the manuscript: “Using 5 neighboring locations for interpolation minimized these artifacts without affecting the contour map. However, with 10 neighbors, interpolation accuracy was affected according to a chi-square test (e.g., p < 0.05 for the 103 days in Wave 2).” With similar tests, we found that the default kriging parameters (other than neighbor count) were optimal (or lead to equivalent results) regardless of semivariogram used. Multiple kriging parameters are used to define a search neighborhood, the window which delineates which measured locations will and will not be included to predict the value of a region. One such parameter divides this search window into multiple sectors. However, utilizing four sectors led to poorer interpolation of true case counts by chi-square test (significantly different [p<0.05] for 37% of dates in Wave 1 and 82% of dates in Wave 2). Thus, a single sector was used. These parameters are now mentioned in the Methods section: “All other EBK parameters used were defaulted to those provided by the ArcGIS Advanced Geostatistics toolbox (Sector Type: 1 sector, Neighborhood Type: Standard, Search Radius: 1).” The use of TPS in Toronto is now justified. Postal codes with >5 cases are interpolated as such (≥5-10 cases) over twice as often with TPS relative to Power (991 vs 414, respectively). Furthermore, the root mean square error of case count to interpolated case range of PCs with > 5 cases is higher using the Power semivariogram (6.4 with Power, 5.4 with TPS), indicating that TPS outperforms Power at interpolating case counts. A chi-square test comparing the interpolation of daily Toronto case counts using the TPS and Power semivariograms similarly showed that while use of the Power semivariogram was never significantly different from true case counts, the TPS semivariogram better matched ground truth (p-value TPS > p-value Power for 85% and 78% of dates in Waves 1 and 2, respectively). Similarity of Interpolation to True Cases by Chi-Square Test: Kriging utilizing the Power and TPS Semivariogram Days with Greater Similarity [> p-val] to actual cases Days (≥1 PC with ≥ 6 Cases) pTPS > pPOWER pPOWER > pTPS pTPS = pPOWER Wave 1: 60 2 9 71 Wave 2: 112 11 20 143 All six municipalities were evaluated with both the Power and TPS semivariograms across all dates evaluated, the output of which is available in the Zenodo archive. (B) We believe that semivariogram performance in Toronto was due to its far higher population frequency and density relative to the other areas analyzed. Toronto has the highest density of postal codes (75.3 PCs per km2) compared to the other regions investigated (Hamilton: 13.0 PCs per km2; Kitchener/Waterloo: 42.0 PCs per km2; London: 23.9 PCs per km2; Ottawa: 7.9 PCs per km2; Windsor/Essex: 6.0 PCs per km2). While the PC density of Kitchener/Waterloo is somewhat comparable to Toronto, the population density of Kitchener/Waterloo is 2.5x smaller. Furthermore, the number of COVID-19 cases experienced between the two regions were far different, with Toronto having nearly 15-fold more cases compared to Kitchener/Waterloo (see Table 1). Toronto exhibits far more PCs with cases than the other regions tested on most dates. The majority of these PCs have cases between 1-5 (<1% of PCs in Toronto had >5 cases across all dates analyzed). This pushes the interpolated case counts downwards (similar to how zero-case PCs depressed kriging values; see next section). Since the “Power” semivariogram is a parabolic mathematical representation of cases in the region, a large amount of low-case PCs may ‘smooth’ any contour peaks in the region. Since TPS semivariograms attempt to pass through binned data points exactly, these peaks are not lost. Thus, the true case count of high case areas are better represented within the kriging contour. Kriging analysis was performed on COVID-19 case data that did not include PCs with zero cases. In the first paragraph of Methods subsection “Empirical Bayesian Kriging analysis”, we state: “Only PCs with ≥1 case were included in this analysis, as locations without confirmed cases were found to severely depress kriging signals.” PCs with zero case counts are more frequent, even on dates where PCs with cases were at its maximum (e.g. from April 12 to the 14, 2021, 2377 PCs in Toronto had ≥1 case, which is only 5% of the total number of PCs in this region [2.4 to 3.8% for the other 5 regions of interest). These PCs were so pervasive that they depressed the interpolated values of actual cases in PCs with cases. The case count interpolated by kriging was never representative of (i.e. biased against) actual case counts when zero case PCs were included in our testing. We modified the relevant (above) to further explain this: “Only PCs with ≥1 case were included in this analysis, as locations without confirmed cases greatly outnumbered PCs with cases (≥95% of PCs on any given date evaluated) leading to the severe depression of kriging signals.” Major Comment #5: Is there a way to incorporate uncertainty in the kriging analysis? I would also be cautious about using the term “significant” to describe areas with interpolated counts >5, as this may be mistaken for statistical significance. Response: The ArcGIS software is capable of determining uncertainty when performing Kriging (https://desktop.arcgis.com/en/arcmap/10.5/extensions/geostatistical-analyst/kriging-in-geostatistical-analyst.htm) with standard error maps (https://desktop.arcgis.com/en/arcmap/latest/extensions/geostatistical-analyst/using-ordinary-kriging-to-create-a-prediction-standard-error-map.htm). We no longer have access to the ICES computer system to generate such plots. Furthermore, The ‘layer’ files are linked to the input used to generate the kriging layer which is no longer available to us. The main text has been edited to remove instances of the term “significant” for regions interpolated by kriging consisting of >5 case counts. This was changed to “region of interest”, “localized hotspot”, or avoided. The name of Supplemental Figure S3 was also changed. Major Comment #6: ...graphs in Figure 8 were a bit challenging to interpret. Visually, it may help to arrange the points similarly to how they are geographically located and/or to change the length of the edges in proportion to the duration separating adjacent pairs (the current label). Response: The directional network graphs in Figure 8 were created with the MatLab digraph function. digraph does not provide any option to incorporate the recommended changes. The order of data points and edge length are automatically specified. Our only option was to label each path with distance, number of days separating pairs of neighboring streaks, PC identifiers, etc. The maps accompanying the graphs provide a geographic context for each network. Figure 8 and Extended Data Tables S9 and S10 remain unchanged. Major Comment #7: I would like further discussion about how the authors see these analyses being applied, especially in real-time. For example, the first paragraph of the Discussion says that this method “enabled early detection of disease clusters” – please provide additional evidence of this from the analyses. Additionally, based on the authors’ experience of applying many different methods, are there specific ones that the authors would recommend for real-time use (or public health practice in general)? Response: We provide an example within which the FSA N5Y in London Ontario was identified as a region of interest (>5 cases interpolated) by kriging, one week before it was publicized (Figure 6). To provide further evidence of early detection, additional examples (in a new supplementary figure S3A and S3B) of identified localized hotspots prior to public announcement are described: “Localized hotspots within the FSA M9P were observed as early as March 31st, 2020 however the FSA was not flagged by Gi* analysis until April 6th, 2020 (Extended data, Section 1 - Figure S3A). The localized hotspot covers the Village of Humber Heights Retirement Home in Toronto, which was reported to have a COVID-19 outbreak on April 12th, 13 days after the localized hotspot was first detected by kriging. “ “For example, localized hotspots in FSA M9V were identified sporadically, and the interpolated value does not always match total cases (Extended data, Section 1 - Figure S3B). The localized hot spots cover the PC M9V 5B5 starting from April 4th. Outbreaks in the long-term care home within this PC (Humber Valley Terrace long-term care home in Toronto) were reported on April 16th, 2020. This FSA was not flagged by Gi* analysis until April 19th (Extended data, Section 1 - Figure S3B).” There were several instances where kriging identified a localized hotspot prior to public declaration within the same region. These was not found by either Gi* analysis or Cluster and Outlier analysis. While kriging analysis requires more time than these other statistics to generate results (minutes vs seconds per hotspot), software automation on high-powered systems at provincial and municipal scale improved performance of these processes. In April 2021, the Ontario Ministry of Health requested that we perform a full geostatistical analysis of COVID-19 in four municipal regions [London, Ottawa, Toronto and Windsor/Essex] from January and March 2021. We returned the results, including an evaluation of localized hotspots with kriging, within 5 days (see Discussion, paragraph 7). The “Streak” analysis method (based on results from the Cluster and Outlier analysis tool) was only used to trace disease spread; this was a retroactive analysis to identify neighboring, persistent, and overlapping COVID-19 clusters. We believe that additional work is required to prove the validity of use of this approach pro-actively. Early hot spot detection is predicated on the availability of current and complete case data. Except for holiday periods, COVID-19 case data was preprocessed and updated on a weekly basis at ICES. As previously published, the number of cases on the final 3 days of the prior dataset was updated and usually increased in the subsequent release (additional testing data was added to those dates), especially in rural regions where testing was subject to adjustment. We have therefore added the following to the Discussion: “… and enabled early detection of disease clusters, which could be exploited to prevent or limit further spread at or close to these hotspots (provided complete and up-to-date COVID-19 case data is made available in a timely manner).” Minor Comment #1: In the second paragraph of the introduction, the authors include R in a list of tools that were not used because they require background levels, but R is very general software with packages that may be used without disease background levels. I would consider removing it from this list. Response: Geostatistical epidemiology has usually required pre-existing background levels of disease, which is not relevant at the beginning of the COVID-19 pandemic. R and the majority of available epidemiology packages include background level adjustment. While some R packages may permit background to be ignored, we have removed R from the software listed. Minor Comment #2: In my opinion, some sections of the methods may be moved to the Extended Data (e.g. paragraphs beginning “Additional ArcPy scripts…” and “These processes were then integrated…”) for conciseness. Tables 1 and 2 may also be better suited to the Extended Data. Response: Table 2 has been moved to the Extended Data, as requested. Table 1 remains, as previously discussed (Reviewer #2, Major Comment #2). The paragraph beginning “These processes were then integrated…” contains our description of the Geostatistical Epidemiology Toolbox, which is important for reproducibility and portability of the methods we describe. We highlight this in the paper, and F1000Research requires that the software be available as a condition of publication. We have reduced its length rather than removed it. The deleted, relevant information can now be found within the User Manual accompanying the toolbox (“UserManual_GeostatisticalEpidemiologyToolbox_CytoGnomix.pdf”) The paragraph beginning with “Additional ArcPy scripts…” has been moved to the Zenodo archive (“Documentation_for_Each_Section_of_Zenodo_Archive.docx”. Minor Comment #3: Please clarify the paragraph about FSAs with case counts <5 – was it possible to analyze these FSAs without masking, just within a separate computing environment? It was not clear to me whether they were masked or not in the final analysis. Response: All analyses described using unmasked true case count data within the ICES environment, the only exception being the Gi* analysis that was performed to assess the impact of masking on the geostatistical results (described in the fourth paragraph of the Methods, where we found that masking significantly affected results: “We concluded that errors introduced by masking count values precluded analysis of masked data and required all work to be carried out within the RAE computing environment.” We now explicitly state that no other geostatistical analysis described in this study used masked data, with the following statement in the Methods: “All geostatistical analyses presented in this study were performed against unmasked, true case counts.” We also modified an earlier statement in the same paragraph regarding ICES stipulation that we mask FSAs/PCs with 1-5 cases to clarify that this practice applied only to data export: “To ensure patient privacy, ICES stipulated that case counts could not be exported from the ICES system unless FSAs and/or PCs exhibiting between 1 and 5 daily COVID-19 cases were masked.” The following was also added to the Results (first para.): “Changes in the distribution of COVID-19 infections over time were evaluated through geostatistical analysis of true (unmasked) case counts within both FSAs and PCs.” Minor Comment #4: In the fourth paragraph of the results, why were comparisons between kriging and the cluster/outlier methods restricted to March 26 to December 28, 2020? Response: The comparison between kriging and Cluster and Outlier analysis was part of a feasibility analysis (performed in January 2021) to compare the two methods. Expanding this analysis was unlikely to provide novel insights. We prioritized our limited access time to the data and computing environment to perform other analyses. Minor Comment #5: In Figure 3B, what do the blue crosses represent? I thought they represented the observed data, in which case I would have expected the same blue crosses in the top and bottom panel. Please clarify. Response: Blue crosses are bins of paired locations, grouped by distance and direction (as described in the Figure 3 description). How these bins are grouped by ArcGIS software is indeed different whether the Power or TPS semivariogram is being used. Additionally, how data points are binned can regionally differ, as the values and distances between points vary from location to location. However, the two semivariograms from Figure 3B were not associated with each other. The original purpose of Figure 3B was to provide examples of “Power” and “TPS” semivariograms derived from this data. While not implicitly stated in the figure legend, we see now that how the inferrence of a relationship between the two semivariograms could be made. Figure 3B has therefore been updated with semivariograms that are representative of the kriging map presented in Figure 3A. The binned blue crosses for the “Power” and “TPS” semivariograms are similar, although not identical (for the reasons given earlier). Minor Comment #6: Please provide additional information on the “relative density” metric in Figure 4. Is there a reason this particular area and time were highlighted in this figure? It may be interesting to show a hotspot that occurred during a wave rather than in a time window with low disease burden. Response: Figure 4 represents a region where COVID-19 cases were highly dispersed over a period of time. There are indeed likely other additional regions that could have been used, however the example selected is indeed interesting and worthy of discussion. The time window (September 10th to the 29th, 2020) spans the very end of Interwave 1 (September 24th, 2020), leading into Wave 2, a time where the frequency of cases was rapidly increasing. The frequency of dates in which this FSA was called significant by Gi* analysis was similarly increasing. We therefore do not feel that replacing this figure for another example would be beneficial. Minor Comment #7: If possible, please combine all resources into one repository. Response: We have combined the data and software Zenodo archives into a single archive (titled ‘Data and Software Archive for \"Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada\"’). All references to the Zenodo archive within the main text now point to this archive. Minor Comment #8: I did not see underlying data in any of the linked repositories. If the underlying data cannot be publicly shared, please provide a statement describing how the data may be accessed. Response: The underlying data can be found in the file \"Section_3.All-Data_Files.Kriging_GiStar_Local_and_GlobalMorans.2020_2021.zip' in the Zenodo archive (https://zenodo.org/record/5585812#.YtkdD3bMI2w). It contains not only output from our geostatistical analyses, but other Ontario COVID-19 case data as well (where cases between 1-5 are masked, as required). This is mentioned in the “Data Availability” section of the manuscript: Original statement: “Sections 3 and 4 contains the data files containing and the map image files displaying the underlying statistics from the various geostatistical analyses performed in this study.” This has now been clarified to indicate that Section 3 contains the data files, while Section 4 contains map images: “Sections 3 and 4 respectively consist of data files containing and map image files displaying the underlying statistics from the various geostatistical analyses performed in this study.” We also modified the “Extended Data” subsection that describes Section 3, changing the term “output files” to “underlying data” to make the location of the underlying data clearer." } ] }, { "id": "129171", "date": "24 May 2022", "name": "Ezra Gayawan", "expertise": [], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn the introduction, the authors, arguing against some geostatistical software, stated that “… however, these were not used in the present study because of their requirement to include disease background levels, which was not relevant for COVID-19.” I wonder what they really meant by “disease background levels” and how it restricts the use of the mentioned software including R for making geospatial analysis of COVID-19 data. As a fact, there are several of such analyses out there that used different methods and software particularly R. A Poisson geoadditive model, for instance, can be fitted to case count data on COVID-19 over time, which will generate some beautiful spatial maps without the need for any background disease as claimed.\n\nThe relationship between FSA and PC is not clear in the manuscript. This may be confusing for some readers, especially those not familiar with Canada. More detail is required in this aspect by clearly mentioning the benefits of why both FSA and PC were chosen rather than either one of them. An illustrative graph showing the FSA and PC regions would be helpful.\n\nIt is difficult to understand the illustration in Figure 1. A mathematical notation/formula should be used to support the illustration, clearly defining all the parameters involved in the formula.\n\nThe authors mention that \"the software can be easily modified to accommodate other Canadian provinces and, with additional effort, other countries.\" However, there is no guide or link to a description of how the developed tool could be used and probably extended to other provinces or countries.\n\nMore details are required for the multinomial logistic model considered. Explicit details such as the response variable and the corresponding covariates should be clearly stated. If possible, the regression model should include stratification variables as covariates, such as categorized age, and \"at-risk group\" for example. The conclusion drawn from such analysis can be discussed in the Discussion session. It is not clear whether the developed toolbox was used for the estimation of the multinomial regression model or the Directional Acyclic Graph Network.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [ { "c_id": "8549", "date": "21 Jul 2022", "name": "Peter Rogan", "role": "Author Response", "response": "Comment #1. In the introduction, the authors, arguing against some geostatistical software, stated that “… however, these were not used in the present study because of their requirement to include disease background levels, which was not relevant for COVID-19.” I wonder what they really meant by “disease background levels” and how it restricts the use of the mentioned software including R for making geospatial analysis of COVID-19 data. As a fact, there are several of such analyses out there that used different methods and software particularly R. A Poisson geoadditive model, for instance, can be fitted to case count data on COVID-19 over time, which will generate some beautiful spatial maps without the need for any background disease as claimed. Response: We appreciate this comment, in particular about the Poisson geoadditive model. Depending on which R script is used, analysis with R may or may not require background levels to be input. We have removed the citation to R, as suggested by another reviewer. Comment #2. The relationship between FSA and PC is not clear in the manuscript. This may be confusing for some readers, especially those not familiar with Canada. More detail is required in this aspect by clearly mentioning the benefits of why both FSA and PC were chosen rather than either one of them. An illustrative graph showing the FSA and PC regions would be helpful. Response: To address the lack of familiarity on Canadian Forward Sortation Areas and Postal Codes, the sentence which introduces FSAs and PCs in the Introduction has been expanded. We also relate FSAs conceptually to U.S. zip codes: “distributed at the level of individual forward sortation areas (FSA) and postal codes (PCs; a smaller geographic segment within an FSA). Area-to-area analyses were performed on COVID-19 case data at the provincial level by FSA, a geographical unit similar to zip codes in the United States which can encompass hundreds of PCs.” We have also added the following to Table 1: map images illustrating the PC boundaries of the municipalities of interest, a general Ontario map indicating the locations of each of these regions, the total number of FSAs and PCs in each region, and their total area of each. COVID-19 hotspot communities were often identified within FSAs. Prioritization for COVID-19 vaccinations (when supply was initially limited) was informed using hotspots identified at this level of granularity (Ontario Ministry of Health: COVID-19: Guidance for Prioritization of Phase 2 Populations for COVID-19 Vaccination. 2021). For this reason, we evaluated COVID-19 hotspots at this level of resolution. However, since the distributions of COVID-19 infections was often non-uniform in many FSAs (as we describe), this level of granularity was insufficient to fully elucidate its local distributions, and analysis of PCs was necessary. This possibility is mentioned in the Introduction (second paragraph): “Available case data analyzed has been typically aggregated at the municipal or county level, however higher resolution spatial analyses has been limited as finer granularity for the distribution of COVID-19 cases has often been lacking.“ Subsequently, we generally describe FSAs and PCs. However, it was not obvious that PC-level COVID-19 case data produced a high level of geographic resolution that had been previously unavailable. We have therefore added the following at the end of this paragraph:: “Therefore, by evaluating COVID-19 case data at the PC level, we will be able to evaluate disease distributions at a high level of granularity.” Comment #3. It is difficult to understand the illustration in Figure 1. A mathematical notation/formula should be used to support the illustration, clearly defining all the parameters involved in the formula. Response: Formulation of the Getis-Ord local statistic is now presented in the third paragraph of the Introduction, with descriptions of each parameter within each equation, as requested.. We have also expanded the Figure 1 legend to describe how the weight function of these formulas differ depending on the spatial relationship being used. Weights of two features are equal in Fixed and K Nearest Neighbors, given that the two points are within a given distance metric (e.g. within 1km for Fixed, or is one of the K closest neighbors to the feature being evaluated for KNN; otherwise, wi,j = 0). The inverse distance spatial relationship, however, computes weight as the inverse Euclidean distance between two features being evaluated. This is calculated as wi,j = di,j-β where di,j is the Euclidean distance between two points and β is the inverse distance power variable (β = 1 in this study). This is now provided in the legend of Figure 1. Comment #4. The authors mention that \"the software can be easily modified to accommodate other Canadian provinces and, with additional effort, other countries.\" However, there is no guide or link to a description of how the developed tool could be used and probably extended to other provinces or countries. Response: We have added a section to the Geostatistical Epidemiology Toolbox user manual (in the Zenodo archive) which details the steps required for evaluation other Canadian Provinces or other countries. We have modified the original statement in the main manuscript to direct readers to the Geostatistical Epidemiology Toolbox user manual (which now contains a section on modifying the toolbox for other countries and Canadian provinces):“ While the toolbox was designed to evaluate COVID-19 case data in Ontario, the software can be easily modified to accommodate other Canadian provinces and, with additional effort, other countries (as described in the Geostatistical Epidemiology Toolbox user manual 29 ).” Using the toolbox to evaluate disease geostatistics in other Provinces is a relatively straightforward, requiring only alteration of a few lines of the main Python toolbox code (“GeostatisticalEpidemiologyToolbox_CytoGnomix.pyt”; see Toolbox guide sub-section “Evaluating Other Canadian Provinces” within the Zenodo archive file “Software.GeostatisticalEpidemiologyToolbox.zip”). Modifying the Toolbox to evaluate hotspots and interpolation in other countries would be more involved ( “Evaluating Other Countries” section of the manual). The structure of the shape files that define the regions equivalent to an FSA or a postal code in other countries will likely follow a different naming convention (for example, county subdivisions and zip codes in the United States). We now indicate in the Toolbox user manual which column names used by the Toolbox are most likely to require modification ( ‘PROV’ and ‘PRNAME’). Since it is not possible to generalize the structure of every shape file defining geographic elements of other countries, potential users should consider contacting us for assistance. Comment #5. More details are required for the multinomial logistic model considered. Explicit details such as the response variable and the corresponding covariates should be clearly stated. If possible, the regression model should include stratification variables as covariates, such as categorized age, and \"at-risk group\" for example. The conclusion drawn from such analysis can be discussed in the Discussion session. It is not clear whether the developed toolbox was used for the estimation of the multinomial regression model or the Directional Acyclic Graph Network. Response: Postal codes were identified as a high-case cluster (by Cluster and Outlier analysis) over a period of >3 consecutive days (i.e., PC “streaks”), and established which of these streaks occurred in two neighboring PCs in close succession. We noticed that the number of cases reported in each paired streak, the interval of time separating each streak, and the physical distance between the PCs might be related. To establish this, we derived multinomial logistic regression models based on these factors, in which the total number of cases within the paired streaks was defined as the response variable. The relationship between the number of cases between streaks of pairs of PCs in close proximity and the time separating the occurrence of those two streaks was significant. We now provide the R code used to derive these multinomial logistic regression models (“Streak_Analysis_using_Multinomial_Logistic_Regression_Models.Rmd”) as a new section within the Zenodo archive (“Software.Additional_Programs_for_Cluster_Outlier_Streak_Identification_and_Pairing.zip”). The paragraph describing the multinomial logistic regression model (third paragraph of the Results has been updated to reflect this change: “The distribution of and relationships between clustered PCs with persistent COVID-19 cases”). This section has been revised to describe the software used to derive the model (including the name of the script and a citation of the Zenodo archive), and explicitly states which of the three variables was used as the response variable: The input data are also included in the archive. The description now states: “To assess the significance of these results, a multinomial logistic regression model was derived in R (“Streak_Analysis_using_Multinomial_Logistic_Regression_Models.Rmd” which uses the multinom function of the nnet package; available in Zenodo archive 29 ), evaluating (1) the total number of cases in each pair of PCs over the course of both streaks (classified as either <25, between 25 and 49, or ≥50 cases; the response variable of the regression), (2) the duration … ” This analysis was not performed for stratified case data because it considerably decreases the number of high-case clusters detected per class (Table 1). This would result in far fewer and shorter PC “streaks”, and the lower statistical power would make analysis would less meaningful. The Geostatistical Epidemiology Toolbox was developed to perform and visualize geostatistical analyses through the ArcMap graphical user interface using ArcPy (which enables Python programs to access ArcGIS’s geoprocessing tools and extensions). The directional acyclic graph networks, as well as the regression, were performed outside of this environment (using MatLab and R, respectively). Furthermore, these techniques examined a subset of our results. Thus, the toolbox does not and can not perform either task." } ] } ]	1	https://f1000research.com/articles/10-1312
https://f1000research.com/articles/11-177/v1	14 Feb 22	{ "type": "Review", "title": "Framing and understanding the whole aspect of oral sex from social and health perspective: a narrative review", "authors": [ "Cennikon Pakpahan", "Darmadi Darmadi", "Agustinus Agustinus", "Andri Rezano", "Darmadi Darmadi", "Agustinus Agustinus", "Andri Rezano" ], "abstract": "Since thousands of years ago, oral sex has become part of sexual behavior among humans. Oral sex is considered taboo. Its taboo does not lie in the behavior, but its expression is deemed inappropriate. As technology becomes more sophisticated, human rights also stand out, leading to the disclosure of the practice in the 21st century. The oral sex that is discussed on a large scale in media encourages people to express it as feedback whether within right or not. It all depends on the value of each people. We found that this sexual behavior is found everywhere regardless of religion, culture, and race. Pop culture influences this behavior so much, it can be seen from music, movies, and television programs that provoke oral sex. Many motivations underlying this behavior include getting sexual pleasure for the sake of living well-being. But it is undeniable that this behavior is still controversial. It could be at risk of causing disease and, on the other hand, is reported to provide many benefits. According to our theory, oral sex is not a new behavior crossing boundaries. It is just an old behavior that surfaces because of the factors that support it. This behavior, which is still considered taboo, has its disadvantages such as sexually transmitted disease but has also benefits such as preventing preeclampsia.", "keywords": [ "oral sex", "sexual behaviour", "well-being", "pop culture", "sexually transmitted disease", "preeclampsia" ], "content": "Introduction\n\nOral sex is sexual activity with genital stimulation using the mouth, tongue, teeth, or throat. Currently, oral sex is frequent in both heterosexual and homosexual couples. Oral sex involves oral-vaginal contact (cunnilingus), oral-penile contact (fellatio), oral-anal contact (anilingus).1 Besides that, Keating also stated that breast biting or licking was included in oral sex behavior. Oral sex has become a part of sexual behavior in society regardless of age.2\n\nTwo types of oral sex widely accepted in society are “going down” activities, cunnilingus, and fellatio. The aim of the cunnilingus is stimulation of the clitoris. The cunnilingus can start with a kiss to the lower part of the stomach’s partner and then the thigh's side to the clitoris.3 Meanwhile, fellatio or sucking (blow job) is an activity the penis will be stimulated by licking by his partner. His partner will lick the shaft of the penis, even the testicles. In fellatio, men can ejaculate, ejaculation can be done outside, or sometimes the partner will swallow ejaculate. This action sometimes causes discomfort and not necessarily for everyone but tasting this ejaculate becomes advanced satisfaction for the “sucker” or “kisser”. Fellatio and cunnilingus can be done simultaneously, known as the “69” position.3,4 Moreover, it must be understood that ejaculate fluid still risks transmitting diseases. This should be considered and communicated to the partner when deciding this.\n\nOral sex can be considered an ancient activity from past manuscripts. As can be seen from the Hebrew, the Greeks to the Kamasutra manuals and the reliefs of several historical buildings depict this activity. Several moral, religious, medical, legal, and cultural factors influence the practice. Several cultures and religions give perceptive that oral sex is weird and unusual sexual behavior.4 But currently, the trend of oral sex has increased prominently. The development of technology and media also supports this.\n\nOral sex in this era is introduced in films and music videos, song lyrics, and literature. Several movies and music videos are not reluctantly labeled as hard-core and X-rated. Some scenes in the movie shown in public cinema presented men and women actively and even unstimulated in sexual positions, including oral sex.5 The Brown Bunny’s Vincent Gallo, 9 Songs’s Michael Winterboom, Nymphomaniac vol 1& 2's Lars von Trier, Love's Gaspar Noe and many more movies are movies that promote explicitly oral sex in a graphic scene in the history of cinema.6 Other than that in music, “Summer of 69” of Bryan Adams to the most recent Ariana Grande's song “34 + 35” are song which describes how oral sex activities are carried out by both men and women simultaneously with position 69.7,8\n\nThese television programs and films also play a role in encouraging premarital sex behavior and uncommitted.9 This trend is known as “hooking up”, this term refers to sex in an uncommitted and casual context. Oral sex is part of this “hooking up” trend.10,11 Hooking up is depicted through films such as “No strings attached”, “Friends with benefits”, etc., or cable television program such as “MTV's Jersey Shore”.12\n\nDespite sexual expression between partners, oral sex can also be defined as a form of sexual harassment and violence.2 Oral sex as a form of sexual violence can occur in heterosexuals and homosexuals. The rate of oral sex as an act of harassment varies widely. This suggests that investigations for sexual harassment do not have to focus on vaginal or anal genitals. However, tracing the oral organs is also necessary to confirm allegations of sexual misconduct. Evidence, for example, can be done by detecting sperm or seminal plasma in the victim's mouth in cases of fellatio or by performing penis swabs in cases of cunnilingus.13\n\n\nPrevalence of oral sex\n\nWylie conducted an extensive survey on 26,032 participants aged > 16 years in 26 countries from the Americas, Europe, Asia, and Australia. As many as 38% of the participants engaged in oral sex as a sexual activity. Oral sex has a very high prevalence among all sex orientation groups.14 Meanwhile, data by Richters et al. reported 19,307 Australians aged 16 to 59 found 32% of the respondents had oral sex from their last sexual history.15 According to D'souza et al., there are differences in oral sex behavior compared to gender, age, and race. Oral sex behavior exists in married couples or adults and adolescents, and young adults.16 In a report from the Child Trends Data Bank in 2015, adolescents aged 15-19 years, both boys and girls, reported having oral sex as much as 39% and 38%. Women said giving more oral sex than men.17\n\nIn developing countries in Africa, such as Nigeria, it is reported that the influence of the media and the Internet affects a person's sexual attitudes and behavior. Out of 400 respondents, 352 people had oral sex. Some of them learned this behavior from the internet.18 In Addis Ababa, Ethiopia, a study reported oral sex among high school adolescents in 3840. Adolescents who had practiced oral sex is 5.4% (190) person. Oral sex is closely related to the concept of best friends (AOR = 5.7; 95% CI 3.6-11.2) and having illiterate mothers (AOR = 11.5; 95% CI 6.4-18.5).19 Besides that, oral sex behavior is one of the activities carried out and offered by sex workers. In some countries in Asia, the percentage of women who engage in oral sex varies 5% in Indonesia,20 16% in Thailand,21 and 18% in India.22\n\n\nPerspectives and motives in oral sex\n\nIn adolescents and young adults, NBC (2005) reports that 40-47% of young people who do oral sex do not need to worry about pregnancy, meet the right person, and feel the sense for the first time. Other reasons, many couples in serious relationships want to experience sexual pleasure but are not pregnant,23 experience sex without using a condom,23-26 maintain virginity,24,26 answer curiosity about sexual activities,24 then believed that oral sex has a low risk of STD transmission.23-26\n\nIn teenagers, having oral sex is related to increased popularity,27 improvement of relationships between teenagers,24,25 engaging in sexual activity without commitment,23 assumption that oral sex is not sex,23 and also sex with someone is a generous behavior.27 The same perspectives and motivations were also found in married couples. Holway and Tillman reported on the timing of oral sex in marriage among young adult couples. Their report stated that women who were late or never performed oral sex reported being more satisfied with their relationships with their partners. The fundamental reason is they do not feel forced when having sexual intercourse and do not need to worry about the transmission of disease due to sexual relations.28\n\nMeanwhile, oral sex is behavior that risks transmitting various diseases. Teens and young adults even claim oral sex is less risky and more acceptable than vaginal sex. Sometimes they perform oral sex because they do not want contraception and protection while having sex.29 This fact shows the need for health workers and counsellors who provide the correct perspective in education or sex counselling.28,29\n\nPenhollow et al. also conducted a study on 408 students. They asked students' involvement in religious activities, frequency of worship attendance, their feelings about religion, their perception of God in sex and then looked at their participation in several sexual activities such as oral sex.30 Results indicated that religiosity variables, mainly frequency of religious attendance and religious feelings, were significant predictors of sexual behavior such as oral sex.18 The religious factor was reported as one of the reasons a person does not engage in oral.16 Apart from that, another influencing factor in higher education.28\n\n\nAttitudes in oral sex\n\nAttitudes towards oral sex tend to vary in population. The study surveyed 8600 people aged 16-64 years regarding their sexual activity. The analysis results stated that oral sex is one of the mandatory activities in sex activities besides kissing, cuddling, and vaginal intercourse. About 74% of their respondents reported that women want stimulation over their genitals orally, and 70% stimulate their partners' genitals orally.31 This proves that genital mouth stimulation is widespread in married couples.32\n\nAnother study on young couples reported that every young couple had at least one oral sex session a year.28 If oral sex is practiced mainly by women, even sometimes ingesting ejaculate to prevent pregnancy.28,33 men are reported to prefer oral sex and partners who engage in oral sex.34 However, there is no gender difference in oral sex.35 For several couples, oral sex is an indicator of the satisfaction of sexual life.36\n\nOne study reported 368 women in the 45-59 years age group (19.5%), 60-74 years (2.2%) and 75 (over 0.8%) had at least one oral sex in a week.37 Whereas in 341 men surveyed, the age group 45-59 years (20.1%), 60-74 years (6.5%), and 75 years (8.8%) perform oral sex at least once a week.37\n\nMen at risk for adultery are more likely to engage in oral sex.38 Oral sex can be used to detect infidelity, material retention behavior, and orgasm with sperm retention. Oral sex, which is used as s detector for adultery, is indicated, for example, in cunnilingus activity; one study states that men are still likely to feel and smell their rival's semen around the vagina related to their previous sexual activity.39\n\nMany studies have reported that couples during oral sex mostly do not use condoms. However, Auslender et al. reported different results. The results were all in young adults when oral sex took protective measures to reduce the process of transmitting diseases such as Herpes simplex such as microbicide surrogate products.40\n\nIn 2015, a study enrolled 346 men and women regarding their expressions and attitudes towards oral sex, either receiving or doing for the first time. They address various expressions: happy, fearful, indifferent, strange, disgusted, surprised, relieved, proud, and sad. The most common expression for oral sex recipients was feeling happy (38.7%). Interestingly, 10.8% thought this behavior was disgusting, and 8.2% thought this was strange. In another case who did oral sex, dominant among them felt fearful as much as 17.1%, 15.8% felt indifferent, 2.8% felt disgusted, and only 12% felt happy doing it.41 Others reported on a focus group discussion study involving women with experiences of fellatio and cunnilingus. They stated a feeling of good emotional vulnerability when engaging in oral sex on their partners.42\n\nDuring oral sex, the aim is to orgasm for the partner. Richerts et al. (2006) conducted a study on a large population. 50% of women experience orgasm during vaginal intercourse, but when intercourse is added with cunnilingus activity, 73% will experience orgasm. Oral sex strengthens the increased incidence of orgasm in partners, especially in women.15\n\n\nOral sex risk\n\nMany reports have stated that oral sex can be local infections, rather a cunnilingus, fellatio, or anilingus. Pathogens that are often transmitted through oral sex are viruses (Herpes simplex viruses, Hepatitis virus, Human papillomaviruses, and less frequently HIV) and bacteria (mainly syphilis, gonorrhea, group B Streptococcus).43,44 In addition, infections such as Molluscum contagiousum, Candidiasis, Epstein Barr virus, and Aspergillosis can also be spread through the process of oral sex.45\n\nGonorrhea infection is possible in oral sex. Sex workers with inconsistent condom use for oral sex were reported 17.1 times more likely infected (95% CI: 8.0 ± 36.5) than consistent condom users to develop pharyngeal gonorrhea.46 HSV-1 is transmitted through genital and oral contact. This lesion is one of the most prevalent lesions among women, even young.47,48 HSV-1 is more likely to spread to the female genital organs than male genital organs.49 For young people, acquiring a lifelong recurrent infection such as genital herpes is not only an unfortunate surprise diagnosis, it can also invoke anxiety, guilt, and social-sexual isolation.50,51\n\nUnusual infections have also been reported after oral sex. The incidence of pharyngitis with Trichomoniasis vaginalis was reported in men who routinely had oral sex with their partner who had vaginal Trichomoniasis.52 So far, it is infrequent for Trichomoniasis to spread by mouth and cause a local infection. In addition, parasites such as Toxoplasma gondii is found in ejaculate fluid, possibly spread through oral sex.53,54 There may be a positive association or association between Toxoplasma transmission and oral sex behavior, especially fellatio. However, this condition depends on the activity of fellatio, whether it will be sperm swallowed or not.\n\nA severe infection has been reported by Froissart et al. They reported two cases of severe infection that occurred through oral sex activity. The first case complained of fever, pubic erythema, penile edema, and cellulitis and the second case complained of genital bubo, foreskin edema, fever, glans erosion, and cellulitis. Both of these cases occurred after performing fellatio activities with their sex partners. In this case, the suspicion of the transmission process was an abrasion of the penis during traumatic oral sex. Cellulitis of the pubis is an infrequent case. The trauma of the genital organs due to the bite of the partner is presumed as a port de entry.43\n\nSevere soft tissue infections such as Fournier's gangrene were also reported by Lutz and Gerber (2020) through oral sex with commercial sex workers. This male patient experienced swelling and sloughing of the skin of his penis after reportedly engaging in oral sex. During intercourse, his partner nicked the shaft of the penis using her teeth.55 Takenouchi et al. also reported a rare infection, Lemierre syndrome, in a 58-year-old man after oral sex with a sexual partner two days previously.56 Lemierre syndrome is characterized by thrombophlebitis of the internal jugular veins and bacteremia caused by anaerobic organisms following a recent oropharyngeal infection.57\n\nCunnilingus should be avoided in pregnant women. Hosseini and Hunt reported a case of Streptococcus mitis Chorioamnionitis in a 43-year-old pregnant woman who had oral sex with his partner. This infection occurred ten days before contractions after dental scaling and oral sex.58 The same case was also reported by Gherman et al. in Australia that infected by Streptococcus viridans after cunnilingus.59 Both Streptococcus mitis and Streptococcus viridans are normal flora in the oral cavity.\n\nWHO's guidelines for adolescent sexual and reproductive health and rights in 2018 recommends giving antibiotic prophylaxis to children who experience sexual abuse with the suspicion of one of which is oral sex, WHO considers that oral sex by unknown offender has a significant risk of sexual transmitted disease.60 According to Barbara et al., oral sex was the riskiest behavior than vaginal and anal sex. Cunnilingus has an OR of 2.199 and fellatio of an OR of 2.756 to have infected. This study reported that people who performed oral activities have higher risks associated with STD/HIV transmission than those not.61\n\nOther serious risks that arise due to oral sex behavior include human papillomavirus infection, which causes oral squamous papilloma, oral verruca vulgaris, condyloma acuminata, focal epithelial hyperplasia, epidermoid carcinoma, and oropharyngeal squamous cell carcinoma.62–64 One study from Indonesia proves a strong correlation between the activity of oral and anal among homosexuals and HPV infection (OR 6.854).65 According to Brown et al., women who had more than three times oral sex with their partners in the previous month had a higher risk of developing oral HPV than those who had less.66\n\n\nBenefits obtained due to oral sex\n\nMeuleman et al. reported that oral sex might be a protective factor in recurrent miscarriage cases. This study was conducted on 97 women who experienced unexplained consecutive miscarriages. Recurrent miscarriage cases occur due to an imbalance of immunity in the embryo's implantation into the endometrium.67 Koelman et al. stated that exposure to oral sex could reduce the incidence of preeclampsia.33\n\nPittrof et al. performed a study on 619 women engaged in oral sex. They have a lower risk of developing endometriosis and pelvic inflammatory disease than their counterparts. The assumption that oral sex can be a protective factor is that endometriosis and PID require adaptive immunity in the lymphoid system.68 Meanwhile, the oropharynx is a channel that is rich in lymph channels, thereby facilitating the stimulation of adaptive immunity. Primed lymphocytes in the nasopharyngeal tract will be found later in the endocervix.69 In addition, it is possible to induce genital T-cells and B-cells through sub-lingual immunization.70\n\nTestosterone also affects the libido of women. Testosterone in semen can logically affect the libido of the sexual partner. Women who did not use condoms at the time of intercourse had more sexual intercourse than women who did.71 But there are no specific reports in the case of women who swallowed semen. Semen also had an antidepressant effect, such as serotonin. It has been reported that women whose partners used a condom during intercourse were more likely to be depressed than those who did not use it.71\n\nSome interesting substances are opioids such as endorphin, enkephalin, and other cytokines also present in semen. These substances affect sperm motility, such as endorphins and calcitonin.72 Endorphin and enkhapalines function to reduce anxiety and induce analgesia and drowsiness.73 Likewise, with oxytocin, oxytocin is a hormone that plays a role in increasing bonding and intimacy in partners. This hormone impacts penile erection and female orgasm.74 However, in the case of semen ingestion, the activity levels of these substances will be significantly reduced in the blood due to the absorption, distribution, and metabolism processes.\n\nBesides that, several benefits are felt during oral sex, such as satisfaction in intercourse and emotional or pleasure in intercourse. A study on 410 women who had oral sex showed that their male partners delay orgasm so that the intercourse time is longer.75 Oral sex is a positive activity that provides sexual satisfaction and relationships.76,77\n\nAnother benefit of oral sex is sperm retention by male partners.78 Cunnilingus is considered one of the activities that help women experience orgasm.15 Reports show that oral sex helps sexual activity last longer than usual.79 Another study reported that 233 men who had oral sex with their partners would spend more time having sex with them, doing more copulatory behavior that replaced semen, and reported greater sexual arousal.38 Men engaging in oral sex with their partners as part of strategy provide a more comprehensive range of benefits. Men who are higher in consideration are more likely to benefit their partner.79\n\n\nConclusion\n\nOral sex is currently independent of age and gender. In adolescents and young adults, the reason for having oral sex is wanting to feel sexual pleasure but not getting pregnant or losing your virginity, doing intercourse without contraception, and having minimal risk of STD. In addition, there is also a reason for “friends with benefits” and popularity among peers. In late adulthood, oral sex is reported to be one of the mandatory activities besides kissing, cuddling, and vaginal intercourse. Oral sex is also one activity that supports orgasm in a married couple. The expressions felt by those who had oral sex varied from feeling happy, afraid, and feeling strange. Oral sex is also reported to be one way to detect cheating in a relationship. One of the risks posed by oral sex is infection. Some have said the benefits of oral sex include increased immunity and a reduced risk of recurrent bleeding and preeclampsia.\n\n\nData availability\n\nNo data are associated with this article.", "appendix": "References\n\nSaini R, Saini S, Sharma S: Oral sex, oral health and orogenital infections. J Glob Infect Dis. 2010; 2(1): 57–62. PubMed Abstract \| Publisher Full Text\n\nKeating SM: Oral sex—a review of its prevalence and proof. J Forensic Sci Soc. 1988; 28(5–6): 341–355. PubMed Abstract \| Publisher Full Text\n\nHyde JS, Delamater JD: Understanding Human Sexuality. 13th ed.Odoardi E, editor. New York: 2017; 214–215 p.\n\nFry MJ, Cochran JJ, Ohlmann JW, Anderson DR: 2019 Cengage Learning. WCN 02-200-203.2019; 249–251 p.\n\nFilmsite: Sex in Cinema: Pre-1920s Greatest and Most Influential Erotic/Sexual Films and Scenes.2020. Reference Source\n\nRanker: 15 Movies Where the Actors Really Had Sex.2021. Reference Source\n\nTimeout: Out T. Top 25 oral sex songs.2014. Reference Source\n\nBurgos J: Ariana Grande’34+35′ Lyrics Meaning: Doja Cat, Megan Thee Stallion\|StyleCaster.Reference Source\n\nKunkel D, Eyal K, Finnerty K, et al.: Sex on TV 4: A Kaiser Family Foundation Report. Sex TV 4 A Bienn Rep to Kaiser Fam Found.2005; 81. Reference Source\n\nGarcia JR, Reiber C, Merriwether AM: Sexual Hookup Culture: A Review. Rev. Gen. Psychol. 2013; 16(2): 161–176.\n\nKuperberg A, Padgett JE: Dating and hooking up in college: Meeting contexts, sex, and variation by gender, partner’s gender, and class standing. J Sex Res. 2015; 52(5): 517–531. PubMed Abstract \| Publisher Full Text\n\nAubrey JS, Smith SE: The Impact of Exposure to Sexually Oriented Media on the Endorsement of Hookup Culture: A Panel Study of First-Year College Students. Mass Commun. Soc. 2016; 19(1): 74–101. Publisher Full Text\n\nKeating SM, Higgs DF: Oral sex—further information from sexual assault cases. J Forensic Sci Soc. 1992; 32(4): 327–331. PubMed Abstract \| Publisher Full Text\n\nWylie K: A Global Survey of Sexual Behaviours. J Fam Reprod Heal. 2009; 3(2): 39–49.\n\nRichters J, De Visser R, Rissel C, et al.: Sexual practices at last heterosexual encounter and occurrence of orgasm in a national survey. J Sex Res. 2006; 43(3): 217–226. Publisher Full Text\n\nD’Souza G, Cullen K, Bowie J, et al.: Differences in oral sexual behaviors by gender, age, and race explain observed differences in prevalence of oral human papillomavirus infection. PLoS One. 2014; 9(1): 19–21. Publisher Full Text\n\nChild Trends: Oral Sex Behaviors among Teens.2013; (December). Reference Source\n\nAsekun-Olarinmoye E, Asekun-Olarinmoye OS, Adebimpe W, et al.: Effect of mass media and Internet on sexual behavior of undergraduates in Osogbo metropolis, Southwestern Nigeria. Adolesc Health Med Ther. 2014; 15. Publisher Full Text\n\nCherie A, Berhane Y: Oral and anal sex practices among high school youth in Addis Ababa, Ethiopia. BMC Public Health. 2012; 12(1): 5. PubMed Abstract \| Publisher Full Text Reference Source\n\nFajans P, Ford K, Wirawan DN: STD knowledge and behaviours among clients of female sex workers in Bali, Indonesia. AIDS Care. 1994; 6(4): 459–475. PubMed Abstract \| Publisher Full Text\n\nSwaddiwudhipong W, Nguntra P, Chaovakiratipong C, et al.: Effect of health education and condom promotion on behavioral change among low socioeconomic prostitutes in Mae Sot, Tak, Thailand. Southeast Asian J Trop Med Public Health. 1990 Sep; 21(3): 453–457. PubMed Abstract\n\nBhave G, Lindan CP, Hudes ES, et al.: Impact of an intervention on HIV, sexually transmitted diseases, and condom use among sex workers in Bombay, India. AIDS. 1995 Jul; 9(Suppl 1): S21–S30.\n\nDotson-Blake KP, Knox D, Zusman ME: Exploring Social Sexual Scripts Related to Oral Sex: A Profile of College Student Perceptions. Prof Couns. 2012; 2(1): 1–11. Publisher Full Text\n\nCornell JL, Halpern-Felsher BL: Adolescents tell us why teens have oral sex. J Adolesc Health. 2006; 38(3): 299–301. PubMed Abstract \| Publisher Full Text\n\nGoldstein R, Halpern-Felsher B: Adolescent Oral Sex and Condom Use: How Much Should We Worry and What Can We Do?. J Adolesc Health. 2018; 62(4): 363–364. PubMed Abstract \| Publisher Full Text\n\nBrewster KL, Tillman KH: Who’s Doing It? Patterns and Predictors of Youths’ Oral Sexual Experiences. J Adolesc Health. 2008; 42(1): 73–80. PubMed Abstract \| Publisher Full Text\n\nPrinstein MJ, Meade CS, Cohen GL: Adolescent oral sex, peer popularity, and perceptions of best friends’ sexual behavior. J Pediatr Psychol. 2003; 28(4): 243–249. PubMed Abstract \| Publisher Full Text\n\nHolway GV, Tillman KH: Timing of Sexual Initiation and Relationship Satisfaction in Young Adult Marital and Cohabiting Unions. J Fam Issues. 2017; 38(12): 1675–1700. PubMed Abstract \| Publisher Full Text\n\nHalpern-Felsher BL, Cornell JL, Kropp RY, et al.: Oral versus vaginal sex among adolescents: Perceptions, attitudes, and behavior. Pediatrics. 2005; 115(4): 845–851. PubMed Abstract \| Publisher Full Text\n\nPenhollow T, Young M, Denny G: The impact of religiosity on the sexual behaviors of college students. Am J Heal Educ. 2005; 36(2): 75–85. Publisher Full Text\n\nSmith AMA, Patrick K, Heywood W, et al.: Sexual practices and the duration of last heterosexual encounter: Findings from the Australian longitudinal study of health and relationships. J Sex Res. 2012; 49(5): 487–494. PubMed Abstract \| Publisher Full Text\n\nCherlin AJ, Laumann EO, Gagnon JH, et al.: Social Organization and Sexual ChoicesThe Social Organization of Sexuality: Sexual Practices in the United States. Contemp. Sociol. 1995; 24: 293. Publisher Full Text\n\nKoelman CA, Coumans ABC, Nijman HW, et al.: Correlation between oral sex and a low incidence of preeclampsia: A role for soluble HLA in seminal fluid?. J Reprod Immunol. 2000; 46(2): 155–166. PubMed Abstract \| Publisher Full Text\n\nVannier SA, Byers ES: A qualitative study of university students’ perceptions of oral sex, intercourse, and intimacy. Arch Sex Behav. 2013; 42(8): 1573–1581. PubMed Abstract \| Publisher Full Text\n\nTolman DL, Mcclelland SI: Normative sexuality development in adolescence: A decade in review, 2000-2009. J Res Adolesc. 2011; 21(1): 242–255. Publisher Full Text\n\nSanttila P, Wager I, Witting K, et al.: Discrepancies between sexual desire and sexual activity: Gender differences and associations with relationship satisfaction. J Sex Marital Ther. 2008; 34(1): 31–44. PubMed Abstract \| Publisher Full Text\n\nOffice AM: AARP/Modern Maturity Sexuality Study.1999.\n\nPham MN, Shackelford TK, Sela Y: Women’s oral sex behaviors and risk of partner infidelity. Pers Individ Dif. 2013; 55(4): 446–449. Publisher Full Text\n\nShackelford TK, Pound N: Sperm competition in humans: Classic and contemporary readings. Sperm Competition in Humans: Classic and Contemporary Readings. 2006: 1–283. Publisher Full Text\n\nAuslander BA, Catallozzi M, Davis G, et al.: Adolescents’ and young women’s use of a microbicide surrogate product when receiving oral sex. J Pediatr Adolesc Gynecol. 2014; 27(1): 37–40. PubMed Abstract \| Publisher Full Text\n\nVasilenko SA, Maas MK, Lefkowitz ES: “It Felt Good but Weird at the Same Time”: Emerging Adults’ First Experiences of Six Different Sexual Behaviors. J Adolesc Res. 2015; 30(5): 586–606. PubMed Abstract \| Publisher Full Text\n\nSovetkina E, Weiss M, Verplanken B: Perception of vulnerability in young females’ experiences of oral sex: Findings from the focus group discussions. Cogent Psychol. 2017; 4(1): 1–18. Publisher Full Text\n\nFroissart A, Martinez V, Jaureguiberry S, et al.: Local infections after oral sex. Med Mal Infect. 2011; 41(3): 152–153. Publisher Full Text\n\nCherpes TL, Melan MA, Kant JA, et al.: Genital tract shedding of herpes simplex virus type 2 in women: Effects of hormonal contraception, bacterial vaginosis, and vaginal group B Streptococcus colonization. Clin Infect Dis. 2005; 40(10): 1422–1428. PubMed Abstract \| Publisher Full Text\n\nRan Y, Lu Y, Cao L, et al.: Primary laryngeal aspergillosis related to oral sex? A case report and review of the literature. Med Mycol Case Rep. 2013; 2(1): 1–3. PubMed Abstract \| Publisher Full Text\n\nWong ML, Chan RKW: A prospective study of pharyngeal gonorrhoea and inconsistent condom use for oral sex among female brothel-based sex workers in Singapore. Int J STD AIDS. 1999; 10(9): 595–599. PubMed Abstract \| Publisher Full Text\n\nHorowitz R, Aierstuck S, Williams EA, et al.: Herpes simplex virus infection in a university health population: Clinical manifestations, epidemiology, and implications. J Am Coll Heal. 2010; 59(2): 69–74. PubMed Abstract \| Publisher Full Text\n\nPeña KC, Adelson ME, Mordechai E, et al.: Genital herpes simplex virus type 1 in women: Detection in cervicovaginal specimens from gynecological practices in the United States. J Clin Microbiol. 2010; 48(1): 150–153. PubMed Abstract \| Publisher Full Text\n\nGray E, Morgan J, Lindeman J. Herpes simplex type 1 versus Herpes simplex type 2 in anogenital herpes; a 10 year study from the Waikato region of New Zealand Erana. 2008; 121(1271): 43–50. Reference Source\n\nAzwa A, Barton SE: Aspects of herpes simplex virus: A clinical review. J Fam Plan Reprod Heal Care. 2009; 35(4): 237–242. Publisher Full Text\n\nHendry K: Oral Sex and HSV-1 Knowledge Among College Freshmen Females.2017.\n\nCarter-Wicker K, Utuama O, Omole F: Can trichomoniasis cause pharyngitis? A case report. SAGE Open Med Case Reports. 2016; 4: 2050313X1668213. PubMed Abstract \| Publisher Full Text\n\nDass SAH, Vasudevan A, Dutta D, et al.: Protozoan parasite Toxoplasma gondii manipulates mate choice in rats by enhancing attractiveness of males. PLoS One. 2011; 6(11): 1–6. Publisher Full Text\n\nKaňková, Hlaváčová J, Flegr J: Oral sex: A new, and possibly the most dangerous, route of toxoplasmosis transmission. Med. Hypotheses. 2020; 141(March): 109725. PubMed Abstract \| Publisher Full Text\n\nLutz S, Gerber D: Oral-Sex-Associated Fournier’S Gangrene Following Contact With Commercial Sex Worker. Chest. 2020; 158(4): A868. Publisher Full Text\n\nTakenouchi S, Kunieda T, Yamada R, et al.: Lemierre syndrome caused by oral sex. J Formos Med Assoc. 2014; 113(10): 762–763. PubMed Abstract \| Publisher Full Text\n\nEilbert W, Singla N: Lemierre’s syndrome. Int J Emerg Med. 2013; 6(1): 1.\n\nHosseini BS, Hunt J: Streptococcus mitis Chorioamnionitis after Dental Scaling and Oral Sex. Case Rep Obstet Gynecol. 2020; 2020: 1–3. PubMed Abstract \| Publisher Full Text\n\nGherman RB, Browning J, Tramont J, et al.: Streptococcus viridans intra-amniotic infection associated with antecedent cunnilingus. Aust New Zeal J Obstet Gynaecol. 1999; 39(2): 257–260. PubMed Abstract \| Publisher Full Text\n\nOMS: WHO recommendations on adolescent sexual and reproductive health and rights.2018; 1–88 p. Reference Source\n\nSanta-Bárbara RC, Hueso-Montoro C, Martín-Salvador A, et al.: Association between sexual habits and sexually transmitted infections at a specialised centre in granada (Spain). Int J Environ Res Public Health. 2020; 17(18): 1–9.\n\nRosenquist SE: Is Oral Sex Really a Dangerous Carcinogen? Let’s Take a Closer Look. J. Sex. Med. 2012; 9(9): 2224–2232. PubMed Abstract \| Publisher Full Text\n\nFernández-López C, Morales-Angulo C: Otorhinolaryngology Manifestations Secondary to Oral Sex. Acta Otorrinolaringol (English Ed.). 2017; 68(3): 169–180. PubMed Abstract \| Publisher Full Text\n\nShah A, Malik A, Garg A, et al.: Oral sex and human papilloma virus-related head and neck squamous cell cancer: A review of the literature. Postgrad Med J. 2017; 93(1105): 704–709. PubMed Abstract \| Publisher Full Text\n\nGofur ARP, Bramantoro T, Palupi R: Identification of sexual behavior in community at risk of oral human papillomavirus infection. Syst Rev Pharm. 2020; 11(6): 543–549.\n\nBrown B, Blas MM, Cabral A, et al.: Oral sex practices, oral human papillomavirus and correlations between oral and cervical human papillomavirus prevalence among female sex workers in Lima, Peru. Int J STD AIDS. 2011; 22(11): 655–658. PubMed Abstract \| Publisher Full Text\n\nMeuleman T, Baden N, Haasnoot GW, et al.: Oral sex is associated with reduced incidence of recurrent miscarriage. J Reprod Immunol. 2019; 133(July 2018): 1–6. PubMed Abstract \| Publisher Full Text\n\nPittrof R, Sully E, Bass DC, et al.: Stimulating an immune response? Oral sex is associated with less endometritis. Int J STD AIDS. 2012; 23(11): 775–780. PubMed Abstract \| Publisher Full Text\n\nJohansen FE, Baekkevold ES, Carlsen HS, et al.: Regional induction of adhesion molecules and chemokine receptors explains disparate homing of human B cells to systemic and mucosal effector sites: Dispersion from tonsils. Blood. 2005; 106(2): 593–600. PubMed Abstract \| Publisher Full Text\n\nÇuburu N, Kweon M-N, Hervouet C, et al.: Sublingual Immunization with Nonreplicating Antigens Induces Antibody-Forming Cells and Cytotoxic T Cells in the Female Genital Tract Mucosa and Protects against Genital Papillomavirus Infection. J Immunol. 2009; 183(12): 7851–7859. PubMed Abstract \| Publisher Full Text\n\nGallup GG, Burch RL, Platek SM: Does semen have antidepressant properties?. Arch Sex Behav. 2002; 31(3): 289–293. Publisher Full Text\n\nMungan NA, Mungan G, Basar MM, et al.: Effect of seminal plasma calcitonin levels on sperm motility. Arch Androl. 2001; 47(2): 113–117. PubMed Abstract \| Publisher Full Text\n\nGrossman A, Clement-Jones V: 3 Opiate receptors: Enkephalins and endorphins. Clin Endocrinol Metab. 1983; 12(1): 31–56. Publisher Full Text\n\nTurner RA, Altemus M, Enos T, et al.: Preliminary Research on Plasma Oxytocin in Normal Cycling Women: Investigating Emotion and Interpersonal Distress. Psychiatry. 1999; 62(2): 97–113. PubMed Abstract \| Publisher Full Text\n\nSela Y, Shackelford TK, Pham MN, et al.: Do women perform fellatio as a mate retention behavior?. Pers Individ Dif. 2014; 73: 61–66. Publisher Full Text\n\nBrody S, Costa RM: Satisfaction (sexual, life, relationship, and mental health) Is associated directly with penile-vaginal intercourse, but inversely with other sexual behavior frequencies. J Sex Med. 2009; 6(7): 1947–1954. PubMed Abstract \| Publisher Full Text\n\nBrody S: The relative health benefits of different sexual activities. J Sex Med. 2010; 7(4 PART 1): 1336–1361. Publisher Full Text\n\nPham MN, Shackelford TK, Sela Y, et al.: Is cunnilingus-assisted orgasm a male sperm-retention strategy?. Evol Psychol. 2013; 11(2): 405–414. PubMed Abstract\n\nPham MN, Shackelford TK, Holden CJ, et al.: Men’s Benefit-Provisioning Mate Retention Behavior Mediates the Relationship Between Their Agreeableness and Their Oral Sex Behaviors. Arch Sex Behav. 2015; 44(6): 1723–1728. PubMed Abstract \| Publisher Full Text" }	[ { "id": "123285", "date": "15 Feb 2022", "name": "Thi Tu An Nguyen", "expertise": [ "Reviewer Expertise sexual and reproductive health", "disability", "applied health", "sociology", "anthropology", "family and gender." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nFirst, I would like to take this opportunity to say thank you for giving me this chance to review this interesting topic.\nIn my opinion, I would like to say thank you to the authors who spent time writing this article. However, this is not a review paper, because:\nThere is no rationale for this paper. Why did you do this review? What contexts are you looking for? Are you looking for this in a certain country or globally? Method: what databases did you search for these papers? Time frame? Countries? Etc? The topic of the review is not discussed comprehensively in the context. To me, this paper is very descriptive. It needs more critical thinking. The conclusion is so simple. The authors should restate their aims/objectives and future directions or implications (if needed).\n\nI think this paper should be revised a lot before it can be published. My recommendations are below:\nIntroduction:\nThe authors need to clarify: Why are you doing this review? What are your aims/objectives? Defining oral sex and pop culture\nParagraph No3 (from the top) - page 3/9: The last sentence needs references. Paragraph No4 (from the top) - page 3/9: The first sentence needs references.\nPrevalence of oral sex\nI suggest this headline should be The prevalence of oral sex of some countries around the world. This section is so descriptive. You should say some things such as what is your thinking of these oral sex rates?\nPerspectives and motives in oral sex\nYou should add on the countries where these studies were conducted. Again, what do you think about these studies influencing your aims?\nAttitudes in oral sex\nAgain, which nationalities of these participants in these studies? Paragraphs No 2&3 should be deleted because they are irrelevant to this section.\nOral sex risk\nThis section is good.\nBenefits obtained due to oral sex\nI suggest this headline should be “oral sex benefits”. Again, which nationalities of these participants in these studies?\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? Partly", "responses": [ { "c_id": "7880", "date": "28 Feb 2022", "name": "Cennikon Pakpahan", "role": "Author Response", "response": "We are very grateful for the excellent feedback from reviewers. We have considered it and revised it according to your suggestions in our latest version. We are waiting for a good response from you." } ] } ]	1	https://f1000research.com/articles/11-177
https://f1000research.com/articles/11-808/v1	20 Jul 22	{ "type": "Study Protocol", "title": "Definition of ‘close contacts’ in leprosy studies: protocol for a scoping review", "authors": [ "Maya Ronse", "Claudia Nieto-Sanchez", "Sien De Coninck", "Kristien Verdonck", "Koen Peeters Grietens", "Maya Ronse", "Sien De Coninck", "Kristien Verdonck", "Koen Peeters Grietens" ], "abstract": "Despite difficulties to document transmission pathways (assumed to be airborne), increased risk of leprosy infection has been shown for individuals living in close contact with patients. However, variations in the concept of ‘close contacts’ are used in different settings and studies. We conduct this review to identify criteria of space (location, geographical variables, distance, indoor vs outdoor), time (including frequency and duration), physical exposure (skin to skin, sexual), and relationship (familial, occupational, social) involved in the definition of ‘close contacts’ in leprosy studies. We expect this review to provide an overview of the (lack of) conceptualization of this term and its variations across settings. Primary studies and reviews are eligible for inclusion in this review. The main source of records will be the PubMed interface. Secondary searches will be conducted in Google Scholar, as well as through the reference lists of selected publications. The search strategy is based on the combination of the condition of interest (leprosy) and the concept under study (‘contact’). The findings of this review will be presented using thematic narrative synthesis, tables, and figures. The protocol is written in line with the Prisma Extension for Scoping reviews (PRISMA-ScR).", "keywords": [ "Leprosy", "close contacts", "scoping review." ], "content": "Introduction\n\nDespite difficulties to document transmission pathways (assumed to be airborne), increased risk of leprosy infection has been shown for individuals living in close contact with patients. The World Health Organisation (WHO) defines close contact as “a person having close proximity to a leprosy patient for a prolonged duration. Such persons are considered ‘exposed’ to leprosy and may or may not have been infected. ‘Prolonged duration’ is typically defined as having been in contact with an untreated patient for 20 hours per week for at least three months in a year, e.g. family members, neighbours, friends, school children in same class; co-workers in same office, etc”.1 However, variations of this definition are used in different settings and studies.\n\nClustering of leprosy cases within households (often referred to as ‘household contacts’) has been documented,2–4 as well as occurrence of new cases at close geographical distance from previous leprosy cases.5 People living in the same household or at close distance are frequently linked through either social activities or networks,6 raising the question whether the “distance” someone lives from an index case determines the risk of infection or whether it acts as a proxy for other explanatory variables that are more directly associated with leprosy risk, such as types and conditions of close human contacts.7,8 Similar to other infectious diseases,9 duration of contact has also been considered a criterion to determine risk of exposure.\n\nWe conduct this review to identify criteria of space (location, geographical variables, distance, indoor vs outdoor), time (including frequency and duration), physical exposure (skin to skin, sexual), and relationship (familial, occupational, social) involved in the definition of ‘close contacts’ in the context of risk of leprosy. We expect this review to provide an overview of the conceptualization of this term and its variations across settings.\n\nThis review is part of the study “Improving leprosy prevention strategies by integrating social network analysis with spatial and molecular epidemiology data of Mycobacterium leprae in the Comoros”, supported by ITM’s Structural Research Funding, and funded by the Flemish Ministry of Economy, Sciences and Innovation (EWI).\n\nThe central goal of this review is to identify definitions of ‘close contacts’ used in the description of risk for leprosy transmission, as well as specific criteria of space, time, physical exposure, and relationship employed in these definitions.\n\n\nMethods\n\nRecords will be included in the review if they meet all the following criteria:\n\n• Reports of primary studies or review articles (not opinion papers); and\n\n• Using the word ‘contact’ in relation to risk of leprosy, and\n\n• Including a definition of ‘contact’ in relation to risk of leprosy infection\n\nInter and extra-domiciliary exposures will be included. We expect definitions of contacts to include different criteria to establish risk in relation to space, time, physical contact, and relationships.\n\nThe review will consider persons of any age and sex, residing in leprosy-endemic areas. Definitions might include participants recruited in the community (active case finding) or in health establishments (passive case finding); they may be symptomatic or asymptomatic.\n\nPubMed interface will be used for the primary search, without any a priori restrictions to language or date. A limited search of Google Scholar as a secondary source will also be conducted. We intend to screen the reference lists of included records (especially review papers) and contact experts in the field to check if we have missed any potentially relevant records.\n\nThe search strategy is based on the combination of two concepts: the condition of interest and the concept of ‘contact’. The Boolean operators “AND” and “OR” will be used to combine search terms. Table 1 summarizes the planned search syntax for PubMed. The same general strategy will be used to search in Google Scholar.\n\nAll retrieved records will be imported into COVIDENCE. Duplicate records will be identified and excluded using COVIDENCE and Mendeley. Two reviewers will independently select full-text papers to be included in this review. Discordances will be solved through discussion with the review team. Two reviewers will extract data items into a data extraction form in COVIDENCE that will include the categories included in Table 2. This table will be pilot tested on five papers, and then refined based on the results of the pilot. Data extraction will only consider published records; no contact with authors is planned.\n\nThematic narrative synthesis will be our main method of data reporting. Results will be inserted in each one of the categories specified in the final data extraction form. Information extracted from each manuscript will be indicated in summary tables. If considered useful, additional figures will be created.\n\nThis protocol is registered in F1000Research. The protocol has been developed in line with the Prisma Extension for Scoping reviews (PRISMA-ScR) recommendations.10\n\nTimeframe\n\n• Protocol publication: July 2022\n\n• Search, selection, data extraction and synthesis: July 2022 – October 2022\n\n• Writing of review paper: November 2022 – January 2023\n\nStudy status\n\nIn preparation of this protocol, preliminary searches have been conducted (mostly to grasp the extent of the available literature). However, formal reviewing activities had not started yet.\n\n\nData availability\n\nNo data are associated with this article.", "appendix": "References\n\nWorld Health Organization (WHO): Leprosy/Hansen disease: contact tracing and post-exposure prophylaxis. World Health Organization;2020. Regional Office for South-East Asia.\n\nWeng X, Xing Y, Liu J, et al.: Molecular, ethno-spatial epidemiology of leprosy in China: Novel insights for tracing leprosy in endemic and non endemic provinces. Infect. Genet. Evol. 2013; 14: 361–368. PubMed Abstract \| Publisher Full Text\n\nBlok DJ, de Vlas SJ , Fischer EAJ, et al.:Chapter Two - Mathematical Modelling of Leprosy and Its Control.Anderson RM; Basáñez MGBT-A in P, editors. Mathematical Models for Neglected Tropical Diseases: Essential Tools for Control and Elimination, Part A. Academic Press; 2015; pp. 33–51. Publisher Full Text\n\nOrtuno-Gutierrez N, Baco A, Braet S, et al.: Clustering of leprosy beyond the household level in a highly endemic setting on the Comoros, an observational study. BMC Infect. Dis. 2019; 19: 501. PubMed Abstract \| Publisher Full Text\n\nKendall C, Kerr LRFS, Miranda JGV, et al.: A social network approach for the study of leprosy transmission beyond the household. Trans. R. Soc. Trop. Med. Hyg. 2022; 116: 100–107. PubMed Abstract \| Publisher Full Text\n\nAshamalla L: Impact of Leprosy on Family and Intimate Relationships. Int. J. Dermatol. 1987; 26: 305–307. PubMed Abstract \| Publisher Full Text\n\nFeenstra SG, Nahar Q, Pahan D, et al.: A qualitative exploration of social contact patterns relevant to airborne infectious diseases in northwest Bangladesh. J. Health Popul. Nutr. 2013; 31: 424–434. PubMed Abstract \| Publisher Full Text\n\nFeenstra SG, Nahar Q, Pahan D, et al.: Social contact patterns and leprosy disease: a case-control study in Bangladesh. Epidemiol. Infect. 2013; 141: 573–581. PubMed Abstract \| Publisher Full Text\n\nMossong J, Hens N, Jit M, et al.: Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases. PLoS Med. 2008; 5: e74. PubMed Abstract \| Publisher Full Text\n\nTricco AC, Lillie E, Zarin W, et al.: PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann. Intern. Med. 2018; 169: 467–473. PubMed Abstract \| Publisher Full Text" }	[ { "id": "155569", "date": "05 Dec 2022", "name": "Millawage Supun Dilara Wijesinghe", "expertise": [ "Reviewer Expertise Leprosy", "Public Health", "Health Promotion", "Occupational Health" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThank you for the opportunity to review this paper, focusing on a crucial topic. This protocol for a scoping review is well-written and provides adequate details about the proposed methods. Furthermore, the methods seem well justified.\nI have a few minor suggestions which will improve the paper further.\nAbstract\n\nThe abstract should be structured as mentioned in the PRISMA-ScR guidelines1.\n\nIt is always better to have MeSH terms as keywords.\nIntroduction\nIn the introduction section, it is better to have what are the problems associated with not having a proper definition of 'close contact'.\n\nIt is also best to describe current discrepancies in the definition of contact in leprosy.\n\nThe authors can further justify the rationale for undertaking this review in the present context.\nMethods\nSearch strategy\nWhat about grey literature? Are you planning to include them?\n\nTable 2 - Setting - location - at what level (country level or below)?\n\nIntervention (If existing) - is this for identification of the index case or identification of contacts?\nProtocol and Registration\nPlease include the protocol's web address or registration number.\n\nIs the rationale for, and objectives of, the study clearly described? Yes\n\nIs the study design appropriate for the research question? Yes\n\nAre sufficient details of the methods provided to allow replication by others? Yes\n\nAre the datasets clearly presented in a useable and accessible format? Not applicable", "responses": [] }, { "id": "172157", "date": "13 Jun 2023", "name": "Vimal Kumar", "expertise": [ "Reviewer Expertise Leprosy", "tuberculosis", "animal experimentation" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nSummary:\nThe authors conducted this review to identify criteria of space (location, geographical variables, distance, indoor vs outdoor), time (including frequency and duration), physical exposure (skin to skin, sexual), and relationship (familial, occupational, social) involved in the definition of ‘close contacts’ in the context of risk of leprosy. They expect that this review will provide an overview of the conceptualization of this term and its variations across settings.\nThe proposal has good scientific and technical merit as the definition of contacts must be accepted in similar sense worldwide as still some ambiguity persists with the term 'contacts'.\nComments:\na. Is the rationale for, and objectives of, the study clearly described?\nComment: Yes, the rationale for, and objectives of, the study clearly described.\nAs the objective is to conceptualize the term on the different criteria of space, time, physical exposure, and relationship the correlation of the above facts will help in reaching the final conclusion in a better way.\nb. Is the study design appropriate for the research question?\nComment: Yes the study design is appropriate for the research question. The idea is innovative and has good novelty sense.\nc. Are sufficient details of the methods provided to allow replication by others?\nComment: Yes, sufficient details of the methods have been provided to allow replication by others. As the assay will evaluated on the different criterion, it will be very beneficial for the leprosy experts to come to a common conclusion for the leprosy contacts.\nd. Are the datasets clearly presented in a useable and accessible format?\nComment: The datasets have been presented in a useable and accessible format but I have one suggestion regarding improvement of the same.\nSuggestion: Instead of two, three reviewers should independently select full-text papers to be included in this review for the significant results.\n\nIs the rationale for, and objectives of, the study clearly described? Yes\n\nIs the study design appropriate for the research question? Yes\n\nAre sufficient details of the methods provided to allow replication by others? Yes\n\nAre the datasets clearly presented in a useable and accessible format? Partly", "responses": [] }, { "id": "172160", "date": "13 Jul 2023", "name": "Veronica Schmitz", "expertise": [ "Reviewer Expertise Immunology of leprosy", "clinical research" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript entitled \"Definition of ‘close contacts’ in leprosy studies: protocol for a scoping review\" by Ronse et al. describes the literature review that the authors plan to carry out with a highly relevant topic which is the definition of contacts in leprosy. The close contact for leprosy is defined by WHO, however many different authors provide different definitions and found different results of what is a close contact or household contact.\"\nThe article has straightforward question and a search strategy defined.\nMinor points: Methods:\nThe eligibility criteria: I would suggest to define study inclusion and exclusion criteria separately.\n\nWhy don't you also use EMBASE, Web of Science, Scopus, LILACS, Virtual Health Library or Cochrane Library databases?\n\nIt is not clear if the development process will include the characterization of each selected study, evaluation of their quality, identification of important concepts, and comparison of statistical analyses used.\n\nIs the planning/Timeframe updated?\n\nIs the rationale for, and objectives of, the study clearly described? Yes\n\nIs the study design appropriate for the research question? Yes\n\nAre sufficient details of the methods provided to allow replication by others? Yes\n\nAre the datasets clearly presented in a useable and accessible format? Not applicable", "responses": [] } ]	1	https://f1000research.com/articles/11-808
https://f1000research.com/articles/11-420/v1	13 Apr 22	{ "type": "Software Tool Article", "title": "DSMZCellDive: Diving into high-throughput cell line data", "authors": [ "Julia Koblitz", "Wilhelm G. Dirks", "Sonja Eberth", "Stefan Nagel", "Laura Steenpass", "Claudia Pommerenke", "Wilhelm G. Dirks", "Sonja Eberth", "Stefan Nagel", "Claudia Pommerenke" ], "abstract": "Human and animal cell lines serve as model systems in a wide range of life sciences such as cancer and infection research or drug screening. Reproducible data are highly dependent on authenticated, contaminant-free cell lines, no better delivered than by the official and certified biorepositories. Offering a web portal to high-throughput information on these model systems will facilitate working with and comparing to these references by data otherwise dispersed at different sources.\nWe here provide DSMZCellDive to access a comprehensive data source on human and animal cell lines, freely available at celldive.dsmz.de. A wide variety of data sources are generated such as RNA-seq transcriptome data and STR (short tandem repeats) profiles. Several starting points ease entering the database via browsing, searching or visualising. This web tool is designed for further expansion on meta and high-throughput data to be generated in future. Explicated examples for the power of this novel tool include analysis of B-cell differentiation markers, homeo-oncogene expression, and measurement of genomic loss of heterozygosities by an enlarged STR panel of 17 loci.\nSharing the data on cell lines by the biorepository itself will be of benefit to the scientific community since it (1) supports the selection of appropriate model cell lines, (2) ensures reliability, (3) avoids misleading data, (4) saves on additional experimentals, and (5) serves as reference for genomic and gene expression data.", "keywords": [ "DSMZ", "human and animal cell lines", "RNA-seq", "STR", "HLA", "omics data", "LL-100", "leukemia", "lymphoma", "homeobox" ], "content": "Introduction\n\nFor more than 70 years, cell lines have become indispensable for life sciences, especially for biomedical research. Human and animal cell lines represent cost-effective model systems of almost unlimited availability. Furthermore, they are relatively easy to manipulate. The vast majority of cell lines are derived from spontaneously immortalised tumour cells carrying specific characteristics. They have become essential models not only for cancer research such as investigating mechanisms of tumorigenesis, targets for therapy, or drug efficacies but also for other areas of biological sciences. Cell lines are made available to the scientific community by cell lines banks, who also control and guarantee for cell line authenticity. In general both, diagnosis and clinical parameters of the donor as well as molecular characteristics of the cell line itself, are required for the selection of an appropriate model cell line for a specific research question.\n\nUsually, the required information about cell lines has to be gathered from different sources, often including the study of literature. In addition to the information provided in the cell line data sheets of the biorepositories themselves, several online databases independent of the biorepositories can be consulted. The largest available online platform listing key information and references from continuous cell lines is Cellosaurus1. However, so far the mentioned sources contain only limited information about genetic or transcriptional aberrations characterising a cell line. Today, molecular characteristics obtained from high-throughput sequencing data from cell lines become more and more relevant for the selection of appropriate models. In this context, the cell lines project database of COSMIC (Catalogue of Somatic Mutations in Cancer) provides mutation profiles and copy number variations of over 1,000 cancer cell lines2. Further publicly accessible datasets for download are multiple high-throughput sequencing data from the CCLE (Cancer Cell Lines Encyclopedia) panel via the DepMap Portal which also offers interactive data visualisation3. In order to support the search for appropriate cell line models Jeong et al. developed the online database GEMiCCL which enables the comparison of genomic, transcriptomic and copy number data generated in different projects, including CCLE, COSMIC and the NCI-60 cell lines panel4. Importantly, the comparison of the data from different sources points out that e.g. mutation data can strongly vary for a cell line depending on the data source. This observation is not surprising, as selective culture conditions can foster evolution of cell lines, impacting the genetic and transcriptional diversity of the same cell line between two laboratories5. Thus, the major drawbacks during the selection process for an appropriate model cell line are either that the molecular data cannot easily be traced back to the source of the cell line and culture conditions used for the generation of the data, and that bioinformatics skills are required to re-analyse publicly available omics data after downloading.\n\nSo far, most molecular data including high-throughput sequencing data are available from different sources but not from the cell line repository itself. This fact ultimately confronts the selection of cell lines with the question from which resource the cell line with the appropriate molecular characteristics is actually available. To overcome this limitation we developed DSMZCellDive, a novel web portal that offers access to evaluated RNA-seq data and STR profiles generated from material of human and animal cell lines that are provided to the scientific community via the DSMZ catalogue.\n\n\nMethods\n\nAll data were provided by internal sources at the DSMZ, extracted from various formats using tailored scripts, and finally transferred into an SQL database. The data were integrated by using cell culture identifiers, such as the name of the cell line and DSMZ ACC-No. The SQL database is based on MariaDB Version 10.3. PHP 7 is used to generate the web pages and to query an internal SQL database. The JavaScript libraries jQuery and Plotly.js are used to do asynchronous server requests and draw charts, respectively. Heat maps are created using the R library heatmaply. The PHP library Parsedown is used to display the COI barcoding report.\n\nThe importance of machine-readability is increasing steadily. So far, web search engines use a standardised vocabulary (schema.org) to do basic queries. The Bioschemas initiative (bioschemas.org) aims to extend these vocabularies for life sciences. We have integrated Bioschemas profiles and added a machine-readable markup for all cell lines. The Bioschemas representations enhance interoperability and standardisation of DSMZCellDive.\n\nDSMZCellDive can be accessed at celldive.dsmz.de with every modern browser and is free of charge.\n\n\nResults\n\nDSMZCellDive is designed to provide a data portal to high-throughput and meta data of cell lines hosting diverse data sources. Gene expression data beside HLA (human leukocyte antigen) information, STR (short tandem repeat) profiles, and COI (cytochrome c oxidase I) DNA barcodes are bundled at start as listed in Table 1 and there is more to come. In the following current data sources are described briefly.\n\n*100 leukemia and lymphoma cell lines + NC-NC, a B lymphoblastoid cell line.\n\nThe vast majority of data entries in DSMZCellDive is composed of RNA-seq data. We started with our published data on 100 human leukemia and lymphoma cell lines (LL-100 panel)6. In contrast to the cited paper, the non-malignant cell line NC-NC, a B lymphoblastoid cell line, is included and RNA-seq data were quantified via Salmon7 and normalised via DESeq28 in order to keep pace with state-of-the-art data analysis.\n\nHLA genes encode proteins in the major histocompatibility complex (MHC) which play a central role in discriminating self and non-self9. Although the HLA gene cluster on chromosome 6 is highly polymorphic, it is not suitable for cell line authentication due to a low exclusion rate and instability of gene expression. Furthermore, HLA typing is important for cancer research since determination of tissue compatibility by tumour neoantigen binding to HLA surface proteins and rejection of specific HLA alleles play a role. Here, HLA typing was determined on LL-100 RNA-seq data via arcasHLA, an alignment-based tool9.\n\nThe applied genotyping system (Promega Powerplex 18D) uses STR microsatellite repeats which are located at 17 specific genomic loci that are highly polymorphic in human populations including gender determination via Amelogenin. STR typing is serving as a reference technique for identity control of human cell lines at biological resource centers and available as global standard (ANSI/ATCC ASN-0002-2021 (2021). Authentication Of Human Cell Lines: Standardization Of Short Tandem Repeat (STR) Profiling. ANSI eStandards Store). Data sources were kindly provided by ATCC, JCRB, and amended by DSMZ10.\n\nDNA barcoding for animal samples is frequently based on the Cytochrome c oxidase subunit 1 (COI or COX1) DNA sequence known to exert specific differences between species - prerequisite for species identification. DSMZCellDive harbours COI barcodes for all animal cell lines available at the DSMZ.\n\nAll data were extracted from various data formats and integrated into a relational SQL database. The database structure contains seven tables in total and can be extended with more data types easily (Figure 1). All data types that belong to DSMZ cell lines are connected to the celllines table via one-to-many connections to its primary key cell_id. Since one cell line can have multiple STR profiles, a meta table is used to connect profiles to cell lines. This should not be confused with the fact that one cell line may carry multiple STR alleles per STR loci, a phenomenon called microsatellite instability (MSI). The whole COI barcoding DNA sequence as well as the report is saved as markdown in a single text field as currently no search or comparison operations are planned on these data, since species-specificity only not genetic individuality is resolved by this technique.\n\nPrimary keys are blue and marked with a key symbol, foreign keys are blue. Each color represents a different data type: blue for RNA-seq data, green for STR profiles, yellow for HLA typing data, and red for COI barcoding data. All data sets are integrated via a central cell line table (black).\n\nThe DSMZCellDive website was designed to be easily extensible by more data types. For this reason, the web layout contains a sidebar instead of a classical navbar, as it allows more content. The header contains breadcrumbs to meet the requirements of the hierarchical structure of the page. The starting page gives an overview on all available data types and provides links to all tables and tools. Each data source has its own overview page, describing the data, available literature and providing further links.\n\nEach RNA-seq data set has its own entry page and supports visualisation as bar chart or heat map. An interactive web interface enables the user to enter genes (up to five for bar charts and up to 20 for heat maps), select tumour entities or cell lines directly, and choose whether normalised data, raw counts, or TPM (transcripts per kilobase million) values should be used. Currently, only RNA-seq data from the LL-100 panel are available; however, it is planned to add more data sets in the near future. For this reason, an integrated view on all RNA-seq data from the different projects was added early on. Since data are normalised within each project, normalised values between projects should not be compared, only TPM data and bar charts are available here.\n\nThe STR data sets come with a browser and a search tool. While the browser allows access to unique comprehensive STR data sets of DSMZ and other major cell lines banks, the search tool allows users to compare own STR profiles for similarity matching with regard to authenticity. As a result of the search closest matches according to the following equation are displayed and the ratio to the reference is given in percent distance as described previously11.\n\n\n\nThe result page offers further information on the cell lines and is cross-linked to the respective cell line detail page, which also enables access to the cell line data sheet of the DSMZ catalogue.\n\nAll data are integrated on cell line level. Each of the currently almost 900 cell lines has its own detail page, including meta data on the cell line, i.e. the species, cell type, morphology, and culture media. Depending on whether it is a human or animal cell line, STR profiles or COI DNA barcode reports are displayed, respectively. If the cell line belongs to any RNA-seq project, a histogram of all genes is shown, as well as HLA typing data.\n\n\nUse cases\n\nOur new web tool can be applied to analyse and visualise the expression of B-cell development and differentiation markers in B-cell derived cancer cell lines (Figure 2). B-cells originate from multipotent hematopoietic stem cells in the bone marrow and undergo a series of antigen-independent and antigen–dependent differentiation and maturation steps until they finally become memory or plasma B-cells that secrete antibodies. These steps are associated with the expression of well-studied marker genes, many of them encode for cell surface molecules commonly used for immunophenotyping. Importantly, B-cell derived cancer cells still mirror the differentiation and maturation phase of their normal B-cell counterpart, which is also reflected in the expression profile of B-cell marker genes and is crucial for the diagnosis of B-cell neoplasms12,13. Figure 2B depicts a heat map illustrating the expression of a customised selection of 18 B-cell differentiation marker genes (CD1A, CD19, CD24, CD27, CD34, CD38, CD40, CD79A, CD79B, CD80, CR2, CXCR4, IL2RA, MME, MS4A1, SDC1, SLAMF7, and TNFRSF8) across the B-cell derived cell lines included in the LL-100 panel. Intriguingly, specific B-cell markers get lost in the tumour cells. For example, although CD19 is usually expressed in all B-cells from pre-B-cells until the terminal differentiation to plasma cells14, its expression is typically absent in Hodgkin lymphoma (HL), plasma cell leukemia (PCL), primary effusion lymphoma (PEL) and in a fraction of Diffuse large B-cell lymphoma (DLBCL)15,16. Accordingly, CD19 loss is also seen in cell lines representing HL, PCL, and PEL (Figure 2C). The DLBCL cell line OCI-LY3 is an example for weak CD19 expression on mRNA and protein level compared to DLBCL cell line NU-DHL-1 harboring the highest CD19 expression across all analyzed cell lines (Figure 2C and 2D). Thus, DSMZCellDive can assist the selection of model cell lines e.g. with varying levels of CD19.\n\n(A) For customised analysis of RNA-seq data of the LL-100 project via the new web tool 18 genes and 12 tumour entities were selected to visualise expression pattern in a heat map (red arrow). (B) The resulting heat map depicts normalised expression of the genes in rows within the selected cell lines depicted in columns. Red arrow: CD19. (C) Alternatively, expression of single genes can be visualised in a bar chart. As an example normalised expression of CD19 (indicated by an arrow in B) is shown in the same tumour entities selected in A and B. Additionally, a table listing the values for normalised CD19 expression per cell line appears underneath the bar chart. (D) Protein expression of CD19 in three of the cell lines depicted in C (red arrows). Flow cytometry data were taken from the corresponding cell line data sheets of the DSMZ catalogue to which users are guided by clicking on the blue cell line names in the table depicted in C.\n\nHomeobox genes encode transcription factors sharing a special helix-turn-helix 3D-structure which mediates interaction with DNA, cofactors and chromatin. This homeodomain is formed by 60 amino acid residues and represents a platform performing gene regulation. Homeobox genes control fundamental processes in development and differentiation during embryogenesis and in the adulthood17. Therefore, deregulation of their activity is a common theme in cancer including hematopoietic malignancies.\n\nAccording to their conserved homeobox sequences, these genes are arranged in eleven classes and several subclasses18. The NKL subclass (NK-like) belongs to the ANTP class (according to the Drosophila antennapedia gene) and consists of 48 members in humans. Their physiological expression pattern in the hematopoietic compartment has been termed “NKL-code“ comprising eleven genes19. This code is a useful tool to evaluate deregulated NKL homeobox genes in myeloid and lymphoid leukemia/lymphoma patients. To date, 24 aberrantly activated NKL homeobox genes are described in T-cell acute lymphoblastic leukemia (T-ALL), representing the strongest group of oncogenes in this malignancy20. TLX1 (formerly HOX11) and TLX3 (HOX11L2) are the most frequently deregulated NKL homeobox genes in T-ALL while NKX2-5 is only rarely expressed19.\n\nCell lines are useful models to investigate regulation and function of oncogenes including homeobox genes. To identify a leukemia/lymphoma cell line expressing a particular homeo-oncogene, our published LL-100 dataset and the here presented online tool DSMZCellDive may assist to find a suitable cell line model6. Figure 3A illustrates generated results, showing gene expression data for TLX3 and NKX2-5 as barplots. Both genes are expressed in particular T-ALL cell lines while silenced in cell lines derived from other leukemia/lymphoma entities21,22. NKL homeobox gene VENTX is physiologically expressed in lymphoid T-cell progenitors and myeloid conventional dendritic cells (cDC)23. MUTZ-3 is an AML (acute myeloid leukemia) cell line derived from a cDC progenitor. This cell line expresses VENTX and represents a useful model to investigate differentiation of dendritic cells and their derived malignancies23. Figure 3B shows NKL homeobox gene activities for VENTX, TLX3 and NKX2-5 in selected cell lines as heat map, demonstrating strikingly high VENTX expression in MUTZ-3. Thus, DSMZcellDive is a useful tool to identify and illustrate normal and aberrant (homeobox) gene expression in leukemia/lymphoma cell lines.\n\n(A) Bar plots showing activities for NKL homeobox genes TLX3 (above) and NKX2-5 (below) in the LL-100 panel. Both genes are exclusively expressed in T-ALL cell lines DND-41, HPB-ALL (TLX3) and CCRF-CEM (NKX2-5). T-ALL cell lines are indicated by a bracket. (B) Heat map showing activities for NKL homeobox genes VENTX, TLX3 and NKX2-5 in AML and T-ALL cell lines (left). VENTX is prominently expressed in myelomonocytic cell line MUTZ-3, representing a model for conventional dendritic cells. A color-code assigns tumour entities to the cell lines as indicated in A and B (right).\n\nAlthough in vitro evolution of tumour cell lines is well known5, the underlying genomic alterations often remain obscure. Despite elaborate quality control via STR genotyping of lot charges, crucial genetic changes of a tumour model may remain hidden to the applying scientist.\n\nThe importance of MSI and LOH (loss of heterozygosity) can be demonstrated in one of the most commonly used models for AML research, the cytokine-dependent cell line THP-1. A recent publication by Noronha et al. describes a large genetic divergence between THP-1 cells from a European and a US biorepository24. Although globally standardised STR genotyping in biorepositories is primarily used to prevent the spread of misidentified cell lines, STR typing can distinguish subclones from parental cell lines when minor changes in the STR profile have occurred due to MSI or LOH (Figure 4A). Specifically, it is LOH changes that may qualitatively reveal the loss of a heterozygous chromosomal region but do not allow quantitative conclusions to be drawn. For the divergent THP-1 cell lines, the STR profiles search via DSMZCellDive using 17 STR loci yield similarities of 94.4% and 88.9%, respectively (Figure 4B), indicating a close genetic relationship between THP-1 cell lines of different repositories. Despite these high similarities, critical genetic targets of MLL (mixed lineage leukemia) differed substantially between cell bank-specific THP-1 cells24. Thus, not only is cross-contamination of cell lines a serious problem for the reproducibility of scientific data, but also silent LOH events within a scientific tumour model.\n\n(A) In the upper half the heterozygous wild type status of STR locus D5S818 on chromosome 5 is shown, corresponding STR electropherograms are depicted on the right. MSI is caused by a replication error during DNA synthesis and may result in a new allele 9 by allelic drift. LOH can occur by a deletion mutation (LOH DEL) or by recombination between paternal chromosomes known as uniparental disomy (UPD). In both LOH cases, genomic DNA is lost and may lead to undesired losses of particular physiological properties at worst. (B) Searching for the reference STR profile of the cell line THP-1 via DSMZCellDive delivers similarity scores to other cell line profiles. Highlighted cell lines in green indicate authenticity without doubt, while cell lines with MSI datasets below 80% in particular would be highlighted in yellow and require additional testing. Hits below 60% are thought to be definitely genetically different.\n\nThus, DSMZCellDive enables scientists to verify the authenticity of cell lines by providing an extended STR-17 panel, which measures the degree of correspondence between the original cell line and already slightly modified cell lines. Since all commonly measured STR loci for authentication are combined in the STR-17 panel, this is independent of the STR typing kits used. By presenting the diploid STR datasets in two columns, LOH and UPD events can be deduced, which in turn immediately shows users how often and at what point their own STR data has deviated from the STR reference profile. The described tools will increase reliability of in vitro data towards trusted scientific conclusions.\n\n\nConclusion\n\nWith the interactive web portal DSMZCellDive at hand, access to cell lines omics and meta data is bundled at one site. DSMZCellDive presents its own RNA-seq data exclusively from cell lines of the DSMZ. The novel web portal allows researchers to browse and visualize authentic NGS data generated according to high quality standards e.g. to support the selection of appropriate model cell lines, while cell lines are acquired. Furthermore, its concept allows implementation of future data readily and, more importantly, provides reliable data of cell lines available at DSMZ, which can serve as reference data for industry and science.\n\n\nData and software availability\n\nAll data underlying the results are available as part of DSMZCellDive and no additional source data are required.\n\nWebsite: https://celldive.dsmz.de\n\nSource code at github to download and process:\n\nWebsite: https://github.com/JKoblitz/DSMZCellDive\n\nRNA-seq: https://github.com/claupomm/RNA-seq_ll100\n\nHLA analysis: https://github.com/claupomm/HLA-analysis\n\nZenodo for archived source code at time of publication:\n\nWebsite: https://doi.org/10.5281/zenodo.6404422\n\nRNA-seq pipeline: https://doi.org/10.5281/zenodo.6401600\n\nHLA analysis: https://doi.org/10.5281/zenodo.6401594\n\nLicense: MIT License", "appendix": "Author contributions\n\n\n\nJK designed the concept of the web portal and database, wrote all code and the manuscript. WGD provided STR profiling and COI barcoding data and wrote the manuscript. SE and SN provided expertise and wrote the manuscript. LS initiated and designed the basic concept of the web portal. CP provided preliminary work to the web tool, supervised the project, contributed RNA-seq and HLA data, and wrote the manuscript. All authors edited the manuscript.\n\n\nAcknowledgements\n\nWe thank all our colleagues at the Leibniz-Institute DSMZ who contributed to improve the usability of DSMZCellDive. In particular we thank Hilmar Quentmeier for initiating this project, Silke Fähnrich for enhancing the STR part, furthermore Boyke Bunk and Lorenz Reimer for organisational support.\n\n\nReferences\n\nBairoch A: The Cellosaurus, a cell-line knowledge resource. J Biomol Tech. 2018; 29(2): 25–38. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nIorio F, Knijnenburg TA, Vis DJ, et al.: A landscape of pharmacogenomic interactions in cancer. Cell. 2016; 166(3): 740–754. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGhandi M, Huang FW, Jané-Valbuena J, et al.: Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature. 2019; 569(7757): 503–508. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nJeong I, Yu N, Jang I, et al.: GEMiCCL: mining genotype and expression data of cancer cell lines with elaborate visualization. Database (Oxford). 2018; 2018: bay041. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nBen-David U, Siranosian B, Ha G, et al.: Genetic and transcriptional evolution alters cancer cell line drug response. Nature. 2018; 560(7718): 325–330. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nQuentmeier H, Pommerenke C, Dirks WG, et al.: The LL-100 panel: 100 cell lines for blood cancer studies. Sci Rep. 2019; 9(1): 8218. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nPatro R, Duggal G, Love MI, et al.: Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017; 14(4): 417–419. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLove MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15(12): 550. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nOrenbuch R, Filip I, Comito D, et al.: arcasHLA: high-resolution HLA typing from RNAseq. Bioinformatics. 2020; 36(1): 33–40. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDirks WG, MacLeod RAF, Nakamura Y, et al.: Cell line cross-contamination initiative: an interactive reference database of STR profiles covering common cancer cell lines. Int J Cancer. 2010; 126(1): 303–4. PubMed Abstract \| Publisher Full Text\n\nTanabe H, Takada Y, Minegishi D, et al.: Cell line individualization by STR multiplex system in the cell bank found cross-contamination between ECV304 and EJ-1/T24. Tissue culture research communications. 1999; 18(4): 329–338. Publisher Full Text\n\nKüppers R: Mechanisms of B-cell lymphoma pathogenesis. Nat Rev Cancer. 2005; 5(4): 251–62. PubMed Abstract \| Publisher Full Text\n\nde Leval L, Jaffe ES: Lymphoma Classification. Cancer J. 2020; 26(3): 176–185. PubMed Abstract \| Publisher Full Text\n\nWang K, Wei G, Liu D: CD19: a biomarker for B cell development, lymphoma diagnosis and therapy. Exp Hematol Oncol. 2012; 1(1): 36. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGathers DA, Galloway E, Kelemen K, et al.: Primary Effusion Lymphoma: A Clinicopathologic Perspective. Cancers (Basel). 2022; 14(3): 722. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMasir N, Marafioti T, Jones M, et al.: Loss of CD19 expression in B-cell neoplasms. Histopathology. 2006; 48(3): 239–46. PubMed Abstract \| Publisher Full Text\n\nBürglin TR, Affolter M: Homeodomain proteins: an update. Chromosoma. 2016; 125(3): 497–521. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHolland PWH, Booth HAF, Bruford EA: Classification and nomenclature of all human homeobox genes. BMC Biol. 2007; 5: 47. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNagel S: NKL-Code in Normal and Aberrant Hematopoiesis. Cancers (Basel). 2021; 13(8): 1961. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNagel S, Pommerenke C, Scherr M, et al.: NKL homeobox gene activities in hematopoietic stem cells, T-cell development and T-cell leukemia. PLoS One. 2017; 12(2): e0171164. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMacLeod RAF, Nagel S, Kaufmann M, et al.: Activation of HOX11L2 by juxtaposition with 3'-BCL11B in an acute lymphoblastic leukemia cell line (HPB-ALL) with t(5;14)(q35;q32.2). Genes Chromosomes Cancer. 2003; 37(1): 84–91. PubMed Abstract \| Publisher Full Text\n\nNagel S, Kaufmann M, Drexler HG, et al.: The cardiac homeobox gene NKX2-5 is deregulated by juxtaposition with BCL11B in pediatric T-ALL cell lines via a novel t(5;14)(q35.1;q32.2). Cancer Res. 2003; 63(17): 5329–34. PubMed Abstract\n\nNagel S, Pommerenke C, Meyer C, et al.: NKL Homeobox Gene VENTX Is Part of a Regulatory Network in Human Conventional Dendritic Cells. Int J Mol Sci. 2021; 22(11): 5902. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNoronha N, Ehx G, Meunier MC, et al.: Major multilevel molecular divergence between THP-1 cells from different biorepositories. Int J Cancer. 2020; 147(7): 2000–2006. PubMed Abstract \| Publisher Full Text" }	[ { "id": "135181", "date": "24 May 2022", "name": "Beate Rinner", "expertise": [ "Reviewer Expertise Cell line establishment", "Cell line characterization", "cell line quality check" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn the submitted article of Koblitz et al., DSMZCellDive, a comprehensive data source for human and animal cells, will be presented, one aim is to provide high-throughput information through a web portal that aggregates data and references that are otherwise spread across multiple sources.\n\nA variety of data sources are generated, such as RNA-seq transcriptome data and STR (Short Tandem Repeats) profiles, which are essential for working with cell lines.\n\nThe new tool is explained and described in detail, e.g. how to access the database via browsing, searching or visualization. The database can be extended with meta- and high-throughput data that will be generated in the future to finally allows a comprehensive summary and detailed characterizations of a cell line.\nTo illustrate the power of the tool, analysis of B-cell differentiation markers, homeo-oncogenes, homeo-oncogene expression, and measurement of genomic loss of heterozygotes through an expanded STR panel of 17 loci were described.\n\nDSMZCellDive offers enormous added value to the scientific community by supporting the selection of suitable model cell lines and thus ensuring the reliability and reproducibility of experiments.\n\nOptimal in vitro conditions also save resources in the long term. The comprehensive data acquisition and provision of the tool leads to a massive upgrading of in vitro models, which enables the reduction of animal experiments and thus sustainably implements the 3R principles in research.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "8518", "date": "20 Jul 2022", "name": "Claudia Pommerenke", "role": "Author Response", "response": "We thank the reviewer for the evaluation of our work and appreciate the positive comments." } ] }, { "id": "135173", "date": "06 Jul 2022", "name": "Arihiro Kohara", "expertise": [ "Reviewer Expertise cell biology", "genetic mutation" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this manuscript, the authors are concerned with the creation of a new web portal that creates a database of cell metadata and characteristic analysis information in cell banks and biorepositories, and will be able to provide useful information for researchers using cell lines. This manuscript can be highly evaluated as an initiative. We also hope that information such as RNA-seq will be expanded in the future, and that fusion gene search based on sequence information and data sharing with other banks will also be expected.\nHowever, I think it will be a better manuscript if you reconsider the following points, so please consider modifying it.\nMajor\nIn the RNA-seq heat map analysis, the clustering results performed based on the similarity of the expression profile of each gene are displayed, but the clustering result based on the similarity of the expression profile of each cell line should also be displayed.\nMinor\nThe legend in Fig. 4B is not appropriate. There are no cell lines highlighted in yellow, while there is no indication of the color of cells highlighted in red.\n\nAlthough the data in Fig. 4B shows only 9 loci data as an example of LOH, it is considered that 17 loci data is collected in this database, so please describe the verification using all the data.\n\nAlso, why not explain the example of MSI-H using MOLT-4 etc.?\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "8519", "date": "20 Jul 2022", "name": "Claudia Pommerenke", "role": "Author Response", "response": "We thank the reviewer for their valuable comments. Please find our responses here: Major \"In the RNA-seq heat map analysis, the clustering results performed based on the similarity of the expression profile of each gene are displayed, but the clustering result based on the similarity of the expression profile of each cell line should also be displayed.\" Thank you for your note on the heat map display. Clustering by cell line has been offered as option in the past, albeit by cell line solely without gene clustering. We now enabled clustering by cell line line and gene simultaneously (option “both”). Minor \"The legend in Fig. 4B is not appropriate. There are no cell lines highlighted in yellow, while there is no indication of the color of cells highlighted in red.\" Many thanks to the reviewer for the hint. We have now displayed the colors correctly in Fig. 4B and described the cell lines highlighted in red as genetically unbiased. \"Although the data in Fig. 4B shows only 9 loci data as an example of LOH, it is considered that 17 loci data is collected in this database, so please describe the verification using all the data.\" Figure 4B has been redone so that all STR locations are now captured and the matches across STR 17 are completely shown. \"Also, why not explain the example of MSI-H using MOLT-4 etc.?\" An explanation of the MSI phenomenon based on MOLT-4 would unfortunately go beyond the scope of this paper. For a satisfactory explanation, the failure of DNA MMR and the origin of DNA replication errors would have to be presented, so that the scope in this manuscript would be exceeded. In addition, it would need to be discussed much more deeply that the rule established by Amanda Capes-Davies for relatedness of cell lines when there is at least 80% similarity of the STR profile does not apply to MSI cell lines (Capes‐Davis, Amanda, et al. \"Match criteria for human cell line authentication: where do we draw the line?\" International journal of cancer 132.11 (2013): 2510-2519). Finally, MSI lines need additional tests as described in the STR standard of 2021 (ANSI/ATCC ASN-0002-2021 (2021) Authentication Of human cell lines: standardization of Short Tandem Repeat (STR) profiling. ANSI eStandards Store)." } ] } ]	1	https://f1000research.com/articles/11-420
