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546334	Novel Enzyme Shows Potential as an Anti-HIV Target	null	At just 9.8 kilobases, the HIV genome pales in comparison to the 3.2 gigabases of its human and nonhuman primate targets. The compact retrovirus encodes just 14 proteins, which play different roles in promoting viral infection and virulence. As a retrovirus, HIV uses the host's cellular machinery—including RNA polymerases, which carry out transcription—to copy its RNA genome into DNA and infiltrate human chromosomal DNA. Once the virus is integrated (now called a provirus), its genes can be transcribed. Adept as HIV is in exploiting its host's molecular resources, the virus can't establish a foothold without the services of its skeleton crew. The HIV transcription factor Tat (“transactivator of transcription”), for example, is an essential regulator of HIV gene expression. Without Tat, HIV transcripts don't reach full length and can't effect viral replication. In a new study, Melanie Ott and colleagues identify an enzyme that regulates viral transcription by modifying Tat. The regulation of HIV genes depends on a complex interplay between proviral DNA, cellular proteins and transcription factors, and Tat. Unlike most transcription factors, Tat activates transcription by binding to RNA, specifically to a bulging “stem-loop” structure that forms at one end of all viral transcripts called the trans -acting responsive element (TAR). Tat binding to TAR requires recruiting the enzyme cyclin-dependent kinase 9 (CDK-9) to the HIV promoter (where transcription begins). CDK-9 chemically modifies the RNA polymerase and enhances its transcribing efficiency. The transcription process—including the labyrinthine protein–protein and protein–DNA (and in the case of Tat, protein–RNA) interactions—is highly regulated. One process that figures prominently in this regulation is acetylation, which adds an acetyl group (a molecule made of oxygen, hydrogen, and carbon) to a molecule or protein. Histone acetylation was long thought to influence transcription by regulating the structure and function of chromatin, which is an assembly of proteins (mostly histones) and DNA. Another, more widely accepted model proposes that histone acetylation controls transcription by recruiting cofactors required for transcription. Acetylation and deacetylation enzymes can also target other proteins. Of the three classes of deacetylases known to modify human histones, the sirtuins (SIRT1–7) appear to preferentially target a number of nonhistone proteins. Ott and colleagues first tested the ability of all seven SIRT proteins to deacetylate Tat by placing them in a test tube with Tat proteins. Though three SIRT enzymes caused Tat acetylation, only one, SIRT1, is a nuclear enzyme, like Tat, suggesting that SIRT1 might work similarly in living cells. Recycling of Tat through deacetylation by SIRT1 Ott and colleagues went on to show that transcription via Tat occurs in the presence of SIRT1, but not when SIRT1's catalytic center is removed. Experiments using cells taken from transgenic mice lacking SIRT1 demonstrated that introducing human SIRT1 enzymes increased Tat's transcriptional effects in a dose-dependent manner, while treating cells with the small molecule HR73, a derivative of a molecule that inhibits the yeast version of the SIRT1 protein, caused a 5-fold reduction in HIV transcription. The authors propose a cycle of transcriptional transactivation in which SIRT1 deacetylates Tat at the HIV promoter. Deacetylated Tat associates with CyclinT1 and TAR, and leads to transcription. Tat acetylation dissociates Tat from CyclinT1 and TAR, and transfers Tat to the elongating polymerase complex. Since acetylated Tat can't recruit CyclinT1 and CDK-9, the authors explain, a new round of transcription requires that new, unacetylated Tats are produced or existing Tats are deacetylated. Thus, efficient viral replication depends on adequate Tat supplies. And since HIV gene expression relies on SIRT1's enzymatic activity, inhibiting SIRT1 could prove to be a promising anti-HIV therapy. Future study will have to verify whether inhibiting SIRT1 can successfully put the brakes on HIV transcription and control the virus (See also “A New Paradigm in Eukaryotic Biology: HIV Tat and the Control of Transcriptional Elongation” [DOI: 10.1371/journal.pbio.0030076 ]).	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546334.xml
509422	Use and improvement of microbial redox enzymes for environmental purposes	Industrial development may result in the increase of environmental risks. The enzymatic transformation of polluting compounds to less toxic or even innocuous products is an alternative to their complete removal. In this regard, a number of different redox enzymes are able to transform a wide variety of toxic pollutants, such as polynuclear aromatic hydrocarbons, phenols, azo dyes, heavy metals, etc. Here, novel information on chromate reductases, enzymes that carry out the reduction of highly toxic Cr(VI) to the less toxic insoluble Cr(III), is discussed. In addition, the properties and application of bacterial and eukaryotic proteins (lignin-modifying enzymes, peroxidases and cytochromes) useful in environmental enzymology is also discussed.	Introduction Chromate reductases are a group of enzymes that catalyze the reduction of toxic and carcinogenic Cr(VI) to the less soluble and less toxic Cr(III). These proteins have recently raised enormous interest because of their central role in mediating chromium toxicity and their potential use in bioremediation and biocatalysis. Chromate (Cr(VI)) is generated as by-product of various industrial processes such as leather tanning, chrome-plating, pigment production and thermonuclear weapon manufacture [ 1 ]. Its high water solubility facilitates a rapid leaching, provoking a wide dispersion capable to contaminate drinking water supplies. Therefore, the characterization of enzymes that reduce chromate, as well as the study of their induction patterns and gene expression are relevant to complete our understanding of chromium metabolism in order to minimize the toxicity of this compound in the environment. The chromate-reducing activities have been located in the cell membrane or in the cytoplasm of many bacteria [ 2 ]. Their ubiquities in many different organisms suggest that they might share a common role in, for example, physiological redox sensing or detoxification. Recently, two novel dimeric flavoproteins with chromate reductase activity, ChrR (from Pseudomonas putida ) and YieF (from E. coli ) have been purified and characterized [ 1 ]. These enzymes were able to transform chromate to the less toxic Cr(III). However, while ChrR was not a pure two-electron reducer of chromate, YieF was able to catalyze a three-electron reduction. The role of ChrR and YieF in protection against chromate toxicity was also investigated and the results suggested that both enzymes may have an important role in protection against chromate toxicity [ 1 ]. The ability of some microorganism and their enzymes to remove toxic pollutants has been recently reviewed [ 3 - 6 ]. The identification and characterization of the degradative pathways functioning in microorganism have been the starting point for biotechnological and environmental applications [ 3 ]. Discussion The intensive industrial and agricultural development has been considered as responsible for a widespread contamination of soil, air and groundwater with toxic pollutants, which are harmful for human health and the environment [ 6 ]. These contaminants enter the environment through different paths, which may include direct application, combustion processes and natural emissions. Major contaminants are polycyclic aromatic hydrocarbons (PAHs), petroleum hydrocarbons, phenols, polychlorinated biphenyls, azo dyes, organophosphorus pesticides and heavy metals [ 3 ]. In particular, Cr(VI) is a common pollutant due to the use of chromium compounds in tanning and other industries. Chromate shares structural similarities with sulphate ion (SO 4 -2 ) and may be introduced in eukaryotic and bacterial cells by the sulphate transport system [ 1 ]. In bacteria, flavoenzymes such as glutathione reductase reduce Cr(VI) by a one electron transfer leading to the formation of the highly unstable radical Cr(V) and the flavin semiquinone form of the enzyme. Both species undergo a further redox cycle in which Cr(VI) is re-generated by one-electron transfer to oxygen, producing and accumulating reactive oxygen species (ROS). The appearance of relatively large quantities of ROS, and the consequent oxidative stress are responsible for the toxic effects and cellular damage attributable to the presence of Cr(VI). On the other hand, trivalent chromium Cr(III) is water insoluble, less bio-available and less toxic [ 1 ]. Thus, the strategies employed to eliminate chromate toxicity would involve its reduction to Cr(III) by chemical or biological means. While chemical methods are expensive at the large scale required to decontaminate waste sites, microorganisms are commonly used for environmental purposes through the exploitation of their natural catalytic activities. Enzymatic treatments have a minimal impact on ecosystems, as they present no risk of biological contamination. Furthermore, enzymes can act over a wide range of pH, temperature and ionic strength and also may be active in the presence of high concentrations of organic solvents in which major pollutant molecules are soluble [ 6 ]. Several bacterial enzymes that can be used in bioremediation have been described; they include mainly oxidative enzymes such as mono-and dioxygenases but their use is restricted by the need of cofactors, which can only be efficiently regenerated inside the microorganism [ 6 ]. In the last two decades bioremediation has explored the use of the catalytic machinery of white rot fungi to remove toxic pollutants. White rot fungi comprise all those fungi capable to degrade lignin, a polyphenolic polymer highly resistant to bacterial biodegradation. Many strains from the genera Pleurotus, Bjerkandera, Phanerochaete , and Trametes produce extracellular enzymes with ligninolytic activity. These enzymes are often referred to as lignin-modifying enzymes and include mainly Lignin peroxidase, Manganese dependent peroxidase and laccase [ 4 ], though some authors have reported other related enzymes such as a Mn-independent MnP activity [ 7 ]. Besides lignin-modifying enzymes, several other enzymes such as the heme-containing peroxidases, chloroperoxidase and horseradish peroxidase, and the non-enzymatic hemeproteins, hemoglobin and cytochrome c , are able to oxidize organic compounds in the presence of hydrogen peroxide. An interesting feature of these enzymes is their remarkable low specificity towards substrates that arises from their own catalytic mechanism. In vivo , peroxidases use endogenous low-molecular weight compounds, called mediators, to generate free radicals capable to carry out a wide variety of reactions such as oxidations, bond cleavage, hydroxylations, polymerization and demethylation [ 4 ]. Several research efforts have been focused on the ability of peroxidases to degrade pollutants such as PAH's, azo dyes and organophosphorus pesticides [ 8 - 10 ]. Strong regulations have been established to push the industrial sector to develop new programs destined to a greater environmental care. Nowadays, industry is strongly dependent on petroleum and its derivatives as a source for raw materials and energy. There are still large reserves of crude oil, which are heavy oils with a high content of sulphur and heavy metals. The use of these fuels generate a great pollution, being one of their most important environmental impacts the formation of the acid rain which takes place by the sulphur oxide production during combustion. Redox enzymes may encounter fields of application not only in the bioremediation of polluted environments, but also in the development of novel clean technologies to avoid or diminish the environmental contamination. Biocatalytic methods for sulphur removal from straight-run diesel fuel have been developed [ 11 ]. The removal of heavy metals from the petrophorphyrin-rich fraction of asphaltenes has also been reported [ 12 , 13 ]. Thus, enzymes can play an important role in the development of alternative or complementary biotechnological processes with potential application in polluting industries. Despite their potential application in bioremediation and clean processes, the activity of oxidative enzymes may be limited, among other factors, by the low bioavailability of the pollutants and by the relatively low operational stability of the enzyme under the environmental conditions required to carry out the bioremediation. Several strategies to increase the catalytic activity of peroxidases have been proposed, including chemical modification of the enzyme [ 14 , 15 ] and genetic tools [ 16 ]. Recently, with the cloning and expression in suitable hosts, larger amounts of the desired enzymes may be produced, facilitating their characterization and their direct use in environmental applications. Further, through the use of novel techniques such as directed molecular evolution [ 17 ], proteins designed specifically for bioremediation could be made available in a not distant future. In the last few years there has been an extensive research in the application of laboratory evolution for tailoring redox enzymatic systems (laccases, peroxidases, cytochrome P450 monooxygenases) to improve their activities and stabilities against temperature or organic solvents [ 18 - 20 ]. The application of this powerful approach for bioremediation issues is coming up, but first a big effort in the high-throughput (HTP) screening methodology must be done. So far, little has been reported on the optimisation of suitable HTP for the detection of xenobiotics [ 21 ]. Therefore, the success in the enzyme evolution for environmental issues will be highly dependent on the automation of HTP. Microbial genomics is a new emerging field that enables us to look at parts of the environment that were, until recently, masked to us. Present estimations suggest that more than 99% of the microorganisms in most environments (also those subjected to chronic contamination) are not amenable to grow in pure culture, and thus very little is known about their enzymatic activities. We can now access the genomes of non-culturable microorganisms through creating the "so-called" metagenomic-libraries and identify protein-coding genes and biochemical pathways that will shed some light on their properties and function [ 22 ]. New enzymatic systems found in contaminated areas can be used as parental types for some rounds of directed evolution with the main aim of improving the catalytic performance for their use towards solving a broad range of environmental problems. Conclusion The even more strict regulations on hazard wastes has forced to the development of new environmentally compatible strategies to substitute or complement the conventional ones. Chemical technologies are expensive when applied to large scale and in many cases are technically not feasible. On the other side, by exploitation of the huge diversity of natural activities and metabolic pathways presented by microorganisms, new strategies can be envisaged. The use of oxidative enzymes as biocatalysts for environmental purposes presents a promising potential due to their low specificity and low energetic requirements. However, further characterization of new biocatalysts is needed. The use of novel technologies such as molecular directed evolution may have a large impact in the tailoring and further application of enzymes not only for bioremediation but also for the development of friendly environmental technologies.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509422.xml
545199	Climate Drives the Meningitis Epidemics Onset in West Africa	Background Every year West African countries within the Sahelo-Sudanian band are afflicted with major meningococcal meningitis (MCM) disease outbreaks, which affect up to 200,000 people, mainly young children, in one of the world's poorest regions. The timing of the epidemic year, which starts in February and ends in late May, and the spatial distribution of disease cases throughout the “Meningitis Belt” strongly indicate a close linkage between the life cycle of the causative agent of MCM and climate variability. However, mechanisms responsible for the observed patterns are still not clearly identified. Methods and Findings By comparing the information on cases and deaths of MCM from World Health Organization weekly reports with atmospheric datasets, we quantified the relationship between the seasonal occurrence of MCM in Mali, a West African country, and large-scale atmospheric circulation. Regional atmospheric indexes based on surface wind speed show a clear link between population dynamics of the disease and climate: the onset of epidemics and the winter maximum defined by the atmospheric index share the same mean week (sixth week of the year; standard deviation, 2 wk) and are highly correlated. Conclusions This study is the first that provides a clear, quantitative demonstration of the connections that exist between MCM epidemics and regional climate variability in Africa. Moreover, this statistically robust explanation of the MCM dynamics enables the development of an Early Warning Index for meningitis epidemic onset in West Africa. The development of such an index will undoubtedly help nationwide and international public health institutions and policy makers to better control MCM disease within the so-called westward–eastward pan-African Meningitis Belt.	Introduction Meningococcal meningitis (MCM) has affected Sahelian Africa for centuries and became endemic over the past 25 y. During the 1980s, the World Health Organization (WHO) registered between 25,000 and 200,000 disease cases per year, with about 10% of them resulting in death, and with the highest infection rates observed in younger children [ 1 ]. MCM became, therefore, a public health concern in the poorest regions in the world following the severe drought at the end of the 1970s. MCM is an infection of the meninges, caused by the bacteria Neisseria meningitidis , that causes high death rates in African communities. The agent is highly contagious, and person-to-person aerial transmission occurs through respiratory and throat secretions [ 2 ]. Interaction between different environmental parameters (e.g., immune receptivity of individuals, a poor socioeconomic level, the transmission of a more virulent serotype [such as the recent emergence of the serogroup W135 in West Africa], social interactions [such as pilgrimages, tribe migrations, and meetings], and some specific climatic conditions) may play a part in MCM disease outbreaks and spread within local populations [ 2 ]. Among favorable conditions for the resurgence and then dispersion of the disease, climatic conditions may be important as environmental forces inducing periodic fluctuations of disease incidence. Recent findings concerning the population dynamics of some infectious diseases have clearly identified the importance of climate as a major driver [ 3 , 4 ]. MCM outbreaks in West Africa usually start at the beginning of February, and then disappear in late May. The geographical distribution of disease cases is called the “Meningitis Belt” and is roughly circumscribed to the biogeographical Sahelo-Sudanian band [ 5 , 6 ]. This Sahelo-Sudanian region has a dry winter, dominated by northern winds, called the Harmattan, followed by a wet season starting in spring with the monsoon. The co-occurrence in both space and time of MCM disease cases and climate variability within the Sahelo-Sudanian area suggests that the occurrence of MCM might be directly related to climate. So far, very few studies have tried to quantify the potential linkages that could exist between climate and MCM outbreaks ( Figure 1 ). Figure 1 The “Meningitis Belt” in West Africa Modified from the WHO [ 9 ]. The winter climate causes damage to the mucous membranes of the oral cavity through dry air and strong dust winds, and creates propitious conditions for the transmission of the bacteria responsible for MCM; low absolute humidity and dust may enhance meningococcal invasion by damaging the mucosal barrier directly or by inhibiting mucosal immune defenses. In contrast, higher humidity during both the spring and summer seasons strongly reduces disease risk by decreasing the transmission capacity of the bacteria [ 7 , 8 ], and MCM epidemics generally stop with the onset of rainfall [ 9 ]. In addition to the seasonal cycle, the link between climate and meningitis has also been documented at the interannual scale in northern Benin, where Besancenot et al. [ 10 ] have suggested a positive relationship between low absolute humidity and interannual variability in meningitis. Meanwhile, although the global influence of climate is quite clear, the effects of climatic variability on MCM population dynamics are still only partially known because of the mixing of different processes acting at different spatial hierarchical scales, and the interactions between disease outbreaks and medical, demographical, and socioeconomic conditions. Most studies thus far have focused on very small spatial scales, and the need remains to discriminate between local properties and potential large-scale effects in disease patterns, to go beyond data heterogeneities and idiosyncratic details in order to identify important disease patterns influenced by large-scale forces such as climate variability (see Methods). The aim of the present work is thus to document the climatic context of MCM disease outbreaks and population dynamics in a highly affected Sahelian country, that is, Mali, and to show, if it exists, the presence of a correlation between climate and seasonal resurgence of disease. The idea behind the present study was to explain MCM disease dynamics in Mali in a statistically robust way, which will permit us to propose some tools for predicting disease risks for the benefit of public health. Methods The Scaling-Up Approach: From Local to Global Scales Recent findings concerning the population dynamics of some infectious diseases have clearly identified the importance of climate as a major driver [ 3 , 4 ]. With evidence of the impact of large-scale meterological phenomena such as El Niño on infectious disease patterns, modern epidemiology is now confronted with a scale problem in the identification of the spatiotemporal scales that might be relevant to explain patterns and processes [ 11 ]. Since most previous studies have focused on very small spatial scales, there is a need for “bottom-up” approaches to discriminate between local properties and potential large-scale effects on disease patterns. One of the simplest assumptions of these “bottom-up” approaches is the assumption that local scales are random processes overlaying a driving large-scale phenomenon such as climate variability. As such, this scaling-up approach seeks to point out the emerging patterns conditioned by the large-scale processes, with a random or deterministic function f such that: Local data = f (large-scale forces, idiosyncratic details). The aggregation of local data in the scaling-up approach is a simple way to go beyond data heterogeneities and idiosyncratic details so that only the important disease effects of large-scale forces remain. That is the rationale for our study: to show that large-scale phenomena such as the seasonal Harmattan winds over the whole of Mali can contribute to the periodic resurgence of MCM and its variation in time on a national scale, even if this aggregate analysis for the entire country is not able to capture variations at smaller space scales. Epidemiological Data: The WHO Weekly Reports The diagnosis of MCM is based on both physical examination and on evaluation of the cerebrospinal fluid (CSF) from a lumbar puncture. As the disease is characterized by a sudden onset of intense headache, fever, nausea, vomiting, photophobia, and stiff neck, in association with neurological symptoms (lethargy, delirium, coma, and convulsions), the WHO [ 9 ] recommends that the clinical diagnosis include an examination for meningeal rigidity, neurological signs, purpura, blood pressure, and focal infection. A lumbar puncture and CSF examination are then used to confirm the diagnosis based on physical examination and to identify the meningococcus [ 9 ]. This diagnosis is the basis for disease surveillance and case reporting using a standard case definition for MCM ( Box 1 ) that can be implemented in any health-care setting. Meningitis reports are included in the weekly reports of notifiable diseases and are aggregated at different spatial scales from the health site to the country level. The present study is based on these weekly reports by the WHO's Department of Communicable Disease Surveillance and Response of cases and deaths due to MCM over the whole of Mali from 1994 to 2002. Box 1. Standard Case Definition of MCM Modified from the WHO [ 9 ] This case definition allows the detection of cases of meningococcal septicemia. Suspected case of acute meningitis a . Sudden onset of fever (>38.5 °C rectal or 38.0 °C axillary) with stiff neck. In patients under 1 y of age, a suspected case of meningitis occurs when fever is accompanied by a bulging fontanelle. Probable case of bacterial meningitis b . Suspected case of acute meningitis as defined above with turbid CSF. Probable case of MCM b . Suspected case of either acute or bacterial meningitis as defined above with Gram stain showing Gram-negative diplococcus or ongoing epidemic or petechial or purpural rash. Confirmed case c . Suspected or probable case as defined above with either positive CSF antigen detection for N. meningitides or positive culture of CSF or blood with identification of N. meningitides. a Often the only diagnosis that can be made in dispensaries (peripheral level of health care). b Diagnosed in health centers where lumbar punctures and CSF examination are feasible (intermediate level). c Diagnosed in well-equipped hospitals (provincial or central level). The Typical Seasonal Pattern of the Disease In this study, an epidemic is defined in terms of population dynamics following Anderson and May [ 12 ] and Grenfell and Dobson [ 13 ]. This definition considers disease resurgence and its variation in time and allows us to focus on the cyclic character of the disease resurgence each year, even if the number of annual cases is low, and it makes it easier to find temporal correlations between climate and disease. To represent a typical seasonal cycle of a meningitis epidemic, we computed the weekly mean of standardized anomalies M ( w ) of the number of cases as where X̄ y and σ y represent, respectively, the mean and the standard deviation of the 54 weekly values of cases X y ( w ) for the year y, and N = 9 represents the number of years for the 1994–2002 period. The Onset of the Epidemic We determined the week of the onset of the epidemic for each year by characterizing a breaking slope in the annual cycle of the number of cases. The dates of the breaking slope have been determined objectively by using the Mann–Whitney–Pettitt test [ 14 ], which is a nonparametric test used here to detect a “change point” in a time series. A change point is defined as a point on either side of which values are on average higher or lower than the whole of the other data points. Considering the studied time series X y ( w ), we computed U y ( w ) as where 2 ≤ w ≤ 54 and U y (1) = V y (1), where V y ( w ) is defined by Then the the most significant change point of the year y is the point for which the value \|U y ( w )\| is maximized. The probability P y ( w ) of a given week being a change point is defined by where T = 54 (the length of the time series in weeks). Atmospheric Data: The NCEP/NCAR Reanalysis The National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) have completed a reanalysis project with a current version of the Medium Range Forecast model [ 15 ]. This dataset consists of a reanalysis of the global observational network of meteorological variables (wind, temperature, geopotential height [i.e., the height of a pressure surface above mean sea level], humidity on pressure levels, surface variables, and flux variables such as precipitation rate), with a “frozen” state-of-the-art analysis and forecast system at a triangular spectral truncation of T62, performing data assimilation throughout the period from 1948 to the present. This analysis enables circumvention of problems involving previous numerical weather prediction analyses due to changes in techniques, models, and data assimilation. Data are reported on a 2.5° × 2.5° grid every 6 h (00.00, 06.00, 12.00, and 18.00 UTC) on 17 pressure levels from 1,000 hPa to 10 hPa, a good resolution for studying synoptic weather systems. For this study we used the wind speed fields at 1,000 hPa (near the surface) for the 9 y of the 1994–2002 period: first we averaged the four outputs of each day, and then we averaged these daily means for each week to obtain a weekly value. Computation of the Harmattan Wind Index The principal component analysis (PCA) [ 16 ] is a multivariate procedure that extracts the common variance that exists in a set of variables. The main use of PCA is to reduce the size of a dataset while retaining as much information as possible in principal components (PCs), which are linear combinations of the initial variables. In this study, this technique has been used in order to summarize the spatiotemporal variability of wind fields at low levels. As the input data are spatial objects (grid points), the PCA gives for each mode a spatial pattern associated with a time series (the PC). We performed the PCA on the weekly values from 1994 to 2002 of wind speed at 1,000 hPa over the Mali window (in red in Figure 1 ) by taking into account all the grid points from 12.5° N to 25° N and from 12.5° W to 2.5° E. The input matrix was thus composed of 6 × 7 = 42 loadings (the number of grid points over the spatial window) and 486 scores (the number of weeks in the 1994–2002 period). Data was first standardized in order to extract the correlation matrix C = X′X, where X represents the input matrix and X′ its transpose. The α th PC time series ψ α can thus be obtained by a linear combination of the initial variables through where u α is the α th eigenvector of the correlation matrix C associated with the eigenvalue λ α . The α th spatial pattern is the correlation map between the initial wind fields and the α th PC time series. The examination of the different spatial patterns and PC time series (not shown here but previously discussed in [ 17 ]) reveals a close relationship between Harmattan wind dynamics and the third PC with negative values, which represents a strong wind in southern Mali. The Harmattan wind index of the study thus represents the third PC, with a temporal pattern very similar to the seasonal cycle of wind speed associated with the Harmattan winds over Mali. Results The “Epidemic Seasonality” in Mali The weekly records of the WHO's Department of Communicable Disease Surveillance and Response of cases and deaths due to MCM for the 1994–2002 period allowed us to describe the seasonal evolution of MCM epidemics in Mali. Two important parameters were used: the date of the onset of the epidemic and the date of the seasonal maximum number of cases. We determined for each year the week of the onset of the epidemic (here called “ W o ”) as determined by a breaking slope in the annual cycle of the number of cases. The dates of breaking slope have been determined objectively by using the Mann–Whitney–Pettitt test [ 14 ], which is a nonparametric test used here to detect a change point in a time series. This test has the advantage of being adapted to small samples, giving the point of the most significant change and the probability of it being a significant change point (see Materials and Methods). The mean date of epidemic onset fell between the fifth and sixth week of the year (7–15 February), with a standard deviation of about 2 wk (5.2 ± 1.7 wk). For the 1994–2002 period, the maximum number of cases occurred between week 13 and week 14, that is, between 1 April and 15 April, with a standard deviation of about 2 wk (13.7 ± 1.6 wk) ( Figure 2 ). Figure 2 The Seasonal Periodicity of Meningitis Cases Mean seasonal pattern of the number of cases of MCM over the 1994–2002 period in standardized anomalies (bars). The red curve represents the same evolution, but in composite mean, using the week of epidemic onset as the reference date, W o , each year. Time series in red is shown from “ W o − 3 wk” to “ W o + 30 wk.” In order to mitigate the effect of strong variability from one year to another during the 1994–2002 period, we computed the average of standardized anomalies of the number of cases (bars in Figure 2 ) to represent a typical seasonal pattern of a meningitis epidemic. The first 5 wk are characterized by negative anomalies. The average length of the “epidemic year,” as defined by the number of consecutive weeks with positive anomalies, is 4 mo (16 wk). To improve the description of the seasonal pattern of the epidemic and to reduce noise due to the variability of the onset date year to year, we determined the composite mean of the number of cases over the 1994–2002 period by using the week of epidemic onset for each year as the respective reference date, W o . The red curve of Figure 2 shows the mean seasonal course before and after the onset of the epidemic, showing an abrupt increase of the number of cases—the “upward phase”—until the sixth week after the onset, a highly active period of the disease—the “active phase”—from “ W o + 6” to “ W o + 10,” followed by a decrease of the number of cases—the “downward phase”—until the end of the epidemic around 16 wk after the onset. Both upward and downward phases lasted on average 1.5 mo. The Atmospheric Circulation during an Epidemic in Mali Rainfall distribution over West Africa is controlled by the meridional migration of the intertropical convergence zone following the seasonal excursion of the sun [ 18 ]. The latitudinal shift of this zone of high humidity and instability leads to an opposition of two main annual regimes: the bimodal regime of the Guinean latitudes (from the equator to 7° N) with two rainy seasons during spring and autumn, and the unimodal regime of monsoon over Sudano-Sahelian Africa and succession of a dry winter and a wet summer [ 19 ]. North of the intertropical convergence zone, the intertropical front is defined as the confluence line between moist southwesterly monsoon winds and dry northeasterly Harmattan [ 20 , 21 ]. The seasonal progression of this system, involving a migration toward the summer pole of moisture and winds converging in the low layers, can be documented by using weekly fields surface wind speed from NCEP and NCAR data, which provide gridded atmospheric parameters with a 2.5° resolution [ 15 ]. The relationship between atmospheric circulation and the seasonal course of the MCM epidemic in Mali was studied using a regional index summarizing the spatiotemporal evolution of the low-layer circulation. This index was obtained from a dominant mode of a PCA (see Materials and Methods) applied to weekly fields of surface wind speed over the 1994–2002 period in Mali. The seasonal pattern shows the Harmattan wind dynamics ( Figure 3 ) with negative values representing strong winds, and positive values representing weak winds, in the southern part of Mali, the area under study in the present work. Figure 3 Temporal Patterns of Epidemics and Climate Weekly means of the Harmattan wind index over the 1994–2002 period and mean seasonal pattern of the number of cases of MCM (in standardized anomalies). Using this atmospheric index, we defined the date of “winter maximum” as the first minimum of the wind index for each year of the period 1994–2002. The winter maximum thus corresponds to the week where wind speed is the strongest. The mean date of winter maximum is around the sixth week, with a standard deviation of 2 wk, corresponding to the week when the Intertropical Front is located at its southern latitude. The Harmattan wind index shows a temporal pattern very similar to the that of the number of cases of MCM, with a clear breaking slope at the sixth week, on 15 February, corresponding to the onset of the epidemic and to the winter maximum, and with a recession of the disease at the 16th week concomitant with the onset of the wet season in the south part of Mali in early May. It is interesting to note that although they are determined from two different datasets, the mean weeks of winter maximum and of the onset of the epidemic are identical, 7–15 February. This coherence is reinforced by a very strong correlation between the two dates (0.92) for the years 1994 to 2002. Figure 4 shows the linear regression analysis between week of winter maximum and week of epidemic onset. Although the number of years under consideration is low, the scatter plot points out the close statistical linkage between these two events, suggesting that the winter maximum explains more than 85% of the variance in the week of epidemic onset in Mali: An earlier winter is associated with an earlier onset of the epidemic, and a later winter with a later onset. However, even though the results of the correlation analysis are strongly significant, the high R 2 is partially due to the low number of considered years (only nine); this low number is the main limitation of the present analysis. Figure 4 The Onset of Epidemics and the Winter Maximum Scatter plot of the week of epidemic onset and the week of winter maximum over the 1994–2002 period. Discussion In this paper and a previous publication of ours [17], by using the weekly number of cases of MCM disease in Mali and large-scale fields of surface wind speed, we clearly identify a strong relation between climate and the seasonal pattern of MCM cases in Mali. It is shown that the onset of disease outbreak is characterized by a clear breaking slope in the seasonal cycle of the number of cases at the sixth week of the year, that is, 15 February. The computation of an atmospheric index based on surface wind speed over Mali points out that this abrupt shift is also present in the atmospheric signal, corresponding to the winter wind maximum, when Harmattan winds are the strongest in Sahelo-Sudanian Africa. The similarity in the seasonal patterns of both Harmattan winds and MCM disease cases is obvious, with a strong correlation between the week of winter maximum and that of the onset of epidemic. Similar results, not illustrated here, have been obtained by using surface temperatures and specific humidity for the computation of atmospheric indexes, attesting to the robustness of the analysis. However, whatever the climatic index is used, this analysis does not allow us to link the intensity of the “epidemic” (the annual number of cases) to the intensity of winter in terms of absolute humidity and surface wind speed. This lack of a relation may be due to the time series length, with an insufficient number of years to study interannual variations, or it may imply that the climatic influence is limited to explaining the occurrence of the seasonal cycle of the epidemic and its geographical range distribution, but not its intensity. Although they fail to forecast epidemic intensity, such climatic indexes, with their correlation with the onset and the seasonal course of the epidemic in Sahel, provide an important means of disease monitoring and prediction in Africa. Indeed, the seasonal pattern of humidity and Harmattan winds can be easily tracked, thus promoting the emergence of an Early Warning Index (EWI) for the onset of MCM epidemics. The seasonal forecast of this EWI based on Harmattan winds could thus be implemented routinely by using comprehensive coupled models of the atmosphere, oceans, and land surface that provide a degree of predictability of climate fluctuations with a seasonal lead time in many parts of the world [ 22 ]. The ability of the climate models to predict the winter maximum could be tested by using the outputs of the Development of a European Multi-Model Ensemble System for Seasonal to Interannual Prediction (DEMETER) project, which was conceived and funded under the European Union Fifth Framework Environment Programme. The principal aim of DEMETER was to advance the concept of multimodel ensemble prediction by using a number of state-of-the-art global-coupled ocean–atmosphere models and to produce a series of 6-mo multimodel ensemble hindcasts. The DEMETER project already has application partners in agronomy and in tropical disease prediction [ 22 ]. This EWI parameter, in association with other environmental parameters implicated in disease resurgence [ 23 ], could help to more precisely characterize disease risk maps at regional scales. The natural extension of this work is to relate this information on the timing of disease outbreaks with specific spatial environmental characteristics at finer scales, in an Early Warning System based on the monitoring of the impact of climate variability and environmental change on epidemic occurrence in West Africa. Recent findings by Molesworth et al. [ 23 ] have already quantified the relationship between the environment and the location of the epidemics to propose a model based on environmental variables and to identify regions at risk for meningitis epidemics. The combination of the EWI for MCM epidemic onset and risk maps at regional scales could be a starting point to more optimally direct national and international health policy strategies and to optimize mass vaccination campaigns. In addition, more general measures can be taken by national authorities to improve the control of MCM disease, such as closing markets and schools and discouraging social gatherings when an outbreak is likely to occur [ 9 ]. Patient Summary Background Climate is known to be one of the factors that can affect when and how epidemics occur; for example, floods often increase the risk of waterborne disease. However, there are many more subtle climatic changes that might also be important in affecting when and how diseases occur. What Did the Researchers Do? They looked at the relationship between a recurring epidemic of a disease called meningococcal meningitis in Mali in West Africa and the local climatic conditions, especially the winds. Meningococcal meningitis is a serious infection of the lining of the brain and spinal cord by a bacterium (called Neisseria meningitides ). These researchers had previously published some detailed work on the local climate in a French journal. In this paper they have focussed more on the aspects that deal with disease. They found out that over several years the onset of the epidemic coincided with the peak of the winds. Who Will Use These Results? People who would find these results useful are those who plan for epidemics. Such information will allow them to plan in advance, and even predict whether an epidemic will occur at all. However, these results were based on only the years between 1994 and 2002, and so will need to be confirmed in more years.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545199.xml
300884	Structure and Implications of JAMM, a Novel Metalloprotease	null	Proteins may be the workhorse of the cell, but when a cell can synthesize one protein in a matter of minutes, chances are some will become obsolete. Though many proteins put in years of productive service, others quickly outlive their usefulness and can even damage the cell. Proteins that help form bone and muscle, for example, function for years while regulators of mitosis and cell proliferation might finish their jobs in seconds. Such short-timers are soon tagged as superfluous by a chain of small proteins called ubiquitin, which marks the proteins for degradation in an enzyme called the proteasome. Once in the proteasome, these proteins are broken down and can then be recycled for more productive ventures. A massive structure by cellular standards, the proteasome consists of multiple subunits, including a cylindrical core particle called 20S, which catalyzes degradation, and regulatory complexes called 19S caps, which form lid and base structures at both ends of the core. While the structure and biomechanics of the 20S core have been well characterized, much less is known about the functional mechanics of the regulatory complexes. The lid--base complex recognizes only ubiquitin-tagged proteins, which are then unfolded so they can enter the proteasome. But first ubiquitin chains must be detached from the protein, a task performed by an enzyme in the proteasome called Rpn11 isopeptidase. How the lid–base complex removes the ubiquitin tag, unfolds the protein, and shuttles it into the proteasome's core is not clear. Now Raymond Deshaies and colleagues present the structure of a homolog of the 19S lid's isopeptidase enzymatic center and provide new insights into these questions. The proteasome Rpn11 subunit contains a key region called the JAMM motif, which Deshaies' lab has shown previously is required for the proteasome to remove ubiquitin tags. For the work discussed in this paper, the researchers set out to understand how the proteasome strips off ubiquitin tags from proteins about to be destroyed by determining the three-dimensional structure of the JAMM motif. The researchers tested many genes to look for a JAMM-containing protein that would crystallize properly and found one in the heat-loving prokaryote Archaeoglobus fulgidus . After determining the structure of the JAMM protein (called AfJAMM), the researchers discovered that AfJAMM looks nothing like the well-known deubiquitinating enzymes. But the arrangement of a set of amino acids that binds a zinc ion and forms the proposed active site of AfJAMM does resemble that found in a well-known protein-degrading metalloprotease called thermolysin, even though in other respects AfJAMM and thermolysin have very different features. The researchers mutated amino acid residues in another JAMM protein called Csn5 (they expected these residues to be critical for isopeptidase activity as well, based on comparisons of the AfJAMM and thermolysin structures) and found that the residues are indeed important for Csn5 function. These results suggest that JAMM does indeed represent a novel family of metalloproteases. As for the wider function of JAMM proteins, the researchers speculate that these proteins are likely to be involved in a variety of important regulatory systems since they appear in life forms that lack ubiquitin and ubiquitin-like proteins. The crystal structure reported in this paper will provide a valuable tool for investigations into the underlying structural and functional mechanisms of these enzymes. And it may have important therapeutic implications. Proteasome inhibitors are promising anticancer therapies—fighting cancer by blocking machinery required by rapidly dividing cells. In the hopes of developing more targeted therapies, scientists are trying to fine-tune their control of the ubiquitin system and the proteasome. Inhibiting the JAMM domain of enzymes like Csn5, which remove ubiquitin-like tags from proteins upstream of the proteasome, for example, might just do the trick. The active site of JAMM	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC300884.xml
539287	Soy versus whey protein bars: Effects on exercise training impact on lean body mass and antioxidant status	Background Although soy protein may have many health benefits derived from its associated antioxidants, many male exercisers avoid soy protein. This is due partly to a popular, but untested notion that in males, soy is inferior to whey in promoting muscle weight gain. This study provided a direct comparison between a soy product and a whey product. Methods Lean body mass gain was examined in males from a university weight training class given daily servings of micronutrient-fortified protein bars containing soy or whey protein (33 g protein/day, 9 weeks, n = 9 for each protein treatment group). Training used workouts with fairly low repetition numbers per set. A control group from the class (N = 9) did the training, but did not consume either type protein bar. Results Both the soy and whey treatment groups showed a gain in lean body mass, but the training-only group did not. The whey and training only groups, but not the soy group, showed a potentially deleterious post-training effect on two antioxidant-related related parameters. Conclusions Soy and whey protein bar products both promoted exercise training-induced lean body mass gain, but the soy had the added benefit of preserving two aspects of antioxidant function.	Background Many male exercisers avoid soy protein because there is a perception that it is inferior to proteins like whey for supporting lean boss mass gain. This perception persists even though there are no studies comparing whey and soy for effects on lean body mass gain. Soy may actually help promote lean body mass gain by the antioxidants associated with soy protein. Antioxidants are agents, either consumed in the diet or made by the body, which work against molecular damage due to oxidant reactions caused by free radicals, which are reactive molecules with an unpaired electron [ 1 ]. Soy protein isolate contains a mixture of antioxidants including isoflavones, saponins, and copper, a component of a number of antioxidant enzymes [ 2 ]. Body free radical production seems to be particularly high during exercise, and the resulting oxidant stress appears to contribute to muscle damage and fatigue [ 3 ]. This damage and fatigue could conceivably limit progress in exercise training by slowing muscle recovery between exercise workouts. This could limit lean body mass gain during an exercise program. If soy protein can promote lean body mass gain at least as well as whey, there may be one advantage to consuming soy protein. Soy protein contains antioxidants which may not only help with lean body mass gain, but which can also promote other aspects of health. Antioxidant actions are thought to work against the onset and severity of many diseases and health problems [ 1 ]. This may be particularly important during exercise training, which in some cases, depletes antioxidant capacities and/or increases oxidant stress [i.e. [ 4 , 5 ]]. This may explain why high degrees of chronic exercise can be detrimental. For example, some athletes show increases in histochemical muscle lesions as well as high cancer mortality, which have been linked to prolonged periods of exercise [ 6 , 7 ]. However, this area has been controversial since some studies suggest that long term exercise training produce body adaptations which increase antioxidant defenses [i.e. [ 8 , 9 ]]. Either way, soy protein antioxidants could conceivably exert beneficial effects during exercise training, either by restricting antioxidant depletion or by enhancing antioxidant capacity increases. The present study compared a soy protein product to a whey protein product in subjects undergoing a 9 week weight training program. Subjects were evaluated for lean body mass gain and changes in antioxidant status. The latter was done using one measurement of a component of antioxidant capacity and one for a component of oxidant stress. The former was based on an assay called plasma antioxidant status which assesses the ability to scavenge certain chemically generated radicals. The oxidant stress parameter was plasma myeloperoxidase, a measure of neutrophil activation, which is associated with increased secretion of superoxide radical [ 1 ]. Methods Subjects This study was approved by the Human Subjects Review Committee for Biomedical Sciences at The Ohio State University. All subjects signed an informed consent form. Male subjects, aged 19–25, were recruited from the Sport, Fitness and Health Program courses at The Ohio State University to participate in the present 9-week study. All subjects were considered experienced weightlifters with at least 1 year or more experience in strength training, which was confirmed by a questionnaire. Subjects were reported to be non-smokers, non-vegetarians, not currently taking supplements of any kind, and having no major health problems (i.e., diabetes, cardiovascular disease, etc.). All subjects had a body mass index (BMI) of less than 30. Strength Training Program At the start of the study, each subject was put on a common strength training program to strictly follow for the duration of the 9 week study. Subjects were given either workout 1 or workout 2. The two workouts were identical with the exception of exercise order and were designed to prevent subjects in the strength training classes from having to perform the same exercises at the same time. Midway through the program, subjects with workout 1 were given workout 2 and vice versa in order to maintain consistency. The strength training protocol was 3 sets of 4–6 repetitions for 14 exercises so that strength was the variable being maximized. The following exercises were performed to work all major muscle groups: 1) chest press; 2) chest fly; 3) incline press; 4) lat pull-down; 5) seated row; 6) military press; 7) lateral raise; 8) preacher curl; 9) bicep curl; 10) supine tricep extension; 11) seated tricep extension; 12) leg press; 13) calf raise; and 14) abdominal crunches. Protein Treatments Subjects were randomly assigned in a double-blind manner to either a soy, whey, or control group. The controls did the exercise program but did not consume a protein product (n = 9/each group). The soy protein product was DrSoy ® Bars, which contained 11 grams of protein and an assortment of micronutrients. The whey bars were made using the same recipe as the DrSoy ® Bars except that whey protein was substituted for soy protein. The products were supplied to study personnel in plain wrappers with different colors for each product. The color code was unknown to the subjects and study personnel who were in contact with the subjects. Each subject was instructed to consume 3 bars per day for the 9-week training period. This was in addition to the subjects' self-selected diet. Subjects were instructed not to change eating patterns during the course of the study. The time of the day when the bars were consumed was recorded daily in the subject's fitness log so that compliance could be monitored. Measurements Lean body mass was analyzed by hydrostatic weighing. Each subject performed at least 3 efforts and an average reading was taken. Blood was drawn into heparin tubes before and after the 9 week treatment period on a day when the subjects did not exercise. Blood was spun at 3000 × g and the plasma was stored at -70°C until analysis. Unfortunately, a problem during blood processing made some plasma samples unavailable for analysis. Plasma was analyzed for free radical scavenging capacity using the Total Antioxidant Status Assay Kit from Calbiochem-Novachem Corp. (San Diego, CA). Plasma myeloperoxidase was analyzed using an ELISA kit from Calbiochem-Novachem. Statistical analysis Statistical analysis was done by the Jump 3.1 program (SAS Institute, Cary, NC), with significance at p < 0.05. For each parameter and treatment group, values prior to the 9 week treatment were compared to values after treatment by paired, 2-tailed Student's t-test. In addition, for lean body mass, the changes in values for soy treatment were compared to the change in values for the other two groups by Tukey test. Results Baseline subject characteristics are given in Table 1 . Exercise training plus soy or whey treatments each produced a statistically significant increase in lean body mass, but the training alone did not (Figure 1 ). A comparison of the change in lean body mass for the soy group versus the change in the whey group did not show a significant difference (Figure 2 ). Plasma radical scavenging capacities fell in the whey and training alone groups, while the myeloperoxidase values rose in those same two groups (Figures 3 and 4 ). The values were unchanged in the soy group (Figures 3 and 4 ). Table 1 Subject characteristics. WHEY SOY CONTROL (Training Alone) AGE 20.36 ± 0.34 21.67 ± 0.24 20.44 ± 0.63 HEIGHT (cm) 180 ± 1.55 179 ± 1.30 178 ± 1.81 WEIGHT (kg) 81 ± 2.81 79 ± 2.49 79 ± 0.48 LBM (kg) 67 ± 1.96 66 ± 2.30 67 ± 1.65 Values are means ± SEM. Figure 1 Lean body mass pre- and post-treatment . Values are % lean body mass (kg) ± SEM from 9 subjects per group. Significantly different from pre-treatment values (paired t-test, p < 0.05) Figure 2 Percent change lean body mass . Values are % change in lean body mass ± SEM. Different letters indicate significantly differences between groups (Tukey test, p < 0.05) Figure 3 Plasma antioxidant status . Values are mM of trolox equivalents ± SEM (N = 5 for control and whey, 8 for soy) Significantly different from pre-treatment values (paired t-test, p < 0.05) Figure 4 Plasma myeloperoxidase . Values are mg/L ± SEM (N = 5 for control and whey, 8 for soy) Significantly different from pre-treatment values (paired t-test, p < 0.05) **Significantly different from pre-treatment values (paired t-test, p < 0.01) Discussion In this study, soy and whey were both effective at increasing lean body mass with exercise training, but the soy had the added advantage of inhibiting two negative effects of training on antioxidant status. The percent change in the radical scavenging capacity (total antioxidant status) seen with training alone and training plus whey was substantial compared to the differences typically seen for these types of measurements[ 11 - 13 ]. The lean body mass data seen here contradicts the common, but unconfirmed notion that soy is inferior to whey for promoting lean body mass gain. It should be noted, however, that the general trend for this study may or may not be duplicated for other study designs. For example, the time frame used here, 9 weeks, is not overly long for seeing lean body mass gain, which may explain why the training alone did not produce an effect on lean body mass gain. Thus, the effects of soy or whey on lean body mass gain versus training alone may be more pronounced than in longer studies. It should also be noted that the training program used here emphasized low exercise repetitions in subjects not used to this type of training. In addition, this study included only subjects that were still relatively early in their training experience, and placed no restriction on Calorie intake. These design considerations were geared toward gaining bulk and power. The effects of whey or soy on lean body mass might be different in a design that emphasizes higher repetitions or Calorie restriction in other types of subjects. In addition, it can be noted that the current study diet intervention used bars which included added micronutrients. Thus, this study did not determine if the effects of the soy or whey protein required co-administration of micronutrients. It is not known whether the negative effects of training seen here for antioxidant status in the whey plus training alone groups would continue upon longer training. The current state of knowledge concerning exercise training effects on antioxidant defenses does not present a clear pattern [i.e. [ 4 , 5 , 8 , 9 ]], possibly because of the highly variable circumstances involved in different studies such as training intensity, types of exercise done, types of antioxidant measures used, fitness level of the subjects, length of training, and dietary patterns of the subjects. These variables may help explain why some studies find training-induced declines in antioxidant defense while others find no change or even an increase. Nonetheless, the present study suggests that soy protein intake can promote antioxidant function during training which could be helpful no matter what the effects of training by itself. Another unresolved issue is whether the effects on lean body mass seen here for the two proteins were due to increased total protein intake or other factors. In regard to the former, the data regarding the amount and type of protein intake necessary to produce optimal strength training gains is conflicting. While a diet meeting the current RDA for protein intake (0.8 g/kg body mass) may be sufficient for the sedentary individual, recent studies suggest dietary protein exceeding that of the RDA is needed for muscle hypertrophy [ 14 , 15 ]. One of the difficulties in deriving an exact protein recommendation for exercisers is that total energy intake has not been consistent in the studies. In some studies, total energy intake was low, which can cause an abnormally high percentage of energy output to be derived from protein [ 15 , 16 ]. In the present study, a 3 day diet record gave no indication that Calorie intake was low (data not shown). If soy and whey promotion of lean body mass gain was not due to increased total protein intake, which remains uncertain, then other factors were responsible. In the case of soy protein, there are associated antioxidants [ 2 ]. As presented in the Introduction, this could conceivably help indirectly with lean body mass gain. In the case of whey, the content of essential amino acids, especially those with sulfur, may be conducive to promoting lean body mass gain [i.e. [ 17 , 18 ]]. In summary, soy and whey protein bars both supported lean body mass gain in conjunction with a short term power-based weight training program, but only the soy bar prevented a training-induced drop in antioxidant capacities. Competing interests Author AB owns the company that produces the soy bars used in the study. Authors' contributions ECB planned and carried out specifics of the intervention. RAD conceived the general aims of the study and chose the blood measurements. AB invented the protein bars and planned specifics of the nutrition intervention. STD planned the general aspects of the exercise intervention.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539287.xml
539244	The role of transforming growth factor-beta (TGF-beta) during ovarian follicular development in sheep	Background Recently, several members of the transforming growth factor-beta (TGF-beta) superfamily have been shown to be essential for regulating the growth and differentiation of ovarian follicles and thus fertility. Methods Ovaries of neonatal and adult sheep were examined for expression of the TGF-betas 1–3 and their receptors (RI and RII) by in situ hybridization using ovine cDNAs. The effects of TGF-beta 1 and 2 on proliferation and differentiation of ovine granulosa cells in vitro were also studied. Results The expression patterns of TGF-beta 1 and 2 were similar in that both mRNAs were first observed in thecal cells of type 3 (small pre-antral) follicles. Expression of both mRNAs continued to be observed in the theca of larger follicles and was also present in cells within the stroma and associated with the vascular system of the ovary. There was no evidence for expression in granulosa cells or oocytes. Expression of TGF-beta 3 mRNA was limited to cells associated with the vascular system within the ovary. TGFbetaRI mRNA was observed in oocytes from the type 1 (primordial) to type 5 (antral) stages of follicular growth and granulosa and thecal cells expressed this mRNA at the type 3 (small pre-antral) and subsequent stages of development. The TGFbetaRI signal was also observed in the ovarian stroma and vascular cells. In ovarian follicles, mRNA encoding TGFbetaRII was restricted to thecal cells of type 3 (small pre-antral) and larger follicles. In addition, expression was also observed in some cells of the surface epithelium and in some stromal cells. In granulosa cells cultured for 6 days, both TGF-beta 1 and 2 decreased, in a dose dependent manner, both the amount of DNA and concentration of progesterone. Conclusion In summary, mRNA encoding both TGF-beta 1 and 2 were synthesized by ovarian theca, stroma and cells of the vascular system whereas TGF-beta 3 mRNA was synthesized by vascular cells. Luteinizing granulosa cells also responded to both TGF-beta 1 and beta 2 in vitro. These findings in sheep are consistent with TGF-beta potentially being an important autocrine regulator of thecal cell function and possibly a paracrine regulator of ovarian cell function at various development stages.	Background Members of the transforming growth factor-beta (TGF-β) superfamily are important intraovarian growth factors [ 1 - 6 ]. Three key members of the TGF-β subfamily, namely TGF-β1, TGF-β2 and TGF-β3, have been shown to be produced by ovarian cells [ 7 - 13 ]. However, the cellular distribution of these proteins varies between species. Likewise, the effects of TGF-βs on granulosa cell function also vary between species. In rodents, TGF-βs are potent stimulators of granulosa cell proliferation [ 14 - 16 ] whereas in other species, such as cattle and pigs, these growth factors have only a mild stimulatory or even inhibitory effect [ 17 - 20 ]. Likewise, TGF-βs stimulate progesterone synthesis from rodent granulosa cells [ 21 - 23 ] where inhibitory effects are observed in granulosa cells collected from sheep, cattle and pigs [ 17 , 24 - 26 ]. Exceptional ovulation rates and sterility have been observed in lines of sheep with mutations in two members of the TGF-β superfamily, namely growth differentiation factor 9 or bone morphogenetic protein 15 or one of their receptors, activin like kinase-6 [ 6 , 27 ]. However, little is known about the roles of other members of the TGF-β superfamily in sheep and thus the potential interactions of members of the TGF-β superfamily are unclear. The objectives of this study in sheep were to localize the ovarian cellular types expressing mRNA encoding TGF-β1, TGF-β2, TGF-β3, TGFβRI and TGFβRII and to determine the effects of TGF-β1 and TGF-β2 on granulosa cell proliferation/survival and progesterone production in vitro . Methods Generation of cDNAs encoding a portion of the coding region of genes of interest Except where indicated, laboratory chemicals were obtained from BDH Chemicals New Zealand Ltd (Palmerston North, New Zealand), Invitrogen (Auckland, New Zealand) or Roche Diagnostics N.Z. Ltd. (Auckland, New Zealand). Total cellular RNA was isolated from ovine ovary using TRIzol according to manufacturer's instructions. First strand cDNA was produced from total cellular RNA using a poly t primer. Complementary DNAs encoding a portion of the coding sequence of the genes were isolated using standard PCR techniques. For individual cDNAs generated, primer sequences and annealing temperature are given in table 1 . Resulting PCR products were ligated into appropriate vectors and their nucleotide sequence determined by automated sequence analysis (Waikato DNA Sequencing Facility; The University of Waikato; Hamilton, New Zealand). These sequences were compared with known sequences to confirm identity using the GAP program of GCG (Wisconsin Package Version 10.2, Genetics Computer Group; Madison, Wisconsin). All sequences were >80% identical to those listed as reference sequences in table 1 indicating that the ovine homologue of the respective genes had been obtained. Table 1 GenBank reference numbers used for primer design, primer sequences, annealing temperatures, and GenBank accession numbers for the resulting ovine sequence for the various genes amplified. Gene Reference: (Genbank #) Forward Primer (5' to 3') Reverse Primer (5' to 3') Annealing temperature Genbank # (resulting sequence) TGF-β1 NM_011577 ggaattcatgccgccctcggggctgcgg (EcoR I site and bases 867–888) ggtctagatcagctgcacttgcaggagcg (Xba I site and bases 2040–2020) 63°C ND TGF-β2 M19154 ggaattcatgcactactgtgtgctgagc (EcoR I site and bases 468–488) ggtctagagctgcatttrcaagacttkac (Xba I site and bases 1794–1773) 64°C AY656797 TGF-β3 J03241 ggaattcgcaaagggctctggtggtcctgg (EcoR I site and bases 277–299) ggtctagaccagttctcctccaagttgcgg (Xba I site and bases 1206–1186) 62°C AY656798 TGFβRI U97485 cacagatgggctttgctttg (bases 180–199) ccttgggtaccaactatctc (bases 1007–988) 50°C AY656799 TGFβRII S69114 gtcctgtggacgcgcat (bases 80–97) aggagcacatgaagaaagtc (bases 449–430)* 50°C AY656800 TGFβRII (for PCR) various gccaacaacatcaaccac gggtcrtggtcccagca 53°C AY751461 TGFβRII (internal for PCR) AY751461 tcgccgaggtctacaagg atgccctggtggttgagc 55°C N/A * Sequence is based on the corresponding ovine sequence obtained from an ovine est clone. ND, the complete sequence of the clone was not determined, as the ovine TGF-β1 sequence is known. The clone was sequenced from both ends and resulting sequence compared to the known ovine TGF-β1 sequence to confirm identity of the isolated cDNA. N/A as the sequence overlaps that of AY751461. Collection of tissue samples All experiments were performed in accordance with the 1999 Animal Welfare Act Regulations of New Zealand. All animals had ad lib access to pasture and water and lambs were kept with their mothers until just prior to tissue collection. Romney ewes and lambs were killed by administration of a barbiturate overdose (Pentobarbitone; 200 mg/kg, Southern Veterinary Supplies, Christchurch, New Zealand). Recovered ovaries were fixed in 4% (w/v) phosphate-buffered paraformaldehyde and embedded in paraffin wax. In Situ Hybridization Cellular localization of mRNAs was determined using the in situ hybridization protocol described previously with minor modifications [ 28 ]. Sense and anti-sense RNA probes were generated from cDNA encoding the gene of interest with T7, T3 or SP6 RNA polymerase using the Riboprobe combination system (Promega, Dade Behring Diagnostics Ltd., Auckland, New Zealand). For all in situ hybridizations, 4–6 μm tissue sections were incubated overnight at 55°C with 45,000 cpm/μl (approximately 48,000 dpm/μl) of 33 P-labelled antisense RNA. Non-specific hybridization of RNA was removed by RNase A digestion followed by stringent washes (2 × SSC, 50% formamide, 65°C and 0.2 × SSC at 37°C). Following washing, sections were dehydrated, air dried and coated with autoradiographic emulsion (LM-1 emulsion; Amersham Pharmacia Biotech, New Zealand). Emulsion-coated slides were exposed at 4°C for 3 weeks, developed for 3 1/2 minutes in D19 developer (Eastman Kodak, Rochester, NY), development was stopped using a 1 minute incubation in 1% acetic acid and slides were fixed with a 10 minute incubation in Ilfofix II (Ilford Limited, Cheshire, England). Sections were stained with hematoxylin and then viewed and photographed using both light and dark field illumination on an Olympus BX-50 microscope (Olympus New Zealand Ltd., Lower Hutt, New Zealand). Non-specific hybridization was monitored by hybridizing at least two tissue sections from each age group (lamb and adult) with approximately equal concentrations of the sense RNA for each gene. Hybridization was considered to be specific when the intensity of silver grains, as measured by visual assessment, over a cellular type was greater than that observed in the area of the slide not containing tissue. For all genes, hybridization of the sense RNA over the tissue section was similar or lower in intensity to that observed on the areas of the slide not containing tissue of both the sense and antisense hybridized slides and thus was considered non-specific. Follicular classification Classification of follicles was based on the system outlined by Lundy et al. [ 29 ]. Briefly, type 1/1a follicles consist of an oocyte surrounded by a single layer of flattened or mixed flattened and cuboidal cells. Type 2 follicles contain 1 < 2 layers of cuboidal granulosa cells whereas type 3 follicles contain 2 < 4 layers of cuboidal granulosa cells. Type 4 follicles have >4 layers of granulosa cells and a well defined theca but have not yet formed an antrum. Type 5 follicles have multiple layers of granulosa cells, a well defined theca and a defined antrum. All follicles with signs of degeneration (i.e. pyknotic granulosa cells, lack of a distinct basement membrane or degenerate oocytes) were excluded from the study. Ovarian sections from a minimum of eight animals, including at least three lambs and three adults, were examined for each gene studied. In addition, each follicle class was observed in a minimum of three animals. No differences in expression patterns between lamb and adults ovaries were noted in this study. Granulosa cell culture Ovaries were collected from ewes following slaughter at the local abattoir, transported back to the laboratory at room temperature, washed in 3% bleach solution in PBS for 5 minutes, rinsed twice in PBS and stored in Leibovitz media containing 0.1% BSA, 100 U/ml penicillin and 100 μg/ml streptomycin. Follicles approximately 1–2 mm in diameter were dissected away from the ovaries and stored in Leibovitz media until collection of granulosa cells. The granulosa cells were collected by cutting follicles in half followed by manual scraping of cells from the follicular wall using a wire loop. Oocytes and follicular debris were removed from the cells using a micro-glass pipette. Remaining cells were collected by centrifugation at 300 g for 5 min at room temperature, washed once in 5 mls Leibovitz media, twice in 5 mls McCoys media (Sigma, Auckland, New Zealand) with 100 U/ml penicillin, 100 μg/ml streptomycin and 2 mM GlutaMAX-1 and resuspended using a syringe and needle. Cell viability was determined using trypan blue exclusion and 100,000 viable cells per well (250 μl total volume) were added in McCoys media containing 100 U/ml penicillin, 100 μg/ml streptomycin, 2 mM GlutaMAX-1, 5 ng/ml selenium (Sigma), 10 ng/ml insulin (Sigma), 5 μg/ml apo-transferrin (Sigma), 30 ng/ml androstenedione (Sigma), 3 ng/ml ovine FSH (purified in our laboratory; 1.4 X USDA-oFSH-19-SIAFP RP2), 1 ng/ml IGF-1 (Long-R3, GroPep, Adelaide, SA 5000, Australia) with varying doses (0–10 ng/ml) of purified human TGF-β1 and recombinant human TGF-β2 (R & D Systems, Minneapolis, MN). Cells were cultured at 37°C in a 5% CO2 incubator. Every 48 hours, 200 μl of media was removed from each well and replaced with 200 μl of warmed media that had been prepared at the start of the culture and stored at 4°C. Media samples from the last 48 hours of treatment were collected on day 6 of treatment and frozen at -20°C for later determination of progesterone concentrations by RIA. Unattached cells were removed by 2 washes with McCoys media at 37°C. Attached cells were lysed by incubating cells at 37°C in 100 μl distilled water for 1–2 hours followed by freezing at -70°C. All treatments were performed at least in triplicate with three independent pools of granulosa cells. Within an assay, individual values outside of 20% of the mean value for the treatment were discarded. Points in which at least 2 of the replicates were not within 20% of each other were regarded as missing data. This occurred for the 10 ng TGF-β1 measure of DNA in a single pool of granulosa cells. Measurement of DNA The amount of DNA present in each well was determined by comparing binding of Hoechst 33258 dye (Sigma, final concentration in well of 10 μg/ml) in samples to calf thymus DNA standard measured with a Wallac 1420 plate reader at 350 nm for excitation and 460 nm for emission. Sensitivity of the assay (+ two SD of control buffer value) was 33 ng per well and the intra- and inter-assay co-efficients of variation (CV), based on variability of the 100, 250, 1000 and 2500 ng standard curve points were 3.9% and 8.8%, respectively. No samples were below the sensitivity of the assay. Measurement of Progesterone Concentrations of progesterone in media were determined by RIA as described [ 30 ]. The sensitivity of the assay (90% maximum binding) was 13 pg/ml and the intra- and inter-assay CV, averaged for a standard pool sample at approximately 20%, 50% and 80% binding, was 8.3% and 19.7%, respectively. No samples were below the sensitivity of the assay. Determination of expression of TGFβRII mRNA in cultured granulosa cells Granulosa cells were collected as described above and either frozen immediately after collection or plated in 6 well culture dishes at a density of 1.0–1.5 × 10 6 viable cells per well in 2 mls of control (i.e. no TGF-β) culture media described above for 48 hours. At this time, unattached cells were removed by washing the wells twice with PBS. RNA was collected using TRIzol according to the manufacturer's instructions. First strand cDNA was produced from total cellular RNA using the SuperScript™ preamplification system for first strand cDNA synthesis. An initial PCR was performed with 4 week old ovary RNA to obtain the ovine sequence of a region of the TGFβRII gene which spans introns 4 and 5 in the human sequence (AY675319) and a second set of primers was designed based on the ovine sequence (see table 1 ). Expression of TGFβRII was determined by PCR using the Qiagen Taq PCR core Kit (Biolab Scientific Limited) and the internal ovine primers listed in table 1 with the following conditions: initial denaturing cycle of 3 minutes at 94°C followed by 40 cycles of denaturing at 94°C for 1 minute, annealing at 55°C for 1 minute and extension at 72°C for 2 minutes and a final extension at 72°C for 10 minutes. cDNA generated from a 4 week old lamb ovary was run as a positive control whereas replacement of cDNA with water was used as a negative control. Expression of TGFβRII was assessed by visualization of DNA bands of the correct size following gel electrophoresis. Identity of product was confirmed by sequencing. Statistical analysis Concentration of progesterone per μg DNA was calculated for individual wells before averaging for each treatment within each assay. Points in which at least 2 of the replicates were not within 30% of each other were regarded as missing data. Changes in the concentrations of progesterone in media and DNA content after culture were analysed with the general linear model procedure of SAS. Replicate was included in the model as baseline progesterone and DNA values varied among the granulosa cell pools. Differences between least square means were evaluated using least significant differences and were considered significant when p < 0.05. Data presented are least square means. The standard errors of least square means were 0.7 ng/well, 0.2 μg/well and 0.5 ng/μg for progesterone, DNA and p4 per DNA, respectively. Results In situ hybridization TGF-β1 The mRNA for TGF-β1 was not observed in granulosa cells or oocytes of any follicles (Figure 1a,1b , table 2 ). However, TGF-β1 mRNA was observed in stromal and/or thecal cells of type 3 follicles, in the theca interna of type 4 and 5 follicles and also in the stroma and cells of the vascular system. Within the theca interna, the cells closest to the basement membrane usually had more intense signal than those further away (Figure 1a,1b ). Figure 1 Localization of expression of mRNA encoding TGF-βs in ovine ovaries. Panels a and b contain corresponding light field and dark field views of a type 5 follicle from an adult ewe hybridized to TGF-β1 antisense RNA. Silver grains indicating hybridization of the TGF-β1 antisense RNA are observed concentrated in thecal (t) cells close to the basement membrane with no specific hybridization observed in either the granulosa cells (gc) or oocyte (o). The inset in panel b contains a dark field view of the same area of the tissue hybridized to the TGF-β1 sense RNA. Note the lack of specific concentration of silver grains over any cellular type. Panels c and d contain several type 5 (5) follicles and a type 4 (4) follicle in a 4 week old lamb hybridized to TGF-β2 antisense RNA. Note the lack of hybridization in the oocytes and granulosa cells of the type 4 and 5 follicles and the concentration of silver grains in thecal cells around the follicles as well as the stromal cells between the follicles and scattered cells of the surface epithelium (se). Observe the equal distribution of silver grains over the thecal cells. The inset in panel d contains a dark field view of the same area of the tissue hybridized to the TGF-β2 sense RNA. Note the lack of specific concentration of silver grains over any cellular type. Panels e and f contain corresponding light field and dark field views of an ovarian section obtained from an adult ewe hybridized to TGF-β3 antisense RNA. There is a lack of hybridization in the section including the granulosa and thecal cells of the types 4 (4) and 5 follicle (5) as well as the oocyte of the type 4 follicle, stroma tissue and the surface epithelium (SE). Panels g and h contain light field and dark field views of a blood vessel (v) from an adult ewe hybridized to TGF-β3 antisense RNA. Observe the specific hybridization in the wall of the vessel (v ). Panel i contains a dark field view of the same area of the tissue hybridized to TGF-β3 sense RNA. Note the lack of specific concentration of silver grains over any cellular type. Scale bar equals approximately 100 μm for all panels. Table 2 Summary of expression of mRNA encoding TGF-βs and receptors in ovine ovary. Gene Follicular type Stroma Vascular System 1/1a 2 3 4 5 TGFβ1 - - t t t + + TGFβ2 - - t t t + + TGFβ3 - - - - - - + TGFβRI o o o, gc, t o, gc, t o, gc, t + + TGFβRII - - t t t + + +, expression observed; -, expression not observed; o, oocyte; gc, granulosa; t, theca TGF-β2 The pattern of expression of mRNA encoding TGF-β2 was similar to that observed for TGF-β1, with hybridization limited to the thecal cells of type 3 and larger follicles (Figure 1c,1d , table 2 ). However, hybridization within the thecal layer appeared evenly distributed in contrast to the signal for TGF-β1 (compare panels a, b and c, d in Figure 1 ). Expression of TGF-β2 mRNA was also observed in some surface epithelium and stromal cells as well as cells associated with the vascular system. TGF-β3 Expression of TGF-β3 mRNA was exclusive to cells associated with the vascular system of the ovary. Expression was not observed in the granulosa, theca, or oocyte of any follicle examined (Figure 1e,1f,1g,1h,1i , table 2 ). TGFβRI Expression of TGFβRI mRNA was observed in oocytes of all types of follicles (Figure 2a,2b,2c,2d , table 2 ). Granulosa and thecal cells of type 3 and larger follicles also expressed TGFβRI mRNA (Figure 2c,2d ). Signal was also observed in the surface epithelium, stromal cells (Figure 2a,2b,2c,2d and luteal tissue (data not shown). Figure 2 Localization of expression of mRNA encoding TGF-β receptors in ovine ovaries. Panels a and b contain corresponding light field and dark field views of several small follicles from a 4 week old lamb following hybridization to the TGFβRI antisense RNA. Note specific hybridization in the oocytes of types 1/1a follicles (1) and type 2 follicles. Observe that some cells of the surface epithelium also express TGFβRI. Panels c and d contain corresponding light field and dark field views of a type 5 follicle from a 4 week old lamb following hybridization to the TGFβRI antisense RNA. Note the hybridization signal in the granulosa (gc), theca (t) and oocyte (o) of the type 5 follicle. Signal was also observed in many stromal cells. The inset in panel d contains a dark field view of the same area of the tissue hybridized to TGFβRI sense RNA. Observe the lack of specific concentration of silver grains over any cellular type. Panels e and f contain corresponding light field and dark field views of several small follicles from a 4 week old lamb following hybridization to the TGFβRII antisense RNA. Note the lack of specific hybridization in the type 1/1a and 2 follicles. Expression was observed in the theca of type 4 and 5 follicles however, note the lack of expression in the granulosa cells and oocytes of these follicles. Note also that some cells of the surface epithelium also express TGFβRII. The insert in panel f contains a dark field view of the same area of the tissue hybridized to TGFβRII sense RNA. Note the lack of specific concentration of silver grains over any cellular type. Panels g and h contain corresponding light field and dark field views of a type 5 follicle as well as several type 1/1a follicles from a 4 week old lamb ovary hybridized to the TGFβRII antisense RNA. Note that hybridization is limited to the theca (t) of the type 5 follicle and several stromal cells and is not observed in the granulosa cells (gc) or oocyte (o) of the type 5 follicle. In addition, signal is observed in the stroma around the type 1/1a follicles (1) but is not observed in the type 1/1a follicles. Scale bar equals approximately 100 μm for all panels. TGFβRII Expression of TGFβRII mRNA was not observed in types 1,1a or 2 follicles (Figure 2e,2f,2g,2h , table 2 ). Also, in larger follicles TGFβRII mRNA was not detected in granulosa cells or oocytes (Figure 2e,2f,2g,2h ). In type 3 and larger follicles, expression of TGFβRII was localized to the theca interna (Figure 2e,2f,2g,2h , table 2 ). As was observed with TGF-β1, expression of TGFβRII within the theca was most intense in the cells adjacent to the basement membrane (Figure 2e,2f,2g,2h ). Signal was also observed in some cells of the surface epithelium (Figure 2e,2f ), and in stroma (Figure 2e,2f,2g,2h ) and luteal tissue (data not shown). Effects of TGF-βs on granulosa cell function in vitro and expression of TGFBRII in cultured cells Both TGF-β1 and TGF-β2 inhibited progesterone synthesis of cultured granulosa cells, whether expressed as a function of number of cells placed in culture (Figure 3 , top panel) or as a function of DNA content at the end of culture (Figure 3 , bottom panel) with significant affects observed with as little as 0.1 ng/ml of either TGF-β. Treatment with either TGF-β also reduced DNA content at the termination of culture (Figure 3 , middle panel). For both variables, no differences were observed between the effect of TGF-β1 and TGF-β2 at any dose of growth factor tested. In contrast to the lack of detectable expression of the TGFβRII mRNA observed in situ , freshly isolated or cultured granulosa cells expressed mRNA for the TGFβRII when assessed by RT-PCR (Figure 4 ). Figure 3 Effects of TGFβs on granulosa cell function. Effects of TGF-β1 and TGF-β2 on secretion of progesterone during the last 48 hours of culture (top), content of DNA at the termination of culture (middle) and progesterone concentration per μg of DNA. Values are expressed as the LS mean from 3 separate experiments. The dose of either TGF-β1 or TGF-β2 is indicated along the bottom of the graphs. For each variable, asterisk(s) indicates values that are different from the control (0) value (* p < 0.05; p < 0.01, * p < 0.001). Comparisons were also made between the values obtained for TGF-β1 and TGF-β2 at each dose; however, no significant differences were observed at any dose tested. Figure 4 Expression of TGFβRII in cultured granulosa cells. Determination of expression of TGFβRII in granulosa cells immediately following collection and following 48 hours of culture. Lanes 1–3 contain PCR products (766 bases) following amplification with ovine TGFβRII primers from 3 separate pools of granulosa cells at the time of collection, lanes 4–6 contain PCR products (766 bases) following amplification with ovine TGFβRII primers from 3 separate pools of granulosa cells collected 48 hours after culture, lane 7 contains the negative control water blank whereas lane 8 contains the PCR product from the positive control 4 week old ovary sample. Migration of DNA molecular weight standards are indicated on the left hand side. Discussion In the ewe, expression of TGF-β1 and TGF-β2 mRNA in the follicle was limited to thecal cells during all stages of follicular growth examined. Furthermore, expression of TGF-β3 mRNA was not observed in any follicular cells. This is in contrast to the observed expression patterns for these proteins in other species where TGF-β1 and TGF-β2 have been localized to granulosa as well as thecal cells and sometimes also to the oocytes of many species [ 8 , 12 , 13 , 31 - 33 ]. Also in contrast to sheep, expression of TGF-β3 in cattle and cats was observed in the oocyte, theca and granulosa of follicles at various stages of development [ 12 , 13 ]. In pigs, the theca interna has been proposed to be the major source of TGF-β since granulosa cells express TGF-β1 mRNA without seeming to make the protein [ 11 ]. Similarly, expression of TGF-β2 mRNA has been observed in bovine oocytes, but no detectable TGF-β activity was observed [ 17 ], although other studies have demonstrated TGF-β protein in the oocytes using immunocytochemistry [ 12 ]. In addition, granulosa cells isolated from pigs and cattle produce little if any TGFβ bioactivity when cultured in vitro [ 9 , 11 ]. Thus, it seems likely that in some species, follicular TGF-β activity originates primarily from the thecal cells, with control of activity possibly occurring at several levels including gene transcription (this study), protein translation [ 11 ] or activation of the protein [ 17 ]. Similar to what has been observed in other species [ 32 , 34 , 35 ], expression of TGFβRI mRNA was observed in several different cell-types of the sheep ovary including the oocyte, granulosa cells, thecal cells, stroma, luteal cells and surface epithelium. While expression of TGFβRII mRNA was also observed in stroma, luteal cells and the surface epithelium, its expression within the follicle was limited to the theca. A similar pattern of expression for the TGFβRII mRNA was observed in mouse follicles, with expression most prominent in the theca and barely detectable in granulosa cells [ 8 ]. However, using immunocytochemistry, strong staining for TGFβRII has been observed in granulosa cells with no to little staining in oocytes and in the theca in other species [ 13 , 32 , 35 - 37 ]. The reasons for these observed differences in localization of the TGFβRII are uncertain but may be due to differences in techniques or species differences. Expression of mRNA encoding all three TGF-β isoforms and the TGF-β type I and II receptors were observed in cells associated with blood vessels and both receptor types and TGF-β1 and 2 mRNAs were observed in the stroma surrounding follicles indicating a potential role for TGF-β in regulating certain functions in the ovarian stroma and vascular network. TGF-β is known to be important in regulating angiogenesis [ 38 , 39 ]. Moreover, in the ovary, both TGF-β1 and TGF-β3 mRNAs are upregulated during revascularization following autotransplantation of rat ovaries [ 40 ] further supporting a role for these factors in regulating vascular function. The much more restricted pattern of expression of TGFβRII mRNA in sheep indicates that the TGFβRI may well be involved with other type II receptors in the signalling of other members of the transforming growth factor family. In agreement with this, TGFβRI has recently been shown to be involved in signalling of the oocyte-derived GDF-9 along with BMPRII [ 41 , 42 ]. In other species, GDF-9 has been shown to regulate granulosa cell mitosis and differentiation [ 6 ] and has been shown to be essential for normal follicular growth and development in both mice [ 43 ] and sheep [ 44 , 45 ]. Thus, expression of TGFβRI mRNA as well as BMPRII [ 46 , 47 ] in granulosa cells is probably mediating the effects of GDF-9. Localization of both of these receptors in granulosa cells from the type 3 (secondary) stage of development onwards is consistent with the presence of normal primary but not secondary follicles in both sheep [ 44 ] and mice [ 43 ] lacking biologically active GDF-9. Interestingly, in sheep, TGFβRI mRNA and BMPRII [ 46 , 47 ] are also both localized in oocytes from the type 1 (primordial) stage onwards suggesting that GDF-9 may also regulate oocyte function in this species. The suppression of progesterone production and DNA content in granulosa cell cultures by TGF-β1 or TGF-β2 is similar to inhibitory to mild stimulatory effects observed in bovine, ovine and porcine granulosa cell cultures and contrary to the strong stimulatory effects observed in rodents [ 11 , 14 - 18 , 20 - 26 ]. The decreased DNA content observed following treatment accounts for some, but not all, of the decrease observed in progesterone concentration in the granulosa cell cultures. The suppression of progesterone synthesis indicates an anti-differentiative role for this growth factor as has been observed for other members of the TGF-β superfamily. The decreased content of DNA observed following culture could be related to a suppression of granulosa cell proliferation or survival. Since TGF-β can stimulate apoptotic pathways in concert with other factors [ 48 , 49 ], a role for TGF-β in regulating apoptosis of ovarian cells has been proposed. No differences in the efficacy of TGF-β1 and TGF-β2 were observed in ovine granulosa cells. Similarly, TGF-β1 and TGF-β2 were equally efficacious in stimulating inhibin production in luteinized human granulosa cells [ 50 ] and in modulating gonadotrophin receptor expression in both rat and porcine granulosa cells [ 51 ]. Interestingly, while both TGF-β1 and TGF-β2 mRNA were synthesized by the theca interna, their spatial patterning within the theca was quite different. TGF-β1 mRNA was concentrated in the thecal cells closest to the basement membrane, similar to the localization observed for the TGFβRII mRNA. In contrast, TGF-β2 mRNA expression was observed throughout the thecal layer. The role, if any, of the apparent differential regulation of these two isoforms in subtypes of thecal cells is currently unknown. Given the potent effects of both TGF-β1 and TGF-β2 on granulosa cell function in vitro , the lack of detectable expression of TGFβRII mRNA in these cells using in situ hybridization was very surprising. There are several potential explanations for these apparent conflicting results. It is possible that TGFβRII is expressed in ovine granulosa cells and the technique utilized simply failed to detect this message. The detection of mRNA encoding TGFβRII in isolated granulosa cells both before and after culture using RT-PCR would seem to support this assumption. However, it is possible that the isolation and culture of the granulosa cells potentially could be inducing expression of TGFβRII as most all cells in culture express TGFβRII [ 52 ]. In addition, strong expression of TGFβRII mRNA in luteal tissue is also consistent with up regulation of the TGFβRII in these cells as induction of progesterone synthesis by the ovine granulosa cells can be considered to indicate at least a partial luteinization of these cells. Finally, it is also possible that TGFβs are using another member of the type II receptor family to mediate their effects. The existence of a second type II receptor capable of mediating TGF-β effects is supported by the inability of cell lines expressing TGFβRII to bind to TGFβ2 but not TGFβ1 [ 53 ] and cell lines responsive to TGF-β without a detectible type II TGFβR [ 52 ]. Conclusions Expression of mRNAs encoding TGF-β1 and TGF-β2 as well as both type I and II TGF-β receptors were observed in the theca of small growing follicles indicating that TGF-βs may be regulating thecal cell function in an autocrine manner. Expression of mRNA encoding TGF-β type I and II receptors is also observed in luteal cells, stroma, the vascular system and surface epithelium suggesting that TGF-βs may also regulate other cell types in the sheep ovary. Since granulosa cells showed no evidence of expressing any of the TGF-β ligands and expression of the TGF-β type II receptor was equivocal, it seems likely that any TGF-β effects in granulosa cells in vivo are due to paracrine or endocrine actions and possibly regulated through an alternative type II receptor. Authors' contributions AHB, LDQ and LJH cloned the ovine TGF-βs and receptors, completed sequencing projects and alignments, and performed the in situ hybridizations and PCRs. SL and KLR performed the granulosa cell bioassays including progesterone and DNA measurements. JLJ and KPM designed and co-ordinated the experiments, performed statistical analysis and drafted the manuscript. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539244.xml
490028	Genome-Wide Survey of Cohesin: A Molecular Guardian of Genomic Fidelity	null	At a fundamental level, the continuity of life depends on cell division. Humans generate many millions of cells per second just to stay alive, with most cell types dividing and multiplying repeatedly during a lifetime. Details of cell division vary from cell to cell and organism to organism, but certain features are universal, including what is arguably a cell's most crucial task: the faithful duplication and segregation of its genetic material. During mitosis, a cell copies its nuclear DNA, then splits into two identical daughter cells, a process that involves moving the replicated chromosomes (called sister chromatids) toward opposite ends of the cell. After chromosomes replicate, a protein complex called cohesin binds the sister chromatids together. Cohesion helps the cell distinguish between the copies, which in turn aids proper distribution. Improper sister chromatid segregation can yield an abnormal number of chromosomes (called aneuploidy) in the daughter cells, a condition associated with cancer. During meiosis—the cell division that produces egg and sperm cells—aneuploidy causes a number of congenital disorders, including Down's syndrome. PeakFinder automates identification of peaks in ChIP data To end up in their appropriate positions, sister chromatids must establish attachments to tentacle-like protein polymers called spindle microtubules, which emanate from spindle poles at opposite ends of a cell. Cohesion between the chromatids makes these bipolar attachments possible and keeps sister chromatids from separating after they attach to the spindle. Cohesion occurs along the length of a chromosome and is particularly strong around centromeres, the pinched region of a chromosome. Centromeres, in turn, assemble another protein complex called the kinetochore, which mediates the attachment of chromosomes to spindle microtubules; together, they guide chromosomes to their respective destinations. Cohesin's binding locations were discovered by removing chromatin—the mass of DNA and proteins that forms chromosomes—from cells, and purifying the regions associated with cohesin. These studies looked at cohesin's binding distribution either genome-wide or at select regions of a few chromosomes. Here, two research groups use a similar approach to provide a broader picture in their analysis of cohesin binding in the budding yeast Saccharomyces cerevisiae , a favorite system for cell biologists. In the first paper, Jennifer Gerton and colleagues generated a map for the entire yeast genome of locations where cohesin binds to chromosomes during meiosis and mitosis. In the second paper, Paul Megee and colleagues found that centromeres attract large concentrations of cohesin to their flanks and that the assembly of these cohesin domains is mediated by centromere–kinetochore complexes. Gerton's group reports that large regions surrounding centromeres have “intense” cohesin binding. These binding sites correlate with DNA base composition—DNA is composed of four chemical bases, or nucleotides, that are referred to as A, C, G, and T—showing a strong association with AT-rich regions. In meiotic chromosomes, cohesin binding sites are interspersed between the DNA double-strand breaks that initiate the exchange of genetic information characteristic of meiosis, perhaps keeping the chromatids attached without interfering with genetic recombination. Most striking, the authors note, is the observation that cohesin binding changes according to the cell's gene transcription program. Cohesin prefers DNA that lies between active transcription zones and is unceremoniously displaced from regions where RNA transcripts are being made (a process called elongation). This suggests that elongation through a region and cohesion binding may be incompatible. These observations support previous work indicating that DNA sequences required for the replication and segregation of chromosomes must be protected from transcription to function properly. Whatever the explanation, this finding begs the question of how more complicated genomes can accommodate these two seemingly contradictory processes. Megee's group investigated whether all yeast chromosomes have these large centromere-flanking cohesin regions and whether the centromeres and DNA sequences that surround them somehow facilitate the assembly of cohesin complexes. By removing centromeres and generating cells incapable of assembling kinetochores, the researchers show that the assembly of these cohesin regions is mediated solely by the centromere–kinetochore complex. What's more, inserting centromeric DNA sequences in abnormal chromosomal locations produced new cohesin-assembling regions around these “neo” centromeres. The kinetochores' influence appears to stretch over tens of thousands of DNA bases and serves chromatid segregation in two crucial ways: by recruiting high levels of cohesin to centromeres' sides, which attaches chromatids to their bipolar spindles, and by attaching chromatids to microtubules, which provides their passage to the cell's opposite sides. The maintenance of genomic integrity, the authors conclude, likely relies on the coordination of these essential functions.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC490028.xml
548319	Iron homeostasis in neuronal cells: a role for IREG1	Background Iron is necessary for neuronal function but in excess generates neurodegeneration. Although most of the components of the iron homeostasis machinery have been described in neurons, little is known about the particulars of their iron homeostasis. In this work we characterized the response of SH-SY5Y neuroblastoma cells and hippocampal neurons to a model of progressive iron accumulation. Results We found that iron accumulation killed a large proportion of cells, but a sub-population became resistant to iron. The surviving cells evoked an adaptative response consisting of increased synthesis of the iron-storage protein ferritin and the iron export transporter IREG1, and decreased synthesis of the iron import transporter DMT1. Increased expression of IREG1 was further substantiated by immunocytochemistry and iron efflux experiments. IREG1 expression directly correlated with iron content in SH-SY5Y and hippocampal cells. Similarly, a high correlation was found between IREG1 expression and the rate of iron efflux from SH-SY5Y cells. Conclusions Neuronal survival of iron accumulation associates with increased expression of the efflux transporter IREG1. Thus, the capacity of neurons to express IREG1 may be one of the clues to iron accumulation survival.	Background Because of its intense oxidative metabolism, the brain consumes a high fraction of total oxygen generating large amounts of reactive oxygen species [ 1 , 2 ]. Although brain antioxidant defenses function properly during most of human life, a number of neurodegenerative processes which involve redox-active iron accumulation become evident with age [ 3 - 5 ]. Iron is a pro-oxidant that in the reductive intracellular environment catalyses hydroxyl radical formation through the Fenton reaction [ 6 ]. At present, the crucial components of the iron homeostasis machinery have been identified. Thus, current efforts should be directed to the understanding of the mechanisms that regulate cellular iron levels and antioxidant defenses. This is of primary importance for the development of strategies to ameliorate iron accumulation and oxidative damage in neurons. In vertebrates, cellular iron levels are post-transcriptionally controlled by the activity of iron regulatory proteins (IRP1 and IRP2), cytosolic proteins that bind to structural elements called iron-responsive elements (IREs). IREs are found in the untranslated region of the mRNAs of the major proteins that regulate cellular iron homeostasis: the transferrin receptor, involved in plasma-to-cell iron transport, and the iron-storage protein ferritin. IRP2-/- mice are born normal but in adulthood develop a movement disorder characterized by ataxia, bradykinesia and tremor [ 7 ]. IRP1-/- mice are normal with slight misregulation of iron metabolism in the kidney and brown fat [ 8 ]. Thus, IRP2 seems to dominate the physiological regulation of iron metabolism whereas IRP1 seems to predominate in pathophysiological conditions. Iron is internalized into cells by the import transporter DMT1. Four DMT1 isoforms have been identified that differ in both the N-and the C-termini [ 9 ]. Two of the isoforms have a 3' iron responsive element (IRE) in their mRNA. Additional variation is given by exons 1A and 1B in the 5' end. Expression of DMT1 in response to iron availability follows a pattern similar to transferrin receptor [ 10 ], but its control by the IRE/IRP system is not clear [for review see [ 11 ]]. A new iron transporter, IREG1, also known as ferroportin or MTP1, was recently described [ 12 , 13 ]. The protein is expressed mainly in enterocytes and macrophages [reviewed in [ 14 ]]. In enterocytes IREG1 is responsible for iron efflux during the process of intestinal iron absorption, while in Kupffer cells IREG1 mediates iron export for reutilization by the bone marrow [ 15 ]. The presence of both DMT1 and IREG1 has been described in neurons, glioma cells and astrocytes [ 16 - 18 ]. The presence of IREG1 in neurons opens the possibility that they may be able to down-regulate intracellular iron concentration through its expression. In this study we examined iron homeostasis in SH-SY5Y neuroblastoma cells and hippocampal neurons. We found that iron accumulation killed a large proportion of cells, but a sub-population became resistant to iron accumulation developing an adaptative mechanism intended to decrease intracellular iron content. Results Iron accumulation and cell death Iron accumulation was determined in SH-SY5Y cells grown to confluence and then cultured for two days in media containing from 1.5 to 80 μM iron (Figure 1A ). Total cell iron increased with increasing extracellular iron, reaching a plateau at 40–80 μM Fe (Figure 1B ). The observed increase in cell iron was accompanied by increases in the labile iron pool (Figure 1C ). Iron accumulation indeed caused loss of cell viability, with hippocampal neurons demonstrating higher sensitivity than SH-SY5Y cells to iron treatment (Figure 2 ). Nevertheless, a sub-population of cells survived to high iron concentrations. It was of interest to inquire into the processes underlying this adaptation, since they could help to understand iron accumulation observed in a number of neurodegenerative diseases. Consequently, we characterized the components of the iron homeostasis machine during the process of iron accumulation. Ferritin and DMT1 regulation Ferritin, the main iron-storage protein in mammalian cells, is considered the first line of defense against iron overload. Increasing iron from 1.5 to 5 μM produced a robust 4-fold increase in cell ferritin content (Figure 3A ). Further increases in iron induced additional increases in ferritin. At 80 μM extracellular iron, ferritin increased 11-fold compared to the basal 1.5 μM iron condition. In molar base, ferritin increased more than iron. The iron to ferritin mol : mol ratio decreased from 1500 at 1.5 μM Fe to 400 at 10 μM Fe to 200 at 80 μM Fe (Figure 3B ). We further characterized iron homeostasis in SH-SY5Y cells by examining the expression of the iron importer DMT1 (Figure 4 ). A 3.5-fold decrease in DMT1 protein expression was observed when iron increased from 1.5 to 80 μM. The presence of DMT1 even at high iron concentration explains the sustained iron uptake observed at 80 μM Fe [ 19 ]. Thus, DMT1 activity persisted even under conditions of iron accumulation that preceded cell death. IREG1 expression and functionality Given that the presence of IREG1 in the central nervous system has been reported [[ 16 ]], it was of interest to examine if it participates in neuronal iron homeostasis. Western blot analysis revealed that SH-SY5Y cells expressed anti-IREG1 reactive bands of 65.3 and 122.1 KDa molecular weight (Figure 5A ). Densitometric analysis revealed a 10-fold increase in the 122.1 KDa band in the 1.5 to 80 mM Fe range while the 65.3 band had a minor increase (Figure 5A ). Both bands were eliminated if the antibody was incubated with the immunogenic peptide before the assay (Figure 5B ). A similar pattern was obtained with an independent anti-IREG1 antibody (the kind gift of Dr. David Haile). Thus, it is most likely that the 65.3 and 122.1 KDa bands correspond to the monomer and dimer of IREG1. The stability of the 122.1 KDa band was dependent of the concentration of b-mercaptoethanol in the sample buffer since increasing b-mercaptoethanol produced a shift in the 122.1 KDa /65.3 KDa band ratios (Figure 5C ). It is possible that in neuronal cells Ireg1 tends to form S-S bridged dimers resistant to the electrophoresis conditions. The presence of IREG1 in SH-SY5Y neuroblastoma cells and hippocampal neurons was further documented by immunocytochemistry. IREG1 was detected in both types of cells, with a predominantly cytosolic distribution pattern (Figure 6 ). The levels of IREG1 expression were directly proportional to the amount of iron in the culture. Thus, it was determined by two independent methods that IREG1 expression in neuronal cells increased with cell iron content. Efflux of iron from neurons has never been reported. In view of the presence of IREG1, we tested whether SH-SY5Y cells actually had an iron efflux function. To that end, iron efflux from cells pre-cultured for 2 days with varied iron concentrations was determined by atomic absorption spectrometry. This method was preferred to the use of radioisotopic iron since the latter could underestimate a putative iron efflux because of isotope dilution with the pre-existing iron pool (see Figure 1B ). SH-SY5Y cells had discrete but measurable iron efflux activity (Figure 7A ). The iron efflux rate increased markedly in the 20–80 μM Fe range (Figure 7B ). Interestingly, the efflux rate correlated closely with the presence of the 122.1 KDa band, while the correlation between efflux activity and the 62.5 KDa band was weaker (Figure 7C ). Discussion The number of neurological diseases associated with iron accumulation in the brain underlines the need for increased knowledge of the mechanisms of brain iron homeostasis. In this study we show that iron accumulation by SH-SY5Y neuroblastoma cells and hippocampal neurons resulted in cell death of part of the population, while another fraction survived by adapting the expression of iron homeostasis proteins. Iron content increased significantly as a function of Fe in the culture up to 20–40 μM Fe, increasing very little thereafter up to 80 μM Fe. Cell iron increase was accompanied by increased ferritin content. The increase in ferritin more than compensated for the increase in iron. Iron to ferritin mol ratios of 1500, 260 and 190 were obtained for 1.5, 20 and 80 μM Fe in the culture media. Thus, the IRE/IRP system of SH-SY5Y cells over-responded to iron accumulation in terms of ferritin expression. Despite the increase in ferritin, the LIP increased between 1.5 and 80 μM Fe. This finding clearly indicates that in SH-SY5Y cells the level of labile iron is a function of total iron, even in the presence of ample ferritin supply. It is possible that ferritin-stored iron contributes to the LIP each time that ferritin undergo lisosomal degradation. Iron accumulation was accompanied by a marked decrease in DMT1 expression. Nevertheless, some DMT1 persisted even at 40–80 μM iron. The persistence of DMT1 at high iron concentrations could underline the continuous iron uptake observed under these conditions [ 19 ]. This is curious because at 40–80 μM Fe cells were dying. Sustained DMT1 expression points to the inability of neuronal cells to shut-off iron uptake and the need for additional defense mechanisms to prevent iron-mediated cell death. The discovery of increased IREG1 expression in response to cell iron accumulation is a major break-through in the understanding of cell survival under conditions of iron accumulation. Total IREG1, and especially a putative IREG1 dimer, increased markedly in the 20–80 μM Fe range. Thus, in SH-SY5Y cells IREG1 is up-regulated by increased cell iron. Expressed IREG1 was functional since it associated with increased iron efflux activity. Iron efflux activity in astrocytes [ 18 ] and neurons (this work) indicate that iron efflux from brain cells is a dynamic process, and highlights the importance of iron transporters as determinants of iron accumulation. The regulation of IREG1 expression is unknown but seems to be cell-specific. In enterocytes, IREG1 expression is induced by iron deficiency [ 13 ] while in macrophages iron increases IREG1 expression [ 20 ]. The findings reported here indicate that in neuronal cells IREG1 has a macrophage-like regulation. This is certainly the case for cells in the 40–80 μM range that survived to iron accumulation. IREG1's predominantly cytosolic distribution pattern is similar to that of Kupffer cells [ 12 ]. Again, this distribution points to macrophage-like behavior of neuronal IREG1. In examining brain biopsies from Alzheimer's patients an intriguing question arises: Why do some neurons die or present evident signs of degeneration while others in the vicinity show a normal phenotype? Extrapolating on the data presented here, it is tempting to hypothesize that surviving neurons induce IREG1 expression while sick neurons do not. Nevertheless, at present we cannot exclude that other regulatory molecules may play a pivotal role under these conditions. Conclusions Hippocampal neurons and SH-SY5Y cells displayed an active system to regulate iron content. Nevertheless, this system was unable to block iron accumulation which resulted in death of part of the cell population. Another fraction of the cell population developed an adaptative mechanism that includes decreased expression of the import transporter DMT1 and increased expression of ferritin and the efflux transporter IREG1. The finding that neurons regulate the expression of functional IREG1 opens new avenues for the understanding and possible treatment of iron-related neurodegenerative processes. Methods Antibodies and immunodetection Antibody D-1, prepared against the C-terminal end of the IRE-containing isoform of DMT1 was used as described previously [ 10 ]. Additionally, a rabbit polyclonal antibody against peptide CGPDEKEVTKENQPNTSVV, corresponding to the consensus sequence of human, rat and mouse carboxyl-terminal sequence of IREG1, was obtained from BioSonda, Chile . Western analysis Cell extracts, cells were prepared treating cells with lysis buffer (50 μl per 1 × 106 cells of 10 mM MOPS, pH 7.5, 3 mM MgCl2, 40 mM KCl, 1 mM phenylmethylsulfonyl fluoride, 10 μg/ml leupeptin, 0.5 μg/ml aprotinin, 0.7 μg/ml pepstatin A, 5% glycerol, 1 mM dithiothreitol, 0.1% Triton X-100). The mixture was incubated for 15 min on ice and centrifuged for 10 min at 5,000 × g. Protein concentrations were determined using the bicinchoninic acid (BCA) protein assay. The supernatant was stored at -70°C. For Western analysis, 30 micrograms of protein from each sample were boiled in Laemmli sample buffer for 5 min and subjected to SDS-PAGE on a 7.5% acrylamide gel. Proteins were transferred to nitrocellulose membrane and blocked for 1 hr at 25°C with 5% nonfat dry milk in blocking saline (20 mM Tris, 0.5 M NaCl, 0.05% Tween-20). Membranes were incubated with primary antibody overnight at 4°C, rinsed with blocking saline and incubated with horseradish peroxidase-conjugated anti-rabbit IgG antibody for 1 hr at 25°C. Transferred proteins were detected with a peroxidase-based chemiluminiscence assay kit (SuperSignal, Pierce Chem. Co., Rockford, IL). Chemiluminiscence was detected using a Molecular Imager FX device (Bio-Rad, Hercules, CA). The bands were quantified by densitometry using the Quantity One (Bio-Rad) software. Cell culture and iron challenge Human neuroblastoma SH-SY5Y cells (CRL-2266, American Type Culture Collection Rockville, MD), were seeded at 1 × 105 cells in 2-cm 2 plastic wells and cultured in a 5 % CO 2 incubator in MEM/F12 medium supplemented with 10 % fetal bovine serum and 5 mM glutamine. The medium was replaced every two days. Under these conditions, doubling time was about 48 hours. After 8 days in culture, the culture reached a steady-state number of cells. At this time, cells were challenged with iron for the next two days as described [ 19 ]. In brief, low-iron culture media was supplemented with either 1, 5, 10, 20, 40 or 80 μM Fe 3+ as the complex FeCl 3 -sodium nitrilotriacetate. Cell viability was quantified by the MTT assay (Molecular Probes, OR) following the manufacturer's instructions. This model of iron loading attempts to replicate neuronal iron accumulation that occurs during life [ 4 ]. Hippocampal neurons were prepared from E18.5 rat embryos [ 21 ]. Neurons were plated over poly-L-lysine coated cover slips at 100,000 cells/cm 2 . Cultures were maintained in 10% bovine serum until 3 hours after plating, when the culture medium was replaced with medium containing B27 supplement [ 22 ]. After 3 days in culture, the cells were challenged with iron as described above. Labile iron pool The intracellular labile or reactive iron pool of neuroblastoma cells was determined as described [ 23 , 24 ]. The increase in fluorescence after the addition of SIH chelator is directly proportional to the iron labile pool, i.e., iron in complexes with affinity constant < 10 6 . Immunocytochemistry Cells grown in cover slips were sequentially fixed with 2% and 4% parafolmaldehyde (PFA) in Eagles' MEM, and then washed three times with phosphate-buffered saline (PBS). The fixed cells were permeabilized with Triton-X-100 (0.2%) in PBS at room temperature for 3 min and blocked with defatted milk (10%) in PBS for more than 1 h. The cells were incubated with anti-IREG1 antibody (1:500) overnight at 4°C, washed with PBS and then incubated with Alexa-546-conjugated goat anti-rabbit IgG. The labeled cells were observed with a Zeiss LSM 510 Meta confocal laser scanning microscope. Data analysis Variables were tested in triplicates, and experiments were repeated at least twice. Variability among experiments was <20%. One-way ANOVA was used to test differences in mean values, and Turkey's post-hoc test was used for comparisons (In Stat program from GraphPad Prism). Differences were considered significant if P < 0.05. Authors' contributions MTN conceived of the study, participated in its design and coordination and drafted the manuscript. PA performed the experiments with hippocampal neurons, did the ferritin assays and participated in the analysis and interpretation of data. MN optimized the immunocytochemistry detection of IREG1, performed the confocal microscope observations and participated in the analysis and interpretation of data. VT did the Western blot, labile iron pool and viability assays and contributed to the discussion of the results. MA set up the method to determine total Fe concentration, did the sample and control measures of iron and participated in the analysis and interpretation of data. All coauthors participated in refining the text.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548319.xml
524214	The big problem of the missing cytology slides	Cytology slides are often unique and irreplaceable. Unlike surgical pathology cases, where additional paraffin sections can be cut, cytology slides often cannot be duplicated because there are only a few direct smears or the diagnostic material is present on a single slide. Cytology slides are often "sent out" to other physicians, laboratories or hospitals, typically so that the pathologist at the institution where the patient will receive treatment can review the slides. Less often, a cytology lab sends out the slides for a second opinion or as part of the discovery process in a lawsuit, where they may or may not be defendants. Rarely, unique and irreplaceable cytology slides are lost. This article presents a hypothetical scenario that is based on reported state appellate court decisions. The article discusses some of the legal issues that will affect the defendant cytologist/cytology lab and the "expert cytologist," and suggests some steps a cytologist/cytology lab can take to minimize the risk of repercussions from a lost unique and irreplaceable cytology slide.	1. What is already known on this topic? A WestLaw search (similar to PubMed, but searches state and federal cases and statutes as well as commentary) uncovered only a handful of reported appellate cases that directly applied to the issue of lost cytology slides. There are many cases and statutes dealing with lost and altered evidence (other than cytology slides), but the circumstances surrounding cytology slides are unique. I did not see any previous reviews or commentary specifically addressing the topic. Notwithstanding the relative paucity of on-point legal authority, the issue is one commonly addressed by cytology laboratories and cytologists and many have approached the issue thoughtfully and prudently. 2. What is not highlighted and what this review would answer? This review synthesizes the available legal cases and presents to practicing cytologists a short, relatively concise summary in the format of a hypothetical case. The review seeks to incorporate the legal issues with the practical aspects of running a cytology laboratory. The review answers how some state courts might approach the problem of lost and irreplaceable cytology slides, and offers general ideas to cytologist for minimizing the risk from lost slides. The big problem of the missing cytology slides The issues surrounding the decision whether to send out diagnostic patient slides are more important in cytology than in surgical pathology because the cytology slides are typically unique and irreplaceable. Unlike surgical pathology cases, where additional paraffin sections can be cut, cytology slides often cannot be duplicated because there are only a few direct smears or the diagnostic material is present on a single slide. Slides are routinely "sent out" for a variety of reasons. Most commonly, slides are sent to another institution because the patient's pathology slides will be reviewed before treatment. Some smaller laboratories with only one or two pathologist may send out slides as part of their quality assurance procedures. More rarely, but increasingly, slide's are requested as part of existing or contemplated litigation. Slides might be lost in any of these circumstances. A laboratory or hospital might loose the slides and not discover their absence until the slides are requested. This article will discuss the approach the US legal system takes in addressing what happens when cytology slides are lost, and what steps a prudent laboratory might take to manage the risk. The article also intends to improve cytopathologists' awareness and understanding of some of the legal issues that arise when evidence is missing and perhaps promote an international comparative discussion of alternative legal approaches. In the US, most of medical malpractice law is made and interpreted by state legislatures and state courts. What follows is a hypothetical story based on several legal decisions made by appellate state courts in the United States and reported in the legal literature. Although based on real cases and available to the public, the names have been changed. Importantly, none of this is intended as legal advice and readers should consult their attorney about specific questions. Facts Rugged Labs (RL) is a small, independent laboratory. Part of Rugged Labs' work involves providing Big Giant Lab (BGL) with overflow services for cytopathology. In December of 1995, BGL bought out RL. In 1994 and 1995, a RL cytotechnician interpreted two Pap smears from 30-year-old Ms. Penny as normal. In 1996 a cervical biopsy from Penny showed adenocarcinoma. Ms. Penny underwent a radical hysterectomy, which confirmed the invasive endocervical adenocarcinoma. Ms. Penny is alive today, but endured extended post-operative hospitalization. At the time of the hysterectomy, Penny Plaintiff's oncologist requested that the 1994 and 1995 PAP smear slides be sent to Dr. Experta, who interpreted both Pap smears as containing "abnormal cell groups consistent with adenocarcinoma." Dr. Experta also reviewed the biopsy and in a note concluded that the cells on the Pap smears were consistent with the adenocarcinoma diagnosed on the cervical biopsy. Approximately 6 months later, Plaintiff Penny decided to sue for medical malpractice based on failure to diagnose her endocervical adenocarcinoma on the Pap smears. At some time before the plaintiff filed her lawsuit Dr. Experta's assistant apparently mailed the slides back to BGL. The Pap smear slides are lost, presumably in the mail, by BGL or Dr. Experta's office. RL, the independent laboratory, asked the trial court to grant it summary judgment on the basis that the evidence was lost and no questions of fact remained. Summary judgment means that there are no outstanding questions of fact and the court needs to decide only questions of law. Summary judgment means there is no trial with a jury or judge hearing and weighing evidence. The question of law RL wanted the court to determine on summary judgment was that the lost slides substantially prejudiced RL and summary judgment was, therefore, appropriate. RL included in its motion for summary judgment an affidavit from an expert stating that she could not give an opinion without having the slides to look at. An affidavit by Dr. Experta's secretary stated that the slides were returned to BGL by US mail. BGL submitted an affidavit attesting they did not lose the slides. The parties to the lawsuit stipulated that the slides were lost. The trial court agreed with RL that there should be summary judgment in RL's favor, reasoning that no questions of fact needed to be answered and that a trial would unduly prejudice RL because of the spoliation of evidence. For a summary of the facts, please see Fig. 1. The Appellate Court's Opinion The Plaintiff appealed and the state appellate court reversed the trial court, concluding that the trial court made a mistake in not allowing the case to go to trial. The appeals court reasoned that the case turned on a question of fact; "The slide either showed the presence of cancer cells or it did not." The appellate court envisioned the trial as follows: the cytotechnologist from RL would "testify to her conclusions" and the plaintiff would have Dr. Experta testify to her conclusions. There should be a trial because there were questions of fact including, in the words of the majority, whether the slide had "cancer cells" or not. The majority also discounted the affidavit from BGL, stating that the conclusory statement that BGL had not lost the slides was not valid; just because BGL couldn't find the slides did not mean they never had them. In a footnote, the majority noted that although they aren't accusing anyone, they couldn't help but notice that missing the slides benefited BGL and RL. One judge dissented in the three-judge panel that decided the case. The dissent focused on two points. First, the dissent emphasized that the defendant RL had nothing to do with loosing the slides. Although the plaintiff, Ms. Penny, had no "direct role" in the loss of evidence, the dissent treated Dr. Experta as an agent of the plaintiff and concluded that Dr Experta should have sent the slides back to RL not GBL. The dissent also reasoned that its approach would "encourage experts to treat more carefully evidence delivered into their hands." Secondly, the dissent emphasized that the defendant RL is disadvantaged by the loss of the slide and the plaintiff has gained a significant advantage. The dissent sees a trial where the cytotechnologist's faces a serious credibility problem because her testimony will come across as blatantly self-serving. The cytotech will be limited to "opining that he made no error." Moreover, the fact-finder may conclude that the cytotechnologist is wrong since many may presume that the expert pathologist must be right. Finally, the defendants cannot obtain their own expert to bolster their case, because no cytology slides remain for review. The dissent concludes that summary judgment for RL was proper because the trial court had good reasons to conclude that the lost evidence was going to unduly prejudice the defendant RL. Issues The most obvious issue this case brings up is the difficulty in deciding what to do when it isn't clear who lost the evidence, or when a third party lost the evidence. In contrast, is the situation where one party is responsible for inadvertently losing the evidence or, even worse, where one party deliberately loses or destroys evidence. This is called spoliation of evidence and includes meaningful alteration of the evidence. The court will determine the severity of the sanction for spoliation by the degree of willfulness or bad faith and the extent of the prejudice suffered by the non-responsible party. For example, in one case, surgeons performed a hepatectomy after a small needle core liver biopsy was interpreted as cancer. The hepatectomy specimen showed only cirrhosis and no cancer was found. The small needle liver biopsy was subsequently lost by the hospital. The patient sued for medical malpractice, claiming that the core biopsy was misdiagnosed and lead to an unnecessary hepatectomy. The trial court instructed the jurors that they could "draw the strongest possible inference against [the hospital] as to what the lost cytology slides would have shown." In other words, losing the slide means your opposition can make the slide show whatever they want. Interestingly, in the hepatectomy case, the defendants prevailed by arguing that the diagnosis of cancer and the decision to undergo resection were reasonable, regardless of the cytology results, because the patient had active hepatitis B and a suspicious liver mass on imaging. They argued that even with a negative cytology result the surgeons would have gone ahead with the hepatectomy. But our case is different. Neither party, according to the majority, is responsible for losing the slides, or put another way, either party might be responsible for losing the slides. Several judicial options exist and none are neutral. One is to impose no sanctions and to proceed as usual, only without the slides, as the majority opinion advocated. This likely favors the plaintiff, particularly when there is a subsequent surgical specimen with cancer. A second option is to try to determine which party the court thinks is more prejudiced by the lost slides and then impose a legal remedy, as the trial court did in our hypothetical case by granting summary judgment. The difficulty is that it will not be clear which side is more prejudiced until the slide is recovered. The critical question of whether the negative diagnosis fell below the standard of care can likely be adequately answered only if the parties and their experts can review the slide. A third option might be to not allow Dr. Experta's testimony if the defendant can show that the expert knew or should have known that there was going to be litigation [ 1 ]. Arguably Dr. Experta should have returned the slides with greater care, regardless of whether litigation was contemplated or whether, as it seems in this case, the slides were sent to routinely review pathology slides before treatment. Interestingly, each option leads to a different result based on bias about which party is ultimately more responsible or more likely responsible for loosing the slides and a bias about the standard of care. The majority's opinion included a note that the benefit to BGL from losing the slides can't be ignored, a clear statement that the plaintiff had no responsibility for losing the slides, and a simplistic view about the standard of care reflected by the statement that "the slide either showed the cancer cells or it did not." The majority's subtext is that the plaintiff did nothing wrong and they weren't completely sure about the laboratory. The dissenting opinion, in contrast, treated Dr. Experta as the plaintiff's agent and was dissatisfied that Dr. Experta returned the slide to BGL instead of RL, even though at the time BGL had purchased RL. The dissent also showed a more nuanced understanding of the standard of care, conveying skepticism about Dr. Experta's look back conclusion that the Pap smears were "consistent" with adenocarcinoma. The dissent reasoned that perhaps the cells are consistent with malignancy only in the retroscope and that a defense expert might reasonably conclude that it was "not below the standard of care to determine the biopsy negative" were the slides available for review. Comment The facts often surrounding a cytopathology medical malpractice case are that there is a subsequent biopsy or surgical specimen with a discrepant diagnosis. If, as in the hypothetical Penny vs. GBL , a court does not dismiss the plaintiff's case, the absence of the cytology slide will likely impact the defendant cytologist more adversely because many people will assume that the cancerous cells were on the slide and the cytologist or cytotechnologist missed the cancer, which, after all, was present on the subsequent biopsy. In the hypothetical's facts, this was particularly true since Dr. Experta had already opined that the Paps were "consistent with adenocarcinoma." The defendant cytologist/cytology lab is at a serious disadvantage if the court allows Dr. Experta's opinion as admissible evidence. The majority's comment that GBL benefited from the lost slides and the appellate court's decision to allow the plaintiff to go to trial, suggests the court's bias that they believed Dr Experta's interpretation was the correct one. Admittedly, a cytology lab or cytologist does benefit if slides are lost and the court does not attach any responsibility for losing the slides to the potential laboratory or cytologist defendant, because the plaintiff will not have enough evidence to prevail. Similarly, if the slides are discarded after the legal time periods the likelihood of a successful lawsuit is slim because the plaintiff will not have enough evidence, and the defendant complied with legal requirements regarding slide retention. The hypothetical case of Penny vs GBL differs. Remember that once the court allows the case to go to trial, GBL only benefits from absent slides if the defendant initially misinterpreted the slides. If the slides contained no malignant cells, and Dr. Experta over-interpreted the slides, then GBL is prejudiced by not being able to show the slide. Cytology slides are typically in possession the cytology labs. The slides may be sent out for a variety of reasons, but at least initially the lab has possession of the cytology slides. This is both an advantage and a disadvantage for the lab. The disadvantage is that if slides are lost while in the lab's possession a court will typically see it as the lab's responsibility to safeguard the slides. This allows the plaintiff to have the jury infer whatever is best for the plaintiff's case; that the slide had malignant cells when the cytology diagnosis was benign or that there were only benign cells when the diagnosis was malignant, as in the hepatectomy case. The advantage for the cytology lab is that it is in a position of relative control. The lab can implement a system to help reduce the chances of losing a slide and reduce the risk if a slide is lost. Although the lab may want to employ the help of an attorney experienced in these matters, there are several steps every cytology lab can take. First, the lab should ensure that cytology slides are retained for the time that the current federal CLIA regulations, applicable state regulations and the CAP checklist require. All glass cytology slides must be retained for at least 5 years and fine needle aspiration slides retained for 10 years. (Some state regulations may require longer times.) The CAP checklist also requires policies for "protecting and preserving the integrity and retrieval of original slides in cytopathology" and "to ensure defined handling and documentation of the use, circulation, referral, transfer and receipt of original slides to ensure availability of materials for consultation and legal proceedings." Keeping careful records about when and which slides are released to whom is essential for reducing the risk of losing slides. In the send out cases where slides are sent out for a routine second opinion not sought in contemplation of a law suit or because a patient will be treated elsewhere, the lab might obtain the borrower's explicit written agreement that the borrower has responsibility for the slides with an explicit provision about a duty to indemnify the cytology lab for any losses due to a lost slide or slides. A documented telephone call to request the return of tardy slides may also be worthwhile. In cases where slides are requested in contemplation of a lawsuit, the lab may be able to implement a policy that review of slides is done at the lab, ensuring that the lab retains possession. Alternatively, the lab may pursue or agree to a court order requiring production of the slides that clearly addresses who is responsible for the slides and includes an indemnity clause in the event the slides are lost. It is reasonable to make a distinction between sending out non-reproducible slides to an institution that will treat the patient and sending out non-reproducible slides to the plaintiff's expert witness. It is, therefore, important that the lab understands the purpose for which the slides are requested. A documented telephone conversation may clarify the purpose of the outside review and allow the lab to appropriately "triage" the case. Laboratory administrators should understand that the cytology lab serves a public function in safeguarding cytology slides. Court's have recognized a public policy reason to have the laboratory safeguard slides, in part so that the slides are available in the event of malpractice litigation. At the same time, many states have statutes that give patients the right to examine and copy their medical records (the recent federal HIPAA does the same). These two propositions are not mutually exclusive. One state case considered the question of whether a patient/plaintiff had a right to "immediate possession of pathology slides" and concluded that the plaintiff did not. The court decided that the patient's rights did not exceed the patient's statutory right in the slides. In other words the court was not going to find a common law, or customary, right in the slides that gave the patient a greater right than the applicable statute. The decision noted that the legislative history of the statute included remarks that pathology slides were part of the medical record. The judges then approached the second question about what to do when the "medical record" cannot be duplicated, as with a Pap smear or other cytology slide. In answering this question, the court noted that hospitals and laboratories have public as well as private duties. One of their public duties is to retain slides so that the slides are available in the event of malpractice litigation. This meant that patients do not have a legal right to possess parts of the medical record that cannot be duplicated. The court, however, did not grant the lab complete authority to never release the slides. Since the public policy reason depended fundamentally on preserving slides to help the legal system run smoothly, the decision reminded the laboratory or hospital that, pursuant to the clear terms of a statute, it must send the original slides to a "licensed institution, laboratory or physician" at the patient's written request. The dissent characterized the pivotal issue differently and concluded that the patient had a right to immediate possession because the slides contained the patient's cells and she had the right "to control one's body." The dissent reasoned that recent advancement in genetic science and the accompanying difficult privacy issues raised by genetic information strengthened the patient's right to possession of the cells on the glass slide. The majority addressed this argument and, citing the well known case of Moore vs Regents of the University of California [ 2 ], reminded the reader that no court has recognized that a patient has property rights in cells taken for diagnostic purposes. I mention the dissent to emphasize that the issues surrounding possession and use of glass slides are complex and evolving and it often difficult to predict what a court will say. In summary, lost slides can be a problem for cytology laboratories and cytologists, whether responsible for losing the slides or not. The prudent cytologist will minimize the risk of lost slides, because, as the hypothetical case of Penny v GBL illustrates, lost slides can result in problems for cytologists and the cytopathology laboratory A good place to start is to ensure that existing CLIA regulations, applicable state regulations and other guidelines, such as the CAP checklist, are in place in the laboratory. Thinking about the issue and implementing appropriate risk management strategies with the help of an attorney are also prudent measures. Table 1 The top 10 take home messages 1. Spoliation of evidence includes meaningful alteration of the evidence as well as losing the evidence. 2. A court may look at which party benefits from losing the unique and irreplaceable slides as well as which party was last in possession of the slides and impose appropriate sanctions. 3. One remedy a court may impose on the party responsible for losing the slides is to allow the factfinder, whether jury or judge, to infer that the slides show whatever is best for the opposition's case. 4. Cytologists should adhere to federal, state and respected published checklists regarding how long to keep slides and implement lab policies regarding the circulation and transfer of original slides. 5. A cytology lab should consider calling to find out the reason why a slide is requested so that it can respond appropriately. 6. A cytology laboratory should consider sending unique and irreplaceable cytology slides by registered mail. 7. Some state legislatures and courts recognize a public policy reason for cytology labs to retain and protect cytology slides. 8. Although patients have a right to inspect slides, they typically do not have a legal right to immediate possession. 9. A cytology lab should consider implementing a policy that requires review of the slides at the lab when slide review is in contemplation of a law suit. If this is not possible, then the lab can agree to a court order that clearly spells out who is responsible if slides are lost with indemnification to the lab for lost slides. 10. When in doubt, the prudent cytologist should contact their attorney.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524214.xml
554094	Ultrasound imaging versus morphopathology in cardiovascular diseases. Coronary collateral circulation and atherosclerotic plaque	This review article is aimed at comparing the results of histopathological and clinical imaging studies to assess coronary collateral circulation in humans. The role of collaterals, as emerging from morphological studies in both normal and atherosclerotic coronary vessels, is described; in addition, present role and future perpectives of echocardiographic techniques in assessing collateral circulation are briefly summarized.	In the past 25 years, the concept of a compensatory function of the coronary collaterals (or anastomoses) – i.e. vessels that join different coronary arteries or branches – has been practically cancelled from the mind of cardiologists since cineangiography shows that the onset of coronary heart disease (CHD) occurs independently of their presence. The assumption, therefore, was and is that they have no compensatory meaning [ 1 ] and coronary obstruction causes ischemia. A crucial and questionable assumption which disregards solid and recognized pathological data and supports invasive therapies, the diagnostic gold standard being the coronary cineangiography. In many cardiological centers, at the first chest discomfort, the latter is the guide for emergency angioplasty + stent or surgical bypass when a coronary ostruction is found; with the belief that a severe coronary stenosis causes angina pectoris, its occlusion an acute myocardial infarct (AMI) or sudden death (SD) and chronic ischemia explains hibernating myocardium. By injection under controlled pressure of plastic materials through the aorta, casts of coronary arteries, including coronary ostia, in normal and pathological hearts were obtained. They gave an objective tridimensional view of anatomy, different patterns of coronary distribution and overall collaterals in relation to coronary lumen reduction. The method allowed a histologic control of the myocardium [ 2 - 4 ]. The casts of normal coronary arteries showed a smooth surface without identations easily identified when even a minor lumen reduction was present. In hearts of normal people dead by accident without pathological findings at autopsy, homocoronary (between branches of the same coronary artery) and intercoronary (between different coronary arteries) anastomoses were present everywhere joining at any level the intramural branches. Only in two of more than 600 hearts, superficial collaterals between extramural coronary arteries were seen and sampled for histology. The diameter of the innumerable normal collaterals ranged from 20 (maximal penetration of plastic injection) to 350 microns, frequently assuming a corkscrew aspect, possible adaptation to the contraction cycle of the myocardium (Figure 1 ). The first conclusion was that arterial intramural system, including the terminal bed, is an anastomotic network, at least from the anatomical viewpoint. Figure 1 Coronary anastomoses or collaterals. A) intercoronary ventricular and (B), atrial. C) homocoronary anastomoses. Note the innumerous collaterals joining different intramural branches at any level of their course. They have frequently a corkscrew aspect (D) visible also histologically (E), as adaptation to cardiac contraction-relaxation cycle. In hypertrophic hearts with normal coronary arteries and in normal hearts of patients with chronic hypoxia, e.g. anemia, collateral diameter and length were increased in the whole intramural system (500 microns; Figure 2 ). The more impressive change was seen in presence of coronary stenosis greater than 70% with a diameter and length exceeding 1000 microns and several centimeters respectively (Figure 3 ). The other peculiarity was that collateral enlargement was strictly related to a stenosis filling distal tract of the obstructed vessel ( satellite anastomoses ); when more than one severe stenoses exist each one had its own satellite collaterals. However, an identical obstruction located at the same level of an artery might show relatively few highly enlarged collaterals (the only ones visible by cineangiography), or numerous relatively small collaterals (Figure 4 ). A finding possibly due to a redistribution of blood flow consequent to newly formed severe stenoses or an infarct. In the latter condition, all vessels within the necrotic tissue disappear ( avascular area seen in plastic casts; Figure 5 ) and the surviving collaterals at periphery will further enlarge since the pressure gradient distal to the coronary obstruction persists. Figure 2 Vessel changes in relation to modification of the cardiac mass. A) atrophic heart with acquired serpentoid form of extramural vessels due to cardiac mass reduction, and minor intramural vascularity. The contrary is seen in cardiac hypertrophy (B) in which the extramural arteries increase in length and diameter (but not in number) to adapt themselves to the greater myocardial mass. Similarly, the same enlargement is seen in the intramural branches. Cor pulmonale, in which condition the right ventricle may become greater than the left one, is an extreme example of adaptation of extramural (C) and intramural, including collaterals (D). No histologic evidence exists of new vessel formation. The cardiac vein show a similar behaviour. Figure 3 Collateral enlargement in topographical relation (satellite) with severe stenosis or occlusion. A double occlusion of LAD (anterior view) and occlusion of RCA (posterior view) apparently compensated by enlarged collaterals in a non cardiac patient dead from brain hemorrhage. B, similar condition in cases with RCA occlusion (arrow) without corresponding myocardial infarct with numerous homo and intercoronary collaterals of the anterior wall (C), and (D) septum. Occlusion of LAD without evidence of other stenotic changes of the coronary arteries in a 39-year-old woman with rheumatic heart disease and mitral insufficiency. In this case, arteritis was documented histologically by sampling before corrosion. An acute infarct (avascular area at the apex, arrow) was present. F, a single, high enlarged collateral from LCX, supplying the distal tract of an occluded LAD. Note, numerous normal anastomoses. This indicates that ischemia is not the cause (no diffuse enlargement of all collaterals in the whole ischemic area) but rather pressure gradient induces selective compensatory routes. Figure 4 Different aspects of collateral compensation in presence of the same occlusive pattern of LAD. A, relatively few very enlarged collaterals and (B) numerous relatively small collaterals. This divergency may be due to progressive atherosclerotic obstruction of other main vessels or lost of the intramural vasculature, including collaterals, following an infarct. Chart C shows all the possibilities of flow redistribution. The histology of the enlarged anastomoses corresponds to a capillar-like wall, even in the rare extramural collaterals with rudimentary focal tunica media (C). D), enlarged collaterals in a case of anomalous origin of LAD from the pulmonary artery and (E,G) different aspects of giant capillaries (or plexus) in various stages of an acute/old infarction. The absence of new vessel formation is well documented in recent infarcts associated with endocardial thrombus (G). In the latter numerous new vessels form in the granulation tissue repair of the thrombus in contrast to their absence in infarct (arrow; postmortem coronary injection for vessels identification). Figure 5 Avascular area of an infarct. By plastic cast (A anterior, B posterior view) or postmortem angiogram (C) the infarcted zone (arrow) lacks of intramural vessel injection ("avascular area"). Stretching of the necrotic myocardium and secondary vascular damage with wall degeneration and thrombosis (D), explain this vascular "sequestration" which occurs in early phase. This may indicate a blockage without possibility of therapeutical intervention via blood flow within the infarcted myocardium. Note that the avascular area in this AMI case documented histologically, depended from LAD without evidence of occlusion or severe stenosis. The occluded vessel (arrow) was (B) the RCA, the distal part of which was filled by numerous anastomoses. No myocardial damage was seen in its territory. By dissection even an expert pathologist, the diagnosis could be of myocardial infarction following occlusion of the RCA. E) obliterative intimal hyperplasia in arterioles around a seven days old infarct with early repair process. Another satellite collateral system is annexed around and within the atheroclerotic plaque. Plastic casts and histological serial sections showed an extensive vascularization limited only at plaque level and formed by giant adventitial capillary-like vessels filled by intracoronary radiopaque injected material, connecting secondary branches proximal and distal to the stenosis as well as new vessels formed within the atherosclerotic intima i.e. arterioles, with a well developed tunica media, related to angiomatous plexuses which open in the residual lumen (Figure 6 ). This plaque satellite system may explain why by cineangiography the coronary tract distal to stenosis is immediately filled while in its absence a delay or flow reduction should be expected. Figure 6 Vascularization of a coronary atherosclerotic plaque showing different aspects of neovascularization. By serial sections of postmortem injected plaques, giant advential capillary-like vessels (A) are connected with secondary branches proximal and distal to the plaque and with new arterioles (B) with a well developed tunica media (indication of functioning blood flow), within the thickened, atherosclerotic intima in turn joined through angiomatous plexuses (C) to the residual lumen (D) E) plastic casts of plaques with different aspects of vascularization. Both homo-intercoronary and plaque collateral systems are anatomical structures capable to adapt in particular pathological conditions. The question is whether or not they are able to prevent ischemia and compensate an occlusion which by cineangiography appears as a "cut off" of a vessel without imaging of its distal tract. It must be stressed that in postmortem casts with coronary occlusion the latter was always injected through collaterals. In 87% of AMI patients, within four hours from clinical onset, a cineangiographic occlusion was observed and in 88% of cases undergone emergency bypass surgery, a "layered thrombus" was recovered "proximal to stenosis" [ 5 ]; a thrombus due to plaque rupture [ 6 - 8 ] causing the infarct or sudden death. In discussing this dogma the first need is to review the function of the collaterals. Collateral function Capillary function in presence of normal coronary arteries In normal hearts and in pathologic hearts with normal coronary arteries, the collaterals, due to their capillary structure, participate to the metabolic exchange as terminal capillary bed. This means a much greater extent of the exchange surface which invalidates any "one myocardial / one capillary" model to study the delivery of any substance from capillary to myocardial cell. The myocardial interstitium is crossed by a myriad of "endothelial" vessels in any direction. Compensatory function in presence of coronary obstruction The demonstration of tridimensional collateral enlargement by casts indicates, per se, that there was an increased blood flow. Their adequacy to compensate one or more severe coronary obstructions is documented by the following main facts: 1. At the first episode of coronary heart disease (CHD) in apparently healthy people acting their normal life, 89% with a fatal AMI had one or more (47%) severe atherosclerotic stenosis greater than 70% ;65% of sudden and unexpected death (SUD) showed the same finding in one or more (35%) vessels; 66% of non cardiac patients dead from other diseases and 39% of normal subjects dying from accident had the same severe atherosclerotic stenosis in one or more (40% and 16% respectively) coronary arteries (Table 1 ). At histology, all plaques were old lesions preexisting months or years without any evidence of CHD despite a stressful life and in absence of a myocardial infarct. The only explanation is that the collateral system was able to fully compensate the blood flow reduction consequent to the stenoses. Table 1 Maximal atherosclerotic lumen diameter reduction and number of main arteries with severe (≥ 70%) stenosis Source Acute myocardial infarct Sudden death unexpected Non cardiac atherosclerotic Patients Accidental death in normal people 1st chronic 1st chronic Cases 145 55 133 75 100 97 % Lumen reduction 0 3 - 10 - 7 8 <50 3 1 18 - 10 20 50–69 10 - 18 5 17 31 70–79 30 8 21 8 11 19 80–89 45 11 39 14 24 13 ≥ 90 54 35 27 48 31 6 No. arteries ≥ 70% 1 61 16 40 13 26 22 2 49 22 34 26 18 13 > 3 19 16 13 31 22 3 1 st episode, in apparently normal people without extensive monofocal myocardial fibrosis Chronic, in subjects with history of coronary heart disease and/or extensive myofibrosis. 2. Myocardial infarct size measured planimetrically was not related to the number of severe coronary stenoses found in each AMI case (Table 2 ) as should be. More severe coronary stenoses should determine a higher ischemia resulting in larger infarcts. Table 2 Lack of correlation between number of severe (≥ 70%) coronary stenoses and acute infarct size (% left ventricular mass) in 200 consecutive and selected fatal cases. Source Acute myocardial infarct Cases 200 97 103 ≤ 20 size > 20 Lumen reduction < 69 7 10 ≥ 70 90 93 in 1 39 38 2 37 34 ≥ 3 vessels 14 21 p < 0.05 for trend 3. No relation between the total vascular territory of obstructed coronary artery and infarct size which often extended in territories of non stenosed or occluded vessels. In vivo hypokinetic zones expand in well perfused region [ 9 ]. 4. The relatively frequent finding of a coronary occlusion without an infarct. 5. In an experiment done in a leading dog lab, a controlled coronary stenosis, maintained for few days and then occluded, did not determine any dysfunction or infarct because a dramatic increase of collateral flow [ 10 - 12 ]. These are the main facts supporting the concept that collaterals shown postmortem succeed in limiting or abolishing ischemia induced by coronary obstruction and question the existence of chronic ischemia due to coronary atherosclerosis since a plaque takes time to develop while collaterals [ 10 , 11 ] adapt itself quickly as soon a pressure gradient between stenosis and distal vessel is established. On the other hand, there is no demonstration of a possible failure, both acute or chronic, of collaterals; including spasm since they have not tunica media. The inability of cineangio imaging to visualize collateral systems is explained by its very limited power of resolution of all intramural vessels and by the selective injection of radiopaque labelled blood flow in one coronary artery competing with non labelled flow from the other coronary artery. Only very enlarged intercoronary anastomoses can be seen cineangiographically without any value in relation to cardiac dysfunction. Acute ischemia induced by balloon inflation at angioplasty may depend on sudden occlusion by compression of the collateral plaque system. Active coronary atherosclerotic plaque according to cineangio imaging Active plaque means an impending infarct expressed by a variety of angiographic signs as irregular lumen, haziness with ill-defined margins, smudge appearance, inhomogeneity, opacification, luciencies, persistence of radiopaque material, etc. Signs difficult to correlate with postmortem findings since terminal changes can not be excluded. They may represent the irregular vascularization of the atherosclerotic plaque opacified by the injected radiopaque material. Worthy of note is that cineangio defects can persist unchanged per years [ 13 ]. Cineangio coronary occlusion The very high frequency of coronary occlusion seen angiographically in AMI patients (see above) does not correspond to that observed in pathological studies in which the mean figure is 50% for AMI and 29% for SUD patients. Nevertheless, different selection of material, divergent definition and an absence of a correct correlation of all pertinent variables give reason of dissimilar conclusions. In 200 selected AMIs and 208 SUD cases the unique cause of occlusion was a thrombus found in 41% and 29% respectively. In AMI group it correlated significantly with a lumen reduction greater than 70% (93%), length of plaque more than 6 millimeters (95%), its concentric shape (100%), prevailing atheroma (84%), medial neuritis (92%) infarct size greater than 50% (86%). SUD cases showed a similar behavior. In reality, both clinicians and pathologists observe a phenomenon which started before, missing its onset and sequence of events to distinguish whether primary or secondary. In only one case reported in literature [ 14 ], this sequence and histological examination of the whole heart was possible in a 45 year old man suffering a two months unstable angina. At coronary cineangiography there were two critical stenoses of the left anterior descending branch (LAD), one proximal and another distal to the origin of diagonal branch and a critical stenosis in the first tract of the right coronary artery (RCA). An antero-septal-lateral hypokinesis was documented. After the fourth left coronary injection, in absence of any symptom or sign and cineangio imaging changes, a first ECG showed downsloped ST segment. The latter persisted for other four LAD injections when the vessel disappeared, again, without any subjective and objective signal. Intracoronary vasodilator and fibrinolytic agents, successful angioplasty in reopening critical stenoses, surgical bypass in rapid sequence were performed without re-establishing flow. Only for few short periods a reflow occurred with an imaging of occlusion which from the distal tract ascended till the origin of LAD (Fig. 7 ) and not at the site of angioplastically reopened stenoses. An interesting note is that a severe chest pain started after angioplasty, 90 minutes from the first ECG change. The patient survived an extensive myocardial infarction and 12 months later underwent heart transplantation because irreversible congestive heart failure. We had the opportunity to examine the heart removed at surgery confirming a large (40% of the total left ventricular mass) antero-septal-lateral scar, end result of the infarct, scattered foci of fibrosis everywhere, absence of small vessel disease, colliquative myocytolysis expression of congestive failure, severe lumen reduction by sclerosis of LAD (90%) – despite it showed a normal lumen at bypass surgery – and vein graft (80%) without evidence of thrombosis, RCA occlusion by an organized thrombus located in an atherosclerotic plaque with 90% lumen reduction, medial neuritis i.e. lympho-plasmacellular inflammation of nerves closed to the tunica media, in all atherosclerotic plaques, absence of an infarct in RCA territory. Figure 7 Cineangiographic monitoring in a patient with non occlusive LAD stenosis (A) who developed an extensive infarct without angiographic occlusion. The subsequent imaging of occlusion began distally (B) and ascended to the origin (C) of the vessel (arrow) indicating that the angiographic "pseudocclusion" was due to stasis for increased peripheral resistance and not for primitive thrombosis, not shown morphologically (see text). One case is only one case but when for the first time shows how the events developed, it becomes a precious mile stone for our knowledge demonstrating that the cineangio occlusion was a pseudocclusion namely a blood flow stasis in LAD secondary to an increased intramyocardial resistance. The first main question is how many of the 87% cineangio occlusion are pseudocclusion and whether the "layered" thrombus recovered at bypass surgery was a true thrombus or a coagulum which frequently show a layering of blood elements not seen in thrombus formation. "Red" thrombus, namely a coagulum, is frequently and erroneously considered as thrombus. The second question concerns the nature of increased intramyocardial resistance: spasm of intramural arterial vessels or their extravascular compression by an asynergic myocardium? The first sign of CHD is hypokinesis of a myocardial zone which particularly in systole may compress vessels. Any time there is an increase of the intraventricular pressure with bulging of hypokinetic myocardium such a compression may abolish blood flow with subsequent infarction. In the reported patient location and infarct size corresponded to the hypokinetic area observed before the infarct onset. A last comment deserves the supposition that small atherosclerotic plaques undetectable at cineangio, may rupture causing an infarct. A supposition based on the cineangio finding of a non critical stenosis observed in a vessel tributary of a territory in which an infarct will develop. Since, when the latter occurred, stenoses in other non supplying vessels did not show a further lumen reduction, the conclusion was that even the plaque related to infarction had a non critical lumen reduction [ 15 ]. A conclusion that ignores the following two main facts. First that no one pathological study demonstrated the rupture of a small plaque associated with a thrombus occluding a normal or mild stenotic lumen. Second, myocardial asynergy by increasing intramyocardial resistance, promotes plaque progression by an increased dynamic stress on wall of the supplying extramural artery. For instance, in the previous case both LAD and vein graft with a normal lumen at surgery, in 12 months became critically stenotic (90% and 80% respectively). Regional myocardial dysfunction is an important cofactor in accelerating atherosclerosis lesion in related artery. Target of ultrasound diagnosis: the present and the future In the past years, clinical methods available to measure collateral flow have been too crude and showed major limitations, thus contributing to debate and confusion about the functional relevance of collateral circulation in the human myocardium. Coronary angiography allows visualization of collateral vessels having a diameter ≥100 μm, that actually prevents the majority of them from being detectable with this technique [ 16 , 17 ]. On the other hand, scintigraphic perfusion imaging techniques have limited spatial resolution [ 18 ]. Intracoronary wedge pressure and Doppler flow velocity measurements clearly demonstrated the presence of considerable collateral flow even in patients without angiographic evidence of collaterals [ 19 , 20 ], but they are invasive and not suitable for routine clinical use. With the introduction of new generation echo contrast agents and advanced ultrasound techniques, myocardial contrast echocardiography (MCE), an ultrasound imaging technique that utilizes physiologically inert gas-filled microbubbles as red blood cell tracers, has gained importance for the non-invasive assessment of blood flow at the level of myocardial perfusion [ 21 , 22 ]. Although evaluation of viability is the main clinical application of MCE [ 23 ], indirect assessment of collateral derived myocardial perfusion has been described in different clinical and experimental settings. In patients with severe left coronary artery disease, the placement of a graft to the posterior descending coronary artery was found to improve the collateral derived peak contrast effect within the anterior left ventricular wall [ 24 ]. In a series of subjects with healed myocardial infarction and total occlusion of the culprit vessel, a correlation was found between angiographic collateral grade and peak contrast effect after contralateral intracoronary contrast injection [ 25 ]. Collateral perfusion detected by MCE paralleled changes detected by radiolabeled microspheres during thrombosis and vasodilator administration in a canine model [ 26 ]. The usefulness of MCE has been confirmed in subjects without coronary occlusion where it was able to map the myocardial territory perfused by coronary collateral flow and to evidence immediate reduction of perfusion when collateral flow was abolished by angioplasty [ 27 ]. In patients with no prior myocardial infarction undergoing coronary angiography, intracoronary MCE effectively quantified coronary collateral flow, as demonstrated by the linear correlation existing between peak echo contrast effect and collateral flow index determined by intracoronary wedge pressure [ 28 ]. On the other hand, a strong correlation was reported between collateral receiving area at MCE and regional wall motion score index in patients with coronary occlusion, thus providing evidence that collateral derived perfusion is a good indicator of preserved regional function [ 29 ]. Likely, the grade of collateral flow on MCE was inversely correlated to the infarct size and was able to predict functional improvement following coronary revascularization [ 30 ]. Using an experimental model of chronic ischemia, it was found that not only the presence of collaterals can be identified by MCE, but also that temporal and spatial development of collateral circulation can be tracked serially [ 31 ]. Finally, intravenous MCE has been recently reported to provide qualitative and quantitative evaluation of collateral blood flow in the presence of an occluded infarct-related artery, and to emerge as the only predictor of true collateral blood flow among other markers [ 32 ]. All these reports as a whole support the concept that MCE provides important information on collateral flow and represents a promising mean for evaluating the status of coronary collateral circulation in clinical practice. Some important caveat , however, have to be taken into account. First, although the peak contrast pixel intensity has been reported as the most accurate of the variables obtained to measure collateral flow, there is a remarkable scatter in the correlation between peak pixel intensity and true collateral flow [ 33 ]. Second, it is known that regional contrast heterogeneity is common, resulting in frequent false positive perfusion defects [ 34 ]. Finally, coronary collateral vessels may cause additional dilution of contrast affecting the transit rate calculation. Further technical improvements may contribute in the near future to ensure standardization of the acoustic window and provide a quantitative evaluation of collateral flow. These issues appear to be of crucial importance to turn the echocardiographic assessment of coronary collateral flow into a ready-to-go clinical tool. Besides the attempt to obtain direct echocardiographic assessment, coronary collateral circulation can indirectly affect the result of diagnostic stress testing with the use of echocardiographic technique. Increased vulnerability to myocardial ischemia induced by pharmacological coronary vasodilation was reported consistently with the hypothesis of a facilitated steal phenomenon in the presence of good collateral circulation [ 35 ]. On the other hand, the role of collaterals against echocardiographically-assessed stress-induced myocardial ischemia is controversial, some Authors reporting a protective [ 36 ] and others a neutral [ 37 ] effect. However, dobutamine-induced wall motion worsening in myocardial territories supplied by occluded epicardial vessels has been reported in case of evident collateral circulation [ 38 ], thus emphasizing the importance of a preserved, though reduced, blood flow to distinguish jeopardized myocardium from necrotic tissue. Differently, the ability of low-dose dobutamine stimulation to identify myocardial regions with a high probability of functional improvement after revascularization seems to be independent of both severity of underlying coronary stenosis and degree of collateralization of the involved coronary vessel [ 39 ]. The application of low-frequency ultrasound to intravascular microbubble contrast agents has been receiving attention in the last few years due to its potential therapeutic application, primarily as targeted gene delivery systems [ 40 ]. Further evidence from experimental studies has shown small capillary ruptures in exteriorized rat skeletal muscle [ 41 ], intact mouse muscle [ 42 ] and rabbit myocardium [ 43 ] to follow the application of ultrasound power. However, capillary rupturing via microbubble destruction with ultrasound is able to enhance arterioles per muscle fiber, arteriole diameters, and maximum nutrient blood flow in skeletal muscle [ 44 ]; thus, it may be tailored to stimulate an arteriogenesis response that restores hyperemia blood flow following arterial occlusion [ 45 ]. The potential of this method to become a clinical tool for stimulating blood flow to organs affected by occlusive vascular disease and, in particular, to the myocardium represents an interesting track for future research involving the application of ultrasound technology in the ischemic heart disease. Final consideration on coronary atherosclerotic plaque Any hypothesis on the pathogenic role of a plaque and its activity and vulnerability should consider all interrelated variables for a correct interpretation of findings. When only one or few variables are investigated erroneous conclusions can be reached. An atherosclerotic plaque is always an active structure since its progression depends on a sequence of events due to a variety of correlated phenomena; while vulnerability is just an hypothesis which believe that some findings indicate a risk of plaque rupture. The known variables are: degree of lumen reduction, shape, length, satellite collaterals, tunica media changes, inflammatory reaction per se and associated with media nerves (medial neuritis), survival (Table 3 ) macrophagic repair process, inflammation, vascularization hemorrhage, proteoglicans, atheroma, calcification, smooth muscle cell and elastic fiber hyperplasia, rupture, thrombosis, various factors released from all involved cells, hemodynamic pressure stresses, regional myocardial asynergy, spasm plus still unknown variables to be included. Table 3 Occlusive coronary thrombus versus significantly main correlated variables. Percentage distribution Source Acute myocardial infarct Sudden unexpected death Cases Total 200 208 Cases+occlusive thrombus% 41 15 Lumen reduction% ≤ 69 7 - 70–79 33 16 80–89 35 47 > 90 24 38 Length stenosis mm ≤ 5 6 6 5–20 38 19 > 20 56 75 Concentric 100 94 Atheromatous 84 75 Medial neuritis 92 92 Infarct size % ≤ 10 20 - 11–20 32 - 21–30 48 - 31–40 44 - 41–50 78 - > 50 86 - Survival days ≤ 2 29 3–10 51 11–30 45 Survival minutes < 10 - 12 10–60 - 23 61–180 - 30 Most studies analized few variables mainly observed in animals after hypercholesterol diet or in familial hypercholesterolemia. A pattern [ 46 , 47 ] totally different from that seen in general population and CHD. Furthermore, myocardial infarction is not synonymous of sudden/unexpected death, thrombus is a totally divergent structure from coagulum, collaterals can not be ignored and meaning of the coronary atherosclerotic plaque can be interpreted in another way. The presence of functioning collaterals induces a particular hemodynamic condition within the residual lumen at the plaque level with proximal flow reduction counterbalanced by distal collateral flow. Any time there is a regional asynergy (Figure 8 ) with increasing intramural resistance, stasis in related artery will result in blockage of flow within the lumen with the most favourable situation for intimal hemorrhage, rupture, and thrombosis as secondary phenomena and not primary cause of an infarct. It is hard to believe that occlusion of a pinpoint lumen already compensated by collaterals is the cause of an infarct and rupture of a cap causes infarct or sudden death; being clear that any acute coronary syndrome is an etiopathogenetic entity which can not be caged in any unifying theory [ 48 ]. In the next review on different types of myocardial damage, this argument will be further reconsidered. Figure 8 The coronary thrombus is a multivariant phenomenon (A), including medial neuritis. Its location in severe (≥70) stenosis associated with other factors (retrograde collateral flow, reduced fibrinolytic activity, etc, see text) justifies the concept that is a secondary phenomenon. Any time there is an increased peripheral resistance (B) (spasm, intramural extravascular compression following infarction, etc), stasis in related main vessel and in collaterals both outside and within the plaque is expected with hemorrhage, plaque rupture and trombosis (C). On the other hand, it is difficult to accept that acute occlusion of a pin-point lumen bypassed by preexisting functioning collaterals (D) may result in infarct necrosis or sudden death. Even experimentally occlusion of a severe "chronic" (7 days) stenosis does not produce any ischemic dysfunction. Authors' contributions Prof. Giorgio Baroldi contributed to the conception and organization of this review and to the final comments. Dr. Riccardo Bigi and Dr. Lauro Cortigiani summarized the use of ultrasound techniques in atherosclerotic plaque imaging.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC554094.xml
545600	Bioconductor: open software development for computational biology and bioinformatics	A detailed description of the aims and methods of the Bioconductor project, an initiative for the collaborative creation of extensible software for computational biology and bioinformatics.	Background The Bioconductor project [ 1 ] is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics (CBB). Biology, molecular biology in particular, is undergoing two related transformations. First, there is a growing awareness of the computational nature of many biological processes and that computational and statistical models can be used to great benefit. Second, developments in high-throughput data acquisition produce requirements for computational and statistical sophistication at each stage of the biological research pipeline. The main goal of the Bioconductor project is creation of a durable and flexible software development and deployment environment that meets these new conceptual, computational and inferential challenges. We strive to reduce barriers to entry to research in CBB. A key aim is simplification of the processes by which statistical researchers can explore and interact fruitfully with data resources and algorithms of CBB, and by which working biologists obtain access to and use of state-of-the-art statistical methods for accurate inference in CBB. Among the many challenges that arise for both statisticians and biologists are tasks of data acquisition, data management, data transformation, data modeling, combining different data sources, making use of evolving machine learning methods, and developing new modeling strategies suitable to CBB. We have emphasized transparency, reproducibility, and efficiency of development in our response to these challenges. Fundamental to all these tasks is the need for software; ideas alone cannot solve the substantial problems that arise. The primary motivations for an open-source computing environment for statistical genomics are transparency, pursuit of reproducibility and efficiency of development. Transparency High-throughput methodologies in CBB are extremely complex, and many steps are involved in the conversion of information from low-level information structures (for example, microarray scan images) to statistical databases of expression measures coupled with design and covariate data. It is not possible to say a priori how sensitive the ultimate analyses are to variations or errors in the many steps in the pipeline. Credible work in this domain requires exposure of the entire process. Pursuit of reproducibility Experimental protocols in molecular biology are fully published lists of ingredients and algorithms for creating specific substances or processes. Accuracy of an experimental claim can be checked by complete obedience to the protocol. This standard should be adopted for algorithmic work in CBB. Portable source code should accompany each published analysis, coupled with the data on which the analysis is based. Efficiency of development By development, we refer not only to the development of the specific computing resource but to the development of computing methods in CBB as a whole. Software and data resources in an open-source environment can be read by interested investigators, and can be modified and extended to achieve new functionalities. Novices can use the open sources as learning materials. This is particularly effective when good documentation protocols are established. The open-source approach thus aids in recruitment and training of future generations of scientists and software developers. The rest of this article is devoted to describing the computing science methodology underlying Bioconductor. The main sections detail design methods and specific coding and deployment approaches, describe specific unmet challenges and review limitations and future aims. We then consider a number of other open-source projects that provide software solutions for CBB and end with an example of how one might use Bioconductor software to analyze microarray data. Results and discussion Methodology The software development strategy we have adopted has several precedents. In the mid-1980s Richard Stallman started the Free Software Foundation and the GNU project [ 2 ] as an attempt to provide a free and open implementation of the Unix operating system. One of the major motivations for the project was the idea that for researchers in computational sciences "their creations/discoveries (software) should be available for everyone to test, justify, replicate and work on to boost further scientific innovation" [ 3 ]. Together with the Linux kernel, the GNU/Linux combination sparked the huge open-source movement we know today. Open-source software is no longer viewed with prejudice, it has been adopted by major information technology companies and has changed the way we think about computational sciences. A large body of literature exists on how to manage open-source software projects: see Hill [ 4 ] for a good introduction and a comprehensive bibliography. One of the key success factors of the Linux kernel is its modular design, which allows for independent and parallel development of code [ 5 ] in a virtual decentralized network [ 3 ]. Developers are not managed within the hierarchy of a company, but are directly responsible for parts of the project and interact directly (where necessary) to build a complex system [ 6 ]. Our organization and development model has attempted to follow these principles, as well as those that have evolved from the R project [ 7 , 8 ]. In this section, we review seven topics important to establishment of a scientific open source software project and discuss them from a CBB point of view: language selection, infrastructure resources, design strategies and commitments, distributed development and recruitment of developers, reuse of exogenous resources, publication and licensure of code, and documentation. Language selection CBB poses a wide range of challenges, and any software development project will need to consider which specific aspects it will address. For the Bioconductor project we wanted to focus initially on bioinformatics problems. In particular we were interested in data management and analysis problems associated with DNA microarrays. This orientation necessitated a programming environment that had good numerical capabilities, flexible visualization capabilities, access to databases and a wide range of statistical and mathematical algorithms. Our collective experience with R suggested that its range of well-implemented statistical and visualization tools would decrease development and distribution time for robust software for CBB. We also note that R is gaining widespread usage within the CBB community independently of the Bioconductor Project. Many other bioinformatics projects and researchers have found R to be a good language and toolset with which to work. Examples include the Spot system [ 9 ], MAANOVA [ 10 ] and dChip [ 11 ]. We now briefly enumerate features of the R software environment that are important motivations behind its selection. Prototyping capabilities R is a high-level interpreted language in which one can easily and quickly prototype new computational methods. These methods may not run quickly in the interpreted implementation, and those that are successful and that get widely used will often need to be re-implemented to run faster. This is often a good compromise; we can explore lots of concepts easily and put more effort into those that are successful. Packaging protocol The R environment includes a well established system for packaging together related software components and documentation. There is a great deal of support in the language for creating, testing, and distributing software in the form of 'packages'. Using a package system lets us develop different software modules and distribute them with clear notions of protocol compliance, test-based validation, version identification, and package interdependencies. The packaging system has been adopted by hundreds of developers around the world and lies at the heart of the Comprehensive R Archive Network, where several hundred independent but interoperable packages addressing a wide range of statistical analysis and visualization objectives may be downloaded as open source. Object-oriented programming support The complexity of problems in CBB is often translated into a need for many different software tools to attack a single problem. Thus, many software packages are used for a single analysis. To secure reliable package interoperability, we have adopted a formal object-oriented programming discipline, as encoded in the 'S4' system of formal classes and methods [ 12 ]. The Bioconductor project was an early adopter of the S4 discipline and was the motivation for a number of improvements (established by John Chambers) in object-oriented programming for R. WWW connectivity Access to data from on-line sources is an essential part of most CBB projects. R has a well developed and tested set of functions and packages that provide access to different databases and to web resources (via http, for example). There is also a package for dealing with XML [ 13 ], available from the Omegahat project, and an early version of a package for a SOAP client [ 14 ], SSOAP, also available from the Omegahat project. These are much in line with proposals made by Stein [ 15 ] and have aided our work towards creating an environment in which the user perceives tight integration of diverse data, annotation and analysis resources. Statistical simulation and modeling support Among the statistical and numerical algorithms provided by R are its random number generators and machine learning algorithms. These have been well tested and are known to be reliable. The Bioconductor Project has been able to adapt these to the requirements in CBB with minimal effort. It is also worth noting that a number of innovations and extensions based on work of researchers involved in the Bioconductor project have been flowing back to the authors of these packages. Visualization support Among the strengths of R are its data and model visualization capabilities. Like many other areas of R these capabilities are still evolving. We have been able to quickly develop plots to render genes at their chromosomal locations, a heatmap function, along with many other graphical tools. There are clear needs to make many of these plots interactive so that users can query them and navigate through them and our future plans involve such developments. Support for concurrent computation R has also been the basis for pathbreaking research in parallel statistical computing. Packages such as snow and rpvm simplify the development of portable interpreted code for computing on a Beowulf or similar computational cluster of workstations. These tools provide simple interfaces that allow for high-level experimentation in parallel computation by computing on functions and environments in concurrent R sessions on possibly heterogeneous machines. The snow package provides a higher level of abstraction that is independent of the communication technology such as the message-passing interface (MPI) [ 16 ] or the parallel virtual machine (PVM) [ 17 ]. Parallel random number generation [ 18 ], essential when distributing parts of stochastic simulations across a cluster, is managed by rsprng . Practical benefits and problems involved with programming parallel processes in R are described more fully in Rossini et al. [ 19 ] and Li and Rossini [ 20 ]. Community Perhaps the most important aspect of using R is its active user and developer communities. This is not a static language. R is undergoing major changes that focus on the changing technological landscape of scientific computing. Exposing biologists to these innovations and simultaneously exposing those involved in statistical computing to the needs of the CBB community has been very fruitful and we hope beneficial to both communities. Infrastructure base We began with the perspective that significant investment in software infrastructure would be necessary at the early stages. The first two years of the Bioconductor project have included significant effort in developing infrastructure in the form of reusable data structures and software/documentation modules (R packages). The focus on reusable software components is in sharp contrast to the one-off approach that is often adopted. In a one-off solution to a bioinformatics problem, code is written to obtain the answer to a given question. The code is not designed to work for variations on that question or to be adaptable for application to distinct questions, and may indeed only work on the specific dataset to which it was originally applied. A researcher who wishes to perform a kindred analysis must typically construct the tools from scratch. In this situation, the scientific standard of reproducibility of research is not met except via laborious reinvention. It is our hope that reuse, refinement and extension will become the primary software-related activities in bioinformatics. When reusable components are distributed on a sound platform, it becomes feasible to demand that a published novel analysis be accompanied by portable and open software tools that perform all the relevant calculations. This will facilitate direct reproducibility, and will increase the efficiency of research by making transparent the means to vary or extend the new computational method. Two examples of the software infrastructure concepts described here are the exprSet class of the Biobase package, and the various Bioconductor metadata packages, for example hgu95av2 . An exprSet is a data structure that binds together array-based expression measurements with covariate and administrative data for a collection of microarrays. Based on R data.frame and list structures, exprSets offer much convenience to programmers and analysts for gene filtering, constructing annotation-based subsets, and for other manipulations of microarray results. The exprSet design facilitates a three-tier architecture for providing analysis tools for new microarray platforms: low-level data are bridged to high-level analysis manipulations via the exprSet structure. The designer of low-level processing software can focus on the creation of an exprSet instance, and need not cater for any particular analysis data structure representation. The designer of analysis procedures can ignore low-level structures and processes, and operate directly on the exprSet representation. This design is responsible for the ease of interoperation of three key Bioconductor packages: affy , marray , and limma . The hgu95av2 package is one of a large collection of related packages that relate manufactured chip components to biological metadata concerning sequence, gene functionality, gene membership in pathways, and physical and administrative information about genes. The package includes a number of conventionally named hashed environments providing high-performance retrieval of metadata based on probe nomenclature, or retrieval of groups of probe names based on metadata specifications. Both types of information (metadata and probe name sets) can be used very fruitfully with exprSets : for example, a vector of probe names immediately serves to extract the expression values for the named probes, because the exprSet structure inherits the named extraction capacity of R data.frames . Design strategies and commitments Well-designed scientific software should reduce data complexity, ease access to modeling tools and support integrated access to diverse data resources at a variety of levels. Software infrastructure can form a basis for both good scientific practice (others should be able to easily replicate experimental results) and for innovation. The adoption of designing by contract, object-oriented programming, modularization, multiscale executable documentation, and automated resource distribution are some of the basic software engineering strategies employed by the Bioconductor Project. Designing by contract While we do not employ formal contracting methodologies (for example, Eiffel [ 21 ]) in our coding disciplines, the contracting metaphor is still useful in characterizing the approach to the creation of interoperable components in Bioconductor. As an example, consider the problem of facilitating analysis of expression data stored in a relational database, with the constraints that one wants to be able to work with the data as one would with any exprSet and one does not want to copy unneeded records into R at any time. Technically, data access could occur in various ways, using database connections, DCOM [ 22 ], communications or CORBA [ 23 ], to name but a few. In a designing by contract discipline, the provider of exprSet functionality must deliver a specified set of functionalities. Whatever object the provider's code returns, it must satisfy the exprSets contract. Among other things, this means that the object must respond to the application of functions exprs and pData with objects that satisfy the R matrix and data.frame contracts respectively. It follows that exprs ( x ) [ i,j ] , for example, will return the number encoding the expression level for the i th gene for the j th sample in the object x , no matter what the underlying representation of x . Here i and j need not denote numerical indices but can hold any vectors suitable for interrogating matrices via the square-bracket operator. Satisfaction of the contract obligations simplifies specification of analysis procedures, which can be written without any concern for the underlying representations for exprSet information. A basic theme in R development is simplifying the means by which developers can state, follow, and verify satisfaction of design contracts of this sort. Environment features that support convenient inheritance of behaviors between related classes with minimal recoding are at a premium in this discipline. Object-oriented programming There are various approaches to the object-oriented programming methodology. We have encouraged, but do not require, use of the so-called S4 system of formal classes and methods in Bioconductor software. The S4 object paradigm (defined primarily by Chambers [ 12 ] with modifications embodied in R) is similar to that of Common Lisp [ 24 ] and Dylan [ 25 ]. In this system, classes are defined to have specified structures (in terms of a set of typed 'slots') and inheritance relationships, and methods are defined both generically (to specify the basic contract and behavior) and specifically (to cater for objects of particular classes). Constraints can be given for objects intended to instantiate a given class, and objects can be checked for validity of contract satisfaction. The S4 system is a basic tool in carrying out the designing by contract discipline, and has proven quite effective. Modularization The notion that software should be designed as a system of interacting modules is fairly well established. Modularization can occur at various levels of system structure. We strive for modularization at the data structure, R function and R package levels. This means that data structures are designed to possess minimally sufficient content to have a meaningful role in efficient programming. The exprSet structure, for example, contains information on expression levels ( exprs slot), variability ( se.exprs ), covariate data ( phenoData slot), and several types of metadata (slots description , annotation and notes ). The tight binding of covariate data with expression data spares developers the need to track these two types of information separately. The exprSet structure explicitly excludes information on gene-related annotation (such as gene symbol or chromosome location) because these are potentially volatile and are not needed in many activities involving exprSets . Modularization at the R function level entails that functions are written to do one meaningful task and no more, and that documents (help pages) are available at the function level with worked examples. This simplifies debugging and testing. Modularization at the package level entails that all packages include sufficient functionality and documentation to be used and understood in isolation from most other packages. Exceptions are formally encoded in files distributed with the package. Multiscale and executable documentation Accurate and thorough documentation is fundamental to effective software development and use, and must be created and maintained in a uniform fashion to have the greatest impact. We inherit from R a powerful system for small-scale documentation and unit testing in the form of the executable example sections in function-oriented manual pages. We have also introduced a new concept of large-scale documentation with the vignette concept. Vignettes go beyond typical man page documentation, which generally focuses on documenting the behavior of a function or small group of functions. The purpose of a vignette is to describe in detail the processing steps required to perform a specific task, which generally involves multiple functions and may involve multiple packages. Users of a package have interactive access to all vignettes associated with that package. The Sweave system [ 26 ] was adopted for creating and processing vignettes. Once these have been written users can interact with them on different levels. The transformed documents are provided in Adobe's portable document format (PDF) and access to the code chunks from within R is available through various functions in the tools package. However, new users will need a simpler interface. Our first offering in this area is the vignette explorer vExplorer which provides a widget that can be used to navigate the various code chunks. Each chunk is associated with a button and the code is displayed in a window, within the widget. When the user clicks on the button the code is evaluated and the output presented in a second window. Other buttons provide other functionality, such as access to the PDF version of the document. We plan to extend this tool greatly in the coming years and to integrate it closely with research into reproducible research (see [ 27 ] for an illustration). Automated software distribution The modularity commitment imposes a cost on users who are accustomed to integrated 'end-to-end' environments. Users of Bioconductor need to be familiar with the existence and functionality of a large number of packages. To diminish this cost, we have extended the packaging infrastructure of R/CRAN to better support the deployment and management of packages at the user level. Automatic updating of packages when new versions are available and tools that obtain all package dependencies automatically are among the features provided as part of the reposTools package in Bioconductor. Note that new methods in R package design and distribution include the provision of MD5 checksums with all packages, to help with verification that package contents have not been altered in transit. In conclusion, these engineering commitments and developments have led to a reasonably harmonious set of tools for CBB. It is worth considering how the S language notion that 'everything is an object' impacts our approach. We have made use of this notion in our commitment to contracting and object-oriented programming, and in the automated distribution of resources, in which package catalogs and biological metadata are all straightforward R objects. Packages and documents are not yet treatable as R objects, and this leads to complications. We are actively studying methods for simplifying authoring and use of documentation in a multipackage environment with namespaces that allow symbol reuse, and for strengthening the connection between session image and package inventory in use, so that saved R images can be restored exactly to their functional state at session close. Distributed development and recruitment of developers Distributed development is the process by which individuals who are significantly geographically separated produce and extend a software project. This approach has been used by the R project for approximately 10 years. This was necessitated in this case by the fact no institution currently has sufficient numbers of researchers in this area to support a project of this magnitude. Distributed development facilitates the inclusion of a variety of viewpoints and experiences. Contributions from individuals outside the project led to the expansion of the core developer group. Membership in the core depends upon the willingness of the developer to adopt shared objectives and methods and to submerge personal objectives in preference to creation of software for the greater scientific community. Distributed development requires the use of tools and strategies that allow different programmers to work approximately simultaneously on the same components of the project. Among the more important requirements is for a shared code base (or archive) that all members of the project can access and modify together with some form of version management system. We adopted the Concurrent Versions System [ 28 , 29 ] and created a central archive, within this system, that all members of the team have access to. Additional discipline is needed to ensure that changes by one programmer should not result in a failure of other code in the system. Within the R language, software components are naturally broken into packages, with a formal protocol for package structure and content specified in the R Extensions manual [ 30 ]. Each package should represent a single coherent theme. By using well defined applications programming interfaces (APIs) developers of a package are free to modify their internal structures as long as they continue to provide the documented outputs. We rely on the testing mechanisms supported by the R package testing system [ 30 ] to ensure coherent, non-regressive development. Each developer is responsible for documenting all functions and for providing examples and possibly other scripts or sets of commands that test the code. Each developer is responsible for ensuring that all tests run successfully before committing changes back to the central archive. Thus, the person who knows the code best writes the test programs, but all are responsible for running them and ensuring that changes they have made do not affect the code of others. In some cases changes by one author will necessitate change in the code and tests of others. Under the system we are using these situations are detected and dealt with when they occur in development, reducing the frequency with which error reports come from the field. Members of the development team communicate via a private mailing list. In many cases they also use private email, telephone and meetings at conferences in order to engage in joint projects and to keep informed about the ideas of other members. Reuse of exogenous resources We now present three arguments in favor of using and adapting software from other projects rather than re-implementing or reinventing functionality. The first argument that we consider is that writing good software is a challenging problem and any re-implementation of existing algorithms should be avoided if possible. Standard tools and paradigms that have been proven and are well understood should be preferred over new untested approaches. All software contains bugs but well used and maintained software tends to contain fewer. The second argument is that CBB is an enormous field and that progress will require the coordinated efforts of many projects and software developers. Thus, we will require structured paradigms for accessing data and algorithms written in other languages and systems. The more structured and integrated this functionality, the easier it will be to use and hence the more it will be used. As specific examples we consider our recent development of tools for working with graph or network structures. There are three main packages in Bioconductor of interacting with graphs. They are graph , RBGL and Rgraphviz . The first of these provides the class descriptions and basic infrastructure for dealing with graphs in R, the second provides access to algorithms on graphs, and the third to a rich collection of graph layout algorithms. The graph package was written from scratch for this project, but the other two are interfaces to rich libraries of software routines that have been created by other software projects, BOOST [ 31 , 32 ] and Graphviz [ 23 ] respectively, both of which are very substantial projects with large code bases. We have no interest in replicating that work and will, wherever possible, simply access the functions and libraries produced by other projects. There are many benefits from this approach for us and for the other projects. For bioinformatics and computational biology we gain rapid access to a variety of graph algorithms including graph layout and traversal. The developers in those communities gain a new user base and a new set of problems that they can consider. Gaining a new user base is often very useful, as new users with previously unanticipated needs tend to expose weaknesses in design and implementation that more sophisticated or experienced users are often able to avoid. In a similar vein, we plan to develop and encourage collaboration with other projects, including those organized through the Open Bioinformatics Foundation and the International Interoperability Consortium. We have not specifically concentrated on collaboration to this point in part because we have chosen areas for development that do not overlap significantly with the tools provided by those projects. In this case our philosophy remains one of developing interfaces to the software provided by those projects and not re-implementing their work. In some cases, other projects have recognized the potential gains for collaboration and have started developing interfaces for us to their systems, with the intent of making future contributions [ 33 ]. Another argument in favor of standardization and reuse of existing tools is best made with reference to a specific example. Consider the topic of markup and markup languages. For any specific problem one could quickly devise a markup that is sufficient for that problem. So why then should we adopt a standard such as XML? Among the reasons for this choice is the availability of programmers conversant with the paradigm, and hence lower training costs. A second reason is that the XML community is growing and developing and we will get substantial technological improvements without having to initiate them. This is not unusual. Other areas of computational research are as vibrant as CBB and by coordinating and sharing ideas and innovations we simplify our own tasks while providing stimulus to these other areas. Publication and licensing of code Modern standards of scientific publication involve peer review and subsequent publication in a journal. Software publication is a slightly different process with limited involvement to date of formal peer review or official journal publication. We release software under an open-source license as our main method of publication. We do this in the hope that it will encourage reproducibility, extension and general adherence to the scientific method. This decision also ensures that the code is open to public scrutiny and comment. There are many other reasons for deciding to release software under an open-source license, some of which are listed in Table 1 . Another consideration that arose when determining the form of publication was the need to allow an evolutionary aspect to our own software. There are many reasons for adopting a strategy that would permit us to extend and improve our software offerings over time. The field of CBB is relatively volatile and as new technologies are developed new software and inferential methods are needed. Further, software technology itself is evolving. Thus, we wanted to have a publication strategy that could accommodate changes in software at a variety of levels. We hope that that strategy will also encourage our users to think of software technology as a dynamic field rather than a static one and to therefore be on the lookout for innovations in this arena as well as in more traditional biological ones. Our decision to release software in the form of R packages is an important part of this consideration. Packages are easy to distribute, they have version numbers and define an API. A coordinated release of all Bioconductor packages occurs twice every year. At any given time there is a release version of every package and a development version. The only changes allowed to be made on the release version are bug fixes and documentation improvements. This ensures that users will not encounter radical new behaviors in code obtained in the release version. All other changes such as enhancements or design changes are carried out on the development branch [ 34 ]. Approximately six weeks before a release, a major effort is taken to ensure that all packages on the development branch are coordinated and work well together. During that period extensive testing is carried out through peer review amongst the Bioconductor core. At release time all packages on the development branch that are included in the release change modes and are now released packages. Previous versions of these packages are deprecated in favor of the newly released versions. Simultaneously, a new development branch is made and the developers start to work on packages in the new branch. Note that these version-related administrative operations occur with little impact on developers. The release manager is responsible for package snapshot and file version modifications. The developers' source code base is fairly simple, and need not involve retention of multiple copies of any source code files, even though two versions are active at all times. We would also like to point out that there are compelling arguments that can be made in favor of choosing different paradigms for software development and deployment. We are not attempting at this juncture to convince others to distribute software in this way, but rather elucidating our views and the reasons that we made our choice. Under a different set of conditions, or with different goals, it is entirely likely that we would have chosen a different model. Special concerns We now consider four specific challenges that are raised by research in computational biology and bioinformatics: reproducibility, data evolution and complexity, training users, and responding to user needs. Reproducible research We would like to address the reproducibility of published work in CBB. Reproducibility is important in its own right, and is the standard for scientific discovery. Reproducibility is an important step in the process of incremental improvement or refinement. In most areas of science researchers continually improve and extend the results of others but for scientific computation this is generally the exception rather than the rule. Buckheit and Donoho [ 35 ], referring to the work and philosophy of Claerbout, state the following principle: "An article about computational science in a scientific publication is not the scholarship itself, it is merely advertising of the scholarship. The actual scholarship is the complete software development environment and that complete set of instructions that generated the figures." There are substantial benefits that will come from enabling authors to publish not just an advertisement of their work but rather the work itself. A paradigm that fundamentally shifts publication of computational science from an advertisement of scholarship to the scholarship itself will be a welcome addition. Some of the concepts and tools that can be used in this regard are contained in [ 36 , 37 ]. When attempting to re-implement computational methodology from a published description many difficulties are encountered. Schwab et al. [ 38 ] make the following points: "Indeed the problem occurs wherever traditional methods of scientific publication are used to describe computational research. In a traditional article the author merely outlines the relevant computations: the limitations of a paper medium prohibit complete documentation including experimental data, parameter values and the author's programs. Consequently, the reader has painfully to re-implement the author's work before verifying and utilizing it.... The reader must spend valuable time merely rediscovering minutiae, which the author was unable to communicate conveniently." The development of a system capable of supporting the convenient creation and distribution of reproducible research in CBB is a massive undertaking. Nevertheless, the Bioconductor project has adopted practices and standards that assist in partial achievement of reproducible CBB. Publication of the data from which articles are derived is becoming the norm in CBB. This practice provides one of the components needed for reproducible research - access to the data. The other major component that is needed is access to the software and the explicit set of instructions or commands that were used to transform the data to provide the outputs on which the conclusions of the paper rest. In this regard publishing in CBB has been less successful. It is easy to identify major publications in the most prestigious journals that provide sketchy or indecipherable characterizations of computational and inferential processes underlying basic conclusions. This problem could be eliminated if the data housed in public archives were accompanied by portable code and scripts that regenerate the article's figures and tables. The combination of R's well-established platform independence with Bioconductor's packaging and documentation standards leads to a system in which distribution of data with working code and scripts can achieve most of the requirements of reproducible and replayable research in CBB. The steps leading to the creation of a table or figure can be clearly exposed in an Sweave document. An R user can export the code for modification or replay with variations on parameter settings, to check robustness of the reported calculations or to explore alternative analysis concepts. Thus we believe that R and Bioconductor can provide a start along the path towards generally reproducible research in CBB. The infrastructure in R that is used to support replayability and remote robustness analysis could be implemented in other languages such as Perl [ 39 ] and Python [ 40 ]. All that is needed is some platform-independent format for binding together the data, software and scripts defining the analysis, and a document that can be rendered automatically to a conveniently readable account of the analysis steps and their outcomes. If the format is an R package, this package then constitutes a single distributable software element that embodies the computational science being published. This is precisely the compendium concept espoused in [ 36 ]. Dynamics of biological annotation Metadata are data about data and their definition depends on the perspective of the investigator. Metadata for one investigator may well be experimental data for another. There are two major challenges that we will consider. First is the evolutionary nature of the metadata. As new experiments are done and as our understanding of the biological processes involved increases the metadata changes and evolves. The second major problem that concerns metadata data is its complexity. We are trying to develop software tools that make it easier for data analysts and researchers to use the existing metadata appropriately. The constant changing and updating of the metadata suggests that we must have a system or a collection process that ensures that any metadata can be updated and the updates can be distributed. Users of our system will want access to the most recent versions. Our solution has been to place metadata into R packages. These packages are built using a semi-automatic process [ 41 ] and are distributed (and updated) using the package distribution tools developed in the reposTools package. There is a natural way to apply version numbers so users can determine if their data are up to date or if necessary they can obtain older versions to verify particular analyses. Further, users can synchronize a variety of metadata packages according to a common version of the data sources that they were constructed from. There are a number of advantages that come from automating the process of building data packages. First, the modules are uniform to an extent that would not be possible if the packages were human written. This means that users of this technology need only become acquainted with one package to be acquainted with all such packages. Second, we can create many packages very quickly. Hence the labor savings are substantial. For microarray analyses all data packages should have the same information (chromosomal location, gene ontology categories, and so on). The only difference between the packages is that each references only the specific set of genes (probes) that were assayed. This means that data analysts can easily switch from one type of chip to another. It also means that we can develop a single set of tools for manipulating the metadata and improvements in those tools are available to all users immediately. Users are free to extend data packages with data from other, potentially proprietary, sources. Treating the data in the same manner that we treat software has also had many advantages. On the server side we can use the same software distribution tools, indicating updates and improvements with version numbering. On the client side, the user does not need to learn about the storage or internal details of the data packages. They simply install them like other packages and then use them. One issue that often arises is whether one should simply rely on online sources for metadata. That is, given an identifier, the user can potentially obtain more up-to-date information by querying the appropriate databases. The data packages we are proposing cannot be as current. There are, however, some disadvantages to the approach of accessing all resources online. First, users are not always online, they are not always aware of all applicable information sources and the investment in person-time to obtain such information can be high. There are also issues of reproducibility that are intractable as the owners of the web resources are free to update and modify their offerings at will. Some, but not all, of these difficulties can be alleviated if the data are available in a web services format. Another argument that can be made in favor of our approach, in this context, is that it allows the person constructing the data packages to amalgamate disparate information from a number of sources. In building metadata packages for Bioconductor, we find that some data are available from different sources, and under those circumstances we look for consensus, if possible. The process is quite sophisticated and is detailed in the AnnBuilder package and paper [ 41 ]. Training Most of the projects in CBB require a combination of skills from biology, computer science, and statistics. Because the field is new and there has been little specialized training in this area it seems that there is some substantial benefit to be had from paying attention to training. From the perspective of the Bioconductor project, many of our potential users are unfamiliar with the R language and generally are scientifically more aligned with one discipline than all three. It is therefore important that we produce documentation for the software modules that is accessible to all. We have taken a two-pronged approach to this, we have developed substantial amounts of course material aimed at all the constituent disciplines and we have developed a system for interactive use of software and documentation in the form of vignettes and more generally in the form of navigable documents with dynamic content. Course materials have been developed and refined over the past two to three years. Several members of the Bioconductor development team have taught courses and subsequently refined the material, based on success and feedback. The materials developed are modular and are freely distributed, although restrictions on publication are made. The focus of the materials is the introduction and use of software developed as part of the Bioconductor project, but that is not a requirement and merely reflects our own specific purposes and goals. In this area we feel that we would benefit greatly from contributions from those with more experience in technical document authoring. There are likely to be strategies, concepts and methodologies that are standard practice in that domain that we are largely unaware of. However, in the short term, we rely on the students, our colleagues and the users of the Bioconductor system to guide us and we hope that many will contribute. Others can easily make substantial contributions, even those with little or no programming skills. What is required is domain knowledge in one field of interest and the recognition of a problem that requires additional domain knowledge from another of the fields of interest. Our experience has been that many of these new users often transform themselves into developers. Thus, our development of training materials and documentation needs to pay some attention to the needs of this group as well. There are many more software components than we can collectively produce. Attracting others to collaboratively write software is essential to success. Responding to user needs The success of any software project rests on its ability to both provide solutions to the problems it is addressing and to attract a user community. Perhaps the most effective way of addressing user needs is through an e-mail help list and one was set up as soon as the project became active. In addition it is important to keep a searchable archive available so that the system itself has a memory and new users can be referred there for answers to common questions. It is also important that members of the project deal with bug reports and feature requests through this public forum as it both broadcasts their intentions and provides a public record of the discussion. Our mailing list (mailto: bioconductor@stat.math.ethz.ch ) has been successful: there are approximately 800 subscribers and about 3,000 email messages per year. Attracting a user community itself requires a method of distributing the software and providing sufficient training materials to allow potential users to explore the system and determine whether it is sufficient for their purposes. An alternate approach would be to develop a graphical user interface (GUI) that made interactions with the system sufficiently self-explanatory that documentation was not needed. We note that this solution is generally more applicable to cases where the underlying software tasks are well defined and well known. In the present case, the software requirements (as well as the statistical and biological requirements) are constantly evolving. R is primarily command-line oriented and we have chosen to follow that paradigm at least for the first few years of development. We would of course welcome and collaborate with those whose goal was in GUI development but our own forays into this area are limited to the production of a handful of widgets that promote user interaction at specific points. Users have experienced difficulties downloading and installing both R and the Bioconductor modules. Some of these difficulties have been caused by the users' local environments (firewalls and a lack of direct access to the internet), and some by problems with our software (bugs) which arise in part because it is in general very difficult to adequately test software that interacts over the internet. We have, however, managed to help every user, who was willing to persist, get both R and Bioconductor properly installed. Another substantial difficulty that we had to overcome was to develop a system that allowed users to download not just the software package that they knew they wanted, but additionally, and at the same time, all other software packages that it relies on. With Bioconductor software there is a much larger inter-reliance on software packages (including those that provide machine learning, biological metadata and experimental data) than for most other uses of R and the R package system. The package, reposTools contains much of the necessary infrastructure for handling these tasks. It is a set of functions for dealing with R package repositories which are basically internet locations for collections of R packages. Once the basic software is installed, users will need access to documentation such as the training materials described above and other materials such as the vignettes, described in a previous section. Such materials are most valuable if the user can easily obtain and run the examples on their own computer. We note the obvious similarity with this problem and that described in the section on reproducible research. Again, we are in the enjoyable situation of having a paradigm and tools that can serve two purposes. Other open-source bioinformatics software projects The Open Bioinformatics Foundation supports projects similar to Bioconductor that are nominally rooted in specific programming languages. BioPerl [ 42 ], BioPython [ 43 ] and BioJava [ 44 ] are prominent examples of open-source language-based bioinformatics projects. The intentions and design methodologies of the BioPerl project have been lucidly described by Stajich and colleagues [ 45 ]. BioPerl In this section we consider commonalities and differences between BioPerl and Bioconductor. Both projects have commitments to open source distribution and to community-based development, with an identified core of developers performing primary design and maintenance tasks for the project. Both projects use object-oriented programming methodology, with the intention of abstracting key structural and functional features of computational workflows in bioinformatics and defining stable application programming interfaces (API) that hide implementation details from those who do not need to know them. The toolkits are based on highly portable programming languages. These languages have extensive software resources developed for non-bioinformatic purposes. The repositories for R (Comprehensive R Archive Network, CRAN) and Perl (Comprehensive Perl Archive Network, CPAN) provide mirrored WWW access to structured collections of software modules and documents for a wide variety of workflow elements. Development methodologies targeted at software reuse can realize large gains in productivity by establishing interfaces to existing CPAN or CRAN procedures instead of reimplementing such procedures. For reuse to succeed, the maintainer of the external resource must commit to stability of the resource API. Such stability tends to be the norm for widely-used modules. Finally, both languages have considerable interoperability infrastructure. One implication is that each project can use software written in unrelated languages. R has well-established interfaces to Perl, Python, Java and C. R's API allows software in R to be called from other languages, and the RSPerl package [ 46 ] facilitates direct calls to R from Perl. Thus there are many opportunities for symbiotic use of code by Bioconductor and BioPerl developers and users. The following script illustrates the use of BioPerl in R. > library(RSPerl) > .PerlPackage("Bio::Perl") > x <- .Perl("get_sequence", "swiss", "ROA1_HUMAN") > x$division() [1] "HUMAN" > x$accession() [1] "P09651" > unlist(x$get_keywords()) [1] "Nuclear protein" "RNA-binding" [3] "Repeat" "Ribonucleoprotein" [5] "Methylation" "Transport" ... The .PerlPackage command brings the BioPerl modules into scope. .Perl invokes the BioPerl get_sequence subroutine with arguments "swiss" and "ROA1_HUMAN". The resulting R object is a reference to a perl hash. RSPerl infrastructure permits interrogation of the hash via the $ operator. Note that RSPerl is not a Bioconductor-supported utility, and that installation of the BioPerl and RSPerl resources to allow interoperation can be complicated. Key differences between the Bioconductor and BioPerl projects concern scope, approaches to distribution, documentation and testing, and important details of object-oriented design. Scope BioPerl is clearly slanted towards processing of sequence data and interfacing to sequence databases, with support for sequence visualization and queries for external annotation. Bioconductor is slanted towards statistical analysis of microarray experiments, with major concerns for array preprocessing, quality control, within- and between-array normalization, binding of covariate and design data to expression data, and downstream inference on biological and clinical questions. Bioconductor has packages devoted to diverse microarray manufacturing and analysis paradigms and to other high-throughput assays of interest in computational biology, including serial analysis of gene expression (SAGE), array comparative genomic hybridization (arrayCGH), and proteomic time-of-flight (SELDI-TOF) data. We say the projects are 'slanted' towards these concerns because it is clear that both projects ultimately aim to support general research activities in computational biology. Distribution, documentation and testing BioPerl inherits the distribution paradigm supported by CPAN. Software modules can be acquired and installed interactively using, for example perl -MCPAN -e shell . This process supports automated retrieval of requested packages and dependencies, but is not triggered by runtime events. Bioconductor has extended the CRAN distribution functionalities so that packages can be obtained and installed 'just in time', as required by a computational request. For both Perl and R, software modules and packages are structured collections of files, some of which are source code, some of which are documents about the code. The relationship between documentation and testing is somewhat tighter in Bioconductor than in BioPerl. Manual pages and vignettes in Bioconductor include executable code. Failure of the code in a man page or vignette is a quality-control event; experimentation with executable code in manual pages (through the example function of R) is useful for learning about software behavior. In Perl, tests occupy separate programs and are not typically integrated with documentation. Details of object-oriented procedure Both R and Perl are extensible computer languages. Thus it is possible to introduce software infrastructure supporting different approaches to object-oriented programming (OOP) in various ways in both languages. R's core developers have provided two distinct approaches to OOP in R. These approaches are named S3 and S4. In S3, any object can be assigned to a class (or sequence of classes) simply by setting the class name as the value of the object's class attribute. Class hierarchies are defined implicitly at the object level. Generic methods are defined as ordinary functions and class-specific methods are dispatched according to the class of the object being passed as an argument. In S4, formal definition of class structure is supported, and class hierarchy is explicitly defined in class definitions [ 12 ]. Class instances are explicitly constructed and subject to validation at time of construction. Generic methods are non-standard R functions and metadata on generic methods is established at the package level. Specific methods are dispatched according to the class signature of the argument list (multiple dispatch). Overall, the OOP approach embodied in S4 is closer to Dylan or Scheme than to C++ or Java. Bioconductor does not require specific OOP methodology but encourages the use of S4, and core members have contributed special tools for the documentation and testing of S4 OOP methods in R. OOP methodology in Perl has a substantial history and is extensively employed in BioPerl. The basic approach to OOP in Perl seems to resemble S3 more than S4, in that Perl's bless operation can associate any perl data instance with any class. The CPAN Class::Multimethod module can be used to allow multiple dispatch behavior of generic subroutines. The specific classes of objects identified in BioPerl are targeted at sequence data (Seq, LocatableSeq, RelSegment are examples), location data (Simple, Split, Fuzzy), and an important class of objects called interface objects, which are classes whose names end in 'I'. These objects define what methods can be called on objects of specified classes, but do not implement any methods. BioJava, BioPython, GMOD and MOBY Other open bioinformatics projects have intentions and methods that are closely linked with those of Bioconductor. BioJava [ 44 ] provides Dazzle, a servlet framework supporting the Distributed Annotation System specification for sharing sequence data and metadata. Version 1.4 of the BioJava release includes java classes for general alphabets and symbol-list processing, tools for parsing outputs of blast-related analyses, and software for constructing and fitting hidden Markov models. In principle, any of these resources could be used for analysis in Bioconductor/R through the SJava interface [ 46 ]. BioPython [ 43 ] provides software for constructing python objects by parsing output of various alignment or clustering algorithms, and for a variety of downstream tasks including classification. BioPython also provides infrastructure for decomposition of parallelizable tasks into separable processes for computation on a cluster of workstations. The Generic Model Organism Database (GMOD) project targets construction of reusable components that can be used to reproduce successful creation of open and widely accessible databases of model organisms (for example, worm, fruitfly and yeast). The main tasks addressed are genome visualization and annotation, literature curation, biological ontology activities, gene expression analysis and pathway visualization and annotation. BioMOBY [ 47 ] provides a framework for developing and cataloging web services relevant to molecular biology and genomics. A basic aim is to provide a central registry of data, annotation or analysis services that can be used programmatically to publish and make use of data and annotation resources pertinent to a wide variety of biological contexts. As these diverse projects mature, particularly with regard to interoperability, we expect to add infrastructure to Bioconductor to simplify the use of these resources in the context of statistical data analysis. It is our hope that the R and Bioconductor commitments to interoperability make it feasible for developers in other languages to reuse statistical and visualization software already present and tested in R. Using Bioconductor (example) Results of the Bioconductor project include an extensive repository of software tools, documentation, short course materials, and biological annotation data at [ 1 ]. We describe the use of the software and annotation data by description of a concrete analysis of a microarray archive derived from a leukemia study. Acute lymphocytic leukemia (ALL) is a common and difficult-to-treat malignancy with substantial variability in therapeutic outcomes. Some ALL patients have clearly characterized chromosomal aberrations and the functional consequences of these aberrations are not fully understood. Bioconductor tools were used to develop a new characterization of the contrast in gene expression between ALL patients with two specific forms of chromosomal translocation. The most important tasks accomplished with Bioconductor employed simple-to-use tools for state-of-the-art normalization of hundreds of microarrays, clear schematization of normalized expression data bound to detailed covariate data, flexible approaches to gene and sample filtering to support drilling down to manageable and interpretable subsets, flexible visualization technologies for exploration and communication of genomic findings, and programmatic connection between expression platform metadata and biological annotation data supporting convenient functional interpretation. We will illustrate these through a transcript of the actual command/output sequence. More detailed versions of some of the processing and analysis activities sketched here can be found in the vignettes from the GOstats package. The dataset is from the Ritz laboratory at the Dana Farber Cancer Institute [ 48 ]. It contains data from 128 patients with ALL. Two subgroups are to be compared. The first group consists of patients with a translocation between chromosomes 4 and 11 (labeled ALL1/AF4). The second group consists of patients with a translocation between chromosomes 9 and 22 (labeled BCR/ABL). These conditions are mutually exclusive in this dataset. The Affymetrix HGu95Av2 platform was used, and expression measures were normalized using gcrma from the affy package. The output of this is an object of class exprSet which can be used as input for other functions. The package hgu95av2 provides biological metadata including mappings from the Affymetrix identifiers to GO, chromosomal location, and so on. These data can, of course be obtained from many other sources, but there are some advantages to having them as an R package. After loading the appropriate packages we first subset the ALL exprSet to extract those samples with the covariates of interest. The design of the exprSet class includes methods for subsetting both cases and probes. By using the square-bracket notation on ALL, we derive a new exprSet with data on only the desired patients. > data("ALL") > eset <- ALL[, ALL$mol %in% c("BCR/ABL", "ALL1/AF4")] Next we find genes which are differentially expressed between the ALL1/AF4 and BCR/ABL groups. We use the function lmFit from the limma package, which can assess differential expression between many different groups and conditions simultaneously. The function lmFit accepts a model matrix which describes the experimental design and produces an output object of class MArrayLM which stores the fitted model information for each gene. The fitted model object is further processed by the eBayes function to produce empirical Bayes test statistics for each gene, including moderated t -statistics, p -values and log-odds of differential expression. The log 2 -fold changes, average intensites and Holm-adjusted p -values are displayed for the top 10 genes (Figure 1 ). We select those genes that have adjusted p -values below 0.05. The default method of adjusting for multiple comparisons uses Holm's method to control the family-wise error rate. We could use a less conservative method such as the false discovery rate, and the multtest package offers other possibilities, but for this example we will use the very stringent Holm method to select a small number of genes. > selected <- p.adjust(fit$p.value[, 2]) < 0.05 > esetSel <- eset [selected, ] There are 165 genes selected for further analysis. A heat map produced by the heatmap function from R allows us to visualize the differential action of these genes between the two groups of patients. Note how the different software modules can be integrated to provide a very rich data-analysis environment. Figure 2 shows clearly that these two groups can be distinguished in terms of gene expression. We can carry out many other tests, for example, whether genes encoded on a particular chromosome (or perhaps on a specific strand of a chromosome) are over-represented amongst those selected by moderated t -test. Many of these questions are normally addressed in terms of a hypergeometric distribution, but they can also be thought of as two-way or multi-way tables, and alternate statistical tests (all readily available in R) can be applied to the resulting data. We turn our attention briefly to the use of the Gene Ontology (GO) annotation in conjunction with these data. We first identify the set of unique LocusLink identifiers among our selected Affymetrix probes. The function GOHyperG is found in the GOstats package. It carries out a hypergeometric test for an overabundance of genes in our selected list of genes for each term in the GO graph that is induced by these genes (Figure 3 ). The smallest p -value found was 1.1e-8 and it corresponds to the term, "MHC class II receptor activity". We see that six of the 12 genes with this GO annotation have been selected. Had we used a slightly less conservative gene selection method then the number of selected genes in this GO annotation would have been even higher. Reproducing the above results for any other species or chip for which an annotation package was available would require almost no changes to the code. The analyst need only substitute the references to the data package, hgu95av2 , with those for their array and the basic principles and code are unchanged. Similarly, substitution of other algorithms or statistical tests is possible as the data analyst has access to the full and complete source code. All tools are modifiable at the source level to suit local requirements. Conclusions We have detailed the approach to software development taken by the Bioconductor project. Bioconductor has been operational for about three years now and in that time it has become a prominent software project for CBB. We argue that the success of the project is due to many factors. These include the choice of R as the main development language, the adoption of standard practices of software design and a belief that the creation of software infrastructure is an important and essential component of a successful project of this size. The group dynamic has also been an important factor in the success of Bioconductor. A willingness to work together, to see that cooperation and coordination in software development yields substantial benefits for the developers and the users and encouraging others to join and contribute to the project are also major factors in our success. To date the project provides the following resources: an online repository for obtaining software, data and metadata, papers, and training materials; a development team that coordinates the discussion of software strategies and development; a user community that provides software testing, suggested improvements and self-help; more than 80 software packages, hundreds of metadata packages and a number of experimental data packages. At this point it is worth considering the future. While many of the packages we have developed have been aimed at particular problems, there have been others that were designed to support future developments. And that future seems very interesting. Many of the new problems we are encountering in CBB are not easily addressed by technology transfer, but rather require new statistical methods and software tools. We hope that we can encourage more statisticians to become involved in this area of research and to orient themselves and their research to the mixture of methodology and software development that is necessary in this field. In conclusion we would like to note that the Bioconductor Project has many developers, not all of whom are authors of this paper, and all have their own objectives and goals. The views presented here are not intended to be comprehensive nor prescriptive but rather to present our collective experiences and the authors' shared goals. In a very simplified version these can be summarized in the view that coordinated cooperative software development is the appropriate mechanism for fostering good research in CBB.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545600.xml