https://f1000research.com/articles/10-777/v1	09 Aug 21	{ "type": "Research Article", "title": "A comparative study of red brick powder and lime as soft soil stabilizer", "authors": [ "Aisyah Salimah", "Miftah Hazmi", "Muhammad Fathur Rouf Hasan", "Putera Agung Maha Agung", ". Yelvi", "Miftah Hazmi", "Muhammad Fathur Rouf Hasan", "Putera Agung Maha Agung", ". Yelvi" ], "abstract": "Background: Soil has an important role to play in planning buildings because it supports the loads above it. Different types of soil with poor mechanical properties require more attention. Therefore, it is necessary to put in more effort to stabilize soil in order to improve its properties. This study aimed to compare the potential of lime and brick powder as stabilizers based on the values of California bearing ratio (CBR). Soil stabilization can be defined as the process of stabilizing soil properties by chemical or physical means to improve its engineering efficiency. The main objectives of stabilizing soil are to increase the bearing capacity of soil, to increase its resistance to weathering processes, and its permeability. Methods: In this work laboratory tests were done with disturbed and undisturbed soil samples. The proportions of lime or red brick powder additives mixed together are 0%, 5%, 10%, and 15% of the original soil sample. From the results of the laboratory tests, the soil type obtained is MH soil based on the Unified Soil Classification System (USCS). The MH soil type is a low plasticity silt soil. Results: The study’s results showed that with the addition of lime and brick powder, the soil could be stabilized. In both soaked and unsoaked CBR tests, there was an increase in the CBR value for each proportion of the mixed additives. However, red brick powder had a significant increase of 15%. Conclusions: This study found a very large range of variations because of the many material requirements for each test. We suggest other researchers perform the CBR test by reducing the range of variations in the additives to get firm data and using our experimental procedure in this study for further research.", "keywords": [ "Soft soil", "lime", "brick powder", "CBR", "hambalang" ], "content": "Introduction\n\nSoil is considered to be a three-phase system consisting of soil particles, pores (air) between its particles, and liquid (water) which varying degrees, fills and flows through the pores.1 Based on the particle size of soil, there are several types of soil, namely gravel, sand, silt, clay.2 The large content of silt and clay in soil affects its geotechnical characteristics that can vary: shrink when dry, and expand when wet; in the presence of water, they swell and become plastic.3 Constructions such as buildings, highways, bridges, tunnels, dams, and towers are established on the ground that functions to support the loads above it.4 Engineers often have problems using soft soil, which has; weak mechanical properties. Soft soil is a cohesive soil consisting of very small grains, characterized by low shear strength and high compressibility, which does not possess sufficient strength to support loads. It is necessary to treat these soils to provide a stable subgrade and avoid excessive land subsidence. A soil is categorized as soft soil if its shear strength value is 12 – 25 kPa.5\n\nFor these reasons, soft soils need treatment before they can be used as a material subgrade by enhancing their engineering properties. Soil stabilization aims at improving soil properties and increases its resistance to softening by water. In principle, it means rearranging soil grains for them to be very tight and interlocked together.6,7 The stabilization process, which is mixing soil with additives, can change the texture or plasticity of soil, its gradation, or act as a binder for soil cementation.8\n\nIn recent years, a considerable number of field and laboratory experiments have been carried out using various additives, such as lime,9–11 silica fume,12 and fly ash.13,14 However, not much research has been done on soil stabilization using red brick powder as a soil stabilizer.15,16 Moreover, every red brick manufacturer knows its history, which does not always have the same characteristics. This could indicate differences in the test results at every location.17 Therefore, it is necessary to do more research on the effect of red brick powder on soil stability. Also, lime and red brick powder are compared in this work. The impact of lime and red brick powder on the geotechnical qualities of soft soil was examined by conducting the CBR test. The CBR values for the soil mixture progressively increased.18,19 The CBR value increased because the soil structure changed from being dispersed to flocculated. Thus, in this study, lime and brick powder were used as stabilizers on soft soils.\n\nThe study aims to compare the potential of lime and brick powder in stabilizing soft soil. Soil stabilization parameters were measured based on their effect on the CBR values of soaked and unsoaked soil samples. This test is a penetration test which entails inserting an object into the test object. Through this way, the strength of the base or other materials used to make the pavement can be assessed. As soil is not always in a dry condition, it would not be enough to do the CBR test with unsoaked soil samples; it must be done also with soaked soil. Soaking simulates adverse moisture conditions such as those caused by possible rain or flooding, and it is used in most CBR test. The difference between the soaked and unsoaked CBR testing procedure is that in the soaked CBR, the soil sample that has been molded is first soaked for 4 days (96 hours) by placing a standard load of 10 lb above the mold and then penetration test is carried out afterward. The mixed proportions of lime or red brick (additives) powder are 0%, 5%, 10%, and 15% of the original soil. In this study, the index and engineering properties of the original soil and mixed soil were tested. Index properties test includes testing moisture content, specific gravity, Atterberg limit, and grain size analysis. While testing the original soil with a variation of the mixture of lime or red brick powder, the standard compaction test and CBR analysis are carried out.\n\nLime is commonly used as additional material for soil stabilization especially for the construction of highways. Lime reacts with soil and changes its mineral properties. This is due to its reaction with calcium ions, which leads to the formation of cementitious holding capacity of soil (decreases moisture content), reduction of swelling, and improvement of soil stability.20 Previous studies21,22 revealed that the stabilization of subgrades by lime could significantly improve their engineering properties. Using lime for soil stabilization gives a significant level of long-term strength gain, which is developed through a long-term pozzolanic reaction.23\n\nRed brick is made of clay, which is burned at a high temperature until a reddish color is obtained. It cannot be broken down when immersed in water. Red brick has refractory properties and can withstand compressive loads.24 There are scanty research works that have used red brick powder as a stabilizer because it is not commonly used. Each area has different red brick characteristics. Previous researches works have found that in CBR results, the primary strength parameters of soil were substantially improved by the use of brick powder.25\n\n\nMethods\n\nThe type of soil used in this research is soft soil located in Hambalang, Bogor. The rock that makes up the area at the top is in the form of Quaternary volcanic breccia; it is less compacted, with its surface utterly weathered into sandy clay. Its colour is gray-brown, it is soft and 0.30-1.50 meters thick. In the breccia unit, the localities have lenses or inserts that are flaky, swollen, stiff, partially scraped, and soft when exposed on the surface. Their colour is gray to brownish-gray. Figure 1 shows a systematic geological map of Bogor, Indonesia.26 The green area is the sampling location used in this study where the surficial deposits show clay shale.\n\nReproduced with permission from the Head of the Geological Survey Institute of Indonesia.\n\nThe method used in this research is a descriptive method, with tests conducted in the laboratory. Soil samples were taken in October during rainy season near the project site of the homestead of Athlete Hambalang, Bogor, Indonesia. Its geographical coordinates are 6°33′14.5″S and 106°53′22.1″E. Soil sampling was taken from a depth of 1 m to approximately 200 kilograms. Soil materials used for the test were disturbed and undisturbed soil samples. The undisturbed soil sample was used for dry density and engineering properties testing. The test was applied to identify the existing soil. Also, several stages of the laboratory tests were carried out with the disturbed samples. The laboratory test included (i) index properties of soil test, (ii) standard proctor compaction test, and (iii) California Bearing Ratio test (CBR) soaked and unsoaked test. Index properties of soil test included specific gravity, sieve analysis, hydrometer test, and atterberg limit used to determine the classification of soil. Before the compaction and CBR test was started, the soil sample was dried and filtered with sieve number 4 (smaller than 4.75 mm). Also, lime and brick powder were filtered with sieve number 40 (smaller than 0.475 mm). Lime and brick powder were obtained from Bogor, West Java. The additives were mixed as a percentage of 0%, 5%, 10%, and 15% of soft soil ratio by weight. In the Standard Proctor test, each mixture of the additives required 6 samples with the composition of each sample being 2 kg of soil mixed with either lime or brick powder, based on the percentage determined by each sample. Each percentage of the mixture has 6 samples where the total sample is 48 for lime and brick powder. Furthermore, the Standard Proctor test was carried out to obtain optimum moisture content (Wopt) and maximum dry density (γd max) for each mixed sample of the various proportions of lime and brick powder. The CBR test compares the resistance to penetration of the test specimen to that of a standard sample of well-graded crushed stone material using a standard-sized piston in a simple empirical approach. CBR test is one of the ways used to measure the bearing capacity of subgrades.27 Based on the optimum moisture content (Wopt) obtained from the standard Proctor test, we could use the optimum moisture content for the next stage, that is, to conduct the soaked and unsoaked CBR test with various mixtures of the additives. Each mixture of the additives required 2 samples with the composition of each sample being 5 kg of soil mixed with lime or brick powder, based on the percentage determined by each sample. So for each soaked and unsoaked CBR test, 8 samples are needed. CBR tests were carried to study the behavior and bearing capacity of the soil when mixed with the additives (lime and brick powder). After molding the soil shape, each of the soil sample used for the soaked CBR test was soaked in water for 4 days (96 hours), before the penetration test. While in the unsoaked CBR test, no soaking was carried out, but a direct penetration test. The sample was left in the mold to be used for penetration test. The piston was placed on the sample with the perforated plate and the necessary surcharge weights where put in place on the soil. Loading began at a rate of 0.05 in (12.7 mm) per minute. Test loads were recorded at eleven predefined depths of up to 0.500in as the piston entered the soil (13 mm). All these tests are also referred to as ASTM standards.28–33 Manufacturers of the dial gauge equipment used Mitutoyo analog type.\n\nStatistical analysis using 2nd order polynomial regression was done. The software used was Microsoft Excel 2019. Polynomial relation regression results show quadratic regression function and coefficient of determination (R2). The coefficient of determination is a statistical measurement that shows how much ability the independent variable has in explaining the dependent variable. A value close to 1.0 indicates a regression function that explains a lot of the function variable. This makes it a very reliable model for forecasting the future. While a value close to 0.0 indicates that the calculation fails to simulate the data accurately.\n\n\nResults and discussion\n\nThe physical and mechanical properties of the original soil can be seen in Table 1.36 The soil samples contained more than 95% fine-grains, with size smaller than 0.075 mm. Based on the results, Hambalang soils can be classified as soft soils with high plasticity (symbol MH based on the Unified Soil Classification System) due to their undrained shear strength of >25 kPa. Also, in a previous report, the Department of Settlements and Regional Infrastructure classifies Hambalang soil as fat clay because it has a high swelling potential.\n\nFigures 2 and 3 show the relations between moisture content against the dry density for the various proportions of lime and brick powder obtained from the compaction test. The figures also show the influence of lime and brick powder on the optimum moisture content of the soil.\n\nLime and brick powder have high effect on the soil's maximum dry density (MDD) in all the mixed samples. The highest is observed in the samples with 15% additive, where the value increased from 1.58 for the soil not mixed to 1.7 for the soil mixed with 15% lime and 1.68 for the soil mixed with 15% brick powder. These were obtained at optimum moisture content of 21.115% for brick powder and 21.06% for lime. Optimum moisture in the compaction test was used as a mixture in the CBR test. The MDD of the soil samples increased because lime and brick powder have relatively higher specific gravities than soil. When the proportion of lime and brick powder increases, the maximum dry density of the soil increases compared to the original soil. The increase in water content at MDD conditions can be seen in Figures 2 and 3. This can occur because of the pozzolanic reaction which causes the maximum density conditions to require a little more water.\n\nAs seen in Figure 4, the maximum dry density of the mixture of lime and brick powder is at the 15% additive level. The increase in dry bulk density (γd) was due to additional material filling the cavities in the original soil decreasing the pore number. A decrease in the incidence of an increase in soil density leads to an increase in dry density.\n\nThe CBR soaked and CBR unsoaked tests were carried out with the original soil from lime and red brick powder at predetermined levels (5%, 10%, and 15%) by observing any changes in the CBR value at the top and bottom. The relationship between the addition of lime and red brick powder to the original soil on the CBR values of soaked and unsoaked is shown in Figure 5.\n\nThe results of the test data on the discovery of CBR values that were soaked and soil that were not soaked increased with the addition of lime or red brick powder. This is because the original soil grains and additives react with one another in a process known as pozzolanization reaction. In mixed soil samples, the strength generated is determined by the strength of the brick grain and the friction between the grains, because the soil and brick grains are non-cohesive. So, the strength of the mixed soil is not due to cohesion but due to friction between grains. This finding agrees with another finding, which explained the strength of mixed soils in different cases.34\n\nThe highest CBR value of lime and red brick powder is found in the 15% mixture. The CBR-soaked result for lime has a higher value (7.58%) than that of brick powder (4.55%). While the CBR unsoaked result of red brick powder has the highest CBR value (19.2%) compared to lime (16.91%).\n\nThe CBR soaked value is smaller than the CBR unsoaked value because, at the time of immersion, the water initially fills the pore cavities. Over time, the size of the soil grains expands to their maximum when the water is saturated. In these conditions, the bonds between the soil grains become weak so that the bearing capacity of the soil decreases. This result is similiar to another finding which showed that the more saturated the soil is, the less its bearing capacity.35\n\nThe increase in CBR value is due to the cementation process, which makes the soil clump, thus increasing the binding power between the grains. This makes the pore cavity to be surrounded by a more rigid cementation material, which results in the grains becoming strong and not easily destroyed.21\n\n\nConclusions\n\nThe MDD of the soil sample increases when mixed in various proportions of lime and brick powder. The soil sample mixed with 15% of additives had the highest maximum dry density. The soaked and unsoaked CBR values increased with the variation of lime and red brick powder. The highest CBR soaked value is obtained from a lime mixture of 15%. The highest unsoaked CBR value can be obtained from a combination of red brick powder by 15%. However, this study has a very large range of variations because of the many material requirements for each test. We suggest other researchers perform the CBR test by reducing the range of variations in the additives to get firm data and using our experimental procedure in this study for further research.\n\n\nData availability\n\nZenodo: A comparative study of red brick powder and lime as soft soil stabilizer (Dataset). https://doi.org/10.5281/zenodo.5028251.36\n\nThis project contains the following underlying data:\n\n- CBR soaked and unsoaked 10(percent) Mixed with Lime.xlsx\n\n- CBR soaked and unsoaked 15(percent) Mixed with Lime.xlsx\n\n- CBR soaked and unsoaked 5(percent) Mixed with Lime.xlsx\n\n- CBR soaked and unsoaked resume value mixed percentage.xlsx\n\n- CBR soaked and unsoaked soil.xlsx\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nCompeting interests\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis research was supported by UP2M Politeknik Negeri Jakarta through the PNJ DIPA funding [184/PL3.18/SPK/2021]. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.", "appendix": "Acknowledgments\n\nThe authors would like to sincerely appreciate the Head of UP2M Politeknik Negeri Jakarta for providing support. The authors also acknowledge the Head of Laboratory of the Civil Engineering Department of PNJ for granting permission to use laboratory facilities.\n\n\nReferences\n\nShillito R, Fenstermaker L: Soil Stabilization Methods with Potential for Application at the Nevada National Security Site: A Literature Review.2014; no. 45255. Publisher Full Text\n\nWooltorton FLD: Soil Mechanics in Foundation Engineering.1973; 7(2).\n\nNegi AS, Faizan M, Siddharth DP: Soil stabilization using lime.2013; 2(2): 448–453.\n\nRoy S, Kumar Bhalla S: Role of Geotechnical Properties of Soil on Civil Engineering Structures. Resour. Environ. 2017; 7(4): 103–109. Publisher Full Text\n\nWesley LD: Geotechnical Engineering in Residual Soils. Wiley; 2010.\n\nSherwood PT: Soil stabilization with cement and lime . London: HMSO; 1993.\n\nAmu OO, Adetuberu AA: Characteristics of bamboo leaf ash stabilization on lateritic soil in highway construction. Int. J. Eng. Technol . 2010; 2(4): 212–219.\n\nDang LC, Hasan H, Fatahi B, et al.: Enhancing the engineering properties of expansive soil using bagasse ash and hydrated lime. Int. J. GEOMATE . 2016; 11(3): 2447–2454.\n\nKumar A, Kumar A, Prakash V: Stabilization of Expansive Soil with Lime and Brick Dust. Int. J. All Res. Educ. Sci. Methods . 2016; 4(9): 2455–6211.\n\nKhazaei J, Moayedi H: Soft Expansive Soil Improvement by Eco-Friendly Waste and Quick Lime. Arab. J. Sci. Eng. 2019; 44(10): 8337–8346. Publisher Full Text\n\nAl-Swaidani A, Hammoud I, Meziab A: Effect of adding natural pozzolana on geotechnical properties of lime-stabilized clayey soil. J. Rock Mech. Geotech. Eng. 2016; 8(5): 714–725. Publisher Full Text\n\nAlrubaye AJ, Hasan M, Fattah MY: Stabilization of soft kaolin clay with silica fume and lime. Int. J. Geotech. Eng. 2017; 11(1): 90–96. Publisher Full Text\n\nPhetchuay C, Horpibulsuk S, Arulrajah A, et al.: Strength development in soft marine clay stabilized by fly ash and calcium carbide residue based geopolymer. Appl. Clay Sci. 2016; 127–128: 134–142. Publisher Full Text\n\nWang FH, Zhang F, Chen YJ, et al.: A comparative study on the heavy metal solidification/stabilization performance of four chemical solidifying agents in municipal solid waste incineration fly ash. J. Hazard. Mater. 2015; 300: 451–458. Publisher Full Text\n\nB SN: Effect of Burnt Brick Dust on Engineering Properties on Expansive Soil. Int. J. Res. Eng. Technol. 2014; 03(04): 433–441. Publisher Full Text\n\nKhan R, Sonthwal VK: Soil stabilization using brick kiln dust and waste coir fibre. Int. J. Recent Technol. Eng. 2019; 8(2): 2574–2578.\n\nTang Xu Y, et al.: Investigation of the medium calcium based non-burnt brick made by red mud and fly ash: durability and hydration characteristics. Int. J. Miner. Metall. Mater. 2019; 26(8): 983–991. Publisher Full Text\n\nKumar KSR, Thyagaraj T: Comparison of lime treatment techniques for deep stabilization of expansive soils. Int. J. Geotech. Eng. 2020; 00(00): 1–19. Publisher Full Text\n\nPancar EB, Akpinar MV: Comparison of Effects of Using Geosynthetics and Lime Stabilization to Increase Bearing Capacity of Unpaved Road Subgrade. Adv. Mater. Sci. Eng. 2016; 2016. Publisher Full Text\n\nChemeda YC, Deneele D, Christidis GE, et al.: Influence of hydrated lime on the surface properties and interaction of kaolinite particles. Appl. Clay Sci. 2015; vol. 107, no. February 2019: 1–13. Publisher Full Text\n\nAndavan S, Pagadala VK: A study on soil stabilization by addition of fly ash and lime. Mater. Today Proc. . 2020; vol. 22, no. xxxx: 1125–1129. Publisher Full Text\n\nAsgari MR, Baghebanzadeh Dezfuli A, Bayat M: Experimental study on stabilization of a low plasticity clayey soil with cement/lime. Arab. J. Geosci. 2015; 8(3): 1439–1452. Publisher Full Text\n\nSharma LK, Sirdesai NN, Sharma KM, et al.: Experimental study to examine the independent roles of lime and cement on the stabilization of a mountain soil: A comparative study. Appl. Clay Sci . 2018; 152(June): 183–195. Publisher Full Text\n\nLourenço PB, Fernandes FM, Castro F: Handmade clay bricks: Chemical, physical and mechanical properties. Int. J. Archit. Herit. 2010; 4(1): 38–58. Publisher Full Text\n\nAkshatha M, Bharath M: Improvement in CBR of Black Cotton Soil Using Brick Powder (Demolition Brick Masonry Waste) and Lime. Int. J. Innov. Res. Sci. Eng. Technol. 2016; 5(9): 16848–16855. Publisher Full Text\n\nEffendi B, Kusnama AC, Hermanto: Geological Map of The Bogor Quadrangle West Java.1998; vol. Second Edi.\n\nLi T, Kong L, Liu B: The California bearing ratio and pore structure characteristics of weakly expansive soil in frozen areas. Appl. Sci. 2020; 10(21): 1–22. Publisher Full Text\n\nAmerican Standard Testing and Material (ASTM) D 4318-00: Standard Test Methods for Liquid Limit, Plastic Limit, and Plasticity Index of Soils. American Standard Testing and Material (ASTM); 2000; 8. .\n\nASTM D1883-16: Standard Test Method for California Bearing Ratio (CBR) of Laboratory-Compacted Soils.West Conshohocken: ASTM International; 2016.\n\nASTM D698-12e2, Standard Test Methods for Laboratory Compaction Characteristics of Soil Using Standard Effort (12 400 ft-lbf/ft3 (600 kN-m/m3)).West Conshohocken, PA: ASTM International; 2012.\n\nASTM D4531-15, Standard Test Methods for Bulk and Dry Density of Peat and Peat Products.West Conshohocken, PA: ASTM International; 2015.\n\nASTM D4318-17e1, Standard Test Methods for Liquid Limit, Plastic Limit, and Plasticity Index of Soils.West Conshohocken, PA: ASTM International; 2017.\n\nASTM D7928-17, Standard Test Method for Particle-Size Distribution (Gradation) of Fine-Grained Soils Using the Sedimentation (Hydrometer) Analysis.West Conshohocken, PA: ASTM International; 2017.\n\nRaheem AA, Bello OA, Makinde OA: A Comparative Study of Cement and Lime Stabilized Lateritic Interlocking Blocks. Pacific. J. Sci. Technol. 2010; 2: 11.\n\nIge JA: International Journal of Engineering Technology Research & Management Comparative Analysis of Selected Stabilization Agents for Subgrade Soil. no. 02, pp. 73–91.\n\nSalimah A, Miftah H: A comparative study of red brick powder and lime as soft soil stabilizer (Dataset) (Version 1) [Data set]. Zenodo. 2021. Publisher Full Text" }	[ { "id": "91503", "date": "10 Nov 2021", "name": "A. U. Ravi Shankar", "expertise": [ "Reviewer Expertise Pavement Materials", "Concrete Pavement" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors have conducted laboratory investigation to improve CBR of silty soil by using red brick powder and lime. The authors stabilized fine grain soil with and brick powder. The CBR values improved up 15 % addition of red brick powder. They could satisfy their objective. Not much information is generated. The reason for improvement in strength. The chemical composition of Brick Powder, Gradation etc. are missing. If it is only for pavement then only CBR improvement may not be sufficient as per new codes. Within the presented data the following pros and cons are observed. The suggested modification along with grammar check may help in improving the quality of paper.\nThe Text should be written in third person - 'I' and 'we' should not be there.\nAbstract: Statement: Soil has an important role to play in planning buildings because it supports the loads above it.\nComment: May be corrected as 'Role of soil in building construction...'.\nStatement: Soil stabilization can be defined as the process of stabilizing soil properties by chemical or physical means to improve its engineering efficiency.\nComment: Can be corrected as ‘process of modifying the soil properties....’.\nIntroduction: Statement: Therefore, it is necessary to do more research on the effect of red brick powder on soil stability. Also, lime and red brick powder are compared in this work. The impact of lime and red brick powder on the geotechnical qualities of soft soil was examined by conducting the CBR test.\nComment: Modify the sentences as ‘Also, the stabilizing effect of lime and red brick powder are compared in this work. The influence of lime and red brick powder on the geotechnical qualities of soft soil was examined by conducting the CBR test'.\nStatement: The CBR value increased because the soil structure changed from being dispersed to flocculated. Thus, in this study, lime and brick powder were used as stabilizers on soft soils.\nComment: Remove the above statements.\nStatement: In this study, the index and engineering properties of the original soil and mixed soil were tested.\nComment: Remove the term ‘original’ and may be replaced with term either ‘soil or silty soil or untreated soil’ wherever applicable in the manuscript.\nStatement: Literature review\nComment: Literature review can be combined with introduction part.\nMethods: Statement: The proportions of lime or red brick powder additives mixed together are 0%, 5%, 10%, and 15% of the original soil sample.\nComment: Can be corrected as 'The proportions of lime or red brick powder additives mixed are 0%, 5%, 10%, and 15% with the soil'.\nStatement: From the results of the laboratory tests, the soil type obtained is MH soil based on the Unified Soil Classification System (USCS). The MH soil type is a low plasticity silt soil.\nComment: Can be corrected as ‘The soil type obtained is MH (low plasticity silt) as per the Unified Soil Classification System (USCS)'.\nMaterial and sampling:\nComment: Properly described.\nExperimental technique: Statement: proctor, atterberg\nComment: Capitalize first letter as ‘Proctor’, ‘Atterberg’\nStatement: CBR, and other abbreviations\nComment: All abbreviations are to be used at the first appearance throughout the manuscript.\nResults and discussion: Statement: However, red brick powder had a significant increase of 15%.\nComment: Can be corrected as ‘However, red brick powder addition has contributed to a significant increase in CBR value (15%)'.\nStatement: Table 1\nComment: Atterberg limits, CBR need to be indicated without decimals. Moisture contentment can be represented with 1 decimal. For Parameter % sand, unit %, value 4.55%, include correction as - Parameter sand, unit %, value 4.55. Make corrections wherever applicable in the manuscript.\nStatement: Figure 2, 3 and 4\nComment: Check x and y axes titles and units and incorporate correction (uniform writing style and standard units are to be used).\nStatement: Lime and brick powder have high effect on the soil's maximum dry density (MDD) in all the mixed samples.\nComment: Instead of term ‘high effect’ use ‘significant' or 'notable effect’.\nStatement: Figure 5\nComment: Correction to be incorporated for CBR values.\nStatement: Description of Results and discussion.\nComment: Description has grammatical errors. It could be improved. Needs modification.\nConclusions: Statement: This study found a very large range of variations because of the many material requirements for each test. We suggest other researchers perform the CBR test by reducing the range of variations in the additives to get firm data and using our experimental procedure in this study for further research.\nComment: Authors need to draw conclusions on your work. Suggestions are not needed. Rewrite conclusions.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "138934", "date": "22 Jun 2022", "name": "Reginald B. Kogbara", "expertise": [ "Reviewer Expertise Stabilization/solidification of problematic soils and wastes", "subgrade soil stabilization using polymers", "characterization", "and utilization of cement-based materials." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe paper concisely describes experiments aimed at investigating the effect of lime and red brick powder on soft soil stabilization. Specifically, its use of red brick powder for soil stabilization allows for beneficial reuse of what might otherwise be a waste material for soil stabilization. Hence, the work is scientifically valid and contributes to knowledge in the area of soil stabilization. The experimental design is appropriate and the work is technically sound with sufficient details that allow replication of the work by others, and the conclusions made are supported by the results of the study.\n\nMajor Points:\nThe authors should better put the work into context by citing current literature that deal with similar investigations and highlighting the contribution of this work that is different from what was done in similar studies. For example, see Blayi et al., (2020)1; Srikanth Reddy et al., (2018)2; and Bhavsar et al., (2014)3\n\nCould the authors please state the sources of the lime and red brick powder used for the soil stabilization?\nMinor Points:\nIt would have been more helpful if compressive strength data was included to facilitate comparison with data in other studies related to the use of lime and waste brick powder for soil stabilization.\n\nThe authors should explain clearly the expression “Statistical analysis using 2nd order polynomial regression was done”, stating the specific dataset the polynomial regression was applied on. For example, was the polynomial regression done on the moisture content – dry density data?\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/10-777
https://f1000research.com/articles/11-408/v1	11 Apr 22	{ "type": "Data Note", "title": "Applicability of open science practices to completed research projects from different disciplines and research paradigms", "authors": [ "Jürgen Schneider" ], "abstract": "The purpose of this data collection was to uncover the extent to which communities have emerged that cultivate a shared understanding of open science. In a cross-sectional survey, we assessed the applicability of 13 open science practices over different disciplines and research paradigms. Focusing on completed research projects, participants were able to draw informed evaluations concerning the applicability of open science practices. The total sample is N=295 researchers, with approximately equal numbers from six broad disciplines (between 42 and 52 participants per discipline). The survey included an attention check.", "keywords": [ "Open Science", "Open Access", "Open Data", "Open Education", "Open Evaluation", "Open Methods", "Open Participation", "Open Policies", "Open Software", "Open Tools" ], "content": "Introduction\n\n“Open science” is not a new term in the repertoire of academic disciplines, it has developed over the last several decades. However, what researchers understand by open science and which open science practices they refer to in particular varies greatly between research projects. In some research projects, open science practices are closely related with aspects of the research paradigm’s philosophy of science (e.g., preregistration in critical rationalism), in other research projects, they are at odds (e.g., replicability in constructivism). Accordingly, the implementation of open science practices naturally varies in degree of implementation and stage of development. The purpose of this data collection was to reveal the extent to which subcommunities have emerged that share a common profile of implementing open science practices and how they are related to research paradigms and disciplines.\n\n\nMaterials and methods\n\nThe study was conducted as a cross-sectional survey using the survey tool formr (Arslan, Walther & Tata, 2020). In order to achieve a high ecological validity, the survey referred to the applicability of open science practices in concrete research projects instead of time periods (e.g., referring to the past year). We focused on evaluating completed research projects as participants were able to draw on their experiences from all phases of the project, which allowed them to make informed assessments of the factors that influenced research project decisions. Participants were recruited via the online access panel provider prolific.co. We used prolific’s built in filter to target researchers (“Industry Role = Researcher”). In the study description for prolific, we merely indicated that the study addressed practices in research projects; the focus on open science practices was avoided to reduce selection bias in the sample:\n\n“In this study, you will indicate whether 13 practices are potentially applicable to a research project you were conducting. The survey contains only 16 items in total.\n\nWe are looking for participants who have conducted a research project associated with one of the disciplines\n\n• Natural sciences\n\n• Engineering and technology\n\n• Medical and health sciences\n\n• Agricultural and veterinary sciences\n\n• Social sciences\n\n• Humanities and the arts”\n\nParticipants took on average 3.98 minutes (median 3.43) to answer the survey and received USD 0.85 as compensation (approx. USD 12.81 per hour on average). The first participant started on August 20 2021, the last session on March 16 2022.\n\nWe aimed for a sample distributed across all research disciplines. For this reason, we drew on the classification of research fields from the OECD Frascati Manual (OECD, 2015). For each “broad classification” (natural sciences, engineering and technology, medical and health sciences, agricultural and veterinary sciences, social sciences, humanities and the arts) we aimed for n=50 participants, which would have led to a total sample of N=300 (limit of allocated financial resources). As soon as 50 participants from a discipline finished the survey, access to the survey closed for participants from that discipline (“cell closed”). For two disciplines we exceeded the stopping rule (Natural Sciences, Social Sciences), as cells only closed after the last participant from that cell finished the survey, while further participants from that cell were still able to begin the survey (see Table 1). In addition, we were only able to recruit 42 participants for the agricultural and veterinary sciences despite several postings on prolific. This may not be surprising, since agricultural and veterinary sciences is a narrower field compared to the other classifications.\n\nOn the first page, participants agreed to the declaration of consent.\n\nOn the second page they indicated the discipline in which the research project was based regarding which they would like to answer the following questions: “Discipline. On the next page you will answer questions regarding a previous research project. To which discipline is this research project most closely related?” In a dropdown menu, participants were able to choose from all 42 second-level classifications from the OECD Frascati Manual (OECD, 2015). In using the second-level classifications, we tried to avoid inconsistent assignments to the broad classifications by the participants. After that an attention check item was displayed (see below).\n\nThe third page gave a quick instruction on how to answer the items following on the next page: “When answering the items on the next page, please think of a research project of yours that you have already completed. Regardless of whether you actually applied the practices in this research project: Which of the practices would have been potentially applicable, given all the characteristics and circumstances of the project? This includes both scientific, and practical considerations in conducting the study.”\n\nOn top of the fourth page the following question was displayed: “To what extent are the following behaviors applicable in your research project?” Which was then followed up by 13 items on open science practices (item labels see Table 2). The practices were derived and synthesized from the FOSTER Taxonomy of Open Science and nine additional expert interviews from different disciplines. On the bottom of the page we assessed the research paradigm the project was situated in: “Research paradigm. What was the project’s primary research interest and design?” with the single choice answer categories “mainly qualitative empirical”, “mainly quantitative empirical”, “explicitly mixed-methodological (equally qualitative and quantitative empirical)” and “nonempirical”.\n\nFor details on items and item statistics, see the codebook (created with the R package codebook; Arslan, 2019) in the Extended data (Schneider, 2022).\n\nParticipants had to pass an attention check at the beginning of the survey in order to be able to complete the other questions. The attention check looked as follows:\n\n“Please read the following scenario briefly and answer a question about it:\n\nA famine has broken out in your village. You and some others have been chosen to leave the village and search for food. It begins to rain heavily and soon there will be flooding. Participants in studies like this are sometimes not very attentive. We have included this question here to check if you have actually read the scenario. If you read this, leave the following question unanswered just click next.\n\nAccording to the scenario, would it be appropriate to take the raft and leave the others behind?”\n\nFollowed by a seven-point Likert scale with the ankers “absolutely no” and “absolutely yes”. The attention check was considered “passed” if nothing was marked on the seven-point Likert scale (i.e. an NA value on this item). Overall, 20 participants eligible for participation failed the attention check and were thus excluded. These participants are not included in the data set that is available for download (Schneider, 2022). They jumped to the end of the survey after failing the attention check and therefore did not complete the 13 items on the open science practices.\n\nAs a limitation regarding data validation, it should be noted that we did not target a representative sample of researchers across disciplines. For the data set, it was important that we had variance in the backgrounds of the researchers. Any analyses comparing disciplines should therefore be interpreted with caution.\n\nThe present data collection received approval from the ethics committee of the Faculty of Economics and Social Sciences at the University of Tübingen (no approval number). Participants agreed to the consent details printed below before beginning the survey.\n\n\nData availability\n\nZenodo: Applicability of open science practices to completed research projects from different disciplines and research paradigms. https://doi.org/10.5281/zenodo.6416604 (Schneider, 2022).\n\nThis project contains the following underlying data:\n\n• osc_data.RData (data set as RData-file)\n\n• osc_data.csv (data set as CSV-file)\n\nZenodo: Applicability of open science practices to completed research projects from different disciplines and research paradigms. https://doi.org/10.5281/zenodo.6416604 (Schneider, 2022).\n\nThis project contains the following extended data:\n\n• codebook.html (codebook report of survey and its items)\n\n• STROBE-checklist-v4-cross-sectional.pdf (STROBE Statement: Checklist of items that should be included in reports of cross-sectional studies)\n\n• Consent Statement.pdf (Consent Statement: Details of the Consent Statement the participants agreed to)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgements\n\nWe thank the nine interviewees from the pilot study. We acknowledge support by Open Access Publishing Fund of University of Tübingen.\n\n\nReferences\n\nArslan RC: How to Automatically Document Data With the codebook Package to Facilitate Data Reuse. Adv. Methods Pract. Psychol. Sci. 2019; 2(2): 169–187. Publisher Full Text\n\nArslan RC, Walther MP, Tata CS: formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R. Behav. Res. Methods. 2020; 52(1): 376–387. PubMed Abstract \| Publisher Full Text\n\nSchneider J: Applicability of open science practices to completed research projects from different disciplines and research paradigms. [Dataset].2022. Publisher Full Text" }	[ { "id": "137033", "date": "24 May 2022", "name": "Suzanne Dumouchel", "expertise": [ "Reviewer Expertise research infrastructures", "social sciences and humanities", "FAIR data", "EOSC", "Open Science" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe process of the survey is clearly described such as the tools that have been used and the reasoning behind them. The selection of the researchers is also well explained and the average per discipline is relevant for this kind of study. However, it could be interesting to be precise with any information regarding the geographic coverage of the researchers and their career stage. It can contribute to better understand of the OS practices. This might have been taken into account however it is not mentioned in the paper.\nIt seems particularly relevant to offer the possibility to specify the discipline and not to stay at the level of the broad classification. On this topic, further explanation of the reasoning behind the broad classification could be useful, especially to understand why \"agricultural and veterinary sciences\" are not part of natural sciences. What is the reasoning behind this?\nThe selection of the Frascati Manual seems to be relevant but more details can be provided to mention maybe other options and to explain why this one has been selected and upon which criteria?\nThis precision can be expected as well for the FOSTER Taxonomy of Open Science.\nThe role of the nine additional expert interviews is not clear enough. It is difficult for the reader to understand how practices have been synthesised from both the FOSTER Taxonomy and the expert interviews. The paper could be stronger by explaining 1) the goal and process of the interviews; 2) the selection of these experts (for instance regarding the disciplines as it is the main focus in the paper); 3) how the practices have been built from these interviews and the taxonomy. For instance, it can be interesting to highlight the potential bias or reasoning to synthesise in one way or another.\nIt is interesting to see that the survey has run between August 2020 and March 2022. Regarding the increase of knowledge and practices related to Open Science, the answers might have evolved between both. Even if it can be quite tricky to determine this aspect, it can be relevant to mention or highlight any difference if some have been noticed.\n\nLastly the reader could expect a short conclusion about the main outputs of the survey. And if the goal is to provide it in a dedicated paper, some highlights can be useful or at least it can be announced at the end of the paper.\n\nIn any case, this kind of survey is particularly relevant and should contribute to implement the OS practices in the different disciplines as well as to better identify the needs for the researchers. With these small precisions, we believe the paper (and the data collected) contributes to the OS reflexion.\n\nIs the rationale for creating the dataset(s) clearly described? Yes\n\nAre the protocols appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and materials provided to allow replication by others? Partly\n\nAre the datasets clearly presented in a useable and accessible format? Yes", "responses": [ { "c_id": "8520", "date": "18 Jul 2022", "name": "Jürgen Schneider", "role": "Author Response", "response": "Thank you very much for your constructive feedback. I will respond to your comments chronologically: We agree that information regarding the geographic coverage and their career stage would complement the data set. Unfortunately, we had to keep the survey short due to financial resources. Therefore, we don’t have these data. We agree that specifying the disciplines might be a valuable information for data users. Therefore, we have now included the disciplines in the data set as well as the Codebook. Concerning the Frascati manual, we added the following paragraph to the methods section: “The Frascati Manual is an internationally acknowledged standard on the methodology of collecting and using research and development statistics, developed by the OECD. As a standard, it is the first choice for the definition and taxonomy of research disciplines.” Concerning the FOSTER taxonomy, we added the following paragraph to the methods section: “The FOSTER taxonomy is the only taxonomy on open science that we know of. It was created as part of the FOSTER Plus project, an EU-funded project on Open Science. The goals in the project explicitly covered the generation of high quality training resources, which includes the taxonomy we use.” We agree that more information on the synthesis of the FOSTER taxonomy and the interviews would help readers understand the construction of the survey. We therefore added the following paragraph to the methods section: “Through the top-down and bottom-up approach, blind spots were mutually exposed to ensure that the broadness of open science practices are reflected in the survey. […] For the bottom-up approach, we interviewed nine experts in open science. We recruited the experts from an open science fellows program in which they served as mentors. Following the theoretical sampling approach, we recruited mentors who came from a variety of disciplines (e.g., sociology, computer science, sinology) and applied different research paradigms (qualitative, quantitative, mixed methods, theoretical). In a focused interview, interviewees were given a narrative prompt to retrospectively consider open science practices in their field: \"Please recall one of your most recently completed research projects. Thinking about the entire span of the project, from the initial idea to the completion of the project, what aspects of open science do you consider significant and how can they be exemplified in research projects?\" The interviewer then asked exmanent follow-up questions about other practices: \"Are there other aspects of Open Science that you consider significant in your research projects (i.e., potentially others as well)? If so, how could these be implemented?\". The interviewer also asked intrinsic follow-up questions to clarify individual practices mentioned. Two trained coders transcribed and segmented the interview material around each open science practices mentioned. Disagreements in the coding process were resolved through discussion throughout the coding process. With the segmented material, the coders conducted a qualitative content analysis. They abstracted the practices named by the interviewees to an equivalent level of abstraction in two stages. These practices thus obtained were finally compared and synthesized with the FOSTER taxonomy resulting in 13 items on open science practices.\" We agree that the choice of the timeframe may raise some questions. The reason for the long time frame was our desire to recruit more researchers from the broad classification of \"agricultural and veterinary sciences\". Accordingly, we have added a paragraph: “This is also the reason why the data collection is spread over a longer period of time. After the start of data collection, participants of the other broad classifications could be collected within a few weeks. Due to the repeated invitation of researchers from the agricultural and veterinary sciences, the period of data collection stretched out, unfortunately, only a few additional participants could be recruited (see codebook).” We agree that information on the output of the survey would be interesting information for the readers. We included the following paragraph in a newly created “Future analyses” section: “In the future, the data will be analyzed to answer the questions whether there are different communities in the application of open science practices and to what extent the open science practice profiles of these communities are similar or different to each other. Are there open science practices that all communities share? Are there practices for which there are particularly strong differences between communities? In addition, the role of research disciplines and research paradigms will be explored.”" } ] }, { "id": "137032", "date": "27 May 2022", "name": "Lauren Cadwallader", "expertise": [ "Reviewer Expertise Scholarly communications", "publishing", "open science." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis research aims to gain insights into open science practices in six broad disciplinary areas by asking researchers about the potential to practice open science behaviours in relation to a past project. Thirteen different open science behaviours are included, which give a comprehensive view of open science rather than just publishing related activities.\nThe rationale for the study is good and asking researchers about past projects, rather than asking them to predict future work, is an interesting and valuable approach to assessing open science practices. The range of open science practices included in the survey is broad, which should give a good insight into all activities that contribute to the aims of being open. However, one aspect I think is lacking is the extent to which researchers were mandated by their funder or institution to carry out any of these activities, which would add context to the extent to which they view certain practices as applicable.\nIn terms of the demographics of the survey sample, it is good to see balanced sample sizes in the disciplines and the inclusion of whether the researcher's work is quantitative, qualitative or mixed methods. The methodology should include more information on which geographical areas were targeted for respondents and information on career stages of the respondents if possible, as these are both factors in adoption of open science practices.\nI have concerns that the wording used in the Likert scale may have been confusing for respondents. The aim was to get researchers to report on their past research but the question about open science practices was in the present tense (\"To what extent are the following behaviours applicable...\" [emphasis added]). I'm also unsure of how to interpret the \"not at all applicable\" response - the codebook seems to suggest a \"N/A\" option was also offered but this doesn't seem to have been used by anyone. For example, were all respondents creating software but not all thought that sharing software openly applied to their project? Or were the respondents who chose \"not at all applicable\" really saying they didn't create software? Including the survey instrument (i.e. a pdf copy of the survey questions as presented to the respondents) might help with understanding this better.\nA couple of other specific points: - There is no mention of data handling with respect to GDPR rules. - The codebook gives an identical explanation for two variables - osp_sco and osp_cit. Presumable the latter is Citizen Science and not Science Communication.\nThe dataset in Zenodo is well presented and easy to use (aside from the labelling mistake mentioned above). As mentioned earlier, I would recommend adding the survey instrument to the dataset to aid understanding and also enable others to repeat this approach.\n\nIs the rationale for creating the dataset(s) clearly described? Yes\n\nAre the protocols appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and materials provided to allow replication by others? Partly\n\nAre the datasets clearly presented in a useable and accessible format? Partly", "responses": [ { "c_id": "8521", "date": "18 Jul 2022", "name": "Jürgen Schneider", "role": "Author Response", "response": "Thank you as well for the constructive comments. I will respond to your comments chronologically: We agree that it would have been interesting to have data on the mandates of funders or institutions. Unfortunately, we can't collect this data a posteriori. However, there is first evidence that mandates at the level of the research institution do not necessarily have the greatest impact on researchers' open science practices. For example, the existence of a research data policy at a research institution is not related to higher data sharing: https://doi.org/10.31234/osf.io/9yhcz We agree that information on the geographical areas and career stage of participants would complement the data set. Unfortunately, we had to keep the survey short due to financial resources. Therefore, we don’t have these data. I agree that the wording of the items in the present tense is unfortunate. Participants were encouraged to ask us questions via the survey-internal direct messaging system if any questions arose during the course of the questionnaire. The participants did indeed use this opportunity, and we received 27 direct messages. However, these inquiries were all aimed at the attention check that was placed at the beginning of the questionnaire, no questions arose about the subsequent items. We have been careful not to collect personalized data in the survey for which the GDPR would be relevant. Thank you for the pointing out the mistake in the codebook. We corrected this and uploaded a new version of the codebook." } ] } ]	1	https://f1000research.com/articles/11-408
https://f1000research.com/articles/11-807/v1	20 Jul 22	{ "type": "Research Article", "title": "Mental health burden and predictors among Egyptian healthcare workers during the COVID-19 pandemic", "authors": [ "Enas Elsherbeny", "Heba Elhapashy", "Mahmoud Ageez", "Aiman El-Saed", "Nermeen Niazy", "Enas Elsherbeny", "Mahmoud Ageez", "Aiman El-Saed", "Nermeen Niazy" ], "abstract": "Background: The coronavirus disease 2019 (COVID-19) pandemic is known to have negatively affected the physical and mental well-being of healthcare workers. Estimating such a burden in a limited-resource setting may be essential in the ongoing fight against the pandemic. This research aims to assess the prevalence of mental health problems, that is, depression and anxiety, among healthcare workers during the COVID-19 pandemic in Egypt and their associated factors and predictors. Methods: A cross-sectional study was conducted through an online survey to screen for anxiety using the Generalized Anxiety Disorder (GAD-7) score and depression using the Patient Health Questionnaire (PHQ-9) score among healthcare workers in direct or indirect contact with COVID-19 cases. Results: Analysis of participants’ responses showed that 36.7% suffered from depression, while 30.7% had moderate to severe anxiety. Independent predictors of depression were feeling unsure or dissatisfied with one’s income (AOR =8.87 and 8.51, respectively), working exclusively in private or governmental hospitals (AOR = 8.15 and 5.1, respectively), and serving in central or insurance hospitals (AOR = 2.21). Meanwhile, independent predictors of anxiety were working in governmental hospitals (AOR = 5.87), working duration from 5 to 10 years (AOR = 4.65), and suffering from other comorbidities (AOR = 2.18). Working as a nurse was a protective factor against anxiety (AOR = 0.36). Conclusions: The COVID-19 pandemic considerably affected the mental well-being of health care workers in Egypt. Income, type of hospital, working duration, and other comorbidities were the main predictors of health care workers’ mental health. Examining the mental burden of the pandemic on health care workers is important so that current and future crises can be managed better.", "keywords": [ "Keywords: Healthcare workers", "Mental health", "Anxiety", "COVID-19", "Depression", "Egypt" ], "content": "Introduction\n\nSince the outbreak of coronavirus disease 2019 (COVID-19) in China, the public has struggled against it in terms of resources. Critical resources in this battle include healthcare workers (HCWs) as well as their well-appreciated efforts all the way down. Acknowledging their work against dynamic factors in the COVID era, researchers became concerned with their mental health and the extent to which they deal with all of this. Protecting HCWs from the adverse psychological effects of the pandemic is critical (Albott et al., 2020).\n\nThere is much doubt surrounding the epidemiological features, clinical presentation, natural history, and rapid transmission character of COVID-19. All these lead to an increased occurrence of psychological problems, such as fear and anxiety, in the general population. HCWs who deal directly or indirectly with suspected or confirmed COVID cases are prone to both high-risk infection and mental health problems (Elbay et al., 2020).\n\nThroughout the world, the public is being informed about the physical effects of COVID-19 infection and ways to prevent exposure and manage its symptoms. However, the effects of this pandemic on one’s mental health have not been studied at length. Because all efforts are focused on understanding the epidemiology, transmission patterns, clinical features, and management of the COVID-19 outbreak, little attention has been paid to its impact on one’s mental health and strategies to prevent stigmatization (Javed et al., 2020).\n\nUnderstanding how the current pandemic affects mental health is also important in preparation planning. Some research papers have recently covered the psychological impact of COVID-19 and its associated mental health disorders that affect HCWs (Raudenská et al., 2020; Manchia et al., 2022).\n\nThe Egyptian healthcare system is extremely variable (governmental versus private), crowded, and generally under-resourced. Assessing the magnitude of mental health problems in such a limited-resource setting may be essential in the ongoing fight against the pandemic. Studies that measure the psychological impact of the pandemic on Egyptian HCWs remain limited. Hence, the objective of the current research is to examine the prevalence of depression and anxiety and recognize their associated factors and predictors among HCWs during the pandemic.\n\n\nMethods\n\nThis cross-sectional online survey was conducted from March to June 2021.\n\nParticipants were health care workers (HCWs) from different public and private hospitals within Mansoura City. Inclusion criteria were health care workers actively involved in patient care during COVID-19, while there were no exclusion criteria. A nonprobability sampling method was used to recruit the participants. A total of 313 respondents anonymously completed the electronic online survey.\n\nSample size calculation was based on the prevalence of anxiety and depression among HCWs during the COVID-19 pandemic (18%) (Pappa et al., 2020). The calculated sample size of this study was 227 HCWs, using the following formula (Daniel and Cross, 2018): n=Z2P1−Pd2, where Z = 1.96 for 95% confidence interval, P = expected prevalence (18%), and d = precision (margin of error) = 0.05. The sample size was increased by 10% for a total of at least 250 HCWs allowing for no responders and dropouts.\n\nThe questionnaire was designed on Google Forms and delivered through an online link among HCW groups in Egypt. Distribution of the links was done through emails and WhatsApp messages to the group members. Online data collection was the most feasible for this period because of the lockdown, and it also has the advantage of obtaining information from a large and wider geographical audience. The self-administered, anonymous data collection form was designed electronically in Arabic language using a secure and password-protected platform. The data collection form was piloted on a subsample of participants before wider dissemination; informed consent was obtained from participants at the outset of the survey. The collected data were password-protected and saved in a secured research drive available only to the research team. A predesigned self-administered questionnaire was created after wide-ranging literature analysis and based on related studies (Grace et al., 2005; Khalid et al., 2016; Lai et al., 2020; Sehsah et al., 2021). It contained the following sections: personal data including sex, age, marital status, highest educational degree, and whether the participants had children; occupational data including specialty, current job position, income, and place of work; health-related data including presence of physical/mental illness and smoking; degree of involvement in the current pandemic; and mental health assessment using the Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) Questionnaire given in Arabic language.\n\n\n\na. Patient Health Questionnaire (PHQ-9): The PHQ-9 is a screening tool used by medical professionals as a diagnostic instrument for depression, especially during the lockdown related to the COVID-19 outbreak. It is a depression module that scores each of the nine DSM-IV criteria as “0” (not at all) to “3” (nearly every day). Depression severity is classified as none (0–4), mild (5–9), moderate (10–14), moderately severe (15–19), and severe (20–27). Depression screening in adults resulted in 61% sensitivity and 94% specificity (Kroenke et al., 2001). PHQ has excellent internal consistency reliability (Cronbach’s alpha = 0.857) (AlHadi et al., 2017).\n\nb. Generalized Anxiety Disorder (GAD-7) (Mossman et al., 2017): The GAD-7 is a mental health evaluation model aimed at anxiety severity. It is a questionnaire administered to patients in the clinical environment. The subject is prompted to recall their behavior in the past two weeks, and seven criteria are accompanied by a scale describing the frequency of anxiety symptoms exhibited two weeks before evaluation. The scale consists of “Not at all” (0 points), implying that the subject has not experienced anxiety symptoms in the two-week period; “Several days” (1 point), meaning the subject has experienced symptoms on some days (seven or less); “More than half the days” (2 points), in which the subject has experienced symptoms for more than seven days; and “Nearly every day” (3 points), implying that symptoms were experienced almost every day for two weeks. Each of the seven questions can be rated from 0 to 3 based on the scale introduced above. Therefore, the overall GAD-7 score ranges between 0 and 21 (0 - no anxiety, 21 - severe anxiety). GAD-7 has excellent internal consistency reliability (Cronbach’s alpha = 0.79–0.91) (Williams, 2014). The Arabic version was validated and had acceptable psychometric properties (AlHadi et al., 2017).\n\nEthical approval was obtained from the Institutional Research Board, Faculty of Medicine, Mansoura University (reference number R.21.12.1567.R1.R2) on 25 January 2021. The participants provided written informed consent electronically after being briefed on the purpose of the study and before data were collected. Those who agreed to participate completed the submission process. The data were kept confidential in accordance with the revised Helsinki Declaration of Biomedical Ethics.\n\nStatistical analysis was performed using Statistical Package for Social Sciences (SPSS) version 20 (IBM, SPSS Statistics, New York, USA). Descriptive analysis was adopted to present summary statistics such as mean, median, standard deviation (SD), and interquartile range (IQR) for numerical variables using significance tests including the Mann–Whitney U test (for independent samples). Qualitative data were expressed using frequencies and percentages, while chi-square test was used to examine statistical associations. A P-value of < 0.05 was considered statistically significant. Binary stepwise logistic regression analysis was utilized to predict independent variables of depression and anxiety. Significant predictors in univariate analysis were entered into the regression model utilizing forward Wald method/Enter. Adjusted odds ratios and their 95% confidence interval were calculated.\n\n\nResults\n\nA total of 313 HCWs were included in the current analysis. Only the fully completed forms were delivered to the researchers and used in the analysis so there is no information about participants who may have withdrawn. Table 1 shows that 36.7% of HCWs during the COVID-19 pandemic suffered from depression as diagnosed by PHQ-9. Depression severity varied from moderate (20.1%) to moderately severe and severe (8.3% for both). This caused difficulty for 89.1% of the participants to work, take care of things at home, or even get along with other people, which varied from “somewhat difficult,” “very difficult” to “extremely difficult” (29.0%, 37.0%, and 23.2% respectively). Similarly, the GAD-7 questionnaire revealed that 30.7% suffered from anxiety with nearly equal percentages for moderate and severe degrees. For 85.3% of the participants, anxiety led to difficulty performing work, taking care of things at home, or even getting along with other people, with degrees varying from “somewhat difficult,” “very difficult,” to “extremely difficult” (31.3%, 38.0%, and 16.0%, respectively).\n\nAs shown in Table 2, the mean age of HCWs was 32.1+7.7 years with nearly half of them aged 30 to 40. The majority were females (78.3%), married (70.9%), had children (72.5%), and from urban areas (59.3%), with only 19.2% satisfied with their income. Approximately 2.2% of the HCWs were smokers, and 21.7% had one or more comorbidities, mainly hypertension and diabetes. Bivariate analysis was performed to identify demographic, behavioral, and health factors associated with depression or anxiety during the COVID-19 pandemic (Table 2). Depression was more frequent in females than males (40.0% vs. 25.0%, p = 0.023) and those with hypertension, diabetes, and other comorbidities (p-value reached significance only with other comorbidity). Meanwhile, depression was less frequent among those satisfied with their income (8.3% compared to >40% in other groups). Anxiety was more frequent among those with hypertension, diabetes, and other comorbidity (p = 0.029, p = 0.010, and p = 0.001, respectively) but negatively associated with number of children (p = 0.018).\n\n* Only 172 participants completed the question of residence.\n\nRegarding occupational characteristics (Table 3), about half of the participants (52.4%) were nurses. The majority worked in governmental health sectors (71.6%) and insurance hospitals (55.9%) and were directly exposed to COVID-19 as frontline HCWs (59.1%). More than one-third (37.5%) had worked for more than 10 years. Depression was frequent among HCWs within governmental sectors (40.6%) and insurance hospitals (4.9%) and with indirect exposure to COVID-19 patients (46.1%) with statistically significant differences compared to other groups with p values 0.004, 0.017, and 0.004 respectively. Similarly, anxiety was more prevalent among technicians and other HCWs (46%), private-sector HCWs (34%), and HCWs with career durations ranging from 5 to 10 years (43.4%) with statistically significant differences compared to other groups.\n\nMultivariate analysis was performed to identify independent predictors of depression and anxiety (Table 4). Independent predictors of depression were being unsure or dissatisfied with one’s income (AOR = 8.87 and 8.51, respectively), working only in private or governmental hospitals (AOR = 8.15 and 5.1, respectively), and employed in central or insurance hospitals (AOR = 2.21). Meanwhile, independent predictors of anxiety were working in governmental hospitals (AOR = 5.87), working duration from 5 to 10 years (AOR = 4.65), and suffering from other comorbidities (AOR = 2.18), while working as a nurse was identified as a protective factor against anxiety (AOR = 0.36).\n\n* Multivariate logistic regression was done using backward elimination of all variables included in univariate analysis, with p-value < 0.1. OR, odds ratio; 95% CI, 95% confidence interval.\n\nA detailed description of PHQ-9 items to assess depression severity (Table 5) showed that through several days of the week, more than half of the participants felt depressed or little pleasure with activities (59.1% and 54.6%, respectively). Approximately half of them felt tired or had little energy (52.4%), suffered from poor appetite or overeating (48.2%), and had trouble falling or staying asleep or sleeping excessively (47%). Analysis of the seven GAD-7 questionnaire items revealed that through several days of the week, 58.1% felt nervous, anxious, or on edge, 52.1% worried excessively about different things, 44.4% were unable to stop or control worrying, and 43.8% had trouble relaxing.\n\n\nDiscussion\n\nThe current study investigated 313 HCWs in different hospitals during the COVID-19 pandemic to assess the prevalence and identify the predictors of depression and anxiety among them. Analysis of participants’ responses showed that 36.7% of HCWs suffered from depression during the COVID-19 pandemic as diagnosed by PHQ-9. The severity of depression varied from moderate (20.1 %) to moderately severe and severe (8.3% for both). Similarly, the GAD-7 questionnaire responses revealed that 30.7% suffered from anxiety with nearly equal distributions for moderate and severe degrees. This was consistent with Aoun et al. (2020), an Egyptian study, which found 27.4% of HCWs had depression while 23.6% had moderate to severe anxiety during the COVID-19 pandemic in the Middle East. This also agrees with Pappa et al.’s findings in their systematic review of 13 studies, which identified prevalence rates of 22.8% for depression and 23.2% for anxiety (Pappa et al., 2020). While earlier studies found higher prevalence, 80.7% of physicians reported varying degrees of psychological distress (Sehsah et al., 2021) from 61% (Que et al., 2020) to 71.5% (Lai et al., 2020) among doctors in China. This variance in prevalence rates may be due to the variability of the study locations and time lapses since the start of the pandemic. This emphasizes the need for proper mental health screening for HCWs during the COVID-19 outbreak (Pappa et al., 2020; Chung JPY and Wai-Song, 2020).\n\nTo achieve the second study objective, a bivariate analysis was conducted (Table 2). Regarding demographic, behavioral, and health factors associated with mental health outcomes, depression was more frequent in females and those with hypertension, diabetes, and other comorbidities. Meanwhile, depression was less prevalent among those satisfied with their income. Also, while anxiety was more frequent among those with hypertension, diabetes, and other comorbidities, it was negatively associated with number of children. This is consistent with studies that have found a higher prevalence of anxiety among females (Aoun et al., 2020; Lai et al., 2020; Pappa et al., 2020). Other studies found that younger participants were more prone to psychological distress, which was not consistent with our results, as age was not an associated factor. In addition, Sehsah et al. found being currently unmarried, having no children, suffering from a chronic illness, and having only an MBBCh degree as associated factors. This conflict may be due to time lapse issues, as it was assumed at the start of the pandemic that all ages would be affected equally with infection, or the start of obligatory vaccination for all workers.\n\nThe current study reported the following occupational factors that favor the occurrence of depression: working in governmental sectors and insurance hospitals, being indirectly exposed to COVID-19 patients (Sehsah et al., 2021), having only MBBCh degree, currently working in Egypt, and with short (<15 years) work duration.\n\nThis study also performed multivariate analysis to identify independent predictors of depression and anxiety (Table 4): being unsure or dissatisfied with one’s income, employed only in private or governmental hospitals, and working in central or insurance hospitals. Fear of income loss because of being a COVID patient may explain this result. Furthermore, working in governmental hospitals from 5 to 10 years and suffering from other comorbidities were independent predictors of anxiety; meanwhile, working as a nurse was a protective factor against anxiety. The lack of personal protective equipment in Egyptian governmental hospitals during the pandemic (United Nations Industrial Development Organization (UNIDO), 2020) may explain why workers in this type of hospital suffer from anxiety or depression. People with comorbidities are more prone to contract COVID infection, making them more anxious than others.\n\nPsychological distress predictors differed across studies. Lai et al. (2020), in a Chinese study conducted with 1,257 HCWs in 34 hospitals, found that hospitals being in the province where the pandemic began and the position of HCW as frontline workers were independent risk factors affecting HCWs’ mental health outcomes. Meanwhile, another Egyptian study identified the following predictors: being female, having chronic disease, serving as frontline workers, and having fewer than 15 years of job experience (Sehsah et al., 2021).\n\nRecent evidence from a rapid review of the impact of COVID-19 on the mental health of HCWs, as implications for supporting psychological well-being across 14 databases, suggested that female nurses with close contact with COVID-19 patients may have the most to gain from efforts aimed at supporting psychological well-being (De Kock et al., 2021).\n\nDespite inconsistencies in the findings of previous studies, no groups should be ignored when addressing psychological well-being. While psychological interventions targeting higher resilience among individuals may be beneficial, it is evident that to build a resilient workforce, occupational and environmental factors must be addressed.\n\nTherefore, we recommend further research and analysis of the psychological aspects of HCWs to alleviate their stress. Moreover, psychiatrists should be involved and closely screen all HCWs to improve mental health outcomes. Further studies should also be conducted to investigate the long-term psychological impact of the COVID-19 pandemic.\n\nThe current study used well-standardized, validated tools to screen HCWs for mental health disorders as well as examine multiple modifiable and nonmodifiable variables using univariate and multivariate analyses. Nevertheless, some limitations should be acknowledged. One is that the cross-sectional design of the study did not allow for an analysis of causal relationships and long-term impacts of the pandemic; another is that the self-selected nonprobability sample may compromise generalizability.\n\n\nConclusion\n\nThe COVID-19 pandemic significantly affected the mental well-being of HCWs in Egypt, the main predictors of which were income, type of hospital, working duration, and other comorbidities. Evaluating the pandemic’s mental burden on HCWs is important to better manage the current pandemic and future crises of a similar nature.\n\n\nData availability\n\nHarvard Dataverse: Replication Data for: Mental Health Burden and Predictors among Egyptian Healthcare Workers during the COVID-19 Pandemic, https://doi.org/10.7910/DVN/QM837K (El Sherbeny, 2022a).\n\nThis project contains the raw data file.\n\nHarvard Dataverse: Replication Data for: Mental Health Burden and Predictors among Egyptian Healthcare Workers during the COVID-19 Pandemic, https://doi.org/10.7910/DVN/FEJURS (El Sherbeny, 2022b).\n\nThis project contains the blank questionnaire and the data key.\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "Acknowledgements\n\nThanks to all health care worker for sharing in this study. As well as Research Ethics Committee of the Faculty of Medicine at Mansoura University for its cooperation.\n\n\nReferences\n\nAlbott CS, Wozniak JR, McGlinch BP, et al.: Battle Buddies: Rapid Deployment of a Psychological Resilience Intervention for Health Care Workers During the COVID-19 Pandemic. Anesth Analg. 2020 Jul; 131(1): 43–54. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAlHadi AN, AlAteeq DA, Al-Sharif E, et al.: An arabic translation, reliability, and validation of Patient Health Questionnaire in a Saudi sample. Ann Gen Psychiatry. 2017 Dec; 16(1): 1–9. Publisher Full Text\n\nAoun A, Rahman YA, Mostafa NM, et al.: Impact of the covid-19 pandemic on health care workers? mental health: a cross-sectional study. Allied J Med Res. 2020; 4(1): 57–62.\n\nChung JPY, Wai-Song Y: Staff mental health self- assessment during the COVID-19 outbreak. East Asi Arch Psy. 2020; 30: 34. Publisher Full Text\n\nDaniel WW, Cross CL: Biostatistics: a foundation for analysis in the health sciences. Wiley;2018 Nov 13.\n\nDe Kock JH, Latham HA, Leslie SJ, et al.: A rapid review of the impact of COVID-19 on the mental health of healthcare workers: implications for supporting psychological well-being. BMC Public Health. 2021 Dec; 21(1): 1–8. Publisher Full Text\n\nElbay RY, Kurtulmuş A, Arpacıoğlu S, et al.: Depression, anxiety, stress levels of physicians and associated factors in Covid-19 pandemics. Psychiatry Res. 2020 Aug 1; 290: 113130. PubMed Abstract \| Publisher Full Text\n\nEl Sherbeny E: “Replication Data for: Mental Health Burden and Predictors among Egyptian Healthcare Workers during the COVID-19 Pandemic” [Dataset].2022a. Harvard Dataverse, V2. Publisher Full Text\n\nEl Sherbeny E: “Replication Data for: Mental Health Burden and Predictors among Egyptian Healthcare Workers during the COVID-19 Pandemic”.2022b. Harvard Dataverse, V2. Publisher Full Text\n\nGrace SL, Hershenfeld K, Robertson E, et al.: The occupational and psychosocial impact of SARS on academic physicians in three afected hospitals. Psychosomatics. 2005; 46: 385–391. PubMed Abstract \| Publisher Full Text\n\nGrover S, Dua D, Sahoo S, et al.: Why all COVID-19 Hospitals should have Mental Health Professionals: the importance of mental health in a worldwide crisis!. Asian J Psychiatr. 2020; 51: 102147. PubMed Abstract \| Publisher Full Text\n\nJaved B, Sarwer A, Soto EB, et al.: The coronavirus (COVID-19) pandemic's impact on mental health. Int J Health Plann Manage. 2020 Sep; 35(5): 993–996. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKhalid I, Khalid TJ, Qabajah MR, et al.: Healthcare workers emotions, perceived stressors and coping strategies during a MERS-CoV outbreak. Clin Med Res. 2016; 14: 7–14. Publisher Full Text\n\nKroenke K, Spitzer RL, Williams JB: The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep; 16(9): 606–613. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLai J, Ma S, Wang Y, et al.: Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Netw Open. 2020; 3: e203976–e203976. PubMed Abstract \| Publisher Full Text\n\nManchia M, Gathier AW, Yapici-Eser H, et al.: The impact of the prolonged COVID-19 pandemic on stress resilience and mental health: A critical review across waves. Eur Neuropsychopharmacol. 2022 Feb; 55: 22–83. Epub 2021 Oct 29. Publisher Full Text \| PubMed Abstract \| Free Full Text\n\nMossman SA, Luft MJ, Schroeder HK, et al.: The Generalized Anxiety Disorder 7-item scale in adolescents with generalized anxiety disorder: Signal detection and validation. Ann Clin Psychiatry. 2017; 29(4): 227–234A.\n\nPappa S, Ntella V, Giannakas T, et al.: Prevalence of depression, anxiety, and insomnia among healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. Brain Behav Immun. 2020 Aug 1; 88: 901–907. PubMed Abstract \| Publisher Full Text\n\nQue J, Le Shi JD, Liu J, et al.: Psychological impact of the COVID-19 pandemic on healthcare workers: a cross-sectional study in China. Gen Psychiatr. 2020; 33: e100259. PubMed Abstract \| Publisher Full Text\n\nRaudenská J, Steinerová V, Javůrková A, et al.: Occupational burnout syndrome and post-traumatic stress among healthcare professionals during the novel coronavirus disease 2019 (COVID-19) pandemic. Best Pract Res Clin Anaesthesiol. 2020 Sep; 34(3): 553–560. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nSehsah R, Gaballah MH, El-Gilany AH, et al.: Psychological distress among Egyptian physicians during COVID-19 pandemic. Int Arch Occup Environ Health. 2021 May; 94(4): 731–740. PubMed Abstract \| Publisher Full Text\n\nUNIDO:Coronavirus: The Economic Impact. the economic impact – 10 July 2020. Retrieved March 30, 2022. Reference Source\n\nWilliams N: The GAD-7 questionnaire. Occup Med. April 2014; 64(3): 224. Publisher Full Text" }	[ { "id": "156635", "date": "25 May 2024", "name": "Prof. Dr. Amal El Safty", "expertise": [ "Reviewer Expertise Occupational and Environmental Medicine", "Clinical Toxicology" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe research aims to assess the prevalence of depression and anxiety, among healthcare workers during the COVID-19 pandemic in Egypt and their associated factors and predictors, using the Generalized Anxiety Disorder (GAD-7) score and the Patient Health Questionnaire (PHQ-9) score. The research concluded that income, type of hospital, working duration, and suffering from other comorbidities were the main predictors of HCW’s mental health. The study design is appropriate and it is advised to point to the round number of targeted HCW either online or what’s app to calculate the response rate The research methods and analysis are clearly explained and allow replication. The conclusions are adequately supported by the results. It is very interesting and relevant topic that was clearly addressed by the authors.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-807
https://f1000research.com/articles/11-806/v1	20 Jul 22	{ "type": "Research Article", "title": "The gaming problem: A latent class analysis of DSM-5 criteria for Internet Gaming Disorder in a non-clinical sample", "authors": [ "Jodie Raybould", "Dylan Watling", "Michael Larkin", "Richard Tunney", "Dylan Watling", "Michael Larkin", "Richard Tunney" ], "abstract": "Background: In this study we aimed to test whether suggested DSM-5 criteria for Internet Gaming Disorder (IGD) share a similar latent structure to formally recognised addiction. Methods: We used latent class analysis on a dichotomous measure of IGD. The data was collected from a convenient general population sample (500) and a targeted gaming forum sample (236).\nResults: We found a four or six-class model to be most appropriate, ranging from ‘casual/non-gamer’ to ‘potentially disordered’ with increasing symptom severity. The majority of ‘potentially disordered’ gamers (5+ criteria) were found to be 18-30 years old, and no ‘potentially disordered’ gamers were over 42. Conclusions: The results suggest that gaming may share a similar latent structure to established addictions, with adolescents and young adults being more at risk. Studies replicating these results would be beneficial, with further emphasis on a critical evaluation of the criteria and symptom cut-off point.", "keywords": [ "Gaming", "Internet Gaming Disorder", "Pathological Gaming", "Latent Class Analysis", "Addiction", "Behavioural Addiction" ], "content": "Abbreviations\n\nAIC: Akaike Information Criteria\n\nBIC: Bayesian-Information Criteria\n\nDSM: Diagnostic and Statistical Manual\n\nGD: Gaming Disorder\n\nICD: International Classification of Diseases\n\nIGD: Internet Gaming Disorder\n\nLR: Likelihood Ratio\n\n\nIntroduction\n\nGaming Disorder (GD) was recently recognised by the World Health Organization (2020) as a behavioural addiction in the eleventh edition of the International Classification of Diseases (ICD-11), while the apparently synonymous Internet Gaming Disorder (IGD) is not recognised diagnostically, but was included in the Diagnostic and Statistical Manual (DSM-5) to foster research in the area (American Psychiatric Association, 2013).\n\nA comparison of both systems in Mexico found that prevalence estimates of the DSM were almost twice as high as the ICD (Borges et al., 2021). Similarly, Jo et al. (2019) found that while all ICD-11 cases were found by the DSM-5, not all DSM-5 cases were found by the ICD-11. This could suggest that the current DSM-5 criteria are too inclusive, or that the ICD-11 criteria are not sensitive enough. We have focused this study on the DSM-5 criteria, since evidence has shown the measure to have robust psychometric properties (Lemmens et al., 2015). In addition, Aarseth et al. (2017) highlighted a number of concerns with the inclusion of GD in the ICD-11.\n\nPrevious studies on gaming have been inconsistent in classification, and results on prevalence, course, treatment, and biomarkers have been inconclusive (Petry et al., 2014). Many researchers believe that gaming can become problematic (Charlton & Danforth, 2007; Gentile, 2009), while some are cautious (James & Tunney, 2017) and do not regard IGD as a genuine behavioural addiction. Some of the concerns highlighted by Aarseth et al. (2017) around gaming in the ICD-11 are relevant to the IGD, and these suggest that the introduction of gaming in any diagnostic manual is premature. In fact, Przybylski and Weinstein (2019) suggested that disordered gaming may actually be a symptom of a different underlying issue.\n\nLatent class analyses help researchers to determine the number and type of classes a potential disorder may be split into, however the results are generally a function of the sample characteristics, and so may not be representative of ‘definite’ classes. Despite this, we can examine the classes found across several studies and see that research on problem gambling typically reports a three- (Chamberlain et al., 2017; James et al., 2016; McBride et al., 2010) or four-class pattern (Kong et al., 2014; Xian et al., 2008), with increasing severity between classes. Similarly, substance use has been found to fit a three-class (Cohn et al., 2017; Evans et al., 2020; Henry & Muthen, 2010; Safiri et al., 2016), or four-class model (Morean et al., 2016; Yu et al., 2018), categorised by severity. Interestingly, Deleuze et al. (2015) investigated both behavioural and substance addiction and found three theoretical subgroups. These included addiction-prone individuals, at-risk users, and not-prone individuals. They noted that although only a small sample of participants reported gaming, it was associated with loss of control and negative outcomes over half of the time.\n\nPrevious research into IGD has found a similar three-class model (Lemmens et al., 2015; Peeters et al., 2019), with Peeters et al. (2019) suggesting that the DSM-5 criteria could be helpful in identifying what they called ‘problematic’ gamers. However, they note that a strict cut-off point could lead to false positives. In contrast, Myrseth and Notelaers (2018) found a five-class model using the Gaming Addiction Scale-Adolescents. Despite this, Deleuze et al. (2017) determined in their study that a two-class system was more able to distinguish between ‘problematic’ and ‘regular’ gamers. This dichotomous outcome hints at gaming being different to established addiction disorders and suggests a need for more research into how gaming compares to formally recognised addictions.\n\nThe listed studies either used a small sample, did not include adults, or used non-DSM criteria. Although Clement (2021) reported that most gamers in the UK during 2019 were young adults (16-24), a significant number were older. In fact, 52% aged 25-34 were identified as gamers, 36% aged 35-44, and 40% aged 45-54. This would suggest that including a range of ages in gaming analysis could be beneficial.\n\n\nMethods\n\nUsing data collected from a cross-sectional online survey we conducted latent class analysis of DSM-5 criteria for IGD. Data was collected from a sample of adults (18+) to provide evidence towards whether IGD has a similar class structure to established addictions.\n\nFive-hundred participants from the general population were recruited using convenience sampling through prolific.com in return for £7.50 (US$10.02). There were 244 females, 250 males, and six selected the option ‘other’. The average age was 29.67 years (sd = 10.04). A further 236 participants were recruited from online gaming forums (Discord and Reddit). Eighty-two were female, 139 were male, seven selected ‘other’, and five did not answer. The average sample age was 25.41 years (sd = 6.52).\n\nPotentially problematic symptoms associated with gaming were measured using nine dichotomous (Yes/No) items from the IGD scale (Lemmens et al., 2015), based on the diagnostic criteria of IGD described in the DSM-5 appendix. The survey was hosted at Qualtrics.com as part of a preregistered study (Raybould & Tunney, 2020) that gained ethical approval from the Aston University ethics committee. The targeted gamer sample also completed the IGD questions at Qualtrics.com in a study approved by Aston University.\n\nWe conducted latent class analysis on the samples separately using poLCA in RStudio (Linzer & Lewis, 2011), and then combined samples to examine IGD distribution across non-gamers, casual gamers, and dedicated gamers as a whole. Following this, we analysed the relationship between age and gaming using regression and descriptive statistics.\n\nEthical approval [Ref: 1598] was granted by the Aston University ethics committee. All methods were carried out in accordance with relevant guidelines and regulations. Written informed consent was obtained from all participants.\n\nAn earlier version of this article can be found on Research Square (doi: 10.21203/rs.3.rs-1003239/v1).\n\n\nResults\n\nLatent class analysis of the separate samples (Tables 1 & 2) suggested a two-, four-, or five-class model in the general population, and a two-, four- or six-class model in the gaming sample. The lowest Bayesian-Information Criteria (BIC), Akaike Information Criteria (AIC), and Likelihood ratio (LR) indicated different models, suggesting high model uncertainty.\n\nWe then compared the distribution of participant responses (Figure 1) and found left-skewed results for both samples, with a more normal distribution in the gamers. This suggests that a large number of the general population were casual/non-gamers, while most of the gaming sample scored 2-3 checklist items. Interestingly, participants scoring 5+ were similar in both samples, suggesting an equal share of potential candidates for diagnosis (Raybould et al., 2022).\n\nWe repeated class analysis in the combined sample, testing model fit up to six classes since the BIC was consistently larger (Table 3). The three- and five-class models failed to reach significance, whereas the two-, four-, and six-class models were significant. The lowest BIC indicated a four-class model, however the lowest AIC and LR suggested six-classes. We therefore analysed both in more detail (Table 4).\n\nA ‘casual/non-gamer’ class (1) with low likelihood of symptoms, and ‘potentially disordered’ class with high likelihood of all symptoms (4/6) was present in both models. In the four-class model we found a group who are more likely than not to be preoccupied with gaming and use games to escape (2: ‘mild gamer’), and a group who are additionally likely to be unable to stop and have lost interest in other hobbies (3: ‘at-risk’). Similarly, the six-class model included class 2 ‘mild gamers’, and ‘at-risk’ gamers as class 4. In addition, we found class 3 ‘moderate gamers’ who are likely to be preoccupied, gaming to escape, and have withdrawal, and class 5 ‘borderline’ gamers who are likely to be preoccupied, increasing play, playing despite life impact, lying and gaming to escape. Averaged probability scores suggest a potential path of increasing severity in the four-class (1 – 0.036; 2 – 0.290; 3 – 0.434; 4 – 0.755), and six-class model (1 – 0.033; 2 – 0.268; 3 – 0.399; 4 – 0.476; 5 – 0.604; 6 – 0.850). To check the validity of this we asked R to predict participant class (Tables 5 and 6), and cross-tabulated predictions against IGD scores (Table 7).\n\nParticipant class predictions for a four-class latent structure.\n\nParticipant class predictions for a six-class latent structure.\n\nAge related to IGD Score (F1,735 = 68.373, R2 = .085, p = .000), and accounted for 9% of symptom variation. We found that 15.65% of participants aged 18-20 selected 5+ criteria, compared to 13.75% aged 21-30, 8.28% aged 31-40, 4.44% aged 41-50, and 0% over 50. Further analysis on average results by age found that participants 18-20 were more likely to have mild symptoms and a higher mean IGD score (Table 8).\n\nDespite this, 71.43% (four-class) and 63.64% (six-class) of ‘potentially disordered’ gamers were over 21, while only 17.14% (four-class) and 14.63% (six-class) were over 30. There were none over the age of 42. This suggests that while some older adults display potentially disordered gaming, young adults appear more at risk.\n\n\nDiscussion\n\nThe criteria for IGD appears to have a four- or six-class structure ranging from ‘casual/non-gamers’ to ‘potentially disordered’ with increasing severity, suggesting that IGD may be presenting in a similar manner to established addictions. A four-class model was identified in both the combined and separate sample analysis; however, a six-class model may offer more nuance.\n\nWe additionally found that most potentially disordered gamers were under 30 years old, and none were over 42. Additionally, mean IGD scores continued to decrease with age, reaching as low as 0.26 in those over 51. Lemmens et al. (2015) also found that 31-40 year olds scored significantly lower than young adults and adolescents, which may suggest that adolescents and young adults are more at risk. Despite this, gaming is a new activity, with the first home consoles introduced in the 1970s. Contemporary gaming is very different from these simple arcade-style games, and Olson et al. (2011) reported that younger adults were more likely to use new technology, specifically computer/video games than older adults. Since the apparent addictive nature of gaming has only emerged recently it is therefore possible that future studies will find more potentially disordered gamers among older participants who have had more exposure to ‘modern’ videogaming from a young age.\n\nIn exploring the current DSM-5 symptom criteria, relationship issues were less than 50% likely in all classes except model-six ‘potentially disordered’ gamers (57%), suggesting it may not be an appropriate criterion. However, without additional information on relationships we cannot test this result. Similarly, lying, and increased involvement were both less than 50% likely for low-moderate classes, but at least 70% likely in ‘borderline’ or ‘potentially disordered’ gamers. These may therefore be signs of maladaptive gaming. In contrast, preoccupation and gaming to escape were over 50% likely in all but the ‘casual/non-gamer’ class and therefore may be facets of gaming generally rather than an indication of potentially disordered use.\n\nWithdrawal symptoms were found to be 100% likely in the ‘moderate gamer’ and ‘potentially disordered’ class (six-class), suggesting a group of non-clinical gamers who experience withdrawal. Despite this, Kaptsis et al. (2016) found the evidence on withdrawal in behavioural addiction was underdeveloped, and symptoms were reported in less than 50 participants across five studies. They noted that withdrawal in IGD can be mistaken for reactions to imposed deprivation, and many studies did not specify the expected withdrawal symptoms proposed by the DSM-5. Further to this, Orford et al. (1996) reported that emotional withdrawal in gambling did not significantly contribute to maintaining the addiction, while Rosenthal and Lesieur (1992) found that some abstaining gamblers experienced symptoms which did not correlate with substance abuse withdrawal. Studies relying on a participant’s understanding of withdrawal therefore may not accurately reflect potential symptoms.\n\nIn our sample we found a suggested prevalence of 2.98 – 4.74% of ‘potentially disordered’ gamers. There appears to be a lot of variation in estimated prevalence rates for IGD, (0.7-27.5% - Mihara and Higuchi (2017); 0.7%-15.6% - Feng et al. (2017); 1.6% - Müller et al. (2015); 3.1% - Ferguson et al. (2011); 3.7% - Kuss et al. (2013)) however our results were in the expected range. Despite this, the prevalence rates of participants endorsing 5+ criteria were 11.82%, suggesting that the current cut-off may be too low. In fact, when amending this to 7+ symptoms we found a prevalence of 3.26%.\n\nFuture research into IGD should continue to build evidence on whether gaming is addictive, with an emphasis on critically evaluating the suggested criteria. Additionally, research comparing online and offline play, and various game types, may help to explain the different findings between studies. Subtle differences may arise as the social benefits of online multiplayer are likely to be significantly different from local multiplayer. Similarly, while most online games involve multiplayer competitive elements, offline gaming is often single-player storylines.\n\n\nData availability\n\nOpen Science Framework: Impulsivity, Scarcity and Maladaptive Choice Behaviours Project, https://doi.org/10.17605/OSF.IO/WXJUM (Raybould et al., 2022).\n\nThis project contains the following underlying data:\n\n- LCA Dataset.xlsx\n\n- Full Survey Dataset.xlsx\n\nOpen Science Framework: What are the Relationships between Impulsivity, Scarcity and Addiction?, https://doi.org/10.17605/OSF.IO/WXJUM (Raybould et al., 2022).\n\nThis project contains the following extended data:\n\n- Grisk_SocialStatus_Questions.pdf\n\n- 9. AUDIT.pdf\n\n- 6,8. MacArthur Scale of Subjective Social Status.pdf\n\n- 5,7. NSSEC.pdf\n\n- 16. GMQ-F.pdf\n\n- 15. Debt Questions.pdf\n\n- 14. TFEQ-18.pdf\n\n- 13. DSM-V Criteria for Gaming Disorder.pdf\n\n- 12. PGSI.pdf\n\n- 10. CDS5.pdf\n\n- 11. DUDIT.pdf\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "References\n\nAarseth E, Bean AM, Boonen H, et al.: Scholars’ open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal.2017; 6: 267–270. PubMed Abstract \| Publisher Full Text\n\nAmerican Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders Fifth Edition: DSM-5. Washington:American Psychiatric Publishing;2013.\n\nBorges G, Orozco R, Benjet C, et al.: (Internet) Gaming Disorder in DSM-5 and ICD-11: A Case of the Glass Half Empty or Half Full: (Internet) Le trouble du jeu dans le DSM-5 et la CIM-11: Un cas de verre a moitie vide et a moitie plein. Can J Psychiatry. 2021; 66: 477–484. PubMed Abstract \| Publisher Full Text\n\nChamberlain SR, Stochl J, Redden SA, et al.: Latent class analysis of gambling subtypes and impulsive/compulsive associations: Time to rethink diagnostic boundaries for gambling disorder? Addict Behav. 2017; 72: 79–85. PubMed Abstract \| Publisher Full Text\n\nCharlton JP, Danforth ID: Distinguishing addiction and high engagement in the context of online game playing. Comput Hum Behav. 2007; 23: 1531–1548. Publisher Full Text\n\nClement J: Gaming penetration in the United Kingdom (UK) 2013-2019, by demographic group 2021.Retrieved 10/03/2021. Reference Source\n\nCohn A, Johnson A, Pearson J, et al.: Determining non-cigarette tobacco, alcohol, and substance use typologies across menthol and non-menthol smokers using latent class analysis. Tob Induc Dis. 2017; 15, 5. PubMed Abstract \| Publisher Full Text\n\nDeleuze J, Nuyens F, Rochat L, et al.: Established risk factors for addiction fail to discriminate between healthy gamers and gamers endorsing DSM-5 Internet gaming disorder. J Behav Addict. 2017; 6: 516–524. PubMed Abstract \| Publisher Full Text\n\nDeleuze J, Rochat L, Romo L, et al.: Prevalence and characteristics of addictive behaviors in a community sample: A latent class analysis. Addict Behav Rep. 2015; 1, 49–56. PubMed Abstract \| Publisher Full Text\n\nEvans BE, Kim Y, Hagquist C: A latent class analysis of changes in adolescent substance use between 1988 and 2011 in Sweden: associations with sex and psychosomatic problems. Addiction. 2020; 115: 1932–1941. PubMed Abstract \| Publisher Full Text\n\nFeng W, Ramo DE, Chan SR, et al.: Internet gaming disorder: Trends in prevalence 1998–2016. Addict Behav. 2017; 75: 17–24. PubMed Abstract \| Publisher Full Text\n\nFerguson C, Coulson M, Barnett J: A meta-analysis of pathological gaming prevalence and comorbidity with mental health, academic and social problems. J Psychiatr Res. 2011; 45: 1573–1578. PubMed Abstract \| Publisher Full Text\n\nGentile D: Pathological Video-Game Use Among Youth Ages 8 to 18: A National Study. Psychol Sci. 2009; 20: 594–602. PubMed Abstract \| Publisher Full Text\n\nHenry KL, Muthen B: Multilevel Latent Class Analysis: An Application of Adolescent Smoking Typologies with Individual and Contextual Predictors. Struct Equ Modeling. 2010; 17: 193–215. PubMed Abstract \| Publisher Full Text\n\nJames RJE, O’Malley C, Tunney RJ: Sociodemographic predictors of latent class membership of problematic and disordered gamblers. Addict Behav Rep. 2016; 3: 61–69. PubMed Abstract \| Publisher Full Text\n\nJames RJE, Tunney RJ: The relationship between gaming disorder and addiction requires a behavioral analysis. J Behav Addict. 2017; 6: 306–309. PubMed Abstract \| Publisher Full Text\n\nJo YS, Bhang SY, Choi JS, et al.: Clinical Characteristics of Diagnosis for Internet Gaming Disorder: Comparison of DSM-5 IGD and ICD-11 GD Diagnosis. JCM. 2019; 8. PubMed Abstract \| Publisher Full Text\n\nKaptsis D, King DL, Delfabbro PH, et al.: Withdrawal symptoms in internet gaming disorder: A systematic review. Clin Psychol Rev. 2016; 43: 58–66. PubMed Abstract \| Publisher Full Text\n\nKong G, Tsai J, Krishnan-Sarin S, et al.: A latent class analysis of pathological-gambling criteria among high school students: associations with gambling, risk and health/functioning characteristics. J Addict Med. 2014; 8: 421–430. PubMed Abstract \| Publisher Full Text\n\nKuss D, van Rooij A , Shorter GW, et al.: Internet addiction in adolescents: Prevalence and risk factors. Comput Hum Behav. 2013; 29: 1987–1996. Publisher Full Text\n\nLemmens JS, Valkenburg PM, Gentile DA: The Internet Gaming Disorder Scale. Psychol Assess. 2015; 27: 567–582. Publisher Full Text\n\nLinzer DA, Lewis JB: poLCA: An R Package for Polytomous Variable Latent Class Analysis. Psychol Assess. 2011; 42: 1–29.Reference Source\n\nMcBride O, Adamson G, Shevlin M: A latent class analysis of DSM-IV pathological gambling criteria in a nationally representative British sample. Psychiatry Res. 2010; 178: 401–407. Publisher Full Text\n\nMihara S, Higuchi S: Cross-sectional and longitudinal epidemiological studies of Internet gaming disorder: A systematic review of the literature. Psychiatry Clin Neurosci. 2017; 71: 425–444. PubMed Abstract \| Publisher Full Text\n\nMorean ME, Kong G, Camenga DR, et al.: Latent class analysis of current e-cigarette and other substance use in high school students. Drug Alcohol Depend. 2016; 161: 292–297. PubMed Abstract \| Publisher Full Text\n\nMüller KW, Janikian M, Dreier M, et al.: Regular gaming behavior and internet gaming disorder in European adolescents: results from a cross-national representative survey of prevalence, predictors, and psychopathological correlates. Eur Child Adolesc Psychiatry. 2015; 24: 565–574. PubMed Abstract \| Publisher Full Text\n\nMyrseth H, Notelaers G: A Latent Class Approach for Classifying the Problem and Disordered Gamers in a Group of Adolescence. Front Psychol. 2018; 9: 2273. PubMed Abstract \| Publisher Full Text\n\nOlson KE, O’Brien MA, Rogers WA, et al.: Diffusion of Technology: Frequency of Use for Younger and Older Adults. Ageing Int. 2011; 36: 123–145. PubMed Abstract \| Publisher Full Text\n\nOrford J, Morison V, Somers M: Drinking and gambling: a comparison with implications for theories of addiction. Drug Alcohol Rev. 1996; 15: 47–56. Publisher Full Text\n\nPeeters M, Koning I, Lemmens J, et al.: Normative, passionate, or problematic? Identification of adolescent gamer subtypes over time. J Behav Addict. 2019; 8: 574–585. PubMed Abstract \| Publisher Full Text\n\nPetry NM, Rehbein F, Gentile DA, et al.: An international consensus for assessing internet gaming disorder using the new DSM-5 approach. Addiction. 2014; 109: 1399–1406. PubMed Abstract \| Publisher Full Text\n\nPrzybylski AK, Weinstein N: Investigating the Motivational and Psychosocial Dynamics of Dysregulated Gaming: Evidence From a Preregistered Cohort Study. Clin Psychol Sci. 2019; 7: 1257–1265. Publisher Full Text\n\nRaybould JN, Tunney RJ: Addiction: What is the Relationship between childhood scarcity and adult impulsivity? 2020.Reference Source\n\nRaybould J, Watling DC, Larkin M, et al.: Impulsivity, Scarcity and Maladaptive Choice Behaviours Project. [Dataset].2022, June 30. Publisher Full Text\n\nRosenthal RJ, Lesieur HR: Self-Reported Withdrawal Symptoms and Pathological Gambling. Am J Addict. 1992; 1: 150–154. Publisher Full Text\n\nSafiri S, Rahimi-Movaghar A, Yunesian M, et al.: Subgrouping of risky behaviors among Iranian college students: a latent class analysis. NDT. 2016; 12: 1809–1816. PubMed Abstract \| Publisher Full Text\n\nWorld Health Organization: ICD-11 for Mortality and Morbidity Statistics: 6C51 Gaming disorder. The International Classification of Disease.2020.Reference Source\n\nXian H, Shah KR, Potenza MN, et al.: A Latent Class Analysis of DSM-III-R Pathological Gambling Criteria in Middle-Aged Men: Association with Psychiatric Disorders. J Addict Med. 2008; 2: 85–95. PubMed Abstract \| Publisher Full Text\n\nYu M, Sacco P, Choi HJ, et al.: Identifying patterns of tobacco use among US middle and high school students: A latent class analysis. Addict Behav. 2018; 79: 1–7. Publisher Full Text" }	[ { "id": "146753", "date": "08 Aug 2022", "name": "Alexander Bradley", "expertise": [ "Reviewer Expertise Gambling research and statistical methods" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article explores the underlying class structure of the DSM criteria scale in samples of prolific and gaming forum users (discord and reddit). They find both 4 and 6 models provide good model fit in terms of BIC, AIC, Chi-square etc. Young adults had the highest gaming scores.\nIntroduction/Literature Review Introduction could do with more clearly stating it's aims and hypotheses that it wishes to test. For example, in the design there is a suggestion that ICG has similar class structure to established addiction yet in the literature review addictions seemed to vary from 3-4 classes.\nWith the statistical analysis section I am guessing one sample was the prolific sample (N = 294) and Gaming forum sample (N = 236). Is this correct? Please do make this clearer.\nResults Clearer statement of what each of the classes is classed as in the text between tables 4 and table 5 for each type of model.\nIt would also be useful to know what percentage of your two different samples fell into each class. This would relate back to Introduction where prevalence of classes and differences between DSM and IGD were discussed. This could be added in as two extra columns in Table 7.\nAre there any benefits of having 6 or 4 class model in terms of numbers classed as at risk gamers and potentially disordered gamers. i.e. comparison of percentages.\nDo you have any items that might be able to link DSM scores to more behavioural measures like the amount of time spent playing games per week? Or amount spent on gaming?\nDiscussion What extra nuance does a six model hold? You state this and only later suggest what this might be.\nGood points made around withdrawal and the value or not in pre-occupation and escapism as potential facets of gaming or any enjoyable hobby for that matter.\nData Availability Even better if the Rscript with the LCA analysis was also deposited in the OSF so other could check the code.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "157331", "date": "20 Dec 2022", "name": "Veli-Matti Karhulahti", "expertise": [ "Reviewer Expertise Gaming disorder." ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nDear Authors and Editors,\nThank you for inviting me to review this manuscript. Due to my limited expertise on LCA, I asked my colleague Matúš Adamkovič to separately comment on the R code. However, while reading the manuscript, I was surprised to notice that no code has been shared after all, despite the great choice to work with open software. Because I review under the PRO initiative (https://www.opennessinitiative.org), I should note that a justification for non-sharing should be provided or, preferably, the code should be shared for review.\nThe first part of the feedback was initially drafted by me (VMK) and later comments on methodology by MA. We both agree and sign all points made in this review.\n\nThe rationale of the study remains somewhat unclear. In addition to the fact that there are already numerous classification studies in the I/GD literature, there are also large-scale LCA studies1. Although I am warmly welcoming to replications and all other information about the validity of older findings, it is not clear how the present results update the prior understanding. E.g., the sentence about lacking research on age (“including a range of ages in gaming analysis could be beneficial”) is relevant but the MS has little actual analysis or discussion on age beyond Table 8.\n\nSample justification is missing. See2.\n\nWhat language/nationality were the respondents, what were the inclusion/exclusion criteria? This is important especially because IGDS was used for measurement, and a Dutch validation study is cited. If the participants were native English speakers and an English version of the scale was used, please cite an English validation or other scale test, or discuss in the limitations.\n\nRegarding the design and results, a critical limitation is the lacking inclusion of any health and wellbeing variables in the model. For instance, when the study concludes that “IGD appears to have a four- or six-class structure ranging from ‘casual/non-gamers’ to ‘potentially disordered’ with increasing severity”, there seems to be no evidence for severity beyond the total score. Including health or wellbeing measures in the design would’ve allowed assessing severity. In fact, threshold-based categorization and total scores can lead to inference errors because not all nine criteria are (equally) relevant, e.g3,4etc.\n\nFollowing the above notes, the final contribution should be clarified to the reader and explained how it helps better understand I/GD. E.g., the discussion concludes that “IGD may be presenting in a similar manner to established addictions”, but this deduction omits historical and psychometric context. Namely, IGD and IGDS were developed with a confirmatory approach from existing substance use criteria, and thus, logically, the nine DSM symptoms (taken from substance use and gambling) are likely to produce similar models as do their roots. If we study data from treatment-seekers and other clinical samples (especially qualitative ones), we see different symptoms, for which there has been a strong move away from confirmatory IGD models for a long time, see e.g. the more recent ICD-11 criteria5 etc.\n\nI would recommend carefully revising the discussion language, especially regarding the relevance of specific criteria. For instance, the prevalence of relationship issues (“relationship issues were less than 50% likely in all classes except model-six ‘potentially disordered’ gamers (57%), suggesting it may not be an appropriate criterion”) can hardly be considered as evidence for its lack of actual problem-relevance. When analyzing a convenience sample, more severe outcomes are naturally less prevalent, yet these may well be the most valuable signs for identifying actual treatment-seeking or support-needing people. Please carefully reconsider such conclusions and related language in the discussion.\nAdditional notes on method from Matúš Adamkovič:\nAlthough running LCA in the poLCA package is rather straightforward, I’d still welcome mentioning additional technical details in the text (or, alternatively, in the R code).\n\nHow was the data handled? Did you check for patterns of careless responding, improbable values, etc.? Were there any missing values in the data?\n\nPlease consider extending the paragraph in which you describe the specifics of each latent class – as I read it, this is the most important part of the paper and would benefit from a detailed description of the differences in symptoms composition across the different classes.\n\nRelated to the previous point, a visualization of the LCAs (maybe instead of Table 4) would be helpful to easier grasp the between-classes differences.\n\nCould you please add (would work fine in supplementary material) information about the accuracy of the classifications? For example, by calculating the posterior probabilities that cases belong to each class (available in poLCA).\n\nThis point has already been raised by Matti (point no. 4) but since I, too, find it extremely important, I’d like to emphasize it once more. Since the data used for this study comes from a bigger dataset, it’d be valuable to, for instance, compare subgroups across some of these variables. This will provide further insights into the validity of the classification/s.\n\nI suggest removing/moving to supplementary materials tables 5 and 6 since they have little information value.\n\nPlease add a paragraph that will reflect upon the limitations of the study.\nWe hope these comments will be helpful in revising the MS. If our feedback feels unclear or unfair, we can be contacted directly.\nMatti & Matus\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-806
https://f1000research.com/articles/11-805/v1	20 Jul 22	{ "type": "Research Article", "title": "Feasibility and effectiveness of exercise-based prehabilitation in patients opting for elective abdominal surgeries: A pre-post study", "authors": [ "Jean Nikitha Noronha", "Stephen Rajan Samuel", "Vijay Pratap Singh", "H Shivananda Prabhu", "Jean Nikitha Noronha", "Vijay Pratap Singh", "H Shivananda Prabhu" ], "abstract": "Background: Surgical procedures are accompanied by various complications such as decreased respiratory muscle strength, decreased functional capacity, decreased quality of life, and increased the length of hospital stay. There is a growing body of evidence that indicates that exercise-based prehabilitation offered before major abdominal surgeries can improve the above-mentioned complications. Considering the socioeconomic inequalities, educational characteristics, and healthcare system, which are different in low and lower-middle income countries, it is important to know whether interventions such as prehabilitation are feasible and effective in patients undergoing elective abdominal surgeries. Hence, we set out to determine the role of exercise-based prehabilitation in patients opting for these surgeries. Methods: In this feasibility study, 71% of the eligible patients agreed to participate. Baseline values of respiratory muscle strength, functional capacity and quality of life were recorded preoperatively, and an exercise-based prehabilitation programme consisting of chest physiotherapy, aerobic exercises and inspiratory muscle training according to the patient’s capacity was administered until the day of surgery. A total of 62% of the participants completed the study whose postoperative values and a user satisfaction scale were noted. The feasibility parameters of recruitment rate, dropout rates, adherence events, adverse events and participants satisfaction were evaluated and the differences in the preoperative and postoperative values of respiratory muscle strength, functional capacity and quality of life were calculated using the paired t-test accordingly. Results: Feasibility was measured using five parameters. All the values were > 50% and above. The secondary variables respiratory muscle strength, functional capacity, and quality of life were not significant. Conclusions: This study concluded that prehabilitation is feasible and can be effectively delivered to patients scheduled for elective abdominal surgery. Clinical Trials Registry India registration: CTRI/2021/05/033707 (20/05/2021).", "keywords": [ "Pre-operative exercises", "preoperative exercise", "prehabilitation", "elective abdominal surgeries", "surgery", "adults" ], "content": "Abbreviations\n\nACBT: Active Cycle of Breathing Techniques\n\nFC: Functional Capacity\n\nFET: Forced Expiratory Techniques\n\nHR: Heart Rate\n\nIMT: Inspiratory Muscle Training\n\nLOS: Length of Stay\n\nMEP: Maximum Expiratory Pressure\n\nMIP: Maximum Inspiratory Pressure\n\nPEXT: Preoperative Physical Exercise Therapy\n\nPPC: Postoperative Pulmonary Complications\n\nQoL: Quality of Life\n\nRCT: Randomized Control Trials\n\nRPE: Rate of Perceived Exertion\n\nTEE: Thoracic Expansion Exercises\n\nWHOQOL: World Health Organization Quality of life\n\n6MWT: Six-Minute Walk Test\n\n6MWD: Six-Minute Walk Distance\n\n\nIntroduction\n\nAround 235 million major surgical procedures are performed each year globally.1 This number is constantly growing due to the world’s ageing population, expansion, development of novel surgical methods, and the formation of new surgical facilities across the world.2 Despite several ongoing improvements in perioperative care, major abdominal surgeries are associated with postoperative complications and morbidity, and even in the absence of complications, it is seen that there is a reduction in functional capacity (FC).3–5\n\nAround 35% of patients that endure a major abdominal surgery experience a postoperative complication, with approximately 20-40% reduction in their post-operative physical function.6,7 A deterioration in quality of life (QoL) is observed even without complications.8 It is noted that patients who have experienced complications within 30 days post-surgery have a decreased long-term survival rate.9\n\nPostoperative pulmonary complications (PPC) can be caused due to insufficient inspiratory efforts, inadequate sputum expectoration, and a greater respirational demand that produces inspiratory muscle fatigue.10 The mechanism of PPCs is a decline in lung expansion because of prolonged recumbent positioning, shallow breathing, impaired mucociliary work, diaphragmatic dysfunction, and ineffective coughing.11\n\nPrehabilitation is an umbrella term that includes physical exercises, nutritional support, and stress and anxiety reduction.12,13 The concept of prehabilitation was initially reported in 194213 and came to light post-2011 after the systematic review published by Valkenet et al.12,14 It is an intervention of conditioning a patient in the pre-surgical period to cope with the post-surgery stressors.15 It prepares a patient before major surgery and also, at the same time, aims at reducing postoperative complications, promoting physical activity, and also optimises their psychological wellbeing.16–18 Prehabilitation before major surgery aims to maintain the normal levels of functionality and attain a faster recovery of the functional status during post-op inactivity.17–19 Until recently, efforts to improve recovery after major surgery in the post-operative period have been the primary focus.20,21 However, the emergence of prehabilitation signifies a change from the impairment-driven, reactive model of care toward an active method that allows a patient to become active partakers in their care.22\n\nPrehabilitation has been found effective in improving postoperative outcomes in studies other than India. There have been improvements in respiratory muscle strength, FC, and QoL, respectively.5,22,23 Differences in how prehabilitation can work in low and low-middle-income countries like India and how feasible it can be could depend on the socioeconomic inequalities, educational factors, and differences in healthcare setups.\n\nRespiratory muscle strength can be improved by incorporating inspiratory muscle training (IMT), a form of exercise to strengthen the respiratory muscles.24 The decrease in the respiratory muscle can lead to decreasing FC. The six-minute walk test (6MWT) is regularly used to determine FC in patients.25\n\nThe World Health Organization Quality Of Life (WHOQOL) groups developed the WHOQOL-BREF assessment to analyse QoL across various populations that could be applicable cross-culturally.26 This scale contains four domains: physical health, psychological, social relationships, and environmental domains.26\n\nFeasibility studies are research done before the main study to answer questions about whether an intervention is appropriate for further testing,27 i.e., they enable researchers to judge whether or not the ideas and findings can be shaped to be relevant for sustainable study.28,29\n\nPrevious studies done in prehabilitation have proved that exercise-based prehabilitation is effective in people who undergo abdominal surgeries in general. However, there is a paucity of literature on whether it is feasible to carry out a pre-operative/prehabilitation exercise program and know its effectiveness in the rehabilitation stage in countries like India.\n\n\nMethods\n\nThis was a feasibility, a pre-post study conducted in a tertiary care university hospital. All associated study instruments (questionnaires, consent form, etc.) are available in Extended data.48\n\nThe study was approved by the Scientific and Institutional Ethics Committee on 18th February 2021 (IEC KMC MLR 02-2021/37) and registered in CTRI no. (CTRI/2021/05/033707) on 20th May 2021. The patients who met the inclusion criteria were explained about the study. After the explanation, if the patient agreed to participate, they gave written informed consent.\n\nThe patients scheduled for elective surgeries and referred for physiotherapy treatment were screened for the inclusion criteria. The inclusion criteria included patients above 18 years scheduled for elective abdominal surgery. The patients scheduled for laparoscopy surgery or who underwent an emergency or high-risk surgeries were excluded from the study. The patients were recruited for a year from March 2021 to March 2022.\n\nThe study’s primary outcome was to evaluate the feasibility through recruitment rate, dropout rates, adherence to the rehabilitation rate, adverse events, and patient’s level of satisfaction. These criteria were taken from the research regarding the feasibility studies by El kotob et al.35 The investigating team found these criteria most suitable for the study.\n\nThe secondary outcomes evaluated were respiratory muscle strength using the Micro RPMTM and measuring MIP (Maximum Inspiratory Pressure) and MEP (Maximum Expiratory Pressure), and FC through 6MWT done on a 30 m distance back and forth according to the patient’s comfort, and QoL through the WHOQOL-BREF scale.\n\nOnce the study was explained, the baseline values of respiratory muscle strength: MIP, MEP, FC – 6MWT, and the WHOQOL-BREF scales were noted at the beginning of the study. The participants were admitted to the hospital during the duration of the study and the intervention was administered in the hospital to them. An exercise brochure (English/Kannada) was given by the physiotherapist to the patients on their first day of admission to the hospital and a demonstration of the exercises was shown to them. The exercise protocol contained aerobic exercises, i.e., walking 30min/day at least five times a week (according to the patient’s comfort level), breathing exercises that included patient education, Active Cycle of Breathing Techniques (ACBT), Thoracic Expansion Exercises (TEE), Forced Expiration Technique (FET), and Breathing Control twice per day 10-15 min. Inspiratory muscle training was also done through the Threshold IMT device (Philips MAS Respironics®). The resistance was set based on 20% of their MIP measured during the baseline evaluation. Any Other Chest Physiotherapy as indicated according to the patients’ conditions would also be suggested. Progression was according to the patient’s rate of perceived exertion (RPE). The possible post-operative complications that can develop post-surgery, pre-operative education about smoking cessation, and proper nutrition (if the patient has any other co-morbidities) were also explained. The prehabilitation exercises were given daily to the patient by the physiotherapist for an average of 1-4 days, with a small percentage receiving it for more than five days till the duration of their surgery. Routine postoperative protocol was continued later till the day of discharge. Outcomes measures were retaken post-operatively. On the day of discharge, their post-operative values were taken, and patients were given a user satisfaction scale to document their satisfaction regarding the exercise-based prehabilitation programme. This was filled by the patients that had completed the study. The scale was adapted from a previous study by Piron et al34 and modified accordingly to our study. The questionnaire contained 11 questions, of which 1st three were about patients’ willingness to participate, the questions 4th-9th were about the patient therapist’s overall relationship, and the last two were about patients’ general satisfaction with the prehabilitation exercise program.\n\nAll the data collected were entered into the Jamovi version 1.6.23 (RRID:SCR_016142) for data analysis. The data were checked for normality. A paired t-test was used to compare the outcomes’ preoperative and postoperative values within the group and analyze the p < 0.05 - statistically significant data.30,31\n\n\nResults\n\nThe study has been reported per the Consolidated Standards of Reporting Trials (CONSORT) extension for pilot and feasibility study32,33 (see Figure 1 and Reporting guidelines48).\n\nA total of 170 patients were screened, with 56 participants eligible based on the screening for inclusion criteria. Of these 56 participants, 40 consented to participate in this study, with a mean age of 51.5 years (Table 1). Of the 40 eligible to participate, 25 participants completed the exercise based prehabilitation in this study. Their ages ranged from 37 to 74, with their mean age being 49.8 years (Table 2). The data associated with the participants is available in Underlying data.48\n\nIn this study, feasibility criteria were categorized and measured based on these five criteria:\n\n1. Recruitment rate\n\n2. Dropout rates\n\n3. Adherence to the rehabilitation rate\n\n4. Adverse events\n\n5. Participants’ level of satisfaction\n\nRecruitment rate\n\nA total of 170 patients were screened, with 56 patients meeting the inclusion criteria (Figure 2) and 114 excluded. These 114 patients were excluded based on the exclusion criteria, i.e., 1. patients undergoing high risk, emergency, laparoscopic surgeries, or 2. having musculoskeletal/neurological impairments. A total of 84% of these 114 patients were received post-operatively, underwent emergency surgeries, and had to be excluded as they had not received prehabilitation. The rest (14%) were excluded as their planned surgery was laparoscopic surgery, and the last 2% were not included since they did not match the age criteria (Figure 3).\n\nFrom the 56 patients who met the inclusion criteria, 40 agreed to participate in the study, and 16 denied/did not consent to participate, making the recruitment rate 71% (Figure 4).\n\nDropout rate\n\n62% patients of the 40 that consented to participate completed the study and the remaining 38% dropped out of the study (Figure 5). The reasons for dropout of patients are explained in Figure 6.\n\nAdherence\n\nThe adherence was reported to be 62%, as the remaining 38% of the patients could not complete the study due to the reasons explained in Figure 6.\n\nAdverse events\n\nThe prehabilitation exercise program was given to the patients during the hospital stay from the day of admission to surgery and continued postoperatively. No adverse events were reported during the duration of the exercise protocol.\n\nParticipant satisfaction\n\nLastly, the user satisfaction scale was based on the Likert scale, and above satisfactory scores (3+) were obtained for the questions. A summary of their responses with scoring is given in Table 3.\n\nThe Mean for MIP preoperatively was 30.320 cm H2O, and the postoperative was 25.360 H2O (p=0.008). The MEP preoperatively was 30.080 H2O and postoperatively 25.120 H2O (p<0.001). Both the MIP and MEP have shown a decline in the postoperative period (Table 4) (Figure 7).\n\nThe FC was measured using the 6-minute walk test (meters), and the distance was compared preoperatively and postoperatively. The mean distance was 306.712 meters preoperatively, and 213.080 meters postoperatively (p<0.001), which showed a significant decrease in the preoperative and postoperative distance walked by the patients (Table 4) (Figure 8).\n\nQoL was measured using the WHO-QOL BREF scale. The WHOQOL BREF is a shorter form of the WHOQOL. This scale includes scoring based on four domains: physical health, psychological health, social relationships, and environmental aspects. The results showed that there was no statistically significant improvement seen (Table 4 and Figure 9).\n\n\nDiscussion\n\nThe goal of this study was to determine the feasibility and efficacy of prehabilitation as part of a routine rehabilitation programme in patients undergoing elective abdominal surgeries. The current study focused on four key outcomes of feasibility, respiratory muscle strength, FC, and QoL.\n\nFeasibility in terms of research refers to how people who carry out a study or intervention can practically do so in the actual world.35 Feasibility may focus on developmental research, as in developing a feasibility study.36 Feasibility studies are pieces of research done before the main study to answer whether a study can be done or not.35 It estimates the critical parameters needed to construct the main study.27,37–39 Feasibility studies can be conducted for four primary purposes, i.e., process assessment, resource assessment, management, and scientific basis to plan RCT.27 In line with the aforementioned purposes, alongside outcomes mentioned by El-Kotob R et al.,35 our study had five outcomes: recruitment rate, dropout rates, adherence to the rehabilitation rate, adverse events, and user satisfaction scale.\n\nThe recruitment rate is defined as the number of eligible patients who consented to participate in study.35 A total of 170 patients were screened over the duration of 12 months, with 56 meeting the inclusion criteria and 40 agreeing to participate in the study. According to these results, around 71% of the eligible patients were willing to begin an exercise program prior to elective abdominal surgeries. Other comparable trials showed mixed results, some reporting a recruitment rate of 85%,40 some 45%,41 and some as low as 20%.42\n\nDropout rates are those who agreed to participate in the study but were unable to complete it owing to a variety of circumstances. 38% of the individuals in our study dropped out due to unavoidable reasons. Surgery cancellation accounts for 60% of dropouts, scheduled surgery being modified by 20%, and 7% of included individuals being diagnosed with coronavirus disease 2019 (COVID-19), ultimately leading to cancelled surgery and increasing the dropout rate. The outcomes of our study are consistent with the findings of Martin et al., who determined that the reasons for patients dropping out were unavoidable circumstances.41\n\nAnother component analysed in feasibility was adherence, which according to the WHO, was defined as “the degree to which the person’s behaviour corresponds with the agreed recommendations from a health care provider”.43 Any therapeutic intervention’s effectiveness relies on the patient’s ability to keep up with the prescribed therapy.43 In this study, adherence was analysed through the exercise protocol administered in a supervised environment by a physiotherapist in the hospital-based setup. All the patients recruited for the prehabilitation program were admitted to the hospital prior to the surgery. 62% of the participants who completed the study adhered to the program compared to the rest of the 38% who did not adhere. According to a previous study, patients who were given prehabilitation activities face-to-face had a higher adherence rate of 93%, compared to 64% for those given prehabilitation exercises as unsupervised home exercises.40 Lack of social support from family and friends and the patient’s lack of belief in the merits of the exercises have been identified as plausible factors for low adherence in prior trials when prehabilitation was available.41\n\nAdverse events were not reported in our study. Only one of the trials by Martin et al. reported short-term adverse events during the cardiopulmonary exercise testing during the assessment.41\n\nAnother variable assessed in feasibility was the level of satisfaction among patients who finished the exercise-based prehabilitation. The user satisfaction scale addressed three distinct factors, namely, 1. their willingness to participate, 2. the patient-therapist interaction, and 3. their overall satisfaction with the treatment. The scoring was based on the Likert scale and was adapted from a similar study.34 The scoring for the 11 questions was 3+ above 48% of participants strongly agreed that they were willing to participate in exercises preoperatively, and 88% agreed that the exercises were easy to understand and follow. Above satisfactory scorings in the questions that assess the therapist-patient relationship parameters were noted. The third criteria presented that 60% of the participants were satisfied and 40% extremely satisfied with the preoperative exercises, and 92% of them would thoroughly recommend the program.\n\nThe secondary outcomes of our studies were to assess the effectiveness of the exercise-based prehabilitation post-surgery. One of the secondary outcomes included respiratory muscle strength, measured using global measures of MIP and MEP. These significant pressures can be achieved during maximal inspiration and expiration against an obstructed airway, respectively.24,44 The MIP measures inspiratory muscular strength created by a sub-atmospheric pressure, whereas the MEP is a supra-atmospheric pressure developed by abdominal and intercostal muscle effort.44,45 In our study, the mean MIP preoperatively is 30.3 cm H2O and postoperative is 25.4 cm H2O and MEP preoperatively is 30.1 cm H2O and postoperatively is 25.1 cm H2O which shows that there is a decline in the preoperative and postoperative values.\n\nSix min walk test was used to analyse FC. The 6MWT is a submaximal exercise test that measures aerobic capacity and endurance. The distance covered in 6 minutes is utilized as the outcome to compare improvements in performance capability.46 In our study FC was computed through the 6MWD that showed a mean of 307 meters preoperatively and 213 meters postoperatively.\n\nReduced respiratory muscle strength, pain caused postoperatively due to surgery, or even the fact that patients received treatment for less than two weeks preoperatively, i.e., patients could not be admitted/received early preoperatively for an average of four days, could be the possible reasons for the decline in postoperative outcomes. In a previous study conducted by Kulkarni et al., they found that IMT is effective and has significant improvement when compared preoperatively and postoperatively.10 Prehabilitation exercise programs were planned and administered to patients who had more than two weeks until their procedures in this study.10,40,41 Many participants were eliminated from Martin et al.’s study because of these criteria.41 Because there was no established criterion for how many days before prehabilitation patients should be included in our trial, we included all participants who had been referred to us prior to surgery.\n\nThe WHOQOL-BREF scale, a condensed version of the WHOQOL-100, was used to assess QoL. The WHOQOL-BREF scale consists of 26 questions and contains four domains: physical health, psychological, social relationships, and environment.26,47 There was no significant statistical improvement seen.\n\nWell-powered research is aided by high rates of recruitment, adherence, retention, and patient satisfaction. Future studies can have a well-planned duration for prehabilitation so that the patients are able to get the maximum impact of these exercises. Rather than having a heterogeneous population, studies can be done on a specific type of procedure, condition, or surgical incisions. Future possibilities for greater application of prehabilitation through telerehabilitation in these specific settings could also be considered.\n\nThis feasibility pre-post-study had certain drawbacks. The first constraint was the number of days, i.e., the days prior to prehabilitation were not well specified. In this study, the majority of patients had prehabilitation for 1-4 days on average, with only a small percentage receiving it for more than five days. The second hurdle was the referral system or the inability to receive the patients sooner. Because the patients could not be received/recruited earlier and did not have more than 14+ days, the effectiveness and why there is a decline in outcomes cannot be clearly noted. Another drawback of the current study is that it was carried out in a single-site tertiary care hospital, with treatment restricted to patients admitted to the facility. As a result, possible issues with applicability, techniques, and recruiting were undetected.\n\n\nConclusions\n\nIt can be concluded that exercise-based prehabilitation is feasible and can effectively be delivered to patients scheduled for elective abdominal surgery. All the feasibility criteria taken into consideration have been met (>50%). With the recruitment rate of the patients that were approached being 71%, it can be stated that patients that were eligible were willing to participate. However, in order to establish the prehabilitation programs efficacy, a future study must be conducted with a homogenous group and a larger sample size, taking into account the hurdles encountered.\n\n\nData availability\n\nOpen Science Framework: Feasibility and Effectiveness of exercise-based prehabilitation in patients opting for elective abdominal surgeries: a pre-post study. https://doi.org/10.17605/OSF.IO/FH8XB.48\n\nThis project contains the following underlying data:\n\n- Feasibility and Effectiveness of Exercise-based Prehabilitation on Patients opting for Elective Abdominal Surgeries Raw data.csv.\n\nOpen Science Framework: Feasibility and Effectiveness of exercise-based prehabilitation in patients opting for elective abdominal surgeries: a pre-post study. https://doi.org/10.17605/OSF.IO/FH8XB.48\n\nThis project contains the following extended data:\n\n- Feasibility Questionnaire.pdf\n\n- Informed consent form.pdf\n\n- Patient information sheet.pdf\n\n- Prehabilitation exercise protocol.pdf\n\n\nReporting guidelines\n\nOpen Science Framework: CONSORT extension for Pilot and Feasibility Trials Checklist and flow diagram for: ‘Feasibility and effectiveness of exercise-based prehabilitation in patients opting for elective abdominal surgeries: a pre-post study’. https://doi.org/10.17605/OSF.IO/FH8XB.48\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgements\n\nWe want to thank Mr Vivekbhai Dineshbhai Patel for helping us with the statistical processes and suggestions throughout the thesis.\n\n\nReferences\n\nWeiser TG, Regenbogen SE, Thompson KD, et al.: An estimation of the global volume of surgery: a modelling strategy based on available data. Lancet. 2008 Jul; 372(9633): 139–144. Publisher Full Text\n\nRose J, Weiser T, Hider P, et al.: Estimated need for surgery worldwide based on prevalence of diseases: A modelling strategy for the WHO Global Health Estimate. Lancet Glob. Health. 2015 Apr 27; 3: S13–S20. Publisher Full Text\n\nSchilling PL, Dimick JB, Birkmeyer JD: Prioritizing quality improvement in general surgery. J. Am. Coll. Surg. 2008 Nov; 207(5): 698–704. PubMed Abstract \| Publisher Full Text\n\nChristensen T, Kehlet H: Postoperative fatigue. World J. Surg. 1993 Apr; 17(2): 220–225. Publisher Full Text\n\nHughes MJ, Hackney RJ, Lamb PJ, et al.: Prehabilitation Before Major Abdominal Surgery: A Systematic Review and Meta-analysis. World J. Surg. 2019 Jul 1; 43(7): 1661–1668. PubMed Abstract \| Publisher Full Text\n\nVeen EJ, Steenbruggen J, Roukema JA: Classifying surgical complications: a critical appraisal. Arch. Surg. 2005 Nov; 140(11): 1078–1083. Publisher Full Text\n\nNickelsen TN, Jørgensen T, Kronborg O: Lifestyle and 30-day complications to surgery for colorectal cancer. Acta Oncol. 2005; 44(3): 218–223. PubMed Abstract \| Publisher Full Text\n\nLawrence VA, Hazuda HP, Cornell JE, et al.: Functional independence after major abdominal surgery in the elderly. J. Am. Coll. Surg. 2004 Nov; 199(5): 762–772. Publisher Full Text\n\nKhuri SF, Henderson WG, DePalma RG, et al.: Determinants of long-term survival after major surgery and the adverse effect of postoperative complications. Ann. Surg. 2005 Sep; 242(3): 326–343. discussion 341-343. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKulkarni SR, Fletcher E, McConnell AK, et al.: Pre-operative inspiratory muscle training preserves postoperative inspiratory muscle strength following major abdominal surgery - a randomised pilot study. Ann. R. Coll. Surg. Engl. 2010 Nov; 92(8): 700–705. PubMed Abstract \| Publisher Full Text\n\nOverend TJ, Anderson CM, Lucy SD, et al.: The effect of incentive spirometry on postoperative pulmonary complications: a systematic review. Chest. 2001 Sep; 120(3): 971–978. Publisher Full Text\n\nNoronha J, Samuel S, Singh VP, et al.: Effects of exercise-based prehabilitation in children undergoing elective surgeries: a systematic review [version 2; peer review: 2 approved].2022; 15.\n\nBanugo P, Amoako D: Prehabilitation. BJA Educ. 2017 Dec 1; 17(12): 401–405. Publisher Full Text\n\nValkenet K, van de Port IG , Dronkers JJ, et al.: The effects of preoperative exercise therapy on postoperative outcome: a systematic review. Clin. Rehabil. 2011 Feb; 25(2): 99–111. PubMed Abstract \| Publisher Full Text\n\nKim DJ, Mayo NE, Carli F, et al.: Responsive Measures to Prehabilitation in Patients Undergoing Bowel Resection Surgery. Tohoku J. Exp. Med. 2009; 217(2): 109–115. PubMed Abstract \| Publisher Full Text\n\nCabilan CJ, Hines S, Munday J: The effectiveness of prehabilitation or preoperative exercise for surgical patients: a systematic review: JBI Database of Systematic Reviews and Implementation Reports.2015 Jan; 13(1): 146–87.\n\nTopp R, Ditmyer M, King K, et al.: The effect of bed rest and potential of prehabilitation on patients in the intensive care unit. AACN Clin. Issues. 2002 May; 13(2): 263–276. PubMed Abstract \| Publisher Full Text\n\nCarli F, Zavorsky GS: Optimizing functional exercise capacity in the elderly surgical population. Curr. Opin. Clin. Nutr. Metab. Care. 2005 Jan; 8(1): 23–32. PubMed Abstract \| Publisher Full Text\n\nDitmyer MM, Topp R, Pifer M: Prehabilitation in preparation for orthopaedic surgery. Orthop. Nurs. 2002 Oct; 21(5): 43–54. quiz 52–4. PubMed Abstract \| Publisher Full Text\n\nGonçalves and Groth - 2019 - Pré-habilitação como preparar nossos pacientes pa.pdf.\n\nMolenaar CJL, Papen-Botterhuis NE, Herrle F, et al.: Prehabilitation, making patients fit for surgery – a new frontier in perioperative care. Innov. Surg. Sci. 2019 Dec 18; 4(4): 132–138. PubMed Abstract \| Publisher Full Text\n\nKamarajah SK, Bundred J, Weblin J, et al.: Critical appraisal on the impact of preoperative rehabilitation and outcomes after major abdominal and cardiothoracic surgery: A systematic review and meta-analysis. Surgery. 2020 Mar; 167(3): 540–549. PubMed Abstract \| Publisher Full Text\n\nBarberan-Garcia A, Ubré M, Roca J, et al.: Personalised Prehabilitation in High-risk Patients Undergoing Elective Major Abdominal Surgery: A Randomized Blinded Controlled Trial. Ann. Surg. 2018 Jan; 267(1): 50–56. PubMed Abstract \| Publisher Full Text\n\nCosta D, Gonçalves HA, de Lima LP , et al.: New reference values for maximal respiratory pressures in the Brazilian population. J. Bras. Pneumol. 2010 Jun; 36(3): 306–12. PubMed Abstract \| Publisher Full Text\n\nPollentier B, Irons SL, Benedetto CM, et al.: Examination of the Six Minute Walk Test to Determine Functional Capacity in People with Chronic Heart Failure: A Systematic Review. Cardiopulm. Phys. Ther. J. 2010 Mar; 21(1): 13–21. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nWHOQOL-BREF\|The World Health Organization:[cited 2020 Nov 25].Reference Source\n\nTickle-Degnen L: Nuts and bolts of conducting feasibility studies. Am. J. Occup. Ther. 2013 Apr; 67(2): 171–176. PubMed Abstract \| Publisher Full Text\n\nOrsmond GI, Cohn ES: The Distinctive Features of a Feasibility Study: Objectives and Guiding Questions. OTJR (Thorofare N J). 2015 Jul; 35(3): 169–177. PubMed Abstract \| Publisher Full Text\n\nBowen DJ, Kreuter M, Spring B, et al.: How We Design Feasibility Studies. Am. J. Prev. Med. 2009 May; 36(5): 452–457. PubMed Abstract \| Publisher Full Text\n\njamovi - Stats: Open. Now.[cited 2022 Apr 21].Reference Source\n\nThe Comprehensive R Archive Network:[cited 2022 Apr 21].Reference Source\n\nEldridge SM, Chan CL, Campbell MJ, et al.: CONSORT 2010 statement: extension to randomised pilot and feasibility trials. BMJ. 2016 Oct 24; 355: i5239. Publisher Full Text\n\nLancaster GA, Thabane L: Guidelines for reporting non-randomised pilot and feasibility studies. Pilot Feasibility Stud. 2019 Oct 6; 5(1): 114. PubMed Abstract \| Publisher Full Text\n\nPiron L, Turolla A, Tonin P, et al.: Satisfaction with care in post-stroke patients undergoing a telerehabilitation programme at home. J. Telemed. Telecare. 2008 Jul; 14(5): 257–260. PubMed Abstract \| Publisher Full Text\n\nEl-Kotob R, Giangregorio LM: Pilot and feasibility studies in exercise, physical activity, or rehabilitation research. Pilot Feasibility Stud. 2018 Aug 14; 4(1): 137. PubMed Abstract \| Publisher Full Text\n\nFeasibility: The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation. 2455 Teller Road, Thousand Oaks, California 91320:SAGE Publications, Inc.;2018 [cited 2022 Apr 22].Reference Source\n\nArain M, Campbell MJ, Cooper CL, et al.: What is a pilot or feasibility study? A review of current practice and editorial policy. BMC Med. Res. Methodol. 2010 Jul 16; 10(1): 67. PubMed Abstract \| Publisher Full Text\n\nThabane L, Ma J, Chu R, et al.: A tutorial on pilot studies: the what, why and how. BMC Med. Res. Methodol. 2010 Jan 6; 10: 1. PubMed Abstract \| Publisher Full Text\n\nEldridge SM, Lancaster GA, Campbell MJ, et al.: Defining Feasibility and Pilot Studies in Preparation for Randomised Controlled Trials: Development of a Conceptual Framework. PLoS One. 2016; 11(3): e0150205. PubMed Abstract \| Publisher Full Text\n\nSteffens D, Young J, Beckenkamp PR, et al.: Feasibility and acceptability of a preoperative exercise program for patients undergoing major cancer surgery: results from a pilot randomized controlled trial. Pilot Feasibility Stud. 2021 Jan 13; 7(1): 27. PubMed Abstract \| Publisher Full Text\n\nMartin D, Besson C, Pache B, et al.: Feasibility of a prehabilitation program before major abdominal surgery: a pilot prospective study. J. Int. Med. Res. 2021 Nov; 49(11): 030006052110601. PubMed Abstract \| Publisher Full Text\n\nNorthgraves MJ, Arunachalam L, Madden LA, et al.: Feasibility of a novel exercise prehabilitation programme in patients scheduled for elective colorectal surgery: a feasibility randomised controlled trial. Support Care Cancer. 2020 Jul; 28(7): 3197–3206. PubMed Abstract \| Publisher Full Text\n\nPatel NU, Moore BA, Craver RF, et al.: Ethical considerations in adherence research. Patient Prefer. Adherence. 2016 Dec 5; 10: 2429–2435. PubMed Abstract \| Publisher Full Text\n\nGil Obando LM, López López A, Ávila CL: Normal values of the maximal respiratory pressures in healthy people older than 20 years old in the City of Manizales - Colombia. Colomb Med (Cali). 43(2): 119–125. PubMed Abstract \| Publisher Full Text\n\nSouza: Maximal static respiratory pressures - Google Scholar.[cited 2022 Apr 23].Reference Source\n\nATS Statement\|Guidelines for the Six-Minute Walk Test\|American Journal of Respiratory and Critical Care Medicine:[cited 2020 Nov 26].Reference Source\n\nWHOQOL - Measuring Quality of Life\|The World Health Organization:[cited 2020 Nov 25].Reference Source\n\nNoronha JN, Samuel SR, Singh P, et al.: Feasibility and Effectiveness of exercise-based prehabilitation in patients opting for elective abdominal surgeries: a pre-post study. Dataset.2022, June 30. Publisher Full Text" }	[ { "id": "169660", "date": "19 Apr 2023", "name": "Yannick Deswysen", "expertise": [ "Reviewer Expertise Surgery", "abdominal surgery", "perioperative care research", "oncological research" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nInterest in preparing patients for surgery is growing. The use of specific programs such as prehabilitation seems to be able to meet this demand. The proposed article seems to determine the feasibility of physical and respiratory preparation before abdominal surgery in India. This study does not appear to be designed to establish the effectiveness of such a program. The inclusion and exclusion criteria are not adequate, nor is the duration of treatment proposed. Indeed, the literature on the subject seems fairly unanimous in suggesting a program of at least 2 to 3 weeks to obtain an effect on the parameters studied. No impact could therefore be studied for a period of 1 to 4 days.\n\nIs the work clearly and accurately presented and does it cite the current literature? No\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "179321", "date": "30 Jun 2023", "name": "Ianthe Boden", "expertise": [ "Reviewer Expertise Postoperative pulmonary complications after major surgery. Prehabilitation. Physiotherapy and major surgery." ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nOVERALL: The reporting could be improved with some language editing so that the writing is more refined and succinct. There are numerous grammatical errors which detract from the scientific content.\nThe academic reporting of this interesting study unfortunately falls short of expectations. There are very good intentions here to analyze the feasibility of providing prehabilitation to patients prior to major surgery, however, there are numerous limitations in how the study has been designed and reported that seriously diminish the academic validity of this study.\nThis study would benefit from an academic supervisor to improve how this is reported.\nABSTRACT: Please put the study design in the abstract + single centre. Also needs the study sample size.\n\nABBREVIATIONS: FC and PEXT - These two abbreviations are not in standard use within the field. I would recommend that it is spelt out in full and not abbreviated to ensure that the manuscript's message is not lost.\nPARTICPANTS: What do you mean by high risk surgery? This could mean anything.\n\nDESIGN: How is this a pre/post design study? Was there a period before (i.e. no prehab) that outcomes were measured and then compared to a post-intervention phase cohort? Your results don't reflect your title. Your study is simply an observational cohort study.\nSAMPLE SIZE - so a convenience sample then over a year? Not powered to detect a feasibility outcome?\n\nPROCEDURE It would be highly unusual for a patient to be admitted to hospital for prehab in an advanced economy. Prehab is predominantly conducted as an outpatient intervention. This diminishes the generalisability to other sites.\nRESULTS: When comparing within patients ie. the 6MWT you need to ensure that you don't just report the p value but the mean difference and 95%CI.\nREFERENCES: Christensen 1993 - very old reference. Is there a more recent one you could use?\nOverend 2001 is not an appropriate reference to use for the statement in the introduction and is now >20yrs old. Consider Boden & Denehy 20211 for an overview of the respiratory effects of major surgery and effective respiratory prehabilitation interventions.\nNoronha 2022 - not appropriate to use a reference in a paediatric population. Not relevant to your study cohort. There are plenty of adult references you could use to support prehabilitation following major surgery - suggestion Assouline 20202. You will find that this systematic review supports many of your assertions, including the effect of IMT and/or whole body exercise training\nGoncalves & Groth 2019 - not a valid reference. Please replace or edit.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-805
https://f1000research.com/articles/11-475/v1	29 Apr 22	{ "type": "Software Tool Article", "title": "Adamant: a JSON schema-based metadata editor for research data management workflows", "authors": [ "Ihda Chaerony Siffa", "Jan Schäfer", "Markus M. Becker", "Jan Schäfer", "Markus M. Becker" ], "abstract": "The web tool Adamant has been developed to systematically collect research metadata as early as the conception of the experiment. Adamant enables a continuous, consistent, and transparent research data management (RDM) process, which is a key element of good scientific practice ensuring the path to Findable, Accessible, Interoperable, Reusable (FAIR) research data. It simplifies the creation of on-demand metadata schemas and the collection of metadata according to established or new standards. The approach is based on JavaScript Object Notation (JSON) schema, where any valid schema can be presented as an interactive web-form. Furthermore, Adamant eases the integration of numerous available RDM methods and software tools into the everyday research activities of especially small independent laboratories. A programming interface allows programmatic integration with other software tools such as electronic lab books or repositories. The user interface (UI) of Adamant is designed to be as user friendly as possible. Each UI element is self-explanatory and intuitive to use, which makes it accessible for users that have little to no experience with JSON format and programming in general. Several examples of research data management workflows that can be implemented using Adamant are introduced. Adamant (client-only version) is available from: https://plasma-mds.github.io/adamant.", "keywords": [ "Research Data Management", "JSON Schema", "FAIR Principles" ], "content": "Introduction\n\nThe demand of funding organizations and publishers to make research data discoverable, accessible, interoperable, and reusable in the sense of the FAIR principles1 and the associated need for digitization and automation of research data management (RDM) processes pose new challenges for some research fields. In particular, for smaller laboratories in physics departments that operate away from large-scale experiments in astrophysics, or high-energy physics, new processes for research data management must be introduced and established. While the aspects of findability and accessibility can be realized without much effort by means of a data publication on a generic platform, the interoperability and reusability of the (domain-specific) data and metadata often pose a major challenge and requires certain conventions and standards in the communities. There are hardly any common research data management processes in areas such as optics and low-temperature plasma physics, and handwritten laboratory notebooks are still the standard in many places.2 On the other hand, electronic laboratory notebook (ELN) systems, repositories, collaborative tools, and (meta-)data standards already exist that can support the implementation of the FAIR principles and Open Science practices. A major challenge is to integrate these tools and standards into the everyday research activities. This is especially challenging when extremely diverse needs have to be addressed at institutions, no specific standard procedures and (meta-)data standards exist, and only a few scientists at a time are dealing with similar instruments and data.\n\nAdamant has been developed to support especially these often small laboratories and departments in the implementation of digital research data management processes and the step-by-step adoption of the FAIR principles. To this end, a tool is provided for the easy use or compilation and creation of domain-specific metadata and metadata schemas based on the widely used JavaScript Object Notation (JSON) schema standard, which recently has been gaining traction in several scientific communities.3–7 The use of JSON schema in Adamant enables straightforward validation of the metadata ensuring its quality.8,9 Furthermore, storing the metadata in JSON format maintains the adaptability of the created metadata with different RDM tools and processes, and increases the findability of the research data to which the metadata is attached, in view of the fact that JSON documents are human- and machine-readable.8,10,11 An Application Programming Interface (API) based integration with other systems enables the seamless embedding of Adamant into institutional research data management processes. This positions Adamant directly alongside electronic laboratory notebook systems and makes it suitable for ensuring standards-compliant documentation of scientific studies as early as the planning and execution of experiments.\n\nIn its current form, Adamant (v1.0.0) offers various features that can support diverse workflows within RDM activities. The features are as follow:\n\n• Rendering of interactive web-form based on a valid JSON schema\n\n• User-friendly editing process of the rendered web-form and the corresponding schema\n\n• Creating a valid JSON schema and web-form from scratch\n\n• Live validation for various field types\n\n• Quick re-use of existing schemas from a list\n\n• Downloadable JSON schema and its form data\n\n• API-based integration as various form submission functionalities\n\n\nMethods\n\nThis section describes the thought process of selecting the technology stack for the development of Adamant, and the implementation details of the tool’s functionalities. Subsequently, detailed descriptions on how to set up and operate Adamant are described. The code is available from GitHub and is archived with Zenodo.29\n\nTechnology stack and architecture\n\nAdamant has been developed as a web-based tool. This decision was motivated by the end user experience, where end users can use Adamant directly on a web browser available on their machines and handheld devices with no prior installation and configurations required. We considered several things when choosing the right technology stack for developing Adamant, such as the availability and ease of use of the technology, whether its community is active and big, and the possibility of the technology still being relevant in the coming years, often indicated by its adoption rate and popularity. For these reasons, we adopted a technology stack consisting solely of open-source software, such as ReactJS12 and Flask13 (as the main development frameworks). This stack utilizes two of the most popular programming languages, namely JavaScript and Python14 (Python Programming Language, RRID:SCR_008394). On top of that, we utilized Docker (Docker Desktop, RRID:SCR_016445) and Docker Compose for straightforward packaging and deployment of the developed tool.15 Like a typical web tool or application, Adamant consists of front-end and back-end layers. The front-end part serves as the presentation layer in the form of a Graphical User Interface (GUI) for end users to interact with. The back-end part is a server-side part of the tool with the main task of providing processes that are not suitable to be run on the client-side[1]. Lastly, the front-end and back-end layers are bridged using an API built upon the Hypertext Transfer Protocol (HTTP) request methods, such as POST and GET.\n\nThe front-end has been developed in the Node.js16 (v14.15.5) JavaScript runtime environment making use of ReactJS (v17.0.2), which is a popular JavaScript library for developing a highly interactive browser-based GUI. ReactJS is combined with the Material-UI library17 (v4.12.3), which contains many pre-existing user interface (UI) components. The pre-existing components can be modified to one’s need straightforwardly thus accelerating the UI development. The main bulk of the features are implemented on the front-end. This includes the automatic rendering process of a JSON schema into a web-form, form editing logic (editing of the rendered web-form or creating one from scratch), and input validation processes. The back-end is written in Python (v3.8.7) using the Flask library (v2.0.2). Flask is a lightweight web framework and straightforward to use making it suitable for the scope of Adamant development. The back-end’s tasks include providing the front-end with available JSON schemas from the server, data preparation, necessary e-mail notification for users, and API calls for communication with external applications (API based integration), e.g., ELN and online data repository systems.\n\nFigure 1 provides an overview of Adamant’s software architecture and the main functionalities of each application layer along with the corresponding technologies.\n\nAPI, Application Programming Interface; JSON, JavaScript Object Notation; HTTP, Hypertext Transfer Protocol.\n\nFront-end: JSON schema to editable web-form\n\nA JSON schema, like every other JSON document, contains key (word)-value pair instances, where the value parts may contain another set of keyword-value pairs, i.e., nested objects.8,10,11 In a JSON schema, there are a number of schema-specific keywords that are mainly used for validation and annotation of the elements in a schema.8,9 For example, a typical set of schema-specific keywords found in a JSON schema and its sub-schema contains $id/id, $schema, title, type, and properties keywords.9 On many occasions, more specific keywords are used to further annotate or describe the elements in a schema. The specific functions of these keywords are dictated by the schema specification version a JSON schema is specified in, which is declared at the very beginning of the schema under the $schema keyword. A comprehensive documentation of the JSON schema standard can be found at https://json-schema.org/. An example of a JSON schema with the specification version draft 4 is shown in Listing 1, which contains the typical keywords stated earlier, and several field elements. One of the main features of Adamant is to create a web-form representation of a given JSON schema, where users can fill it in and create a JSON document containing the form data for anything they want to describe, e.g., a lab experiment or a dataset. It is worth noting that there are several freely-available libraries and tools for JSON form rendering that conform to the JSON schema specifications.18–21 Unfortunately, the available libraries and tools, though some offer direct editing of the schema, do not provide a user-friendly interface for schema (or form) creation and editing right out of the box as what we have envisioned with Adamant. Therefore, we decided to build a custom JSON schema form renderer from the ground up in order to achieve this, which allows us to maintain full control as well as flexibility during the development of Adamant’s current and future features. At the time of writing this paper, Adamant (v1.0.0) supports the rendering and editing of JSON schemas with a specification version draft 4 or 7.\n\nJSON, JavaScript Object Notation.\n\nAdamant employs a recursive form field rendering process that makes accessing of the keyword-value pairs located within nested objects possible. The rendering process starts by determining the value of the type keyword in the uppermost object (or parent object) of the schema. The type keyword in this location commonly has a string value of object. This value indicates that a properties keyword is present within the same location. The properties keyword’s value is a set of keyword-value pairs (an object), where each pair contains the information that the process needs to render the field. As the process iterates over these keyword-value pairs, it renders a certain form field type according to its type keyword’s value. The acceptable types in a JSON schema are string, number, integer, boolean, array, and object. If the process stumbles upon a field keyword that has the type of object again, then a container will be rendered, and the recursion process is initiated. This process iterates over the current properties keyword’s value following the same procedure as before, and renders each field within the newly created container. In this way, the process will not terminate until all form fields are rendered. This is a condition where the process does not find any field keyword with the type of object anymore. Apart from the type keyword’s values, the renderer also makes use of other keywords’ values to adorn the form field with useful information, such as the values of title and description keywords (annotation keywords). The main steps of this form field rendering process is also represented in a flowchart diagram as shown in Figure 2.\n\nJSON, JavaScript Object Notation.\n\nAnother main feature of Adamant is the capability of editing the rendered fields. This feature allows users to change the values of relevant keywords in the schema, and re-order the rendered fields within the same container. To achieve this feature, apart from the rendering of the form fields, each rendered field is also supplied with several editing interfaces along with the editing and input handling logic. Creating a schema (or form) from scratch is another feature made possible by using the same principle of this form editing feature, which basically presents the user with a blank schema and lets them add the field elements as required.\n\nFor a certain use case, a file upload functionality can be included in a rendered form. This functionality is intended as an alternative way of enriching the metadata when texts are no longer sufficient. For example, an experiment may have a graphical description of its set-up. In this case, the user can include an image file within the metadata using this file upload functionality. To add this functionality, a string-type field element, with the addition of “contentEncoding”:“base64” keyword-value pair, must be specified in the schema. This particular keyword-value pair will inform the rendering function to create a file upload field element, where the selected file is read as a string of base64-encoded binary data. Fortunately, adding the file upload functionality can be done in only a couple of mouse clicks in Adamant. For a smooth experience, the uploaded file is recommended to have the size of less than 500 kilobytes.\n\nLastly, Table 1 presents a complete list of the implemented field types and their relevant keywords in the current version of Adamant (v1.0.0).\n\nNote that the id keyword only works with the JSON schema specification version draft 4, whereas $id is used for the newer specification drafts. Lastly, the contentEncoding keyword is intended to be used with the specification version draft 7 or newer. JSON, JavaScript Object Notation.\n\nFront-end: JSON form data validation using Ajv\n\nAs the user fills in the form, a JSON document containing the entered data is created and updated accordingly and simultaneously, this JSON document is called JSON form data. Upon finishing the form filling process, the created JSON form data can be used for other operations. To ensure the correctness or quality of the entered data, the JSON form data is validated against its schema prior further operation. For this validation purpose, Adamant takes the advantage of the Ajv library (v8.8.2).22 By using this library, any discrepancies between the JSON form data and its schema can be identified. For example, if a field is required to be filled and the user does not provide any input, then the process will throw a validation error with relevant error messages. Many other keyword specific validations are included in this library, which helps with ensuring the quality of the form data with respect to its schema.\n\nBack-end: API-based integration\n\nMany existing web applications provide APIs for seamless integration with other (external) web tools or applications. For instance, web applications that are commonly used in the RDM community include online data repository systems, ELNs, collaborative and version control applications, etc. These applications, more often than not, provide API endpoints that are straightforward to use. Several web tools have also been developed each addressing certain challenges in RDM, such as COPO,3 and Dendro.23 Adamant is equipped with a back-end layer whose main purpose is to ensure the possibility of seamless integration with such web applications. The back-end is written in Python (v3.8.7) using the Flask library (v2.0.2), which is advantageous given numerous web applications provide Python libraries for their API calls. The connection between Adamant’s front-end and back-end is achieved primarily using the POST and GET HTTP request methods. The POST method is used to send data from the front-end to the back-end, which is then pre-processed (if needed) and relayed to the external application (using the provided API). The GET method is used when the client-side requires information or data only available in the server-side or from an external application, e.g., when retrieving schemas from the server, or retrieving tags and database items from an external application. With this straightforward approach, various functionalities can be implemented in the server-side that can help with realizing application-specific RDM workflows.\n\nMany features of Adamant can be explored directly in the client-only version available online at https://plasma-mds.github.io/adamant. This version only lacks the submission-related features, which require the server-side to operate. To access the full features, Adamant can be set up and deployed on a local machine or a server that allows for running both the client and server sides. In most instances, Adamant is not resource intensive, and can be used on a typical smartphone and laptop. However, for deployment and development, we recommend to set up Adamant on a system with at least a 64-bit CPU (with 4 cores) and 8GB of RAM. At the time of writing, Adamant has been tested on Firefox (91.5.1esr), Chrome (v97.0.4692.99), and Chrome Mobile (v97.0.4692.98) web browsers. The following subsections introduce the deployment process of Adamant and how users can interact with it.\n\nSetting up Adamant on a local machine\n\nFor development purpose, Adamant can be set up on a local machine. For a Linux system (tested on Ubuntu 20.04.4 LTS), the following steps can be taken for this:\n\n1. $ git clone https://github.com/plasma-mds/adamant.git — clone the repository\n\n2. $ cd adamant — go to adamant project directory\n\n3. adamant$ npm install — install the dependencies for the client-side\n\n4. adamant$ cd backend — go to backend directory\n\n5. adamant/backend$ python3 -m venv venv — create a python virtual environment\n\n6. adamant/backend$ source./venv/bin/activate — activate the virtual environment\n\n7. adamant/backend$ pip install -r requirements.txt — install the dependencies for the back-end\n\n8. adamant/backend$ ./venv/bin/flask run --no-debugger — start the back-end\n\n9. Start a new terminal\n\n10. adamant$ npm start — on the new terminal, in the adamant project directory, start the client-side\n\nTypically, a web-browser presenting the client-side will open automatically following the last command. In any case, Adamant can be accessed at http://localhost:3000.\n\nDeploying Adamant using Docker\n\nAdamant is intended to be deployed on an institutional server in the internal network. In this way, anyone who is connected to the institute’s network can use Adamant directly. We recommend using Docker to deploy the production build of Adamant, which can be done with the following steps:\n\n1. $ git clone https://github.com/plasma-mds/adamant.git — clone the repository\n\n2. $ cd adamant — go to adamant project directory\n\n3. adamant$ docker−compose build — build the docker images for both back-end and front-end\n\n4. adamant$ docker−compose up -d — start both client and server containers, i.e., the whole system\n\nBy default, the deployed system can be accessed at http://localhost:3000.\n\nGeneral overview of the Adamant UI\n\nThe general overview of the Adamant UI is presented in Figure 3. Adamant renders a given JSON schema into a web-form by uploading the schema from a local drive using the “BROWSE SCHEMA” button, or if already existing, the schema can be selected from a list next to the browse button. Creating a JSON schema from scratch is possible by clicking the “CREATE FROM SCRATCH” button. After uploading or selecting the schema, the schema is checked by Adamant to see whether the schema file type and structure are valid. If the schema is valid, the schema can be rendered by clicking the “RENDER” button. The rendering can be undone by clicking the “CLEAR” button, which also discards the current schema.\n\n(A) Main corpus of the UI; (1) from left to right: JSON schema viewer, auto-populate form, edit schema description, revert all changes; (2) remove form field; (3) collapse or expand the field container; (4) field drag handle; (5) edit field description and (B) field editing panel (as a pop-up on top of the main UI) triggered by clicking (5) the edit button. UI, user interface; JSON, JavaScript Object Notation.\n\nAs a demonstration, Figure 3 shows the rendered web-form based on the schema represented in Listing 1. Each rendered field is shown along with its editing interfaces, and the field container’s header is rendered in blue for a quick identification. Furthermore, the field container can be expanded and collapsed for a good user experience. The editing interfaces found in each field consists of edit and remove button icons, and a drag handle icon. These interfaces allow the user to change the values of relevant keywords in the schema (directly affecting the rendered field), and re-order the rendered fields by dragging and dropping the field to the desired order within the same container. The changes are reflected to the rendered form immediately, which promotes a What You See Is What You Get (WYSIWYG) application experience for the users. On top of that, each field container is equipped with the “ADD ELEMENT” button for adding a new field within the corresponding container. By default, Adamant renders the form in the edit mode right after a schema is rendered. The editing mode can be concluded by pressing the “COMPILE” button, which removes all editing interfaces (thus also removes the editing functionalities) and readies the form for use. In case of needing to edit the form again, the user is able to initiate the editing mode again, and without losing the already entered data.\n\nAdding and removing schemas\n\nA number of schemas can be fixed in the back-end. The back-end serve these stored schemas to the front-end, from which the end users can select. This is important for a quick re-use of the schemas, especially the ones that are regularly used. For this purpose, one can simply add the desired schemas to adamant/backend/schemas/ directory. Likewise, a schema can be removed from this directory. The list of the schemas in the front-end is updated every time the front-end is refreshed.\n\n\nUse cases\n\nAt its core, Adamant is a JSON schema form renderer-editor and JSON form data creator presented in an interactive and user-friendly UI. It can be operated by anyone with no prior knowledge of JSON format and coding. This section elaborates the general and ad hoc use cases of Adamant that it can be suited to.\n\nThe creation or use of a valid JSON schema and the collection of corresponding form data being consistent with the schema can be considered as the general use case of Adamant, which simplifies the collection of structured and standardized metadata. This is particularly relevant for laboratories that are not embedded in large research clusters providing access to established standards and digital research data management workflows. On the one hand, the ability to define required metadata fields and formats supports metadata quality assurance, and on the other hand, storing metadata in JSON format enables further (automated) processing of metadata. This both directly contributes to the “FAIRness” of metadata.\n\nThe use case introduced here aims to highlight how the previously described ability to interface with external systems through API-based integration can be used to generate schema-compliant experiment descriptions in eLabFTW. The open source ELN system eLabFTW24,25 (elabFTW, RRID:SCR_013971) is becoming increasingly popular, especially at universities and research institutions. Given Adamant’s features (JSON schema-based metadata creation, input validations, etc.), one can see why it could be beneficial to collect structured metadata using Adamant rather than doing it directly in the ELN system, especially when the ELN system is designed to be as general as possible in order to accommodate various kinds of experiments from different scientific fields. Note that eLabFTW already offers the possibility to use predefined templates and to edit JSON files. However, a user-friendly possibility to work directly with JSON schemas and to validate the entered metadata on the basis of these predefined schemas is missing so far.\n\nFigure 4 shows the workflow for creating an experiment using Adamant in the eLabFTW system from the end-user’s perspective. The user generates the experiment form by uploading their experiment schema, or selecting it from the list if it already exists. Alternatively, the user can create the form from scratch. If necessary, the user can edit the form (affecting the given schema). For example, changing the title of a certain field, removing a field, etc. When satisfied, the user can compile the rendered form and proceed to fill it in. Upon completing the form, Adamant validates the entered data against the given schema and notifies the user if discrepancies between the entered data and the schema are found, which the user can rectify thereafter. When the entered data are valid, the user can proceed to review the form. After a thorough review, the user can proceed and submit the form. During the submission process, the user will be prompted to input the URL of their eLabFTW system and their eLabFTW API token. Optionally, the user can provide the title and the tags for their experiment. Upon submission, Adamant’s back-end prepares the content and creates a new experiment in eLabFTW accordingly, making use of the available eLabFTW API for python, namely elabapy (v0.8.2).26,27 The user will be notified upon a successful submission, and the created experiment can be viewed in the eLabFTW system.\n\nThe eLabFTW system (v4.2.2) makes use of the TinyMCE text editor28 for free text descriptions of experiments. Here, HTML content can be loaded and rendered. Based on this functionality, the present implementation of the described workflow generates an HTML description list content based on the submitted JSON form data and its schema. The title of the field (obtained from the schema) is used and paired with the value of this field, as shown in Figure 5(a), where the titles are encapsulated within the <dt> tags, the values within the <dd> tags, and the complete pairs in the <dl> tags. The description list is rendered in a way to attain or simulate the look of a form, as presented in Figure 5(b), which increases the readability of the content. This result is achieved by using a custom Cascading Style Sheets (CSS) styling, which can be provided to the eLabFTW system. The generation of this description list content is carried out on Adamant’s front-end side. Note that it is equally possible to upload the experiment information prepared in Adamant directly to the eLabFTW experiment in JSON format. However, this would present it in the form of additional information to the experiment description. Since we consider the structured metadata to be the main component of the experiment documentation, the described workaround based on the HTML description lists in the main body has been chosen. Still, the schema, JSON form data, and uploaded files (if available) are sent as attachments to the eLabFTW experiment. In this way, the schema and form data that describe the experiment are preserved and available for re-use, while retaining the high readability of the experiment body for the user.\n\n(a) Title-value pairs in the HTML description list format, and (b) the rendered description list with a custom CSS styling. CSS, Cascading Style Sheets.\n\nResearch institutions are often equipped with advanced laboratory instruments, such as Scanning Electron Microscopy (SEM) and Mass Spectrometry (MS) instruments just to name a few. These instruments are pivotal for various research investigations in many scientific fields. However, not every researcher at the institute is able to operate and has access to such instruments. To this end, we propose a job request workflow using Adamant that also incorporates the use of eLabFTW for experiment documentation.\n\nThe job request workflow represented in Figure 6 aims to streamline the process of requesting a job or an investigation of an object of interest using a laboratory instrument that needs to be carried out by the designated instrument operator. From Adamant’s perspective, this workflow involves two users, namely the researcher who wants to get something done with an instrument they do not know how to use (or do not have access to), denoted as the “requester”, and the instrument operator, denoted as the “operator”. From the documentary point of view, the requester provides the information required to execute the job, while the operator can add metadata related to the instrument and the analysis method. Hence, the schemas used for this workflow can be divided into two, the request schema and the experiment schema. The request schema is used by the requester, and is a subset of the experiment schema including only the form fields for the request details. The experiment schema is used by the operator, which contains every form field necessary to describe the experiment using the selected instrument. Examples of a request schema and its corresponding experiment schema (complete schema) are available here and here, respectively. Both users are notified automatically per e-mail for relevant events within the workflow, such as when the requester submits the job request and the operator starts working on the request. The e-mail notifications are made sure to work accordingly by including the necessary information of the requester and operator within the used schemas, and by setting up the e-mail notification configuration for the relevant schemas. An example of the e-mail notification configuration file can be found in adamant/backend/conf/, in which each configuration parameter is explained. For using more than one job request workflow, one can simply add another schema-specific configuration into the confList keyword. The right configuration is then automatically selected based on the relevant schema titles.\n\nJSON, JavaScript Object Notation.\n\n\nConclusions\n\nWe have developed a web-based tool named Adamant with the aim of easing the implementation of digital research data management processes. With this, we intent to support the adoption of the FAIR data principles in independent labs, which do not (yet) have access to established research data management infrastructures and domain-specific standards. Adamant provides straightforward compilation and creation of metadata and metadata schemas based on the JSON schema standard, and API-based integration with other available research data management software tools. The intuitive and self-explanatory UI of Adamant increases the accessibility for users with little to no experience with JSON format and programming in general. A flagship implementation of Adamant is the use of the tool, generally, in a core facility or laboratory of a research institute that often hosts advanced scientific equipment, such as the scanning electron microscopy instrument. This is often an advanced expertise that different teams want to use, while a small competence group (experts in such an instrument) ensures that the investigation tasks are optimally processed. Such a use case is demonstrated in the Adamant’s submission of metadata for research lab workflow. With that as an example, Adamant can be suited to many specific use cases by extending it with relevant submission functionalities.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nSoftware availability\n\n\n\n• Adamant (client-only version) available from: https://plasma-mds.github.io/adamant\n\n• Source code available from: https://github.com/plasma-mds/adamant\n\n• Archived source code at time of publication: https://doi.org/10.5281/zenodo.639618229\n\n• License: MIT", "appendix": "Acknowledgements\n\nThe authors would like to thank Nick Plathe for their helpful suggestions and Laura Vilardell Scholten for developing the description list CSS code.\n\n\nReferences\n\nWilkinson MD, Dumontier M, Aalbersberg IJ, et al.: The FAIR guiding principles for scientific data management and stewardship. Sci. Data. 2016; 3: 160018. PubMed Abstract \| Publisher Full Text\n\nIsrael H, Tobschall E, Tristram F: Dataset for the publication “Umfrage zum Forschungsdatenmanagement in der Physik”.2021. Publisher Full Text\n\nShaw F, Etuk A, Minotto A, et al.: COPO: a metadata platform for brokering FAIR data in the life sciences [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Res. 2020; 9: 495. Publisher Full Text\n\nFranke S, Paulet L, Schäfer J, et al.: Plasma-MDS, a metadata schema for plasma science with examples from plasma technology. Sci. Data. 2020; 7: 439. Publisher Full Text\n\nP.-K. consortium: PDBe-KB: a community-driven resource for structural and functional annotations. Nucleic Acids Res. 10 2019; 48: D344–D353. Publisher Full Text\n\nThe Human Cell Atlas Metadata Standards: JSON Schemas: 2022. Accessed: 2022-04-12. Reference Source\n\nMetadata-Schemas-for-Materials-Science: 2022. Accessed: 2022-04-12. Reference Source\n\nPezoa F, Reutter JL, Suarez F, et al.: Foundations of JSON Schema. Proceedings of the 25th International Conference on World Wide Web. 2016; pp. 263–273. International World Wide Web Conferences Steering Committee. Publisher Full Text\n\nDroettboom M, et al.: Understanding JSON Schema.2022. Accessed: 2022-02-04. Reference Source\n\nIntroducing JSON: 2022. Accessed: 2022-03-01. Reference Source\n\nBray T: The JavaScript Object Notation (JSON) Data Interchange Format.RFC 7158, 2014.\n\nReactJS API: 2022. Accessed: 2022-02-04. Reference Source\n\nFlask: 2022. Accessed: 2022-02-04. Reference Source\n\nVan Rossum G, Drake FL: Python 3 Reference Manual. Scotts Valley, CA: CreateSpace; 2009.\n\nMerkel D: Docker: lightweight linux containers for consistent development and deployment. Linux journal. 2014; 2014(239): 2.\n\nNode.js: 2022. Accessed: 2022-04-12. Reference Source\n\nMaterial-UI: 2022. Accessed: 2022-02-04. Reference Source\n\nreact-jsonschema-form: 2022. Accessed: 2022-02-04. Reference Source\n\njsonform: 2022. Accessed: 2022-02-04. Reference Source\n\njsonforms.io: 2022. Accessed: 2022-02-04. Reference Source\n\njson-editor: 2022. Accessed: 2022-02-04. Reference Source\n\nAjv JSON schema validator: 2022. Accessed: 2022-02-04. Reference Source\n\nRocha da Silva J, Aguiar Castro J, Ribeiro C, et al.: Dendro: Collaborative research data management built on linked open data. The Semantic Web: ESWC 2014 Satellite Events. Presutti V, Blomqvist E, Troncy R, et al., editors. Cham: Springer International Publishing; 2014; pp. 483–487. Publisher Full Text\n\neLabFTW: a free and open source electronic lab notebook: 2022. Accessed: 2022-02-04. Reference Source\n\nCarpi N, Minges A, Piel M: eLabFTW: An open source laboratory notebook for research labs. J. Open Source Softw. 2017; 2(12): 146. Publisher Full Text\n\neLabFTW API: 2022. Accessed: 2022-02-04. Reference Source\n\nelabapy at PyPI: 2022. Accessed: 2022-02-04. Reference Source\n\nTinyMCE: 2022. Accessed: 2022-02-04. Reference Source\n\nChaerony Siffa I, Schäfer J, Becker MM: plasma-mds/adamant: Adamant Initial Release v1.0.0 (v1.0.0). Zenodo. 2022. Publisher Full Text\n\n\nFootnotes\n\n1 In this paper, the terms “front-end” and “client-side” are used interchangeably, as well as “back-end” and “server-side”." }	[ { "id": "136392", "date": "03 May 2022", "name": "Felix Shaw", "expertise": [ "Reviewer Expertise Data Science", "Open Science", "Metadata Standards", "Web Development" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nStandards for experimental metadata are in most cases sub-optimal or non-existent. Being able to describe protocols, samples, instruments, etc. in a consistent way is vital to the reusability of data and the reproducibility of work. This situation will only continue with the prevalence of machine learning techniques in science which rely heavily on labeled data. Adamant is a web tool for authoring generic experimental assays and then filling out such assays. Users are presented with an interface in which they can add fields of different data types, and various input restrictions (e.g. enumerations, character lengths, etc.). The system then creates a JSON document that records these fields and can be used later for validation and display. Users can then fill out these generated forms with real assay data which is validated against the JSON document, and in turn, produces another JSON document with the assay data itself.\nThis is a good tool, is well presented, and is easy to use. In functionality, it seems comparable with the ISATools suite of software, although less mature and (arguably) more intuitive. It uses industry-standard software (Python, Flask, React, etc.) and is under an MIT license on Github, meaning anyone can download and modify it. This means if uptake is good, there is a fair possibility of community maintenance. There are precious few tools for authoring metadata schemas, and this is a welcome step in the right direction. I downloaded and tested the docker version and it worked without any problem. I didn't download and run the development version.\nThere are some things I would like to see:\nCreating metadata standards is in my experience very much a community effort. Whilst this tool makes the \"process\" of making metadata standards easy, there needs to be an emphasis on community agreed standards. Otherwise, we risk the proliferation of a multitude of standards that fit only very niche applications.\n\nTalking of community agreed standards, it would be nice to have a large selection of existing standard schemas available for users to select, and then possibly edit. This would be a big time-saver for a lot of researchers.\n\nThere doesn't seem to be a way of using ontology terms for field names, values, or units. Ontologies are the best way of disambiguating metadata, and services such as EMBL/EBI's Ontology Lookup Service make real-time searching for ontology terms easy. I would like to see this implemented in the authoring stage.\n\nI have a feeling this will not scale particularly well. It's fine to fill out a web form for a few samples or assays, but in practice, researchers will have hundreds or thousands of records. Filling out web forms on this scale is impracticable. I would like to know the author's views on how to overcome this issue.\n\nWhilst the authors give the use case of submitting an assay to eLabFTW, it would be nice to see some other integrations, such as with Dataverse, Dspace, or CKAN repositories, which are often used by smaller research facilities (the apparent target audience for this work).\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "8503", "date": "19 Jul 2022", "name": "Ihda Chaerony Siffa", "role": "Author Response", "response": "We thank Felix Shaw for their insightful and constructive comments and helpful suggestions. Some of the comments are in line with what we already have in mind for further development of the tool which we will include in the next version of the manuscript as an outlook. Nevertheless, we will still attempt to address each individual comment briefly as follows: Response for comment 1: We definitely agree and have experienced this matter first hand. At the very early stage, Adamant is intended to be used to create and design the initial experiment schema, which later can be shared/made public in a publicly available collaborative version control platform (like GitHub). Once the schema is made public, the community can participate in the further development and maintenance of the said schema. Response for comment 2: Thank you very much for this suggestion. Besides the public maintenance of already available schemas for the domain of plasma technology (see our community effort at https://www.plasma-mds.org) it is indeed an interesting idea to provide easy access to established standards like Dublin Core, DataCite, etc., via Adamant. We will think further in that direction. Response for comment 3: We agree with the comments regarding ontologies and we have already thought of something in this direction. We will definitely implement features related to the use of ontologies in the future release of Adamant. One thing that we have planned is to have a domain-specific ontology that can be attached to the tool where it can be used to populate the domain-specific knowledge graph. Response for comment 4: This is true. In the field of low-temperature plasma science and technology, there is rarely any case that requires the researcher to fill out hundreds or even thousands of entries in an experiment. However, to make sure that Adamant can be adopted in different research fields, this requirement is, of course, crucial. One thing that we have in mind is to have a feature of uploading a tabular file, which is then translated to its JSON representation. Such a feature would also enable the collection and further processing of standard-conform metadata in “offline” field experiments. Response for comment 5: Currently, we are looking into implementing a feature of dataset publication in the DKAN-based data platform INPTDAT (https://www.inptdat.de/). The idea is to re-use the collected experiment metadata (created with Adamant and stored in the eLabFTW ELN) and bundle it with the dataset for publication. Note that the back-end can be easily adapted to use the existing APIs of the mentioned repository platforms to publish metadata, once it is available in a standardized format." } ] }, { "id": "136576", "date": "07 Jun 2022", "name": "Frank Krüger", "expertise": [ "Reviewer Expertise Data Science", "Provenance", "Metadata" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe FAIR Guiding Principles require, among other things, the provision of rich metadata for research data and the generating processes. For this purpose, structured information that reuses existing vocabulary in a standardized way is desired. While such thorough documentation improves the reusability of the research data, it demands knowledge about appropriate vocabularies (e.g. DCAT, DDI...) and some minimum technical understanding of structured documentation (e.g. JSON, JSON-LD, RDF...) of researchers from all scientific domains. Furthermore, mechanisms to ensure the provision of some minimal required information are necessary. These requirements increase the complexity of providing FAIR data and create the need for appropriate tool support.\nAdamant is a web-based tool for the provision of structured metadata which guides the researcher through the documentation process and provides a means for validation of the content and completeness by providing a schema-based form. The underlying schema can either be loaded from a library or particularly designed for the research process at hand. By providing a rich API, Adamant satisfies further requirements for the integration into complex workflows based on virtual research environments.\nFrom the technical perspective, Adamant employs JSON Schema, a technology to specify the structure of JSON documents including required and optional information. A web-form, based on Python/Flask, is generated from the schema that is presented to the end-user to provide the necessary information. Adamant is publicly hosted for testing purposes and can easily be deployed by using the provided docker image. All code is available from github and archived at Zenodo. The released version worked without any problems for me. I tested the web-form and the integration with elabFTW.\nWhile I like Adamant and the article very much, I have a few suggestions/questions:\nAdamant is based on JSON Schema and JSON, but recently I recognized an increase in RDF-based (meta)data management. I was wondering if RDF/S and SHACL would also be a viable base for Adamant and why the authors didn't employ those.\n\nI further agree with Felix Shaw (Reviewer 1) about the integration of ontologies for the structured and semantic documentation of research data.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [ { "c_id": "8505", "date": "19 Jul 2022", "name": "Ihda Chaerony Siffa", "role": "Author Response", "response": "We thank Frank Krüger for their valuable comments. The following are our responses to each individual comment: Response for comment 1: From our understanding, it is feasible to use RDF(S) formats and SHACL for generating web-forms and validation. Our arguments on using JSON and JSON Schema instead of RDF(S) and SHACL are (in no particular order): RDF(S)/SHACL are ontology-related standards that are surely the means of choice in cases where well-defined ontologies already exist. Note that Adamant specifically targets use cases for which ontologies or metadata standards do not yet exist. JSON Schema supports a set of data types that are analogous to those found in many programming languages (e.g., Python, JavaScript). This allows straightforward implementation of specific input types and their validations. To the best of our knowledge, the JSON format is the de-facto standard of API data interchange. Since Adamant can be used with different external applications by means of API integration, describing the metadata and its schema in the JSON format seems sensible. Many existing metadata schemas are available in the JSON format. On top of that, we plan on using ontologies, serialized in an RDF format, to describe the schema elements that are used in JSON schemas. A Uniform Resource Identifier (URI) can be assigned to each schema element in the JSON format, which allows the interoperability of these schema elements across both formats. Response for comment 2: Please see the response under Reviewer 1’s comments." } ] } ]	1	https://f1000research.com/articles/11-475
https://f1000research.com/articles/9-1381/v1	30 Nov 20	{ "type": "Research Article", "title": "Analysis and study of the potential increase in energy output generated by prototype solar tracking, roof mounted solar panels", "authors": [ "Jacek Harazin", "Andrzej Wróbel", "Andrzej Wróbel" ], "abstract": "Roof mounted solar panels come in form of fixed panels, unable to adjust to sun’s position during day and throughout the year. As an effect, the efficiency of such solution is usually dependent on the roof slope and position of the building in relation to sun’s day arc during seasons. These problems can be bypassed in free standing solar installations by equipping solar panels with solar tracker installations. Thanks to solar tracking, solar panels can be dynamically positioned perpendicular to the sun position and gather energy more efficiently throughout the day. This article presents a possibility of creating a roof mounted solar tracking panel to increase its efficiency. A prototype of solar tracking panel with two axes of movement was designed with an intention of an easy adaptation to being mounted on sloped surfaces of building roofs. A reference stationary panel was used to compare the efficiency of both solutions. A 5-day study was carried out to determine if the proposed solution could provide any benefits. Based on the study, the authors made an attempt to draw a conclusion whether the design could considerably increase the solar energy output to be worth the extra spending associated with solar tracker installation.", "keywords": [ "solar tracker", "household solar energy", "roof solar panels" ], "content": "Introduction\n\nRenewable energy sources are increasingly perceived by the public as a beneficial alternative to fossil fuels in context of preservation of the environment by limiting the carbon emissions. Recent decades show a steady increase of public interest in percentage of renewable energy sources in the overall energy production1–7. More people are also choosing to supply their homes with renewable energy, mainly through the installation of household solar panel systems in the form of free-standing solar installations and roof mounted panels. Even the citizens of countries located in higher latitudes (such as Poland, England or Sweden, and other countries in Europe located on similar latitudes) with less annual access to solar energy due to weather and seasons have showed an increase of interest in household solar panel installations. The increase of awareness and willingness to focus on renewable energy sources can partly be contributed to numerous government programs that promote the transition with numerous discounts and advertise positive results of such transition. The EU is putting large emphasis on promoting renewable energy sources in recent years by dedicating numerous grants for co-financing own solar installations and introducing regulations that favor renewable energy. Thanks to the financial support it is possible to fund a household solar installation with relatively small financial outlay which attracts many household owners previously discounting such solution due to large entry costs. Another factor that contributes to this situation is the advancement in solar cell efficiency and energy storage technologies. This further decreases the payback time for investment costs which attracts more people.\n\nDepending on the availability of open space, future solar installation owners decide either on purchasing big or small factor free-standing solar panel installations or roof-mounted solar panel installations. Apart from the space availability, authors in 5–7 also mention financial factors such as estimated monthly and yearly household power consumption or costs related to solar panel installation and maintenance. Other factors are connected with country regulations regarding the use of renewable energy sources such as discounts and grants for installations, handling of the energy surplus (whether an owner is obligated to return any surplus of energy into the network and if it’s then available as a buffer or if there is any financial gain to be had). Another set of factors is related to weather conditions in a region where the new solar installation is to be mounted. The change in environment albedo and snow/rain fall are some of the more important factors as snow coverage during winter season can significantly alter albedo, resulting in an increase of solar panel energy output. On the other hand, snow coverage of the panels themselves or rainy weather can seriously hinder any power generation in contrast. One of the most important factors in case of stationary solar panels is the setting of optimal tilt angle for maximally efficient power production of solar panels throughout the year. The authors in 8,9 determine the optimal tilt angle based on slightly different factor compositions. The authors in 8 prioritized maximization of the average solar irradiance throughout the taken period whereas the authors in 9 also taken maximum revenues in the area of solar panel into account in their algorithm. As a result, the optimal tilt angle can vary depending on the emphasis taken on the period when solar panels work (whole year, emphasis on the summer season or skipping of the winter season) and other economic factors that can be considered.\n\nThe advantage of free-standing solar installations over the roof mounted ones can become apparent at the point of determining the optimal tilt angles. Free-standing solar panels can be easily equipped with solar tracking devices, coupled with one or two motors that rotate the panel in one or two axes of movement. This method eliminates the need for determining a fixed tilt angle and allows for dynamic adjustment of solar panel tilt angle depending on the season and time of day. The difference in energy production efficiency between stationary mounted solar panels and solar panels equipped with solar tracking capabilities can vary from 10% to 60% depending on the tracking technology used and considered time of the day7,10–19. In addition, countries that are located on higher geographic latitudes can get more benefit from tracker installations because of the higher volatility of sun position during different seasons. The downside, however, is the lower return in additional costs associated with solar tracker and motors required for the system. The cost efficiency of different solutions may vary greatly, depending on whether there are policies in effect, that allow for either storing excess energy in the communal grid or selling it back to the grid7. If there are no such policies in effect, the use of two axis solar trackers may be the only option worth considering due to high amount of budget that has to be allocated for batteries that store the excess energy. If such policies exist, then solar trackers appear more cost effective, especially on areas with lower solar potential.\n\nThis project aims to create a prototype solution that would enable solar tracking on panels usually mounted on household roofs in urbanized areas. Such a solution could potentially increase the daily energy output of solar panels, giving better energy yields from a relatively small space of a household roof. Such a solution could also make roof solar installations more viable in areas of the globe, where daily sun coverage is mediocre or poor. This article is focused on the testing of the first few iterations of the prototype to verify the authors' prediction that such a project could bring benefit.\n\n\nMethods\n\nThis article concentrates on exploring possibilities of combining the flexibility of free-standing solar panels, equipped with solar trackers and the relatively compact nature of roof mounted solar panels (Figure 1). The idea is motivated by the search for a middle ground solution that would provide at least a portion of benefits carried from the use of solar tracking panels without the large space requirement. Building owners in heavily urbanized areas and household owners in tightly packed residential districts do not possess enough space to fit a cost-effective, ground-mounted solar installation, large enough to justify being fully equipped with solar trackers. The article has a preliminary character in terms of tackling many aspects of solar installations and will be mainly focusing on potential gains in power generation efficiency that come with solar tracking installations. The design of the test stand will be oriented towards the ability to be mounted on a sloped roof. A study will involve an analysis of the solar tracking panel efficiency versus a fixed solar panel in a configuration resembling a mounting on a sloped roof. The obtained results will serve in further research to determine if the potential gain is enough to justify expenses that relate to solar tracking installations.\n\n(a) Free standing solar panel, equipped with a solar tracker and actuators, enabling the tracking of sun position throughout the days and seasons19. (b) Roof-mounted solar panel with a fixed mount and no ability to track the sun.\n\nThe plan for the study included construction of two test benches after conceptual design phase in SIEMENS NX 12. The first test bench was meant for creating a reference data set for the standard mounted roof solar panel. It was designed with the slope angle of 45° and a set of adjustable feet to give it some room for adjustment of the slope on site. The model and its individual spatial projections were shown of Figure 2.\n\n(a) Isometric view. (b) Spatial projections.\n\nThe second test bench was capable of rotating in two axes. In order to enable the following of the sun trajectory during the day, a GPS-based solar tracker was added. The assumption was to enable vertical tilt of around 90 degrees and horizontal tilt of roughly 45° in each direction. To realize the movement, bench was equipped with two self-locking linear actuators, with substantial force of 4000 N to provide control even in windy weather. In order to make the construction more compact and suited for roof applications, the decision was made to use the vertical axis as primary axis. The horizontal axis of movement was a secondary axis. This approach unfortunately restricted the freedom of movement, of the solar panel and complicated the solar tracking algorithm because of the necessity to convert spherical coordinate system to a cylindrical one, in case of the azimuth angle and panel horizontal tilt. The solar tracker was created using an Arduino Uno programmable circuit, coupled with a GPS module, with a solar tracking algorithm that uses GPS as input data. After a search for appropriate solar tracking algorithm in literature sources, a decision was made to use the derivative of a PSA (Plataforma Solar de Almeria) algorithm to calculate sun position out of the data provided by the GPS module10–14,17,20–23. The model of a solar tracking panel and its individual spatial projections were shown on Figure 3.\n\n(a) Isometric view. (b) Spatial projections.\n\nTo accommodate the aforementioned system of axis movement with the applied algorithm, a series of angular conversions was prepared, that converted outputted azimuth and zenith angles into angles that were to be achieved by the stand, to properly track the sun position. Solar tracker was set to adjust panel position every 90 seconds. In terms of a proper comparison between results obtained from the reference test bench and the solar tracking test bench, both of them were equipped with identical 50 W monocrystalline solar panels, with a work surface of 540 × 670 mm, capable of outputting 2.78 A of current at 18 V. The same Arduino Uno controller used for the implementation of the solar tracker algorithm was also responsible for registering power outputs of both solar panels at 30 second intervals due to lack of a proper MPPT controller. The power readings were saved on the SD Card memory in form of files that contained consecutive power readings in beforementioned 30 second intervals recorded throughout the day. The outputted power was being drained by two 100 W power resistors, converting all the electrical energy into heat. Each panel had its own power registering loop, coupled with own power resistor. The circuitry involved in the study is completely separated from the measurement loop to avoid any interference from the actuators or the controller. To avoid overflow of memory on the Arduino Uno controller it was unfortunately decided to omit the measurement of power draw from the whole solar tracker circuit during its operation. It is a consideration to upgrade the measuring system in the future experiments, to also include this power draw in the equation. Although the panels are planned to be implemented as a new roof mounted solution, it was very hard to find building owners willing to spare their roof for testing purposes. To mitigate this obstacle, a decision was made to try and consider the possible range of movement, a panel could have, when mounted on a roof. The possible application of the current construction to a building roof would involve rotating the panel by 180° along its base and adjusting the calculation of zenith angle, to include roof inclination in the equation. For the purposes of this experiment, both panels were placed on the ground with adjustable feet as supports. The mechanical part of both test stands was completed around June. The electrical wiring and programming of the Arduino controller was completed in August, just before the tests began. A complete setup placed in its final study destination can be seen on Figure 4.\n\nThe stationary solar panel was raised to adjust its angle to around 30° which is an optimal angle for the latitude of Poland, Upper Silesia, based on the information provided by local solar panel mounting companies.\n\nThe research was conducted right after the completion of test benches which took place in August 2020. It took a total of 5 days between 14.08.2020 and 18.08.2020 (including that day). The research was conducted in Poland, Upper Silesia, with geographic coordinates of 50°22' N and 19°15' E. The sunrise, at the time of the experiment, on average, took place at 5:33 CEST (3:33 GMT). The sunset, at the time of the experiment, on average, took place at 19:58 CEST (17:58 GMT). The average length of the day was around 14 hours and 35 minutes. The area at which the experiment was conducted, was a rectangular plot with width of around 15 meters (in W-E direction) and length of around 100 meters (in S-N direction). Test benches were placed on the furthest side towards the west of the plot and around the middle in the N-S direction. The positioning was dictated by the trees that were growing in the near vicinity of the plot, from the east side. Because of the aforementioned trees, the sun was accessible from around 7:30 CEST (5:30 GMT) in terms of mornings. The view was almost unobstructed from the west side, however, which allowed for tracking the sun almost up to the time of sunset. Both test stands were placed on adjustable feet to keep them in level. According to the information provided, the procedure of daily measurement was as follows:\n\n• taking off the covers that secure the stands from the morning dew and rain\n\n• activation of test stands around 7:00 CEST (5:00 GMT) and their calibration\n\n• verification of correct solar panel alignment after the calibration and routine check of the state of hardware and software\n\n• in case of any errors or damage spotted, necessary debugging or repairs\n\n• continuation of the experiment throughout the day, up until around 20:30 CEST (18:30 GMT) when the sun is below the horizon already\n\n• stopping the research aperture by cutting the circuitry from external power supply\n\n• extraction of the gathered data by pulling the SD card with the data from the SD card module and copying the files to the laptop and USB stick for redundancy\n\n• securing the stand with covers for the night\n\nThe raw data consisted of the date, at which each measurement series was done, time at which each sample was taken and power readings from the fixed, reference solar panel and the tracking panel. The data from each day was processed in Microsoft Excel. All measurements taken throughout the period of the study were placed on a uniform timescale (to achieve that, some samples had to be moved in time by 1–10 seconds). The timescale ranged from 7:00 CEST (5:00 GMT) to 20:00 CEST (18:00 GMT) reflecting the daily study schedule. The time interval between each sample taken was 30 seconds.\n\n\nResults\n\nTable 1 and Table 2 show the aggregated data from gathered samples, showing the total energy gathered on each day by stationary and tracking solar panel. See Underlying data for the full combined and ordered data collected from each sample24.\n\nTable 3 shows a difference in energy gathered between tracking panel and a stationary panel, derived from the data. Table 4 shows the calculated efficiency of tracking solar panel in reference to stationary solar panel. The data were grouped by readings taken from each day of the study period. The day was also divided into three periods: morning (from 7:00 to 10:00), midday (from 10:00 to 15:00) and evening (from 15:00 to 20:00). Throughout the study period, the measurements were taken during different weather conditions. The weather was mostly sunny from 14th to 17th with occasional cloud patches covering the sky from few minutes to about an hour and a short rainfall occurring during the evening of 16th. There was a substantial cloud coverage throughout the evening of 17th.\n\nRMI, raw measurement inputs; CIG, calculated interval gains.\n\nDue to a storm occurring after the morning of 18th the test, that day, had to be stopped. Additionally, in the morning of 14th and 15th there was a necessity to do some maintenance of the solar tracker which involved debugging the software and resulted in a loss of potential power gains during this time period. It can be seen in the negative values, presented on Table 3 and Table 4. This big difference was caused by the tracking panel being greatly misaligned to the position of the sun. Also, in the Table 4, two separate percentages were listed and called raw measurement inputs (RMI) and calculated interval gains (CIG). Because of the way, the data was being gathered (30 second intervals), to calculate the energy produced between each measurement, a mean value between 2 subsequent measurements was taken and multiplied by the time between each measurement. This method is unfortunately prone to rounding errors and that is why the calculation of efficiency was done through the comparison of both RMI and CIG. Deviations between those two percentages are especially apparent in mornings of 14th and 15th when there were troubles with the operation of solar tracker.\n\nThe aggregated data showed a rough increase in tracking panel power generation of about 22–23% in relation to the stationary panel throughout the study period. In terms of mornings, the data was heavily disturbed by the problems that occurred during the test. Nonetheless, the data shows an increase in power income by 29–33% during morning periods throughout the entire study. Evening periods showed over a double amount of energy produced whereas middays showed about 4% increase due to both panels working at full capacity. A graph, presenting an average difference in power gains between stationary and tracking solar panel, throughout the day, was shown on Figure 5.\n\nFigure 5 represents an average daily difference in consecutive power output readings between stationary and solar tracking panels based directly on gathered samples from both solar panels throughout the study period. The red line represents an average of measurements taken from the same time of day throughout the study period. Again, due to problems in the first two days of the study, the graph is heavily disturbed in the morning period. The blue dashed line represents a moving average with a window of 120 samples (equal to one hour). Judging by the moving average, it can be noticed that the peak gain of around 5 W/s was achieved between 9 and 10:30. The efficiency gains are diminishing past 11 and there are no visible gains between 12 and 14. Again, past 14, the solar tracking panel starts to gather more energy with a peak gain of around 15 W/s around 17:30. After that, the gains start to quickly diminish again to 0 towards the evening hours.\n\n\nDiscussion\n\nResults of the study have shown an average daily power output of a stationary solar panel at a level of 0.182 kW-h per day and an average power output of solar tracking panel at a level of 0.224 kW-h per day. The difference in outputted power between stationary and solar tracking panel was 0.042 kW-h which amounts to a 22–23% gain in panel efficiency due to solar tracking ability. The overall mediocre performance of both solar panels over the entire span of the study can be attributed partly to some cloud coverage in the 3rd and 4th day of the study, and a thunderstorm in the 5th day, which forced the authors to terminate the study as early as 10 am. Gains in tracking solar panel performance of this design are lower than those presented in 7,12 and comparable to results presented in 16. The short study period of just 5 days in this setting is highly prone to statistical errors due to the small amount of data collected. Technical difficulties with solar panels in the beginning of the study and bad weather towards last days could have also contributed to this poor performance result over other studies.\n\nThere is a noticeable gain in power output efficiency of solar tracking panel during the morning (29–33%) and especially evening hours (113%). It is most probably due to stationary solar panels positioning and tilt being optimized for maximum efficiency during hours with best solar irradiance. Because of that, there are almost no gains of power over stationary solar panel during midday hours. The daily average collective gain in power from morning and evening hours with a solar tracking panel amounted to around 0.037 kW-h, which contributes around 88.1% of total power gains of solar tracking panel over the stationary solar panel. The results could’ve probably been even higher in favor of mornings and evenings if the test period took longer. This means that tracking solar panels take most of their benefit from solar energy collection during mornings and evenings. Given that the sun elevation decreases significantly towards the winter season, it is possible that more gains are to be had.\n\nIt is very hard to determine the economic cost efficiency based on the information gathered so far. Solar panels bought for the study cost around 393 PLN (101.91 USD) each and the spending associated with construction of both stands reached around 1700 PLN (440.73 USD), with about 2/3 of this cost being spent on the tracking solar panel because of its increased complexity. Another 1030 PLN (267.02 USD) was associated directly with solar tracking panel and that was a spending on actuators. Around 3250 PLN (842.53 USD) was spent in total on the construction of both test stands from which around 2556 PLN (662.61 USD) was associated with the construction of solar tracking panel. The solar tracking panel took around 78% of the budget and 22% were associated with the stationary panel. This means that solar tracking panel project cost around 3.7 times more than the stationary solar panel which indicates a fairly high cost compared to gains in efficiency. However, these costs are uncertain due to few factors. It has to be noted that this project was done by the researchers themselves omitting any costs associated with professional assembly and installation which influence the cost of solar panel installation significantly as pointed out in 5. Also, due to small factor of the study, there were no batteries or inverters involved which also contribute greatly to the costs of overall installation5,7. Broader research should be conducted to determine the effects of abovementioned factors on the overall economical profitability of such installation, including any grants and discounts or national policies regarding renewable energy.\n\n\nConclusions\n\nDespite the big number of obstacles and troubles during the study period, the obtained results show some correlation with results presented in other papers. This signifies that such adaptation of roof mounted solar panels may become a valid solution. The obvious conclusions from this study involve the need for longer testing periods to increase the data pool and reduce the effect of errors and anomalies on the aggregated data. The 50 W power generation limit of used solar panels should also be increased in the future by upscaling the test stands, to investigate power increase with more photovoltaic surface area and decrease the margin of error that is contributed to small scale experiments. Future studies should also involve studying periods in other seasons, to investigate potential power gains that come with different sun elevations during different seasons. The tracking algorithm used for this study was very basic and lacked many utility functions that a fully-fledged solar tracker has. This is an issue that should also be addressed before future studies. For longer study periods, the tracker must be upgraded with a wind measuring probe that is able to determine bad conditions for solar panel work and be able to fold the panel, to prevent any damage. Also, a data registering system must be upgraded with additional memory banks, to be able to collect more data during long periods and provide the data on the power draw, generated by the circuitry and the actuators. Alternatively, a proper MPPT power draw registering system must be added to the testing stand to properly measure the power draw of all elements. It is also very important to investigate the economical profitability of the proposed solution by investigating economical landscape in search of additional costs and benefits associated with solar panel installation.\n\nGiven the infancy of this project, this study was able to provide the data needed for its continuation. In further studies, it is imperative to thoroughly analyze all the potential scenarios that this system would be able to work with, such as different weather conditions and different seasons. Furthermore, a problem of power draw, by the included circuitry, and its effect on the resulting efficiency should be investigated. Lastly, it is also important to conduct a study referring to the advantages of using solar trackers on roof mounted solar panels versus the additional costs that they can generate and potential decrease of roof space that is connected with the problem of panels covering each other.\n\n\nData availability\n\nMendeley Data: Research data on prototype solar panel power output. http://doi.org/10.17632/2bgvhmtrpx.124.\n\nThis project contains the following underlying data:\n\n• Samples. (A collection of data recordings in the .txt format from the days of the study.)\n\n• Research_data.xslx. (Spreadsheet with combined and ordered data collected from each sample.)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgments\n\nI’d like to thank Mr. Mariusz Dziwiński for the help with technical aspects of test stand assembly and overall readiness for help in the event of any problems appearing. I’d like to also thank all the reviewers of previous drafts for the insightful evaluation of this work and helpful comments and suggestions related to the technical and substantive aspects of this work.\n\n\nReferences\n\nGadenne D, Sharma B, Kerr D, et al.: The influence of consumers’ environmental beliefs and attitudes on energy saving behaviours. Energy Policy. 2011; 39(12): 7684–7694. Publisher Full Text\n\nFaires A, Neame C: Consumer attitudes towards domestic solar power systems. Energy Policy. 2006; 34(14): 1797–1806. Publisher Full Text\n\nPalm J: Household installation of solar panels – motives and barriers in a 10-year perspective. Energy Policy. 2018; 113: 1–9. Publisher Full Text\n\nKlepacka AM, Florkowski WJ, Meng T: Clean, accessible, and cost-saving: Reasons for rural household investment in solar panels in Poland. Resources, Conservation and Recycling. 2018; 139: 338–350. Publisher Full Text\n\nGórnowicz R, Castro R: Optimal design and economic analysis of a PV system operating under Net Metering or Feed-In-Tariff support mechanisms: A case study in Poland. Sustainable Energy Technologies and Assessments. 2020; 42: 100863. Publisher Full Text\n\nRachchh R, Kumar M, Tripathi B: Solar photovoltaic system design optimization by shading analysis to maximize energy generation from limited urban area. Energy Convers Manag. 2016; 115: 244–252. Publisher Full Text\n\nRad M, Toopshekan A, Rahdan P, et al.: A comprehensive study of techno-economic and environmental features of different solar tracking systems for residential photovoltaic installations. Renewable and Sustainable Energy Reviews. 2020; 129: 109923. Publisher Full Text\n\nMehleri ED, Zervas PL, Sarimveis H, et al.: Determination of the optimal tilt angle and orientation for solar photovoltaic arrays. Renewable Energy. 2010; 35: 2469–2475. Publisher Full Text\n\nRowlands IH, Kemery BP, Beausoleil-Morrison I: Optimal solar-PV tilt angle and azimuth: An Ontario (Canada) case-study. Energy Policy. 2011; 39: 1397–1409. Publisher Full Text\n\nAbid AJ: Arduino Based Blind Solar Tracking Controller. IETI Transactions on Computers. 2017; 3(1). Reference Source\n\nAl-Naima F, Ali R, Abid AJ: Solar Tracking System Design based on GPS and Astronomical Equations. IT-DREPS Conference & Exhibition. 2013. Reference Source\n\nAwasthi A, Shukla AK, Manohar SR, et al.: Review on sun tracking technology in solar PV system. Energy Reports. 2020; 6: 392–405. Publisher Full Text\n\nHafez AZ, Yousef AM, Haraga NM: Solar tracking systems: Technologies and trackers drive types – A review. Renewable and Sustainable Energy Reviews. 2018; 91: 754–782. Publisher Full Text\n\nMichalsky J: The Astronomical lmanac’s algorithm for approximate solar position. Solar Energy. 1988; 40(3): 227–235. Publisher Full Text\n\nYlimaz S, Ozcalik HR, Dincer F: The analysis on the impact of the roof angle on electricity energy generation of photovoltaic panels in Kahramanmaras, Turkey-A case study for all seasons. Journal of Renewable and Sustainable Energy. 2015; 7(2): 023133. Publisher Full Text\n\nAl-Mohamad A: Efficiency improvements of photo-voltaic panels using a Sun-tracking system. Applied Energy. 2004; 79(3): 345–354. Publisher Full Text\n\nBahrami A, Okoye CO: The performance and ranking pattern of PV systems incorporated with solar trackers in the northern hemisphere. Renewable and Sustainable Energy Reviews. 2018; 97: 138–151. Publisher Full Text\n\nŞenpinar A, Cebeci M: Evaluation of power output for fixed and two-axis tracking PV arrays. Applied Energy. 2012; 92: 677–685. Publisher Full Text\n\nOffice of research in Utah State University, United States of America. (accessed 15 August 2020). Reference Source\n\nYang CK, Cheng TC, Cheng CH, et al.: Open-loop altitude-azimuth concentrated solar tracking system forsolar-thermal applications. Solar Energy. 2017; 147: 52–60. Publisher Full Text\n\nGrena R: Five new algorithms for the computation of sun position from 2010 to 2110. Solar Energy. 2012; 86: 1323–1337. Publisher Full Text\n\nSidek MHM, Hasan WZW, Kadir MZA, et al.: GPS based portable dual-axis solar tracking system using astronomical equation. IEEE International Conference Power & Energy (PECON). 2014. Publisher Full Text\n\nCentro de Investigationes energeticas: Medioambientales y Tecnologicas, Ministerio de ciencia e innovacion, Gobierno de Espana. (accesed 16 August 2020). Reference Source\n\nHarazin J: Research data on prototype solar panel power output. Mendeley Data, V1. 2020. http://www.doi.org/10.17632/2bgvhmtrpx.1" }	[ { "id": "79908", "date": "11 Mar 2021", "name": "Zeundjua Tjiparuro", "expertise": [], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn the abstract please edit the line: This article presents a possibility of creating a roof mounted solar tracking panel to increase its efficiency. (Change bold words to…to increase irradiance efficiency).\n\nIn the Introduction please edit this line: The increase of awareness and willingness to focus on renewable energy sources can partly be contributed…(change bold word to: attributed).\n\nStill in the Introduction, please edit this line: Thanks to the financial support it is possible (..punctuate with a coma after the word support).\n\nIn paragraph 2 of the Introduction in the sentence [big or small factor…. (delete the word factor)].\n\nSentence 2, in paragraph 2, of the Introduction: is either misplaced, or incomplete and will need editing to make it fit where it has been placed. The main problem is that it combines several factors which are diametrically opposite. For instance, space availability is certainly a limitation, but then combining this with household power consumption, which is certainly a motivation for installing solar, makes the write up sound ungrounded. Then another deterrent follows in: costs of installation and maintenance. This how your write up looks starting with the sentence: Apart from the space availability, authors in 5–7 also mention financial factors such as estimated monthly and yearly household power consumption or costs related to solar panel installation and maintenance….[the question is, the factors are mentioned as what? Problems to the installation or factors influencing installation?] But the sentence that follows is one for motivating for installation, but the next two on albedo and snow are a mix of opposites again, leaving the reader confused as to whether the author is motivating or discouraging. In fact, most of the things that the author wants to write about here have been covered in the preceding paragraph, and he is better off deleting the whole of this paragraph.\n\nThe reader will be lost as to which of these installations are better in this sentence: [The difference in energy production efficiency between stationary mounted solar panels and solar panels equipped with solar tracking capabilities can vary from 10% to 60% depending on the tracking technology used and considered time of the day].\n\nThis sentence is not fitting well where it has been placed [In addition, countries that are located on higher geographic latitudes can get more benefit from tracker installations because of the higher volatility of sun position during different seasons] since the preceding sentence is on the advantage of free standing installations being amenable to fitting trackers, the above sentence comes in to disrupt the flow which should continue to point out some limitations of trackers as the author does in the next sentence.\n\nWhat is the meaning of the bold part in the first sentence on page 4, column 1: [The article has a preliminary character in terms].\n\nWhat or which test stand is being referenced in second paragraph on page 4, column 1, the sentence goes like: [The design of the test stand….]\n\nThis sentence, in column 2, page 4, first paragraph has typos highlighted bold. It also makes a claim of adjustable feet which are not there in the model in the figure number referenced: [….and a set of adjustable feet to give it some room for adjustment of the slope on site. The model and its individual spatial projections were shown of Figure 2…]\n\nThe following description, under Test Procedure, must be supported by a bird’s eye view sketch of the site complete with geographical coordinates, otherwise it is unnecessarily complicated [Test benches were placed on the furthest side towards the west of the plot and around the middle in the N-S direction. The positioning was dictated by the trees that were growing in the near vicinity of the plot, from the east side. Because of the aforementioned trees, the sun was accessible from around 7:30 CEST (5:30 GMT) in terms of mornings. The view was almost unobstructed from the west side, however, which allowed for tracking the sun almost...]\n\nIn the list of steps on page 6, the sentence: [activation of test stands around 7:00 CEST (5:00 GMT) and their calibration] is not clear what was done.\n\nThe next step too is not clear as to what was exactly done [verification of correct solar panel alignment after the calibration and routine check of the state of hardware and software].\n\nWhat is a research aperture in step 6…[stopping the research aperture…] please show it.\n\nShow a diagrammatic illustration or labelled images of your experimental set up so that all the modules mentioned in you procedure such as the one below are clear to the reader…[extraction of the gathered data by pulling the SD card with the data from the SD card module and copying the files to the laptop and USB stick for redundancy].\n\nThe listed steps will be much better if numbered than just using bullets.\n\nThe sentence below, immediately after the list of steps, will need editing as the reader will not know what measurement series is, and what samples are.[The raw data consisted of the date, at which each measurement series was done, time at which each sample was taken and power readings from the fixed, reference solar panel and the tracking panel...].\n\nFirst paragraph under results….please attend to the matter of SAMPLES as highlighted in my foregoing comment.\n\nDelete the bold part of the sentence below [Table 3 shows a difference in energy gathered between tracking panel and a stationary panel, derived from the data]\n\nWith respect to the Tables, I think the [J] in the subtitles is the unit of energy [Joules], if so, the small subtitles for your tables must read like this: [Energy collected in Joules (J)].\n\nResults should not include the methodology, please find where to fit the methodology below in the appropriate place under Test Procedure. [The data were grouped by readings taken from each day of the study period. The day was also divided into three periods: morning (from 7:00 to 10:00), midday (from 10:00 to 15:00) and evening (from 15:00 to 20:00). Throughout the study period, the measurements were taken during different weather conditions. The weather was mostly sunny from 14th to 17th with occasional cloud patches covering the sky from few minutes to about an hour and a short rainfall occurring during the evening of 16th. There was a substantial cloud coverage throughout the evening of 17th.]\n\nFirstly, the author must show, even with simple equations, how the raw measurement inputs (RMI) and calculated interval gains (CIG) percentages were calculated. Secondly, the author must know that the percentages he is proposing lack persuasion as he does not point out to their use by previous researchers, or if they are novel approached, and explain why was a novel approach chosen over existing one. Additionally, my previous comment on unacceptability of putting procedure under results is valid for this sentence/paragraph. The author must find an appropriate place for it under Test Procedure.\n\nNot clear from the Tables and Figures presented by the author how he comes by this observation [The aggregated data showed a rough increase in tracking panel power generation of about 22–23% in relation to the stationary panel throughout the study period.]\n\nHow was the Total column in Table 4 calculated?\n\n[….was shown on Figure 5] change to […..is shown in Figure 5].\n\nThe following claim is not in the paper nor is it part of the data recorded or calculated from recorded data: [Results of the study have shown an average daily power output of a stationary solar panel at a level of 0.182 kW-h per day and an average power output of solar tracking panel at a level of 0.224 kW-h per day. y. The difference in outputted power between stationary and solar tracking panel was 0.042 kW-h…].\n\nLook at this sentence in your conclusions, the part I show in bold is not clear [decrease the margin of error that is contributed to small scale experiments].\n\nLook into the following sentence too and replace with bold work with [by]….[ This is an issue that should also be addressed before future studies.]\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8496", "date": "18 Jul 2022", "name": "Jacek Harazin", "role": "Author Response", "response": "Dear Doctor Tjiparuro, First and foremost, I’d like to thank you for a very detailed breakdown of your review. It has shed a lot of light on many issues with my article writing. I value that while still being a young researcher, trying to obtain my own title. I hope that my new revision of the article will do justice to your comments. I will try to address your comments in a similar manner. Ad1. to Ad4. Necessary corrections were made Ad5. After reading the paragraph and after some consideration, given that I can now look back at my own work with a dose of criticism, I came to a similar conclusion that there was no more value added in this section and decided to remove it as suggested. Ad6. I have slightly changed the wording of this sentence to point more clearly on panels with solar trackers. Ad7. I have split this section in two and tried to use better wording to present advantages and disadvantages more clearly and avoid contradictions. Ad8. I believe that this sentence was just a product of me being personally a bit too shy and insecure about this area of research. This article was a journey onto new waters for me personally. I have decided to remove this bit of unnecessary digression to avoid confusion. Ad9. This was a reference to the test stand with a solar tracker. I have slightly modified the sentence to make it clearer. Ad10. Yes, that was a mistake of trying to refer to later stages of the project. A set of “screw-on” feet was later added to both test stands to give it more adjustability on the grassy dirt. Unfortunately, I do not have any technical images for the later stages because the project was being developed and readjusted “on the go”. I have tried to describe it in the article itself to correct this mistake. Ad11. I have prepared a sketch, which will be placed as the new “Figure 6”. It is not very technical, but I hope it will be clear enough to give a picture of the testing environment that I have tried to describe previously. A rough geographical position was initially mentioned at the first paragraph under the “Test procedure”. I unfortunately can’t narrow it down any more due to the plot being part of someone’s private property which was graciously lent for our testing purposes. Ad12. I have tried to expand this description and make it more precise. Ad13. This issue has also been addressed similarly. Ad14. I have changed the wording of this point to be more precise of what I operated in that stage. The actual circuit was also added as the new “Figure 5”. Ad15. I have also tried to address this comment with the new figure I’ve placed. Ad16. Numbering has been added. Ad17. I have tried to word this sentence more clearly so it should cause less confusion. Ad18. Same as above. Ad19. The mentioned part was deleted. Ad20. I also changed the naming like you suggested. Ad21. The addressed paragraph was moved to the “Test procedure” section. Ad22. I have also moved this paragraph to the correct section, and I have tried to explain the equations more clearly. I’ve decided to not insert any specific equations because the formula was very basic and simple. I may have not said that in clear enough manner previously. Basically, because my aperture was taking power output measurements only once each 30 seconds (RMI), I figured that CIG may be a helpful datapoint. I have calculated an average amount of energy produced between each consecutive pair of measurements. The average was taken from each two neighbouring power output measurements and then multiplied by the interval of 30 seconds. Ad23. This result was obtained by averaging the registered power output differences and average gathered energy difference between stationary panel and a panel with a solar tracker on the span of the entire experiment (5 days). I have tried to reword this sentence to better explain how these results were obtained. Ad24. The total column in table 4 was calculated in the same way as I have mentioned above, just that the result was based on a daily measurement. Ad25. Correction has been made. Ad26. This claim was a result of a quick conversion of energy gathered by solar panels, mentioned in tables, from Joules into kilo-Watt-hours. I did forget to actually explain where these values came from all of a sudden. I changed the description to make this conclusion less accidental. Ad27. I have tried to rephrase this sentence and make my thoughts more clear. Ad28. The sentence has been corrected. Again, thank you very much for your attention to detail. I hope that this set of corrections will be acceptable at the very least. I have tried to improve the clarity of my procedures as much as I could. Unfortunately, I have lost memory of some of my decisions made during this research because of the time it took me to finally address these issues, for which I apologise. Best Regards," } ] }, { "id": "119191", "date": "28 Feb 2022", "name": "Wan Zuha Wan Hasan", "expertise": [ "Reviewer Expertise Robotic and Automation", "Solar Energy" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe prototype solar tracking was well working based on the proposed solution. It was a very practical solution to provide a solar tracker in order to increase power energy from solar. The outputs have shown very significantly. Since the solar tracker is a quite well-known solution, the author should discuss more on installation and costing issues against the total collected energy for both ground and roof top installation.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/9-1381