545601	Development of a method for screening short-lived proteins using green fluorescent protein	A method for identifying short-live proteins using a GFP-fusion cDNA library for monitoring degradation kinetics is described.	Background Cellular proteins differ widely in their lability, ranging from those that are completely stable to those with half-lives measured in minutes. Proteins with a short half-life are among the most critical to the cell. Regulated degradation of specific proteins contributes to the control of signal transduction pathways, cell-cycle control, transcription, apoptosis, antigen processing, biological clock control, differentiation and surface receptor desensitization [ 1 , 2 ]. Rapid turnover makes it possible for the cellular level of a protein to change promptly when synthesis is increased or reduced [ 3 ]. Furthermore, degradation rate is itself subject to regulation. For instance, inflammatory stimuli cause the rapid degradation of IκBα, the inhibitor of NFκB, resulting in the activation of that transcription factor [ 4 - 6 ]. Analysis of labile proteins has been time-consuming and labor-intensive. The most definitive form of analysis requires pulse-chase labeling cells and immunoprecipitation extracts. In vitro assay of degradation is simpler than in vivo analysis, but an in vitro assay system may not fully mimic the degradation of proteins in the cells. Genome-wide functional screening and systemic characterization of cellular short-lived proteins has received little attention [ 7 ]. GFP, the green fluorescent protein from the jellyfish Aequorea victoria , has been widely used to monitor gene expression and protein localization [ 8 ]. Recently, we demonstrated that fusion of GFP to the degradation domain of ornithine decarboxylase [ 9 ], a labile protein, can destabilize GFP [ 10 ] and that the degradation of an IκB-GFP fusion protein can be monitored by GFP fluorescence [ 11 ]. These studies demonstrate that introducing GFP as a fusion within the context of a rapidly degraded protein does not alter the degradation properties of the parent molecule, and that the GFP moiety of the fusion protein is degraded along with the rest of the protein. GFP fluorescence, which provides a sensitive, rapid, precise and non-destructive assay of protein abundance, can therefore be used to monitor protein degradation [ 12 ]. Furthermore, fluorescence associated with single cells can be analyzed using fluorescence-activated cell sorting (FACS), a technology easily adapted to high-throughput screening [ 13 ]. We developed a GFP-based, genome-wide screening method for short-lived proteins. We made a GFP fusion expression library of human cDNAs and introduced the library into mammalian cells. Transfected cells were FACS-fractionated into subpopulations of uniform fluorescence. Individual subpopulations were treated with cycloheximide (CHX) to inhibit protein synthesis and re-sorted after 2 hours of treatment. Sorting was gated to recover cells with a fluorescent signal that was diminished compared to the population mode. Repeated application of this process resulted in a high yield of clones that encode labile fusion proteins. Results The selection scheme is shown in Figure 1 . GFP-cDNA expression libraries were transfected into mammalian cells and cells fractionated into subpopulations, each with a narrow range of fluorescence intensities. Subpopulations were then twice enriched for cells with the desired characteristics. Plasmid DNAs were recovered from the selected cells, subjected to sequence analysis and functionally verified. We made the expression libraries with modified pEGFP C1/C2/C3 vectors by cloning the cDNAs downstream of EGFP. The titer of the library was found to be high: around 10 6 cell transformants per microgram of DNA. In addition, we confirmed by PCR amplification that 95% of clones contained a cDNA insert larger than 800 base-pairs (bp) (data not shown). The libraries were thus deemed to be useful for screening short-lived proteins in mammalian cells. We used 293T cells as the recipient. These cells offer two advantages. First, they express the SV40 large T antigen. This allows the library plasmids, which contain an SV40 origin of replication, to be highly replicated. Plasmids can therefore be recovered easily. Second, 293T cells have high transfection efficiency. After we introduced the GFP-fusion libraries into the mammalian cells, the transfected cells were easily separated by FACS from non-transfected cells or cells transformed by non-productive constructs. We imposed selection for cells that became less bright within 2 hours of exposure to cycloheximide (CHX), a protein synthesis inhibitor. We chose a short treatment time to avoid selecting cells that became dimmer as a result of secondary responses other than rapid turnover of the GFP tagged proteins. To enrich for cells that are susceptible to CHX treatment, we started with a cell population that has an approximately log-normal fluorescence histogram distribution, with a working range of 1.5 to 4.5 logs. We used FACS fractionation to divide this population into five subpopulations (R2, R3, R4, R5, R6) of ascending brightness, gating each on successive one-half log 10 intervals of fluorescence (Figure 2 ). Each subpopulation (R2-R6) was divided into two; one portion was treated with 100 μg/ml CHX for 2 hours and the other left untreated. Subpopulations were then reanalyzed to determine whether they had retained a distribution consistent with the gating criteria used to obtain this narrow subpopulation and were susceptible to CHX treatment. We found that subpopulations R3 and R4 were susceptible to CHX treatment (Figure 3 ), whereas R5 and R6 did not change their fluorescence properties in response to CHX (data not shown). The fluorescence intensity of R2 was too low to detect after CHX treatment. The lack of susceptibility of the brighter R5-R6 subpopulations was most likely the result of their expressing predominantly stable proteins, which would be expected to provide more intense fluorescence. We selected R4 for further screening in this study. We collected 10 6 cells from the shifted population, the left shoulder of the population observed in the CHX-treated but not in the untreated R4 cells (Figure 3 ). Plasmid DNAs were recovered from the sorted cells and were propagated in Escherichia coli , resulting in a total of 400 clones. The individual clones were stored in 15% glycerol LB medium in a 96-well format. To perform second-round selection, we grouped the 400 clones into 12 pools, each composed of approximately 33 clones. The individual pools of clones were cultured and used for plasmid preparation. We transfected these 12 groups of plasmid DNA into 293T cells and again subjected them to FACS analysis and gating as before. The EGFP-C1 vector was used as a control. Because enhanced green fluorescent protein (EGFP) is a stable protein, its fluorescence intensity would not be changed by treatment with CHX. We found that eight of the 12 groups showed a decrease of the fluorescence intensity peak by 30-50% (compared to untreated cells) after 2 hours of CHX treatment. In four out of 12 groups, no change in fluorescence intensity was detected. To isolate individual clones with the desired property, we randomly chose one of the eight CHX-responsive groups and characterized individual clones. We analyzed 30 clones from this group by individually transfecting them into 293T cells and determining the half-life by FACS-based analysis of CHX chase kinetics. We found out that 22 clones showed a decrease in fluorescence intensity ranging from 30 to 90% after treatment with CHX for 2 hours. Assuming first order kinetics of turnover, this single-time-point experiment implies that the proteins corresponding to these 22 clones have a range of half-lives ranging from about half an hour to 3-4 hours (Table 1 ). The 22 clones were partially sequenced and BLAST used to search for similar protein sequences in the National Center for Biotechnology Information (NCBI) public database. Of these, 19 corresponded to annotated genes in GenBank and the remaining three to unknown genes. Sequencing analysis also indicated that the inserts of these clones corresponded to full-length or near full-length translation reading frames. As no data are available on the intracellular turnover kinetics of the 19 identifiable proteins, we picked three clones - splicing factor SRp30c, a guanine nucleotide-binding regulatory protein (G protein), and cervical cancer 1 proto-oncogene protein - and examined their turnover by CHX chase and western blot analysis. These three clones (Table 1 , numbers 5, 19 and 26) were estimated in the fluorescence-based screen to have diverse turnover kinetics; two of them have a half-life of less than 1 hour while the third turns over somewhat more slowly. To confirm these estimates of turnover by a means independent of GFP fluorescence, 293T cells were transfected with these clones, treated with CHX and periodically sampled over the next 3 hours. Western blot analysis of cell extracts with antibody to GFP showed that the abundance of all three fusion proteins diminished in the presence of CHX (Figure 4a ). The half-life of the proteins determined by western blot analysis was similar to that determined by FACS analysis. Two of the proteins showed a half-life of about 1 hour, while the proto-oncogene protein appears to initiate abrupt degradation within about 2 hours of treatment with CHX. The results for all three proteins are thus consistent with those observed using the fluorescence-based screening method. As positive and negative controls, we similarly analyzed cells expressing a destabilized version of EGFP, d1EGFP, whose short half-life has been previously characterized [ 10 ], and a stable EGFP protein (Figure 4b ). Sequencing analysis indicated that these three GFP fusion cDNAs do not contain a full-length coding sequence. SRp30c cDNA is missing 17 amino acids at its amino terminus, G protein 20 amino acids, and proto-oncogene p40 three amino acids. To exclude the possibility that the missing amino acids or the fused GFP domain contribute artifactually to protein liability, we amplified the full-length coding sequences of these three genes and expressed them as Myc fusion proteins. Their turnover was examined by CHX chase and western blot analysis with antibody to the Myc tag (Figure 5 ). Turnover rates assessed in this way were similar to those of the GFP fusion proteins obtained from library screening, ruling out the presence of these artifacts. This technology is subject to two kinds of false-positive results. First, fusion to a detection tag such as GFP or Myc may affect the folding of tagged proteins, which could accelerate their turnover. Second, expression of the fusion proteins under the control of viral promoter elements could result in overexpression, with concomitant misfolding or failure to associate with endogenous interaction partners. To rule out these artifacts, we measured the degradation of native non-fusion endogenous counterparts of two of the proteins we identified, those for which antibodies were available. Turnover of the proteins associated with clone 19 and clone 25 was measured by CHX chase and western blot analysis. The results (Figure 6 ) demonstrated that the half-life of clone 19, a guanine nucleotide-binding regulatory protein (G protein), was less than 1 hour and the half-life of clone 25, heat-shock 70 kD protein (hsp70), was about 1 hour. The turnover of the native proteins is thus at least as fast as that of the corresponding clones analyzed in the screen, suggesting that the technology can accurately identify short-lived proteins. Discussion The abundance of a given cellular protein is determined by the balance between its rate of synthesis and degradation. The two are of equal importance in their effect on the steady-state level. Furthermore, degradation determines the rate at which a new steady state is reached when protein synthesis changes [ 3 ]. Despite its importance, degradation, the 'missing dimension' in proteomics [ 7 ], has received far less comprehensive attention than synthesis. This deficiency has arisen because developing the tools for a proteome-wide study of protein turnover is technically challenging. Proteins that are labile tend to be present at low abundance, and methods for characterizing turnover time are laborious. We have developed an efficient and rather specific screen by combining GFP fluorescence, as a high-throughput measure of protein abundance, with pharmacologic shutoff of protein synthesis. Of 30 clones that were recovered from the screen (Figure 1 ) and individually examined by CHX treatment and FACS analysis, 22 (73%) are associated with proteins with a half-life of less than 4 hours. Given the relative rarity of rapidly degraded proteins in the proteome [ 14 ], this result demonstrates the specificity of the screening method. We have so far analyzed a restricted subset of the clones that were recovered in our screening procedure - 30 clones present in one of eight positive pools (among 12) from the R4 population. A second population, R3, appears to be equally rich in clones responsive to CHX. Extrapolation from this small sample implies that perhaps 300-400 (that is, 22 × 8 × 2) clones within the GFP-cDNA library may be found to be associated with proteins that are labile according to our secondary screening criterion. In contrast to the results with the less bright R3 and R4 cell populations, the failure to detect a CHX-sensitive subpopulation among the brighter R5-R6 cells is consistent with the expectation that labile proteins tend to be of lower abundance than more stable proteins. For some of the proteins uncovered in this survey, rapid turnover can be rationalized as intrinsic to their cellular function. SRp30c factor (accession number U87279) is responsible for pre-mRNA splicing. Alterative splicing is a commonly used mechanism to create protein isoforms. It has been proposed that organisms regulate alternative splice site selection by changing the concentration and activity of splicing regulatory proteins such as SRp30c in response to external stimuli [ 15 ]. The finding that SRp30c is a short-lived protein is consistent with its postulated regulatory function. The G proteins are a ubiquitous family of proteins that transduce information across the plasma membrane, coupling receptors to various effectors [ 16 , 17 ]. About 80% of all known hormones, neurotransmitters and neuromodulators are estimated to exert their cellular regulation through G proteins. The G protein (accession number M69013) shown here to short-lived is a G protein α subunit that transduces signals via a pertussis toxin-insensitive mechanism [ 18 ]. Like other pertussis toxin-insensitive G proteins such as the Ga12 class, it causes the activation of several cytoplasmic protein tyrosine kinases: Src, Pyk2 (proline-rich tyrosine kinase 2) and Fak (focal adhesion kinase) [ 19 ]. However, it is not known how this G protein is regulated. Its rapid turnover suggests a testable mechanism of its regulatory activation. Cervical cancer 1 proto-oncogene protein p40 (accession number AF195651), is a third protein shown here to turn over rapidly, but its function is unknown. Further studies of its turnover may provide important information on its function and regulation. In mammalian cells, proteasomes have the predominant role in the degradation of short lived proteins, whereas lysosomal degradation appears to be quantitatively less important [ 20 ]. Determining the mechanism that cells use to degrade the proteins uncovered by the method described here will require the use of specific inhibitors [ 21 ]. Before degradation, most short-lived proteins are covalently coupled to multiple copies of the 76-amino-acid protein ubiquitin [ 22 ], a reaction catalyzed by a series of enzymes [ 23 ]. These ubiquitinated proteins are recognized by the 26S proteasome and degraded within its hollow interior [ 24 ]. This system of regulated degradation is central to such processes as cell-cycle progression, gene transcription and antigen processing. A few proteins have been found to be exceptions [ 25 , 26 ]; like ODC, they do not require ubiquitin modification for degradation by the proteasome. In most cases it is not clear how short-lived proteins are selected to be modified and degraded. Some rapidly degraded proteins have been shown to contain an identifiable 'degradation domain'. Removal of this degradation domain makes such proteins stable, and appending this domain to a stable protein reduces its stability. Such a degradation domain has been identified in a number of short-lived proteins, including the carboxy terminus of mouse ODC [ 6 , 27 ] and the destruction box of cyclins [ 28 ]. In some cases, the signal is a primary sequence - like the PEST sequence [ 29 , 30 ]. However, the identifiable structural features of such degradation domains are not sufficiently uniform to provide a reliable guide to identifying labile proteins. The method we have described does not use ubiquitin conjugation as a search criterion. This approach thus has the potential to discover labile proteins regardless of whether ubiquitin modification plays a role in their turnover. Once a large and representative sample of short-lived proteins is identified, a search for structural motifs among these proteins may facilitate the discovery of those motifs which correlate to protein degradation. Conclusions In this study we have developed an innovative technology to identify labile proteins using GFP-fusion expression libraries. Using this technology we have discovered short-lived proteins in a high-throughput format. This technology will greatly facilitate the discovery and study of short-lived proteins and their cellular regulation. Materials and methods Construction of GFP-cDNA expression libraries Messenger RNAs from brain, liver, and the HeLa cell line (Clontech) were used as templates for cDNA synthesis, using a cDNA synthesis kit from Stratagene according to the manufacturer's recommendation, with some modifications. First-strand cDNA was synthesized using an oligo(dT) primer-linker containing an Xho I restriction site and with StrataScript reverse transcriptase. Synthesis was performed in the presence of 5-methyl dCTP, resulting in hemimethylated cDNA, which prevents endogenous cutting within the cDNA during cloning. Second-strand cDNA was synthesized using E. coli DNA polymerase and RNase H. Adaptors containing Eco RI cohesive ends were introduced into the double-stranded cDNA, which were then digested with Xho I. The cDNAs contained two different sticky ends: 5' Eco RI and 3' Xho I. The cDNAs were separated on a 1% SeaPlaque GTG agarose gel in order to collect those larger than 800 bp. After extracting cDNAs from the agarose gel with AgarACE-agarose-digesting enzyme followed by ethanol precipitation, the cDNAs were directionally cloned into EGFP-C1/2/3 expression vectors with three open reading frames (ORFs) (Clontech). The vectors were modified within the multiple cloning sites in order to be compatible with the cDNA orientation. By this means, cDNA ORFs were aligned to the carboxy terminus of EGFP. The host cell used for plasmid transfection and expression, 293T, expresses the SV40 large T antigen. Therefore, the cDNA EGFP-C1/2/3 vector containing the SV40 origin of replication can replicate independently from chromosome DNA in the host cells, which facilitates the recovery of plasmid DNAs from the host cells. Transfection of the libraries into 293T cells 293T cells were cultured at 37°C in DMEM (Invitrogen) supplemented with 10% FBS, 1% nonessential amino acids and 100 U/ml penicillin, 0.1 mg/ml streptomycin. One day before transfection, cells were seeded in 10-cm plate in 10 ml growth medium without antibiotics. Transfection was performed using Lipofectamine 2000 reagent according to the manufacturer's instructions. Samples (25 μg) of a cDNA library were diluted in 1.5 ml Opti-MEM (Invitrogen). Lipofectamine 2000 was diluted in 1.5 ml Opti-MEM and mixed with diluted DNA. After 20 min incubation, the DNA-Lipofectamine 2000 complex was added to the cells. The cells were incubated for 16 h before analysis. FACS analysis of GFP-expressing cells Cells were harvested by trypsinization, washed, and resuspended in DMEM. Cytometric analysis and sorting were performed using a hybrid cell sorter combining a Becton Dickinson FACStarPLUS optical bench with Cytomation Moflo electronics (Stanford Beckman Center shared facility). Green fluorescence was measured using a 525/50 band pass filter. Gates were set to exclude cellular debris and the fluorescence intensity of events within the gated regions was quantified. Fluorescence-activated cell sorting was performed with a lower forward scatter threshold to detect transfected cells while ensuring that debris and electronic noise were not captured as legitimate events. Transfection efficiency was so high that normal voltages for detecting GFP were reduced. For fractionation, the cell population was gated on the basis of the fluorescence intensity. Cells were sorted at a rate of 8,000 events/sec. 10 6 cells were collected in 12 × 75 mm glass tubes containing 200 μl serum to enhance the cell survival rate. For short-lived protein screening, sorted cells were recultured in a 12-well plate and treated with or without 100 μg/ml CHX for 2 h. The cells then were collected and subjected to FACS analysis and sorting. The cells showing a decrease in fluorescence intensity with CHX treatment were collected for further analysis. Plasmid recovery Plasmid DNA was extracted from sorted cells using a Qiagen mini-plasmid preparation kit. Plasmid DNAs were eluted in water and transformed into electro-competent DH10B E. coli (Invitrogen). Bacterial colonies were transferred to 96-well plates containing LB with 50 μg/ml kanamycin and 30% glycerol. After overnight growth at 37°C, the colonies are stored at -80°C. Plasmid DNAs were prepared from individual clones, sequenced and BLAST searches performed against the NCBI database. Construction of Myc-tagged full-length coding sequences of genes To obtain full-length coding sequence of the genes, we amplified them with a human full-length cDNA kit (Panomics) according to the manufacturer's instructions. The full-length coding sequences of cDNAs were then cloned into the pCMV-Myc vector (Clontech) for expression in 293T cells. Western blot analysis of protein degradation The plasmid DNAs of individual clones were prepared and transfected into 293T cells. The transfected cells, with or without CHX treatment, were collected in PBS and cell lysates were prepared by sonication. Proteins were resolved by SDS-polyacrylamide gel electrophoresis and transferred to a membrane. Fusion proteins were detected using a polyclonal antibody against GFP (Clontech), a monoclonal antibody against the Myc epitope (Sigma), a polyclonal antibody against G protein (Santa Cruz) or an antibody against Hsp70 (Santa Cruz). Bands were visualized with SuperSignal West Pico kit (Pierce). Additional data files Additional data file 1 contains the original data used to perform this analysis and is available with the online version of this paper. Supplementary Material Additional data file 1 The original data used to perform this analysis Click here for additional data file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545601.xml
545198	Seasonal Patterns of Infectious Diseases	Why is that many infectious diseases, like cholera, malaria, and meningococcal meningitis, show seasonal patterns? And how can we accurately determine these patterns?	Meningococcal meningitis in western Africa shows recurrent seasonal patterns every year. Epidemics typically start at the beginning of February and last until May. We can try to explain the observed patterns on the basis of some seasonally varying environmental factor that favors disease transmission. Air dryness produced by strong dust winds is the most likely candidate. But while there are qualitative “stories” of this kind in the literature for many seasonal phenomena, convincing quantitative evidence to support them remains largely elusive. Instead, we tend to see weak associations between environmental and transmission variables when measured by simple, linear correlations. The study of meningococcal meningitis in Mali by Sultan and colleagues in this issue of PLoS Medicine is a remarkable exception [1] . The study reports a strong association between the yearly onset of epidemics and a large-scale regional index for atmospheric circulation related to the Harmattan winds in Sahelo-Sudanian Africa. The Importance of Seasonality Why is a focus on the seasonality of infectious diseases and its variation from year to year so important? Isn't it more important for us to instead understand the effects of long-term climate change on human health? At first sight, understanding seasonal patterns seems disconnected from understanding the impact of long-term climate change. However, seasonal patterns are one major pathway for the subtle but potentially drastic effects of climate change on disease dynamics. Long-term climate change affects seasonal patterns through the lengthening of the transmission season and the crossing of environmental and demographic thresholds that underlie seasonal outbreaks [2] . Thus, identifying the specific environmental factors underlying seasonal transmission is a critical step towards predicting and understanding how long-term environmental trends in mean climate and their variability will impact human health. The Problem of Scale One important difficulty in uncovering seasonal drivers of infectious diseases is to identify the appropriate scale of analysis. The relationship between disease and climate described by Sultan and colleagues only becomes apparent at large spatial scales. The authors argue that these large scales are necessary to eliminate “idiosyncratic” variability in the relationship between cases and climate at the local level. In other words, there are only weak correlations between seasonal variations and climate variables at small scales because of the multiple other factors that play a local role and act as noise. But we should be cautious about the suggestion that appropriate larger scales will always resolve the problem of local variability and present strong linear associations between climate and disease. Public health measures might require predictions not only at national and regional scales, but also at a variety of smaller scales. Moreover, one important source of variation in how infectious diseases respond to climate is the fraction of susceptible individuals in the population. This fraction varies over time as the result of immunity acquired by previous infection, and by the input of births and migrants into the pool of susceptible people. The constant waxing and waning of this pool of hosts underlies the intrinsic potential of the population dynamics of infectious diseases to oscillate and create epidemic outbreaks. The tendency of these intrinsic cycles to go up and down in synchrony at different locations in space will determine whether susceptibility levels act as noise at small scales or, alternatively, whether their effect must be considered in conjunction with climate at larger scales. Because the number of susceptible individuals is a hidden variable in most epidemiological analyses, recently proposed methods for its reconstruction from data on cases must be combined with studies on climate variation if we are to understand the interaction between susceptibility levels and climate variation [ 3 , 4 , 5 ]. The problem of scale also arises when we need to identify the appropriate timing (the temporal window) to detect strong associations between disease outbreaks and environmental covariates. This is particularly important when strong couplings between environment and transmission occur only transiently. This seems to be the case for cholera in Bangladesh, where couplings are strong during El Niños, but considerably weaker the rest of the time [6] . Intermittent couplings provide insight into how the system might behave if pushed into specific dynamic regions by a change in climate. Intermittent couplings also suggest the existence of thresholds in the response to climate, an area of research that remains in need of quantitative approaches. Seasonal Drivers May Be Elusive Besides scale, specific seasonal drivers are often elusive because of the simpler reason that in nature seasonality is ubiquitous. Multiple and covarying drivers have been proposed for the seasonal nature of cholera, including temperature, rainfall, and plankton blooms [7] . Yet the specific roles of these drivers in the bimodal seasonal cycle of cholera, and particularly in the second peak in endemic regions in south Asia, have not been convincingly shown ( Figure 1 ) [8] . We still don't have predictive explanations of the geographic variation in seasonal patterns. We won't find such explanations by considering the average seasonal pattern; instead, we must consider the anomalies in amplitude and onset of the peaks that occur in different years. Figure 1 The Role of Rainfall in Driving the Seasonal Nature of Cholera Is Unclear This photograph was taken during a cholera and nutrition survey during flooding in Bangladesh in 1974. In Bangladesh, monsoon rains appear to have a seasonal “dilution” effect on transmission, producing a decrease in cholera cases during that season. We don't know whether extreme rains also produce a lagged increase in cases later on in the cycle. In other parts of the world, cases typically peak during the rainy season. (Photo: Jack Weissman, Centers for Disease Control and Prevention) Ecologists have considered seasonality in mathematical models of the population dynamics of infectious diseases. Models of populations with seasonally forced, dynamic interactions (births, deaths, aggregation, or disease transmission) reveal an array of possible responses, from simple yearly cycles, through cycles that repeat with longer periods, to irregular chaotic fluctuations. Some models also predict intermittent switching between different dynamic infectious disease behaviors. But typical models consider only simple seasonal forcing functions (mathematical functions that are periodic in time and therefore describe in a generic way the seasonal variation in the transmission rate or some other seasonal parameter—a sine wave is an example). There are some important exceptions to this—some models do incorporate more complicated seasonal forcing functions that describe the actual processes underlying the seasonal drivers of transmission. Examples are models of childhood diseases that describe the regular stopping and starting of school terms [ 9 , 10 , 11 ], and recent malaria models that include the seasonal dynamics of mosquito births and pathogen incubation as functions of temperature and rainfall [12] . The explicit way in which models treat seasonal environmental drivers may be critical in addressing the links between within-year seasonal cycles and those of longer period that are observed in many infectious diseases. For meningococcal meningitis, we still need to examine the connection between the seasonal association described by Sultan and colleagues and the previously proposed role of humidity in inter-annual cycles [13] . The Complexity of Infectious Disease Dynamics Sultan and colleagues' study is exceptional in that it illustrates a clear relationship between an external environmental variable and the initiation of disease outbreaks. In contrast, many studies seeking environmental drivers are plagued by the many confounding factors, particularly the impact that other components of global change have on the transmission dynamics of infectious diseases. Thus, when we examine datasets for malaria, we must also consider the evolution of drug resistance and a growing human population that is increasingly forced to live in areas that are marginal for agricultural production but optimal for malaria transmission. Given this complexity, a serious limiting factor to quantitative analyses and predictive models of ecological and disease patterns is the lack of long-term disease records with similar data collected over a network of spatial locations. The handful of extremely valuable records that have allowed progress in understanding long-term patterns in disease dynamics pale in comparison to the spatiotemporal coverage available for climate studies and modeling. The need to resolve these issues of scale and confounding variability only underscores the urgency and importance of maintaining and developing systematic surveillance programs for infectious diseases around the world.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545198.xml
509423	Similar group mean scores, but large individual variations, in patient-relevant outcomes over 2 years in meniscectomized subjects with and without radiographic knee osteoarthritis	Background Epidemiological studies have, so far, identified factors associated with increased risk for incident or progressive OA, such as age, sex, heredity, obesity, and joint injury. There is, however, a paucity of long-term data that provide information on the nature of disease progression on either group or individual levels. Such information is needed for identification of study cohorts and planning of clinical trials. The aim of the study was, thus, to assess the variation in pain and function on group and individual level over 2 years in previously meniscectomized individuals with and without radiographic knee osteoarthritis (OA). Methods 143 individuals (16% women, mean age at first assessment 50 years [range 27–83]) were assessed twice; approximately 14 and 16 years after isolated meniscectomy, with a median interval of 2.3 years (range 2.3–3.0). Radiographic OA (as assessed at the time of second evaluation) was present in the operated knee in 40%, and an additional 19% had a single osteophyte grade 1 in one or both of the tibiofemoral compartments. Subjects completed the self-administered and disease-specific Knee injury and Osteoarthritis Outcome Score (KOOS). Results There were no significant changes in the group mean KOOS subscale scores over the 2-year period. However, a great variability over time was seen within individual subjects. Out of 143 subjects, 16% improved and 12% deteriorated in the subscale Pain, and 13% improved and 14% deteriorated in the subscale ADL ≥ 10 points (the suggested threshold for minimal perceptible clinical change). Similar results were seen for remaining subscales. Conclusion Group mean scores for this study cohort enriched in incipient and early-stage knee OA were similar over 2 years, but pain, function and quality of life changed considerably in individuals. These results may be valid also for other at risk groups with knee OA, and motivate further careful examination of the natural history of OA, as well as properties of the OA outcome instruments used. Longitudinal outcome data in OA studies need to be analyzed both on an individual and a group level.	Background Drugs that may slow or halt the breakdown of cartilage and other joint tissues in osteoarthritis (OA) and possibly improve symptoms and function are now being developed in the pharmaceutical industry. The potential availability of disease modifying OA drugs has focused attention on our relative lack of information on the 'natural disease history' of OA with regard to changes in symptoms, functional limitations, joint structure and other markers of disease change [ 1 ]. Epidemiological studies have identified factors associated with increased risk for incident or progressive OA, such as age, sex, heredity, obesity, and joint injury, pain, alignment, or laxity. There is, however, a paucity of long-term data that document the rate and nature of natural OA disease progression on either group or individual levels. Such information is needed for identification of study cohorts and planning of clinical trials of disease modifying OA drugs. Even more importantly, knowledge of natural disease progression in different patient groups will be needed to select those future groups that may benefit from such drugs. Only a few of the previously published studies have presented information on longitudinal variation in pain and function in the natural history of knee OA. The "Bristol 500 OA study" noted, that although pain changed little on a group level over a 3-year follow-up period, it varied greatly in individuals, with some subjects reporting marked improvements. Similarly, a minority improved functionally [ 2 - 4 ]. Yet another report suggested that most patients with OA attending rheumatology clinics do not deteriorate radiographically or symptomatically over an 11-year period [ 5 ]. A more recent report stated that 42–44% of community-recruited knee OA individuals did not change in physical functioning over a 3-year study [ 6 ]. Most investigations of the natural history of OA have been concerned with radiographic rather than clinical changes. For example, it was reported that the radiographic Kellgren and Lawrence classification score of 1 could represent incipient OA and be predictive of later development of more advanced radiographic features of OA [ 7 ]. MRI may be more responsive to change in early-stage OA than plain radiography [ 8 ]. However, outcome is usually heterogeneous: study subjects may report improvement or deterioration while they do not change radiographically over the time period assessed. It may also be that a few individuals alone generate much of any change detected at group level [ 9 - 11 ]. A further confounding factor in the longitudinal assessment of OA is the potential influence of the population from which the study group was recruited; a study group recruited from e.g. a specialist outpatient clinic is likely to have, on the average, more severe disease and may be at different risk to progress over time than a study group recruited from the community. The objective of this investigation was to assess both group and individual variation in knee pain, function and quality of life over two years in a study group enriched in incipient and early-stage radiographic knee OA. Methods Patients Approval was obtained from the Research Ethics Committee of the Medical Faculty of Lund University, Sweden. All patients who underwent meniscectomy between 1983 and 1985 were identified by searching the surgical records at the Department of Orthopedics, Lund University Hospital. In this period 552 meniscectomies were performed. Inclusion and exclusion criteria (Figure 1 ) were used to identify 264 former patients who, in 1998, were sent a self-administered questionnaire evaluating their knee-specific symptoms and knee function. Figure 1 Flow chart presenting the inclusion and exclusion criteria for patients. ACL = anterior cruciate ligament, PCL = posterior cruciate ligament, OA = osteoarthritis. Out of 211 individuals (80%) who returned the questionnaires, 6 were excluded because they matched one of the exclusion criteria. At 2 years after the first assessment 5 subjects had died, but the remaining 200 individuals were asked to provide a second evaluation using an identical questionnaire. Replies were received from 143 (72%). Of these 143 participants, 102 were meniscectomized by open surgery, and 41 by arthroscopy. Nineteen underwent an additional meniscus operation in the index knee. All re-operations were performed within 3 years after the original meniscectomy. Twenty-three participants were treated with subsequent meniscectomy of the contralateral knee. One of them underwent high tibial osteotomy and 1, because of OA, received a knee prosthesis in the contralateral knee. Data concerning subsequent surgeries were based on the medical records of Lund University Hospital and on self-reported information. Radiographic assessment At the time of the participants' second evaluation with questionnaires, standing anteroposterior (AP) radiographs of both knees were taken in 15 degrees of flexion using a CGR Phasix 60 generator at 70 kV, 16 mA, film-focus distance 1.5 m (CGR, Liège, Belgium). Ten out of the 143 participants (7%) declined the radiographic examination. All AP radiographs of the tibiofemoral joints from the follow-up were assessed for joint space narrowing (JSN) and osteophytes according to the atlas from Osteoarthritis Research Society International (OARSI) [ 12 ]. The presence of these features was graded on a 4-point scale (range 0–3, with 0 = no evidence of bony changes or JSN). We considered radiographic knee OA to be present if any of the following criteria was achieved in any of the 2 tibiofemoral compartments: JSN ≥ grade 2 or the sum of the 2 marginal osteophyte grades from the same compartment ≥ 2, or JSN grade 1 in combination with an osteophyte grade 1 in the same compartment [ 13 , 14 ]. This cut-off approximates grade 2 knee OA or worse based on the Kellgren and Lawrence scale [ 15 ]. Disease-specific questionnaire The Knee injury and Osteoarthritis Outcome Score (KOOS, Swedish version LK 1.0) is a 42-item self-administered knee-specific questionnaire based on the WOMAC Osteoarthritis Index [ 16 , 17 ]. KOOS was developed to be used for short- and long-term follow-up studies of knee injuries, and it comprises 5 subscales: Pain, Symptoms, Activities of Daily Living (ADL), Sports and Recreation Function (Sport/Rec) and knee-related Quality of Life (QOL). A separate score ranging from 0 to100, where 100 represents the best result, is calculated for each subscale. The questionnaire and scoring manual can be downloaded from . The KOOS is valid, reliable and responsive in follow-up of meniscectomy [ 17 ], anterior cruciate ligament reconstruction [ 18 ] and total knee replacement for OA [ 19 ]. The participants completed the KOOS questionnaire answering questions on their operated index knee. Change The minimal perceptible clinical improvement (MPCI) represents the difference on the measurement scale associated with the smallest change in the health status detectable by the individual. Since the KOOS questionnaire contains the full and original version of the WOMAC LK 3.0 index, we used the MPCI as described for WOMAC [ 20 ]. Thus, a level of 10 points or more of improvement or decline was operationally used as a cut-off representing a clinically perceptible difference. The sensitivity of the questionnaire has been established [ 21 ]. Data collection and statistics If questions were left unanswered in any part of the questionnaire, we returned the questionnaire to be completed. The questionnaires were then completed fully. The Mann-Whitney U-test was used to determine differences between the groups. P -values for categoric data were calculated with Fisher's exact test. All tests were 2-tailed and a P -value of ≤ 0.05 was considered statistically significant (SigmaStat, version 2.0, for Windows). Results Group level The study group comprised 143 individuals, of whom 23 (16%) were women. The participants' mean age at the first follow-up was 51 (range 27–83) years. The assessment was carried out twice: at approximately 14 and 16 years after the surgery, with a median interval of 2.3 (range 2.3 to 3.0) years. Fifty-three (40%) of the 133 individuals who had undergone radiographic examination had radiographic tibiofemoral OA in their index (operated) knee (21% women, age range 29–83, mean 53) and 80 were classified as non having OA (11% women, age range 27–82, mean 50). An additional 25 (19%) (not classified as radiographic OA) had a single osteophyte grade 1 in either one or both tibiofemoral compartments. Mean scores for the KOOS subscales at the first assessment did not change significantly over the 2-year study period (Table 1 ). Moreover, there were no significant changes in group mean subscale scores over 2 years when participants were divided into those with or without radiographic OA in the index knee (Table 1 , Figure 2 ). However, individuals with radiographic OA scored worse at both examinations than did those without radiographic OA. The differences between those with and without OA were statistically significant for KOOS Pain Δ = 11 points ( P = 0.004), other Symptoms Δ = 9 points ( P = 0.013), ADL Δ = 10 points ( P = 0.003), Sport/Rec Δ = 17 points ( P = 0.005), and QOL Δ = 16 points ( P = 0.003) assessed in 2000, and in the dimensions Sport/Rec Δ = 14 points ( P = 0.020) and QOL Δ = 12 points ( P = 0.041) evaluated in 1998. Table 1 KOOS scores overall and in patients without and with radiological signs of OA KOOS subscales Patients p-values Total group non-ROA ROA non-ROA vs. ROA n = 143 n = 80 n = 53 1998 2000 1998 2000 1998 2000 2000 pain mean 85 84 88 87 79 76 0.008 median 94 94 94 94 86 83 SD 20 21 16 18 24 25 range 19–100 25–100 39–100 25–100 19–100 25–100 symptoms mean 85 84 87 87 80 78 0.013 median 93 89 93 93 89 82 SD 19 18 17 16 23 21 range 14–100 14–100 25–100 18–100 14–100 14–100 ADL mean 88 88 90 91 83 81 0.004 median 99 97 99 99 94 90 SD 18 18 15 15 23 21 range 18–100 31–100 44–100 34–100 18–100 31–100 sports/rec mean 69 68 74 76 60 57 0.007 median 80 80 80 85 60 60 SD 31 32 28 28 34 34 range 0–100 0–100 0–100 0–100 0–100 0–100 QOL mean 75 73 78 78 67 63 0.005 median 81 81 81 84 69 63 SD 26 27 23 23 30 30 range 0–100 6–100 25–100 6–100 0–100 13–100 Mean, median, standard deviation and range of KOOS scores overall and in patients without and with radiological signs of OA. Note that 10 patients out of 143 did not undergo radiographic examination. P -values for comparison between KOOS subscale results in patients with and without OA in year 2000 are presented. Figure 2 Group mean KOOS scores for patients assessed in 1998 and 2000. Group mean KOOS scores for patients with (n = 53) and without (n = 80) radiographic osteoarthritis (ROA) assessed in 1998 and 2000. Possible score range 0 to 100, with 100 representing the best result. ADL – Activities of Daily Living, QOL – knee-related Quality of Life. Bars present ± 95% confidence intervals. The bars going upwards have wider caps. Note vertical axis break. We analyzed separately those subjects (N = 57) that did not participate in the second assessment. Their mean KOOS scores at the first examination did not differ significantly from the remainder of the study cohort, indicating little or no inclusion bias for the second follow-up (data not shown). The scores in the 5 patients that underwent additional surgery (e.g. osteotomy, knee arthroplasty) did not differ significantly from the rest of the group. Individual study subject changes In spite of the lack of change on a group level, we found substantial intra-individual variability in the questionnaire subscale scores measured 2 years apart. Out of the total 143 study subjects, 40 had either improved or deteriorated (n = 23 (16%) and n = 17 (12%), respectively) 10 points or more for the KOOS subscale Pain. Of the 23 subjects who had improved in their pain score by these criteria, 14 had also improved in the subscale Symptoms, 17 in ADL, 16 in Sports/Rec, and 17 in QOL. Only 1 of these subjects deteriorated in Symptoms, and 2 in Sports/Rec, none in the other subscales. Of the 17 subjects who deteriorated in Pain, 13 similarly deteriorated in Symptoms, 12 in ADL, 10 in Sports/Rec, and 10 in QOL. When evaluating those who had undergone radiographic examination, there were no significant differences in variability detected whether the subject had radiographic tibiofemoral OA or not ( P = 0.24, Table 2 ). Table 2 The percentage of patients improving, not changing, or deteriorating for KOOS subscales over time non-ROA ROA KOOS subscales cut-off n = 80 n = 53 + no change -- + no change -- % % pain 10 13 76 11 21 66 13 20 6 88 6 8 87 6 symptoms 10 16 69 15 26 55 19 20 6 86 8 13 77 9 ADL 10 9 79 13 19 64 17 20 5 86 9 15 79 6 sports/rec 10 19 60 21 28 42 30 20 11 76 13 21 64 15 QOL 10 20 56 24 26 57 17 20 5 88 8 15 75 9 The percentage of patients, with and without radiographic osteoarthritis (ROA), improving, not changing, or deteriorating for KOOS subscales over the 2 year study period. For definition of ROA see methods. Two cut-offs for change (≥ 10 and ≥ 20 points) are presented. We also evaluated a stricter cut-off of 20 points or more as used for the OARSI responder criteria, as opposed to minimal clinically perceptible change [ 22 ]. With this cut-off, in total 19 patients fulfilled the criterion for improvement or deterioration (n = 9 (6%), n = 10 (7%), respectively) in KOOS Pain. Among the subjects with radiographic OA, 3 (6%) improved and 4 (7%) deteriorated by 20 points or more. Corresponding numbers for those without radiographic OA were 5 (6%) for both improvement and deterioration. In order to explore these changes in more detail, the subjects were divided into quartiles, according to KOOS Pain score at the first assessment (Figure 3 ). The most noticeable changes were found in the quartile representing the worst scores: 21 of 36 (58%) subjects showed a change of 10 points or more in either direction. A corresponding change was seen in 11 (31%) individuals from the second worst quartile and in only 9 (25%) from the second best and best quartiles (6 and 3 subjects, respectively). Comparable results were seen for the other subscales of KOOS (data not shown). Figure 3 KOOS Pain subscale. Patients are divided into 4 subgroups (quartiles) according to the score at entry. Each line represents one patient visualizing the score in 1998 (left endpoint of line) and in 2000 (right endpoint of the same line). Discussion We found no significant change over 2 years in the average patient-relevant outcome scores for this study group of individuals who had undergone meniscectomy about 15 years earlier, even though the group was highly enriched in early-stage and incipient radiographic knee OA. However, we found substantial change in the self-report for individual subjects over the same time period. The generally worse KOOS scores for the individuals with radiographic knee OA, compared to those without, are consistent with earlier reports. Thus, the Baltimore Longitudinal Study of Aging reported that patients with a Kellgren-Lawrence score of 1 were almost twice as likely to report ever having knee joint pain compared with those who had a score of zero. The strength of the association increased with increasing Kellgren and Lawrence score [ 23 ]. Similarly, there was in meniscectomized individuals evidence for a graded increase in pain and functional limitations with increasing severity of radiographic signs of OA [ 24 ]. However, a discrepancy between knee pain and radiographic features of knee OA has also been noted, both cross-sectionally and longitudinally [ 3 , 24 , 25 ]. Depression and lack of muscle strength have been shown to better explain pain than radiographic findings [ 26 - 28 ]. Individual vs. group analysis Few reports have explored OA symptom variation on an individual level [ 2 - 4 ]. A detailed comparison of our results with earlier reports is difficult, since they were conducted before validated and patient-relevant OA disease-specific measurement tools had been widely introduced. The "Bristol OA 500" were patients with advanced radiographic knee OA and a mean age of 65 years recruited from a hospital based rheumatology clinic. In contrast, the mean age of the present study cohort was 50 years, with 2/5 having mild-moderate radiographic OA, and another 1/5 incipient radiographic changes. Further, the cohort reported on here was recruited from a group of individuals that had undergone isolated meniscectomy 15 years earlier, but independent of their subsequent symptom level or disease history. The mean scores of our study group were relatively good and not representative of subjects with advanced OA seeking medical care. The rationale for investigating this particular cohort at this time after surgery was its enrichment in early-stage knee OA, and that it consequently may represent a study group suitable for future pharmacological disease-modifying intervention. We assessed our patients at an interval of 2 years; this period of time being suggested as a minimum for clinical trials of disease modification in OA to detect both structural and symptom change [ 29 ]. It could be that the findings reported here are valid only for post-injury, secondary OA, or for this particular cohort. However, the criteria and delimitations for posttraumatic OA compared to primary OA have recently been shown to be much less clear than thought [ 13 , 14 , 30 ], and meniscal pathology is common also in primary, garden-variety, knee OA [ 31 ]. Tibiofemoral OA was observed in 53 out of 133 patients who were underwent radiographic examination. Isolated patellofemoral OA was rare and, since it did not affect the final results, was not taken into account. A further argument favoring the general applicability of the present results is the concordance of our findings with other longitudinal studies on OA [ 2 - 5 , 32 ]. Methodological issues We applied the criteria for minimal perceptible clinical improvement (MPCI) obtained for the WOMAC; since KOOS contains the WOMAC items and is similar in format. The KOOS subscale ADL is equivalent to the WOMAC subscale Function, while new items have been added to the KOOS subscales Pain and Symptoms. The dimensions assessed by the KOOS subscales Sport and Recreation Function and knee-related Quality of Life are not assessed by the WOMAC. The MPCI for the WOMAC is in the range of 8 to 12 points on a 0–100 scale [ 20 ]. This threshold coincides with the change observed in KOOS scores between 3 and 6 months postoperatively when assessing rehabilitation following reconstruction of the anterior cruciate ligament and concurs with the OARSI definition of moderate improvement in the knee pain assessment for clinical trials in OA [ 18 , 22 ]. However, the OARSI responder criteria were designed for the evaluation of the patient's response to oral NSAID and intra-articular treatment and may differ for other interventions. It may be argued that the subject-related changes observed in this study represent inherent instrument instability. However, validation studies of KOOS support the reproducibility and stability of the KOOS instrument [ 17 - 19 ]. Test-retest data on the KOOS subscale pain obtained from 75 patients about to undergo knee arthroscopy [ 17 ] was used to determine the number of subjects improving, deteriorating or not changing over an average period of 5 days. The proportion of subjects changing over 5 days was approximately half of that changing over 2 years in the present study, in further support that the variation in the present study cannot be explained solely by instrument noise (data not shown). A 'frame shift' in the priorities of the individual patient may occur during long term studies. However, we suggest that a significant frame shift is unlikely to have occurred over this 2 year study period of a cohort with a mean age of 50 years. Significant change of KOOS scores over time were noted in 1/3 of the cohort studied. About half of those who changed clinically improved. This was true in particular for patients with lower (worse) baseline scores. It is thus possible that the lower proportion of 'changers' among those with better baseline scores may have been, at least in part, due to a ceiling effect. Conclusions We conclude that despite unchanged group mean scores over 2 years, pain, function and quality of life change considerably over time in individuals, in this study cohort enriched in incipient and early-stage knee OA. These findings may be applicable also to other at risk patient groups in different phases of OA development, and motivate further careful examination of the natural history of OA, as well as properties of the OA outcome instrument used. We suggest that longitudinal OA study data should be analyzed both on the individual and group level. Our findings may have further relevance to clinical trials of OA that seek to document long term benefit in the form of symptom improvement and structural improvement. It is clear that much additional effort will need to be spent on selection of groups at high risk of progression of symptoms and structural joint change, and the identification of predictors for deterioration. Our results also suggest that the use of responder criteria may be an important aspect of analyzing the outcome of such trials [ 22 , 33 ]. Authors' contributions EMR and LSL planned study and collected the data. PTP performed the statistical analysis and drafted the manuscript. ME formed the database of patients and participated in the statistical analysis. ME, EMR, LSL corrected the manuscript. All authors read and approved the manuscript	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509423.xml
526371	An unusual case of an ulcerative colitis flare resulting in disseminated intravascular coagulopathy and a bladder hematoma: a case report	Background Disorders of coagulation have long been associated with inflammatory bowel disease. Children, as well as adults, with both active and inactive ulcerative colitis have been found to have abnormal coagulation and fibrinolysis. Disseminated intravascular coagulation arises from an overwhelming of the haemostatic regulatory mechanisms leading to an excessive generation of thrombin and a failure of the normal inhibitory pathways to prevent systemic effects of this enzyme. Ulcerative colitis has been associated with disseminated intravascular coagulation in conjunction with septicemia, toxic megacolon and surgery. Case presentation A fourteen-year-old boy with a history of poorly controlled ulcerative colitis presented with nonbilious emesis, hematochezia, and hematuria. Laboratory workup revealed disseminated intravascular coagulation. He was placed on triple antibiotics therapy. An infectious workup came back negative. A computerized tomography (CT) scan of the abdomen revealed a marked thickening and irregularity of the bladder wall as well as wall thickening of the rectosigmoid, ascending, transverse, and descending colon. Patient's clinical status remained stable despite a worsening of laboratory values associated with disseminated intravascular coagulation. Patient was begun on high dose intravenous steroids with improvement of the disseminated intravascular coagulation laboratory values within 12 hours and resolution of disseminated intravascular coagulopathy within 4 days. A thorough infectious workup revealed no other causes to his disseminated intravascular coagulation. Conclusions The spectrum of hypercoagulable states associated with ulcerative colitis varies from mild to severe. Although disseminated intravascular coagulation associated with ulcerative colitis is usually related to septicemia, toxic megacolon or surgery, we present a case of an ulcerative colitis flare resulting in disseminated intravascular coagulation and a bladder hematoma.	Background A wide variety of disorders are associated with the development of disseminated intravascular coagulation (DIC). Initiation usually involves mechanical tissue injury and or endothelial cell activation and injury. DIC arises from an overwhelming of the haemostatic regulatory mechanisms leading to an excessive generation of thrombin and a failure of the normal inhibitory pathways to prevent systemic effects of the enzyme leading to DIC [ 1 ]. Ulcerative colitis has been associated with DIC. In previously reported cases, DIC has arisen from active disease in conjunction with septicemia, toxic megacolon or surgery [ 2 - 5 ]. The authors report a pediatric case of DIC associated with a colitis flare resulting in a bladder hematoma. Case presentation A 14-year-old boy with a diagnosis of ulcerative colitis based on colonic histology, serology and a normal barium study of his small bowels was admitted with a five-day history of nonbilious vomiting and bloody diarrhea. Additional symptoms included recent onset hematuria, and low-grade fevers to 100.4 C over the prior four days. He had also sustained a 25 lb weight loss in the last six months, indicating a lack of disease control. As an outpatient, his maintenance therapy included mesalamine (1 gram three times a day), and mercaptopurine (75 mg once per day). In addition, he had been started on prednisone approximately 7 weeks prior for treatment of an ulcerative colitis flare. His current dose of prednisone was 10 mg once a day. Soon after symptoms begun, he had been placed on ciprofloxacin as treatment for a presumptive flare. Physical exam showed he was afebrile, with a heart rate of 130 beats per minute, respiratory 16 breaths per minute and blood pressure 115/67 mmHg. He was alert although with a sallow appearance. Abdominal exam revealed a soft nontender nondistended abdomen. Rectal showed normal external exam with grossly bloody stool. Initial blood work showed hemoglobin of 12.3, a normal white blood cell count, normal differential and normal platelet count with a mildly elevated prothrombin time of 16.2 with an international normalized ratio (INR) of 1.2. Urine analysis showed a specific gravity of 1.035, 3+blood, +ketones and > 100 RBC per high powered field and 0–5 WBC per high power field. Abdominal ultrasound revealed irregular shaped bladder wall. Patient was placed on intravenous fluids (IV) as well as metronidazole (IV). Blood and urine cultures were sent for analysis. Stool was sent for culture and for Clostridium difficile toxin analysis. Serial repeat lab works the following day revealed a dropping hemoglobin (7.4 g/dL) and platelet count (64 K/mm 3 ) increasing PT/PTT (21.3/47 seconds) with an INR of 1.8. Blood smear showed moderate amount of elliptocytes, schistocytes, microcytes and fragmented red blood cells. Initial DIC panel revealed an elevated D-dimer of 4.9 mcg/mL with a normal thrombin time and fibrinogen. Thrombin time subsequently increased to > 120 seconds. D-dimers increased to 10.3 mcg/mL. A computerized tomography (CT) scan of the abdomen revealed a marked thickening and irregularity of the bladder wall as well as wall thickening of the rectosigmoid, ascending, transverse, and descending colon (Figure 1 ). Urology was consulted and felt that this represented a submucosal hematoma. Patient was begun on broad-spectrum antibiotics because of concerns regarding possible bacteremia and a worsening DIC laboratory picture. Blood, stool and urine cultures returned negative. Viral cultures and monoclonal antibody staining for adenovirus detection in the urine was negative. Despite a worsening in the DIC panel, the patient remained clinically unchanged. IV steroids were begun approximately 36 hours into patient's hospital stay. Patient had a stabilization of PT/PTT/INR/thrombin time and D-dimer, and a subsequent normalization of labs over the following 4-day period ( Figure 2 , 3 , 4 , 5 , 6 , 7 , 8 ). Patient's diarrhea and hematuria resolved as well. Colonscopy revealed chronic colitis consistent with ulcerative colitis. Cystoscopy revealed a fibrin clot consistent with submucosal hematoma. Patient was discharged from the hospital on a steroid taper, and remains in remission to date. Conclusions Disorders of coagulation have long been associated with inflammatory bowel disease [ 6 - 11 ]. Children, as well as adults, with both active and inactive ulcerative colitis have been found to have abnormal coagulation and fibrinolysis[ 11 ]. It is unclear whether this is a direct or indirect result of inflammatory bowel disease. Although hypocoagulable states have been noted in the literature, most studies indicate an associated hypercoagulable state. There appears to be an increase in thrombin-anti-thrombin complex and a decrease in antithrombin III activity, which causes an increase in thrombin generation[ 10 , 12 , 13 ]. Other studies have demonstrated an increase in fibrinogen content, increase Factor VIII, and Factor IX activity, platelet count and aggregation rate[ 9 , 12 ]. These hypercoagulable abnormalities return towards normal with therapy in direct correlation with sedimentation rate and clinical disease activity [ 12 ], but can still show mild abnormalities despite clinical remission[ 14 ]. The hypercoagulable state in ulcerative colitis is associated thromboembolic events; although uncommon, deep vein thrombosis, pulmonary embolisms and stroke have been associated with ulcerative colitis[ 6 , 15 - 18 ]. Disseminated intravascular coagulopathy is a rare occurrence in inflammatory bowel disease. When it occurs, it is usually associated with other co-founding problems such as septicemia, toxic megacolon or surgery. Presented is a case of DIC associated solely with an ulcerative colitis flare resulting in a bladder hematoma. We presume that the occurrence of DIC in this patient resulted from an acute flare on top of a chronic unremitting course of ulcerative colitis. A thorough infectious work-up of this patient did not reveal any infectious etiology that would have predisposed him to develop DIC. The presumed cause of the DIC was damage to the endothelial wall of the colonic blood vessels, which exposed blood to excessive amounts of tissue factor. This in turn led to the excessive generation of thrombin and a failure of the normal coagulation inhibitory pathways. By treating the ulcerative colitis flare, we decreased the intestinal inflammation and thereby decreased the endothelial cell damage. This, theoretically, resolved the DIC. Patient's clinical symptoms and laboratory values normalized after treatment with intravenous steroids, completely resolving the disseminated intravascular coagulopathy. Competing interests The authors declare that they have no competing interests. Authors' contributions DLS drafted the manuscript. KM and DC participated in the manuscript preparation. All authors approved the final manuscript. Figure 1 Abdominal CT revealing a marked thickening and irregularity of the bladder wall consistent with bladder hematoma. Figure 2 Graphic illustration of C-reactive protein throughout hospitalization: Day 1 (admission date) – Day 9 (day of discharge). Patient received intravenous steroids at approximately 36 hours into hospitalization. Figure 3 Graphic illustration of hemoglobin throughout hospitalization: Day 1 (admission date) – Day 9 (day of discharge). Patient received intravenous steroids at approximately 36 hours into hospitalization. Figure 4 Graphic illustration of platelets throughout hospitalization: Day 1 (admission date) – Day 9 (day of discharge). Patient received intravenous steroids at approximately 36 hours into hospitalization. Figure 5 Graphic illustration of prothrombin time throughout hospitalization: Day 1 (admission date) – Day 9 (day of discharge). Patient received intravenous steroids at approximately 36 hours into hospitalization. Figure 6 Graphic illustration of international normalized ratio throughout hospitalization: Day 1 (admission date) – Day 9 (day of discharge). Patient received intravenous steroids at approximately 36 hours into hospitalization. Figure 7 Graphic illustration of partial thromboplastin time C-reactive protein throughout hospitalization: Day 1 (admission date) – Day 9 (day of discharge). Patient received intravenous steroids at approximately 36 hours into hospitalization. Figure 8 Graphic illustration of D-dimer throughout hospitalization: Day 1 (admission date) – Day 9 (day of discharge). Patient received intravenous steroids at approximately 36 hours into hospitalization. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526371.xml
539292	Passive immunotherapy against Aβ in aged APP-transgenic mice reverses cognitive deficits and depletes parenchymal amyloid deposits in spite of increased vascular amyloid and microhemorrhage	Background Anti-Aβ immunotherapy in transgenic mice reduces both diffuse and compact amyloid deposits, improves memory function and clears early-stage phospho-tau aggregates. As most Alzheimer disease cases occur well past midlife, the current study examined adoptive transfer of anti-Aβ antibodies to 19- and 23-month old APP-transgenic mice. Methods We investigated the effects of weekly anti-Aβ antibody treatment on radial-arm water-maze performance, parenchymal and vascular amyloid loads, and the presence of microhemorrhage in the brain. 19-month-old mice were treated for 1, 2 or 3 months while 23-month-old mice were treated for 5 months. Only the 23-month-old mice were subject to radial-arm water-maze testing. Results After 3 months of weekly injections, this passive immunization protocol completely reversed learning and memory deficits in these mice, a benefit that was undiminished after 5 months of treatment. Dramatic reductions of diffuse Aβ immunostaining and parenchymal Congophilic amyloid deposits were observed after five months, indicating that even well-established amyloid deposits are susceptible to immunotherapy. However, cerebral amyloid angiopathy increased substantially with immunotherapy, and some deposits were associated with microhemorrhage. Reanalysis of results collected from an earlier time-course study demonstrated that these increases in vascular deposits were dependent on the duration of immunotherapy. Conclusions The cognitive benefits of passive immunotherapy persist in spite of the presence of vascular amyloid and small hemorrhages. These data suggest that clinical trials evaluating such treatments will require precautions to minimize potential adverse events associated with microhemorrhage.	Background Alzheimer's disease is characterized not only by the presence of parenchymal amyloid deposits and intracellular tangles but also by the presence of amyloid deposits in the vasculature, a condition referred to as cerebral amyloid angiopathy (CAA). The CAA observed in both Alzheimer's disease patients [ 1 ] and some of the transgenic mouse models [ 2 ] is primarily composed of the shorter form of amyloid beta (Aβ), Aβ 1–40 , while the majority of amyloid deposits in the parenchyma are composed of Aβ 1–42 , although the compact amyloid deposits also contain Aβ 1–40 . Anti-Aβ immunotherapy has been considered as a potential treatment for Alzheimer's disease for some time [ 3 , 4 ]. Active immunization with a vaccine including Aβ 1–42 fibrils progressed to human clinical trials where its administration was suspended due to meningoencephalitits in a subset of patients [ 5 ]. To date there have been pathology reports on two patients who participated in the trial and subsequently died [ 6 , 7 ]. Both reports note that while the numbers of parenchymal amyloid deposits appeared lower than expected in these cases, the CAA in these patients did not appear outside the normal range for Alzheimer's disease. In addition, one report mentioned multiple cortical hemorrhages and the presence of hemosiderin around the CAA vessels [ 7 ]. Given the adverse reactions to the active immunization, the irreversibility of such procedures and the variable antibody response to vaccines in older individuals [ 8 ], passive immunization against the Aβ peptide emerged as an alternative immunotherapeutic strategy. Studies in young and middle aged APP-transgenic mice have reported significant amyloid reductions with passive immunization [ 9 - 11 ]. Such treatments also demonstrate rapid improvements of memory function in APP-transgenic mice, sometimes without detectable reductions in amyloid [ 12 - 14 ]. Most recently, intracranial administration of anti-Aβ antibodies has been shown to not only remove Aβ but also clear, early-stage, hyperphosphorylated-tau aggregates [ 15 ]. Importantly, in the only prior study evaluating adoptive antibody transfer in older APP-transgenic mice, Pfeifer et al . [ 16 ] reported a doubling of cerebral microhemorrhages associated with significant reductions in amyloid burden after administration of an N-terminal specific anti-Aβ antibody. Materials and Methods Experiment design Mice derived from APP Tg2576 mice were obtained from our breeding program at University of South Florida started in 1996 [ 17 ]. For the 5-month treatment study, 13 APP-transgenic mice, aged 23 months, were assigned to one of two groups. The first group received weekly intraperitoneal anti-Aβ antibody injections (antibody 2286; mouse-monoclonal anti-human Aβ 28–40 IgG1; Rinat Neurosciences, Palo Alto, CA) for a period of 5 months ( n = 6). The second group received weekly intraperitoneal anti-AMN antibody (2906; mouse-monoclonal anti- Drosophila amnesiac protein IgG1; Rinat Neurosciences, Palo Alto, CA) injections for a period of 5 months ( n = 7). Seven nontransgenic mice were also assigned to one of two groups. The first group received weekly intraperitoneal anti-Aβ antibody injections for a period of 5 months ( n = 4). The second group received weekly intraperitoneal anti-AMN antibody injections for a period of 5 months ( n = 3). For the time course study of 1-, 2- or 3-month treatment, 22 APP-transgenic mice aged 19 months were assigned to one of four experimental groups, as described previously [ 14 ]. The first three groups received weekly intraperitoneal anti-Aβ antibody injections for 3 months, 2 months or 1 month, ending when all mice were 22 months of age. The fourth group received weekly intraperitoneal anti-AMN antibody injections for 3 months. Behavioral analysis Following 3 and 5 months of treatment, the mice from the 5-month study were subjected to a two-day radial-arm water-maze paradigm. The apparatus was a 6-arm maze as described previously [ 18 ]. On day one, 15 trials were run in three blocks of 5. A cohort of 4 mice were run sequentially for each block (i.e., each of 4 mice get trial one, then the same mice get trial two, etc.). After each 5-trial block, a second cohort of mice was run permitting an extended rest period before mice were exposed to the second block of 5 trials. The goal arm was different for each mouse in a cohort to minimize odor cues. The start arm was varied for each trial, with the goal arm remaining constant for a given individual for both days. For the first 11 trials, the platform was alternately visible then hidden (hidden for the last 4 trials). On day two, the mice were run in exactly the same manner as day one except that the platform was hidden forall trials. The number of errors (incorrect arm entries) was measured in a one-minute time frame. As standard practice, mice failing to make an arm choice in 20 seconds are assigned one error, but no mice in this study had to be assigned an error in this manner. The same individual administered the antibody treatments and placed mice in the radial-arm water maze. Due to the numbers of mice in the study the researcher was unaware of treatment group identity of each mouse. Also, the dependent measures in the radial-arm water-maze task are quantitative, not evaluative, so the potential for tester bias is reduced. In order to minimize the influence of individual trial variability, each mouse's errors for 3 consecutive trials were averaged producing 5 data points for each day, which were analyzed statistically by ANOVA using StatView (SAS Institute Inc., NC). Tissue preparation and histology On the day of sacrifice mice were weighed, overdosed with 100 mg/kg Nembutal (Abbott laboratories, North Chicago, IL), and then intracardially perfused with 25 mL of 0.9% sodium chloride. Brains were rapidly removed, and the left half of the brain was immersion fixed for 24 h in freshly prepared 4% paraformaldehyde in 100 mM KPO 4 (pH 7.2) for histopathology. The hemi-brains were then incubated for 24 h in 10%, 20% and 30% sucrose sequentially for cyroprotection. Horizontal sections of 25 μ thickness were collected using a sliding microtome and stored at 4°C in Dulbecco's phosphate-buffered saline with sodium azide (pH 7.2) to prevent microbial growth. A series of 8 equally spaced tissue sections 600 μ apart were randomly selected spanning the entire brain and stained using free-floating immunohistochemistry for total Aβ (rabbit polyclonal anti-pan Aβ; Biosource, Camarillo, CA, 1:10,000) as previously described [ 2 , 14 ]. A second series of tissue sections 600 μm apart were stained using 0.2% Congo red in NaCl-saturated 80% ethanol. Another set of sections were also mounted and stained for hemosiderin using 2% potassium ferrocyanide in 2% hydrochloric acid for 15 min, followed by a counterstain in a 1% neutral red solution for 10 min. Quantification of Congo red staining and Aβ immunohistochemistry was performed using the Image-Pro Plus (Media Cybernetics, Silver Spring, MD) to analyze the percent area occupied by positive stain. One region of the frontal cortex and three regions of the hippocampus were analyzed (to ensure that there was no regional bias in the hippocampal values). The initial analysis of Congo red was performed to give a total value. A second analysis was performed after manually editing out all of the parenchymal amyloid deposits to yield a percent area restricted to vascular Congo red staining. To estimate the parenchymal area of Congo red, we subtracted the vascular amyloid values from the total percentage. For the hemosiderin stain the numbers of Prussian blue-positive sites were counted on all sections and the average number of sites per section calculated. Looking at the sections at a low magnification we were able to observe a qualitative differences between animals; however, the percent area was so low that many fields contained no positive stain. Eight equally spaced sections were examined and the number of positive profiles was determined and averaged to a per-section value. To assess possible treatment-related differences, the values for each treatment group were analyzed by one-way ANOVA followed by Fisher's LSD means comparisons. Results Reversal of cognitive deficits by passive amyloid immunotherapy The radial-arm water-maze task detects spatial learning and memory deficits in transgenic mouse models [ 18 , 19 ]. We treated 23-month-old mice for 5 months with anti-Aβ antibody 2286 or control antibody 2906 (against a Drosophila -specific protein) and tested them for spatial navigation learning in a two-day version of the radial-arm water maze after 3 months of treatment and, using a new platform location, again after 5 months of treatment. At both testing times we found that APP-transgenic mice treated with the control antibody failed to learn platform location over two days of testing and were significantly impaired compared to the nontransgenic mice treated with either antibody (Fig. 1 ). However, APP-transgenic mice administered the anti-Aβ antibodies demonstrated a complete reversal of the impairment observed in the control-treated APP-transgenic mice, ending day two with a mean performance near 0.5 errors per trial (Fig. 1 ). Although learning at the later time point, when the mice were 28 months of age, may have been slightly slower for all groups, there was no impairment of the anti-Aβ antibody-treated APP. Figure 1 Spatial learning deficits in APP-transgenic mice were reversed following 3 and 5 months of immunization. Mice were tested in a two-day version of the radial-arm water maze. Solid lines represent APP-transgenic mice while dashed lines represent nontransgenic mice. Open symbols indicate anti-AMN, control-antibody treatment (○: APP-transgenic, control antibody; △: nontransgenic, control antibody) while closed symbols indicate anti-Aβ antibody treatment (●: APP-transgenic, Aβ antibody; ▲: nontransgenic, Aβ antibody). Panel A shows mean number of errors made over the two-day trial period following 3 months of immunization. Each data point is the average of 3 trials. Panel B shows the mean number of errors made over the 2-day trial period following 5 months of immunization. For both graphs * indicates p < 0.05, indicates p < 0.001 when the APP-transgenic mice receiving control antibody are compared with the remaining groups. Passive amyloid immunotherapy clears parenchymal Aβ deposits, but increases vascular amyloid In a prior experiment examining the effects of passive anti-Aβ immunotherapy for 1, 2 or 3 months in APP-transgenic mice killed at 21 months of age [ 14 ], we found a time-dependent reduction of both Aβ immunostaining of diffuse and fibrillar deposits and Congo-red staining of fibrillar amyloid deposits. In the current study we found a similar reduction in both Aβ immunostaining (Table 1 ) and total Congo-red staining (Fig. 2A , left panel; p < 0.001 frontal cortex and p < 0.01 hippocampus) after 5 months of immunotherapy. We noted that the bulk of what remained was vascular amyloid. We then separately analyzed vascular and parenchymal deposits which revealed a near 90% reduction in parenchymal deposits ( p < 0.001) but a 3–4 fold elevation of vascular Congo-red staining ( p < 0.0001; Fig. 2A , center and right panels, respectively). We also separately analyzed vascular and parenchymal Congo-red staining on mice from our earlier study [ 14 ], treated passively for 1, 2 or 3 months with anti-Aβ or control antibody, and found a similar result. There was a graded reduction in overall Congo-red staining nearing 75% as duration of antibody exposure increased (as reported previously; Fig. 2B ). However, when separated into vascular Congo-red deposits and parenchymal deposits, there was an antibody-exposure-time-dependent increase in vascular deposition in both hippocampus and frontal cortex (Fig. 2C ; p < 0.05 frontal cortex and hippocampus) and a corresponding nearly 90% decrease in parenchymal deposits (Fig. 2D ; p < 0.001 in frontal cortex and hippocampus). Table 1 Total Aβ load is significantly reduced following 5 months of anti-Aβ antibody treatment. Percent area occupied by positive immunohistochemical stain for Aβ is shown ± standard error of the mean for both the frontal cortex and hippocampus. Also shown is the percent reduction of Aβ observed following anti-Aβ antibody treatment Region % area positive for Aβ: control treated % area positive for Aβ: anti-Aβ treated % reduction following anti-Aβ antibody treatment Frontal Cortex 34.855 ± 2.265 9.681 ± 0.754 72 Hippocampus 23.994 ± 0.985 8.212 ± 0.596 66 Figure 2 Passive immunization with anti-Aβ antibodies decreases total and parenchymal amyloid loads while increasing vascular amyloid in frontal cortex and hippocampus of APP-transgenic mice. Panel A shows total amyloid load measured with Congo red, vascular amyloid load and parenchymal amyloid load from APP-transgenic mice administered control IgG (C) or anti-Aβ IgG (Aβ) for a period of 5 months. Panels B-D show total amyloid load (Panel B), vascular amyloid load (Panel C) and parenchymal amyloid load (Panel D) from APP-transgenic mice administered control IgG for 3 months (Cont IgG) or anti-Aβ IgG for a period of 1, 2, or 3 months (Anti-Aβ IgG). For all panels, the solid bar and solid line represent values from the frontal cortex, while the open bar and dashed line represent values from the hippocampus. p < 0.01. These differences were readily observed examining micrographs of sections from these mice. Mice treated with control antibodies revealed occasional cortical vascular amyloid deposits (22 months, Fig. 3A , 28 months, Fig. 3C ), while mice administered anti-Aβ antibodies had increased amounts of vascular amyloid staining (3-month treatment, Fig 3B ; 5-month treatment, Fig 3D ). Those vessels containing amyloid following treatment with anti-Aβ antibody also exhibited apparent increases in microglial activation as measured by CD45 expression (Fig. 3F ) compared to mice treated with control antibody (Fig. 3E ). Unfortunately, the shifting numbers and sizes of vascular and parenchymal deposits caused by the antibody therapy greatly complicated measurement of microglial activation per vascular deposit area so that this apparent increase in staining intensity could not be quantified accurately. Figure 3 Increased Congo red staining of blood vessels following anti-Aβ antibody administration is associated with activated microglia. Panels A and B are from the frontal cortex of 22-month-old APP-transgenic mice immunized for 3 months with either control antibody (3A) or anti-Aβ antibody (3B). Panels C and D are from the frontal cortex of 28-month-old APP-transgenic mice immunized for 5 months with either control antibody (3C) or anti-Aβ antibody (3D). Panels E and F show a high-magnification image of CD45 immunohistochemistry (black) counterstained with Congo red (red) from 28-month-old APP-transgenic mice immunized for 5 months with either control antibody (Panel E) or anti-Aβ antibody (Panel F). Panels A-D, magnification = 100X. Scale bar in Panel B = 50 μ for panels A-D. Panels E-F, magnification = 200X. Scale bar in Panel E = 25 μm for panels E-F. Passive amyloid immunotherapy causes increased microhemorrhage We used the Prussian blue histological stain to label hemosiderin, a ferric oxide material produced in the breakdown of hemoglobin. Extravenous blood in the brain leads to microglial phagocytosis of the erythrocytes and breakdown of the hemoglobin within them. These ferric oxide-containing microglia are thus markers of past hemorrhage. In untreated, aged APP-transgenic mice we observed very few profiles positive for Prussian-blue staining in the frontal cortex (section counterstained with neutral red; Fig. 4A ). However, following anti-Aβ antibody treatment for 5 months we observed an increase in the number of Prussian-blue profiles in the frontal cortex, which were readily detectable at a low magnification in the microscope (Fig. 4B ). In the absence of anti-Aβ treatment, or even when treated with antibody for one month, most vessels did not stain with Prussian blue, and could be identified only using the red counterstain (Fig. 4C ). However, even with 3 months of anti-Aβ antibody treatment we observed frequent vessels with associated Prussian-blue staining (Fig 4D ). Using adjacent sections stained for Congo red, we confirmed that all vessels showing microhemorrhage contained amyloid (Figs. 4E and 4F ; we were unable to double-label Prussian blue-stained sections with either Congo red or thioflavine-S). However, only a minority of vessels containing amyloid demonstrated hemorrhage. Figure 4 Microhemorrhage associated with CAA following systemic administration of anti-Aβ antibodies. Panels A and B are low magnification images of the frontal cortex of APP-transgenic mice receiving either control antibodies (Panel A) or anti-Aβ antibodies (Panel B) for a period of 5 months. Panels C and D show representative images of amyloid containing vessels stained for Prussian blue (blue), counterstained with neutral red (red), from APP-transgenic mice receiving either control antibodies (Panel C) or anti-Aβ antibodies (Panel D) for a period of 3 months. Panel E shows a blood vessel in the frontal cortex stained for Prussian blue (blue), counterstained with neutral red, from an APP transgenic mouse administered anti-Aβ antibodies for 5 months. Panel F shows the same blood vessel on an adjacent section stained for Congo red, indicating that the blood vessel does in fact contain amyloid. Scale bar panel A = 120 μm for panels A-B. Scale bar panel C = 25 μm for panels C-D. Scale bar in panel F = 25 μm for panels E-F. When we counted the number of Prussian blue-positive profiles in those animals receiving control antibody there was an average of one profile per every two sections (Fig. 5 ) and this number remained the same in both control groups (aged 22 or 28 months). Following treatment with anti-Aβ antibody for a period of two months we observed a striking increase in Prussian-blue staining, approximately five times that observed in either the control group or the mice immunized for one month (Fig. 5 , p < 0.001). Following this initial increase in Prussian-blue staining, we observed a linear increase in staining associated with increasing duration of anti-Aβ antibody treatment (Fig 5 ). Five months of anti-Aβ antibody treatment demonstrated a six-fold increase in Prussian-blue staining when compared the control groups (Fig. 5 ). Figure 5 Number of Prussian blue-positive profiles increases with duration of anti-Aβ antibody exposure. The graph shows quantification of the average number of Prussian blue-positive profiles per section from mice administered control IgG for 3 or 5 months (Cont) or anti-Aβ IgG for 1, 2, 3 or 5 months (anti-Aβ). ** p < 0.01. Discussion Earlier studies with vaccines against the Aβ peptide demonstrated protection from the learning and memory deficits associated with amyloid accumulation in APP-transgenic mice [ 14 , 19 ]. Passive immunization protocols with anti-Aβ antibodies also produced cognitive benefits, in some cases even in the absence of significant reduction in amyloid burden [ 12 , 13 ]. Our recent work found that 3 months of anti-Aβ treatment of 18-month-old APP-transgenic mice improved spontaneous alternation performance on the Y-maze [ 14 ]. In the present work we confirmed that passive anti-amyloid immunotherapy can reverse spatial learning deficits in APP-transgenic mice and that this benefit of immunotherapy is retained, even in aged mice (26 and 28 months old at testing) with long-established amyloid pathology. Additionally, we describe a more rapid means of testing spatial reference memory to reveal learning and memory deficits in APP-transgenic mice. This two-day version of the radial arm water maze included greater spacing of individual trials (mice spent time in their home cage after every trial), combined with less spacing of aggregate trials (fifteen trials per day rather than four or five) to facilitate learning of platform location in the nontransgenic mice, with a clear absence of learning in the age-matched transgenic mice. A substantial reduction in total Congophilic amyloid deposits was observed in old APP-transgenic mice treated with anti-Aβ antibodies for 2 or more months. This measurement of total Congo-red staining included both parenchymal and vascular amyloid staining. When we analyzed the sections for only vascular amyloid (CAA) we found that this measure was significantly increased following 2, 3 and 5 months of anti-Aβ antibody treatment. The remaining parenchymal amyloid load was almost completely eliminated with this antibody approach. Clearly, because total amyloid load was significantly reduced not all amyloid was shifted into the vessels; but, it appears that at least some of the Congophilic material was redistributed to the vasculature. At the present time the mechanism for this redistribution is unclear. However, one possibility is that the microglia associated with the antibody-opsonized amyloid, either by phagocytosis or surface binding, and transported the material to the vasculature, possibly in an attempt to expel it. We and others have shown evidence for microglial involvement in the removal of amyloid using both intracranial anti-Aβ antibody injections [ 11 , 21 ] and systemically administered anti-Aβ antibody treatment [ 14 ], as well as ex vivo studies [ 10 , 22 ]. Here we also report our impression that microglia surrounding CAA vessels in immunized mice expressed more CD45 than control transgenic mice. This increased expression could be due to either increased expression in the same number of microglial cells or an increased number of microglial cells in these animals. It is feasible that this microglial activation was simply in reaction to the presence of increased amyloid in the blood vessels. However, it is equally likely that microglia activated by the opsonized material migrated to the vessels for disposal of the amyloid. Cerebral amyloid angiopathy (CAA) is defined as the deposition of congophilic material in meningeal and cerebral arteries and arterioles (capillaries and veins can also show CAA but less frequently), and it occurs to some extent in nearly all Alzheimer's disease patients [ 23 ]. Severe CAA, affecting about 15% of cases, can be associated with both infarction and hemorrhagic injury [ 24 , 25 ]. It has also been shown that the severity of CAA can be directly linked to the severity of dementia in Alzheimer's disease patients [ 26 ]. In the current study we found a significantly increased number of microhemorrhages in the brain as detected by Prussian-blue staining, associated with the increase in CAA following passive immunization. Another transgenic mouse model of amyloid deposition, the APP23 mice, have been shown to deposit amyloid in both brain parenchyma and blood vessels and show a CAA associated increase in spontaneous cerebral hemorrhages [ 27 ]. Moreover, Pfeifer et al . [ 16 ] showed that these spontaneous hemorrhages were significantly increased following 5 months of passive immunization of 21-month-old APP23 mice using an anti-Aβ antibody with an N-terminal epitope, similar to those typically developed in active immunization with vaccines [ 4 , 28 , 29 ]. When young mice (6 months of age) were immunized following the same protocol, no hemorrhages were observed. More recently, DeMattos et al . [ 30 ] showed that passive immunization with an N-terminal antibody (3D6: directed against amino acids 1–5 of Aβ) of PDAPP transgenic mice also resulted in significantly increased microhemorrhage. They were unable to detect increased microhemorrhage with a mid-domain antibody (266: directed against amino acids 13–28 of Aβ). Notably, antibody 266 fails to bind Aβ deposited in CAA vessels or amyloid plaques [ 31 ]. Importantly, Ferrer et al . [ 7 ] noted the presence of CAA and microhemorrhage in the brain of one patient that participated in the Aβ-vaccine trial, even though the parenchymal amyloid appeared lower than expected. Also, Nicoll et al . [ 6 ] noted that CAA appeared unaffected in the brain of another patient that participated in the Aβ-vaccine trial. It remains to be determined whether these observations regarding increased CAA and microhemorrhage in transgenic mice are relevant to trials of passive immunotherapy in humans. It should be noted that, in spite of extending the period of immunotherapy to 5 months, there was no discernable loss of the cognitive benefits of immunotherapy in the transgenic mice, all of whom showed increased microhemorrhage. While the observation that antibody 266 does not result in vascular leakage encourages testing of this idiotype, data from the Zurich cohort of the Aβ vaccine trial argue that brain-reactive antibodies may be important for cognitive benefits [ 32 ]. Conclusions Our opinion is that these results suggest that passive immunotherapy against Aβ should proceed with appropriate precautions taken to minimize the risk of hemorrhage (e.g., by excluding patients taking anticoagulants) and instituting measures to detect such hemorrhages if they do occur, irrespective of the antibody specificity or proclivity for microhemorrhage in aged APP-transgenic mice. List of abbreviations Aβ : Amyloid-beta. APP: Amyloid precursor protein CAA: Cerebral amyloid angiopathy. IgG1: Immunoglobulin G type 1. Competing interests The authors declare that they have no competing interests. Authors' contributions DMW treated the mice, performed the behavioral analysis, processed the tissue and performed pathological analyses, and drafted the manuscript. ARojiani evaluated slides and provided expert opinion regarding CAA and microhemorrhage. ARosenthal and SS developed, produced and purified the antibodies used in the studies. MJF performed DNA extraction and PCR for genotyping of the mice. MNG oversees the breeding colony generating mice for the studies, collected samples from the mice and assisted in editing the manuscript. DM conceived the design of the study, guided data interpretation and assisted in editing the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539292.xml
554095	The role of NGOs in global health research for development	Background Global health research is essential for development. A major issue is the inequitable distribution of research efforts and funds directed towards populations suffering the world's greatest health problems. This imbalance is fostering major attempts at redirecting research to the health problems of low and middle income countries. Following the creation of the Coalition for Global Health Research – Canada (CGHRC) in 2001, the Canadian Society for International Health (CSIH) decided to review the role of non-governmental organizations (NGOs) in global health research. This paper highlights some of the prevalent thinking and is intended to encourage new thinking on how NGOs can further this role. Approach This paper was prepared by members of the Research Committee of the CSIH, with input from other members of the Society. Persons working in various international NGOs participated in individual interviews or group discussions on their involvement in different types of research activities. Case studies illustrate the roles of NGOs in global health research, their perceived strengths and weaknesses, and the constraints and opportunities to build capacity and develop partnerships for research. Highlights NGOs are contributing at all stages of the research cycle, fostering the relevance and effectiveness of the research, priority setting, and knowledge translation to action. They have a key role in stewardship (promoting and advocating for relevant global health research), resource mobilization for research, the generation, utilization and management of knowledge, and capacity development. Yet, typically, the involvement of NGOs in research is downstream from knowledge production and it usually takes the form of a partnership with universities or dedicated research agencies. Conclusion There is a need to more effectively include NGOs in all aspects of health research in order to maximize the potential benefits of research. NGOs, moreover, can and should play an instrumental role in coalitions for global health research, such as the CGHRC. With a renewed sense of purpose and a common goal, NGOs and their partners intend to make strong and lasting inroads into reducing the disease burden of the world's most affected populations through effective research action.	" Each country needs to be able to generate knowledge relevant to its own situation, to allow it to determine its particular health problems, appraise the measures available for dealing with them, and choose the actions likely to produce the greatest improvement in health. This should not be seen as the exclusive preserve of universities or research councils, but equally of health/public services, non-governmental organizations, etc." [ 1 ]. 1 Introduction Non-governmental organizations (NGOs) have been defined by the World Bank as 'private organizations that pursue activities to relieve suffering, promote the interests of the poor, protect the environment, provide basic social services, or undertake community development'. NGO activities can be local, national or international. NGOs have contributed to the development of communities around the world and are important partners of many governments – while remaining independent from governments. According to the Human Development Report [ 2 ], there were in 2002 over 37,000 NGOs in the world, a growth of 19.3% from 1990. Their purposes differ but overall two categories dominate: economic development and infrastructure (26%) and research (23%) . NGOs are generally regarded as valued partners in health research for development, research being viewed as a broad process involving not only the production of knowledge, but also up-stream and down-stream activities needed for its relevance and effectiveness, such as priority setting and knowledge translation. NGOs have made and continue to make substantive contributions through supporting relevant and effective research. In her address at the First Steering Committee Meeting of the International Conference on Health Research for Development in 1999, the (then) Director General of the World Health Organization (WHO), Dr. Gro Harlem Brundtland, voiced her appreciation of NGOs as a partner with WHO in health research [ 3 ]. There are several views on what is meant by global health and global health research. In its simplest form, global health is population health on a global scale, and global health research is research which addresses the health of human populations around the globe. Global health also refers to 'inherently global health issues', that is, health-determining phenomena that transcend national borders and political jurisdictions, such as globalization and climate change. In setting global health research priorities, both the burden of disease and inherently global issues should be considered [ 4 , 5 ]. The vision of health research as proposed by the Commission on Health Research for Development [ 6 ] is a systems approach driven by equity, focused on country needs and priorities, and within an interactive regional and global framework. This paper will address global health as it was defined in a Canadian consultation paper on global health research held in 2001 , that is, the health of individuals and societies in less developed, less resourced, poorer nations and regions of the world. A major global health research issue is the inequitable distribution of research efforts and funds directed towards populations suffering the world's greatest health problems. This situation has been referred to as the 10/90 gap because only a meager 10% of all health research funding is being used to address 90% of the world's burden of disease, suffered primarily in developing countries [ 7 ]. Because of this imbalance, there have been major attempts at redirecting research efforts and funds to the health problems of low and middle income countries. One of the roles of health research is to ensure that the measures proposed to break out of the vicious cycle of ill health and poverty are based, as far as possible, on evidence, so that the resources available to finance these measures are used in the most efficient and effective way possible [ 8 ]. There are many different types of health research. At the 6 th Global Forum on Health Research, held in Arusha, Tanzania in November 2002, Dr. Gerald Keusch, Director of the Fogarty International Center, listed the scope of health research as including: fundamental discovery research, pathogenesis research, epidemiology research, clinical research, product development research, translational and adaptational research, operational research, health services research, policy research and research on health systems [ 9 ]. NGOs involved in health research have primarily undertaken operational and action research, but many have also participated in other types of research such as epidemiological research, social science research, product development research, translational research, health services research, and policy research. The purpose of this paper is to document the role that NGOs have played in global health research and to highlight the need to expand this role. This paper is also intended as a tool to stimulate research activity in NGOs and to advocate for increased NGO involvement in global health research. Following a brief review on the central role of global health research in development, the roles of NGOs at different stages within the research process are discussed and illustrated with a few examples. Key challenges are also identified. The last part of the paper identifies future needs for strengthening the role of NGOs in global health research. 2 Global Health Research and Development While research means different things to different people, it may best be defined as 'a knowledge loop' from generation of knowledge to its effective use [ 10 ]. Indeed, there has been a progressive paradigm shift from narrow 'research' to broader 'knowledge creation and management' [ 11 ]. This broad definition is consistent with that of the Organization for Economic Co-operation and Development (OECD) [ 12 ] which states that "research and experimental development comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new application". Research is recognized as a fundamental ingredient for action [ 13 , 14 ], and it is essential for development because it informs policies and programs; it also guides the development of human resources in these and related domains (see Figure 1 ). However, the links among research, policy-making, programming and training, with advocacy constantly in the background, need to be strengthened. It is being increasingly recognized that investments in health research can be economic and social investments [ 15 ]. In a WHO discussion paper on knowledge for better health, the emphasis is on research as an investment rather than a cost, on the need to turn research into action, and on the vital part of the civil society ( World report on knowledge for better health 2004). Figure 1 The relationship between research and development 2.1 Global health research priorities The call to shift health research priorities from problems of industrialized countries to those affecting populations in developing countries is not new. In 1990, concerns regarding the inequitable distribution of research efforts were first raised in the Report to the Commission on Health Research for Development [ 6 ]. Since then, progress has been made to try to correct this gap, and to build capacity in the countries of greatest need. The 2002 WHO World Health Report [ 16 ] focuses on risks that contribute to the global burden of disease and death, both in developing and developed countries. Dollar expenditures on health research today, however, remain markedly inequitable in terms of populations served and disease burden addressed. Pneumonia, diarrheal diseases, tuberculosis and malaria, when combined, have been estimated to account for more than 20% of the disease burden in the world (mostly in developing countries), yet they receive less than 1% of the total public and private funds which are devoted to health research. The 10/90 gap is as wide as ever [ 7 ]. 2.2 Milestones in global health research and development Several important initiatives have been undertaken to address the global health research agenda. They have been fostered by individuals and groups from local, national and international bodies who shared a common vision in advocating for health research directed towards the low and middle income countries. 2.2.1 Commission on Health Research for Development The Commission on Health Research for Development declared in 1990 that "For the most vulnerable people, the benefits of research offer a potential for change that has gone largely untapped" [ 6 ]. The Commission highlighted several obstacles in undertaking this research, and among others: 1) the insufficient (worldwide) funding of health research directed towards health problems of people in developing countries; 2) the inefficient application of resources; 3) the neglect of major health problems; 4) the lack of individual and institutional health research capacity; 5) the lack of technology transfer; and 6) fragmentation and competition among research initiatives. The challenge to remedy this situation was set down and ultimately led to the establishment of the Council for Health Research in Development (COHRED) in 1993. COHRED works in partnership with WHO, the World Bank and other organizations to strengthen the role of health research at the country level. Over the years, COHRED has assisted increasing numbers of countries in the exploration and implementation of essential national health research (ENHR) strategies. Networks were created to facilitate national level activities in Africa, Asia, and the Commonwealth Caribbean. For example, AFRO-NETS, the 'African Networks for Health Research and Development', was established in 1997 to facilitate exchange of information among different networks active in this type of research in English-speaking Africa, and to facilitate collaboration in the fields of capacity building, planning and research. Regional and global working groups and projects were established which allowed experiences with ENHR to be shared. Several communication strategies were utilized, including quarterly newsletters, websites and other publications to share experiences and lessons learned. A framework for capacity development, a critical component of ENHR, was established through partnerships and like-minded networks and organizations. The book, ' Forging Links for Health: Perspectives from the Council on Health Research for Development ", [ 14 ] and the discussion paper ' Health Research for Development: The Continuing Challenge [ 1 ] review what has happened in the intervening years since the Commission on Health Research for Development made its first major recommendations in 1990. Several questions remain unanswered: • To what extent have the recommendations been implemented? • Have the recommendations made a real difference in the lives of the countries that carry 90% of the disease burden? • Has 'Essential National Health Research' worked? • What is the current situation with regard to health research for development? • Where and how do we proceed from here? The 2000 International Conference on Health Research for Development provided COHRED and several partner organizations with an opportunity to review and reflect on their experience with health research, its impact on health and equity and to devise a global strategy for the first years of the coming millennium [ 14 ]. 2.2.2 Global Forum for Health Research The Global Forum for Health Research, created in 1998 as a response to the Report of the WHO ad hoc Committee on Health Research Relating to Future Intervention Options [ 17 ], has provided a forum for stakeholders to review global health research priorities, promote ongoing analysis of the international health research situation and facilitate coalition building to support its central objective to help correct the 10/90 gap. The Global Forum is managed by a council of 20 members representing government policymakers, multilateral and bilateral agencies, foundations, international NGOs, women's associations, research institutions, and the private sector. It holds funding competitions on targeted global health topics and awards research grants to applicants from low and middle income countries. Its most recent report [ 18 ] emphasized the need for action by combined efforts of the public and private sectors. It also recognized the role of NGOs as a partner in contributing to these efforts. 2.2.3 Canadian Coalition for Global Health Research In November 2001, four Canadian federal agencies, Canadian International Development Agency (CIDA), International Development Research Centre (IDRC), Health Canada, and Canadian Institutes of Health Research (CIHR) signed a Memorandum of Understanding to support national consultation regarding Canada's role in global health research. This marked the first time in Canadian history that Canada's two overseas development agencies, Health Canada and Canada's major federal health research funding agency have collaborated to address global health research. The Canadian Coalition for Global Health Research (CCGHR) is developing into a network of health researchers, funding agencies, NGOs, and other stakeholders committed to support the pursuit of effective global health research by ensuring that all these groups work together as effectively as possible with researchers in developing countries. This collaborative approach serves as a framework for future research projects in the area of global health, with each organization bringing its own specific area of expertise to the table. It aims to improve the effectiveness of development assistance and to increase the sustainable health gains per dollar of Canadian funds invested in research. 3 Key Roles of NGOs in Global Health Research Inequities in health are caused by a number of determinants, including the use of or access to health care facilities. Research which addresses these issues requires an intersectoral approach, involving trans-disciplinary teams and methodologies. Building trans-disciplinary teams requires commitment from the research community to seek out colleagues from other disciplines, from the funding agencies to appreciate innovative initiatives, from the community at large as partners and contributors, and from the policy arena to develop strategies for intersectoral policies and programs which may well have the lead outside ministries of health. Indeed, working outside government altogether may well be a solid and sustainable strategy. Understanding and engaging the broader community on these issues comes naturally to communities unrestricted by bureaucratic boundaries. This is where NGOs excel. NGOs have contributed to all different stages of the research cycle (see Figure 2 ), namely in advocacy, priority setting, capacity building, resource mobilization, sharing and utilization of research findings, and networking. Traditionally, many NGOs which have undertaken activities that address health issues in resource-poor settings are service-oriented NGOs and concentrate their efforts on implementing "action" programs. This type of NGO finds it difficult to identify resources that would allow them to conduct research. While there are NGOs involved in actually conducting research, for most the focus is usually evaluation. Links with the research community are often weak. Other NGOs undertake innovative field-based experimental research. The effectiveness of these initiatives is often learned by trial and error. Unfortunately, while this enhances effective and efficient implementation in the field, research results are only infrequently analyzed appropriately. There are also barriers to dissemination or sharing of research results to a wider audience (eg. other districts within the same country) and to different audiences (eg. to other researchers, research institutions, etc.). Typically, NGO involvement in research is more downstream of knowledge production and it usually takes the form of a partnership with more traditionally-oriented research organizations such as universities or dedicated research agencies. There is a need to include NGOs in the reconceptualization of global health research to ensure completion of the cycle from generation of knowledge to its effective use. Figure 2 Research Process We describe the key roles of NGOs below, using, as a framework, the categories of primary functions of health research systems as recently identified by Butler [ 1 ]. 3.1 Stewardship One of the strengths of NGOs has been as advocates for the populations they serve. Health research can make NGOs become more effective advocates. Governments depend on health research for needs assessments, formulation of policy options, implementation of interventions and evaluation of action plans. Empowered citizens and NGOs can demand accountability of the government. They can also encourage international donors to focus on the health priorities of countries and thus facilitate a check and balance mechanism for good governance. Good governance is needed to improve collaboration and cooperation at the international, national and regional levels in order to tackle inequity. High scientific standards are fundamental components of effective health governance, particularly as they relate to health research systems. The role of research in mobilizing and supporting NGOs, particularly around issues of inequities, is important. NGOs can provide stewardship in terms of the promotion and advocacy for relevant research, shaping research priorities, and the setting and interpretation of ethical frameworks for research. NGOs can often play a more powerful role using the results of research than can the research community itself. Mobilizing communities, utilizing mechanisms for advocacy and acting as an interface between the research community and its wider community will enhance a sense of strong governance and stewardship. 3.1.1 Promotion and advocacy for relevant global health research There is widespread agreement that health research is not sufficiently valued by many societies as a critical input to human and socioeconomic development. The result is often an environment that is neither conducive to, nor supportive of, research. A culture is necessary that recognizes the value of research and one which builds a supportive environment for research [ 19 ]. There is a need not just to allocate funds for research, but also to allocate these funds to areas of research that would have the greatest or maximum social benefit. Advocacy for relevant research, that is, the type of research that will make a difference in terms of equity, health, well-being and development of people, is an important role for NGOs [ 20 ]. Not only can NGOs identify researchable topics, but they can also stimulate demand for relevant research. However, the existing power structure in the research arena often works against NGOs because of a narrow view of research as merely producing new knowledge, with limited consideration of upstream operations (identification of research needs, questions, and priorities), downstream actions (knowledge management, dissemination and translation), and the advocacy efforts required to connect research with policies, programs and training. Historically, the influence of the biomedical researchers' lobby has been the strongest with regard to agenda-setting and fundraising. Behavioral scientists and social health researchers generally have much weaker potential to influence resource allocation, agenda-setting and policy formulation. Partnerships could be strengthened and supported between NGOs and social science researchers in resource-poor countries to improve influence potential, as the social sector issues that tend to be most relevant to human populations are also of utmost importance to NGOs. Creating a favorable environment for "relevant" research requires a health system that is supportive and provides financing opportunities. It also requires the existence of a culture of "evidence-generating and evidence-based research". There must be a healthy relationship between communities, researchers and policy makers. Networks to share experiences, lessons learned and policy impact can be enhanced by partnerships with NGOs. A disproportionately large number of people living in developing countries suffer large disease burdens. Promoting research and development on neglected diseases or issues of global health significance may contribute to bridging the 90/10 research gap, by stimulating research by public or civil society organizations on issues that do not represent marketable research, and are therefore neglected by the private sector. There is a role for NGOs in advocating for more research on these neglected topics (see under 4.1, example of initiative for neglected disease drugs, Médecins sans Frontières [MSF]). Health research needs to generate knowledge that will facilitate the identification of choices and options to reinforce equity-based policies and programs. In doing so, it also needs to address the difficulties of collecting data that are of primary importance when inequities are discussed. The essential function that data serve will allow tracking and monitoring of resources for research and for improving opportunities for those researchers in more disadvantaged countries. NGOs often have access to information that will highlight inequities and the determinants of inequities. Similarly, NGOs can advocate for formative and evaluative research on programs that address major health problems, but which are generally a low priority for funding agencies. In doing so, they can contribute to making data available for evidence-based decision-making in policy and program planning. Food system-based approaches to reducing micronutrient deficiencies and malnutrition in general are one of these under-researched areas. 3.1.2 Shaping research priorities NGOs are well-placed to foster public participation in decisions about health research, as they are close to communities. They can provide the mechanisms by which such public participation is ensured in decision-making processes. Significant progress has been made over the last decade in health research priority-setting for the implementation of ENHR at the country level. Among the lessons learned, it appears that community involvement is in most cases an unresolved issue [ 21 ]. What is certain is that, critically at the priority-setting stage of the research cycle, the community must be involved, and NGOs may be instrumental in achieving this. Defining the research that needs to be done requires the input of civil society and NGOs as much at the beginning as at the end, in terms of dissemination, communication and action. 3.1.3 Setting and interpreting ethical frameworks NGOs assume a range of roles in research, but a thread that runs through all these is their representation and advocacy for the vulnerable. Broad research roles are described in greater detail in other sections of this paper. This section focuses on the role of NGOs in shaping and interpreting ethical frameworks [ 22 - 25 ], that is, the incorporation of ethical principles in their research partnerships with other organizations. As researchers or research partners, NGOs have a responsibility to ensure that ethical issues are addressed in both the design and conduct of the research. There are distinctive challenges in conducting health research in developing countries, namely to fulfill moral duties of justice and respect in the face of poverty, lack of resources and the potential for exploitation. The Nuffield Council on Bioethics [ 26 ] designed an ethical framework for health research in developing countries based on the duty to alleviate suffering, to show respect for persons, to be sensitive to cultural differences, and to not exploit the vulnerable. As NGO research is often conducted among the most vulnerable populations, where power relations are tipped in favor of researchers and those who are literate and eloquent, issues of informed consent and participants' understanding of it and the research, as well as participants having access to the benefits of research, are of special concern. Particularly when research is conducted by first world researchers in resource-limited settings, NGOs who partner in this research at times need to recommend and advocate for reviews from local research and ethics committees, as well as those from industrialized countries. Where relevant, they may also encourage the development of independent national ethics committees and national ethical guidelines, taking account of existing international guidelines [ 22 - 25 ]. This process may involve interpreting cultural ethical frameworks and beliefs, for instance, culturally appropriate means of obtaining informed consent from research participants. In addition, NGOs can make sure that the development of local expertise in health research is an integral component of research proposals. As watchdogs, NGOs actively seek breaches of ethics and hold researchers to account when the principles of respect for persons, beneficence and justice are not upheld, a role they are well positioned to assume given their understanding of and links to marginalized groups. Watchdogs, as they uncover ethical breaches that may be defined by culture or power relations, have assisted in shaping ethical frameworks to better address ethics when research is conducted among vulnerable groups. In the communities where NGOs work, they can act as community partner members of and witnesses to research. In this role they can assist with, for example, interpreting research objectives to participants to ensure that consent is informed and the rights of subjects are respected. They may provide researchers with enumerators or local information to expedite the data collection process. NGOs can also monitor the long-term outcomes arising from research, and make sure that the participants benefit from successful intervention. As knowledge translators, NGOs interpret the knowledge generated by research to their constituents, a key role in working towards the vulnerable having access to the benefits of research that could improve their lives. This may be research conducted in these communities or globally. 3.2 Mobilizing resources for research While current levels of financial resources are not sufficient to adequately respond to the demonstrated need for health research, there are many sources of "funds" for health research. Some are monetary contributions and some are in-kind contributions. NGOs can provide not only direct funding for projects (albeit in a limited manner) but, and perhaps equally important, they can provide valuable in-kind funding. Thus, personnel or materials developed by NGOs can be used in health research projects at little or no cost. Some NGOs are directly involved in the administration of research grants. Others may be the fiduciary agent for a grant to a research organization that is exploring an issue related to an NGO program. However, most are organizations that work with communities. A major role is therefore to identify resource gaps using networks to link communities, health providers and managers, and funding agencies in a meaningful way so that financing can appropriately be directed to targeted health issues. NGOs may also contribute by identifying other potential sources of funding, for instance, in the local private sector. 3.3 Knowledge generation Knowledge can be acquired in various ways, by many methods, and by different types of people; there are different cultures of enquiry. Because of their typical 'grass-roots' experience, several NGOs are able to access indigenous knowledge and specific information, which may be less attainable for other types of organizations. This type of knowledge might be very useful when pooled with knowledge acquired by others; in this way, a more comprehensive analysis can occur. NGOs can be particularly adept in conducting formative research (baseline studies, needs assessment), in operational or action research and in process and impact evaluation. This type of research is particularly relevant for setting priorities, for informing intervention, as well as for identifying further research needs. Although knowledge generation is generally not a primary NGO activity, there may be specific 'knowledge generation' research niches for NGOs. For instance, as suggested by the Canadian Council for International Cooperation (CCIC) and actually carried out by a few NGOs, " There is a need for NGOs to be more involved in policy research even in Canada " (Interview with B. Tomlinson, CCIC). Figure 3 illustrates the research cycle in the narrow sense of knowledge generation. This cycle applies whatever the research type, and whether the research is conducted by an NGO or an academic institution. Figure 3 The research (knowledge generation) cycle (adapted from McKenzie [36]) 3.4 Utilization and management of knowledge While asserting that the production of knowledge is the primary function of research, and that levels of knowledge have increased considerably, a discussion paper for the International Conference on Health Research [ 1 ] also recognizes that the ability to draw from research in terms of lessons learned, application to interventions, and programming and policies which support the overarching goal of equity, is often lacking. Inadequacies include the inability of developing countries to access pertinent international research literature and knowledge bases (either as contributors or users), the inability to access new information technologies, and the inability to ensure closer links among the research community, health service managers and health policy makers. The effective use of research findings and their dissemination is an increasingly important public health policy concern. In 1995, an international research conference was held in Vancouver, Canada, on dissemination research. This type of research is similar to what is now called 'translational research' , that is, the conversion of research findings from basic, clinical or epidemiological environmental health science research into information, resources, or tools that can be applied by health care providers and community residents to improve public health outcomes in at-risk neighborhoods. NGOs are frequently at the interface of applied research and policy-making, at least at the administrative level, and their potential input into research utilization for policy-making needs to be valued. Research can make a substantive contribution in at least three phases of the policy-making process: agenda-setting, policy formulation, and implementation [ 27 ]. It is widely recognized that health research is underutilized in policy-making. The generation of new knowledge is highly valued, but its translation and use does not appear to be valued as much [ 28 ], which may partly explain why application of newer knowledge is often a weak link in the research cycle. Factors potentially enhancing utilization can be identified by exploration of priority-setting, activities of the health system at the interface between research and policy-making, and the role of recipients, or "receptors", of health research [ 27 ]. There are several models of research utilization in policy-making, but interactive or exchange models may be more conducive to the effective use of research than unilateral models because they bring researchers and decision-makers closer together [ 10 , 27 ]. NGOs often play a critical role in interpreting the evidence and translating its relevance for local communities. Inevitably the level of involvement by the community depends on relevance and opportunity for action and advocacy. Assessing and evaluating opportunities for advocacy and action occur as NGOs work with communities on these issues. Effective involvement of the community and its participation is a "matter of reciprocity and continuing dialogue in which participation takes different forms and influences change in several directions" [ 14 ]. Once the evidence has been analyzed and assimilated, NGOs can serve as intermediaries in delivering feedback to communities and in the planning, implementing and monitoring of new interventions, policies or other actions which might have been proposed. The knowledge and information acquired by NGOs can be unique and offer added insight into new ideas for future health research. This is, in part, because of the extensive interrelationships NGOs have forged with different communities, organizations, the private sector and governments, among others, often over decades of dedicated work. Additionally, NGOs are in a good position to test the ability of research findings to be scaled up in a 'real world' environment. According to Lavis et al [ 10 ], while the "knowledge loop" needs to be completed, that is, from knowledge production to knowledge-based decision-making through knowledge transfer or brokering, not all research organizations should become involved in knowledge transfer; if they do, the knowledge pyramid may be shaky. Innovations stemming from research are at the base of the pyramid, and actionable messages are at the top. Individual studies and synthesis of research knowledge are the intermediate layers. Lavis et al contend that it may not be relevant to transfer knowledge from individual studies, but rather, from bodies of cumulative research knowledge, and that knowledge transfer brokers are needed for this purpose. This model of specialized roles is probably more relevant at the macro level and in industrialized countries. In resource-poor countries, polyvalent organizations such as NGOs have a key role in sharing, translating and implementing research findings at the community and country level. They provide channels for the use of research results at the community level, as they are closest to the communities themselves. For that very reason, they may also feel more compelled to complete the research cycle, including application of the findings. Third World Network , for instance, an independent non-profit international network of organizations and individuals involved in issues relating to development, conducts and disseminates research to help organizations around the world participate in and influence international economic and social policy. NGOs may also be involved in testing pilot models of intervention and in their subsequent scaling-up. 3.5 Capacity development The preliminary examination of the functions performed by the some 125 organizations involved in a significant way in health research reveals that while knowledge generation is a concern shared by most, research capacity strengthening receives relatively little attention [ 1 ]. One weakness or inattention in research capacity strengthening activities, for example, has been the lack of a recognized career path for local health researchers which has resulted in diverting promising researchers to other careers or to other countries. The development and retention of research capacity remains a challenge in many countries [ 29 ]. Quality control and assurance requires skills and structures which support these objectives. Skills such as leadership, advocacy, networking and communication are important and need to be built through capacity development. Research management is also a skill which needs to be strengthened and a skill that will improve the quality, appropriateness and timeliness of research and its dissemination. NGOs in the North and in resource-poor countries often have the capacity for facilitating training and for sharing the lessons learned in needed skills. Partnership with NGOs in such capacity-building needs to be valued and reinforced. The Canadian Society for International Health (CSIH) and the Canadian Public Health Association (CPHA) have participated in capacity-building activities in many countries and continue to share their experiences and lessons learned. Support for such sharing and building capacity makes sense and should be facilitated by donor agencies. WHO, through its creation of a Department of Research Policy and Cooperation within the cluster of Evidence and Information for Policy, has defined as one of its objectives: "the development of initiatives aimed at strengthening research capacity in the developing world with the ultimate aim of enshrining research as a foundation for policy". A number of other international initiatives have also attempted to address some of these capacity issues: the International Health Policy Program (IHPP), the Applied Research on Child Health (ARCH) project, the Swiss Commission for Research Partnership with Developing Countries (KAPE) and, in Canada, the IDRC. Since 1970, IDRC has been providing financial and technical assistance to academic institutions, government agencies and NGOs in developing countries, as a means of promoting sustainable and practical development and strengthening indigenous research capacity. IDRC's experience provides important and valuable lessons about implementing applied research in partnership with NGOs [ 30 ], as summarized in the table 1 . Table 1 Lessons learned from research in partnership with NGOs: IDRC experience First, applied research should have a practical application, reinforce knowledge and skills, and introduce and promote innovative, effective strategies and approaches for improving human health and well-being. Not only should research results be for local application, they should also be shared and adapted to other venues and contexts. Second, efforts need to be made to build knowledge and understanding about the benefits accruing from applied research. NGOs, by their very nature, are action-oriented. Applied research is often perceived as of limited use to their ends, an esoteric, academic exercise of limited value to the immediate needs of the poor and disadvantaged. Time and effort need to be invested in nurturing an understanding within the academic community of the value of applied research within the context of development efforts. Third, applied research should be used to develop and strengthen local research capabilities. NGOs do not, as a rule, possess the internal capacity and skills to design and conduct applied research studies. Attention should be paid to assisting NGOs in making contact with qualified researchers, and increasing NGO knowledge and skills to negotiate the terms of reference for applied research studies. This cannot be achieved simply through providing information about applied research methodologies or organizing a single workshop. Trust has to be developed between the NGO and academic communities, as a means of reinforcing linkages between them and building upon and using their comparative strengths, characteristics and areas of expertise to design and conduct applied research. Fourth, local communities should be involved in the design and implementation of applied research activities. The local people need to understand the purpose of the proposed research, provide input and advice about its design and conduct, and be actively involved in the application and dissemination of research results. Without the active participation of the community, the utility and eventual application of the research results will be of little value. Source : [ 30 ] The CPHA, through the CIDA-funded initiative Canada's International Immunization Program – Phase 2 (CIIP2), dedicated 5% of the program's budget to applied research. Part of this funding was used to strengthen primary health care in developing countries through the NGOs that implemented the immunization and primary health care activities through the auspices of CIIP2. NGOs who wish to become more involved in research generally recognize the need for extramural training and support. Partnering with universities and research institutions may provide such training opportunities. Additionally, there are international institutions such as INTRAC (International NGO Training and Research Centre) that are specifically geared towards meeting the challenges and needs of NGOs in research. Those NGOs that are part of international networks can draw from the body of research conducted elsewhere. NGOs may also provide substantive input into research training, be it by grounding research methods in reality so that research is more applicable, or by providing research sites and questions for academia and graduate students. NGOs may also be in a good position to identify young scientists and promising investigators in host countries. Stimulating the demand for research by user groups, rather than supply-driven research, is one of the three strategies identified by Harrison & Neufeld [ 31 ] for capacity-building for essential national health research. NGOs and communities as user groups could be the target of capacity-building efforts. 4 NGO involvement in health research There is a lack of accessible and centralized information on NGO involvement in health research, although the CPHA CIIP2 applied research publication lists over 20 examples of NGO-related applied research carried out in the 1990s. The examples given below are based on discussions with a limited number of Canadian and international NGOs: CARE, World Vision Canada (WV), CECI (Centre d'étude et de coopération internationale), Inter Pares, HKI (Helen Keller International), and CCIC. In the case of AMREF (Africa Medical Research Foundation), ADI (Alzheimer's Disease International), Médecins sans Frontières (MSF) and RITC (Research for International Tobacco Control), most of the information was obtained from their websites and related publications and documents. The interviews and discussions covered the specifics of the implication of the NGO in health research, lessons learned through the experience, and respondents' perceptions on the role of NGOs in global health research, and on the strengths and weaknesses of their organization in this regard. These selected NGOs provide insight into some of the critical issues facing NGO involvement in global health research. It should be kept in mind that this selection is small and not meant to be representative. Nonetheless, all of these NGOs are involved, directly or indirectly, in global health research, and they are all Canadian or present in Canada. 4.1 NGOs and their involvement in global health research: illustration cases The interviews covered a broad range of cases, from NGOs little involved in research to those actually conducting independent research. The types of involvement are briefly described below. A salient observation is that what is considered as research by different NGOs is, for the most part, unclear and highly variable. This suggests the need for NGOs to develop common views on what is research, the various types of research, and the components of the research process. The interviews also revealed that while some NGOs are reluctant to be involved in research, others are eager to strengthen their capacity to do so. CECI has long been involved in health research, although it is reluctant to call this 'research'. A major activity is the undertaking of baseline studies that typically include an assessment of the health and nutritional status of populations. The data are used to orient or reorient programs, and to inform communities. In Cambodia, for instance, it conducted an initial assessment for a project aimed at improving the livelihood of rural poor in two sectors: health/nutrition, and agriculture marketing (CECI and Cambodia Researchers for Development: Improving Livelihood of the Cambodian Rural Poor: Strategies in Health, Nutrition and Agricultural Commodity Marketing, 2001). One interesting aspect of its recent work is the 'policy feedback' that it conducts in its large projects. The intent of the analysis is to clearly identify the lessons learned, and to discuss these with decision-makers and technical officers. This may be considered as part of 'knowledge translation' and it can be a particularly useful approach in advancing policies and programs. While CECI is also involved in health projects that do not include research even in a broad sense, it conducts research in areas that are indirectly related to health. For instance, in the IDRC-funded project intended to alleviate poverty in Burkina Faso, Viet Nam and Nepal, it collaborates with local universities and research institutions for the research and training components, notably on adapting the assessment of poverty to the specific context. CCIC and its member NGOs are involved in international policy research. For instance, Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreements have implications on access to drugs. In the reorientation of CIDA for improved aid effectiveness, there are obvious health implications, including how to respond to health plans as defined by health ministries, and assist with poverty reduction strategies. CCIC sees research on policies as a critical role of NGOs, and considers that NGOs should be more involved in the policy debate both in Canada and globally. World Vision (WV) Canada is active in research, particularly (but not only) in the framework of its MICAH projects (Micronutrients and Health in Africa) funded by CIDA. It primarily conducts formative and evaluation research (see table 2 for report of findings in Sénégal, published jointly with CIDA). Although it has PhD or MSc level personnel in each of its technical units, it does not have in-house research expertise per se ; it partners with research institutions, in the field and in Canada. It does not have the capacity to analyze all the data that it collects and therefore it collaborates with academic institutions in Canada. Graduate students can use the data for their theses. WV officers may also sit on graduate students' supervisory or examining committees. The primary use of the research findings is to reorient programs and inform the community. As programs may have to change their operations as a result of such research, the exercise may, at times, be regarded as threatening. Table 2 Final evaluation report, World Vision Canada, Micronutrient-for-Health Project in Sénégal (2002) The objectives of the project initiated in 4 districts in 1997 were to reduce micronutrient malnutrition among women and children, to reduce the incidence of illnesses affecting micronutrient status, and to strengthen local capacity for controlling micronutrient malnutrition. The baseline study revealed a high rate of (iron deficiency) anemia in pregnancy (49%), of low retinol (vitamin A) levels in breastmilk (57%), and of low serum retinol concentrations among preschool-age children. Iodine deficiency was widespread, with 20% of school-age children showing severely low urinary iodine levels. A similar survey was conducted after 4 years of project activities, and included control zones in each district. The final evaluation showed an almost complete elimination of vitamin A deficiency in the project areas, which was primarily attributable to the high coverage of vitamin A supplementation of under-fives and postpartum women. Household use of iodized salt increased from 6% to 14%. Anemia remained high among pregnant women (44%), however, in spite of the iron-folate supplementation scheme. The rate of intestinal parasites declined, but the project did not have an impact on diarrhea. The MICAH project had a positive impact in strengthening the national vitamin A policy of Sénégal. The evaluation report was published by the project and widely disseminated. The survey findings and recommendations were fed into the design of an up-scaling phase of the project, with more emphasis on the reduction of anemia among women. CARE is directly involved in research, and its involvement covers the whole process from conceptualization of the research question to data management and dissemination of research results. Some offices have staff whose role is specifically research-related, but this varies. They also work with partners. CARE has even been contracted by some donors to conduct research. The research is primarily qualitative, including participatory approaches, as well as operations and action research. CARE also conducts surveys, situation analyses and policy reviews. It receives funding for research from bilateral and multilateral agencies, and from large organizations such as Family Health International and the Population Council. Helen Keller International (HKI) is a technical assistance NGO that is also directly involved in research as part of its mandate. It addresses the causes of preventable blindness. It also provides rehabilitation services to blind people, and helps reduce micronutrient malnutrition which can cause blindness and death in children. It is involved in most stages of the research cycle, focusing on operations and action research. HKI's focus on blindness and micronutrients is a strength in that its research is more focused than that of other NGOs involved in health and nutrition. Its funds for research come from different sources. A research component may be built into programs, some operational research is conducted with funds for surveillance, or funds are provided for R&D specifically (eg. for FRAT studies [Fortification Rapid Assessment Technique]) and for the development of tools to assess the quality of nutrition interventions leading to adoption of relevant strategies (in Mozambique, Burkina, Mali and Niger). HKI has in-house expertise in research. There are several full-time research positions. In addition, it works with research partners at the local level, as well as with universities in Canada and USA. Inter Pares was created in 1975 to support NGOs from the South and to provide international development education in Canada. Inter Pares uses its own funds to conduct social research on political and economic issues, primarily action research. For instance, it carried out collaborative research with NGOs in the Philippines and of Bangladesh on family planning policy, and in Africa it has carried out research on economic issues. With Forum Afrique Canada , for instance, it is studying Canadian government trade and aid policy after G-8. It has in-house research expertise, particularly in sociology, although there is no research position as such. It usually works with partners, as it is a small NGO. Inter Pares uses research findings mainly for education and advocacy. AMREF has been active since 1957 in the field of applied health research and has an extensive bibliography documenting research results in the form of peer-reviewed publications, theses, manuals, reports, abstracts and conference presentations. The focus of AMREF's research activities has been primarily in the operational and applied domains. Many have addressed the important disease burden caused by communicable diseases such as malaria (see table 3 ) and schistosomiasis, but others have addressed organizational issues such as health information systems and technological issues like field diagnostics. Table 3 Example of an AMREF research study listed in its extensive bibliography In 1995, D'Allessandro et al [ 32 ] published a study which compared the efficacy of insecticide-treated and untreated bednets in preventing malaria in children living in the Gambia. The survey included 2300 children between the ages of 1 and 4 years; 1500 from villages who had received insecticide-treated bednets within their primary health care and 800 from villages which had not received treated bednets. It was found that the greatest benefit, in terms of reduced malaria morbidity, was observed in children who slept regularly under treated bednets. Measurable benefits were also accrued in children who slept regularly under untreated bednets, compared to children who did not use bednets at all. The conclusion of this study was that educational campaigns might well promote even the use of untreated nets because of the additional health benefits, while ultimately aiming at coverage with insecticide-treated bednets. Alzheimer 's Disease International (ADI), an NGO affiliated with WHO, specifically provides support for research among its numerous activities. In particular, it supports the research work of the 10/66 Dementia Research Group (the 10/66 refers to the dementia research gap, in which 'less than one-tenth of all population-based research into dementia is directed towards the two-thirds or more of cases living in developing parts of the world [ 31 ]). The vision of ADI is that research not only generates awareness, but is the basis for policy which, subsequently, can provide the impetus for development of appropriate services for affected persons. The 10/66 Dementia Research Group divides its research activities into pilot studies, qualitative studies, intervention studies and population-based studies. This group has published a consensus statement [ 33 ] and a methods paper [ 34 ], and members are now publishing research results (see table 4 ). This NGO's 10/66 Dementia Research Group has regional networks in India and South Asia, Latin America and the Caribbean, China and South East Asia, Africa and Russia, Eastern and South Eastern Europe which are coordinated by Dr. Martin Prince of the Institute of Psychiatry in London, England. Table 4 Example of an Alzheimer's Disease International- supported health research study The results of a population-based study undertaken in Kerala, India to evaluate a community dementia case-finding program was published by Shaji and collaborators in 2002 [ 35 ]. Their aim had been to validate a training program where local community health workers (CHWs) were trained to identify possible cases of dementia. The training program consisted of 2 ½ hours of formal instruction. Workers' diagnoses were then confirmed by an experienced psychiatrist. The 19 CHWs identified 51 possible cases among 1979 persons aged 60 and older in their communities. There was expert confirmation for 33 of these cases (65%). Although the remaining 18 did not have dementia, 13 did in fact suffer from other psychiatric illnesses and only 5 had no psychiatric diagnosis at all. The conclusion was that CHWs can play an important role in identifying cases of dementia in a community setting. Médecins sans Frontières (MSF) was the first NGO to both provide emergency medical assistance and publicly bear witness to the plight of the populations they served. MSF is at the forefront of emergency health care as well as care for populations suffering from endemic diseases and neglect. MSF has undertaken an initiative on drugs for neglected infectious disease which combines advocacy, research and capacity development, and networking. In contrast with private sector research, it is need-driven rather than profit-driven. Five pilot projects are currently underway focusing on capacity building and technology transfer. This initiative started with a review of pharmaceutical research and development outcomes over the last 25 years and of current private and public initiatives. Highlights of the findings and conclusions, published in Lancet [ 36 ], are provided in table 5 . Table 5 Analysis of trends, drug research and development for tropical diseases, MSF (2002) The extensive review revealed that of 1393 new chemical entities marketed between 1975 and 1999, only 16 were for tropical diseases and tuberculosis. All new drugs for neglected diseases represented a clear therapeutic benefit, and all are included in the WHO Essential Drug List, which indicates the importance of new drugs for neglected diseases. In contrast, over the same period, two out of three new drugs offered little advantage over existing ones. There was no indication that drug development for neglected diseases would significantly improve in the near future, however. Private-public partnerships, or else, incentives to encourage private investment towards the development of new cost-effective drugs may help overcome this limitation. For the most neglected tropical diseases which may not account for a large share of the global burden of disease, a new approach is needed. The feasibility of an international not-for-profit network that would focus on the most neglected diseases is being tested in the on-going pilot projects. Research for International Tobacco Control (RITC) is an International Secretariat based at IDRC headquarters (Ottawa) that funds multidisciplinary tobacco control research projects in developing countries. Its mission is to create a strong research, funding and knowledge base for the development of effective tobacco control policies and programs, through a combination of research, dissemination, strengthening of capacity and coordination. RITC concentrates on research on psycho-social correlates of tobacco use. It provides support to research projects conducted by NGOs, such as, the Youth and Tobacco Survey conducted in Russia by the Russian Public Health Association, with the technical assistance of the CPHA (table 6 ). Table 6 Youth and Tobacco Survey, Russian Public Health Association (RPHA), 1999 This study is part of the Global Youth and Tobacco Survey (GYTS) undertaken in several countries around the world. The survey in Russia was designed to provide prevalence data on tobacco use among adolescents in school (13–16 years), and to better understand and assess students' knowledge, attitudes and practices related to tobacco. Information pertained to, for instance, age of initiation of tobacco use, perceived health risks and social benefits, extent of peer and advertising pressure, perception of the tobacco-related curriculum, and likelihood that tobacco users will quit. The survey raised awareness on the issue of smoking and youth. Several recommendations were made by the Association to Parliament on the basis of survey findings, including the adoption of legislation to limit tobacco advertising, to reduce the tar and nicotine content of cigarettes, and to have an impressive warning labeling on packages. Seminars and conferences on the survey results and their implications were held. The Association has prepared a report: "Tobacco or Health in Russia". Additionally, the President of the RPHA, as a result of the GYTS survey and the ground-breaking leadership role the RPHA played in tobacco control among youth in Russia, was a member of the delegation from the Russian Federation to the WHO Framework Convention on Tobacco Control (FCTC) – hence an example of the translation of applied research results into policy action. CPHA has also provided technical and financial support through its various international initiatives funded by CIDA to its public health association partners to carry out of the GYTS in Burkina Faso, Niger, Haiti, and Cuba; and in partnership with Institutes of Public Health in Bosnia & Herzegovina, Serbia & Montenegro, and in the UN-administered province of Kosovo. The results from the surveys (carried out in collaboration with the Centers for Disease Control and Prevention [CDC] of USA) are being used to develop tobacco control policy and youth-focused smoking prevention and cessation programs. The experience of CSIH in global health research is described under 5.2.1. 4.2 NGOs' perceived strengths and weaknesses in research The following summary of perceived NGO strengths (and weaknesses) in health research is based primarily on the data from individual and group interviews that were specifically conducted as inputs to this discussion paper. It is a common view that NGOs are in a good position to participate in health research because of their knowledge of, and their presence in, local communities. Furthermore, their involvement increases the relevance of research to communities. " NGOs give a human face to research, and they are in a good position also to build on indigenous capacity " (Interview with S. Baker, HKI Africa). Additionally, they may be more compelled to complete the research cycle and apply the findings. Their involvement in research is perceived as a motivation to use the research to design, develop and respond to circumstances affecting development. Evaluation research, in which they are frequently involved, tells them whether or not they have an impact. Since they are closely connected with communities, they have the ability to see the application of their research results. For this reason, NGO-initiated research is often more likely to be translated into practice in a timely manner as it is almost always directly related to practice. The NGO structure brings concreteness and a style which is guided by values and beliefs with an action orientation. Another major strength of some NGOs is their international networks which give them access to technical information and support. Finally, NGO values of ethics, solidarity and dialogue are important for health research to contribute to reducing inequities and for empowerment. 4.3 Constraints to greater NGO involvement in health research 4.3.1 NGO views on research and its congruence with their mandate Many reasons that account for the reluctance of NGOs to become (more) involved in research activities pertain to NGO perceptions on research (Center for Advanced Studies of International Development. Symposium on NGO/Academic Linkages. East Lansing: Michigan State University; April 16–17, 1993; Edwards M, Griffiths M: Terms of Reference for the DSA [Development Studies Association] Workshop on the Academic Practitioner Interface. London: DSA, 1994). In the past, research was an academia-driven and based, elitist and theoretical exercise, the results of which are of little use to NGOs and the communities with which they work. Traditional research strategies and approaches were seen as top-down, non-participative and controlled by external actors. Research activities were regarded as requiring special technical expertise, much time and effort, access to professional journals and research literature, and substantial human and financial resources, characteristics not typically found in NGOs. Finally, the scientific rigor demanded by researchers was believed to be difficult to achieve in field-based situations, where unpredictability and subjectivity are the norm. What NGOs perceive as research and as their role in this respect varies widely. For instance, there is some hesitation and even reluctance in including baseline studies or project evaluation under 'research'. Another obstacle is the fact that some NGOs that raise funds from the public are afraid to go against the expectations of the donors if the money is reallocated for research, and particularly for policy research in Canada: " Donors do not want to hear that NGOs are doing research as they are implementation organizations " (Interview with C. MacDonald, World Vision Canada). 4.3.2 Lack of training opportunities, funding, time and motivation Among other barriers, interview respondents mentioned lack of training opportunities, lack of funding owing to their (limited) mandate, priorities of funding agencies, and time constraints. Because of lack of training or of specialized researchers, NGOs may not be in a position to conduct top quality research, and scientific rigor may be lacking in certain instances. Lack of access to scientific literature when in the field can also be a major shortfall. It is often difficult to secure research funding from certain donors. Many Canadian NGOs rely heavily on negotiated contracts with CIDA, which leaves little time and place for research. However, CIDA does fund some research (in a broad sense), particularly formative and summative evaluations. These are encouraging trends, but the aim should be for bilateral agencies to openly fund some research, like in the UK and some Scandinavian countries. Lack of interest or of a clear view of the whole research process can also be considered as impediments. As several NGOs do not see research as part of their mandate, they may not be willing to get involved in research: " NGOs do not have a research mandate, and therefore we do not foresee developing research expertise in-house. Linking for instance with universities is feasible for development-driven research " (Interview with R. Hazel, CECI). NGOs may have to change their structures and priorities in order to support autonomous research. 4.3.3 Scale and type of NGO research Because NGO research is often conducted on a small scale and is usually of a qualitative nature, it often goes unrecognized by governments, and even by research organizations and funding agencies, which tend to favour large scale quantitative research. NGOs interested in pursuing a research profile require a type of mentorship in terms of standard performance indicators in the research domain. For example, publication has traditionally not been a strength and much NGO research does not reach beyond the gray literature or report level. Because scientific publications are an important means of transfer or dissemination of research results, NGO capacity to publish their findings needs to be strengthened. 4.3.4 Weak links with the international research community There is not enough networking and collaboration between NGOs and the international research community, including academia. This has traditionally been due to a dichotomy in the interests of NGOs and the academic community, in that NGOs are more oriented towards a development agenda, while academics tend towards special research interests. 5 Future needs In light of the above issues and concerns, and in order to foster greater interest and participation of NGOs in research, the barriers of lack of interest, lack of funds, lack of training and lack of recognition, among others, need to be addressed. We discuss some strategies below. 5.1 Opportunities to build NGO capacity in research, in Canada and overseas Substantial global health academic capacity has developed within NGOs both in the U.S. and the U.K. For example, Family Health International (FHI) has integrated research, training, and development capacity on an evidence-based foundation. It also embodies many of the competitive aspects of private sector-led initiatives that can allow creativity and innovation. As emphasized by Harrison and Neufeld [ 31 ], however, capacity building efforts for health research have been of most benefit to industrialized countries. In order to ensure that less developed countries are the principal beneficiaries, they recommend, as part of a three-pronged strategy, the nurturing and support of multi-stakeholder problem-oriented learning, and research networks which include NGOs. The other components of the strategy are research investments that explicitly reduce the high cost of knowledge translation in developing countries, and the stimulation of demand-driven research. A peer-learning process is among the strategies for NGO capacity building in research. NGOs can draw on expertise already developed in research-based NGOs. The learning process should be shared with NGOs from the North and from the South. Additionally, NGOs should consider taking the initiative in organizing scientific activities (seminars, workshops, symposia) on global health research topics, which could serve as a catalyst in bringing together different stakeholders. 5.2 Building partnerships and alliances 5.2.1 Creating and facilitating networks that support global health research The creation of networks which have the common goal of supporting global health research is one way to strengthen partnerships and to consolidate valuable resources from each partner. Leadership and governance issues are necessary hurdles which can be overcome by focusing on the ultimate gains in terms of supporting and conducting successful research activities. NGOs can assist in the establishment and functioning of these networks, particularly by providing stable infrastructure support. One of the greatest challenges is in making the network function effectively through different leadership turnovers in the different partner organizations. CSIH has had global health research as part of its mandate since its formation. CSIH is an active member of the Canadian Coalition for Global Health Research (CCGHR), and a key challenge in this capacity is to develop a strong foundation of understanding and mutual respect amongst all players in global health research, including NGOs. CSIH experience in global health research is described in table 7 . Table 7 The experience of CSIH in global health research In the early years, CSIH partnered with the Canadian University Consortium for Health In Development, which represented all the major universities in Canada and their partners in research and development. This partnership represented a strong and vital part of CSIH's operations. Following the decrease in funding for such a partnership, there was a decision to disband the Consortium and establish a network of universities and colleges that would promote and support academic and research interests within the Society. This network, which was formally given the status of a Division for a few years, has been and continues to be functional but not as a strong advocacy unit. This was largely due to the fact that funding for the network was cut by CIDA in 2000. Nevertheless the network is an important source of technical support for CSIH in its projects and advice. Following the Thailand meeting in October 2000, Canadians were challenged to explore the role that they could play in diminishing the 10/90 Gap in Global Health Research funding available to Low and Middle Income Countries (LMIC). To this end an interest group was formed, of which CSIH was part in order to carry on the momentum of Thailand and future explorations. Key people met with decision makers during the spring and summer of 2000 and September 11, 2001, marked the inaugural workshop in Vancouver to discuss global health research and the 10/90 Gap. CSIH was one of two NGOs who attended. Following that meeting, CSIH was invited to participate in a new Canadian Coalition for Global Health Research (CCGHR). CSIH was active in suggesting that the concept of a coalition was a way to emphasize the role of advocacy and action that is necessary for global health research initiatives to be successful. As of October 2001, the Coalition included two NGOs (CSIH and CPHA) who were part of a lobby to expand the mandate of CIHR (Canadian Institutes of Health Research) to include global health research in more than one Institute. To this end, the Institutes of Gender and of Aboriginal Health joined the Institute of Population Health in realizing its global health mandate. The Global Health Research Initiative memorandum of understanding (MOU) was signed at the 2001 Canadian Conference for International Health (hosted by CSIH). The amendment to MOU as a result of negotiations between CSIH and CIHR included NGOs as one of the important players. The first formal retreat for the coalition was held in August 2002. CSIH was formally named as a member of the Coalition Steering Group. The Working Group on the Role of NGOs in Research was affirmed as separate from the Advocacy Working Group. CSIH agreed to take the lead to collaborate with other key NGOs to develop a paper and case studies. CSIH as part of CCGHR lobbied in the spring and summer of 2002 to the G-8 for the inclusion of a commitment to global health research within NEPAD (New Partnership for Africa's Development). Support for global health research in Africa was announced and funds were set aside for this new initiative. The first Annual Meeting of CCGHR was held at the Canadian Conference on International Health (CCIH) in October 2002. The Working Groups reported at that meeting and CSIH announced the formation of a Research Committee and invited its members to participate. The Executive Director drafted an outline of a background paper on the Role of NGOs in Global Health Research and presented to the plenary session of the annual CCGHR meeting for comment and feed-back. An ad hoc Working Group on Research was formed to draft the background paper with a view that it will be a position paper for CSIH and provide a background working paper for the Coalition. In the autumn of 2002, the first request for proposals for global health research grants was released. Despite the fact that NGOs were named as important partners, they were not invited to be part of the review panel for this round. It was noted as a deficiency in the review of the process by CIHR. To date, CSIH has been an active and welcomed participant of all key meeting of CCGHR Steering Committee meetings. CSIH remains actively engaged in working groups on Governance to determine options for institutionalization of the CCGHR. In collaboration with CIHR and IDRC, CSIH is actively planning the Second Annual Global Health Research Meetings at CCIH and the integration of significant research and development content in the conference. 5.2.2 Partnerships with universities and other research institutions Partnerships with universities and other research institutions is one means of strengthening the research capacity of NGOs, and also of academia. NGOs and research organizations each have a unique 'value-added' contribution to make to global health research and therefore, partnering among them amplifies their individual strengths. Such partnering may be a real challenge for NGOs, however, as their institutional culture is so different. NGOs may be invited by universities to partner, but plans are often already laid out, so that the NGOs may only be involved in executing the plans. What NGOs want is to be part of the research process from the start. An interesting initiative to document and promote South-Canada health research partnerships is currently underway [ 37 ]. NGOs are open to partnerships with academia, but the goal has to be development-oriented. Experience suggests that it is often difficult to reconcile the academic and development framework, for instance when integrating MSc or PhD students in development projects. Nonetheless, integrating graduate students in NGO projects should be a good strategy for balanced and equal partnerships. As less than 1% of university-based health research in Canada is directed towards the problems of global health according to a Canadian Consultation on Global Health Research held in 2001 , the prospects of university-NGO research links are constrained by funding. Nevertheless, the recent Global Health Research Initiative of the coalition of Canadian institutions funding global health research is promising as it opens new avenues for research collaboration between the North and the South, and hopefully also between universities and NGOs. During the 1990s, there were several attempts to bridge the NGO/academic gap with respect to health research in developing countries. Save the Children UK, Oxfam and some US-based institutions supported workshops and symposia that aimed at bringing together representatives from both communities as a means of building links and forging partnerships in support of increasing the scale, scope and relevancy of health research in developing countries (Edwards M, Griffiths M: Terms of Reference for the DSA [Development Studies Association] Workshop on the Academic Practitioner Interface. London: DSA, 1994). CPHA, through the CIDA-funded Canada's International Immunization Program – Phase 2 (CIIP2), supported applied research carried out by Laval University, Université de Montreal and University of British Columbia. At the time, these were quite innovative approaches to applied health research, linking the universities with local NGOs. In 1995 CPHA also organized a Symposium on NGO/University Linkages for Health Research [ 30 ]. One mechanism to expand the use of research generated by NGOs is to improve the linkage between NGOs and universities. Each complements the other in the area of health research. NGOs offer proximity to people and situations, reality-based and context-specific research environments, opportunities to develop and assess innovative strategies and research methods, a means of disseminating and popularizing the results of research projects, and credibility outside of academia. Universities and other research organizations offer expertise in research design and application, an environment for reflection, access to and knowledge about most recent literature, a tradition of scientific rigor and interest in new, innovative research methods and approaches, and a high degree of credibility. Academics can also provide guidance and advice on how to prepare research proposals and to carry out research studies, guidance in the preparation of reports and publishing of research results, and training for NGO staff in research methods. The participants of the CPHA Symposium on NGO/University Linkages for Health Research in Developing Countries [ 30 ] identified several mechanisms that could help bridge the gap between NGOs and universities as a means of facilitating future collaborative research initiatives. There must be first and foremost a real willingness on the part of both parties to modify their attitudes about the role and capabilities that each can offer. Mechanisms to achieve this end include conferences and seminars, newsletters, and the use of e-mail and the Internet. Another suggestion called for the use of "field-friendly" research methodologies. It was also recommended that, although the objective is not to transform NGOs into research institutes, they should receive more training in research methods and proposal development. It was suggested that exchanges take place wherein university researchers use sabbatical leave to work with NGOs and NGO personnel be seconded to universities to provide a field perspective. Additionally, research results need to be disseminated quickly and in a format that ensures maximum access by those in the field who are to apply the knowledge generated. Otherwise, research creates expectations within the NGO community and study population that remain unsatisfied. The development of innovative North-South research partnerships is the focus of a working paper prepared for the CCGHR by Neufeld et al [ 37 ]. As emphasized in this document, such partnerships are not an end in themselves, but rather, they are to contribute to sustainable health research systems and to health development. Principles of research partnerships, and a useful model to assess these, are proposed. Although types of partnerships are not specifically detailed, it is implied that NGOs are important research partners. Finally, as mentioned earlier, stronger partnerships between NGOs and social science researchers in particular should be sought in resource-poor countries. Lessons learned from these partnerships, in the areas of action and indeed policy and legislation (for example, in the tobacco or environment fields) show how evidence can be transformed into action with the right partnerships between researchers and NGOs. 5.2.3 An NGO Network for Global Health Research? NGOs may benefit in various ways from developing a global health research network. First, many NGOs already operate at national and international levels and understand the challenges of coordination and communication which this entails. There is a need to identify overarching principles of NGO contribution to health research. Second, NGOs must be both proactive and interactive within the framework of the health research agenda. Roles must be clearly understood by each partner. In any case, advocacy for relevant research and use of results would be a critical function of the network (see training modules on advocacy [ 38 ]). Such networks may enhance the ability of NGOs to partner with other research stakeholders in multisectoral coalitions, and even to initiate partnerships with research organizations. In the framework of an NGO network of this sort, the following discrete activities could be envisaged by the lead NGO: • To invite NGOs to post on a selected website success stories, as well as their experience/opinions/needs/priority research issues, using a template adapted from the one developed for this purpose in the UK • To organize workshops for NGOs who are, or who wish to become, involved in research, with research organizations where deemed appropriate. The purpose would be: • To link these NGOs in order for them to interact on research issues; • To share lessons learned and success stories of research involvement of NGOs and their partners • To enhance understanding of, and collaboration with, potential research partners; • To set-up a core group of NGOs involved in global health research to convey NGO views to global health research fora and organizations. The following are a few key questions that could be addressed by an NGO network: 1. How can NGOs contribute to the framing of the research questions if we were to support the necessary equity-based research for improving the overall performance of the health system? 2. How do we balance this with the necessity for research which documents and monitors sustained and emerging inequities which may have a greater impact on the health and well being of individuals than the health (care) system will ever have? 3. How can we ensure that NGOs influence research priorities so that they are reflective and evaluative of overseas development assistance (ODA) direction and priorities such as national poverty reduction strategies. For example what is the impact of PRSPs on equity and health? How will researchers monitor this? What could be the potential role of NGOs in partnership with researchers to begin to monitor and evaluate this new direction in overall aid policy? 4. How can NGOs be best represented within the international research community? The new millennium offers many challenges. In order to maximize the potential benefits of health research, all partners including NGOs must share a common vision and recognize and appreciate the strengths of each. Participation in health research needs to be a coordinated effort. One key challenge will be to establish better communication among all partners in health research. This can only be achieved by a willingness to share in leadership, ownership and in the conduct of health research activities. Another key challenge will be to explore ways in which funding for health research can be strengthened. Leveraging must be seen as a strategic tool of NGOs to maximize dollars allocated to health research. Conclusion Several NGOs have had impressive track records in global health research. Other NGOs have expressed an interest in becoming more involved in global health research. Their contribution to more equitable, ethical, relevant and effective research is crucial and needs to be strengthened. Research has to be regarded as a broad loop system rather than restricted narrowly to the production of knowledge. This is particularly critical for global health research whose primary goal should be to improve health and its determinants in low and middle income countries. NGOs principal roles in the process pertain to shaping research priorities, advocacy for more relevant research, translating and using research findings, in addition to generating new knowledge in areas where they may have a comparative advantage, notably qualitative, social, action, evaluative, and policy research. NGO partnerships with research organizations should be seen as means of a mutual enhancement of health research capacity and contribution to development. NGOs should be instrumental in building with other stakeholders coalitions for global health research with the aim of closing the 10/90 health research gap. List of Abbreviations ADI Alzheimer's Disease International AFRO-NETS African Networks for Health Research and Development AIDS Acquired immunodeficiency syndrome AMREF African Medical and Research Foundation ARCH Applied Research on Child Health (ARCH) Project CCIC Canadian Council for International Cooperation CCISD Centre de coopération internationale en santé et développement CCIH Canadian Conference on International Health (hosted by CSIH) CECI Centre canadien d'étude et de coopération internationale CCGHR Canadian Coalition for Global Health Research CDC Centers for Disease Control and Prevention CHW Community health worker CIDA Canadian International Development Agency CIHR Canadian Institutes of Health Research CIIP2 Canada's International Immunization Program – Phase 2 COHRED Council on Health Research for Development CPHA Canadian Public Health Association CSIH Canadian Society for International Health DFID Department for International Development (UK) DSA Development Studies Association ENHR Essential National Health Research FCTC Framework Convention on Tobacco Control (WHO) FHI Family Health International FRAT Fortification Rapid Assessment Technique GYTS Global Youth and Tobacco Survey (WHO and CDC) HKI Helen Keller International IDRC International Development Research Centre IHPP International Health Policy Program INTRAC International NGO Training and Research Centre KFPE Commission for Research Partnerships with Developing Countries LMIC Low and middle-income countries MICAH Micronutrients and Health in Africa (WV project) MSF Médecins sans frontières NEPAD New Partnership for Africa's Development NGO Non-governmental organization OECD Organization for Economic Co-Operation and Development ODA Overseas Development Assistance PRSP Poverty Reduction Strategy Papers RITC Research for International Tobacco Control RPHA Russian Public Health Association SHARED Scientists for Health and Research for Development TRIPS Trade-Related Aspects of Intellectual Property Rights UNDP United Nations Development Programme WHO World Health Organization WV World Vision (Canada) Authors' contributions HD designed the outline of the paper, conducted interviews with NGO representatives, wrote the first complete draft, and coordinated the review process within the CSIH. JHR drafted some sections and provided comments on the successive versions of the papers. MM provided international NGO and a field based perspectives to the paper, in addition to conducting group discussions with NGO personnel. LJ designed the figures, and edited and formatted the text. TG contributed to the conceptualisation and content of the manuscript. She wrote several sections and edited others, and she provided case studies.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC554095.xml
539286	HTLV-1 and -2 envelope SU subdomains and critical determinants in receptor binding	Background Human T-cell leukemia virus (HTLV) -1 and -2 are deltaretroviruses that infect a wide range of cells. Glut1, the major vertebrate glucose transporter, has been shown to be the HTLV Env receptor. While it is well established that the extracellular surface component (SU) of the HTLV envelope glycoprotein (Env) harbors all of the determinants of interaction with the receptor, identification of SU subdomains that are necessary and sufficient for interaction with the receptor, as well as critical amino acids therein, remain to be precisely defined. Although highly divergent in the rest of their genomes, HTLV and murine leukemia virus (MLV) Env appear to be related and based on homologous motifs between the HTLV and MLV SU, we derived chimeric HTLV/MLV Env and soluble HTLV-1 and -2 truncated amino terminal SU subdomains. Results Using these SU constructs, we found that the 183 and 178 amino terminal residues of the HTLV-1 and -2 Env, respectively, were sufficient to efficiently bind target cells of different species. Binding resulted from bona fide interaction with the HTLV receptor as isolated SU subdomains specifically interfered with HTLV Env-mediated binding, cell fusion, and cell-free as well as cell-to-cell infection. Therefore, the HTLV receptor-binding domain (RBD) lies in the amino terminus of the SU, immediately upstream of a central immunodominant proline rich region (Env residues 180 to 205), that we show to be dispensible for receptor-binding and interference. Moreover, we identified a highly conserved tyrosine residue at position 114 of HTLV-1 Env, Tyr 114 , as critical for receptor-binding and subsequent interference to cell-to-cell fusion and infection. Finally, we observed that residues in the vicinity of Tyr 114 have lesser impact on receptor binding and had various efficiency in interference to post-binding events. Conclusions The first 160 residues of the HTLV-1 and -2 mature cleaved SU fold as autonomous domains that contain all the determinants required for binding the HTLV receptor.	Background Human T-cell leukemia virus type 1 (HTLV-1) has been found primarily in CD4+ and CD8+ T-lymphocytes in vivo [ 1 - 3 ], whereas CD8+ T-lymphocytes are thought to be the in vivo reservoir of HTLV-2 [ 4 ]. However, the in vitro tropism of HTLV-1 and -2, as determined using HTLV envelope-pseudotyped virions or envelope-induced cell fusion assays, appears to be ubiquitous [ 5 - 7 ]. Indeed, we recently showed that Glut1, the ubiquitous vertebrate glucose transporter, serves as a receptor for HTLV-1 and -2 envelope glycoprotein (Env) [ 8 ]. While the precise organization and properties of the receptor-interacting Env domains has not been reported, we found that the amino terminal two-thirds of the HTLV-1 extracellular surface component (SU) are sufficient to confer HTLV-1 tropism to an ecotropic Friend murine leukemia virus (F-MLV) Env [ 9 ]. A cell fusion interference assay performed with this HTLV/F-MLV Env chimera and the parental Env confirmed that this 215 amino acid Env domain, harbors HTLV-1 receptor-binding determinants [ 9 ]. The corresponding domain in MLV Env SU – located upstream of a conserved K/R L L T/N L V Q motif in the SU of the HTLV-1 and F-MLV Env [ 9 , 10 ] – is well characterized and comprises two main functional regions: an amino terminal sequence harboring the receptor-binding determinants, VRA, VRB and VRC [ 11 - 13 ], and a proline-rich region (PRR), starting at the first proline residue of the GPRVPIGP sequence [ 11 , 14 ] and flanked by two highly conserved GXDP [ 15 ] and CXXC [ 16 ] motifs (Figure 1 ). In the ecotropic and amphotropic (Ampho) MLV Env, the PRR is a putative hinge region implicated in conformational changes, triggered after receptor binding, and subsequent fusion [ 17 , 18 ]. In the central region of the HTLV SU, a short sequence (Env residues 180 to 205) harbors high proline content and could be a homologue of the MLV PRR. Figure 1 Homologous modular domains in HTLV and MLV envelopes. Friend-MLV (F-MLV) Env and HTLV-1 Env are schematically represented as open and solid boxes, respectively. Boxes represent, from left to right, the signal peptide which comprises the first 34 and 20 amino acid residues of F-MLV and HTLV Env, respectively, the extracellular surface component (SU) and the transmembrane component (TM) including the carboxy terminal R peptide in F-MLV, which is cleaved in the mature Env glycoprotein [64, 65]. Env landmark positions are indicated and the MLV proline-rich regions (PRR) and the HTLV SU PRR homologue (PRRH) are delineated by vertical lines within the SU at the positions indicated by solid arrowheads. The PRR and PRRH start at the first proline (P) residue downstream of the conserved GXDP motif. Env sequences represented in the figure are obtained from F-MLV strain 57 (accession number CAA26561); P-MLV, F-MCF polytropic MLV (AAA46483); X-MLV, NZB xenotropic MLV (AAA46531); A-MLV, amphotropic MLV strain 4070A (AAA46515); HTLV-2 (NP_041006); and HTLV-1, MT2 strain (VCLJMT). Residue numbering starts from the first methionine of the Env signal peptides. Proline residues and homologous motifs are noted in bold. Amino acid sequence alignments were performed using the Clustal program in the Megalign alignment software package (DNAStar) with manual adjustments. Several studies using synthetic peptides and neutralizing antibodies against the HTLV Env have shown that determinants within this proline rich region homologue (PRRH) are involved in interference to Env-mediated syncytium formation [ 19 - 21 ]. The PRRH had been thought to encode the receptor-binding domain, as based on cell-to-cell fusion assays [ 19 , 22 - 24 ]. However, although PRRH synthetic peptides can block HTLV Env-mediated syncytia formation, they have no effect on HTLV SU binding [ 25 ] and infection [ 26 ]. Indeed, we and others have shown that Env receptor binding per se , as well as interference to receptor-binding, cell-to-cell fusion, syncytium formation, and infection involve several distinct cell surface-associated parameters [ 27 - 29 ]. In the present report, we produced soluble forms of wild-type and mutant HTLV-1 and 2 SU amino terminal subdomains and tested their receptor-binding abilities. We also tested their ability to specifically interfere with HTLV Env cell surface binding, Env-mediated cell-to-cell fusion, and retroviral infection. By testing these essential parameters of Env-mediated dissemination, we delineated the Env receptor-binding domain (RBD) to the first 160 residues of the mature HTLV-1 and -2 SU, excluding the PRRH, and we identified a conserved tyrosine residue at position 114 of HTLV-1 Env as a critical determinant for HTLV Env receptor binding. Results Motif conservation and similar modular organization of HTLV and MLV SU, and identification of a proline-rich region homologue (PRRH) in the HTLV SU As shown in Figure 1 , our alignment of the MLV and HTLV SU reveals several notable motif conservations outlining a similar modular organization of the MLV SU and HTLV SU. A (K/R)LL(T/N)LVQ motif, highly conserved between the F-MLV and HTLV-1 SU, is located immediately downstream of the PRR and its PRRH counterpart, respectively. Another highly conserved motif between MLV and HTLV, GXDP, is found immediately upstream of the PRR/PRRH (Figure 1 ). These two motifs compelled us to notice the PRRH, between the PSQ and KLLTLVQ sequences in HTLV-1, and between the PTQ and KILKFIQ sequences in HTLV-2 (Figure 1 ). As counted from the first and last proline in the delineated sequence, the PRRH has a proline content of 30.8% and 30.4% for HTLV-1 and -2, respectively. This is slightly lower than the 35.3%, 36%, 36%, and 35.6% proline content for the ecotropic, polytropic, xenotropic, and amphotropic MLV Env, respectively (Figure 1 ). The presence of a PRRH in the HTLV SU appeared to be characteristic of their MLV-like modular organization, since HTLV SU average proline content outside of the PRRH does not exceed 11%. Functional, soluble HTLV Env-receptor binding determinants MLV SU receptor binding determinants are all located upstream of the PRR [ 11 , 30 ]. To test whether the HTLV Env receptor binding determinants are also located upstream of the potential PRRH, we constructed a chimeric Env and several soluble HTLV-1 and -2 SU amino terminal subdomains. The chimeric HTLV/MLV Env, H1 183 FEnv, comprises the 183 amino terminal residues of the HTLV-1 SU ending with the PSQL residues fused to the PIGP sequence of the F-MLV PRR (Figure 2A ). In this Env chimera the receptor-binding domain (first 269 residues) of the F-MLV Env was replaced with the potentially corresponding domain of the HTLV-1 Env SU (Figure 2A ). The chimeric H1 183 FEnv construct – which lacks the HTLV PRRH but has the MLV PRR – was properly expressed in transfected cells and was revealed on immunoblots with an anti-MLV SU polyclonal antibody (Figure 3A ). Accordingly, an anti-HTLV-1 monoclonal antibody raised against a PRRH epitope did not bind this chimeric Env (data not shown). Figure 2 Schematic representation of HTLV/MLV Env chimeras and HTLV SU amino terminal subdomains. Env landmark positions are indicated and SU landmark sequences and positions are indicated by arrowheads. Open arrowheads indicate the position of construct borders. (A) HTLV/MLV Env chimeras. The H1 215 FEnv and H1 183 FEnv HTLV/MLV Env chimeras were obtained by replacing the 329 and 269 amino terminal residues of the F-MLV Env (open boxes) with the amino terminal 215 and 183 amino acid residues of the HTLV-1 Env (solid boxes), respectively. The H1 215 FEnv chimera, previously described and formerly designated HHproFc [9], has been renamed here for sake of nomenclature homogeneity. (B) Soluble HTLV-1 (H1) and HTLV-2 (H2) SU amino terminal subdomains, H1 215 SU, H2 211 SU, H1 179 SU, and H2 178 SU were constructed as fusion proteins with a carboxy terminal hemagglutinin (HA) or rabbit immunoglobulin Fc (rFc) tag. All amino acid residue numbering starts from the first methionine of the HTLV-1 or -2 Env signal peptide, the amino terminal 20 and 21 aa residues, respectively. Figure 3 Intracellular expression of HTLV-1 Env chimeras and soluble SU subdomains. Cell extracts (A, B) or culture supernatants (C) were prepared from 293T cells transfected with either full length Env (A) or soluble SU subdomains (B, C) expression vectors as depicted in figure 2. Membranes were probed with either (A) an anti-MLV SU antiserum to detect F-MLV and H1 183 FEnv uncleaved Env precursor proteins (F-MLV Prgp85 and H1 183 Fenv Pr, respectively) indicated by arrowheads, and cleaved SU (F-MLV SUgp70 and H1 183 FEnv SU, respectively) indicated by circles, or (B, C) an anti-rabbit IgG antiserum to detect carboxy terminal rFc-tagged soluble subdomains, including the Ampho-MLV SU subdomain (A 397 SU). HTLV-1 and -2 SU amino terminal subdomains with or without their respective PRRH were constructed as fusion proteins with either an influenza hemagglutinin (HA) or rabbit immunoglobulin Fc (rFc) carboxy terminal tag (Figure 2B ). The H1 215 SU and H2 211 SU subdomains comprise the first 215 and 211 residues, counting from the first methionine in the signal peptide through the KLLTLVQ of HTLV-1 and KILKFIQ of HTLV-2 Env, respectively (Figure 2B ). The H1 179 SU and H2 178 SU, comprising the amino terminal 179 and 178 amino acids of the HTLV-1 and -2 Env, respectively, exclude the PRRH sequence (Figure 2B ). Cell lysates and cell culture supernatants were analyzed to evaluate intracellular expression and secretion of functional SU amino terminal domains in transfected-cell cultures, respectively. H1 215 SU and H2 211 SU, containing the PRRH sequence, and H2 178 SU lacking this PRRH were all efficiently expressed in transfected cells (Figure 3B ). It is noteworthy, however, that recovery of tagged H1 179 SU molecules was largely inefficient because the vast majority of this protein was cleaved (data not shown). In contrast, no significant cleavage was observed with the other soluble domains released in the medium (not shown) (Figure 3C ). As expected for immunoadhesins, H1 215 SU, H2 211 SU, and H2 178 SU rFc-tagged domains were detected as dimers under non-reducing conditions (not shown). Immunoblots of cell extracts revealed two forms of intracellular H1 215 SU and H2 211 SU (Figure 3B ); this was likely due to variable glycosylation of these subdomains. However, a single secreted, soluble form of each of these amino terminal subdomains was detected in cell culture supernatants (Figure 3C ). A truncated Ampho-MLV SU-rFc fusion protein that comprises the amino terminal 397 residues of the Ampho-MLV Env fused to a carboxy terminal rFc tag was constructed (A 397 SU) and used as a heterologous control. A single form of this truncated SU was efficiently expressed in transfected cells (Figure 3B ), and abundantly secreted in cell culture medium (Figure 3C ). HTLV-1 and -2 SU subdomains with HTLV receptor binding properties The amino terminal subdomains were tested for their ability to bind to HTLV receptor-presenting cells by flow cytometry. Using this cell surface binding assay, all of the soluble HTLV SU subdomains bound to the A23 hamster fibroblast cell line (Figure 4 ) as well as to all other cell lines tested, including 293T (human kidney fibroblasts), NIH3T3 and NIH3T3TK - (murine fibroblasts) [ 29 ], HeLa (human ovarian carcinoma cells), D17 (canine fibroblast), Jurkat (suspension human T cell line), activated primary human T cells, and numerous other cell lines and primary cell types that are thought to express the HTLV receptor. As expected from our previous work [ 31 ], none of these soluble HTLV SU subdomains showed detectable binding on resting T lymphocytes. Notably, binding of the HTLV SU to these cells occurred whether they formed or not syncytia in the presence of HTLV Env [ 29 ] and data not shown). Binding by H2 178 SU was similar to H2 211 SU, demonstrating that the first 158 residues of the mature HTLV-2 SU, without the 20 amino acids of the amino terminal signal peptide, are sufficient for cell surface binding, and therefore that the PRRH is not required for receptor binding (Figure 4A ). Figure 4 HTLV-1 and -2 SU subdomains interfere with HTLV Env SU cell surface binding. (A) Conditioned medium from control 293T cells (open histograms) or from 293T cells expressing soluble rFc-tagged HTLV-1 H1 215 SU, HTLV-2 H2 211 SU and H2 178 SU, or Ampho-MLV A 397 SU subdomains (filled histograms), were incubated with A23 hamster cells for 30' at 37°C and binding was assessed by flow cytometry following addition of a secondary FITC-conjugated anti rabbit IgG antibody. Similar results were obtained in binding assays performed using all cell lines described in the text. (B) To assess binding interference, target 293T cells were transfected with the indicated Env construct and subsequently incubated with the HA-tagged H2 178 SU domain (filled histograms). Binding was detected by FACS following incubation with an anti HA 12CA5 mouse mAb and a FITC-conjugated anti mouse IgG antibody. Open histograms represent background levels of fluorescence. SU constructs are schematically represented below each graph by solid (HTLV), open (F-MLV) or grey (Ampho-MLV) boxes. To determine whether cell surface binding of these soluble SU domains corresponded to bona fide binding to the HTLV receptor, we performed an Env-specific binding interference assay. In this assay, transfection of the above described chimeric Env and SU subdomains into 293T cells resulted in interference to cell surface binding by the soluble HA-tagged H2 178 SU subdomain (Figure 4B ). Indeed, nearly complete interference was observed when cells were transfected with the amino terminal subdomain constructs, in the presence and absence of PRRH sequences (H1 215 SU and H2 211 SU versus H1 183 FEnv and H2 178 SU) (Figure 4B ). This effect was specific as HTLV SU binding was not inhibited by a heterologous A 397 SU domain (Figure 4B ). Therefore, we showed that the first 163 and 158 residues, with a cleaved signal peptide, of the mature HTLV-1 and HTLV-2 SU, respectively, contained the entire HTLV Env RBD. These data also showed that HTLV-1 and 2 cross-interfered, consistent with the fact that they recognize the same cell surface receptor for infection [ 8 , 32 ]. Interference to HTLV Env-mediated cell-to-cell fusion by HTLV SU amino terminal subdomains Viral envelope interference occurs when cell surface receptors are occupied by receptor-interacting Env components [ 33 - 35 ]. Since interference to the different Env-mediated functions involves distinct components [ 27 - 29 ], we also tested the abilities of the H1 183 FEnv and the HTLV SU amino terminal subdomains to interfere with HTLV Env-mediated cell fusion. Interference to cell fusion was measured using a quantitative HTLV envelope cell fusion interference assay (CFIA), as previously described [ 9 ]. HTLV-1 Env-induced cell fusion was significantly diminished upon expression of the H1 215 SU subdomain in target cells, 12% ± 2% of control fusion ( P < 0.001), consistent with previous observations using the H1 215 FEnv chimera [ 9 ]. Significant interference to cell fusion was also observed with the H1 183 FEnv chimera, which lacked a PRRH, down to 26% ± 4% of control fusion ( P < 0.001) (Figure 5 ). The corresponding HTLV-2 SU subdomains produced a nearly identical cell fusion interference profile: interference by the H2 211 SU isolated domain, in which the PRRH was maintained, resulted in 15% ± 3% of control cell fusion levels, while the H2 178 SU subdomain, lacking the HTLV PRRH, inhibited HTLV-1 Env-induced cell fusion to 24% ± 6% of control levels ( P < 0.001) (Figure 5 ). It is noteworthy that similar data were obtained when comparing cell fusion interference by H1 215 FEnv and H1 183 FEnv. These effects were specific to HTLV SU amino terminal domains as A 397 SU did not interfere with HTLV-1 Env-mediated cell fusion (83% ± 11% of control fusion) (Figure 5 ). Furthermore, no interference was observed when these truncated HTLV SU fragments and chimeric Env were tested against heterologous, fusogenic control Env such as AΔR Env, FΔR, XenoΔR and VSVG (data not shown). Altogether, these results confirmed our findings that receptor-binding determinants are present within the first 183 and 178 amino acids of the HTLV-1 and -2 Env, respectively. They also indicated that the PRRH (H1 215 SU and H2 211 SU), although unnecessary for receptor binding, modulates the efficiency of interference to HTLV Env-induced cell-to-cell fusion ( P < 0.03). Figure 5 HTLV-1 and -2 SU subdomains interfere with HTLV Env-mediated cell fusion. Cell-to-cell fusion assays were performed by cocultivating fusogenic HTLV-1 Env-expressing cells with target cells expressing the Env derivatives indicated and schematically represented below each histogram. HTLV-1 Env-mediated cell fusion in the presence of target cells transfected with empty vector (Mock) yielded 200 to 1000 blue foci in 4 independent experiments and these levels were defined as 100% cell fusion. Cell fusion levels in the presence of HLTV SU mutants or the A 397 SU control Ampho-MLV SU subdomain is shown as percent of control. Mean fusion percentages were determined from three to four independent experiments. Error bars represent the standard error of the mean. Interference to HTLV Env-mediated infection by HTLV SU amino terminal subdomains Interference, as described above, was based on the inhibition of cell-to-cell fusion induced by fusogenic Env expressed in the absence of other viral proteins. We further evaluated the abilities of the Env chimeras and soluble subdomains to specifically interfere with HTLV Env-mediated infection. HTLV Env-pseudotyped MLV virions, MLV(HTLV), were produced to infect 293T target cells. Because these recombinant cell-free virions are not competent for replication, this viral pseudotype infection assay tests a single round of infection, and does not measure replication and subsequent exponential viral dissemination. Therefore, relative infection values are expressed in linear rather than logarithmic scales. Infection of mock-transfected target cells, devoid of interfering Env domains, resulted in a mean infection value of 9905 ± 1117 infectious units per ml (iu/ml), and this was taken as 100% control infection (Figure 6 ). Similar values, 8803 ± 1871 iu/ml or 89% ± 19% of control infection, were obtained upon infection of target cells expressing a heterologous SU subdomain, A 397 SU (Figure 6 ). Expression of the H1 183 FEnv and H1 215 FEnv chimeric Env in target cells significantly reduced MLV(HTLV) infection to 324 ± 98 iu/ml, 3.3% ± 1% of control infection, and to 307 ± 129 iu/ml, 3.1% ± 1.3% of control infection, respectively (Figure 6 and data not shown). Similarly, the H2 178 SU and H2 211 SU subdomains diminished MLV(HTLV) infection to 191 ± 56 iu/ml and 215 ± 122 iu/ml, 1.9% ± 0.6% and 2.2% ± 1.3% of control infection, respectively (Figure 6 ). The specificity of interference to infection by HTLV Env constructs was assessed by their lack of interference abilities toward Ampho-MLV Env-pseudotyped virions, MLV(Ampho) (data not shown). Thus, for both HTLV-1 and -2, the amino terminal domain upstream of the PRRH was sufficient for specific interference to HTLV Env-mediated infection. Furthermore, in contrast to the cell fusion interference assays described above, the PRRH did not detectably influence MLV(HTLV) infection. Figure 6 HTLV-1 and -2 SU subdomains interfere with infection by HTLV envelope-pseudotyped virions. 293T cells (5 × 10 5 ) expressing the indicated interfering Env derivatives were infected with cell-free HTLV-2 Env-pseudotyped virions MLV(HTLV) carrying a LacZ reporter gene. Infected cells were detected 2 days later by X-gal staining. Infection values are represented as percent of control infection, i.e., relative to infection of mock (pCDNA3.1) transfected target cells, calculated as infectious units per ml of virus containing supernatant (i.u./ml). Data are representative of at least three independent experiments performed in duplicate. Error bars represent the standard error of the mean. Because HTLV dissemination appears to occur mostly via cell-to-cell contact, we also tested envelope interference to infection by HTLV-1 SU amino terminal domains using a cell-to-cell transmission interference assay. In this assay, cells harboring interfering chimeric Env and soluble subdomains were cocultured with cells producing MLV(HTLV) virions. Transfection of either chimeric Env or soluble subdomains into HeLa target cells decreased MLV(HTLV) infection to levels similar to those observed in the cell fusion interference assay presented in figure 5 (data not shown). Identification of residues within the HTLV SU amino terminal domain that modulate receptor binding and HTLV Env-mediated interference Two key residues contained in the HTLV SU RBD and conserved between HTLV-1 and -2, arginine 94 (Arg 94 ) and serine 101 (Ser 101 ) for HTLV-1 Env which correspond to Arg 90 and Ser 97 in HTLV-2 Env, have been shown to alter cell-to-cell fusion and infection when mutated [ 36 , 37 ]. To determine whether mutations of these residues had an effect on receptor binding, we generated H1 215 SU subdomains with either Arg 94 or Ser 101 mutated to Ala, yielding the mutant H1(R94A)SU and H1(S101A)SU subdomains, respectively. We also evaluated mutations of Asp 106 , mutant H1(D106A)SU, and Tyr 114 , mutant H1(Y114A)SU, both residues found to be highly conserved between all human and simian T cell leukemia viruses (unpublished observations). Surprisingly, cell surface binding profiles of H1(R94A)SU and H1(S101A)SU mutants were not significantly altered when compared to binding by the parental H1 215 SU, whereas the H1(D106A)SU mutant presented reduced binding to HTLV receptor-bearing cells and the H1(Y114A)SU mutant showed a nearly complete abrogation of cell surface binding (Figure 7A ). Loss of binding observed with the two latter mutants was not due to decreased soluble SU fragment production, as assessed by immunoblotting of transfected-cell culture media (Figure 7A ). Moreover, equivalent binding profiles were obtained when the same mutations were introduced into the HTLV-2 soluble RBD H2 178 SU (data not shown). Altogether, these experiments demonstrated that Tyr 114 , and to a lesser extent Asp 106 , are key residues involved in HTLV Env receptor binding. Figure 7 HTLV-1 SU amino terminal domain mutants. (A) H1 215 SU constructs were generated with the following SU amino terminal point mutations; R94A, S101A, D106A and Y114A. The abilities of these soluble H1 215 SU constructs to bind 293T cells were assessed by flow cytometry (gray histograms). The levels of expression of the various soluble SU subdomains are shown under each histogram. The abilities of the H1 215 SU mutants to interfere with (B) HTLV Env-induced cell fusion and (C) MLV(HTLV) pseudotype infection was assayed as described in Figs. 5 and 6. Data are representative of at least three independent experiments performed in duplicate. Error bars represent the standard error of the mean. We next tested the abilities of these mutants to interfere with HTLV Env-mediated cell fusion and infection, using the assays described above. As mentioned above, all wild-type and mutant HTLV SU subdomains were produced and secreted with a similar efficiency (Figure 7A ). Expression of the H1(D106A)SU and H1(Y114A)SU mutants, with decreased capacities to bind the HTLV receptor, correlated with decreased interference to HTLV Env-mediated cell fusion and infection. Indeed, H1(Y114A)SU, which had nearly undetectable level of binding, showed the lowest levels of interference and thus allowed the highest levels of HTLV Env-mediated cell fusion and infection (56% ± 16% and 46% ± 10%, respectively) (Figure 7 ). Nevertheless, levels of fusion and infection were lower than that observed when the heterologous A 397 SU was used as a negative control of interference (83% ± 11% and 89% ± 19% for cell fusion and infection, respectively). Thus, overexpression of mutant HTLV SU fragments with highly decreased receptor binding abilities can still exert, albeit to a significantly lesser extent, interference to HTLV Env-mediated cell fusion and infection. We found that similar levels of interference to HTLV Env-mediated cell fusion and infection were observed when either the parental H1 215 SU or the mutant H1(S101A)SU were expressed in target cells (Figure 7B and 7C ). This is consistent with the capacity of this mutant to bind target cells at levels similar to that of wild type H1 215 SU. However, interference to HTLV Env-mediated cell fusion and infection did not always correlate with cell surface binding profiles. While the H1(R94A)SU mutant inhibited cell fusion and infection, its effects were significantly lower than those of the wild-type H1 215 SU (56% ± 8% and 32% ± 2.3%, respectively) (Figure 7B,7C ). Thus, although neither Arg 94 nor Ser 101 of the HTLV-1 SU appears to play a direct role in binding, Arg 94 modulates HTLV Env-mediated fusion and infection (Figure 7 ), likely via post-binding effects rather than binding per se . In conclusion, Tyr114 appeared as the main determinant identified so far for HTLV Env binding, whereas the effects previously described with Arg 94 and Ser 101 are most likely associated with post-binding events. Discussion Here, we report the generation of MLV Env with chimeric HTLV/MLV SU and truncated HTLV-1 and -2 amino terminal SU subdomains that can be expressed in and secreted from eukaryotic cell lines in functional, soluble form. Using these constructs, we demonstrated that the amino terminal 163 and 158 residues (i.e., expunged of their Env signal peptide) of the mature HTLV-1 and -2 Env SU, respectively, were sufficient to exert both HTLV receptor binding and efficient interference to diverse HTLV Env-mediated functions, including binding, cell-to-cell fusion and cell-free as well as cell-to-cell infection. Although the PRRH sequence comprising amino acid residues 180 to 215 of the HTLV-1 Env and 176 to 211 of the HTLV-2 Env was previously thought to be a receptor binding site, our data preclude a major role for this region in the binding properties described above. Indeed, whereas a synthetic peptide composed of amino acids 197 to 216 and located within the HTLV-1 PRRH, has been reported to interfere with HTLV Env-induced syncytia formation [ 22 ], this peptide was later shown to compete neither with receptor binding of the entire HTLV-1 Env SU [ 38 ], nor with infection [ 26 ]. It is therefore likely that the effects reported for PRRH-derived peptides, as measured by syncytia formation, are solely due to post-receptor binding events. However, we identified Tyr 114 of the HTLV-1 Env, which corresponds to Tyr 110 of the HTLV-2 Env, as a key residue in HTLV Env binding and for all the aforementioned HTLV Env-mediated functional assays. We could not detect binding of H1(Y114A)SU by flow cytometry, while this mutant exerted residual, albeit significantly decreased, interference to HTLV Env-mediated cell fusion and infection. Altered folding outside of the binding domain per se , rather than direct alteration of the receptor-binding site, could also account for the lack of binding of this mutant. However, we favor the latter hypothesis, since the H1(Y114A)SU mutant was properly folded and transported to the plasma membrane and secreted in the medium as efficiently as wild type RBD, thus arguing against gross misfolding of this mutant. Accordingly, Tyr 114 appears to be conserved in all known human and simian T cell leukemia viruses strains, which share the same receptor. The receptor-binding site in MLV RBD is composed of a combination of several cysteine loops located upstream of the PRR [ 11 , 39 ] which is linked to a conserved anti-parallel β core [ 13 ]. The isolation of an F-MLV SU amino terminal subdomain allowed crystallization of MLV RBD and the modeling of the RBD cysteine loop arrangement [ 13 ]. The precise organization of cysteine loops, likely to harbor the receptor binding determinants, within the HTLV SU amino terminus remains to be established. Nevertheless, the identification of Tyr 114 as a key HTLV-1 RBD residue points at this determinant as a very likely receptor-binding core. This, together with previous works relying on syncytia formation and cell-to-cell transmission [ 36 , 37 ], will help to distinguish between bona fide receptor binding determinants and determinants involved at a post-binding level. Another recently identified determinant, the Pro-His-Gln SU motif conserved among gammaretroviruses such as MLV and feline leukemia viruses (FeLV), has been determined to play a major role in viral entry during post-binding events [ 40 ]. The mechanism of this effect involves a direct interaction of MLV SU soluble forms with Env attached SU carboxy terminus [ 41 - 46 ]. This interaction between the SU amino and carboxy termini leads to the T cell-restricted tropism of a natural isolate of FeLV, FeLV T, in which the SU Pro-His-Gln motif is mutated. Indeed, FeLV T is restricted in cat to T cells because they naturally express an endogenous soluble FeLV RBD-related factor called FeLIX that trans-complements the lack of the SU Pro-His-Gln motif in the FeLV T Env and restores its post-binding defect [ 47 ]. Despite the HTLV-1 and F-MLV SU homologous modular organization and the assignment of several common motifs between the two latter SU, no obvious Pro-His-Gln motif homologue is present in the HTLV SU amino terminus. Whether a FeLIX-like molecule that interacts with HTLV Env exists in human T cells remains to be addressed. Furthermore, the fact that the Pro-His-Gln has been shown to play a major role in transactivation of viral infection in several gammaretroviruses which are efficiently infectious as cell-free virions [ 42 , 44 , 48 ], raises the question whether the apparent lack of such a motif in the HTLV simple oncovirus-like SU is linked to the relative inefficiency of HTLV Env-mediated infection by cell-free virions. The HTLV SU subdomains described here should prove to be valuable in addressing such questions. The recent identification of Glut1, the ubiquitous glucose transporter of vertebrates [ 49 ], as a receptor for HTLV Env [ 8 ] adds an additional similarity between the Env of HTLV, a deltaretrovirus, and that of gammaretroviruses. All these virus Env recognize multimembrane-spanning metabolite transporters [ 50 , 51 ]. This and the common modular organization of the HTLV and MLV SU raise questions regarding the origin of the HTLV Env. It has previously been reported that envelopes of invertebrate retroviruses may have been "captured" from other viruses [ 52 - 54 ]. As HTLV and MLV have strongly divergent overall genomic organizations, "envelope capture" from related ancestor genes might account for the close relationship between the Env of these phylogenetically distant viruses [ 10 ]. Conclusions We have generated truncated domains of the HTLV Env amino terminus, upstream of residues 183 and 178 of the HTLV-1 and -2 Env, respectively, that were sufficient to bind target cells of different species through interaction with the HTLV Env receptor. We also identified a tyrosine at position 114 and 110 in HTLV-1 and -2 Env, respectively, as a key determinant for this binding. In addition to their use for further exploration of the mechanisms involved in HTLV entry, the tagged HTLV-1 and -2 RBD subdomains described here are novel tools for the detection of Glut1 cell surface expression and intracellular trafficking. Indeed, we tracked intracellular expression of EGFP-tagged HTLV SU subdomains by time-lapse microscopy, and found that they are preferentially routed toward cell-cell contact areas (unpublished observations), where Glut1 is particularly abundant [ 55 ] and our unpublished observations). Furthermore, those HTLV SU derivatives could be of particular importance in view of the key roles played by Glut1 in various biological processes, including T cell survival and activation [ 31 , 56 ], tumor genesis [ 57 , 58 ], and neuronal activity [ 59 ]. Interestingly, soluble HTLV SU subdomains inhibit Glut1-mediated glucose transport, and accordingly, expression of mutants with diminished receptor binding ability resulted in less pronounced inhibition [ 8 ] and data not shown). Thus, these HTLV SU derivatives could also be used as glucose transport inhibitors. These data demonstrate the potential for the novel and broad utility of these reagents in the study of HTLV infection as well as biological processes involving glucose transport and metabolism. Materials and methods Construction of chimeric Env and HTLV-1 and -2 SU subdomains To exchange the PRR and PRRH regions, we introduced an allelic Mfe I restriction site in the HTLV-1 and F-MLV Env. Introduction of this site in F-MLV resulted in the substitution of a glutamine and leucine (QL) dipeptide for the parental arginine and valine (RV) residues of the GPRVPIGP motif, at the start of the MLV Env PRR. Introduction of the MfeI site in the PSQL motif of the HTLV-1 SU maintained the parental QL residues, at the start of the HTLV Env PRRH. By exchanging domains at the Mfe I sites, we derived the H1 183 FEnv chimera containing the amino terminal 183 residues of the HTLV Env followed by the F-MLV PRR. In this chimera, the PSQL/PIGP hybrid sequence is generated at the exchange border, and the PRRH of HTLV is replaced by the F-MLV PRR (Figure 2A ). In contrast, the entire PRRH of HTLV-1 is present in the H1 215 FEnv chimera – this Env chimera has been previously described and designated HHproFc [ 9 ]. The H1 183 FEnv and H1 215 FEnv chimeras, as well as the parental HTLV-1 and F-MLV Env, were inserted in an allelic fashion into the previously described pCEL retroviral Env expression vector [ 60 ]. The HTLV-2 Env expression vector, pCSIX/H2, was constructed by inserting the HindIII – EcoRI fragment from pHTE-2 (a gift from M-C Dokhelar) encompassing the HTLV-2 env gene, the pX region and the 3' LTR into pCSI (CMV promoter, SV-40 intron) [ 61 ] at the HindIII and EcoRI restriction sites. The H1 215 SU, H2 211 SU, H1 179 SU, and H2 178 SU subdomains, corresponding to the HTLV-1 and -2 SU amino terminus with and without their respective PRRH, were generated by PCR and subcloned into the pCSI expression vector as fusion proteins harboring a carboxy terminal rFc or HA tag (Figure 2B ). The H1(R94A)SU, H1(S101A)SU, H1(D106A)SU, and H1(Y114A)SU substitution mutants were generated by oligonucleotide-directed PCR mutagenesis on the H1 215 SU vector and subcloned into the pCSI expression vector. All PCR-generated DNA fragments were sequenced using an ABI Prism 310 sequencer. Cloning details are available upon request. Protein expression and immunoblots Approximately 5 × 10 5 293T cells per 35 mm well were transfected with 5 μg of vectors using a calcium-phosphate-Hepes buffered saline (HBS) transfection protocol. Transfection medium was replaced with 3 ml of fresh culture medium twenty hours post-transfection. Forty-eight hours post-transfection cell culture medium (supernatant) was recovered and filtered through a 0.45 μm pore-size membrane to remove cell debris. Twenty μl were directly analyzed by SDS-PAGE (15% polyacrylamide gel), and the rest was aliquoted and stored at -20°C for later use in binding assays (see below). Cell extracts were collected 48 h post-transfection in 1 ml of cell lysis buffer (50 mM Tris-HCl [pH 8.0], 150 mM NaCl, 0.1% sodium dodecyl sulfate [SDS], 1% Nonidet P-40, 0.5% deoxycholate, and a cocktail of mammalian protease inhibitors [Sigma]) and clarified by two successive centrifugations at 13,000 rpm for 10 min at 4°C in a microcentrifuge. Approximately 20 μl of each extract, adjusted after normalization for protein concentration using the Bradford assay (Sigma), were subjected to electrophoresis on SDS-15% acrylamide gels, followed by transfer onto nitrocellulose (Protran; Schleicher & Schuell). Membranes were blocked in phosphate-buffered saline (PBS) containing 5% powdered milk and 0.5% Tween 20, probed with a 1:1000 dilution of a goat anti-RLV gp70 polyclonal antibody (Viromed) followed by a horseradish peroxidase-conjugated anti-goat immunoglobulin (for detection of chimeric Env), or goat anti-rabbit-IgG-horseradish peroxidase-conjugated immunoglobulins (for detection of rFc-tagged SU subdomains). Immunoblots were subsequently washed three times with PBS-0.1% Tween 20 and revealed by chemiluminescence (ECL+, Amersham). Binding and binding interference assays Binding assays were performed as previously described [ 31 ]. Briefly, 5 × 10 5 target cells were detached with a PBS-EDTA solution, collected by centrifugation, incubated for 30' at 37°C with 300 μl of rabbit Fc-tagged soluble HTLV-1, HTLV-2, or Ampho-MLV truncated SU, washed, labeled with an anti-rabbit-IgG FITC-conjugated antibody, and analyzed on a FACSCalibur (Becton Dickinson). Data analysis was performed using the CellQuest software (Becton Dickinson). For interference studies, 293T cells were transfected with 4 μg of Env or Env SU subdomain expression vectors (carboxy terminal rFc-tagged forms) using the calcium-phosphate-HBS method. Under these conditions, transfection efficiencies ranged from approximately 80 to 90% of the target cells. Twenty-four and 48 hours post-transfection, cells were collected and transfected 293T cells expressing the different interfering HTLV or Ampho-MLV domains were incubated with a challenging HA-tagged soluble HTLV-2 SU amino terminal subdomain (H2 178 SU-HA). Cells were stained using a primary 12CA5 anti HA antibody followed by an anti-mouse-IgG FITC-conjugated antibody before detection by flow cytometry. Envelope interference to cell fusion assay Briefly, the HTLV/MLV Env chimera, H1 183 FEnv, was used to interfere with challenging HTLV Env. The interfering non-fusogenic H1 183 FEnv and truncated HTLV SU subdomains were transiently transfected into HeLaCD4LTRLacZ, a cell line highly susceptible to HTLV Env-induced fusion that contains a stably integrated Tat-dependent LacZ expression vector [ 62 ]. These transfectants were cocultured with Tat-expressing NIH3T3(TK-) cells (NIH3T3(TK-)Tat) that were transiently transfected with the challenging HTLV Env. The NIH3T3(TK-)Tat cell line is resistant to HTLV-Env-induced syncytia formation, despite its ability to express the HTLV receptor and to bind HTLV Env, and thus can be used to precisely monitor fusion of the HeLaCD4LTRLacZ target cells [ 9 , 29 ]. H1 183 FEnv Env and truncated HTLV SU subdomains plasmid DNA (2 to 3 μg) was transfected into HeLaCD4LTRLacZ cells, while challenging, fusogenic HTLV-1 Env plasmid (1 μg) was transfected into NIH3T3(TK-)Tat. The interfering Env or SU subdomain-presenting cells were detached 24 hours post-transfection and 1–2 × 10 5 cells were cocultured for 24 hours with 1–2 × 10 5 challenging HTLV-1 Env-presenting NIH3T3(TK-)Tat cells. Subsequently, the cocultured cells were fixed and stained for β-galactosidase expression as described previously [ 60 ]. Transfection efficiencies of the HeLaCD4LTRLacZ target cells were approximately 50%. Mock transfections were performed with similar amounts of control plasmid DNAs. Env interference was measured by the decreased number of blue foci and was expressed as percent blue foci of control fusion (mock-transfected target cells). Data are represented as mean interference (± standard deviation), and statistical significance of interference levels was determined using a pairwise Student's t test. Envelope interference to infection assay MLV(Ampho) and MLV(HTLV) pseudotyped virions were produced after transfection of 10 6 293T cells with 5 μg pCSI/Ampho or pCSIX/H2, respectively, 5 μg pCL/Gag-Pol [ 29 ] and 10 μg of pCLMFG-LacZ [ 63 ], using a calcium-phosphate-HBS transfection protocol. Supernatants were recovered 48 hours post transfection and filtered through 0.45 μm pore-size membrane to remove cell debris, and stored at -80°C. The pCLMFG-LacZ plasmid is a retroviral expression vector that provides a packageable RNA coding for the LacZ gene marker. pCSI/Ampho is an expression vector encoding the Ampho-MLV Env, and the HTLV-2 Env expression vector, pCSIX/H2, is described above. Virion-containing supernatants were used to infect target 293T cells expressing the chimeric Env or HTLV RBD subdomains. Transfection efficiencies of target 293T cells were >80% in all experiments. Infections were performed 36–48 hours post-transfection on cultures grown in 12 well plates (Costar) at 37°C, medium was changed 24 hours later, and confluent cell monolayers were fixed, stained for β-galactosidase activity before counting blue foci. Interference to infection was determined by infecting transfected target cells with approximately 100 and 1000 iu. Infection was evaluated as described above, and the number of LacZ-positive blue colonies counted was normalized by multiplying by the appropriate dilution factor. The resulting infection values were analyzed as iu/ml of virus containing supernatant. Subsequently the relative infection levels in cells expressing the HTLV SU domains were compared to those of mock transfected cells and were expressed as percentages of control infection (% control). List of abbreviations used HTLV Human T-cell leukemia virus SU envelope extracellular surface component Env envelope glycoprotein MLV murine leukemia virus F-MLV Friend-MLV RBD receptor-binding domain PRR proline-rich region PRRH proline rich region homologue Ampho amphotropic HA influenza hemagglutinin rFc rabbit immunoglobulin constant fragment A 397 SU Ampho-MLV Env fused to a carboxy terminal rFc tag CFIA cell fusion interference assay iu/ml infectious units per ml Arg 94 arginine 94 Ser 101 serine 101 Tyr 114 tyrosine 114 FeLV feline leukemia viruses HBS Hepes buffered saline PBS phosphate-buffered saline SDS sodium dodecyl sulfate Competing interests The authors declare that they have no competing interests. Authors' contributions FJK designed and realized or supervised most of the experiments and co-wrote the manuscript. NM participated to some molecular constructions, set up, realized and analyzed most binding assays and FACS analyses and participated to the redaction of the manuscript. ENG set up and performed the cell-to-cell transmission assay and performed the corresponding experiments, CV constructed some of the RBD point mutants and tested them, MS initiated the project, co-participated in the design of the study, co-coordinated its realization and co-wrote the manuscript, and JLB realized some of the molecular constructs, performed some of the experiments, co-participated in the design of the study, co-coordinated its realization and co-wrote the manuscript. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539286.xml
539293	Metabolic scaling: consensus or controversy?	Background The relationship between body mass (M) and standard metabolic rate (B) among living organisms remains controversial, though it is widely accepted that in many cases B is approximately proportional to the three-quarters power of M. Results The biological significance of the straight-line plots obtained over wide ranges of species when B is plotted against log M remains a matter of debate. In this article we review the values ascribed to the gradients of such graphs (typically 0.75, according to the majority view), and we assess various attempts to explain the allometric power-law phenomenon, placing emphasis on the most recent publications. Conclusion Although many of the models that have been advanced have significant attractions, none can be accepted without serious reservations, and the possibility that no one model can fit all cases has to be more seriously entertained.	Introduction: Kleiber and metabolic scaling In 1932, Kleiber published a paper in an obscure journal [ 1 ] showing that standard metabolic rates among mammals varied with the three-quarters power of body mass: the so-called "elephant to mouse curve", termed "Kleiber's law" in this review. Since that date, this and similar allometric scaling phenomena have been widely and often intensively investigated. These investigations have generated continuing debates. At least three broad issues remain contentious, each compounded on the one hand by the problem of obtaining valid data (in particular, finding procedures by which reliable and reproducible measures of standard metabolic rate can be obtained, especially in poikilotherms) and on the other by statistical considerations (in particular, the validity of fitting scattered points to a straight line on a semi-logarithmic plot). The first issue is disagreement as to whether any consistent relationship obtains between standard metabolic rate and body mass. Moreover, those who acknowledge such a relationship hold divergent opinions about its range of application. Is it valid only for limited numbers of taxa, or is it universal? Since the 1960s there has been a measure of consensus: a consistent allometric scaling relationship does exist, at least among homoiotherms. Nevertheless, not all biologists agree, and scepticism is widespread, particularly about the alleged universality of Kleiber's law. Second, assuming that some version of Kleiber's law (a consistent metabolic scaling relationship) applies to at least some taxa, there are disagreements about the gradient of the semi-log plot. That is, if B = aM b , where B = standard metabolic rate, M = body mass, and a and b are constants, what is the value of b ? Kleiber [ 1 ] and many subsequent investigators claimed that b = 0.75, and on this matter too a measure of consensus has obtained since the 1960s. Once again, however, not all biologists agree. A significant minority of investigators hold that b = 0.67; and other values have been suggested, at least for some organisms. Third, assuming a consistent scaling relationship and an agreed value of b , how is Kleiber's law to be interpreted mechanistically? What is its physical or biological basis? For those who claim that b = 0.67, this issue is simple: standard metabolic rate depends on the organism's surface to volume ratio. But for proponents of the majority view, that b = 0.75, the issue is not simple at all. Many interpretations have been proposed, and since several of these are of recent coinage and seem to be mutually incompatible, a critical comparative review seems timely. Kleiber's initial paper [ 1 ] found support within a decade. The allometric scaling relationship B = aM b (B = standard metabolic rate, M = body mass, a and b are constants and b is taken to be approximately 0.75), was inferred by other investigators during the 1930s [ 2 , 3 ]. Relevant data have been reviewed periodically since then (e.g. [ 4 - 15 ]) and recent developments have rekindled interest in the field. Many biological variables other than standard metabolic rate also reportedly fit quarter-power scalings (relationships of the kind V = kM b , where V is the variable in question, k is a constant and b = n/4; n = 3 for metabolic rate). Examples include lifespans, growth rates, densities of trees in forests, and numbers of species in ecosystems (see e.g. [ 9 ]). Some commentators infer that Kleiber's law is, or points to, a universal biological principle, which they have sought to uncover. Others doubt this, not least because it is unclear how (for example) tree densities can be consequences of metabolic scaling or can have the same mechanistic basis. This article focuses on the metabolic rate literature, mentioning other variables only in passing, because most debates in the field have arisen from metabolic rate measurements. Variations in the value of b Most debates about the value of b assume some version of Kleiber's law: i.e. that a single allometric scaling relationship fits metabolic rates over a wide range of organisms. However, as noted in the introduction, there are dissenters. Everyone acknowledges considerable variation both within and among taxa, no matter whether b = 0.75, 0.67, or some other number. The question is whether these variations are deviations from a general law, or whether there is no such law. Conflicting opinions on this fundamental point recall the traditional philosophical difference between physicists and biologists: the former are inclined to see abstract mathematical generalities in any set of numerical data, the latter to see concrete particulars. All recent attempts to explain Kleiber's law by "universal" models have involved physicists and mathematicians; the sceptics are predominantly biologists. Dodds et al. [ 16 ] re-examined published scaling data from Kleiber's original paper onwards and concluded that the consensus ( b = 0.75) was not statistically supported. Feldman [ 17 ] found no evidence for any wide-ranging allometric power law in biology and dismissed all attempts to explain scaling relationships by physical or mathematical principles. Atanasov and Dimitrov [ 18 ] found evidence that b ranges from around 0.67 to more than 0.9 over all major animal groups, the values perhaps reflecting complexity of organisation; single values such as 0.75 emerge only as averages over each group. Other investigators have been less sceptical; publications by Enquist and Niklas [ 19 , 20 ] give particularly impressive support to the generality of Kleiber's law because Niklas was previously among the doubters. Whatever one's position, it is indisputable that the Kleiber relationship has many exceptions, even among mammals. Bartels [ 21 ] showed that some mammals, such as shrews, have B values well above those expected from the Kleiber curve. Andersen [ 22 ] discussed the high B values for whales and seals and attributed them to the cold-water habitat. Nevertheless, Kleiber's law has been extended beyond placental mammals to birds and marsupials. Birds have generally higher a values than placental mammals and marsupials have lower ones, but the 0.75-power relationship is still inferred by many investigators (e.g. [ 4 ]). McNab [ 13 ] accepted Kleiber's law as a general approximation but emphasized species variations, which he attributed to differences in diet, habitat and physiological adaptation. Elgar and Harvey [ 23 ] also found variability among groups of species but reasoned that standard metabolic rates vary taxonomically rather than with temperature regulation, food intake or activity. Economos [ 24 ] was also critical of McNab, at least in respect of mammals. It is difficult to define "standard metabolic rate" in poikilotherms; ambient temperature, time since last meal and other variables markedly affect measurements [ 9 , 13 , 25 ]. A heterogeneous array of poikilotherm data [ 5 ] revealed an "average" b value of roughly 0.75. There were wide divergences in some taxa; notwithstanding these, Hemmingsen [ 4 , 5 ] argued that over all animals, plants and protists, metabolic rate scales as the 0.75-power of body mass. More recently published data [ 26 , 27 ] support this conclusion for a wide range of organisms and body masses. However, a careful re-evaluation of Hemmingsen's data by Prothero [ 28 ] cast further doubt on the applicability of Kleiber's law to unicellular organisms. Scepticism persists, mostly on the grounds of the intrinsic variability of the data, which is too often underestimated because it is disguised in the customary logarithmic plots and is seldom subjected to adequate statistical analysis [ 11 , 29 ]. However, this too has been debated; a suitable choice of procedures for estimating parameters might eliminate inconsistencies and discrepancies from the data, giving more credence to the belief that b = 0.75 over a wide range of taxa [ 30 ]. In the following section we shall examine some of the more divergent data in more detail. In short, there is a clear but by no means total consensus that (i) Kleiber's law is widely (even universally) applicable in biology, (ii) b is approximately 0.75. Variability in the data is generally admitted, so the consensus – and the claim that Kleiber's law manifests a general biological principle – can legitimately be doubted. The mass transfer model [ 31 ] Some of the doubts about the consensus are powerfully supported by studies on small aquatic organisms. Reviewing a large literature on metabolic rates in aquatic invertebrates and algae, Patterson [ 31 ] deployed chemical engineering principles to explain why the b values ranged from about 0.3 to 1.2 in these taxa (his Table 1 provides an excellent summary). Assuming that the delivery of nutrients to each organism entails diffusion through a boundary layer, Patterson showed how water movements and organism size might affect such delivery and hence determine metabolic rate. Using simple geometrical models of organisms (plates, cylinders and spheres), he derived b values ranging from 0.31 to 1.25, more or less consistent with the experimental values. Patterson plotted two dimensionless numbers against each other, viz . Sherwood number, Sh = h m W/D, where h m = mass transfer coefficient, W = characteristic dimension of organism and D = diffusivity; and Reynolds number (a function of organism size), Re = ρUW/μ, where ρ = density, U = water flow speed and μ = coefficient of viscosity. The graphs, which had the form Sh = c.Re d , where d = 0.5 for ideal laminar flow and 0.8 for turbulent flow (c is a constant of proportionality), revealed the relative importance of diffusion and mass transfer (convective movement) in the supply of materials. Patterson was able to derive an expression for h m , and was thus able to relate the supply of materials to body mass. The two main attractions of this model are (1) good agreement with a wide range of data and (2) derivation from basic physical principles without ad hoc biological or other assumptions. Patterson's approach has implicit support in the literature: Coulson [ 32 ] used chemical engineering principles to argue that mammalian metabolic rates are supply-limited, but he did not develop the argument in mathematical detail. However, Patterson's model has drawbacks. First, it is hard to see how his reasoning can be generalised to other taxa, notwithstanding Coulson's proposal (discussed in a later section). Second, by focusing on diffusion and convective mass transfer, he ignored active processes in the uptake of materials, which are likely to dominate in many organisms. Third, he assumed that metabolism in general is supply-limited; in homoiotherms at least, it is more nearly demand-limited under resting conditions, though even this is an oversimplification. The Patterson model has not been given much attention by other investigators in the field and perhaps it deserves more consideration. Despite its inherent limitations (it is exclusively concerned with small aquatic eukaryotes) it is a potentially fruitful contribution to biophysics. Scaling of metabolic rate with surface-to-mass ratio Several workers accept the reality of allometric scaling but question the value b = 0.75, which a consensus of physiologists has accepted since the 1960s. Many of these sceptics claim that the "true" value of b is 0.66 or 0.67 because the principal determinant of metabolic scaling is the surface-to-volume ratio of the organism; hence, assuming constant body density, the surface-to-mass ratio. The first study to suggest this explanation for the mass dependence of B is attributed to Rubner [ 33 ], who studied metabolic rates in various breeds of dog. Heusner [ 34 ] reported that b is approximately 0.67 for any single mammalian species and suggested that the interspecies value of 0.75 is a statistical artefact. Feldman and McMahon [ 35 ] disagreed, but Heusner sustained his position in subsequent articles. For instance, reviewing a substantial body of published data [ 36 ], he argued that metabolic rate data for small and large mammals lie on parallel regression lines, each with a gradient of approximately 0.67 but with different intercepts (i.e. values of a , termed the "specific mass coefficients"). Hayssen and Lacy [ 37 ] found b = 0.65 for small mammals and b = 0.86 for large ones, again suggesting that b = 0.75 is a cross-species "average" with no biological significance; but it is questionable whether their data were measurements of standard metabolic rate in all cases. McNab [ 13 ] reported lower values: 0.60 and 0.75, respectively. Heusner [ 36 ] reasoned that if a few large mammals are added to a sample of predominantly small ones, a single regression line for all the data might have a gradient around 0.75. This, however, is misleading, as the following paragraphs will argue. According to Heusner, the ratio B/M 0.67 is a mass-independent measure of standard metabolism. Variations indicate the effects of factors other than body mass. Other workers broadly share Heusner's opinion (see e.g. [ 12 ] for review and [ 38 ] for a good recent exemplar). Bartels [ 21 ] found a value of 0.66 for mammals; Bennett and Harvey [ 39 ] reported 0.67 for birds. Of course, if B varies as M 0.67 , the interesting problem is not the index ( b ) in the Kleiber equation but the allegedly constant relationship between specific mass coefficient ( a ) and body size. This point was developed by Wieser [ 40 ], who distinguished the ontogeny of metabolism, which comprises several phases but follows the surface rule (M 0.67 ) overall, from the phylogeny of metabolism, which concerns the mass coefficients ( a ). Following Heusner's argument, Wieser [ 40 ] wrote the allometric power law in the form B = a n M 0.66 and deduced that the specific mass coefficient a n = aM 0.09 . Here, a is an interspecific mass coefficient (3.34 w in mammals if M is in kg). Another difficulty with this type of explanation lies in the calculation of body surface area; the Meeh coefficient, k, where surface area = kM 0.67 , is difficult to measure unequivocally but is generally taken as ~10 (see [ 3 ]). Yet another possible difficulty was identified by Butler et al. [ 41 ], who questioned Heusner's dimensional analysis argument and concluded that no version of Kleiber's law (i.e. no value of b that is constant over a range of species) could be substantiated by his approach. The claim that b = 0.67 remains a minority view. Those who accept it are faced with the twin difficulties of (i) establishing that their estimates of surface area are correct and (ii) explaining why, in Wieser's notation, a n = aM 0.09 . Moreover, even if such arguments as Heusner's are valid for homoiotherms, it is hard to justify their extrapolation to poikilothermic animals, plants and unicellular organisms, all of which are held by consensus to fit Kleiber's law (but see the two preceding sections). Why should temperature fluxes across the body surface be the main determinants of metabolic rate in poikilotherms, particularly microorganisms? Even in mammals, maintenance of body temperature might not be the main contributor to energy turnover at rest (see later). Contrary to the view of Dodds et al. [ 16 ], therefore, b = 0.67 cannot be treated as a "null hypothesis". Throughout the remainder of this article, the consensus position will be assumed: Kleiber's law is valid for a wide range of organisms, and b = 0.75. This assumption is made tacitly and provisionally and does not imply dismissal of the foregoing sceptical arguments; but a field can only be reviewed coherently from the consensus point of view. McMahon's model [ 42 ] A vertical column displaced by a sufficiently large lateral force buckles elastically. The critical length of column, l cr , = k(E/ρ) 1/3 d 2/3 , where d = column diameter, E = Young's modulus and ρ = density. If E and ρ are constant then l cr 3 = cd 2 , where c is a constant of proportionality. McMahon [ 42 ] applied this reasoning to bone dimensions for stationary quadrupeds. In a running quadruped the limbs support bending rather than buckling loads but the vertebral column receives an end thrust that generates a buckling load. It follows that all bone proportions change in the same way with animal size. The mass of a limb, w l , = αld 2 , where α is a constant. If w l is proportional to M, as it generally must be, then M = βld 2 , where β is another constant. Hence (given the above relationship between l and d) M is proportional to l 4 , implying that l is proportional to w l 1/4 ; hence d is proportional to w l 3/8 , or M 3/8 . Empirical support for this relationship appeared in [ 43 ]. McMahon [ 42 ] also applied this argument to muscles. The work done by a contracting muscle, W, is proportional to σAΔl, where σ is tensile strength, A is the cross-sectional area and Δl is the length change during contraction. The power developed, W/t (t = time), is therefore σAΔl/Δt. Since σ and Δl/Δt are roughly constant and independent of species, W/t varies with A; and since A is proportional to d 2 , W/t it is proportional to d 2 , and therefore to (M 3/8 ) 2 = M 3/4 . If this deduction applies to any skeletal muscle (as seems plausible), then it applies to the entire set of metabolic variables supplying the muscular system with nutrients and oxygen. Hence, B varies as M 3/4 . A broadly comparable but simpler argument was advanced by Nevill [ 44 ]; large mammals have proportionately more muscle mass than smaller ones. If the contribution of the muscle to B (which Nevill assumes is proportional to M) is partialled out, then the residual B is proportional to M 2/3 . Nevill's paper is seldom cited. One difficulty with McMahon's model is that little of the energy turnover under conditions of standard metabolic rate measurement entails muscle contraction. The model might still be valid if maximum metabolic rate followed the same allometric scaling law as B; this has been widely believed, and Taylor et al. [ 45 ] adduced evidence for it. However, recent detailed studies [ 46 - 48 ] indicate that maximum metabolic rate in birds and mammals scales as M 0.88 , not M 0.75 , although there are disagreements about whether aerobic capacity determines the allometry of maximum metabolic rate [ 48 , 49 ]. Weibel [ 50 ] presented a large set of data to this effect. (On the other hand, there are reports that in birds the index decreases rather than increases with increasing metabolic output, e.g. [ 58 ].) Another drawback of the McMahon model is that it cannot apply to organisms without muscles, such as protists. This perhaps explains why McMahon's elegant deduction has been largely ignored in recent debates about Kleiber's law. The Economos model [ 51 ] An increased gravitational field increases energy metabolism in animals [ 52 , 53 ]. Work against gravity is proportional to M 1.0 . If maintenance metabolism were related to surface area (proportional to M 0.67 ) then a combination of the two effects, surface-to-mass ratio and work against gravity, might explain the observed M 3/4 relationship. This model [ 51 ] is difficult to assess: it is not clear why the two proposed factors, surface area dependence and gravitational loading, should combine for all animals (and other taxa) in just the right proportions to generate a 0.75-power dependence on body mass. To take just one example, aquatic microbes are more affected by Brownian motion than by gravity, so why should they show the same balance between surface-to-mass ratio and gravitational effects as mice or elephants? Pace et al. [ 54 ] suggested that the Economos model could be critically tested under conditions of weightlessness in space. No corroboration (or refutation) by studies on astronauts has been reported. Allometric scaling in cells and tissues Before more recent models purporting to explain Kleiber's law are discussed, some comments are needed on scaling of metabolism at the organ, tissue and cell levels. Belief that the Kleiber relationship can be explained in terms of the inherent properties of the cells dates from the 1930s [ 3 , 55 ] and persists (e.g. [ 56 , 57 ]. Standard metabolic rate (B) is usually measured as oxygen consumption rate, which correlates with nutrient utilization [ 9 , 15 ] and rates of excretion of nitrogenous and other wastes [ 2 ]; so research in the field has been dominated by respiratory studies. Lung volume, trachaeal volume, vital capacity and tidal volume all scale as M but respiratory frequency varies as M -0.31 , ventilation rate as M 0.77 and oxygen consumption rate as M 0.72 [ 58 - 60 ]. All mammals extract a similar percentage of oxygen (~3%) from respired air [ 9 ]. The significance of "pulmonary diffusion capacity" has been debated; it scales as M 1.0 so it is disproportionate in bigger animals [ 17 , 61 - 65 ]. Stahl [ 60 ] described the scaling of cardiovascular and haematological data. Blood haemoglobin concentration is the same for all mammals except those adapted to high altitudes. Blood volume is ~6–7% of body volume for all mammals except aquatic ones. Erythrocyte volume varies with species but bears no obvious relationship to M. The oxygen affinity of haemoglobin varies with body size, being lower in smaller mammals, which unload oxygen to their tissues more rapidly. Capillary density is more or less constant in mammals with bodies larger than a rat's, though it is greater in the smallest mammals [ 65 ]. The heart accounts for ~0.6% of body mass in all mammals [ 66 ]. Heart rate scales as M -0.25 , cardiac output as M 0.81 (60) and circulation time as M 0.25 . The energy cost of supplying the body with 1 ml of oxygen is similar for all mammals [ 15 ]. Standard metabolic rate has two main components: service functions, e.g. the operation of heart and lungs; and cellular maintenance functions, e.g. protein and nucleic acid turnover (e.g. [ 67 ]). Krebs [ 68 ] elucidated this second component by studying tissue slices; his investigation has since been extended. Oxygen consumption per kg decreases with increasing M in all tissues, but tissues do not all scale identically. Horse brain and kidney have half the oxygen consumption rates of mouse brain and kidney but the difference between these species in respect of liver, lung and spleen is 4-fold [ 68 - 70 ]. Metabolic rate in liver scales as M 0.63 ; for some organs the exponent is closer to 1.0; the sum of oxygen consumption rates over all tissues gives – approximately – the expected 0.75 index [ 71 ]. The difficulty of recalculating B from tissue-slice data is considerable, so the Martin and Fuhrman calculation [ 71 ] has wide confidence limits. Spaargen [ 72 ] suggested that tissues that use little oxygen constitute different percentages of body mass in large and small mammals, leading to a distortion of the surface law (B = M 2/3 ), which would otherwise be valid. More recently, however, Wang et al. [ 73 ] repeated the Martin and Fuhrman calculation using improved data, and found impressive support for the consensus B = M 3/4 . Cells of any one histological type are size-invariant among mammals but allometric scaling is reported at the cellular level; e.g. the metabolic rate of isolated hepatocytes scales as M -0.18 [ 74 ]. Numbers of mitochondria per gram of liver (or per hepatocyte), however, scale as M -0.1 [ 75 , 76 ]. The apparent discrepancy between these values might be illusory ( cf. [ 77 ]), or it might indicate a greater proton leak in mitochondria from livers of smaller animals [ 78 ] or allometry in redox slip [ 79 ]. Also, larger animals have smaller inner mitochondrial membrane surface areas (the scaling is M -0.1 ) and different fatty acid compositions [ 71 ]. The discrepancy between the scalings of hepatocyte and whole-body metabolism is probably explained by the decrease in liver mass, which scales as M 0.82 [ 75 , 80 ]. Combining liver mass with hepatocyte oxygen consumption, the derived scaling for liver metabolism is M 0.82 .M -0.18 = M 0.64 , consistent with the experimental tissue-slice data (M 0.63 ; see above). Combining liver mass with mitochondrial number per hepatocyte gives a similar value [ 77 ]. Cytochrome c and cytochrome oxidase contents scale roughly as M 0.75 [ 81 - 85 ]. The allometric scaling of mitochondrial inner membrane area, and the body-size-related differences in unsaturated fatty acid content, remain unexplained. Isolated mammalian cells reportedly attain the same mitochondrial numbers and activities after several generations in culture, irrespective of the tissue of origin or the organism's body mass [ 86 - 88 ]. If allometric scaling is lost at the cellular level after several generations in vitro , then presumably mitochondrial densities, inner membrane areas and cytochrome levels somehow become "normalized". This is a readily testable prediction [see [ 89 ]], but it does not appear to have been subjected to critical experiments. If it is corroborated there will be interesting mechanisms to investigate. The main conclusions from this section are: (a) different organs make different contributions to the scaling of whole-organism metabolic rates; (b) differences at the cellular level make relatively small contributions to scaling at the organ level; (c) these differences at cellular level might disappear altogether after several generations in culture. The most striking conclusion is (b). It implies that allometric scaling of metabolic rate does not after all, for the most part, reside in cellular function but at higher levels of physiological organisation. If this is the case, then the alleged applicability of Kleiber's law to unicellular organisms is called into question. Resource-flow models Coulson's flow model [ 42 ] was mentioned earlier. It relates tissue or organ oxygen consumption rates to circulation times, i.e. to the rate of supply of oxygen and nutrients, and these scale as M 0.25 (see previous section). Coulson's approach contrasts with traditional biochemical measurements: the principal variable is not the concentration of a resource but the supply rate ; metabolic activity depends on encounter frequency not concentration . This perspective merits further development, particularly by extension to the cell internum [ 89 - 93 ]. Obviously, it is within the cell that the reactant molecules are passed over the catalysts; and the flow rate increases with the cell's metabolic activity, as Hochachka [ 93 ] cogently described. However, flow theories advanced to explain Kleiber's law have not followed this line of argument. Banavar et al. [ 94 , 95 ] and Dreyer and co-workers [ 27 , 96 ] have shown that the Kleiber relationship can be deduced from the geometries of transport networks, without reference to fluid dynamics. Broadly, these authors argue that as a supply network with local connectivity branches from a single source (in a mammalian circulatory system, the heart is the source), the number of sites supplied by the network increases. Natural selection has optimized the efficiency of supply. A general relationship can be derived between body size and flow rate in the network: delivery rates per unit mass of tissue vary with the quarter-power of body size (M), implying the validity of Kleiber's law. The most detailed account of this argument [ 95 ] begins with the reasonable assumption that M scales with L D , where L is the physical length of the organism and D is its dimensionality. It proceeds with a theorem: the sum of flows through all parts of the network, F, is proportional to the (dimensionless) length multiplied by the metabolic rate. A quantity measuring the total flow of metabolites per unit mass of organism is then defined: r 1 = F/M. r 1 (which has units of inverse time) measures the dependence of the network's geometry on body mass, so it indicates the energy cost of metabolite delivery. Another parameter, r 2 , measures the metabolite demand by the tissues: r 2 = the dimensionless length of the "service volume" (the amount of tissue that consumes one unit of metabolite per unit time). It is then deduced that B is proportional to (Mr 1 /r 2 ) D/(D+1) . Provided that r 1 and r 2 change proportionately – i.e. supply always matches demand – then for a three-dimensional organism, Kleiber's law follows. According to Banavar et al. [ 94 ], deviations from Kleiber's law indicate inefficiency or some physiological compensation process. This model has been criticized [ 97 ] because the assumed network does not resemble (e.g.) the mammalian circulatory system, where only terminal nodes (capillaries), not all nodes (as the model implies), are metabolite exchange sites. Also, the model seems to predict that r 1 /r 2 will decrease as B rises from standard to maximal; but the best data suggest the opposite trend (see earlier discussion: [ 46 - 48 ]). Banavar et al. do not explicitly allow for differences among tissue types, which are considerable (see above), except perhaps in terms of rather implausible variations among r 1 /r 2 ratios. On the other hand, the model is simple and flexible and it reflects recent developments in the physics of networks. If it could be applied to flow at the cellular level, it might accord with the requirements discussed at the beginning of this section; though it is difficult to see how this can be achieved. Rau [ 98 ] also advanced a fluid-flow model, but his conception is physical not geometrical. Assuming Pouseille flow through an array of similar tubes, such as capillaries, and a roughly constant flow speed, Rau used scaling arguments to derive the relationship t = kM 1/4 , where t is the transport time and k is a constant. If the fluid transport rate (essentially the reciprocal of t) is proportional to B/M, Kleiber's law follows. However, Rau's model appears to assume that because metabolic rate is energy per unit time, it can be equated with the product of fluid volume flow rate and pressure (since energy is equal to pressure times volume). This assumption, which appears to be based exclusively on dimensional analysis, is fallacious. Four-dimensional models Blum [ 99 ] observed that the "volume" of an n-dimensional sphere of radius r is V = π n/2 r n /Γ(n/2 + 1), and that A = dV/dr = nπ n/2 r n-1 /Γ(n/2 + 1). Here, Γ(n) is the gamma-function such that Γ(n + 1) = n n , Γ(2) = 1 and Γ(3/2) = π 1/2 /2. Suppose two objects have "volumes" V 1 and V 2 and "areas" A 1 and A 2 . From the foregoing, A 1 /A 2 = (V 1 /V 2 ) (n-1)/n ; so if n = 4, a 3/4-power relationship between "volumes" (hence, masses?) emerges from a familiar mathematical principle. Might Kleiber's law therefore follow from a four-dimensional description of organisms? Speakman [ 100 ] pointed out that if n = 4, then A is volume (it has three dimensions) and V is hypervolume, the biological significance of which is obscure. However, West et al. [ 88 , 101 , 102 ] have indeed proposed a four-dimensional model to explain the Kleiber relationship, and considerable claims have been made for their account. This model addresses the supply of materials (particularly oxygen) through space-filling fractal networks of branching tubes. It assumes that as a result of natural selection, organisms maximize their use of resources. The initial account [ 101 ] assumed that energy dissipation is minimised at all branch-points in the network and that the terminal branches are size-invariant (for instance, blood capillaries are the same lengths and diameters in mice and elephants). Kleiber's law and analogous scalings were deduced from these assumptions. In particular, the three-quarters-power exponent was shown to be inherent in the geometry of a branching network that preserves total cross-sectional area at each branch point. The circulatory systems of large animals such as mammals are not exactly area-preserving, but West et al. [ 101 ] reasoned that this objection could be circumvented by considering the pulsatile flow generated in the larger arteries by the action of the heart. A second, simpler account [ 102 ] developed the model from a geometrical basis. The crucial feature of the branching network is the size-invariance of the terminal units. The effective exchange area, a , is a function of the element lengths at each level of the hierarchy, but one of these, the terminal one (l 0 ), is invariant. Writing Φ as a dimensionless function of the (dimensionless) ratio l 1 /l 2 leads to a (l 0 , l 1 , l 2 ,...) = l 1 2 Φ(l 0 /l 1 , l 2 /l 1 ...) Introducing a scaling factor, λ, leads to a (l 0 , l 1 , l 2 ,...) = λ 2 l 1 2 Φ(l 0 /λ l 1 , l 2 /l 1 ...) which is not proportional to λ 2 because l 0 is fixed. The dependence of Φ on λ is not known a priori , but it can be parameterized as Φ(l 0 /λ l 1 , l 2 /l 1 ...) = λ ε Φ(l 0 /l 1 , l 2 /l 1 ...), where ε is between 0 and 1. This power law reflects the fractal character of the network's hierarchical organization. Similar reasoning is applied to body volume, hence body mass, and the following expression for the exchange surface area is derived:- a = kM r , r = (2 + ε)/(3 + ε + ζ), where k is a constant and ζ (0 < ζ < 1) is an arbitrary exponent of length, just as ε is an arbitrary exponent of area. If natural selection has acted to maximize the scaling of a , then ε must tend to 1 and ζ to 0. This gives r = 0.75. If a limits the supply of oxygen and nutrients, and hence determines standard metabolic rate, then B is proportional to a and Kleiber's law follows. The model has several attractions: it derives from well-established physical principles, invokes natural selection and is mathematically impeccable. It implies that cells and organelles transport materials internally along space-filling fractal networks rather than by "diffusion", which seems correct [ 83 , 85 , 86 , 103 ]. The self-similarity of these transport networks is emphasized particularly in [ 88 ]. The dimensionalities of effective exchange surfaces, a , are predicted to be closer to 3 than 2; empirically, the microscopic convolutions of surfaces such as the mammalian intestinal mucosa are well known. The mass of the smallest possible mammal is deduced and shown to be close to the mass of the shrew. Other approaches to exchange networks, assuming minimum energy expenditure and scale-invariance, have led to similar models [ 104 ]. The model can be adapted, with no loss of rigour, to new data: Gillooly et al . [ 105 ] showed that the fractal supply network principle can be combined with simple Boltzmann kinetics to explain the effects of both body mass and temperature on metabolic rates. Since mass and temperature are the primary determinants of many physiological and ecological parameters, this work suggests that the model [ 88 ] could revolutionize biology. This is an impressive range of successes. However, West and his co-workers make claims that are less compelling. The observation that cytochrome oxidase catalytic rates fit the same allometric curve as whole-organism metabolic rates is claimed as corroboration. However, cytochrome oxidase is not an organism, or a cell: it does not have a metabolic rate. It is also debatable whether mitochondria can be said to have "metabolic rates". (In contrast, Hochachka and Somero [ 106 ] noted that oxygen turnover in the whole biosphere can be fitted to the same curve; but they recognized this as "a contingent fact with no biological significance".) Also, the explanation derived by West and his colleagues for the alleged body-mass-invariance of the metabolic rates of cultured cells (see earlier) is mathematically neat, but it leads to no experimentally testable predictions, and the heterogeneous data sources cited in this context make the explicandum itself unconvincing. Finally, the model is said to explain the quarter-power scalings of a wide range of biological variables other than metabolic rate, including population densities of trees [ 19 ] and carnivorous animals [ 107 ], plant growth rates, vascular network structure and maturation times [ 18 , 108 ], and life-spans [ 88 ]. It is not clear why any of these variables should depend on the fractal geometries of space-filling supply networks, still less on metabolic rates; though there is widespread interest in the application of scaling laws in ecology, for instance in modelling biodiversity [ 109 ] and food webs [ 110 ]. Moreover, there are definite flaws in the model:- (1) If West et al. were correct, maximal and standard metabolic rates should both scale as M 0.75 . The weight of evidence suggests that maximum rate in homoiotherms scales as M 0.88 (see earlier discussion [ 46 - 49 ] and following section). (2) During maximal energy output by an organism, the supply of material is likely to be limiting. For example, in mammals, muscle contraction is responsible for most of the energy turnover at maximum output and it is generally believed that the rate is limited by oxygen supply (if anaerobic capacity is ignored). However, under standard metabolic rate conditions, energy demand is generally more significant, i.e. for the service and cellular maintenance functions mentioned previously. Therefore, it is not clear why the geometry and physics of the supply system should predict the allometric scaling of standard rather than maximal metabolic rate. ("Supply" and "demand" under conditions of maximal aerobic metabolism are complex terms because many physiological steps are involved. The extent to which each step limits the maximum metabolic rate might be quantifiable by a suitable extension of metabolic control analysis [ 111 ]; this remains an active research area to which West et al. scarcely refer.) (3) The mathematical derivations given in [ 101 ] are idealisations, but they do not seem to allow for large deviations from b = 0.75. However, there are often wide differences among empirical b values, as discussed earlier; these were addressed in, for example, [ 18 ] and [ 31 ]. Also, the model does not account, or allow, for the differences in allometric scaling among mammalian tissues and organs [ 66 , 73 , 80 ]. (4) West et al. accept that some of their proposed hierarchical supply networks might be "virtual" (as in mitochondria) rather than explicit (as in mammalian blood circulation), but it is not clear why such networks must always have the same geometry. For instance, why should the intracellular network discussed by Hochachka [ 93 ] show area-preserving branching? There is no evidence that it does. Moreover, the "flow" of reductants through mitochondria presumably takes place in the plane of the inner membrane, which has one dimension fewer than (say) the mammalian circulatory system, so even if mitochondria can be said to have "metabolic rates", the 0.75-power law cannot apply here; yet, allegedly, it does apply. These difficulties show that the West et al. model, despite its impressive economy, elegance, consistency and range, cannot be accepted unreservedly in its present form. The very generality, or "universality", of this model has made it suspect for some biologists [ 25 ]. The implication that it reveals a long-suspected universal biological principle implicit in Kleiber's law has ensured its attraction for others [ 14 ]. The model of Darveau and co-workers [ 112 ] This group elaborated a multi-cause rather than a single-cause account of allometric scaling. Their "allometric cascade" model holds that each step in the physiological and biochemical pathways involved in ATP biosynthesis and utilization has its own scaling behaviour and makes its own contribution (defined by a control coefficient between 0 and 1) to the whole-organism metabolic rate. Thus, many linked steps rather than a single overarching principle account for Kleiber's law. This idea is inherently plausible, and the model is attractive because it draws upon recent advances in metabolic control analysis in biochemistry [ 111 ] and physiology [ 113 ]. It emphasises that standard metabolic rate is determined by energy demand, not supply; and it predicts an exponent for maximal metabolic rate in mammals between 0.8 and 0.9, rather than 0.75, which agrees with experimental findings [ 46 - 49 ] and the data cited by Weibel [ 50 ]. Implicitly – though the authors do not emphasize this – it seems capable of explaining b values that are far from 0.75 ( cf [ 31 ]). It is hardly surprising, therefore, that many responses to the Darveau et al. model have been positive [e.g. [ 114 ]]. However, Darveau et al. made no attempt to explain why the values of b are typically around 0.75, as West et al. and others have done. The model is phenomenological, not physical and mathematical; their equations are not derived from any fundamental principle(s). Moreover, their data cover only some three orders of magnitude of body mass, whereas many studies have involved much wider ranges. This might make their overall b values misleading [ 103 ] or, alternatively, more credible [ 18 ]. When their equations are applied to a mass range of eight orders of magnitude, different b values are obtained, not necessarily consistent with published data; but on the other hand, the published data might not be correct. In the first published account of this model [ 112 ] the mathematical argument was flawed. The basic equation was given in the form B = aΣc i M b(i) , where a is a constant coefficient, c I is the control coefficient of the i th step in the cascade and b(i) is the exponent of the i th step. By definition, the sum of all the c I values is unity. Darveau et al. did not derive this equation; they stated it. They also stated that the overall exponent, the b term in the Kleiber equation, is a weighted average of all the individual b(i) values, the weighting being determined by the relevant control coefficients. It has been suggested that this leads to untenable inferences. For example, since the units of B and a are fixed, the units of c I must depend on those of b(i); but by definition, both b(i) and c I must be dimensionless. Also, according to the basic equation, the contribution made by each step to the overall metabolic rate depends on the units in which body mass is measured. If this criticism is valid then it is impossible to evaluate the model as it stands, because any attempt to align its predictions with experimental data would be meaningless. Another reservation about this model is that it does not purport to apply to all taxa, as the West et al. model does; it relates only to metazoa, and in particular to homoiotherms. However, most of the relevant data in the literature concern homoiotherms. A subsequent publication from this group [ 115 ] re-stated the basic equation in the form B = aΣc I (M/m) b(i) , where the constant a is described as the "characteristic metabolic rate" of an animal with characteristic body mass m . This eliminates the problem of mass units, because the mass term has been rendered dimensionless; and it is mathematically simple to express control coefficients in dimensionless form. The revised equation might therefore be immune to some of the criticisms levelled at its predecessor. However, some of the earlier reservations remain: the equation remains phenomenological, not physical or geometrical; and the restriction in its range of application is explicit. Nevertheless, these considerations by no means invalidate the model. Indeed, it is supported by data from experiments in exercise physiology [ 116 ]. The models of Darveau et al . [ 112 , 115 ], Banavar et al. [ 94 , 95 ] and West et al. [ 88 , 102 ] all have attractive features; but they all have flaws, and they cannot be reconciled with one another. If the positive contributions to biology that these models represent could be further developed, and their defects eliminated, could they be harmonized? If so, the advancement of our understanding would be considerable. Conclusions Several explanatory or quasi-explanatory models have been proposed for the allometric scaling of metabolic rate with body mass. Most of them have significant attractions, particularly the most recent ones, but none of them can be unreservedly accepted. The variability of experimental data leaves room for doubt that Kleiber's law is universally or even widely applicable in biology [ 17 , 117 ], yet most workers in the field presume that it is. Even if such doubts are set aside, no model has yet addressed every relevant issue. For example, the biochemical reasons for the allometric scalings of mitochondrial inner membrane areas and unsaturated fatty acid contents, and the direct proportionality of "pulmonary diffusion capacity" to body mass, remain unexplained. Despite the continuing controversy in the field, the consensus remains, and practical use has been made of Kleiber's law, for example in making numerical predictions of anatomical and physiological parameters for veterinary applications [ 118 ]. Perhaps the last word should be given to Bokma [ 119 ], whose most recent paper explores the power-scaling of metabolic rate to body mass ( b ) on an intra-specific basis from a total of 113 species. He came to the conclusion that there was no single universal value of b . This evidence alone must make us more sceptical of there being some unifying law involved that demands that b holds close to 0.75. There is clearly no consensus otherwise Nature , Science and the Proceedings of the National Academy of Sciences USA would cease to publish so regularly many of the articles to which we have referred. The subject is not only unresolved, but remains very much within the general interest of biologists. Kleiber's law remains a fascinating mystery; possibly a delusion, possibly a widespread or even ubiquitous biological phenomenon for which no entirely satisfactory account has yet been offered. Recent developments, though mutually conflicting as they stand, have the potential to lead to new insights and to uncover one or more general biological principles that will have a profound impact on our understanding of the living world.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539293.xml
549563	The Darlington and Northallerton Long Term Asthma Study: pulmonary function	Background The Darlington and Northallerton Asthma Study is an observational cohort study started in 1983. At that time little was published about long term outcome in asthma and the contribution of change in reversible disease or airway remodelling to any excess deterioration in function. The study design included regular review of overall and fixed function lung. We report the trends over fifteen years. Methods All asthmatics attending secondary care in 1983, 1988 and 1993 were recruited. Pulmonary function was recorded at attendance and potential best function estimated according to protocol. Rate of decline was calculated over each 5-year period and by linear regression analysis in those seen every time. The influence of potential explanatory variables on this decline was explored. Results 1724 satisfactory 5-year measurements were obtained in 912 subjects and in 200 subjects on all occasions. Overall rate of decline (ml/year (95%CI)) calculated from 5-year periods was FEV1 ♂41.0 (34.7–47.3), ♀28.9 (23.2–34.6) and best FVC ♂63.1 (55.1–71.2)ml/year, ♀45.8 (40.0–51.6).The principal association was with age. A dominant cubic factor suggested fluctuations in the rate of change in middle life with less rapid decline in youth and more rapid decline in the elderly. Rapid decline was possibly associated with short duration. Treatment step did not predict rate of deterioration. Conclusions Function declined non-linearly and more rapidly than predicted from normal subjects. It reports for the first time a cubic relationship between age and pulmonary function. This should be taken into account when interpreting other articles reporting change in function over time.	Background It is recognised that the average decline in pulmonary function is greater in asthmatic subjects than in the general population [ 1 , 2 ]. This might be due to deterioration in potentially reversible disease [ 3 ] or the development of persistent obstruction following airway remodelling [ 4 ]. The published longitudinal studies do not differentiate between the two possible mechanisms. The Darlington and Northallerton Long Term Asthma Study was started in 1983 when little was known about long term outlook in asthmatics. Its objective was to observe mortality and decline in pulmonary function in asthmatics sufficiently severe to be referred for a hospital opinion. Decline in best achievable function is proposed as a measure of the airway remodelling. We accept that this decline might also be associated with Chronic Obstructive Pulmonary Disease (COPD). This label implies a physiological diagnosis, but the condition, like asthma, is better defined in terms of the underlying inflammation [ 5 ]. The diagnoses are therefore not necessarily mutually exclusive. Changes in best function are reported without prejudice to the underlying type of inflammation whether asthmatic, COPD, or both. We wished this to be a population study as far as possible, so we invited all subjects satisfying a broad definition of asthma referred to a single-handed respiratory physician in a well defined geographical area to participate. Very few refused, but patients managed entirely in general practice were necessarily excluded. Best function, assessed according to a defined protocol [ 6 ] implicitly accepted in published guidelines [ 7 ], and potential explanatory variables were recorded prospectively at each visit. Smokers were not specifically excluded, but smoking habit was taken into account when the diagnosis was in doubt. Subjects with severe established fixed obstruction were excluded. Thus there was bias against the inclusion of asthmatic smokers destined to develop fixed obstruction rapidly, so we do not present any analyses confined to smokers. Although it was not until the mid 1980's that the use of prophylactic inhaled corticosteroids became standard practice, the majority of our subjects were maintained on inhaled steroids throughout the period, but the dose intensified [ 8 ]. Therefore only the change in dose could not account for any secular trends in decline in function. In this paper we explore the influence of demographic and other factors on change in function as observed over five year intervals. Methods These, described in detail elsewhere [ 8 - 11 ] are summarised and where directly relevant expanded below. Subjects All asthmatics currently attending secondary care clinics in the Darlington and Northallerton Health Districts were eligible for recruitment in 1983, 1988 and 1993, and reviewed in 1988, 1993 and 1998. Asthma was diagnosed clinically and confirmed by reversibility of FEV1 or peak flow of at least 15% on more than one occasion, either spontaneously, or in response to bronchodilator at any time since referral [ 9 ]. Subjects were only eligible for the study if they had been observed for at least one year before entry, and if not stable when first reviewed, entry was deferred by three months in an attempt to achieve stability. Socio-demographic variables were recorded as previously reported [ 10 ]. The first group of this dynamic cohort study was recruited during the calendar year 1983 but subsequent review and recruitment was between the 1 st April and the 31 st March in subsequent 12-month periods[ 11 ]. Allowance for the extra 3 months of the first interval has been made in calculating rate of change. Subjects are included in this report provided they had two technically satisfactory measurements of actual FEV1 or two estimates of best FEV1 or best FVC according to protocol. Social and demographic variables The following variables recorded included: age, gender, height, duration of asthma, atopy, childhood asthma, smoking habit and lifetime amount smoked, social class. Duration of asthma was determined from the first onset or from relapse after a symptom free interval of at least five years, if this was applicable. Atopy was determined by at least one of the following skin tests resulting in a diameter at least 3 mm greater than control: D Pterynissimus, cat, grass pollen, A fumigatus. Childhood asthma was defined as a childhood history of recurrent lower respiratory tract symptoms with wheeze, in the absence of a localised structural damage such as bronchiectasis. It was sub-divided into those with (Gap Asthmatics) and without (Continuous since Childhood) a symptom free gap of at least five years. Never smokers were those smoking less than one cigarette a day for one year. Ex-smokers had been abstinent for at least three months at the time of examination. The lifetime amount smoked was determined from the average consumption (expressed in packs of 20 cigarettes) multiplied by the duration of smoking to give a figure in pack-years. Therapeutic regimen This was characterised by the use of long acting beta agonists and the corticosteroid step: none, low dose inhaled (<800 micrograms per day), intermediate dose inhaled (800–1000 micrograms per day), high dose inhaled (>1000 micrograms per day), oral 1–9 mgs per day, oral ≥ 10 mgs per day, unstable (treatment not mutually agreed as satisfactory over the last three months). Pulmonary function Actual function Actual function was that recorded at attendance. Best function This was estimated according to the published protocol [ 6 ]. The notes were searched from January 1 st of the previous year, and the highest value, including the after-bronchodilator reading at attendance, was accepted as best subject to the following. (a) If >80% predicted (Cotes [ 12 ]); after-bronchodilator (b) If 70–80% predicted; after-bronchodilator and stable on mutually agreed satisfactory preventative treatment with twice daily recording of peak flow for one week (c) If <70% of predicted; after-bronchodilator with formal trial of corticosteroids (prednisolone 30 mgs for at least five days with stability of peak flow for at least 48 hours) If the above was not already satisfied, best function was immediately established according to the protocol. Measurement Spirometry was performed using a rolling wedge spirometer (Vitalograph Limited) and peak flow with the mini peak flow meter (Clement Clark Limited). Actual function was measured opportunistically at the clinic in current attenders and at a special clinic for those who had been discharged. One of three research fellows, one of two research nurses or CKC were responsible for checking current pulmonary tests in the clinical records and performing further tests when required by protocol for best function. Ethical approval This was obtained from the Darlington, Northallerton and South Durham Ethics Committees at various stages of the study. Statistical analysis The principal independent variable was change during each 5-year period so each individual contributed up to 3 observations to the analysis. For the 200 subjects with observations on all four occasions a secondary analysis could be based on decline over 15 years, and for each of these subjects the mean rate of decline was estimated from the four observations using linear regression analysis. Best and actual/best peak flow measured independently of the spirometric outcome variables were chosen as the functional potential predictors of outcome. This approach was taken to avoid the mathematical relationship between baseline level and change that applies if the spirometric variables are used as predictors of outcome. Many of these potential predictive variables are correlated with each other and there are arguments for and against models examining the effect of socio-economic variables with or without allowance for the respiratory function of the patients and their age. We present a relevant selection from the large range of unrestricted and hierarchical models that we constructed. We allowed for the inevitable regression to the mean associated with outcome measures subject to appreciable variability. Initially the starting value of an outcome functional variable was regressed against a full set of potential predictors of this function in order to generate a set of residuals indicating the extent to which an individual starting measurement is higher or lower than would be expected. Then the change in function was regressed against the residual. The new set of residuals indicates the extent to which the apparent rate of change is affected by regression to the mean enabling an adjusted rate of change to be calculated. This adjusted change in function was then taken as the dependent variable in subsequent analyses. These included the univariate effect of potential risk factors on the adjusted change in function. In the multivariate analyses we omitted variables which were consistently non-significant, but all others are retained in the presentation. Models are shown with and without the inclusion of age. Univariate analysis showed that there were cubic relationships between change in function and age and duration. The cubic terms are retained in the multivariate presentation. We also examined interactions between predictor variables where there was some a priori reason for believing that such an interaction was plausible but none was demonstrated. Results General Of 1138 subjects recruited, 155 died before the first review, 49 were lost to follow up and 22 did not have satisfactory spirometric tests. The remaining 912 had at least one paired result of actual or best FEV1 or best FVC and 200 had satisfactory assessments of best FVC on all four occasions. Demographic details at entry are given in Table 1 . There were no relevant differences in social factors between the subjects observed on all four occasions and the rest. Current smokers represented approximately 13% of the population in 1983/88 and 10% in 1993/98 with a mean tobacco load of ♂29.2 (ex-smokers 27.6) and ♀21.4 (ex-smokers 13.2) pack years. Ever-smokers were significantly older than never-smokers (53.9 v 44.9 years p < 0.001), but allowing for age, the atopic status of ever-smokers and never-smokers was the same. The proportion of subjects stable on inhaled or oral steroids rose from 66.5% in 1983 to 82.1% in 1988 with no increase thereafter. Higher doses (> = 800 micrograms) of inhaled steroids increased from 30.8% in 1988 to 41.6% in 1998. Table 1 Details of subjects at entry Male Female n 457 455 Age (years)(sd) 50.4(15.4) 49.3(16.3) Duration of asthma (years)(sd) 17.0(16.2) 18.6(15.4) Atopic n(%) 258(56.5) 227(49.9) Asthma n(%) childhood 124(27.1) 131(28.8) gap 53(11.6) 42(9.2) adult 280(61.3) 282(63.3) Social Class n(%) 1–2 131(28.8) 139(30.5) 3 168(36.9) 180(39.6) 4–5 156(34.3) 136(29.9) Smoking Habit n(%) never 147(32.2) 247(54.3) ever 239(52.3) 161(35.4) current 71(15.5) 47(10.3) Pulmonary Function(sd) Actual FEV1 l. 2.50(1.09) 1.97(0.79) Best FEV1 l. 2.60(1.08) 2.08(0.82) Best FVC l. 4.17(1.25) 3.05(0.84) Best PEF l/min 465.7(113.7) 382.0(85.1) Actual/Best PEF % 84.4(13.7) 83.2(15.9) Change in function The mean annual decline in function calculated using all five-year intervals (Table 2 ) was greater than expected when compared with predicted values and when expressed as %predicted [ 12 ] there were no consistent differences in the rates of decline of male and female never-smokers. As the confidence intervals suggest, standard deviations were large indicating a wide distribution of changes in different individuals. There was no secular trend in outcome in successive calendar periods. Figure 1 shows changes over 5, 10 and 15 year periods after entry against predicted [ 12 ] (improved >7.5%, no change, deteriorated >7.5%). Actual FEV1 improved in approximately one quarter and best FVC in rather less than 20% of subjects. The proportion of subjects showing deterioration in FEV1 >7.5% (35%) did not increase with time after entry, but excess decline in FVC was observed in more subjects after 15 year's observation (58%) than after five (37%) (χ 2 for trend, 59.0 (p < 0.001)). Table 2 Annual Decline in Pulmonary Function calculated from the mean of all 5-year paired observations, and by linear regression over 15 years in the 200 subjects with all four observations Annual Decline n Actual FEV1 l. Best FEV1 l. Best FVC l. Males Over 5 Years All Subjects 776 41.0 (34.7–47.3) 42.9 (37.5–48.3) 63.1 (55.7–71.2) Never smokers 256 34.2 (22.2–46.2) 33.4 (22.7–44.1) 49.2 (35.6–62.8) Over 15 Years 85 46.7 (38.7–54.7) - 64.7 (54.6–74.8) Females Over 5 Years All Subjects 848 28.9 (23.2–34.6) 34.4 (29.8–39.0) 45.8 (40.0–51.6) Never smokers 375 28.7 (22.4–38.8) 30.6 (22.2–35.2) 45.2 (36.4–54.0) Over 15 Years 115 24.7 (14.8–31.2) - 44.6 (37.9–51.3) Figure 1 The proportion of all subjects and never-smokers showing decline (>7.5%), no change, or improvement (>7.5%) in function against predicted over 5, 10 and 15 years. For the 200 subjects with complete observations over 15 years the mean rate of decline was similar to that observed over five year periods, but the standard deviation of the rates of decline was half that of the 5-year estimates, reflecting greater accuracy from multiple measurements. Even when calculating change this way several individuals improved or showed excessive loss in function against predicted [ 12 ]. Associations with entry variables As there was no secular trend in the change of function over the five year periods, the date of observation is not considered in the analyses below. All subjects: 5-year intervals Univariate analysis The univariate relationships between the potential explanatory variables and change in function after allowance for regression to the mean are summarised in Table 3 . These are derived from all available pairs of observations at five year intervals. The strong associations with age are not linear. This is demonstrated in fig 2 which shows the fitted plots of the cubic equations for the unadjusted rate of decline for all three measures. The maximum decline was in the mid 40's for all three variables (actual FEV1 44 ml/yr; best FEV1 56 ml /yr; best FVC 70 ml/yr). During the eighth decade rate of decline in function recovered towards the published predicted values [ 12 ] to 27, 29 and 49 ml/yr respectively. Table 3 Rate of loss of Function Univariate Coefficients (ml per year) (after allowance for regression to the mean) Actual FEV1 Best FEV1 Best FVC Estimate 95% CI Estimate 95% CI Estimate 95% CI Gender (male v female) 7.7 0.8 + ,16.1 6.2 2.5 + ,14.9 12.2 2.5,21.9 Age at entry (per decade) (difference from age 50) Linear 5.6 + 11.4 + ,0.2 10.1 + 15.9 + , 4.8 + 2.1 + 8.7 + ,4.5 quadratic 4.3 + 6.0 + , 2.5 + 5.0 + 6.8 + , 3.3 + 4.5 + 6.5 + , 2.6 + cubic 1.3 0.3,2.3 2.0 1.0,2.9 1.4 0.3,2.6 Duration of asthma at entry (per decade) (difference from duration 20 yrs) Linear 3.1 + 7.4 + ,1.1 0.5 3.8 + ,4.8 0.1 4.8 + ,5.0 quadratic 3.6 0.6,6.6 2.7 0.5 + ,5.8 5.6 2.2,9.0 cubic 0.9 + 1.6 + , 0.1 + 0.9 + 1.7 + , 0.1 + 1.4 + 2.3 + , 0.6 + Atopic 5.7 + 14.2 + ,2.8 0.2 8.5 + ,8.9 3.0 + 12.7 + ,6.7 Childhood asthma (versus no childhood asthma) Gap 3.4 + 16.7 + ,9.9 1.4 12.2 + ,15.0 4.0 + 19.4 + ,11.3 Yes 20.8 + 30.6 + , 10.9 + 10.6 + 20.9 + , 0.4 + 22.0 + 33.3 + , 10.6 + Social Class (versus classes 1 and 2) Three 6.3 + 16.5 + ,3.8 11.2 + 21.7 + , 0.8 + 9.2 + 20.8 + ,2.3 Four and Five 10.2 + 21.0 + ,0.7 14.5 + 25.6 + , 8.3 + 8.6 + 21.0 + ,3.9 Amount smoked (per 10 pack years) 1.5 0.6 + ,3.7 0.2 2.1 + ,2.4 2.9 0.4,5.4 Best PEF(per 10% deficit) 3.3 + 5.3 + , 1.2 + 2.8 + 4.8 + , 0.7 + 0.4 + 2.7 + ,2.0 Actual/Best PEF(10% deficit) 12.7 + 15.6 + , 9.8 + 2.8 + 6.2 + ,0.6 0.6 + 4.1 + ,2.8 (+) Indicates relative gain in function Figure 2 The relationship between age and annual change in function, observed over 5-year periods There were no statistically significant relationships with atopy. Longer duration of asthma was significantly associated with favourable outcome for all variables. In all cases a cubic relationship between loss of function and duration suggests high initial rates of loss (actual FEV1 55 ml/yr; best FEV1 51 ml/yr; best FVC 74 ml/yr at one year), with improvement to a plateau at around 20 years duration (30 ml/yr, 37 ml/yr and 45 ml/yr). Childhood asthma was significantly associated with a relatively favourable outcome, though this benefit was only seen in those for whom asthma had been continuous. The outcome of the 'gap asthmatics' was similar to those with adult onset. Higher social class was associated with worse outcome, significantly so for best FEV1. Low initial function and worse control as assessed by actual/best PEF both predicted less loss in actual FEV1. Although there were no significant associations with current smoking status, there was significantly greater loss in best FVC with amount smoked. Multivariate analysis As childhood asthma, duration of asthma and age at entry are potentially confounded and were significant in some of the univariate analyses, we performed a series of multivariate analyses progressively including each in turn. Tables 4 , 5 , 6 show the results after the inclusion of duration and then age. Male gender was significantly associated with greater decline in best FEV1 and, in contrast to the univariate analysis, best FVC. After the inclusion of duration, childhood asthma was still associated with favourable outcome in both actual FEV1 and best FVC, but it was displaced by age in all the models. Duration remained significantly associated with less change in best FVC even after allowance for age. In both models, actual FEV1 declined less with lower entry actual/best PEF. Best FEV1 declined more rapidly in those with a high initial best PEF. When age was not included in the model, membership of social classes 1 and 2 remained associated with unfavourable outcome for best FEV1. Table 4 Multivariate Coefficients (sd) for Rate of loss of Actual FEV1 (after allowance for regression to the mean) Age Excluded Age Included Coefficient p Coefficient p Gender (male v female) 5.5 (4.8) 0.25 5.7 (4.7) 0.23 Asthma since childhood 13.5 + (5.1) 0.008 4.9 + (5.8) 0.40 Social Classes 1 & 2 (v. classes 4 & 5) 4.8 (5.4) 0.65 1.8 (5.4) 0.88 Social Class 3 (v. classes 4 & 5) 1.1 (5.1) 0.6 + (5.0) Amount smoked (per 10 pack years) 1.8 (1.2) 0.13 1.0 (1.2) 0.39 Best PEF(per 10% deficit) 1.2 + (1.2) 0.33 0.9 + (1.2) 0.41 Actual/Best PEF(10% deficit) 12.0 + (1.6) <0.0001 13.2 + (1.6) <0.0001 Age at entry (per decade) (difference from age 50) Linear 3.5 + (3.1) quadratic 4.9 + (0.9) cubic 1.2 (0.6) 0.02 Duration of asthma at entry (per decade) (difference from duration 20 yrs) Linear 1.3 (2.8) 2.0 + (2.4) quadratic 3.2 (1.5) 0.9 (0.5) cubic 0.85 + (0.38) 0.03 2.5 + (0.39) 0.52 (+) Indicates relative gain in function Table 5 Multivariate Coefficients for loss of Best FEV1 (after allowance for regression to the mean) Age Excluded Age Included Coefficient (sd) p Coefficient (sd) p Gender (male v female) 11.3 (5.1) 0.03 11.9 (5.4) 0.02 Asthma since childhood 5.1 + (5.3) 0.34 1.1 + (6.0) 0.86 Social Classes 1 & 2 (v. classes 4 & 5) 13. (5.7) 0.05 10.7 (5.6) 0.11 Social Class 3 (v. classes 4 & 5) 2.9 (5.3) 1.4 (5.2) Amount smoked (per 10 pack years) 0.7 (1.3) 0.60 0.5 (1.3) 0.71 Best PEF(per 10% deficit) 3.4 + (1.3) 0.008 3.1 + (1,2) 0.01 Actual/Best PEF(10% deficit) 0.7 + (1.8) 0.71 1.4 + (1.8) 0.44 Age at entry (per decade) (difference from age 50) Linear 8.4 + (3.2) quadratic 5.1 + (0.9) cubic 1.8 (0.5) 0.0003 Duration of asthma at entry (per decade) (difference from duration 20 yrs) Linear 3.1 (2.4) 0.2 (2.4) quadratic 2.5 (1.6) 0.4 (1.6) cubic 0.91 + (0.39) 0.02 0.29 + (0.40) 0.46 (+) Indicates relative gain in function Table 6 Multivariate Coefficients for Rate of loss of best FVC (after allowance for regression to the mean) Age Excluded Age Included Coefficient (sd) p Coefficient (sd) p Gender (male v female) 10.8 (5.6) 0.05 11.4 (5.6) 0.04 Asthma since childhood 16.0 + (6.0) 0.007 4.7 + (6.9) 0.49 Social Classes 1 & 2 (v. classes 4 & 5) 10.7 (6.4) 0.13 7.5 (6.4) 0.29 Social Class 3 (v. classes 4 & 5) 0.2 + (6.0) 1.4 + (5.9) Amount smoked (per 10 pack years) 1.9 (1.4) 0.18 0.9 (1.4) 0.52 Best PEF(per 10% deficit) 0.6 + (1,.4) 0.65 0.6 + (1.9) 0.67 Actual/Best PEF(10% deficit) 1.3 (1.8) 0.47 0.1 (1.9) 0.94 Age at entry (per decade) (difference from age 50) Linear 2.1 + (3.7) quadratic 4.0 + (1.0) cubic 1.4 (0.6) 0.02 Duration of asthma at entry (per decade) (difference from duration 20 yrs) Linear 4.0 (2.8) 0.8 (2.8) quadratic 5.2 (1.7) 3.2 (1.8) cubic 1.46 + (0.44) 0.001 0.97 + (0.46) 0.03 (+) Indicates relative gain in function Height (not tabulated) was consistently directly associated with decline at a significance level of the order of 15% in univariate and multivariate analyses. In the latter analyses, height suppressed the associations with gender and social class. There were no significant associations with instability of regimen, nor with steroid step or the regular prescription of bronchodilators. None of the models considered made any relevant difference to the shape or gradients of the curves shown in fig 2 . 200 Subjects: decline estimated using all four observations Generally similar univariate associations were demonstrated. However on multivariate analysis, amount smoked remained in the FVC model (coefficient 13.3 ml/year per 10 pack years P = 0.020), and the effect of gender was stronger in both models (actual FEV1 23.8, actual FVC 19.8 ml/year, (P < 0.001). Height was again consistently directly associated with decrease in function at a significance level of the order of 15%. When height was included to allow for its association with gender, the difference in rate of decline in FEV1 between males and females was substantially reduced to 12.5 ml per year (p = 0.010) and was no longer significant for best FVC (p = 0.14). Discussion The hypothesis that persistent airway obstruction may develop in asthmatics implies that persistent airway obstruction and reversible obstruction associated with asthma are not mutually exclusive diagnoses However if COPD is regarded as a syndrome; this implies a non-asthmatic inflammatory process [ 5 ]. As the two types of inflammation need not be mutually exclusive, some asthmatics might have both types raising the possibility of an interaction between the two processes in some individuals, 'The Dutch Hypothesis' [ 13 ]. We have already shown that on cross sectional analysis green sputum, which is a feature of severity in COPD [ 14 ], is associated with diminished best function independent of smoking habit [ 15 ]. We are satisfied that our subjects satisfied the clinical criteria for asthma and had the relevant inflammatory process. Of course, the study is not of the entire asthmatic population as some individuals will remain undiagnosed while others will have been managed entirely in general practice, but all those referred to hospital and willing were entered into the study. We believe that the referral threshold was relatively low, and very few patients were referred outwith the local area. The subjects were recruited by a single handed hospital physician, with no other selection. There were no differences in the demography or function of those entering at different times [ 11 ]. Most were stable on maintenance corticosteroids [ 8 ]. The rate of decline of actual FEV1 was similar to that reported by Ulrik [ 1 ] (38 ml/year) and Lange [ 2 ] (50 ml/year). This study demonstrates for the first time that decline in best after bronchodilator function, the definitive physiological measurement for COPD [ 16 ], is similar to that of actual function. Actual/best PEF tended to improve over the period [ 8 ], so measurement of actual FEV1 potentially under-estimates any decline in best FEV1, but in practice loss of actual FEV1was not relevantly different from that of best FEV1. As in the previous studies [ 1 , 2 ] the rate of decline of actual FEV1 is greater than that suggested by reference equations [ 12 , 17 ] which are derived from cross-sectional data. Values derived from longitudinal data may differ from cross-sectional observations for a number of reasons [ 18 , 19 ]. These include a cohort effect and, with lung function, loss of height with ageing which will mask decline in the cross sectional tables. We allowed for loss of height by using height at the start of each 5-year period. After discounting this there was little difference between the genders, the principal association with change in function being the age of the subjects. Longitudinal studies suggest increased loss of FEV1 in elderly normal subjects [ 20 - 22 ], but the rate of decline in our study is greater at all ages than that reported from the general population [ 20 ]. Our results suggest that that a cubic model involving age is appropriate for all of the three measures of respiratory function that we have analysed. Although the pattern in a particular individual cannot be determined from these computed curves, they strongly suggest that decline is not linear. The interpretation of the pattern of change is critically dependent on its normal course. The critical points on the curve include the age at which maximum life-time function is achieved and the possibility of a plateau, before deterioration starts The age when personal best is achieved is variously estimated between the early twenties and the late thirties [ 19 ], and may well vary from person to person. In looking for a plateau phase Robbins et al [ 23 ] demonstrated both positive and negative slopes in different individuals. Any decline seen where improvement or no change is anticipated must be excessive and so the slow decline that we observed in the third decade may be an under-representation of the true loss of function. It is more difficult to explain the faster decline in early compared to late middle age. As the entry criteria of this study were a diagnosis of asthma with no attempt to exclude co-existent COPD, it is possible that this reflects a period of life when the effects of the inflammatory process associated with COPD are particularly apparent. In subjects where asthma and COPD co-exist, COPD might contribute to presentation in these subjects, and decline in function might be particularly rapid especially if there were interaction between the two inflammatory processes. The above is compatible with the apparently unsustainable rates of decline observed early in COPD as in the Euroscop study [ 24 ]. We confirmed that decline accelerates after in late life in these asthmatics as it does in normal subjects [[ 20 , 21 ], and [ 22 ]]. Outcome in successive periods is necessarily confounded by the effects of management and attrition. Attrition is particularly relevant to the analysis of change in function, as the most powerful predictor of survival in these subjects is best function [ 11 ]. Higher dose of inhaled corticosteroids at the start of an observation period was not associated with better outcome within the same period. This is unsurprising because a higher dose reflects more severe disease. More surprisingly, there was also no evidence that the higher average dose in successive periods was associated with a favourable secular trend in observed, or maximum, function. Nevertheless in contrast, actual/best peak flow improved [ 8 ] and standardised mortality declined with time [ 11 ]. The latter was reduced twofold although subjects on higher therapeutic steps remained more likely to die even after allowance for other risk factors including best function. It may be that clinicians are able to recognise subjects of poor prognosis irrespective of function, but are more successful in reducing mortality than loss of function by adjustment of therapy. None of these considerations necessarily imply that the use of inhaled corticosteroids is ineffective in terms of function. As there were, of necessity, no controls, any effect of treatment, dictated by clinical need, is impossible to confirm. Improvement in functional outcome might have been confounded by reduced mortality in those with severe disease, or the dose response curves for reduction of mortality might be very different from those for prevention of airway remodelling. We depended primarily on patient recall in making a diagnosis of childhood asthma. Although we had a low threshold for accepting the diagnosis, presumably recall would be more consistent when childhood symptoms were severe. This might produce a bias in favour of demonstrating associations. Nevertheless the univariate associations with change in function were stronger in those who claimed that they had had persistent symptoms since childhood, than in those who recalled childhood asthma after a gap of at least five years. The outcome in gap asthmatics was similar to those with adult onset, but surprisingly subjects with symptoms persistent since childhood showed a more favourable trend. This appears to be inconsistent with the long established observation that childhood asthma compromises adolescent and early adult lung function and that this is related to persistent symptoms [ 25 , 26 ]. However duration is probably the critical factor. The history of asthma is likely to be long in adults with symptoms persistent from childhood and rapid decline is shown to be associated with short duration. Although these subjects did have relatively poor lung function at entry to the study [ 10 ], probably reflecting their function on reaching maturity, it does not necessarily follow that retarded development will be succeeded by an excessive rate of decline later in life. It may be that at any age whether in childhood or adulthood the first decade of the disease is critical in determining loss of function. This might not be true in those with pure COPD, and explain why our findings are contrary to the 'horseracing effect' (the horse that runs fastest continues to extend its lead) as described by Fletcher in his classical population studies [ 27 ]. There the comparison was with normal subjects rather than those with established airway disease with differing lengths of history. The effect of smoking appeared small, but there were few current smokers and the tobacco load was light. The study was not designed to observe the effects of tobacco smoking in asthma; the separate analysis of non-smokers was intended to describe the decline in the function of asthmatics unencumbered by the effects of cigarette smoking. It is inevitable that we have underestimated the potential association between smoking and decline in function in asthma and so do not suggest that the effect of smoking in asthmatics in general is unimportant. The association between low initial actual/best function, implying poor control, and apparently favourable outcome is highly likely to reflect response to treatment. There was a strong relationship between low social class and poor control in the 1983 entry [ 10 ]. This may account for some of the paradoxical benefit of lower social class, possibly even hiding a real disadvantage. Conclusions We present the decline in function in a dynamic cohort of adult asthmatics observed over fifteen years. The majority were treated with inhaled corticosteroids throughout the period. As there are no internal asthmatic or normal controls our study cannot determine definitively whether there is excess decline in the pulmonary function of adults managed conventionally with inhaled cortico-steroids. It does suggest, however, that the dose of inhaled steroids may not be critical over the recommended range. Our study confirms that the pattern of decline in actual and best ventilatory function is similar. This is important when comparing this study with epidemiological exercises where actual rather than best function has been measured. Furthermore these original findings in respect of the cubic effect of age should be taken into account when interpreting other articles reporting age effects on function, particularly where analysis of cross-sectional observations may imply that decline in the function is linear. Competing interests The author(s) declare that they have no competing interests. Authors' contributions CKC conceived the study and was responsible for design of data forms, recruitment and all the clinical aspects. RJP undertook the analysis of data. Both authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC549563.xml
514499	Stress echocardiography in heart failure	Echocardiography has the ability to noninvasively explore hemodynamic variables during pharmacologic or exercise stress test in patients with heart failure. In this review, we detail some important potential applications of stress echocardiography in patients with heart failure. In patients with coronary artery disease and chronic LV dysfunction, dobutamine stress echocardiography is able to distinguish between viable and fibrotic tissue to make adequate clinical decisions. Exercise testing, in combination with echocardiographic monitoring, is a method of obtaining accurate information in the assessment of functional capacity and prognosis. Functional mitral regurgitation is a common finding in patients with dilated and ischaemic cardiomyopathy and stress echocardiography in the form of exercise or pharmacologic protocols can be useful to evaluate the behaviour of mitral regurgitation. It is clinical useful to search the presence of contractile reserve in non ischemic dilated cardiomyopathy such as to screen or monitor the presence of latent myocardial dysfunction in patients who had exposure to cardiotoxic agents. Moreover, in patients with suspected diastolic heart failure and normal systolic function, exercise echocardiography could be able to demonstrate the existence of such dysfunction and determine that it is sufficient to limit exercise tolerance. Finally, in the aortic stenosis dobutamine echocardiography can distinguish severe from non-severe stenosis in patients with low transvalvular gradients and depressed left ventricular function.	Background The identification of viable hibernating myocardium in patients with coronary artery disease and chronic left ventricular (LV) dysfunction is, up to today, the most common use of stress echocardiography in patients with heart failure. However, to search viable myocardium or the presence of contractile reserve is only one of plugs of the physiopathologic puzzle in a failing heart (Figure 1 and 2 ). If we consider the ability of echocardiography to provide valuable haemodynamic information accurately and non-invasively, it is ideally suited for application during stress testing to objectively assess other physiopathologic components of heart failure. These include the study of exercise physiology, the presence and the behaviour of concomitant mitral regurgitation (MR), the prediction of response to resynchronization therapy etc. Figure 1 Physiopathologic components of systolic heart failure that can be potentially explored with stress echocardiography. Figure 2 Physiopathologic components of diastolic heart failure assessable with stress echo. Therefore, the present review will detail some important potential applications of stress echocardiography in patients with heart failure in the evaluation of the different clinical and physiopathologic aspects of heart failure syndrome. Systolic heart failure Searching the myocardial viability The most common cause of heart failure in the Western world is coronary artery disease, accounting for up to 60% of cases [ 1 ]. In patients with coronary artery disease and chronic LV dysfunction, it is crucial to distinguish between viable and fibrotic tissue to make adequate clinical decisions. Noncontractile but viable myocardium may correspond to different states that are important but difficult to distinguish, i.e., ischemia, stunning, nontransmural infarction, or hibernation and in individual patients these pictures may coexist [ 2 ]. After brief episodes of coronary occlusion and reflow a reversible global LV dysfunction can occur. This phenomenon was called myocardial stunning [ 3 ]. It is characterized as prolonged mechanical dysfunction after coronary reflow despite resumption of normal perfusion and lack of permanent tissue damage. Stunning seems to result from alterations in contractile proteins in response to sublethal ischemic insults. This phenomenon can occur in several settings, including after acute reperfused myocardial infarction and after CABG. In humans, the return of functional recovery may require days to weeks [ 4 ]. Hence, diagnostic methods to distinguish stunning from necrosis are particularly relevant for clinical investigation and management in patients with acute, severe LV dysfunction or cardiogenic shock after revascularization. Persistent wall motion abnormalities can be observed by echocardiography at a time when chest pain, ST segment deviation, and regional perfusion had recovered. The presence of contractile reserve during dobutamine infusion identifies the stunning but viable myocardium from myocardial necrosis. The term " Hibernating myocardium " was first termed by Rahimtoola to indicate the state of reversible dysfunctional myocardium, which was considered to be the result of a state of persistently impaired myocardial function at rest, caused by reduced coronary blood flow, and which could be partially or completely restored to normal either by improving blood flow or reducing oxygen demand [ 5 ]. Echocardiography can detect viable myocardium during infusion of drugs which have ability to elicit an enhanced contractile response by recruiting contractile proteins. At least two drugs have these proprieties: the dobutamine, a synthetic β1 agonist with additional α1- and β2-stimulating properties and the enoximone that inhibits cyclic adenosine monophosphate-specific phosphosdiesterase [ 6 , 7 ]. Routinely, the dobutamine is the most common stressor used, whereas the enoximone is particularly useful in patients on beta-blocker therapy [ 7 , 8 ]. The mechanism by which dobutamine stimulation elicits a contractile response in hypoperfused dysfunctional segments without precipitating ischemia has been demonstrated by Sun et al. [ 6 ]. By using positron emission tomography and echocardiography, they demonstrated that the improvement in contractile function during dobutamine infusion was associated with a concomitant increase in myocardial blood flow. The increase in myocardial blood flow occurs because there is persistent, albeit reduced, coronary flow reserve distal to a stenosis which dobutamine may exploit. Another mechanism whereby contractile response may be elicited during dobutamine infusion is through its peripheral vasodilator effect, which causes reduction in LV end-systolic wall stress by reducing afterload [ 6 ]. Moreover, dipyridamole echocardiography (up to 0.84 mg/kg over 10 minutes) can identify regions with myocardial viability [ 9 ]. Dipyridamole leads to transiently increased coronary flow, which leads to improved contractility in viable myocardium [ 9 ]. A small study comparing dipyridamole with dobutamine revealed 93% concordance [ 10 ]. Combined dipyridamole-dobutamine (low-dose dipyridamole followed by low-dose dobutamine) has also been proposed and found to recruit a contractile reserve in some asynergic segments that were nonresponders after dobutamine or dipyridamole alone [ 11 ]. An initial evaluation of end diastolic wall thickness of akinetic segments with resting echocardiography can be used as an initial screening technique for assessment of viability. Indeed, akinetic regions with an end diastolic wall thickness <6 mm do not contain viable myocardium and do not improve in function after revascularization [ 12 ]. However, in segments with a thickness ≥ 6 mm, additional testing is needed because approximately 40% of these regions do not contain viable myocardium and will not improve after revascularization [ 12 ]. Therefore, myocardial thinning should not be equated with the lack of myocardial viability, and in some patients, these regions can improve in contractile function after revascularization [ 13 ]. The detection of subendocardial infarcts became clinically relevant because the quantification of non-viable myocardium in addition to viable myocardium in that region of LV is important in predicting contractile improvement following revascularization. Thus, the ratio of viable to total myocardium (viable plus non-viable) in the dysfunctional region was more accurate that absolute amount of viable myocardium alone in predicting functional improvement [ 13 ]. Unfortunately, currently available techniques, such as single photon emission computed tomography, dobutamine stress echocardiography and positron emission tomography are still insufficient to provide a comprehensive assessment including the evaluation of subendocardial infraction with respect to magnetic resonance imaging [ 14 ]. During stress echocardiography is possible to observe four response patterns based on regional wall function: normal, ischemic, viable and necrotic. In the normal response, a segment is normokinetic at rest and normal or hyperkinetic during stress. In the ischemic response, a segment worsens its function during stress from normokinesis to dyssynergy. In the necrotic response, a segment akinesia remains akinetic during stress. In the viability response, a segment with resting dysfunction improves during stress. During pharmacologic stress, a viable response at low dose can be followed by ischemic response at high dose (biphasic response). This biphasic response is suggestive of viability and ischemia, with jeopardized myocardium fed by a critically stenosed coronary artery [ 15 ]. A resting akinesia which becomes dyskinesia during stress reflects a purely passive mechanical phenomenon and should not be considered a true active ischemia. The overall sensitivity and specificity of dobutamine echocardiography for predicting recovery of regional function after revascularization was 84% and 81% respectively [ 16 ]. In a study by Afridi et al., the best predictive value for recovery of function after revascularization was most often noted in patients demonstrating an ischemic response during low and high doses of dobutamine infusion [ 17 ]. On the other hand, sustained improvement of regional function during dobutamine infusion was a poor marker of recovery function. Sensitivity of dobutamine echocardiography may be affected by several factors such as the severe reduction of myocardial blood flow that can preclude the contractile response, the premature interruption of dobutamine infusion, resting tachycardia that may renders the myocardium ischemic and dobutamine can only augment ischemia [ 16 ]. On the contrary, the specificity may be affected by the tethering effect, the injured subendocardial portion of myocardium that does not respond to dobutamine when the infarction is confined to subendocardium, and also specificity may be reduced in myocardial regions that do not develop an ischemic response [ 16 ]. The main clinical issue to search the myocardial viability is that patients with evidence of hibernating myocardium who do not undergo revascularization have poor prognosis with high incidence of cardiac events [ 18 ]. In contrast, evidence of viable myocardium in patients undergoing successful revascularization is associated with longer survival and improvement of both symptoms and LV function [ 19 ]. However, the presence of myocardial viability is only relevant in patients with severely depressed LV function and has a prognostic impact only when a significant amount of viable myocardium is present. Therefore, the final end point of searching the myocardial viability is to predict the recovery of global myocardial function after revascularization. At this purpose there is a relation between improvement in left ventricular ejection fraction (LVEF) and the number of segments with contractile reserve, indicating that extent of jeopardized but viable myocardium determine the magnitude of improvement of LV function after revascularization. Usually a level of ≥ 4 viable segments, which corresponds an improvement in wall motion score index >0.25 (about 20% of left ventricle), is advised as a cutoff value to predict improvement of LVEF [ 20 ]. However, despite the presence of substantial viability, in some patients LVEF does not improve after revascularization because not only the amount of dysfunctional but viable tissue but also LV remodelling and enlargement determines the improvement in function following revascularization [ 21 ]. Thus, patients with a high end systolic volume (≥ 140 ml) due to LV remodelling have a low likelihood of improvement of global function [ 21 ] (Figure 3 ). Figure 3 A schematic flow chart for searching segmental and global systolic function in chronic ischemic LV dysfunction. Assessing the functional capacity In most patients with chronic heart failure, symptoms are not present at rest but become limiting with exercise. Despite this, the major measures used to characterise the symptoms, the severity, the mechanisms and the prognosis of heart failure are obtained at rest. Exercise testing, in combination with echocardiographic monitoring, may be an attractive and practical method of obtaining accurate information which can aid in the diagnosis of heart failure as well as the assessment of functional limitation and prognosis. Exercise rather than dobutamine is the stressor of choice to evaluate functional capacity due to the possibility to combine echocardiographic variables with common parameters available during physiologic exercise. Symptom limited exercise testing can be undertaken using either treadmill or bicycle exercise protocols. Available data about the safety of exercise testing in patients with significant heart failure suggest a very low incidence of serious adverse events such as arrythmias or hypothension. The echocardiographic monitoring during exercise testing may have an additional value overt the conventional parameters assessed during exercise testing such as functional capacity, symptoms and peak oxygen uptake that become part of the final interpretation. Indeed, several haemodynamic parameters can be noninvasively obtained with echocardiography such as LVEF at rest and during stress deriving the contractile reserve, the behaviour of mitral valve function, the pulmonary artery pressure, the right ventricular function, the diastolic function (Table 1 ). In this way, it is possible to observe the variation of the monitored variables and to correlate these with the appearance of symptoms, i.e. impairment of global contractile function followed by increase in pulmonary pressure with dyspnoea. The critical level to define the presence of contractile reserve is generally defined as an increase of at least 5% (in absolute terms) in the global LVEF [ 22 ] (Figure 4 ). The change in the systolic pulmonary artery pressure (sPAP) at rest and during exercise is among others, the most frequently utilized echocardiographic variable. It can reliably be estimated by adding the right atrial pressure derived from the tricuspid reguritation jet velocity [ 23 ]. The right atrial pressure can be estimated at rest by the response of inferior vena cava to deep inspiration and assumed to be constant throughout exercise. Sometimes the use of echocardiographic contrast agents such as agitated saline solution may help to enhance Doppler signals. Pulmonary hypertension determined by echocardiography has been defined as a peak of sPAP >30 mmHg at rest and >45 mmHg during exercise [ 24 ]. Right ventricular dysfunction predicts impaired exercise capacity and decreased survival in patients with both moderate and advanced heart failure [ 25 ]. There are several clinically validated methods to detect right ventricular dysfunction. Tricuspid annular plane systolic excursion (TAPSE) visualized from the apical four-chamber view is an easy measure and can be used a surrogate of right ventricular function. A TAPSE value of 14 mm or less means the presence of right ventricular dysfunction and is a significant adverse prognostic indicator [ 26 ]. More recently, the evalution of tricuspid systolic annular tissue Doppler velocity has been introduced as index of right ventricular function and a value less than 10.8 cm/s indicates patients with abnormal right ventricular function [ 27 ]. Table 1 Potential parameters obtainable during exercise echocardiography. Common variables during exercise test Additional echocardiographic variables during exercise test Duration of exercise Contractile reserve Peak VO2 Mitral valve function Anaerobic threshold Pulmonary systolic pressure Oxygen pulse Right ventricular function VO2 workload ratio Diastolic function O2 saturation Figure 4 Echocardiographic apical four-chamber images (end-systolic frames) from two patients with and without contractile reserve. Moreover, these evaluations are useful not only for the diagnosis but also for predicting the outcome of patients overt the symptoms of heart failure. Indeed, some patients with marked reduction in myocardial contractility at rest, but with good residual contractile reserve, have a favourable exercise capacity and prognosis, whereas patients with mild symptoms and similar degree of abnormal myocardial contractility at rest, but without contractile reserve, have poor outcome [ 28 ]. Although a VO2max <14 ml/kg/min is well known as a measure for deciding on eligibility for cardiac transplantation, it has been clearly shown that there is no absolute threshold for adverse prognosis and that VO2max uptake should be considered as a continuous variable. In term of discriminating survivors from non survivors, it appears that VO2max <10 ml/kg/min definitively defines high risk, while a value >18 ml/kg/min defines low risk; those values in between may represent a grey zone. Thus stress echocardiography yields the greatest incremental prognostic value in patients with intermediate values of VO2max (10–14 ml/Kg/min) and helps to further stratify the risk of patients with intermediate (Table 2 ) [ 29 ]. Table 2 Additive prognostic value of stress echo in patients with intermediate values of VO2max (10–14 ml/Kg/min). Risk Low (5–10% year) High (≥ 25–30% year) Exercise capacity ≥ 8–10 min <8 min Contractile reserve yes no Pulmonary hypertension <45 mmHg >45 mmHg Right ventricular dysfunction no yes Mitral regurgitation ↓ or = ↑↑ Looking at the behaviour of mitral valve MR is a common finding in heart failure patients. In patients with dilated and ischaemic cardiomyopathy, the MR is typically functional and reflects geometric distortions of LV chamber, which displaces the normal valve and subvalvar closing mechanisms. This functional MR is a consequence of adverse LV remodelling and increased sphericity of the chamber. It is typically dynamic and a marker of adverse prognosis. The 5-year survival of heart failure patients with functional MR ranges from 39.9% to 48.7% depending on the degree of MR [ 30 ]. Stress echocardiography in the form of exercise or pharmacologic protocols can be useful in the assessment of MR. Exercise echocardiography is usually preferred due to the possibility to reproduce physiological setting. Even though supine bike protocol allows to obtain good image acquisition, upright bicycle or treadmill protocols are more frequently utilized in the practical setting. Treadmill exercises can be performed using the standard protocols such as Bruce or modified Bruce, while gradual increase in the bike workload of 20–25 W every 2–3 minutes is often applied until the patients achieves either the target heart rate or develops symptoms of fatigue or shortness of breath. Sometimes, pharmacologic stress is used with dobutamine protocol at low or intermediate doses infusion. In the collection of echocardiographic data should be included: the MR jet to evaluate the MR jet area and the vena contracta width, the velocity time integrals (mitral and aortic) to calculate the regugitant volume and the effective regurgitant orifice area (EROA), the LV volumes to assess the myocardial contractility and the tricuspid regurgitant jet velocity to measure the sPAP that is an useful index of the haemodynamic burden of MR. Exercise echocardiography can play several roles in the assessment of the behaviour of mitral valve in heart failure patients. First , in symptomatic patients with LV dysfunction and a clinical picture suspicious for new or worsening MR, but not evident at resting echo examination, exercise echocardiography can demonstrate a worsening of MR which helps to correlate this scenario with the patient's symptoms (Figure 5 ) [ 31 ]. Second , LV contractility, in presence of MR, can impair or improve during exercise with consequent modification of MR. Patients with presence of contractile reserve show a decrease in MR [ 32 ], whereas generally a fall in stroke volume is associated with an increase in mitral regurgitant volume during isometric exercise, which increases systemic resistances and thereby afterload [ 33 ]. These observations support the concept of presence of a vicious circle between LV function and behaviour of MR. Therefore, to study these patients with exercise echocardiography may be important for assessing the response of MR to medical therapy and for the following prognostic implications. Indeed, third , in patients with ischemic MR and LV dysfunction, quantitative assessment of exercise-induced changes in the degree of MR provides independent prognostic information. Significant exercise-induced increases in MR (increase in ERO ≥ 13 mm 2 ) unmask patients at high risk of poor outcome. The cardiac mortality rate of medically treated patients with dynamic MR during exercise is 39% at 20 months which represents excess mortality in patients in functional class II or III (Figure 6 ) [ 34 ]. Figure 5 Apical four-chamber view at rest and during exercise in patients with ischemic mitral regurgitation showing a large exercise-induced increase in mitral regurgitation. SPAP = Systolic pulmonary pressure. Figure 6 Relationship between contractile reserve, mitral regurgitation and pulmonary pressure and its contribution in defining the prognosis in patients with functional mitral regurgitation. MR = mitral regurgitation; sPAP = systolic pulmonary pressure. Finally, dobutamine protocol has a different role in the contest of ischemic MR. Generally, in this setting it is used to evaluate the behaviour of MR in relation with the presence or absence of myocardial viability (Figure 7 ). Dobutamine infusion has the ability to decrease MR volume due to a reduction of afterload and mitral orifice size that may occur as a result of the vasodilatory and inotropic effects of dobutamine [ 35 , 36 ]. Therefore, if during dobutamine protocol we find myocardial viability and a concomitant reduction of MR, these results should be interpreted with caution because we cannot assume a direct effect of the presence of myocardial viability on the MR. Thus, the complex interplay between haemodynamic effects of dobutamine, myocardial viability and behaviour of MR has to be taken in mind during clinical management of patient with LV dysfunction and ischemic MR, i.e. revascularization alone versus revascularization plus mitral valve surgery. Figure 7 Targets and effects of dobutamine stress echo in patients with mitral regurgitation and chronic ischemic left ventricular dysfunction. EROA = Effective regurgitant orifice area. Evaluating the contractile reserve beyond hibernating myocardium It is commonly believed that the assessment of contractile reserve is only confined and clinically useful to search the myocardial viability in patients with LV dysfunction and coronary artery disease. Growing published data suggest the utility in searching the presence of contractile reserve in non ischemic dilated cardiomyopathy (DCM). While in the ischemic cardiomyopathy the search of myocardial viability is focused to find the presence of reversible segmental myocardial dysfunction and its possible effect on global systolic LV recovery after revascularization, in DCM the primary end point is to evaluate the presence of residual global contractile reserve. Both dobutamine and exercise testing have been used in the study patients with DCM, but there is a clear predominance for the use of dobutamine test. The doses of dobutamine utilized vary from investigators, but safety in its use in this population has been documented in doses as high as 40 μg/kg per minute. In the interpretation of results both wall motion score index and the LV volume to derive LVEF must be calculated. LV systolic function at the time of diagnosis has been proposed to be the strongest predictor of survival in DCM, but now the presence of contractile reserve recognised by dobutamine echocardiography seems to be the best marker of good prognosis in patients with severe LV dysfunction at rest [ 37 , 38 ]. Patients with significant improvement in their wall motion score index and LVEF during dobutamine infusion have a better survival rate and increase in the LVEF during follow-up period [ 37 ]. The data extracted from dobutamine study can be used as an adjunct or alternative to predict VO2max and exercise capacity of patients with heart failure, especially when the patients fall into the gray zone of VO2max (10–14 ml/kg/min) or when there is limitation to ambulation [ 29 ]. Moreover, the response to dobutamine infusion predicts the improvement in LVEF with beta-blocker therapy in patients with advanced heart failure. Patients with contractile reserve experienced a greater improvement in LVEF with beta-blocker by biologically augmenting myocyte a chamber contractility [ 39 ]. Whereas, in the absence of contractile reserve (when myocytes have been replaced by fibrosis), ventricular function cannot improve by this biological mechanism because there are not enough contractile units and the sympatholytic effects of beta-blocker prevail [ 39 ]. However, the clinical use of dobutamine stress echocardiography in patients with chronic heart failure may be limited by a substantial proportion of patients already receiving beta-blocker therapy at time of evaluation. In these patients enoximone echocardiography might be a valid alternative to low-dose dobutamine for evaluating contractile reserve showing a more potent and a better safety profile than dobutamine [ 8 ]. Stress echocardiography may also help in the identification of patients in the initial phase of cardiomyopathy overt normal resting echocardiographic parameters. Both dobutamine and exercise have to be used to screen for the presence of latent myocardial dysfunction in patients who had exposure to cardiotoxic agents [ 40 ]. Diastolic heart failure The prevalence of diastolic heart failure in the community is now to be at least as high as that reported in previous studies of hospitalised patients; almost half of all patients with heart failure have diastolic heart failure [ 41 ]. The term asymptomatic diastolic dysfunction is used to refer to an asymptomatic patient with a normal LVEF and abnormal echo-Doppler pattern of LV filling; this is often seen, for example, in patients with hypertensive heart disease. If such patients exhibit symptoms of effort intolerance and dyspnoea, especially if there are evidence of venous congestion and edema, the term diastolic heart failure can be used [ 42 ]. Resting echocardiography is most useful in the assessment of LV size, LVEF and the use of Doppler-derived indices of diastolic function has impact on the identification of diastolic dysfunction. However, to determine whether an abnormality of diastolic function is the cause of the patient's symptoms, we need to demonstrate the existence of such dysfunction and determine that it is sufficient to limit exercise tolerance. Therefore, the stress echocardiography, in particular exercise echocardiography could be useful in dyspnoeic patients with apparently normal LV function to unmask the presence of diastolic dysfunction (signs of elevated LV filling pressure) during exercise as cause of symptoms. Patients with diastolic heart failure, as well as those with diastolic dysfunction and little or no congestion, exhibit exercise intolerance for several reasons. First, an elevated LV diastolic and pulmonary venous pressure during exercise causes reduction in lung compliance, which increases work of breathing and evokes the symptom of dyspnoea [ 42 ]. Second, a substantial number of patients who have LV hypertrophy, high relative wall thickness and small end diastolic volume exhibit a low stroke volume and a depressed cardiac output [ 43 ]. These hearts exhibit a limited ability to utilize the Frank-Starling mechanism during exercise. Such limited preload reserve, specially if coupled with the chronotropic incompetence limits the cardiac output during exercise [ 44 ]. Third, elevated LV diastolic and pulmonary venous pressures in patients with normal LVEF are directly related to abnormalities in the diastolic proprieties of the ventricle. This is not to say contractile function is entirely normal, but subtle and latent abnormalities of contractile function could be present in many patients, in whom, however, diastolic dysfunction is the dominant feature [ 42 ]. All these aspects can be assessed during exercise echocardiography (Table 3 ). In particular the assessment of diastolic function during exercise has been shown to be feasible [ 45 ]. Combining transmitral flow velocity with annular velocity obtained at level of the mitral annulus with tissue Doppler (E/E') has been proposed as a tool for assessing LV filling pressures that combines the influence of transmitral driving pressure and myocardial relaxation [ 46 ]. Patients with rest E/E' >15 can be classified as having elevated filling pressure. A rest E/E' <8 suggests normal filling pressure and a range of 8 to 15 represents a gray zone. E and E' velocities increased significantly after exercise. In normal subjects because of proportional increases of both velocities, the E/E' ratio do not change significantly with exercise; this observation can be taken as a normal diastolic response during exercise [ 45 ]. Indeed, if E/E' ratio increases up to 15 we can suppose a pathological increase of LV filling pressure during exercise. This evaluation must be associated to the assessment of cardiac output and sPAP during exercise with appearance of symptoms. Finally, with the evaluation of systolic LV function during exercise it is possible to discover the portion of patients with concomitant latent myocardial dysfunction but predominant diastolic abnormality (Figure 8 ). Table 3 Useful echocardiographic parameters to evaluate diastolic function during exercise test in patients with suspected diastolic heart failure. Transmitral Doppler indices E/E' ratio Cardiac output Preload reserve Contractile reserve Pulmonary systolic artery pressure Figure 8 Schematic diagnostic algorithm in patients with suspected diastolic heart failure. LV = Left ventricle; LVEF = Left ventricular ejection fraction. Aortic stenosis with left ventricular dysfunction Stress echocardiography with dobutamine infusion is particularly useful in clinical decision making in patients with aortic stenosis with LV dysfunction and low transvalvular gradients. In this group of patients, an important clinical question rises: is the low gradient a consequence of low cardiac output due to a severe aortic stenosis which has led to LV dysfunction or is the low gradient a consequence of LV dysfunction is unrelated to aortic stenosis and the aortic stenosis is an incidental finding? It is well known that the transvalvular gradients are flow-depentent parameters so that they are influenced by LV function. The aortic valve area can be accurately determined by Doppler echocardiography with continuity equation and that correlate well with Gorlin formula [ 47 ]. However, it has been shown that valve areas calculated by the Gorlin formula is flow-dependent and usually increase with flow, probably due to the flow dependence of the empirical constant C of the Gorlin formula, which represents the ratio of effective to anatomical orifice area. Burwash et al., with dobutamine stress-echocardiography, demonstrate a flow-dependent increase in actual orifice aortic valvular area calculated with continuity equation [ 48 ]. Therefore, the assessment of valve area does not solve the diagnostic dilemma in these patients, because we cannot distinguish between severe fixed from flow-dependent (relative) aortic stenosis. Thus, it is important to perform pharmacological manoeuvres to increase cardiac output so that valve area can be calculated at higher flow rate. Dobutamine stress echocardiography until 20 γ/kg/min with concomitant evaluation of cardiac output, aortic valve area and gradients, is a useful and reliable test to distinguish between severe fixed from relative aortic stenosis in presence of low gradient and LV dysfunction. On the basis on test results, it is possible to distinguish 3 groups of patients [ 49 ] (Figure 9 ): 1. Patients with an improvement of contractile function but no significant increase in valve area and an increase of transvalvular gradients. These patients have severe fixed aortic stenosis and are good candidate for surgery with an acceptable peri-operative surgical risk. 2. Patients with contractile reserve with an increase of aortic valve area without substantial increase in transvalvular gradients. These patients have a non critical aortic stenosis and the LV dysfunction is not related to the aortic stenosis and should be treated conservatively. 3. Finally, patients without contractile reserve and no modification of valve area and transvalvular gradients. These patients represent an ambiguous group, because can represent patients with end-stage severe aortic stenosis with severe LV dysfunction or patients with severe LV dysfunction without contractile reserve and incidental aortic stenosis. However, this group has very poor prognosis. Figure 9 Possible results during dobutamine stress echocardiography in presence of aortic stenosis, low cardiac output and low transvalvular gradients. AVA: Aortic valve area; CO: Cardiac output. When interpreting the results of a dobutamine study in these patients to rule out or confirm definitively the presence of a severe fixed aortic stenosis, it is advisable to use an absolute cut-off value of the aortic valve area at peak of dobutamine >1 cm 2 rather than an increase of ≥ 0.3 cm 2 from baseline alone [ 49 , 50 ]. Conclusions Beyond the identification of viable hibernating myocardium, stress echocardiography is particular useful in patients with systolic and diastolic heart failure to assess the different physiopathologic component of heart failure syndrome and can aid to an appropriate clinical decision making. List of abbreviations LV : left ventricular MR: mitral regurgitation LVEF: left ventricular ejection fraction DCM: dilated cardiomyopathy TAPSE : Tricuspid annular plane systolic excursion sPAP : Systolic pulmonary artery pressure Competing interests The manuscript is not under consideration elsewhere and the data presented have not been previously published. All authors have read and approved the manuscript. No financial support was received for this study. The content of this manuscript is not associated with any financial interest or other relations that could lead to a conflict of interest. Author's contribution Concerning the authorship, the listed authors have contributed as follows to the manuscript: EA and MP: 1) conception, design, analysis and interpretation of data, 2) drafting of the manuscript and 3) final approval of the manuscript MO and AM: 1) critical revision of the manuscript for important intellectual content, and 3) final approval of the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514499.xml
539279	Proportional odds ratio model for comparison of diagnostic tests in meta-analysis	Background Consider a meta-analysis where a 'head-to-head' comparison of diagnostic tests for a disease of interest is intended. Assume there are two or more tests available for the disease, where each test has been studied in one or more papers. Some of the papers may have studied more than one test, hence the results are not independent. Also the collection of tests studied may change from one paper to the other, hence incomplete matched groups. Methods We propose a model, the proportional odds ratio (POR) model, which makes no assumptions about the shape of OR p , a baseline function capturing the way OR changes across papers. The POR model does not assume homogeneity of ORs, but merely specifies a relationship between the ORs of the two tests. One may expand the domain of the POR model to cover dependent studies, multiple outcomes, multiple thresholds, multi-category or continuous tests, and individual-level data. Results In the paper we demonstrate how to formulate the model for a few real examples, and how to use widely available or popular statistical software (like SAS, R or S-Plus, and Stata) to fit the models, and estimate the discrimination accuracy of tests. Furthermore, we provide code for converting ORs into other measures of test performance like predictive values, post-test probabilities, and likelihood ratios, under mild conditions. Also we provide code to convert numerical results into graphical ones, like forest plots, heterogeneous ROC curves, and post test probability difference graphs. Conclusions The flexibility of POR model, coupled with ease with which it can be estimated in familiar software, suits the daily practice of meta-analysis and improves clinical decision-making.	Background A diagnostic test, in its simple form, tries to detect presence of a particular condition (disease) in a sample. Usually there are several studies where performance of the diagnostic test is measured by some statistic. One may want to combine such studies to get a good picture of performance of the test, a meta-analysis. Also, for a particular disease there may be several diagnostic tests invented, where each of the tests is subject of one or more studies. One may also want to combine all such studies to see how the competing tests are performing with respect to each other, and choose the best for clinical practice. To pool several studies and estimate a summary statistic some assumptions are made. One such assumption is that differences seen between individual study results are due to chance (sampling variation). Equivalently, this means all study results are reflecting the same "true" effect [ 1 ]. However, meta-analysis of studies for some diagnostic tests show that this assumption, in some cases, is not empirically supported. In other words, there is more variation between the studies that could be explained by random chance alone, the so-called "conflicting reports". One solution is to relax the assumption that every study is pointing to the same value. In other words, one accepts explicitly that different studies may correctly give "different" values for performance of the same test. For example, sensitivity and specificity are a pair of statistics that together measure the performance of a diagnostic test. One may want to compute an average sensitivity and an average specificity for the test across the studies, hence pooling the studies together. Instead, one may choose to extract odds ratio (OR) from each paper (as test performance measure), and then estimate the average OR across the studies. The advantage is that widely different sensitivities (and specificities) can point to the same OR. This means one is relaxing the assumption that all the studies are pointing to the same sensitivity and specificity, and accepts that different studies are reporting "truly different" sensitivity and specificity, and that the between-study variation of them is not due to random noise alone, but because of difference in choice of decision threshold (the cutoff value to dichotomize the results). Therefore the major advantage of OR, and its corresponding receiver-operating-characteristic (ROC) curve, is that it provides measures of diagnostic accuracy unconfounded by decision criteria [ 2 ]. An additional problem when pooling sensitivities and specificities separately is that it usually underestimates the test performance [[ 3 ], p.670]. The above process may be used once more to relax the assumption that every study is pointing to the same OR, thus relaxing the "OR-homogeneity" assumption. In other words, in some cases, the remaining variation between studies, after utilizing OR as the summary performance measure, is still too much to be attributed to random noise. This suggests OR may vary from study to study. Therefore one explicitly assumes different studies are measuring different ORs, and that they are not pointing to the same OR. This difference in test performance across studies may be due to differences in study design, patient population, case difficulty, type of equipment, abilities of raters, and dependence of OR on threshold chosen [ 4 ]. Nelson [ 5 ] explains generating ROC curves that allow for the possibility of "inconstant discrimination accuracy", a heterogeneous ROC curve (HetROC). This means the ROC curve represents different ORs at different points. This contrasts with the fact that the homogeneous-ROC is completely characterized by one single OR. There are a few implementations of the heterogeneous ROC. One may classify them into two groups. The first group is exemplified by Tosteson and Begg [ 6 ]. They show how to use ordinal regression with two equations that correspond to location and scale. The latent scale binary logistic regression of Rutter and Gatsonis [ 4 ] belong to this group. The second group contains implementations of Kardaun and Kardaun [ 7 ], and Moses et al [ 8 ]. Moses et al explain a method to plot such heterogeneous ROC curve under some parametric assumptions, and they call it summary ROC (SROC). When comparing two (or more) diagnostic tests, where each study reports results on more than one test, the performance statistics (in the study results) are correlated. Then standard errors computed by SROC are invalid. Toledano and Gatsonis [ 9 ] use the ordinal regression model, and account for the dependency of measurements by generalized estimating equations (GEE). However, to fit the model they suggest using a FORTRAN code. We propose a regression model that accommodates more general heterogeneous ROC curves than SROC. The model accommodates complex missing patterns, and accounts for correlated results [ 10 ]. Furthermore, we show how to implement the model using widely available statistical software packages. The model relaxes OR-homogeneity assumption. In the model, when comparing two (or more) tests, each test has its own trend of ORs across studies, while the trends of two tests are (assumed to be) proportional to each other, the "proportional odds ratio" assumption. We alleviate dilemma of choosing weighting schemes such that do not bias the estimates [[ 11 ], p.123], by fitting the POR model to 2-by-2 tables. The model assumes a binomial distribution that is more realistic than a Gaussian used by some implementations of HetROC. Also, it is fairly easy to fit the model to (original) patient level data (if available). Besides accounting better for between-study variation, we show how to use the POR model to "explain why" such variation exists. This potentially gives valuable insights and may have direct clinical applications. It may help define as to when, where, how, and on what patient population to use which test, to optimize performance. We show how to use "deviation" contrast, in parameterization of categorical variables, to relax the restriction that a summary measure may be reported only if the respective interaction terms in the model are insignificant. This is similar to using grand mean in a "factor effects" ANOVA model (compared to "cell means" ANOVA model). We show how to use nonparametric smoothers, instead of parametric functions of true positive rate (TPR) and/or false positive rate (FPR), to generate heterogeneous ROC for a single diagnostic test across several studies. Our proposed POR model assumes the shape of the heterogeneous ROC curve is the same from one test to the other, but they differ in their locations in the ROC space. This assumption facilitates the comparison of the tests. However, one may want to relax the POR assumption, where each test is allowed to have a heterogeneous ROC curve with a different shape. One may implement such generalized comparison of the competing diagnostic tests by a mixed effects model. This may improve generalizability of meta-analysis results to all (unobserved) studies. Also, a mixed effects model may take care of remaining between-study variation better. Methods Average difference in performances To compare two diagnostic tests i and j, we want to estimate the difference in their performance. However, in reality such difference may vary from one paper (study) to the other. Therefore Δ i,j,p = PERF i,p - PERF j,p , where the difference Δ depends on paper index p, where PERF i,p is observed performance of test i in paper p. To simplify notation, assume that a single number measures performance of each test in each paper. We relax this assumption later, allowing for the distinction between the two types of mistakes (FNR and FPR, or equivalently TPR and FPR). We decompose the differences (1) Δ i,j,p = PERF i,p - PERF j,p = δ i,j + δ i,j,p , where δ i,j is the 'average' difference between the two tests, and δ i,j,p is deviation of the observed difference within paper p from the average δ i,j . The δ i,j is an estimator for the difference between performance of the two tests. Note by using deviation parameterization (similar to an ANOVA model) [[ 12 ], pp.51 & 45] we explicitly accept and account for the fact that the observed difference varies from one paper to the other, while estimating the 'average' difference. This is similar to a random-effects approach where a random distribution is assumed for the Δ i,j,p and then the mean parameter for the distribution is estimated. In other words, one does not need to assume 'homogeneous' difference of the two tests across all the papers, and then estimate the 'common' difference [ 13 ]. The observed test performance, PERF, may be measured in several different scales, such as paired measures sensitivity and specificity, positive and negative predictive values, likelihood ratios, post test odds, and post test probabilities for normal and abnormal test results; as well as single measures such as accuracy, risk or rate ratio or difference, Youden's index, area under ROC curve, and odds ratio (OR). When using OR as the performance measure, the marginal logistic regression model (2) logit(Result pt ) = β 0 + β 1 * Disease pt + β 2 * PaperID pt + β 3 * Disease pt * PaperID pt + β 4 * TestID pt + β7 * Disease pt * TestID pt + β 6 * TestID pt * PaperID pt + β 7 * Disease pt * TestID pt * PaperID pt implements the decomposition of the performance. Model (2) is fitted to the (repeated measures) grouped binary data, where the 2-by-2 tables of gold-standard versus test results are extracted from each published paper. In the model (2) Result is an integer-valued variable for positive test result (depending on software choice, for grouped binary data, usually Result is replaced by number of positive test results over the total sample size, for each group); Disease is an indicator for actual presence of disease, ascertained by the gold standard; PaperID is a categorical variable for papers included in the meta-analysis; and TestID is a categorical variable for tests included. Regression coefficients β 2 to β 7 can be vector valued, meaning having several components, so the corresponding categorical variables should be represented by suitable number of indicator variables in the model. Indexes p and t signify paper p and test t. They define the repeated measures structure of the data [ 10 ]. Note model (2) fits the general case where there are two or more tests available for the disease, where each test has been studied in one or more papers. Some of the papers may have studied more than one test; hence the results are not independent. Also the collection of tests studied may change from one paper to the other, hence incomplete matched groups. From model (2) one can show that LOR pt = β 1 + β 3 * PaperID pt + β 5 * TestID pt + β 7 * TestID pt * PaperID pt and therefore the difference between performance of two tests i and j, measured by LOR, is LOR pi - LOR pj = β 5 * TestID pi - β 5 * TestID pj + β 7 * TestID pi * PaperID pi - β 7 * TestID pj * PaperID pj where we identify δ i,j of the decomposition model (1) with the β 5 * TestID pi - β 5 * TestID pj , and identify δ i,j,p with β 7 * TestID pi * PaperID pi - β 7 * TestID pj * PaperID pj . If there is an obvious and generally accepted diagnostic test that can serve as a reference category (RefCat) to which other tests can be compared, then a "simple" parameterization for tests is sufficient, However, usually it is not the case. When there is no perceived referent test to which the other tests are to be compared, a "deviation from means" coding is preferred for the tests. Using the deviation parameterization for both TestID and PaperID in the model (2), one can show that β 5 * TestID pt is the average deviation of the LOR of test t from the overall LOR (the β 1 ), where the overall LOR is the average over all tests and all papers. Therefore β 5 * TestID pt of model (2) will be equivalent to the δ i,j of the decomposition model (1), and β 7 * TestID pt * PaperID pt equivalent to δ i,j,p . Proportional odds ratio model Model (2) expands each study to its original sample size, and uses patients as primary analysis units. Compared to a random-effects model where papers are the primary analysis units, it has more degrees of freedom. However, in a real case, not every test is studied in every paper. Rather majority of tests are not studied in each paper. Therefore the data structure of tests-by-papers is incomplete with many unmeasured cells. The three-way interaction model (2) may become over-parameterized. One may want to drop the term β 6 * Disease pt * TestID pt * PaperID pt . Then for the reduced model (3) logit(Result pt ) = β 0 + β 1 * Disease pt + β 2 * PaperID pt + β 3 * Disease pt * PaperID pt + β 4 * TestID pt + β 5 * Disease pt * TestID pt we have LOR pt = β 1 + β 3 * PaperID pt + β 5 * TestID pt , where the paper and test effects are completely separate. We call this reduced model the Proportional Odds Ratio (POR) model, where the ratio of odds ratios of two tests is assumed to be constant across papers, while odds ratio of each test is allowed to vary across the papers. Note the difference with the proportional odds model where ratio of odds is assumed to be constant [ 14 ]. In the POR model (4) OR pt = OR p * , t = 1 , 2 , ..., k , p = 1 , 2 , ..., m where t is an index for the k diagnostic tests, and p is an index representing the m papers included in the analysis. OR p is a function capturing the way OR changes across papers. Then to compare two diagnostic tests i and j OR pi / OR pj = where the ratio of the two ORs depends only on the difference between the effect estimates of the two tests, and is independent of the underlying OR p across the papers. Thus the model makes no assumptions about the shape of OR p (and in particular homogeneity of ORs) but merely specifies a relationship between the ORs of the two tests. One may want to replace the PaperID variable with a smooth function of FPR or TPR, such as natural restricted cubic splines. There are two potential advantages. This may preserve some degrees of freedom, where one can spend by adding covariates to the model to measure their potential effects on the performance of the diagnostic tests. Thus one would be able to explain why performance of the same test varies across papers. Also, this allows plotting a ROC curve where the OR is not constant across the curve, a flexible ROC (HetROC) curve. (5) logit(Result pt ) = β 0 + β 1 * Disease pt + β 2 * S(FPR pt ) + β 3 * Disease pt * S(FPR pt ) + β 4 * TestID pt + β 5 * Disease pt * TestID pt + β 6 * X pt + β 5 * Disease pt * X pt To test the POR assumption one may use model (2) where the three-way interaction of Disease and TestID with PaperID is included. However, in majority of real datasets this would mean an over-parameterized model. Graphics can be used for a qualitative checking of the POR assumption. For instance, the y-axis can be LOR, while the x-axis is paper number. To produce such plot, it may be better to have the papers ordered in some sense. One choice is to compute an unweighted average of (observed) ORs of all the tests the paper studied, and use it as the OR of that paper. Then sort the papers based on such ORs. The OR of a test may vary from one paper to the other (with no restriction), but the POR assumption is that the ratio of ORs of two tests remains the same from one paper to another. If one shows ORs of a test across papers by a smooth curve, then one expects that the two curves of the two tests are proportional to each other. In the log-OR scale, this means the vertical distance of the two curves remains the same across the x-axis. To compute the observed LOR for a test in a paper one may need to add some value (like 1/2) to the cell counts, if some cell counts are zero. However, this could introduce some bias to the estimates. Among the approaches for modeling repeated-measures data, we use generalized estimating equations to estimate the marginal logistic regression [ 15 ]. Software is widely available for estimation of parameters of a marginal POR model. These include SAS (genmod procedure), R (function geese), and STATA (command xtgee), with R being freely available open source software [ 16 ]. One may use a non-linear mixed effects modeling approach on the cell-count data for estimation of parameters of the POR model. The Paper effect is declared as random, and interaction of the random effect with Disease is included in the model, as indicated in model (2). However, such mixed effects non-linear models are hard to converge, especially for datasets where there are many papers studying only one or a small number of the included tests (such as the dataset presented as example in this paper). If the convergence is good, it may be possible to fit a mixed model with the interaction of Disease, Test, and the Paper random effect. Such model relaxes the POR assumption, besides relaxing the assumption of OR-homogeneity. In other words, one can use the model to quantitatively test the POR assumption. One should understand that the interpretation of LOR estimate from a marginal model is of a population-average, while that of a mixed model is a conditional-average. Therefore there is a slight difference in their meaning. Expanding the proportional odds ratio model One may use the frameworks of the generalized linear models (GLM) and the generalized estimating equations (GEE) to extend the POR model and apply it to different scenarios. By using suitable GLM link function and random component [[ 17 ], p.72], one may fit the POR model to multi-category diagnostic tests, like baseline-category logits, cumulative logits, adjacent-categories and continuation-ratio logits [[ 17 ], chapter 8]. A loglinear 'Proportional Performance' (PP) regression may be fitted to the cell counts, treating them as Poisson. Also, one may fit the PP model to the LORs directly, assuming a Gaussian random component with an identity link function. Comparing GEE estimates by fitting the model to 2-by-2 tables versus GEE estimates of the model fitted directly on LOR versus a Mixed model fitted on LOR, usually statistical power decreases across the three. Also, there is issue of incorporation of sample sizes that differ across studies. Note some nuisance parameters, like coefficients of all main effects and the intercept, won't need to be estimated as they are no longer present in the model fitted directly on LORs. One may avoid dichotomizing results of the diagnostic test by using the 'likelihood ratio' as the performance measure, and fitting a PP model to such continuous outcome. For a scenario where performance of a single test has been measured multiple times within the same study, for example with different diagnostic calibrations (multiple thresholds), the POR estimated by the GEE incorporates data dependencies. When there is a multi-layer and/or nested clustering of repeated measures, software to fit a mixed-effects POR model may be more available than an equivalent GEE POR. When POR is implemented by a logistic regression on 2-by-2 tables, it uses a grouped binary data structure. It takes a minimal effort to fit the same logistic model to the "ungrouped" binary data, the so-called "individual level" data. Methods of meta-analysis that allow for different outcomes (and different numbers of outcomes) to be measured per study, such as that of Gleser and Olkin [ 18 ], or DuMouchel [ 19 ], may be used to implement the POR model. This would prevent conducting parallel meta-analyses that is usually less efficient. Results Deep vein thrombosis To demonstrate how to fit the POR model, we use a recent meta-analysis of diagnostic tests for deep vein thrombosis (DVT) by Heim et al. [ 20 ]. In this meta-analysis there are 23 papers and 21 tests, comprising 483 potential performance measurements, while only 66 are actually observed, thus 86% of cells are not measured. We fitted the reduced marginal logistic regression model (3). Table 1 shows the parameter estimates for Test effects. SAS code to estimate the parameters is provided [see additional file 1 ].Data files are provided in Additional file 2 . Table 1 Parameter estimates for test effects Coefficient Test Deviation* 95% Confidence Limits p value β 5 † 1 Asserachrom 0.524 0.2293, 0.8186 0.0005 2 Auto Dimertest 0.222 -0.1466, 0.5912 0.2376 3 BC D-Dimer -0.993 -2.4195, 0.4333 0.1724 4 D-Dimer test 0.225 0.1, 0.3494 0.0004 5 Dimertest -2.092 -2.3392, -1.8439 <.0001 6 Dimertest EIA -0.929 -1.1756, -0.6825 <.0001 7 Dimertest GOLD EIA -0.193 -0.4784, 0.0935 0.1871 8 Dimertest II -0.731 -0.9774, -0.4843 <.0001 9 Enzygnost 0.399 0.1209, 0.6766 0.0049 10 Fibrinostika 0.857 0.6865, 1.0266 <.0001 11 IL Test 0.809 0.0914, 1.5256 0.0271 12 Instant I.A. 0.558 0.216, 0.9006 0.0014 13 Liatest -0.143 -0.3375, 0.0511 0.1486 14 LPIA 0.182 -0.0354, 0.3997 0.1007 15 Minutex -0.323 -0.8394, 0.193 0.2197 16 Nephelotex 0.654 0.4325, 0.8745 <.0001 17 NycoCard -0.797 -1.0434, -0.5506 <.0001 18 SimpliRED 0.393 0.1467, 0.6398 0.0018 19 Tinaquant 0.703 0.0113, 1.3948 0.0464 20 Turbiquant -0.328 -1.6596, 1.0032 0.629 21 VIDAS 1.004 0.365, 1.6424 0.0021 β 1 Overall LOR 2.489 2.4175, 2.5606 < .0001* * estimate of deviation from overall LOR p-value for null hypothesis of Deviation = 0 p-value for null hypothesis of LOR = 0 † LOR(Result pt ) = β 1 + β 3 PaperID pt + β 5 * TestID pt Since we have used deviation contrast for the variables, estimate of β 1 is the "overall mean" for the log-OR. This is similar to an ANOVA analysis where the overall mean is estimated by the model. Therefore the average OR is equal to exp(2.489) = 12.049. Components of β 5 estimate deviation of LOR of each test from the overall LOR. Software gives estimates of SEs, plus confidence intervals and p-values, so inference is straightforward. A forest plot may be used to present the results of the modeling in a graphical way. This may connect better with clinically oriented audience. In Figure 1 we have sorted the 21 tests based on their LOR estimate. Figure 1 Comparing performance of each diagnostic test to the overall LOR The horizontal axis is log-OR, representing test performance. The dashed vertical line shows overall mean LOR. For each diagnostic test the solid square shows the LOR, while the horizontal line shows the corresponding 95% CI. If the horizontal line does not intersect the vertical line, the test is significantly different from the overall mean LOR. Note that the CIs in the plot are computed by adding the overall LOR to the CI for the deviation effect of each particular test. This ignores the variability of the overall LOR estimate. One can estimate the LOR of a test and its CI more accurately by some extra computations, or by fitting a slightly modified model. A method is illustrated and implemented [see additional file 1 ]. However, the gain in accuracy was small in this particular example. The model also estimates paper effects. However, one may not be interested in those primarily. One can translate LOR to other measures of test performance. There are numerous types of these measures. We provide code to convert the LOR estimated by the POR model to such measures. Note that majority of them, unlike LOR, are in pairs. This means in order to compare two tests, one needs to use two numbers to represent each single test. For example, sensitivity-specificity is a pair. If a test has a higher sensitivity than the other test, while having a lower specificity, it is not immediately clear which test is better. Also, note that some performance measures are independent of disease prevalence, while others depend on prevalence. This means the same test would perform differently for populations with different disease prevalence. Note in order to compute some of the performance measures, one needs to assume a prevalence and sensitivity or specificity. We assumed a disease prevalence of 40%, and a specificity of 90%, for Table 2 , as the tests are mainly used for ruling out the DVT. Table 2 Other performance measures for the 21 diagnostic tests of DVT Diagnostic Test DOR Prev. Spec. Sens. AUC PPV NPV LRAT LRNT PTO PTOAT PTONT PTPAT PTPNT 1 Asserachrom 20.3 0.4 0.9 0.693 0.888 0.822 0.815 6.933 0.341 0.667 4.622 0.227 0.822 0.185 2 Auto Dimertest 15.0 0.4 0.9 0.626 0.864 0.807 0.783 6.258 0.416 0.667 4.172 0.277 0.807 0.217 3 BC D-Dimer 4.5 0.4 0.9 0.332 0.732 0.688 0.669 3.315 0.743 0.667 2.210 0.495 0.688 0.331 4 D-Dimer test 15.1 0.4 0.9 0.626 0.865 0.807 0.783 6.263 0.415 0.667 4.175 0.277 0.807 0.217 5 Dimertest 1.5 0.4 0.9 0.142 0.566 0.486 0.611 1.419 0.953 0.667 0.946 0.636 0.486 0.389 6 Dimertest EIA 4.8 0.4 0.9 0.346 0.741 0.697 0.674 3.459 0.727 0.667 2.306 0.485 0.697 0.326 7 Dimertest GOLD EIA 9.9 0.4 0.9 0.525 0.826 0.778 0.740 5.248 0.528 0.667 3.499 0.352 0.778 0.260 8 Dimertest II 5.8 0.4 0.9 0.392 0.766 0.723 0.689 3.920 0.676 0.667 2.613 0.450 0.723 0.311 9 Enzygnost 18.0 0.4 0.9 0.666 0.879 0.816 0.802 6.661 0.371 0.667 4.440 0.247 0.816 0.198 10 Fibrinostika 28.4 0.4 0.9 0.759 0.910 0.835 0.849 7.592 0.268 0.667 5.061 0.178 0.835 0.151 11 IL Test 27.0 0.4 0.9 0.750 0.907 0.833 0.844 7.503 0.277 0.667 5.002 0.185 0.833 0.156 12 Instant I.A. 21.1 0.4 0.9 0.701 0.890 0.824 0.818 7.006 0.333 0.667 4.671 0.222 0.824 0.182 13 Liatest 10.4 0.4 0.9 0.537 0.831 0.782 0.745 5.371 0.514 0.667 3.581 0.343 0.782 0.255 14 LPIA 14.5 0.4 0.9 0.616 0.861 0.804 0.779 6.163 0.426 0.667 4.109 0.284 0.804 0.221 15 Minutex 8.7 0.4 0.9 0.492 0.813 0.766 0.727 4.921 0.564 0.667 3.281 0.376 0.766 0.273 16 Nephelotex 23.2 0.4 0.9 0.720 0.897 0.828 0.828 7.202 0.311 0.667 4.801 0.207 0.828 0.172 17 NycoCard 5.4 0.4 0.9 0.376 0.758 0.715 0.684 3.763 0.693 0.667 2.509 0.462 0.715 0.316 18 SimpliRED 17.9 0.4 0.9 0.665 0.878 0.816 0.801 6.648 0.372 0.667 4.432 0.248 0.816 0.199 19 Tinaquant 24.3 0.4 0.9 0.730 0.900 0.830 0.833 7.300 0.300 0.667 4.867 0.200 0.830 0.167 20 Turbiquant 8.7 0.4 0.9 0.491 0.812 0.766 0.726 4.909 0.566 0.667 3.273 0.377 0.766 0.274 21 VIDAS 32.9 0.4 0.9 0.785 0.918 0.840 0.863 7.851 0.239 0.667 5.234 0.159 0.840 0.137 DOR = Diagnostic Odds Ratio Prev. = Prevalence Spec. = Specificity Sens. = Sensitivity AUC = Area Under Curve (assuming homogeneous OR) PPV = Positive Predictive Value NPV = Negative Predictive Value LRAT = Likelihood Ratio For Abnormal Test LRNT = Likelihood Ratio For Normal Test PTO = Pre Test Odds PTOAT = Post Test Odds Of Abnormal Test PTONT = Post Test Odds Of Normal Test PTPAT = Post Test Probability Of Abnormal Test PTPNT = Post Test Probability Of Normal Test We suggest graphs to compare tests when using such "prevalence-dependent paired performance measures" [ 21 ]. In Figure 2 we have used a pair of measures, 'probability of disease given a normal test result' and 'probability of disease given an abnormal test result', the dashed red curve and the dot-and-dash blue curve respectively. Figure 2 Post-test probability difference for diagnostic test VIDAS The way one may read the graph is that, given a particular population with a known prevalence of disease like 40%, we perform the diagnostic test on a person picked randomly from the population. If the test turns normal, the probability the person has disease decreases from the average 40% to about 4% (draw a vertical line from point 0.4 on x-axis to the dashed red curve, then draw a horizontal line from the curve to the y-axis). If the test turns abnormal, the probability the person is diseased increases from 40% to about 57%. The dotted green diagonal line represents a test no better than flipping a coin, an uninformative test. The farther the two curves from the diagonal line, the more informative the test is. In other words, the test performs better. One can summarize the two curves of a test in a single curve, by computing the vertical distance between the two. The solid black curve in the figure is such "difference" curve. It seems this particular test is performing the best in populations with disease prevalence of around 75%. One can use the difference curve to compare several tests, and study effect of prevalence on the way the tests compare to each other. In Figure 3 two tests VIDAS and D-Dimer from the DVT example are compared. From the model estimates we know that both tests perform better than average. And that VIDAS performs better than D-Dimer. Figure 3 Comparing post-test probability difference for VIDAS – D-Dimer The black solid curve is comparing the two tests. For populations with low disease prevalence (around 17%), the D-Dimer is performing better than VIDAS. However, when the prevalence is higher (around 90%), VIDAS is preferred. Simultaneous confidence bands around the comparison curve would make formal inference possible. Random effects A nonlinear mixed effects POR model fitted to cell counts of the DVT dataset does not converge satisfactorily. We fitted the mixed model to a subset of the data where only two tests and seven papers are included, Table 3 . For codes refer to the additional file 1 . Table 3 Data structure for two diagnostic tests Test Paper Instant I.A. NycoCard 3 Elias, A. 1996 (171) X X 8 Legnani, C. 1997 (81) X X 11 Leroyer, C. 1997 (448) X 12 Scarano, L. 1997 (126) X X 13 van der Graaf, F. 2000 (99) X X 21 Wijns, W. 1998 (74) X 22 Kharia, HS. 1998 (79) X TOTAL 6 5 Five of the seven papers have studied both the tests. Result of SAS Proc NLMixed still is sensitive to initial values of parameters. The three-way interaction term of disease, test, and paper in the mixed model (where POR is not assumed) is insignificant, Table 4 . A POR assumption for the two tests may be acceptable. Table 4 Comparing parameter estimates from three models POR-relaxed Mixed * POR Mixed POR Marginal overall LOR 1.389 (0.993, 1.786) 0.868 (0.568, 1.169) 2.593 (2.522, 2.664) Test (NycoCard) -0.903 (-1.811, 0.006) -0.93 (-1.104, -0.755) -0.561 (-0.829, -0.293) TestPaper 0.016 (-1.556, 1.588) --- --- logit(Result) = β 0 + β 1 * Disease + β 2 * PaperID + β 3 * Disease * PaperID + β 4 * TestID + β 5 * Disease * TestID + β 6 * Disease * TestID * PaperID The estimate of overall LOR from both the POR-mixed model and POR-marginal model are significantly different from zero. However, the mixed model estimate of LOR is much smaller than the marginal one. For non-linear models, the marginal model describes the population parameter, while the mixed model describes an individual's [[ 15 ], p.135]. The estimate of deviation of test (NycoCard) from the overall LOR is closer in the two models. Plus the marginal estimate is closer to 0 than the mixed estimate. One expects coefficient estimates of mixed model being closer to zero, compared to the fixed model, while the mixed model CI's being wider. Meta-analysis of a single test: the baseline OR p function Sometimes one may be interested in constructing the ROC curve for the diagnostic test. A homogeneous ROC curve assumes the performance of the test (as measured by LOR) is the same across the whole range of specificity. However, this assumption may be relaxed in a HetROC. We fitted a simplified version of model (5) for test SimpliRED, logit(Result pt ) = β 0 + β 1 * Disease pt + β 2 * S(FPR pt ) + β 3 * Disease pt * S(FPR pt ) where index t is fixed, and then used estimates of the coefficients to plot the corresponding HetROC, Figure 4 . Figure 4 Heterogeneous ROC curve for diagnostic test SimpliRED The eleven papers that studied test SimpliRED are shown by circles where the area is proportional to the sample size of the study. The black dashed curve is ROC curve assuming homogeneous-OR. The red solid curve relaxes the assumption, hence a heterogeneous ROC curve. The amount of smoothing of the curve can be controlled by the "degree-of-freedom" DF parameter. Here we have used a DF of 2. Codes to make such plots are presented in the additional file 1 . Model checking Checking the POR assumption, model (2) may be used to reject significance of the three-way interaction term. However, the dataset gathered for the DVT meta-analysis is such that no single paper covers all the tests. Moreover, out of 21, there are 7 tests that have been studied in only one paper. For Figure 5 we chose tests that have been studied in at least 5 of the 23 papers. There are 5 such tests. Note that even for such "popular" tests, out of 10 pairwise comparisons, 3 are based on only one paper (so no way to test POR). Four comparisons are based on 4 papers, one based on 3 papers, and the remaining two comparisons are based on 2 papers. Figure 5 Observed log-odds-ratios of each diagnostic test We sorted the papers, the x-axis, based on average LOR within that paper. We fitted Lowess smooth lines to the observed LORs of each test separately. Figure 5 shows the smooth curves are relatively parallel. Note the range of LORs of a single test. The LORs vary considerably from one paper to the other. Indeed the homogeneity-of-ORs assumption is violated in four of the five tests. Also, to verify how good the model fits the data, one may use an observed-versus-fitted plot. Plots or lists of standardized residuals may be helpful finding papers or tests that are not fitted well. This may provide a starting point for further investigation. Discussion A comparison of the relative accuracy of several diagnostic tests should ideally be based on applying all the tests to each of the patients or randomly assigning tests to patients in each primary study. Obtaining diagnostic accuracy information for different tests from different primary studies is a weak design [ 3 ]. Comparison of the accuracy of two or more tests within each primary study is more valid than comparison of the accuracy of two or more tests between primary studies [ 22 ]. Although a head-to-head comparison of diagnostic tests provides more valid results, there are real-world practical questions that meta-analysis provides an answer that is more timely and efficient than a single big study [ 23 ]. Meta-analysis can potentially provide better understanding by examining the variability in estimates, hence the validity versus generalizability (applicability). Also, there may be tests that have never been studied simultaneously in a single study, hence meta-analysis can "reconstruct" such a study of diagnostic tests. Relaxing the assumption of OR homogeneity In meta-analysis of two (or more) diagnostic tests, where attention is mainly on the difference between performances of two tests, having a homogeneous estimate of performance of each single test is of secondary importance, and it may be treated as nuisance. The POR model assumes differences between LORs of two tests are the same across all papers, but does not assume the OR of a test is the same in every paper. Hence no need for homogeneity of OR of a test across papers that reported it, but shifting the assumption one level higher to POR. Common versus average effect size The POR model uses "deviation from means" parameterization. Then one does not need to drop the interactions coefficient β 3 in the model logit(Result) = β 0 + β 1 * Disease + β 2 * PaperID + β 3 * Disease * PaperID , to interpret β 1 , the overall LOR. This means the POR model explicitly accepts that performance of the diagnostic test varies across the papers, but at the same time estimates its mean value. McClish explains if a test for OR homogeneity shows heterogeneity, there may be no 'common' measure to report, but still there is an 'average' measure one can report. [ 13 ] Advantages of using 2-by-2 tables We demonstrated how to fit the POR model to the cell counts, rather than to the OR values. This, we believe, has several advantages. 1. One does not need assuming normality of some summary measure. This results in binomial distributional assumption that is more realistic. 2. Also, different study sample sizes are incorporated into the POR model without faulty bias-introducing weighting schemes, as shown by Mosteller & Chalmers [ 25 ]. And extension of the POR model to individual level patient data is much easier. 3. The effective sample size for a meta-analysis by a random model is the number of papers included, which is usually quite small. There is a great danger for overfitting. And the number of explanatory variables one could include in the model is very restricted. Since we use the grouped binary data structure, the patients are the effective sample size, hence much bigger degrees of freedom. The way the random-effects model is usually implemented is by extracting OR from each paper, and assuming LOR being normally distributed. Then the distinction between the two types of mistakes (FNR and FPR, or equivalently TPR and FPR) is lost, since one enters the LOR as datapoints into the model. The bivariate model by Houwelingen et al [ 26 ] tries to fix this, by entering two datapoints into the model for each test from each paper. A fourth advantage of fitting the POR model to the cell counts is that the two types of mistakes are included in the model. Consider the logistic regression logit(Result) = β 0 + β 1 * Disease + β 2 * PaperID . Then we have log(true positive/false negative) = β 0 + β 1 + β 2 * PaperID . Substituting a value for the covariate (here PaperID) such as a modal or average value, and using the model estimates for the betas, one gets the log-odds. Then one exponentiates it to get the TP/FN, call it Q. Now it is easy to verify that sensitivity = Q/(1+Q). Likewise we have log(false positive/true negative) = β 0 + β 2 * PaperID , that we call = log(W). Then specificity = 1/(1+W). Also, one can apply separate weights to the log(true positive/false negative) and log(false positive/true negative), to balance the true positive and false positive rates for decision making in a particular clinical practice. When collecting papers from biomedical literature for meta-analysis of a few diagnostic tests, it is hard to come up with a complete square dataset, where every paper has included all the tests of interest. Usually the dataset contains missing values, and a case-wise deletion of papers with missing tests means a lot of data is thrown away. A method of analysis that can utilize incomplete matched groups may be helpful. The POR model allows complex missing patterns in data structure. Convergence of marginal POR model seems much better than non-linear mixed model, when fitted to cell counts of incomplete matched groups. This is an advantage for using GEE to estimate POR. The fact that one can use popular free or commercial software to fit the proposed models, facilitates incorporation of the POR modeling in the practice of meta-analysis. Unwanted heterogeneity versus valuable variability The POR model utilizes the variation in the observed performance of a test across papers. Explaining when and how the performance of the test changes, and finding the influential factors, is an important step in advancing science. In other words, rather than calling it 'heterogeneity', treated as 'unwanted' and unfortunate, one calls it 'variability' and utilizes the observed variability to estimate and explain when and how to use the agent or the test in order to optimize their effects. Victor [ 32 ] emphasizes that results of a meta-analysis can only be interpreted if existing heterogeneities can be adequately explained by methodological heterogeneities. The POR model estimates effect of potential predictors on between-study variation, hence trying to 'explain' why such variation exists. The POR model incorporates risk of events in the control group via a predictor, such as observed prevalence, hence a 'control rate regression'. [ 26 ] ROC curve Although implementing the HetROC means that one accepts the diagnostic test performs differently in different FPRs along the ROC curve, in some implementations of HetROC, such as method of summary ROC, one compares tests by a single point of their respective ROCs. This is not optimal. (The Q test of the SROC method is a single point test, where that point on the ROC may not be the point for a specific cost-benefit case.) In such method although one produces a complete SROC, but one does not use it in comparing the diagnostic tests. In the POR model, one uses LOR as the measure for diagnostic discrimination accuracy, and builds statistical test based on the LOR-ratio, hence the test corresponds to whole ROCs (of general form). The ROC graph was designed in the context of the theory of signal detectability [ 27 , 28 ]. ROC can be generated in two ways, by assuming probability distribution functions (PDFs) for the two populations of 'diseased' and 'healthy', or by algebraic formulas [ 29 ]. Nelson claims the (algebraic) ROC framework is more general than the signal detection theory (and its PDF-based ROC) [ 5 ]. The location-scale regression models implement ROC via PDFs, while the method of summary-ROC uses algebraic approach. The POR model uses a hybrid approach. While POR may be implemented by logistic regression, the smoothing covariate resembles the algebraic method. Unlike location-scale regression models that use two equations, POR uses one equation, hence it is easier to fit by usual statistical packages. One may use a five-parameter logistic to implement the HetROC. However, the model cannot be linearized, then according to McCullagh [ 14 ] it won't have good statistical properties. The POR model not only relaxes assumption of Var1/Var2 = 1, where Var1 and Var2 are variances of the two underlying distributions for the two populations, but even monotonicity of ROC. Hence the model can be used to represent both asymmetric ROCs and non-regular ROCs (singular detection). In building HetROC curve, the POR model accommodates more general heterogeneous ROCs than SROC, because it uses nonparametric smoother instead of arbitrary parametric functions used in SROC method. When in the POR model the smoother covariate is replaced by log{TPRFPR/ [(1-TPR)(1-FPR)]}, a HetROC similar to SROC of Moses et al is produced. When one uses a smooth function of FPR in the POR model, it is equivalent to using a function of outcome as predictor. This resembles a 'transition model'. Ogilvie and Creelman [ 30 ] claim that for estimating parameters of a best fitting curve going through observed points in the ROC space, least squares is not good since both axes are dependent variables and subject to error. They claim maximum likelihood is a preferred method of estimation. Crouchley and Davies [ 31 ] warn that, although GEE is fairly robust, it becomes inconsistent if any of the covariates are endogenous, like a previous or related outcome or baseline outcome. They claim a mixed model is better for studying microlevel dynamics. We have observed that the smooth HetROC curve may become decreasing at right end, due to some outlier points. Using less smoothing in the splines may be a solution. When there is only one diagnostic test, and one is mainly interested in pooling several studies of the same test, the POR model estimates effect sizes that are more generalizable. By using the smoother (instead of PaperID), one fits a sub-saturated model that allows inclusion of other covariates, hence it is possible to estimate effect of study level factors on performance and explain the heterogeneity. Also it does not assume any a priori shape of the ROC, including monotonicity. Plus, it enables graphing of the HetROC. It does not need omission of interaction terms to estimate the overall performance, and it does not need assumption of OR homogeneity. If several performance measurements of the same test is done in a single study, like evaluating the same test with different diagnostic calibrations, the POR model provides more accurate estimates, by incorporating the dependence structure of the data. Random effects When there is heterogeneity between a few studies for the same diagnostic test, one solution to absorb the extra between-study variation is to use a random/mixed effects model. However, Greenland [ 33 ] cautions when working with random effect models: 1. if adding random effect changes the inference substantially, it may indicate large heterogeneity, needing to be explained; 2. specific distributional forms for random effects have no empiric, epidemiologic, or biologic justification. So check its assumptions; 3. the summary statistic from random-effect model has no population-specific interpretation. It represents the mean of a distribution that generates effects. Random models estimate unit specific coefficients while marginal models estimate population averages. The choice between unit-specific versus population-average estimates will depend on the specific research questions that are of interest. If one were primarily interested in how a change in a covariate affect a particular individual cluster's mean, one would use the unit-specific model. If one were interested in how change in covariate can be expected to affect the overall population mean, one would use the population-average model. The difference between "unit-specific" models and "population-average" models arises only in the case of a nonlinear link function. In essence random-effect model exchanges questionable homogeneity assumption for a fictitious random distribution of effects. Advantage of a random model is that SE and CI reflect unaccounted-for sources of variation, and its drawback is that simplicity of interpretation is lost. When residual heterogeneity is small, fixed and random should give same conclusions. Inference about the fixed effects (in a mixed model) would apply to an entire population of cases defined by random effect, while the same coefficient from a fixed model apply only to particular units in the data set. Crouchley and Davies [ 31 ] explain one of the drawbacks of their random model is that it rapidly becomes over-parameterized, and also may encounter multiple optima. Follow-ups We suggest these follow-ups: 1. the POR model has been implemented both by marginal and mixed models. It would be useful to implement a marginalized mixed POR model; 2. in clinical practice, usually a group of diagnostic tests is performed on an individual, for a particular disease. Some of these tests are requested simultaneously and some in sequence. It would be useful, and practically important, to extend the POR model such that it incorporates such sequence of testing and a priori results; 3. the utility of POR model may be extended to meta-analysis of therapeutics. Competing interests The author(s) declare that they have no competing interests. Authors' contributions MSS conceived of the model, and participated in its design and implementation. JS participated in implementation of the model and performing of the example analysis. Both authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 In this file we present sample codes for a few of the models presented in the paper. The estimation mostly has been done in SAS, while the graphing (and some model-fitting) has been done in R. Click here for file Additional File 2 This zipped file contains 8 data files, in the .csv (comma separated value) and .xls (MS Excel) formats. They are to be used with the SAS and R codes we presented in the Appendix [additional file 1]. Five files are for the SAS codes presented in the Appendix. The file names are "data5.xls", "data5_t12&17.xls", "u125.xls", "data5_t18.xls", "data6.xls". Three files are for the R codes presented in the Appendix. The file names are "obsVSfit.csv", "dataNewExcerpt2.csv", and "data6_lor2.csv". Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539279.xml
529297	Assessment of the dynamics of atrial signals and local atrial period series during atrial fibrillation: effects of isoproterenol administration	Background The autonomic nervous system (ANS) plays an important role in the genesis and maintenance of atrial fibrillation (AF), but quantification of its electrophysiologic effects is extremely complex and difficult. Aim of the study was to evaluate the capability of linear and non-linear indexes to capture the fine changing dynamics of atrial signals and local atrial period (LAP) series during adrenergic activation induced by isoproterenol (a sympathomimetic drug) infusion. Methods Nine patients with paroxysmal or persistent AF (aged 60 ± 6) underwent electrophysiological study in which isoproterenol was administered to patients. Atrial electrograms were acquired during i) sinus rhythm (SR); ii) sinus rhythm during isoproterenol (SRISO) administration; iii) atrial fibrillation (AF) and iv) atrial fibrillation during isoproterenol (AFISO) administration. The level of organization between two electrograms was assessed by the synchronization index (S), whereas the degree of recurrence of a pattern in a signal was defined by the regularity index (R). In addition, the level of predictability (LP) and regularity of LAP series were computed. Results LAP series analysis shows a reduction of both LP and R index during isoproterenol infusion in SR and AF (R SR = 0.75 ± 0.07 R SRISO = 0.69 ± 0.10, p < 0.0001; R AF = 0.31 ± 0.08 R AFISO = 0.26 ± 0.09, p < 0.0001; LP SR = 99.99 ± 0.001 LP SRISO = 99.97 ± 0.03, p < 0.0001; LP AF = 69.46 ± 21.55 LP AFISO = 55 ± 24.75; p < 0.0001). Electrograms analysis shows R index reductions both in SR (R SR = 0.49 ± 0.08 R SRISO = 0.46 ± 0.09 p < 0.0001) and in AF (R AF = 0.29 ± 0.09 R AFISO = 0.28 ± 0.08 n.s.). Conclusions The proposed parameters succeeded in discriminating the subtle changes due to isoproterenol infusion during both the rhythms especially when considering LAP series analysis. The reduced value of analyzed parameters after isoproterenol administration could reflect an important pro-arrhythmic influence of adrenergic activation on favoring maintenance of AF.	Background Atrial Fibrillation (AF) results from multiple, rapidly changing and spatially disorganized activation wavelets sweeping across the surface of the atria [ 1 ]. Among factors contributing to genesis and / or maintenance of circulating wavelets, Autonomic Nervous System (ANS) seems to play a major pro-arrhythmic role [ 2 ]. The arrhythmogenic influence of sympathetic and vagal mechanisms has been documented in several clinical and experimental studies [ 3 , 4 ]. In men, ablation of the major parasympathetic pathways to the atria drastically reduced vagally mediated atrial fibrillation [ 4 ]. It has also been reported that sympathetic stimulation by shortening atrial refractory periods, may increase vulnerability to atrial fibrillation in different experimental models [ 5 ]. The shortening of action potential duration and flattening of the restitution slope to cycle length changes induced by adrenergic activation, are two of the mechanisms favoring spiral wave induction and restraining spiral wave break-up [ 6 ]. Changes in action potential may also contribute to the perpetuation of atrial fibrillation [ 7 ]. In normal hearts, both vagal and sympathetic mechanisms have been associated with paroxysmal atrial fibrillation (PAF) initiation. Most of PAF episodes observed in patients with structural heart disease are triggered by sympathetic activation and vagal withdrawal [ 8 ]. Spectral analysis of heart rate variability before PAF episodes has further clarified the pro-arrhythmic role of the autonomic nervous system [ 9 , 10 ]. Bettoni [ 9 ] observed a primary increase in adrenergic drive occurring over at least 20 minutes before onset of PAF episodes followed by a shift towards a vagal predominance immediately before arrhythmia onset. Other authors described an increase in sympathetic modulation of sinus node (or a loss of vagal modulation) before PAF onset in the majority of patients [ 10 - 12 ]. More recently Lombardi [ 7 ] reported that signs of sympathetic activation characterized up to 70% of PAF episode onset, whereas in the remaining ones a vagal predominance was detectable. An increase in vagal modulation can also promote the stability of AF [ 13 ]. Even if AF has been classically described as a random process, a few studies have recently documented, using various signal processing methods, the existence of some determinism underlying AF. Linear analysis techniques documented relationships between intra-atrial recordings using both time-domain methods [ 14 ] and spectral-domain approaches [ 15 , 16 ], while the presence of non-linear patterns have been also recognized [ 17 , 18 ]. By using linear and non-linear indexes we have recently assessed [ 19 ] the dynamics of intra-atrial signal and local atrial period (LAP) series during different AF episodes. In particular, regularity (R) and synchronization (S) indexes [ 20 ], based on the estimation of the corrected conditional entropy and the corrected cross-conditional entropy respectively, were used to describe the dynamics in intra-atrial signals, whereas the LAP series were investigated using regularity and the level of predictability (LP). These parameters were suitable to describe the fine changing characteristic of atrial signals and LAP series [ 19 ] when passing from different atrial rhythms classified according to the Wells' criteria [ 21 ]. In the present paper, we evaluated whether changes in adrenergic control mechanisms could influence determinisms and dynamics of atrial signals and exploited the capability of linear and non-linear parameters (R and S indexes for intra-atrial signals, R and LP indexes for LAP series) to capture them. Adrenergic activation was mimicked by isoproterenol infusion. The effects of this sympathomimetic drug was evaluated in a small group of patients with a history of PAF during sinus rhythm and atrial fibrillation: four experimental conditions were analyzed (sinus rhythm (SR), sinus rhythm during isoproterenol administration (SRISO), atrial fibrillation (AF) and atrial fibrillation during isoproterenol administration (AFISO)). Experimental protocol Patient population Nine patients (8 males and 1 female; mean age 60 ± 6 years) selected to sustain a left atrial ablation with encirclement of the pulmonary veins by transeptal approach were included in the study. All subjects were suffering from atrial fibrillation (AF) and were non responsive to anti-arrhythmic therapy (pharmacological therapy and electrical cardioversion). Paroxysmal and persistent AF episode were present in, respectively, 5 and 4 subjects. A history of AF was present for an interval ranging from 2 months to 10 years. The mean left ventricular ejection fraction was > 40% in all patients; the mean left atrial diameter was 37 ± 3 mm in 7 patients and 51 ± 8 mm in 2. Structural heart disease was present in 4 patients. Reported symptoms included palpitations (6 subjects), fatigue after effort (9 subjects) and syncope (2 subjects). Arterial hypertension was the most common comorbidity in our study group (4 patients). All the patients were in anti-arrhythmic drug wash-out at the time of the study. Flecainide, propafenone, metoprolol, cordarone and methyldigoxin were ceased ≥ 5 half-lives before ablation. Transoesophageal echocardiography was performed the day before the procedure to exclude atrial thrombus. The Medical Ethical Committee approved this study and all subjects gave their written consent. Study design We investigated the effect of adrenergic activation induced by infusion of isoproterenol on atrial electrical activity. The electrophysiological procedure was performed in the Electophysiology Laboratory of the "Istituto Clinico Sant'Ambrogio" of Milan, Italy. Intracavitary electrocardiograms were recorded during the ablation procedure in which arrhythmic foci inside the pulmonary veins of the left atrium were electrically isolated. The research project protocol included an intracavitary recording of multiple atrial electrograms during sinus rhythm and after induction of atrial fibrillation. In both experimental conditions, the recording was repeated during intravenous infusion of isoproterenol (0.01–0.02 mcg/kg/min) tiered to determine a 30% increase of heart rate. The four clinical experimental conditions were defined as sinus rhythm (SR), sinus rhythm during isoproterenol administration (SRISO), atrial fibrillation (AF) and atrial fibrillation during isoproterenol administration (AFISO). Details on the four epochs of the study can be found in Figure 1 . Figure 1 Timing and sequences of the experimental protocol epochs. The experimental protocol included four recording periods during: I) sinus rhythm (SR); II) sinus rhythm during isoproterenol infusion (SRISO); III) atrial fibrillation (AF); IV) atrial fibrillation during isoproterenol infusion (AFISO). The recordings during SR lasted at least 5 minutes (range 5 – 8 minutes), those during AF 90 seconds on average (range 60 – 120 seconds). The recordings during infusion of isoproterenol started after the drug had determined a 30% increase of heart rate. Induction of AF started 15 minutes after the end of SRISO, to guarantee the correct isoproterenol wash-out. In all the patients, AF inducibility was obtained at twice diastolic threshold by burst atrial pacing (5'-second bursts at an output of 20 mA) from the mid coronary sinus beginning at a cycle length of 250 ms and reducing by 10 ms intervals until atrial refractoriness. All the nine patients were inducible. AF was considered inducible if it persisted for more than 1 minute. If AF terminated after less than 1 minute, induction was repeated until a maximum of 3 times. If AF became sustained (lasting > 10 minutes), ablation was performed after external DC cardioversion. All our patients underwent the procedure in spontaneous SR. The duration of registration was an important parameter for the reliability of the analysis, because an insufficient number of atrial potentials (less than 250 – 300) could give errors in the estimation of conditioned probability. Therefore at least 5 minutes (range 5 – 8 minutes) of sinus rhythm and 90 seconds (range 60 – 120 seconds) of atrial fibrillation were registered. The electrophysiological study was carried out using a deflectable 20 pole St Jude catheter (length 95 cm, 7 F, interelectrode spacing 2 – 10 mm), a deflectable decapolar catheter with a distal ring configuration, Lasso-Cordis Biosense Webster catheter (length 115 cm, 7 F, interelectrode spacing 2 – 5 mm) and 4 mm distal electrode catheter, Medtronic Sprinklr , with irrigated tip (for ablation, length 115 cm, 7 F, interelectrode spacing 2 – 5 mm). The St Jude catheter was in contact with the right atrial wall and inserted in the coronary sinus below the left atrium. The Lasso-Cordis Biosense Webster catheter and the Medtronic Sprinklr catheter were positioned in the superior pulmonary veins at the inside of the atrium. For the purpose of this study, one surface ECG tracing and nine intracavitary atrial electrograms were stored on digital memory for subsequent off line analysis. In all patients, electrograms labeled 2 – 3 – 4 – 5 corresponded, respectively, to the superior, middle, middle inferior and inferior wall of the right atrium; electrogram 6 to coronary sinus ostium; electrograms 7 – 8 – 9 indirectly corresponded to the inferior and the left wall of the left atrium whereas electrogram 10 to the left superior pulmonary vein. Electrograms 2 – 9 were recorded with 20 pole St Jude catheter, electrogram 10 with Lasso-Cordis Biosense Webster catheter. Methods and Data analysis Regularity Conditional entropy ( CE ) may be used to estimate a regularity index, defined as the degree of recurrence of a pattern in a signal. CE represents the amount of information carried by the most recent sample x ( i ) of a normalized realization of x when its past L - 1 samples are known. CE is defined as [ 22 ]: where p ( x L - 1 ) represents the probability of the pattern x L - 1 ( i - 1) of length L - 1 ( x L - 1 ( i - 1) = { x ( i - 1),..., x ( i - L + 1)}) and p ( x ( i ) / x L - 1 ) the conditional probability of the sample x ( i ) given the pattern x L - 1 . In (1) the first summation is extended to all the possible x L - 1 patterns, the second one is extended to all the different L th samples of the pattern x L ( i ) ( x L ( i ) = { x ( i ), x L - 1 ( i - 1)}). CE is maximum if x is complex and unpredictable and it reaches zero as soon as a new sample can be exactly predicted from the previous L -1 ones. Using CE over short data series can cause an unreliable estimate of CE ( CÊ ) : when the conditioning pattern x L - 1 ( i - 1) is found only once in the series x (i.e. p ( x ( i ) / x L - 1 ) = 1), CÊ decreases to zero with L . As a consequence both periodic and completely unpredictable signals exhibit CÊ equal to zero when L increases. Therefore the corrected conditional entropy ( CCE ) must be introduced to perform a reliable measure over short data series: CCE ( L ) = CÊ ( L ) + perc ( L )· Ê (1) (2) where perc ( L ) is the percentage of length L patterns found only one time in the data set and Ê (1) is the estimate of Shannon entropy of the process x. perc ( L )· Ê (1) represents the corrective term that compensates the null information associated to the pattern found only once and it increases with L , while CÊ ( L ) decreases with L . The minimum value of the CCE is the best estimate of CE and it's taken as an index of complexity: the larger the index, the less predictable the processes. The CCE is normalized by the Shannon entropy of the process in order to derive an index independent of the different probability distribution of the processes, thus obtaining: An index of regularity (the opposite of complexity) may be defined as: R x = 1 - min( NCCE ( L )) (4) R x tends to zero if x is a fully unpredictable process, it tends to one if x is a periodic signal and it assumes intermediate values for those processes that can be partially predicted by the knowledge of the past samples [ 20 ]. Synchronization The cross-conditional entropy is introduced to define an index of synchronization, related to the repetition of a complex pattern involving two signals. Given two normalized signals, the cross-conditional entropy of x given a pattern y is defined as [ 20 ]: where p ( y L - 1 ) represents the probability of the pattern y L - 1 ( i ) and p ( x ( i ) / y L - 1 ) the conditional probability of the sample x ( i ) given the pattern y L - 1 . CE x/y represents the amount of information carried by the most recent sample of the signal x when L - 1 past samples of y are known. Over short data series, this definition suffers from the same limitations as conditional entropy, so analogously corrective terms and normalization are introduced. The uncoupling function ( UF ) is defined as: UF x,y ( L ) = min( NCCE y/x ( L ), NCCE x/y ( L )) (6) in order to measure the amount of information carried by one signal that can't be derived from the knowledge of past samples of the other signal. In this way both causal directions are tested and it is taken the one that leads to the best prediction. For every length L pattern, UF chooses as input the signal that can be the best predictor of the other one. Besides, the joint pattern does not take into account past samples of the output signal to prevent to have a high coupling strength only because one signal has a large index of regularity. The minimum of UF is taken as an index of uncoupling between x and y , therefore an index of synchronization (the opposite of uncoupling) can be defined as: S x,y = 1 - min( UF x,y ( L )) (7) and it quantifies the maximum amount of information exchanged between the two signals. S x,y tends to zero if the two processes are uncoupled, it tends to one if they are perfectly synchronized and it assumes intermediate values when the two signals are able to exchange a certain amount of information [ 20 ]. Level of predictability A discrete time series x ( n ) can be modeled as the output of an autoregressive model of p order where n is the discrete-time index, the a k are the model coefficients and w ( n ) is a Gaussian white noise process of variance feeding the model. The actual sample differs from its model prediction, thus generating the prediction error An index of the level of predictability ( LP ) may be defined as follows LP = (1 - σ e / σ x ) (10) where σ e is the standard deviation of e ( n ) and σ x is the standard deviation of the process x . LP measures the percentage of power which may be predicted by the autoregressive model. In the case of a purely random signal ( σ e is quite close to σ x ) LP tends to zero, while in the case of a linearly predictable signal ( σ e tends to zero) the index tends to one and it assumes intermediate values for those processes that may be partially predicted from the model. Signal pre-processing All signals were appropriately recorded and digitized to a 1000 Hz sampling rate at 16-bit resolution. All bipolar electrograms were band-pass filtered (40 – 250 Hz) to remove baseline shift and high frequency noise. In order to cancel the possible effects of ventricular interference (affecting especially recordings during sinus rhythm), the averaged ventricular interference complex was computed and subtracted from each atrial signal [ 16 ]. In details, from the surface ECG, the occurrences of QRS were determined, and a template of the ventricular interference in each atrial electrogram was constructed by signal-averaging windows of 140 ms around each QRS (windows were positioned 40 ms before and 100 ms after the R wave). The template was then subtracted from the atrial signals at each occurrence of QRS. After detecting time-instants of local atrial depolarization using a derivative / threshold algorithm, the detected depolarizations were visually scored and missed / erroneous detections were corrected by an expert operator using an interactive software. Then, the local atrial period (LAP) series were derived as the sequence of temporal distances between two consecutive local atrial activations [ 19 ] (the procedure is shown in Figure 2 ). Figure 2 Extraction of local atrial period (LAP) series from intra-atrial signal. (a) Example of a recorded electrogram during sinus rhythm before pre-processing; (b)-(c) the related LAP series, obtained as the sequence of temporal distances between two consecutive local atrial activations, after detecting time-instants of local atrial depolarization using a derivative / threshold algorithm. a.u. = arbitrary unit In analogy with previous studies [ 14 , 23 ], after canceling the ventricular interference, the absolute value of the output of the band-pass was low-pass filtered (50 Hz) and then sub-sampled (100 Hz) principally to reduce signal length and computation time. Considering the number of recorded signals and patients, we analyzed 79 recordings in SR and in SRISO and 77 recordings in AF and in AFISO. Twelve recordings were disregarded for the low quality of electrograms. For each recording, atrial signals were divided into six-second segments and then analyzed. Regularity index was estimated for each six-second segment in each recording site and for each patient, while synchronization index was estimated for each pair of close recording sites (interelectrode distance equal to one). Statistical analysis The statistical analysis was carried out using Student's t -test for paired data, comparing each rhythm before and after isoproterenol administration, and between organized (SR) and not organized rhythm (AF). Results Atrial signals Figure 3 shows an example of the distribution of regularity index (R) computed in one patient and in a single recording site (electrogram 8) during the four experimental conditions. The R values, computed in the six-second segments, are superimposed to their mean value. A significant reduction (p < 0.001) of the index passing from sinus rhythm to AF was detectable. Comparing the results obtained from the same rhythm with and without isoproterenol, a reduction of R was observed after drug administration in both sinus rhythm and atrial fibrillation. In this particular case, the decrease during sinus rhythm was statistically significant (p < 0.001). In particular, considering all patients recording sites, we observed 59 reductions (42 with p < 0.05) over 79 recordings passing from SR to SRISO and 40 (17 with p < 0.05) over 77 passing from AF to AFISO. This result reflects the global tendency of entire dataset, as illustrated in Table 1 , where the mean value obtained from all patients recording sites is showed, underlining a statistically significant reduction passing both from SR to AF and from SR to SRISO. Figure 3 Values of the R index in a single subject. Example of regularity (R) index computed for a patient in the electrogram 8 during the four phases of the analysis (SR, SRISO, AF, AFISO). Performance of the R index in the various six-second segments (circle) is superimposed to its mean value. A significant reduction of the R index can be observed passing both from sinus rhythm to atrial fibrillation and from sinus rhythm to sinus rhythm after isoproterenol administration. p < 0.001 Table 1 Mean ± SD values of the proposed indexes in the four analyzed phases SR SRISO AF AFISO AS R 0.49 ± 0.08 0.46 ± 0.09 † 0.29 ± 0.09 0.28 ± 0.08 S 0.28 ± 0.02 0.28 ± 0.03 0.20 ± 0.06* 0.20 ± 0.06 LAP R 0.75 ± 0.07 0.69 ± 0.10 † 0.31 ± 0.08* 0.26 ± 0.09 † LP 99.99 ± 0.001 99.97 ± 0.03 † 69.46 ± 21.55* 55 ± 24.75 † Mean ± SD values of the proposed indexes in the four analyzed phases: sinus rhythm (SR), sinus rhythm during isoproterenol infusion (SRISO), atrial fibrillation (AF) and atrial fibrillation during isoproterenol infusion (AFISO) for Atrial Signals (AS) and LAP series. † p < 0.0001 the comparison of a same rhythm before and during isoproterenol infusion. The t -test comparing organized (SR) to not organized (AF) rhythms always results significant (* p < 0.0001). Concerning the synchronization index (S), a significant decrease was observed only when comparing sinus rhythm to atrial fibrillation (Table 1 ). Evaluating results separately for every recording pair, we observed 35 decreases (7 with p < 0.05) over 69 values passing from SR to SRISO and 32 (9 with p < 0.05) over 66 passing from AF to AFISO. Local atrial period LAP series were analyzed using the level of predictability and the regularity index. Figure 4 illustrates an example of the LAP series during SR, SRISO, AF, AFISO and the corresponding NCCE function. The regularity ( R = 1 - min( NCCE )) decreases visibly passing from sinus rhythm to atrial fibrillation. A decrease in both SR and AF after isoproterenol administration is also observed. The mean values showed in Table 1 are obtained as all patients mean and they underline an analogous tendency. In particular, regularity reductions are found in 7 patients after isoproterenol administration during both sinus rhythm and atrial fibrillation (5 with p < 0.05 passing from SR to SRISO; 2 passing from AF to AFISO). Figure 4 LAP series in the four analyzed phases and the corresponding NCCE functions. Example of LAP series during (a) SR, (b) SRISO, (c) AF, (d) AFISO; (e)-(h) the corresponding NCCE functions (solid lines) depicted as sum of two terms: the decreasing one (CE, dotted line) and the increasing one (the corrective term, dash-dotted line). A clear increase in the minimum value (*) can be observed passing from SR to SRISO to AF to AFISO; therefore the R index = 1 - min( NCCE ) (see text for more details) decreases passing from SR to SRISO to AF to AFISO. Figure 5 shows the local atrial period series during SR, SRISO, AF, AFISO and the corresponding prediction errors. The prediction error increases passing from SR to SRISO to AF to AFISO. All patients mean reflects this tendency as shown in Table 1 . In particular, considering single patients, reductions of level of predictability is observed in 8 of them after isoproterenol administration during both sinus rhythm and atrial fibrillation; the reductions are statistically significant (p < 0.05) in 6 patients passing from SR to SRISO, and only in 4 passing from AF to AFISO. Figure 5 LAP series in the four analyzed phases and the corresponding prediction errors. Example of LAP series during (a) SR, (b) SRISO, (c) AF, (d) AFISO; (e)-(h) the corresponding prediction errors. A prediction error increase can be observed passing from SR to SRISO to AF to AFISO, showing the inability of the autoregressive model to predict the LAP series as the rhythm becomes less organized. This is equivalent to a reduction of the LP index = (1 - σ e / σ x ) passing from SR to SRISO to AF to AFISO. Discussion The autonomic nervous system plays an important role in the genesis and maintenance of atrial fibrillation, but characterization and quantification of its pro-arrhytmic effects are extremely complex and therefore difficult to define. Aim of this study was to evaluate the capability of linear and non-linear parameters to capture the fine changing in the dynamics of atrial signals and LAP series during adrenergic activation induced by the injection of a sympathomimetic drug. The existence of determinism and of an underlining order during AF has recently been shown. In particular both linear [ 14 - 16 ] and non-linear [ 17 , 18 ] patterns have been recognized. In the present study, where a relative small population is considered, we observed a reduction of spatial organization after isoproterenol administration both in sinus rhythm and in atrial fibrillation. In particular analysis of LAP series showed a significant decrease of both LP and R indexes within the same rhythm after isoproterenol administration (see Table 1 ). This reduction could be related to an increase of atrial wave fronts disorganization. In fact in previous studies [ 19 ], both indexes were demonstrated to decrease passing from SR to AF-I and AF-II Wells' classes. Therefore it can be argued that the reduction observed after isoproterenol infusion may be a sign of a high disorganization induced by the drug: atrial activation patterns become less periodic, less predictable and less regular. In fact, in agreement with our previous findings [ 19 ], the higher is the regularity and predictability of sequence of atrial activation, the fewer are the circulating 'mother' wavelets according to Jalife's model [ 24 ]. This finding is in agreement with known effects of sympathetic activation at atrial level [ 25 ] and may provide additional insights to the understanding of the pro-arrhythmic role of ANS in patients with AF. In addition, as previously reported [ 19 ], a marked reduction of R and LP indexes was observed passing from SR to AF. Concerning results obtained from atrial signals, both synchronization and regularity indexes showed a marked reduction passing from SR to AF well in keeping with previous findings [ 19 ] that documented the capability of these indexes to discriminate between organized and not-organized rhythms. However the two indexes were not able to evidence any differences after isoproterenol infusion. Only the R index was found significantly decreased in SR after drug administration. Nevertheless, the parameters revealed a tendency toward organization reduction after isoproterenol administration in both rhythms. In particular, responses to isoproterenol were more homogenous during sinus rhythm than during AF. This is maybe due to the fact that patients with a clinical history of AF, could already present alteration in atrial electrical properties likely to be involved in their predisposition to develop AF. Accordingly isoproterenol effects on dynamics of atrial signals are more evident in an organized rhythm (SR) than in AF, where an already disorganized rhythm can not be further fragmented by drug infusion. During AF in fact it has been suggested [ 1 ] that several wavefronts of electrical activity propagate through the atria in an irregular manner; this activity may partly obscure isoproterenol effects. Nevertheless, it has also been reported that atrial electrical activity may vary not only in relation to arrhythmia duration but also in relation to the structural characteristics of the atria [ 26 ]. In conclusion, the proposed set of linear and non-linear parameters is able to capture subtle changes in atrial dynamics during AF and drug infusion. These indexes could be employed to provide new insight into the mechanisms leading to initiation and maintenance of AF episodes.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529297.xml