https://f1000research.com/articles/11-799/v1	18 Jul 22	{ "type": "Method Article", "title": "Interactive visualization of spatial omics neighborhoods", "authors": [ "Tinghui Xu", "Kris Sankaran" ], "abstract": "Dimensionality reduction of spatial omic data can reveal shared, spatially structured patterns of expression across a collection of genomic features. We studied strategies for discovering and interactively visualizing low-dimensional structure in spatial omic data based on the construction of neighborhood features. We designed quantile and network-based spatial features that result in spatially consistent embeddings. A simulation compares embeddings made with and without neighborhood-based featurization, and a re-analysis of Keren et al., 2019 illustrates the overall workflow. We provide an R package, NBFvis, to support computation and interactive visualization for the proposed dimensionality reduction approach. Code and data for reproducing experiments and analysis are available on GitHub.", "keywords": [ "Spatial Omics", "Interactive Visualization", "Dimensionality Reduction", "Networks" ], "content": "Introduction\n\nSpatially resolved omics technologies provide a view into the landscape of complex biological processes (Burgess, 2019; Nawy, 2018). For example, they have revealed novel aspects of tissue differentiation and the structure of certain cancers (Rao et al., 2021; Yoosuf et al., 2020). A spatial transcriptomic or proteomic dataset can be viewed as a spatially indexed collection of high-dimensional vectors (Dries et al., 2021a). The coordinates of each vector correspond to different genomic features (genes expression and protein measurements for spatial transcriptomics and proteomics, respectively) while the spatial index locates each measurement at some location in a tissue or cell.\n\nTwo challenges in the analysis of spatial omics data are:\n\n• Microenvironment dimensionality reduction: considering the large number of simultaneously measured genomic features, some form of dimensionality reduction is essential for effective exploratory analysis. However, for spatially resolved data, a dimensionality reduction should describe microenvironments and their relationships with one another. It is more useful to embed the genomics signature of a cell’s local neighborhood than simply the cell in isolation.\n\n• Streamlined navigation: low-dimensional representations of microenvironments may not be interpretable on their own. To this end, it is helpful to relate the representations to their original spatial and genomic contexts. Ensuring that these correspondences can be explored efficiently is a challenge in itself.\n\nThis paper discusses methods to address these challenges and releases a new R package that implements them. For the first challenge, our approach was to featurize spatial neighborhoods and pass this representation to downstream dimensionality reduction techniques. We explored in-depth features based on (1) histograms of expression levels and (2) local cell network properties. For the second challenge, we designed an interactive visualization that links learned representations with contextual descriptors.\n\nWe evaluated these methods using simulation and a qualitative data analysis. The simulation clarifies the difference between learning representations on individual cells and local cellular neighborhoods. The data analysis recapitulates the findings of (Chen et al., 2020; Keren et al., 2019). We believe that the main advantages of the proposed approach are:\n\n• Modularity: the approach can be made use of existing dimensionality-reduction methods while ensuring that results reflect meaningful spatial structure.\n\n• Flexibility: spatial featurizations can be tailored to specific problem contexts with little changes to the overall workflow.\n\nOur methods are implemented in the R package NBFvis, available on GitHub.\n\nThe remainder of the paper is organized as follows. The Background subsection reviews relevant literature on analysis of spatial omic data. The Methods section describes the proposed method. The Visualisation subsection introduces what kinds of visualization and interactivity are provided in our package. The Simulation subsection and the Results section illustrate the method in simulation and real data analysis, respectively. The Package subsection gives an overview of NBFVis’s functionality. We conclude with a summary and directions for future work in the Discussion.\n\nThe proliferation of spatial omic data has attracted attention from the modeling and visualization communities. Important themes that have emerged include the selection of spatially varying genes, derivation of spatial summary measures, and discovery of spatially consistent microenvironments. The resulting software packages allow analysts to generate overviews of spatial variation as well as focus on specific genomic features of interest.\n\nSeveral studies propose feature-level models of spatial variation to select those with notable spatial expression patterns. SPARK fits a collection of random effects models with diverse sets of kernels to capture variation at several spatial scales Sun et al. (2020). Alternatively (Zhu and Sabatti, 2020), computed a measure of spatial variation based on a spatially induced graph laplacian; genes exhibiting similar patterns of spatial expression are then clustered. Alternatively (Hsu and Culhane, 2020), proposed an adaptation of Moran’s I-statistic to measure the extent of spatial clustering across cell types, highlighting the potential for the classical spatial statistics methods to support modern spatial omics analysis. Like NBFvis, these methods compute spatial statistics to summarize spatial omics datasets. However, they tend not to provide localized measures of spatial structure, focusing instead on tissue-level properties.\n\nThe Giotto package includes approaches to dimensionality reduction and interactive visualization of spatial omics data Dries et al. (2021b). Of particular interest, the package supports interactive visualization that dynamically links embeddings of expression measurements with corresponding cell locations. Note however that these embeddings are derived without reference to spatial features.\n\nSimilar to our approach, Spatial-LDA proposes a variation of the topic models that learns spatially consistent patterns of cell type mixing (Chen et al., 2020). This is achieved by tying together mixed memberships of neighboring cells in a structured prior, and the model is fitted using a custom optimization scheme. Regions with similar topic memberships can be interpreted as microenvironments. Our proposal has a similar data analytic goal; however, we aim to support more generic spatial features while preserving simplicity in implementation.\n\nWe provided a toy simulation to clarify the differences in embeddings when neighborhood information is and is not used. We found that if only cell-level information is considered, the embeddings will be dominated by cell types and fail to reflect microenvironment structure.\n\nDataset construction\n\nAssume that there is one tissue section with three cell types. For each cell, five proteins are measured. Different cell types have different protein profiles, which means the average measurements of proteins differ according to cell type. We assume that cell types are clustered spatially, but that these clusters are close enough so that some areas overlap. These overlapping areas can be considered different microenvironments since the local mixture of protein profiles is different from regions of pure cell types.\n\nFigure 1 is the spatial plot for the simulated dataset. Two thousand “cells” are generated and divided into three different cell types according to a multinomial distribution with the probability (0.2, 0.3, 0.5) for Cell Type 1, 2, and 3,\n\nOverlapping regions can be thought of as their distinct microenvironments. The goal is to construct embeddings that reflect different mixing patterns.\n\nFor this demonstration, we imagined that protein abundances are drawn from a mixture of multivariate normals. The average of each mixture component represents the typical cell profile for each cell type. That is, for each cell, the measurements for each of the five proteins have the form,\n\nNext, we simulated cell locations to get mixed spatial patterns. We used a different mixture of (now two-dimensional) multivariate normals. As before, component means center1, center2, and center3 were drawn from a multivariate normal. Denoting the coordinates of cell i by xiyi and the spatial mean of cell type j by centerj, we drew,\n\nAfter simulation, we obtained a 2000 × 5 expression matrix, each row of which corresponds to the simulated observation of one cell. We called this matrix the “single cell matrix”.\n\nTo extract neighborhood information for each cell, we first found neighborhoods with a given radius (here we used 0.2 units in length). We then calculated statistics within each neighborhood. We chose quantiles of protein content as neighborhood-based statistics, which are simple but effective. For every cell and protein, we derived 21 quantiles q0, q0.05, …, q1 in the neighborhood. After calculation, an extended 2000 × 105 matrix was obtained. We called this the “neighborhood matrix”.\n\nComparison\n\nWe next applied dimensionality reduction methods to both the single cell and the neighborhood matrices, in order to clarify the difference in the resulting embeddings.\n\nFirst, we applied uniform manifold approximation and projection (UMAP) McInnes et al. (2018) to the single cell matrix, whose low-dimensional embeddings are shown in Figure 2. Only three separate clusters are visible in the embedding plot, each corresponding to a cell type. These UMAP embeddings ignore the microenvironments of mixed cell types along cluster borders in the spatial plot. This result indicates that, when spatial information is not directly incorporated, the low-dimensional embeddings are dominated by cell types and fail to distinguish microenvironments.\n\nCell types clustered with one another, but different mixture patterns were not observed. The embeddings were dominated by the cell types, obscuring the presence of microenvironments.\n\nIn contrast, the embedding plot of the neighborhood matrix detects microenvironment structures; see Figure 3. We noticed that there were still three clusters consisting of pure cell types. However, there were additional clusters of mixed cell types. Between the three pure clusters is a region corresponding to microenvironments with mixed cell types in the spatial plot. Furthermore, we noticed that this region can be further divided into spatially consistent “subclusters”. For instance, one region with only blue and green cells was related to the blue-green spatial boundary. This can be treated as a unique microenvironment. Similar red-blue and red-green regions were also visible.\n\nThough simple, the neighborhood quantile statistics make it possible to detect mixture microenvironments. We could further find subclusters like the red-green mixture in the central cluster.\n\nIn summary, UMAP embeddings using the single cell matrix were dominated by cell types and failed to detect microenvironments with mixed cell types. However, by simply applying UMAP to the neighborhood matrix, we were able to detect these spatially meaningful microenvironments.\n\n\nMethods\n\nFirst, we established notation and an overview of the general approach. Let X∈ℝN×D contain expression measurements for D gene or protein expression features across N cells. We call X the expression matrix. Let S∈ℝN×2 contain the spatial locations of the N cells. We first applied a preliminary dimensionality reduction, like principal component analysis (PCA), to the expression matrix X before the following neighborhood-based featurization. We called the reduced matrix X̂∈ℝN×P, where P is the number of dimensions after dimensionality reduction.\n\nBefore we can embed properties of cell neighborhoods, we need to define and derive features for each neighborhood. For each cell xi, we defined its neighborhood using distances induced by S, either containing all cells within a certain radius or simply the K-nearest neighbors. Denote the neighborhood for the cell xi by mi=xi1…xini, where xi1,…,xini are the ni neighbors in the neighborhood and ni is the number of neighbors surrounding xi. We featurized the neighborhoods mi using neighborhood-based featurizaton functions Tj,j=1,…,J. We then rescaled all the derived featurization matrices T1X̂,T2X̂,…,TJX̂ and concatenated them to obtain an extended neighborhood-based featurization TX. The neighborhood matrix from the Simulation subsection is a special case of TX using quantile features.\n\nIn more detail, let Tj:ℝP→ℝpj,j=1,2,…,J be a set of featurization functions. By applying every Tjmi to each neighborhood mi, we can construct X˜j∈ℝN×pj. The matrix X˜j can be rescaled and then combined into a widened neighborhood matrix X˜∈ℝN×∑j=1Jpj. This neighborhood matrix X˜ was input to a dimensionality reduction method to recover a set of embeddings. Our final set of microenvironments was found by clustering these embeddings. Below, we applied K-means to the set of neighborhood-level embeddings.\n\nWe next discuss a specific instantiation of this general procedure, describing the neighborhood and featurization choices used in the Results section and implemented in NBFvis. There, N gives the number of cells in one tissue section, D is the number of proteins measured, and s is the spatial location matrix of the segmented cells. We applied a PCA to the expression matrix X∈ℝN×D and then derived the reduced expression matrix X̂∈ℝN×P. Neighborhoods were constructed by keeping the K nearest neighbors that are also within a given radius.\n\nWe used two types of featurization functions Tj – quantile features and network features. For the ith cell’s neighborhood, Z quantiles q1i,kq2i,k…qZi,k were calculated for the kth protein, where k=1,2,…,P. It means that we derived a PZ-dimensional vector q1i,1q2i,1…qZ−1i,PqZi,P for each neighborhood. Thus, TquantileX:ℝN×P→ℝN×PZ. After featurization, we obtained an N×PZ matrix, which we called the “quantile matrix”. Next, consider the construction of network features. Let Gi denote the geometric graph associated with mi, using the metric induced by s. Based on Gi, we can calculate a variety of node or edge features. The associated network featurization here is TnetworkX:ℝN×P→ℝN×M, where M is the number of network statistics. For example, in the experiments below, we used the number of edges degreeGi and a variety of centrality measures. We used an ensemble of 29 network-based statistics in our example, detailed in Table 1 and the Extended Data XTH1114 and Sankaran (2022).\n\nWe use implementations of these centrality measures from the R packages igraph (Csardi and Nepusz, 2006), centiserve (Jalili, 2017) and sna (Butts, 2020). Network statistics implemented in NBFvis. These functions could be found in centiserve and snr package.\n\nThe final featurization combined both quantile and network features,\n\nTX is a N×PZ+M neighborhood matrix. Rescaling was applied to this neighborhood matrix so that every column was on a similar scale. This rescaled neighborhood matrix was passed to UMAP to obtain low-dimensional embeddings. These embeddings could then be clustered to identify distinct microenvironments. The whole workflow is shown in Figure 4.\n\nA) The spatial omics datasets are composed of two parts: spatial coordinates and expressions of each cell. We applied dimensionality reduction to the expression matrix to derive a reduced one on which features are derived. B) We treat each cell xi as a center and build a neighborhood for it. There are two general ways to construct a neighborhood: using distance between spatial coordinates and using the K-nearest neighbors. In our example, we combined these methods in the following way. First, we included cells whose distance from the central cell was less than a given length. Then we only kept the nearest K cells as its neighbors. C) To derive the quantile featurization for a gene, the quantiles of the distribution of each neighborhood’s expression for that gene are calculated. D) For the centrality featurization, we built a network within the neighborhood. Edges exist between two cells that are close enough. Then, we calculated centralities with respect to the center cell xi. E) We concatenated and rescaled these derived features into what we call a neighborhood matrix. F) We applied uniform manifold approximation and projection (UMAP) to the neighborhood matrix to obtain embeddings for each cell, where we directly applied clustering algorithms. See the Example subsection below for details of the implementation.\n\nSeveral subtle but important details are worth noting. Before we calculate a featurization matrix, a preliminary dimensionality reduction method is needed. First, applying dimensionality reduction decreases the computational burden of downstream analysis. Computing quantiles for each feature in a high-dimensional dataset further increases the dimensionality. For example, computing 10 quantiles for each of 100 variables results in 1000 columns, which significantly increases the computational burden of embedding. Second, a statistical reason for dimensionality reduction is to reduce the noise in the original high-dimensional dataset. If the original data are effectively low-rank, then dimensionality reduction method will reduce unnecessary noise while preserving most statistical information, which is beneficial for the following embedding.\n\nAnother detail is the rescaling of the neighborhood matrix. Although the neighborhood matrix could have hundreds or even thousands of columns, there is no need to apply a preliminary dimensionality reduction to it, since all values are approximately comparable. However, it is necessary to rescale the neighborhood matrix because the ranges of different statistics vary dramatically, causing one or two variables with large variance to dominate the whole UMAP embedding. For instance, the entries in the quantile matrix were between -1.5 and 1.5 in the TNBC dataset, but for the network matrix, it is common to have some network statistics larger than 10. These network statistics would dominate the UMAP embedding if no rescaling is applied.\n\nWe devised an interactive Shiny app (Chang et al., 2015) to analyze outputs from the neighborhood-based analysis, supporting visualization of microenvironment differences. In this subsection, we discuss the design and visual queries supported by the interface.\n\nFigure 5 shows the first component of the Shiny app, the UMAP embedding and linked spatial plot. This is used to relate the low-dimensional embeddings of each cell’s neighborhood features to its overall spatial context. Figure 5a is the two-dimensional UMAP embedding plot derived from the neighborhood matrix. Each point corresponds to one cell. The closer these points are, the more similar their neighborhood featurizations are. To clearly visualize the distribution of cell types, the points in Figure 5a are colored according to cell types.\n\nPart (a) is the two-dimensional embedding of the neighborhood matrix, and (b) is the original spatial layout of cell types.\n\nFigure 5b is the spatial plot. Each point here represents a cell center, derived from the original cell polygon in the tissue section. As before, different cell types are distinguished by colors. Furthermore, the two panels in Figure 5 are dynamically linked. When points are selected in one plot through a mouse brush, the corresponding points will also be highlighted in the other plot. Figure 6 shows the highlighted points in these two plots after one such selection. We can click on the legend on the sidebar to deselect these cell types so that they do not appear. Figure 7 shows the embedding plot and scatter plot after deselecting the immune cells.\n\nThe second component of the Shiny app shows the same embeddings but colored by K-means cluster rather than cell type. For example, in Figure 8, the positions of points are still the same as in Figure 5, but they are clustered into five K-means clusters. A slider is provided at the top of the second component in Figure 8, which is used for changing the value of K in the K-means clustering.\n\nThe third component of this Shiny app supports the comparison of expression levels across K-means clusters using a heatmap, structure plot, and histogram; see Figure 9. There are three tab panels with which we can switch between these three plots. Before making a further comparison, we can filter to cells of interest using the checkboxes at the top of Figure 9. Two groups of checkboxes are offered to select the cell types and K-means clusters to focus on. Based on the filtered cells, an expression heatmap of K-means clusters is provided in Figure 9. By default, it shows the top 10 most differentially expressed features across the selected clusters, based on the median of expression value in each cluster. A numeric input is offered above the heatmap – this controls the number of features appearing in the heatmap. The structure plot of the selected K-means clusters is provided in Figure 10, with which we can see the proportion of each cell type across every cluster. The histogram of expression is available to compare the selected feature’s expression across clusters. For example, Figure 11 is the histogram of the HLA Class 1 content in Clusters 1 and 4. Note that a selection input box is offered above the histogram to change the selected feature easily.\n\nThese views help describe clusters identified by K-means.\n\nThe dominant cell types in each clusters are shown clearly.\n\nUsers could select different expressions by the selection input box above the histogram.\n\nTo show the spatial distribution of a specific feature’s expression, another combination of the embedding and spatial plot is provided in Figure 12. The colors of the points in Figure 12 reflect Human Leukocyte Antigen (HLA) Class 1 content. This expression plot highlights spatial characteristics of the expression content. In this case, expression is elevated in immune cells, especially those closest to the tumor-immune boundary.\n\nInstead of coloring by cell type or K-means cluster, each cell is shaded according to the selected genomic feature.\n\n\nResults\n\nTo illustrate our approach and package, we re-analyzed theTriple Negative Breast Cancer (TNBC) dataset of Keren et al. (2019) (Underlying data). To study this data, Chen et al. (2020) proposed Spatial-LDA, which was found to reveal novel microenvironments. Spatial-LDA models the distribution of cell types within neighborhoods but does not model protein expression directly. In contrast, our proposal considers quantitative protein measurements and network statistics within spatial neighborhoods. Here, we choose the tissue section of Patient 4, which had 6643 cells belonging to six cell types: immune cells (62.6%), keratin-positive tumor cells (25.2%), tumor cells (6.4%), mesenchymal-like cells (3.2%), endothelial cells (1.9%), and unidentified cells (0.5%). We used 41 expression variables, two-dimensional coordinates of cell centers, and cell types for further analysis.\n\nThe first step was to construct the neighborhood quantile matrix. We applied PCA to reduce the dimension of the expression matrix. We kept 19 principal components, which is the smallest number of components required to explain 90% of the variance. These components were labelled as PC1, …, PC19. Next, neighborhoods were defined using a radius of 60 pixels. We only include the cells among the top 40 nearest neighbors to the center cell of the neighborhood. Quantiles for each principal component were calculated based on neighborhoods. To avoid the influence of extreme values, only quantiles q0.10, q0.15, …, q0.90 were included. Hence, we derive a 6643 × 323 quantile matrix of neighborhoods after featurization. The second step was to obtain the network matrix of the neighborhoods. We again used a radius of 60 pixels to define neighborhoods and kept only the 40 closest cells. Networks were constructed based on these neighborhoods. We linked cells whose centers were within 30 pixels of one another. Then, 29 network statistics were calculated according to the neighborhood networks; most of these network statistics were different kinds of network centralities. This resulted in a 6643 × 29 neighborhood network matrix.\n\nThe third step was to combine the quantile and network matrices together into an extended neighborhood matrix. The network matrix was rescaled in this step. The result was a 6643 × 352 neighborhood matrix. The final step applied dimensionality reduction and clustering to the neighborhood matrix. We applied UMAP to the neighborhood matrix to generate two-dimensional embeddings of each cell. K-means was applied to the UMAP embeddings to find potential clusters. These can be interpreted as microenvironments.\n\nWe used a Shiny app implemented in NBFvis to explore the result of UMAP embeddings and K-means clusters. Figure 13 shows the UMAP embeddings and spatial plot of the neighborhood matrix. Figure 13a gives the embeddings based on the reduction of the neighborhood matrix. The points in the embedding plot are colored according to their cell types. There are two main clusters in the embedding plot, composed primarily of immune and tumor cells, respectively. These two clusters are connected by a transition zone of a mixture of tumor and immune cells. Figure 13b is the spatial plot of the cells in the tissue section. By selecting the transition zone in the embedding plot, we found that the cells in this area are located on the boundary of immune cells, tumor cells, and keratin-positive tumor cells. This is shown in Figure 14.\n\nPanel (a) is the UMAP embedding plot colored in cell types. Panel (b) is the spatial plot of the real positions of cell centers. We observe a transition zone between clusters of tumor cells and immune cells in part (a).\n\nThe corresponding cells whose embeddings are in the transition zone in panel (a) are located close to the tumor-immune boundary in panel (b).\n\nK-means clustering applied to the UMAP embeddings suggests potential microenvironments. Figure 15 shows clustering results with K = 5. The clusters are distinguished by their colors. In the embedding plot Figure 15a, the embeddings are divided into five clusters, and the corresponding locations of these clusters are shown in the spatial plot Figure 15b. One finding of note is that the clusters in the embedding space were spatially consistent.\n\nClusters in panel (b) are spatially consistent. There are two special clusters on the tumor-immune boundary, whose embeddings are in the transition zone in panel (a).\n\nIn Figure 15b, two microenvironments were found among the tumor cells and keratin-positive tumor cells, Cluster 3 in the inner part of the tumor cell groups and Cluster 4 close to the boundary of immune cells. This mirrors the findings of Chen et al. (2020). Another finding was a special immune cell microenvironment, Cluster 2, lying on the boundary of immune cells, tumor cells, and keratin-positive tumor cells. This microenvironment was distinguished from the immune microenvironment in the inner part of immune cell groups, which is Cluster 5 in Figure 15b. Notice that Clusters 4 and 5, which are the microenvironments close to the tumor-immune boundary, are in the transition zone in the UMAP embedding plot in Figure 14. Moreover, another microenvironment, Cluster 3, was found in the top-left corner of Figure 15b, separate from the previous two immune microenvironments, Clusters 2 and 5.\n\nNext, we explored the differences between these microenvironments by studying their expression patterns. Figure 16 is the heatmap of the inner and boundary immune microenvironments, which are Clusters 2 and 5 in the Figure 15b, respectively. The heatmap shows the top 10 most differentially expressed proteins between these two clusters, determined by the differences between medians of expressions in each group. We chose the two most differentially expressed proteins, CD45 and CD45RO, for further exploration. The histograms in Figure 17 show the contents of CD45 across these two microenvironments. The inner immune microenvironment has a right-skewed distribution of CD45, indicating that many cells in this microenvironment have a low content of CD45. In contrast, the distribution of CD45 in the boundary immune microenvironment was significantly higher than that in the inner immune microenvironment. Figure 18 is the expression plot of CD45, this confirms that cells along the tumor-immune boundary had elevated CD45.\n\nCluster 2 is on the tumor-immune boundary and Cluster 5 is in the inner part of immune cell groups. The most obvious difference in expressions between these two clusters are CD45 and CD45RO. Cluster 5 had significantly lower CD45 and CD45RO content than Cluster 2.\n\nHistograms for different features can be selected using the interface, and the choice can be guided by a heatmap like in Figure 16.\n\nThe existence of brighter cells near the tumor-immune boundary is consistent with Figures 16 and 17. This view also reveals elevated CD45 in the top-right region, corresponding to Cluster 3.\n\nChecking the histogram and spatial expression of CD45RO in the inner and boundary immune microenvironments, we arrived at similar conclusions. Figure 19 is the histogram of these two microenvironments. The histogram for the inner immune microenvironments has a peak near the minimal value, which does not appear on the histogram of the boundary immune microenvironments. It shows that there were lower contents of CD45RO in the inner immune microenvironment but higher contents of CD45R0. Figure 20 also shows that there was a lighter boundary on the tumor-immune cells, highlighting this microenvironment.\n\nIn contrast to CD45, the distribution in both clusters is strongly right-skewed, even after the preprocessing applied by Keren et al. (2019).\n\nThis marker’s spatial expression structure is similar to that for CD45. The fact that more cells are shaded darkly reflects the right skew observed in the histograms in Figure 19.\n\nWe also used the visualization tool to show the UMAP embedding and clustering results when directly applied to the original cell-level protein expression matrix. We used the same preprocessing as Keren et al. (2019). This serves as a reference point against which to compare the proposed neighborhood-based featurization.\n\nFigure 21 gives the UMAP embedding and spatial plot using the cell-level approach. We found two clusters in the Figure 21a, one mainly made up of immune and one of tumor cells, respectively. The result was similar to the simulation, where UMAP embeddings were dominated by the differences between cell types and microenvironments were hardly distinguishable.\n\nCells are shaded by cell type. Compare with Figure 13.\n\nFigure 22 shows the clustering results after K-means clustering with K = 5. The clustered microenvironments were mixed with each other; in particular, it was difficult to distinguish a tumor-immune boundary microenvironment. Figure 23 compares the clustered spatial plots based on the cell-level and neighborhood-based approaches. In Figure 23a, the cells in Region 1 were a mixture of three microenvironments derived from the cell-level approach. It was difficult to identify which microenvironment this region belonged to. Although Region 2 of Figure 23a was mainly composed of Cluster 3, there were cells from Clusters 4 and 5 distributed throughout. Though in principle it is possible to distinguish microenvironments based on particular mixture patterns across cell types, doing so requires much more effort than examining the neighborhood-based representation.\n\nSub-cell type variation in the embedding plot does not correspond to spatially meaningful microenvironments. Compare with Figure 15.\n\nMicroenvironments with similar expression patterns (and stable cell type mixtures) are enclosed in black boxes. Microenvironments are more clearly visible when using neighborhood-based featurization.\n\nCompared with the cell-level approach, the neighborhood-based featurization has a noticeably clearer clustering result. In Region 1 of Figure 23b, the cells in the boundary of tumor cells are spatially consistent according to their own cell types. Further, in Region 2 of Figure 23b, we observe a dominant microenvironment without needing to parse mixed patterns of cell types.\n\nOverall, the neighborhood-based featurization provides representations with better spatial consistency, simplifying the discovery of microenvironments.\n\nWe next summarize how to use NBFvis to implement the proposed workflow. We first loaded the packages and dataset we need. The dataset patient4 is a 6643 × 59 data frame of all cells in the tissue section of Patient 4 in the TNBC data (Keren et al., 2019). We added two columns named x_center and y_center, which are the coordinates of the calculated cell centers from the spatial raster data.\n\nWe selected 41 variables from dsDNA to HLA Class 1, most of which are proteins and cell type markers. The quantile_matrix function generates the quantile matrix from each cell’s neighborhood.\n\nThe function network_matrix first builds the network inside the neighborhood and then calculates the corresponding network statistics using the argument given by fun. In this example, we used the function centralities, also exported by our package.\n\nThe scales of these two matrices are not the same, which means rescaling is needed. Here we removed Column, index and n_neighborhood in the quantile matrix so that all the columns left were quantile and network variables. Normalization and centering were applied to the centralities matrix so that they had a similar scale to the quantile matrix. We then combined the quantile matrix and the rescaled network matrix to construct an extended featurization matrix, which we called the neighborhood matrix earlier.\n\nThe final step was to input the neighborhood matrix, the cell dataset patient4, and the names of the variable of interest in the function NBFvis. This returned an interactive Shiny app that was the source of figures in the Results section,\n\n\nDiscussion\n\nWe have presented a method for visualizing spatial omics datasets that integrates dimensionality reduction methods like UMAP with neighborhood-based featurization based on quantiles and network properties. According to the results of our simulation, dimensionality reduction based on genomic features alone has difficulty identifying microenvironments because the associated embeddings are dominated by differences in expression patterns across cell types. Also, K-means clustering on the UMAP embeddings from this approach results in spatially inconsistent clusters, making it difficult to identify potential microenvironments. In contrast, our approach, though simple to implement, is able to avoid these problems by leveraging neighborhood information of cells. After combining neighborhood-based statistics like quantiles and centralities, we can detect microenvironments with mixed cell types, paralleling our simulation results. Furthermore, spatially consistent K-means clusters can be derived, supporting discovery of microenvironments.\n\nWe applied our methodology to the spatial omics dataset of (Keren et al., 2019) and found five spatially continuous microenvironments in the cells’ spatial plot. We compared this result with the analogous approach based on cell-level data and found that it is more difficult to identify meaningful microenvironments without an initial featurization step.\n\nOne advantage of our methodology is that the choice of neighborhood-based featurization is flexible. In our example, we used neighborhood quantiles of principal components and network statistics to build the neighborhood matrix for UMAP. These statistics could be replaced by other neighborhood-based statistics like cell-type diversity or local modularity. Also, the embedding and clustering methods are not fixed. We could use alternative dimensionality reduction methods like t-distributed stochastic neighbor embedding (t-SNE) and PCA or clustering methods like spectral clustering depending on the problem structure.\n\nThere are several avenues to develop this work. First, we treated the nodes in the neighborhood networks identically, ignoring their cell types. This is convenient for the computation of network statistics, but the information is nonetheless lost. To address this, it may be possible to build neighborhood networks with different node types and compute corresponding network statistics. A second question is how to combine matrices. Our featurization is based on matrices from two groups of statistics (quantiles and network statistics), and their variances and interpretation could be quite different according to their groups. Is there a more principled approach to scaling and combining these measures into a single featurization? One possible solution could be multiple factor analysis, which distinguishes between groups of statistics (Pagès, 2014). Thirdly, we used K-means clustering in our methodology, which is a common choice but far from the best clustering algorithm for low-dimensional embeddings. K-means clustering is sensitive to outliers in the embedding plot and assumes spherical clusters, making it potentially unreliable. Spectral clustering could be a potential improvement because it is more sensitive to the gradient structures in the UMAP embeddings.\n\n\nData availability\n\nThe TNBC dataset of Keren et al. (2019) can be downloaded from https://www.angelolab.com/mibi-data.\n\nAnalysis code available from: https://github.com/XTH1114/NBFvis\n\nArchived analysis code as at time of publication: DOI: 10.5281/zenodo.6639613\n\nLicense: GNU General Public License", "appendix": "Acknowledgements\n\nWe would like to express our gratitude to all the members of our group, who provided us with precious suggestions for the modification of our methodology and the Shiny app. In particular, we thank MinXing Zheng for suggestions on the choices of network statistics and Xinran Miao and Hanying Jiang for help improving the user interface of our Shiny app.\n\n\nReferences\n\nBurgess DJ: Spatial transcriptomics coming of age. Nat. Rev. Genet. 2019; 20(6): 317–317. PubMed Abstract \| Publisher Full Text\n\nButts CT: sna: Tools for Social Network Analysis. 2020. R package version 2.6.Tables.Reference Source\n\nChang W, Cheng J, Allaire JJ, et al.: Package ‘shiny’.2015.Reference Source\n\nChen Z, Soifer I, Hilton H, et al.: Modeling multiplexed images with spatial-lda reveals novel tissue microenvironments. J. Comput. Biol. 2020; 27(8): 1204–1218. PubMed Abstract \| Publisher Full Text\n\nCsardi G, Nepusz T: The igraph software package for complex network research. InterJournal, Complex Systems. 2006; 1695.Reference Source\n\nDries R, Chen J, Del Rossi N, et al.: Advances in spatial transcriptomic data analysis. Genome Res. 2021a; 31(10): 1706–1718. PubMed Abstract \| Publisher Full Text\n\nDries R, Zhu Q, Dong R, et al.: Giotto: a toolbox for integrative analysis and visualization of spatial expression data. Genome Biol. 2021b; 22(1): 1–31.\n\nHsu L, Culhane A: Tumor spatial autocorrelation and clinical prognosis.2020.Reference Source\n\nJalili M: centiserve: Find Graph Centrality Indices. 2017. R package version 1.0.0.Reference Source\n\nKeren L, Bosse M, Thompson S, et al.: Mibi-tof: A multiplexed imaging platform relates cellular phenotypes and tissue structure. Sci. Adv. 2019; 5(10): eaax5851. PubMed Abstract \| Publisher Full Text\n\nMcInnes L, Healy J, Melville J: Umap: Uniform manifold approximation and projection for dimension reduction. arXiv preprint arXiv:1802.03426. 2018.\n\nNawy T: Spatial transcriptomics. Nat. Methods. 2018; 15(1): 30–30. Publisher Full Text\n\nPagès J: Multiple factor analysis by example using R. CRC Press;2014.\n\nRao A, Barkley D, França GS, et al.: Exploring tissue architecture using spatial transcriptomics. Nature. 2021; 596(7871): 211–220. PubMed Abstract \| Publisher Full Text\n\nSun S, Zhu J, Zhou X: Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies. Nat. Methods. 2020; 17(2): 193–200. PubMed Abstract \| Publisher Full Text\n\nXTH1114Sankaran K: Xth1114/nbfvis: v1.0.1.June 2022. Publisher Full Text\n\nYoosuf N, Navarro JF, Salmén F, et al.: Identification and transfer of spatial transcriptomics signatures for cancer diagnosis. Breast Cancer Res. 2020; 22(1): 1–10. Publisher Full Text\n\nZhu J, Sabatti C: Integrative spatial single-cell analysis with graph-based feature learning. bioRxiv. 2020." }	[ { "id": "255790", "date": "02 Apr 2024", "name": "Guangdun Peng", "expertise": [ "Reviewer Expertise technical and analytical method development for spatial multiomics", "developmental biology", "stem cell biology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript entitled “Interactive visualization of spatial omics neighborhoods”, Xinghua et al. developed a new interactive tool named NBFvis for computing and visualizing low-dimensional representation of spatial protein omics data that incorporates spatial local neighborhood information. The authors attempt to address the challenge in spatial omics to learn the content-awareness low-dimensional representations for precise microenvironment identification. Like Spatial-LDA, the method learned the local neighbors’ protein expression and network statistics to create a neighbor-aware low-dimensional representation and then utilized this representation in downstream UMAP embedding and clustering. The authors validated their method by applying it to simulation data and real TNBC spatial MIBI-TOF data. They also provided a Shiny application for interactive explode of low-dimensional representations. The main limitation is the lack of reasonable comparisons to validate this method. The authors demonstrated the learned low-dimensional embeddings can be used to precisely identify the microenvironment on protein profile simulation data and TNBC spatial MIBI-TOF data, further showcasing the validity or accuracy of using this low-dimensional embedding to identify the microenvironment would be valuable. Perhaps comparing the accuracy of classifiers, like SVM, trained on different low-dimensional representations to distinguish manually annotated microenvironments can help demonstrate this. Secondarily, the content-aware low-dimensional representations were constructed by concatenating two matrices: a quantile matrix based on neighbor protein expression and a centrality matrix based on network statistics. It is worth knowing which matrix or which network features are more crucial in identifying the microenvironment, maybe this can help to provide biological interpretations of those identified microenvironments. Minor concerns: 1. The title \"Interactive visualization of spatial omics neighborhoods\" may not be suitable as the authors only validated their method on spatial protein omics data in this manuscript. 2. In the assumption of the simulated dataset, please explain more about the coefficient in the covariance matrix of the multivariate normal distribution model. 3. How is the study compared to other methods on simulated data or simulating microenvironment? e.g. SOTIP and scDesign3, more benchmarking work (tools and dataset) would be useful. 4. Is the finding that CD45 is important for tumor microenvironment supported by experiment or literature? 5. To improve the readibility of the study, I would encourage the authors to reorganize the figures and merge the figures which explained similar conclusions.\n\nIs the rationale for developing the new method (or application) clearly explained? Partly\n\nIs the description of the method technically sound? Partly\n\nAre sufficient details provided to allow replication of the method development and its use by others? Yes\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Partly", "responses": [] }, { "id": "250359", "date": "02 Sep 2024", "name": "Oscar Ospina", "expertise": [ "Reviewer Expertise Spatial biology", "bioinformatics", "oncology" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript “Interactive visualization of spatial omics neighborhoods” presents a novel and “out of the box” proposal to define cellular neighborhoods from spatial proteomics (and potentially) transcriptomics data. The method is a very interesting approach to the spatial analysis of data modalities that are becoming increasingly popular in the literature. I appreciate not only the statistical framework (called NBFvis) behind the model, but also that the authors made efforts to make the pipeline partially interactive.\nDespite the high current relevance of the data types involved and the novel approach devised by the authors, I consider some major points should be addressed:\nMajor comments:\nI think it’s critical that the method is tested on various tissue types. The users presented the results of running NBFvis on a TNBC sample. However, not all cancer tissues (or even healthy tissues) have a clear structure and compartments. Often, one can find tissue samples where the cells are highly intermixed, and defining microenvironments becomes very challenging. I also think it’s important that NBFvis is tested on data from other technologies, such as spatial transcriptomics. It is equally important that the method is benchmarked against other tissue domain/microenvironment methods. For example, SpaGCN for spatial transcriptomics, or MILWRM for proteomics/transcriptomics. To mention the first two that came to my mind. The field is saturated with methods to achieve similar goals to what NBFvis does, and comparing to others can help the reader ponder the advantages over other methods. Following on the previous point, the authors mentioned SPARK in the “Background” section. But if NBFvis is a microenvironment detection method, it makes more sense to cite other spatial domain/microenvironment detection methods. Spatial-LDA is, of course, one of them, but many others are available, especially if NBFvis is proposed as a solution for spatial transcriptomics. I appreciate the efforts to test NBFvis on a simulated data set. However, I think the simulated data is too simplistic for the intended application. It is true that some older spatial proteomics data only offers a few markers, but this is rapidly changing, and many technologies offer many more markers (10s-100s). Simulating only five proteins seems overly simplistic. In addition, the almost clear-cut differences between cell types are seldom encountered in real data sets. Defining cell types is, in itself, a challenging task in large part because the information from the markers does not provide the categorized levels one would expect due to either technical noise or biology itself. This is especially true for spatial transcriptomics. Another important thing about the simulation performed is that it was unclear what the level of feature dropout was. In spatial omics data, it is very common for a large percentage of the data to consist of zeroes. This has tremendous implications when defining cell types or neighborhoods. It seems that the selection of a radius can significantly impact the results. I suspect the choice of a radius size must be largely driven by the knowledge of the cell biology of the specific tissue being studied or even the research question. However, the authors could have tested several radius sizes to inform the readers about the effects of radius selection. Similarly, selecting the number of PCs might be important. It seems NBFvis does not allow the user to specify the number of PCs. That 19 PCs explained 90% of the variation for the TNBC data does not imply that 19PCs will also explain that amount of variance for other data sets. Throughout the manuscript, it seems the authors are arguing against identifying clusters of cell types instead of “microenvironments”. Yet, in many cases, researchers indeed seek to phenotype their data sets to the cell level instead of the “microenvironment” level. This should be stated appropriately at the beginning of the manuscript, clarifying that NBFvis is a solution to the specific problem of tissue domain/microenvironment detection and not necessarily to cell phenotyping. What is the biological meaning of the centrality metrics? This is not addressed. Perhaps some testing of the method using several combinations of these parameters can provide a glimpse into this. Also, allowing the users to select which centrality metrics to incorporate in the embeddings may (or may not) be helpful.\nMinor comments:\nIn the abstract, I suggest changing “We designed quantile and network-based spatial features…” to “We developed a method that uses quantile and network-based spatial features…”. “… in the R package NBFvis, available on GitHub.” The link to GitHub repo is not working. It looks like the “single-cell matrix” and “expression matrix” terms are used interchangeably. I suggest uniformizing the use of the terms throughout the manuscript. The column names in the output of “network_matrix” are “statistics1”, “statistics2”… etc. Would it be more informative to conserve the actual name of the network metric?\nSuggestions for the code:\nI suggest adding the dependencies in the DESCRIPTION file. I had to re-try the installation several times as I had to install several dependencies. These are some of the unspecified dependencies: expm, shinythemes, centiserve, heatmaply, sna.\n\nIs the rationale for developing the new method (or application) clearly explained? Partly\n\nIs the description of the method technically sound? Partly\n\nAre sufficient details provided to allow replication of the method development and its use by others? Yes\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-799
https://f1000research.com/articles/11-798/v1	18 Jul 22	{ "type": "Research Article", "title": "Micro-shear bond strength of different surface treatments on a polymer infiltrated ceramic network", "authors": [ "Dian Agustin Wahjuningrum", "Calvo Ramírez Juan Norberto", "Méndez Mendieta Luisa Fernanda", "Amanda Andika Sari", "Ajinkya M. Pawar", "Alberto Carlos Cruz González", "Dian Agustin Wahjuningrum", "Calvo Ramírez Juan Norberto", "Méndez Mendieta Luisa Fernanda", "Amanda Andika Sari", "Ajinkya M. Pawar" ], "abstract": "Background: Polymer infiltrated ceramic networks, or hybrid ceramics, are a combination of infiltrating polymerizable organic monomers into a pre-sintered porous ceramic matrix. In addition to having good mechanical properties, the polymer infiltrated ceramic network must comply with the possibility of adequate bonding to the resinous cement. The surface conditioning of this hybrid material must be carefully considered due to its organic composition and ceramic network. The purpose of this research is to evaluate the effect of hydrofluoric acid and a self-etching ceramic primer, under two different application times, on the bond strength of a polymer infiltrated ceramic network. Methods: Blocks of a polymer infiltrated ceramic network were cut to obtain sheets, and these were randomized into five groups. For the group termed AAS, airborne-particle abrasion with Al2O3 (aluminum oxide) of 50µm was used. For groups HF2 and HF6, hydrofluoric acid was used for 20 and 60 seconds respectively, and for the groups MB2 and MB6, a self-etch ceramic primer was applied for 20 and 60 seconds respectively. A silane was applied to the groups AAS, HF2, and HF6 after the treatment. After 24-hour storage in distilled water, a micro-shear bond strength test was performed using a universal mechanical testing machine. All samples were evaluated in a stereomicroscope at 40x and 50x to determine the type of failure. Results: The highest and lowest values of bond strength were reported by groups MB6 and AAS, respectively. Groups HF2, HF6, MB6, and MB2 did not report statistically significant differences. The predominant failure pattern was a mixed failure. Conclusions: With the limitations of the present investigation, the treatments of self-etching ceramic primer and hydrofluoric acid followed by silane were reported to be statistically equal at 20 and 60 seconds.", "keywords": [ "Micro shear bond strength", "polymer infiltrated ceramic network (PICN)" ], "content": "Editorial note\n\nEditorial Note (26th July 2023): The F1000 Editorial Team is currently substantiating that this research was presented at an IIARP conference and should be included in the IIARP Gateway. The Editorial Team is currently requesting further information from the authors regarding this. This Editorial Note will be updated as new information is provided.\n\n\nIntroduction\n\nPICN (polymer infiltrated ceramic network), or hybrid ceramics, were introduced in dentistry as a restorative material, which, by infiltrating polymerizable organic monomers into a pre-sintered porous ceramic matrix, promises to obtain mechanical properties like dental enamel and a density equivalent to that of dentine.1 Hybrid ceramic offers a combined resistance to different failure modes, where the ceramic matrix confers resistance to wear and deformation, while the polymer provides some plastic deformation and reduces toughness or brittleness.2,3 The PICN has a composition of 86%wt of feldspathic ceramic and 14%wt of infiltrate of dimethacrylates (UDMA and TEGDMA, which are urethane-dimethacrylate and triethylene glycol dimethacrylate, respectively).4 It presents mechanical properties comparable to CAD-CAM (computer-aided design/computer-aided manufacturing) polymers with nano-ceramic particles, lower than lithium disilicate, but superior to CAD-CAM feldspathic ceramics.2–4 Hybrid ceramics, in addition to having good mechanical properties, must comply with the possibility of adequate bonding to the resinous cement.5\n\nAdhesive cementation increases the surface energy and the retention of the restoration reinforces its structural strength and maintains marginal integrity.6 Due to its high ceramic content, this type of material requires surface conditioning prior to resinous cement to ensure an adequate bond quality.7 Etching with 5% hydrofluoric acid for 60 seconds is the PICN manufacturer's recommended surface conditioning.5 However, other treatments such as hydrofluoric acid at 9% for 90 seconds, silanes, airborne-particle abrasion with aluminum oxide (30-50 μm particles) and tribochemical silica (CoJet System - 30 μm particles) have been reported.8,9 The association of hydrofluoric acid or air abrasion (aluminum oxide) with a silane agent can achieve considerable values of bond strength, due to the structure with a high content of feldspathic ceramic present in this material (>80%wt), compared to other CAD-CAM materials with polymeric matrix and dispersed ceramic particles, with lower values of bond strength using this same combination of surface treatments.10 However, given the risk of excessive dissolution of the vitreous matrix due to the attack of hydrofluoric acid, an etching agent and silane have been proposed in a single step, known commercially as Monobond Etch & Prime.11 With a chemical in its composition less aggressive than hydrofluoric acid, tetrabutylammonium dihydrogen trifluoride, this self-etching ceramic primer has reported considerable values of bond strength in lithium disilicate and feldspathic ceramics.12\n\nThe objective of this study was to evaluate the effect of hydrofluoric acid and a self-etching ceramic primer, under two different application times, on the bond strength of a polymer infiltrated ceramic network. The null hypothesis was that the mean values of bond strength of the groups treated with Monobond Etch & Prime would be equal to the groups treated with hydrofluoric acid and silane.\n\n\nMethods\n\nWe obtained ethical approval for this study from Faculty of Dentistry, Universidad Nacional de Colombia (approval number B.CIEFO-094-19). No patients or biological material obtained from patients were involved in this investigation.\n\nIn the present study, 15 sheets (8 mm wide and 10 mm high) were made from three VITA ENAMIC EM14 blocks (VITA Zahnfabrik, Bad Sackingen, Germany) by means of cuts every 2 mm using a precision diamond disc with constant cooling with distilled water (Isomet, Buehler Illinois, USA). These sheets were included in cylinders of self-curing acrylic resin (Veracril, New Stetic, Guarne, Antioquia, Colombia), 10 mm high, leaving an exposed face of the hybrid ceramic to receive surface treatment. The exposed surfaces were sanded with #600, #800, #1000, and #1200 grain size silicon carbide abrasive paper for approximately 1 minute under manual pressure. The samples were washed in distilled water with ultrasound for 15 minutes.\n\nThe sheets were randomized into five groups, with three sheets per group (n = 15) according to the surface treatments to be received. The group termed AAS had airborne-particle abrasion with Al2O3 of 50 μm applied for 10 seconds with a pressure of 1 bar, it was then washed with an air-water syringe for 20 seconds followed by drying with pressurized air for 10 seconds. A silane (Monobond N, Ivoclar Vivadent, Schaan, Liechtenstein) was applied with a microbrush rubbing for five seconds and leaving it to act for 60 seconds. Group MB2 used a self-etch primer (Monobond Etch & Prime, Ivoclar Vivadent, Schaan, Liechtenstein) which was applied for 20 seconds and then washed with water from an air-water syringe and dried with pressurized air for 10 seconds. Group MB6: like group MB2, but with the only difference that the primer was left to act for 60 seconds. Group HF2 used 9.6% hydrofluoric acid (Maquira Paraná, Brazil) which was applied for 20 seconds, it was then washed with an air-water syringe for 20 seconds, and dried with pressurized air, silane (Monobond N, Ivoclar Vivadent, Schaan, Liechtenstein) was applied with a microbrush rubbing for five seconds and it was left to act for 60 seconds, then air was gently applied for 10 seconds. Group HF6 was similar to group HF2, but with the difference that the etching with hydrofluoric acid was carried out for 60 seconds. The hydrofluoric acid residues were neutralized in a supersaturated solution of calcium carbonate.\n\nOn the conditioned surfaces, 0.75 mm internal diameter and 0.8 mm high medical grade silicone tubes were positioned and carefully filled with dual resinous cement (LuxaCore Z, DMG, Hamburg, Germany), finally, each cylinder was cured with the high setting for 20 seconds with a LED lamp (Bluephase C8, Ivoclar Vivadent, Schaan, Liechtenstein). In total, 5 tubes were placed for each hybrid ceramic sheet (n = 15). All samples were stored at 37°C for 24 hours in distilled water (Hygrobath, Whip Mix Louisville, KY, United States). Once the storage was completed, the mold tubes were carefully removed with #12 and #15 scalpel blades, exposing the resinous cement cylinders. All the samples were taken to a universal mechanical testing machine (Shimadzu AG-IS, Shimadzu Corporation, Kyoto, Japan), and by means of a steel wire handle, gauge 0.22 mm, with traction force, at a speed of 0.5 mm/min crosshead and a 50N load cell, the micro-shear test was performed. The bond strength was calculated using the equation: R = N/A, where R is bond strength given in MPa, N force in Newtons necessary for failure, and A is the area of the resin-cement-hybrid ceramic joint, measured in mm2. The adhesive area (A) was determined by π.r2, where π is a constant and r is the radius obtained from the internal diameter of the medical-grade silicone tube.\n\nAll samples were evaluated in a stereomicroscope (NIKON SMZ800, Nikon Instruments Inc. New York, United States) at 40× and 50× to determine the type of failure, these were classified as: adhesive failure, i.e. where there is separation of the union between cement and ceramic, leaving an intact ceramic surface; cohesive failure in the ceramic, i.e where separation occurs only in ceramic; cohesive failure in the resin cement, i.e. where separation occurs only in cement; and mixed failure, which is a combination of the cohesive and adhesive patterns.\n\nFor the statistical analysis, normality tests were carried out (Shapiro Wilk), and for the comparison of the groups, one-way ANOVA (Analysis of Variances) tests and Tukey's test were executed. A significance level of p < 0.05 was set. The R-project version R-3.6.3 for Windows was used for the statistical analyses (The R Project for Statistical Computing, St. Louis, Missouri, USA).\n\n\nResults\n\nDescriptively, the results of the groups can be understood as follows: a graphical similarity in the mean values of bond strength the groups MB2, MB6, HF2 and HF6 was observed. the highest data dispersion was obtained in the AAS group, and the lowest graphic dispersion of data were obtained by both groups MB. The highest and lowest mean values of bond strength were reported by groups MB6 and AAS, respectively (Figure 1).\n\nAAS: airborne-particle abrasion, HF2: hydrofluoric acid for 20s and silane, HF6: hydrofluoric acid for 60s and silane, MB2: a self-etch primer for 20s, MB6: a self-etch primer for 60s.\n\nIn the statistical comparison by pairs (Tukey’s test) the groups that used Monobond Etch & Prime and hydrofluoric acid were considered equal, while the group AAS was statistically inferior compared to the other four groups (Table 1). The predominant failure pattern in the study was mixed failure (Table 2 and Figure 2). However, the AAS group exhibited an almost exclusive pattern of adhesive failure. For the other four groups, the mixed failure pattern was predominant. The full data are available from Underlying data.30\n\nA. Adhesive failure, B. Cohesive cement failure, C. Ceramic cohesive failure, D. Mixed failure.\n\n\nDiscussion\n\nIn the present study, the bond strength between a PICN and a resinous cement after the use of hydrofluoric acid, a self-etching ceramic primer, and airborne-particle abrasion was compared. The airborne-particle abrasion group was significantly inferior to the two groups of acid etching agents. Therefore, the hypothesis that raised the statistical equality of the mean values of bond strength in the three surface treatments was not accepted.\n\nAirborne-particle abrasion with aluminum oxide particles is an alternative to increase the roughness of the ceramic substrate by impulsing and impacting the surface with abrasive particles, with the potential risk of microcracks and excessive damage to the treated surface.13 Parameters such as distance, time, pressure, and particle size can result in different roughness patterns.13,14 Abrasion with 30 μm size aluminum oxide has been associated with high roughness values and acceptable bond strength mean values on PICN.15 Although in the literature it is also reported that in CAD-CAM materials with polymeric matrix and dispersed ceramic particles, airborne-particle abrasion with aluminum oxide has shown superior results to acid etching. In PICN an opposite phenomenon generally occurs, this is perhaps based on the microstructural organization of this material.16 The use of airborne-particle abrasion on the surface of a hybrid ceramic creates roughness through impact microcracks, unlike acid etching that creates micropores due to the partial dissolution of the vitreous matrix.17 Etching with hydrofluoric acid and airborne-particle abrasion with aluminum oxide, followed by silane, has been reported with surface energy values in Enamic of 147 mJ/m2 and 96 mJ/m2 respectively. This suggests that the amount of roughness in a surface is not predictive of higher bond strength.18 Another possible explanation is that VITA ENAMIC, unlike other hybrid CAD-CAM materials, contains a porous network of feldspathic ceramic reinforced with alumina and only one infiltrate of urethane dimethacrylate polymer, allowing a better action of the etching agent and assuming the increased risk of surface damage and unevenness if airborne-particle abrasion is used.19 This mechanism probably explains why, even though both methods can create comparable values of surface roughness in a hybrid ceramic, the bond strength results can be higher after a chemical attack by acid.9,20 Only one protocol of air abrasion with aluminum oxide was contemplated in this study, which could be considered as a limitation of the research.\n\nOn the other hand, the self-etching ceramic primer in the literature has reported bond strength results comparable to hydrofluoric acid and silane on polymer infiltrated ceramic network.20,21 Both etching agents can produce similar roughness values, but self-etching ceramic primer was introduced to the market as a less aggressive alternative to hydrofluoric acid.12,22 The physical-chemical action is due to an acid etching with tetrabutylammonium dihydrogen trifluoride and a chemical interaction through trimethoxy propyl methacrylate, without diminishing the mechanical resistance and fatigue of the ceramic substrate.23 Additionally, a formation of a hydrophobic silane layer that is theoretically more resistant to hydrolytic degradation has been associated with the use of this self-etching ceramic primer.24 The etching depth of 9% hydrofluoric acid for 20 and 60s is greater than 290 μm compared to a depth of 7 μm of Monobond Etch & Prime for 40s in VITA ENAMIC.25 Therefore, the indication of which surface treatment to use does not only depend on the bond strength results obtained. Hydrofluoric acid on VITA ENAMIC is dependent on the time and concentration of use. Hydrofluoric acid concentrations of 5% between 30 and 90 seconds do not seem to significantly affect flexural strength, on the contrary, the use of hydrofluoric acid at 10% after 30 seconds reports a significant decrease in flexural strength of this hybrid ceramic.26 In this study a concentration of 9.6% was used, with similar bond strength results between 20 and 60 seconds. A consistent finding that hydrofluoric acid etching of VITA ENAMIC for more than 30 seconds does not significantly improve bond strength by shear test.5 This analysis may be somewhat helpful in supporting the recommendation of the lowest possible time and concentration of hydrofluoric acid to treat the surface of VITA ENAMIC. However, the present investigation had the limitation of only evaluating one hydrofluoric acid concentration.\n\nAdhesive failure patterns have been associated with low values of bond strength, cohesive and mixed patterns seem to be considered more acceptable because they suppose a better infiltration of the resinous cementing agent in the conditioned surface of the PICN.27,28 In the present investigation, the predominant pattern was mixed for the hydrofluoric acid and self-etching ceramic primer groups, consistent with the highest values of bond strength in the study, and an almost exclusive pattern of adhesive failures for the airborne-particle abrasion group, in which the lowest values were obtained. The results of this investigation should be considered with caution since the bond strength test was carried out after the short-term storage of the samples. Bond strength can be affected by hydrolytic degradation of the materials in the small adhesive area, storage in water for long periods of time, or thermal cycling.28,29\n\n\nConclusions\n\nWith the limitations of the present investigation, the self-etching ceramic primer and hydrofluoric acid followed by silane were reported to be statistically equal at 20 and 60 seconds. The 20 second time seems to be a more reasonable option than 60 seconds applying these surface treatments on a PICN. This is because, if the same bond strength result is obtained at 20 and 60 seconds, it can increase the surface energy in less time. Airborne-particle abrasion is not recommended as the first choice of surface treatment in a PICN.\n\n\nData availability\n\nMendeley Data: Micro-shear bond strength of different surface treatments on a polymer infiltrated ceramic network. https://doi.org/10.17632/dfm9wr4bwn.4.30\n\nThis project contains the following underlying data:\n\n– Acronym manuscript Micro-shear bond strength of different surface treatments on a polymer infiltrated ceramic network.docx (description of acronyms used within the data spreadsheets).\n\n– Statistical Data.xlsx (raw data for each group. AAS is airborne-particle abrasion, MB2 is a self-etch primer for 20 seconds, HF2 is 9.6% hydrofluoric acid for 20 seconds, MB6 is a self-etch primer for 60 seconds, HF6 is 9.6% hydrofluoric acid for 60 seconds).\n\n– Description groups.xlsx (statistical examination as a comparison among the groups. These statistical examinations are ANOVA, post hoc ANOVA using Tukey, and the graph of the groups).\n\n– Comparison adhesive resistance groups.xlsx (statistical descriptive among the groups. Shows the components in the statistical descriptive, such as median, kurtosis, percentiles, etc. that show the explore descriptive data among these group).\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "Acknowledgements\n\nThe authors acknowledge the Indonesian Ministry of Education and Faculty of Dental Medicine, Universitas Airlangga, Surabaya-Indonesia and The Faculty of Dentistry, Universidad Nacional de Colombia, Bogotá-Colombia. The statistical analysis of this research was supported by the Faculty of Dentistry, Universidad Nacional de Colombia.\n\n\nReferences\n\nCui B-C, Li J, Lin Y-H, et al.: Polymer-infiltrated layered silicates for dental restorative materials. Rare Metals. 2019; 38: 1003–1014. Publisher Full Text\n\nEl Zhawi H, Kaizer MR, Chughtai A, et al.: Polymer infiltrated ceramic network structures for resistance to fatigue fracture and wear. Dent. Mater. 2016; 32: 1352–1361. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFurtado de Mendonca A, Shahmoradi M, Gouvêa CVD, et al.: Microstructural and Mechanical Characterization of CAD/CAM Materials for Monolithic Dental Restorations. J. Prosthodont. 2019; 28: e587–e594. PubMed Abstract \| Publisher Full Text\n\nHong MS, Choi YS, Lee HH, et al.: Comparison of Mechanical Properties of Chairside CAD/CAM Restorations Fabricated Using a Standardization Method. Materials (Basel). 2021; 14: 3115. PubMed Abstract \| Publisher Full Text\n\nSchwenter J, Schmidli F, Weiger R, et al.: Adhesive bonding to polymer infiltrated ceramic. Dent. Mater. J. 2016; 35: 796–802. Publisher Full Text\n\nFacenda JC, Borba M, Corazza PH: A literature review on the new polymer-infiltrated ceramic-net-work material (PICN). J. Esthet. Restor. Dent. 2018; 30: 281–286. PubMed Abstract \| Publisher Full Text\n\nHelbling F, Özcan M: Adhesion of resin cement to contemporary hybrid ceramic and polymeric CAD/CAM materials: effect of conditioning methods and ageing. J. Adhes. Sci. Technol. 2019; 33: 886–902. Publisher Full Text\n\nMotevasselian F, Amiri Z, Chiniforush N, et al.: In Vitro Evaluation of the Effect of Different Surface Treatments of a Hybrid Ceramic on the Microtensile Bond Strength to a Luting Resin Cement. J. Lasers Med. Sci. Fall. 2019; 10: 297–303. PubMed Abstract \| Publisher Full Text\n\nPapadopoulos K, Pahinis K, Saltidou K, et al.: Evaluation of the Surface Characteristics of Dental CAD/CAM Materials after Different Surface Treatments. Materials (Basel). 2020; 13(13): 981. Publisher Full Text\n\nEmsermann I, Eggmann F, Krastl G, et al.: Influence of Pretreatment Methods on the Adhesion of Composite and Polymer Infiltrated Ceramic CAD-CAM Blocks. J. Adhes. Dent. 2019; 21: 433–443. PubMed Abstract \| Publisher Full Text\n\nPrado M, Prochnow C, Marchionatti AME, et al.: Ceramic Surface Treatment with a Single-component Primer: Resin Adhesion to Glass Ceramics. J. Adhes. Dent. 2018; 20: 99–105. PubMed Abstract \| Publisher Full Text\n\nEl-damanhoury HM, Gaintantzopoulou MD: Self-etching ceramic primer versus hydrofluoric acid etching: Etching efficacy and bonding performance. J. Prosthodont. Res. 2018; 62: 75–83. PubMed Abstract \| Publisher Full Text\n\nGünal-Abduljalil B, Önöral Ö, Ongun S: Micro-shear bond strengths of resin-matrix ceramics subjected to different surface conditioning strategies with or without coupling agent application. J. Adv. Prosthodont. 2021; 13(3): 180–190. PubMed Abstract \| Publisher Full Text\n\nBello YD, Di Domenico MB, Magro LD, et al.: Bond strength between composite repair and polymer-infiltrated ceramic-network material: Effect of different surface treatments. J. Esthet. Restor. Dent. 2019; 31(3): 275–279. PubMed Abstract \| Publisher Full Text\n\nSismanoglu S, Yildirim-Bilmez Z, Erten-Taysi A, et al.: Influence of different surface treatments and universal adhesives on the repair of CAD-CAM composite resins: An in vitro study. J. Prosthet. Dent. 2020; 124(2): 238.e1–238.e9. Publisher Full Text\n\nEldafrawy M, Greimers L, Bekaert S, et al.: Silane influence on bonding to CAD-CAM composites: An interfacial fracture toughness study. Dent. Mater. 2019; 35(9): 1279–1290. PubMed Abstract \| Publisher Full Text\n\nCampos F, Almeida CS, Rippe MP, et al.: Resin Bonding to a Hybrid Ceramic: Effects of Surface Treatments and Aging. Oper. Dent. 2016; 41: 171–178. PubMed Abstract \| Publisher Full Text\n\nChuenjit P, Suzuki M, Shinkai K: Effect of various surface treatments on the bond strength of resin luting agent and the surface roughness and surface energy of CAD/CAM materials. Dent. Mater. J. 2021; 40: 16–25. PubMed Abstract \| Publisher Full Text\n\nNiizuma Y, Kobayashi M, Toyama T, et al.: Effect of etching with low concentration hydrofluoric acid on the bond strength of CAD/CAM resin block. Dent. Mater. J. 2020; 39: 1000–1008. PubMed Abstract \| Publisher Full Text\n\nGrangeiro MTV, Rossi NR, Barreto LAL, et al.: Effect of Different Surface Treatments on the Bond Strength of the Hybrid Ceramic Characterization Layer. J. Adhes. Dent. 2021; 23: 429–435.\n\nel-Damanhoury HM, A. Elsahn N, Sheela S, et al.: Adhesive luting to hybrid ceramic and resin composite CAD/CAM Blocks:Er:YAG Laser versus chemical etching and micro-abrasion pretreatment. J. Prosthodont. Res. 2021; 65: 225–234. PubMed Abstract \| Publisher Full Text\n\nMurillo-Gómez F, De Goes MF: Bonding effectiveness of tooth-colored materials to resin cement provided by self-etching silane primer after short- and long-term storage. J. Prosthet. Dent. 2019; 121: 713.e1–713.e8. Publisher Full Text\n\nDapieve KS, Machry RV, Pilecco RO, et al.: One-step ceramic primer as surface conditioner: Effect on the load-bearing capacity under fatigue of bonded lithium disilicate ceramic simplified restorations. J. Mech. Behav. Biomed. Mater. 2020; 104: 103686. Publisher Full Text\n\nMoreno MBP, Murillo-Gómez F, de Goes MF : Physicochemical and morphological characterization of a glass ceramic treated with different ceramic primers and post-silanization protocols. Dent. Mater. 2019; 35(8): 1073–1081. Publisher Full Text\n\nMurillo-Gómez F, Palma-Dibb RG, De Goes MF: Effect of acid etching on tridimensional microstructure of etchable CAD/CAM materials. Dent. Mater. 2018; 34: 944–955. PubMed Abstract \| Publisher Full Text\n\nMiranda JS, Monteiro JB, Silva PNF, et al.: Can different etching protocols change the properties of a hybrid ceramic? Gen. Dent. 2020; 68: 20–25. PubMed Abstract\n\nKömürcüoğlu MB, Sağırkaya E, Tulga A: Influence of different surface treatments on bond strength of novel CAD/CAM restorative materials to resin cement. J. Adv. Prosthodont. 2017; 9: 439–446. PubMed Abstract \| Publisher Full Text\n\nKilinc H, Sanal FA, Turgut S: Shear bond strengths of aged and non-aged CAD/CAM materials after different surface treatments. J. Adv. Prosthodont. 2020; 12: 273–282. PubMed Abstract \| Publisher Full Text\n\nSilva PNFD, Martinelli-Lobo CM, Bottino MA, et al.: Bond strength between a polymer-infiltrated ceramic network and a composite for repair: effect of several ceramic surface treatments. Braz. Oral Res. 2018; 32: e28.\n\nWahjuningrum DA, Calvo JN, Fernanda MML, et al.: Micro-shear bond strength of different surface treatments on a polymer infiltrated ceramic. Mendeley Data, V1. Dataset. 2022. Publisher Full Text" }	[ { "id": "210203", "date": "20 Nov 2023", "name": "Nantawan Krajangta", "expertise": [ "Reviewer Expertise digital dentistry", "esthetic dentistry", "dental materials" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis study examines the micro-shear bond strength of various PICN surface treatments. This is an In Vitro study, which has potential implications for clinical applications in restorative dentistry using the PICN. The clarity and organization of the manuscript are commendable. I have only minor suggestions for improvement as follows:\nAbstract:\nTo improve the coherence of the abstract, it is recommended to align the sequence of description with the order of experimentation and results. Specifically, the abstract currently discusses HF2 and HF6 before MB2 and MB6, while the presentation of experimental details and results showcases MB2 and MB6 before HF2 and HF6. To enhance consistency, consider revising the abstract to ensure that the order of describing treatments aligns with the order in which the experimentation and results are presented.\nIntroduction:\nThe introduction section is well structured. However, to improve this section, explain and emphasize existing knowledge that has been studied and the gap of knowledge related to surface treatment of PICN.\nMethodology:\n1. Research design:\nPlease explain more about how the manual pressure is uniformly controlled for polishing the specimens.\n\nIt is typically preferred to prepare samples with width and length matching the block dimensions, but the sample in this study has dimensions of 8x10x2 mm. It was prepared by cutting the VITA ENAMIC EM14 block with dimensions of 12x14x18 mm. Please explain the cutting method. To prepare additional samples in the content or use figures.\n\n2. Experimental procedure:\nThe introduction states, \"Etching with 5% hydrofluoric acid for 60 seconds is the PICN manufacturer's recommended surface conditioning.\" However, the testing involved the use of 9.6% HF. Could you provide the rationale for this choice?\n\nIn this study, all samples underwent evaluation using a stereomicroscope (NIKON SMZ800, Nikon Instruments Inc. New York, United States) at both 40x and 50x magnifications to ascertain the type of failure. Why was testing conducted at both 40x and 50x, especially considering that study results are only presented at 50x magnification?\n\nResult:\nThe order of abbreviation descriptions in Tables 1 and 2 should be modified to reflect the order of information presented in the tables.\n\nDiscussion:\nThis study on the effects of 9.6% hydrofluoric acid, therefore, the statement \"This analysis may be somewhat helpful in supporting the recommendation of the lowest possible time and concentration of hydrofluoric acid to treat the surface of the VITA ENAMIC.\" is inaccurate and does not align with the outcomes of this study. Please correct this statement.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "215064", "date": "20 Nov 2023", "name": "Guillermo Manuel Herrera Pérez", "expertise": [ "Reviewer Expertise Ceramics (ferroelectric and ferromagnetic)", "Raman", "and EELS spectroscopies." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nI read the manuscript entitled “Micro-shear bond strength of different surface treatments on a polymer infiltrated ceramic network” written by Wahjuningrum et al. The authors show the interesting results. They evaluate the effect of hydrofluoric acid and a self-etching ceramic primer, considering two different application times. Also, they evaluate the influence of both surface conditions on the bond strength of a polymer-infiltrated ceramic network. The manuscript is well organized, and the references used are fine in number and actual. The authors describe the preparation of samples, and they describe the methodology to determine the bond strength. The current work is complemented by the determination of the type of failure (adhesive failure, cohesive failure, and mixed failure) considering the stereomicroscope technique. The predominant failure pattern was a mixed failure. In general, the statistical analyses and their interpretation seem to have been performed properly and the conclusions reached are in line with the results presented. The methods and analyses provided in this manuscript can be replicated by others. Certainly, the theme of this manuscript is suitable for the journal and surely of wide interest to the reading community of F1000Research.\nThe paper is acceptable after minor revisions for indexing after the comments below are addressed.\nThe scale bar in the stereomicroscope images should be clearer (Figure 2).\n\nAtomic force microscopy (AFM) analysis should be implemented. The authors mention, in the discussion section, \"different roughness patterns, high roughness, and surface roughness\", which needs to be verified (including micrographs) and quantified. Additionally, AFM analysis can provide information about physical defects such as microcracks. Also, this technique allows us to evaluate the presence of micropores.\n\nThe authors focus on the effect of airborne particle abrasion on the surface of a hybrid ceramic. However, the average particle size (including micrographs and histogram analysis) influence on roughness is not investigated. Please conduct transmission electron microscopy analysis.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "215076", "date": "22 Nov 2023", "name": "Sivaranjani Gali", "expertise": [ "Reviewer Expertise Dental ceramics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors investigated the micro-shear bond strength of different surface treatments on a polymer infiltrated ceramic network, especially of VITA Enamic.\n\nThe following are my comments:\nSchematic illustrations are required to differentiate the groups\n\nConclusion can be rephrased in line with the objective of the study.\n\nFlowchart of methodology to be included.\n\nWere the samples thermocycled ?\n\nDiscussion can include the results of similar studies and how this study stands out from the rest?\n\nMechanism of action of sandblasting and acid etching can be illustrated.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nI cannot comment. A qualified statistician is required.\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-798
https://f1000research.com/articles/11-797/v1	18 Jul 22	{ "type": "Research Article", "title": "Multiparty democracy, social cohesion, and human development in Sub-Saharan Africa: A panel data analysis", "authors": [ "Hamidou Issaka Diori", "Anchana NaRanong", "Anchana NaRanong" ], "abstract": "Background: The reintroduction of multiparty democracy in Sub-Saharan Africa during the early 90s and the persistent poor human development performance of the region, have sparked several controversies regarding the need for such a political system in Africa. In the extant literature, these controversies have been characterized by fierce theoretical debates as to whether multiparty democracy influences human development and the scholarly contention that social cohesion, rather than this form of democracy, ameliorates human development. The present study examines these controversies along with the perception of Sub-Saharan African populations concerning the democratic transition and its impact on their well-being. Methods: A panel data analysis of 35 countries was conducted between 1995 to 2019 in order to determine the effect of multiparty democracy, social cohesion, and their interaction on human development. Fixed-effects and system generalized methods of moments estimations were used to control for specific characteristics. Results: The study found that, multiparty democracy, social cohesion, and the interaction between these two variables have a positive long-term effect on human development. More importantly, the study revealed that social cohesion decreases the negative influence of multiparty democracy on human development. Conclusions: Overall, the findings of this study suggest that multiparty democracy is likely to improve the well-being of the populations of Sub-Saharan Africa if the degree of social cohesion is sufficiently high. That also means that social cohesion is susceptible to dampening the negative effect of multiparty democracy on human development in the context of this study. As such, social cohesion is critical in terms of the extent to which multiparty democracy wields influence on human development outcomes in Sub-Saharan Africa. Based on these conclusions, a number of policy recommendations are discussed in the present study towards the achievement of sustained human development in the Sub-Saharan African region.", "keywords": [ "multiparty democracy", "social cohesion", "human development", "Africa", "Sub-Saharan region" ], "content": "Introduction\n\nSub-Saharan Africa, a region of forty-six countries according to the United Nations Development Program (UNDP) and with a combined population of over 1.1 billion inhabitants as of 2019 (Statista, 2020), has long been considered the least developed area in Africa and the world. The causes of this underdevelopment are believed to be dysfunctional political institutions and governance, recurring conflicts, rampant corruption, resource mismanagement, among other debilitating social concerns. In order to help the region develop, if that were the real intention, aid donors in the West (countries and institutions alike) decided to impose multiparty democracy on the whole region. Hence, to act out their decision, these groups have linked most parts of international assistance to political system change in Sub-Saharan Africa, claiming that, democracy (the new system) would reduce the potential of conflicts in the region and foster good governance which, in turn, would stimulate development (Chabal, 2002). However, the events of the past three decades in this region of Africa conflict with such a narrative (Chabal, 2002). The new system has a priori, neither led to social and political stability, nor better forms of governance, let alone development. On the contrary, the inception of multiparty democracy in Sub-Saharan Africa and the resulting poor human development outcomes have sparked several controversies regarding whether the system has had, or is having some tangible effects on the well-being of the population.\n\nOther forms of controversies have emerged on the continent as well. Among the most recurrent, one is concerned with the true intent of Western governments for pushing for democratic transitions in Sub-Saharan Africa, given that a similar system had already collapsed after independence and turned most or all African countries into some variant of a “one-party state” (Alence, 2004). It is worth recalling here that independence in former French and British protectorates and colonies was followed by pluralist polls which suddenly revived the dormant social divisions and animosity within the regions. The explanations provided at the time by authorities in those ancient colonies regarding the reasons why their countries had turned to one-party systems stressed the peril of electoral competition. Those very rationales are today considered as mere alibis used to circumvent democratic transitions in Africa, as the reasoning behind them remain as valid now as it was at independence (Chabal, 2002).\n\nRegardless of the intentions underlying the push for political system change, multiparty democracy in SSA is yet to trigger sound political development from monopartism or monopoly to pluralism and perfect competition. In most African countries, as Chabal has indicated (2002), those who vie for political power belong to a small group of politicians that have been “in the business” for ages. Moreover, in numerous instances, the sitting ruler has arranged to cling to power via manipulation, authoritarianism, and persuasion (Alence, 2004; Chabal, 2002). In short, the new political system (or democracy, as it should be called) has barely led to renewal for the elite, better modes of governance or improvement in quality of life in SSA. Hence, exploring these controversies, in conjunction with Sub-Saharan Africans’ perspective of the democratic transition and its effect on their well-being, remains of particular interest.\n\nTo this end, the current study holds three primary objectives: (1) to determine the effect of multiparty democracy on human development; (2) to determine the effect of social cohesion on human development; and (3) to estimate the effect of the interaction between multiparty democracy and social cohesion on human development. Panel data was then gathered from thirty-five countries in SSA between 1995 and 2019 to test the research hypotheses.\n\nThe present study contributes to the literature on multiparty democracy and human development by proposing a hands-on theoretical model of democratic reform implementation that goes beyond the current models advocated in the existing studies. This conceptual model may enable future researchers to comprehend how and why democracy and human development remain increasingly challenging to African countries. The proposed model stipulates that any political change, regardless of the party that advocates it or the apparent level of diligence attached, must first be initiated by consolidating social cohesion. The present study also contributes to discussions on the foreign assistance literature by improving upon existing studies that have failed to include the nature of African politics in their analysis. The quantitative aid studies are only heedful of the effects of foreign assistance on democratic development in recipient countries following the organization of elections. Few attempts have been made to extend beyond generic political games to grasp the organization of African political systems, the neo-patrimonial character, ethnic and communal considerations, and their effect on the accomplishment of tangible human development. In suggesting a practical model of policy reform implementation and improving upon the existing literature on democracy and development in Africa, great contributions will be made in the search for sustainable development in SSA and the world since the improvement in one particular region may create positive effects in other parts of the globe. In sum, the contributions of the present study are of particular significance to scholars in the field of political science, development studies or sociology, as well as professional politicians and state leaders. They are relevant and timely for the development of a region that suffers from widespread socio-economic crisis and political disorder. The remainder of this study proceeds as follows: Section 2 critically reviews the relevant theories associated with the relationship shared by multiparty democracy, social cohesion, and human development. Section 3 introduces the research methodology, the techniques of data collection, and methods for analysis. Section 4 identifies the key findings derived from the data which were examined and presented in accordance with the technique described in the third section. Finally, section 5 culminates the study with a conclusion and recommendations.\n\n\nTheoretical background\n\nTwo theoretical paths were adapted for testing the hypotheses of the current study, namely, the regime type and poverty theory and the social cohesion theory.\n\nRegime type and poverty theories are founded on the presumption that a close relationship exists between the mode or type of a country’s government and the standard of living of its people. Moreover, these theories imply that democracy has the potential to improve the living standards of the lowest income groups, while nondemocracy lowers the standards (Acemoglu, Naidu, Restrepo, & Robinson, 2019; Altman & Castiglioni, 2009; Besley & Kudamatsu, 2006; Blaydes & Kayser, 2011; Deacon, 2009; Eterovic & Sweet, 2014; Gerring et al., 2015; Gerring, Thacker, & Alfaro, 2012; Haggard & Kaufman, 2008; Hanson, 2015; Kudamatsu, 2012; McGuire, 2013; Miller, 2015; Sen, 1999; Sen, 1981).\n\nThree theories are at the center of the regime type and poverty model (Ross, 2006), two of which are associated with the works of Sen (1999, 1981) on the causes of famine and poverty (Ross, 2006). In his works, Sen first argued that democracy enables the poor to inflict sanctions on governments that enable famines to occur, through electoral processes, and that political leaders would act judiciously to prevent famines and avoid sanctions (Ross, 2006). Secondly, Sen argued that democracies are relatively better than nondemocracies in terms of their capacity to disseminate information from remote and poor areas to the central administration due to the freedom of the press. Thus, according to him, even when leaders of a democratic and a nondemocratic government are equally devoted to preventing the occurrence of famine, democratic leaders are more likely to know precisely when action is required (Ross, 2006).\n\nThe third theory suggests that a democratic system would make more expenses in terms of welfare benefits for the poor, as compared to nondemocratic regimes. Hence, several scholars opine that democracies expend more on services and public goods as the electoral process compels them to, while non-democratic governments face no such constraint (Ross, 2006). A priori, there are good indications that these theories are at least partially correct - democratic regimes appear to be more concerned about social goods and services than non-democratic governments.\n\nIndeed, historical studies have shown a partial correlation between suffrage extension and the size of government welfare spending both in the US (Gouveia & Masia, 1998) and more generally in the Western and Latin American countries (Kristov, Lindert, & McClelland, 1992; Lindert, 1994). In addition, a study of 44 African countries by Stasavage (2005) has outlined a strong substantiation that democracy has augmented government spending on education, while a series of analyses of Latin American countries has found that democracy is highly correlated with higher spending on health, education, and social security (Avelino, Brown, & Hunter, 2005; Brown & Hunter, 2004; Kaufman & Segura-Ubiergo, 2001). However, even if democratic governments increase social expenditure, a posteriori, they do not improve infant or child mortality rates, which are considered by many to be the most accurate and comprehensive indicators of social welfare among the poor (Ross, 2006).\n\nThus, the literature on democracy and development appears to demonstrate conflicting views regarding the plausible effects of multiparty politics on the well-being of people. Until recently, the most commonly held view in this context has been that multiparty democracy ameliorates human development (Gerring et al., 2012; 2015). This view has been observed in various scholarly works (Altman & Castiglioni, 2009; Besley & Kudamatsu, 2006; Blaydes & Kayser, 2011; Brown & Mobarak, 2009; Deacon, 2009; Eterovic & Sweet, 2014; Haggard & Kaufman, 2008; Hanson, 2015; Kudamatsu, 2012; McGuire, 2013; and Miller, 2015) for instance.\n\nLately, however, the commonly held view that the well-being of individuals is influenced by democracy has been fiercely challenged and debunked, with numerous quantitative and qualitative studies conducted to corroborate the absence of a tangible association between regime type and diverse aspects or measures of human development (Gerring et al., 2012; 2015; McGuire, 2006; Ross, 2006; Shandra, Nobles, London, & Williamson, 2004). Further, given recent factual analysis, some of the arguments in favor of the above opinion are questionable. While most people generally believe that democracy would result in higher social expenditures, which, in turn, would improve the welfare of the poor, it has been noted that there is little to no relationship between public spending and human development beyond the context of the OECD countries (Filmer & Pritchett, 1999; McGuire, 2006).\n\nIn bids to reconcile these two views and to probe deeper into the relationship between democracy and human development, Gerring et al. (2012) have introduced the possibility that the developmental effects of democracy may be longer-term, characterized by a distal rather than proximal causal relationship. Hence, these authors opine that empirical works must test the relationship between the two variables while accounting for the time lag of the model. Owing to further research and a series of statistical checks with the infant mortality rate (IMR) as the main measure of human development, in conjunction with two hypotheses (the first, replicating the traditional causal model that links IMR to a country’s achievement or level of democracy in the previous year; and the second, measuring democracy with a “stock” indicator that captures a country’s regime history from 1900 to the observation year), Gerring et al. (2012) have found that the contemporary level of a country’s democracy has a weak association with enhanced human development, while a country’s historical experience with democracy has a strong and robust influence on human development. Hence, the researchers concluded that democracy does ameliorate human development only in cases where it is considered a historical or “stock” phenomenon. In simple terms, this implies that if a democratic system of governance is upheld over a longer period, its net effect will be resolute for the welfare of its citizens. Where one stands today depends essentially upon where one has been (Gerring et al., 2012).\n\nIn the context of the present study, the measure of human development extends beyond the infant mortality rate to relate to the quality of life, improvement in personal income, environmental conditions, and healthcare and education attainment (Seers, 1979). Hence, it is difficult to suggest that sustained or meaningful human development has occurred in Sub-Saharan Africa. Thus far, multiparty democracy has not eradicated poverty or hunger in the region, which are incompatible with any form of development. The measures of human development as well as the other variables used in the present study can be found under Underlying data (Diori & NaRanong, 2022).\n\nIn his work entitled “The quest for good governance and development in Sub-Saharan Africa,” Chabal (2002) quoted the NEPAD (New Partnership for African Development), declaring that peace, quality governance, socio-political stability, institutional consolidation, and the rule of law are necessary for investment and economic growth. Moreover, NEPAD is of the opinion that the aforementioned factors necessary for growth can only be derived from democracy, which has long been considered by Western development agencies and donors as the main precondition for the “takeoff” of any nation intending to transition from a state of underdevelopment to development.\n\nHowever, such a perception of democracy and its impact on development has been met with strong criticism. Today, it is an open secret that democracy in SSA has neither brought about social cohesion and political stability, nor better institutions and economic growth, which are normally considered the prerequisites for any development. This idea was supported by Easterly et al. (2006), who provided substantial proof to show how social equity and group cohesion can lead to better institutions and economic growth. For these researchers, strengthening cohesion within society by creating and maintaining quality institutions that benefit all members and lower socio-economic cleavages is imperative for countries struggling with growth (Easterly et al., 2006).\n\nSocial cohesion within a country is critical for establishing the trust and civic participation required to enact specific reforms as citizens must accept the short-term depravations that naturally arise from reform implementations before the situation ameliorates in due course (Easterly et al., 2006).\n\nThis study drew on Easterly et al.’s theory of social cohesion, institutions, and growth (2006). Social cohesion theory was deemed suitable for this study as it emphasizes the reasons for which multiparty democracy has rarely fostered human development in the SSA region. Hence, the search for tangible effects of multiparty democracy and social cohesion on the development of the SSA region occurred in line with the theoretical lens offered by Easterly et al. (2006) as well as the regime type and poverty theories. The same methodological lenses were utilized to address the research hypotheses, which consisted of testing the short-run and long-term upshots of multiparty democracy and social cohesion on the well-being of the people in SSA.\n\nAs for the literature on social cohesion and human development, it has not been prolific regarding the relationship between the two concepts. Few theoretical and empirical attempts have been made to establish a linkage, both direct and indirect, between the two concepts. In a study that aimed to explore the potential effects of social cohesion on human development using state legitimacy as a mediator between the two variables, Seyoum (2020) finds that social cohesion has a direct and an indirect effect on the well-being of people, i.e., human development. Using data from 180 countries and the state fragility index as a proxy of social cohesion, the latter study identifies several aspects of a socially cohesive state with a significant influence on poverty alleviation and sustained development (Seyoum, 2020). However, decreased or absent social cohesion was found to generate a lack of successful institutions, which, in failed states, are characterized by political and economic rules and regulations that frequently promote indecency and undermine the fair distribution of public wealth (Easterly et al., 2006; Seyoum, 2020). Although resources may proliferate in a failed state, they are seldom used to address public poverty or improve the health system. Hence, the consequence of state fragility would eventually be felt in education (e.g., poor school systems and facilities, the lack of quality and quantity of teaching materials), healthcare (poor healthcare systems and facilities, and inadequate treatment), and income distribution (inequality and discrimination in GDP per capita, unequal access to state resources). The findings consider a tangible relationship between the inadequate provision of goods and public services with state failure and fragility; hence, Amate-Fortes, Guarnido-Rueda and Molina-Morales (2017) conclude that the incapacity of the state to provide for security, necessary goods, and services also has a negative effect on economic growth, and consequently, on human development.\n\nA similar study by Rotberg (2010) finds that in instances where a state fails, its population disperses, human capital is drained, and the total production and per capita income start to dwindle. State failure results in governments failing to account for their citizens and, at times, being unwilling to formulate policies to reduce poverty and advance human development. In short, failed states suffer from a dearth of good governance, ranging from the establishment of credible institutions to the consolidation of democratic achievements, in addition to a dearth of rule of law and equity.\n\nFurthermore, a 2018 OECD report has found that state fragility is mainly caused by a lack of cohesion within a society as well as its fractionalization into groups with opposing identities and daily struggles. In the absence of social cohesion, even the elites, who are to unite such groups, tend to be factionalized, regarding the state as a means of personal profit rather than a politically organized unit that may be developed for common interests.\n\nInequalities and ethnic fractionalization are current challenges that Sub-Saharan Africa faces due to the dreadful disparities between the rich and the poor. Ethnic fractionalizations and various types of inequality operate as channels through which considerable social unrest can erupt (Easterly et al., 2006).\n\nIn summary, social cohesion is proven to be indispensable for SSA countries to transit to human development. Its absence may cause dire social pathologies that may not only have an effect on economic issues but also endanger the subsistence and viability of society at large (Durkheim, 1897). Nowadays, it is unanimously agreed that human development not only depends on economic issues but also on numerous social consensuses to be met.\n\n\nMethods\n\nThe present study uses a panel data technique to determine the effect of multiparty democracy and social cohesion on human development in SSA. Panel data analyses are correlational research strategies entailing a methodical examination of possible relations between a set of variables. They are utilized to determine if variations in an outcome or criterion variable are related to possible changes in one or more predictor variables. This is exactly the case of this study where efforts were made to determine whether the variations in human development measures are attributed to the regime type (multiparty democracy) in use in the SSA region, or to the presence or absence of social cohesion, while controlling for other possible determinants. The panel data approach was selected in this study to address the research hypotheses, developed as follows:\n\nH1: Multiparty democracy has a positive effect on human development.\n\nH2: Social cohesion has a positive effect on human development.\n\nH3: The interaction between multiparty democracy and social cohesion has a positive effect on human development.\n\nIn hypothesis 1, a distinction is made between the long- and short-term effects of multiparty democracy on human development. This hypothesis is consistent with the literature on democracy and development, where an immediate relationship and a log-run effect between the two variables are often observed. This may be viewed through the lens of “supply” (post-electoral government provisions and stimulus packages) or “demand” (advances in human development as demanded by voters). In either observation, multiparty democracy may have a short-term relationship or effect on human development.\n\nAlternatively, with regard to the distal effect of multiparty democracy on human development, this effect may manifest as an increase in economic growth, which eventually leads to higher per capita income, higher achievement in health, education, etc. In this optic, it is possible to affirm that the effects of multiparty democracy on human development are not immediate; rather, they present themselves in the longer run. Countries must enjoy economic growth first before their populations receive the benefits attached to the same. This long-run effect is also echoed in H1.\n\nIn hypothesis 2, however, the empirical evidence offered by extant literature indicates a long-term relationship between social or community cohesion and human development. This is observed via the attainment of quality institutions first, where the latter induces economic growth, subsequently bringing about an improvement in human development (see Easterly et al., Social Cohesion, Institutions, and Growth theory - section 2).\n\nSimilarly to H1, hypothesis 3 exhibits a twofold relationship; one that is immediate and the other long term, in relation to the interaction effect between multiparty democracy and social cohesion on human development. These relations are observed through “supply” and “demand”, as explained in hypothesis 1. The assumption of all of the hypotheses suggests a positive, rather than negative relationship, between multiparty democracy, social cohesion, and human development. This is in line with most theories and empirical research findings in the literature on these relations.\n\nThe population of this study comprises the member states of the SSA region that have experienced democracy for a long period of time. There are 46 countries in total in SSA according to the UNDP. The sample (a non-probability convenience one of 35 Francophones, Anglophones, and Portuguese language speaking countries) was made up of all of the countries in SSA that have had a minimum of 25 years of democratic experience. As for the sampling frame, it constitutes the Eastern, Western, Central, and Southern African countries, and is representative of the four sub-regions of the main Sub-Sahara region (see Table 1 below).\n\nSecondary data about four dependent variables (human development index, infant mortality, life expectancy, and basic drinking water), five independent variables of interest (multiparty democracy 1 and 2, political rights, civil liberties, and social cohesion), and four control variables (GDP per capita, institutional quality, population growth, and political stability), were employed in the present study to test the research hypotheses. These data, which consisted of socio-economic development and human capital indicators of 35 SSA countries for the years 1995-2019 (see Diori & NaRanong, 2022), were compiled from diverse sources such as the 2020 United Nations Development report (UNDP, 2020), for data pertaining to human development; the 2021 World Bank World Development Indicators (World Bank, World Development Indicators, 2021), for data on infant mortality, life expectancy, and basic drinking water; the Freedom House annual survey of civil liberties and political rights (Freedom House, 2021); and Marshall and Gurr (2018) for data on democracy. The data for social cohesion was sourced from the State Fragility Index and Matrix (Marshall & Elzinga-Marshall, 2020) while data on governance and political stability was sourced from Kaufmann and Kraay (2020). Other data regarding population growth was sourced from the United Nations 2019 World Population Prospects (UNDESA, 2020); the data for economic growth was sourced from the 2020 World Bank national account databank (World Bank National Accounts Data, 2020); while data for per capita GDP was sourced from the Maddison Project Database (Bolt & van Zanden, 2020). This approach is consistent with the literature, ensuring that findings were of the same standard as previous empirical studies on multiparty democracy and human development. As far as the time span of the collected data is concerned, one may note that the year 1995 represents three to four years after a full democracy was established in most SSA countries that were sampled in this study. The year 2019 represents the latest year data were available for most or all countries in the sample, and all variables. The full dataset, the data tables, and the link to the data sources can be found under Underlying data (Diori & NaRanong, 2022).\n\nPanel data was used in this investigation to address the research purpose, consisting in finding out whether multiparty democracy and social cohesion have some effects on human development. Three different techniques were utilized to ensure that the data met all of the assumptions of the regression analysis. First, measures of central tendency were used—mean, standard deviation, minimum, and maximum—in order to probe the normality and linearity of the dataset (Table 2). Secondly, correlation matrix (Table 3) was used to check whether the variables were strongly correlated. Thirdly, Breush-Pagan/Cook-Weisberg and Wooldridge tests (Table 4) were carried out to look at issues concerning heteroscedasticity and serial correlation.\n\nIn order to control for the specific characteristics, two estimation techniques were used: panel fixed-effects (FE), and an instrumental variable in the system generalized methods of moments (system-GMM) estimation. The aforementioned panel data estimations were most appropriate for this study for several reasons. First, because they helped to explain how multiparty democracy and the social cohesion variables within each Sub-Saharan country affect human development over time, and by so doing, they allow for the heterogeneity and individuality of each country with respect to the relationship between the dependent and independent variables. Second, with the combination of cross-section and time series observations, these panel data estimations allowed for additional information, greater variability, less collinearity, greater degrees of freedom, and thus more efficiency. Third, they permitted the detection and measurement of the effects of unobserved country specific effects and therefore reduced the bias in the estimated coefficients.\n\nIt is worth noting however that, while the fixed-effect technique was used to control for unobserved country-specific heterogeneities such as structural characteristics, historical differences and time-invariant shocks, the system GMM was used to deal with endogeneity issues and to check for the robustness of the findings. System GMM was chosen and utilized in this study because of its use of internal instruments as parts of the independent variables (Arellano & Bond, 1991).\n\nFinally, note also that, data about some of the variables used in the analysis were incomplete for some countries and time periods, making this panel data unbalanced. The problem was addressed using the Stata 15 software which handled the missing data issue automatically.\n\nThe specification of the statistical models within the study was based on the review of the associated theories. Four different measures of multiparty democracy were included in the basic models, with two in the dynamic models. Of the four measures of democracy, three were sourced from the most popular institution, Freedom House, while one was drawn from Polity 5. As previously indicated, this approach remains consistent with the existing literature, as several scholars have utilized at least two of the same measures for the variable of democracy (see Gerring et al., 2012, 2015). Hence, multiparty democracy 1 (the Freedom House measure of democracy) is termed Democ1, while multiparty democracy 2 (the Polity 5 measure of democracy) has been termed Democ2. Democ1 was reduced to its component levels with two more measures and variables having been added to the analysis - political rights (PR) and civil liberties (CL). The choice of the fifth independent variable, social cohesion (SC), was also consistent with the literature (see Amate-Fortes et al., 2017; Easterly et al., 2006; OECD, 2018; Rotberg, 2010; Seyoum, 2020). The dependent variables in this study were the human development index (HDI), the variable of interest, and three of its proxies: infant mortality (IMR), life expectancy (LEXP), and basic drinking water (BASW). With the exception of the fourth variable, basic drinking water (BASW), which was created by the authors of this study, infant mortality, life expectancy, and human development index are considered prominent in the context of human development research (see Altman & Castiglioni, 2009; Besley & Kudamatsu, 2006; Blaydes & Kayser, 2011; Deacon, 2009; Hanson, 2015; Gerring et al., 2012, 2015; Kudamatsu, 2012; McGuire, 2006, 2013; Miller, 2015; Ross, 2006; Shandra et al., 2004). The interaction between multiparty democracy 1 and social cohesion was termed Democ1SC, while Democ2SC referred to the interaction between multiparty democracy 2 and social cohesion. Finally, the decision was made to control for institutional quality (IQ), per capita GDP (GDPPC), population growth (PGR), and political stability (PS) to curb their influence on the dependent variable, which may have caused a bias in the statistical results.\n\nThe basic models are specified as follows:\n\nFor infant mortality (IMR,it), life expectancy (LXP,it), and basic drinking water (BASW,it), which represent the other dependent variables, the same equation was used along with the independent variables.\n\nThe dynamic panel models are specified as follows:\n\nFor infant mortality (IMR,it), life expectancy (LXP,it), and basic drinking water (BASW,it), which represent the other dependent variables, the same equation and independent variables were used.\n\n− HDI,it represents the human development index for entity i at time t, while hdi,it – 1 is its one-year lag variable.\n\n− Democ stands for multiparty democracy, with β1 as its coefficient.\n\n− SC stands for Social Cohesion and β2 is its coefficient.\n\n− DemocSC stands for the interaction between democracy and social cohesion, with β3 as its coefficient.\n\n− IQ stands for institutional quality, with β4 as its coefficient.\n\n− GDPPC stands for per capita GDP, with β5 as its coefficient.\n\n− PGR stands for population growth, with β6 as its coefficient.\n\n− PS stands for political stability, with β7 as its coefficient.\n\n− αi (i=1 … .n) is the unknown intercept for each country (n entity-specific intercepts).\n\n− uit is the term of error.\n\n\nResults\n\nThe empirical findings of this study are organized and presented in accordance with the following research objectives: (i) to determine the effect of multiparty democracy on human development; (ii) to determine the effect of social cohesion on human development; and (iii) to determine the effect of the interaction between multiparty democracy and social cohesion on human development. The results of the diagnostic checks pertaining to the descriptive statistics, the correlation matrix, and the Breush-Pagan/Cook-Weisberg and Wooldridge tests of heteroscedasticity and serial correlation are documented in the following subsections.\n\nThe descriptive statistics in Table 2 show the potential presence of outliers for variables such as infant mortality: mean (65.389) and standard deviation (27.56); life expectancy: mean (56.217) and dispersion of (6.934); and basic drinking water: mean (63.065) and low dispersion of (15.223). The data indicated that certain countries perform better than others with regard to particular variables. However, owing to the large data observation (822), the outliers did not significantly violate the normality assumption.\n\nTable 3 illustrates that the correlation between multiparty democracy 1 and political rights on one side, and the correlation between multiparty democracy 1 and civil liberties on the other side, are very high, with respective values of 0.97 and 0.96. To resolve this issue of multicollinearity, the concerned variables were separated in the estimation models.\n\nIn Table 4, the results of the analyses revealed the absence of heteroscedasticity. As for the Wooldridge test, the results indicated the presence of serial correlation, which was rectified over the course of the analysis.\n\nBreush-Pagan/Cook-Weisberg Test for Heteroskedasticity\n\nFour varying measures were used to test the hypothesis across the fixed-effects estimation: multiparty democracy 1 or Democ1, multiparty democracy 2 or Democ2, political rights, and civil liberties. The dependent variables were the human development index, the variable of interest, and three of its proxies: infant mortality, life expectancy, and basic drinking water. Other variables were added to the model as control variables in accordance with the existing literature.\n\nFrom models (1) to (3) in Table 5, results showed that both multiparty democracy 1 and 2 (Democ1 and Democ2) appeared related to human development. While multiparty democracy 1 was shown to exert a negative impact on human development at 5%, multiparty democracy 2 appeared to be positively related to human development at a 1% error level. The data indicate that a 5% change in the value of multiparty democracy1 is likely to be associated with -0.0147 points worth of decrease in the human development index, while a single unit change in the value of multiparty democracy 2 will be associated with 0.0110 points worth of increase in the human development index. The immediate implications of these findings corroborated Gerring et al.’s (2012) study, wherein the contemporary level of a country’s democracy was found to have only a weak association with enhanced human development; however, its historical experience with democracy has a strong influence on human development. Given the periodicity of the data that began in 1995, i.e., only 3 to 4 years after the democratization of most countries in SSA, in addition to the fact that multiparty democracy is relatively new in Africa, one may expect it to have little or no effect on the well-being of the population in SSA.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nWith regard to the control variables included in the models, the findings indicated that GDP per capita was the only variable associated with human development. This variable was shown to have a positive impact on human development in models (2) and (3). Bear in mind that the focus of the argumentation of the pro-democracy theories remains on the consolidation of per capita GDP through redistribution. For many scholars, including Aristotle, Madison, and some present-day political economists, it is undeniable that democracy serves as a mechanism for redistribution, and consequently, for human development (Meltzer & Richard, 1981). Hence, these pro-democracy scholars would opine that the advent of democracy would result in higher government social spending, which, in turn, would improve the welfare of the poor and influence human development. Today, this point is contradicted by a mass of existing research findings (see Gerring, et al., 2012; McGuire, 2006; Ross, 2006; Shandra et al., 2004).\n\nFrom models (1) to (3) in Table 6 below, the findings showed that multiparty democracy 2 is negatively associated with infant mortality at the 0.01 level. The forecast of the results suggested that for a unit of change in the value of multiparty democracy 2, a -3.622-point decrease is likely to occur in the struggle toward improvement in infant mortality. As explained in the previous table (Table 4.4), these findings are in line with the current literature. Owing to in-depth exploration and a series of regression checks with the infant mortality rate as the core measure of human development alongside two hypotheses (the first, replicating the traditional causal model that links IMR to a country’s achievement or level of democracy in the previous year; and the second, measuring democracy with a “stock” indicator that captures the regime history of a country from 1900 to the observation year), Gerring et al. (2012) finds that multiparty democracy has a long-term effect on human development characterized by a distal rather than proximal causal relationship. According to these authors, multiparty democracy ameliorates human development only in case it is considered a historical or “stock” phenomenon. This implies that if a democratic system of governance is upheld over a longer period of time, its net effect will be resolute for the welfare of its citizens (Gerring et al., 2012). However, this is not the case with SSA Africa, which has a relatively new democracy, which is a form of government that has not been upheld for long in most countries.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nThe findings further showed that GDP per capita may dampen progress toward the amelioration of the infant mortality rate. The DGPPC exerts a negative impact on infant mortality at the 0.05 level, which may be explained by the lack of sufficient healthcare systems and services throughout SSA. Moreover, many countries in SSA are imbued with unrelenting discrepancies in terms of wealth and rampant poverty. To improve the infant mortality rate in SSA, rather than solely enhancing personal income, governments must implement better public policies that could lead to improvements in environmental conditions and healthcare.\n\nFrom models (1) to (3) in Table 7, the results showed that multiparty democracy 2 is the only variable that was significant out of all independent variables. Democ2 was significant at the 0.01 level, which implies that a unit change in its value is likely to be associated with a unit increase in life expectancy. This result reinforces the prodemocracy theories, which emphasize that popular participation in government empowers ordinary citizens and, consequently, leads governments to become more accountable for their interests (Gerring et al., 2012, 2015; Ross, 2006). The proponents of these theories strongly believe that democracy would lead to higher government social spending, which, in turn, would improve the welfare of the poor and lead to the amelioration in social welfare as measured by mortality, literacy, and other human development outcomes (Gerring et al., 2012, 2015). However, given the limited resources in most SSA countries and the lack of quality institutions, unrelenting discrepancies are observed in terms of wealth and rampant poverty, which may impact life expectancy at birth.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nFrom models (1) to (3) in Table 8, the results demonstrated that none of the four measures of multiparty democracy were related to the measures of human development, which contrasts the prodemocracy theories. However, they corroborate the findings of recent works on the relationship between democracy and human development. Numerous studies with large samples for quantitative and qualitative inquiries have been conducted to corroborate the absence of tangible relations between regime type and diverse aspects or measures of human development (Gerring et al., 2012, 2015; McGuire, 2006; Ross, 2006; Shandra et al., 2004). These studies have fiercely challenged and debunked the commonly held view that democracy influences the well-being of individuals. Beyond the context of the OECD countries, no substantiation of tangible relationships between public spending and human development has been observed (Filmer & Pritchett, 1999; McGuire, 2006).\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nRegarding the control variables that were included in the models, GDP per capita appeared to have a positive effect on basic drinking water, while institutional quality demonstrated a negative effect on the same. The low magnitude of the relationship between per capita GDP and basic drinking water is atypical in the Sub-Saharan African region, where a lack of quality institutions hinders public policy implementations and the potential for an impact of economic growth on human development.\n\nOverall, the findings showed that the four measures of multiparty democracy had mixed effects on the measures of human development. Multiparty democracy 1 appeared to have a negative relation with the human development index, also carrying an insignificant impact on infant mortality, life expectancy, and basic drinking water. Multiparty democracy 2 was shown to entertain two positive relations, one with the human development index and another with life expectancy. Furthermore, negative and insignificant associations were observed with infant mortality and basic drinking water, respectively. Nevertheless, these mixed findings lend support to part of research hypothesis 1 and the recent literature (Gerring et al., 2012, 2015; Ross, 2006), indicating certain long-term positive effects of multiparty democracy on human development. According to the recent literature, multiparty democracy has little to no effect on human development, as characterized in these results by a negative and a low magnitude positive relationship between the two variables (Gerring et al., 2012, 2015; Ross, 2006).\n\nIn order to test this hypothesis across the estimations, one measure of social cohesion (SC) was used, with four varying measures of human development as the dependent variables: the human development index, infant mortality, life expectancy, and basic drinking water. Other variables were added to the model as control variables in accordance with the existing literature: per capita GDP, institutional quality, population growth, and political stability.\n\nFrom models (1) to (4) in Table 9 below, the results showed that social cohesion has a positive effect on infant mortality at the 0.01 level, while it corresponds with a negative impact on the remaining three dependent variables: human development index, life expectancy, and basic drinking water at the same level (0.01). To forecast these results, a unit change in the value of social cohesion will be associated with a 4.164-point increase in infant mortality rate amelioration, and a -0.0132, -1.210, and -1.554 decrease in the human development index, life expectance, and basic drinking water services, respectively. This is consistent with the current literature, which makes frequent usage of infant mortality as a measure of human development, insisting on the presence of a long-term relationship between the two variables.