526417	Genome wide analysis of common and specific stress responses in adult drosophila melanogaster	Background During their life, multicellular organisms are challenged with oxidative stress. It is generated by several reactive oxygen species (ROS), may limit lifespan and has been related to several human diseases. ROS can generate a wide variety of defects in many cellular components and thus the response of the organism challenged with oxidative stress may share some features with other stress responses. Conversely, in spite of recent progress, a complete functional analysis of the transcriptional responses to different oxidative stresses in model organisms is still missing. In addition, the functional significance of observed transcriptional changes is still elusive. Results We used oligonucleotide microarrays to address the specificities of transcriptional responses of adult Drosophila to different stresses induced by paraquat and H 2 O 2 , two oxidative stressors, and by tunicamycin which induces an endoplasmic reticulum (ER) stress. Both specific and common responses to the three stressors were observed and whole genome functional analysis identified several important classes of stress responsive genes. Within some functional classes, we observed that isozymes do not all behave similarly, which may reflect unsuspected functional specificities. Moreover, genetic experiments performed on a subset of lines bearing mutations in genes identified in microarray experiments showed that a significant number of these mutations may affect resistance of adult Drosophila to oxidative stress. Conclusions A long term common stress response to paraquat- or H 2 O 2 -induced oxidative stresses and ER stress is observed for a significant number of genes. Besides this common response, the unexpected complexity of the stress responses to oxidative and ER stresses in Drosophila, suggest significant specificities in protective properties between genes associated to the same functional classes. According to our functional analysis, a large part of the genome may play a role in protective mechanisms against oxidative stress in Drosophila.	Background Cells are frequently submitted to exogenous or endogenous stresses. In aerobic cells, reactive oxygen species (ROS), produced by respiration and other biological processes, are a major source of endogenous stress. These ROS include the superoxide radical (O 2 • - ), hydrogen peroxide (H 2 O 2 ) and the highly reactive hydroxyl radical (OH•). Increased endogenous production, exposition to exogenous sources of ROS or reduction in antioxidant defense capacity cause molecular damages such as alterations in proteins, lipids and DNA, and may lead to cell death. Oxidative stress is believed to limit the lifespan of multicellular organisms [ 1 , 2 ] and oxidative lesions have been implicated in several human cardiovascular and neurodegenerative diseases [ 3 ]. A better understanding of the in vivo responses to oxidative stress is thus of major fundamental and practical importance. Much data describing the action of ROS and their derivatives in cultured cells are now available. For instance, ROS have been shown to activate signal transducing components, like p53 or members of the NF-κB pathway, resulting either in increased antioxidative protection or in activation of apoptotic pathways [ 2 ]. Nevertheless, a comprehensive integrated picture of the in vivo cellular responses of metazoans to oxidative stress is still not available. Genetic data suggest that different protection mechanisms are involved in vivo according to the type of ROS that induces the stress [ 4 ]. In addition, a wide diversity of macromolecules may undergo oxidative damage and induce secondary cellular stresses. These secondary effects of ROS could be similar to the alterations in macromolecules observed in other stress conditions, such as heat stress, endoplasmic reticulum (ER) stress (induced by accumulation of misfolded proteins), or UV-induced DNA damage. The relative importance of these common and specific responses to oxidative and other cellular stresses still has to be determined. In the yeast Saccharomyces cerevisiae , microarray experiments have shown that similar transcriptional responses are observed in a large number of different environmental conditions, including oxidative stress induced by H 2 O 2 or menadione [ 5 , 6 ]. According to the authors, this common environmental stress response (CER) may reflect the need for yeast to adapt quickly to rapidly changing external conditions. Similar transient variations of protein levels were also observed in proteomic experiments and highlighted the existence of an H 2 O 2 stimulon [ 7 ]. It is not clear whether such common stress responses exist in long-living multicellular organisms since, unlike unicellular organisms, their cells are probably submitted to slower and smaller variations of the extracellular medium; furthermore, the survival of just one cell is not generally crucial for the survival of the organism as a whole. Considering its powerful genetic and genomic tools, Drosophila melanogaster is a relevant model to address the question of the specificities of in vivo responses to various stresses in multicellular organisms and to identify novel genes that play a protective role. Nevertheless; there are some limitations to such studies on living flies. Firstly, adult flies are mainly composed of post mitotic cells; thus data obtained with flies may be relevant for comparison with the stress response of post mitotic tissues in other organisms (for instance mammals' neurons) but could be less useful to address the question of stress response in dividing cells. Secondly, limitations also arise from ROS-generating compounds delivery which in Drosophila is usually performed through food ingestion. This method severely limits kinetic studies of acute stress responses on flies, since, within a few hours, large fluctuations in the quantity of ingested food are observed in batches of flies transferred to a new medium. To overcome this problem some experiments were performed on starved flies. The major issue with such an approach is that the observed transcriptional changes could result from the starvation stimulus as well as from the effect of the studied compound. Therefore such experiments may in fact characterize the interference of two different stress responses with different induction times and kinetics rather than a bona fide oxidative stress response. A previous microarray study, performed with such a strategy on 4500 Drosophila genes, analyzed changes in transcription induced by paraquat, which produces superoxide radical (O 2 • - ) intracellularly: 5.2% of the genes (n = 236) were found to be stress responsive. Kinetic analysis revealed that transcriptional modifications lead to the establishment of a more or less stable new expression profile 12 hours after stress induction, thus indicating the existence of a long term stress response (LTSR) [ 8 ]. This stability probably reflects the late response to paraquat-induced stress but variations before 12 h are more difficult to interpret since they may also arise from the stress effects of starvation. This analysis also did not address the question of the specific responses to different ROS and could not distinguish between specific responses to oxidative stress and responses common to other cellular stresses. Furthermore, since the arrays covered only 30% of the estimated total number of Drosophila genes, this study was also limited for functional statistical analysis and detailed analysis of functional classes involved in stress response. From previous considerations, we chose to focus on comparisons of the long term transcriptional response (LTSR) of adult flies 24 h after ingestion of different stress-generating compounds. These responses may be representative of those of postmitotic tissue exposed to physiological chronic stress conditions (even if the level of stress is certainly higher in our experiments). Thus we investigated, at a full genome wide level, the transcriptional LTSR in adult Drosophila submitted during 24 h to three types of stresses: paraquat or H 2 O 2 -induced oxidative stresses and tunicamycin-induced ER stress. This latter drug inhibits N-linked glycosylation, thus leading to an accumulation of misfolded proteins in the ER (referred to as ER stress) which is known to elicit a specific response: the Unfolded Protein Response (UPR) [ 9 ]. We show in this paper that some of the transcriptional changes observed for these three stress conditions are similar, thus defining a class of multiple stress responsive genes. Nevertheless, in addition to this common long term stress response (CLTSR), many genes are transcriptionally regulated in a stress-specific manner. A statistical analysis identified classes of molecular functions or cellular processes over-represented inside clusters of genes undergoing transcriptional changes. Unexpectedly, both up and down regulations were observed for members of the same functional class. This may reveal novel functional specificities for these genes. In addition, we investigated whether genes that display significant transcriptional variations play a functional role in oxidative stress resistance. We present data suggesting that this could be the case for a large number of the stress-responsive genes identified in our study, which emphasizes the polygenicity of the stress responses, at both a molecular and a functional level. Methods Stocks All the lines tested for paraquat stress resistance were collected from the Bloomington stock center. To minimize genetic background effects, when the mutation was linked to a w + transposon insertion, the line was outcrossed for 4 generations against a w - isogenic strain of Canton S background before stress experiments. For homozygous lethal mutations we analyzed flies heterozygous for the mutation issued from a cross between the mutant line and the same w Canton S strain. Stress resistance tests and collection of fly tissues We used 50 ml vials containing 1 ml of a solid medium composed of 1.3% low melting agarose, 1% sucrose and either 1% H 2 O 2 , 5 or 15 mM paraquat, 12 μM tunicamycin (all from Sigma) or no toxic compound (control tubes). These compounds were incorporated at 45°C to avoid loss of activity. 3 day old males were placed in groups of 30 in these vials and maintained at 26°C with a 12:12 light-darkness alternation. In survival tests, dead flies were counted twice a day until the end of the experiment. In each experiment at least 3 vials of 30 male flies were used. To test mutant lines we performed three independent experiments in order to minimize false positive detection. Survival data were submitted to a log-rank analysis to detect statistically significant survival differences between mutant and w Canton S flies. We considered that a mutation had a significant effect on survival under oxidative stress when the mean of log 10 (p-log-rank) for the three experiments was lower than -3 and at least two experiments had p-log-rank < 0.001. For microarray experiments, for each condition, 200 Canton S males were kept 24 hours on the corresponding medium and then frozen in liquid nitrogen for subsequent RNA extraction. Independent batches of males from separate experiments were used for replicate experiments. All fly manipulations were performed at the same stages of the 12:12 light cycle to prevent any undesirable effects from circadian variations. Sample preparation and data analysis We analyzed 4 samples of control flies and 3 (paraquat 15 mM) or 2 (all other conditions) samples of stressed flies. Total RNAs were purified by three rounds of Trizol reagent (GIBCO/BRL) extraction before precipitation. cDNA were synthesized from 10 μg total RNA aliquots and biotin-labelled cRNA targets synthesized using the BioArray high yield RNA transcript-labelling kit (Enzo Biochem) according to the manufacturer's instructions. Hybridizations on Drosophila Genome Arrays (Affymetrix) and subsequent washing were performed on a GeneChip Fluidics Station according to the manufacturer's instructions before scanning on a GeneArray scanner. Data extraction was performed first by the MAS5 Affymetrix program which provides absolute values (AV) and detection p-values (DP) for each probe set. These data were loaded into an Access database for subsequent analysis. We retained only the experimental points that presented a mean value greater than 0.1 for the DPs of all the different samples of at least 1 of our 4 experimental conditions. This reduced the number of probe sets further analyzed from 14028 to 8976. The AV data from each microarray were then normalized against the AV mean value of the 4 control samples by a quantile method which performs optimally [ 10 ]. Since a large number of flies (~300) were used for each RNA sample hybridized to a microarray, variations in signal arising from individual transcription differences are greatly reduced. This is reflected in the high values of correlation coefficients between microarrays corresponding to the same experimental condition (data not shown). The normalized values were used for further comparison of each of the stress condition samples with the 4 control samples and for statistical validations of the variations using the SAM program [ 11 ]. For this analysis, we used a fold change threshold value of 1.5 and a mean FDR (false detection rate) lower than 10%. 1368 independent probe sets that fulfilled these conditions for at least one type of stress were retained for further analysis. A hierarchical divisive clustering of the data of these probe sets was performed using the SOTA [ 12 ] implementation available at . For each probe set, the ratios for all the combinations between stress conditions AVs and reference AVs were computed and Ln2 transformed. The SOTA algorithm used on this dataset with linear correlation distance with 0 offset, 1000 cycles and 1.01 variability threshold parameters, led to the detection of 19 clusters. Functional analysis Information from the Gene Ontology (GO) database (December 2003, [ 13 ]) was combined with the Affymetrix data through the THEA program to investigate which classes are over- or under-represented in the dataset of stress responsive genes. Briefly, according to the Gene Ontology hierarchical structure, each probe set was assigned, when possible, to its original annotation and to the associated parent annotations. The number of probe sets for the different GO terms was computed for groups of probe sets defined according to different criteria (such as whole microarray probe sets, detected probe sets or probe sets belonging to a given cluster). For each GO term G, the distribution between the group D of all the detected probe sets (N G D probe sets issued from a total of N D , probability P G = N G D /N D ) and a group C of particular interest, such as a cluster (N G C probe sets issued from a total of N C ) are compared. The hypothesis of equal repartition between these two groups would predict that, inside the N C probe sets of group C, N C *P G probe sets should be associated to the GO term. We computed the p-value P N for the null hypothesis of no association between the two distributions, with a binomial distribution with N C tries, a probability P G and N G C successes. Threshold values for P N helped to define the GO terms over- or under-represented in the group C. Quantitative real time RT-PCR analyses Experiments were performed as described [ 14 ] with 2 μg of the total RNA samples used for microarrays (control, P15, P5, H1 and T12). Primers were designed to generate an amplicon of about 100 nucleotides and their sequences are described below (Forward/Reverse primers): FBgn0015039: TATGCTCTTCAACCTACTGCTGC/TAGGCGTAAAATTGAATCCACTC FBgn0010383: GACGCTGAACGGATATGGCAT/ATGTAGGTCATCCCGAACTGTC FBgn0015035: CAACTCTGAATTTGGCTCTCATCC/AGCGGGTTTCTCCTCCTCAA FBgn0034334: GAAGCCGGATATGTTACGCAAG/TTCACCAGATAGCCGATGATG FBgn0038024: CCTCAACAAGTACCCGAATGTG/TACTCCCTTCAGTTCCACGGC RP49: CCGCTTCAAGGGACAGTATCTG/CACGTTGTGCACCAGGAACTT Annealing temperature was 62°C except for RP49 and FBgn0034334 transcript level quantifications, for which it was 60°C. We normalized samples by comparison with the levels of the RP49 housekeeping gene. Levels of transcripts under various stress conditions are compared with the transcript level observed in control flies. Results Transcriptome variations in adult Drosophila are strongly dependent on the type of stress to which they are submitted We wished to compare the transcriptomes of flies submitted to continuous stresses induced by ingestion of paraquat, H 2 O 2 or tunicamycin at concentrations leading to similar effects on viability. Survival curves were obtained for 3 day old male flies raised on media containing different concentrations of these drugs (Fig. 1 ). Concentrations of 1% H 2 O 2 , 5 mM paraquat and 12 μM tunicamycin had similar effects on the survival of flies and were chosen for further studies. A paraquat concentration of 15 mM was also used for comparison with previous studies [ 8 ]. Figure 1 Lifespan reduction in Drosophila submitted to paraquat-, H 2 O 2 - and tunicamycin-induced stress 3-5 day-old Canton S wild type males were placed at t = 0 by groups of 30 in vials containing 15mM paraquat (P15: ●), 5 mM paraquat (P5: ◆), 1% H 2 O 2 (H1: △) or 12 μM tunicamycin (T12: □). Dead flies were counted twice a day to determine survival. 3 vials of 30 individuals were used for each condition. When no toxic compound had been incorporated in the medium, more than 90% survival was observed at t = 120 h (not shown). Similar average lifespan was observed for P5, H1 and T12 around t = 80 h while it was significantly reduced in P15. Arrow indicates the time (t = 24 h) at which flies were collected for RNA extraction. Note the 20% lethality observed at this time for P15 condition. Dead flies were discarded before RNA extraction. RNA were obtained from separate experiments with 3 day old male flies reared at 26°C with a 12:12 hours light and dark (LD) alternation, on media containing no drug (4 reference samples), 15 mM paraquat (P15: 3 samples), 5 mM paraquat (P5: 2 samples), 1% H 2 O 2 (H1: 2 samples) or 12 μM tunicamycin (T12: 2 samples). Thus a minimum of 8 pairwise comparisons were made for each condition which ensured good statistical significance, as confirmed by quantitative PCR experiments (see below). Stresses were induced 24 h before collection of flies, which occurred at the same time (9 h) of the 12:12 hours light/dark cycle to eliminate the effect of circadian variations. Hybridizations were performed on Affymetrix GeneChips and the data processed as described in the Material and Methods. The statistical significance of transcriptional variations was assessed using the SAM program with a threshold of 1.5 [ 11 ]. A good correlation was observed between our P15 results and previous studies with the same stress conditions [ 8 ]: among the 246 stress responsive ESTs of Zou et al. , 201 were associated to a detectable probe set on our chip, 56% of which were selected by SAM analysis and 72% of which displayed a fold change greater than 1.3 (not shown). The remaining discrepancies may arise from differences in statistical selections, in analyzed tissues (thorax and abdomen in [ 8 ], whole flies in this study) or in genotype: compared to the w 1118 flies used in [ 8 ], our wild type Canton S flies were more resistant to paraquat 15 mM (mortality of 20% vs 54% at 24 h) and presented an increased medium lifespan (48 vs 35 days at 26°C, on standard medium). Among the 8976 probe sets significantly detected in adult flies (see Material and Methods), 1111 were up or downregulated with P15 treatment, this number being reduced to 608, 72 and 221 for P5, H1 and T12 treatments respectively. Thus, even with similar effects on flies survival, the fraction of the genome detected as stress responsive on microarrays was highly dependent on the nature of the stress, varying about ten times from 7% (P5) to 0.7% (H1). This first analysis defined a total of 1368 probe sets and 1343 genes which are induced or repressed at least in one stress condition. They were used for further analysis. Common and specific responses to different stress We plotted transcriptional variation correlations for the different oxidative stress conditions (Fig. 2 ). We observed a high degree of correlation between the two paraquat experiments (correlation coefficient c = 0.86, Fig. 2a ). The slope of the linear regression curve, however, was 1.14 which indicates that variations in transcription induced by paraquat may be dose-dependent for most genes in D. melanogaster . Lower correlations were observed for the linear regressions between P5 ratios and either H1 ratios (c = 0.64, slope = 0.40, Fig. 2b ), or T12 ratios (c = 0.43, not shown). Figure 2 Correlations between P5 and P15 or H1 microarray measurements For each of the 1368 probe sets selected in the SAM analysis, the mean Ln2 ratios between the absolute values (AV) for stress and reference conditions were compared in two dimensional plots. Bold lines are the linear regression curves for the two comparisons, the thin lines correspond to a complete correlation for eye guidance. A good correlation is observed between P5 and P15 with a slope of 1.14, while it is much weaker between P5 and H1 (slope of 0.4). Clustering analysis provided further information about the specificity of stress responses. We chose an unsupervised divisive clustering method (SOTA [ 12 ]) to analyze the data and we checked that other methods such as Self Organizing Maps [ 15 ] yielded similar results (not shown). The SOTA analysis predicted 19 clusters. The complete list of the 1368 probe sets with their cluster assignment is provided as Tab.S1 (Additional file 1 ) in supplementary data. In Tab.1, (Additional file 8 ) we present the average log-ratios in each stress condition for the 19 identified clusters. These data confirm the high correlation between the results for P15 and P5 and the general tendency toward smaller variations for P5. However, the genes included in cluster 7 exhibit a more severe repression in the P5 condition than in the P15 condition which may reflect a differential transcriptional response as a function of oxidant concentration. Notably, in clusters 5, 6, 7, 9, 10, 13, 16 and 18 which regroup 642 probe sets, significant variations for H1 were observed in the same direction than for P5 or P15. This suggests that, for a large number of genes, both oxidative compounds induce similar transcriptional responses. Therefore, the fact that the number of probe sets validated by the SAM procedure as being significatively affected in the H1 condition is smaller than in the paraquat conditions may be a consequence of a similar but weaker effect of H 2 O 2 on the transcriptome rather than fundamental differences in the responses to the two oxidants. What is the specificity of the oxidative stress responses induced by paraquat or H 2 O 2 compared to the ER stress response induced by tunicamycin? The 19 clusters from Tab.1 (Additional file 8 ) can be regrouped into 7 large classes of genes: Classes A and B contain genes respectively downregulated and upregulated in both oxidative stress and ER stress conditions. Inside these two large groups, 237 genes included in clusters 9, 10 and 13 are regulated in a similar fashion in all four stress conditions. Genes from classes C and D (48% of stress responsive probes) are respectively downregulated and upregulated by oxidative but not ER stress. Conversely, class F genes are upregulated in ER stress but not in oxidative stresses. In the atypical classes E and G, opposite variations are observed for the two types of stress: genes of class G are upregulated by ER stress but downregulated in oxidative stress while genes of class E display an opposite behavior. Overall, our data emphasize both specificities and similarities in these stress responses: the classes A and B (238 and 276 probe sets, respectively) which include genes displaying similar responses to both oxidative and ER stresses, represent a sizeable fraction (38%) of the stress responsive probes. In contrast, genes that vary in opposite directions, included in the classes E (104 probe sets) and G (60 probe sets), represent a smaller part of those stress responsive probes (12%). Classes of stress responsive genes Using the Gene Ontology annotation [ 13 ] we identified the molecular functions that are over- or under-represented among all the 1368 stress-responsive probesets compared to the distribution of functions identified for the complete set of 8976 detectable probesets (see Material and Methods). The analysis was first performed independently for each set of genes validated by the SAM procedure for each stress Table 2a to c (Additional file 9 ). A similar analysis for biological processes is given in supplementary Table S2 (Additional file 2 ). The most prominent functional classes over-represented in the paraquat sets are the peptidases (including peptidases which are part of the proteasome complex), the peptidase inhibitors, the glutathione transferases (GT) and oxidoreductase enzymes or electron transporters, including the P450 cytochromes. These classes could all be involved in the detoxifying processes that follow oxidative stress and are discussed in more detail below. In addition, lipases and more prominently the triacylglycerol lipases, also over-represented, may contribute to the regeneration of membranes after oxidative damage. Most of these features seem to be part of a general stress response since triacylglycerol lipases, peptidases with chymotrypsin or trypsin activity and GTs are also over-represented in the H 2 O 2 and tunicamycin specific sets of genes. The transaminases, the cyclohydrolases, the oxidoreductases and the hydroxymethyltransferases define the signature of functional classes over-represented in the two types of oxidative stresses. In contrast, proteins which bind to iron ions or monooxygenases are specifically over-represented in the paraquat set. As expected, the ER set presents features that are distinct from oxidative stress responses, that is the over-representation of hydrolases acting on glycosyl compounds, UDP-glucuronosyltransferases and tRNA ligases. This last class suggests that modifications of the translation rate may be an in vivo response to ER stress. Besides these ER stress-specific classes, peptidases with elastase activity and epoxide hydrolases are over-represented in both paraquat- and tunicamycin-induced stresses. Interestingly, this last class of proteins is involved in the metabolism of juvenile hormone which has been shown to be involved in heat stress response [ 16 ]. We then performed a similar analysis for the groups of genes identified in the clustering process. To increase the statistical significance of the analysis, we used the 7 groups A to G instead of the 19 initial clusters. This analysis, given as Tables S3 (Additional file 3 ) and S4 (Additional file 4 ) of supplementary data, allowed us to identify molecular function and process signatures in some clusters. For instance, for the genes repressed for oxidative and ER stress conditions (group A) specific over-representations are observed for alkaline phosphatases, diazepam binding proteins and proteins involved in acyl-CoA metabolism. Signatures of group B (genes upregulated for oxidative and ER stresses) include proteins involved in response to abiotic stimuli, including GTs and glutathione peroxydases, and tRNA ligases. This last feature may indicate that the organism reacts to sustained stress by an increase of protein synthesis. Nevertheless, genes involved in proteins biosynthesis are surprisingly under-represented among the stress responsive genes. Retinoid binding proteins and transporters are specifically over-represented in group C. Surprisingly, in this group of genes, a large number of peptidases are present along with a strong proportion of protease inhibitors. Signatures for group D (genes upregulated under oxidative but not ER stress) include chaperones associated with the heat shock response, glutamate synthases and proteins involved in ATP-dependent proteolysis. Glutamate synthases, together with the upregulated genes Ahcy13 and Eip55E , may be required to increase the pool of glutathione, a major actor in redox regulation and phase II detoxification [ 17 ]. Additional signatures for group D include two other processes, inosinate (IMP) biosynthesis and amino acid biosynthesis. Interestingly, we found under-representation of their parent processes (closer to the root of the ontology), namely nucleic acid metabolism and protein biosynthesis. Finally, in the ER stress specific groups F and G, the disulfide isomerase proteins and the glucuronosyltransferases, known to play an important role in the UPR following ER stress in yeast, are over-represented together with proteins involved in lipid metabolism. Overall, our data suggest that oxidative and ER stress induce comparable transcriptional modifications of a significant number of genes known to be involved in a limited number of functional classes. Gene-specific stress responses inside functional classes In contrast to previous work limited to partial analysis of the genome, the use of whole genome Affymetrix chips allowed us to investigate the specificity of transcriptional responses for genes associated with a given functional class. The thioredoxin system plays a major role in oxidative stress defense and needs to be better functionally characterized. In Drosophila, the peroxiredoxin proteins show thiol-dependent peroxidase activity and use thioredoxin, but not glutathione, as a source of reducing power. Indeed, Drosophila lacks glutathione reductase [ 18 ] and its function is apparently substituted by thioredoxin reductase. Interestingly, we observed significant differences in the transcriptional behavior of the members of the thioredoxin system when flies were submitted to paraquat stress. The thioredoxin class (GO:0030508) counts 7 members with either a sequence matching perfectly the consensus catalytic site WCGPCK ( CG4193 , CG3864 , Txl/CG5495 and CG1141 ) or with one mismatch ( CG8993 , CG13473 and CG3719 ). Only the Txl gene is significantly overexpressed over the 1.5 fold threshold, the other genes presenting no change or a weaker overexpression ( Trx-2 ). This strongly argues for a specificity of these thioredoxins in the defense process with an important role for the Txl gene. Similarly, among the five genes presenting a thioredoxin peroxydase activity (GO:0008379), only two ( CG12013 and CG1633 ) are overexpressed, the others ( CG12174 , CG5826 and CG6888 ) being unaffected in the studied conditions. Among the related genes only the peroxyredoxin CG11765 is overexpressed, while the glutathione peroxydase-like CG15116 , very similar to the thioredoxin peroxydase CG12013 , is significantly repressed. These specificities strengthen the concept of a functional diversification of these proteins in spite of their common ability to confer resistance to oxidants in Drosophila cells [ 19 ]. When the organism is challenged to oxidative stress, in addition to performing direct enzymatic detoxification of toxic compounds, it must also limit the appearance of the most toxic species. Therefore, since free iron catalyses the production of the highly toxic hydroxyl radical (OH•) from H 2 O 2 by the Fenton reaction, its concentration must be tightly controlled. Transferrin and ferritin proteins play a major role in this control [ 20 ]. Furthermore, variations in iron concentration may modify gene expression in the cell through the iron regulatory proteins Irp that bind to the iron responsive elements (IRE) located in their target genes UTRs. Under paraquat stress, we observed a coordinated and specific response of genes used in regulation of free iron concentration and iron-regulated response: the two ferritin subunits and the iron regulatory protein 1B ( irp1B ) are overexpressed, while the transferrin 1 ( tsf1 ) gene is severely repressed. Nevertheless, neither the irp1A nor the tsf2 and tsf3 genes show any significant transcriptional change. This suggests that each isoform of these families plays a specific role in iron homeostasis in the organism. More complex specificities can be observed in larger functional classes. The glutathione transferases (GTs; GO:0004364) play important roles the detoxification process after genotoxic stresses [ 21 ]. As expected, a large number of them (16/34) are overexpressed after paraquat-induced oxidative stress Table 3a (Additional file 10 ) but 4 are underexpressed under the same conditions. One of these GT repressed by paraquat (FBgn0034334) is also severely repressed by H 2 O 2 -induced stress. Moreover, among the 16 GTs overexpressed in paraquat-induced stresses, 7 are overexpressed and 3 underexpressed in ER-stressed flies, while 6 show no other significant transcriptional variation. Interestingly, all the GTs overexpressed in both paraquat and tunicamycin experiments are also slightly induced in H 2 O 2 -stressed flies. Overall, our data suggest that both "generalist" GTs that are able to protect the organism against various stresses and more specialized GTs, required only for protection against well defined stresses, coexist inside the cell. A similar conclusion can be drawn for the P450 cytochromes (GO:0015034). Among 58 detectable P450 cytochromes, 12 are underexpressed and 12 overexpressed during paraquat stress, 4 of these latter being also upregulated in tunicamycin-stressed flies (Tab.3b, Additional file 10 ). We observed a general tendency of these paraquat-inducible P450 cytochromes to be also overexpressed in H 2 O 2 -stressed flies. One cytochrome gene (FBgn0015035) displays peculiar behavior since it is induced by paraquat but strongly repressed by H 2 O 2 . Another gene (FBgn0015039) is induced specifically by tunicamicyn. Quantitative RT-PCR experiments confirmed the specificities observed on microarrays (Fig. 3 ). Figure 3 Comparison of transcript level variations detected with microarrays and with quantitative real-time PCR (Q-RT-PCR) Transcript levels were analyzed for genes encoding three P450 cytochromes (FBgn0015039, FBgn0010383 and FBgn0015035) and two glutathione transferases (FBgn0034334 and FBgn0010041). The Ln2 ratios between the transcript levels under stress conditions (P15, P5, H1 and T12) and the reference condition, obtained with Q-RT-PCR (white bars) and microarray analysis (black bars), are indicated for each gene. Error bars: standard errors. The complete data for the peptidases class (GO:0008233) analysis – given as Tab.S5 (Additional file 5 ) of supplementary data- provides a striking feature: most of the 131 peptidases selected by the SAM analysis (among 361 that were detectable) are downregulated by either both paraquat-induced oxidative stress and ER stress (54 peptidases) or paraquat-induced stress only (41 peptidases); nevertheless, a small number (36) of them are upregulated by paraquat. Closer examination of these latter genes revealed that 22 are proteasome endopeptidases. Further analysis of the proteins belonging to the proteasome complex, (GO:0000502) (which also contains proteasome regulatory proteins) shows that 33 out of 45 detectable proteasome constituents (73%) are likely upregulated by paraquat treatment (Tab. 3c, Additional file 10 ), both 19S and 20S subunits being coordinately regulated. Interestingly, the induction level is clearly correlated to the dose of paraquat used. Moreover, this induction is very specific since it is not observed in H1 or T12 conditions for any of these genes. The functional significance of this observation needs to be addressed in Drosophila strains mutant for proteasome subunits, challenged with paraquat, H 2 O 2 or tunicamycin stresses. Many genes transcriptionally affected by oxidative stress modulate oxidative stress resistance When a fly experiences an oxidative stress we can expect that the subsequent transcriptional modifications may arise from several mechanisms. Firstly, the organism can mount a protective response, for instance by inducing proteins which will reduce adverse consequences of the toxic compound. Only a few functional classes (such as GTs, electron transporters, chaperones) identified in our functional analysis of stress-regulated genes can be clearly associated to such known protective mechanisms from oxidative stress (Tab. 2, Additional file 9 ). Secondly the toxic drug itself may induce transcriptional changes which could play a role in its toxicity. The relative part of these protective or toxic responses to oxidative stress is unknown. We thus investigated whether genes detected in our microarray analysis could be involved in oxidative stress protection against paraquat or in its induced toxicity. We addressed this issue using a genetic approach, taking advantage of the availability of numerous strains bearing mutations in genes detected in the microarray paraquat set. Twenty nine such lines were recovered from public stock centers and adult flies were analyzed for their survival after transfer to a medium containing 10 mM paraquat. Most of the mutations used arise from P elements insertion in the 5' regulatory region of the genes which are expected to induce partial or complete loss of function mutations. Indeed, as shown in table 4 , most of them have been characterized as either lethal recessive mutations or hypomorphic loss of function mutations and, in some cases, do not complement a deficiency. Particular attention was paid to ensure that the genetic background was controlled in these experiments and stringent statistical conditions were used for the data analysis (see material and methods). Several conclusions can be drawn from these genetic experiments. a) First, as shown in Fig. 4a , under these conditions, a high proportion of the 29 tested strains present statistically significant survival differences from the w Canton S reference strain. Indeed, the results of our experiments show that 13 mutant lines out of 29 tested (45%) are either significantly more resistant (6 lines) or more sensitive (7 lines) to paraquat than their wild-type counterparts (Tab. 4, Additional file 11 and Fig. 4b ). This ratio is at least 10 times higher that what is expected from previous genetic screens (see discussion) and suggest a strong relationship between transcriptional stress response and functional in vivo susceptibility to oxidative stress. b) For the genes studied there is no clear correlation between the observed induction or repression under paraquat treatment and the effect of the mutation on the paraquat resistance or sensitivity phenotypes (Tab.4, Additional file 11 ). This suggests that, in the steady stress conditions used, both deleterious and protective gene regulations are taking place. c) Our genetic data point out the large functional diversity of genes that are able to modulate the oxidative stress resistance in vivo : ion channel ( Sh ), thioredoxin reductase ( Trxr-1 ), fatty acid elongase ( Baldspot ), phosphatase ( aay ) and phosphatase regulator ( CG9238 ), transcription factor ( Xbp1 ) and peptidase ( Acer ). Interestingly, among these 13 mutants, only 2 were previously known to be associated to oxidative stress resistance ( Sh and Trxr-1 ) and most of them had no known function in adult flies. Coupling between microarray and genetic experiments is thus a powerful way to extend our knowledge on the biological function of Drosophila genes without biased hypothesis and to provide some clues on the function of mammalian homologues. Figure 4 Resistance to paraquat-induced stress of flies mutant for genes identified in microarray experiments a) 29 Drosophila lines bearing mutations in genes identified in our microarray experiments as being stress-responsive were recovered from public stock centers. When the mutation was linked to a w + transposon insertion these lines were outcrossed with a w + Canton S reference line. 3–6 day old male flies were then tested for their resistance to oxidative stress 68 h after transfer to 10 mM paraquat medium. Tested flies were either homozygous (notation #i/#i in the X axis) for viable mutations or heterozygous (notation #i/ w ) for lethal mutations (in this case they are issued from a cross with w + Canton S females). For simplicity, identification of lines (#i) refers to the Bloomington stock number and the genotype of the line is provided in Tab. 4. We present in this Figure the results of one of three independent experiments that we used for the complete statistical analysis presented in Table 4. Compared to male flies issued from a cross between w - males and Canton S females (noted w/+, dark bar), significant differences in resistance or sensitivity to paraquat can be observed for a large number of the lines tested. Error bars: standard error. b) Example of survival curves on 10 mM paraquat-containing medium of some mutant male flies. Flies heterozygous for a lethal mutation in the Angiotensin converting enzyme related ( Acer ) gene are sensitive to paraquat, while flies homozygous for an insertion in the gene CG9238 are clearly more resistant to paraquat than w /+ control flies. Neither of these genes was previously suspected to play a role in oxidative stress resistance. For instance, we found that the Dgp-1 gene is induced in flies challenged with paraquat stress and that its disruption leads to stress resistance. The Dgp-1 protein is strongly similar to the mammalian GTPBP1 protein which presents a GTP binding domain and strong similarity with the elongation factor Ef-Tu [ 22 ]. Interestingly, expression of GTPBB1 is enhanced by gamma interferon in a monocytic cell line, suggesting that this protein in involved in host defense mechanisms. Nevertheless, no phenotype was observed in mice disrupted for this gene, maybe because of compensation by a gene of the same family [ 22 ]. Our data provide evidence that, in flies, Dgp-1, the GTPB1 homologue, is indeed involved in protective mechanisms against stress. The similarity with EF-Tu suggests that this protection might be linked to a downregulation of protein synthesis. In agreement to this hypothesis, it is noticeable that mutants for the translation negative regulator Thor present a significant sensitivity to paraquat stress (confidence index -2,4 in Tab. 4, Additional file 11 and Fig. 4a ) and has been shown to be sensitive to bacterial infection [ 23 ]. Discussion In this paper we present the characterization of the in vivo transcriptional responses of adult Drosophila males submitted to four different continuous stresses : paraquat (two conditions), H 2 O 2 or tunicamycin. Experiments on yeast submitted to several types of stress including oxidative stress have shown that fast transient responses occurring during the first three hours are followed by stable long term (>12 hours) changes [ 5 , 6 ]. Similarly, previous experiments on paraquat-induced stress in Drosophila have shown sustained long term changes in transcript levels which are more or less stable 12 hours after stress induction [ 8 ]. Since, as discussed previously, there are clear technical limitations to short term kinetic studies on Drosophila submitted to ingestion driven stress, we focused our efforts on the observation of these long term stress responses (LTSR) and performed our transcriptome analysis 24 hours after stress induction. At this time point, more than 95% of flies were alive for P5, H1 and T12 treatments, while 19% of lethality was observed in the P15 experiments. In addition, during the next 24 hours, in all conditions, less than 30% of the animals died. We thus expect that any secondary effects linked to the level of lethality are minimal in our experiments. In agreement with this assumption we noticed that in the experiments of Zou et al. similar results were obtained when the transcriptome was analyzed 12 hours (when lethality was negligible) or 24 hours after ingestion of 15 mM paraquat. Furthermore, when functional analysis was performed, we were unable to detect significant differences in the signature of the genes detected in the P5 and P15 experiments, which should be the case if the level of lethality plays an important role for gene transcription. We thus conclude that the secondary effects linked to the levels of lethality in the Zou et al. experiments and in our work do not significantly affect the transcriptome and that the variations observed are primarily due to the stresses experienced by the flies. Our data present clear evidence of a common long-term stress response (CLTSR) in transcription of Drosophila genes: at least 237 genes contained in clusters 9, 10 and 13 show similar changes in transcription for the three stressors studied. This number could be a minimum estimation of the extent of the CLTSR, since it is mainly limited by the weaker transcriptional variations observed in the H 2 O 2 -induced flies. We think that this may be due to a smaller number of cells experiencing stress when flies ingest H 2 O 2 . Additional data for comparison with various stress responses (immune stress [ 24 ], starvation [ 25 ] and, during the submission of this work, hyperoxia and aging [ 26 ]) are presented in Supplementary text T1 (Additional file 7 ) and Table S6 (Additional file 6 ) and confirm the existence of a core of similar transcriptional responses between these stresses. The CLTSR shows certain similarities with the common environmental response (CER) described in yeast [ 5 , 6 ]: in both cases heat-shock genes, genes involved in the detoxification processes, or associated with fatty acid metabolism and DNA repair show similar changes in all the stress conditions studied. Nevertheless, there are also obvious differences between these two responses. For instance, in contrast to what occurs in CER, no large scale coordinated transcriptional changes for genes involved in translation inhibition or energy production were detected in CLTSR. This may reflect the fact that, in our experiments, the CLTSR corresponds to a long-term adaptation of the stressed Drosophila cells, while the variations observed in yeast are transient (of course we cannot exclude long term post-transcriptional modifications in the translation apparatus and the metabolic pathways activities of stressed flies). Alternatively, these data may reflect differences in the adaptation of dividing cells (yeast) and post-mitotic cells (Drosophila) to stress conditions. For instance, in the latter case, upregulation of the iron responsive protein 1b gene may lead to translational downregulation of the succinate dehydrogenase gene through an IRE [ 27 ] and hence modulate energy production as in the yeast, but in a different way. Additionally, in Drosophila, translation repression may also be involved in stress response but relying on a small subset of genes (which would then not have been detected with our functional analysis). Interestingly, in support to this hypothesis, we found that the translational repressor Thor is induced under stress conditions and that mutations in this gene confer a slight but significant sensitivity to paraquat-induced stress. However, our finding that tRNA ligases are upregulated in oxidative and ER stress may indicate a requirement for increased protein synthesis under sustained stress conditions. Kinetic studies using another oxidative stress paradigm are needed to clarify this point. In view of our results, it would be also interesting to investigate possible variations in stress response in mammalian tissues either mitoticaly active or quiescent. Besides their similarities, the LTSRs also display marked differences. One of the most striking specific expressions is displayed by the genes encoding for the proteasome subunits. These proteins belong to the two large complexes 19S (regulatory complex) and 20S (proteolytically active complex) which, together, form the 26S proteasome [ 28 ]. Most of them (73%) are specifically induced by paraquat- but none by H 2 O 2 - or tunicamycin-induced stresses. It is also noticeable that, in contrast to proteasome constituents, ubiquitin protein ligases are under-represented among paraquat responsive genes. The 20S proteasome, inactive in its native form, is able to specifically degrade oxidized proteins in vitro and in vivo, and has been considered to be the main actor in this process [ 29 ]. Nevertheless, it has been recently proposed that, while the 20S proteasome is active during oxidative stress and limits the accumulation of oxidized proteins, the 26S, inactive in presence of ROS, "cleans" the cell in the following recovery process, eliminating thereby the accumulated altered proteins [ 30 ]. This seems to be a very important aspect of oxidative stress defense since oxidization of proteins can result in protein fragmentation and partial unfolding, and induce the formation of cytotoxic insoluble aggregates, a process that is known to be implicated in an increasing number of human pathologies [ 31 , 32 ]. The observed coordinated upregulation of genes encoding both 19S and 20S proteasome subunits when Drosophila cells are submitted to continuous paraquat stress strongly suggests that both complexes are indeed important in vivo for oxidized proteins degradation. We observed no such induction of proteasome components in H 2 O 2 -stressed Drosophila. This result is coherent with previous studies shoving that the proteasome subunit are not transcriptionally regulated in cultured mammalian cells treated with H 2 O 2 [ 33 ]. However this is surprising since it has been shown, in mammalian cells, that the proteasome is in fact involved in the degradation of misfolded glycoproteins as well as oxidized proteins after H 2 O 2 treatment [ 34 ]. Recent data in lens epithelial cells showed that H 2 O 2 induces an increase in proteasome activity and E1 ubiquiting activation enzyme levels without any increase in E1 mRNA levels [ 35 ]. In view of our data, we propose that two different strategies are used in D. melanogaster to deal with oxidative challenge and increase proteasome activity: one response, induced by H 2 O 2 , would rely on post-transcriptional mechanisms as shown in mammalian cells; while the other response, induced by paraquat, would rely on coordinated increase of transcription of the proteasome genes of both 19S and 20S subunits. A number of functional classes are clearly over-represented among the genes involved in the LTSRs. The analysis of these specific functional classes revealed an important heterogeneity of stress-specific responses among their members. For instance, we have shown that only a subset of genes potentially involved in the thioredoxin pathway are upregulated during paraquat stress. Whether the remaining genes are involved in an earlier phase of the stress response, in a subset of tissues or in other processes unrelated to stress protection needs to be addressed. Interestingly, in agreement with this last hypothesis, one of these genes, Jafrac2, which codes for a thioredoxin peroxidase, has been recently assigned an unexpected role in caspase-regulated cell death [ 36 ]. The P450 cytochromes and the glutathione transferases also display striking stress-specific responses. For the GTs, 3 genes are downregulated by tunicamycin and 4 by paraquat, while 6 are upregulated by paraquat and 7 by both drugs. When we tried to correlate this information with GT classifications [ 21 ] we found that the latter group contained almost exclusively δ-type GTs (Table 3a). This suggests that this insect-specific class, unlike other Drosophila GTs, may have acquired a broad-spectrum detoxifying function which is required to counteract both oxidative and tunicamycin-induced cellular damages and/or that these GTs molecular targets are altered in both types of stress. One important issue is whether our findings are representative of long term transcriptional responses in Drosophila submitted to real physiological chronic stresses. Indeed, the stress levels experienced by flies in this work are probably much higher than those experienced in real life. Nevertheless, the tight correlation that we observe between P5 and P15 experiments demonstrates that most of the genes undergoing transcriptional changes at a high concentration of paraquat display similar changes (although at a reduced level) when the concentration is threefold lower. This suggests that many genes identified in this study may also be induced in low intensity chronic stress. A striking feature of our results is the large number of genes not previously associated with stress response which show transcriptional changes under paraquat-induced oxidative stress conditions. We investigated the biological validity of these observations in a genetic study of mutations in some of these genes. Since our microarray data suggest that the stress responses may be highly polygenic (with at least 10% of the genome involved), we took a particular care to ensure that there was a controlled genetic background in these experiments. We found that 45% of the mutations tested were associated with either resistance or sensitivity to paraquat, which confirms this idea of a highly polygenic process. It should be stressed that, since many of the tests were performed on heterozygous flies, the proportion of genes functionally involved in oxidative stress resistance may be higher. Extrapolation of the results obtained with this small subset of 29 genes to the 1107 genes found to be regulated by paraquat, suggests that some 500 genes may modulate paraquat sensitivity in vivo . This contrasts with two previous genetic screens to detect paraquat hypersensitive mutants, which concluded that only a few genes are involved in paraquat hypersensitivity [ 37 , 38 ]. These studies however analyzed only EMS viable mutations on the X, 2nd and 3rd chromosome. They would thus have missed any lethal mutations that could confer a sensitivity phenotype to heterozygous flies by gene dosage reduction. In fact, when we performed a P{ w + ; UAS}- based screen we found that a large proportion of P-element insertions may confer H 2 O 2 or paraquat resistance or sensitivity ([ 14 ] and Girardot et al. unpublished) in agreement with the results presented here. If all the transcriptional responses to a stress were protective for the organism; we would expect a clear correlation between the direction of the transcriptional response of the genes studied and the effect of their mutations on stress resistance. A significant result of our experiments is that we could not find such a correlation. It thus appears that the transcriptional responses to oxidative stress may be either protective or deleterious for the flies. The simplest explanation for this result is that, besides the protective responses mounted by the organism cells (for instance in inducing detoxifying proteins), the paraquat also induces transcriptional changes that play a role in its toxicity. In mammalian cells, several transcription factors may be regulated by oxidative stress, either by direct modification by the ROS or through signaling pathways, and have either pro- (Jun, p53) or anti-apoptotic effects (NF-κB, HSF1) [ 2 ]. In addition, the choice between survival and apoptosis may depend on the intensity of the stress and on the cell type, as it has been clearly demonstrated in the case of p53 [ 39 ]. Signaling pathways which activate these factors are strongly conserved between mammals and Drosophila and it is conceivable that, like in mammalian cells, their activation in flies by oxidative stress may induce complex transcriptional responses of both pro-survival and deleterious factors. In this case the integration of these complex responses at the level of the organism will determine the final outcome (protective or deleterious) and, eventually, in the case of a transient stress of limited intensity, the return to an unstressed equilibrium state. Thus the protective or deleterious role of a stress responsive gene cannot be predicted simply but should be uncovered systematically by genetic studies. Interestingly, in our genetic experiments, halving the dosage of the Xbp1 gene resulted in increased sensitivity of flies to paraquat-induced stress. Xbp1 is known to be involved in ER stress response in mammals [ 40 ]. It has been shown that it is regulated by processing of its mRNA by the C-terminal endonuclease Ire1. Conversely, we observed no transcriptional change of Xbp1 in Drosophila challenged with tunicamycin but it is overexpressed in oxidative stress conditions. Our in vivo genetic study suggests that this regulation is functionally relevant to oxidative stress protection in Drosophila. Thus Xbp1 may protect against different stress conditions through different modes of regulation (transcriptional or post-transcriptional regulation). In agreement to the conservation of this mechanism between flies and mammals, it has been shown recently that, in a mammalian dopaminergic cell line, Xbp1 is induced by the parkinsonian mimetic 6-hydroxydopamine which is known to induce oxidative stress [ 41 ]. Another gene that affects the flies stress resistance in vivo is Acer . This gene encodes one of two Drosophila proteins homologous to the mammalian angiotensin converting enzyme (ACE) gene family. Controversial findings have linked Ace to stress resistance and aging ([ 42 ] and references therein). Acer is more similar to the mammalian gene Ace2 . It has been recently shown that both Acer and Ace2 are essential regulators of heart function [ 43 ]. Interestingly, complete targeted disruption of Ace2 in mice results in increased angiotensin II levels and upregulation of hypoxia-induced genes. In Drosophila, the targets of Acer are not known and complete loss of function of the gene results in embryonic lethality. We found that halving the dosage of Acer in adult flies results in increased sensitivity to paraquat stress. Considering the mammalian data, one hypothesis to explain this result is that heart cells of Acer /+ flies may already experience a mild hypoxic stress which sensitizes them to the additional paraquat-induced oxidative stress. Targeted expression of Acer in Drosophila heart cells may help to test this hypothesis. In this genetic study, based on a small subset from the genes found to be regulated by stress in our microarray experiments, we identified genes with no previously known function as in vivo modulators of oxidative stress resistance. Since genomic programs steadily increase the number of transposon targeted genes it will become easier to perform this kind of genetic analysis to increase our knowledge of integrated mechanisms of stress resistance in Drosophila. In conclusion, our data confirm that full genome scanning by microarray experiments and analysis of multiple experimental conditions constitutes a powerful tool to uncover potentially significant biological features that can be subsequently confirmed by genetic experiments. Supplementary Material Additional file 1 For each of the 1368 probe sets identified as stress responsive in our data analysis, we calculated and reported in this table, for each stress condition, the mean ratio <Stress condition> ≤ (AV stress i / AV ref j )> i,j where AV stress i and AV ref j correspond to the average value measured for the i th sample in the stress condition and the j th sample respectively in the reference condition. To facilitate visual inspection, we used a color code (red corresponding to upregulation, green to downregulation) with thresholds corresponding to fold changes of 1.8 (dark colors), 1.5 (medium) and 1.25 (light). The standard error for each measurement is given in parenthesis. For each probe set, the mean detection p-value from MAS5 analysis of reference samples is reported in column 4 and cluster assignment in column 9. . Click here for file Additional file 2 For stresses induced by a) paraquat (5mM and 15mM experiments), b) H 2 O 2 or c) tunicamycin we analyzed the distribution in biological processes (as defined by the Gene Ontology (GO) database) of the genes selected by the SAM analysis (responsive genes) and compared it to the same distribution for all the genes significantly detected on our microarrays (analysed genes). We report here the significantly over- or under-represented (P < 0.005) biological process and the number of analysed and responsive genes found inside these classes, for the different stress conditions. The p-value P associated to the null hypothesis of no association with a binomial distribution hypothesis is given for each class, (only classes with P < 0.005 were retained). For clarity of the figure some redundant branches of the tree were removed. Color codes for the classes: dark blue: classes present in the 3 stress responses; yellow: classes present in the two oxidative stress responses; green: classes present in paraquat and tunicamycin stress responses; light cyan: classes present in H 2 O 2 and tunicamycin stress responses. 34 Color code for statistical analysis: orange: underrepresented class, blue: over-represented class. . Click here for file Additional file 3 For over or under-represented molecular functions classes we report here the number of analyzed (column 3) and responsive genes found inside the 7 groups of clusters A to G (columns 4 to 10, see text for details on the definition of these groups). A schematic response to oxidative and ER stress of the genes included in these groups is given in the first two lines. The number of genes inside each group is given in line 3. A color code identifies cases when the number of genes differs statistically (p<0.005) from a random distribution: orange: under-represented class, blue: over-represented class. Click here for file Additional file 4 For over or under-represented biological process classes we report here the number of analyzed (column 3) and responsive genes found inside the 7 groups of clusters A to G (columns 4 to 10, see text for details on the definition of these groups). A schematic response to oxidative and ER stress of the genes included in these groups is given in the first two lines. The number of genes inside each group is given in line 3. A color code identifies cases when the number of genes differs statistically (p<0.005)from a random distribution: orange: under-represented class, blue: over-represented class. Click here for file Additional file 5 Stress response for the peptidases Click here for file Additional file 6 List of stress responsive genes detected in aging and hyperoxia, immune or starvation stress experiments were compared with our data. Lines 1 to 3 indicate the number of genes found to be repressed (-), induced (+) or either (total) in the different experiments. Lines 5 to 7 indicate the number of genes in each of these categories found among our 1397 35 stress responsive genes (classes A to F) and the corresponding percentage from the initial number. In lines 8, 9 (respectively 10, 11) the same analysis is reported for genes included in the A (respectively B) classes defined as common stress responsive classes in our analysis. O 2 , old, infection, starvation : expression data from the different experiments compared to our data. All : List of 26 genes which are responsive to at least 4 stresses in these independent experiments Click here for file Additional file 7 Relationships to other stresses Click here for file Additional file 8 Table 1: Stress response characteristics of clusterized genes.The 1368 probe sets retained after statistical analysis were submitted to a divisive clustering algorithm (SOTA) which predicted 19 clusters. For each probe set k inside a cluster we calculated, for each stress condition, the mean ratio R k = <Ln2 (AV stress i / AV ref j )> i,j where AV stress i and AV ref j denote the average value measured for the i th sample in the stress condition and the j th sample respectively in the reference condition. The mean of the R k values provides a measurement of the mean intensity of variation for the genes inside a cluster, which is reported in this table. To facilitate visual inspection, we used a color code (red colors corresponding to upregulation, green colors to downregulation) with thresholds corresponding to fold changes of 1.8 (dark colors), 1.5 (medium) and 1.25 (light). The number N of probe sets in each cluster is also reported. From these values we identified groups of clusters (named from A to G) which present close behavior and were used for statistical functional analysis. Clusters corresponding to the common long term stress response (CLTSR) are outlined in red. Click here for file Additional file 9 Table 2: Functional analysis of stress responsive genes.For stresses induced by a) paraquat (5mM and 15mM experiments), b) H2O2 or c) tunicamycin we analyzed the distribution in functional classes (as defined by the Gene Ontology (GO) database) of the genes selected by the SAM analysis (responsive genes) and compared it to the same distribution for all the genes significantly detected on our microarrays (analysed genes). We report here the significantly over- or under-represented (P<0.005) molecular functions and the number of analysed and responsive genes found inside these classes, for the different stress conditions. The p-value P associated to the null hypothesis of no association with a binomial distribution hypothesis is given for each class, (only classes with P<0.005 were retained). For clarity of the figure some redundant branches of the tree were removed. Color codes for the classes: dark blue: classes present in the 3 stress responses; yellow: classes present in the two oxidative stress responses; green: classes present in paraquat and tunicamycin stress responses; light cyan: classes present in H 2 O 2 and tunicamycin stress responses. Color code for statistical analysis: orange: under-represented class, blue: over-represented class. Click here for file Additional file 10 Table 3: Analysis of stress responses for members of some functional classes.From the 1368 stress responsive probe sets we extracted the subsets associated with genes annotated in the GO database as a) glutathione transferases (GO:0004364), b) P450 cytochromes (from list at http://p450.antibes.inra.fr/) and c) proteasome component (GO:0004299). For each probe set k within one of these subsets, we calculated and reported in this table, for each stress condition, the mean ratio <Stress condition >k =<(AVstressi / AVref j)>i,j where AVstressi and AVrefj correspond to the average value measured for the ith sample in the stress condition and the jth sample respectively in the reference condition. To facilitate visual inspection, we used a color code (red corresponding to upregulation, green to downregulation) with thresholds corresponding to fold changes of 1.8 (dark colors), 1.5 (medium) and 1.25 (light). The standard error for each measurement is given in parenthesis. For each probe set, the mean detection p-value from MAS5 analysis of reference samples is reported in column 3 and cluster assignment in column 8. In column 9 additional information is reported for each class: in a) we indicate the GT class deduced from sequence comparison with human and mouse GTs and from [44] (D: delta, O: omega, T: theta, T2: distantly related to theta, Z: zeta); in b) the name of the genes are reported; in c) we indicate the proteasome subunit to which the genes defined in column 2 belong. Note that in c) a large number of genes not retained by SAM analysis (without cluster number) seem to be upregulated in P15 condition. Genes used for comparison between microarray and quantitative RT-PCR (Fig. 3) are outlined in bold character. Click here for file Additional file 11 Table 4: Analysis of mutant flies' resistance to paraquat-induced oxidative stress. Paraquat resistance of 29 mutant lines was assayed in three independent experiments as described in Fig. 4. The survival data were submitted to a log-rank statistical analysis by comparison with w /+ reference flies. The results are presented in this table. Column 1 contains the tested genotype (same conventions as in Fig. 4a : Bloomington line numbers). The corresponding genotypes are described in column 6. The symbol for the gene affected is reported in column 2. Information from FlyBase about the allele used in this study is given in column 7 with a one character code: A: amorph; H: hypomorph; N: non complementation of deficiency; L: letal; R: recessive mutation; 5: insertion in the 5' regulatory region, 5'UTR or intron; C: insertion in the coding region. Column 8 indicates whether the tested line was outcrossed or not before the test. Column 4 is the result of a log-rank analysis of the second survival experiments shown in figure 4. A confidence index which refers to the mean of log10 (p-log-rank) for the three experiments is given in column 5. We considered that a strain had a significant effect on survival under oxidative stress conditions when this confidence index was lower than -3 and at least two experiments presented p-log-rank < 0.001. Under these stringent conditions 13 genotypes are shown to confer resistance (R) or sensitivity (S) to paraquat as indicated in column 3. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526417.xml
521185	MicroRNA Is a Major Regulator	null	Since their discovery a decade ago, microRNAs (miRNAs) have emerged as major regulators of gene expression in eukaryotes of all kinds. Only 20 to 40 nucleotides long, a miRNA binds to a specific target sequence within a much longer messenger RNA (mRNA), inhibiting its translation and thus controlling expression of the corresponding gene even after the DNA itself has been read. Within the human genome, there are about 250 genes that code for miRNAs. Each miRNA has the potential to bind to many different transcripts. Variations in miRNA sequence dictate the gene transcripts to which each will bind most strongly. It has become clear that miRNAs play a critical role in controlling gene expression, for example, in larval developmental transitions and neuronal development in the worm Caenorhabditis elegans , growth control and apoptosis in the fruitfly Drosophila melanogaster , hematopoietic differentiation in mammals, and leaf development, flower development, and embryogenesis in the plant Arabidopsis thaliana . Despite their significance, the full range of genes miRNAs target is unknown, as is the best method for discovering them. In a new study, Debora Marks, Chris Sander, and colleagues describe an algorithm for determining the targets of miRNAs, and show they include more than 10% of all human genes. The algorithm uses three factors to evaluate whether a potential target site is likely to actually be regulated by miRNA. First, the target site must have some degree of sequence complementarity to one or more of the known miRNAs. Second, the strength with which the predicted target and its miRNA bind together, which can be calculated from the sequence and other structural factors, must be higher than some threshold. Finally, evolutionary conservation—the presence of the target–miRNA pair in different organisms—is factored in, because the likelihood that the target and miRNA actually pair in vivo is greater if the pair is found in multiple types of organisms. Using these principles, and the specific weighting they assigned to each factor, Marks and colleagues identified 2,273 genes in humans, rats, and mice that are likely targets for miRNA regulation. This is probably an underestimate of the total, since the researchers required each candidate gene to have at least two miRNA target sites. The authors identified another 2,128 genes with only one target site, but note that the false-positive rate here is likely to be high. Whatever the final number, the implication is that several thousand of our approximately 30,000 genes are under the control of miRNAs. Of special interest is that these putative targets include many genes known to be associated with the fragile X mental retardation protein, a crucial but still poorly understood player in mRNA regulation, whose absence leads to a type of mental retardation called fragile X syndrome. microRNA gene networks The researchers' findings also reinforce several emerging principles of miRNA-based regulation. First, it is widespread among multicellular eukaryotes, and sequences are surprisingly conserved. Of the 78 known miRNAs in Drosophila , 28 have close relations in mammals. Second, an individual miRNA may regulate multiple genes—Marks and colleagues found that the average miRNA interacts with seven distinct mRNAs, with a range from 0 to 268. Third, the genes regulated by a single miRNA may be functionally related, such as components of the protein degradation system or specific signal transduction pathways. Fourth, single genes may be regulated by multiple miRNAs—the gene that encodes amyloid precursor protein, for example, has at least eight miRNA sites—suggesting that expression may be combinatorially controlled by numerous cellular influences. These results provide resources for a host of experiments to elucidate the mechanism of miRNA action, which is not well understood. Several of the identified mammalian miRNA–target pairs have near-perfect matching sequences. In both plants (where miRNAs were first discovered) and animals, such matches are associated with degradation of the mRNA. The authors fully recognize that their algorithm, called miRanda, is not the last word in miRNA target identification. In order to improve both the search for targets and the algorithm itself, they are making the algorithm and full sets of results in vertebrates available free to other researchers ( www.microrna.org ), who can modify its parameters as experimental results and new models dictate.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521185.xml
548669	clc is co-expressed with clf or cntfr in developing mouse muscles	Background The ciliary neurotrophic factor (CNTF) receptor is composed of two signalling receptor chains, gp130 and the leukaemia inhibitory factor receptor, associated with a non-signalling CNTF binding receptor α component (CNTFR). This tripartite receptor has been shown to play important roles in the development of motor neurons, but the identity of the relevant ligand(s) is still not clearly established. Recently, we have identified two new ligands for the CNTF receptor complex. These are heterodimeric cytokines composed of cardiotrophin-like cytokine (CLC) associated either with the soluble receptor subunit cytokine-like factor-1 (CLF) or the soluble form of the binding receptor itself (sCNTFR). Results Here we show that, during development, clc is expressed in lung, kidney, vibrissae, tooth, epithelia and muscles during the period of development corresponding to when motoneuron loss is observed in mice lacking a functional CNTF receptor. In addition, we demonstrate that it is co-expressed at the single cell level with clf and cntfr , supporting the idea that CLC might be co-secreted with either CLF or sCNTFR. Conclusion This expression pattern is in favor of CLC, associated either with CLF or sCNTFR, being an important player in the signal triggered by the CNTF receptor being required for motoneuron development.	Background CLC (cardiotrophin-like cytokine) shares homology with CNTF (ciliary neurotrophic factor) and CT-1 (cardiotrophin-1) and requires co-expression with either CLF (cytokine-like factor-1) or the soluble form of the CNTFR to be secreted [ 1 , 2 ]. The CLC-CLF heterodimer displays activities only on cells expressing a functional CNTF receptor [ 1 ] and therefore CLC is likely to be part of the developmentally important second ligand for CNTFR. The existence of such a second ligand has been suggested by the phenotype of mice lacking any of the three receptor subunits comprising the functional CNTF receptor complex (LIFRβ, gp130 and CNTFR) which exhibit significant reductions in motoneuron number [ 3 - 5 ] whereas CNTF-deficient mice have no motoneuron loss during development [ 6 ]. There are however two prerequisites for CLC to play a major role in motoneuron development: 1) CLC must be expressed in the environment of motoneurons during development. 2) As it cannot be secreted alone, it must be co-expressed with either CLF or sCNTFR, in the same cell. Results and Discussion Developmental expression of clc Since the expression of clc has only been studied in adult mouse tissues [ 7 ], we first examined the expression of genes encoding CLC or its co-secreted proteins, CLF and CNTFR in various embryonic tissues using reverse transcription and quantitative real-time polymerase chain reaction (RT-PCR). In all tissues tested from E16.5 and E18.5 (Table 1 ), the level of expression of clc is very low when compared with that of clf or cntfr . The highest level of clc expression was observed in the muzzle, a very heterogeneous region containing different positive tissues, as described below. Clc expression is also observed in lung, kidney, brain and skeletal muscles such as the tongue or limb muscles. Table 1 RT-PCR analysis of clc , clf and cntfr expression a clc clf cntfr E16.5 E18.5 E16.5 E18.5 E16.5 E18.5 Skeletal muscle 0.113 ± 0.02 0.936 ± 0.12 0.232 ± 0.003 24.84 ± 2.13 90.25 ± 2.71 6.72 ± 0.76 Heart NS c NS NS NS NS NS Tongue 3.12 ± 0.12 1.2 ± 0.09 495 ± 17.1 77.1 ± 4.64 28.3 ± 10.9 2.6 ± 0.83 Muzzle 11.4 ± 0.75 9.25 ± 0.79 1050 ± 65.3 524 ± 85.8 425 ± 47.5 57.9 ± 4.02 Lung 4.08 ± 0.65 16.4 ± 0.48 2290 ± 490 2240 ± 184 43.8 ± 15.6 ND b Kidney 5.55 ± 0.12 6.75 ± 1.15 61.4 ± 4.59 ND 51.8 ± 9.49 19.8 ± 3.12 Liver 0.191 ± 0.02 0.129 ± 0.03 0.071 ± 0.001 0.034 ± 0.09 0.047 ± 0.002 0.038 ± 0.03 Brain 1.04 ± 0.12 0.317 ± 0.09 150 ± 3.39 74.3 ± 16.4 216 ± 2.01 236 ± 16.1 Spinal cord ND 0.183 ± 0.01 0.123 ± 0.01 61.2 ± 6.25 6.13 ± 0.03 109 ± 27.4 a Expression of clc , clf and cntfr was determined using reverse transcription and quantitative real-time PCR as detailed in Experimental Procedures and expressed as fM of cDNA/μg total RNA. b not determined c not significant To further assess the potential involvement of CLC in the development of motoneurons, we performed in situ hybridization experiments to determine the pattern of expression of clc in the environment of developing motoneurons and compare it with the expression of both clf and cntfr . Motoneuron death occurs between E14.5 and E18.5 in mice lacking in the ability to produce a functional CNTF receptor complex [ 5 ], suggesting that expression of CNTFR and its relevant ligands is critical between these timepoints. We therefore studied clc mRNA expression levels at E16.5. Clc is expressed in muscles along the whole rostro-caudal axis, at the brachial level (Fig. 1A ) as well as at the lumbar level (Fig. 1E and [ 8 ]. It is also expressed in the tongue (Fig. 1C ) like clf (Fig. 1D ). The identity of muscle cells (Fig. 1G ) was confirmed by double staining performed on transgenic mice with the nlacZ reporter gene under the control of the muscle-specific MLC promoter [ 9 ]. All clc -positive muscle fibers also stained positive for clf (Fig. 1E , 1F , 1G , 1H and [ 8 ]). clc expression was not detected in certain clf -positive muscles however, such those around the vibrissae (Fig. 1I and 1J ). Since the level of clc expression is generally low, this could reflect the limited sensitivity of the in situ hybridization technique used. To determine the onset of clc and clf expression in the muscles, the motoneuron targets, we performed in situ hybridizations at different stages. Clc and clf are expressed, although at low levels, as soon as the muscles develop and are clearly observed at E14.5 (Fig. 1K and 1L ). Figure 1 In E16.5 mouse embryos clc is expressed in muscles. Cryostat sections (A, E-L) or vibratome sections (B-D) from E16.5 (A-J) or E14.5 (K, L) were hybridized to clc (A, C, E, G, I and K) or clf (D, F, H, J and L). The control clc sense probe gave rise to very faint staining (B). Transverse section through the forelimb (A, K and L), the hindlimb (E and F) and saggital sections through the tongue (C and D) showing expression of clc and clf in muscles. The identity of the clc -positive cells such as muscle fibers was confirmed by double staining and compared to clf -positive cells. In situ hybridization using Dig-labeled probes for clc and clf (cytoplasmic blue staining) was performed on sections through shoulder muscles (G, H) or vibrissae (I, J) from E16.5 MLC nlacZ mice, which express the nlacZ reporter gene under the control of a muscle-specific MLC promoter. Subsequently, the sections were processed for immunohistochemical detection of β-galactosidase (nuclear brown staining). Arrows indicate double-labeled cells. Transverse section through the muzzle (I and J) shows that vibrissae (arrowheads) are positive for clc and clf whereas only clf is detected in muscles (asterisks) surrounding vibrissae. c, cartilage; m, muscle. Scale bars are 200 μm in A, E and F, 25 μm in G and H and 100 μm in I-L. Clc is also expressed in several organs in which reciprocal epithelial-mesenchymal interactions are essential, such as the developing vibrissae (Fig. 1I and 2I ), tooth, kidney, and lung. In the kidney, clc is expressed in the comma-shaped body (Fig. 2A ). Strikingly, CLF and CNTFR are expressed in different structures, clf being synthesized in the tips of the ureteric (Fig. 2B ) and cntfr being synthesized by mesenchyma cells surrounding these structures (Fig. 2C ). In the lung, both clc and cnftr are expressed faintly in distal airway epithelium whereas clf is strongly expressed in distal and proximal epithelia (Fig. 2D , 2E and 2F ). Sections through molar tooth germs (Fig. 2G and 2H ) show that clf is expressed in both the mesenchyma surrounding the dental follicle which gives rise to alveolar bone and the inner enamel epithelium whereas clc is expressed only in the former. Clc and clf are also co-expressed in the epithelium bordering the mandibles and the lips although clf is also expressed in mesenchyma (Fig. 2I and 2J ). Together these results are in agreement with the expression pattern described for both clf [ 10 ] and cntfr [ 11 ]. Figure 2 Clc is expressed in epithelia Transverse sections from E16.5 mouse embryos were hybridized to clc (A, D, G and I), clf (B, E, H and J) or cntfr (C and F). Sections through the kidney (A-C) show that clc is expressed in developing nephrons (arrows), clf in ureteric tips (arrowheads) and cntfr in nephrogenic mesenchyme. Sections through the lung (D-F) show that whereas clf is strongly expressed in both distal (arrowheads) and proximal (arrows) epithelia, clc and cntfr are weakly expressed in distal epithelium. Boxed areas are shown in higher magnification in the corner of each panel. Sections through molar tooth germs (G, H) show that mesenchyma (arrows) surrounding the dental follicle is positive for both clc and clf and that the inner enamel epithelium (arrowheads) expresses only clf . Coronal sections through muzzle (I, J) show that both clc and clf are expressed in the epithelium bordering the mandibles and in between the lips and mandibles (arrow) as well as in follicles of vibrissae (arrowheads); in addition, clf is expressed in mesenchyma (asterisks). a, pulmonary artery; dp, dental papilla; de, dental epithelium; oc, oral cavity; uli, upper lip; lli, lower lip. Bars: 100 μm in A-H, 200 μm in I and J. Co-expression of clc , clf and cntfr in the developing muscle In transfected cells CLC requires either CLF or sCNTFR to be secreted [ 1 , 2 ]. This cooperative effect requires the expression of genes for both factors in the same cell. To ascertain whether a single muscle cell can express at least CLC and CLF or CLC and sCNTFR, we studied co-expression on hind-limb muscle sections. We performed double in situ hybridization of clc and clf and of clc and cntfr . Most muscle cells expressed both clc , (revealed using NBT/BCIP; Fig. 3A, C ) and clf or cntfr (Fig. 3B, D ; revealed using Fast Red). Co-expression was observed at the single cell level demonstrating that in vivo CLC could be co-secreted either with CLF or sCNTFR. Figure 3 Double-labeling detects co-expression of clc and clf or clc and cntfr in individual muscle cells. Single sections of E16.5 muscles were hybridized with two probes. Dig-labeled clc (A-D) and Fluo-labeled clf (A, B) or cntfr (C, D). Anti-Dig antibodies were applied first and stained using NBT/BCIP to reveal cells expressing clc (A, C). Anti-Fluo antibodies were then applied and detected using Fast red to reveal cells expressing clf (B) and cntfr (D), after removal of the first red reaction product. Most muscle cells express clc and clf or clc and cntfr (examples indicated by arrows). Bars: 100 μm. Conclusions Clc is expressed in developing muscles during the period of motoneuron loss in mice lacking a functional CNTF receptor and it is co-expressed with both CLF and CNTFR. This expression pattern is in favor of the hypothesis that CLC is an important player in the signal triggered by the CNTF receptor and that is required for motoneuron development. In addition, our results show that in the kidney, clc is expressed in cells neighboring those expressing clf or cntfr but it is not co-expressed with these genes suggesting either the possible existence of an additional protein capable of inducing secretion of CLC or that CLC is not secreted in these cells and therefore not functional. Because genetic deletion of cntf fails to perturb neuronal development before birth, we can hypothesize some functional redundancies in vivo that will require the analysis of double or triple knockout mice for CNTFR ligands to clarify their respective involvement in mouse neural development. Methods RT and real time PCR Total RNA was extracted using Trizol reagent (Invitrogen) from E16.5 or E18.5 mouse tissues according to the manufacturer's instructions. Complementary cDNA was synthesised from 2 μg of RNA by random hexamer priming using MMLV reverse transcriptase (Promega). Quantitative PCR was performed using a capillary real-time LightCycler (Roche Diagnostics), and the data analysed using "Fit Point Method" (Roche Diagnostics). For comparison of gene expression levels, all quantifications were normalized to endogenous gapdh to account for variability in the initial concentration of RNA and for differences in the efficiency of the reverse transcription reactions. The following primers were designed to amplify mouse clc : 5'-GCTACCTGGAGCATCAACT-3', 5'-GGTGACTGTACGCCTCATAG-3'; clf : 5'-CAGTCAGGAGACAATCTGGT-3', 5'-ACGTGAGATCCTTCATGTTC-3'; cntfr : 5'-CTACATCCCCAATACCTACA-3', 5'-GTGAATTCGTCAAAGGTGAT-3'; gapdh : 5'-TGCGACTTCAACAGCAACTC-3', 5'-CTTGCTCAGTGTCCTTGCTG-3'. Results are expressed in fmole of cDNA/μgRNA. Probes Plasmid cDNA clones were linearized and transcribed with T7 or T3 polymerase using digoxigenin (Dig) or fluorescein (Fluo)labeling reagents (Roche Diagnostics). Probes were used at a concentration of 500 ng/ml. The cntfr clone was as previously described [ 12 ] and the mouse clf [ 13 ] and clc probes corresponded to the isolated cDNAs. In situ hybridization In situ hybridization was performed as described previously [ 14 ] on 20 μm-thick frozen transverse cryostat sections prepared from mouse embryos fixed with 4% paraformaldehyde in PBS, and cryopreserved in 15% sucrose in PBS before embedding in OCT compound (Miles). Alternatively, 100 μm-thick vibratome sections were prepared from fixed embryos embedded in glutaraldehyde/gelatin. After hybridization overnight at 70°C with Dig-labeled riboprobes, the slides were washed twice in 1X SSC, 50% formamide at 70°C for 30 min and blocked in the presence of 4% blocking reagent (Roche Diagnostics) and 20% inactivated sheep serum. The slides were then incubated with anti-Dig-alkaline-phosphatase (AP)-conjugated antibody (1/5000, Roche Diagnostics), washed and revealed by NBT/BCIP staining. In order to confirm that muscle fibers, per se , express clc and clf , double in situ hybridization / immunohistochemistry was carried out as described [ 15 ] on sections from E16.5 MLC nlacZ mice, which express the nlacZ reporter gene under the control of a muscle-specific myosin light chain promoter. After in situ hybridization, slides were rinsed in PBT (PBS, 0.1% Triton), and sections were successively incubated for 1 h with blocking solution containing 2% BSA, 2% heat-inactivated donkey serum in PBT and then overnight at 4°C with rabbit anti-β-galactosidasel (1/1000, Cappel). After three washes in PBT, slides were incubated 1 h at RT with a biotin donkey anti-mouse secondary antibody. Slides were then washed in PBS, and TBS (50 mM Tris-HCl, 0.15 M NaCl, pH 7.6), and incubated for 30 min at RT in ABC streptavidin/HRP in TBS. Staining was revealed with DAB (D4293, Sigma) in the presence of H 2 O 2 . Double in situ hybridization was performed as described previously [ 14 ]. Briefly, Dig- and Fluo-labeled probes were mixed in hybridization buffer and applied to sections. After hybridization at 70°C overnight and washing at 65°C, the first probe was revealed using a 1:2000 dilution of anti-Fluo-alkaline phosphatase (AP)- conjugate (Roche Diagnostics) and Fast Red (Sigma) as a substrate. Sections were photographed at this stage. After AP inactivation with 0.1 M glycine, pH 2.2, the second probe was revealed using a 1:5000 dilution of anti-Dig-AP and NBT/BCIP staining. Fast Red precipitates were then removed by incubating the slides in increasing concentrations of ethanol culminating in two final incubations in 100% ethanol for 10 min before cleaning with Histoclear and mounting with Eukitt (VWR, Strasbourg, France). Photomicrographs of the NBT/BCIP results were then taken for comparison with those showing the Fast Red results on the same sections. Competing interests The author(s) declare that they have no competing interests. Authors' contributions BB performed in situ hybridizations whereas DD and HG performed RT-PCR analyses. GE and JFG provided the clc and clf probes before publication. OL participated in the experimental design and coordination of the research. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548669.xml
539245	Current practices in spatial analysis of cancer data: data characteristics and data sources for geographic studies of cancer	The use of spatially referenced data in cancer studies is gaining in prominence, fueled by the development and availability of spatial analytic tools and the broadening recognition of the linkages between geography and health. We provide an overview of some of the unique characteristics of spatial data, followed by an account of the major types and sources of data used in the spatial analysis of cancer, including data from cancer registries, population data, health surveys, environmental data, and remote sensing data. We cite numerous examples of recent studies that have used these data, with a focus on etiological research.	Introduction Understanding the spatial patterns of diseases in a population can provide insight as to their causes and controls. Indeed, this notion is at the very root of the field of epidemiology [ 1 ]. The recent explosion in data gathering, linkage and analysis capabilities fostered by computing technology, particularly geographic information systems (GIS), has greatly improved the ability to measure and assess these patterns. Large and complex georeferenced data sets are now readily available through Spatial Data Clearinghouses, facilitating analyses by researchers unaffiliated with the government agencies that have historically controlled data access. Meanwhile, increasingly sophisticated statistical tools have evolved to keep pace with the increased data availability and computing power. The purpose of this article is to provide an overview of spatial data and its relevance to population-based cancer surveillance and research in the United States as of 2004. We begin by discussing a number of the distinctive characteristics of spatial data, which can sometimes hinder efforts to understand cancer etiology. We then proceed to describe the kinds of data sets that are available, accompanied by a survey of some applications using these data. Finally, we discuss several ongoing efforts to provide central repositories of geospatial data. Given the vast scope of cancer research taking place worldwide, our survey is necessarily partial, and we have chosen to emphasize etiology over other research themes with spatial dimensions, such as patterns of treatment or access to care [ 2 ]. Qualities of spatial data Spatial data refer to data with locational attributes. Most commonly, locations are given in Cartesian coordinates referenced to the earth's surface. These coordinates may describe points, lines, areas or volumes. This need not be the only spatial framework; "relative spaces" may be defined in which distance is defined in terms of some other attribute, such as sociodemographic similarly or connectedness along transportation networks [ 3 , 4 ]. Spatial data have special qualities that require specialized statistical techniques and modeling approaches. A complete discussion of these special qualities is well beyond the scope of this article, but here we describe a number of the more compelling and recurring themes. For a focused discussion on the limitations on analysis that these data characteristics impose, see the companion piece to this article, "Current Practices in Spatial Analysis of Cancer Data: Flies in the Ointment, Or, The Limitations of Spatial Analysis" [ 5 ]. Individual humans represent the basic unit of spatial analysis in cancer research. Individuals are categorized as either having or not having a disease or attribute of a disease, and are assigned coordinates corresponding to the location of their place of residence, a technique known as geocoding. As with all measurements, geocoding involves some error. A growing body of literature is exploring the nature of this error and its potential to bias epidemiologic studies [ 6 ]. Among the topics that have been investigated are systematic problems with geographic reference files [ 7 ], the ramifications of different geocoding algorithms [ 8 ], positional accuracy [ 9 ] and how to handle non-residential addresses, such as rented post office boxes [ 10 ]. Assigning individuals to their place of residence also poses problems, although this is usually the only locational information that is available. Often the goal of a geographic analysis is to identify a common environmental exposure in a population, but exposures that are occupational or recreational may not necessarily reveal themselves in a residential analysis. Also, given the long latency period for many cancers and the mobility of the American population, the relevant exposure may be associated with a prior address. Difficult-to-measure behavioral risk factors such as smoking and diet often further confound attempts at geographic analysis. Owing to confidentiality restrictions, researchers outside of central cancer registries typically do not have access to address-level data. In such instances, case data are aggregated by some functional or political unit such as census tract, county or ZIP code. Even when the case data are geocoded, population data must be aggregated, at least to the level of the census block, which is the smallest unit for which any population information is available. Knowing that there are four women with breast cancer living on the same street is not sufficient, by itself, to draw conclusions about whether the street displays an unusual incidence pattern; one must also know the number and ages of women without breast cancer on the same street. Short of conducting one's own thorough door-to-door census, this question cannot be answered, except by aggregating the street segments into blocks. When additional variables, such as measures of income or education, or also of interest, then still larger analytical units must be chosen. The necessity for aggregating spatial data raises a whole set of analytic issues regarding the extent to which the act of aggregating introduces error and bias. It is theoretically possible to achieve dramatically different, even contradictory results, simply as a consequence of aggregating the data in a different fashion [ 11 ]. This is true not only for aggregations at different spatial scales, but also different aggregations at the same scale. Geographers have termed this the "modifiable areal unit problem" [ 12 ]. A special case of the modifiable areal unit problem is the ecological inference problem, which specifically refers to the lack of congruity between associations found in aggregated and individual-level data. In practice, well-chosen scales and groupings can minimize the modifiable areal unit problem and allow reasonable consistency between aggregated and individual-level results [ 13 ]. There will always be exceptions to this, however, as evidenced by the many studies attempting to relate low-level indoor radon concentrations with lung cancer incidence. Individual-level studies have repeatedly found a positive correlation, while area-level studies have found a negative correlation at low radon levels [ 14 - 16 ]. Despite a general appreciation of how these discrepant results represent an example of aggregation bias, there is still active debate over what these results say about low-level radon risk [ 17 , 18 ]. Often analyses need to be performed on data that was collected at different spatial scales, such as a study using cancer cases aggregated by ZIP code and modeled air pollutant data at the census tract level. The resulting scale-translation problem is a recurring one that has inspired many independent solutions, and is known variously as areal interpolation, the polygon overlay problem, and the problem of inference with spatially misaligned data, among other terms [ 19 ]. The most naïve solution to this problem is to assume that each measured value is homogeneous within each spatial unit. Under this assumption, using our example, a ZIP code that is coincident with four census tracts would be broken into four polygons, each having the same cancer rate but different air pollutant values. More sophisticated cartographic overlay techniques have been developed that involve using covariate information to infer variation within spatial units. To date, these techniques have been primarily applied toward estimating population surfaces rather than cancer or other disease rate surfaces [ 20 , 21 ]. Hierarchical Bayesian and multi-level logit models have also shown promise [ 22 - 25 ]. Spatial autocorrelation is another distinctive quality of spatial data that requires the use of specialized analytic methods. Spatial autocorrelation is the tendency for nearby observations to have correlated attribute values. For most data sets involving the distribution of human populations and their characteristics, spatial autocorrelation is positive, meaning that neighboring individuals tend to have similar characteristics. Understanding the characteristics and qualities of spatial autocorrelation is essential to adequately model and interpret geographic patterns. For example, it is not appropriate to perform ordinary least squares regression on spatial data, because the presence of spatial autocorrelation means that the observations are not independent. Performing such a regression generally results in downwardly biased estimations of variance, which yields overstated levels of significance. In general, spatially autocorrelated data is less informative in a model than uncorrelated data. There is an ample literature on assessing and properly accounting for spatial autocorrelation in geographic analysis [ 26 , 27 ]. A final critically important characteristic of spatial data is spatial nonstationarity, or the tendency for relationships between and among variables to vary by geographic location [ 28 ]. First-order or strong stationarity refers to the degree to which measured values vary spatially, while second-order or weak stationarity refers to the degree to which the uncertainties in these measured values vary spatially. So-called global statistics ignore nonstationarity, suggesting that relationships across space are constant. The simple linear equation that has traditionally been used to express the relationship between rainfall and altitude is a well-known example. Local statistics, in contrast, take nonstationarity into account, at least first-order nonstationarity. Brunsdon et al. [ 29 ] used the technique of geographically weighted regression to demonstrate that both the slope and intercept of the rainfall-altitude equation vary considerably in space. The range and breadth of local statistics has seen rapid growth in recent years [ 27 , 30 ]. Local statistics are less adept at accounting for second-order nonstationarity. Indeed, many of these methods require the assumption of constant variance across space. Because of the uneven distribution of human populations, this assumption is seldom met for health data. Specifically, disease rates in areas with smaller numbers of cases are more variable than those in areas with larger numbers of cases, a property that has also been termed "variance instability" [ 31 ]. Variance instability is particularly pervasive on maps, since it is extremely difficult to design a map that is not visually biased toward either sparsely populated or densely populated areas [ 32 , 33 ]. A simple example is the tendency for rural counties to contain disproportionate numbers of unusually high or unusually low disease rates and thus visually dominate a choropleth map. The problem is compounded by the tendency of such counties to be large in size; for these reasons, maps of United States counties are often visually dominated by such states as Idaho, Nevada and Wyoming. Efforts to include information about data uncertainty have shown promise, but have not seen widespread use [ 34 ]. One common way of addressing this problem is to produce smoothed maps, whereby the rate for a given area is influenced by the rates of neighboring areas. There are many algorithms available to accomplish this [ 35 ], ranging from conceptually straightforward spatial filters [ 36 ] to computationally-intensive Bayesian approaches [ 37 , 38 ]. Properly accounting for second-order spatial nonstationarity in maps and models remains an active research area. Types and sources of data In this section we described the primary types and sources of data most frequently used in the geographic analysis of cancer, along with examples of their application. These are summarized in Table 1 . Table 1 Sources of Cancer Registry Data Dataset name Source Agency URL Geographic Resolution SEERStat, Cancer Mortality Maps and Graphs, State Cancer Profiles National Cancer Institute County Florida Cancer Data System University of Miami School of Medicine County Cancer Incidence and Mortality Rates in Kentucky Kentucky Cancer Registry County New York Cancer Incidence by ZIP code NYS Department of Health ZIP code 1. Cancer registries A cancer registry is a data collection system that tracks cancer cases that have been diagnosed or treated in a specific institution or geographic area. Cancer registries typically collect information from medical records provided by hospitals, doctors, other care facilities, medical laboratories, and/or insurers. Data collected by cancer registries is stored under secure conditions so as to protect confidentiality. Historically, observed geographic differences in cancer incidence have been of great interest in trying to understand more about factors which may influence risk of these diseases. Such differences have served as the basis for studies of migrant populations and acculturation differences in migrant groups. They have been possible because cancer is one of the few chronic diseases for which high quality population-based disease surveillance systems have been in place for many years in many countries of the world. Cancer registry data has been widely applied toward the production of cancer atlases [ 39 ], studies analyzing the spatial distribution of particular cancer sites [ 40 ], and studies assessing spatial clustering [ 41 ]. Most recently, cancer studies have been undertaken which build on the combined resources of cancer registry data and increasingly available GIS tools. Because address at diagnosis is available for most registry cases it can be geocoded and integrated in a GIS with social and environmental attribute information available at a variety of geographic scales. Examples of such approaches include studies of childhood cancer which examine rate differences in areas of low versus intense agricultural pesticide use [ 42 ], heavy traffic patterns [ 43 ], or high air pollution [ 44 ]. Alternatively, cancer registry data can serve to identify population-based cases for studies using case-control or cohort designs, which can in turn be integrated into a GIS for area attribute data. Examples of this approach include case-control studies of childhood leukemia and traffic patterns [ 45 - 48 ]. and a studies of breast cancer incidence associated with residence in high pesticide use areas in a large case-control study [ 49 , 50 ]. and in a large cohort study [ 51 ]. For these types of studies, cancer registry data offer both a number of strengths and limitations. Primary strengths include the comprehensiveness of geographic coverage, detailed information on disease subgroups, and rich covariable information on demographic characteristics for each newly diagnosed case of cancer. Because registry data are abstracted from medical records and reflect information for a snapshot in time, primary limitations include the lack of historical information on various factors of potential interest including residential mobility and relevant personal behaviors. Cancer registries typically collect information on the residential address for individuals newly diagnosed with cancer at the time of that diagnosis. Since this is the locational information which serves as the basis for national and international statistics on area cancer rates, it is also useful for looking at area characteristics associated with rate differences, although inferences about etiologic associations are limited for these long latency diseases, and even more so for residentially mobile populations. The Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute (NCI) offers county-level incidence data for its member registries, which cover part or all of eight states, through its SEERStat software. Because it provides direct access to individual cancer records, users must first sign a data access agreement. County-level mortality data for the entire United States, collected and maintained by the National Center for Health Statistics (NCHS), is also accessible through SEER*Stat. These data include all causes of death, not just cancer deaths. Selected county-level cancer data may also be accessed through the NCI's Cancer Mortality Maps and Graphs and State Cancer Profiles web sites. The latter was launched in 2003 and contains a host of innovative statistical graphics. Many individual state registries also offer additional geographically referenced data. For example, the Florida Cancer Data System web site allows users to generate a variety of county- and facility-level tables and county-level maps on demand. The Kentucky Cancer Registry also offers a county-level mapping application. New York State offers a limited set of ZIP code level data for the four most common cancer types in the mid-1990s. Currently, county-level cancer incidence data is not available nationally. 2. Population data The United States Census Bureau is the principal source of data on the entire population; most countries have comparable agencies. Since cancer rates are calculated by dividing the number of cases by the number of people at risk, census data is frequently referred to as "denominator data". Census data are readily available in electronic format through the Census Bureau web site, . Data are available in three basic formats. American FactFinder is a web-based application that allows users to drill down through geographic levels to find data tables of interest. It is most useful for data queries that are well-focused. Data may also be downloaded through an ftp server. This method obtains raw text files that require computer code to be written before the data can be easily accessed or manipulated. This method is most useful for users with large data needs who are in possession of some database programming skills. The third approach is to purchase DVDs from the Census Bureau's Customer Service center. The DVDs allow data output in many spreadsheet and database formats, facilitating the ability for users to process and analyze the data. There are also a large number of third-party vendors who offer similar services [ 52 ]. The four primary data files emanating from the 2000 census are named Summary File 1 through Summary File 4 (SF1–SF4). SF1 contains population counts by age, sex, race and ethnicity and basic housing characteristic information for the entire population, to the block level. SF2 contains similar information, detailed for ethnic subgroups, American Indian and Alaska Native tribes, and multiple-race individuals. These data are suppressed when the total number of individuals in a given geographic unit totals fewer than 100. SF3 contains detailed housing, demographic, and socioeconomic data to the census block group or census tract level, based on a long form that was sent to one in six households. Census block groups have an optimal population size of 1,500 and census tracts have an optimal population size of 4,000, though in practice populations vary widely. SF4 contains the same information as SF3 for detailed race and ethnic groups, with the same suppression rule as SF2. In addition to these four primary data files, the Census Bureau also provides digital cartographic boundary files for political entities in the country, as well as approximations of postal code boundaries known as ZIP code tabulation areas (ZCTAs). The Census Bureau also conducts the American Community Survey (ACS), an ongoing survey designed to reach 3 million households each year nationwide. The goal of this survey is to allow the publication of detailed demographic and socioeconomic information more often than once a decade. Data for geographic units totaling more than 65,000 people will be released annually, while data for smaller geographic units will be based on either a three or five year moving average. It will replace the census long form, which will not be administered in 2010. There will undoubtedly be a challenging adjustment period as public health researchers begin to use ACS data. At present, the level of information available for intercensal time points is quite limited, and derives from Census Bureau estimates at the state or county level. These estimates are used in the calculation of cancer rates by federal and state agencies, although some research has shown that they are not especially reliable, particularly county-level estimates for specific race groups [ 53 ]. Various private vendors publish intercensal estimates for areas smaller than counties, though it is impossible to verify their accuracy. Since many vendors use the Census Bureau estimates as controls (for example, vendor estimates of ZIP code populations in a county must add to the Census Bureau estimate for that county), vendor estimates necessarily suffer from the same limitations as the Census Bureau estimates. Finally, some state governments publish their own population estimates. Generally, these estimates are thought to represent improvements over the Census Bureau estimates because of higher levels of local knowledge and a broader use of data sources. We are unaware of any independent efforts to evaluate these claims, however. Examples include the population estimates and projections published by the California Department of Finance, and those by the Epidemiology Program of the Cancer Research Center of Hawaii. The latter population estimates were developed in response to a concern that the Native Hawaiian population was substantially undercounted in previous censuses, and are used by the NCI in calculating national cancer rates. The 2000 census allowed respondents to select more than one race, although cancer data are only beginning to be collected in this manner. As a result, population data from 2000 must be "bridged" back to the earlier single-race categories to allow comparisons with earlier data. NCHS developed a sophisticated bridging algorithm taking into account age, sex, distribution of single-race groups within counties, and other covariates [ 54 ]. This algorithm is reflected in the 1991–2003 population projections and estimates that are published on the NCI web site and included in their statistical software. The Census Bureau itself uses a simpler algorithm in its estimates, allocating equal proportions of each multiple-race combination to the constituent single races [ 55 ]. Given the multiplicity of population estimates and methods for calculating them that are available, it is important to be aware of the sources of these data, and how they may influence the confidence associated with a particular research result. This is especially true for small-area analyses, where uncertainties are highest. In addition to the issues noted above, it is important to realize that even the decennial census counts are not as accurate as popularly believed. The census represents an attempt to enumerate the population as of a single date, but invariably some people are missed or double-counted. These undercounts and overcounts are differential by race, socioeconomic status, and geographic area, potentially biasing cancer rates [ 56 , 57 ]. Countless epidemiologic and geographic studies make use of census data in some capacity, including most studies that report cancer rates for geographic areas. It is also quite common to use census data where individual-level data are not available, particularly for indicators of socioeconomic status [ 58 - 60 ], educational attainment [ 61 ] and housing characteristics [ 7 ]. Table 2 summarizes the population data sources described in this section. Table 2 Sources of Population Data Dataset name Source Agency URL Geographic Resolution 2000 Census Summary Files 1–4 US Census Bureau Census Tract, Block Group or Block (varies by data element) American Community Survey US Census Bureau Areas with populations >65,000 E-1 City/County Population Estimates, with Annual Percent Change California Department of Finance City/County US Population Data, 1969–2001 National Cancer Institute County 3. Surveys In addition to the Census Bureau as a primary source of sociodemographic attribute data, special survey data can provide valuable information on these characteristics for population groups in some areas. Perhaps one of the best known such surveys is the CDC-sponsored Behavioral Risk Factor Surveillance System (BRFSS), which is touted as the "world's largest telephone survey". Designed in the 1980s to track trends in behavioral risk factors at the state level, this ongoing system of national surveys also provides subarea and subgroup information within some of the larger states. Some researchers have estimated county-level behavioral risk factor prevalence by combining the statewide BRFSS data with county-level demographic data [ 62 , 63 ]. A mapping application to view BRFSS response data at the state and metropolitan level is also available . Another well-known national survey is the NCHS's National Health and Nutrition Examination Survey (NHANES), which has been in place since 1960 and combines questionnaire information with a national physical examination and biomonitoring program. NCHS also sponsors a National Health Care Survey (NHCS), a National Health Interview Survey (NHIS), a National Immunization Survey (NIS), and a National Survey of Family Growth (NSFG). Similarly designed large-scale efforts to track temporal and area differences for targeted health behaviors within a state include California's Tobacco Survey, Women's Health Survey, and Health Information Survey (Table 3 ). Table 3 Sources of survey data. Survey data recorded at the ZIP code level are designed to give valid estimates of risk factor distributions at the State level. Dataset name Source Agency URL Geographic Resolution Behavioral Risk Factors Surveillance Survey (BRFSS) Centers for Disease Control ZIP code National Health and Nutrition Examination Survey (NHANES), National Health Care Survey (NHCS), National Health Interview Survey (NHIS), National Immunization Survey (NIS), National Survey of Family Growth (NSFG). National Center for Health Statistics Metropolitan Statistical Area, National Region California Tobacco Survey California Department of Health Services ZIP code California Women's Health Survey California Department of Health Services ZIP code California Health Information Survey UCLA Center for Health Policy Research ZIP code Although population survey data has not been extensively incorporated into GIS studies to date, these resources may in the future provide some opportunity to characterize regional differences in behavioral risk profiles targeted for specific health outcomes. 4. Environmental data Over the past several decades there has been a large increase in the availability of spatially registered environmental data in the United States and other countries. Much of these data have been collected as a result of environmental regulations or government-funded research efforts. Examples of US programs to collect spatial data on concentrations or releases of pollutants in the environment include the United States Geological Survey (USGS) National Assessment of Water Quality program (NAWQA) , the Environmental Protection Agency (EPA) National Air Toxics Assessment database , and EPA's Toxic Release Inventory program . EPA has organized environmental data in an umbrella database called Envirofacts Data Warehouse . Some states have extensive efforts to collect additional environmental data. An example is California's Pesticide Use Reporting program ) that requires reporting of all agricultural pesticide use at the level of Public Land Survey System sections (a unit approximately one square mile in area). There are several issues to consider in using these data for assigning "exposure" in epidemiologic studies. Monitoring data collected for regulatory purposes should be carefully evaluated for its usefulness for estimating individual exposures. The fate and transport of the chemicals in the environment should also be considered. Simple proximity measures to sites of chemical releases may not adequately describe the transport of the chemical in the environment. The likely route of exposure should be considered along with the biological plausibility for an association between the exposure and disease under study. Finally, much of the environmental monitoring data was collected within the past decade and reconstructing exposure over longer periods more relevant to cancer incidence will be challenging. Environmental databases have begun to be used in epidemiology studies of cancer to determine if disease mortality or incidence rates are higher in areas with specific environmental exposures (i.e., ecologic study designs) or as a means of classifying individuals with respect to their potential exposure in an analytic epidemiologic study design (i.e., case-control, cohort studies). With few exceptions, the residence location is used as the geographic location for assigning exposure. Below we provide an overview of the various types of spatially registered exposure data and include examples of their use in epidemiologic studies of cancer. a. Water quality data The US EPA is responsible for regulating public drinking water supplies. A water supply is regulated if it has 5 or more connections or serves at least 25 people. Routine monitoring is required for a variety of contaminants and naturally occurring elements including disinfection by-products, arsenic, nitrate, certain pesticides and volatile organic chemicals. States are required to report violations of the Maximum Contaminant Levels (MCL) to EPA. Since 1996, EPA has been required to maintain a National Contaminant Occurrence Database (NCOD) using occurrence data for both regulated and unregulated contaminants in public water systems. The majority of historical public water supply measurement data, however, reside with the states. Some states record the latitude and longitude of the locations where the water samples were taken (location in the distribution system, point of entry to the distribution system, or water source location). The location information is typically not publicly available but may be available to researchers with appropriate approvals. The water quality data are reported by utility and to be useful for epidemiologic studies a linkage to the towns served must be established. In larger metropolitan areas multiple utilities may serve a city or, conversely, one utility may serve multiple towns and subdivisions. Therefore, establishing an accurate linkage between the study participant's addresses and water utilities is essential to avoid misclassification of exposure. Long-term exposure metrics can be calculated when a lifetime water source history is collected. Examples of studies using public supply water quality monitoring data include studies of disinfection by-products [ 64 - 66 ]., nitrate [ 67 , 68 ]., radionuclides [ 69 , 70 ]., and arsenic [ 71 , 72 ]. Contaminants such as disinfection by-products and volatile organic compounds vary in concentration across a public supply distribution system. GIS-based modeling efforts have been used to improve estimates of exposure at individual residences [ 73 , 74 ]. In contrast to public water supplies, private domestic wells are not regulated and there are no monitoring requirements, although well owners may be required to provide some water quality information upon the sale of a property in some states. Some states have conducted representative surveys of private well water quality [ 75 ]. A nationwide survey was conducted by EPA in 1988–1990 [ 76 , 77 ]. The US Centers for Disease Control (CDC) conducted a survey of coliform bacteria, nitrate, and atrazine in private wells in nine Midwestern States . The paucity of historical water quality data for private wells limits the exposure assessment for epidemiologic studies of cancer in this population. The USGS NAWQA program has been collecting information on nutrients, pesticides, volatile organic compounds, radionuclides, and major ions in more than 50 river basins and aquifers since 1991. All of the measurement data include spatial attributes. Because the goal of this research effort is to understand ambient water quality (not necessarily the same as drinking water quality) these data may not be of direct use in epidemiologic studies. However, the NAWQA data may be useful in modeling efforts to estimate contaminant levels in private wells. EPA also maintains two data management systems containing water quality information collected by federal, state, and private groups for surface and ground waters in all 50 states. The Legacy Data Center (LDC) is an archived database with data dating from the early 20th century up to the end of 1998. STORET contains data collected beginning in 1999, along with older data documented data from the LDC. Table 4 summarizes the sources of water quality data. Table 4 Sources of Water Quality data Database name Source Agency URL Geographic Resolution National Contaminant Occurrence Database EPA Public water utility National Water Quality Assessment (NAWQA) Data Warehouse USGS Latitude and longitude Legacy Data Center/STORET EPA Latitude and longitude b. Air pollutants The EPA collects and processes monitoring data from states on six criteria air pollutants (carbon monoxide, nitrogen dioxide, ozone, sulfur dioxide, particulate matter [PM10 and PM2.5], lead) and hazardous air pollutants, of which 188 have been identified. The hazardous air pollutants (HAP), also known as air toxics, are those for which there is some evidence of an increased risk for cancer or adverse reproductive outcomes. Routine monitoring of HAPs is not required and the monitoring data that exists is sparsely distributed compared with the criteria air pollutants. The data are maintained in the Air Quality Systems database. EPA compiles HAP emissions from stationary sources (points and areas) and mobile sources in a National Toxics Inventory (NTI) database (now combined with the National Emissions Trends data in the National Emissions Inventory database), which is updated at three-year intervals. To do the updates, EPA obtains emissions inventories from state environmental agencies and supplemental data from other sources, including the Toxic Release Inventory. The first nationwide inventory was in 1996. The spatial scale of the emissions data varies by type of source. Location information for point sources emissions is available, whereas area-source emissions are estimated at the county level. Using a dispersion model EPA has estimated the annual average HAP concentrations for each census tract in the contiguous US [ 78 ]. These datasets are summarized in Table 5 . Table 5 Sources of Air Quality Data Dataset name Source Agency URL Geographic Resolution Air Quality System database EPA Monitoring stations (latitude, longitude) National Emissions Inventory EPA Varies (point locations, county level) Air pollutant monitoring data has been used in studies of lung cancer, which have generally employed some type of dispersion model to estimate exposure for metropolitan areas or census tracts [ 79 - 81 ]. Recently the modeled concentrations of HAP have been used to evaluate childhood cancer incidence [ 44 ]. Other studies have also evaluated traffic density and childhood cancer incidence [ 43 ]. c. Agricultural Pesticides In the United States the U.S. Department of Agriculture (USDA) is the main federal agency responsible for collecting information on pesticide use on crops and livestock. The availability of historical agricultural pesticide use data in the US has been reviewed [ 82 ]. The first comprehensive survey of pesticide use on crops occurred in 1964 [ 83 ] and periodic surveys were conducted thereafter through the 1970s. These early surveys only provided national or regional estimates of crop-specific use for individual pesticides. From 1986 onwards, the USDA surveys produced state-specific estimates of pesticide use on field crops in the major producing states and from 1990 onwards, biannual state-specific estimates of pesticide use on fruits and vegetables were also available. Several states have collected their own pesticide use information but most data collection efforts have been recent. Oregon enacted legislation requiring reporting of agricultural pesticide use beginning in 2002; however, insufficient funding was provided for additional years. State pesticide use data are most comprehensive for California, which has had some type of mandatory reporting for agricultural pesticides since the 1950s, currently overseen by the California Department of Pesticide Regulation. Beginning in 1969, information about restricted-use pesticides was made public. In 1990, a new law required growers to report all pesticide use on crops on a monthly basis, including the pesticide name and manufacturer, crop treated, the public land survey section where the pesticide was applied, the date and time of application, number of acres treated, method of application, and application rates. The availability of this detailed pesticide use data at the spatial scale of a section led to the development of methods to link the use data to cancer incidence data [ 84 ] for use in an ecologic study of childhood cancer at the census tract level [ 42 ]. The California data have also been used in a case-control study of pancreas cancer [ 85 ], cohort study of breast cancer [ 51 ], and an as-yet unpublished case-control study of childhood cancer. Methods have also been developed to estimate potential pesticide exposure at residences by linking pesticide use data to crop maps [ 86 , 87 ]. Pesticide "exposure" is assigned to homes that have crop fields within distances that reflect likely pesticide drift. Table 6 summarizes the sources of pesticide data. Table 6 Sources of Pesticide Data Dataset name Source Agency URL Geographic Resolution Agricultural Chemical Use USDA State California Pesticide Use Reporting database California Department of Pesticide Regulation Public Land Survey Section (approximately one square mile) d. Industrial releases and hazardous waste The Emergency Planning and Community Right to Know Act of 1986 in the United States requires certain industries to report to EPA annually their releases and waste management activities involving specific toxic chemicals. The data are available to the public in a database called the Toxics Release Inventory (TRI). Manufacturing, metal mining, coal mining, and electric generating facilities must report the estimated mass of toxic chemicals released into the environment (air, water, land, or underground injection), treated on-site, or shipped off-site for further waste treatment. Reporting is required only for facilities that meet certain minimum criteria in terms of the pounds of toxic chemical produced or processed; persistent chemicals that bioaccumulate are subject to lower minimum reporting requirements. The regulations do not require environmental monitoring, so much of the data are estimates of releases. Location information is reported by the business and is not verified by EPA. Some of the strengths and limitations of these data for environmental health studies has been described [ 88 , 89 ]. Canada also requires reporting of emissions of chemicals rated by the International Agency for Research on Cancer as likely, probable, and possible human carcinogens for 64 industrial sectors [ 90 ]. These data form part of the Canadian Environmental Quality Database, which also contains a national inventory of municipal waste disposal sites, municipal drinking water data, air quality data, and historical industrial location and productivity data [ 91 ]. A large multi-province case-control study of 18 cancer sites was conducted with the aim of linking residential histories by postal code to the environmental database for cancer surveillance. To date, one analysis of residential proximity to 7 types of heavy industries and risk of non-Hodgkin lymphoma (NHL) has been published. Residential proximity within 3.2 km of copper smelters and <0.8 km of sulfite pulp mills was associated with an increased risk of NHL [ 92 ] after adjusting for employment in the industries evaluated. Earlier case-control studies of NHL [ 93 ] and leukemia [ 94 ] found elevated risks for residing close to industrial sites but these studies relied on a self-reported assessment of the distance of the residence from industrial facilities which may be subject to recall bias. The EPA maintains information on the location of waste handlers, waste treatment facilities and waste sites that are regulated under the Resource and Conservation Recovery Act (RCRA) and the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), also known as the Superfund law in the RCRAInfo database available through the Envirofacts Data Warehouse. Information on the location of companies issued permits to discharge waste into rivers is maintained in the Permit Compliance System database (also available through Envirofacts). These data sources are summarized in Table 7 . Table 7 Sources of Hazardous Waste Data Dataset name Source Agency URL Geographic Resolution Toxics Release Inventory EPA Latitude, longitude HazDat ATSDR Latitude, longitude RCRAInfo EPA Latitude, longitude Permit Compliance System (PCS) The U.S. Agency for Toxic Substances and Disease Registry (ATSDR) was established by Congress in 1980 under CERCLA. Since 1986, ATSDR has been required to conduct a public health assessment at each of the sites on the EPA National Priorities List, waste sites deemed to be the most hazardous. The aim of these evaluations is evaluate exposure to hazardous substances and health effects among the population living in vicinity of the site [ 95 ]. The location of the sites and information on specific contaminants by the type of media (soil, air, water) in which they were measured are available from the ATSDR HazDat database web site. Limitations of these monitoring data for cancer studies include the limited historical measurement data. A few studies have evaluated cancer incidence among those potentially exposed to hazardous waste sites [ 96 ] or municipal waste sites and incinerators [ 97 , 98 ]. The reconstruction of historical exposure to releases from industries and waste sites is difficult for studies of cancers of long latency. A few studies have evaluated proximity and residence duration near sites. Long duration of residence within one-half mile of a chemical plant manufacturing PCBs was positively correlated with blood serum PCB concentrations [ 99 ]. However, none of the epidemiologic studies to date determined whether proximity resulted in meaningful exposure to chemicals from the sites. Confounding by socioeconomic status should also be evaluated because manufacturing and waste facilities are more likely to be located in neighborhoods of lower socioeconomic status [ 100 ] and socioeconomic status is associated with the incidence of some cancers. 5. Remote sensing/aerial imaging Remotely sensed data include images of the earth and our atmosphere obtained by satellites or aircraft. The usefulness of the information depends largely on the technology used to obtain the imagery and the additional processing that has been done to georeference the data. The USGS Earth Resources Observation Systems Data Center (EDC) is the major U.S. storehouse of these data. Aerial photography has been available since the early part of the twentieth century. Digital Orthophoto Quadrangles (DOQs) which are digital images of aerial photos which combine the image characteristics of a photo with the georeferenced qualities of a map are available through EDC from 1987 through the present. DOQs are available in black and white, natural color, or color-infrared images and have 1-meter ground resolution. Satellite imagery useful for land cover characterization includes the multispectral Landsat imagery available as early as 1972. USGS has created historical land use and land cover data derived from 1970s and 1980s aerial photography (the Land Use and Land Cover Data). A national land cover datasets (NLCD) derived from Landsat multispectral imagery for 1992 is available. The Multi-resolution Land Characteristics (MRLC) national dataset which represents land cover in 2000 is currently being developed. Table 8 summarizes these data sources. Applications of these data to studies of cancer have included mapping residences on crop maps to estimate their probable exposure to agricultural pesticides [ 49 , 87 , 101 ]. Table 8 Sources of Remote Sensing Data Dataset name Source Agency URL Geographic Resolution Digital orthophoto quadrangles USGS 1:12,000 Satellite imagery USGS 1 meter to 1 km National Landcover Dataset (NLCD) 1992 USGS 30 meters Multi-resolution Land Characteristics (MRLC) 2000 Centralized geospatial data availability The data sources we have described are available from a multitude of federal and state agencies. The National Cancer Institute's Geographic Information Systems web site offers links to many of these sources, as well as links to freely available geographical tools and resources. There have also been several initiatives to try and compile spatial data into a shared, centralized information system [ 102 ]. Such centralized systems offer the promise of standardized data coding systems, file formats and geographic boundary definitions. They also facilitate the sharing of metadata, or descriptive information about the data. The leader in this endeavor has been the Federal Geographic Data Committee . The FGDC is a consortium of federal agencies with the charge of developing the National Spatial Data Infrastructure (NSDI), a set of technologies, policies, standards and procedures that facilitate the creation and sharing of geospatial data. Among the achievements of the FGDC is the establishment of the National Spatial Data Clearinghouse, a central catalog of links to geospatial data and metadata. In 2003, an enhanced web portal was launched to further facilitate access to this data. Many states have echoed the national clearinghouse with clearinghouses of their own. The New York GIS Clearinghouse , for example, boasts over 400 member institutions providing links to thousands of datasets. The cancer data collection community has yet to fully engage this resource. As of January 2004, no cancer incidence or mortality data was available through the national clearinghouse. The keyword "cancer" provided only a link to the Environmental Defense Scorecard, a web site from which various environmental data sets can be accessed, particularly those published by the EPA . Most of the very limited data in the "human health and disease" category accessible through the web portal consisted of hospital and other health facility locations for a smattering of states. In some cases, the steps required to make cancer data available through the national clearinghouse would be modest. For example, the NCI's mortality data, geographic boundary files, and associated metadata used in its Cancer Mortality Maps and Graphs web site are easily accessed and downloaded, and only minor modifications would be required to make them compliant with FGDC standards. The DataWeb is another centralized online data resource, consisting of a network of online data libraries created in a collaboration between the CDC and the US Census Bureau. The libraries consist of both microdata and aggregate data in numerous categories. Available health data includes NHANES and NHIS survey data and county-level mortality. Information in DataWeb is accessed through DataFerret, an application that prepares data sets for the user to download. It allows users to select a "databasket" of variables and then recode those variables as needed. Users develop and customize data tables and may download them to their desktop in a variety of common formats. Conclusion In this article we have surveyed the distinctive characteristics of spatial data, along with commonly available sources of data relevant to etiologic cancer research. Spatial analysis is invaluable for data exploration, identification of geographic patterns, generation of new hypotheses, and providing supporting evidence about existing hypotheses. A geographic perspective will be increasingly relevant as GIS software, spatial analytic methods, and the availability and quality of geographically referenced data continues to improve.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539245.xml
212700	Developmental Origins and Evolution of Buchnera Host Cells	null	When it comes to exploiting a niche, endosymbionts take the prize. In endosymbiosis, one organism—the endosymbiont —invades the cells of another, in some cases taking up residence in a way that actually benefits the host. Bacteria are particularly adept at making themselves indispensable by insinuating themselves into some fundamental aspect of an organism's biology. The endosymbiotic hypothesis proposes that this is how certain eukaryotic organelles evolved from endosymbiotic bacteria. Insights into the mechanisms governing endosymbiosis will help biologists understand how this mutually beneficial relationship evolved and provide clues to one of the fundamental questions in biology: How did the eukaryotic cell evolve? Over 10% of insect species rely on endosymbionts for their development and survival. In this issue, David Stern and colleagues look at one of the most studied pairs, the pea aphid and Buchnera aphidicola , and discover clues to the molecular foundation of their shared fate. ( Buchnera , which can no longer survive outside its host cell, is thought to produce essential amino acids that the aphid cannot get on its own.) While it is known that Buchnera are transferred from clusters of bacteriocytes in the mother to the adjacent early-stage embryo, it has been unclear how the bacteriocytes develop. Previous studies of the bacteria's genome have failed to explain the genetic basis of Buchnera 's ability to invade aphid cells. Consequently, Stern and colleagues have focused on the bacteriocytes, the specialized insect cells that house Buchnera , shedding light on the development of these cells as well as on the evolutionary adaptations in the aphid that made the bacteriocytes hospitable to Buchnera . The researchers show that bacteriocytes differentiate and proliferate independently of Buchnera 's presence in the cell, and they identify three aphid transcription factors (proteins that regulate gene expression) that are expressed in three distinct stages during early-bacteriocyte development in the aphid embryo. The first protein is expressed just before Buchnera enters the embryo; a second, as the bacteria invades; and a third, after the transfer is nearly complete. A second wave of the same transcription factors occurs at a later stage in aphid embryo development and increases the population of bacteriocytes. This two-step specification of bacteriocytes, which occurs in related Buchnera -carrying aphid species, appears to be an evolutionarily conserved feature of aphids. It even occurs in an aphid species that once had a Buchnera endosymbiont and now has a yeast-like symbiont that lives outside the bacteriocytes. But this process is not observed in males of another aphid species that do not carry Buchnera . While traces of the first transcription factor activated in bacteriocytes are evident, the characteristic gene-expression pattern is not, and the aphids have no mature bacteriocytes. While it seems that the aphid has evolved new domains of expression in the bacteriocyte for these transcription factors—none of these transcription factors is expressed at a similar stage in other insects—the researchers cannot yet say whether these genes direct the specification of bacteriocytes. Still, these transcription factors are likely to play important roles in the bacteriocyte, suggesting that the union of aphids and Buchnera involved significant adaptations by the host. Aphid host of Buchnera endosymbionts	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC212700.xml
539053	Imaging Lymph Nodes with Nanoparticles	null	Accurate staging of cancers is one of the most important parts of the work up of patients for both prediction of prognosis and determination of the most appropriate treatment. And an essential part of this work up is assessing whether or not there has been lymphatic spread. Current methods include surgical removal of nodes for examination and various types of imaging, ranging from ultrasound to newer technologies such as magnetic resonance imaging (MRI). All these methods have problems; some are very invasive, others are very time consuming, and none are completely reliable. 3-D image of lymph node after automated analysis However in one of the more exciting crossovers from chemistry into medicine, researchers have developed nanoparticles to improve the diagnostic accuracy of MRI. The nanoparticles contain a central superparamagnetic iron oxide core and are covered by dextran, imparting long circulation times and biocompatibility. When injected intravenously, the nanoparticles localize to lymphoid tissue, and are internalized into macrophages. There is then a decrease in signal intensity on T2- and T2*-weighted images, and when metastases are present there is a recognizably abnormal pattern on MRI scans. In a previous paper published in the New England Journal of Medicine , Ralph Weissleder and colleagues described using these nanoparticles to assess lymphoid spread in patients with prostate cancer. Now, in a paper published in this month's PLoS Medicine , they have gone further by extending the analysis to patients with different types of cancer, and producing an algorithm that allows semiautomation of the procedure. The authors developed the algorithm in a training group of 36 patients and then validated it in a group of 34 patients. The results are encouraging: the analysis showed a sensitivity of 98% (95% confidence interval, 88%–99%) and a specificity of 92% (95% confidence interval, 87%–96%). The advantages of automating this procedure are substantial, not least because it can remove the problem of different observers assessing data differently. And what is more, once the data have been collected and assessed it is possible to reconstruct a virtual picture of the patient's lymph nodes, thus potentially allowing accurate surgical removal of the nodes.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539053.xml
387280	Phage Display Libraries Identify T Cells	null	Doctors and researchers often look for the rapid proliferation of T cell populations, key defensive players in the immune system, as a telltale sign that the body is working hard to fend off a foreign threat. Every one of these circulating white blood cells carries a T cell receptor (TCR) that binds to a specific protein, or antigen, when displayed on the surface of a cell. A match between TCR and displayed antigen results in the cell's death and the subsequent expansion of T cell clones, all programmed to recognize the original offending protein. Some TCRs bind and expand in response to pathogenic antigens, such as viral or bacterial proteins. But T cells can also react and proliferate inappropriately in response to the body's own proteins, leading to destructive autoimmune diseases such as multiple sclerosis, which is characterized by immune system attacks on nervous tissue. Self-recognizing TCRs, however, can also target and destroy tumors—though full activation of these T cells is inconsistent and poorly understood. Peptide display Identifying the particular antigen behind an exploding population of T cells is invaluable for finding the source of autoimmune diseases and studying immune responses to cancer. But it's a laborious and time-consuming process, as researchers are faced with the prospect of sifting through millions upon millions of possible matches between TCRs and their prospective antigen epitopes—the part of the antigenic molecule to which the receptor binds. Now, as they report in this issue of PLoS Biology , Frances Crawford and colleagues have developed a novel method for rapidly identifying TCR mimotopes—peptide sequences similar or identical to epitopes that also elicit the immune response—which can be used to determine the antigen of a given T cell population. Working backwards, the team started off with two different T cell clones that had been previously selected for with a known antigen—a peptide called p3K. One clone was derived from mice genetically engineered to have broadly reactive T cells; the other, a conventional clone, was much more sensitive to the precise molecular structure of p3K. Crawford and colleagues then created a “peptide library” comprising more than 30,000 baculoviruses (viruses that selectively target insect cells), each one carrying a slightly different version of the p3K gene, varied in regions of the peptide known to be important for TCR binding. These p3K genes were embedded within a major histocompatibility complex (MHC) gene—a type of cell surface protein that holds displayed antigens and is also important for proper TCR recognition. The team then unleashed their virus library onto insect cells that, once infected, began to produce the specific peptide–MHC complexes encoded on the viral DNA. The insect cells then shuttled these proteins to their surfaces, resulting in a vast array of cells that each displayed a unique variant of the p3K–MHC complex. This “display library” was then incubated with fluorescently labeled TCRs from the two different clones. By observing and isolating the insect cells that lit up, the researchers could see which of the thousands of cells displaying peptide–MHC possessed a mimotope capable of binding a TCR. Because the genetic information about the displayed complex was still stored within the virus-infected cell, the researchers could determine the full peptide sequence responsible for the identified mimotopes. Confirming the effectiveness of their method, the results of the fluorescence experiments echoed the authors' original characterizations about the two populations of T cells. The broadly reactive TCR bound to several different uniquely displayed complexes; it had 20 mimotopes. The conventional TCR, however, bound only to one peptide–MHC complex, an almost perfect match to the original p3K peptide. Though this study was based on a known antigen and epitope (which allowed verification of the method), the baculovirus display library technique described here could easily be used on T cell populations with unknown antigens. With such a tool, researchers could, for example, identify the antigens connected with tumor-fighting T cells and, through inoculation, possibly induce the production of similar T cells in cancer patients who lack them.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC387280.xml
549205	Quantitative evaluation and modeling of two-dimensional neovascular network complexity: the surface fractal dimension	Background Modeling the complex development and growth of tumor angiogenesis using mathematics and biological data is a burgeoning area of cancer research. Architectural complexity is the main feature of every anatomical system, including organs, tissues, cells and sub-cellular entities. The vascular system is a complex network whose geometrical characteristics cannot be properly defined using the principles of Euclidean geometry, which is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature. However, fractal geometry is a more powerful means of quantifying the spatial complexity of real objects. Methods This paper introduces the surface fractal dimension (D s ) as a numerical index of the two-dimensional (2-D) geometrical complexity of tumor vascular networks, and their behavior during computer-simulated changes in vessel density and distribution. Results We show that D s significantly depends on the number of vessels and their pattern of distribution. This demonstrates that the quantitative evaluation of the 2-D geometrical complexity of tumor vascular systems can be useful not only to measure its complex architecture, but also to model its development and growth. Conclusions Studying the fractal properties of neovascularity induces reflections upon the real significance of the complex form of branched anatomical structures, in an attempt to define more appropriate methods of describing them quantitatively. This knowledge can be used to predict the aggressiveness of malignant tumors and design compounds that can halt the process of angiogenesis and influence tumor growth.	Background The term "angiogenesis" defines the fundamental process of the development and growth of new blood vessels from the pre-existing vasculature, and is essential for reproduction, development and wound repair [ 1 ]. Under these conditions, it is highly regulated: i.e. "turned on" for brief periods of time (days) and then completely inhibited. The cyclic nature of the microvascular bed in the corpus luteum provides a unique experimental model for examining the discrete physiological steps of angiogenesis in the life cycle of endothelial cells which, together with pericytes (supportive vascular smooth muscle cells), carry all of the genetic information necessary to form tubes , branches and entire capillary networks . However, many human diseases (including solid tumors) are driven by persistently up-regulated angiogenesis [ 1 ]. In some non-malignant processes, such as pyogenic granuloma or keloid formation [ 2 ], angiogenesis is prolonged but still self-limited ; however, this is not true of tumor angiogenesis which, once begun, continues indefinitely until the entire tumor is eradicated or the host dies. Without blood vessels, tumors cannot grow beyond a critical size (1–2 mm) or metastasize to another organ. Angiogenesis is one of the most complex dynamic processes in biology, and is highly regulated by a balance of pro- and anti-angiogenic molecules. It is now widely accepted that the "angiogenic switch" is "off" when the effects of pro-angiogenic molecules is balanced by that of anti-angiogenic molecules, and "on" when the net balance is tipped in favor of angiogenesis [ 1 , 3 ]. Pro- and anti-angiogenic molecules can be secreted from cancer cells, endothelial cells, stromal cells, blood, and the extra-cellular matrix [ 4 , 5 ], the relative contributions of which are likely to change with tumor type and site, as well as with tumor growth, regression and relapse [ 1 ]. Although considerable advances have been made in our molecular and cellular knowledge of the promotion , mediation and inhibition of angiogenesis, very little is known about its underlying complex dynamics . Vasculature and more generally tubular organs develop in a wide variety of ways involving many cell processes [ 6 - 8 ]. In mathematical terms, angiogenesis is a non-linear dynamic system that is discontinuous in space and time , but advances through qualitatively different states . The word state defines the configuration pattern of the system at any given moment, and a dynamic system can be represented as a set of different states and a number of transitions from one state to another over a certain time interval [ 9 , 10 ]. At least seven critical steps have so far been identified in the sequence of angiogenic events on the basis of sprout formation: a) endothelial cells are activated by an angiogenic stimulus; b) the endothelial cells secrete proteases to degrade the basement membrane and extra-cellular matrix; c) a capillary sprout is formed as a result of directed endothelial cell migration, d) grows by means of cell mitoses and migration, and e) forms a lumen and a new basement membrane; f) two sprouts come together to form a capillary loop; and g) second-generation capillary sprouts begin to form [ 1 , 11 , 12 ] (Fig. 1 ). The progression of these states generates a complex ramified structure that irregularly fills the surrounding environment (Fig. 2 ). The main feature of the newly generated vasculature is the structural diversity of the vessel sizes, shapes and connecting patterns. Tumor vessels are structurally and functionally abnormal [ 1 , 3 ]: unlike normal vessels, they are highly disorganized, tortuous and dilated, and have uneven diameters, and excessive branching and shunts. This may be mainly due to the heterogeneous distribution of angiogenic regulators, such as vascular-endothelial growth factor (VEGF), basic fibroblastic growth factor (bFGF) and angiopoietin [ 5 , 13 ], leading to chaotic tumor blood flow, and hypoxic and acidic tumoral regions [ 5 , 14 - 16 ]. Moreover, although it is commonly believed that the endothelial cells making-up tumor vessels are genetically stable, diploid cells (and thus different from genetically unstable neoplastic cells), tumor vasculature seems to be much more unpredictable [ 17 ]. These conditions all reduce the effectiveness of treatments, modulate the production of pro- and anti-angiogenic molecules, and select a subset of more aggressive cancer cells with higher metastatic potential [ 1 ]. A large number of clinical trials of anti-angiogenic therapies are being conducted throughout the world, but investigators are still concerned about how to achieve the maximum benefit from them and how to monitor patient response. There are currently no markers of the net angiogenic activity of a tumor that can help investigators to design specific anti-angiogenic treatment strategies [ 5 , 18 ], but it is reasonable to resume that the quantification of various aspects of tumor vasculature may provide an indication of angiogenic activity. One often-quantified element of tumor vasculature is microvessel density (MVD), which is used to allow a histological assessment of tumor angiogenesis. The results of studies carried out over the last decade have suggested the value of using tumor MVD as a prognostic index in a wide variety of solid cancers, and it has also recently been assumed that MVD may reveal the degree of angiogenic activity in a tumor. On the basis of these assumptions, the quantification of MVD is thought to be a surrogate marker of the efficacy of anti-angiogenic agents as well as a means of assessing which patients are good candidates for anti-angiogenic therapy. However, MVD has a number of substantial limitations, mainly due to the complex biology characterizing tumor vasculature [ 17 ], and the highly irregular geometry that the vascular system assumes in real space , which cannot be measured using the principles of Euclidean geometry because it is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature. However, quantitative descriptors of its geometrical complexity can be usefully abstracted from the fractal geometry introduced by Benoit Mandelbrot in 1975 [ 20 , 21 ]. We here discuss the surface fractal dimension (D S ) as a quantitative index of the 2-D geometrical complexity of vascular networks and their behavior during computer-simulated changes in vessel density and distribution . Geometrical properties of a vascular network The human vascular system can be geometrically depicted as a complex fractal network of vessels that irregularly branch with a systematic reduction in their length and diameter [ 19 ]. Fractal objects are mainly characterized by four properties: a) the irregularity of their shape; b) the self-similarity of their structure; c) their non-integer or fractal dimension ; and d) scaling , which means that the measured properties depends on the scale at which they are measured [ 22 ]. One particular feature of fractal objects is that the schemas defining them are continuously repeated at decreasing orders of magnitude, and so the form of their component parts is similar to that of the whole [ 20 , 21 ]: this property is called self-similarity . Unlike geometrical self-similarity , which only concerns mathematical fractal objects in which every smaller piece is an exact duplicate of the whole (e.g. Koch's snowflake curve, Sierpinski's triangle and Menger's sponge), statistical self-similarity concerns all complex anatomical systems, including tumor vasculature. The smaller pieces constituting anatomical entities are rarely identical copies of the whole, but more frequently "similar" to it and, in such systems, the statistical properties of the pieces are proportional to the statistical properties of the whole [ 23 ]. Dimension is a numerical attribute of an object that does not depend on its process of generation, and has been defined in two ways. The first is the topological or Euclidean dimension (Fig. 3 ), which assigns an integer to every point or set of points in Euclidean space ( E ): 0 to a point (defined as that which has no part); 1 to a straight line (defined as a length without thickness), 2 to a plane surface (defined as having length and thickness, but no depth); and 3 to three-dimensional figures (a volume defined by length, thickness and depth). The second was introduced by the mathematicians Felix Hausdorff and Abram S. Besicovitch, who attributed a real number to every natural object in E lying between the topological dimensions 0 and 3 (Fig. 3 ). Benoit Mandelbrot uses the symbol D γ to indicates the topological dimension, and the symbol D to indicate that of Hausdorff-Besicovitch (also called the fractal dimension ). The D γ and D of all Euclidean figures are coincident ( D γ = D ), but this is not true of fractal objects in which D is always > D γ . As no anatomical entity corresponds to a regular Euclidean figure, their dimension is always expressed by a non-integer number falling between two integer topological dimensions. In our case (Fig. 2 ), the vascular network has a dimension lying between 2 (plane surface) and 3 (volume), and any two-dimensional section of a vascular system (as in the case of a histological section) has a dimension lying between 0 (the dimension of a single isolated point) and 2 when the sectioned vessels entirely fill a plane surface (Figs. 3 and 4 ). Anatomical structures are also hierarchical systems that operate at different spatial and temporal scales , and different patterns can change, appear or disappear depending on the scale of magnification [ 22 ]. A fundamental characteristic is that the process operating at a given scale cannot be important at higher or lower scales [ 23 ]. The irregularity and self-similarity underlying scale changes are the main attributes of the architectural complexity of both normal and pathological biological entities [ 22 - 26 ]. In other words, the shape of a self-similar object does not change when the scale of measure changes because every part of it is similar to the original object; however, the magnitude and other geometrical parameters (e.g. the outline perimeter) of an irregular object differ when inspected at increasing resolutions that reveal an increasing number of details [ 25 ]. Over the last decade, accumulating experimental evidence has shown that the fractal patterns or self-similar structures of biological tissues can only be observed within the scaling window of an experimentally established measure of length ε 1 - ε 2 (Fig. 4 ), within which experimental data sets follow a straight line with a slope (1-D) : i.e. the fractal dimension remains invariant at different magnifications [ 20 - 27 ]. Methods Computer-aided modeling of two-dimensional vascular tree complexity We have developed a computer model to simulate the geometrical complexity of a histological two-dimensional section of a tumor vascular tree that automatically generates an unlimited number of images with a changeable density of vessels irregularly distributed on a planar surface. In order to simplify the model, we considered all of the vessels as rounded, unconnected objects of equal magnitude (Fig. 5 ). As the parameters of a model must be as few as possible and it is necessary to reduce mathematical complexity [ 28 - 30 ], we included only two variables: a) the number of vessels; and b) their distribution in the surrounding environment. The vessel distribution patterns were randomly generated using different time-dependent seeds for random number function generation. One thousand images were automatically generated for each vessel density (from five to 50 vessels, with the number being increased by five in each group), and their D S were estimated using the box-counting method [ 22 ]. D S was automatically estimated using the equation: where ε is the side-length of the box, and N ( ε ) the smallest number of boxes of side ε required to completely contain the irregular object (Fig. 4 ). As the zero limit cannot be applied to biological images, D S was estimated by means of the equation: (2) D S = d where d is the slope of the graph of log [N(ε)] against log (1/ε) , in a fixed range of side-lengths ( ε 1 - ε 2 ) empirically evaluated by visualization [ 20 - 29 ]. Statistical analysis All of the data are expressed as mean values ± standard deviation, and the results were analysed using the Statistica software package (StatSoft Inc. Tulsa, USA). Unvaried analysis was performed by means of the Student t as required for parametric variables. p values of less than 0.05 were considered statistically significant. Results The computer-aided simulations showed that different D S values can be obtained for images with the same vessel density (Fig. 6 ). As the only variable in these images is the vessel distribution pattern, D S depends on the irregular arrangement of the vessels in the surrounding environment. D S also significantly increased ( p <0.05) when higher vessel densities were considered in the system (Fig. 6 ) because of the greater space filled by the vascular component (as shown in Fig. 3 ); the increased density of the vessels reduces the variability in their space-filling properties, and thus the standard deviation (Fig. 6 ). Discussion and conclusions One of the most important and distinctive characteristics of biological systems is the complexity of their shape ( geometrical or spatial complexity) and functions ( behavioral complexity). Complexity is a real quality of organized biological matter that is mainly manifested in the living world as diversity and organization . No two anatomical systems are exactly alike because of the enormous variability not only between the different members of a population, but also between the component parts of an organism. The word complexity has long been used descriptively in order to describe, for example, a large number of genes or cellular interconnections [ 33 ], but complexity can also reside in the structure of a system ( i.e. an intricate architecture or the existence of many different component parts with varying interactions) or its non-linear functions ( i.e. physiological rhythms are rarely strictly periodic but fluctuate irregularly over time) [ 34 ]. The vascular system is a complex network consisting of branched tubes of different sizes that are irregularly settled in the surrounding environment [ 6 , 7 ]. This geometrical characteristic highlights the complexity of its generating process in space and time , and greatly biases any quantitative method that tends to idealize it as a smooth and regular Euclidean object. However, both normal and tumor vasculature can more properly be considered fractal objects because of their irregular shape ( spatial conformation ), self-similar structure, non-integer dimension and dependence on the scale of observation ( scaling effect ) [ 19 , 35 - 37 ]. We here discuss the estimate of D S as a quantitative index of the 2-D spatial complexity of the vascular tree, in order to provide a closer-to-reality measure of this complex anatomical entity (Figs. 3 and 4 ). The theory underlying D S was abstracted from fractal geometry, which is also called the geometry of irregularity [ 20 , 21 ]. The concept of spatial conformation has played a fundamental role in the study of biological macromolecules in chemistry (particularly biochemistry) since the early 1950s. However, it has only been introduced in the science of morphology as theoretical morphology , which studies extant organismal forms (complex structures of interdependent and subordinate elements whose relationships and properties are largely determined by their function in the whole) as a subset of the range of theoretically possible morphologies [ 32 ]. The significance of D S also comes from the fact that, like any other complex biological system, the vascular tree cannot be correctly quantified by measuring its individual properties (i.e. micro-vessel density, MVD). D S is a parameter that depends on: a) the number of vessels; b) the spatial relationships between the vascular components; and c) the interactions between the vascular components and the surrounding environment. In other words, its estimate is "ecologically" important because it provides a quantitative index of the "habitat structure". As computer models are crucial for scientific procedures, and the modeling process itself represents the hypothetical-deductive approach in science [ 30 - 32 ], we developed a simple computer-aided model capable of generating an unlimited number of 2-D images of a simulated vascular network. The model was simplified by using a minimum amount of mathematical complexity and only two variables: the number of vessels and their pattern of distribution. A total of 10,000 images showing a different number of unconnected vessels irregularly distributed on a planar surface were automatically generated (Fig. 5 ) and, interestingly, it was found that D S increased with the number of vessels making up the system (Fig. 6 ); furthermore, its value changed when the same number of vessels were differently distributed in the surrounding environment. In other words, it is plausible that an equal number of vessels may have different space-filling properties depending on their distribution pattern. These results suggest the usefulness of this model when comparing real vasculature configurations in order to explore the morphological variability that can be produced in nature, as it is now well known that aberrant vascular architectures in tumors may affect the uniform delivery of specific drugs to all cancer cells [ 15 ]. The model also suggests that: a) D s can be an estimate of the 2-D geometrical complexity of the vascular system. As 2-D vascular complexity depends on the number of vessels and their distribution pattern, the use of MVD quantification alone to measure the angiogenic dependence of a tumor is strongly biased because the number of vessels does not reflect the number of tumor cells that can be supported by a vessel. Moreover the metabolic needs of cancer cells vary with the tissue of origin and change with tumor progression [ 18 ]. b) D S depends on the degree of vessel contiguity and continuity . These two geometrical properties determine what is called the intercapillary distance , and are not only involved in the spatial complexity of tumor vasculature, but also reflect the inviolable demand of a growing tumor for sufficient levels of nutrition and oxygen exchange. Inter-capillary distances are locally defined by the net balance between pro- and anti-angiogenic molecules in each microtissue region, as well as by non-angiogenic factors such as the oxygen and nutrient consumption rates of tumor cells. In normal tissue, vessel density fairly accurately reflects cell metabolic demands because evolutionary pressures have led to close and efficient coupling between vascular supply and metabolic needs. In tumors, the close coupling between vascular density and oxygen or nutrient consumption ( i.e. the environment) may be loosened [ 18 ], thus altering not only the number of vessels but also the whole vascular architecture [ 15 , 38 ]. c) D S falls between 0 (corresponding to the Euclidean dimension of a point) and 2 (the dimension of a plane). The more D S tends towards 2, the more the analyzed vascular configuration tends to fill a 2-D space and the greater its geometrical complexity. In conclusion, the present study indicates that the complex geometry of tumor vasculature and its well-known biological characteristics [ 18 ] mean that vascular network cannot be measured on the basis of MVD estimates alone. These findings also support the findings of various authors who have shown the uselessness of MVD as a predictor of anti-angiogenic treatment efficacy or for stratifying patients in therapeutic trials [ 14 , 39 - 41 ]. Scientific knowledge develops through the evolution of new concepts, and this process is usually driven by new methodologies that provide previously unavailable observation. The potential broad applicability of the proposed quantitative index makes it possible to explore the range of the morphological variability of vasculature that can be produced in nature, thus increasing its diagnostic importance in cancer research. Abbreviations Ds, Surface fractal dimension; 2-D, two-dimensional; VEGF, Vascular-endothelial growth factor; bFGF, basic fibroblastic growth factor; MVD, microvessel density. Competing interests The author(s) declare that they have no competing interests. Authors' contributions FG conceived, coordinated and designed the study and drafted the manuscript; CR, PC, BF, EEF, EC, MCI participated in designing the study and drafting the manuscript. All of the authors have read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC549205.xml
549211	Life-threatening ventricular arrhythmia recognition by nonlinear descriptor	Background Ventricular tachycardia (VT) and ventricular fibrillation (VF) are ventricular cardiac arrhythmia that could be catastrophic and life threatening. Correct and timely detection of VT or VF can save lives. Methods In this paper, a multiscale-based non-linear descriptor, the Hurst index, is proposed to characterize the ECG episode, so that VT and VF can be recognized as different from normal sinus rhythm (NSR) in the descriptor domain. Results This newly proposed technique was tested using MIT-BIH malignant ventricular arrhythmia database. The relationship between the ECG episode length and the corresponding recognition performance was studied. The experiments demonstrated good performance of the proposed descriptor. An accuracy rate as high as 100% was obtained for VT/VF to be recognized from NSR; for VT and VF to be recognized from each other, the recognition accuracy varies from 84.24% to 100%. In addition, the results were compared favorably against those obtained using Complexity measure. Conclusions There is strong potential for using the Hurst index for malignant ventricular arrhythmia recognition in clinical applications.	Introduction If a life-threatening ventricular tachycardia (VT) or ventricular fibrillation (VF) is detected promptly, a high energy electrical shock can be delivered to the heart, in an attempt to return the heart to a normal sinus rhythm (NSR). If a normal sinus rhythm is misinterpreted as VT or VF, leading to delivering of an unnecessary shock, it can damage the heart, causing fatal consequences to the patient. Therefore, correct and prompt detection of VT or VF is of great importance. However, the detection of these life-threatening cardiac arrhythmia is difficult because the waveform and frequency distribution of these life-threatening arrhythmia changes with the prolonged duration [ 1 ]. Furthermore, practical problems such as poor contact, movement, interference, etc, can produce artifacts that mimic these rhythms [ 2 ]. Till now, many linear techniques for VT/VF detection have been developed, such as the probability density function method [ 3 ], rate and irregularity analysis [ 4 ], analysis of peaks in the short-term autocorrelation function [ 5 ], sequential hypothesis testing algorithm [ 6 , 7 ], correlation waveform analysis [ 8 ], four fast template matching algorithms [ 9 ], VF-filter method [ 2 , 10 ], spectral analysis [ 1 ], and time-frequency analysis [ 11 ]. However, these methods exhibit disadvantages, some being too difficult to implement and compute for automated external defibrillators (AED's) and implantable cardioverter defibrillators (ICD's), and some only successful in limited cases. For example, the linear techniques [ 5 , 11 ] using the features of amplitude or frequency have shown their limits, since the amplitude of ECG signal decreases as the VF duration increases, and the frequency distribution changes with prolonged VF duration. Therefore, more sophisticated signal processing techniques are needed to fully describe and characterize VT and VF and facilitate the development of new detection schemes with high correct detection rate, or equivalently, with low false-positive and false-negative performance statistics. Recent studies [ 12 , 13 ] have shown that the cardiac dynamics are complex and non-linear. Even if they could be described by a set of differential equations, they would be of high dimensionality. Normally, each heart beat is initiated by a stimulus from pacemaker cells in the SA node in the right atrium. The activation wave then spreads through the atria to the AV junction. Following activation of the AV junction, the cardiac impulse spreads to the ventricular myocardium through a specialized network, the His-Purkinje system. This branching structure of the conduction system is a self-similar tree with finely scaled details on a microscopic level. The spread of the depolarization wave is represented by the QRS complex in ECG. Spectral analysis of the waveform reveals a broadband of frequencies. To explain the inverse power-law spectrum, West has conjectured that the repetitive branches of the His-Purkinje system represent a fractal set in which each generation of the self-similar tree imposes greater detail onto the system [ 14 ]. The effect of the finely branching fractal network is to subtly decorrelate the individual pulses that superpose to form the QRS complex. The distribution in path lengths resulting from the fractal nature of the branches give rise to a distribution of decorrelation time. Some methods developed based on the theory of non-linear dynamics have been highlighted for the analysis of the signals generated from non-linear system [ 15 ]. Due to the complex and non-linear dynamical behavior of the cardiac conduction system, non-linear dynamics or non-linear mathematical models are considered to be suitable tools for the analysis of ECG signals. Non-linear techniques have been proven to be major cornerstones for understanding the ECG signals [ 13 , 16 , 17 ]. Some non-linear techniques [ 18 - 20 ] have been developed for life-threatening ventricular arrhythmia recognition. However, there are still many problems requiring solution. The computational demands for most of the existing algorithms are considerably high and a long ECG episode duration is needed. In order to strike a balance between lower computational burden and reliable recognition performance, a non-linear descriptor, the Hurst index, is proposed as a new tool in this study for recognition of the life-threatening ventricular arrhythmia. The Hurst index is defined in the multiscale domain as a feature to quantify the non-linear dynamical behavior (such as, self-similarity, roughness and irregularity) of the ECG signal for detecting the life-threatening ventricular arrhythmia. ECG episodes with VT and VF from MIT-BIH malignant arrhythmia database [ 21 ] are tested for cardiac abnormality recognition. The data also included some NSR signals to check on the validity of the algorithm. Experimental results are compared with those obtained by a typically used non-linear technique, the Complexity measure, which has been shown to perform well for life-threatening ventricular arrhythmia recognition [ 20 ]. In this paper, the complexity measure is Zheng's complexity measure without exception. Detailed description of Zheng's complexity measure technique can be find in [ 20 ]. The present paper is organized as follows. Mathematical background on the proposed non-linear descriptor is given in Section. Methodology for the recognition of ventricular arrhythmia is described in Section. Section covers the experimental results and discussions. Lastly, a conclusion of the proposed study is given in Section. Multiscale-based non-linear descriptor Multiscale analysis is a useful framework for many signal processing tasks. Wavelet transform is a good tool for multiscale analysis, which allows the expansion of a signal from the time domain into the time-frequency domain. In this paper, the Hurst index, defined in multiscale space, is proposed for the characterization of ECG episodes. The Hurst index, H , is a single scalar parameter describing the fractal Brownian motion (fBm) model, which is a useful model for nonstationary stochastic self-similar processes with long term dependencies over wide ranges of frequencies [ 22 ]. fBm is an extension of the ordinary Brownian motion, and is a zero-mean Gaussian nonstationary stochastic process B H ( t ), t ∈ ℝ, 0 < H < 1, [ 23 ]. Self-similarity is inherent to the fBm structure. The fractal dimension D is a commonly used parameter for measuring self-similarity. The relationship between the fractal dimension, D , and the Hurst index H is: D = S - H , where S is the topology dimension. For a one-dimensional signal, S = 2; for a two-dimensional image, S = 3 [ 24 ]. The fBm model has following features: • It is non-stationary, which necessitates some time-dependent analysis. E ( B H ( t ) B H ( s )) = σ 2 /2(\| t \| 2 H + \| s \| 2 H - \| t - s \| 2 H ) (1) where E ( · ) represents the expectation operator, σ is the standard deviation, t is a time variable, s is a time lag variable. Based on Equation (1), the variance of fBm, is computed as var ( B H ( t )) = σ 2 \| t \| 2 H . • It is self-similar, which necessitates some scale-dependent analysis. { B H ( at )} ≜ a H B H ( t ), a ∈ ℝ + (2) where ℝ + is the set of positive real numbers. ≜ means equality in distribution, which means that the fBm has stationary increments, and the probability properties of the process B H ( t + s ) - B H ( t ) only depend on the lag variable s . The scalar index H of fBm is related to the complexity and roughness of fBm samples. Consider a discrete orthogonal wavelet decomposition of a given fBm, B H ( t ). For any given resolution 2 J , the wavelet mean-square representation of fBm is: Computing the corresponding wavelet coefficients amounts to evaluating the following approximate coefficients a j [ n ] and detail coefficients d j [ n ]: where φ ( t ) is the corresponding smooth function of wavelet ψ ( t ). Flandrin et al. in [ 22 ] have deduced the following theorem: When normalized according to Wavelet coefficients of fBm give rise to: where V ψ ( H ) is constant, which depends on both the chosen wavelet and the fBm index H . It follows the power-law behavior of the wavelet coefficients' variance: log 2 ( var ( d j [ n ])) = (2 H + 1) j + constant (9) Therefore, the fBm index H (and hence the associated fractal dimension D = 2 - H ) can be easily obtained from the slope of this variance plotted as a function of scale in a log-log plot. Life-threatening ventricular arrhythmia recognition by Hurst index For each testing ECG episode, the following steps are performed: • Perform wavelet decomposition and computation of its detail coefficients at different scales. • Compute the Hurst index H according to Equation (9). • Detect the life-threatening ventricular arrhythmia in the feature space of H . In this study, the wavelet used is a quadratic spline wavelet with compact support and one vanishing moment. It is a first derivative of a smooth function [ 25 ], whose discrete Fourier transform is: The low-pass and high-pass filters L ( ω ) and G ( ω ) are respectively: The dyadic wavelet transform (WT) of a digital signal f ( n ) can be calculated with Mallat's algorithm [ 26 ] as follows: where is a smoothing operator. is the wavelet transform of digital signal f ( n ). l k \| k ∈ Z and g k \| k ∈ Z are coefficients of a low-pass filter L ( ω ) and a high-pass filter G ( ω ), respectively, and, L ( ω ) = Σ k ∈ Z l k e - ikω , G ( ω ) = Σ k ∈ Zgk e - ikω . Based on the frequency analysis of the ECG characteristic waves [ 27 ], scale 2 j ( j = 1 to 4) are selected. For each experimental episode, its wavelet transform coefficient sets d 1 , d 2 , d 3 and d 4 corresponding to different scales 2 1 , 2 2 , 2 3 , 2 4 are computed. The Hurst index H is then computed according to Equation (9). Smaller Hurst index corresponds to larger fractal dimension and more irregular signal. Comparative Experimental Results and Discussions Description of the test data The database used in this study is the MIT-BIH malignant ventricular arrhythmia database [ 21 ] with a sample frequency of 250 Hz . Typical waveforms of VT and VF as well as NSR are shown in Figure 1 to 3 . Selected ECG episodes with different lengths are tested for evaluating the performance of the life-threatening ventricular arrhythmia recognition using the Hurst index. Each ECG episode is characterized by the Hurst index H , computed by Equation (9). The statistical distribution of the Hurst indexes for characterizing different types of episodes is studied so that VT and VF can be recognized in the feature domain of the Hurst index. Recognition performance is measured by Sensitivity ( SE ), Specificity ( SP ) and Accuracy ( ACR ). They are defined as: Sensitivity = ; Specificity = ; Accuracy = . Where TP is true positive, the abnormal case being correctly recognized as abnormal one; FN is false negative, the abnormal case being wrongly recognized as normal one; TN is true negative, the normal case being correctly recognized as normal one; and FP is false positive, the normal case being wrongly recognized as abnormal one. Lastly, results are compared with that of Complexity measure technique. Figure 1 Typical life-threatening ECG waveform of NSR Figure 2 Typical life-threatening ECG waveform of VT Figure 3 Typical life-threatening ECG waveform of VF In this study, about 5076 ECG episodes are tested for performance evaluation of life-threatening ventricular arrhythmia recognition using the proposed Hurst index. Among them, 2588 cases are NSR episodes, 1390 cases are VT episodes, and 1098 are VF episodes. In order to explore the effect of the time series lengths on the recognition performance using the proposed Hurst index, analyzing was conducted using different lengths of ECG episodes from 1 sec to 5.5 sec with a difference of 0.5 sec . For each length, the whole dataset was randomly divided into two equal parts for training and testing, respectively. From a clinical point of view, it is essential to recognize and diagnose malignant ventricular arrhythmia as soon as possible. This calls for detection with as short a length of the time series as possible. The statistical results, viz, the means and standard deviations for characterizing NSR, VT and VF episodes using the Hurst index are given in Table 1 . As a comparison, the results by the complexity measure technique, are given in Table 2 . Graphical descriptions of the results listed in Tables 1 and 2 are shown in Figure 4 and 5 respectively. Table 1 Statistical results of Hurst index for episode characterization Episode Length Hurst index NSR VT VF Mean SD Mean SD Mean SD 1 sec 0.6099 0.0981 0.8117 0.0775 0.8567 0.0579 1.5 sec 0.6206 0.0805 0.8269 0.0671 0.8597 0.0501 2 sec 0.6317 0.0619 0.8373 0.0558 0.8618 0.0438 2.5 sec 0.6349 0.0549 0.8398 0.0509 0.8682 0.0419 3 sec 0.6389 0.0458 0.8445 0.0409 0.8766 0.0399 3.5 sec 0.6389 0.0458 0.8445 0.0409 0.8766 0.0399 4 sec 0.6395 0.0436 0.8452 0.0403 0.8794 0.0395 4.5 sec 0.6398 0.04 0.8455 0.0397 0.8797 0.0392 5 sec 0.6399 0.035 0.8458 0.0391 0.8799 0.0387 5.5 sec 0.6399 0.035 0.8458 0.0388 0.8799 0.0386 Table 2 Statistical results of Hurst index for episode characterization Episode Length Complexity measure NSR VT VF Mean SD Mean SD Mean SD 1 sec 0.1674 0.0433 0.2775 0.0428 0.2798 0.0498 1.5 sec 0.1476 0.0403 0.2562 0.0428 0.2601 0.0498 2 sec 0.1319 0.037 0.2413 0.0335 0.2454 0.0432 2.5 sec 0.1245 0.0366 0.2311 0.0335 0.239 0.0432 3 sec 0.1192 0.0363 0.2229 0.0349 0.2351 0.037 3.5 sec 0.1129 0.0348 0.2168 0.0349 0.2298 0.037 4 sec 0.1095 0.0332 0.2149 0.0342 0.2242 0.0343 4.5 sec 0.1071 0.0321 0.2136 0.0342 0.2205 0.0343 5 sec 0.1056 0.0315 0.2129 0.0342 0.2187 0.0341 5.5 sec 0.1056 0.0313 0.2129 0.0339 0.2187 0.0341 Figure 4 The mean and standard deviation values for characterizing NSR, VT and VF episodes using the Hurst index Figure 5 The mean and standard deviation values for characterizing NSR, VT and VF episodes using the Complexity measure From the results shown in Figure 4 and 5 , the following observation can be made. • As the episode length increases, the mean of Hurst index for every type of rhythm basically increases and tends to approach a relatively stable value, while the standard deviation decreases gradually. • For a particular episode length, from NSR to VT then to VF, the corresponding Hurst index increases gradually. The increase from NSR to VT is more than the increase from VT to VF. • As the episode length increases, the mean of Complexity measure for every type of rhythm basically decreases and tends to approach a relatively stable value, while the standard deviation decreases gradually. • For a particular episode length, from NSR to VT then to VF, both the Hurst index and the Complexity measure increase gradually, in which, the increase from NSR to VF is far more than the increase from VT to VF. • The mean values of Hurst index vary slower than those of Complexity measure as the episode length increases from 1 sec to 5.5 sec . It is concluded that the Hurst index is more stable than the Complexity measure with respect to episode lengths. Using the Hurst index for VT or VF recognition from NSR with different episode lengths, there is no false detection, meaning that the VT/VF can be totally correctly recognized from NSR without exception. For the Complexity measure, when the length of ECG episode is longer than 1 sec , it has as good performance as the Hurst index; when the length of the ECG episode is 1 sec , there is 6 false negatives and 27 false positives; when the length of the ECG episode is 1.5 sec , there is 1 false negatives and 5 false positives. The statistical values of SE , SP and ACR for VT/VF recognition from NSR using the Hurst index are all 100%. Hence, the Hurst index can be used to detect VT and VT earlier. As for VF differentiation from VT, the statistical values of SE , SP and ACR for different episode lengths using the Hurst index and the Complexity measure, are shown in Table 3 . The computational time of the Hurst index and the Complexity measure for different ECG episode length are presented in Table 4 . From Table 3 , the following conclusions can be obtained: Table 3 Statistical values of SE , SP and ACR for VF differentiation from VT Episode Length Hurst index Complexity measure SE SP ACR SE SP ACR 1 sec 0.8351 0.8482 0.8424 0.8242 0.8302 0.8275 1.5 sec 0.8780 0.8698 0.8734 0.8689 0.8597 0.8637 2 sec 0.9080 0.8834 0.8942 0.9007 0.8798 0.8890 2.5 sec 0.9408 0.9158 0.9268 0.9381 0.9194 0.9277 3 sec 0.9608 0.9439 0.9513 0.9654 0.9489 0.9562 3.5 sec 0.9754 0.9669 0.9707 0.9818 0.9734 0.9771 4 sec 0.9854 0.9849 0.9851 0.9918 0.9885 0.9899 4.5 sec 0.9936 0.9914 0.9924 1 0.9986 0.9992 5 sec 1 0.9978 0.9988 1 1 1 5.5 sec 1 1 1 1 1 1 Table 4 Computation time comparison in seconds Length of episode Hurst index Complexity measure Length of episode Hurst index Complexity measure 1 sec 0.0546 0.0654 1.5 sec 0.0697 0.0824 2 sec 0.0794 0.1143 2.5 sec 0.0933 0.1538 3 sec 0.1168 0.2176 3.5 sec 0.1401 0.2991 4 sec 0.1885 0.4003 4.5 sec 0.2407 0.609 5 sec 0.2803 0.6833 5.5 sec 0.3122 0.7792 • The performance on differentiating VT and VF is worse than the performance of VT/VF recognition from NSR, for both the Hurst index and the Complexity measure. • The recognition performance by either descriptors improves as the length of ECG episode increases. • When the length of ECG episode is less than or equal to 2 sec , the recognition performance for the Hurst index is better. When the length of ECG episode is longer than 2 sec and less than 5 sec , the recognition performance for the Complexity measure is better. When the length of ECG episode is longer than 5 sec , VT and VF can be 100% differentiated with either descriptor, the recognition performance for both descriptors are same. According to Table 4 , the computational time for the Hurst index is less than that for the Complexity measure. These two algorithms are programmed using MATLAB 5.3 running on a SUN SPARC-333 MHz workstation. The computational burden for the Hurst index is O ( N log 2 N ), while the computational burden for the complexity is O ( N 2 ), where N is the length of ECG episode. It is noted that with more powerful computer programming in C, the computational speed will be further improved. Time is an important factor for saving lives in clinical situations, therefore, algorithm with less computational burden is obviously preferred. In addition, using short ECG episode length is preferred for earlier detection of arrhythmia (such as VT/VF). Based on the experimental results, it is observed that the Hurst index has a better potential for clinical adaptation than the Complexity measure. Conclusions In this paper, a new technique based on multiscale analysis and non-linear dynamics was presented for VT and VF recognition. Hurst index defined across multiscale was proposed for characterizing ECG episode so that life-threatening arrhythmia can be recognized. Furthermore, upon applying to the MIT-BIH malignant ventricular arrhythmia database, the performance for malignant arrhythmia recognition using Hurst index was compared with that using Zheng's complexity measure. The Hurst index requires less computation and is more reliable in detecting VT and VF with short ECG episode. There is strong potential for using the Hurst index for malignant ventricular arrhythmia recognition in clinical applications. Authors' contributions SY conceived the study, performed data analysis and drafted the manuscript. CKL and KSM guided the study, helped the analysis and interpretation of the results, and critically reviewed the manuscript. All authors read and approved the final script.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC549211.xml
548133	Effect of bradykinin on nitric oxide production, urea synthesis and viability of rat hepatocyte cultures	Background It is well known that cytotoxic factors, such as lipopolysaccharides, derange nitrogen metabolism in hepatocytes and nitric oxide (NO) is involved among the other factors regulating this metabolic pathway. Hepatocytes have been shown to express large levels of NO following exposure to endotoxins, such as bacterial lipopolysaccharide and/or cytokines, such as tumour necrosis factor-α (TNFα), interleukin-1. The control role of arginine in both urea and NO biosynthesis is well known, when NO is synthesized from arginine, by the NOS reaction, citrulline is produced. Thus, the urea cycle is bypassed by the NOS reaction. Many authors demonstrated in other cellular types, like cardiomyocytes, that bradykinin caused the increase in reactive oxygen species (ROS) generation. The simultaneous increase of NO and ROS levels could cause peroxynitrite synthesis, inducing damage and reducing cell viability. The aim of this research is to study the effect of bradykinin, a proinflammatory mediator, on cell viability and on urea production in cultures of rat hepatocytes. Results Hepatocytes were treated with bradykinin, that stimulates nitric oxide synthase (NOS). NO release was determined using 4,5 diaminofluorescein diacetate (DAF-2DA), as fluorescent indicator of NO. Addition of the NOS inhibitor, N g -nitro-L-arginine methyl ester (L-NAME), to the culture medium inhibited the increase of NO production. Exposure of hepatocytes to bradykinin 0,1 mM for 2 hours resulted in a significant decrease of urea synthesis. Cell viability, instead, showed a significant decrease 24 hours after the end of bradykinin treatment as determined by 3-(4,5-dimethyl-2-thiazolyl)-2,5diphenyl-2H-tetrazolium (MTT) assay. L-NAME addition recovered urea production and cell viability at control values. Conclusion The findings suggest that the cell toxicity, after bradykinin treatment, effectively depends upon exposure to increased NO levels and the effects are prevented by L-NAME. The results show also that the increased NO synthesis induces a reduced urea production, that is another index of cell damage.	Background It is well known that cytotoxic factors, such as lipopolysaccharides, derange nitrogen metabolism in hepatocytes and nitric oxide (NO) is involved among the other factors regulating this metabolic pathway [ 1 ]. NO is a free radical that is involved in many cellular events. In the biological systems NO has an halflife long lasting few seconds. It is an oxidation intermediate, therefore is both an oxidant and a reducing agent of metabolic products. Its biosynthesis is mainly performed by converting L-arginine to L-citrulline. L-arginine analogues, such as N g -nitro-L-arginine methyl ester (L-NAME), act as false substrates and are selective inhibitors of NO synthesis. NO synthase (NOS) is either a constitutive or inducible enzyme. The endothelial isoform (e-NOS) and the neuronal isoform (n-NOS) are constitutive. The inducible form of the enzyme (i-NOS), has the main property to be not regulated by intracellular calcium concentration and Ca 2+ -calmodulin complex, unlike the constitutive form [ 2 ]. It is known that iNOS is expressed by many cell types including macrophages, smooth muscle cells and hepatocytes [ 3 ]. Hepatocytes have been shown to express large levels of NO following exposure to endotoxins, such as bacterial lipopolysaccharide and/or cytokines, such as tumour necrosis factor-α (TNFα), interleukin-1 [ 4 , 5 ]. NO may posses both cytoprotective and cytotoxic properties, depending on the amount and the isoform of NOS by which it is produced [ 6 ]. NO generally mediates beneficial responses, but becomes deleterious when coexistence with enhanced superoxide formation leads to the synthesis of peroxynitrite, a potent oxidant and nitrating agent [ 7 ]. According to this hypothesis, authors studied the effect of bradykinin, a proinflammatory mediator kinin, on cell viability and on urea production in cultures of rat hepatocytes. Kinins exert numerous physiological and pathological actions; they partecipate in vascular and cellular events that accompany the inflammatory processes. In pathological states, kinins are thought to be implicated in inflammatory diseases and in haemorrhagic and endotoxic shock [ 8 ]. To demonstrate the decrease of cell viability and urea production by bradykinin, the authors studied its effects on NO production. The measurements of NO release from hepatocytes were investigated by using a NO-specific fluorescence indicator, 4,5 diaminofluorescein diacetate (DAF-2DA) [ 9 ]. Results Effect of bradykinin treatment on NO production The amounts of released NO were measured using DAF-2DA, that specifically reacts with the oxidized form of NO, producing the fluorescent triazolofluorescein [ 9 ]. NO determination was performed after 2 hours of incubation in the presence of bradykinin (0.01 mM and 0.1 mM). As shown in figure 1 the treatment with 0.01 mM bradykinin did not produce NO increase compared to control, but 0.1 mM bradykinin increased significantly the NO release. In contrast no appreciable NO release was observed during the same period in hepatocytes cultured with 0.1 mM bradykinin and 1.68 mM L-NAME. Effect of bradykinin treatment on urea production To evaluate urea synthesis after bradykinin treatment, the hepatocytes were treated with 1 mM NH 4 Cl for 2 h. Figure 2 shows that only the treatment with 0.1 mM bradykinin significantly decreased urea production and that the treatment with 0.1 mM bradykinin and 1.68 mM L-NAME did not produce a significant urea level decrease in comparison to control. Effect of bradykinin treatment on cell viability To determine the effects of bradykinin on cell viability, the hepatocytes were exposed to bradykinin (either 0.01 mM or 0.1 mM) for an incubation time of 2 hours. In one experimental series, the cell viability was determined by MTT test after 2 hours of incubation. In a second one, culture medium containing bradykinin was removed and replaced with the same fresh medium at 2 hours after the addition of bradykinin, and then cell viability was measured 24 hours after the end of bradykinin treatment. The MTT test after 2 hours of incubation does not indicate any significant viability difference in treated hepatocyte cultures in comparison to control (figure 3A ). By MTT test after 24 h (figure 3B ), a significant lowering of viability is observed in bradykinin 0.1 mM treated hepatocytes in comparison to control. The decrease was significantly reduced by the simultaneous treatment with L-NAME 1.68 mM even if always significantly lower than in control. Cell viability was validated by Trypan blue exclusion test (Table 1 ). Discussion The role of NO as mediator of hepatic injury after endotoxic shock remains controversial [ 16 ]. Increased NO production in response to cytokines has been demonstrated in cultured hepatocytes [ 17 ]. Laskin et al. [ 18 ] demonstrated that the induction of acute endotoxemia, caused an increase in NO production in the liver. This was associated with expression of inducible nitric oxide synthase (iNOS) messenger m-RNA in hepatocytes. Also our data showed an increase of NO production after 2 hours treatment of culture with 0.1 mM bradykinin in an arginine supplemented medium, as substrate for the synthesis of NO. The simultaneous treatment with L-NAME, a known inhibitor of NOS, blocked the increase of NO production. In this work we analyzed the urea synthesis after bradykinin treatment. Urea synthesis was decreased after 2 hours treatment with bradykinin 0.1 mM and the simultaneous treatment with L-NAME leaves urea biosynthesis unaltered. These data can be attributed to the control role of arginine in both urea and NO biosynthesis. When NO is synthesized from arginine, by the NOS reaction, cytrulline, an intermediate of urea cycle, is produced. Thus, the urea cycle is bypassed by the NOS reaction [ 1 ]. Whether NO exerts cytotoxic or cytoprotective action remains unclear [ 6 ]. We also found a significant decrease of viability, at long term, in hepatocytes subjected to bradykinin treatment. The simultaneous treatment of hepatocytes with L-NAME improves cell viability even if control levels are not restored. The data show that the increased NO production plays a role in liver damage induction, that follows the proinflammatory mediator treatment. The hepatocellular injury attributed to NO may be due either to its direct cytotoxicity or its reaction with superoxide to produce the toxic nitrogen metabolite peroxynitrite [ 19 ]. Oldenburg et al. [ 20 ], demonstrated in other cell types, like cardiomyocytes, that bradykinin caused the increase in reactive oxygen species (ROS) generation. At last, our results show that the increased NO synthesis induces a reduced urea production, that is an index of cell damage. The simultaneous treatment of liver cell cultures with L-NAME decreases NO levels and sustains overall biosynthesis activities and cell viability. Conclusions In summary, we conclude that 0.1 mM bradykinin treatment induces an increase of NO levels and reduction of urea synthesis in the hepatocytes. This increased NO production mediates, after 24 hours, cell toxicity as shown by MTT test. In contrast, the administration of the NOS inhibitor L-NAME protects against cell damage and increases urea levels, suggesting that NO plays a key role in the bradykinin-induced liver damage. Methods Materials Unless otherwise specified, all chemicals were obtained from Sigma (St. Louis, MO, USA). Isolation and culture of rat hepatocytes Hepatocytes were isolated from male rats, Wistar strain, (180 to 200 gbw), by a modification of the method of Seglen [ 10 ]. All procedures on the animals were performed according to the CEE directive n. 86/609 on animal experimentation. Rats were anesthetized with diethylether, the pre-perfusion of the liver in situ was performed at a rate of 20–30 ml/min with Ca 2+ -free Hanks balanced salt solution. The liver was then excised and the digestion was carried out by adding 0.05% (w/v) collagenase (type IV) in Hanks balanced salt solution supplemented with CaCl 2 ·H 2 O (0.0186 g/L) at a flux rate of 40 ml/min. At this point liver was transferred to a square plate containing 100 ml of RPMI 1640 medium supplemented with 200 mM L-glutamine, 20 ml/L essential amino acid solution and 10 ml/L non-essential amino acid solution, 1% antibiotic antimycotic stabilized solution and 100 μM L-arginine (incomplete medium). The cells were dispersed by gentle distruption with a stainless steel comb. After filtration through 200 μm Nytal mesh, parenchymal cells (hepatocytes) were separated from nonparenchymal cells (endothelial cells, Kupffer cells and stellate cells) by centrifugation at 50 g in Eppendorf Centrifuge 5810R at 4°C for 2 minutes and then washed twice in washing buffer [ 11 ]. Then the cells were resuspended in the same medium and filtered through 63 μm Nytal mesh. The viability of the cells was more than 80%, as estimated by trypan blue dye exclusion test [ 12 ]. After cell counting the cells were diluited at a concentration of 5 × 10 5 cells/ml with incomplete medium supplemented with 2% fetal calf serum, 0.1 U/ml insulin and 10 -6 M dexamethasone (complete medium). The hepatocytes were then plated in 24 well-plates coated with rat tail collagen at the final cell density of 2.5 × 10 5 cells per well and incubated at 37°C in an humidified atmosphere of 5% CO 2 and 95% air. After 6 hours incubation, the medium was changed and replaced with incomplete medium to remove dead cells. To verify the isolation method efficiency, the acid fosfatase activity per mg of proteins was evaluated. According to literature data, the specific activity of acid fosfatase in nonparenchimal cells is 1,7 folds the same activity in parenchimal cells [ 13 ]. Treatment After 24 hours of culture the hepatocytes were exposed either to bradykinin (0.01 mM and 0.1 mM) or bradykinin 0.1 mM supplemented with L-NAME 1.68 mM [ 14 ]. Determination of NO from hepatocytes DAF-2DA (Alexis Biochemicals, Lausen, Switzerland) was dissolved in DMSO (1 mg/0.45 ml) and diluted to 10 μM in phosphate buffer (0.1 M, pH 7.4). Then the cells were either incubated in phosphate buffer containing 10 μM DAF-2DA, bradykinin (0.01 mM and 0.1 mM) and bradykinin 0.1 mM supplemented with L-NAME 1.68 mM. After 2 hours of incubation in this reaction mixture, the fluorescence from the reaction of DAF-2DA with NO released from hepatocytes was measured with Perkin-Elmer MPF-44B Spectrofluorimeter calibrated for excitation at 495 nm and emission at 515 nm. Results were expressed as a percentage of the fluorescence of the samples in comparison to control. Determination of urea synthesis To determine the effects of bradykinin on urea production, cells were treated either with bradykinin (0.01 mM and 0.1 mM) and cotreated with bradykinin 0.1 mM and L-NAME 1.68 mM. At the same media 1 mM NH 4 Cl was added. After 2 hours urea levels in the media were measured by spectrophotometric method using Urea Color 2 Kit (Sclavo Diagnostics, Siena, Italia) measuring absorbance at 600 nm and blank sample with the same NH 4 Cl final concentration was used. Urea synthesis was calculated as ng urea per cell per hour. Determination of cell viability Cell viability was determined by MTT test method [ 15 ] and confirmed by Trypan blue exclusion test [ 12 ]. MTT (5 mg/ml) was dissolved in RPMI-1640 without phenol red. The solution is filtered through a 0.2 μm filter and stored at 2–8°C for frequent use. To determine the effects of bradykinin on cell viability, cells were either treated with bradykinin (0.01 mM and 0.1 mM) and cotreated with bradykinin 0.1 mM and L-NAME 1.68 mM for a 2 h period. After that cells were used either immediately or after an additional 24 h incubation period in incomplete medium. For the determination of cell viability, the medium has been discarded and MTT solution was added and incubated for 3 hours. At the end of the incubation period the MTT solution was removed and the cells and dye cristals were dissolved by adding dimethylsulfoxide (DMSO). Absorbance was measured at 570 nm in a Shimadzu UV-2100 Spectrophotometer and the results were expressed as a percentage of the absorbance of the samples in comparison to control. Statistical analysis At least four independent determinations of each parameter were compared to control using Student's T-test. Differences were considered significant when p < 0.05 was obtained. Authors' contributions SS: Fluorimetric analysis and overall statistical analysis of data MG: Director of research MS: Spectrophotometric analysis CR: Primary hepatocyte cultures and characterization All authors read and approved the final manuscript	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548133.xml
539251	Negative and positive childhood experiences across developmental periods in psychiatric patients with different diagnoses – an explorative study	Background A high frequency of childhood abuse has often been reported in adult psychiatric patients. The present survey explores the relationship between psychiatric diagnoses and positive and negative life events during childhood and adulthood in psychiatric samples. Methods A total of 192 patients with diagnoses of alcohol-related disorders (n = 45), schizophrenic disorders (n = 52), affective disorders (n = 54), and personality disorders (n = 41) completed a 42-item self-rating scale (Traumatic Antecedents Questionnaire, TAQ). The TAQ assesses personal positive experiences (competence and safety) and negative experiences (neglect, separation, secrets, emotional, physical and sexual abuse, trauma witnessing, other traumas, and alcohol and drugs abuse) during four developmental periods, beginning from early childhood to adulthood. Patients were recruited from four Psychiatric hospitals in Germany, Switzerland, and Romania; 63 subjects without any history of mental illness served as controls. Results The amount of positive experiences did not differ significantly among groups, except for safety scores that were lower in patients with personality disorders as compared to the other groups. On the other side, negative experiences appeared more frequently in patients than in controls. Emotional neglect and abuse were reported in patients more frequently than physical and sexual abuse, with negative experiences encountered more often in late childhood and adolescence than in early childhood. The patients with alcohol-related and personality disorders reported more negative events than the ones with schizophrenic and affective disorders. Conclusions The present findings add evidence to the relationship between retrospectively reported childhood experiences and psychiatric diagnoses, and emphasize the fact that a) emotional neglect and abuse are the most prominent negative experiences, b) adolescence is a more 'sensitive' period for negative experiences as compared to early childhood, and c) a high amount of reported emotional and physical abuse occurs in patients with alcohol-related and personality disorders respectively.	Background It is difficult to assess the impact of childhood traumatic events on the psychiatric disorders in adulthood, as neither prospective research studies, nor experimental approaches are possible. Nevertheless, an increasing number of retrospective reports suggest that psychiatric disorders may be related to childhood psychological traumas such as neglect, physical or emotional abuse [ 1 - 6 ]. In particular, significant correlations between the severity of psychiatric symptoms and that of stressful and traumatic experiences during childhood were found [ 7 - 12 ]. Reports of physical and sexual abuse in childhood are more frequent in psychiatric patients than in the healthy population [ 13 - 16 ]; among these are patients diagnosed with affective disorders [ 17 - 19 ], somatization disorders [ 20 - 22 ], borderline personality disorders [ 3 , 7 , 23 - 25 ], substance-related disorders [ 26 - 28 ], and schizophrenic disorders [ 29 - 31 ]. Specifically, several studies have documented high rates of trauma in individuals with severe mental illness [ 32 ]. For a sample of schizophrenic women, Friedmann and Harisson (1984) reported that 60% of them had suffered childhood sexual abuse [ 33 ]. Abused patients displayed more pronounced symptoms such as hallucinations [ 34 , 35 ] and delusions [ 36 ]. Any conclusion to such reports, however, must be drawn by taking into consideration that the validity of childhood memories, particularly in psychiatric patients, may be questioned, as the range of childhood traumas indexed in these studies is generally limited, and often only childhood sexual abuse is targeted. Moreover, the observed relationships are correlational in nature, and do not justify the conclusion that childhood trauma favors the development of psychiatric disorders. Antecedents of developing psychopathology may also provoke certain parental behavior. Also, a third variable, such as social conditions, may have caused both childhood abuse and later pathological development. Another notable finding is that the prevalence rates of antecedent traumatic events vary considerably across studies. This may be due to different definitions of abuse which include more detailed [ 13 ] or more global [ 23 ] descriptions. Furthermore, the amount of psychosocial elements such as neglect, family disturbance, the nature of preexisting and subsequent attachment patterns, special competencies, etc., is difficult to be assessed or taken into account. Only a limited number of studies [ 37 , 38 ] have so far included control groups, allowing one to compare self-reports of abusive sexual experiences during childhood in psychiatric patients to those in the healthy population. There is also a lack of research studies that assess these issues within different cultural backgrounds. The present study sets out to evaluate reported positive and negative life events from early childhood to adulthood in psychiatric patients. We addressed some of the above-mentioned problems by examining abuse histories across a range of several psychiatric diagnoses within a controlled cross-national design. We sought to examine whether (a) negative life experiences are positively associated with psychiatric diagnoses in adulthood, and (b) early childhood and adolescence were 'sensitive periods', that is, whether psychiatric diagnoses were more closely related to negative experience in these developmental periods. The present study includes a German/Swiss and a Romanian psychiatric group, in order to determine whether reports vary between cultural backgrounds. Methods Subjects Patients were recruited from four Psychiatric Hospitals within two different cultural settings, Switzerland/Southern Germany versus the Moldavia region in Romania: the Center for Psychiatry Reichenau and the Center for Psychiatry Weissenau in Germany, the Psychiatric Hospital Münsterlingen in Switzerland, and the Psychiatric Hospital "Socola", Jassy in Romania. A total of 192 psychiatric inpatients (98 German and 94 Romanian psychiatric patients, range 18–78 years) filled in the questionnaire. Sixty-three control subjects without any history of psychiatric diagnosis were recruited from the clinical staff and the university employees (Konstanz in Germany, Jassy in Romania) as controls (38 Germans and 25 Romanians). The control subjects have been simply inquired whether they had any stationary hospitalization in the psychiatry; no further assessments have been done. After a full explanation of the study, written informed consent was obtained from all subjects. By considering the clinician-made diagnoses which were written down from the medical files available in the psychiatric clinics the patients were recruited from, the patients were distributed in four diagnostic groups: alcohol-related disorders (n = 45), schizophrenic disorders (n = 52), affective disorders (n = 54), and personality disorders (n = 41). At all psychiatric clinics in Germany/Switzerland and Romania the diagnoses were made according to the ICD-10 criteria. Within our patient groups, the following lifetime mental disorders were assessed by using the ICD-10: alcohol-related disorders (dependence syndrome, psychotic and unspecified mental disorders due to the use of alcohol), schizophrenic disorders (paranoid schizophrenia, schizoaffective disorder, and undifferentiated schizophrenia), affective disorders (bipolar depressive disorders, recurrent depressive disorder, cyclothymia, and dysthymia), and personality disorders (borderline, schizoid, paranoid, histrionic, dissocial, and dependent personality disorder respectively). A few patients within our sample were diagnosed with comorbid symptoms: 4 patients with affective disorders had symptoms of substance abuse and 7 of them had anxiety symptoms; also, within the schizophrenic disorders group, 2 patients had symptoms of alcohol abuse and 6 had depressive symptoms. There were also patients who received two diagnoses: one of which was a personality disorder (i.e., 5 patients with affective disorders, 7 with alcohol-related disorders, and 2 with schizophrenic disorders). In these cases, we considered the other diagnosis for the distribution into the diagnostic groups. Table 1 summarizes the demographical characteristics of all subjects. The patient groups were similar with respect to the psychiatric history. There were differences among groups concerning gender distribution, age, and education. The gender-distribution differences among groups were due to the high number of women within the control and the affective disorders groups. With regard to the noted age differences, the patients with affective and alcohol-related disorders respectively had higher mean age as compared to all the other groups. The education differences among groups are only due to the lower educational level in patients with alcohol-related disorders. Romanian patients with affective disorders had a longer psychiatric history than the German/Swiss ones [t(51) = 2.3, p < 0.05]. Regarding gender distribution and the average duration of education, the German/Swiss and Romanian diagnostic groups were similar. The German/Swiss controls were significantly older than the Romanian ones [t(43) = 4.4, p < 0.001] and the German/Swiss patients with alcohol-related disorders were significantly younger than the Romanian ones [t(61) = 3.5, p < 0.001]. Table 1 Demographic characteristics of the control and of the patient groups 1, 2 Alcohol Related Disorders Schizophrenic Disorders Affective Disorders Personality Disorders Controls G/S R G/S R G/S R G/S R G/S R Analysis N N N N N χ 2 p Gender 12 <.05 Female 6 10 10 11 14 19 11 6 23 15 Male 14 15 18 13 10 11 15 9 15 10 Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD F p Age 31 ± 9 45 ± 12 34 ± 8 36 ± 10 40 ± 12 44 ± 8 34 ± 8 32 ± 11 38 ± 13 28 ± 7 6 <.001 Education 2 ± 1 2 ± 1 3 ± 1 3 ± 1 3 ± 1 3 ± 1 2 ± 1 3 ± 1 3 ± 1 3 ± 1 4 <.01 Psychiatric history (yrs) 6 ± 1 7 ± 10 8 ± 9 11 ± 10 4 ± 6 9 ± 9 4 ± 5 6 ± 7 - - 2 n.s. 1 Abbreviations: G/S: German/Swiss; R: Romanian; Education: 0 = no education, 1 = school for the mentally challenged, 3 = middle school, 4 = high school; 2 Areas where the values are written with bold characters indicate significant differences between German/Swiss and Romanian subjects within the diagnostic groups (i.e., alcohol-related disorders, schizophrenic disorders, affective disorders, personality disorders and control group respectively). Material Life experiences were assessed with the Traumatic Antecedents Questionnaire (TAQ) [ 40 ]. The TAQ is a 42-item self-rating questionnaire, which covers 11 subscales enquiring into the severity of positive (i.e., competence and safety) and negative experiences (i.e., neglect, separation, secrets, emotional abuse, physical abuse, sexual abuse, witnessing, other traumas, and alcohol and drugs) during four developmental periods (ages 0–6, 7–12 13–18, and ≥ 19). Each subscale includes 2–6 items. Each item requires the occurrence of a certain type of experience for each of the different age periods. The subjects were asked to score on a frequency/intensity scale the degree to which it describes their experience: 0 ("never or not at all"), 1 ("rarely or a little bit"), 2 ("occasionally or moderately"), 3 ("often or very much"), and DK ("don't know"). In a subsequent step, the average scores were calculated within each developmental period for each of the 11 subscales. The procedure we used was the following: first, the "don't know" responses were noted in a non-numerical manner, by using asterisks (*) to indicate missing values and these values were counted as 0; secondly, the response scores were added up and the sum was divided by the total number of items within the subscale in that age period for which there were numerical scores. By using this procedure, we excluded "don't know" responses from the total scores calculation. Data analysis Comparisons of demographic data were made with analysis of variance (ANOVA) and with two-tailed unpaired t-tests for continuous variables. Chi-square analysis was used to compare nominal data. The differences between groups were evaluated individually for each TAQ scale by repeated-measures ANOVA with the cultural background (German/Swiss versus Romanian), psychiatric status (alcohol-related disorders, schizophrenic disorders, affective disorders, personality disorders or controls), and gender (female versus male) as between-subjects factors, and developmental period (4 periods) as within-subjects factor. The probability level for rejecting the null hypothesis was set at P < 0.05. Post-hoc comparisons were carried out to evaluate main effects and interactions using Bonferroni/Dunn tests. A principal components analysis was also applied to the entire sample in order to identify those factors, which could account for individual variability across the eleven scales of the TAQ. The principal components were derived by using varimax rotation to orthogonalize solutions. Results Positive experiences Table 2 lists group mean scores on each of the two positive experiences scales. The patients generally exhibited lower mean scores on reported positive experiences as compared to the controls. The reported level of competence did not differ between diagnostic groups [F(4,198) = 0.8, n.s] or cultural samples [F(1,198) = 0.1, n.s]. A main effect of developmental period [F(3,594) = 25.7, P < 0.001] was explained by the increase of competence from early childhood to adolescence (P < 0.05), and by the decrease of competence in adulthood as compared to adolescence (P < 0.05). Table 2 Mean scores of positive experiences across developmental periods among all groups Positive Experiences and Age at Onset Alcohol Related Disorders Schizophrenic Disorders Affective Disorders Personality Disorders Control Group Analysis Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD F p Early Childhood (0–6) Competence 1.5 ± 0.9 1.9 ± 0.9 1.7 ± 1.0 1.7 ± 0.9 1.7 ± 0.1 0.7 n.s Safety 1.4 ± 0.8 1.7 ± 0.8 1.6 ± 0.8 1.2 ± 0.8 1.6 ± 0.7 3.2 <.05 Latency (7–12) Competence 2.1 ± 0.8 2.0 ± 0.8 2.1 ± 0.7 1.9 ± 0.8 2.1 ± 0.9 0.2 n.s Safety 1.8 ± 0.8 1.8 ± 0.8 1.9 ± 0.7 1.3 ± 0.7 1.9 ± 0.7 5.1 <.001 Adolescence (13–18) Competence 2.1 ± 0.9 2.1 ± 0.7 2.2 ± 0.6 2.1 ± 0.8 2.3 ± 0.8 0.6 n.s Safety 1.9 ± 0.8 1.7 ± 0.8 1.8 ± 0.8 1.3 ± 0.8 2.0 ± 0.8 4.0 <.01 Adulthood (≥19) Competence 1.9 ± 1.0 1.8 ± 0.8 2.1 ± 0.8 2.0 ± 0.8 2.2 ± 0.8 1.3 n.s Safety 1.7 ± 0.8 1.7 ± 0.8 1.7 ± 0.8 1.5 ± 0.7 2.1 ± 0.7 4.9 <.001 For both cultural samples, patients with personality disorders reported lower values on the safety subscale than any of the other groups [F(4,215) = 4.5, P < 0.01]. Post hoc tests showed that patients with personality disorders (P < 0.001) and those with affective disorders (P < 0.01) reported less such experiences as compared to the controls. The reported level of safety increased through adolescence [F(3,645) = 11.1, P < 0.001], but the interaction of the developmental period with the psychiatric status revealed a decrease in safety accounts from the age of 13–18 years towards adulthood in all patient groups [F(12,645) = 2.8, P < 0.001]. Negative experiences Table 3 shows the mean scores of traumatic experiences for all patient groups and for the control group across developmental periods. Negative experiences were more frequent in patients than in controls as indicated by significant main effects of the psychiatric status on each of the nine subscales. In addition, there was an important increase of amount of reported negative experiences across developmental periods. Table 3 Mean scores of negative experiences among all groups Negative Experiences and Age at Onset Alcohol Related Disorders Schizophrenic Disorders Affective Disorders Personality Disorders Control Group Analysis Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD F p Early Childhood (0–6) Neglect 0.6 ± 0.5 0.7 ± 0.7 0.5 ± 0.5 0.8 ± 0.6 0.2 ± 0.3 8.1 <.001 Separation 0.5 ± 0.6 0.4 ± 0.5 0.4 ± 0.6 0.6 ± 0.8 0.2 ± 0.4 3.9 <.01 Secrets 0.9 ± 0.9 1.2 ± 1.1 1.0 ± 0.9 1.4 ± 1.1 0.6 ± 0.7 4.8 <.01 Emotional Abuse 0.7 ± 0.6 1.0 ± 1.0 0.7 ± 0.8 1.2 ± 0.9 0.3 ± 0.5 8.2 <.001 Physical Abuse 0.4 ± 0.6 0.4 ± 0.5 0.3 ± 0.5 0.7 ± 0.7 0.1 ± 0.3 5.7 <.001 Sexual Abuse 0.0 ± 0.3 0.2 ± 0.6 0.1 ± 0.3 0.3 ± 0.6 0.1 ± 0.4 2.0 n.s. Trauma Witnessing 0.4 ± 0.5 0.4 ± 0.5 0.5 ± 0.6 0.7 ± 0.9 0.1 ± 0.2 7.6 <.001 Other Traumas 0.4 ± 0.5 0.3 ± 0.4 0.2 ± 0.4 0.4 ± 0.6 0.2 ± 0.3 3.1 <.05 Alcohol/Drug Abuse 0.4 ± 0.8 0.3 ± 0.6 0.5 ± 0.7 0.5 ± 0.7 0.1 ± 0.2 4.0 <.01 Latency (7–12) Neglect 0.7 ± 0.6 0.8 ± 0.7 0.7 ± 0.5 1.1 ± 0.8 0.5 ± 0.5 5.0 <.001 Separation 0.6 ± 0.7 0.5 ± 0.6 0.6 ± 0.7 0.9 ± 0.8 0.5 ± 0.6 2.8 <.05 Secrets 1.0 ± 0.9 1.2 ± 0.1 1.1 ± 0.9 1.6 ± 1.1 0.8 ± 0.8 4.2 <.01 Emotional Abuse 0.8 ± 0.6 1.1 ± 0.9 1.0 ± 0.8 1.4 ± 0.9 0.7 ± 0.8 4.6 <.01 Physical Abuse 0.5 ± 0.7 0.6 ± 0.7 0.6 ± 0.6 0.9 ± 0.8 0.5 ± 0.6 2.5 <.05 Sexual Abuse 0.1 ± 0.3 0.2 ± 0.5 0.1 ± 0.2 0.5 ± 0.8 0.1 ± 0.4 5.3 <.001 Trauma Witnessing 0.5 ± 0.6 0.5 ± 0.5 0.7 ± 0.6 0.9 ± 0.8 0.4 ± 0.5 5.5 <.001 Other Traumas 0.4 ± 0.5 0.4 ± 0.4 0.4 ± 0.5 0.5 ± 0.6 0.3 ± 0.4 1.4 n.s. Alcohol/Drug Abuse 0.5 ± 0.7 0.3 ± 0.6 0.6 ± 0.7 0.6 ± 0.8 0.2 ± 0.4 4.1 <.01 Adolescence (13–18) Neglect 1.0 ± 0.6 0.9 ± 0.7 1.0 ± 0.5 1.2 ± 0.7 0.8 ± 0.6 2.5 <.05 Separation 0.9 ± 0.8 0.8 ± 0.8 0.9 ± 0.7 0.9 ± 0.7 0.6 ± 0.7 2.4 <.05 Secrets 1.1 ± 0.9 1.3 ± 1.0 1.1 ± 0.9 1.5 ± 1.0 0.7 ± 0.8 4.7 <.01 Emotional Abuse 0.8 ± 0.6 1.3 ± 0.9 1.1 ± 0.7 1.4 ± 0.9 0.8 ± 0.8 4.6 <.01 Physical Abuse 0.8 ± 0.7 0.5 ± 0.6 0.5 ± 0.6 1.0 ± 0.9 0.5 ± 0.6 5.0 <.001 Sexual Abuse 0.2 ± 0.4 0.2 ± 0.4 0.2 ± 0.4 0.5 ± 0.8 0.1 ± 0.3 3.2 <.05 Trauma Witnessing 0.6 ± 0.6 0.5 ± 0.5 0.7 ± 0.6 1.0 ± 0.8 0.4 ± 0.5 5.9 <.001 Other Traumas 0.6 ± 0.6 0.5 ± 0.5 0.4 ± 0.5 0.6 ± 0.5 0.3 ± 0.3 3.4 <.05 Alcohol/Drug Abuse 1.1 ± 1.0 0.6 ± 0.8 0.7 ± 0.9 0.9 ± 0.8 0.4 ± 0.7 5.3 <.001 Adulthood (19≥) Neglect 1.4 ± 0.8 1.3 ± 0.9 1.2 ± 0.7 1.2 ± 0.8 0.9 ± 0.7 3.0 <.01 Separation 1.6 ± 0.7 1.1 ± 0.9 1.5 ± 0.8 1.2 ± 0.9 1.0 ± 0.7 4.3 <.01 Secrets 1.1 ± 1.0 1.3 ± 1.1 1.2 ± 0.9 1.6 ± 0.9 0.5 ± 0.7 8.1 <.001 Emotional Abuse 0.9 ± 0.7 1.2 ± 0.9 1.1 ± 0.9 1.4 ± 0.9 0.6 ± 0.6 6.8 <.001 Physical Abuse 1.0 ± 0.9 1.0 ± 0.8 0.9 ± 0.9 1.0 ± 0.9 0.4 ± 0.6 5.1 <.001 Sexual Abuse 0.3 ± 0.6 0.6 ± 0.8 0.4 ± 0.7 0.5 ± 0.7 0.2 ± 0.4 2.8 <.05 Trauma Witnessing 0.8 ± 0.6 0.7 ± 0.7 1.0 ± 0.8 1.0 ± 0.9 0.5 ± 0.4 4.3 <.01 Other Traumas 1.2 ± 0.6 1.0 ± 0.7 1.1 ± 0.8 1.0 ± 0.6 0.4 ± 0.4 14.8 <.001 Alcohol/Drug Abuse 2.1 ± 0.8 0.8 ± 0.9 1.1 ± 0.9 1.0 ± 0.9 0.3 ± 0.6 29.3 <.001 With respect to the experiences of neglect , the psychiatric patients reported higher rates than the controls [F(4,214) = 5.7, P < 0.001], the post hoc tests revealing that all patient groups reported more such experiences as compared to the controls: patients with personality disorders (P < 0.001), alcohol-related disorders (P < 0.05), schizophrenic disorders (P < 0.05), and affective disorders (P < 0.05). There was an increase of the amount of reported neglect experiences across developmental periods [F(3,642) = 91.5, P < 0.001]. Across developmental periods there were significant effects of the psychiatric status [F(12,642) = 3.2, P < 0.001]: the post hoc tests showed that patients with personality disorders (P < 0.001) and with alcohol-related disorders (P < 0.01) reported a highly significant increase of the amount of neglect experiences across developmental periods as compared to the controls (Figure 1 ). Figure 1 Mean neglect score across developmental periods among all groups. The psychiatric patients reported higher rates than the controls [F(4,214) = 5.7, P < 0.001]. There was an increase of the amount of reported neglect experiences across developmental periods [F(3,642) = 91.5, P < 0.001]. Error bars stand for standard error of the mean. Asterisks indicate significant main effects of the psychiatric status. Irrespective of the psychiatric status and developmental periods, Romanian subjects generally reported a higher amount of neglect experiences, as shown by the main effect of the cultural background [F(1,214) = 6.4, P < 0.05]. Romanian patients, particularly those with schizophrenic disorders, reported a higher incidence of neglect experiences than their German counterparts (P < 0.01), as revealed by the interaction between the psychiatric status and cultural background [F(4,214) = 5.6, P < 0.001]. As indicated by the interaction between the developmental period and the cultural background, the mean scores of neglect experiences were higher in the Romanian sample as compared to the German/Swiss one for the earliest (0–6 years) period [F(3,642) = 5.3, P < 0.001]. Separation Patients, particularly those with alcohol-related disorders, personality disorders, and affective disorders reported more often separation experiences than controls [F(4,227) = 3.3, P < 0.01, P < 0.01 for post-hocs]. Mean scores on separation increased with age, and were highest in adulthood [F(3,681) = 103.0, P < 0.001]. Secrets Higher patient mean scores were confirmed by the main effect of the psychiatric status [F(4,182) = 6.8, P < 0.001], especially for those with personality disorders (P < 0.001) and with schizophrenic disorders (P < 0.001), as revealed by post-hoc tests. There was also an indication of sensitivity to the cultural background [F(1,182) = 7.5, P < 0.01], as there was an increase in these scores in the Romanian sample, irrespective of the diagnosis and developmental period. Emotional abuse was more frequently reported by patients than by controls [F(4,194) = 7.0, P < 0.001] and more frequently by patients with personality disorders (P < 0.01) and by schizophrenic patients (P < 0.05) than the ones with a history of alcohol-related disorders (Figure 2 ). A main effect of the developmental period [F(3,582) = 24.0, P < 0.001] was explained by an increase of the reported emotional abuse from early childhood to adolescence (P <0.05), and a decrease in adulthood (P < 0.05) were noted. Similar to the case of the neglect experiences, the Romanian sample scored also higher than the German/Swiss sample, mainly for the earliest (0–6 yr.) period, as revealed by the interaction between the development period and the cultural background [F(3,582) = 5.4, P < 0.01]. Figure 2 Mean emotional abuse score across developmental periods among all groups. Emotional abuse was more frequently reported by patients than by controls [F(4,194) = 7.0, p < 0.001]. A main effect of the developmental period [F(3,582) = 24.0, P < 0.001] was explained by an increase of the reported emotional abuse from early childhood to adolescence, and a decrease in adulthood were noted. Error bars stand for standard error of the mean. Asterisks indicate significant main effects of the psychiatric status. Irrespective of the developmental period, physical abuse was more often reported by patients with personality disorders [F(4,202) = 5.7, P < 0.001] (Figure 3 ). Post-hoc comparisons also revealed higher rates of physical abuse reports among patients with alcohol-related disorders (P < 0.01) and with schizophrenic disorders (P < 0.05) than among controls. The reports of physical abuse generally increased across developmental periods, with adulthood as the most susceptible period of such reports [F(3, 606) = 35.1, P < 0.001]. The interaction of the developmental period with the psychiatric status showed that this increase in physical abuse reports across developmental periods was mainly to be remarked in patients [F(12,606) = 3.0, P < 0.001]. Figure 3 Mean physical abuse score across developmental periods among all groups. Physical abuse was more often reported by patients with personality disorders [F(4,202) = 5.7, P < 0.001]. The reports of physical abuse generally increased across developmental periods, with adulthood as the most susceptible period of such reports [F(3, 606) = 35.1, P < 0.001]. Error bars stand for standard error of the mean. Asterisks indicate significant main effects of the psychiatric status. Sexual abuse (Figure 4 ) was primarily reported by patients, and not by controls [F(4,205) = 5.2, P < 0.001], and particularly by patients with personality disorders (P < 0.001). Higher rates of sexual abuse were reported among patients with alcohol-related disorders (P < 0.01), with schizophrenic disorders (P < 0.05), and with affective disorders (P < 0.05) than among controls as shown by post-hoc tests. If sexual abuse was experienced, it occurred particularly in later developmental periods [F(3,615) = 20.4, P < 0.001]. Sexual abuse was more often experienced by female patients [F(1,205) = 10.0, P < 0.001] after puberty [F(3, 615) = 10.0, P < 0.001], as revealed by the interaction between the developmental period and gender. We also found a 3-way interaction between the developmental period, psychiatric status and cultural background [F(12,615) = 2.6, P < 0.01). The interaction between the developmental period and cultural background revealed that Romanian but not German/Swiss schizophrenics reported more frequently sexual abuse particularly in adulthood [F(3,615) = 5.0, P < 0.01]. Figure 4 Mean sexual abuse score across developmental periods among all groups. Sexual abuse was primarily reported by patients, and not by controls, and particularly by patients with personality disorders [F(4,205) = 5.2, P < 0.001]. If sexual abuse was experienced, it occurred particularly in later developmental periods [F(3,615) = 20.4, P < 0.001]. Error bars stand for standard error of the mean. Asterisks indicate significant main effects of the psychiatric status. Trauma witnessing was reported most often by patients with personality disorders as compared to all other groups [F(4,209) = 8.0, P < 0.001]. Post-hoc tests showed that patients with affective disorders (P < 0.01) and with alcohol-related disorders (P < 0.05) also reported more experiences of trauma witnessing than the controls. Irrespective of the diagnosis, Romanian patients, but not controls, reported higher mean scores on this variable and more often than their German/Swiss counterparts [F(1,209) = 17.0, P < 0.001]. The interaction between the cultural background and developmental period indicated in the Romanian sample an increase of trauma witnessing in adulthood [F(3,627) = 8.0, P < 0.001]. Other traumas Similar to the pattern of trauma witnessing, all patients reported a greater number of traumatic events than the control group [F(4,211) = 8.0, P < 0.001]: alcohol-related disorders (P < 0.001), personality disorders (P < 0.001), schizophrenic disorders (P < 0.01), and affective disorders (P < 0.01), as explained by post-hocs. An increase in the amount of other traumas reports across the developmental periods with highest values in adulthood for all patient groups [F(12, 633) = 7.0, P < 0.001] was also revealed. Alcohol and drug abuse As previously expected, patients treated for alcohol-related disorders reported more alcohol and drug abuse than all the other groups [F(4,213) = 12.3, P < 0.001]. The post-hoc tests showed that the other patient groups also reported more alcohol and drug abuse when compared to the control group: affective disorders (P < 0.001), personality disorders, (P < 0.001) and schizophrenic disorders (P < 0.05). As also anticipated, abuse increased across developmental periods until adulthood [F(3,639) = 110.0, P < 0.001], particularly in patients with alcohol-related disorders, as revealed by the interaction between the developmental period and psychiatric status [F(12,639) = 14.3, P < 0.001]. Irrespective of the diagnosis, Romanian patients, but not controls, showed higher mean scores on reporting alcohol and drug abuse than their German/Swiss counterparts [F(4,213) = 3.4, P < 0.01], as shown by the interaction between the psychiatric status and cultural background. Compared to the German group, alcohol and drug abuse in the Romanian sample was higher, particularly in adulthood [F(3,639) = 9.8, P < 0.001]. Interrelations A principal components factor analysis was performed to explore interrelationships among TAQ subscales. The results of this analysis indicated that the most appropriate solution involved five factors that jointly accounted for 56.2% of the total variance in the dataset. Table 4 summarizes the results of the varimax rotation for the five-factor solution. The first factor showed high positive loadings on physical abuse , sexual abuse , trauma witnessing , and other traumas , obviously explains the traumatic experiences. The second factor showed high positive loadings on competence and safety , apparently accounting for variance attributed to positive experiences. The third factor showed high positive loadings on the first year of illness with alcohol and drug abuse . The fourth factor, consisting of separation , evidently explains disruptions of attachment. The fifth factor, which included secrets and emotional abuse , appeared to account for family chaos. Thus, the structure of the study instrument was well reproduced for the present sample, which included different psychiatric diagnoses and different cultural backgrounds. Table 4 Varimax solution with five factors for negative and positive childhood experiences across developmental periods in psychiatric patients with different diagnoses 1 Factor Loading 2 Variables FACTOR 1: Traumatic Experiences 3 FACTOR 2: Positive Experiences 4 FACTOR 3: Vulnerability to Alcohol Abuse 5 FACTOR 4: Disruptions of Attachment 6 FACTOR 5: Family Chaos 7 Competence -0.0 0.8 0.2 0.1 0.1 Safety 0.2 0.8 -0.0 0.0 -0.2 Neglect 0.2 -0.3 0.1 -0.0 0.3 Separation 0.4 0.2 -0.0 0.8 0.1 Secrets -0.0 -0.1 -0.0 0.1 0.7 Emotional Abuse 0.2 0.0 0.6 -0.0 0.6 Physical Abuse 0.7 -0.0 -0.0 0.0 0.0 Sexual Abuse 0.4 0.0 0.0 -0.6 0.1 Witnessing 0.6 0.0 -0.0 0.0 0.2 Other Traumas 0.6 0.2 0.1 0.2 0.1 Alcohol & Drug Abuse 0.4 -0.2 0.5 0.0 -0.3 First Year of Illness -0.1 0.1 0.8 -0.1 0.2 1 Total percent of variance = 56.2% 2 Shaded areas indicate specific domains of the TAQ contributing to each factor 3 Eigenvalue = 4.88; percent of variance = 40.7% 4 Eigenvalue = 1.476; percent of variance = 12.3% 5 Eigenvalue = 1.013; percent of variance = 8.4% 6 Eigenvalue = 0.835; percent of variance = 7.0% 7 Eigenvalue = 0.815; percent of variance = 6.8% Discussion The study aimed at exploring whether psychiatric diagnoses, e.g. alcohol-related disorders, schizophrenic disorders, affective disorders, and personality disorders are related to retrospectively reported positive and negative life events across developmental periods, and if so, whether special developmental periods are characterized by more negative experiences than others. Our findings demonstrate a strong association between reports of traumatic events and certain psychiatric disorders. In other studies, negative experiences were reported by individuals with diagnoses such as affective disorders [ 18 , 41 ] and schizophrenic disorders [ 42 , 43 ], but these experiences were less common and cumulatively less severe. Negative experiences were particularly prominent in patients with personality disorders [ 24 , 25 , 44 ] and in patients with substance-related disorders [ 26 , 45 , 46 ]. Negative experiences were reported more often in late childhood and adolescence than in early childhood and adulthood. Previous studies indicated that the earlier onset of abuse was associated with greater severity and longer duration of mental problems [ 2 , 10 , 45 , 47 ]. If the present findings are consistent with some prior studies [ 5 , 9 , 16 ] in that they indicate a relationship between physical and sexual abuse and psychiatric disorders, they do not support the view expressed by Van der Kolk et al. about early abuse at an early stage of development [ 48 ]. The current investigation showed that many psychiatric patients had terrible histories of childhood physical and/or sexual abuse. This finding was marginally significant for the childhood sexual abuse histories and must therefore be interpreted with caution. However, one should keep in mind that self-report questionnaires depend heavily upon conscious retrieval capacity for autobiographic events. It is conceivable that in the current group of patients, early abuse events were less remembered as compared to abuse events experienced later in childhood. An advantage of the TAQ used in the present study is the assessment of negative experiences during both childhood and adulthood, while most of the other studies have so far focused primarily on the impact of childhood abuse, except Cascardi et al. [ 49 ] and Goodman et al. [ 32 ]. Another advantage of the TAQ is that it addresses the issue of neglect [ 50 ]. Given the sample of patients with different psychiatric diagnoses, this replicates Van der Kolk's et al. notion that patients who experience neglect early in their lives develop serious problems with affect regulation [ 51 ]. The present data add to the evidence, suggesting that neglect, emotional and physical abuse are experienced by many psychiatric patients [ 52 , 53 ]. This implies that although childhood traumas may contribute to a mental disorder in adulthood, the lack of secure attachments maintains it. Although emotional neglect has received less attention, perceived emotional rejection by parents has been associated with alcohol abuse [ 54 ] and delinquency [ 55 ] during adolescence and adulthood. Early emotional injuries could possibly trigger vulnerability to noxious experiences. Furthermore, experiences of parental loss or separation were prominent in adulthood especially for the patients with alcohol-related disorders and with affective disorders. The high incidence of such negative experiences during this period in the patients with alcohol-related disorders could be, at the same time, a direct consequence of the behavioral deviance of these individuals and contribute to the maintenance of alcohol abuse. Limitations of the study The present data has to be considered in the light of several possible limitations. First, the information obtained by self-report and without external evidence could be less reliable and valid, especially if we take into account the sensitive nature of this research. Herman and Schatzow, however, provide empirical support for the validity of abused patients' self-reports as well [ 56 ]. They found that when corroborating evidence is sought, the majority of women are able to obtain confirmation of abuse. No independent corroborating evidence was sought for any self-reported case of childhood negative experiences. Therefore, the validity of abuse reports cannot be assured. Recall may be biased, but there is no evidence that psychiatric patients are more likely to lie about or imagine child abuse [ 57 , 58 ]. There is some evidence, however, that "patients are biased to underreport abuse histories rather than to over report them" [ 59 ]. There were some "don't know" subject answers regarding abuse/neglect experiences, most of them in the early childhood. Most probably, the patients had difficulties recalling experiences that occurred at a very young age rather than trying to evade giving a positive answer. Furthermore, another methodological limitation in this study is that measuring neglect/emotional abuse in early childhood is particularly difficult as the awareness of it necessitates the development of a degree of differentiation and autonomy, which is seldom the case with psychiatric patients. Both individual interviews and self-report questionnaire methods present higher figures than chart reviews do, indicating that patients usually do not spontaneously offer such information to their therapists. When offered, the information is not reliably documented [ 57 ]. However, the data from our ongoing study in patients with personality disorders suggest that reports on events in general and physical abuse events in particular are highly stable across two measurement periods of time separated by 24 months. We also note that our sample consisted of psychiatric inpatients, and thus may not be representative of the broader population of patients with these disorders. The clinical validity of the TAQ has also been criticized [ 60 ]. The questionnaire is meant to be an applied clinically oriented measure, which has not yet been proved to be a psychometrically sound research instrument. This issue should be addressed in future studies using both convergent and divergent instruments. Romanian patients diagnosed with schizophrenic disorders differed significantly, with respect to the number of negative events, as compared to their German counterparts. One factor accounting for this difference might be the stressful environment during the former Ceausescu regime in Romania. During this 25-year period violations of human rights, terror, and corruption prevailed [ 61 , 62 ]. This result may also be due to the different diagnostic procedures used by Romanian and German/Swiss clinicians. Reports of higher rates of psychotic-like or specifically schizophrenic symptoms do not necessarily imply a diagnosis of schizophrenia. Once abuse is identified, a change of diagnosis, from schizophrenia to PTSD, is often made, with significant advantages for the individuals [ 30 ]. Conclusions The present study demonstrates an association between negative life events in childhood and psychiatric diagnoses in adult life, which is in line with a number of other studies [ 6 , 63 ]. Unlike previous reports [ 3 , 64 ], we found that psychiatric patients were more likely to report more negative life events during late childhood and adolescence rather than during early childhood and adulthood. These conclusions corroborate with one of the central hypothesis of life-span psychotraumatology, that is, adolescence is an extremely critical phase in the development of later psychopathology [ 65 , 66 ]. However, in line with findings offered by earlier controlled studies [ 37 , 38 ], psychiatric patients were more likely to report higher rates of negative life events during childhood than controls did. Although one cannot assume a direct causal relationship between childhood abuse and adult psychopathology from the present data, the present study provides further preliminary and explorative evidence for the high load of negative life events in psychiatric patients. An advantage of this study is the examination of the abuse histories across a range of four psychiatric diagnoses within a controlled comparison design. Our findings are important and clinically highly relevant for further etiological research of causal and maintenance factors of psychiatric symptomatic, as well as for the research on the treatment of these conditions. The special value of the study lies in its cross-national comparison from a clinical psychological point of view including a highly underresearched country like Romania. More attention should be paid to the sad situation of the patients in Romania who are often under inadequate pharmacological and insufficient psychotherapeutic treatment, as well as under inappropriate hospitalization conditions. Further research should concentrate on the epidemiology and developmental psychopathology of psychiatric populations in other countries than the usually researched ones. Generally, reports of traumatic experiences during the whole lifespan should be more carefully considered in the clinical diagnosis process and in the development of treatment programs for the psychiatric patients. Competing interests The author(s) declare that they have no competing interests. Authors' contributions ES carried out the study in Germany, performed the statistical analysis and drafted the manuscript. DB carried out the study in Romania and drafted the manuscript. BR conceived of the study and drafted the manuscript. FN participated in the design of the study. MS participated in the design of the study. KS participated in the coordination of the study. KH participated in the coordination of the study. TE conceived of the study and drafted the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539251.xml
539047	Finding Cures for Tropical Diseases: Is Open Source an Answer?	The Tropical Disease Initiative will be a Web-based, community- wide effort where scientists from the public and private sectors join together to discover new treatments	Only about 1% of newly developed drugs are for tropical diseases, such as African sleeping sickness, dengue fever, and leishmaniasis [1] . While patent incentives and commercial pharmaceutical houses have made Western health care the envy of the world, the commercial model only works if companies can sell enough patented products to cover their research and development (R&D) costs. The model fails in the developing world, where few patients can afford to pay patented prices for drugs. It is easy and correct to say that Western governments could solve this problem by paying existing institutions to focus on cures for tropical diseases. But sadly, there does not appear to be enough political will for this to happen. In any case, grants and patent incentives were never designed with tropical diseases in mind. Two main kinds of proposals have been suggested for tackling the problem. The first is to ask sponsors—governments and charities—to subsidize developing-country purchases at a guaranteed price [ 2 , 3 , 4 ]. The second involves charities creating nonprofit venture-capital firms (“Virtual Pharmas”), which look for promising drug candidates and then push drug development through contracts with corporate partners. In this article, we discuss the limitations of these two approaches and suggest a third, “open source,” approach to drug development, called the Tropical Diseases Initiative (TDI). We envisage TDI as a decentralized, Web-based, community-wide effort where scientists from laboratories, universities, institutes, and corporations could work together for a common cause (see www.tropicaldisease.org ). Why Open Source? The idea behind asking sponsors to subsidize developing country purchases at a guaranteed price is that this will prop up drug prices and restore incentives for developing new drugs [ 2 , 3 , 4 ]. In other words, it is a way of fixing the patent problem. However, subsidies have an important weakness: it is almost impossible to determine correctly how large the subsidy should be. In principle, the most cost-effective solution is to set a subsidy that just covers expected R&D costs. But how large is that? R&D costs are very poorly known, with the published estimates quoting uncertainties exceeding $100 to $500 million per drug. If the subsidy is set too low, companies cannot cover their R&D costs and nothing will happen. Set the subsidy too high, and the sponsor's costs skyrocket. To date, no sponsor has tried to implement these proposals. In the “Virtual Pharma” approach, governments and philanthropies fund organizations that identify and help support the most promising private and academic research. Examples include the Institute for One World Health ( www.iowh.org ), a not-for-profit pharmaceutical company funded mainly through private sources and the Gates Foundation, and the Drugs for Neglected Diseases Initiative ( www.dndi.org ), a public sector not-for-profit organization designed to mobilize resources for R&D on new drugs for neglected diseases. Virtual Pharmas have clearly started to bear fruit, and are responsible for most candidate treatments for tropical diseases currently under development. For example, the Drugs for Neglected Diseases Initiative has a portfolio of nine projects spread out across the drug development pipeline for the treatment of leishmaniasis, sleeping sickness, Chagas disease, and malaria [6] . But Virtual Pharmas face three important problems. The first is similar to the problem faced by subsidy proposals: guessing private-sector R&D costs. One needs to understand what a product costs in order to negotiate the best possible price—and guessing wrong is likely to be expensive. Second, Virtual Pharma's development pipelines will run dry without more upstream research. Research has been particularly weak in exploiting genomic insights [7] . Third, tropical disease research is badly underfunded. For this reason, Virtual Pharma cannot succeed without rigid cost containment. We believe that a new, community-wide consortium, the Tropical Disease Initiative, can help solve these problems. Its success would help keep Virtual Pharma's R&D pipeline full. Furthermore, it would use open-source licenses to keep its discoveries freely available to researchers and—eventually—manufacturers. As we explain below, well-designed open-source licenses are the key to containing Virtual Pharmas' R&D costs. While we expect the final choice of license to be made by TDI's members, the guiding principle should be to pick whatever license lets developing country patients derive the most benefit from TDI's work. Possible choices are shown in Box 1 . Box 1. Possible Licenses for TDI Discoveries A public-domain license that permits anyone to use the information for any purpose. Licenses similar to the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0 ) that permit anyone to use the information for any purpose, provided proper attribution is given. Licenses such as the General Public License ( www.opensource.org/licenses/gpl-license.php ) that prohibit users from seeking intellectual property rights. Licenses that permit commercial companies to obtain and exploit patents outside the developing world. These would allow Virtual Pharma to stretch its own R&D funds by letting corporate partners sell patented products to ecotourists, governments, and other consumers living in the industrialized world. How It Works To date, open-source methods have made little headway beyond software [8] . However, computing and computational biology are converging. In the same way that programmers find bugs and write patches, biologists look for proteins (“targets”) and select chemicals (“drug candidates”) that bind to them and affect their behavior in desirable ways. In both cases, research consists of finding and fixing tiny problems hidden in an ocean of code. What would open-source drug discovery look like? As with current software collaborations, we propose a Web site where volunteers use a variety of computer programs, databases, and computing hardware ( Figure 1 ). Individual pages would host tasks like searching for new protein targets, finding chemicals to attack known targets, and posting data from related chemistry and biology experiments. Volunteers could use chat rooms and bulletin boards to announce discoveries and debate future research directions. Over time, the most dedicated and proficient volunteers would become leaders. Figure 1 The TDI Model of Online Collaboration Ten years ago, TDI would not have been feasible. The difference today is the vastly greater size and variety of chemical, biological, and medical databases; new software; and more powerful computers. Researchers can now identify promising protein targets and small sets of chemicals, including good lead compounds, using computation alone. For example, a SARS protein similar to mRNA cap-1 methyltransferases—a class of proteins with available inhibitors—was recently identified by scanning proteins encoded by the SARS genome against proteins of known structure [9] . This discovery provides an important new target for future experimental validation and iterative lead optimization. More generally, existing projects such as the University of California at San Francisco's Tropical Disease Research Unit (San Francisco, California, United States) show that even relatively modest computing, chemistry, and biology resources can deliver compounds suitable for clinical trials [10] . Increases in computing power and improved computational tools will make these methods even more powerful in the future. Just as they do today, Virtual Pharmas would choose the best candidates. The difference is that open-source drugs could not be patented in developing countries. This would not stop Virtual Pharma from developing promising discoveries. (S. Nwaka, V. Hale, personal communications). Importantly, TDI would be a great boost to the efforts of Virtual Pharmas, because it would help to contain the costs of discovering, developing, and manufacturing drugs. Cost Containment TDI would contain costs in three important ways. First, TDI would ask volunteers to donate their time (and any patentable discoveries) to the collaboration. Instead of financial incentives, TDI would offer volunteers non-monetary rewards, such as ideological satisfaction, the acquisition of new skills, enhancement of professional reputation, and the ability to advertise one's skills to potential employers. Software collaborations have demonstrated that these incentives are a good way to attract and motivate programmers [11] . Similar incentives should work equally well for biologists, chemists, and other scientists. Second, we have already pointed out that existing proposals have difficulty containing costs. The root cause is patents. Normally, society relies on competition to keep prices low. Patents—by design—short-circuit competition by giving the owners the legal right to prevent others from using (or even developing) their invention. TDI, on the other hand, would restore competition by making drug candidates available to anyone who wanted to develop them. We expect sponsors to exploit this advantage by signing development contracts with whichever company offers the lowest bid. Such competitive bidding is a powerful way to contain costs, and is also a good way to develop drugs. Virtual Pharma has extensive experience supervising contract research. Third, the absence of patents would continue to keep prices low once drugs reached the market. The generic drug industry shows what happens once drug makers are allowed to compete. US drugs frequently fall to about one-third their original price when patents expire [12] . Intellectual Property Rights Would universities and corporations really let their people volunteer? Won't they insist on intellectual property rights? The practical answer is that sensible managers do not care about intellectual property rights unless they expect to earn a profit. This explains why sophisticated university licensing offices seldom bother to interfere with open-source software projects that are not commercially valuable [13] . The same logic would apply to open-source drug discovery. We would hope that life sciences companies would make a similar calculation. But permitting employees to participate is only the beginning. We think that universities and companies will also donate the data, research tools, and other resources needed to make TDI even stronger. The reason, once again, is that they have little to lose. The value of their intellectual property depends almost entirely on US and European diseases. For this reason, it costs very little to share their information with tropical disease researchers. In fact, drug companies already do this [14] . TDI's main challenge will be to show donors that an open-source project can keep members from diverting donated information back into the commercially lucrative diseases that affect patients in the West. Finally, there are precedents for private companies developing drugs off patent. During the 1950s, March of Dimes (see www.marchofdimes.com ) developed polio vaccines without any patents at all [15] . It then signed guaranteed purchase contracts with any drug maker willing to develop commercial-scale production methods. The incentive may not have been conventional, but it worked. And why not? The contracts made good business sense: contract profits may have been small compared to the profits on patented drugs, but so was the risk. Fifty years later, contract research still makes sense. Generic drug companies, developing world drug manufacturers, contract research organizations, and biotech firms have all said that they would consider contracts to develop open-source drug candidates. (M. Spino, S. Sharma, F. Hijek, and D. Francis, personal communications). Next Steps So far, we have described a shoestring operation that exists mainly on the Web. Except for computer time, budgets would be more or less the same as existing software collaborations. Computing would be expensive but manageable. Today's biologists routinely scrounge resources from university machines or borrow time on home computers [ 16 , 17 ]. This Web-centric approach would be a good start, but not a complete solution. Computational biology works best when it can interact with experimental chemistry and biology. Nevertheless, a low-budget computational approach is probably enough to generate new science, suggest ideas for follow-up experiments, and make new drug candidates available under licenses designed to yield maximum benefit to the developing world. In practice, an open-source drug discovery effort is likely to include modest experiments. Many academic scientists control discretionary resources and, in some cases, tropical disease grants. Furthermore, good science generates its own funding. We expect experimentalists to turn the collaboration's Web pages into grant proposals. That said, TDI's volunteers will be most productive if sponsors back them. Charities could support open-source drug discovery by making wet chemistry and biology experiments a top priority. Corporations could also help by donating funds, laboratory time, or previously unpublished results. One low cost/high value option would be for companies that have already tried a particular research direction to warn TDI if the collaboration was about to investigate a known dead end. (R. Altman, personal communication) Conclusion Open-source drug discovery is feasible—that is, no known scientific or economic barrier bars the way. But what are the risks? Experience with software collaborations highlights the main social and economic challenges. First, the project will have to find and motivate volunteers. Based on existing software collaborations, we estimate a required minimum “critical mass” of a few dozen active members. Second, modest chemistry and biology experiments will be needed to increase the chances for success. Resources of several hundred thousand dollars per year—mostly in the form of in-kind donations of databases, laboratory access, and computing time—would make open-source drug discovery much more powerful. By most standards, such risks are real but acceptable. The largest uncertainties are scientific. Can a volunteer effort based on computational biology and modest experiments produce the high-quality drug candidates that Virtual Pharma needs? A successful program must (1) make a significant contribution toward supplying the genomic insights that tropical disease research needs to move forward, and (2) make useful drug candidates available for development and production under open-source licenses. Open-source drug discovery looks feasible. The only way to be sure is to do the experiment—and we invite you to join us. To learn more about TDI or to volunteer, go to http://www.tropicaldisease.org	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539047.xml
529268	A high prevalence of cumulative trauma disorders in Iranian instrumentalists	Background Cumulative trauma disorders (CTDs) are common in musicians and their prevalence has been the subject of a number of studies in most western countries. Such studies are scarce in developing countries despite the possibility that CTDs may have a different prevalence in these countries, especially when considering traditional musical instruments and different methods of playing. Although not formally studied before, according to our experience the prevalence of CTDs seemed to be high among Iranian instrumentalists. We proposed this study to determine the prevalence of CTDs in amateur music students playing one of the two traditional Iranian instruments: Daf and Setar. Methods In a prospective cross sectional study, we interviewed and examined the students of three music training centers in Iran. Seventy eight instrumentalists, who were playing Daf or Setar and twelve students who had not started playing yet were regarded as case and control groups respectively. Some of them also underwent electrodiagnostic studies. Results Forty-seven percent (17 of 36) of the Setar players and 57% (24 of 42) of the Daf players and fifty-three percent (41 of 78) of the instrumentalists as a whole had CTDs. None of them had carpal tunnel syndrome. Conclusions Our study revealed that the prevalence of CTDs in Iranian instrumentalists was unusually high. In addition to age, other variables may be contributory. This needs to be further studied.	Background Cumulative trauma disorders, also called repetitive stress injuries, overuse syndromes or repetitive motion injuries [ 1 - 3 ] are common in musicians [ 4 , 5 ] and are caused by repetitive motions. Nerve entrapments, stress fractures, tendonitis, bursitis and muscle strains have been labeled in this category [ 1 , 5 ]. To date no study has been performed about the prevalence of cumulative trauma disorders (CTDs) in players of Iranian instruments. According to our experience, it seemed to be unusually high when compared with related prevalence in nonprofessional players of classical instruments as reported by Fry [ 4 ]. This study was performed to determine the prevalence of cumulative trauma disorders in amateur music students playing two traditional Iranian instruments: Daf and Setar. Daf is a percussion musical instrument that has a circular wooden frame covered with goat skin with or without metal discs around its edge. To play Daf the player shakes it and hits it with both hands (fig. 1 ). Setar is a string musical instrument that has 4 strings. It is played by the index of right hand (fig. 2 ). In comparison to classic musical instruments, Setar resembles the Guitar, but Daf doesn't have any similar equivalent. Methods In a prospective cross sectional study, we interviewed and examined the students of three music training centers, numbering 94. Twelve students who were at their first sessions and hadn't begun to play were selected as control group. Age, sex and duration of playing (date of starting and daily playing time) as well as vocational and avocational risk factors for developing CTDs were recorded after a direct interview. Then the students were referred to a physician who did not know whether the student belonged to the case or control group. He then evaluated their upper limbs and necks. Specific attention was paid to pain, paresthesia, sensory changes, tenderness, range of motion, muscle power and muscle stretch reflexes. In addition, Phalen, Tinel and carpal compression tests [ 6 ] were performed to detect the presence of carpal tunnel syndrome (CTS); the most common neuropathy reported in instrumentalists [ 5 ]. Since the standard diagnostic test for CTS is electrodiagnostic study [ 7 ], all of the students were asked to attend our center for electrodiagnostic studies. In all of the participants, antidromic median sensory nerve action potential (SNAP) was obtained from the third digit at both 7 and 14 cm. Then the split times and amplitudes were compared. Also distal latency for the motor median nerve was obtained. We also compared the wrist versus midpalm compound muscle action potential (CMAP) amplitudes [ 8 - 10 ]. Electromyographic investigation was not performed. The data were analyzed by SPSS software using Chi square and Fisher's exact tests. Results Ninety four students were included in this study. Four students were excluded from the study, two because of a history of musculoskeletal pain before attending the music center, one because of playing two instruments and one, serving as a typist. Twelve of the students who had not started to play were assigned to the control group and the remaining 78 students; 42 in Daf and 36 in Setar groups; were considered as case group (table 1 ). Mean age of students in the case group was 21.2 years (SD: 3.8) including 47 females and 31 males. Mean duration of instrument playing in this group was 7.9 months (SD: 5.4). Mean age of students in control group was 25.2 years (SD: 9.2). This group consisted of 9 females and 3 males. Mean Duration of daily playing in Setar students was more than Daf students (1.6 Vs 1.5 hours) which was not statistically significant (P value = 0.8). Mean duration of daily playing in male and female students was 1.8 hours and 1.4 hours respectively. Which was not statistically significant (P value = 0.64). Forty-one students in case group (53% of the total of 78) had musculoskeletal pain and there was a significant correlation between playing Daf and Setar and development of musculoskeletal symptoms. The prevalence of pain among females was twice as much as males but the difference was not statistically significant (P value = 0.12) (table 2 ). The prevalence of musculoskeletal pain in Daf players was more than Setar players (57%vs 47%, P value = 0.38); again, this difference was not significant (table 2 ). Regarding the location of pain, hand was the most common site; it was painful in 65% of cases (table 3 ). Twenty six students, all from the case group attended our electrodiagnostic center, none of them had carpal tunnel syndrome. None of the students in control group had problems in their exams and none of them attended for electrodiagnostic studies. Discussion A large number of amateur Daf and Setar players with a history of playing of less than 1 year (7.9 months) and almost 1.5 hours a day had musculoskeletal pain (that is considered a form of CTDs). The prevalence of pain in this group was much greater than students in tertiary music schools who train for some years for 6 hours a day (53% vs. 9.3–21%, respectively) and almost equals professional orchestra players (73–75%) [ 5 ]. In a group of instrumentalists (Guitarists, Harpists, Pianists etc.) Bejjani et al found a 77.5% prevalence of upper extremity disorders serious enough to impair the performance or to cause the musician to stop playing at least temporarily [ 11 ]. similarly, it is possible that some of the students also had quit playing before they had chance to enter our study (case selection bias) this might have caused an underestimation of the prevalence of the CTDs observed in this study. So it may be reasonably concluded that 53% is the minimum prevalence of CTDs in the studied group. How can we explain this high prevalence? The most important cause of CTDs is repetitive motions and in fact multiplication of duration and intensity of exercise [ 4 ]. Since both the duration and the intensity of exercise in these players were much less than that of professional music students or music trainees, other factors should be considered. According to Fry [ 4 ], other important factors that predispose to CTDs are genetics and student technique. Since the students were taught in certified centers and the music teachers were satisfied with the students' techniques, we assumed that playing method was not of primary concern. The particular instrument has been shown to be a risk factor for developing CTDs [ 5 , 14 ]. On the other hand, Setar is not heavier than guitar, nor does its playing need awkward positions, so the instrument in itself may not explain this high prevalence. Another risk factor is age [ 12 ]. It has been shown that adults who start playing, may be more vulnerable to developing CTDs. The extent to which this may have affected the results of our study is not clear so we additionally proposed that the studied group might have been inherently susceptible to develop CTDs because of some genetic factors such as joint hypermobility. This hypothesis can explain, at least in part, the wide range (9–49%) [ 5 - 12 ] of the prevalence of CTDs in music students by different studies. However, genetic analyses and larger studies are needed for validating this hypothesis. As mentioned, we did not find any case of symptomatic carpal tunnel syndrome or nerve conduction abnormalities suggesting subclinical median neuropathy at the wrist, implying that CTS is a more advanced form of cumulative trauma disorders when compared to musculotendinous unit CTDs. Hand was the most common painful site in this study (65%); a finding which is in concert with other published studies (41–54 %)[ 4 , 11 ]. There are two other findings in the current study left to be explained: First: Daf is played being held using both hands but Setar is being held like Guitar. So it can be postulated that playing Daf is more harmful than Setar and we expected more CTDs in Daf players. Although, the prevalence of CTDs was higher in Daf players, the difference was not significant (p value = 0.38). A significant difference may be found with a large scale study. Second: it has been known that CTDs are more common in females [ 5 , 12 , 13 ]. In our study, we also found a higher occurrence of CTDs among females but the study failed to reveal a statistically significant difference (p value = 0.12), perhaps because of small sample size. Conclusions Our study revealed that the prevalence of CTDs in Iranian instrumentalists was abnormally high. This is an unusual finding that can't be fully explained by the difference in the instruments (classical versus traditional), playing method or intensity of the exercise. Other susceptibility factors such as age at the starting of playing or genetic predisposition may be contributory. Larger studies focusing on individual characteristics and genetic analyses are needed to delineate other important factors. Competing interests The authors declare that they have no competing interests. Abbreviations CTD: cumulative trauma disorders CTS: carpal tunnel syndrome Authors' contributions SS: suggesting the proposal, examining the volunteers, writing the paper. BK & SMJS: examining the volunteers AB: great help in writing the paper and statistical analysis PJ: statistical analysis Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529268.xml
546042	Aging and Death in E. coli	null	As human beings, aging and death are an inevitable part of our lives. As we pass through each decade, the concrete signs of aging—greying hair, aches and pains, the gradual failure of one organ system after another—and the realization that we are mortal increasingly occupies our thoughts. All other multicellular animals and plants also show clear signs of aging, as do some single-celled organisms. In the yeast Saccharomyces cerevisiae (baker's yeast), for example, the function of individual cells gradually declines with time, and each yeast cell has a finite life span. In organisms like this, it has been proposed that reproduction by asymmetric division is a prerequisite for aging. In other words, for a unicellular organism to age, when it divides, it must give rise to a “parent” cell and a smaller offspring cell (as in yeast), which then has to go through a juvenile phase of growth or differentiation before it divides. At each cell division, the parent cell becomes older until it reaches its natural life span and dies. A growing microcolony of E. coli But what about organisms that produce two apparently identical cells when they divide? Do such organisms age? The assumption has been for some years that cells that divide symmetrically do not age and are functionally immortal. Eric Stewart and colleagues have now tested this idea by analyzing repeated cycles of reproduction in Escherichia coli , a bacteria that reproduces without a juvenile phase and with an apparently symmetric division. E. coli is a rod-shaped organism that reproduces by dividing in the middle. Each resultant cell inherits an old end or pole and a new pole, which is made during the division. The new and the old pole contain slightly different components, so although they look the same, they are physiologically asymmetrical. At the next division, one cell inherits the old pole again (plus a brand new pole), while the other cell inherits, a not-quite-so-old pole and a new pole. Thus, Stewart and co-workers reasoned, an age in divisions can be assigned to each pole and hence to each cell. The researchers used automated time-lapse microscopy to follow all the cell divisions in 94 colonies, each grown from a single fluorescently labeled E. coli cell. In all, the researchers built up a lineage for 35,049 cells in terms of which pole—old or new—each cell had inherited at each division during its history. They found that the cells inheriting old poles had a reduced growth rate, decreased rate of offspring formation, and increased risk of dying compared with the cells inheriting new poles. Thus, although the cells produced when E. coli divide look identical, they are functionally asymmetric, and the “old pole” cell is effectively an aging parent repeatedly producing rejuvenated offspring. Stewart and his colleagues conclude that no life strategy is immune to the effects of aging and suggest that this may be because immortality is too costly or is mechanistically impossible. This may be bad news for people who had hoped that advances in science might eventually lead to human immortality. Nevertheless, E. coli should now provide an excellent genetic platform for the study of the fundamental mechanisms of cellular aging and so could provide information that might ameliorate some of the unpleasantness of the human aging process.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546042.xml
548696	Long-term survival rates of laryngeal cancer patients treated by radiation and surgery, radiation alone, and surgery alone : studied by lognormal and Kaplan-Meier survival methods	Background Validation of the use of the lognormal model for predicting long-term survival rates using short-term follow-up data. Methods 907 cases of laryngeal cancer were treated from 1973–1977 by radiation and surgery (248), radiation alone (345), and surgery alone (314), in registries of Connecticut and Metropolitan Detroit of the SEER database, with known survival status up to 1999. Phase 1 of this study used the minimum chi-square test to assess the goodness of fit of the survival times of those who died with disease to a lognormal distribution. Phase 2 used the maximum likelihood method to estimate long-term survival rates using short-term follow-up data. In order to validate the lognormal model, the estimated long-term cancer-specific survival rates (CSSR) were compared with the values calculated by the Kaplan-Meier (KM) method using long-term data. Results The 25-year CSSR were predicted to be 72%, 68% and 65% for treatments by radiation and surgery, by radiation alone, and by surgery alone respectively, using short-term follow-up data by the lognormal model. Corresponding results calculated by the KM method were: 72+/-3%, 68+/-3% and 66+/-4% respectively. Conclusions The lognormal model was validated for the prediction of the long-term survival rates of laryngeal cancer patients treated by these different methods. The lognormal model may become a useful tool in research on outcomes.	Background Literature review [ 1 ] indicated that local control, laryngeal preservation, and survival rates of larynegeal cancer patients were similar after transoral laser resection, open partial laryngectomy, and radiotherapy. Open partial laryngectomy was reserved for patients with locally recurrent tumors. There are still some unanswered questions. Will radiation combined with surgery give a better result than single modality treatment alone? Will treatment results from the community centers follow published data from prestigious centers? After radiotherapy, radio-resistant cells theoretically may take some time to grow before recurrence. Short-term data may not reflect long-term local control and survival rates. We attempt to address these questions in the present study. The lognormal distribution is defined as the distribution of a random variable whose logarithm is normally distributed. The purpose of this study is to validate the use of the lognormal model [ 2 - 4 ] by estimating the long-term survival from short-term follow-up data of laryngeal cancer treated by three different treatment methods: radiation and surgery, radiation alone, and surgery alone. We have previously validated the application of the lognormal model for small cell lung cancer [ 5 ], glottic laryngeal cancer [ 6 ], prostate cancer [ 7 ] and breast cancer [ 8 ]. This model may be useful for randomized clinical trials because it allows the prediction of long-term survival rates several years earlier than is possible by using the standard actuarial life table/Kaplan-Meier method of calculation [ 9 ]. The idea that long-term survival rates can be estimated from short-term follow-up data is attractive because this method shortens the delay in further research to improve cancer treatment. The validation of the lognormal model has two phases. Phase 1 tests the goodness of fit to a lognormal distribution of the survival times of those cancer patients who died with disease. Phase 2 attempts to verify the lognormal model, which uses short-term follow-up data to predict long-term survival rates. These survival rates are then compared with values calculated by the Kaplan-Meier life table method from available long-term data. The second phase has been difficult to implement because of the general lack of large number of patients with sufficiently long follow-up information. With the SEER database [ 10 ], the validation of the lognormal model is now possible. Methods We analyzed a total of 907 cases of laryngeal cancer treated by three treatment methods: radiation and surgery (248 patients), radiation alone (345 patients), and surgery alone (314 patients), registered in two registries, Connecticut and Metropolitan Detroit, from 1973–1977 with known survival status up to 1999 extracted from the SEER database. Fourty-seven patients with unknown survival time and 165 patients with missing treatment methods were excluded. A table of the patient characteristics was listed in Table 1 . The cause-specific survival time was defined as the interval from the date of diagnosis to the date of death from laryngeal cancer or the date of last follow-up for censoring purposes, if the patient was alive and still being followed at the time of analysis. Patients who died of other causes were also censored at date of death. Phase 1 – Test of goodness of fit for lognormality Testing for lognormality was done separately for laryngeal cancer patients who died with disease (as distinct from those who died of an intercurrent disease) treated by: radiation and surgery, radiation alone, and surgery alone. For Phase 1, a minimum chi-square method was used to estimate the standard deviation S and mean M of the log 10 (survival time) of the distribution of patients who died of the cancer. The minimum chi-square test was run by a Microsoft Excel program. A range of S-values and M-values were tested to reduce the chi-square values to a minimum. In order to determine if the observed survival times for a given cohort are lognormally distributed, the results are given in terms of probability levels of significance P for the chi-square estimates which correspond to a minimization of chi-square and hence a maximization of P. The test statistic of the minimum chi-square test was minimized by varying the parameters and the P-value gave the significance of the test. The class intervals were in the powers of 2 in months of the survival time, such as 0–2, >2–4, >4–8, >8–16, and so on. The number of cases in each interval should not be less than 5. The null hypothesis being tested is H 0 : that there is no difference between the observed survival times and the expected survival times calculated from a lognormal distribution with a specified S and M. If P < 0.05 the null hypothesis is rejected. Phase 2 – Validation of the lognormal model A second computer program for the Phase 2 of the study was also run using Microsoft Excel to estimate the cured fraction C by using a maximum likelihood method described by Boag [ 4 ]. Using the lognormal model, the standard deviation (S) was fixed, and only the two remaining parameters, the mean (M) and the cured fraction among all patients (C), were kept floating. Multiple iterations converged to a stable solution for C. The cause-specific survival rate (CSSR) at time τ = [C + (1-C) × Q] × 100%, where Q = the integral of the lognormal distribution between the limits τ and infinity, τ = long-term survival time, C was calculated by the maximum likelihood method. The five-year cohort extended from 1973 to the end of 1977. Prediction of the long-term CSSR were made after one year follow-up, i.e. at the end of 1978, for the laryngeal cancer patients with three different treatments: radiation and surgery, radiation alone, and surgery alone. The predicted CSSR were then validated by comparing with the results calculated by the Kaplan-Meier method using the actual follow-up data available up to 1999. Log-rank tests were performed for the three different treatment groups over the whole time period in order to see if there was a difference in CSSR between treatments. Results Using data from 1973–1977, the minimum chi-square tests verified that the survival times of the patients who died of laryngeal cancer and who were treated by three treatments followed three different lognormal distributions. At minimum chi-square, the S and M values, the numbers of patients N and the P values of the minimum chi-square tests for the three different treatments are listed in Table 2 . As in a prospective trial at interim analysis, Phase 2 was performed for each of the five-year cohort periods after one year of follow-up. Phase 2 predicted, using the maximum likelihood method, the long-term 10-, 15-, 20-, and 25-year CSSR. An S value was selected for the maximum likelihood method, so that the prediction curve obtained by the lognormal model would best fit the Kaplan-Meier graph at one year after the five-year cohort period. Hence at the time of prediction by the lognormal model, the long-term data were not known yet. Table 3 lists the results for each treatment arm and their comparison with calculation obtained by the Kaplan-Meier method. The predictions were validated by comparing them with the Kaplan-Meier calculation using available data up to 1999. The 25-year CSSR were predicted by the lognormal model after only short term follow-up to be 72%, 68% and 65% for treatments by radiation and surgery, radiation alone, and surgery alone respectively. The 25-year CSSR were found to be 72+/-3% (one standard error), 68+/-3% and 66+/-4% respectively by Kaplan-Meier method. Long-term survival rates at other years, e.g. 10-, 15-, and 20-year CSSR, were all within one standard error compared with the Kaplan-Meier calculations. There were no statistically significant differences between the CSSR of the three different treatment groups for all stages combined (p = 0.35 by log-rank test for the three treatments). Figures 1 , 2 and 3 show the comparisons of the three different treatments: radiation and surgery, radiation alone, and surgery alone respectively for laryngeal cancer in the Kaplan-Meier graph at the year 1999 compared with the lognormal model prediction curve which could be obtained at 1978. The SEER database provides localized and regional disease stages, instead of T1N0 or T2N0 stages, etc. The lognormal model prediction of the 25-year CSSR for 454 patients with localized stage disease were 84%, 75%, and 80% for treatments by radiation and surgery, radiation alone, and surgery alone respectively. The 25-year CSSR calculated by the Kaplan-Meier method were 83+/-4%, 75+/-4%, and 77+/-6% respectively (p = 0.08, log-rank test for the three treatments). For 286 patients with regional stage disease, the 25-year CSSR were 62%, 58%, and 52% respectively, and compared with Kaplan-Meier method were 63+/-6%, 58+/-7%, and 46+/-6% respectively (p = 0.76, log-rank test for the three treatments). Discussion The current study demonstrates the application of the lognormal model to a population based study. The lognormal model is being applied in a manner that can be applied to prospective trials in practice. Our previous publication about the application of the lognormal model was for different stages of laryngeal cancer patients treated by one radiation oncologist, Dr. M. Lederman in the Royal Marsden Hospital, United Kingdom [ 6 ]. The current study shows that the lognormal model is applicable in different scenarios. Detroit and Connecticut registries were chosen because they have the earliest data starting from 1973 and they include a large population of both white and black patients. Generally cause-specific death rates underestimate the mortality associated with a diagnosis of the specific cancer, because some patients died of other causes[ 11 ]. Gamel et al .[ 12 ] found that the follow-up time should be one standard deviation beyond the mean of the survival time so as to obtain stable results. In the current study, five-year cohorts extended from 1973 to the end of 1977 were used. Stable results for prediction of the long-term CSSR were obtained after one year of follow-up. In this study, for localized stage disease 5-year CSSR were 91%, 83%, 95% for treatments by radiation and surgery, radiation alone, and surgery alone respectively with Kaplan-Meier method. Jones et al .[ 13 ] found that the 5-year tumor-specific survival for those treated by radiation was 87% and for those treated by surgery was 77% (p = 0.1022). Both radiation and surgery are equally effective for treating early stage laryngeal carcinoma. In the current study, there were marginal difference in the results of the three treatments for localized stage patients. Jorgensen et al .[ 14 ] found that among patients with T1 glottic carcinomas the 5-year locoregional control rate was 88%, i.e. 88% of patients were cured by radiotherapy alone. The 5-year disease-specific survival (DSS) was 99%, i.e. salvage surgery added approximately 11% to the survival of T1 glottic patients. Only 4% (12/312) of T1 glottic patients underwent laryngectomies. Locoregional control among T2 glottic patients was 67% and the DSS 88%, and 18% (41/233) of patients underwent laryngectomies. The corresponding results among T3 glottic patients were 30% and 59%, about 50% of patients underwent laryngectomies. For T3 glottic carcinomas, initial surgery did not produce better survival rates. Franchin et al .[ 15 ] studied T1 and T2 glottic carcinoma. The 5-year and 10-year overall survival rates were 83% and 63.5%, respectively. The overall 10-year local control rate for patients with T1 and T2 glottic carcinoma was 89%. In this study, the treatment results were marginally different for localized stage (p = 0.08, log-rank test for the three treatments) and the treatment results were similar for regional stage (p = 0.76, log-rank test for the three treatments). For localized stage combination radiation and surgery may have more certainty of disease control and hence long-term survival benefit. The treatment results were similar for regional stage because the patients were diagnosed late and disease control may be more difficult. The predicted survivals were within one standard error of the Kaplan-Meier estimations for both localized and regional stages. It shows that the prediction method can work for both good and poor prognosis cases. The practical value of this study is that this lognormal model may be used for prediction of the results of prospective trials earlier than the Kaplan Meier method. This lognormal model may become a useful tool in research about outcomes. Use of this lognormal model could result in more rapid advances in cancer treatment and have the potential benefit of a reduction of cost in cancer research. Competing interests The author(s) declare that they have no competing interests. Authors' constributions PT: Data analysis and writing of the manuscript. EY, RS: Critical appraisal of the manuscript. JT: Data analysis and critical appraisal of the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548696.xml
548682	Daily antibiotic cost of nosocomial infections in a Turkish university hospital	Background Many studies associated nosocomial infections with increased hospital costs due to extra days in hospital, staff time, extra investigations and drug treatment. The cost of antibiotic treatment for these infections represents a significant part of hospital expenditure. This prospective observational study was designed to determine the daily antibiotic cost of nosocomial infections per infected adult patient in Akdeniz University Hospital. Methods All adult patients admitted to the ICUs between January 1, 2000, and June 30, 2003 who had only one nosocomial infection during their stay were included in the study. Infection sites and pathogens, antimicrobial treatment of patient and it's cost were recorded. Daily antibiotic costs were calculated per infected patient. Results Among the 8460 study patients, 817 (16.6%) developed 1407 episodes of nosocomial infection. Two hundred thirty three (2.7%) presented with only one nosocomial infection. Mean daily antibiotic cost was $89.64. Daily antibiotic cost was $99.02 for pneumonia, $94.32 for bloodstream infection, $94.31 for surgical site infection, $52.37 for urinary tract infection, and $162.35 for the other infections per patient. The treatment of Pseudomonas aeruginosa infections was the most expensive infection treated. Piperacillin-tazobactam and amikacin were the most prescribed antibiotics, and meropenem was the most expensive drug for treatment of the nosocomial infections in the ICU. Conclusions Daily antibiotic cost of nosocomial infections is an important part of extra costs that should be reduced providing rational antibiotic usage in hospitals.	Background Nosocomial infections are frequent complications of hospitalization and also an important public health problem in developing countries, as well as in developed ones. The socioeconomic impact, ie, prolongation of hospitalization, mortality, and cost of these infections adversely effects patients and nations' economic well-being [ 1 ]. The cost of nosocomial infections includes increased length of hospital stay, staff time, laboratory cultures of pathogens and antimicrobial treatment [ 2 - 4 ]. Although, cost of antimicrobial treatment is an important part of health expenditure, data on this subject are extremely limited in Turkey. The aim of our study was to determine daily antibiotic cost of nosocomial infection per infected patient in a university hospital. Methods The hospital setting Akdeniz University Hospital is a 600-bed tertiary referral centre in Antalya, Turkey, treating 27 000 patients per year. The study was conducted in six adult medical and surgical intensive care units (ICUs) with a total of 51 ICU beds. Neonatal ICU was not included in the study. Since 1993, the institutional policies of hospital infection control have been implemented by infection control team. Definitions and study population In our hospital, routine prospective, active surveillance of nosocomial infections in all ICUs is performed by one infection control nurse, supervised by an infection control physician. Nosocomial infections are defined using the Centers for Disease Control and Prevention criteria [ 5 , 6 ]. We do not follow patients for signs of infection after discharge unless they are readmitted to the hospital. Between January 1, 2000 and June 30, 2003, all inpatients hospitalized in one of the adult ICUs were included in this study. Data on antimicrobial treatment were recorded for patients aged 15 or above presenting with only one nosocomial infection. For all patients included in the study, the following were recorded: age, sex, infection site, microbiologic data, antimicrobial therapy and antibiotic cost. Measurement of costs In our ICUs, all antimicrobial prescriptions are recommended by an infectious disease consultant. Antimicrobial agents prescribed only for therapeutic indications were recorded. The daily antibiotic cost was calculated in US dollars based on June 2003 prices of antimicrobial agents provided by the hospital pharmacy. The daily antibiotic cost per infected patient was calculated by the multiplication of box price and number of daily doses that was used for that infection. Two costs were calculated for each antimicrobial; the minimal cost (min) was based on the lowest recommended parenteral daily dose and the maximal cost (max) was based on the highest recommended parenteral daily dose. Results Between January 1, 2000, and June 30, 2003, a total of 8460 patients were admitted to the adult ICUs. Overall, 817 patients developed 1407 episodes of nosocomial infections, accounting for an infection rate of 16,6%. Among them, 233 patients (mean age:50,1; sex ratio female:male 0,49) had only one nosocomial infection. Mean daily antibiotic cost was found $89,64 per infected patient ($8,56 to $359,28). Among the sites of nosocomial infections, urinary tract infections had the lowest daily antibiotic cost per infected patient (Table 1 ). The mean daily antibiotic cost for pneumonia was the highest of all sites, but patients with bloodstream infection reached the highest range of daily cost ($31,31 to $359,28). In addition, mean daily antibiotic cost was found $162,35 for seventeen other infections including postoperative meningitis, mediastinitis, and empyema. Table 1 Daily antibiotic costs according to the sites of nosocomial infections. Site of nosocomial infections Number of patients Range of daily cost per infected (US$) Mean (US$) Pneumonia 111 10,02–250,74 99,02 Bloodstream infections 28 31,31–359,28 94,32 Surgical site infections 11 17,12–204,74 94,31 Urinary tract infections 66 8,56–228,68 52,37 Out of 233 patients, 206 patients had microbiologically documented infections, 177 patients were infected by a single pathogen while 29 patients were diagnosed as having polymicrobial infections (Table 2 ). Pseudomonas aeruginosa was the most prevalent bacteria followed by Klebsiella spp. and Acinetobacter spp.. P. aeruginosa infections had the highest overall daily antibiotic cost per infected patient than other pathogens. Among 21 Staphylococcus aureus strains 15 (72%) were resistant to methicillin. The overall daily antibiotic cost of methicillin resistant S. aureus (MRSA) infections was two to three times higher than infections with susceptible strains. However, median daily cost per infected patient for MRSA infections were lower than susceptible strain infections. Table 2 Daily antibiotic cost according to the pathogens. Pathogens No. Overall daily cost (US$) Range of daily cost per pathogen (US$) Median (US$) Pseudomonas aeruginosa 60 5567,06 17,98–204,74 100,04 Acinetobacter spp 36 4951,06 17,98–359,28 92,47 Stenotrophomonas maltophilia 4 310,99 31,31–100,04 89,82 Klebsiella spp 37 3104,22 10,02–179,64 79,6 Enterobacter spp 10 961,79 60,42–139,08 77,28 Escherichia coli 23 1652,57 10,02–179,64 60,41 Proteus spp 3 49,04 13,24–49,04 49,04 Staphylococcus aureus Methicillin-susceptible (MS) 6 476,22 10,02–142,2 74,52 Methicillin-resistance (MR) 15 1188,1 35,88–142,2 71,1 CoNS* MS-CoNS 1 49,64 16,34–49,64 49,64 MR-CoNS 3 148,92 17,52–49,64 49,64 Enterococcus spp 16 1141,25 32,29–142,2 49,64 Candida spp 21 235,52 8,56–38,64 8,56 No pathogen identified 27 3166,75 10,02–359,28 114,6 * Coagulase negative Staphylococcus Among the 350 antibiotic prescriptions for nosocomial infections, piperacillin-tazobactam and amikacin were the most prescribed antibiotics (Table 3 ). Carbapenems especially meropenem were the most expensive drugs. Table 3 Daily cost of antimicrobial agents for nosocomial infections. Antimicrobial agents Number of prescriptions Daily cost per infected (US$) Min Max Betalactams Ampicillin-sulbactam 20 23,92 71,76 Piperacillin-tazobactam 48 85,95 114,6 Ticarcillin-clavulanate 4 14,9 22,35 Carbapenems Imipenem 31 100,04 150,06 Meropenem 23 179,64 359,28 Cephalosporins Cefepime 26 38,64 77,28 Ceftazidime 18 35,82 71,64 Cefoperazone-sulbactam 16 40,28 80,56 Cefazoline 10 10,02 20,04 Ceftriaxone 3 19,7 39,4 Aminoglycosides* Amikacin 52 - 7,96 Netilmicin 21 - 24,48 Tobramycin 3 - 18,56 Fluoroquinolones Ciprofloxacin 18 49,04 98,08 Ofloxacin 2 25,74 51,48 Levofloxacin 1 41,07 82,14 Glycopeptides Vancomycin 13 49,64 87,27 Teicoplanin 12 71,1 142,2 Other antibiotics Clarithromycin 4 11,57 23,14 Trimethoprim-sulphamethoxazole 2 4,48 8,96 Metronidazole 2 5,51 10,04 Antifungal agents Fluconazole 21 8,56 34,24 Total 350 8,56 359,28 * dosage given as once-daily. Disscussion Cost is an important factor which determines the physician's choice of medication to treat patients in spesific stiuations. In this study, we tried to demonstrate the daily cost of antimicrobial treatment of nosocomial infections according to site of infection, pathogen and antimicrobial agent. In different studies, economical analysis regarding costs attributable to nosocomial infections has been evaluated and reported between $1018 to 2280 per infected patient [ 7 - 9 ]. Jarvis et al reported that the estimated average costs of nosocomial infections were $558 to 593 for each urinary tract infection, $2734 for each surgical site infection, $3061 to 40000 for each bloodstream infection, and $4947 for each pneumonia [ 1 ]. Daily cost of antimicrobial treatment has been reported to be a significant extra cost attributable to nosocomial infections. In this study, we found an average daily antibiotic cost of $89,64 per nosocomial infection. It is clear that cost of overall antibiotic treatment for a period of approximately 10–15 days is $900 to $1350. Prolongation of hospital stay has been the major extra cost attributable to nosocomial infections in many reports [ 2 - 4 ], but in comparative case-control study from our country, Yalcin et al. [ 8 ] found that cost of antibiotic therapy of $1190 per infected patient, accounted for about 75% of the total extra cost. This finding may be due to the high prices of antibiotics in Turkey. To calculate the true costs of antibiotic therapy, hidden costs arising from intravenous administration, labor, serum antibiotic assay, monitoring hematological and biochemical indices and adverse effects of antibiotics must be considered [ 10 ]. The present study does not include these relevant "hidden costs" that could substantially modify the total cost of an antibiotic treatment. Although, hidden costs were not calculated, an average daily antibiotic cost of a single nosocomial infection is found to be markedly high in our hospital. This result is within the limits reported by other large economic studies, suggesting that our data is comparable to those found in other countries and with other assessment methods. In a French prevalence survey, Astagneau et al.[ 11 ] reported an average daily antibiotic cost between FF 520 to 1085 (about $86 to $160) per nosocomial infection. French et al.[ 12 ] and Haley et al.[ 13 ] reported an average cost of antibiotic treatment of $190 and between $72 to $128 per nosocomial infection, respectively. In Turkey, Yalcin et al.[ 14 ] found that daily antibiotic cost of nosocomial infections was $70 per patient. The daily antibiotic cost varies markedly according to site of infection. Our study has demonstrated that pneumonia and bloodstream infections were associated with the highest daily antibiotic costs as reported in other studies [ 11 , 13 , 14 ]. Surgical site infections had also high daily antibiotic cost in our study. In their case-control study, Coello et al. reported that antibiotic therapy for surgical patients was the second most significant contributor to cost [ 15 ]. In the present study, nosocomially infected patients that had only one nosocomial infection were considered for analysis. Clearly, antimicrobial treatment of patients with multiple nosocomial infections might be much more expensive. P. aeruginosa infections had the highest daily antibiotic cost followed by other non-fermentative bacilli. Infections caused by P. aeruginosa are difficult to treat because of its virulence and relatively limited choice of effective antimicrobial agents, so, these infections often require combination therapy. Emergence of resistance in P. aeruginosa has been associated with increased morbidity, mortality, and costs [ 16 ]. On the other hand, although the overall antibiotic cost of MRSA infections was higher than infections with susceptible strains, the daily antibiotic cost per infected patient with MRSA was lower with susceptible strain infections. MRSA infections are treated by glycopeptides which cost less than beta-lactams in our country. Astagneau et al reported that the daily antibiotic cost of multi-resistant bacterial infections such as multi-resistant P. aeruginosa infections, was 20% higher than susceptible infections, but the daily antibiotic cost per infected patient for MRSA infections was not higher than for susceptible strain infections [ 11 ]. Expensive antibiotics, such as piperacillin-tazobactam, carbapenems, cefepime, ciprofloxacin, teicoplanin were prescribed more commonly than the cheaper agents such as ampicillin-sulbactam, ceftriaxone or ofloxacin in our ICUs. These expensive antibiotics were mainly prescribed for resistant and severe gram-negative nosocomial infections, such as ventilator-associated pneumonia and postneurosurgical meningitis in ICU. Physicians may be forced to choose empirical antibiotic therapy with broad spectrum antimicrobials by increasing bacterial multi-resistance. In conclusion, mean daily antibiotic cost was found $89,64 per nosocomial infection in our ICUs and nosocomial pneumonia had the highest daily antibiotic cost per infected patient. It is clear that cost of antibiotic therapy of nosocomial infections is an important part of extra cost attributable to nosocomial infection. Approximately one third of nosocomial infections are preventable by full implementation of the current infection control guideline recommendations [ 17 ]. Each institution should develope empirical antibiotic guidelines according to its own local nosocomial infections data. Infection control measures, such as education of health care workers regarding antimicrobial agents and resistance; isolation of patients infected with multi-resistant organisms, should be implemented to reduce infections and expensive antibiotic prescriptions. Competing interests The author(s) declare that they have no competing interests. Authors' conributions DI collated and analyzed the data, participated in the study design and was principal writer of manuscript. ANY conceived the study. GO carried out the laboratory studies. RS, FG, OT and LM participated in the patient management. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548682.xml
514894	Towards the development of a DNA-sequence based approach to serotyping of Salmonella enterica	Background The fliC and fljB genes in Salmonella code for the phase 1 (H1) and phase 2 (H2) flagellin respectively, the rfb cluster encodes the majority of enzymes for polysaccharide (O) antigen biosynthesis, together they determine the antigenic profile by which Salmonella are identified. Sequencing and characterisation of fliC was performed in the development of a molecular serotyping technique. Results FliC sequencing of 106 strains revealed two groups; the g-complex included those exhibiting "g" or "m,t" antigenic factors, and the non-g strains which formed a second more diverse group. Variation in fliC was characterised and sero-specific motifs identified. Furthermore, it was possible to identify differences in certain H antigens that are not detected by traditional serotyping. A rapid short sequencing assay was developed to target serotype-specific sequence motifs in fliC . The assay was evaluated for identification of H1 antigens with a panel of 55 strains. Conclusion FliC sequences were obtained for more than 100 strains comprising 29 different H1 alleles. Unique pyrosequencing profiles corresponding to the H1 component of the serotype were generated reproducibly for the 23 alleles represented in the evaluation panel. Short read sequence assays can now be used to identify fliC alleles in approximately 97% of the 50 medically most important Salmonella in England and Wales. Capability for high throughput testing and automation give these assays considerable advantages over traditional methods.	Background Salmonella express flagellar (H), polysaccharide (O) and capsular (Vi) antigens which determine strain pathogenicity and therefore variation of these antigens has formed the basis for Salmonella serotyping. The Kauffmann-White scheme, first published in 1929, divides Salmonella into more than 2500 serotypes according to their antigenic formulae. Within these, 46 O antigen groups are recognised by Salmonella serotyping. O antigen synthesis and assembly is encoded by the rfb gene cluster which typically contains 12 open reading frames, and ranges in size between serotypes, from approximately 8 kbp to 23 kbp. The variation of O antigens is not due to individual gene sequence variation, but rather to different sets of genes [ 1 ]. Approximately 20,000 repeating flagellin proteins polymerise to form the flagellar filament. The ends of the protein are conserved and responsible for the hairpin shape of the subunit while variation in the central region generates the antigenic diversity. Most serotypes exhibit diphasic flagellar antigen expression by alternately expressing two genes, fliC (phase 1) and fljB (phase 2) which encode flagellins of different antigenicity. Salmonella serotyping methods recognise 63 distinct phase 1 flagellar antigenic factors and 37 phase 2 flagellar antigenic factors although the latter are not always present. Some antigenic factors, denoted by square brackets in formulae, may be present or absent without affecting serotype designation. Serotyping methods are stable, reproducible and have high typeability, yet there are several drawbacks, particularly the dependence on availability of antisera considering the ethics, cost and quality control measures necessary to maintain such a supply. Pulsed-field gel electrophoresis (PFGE) [ 2 , 3 ] is currently the bench-mark for molecular subtyping of Salmonella , however it is best used in combination with plasmid profiling and ribotyping for strain discrimination for epidemiological purposes [ 4 ]. Other approaches include fluorescent amplified fragment length polymorphism (FAFLP) [ 5 ] and multi-locus enzyme electrophoresis (MLEE) [ 6 ] which sample genomic DNA and provide a view of genetic diversity between strains and partially group some serotypes, but on the whole do not group or identify serotypes. Multi-locus sequence typing (MLST) has been used to discriminate between Salmonella strains by sampling variation in a set of housekeeping genes which precludes antigen encoding genes [ 7 ]. In 1993, Luk et al [ 8 ] published a length heterogeneity PCR (LH-PCR)-based method that targeted genes only associated with particular O antigens (A, B, C2 and D), while a more recent study by Fitzgerald et al [ 9 ] developed a serotype specific PCR assay targeting a single O serotype (O:6,14). Several studies have used a molecular approach to discriminate between particular flagellar serotypes (9, 11–12). FliC fragment restriction patterns using a dual enzyme combination allowed differentiation of flagellar types b, i, d, j, l,v, and z 10 but r and e,h nor [f],g,m, [p], g,p, and g,m,s could be separated using this technique [ 10 ]. Hong used restriction fragment patterns of fliC and fljB for serotyping of poultry Salmonella but could not distinguish S . Enteritidis from S . Gallinarum and S . Dublin [ 11 ]. Design of a multiplex-polymerase chain reaction (multiplex-PCR) to identify 1,2, 1,5, 1,6, 1,7, 1,w, e,n,x and e,n,z 15 second-phase antigens has been reported [ 12 ]. Peters and Threlfall reported fliC restriction fragment length polymorphism (RFLP) profiles were not specific enough to differentiate between certain serotypes [ 13 ]. To date no studies have attempted a universal molecular serotyping approach. Relevant publicly available sequence data is incomplete, as is epitope mapping information about specific serotypes, therefore approaches are currently being explored to characterise the expressed antigen or the encoding genes as an alternative to traditional serotyping. For fliC , evidence from antibody binding studies suggests that sequences of ~300 nucleotides of the central variable region of flagellin correlate with serotype [ 14 ] and differences in amino acid sequence can be associated with differences in antigenic specificity. Comparative sequencing has distinguished some salmonella serotypes or biotypes [ 15 - 18 ]. Previous studies have provided full gene sequence for 19 phase 1 flagellar types. The need for a robust single molecular technology to discriminate different serotypes is clear, however sequence data representing all 63 recognised phase 1 flagellar types is incomplete. The aim of this study was to generate full gene sequences for representatives of the majority of phase 1 flagellar serotypes with a view to identifying serotype-specific motifs. These were then used to design a short sequence- or single nucleotide polymorphism-(SNP) based assay targeting characteristic motifs using pyrosequencing. This technology is based on sequencing by synthesis; four nucleotides are added step-wise to a primer-template mix. Incorporation of a nucleotide i.e. extension of the DNA strand, leads to an enzymatic reaction resulting in a light flash. A pyrogram is produced from which the template DNA sequence is deduced. The assay was validated on a panel of 55 strains to initiate a DNA sequence based approach for serotyping Salmonella enterica . Results and discussion Alignment of 106 fliC sequences generated in this study and 32 phase 1 flagellin sequences previously published (see Methods section), representing 35 phase 1 flagellar serotypes revealed a clear division of sequences into two groups. Representative sequences are aligned in Additional file 1 . A tree indicating the relatedness of these sequences generated from translated DNA sequence supported this division with a 100% bootstrap value (Figure 1 ). Sequences encoding phase 1 flagellar antigens exhibiting antigenic factors "g" or "m,t" are referred to as members of the g-complex and the fliC sequences of this group clustered exclusively with the non-motile strains Gallinarum and Pullorum on the tree (Cluster I, Figure 1 ). The level of amino acid sequence homology within Cluster I sequences was 90.05%. Sequences not encoding the antigenic factors "g" or "m,t", formed the second group of sequences (Cluster II), referred to here as the non-g complex. Lower levels (80.3 %) of amino acid similarity were observed within Cluster II. Sero-specific polymorphisms were identified within the central variable region where consensus sequences of Cluster I and Cluster II diverged, between amino acid positions 160 – 407 (based on amino acid numbering system of the sequenced strain of S . Typhimurium (AE008787) represented here as sequence type Typhimurium_a). Figure 1 Protein distance tree of H1 antigens. The tree displays the inferred amino acid sequence distances between full H1 antigens. The label displays the H1 antigen, and the Salmonella serotype or subgroup from which the sequence was obtained. Esherichia coli fliC - H7 sequence was used to root the tree. Bootstrap values are displayed at major nodes. Sequences labelled with _a, _b or _c indicate an H1 allele found to be encoded by multiple sequences (Additional file 2). Salmonella fliC sequences were conserved at their termini and variable in the central region between serotypes [ 16 , 18 ] and clustered according to allele. Amino acid and nucleotide positions described here-in are with reference to the sequenced strain LT2. It was apparent from the alignment of sequences generated in this study that two assays were required, one encompassing Cluster I strains and one for Cluster II. Multiple alignments were created for each cluster and regions of the fliC gene containing sero-specific polymorphisms were identified at nucleotide positions 917 – 933 and 739–749 in Cluster I and Cluster II respectively (Figures 3 and 4 ). PCR primers were designed to amplify the target region in each sequence (see below). One multiplex PCR was developed for each group containing a mixture of specific primers. All primers designed for short sequence assays in this study are shown in Additional file 3 and the testing algorithm is shown in Figure 5 . Figure 3 Sequence motifs at target g. The assay for g-complex strains detected 17 bp of sequence commencing at nucleotide position 917. Fifteen sequence types were identified and differentiated between H1 serotypes. Figure 4 Sequence motifs at target non-g. The assay for non-g complex strains detected 9 bp of sequence commencing at nucleotide position 739. Sixteen sequence types were identified among non-g complex strains tested. Figure 5 Algorithm for identification of unknown isolates. Times given are approximate for 96 samples using methods described. Summary of fliC sequence variation within the g-complex All polymorphisms within the g-complex sequences analysed are displayed in Figure 2 The target region (highlighted) was selected because it conferred multiple sero-specific amino acid substitutions and was variable at the DNA level. In the 17 bp nucleotide sequence assayed, 15 sequence types were identified (Figure 3 ). This region was assayed against the test panel of 17 Salmonella strains belonging to the g-complex and was able to exclusively identify sequence motifs corresponding to phase 1 flagellar serotypes. The serotypes not differentiated by this assay ([f],g,m, [p], g,m, g,m,s and g,m, [p],s or non-motile Gallinarum) were known from full sequencing to be identical at the target region. Figure 2 Amino acid polymorphisms among fliC of g-complex strains. Alignment displaying polymorphic codons only of g-complex fliC genes. Codon numbering is based on LT2 sequence, a slash is used where codons fall between LT2 codons in alignment. Highlighted area indicates region analysed in g-complex assay. Amino acid differences between g-complex strains identified by full sequencing The following polymorphisms located in fliC of the g-complex are likely to be involved in specific epitope formation: two amino acid sequence types were observed in 25 fliC-[f],g,m, [p] sequences obtained from Salmonella enterica serovar Enteritidis strains. Twenty-three S . Enteritidis strains demonstrated complete conservation in their DNA sequence (B16, B18, JTCM02 and 20 phage type 4 strains (Enteritidis_b)). The sequence of B17 was congruent with published S . Enteritidis (M84980) (Enteritidis_a), and exhibited a single amino acid (Ser>Gly at 302) substitution compared to sequence type Enteritidis_b. Published S . Othmarschen (U06455) fliC-g,m , [t] sequence inferred the same amino acid sequence as Enteritidis_a but exhibited a silent mutation at the DNA level. As the fliC sequence for these two serotypes was identical it was apparent that the sequence included here represented an S . Othmarschen strain in which the t factor was absent. Published S . Gallinarum sequences demonstrated 100% DNA homology to Enteritidis_b except for a SNP encoding a stop codon in M84975. S . Pullorum and S . Gallinarum are non-motile as they do not express flagella. Antisera to the g factor antigen react strongly with induced-motility S . Pullorum culture, indicating that g epitopes are expressed in these cells [ 19 ]. This correlates with our sequence data as S. Pullorum clusters with g,m sequences (Figure 1 ). Biotype-specific polymorphisms for S . Pullorum were observed at amino acid position 91 and 323. Molecular identification of S . Pullorum and S . Gallinarum would be of considerable benefit as standard serotyping cannot differentiate these two serotypes. FliC-g,q was differentiated from all other g-complex sequences by an Asp>Gly serotype-specific polymorphism observed at position 284 for S . Moscow. A Thr>Ala substitution at residue 304 conferred by a single nucleotide polymorphism (SNP) was identified between sequences of g,m and g,p, congruent with a previous report [ 20 ], and forms the basis for differentiation of these two serotypes. DNA polymorphisms, but no inferred amino acid substitutions, were observed between strains exhibiting g,m,s and g,m, [p],s. The p factor was not coded for by the fliC sequences of these strains. S . Essen fliC-g,m was distinct from other g and m coding sequences by an Asp>Asn substitution at 283. fliC-g,p,s could be differentiated from fliC-g,p by a Thr>Ala substitution at 254. A motif of two amino acids at positions 302 and 307 was common to S . Derby, S . Agona, S . Adelaide, and S . Berta which exhibit phase 1 flagellar antigenic factors "f" and "g". This motif was exclusive to these serotypes. DNA sequence variation at corresponding positions allowed S . Derby and S . Agona to be distinguished from S . Adelaide and S . Berta. FliC-g,z 51 ; and fliC-m,t with fliC-g,m,t each form distinct clusters (Figure 1 ). Summary of fliC sequence variation within the non-g complex Sequence conservation within alleles that did not encode g or m,t antigenic factors was demonstrated by 97.8 – 99.1% homology and 80.35% homology was measured in the complex. The high level of variability between alleles in this group did not allow association of specific amino acids to epitope formation that was possible with the g-complex sequences. The quantity and distribution of polymorphic bases observed in this group (specified below) meant that there was a choice of regions that could be used for differentiation. Following testing of four possible regions, the region encompassing amino acids 248–250 was selected for use in the final non-g assay. Each serotype had a unique motif at the target region except fliC-l,v and fliC-l,z 13 which shared a sequence type (Figure 4 ). Some amino acid sequences were not identical within non-g alleles, including i, r, d, e,h, a and z 4 ,z 23 ( Additional file 1 ). A previous study of fliC-i sequences reported no variation in a 260 bp region among seven Typhimurium strains [ 17 ]. Six full S . Typhimurium fliC s and a fragment spanning nucleotides 434–1090, corresponding to amino acids 159 – 400, of a further 20 S . Typhimurium strains were sequenced. Three distinct DNA sequences which resulted in translated differences in the expressed peptides were observed within the serotype. Sequence type "Typhimurium_a" was detected in 18 strains, identical to the sequenced strain LT2. Sequence type "Typhimurium_b" was detected in four strains and was differentiated by a SNP at 768, conferring a 256 Glu>Lys substitution. Sequence type "Typhimurium_c" conferred a Glu>Lys substitution and an Ala>Thr substitution at 263 and was found in two strains: 571896 and 571913. Strains 571896 and 571913 were phage type DT104 however, other strains tested did not conform to recognised phage typing patterns so no assured correlation could be made with phage type or other phenotype. S . Choleraesuis sequence ( fliC-c ) differed from that published (AF159459) at one nucleotide, conferring amino acid substitution of Thr >Ser at codon 99. FliC sequences of nine S . Heidelberg strains were identical, consistent with the results of a previous report [ 18 ]. The published sequence for fliC-r of S . Rubislaw (X04505) differed from S . Heidelberg at three amino acids. The S . Muenchen sequence determined in this study differs in twelve amino acids to the published S . Muenchen (X03395), and differed in 25 amino acids from the S . Duisberg sequence in this study. S . Anatum, S . Newport and S . Saintpaul exhibit factors e,h in their phase 1 flagellar. Amino acid sequence was conserved in two strains of S . Saintpaul but distinct for each serotype due to four amino acid substitutions at codons 192, 213, 238, 356. S . Brandenburg and S . Panama exhibit l,v in the phase 1 antigen, no inferred amino acid differences were detected. FliC-l,v sequences clustered with fliC-l,z 13 (Figure 1 ). FliC from three strains exhibiting the z 4 antigenic factor in phase 1 flagellar were sequenced. Cluster analysis grouped these sequences together in the non-g group although they contain regions of sequence similar to g-complex strains (amino acid positions 96 – 164). Z 4 ,z 24 is distinct from z 4 ,z 23 and z 4 ,z 23 sequences varied within the serotype at seven amino acid positions: 235, 237, 239, 242, 253, 351 and 369. The complex mosaic nature of fliC is evident from analysis of amino acid alignment of sequences in particular strains from subgroups in the SARC collection (see Materials and Methods). Molecular serotyping assays By comparison of amino acid sequences coding for antigens of the different serotypes, sero-specific motifs were identified. Individual regions of fliC were selected for the g-group and non-g group to provide unique sequence for as many serotypes as possible, while keeping the assay simple to perform and analyse. Two multiplex PCRs were developed for the production of fliC amplicon of g-complex strains and fliC amplicon of non-g strains. Sero-specific motifs in each amplicon were consequently identified by sequencing-by-synthesis. G-complex assay Fifteen sequence types were identified in the 17 bp of nucleotide sequence assayed (Figure 3 ). Twenty-seven strains were tested and each produced a recognised sequence motif which differentiated between serotypes. Serotypes would be fully resolved through the detection of further polymorphisms, for example g, [s],t and g,t can be separated through additional detection of a A>G change at nucleotide position 777 conferring amino acid Ser>Gly substitution specific to g,t. Non-g assay Fourteen sequence types were identified in the 9 bp of nucleotide sequence assayed (Figure 4 ). Thirty strains were tested, each producing a recognised sequence motif allowing separation of serotypes. Serotypes l,v and l,z 13 gave the same motif at the target region but could be separated by nucleotide substitution A>G at position 783 conferring a Thr>Ala change. The stability of the targeted polymorphisms in Salmonella phase 1 flagellar antigens was demonstrated through testing on a panel of 55 isolates. The SNP responsible for the antigenic difference between serotypes g,m and g,p was within the target region and so could be differentiated by the assay. The amino acid substitution that separated fliC-g,p,u was also encoded within the sequence assayed. Antigens i, r, c, d, b, e,h, k, a, z 41 , z, z 10 , z 4 ,z 23 , z 4 z 24 , g,q, g,m,p, g,p,u, [f],g,t, g,z 51 and biotype S . Pullorum gave unique motifs, l,v and l,z 13 shared a motif. Some serotypes for which certain factors may be present or absent (denoted by square brackets in antigenic formulae) were not separated from similar serotypes: [f],g,m, [p], g,m and g,m, [p],s; [f],g,m, [p] and g,m, [t]; g, [s],t and g,t although these could be separated by other DNA polymorphisms as discussed. Two motifs were observed for k, each specific to S . Thompson and IIIb. Two motifs were observed for d, specific to S . Duisberg and S . Muenchen / S . Schwarzengrund. Published sequence data for fliC-m,t , from serotypes S . Banana, S . Oranienburg and S . Pensacola were included in assay design. The polymorphic region targeted by the assay is predicted to differentiate m,t sequences from other g-complex antigens, and also differentiate S . Pensacola from S . Banana and S . Oranienberg. Strains exhibiting factors m,t were not available for testing. Conclusions A high level of sequence homology between fliC genes of g-complex strains was observed. Data produced for this study is congruent with a previous report of g-complex sequences [ 16 ]. The genetic basis between distinct antigens in this group of sequences can be a single amino acid substitution. Specific motifs could be identified as the genetic basis for particular antigenic differences and hence their involvement in epitope formation and stability among strains inferred. Full gene sequences were distinct for each antigen analysed in this study. Furthermore, analysis of multiple representatives revealed that some antigens were encoded for by multiple sequences. In these cases DNA sequence based methods are more discriminatory than traditional serotyping methods which do not recognise these as distinct antigens. Assays were designed such that an unknown strain could be identified in respect of its phase 1 flagellar antigen in two steps. The specific PCR acted as the first level of identification and the resultant amplicon was used for the pyrosequencing assay. A positive PCR indicated which of two Pyrosequencing assays to apply. Each assay was uniform in that only one mix of pyrosequencing primers and one dispensation order was needed. All the strains tested were successfully amplified by PCR. As some analyses have been performed on unpublished data, exhaustive testing of the assay will be performed to confirm specificity and typeability of all recognised serotypes. Molecular serotyping will incorporate the desirable properties of serology (typeability, reproducibility, epidemiological significance) together with the advantages of DNA analysis (ability to automate, labour saving, serum independent). Antisera production and associated quality control measures would be unnecessary for a DNA sequence based method. Time-consuming flagellar phase reversal to identify both flagellar antigens is not necessary at the genetic level. Other advantages include reduced labour costs, rapid results in comparison to traditional serotyping methods. DNA sequence data is highly portable and easy to interpret. The method described was easily automated by use of the vacuum preparation tool for the DNA strand separation step and could be further automated by use of robotics for PCR set-up. Result output included a pyrogram, raw text and confidence level; automation of data analysis could be achieved by use of a computer script to screen at a set confidence level and cross-check results against a database of recognised motifs. With the capability to identify approximately 97% of phase 1 flagellar antigens from medically important Salmonella strains occurring in England and Wales, the assay can be used now as an economic screen of unknown isolates and alleviate the burden on routine serotyping work. A scheme including the phase 1 flagellar assay and complementary assays for phase 2 flagellar and polysaccharide antigens is currently being piloted and based on incidence data of the top 50 serotypes from 2003, it is anticipated that the scheme will provide a complete molecular serotype for around 80% of isolates and confident prediction of 76% of the remainder. Future work Alternative sero-specific polymorphisms identified in this study could be exploited by similar assays to allow further separation when antigens did not give unique pyrograms. The alliance of the fliC assay to a fljB and rfb assay would allow the full antigenic formulae of Salmonella serotypes to be determined. Common phase 2 flagellar antigens will be selected for sequencing and together with published data will be analysed for sero-specific motifs and a short sequence assay designed with the approach described in this study. In 1993, Luk et a l [ 8 ] outlined a simple length heterogeneity PCR for identification of Salmonella major serogroups A, B, C2, and D. They based their PCR on the presence/absence of genes or sequence polymorphisms within shared genes. Essentially, only serogroups A and D possess a gene to synthesise tyvelose but serogroup A genes carry an early stop codon and do not produce the sugar itself. Only groups B and C2 possess a gene to synthesise abequose but the sequences are distinct. We have also designed a preliminary pyrosequencing assay to distinguish these serogroups based on amplification and short sequences of these genes (data not shown). In summary, epitopes are conformational and it is difficult to determine which amino acids would interact from a linear sequence. However, in the g-complex sequences some amino acid changes could be identified as responsible for differences in antigenic factors because variation was minimal. There is no common factor among the non-g antigens and the sequences are much more heterogenous; there are too many substitutions to draw conclusions about epitope specific sequences. Epitope mapping could be used to further investigate epitopes responsible for antigenic specificity. Methods Bacterial strains Strains exhibiting the different phase 1 flagellar antigenic factors were selected from Salmonella Reference Collections A, B and C obtained from the University of Calgary. Multiple isolates of S . Enteritidis phage type 4, and S . Typhimurium phage type DT104 plus a panel of serotyped strains were gratefully received from the Salmonella Reference Laboratory, Health Protection Agency, Colindale ( Additional file 2 ). DNA preparation, PCR and sequencing MagNA Pure instrument and Total Nucleic Acid Extraction Kit 1 (Roche, East Sussex). PCR reactions contained 1X PCR buffer, 20 pmoles of FL_START2, 20 pmoles rFSa1 [ 21 ], 1 U Taq polymerase, 0.25 mM of each dNTP, 4 mM MgCl 2 (Sigma-Aldrich, Dorset). PCR amplification of the fliC gene was performed with an 9700 GeneAmp PCR System (Applied Biosystems, Cheshire): 35 cycles of 95°C for 60 sec, 50°C for 60 sec, 72°C for 30 sec followed by a 7 min final extension at 72°C. PCR products were purified with Qiaquick spin columns (Qiagen Ltd, West Sussex) and quantitated by gel electrophoresis using Ready-to-Run pre-cast gels (Amersham Biosciences, Buckinghamshire). Fifty to one-hundred nanograms of the purified PCR product was used for cycle sequencing, with specific primers ( Additional file 3 ) and the CEQ DTCS dye terminator kit (Beckman Coulter, Buckinghamshire). Excess dNTPs were removed from sequencing reactions using GenClean, a 96-well plate format gel filtration system (Genetix Ltd, Hampshire). Sequencing reactions were run on a CEQ 8000XL capillary sequencer (Beckman Coulter). Primers were designed on generated sequence aided by Eprimer3 [ 22 ] in a primer walking approach to complete sequencing of the full gene. Sequences generated have been submitted to GenBank (Accession numbers AY649696-AY6497242). Sequence analysis Data were analysed and assembled using SeqMan, a component of the DNA Star software package. Multiple alignments were created using BioEdit (Tom Hall, North Carolina State University). Phylogeny inference package Phylip (Joe Felsenstein, University of Washington) was used to compute a distance matrix from protein sequences and build trees illustrating the relatedness of fliC sequences. Some previously published sequences were included ( Additional file 3 ). Polymorphisms postulated to be serotype specific were identified from the alignments of full fliC sequences; in-house programme MOP-UPs [ 23 ] identified motifs and designed primers to user-specified groups of sequences in the alignment (Anthony Underwood, Health Protection Agency, London). Assay design Two multiplex PCRs were designed to amplify polymorphic regions of both g- and non-g complex fliC sequences. Amplicon sizes were approximately 316 bp for g-complex strains, 170 bp – 250 bp, (size varied according to serotype) from non-g strains. The order of nucleotide dispensation was tailored to enable the first two dispensations to act as negative and positive controls. DNA preparation and Pyrosequencing A 1 μl loop of cells was boiled in 100 μl of sterile distilled water for 10 min at 95°C. One microlitre of lysate was used for PCR. Two PCRs were run in parallel to amplify fragments of the fliC gene. Fifty microlitres of PCR product was prepared containing 1 U Taq polymerase, 0.25 mM of each dNTP, 4 mM MgCl 2 . PCR for amplification of g-complex strains used three forward primers: 100 pmol GPYRO-A; 12.5 pmol GPYRO-B; and 12.5 pmol GPYRO-C; and 125 picomoles of reverse biotinylated primer G-REV. PCR for amplification of non-g strains used 14 forward primers (NON-G-PYRO-A, NON-G-PYRO-B etc.) in equal concentrations. Thirteen biotinylated reverse primers (NON-G-REV-A, NON-G-REV-B etc.) were used in equal concentrations. In each 50 μl reaction 125 pmol of mixed forward primer and 125 pmol mixed reverse primer was used. Primer sequences are detailed in Additional file 3 . Thermocycling was performed with an Applied Biosystems 9700 GeneAmp PCR System using a touch-down programme: initial denaturation step of 94°C for 2 min; followed by 17 cycles of 94°C for 20 sec, 66°C (-1°C per cycle) for 30 sec, 72°C for 30 sec; followed by 20 cycles of 94°C for 20 sec, 54°C for 30 sec, 72°C for 30 sec. The excess primers were removed using a filter plate and vacuum system (Genetix Ltd, Hampshire) before visualising the PCR products on the Ready-To-Run agarose system (as previously). Biotinylated single-stranded DNA was immobilized on streptavidin-coated sepharose beads (Amersham Biosciences, Buckinghamshire) with binding buffer. The mixture was agitated at 1400 rpm for 10 min at room temperature. Single stranded DNA bound to beads was isolated from the mixture using a series of wash steps for 5 seconds each in turn, 70% ethanol, 0.2M NaOH and washing buffer. Ninety-six samples were prepared in 2 minutes by automation of strand separation step using a vacuum preparation tool (Pyrosequencing AB, Uppsala, Sweden). A combination of pyrosequencing primers was used for each assay; 20 primers for the non-g complex assay, and three for the g-complex assay ( Additional file 3 ) into which DNA was eluted. Pyrosequencing primers were annealed to single-stranded DNA on the beads by heating to 80°C for 2 minutes and allowed to cool slowly. Single stranded binding protein, enzyme mix, substrate mix and dNTPs (Pyrosequencing) were added sequentially by the instrument according to the programmed dispensation order. Authors' contributions CM carried out the sequencing, constructed the multiple alignments and designed the assays. TP carried out the serotyping. TP advised on Salmonella serotyping and provided strains. CA CM SG TP and JL participated in the design of the study. CA conceived of and coordinated the study. All authors read and approved the final manuscript. Supplementary Material Additional File 1 Amino acid alignment. Amino acid alignment of 106 fliC gene sequences representing 32 H1 alleles. Sequences labelled with _a, _b or _c indicate an H1 allele encoded by multiple sequences (Additional file 2). Codon numbering is in reference to the sequence of Typhimurium_a which represents sequenced strain LT2. Click here for file Additional File 3 Primers used for PCR and Pyrosequencing. Orientation of the primer is represented by F (forward) or R (reverse) and approximate position is given as nucleotide distance from 5' end of fliC *These primers were also used as pyrosequencing primers Click here for file Additional File 2 Sequences used in this study. Sequences labelled with _a, _b or _c indicate an H1 allele encoded by multiple sequences Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514894.xml
545211	Meningitis and Climate in West Africa	null	Many different things combine to cause epidemics of disease. Among these factors are the characteristics of the infecting organism, the resistance of the host, and, as is increasingly realized, climatic conditions. El Niño, the best known climatic disturbance, is caused by a warming of the Pacific Ocean, which then affects the climate globally. Previous work has suggested that this recurring phenomenon can have a profound effect on the incidence of many diseases, including dengue, malaria, and diarrheal diseases. In a paper in this month's PLoS Medicine , Sultan and colleagues from a climate research institute and an infectious diseases center in France looked at the relation between climate and meningitis outbreaks in Mali in West Africa, a region that every year between February and May sees devastating epidemics of meningococcal meningitis affecting up to 200,000 people. The most important recurring climatic event in this region is a dry wind, known as the Harmattan, that blows throughout the winter, causing a drop in humidity and the production of vast quantities of dust. What the authors found was that over the years 1994–2002, the week of the onset of the yearly meningitis epidemic came at around the same time as the peak of one measure of the wind—the sixth week of the year. As Pascual and Dobson say in their Perspective article on this study, “Sultan and colleagues' study is exceptional in that it illustrates a clear relationship between an external environmental variable and the initiation of disease outbreaks.” How do climatic changes influence disease? In some cases, such as the role of flooding in spreading a waterborne disease, the causes are perhaps obvious, but why should a dry wind affect disease incidence? Previous works have suggested that the climate can work in a number of ways, by influencing the life cycle of both disease vectors and the disease-causing organism, and, as here perhaps, by affecting the resistance of the host. Sultan and colleagues speculate that the drying effects of the wind on the mucous membranes could increase the chances of the organism getting established in the human host. Whatever the causes, one very useful feature of climate is that, once the patterns are understood, they can often be predicted. A way of predicting these meningitis epidemics could be enormously useful. Sultan and colleagues looked at only a few years, but if these findings are confirmed over a longer time period, they could make preparing for an epidemic much more efficient.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545211.xml
549588	Case-Based Study: From Prediabetes to Complications—Opportunities for Prevention	A 31-year-old man presents with central obesity, hypertension, and abnormal lipids. How would you manage this patient?	DESCRIPTION of CASE A 31-year-old white male with no significant past medical history is referred by his workplace to a primary care physician for an elevated blood pressure (BP). He presents to the clinic with no complaints. His mother and grandmother both have diabetes, and his father has hypertension. He has had a 15-pound (lb) weight gain over the last year and has become more sedentary. His BP is 142/90 mm Hg, pulse is 88 beats per minute (bpm), weight is 209 lb, and height is 5′ 11″. On examination he displays moderate central obesity, but otherwise the examination is normal. His fasting cholesterol is 228 mg/dl (to convert milligrams per deciliter of cholesterol [total, HDL or LDL] to micromoles per liter, divide by 39), low-density lipoprotein (LDL) is 166 mg/dl, high-density lipoprotein (HDL) is 32 mg/dl, triglycerides (TG) are 223 mg/dl (to convert mg/dl of triglycerides to mmol/l, divide by 89), and fasting glucose is 114 mg/dl (to convert mg/dl of glucose to mmol/l, divide by 18). What Is the diagnosis? This patient meets the diagnostic criteria for the metabolic syndrome as defined by the National Cholesterol Education Program Adult Treatment Panel III guidelines [ 1 ]. Any three or more of the criteria make this diagnosis (see Table 1 ). Intensive lifestyle modifications such as exercise and weight loss should be made to improve cholesterol, blood pressure, and other cardiovascular disease (CVD) risk factors [ 2 ]. It may be timely to address the prevention of diabetes in patients with metabolic syndrome since these patients are at high risk for development of type 2 diabetes. Lifestyle changes delay the onset or prevent the incidence of type 2 diabetes in patients with glucose intolerance, a key feature of metabolic syndrome [ 3 ]. The patient is started on an exercise and weight loss program, sent for nutritional counseling, and scheduled for a return clinic appointment for three months later. Table 1 National Cholesterol Education Program Clinical Identification of the Metabolic Syndrome Adapted from [ 1 ] Two Years Later The patient returns to the clinic two years later. He presents with complaints of increasing frequency of urination and episodes of blurry vision. He has nocturia and has lost 5 lb in the last week. Otherwise, his review of systems is unremarkable. His blood pressure is 146/88 mm Hg, pulse 80 bpm, and weight 216 lb. His fundoscopic examination is normal. He continues to have moderate central obesity. Current medications are a thiazide diuretic, 12.5 mg once daily (QD), started one year prior. A non-fasting blood sugar is 267 mg/dl. Can a diagnosis be made? There are three criteria for the diagnosis of type 2 diabetes as defined by the American Diabetes Association (ADA), of which any one is sufficient to make the diagnosis (see Box 1 ). This patient meets the criteria for type 2 diabetes. He does not need to have a fasting blood sugar done because a random glucose greater than 200 mg/dl with symptoms of diabetes meets the first criterion. Failing to comply with lifestyle modification, his weight has increased 7 lb in two years and likely contributes to his development of diabetes. Of note, his recent weight loss is presumably due to overt hyperglycemia and glycosuria, further underestimating his true weight increase. Box 1. ADA Diagnostic Criteria for Type 2 Diabetes Random plasma glucose ≥200 mg/dl (11.1 mmol/l) and symptoms or Fasting plasma glucose =126 mg/dl a (6.99 mmol/l) or Two-hour plasma glucose =200 mg/dl a (11.1 mmol/l) in oral glucose tolerance test. a In the absence of symptoms, these criteria should be confirmed by repeat testing on a different day. Source: [ 28 ]. His additional investigations are as follows: fasting glucose, 215 mg/dl; hemoglobin A1c (HbA 1c ), 8.6%; and urine albumin-to-creatinine ratio, 2.0 mg/mmol (normal is <2.5 mg/mmol in men and <3.5 mg/mmol in women). LDL is 176 mg/dl, HDL 32 mg/dl, and TG 292 mg/dl. His electrocardiogram is normal. What are the next steps in management at this time? Diabetes management should involve a multifaceted, goal-directed approach, which includes dietary modifications, diabetes education, assessment of blood sugar readings, and pharmacotherapy. The ADA recommends glycemic and other CVD risk factor goals (see Table 2 ), in addition to foot evaluation and screening for nephropathy and retinopathy, for all adults with diabetes [ 4 ]. The patient is started on metformin, 500 mg twice daily (BID) with meals. Therapy with metformin appears to decrease the risk of diabetes-related endpoints, including a reduction in cardiovascular events independent of glycemic control. There is also less weight gain and fewer hypoglycemic attacks than with insulin and sulphonylureas. Therefore, metformin may be an effective first-line pharmacotherapy of choice in these patients [ 5 ]. There are several oral hypoglycemic agents (i.e., sulfonylureas, metformin, acarbose, and thiazolidinediones) that are effective monotherapy for reducing hyperglycemia. Table 2 ADA Summary of Goals in Adult Patients with Diabetes Source: [ 4 ] The patient is also started on low-dose aspirin, indicated for primary prevention of macrovascular disease in people with diabetes who have any risk factors for CVD [ 4 ], and a cholesterol-lowering agent, a statin, for his increased LDL cholesterol [ 6 ]. He is given a glucose meter, is scheduled to have diabetes education classes and diabetes nutritional counseling for a 1,800-calorie ADA diet, and is instructed to record his pre-meal blood sugars. Smoking cessation is another important aspect of diabetes management to address. He returns in three months for follow-up and has an HbA1c of 7.3%, at which time no additional therapy is started. Three Years Later The patient is now 37 years old and returns for a follow-up appointment. He states that he has felt “pins and needles” in his feet and fingertips. He has had difficulty with maintaining erections but has a normal libido. Blood sugars are 160–190 mg/dl in the mornings and 200–240 mg/dl in the evenings, and the patient reports no hypoglycemic events. He has diminished sensation to vibration over his right great toe and left toes and heel with intact monofilament sensation. The remainder of his examination is unchanged. His medications are metformin at 1 g BID, a thiazide diuretic at 25 mg QD, a statin QD, and an aspirin QD. He is 215 lb, BP is 142/86 mm Hg, and pulse is 76 bpm. Recent laboratory tests produced the following results: a HbA1c of 8.1%, a fasting glucose of 212 mg/dl, and normal electrolytes, creatinine, and liver enzymes. Fasting lipids are LDL 144 mg/dl, HDL 33 mg/dl, and TG 209 mg/dl. What additional diagnostic tests would be helpful at this time, and why? A spot urine albumin-to-creatinine ratio is 7.6 mg/mmol. This measurement technique is preferred because it has lower rates of false-positive and false-negative results than a spot urine microalbumin. Persistent microalbuminuria should be confirmed on two or three subsequent readings within a six-month period to rule out false-positive results. The elevated ratio of microalbumin in the urine signifies early nephropathy because microalbuminuria has been shown to progress to macroalbuminuria and eventual nephropathy in type 1 and type 2 diabetes. Any degree of albuminuria is a risk factor for cardiovascular events in individuals with or without diabetes; the risk increases with the level of absolute microalbuminuria [ 7 ]. Therefore, screening for microalbuminuria should be done annually in all people with type 1 and type 2 diabetes [ 8 ]. Annual screening for diabetic retinopathy should be performed in all people with diabetes after an initial evaluation and reassessed more frequently if retinopathy is diagnosed. This patient remains free of retinopathy, but a significant number of patients with type 2 diabetes have retinopathy at the onset of diagnosis owing to the insidious nature of type 2 diabetes and the failure to diagnose type 2 diabetes early. Tight glycemic control can slow the progression of diabetic retinopathy ( Figures 1–3 ) [ 9 ] and help prevent development of proliferative diabetic retinopathy. Figure 1 Very Mild Diabetic Retinopathy Figure 2 Non-Proliferative Diabetic Retinopathy Showing Several Exudates around the Macula Figure 3 Non-Proliferative Diabetic Retinopathy Showing Macular Edema, a Cotton-Wool Spot below the Optic Disk, and a Few Hemorrhages and Exudates What additional pharmacotherapy should be started at this time? The patient has developed neuropathy and erectile dysfunction, both of which are complications of diabetes. He continues to have suboptimal glycemic control; therefore, additional therapy in the form of combinations is appropriate. The patient is started on a thiazolidinedione (TZD) QD. With continued elevated systolic BP >130 mm Hg and diastolic BP >80 mm Hg, an angiotensin-converting enzyme inhibitor (ACE-I) is started. An ACE-I at this time is appropriate for BP control and has the additional preventative effects of reducing progression to nephropathy and CVD events [ 10 , 11 ]. In addition, continued strict BP control is as effective as tight glycemic control in preventing macrovasular disease in diabetic patients and slowing the progression of diabetic nephropathy and retinopathy [ 12 ]. Erectile dysfunction is a complication associated with diabetes and can be an early sign of neuropathy and vascular disease, therefore a phosphodiesterase-5 enzyme inhibitor is an appropriate choice for patients not on vasodilators or with a history of significant CVD. The statin dose is increased to achieve a goal LDL of ≤100 mg/dl. Diabetic neuropathy is a significant cause of morbidity in diabetes, and its progression correlates directly with glycemic control. Tighter glucose control and proper foot care are effective. It is important to continue emphasis on dietary, exercise, and lifestyle modifications in addition to pharmacotherapy. Five Years Later The patient returns to clinic today after spending the last three years overseas and has not seen a physician in two years. He complains of fatigue, occasional blurry vision, awakening three to four times at night to urinate, and diarrhea at least once a week. He says that he has been compliant with his diabetes medications but has gained 15 lb in the last six months. His medications include metformin at 1 g BID, a TZD BID, and an ACE-I QD. His blood sugar is 289 mg/dl (fasting), BP is 130/90 mm Hg, pulse is 88 bpm, and weight is 221 lb. There are no foot sores or ulcers, but he has diminished sensation to monofilament on the plantar surfaces of both feet. The remainder of his examination is unchanged, including normal fundoscopy. His HbA1c is 9.6%, LDL is 143 mg/dl, and spot urine albumin-to-creatinine ratio is 15 mg/mmol. His creatinine and liver enzymes are normal. His pre-meal blood sugars average 210–250 mg/dl. What is the next most appropriate step in his medical management? He continues to have an elevated HbA1c, worsening neuropathy, and weight gain, which prompt a more effective treatment strategy. There are several options for pharmacotherapy available to choose from at this point. The patient could begin a third oral agent after maximizing the doses of metformin and TZD, or he could begin insulin injections with or without additional oral agents. Because of the significant cost associated with three oral medications and his need for further glycemic control, insulin would be an appropriate choice at this time. However, he should be advised of the side effect of additional weight gain when beginning insulin therapy. DISCUSSION This case presentation illustrates an otherwise healthy appearing patient who is found to have the metabolic syndrome and despite evidence-based management develops type 2 diabetes. This patient likely represents the natural history of type 2 diabetes in most patients. Mild hypertension is often the only presenting sign of metabolic syndrome and prediabetes, allowing an opportunity for prevention of type 2 diabetes. There is an association between metabolic syndrome and the development of CVD and type 2 diabetes [ 13 ]. This syndrome is characterized not only by the criteria given in Table 1 , but also by a state of compensatory hyperinsulinemia [ 14 ]. However, a diagnosis of metabolic syndrome alone does not imply diabetes, as patients with metabolic syndrome can have a fasting plasma glucose less than 110 mg/dl. It is the body's ability to maintain glucose utilization and suppress endogenous glucose production in the setting of this compensatory hyperinsulinemia that separates metabolic syndrome from diabetes. The effect of this hyperinsulinemic state in metabolic syndrome is also believed to be involved in excess pro-inflammatory and pro-thrombotic markers associated with the development of diabetes and CVD [ 15 ]. These patients develop diabetes when tissues of the body fail to utilize glucose appropriately owing to increased resistance to insulin and concomitant beta-cell dysfunction of the pancreas [ 16 ]. Metformin is in the class of biguanides and works by decreasing hepatic glucose output and increasing insulin action in tissues. Metformin has been suggested to help prevent the onset of diabetes but is less effective than diet and lifestyle changes [ 3 ]. Other medications shown to possibly delay or prevent the onset of type 2 diabetes are ACE-I and angiotensin II receptor blockers [ 17 , 18 ]. Patients treated with diuretics can progress to type 2 diabetes even though thiazide diuretics are proven effective in treating hypertension [ 19 , 20 ]. Intensive therapy in patients with type 2 diabetes results in a decreased risk of microvascular complications; therefore, it is appropriate to use combinations of medications in patients with suboptimal glycemia [ 21 ]. The class of TZDs works to lower plasma glucose levels by increasing insulin sensitivity in muscle and liver [ 22 ]. TZDs lower mean HbA1c modestly when added to metformin as compared to metformin alone [ 23 ]. Side effects include weight gain and water retention, and patients with a history of New York Heart Association class III or IV heart failure should not use TZDs [ 24 , 25 ]. The pathophysiology of type 2 diabetes involves, in part, a “relative” deficiency of insulin. Although a state of endogenous hyperinsulinemia occurs, the degree of tissue resistance causes a total decrease in “effective” endogenous insulin. Progression of disease is also attributed to worsening beta-cell dysfunction and decreased release of insulin [ 26 ]. Insulin is used in a variety of combinations and is individualized to patient lifestyle. A frequent starting dose consists of a long- or intermediate-acting insulin, such as NPH insulin, divided into morning and evening doses, or insulin glargine given QD, usually at bedtime. The patient whose case is described here was started on NPH at bedtime, which decreases overnight hepatic glucose production such that the patient begins the morning with near-normal glycemia for daytime oral therapy. There may be times when a post-meal surge in glucose requires extra insulin in addition to the intermediate-acting NPH. In such a case, using a short-acting (regular) insulin before meals provides insulin action that closely approximates normal insulin secretion ( Figure 4 ). The rapid-acting lispro and aspart insulins have an even shorter half-life and quicker onset of action than regular insulin. Common empirical initiation doses range from 0.4–1.2 units of insulin per kilogram per 24 hours. Patients should be advised of hypoglycemia and weight gain as the main side effects of insulin therapy. Insulin and insulin-sensitizer combinations significantly improve hyperglycemia; however, there is an increased incidence of heart failure reported with this combination, prompting close monitoring of patients for signs and symptoms of heart failure [ 27 ]. Figure 4 Using a Short-Acting (Regular) Insulin before Meals Provides Insulin Action That Closely Approximates Normal Insulin Secretion In summary, diabetes prevention and management is an important goal in practice. The morbidity and mortality from diabetes is a significant burden to health care, emphasizing the need for effective prevention and control of diabetes in improving outcomes. Editorial Note The management of the patient in this Learning Forum article is in keeping with two national guidelines—those of the United States National Cholesterol Education Program and the ADA. Both peer reviewers pointed out that clinicians in other countries would follow their own national or regional guidelines. For example, the guidelines for the management of type 2 diabetes published by the United Kingdom's National Institute for Clinical Excellence differ in key ways from the ADA guidelines. We as editors debated whether to insist that the authors include guidance from other parts of the world. We decided that as an international journal we should reflect global variations in practice and allow authors to discuss how patients would be optimally managed in their own countries. There is much we can learn from different approaches to clinical practice worldwide.—The PLoS Medicine Editors Useful Links National Institute for Clinical Excellence Clinical Guidelines for Type 2 Diabetes: www.nice.org.uk/pdf/NICE_full_blood_glucose.pdf International Diabetes Federation (European Region) Desktop Guide to Type 2 Diabetes: www.staff.ncl.ac.uk/philip.home/t2dg1999.htm Key Learning Points The natural history of diabetes suggests that it is a progressive disease, and therapy may need to be frequently changed or augmented over time. The diagnosis of the metabolic syndrome should alert primary care physicians to prescribe intensive lifestyle modifications for prevention of diabetes. Strict BP, lipid, and weight control is just as essential as strict glycemic control in preventing CVD in patients with diabetes. Metformin can reduce the risk of CVD in obese patients with diabetes independent of glycemic control. The decision of combination oral therapy with or without insulin should be individualized to optimize glycemic control and reduce micro- and macrovascular complications.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC549588.xml
514704	Maternal microchimerism in the livers of patients with Biliary atresia	Background Biliary atresia (BA) is a neonatal cholestatic disease of unknown etiology. It is the leading cause of liver transplantation in children. Many similarities exist between BA and graft versus host disease suggesting engraftment of maternal cells during gestation could result in immune responses that lead to BA. The aim of this study was to determine the presence and extent of maternal microchimerism (MM) in the livers of infants with BA. Methods Using fluorescent in situ hybridization (FISH), 11 male BA & 4 male neonatal hepatitis (NH) livers, which served as controls, were analyzed for X and Y-chromosomes. To further investigate MM in BA, 3 patients with BA, and their mothers, were HLA typed. Using immunohistochemical stains, the BA livers were examined for MM. Four additional BA livers underwent analysis by polymerase chain reaction (PCR) for evidence of MM. Results By FISH, 8 BA and 2 NH livers were interpretable. Seven of eight BA specimens showed evidence of MM. The number of maternal cells ranged from 2–4 maternal cells per biopsy slide. Neither NH specimen showed evidence of MM. In addition, immunohistochemical stains confirmed evidence of MM. Using PCR, a range of 1–142 copies of maternal DNA per 25,000 copies of patients DNA was found. Conclusions Maternal microchimerism is present in the livers of patients with BA and may contribute to the pathogenesis of BA.	Background Biliary atresia (BA) is a cholestatic disease of infancy characterized by the destruction of the biliary tree. [ 1 - 3 ] Both the intra-and extra-hepatic biliary ducts demonstrate evidence of a progressive destruction. This results in cholestasis, hepatic fibrosis and eventually cirrhosis. BA is associated with significant morbidity and mortality. Although the incidence of BA is 1 in 10,000 to 14,000 live births, [ 4 , 5 ] it accounts for over 40% of the neonatal cholestatic liver disease in Europe and the United States. [ 6 ] Prior to the hepatic portoenterostomy and liver transplantation, infants with BA had less than a 10% survival at 3 years of life and almost 100% mortality at 7 years of life. [ 7 ] In the United States, it is the leading cause of pediatric liver transplantation. [ 8 ] The etiology of biliary atresia remains unknown. Many hypotheses on the etiology of BA exist. Two leading hypothesis are that BA occurs as a result of ductal plate malformations occurring during development of the liver, or as a result of an immune mediated process triggered by yet to be determined stimulus. [ 9 ] As more knowledge accrues about the histology and immunologic characteristics of BA, the more it appears to be a progressive immune mediated process. Graft versus host disease (GVHD), seen after allogeneic hematopoietic stem cell transplantation, is an immune mediated process triggered by the transfer of alloimmune cells from a donor to a host. GVHD shares many similarities with BA. Both BA and GVHD are characterized by a lymphocytic infiltration around the portal triad and damage to the biliary ducts. [ 10 ] The predominant lymphocytes in both disease are CD4 + T – helper (Th) 1 cells. [ 11 - 14 ] As with BA, in GVHD there is also an increase in cell adhesion molecules and human leukocyte antigen (HLA) class II markers. [ 11 ] Given the similarities between BA and GVHD, we hypothesized that a contributing etiology of BA could be an alloimmune reaction such as in GVHD triggered by maternal microchimerism. Maternal microchimerism occurs when a small number of maternal cells are transferred to the offspring during pregnancy. This is known to occur in up to 40% of normal pregnancies. [ 15 , 16 ] In addition, a clinical precedent of maternal microchimerism causing hepatic GVHD in children with severe combined immune deficiency (SCID) exists. [ 17 ] The aim of this study was to determine the presence and extent of maternal microchimerism in the livers of infants with BA. Methods This study was performed with the approval of the Committee of Human Research at USCF (H9048-20247-01). Cases of BA were identified through a data search in the Anatomic Pathology CoPath system by diagnosis or during patient medical visits to the UCSF Division of Pediatric Gastroenterology, Hepatology, and Nutrition. An explanation of the study was given to each study candidate. Written consent was obtained from each study participant. Fluorescent in situ hybridization (FISH) of male BA livers We modified a previously reported method of FISH, [ 18 ] using X and Y-chromosomes probes. Y-chromosomes were stained with a green fluorescent dye, fluorescein isothiocyanate (FITC). X chromosomes were stained with a red fluorescent dye, cyanine 3 (Cy-3). Nuclear material was stained with a blue fluorescent dye 4", 6"-diamidino-2-phenylindole (DAPI). After initial digestion and staining of the liver specimens, we examined the slides for evidence of female cells, depicted by two red signals, i.e. X chromosomes, with no green signal within the blue nuclear material. Slides were analyzed in a blinded fashion. HLA typing Patients with BA and their mothers were HLA typed. The HLA typing HLA-A, -B, and -DRB1 alleles of the child and mother were determined by sequence specific PCR (SSP) (Pel-Freez Clinical Systems, LLC ® , Brown Deer, WI, USA). Immunohistochemistry Frozen tissues sections of BA patient's livers (5 μm) were fixed in acetone for 10 minutes at 4°C then washed in PBS (5 minutes centrifugation × 3). Sections were blocked with Protein Block (Dako, Carpinteria, CA, USA) for thirty minutes at room temperature. Sections were then incubated with anti-HLA-B14 mouse monoclonal antibody (US Biological, Swampscott, Mass. USA) then washed in PBS. Sections were incubated in goat anti-mouse conjugated with FITC for 30 minutes at room temperature. Sections were rewashed and then counterstained with DAPI. Slides were then examined using a fluorescent microscope. Kinetic Polymerase Chain Reaction (kPCR) Using the HLA types of the patients with BA and their mothers, and a previously reported method of kPCR, evidence of maternal DNA was explored within the liver biopsy specimens of explanted BA livers. [ 18 ] The minor modifications to the kinetic PCR protocol included use of iCyler from BioRad (Hercules, Ca, USA) for amplification. Results Detection of female cells in male BA liver biopsies Using FISH, we examined 11 male BA liver biopsies and 4 male NH liver biopsies. After initial digestion and staining of the liver specimens, we were able to interpret 8 of the BA and 2 NH liver biopsy specimens (Table 1 ). Three BA and 2 NH biopsies underwent poor digestion and had no discernable signal. Figure 1 shows a liver from a male infant with BA. A male cell, depicted by a red signal, the X chromosome, and green signal, a Y chromosome within the blue nuclear material, clearly can be seen (A). In the same specimen, one can also see a female cell, depicted by two red signals, both X-chromosomes with no green signal within the blue nuclear material (B). 7/8 BA specimens had evidence of maternal microchimerism. The number of maternal cells, per biopsy slide, was 2 – 4 cells. Neither of the NH specimens had evidence of maternal microchimerism. Table 1 Overview of maternal microchimerism in patients with BA and NH Diagnosis Chimerism Method # of Maternal cells/DNA per slide (FISH) or per 25,000 copies of patient's DNA (kPCR) BA Present FISH 2 maternal cells per slide BA Present FISH 2 maternal cells per slide BA Present FISH 4 maternal cells per slide BA Present FISH 2 maternal cells per slide BA Present FISH+immunokistochemistry 3 maternal cells per slide BA Not interpretable FISH --- BA Present FISH 2 maternal cells per slide BA Present FISH 3 maternal cells per slide BA Not interpretable FISH --- BA Not interpretable FISH --- BA None detected FISH 0 maternal cells per slide BA Present kPCR 3 copies of maternal DNA per 25,000 copies of patient's DNA BA Present kPCR 1 copy of maternal DNA per 25,000 copies of patient's DNA BA Present kPCR 10 copies of maternal DNA per 25,000 copies of patient's DNA BA Present kPCR 142 copies of maternal DNA per 25,000 copies of patient's DNA NH None detected FISH 0 maternal cells per slide NH None detected FISH 0 maternal cells per slide NH Not interpretable FISH --- NH Not interpretable FISH --- Figure 1 A male cell, depicted by a red signal, the X chromosome, and green signal, a Y chromosome within the blue nuclear material, can be seen in both male BA liver specimens (A&B). In the same specimen, one can also see a female cell, depicted by two red signals, both X-chromosomes with no green signal within the blue nuclear material (arrow). Detection of maternal HLA antigen among BA liver samples To further investigate our findings, three patients with BA and their mothers were HLA typed. Using the HLA marker B14, we examined the BA livers for evidence of maternal microchimerism using immunohistochemistry techniques. An HLA-B14 positive patient served as our positive control (Figure 2 ). Specimen B, our negative control, was a patient who was, along with his mother, negative for HLA-B14. Specimen C, our test specimen, was HLA-B14 - , with an HLA-B14 + mother. Specimen A (positive control) has a bright signal for HLA-B14 while there is only background staining for HLA-B14 in specimen B (negative control). Specimen C, the test specimen, has isolated scattered bright signals suggesting maternal microchimerism. Figure 2 Using the HLA marker B14, we examined the BA livers for evidence of maternal microchimerism using immunohistochemistry techniques. An HLA-B14 positive patient served as our positive control (A). Specimen B, our negative control, was a patient who was, along with his mother, negative for HLA-B14. Specimen C, our test specimen, was HLA-B14 negative, with an HLA-B14+ mother. Specimen A (positive control) has a bright signal for HLA-B14 while there is only background staining for HLA-B14 in specimen B (negative control). Specimen C, the test specimen, has isolated scattered bright signals suggesting maternal microchimerism. Detection of maternal DNA by kPCR Finally, using polymerase chain reaction, in conjunction with the HLA typing of patients and mothers, we were able to affirm that maternal microchimerism occurs in the BA livers. An additional four fresh frozen liver specimens of BA infants, obtained at the time of transplantation, were examined for maternal DNA. All the livers had evidence of maternal microchimerism, with the range of 1 to 142 copies of maternal DNA detected per 25000 copies of patients' DNA. Figure 3 is a representative kPCR for maternal HLA-B40 in the second liver sample. Figure 3 Representative kinetic PCR (kPCR) data for maternal HLA-B40 in BA liver sample. SYBR Green fluorescence is plotted on the y-axis as a function of amplification cycle number on the x-axis. The upper panels depicts results for standard dilutions of HLA-B40 [left to right curves: 25000, 10000, 1000, 100,10, and 1 genomic equivalence (gEq)]. A single copy of template produces fluorescent signal after approximately 36 cycles of amplification. The lower panel shows results from three liver replicates and two negative (no-template) controls. The three liver replicates have a positive signals at 2–5 gEq, while the negative controls remained negative through 50 cycles. In all eleven of twelve patients with BA had evidence of maternal microchimerism by FISH or kinetic PCR, while neither of the two neonatal hepatitis patients had evidence of maternal microchimerism (p = 0.03). Discussion BA is a progressive cholestatic disease of infancy, which is characterized by a mild to moderate lymphocytic infiltration within the extra and intrahepatic bile ducts. It is plausible, that maternal microchimerism may play a role in the etio-pathogenesis of BA by causing an alloimmune reaction given the similarities between BA and GVHD. We have shown that maternal microchimerism is present within the livers of patients with BA. Maternal microchimerism occurs when maternal cells reside in the body of offspring. Maternal-fetal lymphocytic transfer is known to occur during pregnancy starting as early as the tenth week of gestation and continuing up to delivery. [ 19 ] The number of cells that traverse the placenta increases throughout this period. Schroder et al [ 15 ] demonstrated that approximately 1/10 infants has about 0.07% maternal lymphocytes at the time of birth and more recent findings by Lo et al. [ 16 ] have indicated the presence of maternal cells in over 40% of fetal blood samples. Disease has been shown to occur in mothers who have had fetal microchimerism, and children/adults who have had maternal microchimerism. Children who have immunodeficiencies are at greater risk for graft verses host disease owing to engraftment of maternal lymphocytes. In both SCID and DiGeorge syndrome, maternal microchimerism and GVHD have been well described. In a study by Susanne Müller et al., 121 patients with SCID were evaluated for maternal microchimerism using HLA typing. Maternal cells were found in 48 patients, with 19 patients showing signs of GVHD. GVHD manifested itself in the skin and in the liver. [ 20 ] There have been numerous case reports showing GVHD in infancy of patients with DiGeorge. Manifestations of this disease include skin, gastrointestinal tract and liver involvement. [ 21 ] The histologic and immunologic similarities of BA and GVHD are striking. The site of damage in BA and GVHD after bone marrow transplantation is the same. In each, lymphocytes congregate around the bile ducts. The damage occurs to both the intra-and extrahepatic biliary tracts. In a mouse model of acute GVHD, Nonomura et al. showed that transfer of allogeneic cells set along minor HLA mismatch can cause damage to both the intra and extrahepatic biliary ducts. Interestingly, the timeframe in this mouse model of acute GVHD, in terms of lymphocytic infiltration and fibrosis, appear similar to that of BA. [ 14 ] Initially, a peak of lymphocytes around the bile ducts occurs about 2 weeks after transfer of allogeneic cells from donor to host mouse; as the lymphocytic infiltration subsides, liver fibrosis increases. This correlates with disease progression in BA, where initial diagnostic biopsies of BA livers usually show a larger lymphocytic infiltration, and less fibrosis, as compared to biopsies done later, i.e. at the time of liver transplantation. [ 22 ] The lymphocytic infiltrates in both BA and GVHD are predominantly CD4 + T lymphocytes. The genes in BA livers showed differential lymphocytic function, with activation of osteopontin, a regulator of cell-mediated immunity in Th 1 cells, and interferon gamma. [ 23 ] Similarly, in GVHD, the predominant leukocyte is the CD4 + T lymphocyte. Although a variety of complex mechanisms are involved in causing the end organ damage in GVHD, evidence exists showing similarities in effector mechanisms. In a SCID mouse model of acute GVHD, an increase in interferon-gamma secretion with a synchronized increase in activated Th cells was seen during acute GVHD. [ 24 ] The inflammatory responses in both BA and GVHD are also associated with increased expression of adhesion molecules such as CD54, and increased class II HLA markers, such as HLA-DR. HLA-DR and CD54, in both BA and GVHD, are seen predominantly around the bile ducts. [ 11 , 25 , 26 ] Maternal microchimerism is not a rare occurrence in healthy individuals, but is usually not associated with disease. The high occurrence of maternal microchimerism in healthy individuals has been suggested to have a tolergenic effect that may contribute to long-term microchimerism. [ 27 ]Additionally, in utero transplantation of haploidentical cells does not always lead to immune tolerance [28] and may lead to immune sensitization. Thus, the immunological consequences of the migration of maternal cells to the fetus appear to be variable. In most cases the maternal cells are likely to be cleared by the host's immune system or they may escape destruction by the immune system leading to engraftment. Engraftment of maternal immune cells in the fetal biliary tract may result in an immune reaction against the host cholangiocytes. This is what we believe may occur in infants with BA. Alternatively, engrafted maternal cells in the fetus may subsequently be rejected by the immune system of the offspring, leading to destruction of the biliary tree. Maternal microchimerism occurs in the livers of patients with BA. Given the previously well-described relationship between microchimerism and GVHD, and the similarities between BA and GVHD, these findings indicate a potential etio-pathogenisis for BA. Further investigations into the role of maternal microchimerism in BA are warranted. Competing interests None declared. Author's contributions DLS conceived of the hypothesis and contributed to the design and coordination of the study; he also drafted the manuscript. PR and MBH participated in the design of the study and manuscript preparation. DK carried out the kPCR and HLA typing analyses. GM performed the FISH analyses. LBL carried out the kPCR and HLA typing analyses and participated in the study design. MOM participated on the study design and coordination, immunohistochemistry stains and the manuscript preparation. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514704.xml
555758	JAtlasView: a Java atlas-viewer for browsing biomedical 3D images and atlases	Background Many three-dimensional (3D) images are routinely collected in biomedical research and a number of digital atlases with associated anatomical and other information have been published. A number of tools are available for viewing this data ranging from commercial visualization packages to freely available, typically system architecture dependent, solutions. Here we discuss an atlas viewer implemented to run on any workstation using the architecture neutral Java programming language. Results We report the development of a freely available Java based viewer for 3D image data, descibe the structure and functionality of the viewer and how automated tools can be developed to manage the Java Native Interface code. The viewer allows arbitrary re-sectioning of the data and interactive browsing through the volume. With appropriately formatted data, for example as provided for the Electronic Atlas of the Developing Human Brain, a 3D surface view and anatomical browsing is available. The interface is developed in Java with Java3D providing the 3D rendering. For efficiency the image data is manipulated using the Woolz image-processing library provided as a dynamically linked module for each machine architecture. Conclusion We conclude that Java provides an appropriate environment for efficient development of these tools and techniques exist to allow computationally efficient image-processing libraries to be integrated relatively easily.	Background Three-dimensional (3D) images are now commonplace in biomedical research. Techniques for direct capture of 3D data are widespread and new techniques are becoming available, [ 1 , 2 ] to complement existing sectioning methods [ 3 ], confocal and micro-CT/MRI [ 4 ]. In addition such data is being stored in databases that can be accessed freely (EADHB[ 5 ], EMAP[ 6 ], BIOIMAGE[ 7 ], and MRIMA[ 8 ]) and many more such atlases and bioinformatics resources will become available. There are a number of tools available for browsing such data, but they are either commercial with a significant cost for the user (e.g. AVS/Express, VolRen, Amira, Analyse) or free but tied to a specific architecture. Systems based purely on an architecture neutral language such as Java (e.g. ImageJ[ 9 ]) can be slow when processing large 3D volume images and have not been developed with the 3D atlas browsing application in mind. The purpose of this work is to combine the machine-architecture independence of Java, with a highly portable, freely available fast and efficient C-coded image processing library tuned to the requirements of the atlas browsing and data analysis task. The Java Atlas-Viewer (JAtlasView) interface has been developed as a series of modules that can be readily re-used within other applications to build more complex interfaces. The Java interface elements and the image processing library can be downloaded from the EADHB and EMAP web-sites. 3D images are regularly captured as part of biomedical research. In many fields the most useful and regularly used visualisation of the grey-level or colour voxel image is to view sections. These are 2D images generated by digitally cutting throught the volume and mimic the traditional mechanism of physical microtome sectioning for revealing detailed structure. The benefit of digital models is that the sectioning plane, orientation and position, can be selected arbitrarily to suit the required usage and the volume can be scanned interactively. For the expert viewer, digital re-sectioning is sufficient for data-analysis but for others, panning through the volume at non-standard angles leads to disorientation. In addition if used in conjunction with atlas information in which the histology images are segmented in terms of the recognisable tissues, the building of a 3D view of the tissue/anatomical components is very difficult, particularly when learning the anatomy. This orientation and structural visualisation problem is solved by using 3D visualisation of the underlying tissue coupled with interactive feedback of the section location within the volume. The basic structure of the JAtlasView is therefore a combination of a 3D feedback window with a number of section views. Each section view is independent and feedback is provided by displaying the position of the section within the 3D volume either as a simple polygon indicating the plane of section or as a full grey-level image, displayed appropriately in 3D. In addition each section will display the intersection with all other sections currently being viewed. In this short note we describe the structure of the software and the functionality of the interface. This application is directed to the use of the EADHB and EMAP atlases and for browsing 3D grey-level data. In the first instance the data is formatted as a Woolz image structure [ 10 ], tools are available for data conversion and future versions will include this as standard. Implementation The software design has been developed to meet a number of code requirements: • portability to all major architectures – Unix/X11, Microsoft Windows and Macintosh, • fast and efficient image processing, compatible with existing formats and interfaces, • freely available code and modular design so display elements and functionality can be easily included in other applications and • the user-interface should be mappable to the "look and feel" of the specific machine window system. The portability and user-interface behaviour requirements are satisfied by using Java as the language and environment for the user interface level. For image processing we have adopted the ANSI standard C image processing library Woolz. This already includes the required functionality for calculating and manipulating section views through 3D voxel images and is open-source software. A potential problem with Java is that it can be very inefficient for heavy numerical work (such as image processing) and the effort required to port existing libraries (for example Woolz is 185 K lines of code) to Java is too high. To solve this we use the tools within Java for accessing "native" code so that the computational work is undertaken in C. The management and coding of the interface is potentially time-consuming and prone to error with any small change in the C code requiring complementary effort to modify the native interface code. We have addressed this problem by implementing an automated method which will build the interface directly from the C-library header files. By adopting a standard convention for function prototyping it is possible to use a parser generator, javacc[ 11 ] to build a java program that can analyse the C-headers and automatically generate the Java class files and matching C-library files required for the Java native interface (JNI). This has made it possible to relegate generating the interface to an automatic process hidden from the primary code develoment, in fact without this development the system would be very difficult to manage. Two other key choices have been made in the design of the code structure. The first is that the 3D visualisation and feedback should be developed at a level independent of the underlying hardware within an environment that allows a high level of abstraction of the 3D view. The java 3D extension to the core Java environment provides such a model and we have adopted this as standard. Java 3D is available for all Java 2 platforms. The second key choice is that the software will be delivered using Java Webstart[ 12 ]. This is a freely available application that will download code across the internet and check system, version and supplementary module requirements. In addition it will start the application and maintain a local cached version. The local cache will be used for fast start if it is the same version as currently available at source or if the machine is off-line. Source code is maintained with CVS [ 13 ] for version management and tracking and GNU gmake for compilation. The interfaces are developed using Borland JBuilder[ 14 ] or a standard editor (vi) and documented using Javadoc/Doxygen[ 15 ]. Help is provided in two ways, the first is a simple popup "balloon" help on mouse-over and as a series of help files arranged using JavaHelp[ 16 ] which provides an indexing, search and context help facility. The help html files are generated using DreamWeaver [ 17 ] and maintained in a CVS repository. Java is now widely used and the first choice for new applications that require portability across machine architectures. It is a strict object-oriented language and interfaces adhere to the model-view-controller (MVC) design pattern [ 18 ]. Java also defines a standard under the name java-bean , that components should meet to guarantee the MVC behaviour and enable easy re-use in other applications using CASE tools. We have adopted this standard for the JAtlasViewer application so that individual interface elements, e.g. the section panel or even our extended view of the slider, can be used simply and conveniently in other code. Results The user interface, shown in figure 1 , has a primary window for the 3D view and top-level menu options, and a number of section-views for visualising the virtual sections cut through the data. The basic functionality of the viewer is to allow interactive digital resectioning of a 3D grey-level or voxel image. The special feature of this viewer is that any number of section views, each with an independent and arbitrary orientation and position can be displayed. To aid navigation through the volume a 3D feedback window is provided. This displays the bounding box of the 3D volume and a transparent surface, of e.g. the embryo model. In addition feedback of the current section position is provided in a number of selectable options: an intersecting polygon of the plane with the bounding box, display of the plane filled with a solid colour and display of the image of the section mapped onto the plane in the 3D view. With appropriate data, the JAtlasViewer will import a mapped "anatomy". This is in two parts, a hierarchy of terms and a set of "domains" linked to specific terms in the hierarchy. The domains are 3D binary images which identify the region of space or set of voxels within the grey-level image associated with that term. The anatomy will then be used to provide feedback within the section views. These anatomy options, the controls for the section views and the main window options are discussed below. Main dialog When the application is invoked a top-level dialog is presented to the user. Before anything can be displayed the user must select a grey-level 3D image. Currently this must be formatted as a Woolz image, but converters for many 3D formats are available from the EMAP web site. Once read in, the bounding box of the 3D voxel image will be displayed in the main window along with a surface representation of the data if available. This 3D view can be manipulated interactively using the cursor to provide views from arbitrary orientations and positions. The menu options of the primary window are: File Commands to open image data, save views, save and restore settings, recent file-list and quit. View Section Select a section view through the voxel model. A new window will display one of the pre-set sections which are transverse, frontal and sagittal planes if the image model is appropriately aligned. Each of these can be set to display views at arbitrary orientations and locations within the 3D volume image. Anatomy If the voxel model data is configured with a set of anatomical regions, these can be selected from the menu and displayed in the section views. For the EADHB and EMAP atlases the menu hierarchy corresponds to the HUMAT and EMAP anatomy ontologies. 3D View Options to control the 3D visualisation in the main window, toggle the visibility of 3D surface, bounding box and intersection lines, display the focus section and selected anatomy. Orientation Preset 3D orientations to provide standard viewing directions. Help On-line help menu. The 3D view window displays the bounding box of the opened volume and a transparent view of the embryo surface. This surface is pre-determined and stored in the visualization toolkit (VTK[ 19 ]) format. The 3D rendering is programmed in Java 3D, the objects (surface and bounding box) inside the 3D view window can be freely interactively manipulated with controls (using button drag) for rotation, translations and zoom (translation towards the viewer). If an anatomy hierarchy and associated data files are provided then an additional window will allow browsing through the ontology and selection of components for display both in the section views and the 3D view window. As for the embryo surface, the surface models are pre-calculated and stored in VTK format. The data layout recognized by the JAtlasViewer is described in detail on the EMAP web-site. Section views Each Section View is displayed in its own Section Viewer, either inside the main window (Microsoft Windows style) or in an independent external window. Section Viewers are Java components that can be easily imported into other applications. The primary viewing control is to move the view plane-parallel through the image volume as a form of "digital microtome" with section thickness determined by the underlying resolution of the 3D image, i.e. moving the microtome by a single step will move to the next voxel in the stack. The assumption is that once the section orientation has been determined the typical use will be to explore the volume in this fashion. The section position is determined by the "distance" parameter which is the voxel distance from the fixed point (by default in the centre of the bounding-box). Section orientation is selected by setting a number of view-angles. These control the view-direction which is perpendicular to the view-plane. We use the standard viewing angles defined by [ 20 ] which are related to the Euler angles of rotation [ 21 ]. Two of the angles determine the view-direction and the third is rotation around that direction. These angles can be understood in nautical/aeronautical terms as pitch, yaw and roll respectively. These viewing controls are hidden by default. In addition to the primary view-direction controls there are options to assist navigation. These are View-mode: options for automatic roll determination in terms of the pitch and yaw values. Fixed-point: select the fixed point used as the centre of rotation. The effect of setting this is to keep that voxel in view for all view-directions provided the "distance" is zero. Fixed-line: set a second fixed-point and constrain the view so that both fixed points remain in the section. The effect of this is to reduce the degrees of freedom to a single parameter of rotation around the line between the two points. The remaining controls for each section view are to set the feedback options including between section views, between the section view and the 3D view and to allow saving of the view and its settings (view parameters). The within view and between views feedback options are provided by the "Show" menu. This provides toggle controls to enable: • cursor position in the reference image coordinate space and image grey-value to be displayed, • line of intersection with section views. If two views intersect then the line of intersection is displayed in the appropriate colour, • anatomy feedback – shows the domain and name of the anatomical component under the current cursor position, • visible fixed point, • visible fixed line. The 3D view can provide feedback of the viewed sections in terms of the 3D volume. For most users these are important aids to understanding the position and direction of the viewed section. Most publications adhere to a convention for displaying section images, with this interface it is possible to view section data at any orientation and direction, i.e. depending on the view-direction the section may appear "reversed", so positional and directional feedback is critical. The positional feedback is provided in a number of forms but all indicate the intersection of the viewed plane with the bounding-box of the reference image. The most informative choice is to use texture mapping to render the grey-level image of the section into the 3D view. This is computationally expensive and so two other options are provided. These use the intersection polygon between the section plane and bounding box, either as-is, or filled with solid colour. The directional feedback is optional and provided by an arrow displayed in the 3D view. Anatomy manager The primary purpose of the JAtlasViewer is to provide an integrated viewer for 3D atlases . These comprise a grey-level (or potentially colour) reference image and a set of domains or regions which are associated with terms in a text hierarchy. For a geographic atlas these would correspond to the physical geography and the areas associated with individual countries. The hierarchy would then list the country names, perhaps under continents and split into counties. For EADHB and EMAP the reference image is the voxel reconstruction of the embryo and the domains are delineated anatomical components. The hierarchy of terms are the corresponding anatomy ontologies [ 22 , 23 ]. The user can select anatomical terms from the ontology for display in the section and 3D views. Once selected the component is handled by the Anatomy Manager (see fig 2 ) which controls the display properties visibility and colour. The anatomy-manager displays the full component name, visibility control toggles, colour chooser and a delete button. This style has been adopted because the number of possible component selections is large (15–500 depending on stage) and thus the user requires detailed control. In addition, although only selected terms in the anatomical hiearchy have corresponding domains defined, combinations of domains are generated "on-the-fly" so that larger scale structures can also be visualized. The colour chooser button allows the user to change the colour of an anatomy component using a standard color chooser dialogue. The change is reflected immediately in all open Section Views and and the 3D feedback window.. The text field displays the full name of the anatomy component. Anatomy components fall into 2 broad hierarchies starting either at embryo or extra-embryonic component . The intervening higher level structures are separated with "/" (slash) and the final part of the name is capitalised. An asterisk following a name indicates that this is an atomic component, referred to in the anatomy menu as a ( domain ). Anatomical components are selected from the anatomy menu using a left mouse click. Higher level components or structures may also be selected from the anatomy menu using a right mouse click or a combination of the shift key and (left) mouse click. The anatomy name may be scrolled by dragging the mouse left or right inside the text box. The visibility toggles select whether a component is displayed in the section views and in the 3D feedback window. This fine control helps the process of analysis and allows the user to build up a visualization showing all or parts of the anatomy. The delete is a toggle control which removes an anatomy component from the table. Conclusion 3D images are in widespread use in medical and biological research and there are a large number of options to view this data, but many of these are commercial and expensive, and are architecture and operating system dependent. More recently atlases and spatially mapped databases in biomedicine have been developed and whilst these packages can provide solutions for browsing this data we believe a simple, free-to-use, open-source and architecture-neutral solution provides a useful tool for biological research and teaching. The JAtlasViewer is intended to fill this requirement. The viewer provides the browsing functionality to locate and display arbitrary sections through the data with simultaneous 3D display. The JAtlasVIewer can also read and display a full anatomy atlas. The JAtlasViewer is programmed in Java. The 3D programming technology is Java3D, which is a wrapper to the OpenGL or DirectX libraries. The Java and Java3D runtime environment are freely available from the Sun Microsystems web site and in most systems Java is pre-installed. These techniques minimize the coding work and developing time. The file size of the JAtlasViewer is less than 1.5 MB. Java WebStart manages the deployment, installation, upgrade and launch via a simple click on a html page link or an icon in the WebStart application. It is portable to any operating system to which Java has been ported and is currently available for Windows, Linux, Solaris and Mac OS. The JAtlasViewer design is of reusable and extensible components. Based on the viewer a 3D tie-point collector for capturing 3D to 3D correspondences, and an atlas viewer that can also import gene expression data, have been developed. Availability and requirements • Project name: The Mouse Atlas Project • Project home page: • Application download: • Operating system(s): Solaris, Linux, Mac OSX, MS Windows. • Programming language: Java, ANSI C. • Other requirements: Java 1.4, JavaDoc, Java 3D. • License: GNU GPL • Any restrictions to use by non-academics: None Authors' contributions Authors GF and NB undertook the main Java development and implementation, BH and RB develop and maintain the Woolz image processing library and BH implemented the automatic generation of the JNI. DD, JK, MS and SL all contributed to the design and testing of the interface and the preparation of the Atlas data for use with the tool.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555758.xml
529254	Peroxynitrite-mediated inactivation of heme oxygenases	Background Endogenous nitric oxide (NO) and carbon monoxide (CO) are generated by nitric oxide synthase and heme oxygenase, respectively. Like NO, CO has been accepted as an important cellular signaling molecule in biological systems. An up-regulation in both gene and protein expression of heme oxygenase-1 (HO-1) under oxidative/nitrosative stress has been well documented, and the protective role of HO-1 and HO-2 against oxidative damage is proposed. However, data on the direct effect of reactive oxygen/nitrogen species (ROS/RNS) on HO function is incomplete. Using gas chromatography to quantify carbon monoxide (CO) formation from heme oxidation, we investigated the effects of peroxynitrite (ONOO - ) on the in vitro catalytic activity of rat spleen (HO-1) and brain (HO-2) microsomal heme oxygenases. Results Exposure to ONOO - led to concentration-dependent but reversible decreases in the activity of microsomal rat spleen and brain HO activity. Spleen HO activity was 100-fold more sensitive to ONOO - -dependent inactivation compared to that of the brain, with IC 50 values of 0.015 ± 0.005 mM and 1.25 ± 0.25 mM respectively. Inhibition of both rat spleen and brain microsomal HO activity was also observed with tetra-nitromethane, a tyrosine nitrating agent, as well as two NO donors, S-nitrosoglutathione (GSNO) and diethylamine NONOate (DEA-NONOate). However, no additive effect was found following the application of NO donors and ONOO - together. Conclusion These results indicate that ONOO - may regulate HO-1 and HO-2 activities by mechanisms that involve different interactions with these proteins. It is suggested that while nitration of tyrosine residues and oxidation of sulfhydryl groups may be involved, consideration should be given to other facets of ONOO - chemistry. This inhibition of HO activity offers a mechanism for cross talk between the nitric oxide synthase and HO systems.	Background Heme oxygenases (HO, EC 1.14.99.3) are a highly conserved family of proteins that catalyse the oxidative cleavage of heme at the α-meso carbon to yield equimolar amounts of iron, carbon monoxide (CO) and biliverdin. Biliverdin is subsequently reduced to bilirubin by biliverdin reductase. Three distinct isozymes of HO (HO-1, HO-2 and HO-3) have been identified. HO-1 (the inducible isoform) is predominantly expressed in the spleen, the primary site of heme catabolism but has been detected in many different tissues including the liver and the kidney. Several substances and conditions may induce the expression of HO-1. The involvement of HO and products of heme catabolism have been studied extensively with respect to oxidative stress, ischemia, hypoxia and protection against transplant rejection [ 1 - 4 ]. HO-2 (the constitutive isoform) is predominantly expressed in the testes and the brain where HO-2 dependent CO production is thought to aid neuronal function [ 5 - 7 ]. HO-3 is also a constitutive isoform, which shares 90% homology with HO-2 but has very limited catalytic function [ 8 ]. Increasing amounts of evidence suggest that products of heme catabolism have cytoprotective roles such as anti-inflammation, anti-apoptosis and anti-proliferation. Biliverdin and bilirubin have anti-oxidant and anti-inflammatory properties [ 9 - 11 ], while iron is known to regulate transferrin, ferritin and nitric oxide synthase gene expression [ 12 , 13 ]. An up regulation in the synthesis of transferrin and ferritin enhances the binding, transport and storage of iron thus serving as an important control mechanism against the oxidative effects of iron. CO, like NO, has been accepted as an important cellular signalling molecule in biological systems. For example, both NO and CO are known to activate soluble guanylyl cyclase, resulting in elevated cGMP and the cGMP-mediated dilatation of blood vessels. CO also mediates vasodilation by directly activating the calcium-dependent potassium channels in vascular smooth muscle cells [ 14 , 15 ]. In addition, CO inhibits platelet aggregation and proliferation of vascular smooth muscle cells, inhibits apoptosis, and stimulates angiogenesis [ 16 - 19 ]. Because of the diversity in the effects of heme catabolism, several studies have suggested that induction of HO-1 expression by oxidising agents may serve as a defense mechanism against oxidative stress in vivo . For example, an induction in the expression of HO-1 prevents superoxide associated endothelial cell sloughing in diabetic rats [ 20 ]. Similarly, it has been demonstrated that ONOO - , a potent oxidizing agent generated by the interaction of NO and superoxide radical [ 21 ], causes a concentration-dependent increase in HO-1 protein expression and enzyme activity in rat aortic endothelial cells [ 22 - 24 ], as well as human colorectal adenocarcinoma cells [ 25 ]. These studies indicate that ONOO - regulates the expression of HO-1 and that the heme oxygenase pathway contributes to protection against the cytotoxic effects of ONOO - which are due to its reactivity with cellular macromolecules such as the covalent modification of tyrosine, cysteine, methionine or tryptophan residues, oxidation of nucleic bases or the scavenging of cellular antioxidants such ascorbate and urate [ 26 ]. It is proposed that the ONOO - -mediated HO-1 induction might occur via an interactive signalling mechanism that modulates oxidative stress responses but direct effects of ONOO - on HO activity have not been studied. In this work, we examined the effect of ONOO - on HO catalytic activity in rat spleen and brain microsomes respectively. Results Effect of ONOO - and TNM on Microsomal HO activity Exposure of either rat spleen or brain microsomes to ONOO - resulted in decreases of HO activity in a concentration dependent manner (Figure 1A and Figure 1B ). HO-1 (spleen microsomes) was more sensitive towards ONOO - -mediated inactivation compared to HO-2 (brain microsomes) (Figure 1A and Figure 1B ). The IC 50 values for inhibition of HO activity in rat spleen and brain microsomes were 0.015 ± 0.005 mM and 1.25 ± 0.25 mM, respectively. The same concentration of degraded ONOO - did not show any effects on HO activity in rat spleen or brain microsomal fractions. Maximal inhibition for microsomal HO-1 and HO-2 activity was approximately 70%, beyond which there was no further inhibitory effect with increasing concentrations of ONOO - . To investigate whether effects of ONOO - were due to nitration of tyrosine residues, spleen and brain microsomal fractions were treated with TNM, a known tyrosine-nitrating agent. It is shown that HO activity in rat spleen as well as brain microsomal fractions was significantly reduced by TNM albeit at higher concentrations compared to ONOO - (Figure 2 ). Figure 1 ONOO - -mediated inactivation of HO-1 and HO-2. Rat spleen (Figure 1A) and brain microsomes (Figure 1B) (50–100 μg protein) were treated with indicated concentrations of ONOO - or degraded ONOO - in 100 mM potassium phosphate, pH 7.4 at room temperature for 10 seconds. The reaction was stopped by dilution of the reaction mixture to a protein concentration of (0.5 mg/mL) spleen microsomes and (1 mg/mL) brain microsomes in 100 mM phosphate buffer containing 1 mM NADPH and 50 μM methemalbumin. Incubations of the pretreated microsomal fractions were performed for 15 min and enzyme activity was determined by the quantitation of CO formed in the reaction mixture. Data are presented as the mean ± SD of triplicate experiments. The rates of CO formation in the control reactions were 12 ± 1 and 5 ± 1 pmoles CO/min/mg protein for spleen and brain microsomes respectively. IC 50 values for HO-1 and HO-2 were 0.015 ± 0.005 mM and 1.25 ± 0.25 mM respectively. Figure 2 Effect of TNM-mediated nitration on the catalytic activity of HO. HO-1 (rat spleen microsomes and HO-2 (rat brain microsomes). Microsomal protein (50–100 μg) was incubated with 0.2 mM or 2 mM (final concentration) of TNM in 100 mM potassium phosphate buffer, pH 7.4, at 37°C for 20 minutes. The reaction was stopped by dilution of the reaction mixture to a protein concentration of (0.5 mg/mL) in 100 mM phosphate buffer containing 1 mM NADPH and 50 μM methemalbumin. Incubations of the pretreated microsomal protein were done for 15 min and enzyme activity was determined by the quantitation of CO formed in the reaction mixture. Data are presented as the mean ± SD of triplicate experiments. The rate of CO formation in control reactions was 11.4 ± 0.6 and 4.0 ± 0.14 pmoles CO/min/mg protein for HO-1 and HO-2 respectively. The asterisk denotes significant inhibition of the respective HO activity using a one-way ANOVA, P ≤ 0.05. Effects of sulfhydryl modifying reagents on HO activity Since ONOO - may affect protein targets by the oxidation of sulfhydryl groups as well as the nitration of tyrosine residues, we examined and compared the effect of other sulfhydryl modifying reagents on HO activity. Rat spleen or brain microsomal protein was treated with different sulfhydryl modifying reagents such as GSNO, DEA-NONOate, NEM and H 2 O 2 , and a combination of equimolar concentrations of ONOO - and GSNO or ONOO - and DEA-NONOate. We found that GSNO caused a concentration dependent inactivation of both HO-1 and HO-2. Consistent with the effect of ONOO - , GSNO was more active against HO-1 than HO-2 (Table 1 ). In contrast, DEA-NONOate and NEM caused a significant decrease in the catalytic activity of HO-1 at the two concentrations tested (0.2 mM and 2 mM), but did not inhibit HO-2 (Table 1 ). Pre-treatment with equimolar concentrations of ONOO - and DEA-NONOate or GSNO did not result in further inactivation of HO-1 or HO-2 than ONOO - alone. H 2 O 2 at concentrations as high as 2 mM had no significant effect on the catalytic activity of either isozymes. Table 1 Effect of NO donors and sulfhydryl modifying reagents on the catalytic activity of HO-1 (spleen microsomes) and HO-2 (brain microsomes) Heme oxygenase activity (pmoles CO/min/mg protein) Experimental conditions HO-1 (Spleen microsomes) HO-2 (Brain microsomes) Control 11.9 ± 0.6 3.1 ± 0.5 ONOO - 0.2 mM 5.4 ± 0.9* 2.7 ± 0.6 2 mM 3.8 ± 0.9* 1.4 ± 0.3* GSNO 0.2 mM 6.5 ± 0.3* 2.9 ± 0.5 2 mM 4.2 ± 0.2* 1.4 ± 0.1* DEA-NONOate 0.2 mM 4.7 ± 0.4* 2.9 ± 0.7 2 mM 3.6 ± 0.4* 2.4 ± 0.5 NEM 0.2 mM 8.7 ± 0.8 2.9 ± 0.3 2 mM 3.4 ± 0.5* 2.6 ± 0.4 H 2 O 2 0.2 mM 11.3 ± 0.2 3.0 ± 0.4 2 mM 11.8 ± 1.5 3.2 ± 0.6 ONOO - and GSNO 0.2 mM 4.3 ± 0.6* 2.8 ± 0.4 2 mM 4.0 ± 0.2* 1.3 ± 0.2* (ONOO - and DEA-NONOate) 0.2 mM 4.7 ± 0.1* 2.6 ± 0.2 2 mM 3.9 ± 0.6* 1.4 ± 0.3* Microsomal protein (50–100 μg) was incubated with 0.2 mM or 2 mM (final concentration) of ONOO - , GSNO, DEA-NONOate, NEM, H 2 O 2 , equimolar concentrations of ONOO - and GSNO or ONOO - and DEA-NONOate in 100 mM potassium phosphate buffer, pH 7.4, at 37°C for 20 minutes. The reaction was stopped by dilution of the reaction mixture to a protein concentration of (0.5 mg/mL) in 100 mM phosphate buffer containing 1 mM NADPH and 50 μM methemalbumin. Incubations of the pretreated microsomal fractions were done for 15 min and enzyme activity was determined by the quantitation of CO formed in the reaction mixture. Data are presented as the mean ± SD of triplicate experiments. Asterisks denote significant inhibition of the respective HO activity using a one-way ANOVA, P ≤ 0.05. To test whether effects of ONOO - and the sulfhydryl modifying reagents on HO-1 and HO-2 are reversible, ONOO - and DEA-NONOate were pre-incubated with rat spleen and brain microsomal protein for 20, 60 and 120 minutes prior to evaluation of HO activity. The inactivation of HO-1 by ONOO - and DEA-NONOate and HO-2 by ONOO - was reversible following prolonged pre-incubation time (60–120 minutes) Table 2 . However, total HO activity in brain and spleen microsomal protein was not affected by the prolonged pre-incubation for 60–120 minutes in the absence of ONOO - and DEA-NONOate. Table 2 Time dependent reversibility of the effect of ONOO - and DEA-NONOate on the catalytic activity of HO-1 (spleen microsomes) and HO-2 (brain microsomes) Heme oxygenase activity (pmoles CO/min/mg protein) at different pre-incubation times Experimental conditions 20 min 60 min 120 min Spleen microsomes (HO-1) ONOO - Control 10.4 ± 1.0 10.8 ± 0.8 8.7 ± 0.9 0.2 mM 3.6 ± 1.4* 10.5 ± 0.8 8.3 ± 1.1 DEA-NONOate Control 10.6 ± 2.0 11.5 ± 1.3 9.4 ± 0.2 0.2 mM 6.6 ± 0.7* 11.1 ± 1.4 8.9 ± 0.3 Brain microsomes (HO-2) ONOO - Control 3.6 ± 0.5 4.2 ± 0.4 4.4 ± 0.3 2 mM 1.9 ± 0.1* 4.4 ± 0.3 3.8 ± 0.3 DEA-NONOate Control 3.6 ± 0.3 4.1 ± 0.3 4.0 ± 0.3 2 mM 3.0 ± 0.3 3.9 ± 0.1 3.6 ± 0.3 Microsomal protein (50–100 μg) was incubated with 0.2 mM or 2 mM (final concentration) of ONOO - and DEA-NONOate in 100 mM potassium phosphate buffer, pH 7.4, at 37°C for 20, 60 and 120 minutes. The reaction was stopped by dilution of the reaction mixture to a protein concentration of (0.5 mg/mL) in 100 mM phosphate buffer containing 1 mM NADPH and 50 μM methemalbumin. Incubations of the pretreated microsomal fractions were done as described in materials and methods. Data are presented as the mean ± SD of triplicate experiments. Asterisks denote significant inhibition of the respective HO activity using a one-way ANOVA, P ≤ 0.05. Discussion Production of ONOO - in vivo is a consequence of oxidative and nitrosative stress, and ONOO - -mediated tissue injury is thought to be involved in the pathogenesis of many conditions including atherosclerosis, ischaemia/reperfusion, shock, Alzheimer's disease, diabetes and multiple sclerosis [ 27 - 30 ]. Continuous challenge and exposure to oxidative/nitrosative stressors has led to the evolution of numerous defense mechanisms in biological systems and one such mechanism that has been elucidated by many researchers is the HO/CO system [ 4 , 9 - 11 ]. ONOO - causes a concentration-dependent increase in HO-1 protein expression suggesting that the HO pathway contributes to protection against the cytotoxic effects of ONOO - [ 22 - 24 ]. Most studies in this field, however, have focussed on the induction of HO-1 mRNA and/or protein expression under different conditions of oxidative/nitrosative stress rather than enzyme activity. Considering the cellular toxicity of ONOO - and the inhibitory effect of ONOO - on numerous enzyme systems, we sought to investigate the direct effect of ONOO - on the catalytic activity of two microsomal HO isozymes. Rat spleen and brain microsomal fractions were used because of the predominant expression of HO-1 in the spleen and HO-2 in the brain. We have shown that ONOO - inhibits the activity of both HO-1 and HO-2 in a concentration-dependent manner (Figure 1 ). HO-1 was found to be more sensitive to ONOO - treatment compared to HO-2. Lower concentrations of ONOO - (15 μM, final concentration) decreased HO-1 activity by 50% while a much higher concentration (1.25 mM) was required to decrease HO-2 activity by the same magnitude. Generally, HO catalytic function is dependent on an accessory enzyme NADPH-cytochrome P450 reductase (CPR), which serves as a redox partner during the oxidative break down of heme and the conversion of NADPH to NADP + . It is possible therefore, that ONOO - may have altered HO activity indirectly by inactivating CPR. The ONOO - dependent inactivation of recombinant CPR in bacterial membranes has been noted [ 32 ], but our attempt to supplement rat microsomal HO-1 and HO-2 with recombinant rat CPR in the presence of a detergent did not attenuate the effect of ONOO - on microsomal HO-1 and HO-2 (data not shown). This suggests that the effects of ONOO - on HO activity may be mediated by mechanisms that are independent of the effect of ONOO - on microsomal CPR activity. The differential effect of ONOO - on the catalytic activity of HO-1 and HO-2 may suggest a selective mechanism on the catalytic function of the inducible enzyme. This may have direct implications in biological systems where ONOO - is generated at high concentrations. The ONOO - -mediated increase in HO-1 gene and/or protein expression may be a cellular response at the acute phase. Subsequently, total HO activity may then be maintained in certain ranges in order to retain intracellular oxidative responses and the balance of redox states for normal cellular function. This idea is consistent with other studies, which have shown that induction of HO-1 mRNA and protein expression is not always followed by a proportionate increase in catalytic function. For example, by using quantitative RT-PCR it was found that a 3.8-fold increase in sarcoma-induced HO-1 mRNA expression yields only 2.1-fold increase in total HO activity [ 31 ]. Overall, the ONOO - -mediated regulation of the catalytic function of HO-1 and differences in the sensitivity of HO-1 and HO-2 may be attributed to disparity in the amino acid compositions and the structure of the two proteins. Mechanistically, the effects of ONOO - on protein function are mainly due to its reactivity and covalent modification of tyrosine and/or cysteine residues [ 26 ]. This often leads to impaired protein function with very few exceptions such as the recently observed nitration and stimulation of the enzymatic activity of microsomal glutathione S-transferase (MGST) [ 33 ]. To probe mechanisms of ONOO - -mediated inhibition of HO activity observed here, we examined the effects of TNM, another tyrosine-nitrating chemical compound on rat spleen and brain microsomal HO activity. Significant inhibition of HO catalytic activity by TNM was observed for spleen as well as brain microsomal fractions albeit at higher concentrations compared to ONOO - (Figure 2 ). This suggests that both TNM and ONOO - may inactivate HO activity by nitration of tyrosine residue(s) that is/are important for conservation of HO-1 and HO-2 function. This is consistent with data from the analysis of the complete amino acid sequences of rat and human HO-1 [ 34 , 35 ] and HO-2 [ 36 , 37 ]. However, there was no difference in the effects of TNM on HO-1 and HO-2 (Figure 2 ), suggesting that the differential effects observed with ONOO - could be due to modification of amino acid residues other than tyrosine. Oxidation of cysteine residues as a putative mechanism underlying ONOO - -mediated inactivation of HO was investigated. Effects of GSNO, DEA-NONOate, NEM and H 2 O 2 , or a combination of equimolar concentrations of ONOO - and GSNO or DEA-NONOate on HO activity were tested. GSNO showed similar inhibitory effects to ONOO - but a combination of equimolar concentrations of ONOO - and DEA-NONOate or GSNO did not have any additive effect on the ONOO - -mediated inactivation of HO-1 or HO-2. In addition, the inactivation of HO-1 by ONOO - and DEA-NONOate and HO-2 by ONOO - were reversible following prolonged pre-incubation time (60–120 minutes) Table 2 . This differential effect between HO-1 and HO-2 following exposure to ONOO - , GSNO, DEA-NONOate or NEM is suggestive of qualitative as well as quantitative differences in the distribution of target amino acids such as critical tyrosine and/or cysteine residues in the tertiary structures of these proteins. The amino acid sequences of human and rat HO-2 reveals a conserved core of cysteine residues (Cys 264-Pro 265, Cys 281-Pro 282) [ 38 , 39 ], but there are no cysteine residues in the HO-1 amino acid sequence. Despite this fact, results from our experiments show that HO-1 is more sensitive to inactivation by the NO donors GSNO and DEA-NONOate, and NEM (Table 1 ). We considered the possibility that ONOO - might exert its effects by interaction with the substrate as has been reported for the interaction of NO with heme [ 40 ]. This possibility seems unlikely as such a mechanism would be expected to affect the catalytic rate of HO-1 and HO-2 equally. Another consideration is that the chemistry of ONOO - is richer than is usually discussed; in their review Alvarez and Radi [ 41 ] describe the interactions of ONOO - with a number of functional groups that are not often mentioned in the consideration of the interactions of ONOO - with various proteins. Thus, ONOO - inhibition of HO activity could be a result of an interaction with amino acids other than cysteine or tyrosine. This possibility of ONOO - interactions with other amino acids may also explain the reversibility of the inhibition of HO activity by ONOO - . Furthermore, it is possible that ONOO - inhibition of HO-1 and HO-2 occurs courtesy of different facets of ONOO - chemistry. Differences in the relative potency of DEA-NONOate, NEM, GSNO and ONOO - may also be attributed to differences in the chemical properties and the electrophilic potentials of these reagents. For instance, the nitric oxide radical (NO • ) generated from DEA-NONOate is less reactive and unstable compared to NO + produced from GSNO. Collectively, our data indicate that ONOO - may be important in the cross-talk between HO and NO systems. While tyrosine residues for HO-1 and/or sulfhydryl groups for HO-2 should be considered as potential targets for ONOO - interactions, other amino acids should be studied in the elucidation of mechanism(s) of ONOO - action on HO isozymes. Conclusion This study documented for the first time the ONOO - -mediated inactivation of HO-1 and HO-2. The IC 50 for HO-1 was approximately 80-fold less than that for HO-2. While conserved tyrosine residues (HO-1) and/or sulfhydryl group(s) (HO-2) may play a critical role in maintaining the functional capacity of heme oxygenases, the consideration of other amino acids is suggested. In addition, the higher sensitivity of HO-1 to ONOO - -mediated inactivation may indicate dual regulatory mechanisms on the catalytic function of the inducible enzyme under the conditions of oxidative/nitrosative stress. Methods Materials Hemin, ethanolamine, bovine serum albumin (BSA), β-NADPH, N-ethylmaleimide (NEM), tetra-nitromethane (TNM) and reduced glutathione (GSH) were purchased from Sigma Chemical Co. (St. Louis Mo.). Diethylamine NONOate (DEA-NONOate) was obtained from Calbiochem Inc. (Darmstadt, Germany). All other chemicals were reagent grade from a variety of commercial sources. Preparation of rat spleen and brain microsomes Adult male Sprague-Dawley rats (250–300 g) were obtained from Charles River Canada Inc. (St-Constant, Que). The animals were cared for in accordance with the principles and guidelines of the Canadian Council on Animal Care. Microsomal fractions were prepared according to previously described procedures [ 42 , 43 ]. Spleen microsomes were used as a source of HO-1 while brain microsomes were used as a source of HO-2. Preparation of ONOO - and treatment of microsomal protein ONOO - was synthesised from acidified nitrite and H 2 O 2 according to the method of Beckman [ 44 ] and microsomal HO-1 (spleen microsomes) and HO-2 (brain microsomes) were treated with ONOO - following the procedures described by Ji and Bennett [ 33 ]. Briefly, microsomes (50 –100 μg protein in 100 mM potassium phosphate, pH 7.4) were exposed to ONOO - at room temperature at indicated concentrations for 10 seconds by adding a small volume during vigorous mixing. HO activity was initiated by diluting the reaction mixture to a protein concentration of (0.5–1 mg/ml) in 100 mM phosphate buffer containing substrates (50 μM methemalbumin, and 1 mM NADPH). To control for the potential effect of nitrite and nitrate that may be formed during the incubation of ONOO - , ONOO - was allowed to decompose in phosphate buffer prior to incubation with microsomal protein and determination of enzyme activity for some of the reactions. Treatment of microsomes with NO donors, TNM and sulfhydryl modifying reagents GSNO was prepared by reacting equimolar amounts of sodium nitrite and GSH according to the method described by Ji et al ., [ 43 ]. Microsomal protein (50 – 100 μg) was incubated with 0.2–2 mM GSNO, DEA-NONOate, NEM or H 2 O 2 in 100 mM potassium phosphate buffer, pH 7.4, at 37°C for 20 minutes. The reaction was stopped by dilution of the reaction mixture to a protein concentration of (0.5–1 mg/mL) in 100 mM phosphate buffer containing (50 μM methemalbumin, and 1 mM NADPH). In vitro Assay for HO activity HO activity in rat spleen and brain microsomal fractions was determined by the quantitation of CO formed from the oxygen, CPR and NADPH-dependent degradation of methemalbumin as previously described [ 45 , 46 ]. The reaction mixture contained, (0.5–1 mg/mL microsomal protein, 50 μM methemalbumin, and 1 mM NADPH) in 100 mM phosphate buffer. All incubations for the assay of HO activity were performed under the conditions for which the rate of CO formation (pmol CO. mg -1 protein. min -1 ) was linear with respect time and microsomal protein concentration. CO formation was monitored by gas chromatography according to the method described by Vreman and Stevenson [ 46 ]. Statistical analysis Data are presented as the mean ± SD from triplicate experiments and statistical analyses were performed by one-way ANOVA. P values ≤ 0.05 was considered to be significant. Abbreviations HO, heme oxygenases; CPR, NADPH-cytochrome P450 reductase; CO, carbon monoxide; ONOO - , peroxynitrite; GSNO, S-nitrosoglutathione; DEA-NONOate, diethylamine NONOate; NEM, N-ethylmaleimide; TNM, tetra-nitromethane; ROS/RNS, reactive oxygen/nitrogen species; RT-PCR; reverse transcriptase polymerase chain reaction; H 2 O 2 , hydrogen peroxide. Authors' contributions RK, YJ and KN were involved in the experimental design and data collection. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529254.xml
529320	All HEPped Up about Methylation	null	For a recipe to become a meal, it's often necessary to embellish or modify the basic instructions—and to keep a note of the changes that work, so that it can be just as delicious next time around. The same is true for a gene, whose basic recipe—its nucleotide sequence—can be heritably annotated to “epigenetically” influence its level of expression without altering its sequence. Among the many epigenetic influences at work in the genome, methylation of cytosine is one of the most versatile and powerful. Addition of a methyl (-CH 3 ) group to cytosines within a gene's regulatory regions can reduce its transcription. In its extreme form, methylation is involved in silencing one of the two X chromosomes in female mammals. Aberrant methylation underlies susceptibilities to several forms of cancer, and is likely to be involved in numerous other human diseases. The goal of the Human Epigenome Project (HEP) is to map the methylation patterns of human genes, and to determine how they vary: among individuals, among tissues within an individual, and even over time within a single tissue. In this issue, Stephan Beck and colleagues describe the execution and results of a HEP pilot project, in which they analyzed methylation within the major histocompatibility complex (MHC), the set of genes that establish an individual's self-identity within the context of immune surveillance. The key to any such large-scale project is high throughput—a rapid, efficient set of technologies that produce the needed data with minimal human intervention. The strategy used by Rakyan et al. included bisulfite sequencing of DNA, in which unmethylated cytosines are chemically converted to uracils, while methylated cytosines are not. Software they developed detects the methylated sites and provides an overall measure of the methylation level within any given sequence. They confirmed the accuracy of their method with mass spectrometry, an alternative method also suitable for high-throughput screening. They initially analyzed 253 sequences within 90 genes in the MHC, about two-thirds of the total, from multiple tissues in multiple individuals. They found that most genes were either completely methylated or completely unmethylated, while relatively few had an intermediate value. The significance of this distribution pattern is not yet clear, although it does confirm similar results in smaller samples from other research groups. The researchers also confirmed that so-called CpG islands, regions rich in CG dinucleotides, are relatively hypomethylated, especially when they occur at the upstream end of a gene. Methylation levels in a region of the human genome Rakyan et al. also found differences in methylation levels among tissues, with some suggestion that the variations influence tissue-specific alternative splicing, at least in some genes. Intriguing inter-individual differences were also found, with median methylation levels differing significantly between individuals for at least one tissue at almost half the sites analyzed. For instance, such differences were found in liver for the regulatory region for the tumor necrosis factor gene. A major goal of the HEP is to identify methylation variable positions, sites whose methylation state is linked with some important biological state, be it tissue type, developmental stage, or disease state. The pilot project described here begins this undertaking, which will be greatly expanded as the HEP progresses. The first phase of the full-scale HEP, an analysis of 5,000 DNA sequences, is currently underway.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529320.xml
406512	Effects of fire and fire intensity on the germination and establishment of Acacia karroo, Acacia nilotica, Acacia luederitzii and Dichrostachys cinerea in the field	Background While fire has been used in some instances to control the increase of woody plants, it has also been reported that fire may cause an increase in certain fire-tolerant Acacia tree species. This study investigated germination of Acacia karroo , A. luederitzii and Dichrostachys cinerea , thought to be increasing in density, as well as the historically successful encroaching woody species, A. nilotica, in savanna grassland, Hluhluwe-iMfolozi Park, South Africa. A. karroo is thought to be replacing A. nilotica as the dominant microphyllous species in the park. We tested the hypothesis that observed increases in certain woody plants in a savanna were related to seed germination and seedling establishment. Germination is compared among species for burnt and unburnt seeds on burnt and unburnt plots at three different locations for both hot and cool fires. Results Acacia karroo showed higher germination ( A. karroo 5.1%, A. nilotica 1.5% and A. luederitzii 5.0%) levels and better establishment ( A. karroo 4.9%, A. nilotica 0.4% and A. luederitzii 0.4%). Seeds of the shrub Dichrostachys cinerea did not germinate in the field after fire and it is thought that some other germination cue is needed. On average, burning of A. karroo , A. nilotica and A. luederitzii seeds did not affect germination. There was a significant difference in the germination of burnt seeds on burnt sites (4.5%) and burnt seeds on unburnt plots (2.5%). Similarly, unburnt seeds on unburnt sites germinated better (4.9%) than unburnt seeds on burnt sites (2.8%). Conclusion We conclude that a combination of factors may be responsible for the success of A. karroo and that fires may not be hot enough or may occur at the wrong time of year to control A. karroo establishment in HiP. Although germination and establishment of A. karroo was higher than for A. nilotica a competitive advantage after fire could not be shown.	Background The increasing density in the woody component of savannas has been widely reported [ 1 - 5 ] with special mention being made of Acacia karroo Hayne [ 6 , 7 ] and A. nilotica (L.) Willd. Ex Del. subsp. kraussiana (Benth.) Brenan, [ 8 , 9 ]. in some areas, as major contributors to the phenomenon. In Hluhluwe-iMfolozi Park Dichrostachys cinerea (L.) Wight & Arn. and A. luederitzii Engl. var. retinens (Sim) Ross & Brenan are also thought to contribute to this phenomenon. In hard seeded legumes dormancy is broken by rupturing part of the seed coat. The rupturing of the seed coat may be induced by heat from fire [ 10 ] enabling water to enter the seed and start the process of germination. Many studies have confirmed a release of legume seeds from dormancy after fire [ 10 - 17 ]. Fire temperature or intensity also has an effect on the germination of seeds [ 17 , 18 ] and low intensity fires may not be enough to break dormancy of hard-seeded legumes [ 19 ]. In other cases lower fire temperatures are preferable for germination with an increase in fire temperature causing seed mortality [ 18 ]. While some studies report that a decrease in grass cover favours the establishment of woody seedlings due to reduced competition [ 20 , 21 ], others [ 6 , 22 ] challenge these findings. These differences may however, be a result of species reacting differently to fire or competition. Some Acacia species are shade intolerant resulting in decreased seedling establishment in shady areas [ 20 , 23 , 24 ]. Other Acacia species have been found to be tolerant of low light conditions and may even experience increased seedling survival [ 6 ]. The frequency of fires may affect the direction of change in woody plant density [ 5 ]. While it has been suggested that fire may increase Acacia densities [ 10 ], it is also used to clear acacias from grassland [ 25 ]. This contradictory situation in the literature concerning the effect of fire necessitates further research, as it is clear that continuous use of incorrect burning practices may have disastrous consequences. This study investigated the direct (heat) and indirect (grass removal) effects of fire on seed germination and seedling establishment of A. nilotica , A. karroo , A. luederitzii and Dichrostachys cinerea in Hluhluwe-iMfolozi Park (HiP), where an increase in woody plant density over the past 40 years has been reported [ 26 - 28 ]. It has also been reported that A. karroo is apparently replacing A. nilotica as the dominant microphyllous element [ 27 , 28 ]. This study reports on the effects of burning, fire intensity and burning of sites on germination; burning, fire intensity, burning of sites and grass length (shade) on seedling establishment and specific species responses to treatments (treatment species interactions). Results Germination None of the seeds of D. cinerea germinated in the field and it was therefore excluded from the model for the field experiment. Testing for differences among treatments was based on the maximum number of seedlings for each species at each location over the 31-week period (Figure 2 ). A description of the factors used in both the germination and establishment models is given in Table 1 . Figure 2 Mean number of germinated seeds recorded over a 31-week period at three different locations in HiP for a) Acacia karroo , b) Acacia luederitzii and c) Acacia nilotica . Table 1 Descriptions of factors used in the models and number of seeds used for each factor. Germination Establishment Factor/Description Total number of seeds Number not germinated Number germinated Percent germinated Total number of seeds Number not established Number established Percent established Total 4073 3923 150 3.68 4062 3966 96 2.36 Location Seme 1348 1287 61 4.53 1337 1302 35 2.62 Nombali 1364 1300 64 4.69 1364 1316 48 3.52 Le Dube 1361 1336 25 1.84 1361 1348 13 0.96 Species A. karroo 1786 1695 91 5.10 1788 1701 87 4.87 A. luederitzii 720 684 36 5.00 707 704 3 0.42 A. nilotica 1567 1544 23 1.47 1567 1561 6 0.38 Burnt or unburnt burnt 2021 1950 71 3.51 2030 1985 45 2.22 unburnt 2052 1973 79 3.85 2032 1981 51 2.51 Tall or short grass tall (>0.1 m) 2039 1961 78 3.83 2041 1993 48 2.35 short 2034 1962 72 3.54 2021 1973 48 2.38 Site burnt or unburnt burnt 2052 1977 75 3.65 2052 2003 49 2.39 unburnt 2021 1946 75 3.71 2010 1963 47 2.34 The ratio of the model deviance to the degrees of freedom was small (0.29) indicating that the model was a good fit. Location and species were the only main effects significantly affecting germination (Table 2 ). Acacia karroo had the highest germination of all species (Table 1 ). Table 2 Statistics indicating significance of the factors and interactions on germination. Significant factors are in bold. Factor df Log-likelihood Chi-Square Wald Stat. P Location 2 -587.555 13.915 11.547 0.003 Species 2 -597.790 34.386 25.394 0.000 Burnt status 1 -582.073 2.951 2.822 0.093 Grass length 1 -580.622 0.050 0.050 0.822 Site burn status 1 -580.608 0.021 0.021 0.885 Locationspecies 4 -582.584 3.974 3.827 0.430 Locationburn status 2 -582.929 4.664 4.373 0.112 Locationgrass length 2 -586.296 11.397 10.812 0.004 Locationsite burn status 2 -580.703 0.212 0.211 0.900 Speciesburn status 2 -581.173 1.151 1.145 0.564 Speciesgrass length 2 -581.019 0.843 0.837 0.658 Speciessite burn status 2 -583.309 5.424 5.166 0.076 Burn statusgrass length 1 -580.767 0.340 0.341 0.559 Burn statussite burn status 1 -585.060 8.926 8.656 0.003 Grass lengthsite burn status 1 -587.530 13.866 13.082 0.000 Interaction terms that had a significant effect on germination were, location × grass length, burn status × site burn status and grass length × site burn status (Table 2 ). Germination of burnt seeds in burnt sites (4.5%) was significantly higher than that of burnt seeds in unburnt sites (2.5%). Similarly, unburnt seeds in unburnt sites had a higher germination percentage (4.9%) than unburnt seeds in burnt sites (2.8%). The estimated odds of germination and their associated probabilities for the factors and their interactions are given in Additional file 1 . The odds ratios for significant effects were calculated. Thus a comparison between A. karroo and A. nilotica with regards to seeds germinating was made, where Thus the odds of germinating are four times more for A. karroo than for A. nilotica . Similarly A. nilotica was four times less likely to germinate than A. luederitzii while A. karroo and A. luederitzii had the same odds of germinating. Differences in germination among species for the various treatments are given in Table 3 . Table 3 A comparison of germination among species for the different levels of the main factors. A. karroo A. luederitzii A. nilotica Factor/description n Total count Not germ germ % erm Total count Not germ germ %germ Total count Not germ germ % germ LocationSpecies Seme 48 591 558 33 5.91 240 224 16 7.14 517 505 12 2.38 Nombali 48 596 551 45 8.17 240 227 13 5.73 528 522 6 1.15 Le Dube 48 599 586 13 2.22 240 233 7 3 522 517 5 0.97 Burnt or unburntSpecies burnt 72 886 839 47 5.6 360 344 16 4.65 775 767 8 1.04 unburnt 72 900 856 44 5.14 360 340 20 5.88 792 777 15 1.93 Tall or short grassSpecies tall 72 895 851 44 5.17 360 340 20 5.88 784 770 14 1.82 short 72 891 844 47 5.57 360 344 16 4.65 783 774 9 1.16 Site burnt or unburntSpecies yes 72 900 854 46 5.39 360 338 22 6.51 792 785 7 0.89 no 72 886 841 45 5.35 360 346 14 4.05 775 759 16 2.11 There was 2.3 times less germination at Le Dube than at Nombali and 2.6 times less at Le Dube than at Seme. Germinations were 1.2 times more likely at Seme than at Nombali. Seedling establishment The ratio of the model deviance to the degrees of freedom was small (0.17) indicating that the model fitted the data well. Location and species were the only main effects significantly affecting establishment in the field (Table 4 & Figure 3 ). Acacia karroo showed significantly higher percentage establishment than any of the other species ( Additional file 2 , Table 5 & Figure 3 ). Table 4 Statistics indicating significance of factors and interactions on establishment. Significant factors are indicated in bold. Factor df Log-likelihood Chi-Square p Location 2 -443.238 22.292 <0.001 Species 2 -395.199 96.079 <0.001 Burnt status 1 -395.050 0.297 0.586 Grass length 1 -395.049 0.002 0.962 Site burn status 1 -395.040 0.018 0.894 Locationspecies 4 -391.756 6.568 0.161 Locationburn status 1 -380.850 21.812 <0.001 Locationgrass length 2 -373.542 14.617 <0.001 Locationsite burn status 2 -367.865 11.353 0.003 Speciesburn status 2 -367.468 0.795 0.672 Speciesgrass length 2 -367.344 0.248 0.884 Speciessite burn status 2 -367.180 0.329 0.848 Burn statusgrass length 1 -366.723 0.913 0.339 Burn statussite burn status 1 -360.267 12.913 <0.001 Grass lengthsite burn status 1 -351.784 16.965 <0.001 Figure 3 Predicted mean establishment for the significant main effects of a) species and b) location. Vertical error bars show 95% confidence limits. Table 5 A comparison of establishment among species for the different levels of the main factors A. karroo A. luederitzii A. nilotica Factor/Description n Total count Not estab estab % estab Total count Not estab estab % estab Total count Not estab estab %estab LocationSpecies Le Dube 48 599 590 9 1.53 240 239 1 0.42 522 519 3 0.58 Nombali 48 598 553 45 8.14 238 237 1 0.42 528 526 2 0.38 Seme 48 591 558 33 5.91 229 228 1 0.44 517 516 1 0.19 Burnt or unburntSpecies Burnt 72 886 843 43 5.1 347 346 1 0.29 797 796 1 0.13 Unburnt 72 902 858 44 5.13 360 358 2 0.56 770 765 5 0.65 Tall or short grassSpecies Tall 72 897 854 43 5.04 360 358 2 0.56 784 781 3 0.38 Short 72 891 847 44 5.19 347 346 1 0.29 783 780 3 0.38 Site burnt or unburntSpecies Yes 72 900 855 45 5.26 360 359 1 0.28 792 789 3 0.38 No 72 888 846 42 4.96 347 345 2 0.58 775 772 3 0.39 Interaction terms, location × burn status, location × grass length, location × site burn status, burn status × site burn status and grass length × site burn status had a significant effect on establishment (Table 4 ) (Figure 4 ). Figure 4 Predicted mean establishment for significant interactions of site burn status and a) location, b) seed burn status and c) grass length. The solid line represents unburnt sites and the dotted line burnt sites. Vertical error bars show 95% confidence limits. Additional file 2 gives the estimated odds of non-establishment and their associated probabilities for the factors and their interactions. The odds ratios for significant effects were calculated and are given (see Additional file 3 ). Acacia karroo was 16.2 times more likely to establish than A. nilotica. Similarly A. luederitzii was 1.4 times more likely to establish than A. nilotica while A. karroo had 11.2 times more chance of establishing than A. luederitzii. Species differences in establishment for the various treatments are given in Table 5 . The odds of establishment were 8046.2 times less at Le Dube than at Nombali and 5850.5 times less at Le Dube than at Seme. 1.4 times more seedlings were likely to establish at Nombali than at Seme. Discussion The lack of germination of D. cinerea in the field suggests that some disturbance other than fire is needed to cause a release from dormancy and commence germination. Germination of all species in the field was low. As the seeds relied on cotyledons for food, soil moisture may have been a limiting factor. As rainfall was not recorded, this should be kept in mind when interpreting the results. Five point one percent of A. karroo seeds germinated, which was higher than the other two species. Story [ 29 ] found similar levels of germination for A. karroo, with 6.6% of seeds germinating under natural conditions in the field. He also found that A. karroo germination was erratic, with germinations still being recorded after 423 days. This was similar to what was found in this study, with the number of A. karroo seedlings still increasing until the end of the experiment. Acacia nilotica also showed dormancy with sporadic germination events over the 31-week period. Acacia luederitzii did not show dormancy with most germinations taking place in the first 3 weeks of the experiment. Acacia nilotica has a thick seed coat, which could account for it's poor level of germination. One would predict increased germination of burnt seeds due to a breaking of dormancy [ 18 ], but this was not the case. A possible explanation is that the temperature of the fires in this study, though not measured, might not have been sufficient to break dormancy in this species. Some Acacia species are temperature specific, suggesting a temperature threshold for germination [ 18 , 20 ]. This is unlikely in this case as Radford et al . [ 30 ] found A. nilotica seeds to be highly vulnerable to fire with a 80% mortality of seeds on the soil surface. The current study, however, found no difference in germination between burnt and unburnt seed or seeds burnt at different temperatures. This finding is inconsistent with the recent study by Kanz [ 20 ] who found increased seed germination in low fires compared to the control as well as that of Okello and Young [ 31 ] who found increased germination of unburnt seeds. Auld & O'Connell [ 18 ] had similar results to that of Kanz [ 20 ] with strong germination responses to heat. Location had a significant effect on germination with Le Dube having very low germination overall and Seme having the most germinations. Germination at Nombali and Seme were similar. Site-specific effects may be attributed to various factors such as microclimate or soil type. Sites may also have different water infiltration rates and runoff, which may result in differences in germination levels. Okello and Young [ 31 ], however, found that soil type did not affect germination or establishment of Acacia drepanolobium in Kenya. The current study did not find a difference in the number of seedlings in burnt and unburnt patches. While neither burning of seeds nor burning of sites had any effect on germination, the interaction factor proved significant with unburnt seeds showing increased germination in unburnt sites as did burnt seeds in burnt sites. Kanz [ 20 ] also found greater seedling emergence of unburnt seeds in unburnt areas. This might be a result of burnt seeds imbibing faster than unburnt seeds, possibly making them more susceptible to rot. Burnt seeds would therefore show poorer germination in unburnt areas due to increased moisture retention. Similarly, unburnt seeds would require more moisture to imbibe, resulting in decreased germination in burnt areas due to decreased moisture in these open areas. Whilst more seeds germinated in short grass at both Le Dube and Nombali, those at the short-grass site (Seme) had higher levels of germination in tall grass sites. The short grass site at Seme is a white rhinoceros ( Ceratotherium simum ) grazing lawn with very short grass, which may lead to seeds losing moisture through more direct sunlight. This suggests a similar pattern to the seed burn × site burn interaction. The tall grass site at Seme had higher germination than any of the other tall or short grass sites. This may be due to possible site-specific effects mentioned earlier. There was also an interaction between grass length and site burn with seeds in burnt, short grass showing higher germination than those in burnt, tall grass and unburnt sites showing higher germination in tall grass. As half of the seeds on a burnt or unburnt site were burnt themselves, it is possible that this interaction is due to temperature sensitivity in seeds. Burning in tall grass (hotter fires) may be detrimental to the germination of seeds [ 18 ] while cooler fires may be sufficient to break dormancy and cause germination. Higher germinations in unburnt tall grass areas suggest a shade effect. This is not certain, as the effects of shade and grass competition were not separated in this study. Acacia karroo has however been reported as having an increased ability to survive in shade with recruitment of seedlings being dependent on moisture availability [ 6 ]. Tall grass species may retain more moisture than short grass species, affording seeds a better opportunity for germination. No species factor interactions were observed suggesting that though species had different germination levels, they did not respond differently to the treatments. The same factors and interactions found to be significant influences on germination were found to influence establishment. This was expected as increased germination for these treatments would result in better establishment. The interaction patterns for most of the treatments, however, were different to those of the germination model. Owing to the low levels of germination, interspecific and intraspecific competition was thought to play a minor role in seedling establishment. Le Dube again had the least seedlings at 31 weeks while Nombali had the best establishment. Seme, which had the highest level of germination, had establishment levels somewhere between that of the other two sites. It is again suggested that this may be due to soil or rainfall factors. Forty-five out of forty-eight seedlings established at Nombali and thirty-three out of thirty-five at Seme were A. karroo seedlings. This species is known to be dependent on moisture availability for survival [ 6 ] and these two sites might have better water retaining ability than Le Dube. At week 31, 87 A. karroo seedlings had established as opposed to six of A. nilotica and three of A. luederitzii. The high germination, but poor survival of A. luederitzii suggests that the absence of this species in the Hluhluwe section of HiP is not due to seed limitation or germinability, but possibly due to environmental factors decreasing its ability to establish. The differences in seedling survival between species are consistent with those reported by Kanz [ 20 ] who found higher seedling survival for A. karroo than A. nilotica . The location × grass length interaction revealed the same patterns as for germination with regards to Nombali and Seme with Seme showing better establishment in tall grass and Nombali showing better establishment in short grass. There was no difference between establishment on tall and short grass at Le Dube. The short grass site at Nombali had the highest number of seedlings surviving at week 31. The grass length × site burn interaction displayed the same patterns as for the germination model, but this was not the case for the seed burn status × site burn status interaction. While unburnt seeds still did well on unburnt sites, burnt and unburnt seeds showed decreased establishment on burnt sites suggesting that, as a result of increased irradiance, burnt (open) sites may not hold sufficient moisture for seedlings to survive. The interaction effects found to be significant for establishment only, both suggest the importance of fire temperature. Location × seed burn status and location × site burn status could both relate to the different grass lengths, and thus specific fire temperatures, at the three sites. Temperature sensitivity in Acacia species have been reported elsewhere [ 11 , 14 , 17 , 20 ]. Kanz [ 20 ] found increased survival and growth in burnt areas. In this study, Nombali was the only location to have higher establishment on burnt sites, while Seme had increased establishment on unburnt sites and Le Dube very little establishment overall. In general, however, this study found no difference in establishment in burnt and unburnt areas. Chirara, Frost & Gwarazimba [ 7 ] found that intensity of grass defoliation does not affect seedling establishment of A. karroo during the first year. Similarly, there was no difference in establishment of A. karroo in burnt or unburnt and tall or short grass sites. Smith & Goodman [ 32 ] reported that A. nilotica seedlings, however, almost exclusively occurred away from canopy cover, suggesting an inability to establish in shaded environments. Acacia tortilis also showed a greater proportion of established seedlings in open than shaded areas [ 23 ]. We did not find a difference in establishment of A. nilotica in tall and short grass, but its establishment was so low that no real prediction can be made. Conclusions Seedling establishment of A. karroo is strongly moisture dependent [ 6 ] and one would expect that A. karroo is more likely to invade moist rather than semi-arid grassland. This suggests that Hluhluwe Game Reserve, being an area with moist grassland, would be more prone to invasion by A. karroo . It has also been reported that A. karroo has the ability to withstand fire [ 17 ]. A combination of these factors may contribute to the success of A. karroo in the field and may be the reason for A. karroo 's success over A. nilotica as the most important encroaching Acacia species in HiP at present. The literature does, however, suggest that high intensity fires may result in seed mortality [ 18 , 20 ]. It has, however, been reported that A. karroo seedlings survive fires from as little as 12 months of age [ 29 ]. Therefore, if fires are not hot enough to kill the seeds allowing them to germinate and seedlings to establish, management burns in the following year may not be useful in its attempt to control the establishment of this species. Back fires have higher fire intensities than head fires [ 20 ]. We therefore suggest that backfires be used during management burns and that fire frequency be increased in suitable areas in an attempt to slow down the rate of encroachment by A. karroo. It has been reported that spring burns are the most effective ([ 33 ] in [ 29 ]) and this should be taken into account. Methods Study site The study was done in HiP, KwaZulu-Natal, South Africa (28°00' – 28°26' S, 31°43' – 32°09'E). HiP is a 960 km 2 fenced protected area comprising the former Hluhluwe and iMfolozi Game Reserves, and the corridor of land that links the areas. The park has a moderate coastal climate, ranges in altitude from 60 – 750 m above sea level [ 34 ] and has a summer rainfall ranging between 760 and 1250 mm per annum. Hluhluwe Game Reserve has a mean annual rainfall of 990 mm, while iMfolozi Game Reserve has a mean annual rainfall of 720 mm [ 34 ]. Periodic fluctuations in above or below average annual rainfall occur, resulting in wet and dry spells of approximately nine years [ 35 ]. The range in average monthly temperature is between 13 and 33°C [ 36 ]. Most of Hluhluwe Game Reserve is found on rocks of the Ecca and Beaufort series with some basalt in the east [ 37 ]. King [ 37 ] identified seven geological formations: (1) the Granite-Gneiss base, (2) the Table Mountain sandstone, (3) the Dwyka tillite, (4) The Ecca and Beaufort series, (5) the Stormberg series, (6) fault breccias and (7) recent deposits. The main soils types associated with the Ecca and Beaufort series are Swartland and Sterkspruit, while areas of Shortlands, Milkwood and Bonheim series are found in association with the dolerite regions [ 34 ]. They also report that shallow Mispah soils occur extensively in the reserve. The vegetation in the park has been described as bushveld – savannah comprising five broad vegetation types [ 38 ]. The thickets are wooded groups of similar-sized, small (usually less than three metres) trees of mainly one species that grows densely to the exclusion of other species. The thornveld consists of scattered thorn trees on grassland with deciduous, broad-leaved trees standing out above the thorn trees while the woodlands are densely wooded areas of tall trees that may contain many different, mainly broadleaved species. The well drained, shallow soils of the rocky outcrops support scattered trees of various sizes, while the termite mounds are nutrient rich patches sustaining dense clumps of trees that form small, wooded islands [ 38 ]. Locally the reserve is described as Natal Lowveld Bushveld and falls within the savanna biome [ 39 ]. The field experiment took place in the Hluhluwe and Corridor sections of the HiP. Acacia luederitzii occurs in large numbers in certain areas of the iMfolozi part of the reserve but is mostly absent from the Hluhluwe and Corridor sections. Acacia nilotica, A. karroo and D. cinerea are found throughout the park. As opposed to the scattered trees found in iMfolozi, A. nilotica covers extensive areas of Hluhluwe and the Corridor and is usually found below the 300 m contour [ 34 ]. Whateley & Porter [ 34 ] described an A. karroo – D. cinerea induced thicket throughout the area, but particularly in the Corridor and Hluhluwe Reserves. Acacia luederitzii seeds used in this study were therefore collected in iMfolozi Game Reserve while those of the other species were collected in Hluhluwe. Germination The effect of fire, fire intensity and burning of sites on the germination of seeds of A. nilotica , A. karroo , A. leuderitzii and D. cinerea was tested in a field experiment. Seeds of all species were collected between May and August 2000. Parasitized seeds were extracted. Prior to planned management burns, six groups of seeds were placed in tall grass (taller than 0.10 m) and six in short grass (shorter than 0.10 m) at three locations (Nombali, Seme and Le Dube). Tall grass produces hotter fires than short grass due to increased fuel load, which increases available heat energy [ 40 ]. Sites were cleared of existing pods/ seeds prior to the experiment and as podding season was over, no uncontrolled additions are expected to have occurred. Dichrostachys cinerea seeds were only put out at Seme and Nombali. Each group contained 22 A. nilotica , 25 A. karroo , 10 A. leuderitzii and 10 D. cinerea seeds. Seeds were placed on the soil surface a day before each of the burns (Nombali two days before). This is considered the natural situation for the seeds with soil stored seed banks being virtually non-existent [ 41 ]. Seme and Le Dube were burnt on 2 October and Nombali on 30 September 2000 shortly before the start of spring rains and natural seed release. After the burns, three of the groups of burnt seeds were removed from the tall and short grass and placed on unburnt tall and short grass sites at the same location respectively. Three groups of unburnt seeds were then added to each of the tall and short grass sites. A 13 mm mesh cage with 18 cm × 18 cm × 18 cm sides was used to protect each group of seeds and any germinated seedlings from rodent and herbivore predation. Cages were placed at half metre intervals and seeds placed on the soil surface in a group in the middle of each cage Seeds were considered to be germinating when a root started showing. A diagrammatical representation of the experiment is given in Figure 1 . Germination was recorded at 1, 3, 5, 7, 9, 11, 14, 17, 20, 23, 27 and 31 weeks. The experiment ended in May 2001. Figure 1 Diagrammatical representation of the experimental design used to test the effect of fire on seed germination and establishment. Arrows indicate movement of seeds between burnt/unburnt tall/short grass plots. We thus applied 96 possible seed treatment combinations for investigating factors affecting germination in the field (4 species × 2 burn treatments × 3 locations × 2 location burn treatments × 2 fire intensities). Seedling establishment To test the effect of fire, fire intensity, burning of sites and grass length (shade) on seedling establishment of A. nilotica , A. karroo , A. leuderitzii and D. cinerea , data as on week 31 of the field experiment described above were used. Seedlings were considered to be established when they were rooted in the ground and the cotyledons replaced with leaves. Establishment was based on the total number of seeds. Data analysis The "STATISTICA ® " [ 42 ] Generalized Linear Model (GLZ) module was used to construct linear logistic models for germination and establishment proportions as response variables for the field experiment. As data were recorded as presence (1) or absence (0) of seedlings, a binomial distribution was assumed [ 43 ]. In both cases, main effects and second order interactions were included in the model. The logit model may therefore be written as follows: where = the log of variable 1 and 2 at different levels of the factors as given below λ' = the overall mean effect of the categories = the effect of the j th species ( j = A. karroo , A. luederitzii , A. nilotica , D. cinerea ) = the effect of the k th location ( k = Le Dube, Nombali, Seme) = the effect of the l th seed burn status ( l = burnt, unburnt) = the effect of the m th grass length ( m = short, tall) = the effect of the n th site burn status ( n = burnt, unburnt) = the interaction effect between the j th species and the k th location = the interaction effect between the m th grass length and the n th site burn status. The logit model may be written as a generalized linear model as follows: where , , , , , , , , , and are parameters to be estimated from the data and B, C, D, E and F refer to the explanatory variables species, location, burn status, grass length and site burnt status respectively. The estimated parameters for the GLZ were used to obtain the estimated parameters for the logit model. The estimated parameters of the odds were calculated for each factor or combination of factors (including the intercept) as the exponent of the estimated parameters of the logit model. The estimated odds of germination under any condition were then calculated as the product of the estimated parameter of the odds of the intercept (estimated geometric mean odds) and the factor or combination of factors in question. The odds of germination for significant treatment combinations were compared. The predicted number of seeds germinating and seedlings establishing as calculated with the model based on presence/absence data, were seen as being appropriate for interpretation as summaries of the data. Thus, differences in the predicted mean number of seeds germinating and seedlings establishing (given as a fraction of the total number of seeds) were illustrated graphically for each significant treatment combination. Authors' contributions MW designed the experiment, participated in fieldwork, performed the statistical analysis and drafted the document. MJS participated in fieldwork, the coordination of the study and drafting of the document. JJM supervised the work and assisted in the drafting of the document. All authors read and approved the final manuscript. Supplementary Material Additional File 1 The parameters of the logit model and odds, estimated odds of germination and the ratio of germination to non-germination for the factors included in the model for germination of certain Acacia seeds in HiP. Gives parameters of the logit model and estimated odds of germination for the various levels of the factors used. Click here for file Additional File 2 The parameters of the logit model and odds, estimated odds of establishment and the ratio of establishment to non-establishment for the factors included in the model for establishment of certain Acacia species in HiP. Gives parameters of the logit model and estimated odds of establishment for the various levels of the factors used. Click here for file Additional File 3 Odds ratios for all significant interactions of the establishment model. Compares the odds of establishment between different levels of the factors used. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC406512.xml