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nReferring to the control variables that were included in the models (per capita GDP, institutional quality, political stability, and population growth rate), only two appeared to have impacts on the dependent variables. Hence, per capita GDP seemed to dampen progress in infant mortality improvement at the 0.01 level while it showed a positive impact on basic drinking water at the same error level. If we forecast the results of the effect of GDPPC on infant mortality, a 1% change will appear in the value of per capita GDP, which will be associated with a decrease of -0.000951 points toward improvement in the infant mortality rate. Furthermore, a change of 10% in the value of per capita GDP will be associated with a 5.98e-06-points increase in the human development; a 1% change in the same variable is likely to be associated with a 0.000526-point increase in the addition of clean water. These results demonstrate that GDPPC has no positive effect on the accomplishment of a good infant mortality rate in the context of SSA, rather, it shows little effect on the improvement of the human development index and basic drinking water. One reason to believe in this conclusion is that, according to the raw data, the country in SSA with the highest GDPPC, Equatorial Guinea (with $47,562), is not among the best performers as far as infant mortality rate is concerned. The results further showed that political stability appeared to dampen two measures of human development (HDI and BASW) while it showed no effect on infant mortality and life expectation.\n\nOverall, the results have shown that social cohesion was related to human development via infant mortality, as it appeared to have a positive impact at the 0.01 error level. This supports the hypothesis that social cohesion exerts a positive influence on human development. Yet, social cohesion also shows a negative but significant association with other measures of human development (HDI, LEXP, BASW), leading to some mixed findings and support for the research hypothesis, current literature, and the supporting theory, which indicated some long-term positive effects of social cohesion on human development.\n\nTo test this hypothesis across the estimation, SC, which represented a measure of social cohesion was used along with two varying measures of multiparty democracy: multiparty democracy 1 and multiparty democracy 2. However, due to the high correlation between the two measures of multiparty democracy, they were used in separate models. The dependent variables were human development, infant mortality, life expectancy, and basic drinking water. Other variables were added to the model as control variables in accordance with the existing literature.\n\nThe results from models (1) to (4) in Table 10 showed that multiparty democracy 1 had no effect whatsoever on any measure of human development. In contrast, social cohesion had a significant positive relation with infant mortality, although it showed a negative impact on the human development index, life expectancy, and basic drinking water at the 0.01 and 0.1 levels, respectively. These results may be forecasted by hinting that a unit change in the value of social cohesion is associated with a 4.297-point increase in progress toward improvement in infant mortality. Moreover, a unit change in the value of social cohesion is likely to be associated with a -0.0198, -1.567, and -1.671-point decrease in progress toward ameliorating the human development index, life expectancy, and basic drinking water, respectively, in the Sub-Saharan African region. Thus, social cohesion, in this study, improves only the infant mortality rate. Surprisingly, however, the interactive effect of multiparty democracy and social cohesion showed a positive association with the human development index and basic drinking water. It is also worth noting that multiparty democracy 1 failed to show any positive relationship with the human development index or basic drinking water on an individual level. However, when multiparty democracy 1 interacted with social cohesion, the sign of the coefficient of these variables changed, showing a positive association with the human development index and basic drinking water. These findings suggested that despite the level of significance, the interaction between multiparty democracy 1 and social cohesion has the potential to improve human development conditions within a country. The interaction term between multiparty democracy and social cohesion was significant at the 1% level.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nRegarding the control variables included in the models (per capita GDP, institutional quality, political stability, and population growth rate), GDP per capita appeared to have a positive effect on the human development index and basic drinking water, while it demonstrated a negative impact on infant mortality. Meanwhile, political stability showed a negative effect on the human development index and basic drinking water in models (1) and (4). Lack of political stability, when coupled with a lack of quality institutions, uncontrolled population growth, and inadequate income distribution could only hinder progress toward sustained human development. A closer look at the raw data indicated that the best-performing countries in terms of human development in the Sub-Saharan African region had four important factors in common - a controlled population growth rate, better institutions, better per capita share among their population, and above all, a stable political environment.\n\nFrom models (1) to (4) in Table 11, the results demonstrate that multiparty democracy 2 (Democ2) is related to only one measure of human development - basic drinking water. On the contrary, social cohesion was positively related to infant mortality, albeit posing a negative impact on the human development index, life expectancy, and basic drinking water at a 0.01 error level. These results are forecasted to hint that a unit change in the value of social cohesion is associated with a 4.566-point increase in the amelioration of infant mortality rate. Furthermore, a unit change in the value of social cohesion is likely to be associated with a -0.0117, -1.015, and -2.115-point decrease in progress toward amelioration of the human development index, life expectancy, and basic drinking water, respectively, in the Sub-Saharan African region. Thus, social cohesion only improves the infant mortality rate. Note that multiparty democracy 2 had no significant positive relation with any measure of human development. Yet, when it interacted with social cohesion, the effects of the interaction term have become significant with both infant mortality (negatively) and basic drinking water (positively). These findings suggested that regardless of the level of significance, the interaction of multiparty democracy 2 with social cohesion may potentially improve human development conditions within a country. In other words, social cohesion is at its best when associated with multiparty democracy. The interaction term between multiparty democracy 2 and social cohesion was negative and significant at the 0.05 level in model 2 despite social cohesion being positively associated with infant mortality, and positively significant at the 0.1 level with basic drinking water. These results suggested a distal, rather than a proximal, effect of the interaction of both variables in the context of human development.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nOverall, the results have shown that the two measures of interaction between multiparty democracy and social cohesion (Democ1SC and Democ2SC) had positive effects on two measures of human development (HDI and BASW), with a negative impact on infant mortality and no significant association with life expectancy. Further, with regard to the magnitude of the relationship, one could only conclude that the interaction between multiparty democracy and social cohesion has a positive long-term effect on human development. These mixed findings lend support to the third research hypothesis (H3), which assumes that the interaction between multiparty democracy and social cohesion has a positive effect on human development.\n\nNote that fixed effects estimations may have certain disadvantages that derive from the presence of endogeneity and omitted variable prejudice, which has been addressed in this study using an instrumental variable (IV) approach in the system generalized methods of moments.\n\nThe results from the system GMM estimation in Table 12, specifically columns (1) to (5), indicated that the lag of the human development index was statistically significant (0.997, 1.001, 0.992, 0.996, 0.999) at the 1% level. This further implies that human development is strongly persistent in SSA. Considering the choice of one lag length, the insignificant specification test results of the AR (2) (0.790, 0.835, 0.945, 0.882, and 0.528) revealed that the system GMM model did not suffer from second-order serial correlation and that the null hypothesis could be accepted. In addition, the results of the Hansen test (0.167, 0.144, 0.266, 0.185, 0.230) have shown that the instruments used were not over-identified, suggesting that they were valid or not correlated with the error term. The results of the system GMM were, to a lesser extent, consistent with the fixed effects estimation albeit with certain minor differences. The coefficients of many of the variables were not significant compared to the fixed effects. In columns (2, 3, and 5), for instance, social cohesion was shown to have no influence on human development, which is unlike the case of fixed effects estimation, where it exerted a negative impact on three measures of human development (HDI, LEXP, BASW) and a positive impact on the fourth (IMR). Multiparty democracy 2 was also not significant as it was in the fixed effects estimation, just as in the case of its interaction with social cohesion, which was not only insignificant but also illustrated a negative coefficient. In column (3), however, apart from the error level, the statistical direction of multiparty democracy 1 and its interaction with social cohesion did not change, remaining negative and significant for the former and positively significant for the latter at the 1% error level. The positive sign of the interaction between multiparty democracy 1 and social cohesion (Democ1SC) suggested that social cohesion has the potential for dampening the negative effect of multiparty democracy on human development.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nThe results from the system GMM estimation in Table 13 below, specifically columns (1) to (5), indicated that the lag of infant mortality was statistically significant (0.970, 0.970, 0.965, 0.967, 0.981) at the 1% level. This suggests that infant mortality is strongly persistent in SSA. Considering the choice of one lag length, the insignificant specification test results of the AR (2) (0.528, 0.531, 0.450, 0.554, and 0.417) revealed that the system GMM model did not suffer from second-order serial correlation and that the null hypothesis could be accepted. Furthermore, the results of the Hansen test (0.230, 0.219, 0.662, 0.112, and 0.262) showed that the instruments used were not over-identified; hence, they were valid or not correlated with the error term. The results of the system GMM were, to a lesser extent, consistent with the fixed effects estimation, albeit with several differences. The coefficients of many of the variables were significant after controlling for endogeneity issues, unlike in the results of the fixed effects estimation. In column (3), for instance, the coefficient of multiparty democracy 1, which has never shown a positive significance in the fixed effects estimation, has shown a positive value in the GMM estimation, although the statistical direction of its interaction with social cohesion (Democ1SC) is unchanged. In columns (3) and (5), social cohesion was shown to have a positive and a negative impact on infant mortality, unlike in the fixed effects estimation, where it has always been positive. Hence, in column (3), social cohesion has retained its positive effect on infant mortality while the magnitude of the relationship has shrunk from 4.164 at the 1% error level to 1.054 at the 5% level. In column (5), the sign of the coefficient of the variable has become negative at the 10% level. Note that social cohesion has always shown a positive significant relation with infant mortality in the fixed effects estimation. Moreover, in column (5), the sign of the coefficient of multiparty democracy 2 was shown to be negative and significant, similar to its state in the fixed effects estimation. However, its interaction with social cohesion has become positive at the 10% error level, indicating that the negative effect of multiparty democracy 2 on infant mortality has been dampened by its interaction with social cohesion.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nFrom the results of the system GMM estimation method in Table 14, one may note how columns (1) to (5) indicated that the lag of life expectancy was statistically significant (-0.200, -0.114, -0.179, -0.204, -0.182) at the 1% level, suggesting that life expectancy is weakly persistent in SSA. The insignificant specification test results of the AR (2) (0.122, 0.101, 0.012, 0.100, and 0.185) revealed that the system GMM model did not suffer from second-order serial correlation and that the null hypothesis could be accepted. Furthermore, the results of the Hansen test (0.936, 0.936, 0.936, 0.936, 0.937) show that the instruments used were not over-identified; hence, they were valid or not correlated with the error term. The result of the system GMM estimation was, to a lesser extent, consistent with the fixed effects method, albeit with several major differences. The coefficients of many of the variables, which were insignificant in the fixed effects estimation, were found to be significant in the GMM estimation. Hence, in column (1), the sign of the coefficient of multiparty democracy 1 is significant and positive at the 10% level, unlike in the fixed effects estimation, where it appeared to be non-significant and negative. In column (2), the sign of the coefficient of social cohesion remains the same. In column (3), the sign of the coefficient of multiparty democracy 1, which was positive in column 1, was found to be negative and significant at the 1% level, in contrast with the data indicated in the fixed effects estimation results. Further, the interaction between multiparty democracy 1 and social cohesion (Democ1SC), which was insignificant in the fixed effects estimation, has become significant and positive in the GMM estimation (0.314) at the 1% level. In column (5), the coefficient of the social cohesion variable has become positive and significant at the 10% level (0.238), in contrast with the fixed effects estimation results, where it has never been positive. Furthermore, in the same column, the sign of multiparty democracy 2 has remained positive and significant, as in the fixed effects estimation, at the 1% level in the GMM estimation (2.708), whereas its interaction with social cohesion, which was insignificant and negative in the fixed effects estimation, has become significant and negative in the GMM model at the 1% level. This suggests that the combined effects of the two variables had a negative effect on life expectancy.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nThe results of the system GMM estimation method in Table 15, columns (1) to (5) indicated that the lag of basic drinking water was statistically significant (0.993, 0.994, 0.986, 0.997, 0.982) at the 1% level, suggesting that basic drinking water is strongly persistent in SSA. The insignificant specification test results of the AR (2) (0.081, 0.084, 0.097, 0.087, and 0.092) revealed that the system GMM model did not suffer from second-order serial correlation and that the null hypothesis could not be rejected. In addition, the results of the Hansen test (0.771, 0.713, 0.754, 0.634, 0.821) show that the instruments used were not over-identified; hence, they were valid or not correlated with the error terms. The results of the system GMM estimation were, to some extent, totally inconsistent with the fixed effects estimation, with several differences. The coefficients of many of the variables of interest were not significant, relative to the fixed effects. In columns (2, 3, and 5), for instance, social cohesion was shown to have no impact on basic drinking water unlike in the fixed effects estimation where it had a negative but significant effect on all measures of BASW. Moreover, the coefficient of the interaction between multiparty democracy 1 and 2 with social cohesion (Democ1SC and Democ2SC), which were significant and positive in the fixed effects estimation at 1% and 10%, respectively, have become insignificant in the system GMM estimation. Moreover, the coefficients of the multiparty democracy 1 and 2 variables have remained insignificant in the system GMM estimation.\n\n* p<0.01,\n\n p<0.05,\n\n* p<0.1.\n\nOverall, after controlling for endogeneity issues, the results of the system GMM appeared to confirm parts of the research hypotheses, which imply a long-term relationship between multiparty democracy and human development, despite the hybrid character of the findings. Two measures of multiparty democracy, namely Democ1 and democ2, are shown to be positively correlated with two of the four measures of human development (IMR, and LEXP), with a relatively low magnitude association. This suggests a distal, rather than proximal, relationship. Additionally, social cohesion was positively correlated with two measures of human development (IMR and LEXP), much like its interaction with multiparty democracy 1 and 2 (Democ1SC and Democ2SC), which were also positively correlated with the human development index and infant mortality rate, respectively. In sum, these positive significant relationships contrasted with the negative significant and non-significant relations that these variables demonstrated with other measures of human development. Nonetheless, these mixed findings do lend support to the recent literature and hypothesis, which suggests that multiparty democracy has little to no effect on human development, or implies a distal relationship with human development (Gerring et al., 2012; 2015; Ross, 2006).\n\n\nLimitations and implications for future research\n\nThis study was beset by several challenges that affected its timely completion. The first challenge was dealing with the data collection. In longitudinal research designs, it is strongly suggested to use a large sample in order to achieve robust findings. In the present study, that was a challenging task since in Sub-Saharan Africa data are not always readily available. This challenge constrained the scope of the study as well as its smooth completion. Nonetheless, with an inclusive sample of 35 countries out of a population of 46, more than 800 observations, and the use of advanced statistical techniques such as the system generalized method of moments estimation technique. the study yielded reliable results. The complete details about the sample of the study, the excluded countries, and the statistical results can be found under Underlying data (Diori & NaRanong, 2022). The second challenge is related to funding and time. Panel data research studies require the use of data from various sources. Yet, in the context of this study, some data were not free since they come with a fee. That situation caused a great financial burden and delays as a result.\n\nBased on the above-mentioned challenges, several pathways were uncovered for future researchers in the field of development policy and study. First of all, prospective studies can improve on the existing scholarship by conducting case studies that reflect country-specific characteristics. Since the present study was based on cross-sectional time series analysis, it is possible that critical country-level specificities that are crucial for human development may not be unveiled or addressed even though statistical techniques were used to control for such factors. Hence, conducting further studies which will provide more insights at the individual country level, will make a humble contribution to the strand of literature. Further, since factors such as regime type are decisions that countries would have to take, such individual country-level inquiries will be of great contribution to the existing literature. It is therefore suggested that for prospective studies to be able to effectively investigate specific country issues, time series analysis such as autoregressive distributive lag and cointegration methods should be employed. Future studies could also replicate the present study by using different indices as a measure of multiparty democracy, social cohesion, and human development at different time spans and geographical settings. This is so important as the use of different data and measures can offer different results.\n\nStudies on the relationship between democracy and human development are reemerging. It is thus important for subsequent studies to focus on these areas of research. Such studies should look into the interaction between multiparty democracy and social cohesion in order to find out whether a sufficiently high level of social cohesion could damp the negative influence of multiparty democracy on other human development outcomes, such as urbanization, gender inequality, or institutional quality. Further studies in this regard would contribute to the debate on multiparty democracy and human development.\n\nMoreover, the present study examined the effect of democracy and social cohesion on human development from political, social, and economic perspectives. However, it should be noted that the environment forms an important part of the current wave of human development since challenges such as global warming and climate change are transboundary and threaten human survival across the globe. As a consequence, prospective studies should incorporate the environmental dimension of human development in their models. Another area within the democracy and human development literature that prospective studies ought to look at, is to employ a qualitative or mixed-method approach. One limitation of this study was the inability to collect qualitative data where interviews would have been conducted with key government officials and with the international or regional organizations bodies such as the United Nations or the African Union. Interviews with these officials would have enhanced the understanding of how countries are performing with respect to efforts aimed at achieving sustained human development. Therefore, it is suggested that further studies employ either qualitative methods or a mixed-method approach to investigate these issues.\n\n\nConclusions and recommendations\n\nThis study examined the effect of multiparty democracy and social cohesion on human development. Overall, the following results were established after controlling for confounding factors. First, multiparty democracy, which was measured using political rights, civil liberties, and democracy indices from the Freedom House and Polity 5, showed a positive but distal relationship with human development in the Sub-Saharan African region. Second, social cohesion also indicated a positive but distal relationship with human development. Third, the interaction between multiparty democracy and social cohesion exerts a positive long-term effect on human development in Sub-Saharan Africa. Based on the implications of these findings, a number of policy recommendations are discussed for achieving sustained human development in the Sub-Saharan African region.\n\nFrom a multiparty democracy perspective, the fact that most countries in the Sub-Saharan African region are still poor and unable to guarantee economic prosperity and sustained human development for themselves despite their democratic credentials does not imply that multiparty democracy, as a regime type, is incapable of alleviating poverty or ensuring higher quality of life. Yet, to sustain human well-being in the Sub-Saharan African region, power must rest completely in the hands of its people. It is only when the masses can participate in the process of governance that accountability can be strengthened, resources are equitably distributed, and the inequality gap between the rich and the poor be reduced. Hence, countries in the Sub-Saharan region must ensure broader political rights and civil liberties for their people. The findings of the study suggested that civil liberties and political rights have a more negative influence on human development in this region, primarily due to the nature of African democracy, which is elitist, neo-patrimonial, and ethnic. Most contributions in the literature on African politics hold neopatrimonialism and ethnicity responsible for the continent’s disappointing human development record and the large discrepancies between the political enticements of the governments and demands for steady development. To improve the quality of SSA democracy and ensure a better impact on human development, important institutional reforms should be considered, in addition to initiatives to address the ethnic and neo-patrimonial nature of the democracy. For instance, to deal with the ethnic character of democracy, other types of political systems such as the one-party system or party-less democracy may be considered. Both these political systems have the potential to unite individuals over ideologies or leaders, overcoming any divides that are ethnic or linguistic. Moreover, real power must be granted to individuals so that they may elect leaders of their choice based on criteria purposefully set by themselves.\n\nTo address the neo-patrimonial character of SSA democracy, the current weak political party structures and national institutions should be positioned above party and state leaders. Elections should be conducted locally, with each region sending its representative delegates to the federal government. The task of the central or federal government should be to receive, coordinate, and execute the different decisions forwarded by the lower echelon entities or decision-making bodies. Party structures are crucial in politics as they help to determine the status, role, and liability of all members. Beyond party structure, the same adjustment may be carried out in terms of three basic state institutions, which are the state itself, the rule of law, and accountability (Fukuyama, 2011; Matlosa, Ndlovu, Kasenally, & Lodge, 2017). Though these institutions are each distinct, they cannot guarantee that the state is impartial, that the rule of law is vigorous and equitable, and that accountability is exercised in all its forms (Fukuyama, 2011; Matlosa et al., 2017).\n\nFrom a social cohesion standpoint, some urgent policy recommendations are made with the hope to achieve sustained human development. For countries in the Sub-Saharan African region to make progress in terms of human development, leaders must adopt significant steps toward good governance, which includes the consolidation of peace, stability, and security. Political commitment should aim to improve institutional quality, adequate and equal per capita share, and political stability, which are indicators that have consistently revealed a more negative influence on human development in SSA. As for institutional quality, governments in Sub-Saharan Africa should expend more resources to ensure the quality delivery of public services by improving civil service without political interference and manipulation, ensuring that public bureaucracy is susceptible to formulating and implementing sound policies that intend to reduce poverty and increase opportunities for human development.\n\nWhile the donor community and the Bretton Wood Institutions constantly urge developing countries to rely on neoliberal market policies for efficient resource allocation, this study firmly recommends a state-led approach for promoting sustainable economic growth and human development in the Sub-Saharan African region. Yet, state-led approaches should not be understood as those that are repressive or restrictive of press freedom or peoples’ participation in political processes. Rather, it is the discretion of the government to exert influence over policy space rather than being controlled and dictated by external players such as the Bretton Woods institutions. Under the neoliberal market force, most countries in Africa have lost control over their policy space. As a result, they seem to lack the capacity to initiate home-grown policies that internalize domestic norms and values, instead of reflecting a western style of governance. The countries in Sub-Saharan Africa must strengthen their governance structure by determining mechanisms that work best for Africa and the African people rather than blindly emulating the Western world. In brief, while policymaking may have a standard procedure, practices must be exercised based on African context, norms, and values.\n\nFinally, Sub-Saharan African countries must undertake urgent measures to regulate the speedy rate at which their population continues to grow, which, according to this study, exerts a negative effect on human development, especially given the lack of commensurate economic growth to accommodate the surge. The 2019 UN Population Projections indicated that by 2100, the total population in Africa is expected to reach four billion (UN DESA Population Division, 2020). Consequently, it is more difficult to reduce poverty and inequality, expand health and education facilities, and combat hunger and malnutrition. Ultimately, policies that seek to control population growth should be pursued vigorously.\n\n\nData availability\n\nDataverse: Data on the effects of multiparty democracy and social cohesion on human development in Sub-Saharan Africa, https://doi.org/10.7910/DVN/GPTLSJ (Diori & NaRanong, 2022).\n\nThis project contains the following underlying data:\n\n- Dataset.xlsx [the raw data used in the statistical analyses]\n\n- Data Tables.docx [illustrative tables of the measures of the different variables used in the study on the effects of multiparty democracy and social cohesion on human development-based on arithmetic calculations of the mean of five consecutive years in dataset]\n\n- Links to the data sources.docx [these are the links to the sources of all of the data collected for the analyses]\n\n- Tables-Statistical results.docx [these are the findings of the statistical tests: fixed-effects and GMM estimations, as well as the descriptive statistics, correlation matrix, and the Breush-Pagan/Cook-Weisberg and Wooldridge tests for Heteroskedasticity and serial correlation]\n\n- Identification and measurement of the variables used in the study\n\n- List of countries included in the sample and the inclusion-exclusion criteria.docx\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).\n\n\nAuthor contributions\n\n\n\n1. Conceptualization, Investigation, Data curation, Software, Writing-original draft, Methodology\n\n2. Conceptualization, Methodology, Supervision, Review and editing, Formal analysis, Validation", "appendix": "References\n\nAcemoglu D, Naidu S, Restrepo P, et al.: Democracy does cause growth. J. Polit. Econ. 2019; 127(1): 47–100. Publisher Full Text\n\nAlence R: Political institutions and developmental governance in sub-Saharan Africa. J. Mod. Afr. Stud. 2004; 42(2): 163–187. Publisher Full Text\n\nAltman D, Castiglioni R: Democratic quality and human development in Latin America: 1972–2001. Canadian Journal of Political Science/Revue canadienne de science politique. 2009; 42(2): 297–319. Publisher Full Text\n\nAmate-Fortes I, Guarnido-Rueda A, Molina-Morales A: Economic and social determinants of human development: A new perspective. Soc. Indic. Res. 2017; 133(2): 561–577. Publisher Full Text\n\nArellano M, Bond S: Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 1991; 58(2): 277–297. Publisher Full Text\n\nAvelino G, Brown DS, Hunter W: The effects of capital mobility, trade openness, and democracy on social spending in Latin America, 1980–1999. Am. J. Polit. Sci. 2005; 49(3): 625–641. Publisher Full Text\n\nBesley T, Kudamatsu M: Health and democracy. American economic review.2006; 96(2): 313–318.\n\nBlaydes L, Kayser MA: Counting calories: democracy and distribution in the developing world. Int. Stud. Q. 2011; 55(4): 887–908. Publisher Full Text\n\nBolt J, van Zanden JL : Maddison style estimates of the evolution of the world economy. A new 2020 update.2020.\n\nBrown DS, Hunter W: Democracy and human capital formation: education spending in Latin America, 1980 to 1997. Comp. Pol. Stud. 2004; 37(7): 842–864. Publisher Full Text\n\nBrown DS, Mobarak AM: The transforming power of democracy: regime type and the distribution of electricity. Am. Polit. Sci. Rev. 2009; 103(2): 193–213. Publisher Full Text\n\nChabal P: The quest for good government and development in Africa: is NEPAD the answer? Int. Aff. 2002; 78(3): 447–462. Publisher Full Text\n\nDeacon RT: Public good provision under dictatorship and democracy. Public Choice. 2009; 139(1): 241–262. Publisher Full Text\n\nDiori HI, NaRanong A: Data on the effects of multiparty democracy and social cohesion on human development in Sub-Saharan Africa.2022. Harvard Dataverse, [Dataset], V2. Publisher Full Text\n\nDurkheim É: Le suicide: étude de sociologie. Alcan;1897.\n\nEasterly W, Ritzen J, Woolcock M: SOCIAL COHESION, INSTITUTIONS, AND GROWTH. Econ. Politics. 2006; 18(2): 103–120. Publisher Full Text\n\nEterovic DS, Sweet CM: Democracy and Education in twentieth-century Latin America. Econ. Politics. 2014; 26(2): 237–262. Publisher Full Text\n\nFilmer D, Pritchett L: The impact of public spending on health: does money matter?. Soc. Sci. Med. 1999; 49(10): 1309–1323. PubMed Abstract \| Publisher Full Text\n\nFreedom House: Freedom in the World: The Annual Survey of Political Rights and Civil Liberties.2021; 2021.\n\nFukuyama F: The origins of political order: From prehuman times to the French Revolution. Farrar, Straus and Giroux;2011.\n\nGerring J, Knutsen CH, Skaaning S-E, et al.: Electoral democracy and human development. V-Dem Working Paper. 2015; 9.\n\nGerring J, Thacker SC, Alfaro R: Democracy and human development. J. Polit. 2012; 74(1): 1–17. Publisher Full Text\n\nGouveia M, Masia NA: Does the median voter model explain the size of government?: Evidence from the states. Public Choice. 1998; 97(1): 159–177. Publisher Full Text\n\nHaggard S, Kaufman RR: Development, Democracy, and Welfare States: Latin America, East Asia, and Eastern Europe. Princeton University Press;2008.\n\nHanson JK: Democracy and state capacity: complements or substitutes? Stud. Comp. Int. Dev. 2015; 50(3): 304–330. Publisher Full Text\n\nKaufman RR, Segura-Ubiergo A: Globalization, domestic politics, and social spending in Latin America: a time-series cross-section analysis, 1973–97. World Polit. 2001; 53(4): 553–587. Publisher Full Text\n\nKaufmann D, Kraay A: Worldwide Governance Indicators. The World Bank;2020.\n\nKristov L, Lindert P, McClelland R: Pressure groups and redistribution. J. Public Econ. 1992; 48(2): 135–163. Publisher Full Text\n\nKudamatsu M: Has democratization reduced infant mortality in sub-Saharan Africa? Evidence from micro data. J. Eur. Econ. Assoc. 2012; 10(6): 1294–1317. Publisher Full Text\n\nLindert PH: The rise of social spending, 1880-1930. Explor. Econ. Hist. 1994; 31(1): 1–37. Publisher Full Text\n\nMarshall MG, Elzinga-Marshall G; Global Report 2017: Conflict, Governance and State Fragility.2020.\n\nMarshall MG, Gurr T, Jaggers K: Political Regime Characteristics and Transitions, 1800–2018: Dataset Users’ Manual. POLITY™ IV PROJECT. 2018.\n\nMatlosa K, Ndlovu S, Kasenally R, et al.: Democratic development in Africa. EISA;2017.\n\nMcGuire JW: Basic health care provision and under-5 mortality: a cross-national study of developing countries. World Dev. 2006; 34(3): 405–425. Publisher Full Text\n\nMcGuire JW: Political regime and social performance. Contemp. Polit. 2013; 19(1): 55–75.\n\nMeltzer AH, Richard SF: A rational theory of the size of government. J. Polit. Econ. 1981; 89(5): 914–927. Publisher Full Text\n\nMiller MK: Electoral authoritarianism and human development. Comp. Pol. Stud. 2015; 48(12): 1526–1562. Publisher Full Text\n\nOECD: States of Fragility 2018: Highlights. OECD Paris;2018.\n\nRoss M: Does democracy reduce infant mortality? Am. J. Polit. Sci. 2006; 50(4): 860–874. Publisher Full Text\n\nRotberg RI: When states fail: Causes and consequences. Princeton University Press;2010.\n\nSeers D:The Meaning of Development, with a Postscript Seers.Nafziger EW; DC O H, editors. Development Theory: Four Critical Studies. London:Frank Cass;1979.\n\nSen A: The ends and means of development. Development as freedom. 1999; 35–53.\n\nSen AK: Poverty and famines. An essay on entitlement and deprivation.1981.\n\nSeyoum B: State fragility and human development: a study with special emphasis on social cohesion. Int. J. Soc. Econ. 2020; 48: 39–61. Publisher Full Text\n\nShandra JM, Nobles J, London B, et al.: Dependency, democracy, and infant mortality: a quantitative, cross-national analysis of less developed countries. Soc. Sci. Med. 2004; 59(2): 321–333. PubMed Abstract \| Publisher Full Text\n\nStasavage D: Democracy and education spending in Africa. Am. J. Polit. Sci. 2005; 49(2): 343–358. Publisher Full Text\n\nStatista:2020. Sub-Saharan Africa: Population growth from 2009 to 2019.Reference Source\n\nUNDP (United Nations Development Program): Human Development Report 2020: The next frontier. Human development and the Anthropocene.2020.\n\nUNDESA Population Division: World Population Prospects 2019.2020.\n\nWorld Bank National Accounts Data: The World Bank Group.2020.\n\nWorld Bank, World Development Indicators: The World Bank Group.2021." }	[ { "id": "154260", "date": "08 Nov 2022", "name": "Jamiu Adetola Odugbesan", "expertise": [ "Reviewer Expertise Strategic Management", "Organizational Behavior", "Green Management", "Human Resource Management", "Environmental Economics", "Development Economics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAfter careful review of the manuscript “Multiparty democracy, social cohesion, and human development in Sub-Saharan Africa: A panel data analysis” I would like to congratulate the authors for doing such a good research work in your submitted paper for publication in this prestigious journal. The topic is interesting and innovative and would personally like to appreciate your efforts to present your research work in such a nice manner. But before your work will be recommended or will be given any possible acceptance few comments must be incorporated for improving the quality of your work as well as for further publication in this reputed journal. I have the following major observations or queries and comments which may further enhance your piece of work. The authors require to modify the following points in detail.\nIn abstract, kindly incorporate the objectives of the study as well as policy recommendation\n\nThe introduction part is required to add few more sentences to increase the strength of this article and kindly bring in the research problem, objective, novelty and explain it in last paragraph of the section of Introduction.\n\nAdd few more sentences in the very beginning of introduction explaining about your paper’s contribution or attempts for dealing or presenting solutions for a specific problem/s and your special contribution with this research paper.\n\nThe section of “Results” must explain research problems, solutions and the contribution of your study theoretically.\n\nThe literature section requires some improvement with relevant recent studies.\n\nUse of English language requires improvement.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "185318", "date": "07 Aug 2023", "name": "Austin Cheyeka", "expertise": [ "Reviewer Expertise My area of expertise is religion and politics in Southern Africa. However", "I was able to understand the manuscript I reviewed. I am not a quantitative researcher", "but there are quantitative research I am able to comprehend and this manuscript was one of them." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nMultiparty democracy, social cohesion, and human development in Sub-Saharan Africa: A panel data analysis\nThank you for according me an opportunity to review the above captioned manuscript. The topic is interesting and original, and this has the potential to be a significant contribution to the literature on multiparty democracy in Sub-Saharan Africa.\nThe study was longitudinal (1995-2019) and a panel data analysis of 35 countries was done in order to determine the effect of multiparty democracy, social cohesion, and their interaction on human development. The study had 3 objectives: 1). to determine the effect of multiparty democracy on human development; 2). to determine the effect of social cohesion on human development; and 3) to estimate the effect of the interaction between multiparty democracy and social cohesion on human development.\nIn my view the theories employed in the study are appropriate and very well explained. The design of the study is well articulated and appropriate – it has academic merit. Overall, the methods and analysis allow replication of the study. The statistical analysis and the interpretation of the data are appropriate. The manuscript is well structured and it holds together very well. The objectives of the study were ably fulfilled and the study contributes to the literature on multiparty democracy and human development by proposing a hands-on theoretical model of democratic reform that goes beyond the current models advocated in the existing studies (pp. 2-3).\nThe conclusion and recommendations of the manuscript are rooted in the findings. I agree with the conclusion that, “to sustain human well-being in the Sub-Saharan African region, power must rest completely in the hands of its people. It is only when the masses can participate in the process of governance that accountability can be strengthened, resources are equitably distributed, and the inequality gap between the rich and the poor be reduced”(pp. 23-24).\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-797
https://f1000research.com/articles/11-795/v1	18 Jul 22	{ "type": "Research Article", "title": "Deep tissue injury as possible pathogenesis of acute inflammatory swelling or cellulitis after connecting implant super-structures: a case series study", "authors": [ "Deuk-Won Jo", "Young-Kyun Kim", "Mijoo Kim", "Yang-Jin Yi", "Deuk-Won Jo", "Young-Kyun Kim", "Mijoo Kim" ], "abstract": "Background: Acute swelling or cellulitis may develop within a few days after placing a definitive prosthesis or reconnecting a loose healing abutment/prosthesis, though its cause remains unclear. In this study, we propose a mechanism for the underlying pathogenesis. Methods: We retrospectively reviewed the symptoms and signs, onset of symptoms, recovery duration, and laboratory data of seven women and two men (55–84 years) who exhibited acute swelling and pain around dental implants within a month of connecting definitive prosthesis or reconnecting a loose healing abutment/prosthesis between 2013 and 2021. Results: The extent of the swelling varied from the gingiva and vestibule around the implant to the face and neck regions. The swelling persisted despite removal of the connected superstructure. All patients recovered within three weeks of symptom onset. Conclusions: Our findings suggest that the rapid onset of symptoms and signs, progress, duration, and etiology were consistent with the pathogenesis of deep tissue injury, which is characterized by acute inflammatory swelling that initiates from the interface between bone and subcutaneous tissue and progresses outward. Clinicians should be aware of the pathogenesis of pressure-induced injury and provide adequate treatment based on the underlying physiological process.", "keywords": [ "acute inflammatory swelling", "cellulitis", "deep tissue injury", "implant superstructures" ], "content": "Introduction\n\nDuring the prosthetic phase of dental implant treatment, patients may present with severe pain and acute swelling several days after definitive prosthesis delivery or reconnection of a loose healing abutment (HA) or prosthesis. Empirically, most patients recover within several weeks of medical care and follow-up. Unfortunately, the condition may deteriorate, in the form of cellulitis, in some cases, requiring referral to oral and maxillofacial surgery (OMS) specialists.\n\nWhen patients report to the clinic or emergency room (ER) with these complaints, especially of severe pain and swelling around the implant, it is important to determine whether a bacterial infection has caused the signs and symptoms. However, empirically, the patients’ history, physical examination, and laboratory data may not help in conclusively distinguishing between infection and inflammation.1,2 Owing to the similarity in the clinical features of acute inflammatory swelling and cellulitis caused by infections, clinicians often overtreat such patients, and patients may suspect the previous prosthetic procedure to be the cause of the infection. Furthermore, uncertainty about why the (re) connection of the implant superstructures could cause acute symptoms creates a dilemma for clinicians. Exploring the cause and progress of the pathology is the first step to prevent and to resolve it.\n\nIn medicine, a pressure ulcer is the most well-known injury caused by mechanical pressure on the body.3,4 Deep tissue injury (DTI) has been proposed as a subtype of pressure ulcers by public health specialists.3–9 DTI develops when pressure and shear force caused by external mechanical load induce ischemia and tissue deformation in the subcutaneous tissues of the load-bearing area. Acute inflammatory edema develops and spreads to adjacent tissues such as connective tissue and muscle, following a bottom-up pathway, which means that the injury propagates from the inside toward the surface. The injury is initiated at the interface between bone and soft tissue.3,6 Once DTI is initiated, acute edema develops almost immediately and progresses over time as a result of the ischemia-reperfusion injury and obstruction of lymphatic vessels.\n\nBased on the premise that acute swelling may result from pressure and external force applied on the peri-implant gingiva while connecting the implant superstructure, the concept of DTI could explain the pathogenesis underlying the clinical presentation observed in some patients. Furthermore, this could also explain why some patients show signs of infection. The progressive edema and impaired lymphatic system in the peri-implant tissue10,11 increase the risk of infection,12,13 and the transmucosal region of the implant can provide a pathway for microbial invasion.14–17 Therefore, the present case series study aims to propose a possible mechanism of how implant superstructure connections can cause acute swelling and pain, based on the concept of DTI.\n\n\nMethods\n\nTen cases in nine patients, who exhibited acute swelling or suspected infection that developed within a month of placing a definitive prosthesis or reconnecting loosened or exfoliated HAs or prosthesis, were reviewed. The patients were treated at the prosthodontic department of the Seoul National University Bundang Hospital (Seongnam, South Korea) between March 2013 and March 2021. The following data were retrieved from the patients’ medical records: sex, age, medical history, reasons for superstructure connection, physical examination, laboratory examination result (if laboratory examinations were performed), treatment, and recovery time. In addition, the clinical findings, patient factors, and duration of the signs and symptoms were analyzed based on the conceptual framework and physiological process of DTI. The institutional review board at the Seoul National University Bundang Hospital approved this study (IRB No. B-2104-681-101), and the study protocol conforms to the Declaration of Helsinki. The institutional review board waived the need for informed consent due to the retrospective nature of the research.\n\n\nResults\n\nPatient data are summarized in Table 1.18 There were seven women and two men, and their median age was 66 years (55–84 years). Cases 4-1 and 4-2 (Table 1) were of the same patient. Six patients underwent pathological blood investigations.\n\n1 Tooth number follows the FDI tooth numbering system.\n\n2 Normal ranges of vital signs: BP, 90/60 mmHg-120/80 mmHg; RR, 12-18 per minute; PR, 60-100 beats per minute; BT, 36.5°C–37.3°C.\n\n3 Normal ranges of laboratory tests: HbA1c level, 4.0-5.6%; Glucose level, 70-110 mg/dL; WBC count, 4.0-10.0 × 103/μL; CRP level, 0-0.5 mg/dL; BUN level, 10-26 mg/dL; Uric acid level, 3.0-7.0 mg/dL.\n\n4 Implant systems: CMI (Neobiotech, Seoul, South Korea); Luna (Shinheung, Seoul, South Korea); Osseotite (Biomet 3i, FL, USA); Osstem TSIII (Osstem, Seoul, South Korea); Superline (Dentium, Seoul, South Korea).\n\nMost patients stated that the swelling developed within a day of superstructure connection placement, except for one patient who could not recall the time of the onset of symptoms (case 5 in Table 1). Five patients underwent superstructure reconnection during the visit preceding symptoms due to loosening, and the other five underwent definitive prostheses deliveries.\n\nMost patients showed increasing swelling and pain within a certain time, regardless of whether the connected superstructures were retrieved and exchanged with narrower ones. Except for two cases with only localized gingival swelling around the implants, antibiotics were prescribed for all patients based on a cellulitis-like appearance. In three cases (5 [Figure 1a], 7, and 8; Table 1), pus discharge from the peri-implant sulcus was observed. None of the patients developed fever. The symptoms subsided within three weeks in all patients, and there was no relapse. None of the patients showed any significant radiographic change in the alveolar bone after symptom onset. Representative radiographs are presented in Figure 2.\n\n(a) Pus discharge from the peri-implant gingival sulcus (case 5). (b) Swollen, uneven, and bleeding peri-implant gingiva (case 3).\n\nNo significant changes in terms of the crestal height was seen in all presented cases.\n\nIn terms of the patients’ medical history, five of the nine patients were undergoing treatment for diabetes. Moderate to high glycated hemoglobin (HbA1c) and glucose levels were observed in six patients. An abnormal range of uric acid and blood urea nitrogen levels was observed in the patient presenting with two episodes of acute swelling (cases 4-1 and 4-2). This patient was undergoing treatment for renal cell carcinoma and hypothyroidism.\n\nElevated white blood cell (WBC) levels were observed in three patients. Two of these patients showed high C-reactive protein (CRP) levels, while in the other patient, the CRP level was low.\n\nCase 2 (Table 1)18\n\nA woman in her 60s, undergoing treatment for diabetes and hypertension, underwent implant placement in the mandibular left first molar region. After the healing period, a fixture-level impression was made for crown fabrication. Ten days after the impression was recorded, the HA loosened and exfoliated. Therefore, a staff member reconnected the loosened HA.\n\nFive days after the reconnection appointment, the patient revisited the clinic complaining of pain, difficulty in swallowing, and swelling in the gingiva around the implant and the left cheek. The patient reported that the swelling had developed several hours after the reconnection of the HA. Physical examination showed the following: tenderness and edema in the peri-implant gingiva; dysphagia; redness, tenderness, and warmth involving the left cheek and left submandibular region; and mouth opening limitation with a soft end feel. The patient was apyrexial, and there was no pus discharge in relation to the implant.\n\nAfter the HA was disconnected, chlorhexidine irrigation was performed at the implant site. The HA was then replaced with one that was narrower in size. The patient was transferred to the OMS department to confirm a diagnosis of cellulitis. Peri-implant curettage was performed, and an antibiotic (Mesexin: methylol cephalexin lysinate, Hanlim Pharm. Co., Seoul, South Korea) and a non-steroidal anti-inflammatory drug (NSAID; Ketoprofen) were prescribed. Fourteen days after the loosened HA was reconnected, the symptoms and clinical signs had completely subsided. Six days after the onset of symptoms, an HbA1c level of 7.2% was measured during a routine diabetes check-up at the endocrine internal medicine department.\n\nCase 3 (Table 1)18\n\nA man in his 60s, undergoing treatment for diabetes and hypertension, visited the clinic because an implant crown, placed on the implant in the right mandibular first molar region two years previously, had fallen out 10 days earlier. Intraoral assessment revealed that the abutment screw was fractured, so the screw remnant was removed from the fixture. After disinfecting the exfoliated abutment and crown, the prosthesis was reconnected with a new abutment screw.\n\nAt 6:48 am the following day, the patient was transferred by ambulance to the Seoul National University Bundang Hospital ER with severe pain around the implant and adjacent teeth. On arrival, the numerical rating scale score for self-reported pain intensity was 8–9. Vital signs were recorded as systolic blood pressure, 156 mmHg; diastolic blood pressure, 107 mmHg; respiratory rate, 15/min; and body temperature, 36.5°C. Laboratory tests showed HbA1c level, 6.0%; CRP level, 4.58 mg/dL; and WBC count, 8.90 × 103/μL. In the ER, the patient’s dental history was established, pain control was initiated, and the patient was transferred to the prosthodontics department.\n\nDuring the intraoral evaluation performed on the same morning, gingival swelling and redness were observed around the implant. While disconnecting the crown from the implant, sulcular bleeding and uneven and swollen gingiva were observed (Figure 1b). Chlorohexidine irrigation and minocycline ointment were applied in the sulcus, and an HA was connected to the implant. The patient was dismissed after scheduling a follow-up appointment.\n\nThree days later, the patient was transferred to the OMS department due to severe pain, dysphagia, and swelling and tenderness on the right cheek and neck. The patient did not present with fever or chills. Incision and drainage were performed, and an antibiotic (Amoclan duo: amoxicillin and clavulanate) and NSAID (Aclofen: Aceclofenac) were prescribed. Most of the symptoms and signs subsided within 15 days of onset.\n\n\nDiscussion\n\nDTI, a subclass of pressure ulcers, is often unfamiliar to dentists. The pressure-induced injury initiated at the bone and soft tissue interface resolves rapidly after relieving the mechanical load.6,9 Blanching of the peri-implant gingiva is commonly observed during connection of implant superstructures. Sometimes, patients also report intense pain. The blanching and pain resolve within several minutes in most cases. Physiologically, gingival blanching is an induced ischemic condition of the subcutaneous tissue caused by the pressure applied during the connection. The associated pain indicates forcibly overstretched peri-implant tissues by the connected components. Therefore, it is reasonable to attribute the acute pain and swelling to the pressure and force applied to the peri-implant soft tissue during the connection process. Nevertheless, the mechanism explaining the acute inflammatory response and infection following connection/reconnection of a superstructure to an implant remains unclear.\n\nFrom our review of the experience of patients in this study and previous studies on DTI, we concluded that the development of symptoms after connection or reconnection of implant superstructures follows the physiological process of DTI. There are several reasons for considering DTI as the underlying pathogenesis of acute swelling or suspected cellulitis developing after the connection of implant superstructures.\n\nFirst, the act of connecting a superstructure through the transmucosal region of an implant meets the requirements for the development of pressure ulcers, which are external mechanical load, pressure and shear, friction, and tissue and patient tolerance.3,4 Figure 3 shows the events occurring during the abutment connection to the implant. The friction, pressure, and combined force cause tissue deformation and ischemia in the surrounding gingiva of the implant. As a result, strain develops within the gingival connective tissue. The resultant shear force can unleash bone and connective tissue interface injury.\n\nThe induced strain in the connective tissues and shear forces initiate the injury at the bone-connective tissue interface. The arrows represent the direction and distribution of forces. The forces are represented by arrows of the corresponding color.\n\nSecond, the onset and progress of symptoms and signs follow a time frame similar to that in DTI. Most patients stated that the pain and swelling developed on the day of superstructure connection. In cases 3, 8, and 9, the patients visited the ER within 24 h from the previous visit for superstructure connection. In the physiological process of DTI, acute inflammatory edema commences within two to four hours after external mechanical loading,6,7,9 and the injury progresses rapidly and can cause severe tissue damage.5,8 According to previous studies on DTI progression, acute inflammatory edema grows and intensifies by the fifth day after onset, and recovery occurs after approximately 14 days.9 As described in Table 1, most patients presented within six days of the superstructure connection, and resolution of symptoms occurred in two to three weeks.\n\nFinally, the clinical features resemble an inflammatory response more closely than signs of infection. Rapid swelling was the major confounding feature that hindered differentiation between inflammation and infection. The most challenging aspect is determining whether the inflammation was the result of infection. Therefore, antibiotic therapy was administered empirically in most patients in this study. As summarized in Table 1, the symptoms, signs, laboratory data, and time frame of the presentation were not necessarily consistent with the general progression of odontogenic infections in the head and neck region.1 Above all, it was difficult to identify the infection source other than the implant superstructure connection performed several days previously. It can be postulated that a loose superstructure favors microbial invasion through the transmucosal region. However, this does not apply to patients who underwent insertion of a definitive prosthesis for the first time without previous superstructure loosening.\n\nLaboratory data were retrieved to explore the cause of the events. Though both WBC count and CRP level are inflammatory markers and indicators of infection, clinical correlation is important to ensure an accurate diagnosis. The laboratory data in cases 3, 7, 8, and 9 showed elevated WBC count or CRP level (Table 1). In case 3, CRP level was elevated, WBC count was normal, and the respiratory rate and body temperature were within the normal range, despite slight hypertension. In cases 7 and 8, both elevated WBC count and CRP level were increased. Case 9 showed elevated WBC count and normal CRP level. Most patients did not exhibit fever/chills or toxic appearance, which are the clinical signs of cellulitis in the head and neck regions.1,2 A prospective study on facial cellulitis reported that 91% of the patients presented with chills or rigors before or at admission.2 Only one patient (case 8) described chills, although the patient’s body temperature was only slightly elevated within the normal range. Mild tachycardia and elevated WBC count and CRP level were also observed.\n\nEven if the symptoms and signs are caused by infection, it is assumed that infection represents a secondary development resulting from the progressive swelling and impaired lymphatic drainage.13 The lymphatic drainage in the peri-implant tissue10,11 can be obstructed or occluded primarily by pressure from the superstructure connection and the rapidly growing swollen area. Obstruction of lymphatic drainage increases the risk of infection.13 Moreover, the transmucosal region of the implant can be an infection route for microorganisms.15,16\n\nThe rare instances of development of this acute inflammatory condition during routine implant prosthetic treatments seem to be related to the patients’ conditions. Presence of underlying diseases may increase the susceptibility to inflammation and infection.3,4 Diabetes mellitus is a disease that is well known to predispose patients to various infections.12 In the present study, five patients were being treated for diabetes, and laboratory tests revealed moderate to high levels of HbA1c or glucose. Furthermore, the patient who experienced acute swelling twice (cases 4-1 and 4-2) had impaired renal function and hypothyroidism. These underlying conditions may have facilitated the development of acute swelling due to pressure-induced injury.19\n\nAnother contributing factor that could be the triggering of the local defense mechanism in the peri-implant tissue by neurogenic regulation leading to an inflammatory response. The distribution of substance P-containing sensory nerve terminal and neurokinin-1 receptors in the peri-implant epithelium has been reported.17 The pain impulse derived from the implant superstructure connection and the secondary pain caused by the growing DTI is afferently transferred via the substance P-neurokinin-1 receptor pathway. Additionally, substance P itself is known to be involved in antimicrobial activity.14 As a result, the afferent signal via the substance P-neurokinin-1 receptor pathway efferently stimulates neutrophil infiltration, immune regulation, vasodilation, and plasma leakage of endothelial cells.16\n\nBased on the analysis and previous studies on DTI, we suppose that the most likely pathogenic mechanism of acute inflammatory swelling or suspected cellulitis after connection of implant superstructures is the physiological process of DTI and peri-implant defense mechanisms. Figure 4 presents a schematic diagram of the possible pathogenesis of an acute inflammatory swelling caused by mechanical overloading of the gingiva beyond tissue/patient tolerance based on the DTI conceptual framework.3–9 The diagram also describes the relationship between lymphatic obstruction and infection risk,10,11,13 which includes characteristic permeable biological sealing of the peri-implant tissue14–17 and infection.2–4,12,19 In summary, the external mechanical loading exerted by implant superstructure connections can activate the DTI chain reaction as follows: 1) cell deformation and ischemia in the peri-implant gingiva; 2) induced strain on the gingiva and shear force to initiate intra-/inter-cellular edema and inflammatory responses from the interface between the peri-implant connective tissue and bone; and 3) extensive swelling resulting from the ischemia-reperfusion injury and lymphatic obstruction in the peri-implant tissue. The neurogenic defense mechanisms in the peri-implant tissue can also increase the inflammatory responses. This evolving process continues until leukocytosis, particularly neutrophilic leukocytosis, decreases. Additionally, in medically compromised patients, this condition can increase the risk of infection resulting from the combination of lymphatic obstruction and the inherent permeability of the barrier system of the transmucosal region of the implant.\n\nFrom our review of the severity of symptoms, we found that those patients who underwent reconnection of the exfoliated HAs or prosthesis tended to exhibit more severe symptoms than those receiving superstructures for the first time. The relatively stronger pressure applied to the constricted gingiva, which results from the absence of a superstructure, may cause a more intense inflammatory response during super-structure reconnection because the extent of the injury is known to be proportional to the load applied.9 Bacterial infection may be initiated through the transmucosal region of the implant.\n\nIn such cases, clinicians must first reassure the patient by explaining the possible causes of the symptoms and signs depending on the timeframe of the likely pathogenesis. A careful review of the patient’s medical history may aid diagnosis. Then, the superstructure should be disconnected and replaced with a narrower-sized HA to prevent sustained loading and relieve obstruction of the lymphatic drainage system. If the patient presents with acute swelling, fever, chills, tachycardia, elevated respiratory rate, and a toxic appearance, the patient should be immediately transferred to an OMS specialist. In less severe cases, prescription of anti-inflammatory agents and follow-up may be adequate.\n\nThe limitations of this study include the small number of cases, limited availability of blood test results, and lack of bacterial cultures to confirm cases of infection. Further in vivo studies are needed to corroborate the suggested pathogenesis. Structured prospective studies are also needed to trace the duration of symptoms, changes in symptoms and signs, and laboratory test results.\n\n\nConclusions\n\nAcute swelling with or without infection may develop due to acute inflammatory responses triggered by connecting or reconnecting implant superstructures. Clinicians need to be aware of the causes and physiological process of pressure-induced injury. Based on the pathogenesis of the injury, clinicians should evaluate the patient carefully and provide adequate treatment or refer the patient for specialist care.\n\n\nData availability\n\nFigshare: Underlying data for ‘Deep tissue injury as possible pathogenesis of acute inflammatory swelling or cellulitis after connecting implant super-structures: a case series study’, https://doi.org/10.6084/m9.figshare.20133998.v1.18\n\nAdditional data not provided in Figshare are not publicly available due to the privacy of the patients but are available from the corresponding author on reasonable request (Yang-jin Yi, navydent@snubh.org).\n\n\nReporting guidelines\n\nFigshare: STROBE checklist for ‘Deep tissue injury as possible pathogenesis of acute inflammatory swelling or cellulitis after connecting implant super-structures: a case series study’, https://doi.org/10.6084/m9.figshare.20134202.v1.20\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0)", "appendix": "References\n\nHupp JR, Tucker MR, Ellis E: Contemporary oral and maxillofacial surgery. 7th ed.Philadelphia, United States of America:Elsevier Health Science;vol. 201: 318–325.\n\nRath E, Skrede S, Mylvaganam H, et al.: Aetiology and clinical features of facial cellulitis: A prospective study. Infect. Dis. (Lond). 2018; 50: 27–34. PubMed Abstract \| Publisher Full Text\n\nColeman S, Nixon J, Keen J, et al.: A new pressure ulcer conceptual framework. J. Adv. Nurs. 2014; 70: 2222–2234. PubMed Abstract \| Publisher Full Text\n\nDeFloor T: The risk of pressure sores: A conceptual scheme. J. Clin. Nurs. 1999; 8: 206–216. PubMed Abstract \| Publisher Full Text\n\nCeelen KK, Oomens CW, Baaijens FP: Microstructural analysis of deformation-induced hypoxic damage in skeletal muscle. Biomech. Model. Mechanobiol. 2008; 7: 277–284. PubMed Abstract \| Publisher Full Text\n\nOomens CW, Bader DL, Loerakker S, et al.: Pressure induced deep tissue injury explained. Ann. Biomed. Eng. 2015; 43: 297–305. PubMed Abstract \| Publisher Full Text\n\nStekelenburg A, Gawlitta D, Bader DL, et al.: Deep tissue injury: How deep is our understanding?. Arch. Phys. Med. Rehabil. 2008; 89: 1410–1413. Publisher Full Text\n\nStekelenburg A, Strijkers GJ, Parusel H, et al.: Role of ischemia and deformation in the onset of compression-induced deep tissue injury: MRI-based studies in a rat model. J. Appl. Physiol. 2007; 102: 2002–2011. PubMed Abstract \| Publisher Full Text\n\nVan Damme N, Van Hecke A, Remue E, et al.: Physiological processes of inflammation and edema initiated by sustained mechanical loading in subcutaneous tissues: A scoping review. Wound Repair Regen. 2020; 28: 242–265. PubMed Abstract \| Publisher Full Text\n\nAndo Y, Murai O, Kuwajima Y, et al.: Lymphatic architecture of the human gingival interdental papilla. Lymphology. 2011; 44: 146–154. PubMed Abstract\n\nMarchetti C, Poggi P, Reguzzoni M, et al.: Lymphatic vessel system in gingival peri-implant tissues in humans. J. Periodontal Res. 1999; 34: 229–231. Publisher Full Text\n\nAkash MSH, Rehman K, Fiayyaz F, et al.: Diabetes-associated infections: Development of antimicrobial resistance and possible treatment strategies. Arch. Microbiol. 2020; 202: 953–965. PubMed Abstract \| Publisher Full Text\n\nMcGilvray S: Lymphoedema and cellulitis: A narrative review. Wound Pract Res. 2013; 21: 56. Publisher Full Text\n\nDouglas SD, Leeman SE: Neurokinin-1 receptor: Functional significance in the immune system in reference to selected infections and inflammation. Ann. N. Y. Acad. Sci. 2011; 1217: 83–95. Publisher Full Text\n\nMisch CE: Dental implant prosthetics. 2nd ed.Philadelphia, United States of America:Elsevier Health Sciences;2014; 977–981.\n\nYamaza T, Kido MA:Biological sealing and defense mechanisms in peri-implant mucosa of dental implants. Implant Dentistry-The Most Promising Discipline of Dentistry. Turkyilmaxz I, editor.Rijeka, Croatia:Intech Open;2011; pp. 219–236.\n\nYamaza T, Kido MA, Wang B, et al.: Distribution of substance P and neurokinin-1 receptors in the peri-implant epithelium around titanium dental implants in rats. Cell Tissue Res. 2009; 335: 407–415. Publisher Full Text\n\nKim M, Jo D-W, Kim Y-K, et al.: [Figshare] [Dataset].2022. Publisher Full Text\n\nMontenegro J, González O, Saracho R, et al.: Changes in renal function in primary hypothyroidism. Am. J. Kidney Dis. 1996; 27: 195–198. Publisher Full Text\n\nKim M, Jo D-W, Kim Y-K, et al.: [Figshare] [Dataset].2022. Publisher Full Text" }	[ { "id": "149821", "date": "13 Sep 2022", "name": "Patrice Forget", "expertise": [ "Reviewer Expertise Perioperative medicine", "postoperative outcomes", "pain management." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nDear authors,\nThanks for submitting this case series. You describe deep tissue injury as possible pathogenesis of acute inflammatory swelling or cellulitis after connecting implants. Your descriptions are well detailed and interesting.\n\nStrengths of the report include a good reflection on cause and mechanisms of symptoms. Treatments were proposed and described.\n\nWeaknesses include limitations of case reports and case series, i.e. describing what's possible rather than what's effective. Some symptoms like pain and pain management are not described in detail. Patients perspective is a very important aspect, not covered at all.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "301613", "date": "25 Jul 2024", "name": "Mehri Turki Imen", "expertise": [ "Reviewer Expertise Maxillofacial surgery", "Oral pathology", "Implantology" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThanks to the authors who described the occurrence of cellulitis following the placement of a definitive prosthesis or after reconnecting a loose healing abutment. In this report, DTI can not be demonstrated through these cases because of the multifactorial mechanism of cellulitis mainly in debilitating conditions. CT scan should be reported. Additionally, Pressure ulcers and tissue damage should be shown by histological examination, to validate this hypothesis in these cases Figure 1: the discharge of pus is shown in figure (b), so the legend should be inversed Figure 2: First of all, there is a difference between the alveolar crestal bone around the abutment as shown when comparing (a,b) and (c,d). However, the tooth (the third one) is shown in (c) and was absent in (b), and there is no stigma of extraction on radiography. How can you explain this? Moreover, it is not suitable to write “all cases” in the legend of Figure 2.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] } ]	1	https://f1000research.com/articles/11-795
https://f1000research.com/articles/11-789/v1	13 Jul 22	{ "type": "Case Report", "title": "Case Report: Incidental finding of didelphys uterus in a multigravida woman at Caesarean delivery", "authors": [ "Olutosin Awolude", "Ademola Olutoye", "Gbolahan Obajimi", "Ademola Olutoye", "Gbolahan Obajimi" ], "abstract": "Didelphys uterus is one of the rarest Müllerian duct anomalies (MDA) of the female genital tract. Many remain undiagnosed due to possibilities of successful pregnancies and vaginal deliveries in those without or with mild forms of associated cervical and/or vaginal anomalies. Due to this, data on didelphys uterus in pregnancy are rare, with most cases seen during routine ultrasound in pregnancies’ Caesarean section for other obstetric indications. This case was a 36-year-old G4P1+2 female who had successful vaginal delivery in her preceding pregnancy; in index pregnancy, she presented with fetal footling breech in labour and had an emergency caesarean section during which uterine didelphys was diagnosed. Many pregnant women with didelphys uterus will deliver vaginally and, as such, remain undiagnosed. Its presence is one of the possible reasons for persistent abnormal presentations like fetal breech presentation, especially in women with prior successful vaginal deliveries. Early recognition and availability of facilities for management of such incidentally found cases of uterine didelphys will prevent many of the complications associated with pregnancy with them.", "keywords": [ "uterine didelphys", "pregnancy", "caesarean section", "breech presentation" ], "content": "Introduction\n\nMüllerian duct abnormalities (MDA) are a spectrum of genital abnormalities arising from failure of fusion of the Müllerian ducts during the embryological stage of development.1 The prevalence of congenital uterine anomalies varies and can range between 5.5% in the general population and 24.5% in patients treated for miscarriages and infertility.2 The most common forms of uterine anomalies include unicornuate uterus, bicornuate uterus, arcuate uterus, septate uterus and didelphys uterus. Uterine didelphys belongs to MDA class III as defined by American Society of Reproductive Medicine (ASRM). This classification includes adnexal adhesions, distal tubal occlusion, tubal occlusion secondary to tubal ligation, tubal pregnancies, Müllerian anomalies and intrauterine adhesions that result from failure of Müllerian duct fusion at week eight of gestation.3,4 Though uterine didelphys rarely affects fertility, it is commonly associated with adverse pregnancy outcomes such as recurrent miscarriages, preterm deliveries, intrauterine growth-restricted fetuses, low-birth-weight fetuses, and fetal malpresentations. While many cases will remain undiagnosed until evaluations for other gynaecological conditions,5,6 fetal malpresentation diagnosed during pregnancy or at delivery is one of the commonest indications for Caesarean delivery.7 We present a case of Caesarean section in a multiparous woman with uterine didelphys with breech presentation at term in our obstetric service.\n\n\nCase\n\nA 36-year-old G4P1+2 1 alive Nigerian of Yoruba ethnicity, presented for antenatal service following spontaneous conception of singleton gestation at gestational age of 17 weeks. She was the third of her parents’ four children, including three females and one male. The older two sister were multiparous with no significant obstetric complaints. Obstetrics scan done at 23 weeks revealed live singleton fetus in breech presentation within the right horn and empty left horn of the uterus (Figure 1). She was regular at clinic visits and her pregnancy period remained uneventful. Four years earlier, she had a vaginal delivery, at term, of a live neonate with a birth weight of 2.95 kg following spontaneous conception after two prior spontaneous pregnancies loss at about six weeks gestation each.\n\nReview at the antenatal clinic at 37 weeks revealed fetal cephalic presentation at clinical examination. However, at 38 weeks and four days of gestation she presented in labour and obstetrics examination revealed a singleton fetus in longitudinal lie with footling breech presentation. She subsequently had emergency lower segment Caesarean section and was delivered of a live neonate with a birth weight of 3.75 kg via breech extraction from the right horn, the left horn was bulky and equivalent to about 14 weeks size gestation (Figure 2). Each horn had its adjoining normal looking fallopian tube and ovary. The urinary bladder was grossly normal. Her postoperative period was satisfactory and she was discharged on fourth day after surgery.\n\n\nDiscussion\n\nCongenital malformations of the female genital tract are embryological maldevelopments of the Müllerian or paramesonephric ducts.8,9 The prevalence of genital tract malformations has been reported to vary between 6.0-38%.9,10 In the general population it was reported to range between 5-7%, 7-8% in the infertile population and 16-25% in the recurrent miscarriage and infertile population.1,8,11 Malformations involving the uterus have been reported as the most common MDA with septate uterus being the commonest, and didelphys uterus the rarest.12 In a 15-year retrospective analysis, septate uterus were found in 55.6% of cases of female genital tract anomaly, while uterine didelphys accounted for 22.7% of cases.13 Presentations of genital tract anomalies also vary. In paediatric patients, presentation to emergency services with symptoms of severe abdominal pain, likely associated dysmenorrhea if menarche has been reached, obstructed hemivaginal septa, and abdominal swelling from haematometra with or without haematocolpos, are common.1,14\n\nCongenital malformation of the female genital tract is of special interest in the practice of obstetrics as the obstetrics performance is determined by the type of MDA. Some authors have reported increased risk of first- and second-trimester miscarriages, preterm birth, low birth weight, fetal mal-presentation, and ultimately abdominal delivery with uterine didelphys.15,16 However, there have been many reported cases of successful pregnancies and deliveries in patients with uterine didelphys following appropriate pre-pregnancy surgical correction and appropriate obstetrics interventions like cervical cerclage.1,17 In a prospective multicenter study of 286 pregnant women with uterine didelphys conducted in Saudi Arabia, 5.2% of the women had first trimester abortion, 27.5% had preterm labour which were managed conservatively with all delivering at term and of all delivering at term, 5.9% had spontaneous vaginal delivery, 13.3% had operative vaginal delivery and 80.8% of the women delivered by Caesarean section.18 Our patient had two previous miscarriages prior to her first delivery.\n\nDelivery by Caesarean section is, generally, not primarily indicated in cases of uterine didelphys except for additional obstetric indication.19 In our patient, she had successful vaginal delivery in her previous pregnancy and had Caesarean delivery in index case because of the fetal footling breech presentation at term.\n\n\nConclusions\n\nDidelphys uterus is among the rarest of Müllerian duct anomalies and is commonly associated with successful pregnancies outcomes. Many will deliver vaginally and remain undiagnosed, as was the case for the first term pregnancy of the case we presented. However, its presence can be suspected in pregnant women with prior vaginal deliveries now presenting with malpresentations, like persistent fetal breech presentation as seen in this patient. Good antenatal care and management in a facility with adequate obstetric facilities for surgical intervention can prevent complications that can result from undiagnosed cases. This is especially important for cases showing malpresentations as seen in this case of fetal footling breech presentation.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nPatient consent\n\nConsent was obtained from the patient for publication of this case.", "appendix": "References\n\nJorgensen C, Lusiak M: Didelphys Uterus in Pregnancy, an Uncommon Mullerian Duct Anomaly: A Case Report. Clin. Pract. Cases Emerg. Med. 2021; 5(4): 447–449. PubMed Abstract \| Publisher Full Text\n\nChan Y, Jayaprakasan K, Zamora J, et al.: The prevalence of congenital uterine anomalies in unselected and high-risk populations: A systematic review. Hum. Reprod. Update. 2011; 17: 761–771. PubMed Abstract \| Publisher Full Text\n\nThe American Fertility Society The American Fertility Society classifications of adnexal adhesions, distal tubal occlusion, tubal occlusion secondary to tubal ligation, tubal pregnancies, Mullerian anomalies and intrauterine adhesions. Fertil. Steril. 1988; 49: 944–955. PubMed Abstract \| Publisher Full Text\n\nGrimbizis GF, Gordts S, Sardo ADS, et al.: The ESHRE/ESGE consensus on the classification of female genital tract congenital anomalies. Hum. Reprod. 2013; 28: 2032–2044. PubMed Abstract \| Publisher Full Text\n\nMartínez-Beltrán M, Giménez JP: Uterus didelphys with septate cervix and unilateral endometrial carcinoma: A case report. J. Genit. Syst. Disord. 2012; 1(1). Publisher Full Text\n\nRezai S, Bisram P, Alcantara I, et al.: Didelphys uterus: A case report and review of the literature. Case Report. Obstet. Gynecol. 2015; 2015: 865821. PubMed Abstract \| Publisher Full Text\n\nMaiti GD, Tugnait P, Anand AK, et al.: Uterine Didelphys with Pregnancy and Cervical Incompetence. Med. J. Armed Forces India. 2006; 62(2): 200–201. PubMed Abstract \| Publisher Full Text\n\nGao J, Zhang J, Tian W, et al.: Endometrial cancer with congenital uterine anomalies: 3 case reports and a literature review. Cancer Biol. Ther. 2017; 18(3): 123–131. Publisher Full Text\n\nLaufer MR, De Cherney AH: Clinical Manifestations and Diagnosis of Congenital Anomalies of the Uterus. UpToDate. Waltham, MA, USA:Wolters Kluwer;2019. South Holland, The Netherlands.\n\nKim MA, Kim HS, Kim YH: Reproductive, Obstetric and Neonatal Outcomes in Women with Congenital Uterine Anomalies: A Systematic Review and Meta-Analysis. J. Clin. Med. 2021; 10(21): 4797. PubMed Abstract \| Publisher Full Text\n\nSaravelos SH, Cocksedge KA, Li TC: Prevalence and diagnosis of congenital uterine anomalies in women with reproductive failure: a critical appraisal. Hum. Reprod. Update. 2008; 14(5): 415–429. PubMed Abstract \| Publisher Full Text\n\nSimón C, Martinez L, Pardo F, et al.: Müllerian defects in women with normal reproductive outcome. Fertil. Steril. 1991; 56(6): 1192–1193. Publisher Full Text\n\nWang SJ, Oli M, Jinag L, et al.: Clinical analysis of 225 women with congenital uterine malformation. Zhonghua Fu Chan Ke Za Zhi. 2008; 43(7): 493–496. PubMed Abstract\n\nKaraca L, Pirimoglu B, Bayraktutan U, et al.: Herlyn-Werner- Wunderlich syndrome: a very rare urogenital anomaly in a teenage girl. J. Emerg. Med. 2015; 48(3): e73–e75. PubMed Abstract \| Publisher Full Text\n\nGrimbizis GF, Camus M, Tarlatzis BC, et al.: Clinical implications of uterine malformations and hysteroscopic treatment results. Hum. Reprod. Update. 2001; 7(2): 161–174. PubMed Abstract \| Publisher Full Text\n\nVenetis CA, Papadopoulos SP, Campo R, et al.: Clinical implications of congenital uterine anomalies: a meta-analysis of comparative studies. RBM Online. 2014; 29(6): 665–683. PubMed Abstract \| Publisher Full Text\n\nHeinonen PK: Reproductive performance of women with uterine anomalies after abdominal or hysteroscopic mertoplasty or no surgical treatment. J. Am. Assoc. Gynecol. Laparosc. 1997; 4(3): 311–317. Publisher Full Text\n\nOthman M: Uterine Didelphys Pregnancy Management. J. Adv. Med. Med. Res. 2018; 26: 1–5. Publisher Full Text\n\nLin PC, Bhatnagar KP, Nettleton GS, et al.: Female genital anomalies affecting reproduction. Fertil. Steril. 2002; 78(5): 899–915. Publisher Full Text" }	[ { "id": "144392", "date": "05 Sep 2022", "name": "Adepiti Clement Akinfolarin", "expertise": [ "Reviewer Expertise Gynaecological oncology" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a succinctly described case report. It touched essentially on the presentation, examination, diagnosis and treatment. The description and discussion are detailed and have added to the body of knowledge on the subject of MDA.\n\nHowever, one is not convinced that in a didelphic uterus, which is usually smaller than normal uterus, an average sized fetus in cephalic presentation at 37 weeks would spontaneously convert to breech at 38 weeks. What is the cadre of the personnel that performed that examination at 37 weeks?\nEssentially, its a good case report.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "235209", "date": "12 Feb 2024", "name": "Antonella Vimercati", "expertise": [ "Reviewer Expertise perinatal medicine" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nYou present an interesting case of pregnancy in utero didelphys but limited by an insufficient comparison or discussion with the data present in the literature.\nyou should add other recent bibliographical entries on the topic such as at least the following 2:\n\n1. ref [1] 2. ref [2] IN DISCUSSION (after first paragraph)-The mode of delivery should first be explored in more detail, because there are conflicting data in the literature. Indeed, reports are almost equal for those who prefer CS and those who prefer vaginal delivery. It is quite common to get abnormal presentations and malposition in patients with uterus didelphys, but there are reports of successful labor in this group of women. CS was the mode of delivery preferred by some Authors, considering also the strong fear of the patient for the baby, the major muscular component in the cervix, the presence of septum in the vagina should be considered above all if is thick and inelastic resulting in an increased risk for vaginal dystocia and prolongation of the second phase of labor.\n\nThe drawing of figure 1 should be improved and made compatible as position (right and left horn) with the macroscopic figure 2.\n\nIN DISCUSSION (before the last paragraph)- As for as the diagnosis of uterus didelphys you should better stress the usefulness of MRI for differential diagnosis of other rare uterine pathologies, adding 2 bibliographic entries as suggested below:\nThe diagnosis and consequently the management of pregnancy with uterus didelphys represent difficult and well-discussed topics in the literature. Confirming the diagnosis of uterine didelphys with obstructed hemi-vagina and unilateral renal agenesis is particularly challenging and diagnosis of uterine anomalies is often subjective. Although two-dimensional ultrasound is commonly utilized, it is considered the least accurate imaging investigation and when diagnosis is difficult to differentiate better Bicornuate, unicornuate, and didelphic uterus or other uterine pathologies or other rare obstetric complications such as Twin Pregnancies with Complete Hydatiform Mole and Coexistent Normal Fetus it may be useful to use the more accurate pelvic MRI. ref [3] ref [4]\n\nIs the background of the case’s history and progression described in sufficient detail? Partly\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Partly\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Partly\n\nIs the case presented with sufficient detail to be useful for other practitioners? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-789
https://f1000research.com/articles/11-788/v1	13 Jul 22	{ "type": "Research Article", "title": "Analysis of the workload of Dock 16 Ilir workers sing Rapid Upper Limb Assessment, Ovako Working Analysis System, and Nordic Body Map Methods: A quantitative case study", "authors": [ "Christofora Desi Kusmindari", "Poppy Indriani", "A Harits Nu'man", "Salma Mutia Muthmainah", "Ira Erina", "Poppy Indriani", "A Harits Nu'man", "Salma Mutia Muthmainah", "Ira Erina" ], "abstract": "Abstract: Industry players are encouraged to automate as a result of technological advancements. However, due to lack of finances several businesses continue to require human labor in the production process, particularly in the operation of transferring items . Transportation activities at Dock 16 Ilir in Palembang City, starts with delivering items from the shop to the ship or vice versa by utilizing human strength in less ergonomic work positions with little consideration for the weight of the load. Whencarrying goods , the body is bent, the neck is bent, and the arms are distant from the body, putting the body at a very high risk of injury. This type of working position causes muscle aches ranging from mild to severe. The personnel seen in this investigation were rice transporters and cement transporters. The aim of this study is to quantify the workload and provide a design tool to help lessen worker concerns. The Nordic Body Map, Rapid Upper Limb Assessment (RULA), and Ovako Working Analysis System (OWAS)methodologies were used in this investigation. The study's findings showed that the five cement transport workers and four rice transport workers were at risk of developing muscoskeletal illnesses, with a risk level of 3 to 4, indicating that the risk category is very high and comprehensive treatment is required as soon as feasible. According to the OWAS technique, the posture of rice transportation employees has a value of 3, indicating that they are at high danger. Meanwhile, the working posture of cement transportation has a score of 7 with a risk level of 4, indicating that the danger of MSDS is very high. The developing aids are projected to lower the danger of Muscoskeletal Disorders in a backpack-like style that can resist large loads and reduce the risk of Muscoskeletal Disorders.", "keywords": [ "Nordic body map. RULA", "OWAS", "Muscoskeletaldisorders" ], "content": "Introduction\n\nThe industrial world is rapidly evolving and totally automated, making all processes more effective and efficient. However, the usage or role of people as a labor system, particularly in the industrial sector of Indonesia, cannot be avoided or even totally eliminated. One of these is the transfer of commodities at Dock Palembang city that continues to use manual transportation (manual material handling) (Nur et al., 2016; Widiana et al., 2021; Budiman & Setyaningrum, 2006), in which human labor is used to transport commodities ranging from cloting, shelter and food to be shipped to various regions in South Sumatra. According to M. Fitri and W. Laila (Fitri & Laila, 2017), in Indonesia, the consideration of moving materials directly via Manual Material Handling (MMH) is thought to require lower costs than machines, and MMH has been widely employed in medium to micro scale businesses until now. Meanwhile, according to C. H. D. Kusmindari et al. (Kusmindari et al., 2020), the solution to maintaining a decent posture while performing MMH activities is to improve the work system in MMH activities, specifically as a concept (Kusminadri & Tian, 2021).\n\nIndustry participants sincerely hope that production will operate smoothly and withoutany challenges, both in terms of human employees and machinery and materials, and that output targets will be met. As a result, human labor and machines can coexist effectively in the long term. However, humans have limitations, unlike machines, which will not fatigue if they are used for a lengthy period of time. As stated by M. A. Wahyudi et al. (Wahyudi et al., 2015) the usage of employees must be supported by ideal work techniques and workplaces that are in agreement with body posture to accomplish work for an extended period of time without causing injury to the workers.\n\nWorkers’ complaints of musculoskeletal diseases (MSDs) range from slight problems in the skeletal muscles to very severe case (Gómez-Galán et al., 2020; Dewi, 2020; Factsheet 4 - Preventing Work-Related Musculoskeletal Disorders\|Safety and Health at Work EU-OSHA, n.d.). These concerns regarding MSDs must be managed to limit the risk of damage to the movement of the neck (neck), trunk (trunk), and legs (legs), and, most significantly, to preserve the workforce’s concentration at work so that workers feel comfortable. If the workforce is hurt it can effect their health in which case they maybe unable to work or the job they accomplish will be less than optimal causing not only workers but also the industry to suffer.\n\nThe first approach in this study is to identify the MSDs concerns of freight forwarders, who are rice and cement transporters, using Nordic Body Map (NBM) questionnaire data (Purnomo et al., 2010; Wadhikh, 2019; Putri et al., 2021). Following the collection of data, the next stage is to undertake research to identify and analyze work attitudes in order to assess workload, as well as to measure oxygen consumption using the OWAS Ovako Working Analysis SystemOWAS (وآخرون, 2004) and RULA Rapid Upper Limb Assessment RULA methods (Purwaningsih, 2016) (Bintang & Dewi, 2017).\n\nAccording to D. P. Restuputri et al. (Restuputri et al., 2017), the OWAS approach is a way for studying individuals in the process of work that is observed with a dynamic dangerous attitude. Based on the work attitudes observed, a work attitude category will be determined, with four category scales in the OWAS technique ranging from no danger to the highest risk of damage. This is to clarify which work posture resulted in the categorization of work attitudes that require improvement. The observed working posture is the movement of the body from the shoulders, back, hands, and feet. According to OWAS, it would be more appropriate to verify the management of MMH. This is due to the fact that OWAS may measure and examine directly while workers are manually handling materials (El Ahmady et al., 2020).\n\nWhile the RULA technique contains four categories of work attitudes, it also has four categorization scales, ranging from no danger (Safe) to the highest risk of damage. It is possible to determine which work postures result in the categorization of work attitudes that require improvement by watching work postures. (Tiogana & Hartono, 2020).\n\nAs a recommendation for workers in Dock 16 Ilir Palembang City, this study aims to analyze the shoulder, arm and leg of workers who experience MSDs using NBM, analyze the workload of transporting rice using the OWAS work posture classification, analyze the load of cement workers using RULA, and analyze the size or design of acute aids to minimize the risk of injury. The concerns that will be raised in this research, among others, are as follows: What are the work postures and workloads that cause MSDs in workers at Dock 16 Ilir Palembang city after studied by NBM? How can the workload be determined based on OWAS and RULA? How can the size or design of a vehicle be determined?\n\n\nMethods\n\nThe research location at Dock 16 Ilir Palembang city, which operates as a place to transport goods from shop to ships. In this study four rice transport workers and five cement carrier workers at this location were observed for one month.\n\n1. Field study\n\nNBM questionnaire was used to examine the workload of the four rice and five cement transporters OWAS and RULA methods were used to assess the data for risk category classification “position code” in a combination of positions (back, arms, and legs).\n\n2. Literature study\n\nIndustrial Literature Study, which entails gathering data through the study of books that support this research.\n\nThe data was processed by using a predetermined method, namely the NBM test, followed by RULA and OWAS. Data processing in this study comprised assessing objects before and after improving work posture with NBM, RULA, and OWAS.\n\nThe analytical technique employed compares the level of risk of injury to both rice and cement transport employees while employing traditional transportation methods to the suggested transportation methods RULA and OWAS.\n\n\nResults and discussion\n\nThe study was carried out on the rice transportation to ships, where workers continue to use MMH, as well as on the cement transportation section of company. During the initial observation stage, researchers discovered that the method of transporting rice and cement posed a high dangerto the physical well-being of the workers. Following this observation stage, the researcher conducted interviews with numerous workers and received data indicating that workers move 100 kg bags of rice and cement 3 times a day with an average weight of 1-3 tons. it causes workers to experience musculoskeletal disorders\n\nThe results of the NBM Questionnaire are as follows:\n\nThe NBM is an auxiliary questionnaire that defines body parts from head to toe, which specifically was used in this study for workers who transport grains and cement. The NBM questionnaire is important for gathering feedback from workers who transport rice and cement during the MMH process. There are 28 sections in this questionnaire, ranging from 0-27, with a rating score of 1–3. Several complaints were reported at work in the NBM questionnaire findings for workers delivering rice and cement. Table 1 shows the results of the NBM questionnaire on workers delivering rice and cement. Figure 1 shows the flowhart research diagram conducted by researcher.\n\nAccording to Table 1, the four rice transporters are at risk of MSDs because they have a total score of individual complaints in the range of 63–84, indicating that the risk level is at 3, which is a very high-risk category, and comprehensive treatment is required as soon as feasible. Table 2 shows workers in the cement transport industry.\n\nAccording to Table 2, the five cement transport employees are at risk of MSDs since they have a total score of individual complaints in the range of 63–84, indicating that the risk level is at 3, which is a very high-risk category, and thorough action is required as soon as feasible.\n\nRice receipt process\n\nBased on Figures 2 to 4 which show the posture of workers when transporting rice, the results of the OWAS calculation can be seen in Table 3.\n\nTable 3 shows the results of the classification using the OWAS method:\n\nRice transfer process\n\nTable 4 shows the OWAS risk assessment for rice transfer workers.\n\nRice laying\n\nTable 5 shows the OWAS risk level for rice laying workers.\n\nTable 6 summarizes the results of data processing from day one onwards:\n\nAs a result of calculating the work posture of rice transportation workers using the OWAS approach, an average degree of risk of 3–4 was determined.\n\nCement receiving position\n\nAt this point, the labor operator collects cement from other workers seated on the cart/push wheel in charge of distributing cement.\n\nSource: personal documentation.\n\nGroup A:\n\nThe load lifted by the worker is greater than 10 kg. The RULA score is +3, whereas the change score is 0 because the load does not encounter an unexpected increase in load. The posture of cement lifting workers is shown in Figures 5 to 7.\n\nAs a result, the Group A score is shown in Table 7 below:\n\nThis table depicts the upper arm, lower arm, wrist, and wrist twist positions. The blue color describes the upper arm (upper arm) at position 3, the green color describes the lower arm (lower arm) at position 2, the yellow color describes the wrist at position 2, and the orange color describes the wrist rotation at position 0, and the muscle use score is 0 and the force or load score is 0. We look at the column where the four things intersect to ascertain the value of this A score.\n\nThere is a score of 4 after looking for a value for group A. Then, by combining the muscle use score and the force/load score, a final score search is performed to determine whether the operator’s posture contains a level of hazard or not. It can be made using the following formula:\n\nTherefore, Score A is 7.\n\nGroup B:\n\nMuscle Use Score\n\nWorkers who undertake permanent labor in less than 10 minutes have an RULA score of 0, with the additional score of +1 since the posture is static and repeated.\n\nForce/Load Score\n\nIf the load lifted by the workforce is greater than 50 kg – 100 kg, the RULA score is 3, while the change score is 0, because the load does not encounter a sudden increase in load.\n\nThe B score table depicts the neck, trunk, and legs positions is shown in Table 8. The blue color represents the neck at position 3, the green represents the trunk at position 3, and the yellow represents the leg at position 1. The value of this B score is calculated by where the three variables intersect.\n\nWhen a value of 4 is found after searching for a value for group B, a final score search is performed to determine whether the workers’ body posture is in a level of risk or not, by combining the muscle usage score with the force/load score, following the formula:\n\nThe Table 9 C score is the result of adding the A and B scores. The overall score of A is 4, and the total score of B is 7. As a result, the score of Table A and the score of Table B decide the column and value in group C.\n\nTable A of the RULA score table above displays the position of the upper arm, lower arm, wrist, and wrist twist, all of which receive a score of 4, in addition to the score for muscle use (1), and the load score (3), the total score A would be 8. Table B displays a score of 4 for the position of the neck, trunk, and legs, with a score of 1 for muscle use, a score of 3 for load, and a total scoreof 8 for A. The total RULA score is 7 based on the table C score, which is a composite of the outcomes of the A and B scores.\n\nAn RULA score of 7 was obtained with a high danger level and an action level of 4 after performing the calculations using the RULA worksheet. This signifies that immediate action is required. Table 10 shows the outcomes of data processing for the five cement transport personnel from day one onwards.\n\nAccording to Table 18, the average level of action experienced by the workforce is 4, indicating a high level of harm, therefore, a need for immediate action. The results of the RULA method assessment of cement transportation activities revealed that the level of risk from posture and workload in the activities performed could result in the risk of MSD injury.\n\nBased on the results of the body posture calculations by utilizing the OWAS and RULA methods in Tables 14 and 18, it is advised that transportation aid be expected to lessen the load on workers as well as the risk of MSDs for workers. The recommended assistive equipment is a traditional transportation aid made of wood and equipped with a load-bearing rope. The conveyance tool’s design is shown in Figures 8 and 9.\n\nSource: Data Collection.\n\nSource: Data Collection.\n\nWorkers can use this transport during rice transportation duties. It is believed that workers who utilize this tool will have a safe body posture based on OWAS and RULA estimates. However, there are various constraints that have an impact on the work of rice transport personnel. The following are the constraints:\n\na. The center of gravity and stability of the human body\n\nThe weight of the load carried by the rice transport employees, which ranges between 80 and 100 kg, prevents the body posture from remaining straight. Because of the weight of the loadcarried, the body posture will bend forward to prepare for absorption (Yadi, 2012).\n\nb. Regulation of the minister of manpower, transmigration and cooperatives No. PER.01/Men/1978\n\nAccording to the Regulation of the Minister of Manpower, Transmigration, and Cooperatives No. PER.01/Men/1978 concerning Occupational Health and Safety in the Field of Aviation and Wood Transport (Per.01/Men/1978, 1978), there is a legal lifting limits for workers to create a safe and healthy working environment, namely the lifting load is determined based on the calculations of 5/7 body weight. The weight of the load hoisted by the rice transport workers exceeds the predetermined limit, indicating that the impact is clearly hazardous to the workers’ health and safety. (Per.01/Men/1978, 1978).\n\nc. Mayor’s regulation No. 7 Tahun 2009 of Palembang city\n\nA review of the mayor’s regulations controlling environmental management in the vicinity of Dock 16 Ilir Palembang City, particularly Palembang City Mayor Regulation Number 7 of 2009 about the Establishment of the River Port Service Technical Implementation Unit (UPTD). Based on these regulations, it has been explained in Chapter III that the Position of the main duties and functions is contained in Article 4 that the Sungai Port UPTD has the task of carrying out some of the Transportation Service’s tasks, particularly in managing, regulating, maintaining, providing services, supervising and collecting user fees for services, and river port utilization. As a result, it is envisaged that this policy will facilitate loading and unloading activities, as well as the improvement and growth of river ports (Walikota, 2009).\n\n\nConclusions and suggestion\n\nAccording to the results of the NBM questionnaire calculation, the four rice transporters are at risk of MSDs because they have a total score of individual complaints in the range of 71–83, indicating that the risk level is at a score of 3, which is in a very high-risk category, and comprehensive action is required as soon as possible. The five cement transport employees were also at danger of MSDs since they had a total score of individual complaints in the range of 63–84, indicating that the risk level was at a score of 3, as such complete action is required as soon as feasible.\n\nBased on the results of the workers’ posture and workload calculation on the activities of receiving rice, transporting rice, and laying rice from day 1 to day 6, an OWAS score of 3-4 is obtained, which is included in the high to very high risk category, so that the results of the assessment of rice transportation activities using OWAS are obtained. MSDs may be injured as a result of this action. While calculating work posture and workload on 5 cement transportation workers using RULA, it was discovered that workers 1 to 5 received an RULA score of 7, which is included in the action level 4 with high risk level, thus action is required as soon as feasible. The assessment of cement transportation activities using RULA also revealed that the level of risk from posture and workload in the activities performed could result in MSD injury. The transport tools’ design is projected to lower the risk of MSDs but not totally remove it because there are numerous restrictions that effect the results of the rice transport workers.\n\n\nData availability\n\nFigshare: Data Base NBM, RULA, OWAS. https://doi.org/10.6084/m9.figshare.19545670.v1.\n\nThis project contains the following underlying data:\n\nData 1 eng.docx. (NBM data dan OWAS.)\n\nData 2 eng.docx. (NBM data and RULA.)\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver Attribution 4.0 International (CC BY 4.0).\n\n\nAuthor contributions\n\nChristofora Desi Kusmindari: Conceptualization, Formal Analysis, Methodology, Data Curation, and Writing – Review & Editing\n\nPoppy Indriani: Project Aministration\n\nHaritz Nu’man:Methodology, Validation\n\nSalma Mutiamuthmainah: Data Curation,, Formal Analysis, and Writing – Original Draft Preparation\n\nIra Erina: Data Curation, i, Formal Analysis, and Writing – Original Draft Preparation", "appendix": "Acknowledgments\n\nThanks for Iqbal Ramdhani, English Department, Universitas Bina Darma\n\n\nReferences\n\nBintang AN, Dewi SK: Analisa Postur Kerja Menggunakan Metode OWAS dan RULA. Jurnal Teknik Industri. 2017; 18(1): 43. Publisher Full Text\n\nBudiman E, Setyaningrum R: Perbandingan Metode-metode Biomekanika untuk Menganalisis Postur pada Aktivitas Manual Material Handling (MMH). 2006; 46–52.\n\nDewi NF: Identifikasi Risiko Ergonomi dengan Metode Nordic Body Map Terhadap Perawat Poli RS X. Jurnal Sosial Humaniora Terapan. 2020; 2(2): 125–134. Publisher Full Text\n\nEl Ahmady RF, Martini S, Kusnayat A: Penerapan Metode Ergonomic Function Deployment Dalam Perancangan Alat Bantu Untuk Menurunkan Balok Kayu. Jisi: Jurnal Integrasi Sistem Industri. 2020; 7(1): 21–30.\n\nFactsheet 4 - Preventing Work-Related Musculoskeletal Disorders\|Safety and health at work EU-OSHA:n.d.Retrieved March 26, 2022. Reference Source\n\nFitri M, Laila W: KAJIAN PERBAIKAN POSTUR KERJA DENGAN METODE OWAS (OVAKO WORKING POSTURE ANALYSIS SYSTEM) (Studi Kasus di Pabrik Roti Cimpago Putih). Jurnal Sains Dan Teknologi: Jurnal Keilmuan Dan Aplikasi Teknologi Industri. 2017; 17(2): 138. Publisher Full Text\n\nGómez-Galán M, Callejón-Ferre ÁJ, Pérez-Alonso J, et al.: Musculoskeletal risks: RULA bibliometric review. International Journal of Environmental Research and Public Health. 2020; 17(12). PubMed Abstract \| Publisher Full Text\n\nKusminadri CHD, Tian M: Perancangan Sistem Kerja Bagian Pengelasan dengan Metode Rapid Entire Body Assesment. November. 2021; 185–191.\n\nKusmindari CHD, Melita D, Putra FR, et al.: Evaluasi Postur Kerja pada Proses Pengangkatan Semen dengan Menggunakan Metode Ovako Working Analysis System (OWAS) (Studi Kasus PT. Semen Baturaja Palembang) Bina Darma Conference on Engineering Science 2. Bina Darma Conference on Engineering Science. 2020; 2(1): 231–237.\n\nNur RF, Lestari ER, Mustaniroh SA: Analisis Postur Kerja pada Stasiun Pemanenan Tebu dengan Metode OWAS dan REBA, Studi Kasus di PG Kebon Agung, Malang. Teknologi Dan Manajemen Agroindustri. 2016; 5(1): 39–45. Per.01/men/1978. (1978). 1–10.\n\nPurnomo AJ, Umam UK, El Ahmady RF, et al.: Desain Troli Ergonomis sebagai Alat Angkut Gas LPG. IOP Conference Series: Materials Science and Engineering. 2010; 16(1): 131–140. Publisher Full Text\n\nPurwaningsih DPR: ERGONOMIC ASSESSMENT DI PT PERKEBUNAN TAMBI MENGGUNAKAN TOOLS OWAS, RULA, DAN REBA (Studi Kasus di unit perkebunan Tanjungsari) Dyah Priamsari , Ratna Purwaningsih * Program Studi Teknik Industri, Fakultas Teknik, Universitas Diponegoro Dyah.priam. 2016; 1–8.\n\nPutri NT, Amrina E, Fatrias D, et al.: Ergonomic Evaluation on Chicken Feeder Tool at Egg-Laying Chicken Farm SME. Jurnal Optimasi Sistem Industri. 2021; 20(1): 52–60. Publisher Full Text\n\nRestuputri DP, Primadi ES, Lukman M: Analisa Postur Kerja terhadap Aktivitas Manual Material Handling Menggunakan Metode OWAS. Seminar Nasional Teknologi Dan Rekayasa (SENTRA). 2017; 1–8.\n\nTiogana V, Hartono N: Analisis Postur Kerja dengan Menggunakan REBA dan RULA di PT X. Journal of Integrated System. 2020; 3(1): 9–25. Publisher Full Text\n\nWadhikh MK: ANALISA POSTUR KERJA OPERATOR REWORK DENGAN PENDEKATAN METODE OWAS DAN RULA DI PT. JEBE KOKO INDONESIA. 2019.\n\nWahyudi MA, Dania WAP, Silalahi RLR: Work Posture Analysis of Manual Material Handling Using OWAS Method. Agriculture and Agricultural Science Procedia. 2015; 3: 195–199. Publisher Full Text\n\nWalikota P: PERATURAN DAERAH KOTA PALEMBANG NOMOR 07 TAHUN 2009 TENTANG KAWASAN TANPA ROKOK DENGAN RAHMAT TUHAN YANG MAHA ESA WALIKOTA PALEMBANG. 2009; (Issue 57).\n\nWidiana DR, Ramana IA, Handoko L: Penilaian Postur Kerja Menggunakan Rapid Entire Body Assessment dan Perancangan Fasilitas Kerja pada Stasiun Kerja Press di Perusahaan Coco fiber. Jurnal IPTEK. 2021; 25(1): 59–68. Publisher Full Text\n\nYadi S: Titik Berat Dan Stabilitas (Center of Gravity and Stability).2012.\n\nوآخرون, م. ص. ا: No Titleمقدمة في الأعمال في عصر التكنولوجيا 2004; 303." }	[ { "id": "156606", "date": "07 Dec 2022", "name": "Rahul Jain", "expertise": [ "Reviewer Expertise Ergonomics", "Manufacturing system design", "Product development", "Industrial design", "Posture biomechanics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThanks for giving me opportunity of reading this article. I have few suggestions for improvement as given below:\n1. Generally, your introduction section needs to be substantially revised, as you failed to establish the fundamental rationale of your study. You should describe clearly what previous studies found (specifically manual working scenario), what limitations they had, then you can identify the research gap. Why were you interested in investigating it?\n2. How was the questionnaire developed? Neither justification of various items nor any supporting literature is provided. Like from where is the questionnaire developed?\n3. Some of the tables are not present in the article such as Tables 14-18.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "9417", "date": "17 Nov 2023", "name": "Christofora Desi", "role": "Author Response", "response": "Reviewer says: Some of the tables are not present in the article such as Tables 14-18. Answer: this table just for references for other researcher but if is necessary I will present it." } ] }, { "id": "242161", "date": "05 Feb 2024", "name": "Ziyang Xie", "expertise": [ "Reviewer Expertise Ergonomics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article utilizes a mixed-methods approach, including RULA and OWAS, to assess the risk level of workers under high workloads. Overall, the research is meaningful and may greatly impact workplace safety. However, there are also some points need to be addressed:\n\nFormatting and Readability: The manuscript should undergo thorough proofreading to correct formatting inconsistencies, including indents and missing spaces, to enhance readability. Claims Moderation: The claim that \"The industrial world is rapidly evolving and totally automated\" may be too absolute. A more nuanced term like \"increasingly automated\" would be more accurate and reflective of the current industrial landscape. Language Specificity: Terms like \"operate smoothly\" are too vague. Please describe with more specific words. Clarity in Data Presentation: The significance of numeric values in Table 1 needs clarification. The caption should explicitly state the scale used and its relevance to fatiguelessness. Sample Size Justification: The article's sample size appears limited. A justification for this choice and the potential inclusion of a standard 7-level questionnaire for enhanced data reliability and analysis should be considered. Literature Review Expansion: A broader literature review would better situate the study within the existing body of research, particularly focusing on recent studies that contextualize the investigation's relevance. Methodological Detail Enhancement: Detailed descriptions of the methodologies used, including data collection and analysis methods, are necessary for reproducibility and critical assessment by peers. Statistical Analysis Depth: The manuscript would benefit from a deeper explanation of the statistical analysis, including the rationale for method selection and the significance of findings. Discussion of Limitations: A thorough discussion on the study's limitations and their potential impact on the findings would provide a balanced and comprehensive view of the research. Directions for Future Research: The conclusion should offer clear directions for future research, identifying gaps in the current study and suggesting how the research could be extended or refined.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNot applicable\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "242180", "date": "12 Feb 2024", "name": "Philippe Gorce", "expertise": [ "Reviewer Expertise Musculoskeletal disorders", "WRMSD", "Biomechanics", "Ergonomics", "Musculoskeletal Modeling MSD risk Work", "Occupational Health and Disease", "Industrial Ergonomics", "Safety", "Disability", "Rehabilitation", "Sport Biomechanics Surgery", "Occupational Health", "Meta-Analysis", "Meta-Regression", "Gait Analysis", "Posture and Balance", "Computational Biomechanics 3D Modeling", "Motion Capture", "Motion Analysis" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe aim of this study is to quantify the workload and provide a design tool to help lessen worker concerns. The Nordic Body Map, Rapid Upper Limb Assessment (RULA), and Ovako Working Analysis System (OWAS) methodologies were used in this investigation. The study's findings showed that the five cement transport workers and four rice transport workers were at risk of developing musculoskeletal illnesses, with a risk level of 3 to 4, indicating that the risk category is very high and comprehensive treatment is required as soon as feasible. The theme of the proposed article is interesting, but the article needs to be rewritten with a clear objective and hypothesis. The references to international works are insufficient and should be improved in the \"introduction\" and \"discussion\" sections. The method should be detailed, and the choices argued. The results should be presented synthetically, with relevant numerical values, so that the reader can assess the contribution and interest of the proposed work. The discussion should be rewritten, and a limitation section added. Here are a few remarks and recommendations to improve the article:\n\nThe objective of the article is difficult to identify: is it the use of the OWAS and RULA assessment tools? Is it the evaluation of MSD risks with and without the \"backpack\"? etc. The authors must propose a clear objective with a hypothesis. The sample studied was very small (five cement transporters and four rice transporters), which severely limits the scope of the work presented and therefore the generalizability of the results proposed. No information on posture characterization. How are joint angles defined? What measurement systems are used? What method is used? How do the authors go from an activity, i.e. a movement, to a few postures? detailed and developed. There is little or no information on the Nordic Body Map questionnaire. Why did you choose OWAS and RULA to assess MSD risk? Justify this choice in relation to other existing tools. The authors try to propose a solution to reduce the risk of RSI. Why not compare subjects with and without backpack use? Such a comparison would have increased the scientific interest of the article.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-788