545205	Gene Mutations in Lung Cancer: Promising Predictive Factors for the Success of Molecular Therapy	Gefitinib and erlotinib are two new treatments for advanced lung cancer. Gene mutations in the cancer may help predict which patients will respond to these treatments	Lung cancer is the leading cause of death in many countries. To date, cause of cancer death in chemotherapy with cytotoxic agents has been the mainstay of treatment for advanced lung cancer. However, the activity of these agents is quite limited, and they have severe adverse effects. Recent, rapid advances in molecular biology have led to the development of many new agents that inhibit the activities of specific molecules related to tumor growth, invasion, or metastasis [1] , and these agents have the potential to improve the outcome of lung cancer treatment. But we have not yet managed to successfully deliver these agents from the bench to the bedside. Molecular Therapy for Lung Cancer Gefitinib is the first “molecular-target agent” for lung cancer that inhibits the tyrosine kinase of the epidermal growth factor receptor (EGFR; also known as ERBB1). EGFR is frequently overexpressed in non-small-cell lung cancer (NSCLC), especially in squamous cell carcinoma, and its expression is related to the cancer's proliferation. Initial clinical trials of gefitinib showed its modest clinical activity in patients who had failed previous standard chemotherapy. But subsequent randomized trials in patients with previously untreated, advanced NSCLC have not shown a clinical advantage of gefitinib combined with standard chemotherapy over chemotherapy alone [ 2 , 3 , 4 , 5 ]. Erlotinib, another EGFR tyrosine kinase inhibitor for treating NSCLC, which was approved by the United States Food and Drug Administration in November 2004, has a therapeutic profile similar to that of gefitinib. Erlotinib has shown a survival benefit in a phase III trial for chemo-refractory NSCLC that compared erlotinib to best supportive care [6] . (To date, there have been no trials showing a survival benefit of EGFR inhibitors over standard chemotherapy.) Interestingly, in these trials of EGFR inhibitors, EGFR expression levels in the tumors were not correlated with the response; high response rates were seen in women, patients with adenocarcinoma, nonsmokers, and Japanese patients. Recent studies have now shed light on why certain patients are more likely to respond than others—the key lies in the presence of gene mutations. EGFR Gene Mutations in NSCLC In April and May 2004, two new studies published in Science and the New England Journal of Medicine helped to explain at the molecular level the low clinical activity of EGFR inhibitors [ 7 , 8 ]. These studies identified somatic mutations in the EGFR gene, especially around the region encoding the ATP-binding pocket of the receptor's tyrosine kinase domain. These mutations increased the sensitivity of tumor cells to gefitinib. A high incidence of mutations was detected in patients with NSCLC that had a durable clinical response to gefitinib, and subsequent studies revealed that these mutations were also related to the response to erlotinib. Moreover, such mutations were more frequently detected in patients with adenocarcinoma, in women, in Japanese patients, and in nonsmokers [9] —results that were compatible with previous clinical data. These findings should hopefully lead to the identification of subgroups of patients who are likely to benefit substantially from such EGFR inhibitors. But another question was raised by these studies: is it only EGFR gene mutations that determine the response to EGFR inhibitors? RAS Gene Mutations in NSCLC The RAS proteins are low-molecular-weight GTPases that are bound to the inner side of the cell membrane. They are involved in signal transduction pathways: they regulate downstream effector proteins such as Raf/MAP kinase and PI3 kinase, under the influence of various cell surface receptors including EGFR ( Figure 1 ). Mutations of the K-ras gene have been found in up to 30% of lung adenocarcinomas and have been considered a poor prognostic factor [10] . A study by Pao and colleagues published in this issue of PLoS Medicine suggests that the K-ras mutation is an important predictive factor in defining which patients will benefit from receiving EGFR inhibitors [11] . In Pao and colleagues' study, the K-ras mutations were completely associated with a lack of response to EGFR inhibitors (0/14 tumors with K-ras mutations were sensitive). The EGFR mutations were significantly related to response (17/17 tumors with EGFR mutations were sensitive), as observed in previous studies. Figure 1 EGFR Signal Transduction in Cancer Cells Arrows indicate stimulation, and T-bars, inhibition. EGFR-I, EGFR inhibitor; MEK, MAPK kinase. Although the number of tumors examined in this study may be too small to lead to a definite conclusion—and, furthermore, about half of tumors were retrospectively collected—this study is the first to show that mutations of EGFR and K-ras are not related and that K-ras mutations are associated with a lack of sensitivity to EGFR inhibitors. However, since the sensitivity of the method for finding each mutation influences how often it is detected, standardization of detection methods is important. Hence, the true incidence of K-ras mutations in NSCLC (including non-adenocarcinoma) and their refractoriness to EGFR inhibitors need to be established in further studies. In fact, the reported incidence of EGFR mutations differs between institutions. In addition, although Pao and colleagues' study examined such mutations only by DNA sequence, mRNA or protein expression would show mutation status more accurately. Therapeutic Implications In the clinical setting, prolonged disease stabilization with no measurable reduction in tumor size is seen in about half of patients treated with EGFR inhibitors, and a significant survival benefit in this group was shown in a phase III trial [6] . The mutation status of the EGFR gene and K-ras gene among those stabilized tumors should be evaluated; it may reveal two different groups differentiated by mutation status. It will also be important to establish whether, in tumors with an EGFR mutation that eventually acquire resistance to EGFR inhibitors, the resistance is associated with a change of EGFR status (mutation or change in expression) or is associated with a change of K-ras status. Such changes can be revealed by re-examination of tumors at the time of relapse. If resistance is K-ras dependent, the new “K-ras inhibitors” (unfortunately not yet available) may be of help for patients who have developed a K-ras mutation, as well as for patients whose tumors harbor K-ras mutations from the beginning. Although many issues still need to be resolved step by step through prospective trials to show the benefit of this new strategy, these mutations are promising predictive factors for the success of EGFR inhibitors. Even if the population who may benefit from EGFR inhibitors (such as patients who are positive for an EGFR mutation and negative for a K-ras mutation) is very small, the response rate of over 80% is encouraging, and has never before been achieved in advanced NSCLC. Finally, it is important to detect which patients derive no benefit from EGFR inhibitors because severe adverse effects such as acute lung injury can occur in any patient treated with these drugs [12] . By combining all the factors that relate to response or resistance, patients who will benefit from treatment can hopefully be identified. Undoubtedly we have taken a great step forward in molecular therapy for lung cancer treatment.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545205.xml
535899	Divergence of the mRNA targets for the Ssb proteins of bacteriophages T4 and RB69	The single-strand binding (Ssb) protein of phage T4 (T4 gp32, product of gene 32) is a mRNA-specific autogenous translational repressor, in addition to being a sequence-independent ssDNA-binding protein that participates in phage DNA replication, repair and recombination. It is not clear how this physiologically essential protein distinguishes between specific RNA and nonspecific nucleic acid targets. Here, we present phylogenetic evidence suggesting that ssDNA and specific RNA bind the same gp32 domain and that plasticity of this domain underlies its ability to configure certain RNA structures for specific binding. We have cloned and characterized gene 32 of phage RB69, a relative of T4 We observed that RB69 gp32 and T4 gp32 have nearly identical ssDNA binding domains, but diverge in their C-terminal domains. In T4 gp32, it is known that the C-terminal domain interacts with the ssDNA-binding domain and with other phage-induced proteins. In translation assays, we show that RB69 gp32 is, like T4 gp32, an autogenous translational repressor. We also show that the natural mRNA targets (translational operators) for the 2 proteins are diverged in sequence from each other and yet can be repressed by either gp32. Results of chemical and RNase sensitivity assays indicate that the gp32 mRNA targets from the 2 related phages have similar structures, but differ in their patterns of contact with the 2 repressors. These and other observations suggest that a range of gp32-RNA binding specificities may evolve in nature due to plasticity of the protein-nucleic acid interaction and its response to modulation by the C-terminal domain of this translational repressor.	Introduction T4 gp32, the single-strand binding (Ssb) protein of bacteriophage T4, is a well studied member of the Ssb protein family, and was the first such ssDNA-binding replication protein to be discovered [ 1 ]. The protein, product of T4 gene 32, is an essential component of the phage DNA replication complex and also plays essential roles in DNA repair and recombination [ 2 , 3 ]. Like other Ssb proteins, T4 gp32 facilitates transactions at the replication fork, especially along the lagging strand, through its binding to the unwound DNA template and its specific interactions with other protein components of the DNA replisome. T4 gp32 is known to stimulate the phage induced DNA polymerase (T4 gp43) and to play a role in the dynamics of primosome (T4 gp61-gp41 complex) recruitment by the primase-helicase assembly protein T4 gp59 [ 4 - 6 ]. In general, Ssb proteins lack specificity to the ssDNA sequence and this property allows them to perform their physiological roles at all genomic locations undergoing replication, repair or recombination. The presence of a Ssb protein in the right place at the right time may depend, in large measure, on specificity of its interactions with other proteins from the same biological source. T4 gp32 has the interesting property of being able to control its own biosynthesis at the translational level in vivo . The protein binds to a specific target (translational operator) in the 5' leader segment of the mRNA from gene 32, and represses translation of this RNA [ 7 ]. Another Ssb protein, gp5 of the M13 ssDNA phage family, has also been shown to act as a mRNA-specific translational repressor, although in this case, the RNA target is located in the message for another essential M13 replication protein, gp2 (an endonuclease) [ 8 , 9 ]. It is not known if other Ssb proteins, especially those for cellular DNA replication and maintenance, also possess RNA binding functions that regulate specific translation or other physiologically important RNA-dependent processes. In T4, the physiological link between the sequence-independent ssDNA and specific RNA binding functions of gp32 has been explained by a model based on in vitro measurements of the protein's binding affinities to different nucleic acid ligands. It has been observed that ssDNA is favored over translational operator RNA as a ligand for T4 gp32 and that RNA of nonspecific sequence is the least preferred nucleic-acid ligand for this Ssb protein [ 10 - 12 ]. In vivo , T4 encoded mRNA for gp32 is intrinsically more metabolically stable than the typical prokaryotic mRNA and is thought to have opportunities to undergo many cycles of gp32-mediated repression and depression during the replication and other processing of phage DNA. The potential for translation of this mRNA in the T4 infected E coli host is thought to be determined by availability of ssDNA in the metabolic pool [ 10 , 13 , 14 ]. DNA damage or unwinding transactions are thought to draw gp32 away from its mRNA target to the exposed ssDNA, thus causing derepression of translation and upward adjustments in gp32. Repression of the mRNA would then be reestablished if the amount of gp32 exceeded the number of exposed ssDNA sites for the protein. This model is consistent with many in vivo observations relating to levels of T4 gp32 biosynthesis under conditions of DNA damage or abnormal accumulation of ssDNA in the phage infected bacterial host [ 7 ]. It is not clear how T4 gp32 distinguishes between specific RNA and the non-specific nucleic acid sequence of ssDNA or ssRNA ligands. It appears that single-strandedness of the nucleic acid is not the most important criterion used by the protein to selectively bind its own message in the phage-induced mRNA pool. The translational operator for T4 gp32 has been mapped by RNA footprinting assays and determined to consist of two contiguous components, a 5' terminal ~28-nucleotide component that forms a folded structure (RNA pseudoknot) and an adjacent, less structured, >40-nucleotide component that lies 3' to the pseudoknot [ 15 , 16 ]. The 3' terminal component includes several repeats of UUAAA or UAAA sequences, in addition to harboring typical prokaryotic nucleotide determinants for translation initiation by ribosomes [ 7 , 16 , 17 ]. The RNA pseudoknot and UUAAA/UAAA elements are both essential for autogenous repression of the mRNA by T4 gp32 [ 15 , 16 , 18 ]. In vitro studies suggest that the pseudoknot serves as the initial recognition (nucleation) site for the protein and that this gp32-RNA interaction leads to cooperative binding of additional gp32 monomers to the less structured downstream sequence containing the UUAAA/UAAA elements and ribosome-binding site (RBS) [ 16 ]. Cooperative binding to the mRNA is envisaged to be analogous to gp32-ssDNA interactions, except that the UUAAA/UAAA sequence elements probably contribute to specificity of the mRNA interaction to the protein. The 3-dimensional structure of intact T4 gp32 has not been solved, although a number of biochemical and physiological observations have provided clues that the protein is modularly organized into 3 distinct domains [ 19 ]. In particular, studies with proteolytic fragments of purified T4 gp32, including the analysis of a crystal structure for one of these fragments [ 20 ], have assigned the ssDNA binding function to a module formed by an internal segment of the 301-residue protein. It is presumed that this domain is responsible for binding specific RNA as well, although no direct evidence exists for this notion. In the studies described here, we show that the ssDNA-binding domain is highly conserved between T4 gp32 and the phylogenetic variant of this protein from the T4-like phage RB69. Yet, we also show that sequences of the mRNA targets for the two Ssb proteins are different and that the two repressors differ in their patterns of interaction with these targets. We present results suggesting that specificity of gp32 to RNA has co-evolved with specificity of this Ssb protein to other phage induced proteins of DNA metabolism that interact with gp32's C-terminal domain. Our studies suggest that the ability of a diverging regulatory RNA to make alternate contacts with a mutually plastic, but highly conserved, RNA-binding protein site may allow the RNA to tolerate mutational changes without loss of the regulatory function. Such plasticity of the interacting partners could allow for the evolution of a broad spectrum of gp32-RNA binding specificities despite selective pressures that conserve the amino acid sequence of the protein's nucleic acid-binding domain. Methods Bacterial and phage strains used The E coli K-12 strain K802 ( hsdR , hsdM + , gal , met , supE ) was used as host in cloning experiments and the E coli B strain NapIV ( hsdR k + , hsdM k + , hsdS k + , thi , sup o ) was the host for plasmid-mediated gene expression studies that utilized lambda pL control. E coli B strain BL21(DE3), which harbors a T7 RNA polymerase gene under cellular lac promoter control [ 21 ], was used as the host for T7 Φ10-promoter plasmids in pilot experiments that assessed toxicity of cloned RB69 gene 32 to bacterial cells. Cloning and nucleotide sequence determination of RB69 gene 32 In preliminary experiments, we used Southern blot analysis of AseI -digested RB69 genomic DNA to identify and retrieve an ~35-kb DNA fragment that hybridized to a T4 gene 32 -specific riboprobe under stringent conditions. The riboprobe was prepared by methods described previously [ 22 , 23 ] using the T4 gene 32 clone pYS69 [ 15 ], which was generously provided by Y Shamoo. We were unable to clone this AseI fragment in AseI -compatible Eco R1-generated ends of plasmid vectors. However, further digestion of the AseI fragment with ApoI (which generates Nde1 -compatible ends) yielded a shorter, ~15-kb, fragment that could be cloned in the NdeI-EcoRI interval of vector pNEB193 (cat# N3051S, New England Biolabs, Beverly, MA). The cloned fragment was sequenced and found to be very similar to the T4 genetic segment extending from gene 59 through the 5' terminal ~2/3 of gene 32 , except that the RB69-derived DNA appeared to lack a homologue of the T4 ORF 32.1 (see below). Comparisons between the T4 and RB69 gene 59-32 regions are diagrammed in Fig 1 . We retrieved the remainder (3' terminal segment) of RB69 gene 32 from RB69 genomic DNA, through PCR amplification using Taq DNA polymerase. For this purpose, we utilized two primers, one perfectly matching a sequence in the cloned AseI-ApoI RB69 fragment (ie, upstream primer: 5'GCTGCTAAGAAATTGTTCATAG3') and the other (the downstream primer), an 18-mer bearing the sequence 5'CAGCAGCAGTGAAACCTTTA3', was chosen from a PCR screen of an RB69 primer library. DNA amplification was carried out under low-stringency conditions for primer annealing (30 sec at 25°C), which allowed activity from the imperfectly matched downstream primer. We obtained several products that we resolved by agarose gel electrophoresis Only one of these products, an ~35-kb DNA fragment, hybridized, although poorly, to the T4 gene 32 -specific riboprobe initially used for the Southern blot analysis of Ase1 -digested RB69 genomic DNA. This fragment was sequenced, using the PCR, and found to contain the 3' terminal segment of RB69 gene 32 as well as some of the region distal to RB69 gene 32 (relative to the T4 genetic map). Collectively, sequence analysis of the cloned and amplified RB69 genomic segments yielded sufficient information for designing new primers to amplify, from genomic DNA, the entire wild-type RB69 gene 32 , as well as shorter segments of this gene and its putative control region in the untranslated RB69 IC59-32 region (Fig 1 ). DNA sequence information obtained from these analyses was also used for another study, which was aimed at determining the sequence of the entire RB69 genome (GenBank NC_004928). Figure 1 A comparison between the genetic maps of the Ssb protein (gp32) encoding regions of phages T4 and RB69. Note the presence of an open-reading frame (ORF) for a homing endonuclease (SegG protein; [45]) between T4 genes 59 (gp59; primase-helicase loader) and 32 (gp32; Ssb protein). The restriction sites we used for cloning RB69 gene 32 are marked, and compared to the locations of analogous sites in T4. GenBank Accession numbers for the genetic regions of interest are also noted. Assays for plasmid directed gene 32 expression We used the lambda pL plasmid vector pLY965 [ 24 ] to clone RB69 gene 32 sequences that were designated for in vivo expression studies. This vector expresses cloned DNA under control of the heat-inducible λ cI857pL element, which produces sufficient cI857 repressor under uninduced conditions (≤30°C) as to maintain pL -mediated expression at undetectable levels. Minimizing plasmid-driven transcription from pL contributed to stable maintenance of the cloned wild-type RB69 gene 32 , the product of which is highly toxic to bacterial cells. RB69 gene 32 mutants still emerged when such clones were grown at ≤30°C. Some of these mutants were archived for use as controls in certain studies (eg, PL2 and PL8, Fig 4 ). With the T7 Φ10-promoter expression vector pSP72 (Promega) as the cloning vehicle, clones containing the wild-type RB69 gene 32 were not viable when introduced into E coli BL21(DE3), probably because of residual (constitutive) lac -promoter activity in this bacterial host. To circumvent potential toxicity, pSP72-based recombinants were propagated in hosts lacking a T7 RNA polymerase gene. The purified plasmid DNA from these hosts was used for in vitro transcription and translation assays. Methods for the radiolabeling of plasmid encoded proteins and their subsequent analysis by SDS-PAGE have been described elsewhere [ 24 , 25 ], and conditions pertaining to specific experiments are given in figure legends. Figure 4 Results of experiments showing that RB69 gp32 is an autogenous translational repressor. For Panel A, λ CI857PLN -bearing plasmid clones of the diagrammed DNA segments were heat-induced (42°C) and assayed for gp32 synthesis as described in other work [24,27]. RBG32 is a DNA segment that carries the wild-type sequence from -120 through +900 relative to the first base of the initiator AUG of RB69 gene 32. RBG32Δop is a truncated derivative of RBG32 that lacks elements of the putative RNA pseudoknot of RB69 gene 32 (Figs 3 & 6). PL8 is identical to RBG32 except that it carries a single-base substitution (marked with an asterisk) in codon 173, leading to a F173S substitution in RB69 gp32. PL2 is similar to RBG32 and PL8, except that it carries several point mutations (map positions marked with asterisks). Panel B shows results of an experiment in which purified RB69 gp32 was shown to inhibit in vitro translation of purified mRNA from the cloned RBG32 fragment, as well as mRNA from in vitro expressed plasmid clone (coupled transcription/translation). Conditions for these assays are described in METHODS. Purification of gp32 from clones of the structural gene RB69 gp32 and T4 gp32 were purified from the overproducing clones pRBg32Δop (RB69 gp32) and pYS69 (T4 gp32), respectively. We used the gp32 purification protocol outlined by Bittner et al, [ 26 ] with minor modifications. The preparation of crude extracts, from 6-liter batches of heat-inducible E coli NapIV clones of phage genes, was as described previously for T4 RegA protein [ 27 ]. Anionic-exchange chromatography (using Q-Sepharose; Cat# 17-0510-01; Pharmacia) was as described for purification of plasmid-generated RB69 gp43 [ 28 ]. Under the conditions used, gp32 eluted at 0.3–0.4 M NaCl. In the subsequent chromatographic step, utilizing Phenyl-Sepharose (Cat#17-0965-05; Pharmacia), we tested column fractions for nuclease contamination by incubating 4 μl samples with plasmid DNA (~1 μg) overnight at room temperature and then analyzing the mixtures by agarose gel electrophoresis. The gp32-containing fractions that exhibited no hydrolysis of the plasmid DNA were pooled and the protein was purified further by chromatography on ssDNA-agarose (Cat #15906-019; Invitrogen). Pooled fractions from the ssDNA chromatography were dialyzed against a gp32 storage buffer containing 0.1 M NaCl, 20 mM Tris-HCl pH 8.0, 1 mM EDTA, 0.5 mM DTT and 50% glycerol Protein stocks (at 4–8 mg gp32/ml) were stored at -20°C until used. Preparation of RNA for in vitro studies RNA preparations used for footprinting and other in vitro studies originated from in vitro transcription of pSP72 clones of the desired gene 32 sequences Methods have been described elsewhere [ 29 ]. Phage-specific RNA sequences of the purified transcription products used for footprinting included nucleotide positions -102 to +161 (relative to the initiator AUG) in case of the RB69 gene 32 transcripts and positions -96 to +161 in case of the T4 gene 32 transcripts. These products also included a 10-nt sequence from the plasmid's T7 promoter region RNA sequencing was carried out by using the RVT-catalyzed primer-extension (cDNA synthesis) method described elsewhere [ 23 , 29 ]. Sequencing primers were annealed to codons 12 to 20 of the transcripts and the sequenced segments of the RNA spanned nucleotide positions +36 through about -100 relative to the initiator AUG. For in vitro translation assays, the RNA preparations included full length and truncated versions of the gene 32 open-reading frame from each of the 2 phage sources. Assays for gp32-mediated in vitro translational repression We used E coli S30 cell-free extracts (Cat#L1020; Promega) with purified pSP72-based gene 32 recombinant DNA (coupled transcription-translation assays) or purified RNA (DNA-free translation assays) to assess repressor activities of purified RB69 gp32 and T4 gp32. With plasmid-directed gene 32 expression, it was possible to use expression of the plasmid borne bla gene (β-lactamase) as an internal control. Each 50 μl in vitro assay reaction mixture (placed in a 15-ml conical tube) contained 1 μg of plasmid DNA template or 4 μg RNA, 5 μl of a mixture of all amino acids (1 mM each) except L-methionine, 1 μl of an S30-premix cocktail (containing rNTPs, tRNAs, an ATP generating system and required salts), 15 μl S30 extract and the balance of volume in nuclease-free water Reaction mixtures, including any added gp32, were constituted in an ice bath before transferring to 37°C for incubations (30 or 60 min). Reactions were stopped by rechilling in the ice bath. Proteins from 5 μl samples were precipitated with 20 μl acetone, collected by centrifugation, dried and suspended in SDS extraction buffer for analysis by SDS-PAGE and autoradiography. Analysis of plasmid encoded (N-terminal) gp32 fragments was carried out in SDS-PAGE (10% gels) using Tricine as the electrophoresis buffer. This buffer system allows for effective resolution of small polypeptides [ 30 ]. When used, purified gp32 was added at concentrations ranging between 5 and 20 μM. Treatments of RNA with RNases and chemical agents The RNA-modifying chemical reagents Dimethylsulfate (DMS; Cat# D18,630-9; Aldrich) and Diethylpyrocarbonate (DEPC; Cat# D5758; Sigma) and the ribonucleases (RNases A1, T1 and V1 respectively) were used to probe RB69- and T4-derived operator RNAs for intrinsically structured regions. The RNases were also used for RNA footprinting (protection by gp32) studies. DMS was diluted in absolute ethanol at ratios of 1:2, 1:4, and 1:5 ratio v/v and its effects were analyzed at the three concentrations. The reaction buffer contained 30 mM HEPES pH 7.5, 10 mM MgCl2. Reactions were stopped in 0.5 M β-mercaptoethanol and 0.75 M sodium acetate. The protocol for DEPC treatment was identical to that for DMS, except that we used 1 μl of DEPC per 100 μl of reaction mix and incubated the reactions at room temperature for 10 min. For the RNase-sensitivity assays, including gp32-mediated RNA footprinting, digestions with RNases A1 and T1 were carried out in 30 μl buffer containing 60 mM NH 4 Cl, 10 mM Mg acetate, 10 mM Tris-HCl pH 7.4, and 6 mM β-Mercaptoethanol. The buffer for digestions with RNase V1 contained 25 mM Tris-HCl pH 7.2, 10 mM MgCl 2 , and 0.2 M NaCl Incubations were at 37°C in 30 μl buffer in all cases. RNase treatments were halted with an equal volume of buffer containing 0.4 M Na acetate pH 5.2, 20 mM EDTA, and 30 μg E coli tRNA. When used for RNA footprinting, RB69 gp32 or T4 gp32 was added at concentrations in the range between 1 μM and 5 μM. Results A sequence comparison between T4 gp32 and RB69 gp32 The amino acid sequence of RB69 gp32 was deduced from the determined nucleotide sequence of the gene. An alignment between the predicted primary structures of this protein and its T4 homologue is shown in Fig 2 , which also highlights the main differences between the 2 proteins and points out certain functionally important landmarks on the T4 gp32 sequence. The two proteins are identical at ~85% of amino-acid positions (92% overall similarity), with most of the differences being clustered in 2 short blocks of amino-acid sequence in the highly charged C-terminal segment of the protein, D264(RB69)/A264(T4) to L299(RB69)/L301(T4). Both C-terminal segments are rich in serines and aspartates; however, they differ in their arrangements of these residues and the serine-rich cluster is 5 residues longer in T4 gp32 (S282-S286). In contrast to their conspicuous differences in the C-terminal domain, T4 gp32 and RB69 gp32 are closely similar in segments that, in T4 gp32, have been implicated in cooperative gp32-gp32 interactions (95% identity/100% similarity for the N-terminal 21 residues) and ssDNA binding (residues 21 to 254; ~92% identity/~95% similarity). We note that all T4 gp32 residues that have been implicated in ssDNA binding are conserved in RB69 gp32 (Fig 2 ). However, interestingly, codon sequences for the two aligned N-terminal gp32 segments differ at many third nucleotide positions between T4 and RB69, suggesting that there has been natural selection for amino acid identity (and not merely chemical or side-chain similarity) in the N-terminal two-thirds of the phage Ssb protein. We also note that both proteins contain 2 "LAST" (3KRKST7 or 110KRKTS114) sequence motifs, which in the T4 system have been implicated in interactions with the negatively charged surfaces of DNA as well as with the C-terminal domain of gp32 [ 31 ]. One of these motifs (K3-T7) lies near the extreme N-terminus of the protein and the second (K110-S114) is adjacent to a short sequence (residues 102–108) that diverges between T4 and RB69 (~50% similarity), but that also contains 3 conserved charged residues including the DNA-binding tyrosine Y106 of T4 gp32 [ 20 ]. Figure 2 Amino-acid sequence alignments between the Ssb proteins (gp32s) of T4 and RB69. Residues and segments of the T4 gp32 sequence that have been implicated in specific biological functions of the protein are marked as follows: Db [DNA binding residue]; Zb (residues that coordinate Zn ++ in the zinc-binding domain; [20,46]); gp32-gp32 [residues involved in cooperative gp32 binding to ssDNA]; XLgp59 (residue that cross-links to gp59; [42]); LAST (sequence motifs, (Lys/Arg)3 (Ser/Thr)2, that have been proposed to directly bind nucleic-acids or mediate gp32-gp32 interactions [31]). The shaded C-terminal portion of T4 gp32 has been implicated in interactions with other phage induced proteins [38]. The small deletion (Δ 32PR201 ) alters specificity of T4 gp32 in phage replication without affecting autogenous translational repression [39]. The largest vertical arrows denote trypsin-hypersensitive sites (19) The G-to-A mutation marked "(ts)" was isolated in this laboratory as a missense (temperature-sensitive) suppressor of a defective gp43 function (unpublished). In the RB69 gp32 sequence, residues whose codons differ from their conserved T4 counterpart at the third nucleotide are underscored with a single dot; those differing by 2 nucleotides are marked by 2 dots. The RB69 IC59-32 region Figure 3 shows an alignment of the RB69 IC59-32 region with its counterpart (the IC32.1-32 region) from T4 The T4 region (GenBank NC_00866) has been experimentally documented to harbor the translational operator for gene 32 expression [ 6 ]. The RB69 counterpart (GenBank NC_004928) is 7 nucleotides longer and ~70% identical in sequence. By comparison, the gp32 encoding portions of the T4 and RB69 genes are ~80% identical in the overall nucleotide sequence (see Fig 1 for GenBank accession numbers) and their predicted protein products are >90% similar in amino acid sequence. There is an additional 40-nt untranslated sequence in the RB69 IC59-32 region that appears to have no T4 counterpart (Fig 3 ), and ORF321 is missing altogether in RB69 (Fig 1 ). So, it appears that the regions between genes 59 and 32 of T4 and RB69 have undergone more evolutionary divergence from each other than their gp32-encoding regions. However, despite their differences in nucleotide sequence, the translational operator sequence of T4 gene 32 and its putative RB69 counterpart are predicted, by computer programs, to form similar structures. We address this prediction below and present experimental evidence for the RNA structure and its role in translational control of RB69 gp32 synthesis. Figure 3 A comparison between the nucleotide sequences of the T4 IC32.1 - 32 and RB69 IC59 - 32 regions. These 2 regions contain determinants for translation initiation of the respective phage-induced mRNAs for gp32. The chart emphasizes sequence differences (entered as lettered residues in the RB69 sequence) between the 2 regions. The dashes indicate identity between RB69 and T4 residues. Sequence elements contributing to RNA pseudoknot formation in the T4 gene 32-specific mRNA are marked by horizontal arrows. Note the sequence overlap between elements of the pseudoknot and ORF32.1 (segG) of the T4 sequence. Also, see Fig 6 for a summary of properties of the RB69 sequence. RB69 gp32 and T4 gp32 are functionally similar Figure 4 shows results from experiments that measured the effects of RB69 gp32 on its own synthesis in vivo (Fig 4A ) and in vitro (Fig 4B ). The in vivo experiments measured plasmid-directed RB69 gene 32 expression by E coli clones carrying wild-type and mutant versions of the RB69 gene. As shown in Fig 4A , induced expression of the gene was lower (by ~4-fold) with the wild-type construct than with deletion mutants of the untranslated 5' leader of the mRNA (RBG32Δop, Fig 4A ) or missense mutants in the structural gene from this phage (PL2 and PL8 constructs; Fig 4A ). These observations are consistent with the explanation that RB69 gp32, like T4 gp32, is able to bind and repress its own mRNA. The results shown in Fig 4B confirm that purified RB69 gp32 is a potent repressor of translation of purified mRNA for this protein. We have used similar experiments to those for Fig 4 to compare repressor activities of T4 gp32 and RB69 gp32 on identical RNA targets, and observed that either protein can repress gene 32 -specific mRNA from either source (results not shown). However, such experiments, which require 10–30 μM purified protein to demonstrate repression (Fig 4B ), did not unambiguously distinguish between the RNA-binding specificities of the 2 proteins. Also, in phage-plasmid complementation assays, we observed that the cloned RB69 wild-type gene 32 supported efficient growth of T4 gene 32 mutants (bursts of ~100) By these criteria, the T4 and RB69 proteins appeared to be similarly functional in each other's physiological systems. Yet, the natural targets for the 2 proteins are clearly different from each other in topography (Fig 3 ) and as we describe later, RNA-binding specificity differences between the 2 proteins could be detected through in vitro RNA-footprinting assays, which utilized lower concentrations of gp32 than is usually required to detect gp32-mediated repression by in vitro translational assays. RNA structure in the RB69 gene 32 translational initiation region (TIR) As discussed above for Fig 3 , computer-assisted and visual examinations of the RB69 IC59-32 nucleotide sequence predicted an RNA topology that was similar to the T4 gene 32 translational operator, particularly with regards to presence of a putative RNA pseudoknot structure to the 5' side of the Shine-Dalgarno and UUAAA/UUAA sequence elements of the mRNA. We used 3 RNA modifying agents to test directly for intrinsic secondary or higher-order structure in the RB69-derived RNA: DMS, DEPC and RNase V1, respectively. Results are shown in Fig 5 . We observed that the RB69-derived sequence from nucleotide position A(-1) through A(-45), relative to the initiator AUG, was hypersensitive to cleavage following DMS or DEPC treatment (Fig 5A ) and relatively insensitive to cleavage by the dsRNA-specific RNase V1 (Fig 5B ). These observations, which are summarized in Fig 6A , are consistent with the prediction that the A(-1) to A(-45) segment of the RB69 IC59-32 RNA region is intrinsically unstructured. In contrast, the segment of this RNA corresponding to the putative pseudoknot structure can accommodate a range of /RNA sequences. The interaction may also be subject to is hypersensitive to RNase V1 (Fig 5B ) and less sensitive than the A(-1) to A(-45) segment to the 2 chemical agents used (Fig 5A ). There was one unexpected observation in these experiments RB69 nucleotide position U(-20), which is located in the putatively unstructured portion of the RNA target (Fig 6A ), appeared to be insensitive to DEPC modification (Fig 5A ). Below, we show that another position in this segment, G(-10), is relatively insensitive to the ssRNA-specific RNase T1. Possibly, cleavage at U(-20) and G(-10) by RNA modifying agents is affected by RNA hairpin formation in the U(-8) to A(-21) sequence. The location of this putative hairpin, which is not predicted in the T4 RNA counterpart, is diagrammed in Fig 6A . In summary, the T4 gene 32 translational operator region and its putative counterpart from RB69 exhibit several topographical differences from each other, including an additional 6-nt sequence in RB69 that may contribute to RNA secondary structure formation in the RBS. Below, we show that the 2 regions also differ in their interactions with translational repressors. Figure 5 Portions of autoradiograms from RNA sequencing gels showing sites of cleavage in RB69 gene 32-derived RNA following treatments with DMS and DEPC (Panel A) and RNase V1 (Panel B). These experiments probed the RB69 RNA for secondary and higher-order structure. The lanes marked "RNA seq" show results from sequencing untreated RNA by the RVT-catalyzed chain termination method [23,35]. In Panel A the lane marked with a "minus" sign shows the positions of RVT chain termination caused by RNA structure in the untreated RNA. The DMS and DEPC lanes show sites of hypersensitivity (cleavage) of the same RNA to treatment with these chemical agents. In Panel B, the V1 lanes denote the amount of RNase V1 (×10 -5 units) used to digest the RNA substrate. Figure 6 Summaries of results from the chemical and RNase sensitivity and RNA footprinting studies reported here. Panel A shows our interpretation of experiments that probed the existence of RNA structure in RB69 gene 32-specific RNA (Fig 5). The T4-derived RNA counterpart is shown for comparison The "caret" symbol denotes sensitivity to cleavage after DMS treatment; asterisks denote sensitivity to cleavage after DEPC treatment. The darker symbols denote greater sensitivity. Positions that are not marked by any symbols were resistant to the modifying agents under the conditions used. Vertical arrows mark positions that were sensitive to RNase V1. Panel B shows our interpretation of the RNA footprinting studies described in Figs 7 and 8. Positions of protection from RNaseA1 by gp32 are marked by the triangles and protection from RNase T1 by the pentagonal symbols. The darker symbols denote stronger protection. Unmarked positions were not protected by either gp32 from phage source under the experimental conditions used. The footprints of T4 gp32 and RB69 gp32 on gene 32-specific RNA targets from T4 and RB69 We used the ssRNA-specific RNases A1 and T1 to determine the abilities of gp32 from the 2 phage systems to protect RNA targets from cleavage with these enzymes. These RNA footprinting studies also extended the information we obtained from treatments with DMS and DEPC about intrinsic structure of the RNA targets. Results are shown in Fig 7 for the RB69-derived RNA target and Fig 8 for the T4-derived target. Also, a summary of our observations from these experiments is presented on the RNA sequence charts in Fig 6B In the aggregate, our studies showed that T4 gp32 and RB69 gp32 contact RNA targets differently from each other, although the two proteins overlap in their RNA-binding properties. We highlight the following specific observations. Figure 7 In vitro footprinting of RB69 gene 32-specific RNA with purified RB69 gp32 (Panels A and B) and T4 gp32 (Panels C and D). Preparation of RNA and proteins and experimental conditions for footprinting are described in METHODS. Horizontal arrows mark nucleotide positions (Fig 6B) that exhibited gp32-mediated protection from RNaseA (panels A and C) and RNase T1 (panels B and D). Darker arrows denote stronger protection. The results are summarized in Fig 6B. Figure 8 In vitro footprinting of T4 gene32-specific RNA with purified RB69 gp32 (Panels A and C; RNase A) and T4 gp32 (Panels B and D; RNase T1). Conditions for these experiments were identical to those described in Fig 7, except that the RNA substrate used for footprinting was derived from clones of T4 gene 32 rather than RB69 gene 32. See also Fig 6C for a summary. 1. At the protein concentrations used (1–5 μM), the RB69 gp32 footprint on the RNA target from RB69 was 5 residues longer than the footprint of this protein on the T4-derived RNA target; however, the positions of the 2 footprints relative to the respective initiator AUG and 5' terminal boundary of the pseudoknot structure appeared to be identical (Fig 6 ) 2. As can be seen in Figs 7A and 7B , RB69 gp32 protected its own mRNA target strongly within the nucleotide segment between U(-14) and G(-61), and weakly in the segment from U(-2) to G(-9) In contrast, as seen in Figs 7C and 7D , T4 gp32 protected this RNA strongly only in the segment from C(-42) to G(-61) 3. As can be seen in Fig 8C and 8D , T4 gp32 protected the T4-derived RNA strongly in the G(+3) to U(-70) segment In contrast, RB69 gp32 protected this RNA target best in the U(-16) to U(-70) segment (Fig 7A and 7B ) It should be noted that the gp32 footprint sizes reported here are shorter than has been reported in studies that utilized higher concentrations of T4 gp32 with T4-specific RNA targets [ 16 , 32 ]. As stated earlier in this report (Fig 4 ), the higher gp32 concentrations (>5 μM) mask specificity differences between the T4 and RB69 proteins. Discussion Phages T4 and RB69 are phylogenetically related to each other and encode homologous sets of DNA replication proteins that exhibit a significant degree of compatibility with each other's biological systems [ 22 , 24 ]. Despite such overlaps in function, we have commonly observed specificity differences between protein homologues from the 2 phage systems. For example, in plasmid-phage complementation assays, RB69 DNA polymerase (gp43) was observed to be just as effective as T4 gp43 in T4 DNA replication in vivo , whereas the T4 enzyme was less effective than its RB69 counterpart for RB69 DNA replication [ 22 , 33 ]. Also, the 2 DNA polymerases, like the 2 Ssb proteins compared here, are RNA-binding autogenous translational repressors that differ in RNA binding specificity and RNA target sequence. Studies with the T4 versions of gp43 and gp32 clearly show that the binding of these proteins to specific RNA is mutually exclusive with their binding to DNA [ 7 , 34 ]. So, conservation of the translational functions of these proteins may be related to conservation of their replication functions. Based on previous studies with RB69 gp43 [ 35 ], as well as the current study with RB69 gp32, we surmise that neither of these translational repressors possesses a domain that binds RNA exclusively. Rather, in both cases, the RNA binding site seems to be contained within the region of the protein that binds DNA. Thus, it is possible that in phage infected cells, specific RNA serves as a regulator of both the biosynthesis and replicative activities of these proteins. In the purified system we have used to compare RNA footprints for gp32 from T4 and RB69 (Figs 6 , 7 , 8 ), we observed that the same RNA target could exhibit different patterns of protection depending on source of the Ssb protein. This observation suggests that the RNA-protein interaction is intrinsically flexible and can accommodate a range of RNA sequences as long as these sequences can be made to assume a certain configuration. In addition, the interaction could be subject to modulation by intra- and intermolecular protein-protein interactions of the repressor. In this regard, it is known that the extreme N-terminal segment (~20 residues) and C-terminal segment (~100 residues) of T4 gp32 have profound effects on the ssDNA binding activity, which is housed in the region bracketed by these 2 segments of the protein [ 19 , 36 , 37 ]. The N-terminal segment determines cooperative binding to ssDNA (through gp32-gp32 interactions) and the C-terminal segment has been implicated in interactions of gp32 with other phage induced proteins [ 38 ]. Possibly, the observed sequence divergence between the C-terminal domains of T4 gp32 and RB69 gp32 (Fig 2 ) was in part coupled to divergence of the mRNA targets during evolution of the 2 related translational repressors. Although we cannot rule out the possibility that the C-terminal domain of gp32 influences specificity to RNA by interacting directly with this ligand, there are indications that this negatively charged segment of gp32 is a modulator of gp32 interactions with nucleic acids rather than a carrier of nucleic acid binding determinants. In particular, a small deletion that maps within this protein segment (Δ 32PR201 ; Fig 2 ) exhibits altered specificity to other proteins but has no effects on autogenous control of gp32 synthesis in vivo [ 39 ]. Also, recent studies with purified RB69 gp32 implicated the C-terminal domain of this protein in regulating access of gp43 from the same phage to binding sites in the ssDNA-binding module of the Ssb protein [ 40 ]. It has also been shown that in T4, the ssDNA-binding module of gp32 forms specific crosslinks to gp59, the phage-induced primase-helicase loading protein [ 41 , 42 ]. Such observations suggest that the 2 nucleic-acid binding functions of gp32 may be subject to regulation by a combination of intra- and intermolecular protein-protein interactions involving the divergence-prone C-terminal domain. It would be particularly interesting to find out if the gp32 sequence divergence near the DNA binding residue Y106 (Fig 2 ) is important for RNA recognition. X-ray crystallographic studies [ 20 ] suggest that T4 gp32 residues T101-K110 constitute part of the ssDNA-binding surface of the protein, which includes Y84, Y99, Y106 and the nearby "LAST" motif (residues 110–114; 31). Also, as suggested by the 3D structure, these residues are located within or very close to the Zn-binding domain of the protein; ie, the putative "zinc-finger" sequence Cys77-X3-His-X5-Cys-X2-Cys90, which has counterparts in a number of RNA-binding proteins [ 40 ]. The construction and analysis of RB69-T4 gp32 chimeras could help to establish if the divergence near Y106 is responsible for the observed differences in RNA footprints between T4gp32 and RB69 gp32 (Figs 6 , 7 , 8 ). In summary, we envisage that as a mediator of gp32's interactions with other phage induced proteins, the C-terminal domain of gp32 may co-diverge with its protein targets to maintain mutual recognition, and that structural plasticity of a conserved ssDNA-binding domain may allow an also diverging RNA target to establish rearranged contacts within a relatively conserved protein pocket. It is unclear if the 2 sets of divergence are interconnected, but together, they could facilitate the evolution of a high degree of diversity in how the synthesis and/or replication activity of this Ssb protein is regulated among phylogenetic relatives of T4. It will be important to find out if this diversity includes RNA ligands for gp32 that control the DNA-binding activity but not synthesis of gp32, or if autogenous translational repression has been replaced by other mechanisms for control of gene 32 in some T4 relatives. There is at least one reported example where evolution resulted in lack of RNA binding function in the Ssb protein of an M13-like phage [ 43 ]. Also, a scan of available genomic sequences for T4-like phages reveals a high degree of sequence divergence in the putative translational operator regions of the corresponding gene 32 regions. In one case, phage RB49 (GenBank NC_005066), it has been reported that there are no indications that an RNA pseudoknot structure exists in the putative TIR for gene 32, although the UUAA/UUAAA sequence units are conserved in the RB49 IC59-32 region [ 44 ]. It remains to be seen if gp32 from this and other T4 like phages that appear to lack the RNA pseudoknot do bind their respective TIR regions or repress their own translation. Finally, we should comment about ORF32.1 (Fig 1 ) and its possible relevance to evolution of the mRNA target for gp32. This ORF is present in some T4-like genomes (eg T4 and GenBank Ac No AF033323) and absent in others (eg, RB69 and GenBank Ac No AY310907). Recently, it was shown that T4 ORF 32.1 encodes a Seg-type (G1Y-YIG family) homing endonuclease (now named SegG) that mediates its own transfer, along with T4 gene 32, to the ORF32.1 -less genome of phage T2 in T4 × T2 genetic crosses. We note that the 5' terminal sequence of the RNA pseudoknot for T4 gp32 translational control overlaps the reading frame of the segG gene, in addition to being very similar (~83% identity) to the corresponding segment of the pseudoknot sequence of RB69, which lacks a segG gene (Fig 3 ). Possibly, this portion of the RNA pseudoknot preexisted the entry of an ORF32.1 -like sequence element into the gene 59-32 intercistronic region of a T4 progenitor and that the modern day segG gene ( ORF32.1 ) may be a chimera consisting of an extension of the parental segG reading frame into the recipient genome's pseudoknot sequence. Such lateral transfer events and subsequent mutation may have profound influences on evolution of the RNA binding functions of proteins that have relaxed sequence but stringent structural requirements for their RNA target. Competing interests None declared. Authors' contributions Jamilah Borjac-Natour: Conducted most of the experimental work and initial data analysis and prepared summaries; wrote the first draft and participated in subsequent revisions of the manuscript. Vasiliy Petrov: Conducted independent analysis of data and generated summaries and composite figures for presentation in the manuscript. Participated in revision of the manuscript during later stages of preparation. Jim Karam: Directed the study, evaluated results on an ongoing basis, worked closely with the coauthors during preparation of Figures, played a major role during revision of manuscript drafts and communicated the manuscript to the journal.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535899.xml
529452	Fibromatosis of the hand associated with EMO syndrome: A Case report	Background EMO syndrome, defined as a triad including exophthalmus, pretibial myxedema and osteoarthropathia, is a rare condition in patients suffering from hyperthyreosis. Case presentation We here describe an interesting case of EMO syndrome associated with unilateral fibromatosis of the hand and an initial stage of generalized myxedema of the skin. To our knowledge a similar case has not yet been described in literature though reports about associated fibromatosis, e.g. located retroperitoneally, already exist. Familiar explanations include its initiation by autoimmune processes or aberrant T-cell cytokine stimulation leading to an overwhelming production of glycosaminoglycans. Conclusion Interpreting our case in context with previous reports we conclude that associated fibromatosis induced by autoimmune processes may affect a variety of different localizations and therefore requires careful monitoring. A therapeutical attempt by using UVA1 irridation for pretibial myxedema remained without a satisfying regression.	Background EMO syndrome is a rare condition seen in patients suffering from hyperthyreosis. It is defined as a triad of exophthalmus, pretibial myxedema and osteoarthropathia occurring in less than 1% of patients suffering from Graves' disease [ 1 ]. We here describe an unusual case of EMO syndrome associated with unilateral fibromatosis and an initial stage of generalized myxedema of the skin. Case presentation In October 2003, a 64-year-old male Caucasian patient was admitted with aggravating pretibial myxedema. Five years ago, he was diagnosed with hyperthyreosis caused by Plummer's disease. Laboratory findings revealed a repressed TSH of 0.01 mU/L (0.4–4.0 mU/L). The patient was treated with radioiodine therapy. Today he suffers from hypothyreosis and a daily substitution of 100 μg L-Thyroxin is performed. Within the months following the radioiodine therapy, an erythema progressing into a manifest pretibial myxedema developed, followed by exophthalmus and fibromatosis of the right hand within the next three years. Surgical orbita decompression due to massive exophthalmus was performed, followed by a subsequent correction of the ocular muscles. Additionally, the fibromatosis of the right hand was excised. Retrospective histological findings revealed a regressive sclerotic fibrosis of firm kollagenous fibers embedded in soft and fat tissue were consistent with a generalized fibrosing process as known in myxedema. Within the last months, decent mucous plaques of the upper limps decreased. The patient now reported progressing congestion of lymph and decreasing flexibility of the lower legs caused by the pretibial myxedema. Clinical examination confirmed massive pretibial myxedema, lymphatic congestion of the lower legs, generalized myxedema accentuating the upper limps, a residual postsurgical nodular tumor of the ulnar aspect of the right hand, exophthalmus, and severe hypertrophic osteopathy of the distal phalanges with clubbed fingers and hippocratic nails (Fig. 1 ). A Complete check-up including autoantibodies remained unremarkable. Under substitution of 100 μg L-Throxin daily we found the following thyroidal values: T3 0.94 ng/ml (0.59–1.74), T4 10.17 μg/dl (4.50–12.00), TSH 0.47 μIE/ml (0.38–4.70), fT3 2.64 pg/ml (1.45–3.48), fT4 1.44 ng/dl (0.71–1.85). There were no hints for additional fibromatosis. The classical combination of exophthalmus, pretibial myxedema and acropachy led to the diagnosis of EMO syndrome associated with fibromatosis of the right hand and a beginning generalized myxedema of the skin. Figure 1 Pretherapeutic clinical appearance of a 64-year-old patient consistent with the diagnosis of EMO syndrome, exophthalmus (a), combined lymphatic congestion and pretibial myxedema (b) and palmoulnar fibromatosis (intrasurgical, c). Conclusions Grave's disease is known to eventually develop after radioiodine therapy [ 2 ] and this may be followed by a EMO syndrome. To our knowledge this is the first report about a EMO syndrome combined with coexistent palmoulnar fibromatosis. The patient was treated with lymphdrainage and physiological compressive therapy. As Farr et al. [ 3 ] reported the successful use of PUVA in a case of scleromyxedema, we initiated a therapeutic attempt with conventional UVA1 irradiation five times a week for one week followed by three times per week for three consecutive weeks (20 J/cm 2 single dose, 280 J/cm 2 cumulative dose). While the congestion of lymph clearly improved, pretibial myxedema remained without any signs of regression. A massive recurrence after excision of thyroid dermopathy, as described in literature, could not be observed in our patient during a follow-up of 2.5 years. Generalized fibrosing processes are thought to be based on an accumulation of glycosaminogylcans. Common explanations comprise its initiation by autoimmune processes, e.g. thyreotropin receptors on fibroblasts, or aberrant T-cell cytokine stimulation, leading to overwhelming glycosaminoglycan production [ 4 ] Fibrosing processes such as retroperitoneal or sellar associated with EMO syndrome or multifocal fibrosclerosis, respectively, have been previously reported [ 5 , 6 ]. Nevertheless, coexistent palmar fibromatosis so far has not been described. Therefore, we conclude that concomitant fibromatosis might appear in various localizations requiring elaborated diagnostic procedures and monitoring in all patients affected. We started low-dose UVA1 irradiation of the pretibial myxedema known to be able to degrade pathologic collagenous architecture by inducing dermal matrix-metalloproteinases as well as by decreasing abnormal cytokine liberation following T-cell apoptosis [ 7 ]. Nevertheless, our patient discontinued UVA1 phototherapy due to non response after a cumulative dosage of 280 J/cm 2 UVA1 (seven treatment sessions). However, we suggest that phototherapy might also be considered as an adjunct therapeutic alternative in persistent EMO syndrome. Competing interests The author(s) declare that they have no competing interests. Authors' contributions C.A. attended to the patient, participated in the design of the case report, and drafted the manuscript. A.K. conceived the study. F.B., A.B. and P.A. participated in its design and coordination. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529452.xml
535906	Transcriptional oscillation of canonical clock genes in mouse peripheral tissues	Background The circadian rhythm of about 24 hours is a fundamental physiological function observed in almost all organisms from prokaryotes to humans. Identification of clock genes has allowed us to study the molecular bases for circadian behaviors and temporal physiological processes such as hormonal secretion, and has prompted the idea that molecular clocks reside not only in a central pacemaker, the suprachiasmatic nuclei (SCN) of hypothalamus in mammals, but also in peripheral tissues, even in immortalized cells. Furthermore, previous molecular dissection revealed that the mechanism of circadian oscillation at a molecular level is based on transcriptional regulation of clock and clock-controlled genes. Results We systematically analyzed the mRNA expression of clock and clock-controlled genes in mouse peripheral tissues. Eight genes ( mBmal1 , mNpas2 , mRev-erbα , mDbp , mRev-erbβ , mPer3 , mPer1 and mPer2 ; given in the temporal order of the rhythm peak) showed robust circadian expressions of mRNAs in all tissues except testis, suggesting that these genes are core molecules of the molecular biological clock. The bioinformatics analysis revealed that these genes have one or a combination of 3 transcriptional elements (RORE, DBPE, and E-box), which are conserved among human, mouse, and rat genome sequences, and indicated that these 3 elements may be responsible for the biological timing of expression of canonical clock genes. Conclusions The observation of oscillatory profiles of canonical clock genes is not only useful for physiological and pathological examination of the circadian clock in various organs but also important for systematic understanding of transcriptional regulation on a genome-wide basis. Our finding of the oscillatory expression of canonical clock genes with a temporal order provides us an interesting hypothesis, that cyclic timing of all clock and clock-controlled genes may be dependent on several transcriptional elements including 3 known elements, E-box, RORE, and DBPE.	Background The circadian rhythm of about 24 hours is a fundamental physiological function observed in almost all organisms from prokaryotes to humans. Circadian rhythms have been known to be generated in pacemaker cells, the suprachiasmatic nuclei (SCN) of hypothalamus in mammals, and entrained by environmental cues, such as light, temperature, noise, feeding or social cues, whereas a recent analysis using mPer2 luciferase knockin mice has demonstrated that peripheral tissues express self-sustained circadian oscillations [ 1 ]. The output of circadian oscillation appears as locomotive activity, hormonal secretion, the sleep-wake cycle, and many other physiological functions. Disruption of the circadian rhythms has been associated with various kinds of diseases, such as cardiovascular diseases, psychiatric diseases and cancer in humans [ 2 - 6 ]. Identification of clock genes has allowed study of the molecular bases for circadian behaviors and temporal physiological processes and has prompted the idea that molecular clocks reside not only in a central pacemaker, but also in peripheral tissues, even in immortalized cells [ 2 , 3 , 6 ]. Furthermore, previous molecular dissection revealed that the mechanism of circadian oscillation at a molecular level is based on transcriptional regulation of clock and clock-controlled genes, which consists of interwoven positive and negative feedback loops [ 2 , 7 - 10 ]. There is a distinct connection between genes and behaviors in circadian rhythms, which is conserved from fly or other lower organisms to humans [ 6 , 8 ]. The Drosophila period mutants, originally identified as a circadian mutant brought us the first clock gene, period [ 8 , 11 ], while a point mutation of hPer2 was recently shown to cause a familial advanced sleep phase syndrome [ 12 ]. As described above, circadian rhythms rely on a negative feedback loop in gene expression that involves a limited number of clock genes. Recent molecular dissection has increased our understanding of the molecular nature of the transcriptional regulation of some clock genes. The circadian phenotypes at the cellular level may be represented as temporal mRNA expression. Global gene expression profiling using microarrays has led to the discovery of many circadian-regulated genes, but there is only a minor overlap of cycling transcripts between tissues [ 10 , 13 , 14 ]. Thus, circadian rhythms are an appropriate study target for systems biology. In this study, we systematically examined the mRNA expression of common circadian-regulated genes in several mouse peripheral tissues and made oscillatory profiles of canonical clock genes. Moreover, by bioinformatics, we identified 3 clock elements for circadian transcription (E-box, RORE, DBPE). These 3 elements and their combination would suffice to explain the biological timing of expression of these clock and clock-controlled genes. Results and discussion To examine the circadian expression of mouse clock and clock-related genes in peripheral tissues, we performed the quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR) method on mRNAs from 7 different mouse peripheral tissues (heart, lung, liver, stomach, spleen, kidney, and testis; Fig. 1 ). After entrainment of housed mice for 2 weeks under a light-dark (LD) cycle, samples were collected every 4 hr starting at circadian time (CT) 0 (n = 3 at each time point) in the third dark-dark (DD) cycle. Out of 14 mouse genes examined, 8 genes ( mBmal1 , mNpas2 , mRev-erbα , mDbp , mRev-erbβ , mPer3 , mPer1 and mPer2 ; given in the temporal order of the rhythm peak; see also Fig. 2 ) showed robust circadian of mRNA expression in all tissues except the testis. These genes should thus be considered to be core molecules of the circadian clock. Circadian mRNA expression patterns were similar in each tissue with the exception of testis, where weak or no rhythm was observed. This common pattern of the rhythm throughout many peripheral tissues implies that there may exist a universal mechanism for resetting the peripheral clock. The peak transcript level of each circadian rhythm was as follows: mBmal1 and mNpas2 , in subjective night at CT20-CT0; mRev-erbα , in subjective day at CT4-8; mDbp and mRev-erbβ , at CT8; mPer3 , at CT8-12; mPer1 , at CT12; and mPer2 , at CT12-16 (Figs. 1 , 2 , and 4 ). In the peripheral tissues mRNA peaks occurred approximately 4 hr later than those in the central pacemaker, SCN [ 15 - 20 ]. In the testis, 4 genes ( mBmal1 , mNpas2 , mRev-erbα , and mDbp) showed weak rhythms of their mRNA expression, while no other genes, including the mPer family, showed any clear oscillation. Surprisingly, the expression of mPer1 transcripts in the testis, which did not show a circadian rhythm, was substantially higher than other tissues, and exceeded RNA expression of other genes studied in the testis. This is consistent with data recently reported [ 21 - 23 ]; although a previous report indicated circadian rhythm of mPer1 in the testis [ 20 ]. These findings suggest that mPer1 may play an alternative role in the testis, including developmental regulation during spermatogenesis. The rhythm of mCry1 mRNA expression was obviously circadian (peaking at CT16-20, with a trough at CT4-8) except in the testis, but the peak-trough amplitude was relatively smaller than that of the above genes. mCry2 and mClock RNA levels seemed to be rhythmic except in the testis, but the rhythm was rather weak and not clearly circadian. No circadian rhythms were observed in the remaining 3 genes examined, i.e. mCKI-δ , mCKI-ε , and mTim . Despite a central role in Drosophila for timeless ( dTim ), the mammalian homologue ( mTim ) was originally found to show weak or no rhythm in the SCN [ 24 - 26 ]; and its functional role in mammalian clocks remains controversial [ 27 , 28 ]. Figure 1 Temporal mRNA expression of clock and clock-related genes in mouse peripheral tissues Abscissa presents time at CT (circadian time); and ordinate, mRNA amounts. The relative levels of each RNA were normalized to the corresponding G3-PDH RNA levels. The maximum RNA amount was set to 100. Data are presented as the mean ± SE of triplicate samples. Figure 2 Circadian mRNA expression of canonical clock genes in mouse peripheral tissues The maximum RNA amount in a 24-h period is indicated by the darkest red (100), while no RNA (0) shown by white. The depth of the color corresponds to the RNA amount. Figure 4 Diagram representing the relationship between 3 transcriptional elements and the peak mRNA expression of canonical clock genes The peak of Per3 mRNA expression is at CT8-12, and its regulatory region includes only conserved DBPEs (yellow) among the 3 elements. The peak of Per2 mRNA is at CT12-16, and its promoter region includes only an E-box (green). The peaks of Bmal1 and Npas2 mRNA are at CT20-0, and their regulatory regions contain only ROREs (blue). The peaks for the other clock genes, which contain 2 or 3 elements, are placed as indicated. The bar at the top represents light (gray) and dark (black) cycles. As described above, the expression of 8 genes fluctuated in an overt circadian fashion; and so we aligned them in the order of the peak of their oscillatory phase (Fig. 2 ). Among them, the transcriptional oscillation of 2 representative clock genes, Bmal1 and Per2 , was examined by using the real-time luciferase reporter assay. NIH3T3 cells were transfected with the hBmal1 -Luc or mPer2 -Luc construct and then stimulated with a high concentration of serum. After the serum shock, in the presence of luciferin, light emission was measured and integrated for 1 min at intervals of 15 min. Both promoters fused to luciferase showed circadian rhythms (Fig. 3 ). The phase of Bmal1 oscillation in cultured cells was almost the opposite of that of Per2 , which is consistent with data of mRNA expression in mouse peripheral tissues obtained by real-time RT-PCR (Fig. 2 ). This result indicates that the promoter regions used in the real-time luciferase reporter assay are sufficient for producing circadian transcriptional oscillation. The promoter analyses of several clock genes have been reported, as described below. Figure 3 Transcriptional oscillation of Bmal1 and Per2 Transcriptional oscillation of Bmal1 (red) and Per2 (blue) was monitored by using a cell culture-based luminescence reporter assay. NIH3T3 cells were transfected with the hBmal1 -Luc or mPer2 -Luc constructs and then stimulated with a high concentration of serum. After the serum shock, in the presence of luciferin, light emission was measured and integrated for 1 min at intervals of 15 min. Ordinate and abscissa represent relative counts and time after serum shock, respectively. The peak of the count was set to 1. 1440 minutes = 1 day. Figure 5 Table 1. Three transcriptional elements (RORE, E-box, and DBPE) conserved among the sequences of 3 species (human, mouse, and rat) Numbers in parenthesis indicate the number from the transcriptional start site. The sequences of the binding elements are in bold type, and the sequences matching the consensus sequence are underlined. H: human, M: mouse, R: rat. A molecular mechanism of canonical clock genes is based on transcriptional regulation via interlocked feedback and/or feed-forward loops [ 2 , 4 , 7 , 8 ]. One example of the regulation of a known characterized gene in mammals is that of Per1 . The transcription of Per1 is activated by binding of the CLOCK/BMAL1 hetero-complex, both members of which are bHLH-PAS (basic helix-loop-helix-Per-Arnt-Sim) proteins, to the E-boxes in the promoter region of Per1 [ 29 ]. The translated PER1 is posttranslationally modified by CKI-ε [ 30 ] and, together with other clock proteins such as CRYs [ 31 ], is returned to the nucleus to suppress its own transactivation, resulting in closure of the PER1 loop. E-box elements are also known to be essential for transcriptional regulation of many clock-controlled output genes including the vasopression genes [ 32 ]. On the other hand, one of the positive elements, BMAL1, whose mRNA expression is cycled antiphase to Per s, as described above, forms another loop [ 33 , 34 ]. The orphan nuclear receptors RORα and REV-ERBα regulate circadian transcription positively and negatively, respectively, through ROR/REV-ERB elements (ROREs) in the promoter region of Bmal1 [ 16 , 35 ]. Moreover, an in silico search identified these 2 ROREs in the promoter region of Npas2 (Table 1, see figure 5 ), the expression pattern of which was very similar to that of Bmal1 . These findings gave us the idea that the circadian pattern of RNA expression might be dependent on transcriptional regulation by specific transcription factors. Using the NCBI database and Celera Database System, we systematically searched for the above 2 elements and another clock element, a DBP-binding element (DBPE), described below. These elements are conserved among human, mouse, and rat genome sequences in the regions 9-kb upstream and 5-kb downstream of the transcription start site (Table 1, see figure 5 ). Intriguingly, the transcriptional elements corresponded to the cyclic pattern of the clock genes shown in Figure 4 . Bmal1 and Npas2 , the circadian peaks of which were both in subjective night at CT20-24, included ROREs in their promoters, as described above. In the promoter of Per1 and Per2 , the peaks of which were in subjective day at CT12-16, E-boxes were found. In fact, the conserved E-box in Per2 is not a typical E-box of the molecular clock, CACGT G , but an atypical element, CACGT T . Compared with Per1 , which contains 5 conserved E-boxes, Per2 may have other unknown factors and elements responsible for its robust transcriptional oscillation. Per1 , whose peak was a bit earlier than that of Per2 , has another element, a DBPE, in its promoter region, in addition to the 5 E-boxes well studied in vitro [ 36 ]. Per3 , the peak of which was even earlier at CT8-12, did not have conserved E-boxes but instead contained DBPEs in its gene. Three genes, Rev-erbα , Dbp , and Rev-erbβ , the peaks of which were between those of Bmal1 and Per , had a mixed combination of the elements. The Rev-erbα genome sequence included 1 RORE, 1 DBPE, and 5 E-boxes, whereas Rev-erbβ included all 3 elements only in the mouse genome sequence. Dbp contained 2 ROREs and 2 E-boxes in each genome. Among the elements described above, some of them in ( Bmal1 , Dbp , and Per1) were experimentally studied and confirmed [ 16 , 29 , 35 - 38 ]. Transcripts of 8 genes ( mBmal1 , mNpas2 , mRev-erbα , mDbp , mRev-erbβ , mPer3 , mPer1 , and mPer2 ) showed a robust circadian rhythm in different peripheral tissues (see Fig. 1 ). The amount of mRNA in the trough was nearly zero and the peak-trough amplitude of these genes was clearly higher than that of the others examined. Thus, in terms of mRNA expression among the canonical clock genes examined, these 8 genes likely constitute the core molecules of a molecular circadian clock. The expression timing in a 24-h period appears to be conveyed through 3 kinds of sequence elements bound by specific transcription factors (see Fig. 4 ). Recent genome-wide analyses using microarrays revealed that many genes (about 10 % of the total number of genes studied) oscillated but only several tens of common genes overlapped between two tissues examined [ 13 , 14 ]. Among the core candidate genes with similar circadian regulation in those 2 tissues, we examined the circadian transcription of 15 candidate genes besides the known clock genes, but could not find genes with oscillatory behavior in different peripheral tissues comparable to that in the 8 genes described above. The 8 genes studied here may approximate the entirety of the core oscillatory genes in the genome. If so, the 3 elements described here may be sufficient for explaining the biological timing of mRNA expression of clock genes. However, our preliminary results showed that an atypical E-box in Per2 promoter may be insufficient for full transcriptional oscillation (Akashi and Takumi, unpublished data). Further detailed studies of each promoter, combined with systematic analyses using microarrays and real-time RT-PCR, will give us a more detailed comprehension of the intertwined positive and negative regulatory loops of molecular biological clocks. Conclusions The current study has clarified the detailed circadian expression of mRNAs for clock and clock-related genes in different peripheral tissues of the mouse. The observation of oscillatory profiles of canonical clock genes is not only useful for physiological and pathological examination of the circadian clock in various organs but also important for systematic understanding of transcriptional regulation on a genome-wide basis. Our finding of the oscillatory expression of canonical clock genes in a temporal order provides us an interesting hypothesis, that cyclic timing of all clock and clock-controlled genes may be dependent on several transcriptional elements including 3 known elements, E-box, RORE, and DBPE. Methods Animals Male Balb/c mice purchased 5 weeks postpartum from Japan SLC (Hamamatsu, Japan), were exposed to 2 weeks of light-dark (LD) cycles and then kept in complete darkness as a continuation of the dark phase of the last LD cycle. mRNA expression was examined in the third dark-dark (DD) cycle. All protocols of experiments using animals in this study were approved by the OBI (Osaka Bioscience Institute) Animal Research Committee. Quantitative RT-PCR Real-time quantitative RT-PCR was performed by using an ABI PRISM 7000 (Applied Biosystems). The PCR primers were designed with Primer Express software (Applied Biosystems), and the sequences of the forward and reverse primers were as follow: mPer1 FW: CAG GCT AAC CAG GAA TAT TAC CAG C, mPer1 RV: CAC AGC CAC AGA GAA GGT GTC CTG G; mPer2 FW: GGC TTC ACC ATG CCT GTT GT, mPer2 RV: GGA GTT ATT TCG GAG GCA AGT GT; mPer3 FW: CTG CTC CAA CTC AGC TTC CTT T, mPer3 RV: TTA GAC AGC AAG GCT CTG GTT CT; mNpas2 FW: GTA TGC ACA GAG CCA AGT GAT GTT, mNpas2 RV: TGC TCA CTG TGC AGA GAT GTT G; mDbp FW: AAT GAC CTT TGA ACC TGA TCC CGC T, mDbp RV: GCT CCA GTA CTT CTC ATC CTT CTG T; mBmal1 FW: GCA GTG CCA CTG ACT ACC AAG A, mBmal1 RV: TCC TGG ACA TTG CAT TGC AT; mRev-erbα FW: CGT TCG CAT CAA TCG CAA CC, mRev-erbα RV: GAT GTG GAG TAG GTG AGG TC; mRev-erbβ FW: ACG GAT TCC CAG GAA CAT GG, mRev-erbβ RV: CCT CCA GTG TTG CAC AGG TA; G3-PDH FW: ACG GGA AGC TCA CTG GCA TGG CCT T, G3-PDH RV: CAT GAG GTC CAC CAC CCT GTT GCT G; mCry1 FW: CCC AGG CTT TTC AAG GAA TGG AAC A, mCry1 RV: TCT CAT CAT GGT CAT CAG ACA GAG G; mCry2 FW: GGG ACT CTG TCT ATT GGC ATC TG, mCry2 RV: GTC ACT CTA GCC CGC TTG GT; mCKIε FW: GGA TGT GAA GCC CGA CAA CTT, mCKIε RV: TCT CGA CGG CTT TGC TCA AT; mCKIδ FW: CCA GCC TGG AAG ACC TGT TC, mCKIδ RV: TGG CCA GCC CAA AGT CAA; mClock FW: CCT ATC CTA CCT TGG CCA CAC A, mClock RV: TCC CGT GGA GCA ACC TAG AT; mTim FW: ACA TGT GGG CAA TGG CTT, mTim RV: CTG CTC CAC AAA GTG AAA GGT. Specificity of gene amplification was confirmed by measuring the size and purity of the PCR product by gel electrophoresis, and by analyzing the dissociation curve with ABI PRISM 7000 SDS software (Applied Biosystems). For a 25-μl PCR reaction, 50 ng cDNA template was mixed with the forward and reverse primers to a final concentration of 300 nM each and 12.5 μl of 2x SYBR Green PCR Master Mix (Applied Biosystems). The reaction was first incubated at 50°C for 2 min, then at 95°C for 10 min, followed by 40 cycles of 95°C for 15 sec and 60°C for 1 min. Each gene-specific PCR was performed in triplicate. G3-PDH primers were used as the control. Real-time luciferase reporter assay NIH3T3 cells were cultured, transfected with hBmal1 -Luc or mPer2 -Luc, and incubated for 24 hours. The medium was then exchanged for serum-rich medium (DMEM, supplemented with 50 % serum). Two hours later this medium was replaced with normal culture medium. In the presence of 0.1 mM luciferin, light emission was measured and integrated for 1 min at intervals of 15 min, with a photomultiplier tube (Hamamatsu Photonics). In silico search The sequences were downloaded from the Celera Database System and the NCBI Gene database. Each gene sequence spanning from 9 kb upstream to 4 kb downstream of the transcription start site was examined in each database. Multiple sequence alignments of these sequences for each gene were obtained by Clustalw version 1.83 with default parameters. The binding elements were then searched from these alignments using a pattern finding tool, fuzznuc, with the following consensus sequences allowing for a 1-base mismatch: DBPE: [GA]T[GT]A[TC]GTAA[TC] E-Box: CACGTG RORE: [AT]A[AT]NT[AG]GGTCA The accession numbers used and the sequence numbers analyzed are as follow: Bmal1 ; Human, NT_009237.16, 12054318–12069318, Mouse, NT_081129.1, 107781–122781, Rat, NW_047562.1, 13774073–13789073, Npas2 ; Human, hCG27614, 95632226–65646226, Mouse, mCG8437, 35980102–35994102, Rat, rCT22431, 39204499–39218499, Rev-erbα ; Human, hCG93862, 34926094–34912094, Mouse, mCG15360, 105438925–105424925, Rat, rCG33292, 82492796–82478796, Dbp ; Human, NT_011109.15, c21417778–21402778, Mouse, NT_078442.1, 59711–74711, Rat, NW_047558.1, 5120734–5135734, Per3 ; Human, NT_021937.16, 1962822–1977822, Mouse, NT_039268.2, c4331528–4316528, Rat, NW_047727.1, c8016956–8001956, Per1 ; Human, NT_010718.14, c6905708–6890708, Moues, NT_039515.2, 65661216–65676216, Rat, rCG34390, 52960430–52974430, Per2 ; Human, NT_005120.14, c5136562–5121562, Mouse, NT_039173.2, c5833757–5818757, Rat, NW_047817.1, c6827703–6812703. List of Abbreviations used SCN, suprachiasmatic nuclei; RT-PCR, reverse transcription-polymerase chain reaction; CT, circadian time; LD, light-dark; DD, dark-dark; bHLH-PAS, basic helix-loop-helix-Per-Arnt-Sim; RORE, ROR/REV-ERB element; DBPE, DBP-binding element; NCBI, the National Center for Biotechnology Information. Authors' contributions TY and YN carried out the molecular biology studies. HS carried out the in silico study. MA carried out the real-time luciferase reporter assay. TM participated in the coordination, and provided financial support. TT conceived of the study, participated in its design and coordination, and drafted the manuscript. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535906.xml
526761	First successful case of in vitro fertilization-embryo transfer with venom immunotherapy for hymenoptera sting allergy	Background To describe immune and endocrine responses in severe hymenoptera hypersensitivity requiring venom immunotherapy (VIT) during in vitro fertilization (IVF). Case presentation A 39-year old patient was referred for history of multiple miscarriage and a history of insect sting allergy. Four years earlier, she began subcutaneous injection of 100 mcg mixed vespid hymenoptera venom/venom protein every 5–6 weeks. The patient had one livebirth and three first trimester miscarriages. Allergy treatment was maintained for all pregnancies ending in miscarriage, although allergy therapy was discontinued for the pregnancy that resulted in delivery. At our institution ovulation induction incorporated venom immunotherapy (VIT) during IVF, with a reduced VIT dose when pregnancy was first identified. Serum IgE was monitored with estradiol during ovulation induction and early pregnancy. Response to controlled ovarian hyperstimulation was favorable while VIT was continued, with retrieval of 12 oocytes. Serum RAST (yellow jacket) IgE levels fluctuated in a nonlinear fashion (range 36–54%) during gonadotropin therapy and declined after hCG administration. A healthy female infant was delivered at 35 weeks gestation. The patient experienced no untoward effects from any medications during therapy. Conclusion Our case confirms the safety of VIT in pregnancy, and demonstrates RAST IgE can remain <60% during IVF. With proper monitoring, VIT during IVF can be safe and appropriate for selected patients and does not appear to adversely affect blastocyst implantation, early embryo development or perinatal outcome. Further studies will be needed to develop VIT guidelines specifically applicable to IVF.	Introduction Insect sting allergies affect approximately 3% of the general population, and patients with insect sting allergy during pregnancy are generally advised to continue venom immunotherapy (VIT). However, there have been no descriptions of VIT during infertility therapy despite increased utilization of the advanced reproductive technologies [ 1 ]. In this report, we present endocrine and immunologic parameters observed during a successful in vitro fertilization cycle where a standard insect sting allergy protocol was used. Case report A 39 year-old Caucasian G 4 P 1031 was referred for evaluation and management of recurrent pregnancy loss. Medical history was significant for known carrier state for β-thalassemia. Mild hypothyroidism had been diagnosed in 2002 with immediate initiation of replacement therapy. The patient was a non-smoker, in good general health and had no gynecologic complaint. BMI was 21.7 kg/m 2 . In 1997, she experienced a severe hypotensive anaphylactic reaction following a yellow jacket sting ( Vespula spp.) resulting in a full allergy work-up. The patient began subcutaneous injection of 100 mcg mixed vespid hymenoptera venom/venom protein (Pharmalgen ® ; ALK Abello, Hørsholm, Denmark) every 5–6 weeks, which was well tolerated. All four conceptions were established without medical assistance, involved the same partner, and were achieved after the hymenoptera hypersensitivity diagnosis. The initial pregnancy occurred three years before presentation and resulted in a first trimester spontaneous abortion. No adjustment was made to the allergy injection regimen during that pregnancy. Fetal cardiac activity was initially present, but was lost at 10 weeks' gestation for unknown reasons. No curettage was performed. One year later, a second pregnancy was established but for this pregnancy hymenoptera venom therapy was discontinued when pregnancy was first recognized (~6 weeks). A 3170 g female infant was delivered vaginally at 40 1/2 weeks' gestation. In 2001 and 2002, the patient established two additional pregnancies and hymenoptera therapy was maintained at 5–6 week intervals for both; both resulted in first trimester spontaneous abortions. For these miscarriages, dilation and curettage was undertaken but no karyotype was performed and no cause for the losses was identified. At our institution, euthyroid status was verified, the thalassemia carrier state was confirmed, and we identified a new homozygous A223V mutation at the methyltetrahydrofolate reductase (MTHFR) locus. Folic acid intake was immediately increased to 800 mcg/d, although a baseline serum homocysteine level was not measured. Factor V Leiden, protein S, protein C, and other coagulation tests were normal, as were karyotypes obtained from both partners. Anticardiolipin, antiphospholipid and antiovarian antibody titres were all negative. However, transvaginal saline uterine sonography revealed a uniform 5 mm echodense lesion consistent with an endometrial polyp. Outpatient hysteroscopic polypectomy was performed without complication. After discussing various infertility therapies and associated success rates given her age, the patient elected to undergo IVF. In March 2003, the patient began programmed ovarian hyperstimulation using a combined recombinant-FSH+hMG protocol (300 IU/d Humegon ® , Ferring Pharmaceuticals Inc.; Tarrytown, NY USA and 300 IU/d Gonal-F ® , Serono Labs; Norwell, MA USA). Pre-treatment pituitary downregulation was achieved via 5 u/d leuprolide acetate and was continued × 3 d after gonadotropin therapy commenced. No alteration was made in the patient's allergy injection sequence during ovulation induction ( i.e ., 100 mcg every 5–6 weeks), and serum yellow jacket RAST IgE measurements were obtained via commercial fluoroimmunoassay including positive and negative controls (UniCAP ® IgE kit, Pharmacia Diagnostics, Uppsala, Sweden). While absolute IgE levels remained <0.35 kU/l throughout therapy, percentage IgE results were variable and these data are summarized in Figure 1 . Figure 1 Relationships among serum luteinizing hormone (LH-blue), estradiol (E2-black), and yellow jacket RAST %IgE (IgE-red) observed during in vitro fertilization and concomitant venom immunotherapy. On cycle day 10, subcutaneous hCG (10,000 IU) was given [ 2 ] with serum estradiol at 1090 pg/ml. Twelve oocytes were retrieved and 7 advanced to the 2 pn stage following conventional insemination. A four-day course of methylprednisolone (16 mg/d) was started on the day of oocyte retrieval. On post-fertilization day three, the ultrasound-guided transfer of four embryos was performed. Immediately following embryo transfer, the patient was placed on oral aspirin (81 mg/d) and subcutaneous heparin (5,000 IU b.i.d). Luteal phase support was administered as daily 50 mg IM progsterone in oil injections. Two weeks after embryo transfer, serum hCG was 72 mIU/ml. On May 5, 2003, transvaginal ultrasound confirmed a single intrauterine pregnancy with fetal cardiac rate at 126/min. Progesterone was discontinued at the 10 th gestational week. Immunology and perinatology consultants agreed with reduced dose allergy protocol through the third trimester, and hymenoptera venom protein extract (75 mcg) treatment was maintained to 32 weeks gestation. The patient experienced no untoward reaction or hypersensitivity to gonadotropins, VIT, or supplementary progesterone during therapy. At 32 weeks, obstetrical sonogram suggested reduced amniotic fluid levels and the patient was given intramuscular betamethasone (12 mg/d × 2 days) and placed on bedrest. At this point allergy injections were discontinued since the patient was not outdoors and risk for insect sting was regarded as low. Intravenous oxytocin was started at 35 weeks due to oligohydramnios and resulted in vaginal delivery of a 2495 g female infant. Mother and baby were discharged home after an uncomplicated two-day postpartum course. Allergy injections resumed (100 mcg every 5–6 weeks) when breastfeeding was completed three months later. Conclusion Overall, the incidence of allergy to insect stings is ~3% in adults [ 3 ], with allergy to hymenoptera species venom comprising an important subset of this population. Whether or not severe insect sting allergy contributes to poor reproductive outcome has been discussed in earlier reports [ 3 - 5 ], yet the immunology of pregnancy remains complex and poorly understood. While connections between infertility/spontaneous abortion and immune dysfunction have been explored by others [ 6 , 7 ], the reported conclusions have been highly variable [ 8 , 9 ]. In addition, difficulty with immunoassay standardization has made some findings difficult to reproduce [ 10 ]. Although continuation of allergy therapy during pregnancy is generally recommended [ 11 ], the interaction between ovulation induction agents and hymenoptera venom therapy has never been characterized. Our patient experienced no hypersensitivity or untoward effects during allergy therapy and gonadotropin use; both were well tolerated when administered together. We observed a variable IgE pattern, with a gradually increasing IgE response progressing with follicular growth during ovulation induction. Interestingly, a sharply diminished IgE level was registered immediately after hCG administration. The significance of the reduced terminal immunoglobulin titre is unkown but may reflect an immunomodulatory attenuation effect of hCG and/or progesterone [ 12 ]. Evaluation of this patient with a history of multiple spontaneous abortions identified additional factors which might contribute to a poor reproductive outcome. Specifically, endometrial polyps [ 13 ] and homozygous MTHFR mutation [ 14 ] are recognized independent risk factors for miscarriage. In addition to venom protein, our patient received other medications which modify immune response including aspirin [ 15 ], heparin [ 16 ], progesterone [ 17 ], and human chorionic gonadotropin [ 12 ]. Methylprednisolone [ 18 ] was administered at embryo transfer and betamethasone was given near delivery [ 19 ]. While for our patient VIT was a component of therapy culminating in a satisfactory reproductive outcome, the result should be recognized as the sum of all clinical interventions and insufficient data exists to ascribe specific roles for individual treatments. Levels of IgG4 blocking antibody were not quantified in this study, although measurement of this parameter in subsequent studies may offer additional insight into potential mechanisms of protection ( i.e ., reduction of miscarriage risk). It has been hypothesized that early production of IL-10 associated with VIT may induce T-cell anergy, dampening T helper type 2 response and resulting in a T helper type 1 dominant cytokine response. As the role of T helper 1 type immune response in blastocyst implantation becomes more completely characterized, T helper type 1 function may prove to be important in early placental dysfunction or recurrent pregnancy loss [ 20 ]. These potential mechanisms notwithstanding, when anatomic and hematologic abnormalities were corrected and VIT for insect sting allergy therapy was continued, a healthy livebirth after IVF was achieved. Our report offers, for the first time, reassurance for women undergoing IVF who also suffer from severe insect sting allergy requiring VIT. Data derived from further studies will be helpful as VIT guidelines are developed specifically for patients undergoing IVF. Competing interests The authors declare that they have no competing interests. Authors' contributions ESS was the principal physician and coordinated the research. SCC, CRK and MP edited the manuscript. MJT was chief embryologist and edited the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526761.xml
555943	PHACCS, an online tool for estimating the structure and diversity of uncultured viral communities using metagenomic information	Background Phages, viruses that infect prokaryotes, are the most abundant microbes in the world. A major limitation to studying these viruses is the difficulty of cultivating the appropriate prokaryotic hosts. One way around this limitation is to directly clone and sequence shotgun libraries of uncultured viral communities (i.e., metagenomic analyses). PHACCS , Phage Communities from Contig Spectrum, is an online bioinformatic tool to assess the biodiversity of uncultured viral communities. PHACCS uses the contig spectrum from shotgun DNA sequence assemblies to mathematically model the structure of viral communities and make predictions about diversity. Results PHACCS builds models of possible community structure using a modified Lander-Waterman algorithm to predict the underlying contig spectrum. PHACCS finds the most appropriate structure model by optimizing the model parameters until the predicted contig spectrum is as close as possible to the experimental one. This model is the basis for making estimates of uncultured viral community richness, evenness, diversity index and abundance of the most abundant genotype. Conclusion PHACCS analysis of four different environmental phage communities suggests that the power law is an important rank-abundance form to describe uncultured viral community structure. The estimates support the fact that the four phage communities were extremely diverse and that phage community biodiversity and structure may be correlated with that of their hosts.	Background Most environmental viruses are phages (a.k.a., bacteriophages) that infect prokaryotic cells, both Bacteria and Archaea. On average there are about ten phage particles per host cell [ 1 ]. Extrapolations from the number of prokaryotes [ 2 ] make phages the most abundant biological entities in the biosphere with an estimated 10 31 viral particles. By killing prokaryotes, phages can strongly impact microbial community biomass [ 3 ] and structure [ 4 ]. Despite their importance, very little is known about phage biodiversity. Traditionally, the study of environmental phage diversity, dynamics, and ecology requires growing prokaryotes on microbiology plates and infecting them with phages. However this standard technique is limited by the fact that only a small fraction of environmental microbes are readily cultured [ 5 ] and that each phage species generally only has a very narrow number of possible microbial hosts [ 6 ]. In addition, even if it is possible to observe phages with an electron microscope, pictures are not sufficient to identify species because of the low taxonomic resolution of viral morphology. Cultivating and observing phages do not permit to assess environmental phage diversity. Biodiversity is composed of richness, or total number of different species [ 7 ], and evenness, expressing the relative abundance of each species [ 8 ]. The Shannon-Wiener index quantifies diversity as a single term combining richness and evenness [ 9 ]. A high richness and high evenness together represent a high level of diversity. A new approach to accessing natural microbial diversity is through the creation of shotgun sequence libraries from environmental metagenomes (sum of all genomes) [ 10 - 14 ], so that the genetic information of each genotype of the community is recorded, qualitatively (sequence) and quantitatively (abundance of each sequence). The community is analyzed by sequencing a part of the library. The metagenomic data used here is the contig spectrum, determined by assembly of environmental random shotgun DNA fragments. The contig spectrum is a vector containing the number of contigs (groups of overlapping sequences) of size q (number of sequences in the group) [ 10 ]. The stringency of the assembly parameters can be varied so that only sequences belonging to the same genotype overlap. Thus, for one genotype, the bigger the contigs in the contig spectrum, the higher the number of copies and the more abundant this genotype. Based on this, the contig spectrum provides important information about the abundance and diversity of genotypes within a community. In this work, we present PHACCS (PHAge Communities from Contig Spectrum), an online computational tool to assess the diversity and structure of environmental viral communities from the contig spectrum of shotgun sequence data. The PHACCS program and its predictions are first described and then used to analyze four environmental viral communities. Implementation Platform and software The standalone core mathematics for PHACCS consists of Matlab (MathWorks Inc., Natick, MA.) scripts that are partly based on the previous works [ 10 - 12 ]. A CGI (Common Gateway Interface) script written in PERL (Practical Extraction and Report Language) is used to input and output data from and to an HTML (Hyper Text Markup Language) interface. PHACCS was developed and tested on a Linux-based (2.6.6 kernel) personal computer running PERL 5.8.3 (with CGI module), Matlab 6.5.0, and Apache 2.0.50 web server. Obtaining a contig spectrum The input for PHACCS is the contig spectrum, a vector containing the number of q -contigs (groups of q overlapping sequences) from the in silico assembly of random shotgun DNA fragments. Detailed information about the way to get viral metagenomes and their contig spectrum can be found in [ 10 - 12 ]. Briefly, viral communities were isolated via tangential flow filtration and cesium chloride centrifugation, and their DNA was extracted. The DNA was randomly fragmented, used to create a linker amplified shotgun library [ 15 ] and clones were sequenced (between 500 and 1200 for studies [ 10 - 12 ]). The sequence assembly program Sequencher (Gene Codes Corp., Ann Arbor, MI.) was used to assemble phage sequences having at least 98% identity on at least 20 bp [ 10 ]. The stringency of the assembly parameters was experimentally determined so that only fragments belonging to the same genotype assemble together. Closely related phage genomes (e.g., coliphages T3 and T7) can be discriminated using these parameters [ 10 ]. The number of contigs of each size was then recorded to generate the contig spectrum. The number of sequences in the largest contig defines the contig spectrum degree. Modified Lander-Waterman algorithm PHACCS uses a modified version of the Lander-Waterman algorithm [ 16 ] to predict a contig spectrum from assumed population parameters. The original Lander-Waterman algorithm is a way of predicting the contig spectrum of a randomly fragmented genome (e.g., a single viral species) given: i) the length L of the genome, ii) the number N of DNA fragments studied, iii) the average size s of these fragments, and iv) the minimum overlap length o for the sequence assembly [ 16 ]. Given this data, the predicted values of the following quantities are calculated: • Probability p of an overlap: p = 1 - e - Nx / L with x = s - o • Probability w q for a fragment to be part of a q -contig (overlap of q fragments): w q = qp q - 1 (1 - p ) 2 • Expected number of fragments c q that are part of a q -contig: c q = Nw q • Contig spectrum: The modified Lander-Waterman algorithm is a generalization of the original algorithm to a group of M different genotypes (e.g., a whole viral community) [ 10 ]. The predicted contig spectrum can be calculated as the sum of the contig spectra for each individual genotype i . • Expected number of fragments c q part of a q -contig: w qi is the probability for a fragment to be part of a q -contig for the genotype i and n i is the expected number of fragments for the genotype i . In this modified algorithm, since there are several genotypes, an assumption about their underlying distribution within the community in terms of abundance has to be made. Relative rank-abundance forms PHACCS offers six basic functional forms of relative rank-abundance for biological populations: the power law, logarithmic, exponential, broken stick, niche preemption, and lognormal distributions. The first three functional forms are empirical models that were designed to describe an asymptotic drop-off in the abundance [ 17 ]: • Power: n i = ai - b for 1 ≤ i ≤ M • Logarithmic: n i = a (log( i + 1)) - b for 1 ≤ i ≤ M • Exponential: n i = ae - ib for 1 ≤ i ≤ M The parameter a represents the abundance of the most abundant genotype, b is a parameter related to the evenness, and M is the number of different genotypes in the community. Two ecological models are based on a partitioning of resources between species [ 18 , 19 ]: • Broken stick: for 1 ≤ i ≤ M • Niche preemption: n i = Nk (1 - k ) i - 1 and n M = N (1 - k ) M - 1 for 1 ≤ i ≤ M - 1 The broken stick function has only one parameter, M , and assumes a random distribution of resources, whereas in the niche preemption function, each species takes only a fraction k of the remaining resources in the environment. The sixth functional form is the lognormal distribution. It is the most commonly used species distribution, with numerous theoretical justifications in the literature [ 20 , 21 ]. The relationship is specified as species density versus abundance and needs to be transformed to give a rank-abundance relationship. Our rank-abundance form was obtained by dividing the area under the normal distribution with standard deviation σ into M equal area slices and associating an abundance n i with the i -th slice by calculating an average value for the abundance within the slice. The result is: where erf is the error function and erf 1 its inverse. Modeling the viral community structure The PHACCS algorithm is represented in Figure 1 . The experimentally determined contig spectrum of a sample and the other parameters needed for the modified Lander-Waterman algorithm are the input. For a given rank-abundance function, assumed values of the function parameters (number of different genotypes, as well as b for the power law, logarithmic, exponential and lognormal distributions and k for niche preemption) are used to predict a contig spectrum using the modified Lander-Waterman algorithm. To determine the model fitness, the error between the actual and the predicted contig spectrum is calculated as the variance-weighted sum of squared deviations, L being the contig spectrum vector length and c q ' the experimental number of fragments that belong to a q -contig: The best descriptive model for a community structure is defined as the one with the smallest error. For each rank-abundance function tested, the global minimum for the error is found by optimizing the value of the function parameters. The values of the error can be roughly interpreted as logarithms of odds ratios of the observed contigs being seen from community distributions of the specified forms. Thus a value of 0.1 for the difference in errors between two models corresponds to an odds ratio of e 0.1 which is about 11:10 between the two models. This means that the model with the smallest error is about 10% more likely to give rise to the observed data. Predicting the viral community diversity For each rank-abundance form, the best model is used by PHACCS to assess diversity. The richness S is estimated as equal to the number of different genotypes M found in the community structure model. The abundance of the most abundant genotype is also directly determined from the model as the highest rank-abundance value. The Shannon-Wiener index, which is a measure for diversity, is calculated using the relative rank-abundance values r i = n i / N of all individual genotypes i [ 9 ]: • Shannon-Wiener index H ' (in nats): The evenness is derived from H ' [ 18 ]: • Evenness E : E = H '/ H max = H '/ln S Comparison of four phage communities As a case study, four viral metagenomes obtained from previous studies and belonging to different ecosystems were tested. Two of these were phage community samples of near-shore surface seawater from Scripps Pier (SP) and Mission Bay (MB), San Diego, California, USA [ 10 ]. The two other samples are sediments from Mission Bay (MBSED) [ 11 ] and human feces (FEC) [ 12 ]. A compilation of the data for these samples is presented in Table 1 . These four datasets were analyzed with PHACCS using all six rank-abundance models. Results Best abundance forms The errors obtained from the contig spectrum analysis of the different samples are presented in Table 2 . For each sample the best descriptive model of the community structure is the one with the smallest error. The SP community was best described by using the power law (error of 1.84), closely followed by the lognormal (error of 1.93) and logarithmic (error of 2.57) distributions. The exponential and niche preemption distributions had poor fits, with errors of 12.0. The MB community modeling gave qualitatively the same results. Power law was the best fit with an error of 2.15 and exponential and niche preemption were last with an error of 16.2. The FEC community also had the same sequence of best fitting rank-abundance forms. The best model was given by using the power law form (error 9.79). Exponential and niche preemption did a poor job of explaining the data, coming in last with an error of 60.0. For the MBSED community, the power law, lognormal, logarithmic and exponential distributions all tied for the best fit (with an error of 0.0104), whereas broken stick gave the worst fit (error of 0.0157). Phage community diversity and structure The different diversity indicators and the rank-abundance curves obtained by using the best descriptive model for each sample are summarized in Figure 2 . The MBSED community was the richest with an estimated 7340 different phage genotypes. MB had ~7180 different genotypes, SP ~3350, and FEC was the least rich sample with ~2390 different genotypes. MBSED was the most even community with the maximum possible evenness of 1.00 (flat rank-abundance curve), followed by SP (evenness of 0.932), MB (evenness of 0.900), and FEC (evenness of 0.873). The most abundant genotype represented 4.80% of the total community for FEC, 2.63% for MB, 2.03% for SP and around 0.01% for MBSED. Based on the Shannon-Wiener diversity index, MBSED was overall the most diverse community with 8.90 nats, then MB (7.99 nats), SP (7.57 nats), and finally FEC (6.80 nats), the least diverse community. Discussion Using PHACCS PHACCS is publicly accessible at and the source code is freely available [see Additional file 1 ]. The biological information PHACCS needs as an input is the viral community's contig spectrum, average genome size, average shotgun DNA sequence length, and the minimum overlap length used for the assembly. PHACCS has two HTML interfaces. The basic interface assumes default values for marine phage communities (average genome size of 50 kb, average fragment length of 650 bp and minimum overlap of 20 bp). All rank-abundance forms (power law, expoential, logarithmic, lognormal, broken stick and niche preemption distributions) are tested for up to 100,000 genotypes. In the advances interface (Figure 3 ) the user can change all biological and computational parameters. PHACCS analyses are computer intensive. On a dual-Opteron™ server, the computation for the SP sample takes ~5 minutes. The broken stick and lognormal rank-abundance forms account for most of the computation time (data not shown). Increasing the range of genotypes to search dramatically increases the time needed to complete the analysis (data not shown). PHACCS estimations about the virus community are: i) structure – best descriptive rank-abundance form, model equation and error, and ii) diversity – richness, evenness, abundance of the most abundant genotype, and Shannon-Wiener index. Graphic representations of the community structure and of the error minimization can also be displayed. The error provides information about which model has the best fit relative to the others for a given contig spectrum. For each type of distribution, the user is informed if the best model (i.e., the error's global minimum) has not been found using the given computation parameters. Importance of the contig spectrum quality Predictions by PHACCS are dependent on the quality of the contig spectrum input. The difference in error between two models can be small (Table 2 ) and using an inappropriate model can change the estimated diversity. For example, the predicted richness for the SP sample is about four times higher for the lognormal distribution than for the power law (data not shown). A useful contig spectrum requires that: i) the same clone be sequenced only once (remove all redundant clones), ii) the sequences be trimmed to remove ambiguities ("N"'s) and, iii) the assembly parameters be sufficiently stringent so that only sequences from the same genotype are part of the same contig (experimental determination by assembly of known sequences). All these experimental problems bias the observed occurrence of the DNA fragments, and thus the contig spectrum. Additionally, accurate community estimations are not to be expected if the contig spectrum only has a small degree (only small contigs) (e.g., MBSED, [1152 2 0 ...]). As a general rule, the higher the contig degree, the better the estimations, because the model fitting is done over a larger number of points. For the same reason, the number of trailing zeros in the contig spectrum is important. Adding zeros at the end of the contig spectrum will improve PHACCS predictions (e.g., 10 trailing zeros were used in the present analyses) but will also increase the computation time. Limitations The way the contig spectrum is obtained leads to approximations of the viral diversity. In the samples analyzed here, only the DNA from viruses smaller than 0.22 μ m is collected. Larger viruses and RNA viruses are not represented in the shotgun library and in the resulting contig spectrum. The contig spectrum assembly parameters (98% identity on at least 20 bp for phages) are stringent enough to limit the number of false-contigs (contigs between DNA fragments from different genotypes), but may on the other side omit some true-contigs (DNA fragments that are designated as non-overlapping when they actually belong to the same genotype). Additionally, the present implementation of the Lander-Waterman algorithm assumes that all DNA fragments and all the genotypes have the same size. For these reasons, PHACCS estimates should be considered approximations. Phage community structure and diversity The comparative analysis of the four phage communities showed that the power law seems overall to be a powerful rank-abundance distribution to model phage community structure (Figure 2 ). A recent simple predator-prey model based on the observed marine phage-host dynamics explains how a power law distributed phage rank-abundance can be obtained from a modified Lokta-Volterra model [ 23 ]. Before analyzing the viral samples with the contig spectrum approach, the number of viral genotypes in an environment was totally unknown. The viral communities turned out to be extremely diverse with estimated Shannon-Wiener diversity indices between 6.8 nats (fecal sample) and 8.9 nats (sediment sample) (Figure 2 ), representing diversity levels higher than for most bacterial communities [ 11 ]. Because phages are specific predators, the structure and diversity of phage communities could be directly correlated to the structure and diversity of the coexisting microbial communities [ 2 ]. Some facts seem to support this hypothesis. First, the extreme diversity of the sediment viral community may reflect the higher diversity of the microbial communities found in sediments using automated rRNA intergenic spacer analysis (ARISA) [ 24 ] in comparison with seawater. Also, only a few hundred different bacterial species were reported in the human colon intestinal flora [ 25 ] using the 16s ribosomal DNA methodology, which could account for the relatively low phage richness in the fecal sample. Conclusion PHACCS is a web-based service that predicts community structure and diversity using the contig spectrum from metagenomic random shotgun sequence data. This methodology allows PHACCS to determine the mathematical model that most accurately reflects the underlying genotype abundance distribution (i.e., power law, logarithmic, exponential, broken stick, niche preemption, or lognormal distributions) and use it to makes estimates about the diversity of the communities, (i.e., richness, evenness, Shannon-Wiener index and abundance of most abundant genotype). Using uncultured environmental viral samples, PHACCS has been used to confirm that phage biodiversity is higher than in any previously observed community and that the structure of viral communities may closely follow that of their hosts. PHACCS is designed for biologists to mathematically analyze their viral shotgun libraries and gain insights about viral ecology and population dynamics. Availability and requirements • Project name: PHACCS – PHAge Communities from Contig Spectrum • Project home page: • Operating system(s): Unix based system for PHACCS and its web interface. Platform independent for PHACCS core. • Programming language: Matlab (for the core scripts) and Perl • Other requirements: For the interface: CGI.pm Perl module, ppmtogif, webserver program (to use PHACCS as a web service) • License: GNU GPL Authors' contributions FA developed the PHACCS main program and its interface. BRB helped with the programming. BRB, DB, PMN, PS, BF, JN and JM developed the modified Lander-Waterman algorithm and implemented it with Matlab. FR and MB helped write the manuscript and provided the test datasets. All authors read and approved the final manuscript. Supplementary Material Additional File 1 This file contains the script files part of PHACCS. These files are either standard text or picture files. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555943.xml
524189	Analysis of Maxi-K alpha subunit splice variants in human myometrium	Background Large-conductance, calcium-activated potassium (Maxi-K) channels are implicated in the modulation of human uterine contractions and myometrial Ca 2 + homeostasis. However, the regulatory mechanism(s) governing the expression of Maxi-K channels with decreased calcium sensitivity at parturition are unclear. The objectives of this study were to investigate mRNA expression of the Maxi-K alpha subunit, and that of its splice variants, in human non-pregnant and pregnant myometrium, prior to and after labour onset, to determine whether altered expression of these splice variants is associated with decreased calcium sensitivity observed at labour onset. Methods Myometrial biopsies were obtained at hysterectomy (non-pregnant, NP), and at Caesarean section, at elective (pregnant not-in-labour, PNL) and intrapartum (pregnant in-labour, PL) procedures. RNA was extracted from all biopsies and quantitative real-time RT-PCR was used to investigate for possible differential expression of the Maxi-K alpha subunit, and that of its splice variants, between these functionally-distinct myometrial tissue sets. Results RT-PCR analysis identified the presence of a 132 bp and an 87 bp spliced exon of the Maxi-K alpha subunit in all three myometrial tissue sets. Quantitative real-time PCR indicated a decrease in the expression of the Maxi-K alpha subunit with labour onset. While there was no change in the proportion of Maxi-K alpha subunits expressing the 87 bp spliced exon, the proportion of alpha subunits expressing the 132 bp spliced exon was significantly increased with labour onset, compared to both non-pregnant and pregnant not-in-labour tissues. An increased proportion of 132 bp exon-containing alpha subunit variants with labour onset is of interest, as channels expressing this spliced exon have decreased calcium and voltage sensitivities. Conclusions Our findings suggest that decreased Maxi-K alpha subunit mRNA expression in human myometrium at labour onset, coupled to an increased proportion of Maxi-K channels expressing the 132 bp spliced exon, may be linked to decreased Maxi-K channel calcium and voltage sensitivity, thereby promoting enhanced uterine activity at the time of labour.	Background The regulatory mechanisms for uterine smooth muscle contractility during human pregnancy and labour are poorly understood. Such information is essential to understanding the clinical problems associated with human parturition and particularly preterm or premature labour. It is clear however that the myometrium is transformed from a state of relative quiescence during pregnancy, to one of maximal contractile activity at the time of labour. It is also established that the state of contractility of uterine smooth muscle is intrinsically linked to cell membrane ion channel activity [ 1 , 2 ]. Potassium (K + ) channels are functionally important in the regulation of smooth muscle tone [ 3 ]. Among the diverse family of K + channels, large-conductance, calcium-activated K + (Maxi-K, also known as BK Ca ) channels are the predominant K + channels in myometrium, and thus have been implicated in the control of cellular excitability [ 4 ]. While evidence for an important role of Maxi-K channels is not particularly strong, it is thought that they play a pivotal role in the modulation of uterine contractility and myometrial calcium homeostasis. Pharmacological inhibition of Maxi-K channels, by the specific channel blocker iberiotoxin, increases contractile activity in human uterine tissue [ 5 ], whereas compounds that promote Maxi-K channel opening, such as NS1619, have a potent relaxant effect on pregnant human myometrium [ 6 ]. Structurally, Maxi-K channels are tetramers of a pore-forming α subunit of the slo gene family, and a regulatory β subunit [ 7 - 10 ]. The α subunit comprises 7 transmembrane regions (S0-S6) and 4 intracellular hydrophobic domains (S7-S10) [ 11 ]. The β subunit is a structurally unique, membrane-spanning protein that contributes to channel gating and pharmacology [ 12 ]. The α subunit is encoded by a single gene. However, it achieves molecular diversity by extensive alternative splicing of its gene transcript at several sites [ 7 , 13 - 15 ], which generates Maxi-K channel variants. There is a substantial body of evidence indicating that alternate splicing of the maxi-K transcript plays a major role in regulating potassium channel conductance [ 7 , 15 ]. These data include evidence for splice variation effecting calcium and voltage sensitivity, surface expression, and sensitivity to protein phosphorylation of the maxi-K channel [ 16 , 17 ]; [ 18 ]. Alternative splicing of the maxi-K channel α subunit is considered to be a molecular mechanism by which the channel is able to adjust and tune its response to a variety of regulatory and conductance requirements. Further evidence of the role of alternate splicing of the maxi-K transcript in altering maxi-K protein function in myometrium is provided by the finding of up-regulation of maxi-K splice variants known to alter channel current through alterations in calcium and voltage sensitivity in pregnant mouse myometrium [ 19 ]. What initiates alternative splicing of the α subunit transcript is incompletely understood, however there is evidence that expression of different alternatively spliced transcripts can be hormonally induced [ 20 , 21 ]. It appears that expression of different pore-forming α subunit isoforms, with associated regulatory β subunits, occurs in a tissue-specific manner, thereby providing functional specificity [ 22 ]. Maxi-K channels have been identified both in human non-pregnant [ 23 ] and pregnant [ 24 ] myometrium. For animal myometrial tissues, the data outlining Maxi-K α subunit mRNA expression in relation to labour are conflicting [ 19 , 25 , 26 ]. For human myometrium, it has more recently been reported that protein expression of both α and β subunits is down-regulated with labour onset [ 27 ]. Although multiple alternatively spliced exons of the Maxi-K α subunit have been identified [ 10 , 19 , 21 , 28 ], there is no information available to date pertaining to expression of α subunit splice variant mRNA transcripts in human myometrium during pregnancy or at the time of labour. Because phosphorylation sites can be introduced into the channel protein via alternatively spliced exons [ 19 ], alternative splicing may represent an important control mechanism regulating Maxi-K channel function during pregnancy and at labour. The aim of this study was to investigate the expression of alternatively spliced exons of the Maxi-K α subunit transcript in non-pregnant myometrium and in pregnant myometrium, prior to and after labour onset using quantitative real-time PCR. Methods Patient recruitment and tissue collection Patient recruitment took place in the Department of Obstetrics and Gynaecology, University College Hospital Galway (UCHG), Ireland, between October 2001 and August 2002. The study was approved by the Research Ethics Committee, UCHG, and recruitment was carried out by provision of information sheets and obtaining written informed consent. Biopsies of myometrium were excised from the midline of the upper lip of the uterine incision made at caesarean section, at elective (pregnant not-in-labour, PNL; n = 8) and intrapartum (pregnant in-labour, PL; n = 7) procedures. The mean age of the women was 33.3 years (range 26–42) of whom four were primagravida and eleven were multigravida. All women were delivered between 37 and 41 weeks gestation. There was no significant difference between those undergoing elective or emergency caesarean section in terms of age, parity or gestation. Women who had received prostaglandins or oxytocin were excluded from the study. Reasons for emergency section included breech presentation, previous caesarean section and abnormal foetal position. The criteria for inclusion in the intrapartum group were regular spontaneous uterine contractions, effacement of the cervix, and cervical dilatation >3 cm prior to caesarean section. Samples of non-pregnant myometrium (NP; n = 7) were excised from the body of the uterus of hysterectomy specimens from pre-menopausal women. The mean age of women undergoing hysterectomy was 42.5 years (range 34–48). Women with malignant conditions, and those receiving exogenous hormone therapy (e.g. progestagens), were excluded from the study. Immediately upon removal, tissue samples were rinsed in sterile saline, snap frozen in liquid nitrogen and stored at -80°C until RNA extraction. RNA preparation/Reverse Transcriptase-Polymerase Chain Reaction RNA was isolated from frozen tissue by homogenisation in TRIzol ® Reagent (Life Technologies, Paisley, UK) [ 29 ]. RNA concentration was determined by absorbance at A 260 . To eliminate any residual contaminating genomic DNA, all RNA samples were DNase-treated with the DNA-free™ DNA removal kit (Ambion, Huntingdon, Cambridgeshire, UK), as previously described [ 30 ]. RNA concentration was measured again by absorbance at A 260 , after removal of DNA, and adjusted to a final concentration of 500 ng/μL. Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) was performed to check for mRNA expression of all potential spliced exons of the Maxi-K α subunit in non-pregnant and pregnant myometrium, prior to and after labour onset. Purified RNA samples were reverse transcribed using oligo (dT) 15 primer and 200 IU M-MLV reverse transcriptase (Promega, Madison, WI, USA), as previously described [ 30 ]. PCR amplification was performed with 20 pmol of each specific oligonucleotide primer pair (Table 1 ), and 1.25 IU Taq DNA Polymerase (Promega, Madison, WI, USA) as previously described [ 30 ]. Primer pairs were designed to flank predicted splice sites, allowing spliced exon expression in these different regions to be assessed. PCR products were separated by electrophoresis on a 1.5% agarose gel and visualised after ethidium bromide staining by UV illumination. Bands identified were purified by gel extraction using Qiagen Gel Extraction kit (Qiagen, West Sussex, UK), and sent for sequencing (MWG-Biotech Ltd., Milton-Keynes, UK). Table 1 Primer Pairs Primer name Primer sequence (5' – 3') Primer Tm (°C) Maxi 0F CGGAGGCAGCAGTCTTAG 58.2 Maxi 0R AAGAAAGTCACCATGGAGGAG 57.9 Maxi 1F CTCCTCCATGGTGACTTTCTT 57.9 Maxi 1R TTACAAGTGCACCGATGCTG 57.3 Maxi 2F GGAAACCGCAAGAAATAC 53.1 Maxi 2R ACCTCATGGAGAAGAGGTTG 57.3 Maxi 3F GGTCTGTCCTTCCCTACTGT 59.4 Maxi 3R CAAAGATGCAGACCACGACA 57.3 Maxi 4F GTGCCAGCAACTTTCATTAC 55.3 Maxi 4R TCAGGGTCATCATCATCGTC 57.3 Maxi 5F ACAGCATTTGCCGTCAGTG 56.7 Maxi 5R GGTCCGTCTGCTTATTTGCT 57.3 β-actin F CAACTCCATCATGAAGTGTGAC 55.8 β-actin R GCCATGCCAATCTCATCTTG 59.3 Splice variant-specific cDNA synthesis Splice variant-specific cDNAs were prepared for each RNA sample using reverse primers as shown in Table 2 . 3 μg of purified RNA (1 μg for β-actin) was reverse transcribed to cDNA for each amplicon of interest using 500 nmol/L specific reverse primer and 200 IU M-MLV reverse transcriptase (Promega, Madison, WI, USA), as previously described [ 30 ]. These cDNAs were stored at -20°C until required for real-time PCR. New forward primers were designed upstream of the spliced exon sequences, to ensure that product size was approximately 200 bp, the optimum product length for use with hydrolysis TaqMan probes. Table 2 Amplicon-specific primer and probe sequences Primer name Primer/Probe sequence (5' – 3') Primer/Probe Tm (°C) Conserved F TGCACAAAGAGGTATGTCATCAC 58.9 Conserved R GTTTGCTGTGGATGGGATGGA 59.8 Conserved Probe 6F * -CCCACTCGTCGCAGTCCTCCAGCAAGAAGA XT♣ 68.9 132 bp splice F ACGCTCAAGTACCTGTGGACCGT 64.2 132 bp splice R TGTGGTTCCAGTTGAGTCACCA 60.3 132 bp Probe 6F-CTCCAGGGTGGAGTGATTGGCTGTATGTT XTCAC 71.5 87 bp splice F CATCGCAAGTGATGCCAAAGAA 58.4 87 bp splice R TCAACTGGCTCGGTCACAAGC 61.8 87 bp Probe 6F-TTGCAGCTAGATCACGCTATTCCAAAGATCCA XT 68.9 β-actin F CAACTCCATCATGAAGTGTGAC 55.8 β-actin nested R GTCAAGAAAGGGTGTAACGCA 55.4 β-actin Probe 6F-TGGCACCCAGCACAATGAAGATCAAATCA XT 70.3 * 6F = FAM reporter dye; ♣ XT = TAMRA quencher dye Synthesis of cDNA standards Standards (1 × 10 9 to 1 × 10 4 cDNA copies, in 10-fold increments) were created for each spliced exon and conserved region amplicons, and for β-actin, to enable accurate quantitation of product-specific cDNA copy numbers. Amplicon-specific PCR products were generated by RT-PCR (as described above) using primers shown in Table 2 . Products were purified using Qiagen PCR purification kit (Qiagen, West Sussex, UK), quantified by absorbance at A 260 , and ligated into TA cloning vector pCR ® 2.1 (TA cloning ® kit, Invitrogen Ltd, Paisley, UK), according to manufacturers' instructions. Vector-ligated PCR products were transformed into One Shot ® TOP10 cells, which were plated on Luria-Bertani (LB) agar plates containing 50 μg/mL kanamycin antibiotic, and incubated overnight at 37°C. Plasmid templates containing inserts in the desired orientation to transcribe sense RNA, as determined by colony PCR, were linearized by HindIII digestion. 2 μL of digestion products were electrophoresed on 1% agarose gels and visualised to ensure complete plasmid linearisation. Sense cRNA transcripts were generated by in vitro transcription using the MAXIscript™ In vitro Transcription Kit (Ambion, Huntingdon, Cambridgeshire, UK). 1 μg of linearized plasmid DNA was in vitro transcribed in a final volume of 20 μL containing 0.5 mmol/L each of ATP, CTP, GTP, and UTP, 2 μL 10X Transcription buffer, and 2 μL T7 Enzyme mix for 1 hr at 37°C. After transcription, samples were treated with DNA-free™ DNA removal kit (Ambion, Huntingdon, Cambridgeshire, UK) to remove plasmid DNA. The supernatant, containing purified cRNA, was pipetted onto pre-hydrated NucAway™ spin columns (Ambion, Huntingdon, Cambridgeshire, UK) to remove free nucleotides from the transcription reaction and further purify the cRNA samples. These columns were centrifuged at 1200 g for 2 min. Eluted cRNA concentration was determined by absorbance at A 260 . Copy number/μL of cRNA was calculated according to the following formula, available from the Roche Lightcycler™ website: Once the total amount of cRNA copies/μL had been calculated, serial dilutions of cRNA standards were produced (from 1 × 10 9 cRNA copies/μL to 1 × 10 4 cRNA copies/μL, in 10-fold increments) for each product-specific cRNA molecule generated. Serially-diluted cRNA standards were reverse transcribed in a 20 μL final volume as described above, using transcript-specific reverse primers (Table 2 ), thereby generating product-specific cDNA standards. These cDNA standards were stored at -20°C until required for real-time PCR. Quantitative expression analysis using real-time PCR Real-time PCR amplification was performed on the Lightcycler™ instrument using the Lightcycler™ FastStart DNA Master Hybridization Probes kit (Roche Diagnostics, Mannheim, Germany). Hydrolysis TaqMan probes were synthesized for each amplicon to be quantified (TIB MolBiol Syntheselabour, Berlin, Germany), and are shown in Table 2 . Probes were designed with consideration taken for the design parameters outlined by Bustin [ 31 ]. Probes were resuspended in PCR-grade water to a working stock concentration of 4 μmol/L, and stored in the dark at 4°C. Prior to quantitative analysis, several titration experiments for cDNA, probe, primer, and MgCl 2 concentration were performed to determine optimum reaction conditions for amplification. The following master mix of the reaction components was prepared to the indicated end-concentration: 10.6 μL water, 2.4 μL MgCl 2 (3 mmol/L), 1.0 μL forward primer (0.5 μmol/L), 1.0 μL reverse primer (0.5 μmol/L), 1.0 μL specific probe (200 nmol/L) (see Table 2 ) and 2 μL Hybridization Master Mix. The master mix (18 μL) was aliquoted into Lightcycler™ glass capillaries (Roche Diagnostics) and 2 μL cDNA (samples and standards) was added to respective capillaries. Capillaries were centrifuged at 3000 rpm for 5 s, and loaded into the Lightcycler™ instrument. The experimental protocol used for TaqMan probe quantitative analysis consisted of two stages: initial denaturation (95°C for 10 mins), followed by 45 cycles of denaturation (95°C for 0 s) and annealing/extension (59–61°C for 50 s). The annealing temperature used in each experiment was dependent on the melting temperature of both the primers and probe involved. Fluorescence data were acquired at the end of each annealing/extension cycle. Data analysis was performed using Lightcycler™ Second Derivatives Method software. This method automatically determines the threshold cycle (C T ) values for each individual sample using a software algorithm, which allows initial mRNA concentration in each sample to be accurately quantified based on the standards used. Using this method removes user influence, as well as any influence of background fluorescence on the data. The fluorescence display mode used was F1/F2, which is the optimal setting for use with hydrolysis TaqMan probes. PCR products were isolated from capillaries after each program had finished and were visualised by electrophoresis on 1.5% agarose gels. Statistical analysis The SPSS computer software package was used for all statistical analyses (Statistical Package for the Social Sciences, v.10, SPSS Inc., Chicago, IL, USA). Multiple group comparisons were made using analysis of variance (ANOVA), which were followed by individual group comparisons using the Tukey HSD test, where appropriate. Results Analysis of expression of alternatively spliced exons of the Maxi-K α subunit in human myometrium RT-PCR analysis of the Maxi-K α subunit gene, using primers designed to flank predicted splice sites, produced a variety of bands in samples of non-pregnant (NP), pregnant not-in-labour (PNL) and pregnant in-labour (PL) myometrium (data not shown). From this analysis, only two potential alternatively spliced exon-containing PCR products were identified in the three tissue sets assayed (Figure 1 ). Sequence analysis of these bands confirmed the presence of two alternatively spliced exons, both of which had previously been identified in human myometrium. The first was a 132 bp spliced exon located in the S0-S1 linker region identified by Korovkina et al. [ 26 ], and the second was an 87 bp spliced exon located in the S8-S9 linker region identified by Wallner et al. [ 10 ]. PCR of reverse transcriptase negative controls (RT-) and a water control (no cDNA template) did not generate any products, confirming the absence of genomic DNA contamination (data not shown). Figure 1 Detection of alternatively spliced exon-containing RT-PCR products . Ethidium bromide stained agarose gels (2%) showing ( A ) 132 bp spliced exon-containing (437 bp) and exon-less (305 bp) PCR products and ( B ) 87 bp spliced exon-containing (622 bp) and exon-less (535 bp) PCR products, in non-pregnant (NP), pregnant not-in-labour (PNL), and pregnant in-labour (PL) myometrial tissues. M = 100 bp marker (Promega, US); M 2 = 2-log ladder (New England Biolabs Inc., UK). Quantitative analysis of alternatively spliced exon expression using real-time PCR Quantitative analysis of alternatively spliced exon expression was performed using sequence-specific hydrolysis TaqMan probes to analyse mRNA expression of these exons in non-pregnant myometrium and pregnant myometrium, prior to and after labour onset, as outlined. In order to correct for random errors from sources such as pipetting inaccuracies, separate real-time PCR reactions were performed in triplicate for each amplicon involved. Agarose gel electrophoresis, as well as sequencing analysis, confirmed the specificity of PCR products formed, yielding single product bands of the expected size (data not shown). Quantitative results for each amplicon were obtained by determination of the threshold cycle (C T ) values for each sample, as determined mathematically by the "Second Derivatives" method. Mean absolute cDNA copy number values for each probed amplicon involved, in each myometrial sample, were calculated and grouped per tissue set (i.e. NP, PNL, PL), as shown in Figure 2 . All data were normally distributed, as determined by Normality plots for each group (P > 0.05). Analysis of the expression of the housekeeping gene, β-actin, showed no significant differences between the three tissue sets assayed (P > 0.05). The 3' conserved region of the Maxi-K α subunit was analysed as a measure of overall α subunit expression. The results of this analysis indicated a decrease in expression of the α subunit transcript with labour onset (Figure 2A ). Although this did not reach statistical significance (P = 0.052), the observed decrease in α subunit mRNA expression at labour is in agreement with the decrease seen in α subunit protein levels at labour, reported recently [ 27 ]. Quantitative analysis of the expression of the 132 bp and 87 bp spliced exon transcripts indicated no significant differences in expression, in absolute terms, between NP, PNL, and PL tissues (P > 0.05)(Figure 2B ). Figure 2 Maxi-K α subunit mRNA expression analysed by quantitative real-time PCR . Results shown represent mean (± standard error of the mean, SEM) copy number values for ( A ) total Maxi-K α subunit (represented by the 3' conserved region), and β-actin, and ( B ) the 132 bp and 87 bp alternatively spliced exons of the Maxi-K α subunit. Copy number values were obtained based on product-specific serially-diluted cDNA standards, generated individually for each amplicon of interest. Tissue sets are indicated by striped columns (non-pregnant, NP), black columns (pregnant not-in-labour, PNL) and open columns (pregnant in-labour, PL). The results of expression analyses for the 87 bp and 132 bp spliced exons as a proportion of the total Maxi-K α subunit (i.e. the 87 bp and 132 bp variants) are demonstrated in Figure 3 . Analysis of mRNA expression of the 87 bp variant indicated no significant differences between the three tissue sets assayed (Figure 3A ). Expression of this variant mRNA accounted for only 1% of total Maxi-K α subunit expressed. However, the proportion of Maxi-K channels expressing the 132 bp spliced exon was significantly increased with labour onset (PL), compared to both non-pregnant (NP)(P < 0.05) and pregnant not-in-labour myometrial tissues (PNL) (P < 0.01)(Figure 3B ). Duplicate RT and quantitative PCR analysis confirmed these data. The increase in proportion of this 132 bp variant could be equated to approximately 1.7 fold, from 9% to 15% of total α subunit mRNA expressed. Figure 3 Expression of 132 bp and 87 bp variant mRNAs of the Maxi-K α subunit . The histograms show the mean (± standard error of the mean, SEM) of the ratios of spliced exon to total maxi-K α subunit mRNA for both ( A ) the 87 bp and ( B ) the 132 bp variants in NP, PNL and PL tissues. Results indicate significantly higher expression of the 132 bp exon as a proportion of the total α subunit with labour onset, compared to non-pregnant and pregnant not-in-labour samples. There is no change in expression of the 87 bp variant between the three tissue sets. Tissue sets are indicated by striped columns (non-pregnant, NP), black columns (pregnant not-in-labour, PNL) and open columns (pregnant in-labour, PL). *P < 0.05 versus PL; + P < 0.01 versus PL. Discussion In this study RT-PCR analyses were performed to identify mRNA expression of the Maxi-K α subunit, and alternatively spliced exons of this subunit, in human myometrium in its non-pregnant state, and at term pregnancy, prior to and after labour onset. This was followed by quantitative real-time PCR, which was performed to determine the overall pattern of expression of the Maxi-K α subunit as well as expression of alternatively spliced exons of this subunit identified in these tissue sets. Our findings indicate a trend towards a decrease in α subunit mRNA levels with human labour onset. In order to maintain the uterus in a quiescent state during pregnancy, K + channels provide a potent repolarizing current through the efflux of K + ions, thereby dampening cell excitability and promoting cell relaxation [ 32 ]. Previous studies on murine and rodent myometrium have reported conflicting results for Maxi-K α subunit mRNA and protein expression during pregnancy and with labour onset. Song et al. [ 26 ] identified a decrease in Maxi-K α subunit protein levels in rats at term pregnancy, whereas Benkusky et al. [ 19 ] indicated an increase in protein levels of this subunit in mouse term myometrium. However, a recent report has outlined significant down-regulation in the protein levels of both α- and β-subunits of the Maxi-K channel in human myometrium at labour onset, suggesting that the loss of Ca 2+ and voltage sensitivity is at least partly due to decreased levels of the Maxi-K channel [ 27 ]. Our findings are in agreement with this report, with the highest levels of mRNA expression in the PNL group, and decreased mRNA expression of the Maxi-K α subunit with labour onset (Figure 2 ). Although the decrease in mRNA expression between PNL and PL tissues was ~50%, it was found not to be statistically significant (P = 0.052). A reduction in expression of the Maxi-K α subunit could allow for enhanced myometrial contractility, as reduced α subunit expression would permit an increase in intracellular Ca 2+ levels without the activation of an opposing K + conductance [ 32 ]. Maxi-K channels derive their molecular diversity by alternative splicing of their α subunit transcript at several key sites, which generate channel variants with distinct phenotypes [ 7 , 15 , 16 ]. Previous studies provide evidence that alternate splicing effects calcium and voltage sensitivity of the maxi-K channel and thus channel function in myometrium [ 16 ], surface expression [ 17 ], and sensitivity to protein phosphorylation of the maxi-K channel [ 18 ]. Further direct evidence for the role of alternate splicing of the maxi-K transcript in altering maxi-K protein function in myometrium is provided by the finding of up-regulation of maxi-K splice variants known to alter channel current through alterations in calcium and voltage sensitivity in pregnant mouse myometrium [ 19 ]. Our results from RT-PCR analysis indicate the presence of only two spliced exons, both of which had been identified previously, in human myometrium. The 132 bp exon, previously identified by Korovkina et al. [ 28 ], encodes a 44 amino acid peptide that is inserted into the first intracellular loop of the Maxi-K α subunit, and contains four potential consensus sites for post-translational modification. The 87 bp exon, isolated by Wallner et al. [ 10 ], encodes a 29 amino acid peptide that is introduced into the loop region between hydrophobic regions S8 and S9 of the α subunit protein. Protein sequence analysis of this exon using PROSITE revealed a potential cAMP-/cGMP-protein kinase phosphorylation site (KKeT). Quantitative real-time PCR was used to determine whether identified spliced exons displayed altered expression in pregnancy and/or with labour onset. The use of hydrolysis TaqMan probes provided high reaction specificity and sensitivity, and allowed for highly accurate quantification of target sequences. Our results indicate that there was no significant change in expression of the 87 bp spliced exon, in absolute terms, in non-pregnant (NP), pregnant not-in-labour (PNL) and pregnant in-labour (PL) myometrium. Furthermore, analysis of the expression of this spliced exon as a proportion of the total α subunit expressed (i.e. the 87 bp exon-containing α subunit splice variant) also showed no differences between the three tissue sets assayed. The proportion of Maxi-K α subunits expressing this variant was very low, accounting for only ~1% of Maxi-K channels expressed in the three tissues sets. Little is currently known about the physiological effects of expression of this variant of the Maxi-K channel. However, as described above, it contains a consensus sequence for protein kinase phosphorylation; therefore, it may have important consequences for post-translational modification of channel function. Also, the region into which this exon is inserted, between hydrophobic regions S8 and S9 of the α subunit protein, is thought to be involved in determining the Ca 2+ sensitivity of the Maxi-K channel [ 16 ]. In contrast, while there was no significant change in the mRNA levels of the 132 bp spliced exon in absolute terms between the three tissue sets, there was a significant increase (~1.7 fold) in the proportion of Maxi-K α subunits expressing this exon with labour onset, compared to both non-pregnant and pregnant not-in-labour tissues. Messenger RNA for this 132 bp variant was expressed at much higher levels in comparison to the 87 bp variant, accounting for 9% of total Maxi-K channels in NP and PNL tissues, increasing to 15% at labour onset. An increased proportion of myometrial Maxi-K α subunits expressing the 132 bp spliced exon with labour onset in the human is of interest, as the presence of this exon has been shown to decrease both the Ca 2+ and voltage sensitivities of the Maxi-K channel [ 28 ]. Thus, our findings may provide an additional explanation for the observation of decreased Ca 2+ and voltage sensitivities of Maxi-K channels after labour onset [ 24 ] to reduced expression levels of the α- and β-subunits reported recently [ 27 ]. The exact mechanism by which the presence of this exon causes decreased sensitivity of the Maxi-K channel is unknown. It is possible that post-translational modifications at the four consensus sites present in the exon, perhaps in combination with conformational changes in the intracellular loop due to its increased length, may bring about the observed changes. Determination of the precise mechanism by which the 132 bp exon causes decreased channel sensitivity is an interesting question and is the subject of ongoing investigations in our laboratory. Conclusions Following the onset of labour, the putative disabling of the link between Ca 2+ and Maxi-K channel activation would permit Ca 2+ levels in the cell to rise without the activation of an opposing K + conductance, hence increasing the availability of Ca 2+ for myometrial contraction [ 30 ]. Our findings here suggest that, in human myometrium at labour onset, in addition to decreased Maxi-K α subunit mRNA expression, the increased proportion of Maxi-K α subunits containing the 132 bp spliced exon that are insensitive to Ca 2+ and voltage levels, is responsible for enhanced uterine activity at the time of labour. Whether these variants are assembled as homo- or hetero-tetramers at the plasma membrane remains to be determined. Further investigations are required to assess factors such as the role of β-subunit attachment and modulation of the calcium bowl, and their input to regulation of Maxi-K channels during human pregnancy and labour. This study provides the first quantitative analysis of Maxi-K α subunit mRNA expression in human myometrium, and also highlights alternative exon splicing as a potentially important control mechanism by which myometrial Maxi-K channels may be modulated to suit their functional requirements during these physiological processes. Authors' Contributions MC designed the quantitative RT-PCR techniques and carried out all experimental work. JJM recruited patients, organised the collection of tissues, and conceived of the study. TJS conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524189.xml
514710	Use and comparison of different internal ribosomal entry sites (IRES) in tricistronic retroviral vectors	Background Polycistronic retroviral vectors that contain several therapeutic genes linked via internal ribosome entry sites (IRES), provide new and effective tools for the co-expression of exogenous cDNAs in clinical gene therapy protocols. For example, tricistronic retroviral vectors could be used to genetically modify antigen presenting cells, enabling them to express different co-stimulatory molecules known to enhance tumor cell immunogenicity. Results We have constructed and compared different retroviral vectors containing two co-stimulatory molecules (CD70, CD80) and selectable marker genes linked to different IRES sequences (IRES from EMCV, c-myc , FGF-2 and HTLV-1). The tricistronic recombinant amphotropic viruses containing the IRES from EMCV, FGF-2 or HTLV-1 were equally efficient in inducing the expression of an exogenous gene in the transduced murine or human cells, without displaying any cell type specificity. The simultaneous presence of several IRESes on the same mRNA, however, can induce the differential expression of the various cistrons. Here we show that the IRESes of HTLV-1 and EMCV interfere with the translation induced by other IRESes in mouse melanoma cells. The IRES from FGF-2 did however induce the expression of exogenous cDNA in human melanoma cells without any positive or negative regulation from the other IRESs present within the vectors. Tumor cells that were genetically modified with the tricistronic retroviral vectors, were able to induce an in vivo anti-tumor immune response in murine models. Conclusion Translation of the exogenous gene is directed by the IRES and its high level of expression not only depends on the type of cell that is transduced but also on the presence of other genetic elements within the vector.	Background Gene therapy protocols would strongly benefit from the development of a one step technique that would allow cells to be genetically modified through the introduction of several therapeutic genes. In order to induce the translation and expression of exogenous cDNAs, carried by a single vector, researchers have cloned internal ribosomal entry sites (IRES) upstream from these exogenous cDNAs. This approach should lead to the translation of three cistrons from an unique mRNA and therefore to the consequent expression of the three encoded proteins [ 1 - 6 ]. In most cases, the IRES from EMCV is cloned into polycistronic vectors as it induces high levels of DNA translation [ 3 , 7 , 8 ]. The capacity of other IRESes to induce high levels of exogenous cDNA expression in different cell types has been compared to the capacity of the EMCV IRES [ 2 - 4 , 9 - 11 ]. However, in most cases, these comparisons were carried out after different IRESes had been inserted into a single, characterized, dicistronic (one IRES) or tricistronic (two IRESes) mRNA and after the in vitro vector translation efficiency had been established [ 9 - 14 ]. These studies are useful in choosing the IRES that will drive the in vivo expression of heterologous proteins, they do, however, give little information as to the potential in vivo interactions that occur between different IRESs cloned into the same MuLV-based retroviral vector. We cloned tricistronic vectors encoding three different cDNAs. This involved using at least two IRESes to translate the second and third cistrons. Using the same IRES twice in a single vector could, however, induce recombination events and the loss of the second IRES and cistron. In the same way, using the same cistron twice could lead to a competition between the two IRESs for the binding to cell type specific translation factors. For these reasons, we chose to clone and compare the efficiency of different IRESes cloned into the same vector. We chose the IRES of EMCV (IRES EMCV ), the IRES of the c-myc proto-oncogene (IRES C-MYC ), the IRES of FGF-2 (IRES FGF-2 ) and the IRES of the HTLV-1 lentivirus (IRES HTLV-1 ) [ 1 , 8 , 15 - 22 ]. The vectors were constructed so that the third cistron was translated from the IRES EMCV and the second cistron was translated from the IRES EMCV , IRES C-MYC, , IRES FGF-2 or IRES HTLV-1 . Recently, it has been shown that retroviral vectors derived from MuLV contain an additional IRES on the 5' gag sequence [ 20 , 23 ]. The vectors described here contained three IRESes: the IRES from MuLV located between the LTR and the Psi sequence controlling the translation of the first cistron, the IRES from a different origin and the IRES from EMCV respectively controlling the translation of the second and third cistrons (Figure 1A and 1B ). The exogenous genes cloned into the tricistronic vectors were chosen for their potential use in clinical trials. They code for co-stimulatory molecules known to enhance tumor cell immunogenicity: CD80, a member of the B7 family and CD70, a member of the TNF family [ 7 , 24 - 26 ]. These molecules act in synergy to enhance the induction of Ag-mediated anti-tumor immunity when co-expressed with tumor antigens [ 7 , 24 , 25 , 27 ]. We generated retroviral vectors that encoded the two co-stimulatory molecules CD70 and CD80, and a selection gene. We compared the efficacy of these vectors in their capacity to genetically modify various human and murine cells, and also observed how they affected the selection and culture of these cells following transduction. We then compared the expression of the three exogenous genes within the genetically modified cells. Murine melanoma cells were then tested in two different murine tumor models for their ability to induce an in vivo anti-tumor immune response, regardless of the percentage of co-stimulatory molecules expressed by the transduced cells. Results Construction of tricistronic retroviral vectors expressing CD70 and CD80 We constructed tricistronic vectors that would induce the expression of three cDNAs (CD70, CD80 and a selection gene) from one promoter (LTR viral promoter) (Figure 1 ). The constructions are described in the Methods . Expression of the first open reading frame (cDNA encoding a co-stimulatory molecule) occurs from one IRES (MuLV) located at the 5' extremity of the mRNA. The second and third open reading frames are translated from two identical or two different IRESes. TFG EMCV NEO or TFG EMCV ZEO were constructed so that the translation of the selection gene and the second co-stimulatory molecule could be induced from two identical IRES EMCV (Figure 1A ). TFG HTLV-1 , TFG C-MYC and TFG FGF-2 were constructed to allow the expression of the selection gene from IRES HTLV-1 , IRES C-MYC or IRES FGF-2 while the translation of the third open reading frame was under the control of IRES EMCV (Figure 1B ). Efficiency of the different IRESes in inducing the expression of the selection gene (NEO or ZEO) in different cell types We generated retroviral vectors using the different plasmids described in Figure 1 and transfected ψCRIP cells or triple-transfected the 293T packaging cell line. We obtained viable G418 or zeocin-resistant ψCRIP cells after transfection with TFG EMCV NEO, TFG EMCV ZEO, TFG HTLV-1 ZEO, TFG HTLV-1 NEO, TFG FGF-2 ZEO or TFG FGF-2 NEO but none after transfection with TFG cMYC ZEO or TFG cMYC NEO. We tested the supernatants from ψCRIP or 293T transfected cell suspensions for the presence of replication competent retroviruses (RCR) through the dosage of reverse transcriptase activity. The supernatants from all the transfected packaging cells were free of reverse transcriptase activity. The titers of the different retroviruses produced different results, depending on the experiments, varying from 10 4 to 10 6 particles/ml. We used 10 5 particles of each type of retrovirus that was produced (TFG FGF-2 ZEO, TFG HTLV-1 ZEO or TFG EMCV ZEO) or the 48 hour supernatants from transiently transfected TFG cMYC ZEO ψCRIP or 293T cells to transduce different types of mammalian cells. The murine cells used were either NIH-3T3 fibroblasts or B16.F10 melanoma cells. To establish a human model, we cultured melanoma cells from biopsies as described in the Methods . During the course of this study we obtained 23 melanoma biopsies. Fifteen cell cultures were obtained from these biopsies which represents a yield of 65 %. The quality and characteristics of the melanoma cells were determined by immunohistochemistry, on cytospin cells, using anti-cytokeratin (KL-1) (negative control), anti-S100 protein, anti-melanA/MART1 and anti-HMB-45/gp100 antibody staining as described in the Methods . The 15 human cell cultures obtained all stemmed from melanoma cells (data not shown). The transduced cells were selected for their resistance to G418 or zeocin. Fifteen days after the transduction with each retroviral vector, we selected G418 or zeocin-resistant cells. Apart from the TFG CMYC ZEO transduced cells, we obtained roughly the same number of zeocin or G418 resistant clones with the different retroviral constructs. Both murine and human cells could be successfully genetically modified using the engineered trigenic retroviral vectors. No vector was statistically more efficient in obtaining a higher yield of resistant clones. However, the TFG EMCV ZEO, TFG FGF-2 ZEO and TFG HTLV-1 ZEO cells were long lasting, viable and could be expanded, whereas neither murine nor human TFG cMYC ZEO transfected cells displayed long-term viability. The selected genetically modified cells expressed co-stimulatory molecule mRNAs Cells were stably transduced with MFG derived vectors encoding CD70, CD80 and an antibiotic resistance gene. After selection with the appropriate antibiotics (G418 or Zeocin), the stably transduced cells were analyzed for the expression of the different mRNAs, by RT-PCR using specific primers. The aim of the RT-PCR analysis was to show, through the expression of the full length RNA, that successful transcription of the construct had been achieved. We were uncertain whether the transcription of the ectopic DNA was complete. RT-PCR analysis was performed using cells that were resistant to Zeocin. We are convinced that the mRNA transcribed from the ectopic DNA contains the IRES zeocin cassettes. As we can noticed in figure 2A , the primers used for PCR analysis n°4 and 5 overlapped. They hybridized with the sequence corresponding to the ZEO gene. Our hypothesis is that if we can amplify the two segments of the construction (CD70-IRES-ZEO and ZEO-IRES-CD80 or CD80-IRES-ZEO and ZEO-IRES-CD70) at the same time from the ectopic RNA, then the full length RNA had been transcribed. We have already performed other RT-PCR analyses using this the long ranger taq polymerase from Applied (France). We have been able to amplify full length RNA from all constructs (data not shown). Taken together our data strongly suggests that the full length RNA was transcribed from all the viral constructs. These RT-PCR results suggest that there was no downregulation of CD70 or CD80 expression at the transcriptional and post-transcriptional levels. The selected genetically modified cells expressed the co-stimulatory molecules at different levels The cell populations were tested for co-stimulatory molecule expression by flow cytometry using Abs that were directed against CD70 and CD80. Within a given population, a large percentage of cells expressed the two co-stimulatory molecules in a stable manner and at high levels. Figure 3F shows the results of the flow cytometric analysis of human melanoma cells transduced with TFG FGF-2 ZEO. Figure 3 is representative of the cytometric analyses carried out on the murine B16.F10 melanoma cells transduced with 48 hr supernatants of 293T cells transfected with the 4 different types of retroviral vectors. A high percentage of B16.F10 cells transduced with TFG FGF2 ZEO or TFG HTLV-1 ZEO retroviral vectors (Fig. 3D and 3E respectively) expressed both co-stimulatory molecules. The percentage of B16.F10 cells, transduced with TFG EMCV ZEO or TFG c-MYC ZEO, expressing only CD80 was higher than the percentage of cells expressing only CD70 or both molecules (Fig. 3B and 3C respectively). The level of expression of the two molecules differed depending on the vectors used and the cell types that were transduced, as shown in Table 1 - see additional file 1 . In theory, selected clones expressed both molecules. In fact, in any selected clone, we found cells that expressed only one of the molecules (CD70 or CD80) and cells that expressed the two molecules. Murine cells In murine cells (either fibroblasts or melanoma cells), a high percentage of cells only expressed CD70. This was not due to the expression of the CD70 molecule, in itself. Indeed, when we used constructs with CD80 as the first cistron, we obtained a high percentage of cells that only expressed CD80. This percentage could be attributed to a negative regulation of the translation of the third cistron. Even after the selection of transfected cells, we obtained cells which did not express detectable levels of co-stimulatory molecules. Indeed, in TFG HTLV-1 ZEO, TFG FGF-2 ZEO or TFG EMCV ZEO transduced murine NIH-3T3 cells, we respectively found 35%, 31% or 44% of cells that expressed undetectable levels of CD70 or CD80. Expression levels were assessed regardless of the resistance gene that was used (NEO or ZEO). We tested the expression of the two co-stimulatory molecules immediately after transduction or after selection. No correlation could be established between the time of analysis and the percentage of cells expressing both molecules. One clone could be composed of a majority of cells (60%) expressing both molecules at day 5 post selection, only have a small percentage of these cells at day 15 and up to 95 % on day 25. Indeed, even within a selected population of cells, the percentage expressing both co-stimulatory molecules could vary from 5 up to 95 % of the total cell number. After transduction with a single vector, 20 clones were selected. Within the same clone, some cells expressed only one co-stimulatory molecule whereas others expressed both molecules. These observations are reflected by the high SD of the percentage of cells expressing co-stimulatory molecules (Table 1 - see additional file 1 ). None of the vectors used were found to be adequate for the transfection of murine cells. Human cells For human cells, we chose to use a pool of transduced cells, rather than clones, to stay as close as possible to the reality of human clinical protocols. When we used TFG HTLV-1 ZEO (CD80 first) or TFG HTLV-1 ZEO2 (CD70 first) we obtained cells that expressed only the first cistron. We obtained a better yield of cells expressing the two co-stimulatory molecules when using the TFG FGF-2 ZEO construct (70% of cells expressing the two molecules in a stable manner). Again, even within a selected population of cells, the percentage of cells expressing both co-stimulatory molecules could vary considerably (from 45 to 95 % of total cell number). In human melanoma cells, the use of tricistronic vectors in which IRES FGF-2 induced the translation of the second cistron, and IRES EMCV the translation of the third cistron, led to a high percentage of cells expressing the three cistrons. Expression of the tricistronic transgene slows the tumor growth rate after s.c. injection of B16.F10 in an established model Among selected cells, the percentage expressing both co-stimulatory molecules varied. We have previously shown that melanoma cells expressing high levels of CD70 alone or in combination with CD80 induced in vitro splenocyte proliferation [ 7 ]. Using a pool of selected cells that were genetically modified by TFG HTLV-1 ZEO (52 % CD70, 21 % both CD70 and CD80), TFG FGF-2 ZEO (5 % CD70, 33 % both CD70 and CD80), TFG EMCV ZEO (27 % CD70, 16 % both CD70 and CD80) or double-transfected with DFG CD70 and DFG CD80 (>65 % both CD70 and CD80), we showed that different percentages of cells expressing both co-stimulatory molecules (even as little as 20 %) could induce a proliferative response in splenocytes. A substantial increase in spleen cell proliferation was observed when the two molecules were expressed following genetic modification with all the viral vectors. This increase was similar to that induced by the use of double transfected cells (data not shown). To determine whether the local expression of CD70 and CD80 could affect tumor establishment, we sub-cutaneously injected 10 5 cells, from each type of tumor, into the flanks of C57BL/6 mice (Figure 4A ). These cells had previously been used in splenocyte proliferation experiments. Subcutaneous injection of B16.F10 cells into B6 syngeneic immunocompetent mice led to the development of tumors. However, there was a delay in the appearance of tumors derived from transduced or double-transfected cells compared with tumors induced by the inoculation of parental or mock-transfected cells (control B16.F10 cells transfected with a retroviral vector encoding the zeocin-resistance gene). Although, all mice had palpable tumors before day 10, the growth rate was significantly slower for TFG FGF-2 ZEO or TFG HTLV-1 ZEO transduced cell tumors compared to parental cell tumors (p < 0,01) and double transfected cell tumors (p < 0.001) on day 20 (Figure 4A ). This decrease in tumor growth was less pronounced in tumors derived from cells modified by tricistronic vectors than in tumors derived from cells modified by two independent vectors. This could be due to the level of expression of the co-stimulatory molecules on the cell surface. We have previously shown that co-expression of the two co-stimulatory molecules is necessary to induce an in vivo immune response. Here we show that, for the B16.F10 melanoma cell model, we had to inject as many as 6 × 10 4 cells (60 % of the injected cells) expressing both co-stimulatory molecules to observe an immune response. We have previously shown that the anti-tumor effect is more difficult to obtain in a MHC class I loss variant than in a MHC class I positive model [ 7 ]. To confirm how important the percentage of cells expressing both co-stimulatory molecules is in inducing an in vivo immune response, we transduced TS/A adenocarcinoma cells using the same retroviral vectors, as previously described. We pooled the zeocin resistant cells and chose two pools. In the first pool of cells transduced with TFG EMCV ZEO, 34 % only expressed CD70 and 23 % expressed both CD70 and CD80. In the second pool of cells transduced with TFG FGF-2 ZEO, 73 % only expressed CD70 and 20 % expressed both CD70 and CD80. These two pools were injected sub-cutaneously into syngeneic immunocompetent BALB/c mice. These injections led, in all cases, to the development of tumors. However, when the cells were double-transfected with two independent vectors and more than 70 % of cells expressed both co-stimulatory molecules, most of the palpable tumors spontaneously decreased within 10 days. In contrast, only a delay in the appearance of the tumors derived from transduced cells could be observed. This delay was more or less pronounced depending on the percentage of cells expressing both molecules. There was no delay in the appearance of tumors derived from the pool containing 34 % of cells expressing only CD70 and 23 % of cells expressing CD70 and CD80. A delay was observed in the appearance of tumors derived from the pool containing 73 % of cells expressing only CD70 and 20 % of cells expressing CD70 and CD80 (figure 4B ). Discussion In this study, we have constructed and tested different tricistronic retroviral vectors containing IRES elements from different origins. As IRESes are remarkably efficient when used in bicistronic vectors, it was particularly interesting from a biotechnological point of view (for gene therapy protocols) to design polycistronic vectors that could allow the expression of several proteins from the same mRNA. Several authors have reported the construction of different vectors using the IRES EMCV or the IRES FMDV2A to trigger the high level expression of an exogenous gene[ 2 - 4 , 10 , 11 , 28 ]. Prats and coll. have described several other IRESes including the IRESs from the c-myc proto-oncogene, the IRES from FGF-2 and the IRES from HTLV-1 [ 17 , 18 , 20 , 21 ]. The first aim of our work was to determine whether one of these IRESes could induce a higher level of exogenous protein expression than the IRES from EMCV in different cell lines. The second aim was to design polycistronic vectors carrying different IRESes to avoid the risk of recombination between IRESes. The third aim was to obtain genetically modified melanoma cells through transduction with tricistronic retroviral vectors. These tumor cells would therefore be genetically modified to express two co-stimulatory molecules, CD70 and CD80, which are known to induce an anti-tumor response in syngeneic mice. As we have generated retroviral vectors derived from the well known MFG vector (MuLV vector), we already had one additional IRES upstream from the first ATG codon (initiation codon of the first exogenous cDNA). This IRES has been described by Vagner and coll [ 20 ]. The first IRES (MulV) and the third IRES (EMCV) were conserved in all the vectors. The second IRES responsible for inducing the translation of the selectable marker, was the IRES from either EMCV, FGF-2, c-myc or HTLV-1. The choice of IRES that was used to express the cDNA encoding the G418 or zeocin-resistance genes was unimportant as we obtained resistant cells in all the cell lines tested: murine tumor cells (B16.F10, TS/A), murine fibroblasts (NIH3T3), packaging cell line (ψCRIP), human melanoma and lung adenocarcinoma cells (A549). However, when the IRES from the c-myc proto-oncogene was used, we never obtained long-lasting zeocin or G418 resistant murine or human cells, whether these were tumor cells or fibroblasts. So far, most of the cellular mRNAs that contain IRESes and code for proteins involved in the control of cell proliferation and differentiation, require stringent regulation like for example the c-myc mRNAs [ 13 , 15 , 29 , 30 ]. These genes need to be expressed at very specific stages of the cell cycle and/or in response to different stimuli [ 17 , 19 ]. This has also been shown for FGF-2. Indeed the CUG-initiated isoforms of FGF-2 are translationally activated in response to stress [ 21 ]. Such observations suggest that when the IRES c-myc is used, translation is strongly downregulated [ 30 ]. We obtained long-lasting viable resistant cells when we used the IRESes from EMCV, FGF-2 or HTLV-1. The number of clones obtained after transduction or transfection was roughly the same depending on the experiments and the cell lines tested. This indicated that only a few (if any) recombination events occurred when we used the same IRES (EMCV) twice in the same retroviral vector. The first and third IRESes are responsible for inducing the translation of the two co-stimulatory molecules. These IRESes competed to induce the expression of the two exogenous cDNAs. Indeed within the same population of selected cells, whatever the retroviral vector used, we were able to obtain cells that only expressed the first exon, or only the third exon or both exons. The percentage of cells that expressed both co-stimulatory molecules varied with the cell passage and from one selected clone to another. This is true regardless of the cell line tested: murine tumor cells (B16.F10, TS/A), murine fibroblasts (NIH3T3), murine packaging cell line (ψCRIP), human melanoma cells and human lung adenocarcinoma cells (A549). There is a difference in the IRES-dependent mechanism that occurs in cellular and viral internal initiation. Currently, two cellular trans -acting factors, the La antigen and PTB have been found to bind to picornavirus IRES elements and to be essential for their internal initiation of translation [ 29 , 31 , 32 ]. However, these proteins do not specifically bind to eukaryotic cellular mRNAs with the same efficiency. IRES function must require either different amounts of translation initiation factors or, more likely, additional proteins similar to those required for the cap-dependent initiation of protein synthesis [ 29 , 33 ]. Borman and coll. have recently shown that the recognition of different IRES elements varies within different tissue culture cell lines [ 9 , 12 ]. The activity of a particular IRES within a cell may be dependent on the relative level of stimulatory and inhibitory molecules [ 34 ]. It is possible that different trans -acting factors that are dependent on a specific IRES may be required. It could be that the MuLV IRES (first exon) binds those trans -acting factors with a higher affinity than the IRES from EMCV (third exon). Anthony and Merrick suggested that translation factors, that have a higher affinity for the cap structure than for the IRES element, could be sequestered at the m7GpppN cap structure and would therefore be unavailable for the internal initiation of translation at saturating concentrations of capped bicistronic RNA [ 1 , 35 ]. This would lead to an increased translation of the first cistron and a decreased translation of the second and third cistrons that are thought to be dependent on internal initiation of translation. In our case, we have an IRES (IRES MulV) on the 5' end of the mRNA. This IRES induces the translation of the first co-stimulatory molecule. However, while the IRES from EMCV or HTLV-1 could interact with other IRESes present within the retroviral construct (the IRES from gag or the IRES from EMCV), we found that the IRES from FGF-2 induced the expression of exogenous cDNA in human melanoma cells without any positive or negative regulation from the other IRESes. We have previously shown that two co-stimulatory molecules (CD70 and CD80), expressed on the surface of tumor cells could induce an anti-tumor immune response when the cells were injected into a syngeneic animal [ 7 , 27 ]. In tumor cells that were genetically modified by the tricistronic retroviral vector, we attempted to induce an in vivo anti-tumor response in murine models. We first showed that B16.F10 cells that were genetically modified by the tricistronic vectors, could induce in vitro proliferation of spleen cells. These B16.F10 cells were then injected into syngeneic animals and tumor growth was monitored. We observed that in this murine model (C57BL/6) or in the BALB/c murine model (breast adenocarcinoma TS/A cells), co-expression of the two co-stimulatory molecules by at least 50 % of cells was necessary to induce an anti-tumor response. CD70 expression, alone or in association with a low level of CD80 expression, was not sufficient to induce anti-tumor immunity. These findings show that at least 50 % of the genetically modified cells must express the CD70 and CD80 co-stimulatory molecules before starting an immunotherapy protocol. Establishing cultures of human melanoma cells derived from biopsies was very difficult, we obtained a low yield of 63 %. We could infect human melanoma cells with the tricistronic retroviral vector with an efficiency of 50 %. However, within the 50 % of cells that were genetically modified we could only obtain a high percentage of cells expressing both co-stimulatory molecules when we used the tricistronic recombinant amphotropic viruses obtained with the IRES FGF-2. Conclusion The ability of retroviral vectors carrying IRESes to deliver genes, in vitro and in vivo, to a variety of dividing cell types has been applied to research and gene therapy for the past 10 years. Our work shows that it is difficult to chose which IRES must be inserted into a polycistronic gene therapy vector, when the aim is to ensure a high level of translation of the exogenous gene. This level of expression will depend on the type of cell that is transduced but also on the presence of other genetic elements within the vector. Methods Cell lines The murine melanoma B16.F10 cell line and the mouse mammary adenocarcinoma TS/A cell line, previously described, were cultured in RPMI 1640 supplemented with 2 mM glutamine and 10% fetal calf serum (FCS) (GIBCO-BRL, Cergy-pontoise, France). NIH-3T3 cells and the cysteine-rich intestinal protein (ψCRIP) and 293T packaging cell lines, were purchased from the American Type Culture Collection (Rockville, Md, USA). These three cell lines were cultured in Dulbecco's modified Eagle's medium supplemented with 10 % FCS [ 27 ]. All cell lines were periodically tested for mycoplasma infection using a DNA hybridization probe (Stratagene, La jolla, CA, USA). Primary culture of human melanoma cells Melanoma tumor biopsies were dissected into small explants and then enzymatically digested with collagenase (5 mg/ml) and hyaluronidase (3 mg/ml) (SIGMA, Saint Quentin Fallavier, France) for 1 hour at 37°C under agitation. The cells were then centrifuged (5 minutes at 1200 rpm) and transferred to a culture flask and left to proliferate for 10 days. These cells were cultured in RPMI 1640 supplemented with 2 mM glutamine, 10% FCS, non-essential amino acids and vitamins (SIGMA, France). During the first 4 days after the first passage, cells were cultured with 0.1 mg/ml of G418 (GIBCO-BRL, Cergy-pontoise, France) to remove fibroblasts as described by Mouriaux and coll[ 36 ]. The quality and characteristics of the melanoma cells were studied by immunohistochemistry using anti-cytokeratin (KL-1), anti-S100, anti-HMB45/gp100 and anti-melanA/MART1 (clone A103) antibodies (all from DAKO SA, Trappes, France). Retroviral constructs The pMDgag/pol and pBA-GALV plasmids were obtained from the Genethon (Evry, France). The tricistronic vectors are MFG-based retroviral vectors. These vectors were derived from the DFG-human-CD80 (hCD80) and DFG-human-CD70 (hCD70) vectors that have previously been described [ 7 , 27 ]. The first cistron (cDNA encoding hCD70 or hCD80) was cloned between the Nco1 and BamH1sites of the MFG vector. The AUG of this molecule corresponds to the AUG of the env gene of the MFG vector. Construction of TGF EMCV ZEO or NEO In these vectors, the translation of the genes encoding the two co-stimulatory molecules and the cDNA encoding the G418 or zeocin resistance genes are under the control of the IRES EMCV . We digested the Blue-script plasmid (PKs) (Stratagene, La jolla, CA, USA) with Xho1 and EcoRV to insert the cDNA encoding IRES EMCV (636 bp), obtained from PCR amplification of pIRES-EGFP (Clontech, Palo Alto, CA, USA), and obtained a PKs IRES EMCV vector. This vector was digested by Nco1 and EcoR1 and ligated with the cDNA encoding either CD70 or CD80, obtained from the PCR amplification of DFG-CD70 or DFG-CD80 respectively. The PKs IRES EMCV CD70 or PKs IRES EMCV CD80 vectors were digested by BamH1. These inserts have been cloned into either DFG CD80 NEO or ZEO by partial digestion using BamH1, generating the (T) tricistronic vectors TFG EMCV NEO or TFG EMCV ZEO with CD80 as first cistron and CD70 as third cistron or in DFG CD70 NEO or ZEO generating the same type of tricistronic vectors but where CD70 is the first cistron and CD80 is the third cistron. Construction of TGF FGF-2 ZEO, TGF HTLV-1 ZEO, TGF C-MYC ZEO or NEO Through PCR amplification, we cloned the DNA encoding the IRES of the human basic Fibroblast Growth factor (FGF-2) (547 bp), the IRES of the c-myc oncogene (cMYC)(602 bp) and the IRES of the HTLV-1 lentivirus (249 bp) upstream from the cDNA encoding the G418 or zeocin resistance genes in the PKs plasmid. We generated different combinations of cDNAs with BamH1 sites on both the 5' and 3' ends: IRES HTLV-1 -NEO, IRES HTLV-1 -ZEO, IRES FGF-2 -NEO, IRES FGF-2 -ZEO, IRES cMYC -NEO and IRES cMYC -ZEO. These constructs were inserted downstream from the gene encoding the first co-stimulatory molecule on the BamH1 site. We generated the TFG FGF-2 NEO or ZEO, or TFG c-MYC NEO or ZEO and TFG HTLV-1 NEO or ZEO tricistronic vectors (Figure 1A ). All the vectors were sequenced. Transfection and transduction CRIP packaging cells were transfected with the different plasmids using the lipofectamine technique followed or not by selection with G418 (1 mg/ml) (from Life Technologies, GIBCO-BRL, France) or Zeocin (0.2 mg/ml) (CAYLA, France). The resistant CRIP clones were expanded and screened for viral titers which were of approximately 10 4 viral particles/ml/48 hours/10 6 CRIP cells. 293T cells were triple-transfected with the different plasmids: TFG, pMDgag/pol and pBA-GALV. Estimation of the viral titer in transiently transfected 293T cells showed the presence of 10 6 viral particles/ml/48 hours/10 6 293T cells. Fibroblasts or tumor cells (B16.F10, TS/A or human melanoma) were transduced with the retroviral vectors using polybrene (8 μg/ml) (SIGMA, France). The stably transduced cells were selected using G418 or Zeocin depending on the viral particles used, and the resistant cells were either cloned or pooled and used in subsequent experiments. RT-PCR Cells were cultured in T-75 cm 2 culture-flasks for 72 h until they reached sub-confluence. Total RNA was isolated from a suspension, as described by Choczynski and Sacchi (1987) [ 37 ], of 5 × 10 6 cells using TRIZOL™ reagent following the manufacturer's recommendations (Life Technologies, Cergy Pontoise, F). RNA solutions were treated with 5 units of DNAse 1 (Roche Diagnostics, Mannheim, D) to remove any contaminating genomic DNA. mRNA was transcribed into cDNA using the Ready-to-go™ kit (Amersham Pharmacia Biotech. Inc. Piscataway, NJ, USA) and random primers were purchased from Life Technologies. Amplification of cDNA was carried out using 1U/100 μl of Taq DNA polymerase (Roche Diagnostics, Mannheim, D) in a PTC-100™ Programmable Thermal Controller (MJ Research, Watertown, Mass, USA) after 33 temperature cycles consisting of denaturation at 94°C (60 s), annealing at 65°C (60 s) and elongation at 72°C (120 s). The following primers were used: MFG sense primer (Trigen 1): 5'-TGTAAAACGACGGCCAGTCACGTGAAGGCTGCCGACC-3', ZEO anti-sense primer (trigen 5): 5'-CAGGAAACAGCTATGACCCACCGGAACGGCACTGGTC-3', ZEO sense primer (trigen 4): 5'-TGTAAAACGACGGCCAGTGACCAGTGCCGTTCCGGTG-3' and MFG anti-sense primer (trigen 10): 5'-CAGGAAACAGCTATGACCGCCTGGACCACTGATATCCTGTC-3'. PCR products and the lambda/hindIII molecular weight marker (Promega, Lyon, F) were separated by electrophoresis on 0,8% agarose (Roche, Mannheim, D), Tris Borate EDTA (Interchim, Monluçon, F) gels and visualized by staining with ethidium bromide. Immunostaining and flow cytometric analysis Transduced cells were stained for membrane expression of the two co-stimulatory molecules using PE-conjugated mouse anti-human CD70 mAb and FITC-conjugated mouse anti-human CD80 mAb (Pharmingen, Hamburg, D) as previously described [ 7 ]. Stained cells were analyzed using a FACScalibur (Becton Dickinson, Mountain View, USA). Establishment of murine tumor models Female C57BL/6 (H-2b), or BALB/c (H-2d) mice were obtained from CERJ Janvier (St Quentin-Fallavier, France). All ear-tagged mice were kept in the special pathogen-free animal facility in our institution and were used for experiments between the age of 6 to 8 weeks. To establish subcutaneous (s.c.) tumors, 105 cells (twice the minimal tumorigenic dose) were suspended in 0.1 ml of PBS and injected s.c. into the flank. Animals were examined daily until the tumor became palpable, the diameter of the tumor, in two dimensions, was then measured twice a week. The animals were sacrificed when the tumor size reached 2.5 × 2.5 cm in the control group. The statistical significance of the data was established using the two sample student's t-test. A p-value of less than 0.01 was considered to be statistically significant. Authors' contributions VDE carried out the cellular and in vivo studies, SB the synthesis of the retroviral vectors (molecular biology and virology). PR performed the characterization of the melanoma biopsies. LC provided all the IRES sequences. BC and ACP are responsible for conceiving this work. BC participated in the design, coordination and drafting of this manuscript. GF is the director of the laboratory. All authors read and approved the final manuscript. Supplementary Material Additional file 1 Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514710.xml
529446	Hereditary risk factors for the development of gastric cancer in younger patients	Background It is believed that the development of gastric cancer (GC) before the age of 50 has a hereditary basis. Blood group A and history of gastric cancer in first-degree relatives have been shown to be risk factors for GC. Methods In this case-control study, we enrolled patients with GC who were diagnosed before the age of 50. Patients who were diagnosed as having GC were selected. A total of 534 cases were found; of these, 44 diagnosed before the age of 50 were included in the case group. For the control group, 22 males and 22 females were randomly selected from the remaining subjects, who had diagnoses of GC after the age of 50. All the surviving patients and family members of the dead patients were interviewed about the history of cancer in the family and the age at which other family members developed cancer. The blood group of each subject was also obtained. Results forty-four cases under 50 years old (mean age: 36.2 years) and forty-four controls (mean age: 67.1 years) were enrolled in the study. At the time of the study, 59.1% of the study group and 50% of the control group were alive (P value = NS). In the study group, 68.1%, 13.6%, 13.6% and 4.5% had blood groups O, A, B and AB, respectively. In the control group the corresponding figures were 27.7%, 63.6%, 6.8% and 4.5%. First or second-degree relatives with cancer, including gastric (the most frequent), breast, lung, gynecological and hematological malignancies, were noted in 54.5% of the cases and 11.4% of the controls (p < 0.01). Family histories of cancer were accepted as valid provided that they were based on valid medical documents. Conclusions It seems that the development of GC before the age of 50 is likely to be accompanied by familial susceptibility. Interestingly, our study showed a significant correlation between blood group O and the development of gastric cancer under the age of 50.	Background Gastric cancer is the second most common cause of cancer-related death in the world [ 1 ]. Its incidence varies considerably worldwide [ 2 ]. In general, it is a larger problem in developing countries than in industrialized nations, and shows a predilection for urban and lower socioeconomic groups [ 3 , 4 ]. The estimated crude rate accounts for approximately 9.9% of cancers worldwide [ 5 ]. Gastric cancer rarely occurs before the age of 40. The incidence rises steadily thereafter, peaking in the seventh decade. Men are nearly twice as susceptible as women. This cancer alone is the cause of more than 750,000 deaths per annum in the world [ 6 ]. Marked variation within countries has also been observed [ 3 , 4 ], particularly in high-risk countries [ 7 ]. In developing countries, the overall incidence of gastric cancer is increasing and projections indicate that the annual number of new cases will increase significantly during the next few decades as a result of adult population growth [ 6 ]. A recent cancer survey by the Iranian Ministry of Health and Medical Education revealed that gastric adenocarcinoma is the most common fatal cancer in Iran, with a wide variation of death rate among different provinces [ 8 ]. According to recent cancer statistics, deaths due to gastric cancer constitute about 39% of all deaths due to cancer each year in some parts of Iran [ 9 ]. The reduced incidence of gastric cancer in western countries reflects a decrease in cancers arising in the distal stomach (body and antrum). In contrast, the incidence of cancer in the proximal stomach and esophagogastric junction has steadily increased, at a rate exceeding that of any other cancer except melanoma and lung cancer [ 10 - 13 ]. In a very recent study, our group showed that cardiac cancer constitutes 49.5% of all sites for gastric cancer in Iran. In contrast, cancers of body and antrum comprise 20.6% and 29.9% respectively [ 9 ]. Unlike cancer of the distal stomach, cancers of the proximal stomach and esophagogastric junction are more common among higher socioeconomic classes [ 6 ]. Overall, these observations suggest that proximal cancers share a similar pathogenesis, which is distinct from that of distal cancers. Zanghieri and La Vecchia found that about 10% of cases show familial clustering. Epidemiological studies have shown that the risk of gastric cancer in first-degree relatives is increased 2- to 3-fold [ 14 - 17 ]. The relative contributions of inherited susceptibility and environmental effects on familial gastric cancer are poorly understood. In general, familial genetic mechanisms do not play as important a role in gastric cancer as they do in e.g. colorectal cancer. Nonetheless, in some regions, a family history of gastric cancer may be a risk factor for the disease, although this might reflect environmental factors shared by members of a family [ 18 ]. Rate collections of familial aggregates of gastric cancer have been reported, but are distinctly unusual. As yet there is no comprehensive hypothesis for the development of gastric cancer. Gastric cancers are associated with chromosomal aberrations and other genetic defects, but none of these is necessary or sufficient for cancer to occur. In a review about genetic predisposition to gastric cancer, Bevan and Houlston (1999) concluded that several genes may be associated with increased risk [ 19 ]. Gastric cancer is a manifestation of several inherited cancer predisposition syndromes including hereditary nonpolyposis colon cancer, familial adenomatous polyposis, Peutz-Jeghers syndrome and Cowden disease. This suggests the presence of predisposing genes with different effects. Many studies have addressed the correlation between ABO antigens and the development of gastric cancer, but most of these have indicated a correlation between sporadic cases of gastric cancer and blood group A. This association further supports the role of genetic factors in the development of gastric cancer [ 21 ]. Blood type A is more strongly associated with the diffuse histopathological type of gastric cancer than the intestinal type [ 21 , 22 ]. To our knowledge, similar studies on the specific category of gastric cancer in younger patients are scanty. This may be one of the first studies on the role of hereditary factors in the development of the gastric cancer in younger patients. Methods The study was designed as a case-control study. We set up an active surveillance to identify patients with gastric cancer. Patients' records in the department of pathology in the main private referral facility in Tehran were scrutinized for gastric cancer cases between 1999 and 2003. Patients are referred here from all regions of the country and from different ethnic backgrounds and they are operated upon in the same hospital, so all the operation and pathology reports were available simultaneously. All the pathology reports were prepared and diagnosed by the same pathologists. The cases were selected from patients who were diagnosed with gastric cancer before the age of fifty. The sex-matched controls were randomly selected and enrolled from patients who were diagnosed over the age of fifty. All the patients and their family were interviewed regarding the history of gastric or other types of cancer over three generations, and the blood groups of affected members were ascertained. Family histories of cancer were accepted as valid provided that they were based on valid medical documents. The transfusion records of the operation were also used to identify the patients' blood groups. Statistical analysis was performed using the SPSS Statistical Package (version 10.0). The quantitative variables were expressed as means (minimum-maximum) when appropriate. A chi-square test was performed to ascertain the overall effect of blood group on the development of gastric cancer before the age of 50. All statistical tests were two-sided and differences at the 0.01 level were considered statistically significant. Results At the beginning of the study, 44 cases (mean age: 36.2, 18–49; m/f = 1) under 50 years old and 44 sex-matched controls (mean age: 67.1, 50–88) were enrolled. Table 1 shows the pathological characteristics of all 88 subjects. At the time of the study, 59.1% of the case group and 50% of the control group were alive; 53.8% of the case group and 38.6% were living in Tehran, but no information on residence background was available. Data regarding first-degree relatives were complete for both groups. These data comprised information on 383 persons in the case group (average 9.1 for each proband) and 498 in the control group (average 11.6 for each proband). Table 2 shows the distribution of blood groups in the two subject groups. Gastric (22 cases) and other types of cancer were reported in 54.5% of the first-degree relatives of the cases and 11.4% of the first-degree relatives of the controls (p < 0.01). The "other types of cancer" among relatives of the case group comprised colorectal (7 cases), breast (3 cases), lung (3 cases), gynecological (2 cases), hematological (1 case) and bladder (1 case) malignancies. For the control group, the corresponding figures were colorectal (2 cases), breast (1 case), lung (1 case) and prostate (1 case) malignancies. Figures 1 , 2 , 3 show three pedigrees of familial connections. Table 1 The pathologic characteristics of the tumor in the case and control group (n = 44 in each group). Pathologic differentiation Pathologic Type Location of the tumor Case group Well differentiated 1.4% Diffuse 0.5% Cardia 13.6% Moderately differentiated 5.0% Body 18.2% Poorly differentiated 1.4% Intestinal 7.3% Distal 68.2% Control group Well differentiated 7.3% Diffuse 5% Cardia 22.7% Moderately differentiated 5.0% Body 29.5% Poorly differentiated 7.7% Intestinal 5% Distal 47.7% P value NS NS NS Table 2 Frequency of the different blood groups in the study population ( n = 44 ). The figures in parentheses are the number of the patients . Blood group O A B AB Cases (30) 68.1% (6) 13.6% (6) 13.6% (2) 4.5% Controls (11) 27.3% (28) 63.6% (3) 6.8% (2) 4.5% P value <0.05 <0.01 NS NS Figure 1 A family with aggregation with gastric cancer (GC: Gastric Cancer; Ca: History of gastric cancer but not confirmed by a pathologic reports for the histologic type of cancer). Figure 2 A family with a history of the aggregation with Colorectal cancer (GC: Gastric Cancer; CRC: Colorectal Cancer; PLP: Colorectal Polyps; Numbers in circles: Current age of the persons; CAG: Chronic Active Gastritis). Figure 3 A family with a history of the aggregation with other cancers as well as gastric cancer (GC: Gastric Cancer; Lung: Lung Cancer; Blad: Bladder Carcinoma). Discussion This case control study demonstrates that hereditary factors, especially familial history of cancer and possession of blood group O, are associated with the development of gastric cancer under the age of fifty. To our knowledge, this may be the first study showing a correlation between blood group O and the development of gastric cancer in a specific category of patients. Risk factors for gastric cancers have been explored in a number of previous studies, including genetic factors such as blood group. Haenszel et al. suggested an association between gastric cancer and blood type A, supporting the view that genetic factors have a role in the development of gastric cancer [ 21 ]. Our study emphasizes the role of genetic factors in one subcategory of patients, those who develop gastric cancer under the age of fifty. Blood group A is more strongly associated with the diffuse histopathological type of gastric cancer than the intestinal type [ 21 , 22 ]. In our study, most of the patients had a diffuse rather than intestinal type, so we could not test this association. A larger sample size would be needed. On the other hand, there might be a higher prevalence of Helicobacter pylori in our community, causing a higher incidence of the diffuse type of gastric cancer. However, there were no significant differences in histological type of gastric cancer between the case and control groups. In a study by Su et al. in 2001, a total of 6685 patients with esophageal carcinoma and 2955 patients with cardiac cancer in the Chaoshan district were retrospectively assessed for their association with ABO blood groups. Su et al. showed that the distribution of ABO blood groups in patients with esophageal carcinoma or cardiac cancer was similar to that in the normal local population, but there was an association between blood group B and the development of cancer of cardia in males [ 23 ]. In our study, approximately 54% of the case group had a familial history of cancer compared to 11% of the control group. This seems compatible with the findings of a population-based case-control study of stomach cancer in Warsaw, Poland. Here, the investigators interviewed 464 cases and 480 controls to evaluate the role of family history and other risk factors. A greater than threefold increase in risk was associated with a history of gastric cancer in a first degree relative (OR = 3.5), but no excess risk was seen for other forms of cancer. The risk associated with familial occurrence was not significantly modified by gender, age or ABO blood type, and did not vary with Lauren histological classification24. Despite the relatively large sample size in the Polish study, younger patients were not evaluated as a separate category. This may explain the difference between their results and ours. Furthermore, they defined "positive family history" as having a first-degree relative with gastric cancer. In contrast, we considered all types of malignancy in first and second-degree relatives; though the familial incidence of other (non-GI) malignancies in our study may reflect their higher frequency in the community rather than any genetic risk factor. The Polish study did not confirm previous results on the correlation between blood group A and gastric cancer. Moreover, another study by Parsonnet et al on 90 cases and 89 controls showed no association between ABO blood group and malignancy [ 25 ]. In a multicentric study in Italy, 1016 patients with gastric cancer and 1623 population controls were interviewed to determine family histories of gastric, esophageal and colorectal cancer. A significant association was found with history of gastric cancer in a sibling or parent (odds ratios 2.6 and 1.7, respectively). Among the adult siblings of controls and cases, the prevalences of gastric cancer reported at interview were 1 and 2.7%, respectively. A further increase was noted in families with at least one affected parent (1.4 and 5.7%). The risk of gastric cancer associated with a positive family history was greater (increased about 2-fold) among residents of low-risk areas. Among the cases, there was no relationship between family history of gastric cancer and blood group A or histological type according to the Lauren classification [ 26 ]. In our study, there was no significant relationship between the histological type of the cancer and positive family history or blood group. However, this does not prove that the two variables do not correlate; an association might become apparent with a larger study. Mecklin et al studied the clinical and histopathological characteristics of gastric carcinoma in young patients (under 40 years old) in Finland in 1988. In 94% of the young patients, the carcinoma was of the diffuse type. They showed a poor prognosis, an equal sex ratio, and a strong association with blood group A in their study group. They also found a highly significant over-representation of gastric cancer in the parents of the index cases (p < 0.001) [ 27 ]. The difference between Mecklin's study and ours in the blood groups identified as risk factors may reflect ethnic differences; both studies confirm a significant correlation between a specific blood group and the development of gastric cancer. Future studies may use linkage analysis to detect genetic abnormalities in chromosomal regions that are located near the genes encoding the ABO antigens. Matching the geographical origins of the cases and controls could have improved the power of our study by excluding ethnic factors from the study population. However, this is very difficult to achieve in such studies because there is a high rate of combinations between races in the country. In addition, the sample size was too small for such effects to be excluded. However, there were no significance differences between the two groups in respect of the origins of the subjects. In conclusion, our results show that familial history of cancer, and hereditary factors including blood group, have a role in the development of gastric cancer in young patients. The role of environmental factors may be more important in older patients and can be considered in future studies. Competing interests The authors declare that they have no competing interest. Authors' contributions MY designed and assisted in the conduction of the study, analyzing of the data and draft the manuscript. NR, FS, RB and YJ assisted in the conducting and designing the study and interview with the study cases as well as drafting manuscript. AM and MA assisted in analyzing of the study and conducting interviews. AA and MH reviewed and approved the pathology reports of the patients and case collecting. RM supervised the study scientifically and executively and assisted in drafting the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529446.xml
515368	Genetic Analysis of Pathways Regulated by the von Hippel-Lindau Tumor Suppressor in Caenorhabditis elegans	The von Hippel-Lindau (VHL) tumor suppressor functions as a ubiquitin ligase that mediates proteolytic inactivation of hydroxylated α subunits of hypoxia-inducible factor (HIF). Although studies of VHL-defective renal carcinoma cells suggest the existence of other VHL tumor suppressor pathways, dysregulation of the HIF transcriptional cascade has extensive effects that make it difficult to distinguish whether, and to what extent, observed abnormalities in these cells represent effects on pathways that are distinct from HIF. Here, we report on a genetic analysis of HIF-dependent and -independent effects of VHL inactivation by studying gene expression patterns in Caenorhabditis elegans. We show tight conservation of the HIF-1/VHL-1/EGL-9 hydroxylase pathway. However, persisting differential gene expression in hif-1 versus hif-1; vhl-1 double mutant worms clearly distinguished HIF-1–independent effects of VHL-1 inactivation. Genomic clustering, predicted functional similarities, and a common pattern of dysregulation in both vhl-1 worms and a set of mutants (dpy-18, let-268, gon-1, mig-17, and unc-6), with different defects in extracellular matrix formation, suggest that dysregulation of these genes reflects a discrete HIF-1–independent function of VHL-1 that is connected with extracellular matrix function.	Introduction The von Hippel-Lindau (VHL) gene is a tumor suppressor that is mutated in the majority of both hereditary and sporadic, clear-cell renal carcinomas ( Kaelin 2002 ). In hereditary VHL disease affected individuals are also predisposed to pheochromocytomas and retinal/central nervous system hemangioblastomas and develop multiple benign lesions in the kidney and other organs. Despite more than a decade of intensive investigation following identification of the defective gene in 1993 ( Latif et al. 1993 ), the nature of the VHL tumor suppressor mechanism and how it relates to the physiological function of VHL remains unclear ( Kaelin 2002 ). To date, the best-understood function of VHL is as a ubiquitin ligase that affects oxygen-dependent proteolytic targeting of the α subunits of hypoxia-inducible factor (HIF) ( Maxwell et al. 1999 ; Ohh et al. 2000 ). Oxygen-dependent hydroxylation of two HIF-α prolyl residues by HIF prolyl hydroxylases ( Epstein et al. 2001 ; Ivan et al. 2001 ; Jaakkola et al. 2001 ) promotes interaction with VHL and targets HIF-α for degradation by the ubiquitin-proteasome pathway. In VHL-defective cells HIF-α subunits are stabilized and HIF is constitutively activated, resulting in the upregulation of HIF target genes ( Maxwell et al. 1999 ). Whether this, or other putative VHL pathways, accounts for the tumor suppressor action is the subject of active investigation ( Kondo et al. 2002 , 2003 ; Maranchie et al. 2002 ). For instance, a number of different VHL-dependent cellular phenotypes have been defined by contrasting VHL-defective cells with transfectants re-expressing wild-type VHL ( Kaelin 2002 ). These have highlighted effects of VHL on invasiveness, branching morphogenesis, and matrix assembly ( Ohh et al. 1998 ; Koochekpour et al. 1999 ; Davidowitz et al. 2001 ; Kamada et al. 2001 ; Esteban-Barragan et al. 2002 ). However, mechanistic links to VHL function have not yet been defined and it is unclear whether or not these effects are secondary to dysregulation of HIF. This has led to attempts to define the existence, or otherwise, of non-HIF, VHL-regulated pathways by comparing patterns of gene expression induced by VHL inactivation with those induced by hypoxia ( Wykoff et al. 2000 ; Zatyka et al. 2002 ; Y. Jiang et al. 2003 ). The observed patterns are not fully concordant, suggesting that there may be non-HIF, VHL-regulated pathways. However, these studies leave important uncertainties since HIF dysregulation might have secondary effects on pathways that are not themselves responsive to hypoxia and VHL might target hypoxia pathways other than HIF. To address this we have used a genetic approach in Caenorhabditis elegans. Whereas mammalian cells possess three HIF-α isoforms that are targeted by VHL, C. elegans has a single HIF-α homolog (HIF-1) and a single VHL homolog (VHL-1), simplifying the genetic approach ( Epstein et al. 2001 ; H. Jiang et al. 2001 ). Since homozygous vhl-1 and hif-1 loss-of-function worms are viable, we created hif-1; vhl-1 worms and compared the effects of vhl-1 inactivation on gene expression in wild-type and HIF-1–defective backgrounds. Our results clearly demonstrate the existence of both HIF-dependent and HIF-independent pathways of VHL-dependent gene expression. HIF-1–dependent effects of vhl-1 inactivation on gene expression were also produced by inactivation of the HIF prolyl hydroxylase homolog EGL-9. In contrast, the HIF-1–independent effects of vhl-1 inactivation were not observed in egl-9 loss-of-function worms but were seen in a panel of mutant worms (dpy-18, let-268, gon-1, mig-17, and unc-6) bearing defects in genes involved in extracellular matrix function, supporting the existence of a conserved non-HIF pathway connecting VHL with an as yet unknown extracellular matrix function. Results Effect of VHL-1 Inactivation on Gene Expression in C. elegans As a first step in defining VHL-1–dependent pathways in C. elegans, a whole-genome microarray was probed to compare transcript patterns in vhl-1 versus wild-type worms ( n = 1). From this array a set of genes (selected for amplitude of differential expression, signal intensity, quality of array signal, and putative function) was assayed quantitatively by ribonuclease (RNase) protection ( Table 1 ). Of the 14 genes analyzed, six (F22B5.4, unknown function; nhr-57, predicted nuclear hormone receptor; fmo-12, predicted flavin monooxygenase; egl-9, HIF-1 prolyl hydroxylase [ Epstein et al. 2001 ]; phy-2, procollagen prolyl 4-hydroxylase α subunit [ Friedman et al. 2000 ]; and cah-4, predicted carbonic anhydrase) were strikingly downregulated by VHL-1 ( Figure 1 A; Table 2 , column B). Further analysis in synchronized worm populations indicated that the VHL-1–dependent effects were observed in all stages ( Figure 1 B and unpublished data). Figure 1 HIF-1–Dependent Effects of VHL-1 Inactivation Representative RNase protection assays of genes that were differentially expressed in the vhl-1 versus wild-type microarray in (A) mixed-stage and (B) synchronized populations of worm. All genes are regulated by the VHL-1/HIF-1/EGL-9 pathway. (C) Regulation of nhr-57 mRNA in egl-9; vhl-1 worms and by egl-9 RNAi and DIP in vhl-1 worms. For RNAi experiments controls were L4440 vector alone (−) and C17G10.1, an irrelevant putative dioxygenase. F21C3.5 is a constitutively expressed gene used to control for RNA integrity. RNase protection assays were performed using worms cultured under normoxic conditions, unless otherwise indicated. Table 1 Top 30 Upregulated Genes in the vhl-1 versus Wild-Type Microarray Comparison and Confirmation of Selected Genes by RNase Protection Assays Confirmation of selected genes: Y, reproducible upregulation of gene in vhl-1 /wild-type worms as confirmed by RNase protection assays; N, no reproducible upregulation of gene as tested by RNase protection assays; —, not determined. Gene name refers to the three-letter gene name where available and open reading frame name (WormBase); details of name changes and primers in arrays are from http://worm-chip.stanford.edu/pcr.all_primers.plus_gels.4–10-02.txt . Description is the predicted protein, annotated by Proteome/Incyte; —, protein of unknown function. Microarrays and RNase protection assays were performed using worms cultured under normoxic conditions Table 2 Differential Expression of VHL-1–Regulated Genes in Mutants Affecting the HIF-1/VHL-1/EGL-9 Pathway Column A, data from the microarray comparison of vhl-1 versus wild-type worms. Columns B to I, data from RNase protection assays. The figures represent the (fold) differences in expression averaged for the indicated number (n) of independent comparisons. Statistical analysis of differential expression was performed where n ≥ 3; , p < 0.05. Statistical analysis was performed for differences between vhl-1 versus wild-type (column B) and egl-9 versus wild-type (column C); †, p < 0.05. N, normoxia; H, hypoxia (0.1% oxygen) Analysis of the EGL-9/HIF-1 Pathway To determine the extent to which disruption of the conserved EGL-9/HIF-1 pathway mediates these effects we studied wild-type, hif-1, vhl-1, and egl-9 single mutant worms and hif-1; vhl-1 and egl-9; hif-1 double mutant worms. Apart from the mild phenotype of the vhl-1 worms (slightly uncoordinated, slow growth, and reduced brood size) and the egg-laying defective phenotype of egl-9, none of the worm strains showed obvious phenotypic abnormalities. Interestingly, hif-1 corrected the phenotype of egl-9. The findings indicate that all six genes are strongly regulated by the EGL-9/HIF-1 pathway ( Figure 1 A; Table 2 ). All six genes were inducible by hypoxia in wild-type worms ( Table 2 , column D) and strikingly upregulated in egl-9 worms ( Table 2 , column C). hif-1 inactivation abrogated the upregulation by the egl-9 mutation ( Table 2 , columns C and F) and strikingly reduced induction by hypoxia ( Table 2 , columns D and G). Computational analysis revealed that five (F22B5.4, nhr-57, fmo-12, egl-9, and cah-4 ) of the six genes contained a potential HIF-1 binding core motif (RCGTG) within an arbitrarily defined region (−1,000 to +250 nucleotides) that was conserved in Caenorhabditis briggsae ( Table 3 ), suggesting that these genes are direct HIF-1 transcriptional targets. Table 3 Evolutionarily Conserved HBS Consensus Sequences The sequence column shows alignments between C. elegans and C. briggsae that conserve a match (bold type) to the mammalian HBS consensus motif, RCGTG, where R = A or G. Matches were found on both the sense and antisense strands; matches that are perfect palindromes (CACGTG) can be considered equally good matches to both the sense and antisense strand. The antisense matches are oriented to demonstrate alignment with the consensus motif. The positions of the aligned sequences are shown relative to the translation initiation site. The gene cah-4 has two alternate first exons (denoted “a” and “b” in WormBase); both were evaluated. In addition to the genes shown, C01B4.7, F56A4.10, C01B4.9, and C01B4.6 were screened for conserved RCGTG motifs, but none was found Though the six genes all conformed to the above patterns to demonstrate regulation by the EGL-9/HIF-1 pathway ( Figure 1 A; Table 2 ), there were differences. First, for some genes (F22B5.4, nhr-57, and fmo-12 ) expression in normoxia was entirely dependent on HIF-1, whereas other genes retained substantial normoxic expression in hif-1 worms ( Figure 1 A). Second, three genes (nhr-57, egl-9, and cah-4) showed modest upregulation, and one gene (phy-2) showed modest downregulation, by hypoxia that was independent of HIF-1, VHL-1, and EGL-9 ( Table 2 , columns G–I). Finally, for certain genes, upregulation was clearly greater in egl-9 than vhl-1 worms, results being particularly striking for nhr-57 ( Table 2 , columns C and B). To pursue this, we created egl-9; vhl-1 double mutants and also exposed vhl-1 worms to egl-9 RNAi. Both procedures increased nhr-57 expression, indicating that EGL-9 has non–VHL-1–mediated effects on this pathway ( Figure 1 C). Interestingly, the effects of genetic inactivation of egl-9 in the vhl-1 background were not mimicked by the dioxygenase inhibitor 2,2′-dipyridyl (DIP), suggesting that the VHL-1–independent repressive effects on nhr-57 may be nonenzymatic. Evidence for a VHL-1–Dependent, HIF-1–Independent Pathway To address directly whether HIF-1–independent, VHL-1–mediated pathways exist, we performed further microarray comparisons of RNA from hif-1; vhl-1 and hif-1 worms ( n = 3). Fewer genes showed differential expression than in the vhl-1 versus wild-type array; however, persisting differential expression did suggest the existence of VHL-1 pathways that are independent of HIF-1 ( Table 4 ). To test this, a number of genes were selected for further validation by RNase protection assay on the basis of amplitude of differential expression, p value, signal intensity, and quality of array signal. Of the 25 genes analyzed by RNase protection assay ( Table 4 ), six (C01B4.7, F56A4.10, C01B4.9, and C01B4.8, all predicted transmembrane proteins belonging to the major facilitator superfamily [InterPro: IPR007114 and IPR005828]; F56A4.2, a predicted C-type lectin [InterPro: IPR001304]; and C01B4.6, a predicted aldose epimerase [InterPro: IPR008183]) showed clear downregulation by VHL-1 in a HIF-1–independent manner ( Figure 2 A; Table 5 , column C). These effects were observed across essentially all developmental stages of the worm ( Figure 2 B). Computational analysis revealed that only one (C01B4.8) of the five HIF-1–independent, VHL-1–dependent genes tested (C01B4.7, F56A4.10, C01B4.9, C01B4.8, and C01B4.6; no single ortholog of F56A4.2 could be identified in C. briggsae ) contained a potential HIF-1 binding site (HBS) within an arbitrarily defined region that was conserved in C. briggsae (see Table 3 ). This contrasts with the HIF-1–dependent, VHL-1–dependent genes validated by RNase protection assay (see Figure 1 A), for which potential HBSs could be defined for five of the six genes tested (see Table 3 ). Figure 2 HIF-1–Independent Effects of VHL-1 Inactivation RNase protection assays of genes that were differentially expressed in the hif-1; vhl-1 versus hif-1 microarrays in (A) mixed-stage and (B) synchronized populations of worm. The results confirm the existence of VHL-1–dependent, HIF-1–independent effects on gene expression. Table 4 Upregulated Genes in the hif-1; vhl-1 versus hif-1 Microarray Comparisons and Confirmation of Selected Genes by RNase Protection Assays Confirmation of selected genes: Y, reproducible upregulation of gene in hif-1; vhl-1 / hif-1 worms as confirmed by RNase protection assays; N, no reproducible upregulation of gene as tested by RNase protection assays; asterisk, not assayed, riboprobe could not be constructed; NS, no signal by RNase protection assay; —, not determined. Microarrays and RNase protection assays were performed using worms cultured under normoxic conditions. C35B8.1, C46A5.3, R03D7.5, T11F9.8, and ZK1010.7 were also tested by RNase protection assay based on microarray data; these genes did not show reproducible upregulation by RNase protection assays Table 5 Differential Expression of HIF-1–Independent, VHL-1–Regulated Genes in Mutants Affecting the HIF-1/VHL-1/EGL-9 Pathway and Procollagen Hydroxylases Columns A and B, data from microarray comparisons; columns C to K, data from RNase protection assays. The figures represent the (fold) differences in expression averaged for the indicated number (n) of independent comparisons. Statistical analysis of differential expression was performed where n ≥ 3; , p < 0.05. N, normoxia; H, hypoxia (0.1% oxygen) Interestingly, all six genes validated by RNase protection assay to be negatively regulated by VHL-1 in a HIF-1–independent manner localize within 45 kb on Chromosome V (although they were not situated in physical proximity on the array). We applied single-linkage clustering (nearest-neighbor method) ( Sneath 1957 ; Dillon and Goldstein 1984 ; Roy et al. 2002 ) to identify spatial clusters of genes considered to be negatively regulated by VHL-1 in a HIF-1–independent manner from the microarray data ( Table 4 ) and random sampling to evaluate the significance of such clusters. Using a clustering threshold of 96,985 bp (see Materials and Methods ), one cluster of ten genes and four clusters of two genes were identified ( Figure 3 A). On 100,000 simulated datasets of 57 randomly selected genes (equal number to that of VHL-1–dependent, HIF-1–independent genes; Table 4 ), the frequency of observed cluster sizes was as follows: one gene, 5,043,442; two genes, 298,425; three genes, 18,198; four genes, 1,190; five genes, 66; six genes, 4. No clusters of more than six genes were observed. Therefore, the cluster of ten VHL-1–regulated (HIF-1–independent) genes, which extends over 110 kb to include F56A4.9, Y45G12C.9, Y45G12C.12, and Y45G12C.2 in addition to the six genes validated by RNase protection assays, can be considered statistically significant to p ≪ 10 −5 ( Figure 3 B). Recent C. elegans genomic assemblies (for example, WS120) have shown that the entire 110-kb region containing the coregulated gene cluster is arranged in tandem with a second nearly identical segmental duplication of the locus (>99.9% identical in alignment). At this level of identity, our microarray and RNase protection analyses cannot discriminate between the two copies of each gene, so for all of our analyses we have only used the names of the distal copy and genes from the proximal copy were excluded from computational analyses. Figure 3 Chromosomal Clustering of VHL-1–Dependent (HIF-1–Independent) Genes (A) Chromosomal localization of VHL-1–dependent, HIF-1–independent genes. The positions of the genes from Table 4 are indicated by vertical ticks along the C. elegans chromosomes (shown to scale). Where two such genes are too close to be clearly resolved, the tick is marked by an asterisk. The single significant spatial clustering of VHL-1–dependent, HIF-1–independent genes is indicated by a red rectangle. The histogram under each chromosome shows the gene density (deeper bar, greater density) calculated as a sliding window of 100,000 bp moving with 10,000-bp increments along each chromosome. Dark blue indicates total annotated gene density, and light blue indicates the density of genes from the microarray that passed preliminary quality control. (B) Organization of the VHL-1–regulated (HIF-1–independent) gene cluster from Chromosome V. The relative positions and sizes of gene transcription units are shown to scale, with genes transcribed left to right above the horizontal line and right to left below the line. Names in black indicate genes that passed all selection criteria to be considered upregulated in hif-1; vhl-1 versus hif-1 worms (see Table 4 ). Genes with a mean >2.0-fold upregulation are indicated by green boxes, 1.5- to 2-fold are yellow, and <1.5-fold are red. Genes for which no data were obtained are shown as light grey. Table 6 C. elegans Strains and Alleles a Note that eDf18 carries a weak gon-1 mutation that renders the CB4504 strain temperature sensitive for the Gon phenotype Extracellular Matrix Link to Novel VHL-1 Pathway Since ubiquitin ligases commonly recognize more than one substrate, we considered whether these HIF-1–independent genes might be regulated by prolyl hydroxylation of another VHL-1 substrate by EGL-9. However, this was not supported by any differential expression in egl-9; hif-1 versus hif-1 worms ( Figure 4 A; Table 5 , column E). Nevertheless, two genes, C01B4.7 and C01B4.8, were upregulated in hif-1 worms by hypoxia and the 2-oxoglutarate dioxygenase inhibitors, DIP and dimethyloxalylglycine (DMOG) ( Figure 4 ; Table 5 , column F), suggesting that another enzyme in this class might be involved. The procollagen prolyl hydroxylases DPY-18, PHY-2, and PHY-3 ( Friedman et al. 2000 ; Riihimaa et al. 2002 ) and the procollagen lysyl hydroxylase LET-268 ( Norman and Moerman 2000 ) were tested as potential candidates. A clear pattern was observed. All six VHL-1–regulated, HIF-1–independent genes were reproducibly downregulated by DPY-18 and LET-268 but not by PHY-2 or PHY-3 ( Figure 5 A; Table 5 , columns H–K). The strain carrying the heterozygous let-268 mutation is heterozygous for unc-4, dpy-10, and unc-52; however, the VHL-1–dependent, HIF-1–independent genes were not differentially expressed in unc-4, dpy-10, or unc-52 worms, indicating that the effects were due to LET-268 (unpublished data). Further experiments on dpy-18; hif-1 double mutant worms clearly indicated that the effects of DPY-18 on this group of genes were (like the effects of VHL-1) HIF-1 independent ( Figure 5 C and unpublished data). Figure 4 Responses of VHL-1–Dependent, HIF-1–Independent Genes to egl-9 Inactivation, Hypoxia, and 2-Oxoglutarate Dioxygenase Inhibitors RNase protection assays showing regulation of VHL-1–dependent, HIF-1–independent genes by (A) EGL-9 and hypoxia and (B) pharmacological inhibitors of 2-oxoglutarate dioxygenases: DIP and DMOG. None of the genes is regulated by EGL-9, but two genes (C01B4.7 and C01B4.8) show modest induction by hypoxia, DIP, and DMOG. Figure 5 Sensitivity of VHL-1–Regulated Genes to Defects in Extracellular Matrix-Associated Proteins RNase protection assays showing altered expression of VHL-1–regulated genes that are HIF-1 independent (upper six panels) and HIF-1 dependent (F22B5.4) in worms bearing mutations affecting (A) procollagen prolyl and lysyl hydroxylases and (B) other extracellular matrix-associated proteins. A common pattern of upregulation is observed in hif-1; vhl-1, vhl-1, dpy-18, let-268, gon-1, mig-17, and unc-6 worms but not other mutants. This contrasts with the HIF-1–dependent gene F22B5.4, which is upregulated in vhl-1 worms but none of the other mutants. (C) RNase protection assay for C01B4.9 illustrating DPY-18–mediated changes in expression that are independent of HIF-1. Downregulation by DPY-18 and LET-268 is consistent with the positive effects of hypoxia, DIP, and DMOG, since all these stimuli inhibit DPY-18 and LET-268. However, the involvement of a lysyl, as well as a prolyl, hydroxylase suggests that the effects were unlikely to arise from failure of hydroxylation of a second prolyl hydroxylation substrate recognized by VHL-1 and were more likely to be related to a common function of DPY-18 and LET-268, such as a function in extracellular matrix formation. To pursue this, we tested the effects of defects in proteins involved in other aspects of extracellular matrix formation (either in the cuticle or basement membrane) that are distinct from protein hydroxylation. These experiments indicated that the six genes were, to varying extents, upregulated in the basement membrane-associated gon-1 (heterozygote), mig-17, and unc-6 mutant worms but not in the cuticle-associated dpy-11, bli-4, or sqt-3 mutant worms ( Figure 5 B and unpublished data). In contrast, none of the HIF-1–dependent genes was upregulated in these mutants ( Figure 5 B and unpublished data). GON-1 and MIG-17 encode secreted metalloproteases and UNC-6 encodes a netrin; all are thought to be involved in basement membrane remodeling/cell migration during gonadal morphogenesis ( Hedgecock et al. 1990 ; Blelloch and Kimble 1999 ; Nishiwaki et al. 2000 ). Conversely, DPY-11 (a thioredoxin) and BLI-4 (a serine endoprotease) are both involved in collagen formation in the worm cuticle ( Thein et al. 2003 ) and SQT-3 encodes a cuticular collagen. These results therefore extend the characterization of the VHL-1–dependent, HIF-1–independent pathway and support a connection with extracellular matrix/basement membrane function. Discussion By comparing the effects of vhl-1 inactivation in different genetic backgrounds, these data clearly distinguish HIF-1–dependent and –independent effects of VHL-1 on gene expression. Somewhat surprisingly, all of the VHL-regulated genes analyzed fell into one of two patterns: independent of HIF-1 and EGL-9 and dependent on DPY-18, LET-268, GON-1, MIG-17, and UNC-6, or the reverse, suggesting that they reflect perturbation of two discrete aspects of VHL-1 function. The HIF-1–dependent expression pattern of all six genes chosen for detailed analysis from the vhl-1 versus wild-type array underlines the importance of the HIF-1 pathway in VHL-1 function. Computational analysis revealed that five of these genes (F22B5.4, nhr-57, fmo-12, egl-9, and cah-4 ) have at least one HIF-1 binding core motif (RCGTG) that is conserved in C. briggsae within an arbitrarily defined (−1,000 to +250 nucleotides) promoter region, suggesting that they are direct HIF-1 transcriptional targets. Several genes ( egl-9, HIF prolyl hydroxylase; phy-2, procollagen prolyl 4-hydroxylase α subunit; and cah-4, carbonic anhydrase) have mammalian homologs that are HIF targets ( Ivanov et al. 1998 ; Takahashi et al. 2000 ; Epstein et al. 2001 ), emphasizing the extent of conservation of the pathway. Others, such as flavin monooxygenase fmo-12 and the nuclear hormone receptor nhr-57, are apparently novel HIF-1 target genes. Interestingly, some of these HIF-1–dependent genes were partly downregulated by EGL-9 in a VHL-1– and iron-independent manner, suggesting that, in addition to the HIF-1/VHL-1 pathway, EGL-9 regulates HIF-1 transcriptional activity via a novel pathway. Remarkably, among the candidate genes tested from the hif-1; vhl-1 versus hif-1 screens, all six that showed reproducible (HIF-1–independent) regulation by VHL-1 were located within 45 kb on Chromosome V. Analysis of the microarray data revealed that there was indeed a single, highly significant ( p < 10 −5 ) chromosomal cluster of genes negatively regulated by VHL-1 in a HIF-1–independent manner and that in total this cluster extended over 110 kb to include F56A4.9, Y45G12C.9, Y45G12C.12, and Y45G12C.2 in addition to the six genes validated by RNase protection assay. The chromosomal localization of genes in C. elegans is not random, with functionally related genes located close to one another ( Roy et al. 2002 ) or even organized into operons ( Blumenthal and Gleason 2003 ). Even though, based on the absence of spliced leader SL2 sequences ( Blumenthal et al. 2002 ) and the presence of inverse transcriptional orientations, the genes in this cluster do not appear to be within the same operon, there may be a functional relevance to their physical proximity. Four of the six genes validated by RNase protection assay (C01B4.7, F56A4.10, C01B4.9, and C01B4.8) encode membrane transporters of the major facilitator superfamily, a family of transporters involved in passive transport of small solutes. C01B4.9 clusters phylogenetically with monocarboxylate transporters, and C01B4.7, F56A4.10, and C01B4.8 cluster with sodium phosphate transporters (unpublished data). Both gene families have been subject to rounds of gene duplication in the vertebrate and nematode lineages. As such, it is not possible to define one-to-one orthologous relationships for these genes between C. elegans and Homo sapiens. Nevertheless, the genomic clustering, predicted functional similarities, and common pattern of perturbed expression across an extensive set of mutant worms suggest that the upregulation of the genes in vhl-1 worms reflects the disturbance of a specific function of VHL-1. The common effects of inactivating mutations in vhl-1 and in genes that manifest functional overlap in extracellular matrix formation— dpy-18 and let-268 (encoding procollagen hydroxylases) ( Friedman et al. 2000 ; Norman and Moerman 2000 ), gon-1 and mig-17 (encoding secreted metalloproteases) ( Blelloch and Kimble 1999 ; Nishiwaki et al. 2000 ), and unc-6 (encoding the extracellular guidance protein, netrin) ( Hedgecock et al. 1990 )—suggest a related function for this HIF-1–independent VHL pathway. Interestingly, VHL-defective renal carcinoma cells demonstrate a variety of matrix-related abnormalities, including abnormal fibronectin assembly, defective formation of fibrillar adhesions, and changes in branching morphogenesis and migration ( Ohh et al. 1998 ; Koochekpour et al. 1999 ; Davidowitz et al. 2001 ; Kamada et al. 2001 ; Esteban-Barragan et al. 2002 ). These abnormalities can be corrected by transfection of renal carcinoma cells with wild-type vhl, indicating that they are attributable, either directly or indirectly, to VHL loss of function. Furthermore, immunoprecipitation studies using renal carcinoma cell extracts have indicated that VHL binds to fibronectin ( Ohh et al. 1998 ). Most tumor-associated VHL mutants, when transfected into VHL-defective renal carcinoma cells, are defective in both complementing HIF dysregulation and fibronectin binding ( Kaelin 2002 ). However, mutations associated with type 2C (predisposition to pheochromocytoma only) VHL disease complement defective HIF regulation but bind fibronectin with lower affinity than wild-type VHL ( Hoffman et al. 2001 ). Though the precise link to abnormal matrix assembly remains unclear, this has suggested a HIF-independent function of VHL. The present study supports the existence of a HIF-independent pathway connected with extracellular matrix function and suggests that this may be a highly conserved function of VHL that is potentially amenable to genetic analysis in model organisms. Materials and Methods Strains and culturing conditions. Worms were studied as mixed-stage populations or as synchronized populations following brief exposure to sodium hypochlorite. Exposure to hypoxia (2% or 0.1% oxygen), DIP (200 μM), and DMOG (1 mM) was for 18 h ( Epstein et al. 2001 ). RNA interference (RNAi) was performed by feeding worms Escherichia coli strain HT115(DE3) expressing double-stranded (ds) RNA on Nematode Growth Medium containing 1 mM isopropyl-β- D -thiogalactopyranoside (ITPG) and 50 μg/ml ampicillin for 72 h. Plasmids for ds RNA production were derivatives of the L4440 vector and were obtained from J. Ahringer (Cambridge, United Kingdom); ds RNA sequences are available on WormBase ( http://www.wormbase.org ). Wild-type worms were Bristol strain (N2); mutant strains were obtained from the Caenorhabditis Genetics Center ( Table 6 ). Strains were maintained at room temperature except for the temperature-sensitive gon-1 worms (maintained at 18 °C). The double mutants hif-1; vhl-1, egl-9; hif-1, and dpy-18; hif-1 were constructed using either fog-2 or unc-51 to mark hif-1 (+); the double mutant egl-9; vhl-1 was constructed using unc-42 to mark egl-9 (+); PCR was used to confirm homozygosity. Microarray screening. Microarray comparisons of wild-type versus vhl-1 worms and hif-1 versus hif-1; vhl-1 worms were performed on independent samples of RNA ( n = 1 and 3, respectively), using near full-genome C. elegans DNA microarrays ( M. Jiang et al. 2001 ). Total RNA was extracted from mixed-stage populations of worm cultured under normoxic conditions using Tri-reagent (Sigma, Poole, Dorset, United Kingdom) and mRNA purified using oligo-dT beads (Qiagen, Crawley, West Sussex, United Kingdom). cDNA synthesis and microarray hybridization and scanning were performed as described previously ( M. Jiang et al. 2001 ). Cy5-dUTP was used to label cDNA from wild-type and hif-1 worms and Cy3-dUTP was used to label cDNA from vhl-1 and hif-1; vhl-1 worms. The arrays were computer normalized by the default procedure in the Stanford Microarray Database (SMD); primary array data are available on the SMD ( http://genome-www.stanford.edu/microarray ) and are also shown in Tables S1 through S4 . Fold change was calculated as the ratio of the means of Cy3-dUTP intensity to normalized Cy5-dUTP intensity (normalized to correct for signal differences between Cy3-dUTP and Cy5-dUTP intensities across the whole array) with median background intensities subtracted from both signal intensities to correct for the background (see SMD). Genes with background-corrected signal intensities below zero or with array spots that were flagged in the SMD as being unreliable were discarded as a preliminary quality control. For the hif-1 versus hif-1; vhl-1 microarray comparisons ( n = 3) the log 2 fold change was calculated as the mean of the three log 2 transformed fold changes. To test for significant upregulation, the mean log 2 fold change was compared with zero using a Student's t test. The genes were ranked by amplitude of fold upregulation and a subset of genes was selected for potential validation by RNase protection assays (see Tables 1 and 4 ) based on the following criteria: (a) t test, p < 0.10 (for the hif-1 versus hif-1; vhl-1 microarray comparisons, n = 3); (b) mean Cy3-dUTP and Cy5-dUTP background-corrected signal intensities exceeding 300 and 100 U, respectively (lower intensities than these were difficult to detect by RNase protection assay); and (c) high spot quality as judged by manual inspection. For the hif-1 versus hif-1; vhl-1 microarray comparisons ( n = 3), genes (which had been filtered as described above) were considered to be differentially expressed if the mean fold change was greater than 2.0 (see Table 4 ). RNase protection assays. Assays were performed on total RNA from mixed-stage populations of worm cultured under normoxic conditions, unless otherwise indicated. Details of riboprobe templates are provided in Table 7 ; details of genes tested are shown in Tables 1 and 4 . Quantification was performed using a phosphorimager (Molecular Dynamics, Sunnyvale, California, United States) and related to an internal control assay for the constitutively expressed F21C3.5 (protein with similarity to mouse prefoldin subunit 6). Where n ≥ 3, the log 2 fold change was calculated from the mean of the log 2 transformed fold changes and statistical significance was calculated by comparing the mean log 2 fold change with zero using a Student's t test. Table 7 Sequence and Length of Riboprobes a Note that the protected region of the egl-9 transcript does not overlap the sa307 deletion in the JT307 egl-9 strain Computational analyses (1) Identification of potential HBSs (see Table 3 ). Orthologs of C. elegans genes were identified in the C. briggsae genome assembly (cb25) as reciprocal best matches by BLASTN, initiated with the C. elegans gene coding sequence (a single ortholog of F56A4.2 could not be defined). Translation initiation sites (well-annotated surrogates for transcriptional start sites; none of these genes are annotated as having spliced 5′ UTRs) were inferred in both C. briggsae and C. elegans through alignment with the C. elegans coding sequence (WormBase, WS117). Sequences encompassing the 1,000 nucleotides upstream to 250 nucleotides downstream of the translation start sites for orthologous genes were aligned using DNA Block Aligner ( Jareborg et al. 1999 ) with the following options: gap = 0.001 and blockopen = 0.005. Sequence alignments were searched with the HBS motif RCGTG ( Camenisch et al. 2001 ), identifying cases where HBS-like motifs were conserved between both C. elegans and C. briggsae. (2) Single-linkage analysis to determine spatial clusters of VHL-1–dependent, HIF-1–independent genes (see Figure 3 ). A maximum distance for the linking of two clusters was determined by ranking the distance between 10,000 randomly selected pairs of genes from the same chromosome (but sampled over all six nuclear chromosomes) and selecting as a threshold the first percentile of the distribution, 96,985 bp. Intergene distances were calculated from the closest point between the annotated coding sequence of each gene; genes on separate chromosomes were considered to have an infinite intergene distance. Simulations were performed using genes selected at random from genes that were represented on the microarray and that passed preliminary quality control criteria. All genomic coordinates were based on genomic assembly WS120 and the associated WormBase annotation of genes obtained from the University of California, Santa Cruz Genome Browser ( http://genome.ucsc.edu/ ). The software used for simulations and clustering was implemented in Perl and is available on request. Supporting Information Primary microarray data can be viewed at http://genome-www.stanford.edu/microarray . Table S1 vhl-1 versus Wild-Type Microarray Comparison Primary microarray data for the vhl-1 (green, channel 1) versus wild-type (red, channel 2) comparison. (6.5 MB XLS). Click here for additional data file. Table S2 hif-1; vhl-1 versus hif-1 Microarray Comparisons I Primary microarray data for the three independent hif-1; vhl-1 (green, channel 1) versus hif-1 (red, channel 2) microarray comparisons. Continued in Tables S3 and S4 . (6.6 MB XLS). Click here for additional data file. Table S3 hif-1; vhl-1 versus hif-1 Microarray Comparisons II Continuation of Table S2 . (6.6 MB XLS). Click here for additional data file. Table S4 hif-1; vhl-1 versus hif-1 Microarray Comparisons III Continuation of Tables S2 and S3 . (6.6 MB XLS). Click here for additional data file. Accession Numbers Primary array data have been deposited in ArrayExpress ( http://www.ebi.ac.uk/arrayexpress/ ) under accession number E-SMDB-23. The H. sapiens VHL gene discussed in this paper can be found in Online Mendelian Inheritance in Man (OMIM) under accession number 608537 ( http://www.ncbi.nlm.nih.gov:80/entrez/dispomim.cgi?id=608537 ). The C. elegans genes discussed in this paper ( bli-4, C01B4.6, C01B4.7, C01B4.8, C01B4.9, cah-4, dpy-10, dpy-11, dpy-18, egl-9, F21C3.5, F22B5.4, F56A4.2, F56A4.9, F56A4.10, fmo-12, fog-2, gon-1, hif-1, let-268, mig-17, nhr-57, phy-2, phy-3, sqt-3, unc-4, unc-6, unc-42, unc-51, unc-52, vhl-1, Y45G12C.2, Y45G12C.9, and Y45G12C.12) can be found in the WormBase database by including the name of the gene at the end of the URL (e.g., for bli-4, http://wormbase.org/db/gene/gene?name=bli-4 ). Table 4 Continued	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC515368.xml