https://f1000research.com/articles/11-787/v1	13 Jul 22	{ "type": "Case Report", "title": "Case Report: Synchronous bilateral lipoma arborescens of the bicipitoradial bursa", "authors": [ "Rafik Elafram", "Majdi Ben Romdhane", "Nayssem Khessairi", "Ahmed Hamdi", "Majdi Ben Romdhane", "Nayssem Khessairi", "Ahmed Hamdi" ], "abstract": "Background: Lipoma arborescens (LA) is an infrequent benign tumor made of mature sub-synovial fatty cell proliferation that may arise into the synovial joint, the bursae or the tendon sheaths. This condition affects mainly the knee joint, but the bicipitoradial bursa is an exceptional location. We report herein a case of a synchronous bilateral (LA) of the bicipitoradial bursa. Case presentation: A 52-year-old patient, with no medical history, presented with a swelling of both front arms that had been progressing for nine years. Physical examination showed a mass in the antecubital fossae of 3cm on the left side and 0.5cm on the right side. Both masses were tender, well-defined, fixed, without inflammatory signs and painful on elbow flexion. A magnetic resonance imaging (MRI) scan was performed, revealing the presence of a septate soft-tissue mass of the distal portion of the brachial muscle of 70x46x27mm. This mass had a heterogeneous fat signal in its depth and a homogeneous fat composition on the outside. The diagnosis of liposarcoma was suspected. The patient underwent surgery to remove both masses. Gross examination showed a characteristic frond-like or digitiform pattern. Microscopical examination demonstrated papillary proliferation of the synovial villi. The final diagnosis was of LA. The patient had no complications and there was no recurrence of LA. Conclusions: LA is a rare condition, and the bicipitoradial bursa is an exceptional location. Histological confirmation is mandatory to correct the diagnosis.", "keywords": [ "benign", "joint masses", "lipoma arborescens" ], "content": "Introduction\n\nLipoma arborescens (LA) is an infrequent benign tumor made of mature sub-synovial fatty cell proliferation that may arise into the synovial joint, the bursae or the tendon sheaths.1 Its name comes from arbo meaning tree, which describes the frond-line gross aspect of the mass.2 It can also be named villous lipomatous proliferation of the synovial membrane thus indicating it’s non-neoplastic nature.3 This condition affects mainly the knee joint, but the bicipitoradial bursa is an exceptional location.1\n\nWe herein report a case of a synchronous bilateral (LA) of the bicipitoradial bursa. Extra or periarticular location of LA such as in our case in the bicipitoradial bursa are exceptional localization with few cases in the literature.\n\n\nCase presentation\n\nA 52-year-old Caucasian male patient (occupation, policeman), with no medical history, presented with swelling of both front arms associated with cramps and pain irradiating to the shoulders, which had been developing for nine years.\n\nThere was no history of fever or weight loss nor traumatic accident. Physical examination showed a mass in the antecubital fossae of 3 cm on the left side and 0.5 cm on the right side. Both masses were tender, well-defined, fixed, without inflammatory signs and painful on elbow flexion. Ultrasound scan showed a fusiform under-aponeurotic intramuscular mass with lobulated edges, encasing the median nerve.\n\nThis aspect corresponded to a fibrolipoma of the median nerve without vascularization. A magnetic resonance imaging (MRI) scan was performed, revealing the presence of a septate soft-tissue mass of the distal portion of the brachial muscle of 70×46×27 mm (Figure 1). This mass had a heterogeneous fat signal in its depth and a homogeneous fat composition on the outside. It was adjacent to the humerus and invaded the posterior cortical bone. These features led us to conclude the diagnosis of a liposarcoma. The patient had a biopsy of the left antecubital fossa. The histopathology concluded to a well-differentiated adipocytic tumor. The patient underwent surgery to remove both masses with complete removal of the tumors with no harm to the nervous system structure. Gross examination showed a characteristic frond-like or digitiform pattern. Microscopical examination demonstrated papillary proliferation of the synovial villi (Figure 2 and Figure 3). These villi were covered by hyperplastic inflamed synovium with adipocyte axis, made of mature fatty cells and fine fibrovascular septa (Figure 4 and Figure 5). The final histopathological examination confirmed the diagnosis of LA. The biopsy was not sufficient to confirm the diagnosis.\n\nSynovial villi enlarged by abundant mature adipocytes. Note the variable degrees of fatty infiltration of the subsynovial tissues (hematoxylin and eosin (HE); magnification, ×40).\n\nSynovial villi enlarged by abundant mature adipocytes. Note the variable degrees of fatty infiltration of the subsynovial tissues (hematoxylin and eosin (HE); magnification, ×40).\n\nThe synovial layer is only a few cells with substitution of subsynovial tissue by mature adipocytes (hematoxylin and eosin (HE); magnification, ×200).\n\nCapillaries and small amounts of chronic inflammatory cells are present (hematoxylin and eosin (HE); magnification, ×400).\n\nThe post-operative follow-up over two years remained simple and quasi painless. The definitive histopathological examination of both masses led to the diagnosis of LA.\n\n\nDiscussion\n\nFirst described by Albert Hoffa in 1904, the incidence of LA is still unknown. Only a few cases have been reported in the literature.4 In the reported cases, the ages range between 9 and 68 years old with no affinity for either sex.5,6 Two types of LA have been described: primary and secondary, regarding to the age and the existence of associated conditions. The primary type occurs mainly in young patients during the first two decades of life and is idiopathic. Otherwise, the secondary type usually occurs in elderly patients and is associated with existing chronic damage such as degenerative disease, trauma, meniscal or synovial injury. This type is more commonly found.7,8\n\nLA is frequently observed in the knee, but can be described in the hips, shoulders, wrist, or elbow. The lesion mostly affects a single joint, but in some patients, it may be found in polyarticular form. Extra or periarticular location of LA such as in our case in the bicipitoradial bursa has rarely been reported.9,10 Howe and Wenger have suggested that LA is divided into two groups: typical presentation (unilateral knee involvement) and atypical presentation (polyarticular LA and outside of the typical location of the knee).10 Nevertheless, there was no significant difference in age of diagnosis, presence of degenerative or inflammatory arthritis between the typical and atypical presentations.10 The etiology of LA is still unknown. Some hypotheses suggest that LA may appear in joints with chronic inflammation leading to proliferation and hypertrophy of the synovial membrane with subsequent adipose differentiation. The existence of a specific vulnerability of the sub-synovial fatty tissue has also been noted.9,11 The role of steroid injections and diabetes has also been investigated.2 Patients with LA usually present with painless joint swelling.8 Some patients complain of an intermittent pain that can be attributed to the enclosure of the expanded joint villi.11 The bicipitoradial bursa is situated between the distal tendon of the biceps brachii muscle and the anterior part of the tuberosity of the radius. It totally or partially surrounds the biceps tendon.\n\nWith pronation, the radius tuberosity rotates posteriorly, inducing a compression of the bursa between the tuberosity and the biceps tendon. If inflamed or distended, the bursa may cause an enclosure of the radial and the median nerves. By its localization, the bicipitoradial bursa is subject to pressure, which can explain the emergence of LA. Furthermore, the role of abnormal hypertrophy of the radial tuberosity has been described as increasing micro-trauma in high pressure areas, explaining the occurrence of LA in the bicipitoradial bursa.1,8\n\nIn LA, results of laboratory tests, such as rheumatoid factors, uric acid, C-reactive protein and erythrocyte sedimentation rate, are normal. Arthroscopy in the affected joint can reveal a yellow-white hypertrophied synovium with adipocytic villi projections into the joint space.8,12,13 Conventional radiographs have a limited value in this case, they only show nonspecific findings as in some cases articular soft tissue density is associated with signs of arthrosis.7 LA appears on ultrasonography as a high echo pattern comparable with the adjacent subcutaneous adipocytic tissue. The consistency of the mass is mainly smooth and expandable. Ultrasonography is useful in detecting the localization and size of LA.3 In our case, the ultrasonography imaging concluded to a fibro lipoma of the median nerve. Since the invention of MRI, diagnostic accuracy has increased.11,13\n\nLA usually presents as nodular or villous sites in hypersignal on T1 and T2 sequences that are erased on the short tau inversion recovery (STIR) or fat saturation sequences. The residual non-fatty component of the enlarged synovium in the condition shows heterogeneous hypersignals in T2 and STIR sequences and hypo signals or intermediate signals in T1 sequences.7 However, in our case, the MRI findings were not unequivocal, and we were oriented to a neoplastic lesion. In fact, sometimes the imaging may imitate a well-diffracted liposarcoma (WDL). In cases of WDL, we can find a mostly adipose mass with an irregularly thickened nodular septa.14 Most soft-tissue tumors can also manifest as neoplastic lesions. The decision of surgery is made if a tumor significantly grows in size or becomes symptomatic.15\n\nIf preoperative investigations cannot firmly assess the benign, low-grade malignant or high-grade malignant nature of the lipomatous mass, then it is recommended that the patient undergoes a biopsy and two-stage removal of the tumor.16 The gold standard treatment of LA is surgical excision. For LA, occurring in joints, arthroscopic synovectomy and open resection are the main interventions with identical results to open surgery and low recurrence rates.17 Histopathological examination eventually confirmed the diagnosis of LA. Indeed, it presents as a fatty-mass with a finger-like or ramified villous proliferation.18 Histologically, there is a synovial hyperplasia with scattered chronic inflammatory cells and extensive shedding of mature fat cells in the sub synovial tissue.9,18\n\nThe fat cells are assisted by nourishing blood vessels and are overlayed by multiple synovial cells layers. Synovium responds to the irritation by increasing capillary blood flow, which lead to an influx of inflammatory cells, and synovial hyperproliferation. As this becomes chronic, adipocytes can also infiltrate the sub synovial tissue.8\n\n\nConclusions\n\nLA is a rare condition and an infrequent cause of joint masses. The bicipitoradial bursa is an exceptional location. This entity has characteristic features, but radiological examination may miss the diagnosis especially in atypical locations. Recognizing the clinical and imaging findings is necessary to avoid misdiagnosing this condition.\n\n\nData availability\n\nAll data underlying the results are available as part of the article and no additional source data are required.\n\n\nConsent\n\nWritten informed consent for publication of their clinical details and clinical images was obtained from the patient.", "appendix": "References\n\nKord Valeshabad A, De La Vara D, Shamim E, et al.: Lipoma arborescens of the bicipitoradial bursa. Skelet. Radiol. 2017; 47(4): 549–551. PubMed Abstract \| Publisher Full Text\n\nGil Hecht G, Hopkins JN, Lum ZC, et al.: Bilateral lipoma arborescens -A proliferative case demonstrating progression in an adolescent male. J. Orthop. 2018; 15: 736–740. PubMed Abstract \| Publisher Full Text\n\nHallel T, Lew S, Bansal M: Villous lipomatous proliferation of the synovial membrane (lipoma arborescens). J. Bone Joint Surg. Am. 1988 Feb; 70(2): 264–270. PubMed Abstract \| Publisher Full Text\n\nWang C, Alfayez S, Marwan Y, et al.: Knee Arthroscopy for the Treatment of Lipoma Arborescens. JBJS Reviews. 2019; 7(4): e8–e8. PubMed Abstract \| Publisher Full Text\n\nKulkarni HG, Kulkarni GS, Kulkarni PG: Lipoma Arborescens - Eyes See What Mind Knows! J. Orthop. Case Rep. 2017 Sep-Oct; 7(5): 59–62. PubMed Abstract \| Publisher Full Text\n\nFornaciari P, Schai PA, Kurrer MO, et al.: Arthroscopic Synovectomy in Bilateral Lipoma Arborescens. J. Orthop. Case Rep. 2016 Nov-Dec; 6(5): 7–13. PubMed Abstract \| Publisher Full Text\n\nMohammad HR, Chaturvedi A, Peach C: An unusual case of lipoma arborescens. Ann. R. Coll. Surg. Engl. 2016 Sep; 98(7): e126–e129. PubMed Abstract \| Publisher Full Text\n\nSanamandra SK, Ong KO: Lipoma arborescens. Singap. Med. J. 2014 Jan; 55(1): 5–10; quiz 11. PubMed Abstract \| Publisher Full Text\n\nSchubert T, Navez M, Galant C, et al.: Femoral osteochondroma responsible for ischiofemoral impingement, bursitis, and secondary lipoma arborescens mimicking malignant transformation. Acta Radiol. Open. 2019 Dec 11; 8(12): 2058460119892409. PubMed Abstract \| Publisher Full Text\n\nHowe BM, Wenger DE: Lipoma arborescens: comparison of typical and atypical disease presentations. Clin. Radiol. 2013 Dec; 68(12): 1220–1226. PubMed Abstract \| Publisher Full Text\n\nChander B, Awasthi B, Preet K: Synchronous Lipoma arborescens of bilateral wrist: An extremely rare manifestation and a new perspective on etiopathogenesis. J. Cancer Res. Ther. 2015 Jul-Sep; 11(3): 646. PubMed Abstract \| Publisher Full Text\n\nKalia V, Daher O, Garvin G, et al.: Synchronous bilateral lipoma arborescens of bicipitoradial bursa-a rare entity. Skelet. Radiol. 2018 Oct; 47(10): 1425–1429. PubMed Abstract \| Publisher Full Text\n\nDinauer P, Bojescul JA, Kaplan KJ, et al.: Bilateral lipoma arborescens of the bicipitoradial bursa. Skelet. Radiol. 2002; 31: 661–665. PubMed Abstract \| Publisher Full Text\n\nMinami S, Miyake Y, Kinoshita H: Lipoma arborescens arising in the extra-articular bursa of the knee joint. SICOT J. 2016; 2: 28. PubMed Abstract \| Publisher Full Text\n\nLevadoux L, Gadea J, Flandrin P, et al.: Lipoma arborescens of the elbow: a case report. J. Hand Surg. Am. 2000 May; 25(3): 580–584. PubMed Abstract \| Publisher Full Text\n\nDoyle AJ, Miller MV, French GJ: Lipoma arborescens in the bicipital bursa of the elbow: MRI findings in two cases. Skelet. Radiol. 2002; 31: 656–660. PubMed Abstract \| Publisher Full Text\n\nHauptfleisch J, English C, Murphy D: Elbow magnetic resonance imaging: imaging anatomy and evaluation. Top. Magn. Reson. Imaging 2015 Apr; 24(2): 93–107. Publisher Full Text\n\nGarnaoui H, Rahmi A, Messoudi A, et al.: Intra-articular lipoma arborescens of the knee: A report of two cases with bilateral localization. Int. J. Surg. Case Rep. 2018; 51: 224–227. PubMed Abstract \| Publisher Full Text" }	[ { "id": "144562", "date": "08 Aug 2022", "name": "Reetu Kundu", "expertise": [ "Reviewer Expertise Cytology and Gynecological Pathology" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors have described a rare entity. The report of a case of a synchronous bilateral lipoma arborescens of the bicipitoradial is uncommon. The bicipitoradial bursa is indeed an exceptional location. As pointed out recognizing the clinical and imaging findings is necessary to avoid misdiagnosing this condition. One suggestion is to improve the contrast for Figures 2 and 3.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "246715", "date": "01 Mar 2024", "name": "Samuel Navarro", "expertise": [ "Reviewer Expertise Pathology of bone and soft tissue. Pediatric Pathology: tumoral." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nInteresting case of an atypical lesion, bilateral and located in an unusual site. Arborescens lipoma is a well recognized clinico-pathological entity, maily found in the knee joint.. This teaching case reveals the importance of clinico-radiological approach ( discarding malignancies such as liposarcoma), and the mandatory confirmation with pathological analysis.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] }, { "id": "246639", "date": "21 Mar 2024", "name": "Sam Sedaghat", "expertise": [ "Reviewer Expertise MSK", "soft tissue sarcoma" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis case report deals with a rare lipoma arborescence in the bicipitoradial bursa. Due to the rarity of this finding in an exceptional location, this case report is very interesting to a broad readership. I would advise the authors to perform a minor revision. My comment targets the main appearance and configuration of the tumor. As shown in Figure 1, the tumor has a lobulated configuration. Would be interesting to mention in the discussion that in future studies the main appearance and configuration of this tumor could be investigated and please cite the following two paper:[1],[2]. Although these papers mention soft tissue sarcoma, they show the importance of investigating the main appearance/configuration of benign and malignant soft tissue masses.\n\nDetermining the configuration of such tumors is a quite novel approach. Therefore, these two papers are interesting for that approach I requested to add for further studies.\n\nIs the background of the case’s history and progression described in sufficient detail? Yes\n\nAre enough details provided of any physical examination and diagnostic tests, treatment given and outcomes? Yes\n\nIs sufficient discussion included of the importance of the findings and their relevance to future understanding of disease processes, diagnosis or treatment? Yes\n\nIs the case presented with sufficient detail to be useful for other practitioners? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-787
https://f1000research.com/articles/11-642/v1	13 Jun 22	{ "type": "Opinion Article", "title": "\"Acute Kidney Injury predictive models: advanced yet far from application in resource-constrained settings.\"", "authors": [ "Busisiwe Mrara", "Fathima Paruk", "Olanrewaju Oladimeji", "Fathima Paruk", "Olanrewaju Oladimeji" ], "abstract": "Acute kidney injury (AKI) remains a major cause of morbidity and mortality in hospitalized patients, particularly critically ill patients. It poses a public health challenge in resource-constrained settings due to high administrative costs. AKI is commonly misdiagnosed due to its painless onset and late disruption of serum creatinine, which is the gold standard biomarker for AKI diagnosis. There is increasing research into the use of early biomarkers and the development of predictive models for early AKI diagnosis using clinical, laboratory, and imaging data. This field note provides insight into the challenges of using available AKI prediction models in resource-constrained environments, as well as perspectives that practitioners in these settings may find useful", "keywords": [ "Acute Kidney Injury", "predictive models", "resource-constrained settings" ], "content": "Background\n\nAcute kidney injury (AKI) epidemiology in low-resource settings is underreported due to difficulties with paper-based reporting and diagnosis confirmation due to limited access to laboratory testing. This has been identified as one of the barriers to the advancement of global initiatives aimed at eliminating preventable AKI deaths by 2025.1 Furthermore, epidemiologic research on the development of predictive models of AKI in resource-limited settings is lacking; the few publications on the subject are validations of models developed in well-resourced countries.\n\nSeveral predictive models for the early prediction of AKI in critically ill patients have been developed, utilizing patient data available in intensive care units (ICUs) and, more recently, machine-learning algorithms.2,3 The silent and delayed onset of AKI makes early intervention and management difficult, resulting in the progression to dialysis-requiring renal impairment and chronic kidney disease, which is an unaffordable cost in resource-constrained healthcare systems. It is hoped that early detection will allow for interventions such as reducing the impact of nephrotoxic drugs and fluid titration.\n\nMost AKI prediction models have been developed with predictors based on susceptibilities like chronic comorbidities and exposures such as surgical procedures and sepsis. These models had variable performance in the early prediction of AKI; however, their combination with biomarkers improved their predictive performance and focused biomarker use on patients with a high pre-test probability of AKI, thus streamlining biomarker use in the determination of AKI risk.4,5\n\n\nChallenges with models’ application in resource-constrained settings\n\nDespite these advances, some models have been criticized for methodological flaws such as using creatinine as both a predictor and an outcome, having low rates of AKI in the development cohort, using single-centre data, and lacking validation.6 Furthermore, there is limited data on the models’ use for the intended purpose of directing interventions to prevent further kidney injury, presumably due to difficulties with the models’ multiple variables. The models predict AKI up to 24 hours ahead of time, a short timeframe that may allow for changes in medication and fluid prescription but is unlikely to have a significant impact on an already evolving injury process.\n\nThe published models integrated into health information systems with electronic alerts have not consistently demonstrated appreciable effects on AKI outcomes.3 Electronic health records are prohibitively expensive in resource-constrained settings. The application of AKI bundle interventions has yielded mixed results in terms of benefit in reducing AKI rates,7,8 with even less evidence of benefit from individual interventions such as avoidance of nephrotoxins and overzealous fluid resuscitation, raising the possibility of heightened awareness and improved care quality as the reason for improvement rather than the interdependence of the interventions.\n\nFor various concerns, the applicability of currently available predictive models in low-resource contexts remains debatable and needs to be refined. Patients in low-resource settings are frequently sicker (due to delayed presentation, limited access to health care or ICU, or both), younger, and have comorbid communicable diseases. Advanced HIV-related illnesses are common, which may influence the occurrence and complications of AKI. HIV is a significant AKI predictor that should be investigated in AKI predictive models for developing countries. The prevalence of HIV in South Africa is as high as 21% in some areas,9 compared to 5% in the USA, where some of the AKI risk models were developed.\n\nAdditionally, HIV illness is comparatively more severe due to late presentation and regulated antiretroviral treatment initiation. Hence, research into HIV as a risk factor and its impact on AKI development in patients with severe acute illness requiring ICU admission is critical. Several researchers have identified HIV infection as an independent risk factor for AKI10; the risk is associated with HIV progression as measured by CD4 count and viral load, tenofovir disoproxil fumarate treatment, and hepatitis C co-infection. Other risk factors include the use of herbal and traditional medications with unknown nephrotoxic potential, as well as the high prevalence of infectious disease, traumatic injuries, and pregnancy-related hypertensive disorders. The disparities in AKI epidemiology and causation between high and low-income settings may also be influenced by health-care quality, which is linked to healthcare funding. As a result, the participants and predictors used to develop AKI prediction models in high-income settings are theoretically distinct from those prevalent in resource-constrained settings.\n\nFurthermore, because the impact and practicability of these predictive tools in high-income settings has not been thoroughly studied, models that are simple to use and incorporate concrete actions to prevent AKI would be advantageous. The cost of the biomarkers, including importation and implementation with specialized laboratory equipment and expertise, is also a barrier to implementation in resource-constrained settings where basic laboratory tests such as 24-hour serum creatinine are difficult to achieve.\n\n\nConclusion\n\nWhile AKI predictive modelling in high-income health systems is rapidly evolving, lower-income health systems should carefully consider the applicability and costs of these models in resource-constrained settings, unless the resources are abundant. Otherwise, most resource-constrained settings should concentrate on raising awareness about AKI risk, meticulous patient monitoring, careful drug and fluid prescription practice, and general measures to improve health care quality, which is all that is currently feasible.\n\n\nAuthor contributions\n\nBM and OO initiated discussion of the idea; BM and OO created the first draft. BM, OO, and FP critically reviewed and approved this final version.\n\n\nData availability\n\nNo data are associated with this article.", "appendix": "References\n\nAnand S, Cruz DN, Finkelstein FO: Understanding acute kidney injury in low resource settings: a step forward. BMC Nephrol. 2015; 16: 5. PubMed Abstract \| Publisher Full Text\n\nBasu RK, Kaddourah A, Goldstein SL: Assessment of a renal angina index for prediction of severe acute kidney injury in critically ill children: a multicentre, multinational, prospective observational study. Lancet Child Adolesc Health. 2018; 2(2): 112–120. PubMed Abstract \| Publisher Full Text\n\nFlechet M, Falini S, Bonetti C, et al.: Machine learning versus physicians’ prediction of acute kidney injury in critically ill adults: prospective evaluation of the AKI predictor. Crit Care 2019; 23(1): 282. PubMed Abstract \| Publisher Full Text\n\nJoannidis M, Forni LG, Haase M, et al.: Use of Cell Cycle Arrest Biomarkers in Conjunction with Classical Markers of Acute Kidney Injury. Crit Care Med. 2019; 47(10): e820–e826. PubMed Abstract \| Publisher Full Text\n\nKellum JA, Ronco C, Bellomo R: Conceptual advances and evolving terminology in acute kidney disease. Nat Rev Nephrol. 2021 Jul; 17(7): 493–502. PubMed Abstract \| Publisher Full Text\n\nNeyra JA, Leaf DE: Risk Prediction Models for Acute Kidney Injury in Critically Ill Patients: Opus in Progressu. Nephron. 2018; 140(2): 99–104. PubMed Abstract \| Publisher Full Text\n\nDoyle JF, Sarnowski A, Saadat F, et al.: Does the Implementation of a Quality Improvement Care Bundle Reduce the Incidence of Acute Kidney Injury in Patients Undergoing Emergency Laparotomy? J Clin Med. 2019; 8(8) PubMed Abstract \| Publisher Full Text\n\nMeersch M, Schmidt C, Hoffmeier A, et al.: Prevention of cardiac surgery-associated AKI by implementing the KDIGO guidelines in high-risk patients identified by biomarkers: the PrevAKI randomized controlled trial. Intensive Care Med. 2017; 43(11): 1551–1561. PubMed Abstract \| Publisher Full Text\n\nGutreuter SI, Igumbor E, Wabiri N, et al.: Improving estimates of district HIV prevalence and burden in South Africa using small area estimation techniques. PLOS One. 2019; 14(2): e0212445. PubMed Abstract \| Publisher Full Text\n\nWearne N, Hung R, Bohmer R, et al.: kidney disease in Africans with HIV and tuberculosis. AIDS. 2019; 33(7): 1207–1213. PubMed Abstract \| Publisher Full Text" }	[ { "id": "140612", "date": "22 Jun 2022", "name": "Jeffrey Lipman", "expertise": [ "Reviewer Expertise Intensive Care" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a nice description of the problems of Acute Kidney Injury (AKI) prediction models. As the authors state, AKI is not an uncommon phenomenon in ICU and potentially its prediction could be used to mitigate the consequences of AKI.\nCreatinine is the common biomarker used for kidney function and hence used in the diagnosis of AKI. Its problems in kidney injury are commonly known, a crude marker with a delayed response – today’s creatinine is yesterday’s renal function. In this opinion piece, the authors quite correctly point out the problems of using creatinine in the prediction of AKI, both from the point of view of its delayed response and that it is used in the prediction and the outcome of AKI.\nI have merely one comment - the authors are from South Africa which could be described as a low-income/low-resource setting/region (accepted). In South Africa, there is a large HIV \"burden\". This may not be so in all similar low-resource regions. The authors link low resources with HIV infections – I would suggest this not to be the case and the authors should “delink” the two issues. Sure bring up the problems of HIV and kidney involvement, but separate the two issues for this manuscript.\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nAre arguments sufficiently supported by evidence from the published literature? Partly\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Partly", "responses": [ { "c_id": "8487", "date": "13 Jul 2022", "name": "busisiwe Mrara", "role": "Author Response", "response": "Thank you for sharing your insights. It is correct that the prevalence of HIV is not directly linked to low-resource environments, and is not high in some low and middle-income countries. The problem we would like to emphasise is the advanced presentation of HIV in settings where health care access is inadequate and the consequent possible impact on the occurrence of Acute Kidney Injury." } ] }, { "id": "140611", "date": "30 Jun 2022", "name": "Nolubabalo Unati Nqebelele", "expertise": [ "Reviewer Expertise Nephrology", "Chronic kidney disease", "Acute Kidney disease" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a clearly articulated opinion article on the challenges encountered with the use of AKI predictive models in resource-constrained settings. These models have gained popularity and are rapidly evolving in well-resourced environments. The authors discuss the challenges with the general applicability of these models in low-resourced settings.\n\nIn paragraph 2, the authors discuss the 'unaffordable cost of dialysis-requiring renal impairment in resource-constrained healthcare systems', without providing a reference. There are various publications on this issue and a reference should be provided.\nIn the challenges with the models' application in resource-constrained settings (paragraphs 6-7), there is a strong emphasis on HIV infection. Though important and should perhaps be considered in AKI predictive models, the prevalence of HIV varies extensively, even in low-resourced settings and this should be considered in the discussion.\nIt is commendable that the authors conclude that raising awareness of AKI and paying attention to patient monitoring and care is where most attention should be placed in resource-limited settings at this stage. Furthermore, the availability of less-than-ideal creatinine should be improved upon in resource-constrained healthcare systems.\n\nIs the topic of the opinion article discussed accurately in the context of the current literature? Yes\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nAre arguments sufficiently supported by evidence from the published literature? Partly\n\nAre the conclusions drawn balanced and justified on the basis of the presented arguments? Yes", "responses": [ { "c_id": "8488", "date": "13 Jul 2022", "name": "busisiwe Mrara", "role": "Author Response", "response": "Thank you for your valuable input. We have added a reference supporting the assertion regarding the astronomical costs of dialysis. We accept that HIV prevalence is variable in low-income settings. We have reworded the paragraph to delink HIV prevalence and low-income settings. However, we would like to emphasise that the advanced presentation of HIV and its complications including Acute Kidney Injury, could be an issue in areas of inadequate health care access." } ] } ]	1	https://f1000research.com/articles/11-642
https://f1000research.com/articles/11-786/v1	13 Jul 22	{ "type": "Review", "title": "Emergency contraception from historical myth to modern reality: a historical timeline and updated interpretation", "authors": [ "Norman D GOLDSTUCK" ], "abstract": "Introduction: Emergency contraception is the use of a birth control method after coitus has taken place and there is a fear that it may lead to a pregnancy. Historical attempts were more likely to be harmful rather than effective. Oral estrogens, progestins, anti-progesterone, and partial agonist/antagonists of progesterone have all been used with varying degrees of efficacy. Currently ethinyl estradiol/levonorgestrel combinations, levonorgestrel alone, ulipristal acetate, and mifepristone are the usual oral methods depending on availability. Copper carrying and more recently levonorgestrel releasing intrauterine devices have also been used successfully. The intrauterine devices appear to be more effective than the oral methods and are also regular contraceptive methods and in addition have therapeutic properties.\nBackground: The evolution from longer duration oral treatments with side effects to the current single tablet of levonorgestrel, ulipristal acetate, or mifepristone with low side effects and reasonable efficacy is described. The role of the highly effective copper intrauterine device and now also the levonorgestrel intrauterine device for emergency contraception is examined.\nConclusion: Oral emergency contraception is a short term solution. Expanding emergency contraception to include the levonorgestrel releasing intrauterine device may provide long term contraception and health benefits as well as providing emergency contraception.", "keywords": [ "emergency", "contraception", "estrogens", "progestins", "anti-progestins selective progesterone modulators", "copper intrauterine device", "levonorgestrel intrauterine device." ], "content": "Introduction\n\nPregnancy is a continuum from fertilization to parturition. Under normal circumstances the process takes approximately 40 weeks. Humans understand what initiates this process and have developed technologies to disrupt the process anywhere along the continuum. At what stage this may be done legally varies from country and locality around the world. Attempts to disrupt the continuum are easier and more likely to be legal the earlier it is attempted. Emergency contraception (EC) is the attempt to disrupt this continuum at the interface of where pre-conception and conception meet. It therefore finds itself straddling the area of contraceptive versus abortifacient. This review is however, is concerned only with the physiology and pharmacology of emergency contraception and not with any legal or moral standpoints regarding this issue. These will be used to later challenge some long held perceptions regarding EC.\n\nFollowing unprotected sexual intercourse a woman has two options: i) do nothing and hope for the best with a 0.1% to 25% of becoming pregnant depending on the time of the cycle of exposure, or ii) use a form of EC. EC is often provided when a high sensitivity pregnancy test (HSPT) is negative and is usually not regarded as abortifacient as there is no way of knowing at this stage whether conception has indeed occurred and whether implantation has taken place, even if it may be suspected that it has, based on extrapolating the facts known about the physiology of conception.\n\nThe rate of unintended pregnancy, while dropping, remains high.1 The use of emergency contraception in the form of a long-acting reversible contraceptive (LARC) or when a short acting form of EC is given in combination with a LARC, may help to reduce this.2\n\nThis review will examine the pharmacokinetics and pharmacodynamics and clinical results of previous and existing methods of emergency contraception to be able to determine the possible mechanism of action and efficacy. It will avoid one problem of most reviews on this subject of conflating pregnancy rates from studies of the various methods as necessarily being synonymous with efficacy, given how difficult true efficacy is to determine.\n\n\nHistorical aspects of emergency contraception\n\nHistorical methods of emergency contraception are of interest because they form the background against which to evaluate our advances. Methods of attempting to prevent conception after coitus have been documented as far back as ancient Roman times. Folklore has continued to promote useless methods such as douching up until modern times. The physiology is against the probability of these methods from working.\n\nIf coitus has taken place in the peri-ovular period then spermatozoa can easily penetrate the cervical mucus plug which has a high Insler score3 at this time. Spermatazoa usually penetrate the mucus plug and may even reach the Fallopian tubes within a few minutes.4 In order for a contraceptive method to work at this stage then i) the impending ovulation must be delayed so that viable spermatozoa cannot reach the ovum, or ii) if one of the spermatozoa has succeeded in breaching the membrane of the ovum then this ovum should be unable to implant in the already decidualized endometrium. Once this is understood it is clear that it is too late for the use of a douche, irrespective of what it is, and a systemic product which does not target the prevention of ovulation or the formation of a decidualized endometrium or act on the endometrium itself is not likely to be of value. Many different types of douches and potions have been used over the years and have been of little value and occasionally some have been toxic.4 Finally in the twentieth century chemical compounds which specifically targeted the reproductive tract became available and the prospect of effective and safe emergency contraception had arrived.5\n\n\nOral emergency contraception\n\nThe ability of estrogens to interfere with pregnancy in animals has been known since the 1920’s. A number of synthetic and semi-synthetic estrogens were synthesized in the late 1930’s and were soon licensed for medical use. These included diethyl- stilbestrol (DES), Ethinyl-estradiol (EE2), conjugated equine estrogens (CEE), and estradiol esters eg., estradiol propionate.\n\nThe interest in using them as EC initially was to prevent pregnancy after sexual assault and was based on the fact that veterinarians had used them after ‘inappropriate’ mating.4,5 Studies began on EC use in the 1960’s on DES in North America6,7 and EE2 in the Netherlands.8,9 These compounds were generally administered for five days and were often given with anti-emetics. Administration had to be commenced within 72 hours of unprotected intercourse (UIC). Additionally, because of the side effects, they were given largely to women who were deemed at greater pregnancy risk because of these side effects. In one study they were given only to women at ‘midcycle’ and who were assumed to be post-ovulatory.10 The mechanism of action of emergency estrogens is thought to be the more rapid transport of fertilized ova through the Fallopian tube and retarded maturation of the endometrium with long lasting basal vacuoles thus inhibiting implantation.9 A study on EE2 and CEE11 was the first study which attempted to assess the efficacy of EC by attempting to correlate the pregnancy rate with the expected number of pregnancies without treatment using the method of Barrett and Marshall.12 The dose regimes of the various estrogen formulations is given in Table 1.13 High dose estrogens are no longer used because they pose a thrombotic risk.\n\nIn 1972, Albert Yuzpe in Canada observed that a single dose of 0.05 mg (50 μg) EE2 together with 0.5 mg (500 μg) of dl-norgestrel (dl-NG) produced endometrial changes.14 This was thought to be a possible mechanism of action, when using this combination as an EC. Current oral contraceptives however have less than 50 μg of EE2 (anywhere between 10-35μg) and use levonorgestrel (LNG), the active enantiomer of dl-NG. The era of the ‘emergency contraceptive pill’ (ECP) had begun.\n\nA trial with an arbitrary dose of 0.1mg of EE2 and 1mg of dl-NG (given as two doses 12 hours apart) was conducted. This was two doses of two tablets of an existing oral contraceptive available at the time. The first dose had to be given within 72 hours of unprotected coitus. The first study was published in 1974.15 There was a pregnancy rate of 2.02%. Many other studies gave similar results. This method provides a dose of EE2 which is 125 times lower than that of the high dose estrogen regime. Since most practitioners were familiar with the oral contraceptive there was no reluctance to use this method as there had been with the high dose estrogens. This development would create an awareness in health professionals and later the public to the possibilities of emergency contraception.\n\nA double-blind randomized controlled trial of high dose EE2 with the Yuzpe method showed no difference in pregnancy rates but far fewer side effects such as nausea, vomiting, and bleeding irregularities, so the use of high dose estrogens for emergency contraception was over.16 In order to use this method with modern oral contraceptives the tablets must be juggled around to approximately fit these doses.17 The maximum serum levels of LNG were found to be 15.6±9.2 ng/ml and 391±123 pg/ml for EE2 after a single dose of 500 μg LNG and 100 μg of EE2.18 A later analysis showed that the efficacy of the method was overestimated and was probably 51.4-66% effective19 at best.\n\nDanazol (Danol©, Cipla, Mumbai, India) is a steroid with androgenic, progestogenic, anti-gonadotropic and anti-estrogenic activity. It was evaluated as an emergency contraceptive but was not as effective as the Yuzpe method.20,21 Thus, its use was abandoned and it is of historical interest only.\n\nIn 1980 the French company Roussell-Uclaf synthesized Mifepristone (RU486) which was highly anti-progestogenic and anti-glucocorticoid. Anti-progestins bind to progesterone receptors and block its actions. This results in abortion in early pregnancies and can also block other luteal phase effects, including endometrial decidualization. It may also prevent ovulation if given before ovulation has taken place.22 This compound became highly controversial and was later sold by the manufacturers to Exelgyn.\n\nIt has now become available in most countries as an abortifacient. Early emergency contraceptive studies of a 600 mg dose versus the Yuzpe method showed that it was as or more effective with fewer side effects.20,23 Mid-level doses of 25-50 mg of mifepristone appear to be more effective and have fewer side effects than LNG.24 A study comparing 600 mg, 50 mg, and 10 mg of mifepristone found no significant efficacy differences between the three while the 10 mg dosage was associated with less menstrual cycle disturbance.25 There is evidence that doses as low as 5 mg are effective.26 The mechanism of action of mifepristone depends on the dose and day of cycle when it is given. The most used 10 mg dose delays ovulation when it is given pre-ovulatory.27 The calculated efficacy from 10 mg studies is 83%.28 This is probably overstated due to the methodology of calculating efficacy in these studies. Mifepristone is not available for use for EC because of its role in medical abortions in most countries. It is available for EC in Russia, China, Cuba, and Vietnam. The antiprogestin gestrinone (10 mg) has also been used and appears to be as effective as 10 mg mifepristone.29\n\nRacemic dl-norgestrel was discovered by Hughes at Wyeth in 1963 via modification of norethisterone, one of the earliest progestins. It was thus considered to be a ‘second-generation’ progestin. The active isomer was later shown to be d-norgestrel or d(-)-norgestrel. The ‘minus’ sign indicates that the ‘d’ structural form rotates polarized light to the left in a levorotatory manor, hence the name levonorgestrel (LNG), while the inactive enantiomer, dextronorgestrel (l(+)-norgestrel) does the opposite. Early papers on LNG still refer to it as d-NG. Only LNG is used nowadays.\n\nBy the end of the 1970’s LNG was available in combination with EE2 in combined oral contraceptive pills, on its own in progestin only pills, and was undergoing evaluation as a subcutaneous implant, an intrauterine device, and as a long-acting injectable contraceptive. The ovulatory delaying or suppressing effect of progesterone had been known since 1937 and the early oral contraceptives only added estrogen because the combination gave better cycle control.30 The rationale for using a progestin only compound in place of the estrogen/progestin combination of the Yuzpe method was therefore evidence based. The side effects of EE2 would be avoided and possibly some aspects of estrogen/progestin interaction. Experimentation with varying doses of LNG began in the early 1970’s with the focus on using it as a modified ‘on demand’ birth control method rather than as a true emergency contraceptive.\n\nInitial evaluation\n\nEarly formal studies were conducted in Hungary using 0.75 mg LNG as an emergency contraceptive31 and also as a deliberate ‘morning-after’ contraceptive where women who had infrequent coitus and who were not suited to other forms of contraception would only take one or two doses of 0.75 mg LNG after coitus.32 The efficacy and side effect profile appeared to be satisfactory for use as a postcoital emergency contraceptive but not as a deliberate ‘morning-after’ method with a frequency of once a week or more. A study in Germany using 0.4 mg and 0.75 mg LNG in the same ‘morning-after’ regimen came to the same conclusion that use as an infrequent emergency contraceptive would be preferable.33 A multi-center EC study in Hungary had 23 pregnancies in 1,315 subjects (1.75%). This study used the regime consisting of 0.75 mg LNG twice daily for five days and was the forerunner of the very large studies later conducted by the World Health Organization (WHO). The results are similar to those later found by the WHO and, like the WHO results, are better than those achieved in ‘real world’ situations. The reasons for this are explained later.34\n\nComparative studies\n\nThe first comparative study of LNG with the Yuzpe method was conducted in Hong Kong.35 The Yuzpe method was compared with two doses of 0.75 mg LNG given 12 hours apart. The subjects had intercourse more than once in the treatment cycle so there was no attempt to calculate efficacy.\n\nThere was a 3.5% failure rate in the Yuzpe group and a 2.9% failure rate in the LNG group. The incidence of nausea, vomiting and fatigue was significantly higher in the Yuzpe group. This was followed up with a large WHO comparative study of the same two regimes commenced within 72 hours after unprotected coitus. The pregnancy rate was 1.1% for the LNG group and 3.2% for the Yuzpe group. An efficacy of 85% for the LNG group and 57% for the Yuzpe group was calculated. The efficacy declined with the time after starting treatment, especially after 24 hours. Nausea and vomiting were significantly higher in the Yuzpe group.36 A further WHO trial compared mifepristone 10 mg, versus two doses of LNG 0.75 mg 12 hours apart and a single dose of LNG 1.5 mg (Plan-B©, Barr Pharmaceuticals Montvale, New Jersey, USA) within 72 hours of unprotected coitus. The pregnancy rates were 1.5% for both the mifepristone and single dose of 1.5 mg LNG and 1.8% for the two 0.75 mg doses of LNG. There were no significant side effects for all groups although the mifepristone tended to delay the next menses.37 A later study showed a 1.3% failure rate for the two dose LNG regime and 2% for the mifepristone 10 mg regime.38 An earlier study had attempted to calculate the efficacy difference between LNG in two doses and mifepristone and found mifepristone to be 79.7% and LNG 59.1% effective using Dixon’s method.11,39\n\nPharmacokinetics and mechanism of action\n\nThe maximum serum levels of LNG are around 15.2 ng/ml for the 750 μg dose which is similar to that of the Yuzpe regime18 and a maximum level of 19.1 (±9.7) ng/ml was reported for the 1.5 mg dose.40 LNG serum levels are very variable so the data for the different doses are not directly comparable. LNG 1.5 mg appears to act by delaying or preventing ovulation. It does this if given 48 hours before the luteinizing hormone LH surge. It is ineffective if LH levels are on the rise. There is no effect on the endometrium, progesterone levels or fertilization or implantation or ectopic pregnancy or a developing fetus.41 The International Federation of Gynecology and Obstetrics (FIGO) considers the mechanism of action of LNG as “inhibition of ovulation and thickening of cervical mucus” and that language on “implantation” should not be included on product labelling.42 A limited and constrained mechanism of action must limit the efficacy. More recently there has been some concern that LNG 1.5 mg is much less effective in women who weigh more than 75 kg or have a body mass index (BMI) of more than 30 kg/m2.43\n\nLNG for EC has been available for about 20 years in most countries’ worldwide. It is available mostly without prescription and even ‘off the shelf’ in some jurisdictions because of its proven safety. Currently LNG 1.5 mg is is the benchmark or ‘gold-standard’ against which past and future oral emergency contraception can be judged.\n\nThe exploitation of pharmaceutical ligand molecules which bind selectively to different receptors has been used since the 1950’s. These molecules may have agonist activities at some receptors and antagonistic activities at the same or other receptors depending on dosage. Beta-blockers, opioids, and anti-histamines are good examples. Ulipristal acetate (UPA) is closely chemically related to mifepristone and has both agonistic and antagonistic effects on the progesterone receptor site and is therefore a selective progesterone receptor modulator (SPRM). Unlike mifepristone it stimulates rather than inhibits glucocorticoid activity but these effects have no influence on its use as an ECP.41\n\nPharmacokinetics and pharmacodynamics\n\nUPA, unlike the other molecules used as ECP was specifically developed as an emergency contraceptive pill by Laboratoire HRA Pharma. It has been licensed for EC in many countries as UPA 30 mg (Ella® or EllaOne®. HRA Pharma, London, UK). The pharmacokinetics and pharmacodynamics were studied before its widespread clinical usage.44 Following a single dose administration of UPA in 20 women under fasting conditions, maximum plasma concentrations of UPA are around 180 ng/ml with a half-life of around 32 hours. It is highly bound to plasma proteins and mainly metabolized by cytochrome P450. It can be taken with or without food.\n\nUPA 30 mg has been studied in relation to the LH peak and at different ovarian follicle diameters and in relationship to ovulation.45 UPA inhibits follicle rupture if given before the LH rise and even if the leading follicle was up to 18 mm. If given on the day of the LH peak UPA can delay ovulation, and thus exhibit efficacy for up to 48 hours after the LH surge. If LNG is given at this stage, it is not effective.45 UPA may also have an inhibitory effect on follicle rupture. This gives it a larger window of potential efficacy than LNG. The fertile window is normally from five days before ovulation to the day of ovulation itself (Figure 1). UPA like LNG does not appear to have any endometrial effects with short term use but UPA does when used long term.46 Lack of endometrial effect is a factor restricting the window of action of LNG and UPA.\n\nClinical evaluation\n\nUPA appears to be the most effective ECP with efficacy rates calculated to be between 62-85%.47 UPA has been compared to LNG, the benchmark ECP, and been found to be more effective.48,49 The pregnancy rate with UPA was 42% lower than LNG in the first 72 hours and 65% lower in the first 24 hours. UPA was significantly more effective in the 72-120 hour subgroup. LNG is known to only be partially effective at best after 72 hours because of its failure to be effective after ovarian follicular size of 15 mm.50 Side effects of UPA included headaches, nausea and dizziness and the next menstrual period was delayed by 2.5 days on average. UPA is also less effective in overweight and obese women but is less affected by BMI than LNG.51 UPA 30 mg becomes less effective after BMI ≥30 (LNG BMI ≥25) and becomes virtually ineffective at BMI ≥35(LNG ≥30). The current epidemic of obesity in some countries limits this option. There has been some speculation on the use of higher doses in these women.51\n\nUPA 5 mg daily as a treatment for fibroids has resulted in some cases of liver toxicity. While this is not likely with a single dose of UPA 30 mg there is some concern over instances of repeated doses of UPA 30 mg. For this reason, there is concern where it may be available without prescription and used repeatedly or even where it is prescribed repeatedly.52\n\nThere is some evidence that meloxicam (a cyclo-oxygenase type-2 inhibitor) may be an ECP when given in a 30 mg dose for five days; the COX-2 inhibitor meloxicam when added to 1500 μg of LNG significantly increased the proportion of cycles with no follicular rupture or ovulatory dysfunction. COX-2 inhibitors appear to be able to disturb the ovulatory process after the onset of the LH surge.53 There is no information on other newer COX-2 inhibitors like etoricoxib or celecoxib.\n\n\nThe efficacy of oral emergency contraception.\n\nThere have not been any trials of the efficacy of oral emergency contraceptives (ECP) with a placebo as control, for ethical reasons. The determination of the effectiveness of oral emergency methods therefore rests on the probability that a particular coital act would result in a pregnancy. Initially the method of Dixon11 which was based on values determined by Barrett and Marshall12 was used. More recently, estimated risks of pregnancy by day of cycle have been based on the work of Wilcox and colleagues They conducted a detailed study relating the day of the menstrual cycle on which coitus occurred and how likely pregnancy would be to result on that day in women attempting to conceive.54 This data has been used for the last 20 or more years to estimate the efficacy of ECP.\n\nHumans are the only species which seem to understand that pregnancies are produced by coitus. While most species engage in coitus for reproductive purposes only (the Benobo may be an exception), humans also use coitus for bonding purposes where reproduction is not wanted and not desired. The idea that measuring pregnancy rates in couples using coitus to create a pregnancy and applying them to those who are having coitus with the strict intention of not producing a pregnancy is not really logical. The act of coitus is complicated and cannot be singularly compared with for example, renal or liver function. Not all coital acts will therefore have the same possibility of producing a pregnancy, irrespective of all other factors but this cannot be quantified. Couples who are attempting to produce a pregnancy are pre-screened while assignations leading to requests for ECP may involve an unknowingly infertile partner. The male may have a low or non-existent sperm count or chronic epididymitis or prostatitis, while the female may have early endometriosis, adenomyosis, fibroids, or sub-clinical tubal infection. A full gynecological history and/or examination is rarely taken before ECP is prescribed and it obviously is not if the ECP is acquired over the counter or directly off the shelf. Some of the differences between coitus for planned pregnancy and non-reproductive intended coitus are given in Table 2. The conclusion from this is that coitus is not as efficient at producing a pregnancy when it is not specifically directed to pregnancy production but takes place none the less.\n\n† Excluding failure of a contraceptive method other than condoms.\n\nWomen who are not attempting to achieve a pregnancy will often not keep a good track of menstrual cycles. In one study pregnanediol concentrations show that 30% of women presenting for the ECP believed they were in the fertile phase of the cycle but were not.55 Some women are also not in the part of the cycle they think they are by calculation.56 Women presenting for ECP often do not show the same numbers of sperm in the vagina as those who are trying to get pregnant at the same post-coital interval.57\n\nThis information plus information on the relative efficacy of the intrauterine device for emergency contraception also appears to indicate the calculated efficacy of ECPs is overstated.2 The circumstances surrounding ‘unprotected intercourse’ do not need any elaboration to those who have dispensed emergency contraception after taking a detailed history of said circumstances. The efficacy of oral emergency contraception is therefore probably overstated.\n\n\nThe intrauterine device as emergency contraception\n\nMore than a century after its introduction in Germany by Richter and Grafenberg58,59 the intrauterine device (IUD) has finally come into its own. It has had a checkered history of being bedeviled by being associated with the problems of pain, bleeding, and infection. After World War II the use of thermoplastics was introduced by Lippes to solve these problems.60 However, to be effective plastic IUDs need to have a minimum surface area of 600 mm2,61 so the problems persisted to a large extent. In the late 1960’s Zipper, from Chile, the world’s largest copper producer, showed that copper had a powerful anti-fertility effect in rabbits and humans,62 which was confirmed by Chang and Tatum.63 This exciting find led to a series of clinical studies in Chile using increasing copper loads on a polyethylene ‘T’ frame from 30 mm2 to 200 mm2 to find a load which appeared to be effective.64 Freed of any constraints of the size and surface area of the plastic frame, the choice was made from anatomical data from Dickinson which Lippes had used earlier for the plastic devices.65 Modern day ultrasound measurements have been used to question the frame sizes that were chosen but they have largely persisted for the ‘T’ framed devices still used today.\n\nMechanism of action of copper as an emergency contraception\n\nThe mechanism of action of copper as an emergency contraceptive is probably the same as that of when it is used as a long-acting reversible contraceptive (LARC) except that it is placed after coitus so that some actions may not apply. The early copper IUDs had copper loads of 200 mm2 and released 45 μg of copper per day.66 Peak release of copper occurs in the first two cycles of use and since copper ionizes very rapidly in an ionic solution like endometrial fluid it is fair to assume this release begins immediately. Current copper IUDs tend to have greater surface area of copper and the release rate will be even greater. In the genital tract copper could act at any stage in the reproductive process. It could interfere with sperm directly, inhibit tubal sperm transport, be toxic to the fertilized egg or blastocyst, or disturb the intrauterine environment preventing implantation. There is reasonable evidence that all these mechanisms may occur.67 Copper also reduces sperm penetration through cervical mucus68 but this mechanism will not influence an emergency IUD.\n\nClinical evaluation of the emergency copper IUD\n\nLippes and colleagues published the first studies of the emergency copper IUD.69,70 None of the 299 women became pregnant and a good percentage were assumed to be in the fertile window based on dates and ‘spinnbarkheit’ length. A large percentage were nulliparous. The use of IUDs in nulliparae was quite contentious at the time and had not yet gained more general acceptance as it has currently. The copper-7 200 (Gravigard® GD Searle High Wycombe, Bucks, UK), T copper 200 (TCu 220, Janssen-Cilag, High Wycombe, Bucks, UK) and the T copper 300 were the devices which were used. While most insertions took place within three days after UIC, some insertions took place up to seven days after UIC. These studies generated a lot of enthusiasm for the method as the high estrogen oral method was the only other method available at the time. The publication of the larger Yuzpe study71 rapidly dampened enthusiasm for the emergency IUD. A secondary problem was that there was a high discontinuation rate for the emergency copper IUD in this study. This finding was to be replicated in other studies.\n\nTwo further studies in the United Kingdom included subjects up to 10 days after UIC72,73 and one included a plastic IUD72 which were followed by another UK study which included some plastic IUDs.74 These inclusions may have been unintentional due to protocol violation. The only randomized study of the copper IUD versus an oral emergency method was reported from Italy where EE2 for five days was compared. There were no pregnancies in either group.75 Two further Italian studies followed in which insertions were conducted up to seven days after UIC.76,77\n\nAt this stage in the mid-1980’s two interesting facts emerged; i) despite all completed studies using seven days after UIC as their cut-off point, all formal recommendations from the WHO, the Royal College of Obstetricians and Gynaecologists in the United Kingdom, and the American College of Obstetricians and Gynecologists, recommended five days as the cut-off point for insertion of an emergency IUD. The five day ruling was presumably based on the data of Croxatto and co-workers showing that implantation took place mainly on the 6th day after fertilization.78 This was only changed years later to ‘five days after the expected day of ovulation’, following the realization of how inadequate this was for UIC in the early follicular phase. ii) The withdrawal of the Copper 7 IUD in the United States meant there was a short interval where no copper bearing IUDs were available there until the Copper T 380A (Paragard®, Cooper Cos Inc, Pleasanton, California, USA) was approved. Unlike in the US most other middle and higher income countries still had a variety of different types of copper IUDs at their disposal.\n\nShortly thereafter a study in Egypt reported four pregnancies in the copper IUD group and 22 in a control group who received no treatment.79 This was the first study to report a pregnancy. While there are anecdotal reports of pregnancy with copper IUDs in western countries80 there are at present no reports of a pregnancy in a single copper IUD for EC study in a western country following two extensive systematic reviews (8,550 insertions and 12 pregnancies, all from Egypt or China).81,82 Both reviews showed a pregnancy rate of about 0.1%. Only the Multiload IUDs (MLCu 250 and MLCu 375, Multilan SA, Fribourg, Switzerland) and GyneFix (Contrel, Ghent, Belgium) IUDs have an official indication for use as EC.41 All other copper IUDS used as EC are being used ‘off label’.\n\nNewer clinical studies\n\nThe temporary unavailability of the copper IUD in the US and extreme interest in LNG oral emergency contraception led to a hiatus in emergency copper IUD evaluations in Western countries. The bulk of experience with various types of copper IUDs for EC now started coming from China.83 Chinese studies are often comparative with oral EC methods but there have not been any controlled studies. IUD insertion for EC in Chinese studies is always five or fewer days after UIC. From the mid 1990’s the LNG releasing IUD started to become available and shortly thereafter sub dermal implants. These together with the copper IUD and sometimes including the injectables came to be known as long-acting reversible contraceptives (LARCs). LARCs were largely independent of user input and this led to the idea that they would be more successful as contraceptives. There is evidence that this is true.84 This increased the use of IUDs and interest in the copper IUD was rekindled. This in turn provided the impetus for a slew of new copper IUD for EC studies, mainly from Turok and colleagues.85,86\n\nAmong the advances these studies have demonstrated is that the previous and current recommendations regarding emergency IUD use are not scientifically based. The original recommendation of five days after UIC was based on the estimated time to implantation of six days78 which is in any case variable. The updated recommendations of five days after the presumed day of ovulation is also speculative as there is no way of determining this. Recent evidence shows clearly that an emergency copper IUD can be inserted anytime during the cycle provided a HSPT is negative as this also allows for multiple episodes of unprotected coitus in the same cycle.87–89 This approach avoids being dependent on answers to questions regarding the time of the cycle and delay after UIC which may be either incorrect or untruthful. The limitations as previously accepted for IUDs are not scientifically based and the scientific limitations for the major EC methods are shown in Figure 1. Naturally physicians and providers are always free to exercise their own preference, for reasons other than scientific evidence.\n\nThe role of LNG-IUDs\n\nWomen who request emergency contraception are at risk for pregnancy at the time and presumably in the future. As well as being given an LNG oral emergency contraceptive, many are given a conventional contraceptive at the same time. A LARC method is often suggested and for those who do not want a copper IUD, one of the LNG containing IUDs90 is an option, as is the sub dermal implant unless the woman was given UPA which might theoretically interfere with the initial action of the levonorgestrel-releasing intrauterine system (LNG-IUS) or implant and require a waiting period. A non-randomized study of the TCu 380A versus oral LNG 1.5 mg plus insertion of an LNG-IUS 52mg at the same time produced only a single pregnancy in the LNG oral plus LNG-IUS group. This was less than would have been expected for LNG alone.91\n\nMechanism of action of intrauterine LNG as an emergency contraceptive\n\nThe levonorgestrel-releasing intrauterine systems (LNG-IUS) (LNG-IUS 52 mg Mirena©, Bayer Pharma, Berlin, Germany, Levosert©, Lilletta© Actavis, Reykjavik, Iceland), LNG-IUS 19.5 mg (Kyleena©, Bayer Pharma, Berlin, Germany, LNG-IUS13.5 mg, Jaydess©/Skyla©, Bayer Pharma, Berlin, Germany) are very effective for contraception and work by three main methods; they i) act on cervical mucus to reduce sperm penetration (decrease Insler score), ii) alter tubal mobility, and iii) produce a pseudo-decidualized atrophic endometrium, and less importantly, iv) a partial inhibition of the LH surge leading to anovulation (40%) with the LNG-IUS 52 mg device.92 These effects are achieved over a number of cycles. Serum levels of LNG are around 200 picogram/ml (0.2 ng/ml) compared with 20 ng/ml for the oral LNG 1.5 mg pill which is achieved within hours.40 The silastic membrane of the LNG-IUS 52mg device allows a constant release of about 20 μg/day of LNG so there is no immediate surge of LNG. This is known as zero order kinetics whereas pills for EC and the copper IUD will deliver using largely first order kinetics which are dose dependent if all other factors e.g., first pass metabolism, absorption etc. are excluded.\n\nAn LNG-IUS will produce a tissue concentration of LNG of 800 ng/gm in the endometrium after 36 days when LNG is released at 30 μg/day (higher than the current LNG-IUS 52mg which releases 20 μg/day).93 The mechanism of action of the LNG-IUS as an emergency contraceptive is therefore difficult to explain in terms of the foregoing and is therefore unknown at present.\n\nClinical evaluation of the emergency LNG IUD\n\nTurok et al., performed a randomized non-inferiority trial of the TCu 380A versus the LNG-IUS 52mg.94 The study was encouraged by the possible effectiveness of plain plastic devices.72,74 There were 321 subjects in the TCu38A group and 317 in the LNG-IUS 52mg.There was one pregnancy in the LNG-IUS 52mg group and none in the TCu 380A group. These differences were not statistically significantly different.\n\n\nThe efficacy of emergency IUD insertion\n\nRelatively few physicians recommend the emergency IUD.95 It is an invasive and time consuming procedure and, unless specifically requested, it is probably more often advised and inserted when the woman requesting EC is perceived to be at most risk. The majority of emergency IUD studies do not correlate the day of insertion with the cycle day on which it was inserted because in many cases there have been multiple episodes of UIC. There has only been one report of a randomized study75 but many group comparative studies.2,81 Although not explicitly stated it is reasonable to assume that, overall, the IUDs were placed more often when the clinician thought the woman was at a higher risk of pregnancy. Despite this bias (against the IUD) the relative risk for pregnancy with an IUD versus the main oral methods (these were not segregated in most studies) was anywhere from one third to one thousand times lower.2 Assuming an efficacy of about 50-60% for oral methods the emergency IUD efficacy must asymptotically approach 99%,2 especially when considering insertions by inexperienced personnel may fail to correctly place an emergency copper IUD, which unlike an interval IUD insertion, only offers a limited window in which to re-attempt the insertion in an already stressed subject.\n\n\nEmergency IUDs as LARC\n\nThe notion of providing LARC contraception at the same time as providing emergency contraception despite its appeal has not had much impact on providing IUDs for emergency contraception. There is a historically high discontinuation rate of most copper IUDs, especially in women of lower parity, for various reasons, despite counselling96 except with the very small GyneFix® device which is also licensed as an emergency IUD.97–99 In some studies where recipients of an emergency IUD were followed up the discontinuation rate was very high70,72,76,100,101 for a variety of reasons and for different devices (Table 3).\n\n\nDetermination of an emergency contraceptive agent as a contraceptive or an abortifacient\n\nA compound which is given to disrupt an established pregnancy which may be determined i) clinically, ii) via imaging, or iii) biochemically is clearly an abortifacient e.g., mifepristone, misoprostol, or oxytocic’s when used for that purpose in the presence of a biochemical and/or image confirmation. In the absence of evidence of an established pregnancy the determination of emergency contraception as an abortifacient is purely speculative and based on the supposition that an ovum may have become fertilized and may have been either i) prevented from implanting or ii) having been implanted has been dislodged from the endometrium which had decidualized. Arguments to the contrary i.e., that emergency oral methods are abortifacient are unverifiable by physiological and pharmacological actions. All contraceptives work by one or more of the following mechanisms; i) preventing or incapacitating sperm from reaching the upper genital tract, ii) preventing folliculogenesis and/or ovulation, iii) preventing fertilization, iv) altering tubal mobility, or v) altering endometrial structure and/or function.\n\nAll major methods of contraception including IUDs, combined oral contraceptives, implants, or injectables may fail to prevent pregnancy, however rarely. In that case all the above mechanisms failed. There must logically be occasions where all mechanisms fail, except one e.g., endometrial decidualization was not mature enough to support the fertilized ovum, in which case it may have implanted and/or failed to attach. Without a chemical test to confirm fertilization or imaging methods with sufficient resolution to observe this then all these suppositions are speculative, no matter how rational they seem to be as a thought experiment. All emergency contraception, especially the IUD if it is inserted more than seven days after unprotected sex, irrespective of the day of cycle, should always be preceded by a negative HSPT, to confirm the non-existence of a pregnancy as accurately as possible given current technology.\n\nAdvocacy groups have done a remarkable job in getting ECPs off prescription and freely available over the counter in many countries, since they must be taken as soon as possible after UIC and their efficacy is compromised by time delay and increasing BMI. Delayed use beyond 72 hours and BMI over 25 start reducing efficacy markedly for LNG and significantly but less so for UPA, although a presumed minimum efficacy for LNG has been calculated.102 This improved availability does not come without consequences and cost. There is both a lost opportunity to provide a more effective emergency contraceptive method which is a LARC, and so unintended pregnancy still remains a future threat, and there is also the possibility that repeated use of UPA may be harmful.52\n\nA confirmation of the LNG-IUD study94 and establishing whether the LNG-IUS 13.5mg and LNG-IUS 19.5mg can operate as emergency contraception is a priority. This will be difficult to accomplish. The LNG release rates are lower and the physical sizes of these LNG-IUSs are smaller than the one tested. In contradistinction the early copper devices used for EC had lower copper loads than the newer ones used for EC so that it was logical that they would be as or more effective for EC. The LNG containing IUDs bring proven well established additional health benefits beyond their role as contraceptives and the copper IUD does as well albeit to a lesser extent.103,104 The problem of discontinuation can be addressed, in part at least, by selecting the most appropriate device (Figure 2), a task which will become easier if a greater selection of sizes and choices for both copper and hormonal IUDs become available. Perhaps then the repeated calls for the use of more use of emergency IUDs will be satisfied.105 It appears that the LNG-IUS can also be inserted up to 14 days after UIC106 which makes it more versatile as an EC.\n\n\nConclusion\n\nCurrently all available evidence, including sensitive biochemical hormonal level estimations and high resolution imaging techniques cannot demonstrate that emergency contraception is anything other than contraception despite protestations to the contrary.107 We are living in the age of ‘hook-up’ culture with young people using dating platforms such as Tinder, Instagram, and Bumble to name a few. There is evidence that this has changed behavior somewhat making women more reluctant to demand condom use for the more attractive men and no reluctance on the part of men to not use protection.108 This can only increase the need for EC (and treatment for sexually transmitted infections) in the future.\n\n\nData availability\n\nNo data are associated with this article.", "appendix": "References\n\nFiner LB, Zolna MR: Declines in unintended pregnancy in the United States, 2008–2011. N. Engl. J. Med. 2016; 374: 843–852. PubMed Abstract \| Publisher Full Text\n\nCheung TS, Goldstuck ND, Gebhardt GS: The intrauterine device versus oral hormonal methods as emergency contraceptives: A systematic review of recent comparative studies. Sex. Reprod. Healthc. 2021; 28: 100615. PubMed Abstract \| Publisher Full Text\n\nInsler V, Melmed H, Eichenbrenner L, et al.: The cervical score. Int. J. Gynecol. Obstet. 1972; 10: 223–228. Publisher Full Text\n\nVan Look F:Post coital contraception: a cover up story.Diczfalusy E, Bygdeman M, editors. Fertility regulation today and tomorrow. New York:Serono symposia Publication, Raven Press;1987; Vol. 36: p. 29–42.\n\nHaspels AA: Emergency contraception: a review. Contraception. 1994; 50: 101–108. Publisher Full Text\n\nMorris JM, van Wagenen G : Compounds interfering with ovum implantation and development. III. The role of estrogens. Am. J. Obstet. Gynecol. 1966; 96: 804–815. PubMed Abstract \| Publisher Full Text\n\nKuchera KK: Postcoital contraception with diethylstibestrol-updated. Contraception. 1974; 10: 47–54. PubMed Abstract \| Publisher Full Text\n\nHaspels AA: The morning-after pill: a preliminary report. IPPF Med. Bull. 1968; 3: 6.\n\nHaspels AA: Interception. Posycoital estrogens in 3,016 women. Contraception. 1976; 14: 375–381. PubMed Abstract \| Publisher Full Text\n\nNotelovitz M, Bard DS: Conjugated estrogen as a post-ovulatory interceptive. Contraception. 1978; 17: 443–454. PubMed Abstract \| Publisher Full Text\n\nDixon GW, Schlesselman JJ, Ory HW, et al.: Ethinyl-estradiol and conjugated estrogens as postcoital contraceptives. JAMA. 1980; 244: 1336–1339. PubMed Abstract \| Publisher Full Text\n\nBarrett JC, Marshall J: The risk of conception on different days of the menstrual cycle. Popul. Stud. 1969; 23: 455–461. PubMed Abstract \| Publisher Full Text\n\nSitka CS: Emergency postcoital contraception. Glob. Libr. Women's Med. 2008. Publisher Full Text\n\nYuzpe AA:Post coital contraception.Saxena BN, Mokkapati S, Toteja GS, editors. Post-coital, once a month and menses inducing agents in the control of female fertility. New Delhi:Indian Council of Medical Research;1972; p. 149–163.\n\nYuzpe AA, Thurlow HJ, Ramzy I, et al.: Post coital contraception-a pilot study. J. Reprd. Med. 1974; 13: 53–58.\n\nVan Santen MR, Haspels AA: Comparative randomized double-blind study of high dosage ethinyl-estradiol versus ethinyl-estradiol and norgestrel combination in postcoital contraception. Acta Endocrinol. 1982; Supl 246: 2–4.\n\nTrussell J, Schwarz EB:Emergency contraception.Hatcher RA, Trussell J, Nelson A, et al., editors. Contraceptive technology. New York, NY:Ardent Media;2011; p. 113–145.\n\nKives S, Hahn PM, White E, et al.: Bioavailability of the Yuzpe and levonorgestrel regimens of emergency contraception: vaginal vs. oral administration. Contraception. 2005; 71: 197–201. PubMed Abstract \| Publisher Full Text\n\nTrussell J, Ellertson C, Von Hertzen H, et al.: Estimating the effectiveness of emergency contraceptive pills. Contraception. 2003; 67: 259–265. PubMed Abstract \| Publisher Full Text\n\nWebb AM, Russel J, Elstein M: Comparison of the Yuzpe regimen, danazol, and mifepristone (RU486) in oral postcoital contraception. BMJ Clin Res. 1992; 305: 927–931. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGuillebaud J, Kubba A, Rowlands S, et al.: Post-coital contraception with danazol, compared with an ethinyloestradiol- norgestrel combination or insertion of an intra-uterine device. J. Obstet. Gynaecol. 1983; 3(2): S64–S68. Publisher Full Text\n\nVan Look PF, von Hertzen H : Clin use of antiprogestogens. Hum. Reprod. Update. 1995; 1: 19–34. PubMed Abstract \| Publisher Full Text\n\nGlasier A, Thong KJ, Dewar M, et al.: Mifepristone (RU 486) compared with high-dose estrogen and progestogen for emergency postcoital contraception. N. Engl. J. Med. 1992; 327: 1041–1044. PubMed Abstract \| Publisher Full Text\n\nShen J, Che Y, Showell E, et al.: Interventions for emergency contraception. Cochrane Database Syst. Rev. 2019; Issue 1. Art. No.: CD001324. Publisher Full Text\n\nTask Force on Postovulatory Methods of Fertility Regulation: Comparison of three single doses of mifepristone as emergency contraception: a randomized trial. Lancet. 1999; 353: 697–702. Publisher Full Text\n\nCarbonell JL, Garcia R, Breto A, et al.: Mifepristone 5 mg versus 10 mg for emergency contraception: double -blind randomized clinical trial. In. J. Women’s Health. 2015; 7: 95–102. Publisher Full Text\n\nGemzell-Danielsson K, Mandl I, Marions L: Mechanisms of action of mifepristone when used for emergency contraception. Contraception. 2003; 68: 471–476. PubMed Abstract \| Publisher Full Text\n\nPiaggio G, Heng Z, von Hertzen H , et al.: Combined estimates of efficacy of mifepristone 10 mg in emergency contraception. Contraception. 2003; 68: 439–446.\n\nWu S, Dong J, Cong J, et al.: Gestrinone compared with mifepristone for emergency contraception: a randomized controlled trial. Obstet. Gynecol. 2010; 115: 740–744. Publisher Full Text\n\nDhont M: History of oral contraception. Eur. J. Contracept Reprod. Health. 2010; 15: S12–S18. Publisher Full Text\n\nSeregely G, Vero T: Postcoital contraception with 0.75 mg d-norgestrel (Postinor). Ther. Hung. 1981; 29: 31–34. PubMed Abstract\n\nFarkas M, Apro G, Sas M: Clinico-pharmacological examination of Postinor (0.75 mg d-norgestrel). Ther. Hung. 1981; 29: 22–30. PubMed Abstract\n\nCanzler E, Ahrendt HJ, Ahrendt S: Experiences with levonorgestrel in postcoital contraception. Zentralbl. Gynakol. 1984; 106: 1182–91. German.\n\nSeregely G: Results of a multicentre trial of Postinor. Ther. Hung. 1982; 30: 72–78. PubMed Abstract\n\nHo PC, Kwan MSW: A prospective randomized comparison of levonorgestrel with Yuzpe regimen in postcoital contraception. Hum. Reprod. 1993; 8: 389–392. PubMed Abstract \| Publisher Full Text\n\nTask Force on Postovulatory Methods of Fertility Regulation: Randomised controlled trial of levonorgestrel versus the Yuzpe regimen of combined oral contraceptives for emergency contraception. Lancet. 1998; 352: 428–433. Publisher Full Text\n\nVon Hertzen H, Piaggio G, Peregoudov A, et al.: Low dose mifepristone and two regimens of levonorgestrel for emergency contraception: a WHO multicentre randomized trial. Lancet. 2002; 360: 1803–1810. Publisher Full Text\n\nHamoda H, Ashok PW, Stalder C, et al.: a randomized trial of mifepristone (10 mg) and levonorgestrel for emergency contraception. Obstet. Gynecol. 2004; 104: 1307–1313. PubMed Abstract \| Publisher Full Text\n\nWu SC, Wang CP, Wang YQ, et al.: A randomized double-blind multicenter study comparing levonorgestrel and mifepristone for emergency contraception. J. Reprod. Med. 1999; 8(Suppl 1): S43–S46. Chinese.\n\nBarr Pharmaceuticals Inc: Plan B One-Step (levonorgestrel) tablet, 1.5 mg, for oral use. Summary of product characteristics.July 2009.Reference Source\n\nGemzell-Danielsson K, Rabe T, Cheng L: Emergency Contraception. Gynecol. Endroc. 2013; 29: 1–14. Publisher Full Text\n\n“Mechanism of action: How do levonorgestrel-only emergency contraceptive pills (LNG ECPs) prevent pregnancy?” (PDF). London:International Federation of Gynecology and Obstetrics. Archived (PDF):December 29, 2014.\n\nFestin MP, Peregoudov A, Seuc A, et al.: Effect of BMI and body weight on pregnancy rates with LNG as emergency contraception: analysis of four WHO HRP studies. Contraception. 2017; 95: 50–54. PubMed Abstract \| Publisher Full Text\n\nWatson Pharma, Inc: Ella 30 mg. Summary of product characteristics.August 2010.Reference Source\n\nGemzell-Danielsson K: Mechanism of action of emergency. Contraception. 2010; 82: 404–409. PubMed Abstract \| Publisher Full Text\n\nMutter GL, Bergeron C, Delegdisch L, et al.: The spectrum of endometrial pathology induced by progesterone receptor modulators. Mod. Pathol. 2008; 21: 591–598. PubMed Abstract \| Publisher Full Text\n\nFine P, Mathe H, Ginde S, et al.: Ulipristal acetate taken 48-120 hours after intercourse for emergency contraception. Obstet. Gynecol. 2010; 115: 257–263. PubMed Abstract \| Publisher Full Text\n\nCreinin MD, Schlaff W, Archer DF, et al.: Progesterone receptor modulator for emergency contraception: a randomized controlled trial. Obstet. Gynecol. 2006; 108: 1087–1089.\n\nGlasier AF, Cameron ST, Fine PM, et al.: Ulipristal acetate versus levonorgestrel for emergency contraception: a randomized non-inferiority trial and meta- analysis. Lancet. 2010; 375: 555–562. PubMed Abstract \| Publisher Full Text\n\nCroxatto HB, Brache V, Pvez M, et al.: Pituitary-ovarian function following the standard levonorgestrel emergency contraceptive dose or a single 0.75- mg dose given on the days preceding ovulation. Contraception. 2004; 70: 442–450. PubMed Abstract \| Publisher Full Text\n\nGlasier A, Cameron ST, Blithe D, et al.: Can we identify women at risk of pregnancy despite using emergency contraception? Data from randomized trials of ulipristal acetate and levonorgestrel. Contraception. 2011; 84: 363–367. PubMed Abstract \| Publisher Full Text\n\nMozzanega B: Ulipristal acetate and liver-injuries: while Esmya is revoked, EllaOne is allowed in repeated self-administrations possibly exceeding UPA toxic-dosing with Esmya. J. Hepatol. 2020; 74: 750–751.\n\nJesam C, Salvatirra AM, Schwarz JL, et al.: suppression of follicular rupture with meloxicam, a cyclooxygenase-2 inhibitor: potential for emergency contraception. Hum. Reprod. 2010; 25: 368–373. PubMed Abstract \| Publisher Full Text\n\nWilcox AJ, Weinberg CR, Baird DD: Timing of sexual intercourse in relation to ovulation. Effects on the probability of conception, survival of the pregnancy, and sex of the baby. N. Engl. J. Med. 1995; 333: 1517–1521. PubMed Abstract \| Publisher Full Text\n\nStirling A, Glasier A: Estimating the efficacy of emergency contraception-how good are the data? Contraception. 2002; 66: 19–22. PubMed Abstract \| Publisher Full Text\n\nEspinos JJ, Rodriguez-Espinosa J, Senosiain R, et al.: The role of matching menstrual data with hormonal measurements in evaluating effectiveness of postcoital contraception. Contraception. 1999; 60: 243–247. PubMed Abstract \| Publisher Full Text\n\nEspinos-Gomez JJ, Senosiain R, Mata A, et al.: What is the seminal exposition among women requiring emergency contraception? A prospective, observational study. Eur. J. Obstet. Gynecol. Reprod. Biol. 2007; 131: 57–60. PubMed Abstract \| Publisher Full Text\n\nRichter R: Ein Mittal zur Verhuetung der Konzeption. Deutsch Med. Wschr. 1909; 35: 1525–1527. German. Publisher Full Text\n\nGrafenberg E:Silk as anticoncipient.Bendix K, editor. Geborten Regelung – Vortraege und Verhandlung en des Aerztekursus vom 28–30 Dezember 1928. Berlin:Selbsverlag;1929. German.\n\nLippes J: Contraception with intrauterine plastic loops. Am. J. Obstet. Gynecol. 1965; 93: 1024–1030. PubMed Abstract \| Publisher Full Text\n\nMoyer DL, Mishell DR: Reactions of human endometrium to the intrauterine foreign body. II. Long term effects on the endometrial histology and cytology. Am. J. Obstet. Gynecol. 1971; 111: 66–80. PubMed Abstract \| Publisher Full Text\n\nZipper J, Medel M, Prager R: Suppression of fertility by intrauterine copper and zinc in rabbits: A new approach to intrauterine contraception. Am. J. Obstet. Gynecol. 1969; 105: 529–534. PubMed Abstract\n\nChang CC, Tatum HJ: A study of the antifertility effect of intrauterine copper. Contraception. 1970; 1: 265–270. Publisher Full Text\n\nZipper JA, Tatum HJ, Medel M, et al.: Contraception through the use of intrauterine metals. I. Copper as an adjunct to the “T” device. The endouterine copper “T”. Am. J. Obstet. Gynecol. 1971; 109: 771–774. PubMed Abstract \| Publisher Full Text\n\nDickinson RL: Human Sex Anatomy. Second ed.Huntington, NY:Robert E. Krieger Publishing Co.;1971.\n\nHagenfeldt K: Intrauterine contraception with the copper T device. 1. Effect on trace elements in the endometrium, cervical mucus and plasma. Contraception. 1972; 6: 37–54. Publisher Full Text\n\nOrtiz ME, Croxatto HB: Copper T intrauterine device and levonorgestrel intrauterine system: biological bases of their mechanism of action. Contraception. 2007; 75: S16–S30. PubMed Abstract \| Publisher Full Text\n\nElstein M, Ferrer K: The effect of a copper-releasing intrauterine device on sperm penetration in human cervical mucus in vitro. J. Reprod. Fertil. 1973; 32: 109–111. PubMed Abstract \| Publisher Full Text\n\nLippes J, Malik T, Tatum HJ: The postcoital copper-T. Adv. Plan. Parent. 1976; 11: 24–29. PubMed Abstract\n\nLippes J, Tatum HJ, Maulik D, et al.: Postcoital copper IUDs. Adv. Plan. Parent. 1979; 14: 87–94.\n\nYuzpe AA, Lance WJ: Ethinylestradiol and DL-norgestrel as a potential contraceptive. Fertil. Steril. 1977; 28: 932–936. Publisher Full Text\n\nBlack TRL, Goldstuck ND, Spence A: Post-coital intrauterine device insertion-a further evaluation. Contraception. 1980; 22: 653–658. PubMed Abstract \| Publisher Full Text\n\nGoldstuck ND: Delayed postcoital IUD insertion. Contracept. Deliv. Syst. 1983; 4: 293–296.\n\nGuillebaud J, Kubba A, Rowlands S, et al.: Post-coital contraception with danazol, compared with an ethinyloestradiol-norgestrel combination or insertion of an intra-uterine device. J. Obstet. Gynaecol. 1983; 3: S64–S68. Publisher Full Text\n\nGottardi G, Marzi MM, Pozzi S: Postcoital estrogen or IUD? IPPF Reg Bull. 1979; 8: 7–8.\n\nGottardi G, Spreafico A, de Orchi L : The postcoital IUD as a an effective continuing contraceptive method. Contraception. 1986; 34: 549–558. PubMed Abstract \| Publisher Full Text\n\nLuerti M, Tonta A, Ferla P, et al.: Postcoital contraception by estrogen/progestagen combination or IUD insertion. Contraception. 1986; 33: 61–68. Publisher Full Text\n\nCroxatto HD, Carillo D: Studies on the duration of egg transport in the human oviduct: Part I. Fertil. Steril. 1972; 23: 447–458. PubMed Abstract \| Publisher Full Text\n\nAskalani AH, Al-Senity AM, Al-Agizy HM, et al.: Egypt. Obstet. Gynecol. 1987; 13: 63–66.\n\nKubba AA, Guillebaud Y: Failure of post-coital contraception after insertion of an intrauterine device. Case report. Br. J. Obstet. Gynecol. 1984; 91: 596–597. PubMed Abstract \| Publisher Full Text\n\nCleland K, Zhu H, Goldstuck N, et al.: The efficacy of intrauterine devices for emergency contraception: a systematic review of 35 years of experience. Hum. Reprod. 2012; 27: 1994–2000. PubMed Abstract \| Publisher Full Text\n\nGoldstuck ND, Cheung TS: The efficacy of intrauterine devices for emergency contraception and beyond: a systematic review update. Int. J. Women's Health. 2019; 11: 471–479. PubMed Abstract \| Publisher Full Text\n\nYang Y, Zhang XM, Wei DY, et al.: Clinical study of mifepristone, A-nordrin and intrauterine device used for emergency contraception. J. Reprod. Med. 1997; 6: 171–173 [Chinese].\n\nWinner B, Peipert JF, Zhao Q, et al.: Effectiveness of long-acting reversible contraception. N. Engl. J. Med. 2012; 366: 1998–2007. Publisher Full Text\n\nTurok DK, Gurtcheff SE, Handley E, et al.: A pilot study of the Copper T380A IUD and oral levonorgestrel for emergency contraception. Contraception. 2010; 82: 520–525. PubMed Abstract \| Publisher Full Text\n\nTurok DK, Jacobson J, Dermish A, et al.: Pregnancy rates 1 year after choosing the copper T380 IUD or oral levonorgestrel for emergency contraception: a prospective observational study. Contraception. 2012; 86: 294. Publisher Full Text\n\nTurok DK, Godfrey EM, Wojdyla D, et al.: Copper T380 intrauterine device highly effective at any time in the menstrual cycle. Hum. Reprod. 2013; 28: 2672–2676. PubMed Abstract \| Publisher Full Text\n\nThompson I, Sanders JN, Schwarz EB, et al.: Copper intrauterine device placement 6–14 days after unprotected sex. Contraception. 2019; 100: 219–221. PubMed Abstract \| Publisher Full Text\n\nSanders JN, Howell L, Saltzman H, et al.: Unprotected intercourse in the 2 weeks prior to requesting emergency intrauterine contraception. Am. J. Obstet. Gynecol. 2016; 215: 592.e1–592.e5. Publisher Full Text\n\nGoldstuck ND: Clarification of the Jaydess (Skyla) LNG-IUS 13.5mg and Kyleena LNG-IUS 19.5mg as intrauterine contraceptive systems. Exp. Review Med. Dev. 2017; 14: 593–599. PubMed Abstract \| Publisher Full Text\n\nTurok DK, Sanders JN, Thompson I, et al.: Preference for and efficacy of oral levonorgestrel for emergency contraception with concomitant placement of a levonorgestrel IUD: a prospective cohort study. Contraception. 2016; 93: 526–532. PubMed Abstract \| Publisher Full Text\n\nGoldstuck ND, Le HP: Delivery of progestins via the subdermal versus the intrauterine route: comparison of the pharmacology and clinical outcomes. Expert Opin. Drug Deliv. 2018; 15: 717–727. PubMed Abstract \| Publisher Full Text\n\nNilsson CG, Haukkamaa M, Vierola H, et al.: Tissue concentrations of levonorgestrel in women using a levonorgestrel releasing IUD. Clin. Endocrinol. 1982; 17: 529–536. PubMed Abstract \| Publisher Full Text\n\nTurok DK, Gero A, Simmons RG, et al.: Levonorgestrel vs. copper intrauterine devices for emergency contraception. N. Engl. J. Med. 2021; 384: 335–344. PubMed Abstract \| Publisher Full Text\n\nHarper CC, Speidel JJ, Drey EA, et al.: Copper intrauterine device for emergency contraception: clinical practice among contraceptive providers. Obstet. Gynecol. 2012; 119: 220–226. PubMed Abstract \| Publisher Full Text\n\nAoun J, Dines VA, Stovall DW, et al.: Effects of age, parity and device type on complications and discontinuation of intrauterine devices. Obstet. Gynecol. 2014; 123: 585–592. PubMed Abstract \| Publisher Full Text\n\nWildemeersch D, Jandi S, Pett A, et al.: Use of frameless intrauterine devices and systems in young nulliparous and adolescent women: results of a multicenter study. Int. J. Women's Health. 2014; 6: 727–734. PubMed Abstract \| Publisher Full Text\n\nGoldstuck ND, Wildemeersch D: Practical advice for emergency contraception in young women. Obstet. Gynecol. Int. 2015; 2015: 1–6. Publisher Full Text\n\nWildemeersch D, Pett A, Jandi S, et al.: Precision intrauterine contraception may significantly increase continuation of use: a review of long-term clinical experience with frameless copper-releasing intrauterine contraception devices. Int. J. Women's Health. 2013; 5: 215–225. PubMed Abstract \| Publisher Full Text\n\nTurok DK, Jacobsen JC, Dermish AI, et al.: Emergency contraception with a copper IUD or oral levonorgestrel:an observational study of 1-year pregnancy rates. Contraception. 2014; 89: 222–228. PubMed Abstract \| Publisher Full Text\n\nEnvall N, Koefoed NG, Kopp-Kallner H: Use of effective contraception 6 months after emergency contraception with a copper intrauterine device or ulipristal acetate – a prospective observational cohort study. Acta Obstet. Gynecol. Scand. 2016; 95: 887–893. PubMed Abstract \| Publisher Full Text\n\nRaymond E, Taylor D, Trussell J, et al.: Minimum effectiveness of the levonorgestrel regimen of emergency contraception. Contraception. 2004; 69: 79–81. PubMed Abstract \| Publisher Full Text\n\nBahamondes L, Bahamondes MV, Shulman LP: Non-contraceptive benefits of hormonal and intrauterine reversible contraceptive methods. Hum. Reprod. Update. 215; 21: 640–651. Publisher Full Text\n\nGoldstuck ND: Modern menstruation: Is it abnormal and unhealthy? Med. Hypotheses. 2020; 144: 109955. Publisher Full Text\n\nBelden P, Harper CC, Speidel JJ: The copper IUD for emergency contraception, a neglected option. Contraception. 2012; 85: 338–339. PubMed Abstract \| Publisher Full Text\n\nBooras CM, Sanders JN, Schwarz EB, et al.: Risk of pregnancy with levonorgestrel-releasing intrauterine system placement 6-14 days after unprotected sexual intercourse. Obstet. Gynecol. 2021; 137: 623–625. PubMed Abstract \| Publisher Full Text\n\nKahlenborn C, Peck R, Severs WB: Mechanism of action of levonorgestrel emergency contraception. The Linacre Quart. 2015; 82: 18–33. PubMed Abstract \| Publisher Full Text\n\nEleftheriou A, Bullock S, Graham CA, et al.: Does attractiveness influence condom use intentions in women who have sex with men? PLoS One. 2019; 14: e0217152. PubMed Abstract \| Publisher Full Text" }	[ { "id": "151136", "date": "13 Oct 2022", "name": "Hannat Akintomide", "expertise": [ "Reviewer Expertise Contraception clinical practice and research including emergency contraception", "combined oral contraception and intrauterine contraception." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThank you for the invitation to peer review this manuscript.\nOverall, emergency contraception (EC) is indeed relevant and has evolved over decades with quite a few ‘backs and forths’. So its history would be interesting educational reading to both clinical and non-clinical audiences. This manuscript provides sufficient detail with over 100 references cited, hence warranting extra care with clarity and flow. It could also be improved significantly by more focus on facts and figures and excluding several digressions.\nTo ensure comprehensiveness, every new aspect of history reported needs to state the occurrence time in a manner that engages the reader without sounding repetitive - the year, or how soon before or after an incident or event that has been mentioned, etc. This has so far been partly done and should be improved upon please. For example, under the section \"The copper bearing IUD\" and subsection \"Clinical evaluation of the emergency copper IUD\", the first sentence \"Lippes and colleagues published the first studies of the emergency copper IUD.69,70\" is inadequate for this reason. Although the sentence has been referenced, a reader expects to see/learn what year this was in the text. Similarly inadequate appears the sentence in the same paragraph \"The publication of the larger Yuzpe study71 rapidly dampened enthusiasm for the emergency IUD\" - why... what year was this? There should be no need to sift through references to determine this.\nFor clarity and flow, the subheadings/sections/subsections created support the reading of this history and enable signposting. I believe this manuscript could benefit further by refining these to achieve more simplicity for the manuscript structure e.g. under each of the types of oral / intrauterine EC subheadings, have only history and evaluation (to include efficacy and future research) as further subsections, and discuss everything in paragraphs under these, and then summarise the structure in the introduction to guide audience. Other non-EC history issues discussed in the manuscript could be given a shorter section, e.g. within the introduction or prior to the conclusion, for mentions of EC IUDs as LARC and the argument about EC being an abortifacient. The current sections on these are quite long and probably even digress into issues that may be considered irrelevant to EC history or more of personal opinion e.g. that EC should be provided \"... irrespective of day of cycle...\" on page 11.\nExtra revision of the manuscript could also improve clarity and flow throughout with these suggestions - ensuring the history detail is in sequences (1920s prior to 1960s); specifying the year, or number of years over which, a product was introduced or phased out; avoiding repetition especially in the introduction section; avoiding digression e.g. the sentence on page 4 \"In order to use this method with modern oral contraceptives the tablets must be juggled around...\" appears out of place and should be removed; several sentences could be split or shortened; sections should focus on their purpose e.g. introduction narrating some background and what the manuscript will discuss, while conclusion summarising EC history and potential future; the current conclusion seems to introduce new issues that are irrelevant to the topic and even cited a new reference that possibly belongs somewhere else - where did 'hook-up culture' and 'Tinder' come from and how are they relevant to EC history?\nUnable to quickly find any better examples, kindly find here some links to articles that discuss contraception history to show use of specific times, shorter sentences and avoiding digression:\nhttps://www.pandiahealth.com/resources/birth-control-throughout-history/\nhttps://www.ellaone.co.uk/magazine/features/the-brief-history-of-contraception\nhttps://en.m.wikipedia.org/wiki/History_of_birth_control\n\"History of contraception\": https://www.sciencedirect.com/science/article/pii/S1744187006000874\n\nWith best wishes\n\nIs the topic of the review discussed comprehensively in the context of the current literature? Partly\n\nAre all factual statements correct and adequately supported by citations? Partly\n\nIs the review written in accessible language? Yes\n\nAre the conclusions drawn appropriate in the context of the current research literature? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-786
https://f1000research.com/articles/11-784/v1	12 Jul 22	{ "type": "Research Article", "title": "Viral load and gastrointestinal inflammation in COVID-19 patients", "authors": [ "Aditya Riadi Syafei", "Titong Sugihartono", "Iswan Abbas Nusi", "Poernomo Boedi Setiawan", "Herry Purbayu", "Ummi Maimunah", "Ulfa Kholili", "Budi Widodo", "Husin Thamrin", "Amie Vidyani", "Hasan Maulahela", "Yoshio Yamaoka", "Muhammad Miftahussurur", "Aditya Riadi Syafei", "Iswan Abbas Nusi", "Poernomo Boedi Setiawan", "Herry Purbayu", "Ummi Maimunah", "Ulfa Kholili", "Budi Widodo", "Husin Thamrin", "Amie Vidyani", "Hasan Maulahela", "Muhammad Miftahussurur" ], "abstract": "Background: ACE-2 receptors are well-known as binding receptors to spike protein of SARS-CoV-2 highly expressed in the gastrointestinal system. The Role of SARS-CoV-2 viral load and its effect on gut inflammation in COVID-19 patients are still not well-understood. This study aims to determine the impact of SARS-CoV-2 viral load on gastrointestinal inflammation. Methods: A total of 44 inpatient subjects who fulfilled eligibility criteria were examined for cycle threshold values from nasopharyngeal swab samples collected from several nucleic levels based on fluorescence signal and calprotectin levels of stool samples using Calprotectin enzyme-linked immunosorbent assay (ELISA) kit. Results: Of 44 subjects, 52.3% were male, with a median age of 52.5 years. Hypertension or diabetes was found in 26 patients. The median cycle threshold value was 31.3 with a value range of 10.9-40.0, median cycle threshold was significantly lower in subjects with comorbidity with P = 0.01. The median fecal calprotectin level was 42 μg/g with a value range of 5.1-1,393.7 μg/g, with median fecal calprotectin significantly higher in subjects with gastrointestinal symptoms with P = 0.008 with a relative risk (RR) of 5.5. There was a significant correlation between cycle threshold and fecal calprotectin in subjects with comorbidity with P <0.05, a coefficient contingency of 0.414. Conclusion: Subjects with comorbidity are prone to have higher viral loads paralleled with gastrointestinal inflammation. Subjects with overt gastrointestinal manifestations had a five-fold higher degree of gut inflammation.", "keywords": [ "COVID-19", "cycle threshold", "fecal calprotectin", "gastrointestinal symptoms", "infections" ], "content": "Introduction\n\nCoronavirus Disease 2019 (COVID-19) has been declared a global pandemic by World Health Organization (WHO) since March 2020.1 COVID-19 is caused by infection of Coronavirus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the genus of Betacoronavirus and family of Coronaviridae, similar to SARS-CoV and Middle East Respiratory Syndrome Coronavirus (MERS-CoV) that cause respiratory problems. The virus infects host cells that express Angiotensin-Converting Enzyme 2 (ACE-2) receptor, it is found higher in the lungs and gastrointestinal system. Infection of SARS-CoV-2 activates the innate immune system and then releases cytokines, chemokines, and pro-inflammatory mediators.2\n\nThe current diagnostic test suggested by WHO is based on Nucleic Acid Amplification Test (NAAT), such as Reverse-Transcription Polymerase Chain Reaction (RT-PCR). The cycle threshold is the number of replication cycles required by the fluorescence signal to pass the threshold. Cycle threshold inversely correlated to quantitative viral loads detected in the sample, although PCR testing does not distinguish live viruses from nonviable viruses.3,4 Several studies showed the clinical utility of cycle threshold value and high viral load correlated with disease severity, but other studies show no correlation in different samples settings.3,5,6 Clinical symptoms of COVID-19 are fever, cough, respiratory symptoms, and currently, extra-pulmonary clinical manifestations, including gastrointestinal, have been reported to vary in more than 20% of hospitalized patients. One study in 2020 showed the presence of the SARS-CoV-2 genome in stool samples.6,7 This proves that the SARS-CoV-2 infection in the gastrointestinal tract is thought to be caused by the expression of ACE-2 in the digestive tract. Transmembrane Serine Protease 2 (TMPRSS2) is expressed including in gastrointestinal epithelium, that facilitates cell entry by priming of the spike protein.8\n\nSeveral studies found virus RNA in stool specimens and anal swabs, however, it remains unclear when the virus starts shedding in the gastrointestinal tract and takes a longer duration of viral shedding than in the respiratory tract. Gastrointestinal manifestations in SARS-CoV-2 infected patients provide clues whether inflammation occurs in gastrointestinal tissue. Fecal calprotectin, a protein released by neutrophils and used as a direct marker of mucosal inflammation of any etiology, sensitive and non-invasive biomarker in mucosal inflammation.9,10 Diarrhea in cases of viral infection can naturally be inflammatory or non-inflammatory, based on the research data, it includes the results of non-inflammatory mechanisms. Another study in 2021 showed an increase in fecal calprotectin levels in 66.7% of COVID-19 patients in asymptomatic gastrointestinal tract patients.11,12\n\nThe gastrointestinal system in SARS-CoV-2 infected patients occur gut microbiome alteration characterized by a decrease in diversity with shifting toward pathogenic bacteria and away from beneficial symbionts. The virus enters cells by recognizing receptor ACE-2 to invade the host cell via TMPRSS2 and initiate an immune response that results in increased gut permeability and dysbiosis.12 Gut dysbiosis and ACE-2 impairment lead to a leaky gut. In a viral infection, high levels of circulating pro-inflammatory cytokines can alter the gut microbiome and disturb intestinal integrity. Increased inflammation in the intestine leads to a leaky gut allowing bacterial antigens and toxins to translocate to the systemic circulation, leading to worsening clinical outcomes in COVID-19 patients.12,13\n\nStudies analyzing fecal calprotectin levels in SARS-CoV-2 infection are relatively still limited.11 Some studies mention the association between cycle threshold values and disease severity, while other studies show significant fecal calprotectin increase results in COVID-19 patients, but studies on the association between the two have yet to be understood.5,6,11 We determined a correlation between the cycle threshold value of nasopharyngeal swab and fecal calprotectin in COVID-19 patients.\n\n\nMethods\n\nThis research was an observational analytic study with a cross-sectional design. We conducted consecutive sampling at Dr. Soetomo Teaching Hospital Surabaya from 1 September to 30 November 2020. Since there was no prior study of these specific subjects we decided to count the minimum sample size using infinite population formula. We analyzed 44 samples from non-ICU that meet this research eligibility criterion. Inclusion criteria were age 18 or above, a confirmed case of COVID-19, and signed participants’ agreement of this study. Exclusion criteria were the patient's refusal to participate in this study, gastrointestinal malignancies, liver cirrhosis, End-Stage Renal Disease, and Inflammatory Bowel Disease. Written informed consent was obtained from all patients and the research protocol approved by Faculty of Medicine, Universitas Airlangga-Dr. Soetomo Teaching Hospital Surabaya, Indonesia health research ethics committee with certificate number 0065/KEPK/IX/2020. Patients confirmed COVID-19 based on PCR results from nasopharyngeal swab specimens. The RT-PCR cycle threshold value was measured from an analytical phase of a nasopharyngeal swab specimen using a nucleocapsid (N) gene target with a negative value >40. Analytical phase was conducted in bio-safety level 2 facility in close system with automated process, using rt-PCR kit Biocov, Acon and light cycler Roche or Gentier (China). Cycle threshold value data were collected from clinical microbiologists at The Department of Clinical Microbiology Faculty of Medicine Universitas Airlangga, Surabaya. Fecal calprotectin level is calprotectin measured in the patient's feces sample. Stool preparations are taken by the nurse or by the patient. Stool with a minimum of five grams was analyzed using the PhiCal© Calprotectin enzyme-linked immunosorbent assay (ELISA) kit (Immundiagnostik AG, Stubenwald-Allee 8a, D-64625 Bensheim). Calprotectin remained stable in feces for six days with a normal reference value of <50 μg/g. We took 44 samples that were eligible for this study and analyzed all samples as subjects fulfilled all research variables.\n\nData were analyzed using the IBM SPSS Statistics version 25 (IBM Corp., USA). Demographic data and clinical characteristics are presented descriptively, frequency and percent for categorical data types (nominal and ordinal), while mean, standard deviation, median, and minimum-maximum for continuous data (interval and ratio). The independent variable is the cycle threshold value as numerical data (ratio and interval). The dependent variable is fecal calprotectin level as numerical data (ratio and nominal). Correlational numerical analytic tests carried out the association between variables in this study. The correlation test was performed using Pearson. The P-value that is considered statistically significant was <0.05 and the confidence interval (CI) was 95%.\n\n\nResults\n\nSubjects based on gender were male with 52.3% and female was 47.7%. The median age of subjects was 52.5 years with the youngest age of 18 years and the oldest of 65 years. The highest number of subjects was based on a range of age 51-60 years at 29.54%. Eighteen subjects were without comorbidity (40.9%) and the highest comorbidity in subjects was diabetes mellitus and hypertension in 14 patients (31.8%), followed by diabetes mellitus 18.2% and hypertension 9.1%. The characteristics of subjects based on clinical manifestations were cough 75%, fever 70.5%, shortness of breath 68.2%, and anosmia 9.1%. The characteristics of subjects based on gastrointestinal manifestations were anorexia 63.6%, nausea 38.6%, diarrhea 31.8%, vomiting 29.5%, and abdominal pain 11.4%. Mean symptom onset was 4.02 ± 2.64 days with a median of three days. The shortest onset was one day and the longest onset was 14 days.\n\nTable 1 shows median systolic and diastolic blood pressures of 130 and 80 mmHg, the median pulse of 88 times per minute, median respiratory rate of 21.5 times per minute, median axillary temperature of 36.7°C, and peripheral oxygen saturation of 97%. Laboratory characteristics of subjects showed a median lymphocyte value of 1,295/mm3 slightly below the normal range of 1,300-4,000/mm3, the median neutrophil-lymphocyte ratio was 4.9348, median ferritin was 588.4 μg/L, and median D-dimer was 1,150 μg/L.\n\nThe measurement of cycle threshold value was obtained based on fluorescence with RT-PCR technique used to detect SARS-CoV-2 genes in upper respiratory tract specimens of subjects. This value is obtained based on a real-time amplification curve based on signal changes and then determines the quantitative detection of SARS-CoV-2 at the nucleic acid level. The mean cycle threshold value for all subjects was 30.33 ± 6.07 with a median of 31.31, a minimum value of 10.09, and a maximum of 40.00. The median cycle threshold value in subjects with comorbidity was 30.4 significantly lower (P = 0.01). Comorbidity consists of diabetes mellitus, hypertension, or a combination of these. Distribution of subjects with gastrointestinal symptoms and subjects with diarrhea symptoms did not significantly differ in cycle threshold value (Mann-Whitney test, P = 0.921, and P = 0.521, respectively). Distribution of cycle threshold value in subjects group based on WHO severity classification also did not show a significant difference between mild, moderate, severe, or critical (the Kruskal-Wallis test, P = 0.436).\n\nBased on the kit used in the laboratory, fecal calprotectin cut-off value <50 μg/g was considered negative. In this study, 26 subjects (59.1%) with fecal calprotectin levels <50 μg/g, subjects with fecal calprotectin levels ≥50 μg/g were 18 patients (40.9%). The mean fecal calprotectin level in all subjects is 124.51 ± 240.54 μg/g with a median of 42 μg/g and a minimum value of 5.1 μg/g and a maximum of 1,393.7 μg/g. Table 2 showed the results of the Mann-Whitney test, statistically significant differences in fecal calprotectin increase in the group of subjects with gastrointestinal symptoms (61.70 vs 21.55 μg/g, P = 0.008, respectively). This study also found that fecal calprotectin correlates with hemoglobin levels with P < 0.05 and a coefficient correlation of -.307. The median value of fecal calprotectin levels was found higher in groups of subjects with symptoms of diarrhea than in subjects without symptoms of diarrhea (143.45 vs 24.4 μg/g, P < 0.0001, respectively). Subjects with symptoms of diarrhea tend to have fecal calprotectin levels ≥50 μg/g with a relative risk (RR) of 5.571 (95% CI; IQR 2.47-12.56) with P < 0.0001 in the Chi-Square test. This study also found that fecal calprotectin correlates with D-dimer in subjects with symptoms of diarrhea with P = 0.024 and a coefficient correlation of.598 (normal reference of D-dimer <500 ng/ml).\n\n* Mann-Whitney test; SD: Standard Deviation.\n\nThe non-parametric Spearman correlation test showed no significant correlation between the cycle threshold value and fecal calprotectin levels (P = 0.613; r = 0.078) in this study. Spearman's non-parametric test showed no statistically significant relationship between the cycle threshold value and fecal calprotectin levels in subjects with gastrointestinal symptoms and diarrhea symptoms (P = 0.353 and P = 0.817, respectively). However, in subjects with comorbidity, based on Fisher’s exact test there was a sufficient correlation between cycle threshold value with fecal calprotectin cut-off of ≥50 μg/g with P < 0.05, contingency coefficient of 0.414.\n\n\nDiscussion\n\nThis study found that viral load correlates with gastrointestinal inflammation in the population with comorbidity. This study also showed patients with comorbidity have higher viral loads than subjects without comorbidity. These findings suggest that comorbidity becomes an independent risk factor for gastrointestinal inflammation and an infection risk factor.14 Studies showed that people with comorbidity are at higher risk of infection and have more severe disease manifestations. Several studies suggested that patients with comorbidity had compromised immune systems to infection.15 This study found that subjects with comorbidity had a lower cycle threshold than subjects without comorbidity suggesting that patients with comorbidity are prone to have more viral load and inadequate immune response to infection. A study in 2020 found that the risk of infection in a population with comorbidities such as diabetes mellitus or hypertension is associated with the up-regulation of ACE-2. Another study also showed a risk of mortality relatively higher in populations with comorbidity.15,16\n\nWidely known SARS-CoV-2 is attached to ACE-2 receptors in the respiratory or gastrointestinal system. Up-regulation of ACE-2 receptors in comorbidity population, attached with the virus with inappropriate immune response causing ineffective defense mechanism against the virus and replicating at higher levels.15,16 A study in 2020 stated that patients with comorbidity had a decrease in gut microbiome diversity. The gut microbiome had several benefits as normal flora in gastrointestinal systems, such as a defense mechanism against pathologic entities. Several pathomechanisms disrupt gastrointestinal mucosal homeostasis.17 This study found in subjects with diarrhea symptoms, fecal calprotectin correlates with D-dimer. COVID-19 that occurs hypercoagulable state, caused by endothelial dysfunction that causes fibrin to degrade and release D-dimer protein component in the infected patient was found significantly increased. This pro-thrombotic state could induce tissue ischemia, including intestinal mucosa layer, activation of a local gut immune response, and induce calprotectin release.18,19 This study also found that fecal calprotectin negatively correlates with hemoglobin. This founding shed a new perspective on the role of thrombosis and the consequences of intestinal damage. Gastrointestinal inflammation correlates with more severe anemia due to colitis or micro gastrointestinal bleeding need further study to investigate. Hyper-inflammatory state in COVID-19 not only causes alteration in gastrointestinal homeostasis led to inflammation but also alters the metabolism of iron by producing hepcidin, in response to IL-6 activity, that causes reduced transferrin and inhibits iron absorption in the intestinal ultimately causing iron deficiency. The limited understanding of gastrointestinal inflammation and its effect on systemic iron metabolism needs further investigation.18–21\n\nThis study also found fecal calprotectin potential as a non-invasive biomarker to determine disruption of gastrointestinal mucosal homeostasis, whether due to direct viral infection on gut epithelial cells or secondary to systemic inflammation response. This study also found that gut inflammation happened more severely in subjects with an overt gastrointestinal manifestation such as abdominal pain, diarrhea, nausea, vomiting, and anorexia. One study suggests viral infect enteroids, disrupt intestinal permeability resulting in enterocyte dysfunction.22 Studies in 2020 also support these findings of significantly increasing fecal calprotectin in patients who suffered diarrhea.23 One study suggests that symptoms may be direct mucosal pathology of viral infection or secondary to virus-induced inflammation, in turn, due to the entry of inflammatory cells into intestinal mucosa, including neutrophils and lymphocytes, and thus disruption of gut microbiota. This also found higher viral loads in stool specimens in subjects with diarrhea symptoms.24 One study in 2021 found specific Immunoglobulin A (IgA) of Receptor Binding Domain (RBD) specific to SARS-CoV-2 in stool, this suggesting that immune response to inflammation in a gut system can be primary or secondary from a systemic response.25\n\nSeveral studies found that viral clearance in the gut system takes longer than in the respiratory system. Virus clearance in the gut system varies up to several days to weeks after seroconversion from upper respiratory samples.26 A study conducted in 2020 stated that patients with gastrointestinal symptoms have more extended duration virus clearance and are more likely to have positive stool tests. This suggests the potential risk of fecal-oral transmission and raises the question of whether this prolonged delayed clearance in the gut system causes persistent gastrointestinal inflammation or becomes one of the long COVID-19 manifestations that needs further investigation.27\n\nThere were several limitations of this study. The monocentric study with a small sample of this study might not be enough to represent the general population. Therefore, further investigation with more samples collected might be needed. In addition, this study did not consider the time of sample collecting and did not analyze with cycle threshold from anal swabs or stool specimens.\n\n\nConclusion\n\nThere were significantly higher viral loads in subjects with comorbidity in this study. Subjects with overt gastrointestinal manifestations had a five-fold higher degree of gut inflammation. Viral loads and gut inflammation were correlated in subjects with comorbidity.\n\n\nData availability\n\nFigshare. Raw Data of Viral Load and Gastrointestinal Inflammation Research in COVID-19 Patients.xlsx. DOI: https://doi.org/10.6084/m9.figshare.19769218.v2.28\n\nThis project contains the following underlying data:\n\n- The raw material data contain much information about general biodata patients, the observational result of vital signs, head/neck, thoracal, abdominal, and extremity.\n\n- In addition, the data include Peripheral Complete Blood Count, Inflammation markers, CT value to see the viral load, and the fecal calprotectin\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).\n\n\nAuthor contribution\n\nSyafei, AR: Conceptualization, Methodology, Writing—original draft preparation; Writing—review and editing; Sugihartono, T: Conceptualization, Writing—original draft preparation, Writing—review and editing; Nusi, IA: Methodology, Resource; Setiawan, PB: Data accuration, Validation; Purbayu, H: Methodology, Writing—review and editing; Maimunah, U: Methodology, Writing—original draft preparation; Kholili, U: Writing—review and editing, Validation; Widodo, B: Conceptualization, Writing—review and editing; Thamrin, H: Methodology, Resource; Vidyani, A: Data curration, Validation; Maulahela, H: Data accuration, Investigation; Yamaoka, Y: Data Accuration, Supervision; Miftahussurur, M: Conceptualization, Supervision, Writing—original draft preparation.", "appendix": "Acknowledgments\n\nThe authors would like to thank to Faculty of Medicine Universitas Airlangga, Surabaya, East Java, Indonesia.\n\n\nReferences\n\nDi Gennaro F, Pizzol D, Marotta C, et al.: Coronavirus Diseases (COVID-19) Current Status and Future Perspectives: A Narrative Review. Int. J. Environ. Res. Public Health. 2020; 17(8). PubMed Abstract \| Publisher Full Text Reference Source\n\nAmbrose PA, Goodman WA: Impact of COVID-19 on Patients with Inflammatory Bowel Disease. J. Explor. Res. Pharmacol. 2021 Oct 12.\n\nMagleby R, Westblade LF, Trzebucki A, et al.: Impact of Severe Acute Respiratory Syndrome Coronavirus 2 Viral Load on Risk of Intubation and Mortality Among Hospitalized Patients With Coronavirus Disease 2019. Clin. Infect. Dis. 2021 Dec 6; 73(11): e4197–e4205. PubMed Abstract \| Publisher Full Text\n\nTheodore DA, Greendyke WG, Miko B, et al.: Cycle Thresholds Among Solid Organ Transplant Recipients Testing Positive for SARS-CoV-2. Transplantation. 2021 Jul 1; 105(7): 1445–1448. PubMed Abstract \| Publisher Full Text\n\nFajnzylber J, Regan J, Coxen K, et al.: SARS-CoV-2 viral load is associated with increased disease severity and mortality. Nat. Commun. 2020 Oct 30; 11(1): 5493. PubMed Abstract \| Publisher Full Text\n\nZheng S, Fan J, Yu F, et al.: Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang province, China, January- March 2020: retrospective cohort study. BMJ. 2020; 369.Reference Source\n\nSurendra H, Elyazar IR, Djaafara BA, et al.: Clinical characteristics and mortality associated with COVID-19 in Jakarta, Indonesia: A hospital-based retrospective cohort study. Lancet Reg. Health – West. Pac. 2021 Apr 1 [cited 2022 Feb 15]; 9.Reference Source\n\nMitsuyama K, Tsuruta K, Takedatsu H, et al.: Clinical Features and Pathogenic Mechanisms of Gastrointestinal Injury in COVID- 19. J. Clin. Med. 2020; 9(11). PubMed Abstract \| Publisher Full Text Reference Source\n\nAmirian ES: Potential fecal transmission of SARS-CoV-2: Current evidence and implications for public health. Int. J. Infect. Dis. 2020 Jun; 95: 363–370. PubMed Abstract \| Publisher Full Text\n\nMcMahon CW, Chhabra R: The role of fecal calprotectin in investigating digestive disorders. J. Lab. Precis. Med. March 2018 [cited 2018 Jan 1]; 3(3). Publisher Full Text Reference Source\n\nShokri-Afra H, Alikhani A, Moradipoodeh B, et al.: Elevated fecal and serum calprotectin in COVID-19 are not consistent with gastrointestinal symptoms. Sci. Rep. 2021 Nov 9; 11(1): 22001. PubMed Abstract \| Publisher Full Text\n\nAktas B, Aslim B: Gut-lung axis and dysbiosis in COVID-19. Turk. J. Biol. Turk. Biyol. Derg. 2020; 44(3): 265–272.\n\nAan FJ, Glibetic N, Montoya-Uribe V, et al.: COVID-19 and the Microbiome: The Gut-Lung Connection. Ref. Module Food Sci. 2021.\n\nRudra S, Das S, Hoque E, et al.: Comorbidities of COVID-19 Patients with Low Cycle Threshold (Ct) Value of Nucleocapsid (N) Gene: An Application to Cluster-Based Logistic Model.(214): 5.\n\nBiswas M, Rahaman S, Biswas TK, et al.: Association of Sex, Age, and Comorbidities with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis. Intervirology. 2021; 64(1): 36–47.\n\nRabaan AA, Tirupathi R, Sule AA, et al.: Viral Dynamics and Real-Time RT-PCR Ct Values Correlation with Disease Severity in COVID-19. Diagnostics. 2021 Jun; 11(6): 1091. PubMed Abstract \| Publisher Full Text\n\nVillapol S: Gastrointestinal symptoms associated with COVID-19: impact on the gut microbiome. Transl. Res. J. Lab. Clin. Med. 2020 Dec; 226: 57–69.\n\nGiuffrè M, Di Bella S, Sambataro G, et al.: COVID-19-Induced Thrombosis in Patients without Gastrointestinal Symptoms and Elevated Fecal Calprotectin: Hypothesis Regarding Mechanism of Intestinal Damage Associated with COVID-19. Trop. Med. Infect. Dis. 2020 Sep; 5(3): 147. PubMed Abstract \| Publisher Full Text\n\nJose RJ, Manuel A: COVID-19 cytokine storm: the interplay between inflammation and coagulation. Lancet Respir. Med. 2020 Jun; 8(6): e46–e47. PubMed Abstract \| Publisher Full Text\n\nClaise C, Saleh J, Rezek M, et al.: Low transferrin levels predict heightened inflammation in patients with COVID-19: New insights. Int. J. Infect. Dis. 2022 Mar 1; 116: 74–79. PubMed Abstract \| Publisher Full Text\n\nBellmann-Weiler R, Lanser L, Barket R, et al.: Prevalence and Predictive Value of Anemia and Dysregulated Iron Homeostasis in Patients with COVID-19 Infection. J. Clin. Med. 2020 Aug; 9(8): 2429.\n\nOjetti V, Saviano A, Covino M, et al.: COVID- 19 and intestinal inflammation: Role of fecal calprotectin. Dig. Liver Dis. Off. J. Ital. Soc. Gastroenterol. Ital. Assoc. Study Liver. 2020 Nov; 52(11): 1231–1233.\n\nEffenberger M, Grabherr F, Mayr L, et al.: Faecal calprotectin indicates intestinal inflammation in COVID-19. Gut. 2020 Aug; 69(8): 1543–1544. PubMed Abstract \| Publisher Full Text\n\nBritton GJ, Chen-Liaw A, Cossarini F, et al.: Limited intestinal inflammation despite diarrhea, fecal viral RNA and SARS-CoV-2- specific IgA in patients with acute COVID-19. medRxiv. 2020 Jan 1. 2020.09.03.20183947.\n\nBritton GJ, Chen-Liaw A, Cossarini F, et al.: SARS-CoV-2-specific IgA and limited inflammatory cytokines are present in the stool of select patients with acute COVID-19. medRxiv. 2020 Jan 1. 2020.09.03.20183947.\n\nParasa S, Desai M, Thoguluva Chandrasekar V, et al.: Prevalence of Gastrointestinal Symptoms and Fecal Viral Shedding in Patients With Coronavirus Disease 2019. JAMA Netw. Open. 2020 Jun 11; 3(6): e2011335. PubMed Abstract \| Publisher Full Text\n\nZerbato V, Di Bella S, Giuffrè M, et al.: High fecal calprotectin levels are associated with SARS-CoV-2 intestinal shedding in COVID-19 patients: A proof-of-concept study. World J. Gastroenterol. 2021 Jun 14; 27(22): 3130–3137. PubMed Abstract \| Publisher Full Text\n\nSyafei AR, Sugihartono T, Nusi IA, et al.: Raw Data of Viral Load and Gastrointestinal Inflammation Research in COVID-19 Patients.xlsx. figshare. Dataset. 2022. Publisher Full Text" }	[ { "id": "145103", "date": "09 Aug 2022", "name": "Yen-Po Wang", "expertise": [ "Reviewer Expertise functional GI disease", "IBD", "GERD", "endoscopy", "small bowel endoscopy", "EUS" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a prospective study evaluating GI symptoms, diarrhea, and laboratory values in patients with COVID-19 infection. The idea was sound but the statistical analysis wasn't complete and therefore some issues need further clarification.\nMany diseases or conditions may be related with fecal calprotectin. The underlying disease of patients should be added in the demogrpahic data. How many patients had functional GI disease prior to COVID-19 infection? How many patients received abdominal surgery prior to COVID-19 infection?\n\nIn table 1, ferritin level should be further checked. Neurophil-lymphocyte ratio digit number should be identical. Standard deviation may be added on the table.\n\nIt seemed that many patietns had increasd fecal calprotectin in this study. How many patients had fecal calprotectin level >250 ug/g? What were their findings in colonsocopy? Were any of them found to have IBD?\n\nIn patients with diarrhea, did they receive stool culture exam? Are there any patients found with enteric infection, or even Clostridium difficile symptoms?\n\nWhat did 'gastrointestinal symptom' mean and include in this study?\n\nIn patients with comorbidity, fecal calprotectin was related with cycle threshold value. What is the difinition of comorbidity? How many patients had comorbidity? Did it mean GI comorbiidity or also other comorbidity? The authors stated that comorbitidy is an independent risk factor for GI inflammation, however, there is no multivariate analysis or regression analysis in evluating this issue in this study.\n\nWhen did the patients receive stool tests? What is the durgation between NP swab and stool tests?\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [ { "c_id": "8670", "date": "02 Sep 2022", "name": "Muhammad Miftahussurur", "role": "Author Response", "response": "Response to Reviewer 1: Thank you for your suggestion and questions. We did not put underlying disease into account, furthermore we excluded patients from samples based on criteria that we believed relate to fecal calprotectin level as we mentioned the exclusion criteria in Methods section Study design and participants page 10, we excluded patients with history of gastrointestinal malignancies and Inflammatory Bowel Disease. History of abdominal surgery we did not include in the criteria, therefore we will add it in the study limitations. Thank you for your suggestion. We will resolve the mis-type in ferritin and also add the mean and standard deviation as per the reviewer's suggestion. Thank you for your question. In this study we were using laboratory tool cut-off point from PhiCal© Calprotectin enzyme-linked immunosorbent assay (ELISA) kit (Immundiagnostik AG, Stubenwald-Allee 8a, D-64625 Bensheim) with value of <50 μg/g considered negative. Regarding samples with fecal calprotectin level >250 μg/g, there were six patients but due to limited resources and safety concerns, patients have not undergone colonoscopy, as we will add in the limitations. Thank you for your question. The total number of subjects involved in our study is 44 patients, none of them received stool culture examination nor stool examination. We will disclose this as limitations. Thank you for your question. We defined gastrointestinal symptoms as nausea, vomitting, anorexia, diarrhea and abdominal pain. We will add this definition in the Characteristic subjects. Thank you for your question and comment. In this study we grouped comorbidity as diabetes mellitus, hypertension, or both. In this study we found 26 patients with comorbidity. After we did regression we found no significant correlation between comorbidity and gut inflammation, therefore we will rephrase the statement ”comorbidity becomes an independent risk factor for gastrointestinal inflammation” to “comorbidity becomes a risk factor for an infection”. Thank you for your question. The patients received stool test within 24 hours after patients had confirmed positive results from nasopharyngeal swab." } ] }, { "id": "165778", "date": "04 Apr 2023", "name": "Ener Cagri Dinleyici", "expertise": [ "Reviewer Expertise Microbiota", "Intestinal microbiota composition" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a prospective study which aims to evaluate gastrointestinal involvement in patients with COVID 19, during the first phase of the pandemic in 2020. Although the idea was original at the time of the study, it has been more than 3 years since the pandemic and a vast knowledge of SARS-CoV-2 has emerged. The sample size is too small to make some conclusions, in addition to this, patient population is so heterogenous to evaluate GI inflammation. The authors make some conclusions about the GI invıolvement and presence of co-morbidities, but the sample size is not enough to make this conclusion. Fecal calprotectin is a marker for GI inflammation however not specific for one disease and might be increased in different conditions including FGID.\n\nIs the work clearly and accurately presented and does it cite the current literature? No\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nNo\n\nAre all the source data underlying the results available to ensure full reproducibility? No source data required\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] } ]	1	https://f1000research.com/articles/11-784