423157	Ethereal Ethics	In response to the Blackburn and Rowley essay on the President's Council on Bioethics, several thought-provoking opinions on ethical challenges in biomedical research are expressed by prominent stakeholders	It is a great pity when vested interest and dogma dominate what should be a well-informed and rational debate. The essay by Elizabeth Blackburn and Janet Rowley (2004) , about the output and the workings of the President's Council on Bioethics, therefore prompted in me a strong reaction of sadness and despair, although I have to admit not one of surprise. In the United Kingdom, we have had an almost continuous debate since the mid 1980s on topics relating to research on early human embryos. I myself have been involved in some of this debate, especially over the last few years, relating to human embryonic stem cells and nuclear transfer. I will not dwell on the political outcomes of this debate, which are widely known, but I want to stress that it has been one that has been very well informed, with contributions from all sides, including many highly respected moral philosophers and bioethicists. These include notable individuals such as Dame Mary Warnock and bodies such as the Nuffield Bioethics Council, who have been especially valuable because of their independence. So why are the conclusions reached by bioethicists in the UK, who are generally supportive of research involving human embryos, different from those of the President's Council on Bioethics? The same scientific information is available on both sides of the Atlantic. The rules of logic are the same. So it has to be the way the information is interpreted or filtered. This implies bias or vested interest or the input of dogma that is based on belief rather than rational thought. Some examples of this are discussed in the Blackburn and Rowley essay, and they are very worrying. The scare mongering about preimplantation genetic diagnosis is ridiculous—simple mathematics shows that it is implausible to use this technique to screen the usual number of embryos obtained in one round of in vitro fertilisation for more than two or three genetic traits, while we know that intelligence must rely on many more. I am a great fan of science fiction, but I can recognise it as such. I worry that some members of the President's Council seem unable to do this. Many of these daft ideas were already promoted in a book by Francis Fukuyama (2002) , and while they can be a harmless way of promoting debate, they should not be included in documents meant to inform policy makers. It is certainly very unfortunate if the input of real science in the Council is to be reduced. The scientific issues are complex. For example, we certainly do not know nearly enough about either adult or embryonic stem cells to say which will be the best for therapies, and of course it is possible that both will turn out to be useful for different problems. Both also offer exciting new ways to explore human disease and the influence of genetics and environment without having to rely on human experimentation. But any committee looking into what is ethically acceptable has to be provided with a balanced view of what will be possible in the near future. There is no point in being too speculative, in part because it is also difficult to predict what will be ethically acceptable in the future. If cures come from the use of human embryonic stem cells, then I suspect that there will be widespread acceptance, as happened with heart transplants and with in vitro fertilisation, both of which were initially greeted with horror by many. It is impossible to have an informed debate without accurate and appropriate information, and there seems little point in having a debate that is not informed. Because of various sensitivities, it seemed to me before the creation of the President's Council on Bioethics that for far too long the issues relating to embryo research had not been considered properly within the United States. The President's Council was therefore an opportunity to redress this situation. But from the evidence I fear it will not succeed. Moreover, it does the general public a disservice to pretend to have a serious committee exploring issues of bioethics when that committee fails to live up to the ideals of impartiality and rationality.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC423157.xml
555764	The role of the MAPK pathway alterations in GM-CSF modulated human neutrophil apoptosis with aging	Background Neutrophils represent the first line of defence against aggressions. The programmed death of neutrophils is delayed by pro-inflammatory stimuli to ensure a proper resolution of the inflammation in time and place. The pro-inflammatory stimuli include granulocyte-macrophage colony-stimulating factor (GM-CSF). Recently, we have demonstrated that although neutrophils have an identical spontaneous apoptosis in elderly subjects compared to that in young subjects, the GM-CSF-induced delayed apoptosis is markedly diminished. The present study investigates whether an alteration of the GM-CSF stimulation of MAPKs play a role in the diminished rescue from apoptosis of PMN of elderly subjects. Methods Neutrophils were separated from healthy young and elderly donors satisfying the SENIEUR protocol. Neutrophils were stimulated with GM-CSF and inhibitors of the MAPKinase pathway. Apoptosis commitment, phosphorylation of signaling molecules, caspase-3 activities as well as expression of pro- and anti-apoptotic molecules were performed in this study. Data were analyzed using Student's two-tailed t -test for independent means. Significance was set for p ≤ 0.05 unless stated otherwise. Results In this paper we present evidence that an alteration in the p42/p44 MAPK activation occurs in PMN of elderly subjects under GM-CSF stimulation and this plays a role in the decreased delay of apoptosis of PMN in elderly. We also show that p38 MAPK does not play a role in GM-CSF delayed apoptosis in PMN of any age-groups, while it participates to the spontaneous apoptosis. Our results also show that the alteration of the p42/p44 MAPK activation contributes to the inability of GM-CSF to decrease the caspase-3 activation in PMN of elderly subjects. Moreover, GM-CSF converts the pro-apoptotic phenotype to an anti-apoptotic phenotype by modulating the bcl-2 family members Bax and Bcl-xL in PMN of young subjects, while this does not occur in PMN of elderly. However, this modulation seems MAPK independent. Conclusion Our results show that the alteration of p42/p44 MAPK activation contributes to the GM-CSF induced decreased PMN rescue from apoptosis in elderly subjects. The modulation of MAPK activation in PMN of elderly subjects might help to restore the functionality of PMN with aging.	Introduction Neutrophils represent the first line of defence against aggressions [ 1 ]. They are the first cells to arrive at the site of the aggression. Neutrophils can directly eliminate the invading organisms, but most of the time they set the stage, with other cells of the innate immune system including macrophages and dendritic cells, to the development of the adaptive immune response [ 2 ]. The interaction between the innate and adaptive immune response confer to the organism an efficacious defence against infections, cancers and other aggressions. Once the neutrophils finished their cleaning and modulating role, they should disappear in an ordered manner without releasing toxic products from their granules that eventually harmed the surrounding tissues. If they do not disappear they would induce a chronic inflammatory process. Their elimination for the sake of the organism is occurring through apoptosis [ 3 - 5 ]. Thus, neutrophils are programmed to die spontaneously in the absence of pro-inflammatory stimuli [ 6 , 7 ]. This death assures a proper resolution of the inflammation in time and place. However, in the presence of pro-inflammatory stimuli including lipopolysaccharide (LPS), granulocyte-colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF) neutrophils are able to postpone their spontaneous propensity for dying and thus, remain active during more than 72 hours [ 8 ]. This delayed apoptosis confers to neutrophils a highly efficacious manner to maintain their activity be able to eliminate properly the aggressors. It is well accepted that aging is linked to an increase in the susceptibility to various infections [ 9 ]. This is mostly related to the dysregulation of the immune response [ 10 - 12 ]. The most studied part is the T-cell induced cellular immune response, which is considered to be the most affected by the aging process. However, nowadays it is also accepted that neutrophils functions are also altered with aging, even in healthy elderly satisfying the SENIEUR protocol requirements [ 13 - 15 ]. The most affected functions are the chemotaxis, the free radical productions and killing. Recently, we have demonstrated that although neutrophils have an identical spontaneous apoptosis in elderly subjects compared to that in young subjects, the GM-CSF induced delayed apoptosis is markedly diminished [ 6 ]. This observation was confirmed by other groups [ 17 , 18 ]. This decreased GM-CSF induced delay in PMN apoptosis could have far reaching consequences for PMN functions and the body defence against infections. The mechanism of the GM-CSF induced delay of PMN apoptosis is under intense investigation. It is well known that GM-CSF induces three distinct signalling pathways in neutrophils: the Jak/STAT, the MAPK and the PI3K pathways [ 19 - 21 ]. Recently, it became evident that the MAPK and PI3K pathways are participating in the GM-CSF induced delayed apoptosis of PMN in young subjects [ 22 ]. Recently, we provided evidence that the Jak/STAT pathway is also contributing to the apoptosis delaying effect of GM-CSF (manuscript submitted). Furthermore, these signalling pathways modulate the expression of Bcl-2 family members as well as that of caspases which play a determinant role in the fate of cells towards survival or apoptotic death [ 23 - 25 ]. MAPKinases have been shown to have important roles in intracellular mechanisms responsible for neutrophils activation induced by various stimuli, as well as the modulation of their apoptosis [ 23 , 26 - 30 ]. There exist three different MAPKs: the extracellular regulated kinase (ERK1/2 or p42/44), the p38 and the c-Jun terminal kinase (JNK). Activation of the p42/44 MAPK occurs through phosphorylation of threonine and tyrosine residues by an upstream MAPKK (MEK1 and 2) [ 31 ]. Both kinases are known to be weakly auto-phosphorylated on tyrosine. The activation of p38 is occurring in the same manner with the MEK3/6 [ 32 ]. The p42/p44 MAPK is definitively involved in the PMN apoptosis rescuing activity of various agents including LPS, GM-CSF [ 26 - 30 ] while the role of p38 MAPK remains controversial and seems to depend on the stimuli used [ 33 - 36 ]. The present study investigates whether an alteration of the GM-CSF MAPK stimulation play a role in the diminished rescue from apoptosis of PMN of elderly subjects. In the present paper we present evidence that an alteration in the ERK1/2 activation occurs in PMN of elderly subjects under GM-CSF stimulation and this plays a role in the decreased delay of apoptosis of PMN in elderly. We also show that p38 MAPK does not play a role in GM-CSF delayed apoptosis in PMN of any age-groups. Our data also show that the alteration of the p42/p44 MAPK activation results in the inability of GM-CSF to convert the pro-apoptotic phenotype of PMN of elderly subjects to an anti-apoptotic phenotype by modulating the Bcl-2 family members Bax and Bcl-xL as well as the caspase-3. Materials and methods Reagents and antibodies Human recombinant GM-CSF was purchased from Calbiochem-Novabiochem (La Jolla, CA). Ethylene glycol-bis (β-aminoethyl ether)- N, N, N', N' -tetraacetic acid (EGTA), aprotinin, sodium orthovanadate (Na 3 VO 4 ), phenylmethylsulfonyl fluoride (PMSF) and ethylenediaminetetraacetic acid (EDTA) were obtained from Sigma-Aldrich (St Louis, MO). Leupeptin, chymostatin and pepstatin were from Boehringer Mannheim (Mannheim, Germany). Iscove's medium was purchased from Life Technologies (Grand Island, NY). The anti-caspase-3 antibody recognizing the p17 fragment of cleaved caspase-3 was a generous gift of Dr. D. Nicholson (Merck Frosst Co., Montreal, QC). Anti-phosphotyrosine mAb (4G10), anti-Bax and anti-Bcl-xL were purchased from Upstate Biotechnology Inc. (Lake Placid, NY). Polyclonal anti phospho-p42/p44 MAPK (Thr202/Tyr204), anti-p42/p44 MAPK, anti phospho-p38 MAPK (Thr180/Tyr182) and anti-p38 MAPK antibodies were from Santa Cruz (Santa Cruz, CA). The MEK inhibitor PD98059 and p38 inhibitor SB203580 were from Calbiochem. Cell permeable inhibitors of caspase-3 (Z-DEVD-FMK) and caspase-8 (Z-IETD-FMK) were purchased from Bio-Rad Laboratories (Mississauga, ON). Fluorometric caspase-3 substrate (Ac-DEVD-AMC), caspase-3 inhibitor (DEVD-CHO), caspase-8 substrate (Ac-IETD-AMC) and caspase-8 inhibitor (IETD-CHO) were from Biosource International. Propidium iodide was from R&D Systems (Minneapolis, MN). Other reagents were obtained from Sigma-Aldrich unless stated otherwise. PMN isolation Venous blood was collected from 20 young (20–25 years) and 20 elderly (65–85 years) individuals satisfying the SENIEUR protocol criteria for immunogerontological studies, as described [ 37 ]. All subjects gave their informed consent and the protocol was approved by the Hospital Ethical Committee. Neutrophils were separated by sequential sedimentation on 2% Dextran T-500 (Amersham Biosciences) in 0.9% sodium chloride, centrifugation on a Ficoll-Hypaque cushion (specific gravity 1.077, Amersham Health, Baie d'Urfé, QC) and hypotonic lysis of erythrocytes, as described [ 16 ]. Light microscopy showed that more than 97% of the cell population was composed of neutrophils. Cell viability was greater than 95% as assessed by Trypan blue exclusion. PMN cultures All experiments were performed using media, serum and reagents that were free of endotoxins to avoid non-specific activation of PMN. Purified PMN were suspended (5 × 10 6 cells/ml) in Iscove's modified Dulbecco's medium supplemented with 10% autologous serum, 50 U/ml penicillin and 25 μg/ml streptomycin and incubated in the presence or absence (control) of GM-CSF, at a concentration of 20 ng/ml which had been previously determined to induce maximal PMN response. Other agents used included: H 2 O 2 (250 μM) and FMLP (10 -8 M). These concentrations were previously determined to induce maximal activation (16). The cells were incubated for various periods of time (6 and 18 hours) in polypropylene tubes (Becton Dickinson Labware, Lincoln Park, NJ) at 37°C in a humidified 5% CO 2 -95% air incubator. For some experiments the MEK1/2 inhibitor, PD98059, and the p38 inhibitor, SB203580, were used at 30 μM and 10 μM, respectively for 1 hour prior to GM-CSF stimulation, as this concentration (from 7,5 to 100 μM) and time point (from 30 to 240 min) had been shown to be the most effective to block these MAPK activities. Stock solution of GM-CSF, H 2 O 2 , FMLP, and PD98059 as well as SB203580 were prepared in DMSO (final concentration < 0.01% v/v). Preliminary experiments showed that these concentrations of DMSO did not increase cell necrosis or the rate of PMN apoptosis. Assessment of PMN apoptosis Apoptosis of PMN was measured by flow cytometry using FITC-conjugated Annexin V to label externalized phosphatidylserine, whereas propidium iodide staining was used to differentiate apoptosis from necrosis [ 38 ]. The cells were washed in cold PBS and then gently resuspended in 0.5 ml of binding buffer (10 mM HEPES, 140 mM NaCl, 2.5 mM CaCl 2 , pH 7.4) in 12 × 75 mm polystyrene tubes. FITC-Annexin V at a saturating concentration was added to the cell suspension and incubations were performed in the dark at room temperature for 15 min. Non-specific staining was determined using a Ca 2+ -free buffer (10 mM HEPES, 140 mM NaCl, 10 mM EDTA, pH 7.4). Fluorescence was filtered through a 530/30 nm band pass to record FITC-Annexin V emission and a 582/42 nm band pass to detect PI emission. Fluorescence intensity was measured on a FACScan flow cytometer (Becton Dickinson, Mountain View, CA) equipped with a 15 mm air cooled 488 nm argon-ion laser. Gating on physical parameters was used to exclude cell debris and clumps. A minimum of 10,000 events was analyzed in each experiment. Western blot analysis of p42/p44 MAPK, p38 MAPK, Bax, Bcl-xL and caspase-3 PMN (10 7 cells) were cultured in the absence or presence of GM-CSF (20 ng/ml) and lysed in a buffer containing 20 mM Tris-HCl, pH 7.4, 137 mM NaCl, 10% glycerol, 1% Nonidet P-40, 2 mM sodium vanadate and 100 mM sodium fluoride for a 30 min on ice. Cell lysates were centrifuged at 16,000 × g for 15 min and protein concentration of the supernatants was determined by using the Bradford protein assay reagent (Bio-Rad). 20 μg of cell lysates were resolved on a 8% SDS-PAGE, transferred to Hybond nitrocellulose membranes (Amersham Biosciences) and antigens revealed by probing the membrane with an anti-phosphotyrosine antibody (4G10) or the relevant antibodies p42/p44MAPK and p38MAPK (phosphorylated or not), Bax, Bcl-xL, caspase-3. Membranes were then washed six times with TBS and incubated with horseradish peroxidase-conjugated secondary antibody for 1 h at room temperature. The protein bands were revealed by densitometry analysis was performed using the Chemigenius 2 Bio Imaging System (Syngene, Frederick, MD) [ 37 ]. Determination of caspase 3-activity PMN (5 × 10 6 cells) were lysed in 100 μl of a 10 mM potassium phosphate, 1 mM EDTA buffer (pH:7.4) containing 0.5% Triton X-100 supplemented with 2 mM PMSF, 10 μg/ml leupeptin, 10 μg/ml pepstatin, and 10 mM dithiotreitol for 15 min on ice and spun at 14,000 rpm for 20 min. The lysate (100 μg) was diluted to 1 ml with ICE buffer (50 mM HEPES, 10% sucrose, 0.1% CHAPS, pH 7.5) containing 50 μM of the caspase-3 substrate Ac-DEVD-AMC (aspartate-glutamate-valine-aspartate-AMC) [ 23 ] and 10 mM freshly prepared dithiotreitol. Five hundred μl of reaction mixture were diluted with 1.5 ml of ICE buffer and fluorescence (excitation wavelength 400 nm, emission wavelength 505 nm) was read at 1 h time point. The release of fluorochrome was linear with time and with the protein concentration used. Standards containing 0–1500 nM AMC were used to determine the amount of spontaneous release of fluorochrome. Specificity for caspase-3 activity was demonstrated by using the caspase-3 inhibitor DEVD-CHO (24). A very low level of non-specific activity was present, and the effects of the inhibitor were concentration-dependent. The inhibitor of caspase-8 IETD-CHO [ 25 ] activity assessed by the fluorochrome substrate Ac-IETD-AMC was also included to insure the specificity of caspase-3 activation. Statistical analysis Results are representative of experiments performed with 20 individual donors of each age group. Results are presented as pooled data from the entire series of experiments (mean ± SD). Data were analyzed using Student's two-tailed t -test for independent means. Significance was set for p ≤ 0.05 unless stated otherwise. Results 1. Spontaneous and GM-CSF-induced apoptosis of PMN: effect of aging 1.1 Spontaneous apoptosis In control neutrophils obtained from young subjects, the mean percentage of apoptotic cells increased steadily from 5 ± 2.7% at 0 hour to 30 ± 6.5% at 18 hours (Fig 1A and 1B , white columns, NS). Similar observations were found for PMN of elderly subjects where we found that 8 ± 3.0%, 14 ± 3.2% and 44 ± 7.0% were apoptotic, measured by the expression of Annexin-V at 0 h and 18 h, respectively (Figure 1A , filled columns, NS). Even if a tendency towards a higher susceptibility to apoptosis is observed with aging, this is not significant. It is of note that, the differences in PMN apoptosis between the basal state and after 18 h of culture are statistically significant in case of PMN of young (p < 0.01), as well as of elderly (p < 0.01) subjects. Figure 1 Measurement of human neutrophils apoptosis with aging by flow cytometry. A ) GM-CSF-treated (20 ng/ml) or untreated neutrophils were cultured during various time periods (from t = 0 to t = 18 h) and stained with Annexin-V conjugated to FITC. FACS analyses were performed for fluorescence intensity and data were reported in a time-dependent manner for the different experimental conditions and compared to control neutrophils from young (white columns) and elderly donors (black columns). Identical experiments were done with Z-DEVD-FMK, inhibitor of caspase-3 activity (iC3) in the presence or absence of GM-CSF. Data represent percentage of apoptotic cells from the neutrophil pool. Data were statistically analyzed for 20 different donors of each group indicated by p < 0.01. B ) The same experiments were done using H 2 O 2 (250 μM), Dexamethasone (10 -8 M) and FMLP (10 -8 M). Data are from 10 independent experiments with p < 0.01. 1.2 Effects of various stimulants on apoptosis of neutrophils cultured in vitro We evaluated, by the expression of Annexin-V using flow cytometry measurements, the effects of GM-CSF, H 2 O 2 , Dexamethasone (Dex), FMLP and Z-DEVD-FMK, an inhibitor of caspase-3 (iC3) on the modulation of the PMN apoptosis for various periods of time. It is well known that GM-CSF is able to rescue PMN from their spontaneous apoptosis [ 6 ]. As shown in Figure 1A the percentage of apoptotic PMN of young subjects treated by GM-CSF decreased significantly (p < 0.01) after 18 hours of culture compared to control cultures, starting already at 6 hours (data not shown). In contrast, in PMN of elderly subjects after GM-CSF treatment a decrease in apoptosis starting at 6 hours of culture could be also observed, however this did not become statistically significant at any culture time (at 18 hours) compared to control cultures (Figure 1A , filled columns). It is of note that no age-related differences could be demonstrated for the other treatments (Figure 1B ), except for dexamethasone. In contrast to GM-CSF, dexamethasone did not decrease significantly the PMN apoptosis in young subjects, but slightly increased that of elderly subjects, which resulted in a significant difference with age (Figure 1B ). Finally, we studied the effect of an inhibitor of caspase-3 on PMN spontaneous apoptosis. We found that the iC3 significantly decreased the spontaneous apoptosis of PMN in both age-groups (Figure 1A ). The caspase-3 inhibitor significantly increased the anti-apoptotic effect of GM-CSF as compared to GM-CSF alone in PMN of young subjects (5 % vs 14 %, respectively; p < 0.05). These results indicate an efficient synergism at 18 h between the effect of GM-CSF and of the caspase-3 inhibitor when compared to spontaneous apoptosis in PMN of young subjects (5 % vs 30 %, respectively; p < 0.05). The synergism seen in the case of young donors is missing in the case of elderly donors since GM-CSF is inefficient. Furthermore, these results indicate that caspase-3 is implicated in the spontaneous and GM-CSF modulated apoptosis of PMN of young and elderly subjects. Altogether, these results suggested that GM-CSF sustained survival is defective with aging. Thus, the question rose, whether an alteration in the signal transduction of GM-CSF receptor could contribute to the altered rescue of PMN of elderly subjects from apoptosis. 2. Study of the involvement of the MAPK signalling pathways in the GM-CSF induced rescue from apoptosis of PMN of young and elderly subjects PMN of young and elderly subjects were stimulated with GM-CSF during various periods of time (1, 5 and 10 minutes, see figure 2 lanes 2, 3, 4), cytosolic proteins were sized by SDS-PAGE and their pattern of tyrosine phosphorylation was assessed by Western blotting with an anti-phosphotyrosine mAb (4G10). At the basal level, the protein-tyrosine phosphorylation was significantly already enhanced in PMN of elderly subjects compared to that of young subjects (Figure 2A lane 1, p < 0.01). There is a kinetic increase of the protein-tyrosine phosphorylation of almost each bands (e.g. p42/44, p110) in PMN of young subjects after GM-CSF stimulation at 1 min and 5 min (lane 2 and lane 3 respectively, left panel, p < 0.01 compared to basal state) starting to decrease at 10 min (lane 4 left panel). In contrast, no significant kinetics in the protein-tyrosine phosphorylation could be observed in PMN from elderly subjects stimulated with GM-CSF, probably because of the intense protein-tyrosine phosphorylation level at the basal state (Figure 2A lane 1 right panel). Figure 2B is representing the densitometric scanning of the gels as described in the Materials and Methods section. Figure 2 Protein tyrosine phosphorylation of whole PMN cell lysates after short stimulation with GM-CSF Freshly prepared neutrophils were stimulated with GM-CSF for 1 to 10 min and immediately lysed. Lysates were sized on SDS-PAGE followed by western-blotting using anti-phosphotyrosine mAbs to reveal protein phosphorylation. The gel shown here is representative of 10 independent experiments. Image analyzer was used to measure the amount of phosphorylation and represented above the gel for each experimental condition in the case of young (white columns) and elderly donors (black columns). Similar phosphorylation patterns were obtained from others experiments. A significant increase in total phosphorylation in indicated by p < 0.01, p < 0.05. A significant difference in basal phosphorylation status of PMN from young and elderly donors was found and indicated by *p < 0.05. We then focused on p42/p44 MAPK proteins which were shown to be activated in PMN following GM-CSF receptor stimulation, as well as by other stimulants [ 26 - 30 ]. It was already demonstrated that p42/p44 MAPK activation contributed to the decrease of spontaneous apoptosis by GM-CSF [ 22 ]. Therefore, we studied the GM-CSF induced ERK1/2 activation in PMN in both age-groups. It is of note that the ERK1/2 tyrosine phosphorylation already detectable at basal level did not change during the non-stimulated culture times (1 h, 6 h, 18 h) when compared to the protein level expression. However, the pre-incubation of the PMN of young subjects with an inhibitor of MEK1/2, PD98059 (i-ERK), lead to the complete abrogation of p42/p44MAPK phosphorylation after 18 hours (Figure 3 , young subjects, left panel). In PMN of young subjects the protein-tyrosine phosphorylation of p42/p44MAPK increased by two times after 5 minutes of GM-CSF stimulation and remained thereafter for 18 hours with a slight decrease at 6 hours (Figure 2 , young subjects, right panel). This increase was mainly due to the p44 components of the ERK1/2. Once more the PD98059 abrogated the GM-CSF induced ERK1/2 activation measured by tyrosine phosphorylation. In contrast, in PMN of elderly we observed a very strong basal tyrosine phosphorylation (non-stimulated) compared to that of young subjects (p < 0.01), which decreased thereafter during the non-stimulated incubation (Figure 3 , elderly subjects, left panel). We could not demonstrate any changes in tyrosine phosphorylation of p42/p44MAPK during the 6 first hours activation by GM-CSF in PMN of elderly donors (Figure 3 , elderly subjects, right panel), which even decreased thereafter during the 18 hours of stimulation. The i-ERK could only partially inhibit the GM-CSF induced ERK1/2 tyrosine phosphorylation. Altogether these data indicate that GM-CSF activates the p42/p44 MAPK by phosphorylation on tyrosine in a sustained manner during the 18 hours of culture in PMN of young, while this activation is completely absent in PMN of elderly subjects. Figure 3 Activation of p42/p44 MAPK following short and long-time incubation with GM-CSF, effect of aging. Neutrophils of young ( A ) and elderly subjects ( B ) were stimulated either for 5, 30, 60 min, 6 and 18 hours with GM-CSF alone or pre-treated with PD98059 (i-ERK) for 1 hours prior to GM-CSF stimulation for 18 hours. Neutrophils were then lysed and analyzed by western-blotting experiments for p42/p44 MAPK phosphorylation revealing by phospho-anti-p42/p44 MAPK polyclonal Abs. Control loading are shown under each blot for p44. Experiments were performed for 15 different donors of each group. Next, we assessed the protein tyrosine phosphorylation of p38 MAPK (Figure 4 ). The role of p38 in PMN apoptosis is still controversial [ 33 - 36 ]. There is no evidence that GM-CSF modulate its activation. However, p38 MAPK activation has been implicated in the spontaneous apoptosis of PMN [ 33 , 34 ]. We present here data that p38 MAPK is tyrosine phosphorylated already at the basal level, in a significantly (p < 0.01) higher level in PMN of elderly subjects compared to young subjects (Figure 4A and 4B ). We also show an increase in p38 MAPK phosphorylation after 5 min of stimulation by GM-CSF in PMN of young subjects sustained for 6 hours (Figure 3A , p < 0.01) and returning to the basal level after 18 hours when comparing with control protein loading. It is of note than when the PMN were left untreated for 18 hours the phosphorylation of p38 on tyrosine was significantly increased either compared to the basal non-stimulated status (p < 0.05) or to the 18 hours GM-CSF stimulation (p < 0.05). There was no tyrosine phosphorylation modulation of p38 in PMN of elderly subjects in response to GM-CSF stimulation (Figure 3B ), which was already very high at basal level compared to PMN of young subjects (p < 0.01). These data also suggest that p38 MAPK participate to the spontaneous apoptosis of PMN in both age-groups, but did not participate to the GM-CSF delay of apoptosis. These results further indicate that we assist to an alteration of the signal transduction in PMN of elderly subjects in regard to the MAPK pathways. Figure 4 Time-dependant activation of p38 MAPK following incubation with GM-CSF, effect of aging. Neutrophils were stimulated with GM-CSF from 0 to 18 hours and immediately lysed. Western-blotting experiments of neutrophils of young ( A ) and elderly subjects ( B ) lysates were conducted by revealing with anti-phospho-p38 MAPK polyclonal Abs. Control loading for p38 are shown under each blot. Blots are representative of 15 independent experiments. Then, we tried to link the alteration described previously in the MAPK pathways in PMN of elderly subjects to the inability of GM-CSF to rescue them from apoptosis using the pharmacological inhibitors of p42/p44 and p38 MAPKs. We assessed the spontaneous and GM-CSF delayed apoptosis of PMN after 18 hours treatment with PD98059 and SB203580 (Table 1 ). We found by Annexin-V/PI staining that apoptosis commitment was not significantly affected by any of these inhibitors in PMN of young and elderly subjects (Table 1 ). When the PD98059 was applied as pre-treatment to GM-CSF stimulation, it completely abolished the GM-CSF anti-apoptotic effect in PMN of young subjects, while it had no effect on GM-CSF of elderly subjects (Table 1 ). When the SB203580 was applied as a pre-treatment prior to GM-CSF stimulation it could not abrogated the GM-CSF apoptosis rescuing effect, indicating that p38 is not concerned by the GM-CSF induced rescue. In PMN of elderly, the SB203580 pre-incubation had a similar effect than in PMN of young individuals. Altogether, these data revealed two main observations, first, the role of the p42/p44 MAPK pathway in PMN survival in contrast to that of p38 MAPK under GM-CSF stimulations and second, the altered stimulating effect of GM-CSF via the decreased p42/p44 MAPK phosphorylation due to an increased basal over-activation contributes to the decreased survival of PMN of elderly subjects. Table 1 Neutrophil apoptosis modulation by MAPKinase inhibitors Treatment Culture time (hours) Annexin-V positive cells (%) Young Elderly 0 11 ± 2 15 ± 3 None 6 11 ± 3 20 ± 3 18 34 ± 6 48 ± 10 GM-CSF 6 11 ± 4 10 ± 5 18 18 ± 3 41 ± 9 PD98059 18 33 ± 7 45 ± 10 GM-CSF + PD98059 18 40 ± 10 50 ± 15 SB203580 18 43 ± 2 53 ± 5* GM-CSF + SB203580 18 24 ± 3 33 ± 5* The cells were cultured for the indicated time in the presence or absence of GM-CSF (20 ng/ml) and the presence or absence of PD98059 (30 μM) or SB203580 (10 μM). The percentage of apoptotic was determined by labeling with FITC-conjugated Annexin-V and cell integrity, by Propidium iodide (PI) staining. The cells were analyzed by cytofluorimetry. Data are shown as the mean ± SD of five 5 independent experiments. Significant differences between young and elderly subjects are indicated by an asterisk (, p < 0.05 and , p <0.01). 3. Role of the Bcl-2 family members Bax and Bcl-xL in GM-CSF induced rescue of PMN from apoptosis The Bcl-2 family members are actively participating in the apoptotic process by being either pro-apoptotic such as Bax or anti-apoptotic such as Bcl-xL [ 6 ]. Their role in the PMN spontaneous and GM-CSF induced apoptosis was recently studied [ 9 ]. It was shown that the ratio of the pro- and anti-apoptotic molecules was essential. However, the presence of Bcl-xL in PMN is still debated [ 40 ]. Here, first we studied how the GM-CSF affected Bax and Bcl-xL expression after 18 hours of culture in PMN of young and elderly subjects. We found that in PMN of young subjects concomitantly to its anti-apoptotic effect the GM-CSF decrease significantly the expression of Bax (p < 0.01) and increase the expression of Bcl-xL (Figure 5A and 5C , Figure 6A ). In PMN of elderly subjects the GM-CSF was unable to modulate the expression of Bax, however slightly increased that of Bcl-xL (Figure 5B and 5D , Figure 6A ). Nevertheless, when the ratio is calculated there is a significant shift towards survival (Bcl-xL) in PMN of young subjects (Figure 6B ), while this is the contrary in PMN of elderly (increase of Bax) (Figure 6B ). When the inhibitors were used they did not modulate the expression neither of Bax nor of Bcl-xL in any age-groups. These data altogether indicate that the GM-CSF stimulation create an anti-apoptotic milieu in the ratio of the Bcl-2 pro-and anti-apoptotic members, while this is the contrary in PMN of elderly subjects. Moreover, the MAPK pathways do not seem to intervene in the modulation of the expression of the Bcl-2 family members in PMN. Figure 5 Expression of bcl-2 family members Bax and Bcl-xL in PMN with aging upon treatment with GM-CSF and PD98059 and SB203580 for 18 h. Neutrophils were cultured in presence of GM-CSF alone or in combination with either the p42/p44 MAPK inhibitor, PD98059, or the p38 MAPK inhibitor, SB203580, for 18 h. Then, neutrophils were lysed and western-blotting experiments were executed to investigate the amount of Bax in young ( A ) and elderly donors ( B ). The same experiments were conducted for studying Bcl-xl expression in PMN of young ( C ) and elderly subjects ( D ). GM-CSF significantly decreased the expression of Bax in PMN of young subjects (A, p < 0.01), without any effect in PMN of elderly subjects (B). GM-CSF significantly increased the expression of Bcl-xL (p < 0.05) in both age groups (C and D), Blots are representative of 15 independent experiments. Figure 6 Densitometric analyses of the expression of bcl-2 family member Bax in PMN with aging upon treatment with GM-CSF and PD98059 and SB203580 for 18 h as well as the ratio of the expression of Bax/Bcl-xL. Densitometric analysis were performed as described in the Materials and Methods section for the expression of Bax in neutrophils of young (white columns) and elderly subjects (black columns) under GM-CSF stimulation ( A , p < 0.01) and after the application of inhibitors, PD98059 (i-ERK) and SB203580 (i-p38) ( B , p < 0.01). The ratio of Bax to Bcl-xL in PMN of young (white columns) and elderly subjects (black columns) under GM-CSF stimulation and modulation by inhibitors is represented ( C ). 4. Role of caspase-3 in the apoptosis of PMN and its modulation by GM-CSF through the MAPK pathway We have shown that caspase-3 is implicated in the spontaneous and GM-CSF modulated apoptosis of PMN of young and elderly subjects. Caspase-3 is in an uncleaved form when not activated (procaspase-3). Here we analyzed by western-blotting experiments the amount of activated caspase-3 after different experimental conditions including GM-CSF and inhibitors treatment. We found that after 18 hours, GM-CSF-treated PMN of young subjects reduced significantly the expression of activated caspase-3 as compared to untreated cells (Figure 7A , young, lane 2 and 3, p < 0.01). In PMN of elderly subjects the expression of activated caspase-3 did no change after 18 hours of GM-CSF stimulation, compared to the non-stimulated status (Figure 7A , lane 2 and 3, elderly). When we applied the inhibitor PD98059, we found a reestablishment of the activated caspase-3 (Figure 7A lane 4, upper panel) compared to the GM-CSF-treated PMN. The p38 inhibitor, SB203580, did not influence significantly the activated caspase-3 expression modulation by GM-CSF. No modulation of the activated caspase-3 expression was found at any experimental conditions in PMN of elderly (Figure 7A lane 4, lower panel). These last data indicate a link between p42/p44MAPK and caspase-3 activation, however other transduction pathways could also play a role. Figure 7 Expression of activated caspase-3 in PMN with aging upon treatment with GM-CSF and PD98059 and SB203580 for 18 h A ) Neutrophils of young (upper panel) and elderly subjects (lower panel) were cultured in presence of GM-CSF alone or in combination with either the inhibitor PD98059 (i-ERK) or SB203580 (i-p38), for 18 h. Then, neutrophils were lysed and western-blotting experiments were performed to investigate the amount of active caspase-3. With aging no changes were found by any agents used (lower panel) while neutrophils from young donors (upper panel) showed significant modulation by GM-CSF and PD98059. B , Densitometric analyses were performed as described in the Materials and Methods section for the expression of activated caspase-3 in neutrophils of young (white columns) and elderly donors (black columns) with p < 0.01. To confirm these results, we measured the caspase-3 activity by a specific fluorescent substrate (Table 2 ). In PMN of young subjects the activity of caspase-3 increased progressively after 6 hours of culture for reaching a peak value at 18 hours. For all the incubation times, the caspase-3 activity was significantly higher (p < 0.05) in the case of elderly donors (Table 2 ), except at 6 hours. Under GM-CSF stimulation, caspase-3 activity was significantly decreased at 6 hours (p < 0.05), 18 hours (p < 0.01) in PMN of young subjects. It is of note that GM-CSF could not restore the caspase-3 activity to the level of freshly prepared PMN. In the aged group, in PMN under GM-CSF treatment no significant decrease could be detected in caspase-3 activity compared to the spontaneous activities of caspase-3. These data support the fact that GM-CSF is involved in the modulation of caspase-3 activity which decreases in PMN of young subjects concomitantly to their rescue from apoptosis, while PMN of elderly subjects are unable to decrease caspase-3 activity when GM-CSF is provided in the milieu. Table 2 Modulation of caspase-3 activity in PMN by MAPkinase inhibitors Treatment Culture time (hours) Caspase-3 activity (arbitrary fluorescence units) Young Elderly 0 92 ± 20 126 ± 29 None 6 218 ± 38 188 ± 53 18 908 ± 118 1396 ± 207 GM-CSF 6 113 ± 31 149 ± 42 18 447 ± 87 979 ± 96* PD98059 18 781 ± 216 1024 ± 413 GM-CSF + PD98059 18 1126 ± 376 1145 ± 387 SB203580 18 1055 ± 267 792 ± 291 GM-CSF + SB203580 18 459 ± 119 900 ± 147 * PMN isolated from young and elderly donors were maintained in culture for the indicated periods of time. The cells were left untreated, or exposed to GM-CSF (20 ng/ml) or a combination of GM-CSF (20 ng/ml) and either in the presence or absence of PD98059 (30 μM) or SB203580 (10 μM). Caspase-3 activity was measured using a fluorescent substrate. Data are representative of 10 independent experiments. The asterisk (*) indicate significant differences (p < 0.05) between the two groups of donors. To further link the MAPK pathways to survival/apoptosis of PMN we assessed the caspase-3 activity under GM-CSF stimulation after PD98059 and SB203580 pre-treatment. We found that any of these inhibitors alone did not modulate significantly the caspase-3 activity during the spontaneous apoptosis of PMN obtained either from young or elderly subjects (Table 2 ). The diminution of caspase-3 activity by GM-CSF in PMN of young subjects (from 908 ± 118 to 447 ± 87) could be completely reversed by PD98059 (from 447 ± 87 to 1126 ± 376), while the SB203580 could not modulate the effect of GM-CSF on caspase-3 activity. These inhibitors had no significant effect on PMN of elderly subjects. These data further confirm the essential role of the p42/p44 MAPK pathway in PMN survival by modulating the caspase-3 activity, while p38 MAPK is not concerned. Discussion Many clinical data indicate that elderly subjects are more susceptible to infections, particularly to that of the higher respiratory tracts, more likely caused by atypical organisms as well as to sepsis by gram negative bacteria [ 9 , 14 ]. PMN are the first cells to arrive at the site of invasion and respond very quickly by the destruction of the aggressor. Recently, besides the alterations of the adaptive immune response it was demonstrated that some functions of the PMN including chemotaxis, killing and production of bactericidal substances are decreasing with aging [ 13 ] while others remain unchanged such as phagocytosis [ 41 ]. One particular aspect of neutrophils homeostasis is their propensity to die spontaneously i.e in the absence of pro-inflammatory stimuli for preserving the organism from undue destruction or chronic inflammation. In contrast, when an inflammatory process increases the level of pro-inflammatory mediators such as GM-CSF, G-CSF and LPS, PMN remain functional for 72 hours and die thereafter by apoptosis. We have found that in PMN of elderly subjects the GM-CSF was not able to rescue them from apoptosis as efficiently as in PMN of young subjects [ 16 ]. Here we present data confirming and extending these results. Except GM-CSF any other agents used for modulating PMN apoptosis was found to demonstrate significant age-related differences. GM-CSF acts as a ligand for its specific receptor for exercising its anti-apoptotic effect. This means that if in PMN of elderly the GM-CSF is not able to exert its anti-apoptotic activity, an alteration in the signalling of GM-CSF may exist. In fact, in this study we demonstrate an alteration in the p42/p44 MAPK activation in PMN of elderly subjects participating in the altered rescue of PMN from apoptosis. Moreover, we show that p38 MAPK does not participate in the rescue from apoptosis either in young or elderly subjects. We present also data that molecules modulating the apoptotic fate of PMN were differentially related to the MAPK pathways. We demonstrate that the p42/p44 MAPK is not linked to the modulation of the expression of the Bcl-2 family members, while caspase-3 is partially modulated by this MAPK. GM-CSF is activating three signalling pathways, Jak/STAT, MAPK and PI3K [ 19 ]. It is now well accepted that in eosinophils all three pathways are implicated in the GM-CSF induced rescue from apoptosis [ 42 ]. In PMN it is now also well established that p42/p44 MAPK and PI3K are implicated in the GM-CSF induced rescue from apoptosis [ 22 ]. We have recently shown that the Jak/STAT signalling pathway was also involved. We were the first to demonstrate that GM-CSF is unable to rescue PMN of elderly subjects from apoptosis [ 16 ]. This was since confirmed by other groups. This fact could have far reaching consequences on the susceptibility of elderly to infections. Thus it is very important to understand why this phenomenon is occurring in PMN of elderly. As the p42/p44 MAPK was implicated in PMN of young subjects in the rescue from apoptosis, we studied whether this could contribute to the failure of rescue with aging. In fact, the activation of this MAPK by GM-CSF, as well as by other substances is strongly related to its anti-apoptotic effect, showed by the use of specific MEK1/2 inhibitors [ 26 - 30 ]. Our present data show that p42/p44 MAPK could not be activated by GM-CSF in the PMN of elderly. This inability exists either for the short stimulation times or for longer periods. It is clear from the experiments on PMN of young subjects that the activation of p42/p44 MAPK is sustained at least for 18 hours induced by GM-CSF. To confirm that the p42/p44 MAPK is participating to the rescue of PMN from apoptosis we used the inhibitor PD98059. We found, as others [ 26 - 30 ] that in PMN of young subjects the use of PD98059 reversed the GM-CSF inhibitor of apoptosis clearly demonstrating that the ERK/1/2 is effectively involved in the rescue of apoptosis. In the case of elderly subjects the lack of p42/p44 MAPK activation contributes to the altered rescue of PM from apoptosis and in fact, the PD98059 could not modulate the PMN apoptosis. We also studied whether another member of the MAPK family namely the p38 MAPK participates to the GM-CSF induced rescue from apoptosis. The role of the p38 MAPK in PMN apoptosis is controversial [ 33 - 36 ]. Nevertheless, the consensus seems to exist that its activation participates in the PMN spontaneous apoptosis. Our present results confirm this contention in both age-groups. There is a controversy whether the activation of p38 MAPK participates in the rescue from apoptosis under various stimulations. In this regard the results of the literature seem to suggest that p38 MAPK does not participate in the PMN apoptosis delaying effect of GM-CSF [ 33 - 36 ]. Our present results indicate that p38 does not contribute to the rescue from apoptosis neither in PMN of young or elderly subjects. Finally to understand how the p42/p44 MAPK can be implicated in the GM-CSF induced apoptosis of PMN we studied molecules intervening in the modulation of PMN apoptosis. These molecules enclosed those of the Bcl-2 family members and the caspases, mainly caspase-3. It was shown that the Bcl-2 family members are either pro-apoptotic or anti-apoptotic. In PMN the most important pro-apoptotic molecule is Bax and the most important anti-apoptotic ones are the Mcl-1, A1 and Bcl-xL [ 6 ]. The presence of Bcl-xL is still controversial. The ratio between these molecules determines the fate of PMN. We wanted to see whether the p42/p44 MAPK activation by GM-CSF is linked to the expression of the Bax and Bcl-xL molecules and their ratio. It is known that the p42/p44 MAPK is linked to the phosphorylation of Bad and freeing in this way the Bcl-xL, leading to an anti-apoptotic milieu [ 43 ]. We found that GM-CSF decreases the expression of Bax after 18 hours of stimulation, while it increased the expression of Bcl-XL which gives a ratio in favour of Bcl-xL, representing the survival. The contrary is occurring in PMN of elderly where the ratio is in favour of Bax and so pro-apoptotic. Weinmann et al . [ 44 ] showed that GM-CSF did not modulate the expression of Bcl-xL. Discrepancies may come from the fact that the concentration of GM-CSF used was 300 U/ml in their case and only 200 U/ml in our study. When we treated PMN with higher concentration we also found a drop in the effect of GM-CSF on Bcl-xL expression. The use of PD98059 could not reverted the effect of GM-CSF on the ratio of Bax/Bcl-xL indicating that the p42/p44 MAPK is not acting directly on these molecules of the Bcl-2 family. This indicates also that the p42/p44 MAPK is not the only signalling pathway participating in the GM-CSF induced rescue from apoptosis. As indicated the Jak/STAT and PI3K pathways are also participating. In PMN of elderly as the p42/p44 MAPK could not be activated by GM-CSF at any time points, it was evident that no modulation by ERK1/2 inhibitor was found. The p38 MAPK is not involved in the modulation of these molecules in PMN at any age-groups. Furthermore, we were also interested to study the effects of p42/p44 MAPK on the expression and activity of another very important executioner protein, the caspase-3. Caspase-3 was implicated in the spontaneous and GM-CSF induced rescue of PMN from apoptosis. In fact we confirmed that GM-CSF could decrease the activated caspase-3 expression and activity in PMN of young subjects, while has no effect in PMN of elderly. It was also known that the p42/p44 MAPK is inhibiting the activation of caspase-8 [ 23 ]. The use of PD98059 indicated in PMN of young subjects that the p42/p44 MAPK is implicated in the GM-CSF induced inhibition of caspase-3, however this inhibition was not complete. This also indicates that the GM-CSF has other pathways to modulate the proteins participating in the executioner phase of apoptosis. In case of PMN of elderly subjects once again no modulation of caspase-3 could be demonstrated in any experimental conditions. For the participation of p38 MAPK in the modulation of caspase-3 by GM-CSF more work is needed as the results were not so clear cut. Altogether, our data demonstrate to our best knowledge for the first time that the lack of activation of p42/p44 MAPK contribute to the decreased rescue of PMN from apoptosis in elderly individuals. This decreased activation results in a pro-apoptotic Bcl-2 family members over-expression and the activation of caspase-3 in contrast to PMN of young subjects. We also present data that the activation of p42/p44 MAPK should be sustained for at least 18 hours to ensure an efficient rescue of PMN from apoptosis by GM-CSF. Moreover, our results confirm that the p38 MAPK participates to the spontaneous apoptosis of PMN in both age-groups while it did not participate in the rescue of PMN apoptosis by GM-CSF. Thus, the perspective of modulation of the p42/p44 MAPK activation in PMN of elderly subjects may be useful to restore the effectiveness of GM-CSF and contribute to more effective PMN functionality in elderly. We explore actually what means can be used to achieve such an increase in p42/p44 MAPK activation, including the modification of the PMN membrane composition.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555764.xml
549601	Why Bigger Is Not Yet Better: The Problems with Huge Datasets	Traditional two dimensional journal publishing may no longer be enough, and may be hindering, the interpretation of the complex datasets and analyses generated by microarray experiments in medicine	“Publishing results in traditional paper based way in a journal hides too much information.” This is the verdict of Markus Ruschhaupt and colleagues who, in a paper in Statistical Applications in Genetics and Molecular Biology (3: article 37), discuss a paradigm for the presentation of complex data—in this case, from microarray analyses. The title of the article, “A Compendium to Ensure Reproducibility in High-Dimensional Classification Tasks,” may not lend itself easily to a clinical audience, but the underlying message to clinicians could not be more important: that, currently, studies involving large datasets, especially ones that have a clinical outcome, are so poorly reported (or possibly so poorly done) that many are not reproducible. This problem was also the topic of a recent meeting in Heidelberg, “Best Practice in Microarray Studies” ( http://www.biometrie.uni-heidelberg.de/workshops/bestpractice/index.htm ). As microarrays have become mainstream research tools in biology and medicine, the large datasets and complex analyses from these studies have presented challenges: for authors in analyzing the data, for reviewers and editors in deciding on the suitability of papers for publication, for journals in determining how much data needs to be presented within the paper itself, for other researchers in reproducing the data, and, finally, for readers in deciding how to assess the data presented. The results from several high-profile papers have already proved difficult to reproduce, even by those with sufficient time and computing expertise. Where do such analyses leave the new science of molecular pathology? Ruschhaupt and colleagues comment that “the literature on the induction of prognostic profiles from microarray studies is a methodological wasteland.” Much the same could be said of other applications of molecular biology to clinical samples. A systematic review of molecular and biological tumor markers in neuroblastoma (Clin Cancer Res 10: 4–12) found that its conclusions were limited by “small sample sizes, poor statistical reporting, large heterogeneity across studies…and publication bias.” John Ioannidis and colleagues (Lancet 362: 1439–1444) did a similar analysis of 30 microarray studies with major clinical outcomes in cancer. They showed that the studies were small—median sample size was 25 patients, and validation was incomplete in most studies. They recommended that molecular prognostic studies be classified as phase 1 (early exploratory probing associations), phase 2 (exploratory with extensive analyses), or phase 3 (large confirmatory studies with pre-stated hypotheses and precise quantification of the magnitude of the effect), and that only studies that had undergone phase 3 testing should be considered robust enough for use in clinical practice. Most current studies should be considered as phase 1 or, at best, phase 2. So, despite considerable hype, the published studies are far from the level of evidence that would be accepted for virtually any other medical test. In a review in 2003 (Hematology [Am Soc Hematol Educ Program] 2003: 279–293), Rita Braziel and colleagues concluded, “rapid identification and neutralization of spurious results is essential to prevent them from becoming accepted facts.” But these problems are not new in medical research. In 1994 (BMJ 308: 283–284), Doug Altman, who was instrumental in developing the CONSORT guidelines for reporting of clinical trials, said that “huge sums of money are spent annually on research that is seriously flawed through the use of inappropriate designs, unrepresentative samples, small samples, incorrect methods of analysis, and faulty interpretation,” and “that quality control needs to be built in from the start rather than the failures being discarded.” So how can we ensure that the wealth of data pouring out of microarray and other molecular diagnostic studies is turned into meaningful knowledge? The Microarray Gene Expression Data Society has proposed a set of guidelines (MIAME) for the reporting of microarray data, and that all such data should be deposited in public databases. But as Ruschhaupt and others have shown, disclosure of results and data is not enough, since there is little consensus on the appropriate statistical analyses and many are developed on a case by case basis, which may not be reproducible, even by the authors. Some researchers advocate the use of standard statistical packages, which allows the reader to repeat an entire analysis quickly and, hence, assess the robustness of the results. Some authors have produced a transcript of their statistical analyses as a supplement to their articles (e.g., Nucleic Acids Res 32: e50). At the very least authors should have a protocol with a prespecified plan for patient selection and statistical analysis—accepted practice for clinical trials, but not yet for other medical research. An ultimate aim for reporting would be the type of compendium discussed by Ruschhaupt and colleagues—“an interactive document that bundles primary data, statistical processing methods, figures, and derived data together with the textual documentation and conclusions.” One such compendium is illustrated in a paper by Robert Gentleman (Stat Appl Genet Mol Biol 4: article 2). PLoS Medicine is keen to work with authors towards making such reporting possible. But although the time might have gone when the two-dimensional journal article could suffice for complex papers, clinicians should nonetheless apply the same critical assessment that they would for any other clinical tool. If a result is too good to be true, it probably is.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC549601.xml
526775	Serum adiponectin as a biomarker for in vivo PPARgamma activation and PPARgamma agonist-induced efficacy on insulin sensitization/lipid lowering in rats	Background PPARγ agonists ameliorate insulin resistance and dyslipidemia in type 2 diabetic patients. Adiponectin possesses insulin sensitizing properties, and predicts insulin sensitivity of both glucose and lipid metabolism. In diet-induced insulin resistant rats and ZDF rats, the current studies determined the correlation between PPARγ agonist-upregulated fatty acid binding protein(FABP3) mRNA in adipose tissue and PPARγ agonist-elevated serum adiponectin, and the correlation between PPARγ agonist-elevated serum adiponectin and PPARγ agonist-mediated efficacy in insulin sensitization and lipid lowering. Results Parallel groups of SD rats were fed a high fat/sucrose (HF) diet for 4 weeks. These rats were orally treated for the later 2 weeks with vehicle, either PPARγ agonist GI262570 (0.2–100 mg/kg, Q.D.), or GW347845 (3 mg/kg, B.I.D). Rats on HF diet showed significant increases in postprandial serum triglycerides, free fatty acids (FFA), insulin, and area under curve (AUC) of serum insulin during an oral glucose tolerance test, but showed no change in serum glucose, adiponectin, and glucose AUC. Treatment with GI262570 dose-dependently upregulated adipose FABP3 mRNA, and increased serum adiponectin. There was a positive correlation between adipose FABP3 mRNA and serum adiponectin (r = 0.7350, p < 0.01). GI262570 dose-dependently decreased the diet-induced elevations in triglycerides, FFA, insulin, and insulin AUC. Treatment with GW347845 had similar effects on serum adiponectin and the diet-induced elevations. There were negative correlations for adiponectin versus triglycerides, FFA, insulin, and insulin AUC (For GI262570, r = -0.7486, -0.4581, -0.4379, and -0.3258 respectively, all p < 0.05. For GW347845, r = -0.6370, -0.6877, -0.5512, and -0.3812 respectively, all p < 0.05). In ZDF rats treated with PPARγ agonists pioglitazone (3–30 mg/kg, B.I.D.) or GW347845 (3 mg/kg, B.I.D.), there were also negative correlations for serum adiponectin versus glucose, triglycerides, FFA (for pioglitazone, r = -0.7005, -0.8603, and -0.9288 respectively; for GW347845, r = -0.9721, -0.8483, and -0.9453 respectively, all p < 0.01). Conclusions This study demonstrated that (a) PPARγ agonists improved insulin sensitivity and ameliorated dyslipidemia in HF fed rats and ZDF rats, which were correlated with serum adiponectin; (b) Serum adiponectin was positively correlated with adipose FABP3 mRNA in GI262570-treated rats. These data suggest that serum adiponectin can serve as a biomarker for both in vivo PPARγ activation and PPARγ agonist-induced efficacy on insulin resistance and dyslipidemia in rats.	Background Type 2 diabetes mellitus (T2D) and the metabolic syndrome are characterized by resistance to the action of insulin in peripheral tissues, including skeletal muscle, liver, and adipose. Activation of the peroxisome proliferator-activated receptor gamma (PPARγ) improves insulin sensitivity and lowers circulating levels of glucose, triglycerides and free fatty acids without stimulating insulin secretion in rodent models of T2D [ 1 , 2 ]. PPARγ agonists also alleviate peripheral insulin resistance in humans, and have been effectively used in treatment of T2D patients [ 3 - 5 ]. Fatty acid binding protein(FABP3), adipocyte lipid binding protein(aP2) and lipoprotein lipase (LPL)are response genes of PPARγ and are indicators for in vivo PPARγ activation in adipose tissue [ 6 - 9 ]. Adiponectin, an adipose-specific plasma protein, possesses insulin sensitizing and anti-atherogenic properties [ 10 ]. It has been well documented that plasma adiponectin is lower in obese subjects than in lean subjects, lower in diabetic patients than in non-diabetic patients [ 10 - 13 ], and is negatively correlated with body weight, visceral fat mass, and resting insulin level [ 11 , 12 ]. Hotta et al also reported that adiponectin decreased in parallel with the progression of T2D in rhesus monkeys, and there is a strong correlation between plasma adiponectin and systemic insulin sensitivity [ 14 ]. Studies by Maeda et al showed that adiponectin knockout mice developed hyperglycemia and hyperinsulinemia while on HF diet, which was reversed by adenoviral-mediated adiponectin expression [ 15 ]. Exogenous adiponectin also lowered hepatic glucose production during a pancreatic euglycemic clamp [ 16 ], and increased post-absorptive insulin-mediated suppression of hepatic glucose output [ 10 ]. The PPARγ agonist, class of insulin sensitizer, has the marked effect of up-regulating serum adiponectin. Combs et al reported that the PPARγ agonist rosiglitazone increased plasma adiponectin in db/db mice [ 17 ]. Yang et al reported rosiglitazone increased plasma levels of adiponectin in type 2 diabetic patients [ 18 ]. Tschritter et al analyzed the associations between plasma adiponectin and insulin sensitivity and serum lipid parameters in nondiabetic individuals, and concluded that plasma adiponectin predicts insulin sensitivity of both glucose and lipid metabolism [ 19 ]. While PPARγ agonists increase plasma adiponectin and adiponectin levels predict insulin sensitivity, there is not a clear demonstration of the relationships among PPARγ agonist-increased adiponectin and PPARγ agonist-mediated efficacy on insulin sensitivity/in vivo PPARγ activation. Therefore, the current studies were designed to define these relationships and assess serum adiponectin as a biomarker for in vivo PPARγ activation and PPARγ agonist-induced efficacy on insulin sensitization and lipid lowering. Results High fat/sucrose (HF) diet induced changes in SD rats Rats on the HF diet for 4 weeks showed marked insulin resistance and dyslipidemia, indicated by significant increases in postprandial serum levels of triglycerides, free fatty acids, insulin, and area under curve (AUC) for serum insulin during OGTT. But the HF diet did not cause changes in postprandial serum glucose or OGTT glucose AUC compared with rats on normal diet, consistent with an insulin resistant, pre-diabetic phenotype. Serum adiponectin level in rats on HF diet was slightly higher than that in normal diet rats at week 2, but back to the same level at week 4 (Table 1 ). Table 1 HF diet induced changes in SD rats. Normal diet HF diet Triglyceride (mg/dL) Prior to start 95.0 ± 8.7 115.6 ± 13.7 2 weeks diet 100.4 ± 7.6 446.2 ± 38.7++ 4 weeks diet 121.7 ± 9.1 388.1 ± 44.5++ Free fatty acid (mEq/L) Prior to start 0.36 ± 0.05 0.41 ± 0.04 2 weeks diet 0.38 ± 0.05 0.56 ± 0.04++ 4 weeks diet 0.24 ± 0.02 0.67 ± 0.06++ Glucose (mg/dL) Prior to start 166.8 ± 5.3 162.8 ± 4.3 2 weeks diet 170.0 ± 11.3 174.1 ± 2.5 4 weeks diet 176.6 ± 2.8 167.0 ± 4.0 Post-prandial insulin (ng/ml) Prior to start 0.71 ± 0.11 1.06 ± 0.15 2 weeks diet 1.26 ± 0.29 2.72 ± 0.47++ 4 weeks diet 1.23 ± 0.22 2.39 ± 0.35++ Insulin AUC during OGTT 4 weeks diet 241.6 ± 19.5 528.6 ± 84.9** Glucose AUC during OGTT 4 weeks diet 7360 ± 416 7533 ± 496 Serum adiponectin (μg/ml) Prior to start 3.59 ± 0.25 3.53 ± 0.25 2 weeks diet 3.64 ± 0.32 4.96 ± 0.41* 4 weeks diet 3.75 ± 0.40 4.35 ± 0.40 p < 0.05 vs Before diet, p < 0.01 vs Before diet, ++p < 0.01 vs Normal diet. PPARγ agonist on adiponectin in SD rats As showed in Fig. 1 , treatment of SD rats on HF diet with GI262570 for 2 weeks dose-dependently increased serum adiponectin, and upregulated adipose FABP3 mRNA without effect on housekeeper genes 18S, β-actin, and cyclophilin. There was a positive correlation between adipose FABP3 mRNA and serum adiponectin (Pearson Correlation Coefficients 0.7350, p < 0.01). A marked increase in serum adiponectin was also observed in GW347845-treated HF fed SD rats (30.93 ± 0.45 vs 4.86 ± 0.30 μg/ml in vehicle. p < 0.01). Figure 1 Efeects of PPARγ agonist GI262570 on serum adiponectin level (a), adipose FABP3 mRNA level (b), and the correlation between serum adiponectin and adipose FABP3 mRNA. SD rats were on HF diet for 4 weeks. GI262570 was oral dosed for the later 2 weeks. Mean ± SEM. N = 5–8 in each group. p < 0.05 vs vehicle. p < 0.01 vs vehicle. PPARγ agonist-increased serum adiponectin and PPARγ agonist-mediated efficacy on insulin sensitivity and lipid lowering Treatment of rats on HF diet with GI262570 for 2 weeks significantly decreased the diet-induced elevations in postprandial serum triglycerides, free fatty acids, insulin, and insulin AUC in a dose-dependent manner (Fig. 2 ). Treatment with GW347845 showed a qualitatively similar effect to that of GI262570 treatment (Table 2 ). There were negative correlations for adiponectin versus triglycerides, free fatty acids, insulin, and insulin AUC (For GI262570, r = -0.7486, -0.4581, -0.4379, and -0.3258; p < 0.005, 0.005, 0.01 and 0.05 respectively, Fig. 3 ; For GW347845, r = -0.6370, -0.6877, -0.5512, and -0.3812, p < 0.01, 0.01, 0.01 and 0.05 respectively, Table 2 ). Figure 2 Effects of PPARγ agonist GI262570 on serum insulin, triglycerides, free fatty acids, and insulin AUC during OGTT. SD rats were on HF diet for 4 weeks. GI262570 was oral dosed for the later 2 weeks. Mean ± SEM. N = 7–9 in each group. Table 2 Effect of GW347845 (3 mg/kg, B.I.D.) in rats on HF diet. Triglycerides (mg/dL) FFA (mEq/L) Serum Insulin (ng/ml) Insulin AUC (min × ng/ml) Normal diet 98.6 ± 8.6 0.26 ± 0.03 1.34 ± 0.19 241.0 ± 22.8 Diet-Vehicle 455.6 ± 94.2 0.65 ± 0.07** 1.88 ± 0.16* 356.9 ± 25.3** Diet-GW347845 139.4 ± 14.8++ 0.37 ± 0.03++ 1.16 ± 0.08++ 267.9 ± 34.2 Corr. Coeff. -0.637 -0.6877 -0.5512 -0.3812 Vs adiponectin p < 0.01 p < 0.01 p < 0.01 p < 0.05 Corr. Coeff.: Pearson Correlation Coefficient. p < 0.05 vs Normal diet. p < 0.01 vs normal diet. ++ p < 0.01 vs diet-vehicle. N = 7–8 in each group. Figure 3 Correlation between PPARγ agonist GI262570 (0.2–100 mg/kg)-elevated serum adiponectin and GI262570-decreased serum insulin, triglycerides, free fatty acids, and insulin AUC during OGTT in HF fed SD rats. PPARγ agonists in Zucker rats Compared with Zucker lean rats, ZDF rats had higher serum insulin, glucose, TG, FFA, but similar serum adiponectin levels. Treatment of ZDF rats with PPARγ agonist pioglitazone or GW347845 for 2 weeks resulted in significantly lower serum glucose, triglycerides, free fatty acids, and modestly lower serum insulin, compared to vehicle treatment. Both pioglitazone and GW347845 markedly increased serum adiponectin in ZDF rats (Table 3 ). There were also negative correlations for serum adiponectin versus glucose, TG, FFA (for pioglitazone, r = -0.7005, -0.8603, and -0.9288 respectively; for GW347845, r = -0.9721, -0.8483, and -0.9453 respectively, all p < 0.01). Table 3 Effect of pioglitazone and GW347845 in ZDF rats. Insulin (ng/ml) Glucose (mg/dL) Triglycerides (mg/dL) FFA (mEq/L) Adiponectin (μg/ml) ZDF lean rats Vehicle 0.3 ± 0.1 158 ± 4 82 ± 7 0.31 ± 0.02 10.2 ± 0.5 ZDF rats Vehicle 2.9 ± 0.5* 525 ± 25 912 ± 97 0.62 ± 0.03 10.0 ± 1.1 Pioglitazone (mg/kg, B.I.D) 3 2.5 ± 0.6 + 214 ± 64 + 251 ± 81 ++ 0.26 ± 0.09 ++ 44.0 ± 7.7 ++ 10 2.8 ± 0.5 154 ± 17 ++ 129 ± 19 ++ 0.16 ± 0.01 ++ 60.0 ± 1.5 ++ 30 2.3 ± 0.4 + 154 ± 9 ++ 129 ± 16 ++ 0.14 ± 0.01 ++ 63.0 ± 0.8 ++ GW347845 (mg/kg, B.I.D) 3 1.7 ± 0.2 ++ 147 ± 6 ++ 95 ± 10 ++ 0.12 ± 0.01 ++ 66.1 ± 0.6 ++ p < 0.01 vs ZDF lean rats. + p < 0.05 vs Vehicle-treated ZDF rats. ++ p < 0.01 vs Vehicle-treated ZDF rats. N = 6–12 in each group. Discussion Adiponectin possesses insulin sensitizing and anti-atherogenic properties [ 10 ]. In most clinical reports, primate studies, and genetic models, serum adiponectin level had been reported to be negatively correlated with body weight, visceral fat mass, and resting insulin level [ 10 - 13 ]. The present study showed that rats fed a HF diet had significantly higher serum insulin and lipids with in 2 weeks, which indicates insulin resistance. However, serum adiponectin level was not decreased by the diet up to 4 weeks. We have subsequently kept rats on the HF diet for up to 20 weeks, and observed a slight increase (instead of decrease) in serum adiponectin level (data not shown). Our data may suggest that the HF diet-induced insulin resistance happened much early than diet-induced change in serum adiponectin. Our data is consistent with studies by Naderali EK et al [ 19 ]. In their report, 16 weeks of high fat/glucose diet resulted in significantly higher body weight, fat pad masses, plasma leptin, and higher plasma level of adiponectin, besides higher levels of plasma TG and FFA. PPARγ is a member of the PPAR family of the nuclear receptor superfamily [ 6 ]. PPARγ agonists increase insulin sensitivity and circulating adiponectin [ 1 , 2 , 17 , 18 ]. The response genes of PPARγ for in vivo PPARγ activation include LPL, AP2 and FABP3 [ 6 , 7 , 9 ]. The current study demonstrated that as in other species the PPARγ agonist GI262570 upregulated serum adiponectin level and adipose FABP3 mRNA level in SD rats in a dose-dependent manner. Interestingly, there is a positive correlation between PPARγ full agonist-upregulated serum adiponectin level and adipose FABP3 mRNA level, demonstrating the serum adiponectin level could be a biomarker for in vivo PPARγ activation. We did perform parallel experiments to check mRNA levels of PPARγ response genes FABP3, aP2 and LPL in epididymal fat. We found that basal level of FABP3 mRNA was very low compared to aP2 and LPL (FABP3:LPL:aP2 = ~1:250:2500), and that PPARγ agonist GI262570 dose-dependently increased FABP3 mRNA. AP2 was abundant in epididymal fat tissues, and was only slightly increased by GI262570 in a non-dose-dependent manner (data not shown). LPL was decreased in high fat diet fed rats, which was reversed by GI262570 but not dose-dependently (data not shown). With in vivo chronic exposure, the effect of PPARγ agonists on gene expression is difficult to separate from the effects on differentiation. In general we find aP2 a better marker of adipocyte differentiation than PPARγ activation. Since PPARγ agonist-mediated action in vivo may vary with organs/tissues (such as liver vs fat; subcutaneous fat vs omental or epididymal fat) [ 20 , 21 ] and duration of treatment, all PPARγ response genes may not be changed in the same manner in one tissue following chronic treatment. Therefore the authors consider that the dose-dependently GI262570 upregulated FABP3 mRNA in epididymal fat caught in the present study is of value for quantitative in vivo PPARγ activation. Thus the correlation data using FABP3 mRNA is of value. Adiponectin has been demonstrated to have an insulin sensitizing effect [ 10 ]. Circulating adiponectin levels were positively correlated with insulin sensitivity, measured both by an euglycemic-hyperinsulinemic clamp and estimated by an oral glucose tolerant test, were negatively correlated with fasting lipids [ 22 ]. The PPARγ agonist rosiglitazone increased plasma level of adiponectin, decreased fasting plasma glucose and HBA 1C , and ameliorated insulin resistance in type 2 diabetic patients [ 18 ]. However, the relationship between PPARγ agonist-increased circulating adiponectin and PPARγ agonist-induced efficacy on insulin resistance has not been studied. The current study showed that PPARγ agonists increased serum levels of adiponectin, ameliorated insulin resistance and lipid profile in both diet-induced insulin resistant rats and ZDF rats. There is a correlation between PPARγ agonist-increased serum adiponectin level and PPARγ agonist-induced efficacy in insulin sensitivity/lipid lowering. These data provide a link between PPARγ agonist-elevated circulating adiponectin level and PPARγ agonist-mediated efficacy in insulin sensitivity and lipid lowering, and indicate that serum adiponectin level could be a biomarker for in vivo PPARγ efficacy. Other adipokines, such as leptin, are important in obesity and insulin resistance. Unlike adiponectin, leptin is positively correlated with fat amount, mass and percentage [ 23 ]. It has been reported that PPARγ agonists inhibit the expression and function of leptin [ 24 , 25 ]. Our unpublished study showed that high fat diet resulted in insulin resistance and higher serum leptin level in rats. Treatment of these insulin resistant rats with PPARγ agonist GW7845 improved insulin sensitivity, but did not affect serum leptin level. Therefore leptin is not considered to be a marker for PPARγ efficacy. There are indices for in vivo PPARγ activation (i.g., adipose FABP3 mRNA), or for in vivo PPARγ efficacy on insulin sensitization (i.g., serum insulin and glucose). These indices can not be used to represent both in vivo PPARγ activation and in vivo PPARγ efficacy on insulin sensitization. It is well known that circulating adiponectin increases insulin sensitivity [ 10 ], is decreased in T2D patients [ 10 - 13 ], and is negatively correlated with insulin resistance [ 22 ]; PPARγ agonists increase insulin sensitivity as well as circulating adiponectin [ 17 , 18 ]. The correlations, serum adiponectin vs adipose FABP3 mRNA and serum adiponectin vs insulin/lipids, in our study demonstrated that serum adiponectin is a good biomarker for both in vivo PPARγ activation and in vivo PPARγ efficacy on insulin sensitization. Conclusions These studies demonstrated that in both diet-induced and genetic rat models of insulin resistant (metabolic) syndrome the full PPARγ agonists GI262570, GW347845, and pioglitazone significantly elevated serum adiponectin levels, increased adipose transcription of the PPARγ response gene FABP3, and were efficacious as expected. This is the first demonstration of correlation among PPARγ agonist-increased serum adiponectin, PPARγ agonist response gene mRNA, and PPARγ agonist-mediated efficacy in insulin sensitivity and lipid lowering. These data indicate that serum adiponectin can serve as a biomarker for both in vivo PPARγ activation and PPARγ agonist-induced efficacy in rats. Methods Experimental animal and protocols All procedures performed were in compliance with the Animal Welfare Act and U.S. Department of Agriculture regulations, and were approved by the GlaxoSmithKline Animal Care and Use Committee. Male caesarian derived Sprague Dawley rats (SD, 225–250 g) (Charles River, Indianapolis, IN) were fed rodent chow Purina 5001 (Harlan Teklad, Indianapolis, IN). Male Zucker diabetic fatty (ZDF) and male Zucker lean rats (8 weeks old) (Genetic Models, Indianapolis, IN) were fed Formulab Diet 5008 (PMI Feeds, Richmond, IN). After an adaptation period of 1 week, SD rats were fed a HF diet (TD88137, Containing 34.146% sucrose. 42% of calories from fat. Harlan Teklad, Indianapolis, IN) for 4 weeks. SD Rats fed chow Purina 5001 served as normal diet control. SD rats on HF diet were treated with vehicle (0.5% hydroxypropyl methylcellulose and 0.1% Tween 80), PPARγ agonist GI262570 [ 7 , 26 - 28 ] (0.2, 2, 20, or 100 mg/kg, QD), or PPARγ agonist GW347845 (3 mg/kg, BID) for the last 2 weeks. ZDF rats were gavaged twice daily for 14 days with vehicle, PPARγ agonist pioglitazone [ 4 ] (3, 10, or 30 mg/kg), or PPARγ agonist GW347845 (3 mg/kg) [ 29 , 30 ]. Zucker lean rats were gavaged twice daily for 14 days with vehicle. One day prior to the end of dosing (after 13 days of dosing), serum was obtained from tail vein of SD rats for determining postprandial levels of glucose, insulin, triglycerides, free fatty acids, and adiponectin. The SD rats were then implanted with a jugular cannula. Oral glucose tolerant tests (OGTT) were performed in these SD rats after 14 days of dosing. At the end of the study, SD rats were euthanized with CO 2 . White adipose tissue (WAT, epididymal fat pad) were saved for determining mRNA levels of PPARγ response gene FABP3. In Zucker rats, serum was collected after 2 weeks of dosing for determining postprandial levels of glucose, insulin, triglycerides, free fatty acids, and adiponectin. Zucker rats were then euthanized with CO 2 . Determination of postprandial serum chemicals Serum glucose, triglycerides, and free fatty acids were measured using Ilab600 Clinical Chemistry System (Instrumentation Laboratory). Determination of serum adiponectin Serum adiponectin of SD rats was determined by using adiponectin RIA kit (Linco Research, MO), according to the manufacture's instruction. Serum adiponectin of ZDF rats was determined by using adiponectin ELISA kit (B-Bridge International, CA), according to the manufacture's instruction. Jugular vein cannulation Under anesthesia with isoflurane, surgical site was prepared using standard aseptic technique (with Hiboclens ® Chlorhexidine Gluconate, Zeneca Pharmaceuticals, Delaware). A longitudinal incision was made over the right external jugular vein. 5–10 mm of the vein was exposed by blunt dissection. Jugular cannula (Access™ Technologies, IL) was inserted into the vein for about 1 inch. The cannula was secured using sterile sutures. The cannula was routed subcutaneously, exteriorized between the scapulae. The cannula was then filled with dextrose-heparin solution (50:50), and heat sealed. OGTT Rats implanted with jugular cannula were fasted overnight. The following morning, dextrose (0.5 g/ml in water, 2 g/kg body weight) was administered by oral gavage. Blood samples (0.3 ml/time) were obtained from the jugular cannula before gavage, 10, 20, 30, 45, 60, 90 and 120 min after gavage. Blood glucose was immediately measured by using Elite ® XL Glucometer (Bayer, Tarrytown, NY). Serum was collected for insulin measurement. Area under curves (AUCs) for glucose and insulin during OGTT were calculated by using WinNonlin™ Noncompartmental Model 200. Determination of insulin level Serum insulin of SD rats level was determined using Rat Insulin ELISA kit (Crystal Chem Inc, IL), according to the manufacture's instruction. Serum insulin level of ZDF rats was determined using Igen's M-SERIES M-8 Analyzer (Igen International, Inc., Gaithersburg, MD). Determination of FABP3 mRNA level in white adipose tissue by real time PCR Total RNA in epididymal fat pad was isolated by the TRIZOL ® method [ 31 ]. All RNA samples were DNased using the DNA- free ™ kit (Ambion – according to protocol). The samples were then quantitated by RiboGreen™ (Molecular Probes – according to protocol). GAPDH gene expression was analyzed in the absence of reverse transcriptase to ensure the samples were free of genomic DNA. The samples were then converted to cDNA using the High Capacity cDNA Archive Kit (Applied Biosystems – according to protocol). Samples were diluted to a final concentration of 5 ng/ul of cDNA. PCR results were generated using the 5' nuclease assay (TaqMan) [ 32 ] and the ABI 7900 Sequence Detection System (Applied Biosystems, Foster City, CA). Primers and probe for FABP3 are: Forward-GTCGTGACACTGGACGGAGG; Reverse-TTCCCATCACTTAGTTCCCGTG; Probe-CAGAAGTGGGACGGGCAGGAGACTACG. The primers and probe for Cyclophilin are: Forward-TATCTGCACTGCCAAGACTGA; Reverse-CCACAATGCTCATGCCTTCTTTCA; Probe-CCAAAGACCACATGCTTGCCATCCA. A master mixture was utilized which included 900 nM each of the forward and reverse primers, 100 nM probe, and 1 × PCR master mix (Applied Biosystems). The PCR reaction consisted of 12.5 ng of cDNA in a 12.5 ul total reaction volume. The PCR cycling conditions were 95°C for 10 minutes, and 40 cycles of 95°C for 15 seconds and 60°C for 1 minute. Statistical analysis There was a minimum of 5 rats for each data point. Data are presented as mean ± SEM. Correlation between two parameters and the significant level of correlation were analyzed by Pearson correlation analysis. Differences between vehicle and treated groups were analyzed by two-way ANOVA. P less than 0.05 was taken to be significant. List of abbreviations QD: Once a day BID: Twice a day PCR: Polymerase Chain Reaction GAPDH: Glyceraldehyde-3-Phosphate Dehydrogenase ANOVA: Analysis of Variance Authors' contributions BY is the principal investigator. LC, LGC, JM, and DW participated in the in vivo experiments. KC and JS performed the real time PCR. KB, SS and GP participated in study design and manuscript preparation.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526775.xml
524176	Participant characteristics associated with withdrawal from a large randomized trial of spermicide effectiveness	Background In most recent large efficacy trials of barrier contraceptive methods, a high proportion of participants withdrew before the intended end of follow-up. The objective of this analysis was to explore characteristics of participants who failed to complete seven months of planned participation in a trial of spermicide efficacy. Methods Trial participants were expected to use the assigned spermicide for contraception for 7 months or until pregnancy occurred. In bivariable and multivariable analyses, we assessed the associations between failure to complete the trial and 17 pre-specified baseline characteristics. In addition, among women who participated for at least 6 weeks, we evaluated the relationships between failure to complete, various features of their first 6 weeks of experience with the spermicide, and characteristics of the study centers and population. Results Of the 1514 participants in this analysis, 635 (42%) failed to complete the study for reasons other than pregnancy. Women were significantly less likely to complete if they were younger or unmarried, had intercourse at least 8 times per month, or were enrolled at a university center or at a center that enrolled fewer than 4 participants per month. Noncompliance with study procedures in the first 6 weeks was also associated with subsequent early withdrawal, but dissatisfaction with the spermicide was not. However, many participants without these risk factors withdrew early. Conclusions Failure to complete is a major problem in barrier method trials that seriously compromises the interpretation of results. Targeting retention efforts at women at high risk for early withdrawal is not likely to address the problem sufficiently.	Background Retention of participants has been a consistent problem in clinical studies of barrier contraceptive methods. For example, in six large studies of condoms, diaphragms, and spermicides conducted in the past decade, more than 30% of the participants failed for reasons other than pregnancy to complete the intended six months or six menstrual cycles of follow-up [ 1 - 6 ] Such high dropout rates seriously compromise the interpretation of trial results. Issues regarding the design of barrier method studies have become increasingly important to researchers and public health scientists since the onset of the HIV epidemic because of the urgent need for methods to prevent this disease and other sexually transmitted infections. Numerous new barrier contraceptive methods and microbicides are currently in various stages of development and testing. Devising effective approaches to maximize retention in these studies will be critical. In this analysis, we used data from a large, recently completed randomized trial of the efficacy and safety of five spermicide products to determine whether we could identify specific subgroups of participants who were at particular risk for failure to complete the trial. Our goal was to provide information that might assist in the development of targeted approaches to improve follow-up in future trials. Methods The primary purpose of this randomized trial was to estimate and compare the probability of pregnancy during six months of typical use of five nonoxynol-9 spermicide products. Safety, acceptability, and product use were additional specified outcomes. The trial was conducted at 14 sites in the United States between June 1998 and August 2002. The study was approved by the institutional review boards at each site and at Family Health International. All participants signed written informed consent forms before enrollment. A full description of the trial procedures has been published previously [ 7 ]. In brief, the study enrolled 1536 healthy, sexually active women aged 18–40 years who had no history suggestive of subfecundity, who were at low risk for sexually transmitted infections, and who stated that they were willing to rely on a spermicide as their only contraceptive method for 7 months and to accept a moderate risk of pregnancy. At the enrollment visit, each volunteer had an interview, pelvic examination, Pap smear, wet prep, and urine pregnancy test. After eligibility was established, she completed a self administered questionnaire that included a question about strength of desire to avoid pregnancy. Each eligible participant was randomly assigned to one of the five study spermicide groups. She was given a supply of her assigned spermicide and a diary on which to record relevant information daily throughout the study. Some participants at two centers were enrolled into a substudy to evaluate colposcopic effects of the spermicides. Participants were encouraged but not required to inform their partners about the study except at one center, where the Institutional Review Board required signed consent of the partner. Follow-up visits were scheduled at 4, 17, and 30 weeks after admission. Each participant was also asked to return to the study site if she wished to discontinue use of the spermicide. At each visit, the participant was interviewed, and a urine pregnancy test was done. At the 4-week and final visits, she completed a seven-page acceptability questionnaire. A pelvic examination was performed at the final visit and at other visits as indicated. Colposcopy substudy participants had a vaginal colposcopy at each follow-up visit. Each participant was asked to do a pregnancy test at home 2, 10, and 23 weeks after admission and to telephone the site with the result. If a participant missed a scheduled contact, study procedures required that staff make at least four attempts to contact her by at least two different modalities (telephone, mail, etc.) If they could not contact her directly, staff were to try to reach her through an alternate contact person identified by the participant at admission. Compensation for completion of all scheduled visits in the primary study ranged from $120 to $400 at the 14 study sites; at most sites, the amount was divided evenly among the separate visits. In this analysis, we included all randomized participants except for 22 who were discovered to have been pregnant at admission and who therefore contributed no data to the primary analysis. We classified each of the remaining 1514 participants as having completed the study if she considered the spermicide to be her primary contraceptive method for at least 183 days after randomization, or she became pregnant before she stopped relying on it. Otherwise, she was classified as having failed to complete the study. We assigned each participant's last day in the analysis as the earliest of the following dates: the estimated date of fertilization of a pregnancy; the date she was last known to have been relying primarily on the assigned spermicide for contraception; the latest date her pregnancy status could be reliably determined; and 183 days after randomization. These rules were the same as those used in the prior primary pregnancy analyses [ 7 ]. We assessed the associations between failure to complete and 17 baseline factors of interest, which were prespecified before the analysis. Among the subset of participants who were in the analysis for at least 6 weeks, we examined the associations between final status category and various factors that characterized their experience during the first 6 weeks in the study. Factors were categorized in part to ensure substantial numbers of participants in each level. Hypotheses about the effects of factors on completion status were tested using chi square tests, Fisher's exact tests, Mantel Haenszel tests. Parameters estimated by multivariable logistic regressions were tested using Wald tests. We included factors in regression models if they were associated with the outcome (alpha<0.10) in bivariable analyses. None of the included factors were highly correlated. In both bivariable and multivariable analyses, a p-value of <0.05 was considered to indicate a significant association. Results Of the 1514 participants in this analysis, 635 (42%) failed to complete the study for reasons other than pregnancy. The proportion who withdrew early at each of the 14 study sites ranged from 17% to 83%. Only 3 centers had completion rates ≥65%. Forty nine participants (8% of those who withdrew) were discontinued by the site investigator because of a concern about their safety (such as increased risk of sexually transmitted infection that would indicate need for condom use, or use of a drug contraindicated in pregnancy that would indicate need for a more effective contraceptive than spermicide alone), staff error, or closure of the trial at the study site (Table 1 ). Of the 586 who withdrew on their own accord, 382 (65%) did not provide a reason, in most cases because they did not return for a discontinuation visit. The other 204 women reported a variety of reasons; 99 cited complaints that might have been related in some way to the spermicide. Of the other 105 participants, only 31 said that they would like to continue using the spermicide after leaving the study. Table 1 Reasons for early withdrawal Reason Participants N = 635 n % Discontinued by site Safety concerns 38 6% Site closure/staff error 11 2% Participant decision, reason provided* 204 32% Unwillingness to continue study visits 60 9% Objections from partner † 48 8% Desire to change contraceptive method † 42 7% Separation from partner 40 6% Side effects or other medical events † 37 6% Cessation of sexual activity 18 3% Dissatisfaction with spermicide † 8 1% Distrusted contraceptive efficacy † 8 1% Desire for pregnancy 7 1% Mistaken suspicion of pregnancy 4 1% Participant decision, reason unknown 382 60% Participants may have provided more than one reason † Considered "related to spermicide" in text During their time in the analysis, women who failed to complete the study were less compliant with follow-up visits and diary records than women who completed (Table 2 ). Twenty-one percent of the population (135 participants) contributed no data at all to the analysis after admission. Table 2 Protocol compliance by final status category Final status category p-value † Completed study Did not complete study Number of participants 879 (58%) 635 (42%) Median days in analysis per participant 183 32 Mean % of expected follow-up visits completed 85% 64% <.0001 Mean % of expected diary days recorded* 97% 72% <.0001 Mean % of expected pregnancy tests completed* 95% 97% 0.0001 The number of expected visits was prorated for each participant considering the total duration of her participation in the analysis † p-value from independent sample t-test. Of the 17 baseline factors examined separately, nine were associated with significantly increased (p < 0.05) relative risk of failure to complete the trial (Table 3 ). Factors that did not significantly increase risk included spermicide group, race, educational level, prior spermicide use, strength of desire to avoid pregnancy as reported on the self-administered admission questionnaire, desire for additional children, reason for choosing spermicide as a contraceptive method, and enrollment date relative to notification in 1999 of new data suggesting concern about the possibility that nonoxynol-9 might affect the risk of HIV acquisition. In multivariable analyses including the nine high risk factors and one additional factor (level of schooling, which was marginally associated with withdrawal, p = 0.09), only the associations with young age, unmarried status, frequent intercourse, enrollment at a university center, and enrollment at a center with a lower recruitment rate remained significant. Table 3 Association between baseline factors and failure to complete study Total Did not complete study Relative Risk (95% confidence interval) N n % Age ≤25 years 660 317 48.0 1.29 (1.15 – 1.45) > 25 years 854 318 37.2 1 Relationship single not living with partner 522 247 47.3 1.21 (1.07 – 1.36) married or living with partner 992 388 39.1 1 Living children None 639 288 45.1 1.14 (1.0 1 – 1.28) Any 875 347 39.7 1 Baseline coital frequency ≥8 acts per month 862 389 45.1 1.21 (1.07 – 1.37) ≤7 acts per month 640 239 37.3 1 Geographic region of US West 424 215 50.7 1.28 (1.12 – 1.46) South 460 170 37.0 0.93 (0.80 – 1.09) Northeast 630 250 39.7 1 Center type university 1069 476 44.5 1.25 (1.08 – 1.44) other 445 159 35.7 1 Recruitment rate at study site ≤4 per month 640 301 47.0 1.23 (1.09 – 1.38) > 4 per month 874 334 38.2 1 Reimbursement rate ≤$200 462 232 50.2 1.31 (1.16 – 1.47) >$200 1052 403 38.3 1 Participation in colposcopy study No 1381 590 42.7 1.26 (0.99, 1.61) † Yes 133 45 33.8 1 University centers were defined as those at which participants were seen in a primary university clinic setting. These included: University of Alabama at Birmingham, Birmingham, AL; University of Tennessee at Memphis, Memphis, TN; The University of Texas Health Science Center at San Antonio, San Antonio, TX; Baylor College of Medicine, Houston, TX; Medical University of South Carolina, Charleston, SC; University of Pittsburgh and the Magee-Womens Research Institute, Pittsburgh, PA; University of Pennsylvania Medical Center, Philadelphia, PA; University of Arizona Health Sciences Center, Tucson, AZ; NYU School of Medicine, New York, NY. Other centers included: Johns Hopkins Medical Services Corporation, Baltimore, MD; Vermont Women's Choice Program of Planned Parenthood, Burlington, VT; Eastern Virginia Medical School, Norfolk, VA; Minneapolis Medical Research Foundation, Minneapolis, MN; Planned Parenthood of Central and Northern Arizona, Phoenix, AZ † Although this confidence limit includes 1, the p-value for the association between this factor and early withdrawal was 0.047. Of the 1095 participants who contributed more than 6 weeks to the analysis, those who in their first 6 weeks were not compliant with follow-up visits, coital diary completion, or use of the spermicide during sex were significantly less likely than others to complete the study (Table 4 ). However, among the 925 participants who completed a contact during the initial 6 weeks, neither reported complaints nor any measure of satisfaction with the spermicide during the first 6 weeks was associated with increased risk of early withdrawal. We created a single variable to indicate whether or not each subject was "happy" with the spermicide in the first 6 weeks after admission (i.e., she found it acceptable, had no side effect or adverse event, and had a satisfied partner). Women who were "happy" were not significantly less likely than other women to withdraw early. Table 4 Association between early study experience and failure to complete study Experience during first 6 weeks Total Did not complete study Relative Risk (95% confidence interval) N n % Completed at least one follow-up visit yes 925 203 21.9 0.68 (0.53 – 0.87) no 170 55 32.4 1 Completed at least one pregnancy test within first 4 weeks yes 1070 250 23.4 0.73 (0.41 – 1.31) no 25 8 32.0 1 Provided diary information for each day yes 958 215 22.4 0.71 (0.54 – 0.94) no 137 43 31.4 1 Used spermicide at every coital act yes 739 153 20.7 0.70 (0.57 – 0.87) no 356 105 29.5 1 Of those who completed follow-up visit Reported medical complaints yes 437 104 23.8 1.17 (0.92 – 1.50) no 488 99 20.3 1 Disliked spermicide somewhat or a lot yes 52 12 23.1 1.05 (0.63 – 1.76) no 873 191 21.9 1 Distrusted contraceptive efficacy yes 209 51 24.4 1.15 (0.87 – 1.52) no 716 152 21.2 1 Disliked timing of application yes 435 96 22.1 1.01 (0.79 – 1.29) no 490 107 21.8 1 Complained about messiness yes 375 76 20.3 0.88 (0.68 – 1.13) no 550 127 23.1 1 Had problems with insertion yes 465 105 22.6 1.06 (0.83 – 1.35) no 460 98 21.3 1 Reported that partner disliked spermicide yes 208 52 25.0 1.18 (0.90 – 1.56) no 717 151 21.1 1 Happy with spermicide † yes 408 80 19.6 0.82 (0.64 – 1.05) no 517 123 23.8 1 *Includes only participants in the analysis for at least 6 weeks † Did not dislike spermicide, had no side effect/AE, and had a satisfied partner Discussion and conclusions In analyzing data from longitudinal studies, researchers commonly assume that the experience of participants who withdraw early, had they stayed in the study, would have been similar to the experience of those who completed. However, this assumption is generally impossible to confirm and is often implausible. If the assumption is false, the study findings may substantially misrepresent the likelihood of the outcome in the study population. If the degree of misrepresentation is not consistent across study groups, comparisons could be seriously biased. Indeed, some expert epidemiologists have suggested that a trial with losses of greater than 20% of the participants "would be unlikely to successfully withstand challenges to its validity" [ 8 , 9 ]. Our study, like other recent barrier contraceptive method studies, did not even approach this standard: 42% of our enrolled participants did not complete the trial. Furthermore, the participants who failed to complete were different in key ways from those who did – they reported significantly more frequent coitus at baseline, and they also were more likely to be younger, unmarried, and poorly compliant with study procedures and method use in the first few weeks after admission. All of these characteristics were associated to some extent with elevated risk of pregnancy in our population [ 7 ], which suggests that our high withdrawal rate indeed may have distorted our findings: the pregnancy probabilities that we reported may be underestimates. Clearly, increased attention to preventing this problem in future studies is imperative. In performing this analysis, our intention was to explore the potential impact of focusing retention efforts on participants with characteristics that are associated with failure to complete. However, although we did find some factors that were significantly associated with early withdrawal, none was highly predictive; that is, many participants without these factors failed to complete the study, and many with these factors did complete. Therefore, applying special efforts only to the high-risk participants would not likely have been sufficient to raise completion rates to desirable levels. In future trials, aggressive follow-up measures should be instituted universally. Such efforts might include assigning individual "case-workers" to participants, using novel means for communicating with the participants, such as pagers, conducting visits at participants' homes or at other locations convenient for them, providing specific reimbursement for expenses such as travel, parking, and child care, or providing extra incentives for completing follow-up. Researchers should be mindful, however, that one downside to some of these approaches is that they might influence participants' use of the study product or other behaviors related to the study outcome, which is detrimental if the goal of the trial is to estimate effectiveness during "typical use" of the product. In our study, participants who enrolled at study centers where enrollment was slow were at increased risk of failure to complete the study. The reason for this association is unclear. Factors at these centers that hindered enrollment also may have adversely affected participants' interest in remaining in the study. Alternatively, in responding to pressure to hasten recruitment, these centers may have enrolled women who were not good candidates for study completion. This latter possibility emphasizes the need to maintain a careful balance between recruitment and retention goals: rapid recruitment of participants who then drop out of the study is not beneficial to the study as a whole. The amount of reimbursement promised to our participants was strongly associated with final completion status in the bivariable analysis, but this effect was not significant when adjusted for other factors in our multivariable model. Numerous prior studies have shown that modest monetary incentives (e.g., $20 or less) increase response rates to surveys or short follow-up studies [ 10 , 11 ] Some data also suggest that the value of the incentive matters, although possibly with diminishing returns as the value increases [ 12 , 13 ]. However, the effect of higher levels of compensation in longer trials such as ours has not been rigorously studied. The possibilities that large financial incentives could be coercive, weaken generalizability, or encourage bogus participation are important concerns [ 14 ]. We were surprised that several of the factors that we expected would be associated with early withdrawal did not show significant associations in this analysis. When we began this analysis, we presumed that one reason for both slow enrollment and poor follow-up rates in barrier method trials is the relatively poor efficacy of these products: women may consider them to be temporary or backup methods and thus may be unwilling to use them as their sole or primary contraceptive for the 6–12 month duration of these studies. However, in our study, participants who strongly wished to avoid pregnancy or who had completed their desired family size were not more likely than others to drop out, nor were participants who expressed concerns about contraceptive efficacy early in the trial. Furthermore, neither early medical problems nor other complaints about the spermicides were predictive of withdrawal. These findings differ from that of a previous randomized trial of spermicides conducted mostly in developing countries. In that trial, participants who initially liked the assigned product very much were more likely than others subsequently to complete the study and to use the product for a longer period of time after admission [ 15 ]. In one respect, the poor retention rate in our study and in other barrier method trials is a result of the design of these studies, which typically call for censoring data (and in most barrier method trials, terminating active follow-up) when participants stop relying on the assigned contraceptive method. This design prohibits a true intent-to-treat analysis and is consequently a potential source of bias. Clearly, retention would be higher if the trials were designed at the outset to follow all subjects for the full intended duration of follow-up, even if they switched contraceptive methods. However, data from participants who are not using the method under study are not necessarily relevant to the efficacy and safety of the method. For the results of these trials to be meaningful, as many subjects as possible must not only complete follow-up but also continue to use the method during the full follow-up period. In our study, almost all the women who gave a reason for withdrawing early either cited problems with the spermicide or indicated that they wished to switch to another method after leaving the study. Our results are consistent with the findings of the 1995 National Survey of Family Growth, which showed that more than 47% of US spermicide users stopped relying on the method within the first 6 months of use [ 16 ]. These findings are discouraging: they suggest that even if the retention in the study could be improved by aggressive follow-up techniques, the likelihood of significant extension of method use is low. Our results suggest that to reduce bias potentially introduced by a large proportion of participants failing to complete the study, future barrier contraceptive method researchers should consider approaches in addition to those directly aimed at tracking and retaining individual participants. For example, both to reduce the burden on participants and to help the study staff maintain focus on follow-up, limiting data collection to critical variables may be appropriate. Complete collection of key data is clearly preferable to inadequate collection of less important data. Reducing the planned duration of follow-up would also certainly reduce withdrawals; although a larger sample size would be needed to provide the desired levels of precision and power, this disadvantage might be overcome if the shorter study were more attractive to potential participants. Given the large proportion of women who stop using the method earlier than 6 months, it is not clear that 6-month pregnancy probabilities are clinically needed anyway. Adding a run-in period to the trial before randomization might be helpful in excluding participants likely to drop out very early after admission, although such an addition might deter enrollment of other women as well, which is also a problem in these trials. Finally, innovative study designs to measure product efficacy should be evaluated. The design proposed by Steiner et al., which compares the one-month pregnancy probability in a relatively small number of women using a contraceptive method to the probability in women using a placebo, offers an alternative to the traditional 6–12 month trial [ 17 ]. It showed some promise in a pilot study and is currently being further tested in a study of a new candidate spermicide. Competing interests No authors have any declared interests except the following: Elizabeth Raymond owns stock in Johnson and Johnson. Mitchell Creinin serves as a speaker for Ortho. Alfred Poindexter has had research grants from Columbia Laboratories and serves as speaker for Ortho. Authors' contributions EGR helped design the trial, managed the trial, planned this analysis, and drafted the manuscript. PLC and BPL helped design the trial and/or this analysis, performed the analysis, and contributed to the manuscript. JL designed the trial and contributed to the manuscript. Other authors participated in the design of the trial, conducted the trial, and contributed to the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524176.xml
423143	Integrin Bidirectional Signaling: A Molecular View	Cells receive and send signals across the plasma membrane using the integrin family of receptors. What is it about their structure that can mediate their function?	It goes without saying that the cellular plasma membrane effectively creates a barrier between the inside (intracellular area) and outside (extracellular area) of the cell it defines. In order for the cell to sense and respond to its environment (including other cells and the supporting structures that comprise the extracellular matrix [ECM]) and for the environment to influence cell function (including cell growth and movement), bidirectional signaling across the plasma membrane has to be mediated by receptors and other structures. About two decades ago, it became widely appreciated that many of the cell surface receptors that mediate cell–cell and cell–ECM interactions were structurally and functionally related, and the term “integrins” was coined to reflect the capacity of members of this family to integrate the extracellular and intracellular environment ( Hynes 1987 ). Integrin-mediated interactions are vital to the maintenance of normal cell functioning because of their ability to mediate inside-out (intracellular to extracellular) and outside-in (extracellular to intracellular) signaling. Integrin dysfunctions are associated with numerous human disorders such as thrombosis, atherosclerosis, cancer, and chronic inflammatory diseases. Despite a total of nearly 30,000 integrin-related articles in the literature, intensive effort—more than 200 articles per month—continues to focus on understanding the roles of integrins in both physiological and pathological processes. The Integrin Family The integrin family comprises 20 or more members that are found in many animal species, ranging from sponges to mammals ( Hynes 2002 ). They consist of two distinct, associated subunits (noncovalent heterodimers), where each subunit (α, β) consists of a single transmembrane domain, a large extracellular domain of several hundred amino acids (composed of multiple structural domains), and typically, a small cytoplasmic domain of somewhere between 20–70 residues ( Figure 1 ). The extracellular domains bind a wide variety of ligands, whereas the intracellular cytoplasmic domains anchor to cytoskeletal proteins. In this manner, the exterior and interior of a cell are physically linked, which allows for bidirectional transmission of mechanical and biochemical signals across the plasma membrane, and leads to a cooperative regulation of cell functions, including adhesion, migration, growth, and differentiation. A central topic in the integrin research over the past decade has been the mechanism of inside-out activation ( Liddington and Ginsberg 2002 ). In their resting state, integrins normally bind the molecules that activate them with low affinity. Upon stimulation, a cellular signal induces a conformational change in the integrin cytoplasmic domain that propagates to the extracellular domain. Integrins are transformed from a low- to a highaffinity ligand binding state. Such inside-out regulation of integrin affinity states is distinct from the outside-in signaling observed upon activation of most other transmembrane receptors (e.g., growth factor–growth factor receptor interactions), including integrins. The inside-out signaling protects the host from excessive integrin-mediated cell adhesion, which could, for example, lead to spontaneous aggregation of blood cells and have profound pathological consequences. Figure 1 A Model for Integrin Inside-Out Activation and Clustering Cellular stimulation induces a conformational change in talin that exposes its talin head domain. The talin head domain binds to the β cytoplasmic tail, which displaces the α tail from its complex with the β tail, which in turn leads to an unclasping and a membrane-associated structural change of the cytoplasmic face ( Vinogradova et al. 2002 , 2004 ). Notice the proposed shifted membrane interface for both membrane-proximal helices before and after unclasping (green bars), which suggests a “fanning-out” unclasping process ( Vinogradova et al. 2004 ). The unclasping initiates the opening of the integrin C-terminal stalks—including the transmembrane domains ( Luo et al. 2004 )—which is necessary for the switchblade shift of the extracellular headpiece from the bent to the extended form for high-affinity ligand binding ( Takagi et al. 2002 ). The α subunit is in blue and the β subunit is in red. The ligated integrins cluster, possibly via oligomerization of transmembrane domains ( Li et al. 2003 ). The model was generated based on the crystal structure of α v β 3 extracellular domain ( Xiong et al. 2001 ) and the nuclear magnetic resonance structure of the cytoplasmic domain ( Vinogradova et al. 2002 , 2004 ) with the helices extending to the transmembrane domain. The Heads and Tails of Inside-Out Signaling Mutational studies provided the initial hints that disruption of the non-covalent clasp between α and β cytoplasmic tails is clearly the event within the structure of the integrin that initiates inside-out signaling. Point mutations in the α and β cytoplasmic tails that are near the membrane or deletion of either region result in constitutive activation of the receptor ( O'Toole et al. 1991 , 1994 ; Hughes et al. 1995 ). Mutating a single specific residue in the cytoplasmic tail of either subunit led to integrin activation, but a double mutation, which would have allowed retention of a salt bridge between the subunits, did not ( Hughes et al. 1996 )—suggesting that integrin inside-out activation is dependent upon regulation of the interaction between the two subunits. In support of this hypothesis, peptides corresponding to α and β cytoplasmic tails have been shown to interact with each other ( Haas and Plow 1996 ). Since these original observations, there has been an intensive effort to understand the mechanism for regulation of integrin activation by the cytoplasmic region (for a recent review, see Hynes 2002 ). On the road toward this goal, Ginsberg and colleagues discovered that the head domain of a cytoskeletal protein—talin—plays a key role in binding to integrin β cytoplasmic tails and inducing integrin activation ( Calderwood et al. 1999 ). Many other intracellular proteins bind to the α and β cytoplasmic tails ( Liu et al. 2000 ), but the importance of talin in integrin activation is particularly convincing since it has been confirmed by multiple laboratories ( Vinogradova et al. 2002 ; Kim et al. 2003 ; Tremuth et al. 2004 ) using various methods including overexpression and gene knockdown (siRNA) approaches ( Tadokoro et al. 2003 ). In 2001, Springer and coworkers provided evidence for a model by which separation of the C-terminal portions of the α and β subunits results in inside-out activation. They showed that replacement of the cytoplasmic-transmembrane regions by an artificial linkage between the tails inactivates the receptor, whereas breakage of the clasp activates the receptor ( Lu et al. 2001 ; Takagi et al. 2001 ). Shortly thereafter, the model gained direct and strong experimental support from a structural analysis in which the membrane-proximal helices of the two subunits were found to clasp in a weak “handshake” that could be disrupted by talin or constitutively activating mutations ( Vinogradova et al. 2002 ). The model has been further verified by other biophysical studies ( Kim et al. 2003 ) and extended to other integrins ( Vinogradova et al. 2004 ). Since the membrane-proximal regions of integrin α and β cytoplasmic tails are highly conserved, the generalization of this signaling mechanism to all integrins was to be anticipated. A dynamic image of how such cytoplasmic unclasping occurs at the membrane surface can now be modeled ( Figure 1 ) ( Vinogradova et al. 2004 ). Straightening Out the Outside On the extracellular side, ground-breaking insights were provided when the crystal structure of the extracellular domain of integrin α v β 3 (the nomenclature identifies the particular α and β subunits) was determined ( Xiong et al. 2001 ). In addition to the exquisite structural details, the overall conformation was surprisingly bent ( Figure 1 ), which contrasted with structures revealed by the earlier electron micrographic studies that showed an extended, stalk-like structure ( Weisel et al. 1992 ). Springer and coworkers used a series of biochemical/biophysical experiments to suggest that the bent structure represents an inactive form of integrin ( Takagi et al. 2002 ), whereas activation induces a switchblade shift that converts the bent form to the extended form ( Figure 1 ). A molecular picture has emerged for integrin insideout activation where a cellular signal induces the conformational change of talin exposing its head domain allowing it to bind to the integrin β cytoplasmic tail. This interaction unclasps the complex between the cytoplasmic tails, which then allows a conformational shift in the extracellular domain from a bent to a more extended form for high-affinity ligand binding ( Figure 1 ) ( Takagi et al. 2002 ). The activated integrins may then undergo clustering whereby the transmembrane domain of each type of subunit (the α or β) interacts with itself—called homotypic oligomerization of the transmembrane domains ( Figure 1 ) ( Li et al. 2003 ). Ligand occupancy and receptor clustering initiates outside-in signaling that, in turn, regulates a variety of cellular responses (see below). The three steps in Figure 1 occur as part of a dynamic equilibrium, and perturbation of any step can shift the equilibrium, leading to transient, partial, or permanent integrin activation/inactivation depending on the extent of perturbation. For example, deletion of aIIb cytoplasmic tail completely removes the clasp and permanently activates the receptor ( O'Toole et al. 1991 ), whereas a particular disease mutation may only impair the clasp and partially activate the receptor (Peyruchaud et al. 1997). While the model in Figure 1 is based on direct structural evidence for the cytoplasmic face ( Vinogradova et al. 2002 ; Kim et al. 2003 ) and the extracellular domain ( Takagi et al. 2002 ), the changes in the transmembrane region remained speculative. In this issue of PLoS Biology , Luo et al. (2004) provide what is, to our knowledge, the first experimental evidence for the transmembrane domain separation, an event suggested by the model shown in Figure 1 . By selectively altering the residues that can interact with one another, the authors defined a specific transmembrane domain interface in resting α IIb β 3 and showed that this interface is lost upon activation of this integrin. Backed by extensive structural and biochemical data on the integrin cytoplasmic/extracellular domains, this transmembrane domain study takes the next vital step toward a more complete understanding of the unclasping mechanism for integrin activation. Although the energy required for lateral separation of the transmembrane domains in membrane appears to be high, the third step in Figure 1 (clustering via transmembrane domain oligomerization) may compensate for it. Filling in the Pieces Despite the molecular level of our understanding of integrin activation, a number of key questions remain unresolved. Although we know that the membrane-proximal clasp on the integrin cytoplasmic face controls the integrin activation, the distal side of either the α or β cytoplasmic tails may also play a role in integrin activation, since other mutations indicate that the C-terminal membrane distal region is important in regulating integrin activation via a mechanism that is yet unknown. Thus, the picture for the cytoplasmic face-controlled inside-out activation may be substantially more complicated than specified in Figure 1 . There may exist other factors, such as negative regulators, in cells that bind to the cytoplasmic tails or their complex, and control the conformational change required for integrin activation. Also, there may be pathways other than the talin-mediated one that lead to integrin activation. Structures of the integrin cytoplasmic face bound to talin and the many other proteins known to bind to the cytoplasmic tails of integrins will undoubtedly provide further insights. In the transmembrane region, although there is ample evidence for heterodimeric transmembrane domain association ( Adair and Yeager 2002 ; Schneider and Engelman 2003 ; Gottschalk and Kessler 2004 ; Luo et al. 2004 ) and dissociation upon integrin activation ( Luo et al. 2004 ), a definitive structural view is missing. Some studies have proposed that homo-oligomerization is essential for inducing integrin activation ( Li et al. 2003 ). However, the data provided by Luo et al. do not appear to support this model. On the extracellular side, while the C-terminal unclasping and separation of the cytoplasmic and transmembrane regions appears to relieve the structural constraint and may allow the unbending of the extracellular domain to attain the high-affinity ligand binding state ( Takagi et al. 2002 ), a thorough molecular understanding of this process awaits high resolution structures of the intact receptor in inactive and active forms. What About Outside-In? Upon the inside-out activation, integrins bind to specific extracellular matrix proteins. However, for the integrins to grip tightly to the extracellular matrix to mediate cell adhesion and migration, the integrin cytoplasmic domains must be anchored to the cytoskeleton ( Giancotti and Ruoslahti 1999 ). This is achieved by “outside-in” signaling, i.e., when an integrin binds to the extracellular ligand, it clusters with other bound integrins, resulting in the formation of highly organized intracellular complexes known as focal adhesions that are connected to the cytoskeleton. The focal adhesions incorporate a variety of molecules, including the cytoplasmic domains of the clustered integrins, cytoskeletal proteins, and an extensive array of signaling molecules. The high local concentrations of these molecules facilitate cascades of downstream intracellular responses via protein–protein interactions, which are linked to the cytoskeleton as well as to complex intracellular signaling networks. Although many intracellular components involved in outsidein signaling have been identified, and much has been learned about various signaling pathways involved in outside-in signaling ( Giancotti and Ruoslahti 1999 ), a molecular view of how the various events occur in time and space is still very uncertain. In particular, little structural insight has been obtained for early outside-in intracellular events following ECM–integrin binding, e.g., upon ECM engagement. How is the integrin cytoplasmic domain connected to the cytoskeleton? How is this connection regulated during cell adhesion and migration? The next wave of structural information may provide insights into these important and fertile areas of investigation.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC423143.xml
529308	The role of thallium-201 and pentavalent dimercaptosuccinic acid for staging cartilaginous tumours	Introduction Heterogeneity of cartilage tumours may confound accurate diagnosis and grading resulting in under and over treatment. Improved preoperative assessment of malignancy and grade would be invaluable for developing a rational plan for treatment. We examined correlations between nuclear tracer avidity and malignancy grade in cartilage tumours. Methods Between 1996 and 2000, 92 consecutive patients with cartilaginous tumours (50 benign, 42 non-metastatic malignant) underwent nuclear scanning. Thallium-201 (TL-201) and pentavalent dimercaptosuccinic acid (DMSAV) were used as nuclear isotopes. Scanning with these agents was performed on separate days 48 hours apart. Static and SPECT images were obtained at 30 m and 4 h after injection of nuclear tracer. Pathology review was undertaken blinded to the results of the nuclear scans and correlations between histologic results and trace uptake at 4 hours examined. Results 25 patients with negative DMSAV had benign tumours. 15/17 tumours with positive TL-201 had malignant tumours. 11/13 patients with both positive DMSAV and TL-201 scans had intermediate or high grade tumours and 4 of these developed metastases. We have developed an algorithm for the management of patients with tumours that aims to avoid over treatment of low grade tumours and under treatment of high grade tumours. Conclusion Functional nuclear scanning with TL-201 and DMSAV complements other imaging modalities in the management of cartilaginous tumours.	Background Traditionally, the determination of malignancy and its grade in cartilage tumours has been from the combination of history, radiographic features with or without computed tomography and histologic examination [ 1 - 3 ]. More recently, magnetic resonance imaging has also been employed [ 4 - 6 ]. However, cartilage tumours are recognized for their histologic heterogeneity [ 7 - 9 ] and bizarre physical features, such that reliance on anatomic imaging and accuracy of biopsy alone for interpretation of state of malignancy or benignity may be misleading. While the recognition of high grade malignancy is not difficult, the differentiation between benign and low grade (grade I) tumours can present a diagnostic dilemma [ 10 , 11 ]. Such a dilemma may lead inadvertently to under-or over-treatment of cartilage tumours. Functional nuclear scans employ isotopes that become substrates for various cellular metabolic cycles and therefore, are useful for determining the metabolic activity in these tissues [ 12 ]. Given that malignant tumours are more metabolically active than benign tumours, and that there is a relationship between grade of malignancy and metabolic activity, functional nuclear scans may help to differentiate between cartilage tumours of varying metabolic activity, which in turn, may shed some light on their state of malignancy. We now report our experiences with 2 radio-siotopes, Thallium-201 (Tl-201) and pentavalent dimercaptosuccinic acid (DMSAV) for determining the metabolic activity of cartilage tumours, and their value in differentiating between malignant and benign cartilage tumours in 92 consecutive cartilage tumours. We describe their role in the development of our current regimen for treating cartilage tumours. Methods Patients Between January 1997 and December 2000, 92 consecutive patients were referred to our institution for investigation and management of suspected chondral tumours. There were 50 females and 42 males with a median age of 45 years (range 16–87 years). Tumours were located in the humerus (17), chest wall (3), femur (27), hand (3), knee (3), vertebra (1), scapula (7), tibia (16), pelvis (9), foot (4), radius (2). All patients had previously unoperated tumours and no patient presented with metastases. Investigations All patients were examined with plain radiographs, computed tomography and magnetic resonance imaging. From 1997 onward, TL-201 and/or DMSAV scans were also performed on patients with suspected chondral tumours. Tl-201 and DMSAV scintiigraphy were conducted at two centers (SVH, PMCI) with similar imaging protocols. All studies were conducted using a gamma camera. A pre-determined dose of radioisotope was administered intravenously and scintigraphic images obtained at 30 minutes (early phase) and 3–4 hours (late phase) after injection in all cases. Early phase static images were acquired over the area of interest and late phase images consisted of whole body imaging and SPECT over the area under investigation. A low energy high resolution, parallel-hole collimator was used and image acquired in a 128 × 128 matrix for 5 minutes. A simple grading system was devised for late phase isotope uptake with NO UPTAKE indicating no tumour uptake greater than background activity and INCREASED UPTAKE indicating definite activity greater than the background level. The background level referred to is that of the tissue within which the tumour arose, that is, bone. We selected the late phase results for correlation with the results of histological examination of the surgical specimens because early uptake at 30 minutes may also represent peritumoural inflammation or vascularity, which may confound the interpretation of results. In contrast, late phase uptake represented true tumour uptake of isotope. Tumours The pathologist (JS) is the designated lead pathologist on the Victorian Bone Tumour Registry. For the purpose of this study, assessments of surgical tissue and histologic re-evaluation were conducted without prior knowledge of the results of the functional nuclear scans. There were 50 benign tumours and these consisted of enchondromata (29), osteochondromata (17), chondroblastoma (3), and chondromyxoid fibroma (1). There were 42 malignant tumours and these consisted of 38 central chondrosarcoma and 4 dedifferentiated chondrosarcoma. Of these malignant tumours, 22 were graded as grade I, 12 as grade II and 8 as grade III according to. Treatment All tumours in this study were treated with excision. In those tumours that were considered to be benign or grade 1 malignancy as based on history, examination, plain radiography, magnetic resonance imaging and functional scanning, were treated by careful intralesional curettage, burring with a high speed dental burr, pulsatile lavage, chemical cautery with phenol and then the defect filled with polymethylmethacrylate cement. In those tumours that were considered to be clearly malignant and interpreted as grade 2 and higher or if the functional nuclear scans showed significant uptake, wide resection was employed. Because of the histologic heterogeneity of cartilage tumours, the majority of tumours were not biopsied prior to definitive surgery. Biopsy was considered if there was doubt about the diagnosis, or if the anticipated treatment was potentially far greater than may have been required. If biopsy was preferred but could not be safely performed preoperatively, for example, a periacetabular tumour, frozen section drill biopsy would be conducted as part of the initial surgical approach to the tumour. Follow-up No patients were lost to follow-up. Patients with malignant tumours were reviewed every 3 months for the first 2 years and 6 monthly after that for a further 2 years with a plan for yearly review for the following 4 years. Computed tomography of the chest was performed every 6 months, and plain radiographs obtained of the operated area at each visit. The median follow-up was 3.7(0–6) years. At last review, 85 patients were alive without disease, 2 were alive with pulmonary metastases. 3 patients had died of metastatic disease, one patient died from intraoperative complications and 1 patient died from a pulmonary embolus 1 month after surgery. There were no local recurrences. Results Thallium scans Eighty seven of ninety two patients underwent thallium scanning. Of these, 17 patients had increased uptake on the delayed scans, and 70 patients had no uptake on the delayed scans. DMSA(V) scans Eighty three of ninety two patients underwent DMSA(V) scanning. Of these, fifty eight patients had increased uptake on the delayed scans and twenty five patients had no uptake on the delayed scans. Combined thallium and DMSA(V) scans Seventy eight of ninety two patients had both thallium and DMSA(V) scanning. There was no uptake with Thallium and DMSA(V) scanning in twenty patients. Thallium scanning was negative and DMSA(V) was positive in forty five patients. There was uptake on both Thallium and DMSA(V) scanning in 13 patients. There was no case where there was thallium uptake without DMSA(V) uptake. Correlation between functional scanning and state of benignity /malignancy of tumours a. Thallium scans Of the 50 benign tumours, 45 underwent thallium scanning. Forty-three tumours had negative scans and 2 had positive scans. Of the 42 malignant tumours, 27 had negative thallium scans and 15 had positive scans. b. DMSA(V) scans Of the 50 benign tumours, 47 had DMSA(V) scans. Twenty five of these tumours had negative scans and 22 had positive scans. Of the 42 malignant tumours, 36 had DMSA(V) scans. All 36 of these were positive. No malignant tumour was DMSA(V) negative. c. Combined thallium and DMSA(V) scans There 78 tumours that were scanned with both thallium and DMSA(V). Of the 42 benign tumours, 2 had positivity forboth thallium and DMSA(V), 20 had positivity only for DMSA(V) and 20 had no uptake on either scan. Of the 36 malignant tumours that were scanned with both isotopes, 11 showed positivity for both thallium and DMSA(V), while 25 tumours showed positivity for DMSA(V) only. No malignant tumour was negative to thallium scanning. Correlation between functional scanning and tumour grade in 42 choindrosarcomas a. Thallium scans Of the 42 chondrosarcomas, 7 grade II and 8 grade III tumours had positive thallium uptake. No grade I tumour had thallium uptake. Twenty two grade I tumours, and 5 grade II tumours showed no uptake. b. DMSA(V) scans Thirty six of the 42 chondrosarcomas had DMSA(V) scans. All were positive (20 grade I, 11 grade II, 5 grade III). No chondrosarcoma was DMSA(V) negative. Correlation between functional scanning and metastasis No patient with a negative thallium scan developed metastasis. Six of seventeen patients with positive thallium scans developed metastases. In contrast, four of fifty eight patients with positive DMSA(V) scans developed metastases. In patients where both scans were performed, four of thirteen patients developed metastases. Discussion Anatomic imaging such as computed tomography [ 13 ] and magnetic resonance imaging [ 4 - 6 , 14 ] provide excellent morphologic delineation and localisation of bone tumours. These tests are invaluable in the surgical planning for patients with musculoskeletal tumours However, these tests do not always give an indication of the biologic behaviour of the tumour, particularly if there are subtleties between benign and low grade malignant states [ 15 ]. Cartilaginous tumours of bone are characterized by radiologic and histologic heterogeneity [ 7 , 8 ] that may give rise to diagnostic dilemas. Benign tumours such as enchondromas and osteochondromas may appear large and bizarre giving an impression of biologic aggressiveness, particularly those in the hand, while some chondrosarcomas such as a clear cell chondrosarcoma may be small, well defined, slow growing and apart from osteolysis have no other hallmark of malignancy [ 16 - 18 ] such as cortical destruction or soft tissue extension to express its malignant phenotype. One of the major difficulties in orthopaedic oncology is the differentiation between enchondroma and grade 1 chondrosarcoma [ 19 ]. Conventional technetium monodiphosphonate skeletal scans are employed to identify uni-or multifocal disease when bone tumours are suspected [ 12 ]. For positivity, this scanning modality relies on the interactions between tumour and host bone that incite an osteoblastic response by adjacent bone and does not necessarily imply malignancy. For example, enchondroma and chondrosarcoma frequently demonstrate a similar uptake of nuclear tracer, without differentiating between benignity and malignanc. Reliance on preoperative histologic diagnosis for determining the nature of a cartilage lesion can also be difficult. Biopsy of a suspicious cartilage tumour is most helpful when clear malignancy is demonstrated because a benign finding does not necessarily exclude malignancy. The histologic heterogeneity of cartilage tumours, however, is well recognized and unless the biopsy accurately targets the most malignant part of the tumour, there is a risk that the histologic diagnosis may under-report the state of malignancy if this should exist. Functional nuclear scans reflect the metabolic activity of tumours and may provide important information regarding their biologic behaviour. In this regard, hypermetabolic tumour tissue is likely to be more active than surrounding normal tissue and this difference may be valuable for distinguishing between benign and malignant tumours. Similarly, when dealing with grades of malignancy, a higher level of metabolic activity may be expected from high grade tumours in comparison to lower grade counterparts. Since the late 1970s, thallium (Tl-201) scanning has been used extensively as a safe method to assess ventricular function in patients with myocardial ischaemia and the results have been interpreted as reflecting relative levels of myocardial metabolic activity. As Tl-201 is a potassium analogue, its uptake into cells depends on the sodium potassium ATPase dependent pump. Tl-201 is a readily available, cyclotron produced radionuclide that decays by electron capture with a half-life of approximately 73 hours. The liver, spleen, kidneys, myocardium, thyroid, choroids plexus of the lateral ventricles and testis normally demonstrate avidity for Tl-201, with very minimal uptake in healing surgical wounds. Tl-201 is thought to accumulate less well within connective tissue, which contains inflammatory cells and almost undetectable in necrotic tissue. Localization of Tl-201 within tumours appears to be influenced by tumour vascularity, tumour cellularity, the metabolic rate of the tumour and the histological type of tumour. Thallium uptake studies [ 20 - 23 ] in patients with bone tumours have been used to predict response to preoperative chemotherapy by correlating the histological degree of tumour necrosis to changes in Tl-201 uptake. The correlation between thallium uptake and tumour metabolic activity, thus makes it a good candidate tracer to assess malignancy in chondromatous tumours. 99Tcm-Dimercaptosuccinic acid (DMSA) is another readily available isotope, which was first described as an isotopic agent for investigating the renal parenchyma in a variety of disease entities [ 24 - 26 ]. Subsequently, the pentavalent form of 99Tcm-dimercaptosuccinic acid (99Tcm-(V)DMSA) developed a recognised role for imaging medullary thyroid carcinoma, [ 27 - 30 ] and this role was further investigated in relation to assessing bone metastases and other neoplastic conditions such as multiple myeloma, osteosarcoma and chondrosarcoma. [ 31 - 33 ]; [ 28 , 34 ]. Of note, uptake of DMSA(V) is reported to be absent in vertebral collapse and osteoarthritis [ 35 ]. Our study has demonstrated that the combined use of Tl-201 and DMSA(V) scanning may be correlated with the benignity, malignancy and grade of cartilaginous tumours. For a tumour that is hetereogeneous not only on radiologic but also pathologic appearance, the use of functional nuclear scanning may help to differentiate particularly between the low grade and benign lesions. Of note, no malignant lesion had a negative DMSA(V) scan, and only 2 out of 45 benign tumours showed thallium uptake in our study. While this modality of investigation does not replace the value of combining elements from the clinical presentation, plain radiographic changes and pathology, functional nuclear scanning may increase the confidence of diagnosing a low grade or benign tumour, and the availability of information preoperatively may also be helpful for tumours that are deeply situated and difficult to biopsy. With regard to biopsy, localized thallium or DMSA(V) positivity may be useful for guiding tissue sampling from the most metabolically active site, thus enhancing the procurement of potentially the most aggressive/malignant part of the tumour [ 12 ]. Although, the median duration of follow up in this study was limited to 3.7 years, the high proportion of metastases in patients whose sarcomas were thallium positive may suggest a role for thallium scanning as a prognostic indicator for metastasis in chondrosarcoma. Interestingly, the combination of DMSA(V) with thallium scanning did not improve the prognostic value for metastases. This may be attributed to the fact that the spread of DMSA(V) positivity amongst the tumours was greater than thallium positivity, whereas the latter was positive only in patients with grade II and III chondrosarcomas, which are the ones that mainly metastasise. We cannot explain why 2 out of 45 benign tumours were thallium positive. The specimens were reviewed by a panel of pathologists expert in bone pathology and none conferred a diagnosis of sarcoma. In both of these cases, DMSA(V) positivity was also observed. It is important to note that these tumours occurred in the hand and foot, although not part of the syndrome of enchondromatosis. It is appreciated that small bone enchondromata may behave locally in a very aggressive manner without any cytologic evidence of malignancy [ 19 ]. However, small bone chondrosarcoma are also know to be fatal and careful inspection of imaging and pathology is required to ensure distinction between benign and malignant lesions which may behave similarly [ 36 , 37 ]. No conclusion can be drawn about the biologic significance of our finding of 2 benign small bone tumours with thallium uptake, in view of the very small numbers of these in our study. One patient had a small toe amputation and the other had curretage, chemical cautery and cementation of a phalangeal lesion. Neither have represented with local or systemic recurrence of disease. As a result of this study, we now undertake the following sequence of scanning and treatment (Figure 1 ). All patients with a suspected chondral tumour would undergo a DMSA(V) scan. If this is negative, no further scanning is performed and the tumour is regarded as benign because our study had indicated that no malignant tumour had a negative DMSA(V) scan. These tumours would then be treated on their individual merits. If there is uptake on the delayed DMSA(V) scans our study had indicated that half of these are likely to be malignant therefore, patients would undergo thallium scanning. If there is no uptake, then based upon our study, the result would be interpreted as benign cartilage tumour or grade 1 chondrosarcoma. Patients may then undergo intralesional curettage with chemical cautery and cementation or wide excision. If there is uptake on the thallium scan, our study demonstrated that there is a very high likelihood that these tumours would be grade II or III and a wide excision would be recommended. Figure 1 Algorithm for the use of DMSA(V) and thallium scanning for cartilaginous tumours. Thal : Thallium-201; DMSA(V) : Pentavalent dimercaptosuccinic acid +ve : positive uptake; -ve : no uptake. Surgical treatment for cartilage lesions vary widely [ 38 ]. Intralesional curettage together with local adjuvant treatment is often recommended for benign tumours but the management of chondrosarcoma follows the same principles as espoused for all sarcomas [ 39 , 40 ]. Wide resection with a cuff of normal tissue radially and axially around the tumour is encouraged. The importance of good margins is highlighted by the predilection for local recurrence of incompletely excised chondrosarcoma [ 41 - 43 ], and also because of the risk of chondrosarcomas recurring at a higher maliginancy grade with its associated increased risk of metastasis [ 44 ]. Inaccurate diagnosis and or grading may thus result in under- or over treatment of cartilage neoplasms that may later manifest as troublesome local recurrence or unnecessary loss of function from ablative surgery. The management of grade 1 tumours remains controversial. Some authors have recommended intralesional curretage, adjuvant treatment and cementation for these lesions [ 45 , 46 ]. In a series of 40 enchondromata and low grade chondrosarcomas, Bauer et al. observed a local recurrence of 0.09 over 10 years using this modality of treatment. In all cases, local control was subsequently achieved by repeating the earlier surgery on the recurrence. Neither recurrence occurred as a higher grade of tumour. In contrast, some have recommended wide excision of grade I lesions and so called "borderline" chondrosarcoma for fear of tumour recurrence at a higher grade, which would portend toward a poorer outcome [ 47 , 48 ]. The relationship between thallium positivity and higher grades of chondrosarcoma in our study suggests that it would be important to review in a prospective manner the outcome of surgery based upon our algorithm of preoperative scanning. Conclusion There has been rising interest in studying non-invasive techniques of imaging cartilage tumours to try and determine their biologic aggressiveness prior to definitive surgery. The advantages of functional nuclear scanning with DMSA(V) and thallium are that they are easy to perform in the majority of nuclear medicine departments, the isotopes are easily available and the costs are not prohibitive. We have found that the information derived from our study complements other imaging modalities and apart from improving our understanding of cartilaginous tumours, has also assisted us in developing a strategy for their treatment. Competing interests The author(s) declare that they have no competing interests. List of abbreviations TL-201 – Thallium -201 DMSA(V) – Pentavalent dimercaptosuccinic acid Authors contribution Prof. Peter Choong Surgeon, carried out surgery, participated in clinical and diagnostic practice. Wrote and prepared manuscript Dr. Toshikunisada Orthopaedic oncology fellow, collected diagnostic data Dr. Stephen Schlicht Nuclear physician, Participated in manuscript preparation, and conduct of diagnostic tests Dr. Rodney Hicks Nuclear physician, Participated in manuscript preparation and conduct of diagnostic tests Dr. John Slavin Pathologists, participated in blinded review of patients histology	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529308.xml
555957	Preprandial ghrelin is not affected by macronutrient intake, energy intake or energy expenditure	Background Ghrelin, a peptide secreted by endocrine cells in the gastrointestinal tract, is a hormone purported to have a significant effect on food intake and energy balance in humans. The influence of factors related to energy balance on ghrelin, such as daily energy expenditure, energy intake, and macronutrient intake, have not been reported. Secondly, the effect of ghrelin on food intake has not been quantified under free-living conditions over a prolonged period of time. To investigate these effects, 12 men were provided with an ad libitum cafeteria-style diet for 16 weeks. The macronutrient composition of the diets were covertly modified with drinks containing 2.1 MJ of predominantly carbohydrate (Hi-CHO), protein (Hi-PRO), or fat (Hi-FAT). Total energy expenditure was measured for seven days on two separate occasions (doubly labeled water and physical activity logs). Results Preprandial ghrelin concentrations were not affected by macronutrient intake, energy expenditure or energy intake (all P > 0.05). In turn, daily energy intake was significantly influenced by energy expenditure, but not ghrelin. Conclusion Preprandial ghrelin does not appear to be influenced by macronutrient composition, energy intake, or energy expenditure. Similarly, ghrelin does not appear to affect acute or chronic energy intake under free-living conditions.	Background Ghrelin, a peptide secreted by endocrine cells in the gastrointestinal tract, is thought to play a significant role in the regulation of energy balance due to its effects on the stimulation of food intake [ 1 , 2 ] and weight gain [ 1 - 3 ] in rodents. It has been suggested that ghrelin may also play a role in meal initiation in humans, since the concentration of ghrelin increases immediately prior to a meal [ 4 ] and decreases after eating [ 4 - 6 ]. Furthermore, ghrelin infusions are associated with feelings of hunger and increased energy intake during a buffet-style lunch [ 7 ]. Despite the evidence indicating a role in acute food intake, little is known about the factors regulating ghrelin and its effects on long-term energy balance in humans. One hypothesis is that ghrelin secretion is up-regulated in periods of negative energy balance and down-regulated in periods of positive energy balance [ 8 ]. Since energy balance is a function of both energy intake and expenditure, ghrelin concentrations should increase or decrease with fluctuations in food intake (macronutrient composition and/or energy intake) and/or energy expenditure. In turn, increased ghrelin concentrations should be associated with higher food intake. However, the effects of daily fluctuations in food intake and energy expenditure on ghrelin have not been investigated in humans. The purpose of the present study was to determine how changes in macronutrient composition, energy intake, and energy expenditure affect preprandial ghrelin concentrations, and ghrelin's subsequent effects on food intake. Results Body weight and composition Ghrelin was negatively related to body fat percentage (r = -0.46, P < 0.05) and BMI (r = -0.18, P < 0.02), but not body weight (r = -0.16, P > 0.45). There were no significant body weight changes during the seven day observation periods (2)(data not shown, P > 0.40). Effect of treatment on macronutrient and energy intake The composition of the treatment beverages and their contribution to daily food intake is listed in Table 1 . Overall, macronutrient intake during the seven day observation periods was primarily determined by the composition of the treatment beverages (Table 2 ). Table 1 Macronutrient composition of treatment beverages for one day, and their proportion of total daily macronutrient and energy intake during the seven day treatment periods. Hi-CHO Hi-PRO Hi-FAT Composition of Treatment Energy (MJ/d) 2.13 2.11 2.11 Carbohydrate 113 83 8 Protein (g/d) 6 34 7 Fat (g/d) 4 4 50 Percentage of Total Daily Intake Energy (%) 17.5 ± 4.0 17.1 ± 3.2 17.8 ± 3.4 Carbohydrate (%) 25.8 ± 4.4 20.2 ± 4.3 2.5 ± 0.7 Protein (%) 4.5 ± 12.9 28.3 ± 4.8 7.7 ± 2.3 Fat (%) 5.1 ± 2.4 5.0 ± 1.8 41.5 ± 9.9 presented as means ± SD Hi-CHO = carbohydrate treatment beverage Hi-PRO = protein/carbohydrate treatment beverage Hi-FAT = fat treatment beverage Table 2 Effect of the treatment beverages on macronutrient and energy intake Hi-CHO Hi-PRO Hi-FAT Macronutrient Intake (% of daily total) Carbohydrate (%) 60.4 ± 6.1 a 56.4 ± 6.9 b 47.0 ± 8.3 c Protein (%) 13.5 ± 2.3 a,c 16.6 ± 3.2 b 13.5 ± 3.3 c Fat (%) 26.3 ± 5.7 a 26.0 ± 5.6 a 39.1 ± 6.3 b Macronutrient (g/day) and Energy (MJ/d) Intake Carbohydrate (g) 450.9 ± 80.4 a 427.3 ± 83.3 b 347.3 ± 102.3 c Protein (g) 100.6 ± 22.0 a,c 123.4 ± 19.4 b 97.5 ± 22.3 c Fat (g) 91.0 ± 34.2 a 88.8 ± 27.6 a 126.9 ± 29.8 b Energy (MJ/d) 12.6 ± 2.7 12.7 ± 2.3 12.2 ± 2.5 presented as means ± SD different letters in the row denote statistical significance (mixed model ANOVA) Hi-CHO = carbohydrate treatment beverage Hi-PRO = protein/carbohydrate treatment beverage Hi-FAT = fat treatment beverage Energy expenditure and macronutrient intake effects on preprandial ghrelin Average 24 hour energy expenditure (24EE; uncorrected activity log alone) was 13.9 ± 1.9 MJ/d compared to 12.6 ± 1.6 MJ/d for total energy expenditure (TEE; doubly labeled water), which is an average over-reporting of energy expenditure of 11%. Thus, our assumption that subjects would likely misreport energy expenditure and the values would require adjustment was valid. The mean preprandial ghrelin concentrations during the last week of each treatment period were 2501.4 ± 438.0 pg·mL -1 for Hi-CHO, 2869.5 ± 817.3 pg·mL -1 for Hi-PRO, and 2688.2 ± 755.5 pg·mL -1 for Hi-FAT (Figure 1 ). These values are higher than reported in similar investigations. This discrepancy is explained by the use of the Linco Research Total Ghrelin RIA kit, which produces values that are approximately 10-fold higher than the most commonly used kit (Phoenix Pharmaceuticals)[ 9 ]. In a side-by-side comparison, both kits have been found to be analytically acceptable despite the differences in values obtained [ 9 ]. Furthermore, the ghrelin concentrations of at least two studies using the same kit were very similar to those we measured [ 10 , 11 ]. The within- and between-subject coefficients of variation for the two observation periods (seven days per period) were 12.9% and 23.0%, respectively. Figure 1 Effect of covert manipulation of macronutrient intake on preprandial ghrelin over the course of one week. Hi-CHO = carbohydrate treatment beverage Hi-PRO = protein/carbohydrate treatment beverage Hi-FAT = fat treatment beverage 1 = Monday 2 = Tuesday 3 = Wednesday 4 = Thursday 5 = Friday 6 = Saturday 7 = Sunday There were no significant treatment effects (mixed model ANOVA). Data are shown on the original scale (see text for details) Preprandial ghrelin was not influenced by treatment, 24EE, macronutrient composition, and selected (without treatment beverages) and total (including treatment beverages) energy intake (breakfast or entire day), or the interactions between these variables (previous or same day)(all P between 0.40 to 0.80). As a further test, we included energy intake for seven days prior to- and two days after each ghrelin value. None of these days were significant (all P between 0.40 to 0.90). Individual day and mean 24EE up to the prior 4 four days before each ghrelin measurement was also not significant (all P between 0.10 to 0.90). Effect of ghrelin and energy expenditure on macronutrient and energy intake Selected and total energy intake for the entire day were significantly influenced by treatment period (P < 0.02), Monday/Friday effect (P < 0.003), Sunday effect (P < 0.03), and 24EE (P < 0.008) (Table 3a ). Classifying energy intake into the three macronutrients, the only macronutrient influenced by 24EE was total and selected carbohydrate intake (P < 0.03, and P < 0.02, respectively) (Table 3b ). There was no significant effect of ghrelin on total or selected energy intake for breakfast or entire day (all P between 0.80 to 0.90). Table 3 Determinants of total energy intake (log 10 ) (A) and carbohydrate intake (log 10 ) (B) A Independant Variable Slope SE P Intercept -0.04 0.23 0.85 Treatment Period 0.13 0.05 <0.02 Sunday effect 0.18 0.08 <0.02 Monday/ Friday effect -0.18 0.06 <0.003 24EE (log 10 ) 1.53 0.57 <0.001 B Independant Variable Slope SE P Intercept 3.94 0.09 <0.0001 Treatment Period 0.10 0.03 <0.003 24EE (log 10 ) 0.53 0.23 <0.03 Treatment Period = first 8 wk treatment vs. second 8 wk treatment period Sunday effect = Sunday vs. other days of the week Monday/ Friday effect = Monday and Friday vs. the other days of the week 24EE = daily energy expenditure Power analyses The partial correlation between breakfast energy intake and ghrelin was 0.07. At 80% power, we could have detected a ghrelin effect if the true partial correlation was a small as 0.36. For powers of 90% and 95%, the true partial correlations would have had to be 0.40 and 0.43, respectively. The partial correlation between total energy intake and ghrelin was even lower than that with breakfast energy intake (r = 0.003). Note that, for a partial correlation of 0.40, ghrelin would have only been explaining about 16% (0.40 2 ) of the variation in energy intake, still a relatively small percentage of explained variation for a hormone purported to exert a large influence on intake. Discussion Of the variables related to energy balance measured in this study (daily macronutrient and energy intake, energy expenditure, and body weight and composition), none appear to play a role in preprandial ghrelin regulation. Similarly, ghrelin did not significantly predict macronutrient or energy intake, despite a power analysis indicating that we would have detected even a moderate effect of ghrelin on intake. Most of the evidence linking food intake and ghrelin comes from single meal, short-term studies. The ingestion of amino acids or a protein meal results in a post-prandial increase in ghrelin [ 12 - 14 ], whereas high- [ 14 , 15 ] or moderate carbohydrate [ 4 , 5 , 16 ], and fat [ 14 ] meals decrease ghrelin. Carbohydrate meals may result in a greater post-prandial suppression of ghrelin than fat [ 16 , 17 ]. However, it has been reported that preprandial ghrelin is unrelated to macronutrient intake in a large (118 subjects) cross-sectional study [ 18 ] and a 12 week longitudinal study [ 19 ]. Similarly, three weeks of a high fat diet has been shown to have no effect on fasting ghrelin [ 20 ]. Based on the results of the current study and others [ 18 - 20 ], it appears that macronutrient intake does not affect preprandial ghrelin, and any macronutrient-specific effects are limited to the post-prandial period. Wren et al.[ 7 ] were the first investigators to demonstrate that the infusion of ghrelin acutely results in an increase energy intake in humans. The lack of an energy-intake stimulating effect of ghrelin on food intake in the present study when compared to Wren et al.[ 7 ] may be related to the amount of ghrelin that was infused (resulting in concentrations twice that under fasted conditions), and the non-free living nature of the subjects. However, other studies have also failed to detect an increase in hunger after ghrelin infusion [ 21 , 22 ]. Ghrelin concentrations do not predict the timing of a meal request or meal size [ 23 ], and are unaffected by energy-restricted diets [ 10 , 18 , 24 ] and when appetite is increased [ 10 ]. Interestingly, it has also been shown that fasting ghrelin is negatively associated with energy intake [ 25 ]. In this same study [ 25 ], Caucasians had ghrelin concentrations that were approximately double that of Pima Indians, yet there was no difference in food intake between the groups. Although body weight typically increases by ≈ 4.5 kg in men and ≈ 7.3 kg in women over the course of 30 years [ 26 ], the human body regulates energy balance rather well (within 1% over the course of 20 years)[ 27 ]. The strength of the relationship between total energy intake and 24EE measured in this study reflects this regulation, but our data indicate that 24EE does not influence ghrelin. One other study has shown that ghrelin does not appear to be influenced by exercise, regardless of exercise intensity [ 28 ]. This longitudinal study (three months) of normal weight young women indicated that ghrelin increases in response to an exercise regimen, but only when exercise induces weight loss. Therefore, it appears that ghrelin is not influenced by changes in energy expenditure alone. Conclusion In conclusion, it appears that macronutrient and energy intake, and energy expenditure have no effect on preprandial ghrelin. None of the variables measured in this study explain the high daily variability in preprandial ghrelin observed over the course of two-seven day periods. In turn, this study fails to detect the energy intake-stimulating effect of ghrelin, despite carefully measured food intake that lasted more than a week and a study powered to detect even a moderate effect of ghrelin. Methods Subjects Twelve healthy, non-smoking men were recruited from the Beltsville, MD area to participate in this study (Table 4 ). All subjects were weight-stable, and not using any medications known to affect food intake, appetite or water balance. The John Hopkins Bloomberg School of Public Health Committee on Human Research approved the study protocol. Subjects provided written informed consent and received a medical evaluation by a physician that included measurement of blood pressure and analysis of fasting blood and urine samples to screen for presence of metabolic disease. Table 4 Characteristics of the subjects (n = 12) Mean SD Age (yr) 39 9 Height (m) 1.81 0.07 Weight (kg) 79.9 8.3 Body Mass Index (kg·m -2 ) 24.1 1.4 Body Fat (%) 18.1 1.7 Ad libitum feedings Voluntary food intake was studied continuously for 16 weeks, whereby subjects consumed only foods provided by the Human Studies Facility (HSF) at the Beltsville Human Nutrition Research Center (BHNRC). Subjects choose foods ad libitum from the menus, and could consume any part or all of a food item, then return the remaining portion to be weighed. BHNRC staff that came into contact with the subjects provided no guidance as to the quantities and/or types of food items chosen. During weekdays, subjects reported to the BHNRC in the morning to eat breakfast, pack selected food items for lunch, then return again in the evening for dinner. Any food taken from the HSF that was subsequently not eaten (all or partial quantities), was returned the next day, and weighed and recorded. On Friday evenings, subjects were provided with coolers packed with a large amount of food for weekend meals. The weekend coolers provided a wide variety of foods in excess quantities, and subjects were allowed to request additional food items be included. Weekend food could be consumed on either day as long as the subjects logged which day each food item was eaten. All uneaten weekend food was returned on Monday, and weighed and recorded. Although subjects were instructed to consume only food items provided by HSF, they were allowed free access to beverages including caloric, noncaloric and alcoholic beverages. Detailed records of the amount, composition and name brand of beverages was submitted daily. In addition to beverages provided on the menu (milk and juice), both regular and decaffeinated coffee and tea were available at meals. Menus Food items offered in the morning (breakfast and lunch) were presented in a cafeteria-style setting as three different rotating menus, each lasting seven days (Table 5 ). Some food items remained on all three menus (e.g. milk and orange juice). In the evening, breakfast and lunch items were also available. A typical dinner was presented cafeteria-style as one or two entrée selections with optional gravies or sauces, and a minimum of three vegetables and side dishes. A garden salad with a variety of additional toppings and dressings was also available. Fifteen different dinner menus were rotated daily (Table 5 ). Table 5 Representative food offerings during breakfast and lunch (one of three weekly rotations), and one dinner (1 of 15 daily rotations). BREAKFAST AND LUNCH DINNER Beverages Cereals Bread Meat, Dairy, Eggs Snack Packaged Foods Produce #15 2 % milk Hot (6) English muffin Ham Fig bars Vegetable soup Apple Turkey Skim milk Cold (10) Waffle Chicken salad Granola bar (LF) Beef w/veg soup Orange Chicken gravy Orange juice Honey bun Salami Popcorn Clam chowder Banana Mashed potatoes Apple juice Bread (4) Provolone cheese Short bread cookies Noodle soup Grapes Mixed Vegetable juice Pita bread American cheese Brownie Pizza Peaches Citrus salad Buttery cracker Scrambled egg Strawberry twist Pocket sandwhich Dates Cranberry sauce Saltine cracker Bacon Chocolate bar (2) Sausage biscuit Garden salad Sourdough bread Yogurt (FF) Peanuts Lettuce Macaroni & cheese Cottage cheese Peanut butter Tomato Parmesan chesse Carrots Cucumber Celery (#) = number of items available in a category LF = low fat FF = fat free The goals of the menu design were to allow detection of macronutrient selection by offering a wide range of carbohydrate, fat- and/or protein-rich foods, and to provide a variety of commonly available foods typical of what many Americans eat. In a research setting it is impossible to duplicate the degree of food choice available in real life. However, more than 300 food items were used to develop menus for this study, and specific requests for food items were incorporated into the menus whenever possible. Recording and tracking of food intake After each subject selected his desired foods, he presented them to a staff member that recorded the identity and weight of each food item by hand and on a computer (combination of bar code recognition of the food item and hand-entering of the weight). Upon termination of feeding, each subject presented his tray to a staff member that weighed any uneaten food. The accuracy of the food item recording process was verified by comparing the information on the computer with the hand-entered logs. This verification procedure was followed daily, and repeated at the end of the study with all food records. Energy and macronutrient composition were determined by consultation with the USDA Nutrient Database for Standard Reference [ 29 ]. Covert manipulation of macronutrient composition During the 16 weeks of ad libitum intake, subjects were randomly assigned to two of three treatments. Each treatment lasted 8 weeks with no break between the periods. The treatments consisted of a daily beverage that contained ≈ 2 MJ/day of predominantly carbohydrate (Hi-CHO), fat (Hi-FAT), or a combination of protein and carbohydrate (Hi-PRO) (Table 1 ). The daily beverage was divided into three equal portions, and subjects consumed them with each of the three primary meals. The protein drink was designed to provide half the daily Recommended Daily Allowance (RDA) [ 30 ] of protein, with the balance carbohydrate. The drinks were formulated using sucrose, heavy whipping cream, and egg white as the principle source of carbohydrate, fat, and protein, respectively. Water, fat free non-dairy creamer, and aspartame were used to provide volume, adjust texture and add sweetness. Cocoa was added to all drinks to provide a uniform taste and appearance. Subjects were blinded to the treatments and the three drinks were judged to be indistinguishable by a taste panel conducted in our laboratory. Ghrelin analysis Each morning for the last seven days of each treatment period, subjects reported to the laboratory after a 10–12 hr fast, provided a blood sample, then reported to the HSF to eat breakfast. Blood was collected in tubes containing EDTA, centrifuged, and stored at -80°C until analysis. Plasma ghrelin was analyzed using a commercially available radioimmunoassay kit (Total Ghrelin, Linco Research, Inc.). The intra- and interassay coefficients of variation (CV) were 5.6% and 7.3%, respectively. Body weight and composition Before breakfast and after voiding, body weight was determined weekly on an electronic balance to the nearest 0.01 kg. Body composition was measured by Dual-energy X-ray Absorptiometry (DEXA; QDR 4500, Hologic, Inc, Waltham, MA). Total and 24 hr energy expenditure (24EE) To "capture" daily variations in energy expenditure, we combined a self-reported activity log [ 31 ] and doubly labeled water measurements. Although doubly labeled water is the "gold standard" measure of free-living energy expenditure, its use is limited by the production of a single value that is assumed to represent average energy expenditure over the course of the dosing period (seven days in this study). This seven day value for energy expenditure is not useful to compare with daily variation in ghrelin and food intake (macronutrient composition and energy intake). Since self-reported measures of energy expenditure (that can provide a daily energy expenditure value) may be misreported by subjects [ 32 , 33 ], we adjusted the daily numbers using doubly labeled water measurements (see below). Twenty-four hour energy expenditure (24EE) was estimated using a daily recording log method, modified from Bouchard et al. [ 31 ]. Briefly, subjects recorded their daily activities in a log every 15 min over the course of the last seven days of each treatment period. Activities were entered in as a number (1–9), corresponding to example activities listed in the log. Each activity assumed a pre-determined energy expenditure score, thus energy expenditure was calculated as time spent in that activity times the energy expenditure rate. Total energy expenditure (TEE) was concurrently measured by the doubly labeled water method as described by Speakman [ 34 ], which provided an estimate of energy expenditure during the last seven days of each treatment period. Subjects reported to the BHNRC between 6:30 and 9:00 a.m., at which time they received an oral dose of H 2 18 O (0.16 g/kg body weight) and 2 H 2 O (0.30 g/kg body weight). Urine samples were collected immediately before the dose and on every morning (second void) for the last seven days of the treatment period. The first sample was collected approximately 24 hr after the dose. Enrichments of 2 H and 18 O in urine samples were measured by infrared spectroscopy and isotope ratio mass spectrometry, respectively. TEE was calculated using the equations of Weir [ 35 ]. Individual daily 24EE values were corrected using the ratio adjustment (notation denoting subjects is suppressed), 24EE dayx, corrected = 24EE dayx × (TEE/24EE day 1–7 ), where 24EE dayx is the uncorrected daily energy expenditure value from the activity log for one of the seven days (day X), TEE is the daily mean energy expenditure estimate using doubly labeled water. Represents a single value during the seven days of measurement (of which 24EE dayx is one), and 24EE day 1–7 is the mean of the seven days of uncorrected 24EE values corresponding to TEE, of which 24EE dayx is one. To simplify the notation, the 24EE dayx, corrected value for day X will subsequently be referred to as 24EE. Data transformation To check the assumption of homogeneous variances necessary for valid F-tests and correct P-values, we used the standard technique of plotting the standard deviations (SD's) against the means for selected energy intake, grouping observations by subject and treatment period. The results of this scatter plot revealed a strong positive linear relationship (r = 0.67, P < 0.001). The relationships between the SD and mean for macronutrient and energy intake (total and selected), and 24EE were also positive and significant. This indicated that the SD's (variances) were a function of the mean and that the data needed to be transformed. We followed methods described by Draper and Smith [ 36 ], and used a family of transformations based on logarithms. For selected energy intake, this transformation was log (b 0 + b 1 y i ), where b 0 and b 1 are the estimated coefficients of the line fit by regressing the SDs on the means, and y i represents the energy intake data. The other variables were transformed using this same family of transformations. This procedure resulted in homogeneous variances for all variables once transformed, satisfying ANOVA assumptions. We present the data on the original scale in tables and figures for ease of interpretation (unless indicated otherwise). Due to the free-living nature of the subjects, there were three observations (of 168) where (for unknown reasons) a subject's food intake differed greatly from habitual intake due to a skipped meal or meals with low energy intake. For this reason, these observations were not used in the analyses. Additionally, a preliminary sensitivity analysis and residual diagnostics (e.g., restricted likelihood distance, Cook's D; optional output of Proc Mixed, new in version 9.1, in [ 37 ]) suggested they were outliers. Statistical analysis The experimental design was an incomplete block crossover design, with two of the three drink treatments given sequentially to each subject. Data were analyzed in the mixed linear models framework, using the Proc Mixed procedure in SAS (version 9.1)[ 37 ]. Subject-to-subject variation was modelled as a random effect. Repeatedly measuring each subject over the seven days induced an autoregressive covariance structure we modelled as AR(1). Other design effects we retained in our modelling were a two level period effect ((first 8 week treatment period (1) vs. the second 8 week period (2)), and two day-of-the-week variables, found in a preliminary analysis to account for day-of-the-week effects. Each of these day-of-the-week variables classify days into two groups: (1) Sunday (0 vs. 1 for other days of the week) and (2) Monday/Friday (0 vs. 1 for other days of the week). They allow for the major differences in food intake and energy expenditure due to day-of-the-week effects. Some subject-specific variables, such as body weight, were included as covariates as appropriate. The treatment effects (Hi-CHO, Hi-PRO, and Hi-FAT) were included in all models. For models predicting ghrelin concentration, we included 24EE, energy intake, and the interaction between 24EE and energy intake. We also considered prior day (up to 7 days) and subsequent day (up to 2 days) values for energy intake and ghrelin, and their interactions as candidate covariates. Values for up to 4 prior days for 24EE were used to predict ghrelin. For models predicting daily energy intake, we included preprandial ghrelin concentrations, 24EE, the interaction between ghrelin and 24EE, and additionally considered as candidate covariates the prior (seven days) and subsequent (two days) days for these two variables and their interactions. We explored models that included other variables and interactions, but none of those variables appeared useful. Data are presented as total intake (intake including treatment drinks) and/or selected intake (intake without treatment drinks). Values are presented as means ± SD unless indicated otherwise. Since a preliminary analysis suggested that the effect of ghrelin on energy intake was small or negligible, we conducted a power analysis to determine our ability to detect an effect of ghrelin if the effect was small. This was accomplished by Monte-Carlo simulation (creating simulated data sets based on the data we collected) and, starting with no effect of ghrelin (a true coefficient of zero for ghrelin in a regression context), determining how large the true coefficient needed to be to obtain significance for most of the simulations, at powers of 80%, 90%, and 95%, with 1000 simulations for each coefficient value. These results are most easily interpreted as how large a partial correlation between ghrelin and energy intake (adjusting for all other fixed and random effects, other than ghrelin) would be necessary for us to detect it. We conducted this analysis for both total energy intake and breakfast energy intake (the latter was the meal most likely to be influenced by preprandial ghrelin because of the timing of the blood draw). Authors' contributions MK was responsible for statistical analysis and interpretation. DR was responsible for supervising the food intake portion of the study. WR conceived the study, and supervised the data collection and analysis. DP was responsible for ghrelin analysis, data collection, statistical analysis and manuscript preparation. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555957.xml
300700	In PLoS Biology, volume 1, issue 1:	null	One of the variants associated with increased diabetes risk was incorrectly indicated throughout this article. The A1369S variant in the gene ABCCB should have been written S1369A. The alanine variant is associated with increased risk. This mistake affects Tables 2 and 4, the text of the article in the section entitled " ABCCB and KCNJ11 " on page 45, and the Supporting Information Tables S1 and S2. The full text XML and HTML versions of the article, and the supporting Tables S1 and S2 have been corrected online.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC300700.xml
544866	The association between male infertility and sperm disomy: Evidence for variation in disomy levels among individuals and a correlation between particular semen parameters and disomy of specific chromosome pairs	Background The association between infertility and sperm disomy is well documented. Results vary but most report that men with severely compromised semen parameters have a significantly elevated proportion of disomic sperm. The relationship between individual semen parameters and segregation of specific chromosome pairs is however less well reported as is the variation of disomy levels in individual men. Methods In order to address these questions the technique of fluorescent in-situ hybridisation (FISH) was utilised to determine the disomy levels of chromosomes X, Y and 21 in 43 sperm samples from 19 infertile males. The results generated from this study were analysed using logistic regression. Results In this study we compared levels of sperm concentration, motility and morphology with levels of sperm disomy for chromosome 21 and the sex chromosomes. Our results suggest that there is considerable variation in disomy levels for certain men. They also suggest that oligozoospermic males have significantly elevated levels of sex chromosome disomy but not disomy 21; they suggest that severe asthenozoospermic males have significantly elevated levels of disomy 21 but not sex chromosome disomy. Surprisingly, severe teratozoopsermic males appeared to have significantly lower levels of sperm disomy for both the sex chromosomes and chromosome 21. Conclusion We suggest that the association between sex chromosome disomy and oligozoospermia may be due to reduced recombination in the XY pairing region and discuss the relevance of our findings for the correlations between sperm disomy and sperm motility and morphology.	Background The relationship between male infertility and elevated proportions of sperm with extra or missing chromosomes in any given ejaculate is now extensively documented. There have been over 30 studies that have investigated this effect [e.g. [ 1 - 7 ]], and the majority have suggested a highly significant relationship between decreased semen quality parameters and increased sperm disomy. At least three studies however [ 3 , 8 , 9 ] have suggested that there is only a moderate increase in disomy associated with male infertility and a further three have found no significant relationship [ 2 , 10 , 11 ]. The reasons for these apparent discrepancies between groups are not clear although they may reflect laboratory-specific differences in stringency of scoring criteria, collection of semen samples after different periods of abstinence and/or criteria for patient selection differing from study to study. An alternative explanation however is that, among individuals and individual patient cohorts, some men have elevated levels of sperm disomy associated with infertility whereas others do not. If this is the case, there are a number of possible explanations; perhaps environmental influences could play a role. Indeed, a number of synthetic chemicals have been shown to be able to mimic endogenous hormones and affect the normal pattern of reproductive development [ 12 ]. In humans, levels of sperm disomy can be increased by environmental factors such as alcohol abuse and heavy smoking [ 13 , 14 ]. Intrinsic factors such as age and DNA polymorphisms have also been implicated. Indeed age and its effect on sperm disomy is well established [ 15 , 16 ]; Abruzzo et al. [ 17 ] found no effect of Y chromosome alphoid array size on Y chromosome non-disjunction, however Hobbs et al. [ 18 ] recently identified a genetic polymorphism involved in folate metabolism as a significant risk factor for trisomy 21. A number of authors [ 4 , 11 , 19 - 21 ] refer to "severe oligoasthenoteratozoospermia (OAT)." Pang et al. [ 4 ] defined OAT as a sperm concentration of less than 15 million per ml, motility of less than 41% and normal morphology of less than 4.4%. This phenotype has been associated with increases in sperm disomy levels of around tenfold compared to normal controls [ 4 ]. Other papers however are less descriptive about the semen parameters in their patient cohort, and few studies set out to establish any relationship between individual semen parameters and the frequency of disomy of specific chromosomes. Exceptions to this include two studies that have examined patients with teratozoospermia alone [ 7 , 22 ]. Further studies, demonstrated a negative correlation between sperm disomy for sperm concentration [ 7 , 23 , 24 ]. Correlations were also found between disomy and progressive motility [ 24 , 25 ], disomy and teratozoospermia [ 7 , 25 ]. Viville et al. [ 22 ] analysed four individual patients presenting with four different types of total teratozoospermia. In that study, no significant difference was reported for three patients however one patient with macrocephalic spermatozoa had an aneuploidy rate of around 90%, demonstrating a significant correlation with morphology for patients with macrocephalic spermatozoa. In most of the above studies either semen parameters and or aneuploidies for individual chromosome pairs were grouped together and thus not considered individually. Moreover, cases where males have given multiple samples are rare and thus there are few occasions where the individual specific parameters have been compared on a sample-by-sample basis. Establishing chromosome-specific and parameter-specific correlations between male infertility and percentage of aneuploid sperm in an ejaculate is a preliminary step towards understanding the mechanisms of the association between male infertility and chromosome segregation. In this study, our results provide evidence for a variation in rates of disomy for individual men and a correlation between specific semen parameters and individual chromosome disomies. Methods Patient cohort and experimental design A series of males undergoing infertility treatment with a range of andrological phenotypes were assessed for conventional semen parameters and for sperm disomy. All patients were attending IVF clinics in the central London area. Semen samples were taken, with patients' informed consent, from 19 different men on 43 occasions from infertility clinics in central London. None had known constitutional karyotypic abnormalities or Y chromosome deletions. We received 1 sample each from 12 men, 2 samples from one man, 3 samples from 2 men, 4 samples from one man, 6 samples from 2 men and 7 samples from one man. In some men one, two or three of the semen parameters measured (concentration, motility and morphology) were within the normal range; these were hence placed in a control group. In other cases (test group) individual parameters were in the abnormal range (see subsequent section for andrological criteria). Given that some samples were taken from individual patients on several occasions, sometimes males appeared in the control group for some samples and in the test group for others. We restricted our molecular cytogenetic studies to chromosome 21 and the sex chromosomes for three reasons. First, according to previous studies [ 26 - 28 ] these are the most prone to non-disjunction in sperm and hence the most likely to give significant results. Second, the sheer number of sperm that needed to be scored per individual to establish statistically significant results precluded the study of large numbers of chromosome pairs. Finally these pairs are the most clinically significant as they lead to common mutant phenotypes among liveborns. That is, unlike most trisomies that abort in the first trimester, trisomies of the sex chromosomes and chromosome 21 frequently go to term and can lead to Klinefelter Syndrome and Down Syndrome respectively. Semen analysis Men were required to abstain from ejaculating for between 2 and 5 days prior to providing a sample for the study. Samples were produced on site into sterile 60 ml containers and kept at room temperature for up to 60 minutes to allow for liquefaction. Semen parameters were then analysed according to guidelines defined by WHO [ 29 ]. Patients were assessed for sperm quality using WHO guidelines and Kruger strict criteria for assessment of morphology. Concentration, percent motility, forward progression and the percentage of normal morphology were noted. The same operator performed all analyses. Sperm morphology was assessed on unstained samples, using phase contrast microscopy at a magnification of × 640. Evaluation of normal forms was based on Kruger strict criteria as described by Menkveld et al [ 30 ]. Individual samples were then placed in three occasions into a "test" or "control" group. On the first occasion, the control group had a sperm concentration of ≥ 20 million/ml and the test group <20 million/ml. On the second occasion, the control group had forward motility of ≥ 20% and the test group <20%. On the third occasion the control group had a normal morphology of ≥ 4% and the test group <4%. The cut-off points for considering individual samples as being in the test or control groups were based on WHO guidelines for oligozoospermia, severe asthenozoospermia, and severe teratozoospermia and were comparable to those used in other studies for sperm disomy [e.g. [ 4 ]]. In each case the sample was assessed by fluorescent in-situ hybridization (FISH) for the proportion of disomic sperm. FISH analysis FISH analysis was performed according to Griffin et al [ 15 ]. Briefly samples were prepared as follows: samples were washed in a buffer solution (10 mM Tris HCl, 10 mM NaCl, pH 8.0), smeared onto clean microscope slides, and dehydrated in an alcohol series. Slides were then air dried, and sperm heads were swelled by successive incubations in 0.1 M DTT (30 minutes) and 0.1 M LIS (1 hour). Slides were then dehydrated in an alcohol series and air dried ready for subsequent FISH studies. Three colour FISH was carried out for chromosomes 21, X and Y in each patient using directly labelled commercially available probes (Vysis Inc., Downers Grove, Il, USA). Spectrum Orange LSI 21 DNA probe, Spectrum Green CEP Y (satellite III) DNA probe, and a combination of the CEP X centromeric alpha-satellite probes one labelled in Spectrum Orange and one in Spectrum Green were used to give a yellow colour. The protocol followed was identical to that of Griffin et al. [ 15 ] with the exception that the colour combinations (above) used. Approximately 5,000 sperm were scored per patient by two or more independent observers. The proportion of aneuploid sperm per sample for each chromosome was noted. Statistical Analysis The hypotheses of interest were whether the rate of disomy was significantly different for the test and control groups in terms of sperm concentration, morphology or motility. To this end, in the first case, all oligospermic patients designated "O" (i.e. O, OT, OA and OAT in table 1 ) were in the test group and the remainder were in the control group. In the second case, the test group were severe asthenozoospermic patients designated "A" (A, OA, AT and OAT – control group were the remainder) and, in the third case, the test group were severe teratozoospermic patients designated "T" (T, OT, AT and OAT – control group were the remainder). Thus six patients (5, 9, 10, 12, 14 and 17) appeared in more than one group on at least one occasion. Data on the rate of disomy were generated for chromosome 21 and the sex chromosomes. To test these hypotheses six logistic regression models were fitted in the statistical software package SAS (Version 8.2). For each model an Odds Ratio, a 95% confidence interval and a p-value were calculated. A confidence interval that does not contain 1 implies that there is evidence that the disomy rates were significantly different for that comparison and hence has a corresponding p-value < 0.05. Table 1 Incidence of sperm disomy for the sex chromosomes and chromosome 21 and the semen analysis in 43 men. Patient number % disomy sex chromosomes % chromosome 21 disomy Total cells scored count (million/ml) Motility (%) % abnormal forms Semen analysis 1 0.50% 0.43% 5097 6.9 26 97 OT 2 1.02% 0.10% 5000 6.6 48 98 OT 3 0.29% 0.29% 4864 128 63 86 N 4 0.35% 0.20% 4790 13.5 17 98 OAT 5a 0.17% 0.24% 5400 61 24 95 N 5b 0.22% 0.10% 5092 37.5 7 95 A 5c 0.12% 0.10% 5000 22 45 99 T 5d 0.06% 0.14% 5000 63 13 94 A 6a 0.14% 0.08% 5000 48 44 98 T 6b 0.12% 0.04% 5000 40 50 99 T 7 0.18% 0.20% 5000 4.8 <10 95 OA 8 0.74% 0.00% 544 <0.01 <10 100 OAT 9a 0.73% 0.25% 5066 17 18 96 OAT 9b 0.45% 0.24% 5056 12 11 97 OAT 9c 0.30% 0.14% 5084 21 30 96 T 9d 0.10% 0.22% 5000 80 8 98 AT 9e 0.18% 0.12% 5063 13.3 26 97 OT 9f 0.24% 0.12% 5004 7.9 42 98 OT 10a 0.24% 0.38% 5000 25 48 99 T 10b 0.02% 0.04% 5000 8 38 97 OT 10c 0.16% 0.12% 5000 22 41 98 T 11 0.17% 0.09% 5275 41 46 93 N 12a 0.96% 1.46% 4050 69 10 91 A 12b 0.44% 0.11% 5449 10.3 26 87 O 12c 0.30% 0.12% 5048 9.5 11 97 OAT 12d 0.24% 0.14% 5018 63 17 97 AT 12e 0.18% 0.08% 5031 32 41 96 T 12f 0.12% 0.06% 5061 57 37 96 T 12g 0.14% 0.18% 5000 24 58 87 N 13 0.06% 0.02% 5000 96 60 92 N 14a 0.65% 0.20% 3521 12 36 97 OT 14b 0.24% 0.08% 5009 7.5 53 99 OT 14c 0.14% 0.10% 5001 37 27 97 T 14d 0.08% 0.14% 5037 16 45 98 OT 14e 0.20% 0.04% 5000 30 40 100 N 14f 0.27% 0.37% 4108 16 38 94 O 15 2.00% 0.59% 5293 14 57 96 OT 16 0.31% 0.21% 5120 47 49 89 N 17a 0.24% 0.24% 5000 18 53 92 O 17b 0.08% 0.04% 5000 49 44 96 T 17c 0.08% 0.04% 5000 44 56 92 N 18 0.10% 0.26% 5000 123 10 96 AT 19 0.30% 0.18% 5107 52 46 89 N Patient number: Letters after patient numbers indicate consecutive samples from the same patient e.g. 10b is the second sample from patient 10 Semen Analysis: O = oligozoospermia (sperm concerntration <20 million/ml); A = severe asthenozoospermia (formward motility <40%); T = severe teratozoospermia (normal motility <4% by strict Kruger criteria); N = normozoospermia (>20 million/ml concentration; >40% formward motlity; >4% normal morphology). Results A total of 209,188 spermatozoa were scored (approximately 5,000 per sample). The total rate of disomy for the sex chromosomes and chromosome 21 was found to be 0.3% (633/209,188) and 0.19% (398/209,188) respectively. Disomy levels ranged from 0.02% – 2.00% for the sex chromosomes and 0.00% – 1.46% for chromosome 21. For the patients who gave multiple samples, individual disomy rates were surprisingly varied: For instance patient 9 (who gave 6 samples) had sex chromosome disomy frequencies ranging from 0.1% and 0.73%. The results of each individual sample are presented in Table 1 where, in each case, the semen parameters as well as the sperm disomy rates for each individual chromosome are given. The results of the logistic regression analysis (table 2 ) clearly demonstrate that men with oligozoospermia (figure 1a ), (sperm concentration < 20 million/ml) have significantly elevated levels of sex chromosome disomy (Odds Ratio 2.39, p < 0.0001) in their sperm compared to men with normal sperm count levels (sperm concentration ≥ 20 million/ml). As the lower limit of the 95% confidence interval for the Odds Ratio is 2.04 these data suggest that the rate of sperm disomy is likely to be at least twice as high in test patients compared to controls. Further analysis revealed that this increase was largely accounted for by an increase in XY disomy, which is usually associated with non-disjunction errors of meiosis I (data not shown). Conversely there was no evidence of a significant association between oligozoospermia and sperm disomy for chromosome 21. For the motility data (figure 1b ) however, the opposite situation pertained. That is, there was no significant difference between sperm disomy levels for the sex chromosomes (XY, XX or XY disomy) whereas men with motility of < 20% (asthenozoospermia) had significantly elevated levels of chromosome 21 disomy compared to controls (Odds Ratio 1.75, p < 0.0001), (table 2 ). Finally (and surprisingly) men with severe teratozoospermia (figure 1c ), (< 4% abnormal forms) had significantly reduced levels of sperm disomy for both pairs of chromosomes compared to controls. (Sex chromosome disomy, Odds Ratio 1.22, p = 0.013, Chromosome 21 disomy, Odds Ratio = 1.54, p=<0.0001) (table 2 ). Figure 2 shows examples of normal and XY disomic sperm. Table 2 Logistic regression analysis of individual disomy rates compared to semen parameters. a. Sperm concentration, b. sperm motility, c. sperm morphology. (C) = control values, ( T ) = test values. a. Sperm concentration Chromosome Mean disomy SD (4 dp) Odds Ratio (95% Confidence Interval) p-value 21 ( C ) 0.19% ( T ) 0.20% 0.0018 0.0028 1.14 (0.94, 1.40) 0.18 Sex ( C ) 0.20% ( T ) 0.48% 0.0046 0.0015 2.39 (2.04, 2.81) < 0.0001 b. Motility Chromosome Mean disomy SD Odds Ratio (95% Confidence Interval) p-value 21 ( C ) 0.16% ( T ) 0.28% 0.0013 0.0037 1.75 (1.43, 2.14) < 0.0001 Sex ( C ) 0.30% ( T ) 0.37% 0.0037 0.0029 1.12 (0.95, 1.34) 0.19 c. Morphology Chromosome Mean disomy SD Odds Ratio (95% Confidence Interval) p-value 21 ( C ) 0.24% ( T ) 0.16% 0.0039 0.0013 1.54 (1.26, 1.89) < 0.0001 Sex ( C ) 0.33% ( T ) 0.28% 0.0039 0.0024 1.22 (1.04, 1.43) 0.013 Figure 1 a) Mean sperm disomy frequencies for the sex chromosomes and chromosome 21 in two groups with sperm concentration of ≥ 20 million/ml and < 20 million/ml. b) Mean sperm disomy frequencies for the sex chromosomes and chromosome 21 in two groups with percentage of motility of ≥ 20% motility and < 20% sperm motility. c) Mean sperm disomy frequencies for the sex chromosomes and chromosome 21 in two groups with ≥ 4% normal morphology and < 4% normal morphology. Error bars represent SEM. Figure 2 Image of five sperm with chromosome X labelled in yellow, Y in green and 21 in red. The sperm at the bottom left and top centre-left are XY disomic. Discussion To the best of our knowledge, this is the first report that demonstrates a relationship between individual clinically defined semen parameters and segregation of specific chromosome pairs. The relationship between sex chromosome disomy and the failure of spermatocytes to complete spermatogenesis is manifested by significantly higher sex chromosome disomy levels in oligozoospermic men. These results are similar to those of Rives et al. [ 23 ], Vegetti et al. [ 24 ], Calogero et al. [ 7 ] who also reported a relationship between sex chromosome disomy and sperm concentration. Here however we also report the absence of such an effect for chromosome 21 and this leads us to propose the hypothesis that this effect may be restricted to the sex chromosome bivalent. This could be confirmed by further studies using probes for different autosomes and studies are ongoing in this regard. A common mechanism leading to both XY disomy and failure of spermatogenesis is aberrant pairing in the pseudoautosomal region. That is, Hassold et al. [ 31 ] demonstrated that men with paternally derived Klinefelter syndrome arose through a reduction or absence in pairing in the pseudoautosomal region. Furthermore, the term "obligatory" has often been used to describe the need for X and Y to pair and recombine in order for spermatogenesis to proceed properly [ 32 ]. In the light of our results therefore we propose that a common mechanism leading to oligozoospermia and increased levels of XY disomy involves a perturbation in the mechanisms of synapsis and/or recombination in the XY paring region. In order to test this hypothesis, in future studies, we will use single sperm PCR [ 33 ] using primers both within and outside the XY paring region. A significant difference between oligozoospermic males compared to controls would provide evidence to support our hypothesis. Our results also suggest a significant association between asthenozoospermia (poor motility) and non-disjunction of chromosome 21. This is similar to reports by Vegetti et al. [ 24 ] but in this case, we found no such association with the sex chromosomes. One possible explanation is that over expressed genes on chromosome 21 significantly impair the formation of the sperm midpiece through which sperm motility is mediated. This seems unlikely however since chromosome 21 is a gene-poor chromosome and there are thought to be few genes expressed in the spermatocyte itself that impact on spermiogenesis. It is also possible that there are gene products (e.g. micro tubular or motor proteins) common to both normal chromosome segregation of chromosome 21 (or the acrocentric (non-Y) chromosomes, or the autosomes in general) and normal formation of the structures that mediate sperm motility. We could establish the extent to which this effect is widespread in other autosomes by similar experiments using probes for other chromosomes; again these studies are ongoing. A final possibility is that our results represent a statistical anomaly. While correlations for individual males who have given multiple (four or more) samples are relatively consistent for sperm concentration, they are less so for motility (see table 1 ). If disomy were related to motility by a genetic cause, then would expect a consistency in chromosomal aneuploidies from individual patients who gave multiple samples. In patient 5 however, his highest motility sample of 45% also had the lowest proportion of autosomal disomy (0.1%) and the highest (0,24%) in a "normal" motility sample. There was also considerable evidence of varying disomy levels when motility remained relatively constant for instance patient 10, had normal motility in all samples, the disomy frequency ranged from 0.12 – 0.38%. Clearly therefore further studies are necessary before a stronger relationship between autosomal sperm disomy and asthenozoospermia can be established. The apparent inverse association between sperm morphology and chromosome segregation was surprising and it is, again, possible that this is a statistical anomaly. Indeed although a number of studies have found no significant correlation between morphology and disomy [ 24 , 34 - 36 ], others suggest a positive correlation between disomy and abnormal morphology [ 7 , 25 ]. The high level of significance, the fact that the effect is clear in two separate chromosome pairs and the fact that different effects were seen for concentration and morphology would argue that this is a genuine phenomenon. Moreover this is one of the few studies that has used repeat samples from individual patients and, in some cases, the same individual appeared in different groups depending on his semen parameters at the time of donation. In other words disomy levels appear not to be consistent among individuals, rather they relate more to their semen parameters on any given day, perhaps as a result of extrinsic factors. Other studies have reported that teratozoospermic males have elevated levels of sperm disomy, Calogero et al. [ 7 ] found a correlation between increased sperm disomy levels and teratozoospermia as did Viville et al. [ 22 ] but only an association with macrocephalic spermatozoa. For the most part however these individuals were defined as "OAT" i.e. also oligozoospermic and asthenozoospermic and thus it is possible that the association of teratozoospermia alone was not measured fully. Future studies warrant investigating this further using more chromosome pairs and individuals who display severe teratozoospermia but normal levels of sperm concentration and motility. Conclusions In conclusion we provide evidence that sperm disomy levels can vary considerably between samples from the same man, the reasons for this are unclear but one possible explanation is the involvement of extrinsic factors or lifestyle changes. Such differences provide hope for possible treatment regimes to improve disomy rates. The evidence of correlations between individual semen parameters and increased disomy of individual chromosome pairs, while statistically significant, warrants further investigation. Closer correlations of disomy rates in men with defects in only one of the three criteria used to measure semen quality will form the basis of our future investigations. In future studies it is also likely that we would include a second control group of normal, fertile donors not attending fertility clinics. Ethical considerations precluded this in this case. Through these studies, a closer understanding of the mechanistic basis of the relationship between chromosome segregation and infertility will be achieved. Authors' contributions HGT- performed the majority of FISH experiments, scoring of semen samples, collected data generated within this study and assisted in drafting the manuscript. SH- performed all semen assessments. MD and DC- performed FISH experiments and acted as independent scorers of semen samples. DW- performed statistical analysis. XPZ- provided patient samples with signed informed consent. DKG- conceived the study and participated in its design and drafted the manuscript. All authors have read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544866.xml
543462	Integrating HIV Prevention and Treatment: From Slogans to Impact	Background Through major efforts to reduce costs and expand access to antiretroviral therapy worldwide, widespread delivery of effective treatment to people living with HIV/AIDS is now conceivable even in severely resource-constrained settings. However, the potential epidemiologic impact of treatment in the context of a broader strategy for HIV/AIDS control has not yet been examined. In this paper, we quantify the opportunities and potential risks of large-scale treatment roll-out. Methods and Findings We used an epidemiologic model of HIV/AIDS, calibrated to sub-Saharan Africa, to investigate a range of possible positive and negative health outcomes under alternative scenarios that reflect varying implementation of prevention and treatment. In baseline projections, reflecting “business as usual,” the numbers of new infections and AIDS deaths are expected to continue rising. In two scenarios representing treatment-centered strategies, with different assumptions about the impact of treatment on transmissibility and behavior, the change in the total number of new infections through 2020 ranges from a 10% increase to a 6% reduction, while the number of AIDS deaths through 2020 declines by 9% to 13%. A prevention-centered strategy provides greater reductions in incidence (36%) and mortality reductions similar to those of the treatment-centered scenarios by 2020, but more modest mortality benefits over the next 5 to 10 years. If treatment enhances prevention in a combined response, the expected benefits are substantial—29 million averted infections (55%) and 10 million averted deaths (27%) through the year 2020. However, if a narrow focus on treatment scale-up leads to reduced effectiveness of prevention efforts, the benefits of a combined response are considerably smaller—9 million averted infections (17%) and 6 million averted deaths (16%). Combining treatment with effective prevention efforts could reduce the resource needs for treatment dramatically in the long term. In the various scenarios the numbers of people being treated in 2020 ranges from 9.2 million in a treatment-only scenario with mixed effects, to 4.2 million in a combined response scenario with positive treatment–prevention synergies. Conclusions These analyses demonstrate the importance of integrating expanded care activities with prevention activities if there are to be long-term reductions in the number of new HIV infections and significant declines in AIDS mortality. Treatment can enable more effective prevention, and prevention makes treatment affordable. Sustained progress in the global fight against HIV/AIDS will be attained only through a comprehensive response.	Introduction In June 2001, heads of state and government convened a United Nations Special Session on HIV/AIDS and adopted unanimously the “Declaration of Commitment on HIV/AIDS” [ 1 ]. In preparation for that session, Schwartländer et al. published an estimate of the resource needs for an expanded global response to the epidemic, which called for around US$10 billion for the fight against HIV/AIDS in 2005 [ 2 ]. In 2002, on the occasion of the 14th International AIDS conference in Barcelona, Spain, Stover et al. showed that such an immediate and expanded response in low- and middle-income countries could reverse the course of the HIV/AIDS epidemic and avert nearly 30 million infections through 2010 [ 3 ]. Today, more resources are available for the fight against HIV than ever before, but global efforts to confront the epidemic continue to disappoint. Worldwide in 2004, more people were living with HIV and more people died of AIDS than in any previous year [ 4 ]. In sub-Saharan Africa, home to two-thirds of all people living with HIV/AIDS, and three out of four people dying from AIDS [ 4 ], only one in 50 persons with advanced disease had access to life-saving medicines at the beginning of 2004 [ 5 ]. The theme of the 15th International AIDS Conference in Bangkok last summer was timely and relevant. “Access for All” calls for extending to all of those in need both sufficient resources and a set of proven interventions to prevent new infections and save lives through effective treatment. Recent developments in HIV treatment, with simple combination therapies priced at less than US$150 per year—unthinkable just a short time ago—were a major driver of discussions during the conference. Widespread access to effective antiretroviral therapy (ART) for people living with HIV/AIDS is now conceivable even in countries with severely limited resources. The World Health Organization and its partners in the Joint United Nations Programme on HIV/AIDS have defined an ambitious “3 by 5” target of 3 million people on ART—half of those in most urgent need—by the end of 2005. The potential epidemiologic impact of large-scale roll-out of treatment programs, however, remains uncertain. Experience to date is limited, and comes mostly from Western countries and Brazil. While declines in AIDS mortality in the industrialized world have been impressive [ 6 , 7 , 8 ], many of these success stories have been accompanied by a resurgence in HIV incidence due to increasing risk behavior as emphasis shifted from prevention to treatment in the 1990s [ 9 , 10 , 11 ]. Will the extension of ART to millions who suffer from AIDS in developing countries be the long-awaited breakthrough in the response to HIV, or will the emphasis on treatment detract from prevention efforts, and thus hamper AIDS control in the medium and long term? The experience in high-income countries underscores the potential perils of failing to adapt prevention strategies to an environment in which life-saving treatment becomes available on a large scale; however, more favorable outcomes in some settings [ 12 , 13 ] indicate that rising risk behavior is not an inevitable outcome of increased treatment access. In our previous analysis of the potential benefits of a comprehensive package of preventive interventions [ 3 ], we noted that these prevention effects would be achieved only in the presence of wide-scale treatment and political support. The two intervening years have seen a dramatic rise in both momentum and financial resources for ART scale-up, but the potential epidemiologic impact of treatment in the context of a broader strategy for HIV/AIDS control has not yet been examined. In this paper, we quantify the opportunities and potential risks of large-scale treatment roll-out. The results of this analysis will be informative for all regions and countries, independent of the level and stage of the epidemic. However, since three of four deaths from AIDS occur in sub-Saharan Africa, successes and failures in rolling out treatments immediately will have the most dramatic effects in this region. We therefore focus our analyses and discussions in this paper on the HIV epidemics in sub-Saharan Africa . Methods Projections of HIV Epidemics in Sub-Saharan Africa Baseline projections of HIV epidemics in sub-Saharan Africa have been developed by the Joint United Nations Programme on HIV/AIDS and the World Health Organization based on the most current data available, and in collaboration with epidemiologic experts and analysts within the countries assessed [ 4 ]. These “business as usual” forecasts from 2004 to 2020 are characterized by the absence of behavioral change or ART scale-up in future years. Combined with the natural dynamics of the epidemic, these assumptions result in a relatively stable HIV prevalence rate. To simulate the effects of prevention and treatment on HIV/AIDS incidence, prevalence, and mortality, we first adapted the analytic approach used in the previously described Goals model [ 3 ] to allow explicit modeling of treatment effects, and calibrated the model to the baseline projections for three African regions (East, West/Central, and Southern) (see Protocol S1 for more details). In line with the predominant epidemiologic pattern in sub-Saharan Africa of HIV spreading through heterosexual contact, the model divides the sexually active population into five different interacting risk groups: single men, single women, married men, married women, and female sex workers. In sub-Saharan Africa HIV is transmitted via other modes at comparatively low levels, and these modes were therefore not considered in our analyses. The model includes underlying regional demography, acquisition of HIV and other sexually transmitted infections (STIs), progression from HIV to AIDS, and progression from AIDS to death. Annual risks of HIV infection in each risk group depend on the number of partnerships, the number of sex acts per partnership, HIV prevalence among partners and condom use. These risks are magnified by the presence of other STIs [ 14 ] and also vary as a function of the time since infection, with the highest risks during acute infection, followed by lower levels that persist until viral loads rise with the onset of clinical AIDS [ 15 , 16 , 17 ]. The regional models were calibrated as follows: first, plausible ranges were specified for model parameters governing sexual behavior and biological factors (e.g., transmission risks and cofactor effects of other STIs) based on review of published studies and survey results; second, multiple simulations were undertaken by sampling values from each of the ranges and recalculating the model for each set of sampled parameter values; third, model fit was assessed by comparing modeled prevalence for adult males and females separately to baseline projections through 2020; and fourth, the best-fitting parameter set in each regional model was selected for the purpose of scenario analysis (see Protocol S1 ). Alternative Scenarios for Prevention and Treatment Potential impacts of prevention efforts at a given coverage level were based on previously published estimates [ 3 ] for a comprehensive package of 12 interventions that included mass media campaigns, voluntary counseling and testing, peer counseling for sex workers, school-, youth- and workplace-based programs, condom promotion and distribution, treatment for STIs, and prevention of mother-to-child transmission. The comprehensive package described by Stover and colleagues also included interventions such as harm reduction for injecting drug users and peer outreach for men who have sex with men, which we have not modeled for sub-Saharan Africa. Impacts were captured in terms of changes in condom use, sexual partnerships, treatment-seeking for STIs, and age at first sex. The impacts of treatment included increased survival by a median of 3 y, reductions in transmission probabilities given contact with an infected partner, and behavior change. We examined a range of alternative scenarios based on various levels and effectiveness of prevention interventions, with and without successful attainment of the 3 by 5 treatment target for sub-Saharan Africa: Baseline (“business as usual”). Risk behaviors are maintained at current levels, and no treatment scale-up occurs. This is simply the baseline scenario that produces a relatively stable prevalence rate over the duration of the projection, with the number of people living with HIV and the number of new infections rising slowly over time because of population growth. Treatment-centered response. In two alternative scenarios, the 3 by 5 target of 50% coverage of those in need of treatment by the end of 2005 is attained, and scale-up continues to reach 80% ART coverage of those in need by 2010, maintained at 80% thereafter. In an “optimal ART effects” scenario, we assumed that treatment reduces transmissibility by 99%, and that those under treatment have 50% lower annual partnership numbers and two times higher condom use than other adults. With a response that focuses primarily on treatment, it is assumed that behavior in the general community of infected and uninfected adults is unchanged from the baseline. In an alternative “mixed ART effects” scenario, less optimistic assumptions were made: that treatment reduces transmissibility only to the same levels as in asymptomatic infected individuals (two-thirds reduction from no treatment), and that behavior in treated patients is the same as in other adults. To capture the possibility of behavioral disinhibition in response to treatment availability, we assumed that condom use declines by 10% in both treated patients and the general community, with other behaviors unchanged. The potential for disinhibition is suggested primarily by experience in some developed countries, where condom use increased dramatically in the populations at highest risk prior to the introduction of ART but then declined; the likelihood and magnitude of reductions in condom use in sub-Saharan Africa, where such prevention-induced changes generally are much less prominent today, might be questioned. We therefore considered in sensitivity analyses a variant of this scenario that excludes disinhibition but preserves all other assumptions. Prevention-centered response. In the absence of wide availability of treatment, reflecting weaker political and social support for HIV control efforts, we modeled a scenario in which the comprehensive prevention package described previously [ 3 ] has only partial effectiveness at the population level, and no ART scale-up occurs. As evidence about the magnitude of treatment–prevention interactions remains limited, we considered a reduction of 50% from the full impact as a base case and examined a range of reductions from 25% to 75% in sensitivity analyses. Combined response. We examined two scenarios combining treatment and prevention efforts, reflecting either optimistic or pessimistic possibilities. In the optimistic scenario, treatment strengthens prevention efforts. ART coverage is the same as in the two treatment-centered scenarios, with optimal assumptions about treatment impact on transmissibility and patient behavior. It is assumed that widespread availability of treatment enables the full impact of prevention efforts to be attained as described by Stover et al. [ 3 ]. In a more pessimistic scenario, an emphasis on treatment leads to less effective implementation of prevention. This scenario includes the mixed assumptions about ART effects (excluding disinhibition in the general community), and assumes only 25% attainment of the maximum potential impact of prevention efforts. Additional scenarios could include pessimistic assumptions about limited ART scale-up levels and timing, emergence of large-scale drug resistance resulting from low adherence, or other possible unintended outcomes of wider treatment. Certainly, large-scale treatment efforts will demand close monitoring of adverse effects. However, experience with treatment programs in developing countries has been encouraging thus far, with reported adherence levels that are at least as high as those in developed countries [ 18 , 19 ]. Results In the baseline projections for sub-Saharan Africa, the annual number of new adult HIV infections rises from 2.4 to 3.7 million between 2004 and 2020, and adult AIDS mortality rises from 1.8 to 2.6 million ( Figure 1 ). If scale-up of ART reaches the 3 by 5 target and eventually expands to 80% coverage, without any behavior change in the broader community (treatment-centered response/optimal ART effects), the annual number of new infections could be reduced by up to 6% compared to baseline by 2020. Mortality would initially decline by 33% but long-term trends would converge toward the baseline. We note that total annual death numbers indicate broad trends in mortality but mask more subtle health gains in the form of years added to individuals' lives. Figure 1 HIV Incidence and AIDS Mortality among Adults in Sub-Saharan Africa, 2003–2020, under Different Intervention Scenarios (A) HIV incidence. (B) AIDS mortality. With less optimistic assumptions (treatment-centered response/mixed ART effects), the number of new infections rises, to 4.3 million per year by 2020 (a 14% increase); mortality trends are similar to the optimistic scenario in the short term, but worse in the long term, even compared to the baseline. Excluding the assumption of reduced condom use through disinhibition from the treatment-centered/mixed effects scenario has minimal effect on the results, lowering the number of new infections in 2020 by only 2% compared to the scenario that includes disinhibition. A prevention-centered response would have greater impact on the number of new infections, lowering annual incidence by more than half by 2020. The long-term mortality trend is more favorable in the prevention-centered scenario than in the treatment-centered scenario because of reduced incidence, but prevention would produce negligible mortality benefits in the near- and mid-term future in comparison to strategies that include ART. Alternative assumptions regarding overall effectiveness in a prevention-centered response produce results that scale as expected, with reductions in annual incidence of 34% to 64% and reductions in annual mortality of 20% to 42% by 2020. If treatment and effective prevention are scaled up jointly in a combined response, the benefits in terms of both infections and deaths averted could be substantially higher. In an optimistic scenario in which treatment programs support expanded prevention, the annual number of new infections would be 74% lower and annual mortality would be 47% lower by 2020, compared to baseline. It is worth noting that the long-term decline in AIDS deaths is driven more by prevention of new infections than by direct survivorship benefits from ART. In a pessimistic scenario in which a more narrow treatment focus limits effective prevention, the overall benefits are much more modest, with 26% and 16% reductions, respectively, in new infections and mortality by 2020 compared to the baseline. Prevalence rises by 7% in the optimal and by 27% in the mixed treatment-centered scenarios by 2020, as longer survival for treated patients offsets reductions in new infections through reduced transmissibility (and risk reductions among treated patients in the more optimistic scenario) ( Figure S1 ). In scenarios that include prevention efforts, prevalence declines by 41% in the prevention-centered scenario, by 53% in the optimistic combined response, and by 6% in the pessimistic combined response by 2020. The total number of infections averted through a combined response would be 29 million over the period 2004 to 2020 if treatment enhances prevention, a benefit that is ten times greater than that of a strategy which focuses on treatment only, even with optimal assumptions, and 51% greater than that of a strategy which focuses on (less effective) prevention alone ( Table 1 ). If a treatment focus limits the effectiveness of prevention, on the other hand, the total number of averted infections between 2004 and 2020 would be 9 million. Similarly, the benefits of a combined response in terms of mortality reductions are considerably higher under optimistic circumstances than the benefits of either treatment only or prevention only, with 10.1 million deaths averted (27%) through 2020 when treatment enhances prevention, compared to 5.0 million (13%) in the optimal-effects treatment only scenario, 3.5 million (9%) in the mixed-effects treatment only scenario, and 4.8 million (13%) with prevention only. Under more pessimistic assumptions about treatment–prevention interactions, the combined response would avert 5.8 million deaths (16%). Table 1 also reports total benefits of the various strategies over the shorter term, in which the ranking of alternatives is similar with regard to the total number of infections averted, but mortality reductions are attributable almost exclusively to treatment. Table 1 Total New Adult Infections and Deaths in Sub-Saharan Africa, 2004–2010 and 2004–2020, under Different Intervention Scenarios Combining treatment with prevention efforts will reduce the resource needs for treatment substantially in the long term ( Figure 2 ). In the various scenarios the numbers of people being treated in 2020 ranges from 9.2 million in the treatment only (mixed effects) scenario, to 4.2 million in the optimistic combined response scenario. Figure 2 Number of Persons on ART in Sub-Saharan Africa, 2004–2020, under Various Scenarios Discussion In this paper, we have examined the potential epidemiologic impact of global HIV/AIDS control efforts under a range of alternative scenarios reflecting varying implementation of strategies for prevention and treatment. Although we focus in particular on population health outcomes and epidemiologic trends, we recognize that there are numerous other social, economic, and individual health effects of interventions including ART that are beyond the scope of this analysis. We also restrict our focus in this paper to sub-Saharan Africa, where the overwhelming majority of people living with and dying from HIV/AIDS reside; however, our findings have broader applicability and more general implications in the worldwide fight against HIV/AIDS, which we highlight here. The Potential for Treatment to Enhance Prevention Must Be Exploited Effective prevention requires more than having sufficient funds to offer information and services. It also requires an environment that encourages people to internalize messages about risky behavior and to adopt actual behavior change, and allows people to utilize services such as testing and counseling without fear of stigma or discrimination. Stoneburner and Low-Beer have argued that the supportive social and political environment in Uganda allowed people to discuss AIDS with family members and close friends, which led to greater behavior change than in Kenya or Zambia where most people received information from mass media only [ 20 ]. People have little reason to seek HIV testing when a positive result brings only negative consequences, whereas widespread availability of treatment provides a major incentive for people to learn their serostatus. Involving communities and family members in the delivery of treatment—for example, as treatment monitors—offers unique entry points for effective prevention activities and a lever for population-wide behavior change. Experience with community roll-out of treatment programs has shown, for example, that uptake of voluntary counseling and testing increased by 300% in one year of roll-out in Haiti, and by a factor of 12 in Khayelitsha, South Africa, after treatment introduction [ 21 , 22 ]. A study targeting nine commuter sites in South Africa found the highest levels of condom use, willingness to use a female condom, and willingness to have an HIV test in Khayelitsha, a difference that may be attributed largely to the availability of ART and comprehensive AIDS care [ 23 ]. If increased uptake of voluntary counseling and testing is indicative of broader prevention effectiveness where ART is available, we estimate that over 50% more new infections and more than twice as many deaths could be avoided through a combined response compared to prevention alone. In contrast, if a narrow treatment scale-up leads to reduced effectiveness of prevention, short-term mortality reductions will come at the expense of longer-term progress in stemming the tide of the epidemic. During most of the past 15 years, efforts to address the AIDS epidemic in sub-Saharan Africa have focused on prevention. There have been successes in some countries, but overall these efforts have not achieved their goals. The advent of vastly expanding treatment programs in the coming years, if opportunities to capitalize on broadened political support and community mobilization can be seized, offers the potential to enhance prevention effectiveness and avert many new infections and deaths. Only Effective Prevention Will Make Treatment Affordable in the Long Run While prevention programs are unlikely to achieve full impact in the absence of treatment, so too is the impact of treatment programs reduced if vigorous prevention efforts are absent. Without effective prevention, the number of people requiring care and treatment will grow each year. As more and more people are kept alive with ART the treatment burden will become enormous unless effective prevention reduces the number of people becoming newly infected. Without effective prevention programs, we project that the number of people receiving treatment will grow to 6.3 million by 2010 and up to 9.2 million by 2020 in Africa alone to achieve 80% coverage of those in urgent need. Meeting this need would require a tremendous increase in financing, human capacity and infrastructure that might not be attainable. If effective prevention programs are combined with treatment programs, the same level of 80% ART coverage would be achieved by treating 5.8 million in 2010 and 4.2 million in 2020. In other words, the same goal could be attained at a far lower treatment cost and with a much greater chance of sustainability. A Successful Global Response Cannot Rely on Either Prevention or Treatment Alone Over the long term, it is effective prevention that will reduce the burden of illness due to AIDS and the number of people in need of ART. The lessons learned in the industrialized world have to be taken on board. The availability of treatment and the shift in focus away from very effective prevention programs has led to increases in unsafe sexual behavior, STIs, and HIV transmission in some settings [ 9 , 10 , 11 ]. There is no doubt that effective therapy can extend and improve the quality of life for those who are treated, but it also must be integrated into a comprehensive community response to HIV so that it can enhance the effectiveness of prevention efforts. Long-term, sustained progress in the fight against AIDS demands more than an exclusive focus on either prevention or treatment alone. Prevention makes treatment affordable, and treatment can make prevention more effective. Countries in sub-Saharan Africa are faced with the most devastating epidemic of our times. We now have the unique opportunity to derive the maximum impact from available resources. The results from our analyses show how potential synergies between prevention and treatment could be translated into considerable health benefits at the population level. But synergies do not mean simply that prevention and treatment are pursued in parallel. When whole communities become involved in the scale-up of treatment access—as will be necessary to achieve the ambitious treatment targets defined by the 3 by 5 campaign—crucial opportunities can be created for increasing their involvement in prevention activities. Only if interactions with patients, family, and community members occasioned by the provision of treatment are also used to reinforce prevention, and only if prevention workers have an opportunity to refer those in need to care and treatment, will we move at last from slogans to impact. Supporting Information Figure S1 Adults Living with HIV/AIDS in Sub-Saharan Africa, 2003–2020, under Different Intervention Scenarios (80 KB EPS). Click here for additional data file. Protocol S1 Technical Appendix (172 KB PDF). Click here for additional data file. Patient Summary Background Infections from HIV continue to increase, especially in sub-Saharan Africa. The World Health Organization has a plan to get more than 3 million people on treatment by 2005 (the “3 by 5” initiative); however, the overall effect of this plan on the population's health is uncertain, and will depend on the balance between treatment and prevention efforts. What Did the Researchers Do? They tried to predict the number of new infections and deaths each year in sub-Saharan Africa from now until 2020 depending on whether control efforts focused on prevention, treatment, or both. What they found was that by far the most effective way of decreasing new infections and deaths was to combine the two approaches, and that by doing so more than 29 million new infections and 10 million deaths might be prevented compared with continuing at current levels of prevention and care. Why Is This Information Important, and Who Will Use It? Despite the huge amounts of money directed at HIV/AIDS, because the problem is so vast, the resources are not enough. Hence it is important to target these resources effectively. Policy makers around the world could use information like this to decide where best to direct attention and funding to combat HIV/AIDS. Where Can I Find More Information? Joint United Nations Programme on HIV/AIDS, AIDS epidemic update, December 2004: http://www.unaids.org/wad2004/report.html World Heath Organization, 3 by 5 Initiative: http://www.who.int/3by5/ Global HIV Prevention Working Group: http://www.kff.org/hivaids/hivghpwgpackage.cfm	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC543462.xml