https://f1000research.com/articles/11-782/v1	12 Jul 22	{ "type": "Research Article", "title": "Storytelling and its influence on the promotion of tourism for the national sanctuary of Huayllay, Pasco Region, Peru in 2021", "authors": [ "Robert Alexander Jara Miranda", "Ghinnett Yoyssy Obregon Trujillo", "Huberta Violeta Obregon Trujillo", "Flor Alicia Calvanapón Alva", "Winston Rolando Reaño Portal", "Ghinnett Yoyssy Obregon Trujillo", "Huberta Violeta Obregon Trujillo", "Flor Alicia Calvanapón Alva", "Winston Rolando Reaño Portal" ], "abstract": "Background: The objective of the study was to determine the influence of storytelling in the tourism promotion of the Huayllay National Sanctuary. Methods: A quantitative approach study was used, a pre-experimental design with a single control group, and the study population consisted of 19 visitors to whom a pre-test and post-test were performed to evaluate the results obtained. The information collected was processed through the SPSS 26 statistical program and subsequently the event tree analysis (ETA) was performed to determine the degree of influence between the study variables. Results: Results of 0.677 and 0.795 indicate that storytelling does have an influence on the promotion of tourism for the study area. Conclusions: The study was able to determine that there is an influence between storytelling and tourism, and this can be used as a tourism promotion tool not only at the local level of the study site, but also at the national level.", "keywords": [ "Tourism", "storytelling", "promotion", "experiences", "destinations." ], "content": "Introduction\n\nIn recent decades, tourism has gained greater relevance around the world because it is a powerful alternative tool for economic growth, which is why it has become so dynamic for both the public and private sectors. In this sense, a great number of cities are looking for an ideal tool or strategy to promote their tourist destinations efficiently and achieve their consolidation in the competitive tourist market (Nieto, Román & Bonillo, 2016, p.129).\n\nUnder these circumstances, the idea was born to investigate the influence of a commercial communication tool called storytelling, which appeals to the emotional factor through stories, anecdotes and tales; it should be noted that storytelling already represents a successful model in countries such as Spain, Ecuador, China, Italy, and Cuba, where it has achieved an extraordinary influence due to its importance in the tourist's choices for their next destinations (Yavuz et al., 2016).\n\nBoari and Vidal (2020) analyzed the promotion of Cuban tourism using storytelling. They concluded that Cuban tourism efficiently uses storytelling for the promotion of its tourist destinations, taking into account all its cities and tourist attractions. As more than a trip, Cuba provides a reunion with the world that no longer exists.\n\nOn the other hand, Pancca (2018) attempted to determine the effectiveness of storytelling as a commercial strategy for the consolidation of textile artisans in the Cusco region. It was determined that only a small percentage of artisans use storytelling for advertising, and they are the ones that have managed to obtain the best results, such results are reflected in the increase of their sales.\n\nAs for storytelling in tourism, it is a recent phenomenon, despite the fact that storytelling has always been present in our lives. This tool tends to enhance the intangible aspects based primarily on emotional and narrative communication to convey a clear message that connects emotionally with the potential visitor (Acosta & Perez, 2019).\n\nRecent research in countries where tourism activity has prospered favorably support and have documented the effectiveness of storytelling for the promotion of tourist destinations. Compared to other conventional tools which only overload social networks with information, storytelling the effective communication of a tourist destination through the art of telling a story, tale, or experience, in a way that connects with the emotions and feelings of the potential visitor (Carbache et al., 2019).\n\nIn Peru, the promotion of tourist destinations still retains the sustained trend of relying mainly on traditional techniques, using basic tactics which lack creativity and do not exceed the standard promotion, which are very unconvincing and fail to connect emotionally with the potential tourist and, therefore, do not motivate the intention to travel (Camprubí, 2019). In recent years, given the competitiveness of tourist destinations, it has become necessary to investigate new tools to create a good differentiation strategy and increase the level of visitors to which tourist destinations aspire.\n\nThe lack of good techniques or tools for the promotion of tourist destinations prevents the possibility of increasing the flow of visitors, and therefore the opportunity to consolidate the tourism market. Emerging tourist destinations are the most affected, limiting development and preventing potential tourists from knowing about the tourist area and choosing it as an option when choosing a destination to which they wish to travel (Castillo & Castaño, 2015, p.7).\n\nAs a theoretical contribution of the present research, this constitutes a new perspective for tourism promotion, which will allow it to establish itself with greater consistency and solid foundations. Likewise, special attention will be paid to a tourism promotion tool such as storytelling, achieving a connection with the feelings and emotions of potential visitors, so that the promoted destination will be visited.\n\nIn practice, the impact of the research is that the proposed use of storytelling as a tool for tourism promotion of the Huayllay National Sanctuary will be favorable for the destination, since the use of new tools for the promotion of destinations is more efficient than the traditional ones and will allow achieving a greater flow of visitors, and its consolidation as a tourist destination. It should be noted that it will have a positive impact on the progress of tourism in the area.\n\nThe social contribution of the research is that on the one hand it will allow the future visitors to get to know a new tourist destination, from another point of view it will allow the local population to increase their economic income, and therefore the quality of life of the local population can be improved. They can also consolidate their destination in the tourist market as an ideal destination which should be visited. It will leave an innovative legacy for companies in the industry, which can choose to carry out their promotional campaigns using storytelling as a tourism promotion tool.\n\nFinally, as a methodological utility, it contributes with scientific methods through arguments, concepts, and information on tourism promotion. Likewise, to confirm its veracity, the measurement instruments will be validated. Special attention will be paid to the use of a relatively new tool for the tourism sector, storytelling, which currently does not have enough previous research at a national scope, so it will serve as a support for future research.\n\nFrom this perspective, the main objective of this research is to determine the influence of storytelling in the tourism promotion of the Huayllay National Sanctuary.\n\n\nMethods\n\nThe type of research used in the study was applicative and explanatory since it will investigate both variables, making use of science, and its primary mission is to provide a general solution to a practical problem.\n\nFor the present study, a pre-experimental design (pre-post) with a single control group was chosen, the study population consisted of visitors to the Huayllay National Sanctuary, and only the independent variable (storytelling) was manipulated, but not the dependent variable (tourism promotion).\n\nChávez (2020) indicates that the pre-experimental design allows the approach to a certain phenomenon under investigation. Subsequently, the formulation of a study hypothesis was carried out, so a stimulus is applied to a single group (pre-test and post-test) in order to appreciate its variation in the results (p.168).\n\nStorytelling is, naturally, the art of telling a story. Its most important characteristic lies in the connection that is created with the recipients, since the objective is to connect emotionally through a story, a tale, narration. This is based mainly on transmitting feelings and emotions since stories have the power to convince. In tourism it would focus on visiting the destination, motivated by the stories and videos giving rise to the visit of the place (Carbache et al., 2019).\n\nTourism promotion is one of the fundamental pillars of destination marketing. Since it is aimed at persuading potential tourists about the tourist offer. Likewise, the competitiveness of tourist destinations is subject to the way they promote themselves, therefore, tourism promotion is of radical relevance for destination management. In relation to this, tourism promotion can be divided into advertising, sales promotion and public relations (Castillo & Castaño, 2015).\n\nIn the present investigation the study population is constituted by the visitors of the Huayllay National Sanctuary, Pasco Region 2021. The sample of the present study was determined under a non-probabilistic sampling by convenience criterion, since it was subject to the researchers' criteria, so the sample size was established at 19 people.\n\nIn the present research, the survey technique was chosen. The survey is one of the research techniques with much greater effectiveness in social studies of a scientific nature, and many investigations usually begin and end with a survey (López & Fachellí 2016, p.6).\n\nThe use of the questionnaire instrument was considered two times, to determine if the storytelling influences the tourism promotion of the Huayllay National Sanctuary, Pasco Region 2021. After the respective analysis using the SPSS 26 statistical program, and finally the Eta test was carried out.\n\nTo provide validity to the evaluation instrument, the anticipated tests were tested and validated through the judgement of experts from the Cesar Vallejo University. Likewise, the Pearson coefficient was used, considering the following formula:\n\nTo find the correlation between the questions and the test as a whole, the McNemar corrector was used:\n\nS12: Changes of total scores\n\nS12: Question changes\n\nIf rMcN s greater than 0.35 the item is set as valid.\n\nFor the reliability of the work, a pilot test was carried out with 19 people using Cronbach's Alpha test, which obtained a value of 0.939. Once the reliability was demonstrated, the instrument was applied to the estimated sample according to the inclusion and exclusion criteria. Once the instrument had been assessed as reliable, the same methodology used in the pilot test was used to collect data from the study sample.\n\nBased on the data obtained from the application of the instrument (questionnaire), the information obtained was analyzed in depth using the SPSS 26 statistical program. The results will be interpreted by means of graphs and statistical tables.\n\nThe present study was respectful of the APA 7th edition norms, as well as the right to audit, the authors were cited accordingly, and the people who participated in the study were informed of its objectives. The research criteria of the Professional School of Tourism and Hotel Management of the César Vallejo University were followed.\n\nThe research was approved by a research ethics committee, set out in the documents entitled Annexes No. 2 and No. 3 “PROTOCOL FOR THE REVIEW OF RESEARCH PROJECTS BY THE RESEARCH ETHICS COMMITTEE”, chaired by Roberto Macha Huamán, President of the Research Ethics Committee of the Faculty of Business Sciences of the Universidad Cesar Vallejo.\n\nRegarding consent for participation in the research, participants were provided with a written informed consent form which was intended to provide information to the person about the survey. Information such as the use of the potential answers, the duration of the survey, the receipt of an incentive for answering the questionnaire and the assurance that the identity of each person would be protected, always keeping them anonymous, were included in this form.\n\n\nResults\n\nTable 1 shows that the publicity of the Huayllay National Sanctuary was at a deficient level in the Pre-Test corresponding to 100.00% (Jara Miranda et al., 2022). However, in the Post-Test the publicity showed an efficient level, since the result was 100.00%, which is indicated by the scale.\n\nTable 2 shows that the sales promotion of Huayllay National Sanctuary had a deficient level in the Pre-Test corresponding to 52.00%, a regular level of 47.9%. However, in the Post-Test, the sales promotion showed an efficient level, since the result was 78.9%, showing an improvement.\n\nTable 3 shows that the public relations of the Huayllay National Sanctuary were deficient in the pre-test, corresponding to 100.0%. However, the post-test showed an efficient level of public relations, since the result was 94.7%, showing an improvement.\n\nHa: Storytelling influences the Tourism Promotion of Huayllay National Sanctuary, Pasco Region 2021.\n\nHo: Storytelling does not influence the Tourism Promotion of Huayllay National Sanctuary, Pasco Region 2021.\n\nThe p-value of the Pearson's test (Sig.<0.05) is 0.000, so the null hypothesis can be rejected, and we accept the alternative hypothesis; concluding, indicating that; effectively storytelling influences the tourism promotion of the Huayllay National Sanctuary, Pasco Region 2021.\n\nBased on the results obtained, it is determined that the storytelling does influence the tourism promotion of the Huayllay National Sanctuary, and vice versa (Table 4). When applying the ETA test (Table 5), it was found that variable 1 has an influence on variable 2, with an ETA value of 0.795, and variable 2 has an influence on variable 1 with an ETA value of 0.677, with values close to 1 indicating that there is an influence between the two.\n\n\nDiscussion and conclusion\n\nThe present study shows the influence of storytelling for the tourist promotion of the National Sanctuary of Huayllay, in that sense, its clear influence was determined, as well as the high acceptance rate. This is like the research of Pancca (2018) who determined that only a small percentage of artisans use storytelling for advertising and are those who have managed to obtain the best results, such results are reflected in their increased sales. In the same way it agrees with the theory of Arkun, Keskin, and Ayar (2015) who indicate that storytelling as a tool for tourism promotion is an essential component for the marketing of tourist destinations, and is established as the way to publicize experiences, stories, and anecdotes to manifest different situations or data by way of stories whether real or fictional.\n\nTherefore, this study coincides with the research of Camprubí (2019), for which the primary objective was to examine the performance of storytelling in a tourist destination through the stories, narratives and legends of the place, concluded that the relevance of storytelling as a tool is solid and has demonstrated strength and effectiveness when promoting the tourist destination. Taking into account that the study area has myths and legends, which contribute favorably to the successful use of storytelling, contributing to the tool being more than effective within the study area.\n\nThis is one of the first studies at national level in relation to this new commercial communication tool oriented to the travel and tourism sector. It should be noted that there are other studies oriented to the advertising of recognized brands and even banking entities and they have demonstrated their solidity and strength.\n\nIn conclusion, the findings of the study show the influence of storytelling as a tool for tourism promotion of Huayllay National Sanctuary, so it could build an excellent alternative for the communication of tourist destinations.\n\n\nData availability\n\nZenodo: Storytelling and its influence on the tourist promotion of the national sanctuary of Huayllay, Pasco Region-2021. https://doi.org/10.5281/zenodo.6677467 (Jara Miranda et al., 2022).\n\nThis project contains the following underlying data:\n\n• Results-BAREMOS.xlsx (results in data processing tables)\n\n• STORY – RELIABILITY.xlsx (pilot test applied to 20 people to measure the reliability of the questionnaires)\n\n• SSPS STORY.xlsx (Survey collection database)\n\nZenodo: Storytelling and its influence on the tourist promotion of the national sanctuary of Huayllay, Pasco Region-2021. https://doi.org/10.5281/zenodo.6677467 (Jara Miranda et al., 2022).\n\nThis project contains the following extended data:\n\n• Questionnaire.docx (blank version of the questionnaire)\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).", "appendix": "References\n\nAcosta H, Perez G: Digital narratives, digital stories and transmedia narratives: systematic review of literature in education in education in the iberoamerican context. Revista Espacios. 2019; 40.Reference Source\n\nArkun A, Keskin H, Ayar H: The influence of Storytelling approach in Travel writings and readers empathy and Travel Intentions. Revista Social and Behavioral Sciences. 2015; 207: 577–586.Reference Source\n\nArias J: Research protocol III: the study population Revista Argelia de México.2016; 63: 201–206.Reference Source\n\nBoari C, Vidal D:2020. Cuban tourism through the use of technologies and practices such as storytelling tools. Alfa publications magazine. Reference Source\n\nCamprubí R: Storytelling in tourism destination branding: Girona case. Cuadernos de turismo. 2019; 46: 268–269.Reference Source\n\nCarbache C, Ureta S, Nervarez J: Contribution of Storytelling for the creation of emotional marketing in Bahía de Caráquez Ecuador 2019. Scielo. 2019; 10: 140–150. Publisher Full Text Reference Source\n\nCastillo M, Castaño V: Tourism promotion through traditional and new techniques. Studies and Perspectives in Tourism. 2015; 24: 737–757.Reference Source\n\nChávez.: Pre-experimental and quasi-experimental designs applied to social sciences and education. Reseachgate. 2020; 2: 168 167–168 178.Reference Source\n\nJara Miranda RA, Obregon Trujillo GY, Obregon Trujillo HV, et al.: Storytelling and its influence on the tourist promotion of the national sanctuary of Huayllay, Pasco Region-2021 [Data set]. Zenodo. 2022. Publisher Full Text\n\nNieto, Román, Bonillo: Tourism at the global level. Faculty of Economics and Business, University of Almeria;2016.Reference Source\n\nPancca V: Storytelling as an advertising technique for the positioning of textile artisans in the Cusco Region 2015-2017. Research Journal: Graduate School of the University of the Altiplano of Puno. 2018; 7.Reference Source\n\nSánchez R: Importance of tourism for the regions.2021.Reference Source\n\nYavuz M, Sumbul M, Ergec N, et al.: Storytelling in destination brand communication: A qualitative analysis. International Interdisciplinary. 2016.Reference Source" }	[ { "id": "151093", "date": "12 Dec 2022", "name": "Ambrocio Teodoro Esteves Pairazamán", "expertise": [ "Reviewer Expertise The area of research is based on my 03 degrees and is holistic because I research in the area of health", "education", "administration. And that I am a Biologist", "Bachelor in Education", "Bachelor in Administration and Master in Research and Teaching and also a Doctorate in Educational Administration." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article is important because it highlights the importance of storytelling specifically in the area of tourism, because we must take into account that through travel we have new experiences and emotions, so the proper use of this concept will allow us to connect more and better with people, while allowing an increase in tourism promotion of the country.\nThis study contributes substantially to storytelling being considered as a potential resource to boost the tourism sector. However, it is important to make some specifications in the methods used.\nWhat was taken into account when choosing Huayllay National Sanctuary as the setting for this research?\nIn addition to this, although it is known in the conclusion that there is a positive influence of storytelling as a tourism promotion tool for the Huayllay National Sanctuary, which is a positive point in the article, there is something that is still up in the air, which is to give a detailed explanation of why the ETA test was used as a technique to measure hypotheses between variables and why the use of more well-known relationship tests such as Pearson's Chi-Square or Spearman's Chi-Square was not considered.\nIt also remains to be clarified whether the same people used in the pilot test were considered within the total of the final sample chosen.\nAnd finally, it was considered whether there could be some kind of problem in the representativeness and generalization of the results obtained, due to the small sample of respondents.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "157194", "date": "03 Jan 2023", "name": "Iulia C. Muresan", "expertise": [ "Reviewer Expertise tourism management", "sustainable development", "consumer behaviour" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nDear author/s, the topic of the manuscript is interesting, however there are some aspect that must be improved:\nPlease state the research questions/research hyphotheses.\n\nIt is not clear which is the novelty of the research.\n\nPlease present the research instrument, and the profile of the respondents.\n\nThe sample size is really small. I strongly recommend to reconsider the sample size. It would be useful to present some data about the tourism activity in the region.\n\nPlease compare your results with other similar ones.\n\nWhich are theoretical contributions? what about the managerial implications?\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? No\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] } ]	1	https://f1000research.com/articles/11-782
https://f1000research.com/articles/11-778/v1	12 Jul 22	{ "type": "Brief Report", "title": "Acetylation mediates taurocholate uptake in hepatocytes possibly through modulation of NTCP1 activity", "authors": [ "Sayra Y. López-Ramirez", "Adriana M. López-Barradas", "Lilia G. Noriega", "Sayra Y. López-Ramirez", "Adriana M. López-Barradas" ], "abstract": "Hepatic Sodium Taurocholate cotransporter polypeptide (NTCP1) captures approximately 80% of the conjugated bile acids that come from the enterohepatic circulation. Transcriptionally, NTCP1 expression is activated by an RAR/RXR heterodimer, which is repressed by SHP when intracellular bile acids are high. In addition, NTCP1 activity is post-translational modulated by phosphorylation. However, whether NTCP1 could be regulated by acetylation is unknown. A bioinformatic analysis for the mouse NTCP1 protein sequence showed potential lysine acetylation sites. Thus, we evaluated taurocholate uptake in hepatocytes incubated with NAM, which induced a two-fold increase in the content of acetylated proteins. Interestingly, taurocholate uptake was reduced by 50% in hepatocytes incubated with NAM. These results demonstrate that acetylation mediates taurocholate uptake in hepatocytes possibly through modulation of NTCP1 activity.", "keywords": [ "Bile acids", "cotransporter", "post-translational modification" ], "content": "Introduction\n\nSodium Taurocholate cotransporter polypeptide (NTCP1), codified by the gene solute carrier 10A1 (SLC10A1), is a bile acid transporter dependent of sodium, which modulates bile acid enterohepatic circulation. NTCP1 expression in the basolateral membrane of hepatocytes captures approximately 80% of the conjugated bile acids that come from the enterohepatic circulation.1 The NTCP1 ortholog in mice is a protein with 362 amino acids and seven transmembrane domains.2 This transporter is unidirectional, and with a 2:1 stoichiometry, transporting two Na+ ions for each taurocholate molecule.3\n\nIntracellular and extracellular bile acid concentration regulates the activity and/or the expression of transporters implicated in bile acid enterohepatic circulation. For example, high intracellular concentration of bile acids are harmful to hepatocytes. Thus, high bile acids levels negatively regulate NTCP1 transcription as an adaptive response to decrease bile acid uptake, and alterations in this regulation is directly associated with cholestasis.4,5 Furthermore, NTCP1 expression is positively regulated by a heterodimer conformed by the retinoic acid receptor (RAR) with the retinoid receptor X (RXR), which is disturbed by the nuclear receptor Farnesoid X receptor (FXR). When bile acid concentration rises, FXR forms a heterodimer with RXR and binds to FXR/RXR response element in the SHP promoter. SHP then decreases the transactivation of RAR/RXR in the NTCP1 promoter, resulting in a decreasing NTCP1 expression.5,6\n\nIn addition to the transcriptional regulation, NTCP1 can also be regulated through post transductional modifications. In fact, NTCP1 is target of phosphorylation in serine and threonine residues. Specifically, a rise in cAMP leads to NTCP1 dephosphorylation at Ser226 promoting the translocation of NTCP1 to the membrane and its bile acid uptake activity.7,8 NTCP1 dephosphorylation is mediated by the protein phosphatase 2B (PP2B) that is activated by an increase of intracellular calcium.9 Moreover, the phosphorylation/dephosphorylation of the motif Thr225 and Ser226 is critical for NTCP1 plasma membrane localization.10 In addition to phosphorylation, NTCP1 endogenous ubiquitylation sites have been identified in murine tissues by mass spectrometry.11 In fact, NTCP1 is subjected to degradation via the ubiquitination/proteasomal pathway.12 Nevertheless, to our knowledge there has not been an evaluation of whether acetylation could be a post transcriptional modification affecting NTCP1 activity. Therefore, the aim of our work was to evaluate whether nicotinamide, a known general inhibitor of deacetylases that increases the acetylation status of intracellular proteins, could affect bile acid uptake and NTCP1 acetylation.\n\n\nMethods\n\nIn silico analyzes were performed for the mouse NTCP1 protein sequence (362 aa), with two software. We first used Prediction of acetylation on internal lysines (PAIL) (http://bdmpail.biocuckoo.org/) as described in previous studies.13 This software facilitates the identification of possible acetylation sites in internal lysines with an accuracy of 85–89%. The internal lysines with a score greater than one predicted by the PAIL program in the NTCP1 amino acid sequence were visualized in the protein structure using the open-source tool Protter (http://wlab.ethz.ch/protter/start/).14\n\nMouse primary hepatocytes were isolated from male C57BL/6 mice of 8–12 weeks of age obtained from the Departamento de Investigación experimental y Bioterio at Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubiran (INCMNSZ). The procedures were performed in accordance with the Mexican Federal Regulation for Animal Experimentation and Care (NOM-062-ZOO-2001) and approved by the Animal Ethics Research Committee of INCMNSZ (Approval number 1560). Briefly, primary hepatocytes were obtained by in situ perfusion of the liver according to the method by Berry and Friend.15 Firstly, we cannulated and exsanguinated the liver in vivo followed by a continuous perfusion with collagenase. Secondly, we removed the liver and disaggregated the tissue in Hanks balanced salt solution (HBSS). Thirdly, we filtered the cell suspension through a 70 μM mesh and washed the filtered cells twice with HBSS. Finally, we re-suspended the cells in DMEM/F-12 supplemented with 1% antibiotic and 10% fetal bovine serum.\n\nFirstly, we seeded hepatocytes into a 6-well or a 24-well CellBIND plate at 75% confluence and incubated at 37 °C. Unattached cells were removed by medium change after 4 hours. Cells were then treated with Nicotinamide 10 mM for 4 hours. After incubation, we used for western blot analysis cells in the 6-well plate as described below. On the other hand, cells in the 24-well plate were used to perform the taurocholate uptake assay.16 Briefly, hepatocytes were incubated in uptake buffer (D-glucose 11 mM, KCl 5.3 mM, CaCl2 1.8 mM, KH2PO4 1.1 mM, HEPES 10 mM MgSO4 0.8 mM, pH 7.4) with or without sodium 136 mM in presence of sodium taurocholate 10 μM supplemented with 0.1 μCi of [G-3H]-taurocholic acid (specific activity 1–5 Ci/mmol, Perkin Elmer) for 20 min at 37 °C. We then washed the cells three times with PBS 1x, and lysed with SDS 0.05%. An aliquot of cell lysate was placed in a vial with scintillation liquid. We used a beta liquid scintillation counter to quantify the amount of 3H in the cell lysate.\n\nPrimary hepatocytes incubated with nicotinamide were homogenized in lysis buffer (Tris-HCl 50 mM, EDTA 1 mM, NaCl 150 mM, NP-40 1%) supplemented with phosphatase inhibitors (NaP2O7 5 mM, Na3VO4 1 mM, NaF 50 mM), protease inhibitors (Complete mini, Roche), and deacetylase inhibitors (Nicotinamide 5 mM, Sodium butyrate 1 mM). Homogenates were centrifuged 10,000 g, 10 minutes at 4 °C, and protein concentration in supernatants was measured using the Lowry method (BioRad). Western blot was performed using 40 μg of total protein. Proteins were separated with a 10% SDS-PAGE and transferred to a PVDF membrane. To evaluate the acetylated status of hepatic proteins, PVDF membranes were incubated with an antibody against acetylated lysines (#9441, Cell signaling). Proteins were detected using ultrasensitive horseradish peroxidase chemiluminescence (Pierce). A tubulin antibody (sc-7396 Santa Cruz Biotechnologies) was used for normalization.\n\nThe data are depicted as the mean ± standard error of the mean (SEM). Densitometry analysis of acetylated proteins was quantified by ImageJ PC software. To assure reproducibility, taurocholate uptake experiments were performed four times. Our results were analyzed using a one-way ANOVA or an unpaired t-test using GraphPad Prism program v 7.0a (GraphPad Prism, GraphPad Software, Inc. La Jolla CA). Differences were considered significant at P<0.05.\n\n\nResults\n\nTo determine which internal lysines (K) on NTCP1 could be an acetylation target, the fasta sequence obtained from NCBI Slc10a1 [mus muculus] GenBank: AAH94023.1 was entered into the PAIL software. The in silico analysis showed eleven possible lysines that could be target of acetylation with a precision of 89.21%, four of these lysines had a score greater than one, which were K in positions 81, 113, 309 and 336. To locate these acetylation sites in the amino acid sequence and expected structure of NTCP1, we entered the NTCP1 amino acid sequence obtained from UniProt (UniProtKB-O08705) in Protter. The identified lysines were localized in the intracellular domains of NTCP1, except for K81 that was localized in an extracellular domain (Figure 1A).\n\nA) Predicted topological structure of mouse sodium and bile acid co-transporter NTCP1 generated using Protter v 1.0. We observe the seven transmembrane domains, and the extracellular amino-terminus and the intracellular carboxy-terminus identified by Phobius. High-throughput phosphorylation, ubiquitylation, and N-glycosylation sites are indicated according to phosphosite.com. The identified internal lysines by the in silico PAIL analysis as potential acetylation sites are highlighted in red. B) Global lysine acetylation in primary hepatocytes incubated with nicotinamide (NAM) 10 mM for 4 h. Lysates were analyzed by western blot using an anti-acetylated–lysine (AcK) antibody. The loading control was tubulin. Data are presented as mean ± SEM and * indicates a significant difference versus vehicle (V) at P < 0.05 by Student’s t-test. C) [3H]-Taurocholate uptake into primary hepatocytes was determined to evaluate NTCP1 activity. We performed four independent biological experiments with primary hepatocytes obtained from different C57BL6 mice and each experiment included at least 4 replicates. Significant difference is designated by letters were a > b at P < 0.05 by One-way ANOVA.\n\nThe effect of acetylation on taurocholate uptake was evaluated in mouse primary hepatocytes treated with or without nicotinamide 10 mM for 4 hours. Nicotinamide incubation significantly increased acetylated proteins with respect to the control (Figure 1B). Unfortunately, we were unable to immunoprecipitate NTCP1 and to confirm whether NTCP1 was specifically acetylated. Nevertheless, when we evaluated taurocholate uptake, which depends mainly on NTCP1 activity, it was significantly increased in hepatocytes treated with NaCl 136 mM when compared to those without NaCl. Notably, when hepatocytes were previously treated with nicotinamide, we observed a significant reduction on taurocholate uptake (Figure 1C), suggesting that NTCP1 activity may depend on acetylation.\n\n\nDiscussion\n\nOur results demonstrate that an increase in acetylated proteins is associated with a decrease in taurocholate uptake by primary hepatocytes. Unfortunately, we were unable to evaluate whether this effect was a result of direct acetylation of NTCP1. However, our result suggest that acetylation is a postraductional modification that could impact hepatic bile acid homeostasis.\n\nAcetylome analysis has provided evidence about the implications of this post-translational modification on physiological and pathological circumstances. For example, acetylation increases in skeletal muscle during aging17 and insulin resistance,18 affecting the activity of several proteins including enzymes, transcriptional factors, among others. However, few reports have thus far reported the acetylation of cotransporters. We have recently showed that acetylation regulates the stability and activity of the potassium-chloride cotransporter 4 (KCC4) in kidney.19 Thus, it is possible that NTCP1 stability or activity may also be modulated directly by acetylation. However, it is also possible that the decrease in taurocholate uptake could be the result of acetylation of FXR, which is known to increase its stability and inhibits its dimerization with RXR,20 possibly affecting NTCP1 expression.\n\nAcetylation of proteins depends on acetyl-CoA levels and the activity of acetylases and deacetylases such as sirtuins, which are dependent of NAD levels. Therefore, maximum acetylation is normally achieved during feeding conditions, and also with minimal mitochondrial activity.21 This suggest that bile acid uptake in the liver will be restricted during feeding condition and promoted during fasting. In fact, Dumaswala et al. reported that hepatic basolateral membrane (BLM) taurocholate uptake is enhanced by 65% in fasted animals.22 Furthermore, the regulation of NTCP1 activity by acetylation may decrease bile acid uptake in pathologies where hyperacetylation of hepatic proteins is also observed, such as fatty liver disease. However, additional research is necessary to demonstrate its implications.\n\nIn conclusion, our results demonstrate that acetylation mediates taurocholate uptake in hepatocytes possibly through modulation of NTCP1 activity.\n\n\nData availability\n\nFigshare: Acetylation mediates taurocholate uptake in hepatocytes possibly through modulation of NTCP1 activity. https://doi.org/10.6084/m9.figshare.19226010.v2\n\nThis project contains the following underlying data:\n\n1. An excel file with: 1) the raw data of the in-silico analysis performed in PAIL; 2) the raw data of the densitometry analysis of global lysine acetylation; and 3) the raw data of the taurocholate uptake assay.\n\n2. Raw images of western blots for acetylated lysines (AcK) and tubulin.\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\n\nAuthor contributions\n\nConceptualization, S.Y.L.R. and L.G.N.; investigation, S.Y.L.R. and A.M.L.B.; formal analysis, S.Y.L.R. and L.G.N.; funding acquisition, L.G.N; writing—original draft preparation, S.Y.L.R. and L.G.N.; writing—review & editing, L.G.N.; All authors have read and agreed to the published version of the manuscript.", "appendix": "Acknowledgments\n\nWe thank all members of Fisiología de la Nutrición department for discussion, Sayra Y. López-Ramirez is a doctoral student from Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México (UNAM) and received fellowship 512595 from CONACYT.\n\n\nReferences\n\nHagenbuch B, Scharschmidt BF, Meier PJ: Effect of antisense oligonucleotides on the expression of hepatocellular bile acid and organic anion uptake systems in Xenopus laevis oocytes. Biochem. J. 1996 Jun 15; 316(Pt 3): 901–904. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nMareninova O, Shin JM, Vagin O, et al.: Topography of the membrane domain of the liver Na+-dependent bile acid transporter. Biochemistry. 2005 Oct 25; 44(42): 13702–13712. PubMed Abstract \| Publisher Full Text\n\nWeinman SA: Electrogenicity of Na(+)-coupled bile acid transporters. Yale J. Biol. Med. 1997 Jul-Aug; 70(4): 331–340. PubMed Abstract \| Free Full Text\n\nAnwer MS, Stieger B: Sodium-dependent bile salt transporters of the SLC10A transporter family: more than solute transporters. Pflugers Arch. 2014 Jan; 466(1): 77–89. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nAnwer MS: Cellular regulation of hepatic bile acid transport in health and cholestasis. Hepatology. 2004 Mar; 39(3): 581–590. PubMed Abstract \| Publisher Full Text\n\nTrauner M, Boyer JL: Bile salt transporters: molecular characterization, function, and regulation. Physiol. Rev. 2003 Apr; 83(2): 633–671. PubMed Abstract \| Publisher Full Text\n\nAnwer MS, Gillin H, Mukhopadhyay S, et al.: Dephosphorylation of Ser-226 facilitates plasma membrane retention of Ntcp. J. Biol. Chem. 2005 Sep 30; 280(39): 33687–33692. PubMed Abstract \| Publisher Full Text\n\nWebster CR, Blanch C, Anwer MS: Role of PP2B in cAMP-induced dephosphorylation and translocation of NTCP. Am. J. Physiol. Gastrointest. Liver Physiol. 2002 Jul; 283(1): G44–G50. PubMed Abstract \| Publisher Full Text\n\nKosters A, Karpen SJ: Bile acid transporters in health and disease. Xenobiotica. 2008 Jul; 38(7-8): 1043–1071. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nStross C, Kluge S, Weissenberger K, et al.: A dileucine motif is involved in plasma membrane expression and endocytosis of rat sodium taurocholate cotransporting polypeptide (Ntcp). Am. J. Physiol. Gastrointest. Liver Physiol. 2013 Nov 15; 305(10): G722–G730. Epub 2013 Sep 5. PubMed Abstract \| Publisher Full Text\n\nWagner SA, Beli P, Weinert BT, et al.: Proteomic analyses reveal divergent ubiquitylation site patterns in murine tissues. Mol. Cell. Proteomics. 2012 Dec; 11(12): 1578–1585. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKühlkamp T, Keitel V, Helmer A, et al.: Degradation of the sodium taurocholate cotransporting polypeptide (NTCP) by the ubiquitin-proteasome system. Biol. Chem. 2005 Oct; 386(10): 1065–1074. PubMed Abstract \| Publisher Full Text\n\nLi A, Xue Y, Jin C, et al.: Prediction of Nepsilon-acetylation on internal lysines implemented in Bayesian Discriminant Method. Biochem. Biophys. Res. Commun. 2006 Dec 1; 350(4): 818–824. Epub 2006 Oct 2. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nOmasits U, Ahrens CH, Müller S, et al.: Protter: interactive protein feature visualization and integration with experimental proteomic data. Bioinformatics. 2014 Mar 15; 30(6): 884–886. Epub 2013 Oct 24. PubMed Abstract \| Publisher Full Text\n\nBerry MN, Friend DS: High-yield preparation of isolated rat liver parenchymal cells: a biochemical and fine structural study. J. Cell Biol. 1969 Dec; 43(3): 506–520. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHarris MJ, Kagawa T, Dawson PA, et al.: Taurocholate transport by hepatic and intestinal bile acid transporters is independent of FIC1 overexpression in Madin-Darby canine kidney cells. J. Gastroenterol. Hepatol. 2004 Jul; 19(7): 819–825. PubMed Abstract \| Publisher Full Text\n\nKoltai E, Szabo Z, Atalay M, et al.: Exercise alters SIRT1, SIRT6, NAD and NAMPT levels in skeletal muscle of aged rats. Mech. Ageing Dev. 2010 Jan; 131(1): 21–28. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nHirschey MD, Shimazu T, Jing E, et al.: SIRT3 deficiency and mitochondrial protein hyperacetylation accelerate the development of the metabolic syndrome. Mol. Cell. 2011 Oct 21; 44(2): 177–190. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNoriega LG, Melo Z, Rajaram RD, et al.: SIRT7 modulates the stability and activity of the renal K-Cl cotransporter KCC4 through deacetylation. EMBO Rep. 2021 May 5; 22(5): e50766. Epub 2021 Mar 22. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nKemper JK, Xiao Z, Ponugoti B, et al.: FXR acetylation is normally dynamically regulated by p300 and SIRT1 but constitutively elevated in metabolic disease states. Cell Metab. 2009 Nov; 10(5): 392–404. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nNeufeld-Cohen A, Robles MS, Aviram R, et al.: Circadian control of oscillations in mitochondrial rate-limiting enzymes and nutrient utilization by PERIOD proteins. Proc. Natl. Acad. Sci. U. S. A. 2016 Mar 22; 113(12): E1673–E1682. Epub 2016 Feb 9. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDumaswala R, Berkowitz D, Setchell KD, et al.: Effect of fasting on the enterohepatic circulation of bile acids in rats. Am. J. Phys. 1994 Nov; 267(5 Pt 1): G836–G842. PubMed Abstract \| Publisher Full Text" }	[ { "id": "172933", "date": "17 Aug 2023", "name": "Giuliano Ciarimboli", "expertise": [ "Reviewer Expertise Transporters", "regulation" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript “Acetylation mediates taurocholate uptake in hepatocytes possibly through modulation of NTCP1 activity” by López-Ramirez et al. is a brief report suggesting that acetylation may regulate activity of the hepatic Sodium Taurocholate cotransporter polypeptide (NTCP1).\nThis idea is physiologically of high interest. In their work the authors tried to substantiate this idea by performing a bioinformatic analysis of the murine NTCP1 sequence to identify potential acetylation site. Then, they measured the taurocholate uptake in murine primary hepatocytes and the presence of acetylated proteins in lysates from these hepatocytes under inhibition of deacetylation by nicotinamide. The results of this investigation were that 1) the sequence of murine NTCP1 contains potential acetylation sites; 2) deacetylation inhibition by nicotinamide increases protein acetylation and decreases taurocholate uptake in murine primary hepatocytes.\nThese results are indeed very interesting, but I think that they are too preliminary to give the work an academic merit. For example, after identifying potential acetylation sites in murine NTCP1, I would expect that these sites are mutated and that the transport properties of mutated and wild-type NTCP1 are investigated in an expression system. In the same way, I would expect a better characterization of NTCP1 modulation by nicotinamide in primary hepatocytes: what is the mechanism at the basis of this regulation? A change in transporter affinity or in transporter turn-over?\nSpecific comments: Material and Methods:\nPrimary hepatocyte isolation: for the readers, who are not familiar with this technique, it would be interesting to know how pure this preparation is. Does it contain other cells than hepatocytes?\n\nTaurocholate assay has been performed in the presence or not of 136 mM Na+. Did the authors perform control experiments to exclude that osmotic effects are responsible for the measured uptake differences, for example using 136 mM N-methyl-D-glucamine instead of Na+?\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Partly\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate? Yes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "187394", "date": "17 Aug 2023", "name": "Stan F J van de Graaf", "expertise": [ "Reviewer Expertise Bile salt uptake transporters" ], "suggestion": "Not Approved", "report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe present manuscript by López-Ramirez et al. describes a possible novel post-translation modification of NTCP and its potential functional consequence. As I require two disclaimers like “possible” and “potential” within a single summarized sentence to discuss the data, no strong, convincing data is to be expected.\nMajor comments\nNo data is provided that suggests that NTCP it directly modified by acetylation. A total cellular lysine acetylation is shown and functional consequences of a high concentration of very a-specific drug that affects multiple processes, not specific for acetylation.\nAs it has been described previously that other transporters contribute significantly to TCA uptake in mouse hepatocytes, a sodium-free condition with NAM should have been included in Figure 1C.\nThe relevance of acetylation for human NTCP is not discussed, nor experimentally tested, not even if the lysine residues are conserved in other species. No NTCP blot is included.\nMinor comments\nNTCP is the full official protein name, not NTCP1.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? No\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate? No\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? No", "responses": [] } ]	1	https://f1000research.com/articles/11-778
https://f1000research.com/articles/11-776/v1	12 Jul 22	{ "type": "Research Article", "title": "Assessment of cardiorespiratory fitness among medical students: a prospective study", "authors": [ "Abhishek Sharma", "Shiva Pratik Sah", "Ashik Rajak", "Ayush BC", "Aashutosh Sah", "Rabindra Dhakal", "Nawanit Maskey", "Samyak Bajracharya", "Aavash Mishra", "Goody Jha", "Shiva Pratik Sah", "Ashik Rajak", "Ayush BC", "Aashutosh Sah", "Rabindra Dhakal", "Nawanit Maskey", "Samyak Bajracharya", "Aavash Mishra", "Goody Jha" ], "abstract": "Background: Physical activity and fitness level of fitness decline mostly between adolescence and early adulthood. This leads to risks of non-communicable diseases in the future. Medical students, assumed to have an extensive understanding of physical exercise and its benefits, are less active than they were before attending graduate school. This study aimed to assess changes in physical fitness and physical activity of students over-time. Methods: This was a prospective study undertaken at Basic Science Complex of Kathmandu Medical College Teaching Hospital in Nepal. In total, 72 medical students were put through a modified Harvard step test during their first year and then three years later during their third year at medical school. Maximum aerobic capacity (VO2 max) was calculated subsequently by plotting the average pulse rate on the Astrand-Rhyming Nomogram. Results: The mean value of relative maximum aerobic capacity (VO2 max) decreased from first year to the third year. When the mean values of body mass index and relative maximum aerobic capacity were compared between first year and third year, the difference was found to be statistically significant (p-value=0.000). The physical fitness index and relative maximum aerobic capacity in both years were positively correlated r (70) = +.59, p<0.001(first year); r (70) = +.47, p<0.001(third year). Meanwhile, body mass index and relative maximum aerobic capacity in the third year were negatively correlated and statistically significant with r (70) = -0.23, p=.045. Conclusions: Cardiorespiratory fitness of the students steadily declined as they progressed through their academic years. Positive correlation between cardiorespiratory fitness and physical fitness index was established along with negative correlation between body mass index and cardiorespiratory fitness. The findings in this study expose the lack of fitness in youth as they focus more on academics, giving the impression that they forget to implement a fitness routine in their lifestyle.", "keywords": [ "Cardiorespiratory fitness", "Harvard step test", "Medical students", "Physical fitness index", "Relative VO2max", "VO2max" ], "content": "Abbreviations\n\nBMI: Body mass index\n\nNCDs: Non-communicable diseases\n\nPFI: Physical fitness index\n\nVO2 max: Maximum aerobic capacity\n\n\nIntroduction\n\nNon-communicable diseases (NCDs) are the leading cause of death worldwide and are emerging as a global health threat. NCDs account for 71% of all deaths globally, out of which 77% of death are in middle and low income countries according to data extracted from WHO website on NCDs which was last updated on 13th April, 2021.1 Physical fitness is considered one of the most important health markers, as well as a predictor of morbidity and mortality of various non-communicable diseases.2 About one and a half million deaths due to NCDs worldwide annually can be attributed to insufficient physical activity.1\n\nPhysical fitness is defined as a set of attributes or characteristics individuals have or achieve, that relates to their ability to perform physical activity3 while physical activity is defined as any bodily movement produced by skeletal muscles that result in energy expenditure.4 A higher level of physical fitness is credited with lower rates of cardiovascular disease and also has positive effects on depression, anxiety, mood status, and self-esteem.2,5 However, the physical activity and fitness level of youth is steadily declining with more than one-third of the population being unfit - which appears to occur during adolescence and early adulthood.6 A recent study also showed a marked decline during high school and university years.7 College life is a period during which individuals have to struggle with academic workload, lack of free time - often picking up habits like smoking and lack of balanced diet posing a barrier to the adoption of healthy practices.8 In spite of this, it is presumed that medical students have substantial knowledge about physical activity and its benefits. However, research has shown that more than half of the clinicians and medical students perform less physical activity, as compared with their levels of activity undertaken prior to graduate training.7\n\nAs health care professionals, medical students will influence their patient's attitude toward maintaining optimal physical fitness and advocating good health physical exercise. For better productivity, students should be healthy and have good physical fitness.9 Therefore, there is a need for students to measure and analyze their physical fitness for their benefit. There are few studies regarding physical fitness among medical students in Nepal. Hence, the present study emphasizes assessing physical fitness among young medical students in a tertiary care hospital with the help of a heart rate which is measured in terms of maximum aerobic capacity (VO2 max). VO2 max has been considered by the World Health Organization as the single best indicator of cardiorespiratory fitness.10 Cardiorespiratory fitness is the overall capacity of the cardiovascular and respiratory systems and the ability to carry out prolonged strenuous exercise. It is one of the most frequently cited measurable components of physical fitness; other components include muscular endurance, muscular strength, body composition, and flexibility.3 VO2 max is the maximal oxygen consumption attained during a graded maximal exercise to voluntary exhaustion.11,12 Direct measurement of VO2 max is the standard index of cardiorespiratory fitness, although the use of indirect measurement of VO2 max is considered suitable for epidemiological studies.13\n\nIn the present study, a step test has been used for measuring the VO2 max of students as it is considered to be a practical field test for assessing individual aerobic fitness.14 This prospective study aimed to assess changes in physical fitness and physical activity of students in their first year at medical school followed up in the third year to assess the changes.\n\n\nMethods\n\nThis was a prospective study conducted in Basic Science Complex of Kathmandu Medical College Teaching Hospital, Duwakot in Nepal between January 2017 and January 2020. It included apparently healthy male and female medical students in their first year willing to participate voluntarily. The same participants were followed up during their third year and underwent the same test. Participants having any acute or chronic illness, locomotive and musculoskeletal disability, and those taking regular medications were not included in this study. Convenience sampling was used to collect data, which included all 150 medical students in the class. The students were briefed in the class about the project and were asked for voluntary consent, and 72 of the participants agreed to take part in the research. Since this was a convenient sampling we were not able to address potential bias in the study. The limitation of this design is that it lacks generalizability and may not be representative of the sample population.\n\nThe data was collected, compiled and analyzed using Statistical Package for the Social Sciences (SPSS) software version 20. Analysis was done using descriptive statistics like frequency, percentage, mean, standard deviation, and inferential statistics like students t-test and Pearson correlation analysis.\n\nEthical clearance was obtained from the Institutional Review Committee of Kathmandu Medical College (approval reference number: 30122016, approved granted on 30th December 2016) prior to data collection. Informed written consent with details of ethical issues (confidentiality, anonymity, and beneficence) was obtained from all the participants of this study. All procedures were conducted in accordance with the principles of the Declaration of Helsinki. Participants received no monetary compensation.\n\nPrior explanation about the aim and purpose of the study, test procedure, method of testing, and instructions on how to perform the test were given. Detailed history of each participant was taken which included any history of hypertension, diabetes, asthma or any chronic illness along with any medications being taken. They were also assessed for any physical disabilities and their anthropometric measurements like weight, height, and body mass index were noted. Weight was measured with CAMRY digital weighing scale Model no EB9374. Subsequently, the students were put through a modified Harvard Step Test. The step test was conducted in a closed room during evenings at the hostel premises for the convenience of the students. The step test was undertaken by the authors themselves with proper instructions. The process undertaken to conduct the Harvard step Test was replicated completely during the follow-up session with no difference in the procedure.\n\nThe Harvard Step Test is a submaximal step test used as an indirect predictor of VO2 max. Submaximal step tests are those tests that measure the VO2 max without the test protocols reaching the maximum of their cardiovascular and respiratory system performance. The original Harvard Step Test was developed for taller people of western countries by Brouha et al (1943) during World War II which consisted of a big step with a height of 20 inches.15 However, this test is not applicable to relatively shorter people of Nepal. The application of the original Harvard Step Test was also found to be unsatisfactory in the Indian population because of the step height of 20 inches.16 Therefore, in the modified Harvard Step Test, a shorter step height of 16 inches has been used.\n\nAfter familiarizing the participants with the Harvard Step Test, resting pulse rate was noted. The participants were then asked to step up and down the step. A metronome was used to maintain the rhythm. On the count of one, the participants would keep one foot on the bench followed by the other; on the count of two he/she would put the first foot off the bench followed by the other. The participants were asked to step up and down 20 times per minute according to the metronome for five minutes or until exhaustion.17 Exhaustion is defined as the point when the participant can no longer maintain the stepping rate for 15 seconds. The time was noted with the help of a stopwatch. At the end of the test, the participants were asked to sit on a chair and the pulse was measured. The pulse was recorded during one to one and half minute, two to two and half minute, three to three and half minute interval immediately after the test. This is called recovery pulse.16 VO2 max was then calculated by plotting the average pulse rate on the Astrand-Rhyming Nomogram.18\n\nPhysical fitness was calculated by the formula:\n\n\nResults\n\nA total of 150 participants were approached to include in the study. However, only 72 participants met the inclusion criteria after undergoing examination for eligibility and giving consent and were hence included in the study.33 Among them, 49 were men and 23 were women. In the follow-up session all 72 participants were again assessed for any new disabilities, illness or intake of medications and all were deemed eligible and participated in the study. No participants were lost to follow-up. Majority of the participants were adolescents within the age range of 18-22 years. The mean ± standard deviation (SD) of BMI, physical fitness index (PFI) and relative VO2 max is shown in Table 1.\n\nWhen the mean values of BMI and Relative VO2 max was compared between the first year and the third year, the difference was found to be statistically significant with P value of 0.000. However, the difference in mean value of PFI was not found to be statistically significant with P value of 0.610 (Table 1).\n\nMajority of the participants had a normal BMI. Number of participants who were underweight decreased from 15 to 9 whereas the number of participants in the overweight and obese groups increased (Table 2).\n\nMost of the students had excellent PFI scores, 55 students in the first year and 56 in the third year. Only 5 students had poor PFI in the first year and 6 had poor PFI in the third year (Table 3).\n\nPhysical fitness Index mean value was similar, with 78.87±18.86 and 79.43±19.99 in the first and the third year respectively. It was found that there was no significant difference in the mean values of Physical fitness index in the first and the third year (Table 4).\n\nThis table shows the comparison of categories of BMI with relative Vo2 max in the first year. The majority of the participants fall under the normal BMI category and had a relative v02 max of 37.92 ml/kg/min. Only 16 participants fall under the overweight and obese category of BMI and had a comparatively lower relative Vo2 max of 36.19 ml/kg/min and 34.09 ml/kg/min respectively (Table 5).\n\nThrough this table we can see that the mean relative V02 max has decreased from the first year to the third year. The mean relative VO2 max was 37.46±7.67 ml/kg/min in the first year vs 34.95±7.7 ml/kg/min in the third year. In the table we can also see that a higher change in VO2 max was seen in the male population with 3.1ml/kg/min difference in the first year and the third year (Table 6).\n\nIn the first year, the correlation coefficient between PFI and relative VO2 max was 0.594 with a P value of 0.000 which was statistically significant. Students with a higher VO2 max also had high PFI (Table 7).\n\n Correlation is significant at the 0.01 level (2-tailed).\n\nIn the third year, the correlation coefficient between Physical Fitness Index and relative VO2 max was found to be 0.475 with a P value of 0.000. The correlation was found to be statistically significant (Table 8).\n\n Correlation is significant at the 0.01 level (2-tailed).\n\nThe correlation coefficient between BMI and relative VO2 max in the first year was found to be -0.123 with a P value of 0.302. The correlation was not found to be statistically significant (Table 9).\n\nThe correlation coefficient between BMI and Relative VO2 max in third year was found to be -0.238 with a P value of 0.045. The correlation was found to be inverse and statistically significant (Table 10).\n\n* Correlation is significant at the 0.05 level (2-tailed).\n\n\nDiscussion\n\nThis study is a prospective study conducted once the students entered medical school during their first year. A follow-up data collection was done during their third year after having spent three years in medical school with no intervention in between. Various parameters indicating cardiorespiratory fitness were compared as the participants progressed through medical school. Amongst those parameters, VO2 max was taken as the best indicator of cardiorespiratory fitness.\n\nBody mass index comparison in medical school\n\nWe measured the BMI of medical students when they first entered medical school and compared it with their BMI three years later. In the first year, 13.8% of the students were overweight and 8.3% of the students were obese. Subsequently, in the third year, 22.2% of them were found to be overweight and 9.72% of them were obese. The mean BMI in the first year and third year were 21.07±3.02 and 21.63±3.05, respectively. The comparison of the baseline BMI and subsequent BMI showed a statistically significant increase.\n\nBMI of medical students of Nepal in previous research\n\nA study conducted in 2005 among students of third-year medical school in Nepal19 showed only 1% and 2% of males and females to be overweight. However, a study conducted in 2017 at the Institute of Medicine found 32.5% of students to be overweight and 11.4% to be obese.20 However, a prospective study comparing BMI of medical students in Nepal was not found.\n\nBMI changes in students of university program\n\nA prospective study monitoring weight gain of students as they entered the university as a freshman and during their sophomore years was done in the United States.21 The study which was conducted in two universities, showed an increase of 3.1% and 15.6% in overweight/obesity rates from baseline to sophomore year, respectively. This study also supports the theory that getting into a university for a graduate degree may affect fitness level.\n\nPrevalence of obesity in Nepal\n\nAccording to the STEPS survey in 2019 of Nepal, 20% of adults were overweight and 4.3% were obese.22 Comparing this with our data on youths (18-22 years) which is a subset of the population taken in the STEPS survey we can see that practices leading to overweight and obesity begin from this age range in the youth itself. This study helps us show that targeting interventions in youth during their academic ventures can help reduce the overall overweight and obesity burden of Nepal.\n\nRelative VO2 max change in medical school\n\nA relative VO2 max is considered the strongest indicator of cardiorespiratory fitness. We found that the baseline mean relative VO2 max was found to be 37.46±7.68 ml/kg/min. In the final data collection, the mean relative VO2 max was 34.95±7.72 ml/kg/min. Although the mean VO2 max was found to be in the average range of non-athletes which is 35-40ml/kg/min for males and 27-31ml/kg/min,23 it showed a statistically significant decrease from the first year to the third year. This study indicates that the cardiorespiratory fitness of the students decreased after being enrolled in medical studies. During the transition into college years, various factors come into play; academic pressure, changes in family and peer social support and risk-taking behaviors.24 Studies have also found that academic stress that students face in medical school brings about a decrease in exercise, poor nutrition and increased drug use25; all these combined plays a critical role in declining fitness. Moreover, there is evidence suggesting that youths who attend college are prone to have a greater weight gain than those who do not which also impacts fitness.26 The findings in these studies support our findings suggesting that college students experience a decline in fitness as they progress through school.\n\nVO2 max of medical students in Nepal in previous research\n\nA 2008 study done at Nepal Medical College in medical students who did not smoke showed a VO2 max of 54.32ml/kg/min and 44.88 ml/kg/min in men and women, respectively.27 Similarly, a study done to assess cardiorespiratory fitness in 2013 at Kathmandu Medical College showed a VO2 max of 48.8 and 37.3 ml/kg/min in boys and girls.28 These data showed considerably good cardiorespiratory fitness at a point of time. However, since the studies were cross-sectional studies we cannot predict the progression of cardiorespiratory fitness throughout medical school. A previous study done in a similar age group of Nepalese youth also showed a VO2 max of 48.30 ml/kg/min.29 In regards to the previous studies where absolute VO2 max is calculated, our study calculated relative VO2 max, the difference being that the absolute VO2 max is the total amount of oxygen consumed by the body irrespective of the person's age, gender, mass while relative VO2 max is the value corrected for mass. This change was essential as the relative VO2 max helped us compare individuals and their own previous VO2 max. For example, a heavier person burns more oxygen during rest showing high absolute VO2 max when in reality VO2 max corrected for the mass may show a lower value. This fact helps us understand that absolute VO2 max values are not ideal for comparison since their weight is a variable parameter. Also, we were able to do a prospective study which helped us compare the change in VO2 max as the students progressed through medical school. Compared to these studies we can see that in the current scenario the VO2 max of Nepalese youth has significantly decreased portraying the increasing trend of a sedentary lifestyle and increased risk of non-communicable diseases. The nationwide STEP 2019 survey22 has also shown the increasing trend of obesity and increased risk of non-communicable disease in Nepal in the current scenario to support this theory.\n\nVO2 max of students in other university programs\n\nA cross-sectional study conducted in the department of physiology of Maharishi Markandweshwar Institute of Medical Sciences and Research, Mullana found that VO2 max for men was 45.66±8.9 ml/kg/min and for women was 37.85±4.3 ml/kg/min. This study is also a cross-sectional study unlike ours and is unable to predict changes in the VO2 max levels. From the study, it was concluded that their subjects fitted in the category ‘fair’ on cardiorespiratory fitness scale, which could be because of the decreased physical activity, unhealthy lifestyle behaviors as are established during the years of gaining education, which may influence adult behavior and health status.30\n\nAnother study compared the VO2 max levels of male students of one university with the other and also, female students of one university with the other. Maximum oxygen consumption of male students fall in the category ‘good’, according to the criteria of Cooper's oxygen consumption, for the Romanian students, the value is 50.9, while for the Serbian students, the value is 46.1 ml/min/kg. The maximal oxygen consumption of female Romanian students was 39.6, and of female Serbian students was 34 ml/min/kg, according to Cooper, it falls in the category ‘average’.31 This research showed that the maximum oxygen consumption of students across different universities is comparable, however, they fail to elucidate factors that can influence VO2 max levels.\n\nRelative VO2 max correlation with BMI\n\nIn our study, we have found that in the third year, the relative VO2 max of students decreased with increase in BMI. A study conducted in 2020 also revealed similar results32. It is also seen that a larger body mass and a high degree of correlation between body mass and relative VO2 max indicators are characteristics of mesomorphic and endomorphic-mesomorphic somatotypes. Whereas, smaller body mass and a lower degree of correlation between body mass and relative VO2 max indicator are characteristics of ectomorph and balanced somatotypes.32 This shows that different body types have a different characteristic association between relative VO2 max and Body mass index.\n\n\nConclusion\n\nOur study being a prospective study covered the gap in data that arose from cross-sectional studies about fitness levels in students. This study was able to provide data about medical students’ physical fitness which may contribute to the burden of non-communicable disease in the future. The significant data showing changes from the first year to the third year of medical school represents lack and/or decrease of physical activity during the time period in the school. This highlights a major gap in the curriculum i.e focus on the physical fitness of the students. The academic coursework should include and proactively focus on the physical activity of the students and promote them to adopt a healthier lifestyle as a part of their daily routine. If implemented this could significantly decrease the burden of non-communicable diseases in the future.\n\n\nData availability\n\nHarvard Dataverse: Assessment of Cardiorespiratory fitness among medical students: A prospective study. https://doi.org/10.7910/DVN/HNZKHI.33\n\nData are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).", "appendix": "References\n\nNoncommunicable Diseases - World Health Organization:2021 [cited 2022 June 13].Reference Source\n\nBlair SN, Kohl HW, Paffenbarger RS, et al.: Physical fitness and all-cause mortality: A prospective study of healthy men and women. JAMA. 1989 Nov; 262(17): 2395–2401. PubMed Abstract \| Publisher Full Text\n\nKaminsky LA; American College of Sports Medicine., & American College of Sports Medicine: ACSM's health-related physical fitness assessment manual. Philadelphia:Wolters Kluwer Health/Lippincott Williams & Wilkins;2014.\n\nCaspersen CJ, Powell KE, Christenson GM: Physical activity, exercise, and physical fitness: Definitions and distinctions for health-related research. Public Health Rep. 1985 Mar; 100(2): 126–131. PubMed Abstract\n\nOrtega FB, Ruiz JR, Castillo MJ, et al.: Physical fitness in childhood and adolescence: A powerful marker of health. Int. J. Obes. 2008 Jan; 32(1): 1–11. PubMed Abstract \| Publisher Full Text\n\nBelton S, O’Brien W, Meegan S, et al.: Youth-physical activity towards health: Evidence and background to the development of the Y-PATH physical activity intervention for adolescents. BMC Public Health. 2014 Dec; 14(1): 1–2. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nGnanendran A, Pyne DB, Fallon KE, et al.: Attitudes of medical students, clinicians and sports scientists towards exercise counselling. J. Sports Sci. Med. 2011 Sep; 10(3): 426–431. PubMed Abstract\n\nAlmutairi KM, Alonazi WB, Vinluan JM, et al.: Health promoting lifestyle of university students in Saudi Arabia: a cross-sectional assessment. BMC Public Health. 2018; 18(1): 1093. PubMed Abstract \| Publisher Full Text\n\nCalestine J, Bopp M, Bopp CM, et al.: College Student Work Habits are Related to Physical Activity and Fitness. Int. J. Exerc. Sci. 2017; 10(7): 1009–1017. PubMed Abstract\n\nShephard RJ, Allen C, Benade AJ, et al.: The maximum oxygen intake: An international reference standard of cardio-respiratory fitness. Bull. World Health Organ. 1968; 38(5): 757–764. PubMed Abstract\n\nDlugosz EM, Chappell MA, Meek TH, et al.: Phylogenetic analysis of mammalian maximal oxygen consumption during exercise. J. Exp. Biol. 2013 Dec 15; 216(24): 4712–4721. PubMed Abstract \| Publisher Full Text\n\nClemente CJ, Withers PC, Thompson GG: Metabolic rate and endurance capacity in Australian varanid lizards (Squamata: Varanidae: Varanus). Biol. J. Linn. Soc. 2009 Jul 1; 97(3): 664–676. Publisher Full Text\n\nSiconolfi SF, Cullinane EM, Carleton RA, et al.: Assessing VO2 max in epidemiologic studies: Modification of the Astrand-Rhyming test. Med. Sci. Sports Exerc. 1982 Jan; 14(5): 335–338. PubMed Abstract \| Publisher Full Text\n\nLiu CM, Lin KF: Estimation of (V) over dot O-2max: A comparative analysis of post-exercise heart rate and physical fitness index from 3-minute step test. J. Exerc. Sci. Fit. 2007 Jan; 5(2): 118–123.\n\nBrouha L: The step test: A simple method of measuring physical fitness for muscular work in young men. Res. Q. Am. Assoc. Health Phys. Educ. Recreat. 1943 Mar; 14(1): 31–37. Publisher Full Text\n\nDas SK, Mahapatra S, Bhattacharya G, et al.: Determination of physical fitness index (PFI) with modified Harvard step test (HST) in young men and women. Indian J. Physiol. Allied Sci. 1993; 47(2): 73–76.\n\nCheevers A, Pettersen C: Harvard step test. Hoge Schoolvan Amsterdam:Amsterdam Institute of Allied and HealthEducation, European school of Physiotherapy;2007. Accessed May 28, 2022.Reference Source\n\nÅstrand PO, Ryhming I: A nomogram for calculation of aerobic capacity (physical fitness) from pulse rate during submaximal work. J. Appl. Physiol. 1954 Sep; 7(2): 218–221. PubMed Abstract \| Publisher Full Text\n\nKumar A, Ramiah S: Anthropometric studies on students of the Nepal Medical College: Elbow breadth. Kathmandu Univ. Med. J. 2005 Oct-Dec; 3(4): 345–348. PubMed Abstract\n\nNepal G, Tuladhar ET, Dahal S, et al.: Lifestyle practices and obesity in Nepalese youth: A cross-sectional study. Cureus. 2018; 10(2): e2209. PubMed Abstract \| Publisher Full Text\n\nLloyd-Richardson EE, Bailey S, Fava JL, et al.: Tobacco Etiology Research Network (TERN). A prospective study of weight gain during the college freshman and sophomore years. Prev. Med. 2009 Mar; 48(3): 256–261. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nDhimal M, Bista B, Bhattrai S, et al.: Report of non-communicable disease risk factors; STEPS Survey of Nepal 2019. Kathmandu:Nepal Health Research Council;2020.\n\nEn.wikipedia.org: VO2 max - Wikipedia.2022. Accessed 28 May 2022.Reference Source\n\nLightfoot CA: The impact of academic, social and mentoring experiences on the persistence of minority and non-minority college students. University of Houston;2000.\n\nWeidner G, Kohlmann CW, Dotzauer E, et al.: The effects of academic stress on health behaviors in young adults. Anxiety, Stress & Coping. 1996; 9(2): 123–133. Publisher Full Text\n\nHovell MF, Mewborn CR, Randle Y, et al.: Risk of excess weight gain in university women: A three-year community controlled analysis. Addict. Behav. 1985; 10(1): 15–28. PubMed Abstract \| Publisher Full Text\n\nPrajapati R, Upadhyay Dhungel K, Pramanik T, et al.: Assessment of some pulmonary parameters and cardiorespiratory fitness status in Nepalese medical students. Nepal Med. Coll. J. 2008 Mar; 10(1): 28–29. PubMed Abstract\n\nHada S, Amatya S, Gautam K: Cardiopulmonary fitness test among Nepalese students. Janaki Med. Coll. J. Med. Sci. 2013; 1(1): 3–8. Publisher Full Text\n\nPramanik T, Roy CP: Some parameters of pulmonary function tests of young male sedentary non smoker Nepalese and Indians: A comparative study. Indian J. Physiol. Allied Sci. 2001; 55: 133–136.\n\nNabi T, Rafiq N, Qayoom O: Assessment of cardiovascular fitness [VO2 max] among medical students by Queens College step test. Int. J. Biomed. Adv. Res. 2015; 6(5): 418–421.\n\nBadau D, Goran P, Mitić D, et al.: Fitness Index and VO2 Max of Physical Education Students. Ovidius University Annals, Series Physical Education and Sport/Science, Movement and Health. 2015; 15(2, Supplement): 246–251.\n\nMiroshnichenko V, Furman Y, Brezdeniuk O, et al.: Correlation of maximum oxygen consumption with component composition of the body, body mass of men with different somatotypes aged 25-35. Pedagogy Phys. Cult. Sports. 2020; 24(6): 290–296. Publisher Full Text\n\nSharma A, Sah SP, Rajak A: Assessment of Cardiorespiratory fitness among medical students: A prospective study. Harvard Dataverse. 2022; V1. [Dataset], UNF:6:A6DOFSp6fnOioEqHsboUoA== [fileUNF].Publisher Full Text" }	[ { "id": "145112", "date": "17 Aug 2022", "name": "Karani Magutah", "expertise": [ "Reviewer Expertise Medical physiology/exercise and sports medicine" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAbstract\nThe first line states “…fitness level of fitness decline…” This needs editing.\n\nBetween 1st year and 3rd year of study is a 2-year gap and not 3 years as the authors state.\n\nAuthors say “The findings in this study expose the lack of fitness in youth as they focus more on academics, giving the impression that they forget to implement a fitness routine in their lifestyle” - the study has not investigated whether participants “remember” or “forget” fitness routines but goes ahead to make a conclusion on this.\n\nMethods\nGenerally well written and procedures well described.\n\nThis study took place between January 2017 and January 2020. It may be necessary to let readers appreciate how a student in 1st year of study in 2017 would only be a 3rd year in 2020 (and not a 4th year).\n\nThe sampling technique looks more like a census and not convenience. All students who gave consent were sampled.\n\nHow was BMI measured?\n\nResults\nNormally, females and males perform physical activities differently and, further, have differences in the various physiological parameters - for example, their VO2max values are graded differently. It is unclear why their data was pooled together for analysis.\n\nThere are a lot of repetitions of data (tables and prose). This should be revised.\n\nBMI categorizations and physical fitness index categories should be defined for readers. For example, what does \"very good PFI\" mean? What does \"underweight\" mean?\n\nTable 4 refers to PFI between 1st and 3rd year yet the table data is for 1st and 2nd year.\n\nTables 5 and 6 have VO2max pooled for males and females. This should be disaggregated for sex and age as physiologically expected.\n\nThere are too many tables! 10. This makes the work a little untidy. They could be reduced to a maximum of 4 or 5 without losing the information they carry.\n\nDiscussion\nThe opening statement “This study is a prospective study conducted once the students entered medical school during their first year” needs revision. It is not sound.\n\nAuthors state “A follow-up data collection was done during their third year after having spent three years in medical school with no intervention in between.\" If they have spent 3 years since joining 1st year, then they are in 4th year and not 3. No?\n\nThe discussion section has a lot of results. This should be revised. Discussions should explain the findings and the physiologic mechanisms involved, and place the current findings in perspective given other studies.\n\nAuthors compare their cardiorespiratory fitness findings with those from literature that are already disaggregated per sex. Theirs are not. It would be interesting to see if there is a drop in both sexes or how this compares.\n\nConclusion\nSome conclusions are not derived from the current work. For example, we do not know that the curriculum lacks in physical activity scheduled time and etc.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Partly\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? No\n\nAre the conclusions drawn adequately supported by the results? Partly", "responses": [] }, { "id": "176797", "date": "03 Jul 2023", "name": "Anderson Marques de Moraes", "expertise": [ "Reviewer Expertise Experience in Physical Activity and Health", "Exercise Physiology and Sports Training with emphasis on Growth and Development", "Body Composition and Bone Geometry." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nOVERALL COMMENT\nThe article entitled “Assessment of cardiorespiratory fitness among medical students: a prospective study” to aimed to assess changes in physical fitness and physical activity of students over-time. The article is well written and structured. This is an interesting topic, with increasing relevance in the literature. It brings an important discussion about the level of cardiorespiratory fitness in medical students.\nMAJOR COMMENTS\nINTRODUCTION\nDespite being well written, the introduction does not provide enough information based on the level of cardiorespiratory fitness in university students and its consequences for this population. In order to contribute to the study, the authors could use the study by (Jalene et al., 20191) or the study of (Singh et al., 20232).\n\nThe authors cite that “A recent study also showed a marked decline during high school and university years, however reference 7 is from 2011 (12 years ago). Could you insert a newer reference?\n\nThe authors describe at the end that “In the present study, a step test has been used for measuring the VO2 max of students as it is considered to be a practical field test for assessing individual aerobic fitness. I believe it is necessary to say that other tests can be used to assess this capacity, therefore, better justify the use of this test.\nMATERIALS AND METHOD\nStudy design\nThe paragraph “The limitation of this design is that it lacks generalizability and may not be representative of the sample population” refers to the limitation of the study, I believe it would be better at the end of the discussion.\nStatistical methods\nWas the analysis of normality of data distribution performed? Both the t-test and Pearson's correlation require that the data have a normal distribution for their use. Also include the degree of significance used (e.g. p < 0.05 or 5%).\n\nPlace this item at the end of Methods.\nEthical considerations\nInsert this item right after Study design\nRESULTS\nWas any analysis of the level of physical fitness, for example the IPAQ, carried out at the beginning of the assessments? This data is very important to analyze each student individually. Thus, it will be possible to establish the baseline level for the first analysis. If no initial physical fitness assessment was performed, this should also be considered as a limitation of the study.\n\nThe first paragraph should be in the methodology as a description of the sample.\n\nI suggest that the data from tables 1, 2 and 3 are in a single table.\n\nWhy was the data analyzed with men and women together? It is known that men and women have different characteristics, mainly related to the hormone.... men are modulated by testosterone (greater fat free mass gain) while women by progesterone (greater fat accumulation). Were analyzes performed separately by gender? Were the results the same? I believe justification is needed for these joint analyses.\n\nIt would be interesting, in the tables or in the text, to put the values in %, as it would facilitate the comparison and analysis of the results.\nDISCUSSION\nThe discussion is long, could be more specific and discuss the results without the need for threads.\n\nIn addition, it is necessary to add the limitations of the study, for example, the low number of participants, in addition to the items mentioned above.\n\nIs the work clearly and accurately presented and does it cite the current literature? Partly\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nPartly\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-776
https://f1000research.com/articles/11-775/v1	11 Jul 22	{ "type": "Software Tool Article", "title": "vcferr: Development, validation, and application of a single nucleotide polymorphism genotyping error simulation framework", "authors": [ "V.P. Nagraj", "Matthew Scholz", "Shakeel Jessa", "Jianye Ge", "August E. Woerner", "Meng Huang", "Bruce Budowle", "Stephen D. Turner", "Matthew Scholz", "Shakeel Jessa", "Jianye Ge", "August E. Woerner", "Meng Huang", "Bruce Budowle", "Stephen D. Turner" ], "abstract": "Motivation: Genotyping error can impact downstream single nucleotide polymorphism (SNP)-based analyses. Simulating various modes and levels of error can help investigators better understand potential biases caused by miscalled genotypes. Methods: We have developed and validated vcferr, a tool to probabilistically simulate genotyping error and missingness in variant call format (VCF) files. We demonstrate how vcferr could be used to address a research question by introducing varying levels of error of different type into a sample in a simulated pedigree, and assessed how kinship analysis degrades as a function of the kind and type of error. Software availability: vcferr is available for installation via PyPi (https://pypi.org/project/vcferr/) or conda (https://anaconda.org/bioconda/vcferr). The software is released under the MIT license with source code available on GitHub (https://github.com/signaturescience/vcferr)", "keywords": [ "bioinformatics", "kinship", "python", "genealogy", "GWAS", "simulation", "benchmarking" ], "content": "Introduction\n\nSingle nucleotide polymorphisms (SNPs) are inherited single base-pair substitutions in genomic DNA that are easily characterized by microarray, targeted, or whole-genome sequencing, and have a wide range of uses in personalized medicine, disease association studies, population genetics, genealogy, and forensics.1,2 Genotyping error occurs at known rates on genomic sequencing and array platforms.3 However, novel applications of sequencing or genotyping such as those encountered in forensics4 or ancient DNA,5 or novel downstream data analysis techniques such as imputation on low-pass whole-genome sequencing6–8 can result in genotyping errors that differ from well-established rates and types of errors that occur in typical genotyping and high-coverage sequencing in high-quality samples. Different applications or data analysis procedures can result in errors that can manifest in a variety of ways, for example, with differing rates of drop in or drop out of heterozygous calls.\n\nThere are several existing tools for simulating sequencing or genotype array data. Wgsim is a tool for simulating sequencing reads from a reference genome, allowing for a uniform user-defined substitution sequencing error.9 The ART sequencing read simulator allows for technology-specific read error models and base quality value profiles derived empirically from large sequencing datasets.10 Downstream of raw sequencing read error simulation, other tools provide methods for simulating genotyping data (as if variant calling had already been performed, or genotyping microarrays were being used to generate SNP genotypes). The ped-sim software allows for simulating large, arbitrarily complex pedigrees with genotypes drawn from founders in a variant call format (VCF) file,11 allowing for realistic familial data to be generated by employing sex-specific genetic maps and realistic crossover interference models.12 Ped-sim allows for specifying the rate of genotyping error and the rate of an opposite homozygous error conditional on a genotyping error at a marker, but does not allow for arbitrary specification of substitution rates in biallelic SNPs (such as different rates for heterozygous to homozygous reference drop-out versus homozygous reference to heterozygous drop-in), and it applies these universal error rates to all samples in a multi-sample VCF.\n\nWhile there are tools available to simulate errors in sequencing reads, and other tools such as ped-sim which allow for broad specification of global error rate in genotype calls, to our knowledge there is no existing tool that allows for individual specification of the type and degree of genotyping error an arbitrary sample in a VCF (e.g., different rates for heterozygous to homozygous reference versus homozygous to heterozygous). The ability to precisely simulate the degree and kind of genotyping error (based on error probabilities discovered from prior upstream data analysis) is necessary to facilitate testing and evaluation of downstream applications which may be differentially sensitive to different types of genotyping errors. Here we describe our efforts to develop, validate, and demonstrate an application and usage of vcferr, a user-friendly python tool for probabilistically simulating arbitrarily specified genotyping error and missing data into VCF files. Source code, PyPI/bioconda package, and code to reproduce the results presented here are given in the Software availability section below.26,27\n\n\nMethods\n\nvcferr is written in Python and distributed to run directly from a command line interface. The tool is built using pysam,13 which internally manages reading and writing VCF file contents. When run on an input VCF, vcferr will load all variant records for a given sample. The tool checks each genotype, and randomly draws from a list of possible genotypes (heterozygous, homozygous for the alternate allele, homozygous for the reference allele, missing) with each element weighted by error rates specified by the user. The processing runs iteratively for every site in the input VCF, with the output streamed or optionally written to a new output VCF file. The following error and missingness models are available:\n\n• rarr = Heterozygous drop out to homozygous reference: 0/1 or 1/0 to 0/0\n\n• aara = Homozygous alternate to heterozygous: 1/1 to 0/1\n\n• rrra = Homozygous reference to heterozygous drop in: 0/0 to 0/1\n\n• raaa = Heterozygous to homozygous alternate: 0/1 or 1/0 to 1/1\n\n• aarr = Homozygous alternate to homozygous reference: 1/1 to 0/0\n\n• rraa = Homozygous reference to homozygous alternate: 0/0 to 1/1\n\n• ramm = Heterozygous to missing: 0/1 or 1/0 to./.\n\n• rrmm = Homozygous reference to missing: 0/0 to./.\n\n• aamm = Homozygous alternate to missing: 1/1 to./.\n\nWe validated vcferr by reviewing concordance metrics between VCF files before and after error simulation. To perform this validation we used data from the 1000 Genomes Project14 (see Underlying data) and the companion error assessment tool described below. The code for accessing the 1000 Genomes Project data and for reproducing the analyses presented in this paper is available from Extended data.25 First, we retrieved all genotype calls for chromosome 22 from the 1000 Genomes file transfer protocol (FTP) site. Next, we simulated a set of error rates for one sample. We observed that the proportion of mismatches reported by our bcftools-based error assessment procedure aligned as expected to each of the specified error probabilities. We also confirmed that the simulation of error in one sample did not trigger any mismatches for other samples in the VCF. The chromosome 22 VCF includes 1,103,547 positions and 2504 samples, and genotype error simulation took approximately five minutes on a single CPU (central processing unit). The code used to fully reproduce this validation analysis is described in the Extended data section below.25\n\nAs part of this analysis we developed a companion tool (called nrc) to measure all types of error types that can be observed with biallelic SNPs between a reference and a query sample. This tool also computes the nonreference concordance (NRC), which is defined as:\n\nWhere err, era, and eaa, are defined as the the counts of mismatches for the homozygous reference, heterozygous, and homozygous alternate genotypes, and mra, and maa are the counts of the matches at the heterozygous and homozygous alternate genotypes (the number of homozygous reference matches, mrr, is omitted from this analysis). We implemented this procedure as a Docker container, which first runs bcftools stats13 followed by post-processing results using R. The Dockerfile needed to build the nrc image is available in the Software availability section below,27 where the Docker image can be pulled directly from the GitHub container registry.\n\nvcferr is packaged in Python and available to be installed from PyPi or Bioconda. Once installed, the tool can be used through the command line without calling the Python interpreter. vcferr requires a path to an input VCF from which error will be simulated as the first positional argument. The tool also requires a specification for --sample for the ID of the sample to be simulated as it appears in the VCF header. All other error flags are optional, as is --output-vcf which if used will define the path to which the VCF should be written. If no value is passed to a given error or missingness option, then the probability will default to 0. The following is a minimal example of usage, which will result in 5% of the heterozygous genotypes in “sampleX” to be erroneously called as homozygous reference, and 1% of that same individual’s heterozygous genotypes to be erroneously called as homozygous alternate, with output being written to a new bgzipped VCF file:\n\nThe companion tool nrc for assessing individual error rate probabilities and overall non-reference concordance is available as a Docker image from the GitHub container registry. Once installed, the container can be run through the command line with no dependencies other than Docker. The container expects two VCF files and a sample ID which exists in both VCFs to compare. Optionally, a set of sites at which to compare can be specified (default is to compare all sites). This is useful to restrict analyses to a subset of sites (e.g., those that have at least some minimum minor allele frequency from GnomAD, given that filtered site VCF). Example usage:\n\n\nUse cases\n\nTo demonstrate how vcferr could be used to address a research question, we conducted an analysis of the impact of genotyping error on pairwise kinship estimation. For instance, a heterozygous drop-out to homozygous reference may be much better tolerated than a switch from homozygous reference to homozygous alternate. We first generated simulated pedigree data using ped-sim12 with founders drawn from the British in England and Scotland (GBR) population in the 1000 Genomes Project data. The simulated data was masked to a subset of 590,241 sites, including content from the Illumina Global Screening Array. With all data originally simulated to include no error, we next identified an individual for which we would inject genotyping error. We used vcferr to iterate through each error mode from 0 to 20% error at 1% steps, holding all other error modes constant at 0.\n\nNext, we obtained KING robust15 kinship coefficients from akt16 for all pairwise comparisons that included the error-simulated individual in the resulting simulation VCFs. We then used the kinship coefficients to infer relatedness out to the third-degree and compared accuracy of degree inference to truth from the original simulated pedigree. The results of this analysis are summarized in Figure 1. Code needed to reproduce this entire analysis, implemented as a Snakemake workflow,17 is available in the Zenodo archive described in the Extended data section below.25\n\nEach line corresponds to a type of error, with error rates from 0 to 0.2 stepped at 0.01 increments while holding all other types of error constant at 0. The solid black line at the bottom represents the accuracy at guessing, which is the floor for relationship degree classification.\n\nIn short, certain kinds of error dramatically decrease accuracy of relatedness inference with the KING robust estimator. Note that the sample for which errors were simulated included 430,056 homozygous reference sites, 105,413 heterozygous sites, and 54,772 homozygous alternate site, resulting in varying absolute counts of errors being simulated at each 0 to 20% step (as expected in any sample with genotypes from microarray or sequencing). By leveraging vcferr to inject a range of genotyping error scenarios, we can identify the scenarios that are most likely to impact kinship analysis.\n\nGenome-wide association studies (GWAS) are a widely used approach for genetic epidemiology studies attempting to understand genetic underpinnings to complex human disease.18 Formalin-fixed, paraffin-embedded (FFPE) tissue fixation is a standard means to preserve tissues from clinical samples, and can result in genotyping error19 that can vary by type, with heterozygous errors being more commonly discordant.20 Power and sample size requirements for GWAS are impacted by genotyping error.21 If error probabilities for different sample types such as FFPE tissue samples are known, the impact of different types of genotyping error on GWAS power or sample size requirements can be estimated in simulation. One of many available tools can be used to simulate GWAS data with known sample size, effect size, SNP density, etc.22,23 Following data simulation, vcferr can be used to inject error in samples of interest, precisely controlling the degree and kind of error in each sample.\n\nSimilarly, a polygenic risk score (PRS) captures the additive effect of hundreds, or perhaps thousands of SNPs, and are computed on genome-wide genotyping data using a prediction model based on summary statistics from external GWAS studies.24 PRS are first calculated by summing the risk alleles an individual has where each risk allele is weighted by the risk allele effect size as estimated by a large GWAS on that phenotype. The PRS is then applied to target genotype data to assess overall genetic liability to developing the trait or disease. If the target genotypes result from a process that introduces error at different levels for different zygosity (e.g., low-pass whole genome sequencing), the performance of a PRS will be impacted differently depending on the type and kind of error introduced. If this error profile is known by characterizing against high-quality samples, those error profiles can be used to inject error at those specified rates into samples simulated for assessing the predictive ability of a PRS in a new target genotype collection using the same approach above for GWAS.\n\n\nSummary\n\nvcferr provides a flexible, user-friendly interface to simulate genotyping error in VCF files. While tools exist to simulate entire VCFs with error (e.g. ped-sim12), to our knowledge at the time of writing there are currently no other tools that can simulate arbitrary individuals in the VCF at varying types and levels of error while leaving all other samples as-is. We anticipate that vcferr will be useful for researchers in multiple areas, including forensic genomics and medical genetics.\n\n\nData availability\n\nThe 1000 Genomes Data14 used in this study is freely accessible to anyone without registration via the The International Genome Sample Resource website here: https://www.internationalgenome.org/category/ftp/.\n\n\n\n• Archived analysis code at time of publication: https://doi.org/10.5281/zenodo.659913425\n\n• License: Creative Commons Attribution 4.0 International license (CC-BY 4.0)\n\n\nSoftware availability\n\nThe vcferr python tool is the primary software tool described and demonstrated in this paper.\n\n• Software available from: PyPI (https://pypi.org/project/vcferr/) and Bioconda (https://anaconda.org/bioconda/vcferr)\n\n• Source code available from: https://github.com/signaturescience/vcferr\n\n• Archived source code at time of publication: https://doi.org/10.5281/zenodo.661179626\n\n• License: MIT\n\nThe nrc companion tool was created for assessing error produced by vcferr\n\n• Software (Docker image) available from: https://ghcr.io/signaturescience/nrc\n\n• Source code available from: https://github.com/signaturescience/nrc\n\n• Archived source code at time of publication: https://doi.org/10.5281/zenodo.661178227\n\n• License: MIT", "appendix": "Acknowledgements\n\nThe authors acknowledge Dr. Mike Coble for helpful discussions about the software and its use cases.\n\n\nReferences\n\nNielsen R, Paul JS, Albrechtsen A, Song YS: Genotype and SNP calling from next-generation sequencing data. Nat. Rev. Genet. June 2011; 12(6): 443–451. PubMed Abstract \| Publisher Full Text\n\nKim S, Misra A: SNP genotyping: Technologies and biomedical applications. Annu. Rev. Biomed. Eng. 2007; 9: 289–320. PubMed Abstract \| Publisher Full Text\n\nPompanon F, Bonin A, Bellemain E, Taberlet P: Genotyping errors: causes, consequences and solutions. Nat. Rev. Genet. November 2005; 6(11): 847–859. Publisher Full Text\n\nGorden EM, Greytak EM, Sturk-Andreaggi K, et al.: Extended kinship analysis of historical remains using SNP capture. Forensic Sci. Int. Genet. March 2022; 57: 102636. PubMed Abstract \| Publisher Full Text\n\nHui R, D’Atanasio E, Cassidy LM, et al.: Evaluating genotype imputation pipeline for ultra-low coverage ancient genomes. Sci. Rep. October 2020; 10(1): 18542. PubMed Abstract \| Publisher Full Text\n\nMartin AR, Atkinson EG, Chapman SB, et al.: Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations. bioRxiv. April 2020; page 2020.04.27.064832.Publisher Full Text\n\nLi JH, Mazur CA, Berisa T, Pickrell JK: Low-pass sequencing increases the power of GWAS and decreases measurement error of polygenic risk scores compared to genotyping arrays. bioRxiv. May 2020; page 2020.04.29.068452. Publisher Full Text\n\nRubinacci S, Ribeiro DM, Hofmeister RJ, Delaneau O: Efficient phasing and imputation of low-coverage sequencing data using large reference panels. Nat. Genet. January 2021; 53(1): 120–126. PubMed Abstract \| Publisher Full Text\n\nLi H: Wgsim.2011.Reference Source\n\nHuang W, Li L, Myers JR, Marth GT: ART: A next-generation sequencing read simulator. Bioinformatics. February 2012; 28(4): 593–594. PubMed Abstract \| Publisher Full Text\n\nDanecek P, Auton A, Abecasis G, et al.: he variant call format and VCFtools. Bioinformatics. 06 2011; 27(15): 2156–2158. PubMed Abstract \| Publisher Full Text\n\nCaballero M, Seidman DN, Qiao Y, et al.: Crossover interference and sex-specific genetic maps shape identical by descent sharing in close relatives. PLoS Genet. December 2019; 15(12): e1007979. 1553-7404. Publisher: Public Library of Science. PubMed Abstract \| Publisher Full Text\n\nDanecek P, Bonfield JK, Liddle J, et al.: welve years of SAMtools and BCFtools. GigaScience. February 2021; 10(2): giab008. 2047-217X. PubMed Abstract \| Publisher Full Text\n\nAuton A, Abecasis GR, Altshuler DM, et al.: A global reference for human genetic variation. Nature. October 2015; 526(7571): 68–74. Publisher Full Text PubMed Abstract \| Reference Source\n\nManichaikul A, Mychaleckyj JC, Rich SS, et al.: Robust relationship inference in genome-wide association studies. Bioinformatics. 10 2010; 26(22): 2867–2873. 1367-4803. PubMed Abstract \| Publisher Full Text\n\nArthur R, Schulz-Trieglaff O, Cox AJ, et al.: AKT: ancestry and kinship toolkit. Bioinformatics. 09 2016; 33(1): 142–144. 1367-4803. PubMed Abstract \| Publisher Full Text\n\nKöster J, Rahmann S: Snakemake–a scalable bioinformatics workflow engine. Bioinformatics. 08 2012; 28(19): 2520–2522. Publisher Full Text\n\nGallagher MD, Chen-Plotkin AS: The post-gwas era: From association to function. Am. J. Hum. Genet. 05 2018; 102(5): 717–730. PubMed Abstract \| Publisher Full Text\n\nSikora MJ, Thibert JN, Salter J, et al.: High-efficiency genotype analysis from formalin-fixed, paraffin-embedded tumor tissues. Pharmacogenomics J. 06 2010; 11(5): 348–358. PubMed Abstract \| Publisher Full Text\n\nHertz DL, Kidwell KM, Thibert JN, et al.: Genotyping concordance in dna extracted from formalin-fixed paraffin embedded (ffpe) breast tumor and whole blood for pharmacogenetic analyses. Mol. Oncol. 07 2015; 9(9): 1868–1876. PubMed Abstract \| Publisher Full Text\n\nLin H, Sun N, Mane S, et al.: Impact of genotyping errors on statistical power of association tests in genomic analyses: A case study. Genet. Epidemiol. 12 2016; 41(2): 152–162. PubMed Abstract \| Publisher Full Text\n\nFortune MD, Wallace C: simgwas: a fast method for simulation of large scale case–control gwas summary statistics. Bioinformatics. 10 2018; 35(11): 1901–1906. PubMed Abstract \| Publisher Full Text\n\nTang Y, Liu X: G2p: a genome-wide-association-study simulation tool for genotype simulation, phenotype simulation and power evaluation. Bioinformatics. 02 2019; 35(19): 3852–3854. PubMed Abstract \| Publisher Full Text\n\nTorkamani A, Wineinger NE, Topol EJ: The personal and clinical utility of polygenic risk scores. Nat. Rev. Genet. 05 2018; 19(9): 581–590. PubMed Abstract \| Publisher Full Text\n\nNagraj VP, Scholz M, Jessa S, et al.: Documentation and code for reproducing analyses presented in: vcferr: Development, Validation, and Application of a SNP Genotyping Error Simulation Framework [Software]. Zenodo. 2022. Publisher Full Text\n\nNagraj VP, Turner S, Scholz M: signaturescience/vcferr: v1.0.2-zenodo (v1.0.2-zenodo). Zenodo. 2022. Publisher Full Text\n\nTurner S: signaturescience/nrc: v1.0.0 (v1.0.0). Zenodo. 2022. Publisher Full Text" }	[ { "id": "235770", "date": "20 Feb 2024", "name": "Ardalan Naseri", "expertise": [ "Reviewer Expertise Computational biology", "Bioinformatics", "Population genetics", "Identity by descent", "Artificial Intelligence" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe paper presents a new tool called vcferr, which can be used to simulate genotyping errors and missing data in variant call format (VCF) files. The authors demonstrate how vcferr can help answer research questions by introducing various levels and types of errors into a simulated pedigree, and evaluating how kinship analysis is affected. While there are other similar tools available, the authors highlight the unique features of their work.\nHowever, some minor clarifications are needed. The terms \"degree\" and \"kind\" of genotyping errors require further explanation. I assume \"Kind\" refers to different error models, such as RARR or AARA, while \"degree\" refers to the rates. In the manuscript, they have been referred to as type as well. A more coherent terminology would be helpful.\n\nRegarding the implementation, \"randomly draws from a list of possible genotypes (heterozygous, homozygous for the alternate allele, homozygous for the reference allele, missing) with each element weighted by error rates specified by the user.\". It is unclear whether the values used for weighting are p_rarr, p_aar, etc., and if so, are the actual error rates produced by the tool the same? Would a p_rarr of 0.05 change exactly 5% of heterozygous sites to homozygous reference? Additionally, it would be useful if the tool provided a seed value for reproducibility (if not available yet) when benchmarking other tools.\nOverall, the paper is well-written, and the tool provides a valuable resource for the research community.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [] }, { "id": "266345", "date": "02 May 2024", "name": "Gianluca Della Vedova", "expertise": [ "Reviewer Expertise Algorithms" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe paper present a tool for simulating genotyping errors on top of a know vcf file. The tool has a clear scope and usefulness. The paper is well written and easy to follow. I have only a few, very minor, suggestions but I recommend to accept the paper.\nPage 3, \"specified genotyping error\". I suggest to state if you accept some kind of error profile. Page 3. \"The tool is built using\" -> \"The tool depends on\" Page 4. \"from which error will be simulaed as the first positional argument\". Please state explicitly that this is the ground truth you will use in your simulation steps. Page 4. (last paragraph) \"The companion tool nrc ... registry\". You have already discussed nrc and it docker image about half a page befor (just before Operation). Page 5, Code snippet #1. I expect a single \"docker run\" to suffice. May you explain why you also have a docker pull and a docker tag? Page 5, Code snippet #2. \"Loop through ... error mode\". I cannot find any loop in that code. Please make the code and the comments consistent. Page 7, Underlying data. Now that web browsers do not support ftp, I think it's time to move away from it, especially since it provides no advantages. That's not much that the authors can do, so it's mostly a suggestion for future works. Page 7. Please explain (here or somewhere else in the paper) why you have decided to release nrc as a docker image, instead of via conda (as you have done for vcferr). I find puzzling to use two different installation methods, so it's better to provide a rationale.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [] }, { "id": "260018", "date": "15 May 2024", "name": "Cristiane Taniguti", "expertise": [ "Reviewer Expertise Bioinformatics", "statistical genetics", "plant genetics", "polyploids" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe software presents a method for simulating genotyping errors in specific samples in a VCF file. The novelty compared to other software available is that it can introduce different error types and intensities. Having the tool in Conda or Docker is also a great advantage, as some other tools created for the same purpose are currently outdated and difficult to install. The authors provide two use cases, one measuring the impact of the different error types in kinship analysis and the other in GWAS and polygenic risk score estimation. The authors provide links for all mentioned resources including the software by itself, a companion package called nrc, and a Snakemake workflow to reproduce the analysis of the first use case. Results are presented for only the first of the cases. Despite not being necessary to understand the application, having access to results for the second use case would consolidate the statement. If not presently available, I recommend considering two additional features: incorporating a seed option for simulations and providing detailed information on the absolute number of modified genotypes and their final counts. Not knowing the absolute numbers, users can easily get lost in the interpretations of the results once the error rate parameters are based on frequencies and the absolute number will depend on the proportion of the initial genotypes, as emphasized in paragraph #12. I noticed that the introduction doesn't mention amplicon sequencing techniques like genotyping-by-sequencing (GBS or RAD-seq) as a means to obtain SNPs. In the plant genetics field, GBS methods have been broadly used. Compared to the other methodologies mentioned in the text, GBS results have been showing a higher number of genotyping errors. Lots of efforts in terms of software have been made to try to overcome these errors (see Furuta et al. 2023 for an example Ref [1]). Briefly mentioning it in the text could expand the audience and the applications to this other domain. Other than predicting the accuracy rate for certain doubt quality samples, do you think that the tool could be useful to also measure the capabilities of these software designed to fix genotyping errors? Overall, the text is well-written and follows a logical description for a software release.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Partly\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-775
https://f1000research.com/articles/11-774/v1	11 Jul 22	{ "type": "Research Article", "title": "Detecting, extracting, and mapping of inland surface water using Landsat 8 Operational Land Imager: A case study of Pune district, India", "authors": [ "Rushikesh Kulkarni", "Kanchan Khare", "Humera Khanum", "Humera Khanum" ], "abstract": "Background: Recent developments in optical satellite remote sensing have led to a new era in the detection of surface water with its changing dynamics. This study presents the creation of surface water inventory for a part of Pune district (an administrative area), in India using the Landsat 8 Operational Land Imager (OLI) and a multi spectral water indices method. Methods: A total of 13 Landsat 8 OLI cloud free images were analyzed for surface water detection. Modified Normalized Difference Water Index (MNDWI) spectral index method was employed to enhance the water pixels in the image. Water and non-water areas in the map were discriminated using the threshold slicing method with a trial and error approach. The accuracy analysis based on kappa coefficient and percentage of the correctly classified pixels was presented by comparing MNDWI maps with corresponding Joint Research Centre (JRC) Global Surface Water Explorer (GSWE) images. The changes in the surface area of eight freshwater reservoirs within the study area (Bhama Askhed, Bhatghar, Chaskaman, Khadakwasala, Mulashi, Panshet, Shivrata, and Varasgaon) for the year 2016 were analyzed and compared to GSWE time series water databases for accuracy assessment. The annual water occurrence map with percentage water occurrence on a yearly basis was also prepared. Results: The kappa coefficient agreement between MNDWI images and GSWE images is in the range of 0.56 to 0.96 with an average agreement of 0.82 indicating a strong level of agreement. Conclusions: MNDWI is easy to implement and is a sufficiently accurate method to separate water bodies from satellite images. The accuracy of the result depends on the clarity of image and selection of an optimum threshold method. The resulting accuracy and performance of the proposed algorithm will improve with implementation of automatic threshold selection methods and comparative studies for other spectral indices methods.", "keywords": [ "Surface water", "Landsat 8 OLI", "MNDWI", "Water index", "Confusion matrix", "Otsu’s Threshold" ], "content": "Introduction\n\nBy 2030, the world is anticipated to face a 40 percent water crisis as a result of urbanization, strain on food production, population increase, and increasing demand from the industrial, domestic, and energy sectors1,2. The current water crises are a result of poor water management and not because of adequacy of water. Sustainability of water can be maintained with proper governance and appropriate water management practices3. Inland water bodies are critical for the survival of all forms of life and need to be monitored frequently4. The regular monitoring and mapping of surface water is of paramount importance for better water resource management5.\n\nSurface water bodies are dynamic in nature as they shrink and expand with the course of time6. Remote sensing is an effective and low cost alternative to conventional in-situ water quality monitoring systems7,8. Recent advancements in optical remote sensing have catapulted the field of surface water sensing into a new era. It has been used in water resource assessment and management in the last four decades9–19. These applications involve delineation of surface water and assessing water quality using thematic information extraction techniques20.\n\nBoth active and passive remote sensing have been used to detect and extract surface water bodies9. Optical remote sensing of water is based on the difference between spectral reflectance of land and water. Water absorbs most of the energy beyond near-infrared wavelength whereas other land features have higher reflectance in those wavelengths. Thus, water appears as a dark spot in near-infrared and higher wavelength bands of multispectral images which makes it easy to differentiate water from non-water topographic features. The accuracy depends on the weather conditions during the image captured and topography of the study area. Microwave is very effective during the presence of clouds, rain fields, the presence of water vapor and aerosols. Microwave remote sensing of surface water is based on the backscattering properties of water in the microwaves region. The surface of water behaves as a specular reflector for incident microwaves, and responds with no or very low signal returns. Thus, water is easily distinguished from other topographic features in and around the area.\n\nApplications of remote sensing for various purposes of water resource management were proposed for the first time for surface water bodies in India21. Moderate Resolution Imaging Spectroradiometer (MODIS), a coarse resolution but high temporal resolution sensor have been successfully applied to near-real time surface water monitoring22–25. The Visible Infrared Imaging Radiometer Suite onboard Suomi National Polar-orbiting Partnership (Suomi NPP-VIIRS) has been tested for detecting surface water26. The low resolution satellites have major limitations in observing small water bodies. Cloud cover is another issue often associated with low resolution satellites. Landsat is the most successful series of satellites in monitoring surface water bodies in the history of remote sensing9. Landsat 8 Operational Land Imager (OLI) is the most recent satellite in the Landsat series and is widely used in detecting surface water bodies11–19. Systeme Probatoire d’Observation dela Tarre (SPOT), which has an improved spatial resolution of 10 m but that is not available free of cost, is used in a few studies for applications of surface water27,28. The MultiSpectral Instrument (MSI) onboard Sentinel-2 with spatial resolutions of 10m and a revisit time of 10 days at equator and five days with two satellites under cloud free conditions is used to detect surface water29–31. Many works specifically reviewed recent accomplishments, current status, and limitations in this domain, including geographic scale, integration with in-situ hydrological data, cloud obscuration, and other land feature classes.7–9,32–34.\n\nWater extraction methods using remote sensing have been pursued by advancing sensors and through the development of various methods like thematic classifications, Linear Unmixing, single band thresholding and multispectral water indices5,9,20,35. The method selection from the list above is based on the scale of the water map and the proportion of water bodies to non-water area in the image.\n\nThe method of extracting features of surface water using water indices remains popular because it is simple to implement, has a relatively fast processing time, and produces fairly accurate results36,37. These methods have produced excellent results when used with Landsat imagery11,38,39. Surface water features can be distinguished using a variety of water indexes, including Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Automated Water Extraction Index (AWEI). NDWI uses the green and near infrared (NIR) band to delineate water features in the image40. Nevertheless, The NDWI is unable to suppress the built-up land signal which make it difficult to differentiate water and built up area effectively20. MNDWI is a modified version of NDWI that uses green and short-wave infrared (SWIR) bands to overcome limitations encountered by NDWI for extracting water using space observation. AWEInsh, an automated water extraction index with no shadow, and AWEIsh, an automated water extraction index with a shadow, are two more additional water indices that have been proposed for water delineation41.\n\nSelecting an optimum threshold to discriminate water accurately from land is a challenging and complex task41. Ideally, spectral index images assign higher values to water and negative values to the non-water pixels. Thus, zero is ideally a reference value to separate water and non-water pixels. However, in practice most of the times the threshold values are non-zero. In this study automated Otsu’s threshold method and trial-and error methods are used to estimate optimum threshold values42,43.\n\nPekel (2016) presented a comprehensive validation protocol for accuracy analysis of the Global Surface Water Explorer (GSWE) dataset44. This dataset has been validated using the total 40,124 control points distributed geographically and temporarily all across the globe. GSWE is produced from Landsat imagery at the global scale over the past 32 years.\n\nIn this study, we demonstrated a case study of Pune district for detection and mapping of surface water using the MNDWI spectral index method. The objective of the study is evaluation of the MNDWI water indices method for extraction of surface water from Landsat 8 OLI images having multiple water bodies located spatially apart. The time series surface water map is prepared for the entire year using the cloud free images. The surface water maps so developed are assessed for accuracy by comparing them with a reference surface water map prepared by The European Commission’s Joint Research Centre in the framework of the Copernicus Programme.\n\n\nMethods\n\nThe processes followed for achieving the objectives of study are represented in Figure 2. In summary, the process starts with downloading the cloud free Landsat 8 OLI of the study area (see Underlying data) and carrying out initially radiometric and geometric corrections, and cloud detection. In the next step MNDWI spectral indices were calculated from the Landsat images in order to enhance all water pixels in the image. Water bodies were extracted using the threshold slicing method using Otsu and trial and error method. Finally, the images were assessed for accuracy by comparing with a reference image. All processes followed are explained in the separate subsections below.\n\nThe study area for development of surface water maps is between 18.01 N and 19.36 N and 73.34 E and 74.76 E which is a portion of the Pune district administrative boundary in India. Pune lies on the west of the Deccan plateau (Figure 1), at an altitude of 560 m (1,840 ft) above mean sea level. It is located in western Maharashtra along the foothills of the Sahyadri Mountains45.\n\nLandsat 8 image courtesy of the U.S. Geological Survey.\n\nOLI, Operational Land Imager; ToA, Top of Atmosphere; MNDWI, Modified Normalized Difference Water Index; JRC, Joint Research Centre; GSWE, Global Surface Water Explorer. Landsat 8 images courtesy of the U.S. Geological Survey.\n\nThis area is chosen for two reasons. First, it has heterogeneous topography comprising hills on the western side and plain terrain on the eastern side of the district. It covers all the types of surface water bodies, such as rivers, lakes, and reservoirs. Secondly, the authors are from this region, which provides prior knowledge and understanding of the selected area.\n\nAccording to the 2011 Census of India, Pune district had a total population of 9.429 million, meaning it lies within India’s top ten most populated cities45. The monsoon season in Pune is observed from June to September, and the cloud presence makes it challenging for water extraction from remote sensing. Therefore, surface water extraction analysis were performed for the non- rainy season.\n\nLandsat is one of the best known satellite series in history. Since the first mission was initiated in 1972, medium-resolution photographs have been consistently supplied for almost 50 years now. Landsat 8 OLI images have a moderate spatial resolution (30 m), spectral resolution (eleven bands) and temporal resolution of 16 days. Launched on 11 February 2013, Landsat 8 is the most recent Landsat satellite. It is fitted with an enhanced ”Operational Land Imager (OLI)” sensor with the addition of two thermal Infra- Red sensors (TIRS). The Landsat 8 OLI sensor has a better rate of classification because it provides improved 12-bit data quantization compared to 8-bit quantization of other sensors. A total of 13 Cloud free Landsat 8 OLI images were selected and downloaded from the US Geological Survey (USGS) earth explorer (see Underlying data) for the study area during the year 2016 (Table 1). All images contained 1 – 7 bands with 30 m resolution. The quality of the image is ensured with the information in pixel- qa product downloaded along with the Landsat 8 image. This product provided the information about cloud and cloud confidence and cloud shadow. More information about the quality evaluation can be found here.\n\nThe first step in the pre-processing is to transform raw digital numbers (DN) to Top of Atmosphere (ToA) reflectance (Figure 3). The pre-processing is performed using Semi-Automatic Classification Plugin of QGIS (3.22.3) open source software (please note that all pre-processing of the raw images, calculation of MNDWI, cropping of images and thresholding using trial and error presented in the methods is performed using QGIS open source software). Landsat Collections Level-1 data can be re-scaled to top of atmosphere (ToA) reflectance using radiometric re-scaling coefficients (see Underlying data46). DN is a mathematical value of spectral data and not physical measured data so it is to be converted to ToA. DN can be converted to ToA reflectance using the re-scaling coefficients in the MTL using (Equation 1):\n\n\n\nLandsat 8 images courtesy of the U.S. Geological Survey.\n\nWhere Mp and Ap are the metadata defined multiplicative and additive band specific re-scaling factors, respectively. The quantized and calibrated standard product pixel values are denoted by Qcal. It is not corrected for the sun angle, which results in the ToA reflectance as (ρλ),\n\n\n\nwhere θSE is the local sun elevation angle as specified in the metadata and θSZ denotes the local solar zenith angle as calculated using (900 -θSE).\n\nMNDWI were initially calculated to enhance the difference between water and non-water areas. Surface water bodies tend to have positive values in MNDWI images, whereas, soil, vegetation and built up areas are expected to represent negative values20. Xu (2006) proposed that the Short-wave Infrared (SWIR) band can reflect subtle features of water more effectively compared to Near Infrared (NIR) band and substituted SWIR for NIR band in NDWI20. The MNDWI method has been commonly used and is a powerful index that can extract water bodies. It is expressed by an Equation (3).\n\n\n\nWhere the subscript ρ denotes the surface reflectance value computed from bands 3 (green), and 7 (visible) (SWIR-2).\n\nThis study restricts the surface water bodies mapping to the Pune district administrative area. The MNDWI images are subsetted using the shapefile to remain focused on the surface water bodies in the study area (Figure 4). All the image processing algorithms mentioned in this section are performed using QGIS (3.22.3) open source software.\n\nLandsat 8 image courtesy of the U.S. Geological Survey.\n\nOtsu’s threshold is a simple and effective approach for determining the optimum threshold24. In Otsu’s threshold method all the pixels of the image are separated by discriminant creation so as to maximize the separability of two resultant classes, including object and background. In an ideal case the histogram has two distinct peaks representing object and background so that the threshold can be chosen at the bottom between two peaks. Therefore, it is essential to calculate the grey-level histogram for the whole image before calculating the optimal threshold. Google Earth Engine (GEE) open source cloud platform was used to run the Otsu’s threshold algorithm. The link to the Java code of the algorithm in GEE can be found in Extended data47. The MNDWI image was an input to the GEE platform, and the expected result is a binary water and no- water image. We encountered a problem of the maximum number of pixels in an image exceeding the permissible number of pixels while running Otsu’s algorithm on GEE platform. The polygon area of the study region is split into two small polygons in the form of shape-file. We then estimated separately the threshold for the small areas which were then combined in the freely available QGIS (version 3.22.3) to get the surface map. Although, Otsu is described as simple approach in the literature, its success depends on many parameters like grey scale distribution, proportion of the two classes, the nature of images and many others.\n\nThe optimal threshold estimated using the Otsu threshold method did not work satisfactorily and the image obtained encountered ‘salt-pepper error’ (Figure 5). The alternative, iterative trial and error method based on visual interpretation was used in this study to find the optimal threshold to discriminate water and non-water from the MNDWI image. An initial threshold of 0 was applied to all the water index images to judge classification status by visual interpretation. Based on the initial screening, the threshold is adjusted to get higher kappa values. The optimal threshold so selected was used to generate surface water map. This water map was analyzed for classification accuracy compared with the JRC monthly map, available in Underlying data48.\n\nLandsat 8 image courtesy of the U.S. Geological Survey.\n\nThe major limitations of MNDWI is that, it easily misclassifies shadow and dark roads as water bodies23. In this work, the terrain shading plugin of QGIS was used to simulate mountain shadows derived from the digital elevation model (DEM) and the position of the sun. The position of the sun is available in the Metadata file downloaded with the other spectral bands from USGS. Considering the error of overestimate of water bodies, all common pixels classified as water and also in the region of shadow depth, are removed by raster calculator using logical equation.\n\nThe binary images of surface water during the non-rainy season were developed for the year 2016, which depicts water and non-water areas. These monthly water images were added by raster calculator and percentage occurrence of water for a year were estimated. The frequency with which pixels classified as water, are represented as percentages of occurrence.\n\nSurface water maps produced by water index method over time should be verified for accuracy as the images are historic and because surface water changes with time. There is no physically measured database of water surface area at that point of time to compare. Thus, the obtained MNDWI water maps are compared with JRC GSWE surface water maps of the corresponding months (see Underlying data48).\n\nThe accuracy analysis is performed using a confusion matrix method developed by comparison between reference images and the indexed-based surface water map24,32. It represents the correspondence between the resulting image of classification and the reference image. The method is well documented and illustrated in many references to calculate the confusion matrix parameters18,33. Those articles are referred to and followed in this study. The Producer’s Accuracy (PA), User’s Accuracy (UA) and Overall Accuracy (OA) represent the correctness classification of surface water images and are expressed in percentage. These calculations do not consider the agreement between data-sets that occur by chance alone. Hence, the kappa coefficient tool to control the random agreement factor, is often used. Kappa coefficient ranges from -1 to + 1, where 0 represents agreement occurring by chance and 1 represents perfect agreement.\n\n\nResults and discussion\n\nAfter the radiometric corrections and the creation of the subset to study area extent, all images are processed (using QGIS 3.22.3) for derivation of water indices (see Figure 4). The figures use the YYYYMMDD format to express dates corresponding to the Landsat image. The MNDWI images clearly visualizes enhancement in open surface water features. Surface water features appear bright compared to other non-water features. The western side of the study region is mountainous, which is where the majority of surface water bodies are located. Among all the derived images the MNDWI index is in the range of -1 to 0.86. The brightness variation is observed because of the topographic corrections characterized by undulating and complex terrain. MNDWI images derived on 22nd February 2016 and 9th March 2016 indicate cloud cover of 23.09 % and 9.83 %, respectively.\n\nThe water indices images are processed for separation of water and non-water regions using a threshold slicing method. The Otsu’s threshold method is evaluated for threshold slicing for all available images. The derived binary classified image, consisting of water and non-water pixels, is compared for accuracy to the JRC GSWE water map for the corresponding month using a confusion matrix. The threshold value and confusion matrix parameters for each image are presented in Table 2. The result obtained using the Otsu’s threshold method were unsatisfactory and the model failed to produce decent results (see Figure 5). The sample calculation for clear and cloud free image captured on 6th February 2016 have been presented for discussion. The results for the rest of the images are similar. The input MNDWI image, corresponding grey scale histogram and output surface water image from Otsu’s threshold are presented in the Figure 5. MNDWI images have the range of values(-1 to 0.86), resulting in the formation of multi-modal histograms. The output image is a result of ’salt-and-pepper’ noise. The threshold value obtained by Otsu method for this image is -0.04. The threshold divides images into two classes: pixel values less than -0.04 and pixel values greater than -0.04.\n\nThsd, Threshold; PA, Producer’s Accuracy; UA, User’s Accuracy; OA, Overall Accuracy.\n\nForward class pixels with values less than the cutoff have a majority of non-water characteristics. This portion of the binary image appears as ’salt’. The pixels with values more than threshold includes maximum pixels with water and other features as well. Background classes have a large number of pixels compared to forward classes. However, it has been demonstrated that this method produces unstable results when the proportions of water and non-water pixels are not equal and do not form a bimodal histogram34. Data transmission error while calculating the threshold in Otsu’s algorithm could be another reason for the unsatisfactory result.\n\nThe iterative trial and error method was used as an alternative to the Otsu method (Figure 7). The optimum threshold value was determined for each image. The result classified binary image is compared with the reference image. The confusion matrix parameters are performed for all images of MNDWI derived by both Otsu’s Method and trial and error method (Table 2). The threshold by the Otsu’s method is less than zero, whereas, the threshold by trial and error method are all positive values. Based on the classification point of view, the producer’s accuracy (PA) represents error of omission. Otsu’s method analyses the gray scale histogram and classifies more pixels as water. PA of surface water map derived using the Otsu’s method and trial and error method, indicate the proportion of the GSWE image that is classified as water. More pixels of the water class reduces the percentage of omission in comparison with the GSWE water map. Both methods result in high PA for classification. UA of MNDWI surface water map derived using the Otsu’s method and trial and error method, represent the probability that pixels classified as water actually represent water in the GSWE data. UA measures error of commission, which represents the number of pixels assigned to the incorrect class. The Otsu’s threshold method classified all pixels with a gray scale level more than the respective threshold as water. This class has other topographic features along with water. Thus, the error of commission obtained is high for the MNDWI surface water maps derived by the Otsu’s method. However, iterative trial-and-error method performed better in terms of UA for surface water mapping. The minimum threshold value 0.12 is applied to the image captured in May and maximum threshold value 0.46 is applied to images acquired in February. The threshold values depend on the MNDWI range of the image. The MNDWI index observed is higher in February and lower in May among all the images of the study area. The summer season in the study area peaks around May during which the majority of surface water bodies shrink and have less water availability (see Table 3). The reduced amount of water causes turbidity and exposes silt affecting the satellite reflectance, resulting in a reduction in the number of classified water bodies. This is the reason for less MNDWI index during the summer season, between April and May. The monsoon season is observed during June to September in the study area during which the reservoirs are in full water condition (i.e. the reservoir is filled with maximum capacity of water). However the presence of cloud limits the availability of clear images. The images of immediate post monsoon season are observed with high (>0.7) MNDWI values. The non-water area has a wetness factor, which is why the lower MNDWI index has been raised from -1 to -0.7. The reservoirs with full water conditions can be easily visualized and delineated by the MNDWI method.\n\nMountain shadows have sometimes been misclassified as water. The DEM have been used to detect the misclassified portion of the surface water by mountain shadow noise (Figure 6 (a)). The mountain shadow depth in relation to sun elevation angle and DEM have been derived, and the mountain shadow depth can be seen as the white spots in the Figure 6 (b). The surface water derived by trial and error method to MNDWI spectral image is the overlay with the mountain shadow depth in Figure 6 (c). This misclassification is removed by applying logical operation (Figure 6 (d)). Surface water bodies located towards the western hilly regions of the study area are extracted successfully (Figure 8). The MNDWI result is presented in Table 2, and all are followed by shadow depth analysis for removal of misclassification of water bodies.\n\n(a) Digital Elevation Model (DEM) of Pune. (b) Mountain shadow depth derived from DEM. (c) Misclassified mountain shadows as water (red area is water and white area is mountain shadow). (d) Integrating shadow depth with binary Modified Normalized Difference Water Index (MNDWI) image to remove misclassified water. Landsat 8 image courtesy of the U.S. Geological Survey.\n\nLandsat 8 image courtesy of the U.S. Geological Survey.\n\nThe intra-annual distribution of surface water is prepared by mapping maximum water extents during eight months of the year in 2016. The comprehensive picture of the dynamics of the surface water on yearly basis is prepared. The percentage of occurrence at which water was present on the surface during all months except monsoon season, June to September, was captured in a single image (Figure 8). Performing the accuracy analysis of the map is not possible and can be compared with a similar database. The JRC GSWE map has weekly, monthly and yearly data of surface water. The annual surface water map, JRC GSWE annual image of 2016, is delineated for the study area extent (Figure 9). The JRC GSWE yearly image is a single image representing all months of water occurrence in that year, in terms of permanent and seasonal water.\n\nThe overall water occurrence computed by MNDWI during the dry period only, would be biased because it would give more weight to the dry period than the wet period.\n\nThis could be a limitation of the study and proposed for a future aspect of the research.\n\nThe surface area of seven clearly visible reservoirs in the MNDWI maps and with surface area more than 500 hectors, were estimated for each of the eight months and compared to the surface area of those reservoirs calculated using GSWE data for the same months (Table 3). The seven reservoirs are Bhama Askhed, Bhatghar, Chaskaman, Mulashi, Panshet, Shivrata and Varasgaon. The information on water occurrence and recurrence is presented in Figure 9 and Figure 10. The pattern in changing surface area by both the methods is the same. The surface area of all reservoirs is higher by GSWE methods during all the eight months except October and November, which is immediately after the monsoon months. The maximum difference in the values of surface area is observed in May and October. During May, the water storage is less in reservoirs with deteriorated water quality. In both the cases, the MNDWI method classified water for less surface area values. After the immediate monsoon, the surrounding dry land areas of the water bodies are generally misclassified as water bodies class areas due to wetness during the monsoon the in spectral indices method. The thematic maps and temporal profile were used to characterize the transition between the months of the years. MNDWI performed better in delineating large water bodies, as demonstrated by comparison to the reference data. The method also monitored the changes in quantity of water on a yearly basis.\n\n\nConclusions\n\nInland surface water bodies in Pune district were detected and mapped using MNDWI spectral index derived from Landsat 8 OLI. The surface water was detected and mapped using cloud free images from eight months of the year 2016. Long term monitoring of surface water using spectral indices derived from Landsat is possible, however it is susceptible to cloud presence and some topographic restrictions.\n\nAutomatic Otsu’s threshold method is tested to separate water and non-water classes from the MNDWI image. The results obtained with Otsu’s method are not satisfactory. The MNDWI images input to Otsu’s method represent a threshold in the range -1 to 0.86. The image is multi-modal and has more than two classes. Otsu’s method requires that the number of pixels of both the classes should be proportionate. The MNDWI image has large discrepancy between the number of water and non-water pixels. The trial and error method of threshold slicing is tedious and time consuming. The trial and error method was used in iterative manner to achieve a better result. The threshold is different for all MNDWI images acquired on different dates. The Kappa coefficient represent better agreement between MNDWI and GSWE reference maps. The result obtained by trial and error methods are satisfactory.\n\nThe shadow depth derived using DEM is integrated with the MNDWI image to remove the shadow effect. The shadow effect is successfully removed and better results are achieved.\n\nAn annual surface water occurrence map is prepared from monthly surface water maps to study the dynamics of surface water. Permanent water occurrence at seven reservoirs with more than 100 Ha surface area were analyzed and compared for surface water areas on a yearly basis with reference images.\n\nAccuracy analysis of the result is challenging because of the unavailability of physically measured data. The physically measured data for such cases is rarely available. The result obtained in this study are compared with the reference map. Hence, the comprehensive accuracy analysis could be a limitation of this study. The performance of the method may differ from the result presented in this study, by implementation of improved automatic threshold method, consideration of vegetation cover, and water quality as an aspect of further research.\n\n\nData availability\n\nThe cloud free Landsat 8 Operational Land Imager (OLI) images of the Pune District (path:147 and row:047) that were used in this study are publicly available from the US Geological Survey (USGS) Global Visualization Viewer here: https://earthexplorer.usgs.gov/\n\nThe Joint Research Centre Global Surface Water Explorer (JRC GSWE) monthly map used for comparison in this study44 is publicly available for download here: https://jeodpp.jrc.ec.europa.eu/ftp/ jrc-opendata/GSWE/MonthlyHistory/VER3-0/ tiles/2016/2016_12/\n\nZenodo: Surface Water Maps of Pune District in India. https://doi.org/10.5281/zenodo.659967348. This project contains the following underlying data:\n\nPune-SRTM_DEM.tiff (SRTM Digital Elevation Model representing surface topography of the study area).\n\nPune-SRTM_DEM.hdr (metadata about the Pune-SRTM_DEM.tiff).\n\nSurface_Water_Pune_20160121.tif (binary image representing the water and non-water areas in the study area on 21st January 2016. The nomenclature of the file is as Surface_Water_Pune_YYYYMMDD. Similar files are available at the same link for the other cloud free dates in 2016).\n\nSurface_Water_Pune_20160121.hdr (meta-data about the image file from 21st January 2016. The nomenclature of the file is as Surface_Water_Pune_YYYYMMDD. Similar files are available at the same link for the other cloud free dates in 2016).\n\nZenodo: Top of Atmospheric Reflectance (ToA) Landsat 8 OLI. https://doi.org/10.5281/zenodo.664038846.\n\nThis project contains the following underlying data:\n\nRT_LC08_L2SP_147047_20160121_20200907_02_ T1_SR_B1.TIF (top of atmospheric reflectance calculated from the raw digital number of Landsat 8 OLI on 21s January 2016. The image contains seven visible bands named as B1 to B7. All images captured on cloud free days of the year 2016 are made available at the same link).\n\nRT_LC08_L2SP_147047_20160121_20200907_02_ T1_SR_B1.TIF.aux.xml (the description of the above image in xml format. All descriptions for each image are made available at the same link).\n\nData are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).\n\nAnalysis code available from: https://github.com/rushikulk/Otsus_Threshold/tree/v1.0.0\n\nArchived analysis code at time of publication: https://doi.org/10.5281/zenodo.660254547.\n\nLicense: GPL-3.0-only", "appendix": "Acknowledgements\n\nWe are grateful to the U.S. Geological Survey website for making satellite data freely available.\n\n\nReferences\n\nBoretti A, Rosa L: Reassessing the Projections of the World Water Development Report. npj Clean Water. 2019; 2(1): 15. Publisher Full Text\n\nUnited Nations: The United Nations World Water Development Report. UNESCO, 2015; ISBN 9789231000713.\n\nEL-Nwsany RI, Maarouf I, Abd el Aal W: Water management as a vital factor for a sustainable school. Alexandria Engineering Journal. 2019; 58(1): 303–313. Publisher Full Text\n\nKarpatne A, Khandelwal A, Chen X, et al.: Global monitoring of inland water dynamics: State-of-the-art, challenges, and opportunities. Studies in Computational Intelligence. 2016. Publisher Full Text\n\nMahmud HB, Nagai M: Automated extraction of flood for large scale area using weight average otsu’s method from alos-2 dual polarization and modis. The 40th Asian Conference on Remote Sensing (ACRS 2019) Daejeon, Korea. 2019.\n\nBassi N, Dinesh Kumar M, Sharma A, et al.: Status of wetlands in India: A review of extent, ecosystem benefits, threats and management strategies. Journal of Hydrology: Regional Studies. 2014; 2: 1–19. Publisher Full Text\n\nChang NB, Bai K: Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. CRC Press, 2018. Publisher Full Text\n\nPalmer SCJ, Kutser T, Hunter PD: Remote sensing of inland waters: Challenges, progress and future directions. Remote Sensing of Environment. 2016; 157: 1– 8. Publisher Full Text\n\nHuang C, Chen Y, Zhang S, et al.: Detecting, extracting, and monitoring surface water from space using optical sensors: A review. Reviews of Geophysics. 2018; 56(2): 333–360. Publisher Full Text\n\nChang NB, Imen S, Vannah B: Remote sensing for monitoring surface water quality status and ecosystem state in relation to the nutrient cycle: A 40-year perspective. Critical Reviews in Environmental Science and Technology. 2014; 45(2): 101–166. Publisher Full Text\n\nAcharya TD, Lee DH, Yang IT, et al.: Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree. Sensors (Basel). 2016; 16(7): 1075. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nXie H, Luo X, Xu X, et al.: Evaluation of Landsat 8 OLI imagery for unsupervised inland water extraction. International Journal of Remote Sensing. 2016; 37: 1826–1844. Publisher Full Text\n\nLi Y, Gong X, Guo Z, et al.: An index and approach for water extraction using Landsat–OLI data. International Journal of Remote Sensing. 2016; 37(16): 3611–3635. Publisher Full Text\n\nDu Z, Li W, Zhou D, et al.: Analysis of Landsat-8 OLI imagery for land surface water mapping. Remote Sensing Letters. 2014; 5(7): 672–681. Publisher Full Text\n\nGao H, Wang L, Jing L, et al.: An effective modified water extraction method for Landsat-8 OLI imagery of mountainous plateau regions. IOP Conference Series: Earth and Environmental Science. 2016; 34: 012010. Publisher Full Text\n\nYang Y, Liu Y, Zhou M, et al.: Landsat 8 OLI image based terrestrial water extraction from heterogeneous backgrounds using a reflectance homogenization approach. Remote Sensing of Environment. 2015; 171: 14–32. Publisher Full Text\n\nLiu Z, Yao Z, Wang R: Assessing methods of identifying open water bodies using Landsat 8 OLI imagery. Environmental Earth Sciences. 2016; 75: 873. Publisher Full Text\n\nJi L, Geng X, Sun V, et al.: Target Detection Method for Water Mapping Using Landsat 8 OLI/TIRS Imagery. Water. 2015; 7(2): 794–817. Publisher Full Text\n\nSingh K, Ghosh M, Sharma S: WSB-DA: Water Surface Boundary Detection Algorithm Using Landsat 8 OLI Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2016; 9(1): 363–368. Publisher Full Text\n\nXu H: Modification of Normalised Difference Water Index ( MNDWI ) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing. 2006; 27(14): 3025–3033. Publisher Full Text\n\nBhavsar PD: Review of remote sensing applications in hydrology and water resources management in India. Advances in Space Research. 1984; 4(11): 193–200. Publisher Full Text\n\nFluet-Chouinard E, Lehner B, Rebelo LM, et al.: Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data. Remote Sensing of Environment. 2015; 158(1): 348– 361. Publisher Full Text\n\nPekel JF, Vancutsem C, Bastin L, et al.: A near real-time water surface detection method based on HSV transformation of MODIS multi-spectral time series data. Remote Sensing of Environment. 2014; 140: 704–716. Publisher Full Text\n\nCai X, Feng L, Hou X, et al.: Remote Sensing of the Water Storage Dynamics of Large Lakes and Reservoirs in the Yangtze River Basin from 2000 to 2014. Scientific Reports. 2016; 6: 36405. PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nLu S, Jia L, Zhang L, et al.: Lake water surface mapping in the Tibetan Plateau using the MODIS MOD09Q1 product. Remote Sens Lett. 2017; 8(3): 224–233. Publisher Full Text\n\nChang WLH, Yun C, Rui L: An evaluation of Suomi NPP-VIIRS data for surface water detection. Remote Sens Lett. 2015; 6(2): 155–164. Publisher Full Text\n\nDavranche A, Lefebvre G, Poulin B: Wetland monitoring using classification trees and SPOT-5 seasonal time series. Remote Sens Environ. 2010; 114(3): 552–562. Publisher Full Text\n\nFisher A, Danaher T: A Water Index for SPOT5 HRG Satellite Imagery, New South Wales, Australia, Determined by Linear Discriminant Analysis. Remote Sens. 2013; 5(11): 5907–5925. Publisher Full Text\n\nDu Y, Zhang Y, Ling F, et al.: Water Bodies’ Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band. Remote Sens. 2016; 8(4): 354. Publisher Full Text\n\nYang X, Zhao S, Qin X, et al.: Mapping of Urban Surface Water Bodies from Sentinel-2 MSI Imagery at 10 m Resolution via NDWI-Based Image Sharpening. Remote Sens. 2017; 9(6): 596. Publisher Full Text\n\nBhangale U, More S, Shaikh T, et al.: Analysis of Surface Water Resources Using Sentinel-2 Imagery. Procedia Comput Sci. 2020; 171: 2645–2654. Publisher Full Text\n\nOlmanson LG, Brezonik PL, Bauer ME: Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and Limitations of Current and Upcoming Satellite Systems. Handbook of Environmental Chemistry. 2015; 111–140. Publisher Full Text\n\nBijeesh TV, Narasimhamurthy KN: Surface water detection and delineation using remote sensing images: a review of methods and algorithms. Sustainable Water Resources Management. 2020; 6: 68. Publisher Full Text\n\nChawla I, Karthikeyan L, Mishra AK: A review of remote sensing applications for water security: Quantity, quality, and extremes. J Hydrol. 2020; 585: 124826. Publisher Full Text\n\nde Moura Reis LG, de Oliveira Souza W, Neto AR, et al.: Uncertainties involved in the use of thresholds for the detection of water bodies in multitemporal analysis from landsat-8 and sentinel-2 images. Sensors (Basel). 2021; 21(22). PubMed Abstract \| Publisher Full Text \| Free Full Text\n\nFisher A, Flood N, Danaher T: Comparing Landsat water index methods for automated water classification in eastern Australia. Remote Sens Environ. 2016; 175: 167–182. Publisher Full Text\n\nJiang H, Feng M, Zhu Y, et al.: An Automated Method for Extracting Rivers and Lakes from Landsat Imagery. Remote Sens. 2014; 6(6): 5067–5089. Publisher Full Text\n\nTulbure MG, Broich M: Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011. ISPRS J Photogramm Remote Sens. 2013; 79: 44–52. Publisher Full Text\n\nLi W, Du Z, Ling F, et al.: A Comparison of Land Surface Water Mapping Using the Normalized Difference Water Index from TM, ETM+ and ALI. Remote Sens. 2013; 5(11): 5530–5549. Publisher Full Text\n\nMcFeeters SK: The use of the normalized difference water index (ndwi) in the delineation of open water features. Int J Remote Sens. 1996; 17(7): 1425–1432. Publisher Full Text\n\nFeyisa GL, Meilby H, Fensholt R, et al.: Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery. Remote Sens Environ. 2014; 140: 23–35. Publisher Full Text\n\nZhou S, Kan P, Silbernagel J, et al.: Application of image segmentation in surface water extraction of freshwater lakes using radar data. ISPRS Int J Geo-Inf. 2020; 9(7): 424. Publisher Full Text\n\nSarp G, Ozcelik M: Water body extraction and change detection using time series: A case study of Lake Burdur, Turkey. J Taibah Univ Sci. 2016; 11(3): 381–391. Publisher Full Text\n\nPekel JF, Cottam A, Gorelick N, et al.: High-resolution mapping of global surface water and its long-term changes. Nature. 2016; 540(7633): 418–422. PubMed Abstract \| Publisher Full Text\n\nMundhe N, Ravindra G, Jaybhaye R: A study of urbanization in pune district using geoinformatics approach. International Journal of Advance and Applied Research. 2014; 2: 45–55.\n\nKulkarni R, Khare K, Khanum H: Top of atmospheric reflectance (toa) landsat 8 oli. dataset, 2022. http://www.doi.org/10.5281/zenodo.6640388\n\nrushikulk: rushikulk/otsus_threshold. code, 2022. http://www.doi.org/10.5281/zenodo.6602545\n\nRushikesh K, Kanchan K, Humera K: Surface water maps of pune district in india. dataset., 2022. http://www.doi.org/10.5281/zenodo.6599673" }	[ { "id": "148769", "date": "14 Sep 2022", "name": "Bharath R", "expertise": [ "Reviewer Expertise Hydrology", "Flood model development", "Remote sensing and GIS application in Hydrology." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nReview of “Detecting, extracting, and mapping of inland surface water using Landsat 8 Operational Land Imager: A case study of Pune district, India” by Rushikesh Kulkarni, Kanchan Khare, and Humera Khanum\nThe paper focuses on using established methods to detect and extract waterbodies and their applications on a case study. The originality of the work lies in the application as such a study has not been carried out for the waterbodies around city of Pune previously. This study is vital to understand the water availability and demand dynamics around the city that may eventually help town planning officials to make sound decisions in the future. The use of open-source platforms like QGIS and GEE will enable reproducibility of the approach and thus can be applied to other parts of the country/world.\n\nComments:\nFigure 2: The figure would need to be enhanced as it is of a lower resolution.\n\nFigure 2 is introduced before Figure 1. It is advised to change the order of the sections as Study area – Data – Methods instead of the current Methods – study area – data. This could also resolve the discontinuity, as the introduction of methods is in page 4 and the description of the methods in page 6.\n\nFigure 6 pertains to mountain shadows and Figure 7 about the Otsu method. However, in the write-up Otsu method is discussed prior to mountain shadow effect. The authors could consider changing Figure 6 to reflect Otsu Method results followed by Figure 7 about mountain shadow. This would help in improving continuity of the paper.\n\nThe MNDWI index has been used to determine Annual surface water occurrence map and reservoir surface area comparison. However, there is no mention about them in the previous sections. The authors could list them as applications of their analysis in any relevant section.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] }, { "id": "143930", "date": "13 Jan 2023", "name": "Phaisarn Jeefoo", "expertise": [ "Reviewer Expertise Remote Sensing and GIS" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nRegarding this article, the article is scientifically valid in its current form. The experimental design, including controls and methods, is adequate; results are presented accurately and the conclusions are justified and supported by the data. I have comments on 4 items as follows:\nComment 1: Increase the resolution clarity of the symbol description of figures 2, 4, 5, 9, and 10. The authors should increase the contrast of the figure more - the letters and numbers are too small and makes it difficult for the reader to see clearly.\nComment 2: Conclusion - should add content about limitation of the study.\nComment 3: Copyediting should be done before indexing.\n\nComment 4: References section should be re-checked again before being indexed.\n\nIs the work clearly and accurately presented and does it cite the current literature? Yes\n\nIs the study design appropriate and is the work technically sound? Yes\n\nAre sufficient details of methods and analysis provided to allow replication by others? Yes\n\nIf applicable, is the statistical analysis and its interpretation appropriate?\nYes\n\nAre all the source data underlying the results available to ensure full reproducibility? Yes\n\nAre the conclusions drawn adequately supported by the results? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-774
https://f1000research.com/articles/11-771/v1	11 Jul 22	{ "type": "Method Article", "title": "Heatmaps and consensus clustering for ego network exploration", "authors": [ "Philippe Boileau", "Lisa Kakinami", "Tracie Barnett", "Mélanie Henderson", "Lea Popovic", "Philippe Boileau", "Lisa Kakinami", "Tracie Barnett", "Mélanie Henderson" ], "abstract": "Background: Researchers need visualization methods (using statistical and interactive techniques) to efficiently perform quality assessments and glean insights from their data. Data on networks can particularly benefit from more advanced techniques since typical visualization methods, such as node-link diagrams, can be difficult to interpret. We use heatmaps and consensus clustering on network data and show they can be combined to easily and efficiently explore nonparametric relationships among the variables and networks that comprise an ego network data set. Methods: We used ego network data from the Québec Adipose and Lifestyle Investigation in Youth (QUALITY) cohort used to evaluate this method. The data consists of 35 networks centered on individuals (egos), each containing a maximum of 10 nodes (alters). These networks are described through 41 variables: 11 describing the ego (e.g. fat mass percentage), 18 describing the alters (e.g. frequency of physical activity) and 12 describing the network structure (e.g. degree). Results: Four stable clusters were detected. Cluster one consisted of variables relating to the interconnectivity of the ego networks and the locations of interaction, cluster two consisted of the ego’s age, cluster three contained lifestyle variables and obesity outcomes and cluster four was comprised of variables measuring alter importance and diet. Conclusions: This exploratory method using heatmaps and consensus clustering on network data identified several important associations among variables describing the alters’ lifestyle habits and the egos’ obesity outcomes. Their relevance has been identified by studies on the effect of social networks on childhood obesity.", "keywords": [ "exploratory data analysis", "visualization", "heatmap", "consensus clustering", "networks", "obesity" ], "content": "Introduction\n\nVisualization methods relying on a combination of statistical and interactive techniques are becoming necessary for researchers to efficiently perform quality assessments and glean insights from their data.1 Networks are data structures that are particularly benefiting from such advancements. A network consists of a set of nodes, also called vertices, that are connected to one-another by edges. Networks allow scientists to model and investigate the complexities of structure of the systems they are researching, offering more insight than analyzing their individual components.2 They have been used to model and study various phenomena, from Internet traffic to food webs.\n\nNetwork data are commonly visualized by node-link diagrams (Figure 1), which consist of plotting the nodes and edges. Variables pertaining to the nodes and edges are also often included in the node-link diagram; the node’s colour may represent a categorical variable, or the thickness of an edge may capture an aspect of the relationship between connected nodes. While this makes it easy to discern some topological qualities of the network,3 such as the number of edges a node shares with the other nodes (the node’s degree) or the interconnectedness of the nodes (the network’s density), this visualization’s utility is limited by the size of the network and the number of variables used to describe its various parts.\n\nThe visualization to the left helps observers gain a sense of the structure of the network by emphasizing the most central node. On the other hand, the depiction on the right permits a quick assessment of the network’s connectedness.\n\nAs the number of vertices, edges and variables characterizing each increase, the visualization becomes cluttered and difficult to interpret. These issues are compounded when attempting to perform exploratory data analysis (EDA) on network data with multiple components, i.e. a network in which there are groups of nodes that do not share any edges, or many disjoint ego networks, such as personal social networks. Ego networks consist of a central node (the ego) that is implicitly connected to all other nodes in the network (the alters), which can share edges among themselves. Due to the constraint on the size of the node-link diagrams and the amount of information that can be presented, comparisons between many ego networks at once is difficult.\n\nAn alternative representation technique that may be more appropriate for such network data is the heatmap. A heatmap is a graphical representation of a two-dimensional matrix4 and is a versatile tool for illustrating multivariate data, as demonstrated with the mtcars dataset (https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/mtcars.html) in Figure 2. Since heatmaps can display large quantities of information in a single figure, it is an ideal tool for presenting multiple ego networks and their variables. Heatmaps rely on two key elements to convey information clearly and efficiently: hierarchical clustering and an appropriate color palette.4 These two elements maximize the pattern recognition potential within the visualization. Additionally, when presented in the appropriate medium (i.e. in a dynamic report), heatmaps can be turned into interactive visualizations using software like heatmaply.5 The interactivity of the heatmap can improve its legibility, and therefore its use as an EDA tool.\n\nNotice the cluster of compact cars in the top left corner, clearly grouped together by their relatively small engines and weight (top left, dark green-blue rectangles), and by their superior efficiency (top right, light green and yellow rectangles). The most performant cars are grouped together near the center of the y-axis, clustered together due to their larger engines and reduced efficiency.\n\nAlthough heatmaps offer an efficient way to depict large quantities of data,4 it can be difficult to identify the meaningful patterns in the visualization. Thus, heatmaps’ pattern recognition potential can be augmented by using methods that identify stable patterns under data perturbations. Consensus clustering6 is one such nonparametric method for assessing the stability and stability of patterns identified in a heatmap. More information on consensus clustering is provided in the methods section.\n\nThe objective of this analysis was to determine whether the combination of heatmaps and consensus clustering is an effective tool for representing ego network data. Heatmaps are particularly convenient for depicting high-dimensional data, though, to the best of our knowledge, their application in this setting has yet to be studied. Data from a pilot study investigating the influence of adolescent’s social network on their obesity outcomes were used to evaluate this methodology’s performance.\n\n\nMethods\n\nThis methodology relies on the application of agglomerative hierarchical clustering (referred throughout the paper as hierarchical clustering), heatmaps and consensus clustering to ego network data. The following paragraphs provide details on their individual implementations, and how they are used in tandem to produce a novel EDA method for this data structure.\n\nHierarchical clustering is an unsupervised learning method that aims to find clusters of similar items in a data set, where items can be either variables or observations. Numerous methods exist to quantify the similarity among items, like Euclidean distance, correlation or Manhattan distance. At the start of the procedure, each item forms its cluster. These items are then paired with others based on their similarities, forming new clusters.7 Between cluster similarity can be measured by various methods, though the most popular are the single, average and complete linkage methods. For information on these linkage methods, see James et al.7 With each iteration of the algorithm, the number of elements in each cluster increases, the number of individual clusters decreases and, generally, the average similarity among the items in each cluster decreases. The process ends when only a single cluster remains. The result of this procedure is often depicted by a tree, known as a dendrogram (Figures 2 and 3), illustrated on the axes of the heatmaps. The dendrogram can be used to infer the cluster membership of each item by “cutting” the tree at various levels of similarity, which corresponds to the height of the tree. Cutting the tree at higher levels of similarity will produce granular clusters (i.e. many small groups of similar items), whereas lower levels of similarity will produce larger clusters composed of more dissimilar items. Thus, the dendrogram can be cut at the lowest height that produces an a priori specified number of clusters. Selecting the appropriate number of clusters in the data is a challenging task, though, as we will see later, consensus clustering can help in making a reasonable choice. As is customary with methods relying on some notion of distance, the data subjected to hierarchical clustering are often normalized.\n\nAn aggregation step must take place prior to the application of hierarchical clustering due to the structure of ego network data. Ego networks can be described by variables pertaining to the ego, the alters, the edges between alters and to the network itself, such as its structural characteristics. Unfortunately, there is no obvious way to apply hierarchical clustering to multilevel data, where the higher level comprises the ego and network variables, and the lower level is composed of the alter and edge variables. To transform the data into a format compatible with hierarchical clustering, the alter and edge variables within each network are summarized by some measure of center. The choice of statistic, such as the mean, median or mode, will depend on the characteristics of the variables being summarized. Once this step is accomplished, the transformed ego network data is ready to undergo hierarchical clustering; each observation consists of an ego network described by variables relating to the ego, the network and measures of centers of the alter and edge variables.\n\nThe dendrograms produced by subjecting the transformed ego network data to hierarchical clustering are then used to create the heatmap of the data. The heatmap is comprised of networks across rows and of variables across columns. The cells in the heatmap, represent normalized variable values and, should be colored using a divergent color palette to promote pattern recognition.4\n\nConsensus clustering is then used to identify the number of clusters among the transformed network data’s variables and to quantify the stability of the clusters nonparametrically.6 Consensus clustering repeatedly applies multiple user-defined clustering methods to random subsets of the data and evaluates the frequency with which variables are clustered together over repeated samples. Given a set of n items subjected to some clustering method, the consensus matrix, X, is an n×n matrix where Xi,j corresponds to the fraction of iterations of the algorithm for which items i and j were members of the same cluster. A value near one signifies that items i and j are often clustered together, whereas a value near zero implies that they are rarely grouped together. The resulting consensus matrix is then summarized using the cluster consensus and item consensus statistics,6 which measure within-cluster stability and item-wise stability, respectively.6 Consensus clustering thus identifies stable clusters in the data, further increasing the interpretability of the heatmaps by pinpointing the more meaningful patterns in the visualization. Additionally, Monti et al. use the empirical cumulative density function (ECDF) of the entries in the consensus matrix to identify the appropriate number of stable clusters in the data.6 For example, if hierarchical clustering is used to group the items, consensus clustering can be repeatedly applied such that each iteration of hierarchical clustering specifies a different number of clusters. The ECDFs produced by applying consensus clustering for a range of the number of clusters can then be compared. When the items in the data are perfectly clustered under repetition, i.e. the consensus matrix entries consist of zeros and ones, the ECDF of the consensus clustering is a step function with a single step between zero and one.6 As the clustering becomes less exact, the step transforms into a smooth, monotonically non-decreasing line.6 Sharp changes in the ECDF curves of consecutive consensus clustering procedures can help distinguish the number of stable clusters in the data.6\n\nConsensus clustering is therefore applied to the variables of the transformed ego network data in order to identify the meaningful associations depicted in the heatmap, and to quantify the strengths of these relationships. Hierarchical clustering is used to cluster the random subsets of the data in each iteration. Depending on the goals of the EDA, consensus clustering may also be applied to the ego networks to identify clusters of similar networks.\n\nAn open-source R implementation8 (R Project for Statistical Computing, RRID:SCR_001905) of this methodology was developed and is available in the neatmaps package (v2.1.1).9 This software, along with relevant documentation and examples, is available on CRAN and on GitHub at github.com/PhilBoileau/neatmaps.10 This package makes heavy use of two packages: heatmaply (v.1.3.0)5 was used to produce the heatmaps, and ConcencusClusterPlus (v1.36.0)11 was used to implement consensus clustering.\n\nIn the realm of public health, social networks have been used to model the spread of non-infectious diseases like obesity.12–14 However, as the obesity epidemic currently affects over a third of the world’s population,15 the development of novel methods to better understand and potentially mitigate its spread are needed. While targeting multiple behaviours like diet and physical activity to reduce body weight is recognized as an effective strategy,16 their benefits may be further augmented through social network-based programs. Though evidence suggests that these interventions may positively impact obesity outcomes, further investigation is required.14 Thus, we applied our novel EDA approach to an ego network data set collected by a pilot study exploring the relationship between adolescent social networks and obesity outcomes.\n\nData were obtained from a pilot study on the influence of adolescent’s social networks on health outcomes (n = 46) from the Quebec Adipose and Lifestyle Investigation in Youth (QUALITY) cohort (n = 630). QUALITY is an ongoing longitudinal study which investigates the natural history of obesity using a sample of at-risk Caucasian youths in Quebec.17 At-risk youth were defined as children with at least one overweight parent (i.e. body mass index (BMI) over 30 kg/m2 or waist circumference over 102 cm for men and 88 cm for women, based on self-reported height, weight and waist circumference)17 at the start of the study. The pilot aimed to evaluate the data collection processes and to identify patterns that could lead to new research questions for the full-scale study. A complete case analysis of the pilot data was performed (n = 35 ego networks). QUALITY obtained ethics approval (#MP-21-2005-79, 2040) from the Centre Hospitalier Universitaire Sainte-Justine. Parents signed consent forms and children provided assent. This secondary data analysis was approved by the Concordia Research Ethics Board (#300116369).\n\nEach of the pilot study’s participants (egos) was asked to list up to ten people (alters) with whom they felt comfortable discussing important personal matters in the past year. The egos then reported their alters’ demographic characteristics (age, sex), location of alter’s residence with respect to the ego’s, perceived body type, health behaviours (frequency of physical activity, frequency of eating healthy (e.g. avoiding junk food), frequency of undertaking a diet for weight loss, frequency of Internet use), and support (frequency of encouraging ego to be physically active and frequency of performing at least 30 minutes of physical activity with the alter). Egos also reported on relationship characteristics (duration, closeness, importance, frequency of contact, types of interaction [i.e. face to face, phone, email, SMS, social media, video call and other]), location of interactions (home, work, school, hobby, media and other). The mean of these alter variables was computed within each ego network. Each participant was also asked to answer the questions pertaining to their own frequency of physical activity, of healthy eating, of dieting for weight loss, and of Internet use using questionnaires published in the literature18,19 as described in our previous work.20\n\nOther ego data included height and weight (measured via stadiometer and electronic weight scale, respectively),17 fat mass percentage (measured using dual-energy absorptiometry) and body mass index z-scores in accordance with the WHO growth curves accounting for age and sex.21\n\nEach participant (ego) has an associated network consisting of alters (nodes) based on ego-reported friendship or family ties (edges). Based on these ties, certain topological characteristics of each ego network were computed. These metrics were the ego degree, mean alter degree, density, constraint,22 hierarchy,23 effective size and efficiency.24 Additionally, the networks’ homophily indices25 were calculated for each of the following variables: age, gender, perceived body type and frequency of physical activity, of eating healthy, dieting for weight loss and of Internet use.\n\n\nResults\n\nThe EDA method was applied to the QUALITY ego network data using Euclidean distance as a similarity metric and the average linkage method for between-cluster similarity of the network clusters and the variable clusters. The data were normalized by rescaling each variable to have a range between 0 and 1. For variable vector v of length n with values vi for i = 1, …, n, each value vi was standardized as follows:\n\nThus, hierarchically clustering the variables produces clusters that contain positively linearly-associated variables.26 The consensus clustering step of the method was performed with predefined numbers of clusters ranging from 2 to 10. For each cluster count, 1000 repetitions of the clustering algorithm were performed on a random subset of 80% of the ego networks, as recommended in the documentation of ConcencusClusterPlus (v1.36.0).11\n\nThe heatmap of the QUALITY ego network data is shown in Figure 3, efficiently visualizing the 35 ego networks and their 41 variables. Figure 4 illustrates the consensus matrices for the consensus cluster iterations of three, four and five clusters. The ECDFs produced by the consensus clustering are illustrated in Figure 5. The clusters, their contents (along with each items’ item consensus statistic) and the clusters consensus statistic are also presented (Table 1).\n\nThis evidence suggests that four relatively stable clusters are identified in the data.\n\nThere is a clear change in the distributions of the consensus matrices for four and five clusters, suggesting that there are four clusters among the ego network data variables.\n\nThe ECDFs and the consensus matrix suggest that the data contains four stable clusters. Cluster one consists of variables relating to the interconnectivity of the ego networks and the locations of interaction, cluster two consists of the ego’s age, cluster three contains lifestyle variables and obesity outcomes and cluster four is comprised of variables measuring alter importance and diet.\n\nOf the four clusters identified during consensus clustering, cluster four is the most stable with a cluster consensus of m(5) = 0.988 (Table 1). This cluster corresponds to the six rightmost columns in the heatmap (Figure 3). This grouping suggests a positive linear relationship between the dieting habits of the egos and those of their alters, and the mean strength of the relationships in the egos’ networks. However, upon closer inspection of the heatmap, this result may be due to the lack of variability in the distributions of the variables composing the cluster.\n\nCluster three is also a stable cluster given its cluster consensus value of m(3) = 0.873 (Table 1). This cluster is positioned to the left of the solid blue streak in the center of the heatmap and provides evidence of a positive association between certain lifestyle behaviours and the obesity measures for both the egos and their alters. These results indicate that the frequency of physical activity of the egos and the alters, the frequency with which the alters encourage the ego to be physically active, the homophily of frequency of physical activity, the ego’s and alter’s frequency of healthy eating and the homophily of frequency of healthy eating in the network are potentially related to the egos’ adiposity measures such as BMI z-score, fat mass percentage and perceived body type.\n\nCluster two consists solely of the ego’s age since it was not found to be strongly associated with any of the other variables. This result is unsurprising given that all egos are approximately the same age. Such a homogeneous variable does not provide any meaningful information, and consensus clustering successfully recognized this.\n\nAlthough the results of cluster two, three and four are stable, the first cluster identified using cluster consensus is not. Cluster one has a moderate cluster consensus statistic (m(1) = 0.708), implying that its variables are less strongly associated. This cluster is positioned in between the solid blue and red columns on the right side of the heatmap (Figure 3).\n\nLastly, streaks of a single solid color (blue or red) in Figure 3 indicate that variables comprising these columns exhibit little variability. These variables are, in blue, the ego’s frequency of Internet use for entertainment, number of components, hierarchy, effective size, and, in red, density, proportion of ego interaction with alters at home, and the ego’s dieting frequency.\n\n\nDiscussion\n\nThe heatmap allows analysts to quickly identify potential associations among networks and variables, study the distributions of the variables and assess the quality of the data.\n\nThe results of the consensus clustering augment the interpretation of the heatmap by pinpointing the most meaningful clusters in the data and quantifying the associations among the clusters’ variables. The third and fourth clusters identified by this method capture previously studied relationships among the obesity outcomes and lifestyle behaviours of the egos and alters, and the ego network structure. De la Haye et al. previously observed an association between dietary intake and friendship ties among males in school-based social networks.27 Similarly, the fourth cluster identified via consensus clustering identified an association between friendship ties and dieting habits. The third cluster is consistent with the literature on childhood obesity outcomes and lifestyle behaviours within social networks.22–25 Additionally, this method recognized that ego age could not be meaningfully grouped with any other variable, which would not be apparent if the analysis relied solely on hierarchical clustering. The heatmap also permitted the efficient identification of variables which exhibit little variation, indicating to the study investigators that questions associated with these variables should be modified to capture more discerning information on the measures of interest.\n\nAlthough these results are encouraging, there are some limitations associated with using heatmaps and consensus clustering to explore ego network data. First, this EDA process requires that the data have no missing values, a rare occurrence in empirical research. Although judicious pre-processing and data imputation can remedy the situation, further work must be done to assess the sensitivity of this technique to missingness. Secondly, though consensus clustering can evaluate the quality of the hierarchical clustering, its results are data dependent. Its results should only be taken seriously when the data are a representative sample of the population of interest. Additionally, the data was scaled such that the variables were hierarchically clustered based on the strengths of their linear associations. Other data normalization methods could be used so that the hierarchical clustering targets the non-linear relationships among variables.\n\n\nConclusions\n\nWe demonstrate that, when applied to ego network data, the combination of heatmaps and consensus clustering successfully identified a number of important relationships that are consistent with literature on social networks and childhood obesity. These results may motivate further research in this field. This was accomplished without the need for substantial expertise using network analysis software; only a few functions from the neatmaps R package (v.2.1.1) were required to perform this analysis. Replication in other ego network data sets is warranted in order to further validate this methodology.\n\n\nData availability\n\nThese data were collected by the QUALITY research team, in a small subset of the cohort (35 participants out of the original 630 participants). Data are not provided in an online repository due to ethical considerations regarding confidentiality/privacy concerns for study participants. Data can be made available upon reasonable request sent to the manuscript authors or the QUALITY research team (www.etudequalitystudy.ca).\n\n\nSoftware availability\n\nSoftware available from: https://github.com/PhilBoileau/neatmaps, https://CRAN.R-project.org/package=neatmaps\n\nSource code available from: https://github.com/PhilBoileau/neatmaps\n\nArchived source code at time of publication: https://doi.org/10.5281/zenodo.645038610\n\nLicense: MIT\n\n\nAuthor’s contributions\n\nPB, LP and LK conceived the method. TB and MH furnished the data. PB implemented the method, processed the data and performed analyses. LP, LK and TB supervised the work. PB wrote the manuscript with input from all authors. All authors provided critical feedback on the method, analyses and manuscript. All authors read the final version of the manuscript and approved it.", "appendix": "Acknowledgements\n\nDr. Marie Lambert (July 1952 – February 2012), a pediatric geneticist and researcher, initiated the QUALITY cohort. Her leadership and devotion to QUALITY will always be remembered and appreciated. Finally, we are grateful to all the families participating in the QUALITY cohort.\n\nPortions of this research were presented at the Quebec Society for lipid, nutrition and metabolism scientific meeting (Magog-Orford, Quebec, February 7–9, 2018), the 5th annual PERFORM Centre conference (Montreal, Quebec, May 17, 2018) and the Canadian Statistics Student Conference (Montreal, Quebec, June 2, 2018). Thank you to all attendees who provided valuable feedback.\n\n\nReferences\n\nPerer A, Shneiderman B: Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines. IEEE Comput. Graph. Appl. 2009; 29(3): 39–51. PubMed Abstract \| Publisher Full Text\n\nNewman M: Networks: An Introduction. Oxford University Press;2010.\n\nGehlenborg N, Wong B: Networks. Nat. Methods. 2012; 9(2): 115–115. Publisher Full Text\n\nGehlenborg N, Wong B: Heat maps. Nat. Methods. 2012; 9(3): 213–213. Publisher Full Text\n\nGalili T, O’Callaghan A, Sidi J, et al.: heatmaply: an R package for creating interactive cluster heatmaps for online publishing. Bioinformatics. 2018; 34(9): 1600–1602. PubMed Abstract \| Publisher Full Text\n\nMonti S, Tamayo P, Mesirov J, et al.: Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data. Mach. Learn. 2003; 52(1): 91–118. Publisher Full Text\n\nJames G, Witten D, Hastie T, et al.: An Introduction to Statistical Learning: With Applications in R.2013.\n\nR: The R Project for Statistical Computing:Accessed February 25, 2022.Reference Source\n\nBoileau P: Neatmaps: Heatmaps for Multiple Network Data. R Package v2.1.1.2019.\n\nBoileau P: PhilBoileau/Neatmaps: F1000 Submission. Zenodo. 2022. Publisher Full Text\n\nWilkerson MD, Hayes DN: ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinforma Oxf Engl. 2010; 26(12): 1572–1573. PubMed Abstract \| Publisher Full Text\n\nDemongeot J, Hansen O, Taramasco C: Discrete dynamics of contagious social diseases: Example of obesity. Virulence. 2016; 7(2): 129–140. PubMed Abstract \| Publisher Full Text\n\nChristakis NA, Fowler JH: The Spread of Obesity in a Large Social Network over 32 Years. N. Engl. J. Med. 2007; 357(4): 370–379. Publisher Full Text\n\nHill AL, Rand DG, Nowak MA, et al.: Infectious Disease Modeling of Social Contagion in Networks. PLoS Comput. Biol. 2010; 6(11): e1000968. PubMed Abstract \| Publisher Full Text\n\nHruby A, Hu FB: The Epidemiology of Obesity: A Big Picture. PharmacoEconomics. 2015; 33(7): 673–689. PubMed Abstract \| Publisher Full Text\n\nAugust GP, Caprio S, Fennoy I, et al.: Prevention and Treatment of Pediatric Obesity: An Endocrine Society Clinical Practice Guideline Based on Expert Opinion. J. Clin. Endocrinol. Metab. 2008; 93(12): 4576–4599. PubMed Abstract \| Publisher Full Text\n\nLambert M, Van Hulst A, O’Loughlin J, et al.: Cohort profile: the Quebec adipose and lifestyle investigation in youth cohort. Int. J. Epidemiol. 2012; 41(6): 1533–1544. PubMed Abstract \| Publisher Full Text\n\nMatzat U, Snijders CCP:The online measurement of ego centered online social networks.Welker M, Wenzel O, editors. Online-Forschung 2007: Grundlagen Und Fallstudien. Neue Schriften zur Online-Forschung:Herbert von Halem Verlag;2007; 274–294.\n\nBrunet J, Sabiston CM, O’Loughlin J, et al.: Perceived parental social support and moderate-to-vigorous physical activity in children at risk of obesity. Res. Q. Exerc. Sport. 2014; 85(2): 198–207. PubMed Abstract \| Publisher Full Text\n\nYbarra M, Barnett TA, Yu J, et al.: Personal Social Networks and Adiposity in Adolescents: A Feasibility Study. Child Obes. Print. 2021; 17(8): 542–550. Publisher Full Text\n\nde Onis M , Onyango AW, Borghi E, et al.: Development of a WHO growth reference for school-aged children and adolescents. Bull. World Health Organ. 2007; 85(9): 660–667. Publisher Full Text\n\nBurt R: Structural Holes and Good Ideas. Am. J. Sociol. 2004; 110: 349–399. Publisher Full Text\n\nMoody J, White DR: Structural Cohesion and Embeddedness: A Hierarchical Concept of Social Groups. Am. Sociol. Rev. 2003; 68(1): 103–127. Publisher Full Text\n\nLatora V, Marchiori M: Efficient Behavior of Small-World Networks. Phys. Rev. Lett. 2001; 87(19): 198701. Publisher Full Text\n\nMcPherson M, Smith-Lovin L, Cook JM: Birds of a Feather: Homophily in Social Networks. Annu. Rev. Sociol. 2001; 27(1): 415–444. Publisher Full Text\n\nHastie T, Tibshirani R, Friedman J: The Elements of Statistical Learning Data Mining, Inference, and Prediction. 2nd ed.New York, NY:Springer.\n\nde la Haye K , Robins G, Mohr P, et al.: Obesity-related behaviors in adolescent friendship networks. Soc Netw. 2010; 32(3): 161–167. Publisher Full Text" }	[ { "id": "150275", "date": "29 Sep 2022", "name": "Anjalika Nande", "expertise": [ "Reviewer Expertise infectious disease dynamics", "drug resistance", "networks", "evolutionary dynamics" ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this study, the authors explore whether heatmaps (produced using hierarchical clustering of variables) and consensus clustering can be used in tandem to better visualize and understand ego network data. They test this method on data from the QUALITY cohort that aims to study the influence of an adolescent’s social network on their obesity outcomes. Their method led to 4 stable clusters and managed to successfully identify important associations between variables that have been previously identified in the literature. Their methodology is available as an R package. Overall, the exploratory data analysis method studied here seems to be a useful way to understand ego centered network data and I only have a few comments that may help to strengthen the manuscript.\nMajor comments:\nI think this manuscript will benefit overall if more details are provided regarding the methods used to calculate the different alter and ego variables and the network measures. This will help the reader better interpret the results, and make the study more reproducible.\nMore information is needed about the alter and ego variables and the transformations that were used to get them in a format compatible with hierarchical clustering. Specifically, a brief description of each of the variables, and the methods used to obtain their summary statistic (in this case a measure of center) would be helpful. If possible, it might also be useful to include the general range of the variables prior to normalization. I think having a table in the Supplement with this information would suffice.\n\nIt would help if the normalized distributions of these variables were provided somewhere (maybe in the Supplement) to enable a better interpretation of the heatmap and clusters, and to provide more context to the statement in the second paragraph on page 8 : ‘However, upon closer inspection of the heatmap, this result may be due to the lack of variability in the distributions of the variables composing the cluster’. Related to this, at the beginning of the Results section I’d suggest adding a few words like: ‘For variable vector v of length n (where n is the number of ego networks)…’ to make it clearer that each variable is normalized between 0 and 1 across all the ego networks.\n\nIn the ‘Network measures’ paragraph on page 7, the authors mention the topological characteristics of the network that were computed. Along with the appropriate citations for these metrics, it would be helpful to also have a brief description of how they were calculated. This doesn’t have to be in the Main text; having it in a Supplementary Methods section also works.\n\nMinor comments:\nWhen I first tried to install the R code from Github following the instructions in the README file, install.packages(‘neatmaps’) gave a warning that the dependency ‘ConsensusClusterPlus’ was not available and so I couldn’t load the package after. Since ConsensusClusterPlus is a separate package that also needs to be installed for neatmaps to work, I would suggest adding this to the README.\n\nIt would help if the figure captions are more descriptive overall.\nFigure 3: Include what each axis corresponds to and briefly describe what the colors mean.\n\nFigure 4: Briefly explain what the colors mean and provide an explanation that supports the line ‘This evidence suggests that four relatively stable clusters are identified in the data’. Currently just looking at the figure and the caption isn’t enough to understand this statement.\n\nFigure 5: Describe what the subplot on the right-hand side is showing, currently the caption only mentions the one on the left.\n\nLine 9 page 6 ‘Depending on the goals of the EDA, consensus clustering may also be applied to the ego networks to identify clusters of similar networks’: I found this line confusing, can the authors clarify what they mean by identifying clusters of similar networks?\n\nIs the rationale for developing the new method (or application) clearly explained? Yes\n\nIs the description of the method technically sound? Yes\n\nAre sufficient details provided to allow replication of the method development and its use by others? Partly\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? Partly\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Yes", "responses": [] }, { "id": "240771", "date": "15 Feb 2024", "name": "Jaya Sreevalsan-Nair", "expertise": [ "Reviewer Expertise Data Visualization", "Visual Analytics", "Population Count Data Analysis", "Geospatial Data Analysis", "Analysis of Visualizations", "Machine Learning/Deep Learning." ], "suggestion": "Approved With Reservations", "report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nSummary: This study determines the completeness of visual inferences from an ego network visualization using a combination of heatmaps and consensus clustering.\nComments: 1. While I understand the need for evaluating the combination of visualization and analysis for the proposed study, it would be incorrect to say “Heatmaps are particularly convenient for depicting high-dimensional data ... their application in this setting has yet to be studied.” The reason why I say it is incorrect is that while the original data source is an ego network, the slice of data used in the heatmap is still a high-dimensional dataset. Composite visualizations combining views have also been formalized [Javed and Elmqvist 2012]. Hence, while this particular dataset may have some unique characteristics to test the combination of visualizations, the choice of visualizations itself is not unique or novel.\nJaved, W. and Elmqvist, N., 2012, February. Exploring the design space of composite visualization. In 2012 IEEE Pacific Visualization Symposium (pp. 1-8). IEEE.\n2. The paper is a bit difficult to read because of three points –\n(a) The consensus clustering is used for symmetric matrices (square matrices) in Monti et al. (and in general), however here, it is used for a rectangular matrix. Usually, for rectangular matrices in bioinformatics applications, biclustering is used.\n(b) The ego network of the QUALITY cohort is not explained initially, but when it is explained in the case study, we realize that the data is just high-dimensional data of the ego networks. This work has nothing to do with the ego network as such. The title “ego network exploration” is misleading and perhaps would be better with “comparison of ego networks”. Figure 1 is thus misleading.\n(c) What is the transformation of the ego network? Is it the reordering of rows and columns? This needs to be explicitly mentioned.\n3. I am assuming that Fig.3 is showing a subset of the 630x46 heatmap by choosing 35x41. Can this be clarified? Otherwise, it sounds like Fig.4 and later depicts a 35x41 dataset. How was the subset chosen?\n4. Following up on #2(a), it is still not clear how clusters are computed. Typically Euclidean distance is computed between objects/data items using their feature vectors and this distance metric is used for clustering. Maybe it will help if the actual procedure is written out for the case study. Are the matrices in Fig.4 630x630 or 630x46? It appears to be the former, but the reader should not have to speculate. After the speculation, the “Data Availability” section says it is of 35 participants. If that’s the case then, 35x46 is not a large dataset, which was the premise of this work. Please discuss these aspects.\n5. Are the ordering of the rows and columns the same for the 3 different outcomes in Fig 4?\n6. What is the resampling strategy used for consensus clustering, following Monti et al.?\nOverall, the writing of the paper can be improved by straightforward descriptions – e.g. (a) There are two heatmaps used here – a rectangular one of item x variable, and a square matrix of item x item (for consensus clustering). (b) The clustering of ego networks essentially means clustering of the participants of the cohort based on their ego networks. Just stating that simplifies the understanding of this paper as clustering is typically done for generating levels of detail in visualization.\n[I haven’t tested the code. I hope the issues pointed out by the previous reviewer are resolved.]\nMinor suggestions: 1. Please mention “dendrogram” in the caption of Fig.2. Please also say what the color bar stands for, in the caption (i.e. min-max normalized value). From the caption, it is not clear which variable suggests “smallness” and performance (e.g. hp could also imply performance). 2. In “Data Source”, please avoid calling #subjects (or #ego-networks) and #variables, both as variable n.\n\nIs the rationale for developing the new method (or application) clearly explained? Partly\n\nIs the description of the method technically sound? Partly\n\nAre sufficient details provided to allow replication of the method development and its use by others? Yes\n\nIf any results are presented, are all the source data underlying the results available to ensure full reproducibility? No source data required\n\nAre the conclusions about the method and its performance adequately supported by the findings presented in the article? Partly", "responses": [] } ]	1	https://f1000research.com/articles/11-771
https://f1000research.com/articles/11-770/v1	11 Jul 22	{ "type": "Software Tool Article", "title": "rspatialdata: a collection of data sources and tutorials on downloading and visualising spatial data using R", "authors": [ "Paula Moraga", "Laurie Baker" ], "abstract": "Spatial and spatio-temporal data are used in a wide range of fields including environmental, health and social disciplines. Several packages in the statistical software R have been recently developed as clients for various databases to meet the growing demands for easily accessible and reliable spatial data. While documentation on how to use many of these packages exist, there is an increasing need for a one stop repository for tutorials on this information. In this paper, we present rspatialdata a website that provides a collection of data sources and tutorials on downloading and visualising spatial data using R. The website includes a wide range of datasets including administrative boundaries of countries, Open Street Map data, population, temperature, vegetation, air pollution, and malaria data. The goal of the website is to equip researchers and communities with the tools to engage in spatial data analysis and visualisation so that they can address important local issues, such as estimating air pollution, quantifying disease burdens, and evaluating and monitoring the United Nation’s sustainable development goals.", "keywords": [ "Spatial data", "open data", "visualization", "maps", "sustainable development goals", "R" ], "content": "Introduction\n\nSpatial data plays a crucial role in a wide range of disciplines, such as environment, health, agriculture, economy and society, and can help governments, companies and citizens improve decision-making. A key example is the use of spatial data by statistical offices worldwide to improve the evaluation and monitoring of the United Nations’ Sustainable Development Goals (SDGs) including those related to health, poverty, inequality, climate and the environment.1\n\nSpatial data are critical in determining the future of endangered and threatened species,2 assessing current and future air quality3 and its effect on population health, and for revealing health inequalities and the early warning of infectious disease outbreaks.4 For example, mapping and analysis of spatial data are critical in the development of management plans to ensure the efficient use of natural resources such as land and water so that the benefits of these resources can be enjoyed by future generations.5 Many of these issues do not occur in isolation. Tackling the SDGs requires the integration and combination of data from different sources including social, economic and environmental data. Location often provides the link between these otherwise disparate datasets. High-resolution spatial data is crucial to tailoring management plans to local situations.\n\nThe way we monitor change is being rapidly transformed by advances in technology, computing, and data science techniques. Spatial and spatio-temporal data are becoming increasingly common due to advances in both data collection and management. Novel open data sources such as satellite imagery, remote sensing, and Global Positioning System (GPS) data can be collected in large quantities at high spatial and temporal resolutions, at relatively low cost. At the same time, administrative spatial data are becoming increasingly available in open formats. These data are obtained by registries, surveys, and monitoring stations as well as through community-contributed data platforms. Despite a wealth of large and diverse spatial data sources, spatial data may still be hard to find, difficult to use, or not readily accessible. These hurdles limit the re-use of data and their potential impact. These challenges have been recognised for all scientific data, including spatial, and have led to the development of the Findable, Accessible, Interoperable and Reusable (FAIR) guiding principles for scientific data management and stewardship.6 To maximise their value, data should be FAIR. The first step in (re)using the data is to find them. Therefore, data files should also include descriptive metadata that makes them easily findable for both humans and computers. Once the data are found, users also need to know how data can be accessed, possibly including authentication and authorisation. Data also needs to be interoperable so they can be integrated with other data and interoperate with applications or workflows for analysis, storage and processing. Finally, data should be reusable and to achieve this, they should be well-described so that they can be used and extended in different settings.\n\nR7 is a powerful language for statistical programming that incorporates a wide range of packages that can be used for data access, manipulation, analysis and visualisation.8,9 Moreover, R includes several packages that act as clients for various spatial databases and repositories to meet the growing demands for easily accessible and reliable spatial and spatio-temporal data. While documentation and many open source repositories on how to use these packages to access these data sources exist, there is an increasing need for a one stop repository for information about these data sources and tutorials on how to access them using these packages.\n\nHere, we present rspatialdata, a website that presents a collection of reproducible tutorials on how to download, manipulate and visualize a wide range of spatial data including administrative boundaries, population density, climate and health data using the statistical software R. The website makes it easier for individuals to explore, access and use a range of spatial data facilitating the conversion of data into tangible impacts. rspatialdata makes these diverse data more Findable and Accessible by grouping instructions together in one place and promoting them to the R community. Interoperability and Reuse are made easier by demonstrating how to read and manipulate the data in a common analysis system with tutorials that promote the reuse of data and analyses.\n\n\nMethods\n\nThe tutorials presented in rspatialdata have been created using the open-source R Project for Statistical Computing (RRID:SCR_001905)7 and a number of R packages that allow us to download spatial data corresponding to specific geographic regions and periods of time, as well as to manipulate and visualize the data. Here, we provide a description on how to install the statistical software R and R packages. Then, we show an example on how to download and visualize one of the datasets presented in the website, namely, maximum temperature data. The complete code for all the tutorials can be found at the rspatialdata website, and a summary of the datasets and associated R packages included in the website are summarized in Table 1. The code is available from GitHub and is archived with Zenodo.87\n\nR7 is a free, open source, software environment for statistical computing and graphics with many useful packages for importing and manipulating data, statistical modeling, and visualization. R can be downloaded and installed from the Comprehensive R Archive Network (CRAN) (RRID:SCR_003005). R packages can be installed from CRAN with the function install.packages() passing the name of the package as first argument in quotes. Then, to use the package, the package needs to be loaded with the function library(). For example, we can install and load the visualization package ggplot2 by typing install.packages(\"ggplot2\") and library(ggplot2).\n\nThe WorldClim (RRID:SCR_010244)10 database contains global weather and climate data for historical and future conditions at high spatial resolution. These datasets can be easily downloaded with the R package raster,11 which implements several functions for reading, writing, manipulating, analyzing and modeling of spatial data. To use the raster package, we first need to install it and load it. Then, to download data, we can use the getData() function of the raster package by specifying several arguments about the dataset we wish to obtain. For example, to download global maximum temperature, we specify the database name (e.g., \"worldclim\"), the variable we want to download (e.g., \"tmax\"), and the spatial resolution in minutes of a degree as follows.\n\nThe downloaded object contains 12 files that correspond to the maximum temperature observed each month. We can manipulate the downloaded object to obtain temperature values for a specific month or average temperature spanning several months, and use other R packages to model and visualize the data.\n\n\nOperation\n\nThe software R and RStudio are available for Linux, Mac, and Windows operating systems. It is recommended running these tutorials on a recent version of R (at least R version 4.1.1) and RStudio (at least RStudio version 2021.09.0). R can be downloaded from CRAN, the comprehensive R archive network (https://cran.r-project.org/). CRAN is composed of a set of mirror servers distributed around the world and is used to distribute R and R packages. RStudio is an integrated development environment, or IDE, for R programming. RStudio can be downloaded and installed from http://www.rstudio.com/download. It is recommended updating both R and RStudio at least once a year to keep up to date with the most recent changes.\n\n\nUse cases\n\nThe rspatialdata website provides a collection of data sources and tutorials on how to download and visualize spatial data, including administrative boundaries, population, elevation, climatic variables, and health data. These data come from different sources. For example, remote sensing data are acquired by sensors that are not in contact with the target of investigation and can be done, for example, using satellites orbiting the Earth. Remote sensing is used to measure everything from land cover (e.g., water, habitat), environmental phenomena (e.g., elevation, water and sea temperature), to our human footprint (e.g., night light maps). More precise information on a range of environmental and climatic variables such as temperature, rainfall and air pollution can be obtained using monitoring stations placed at specific places that provide ground measurements of these variables during different periods of time. Surveys are also useful to obtain information about health, economy and social characteristics of the population at the local scale. Here, we describe the data sources included in the website, as well as the R packages that allow us to download the data. We also give examples of where these data can be used to solve problems in different disciplines such as health, ecology and the environment.\n\nAdministrative boundaries are an essential component for making maps and define the spatial extent needed for electoral, planning and statistical studies. These boundaries, which often guide the spatial scale at which data is collected, offer important context to a wide-range of issues. geoBoundaries12 is an open license resource database of political administrative boundaries. The R package rgeoboundaries13 is an R client for the geoBoundaries application programming interface (API) that allows us to download administrative boundaries of countries at different administrative levels.\n\nThis package has been used as a visualization tool for the study of many different real-world problems, such as mapping coronavirus-19 presence in Vietnam,14 understanding the impact of Global Environment Facility Projects in Uganda15 and the influence of travel time to health facilities on stillbirths in Nigeria.16\n\nThe rspatialdata tutorial includes an example of how to retrieve the administrative boundaries of single and multiple countries at different administrative boundary levels. It also covers how to download and visualize these data using the sf17 and leaflet18 packages.\n\nKnowing population sizes and their spatial distributions is crucial for many critical decisions from improving access to health, transportation and energy, to planning and building more resilient and sustainable cities. WorldPop19 aims to provide an open access archive of spatial demographic datasets with a focus on low and middle income countries (LMICs) to support development, disaster response and health applications.\n\nPopulation data from WorldPop has been used extensively to map health conditions such as cancer,20 child growth failure,21 HIV prevalence,22 and the burden of cholera23 in Africa. It has also been used to map local variation in educational attainment in Africa,24 to evaluate the reduction of tree cover in West African Woodlands25 and to assess clean air in the context of the SDGs.26\n\nThe WorldPop Open Population Repository provides access to high-resolution population estimates for individual countries and these data can be obtained with the R package wopr.27 The rspatialdata tutorial shows examples on how to use wopr to download population data for different countries and administrative levels.\n\nOSM28 is a collaborative project to create a free editable map of the world. OSM is built by a community of mappers that contribute and maintain global data about roads, trails, cafés, railway stations, and more. OSM data can be used in many ways. For example, as a basemap to put other data into context, for routing or navigation, and for planning or logistics for humanitarian groups, utilities and governments. OSM data have been used in a wide range of applications including flood inundation modeling,29 air pollution exposure,30 assessment of socio-economic factors and property prices,31 and for the study of crime and place.32\n\nThe package osmdata33 allows us to easily import OSM data in R. The rspatialdata tutorial includes an example of how to retrieve OSM data using the osmdata by creating a bounding box and a query and how to visualized the data with ggplot2, ggmap34 and leaflet.18\n\nElevation data are important in many different applications. For instance, for environmental problems, elevation data have been used as a tool to study the land cover change over the years, in particular, the evolution of European forest cover.35 As another example, researchers also have been using elevation data as a complementary source of information in the analysis of species connectivity through genetic structure.36,37\n\nFor retrieving elevation data from many different regions, one may choose to work with the the elevatr package.38 elevatr provides access to elevation data from several web services including the Amazon Web Services Terrain Tiles,39 the Open Topography Global Datasets API,40 and the USGS Elevation Point Query Service.41\n\nThe rspatialdata tutorial includes an example of how to retrieve and visualize point elevation data for the USA and raster elevation data from a digital elevation model (DEM) for global elevation data.\n\nWorldClim10 is a database that provides high spatial resolution global weather and climate data for historical and future conditions. For example, it provides monthly climate data for minimum, mean, and maximum temperature, precipitation, solar radiation, wind speed, water vapor pressure, and for total precipitation.\n\nThese data may be applicable in many different areas. For environmental problems, it has been used for the study of the global tree restoration potential,42 the understanding of temperature profile in forest regions,43 and the monitoring of drought in South Asia.44 In ecology, to understand geographic distribution of sloths in Costa Rica.2 In health and disease-control related problems, these data have been used, for example, in the study of the levels of arsenic in groundwater,45 the prediction of lymphatic filariasis prevalence in sub-Saharan Africa,46 and the loss of biodiversity on Earth due to the amphibian chytridiomycosis panzootic disease.47\n\nThe package raster11 allows us to easily download the WorldClim data as well as to manipulate and analyze spatial datasets. The rspatialdata tutorial includes an example of how to retrieve maximum temperature data from the WorldClim database and visualize the monthly maximum and mean monthly temperature and other bioclimatic variables over time using ggplot2 and the sf package.17\n\nThe NASA Prediction Of Worldwide Energy Resources (POWER) Project48 provides meteorology, surface solar energy and climatology data for support of renewable energy, building energy efficiency and agricultural needs. Data retrieved from the NASA POWER Project have been used in a few different applications. For example, POWER data have been used in the study of the potential utilization of wind electric pumping systems for water distribution in Cameroon,49 in the analysis of photovoltaic systems usage in China50 and in the study of Dunaliella salina (a type of green micro-algae) cultivation.51\n\nnasapower52 aims to make it quick and easy to automate downloading NASA-POWER data in R. In rspatialdata, we show how to use this package to download rainfall and humidity.\n\nVegetation data are used in a wide variety of applications ranging from environmental applications, such as the rice crop monitoring in Europe,53 to health and disease-control applications, such as malaria transmission dynamics in an indigenous province in Panama.54\n\nVegetation data are captured using Moderate Resolution Imaging Spectroradiometer (MODIS), an instrument onboard the Terra and Aqua NASA scientific research satellites. MODIS captures data in 36 spectral bands in three spatial resolutions across the surface of the earth. Data products derived from these observations include features of the atmosphere, land, cryosphere, and ocean, made available at different frequencies and spatial resolutions. Each data product contains multiple product layers, including original MODIS layers, quality layers and spectral indexes, produced at different intervals and at different spatial resolutions. User guides on each of the product areas are available, which provide in-depth explanations on them.\n\nThe rspatialdata tutorial shows how to use the R package MODIStsp,55 which acts as a client for downloading time series and raster images derived from MODIS Land Product data. Specifically, it shows how to download MODIS Vegetation Index Products (NDVI and EVI)56 and the MODIS Land Cover Products.57\n\nAir pollution data can be of interest for many different agents, from the government to the general population. In this sense, many different studies have been conducted regarding how the UK and other countries have been suffering from different types of pollutants—for instance, on how wood-burning has impacted the PM10 levels in London,58 or how the level of air pollution has a direct impact on the population’s health,3 or even how people from different socioeconomic groups may be exposed to different levels of air pollution depending on their commute in London.59\n\nUK Air is a UK air quality database provided by the Department for Environment Food & Rural Affairs.60 The database provides daily information about the level of pollution for different pollutants (e.g., ozone, carbon monoxide, PM2.5) across the United Kingdom and its territories. Although there are many different ways to retrieve data from this database, one convenient option is using the openair61 R package.\n\nThe openair package provides a set of functions to import and work with these datasets, which are documented in the openair's manual.62 The rspatialdata tutorial includes an example of how to retrieve and visualize data from a specific monitoring network named Automatic Urban and Rural Network (AURN).\n\nThe Demographic and Health Surveys (DHS) Program63 collects, analyzes, and disseminates country-wide subnational level data on population, health, nutrition and HIV. The objective of the DHS Program is to improve and institutionalize the collection and use of data by developing countries for program monitoring and evaluation and for policy making. The R package rdhs64 provides a wrapper to the DHS program API, and can be used to identify particular datasets and download them in R via the DHS API. Examples of issues that have been investigated using DHS data include household smoke-exposure risks associated with cooking fuels and cooking places in Tanzania,65 determinants of unmet need for family planning and implications for women’s health in Gambia & Mozambique,66 and household access to improved drinking water sources and toilet facilities in Ethiopia.67\n\nThe rspatialdata tutorial includes different examples of options on how to retrieve datasets and DHS surveys for an analysis through the DHS API and DHS website from R. And how to search for a specific DHS survey using tag words demonstrating how to extract surveys on Malaria in Rwanda and Tanzania as a case study.\n\nThe Malaria Atlas Project (MAP)68 aims to better understand the global landscape of malaria risk, how this is changing, and the impact of malaria interventions to support malaria intervention and eradication efforts. As part of its work, MAP assembles an extensive collection of malaria data, including parasite rate data (Plasmodium falciparum and Plasmodium vivax), vector occurrence, and satellite images capturing conditions that influence malaria transmission. malariaAtlas69 is an R package to open-access malaria data hosted by MAP and can be used to download all publicly available parasite rate survey points, mosquito occurrence points and raster surfaces from the MAP servers as well as utility functions for plotting the downloaded data. Data provided by malariaAtlas can be used to explore the spatial and spatio-temporal patterns of malaria risk as well as to feed into spatial models of the risk of malaria. Several studies have used MAP data for different purposes, including mapping the global endemicity and clinical burden malaria,70 understand the associated patterns of insecticide resistance in field populations of malaria vectors across Africa,71 and assess the population coverage of artemisinin-based combination treatment and Plasmodium falciparum infection in Africa.72\n\nThe rspatialdata tutorial includes examples of how to retrieve and visualize malaria data from the malariaAtlas package including parasite rate (PR) survey data, vector occurrence data, and rasters of modelled malaria research outputs.\n\nThe information of observed species play an import role in ecological studies, which motivates the existence of different repositories containing these type of data. Examples include GBIF - Global Biodiversity Information Facility (RRID:SCR_005904),73 Biodiversity Information Serving Our Nation (BISON),74 eBird,75 and VertNet.76 Most of these repositories allow researchers to retrieve data using different methods. In R, the aforementioned platforms can be accessed through the rgbif,77 rbison,78 rebird,79 and rvertnet80 packages, respectively. However, in order to integrate all these datasets and interact with them using just one tool, one could choose to work with the spocc package.81 As an example, and aiming to model sloths occurrence in Costa Rica, spocc was used to retrieve relevant data from GBIF.82 Other case studies may include modeling migratory movements of birds83 or estimating population size based on species occurrence.84\n\nThe rspatialdata tutorial includes an example of how to retrieve and visualize species occurrence data by creating a query for a species latin name using the spocc package.\n\n\nDiscussion\n\nOpen and reliable data are crucial for solving global challenges and monitoring the UN Sustainable Development Goals by 2030, including those for improving health, reducing inequalities, and protecting the environment. Accessible spatial data in particular are key to understanding diverse questions ranging from disease spread to climatic trends and necessary for evaluating the impact of interventions and policy decisions.\n\nIn this paper, we present rspatialdata, a website containing a collection of data sources and tutorials on downloading and visualising spatial data using the statistical software R. The website represents an important step towards helping users find, access and visualize spatial data. As a one-stop repository for tutorials on accessing spatial data, we aim to provide an overview for users on what spatial data is available and how it can be accessed from R. We use motivating examples in the tutorials to illustrate how a variety of spatial data can be used to inform evidence-based decision-making in a wide range of fields. The rspatialdata website is a useful resource for individuals working with problems that require spatial data analysis and visualisation, such as estimating air pollution, quantifying disease burdens, predicting species occurrences, and evaluating and monitoring the UN Sustainable Development Goals.\n\nAn ongoing challenge in many disciplines that use spatial data is a lack of data in some locations and periods of time, as well as a lack of disaggregated data corresponding to age groups, genders and other factors. Spatial data are often aggregated at the scale of administrative units rather than locally relevant scales. These limitations make it difficult to compare processes over time and to evaluate outcomes for different population groups. While modeling techniques can be used to fill these gaps,85,86 it is important to continue supporting countries to generate and access data that will help inform better decision-making globally.\n\nWe have chosen to write tutorials for spatial datasets that are important for decision-making in a wide range of fields such as health, climate, environment and ecology. While there may be different packages that do the same as the packages included in the website, rspatialdata tries to present the packages that are easiest to install and use, and includes other additional packages in the reference sections so users can explore additional functionalities and examples these packages provide. The website will be updated by including noteworthy packages to retrieve spatial data as they are discovered, and tutorials of existing packages will be updated if the code to use them changes or there are new notable functions to include. Also, in order to encourage the community to contribute, the website provides guidelines for contribution. The rspatialdata website is not comprehensive and it does not contain all available datasets. Nevertheless, it can provide a useful resource to get users started and a stimulus and location for others to contribute.\n\nWe expect the quantity and variety of spatial data provided by novel data streams such as satellite imagery, remote sensing, and GPS tracking to only increase in the future. The rspatialdata website will be regularly updated to meet the growing demands to access spatial data by the R community and to include new R packages and data sources as they are developed and released. By promoting the reuse and sharing of spatial data and spatial analyses, the rspatialdata website contributes to community-building and sharing of best practices on working with spatial data.\n\n\nData availability\n\nTable 2 contains the databases included in the rspatialdata website.\n\n\nSoftware availability\n\nSoftware available from: https://rspatialdata.github.io/.\n\nSource code available from: https://github.com/rspatialdata/rspatialdata.github.io.\n\nArchived source code at time of publication: https://doi.org/10.5281/zenodo.6779351.87\n\nLicense: MIT", "appendix": "References\n\nAssembly, General: Resolution adopted by the general assembly on 19 september 2016. Technical report, A/RES/71/1, 3 October 2016 (The New York Declaration).2015.\n\nMoraga P: Species Distribution Modeling using Spatial Point Processes: a Case Study of Sloth Occurrence in Costa Rica. R J. 2021; 12(2): 293–310. Publisher Full Text\n\nHeal MR, Kumar P, Harrison RM: Particles, air quality, policy and health. Chem. Soc. Rev. 2012; 41(19): 6606–6630. Publisher Full Text\n\nMoraga P, Dorigatti I, Kamvar ZN, et al.: epiflows: an R package for risk assessment of travel-related spread of disease. F1000Res. 2018; 7: 1374. Publisher Full Text\n\nLiping C, Yujun S, Saeed S: Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques - A case study of a hilly area, Jiangle, China. PLoS One. 2018; 13(7): e0200493. PubMed Abstract \| Publisher Full Text\n\nWilkinson MD, Dumontier M, Aalbersberg IJJ, et al.: The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. March 2016; 3(1): 160018. 2052-4463. Number: 1 Publisher: Nature Publishing Group. PubMed Abstract \| Publisher Full Text Reference Source\n\nR Core Team: R: A Language and Environment for Statistical Computing. Vienna, Austria:R Foundation for Statistical Computing;2018.Reference Source\n\nMoraga P: Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny. CRC Press;2019.\n\nMoraga P: SpatialEpiApp: A Shiny Web Application for the analysis of Spatial and Spatio-Temporal Disease Data. Spatial and Spatio-temporal Epidemiology. 2017; 23: 47–57. PubMed Abstract \| Publisher Full Text\n\nWorldClim: Global climate and weather data.Reference Source\n\nRobert J: Hijmans. raster: Geographic Data Analysis and Modeling. 2020. R package version 3.4-5.Reference Source\n\nRunfola D, Anderson A, Baier H, et al.: geoboundaries: A global database of political administrative boundaries. PLoS One. 04 2020; 15(4): 1–9. PubMed Abstract \| Publisher Full Text\n\nDicko A: rgeoboundaries: A Client to geoBoundaries, A Political Administrative Boundaries Dataset.2020. R package version 0.0.0.9000.Reference Source\n\nHuong NQ, Nga NTT, Van Long N, et al.: Coronavirus testing indicates transmission risk increases along wildlife supply chains for human consumption in viet nam, 2013-2014. PLoS One. 2020; 15(8): e0237129. PubMed Abstract \| Publisher Full Text\n\nRunfola D, Batra G, Anand A, et al.: Exploring the socioeconomic co-benefits of global environment facility projects in uganda using a quasi-experimental geospatial interpolation (QGI) approach. Sustainability. 2020; 12(8): 3225. Publisher Full Text\n\nWariri O, Onuwabuchi E, Alhassan JAK, et al.: The influence of travel time to health facilities on stillbirths: A geospatial case-control analysis of facility-based data in gombe, nigeria. PLoS One. 2021; 16(1): e0245297. PubMed Abstract \| Publisher Full Text\n\nPebesma E: Simple Features for R: Standardized Support for Spatial Vector Data. R J. 2018; 10(1): 439–446. Publisher Full Text\n\nCheng J, Karambelkar B, Xie Y; leaflet: Create Interactive Web Maps with the JavaScript ‘Leaflet’ Library. 2022. R package version 2.1.0.Reference Source\n\nWorldPop (School of Geography and Environmental Science, University of Southampton). 2021.Reference Source\n\nMoraga P: Small area disease risk estimation and visualization using r. R J. 2018; 10: 495–506. Publisher Full Text\n\nOsgood-Zimmerman A, Millear AI, Stubbs RW, et al.: Mapping child growth failure in africa between 2000 and 2015. Nature. 2018; 555(7694): 41–47. PubMed Abstract \| Publisher Full Text\n\nDwyer-Lindgren L, Cork MA, Sligar A, et al.: Mapping hiv prevalence in sub-saharan africa between 2000 and 2017. Nature. 2019; 570(7760): 189–193. PubMed Abstract \| Publisher Full Text\n\nLessler J, Moore SM, Luquero FJ, et al.: Mapping the burden of cholera in sub-saharan africa and implications for control: an analysis of data across geographical scales. Lancet. 2018; 391(10133): 1908–1915. PubMed Abstract \| Publisher Full Text\n\nGraetz N, Friedman J, Osgood-Zimmerman A, et al.: Mapping local variation in educational attainment across africa. Nature. 2018; 555(7694): 48–53. PubMed Abstract \| Publisher Full Text\n\nBrandt M, Rasmussen K, Hiernaux P, et al.: Reduction of tree cover in west african woodlands and promotion in semi-arid farmlands. Nat. Geosci. 2018; 11(5): 328–333. PubMed Abstract \| Publisher Full Text\n\nRafaj P, Kiesewetter G, Gül T, et al.: Outlook for clean air in the context of sustainable development goals. Glob. Environ. Chang. 2018; 53: 1–11. Publisher Full Text\n\nLeasure DR, Bondarenko M, Darin E, et al.: wopr: An R package to query the WorldPop Open Population Repository, version 0.4.5. 2020.Reference Source\n\nOpenStreetMap contributors: Planet dump.2017.Reference SourceReference Source.\n\nHawker L, Rougier J, Neal J, et al.: Implications of simulating global digital elevation models for flood inundation studies. Water Resour. Res. 2018; 54(10): 7910–7928. Publisher Full Text\n\nRamacher MOP, Karl M: Integrating modes of transport in a dynamic modelling approach to evaluate population exposure to ambient no2 and pm2. 5 pollution in urban areas. Int. J. Environ. Res. Public Health. 2020; 17(6): 2099. PubMed Abstract \| Publisher Full Text\n\nDupré D: Urban and socio-economic correlates of property prices in dublin’s area. 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA). pages 556–562. IEEE. 2020.\n\nLangton S, Solymosi R: Open street map for crime and place.2020.\n\nPadgham M, Rudis B, Lovelace R, et al.: osmdata. J. Open Source Softw. jun 2017; 2(14). Publisher Full Text\n\nKahle D, Wickham H: ggmap: Spatial visualization with ggplot2. R J. 2013; 5(1): 144–161. Publisher Full Text Reference Source\n\nZanon M, Davis BAS, Marquer L, et al.: European forest cover during the past 12,000 years: a palynological reconstruction based on modern analogs and remote sensing. Front. Plant Sci. 2018; 9: 253. PubMed Abstract \| Publisher Full Text\n\nO’Connell KA, Mulder KP, Maldonado J, et al.: Sampling related individuals within ponds biases estimates of population structure in a pond-breeding amphibian. Ecol. Evol. 2019; 9(6): 3620–3636. PubMed Abstract \| Publisher Full Text\n\nMulder KP, Cortes-Rodriguez N, Campbell EH, et al.: North-facing slopes and elevation shape asymmetric genetic structure in the range-restricted salamander plethodon shenandoah. Ecol. Evol. 2019; 9(9): 5094–5105. PubMed Abstract \| Publisher Full Text\n\nHollister J, Shah T, Robitaille AL, et al.: elevatr: Access Elevation Data from Various APIs. 2020. R package version 0.3.1. Publisher Full Text Reference Source\n\nRegistry of Open Data on AWS: Terrain Tiles.Reference Source\n\nOpen Topography: Open Topography API.Reference Source\n\nUnited States Geological Survey: The National Map.2017.Reference Source\n\nBastin J-F, Finegold Y, Garcia C, et al.: The global tree restoration potential. Science. 2019; 365(6448): 76–79. Publisher Full Text\n\nDe Frenne P, Zellweger F, Rodriguez-Sanchez F, et al.: Global buffering of temperatures under forest canopies. Nat. Ecol. Evol. 2019; 3(5): 744–749. PubMed Abstract \| Publisher Full Text\n\nAadhar S, Mishra V: High-resolution near real-time drought monitoring in south asia. Scientific Data. 2017; 4(1): 1–14. Publisher Full Text\n\nPodgorski J, Berg M: Global threat of arsenic in groundwater. Science. 2020; 368(6493): 845–850. PubMed Abstract \| Publisher Full Text\n\nMoraga P, Cano J, Baggaley RF, et al.: Modelling the distribution and transmission intensity of lymphatic filariasis in sub-saharan africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling. Parasit. Vectors. 2015; 8(1): 560. PubMed Abstract \| Publisher Full Text\n\nScheele BC, Pasmans F, Skerratt LF, et al.: Amphibian fungal panzootic causes catastrophic and ongoing loss of biodiversity. Science. 2019; 363(6434): 1459–1463. PubMed Abstract \| Publisher Full Text\n\nNASA: The POWER Project.Reference Source\n\nKidmo DK, Bogno B, Deli K, et al.: Economic assessment of wecs for water pumping systems in the north region of cameroon. Renew. Energy Environ. Sustain. 2021; 6: 6. Publisher Full Text\n\nLiang J, Gao X:Assessing the regional grid-parity potential of utility-scale photovoltaic in china. IOP Conference Series: Earth and Environmental Science. IOP Publishing;2020; volume 512. : page 012022.\n\nBorovkov AB, Gudvilovich IN, Avsiyan AL: Scale-up of dunaliella salina cultivation: from strain selection to open ponds. J. Appl. Phycol. 2020; 32(3): 1545–1558. Publisher Full Text\n\nSparks A: nasapower: NASA-POWER Data from R. 2020. R package version 3.0.1.Reference Source\n\nBusetto L, Casteleyn S, Granell C, et al.: Downstream services for rice crop monitoring in europe: From regional to local scale. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2017; 10(12): 5423–5441. Publisher Full Text\n\nHurtado LA, Calzada JE, Rigg CA, et al.: Climatic fluctuations and malaria transmission dynamics, prior to elimination, in guna yala, república de panamá. Malar. J. 2018; 17(1): 1–12. Publisher Full Text\n\nBusetto L, Ranghetti L: Modistsp: an r package for preprocessing of modis land products time series. Comput. Geosci. 2016; 97: 40–48. 0098-3004. Publisher Full Text Reference Source\n\nDidan K: MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V006. NASA EOSDIS Land Processes DAAC.2015. Publisher Full Text\n\nFriedl M, Sulla-Menashe D: MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V006. NASA EOSDIS Land Processes DAAC.Publisher Full Text\n\nFuller GW, Tremper AH, Baker TD: Karl Espen Yttri, and David Butterfield. Contribution of wood burning to pm10 in london. Atmos. Environ. 2014; 87: 87–94. Publisher Full Text\n\nRivas I, Kumar P, Hagen-Zanker A: Exposure to air pollutants during commuting in london: are there inequalities among different socio-economic groups? Environ. Int. 2017; 101: 143–157. PubMed Abstract \| Publisher Full Text\n\nUK-Air: UK Department for Environment, Food & Rural Affairs.Reference Source.\n\nCarslaw DC, Ropkins K: openair—An R package for air quality data analysis. Environ. Model Softw. 2012; 27-28 (0): 52–61. Publisher Full Text\n\nCarslaw DC: The openair book—Tools for air quality data analysis. 2020.Reference Source\n\nICF: The DHS Program Spatial Data Repository. Funded by USAID. Reference Source\n\nWatson OJ, FitzJohn R, Eaton JW: rdhs: an r package to interact with the demographic and health surveys (dhs) program datasets. Wellcome Open Res. 2019; 4: 103. Publisher Full Text Reference Source\n\nAhamad MG, Tanin F, Shrestha N: Household smoke-exposure risks associated with cooking fuels and cooking places in tanzania: A cross-sectional analysis of demographic and health survey data. Int. J. Environ. Res. Public Health. 2021; 18(5): 2534. PubMed Abstract \| Publisher Full Text\n\nYaya S, Idriss-Wheeler D, Uthman OA, et al.: Determinants of unmet need for family planning in gambia & mozambique: implications for women’s health. BMC Womens Health. 2021; 21: 123. PubMed Abstract \| Publisher Full Text\n\nAndualem Z, Dagne H, Azene ZN, et al.: Households access to improved drinking water sources and toilet facilities in ethiopia: a multilevel analysis based on 2016 ethiopian demographic and health survey. BMJ Open. 2021; 11: e042071. PubMed Abstract \| Publisher Full Text\n\nHay SI, Snow RW: The malaria atlas project: Developing global maps of malaria risk. PLoS Med. 12 2006; 3(12): e473–e475. PubMed Abstract \| Publisher Full Text\n\nPfeffer D, Lucas T, May D, et al.: malariaatlas: an r interface to global malariometric data hosted by the malaria atlas project. Malar. J. 2018; 17(1): 352. PubMed Abstract \| Publisher Full Text\n\nBattle KE, Lucas TCD, Nguyen M, et al.: Mapping the global endemicity and clinical burden of plasmodium vivax, 2000–17: a spatial and temporal modelling study. Lancet. 2019; 394 (10195): 332–343. 0140–6736. PubMed Abstract \| Publisher Full Text\n\nHancock PA, Wiebe A, Gleave KA, et al.: Associated patterns of insecticide resistance in field populations of malaria vectors across africa. Proc. Natl. Acad. Sci. 2018; 115 (23): 5938–5943. 0027-8424. PubMed Abstract \| Publisher Full Text\n\nBennett A, Bisanzio D, Yukich JO, et al.: Population coverage of artemisinin-based combination treatment in children younger than 5 years with fever and plasmodium falciparum infection in africa, 2003-2015: a modelling study using data from national surveys. Lancet Glob. Health. 2017; 5 (4): e418–e427. 2214-109X. PubMed Abstract \| Publisher Full Text\n\nGlobal Biodiversity Information Facility: Global Biodiversity Information Facility (GBIF).2021.Reference Source\n\nBiodiversity Information Serving Our Nation: Biodiversity Information Serving Our Nation (BISON).2021.Reference Source\n\nCornell Lab of Ornithology: eBird.2021.Reference Source\n\nVertNet: VertNet.2021.Reference Source\n\nChamberlain S, Oldoni D, Barve V, et al.: rgbif: Interface to the Global’Biodiversity’ Information Facility API.2021.Reference Source\n\nChamberlain S: rbison: Interface to the ‘USGS”BISON’ API.2020.Reference Source\n\nMaia R, Chamberlain S, Teucher A, et al.: rebird: R Client for the eBird Database of Bird Observations.2021.Reference Source\n\nChamberlain S, Ray C, Barve V: rvertnet: Search ‘Vertnet’, a ‘Database’ of Vertebrate Specimen Records.2021.Reference Source\n\nChamberlain S, Ram K, Hart T: spocc: Interface to Species Occurrence Data Sources.2021.Reference Source\n\nMoraga P: Species distribution modeling using spatial point processes: a case study of sloth occurrence in costa rica. R J. 2020; 12(2): 311–320.\n\nWalker J, Taylor P: Using ebird data to model population change of migratory bird species. Avian Conserv. Ecol. 2017; 12(1). Publisher Full Text\n\nDorazio RM, Royle JA: Estimating size and composition of biological communities by modeling the occurrence of species. J. Am. Stat. Assoc. 2005; 100(470): 389–398. Publisher Full Text\n\nMoraga P, Cramb SM, Mengersen KL, et al.: A geostatistical model for combined analysis of point-level and area-level data using inla and spde. Spatial Statistics. 2017; 21: 27–41. Publisher Full Text\n\nMoraga P, Ozonoff A: Model-based imputation of missing data from the 122 Cities Mortality Reporting System (122 CMRS). Stoch. Env. Res. Risk A. 2015; 29: 1499–1507. Publisher Full Text\n\nMoraga P: First release (v1.0.0) rspatialdata/rspatialdata.github.io. [Software].2022. Publisher Full Text" }	[ { "id": "144385", "date": "29 Jul 2022", "name": "Emmanuel Olamijuwon", "expertise": [ "Reviewer Expertise Demography and Social Statistics", "Global Health", "Africa" ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper describes a web platform (rspatialdata) that makes diverse population, health, climate and environmental data more Findable and Accessible. The website also provides instructions for accessing, exploring, and reusing (visualising) the datasets. As the authors note, high-resolution spatial data is crucial to tailoring management plans and service delivery to local situations. By promoting the reuse and sharing of spatial data and spatial analyses, the rspatialdata website contributes to community-building and sharing of best practices for working with spatial data.\nI agree with the authors that there's an increasing need for a central repository for information about spatial data sources and tutorials on their use. The tutorials are purposefully designed and well written in such a way that they will be easy to understand by anyone with basic r-programming experience. The rspatialdata website is also user-friendly, making it easy for anyone with an internet-enabled device to access them. In recognition of the ever-increasing variety of spatial data provided by novel data streams such as satellite imagery, remote sensing, and GPS tracking, the authors have also included a dedicated section for inviting community contributions, which is commendable.\nI have included a few minor comments below with the hopes that they would further strengthen the work.\nTable 1: I suggest changing Demographic and health survey to demographics and health (data focus).\n\nTable 2 is technically a repetition of Table 1.\n\nConsidering the article's peculiar focus on FAIR principles. It will be important to include a tutorial that demonstrates the interoperability of the datasets. That is, linking demographics and health data to Administrative boundaries or Humidity and/or Population data. I believe this would be a more substantial contribution of this article and website.\n\nPlease include some spatial tutorials for the DHS module/page (https://rspatialdata.github.io/dhs-data.html).\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [] }, { "id": "144387", "date": "09 Aug 2022", "name": "Natalia da Silva", "expertise": [ "Reviewer Expertise I'm a Statistician interested in statistical computing", "data visualization among others." ], "suggestion": "Approved", "report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nrspatialdata: a collection of data sources and tutors on downloading and visualizing spatial data using R.\nThis paper presents a website that provides a collection of data sources and tutorials on downloading and visualizing spatial data using R. There are several R packages that simplify the access and reliability of spatial data but rspatialdata can help researchers to find and use spatial data in a simple way, tutorials are focused on read and manipulate data in a common analysis system promoting the data reuse and analyses.\nGeneral comment:\nSince you are presenting a webpage I think it will be good to include a general description of the webpage structure, describing each tabs, and at least an image with the Home tab describing the user interaction. In Methods before Table 1. Also, you should mention which tools you have used to design the webpage.\nIt will be good to include a complete use case with all the visualizations as you have on the webpage, maybe on page 4 you can extend the temperature data example and show and comment on the figures, not just the R code.\nMinor comments:\n“R is a powerful language for statistical programming that incorporates a wide range of packages that can be used for data access, manipulation, analysis, and visualization.” This is a general statement not focused on spatial data and your references are specific and auto references to your work, you can include some general references or be specific to spatial data.\n\nPage 3. It will be useful to include the webpage URL at least once https://rspatialdata.github.io for printed version. The same for the GitHub repo (https://github.com/rspatialdata/rspatialdata.github.io).\n\nPage 4 Table 1, second column contains the R packages, and since this is the first time you mentioned them in the paper I think you should include citation there. Not sure if there is any restrictions on including references in a table in this publishing platform.\n\nPage 4 first paragraph, you should cite ggplot2.\n\nRemove Table 2, it has the same info as Table 1.\n\nIs the rationale for developing the new software tool clearly explained? Yes\n\nIs the description of the software tool technically sound? Yes\n\nAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others? Yes\n\nIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool? Yes\n\nAre the conclusions about the tool and its performance adequately supported by the findings presented in the article? Yes", "responses": [] } ]	1	https://f1000research.com/articles/11-770

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