548279	The importance of socio-economic context for social marketing models for improving reproductive health: Evidence from 555 years of program experience	Background Over the past two decades, social marketing programs have become an important element of the national family planning and HIV prevention strategy in several developing countries. As yet, there has not been any comprehensive empirical assessment to determine which of several social marketing models is most effective for a given socio-economic context. Such an assessment is urgently needed to inform the design of future social marketing programs, and to avoid that programs are designed using an ineffective model. Methods This study addresses this issue using a database of annual statistics about reproductive health oriented social marketing programs in over 70 countries. In total, the database covers 555 years of program experience with social marketing programs that distribute and promote the use of oral contraceptives and condoms. Specifically, our analysis assesses to what extent the model used by different reproductive health social marketing programs has varied across different socio-economic contexts. We then use random effects regression to test in which socio-economic context each of the models is most successful at increasing use of socially marketed oral contraceptives and condoms. Results The results show that there has been a tendency to design reproductive health social marketing program with a management structure that matches the local context. However, the evidence also shows that this has not always been the case. While socio-economic context clearly influences the effectiveness of some of the social marketing models, program maturity and the size of the target population appear equally important. Conclusions To maximize the effectiveness of future social marketing programs, it is essential that more effort is devoted to ensuring that such programs are designed using the model or approach that is most suitable for the local context.	Background In many developing countries, social marketing program have become an essential component, if not the main component, of the national family planning and HIV prevention strategy. Social marketing programs in reproductive health all aim to improve reproductive health of the target population by using commercial approaches to promote healthy behaviors and/or to expand access to essential products and services. While improving reproductive health of the target population is the ultimate aim, donors recognize the potential of social marketing programs to build the sustainable delivery of reproductive health and family planning products and services in developing countries. Different types of social marketing models have been used to achieve these objectives. Social marketing programs have often been classified as either using the non-governmental organization (NGO) model ( sometimes also referred to as the social marketing organization model ) or the manufacturer's model . [ 1 - 3 ]. The NGO model typically focuses on achieving the largest possible health impact among the target population. Hence, the NGO model typically heavily subsidizes products. By contrast, the manufacturer's model was specifically developed in response to the need not only to improve reproductive health, but also to do so in a financially sustainable manner. Programs under the manufacturer's model are treated as temporary interventions with a realistic exit strategy. Such programs typically use experts to provide temporary technical assistance to existing private sector companies, which eventually are expected to continue the program without subsidies. Although the two models are defined largely by the type of management and financial structure, they often also differ in terms of branding, pricing, distribution, and other factors. Moreover, context-specific variations on these two models are common, and some programs use hybrid approaches that integrate features from each of the two broader models [ 4 ]. While many social marketing variants have proven successful, it is generally assumed that the manufacturer's model is more feasible in middle-income countries with a fairly well developed commercial infrastructure, while NGO models are more appropriate in lower-income countries with less less-developed commercial infrastructure [ 4 ]. Although scattered case studies support these assumptions, as yet there has not been any comprehensive empirical assessment of the socio-economic context in which each model works best. This paper analyzes a comprehensive database of annual social marketing statistics. The database is unique in that it includes annual data on social marketing programs in reproductive health in over 70 countries, which cumulatively represent 555 years of experience with social marketing programs. We analyze these data to provide empirical information on the extent to which different social marketing models have been used in different socio-economic contexts, and to identify the socio-economic context in which each model is most effective. Our analysis is restricted to programs that social market condoms or oral contraceptives. As only limited data on the features of social marketing programs are routinely collected, we focus on differences in management structure. In many countries, social marketing programs are an essential component of the national family planning and HIV prevention programs. At present, large-scale social marketing programs for reproductive health are in operation in over 60 countries worldwide. A growing body of evidence shows that social marketing programs can make an important contribution to the reproductive health of the target population [ 5 - 19 ]. In 2002, social marketing programs in 69 countries sold almost 1.6 billion condoms [ 20 ] accounting for more than half of all condoms available from public sources. Total sales of condoms, pills, vaginal foaming tablets and IUDs amounted to over 28 million couple-years of protection (a measure of the number of couples that could be protected from pregnancy for one year). In these countries (excluding China and Russia) social marketing sales of temporary methods of contraception excluding condoms accounted for almost 10 percent of all use [ 21 ]. Social marketing tends to be a cost-effective approach to achieving widespread access to health products and services [ 22 , 23 ]. It uses private sector incentives and organizations to achieve efficiency and revenues from sales offset some of the program costs. The total cost of $6 per couple-year of protection compares favorably with costs to implement public sector family planning programs, which are around $15–20 per couple-year of protection [ 24 - 27 ]. Some programs may eventually become self-sustaining and graduate from donor assistance altogether. Some social marketing programs in low-income countries are now operated by independent local social marketing foundations (e.g., the Ghana Social Marketing Foundation (GSMF) and ADEMAS in Senegal) and in some middle-income countries social marketing sales are continuing well after donor assistance has ended (e.g., condoms in Turkey, oral contraceptives in Morocco, and injectables in Brazil) [ 28 - 30 ]. Three different management structures are common in social marketing programs: 1) management by an affiliate of an international NGO, 2) management by local clinic-based or non-clinic-based organizations, and 3) partnerships with a commercial organization. The most commonly used management structure in health-oriented social marketing programs is management by an NGO. Typically this implies management by an affiliate of an international social marketing organization that provides an expatriate resident advisor. Several social marketing programs are managed by local organizations. For example, some social marketing programs are managed by a specially developed new organization that is independent of international affiliation. These are often called social marketing foundations . This organization may receive technical assistance from an international social marketing organization but it operates as an independent entity. Implementation may also be by an existing organization, such as a family planning association (FPA) or another type of clinic-based organization. In such case an international NGO provides technical assistance to the local organization to develop and operate the social marketing program. Social marketing programs may also be implemented through a partnership between an international NGO and an existing commercial organization. In this case, the international NGO often helps to develop the market for the product through research and promotion, while the commercial partner handles all aspects of packaging, sales and distribution. Not all management approaches are feasible in every context. For example, in countries with relatively high-income levels and a strong commercial sector there may be many opportunities for commercial partnerships, while in other countries there may be few such opportunities, if any [ 4 ]. Similarly, opportunities for management through existing local organizations do not exist in all countries. Furthermore, the context in which social marketing programs are implemented has a crucial impact on the types of programs that can be successful. For example, in a poor country with a rudimentary commercial sector, it is unlikely that commercial partnerships will be successful. On the other hand, in a middle-income country with a well-developed commercial sector and a rapidly developing middle class, it may be counterproductive to use an NGO affiliate model with a highly subsidized product that competes with existing brands. Methods This section analyses empirical data to study differences in social marketing models and their impact. Since data about program characteristics are scarce, we focus on differences in management structure. Specifically, our objectives are to 1) describe to what extent the type of social marketing management structure actually varies according to the socio-economic context in which the programs are implemented, and 2) to examine the effectiveness of various management structures in increasing socially marketed product sales in different contexts. Data For the purpose of this study, we compiled a database that comprises data on most of the major social marketing programs that were in operation at any time during the period between 1988 and 2001. Many, but not all, of these programs were still in operation in 2001. The database contains annual data on several program characteristics and on indicators of the local socio-economic context. The main sources of information for data on program characteristics were DKT International's "Contraceptive Social Marketing Statistics," Population Services International's (PSI) MIS database, and published data on Futures Group International (TFGI) programs [ 26 ]. These three programs are the dominant implementing organization in contraceptive social marketing [ 1 ]. Data on the local context were obtained from the "World Development Indicators 2003 CD-ROM" [ 31 ]. For each social marketing program, the database contains one case for each year of operation within the 1988–2001 study period. In other words, our unit of analysis is the "program-year." Using "program-years" as our unit of analysis has the advantage that all indicators, including program characteristics, can change over time. In addition, it implies that in the analyses programs that have been in operation for a longer period of time are given more weight than newer programs. For example, a social marketing program that has been operating since 1988 will contribute 14 program-years to the database (one case for each year of operation); a program that started in 1995 and was terminated in 1997 will contribute three program-years, and a program that started in 2001 will contribute only one program-year. After restricting the database to those social marketing programs that have a reproductive health component, the database contains information on social marketing programs in over 70 countries, which represent a total of 555 years of program experience. This includes 508 years of experience with condom social marketing and 208 years of experience with OC social marketing. Indicators Our measures of market potential are based on the indicators used by Michigan State University's Center for International Business Education and Research [ 32 ]. Specifically, we use the following indicators of market size, market intensity, and commercial infrastructure: Market size • Population size • Percentage of population living in urban areas Market intensity • Per capita GNI in current international dollars. This indicator measures the GNI converted in international dollars using purchasing power parity. An international dollar has the same purchasing power as a dollar in the U.S. [World Bank 2003] Commercial infrastructure • Telephone mainlines per 1,000 inhabitants • Television sets per 1,000 inhabitants The database also includes selected indicators of the characteristics of the social marketing programs, including: • Management structure (NGO affiliate, local clinic-based and non-clinic-based organizations, and commercial partnerships) • Program maturity/years of operation (less than 3 years, 4–6 years, and 7+ years) • Number of reproductive health products social marketed (one vs. two or more). Only condoms, oral contraceptives, injectables and IUDs are considered. In addition to these indicators of the socio-economic context and of the characteristics of the programs, information is available on the following outcome measures: • Per capita condom sales • Per capita OC sales While some social marketing programs distribute and/or promote injectables or IUDs, their number is not sufficiently large to allow multivariate analyses. Hence, data on sales of injectables and IUDs are not examined in this study. Other indicators of program effectiveness, such as user-prevalence rates are not collected on an annual basis. Ideally, one would also want to examine the cost-efficiency of implementing different social marketing models. A commonly used approach to estimate cost-efficiency is to conduct a cost-effectiveness analysis. By definition, any cost-effectiveness analysis requires obtaining data on both the effectiveness of the program, i.e. the impact of the program, and on the cost of implementing the program [ 33 , 34 ]. Unfortunately, only limited cost information on social marketing programs is available, and the cost data that are routinely collected by the main social marketing organizations are not comparable. Hence, we are unable to assess the cost-efficiency of the programs in our database. Methods In the next sections, we use cross-tabulations to examine to what extent management structure varies by socio-economic context. Since our unit of analysis consists of program-years of operation, these tabulations show the percentage of program-years that had each management type. We also test the extent to which different indicators of socio-economic context affect effectiveness of social marketing programs with different management structures. For this purpose, we use multiple regression analyses to assess the effect of indicators of socio-economic context on per capita condom sales for different management structures. Because each social marketing program has multiple entries in the data set (one for each year of operation), the standard errors in ordinary linear regression are incorrect. We use random-effects regression to solve the problem that observations for a given country-program are not independent [ 35 ]. For each type of management structure, we assess the net effect of socio-economic context on per capita condom sales, after controlling for the number of reproductive health products marketed, program maturity, time period (1995–2001 vs. earlier). Similar analyses are conducted for per capita OC sales. Results Variations in management structure by socio-economic context We now analyze our database to illustrate to what extent different management structures have been used in social marketing programs (see Table 1 ). Overall, data on the management structure of the social marketing programs were available for 555 program years. Of these 55 program years, 72% were managed through an NGO affiliate, 16% by local organizations, and 12% through a commercial partnership. Table 1 Distribution of Years of Social Marketing Program Experience by Management Structure and by Socio-Economic Context Distribution of Program Years % NGO Affiliate % Local Organizations % Commercial Partnership No. of Program Years Population Size <10 Million 76.3% 17.1% 6.6% 211 10–25 Million 62.7% 24.0% 13.3% 150 25+ Million 72.5% 9.0% 18.5% 189 Urban Population <25% 86.1% 13.9% 0.0% 101 25–49% 80.8% 7.7% 11.5% 260 50+% 47.0% 31.0% 22.0% 168 GNI per capita <$1000 97.0% 3.0% 0.0% 132 $1000–3000 68.2% 18.6% 13.2% 258 $3000+ 52.3% 24.5% 23.2% 151 Phone mainlines per 1,000 <5 87.1% 11.8% 1.1% 178 5–30 73.4% 9.2% 17.4% 184 30+ 53.8% 27.4% 18.8% 186 Television sets per 1,000 <20 88.2% 10.1% 1.8% 169 20–100 70.9% 18.7% 10.4% 182 100+ 48.5% 23.3% 28.2% 163 Time Period 1986–93 56.4% 25.4% 18.3% 126 1994–97 66.2% 18.5% 15.3% 216 1998–01 85.9% 8.0% 6.1% 213 Region Eastern Europe 100.0% 0.0% 0.0% 16 Africa 89.7% 7.7% 2.6% 273 Asia 64.2% 17.5% 18.3% 137 Latin America 42.9% 41.9% 15.2% 105 Mid. East/N. Afr. 13.6% 0.0% 86.4% 22 Total 71.5% 16.0% 12.4% 555 Social marketing programs in countries with populations smaller than 10 million have predominantly been managed by NGO affiliates (76% of program-years). In larger countries, other management structures have been somewhat more common. Breakdown by level of urbanization confirms that the range of management strategies used increased with socio-economic status. The percentage of social marketing program-years managed by NGO affiliates ranged from 86% when urbanization was low to 47% when urbanization was high. In highly urbanized populations, 31% of program-years were managed by existing local organizations and 22% by commercial partnerships. Social marketing programs in countries with a low per capita GNI (<$1,000) have been managed predominantly by NGO affiliates (97% of program-years), with local organizations being a distant second (3%). In countries with higher GNI levels, a wider range of management strategies has been used. When the per capita GNI levels are medium-low, management through NGO affiliates was still the most common (68% of all program-years). However, in medium-low GNI countries local organizations accounted for 18% of program years and commercial partnerships for 13%. Finally, when the GNI exceeded $3,000 per capita, NGO affiliates accounted for only 52% of program-years, followed by local organizations (25%) and commercial partnerships (23%). Our indicators of the level of development of the commercial infrastructure show that the NGO model has dominated in settings with a relatively poorly developed commercial infrastructure. For example, NGO affiliates accounted for roughly 87% of program years in countries with fewer than 5 phone mainlines per 1,000 inhabitants, and for 88% of program years in countries with fewer than 20 television sets per 1,000 in habitants. Management through existing local organizations and commercial partnerships is most common in settings with over 30 phone mainlines and over 100 television sets per 1,000 inhabitants. Management structures have also changed over time. For example, the percentage of program-years managed through NGO affiliates has steadily increased from 56% in 1986–93 to 86% in 1998–2001. Simultaneously, management through existing local organizations and commercial partnerships has gradually declined. The last panel of Table 1 shows that management through commercial partnerships has been most common in the Middle East and Northern Africa (87% of program-years), while management through existing organizations has been most common in Latin America (86% of program-years). In Eastern Europe and Africa management through NGO affiliates has dominated (90% and over). In Latin America, management through NGO affiliates and through local organizations have both been common (43% and 42%, respectively). The effect of socio-economic context on the effectiveness of different social marketing management structures We now use random-effect GLS regression analyses to examine to what extent market size, market intensity, commercial infrastructure, and program features (number of products social marketed and program maturity) affect per capita condom sales and per capita OC sales. The variable "number of television sets per 1,000 inhabitants" was removed from the multivariate analyses as it correlated too much with some of the other predictor variables. We conduct separate analyses for social marketing programs managed by NGO affiliates, commercial partnerships, and local organizations. Due to the small number of cases, we are unable to differentiate between existing organizations and new organizations. Management by NGO affiliates The second column in Table 2 shows the predictors of per capita condoms sales in social marketing programs managed by NGO affiliates. The results indicate that among social marketing programs managed through NGO affiliates per capita condoms sales increase significantly with the number of years of program maturity (β = .181 for programs with 4–6 years of maturity; β = .348 for programs with 7 or more years of maturity). Programs that social marketed two or more products have higher per capita condom sales than programs that just market condoms (β = .159). Table 2 Effect of Socio-Economic Context on Condom Sales and CYP Among Social Marketing Programs Managed Through an NGO Affiliate (Random-Effects Regression GLS Coefficients) Per Capita Condom Sales OC Sales Markets Two or More Products .159* .017 Program Maturity 1–3 (ref) 4–6 .181* .001 7+ .348* .003 Time Period <1994 (ref) 1995–2001 .143 .004 Population (in 10 millions) -.006*** -.000* Percent Urban -.002 -.000 Per Capita Gross National Income -.003 .007 Phone mainlines per 1,000 -.001 -.000 Constant .260* (dropped) R Square .236 .082 Number of Program-Years 374 90 Number of Countries Included 58 26 * p < .01; ** p < .05; * p < .10 As expected, social marketing programs managed through an NGO affiliate tend to be more effective, as measured by per capita condom sales, in countries with smaller populations (β = -.006). Per capita condom sales do not vary with the level of urbanization, per capita Gross National Income (an indicator of market intensity), nor with the number of phone mainlines (an indicator of the strength of commercial infrastructure). The third column in Table 2 shows the predictors of per capita OC sales. The results indicate that there is no evidence that our indicators of market size, market intensity, and commercial infrastructure have any significant impact on per capita OC sales. Management by commercial partnerships Table 3 shows the predictors of per capita condom sales in social marketing programs managed using the manufacturer's model. The results shown in Table 3 indicate that among social marketing programs managed through commercial partnerships, per capita condom sales tend to be higher in countries with smaller populations (β = -.012), and with a lower per capita gross national income (β = -.111). The level of commercial infrastructure, as measured by the number of telephone mainlines per 1,000 inhabitants, has a small but significant positive effect on per capita condom sales (β = .001). Table 3 Effect of Socio-Economic Context on Condom Sales and CYP Among Social Marketing Programs Managed Through the Manufacturer's Model (Random-Effects Regression GLS Coefficients) Per Capita Condom Sales OC Sales Markets Two or More Products .078 -.015* Program Maturity 1–3 (ref) 4–6 -.018 .003 7+ -.069 .007 Time Period <1994 (ref) 1995–2001 .099 .007 Population (in 10 millions) -.012* -.002 Percent Urban .001 -.000 Per Capita Gross National Income -.111 .015 Phone mainlines per 1,000 .001 -.000 Constant .278 .030 R Square .384 .185 Number of Program-Years 54 55 Number of Countries Included 9 12 * p < .01; ** p < .05; * p < .10 The third column in Table 3 reveals a different pattern for factors affecting per capita OC sales. Among social marketing programs managed through commercial partnerships, per capita OC sales appear to be lower for those programs that also market other products (β = -.015; p < .010). Our indicator of market intensity, per capita gross national income, has a significant positive effect on per capita OC sales (β = .015). However, population size and urbanization do not have any significant effect. Management by local clinic-based and non-clinic-based organizations Table 4 shows similar analyses for programs managed by local organizations (including both clinic-based and non-clinic-based organizations). The results show that programs in countries with larger populations have significantly higher per capita condom sales (β = .036). However, program in countries with higher levels of urbanization have lower per capita condom sales (β = -.012). Table 4 Effect of Socio-Economic Context on Condom Sales and CYP Among Social Marketing Programs Managed Through Local Organizations (Random-Effects Regression GLS Coefficients) Per Capita Condom Sales OC Sales Markets Two or More Products .075 -.012 Program Maturity 1–3 (ref) 4–6 .158 .022* 7+ .181 .028 Time Period <1994 (ref) 1995–2002 .138 -.010 Population (in millions) .036 .008 Percent Urban -.012* .001 Per Capita Gross National Income .006 .028* Phone mainlines per 1,000 .001 -.001* Constant .436 -.021 R Square .309 .401 Number of Program-Years 80 63 Number of Countries Included 17 12 * p < .01; ** p < .05; * p < .10 The third column in Table 4 shows that among social marketing programs implemented by local organization, OC sales are significantly higher for those programs that have been in operation for seven or more years (β = .031). For these types of social marketing programs per capita OC sales increase with population size (β = .008) and with level of urbanization (β = .028). The level of commercial infrastructure, as measure through the number of telephone mainlines per 1,000 inhabitants, has a small negative effect on per capita OC sales. Discussion Several studies have commented on the differences between social marketing programs that use the non-governmental organization model and those that use the manufacturer's model [ 1 - 3 ]. Although it is increasingly recognized that context-specific variations on these models are common, and that hybrid models exist [ 4 ], it is generally assumed that social marketing programs that use the manufacturer's model are most feasible in middle-income countries with a fairly well-developed commercial infrastructure, while NGO managed models work best in lower-income countries with less-developed commercial infrastructure. As yet, however, there has been little empirical evidence to verify these assumptions. This paper has used a database of annual data on social marketing programs in over 70 countries to verify the extent to which the different social marketing models that have been used vary across socio-economic contexts, and to test in which socio-economic context each of the models is most successful at increasing use of socially marketed products. A rigorous analysis of the relative effectiveness of different social marketing models would require detailed data about the characteristics of the program, including data about financial structures, branding, pricing (and level of subsidies), distribution, and promotion. Because data on the features of social marketing programs are limited, we focused on differences in the programs' management structure. Ideally, we would also like to examine are range of outcome measures, including per capita sales, the user-prevalence, and the unit-cost for each method. Since such prevalence and unit-cost data are unavailable, we have focused on per capita condom and OC sales. We have used empirical analyses to obtain a better understanding of the variations that exist in social marketing programs. Specifically, we have analyzed a database of annual statistics on social marketing programs in over 70 countries, accounting for a total of 555 years of program experience. The database contains annual data on the management structure, program maturity, the number of reproductive health products marketed, and on product sales. The database also contains indicators of the local socio-economic context (market size, market intensity, and commercial infrastructure), including the population size, level of urbanization, per capita GNI, number of telephone mainlines and television sets per 1,000 inhabitants. Our analyses have shown that of the 555 years of social marketing program experience covered by the database, over 70% has used the NGO management structure. Nevertheless, there are considerable variations in management structure. The NGO affiliate management structure has been the dominant model when the per capita GNI is below $3,000 and the level of urbanization below 50%. The data also show that use of the NGO management structure has increase dramatically over the course of our study period. The findings support the theory that there may be more opportunities for successful partnerships with the private sector in countries with a high per capita GNI. The highest percentage of such partnerships (23%) was found in countries with a GNI exceeding $3,000 per capita. This percentage decreases to 13% in countries with a per capita GNI between $1,000 and $3,000. None of the commercial partnerships in our database were in countries with a per capita GNI below $1,000. One of the reasons for this pattern may be that there is more commercial activity and a wider range of possible partners in countries with a higher per capita income. Users in those countries are also more likely to be able to afford the commercially sustainable brands that are marketed under this approach. Although the program characteristics usually appear to be appropriate for the local socio-economic context, it is questionable whether this has always been the case. For example, over 50% of program-years in countries with a medium-high GNI (over $3,000) used the NGO model, even though countries with such income levels typically provide opportunities for commercial partnerships. Our multivariate analyses identified the factors that affect per capita condom and OC sales for each of the four social marketing models. The reader is cautioned, however, that condom and OC sales may also be influenced by other factors that were not measured in our data base, such as HIV prevalence and overall levels of contraceptive prevalence. Bearing these cautions in mind, the analyses yielded the following key findings: Programs managed by NGO affiliates • Per capita condom sales are higher in countries with smaller populations. This may be influenced by the difficulty of achieving high distribution coverage in large, mostly rural countries (e.g., India, Indonesia, Vietnam, Nigeria) and/or the time it takes to large such large populations with social marketing campaigns. Also, social marketing programs in countries with a larger population may have more competition (e.g., India, South Africa). By contrast, several small countries have a high HIV/AIDS prevalence and/or limited method choice (e.g., sub-Saharan Africa); • Per capita condom sales are higher for more mature programs and those that market more than one product. This probably reflects improvements in distribution capability over time, as well as the cumulative effect of behavior change programs that stimulate demand. More developed programs with stronger distribution are also more likely to market several products; • Per capita condom sales do not vary with the level of urbanization, per capita income, or commercial infrastructure. These variables are more likely to affect access-related factors, such as product access and ability to pay. Other factors to look for that may affect sales are related to demand: level of effort of the social marketing program (which reflects funding levels), health context (HIV/AIDS and contraceptive prevalence) and competition from the public sector and other NGOs that may cancel out the higher market potential in the more developed countries; • None of the factors examined had any significant influence on the per capita OC sales of social marketing programs managed through an NGO affiliate. Programs managed by commercial partnerships • Per capita condom sales tend to be higher in countries with smaller populations and with a lower per capita growth. At first glance, this finding is counter-intuitive. That is, initially one would expect sales for commercial partnerships to increase with population and per capita GNI, because commercial program need both a high demand and ability to pay. However, as population size and income increase sales may decline due to increased competition from commercial and other suppliers. Several countries with middle-high incomes (Turkey, the Philippines, and Jordan) or large populations (Turkey, the Philippines, and Indonesia) have strong public sector programs that offer free contraceptives, as well as many commercial suppliers. Also, demand for condoms in these countries has been very low, given that HIV prevalence is low that other contraceptive methods are available. By contrast, smaller countries such as Haiti and Zimbabwe have high HIV rates, less choice of methods, and probably less competition from other suppliers. Programs managed by local clinic-based and non clinic-based organizations • Programs in countries with larger populations have significantly higher per capita condom sales. One likely explanation for this pattern is that local organizations tend to have good distribution networks, which pays off in countries with a larger population. Some of the larger countries (e.g., Bangladesh and Colombia) have well-established organizations with a big market share. For example, in Bangladesh SMC provides almost all condoms and the demand is very high; • OC sales are significantly higher for programs that have been in operation for seven or more years. The longer a program operates, the more developed its distribution is likely to be. Social marketing communication efforts are also more likely to pay off over the long run; • Programs in countries with a higher level of urbanization have lower per capita condom sales. This was anticipated, given that NGOs and family planning associations have a strong track record of serving users in peri-urban and rural areas. In addition, when urbanization increases, access to commercial products sold in pharmacies and other private sector outlets increases as well, which allows commercial suppliers to grow their market share and compete with social marketing and public sector products; • The level of commercial infrastructure, as measured through the number of telephone mainlines per 1,000 inhabitants has a small negative effect on per capita OC sales. This finding may reflect that a better commercial infrastructure implies more competition from commercial suppliers. Conclusions Our analyses of records on 555 years of experience with social marketing programs have illustrated the tendency to design social marketing programs with a management structure suitable for the local context. However, the evidence also shows examples where this has not been the case. While socio-economic context clearly influences the effectiveness of some of the social marketing models, program maturity and the size of the target population appear equally important. Consequently, it is crucial that social marketing programs are designed using the model or approach that is most suitable for the local context. Competing interests Dr. Meekers is the former Research Director of PSI (1996–2001), and has been a paid consultant for other PSI research projects. Author's contributions Dr. Meekers developed the study design, assisted with the analysis, and contributed to the writing of the final manuscript. Mr. Rahaim collected data, conducted literature reviews, and contributed to the editing of the paper. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548279.xml
555566	The levels of plasma low density lipoprotein are independent of cholesterol ester transfer protein in fish-oil fed F1B hamsters	Background Cholesterol ester transfer protein (CETP) plays a major role in regulating the levels of LDL- and HDL-cholesterol. We previously observed a fish-oil-induced elevation of low-density lipoprotein (LDL)-and very-low-density lipoprotein (VLDL)-cholesterol concentrations and a decrease in high-density lipoprotein (HDL)-cholesterol concentration in F1B hamsters. The molecular mechanism/s by which fish oil induces hyperlipidaemic effect was investigated in this study. We examined whether the effects of dietary fish oil on plasma lipoprotein concentrations are due to fish-oil-induced alterations in plasma CETP activity. MIX diet, a diet supplemented with a mixture of lard and safflower oil, was used as the control diet. Results We found that fish oil feeding in hamsters reduced CETP mass as well as CETP activity. Increasing the dietary fat level of fish-oil from 5% to 20% (w/w) led to a further decrease in CETP mass. Supplementation with dietary cholesterol increased both CETP mass and CETP activity in fish-oil and MIX-diet fed hamsters. However, there was no correlation between CETP mass as well as CETP activity and LDL-cholesterol concentrations. Conclusion These findings suggest that cholesterol ester transfer between HDL and LDL is not likely to play a major role in determining fish-oil-induced changes in LDL- and HDL-cholesterol concentrations in F1B hamsters. A possible role of reduced clearance of LDL-particles as well as dietary fat level and dietary cholesterol dependent changes in LDL-lipid composition have been discussed.	Background Fish oil, rich in n-3 polyunsaturated fatty acids (PUFA), is considered beneficial in lowering the risk of coronary heart disease [ 1 , 2 ]. The beneficial effects of n-3 PUFA are mainly due to reduction in plasma triacylglycerol and very-low-density lipoprotein (VLDL) levels [ 3 , 4 ]. However, the effect of fish oil on low-density lipoprotein (LDL)-cholesterol concentration is inconsistent [ 5 ]. High levels of LDL are strong predictors of coronary heart disease. Normolipidaemic subjects show reduction in plasma LDL-cholesterol concentrations following intake of fish oil diet [ 6 , 7 ], however, fish oil supplementation to hyperlipidaemic subjects causes an increase in LDL-cholesterol concentrations [ 8 , 9 ]. The fish-oil-induced increase in LDL-cholesterol concentration is also observed in animal studies [ 10 ]. One of the factors that determine LDL concentrations is reverse cholesterol transport pathway, which removes cholesterol from peripheral tissues and returns to the liver. Cholesterol ester transfer protein (CETP) plays a major role in this pathway to transfer cholesterol esters from high-density lipoproteins (HDL) to VLDL and LDL, in exchange for triacylglycerols [ 11 , 12 ]. Thus, increased CETP activity can cause elevation of LDL-cholesterol concentration while decreasing the HDL-cholesterol concentrations. A positive correlation between plasma CETP concentration and LDL-cholesterol concentration has been observed in primates [ 11 - 13 ]. Thus, fish-oil-induced elevation of LDL-cholesterol concentration might be explained by changes in plasma CETP concentration. CETP mediated exchange of cholesterol esters for triacylglycerols occurs mainly through an equimolar heteroexchange mechanism, which leads to alterations in cholesterol ester: triacylglycerol ratio. In addition to plasma CETP concentration, fatty acid composition of lipoproteins also modifies reverse cholesterol transfer. Cholesterol esters with n-3 polyunsaturated fatty acyl groups are more likely to transfer compared to cholesterol esters with saturated and monounsaturated fatty acyl groups [ 14 ]. This effect might be attributed to change in transition temperature of the lipid core of lipoproteins with change in lipid composition [ 15 ]. We previously observed fish-oil-induced elevation of VLDL-and LDL-cholesterol concentrations and decrease in HDL-cholesterol concentration in F1B hamsters [ 16 ]. In this study, we examined whether the effects of dietary fish oil on plasma lipoprotein concentrations are due to fish-oil-induced alterations in plasma cholesterol ester transfer protein activity. Results LDL-lipid composition The LDL-cholesterol, free cholesterol, cholesterol ester, phospholipid and triacylglycerol concentrations were measured in Bio F1B hamsters treated with fish-oil or MIX diet (Table 1 ). Fish-oil diet led to significantly higher concentrations of total cholesterol, cholesterol ester, free cholesterol, triacylglycerol and phospholipids compared to MIX diet. Increasing the dietary fat levels of fish oil from 5% w/w (low fat) to 20 % w/w (high fat) caused a significant increase in free cholesterol and LDL-triacylglycerol concentrations. On the contrary, LDL-cholesterol ester concentrations decreased significantly (p < 0.0001) when the amount of fat was increased in fish oil diet. There was no effect of increase in dietary fat levels on LDL-cholesterol, cholesterol ester, triacylglycerol or phospholipids concentrations in the hamsters fed with MIX diet. Cholesterol supplementation of the diet led to an increase in LDL-cholesterol, cholesterol ester, triacylglycerol and phospholipids concentrations in hamsters fed with fish-oil diet. However, cholesterol supplementation to the MIX diet had no effect on these parameters. Furthermore, the effect of dietary cholesterol was greater in low fat fish-oil diet fed hamsters compared to the high fat fish oil fed hamsters (Table 1 ). Table 1 LDL-lipid composition of hamsters fed with various diets. LDL-Lipids Diet Chol Low Fat 5% High Fat 20% Statistical significance (3 way ANOVA) Factor P value Total Cholesterol (mmol/l) FO - 4.84 ± 0.61 4.57 ± 0.36 DT 0.0001 + 8.84 ± 2.06 5.10 ± 1.00 DT × DL 0.0020 MIX - 1.54 ± 0.32 1.41 ± 0.25 DT × CHOL 0.0007 + 1.27 ± 0.25 1.63 ± 0.48 DL × CHOL 0.0200 Free Cholesterol (mmol/l) FO - 0.45 ± 0.05 1.53 ± 0.46 DL 0.0001 + 0.69 ± 0.17 1.99 ± 0.45 MIX - 0.28 ± 0.10 0.70 ± 0.13 + 0.38 ± 0.14 0.58 ± 0.15 Cholesterol Ester (mmol/l) FO - 4.08 ± 0.43 2.62 ± 0.84 DT 0.0001 + 8.05 ± 1.96 3.07 ± 1.00 CHOL 0.0001 MIX - 0.87 ± 0.30 0.88 ± 0.29 DT × DL 0.0300 + 0.80 ± 0.17 0.79 ± 0.17 DL × CHOL 0.0004 Triacylglycerol (mmol/l) FO - 0.65 ± 0.08 1.62 ± 0.27 DT 0.0001 + 1.01 ± 0.34 1.53 ± 0.22 DT × DL 0.0001 MIX - 0.24 ± 0.03 0.22 ± 0.04 DL × CHOL 0.0200 + 0.29 ± 0.07 0.17 ± 0.01 Phospholipids (mmol/l) FO - 0.69 ± 0.10 0.66 ± 0.11 DT 0.0001 + 0.98 ± 0.18 0.73 ± 0.10 CHOL 0.03 MIX - 0.37 ± 0.07 0.36 ± 0.06 DT × DL 0.03 + 0.33 ± 0.05 0.36 ± 0.04 DT × CHOL 0.009 FO, fish oil; MIX, MIX diet; Chol, cholesterol; DT, diet type; DL, diet level; CHOL, Cholesterol For details of diets and procedures, see "Materials and methods" section. Animals were fed the indicated diets for 2 weeks. All values represent means ± SD. Change in dietary fat level altered the LDL-cholesterol ester: triacylglycerol ratio (Figure 1 ). There was a significant decrease in LDL-cholesterol ester: triacylglycerol ratio in fish-oil diet fed hamsters when the dietary fat level was increased from 5 % to 20 % (Figure 1A ). However, there was no significant effect of dietary fat level on LDL-cholesterol ester: triacylglycerol ratio in the MIX diet fed hamsters (Figure 1B ). Addition of cholesterol to the high fat fish-oil diet caused a slight but significant increase in LDL-cholesterol ester: triacylglycerol ratio compared to the high fat fish oil diet alone (Figure 1A ). However, addition of cholesterol to the MIX diet had no significant effect on cholesterol ester: triacylglycerol ratio compared to hamsters fed the MIX diet alone (Figure 1B ). Figure 1 Cholesterol ester: triacylglycerol ratio in fish-oil (A) and MIX-diet (B) fed hamsters . Hamsters were fed fish oil (FO) or MIX diet at a low fat (5% w/w) or a high fat (20% w/w) level in the absence (pink) or presence (blue) of 0.25% w/w cholesterol. Lipids were analyzed as described in the methods. Values are means for 12 animals with standard deviations shown by vertical bars. Differences between groups were evaluated using Student's t test. HDL-lipid composition Changes in HDL-lipid composition in Bio F1 B hamsters on different diets are given in Table 2 . Fish-oil diet fed hamsters had significantly lower concentrations of HDL-cholesterol, free cholesterol, cholesterol ester and phospholipids compared to MIX-diet fed hamsters. However, there was no significant effect of fish-oil on HDL-triacylglycerol concentrations. Increasing the dietary fat levels from low fat to high fat caused a decrease in cholesterol ester concentrations in fish-oil diet fed hamsters. Cholesterol supplementation caused an increase in HDL-cholesterol and cholesterol ester concentrations irrespective of the diet type in low fat fed hamsters. However, there was no effect of dietary cholesterol on HDL-cholesterol concentration in high fat fed hamsters. Cholesterol supplementation led to a significant increase in phospholipids concentration for all type of diets, both at low and high fat levels. Table 2 HDL-lipid composition of hamsters fed with various diets. HDL-Lipids Diet Chol Low Fat 5% High Fat 20% Statistical significance (3 way ANOVA) Factor P value Total Cholesterol (mmol/l) FO - 2.90 ± 0.29 2.19 ± 0.48 DT 0.0001 + 3.96 ± 0.87 2.24 ± 0.56 CHOL 0.0020 MIX - 4.74 ± 0.07 5.86 ± 0.37 DT × DL 0.0001 + 6.00 ± 1.23 6.78 ± 0.45 Free Cholesterol (mmol/l) FO - 0.18 ± 0.08 0.31 ± 0.07 DT 0.0001 + 0.31 ± 0.08 0.25 ± 0.16 MIX - 0.60 ± 0.17 0.57 ± 0.03 + 0.60 ± 0.17 0.59 ± 0.12 Cholesterol Ester (mmol/l) FO - 2.67 ± 0.29 1.88 ± 0.41 DT 0.0001 + 3.88 ± 0.71 1.98 ± 0.49 CHOL 0.0009 MIX - 3.55 ± 0.61 4.34 ± 0.42 DT × DL 0.0001 + 4.33 ± 0.80 5.34 ± 0.96 Triacylglycerol (mmol/l) FO - 0.32 ± 0.03 0.44 ± 0.12 DT × DL 0.0400 + 0.39 ± 0.14 0.33 ± 0.10 DL × CHOL 0.0400 MIX - 0.37 ± 0.03 0.32 ± 0.03 + 0.40 ± 0.09 0.30 ± 0.04 Phospholipids (mmol/l) FO - 0.57 ± 0.12 0.59 ± 0.16 DT 0.0001 + 1.62 ± 0.43 1.27 ± 0.23 DL 0.01 MIX - 3.43 ± 0.26 2.91 ± 0.33 CHOL 0.0003 + 4.20 ± 0.45 4.67 ± 0.46 DT × DL 0.0005 DT × CHOL 0.05 DL × CHOL 0.0007 FO, fish oil; Mix, MIX diet; Chol, cholesterol; DT, diet type; DL, diet level; CHOL, cholesterol. For details of diets and procedures, see "Materials and methods" section. Animals were fed the indicated diets for 2 weeks. All values represent means ± SD. Surface lipid to core lipid ratio for LDL and HDL The LDL surface lipids (free cholesterol and phospholipids) to core lipids (cholesterol esters and triacylglycerols) ratio was higher in MIX diet fed hamsters compared to hamsters fed the fish oil diet, at both low and high fat levels (Table 3 ). Increasing the quantity of fat in the diet increased the surface to core lipid ratio, whereas addition of dietary cholesterol had no significant effect, in both fish oil and MIX diet fed hamsters (Table 3 ). The HDL surface lipid to core lipid ratio was also higher in MIX diet fed hamsters compared to the fish oil fed hamsters, at both low fat and high fat levels (Table 3 ). Addition of cholesterol to the fish oil diet caused a significant increase in surface lipid to core lipid ratio, at both low and high fat levels, whereas no significant effect of dietary cholesterol was observed for the MIX diet (Table 3 ). Table 3 Surface lipid to Core lipid ratio of LDL and HDL particles from hamsters fed with various diets. Surface lipid: Core lipid Particle Type Fat level Fish Oil Mix - Cholesterol + Cholesterol - Cholesterol + Cholesterol LDL 5% 0.24 0.18 0.59 0.65 20% 0.52 0.59 0.96 0.98 HDL 5% 0.25 0.45 1.02 1.01 20% 0.39 0.69 0.75 0.93 Surface lipids are composed of free cholesterol and phospholipids. Core lipids are composed of cholesterol esters and triacylglycerols. The surface lipid to core lipid ratio was calculated by dividing the mean surface lipids with mean core lipids. CETP activity and CETP mass It has been shown previously that there is a correlation between the level of CETP and that of LDL-cholesterol. To further investigate our observation of fish-oil-induced elevation of LDL-cholesterol concentrations and a decrease in HDL-cholesterol concentration in F1B hamsters, we measured CETP mass as well as CETP activity. The changes in CETP mass and CETP activity are shown in Figure 2 and 3 respectively. Treatment of hamsters with fish-oil diet led to a decrease in CETP mass (p < 0.0001) and CETP activity (p < 0.002) compared to MIX diet, at low fat level. Increasing the dietary fat levels from low fat to high fat caused a further decrease in CETP mass in fish-oil diet fed hamsters, whereas same change brought an increase in CETP mass in MIX diet fed hamsters (DT × DL interaction, p < 0.002). On the other hand, plasma CETP activity increased in both fish-oil and MIX-diet fed hamsters by increasing the dietary fat levels. Dietary cholesterol caused an increase in CETP mass (p < 0.0002) and CETP activity (p < 0.0001) in both fish-oil and MIX-diet fed hamsters at low fat level. However, cholesterol mediated increase in CETP activity was not observed at high fat levels for both fish oil and MIX diets. Figure 2 Plasma CETP mass in fish-oil and MIX-diet fed hamsters . Plasma CETP mass in hamsters fed with a fish-oil (FO) or a MIX-diet at a low fat (5% w/w) or a high fat (20% w/w) level in the absence (pink) or presence (blue) of 0.25% w/w cholesterol. Plasma was collected and assayed for CETP mass using ELISA as described in the methods. Values are means for 12 animals with standard deviations shown by vertical bars. Differences between groups were evaluated using 3-way ANOVA. Values without a common superscript are significantly different from each other. Figure 3 Plasma CETP activity in fish-oil and MIX-diet fed hamsters . Plasma CETP activity in hamsters fed with a fish-oil (FO) or a MIX-diet at a low fat (5% w/w) or a high fat (20% w/w) level in the absence (pink) or presence (blue) of 0.25% w/w cholesterol. Plasma was collected and assayed for CETP activity using a radioisotope method as described in the methods. Values are means for 12 animals with standard deviations shown by vertical bars. Differences between groups were evaluated using 3-way ANOVA. Values without a common superscript are significantly different from each other. Correlation between CETP mass and CETP activity CETP mass was significantly and positively correlated with CETP activity in low fat fish oil (r = 0.81, p < 0.03) and MIX diet (r = 0.96 p < 0.0003) fed hamsters (Figure 4A ) and high fat MIX diet fed hamsters (r = 0.84, p < 0.02) (Figure 4B ). The correlation between CETP mass and CETP activity in high fat fish-oil fed hamsters was not significant. This indicates that CETP activity is an accurate reflection of CETP mass in both fish-oil and MIX-diet fed hamsters at low fat levels. Figure 4 Correlation between CETP activity and CETP mass in fish-oil and MIX-diet fed hamsters . Correlation between CETP activity and CETP mass in hamsters fed with a fish-oil (blue) or a MIX (red) diet, supplemented with low fat (5% w/w) (panel A) or high fat (20% w/w) (panel B). Plasma was collected and assayed for CETP activity and CETP mass as described in the methods. Correlation between CETP and LDL-lipid levels The correlations between CETP mass, CETP activity and LDL-cholesterol are shown in Figure 5 and 6 respectively. There was no significant correlation between CETP mass and LDL-cholesterol concentrations in fish-oil diet (r = 0.56) or MIX diet (r = 0.48) fed hamsters. Similarly, the CETP activity was not significantly correlated with LDL-cholesterol concentrations in fish-oil (r = 0.48) or MIX diet (r = 0.45) fed hamsters. Figure 5 Correlation between CETP mass and LDL-cholesterol in fish-oil and MIX-diet fed hamsters . Correlation between CETP mass and LDL-cholesterol in hamsters fed with a fish-oil (blue) or a MIX (red) diet. Plasma CETP mass and LDL-cholesterol concentration were assayed as described in the methods. Figure 6 Correlation between CETP activity and LDL-cholesterol in fish-oil and MIX-diet fed hamsters . Correlation between CETP activity and LDL-cholesterol in hamsters fed with a fish-oil (blue) or a MIX (red) diet. Plasma CETP activity and LDL-cholesterol concentration were assayed as described in the methods. Discussion CETP plays an important role in maintaining the levels of plasma LDL and HDL [ 12 ]. Increased levels of plasma CETP cause an increase in the transfer of cholesterol esters from HDL to LDL, thereby raising the levels of LDL. In recent years, antibodies have been raised against CETP as a therapy to lower plasma LDL-levels and to prevent cardiovascular disease [ 12 ]. Fish oil has also gained much interest in the recent years as a therapy against cardiovascular disease. Earlier, we observed that fish oil caused an increase in plasma lipid and lipoprotein levels in a unique animal model, the F1B hamster [ 16 ]. In this study, we investigated whether the increase in plasma LDL-levels in fish-oil fed F1B hamsters is due to an increase in plasma CETP activity. Fish oil caused an increase in LDL-cholesterol concentration and a decrease in HDL-cholesterol concentration compared to hamsters fed a MIX diet (Table 1 and 2 ). However, CETP activity and CETP mass were lower in fish-oil fed hamsters compared to the MIX-diet fed hamsters. Earlier studies in human subjects also show fish-oil-induced reduction in CETP activity compared to safflower oil fed counter parts [ 17 , 18 ]. Moreover, we did not find significant correlation between CETP mass as well as CETP activity and LDL-cholesterol in this study. Data presented here suggests that cholesterol ester transfer between HDL and LDL is not likely to play a major role in determining fish-oil-induced changes in LDL- and HDL-cholesterol concentrations. Cholesterol esters are more liable to transfer in fish-oil fed subjects since the core of the lipoprotein particles from these subjects have lower transition temperature [ 15 ] due to abundance of long chain polyunsaturated fatty acids. This theory is in agreement with the finding that there is increased cholesterol ester mass transfer in eicosapentaenoic acid (omega-3 20:5, EPA) fed rabbits while there was no change in plasma CETP activity [ 14 ]. We did not measure cholesterol ester mass transfer to determine the contribution of HDL-and LDL-fatty acid composition in order to explain fish-oil- induced elevation of LDL-cholesterol concentration. However, our data shows that the LDL and HDL surface lipid to core lipid ratio is significantly lower in fish oil fed hamsters than the MIX diet fed hamsters, at both low and high fat levels. Thus, the composition of the LDL and HDL particles appears to be significantly different between the fish oil and MIX diet fed hamsters. It has previously been shown that the LDL particle composition is an important determinant of LDL clearance [ 19 ]. In our previous study [ 16 ] we have shown that hepatic LDL-receptor mRNA levels were significantly low in fish-oil fed hamsters. In addition there are reports that in cases of CETP deficient subjects, LDL-particles have reduced affinity for LDL-receptor [ 20 ]. One can hypothesize that the increase in both LDL-cholesterol and triacylglycerol concentrations (Table 1 ) in fish-oil fed hamsters may points towards suppression of LDL clearance rather than increased cholesterol ester/triacylglycerol exchange as the cause. Increasing dietary fat level of fish oil decreased cholesterol ester transfer as reflected by decrease in CETP mass (Figure 2 ). Thus, dietary fat level dependent reduction in LDL-cholesterol ester: triacylglycerol ratio in fish-oil diet fed hamsters (Figure 1A ) might be due to the decrease in cholesterol ester transfer. However, in contrast to CETP mass, CETP activity slightly increased with the increase of dietary fat level. The plasma used for CETP activity assay in high fat fish-oil fed hamsters contained very high levels of chylomicrons, VLDL and LDL, which are potential acceptors of cholesterol esters from radiolabeled exogenous HDL [ 21 ]. Thus, CETP activity of high fat fish-oil fed hamsters might be an exaggerated reflection of CETP mass. HDL-total cholesterol and cholesterol ester concentrations were significantly lower in fish-oil diet fed hamsters compared to MIX-diet fed hamsters, while there was no difference in HDL-triacylglycerol concentrations (Table 2 ). Previous studies using hamsters [ 22 , 23 ] and non-human primates [ 24 ] have shown decreased HDL-cholesterol concentrations following fish oil feeding, which support our observation. Plasma HDL-cholesterol concentration is mainly regulated by reverse cholesterol transport pathway and cellular cholesterol efflux [ 25 , 26 ]. The reduction of HDL-cholesterol concentration, while decrease in cholesterol ester transfer in fish-oil fed hamsters compared to MIX-diet fed hamsters implicates that fish-oil-induced HDL-cholesterol lowering effect is not due to the changes in cholesterol ester transfer, but might be attributed to decreased efflux of cholesterol from peripheral cells. Increasing the dietary fat level from low fat to high fat caused a decrease in HDL-total cholesterol and cholesterol ester levels (Table 2 ), which might be due to poor esterification of HDL-free cholesterol-to-cholesterol esters by lecithin-cholesterol-acyl-transferase (LCAT) as n-3 PUFA are known to be less utilized by LCAT for the formation of cholesterol esters [ 27 , 28 ]. Dietary cholesterol supplementation led to an increase in HDL-cholesterol concentration and also caused an increase in CETP mass/activity in both fish-oil and MIX-diet fed hamsters. This finding suggest that cholesterol mediated increase in HDL-cholesterol was not associated with changes in cholesterol ester transfer, but might be due to other factors, possibly due to an increased cholesterol efflux from peripheral cells. The interactive effect of dietary cholesterol and n-3 PUFA on plasma cholesterol ester transfer is not yet known. Cholesterol supplementation caused an increase in plasma CETP activity in both fish-oil and MIX-diet fed hamsters at low fat levels (Figure 3 ), which is consistent with other reports [ 29 ]. These observations suggest that the regulation of CETP is dependent on the presence of dietary cholesterol. Dietary cholesterol is known to increase plasma CETP concentrations [ 29 ]. The increase in plasma CETP concentrations in response to dietary cholesterol is due to an increase in CETP mRNA levels in adipose tissue and liver [ 30 , 31 ]. In hamsters, CETP is mainly expressed in the adipose tissue, and the cholesterol mediated increase in plasma CETP activity is directly related to an increase in adipose tissue CETP mRNA levels [ 31 ]. Our findings are consistent with the previous observations that the regulation of CETP is dependent on dietary cholesterol. However, our observations show that the supplementation of cholesterol to the high fat fish oil and MIX diet had no significant effect on CETP activity as compared to high fat fish oil and MIX diet alone (Figure 3 ). These findings suggest that high fat diets interfere with cholesterol to regulate CETP, which is similar to the observations made for the regulation of the human CETP gene (under publication). Conclusion In summary, fish oil induced increase in LDL-cholesterol concentration in F1B hamsters, as well as effects of diet type, diet fat level and dietary cholesterol level on HDL-lipids were not associated with changes in plasma cholesterol ester transfer activity. It is likely that the dietary fat composition altered the LDL-core lipid composition, which in turn inhibited the uptake of LDL particles. This in combination with decrease of LDL-receptor mRNA levels may be the likely cause of increased plasma LDL-levels in fish-oil fed F1B hamsters. Methods Animals and diets The F1B hamsters (7 weeks old) were obtained from Bio Breeders Inc. (Water Town, MA) and kept on chow diet for one week prior to feeding specific diets. After this equilibration period, hamsters were divided into 8 groups (n = 12) and each group was fed with one of the specified diets. The specified diets consisted of fat free semi-purified diet (ICN Biomedical Inc., OH) that was supplemented with either fish oil (menhaden oil, Sigma Chemical Co., St. Louis, MO) or a mixture of lard and safflower oil in 1.5:1 ratio (MIX diet) [ 16 ]. The fat content of the diets was either 5% w/w (low fat) or 20% w/w (high fat). Due to the presence of cholesterol in fish oil, the low fat fish oil diet contained 0.025% w/w of cholesterol, and the high fat fish-oil diet contained 0.1% w/w of cholesterol. Thus, the same amount of cholesterol was added to the low fat and the high fat MIX diets to keep cholesterol content similar. For the high cholesterol diets, the fish oil and MIX diets were supplemented with additional cholesterol to bring the final concentration of cholesterol to 0.25% w/w. All diets were stored at -20°C and animals were given fresh diets each day. The animals were maintained on specific diets for 2 weeks ad libitum. The food intake was measured daily during the study period, and the body weight was checked at the beginning of the study period, one week later and at the conclusion of the study. There was no difference in food intake and body weight gain between different diet groups. All animals were housed in individual cages in a single room with enriched environment. The Institutional Animal Care use Committee (IACC) approved all experimental procedures, which are in accordance with the principles and guidelines of the Canadian Council on Animal Care. After two weeks on specified diets the animals were sacrificed after 14 hrs of fasting. Blood was collected by cardiac puncture into tubes containing EDTA and centrifuged immediately to separate plasma. Plasma samples were stored at 4°C on ice until further use. Lipoprotein separation and analysis Plasma was centrifuged at 15,500 g for 20 min at 12°C [ 32 ] to separate chylomicrons. The infranatant was separated and used for isolation of other lipoproteins fractions i.e. VLDL, LDL and HDL by sequential density ultra centrifugation [ 33 ]. Isolated individual lipoprotein fractions i.e. VLDL, LDL and HDL were stored at 4°C for further analysis. Total cholesterol concentration was assayed in all lipoprotein fractions using cholesterol assay kit # 402 (Sigma Diagnostics Inc, St. Louis, MO). Total triacylglycerol concentration of lipoprotein fractions was assayed using triglyceride assay kit # 344 (Sigma Diagnostics Inc, St. Louis, MO). Free cholesterol in plasma and individual lipoprotein fractions was assayed using free cholesterol assay kit (Wako Chemicals, VA). Cholesterol ester concentration was determined by subtracting the free cholesterol concentration from total cholesterol concentration. Phospholipids were analyzed using the method of Bartlett [ 34 ]. Cholesterol ester transport protein (CETP) activity assay CETP in the plasma samples was assayed by a radioactive method [ 21 ] that was modified from a previously published method [ 35 ]. LDL- and HDL-lipoprotein fractions were isolated from human plasma [ 36 ] and the HDL-fraction was radiolabeled, using 14 C-cholesterol oleate [ 35 ]. Plasma (5 μl) was combined with radiolabeled HDL (5 μg), LDL (50 μg) and 115 μl of incubation buffer (10 mM Tris, 150 mM NaCl, 2 mM EDTA) and incubated at 37°C for 1 hr. The LDL fraction was separated by heparin-manganese precipitation. The radioactivity in the supernatant and the precipitate was counted and the results were expressed as percent cholesterol ester(CE) transferred/hour. CETP mass CETP mass in plasma samples was quantitatively assayed using CETP ELISA- DAIICHI kit (Daiichi Pure Chemicals Co., LTD, Tokyo) as previously published [ 21 ]. Concentrations of the samples were calculated using a standard curve developed using a CETP stock solution with known concentration. Statistical analysis The effect of diet type, dietary fat level and dietary cholesterol was determined using 3-way analysis of variance, and a Tukey's post hoc test was used to test significant differences revealed by the ANOVA. Values are group means ± SD, n = 12; Differences were considered to be statistically significant if the associated P value was <0.05 [ 37 ]. Competing interests The author(s) declare that they have no competing interests. Authors' contributions PPD conducted all the experiments in this study. PPD and AAM analyzed and interpreted the data, as well as drafted the manuscript. PJD is a collaborator on this project. SKC is the Principal investigator, has conceived the study, participated in its design and final approval of the version to be published. All Authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555566.xml
519022	Garlic's ability to prevent in vitro Cu2+-induced lipoprotein oxidation in human serum is preserved in heated garlic: effect unrelated to Cu2+-chelation	Background It has been shown that several extracts and compounds derived from garlic are able to inhibit Cu 2+ -induced low density lipoprotein oxidation. In this work we explored if the ability of aqueous garlic extract to prevent in vitro Cu 2+ -induced lipoprotein oxidation in human serum is affected by heating (a) aqueous garlic extracts or (b) garlic cloves. In the first case, aqueous extract of raw garlic and garlic powder were studied. In the second case, aqueous extract of boiled garlic cloves, microwave-treated garlic cloves, and pickled garlic were studied. It was also studied if the above mentioned preparations were able to chelate Cu 2+ . Methods Cu 2+ -induced lipoprotein oxidation in human serum was followed by the formation of conjugated dienes at 234 nm and 37°C by 240 min in a phosphate buffer 20 mM, pH 7.4. Blood serum and CuSO 4 were added to a final concentration of 0.67% and 0.0125 mM, respectively. The lag time and the area under the curve from the oxidation curves were obtained. The Cu 2+ -chelating properties of garlic extracts were assessed using an approach based upon restoring the activity of xanthine oxidase inhibited in the presence of 0.050 mM Cu 2+ . The activity of xanthine oxidase was assessed by monitoring the production of superoxide anion at 560 nm and the formation of uric acid at 295 nm. Data were compared by parametric or non-parametric analysis of variance followed by a post hoc test. Results Extracts from garlic powder and raw garlic inhibited in a dose-dependent way Cu 2+ -induced lipoprotein oxidation. The heating of garlic extracts or garlic cloves was unable to alter significantly the increase in lag time and the decrease in the area under the curve observed with the unheated garlic extracts or raw garlic. In addition, it was found that the garlic extracts were unable to chelate Cu 2+ . Conclusions (a) the heating of aqueous extracts of raw garlic or garlic powder or the heating of garlic cloves by boiling, microwave or pickling do not affect garlic's ability to inhibit Cu 2+ -induced lipoprotein oxidation in human serum, and (b) this ability is not secondary to Cu 2+ -chelation.	Background Garlic ( Allium sativum ) has been cultivated since ancient times and used as a spice and condiment for many centuries [ 1 ]. During the past years, there has been a growing awareness of the potential medicinal uses of garlic [ 2 - 5 ]. The antioxidant properties of garlic are well documented [ 6 - 8 ]. In particular, aqueous garlic extract [ 9 ] and aged garlic extract [ 10 - 12 ] are able to prevent Cu 2+ -induced low density lipoprotein (LDL) oxidation. In addition, Ide et al . [ 10 ] and Ho et al . [ 13 ] have shown that some garlic compounds such as S-allylcysteine, N-acetyl-S-allylcysteine, S-allylmercaptocysteine, alliin, and allixin, are also able to prevent Cu 2+ -induced LDL oxidation. Ou et al . [ 14 ] showed that the garlic compounds S-ethylcysteine, N-acetylcysteine, diallyl sulfide, and diallyl disulfide inhibit amphotericin- and Cu 2+ -induced LDL oxidation. Huang et al . [ 15 ] showed that diallyl sulfide, diallyl disulfide, S-allylcysteine, S-ethylcysteine, S-methylcysteine, and S-propylcysteine are able to prevent glucose-induced lipid oxidation in isolated LDL. The protective effect of aged garlic extract [ 10 , 11 ] and S-ethylcysteine, N-acetylcysteine, diallyl sulfide, and diallyl disulfide [ 14 ] on Cu 2+ -induced LDL oxidation may be explained, at least in part, for their ability to chelate Cu 2+ . Interestingly, the diethyl ether extract of aged garlic extract, which also inhibits Cu 2+ -induced LDL oxidation, is unable to chelate Cu 2+ [ 11 ] indicating that its ability to prevent LDL oxidation is unrelated to Cu 2+ -chelation. On the other hand, 95% of the sulfur in intact garlic cloves is found in two classes of compounds in similar abundance: the S-alkylcysteine sulfoxides and the γ-glutamyl-S-alkylcysteines [ 16 ]. The most abundant sulfur compound in garlic is alliin (S-allylcysteine sulfoxide), which is present at 10 mg/g fresh garlic or 30 mg/g dry weight [ 16 ]. When garlic cloves are cut, crushed, or chopped (or when the powder of dried cloves becomes wet in a non-acid solution), the cysteine sulfoxides, which are odorless, are very rapidly converted to a new class of compounds, the thiosulfinates which are responsible for the odor of freshly chopped garlic. The formation of thiosulfinates takes place when the cysteine sulfoxides, which are located only in the clove mesophyll storage cells, come in contact with the enzyme allinase or alliin lyase (E.C. 4.4.1.4), which is located only in the vascular bundle sheath cells. Allinase is active at pH 4–5.8, but is immediately inhibited at acidic pH values below 3.5 or by cooking. Furthermore, microwave heating destroys allinase activity in 1 min [ 17 ]. Due to the abundance of alliin, the main thiosulfinate formed upon crushing garlic is allicin [ 16 ]. The half-life of allicin at room temperature is 2–16 hours; however, in crushed garlic (or in garlic juice) it is 2.4 days [ 16 ]. Several studies have been performed to test the effect of heating on several garlic properties. It has been shown that the boiling of garlic cloves by 15 min impairs significantly its ability to inhibit cyclooxygenase activity [ 18 ] and thromboxane B 2 synthesis [ 19 ]. In addition, heating of garlic cloves by 60 seconds in microwave reduces its anticancer properties [ 17 ]. Interestingly when microwave heating was applied 10 minutes after garlic crushing the anticancer properties were preserved indicating that allinase activation is necessary to generate anticancer compounds which are heat stable [ 17 ]. In a similar way, the hydroxyl scavenging properties of garlic were essentially preserved when garlic extracts were heated at 100°C by 20, 40 or 60 min [ 20 ]. In contrast, heating of garlic extracts by 10 min at 100°C reduced the bactericidal activity against Helicobacter pylori [ 21 ] and the ability to inhibit platelet aggregation [ 22 ]. However, to our knowledge, there are no studies exploring if the heating of garlic cloves or aqueous extract of raw garlic or garlic powder are able to inhibit Cu 2+ -induced lipoprotein oxidation in human serum. In the present paper we studied if the ability of aqueous garlic extracts to inhibit in vitro Cu 2+ -induced lipoprotein oxidation in human serum is altered in the following aqueous preparations: (a) heated extract of garlic powder, (b) heated extract of raw garlic, (c) extract of boiled garlic cloves, (d) extract of microwave-treated garlic cloves, and (e) extract of pickled garlic. In addition it was studied if the above mentioned preparations are able to chelate Cu 2+ . It was found that (a) the heating of garlic extracts or garlic cloves had no influence on the ability of garlic extracts to prevent in vitro Cu 2+ -induced lipoprotein oxidation in human serum, and (b) this protective effect was unrelated to Cu 2+ -chelation. Methods Materials and reagents Bulbs of garlic were from a local market. Garlic powder was from McCormick (Mexico City, Mexico). Copper sulfate, Na 2 EDTA, Na 2 CO 3 , KH 2 PO 4 , and Na 2 HPO 4 were from JT Baker (Mexico City, Mexico). Copper sulfate was dissolved in distilled water. Xanthine oxidase, xanthine, and nitroblue tetrazolium (NBT) were from Sigma Chemical Co. (St. Louis, MO., USA). Preparation of aqueous extracts of garlic Extract of garlic powder (GP) Garlic powder was weighted (0.6 g), dissolved, and stirred with 6 mL of distilled water for 20 min. This solution was centrifuged at 20,124 × g for 5 min at 4°C. The supernatant was recovered and used at the final concentration of 0.05, 0.075, 0.10, and 0.25 mg/mL. Heated extract of garlic powder (HGP) The procedure was similar to the previous one except that the mixture was boiled for 20 min before the centrifugation. The supernatant was recovered and used at the final concentration of 0.05 and 0.10 mg/mL. Extract of raw garlic (RG) Garlic cloves were peeled off, weighted, chopped, and homogenized with distilled water in a Polytron (Model PT2000, Brinkmann, Switzerland). This homogenate was centrifuged at 1,277 × g for 10 min and the supernatant was centrifuged at 20,124 × g for 5 min at 4°C. The supernatant was recovered and used at the final concentration of 0.125, 0.25, 0.5, and 0.75 mg/mL. Heated extract of raw garlic (HRG) The procedure was similar to the previous one except that the homogenate was boiled for 20 min before the second centrifugation step. The amount of water evaporated was replaced at the end of the heating. The supernatant was recovered and used at the final concentration of 0.25 and 0.5 mg/mL. Extract of boiled garlic (BG) Unpeeled garlic cloves were boiled in water for 10 min. After this time, garlic cloves were peeled off and the aqueous extract was prepared as described before (extract of raw garlic). The supernatant was recovered and used at the final concentration of 0.25 and 0.5 mg/mL. Extract of garlic cloves submitted to microwave heating (MG) Unpeeled garlic cloves were submitted to microwave heating for 1 min (1100 watts). After this time, garlic cloves were peeled off and the aqueous extract was prepared as described before (extract of raw garlic). When allinase is inactivated by heating, the cascade of thiosulfinate formation is blocked from alliin, and allicin and its derivates can not be formed. It has been shown that as little as 60 seconds of microwave heating can totally destroy allinase enzyme activity whereas microwave heating for 30 seconds inhibits 90% of allinase activity compared with unheated garlic [ 17 ]. The supernatant was recovered and used at the final concentration of 0.25 and 0.5 mg/mL. Preparation of pickled garlic (PG) Garlic cloves were peeled off carefully to avoid allinase activation and put in an aqueous solution of vinegar (1:1, v/v) and then heated to the boiling point for 30 min. Garlic cloves were put into jars with same solution and then pasteurized for 5 min at 72°C. The jars were closed immediately and stored at 4°C. The experiments with pickled garlic were performed five weeks after. The aqueous extract was prepared as described before (extract of raw garlic). The supernatant was recovered and used at the final concentration of 0.25 and 0.5 mg/mL. Blood collection Blood samples were obtained from 2 male and 3 female healthy volunteers aged 24 to 46 years. The experimental protocol is in compliance with the Helsinki Declaration and written informed consent was obtained from all subjects. A fasting blood sample was drawn from the antecubital fossa vein into glass tubes, allowed to clot, and then centrifuged at 2,000 × g for 10 min. The serum removed was aliquoted and frozen at -80°C until assayed. The concentration of glucose, cholesterol and triglycerides in serum was measured by an autoanalyzer (Hitachi 917 Automatic Analyzer, Boheringer Mannheim Corporation, Indianapolis, IN, USA). Cu 2+ -induced lipoprotein oxidation in human serum A modification of the serum oxidation method described by Regnstrom et al . [ 23 ] was used. This method provides an indication of conjugated dienes formation in lipoprotein fatty acids present in serum exposed to Cu 2+ , assessed by measuring changes in absorbance at 234 nm. The formation of conjugated dienes in lipoprotein deficient serum exposed to Cu 2+ is absent, indicating that diene formation in lipoprotein fatty acids is primarily responsible for the increase in absorbance [ 23 ]. The oxidation curves have three phases: lag, propagation, and decomposition. This method has been used previously by others [ 24 - 28 ]. Serum was diluted to a final concentration of 0.67% in 20 mM phosphate buffer, pH 7.4 and saturated with O 2 . Oxidation was initiated by the addition of CuSO 4 to a final concentration of 0.0125 mM. The formation of conjugated dienes was followed by monitoring the change in absorbance at 234 nm at 37°C on a Beckman DU-64 spectrophotometer equipped with a six position automatic sample changer (Fullerton, CA, USA). Absorbance readings were taken every 10 min over 240 min. The aqueous garlic extracts were added at the indicated concentrations (ranging from 0.05 to 0.75 mg/mL). Control tubes consisted of identical assays conditions but without the garlic extract. Since the transition from lag phase to propagation phase was continuous, lag time was defined as the intercept of the tangents of the propagation and lag phases and expressed in minutes. Determination of Cu 2+ chelation of garlic extracts The Cu 2+ chelating properties of aqueous garlic extracts were assessed using an approach based upon restoring the activity of xanthine oxidase described previously [ 11 ]. This enzyme is inhibited in the presence of 0.050 mM CuSO 4 [ 29 ]. The activity of xanthine oxidase can be assessed by monitoring either the production of superoxide anion or the formation of uric acid. Xanthine oxidase activity would be restored if garlic extracts were able to chelate Cu 2+ . Xanthine oxidase activity was measured by NBT reduction and uric acid production. The following concentrated solutions were prepared in distilled water: xanthine oxidase 168 U/L, xanthine 0.30 mM, NBT 0.15 mM, and Na 2 CO 3 0.4 M. Superoxide anions were generated in a reaction volume of 1 mL containing in a final concentration: xanthine 0.087 mM, Na 2 CO 3 15 mM, NBT 0.022 mM, and 50 mM phosphate buffer pH 7.4 or garlic extract in a volume of 0.1 mL for control or experimental tube, respectively. In additional tubes with or without garlic extract, CuSO 4 was added in a final concentration of 0.050 mM. The reaction was initiated by the addition of 0.025 U of xanthine oxidase, and superoxide anion production was monitored at 560 nm. In the same experiment, xanthine oxidase activity was measured by following the uric acid production at 295 nm [ 30 ]. Absorbance at 560 and 295 nm was obtained every minute for 3 minutes and the results were expressed as change of absorbance/min. The garlic extracts were added at the higher concentration used in the experiments for Cu 2+ -induced lipoprotein oxidation along with (+CuSO 4 ) or without (-CuSO 4 ) 0.050 mM CuSO 4 . Control tubes contained all the reagents but without garlic extracts and they considered as 100% production of uric acid and superoxide anion. In a separate tube with 0.050 mM CuSO 4 , 0.060 mM EDTA was added as an additional control in which was expected the restoration of xanthine oxidase since EDTA is a metal-chelating agent. Statistics Data are expressed as mean ± SEM of five determinations using different serum samples. The variables used to describe the difference between the oxidation curves were lag time, area under the oxidation curve (AUC), and slope of the propagation phase. These parameters were obtained using the GraphPad Prism software v. 3.02 (San Diego, CA, USA). All parameters were compared using either one way analyses of variance followed by Bonferroni's t test or Kruskall-Wallis analysis of variance followed by Dunn's test. p < 0.05 was considered significant. Results Glucose, cholesterol, and triglycerides in human serum The concentration, in mmol/L, of glucose, cholesterol, and triglycerides in serum, of the subjects involved in this study was 4.56 ± 0.15, 4.24 ± 0.42, and 1.05 ± 0.11, respectively. These data show that the human beings from whom the blood serum samples were obtained for this study had no alterations in the circulating levels of glucose, cholesterol, and triglycerides. Effect of garlic extracts on Cu 2+ -induced lipoprotein oxidation in human serum Unheated garlic extracts from raw garlic or from garlic powder inhibited lipoprotein oxidation in a dose-dependent way. Figure 1 shows a representative graph obtained from a single subject. Panel A shows the effect of increasing concentrations of garlic powder extract (0.05 to 0.25 mg/mL) and panel B shows the effect of increasing concentrations of raw garlic extract (0.125 to 0.75 mg/mL) on Cu 2+ -induced lipoprotein oxidation in human serum. The increasing concentrations of garlic extracts displaced the curve to the right, compared to the control curve obtained without garlic extract, indicating that the inhibition of Cu 2+ -induced lipoprotein oxidation is dose-dependent. Lag time, AUC, and slope were obtained from these oxidation curves. Figure 2 shows the lag time (panels A and C) and AUC (panels B and D) and Table 1 shows the slopes of the propagation phase from the five subjects studied. Panels A and B show the effect of garlic powder extract and panels C and D show the effect of raw garlic extract. It can be seen that garlic extracts dose-dependently increased lag time and decreased AUC and slopes. Based on these curves the concentrations of all the extracts studied were chosen: 0.25 and 0.5 mg/mL for HRG, BG, MG, and PG; and 0.05 and 0.1 mg/mL for GP and HGP. Figure 1 Representative curves showing the effect of aqueous garlic extracts on Cu 2+ -induced lipoprotein oxidation in human serum. Panel A shows the effect of garlic powder extract and panel B shows the effect of raw garlic extract. Cu 2+ -induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of CuSO 4 at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O 2 and the readings were followed by 240 min at 37°C. Figure 2 Dose-dependent effect of aqueous garlic extracts on lag time and AUC. Panels A and B shows the effect of garlic powder extract and panels C and D shows the effect of raw garlic extract. Lag time is shown in panels A and C and AUC is shown on panels B and D. a p < 0.01 (panel A) and p < 0.001 (panels B, C, and D) vs. 0 mg/mL. Data are mean ± SEM of five determinations using independent samples. Table 1 Effect of extract of garlic powder (GP) and raw garlic (RG) on the slopes of oxidation curves. GP, [mg/mL] 0 0.05 0.075 0.1 0.25 slope 0.0025 ± 0.0002 0.0017 ± 0.0003 0.0014 ± 0.0002 0.0009 ± 0.0003 0.0003 ± 0.00003 a RG, [mg/mL] 0 0.125 0.25 0.5 0.75 slope 0.0027 ± 0.0002 0.0018 ± 0.0002 0.0022 ± 0.0002 0.0017 ± 0.0002 b 0.0007 ± 0.0003 a Data are mean ± SEM of five determinations using independent samples. a p < 0.001, b p < 0.05 vs. 0 mg/mL. Effect of different treatments of garlic on Cu 2+ -induced lipoprotein oxidation in human serum The effect of HGP, HRG, BG, MG, and PG on the lag time and AUC is shown on Figs. 3 , 4 , 5 , 6 , 7 respectively. The effects of these extracts on the slopes of oxidation curves are shown in Tables 2 and 3 . GP and HGP were studied at 0.05 and 0.1 mg/mL and HRG, BG, MG, and PG were studied at 0.25 and 0.5 mg/mL. The data of HGP and HRG were compared with those of unheated extracts, GP and RG, respectively (Figs. 3 and 4 and Tables 2 and 3 ). The data of BG, MG, and PG were compared with those of RG (Figs. 5 , 6 , 7 and Table 3 ). It can be seen that the extracts increased lag time and decreased AUC at both concentrations studied indicating that they inhibit Cu 2+ -induced lipoprotein oxidation. The decrease in the slope was significant only at the higher concentration for GP and HGP (Table 2 ) and for RG and HRG, BG, and MG (Table 3 ). The decrease in the slope in PG was not significant (Table 3 ). Interestingly, the treatments (heating of extracts of garlic powder or raw garlic or heating garlic cloves by boiling, microwave or pickling) had no significative effect on lag time, AUC, and slope. All the comparisons between unheated and heated extracts were not different. Our data show that the antioxidant ability of garlic on Cu 2+ -induced lipoprotein oxidation in human serum is not significantly affected by the above mentioned treatments. Figure 3 Effect of heated extract of garlic powder (HGP) on lag time and AUC. Aqueous extract of garlic powder was heated at 100°C by 10 min. Aqueous extracts of unheated (GP) and HGP were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu 2+ -induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu 2+ at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O 2 and the readings were followed by 240 min at 37°C. a p < 0.001, b p < 0.01, and c p < 0.05 vs. 0 mg/mL. Δ= HGP. Data are mean ± SEM of five determinations using independent samples. Figure 4 Effect of heated extract of raw garlic (HRG) on lag time and AUC. Aqueous extract of raw garlic was heated at 100°C by 10 min. Aqueous extracts of unheated (RG) or HRG were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu 2+ -induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu 2+ at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O 2 and the readings were followed by 240 min at 37°C. a p < 0.05 vs. 0 mg/mL. Δ= HRG. Data are mean ± SEM of five determinations using independent samples. Figure 5 Effect of aqueous extract of boiled garlic (BG) cloves on lag time and AUC. Comparison was made with aqueous extract of raw garlic (RG). Aqueous extracts of BG and RG were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu 2+ -induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu 2+ at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O 2 and the readings were followed by 240 min at 37°C. a p < 0.001, b p < 0.01, and c p < 0.05 vs. 0 mg/mL. Δ= BG cloves. Data are mean ± SEM of five determinations using independent samples. Figure 6 Effect of aqueous extract of garlic cloves submitted to microwave heating (MG) on lag time and AUC. Comparison was made with aqueous extract of raw garlic (RG). Aqueous extracts of microwave-treated garlic cloves (MG) and RG were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu 2+ -induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu 2+ at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O 2 and the readings were followed by 240 min at 37°C. a p < 0.001 and b p < 0.01 vs. 0 mg/mL. Δ= MG. Data are mean ± SEM of five determinations using independent samples. Figure 7 Effect of aqueous extract of pickled garlic (PG) on lag time and AUC. Comparison was made with aqueous extract of raw garlic (RG). Aqueous extracts of PG and RG were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu 2+ -induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu 2+ at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O 2 and the readings were followed by 240 min at 37°C. a p < 0.05, b p < 0.001 (panel A), and a p < 0.01 (panel B) vs. 0 mg/mL. Δ= PG. Data are mean ± SEM of five determinations using independent samples. Table 2 Effect of extract of garlic powder (GP) and heated garlic powder (HGP) on the slopes of oxidation curves. Extract [mg/mL] 0 0.05 0.05 Δ 0.1 0.1 Δ GP or HGP 0.0024 ± 0.0002 0.0017 ± 0.0002 0.0018 ± 0.0002 0.0013 ± 0.0001 a 0.0013 ± 0.0001 a Data are mean ± SEM of five determinations using independent samples. a p < 0.01 vs. 0 mg/mL. Δ = HGP. Table 3 Effect of different extracts of garlic on the slopes of oxidation curves. Extract, [mg/mL] 0 0.25 0.25 Δ 0.5 0.5 Δ RG or HRG 0.0023 ± 0.0003 0.0020 ± 0.0001 0.0014 ± 0.0001 a 0.0013 ± 0.002 b 0.0011 ± 0.0002 b RG or BG 0.0021 ± 0.0001 0.0016 ± 0.0002 0.0008 ± 0.0002 c 0.0007 ± 0.0004 c 0.0005 ± 0.0001 c RG or MG 0.0024 ± 0.0002 0.0018 ± 0.0002 0.0015 ± 0.0002 0.0011 ± 0.0003 b 0.0005 ± 0.0002 c RG or PG 0.0026 ± 0.0002 0.0023 ± 0.0004 0.0021 ± 0.0004 0.0016 ± 0.0003 0.0019 ± 0.0003 Data are mean ± SEM of five determinations using independent samples. a p < 0.05, b p < 0.01, c p < 0.001, vs. 0 mg/mL. Δ = HRG, BG, MG or PG. Cu 2+ -chelation studies To investigate if the ability of garlic extracts to inhibit Cu 2+ -induced lipoprotein oxidation in human serum was secondary to Cu 2+ -chelation, these extracts were tested in an in vitro system (see material and methods) to know if they were able to chelate Cu 2+ . The results for each extract at the higher concentration are presented in Fig. 8 . Panel A shows uric acid production measured at 295 nm and panel B shows superoxide production measured by the NBT reduction at 560 nm. Cu 2+ -induced a decrease in xanthine oxidase activity measured both by uric acid production at 295 nm which decreased 71% and by NBT reduction at 560 nm which decreased 96% (Fig. 8 ). Uric acid production and NBT reduction were restored by EDTA. The extracts were added at the following concentrations: GP and HGP = 0.1 mg/mL, and RG, HRG, BG, MG, and PG = 0.5 mg/mL. We have previously shown that at these concentrations, the extracts increased lag time and decreased AUC indicating that they were able to inhibit Cu 2+ -induced lipoprotein oxidation (Figs. 3 , 4 , 5 , 6 ). In absence of Cu 2+ (-CuSO 4 ) the extracts were unable to modify uric acid production indicating that they were unable to modify xanthine oxidase activity. In absence of Cu 2+ , NBT reduction was decreased significantly by RG indicating that this extract quenched superoxide anion. In presence of Cu 2+ (+CuSO 4 ) the extracts were unable to restore (a) uric acid production (p > 0.05 vs. CT without Cu 2+ ), with the exception of RG which was able to restore it partially (p < 0.05 vs. CT without Cu 2+ ), and (b) NBT reduction (p > 0.05 vs. CT without Cu 2+ ). In summary, the extracts were unable to restore xanthine oxidase activity indicating that they do not chelate Cu 2+ . Only RG showed a weak Cu 2+ -chelating activity. Figure 8 The Cu 2+ -chelating properties of aqueous garlic extracts were assessed using an approach based upon restoring the activity of xanthine oxidase which has been inhibited in the presence of 0.050 mM CuSO 4 . The activity of xanthine oxidase can be assessed by monitoring either the production of superoxide anion (measuring the reduction of NBT at 560 nm) or the formation of uric acid (following absorbance at 295 nm). Xanthine oxidase activity would be restored if the garlic extracts were able to chelate Cu 2+ . Panel A shows xanthine oxidase activity measuring uric acid production at 295 nm. a p < 0.0001 vs. CT (-Cu 2+ ), b p < 0.0001 vs. CT (+Cu 2+ ), c p < 0.0001 vs. its respective group without Cu 2+ . Panel B shows xanthine oxidase activity measuring superoxide production by NBT reduction at 560 nm. a p < 0.0001 vs. CT (-Cu 2+ ); b p < 0.0001 and c p < 0.05 vs. CT (+Cu 2+ ); d p < 0.05 vs. its respective group without Cu 2+ . CT = Control (-Cu 2+ , +Cu 2+ ), GP = aqueous extracts of garlic powder, HGP = heated aqueous extracts of garlic powder, RG = aqueous extracts of raw garlic, HRG = heated aqueous extracts of raw garlic, BG = aqueous extracts of boiled garlic, MG = aqueous extracts of microwave-treated garlic, and PG = aqueous extracts of pickled garlic. GP and HGP = 0.1 mg/mL, RG, HRG, BG, MG, and PG = 0.5 mg/mL. Data are mean ± SEM of 3 determinations, except for both CT groups and EDTA group in which n = 7. Discussion Garlic has been used for millennia in folk medicine of many cultures to treat cardiovascular diseases and other disorders [ 1 - 8 ]. It has been shown in many cases that the protective effect of garlic is associated with its antioxidant properties [ 7 , 8 ]. The antioxidant properties of some garlic extracts used in this work have been studied. It has been found that aqueous extract of raw garlic scavenges hydroxyl radicals [ 20 , 31 , 32 ] and superoxide anion [ 32 ], inhibits lipid peroxidation [ 20 ], LDL oxidation [ 9 ], the formation of lipid hydroperoxides [ 20 , 31 , 32 ], and in vivo enhances endogenous antioxidant system [ 33 ] and prevents oxidative stress to the heart [ 34 , 35 ]. Chronic administration of raw garlic homogenate increases catalase and superoxide dismutase in rat heart [ 33 ] and protects heart against oxidative damage induced by adriamycin [ 34 ] or ischemia and reperfusion [ 35 ]. Aqueous extract of garlic powder are also able to scavenge hydroxyl radicals [ 36 ] and superoxide anion [ 37 ]. The heated aqueous extract of garlic powder maintains its ability to scavenge hydroxyl radicals [ 20 ]. In addition the ability of the aqueous extracts from boiled garlic cloves to scavenge hydroxyl radicals, superoxide anion, and hydrogen peroxide is not altered (unpublished results from our group). To our knowledge, additional antioxidant properties of the extracts from microwave-treated garlic cloves or from pickled garlic have not been studied. Furthermore, the antioxidant properties of some isolated garlic compounds also have been studied. Allicin, the main component in aqueous extract from raw garlic and garlic powder, scavenges hydroxyl radicals and inhibit lipid peroxidation [ 38 ] and prevents the lung damage induced by ischemia-reperfusion [ 39 ]. The antioxidant properties of allicin may explain, at least in part, the ability of these extracts (from raw garlic or garlic powder) to inhibit Cu 2+ -induced lipoprotein oxidation in human serum. Alliin, the main component in extracts from boiled garlic cloves, microwave-treated garlic cloves and pickled garlic, scavenges hydroxyl radicals [ 40 ], hydrogen peroxide [ 41 ], and inhibits lipid peroxidation [ 41 ] and LDL oxidation [ 42 ]. This may explain, at least in part, the ability of boiled garlic, microwave-treated garlic, or picked garlic to inhibit Cu 2+ -induced lipoprotein oxidation in human serum. Interestingly, it has been shown that another garlic compounds such as S-allylcysteine [ 10 , 13 ], N-acetyl-S-allylcysteine [ 10 ], S-allylmercaptocysteine [ 10 ], alliin [ 10 ], allixin [ 10 ], and S-ethylcysteine, N-acetylcysteine, diallyl sulfide, and diallyl disulfide [ 14 ] are able to inhibit Cu 2+ -induced LDL oxidation. The antioxidant properties of S-allylcysteine [ 43 ], S-allylmercaptocysteine [ 44 ], diallyl sulfide [ 45 ], and diallyl disulfide [ 46 ] also have been seen in vivo in an experimental model of nephrotoxicity induced by gentamicin. Our data strongly suggest that the ability of garlic to prevent Cu 2+ -induced lipoprotein oxidation in human serum is preserved in spite of inactivation of allinase by boiling, microwave or pickling or by the heating of garlic extracts and that the compound(s) involved in the inhibition of Cu 2+ -induced lipoprotein oxidation are heat stable. Our data are in contrast with previous studies in the literature showing that the heating may impair significantly several garlic properties. For example, microwave-treatment for 1 min impaired the anticancer properties of garlic [ 17 ] and the heating of garlic cloves by 15 min impairs significantly its ability to inhibit thromboxane B 2 synthesis [ 19 ], and platelet aggregation [ 22 ], and the cyclooxygenase activity [ 18 ]. The heating by 10 min at 100°C reduced the bactericidal activity against Helicobacter pylori [ 21 ]. Interestingly, Kasuga et al . [ 47 ] have found that garlic extracts, prepared from boiled cloves, show efficacy in the following three experimental models: testicular hypogonadism induced by warm water treatment, intoxication of acetaldehyde, and growth of inoculated tumor cells, and Prasad et al . [ 20 ] found that the heating did not modify the ability of garlic extract to scavenge hydroxyl radicals. The data from Prasad et al . [ 20 ] and Kasuga et al . [ 47 ] strongly suggest that some garlic properties may remain unmodified after heating. Our data are in agreement with those of Prasad et al . [ 20 ] suggesting that the ability to inhibit Cu 2+ -induced lipoprotein oxidation is also preserved after the heating of garlic. In addition, it was found that the garlic extracts used in our study were unable to chelate Cu 2+ suggesting that the ability of these extracts to inhibit Cu 2+ -induced lipoprotein oxidation is not secondary to Cu 2+ -chelation. Only RG showed a weak Cu 2+ -chelation activity, which was more evident at 295 nm. Based on previous data with aged garlic extracts [ 11 ] and some individual garlic compounds such as S-ethylcysteine, N-acetylcysteine, diallyl sulfide, and diallyl disulfide [ 14 ], we expected that our garlic extracts had Cu 2+ -chelating activity. The discrepancy with our data may simply reflect differences in composition in each garlic extract. This is additionally supported by the fact that the diethyl ether extract from aged garlic extract has no Cu 2+ -chelating activity [ 11 ]. The precise mechanism by which our extracts inhibit Cu 2+ -induced lipoprotein oxidation remains to be studied. Conclusions (a) the heating of aqueous extracts of raw garlic or garlic powder or the heating of garlic cloves by boiling, microwave or pickling do not affect garlic's ability to inhibit Cu 2+ -induced lipoprotein oxidation in human serum, and (b) this ability is not secondary to Cu 2+ -chelation. Authors's contributions JPCH conceived, designed and coordinated the study and drafted the manuscript. MGO performed the studies on Cu 2+ -chelation and studied the effect of boiled garlic, picked garlic and garlic submitted to microwave heating on Cu 2+ -induced lipoprotein oxidation in human serum. GA developed in our laboratory the method to oxidize lipoproteins by Cu 2+ and performed studies with garlic extracts of raw garlic and garlic powder. LBE participated in the studies on Cu 2+ -chelation. MM participated in the blood obtention and clinical chemistry analyses of blood serum. ONMC participated in the statistical analyses and developed the method to analyze the Cu 2+ chelating properties of garlic extracts. All authors read and approved the final manuscript. Competing interests None declared.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC519022.xml
538749	Thrombomodulin Ala455Val Polymorphism and the risk of cerebral infarction in a biracial population: the Stroke Prevention in Young Women Study	Background The genes encoding proteins in the thrombomodulin-protein C pathway are promising candidate genes for stroke susceptibility because of their importance in thrombosis regulation and inflammatory response. Several published studies have shown that the Ala455Val thrombomodulin polymorphism is associated with ischemic heart disease, but none has examined the association with stroke. Using data from the Stroke Prevention in Young Women Study, we sought to determine the association between the Ala455Val thrombomodulin polymorphism and the occurrence of ischemic stroke in young women. Methods All 59 hospitals in the greater Baltimore-Washington area participated in a population-based case-control study of stroke in young women. We compared 141 cases of first ischemic stroke (44% black) among women 15 to 44 years of age with 210 control subjects (35% black) who were identified by random digit dialing and frequency matched to the cases by age and geographical region of residence. Data on historical risk factors were collected by standardized interview. Genotyping of the thrombomodulin Ala455Val polymorphism was performed by pyrosequencing. Results The A allele (frequency = 0.85) was associated with stroke under the recessive model. After adjustment for age, race, cigarette smoking, hypertension, and diabetes, the AA genotype, compared with the AV and VV genotypes combined, was significantly associated with stroke (odds ratio 1.9, 95% CI 1.1–3.3). The AA genotype was more common among black than white control subjects (81% versus 68%) but there was no significant interaction between the risk genotype and race (adjusted odds ratio 2.7 for blacks and 1.6 for whites). A secondary analysis removing all probable (n = 16) and possible (n = 15) cardioembolic strokes demonstrated an increased association (odds ratio 2.2, 95% CI 1.2–4.2). Conclusions Among women aged 15 to 44 years, the AA genotype is more prevalent among blacks than whites and is associated with increased risk of early onset ischemic stroke. Removing strokes potentially related to cardioembolic phenomena increased this association. Further studies are needed to determine whether this polymorphism is functionally related to thrombomodulin expression or whether the association is due to population stratification or linkage to a nearby functional polymorphism.	Background Thrombosis is a dynamic balance between factors that promote clot formation, antithrombotic mechanisms, and fibrinolysis. Central to this balance is the thrombomodulin-protein C antithrombotic mechanism. Thrombomodulin forms a 1:1 complex with thrombin on the vascular endothelium, thereby inhibiting the procoagulant actions of thrombin and converting protein C to activated protein C [ 1 ]. Activated protein C promotes fibrinolysis, inhibits thrombosis by inactivating clotting factors Va and VIIIa, and reduces inflammation by decreasing white blood cell and nuclear factor kappa-B activation [ 2 - 5 ]. These relationships are demonstrated in Figure 1 . Because of the central role that the thrombomodulin-protein C pathway plays in thrombosis regulation and inflammatory response, the genes encoding these pathway proteins are promising candidate genes regarding stroke susceptibility. Figure 1 Thrombomodulin / Protein-C relationships and function The thrombomodulin gene ( THBD ) maps to chromosome 20p11.2, contains a single exon and no introns, and spans 4 kb (OMIM 188040, UniGene NM_000361, Locus Link 7056). The thrombomodulin protein is expressed primarily on the luminal surface of vascular endothelial cells and consists of 557 amino acids (aa) (60,300 Dalton): an N-terminal lectin-like module (aa 1–154), a hydrophobic region (aa 155–222), six epidermal growth factor (EGF)-like modules (aa 223–462), a serine and threonine rich region (aa 463–497), a single transmembrane segment (aa 498–521), and a short cytoplasmic tail (aa 522–557) [ 6 ]. A single nucleotide polymorphism (C→T) at position +1418 (C1418T) encodes for an aa change from alanine to valine at protein position 455 (Ala455Val) [ 7 ]. The location of this aa variation corresponds to the sixth EGF region of the thrombomodulin protein as seen in Figure 2 . This location has been shown to be responsible for the high-affinity binding of thrombin and for the suspension of thrombin at a specific position above the endothelial surface in relation to other cofactors, thereby producing optimal protein C activation by thrombin [ 2 , 8 ]. Figure 2 Thrombomodulin protein A few studies have shown that the THBD Ala455Val polymorphism is associated with ischemic heart disease [ 9 , 10 ], but we know of no prior reports examining this polymorphism's association with stroke. Using data from the Stroke Prevention in Young Women Study [ 11 ], we sought to determine the association between the THBD Ala455Val polymorphism and the occurrence of ischemic stroke in young women. In addition, because cardioembolic stroke has a lesser degree of familial aggregation [ 12 ], we performed a secondary analysis excluding cases with cardioembolic etiologies. Methods The Stroke Prevention in Young Women Study (SPYW) is a population-based case-control study that was initiated to examine risk factors for ischemic stroke in young women. In that study the term "population-based" means that cases and their comparison group were identified from the same defined population. The study area included all of Maryland (except the far Western panhandle), Washington DC, and the southern portions of both Pennsylvania and Delaware. Cases were female patients 15 to 44 years of age with a first cerebral infarction as identified by discharge surveillance at 59 regional hospitals and through direct referral by regional neurologists. The methods for discharge surveillance, chart abstraction, and case adjudication have been described previously [ 11 , 13 , 14 ]. The adjudication of stroke cases was performed blinded to genetic information. Stroke cases were classified as having a probable, possible or undetermined etiology as per prior description [ 13 , 14 ]. Control subjects were women without a history of stroke. They were identified by random digit dialing and were frequency matched to the cases by age and geographic region of residence. The original SPYW study consisted of 227 cases and 342 controls. DNA samples were available for a subset of this population consisting of 141 cases and 210 controls. We performed THBD genotyping at the Ala455Val polymorphism for 141 cases and 210 control subjects. This included all case and control samples that were available at that time. Genotyping was performed blinded to case-control status. Genomic DNA was extracted from stored peripheral blood lymphocytes by using standard protocols (Gentra Systems, Minneapolis, MN). The THBD Ala455Val polymorphism was determined by pyrosequencing. The single-nucleotide polymorphism region of the gene was amplified by polymerase chain reaction (PCR) with the use of published primers [ 10 ] except that we labeled the reverse primer with biotin. PCR was performed in 40 μl reactions containing 40 ng of genomic DNA, 15 pmol each of forward and reverse primer, 1.5 U of Amplitaq (Applied Biosystems, Foster City, CA) and MasterAmp PCR PreMix D (Epicenter, Madison, WI). The resulting biotinylated PCR product was bound to streptavidin-coated Sepharose HP beads (Amersham Pharmacia Biotech, Uppsala, Sweden) and the product was denatured according to the manufacturer's protocol (PSQ 96 Sample Preparation Kit, Pyrosequencing AB, Uppsala, Sweden). Following denaturation, an internal sequencing primer (5'-CGACTCGGC CCT T-3') was annealed to the bound single-stranded DNA. We used an automated pyrosequencing instrument (PSQ96, Pyrosequencing AB, Uppsala, Sweden) to perform the genotyping [ 15 , 16 ]. The reactions were performed at 28°C and contained the bound single-stranded DNA with annealed sequencing primer, enzymes (DNA polymerase, apyrase, luciferase, and activating transcription factor sulfurylase), nucleotides (dTTP, dGTP, dCTP, or dATPαS), and substrate (luciferin) supplied by the manufacturer. We monitored continuously the output from the charge-coupled device as a pyrogram, and we analyzed manually the results from the completed sequencing reactions by visually inspecting each program. The validity of the method was confirmed by fluorescent dye terminator sequencing of a subset of samples using standard protocols on an ABI 3100 genetic analyzer (Applied Biosystems, Foster City, CA). We assessed the following potential confounders of the association between the alleles of the THBD Ala455Val polymorphism and stroke: age, race, current cigarette smoking, hypertension, diabetes mellitus, history of angina or myocardial infarction (angina/MI), use of oral contraceptive pills (OCP) or hormone replacement therapy (HRT), sickle cell disease, and sickle cell trait. Age, race, current cigarette smoking status, use of OCP or HRT was determined by subject reports (or proxy report, if a participant was unable to answer). Hypertension and diabetes mellitus, sickle cell disease or sickle cell trait were determined by asking study participants (or a proxy) if a physician had ever told them that they had the condition. We compared means by t tests and proportions by χ2 tests. The probability values presented are based on two-sided tests. Because of the low frequency of the V455 allele, we compared the frequency of the combined AV/VV genotype between cases and controls. Adjusted odds ratios derived from logistic regression were used to determine whether the presence of the Ala455Val test allele was associated with an increased risk for stroke after differences in age, race, current cigarette smoking, hypertension, and diabetes mellitus were controlled for. Additional analyses included: 1). adding ischemic heart disease (angina/MI) into the logistic regression model; 2). evaluation for interactions between genotype and OCP/HRT 3). an analysis excluding sickle cell trait, and 4). an analysis excluding cardioembolic strokes. Results Subject characteristics Characteristics by case-control status are described in Table 1 . The mean age of the cases (i.e., women with a first cerebral infarction) was 35.5 years and the mean age of control subjects was 36.1 years. Cases were more likely than control subjects to be black (44.0% versus 34.8%, p = 0.12), and were significantly more likely to currently smoke cigarettes (p < 0.001), to have hypertension (p < 0.01), diabetes (p < 0.001) and history of angina/MI (p < 0.001). No study subjects reported sickle cell disease, however 6 cases and 5 controls reported sickle cell trait (non-significant difference). Twenty cases and 34 controls reported use of oral contraceptive pills (OCP) or hormone replacement therapy (non-significant difference). Table 1 Characteristics, by case-control status Case (N = 141) Control (N = 210) p-value Mean age (years) 35.5 36.1 .31 Black (%) 44.0 34.8 .12 Current Smokers (%) 45.4 26.7 <.001 Hypertension (%) 27.7 13.3 <.01 Diabetes mellitus (%) 13.5 3.3 <.001 Angina/MI (%) 14.9 4.3 <.001 Genotype and vascular risk factor distributions The distribution of genotypes was in Hardy Weinberg equilibrium for the pooled set of cases and controls, both in total and by race. Among control subjects, the prevalence of the AA genotype was 81% (59/73) for blacks and 68% (93/137) for whites. The relationship between the Ala455Val genotypes and selected stroke risk factors in control subjects is summarized in Table 2 . Blacks were significantly more likely to have the AA genotype than the AV and VV genotypes combined (38.8% vs. 24.1%, p < 0.05). In contrast, there were no significant differences in prevalence of hypertension, diabetes, angina/MI, or sickle cell trait between carriers and non-carriers of the V allele, nor did the frequency of cigarette smoking or OCP/HRT use differ significantly between the two groups. Table 2 Characteristics among control subjects, by thrombomodulin genotype status AA (n= 152) AV/VV (n= 58) p-value Mean age (years) 36.5 34.9 0.17 Black (%) 38.8 24.1 <.05 Current Smokers (%) 26.3 27.6 0.86 Hypertension (%) 11.2 19.0 0.18 Diabetes Mellitus (%) 4.0 1.7 0.34 Angina/MI (%) 2.4 1.9 0.26 Genotype risk Table 3 shows the association of the AA genotype with stroke, stratified by race and other vascular risk factors. The association between the AA genotype and stroke was 2.7 (95% CI 0.9–8.0) among blacks and 1.6 (95% CI 0.8–3.2) among whites. Since logistic regression analysis did not show a significant interaction by race (i.e., the effect of the AA genotype did not differ significantly between blacks and whites), subsequent analyses were conducted on the combined sample. After adjustment for age, race, cigarette smoking, hypertension, and diabetes, the AA genotype was found to be significantly associated with stroke compared with the AV and VV genotypes (OR 1.9, 95% CI 1.1–3.3). Table 3 Frequency of the THBD Ala455Val AA genotype in cases and controls (proportion with AA genotype in parentheses) as stratified by race and other stroke risk factors; with associated crude and adjusted odds ratios Risk Factor Percentage of cases with the AA genotype (proportion) Percentage of Controls with the AA genotype (proportion) Crude OR ^ (95% CI) Adjusted OR^ (95% CI) White 79% (62/79) 68% (93/137) 1.7 (0.9–3.3) 1.6 (0.8–3.2) Black 87% (54/62) 81% (59/73) 1.8 (0.4–7.9) 2.7 (0.9–8.0) Current smoking 84% (54/64) 71% (40/56) 2.2 (0.9–5.3) 3.0 (1.1–7.8) No current smoking 81% (62/77) 73% (112/154) 1.6 (0.8–3.0) 1.5 (0.7–2.9) Hypertension 85% (33/39) 61% (17/28) 3.6 (1.1–11.3) 5.7 (1.4–22.6) No hypertension 81% (83/102) 74% (135/182) 1.5 (0.8–2.8) 1.6 (0.8–3.0) Diabetes* 84% (16/19) 86% (6/7) Not performed Not performed No Diabetes 82% (100/122) 72% (146/203) 1.8 (1.0–3.1) 1.9 (1.1–3.4) Angina/MI ** 86% (18/21) 56% (5/9) Not performed Not performed No Angina/MI 82% (98/120) 73% (147/201) 1.6 (0.9–2.9) 1.7 (.95–3.1) Overall 82% (116/141) 72% (152/210) 1.8 (1.1–3.0) 1.9 (1.1–3.3) * Each variable adjusted for age, race, smoking, hypertension, and diabetes (less the stratified variable). Overall model and Angina/MI adjusted for age, race, smoking, hypertension, and diabetes. Including Angina/MI in adjusted overall model demonstrated no change in association (OR = 1.9 95% CI = 1.1–3.3). ** Insufficient sample size to perform diabetic or angina/MI analyses. ^ The combined AV and VV genotypes within each strata serve as the reference group in all analyses, with the crude OR and adjusted OR assigned a reference value of 1.0. The strength of association between the AA genotype and stroke remained unchanged including history of angina or myocardial infarction in the logistic regression model (OR 1.9, 95% CI 1.1–3.3). Neither OCP/HRT use, nor sickle cell trait demonstrated an interaction with genotype and additional adjustment for these factors did not alter the association between the AA genotype and stroke. Stroke subtype Among the 141 stroke patients, 70 (50%) had a least 1 probable cause, 30 (21%) had no probable cause but a least one possible cause, and 41 (29%) were indeterminate. Table 4 shows the distribution of probable and possible causes. "Other determined causes" of stroke included hematologic disorders, nonatherosclerotic vasculopathy (eg, vasculitis and dissection), migraine, drug abuse and stroke associated with oral contraceptive or exogenous estrogen use. Table 4 Etiologies among cases with a probable or possible cause of stroke Probable Causes 1 (n = 70) Possible Causes 2 (n = 30) Large-artery autherosclerosis 9 8 Cardioembolism* 16 14 Lacune 7 3 Other determined cause** 38 5 1 One patient had 2 probable causes, but only 1 cause is listed according to the following hierarchy: large-artery atherosclerosis > cardioembolism > lacune> other determined cause. 2 Most patients had multiple possible causes, but only 1 cause is listed per patient according to the same hierarchy as for probable causes. * Note one probable case attributed to "other determined cause", also had possible cardioembolism as an etiology, this case was removed from the secondary analysis. A total of 31 cases were removed from the secondary analysis on the basis of either probable (n = 16) or possible (n = 15) cardioembolism as the stroke etiology. ** Other determined causes included: Probable = 38, (10 non-atherosclerotic vasculopathy, 13 hematologic, 4 migraine, 6 oral contraceptive or exogenous estrogen use, 5 other drug related). Possible = 5, (3 hematologic, 2 migraine). A secondary analysis removing all probable (n = 16) or possible (n = 15) cardioembolic strokes was performed using the same adjusted model including age, race, smoking, hypertension, and diabetes. An increased association between non-cardioembolic stroke and the AA genotype was demonstrated (odds ratio 2.2, 95% CI 1.2–4.2). Discussion In our study of the THBD Ala455Val polymorphism, the prevalence of the AA genotype among our control population was similar to that previously reported for the Atherosclerosis Risk in Communities (ARIC) Study population [ 10 ]. Our results indicate a positive association between the AA genotype and stroke among women aged 15 to 44 years. Furthermore, an increased association was demonstrated with the removal of all probable or possible cardioembolic strokes, a finding consistent with a recent meta-analysis demonstrating that cardioembolic stroke appears to have a smaller familial (or genetic) component that other subtypes of ischemic stroke [ 12 ]. Vascular risk factors were not significantly associated with specific genotypes in either analysis. Several recent studies evaluating the THBD Ala455Val polymorphism and coronary artery disease (CAD) have yielded conflicting results. A Swedish case-control study found the alanine allele was associated with CAD [ 9 ]. In contrast, the American prospective ARIC study found the valine allele (AV plus VV) was associated with an increase in CAD risk in both blacks (OR 4.4, 95% CI 1.5–12.9) and whites (OR 1.4, 95% CI 0.9–2.1), although the association attained statistical significance only in blacks [ 10 ]. A British case-control study found no association at all between the THBD Ala455Val polymorphism and CAD [ 17 ]. Consistent with the Swedish results [ 9 ], we observed an association between the alanine allele at this locus and stroke onset at a young age. It is unclear whether the conflicting information regarding the THBD Ala455Val polymorphism, ours included, is due to population-stratification bias, a functionally neutral polymorphism that serves as a marker for a nearby functional mutation (linkage disequilibrium), or the true existence of different associations in the different study populations. Population-stratification bias is due to confounding by population admixture [ 18 ]. An unidentified subpopulation can confound the association between a genotype and disease if the subpopulation is associated with the genotype under study and the risk of disease. Because our results indicate that blacks have a higher prevalence of the AA genotype and have an increased risk of early-onset stroke, the AA genotype might be a marker for African ancestry in general rather than a marker for increased stroke susceptibility. The THBD Ala455Val locus may be in linkage disequilibrium with an unobserved "high-risk" susceptibility locus. Linkage disequilibrium is a function of the history of the population, and thus true associations can occur in one population and not another. Our results are also consistent with a causal association between stroke and the THBD Ala455Val polymorphism, thereby defining a susceptibility locus for the disease. An important criterion for a true susceptibility locus is that the polymorphism is associated with a change in protein expression or function. The THBD Ala455Val polymorphism has not been associated with variation in soluble thrombomodulin concentrations [ 19 ], but soluble thrombomodulin levels do not necessarily indicate the functional status of thrombomodulin on the endothelial surface. The Ala455Val polymorphism resides within a critical region for thrombomodulin function, specifically within the sixth EGF region. Epidermal growth factor (EGF) regions 4, 5, and 6 within the thrombomodulin molecule (see Figure 1 ) appear to play critical roles in the activation of protein C by thrombin [ 2 , 8 , 20 , 21 ]. Furthermore, this contiguous EGF segment is the minimal functional fragment of the thrombomodulin cofactor that can switch the specificity of thrombin from a procoagulant to an anticoagulant enzyme [ 21 , 22 ]. Furthermore, two polymorphisms close to the Ala455Val polymorphism, Arg385Ser and Pro477Ser, have been shown to influence the expression and function of thrombomodulin in a tissue culture model [ 23 ]. Conclusions Thrombomodulin has not previously been examined as a candidate gene for stroke susceptibility. We found that among women aged 15 to 44 years, the AA genotype is more prevalent among blacks than whites and is associated with increased risk of early-onset ischemic stroke. Removing strokes potentially related to cardioembolic phenomena increased this association. Further studies are needed to determine whether this association is due to population stratification, linkage to a nearby functional polymorphism, or variation in thrombomodulin expression or function. Competing interest The author(s) declare that they have no competing interests. Authors' contributions All authors certify that they participated in the conceptual design of this work, the analysis of the data, and the writing of the manuscript to take public responsibility for it. All authors reviewed the final version of the manuscript and approve it for publication. J.W.C., S.J.K., B.D.M., M.A.W. and R.F.M. participated in the writing of the initial draft. M.G., K.K.S., W.H.G. and S.C.R. participated in the genotyping. J.W.C., S.J.K., B.D.M., and L.J.R. participated in the data analysis. All authors provided critiques of the final manuscript. Funding acknowledgments Dr. Cole's effort on this project was supported in part by an American Academy of Neurology Clinical Research Training Fellowship, by the National Institutes of Health Research Training in the Epidemiology of Aging (Grant T32-AG00262-04), and by the Department of Veterans Affairs, Baltimore, Office of Research and Development, Medical Research Service, and Stroke Research Enhancement Award Program. Dr. Kittner was supported in part by the Department of Veterans Affairs, Baltimore, Office of Research and Development, Medical Research Service, Geriatrics Research, Education and Clinical Center, and Stroke Research Enhancement Award Program; a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention; the National Institute of Neurological Disorders and Stroke and the NIH Office of Research on Women's Health; the National Institute on Aging Pepper Center Grant P60 12583; and the University of Maryland General Clinical Research Center (Grant M01 RR 165001), General Clinical Research Centers Program, National Center for Research Resources, NIH. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538749.xml
555599	wFleaBase: the Daphnia genome database	Background wFleaBase is a database with the necessary infrastructure to curate, archive and share genetic, molecular and functional genomic data and protocols for an emerging model organism, the microcrustacean Daphnia . Commonly known as the water-flea, Daphnia 's ecological merit is unequaled among metazoans, largely because of its sentinel role within freshwater ecosystems and over 200 years of biological investigations. By consequence, the Daphnia Genomics Consortium (DGC) has launched an interdisciplinary research program to create the resources needed to study genes that affect ecological and evolutionary success in natural environments. Discussion These tools include the genome database wFleaBase, which currently contains functions to search and extract information from expressed sequenced tags, genome survey sequences and full genome sequencing projects. This new database is built primarily from core components of the Generic Model Organism Database project, and related bioinformatics tools. Summary Over the coming year, preliminary genetic maps and the nearly complete genomic sequence of Daphnia pulex will be integrated into wFleaBase, including gene predictions and ortholog assignments based on sequence similarities with eukaryote genes of known function. wFleaBase aims to serve a large ecological and evolutionary research community. Our challenge is to rapidly expand its content and to ultimately integrate genetic and functional genomic information with population-level responses to environmental challenges. URL: .	Background The micro-crustacean Daphnia is a ubiquitous resident of inland waters within all continents of the globe and is the subject of study for numerous biological disciplines including limnology, ecology, physiology, toxicology, population genetics and evolution. Many attributes make this organism an ideal model for ecological and evolutionary genomics research. As the principal grazers of algae and the primary forage of fish, Daphnia are key members of aquatic food webs and are easily sampled in great numbers. These animals inhabit remarkably diverse environments and show striking patterns of convergent evolution linked to specific habitat transitions [ 1 ]. Their mode of reproduction (cyclical parthenogenesis) is convenient for experimental genetics, providing both long-term clonal lineages and controlled outbred populations by manipulating the environmental cues required for the induction of male production and for mating [ 2 ]. Yet most notably, Daphnia offer unprecedented opportunities to study historical responses to environmental change, by harvesting, dating and resurrecting annually sedimented diapausing eggs within lacustrine basins and by competing past products of evolution against their modern descendents [ 3 , 4 ]. For these reasons, an international network of investigators is creating community resources, already proven to effectively promote genomic-scale investigations in other disciplines (molecular, cell and developmental biology), with a goal to understand connections between genome structure, gene expression, individual fitness and population-level responses to environmental challenges. wFleaBase is a project of the Daphnia Genomics Consortium [ 5 ] and is designed to be a resource where users can search and retrieve sequence data for genes of ecological importance, or find putative genes modulating traits of interest based on their homologies to functionally characterized genes in other model organisms. Therefore, wFleaBase is an organized repository of Daphnia specific sequences with standard bioinformatic tools to facilitate gene discovery. This function includes BLAST analyses and links to gene reports for other eukaryotic genomic models via euGenes [ 6 ]. However, for most of these other model species, characterized genes are ineluctably biased toward those sets whose phenotypic effects are observed in the benign settings of a laboratory. With the additional goal of elucidating the function of novel genes with environment-specific expression patterns, wFleaBase is also designed to help locate genes with no known functions. For this purpose, a pipeline of bioinformatic tools is created to supply DNA markers from raw sequence trace files. Genetic map information on the location of variable DNA markers will soon be presented, allowing researchers to systematically screen genomic regions for the presence of quantitative trait loci (QTL) by using the available markers in their studies. Finally, to facilitate subsequent gene-specific capture by positional cloning, catalogues of available arrayed DNA libraries are displayed within the DGC web pages. The main sources of data for wFleaBase are direct submissions from DGC members and from research at large genome sequencing centers. The latest data can be accessed by web browser at and Internet file transfer at . Construction and content Generic genome database This service is built using tested genome database components and open source software that are shared in common with several other databases. Middleware in Perl and Java are added to bring together BLAST, sequence reports, searches and other bioinformatics programs for web access. The Indiana University Genome Informatics Laboratory houses wFleaBase, along with related genome databases FlyBase [ 7 ] and euGenes [ 8 ]. In the last two years, this work is coalescing with sister organism database projects under the umbrella of Generic Model Organism Database project (GMOD [ 9 ]). The relational database from GMOD [ 10 ] used for FlyBase and wFleaBase is named Chado (after "the Way of Tea" ceremony). It includes a schema for structuring a growing range of genome information, works with the free PostgreSQL database package (among others), and includes a Chado XML exchange format and tools. Significantly, a community of bioinformaticians is sharing development and use of these components. Another project that has made wFleaBase simple to start is Argos (D.G. Gilbert et al., in preparation [ 11 ]), a framework for building and distributing genome databases, with pre-configured core components listed in Table 1 . A third basic GMOD component of wFleaBase is LuceGene (D.G. Gilbert et al., in preparation), which provides rapid, data object-oriented searches, with data and document retrieval of a wide range of genome information. To start wFleaBase, we copied a genome database/web server template from Argos infrastructure, including Chado database and genome informatics tools, loaded the database with a first set of sequences, and produced BLAST comparisons of these against 10 other eukaryote genomes from the euGenes project. The euGenes project provides a standard summary of gene and genome information from eukaryotic organisms, and includes over 200,000 named genes and their functions, with 900,000 genome features. This eukaryote genome collection allows new genomes (like Daphnia 's) to be matched by sequence similarity, then annotated with reference gene information. When Daphnia or other new organism sequences are matched to this data, it suggests their gene function and provides starting points for experiments into their ecological and evolutionary genetic significance. wFleaBase records and accession numbers Sequences are assigned unique and stable accession numbers upon entry into the Chado database, which are organized into seven divisions according to whether they are derived from genome survey sequences (GSS), expressed sequence tags (EST) or high-throughput genomic (HG) and cDNA (HC) projects. Daphnia sequences from other public databases (PB), mitochondrial sequences from molecular systematic studies of the genus (MT) and amplicons of microsatellite DNA markers (MS) are also categorized. To date, wFleaBase contains 14,451 records, including EST (WFes0000001-WFes0012408), GSS (WFgs0000001-WFgs0001495) and MS (WFms0000001-WFms0000548) sequences. Each sequence header provides a short description on the type of sequence, the species and strain from which the sequence was obtained, the library identification code for the cloned fragment with synonyms and contact name. Full contact information is provided elsewhere [ 12 ]. For convenience, sequences can be downloaded in fasta format from each division via the FTP service or by navigating to specific Data sub-directories of the Genomics hyperlink, which is printed on the side menu of the web pages. At this moment, researchers are requested to send new Daphnia sequences to the corresponding author, for processing and archiving the data into wFleaBase. Submissions undergo quality assurance checks for vector contamination and correct taxonomy before they enter the database. Utility Gene searching and discovery As an information and gene discovery system, wFleaBase focuses on providing efficient tools for searching and retrieving records of interest. Its current features are best highlighted by co-navigating the web pages along with a user interested in locating ecologically relevant genes, for example, genes that confer resistance to elevated levels of ultra-violet radiation encountered by closely related species to D. pulex . Beginning at the welcome page, the user can navigate via the hyperlink located at the top menu towards the Blast page of wFleaBase to perform sequence-similarity searches on the archived data using the BLAST family of programs. The user enters a nucleotide sequence, whose gene function is well characterized and evolutionarily conserved, with a goal to find the homologous gene in Daphnia . For example, a Drosophila melanogaster mRNA sequence obtained from GenBank (NM 165564) or from FlyBase (FBgn0003082) for the gene photorepair is used to query all Daphnia sequences using the default settings of the tblastx program. Alternatively, the user can select to query species-specific GSS or EST databases. This search retrieves record WFgs0000440, which is a 917 nucleotide sequence with a best match score of 83 bits and an E-value of 5e-45. Using this information, the user can then download the Daphnia sequence onto their personal computers as a text file, design primers using their own software to probe the arrayed Daphnia cosmid library by the Polymerase Chain Reaction (PCR), identify bacterial clones containing the gene, and characterize the entire locus by sequencing. Indeed, this specific exercise identifies at least three cosmids (out of 37,000) containing a likely homologue to photorepair from Drosophila [ 13 ]. Returning to the welcome page, the user can instead choose to explore tables containing data extracted from automated BLAST searches against the euGenes database, which includes annotated genome sequences from 10 eukaryotic model organisms. Although this option for gene searching is more tedious, it does allow users to focus precisely on the data currently available in wFleaBase. Four tables of BLAST results are offered at by following the "Genomics" hyperlinks located at the top and side menus. At present, Daphnia EST and GSS sequences are each compared to the protein coding genes and to genomic sequences in euGenes. Many options exist for sorting the BLAST tables. The user can specify what BLAST result columns to show, and can sort these columns based on the ascending or descending order of their entries. The tables can also include BLAST results against all organisms within euGenes or the tables can be filtered to include results from comparisons against a single taxon. For example, the same user, now looking to find a Daphnia homologue to genes known to confer salt-resistance to species inhabiting saline environments, begins by searching for names or euGenes accession numbers of functionally related genes within the Blast tables using the wFleaBase search function located in the top menu of the Blast tables. If the user chooses to search for "ATPα", which is a sodium/potassium-exchanging ATPase shown to be under positive selection in brine shrimp populations adapted to ultra-saline waters [ 14 ], 11 EST records that match ATPα in fly are discovered with bit scores and E-values ranging from 42.36 and 0.002 to 327.0 and 2.2e-89. The user can retrieve the Daphnia sequences via hyperlinks located in the first column of the search results, or further uncover the extent of evolutionary conservation for this gene by examining the euGene Reports, also via hyperlinks located in the last column. Alternatively, if the user chooses to use the FlyBase accession number for this gene (FBgn0002921) to retrieve Daphnia homologues using the search function, the same 11 records are obtained. Tools for hunting unknown genes Although effective, the candidate gene approach to finding Daphnia genes of ecological interest is limited by the levels of sequence and functional conservation among characterized genes in other model organisms. Work is underway by the DGC to create the required tools for identifying ecologically relevant genes by positional mapping using microsatellite markers. wFleaBase presently archives 528 microsatellite markers [ 15 ]. Yet, to generate additional loci for genetic mapping in D. pulex and D. magna , wFleaBase integrates a suite of computational programs that (i) identifies microsatellites from raw DNA sequencer trace files, (ii) designs optimal primers for amplifying the markers and (iii) indexes the amplicon, microsatellite motifs and primer information into the Microsat database [ 16 ]. The Microsat database will rapidly grow by applying this pipeline to trace files emerging from the Daphnia genome sequencing project. The wFleaBase search function wFleaBase uses LuceGene to support rapid search and retrieval of the sequence database, of Blast table entries, of Daphnia Medline references and of Daphnia web documents. LuceGene [ 17 ], based on the Lucene [ 18 ] search system, is an open-source part of the GMOD project. A major benefit of LuceGene is the large variety of data formats that can be added to the search system with minimal work. For instance, currently supported formats used in wFleaBase include Simple text, XML (Medline abstracts and Gene sequence annotation), HTML, Tabular data, Bio-formats (Fasta, GenBank, EMBL) and Gene object data used by euGenes. Search terms such as "magna" to retrieve all sequences from this species, can be entered in a Search box at the head of all web pages. The search is refined at the main wFleaBase search page by specifying the search library (sequences, references, documents or Blast tables) and the library fields containing the queried term. Options are also available to detail the output format, and each result is hyperlinked to the source document for easy access to the data. On a separate web page (Batch download), users can recover multiple records obtained from complex queries and save the results to a file. Discussion and conclusions The wFleaBase project is young. Its future success is linked to the DGC and its goal to develop Daphnia into a functional genomics research model, with the added advantage of interpreting observations in the context of natural ecological challenges. wFleaBase is currently designed to facilitate gene discovery for immediate use in research projects. However, the functionality of this service will grow in equal pace with the rapid accumulation of genomics data. Within the next year, this site will host the full genome sequence for D. pulex – a collaborative project involving the U.S. Department of Energy Joint Genome Institute, the Environmental Protection Agency and the DGC. Genetic maps for D. pulex and D. magna are also under construction. Therefore, wFleaBase will soon be enhanced by implementing the CMap module of GMOD and allow users to compare the Daphnia genetic and physical maps emerging from current research and to choose the most appropriate set of markers for quantitative trait locus (QTL) mapping projects. Simultaneously, wFleaBase will also assemble cDNA sequences from another large DGC sequencing effort aimed to document most of the Daphnia transcriptome. Daphnia gene reports will be created in accordance to standards set by current model organism databases [ 19 ]. Gbrowse genome browser and Apollo annotation editor will be used for viewing genome features when they are available. Informatics efforts focus on implementing existing database tools rather than development of new ones, providing a cost-effective genome database for these species. In this way, the current format linking Daphnia genomic information to other model species will be reinforced, allowing greater opportunities to apply the candidate gene approach for identifying genes of ecological importance. Availability and requirements wFleaBase is publicly available and can be accessed at using web browsers and at by using internet file transfer protocols. Authors' contributions JC contributed data, web documentation and aided in the overall design and functionality of this database. VS contributed programming for both the database and Blast searches, and contributed to its design and development. DG contributed the generic database framework design, the overall web structure, the euGenes data and built GMOD database and Blast tools. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555599.xml
548523	The development of a new corporate specific health risk measurement instrument, and its use in investigating the relationship between health and well-being and employee productivity	Background There is a growing body of evidence linking health and well-being to key business issues. Despite this, corporate uptake of workplace health promotion programmes has been slow outside the USA. One possible reason for this is the lack of a generally available health risk measure that is quick and easy to administer and produces data that is rich enough to inform and direct subsequent employee health promotional interventions. Methods We report on the development and validation of the health and well-being (HWB) assessment, a free to use health risk appraisal questionnaire that has been specifically developed for use in the corporate setting. The HWB assessment focuses upon modifiable health issues that directly impact upon business drivers. Development involved interviews with business leaders to ascertain their key areas of focus, scientific and general literature review to find evidence for health status having an impact upon these areas, and end user testing. Three UK-based organisations (insurance, telecommunications and consumer goods sectors) participated in the research. A total of 2224 employees completed the HWB assessment, the short-form 36 (SF-36) and the World Health Organisation Health and Work Performance questionnaire (WHO-HPQ) as part of the validation process. Results The HWB assessment is a twenty item questionnaire covering ten areas of health and well-being. Completion of the HWB assessment generates a global health risk score and ten sub-scores corresponding to the ten areas covered. It is easy to use and quick to complete (average completion time was eight minutes) and showed good internal consistency and test-retest reliability. Statistically significant correlations with similar SF-36 variables were observed. A significant negative correlation between HWB score and productivity decrement, as measured by the WHO-HPQ, was observed (r = -0.4). Individuals with HWB scores above the 25 th percentile were more likely to achieve workplace productivity standards than those with scores below the 25 th percentile (OR 3.62, 95% confidence limits 2.93 – 4.47). Conclusion The HWB assessment generates reliable business focused health risk data that can be used to direct and target appropriate interventions within corporate populations. It may also be useful in quantifying the financial impact health status issues have upon organisations.	Background The last decade has seen increasing interest in the health and well-being of the workforce. This has been driven partly by the increasing burden of direct healthcare costs, but also from a recognition that the economy within the developed world has appreciably changed[ 1 , 2 ]. The relative contribution of industry, compared with the service sector, to gross domestic product (GDP) has steadily declined since 1980. Industry now represents approximately 32% of GDP and services 66%[ 3 ]. With the shifting structure of the economy have come new challenges to occupational health physicians and human resource managers alike. A predominantly service-based economy has fewer tangible assets than its industrialised counterparts and the wealth that is generated is almost completely reliant upon the less tangible "human capital" of employees. It has therefore become an imperative to ensure that this human factor is optimised in order to meet business demands, especially during times of slow economic growth. In parallel with this greater business emphasis on the human factor has come a greater awareness of "post-industrialisation" health issues. These include stress and sleep dysfunction and conditions such as obesity and musculoskeletal pain that have arisen due to greater national wealth and an increasingly sedentary lifestyle [ 4 - 6 ]. The evidence for the impact of many lifestyle factors upon long-term health is overwhelming. Smoking, excess alcohol intake, poor nutritional status, a sedentary lifestyle and psychological distress have all been associated with numerous diseases [ 7 - 10 ]. Indeed it has been estimated that about a quarter of all healthcare costs can be attributed to conditions directly resulting from easily modifiable lifestyle factors[ 11 ]. As well as the long-term consequences of lifestyle on the genesis of disease, there is increasing evidence of the short-term effects such factors have upon individual performance and productivity. Smoking, high body mass index (BMI) and psychological distress have all been shown to have a major impact upon employee productivity at work [ 12 - 14 ]. Additionally, it has been shown that those individuals who are physically active in their leisure time are less likely to have short-term illness-related absence or experience musculoskeletal disorders [ 15 - 17 ]. With these issues gaining greater ascendancy in the corporate world, we saw a need for a short, easy to administer questionnaire that could capture this business critical health status information. By conducting a confidential survey of all employees, aggregated data can be used to provide a first step by which organisations can target and monitor appropriate population-based health interventions within their workforce. A key issue in conducting such surveys is maintaining individual privacy and ensuring confidentiality of information. The majority of US organisations who already conduct annual health surveys of their employee populations do so either via their occupational health departments or external third parties. Although there are a number of general and specific health risk appraisal measures available for corporate use, they are either not well validated, suffer from being too long and cumbersome to administer, or cost an appreciable amount to use. In the case of health related quality of life measures, such as the SF-36, or specific stress indicators such as the general health questionnaire (GHQ), the data that is generated is not specific enough to direct health and well-being interventions within the corporate setting. We report on the development and validation of the health and well-being (HWB) assessment, a free to use twenty item questionnaire. We also describe its use in assessing the impact employee health has upon productivity and performance. Methods Questionnaire development Our principal aim was to develop a questionnaire that focused upon business pertinent health and well-being issues. A secondary aim was that it should be quick and easy to administer with the amalgamated results serving as a baseline from which employers can start to implement appropriate health promotion interventions within their employee populations. We initially surveyed a sample of twelve business managers and executives to ascertain the key issues currently facing their organisations. Interviewees came from four different business sectors, namely (i) Technology (ii) Engineering (iii) Banking and Insurance and (iv) Public sector / Health. Interviews lasted no more than 30 minutes and were semi-structured, asking each interviewee to describe the key issues they faced in their day-to-day operations. We then searched the general and scientific literature for evidence of the effect health parameters have upon the issues identified. The key business issues facing our sample of corporate leaders could be categorised into four separate areas. Table 1 shows these four key areas and summarises how health and well-being can directly impact upon them. Searches of Medline, Embase and PsycINFO were made from 1990 onwards using "productivity", "customer satisfaction", "customer service", "absence", "absenteeism", "medical cost" and "business risk" as key words or phrases. Table 1 Business Pertinent Health & Well-being Issues Business Issue Increasing the productivity of the workforce Improving customer service and satisfaction Reducing the costs of ill-health Reducing potential future business risks and liabilities Modifying effect of employee health and well-being on business issue Many medical conditions and risks (e.g. diabetes, cardiovascular disease, migraine, pain, respiratory disease, high BMI, smoking, excess alcohol consumption) have a direct impact upon the day-to-day productivity of the workforce [12,14,19,22,33]. Sleep disturbance and disruption has a significant impact upon an individual's performance during the working day [34] Psychological distress / stress can have a profound impact upon worker productivity and performance [21,35,36]. Physical and mental health are component factors in developing employee commitment, job satisfaction and a "climate for service" within an organisation. Via these areas the health and well-being of employees is likely to be an indirect contributor to customer service and satisfaction [37-40]. Employee attitude and job satisfaction directly affect sales increases and customer satisfaction. [37]. High risk health status (e.g. poorly controlled medical conditions, sub-optimal nutritional status, lack of physical activity, high levels of psychological distress) are associated with greater medical care expenditure and higher levels of absence [13,28,41-44]. Musculoskeletal issues are the commonest cause of long-term sickness absence in manual workers. [45]. Corporate health and well-being programmes have been shown to produce a return on investment by decreasing medical care costs, worker compensation costs and absence [30,31,46-48]. Improving physical fitness within the workforce can reduce voluntary staff turnover [49]. Union backed employee stress-related liability claims have risen four-fold since 1999, posing a significant risk to the business [50]. Early retirement due to illness is placing a significant burden upon pension plans. Musculoskeletal and psychological issues are the two most frequent health related reasons for early retirement [51]. Domains within HWB assessment that help quantify issue Medical Health Pain Body Mass Index Smoking Status Alcohol Consumption Sleep Status Symptoms of Stress Overall HWB Score Symptoms of Stress Job Satisfaction Medical Health Nutritional Balance Physical Activity Symptoms of Stress Pain Overall HWB Score Physical Activity Symptoms of Stress Pain Following interviews with executives and managers the key issues for businesses could generally be classified in one of four main areas; (i) increasing the productivity of the workforce, (ii) improving customer satisfaction, (iii) reducing the costs associated with employee ill-health and (iv) reducing potential future business risks and liabilities. For all four we found evidence for a modifying effect of health and well-being. The table shows the four identified business areas, the impact employee health and well-being has upon these areas and the domains included within the HWB that assess these areas. Initial questionnaire development involved formulating items that corresponded with the health and well-being areas that impact upon the four key business issues. An initial set of 40 questions was tested and discussed in one to one interviews and focus group discussions. Thirty-five employees and managers, from companies in the four industry sectors described previously, participated in these sessions. Question changes and selection were an iterative process, with the final questionnaire formulated after three rounds of small group testing and one round of initial data collection from 100 volunteers. This background research and subsequent refinement led us to construct a 20-item questionnaire covering ten areas of health and well-being (see additional file 1 : Appendix), which we termed sub-indices. The ten areas were: • Medical health status • The presence of pain • Habitual levels of physical activity • Nutritional balance • Sleep status • Symptoms of stress • Job satisfaction • Smoking status • Alcohol consumption • Body mass index We used a combination of 5-point Likert scales and structured multi-choice questions. Six of the ten areas were assessed by single item "global" questions, including a modification of the non-exercise estimation of VO 2 max question developed by Jackson and Ross[ 18 ]. Body mass index was scored according to desired ranges for the general population, as recommended by the World Health Organisation and the Department of Health. The remaining three areas (nutritional balance, sleep status and symptoms of stress) were assessed by multiple items. The number of possible responses to each of the sleep questions were reduced from an initial five responses to four, as the additional response was not found to be helpful as a discriminator. The checklist for the medical health question was developed according to current best available evidence for medical conditions impacting upon key business issues[ 12 , 19 - 23 ]. A single, non-scoring question on self perception of effectiveness at work was also included, not to replicate existing more detailed productivity measures, but to act as a global screening question to examine the relationship between health and work effectiveness in population analysis. The answer to each question was scored on a scale from zero to one-hundred. This was used as the relevant HWB sub-index for single item variables. The question scores for multi-item variables were averaged to give a zero to one-hundred sub-index score (see additional file 1 : Appendix for full scoring algorithm). The overall HWB score was computed by summing and then averaging all ten sub-index scores, giving equal weight to each of the ten areas. Subjects Three thousand full time employees of three UK-based organisations (one insurance company, one telecommunications company and one consumer goods manufacturer) were invited to complete the questionnaire via the internet. All data transmission utilised 128-bit encryption and all data storage was fully compliant with the UK Data Protection Act (1998). All participants were required to electronically sign an agreement for their anonymised data to be used in amalgamated format for purposes of research. A draw with a prize of a weekend break was offered as an incentive to participate for each company group. Thirty employees re-took the questionnaire four weeks after the initial completion date in order to provide test re-test data. As well as completing the newly developed questionnaire, participants were also asked to concurrently complete the Short Form 36 (SF-36) and part B of the World Health Organisation's Health and Work Performance (WHO-HPQ) questionnaire in order to assess criterion validity[ 24 , 25 ]. The SF-36 was chosen as it is a "gold standard" health-related quality of life measure and because there is some overlap with the HWB assessment in the constructs it assesses. There are a number of well validated productivity measures available for use in the workplace, however the WHO-HPQ was chosen as it is a general productivity measure applicable to both those who have a diagnosed disease and those that do not [ 26 ]. Others have shown a clear relationship between health risk and productivity, it was therefore important for the validation of our questionnaire that this was replicated[ 12 ]. For each participant in the study details on age, gender, sickness absence in the preceding three months, company position, marital status and weekly working hours were also collected. Data analysis All data analysis was carried out using Statistica , a statistical software package distributed by Statsoft Inc. (Tulsa, USA. ) Results Of the 3000 employees invited to participate in the study, 2224 completed the questionnaires (74% response rate). Online completion ensured that there were no missing data points in completed questionnaires. The mean age was 38.1 years (standard deviation 10.7). Fifty-nine per cent of respondents were female (see table 2 ). Age and gender of respondents accurately reflected the demographics of the three company populations as a whole. The average completion time for the HWB assessment was eight minutes. Table 2 Participant characteristics Gender Male: 41% Female: 59% Average Age (years) 38.1 (SD: 10.7) Marital Status Single: 34% Married: 59% Separated / Widowed: 7% Weekly Working Hours <40: 47% 40 – <50: 41% 50 – <60: 9% 60+: 3% Annual Gross Income (£) < 10,000: 13% 10,000–19,999: 27% 20,000–29,999: 30% 30,000–49,999: 21% 50,000+: 9% Company Position Junior: 49% Middle: 40% Senior: 11% Questionnaire validation Principal components factor analysis of the three multi-item variables showed that for each the number of factors extracted was 1. Inter-item correlation, as assessed by the Cronbach α value, for each of these three scales was good (see table 3 ). General linear model analysis indicated that of age, gender, sickness absence, company position, marital status and weekly working hours the only variables that remained a significant predictor of HWB score were sickness absence and age (p < 0.0001 for both). Table 3 α values for the multi-item variables of the HWB Scale Number of items Cronbach α Symptoms of stress 6 0.83 Sleep status 3 0.70 Nutritional balance 3 0.73 Comparison with SF-36 scores Significant correlations were seen between the SF-36 scales that assessed similar areas of health as the HWB sub-indices, namely, bodily pain vs. presence of pain (r = 0.79), mental health vs. symptoms of stress (r = 0.70) and mental component summary measure (MCS) vs. stress (r = 0.71). Additionally, there was a clear association between the overall HWB score and the General Health and Vitality scores of the SF-36 (r = 0.59 and 0.49 respectively). All SF-36 multi-item scales were significantly correlated with the overall HWB score (p ≤ 0.01). WHO-HPQ data The 2224 individuals who completed the HWB assessment and the SF-36 also completed part B of the WHO-HPQ. The output from the WHO-HPQ is a calculated productivity decrement for each respondent, i.e. the proportion of the week that the individual is not working optimally, either because they are absent or because they are not working effectively (so called "presenteeism")[ 24 ]. Mean productivity decrement for the population was 26.4% of weekly working time (SD 20.9), median 20% (25 th percentile was 10% and 75 th percentile was 33.5%) A negative correlation between the HWB score and calculated productivity decrement was observed (r = -0.4, p < 0.0001), i.e. better health status, as measured by the HWB assessment, was associated with less weekly productivity decrement. General linear model analysis indicated that age and the overall HWB score were the only two variables that remained as significant predictors of weekly productivity decrement (p < 0.0001 for both). The 75 th percentile figure of 33.5% productivity decrement per week was taken as the cut-off for achieving the productivity standard within the current population. Similarly, the lower quartile HWB score of 52.1 was used as the cut-off to define poor health. 2 × 2 table analysis using these cut-offs demonstrates an odds ratio of 3.62 (95% confidence limits, 2.93 to 4.47) for making the productivity standard if HWB score is above the lower quartile value, Chi squares 158.82 (Yates Corrected), p < 0.0001. There was a significant correlation between the single question on effectiveness contained in the HWB assessment and the productivity decrement, as calculated by the WHO-HPQ, (r = -0.59, p < 0.0001). Test re-test validity for the HWB assessment Thirty individuals re-took the HWB assessment four weeks after their original completion date. During this time no information or intervention with regard to health and well-being was delivered to them. The correlation between HWB scores at both time points was excellent (r = 0.90), with no significant differences between mean scores or variance of the data sets. HWB scores across the population Table 4 gives the means, medians, standard deviations and inter-quartile values for the HWB score and sub-indices. The distribution of the HWB score was normal, therefore parametric measures were used to analyse differences between independent groups (t-test). There were no significant differences between the HWB score of males and females or between those who typically worked more than 40 hours and those who did not. There was, however, a significant difference in HWB score between those in senior positions within the company and those within junior positions (mean HWB scores 62.9 and 60.7 respectively, p < 0.001). Similarly, those who had less than three days sickness absence in the preceding three months had better HWB scores than those who had more sickness absence (means scores 64.0 and 55.2 respectively, p < 0.0001). Table 4 Overall HWB score plus the ten component sub-index scores for the 2224 questionnaire respondents. Mean score Median score Standard deviation 25 th percentile 75 th percentile HWB score 61.4 62.1 13.7 52.1 71.0 Medical health 62.4 100 41.3 25.0 100 Pain 71.2 75.0 21.9 50.0 75.0 Physical activity 26.3 0 38.1 0 50.0 Nutrition 57.5 58.3 19.0 41.7 75.0 Sleep 62.3 66.7 23.8 50.0 83.3 Stress 55.7 58.3 18.2 41.7 70.8 Job satisfaction 59.0 75.0 30.2 50.0 75.0 Smoking status 77.5 100 41.8 100 100 Alcohol consumption 92.2 100 26.8 100 100 Body Mass Index score 49.7 25.0 42.2 25.0 100 Discussion The association between employee health status and costs incurred by employers is incontrovertible. Numerous studies have clearly shown how health risk factors directly impact upon medical care costs, short- and long-term absence and workers' compensation[ 11 , 27 - 29 ]. Additionally, more recent research is confirming what many of us "intuitively" knew; that the health and well-being of the workforce has a direct impact upon work performance[ 12 ]. Despite this growing body of evidence, many corporations have been slow to implement appropriate measures to assess, intervene and improve the health of their workforce. The reason for this inertia is unclear, especially as corporate health promotion and management programmes have repeatedly been shown to generate a return on investment (ROI) [ 30 - 32 ]. A possible explanation may be that whilst medical care costs are inexorably increasing, by focusing solely upon costs and cost savings we miss capturing corporate leaders' imagination and vision. Combining the message of cost savings with productivity and performance enhancements may just strike the right balance. Measures such as the WHO-HPQ now allow us to objectively measure productivity and, as we have confirmed in this paper, health risk status is an integral component of this construct. As already mentioned, although well-established questionnaires have been extensively validated in many different populations the data that is generated is often of limited value in specifically directing health and well-being interventions. We have presented the first steps of the development and validation of a health risk appraisal measure that has been specifically designed for use in the corporate setting. As well as having good content, criterion and construct validity, the generated data can help health promotion specialists develop appropriate and targeted interventions for the respondent population. The questionnaire provides information on areas such as nutritional choices, levels of habitual physical activity, sleep difficulties and stress symptoms. Amalgamated answers can be used to ensure the correct and most appropriate health interventions are delivered to the population being assessed. In addition, the single question on work effectiveness can be used to confirm the link between the health of the population being studied and their performance, prior to more in-depth evaluations of productivity such as can be made with a specific productivity measure. One would naturally expect those individuals who have taken more time off due to illness to have worse health than those who have been absent for less time. We have demonstrated that sickness absence in the preceding three months is a significant predictor of HWB score and remains so when other variables are controlled for. This is an indication that the HWB assessment is indeed measuring the health and well-being issues that are critical to businesses as a whole. Further confirmation of the discriminant validity of the HWB assessment is needed, however a suggestion that it can detect real differences in health status between groups is also seen in the significantly better scores observed between those with more senior positions as compared with those in junior positions. This difference possibly reflects the better financial rewards, the better access to healthy alternatives and the superior levels of job control associated with more senior corporate positions. The fact that the HWB score and sub-indices were significantly correlated with the broadly similar SF-36 multi-tem scales is an indication that the majority of the constructs assessed by the SF-36 are at least partially reflected in the HWB. Productivity whilst at work can be influenced by a multitude of different factors, however as demonstrated by Burton and colleagues, health is a major contributor[ 12 ]. Our study has confirmed this clear relationship between level of health risk and productivity decrement, which remains significant even when other possible confounders are taken into account. Additionally, we have demonstrated that there is an odds ratio of 3.62 of making the productivity standard for those with good health as compared with those with poor health. This information can quite easily be used by corporations to model future productivity gains and to calculate a likely ROI for the institution of a health promotion programme. Although these initial results appear promising, data collection from a larger employee sample, from different sectors and incorporating a wider age range, is necessary in order to confirm that our observations still hold true. Normalising the scoring (as is often performed with SF-36 data) would also make interpretation easier and more user friendly. Additionally, longitudinal data on whether the HWB assessment can be used as a predictive tool for populations, and hence provide businesses with visibility on how their employee health status issues are likely to affect their bottom line, is the logical next step. This process is already underway in four multinational organisations with populations in both the USA and the UK and is being overseen by the Institute for Health and Productivity Management (IHPM). Conclusion In summary we present a new health risk measure, the Health and Well-being Assessment (HWB), which has the following key features: (i) has been specifically designed for the corporate environment addressing the health and well-being issues that affect key business drivers (ii) is quick, easy and free to use (iii) the generated data is useful for guiding future interventions By combining medical health issues with other more "lifestyle" and well-being focused areas within a short, easy to use questionnaire we believe that we have created a useful corporate tool. List of Abbreviations GHQ – General Health Questionnaire HWB – Health and well-being ROI – Return on Investment SF-36 – Short Form 36 questionnaire WHO-HPQ – World Health Organisation Health and Work Productivity Questionnaire Competing Interests PM has a part-time salaried role with health and well-being business consultants Vielife. No other financial competing interests No non-financial competing interests. Authors' contributions PM performed all of the work that is contained within this paper. Supplementary Material Additional File 1 Health & Well-being Questionnaire Questionnaire and scoring algorithms. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548523.xml
524360	Cerebral relapse of metastatic gastrointestinal stromal tumor during treatment with imatinib mesylate: Case report	Background The management of unresectable or metastatic gastrointestinal stromal tumors (GISTs) has previously been difficult as they are resistant to conventional chemotherapy and radiation. The development of imatinib mesylate has made a major impact on the management of advanced GISTs. It is apparent that there are sanctuary sites such as the central nervous system where imatinib does not achieve adequate concentrations. We describe the case of a man with metastatic GIST who experienced multiple cerebral relapses of disease while systemic disease progression appeared to be controlled by imatinib. Case presentation A 47-year-old man presented in July 1999 with a jejunal GIST with multiple hepatic metastases. The jejunal primary was resected and after unsuccessful cytoreductive chemotherapy, the liver metastases were also resected in December 1999. The patient subsequently relapsed in August 2001 with symptomatic hepatic, subcutaneous gluteal, left choroidal and right ocular metastases all confirmed on CT and PET scanning. Biopsy confirmed recurrent GIST. MRI and lumbar puncture excluded central nervous system involvement. The patient was commenced on imatinib 400 mg bd in September 2001 through a clinical trial. The symptoms improved with objective PET and CT scan response until December 2002 when the patient developed a right-sided foot drop. MRI scan showed a left parasagittal tumor which was resected and confirmed histologically to be metastatic GIST. Imatinib was ceased pre-operatively due to the trial protocol but recommenced in February 2003 on a compassionate use program. The left parasagittal metastasis recurred and required subsequent re-excision in September 2003 and January 2004. Control of the systemic GIST was temporarily lost on reduction of the dose of imatinib (due to limited drug supply) but on increasing the dose back to 800 mg per day, systemic disease was stabilized for a period of time before generalised progression occurred. Conclusion This case illustrates that the brain can be a sanctuary site to treatment of GISTs with imatinib. Maintaining dosing of imatinib in the face of isolated sites of disease progression is also important, as other metastatic sites may still be sensitive.	Background Gastrointestinal stromal tumors (GISTs) are rare mesenchymal gastrointestinal tumors which can have an aggressive course. Management of these tumors apart from surgical resection has been difficult in the past because they are resistant to conventional chemotherapy [ 1 ] and radiation. The development of imatinib mesylate [ 2 ] a receptor tyrosine kinase inhibitor has made a major impact on the management of advanced GISTs. It specifically targets the c- kit (CD117) proto-oncogene gain of function mutation characterising GISTs, blocking the c- kit kinase, leading to growth cessation and significant durable clinical remissions. This oral drug is also active in all phases of chronic myeloid leukemia (CML) as it also targets the bcr-abl tyrosine kinase. It is apparent that there are sanctuary sites such as the central nervous system where imatinib does not achieve adequate concentrations. We describe the case of a man with metastatic GIST who experienced multiple cerebral relapses of disease while systemic disease progression appeared to be controlled by imatinib. Case presentation A 47-year-old man presented in July 1999 with melena. A small bowel series and CT abdomen showed a jejunal mass and a 5 × 5 cm complex hepatic mass. A biopsy of the liver lesion revealed a spindle cell tumor. Laparotomy was performed, and the 7.5 cm jejunal mass was resected. A total of 4 liver lesions were noted, but not resected. The histopathology confirmed a gastrointestinal stromal tumor with clear resection margins. He subsequently had 4 cycles of attempted cytoreductive chemotherapy using doxorubicin and dacarbazine. A repeat CT scan showed progression of the liver metastases. An extended right hemihepatectomy was performed in December 1999 with successful excision of all 4 liver metastases. The patient remained well until review in August 2001 when he complained of lethargy, right upper quadrant abdominal pain, diplopia and blurred vision in the left eye. Examination revealed weakness of the right lateral rectus ocular muscle, an amelanotic left choroidal lesion, hepatomegaly and a subcutaneous nodule in the gluteal region. An enhancing lesion in the infero-lateral region of the right globe was confirmed on CT which was thought to be the cause of the ocular muscle weakness. The CT scan also demonstrated a recurrence of multiple hepatic metastases. There were no intracerebral lesions. The gluteal lesion was biopsied and confirmed recurrence of GIST (CD117 positive). A positron emission tomogram (PET) scan also confirmed disease recurrence in the same distribution. Lumbar puncture and MRI scan of the brain excluded the presence of leptomeningeal or cerebral metastases. The patient was commenced on imatinib mesylate (STI-571, Gleevec, Novartis) 400 mg bd in September 2001 as part of a clinical trial. He felt much improved by November 2001 when a repeat CT abdomen showed stable disease but PET scan now showed no FDG uptake. By January 2002 his diplopia had completely resolved but the left-sided choroidal lesion remained unchanged on fundoscopy. The buttock lesion had also resolved. A progress CT in December 2002 showed minor enlargement of one of the liver lesions. A PET scan however continued to show no areas of abnormal FDG uptake. The patient at that time had developed a right-sided foot drop. MRI of the brain and spine demonstrated a left parasagittal tumor with radiographic features consistent with a meningioma (see Figure 1 ). Imatinib was ceased preoperatively as per the trial protocol. A craniotomy was performed on the 28 th January 2003 with complete resection of the lesion. Histopathology demonstrated metastatic GIST (CD117 positive) (see Figures 2 and 3 ). Post operatively the patient developed recurrent diplopia (due to recurrent right lateral rectus weakness) with blurred vision off imatinib. This was recommenced at a dose of 400 mg bd on the 14 th February 2003 after being ceased 6 weeks earlier because of the documented disease progression in the brain as required by the trial protocol. Drug supply was obtained through a compassionate use program. Repeat fundoscopy in February 2003 showed the choroidal lesion had enlarged. His foot drop persisted, however his diplopia again had completely resolved by March 2003. Mutational analysis on the tumor blocks was carried out. An in-frame GCCTAT insertion/duplication in exon 9 of c- kit in the original jejunal tumor, the liver and the cerebral metastases were detected (See Figure 4 ). No mutations were found in exons 11, 13 or 17 in any of the samples. Due to limited drug supply available on compassionate use (pending local approval for reimbursement), the patient's dose of imatinib mesylate was reduced to 400 mg per day in March 2003. Six weeks later, his diplopia had returned and a progress CT abdomen demonstrated a minor progression of the liver lesions. His liver function tests remained normal. A subsequent PET scan again showed no abnormal uptake despite disease progression on the CT scan. His dose of imatinib mesylate was increased initially to 600 mg per day with resolution of the diplopia. By May 2003 his foot drop had worsened and his dose of imatinib mesylate was increased back to 800 mg per day. Despite the increase in dose, his foot drop worsened. A repeat CT brain demonstrated a recurrence of the cerebral metastasis with surrounding vasogenic oedema in the previous site of resection. A repeat abdominal CT showed no significant change in the size of the liver metastasis and mild shrinking of the nodule in the buttock. Due to limited treatment options available for the cerebral metastasis, a re-resection of the cranial metastasis was offered. A repeat MRI of the brain in late July 2003 confirmed the presence of the left parasagittal lesion with surrounding edema but no mass effect. Repeat craniotomy and incomplete debulking of the parasagittal metastasis was performed on the 9 th September 2003. A small residual area of tumor was seen on the postoperative scan. Abdominal imaging two months later showed that two of the liver lesions had increased in size with the other areas stable. He was not a candidate for further hepatic resection as there was insufficient liver reserve due to the past surgery. Radiofrequency ablation was declined as the patient did not have symptoms referable to the area. The patient remained well until December 2003 when he experienced symptoms of headaches, worsening diplopia, right foot drop and left arm weakness. MRI scan confirmed recurrence of the cerebral metastasis with extension across the falx cerebri. He declined cranial radiotherapy treatment at the time and instead underwent a third resection of the lesion in January 2004 where incomplete debulking was achieved with early improvement of his limb weakness. In April 2004 the patient enrolled into a randomised placebo controlled clinical trial of a novel multi-kinase inhibitor SU-11248 (Pfizer) for the treatment of imatinib refractory GIST. However his condition slowly deteriorated and he died in July 2004. Discussion This case illustrates a man who has had evidence of presumed ocular involvement by the GIST that initially responded to imatinib who had a cranial relapse while the systemic disease initially remained controlled. This would imply that the central nervous system could be a sanctuary site where the imatinib mesylate does not achieve adequate levels. Preclinical mice models of CML have shown development of central nervous involvement on imatinib despite systemic disease control with cerebral spinal fluid levels being 155 times lower than plasma [ 3 ]. This is supported by clinical data from treatment of CML, where isolated cerebral relapses [ 4 , 5 ] have been described and low cerebrospinal fluid (CSF) levels of imatinib mesylate documented during therapy with the drug [ 6 ]. One case of cerebral metastases from advanced GIST responding to imatinib mesylate has been published [ 7 ]. We would postulate that the blood brain barrier might be disrupted in some individuals thereby allowing better penetration of the drug to the brain. However in those individuals with good systemic disease control, the central nervous system may represent a sanctuary site for imatinib sensitive disease to progress. There appears to be a relationship between the presence of different activating kinase mutations of kit and clinical outcomes of GISTs on imatinib [ 8 ]. The exon 9 mutation encoding the extracellular domain occurs in approximately 15% of GISTs resulting in duplication of Ala 502 and Tyr 503 This may be marker for malignant course of the disease as 71% have a highly malignant course and 59% arise exclusively in the small intestine [ 9 ]. Patients with exon 9 mutations also have a much worse prognosis than those with the more commonly found exon 11 mutations [ 8 ]. The difference is likely to be due to differences in downstream signalling in these mutations affecting the susceptibility of the GIST to imatinib and in our case may have compounded the problem with reduced CSF levels of the drug. Exon 17 mutations have been found in some GISTs that have relapsed on imatinib and are thought to be a mechanism of acquired resistance [ 10 ]. The absence of this superadded mutation would lend support to the central nervous system in being a sanctuary site in this patient. Conclusions The central nervous system can be a sanctuary site to treatment of GIST with imatinib mesylate. Prolonged control of the recurrences in this location was achieved by repeated resections. This patient also highlights the importance of maintaining dosing of imatinib mesylate in the face of isolated sites of disease progression, as other metastatic sites may still be sensitive. Cessation and lowering of the dose of the drug led to temporary loss of systemic control in this case. Competing interests David Goldstein and Paul Waring have both consulted and spoken on behalf of Novartis Pharma on imatinib and GIST. Authors' contributions BH, DY, DG and GC participated in the clinical care of the case. PW and VB performed the mutation analysis and prepared the histopathology images. BH and DY drafted the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524360.xml
545952	Analysis of the kinetic mechanism of recombinant human isoprenylcysteine carboxylmethyltransferase (Icmt)	Background Isoprenylcysteine carboxyl methyltransferase (Icmt) is the third of three enzymes that posttranslationally modify proteins that contain C-terminal CaaX motifs. The processing of CaaX proteins through this so-called prenylation pathway via a route initiated by addition of an isoprenoid lipid is required for both membrane targeting and function of the proteins. The involvement of many CaaX proteins such as Ras GTPases in oncogenesis and other aberrant proliferative disorders has led to the targeting of the enzymes involved in their processing for therapeutic development, necessitating a detailed understanding of the mechanisms of the enzymes. Results In this study, we have investigated the kinetic mechanism of recombinant human Icmt. In the reaction catalyzed by Icmt, S-adenosyl-L-methionine (AdoMet) provides the methyl group that is transferred to the second substrate, the C-terminal isoprenylated cysteine residue of a CaaX protein, thereby generating a C-terminal prenylcysteine methyl ester on the protein. To facilitate the kinetic analysis of Icmt, we synthesized a new small molecule substrate of the enzyme, biotin-S-farnesyl-L-cysteine (BFC). Initial kinetic analysis of Icmt suggested a sequential mechanism for the enzyme that was further analyzed using a dead end competitive inhibitor, S-farnesylthioacetic acid (FTA). Inhibition by FTA was competitive with respect to BFC and uncompetitive with respect to AdoMet, indicating an ordered mechanism with SAM binding first. To investigate the order of product dissociation, product inhibition studies were undertaken with S-adenosyl-L-homocysteine (AdoHcy) and the N-acetyl-S-farnesyl-L-cysteine methylester (AFCME). This analysis indicated that AdoHcy is a competitive inhibitor with respect to AdoMet, while AFCME shows a noncompetitive inhibition with respect to BFC and a mixed-type inhibition with respect to AdoMet. These studies established that AdoHcy is the final product released, and that BFC and AFCME bind to different forms of the enzyme. Conclusions These studies establish that catalysis by human Icmt proceeds through an ordered sequential mechanism and provide a kinetic framework for analysis of specific inhibitors of this key enzyme.	Background Posttranslational modification of eukaryotic proteins with lipids is a prevalent mechanism for controlling the subcellular localization and activity of these proteins [ 1 ]. Most proteins terminating in a CaaX sequence (C, cysteine; "a", generally an aliphatic residue; X, the carboxy-terminal residue) are subject to modification by isoprenoid lipids via their ability to serve as substrates for protein farnesyltransferase or protein geranylgeranyltransferase type I [ 2 ]. Following covalent attachment of the farnesyl or geranylgeranyl isoprenoid to the Cys thiol of the CaaX sequence, the majority of these proteins are further processed by removal of the carboxyl-terminal aaX residues by an endoprotease termed Rce1 and methylation of the newly-exposed carboxyl group of the isoprenylated cysteine residue by an enzyme termed isoprenylcysteine carboxylmethyltransferase (Icmt) [ 3 , 4 ]. While isoprenoid modification of CaaX proteins is the principal determinant of their membrane targeting, the subsequent steps of proteolysis and methylation are clearly important. Studies performed using small molecule prenylcysteines such as N-acetyl-S-farnesyl-L-cysteine (AFC) and N-acetyl-S-geranylgeranyl-L-cysteine (AGGC) [ 5 ] showed that carboxyl methylation is a critical determinant of the hydrophobicity of the farnesylated moiety, whereas in the case of geranylgeranylated counterpart the effect is much less. Similar results were obtained in studies with short prenylated peptides [ 6 ]. Ras proteins, which are primarily farnesylated, are largely mislocalized in cells in which the Icmt gene has been disrupted and in cells in which the methylation pathway has been perturbed [ 7 , 8 ], suggesting that this processing step is critical for trafficking and/or stable membrane association. In more biological settings, disruption of either the Rce1 or Icmt genes in mice results in embryonic lethality [ 9 , 10 ], and a very recent study has shown that genetic disruption of Icmt in cells dramatically attenuates their ability to be transformed by the K-Ras oncogene [ 11 ]. Altogether, a picture has emerged in which C-terminal methylation of prenylated proteins is thought to contribute substantially to their affinity for cell membranes [ 12 - 15 ], to influence rates of protein turnover [ 11 , 16 ], and to facilitate functional interactions with other proteins [ 17 - 19 ]. Although Icmt is a protein methyltransferase, the enzyme can efficiently modify simple prenylcysteines [ 6 , 20 - 22 ], a property that has the potential to greatly facilitate kinetic analysis of the enzyme. The only kinetic study of an isoprenylcysteine methyltransferase activity to date was performed prior to the molecular identification of Icmt and involved kinetic analysis of a methyltransferase activity in retinal rod outer segment membranes that was capable of modifying the small molecule substrate N-acetyl-L-farnesylcysteine (AFC) [ 20 ]. However, the cloning of mammalian Icmt [ 23 ], and the development of an expression system to produce recombinant protein [ 8 ], now allows an unambiguous analysis of the properties of this important enzyme. Here we report studies of the kinetic mechanism of recombinant human Icmt produced in Sf9 cells. This analysis was also facilitated by the synthesis of a new small molecule Icmt substrate, biotin-S-farnesyl-L-cysteine (BFC), that allowed development of a facile assay for enzyme activity. Through standard Michaelis-Menten analysis as well as product competition and dead-end inhibitor studies, we demonstrate that catalysis by Icmt proceeds through an ordered sequential mechanism in which the substrate AdoMet binds first and its product AdoHCy is released last. Results Characterization of the small molecule Icmt substrate, BFC To overcome the inherent problems associated with use of S-prenylated peptides and proteins as Icmt substrates (expense in production, unwieldy separation techniques, etc), we synthesized a small molecule substrate for the enzyme that contains an appended biotin moiety (Fig. 1A ) to facilitate the separation required for product analysis. The coupling of biotin moiety to the free amino group of the S-farnesylcysteine, FC, was readily achieved through the use of commercial biotin N-hydroxysuccinimide ester and the product BFC could be readily purified by precipitation or by reverse-phase chromatography (see Methods ). BFC was characterized in terms of its ability to serve as a substrate for recombinant human Icmt using a standard in vitro methylation assay (Fig. 1B ). The apparent K m of BFC was 2.1 ± 0.4 μM, which is essentially identical to the K m of 2.1 μM determined for farnesylated, Rce1-proteolyzed K-Ras (data not shown). Hence, BFC is a comparable to K-Ras as an Icmt substrate and has the added advantages of being a stable small molecule that can be readily captured on avidin resins. Figure 1 A new small-molecule substrate of Icmt A. Structure of biotin-S-farnesyl-L-cysteine (BFC) B. Utilization of BFC as a substrate by recombinant human Icmt. Shown are Michaelis-Menten and Lineweaver-Burk plot (inset) of the formation of BFC-[ 3 H]methylester as a function of BFC concentration. The data shown are the mean of duplicate determinations from a single experiment and are representative of two additional experiments. Distinguishing ping-pong vs. sequential kinetic mechanisms for human Icmt Detailed knowledge of the kinetic mechanism of an enzyme is very important in providing the foundation for analysis of structure-function studies and in inhibitor design studies. For a two substrate enzyme reaction such as that catalyzed by Icmt, there are three basic mechanisms: i) random sequential, ii) ordered sequential, and iii) ping-pong [ 28 , 29 ]. Initial velocity studies can be used to distinguish between a ping-pong mechanism, in which a product is released between the addition of the two substrates, and the sequential mechanisms, in which both substrates must bind before any product is released. Hence, in the first series of studies, the initial velocity of the Icmt reaction at different substrates concentrations was determined. In a ping-pong mechanism for an enzyme with substrates A and B, the plots of 1/v versus 1/[A] at different fixed [B], and vice versa, should yield parallel lines [ 28 ]. In a sequential mechanism, either ordered or random, the family of reciprocal plots should intersect above the X axis (if the binding of A increase the interaction with B), below the X-axis (if the binding of A decreases the interaction with B), or on the X-axis (if the binding of A has no effect on the interaction of B) [ 28 ]. The data obtained in the experiments where AdoMet concentration was varied at a series of fixed BFC concentrations is shown in Fig 2A , and Fig. 2B shows the data obtained when BFC concentration is varied at fixed AdoMet concentrations. These results show that, in each case, the families of reciprocal plots are not parallel and intersect above the X-axis, ruling out the possibility of a ping-pong mechanism. Moreover, the data for the experiments in which BFC concentration was varied at fixed AdoMet concentrations show an intersection of the reciprocal plots on Y-axis (Fig. 2B ), indicating that the reaction behaves as rapid-equilibrium bireactant system [ 28 ]. Figure 2 Distinguishing ping-pong vs. sequential kinetic mechanisms for human Icmt . A. Lineweaver-Burk plot for the methylation of BFC carried out in the presence of (◆) 2 μM, (□) 4 μM and (▲) 8 μM of BFC and varied [AdoMet]. B. Lineweaver-Burk plot for the methylation of BFC carried out in the presence of (◇) 5 μM, (■) 10 μM, (○) 20 μM of AdoMet and varied [BFC]. For both experiments, the incubation time was 20 min and 0.5 μg of Sf9 membranes containing recombinant human Icmt protein were used for each condition. Data shown are the mean of duplicate determinations from a single experiment, and are representative to two such experiments. Distinguishing ordered sequential vs. random sequential mechanisms for human Icmt While the initial velocity studies described above can distinguish between a ping-pong mechanism and a sequential mechanism, they cannot be used to distinguish an ordered from a random mechanism. These two types of sequential mechanisms can be distinguished, however, through the use of so-called "dead-end" substrates that cannot go on to form products [ 30 ]. Hence, we employed such a dead-end inhibitor of Icmt, farnesylthioacetic acid (FTA) [ 31 ], in kinetic studies. To distinguish between the two types of inhibition patterns this compound was examined for its inhibitory properties with respect to both the cognate (BFC) and noncognate (AdoMet) substrates under conditions where the fixed substrate was present at nonsaturating concentrations. The results obtained demonstrate that the FTA is a competitive inhibitor with respect to BFC, with a measured K i of 1.2 ± 0.2 μM (Fig, 3A , see also Table I ). In contrast, the experiments performed with varying AdoMet concentrations show a family of parallel lines (Fig. 3B ), which is a characteristic profile for an uncompetitive inhibition [ 28 , 29 ]. If FTA was able to combine with the free enzyme (i.e. the condition where its cognate substrate BFC binds first), the plots in Fig. 3B would have yielded lines that intersect at negative 1/v and 1/[AdoMet] values, i.e. FTA should have shown a mixed-type inhibitor with respect to AdoMet [ 20 ]. These results indicate that Icmt reaction occurs through an ordered mechanism in which AdoMet binds first to the enzyme followed by BFC binding to the AdoMet-Icmt binary complex. Figure 3 Distinguishing ordered sequential vs. random sequential mechanisms for human Icmt . A. Lineweaver-Burk plot for the dead-end inhibition of BFC methylation by FTA at a fixed concentration of AdoMet. Assays were conducted in the presence of fixed [AdoMet] at 5 μM and either (◇) 0 μM, (■) 5 μM or (○) 10 μM of FTA at the indicated concentrations of BFC. B. Lineweaver-Burk plot for the dead-end inhibition of BFC methylation by FTA at a fixed concerntration of BFC. Assays were conducted in the presence of fixed [BFC] at 4 μM and either (◆) 0 μM, (□) 2.5 μM or (▲) 5 μM of FTA at the indicated concentrations of AdoMet. Assays were conducted as described in the legend to Fig. 2. Data shown are the mean of duplicate determinations from a single experiment, and are representative to two such experiments. Table 1 K i values and type of inhibition for the interaction of a dead-end inhibitor (FTA) and reaction products (AdoHCy, AFCME) with Icmt. The K m values obtained for the two substrates of the reaction, BFC and AdoMet, are also shown for comparaison. Substrate\Inhibitor AdoHcy FTA AFCME BFC Competitive Competitive Noncompetitive K m = 2.1 ± 0.4 μM 3.59 ± 1.03 μM 1.17 ± 0.16 μM 1.91 ± 0.65 μM AdoMet Competitive Uncompetitive Mixed-type K m = 7.8 ± 1.2 μM 3.54 ± 1.12 μM 2.43 ± 0.70 μM Distinguishing the order of product dissociation from human Icmt Two products are formed in the reaction catalyzed by Icmt, a methylated prenylcysteine ( in vivo on proteins, but in vitro also on small molecules or peptides) and AdoHcy. To determine the order of the dissociation of these two products, we performed product inhibition using the prenylcysteine methylester, AFCME, and AdoHcy. Examination of the initial rates of product formation at fixed BFC and varying AdoMet concentrations in presence of three concentrations of AdoHcy (Fig. 4A ), revealed that AdoHcy is a competitive inhibitor with respect to AdoMet with an apparent K i of 3.5 ± 1.0 μM (Table I ). This finding is consistent with both AdoMet and AdoHcy binding to the same form of Icmt, ie. the free enzyme, suggesting that AdoMet binds first in an ordered mechanism and that AdoHcy is the last product released. When the same experiment was performed at varying BFC concentrations, a very similar pattern was observed (Fig. 4B ), revealing that AdoHcy is also a competitive inhibitor with respect to BFC with a K i of 3.6 ± 1.0 μM. While a classic ordered sequential mechanism in which AdoHcy was released last would result in this type of inhibition being non-competitive or mixed-type, this type of behavior in which a single product binds competitively with both substrates can also be observed in ordered bireactant systems that proceed via a rapid equilibrium process [ 28 ]. Figure 4 Distinguishing the order of product dissociation from human Icmt: Inhibition studies with the AdoHcy product . A. Lineweaver-Burk plot for the product inhibition of BFC methylation by AdoHcy at a fixed concentration of BFC. Assays were conducted in the presence of fixed [BFC] at 4 μM and either (◆) 0 μM, (□) 5 μM or (▲) 10 μM of AdoHcy at the indicated concentrations of AdoMet. Assays were conducted as described in the legend to Fig. 2. Data shown are the mean of duplicate determinations from a single experiment, and are representative to three such experiments. B. Lineweaver-Burk plot for the product inhibition of BFC methylation by AdoHcy at a fixed concentration of AdoMet. Assays were conducted in the presence of fixed [AdoMet] at 5 μM and either (◇) 0 μM, (■) 2.5 μM, (○) 5 μM, or (●) 10 μM μM of AdoHcy at the indicated concentrations of BFC. Assays were conducted as described in the legend to Fig. 2. Data shown are the mean of duplicate determinations from a single experiment, and are representative to more than >4 such experiments. The product inhibition experiments were next repeated with AFCME as the second class of product inhibitor. An ordered sequential mechanism with initial departure of the methylated prenylcysteine product requires that noncompetitive or mixed-type inhibition be observed with respect to both of the substrates of the reaction [ 29 ]. The data obtained with L-AFC did indeed demonstrate precisely this [ 20 ]. Noncompetitive inhibition by AFCME was observed with respect to the BFC substrate (Fig. 5A ) with an apparent K i of 1.9 ± 0.6 μM, and mixed-type inhibition was observed with respect to AdoMet as a substrate with an apparent K i of 2.4 ± 0.7 μM, respectively (Fig. 5B ). These kinetic results are summarized in Table I . In addition, essentially identical results were observed with a second prenylcysteine-type product analog N-acetyl-S-farnesyl-L-cysteine methyl amide (AFCMA) (data not shown). Altogether, the results this kinetic analysis are completely consistent with the reaction catalyzed by Icmt proceeding through an ordered sequential mechanism with the AdoMet substrate binding first and the AdoHcy product being released last. Figure 5 Distinguishing the order of product dissociation from human Icmt: Inhibition studies with the AFCME product . A. Lineweaver-Burk plot for the product inhibition of BFC methylation by AFCME at a fixed concentration of BFC. Assays were conducted in the presence of fixed [BFC] at 4 μM and either (◆) 0 μM, (□) 5 μM or (▲) 10 μM of AFCME at the indicated concentrations of AdoMet. Assays were conducted as described in the legend to Fig. 2. Data shown are the mean of duplicate determinations from a single experiment, and are representative to two such experiments. B. Lineweaver-Burk plot for the product inhibition of BFC methylation by AFCME at a fixed concentration of AdoMet. Assays were conducted in the presence of fixed [AdoMet] at 5 μM and either (◇) 0 μM, (■) 5 μM or (○)10 μM of AFCME at the indicated concentrations of BFC. Assays were conducted as described in the legend to Fig. 2. Data shown are the mean of duplicate determinations from a single experiment, and are representative to more two such experiments. Discussion The studies in this report provide the first detailed kinetic analysis of the molecular entity Icmt, the enzyme responsible for the final step in the maturation of CaaX-type protein in eukaryotic cells. To facility analysis of Icmt activity, we synthesized a new substrate for Icmt, biotin-S-farnesyl-L-cysteine (BFC), that has two properties that improve its utility compared with the only other described small molecule substrate for the enzyme, AFC. First, BFC is utilized by the enzyme with a K m (2.1 μM) essentially identical to that of an authentic substrate, farnesylated, Rce1-proteolyzed, K-Ras protein, whereas the apparent Km for AFC is 10-fold higher at 20 μM [ 20 , 31 ]. The second improvement in the BFC substrate is, of course, the appended biotin moiety, which allows facile isolation of product from reaction mixtures using commercially-available avidin resins. Furthermore, this substrate is ideal for use in high-throughput screening for inhibitors of the enzyme since it allows use of scintillation proximity-type assays. Our first series of kinetic studies was designed to distinguish between the two general kinetic mechanisms that exist for multisubstrate enzymes. The first general mechanism is termed sequential and describes reactions in which all the substrates must bind to the enzyme before the first product is released, whereas reactions in which one or more products are released prior to all substrates being added are termed ping-pong. To distinguish between these reaction types, we performed classic steady state kinetic analyses of Icmt. The results of this analysis revealed that catalysis by Icmt exhibits all the properties of rapid equilibrium bireactant system [ 28 , 29 ] and hence proceeds via a sequential mechanism. The second series of experiments we undertook was designed to distinguish between a random sequential vs. ordered sequential mechanism; this involved a determination of whether the enzyme could initially form a complex with either substrate or whether must it bind them in a defined order. To verify the assignment of a sequential mechanism for Icmt and to distinguish between an ordered versus a random sequential mechanism, studies with a dead-end inhibitor of Icmt were performed. In a random sequential mechanism, there is no defined order of either substrate binding or product release, whereas in an ordered sequential mechanism the binding of the first substrate is required for the second and the products dissociate in an obligatory order [ 28 , 29 ]. The studies with the dead-end substrate FTA revealed that FTA is a competitive inhibitor with respect to BFC, whereas in a random mechanism FTA would be expected to be a mixed-type inhibitor with respect to AdoMet [ 28 ]. Furthermore the double-reciprocal plots from the analysis of FTA as an inhibitor with respect to AdoMet showed the parallel lines indicative of an uncompetitive inhibition, signifying that FTA is unable to bind to the free enzyme. Hence, AdoMet binds first to enzyme and FTA interacts with the AdoMet-Icmt complex since, if BFC combined first with enzyme, the inhibition by FTA should have been competitive with respect to BFC and a mixed-type, noncompetitive or competitive inhibition with respect to AdoMet. Together, these results indicate that the reaction catalyzed by Icmt is proceeds through an ordered sequential mechanism in which the AdoMet substrate binds first. Following the assignment of a sequential mechanism for Icmt, product inhibition experiments were employed to investigate the order of product dissociation from the enzyme. The finding that AdoHcy is a competitive inhibitor with respect to AdoMet revealed that this compound could interact with free enzyme; ie. it must be the final product released. Also, the finding that the prenylcysteine methylester AFCME exhibited mixed-type inhibition with respect to AdoMet is the result expected if AdoHcy is the last product released. Interestingly, when AdoHcy was examined for its inhibition with respect to BFC a different result was obtained from that of the previous kinetic study of prenylcysteine methyltransferase activity in rod outer segments [ 20 ]. With recombinant human Icmt, AdoHcy is a competitive inhibitor with respect to BFC, indicating that the Icmt-AdoHcy complex is inactive and cannot bind to BFC, an observation that further reinforces the conclusion of an ordered sequential mechanism for this enzyme. The inhibition constants for AFCME determined in our experiments of 1.9 μM and 2.4 μM with respect to BFC and AdoMet, respectively, are substantially different from those in the previous study on the methyltransferase activity in rod outer segments of 41 μM and 73 μM respectively [ 20 ]. We believe these results are more likely due to the markedly enriched preparation used in our study rather that to any fundamental difference in the enzyme activities; we used 1000-fold less membrane in our assays and it is likely that the hydrophobic AFCME was substantially "sopped up" by the membrane lipid in the previous study, markedly reducing the level available to interact with the enzyme. This phenomenon, which is related to that known as surface dilution kinetics, comes into play when both the concentration of the membrane lipid and of the ligand employed contribute to the kinetic parameter measured [ 32 ]. Conclusions In summary, we have demonstrated that the kinetic mechanism of CaaX protein methylation by Icmt is an ordered sequential mechanism in which the AdoMet substrate associates first with the enzyme and the AdoHCy product dissociates last. This work provides a kinetic framework for the analysis of specific inhibitors of this enzyme that will most assuredly be forthcoming given the recent biological validation of Icmt as a target for blocking oncogenic transformation of cells [ 8 , 11 , 33 ]. Methods Materials Streptavidin-sepharose beads were purchased from Amersham, trans , trans -farnesyl bromide, biotin N-hydroxysuccinimide ester and S-(5'-adenosyl)-L-methionine p-toluenesulfonate were purchased from Sigma-Aldrich, L-cysteine was purchased from Novabiochem, [ 3 H- methyl ]-S-adenosyl-L-methionine was purchased from Perkin Elmer Life Sciences, farnesylthioacetic acid (FTA) was purchased from Biomol, S-(5'-adenosyl)-L-homocysteine was purchased from Fluka. The N-acetyl-S-farnesylcysteine methyl ester (AFCME) and N-acetyl-S-farnesylcysteine methyl amide (AFCMA) were synthesized as previously described ([ 24 - 26 ]). Recombinant human Icmt was prepared by infection of Sf9 cells with a recombinant baculovirus containing the entire open reading frame of the human Icmt cDNA as described [ 8 ]. The membrane fraction of the infected Sf9 cells, isolated as described for studies with the Rce1 protease [ 27 ], was used as the source of Icmt for all studies described. Syntheses of biotin-S-farnesyl L-cysteine (BFC) S-Farnesyl L-cysteine (FC) was prepared by reaction of farnesyl bromide with L-cysteine in methanol/ammoniac solvent as described [ 26 ]. The resultant FC product was separated from L-cysteine by extraction with butanol/H 2 O (1:1); the butanol phase was then evaporated under reduce pressure and the FC product washed several times with hexane to remove residual farnesyl bromide. Two coupling procedures were used to attach the biotin moiety to the amino group of FC; both involved the use of biotin N-hydroxysuccinimide methylester (biotin-NHS) as the biotinylation agent. In the first method, an excess of biotin-NHS (75 μmol) to FC (7.5 μmol) was used. The two compounds were dissolved in 2.3 ml of DMSO and 200 μl of 1M Hepes, pH 12, was added. Following a 2 h incubation at room temperature, the DMSO was evaporated under reduced pressure and the resulting residue extracted with a solution of butanol/H 2 O (1:1). The butanol phase was dried and the residue dissolved in 100 μl of methanol; this solution was then diluted to 1 ml by addition of 0.1% trifluoroacetic acid (TFA). The addition of the TFA resulted in the appearance of a white precipitate of essentially pure BFC as judged by chromatography and NMR analysis. The second coupling method used an excess of FC (2.5 mmol) compared to biotin-NHS (0.73 mmol); these two compounds were dissolved in 18 ml of DMSO. To this solution was added 2 ml of 1M Hepes, pH 12, and the coupling allowed to proceed for 2 h at room temperature. As with the first method, the DMSO was evaporated under reduced pressure, the resulting residue extracted with a solution of butanol/H 2 O (1:1), and the butanol phase dried and the residue dissolved in methanol. Because of the excess of FC present with the BFC product, specific precipitation of the BFC product was unsuccessful. Instead, the BFC was purified by preparative HPLC on a C 18 column developed in CH 3 CN/H 2 O (2:3). On this matrix, BFC was well-resolved from FC. The peak fractions were collected and solvent evaporated under reduced pressure; the resulting product was white solid that was >95% pure as judged by analytical reverse-phase HPLC [C 18 matrix developed in CH 3 CN/H 2 O/TFA (90:10:0.1). Proton NMR spectra of the products obtained by either method were completely consistent with that expected for authentic BFC. Icmt assay The assay developed for Icmt activity involved quantitation of [ 3 H]methyl incorporation into the small molecule substrate BFC. For the standard assay, reactions were initiated by addition of Sf9 membranes containing Icmt (0.5 μg protein) to an assay mixture containing BFC (4 μM) and [ 3 H]AdoMet (5 μM, 1.3 Ci/mmol) in100 mM Hepes, pH 7.4 and 5 mM MgCl 2 in a total volume of 45 μl. Reactions were carried out for 20 min at 37°C, whereupon they were terminated by addition of 5 μl of 10% Tween 20. Following termination, streptavidin beads (10 μl of packed beads suspended in 500 μl of 20 mM NaH 2 PO 4 , pH 7.4, contaning 150 mM NaCl) were added, and the mixtures mixed by gentle agitation overnight at 4°C. The beads were harvested by centrifugation in a tabletop microcentrifuge at 10,000 rpm for 5 min and washed 3 times with 500 μl of 20 mM NaH 2 PO 4 , pH 7.4, containing 150 mM NaCl. The beads were then suspended in 100 μl of the same buffer, transferred to scintillation vials, and radioactivity determined. For the kinetic analyses, the concentrations of substrates (AdoMet, BFC) or additional ligands (eg. AdoHcy, AFCME, etc) were varied as detailed in the legends to the appropriate figures. Abbreviations used Icmt, Isoprenylcysteine carboxyl methyltransferase; AdoMet, S-adenosyl-L-methionine; AdoHcy, S-adenosyl-L-homocysteine; AFC, N-acetyl-L-farnesylcysteine; AGGC, N-acetyl-S-geranylgeranyl-L-cysteine; TFA, trifluoroacetic acid; BFC, biotin-S-farnesyl-L-cysteine; FTA, S-farnesylthioacetic acid; AFCME, N-acetyl-S-farnesyl-L-cysteine methylester; AFCMA, N-acetyl-S-farnesyl-L-cysteine methyl amide Authors' contributions RAB carried out all of the studies reported. PJC conceived of the study, and participated in its design and coordination and helped to draft the manuscript. Both authors read and approved the final manuscript. Figure 6 Proposed kinetic mechanism of human Icmt . See text for details.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545952.xml
544872	Helicobacter pylori and gastroduodenal pathology: New threats of the old friend	The human gastric pathogen Helicobacter pylori causes chronic gastritis, peptic ulcer disease, gastric carcinoma, and mucosa-associated lymphoid tissue (MALT) lymphoma. It infects over 50% of the worlds' population, however, only a small subset of infected people experience H. pylori -associated illnesses. Associations with disease-specific factors remain enigmatic years after the genome sequences were deciphered. Infection with strains of Helicobacter pylori that carry the cytotoxin-associated antigen A ( cagA ) gene is associated with gastric carcinoma. Recent studies revealed mechanisms through which the cagA protein triggers oncopathogenic activities. Other candidate genes such as some members of the so-called plasticity region cluster are also implicated to be associated with carcinoma of stomach. Study of the evolution of polymorphisms and sequence variation in H. pylori populations on a global basis has provided a window into the history of human population migration and co-evolution of this pathogen with its host. Possible symbiotic relationships were debated since the discovery of this pathogen. The debate has been further intensified as some studies have posed the possibility that H. pylori infection may be beneficial in some humans. This assumption is based on increased incidence of gastro-oesophageal reflux disease (GERD), Barrett's oesophagus and adenocarcinoma of the oesophagus following H. pylori eradication in some countries. The contribution of comparative genomics to our understanding of the genome organisation and diversity of H. pylori and its pathophysiological importance to human healthcare is exemplified in this review.	Introduction Helicobacter pylori is a bacterium that colonizes the harshly acidic milieu of the human stomach. More than half of the world's population carries this infection. Infection rates vary among the developed and developing countries of the world. H. pylori infection is on a steep decline in most of the western countries mainly due to the success of combination therapies and improved personal hygiene and community sanitation to prevent re-infection. However, the situation is not improving in many of the developing countries due to failure of treatment regimes and emergence of drug resistance. The infection in some cases leads to chronic superficial gastritis, chronic active gastritis, peptic ulcer disease and gastric adenocarcinoma [ 1 - 4 ]. One of the most distinctive features of H. pylori is the genetic diversity between clinical isolates obtained from different patient populations. Most H. pylori isolates can be discriminated from others by DNA profiling [ 5 - 8 ] or sequencing of corresponding genes due to mainly a high degree of sequence divergence between orthologs (3–5%) [ 9 , 10 ]. Also, H. pylori has a panmictic or freely recombining population structure [ 11 ] and is naturally competent [ 12 ]. These characteristics facilitate an inter-strain recombination due mainly to horizontal exchange of alleles from other strains colonising the same niche, which is extremely common in H. pylori chromosome. However, such genetic recombinations in the H. pylori genome might not be deleterious because they occur in the plasticity zone, a special cluster of DNA rearrangements that protects the essential complement of genes by acting as a bed for foreign DNA insertion or abrogation. DNA loss and rearrangement are therefore a norm for H. pylori , and flexibility and diversity in gene content may contribute to bacterial fitness in different members of the diverse human host population. Post genomic analyses have revealed interesting attributes of H. pylori pathogenicity and novel mechanisms of causation of ulcer disease and cancer have been envisaged. Efforts to know the cause and potential benefits of the genetic diversity of this bacterium has led to some interesting discoveries relating to its co-evolution with the human host, microevolution while during infection and quasi-species development, virulence determinants and eradication strategies. Recent studies reviewed herein collectively aim at testing the speculation about whether H. pylori may be beneficial to human health in certain circumstances and whether eradication of this organism is always necessary? Epidemiological studies are needed in the context of such intriguing hypotheses. Results obtained from such studies might enable the development of a high-throughput screening system for high-risk groups within the huge population of H. pylori -infected individuals. Recent studies have shown that H. pylori infection protects against gastro-oesophageal reflux and oesophageal carcinoma. So it will be important to selectively eradicate H. pylori in people that are at the highest risk of developing gastric carcinoma. Eradication of highly pathogenic H. pylori specifically from high-risk groups would markedly reduce the worldwide incidence of ulcer and gastric cancer. Epidemiology and Evolution H. pylori infection is usually acquired during childhood, where transmission occurs predominantly within families [ 13 ]. A couple of recent studies demonstrated the possible co-existence of a large array of clonal lineages within H. pylori populations that are evolving in each individual separately from one another [ 14 , 10 ]. It is therefore probable that via this semi-vertical transmission of H. pylori strains, there are distinct sets of H. pylori genotypes colonising different human populations. With different strains evolving separately of one another and the fact that H. pylori is a genetically diverse (panmictic) organism, distinct genotypes have been found to be associated with particular geographic regions [ 15 , 16 ]. For example, the shuffling of variant regions within the vacA gene (a gene encoding a vacuolating cytotoxin) within a local H. pylori population has led to predominant vacA genotypes being characteristic of isolates from different geographic regions. In addition, worldwide studies encompassing H. pylori isolates from many geographic regions have demonstrated weak clonal groupings and geographic partitioning of H. pylori isolates [ 9 , 17 ]. If recombination only occurs between a resident H. pylori population, exchange of genetic sequences can genetically homogenise this population. As H. pylori is naturally competent and recombination occurs frequently [ 11 ], specific genotypes associated with different geographic regions occur as a result of this homogenising force. Introduction of polymorphisms and sequence variants from one H. pylori population from a particular geographic region to another H. pylori population from another geographic region via human migration makes the association of particular genotypes with specific geographic locations more difficult. Although the introduction of new polymorphisms into a particular H. pylori population poses a problem with identifying specific genotypes within certain geographic locales, it may, however, provide information on the ancestry of the hosts in whose stomachs the strains were carried. Studies have been aimed at demonstrating the path of human migration to Latin America with conflicting results regarding whether European or Asian populations brought H. pylori to South America [ 16 , 11 ]. However, a recent and comprehensive study by Flaush et al . [ 19 ] demonstrated that sequence analysis of H. pylori isolates recovered from twenty-seven countries displayed geographic partitioning. Thus, polymorphisms within the H. pylori genome can serve as useful markers for studying ancient human migrations. However, a mix up of H. pylori strains between migrated and native populations can sometimes complicate analysis. Accordingly, the study of migrated populations that have remained isolated from the native populations is essential. Genome organization, genetic diversity and microevolution Since its successful isolation in 1983 by Warren and Marshall, H. pylori has been linked to various pathologies and a strong association with gastric carcinoma and mucosa-associated lymphoid tissue lymphoma [ 1 , 3 ] has been established. However, although H. pylori is definitely responsible for these diseases, only less than 10% of people colonized with H. pylori portray disease symptoms. This suggests that specific H. pylori strains may be responsible for virulence in different hosts. Many studies have shown that certain allotypes of the vacA gene and the presence a functional cagA gene are associated with an increased risk of peptic ulceration and gastric cancer, respectively [ 20 - 22 ]. However, these correlations vary based on the host population studied and efforts to correlate other H. pylori alleles with clinical diseases have failed. So how do a few H. pylori strains trigger higher virulence as compared to other strains? Current approaches in functional genomics based on protein- protein interaction and microarray based transcription profiling are helping to decode this mystery. Functional genomics often uses the gene chip based expression profiling to provide a condition-dependent and time-specific genome wide profile of an organism's transcriptome [ 23 , 24 ]. Whereas, comparative genomics juxtaposes two or more genome sequences at the level of gene content and organization [ 25 , 26 ]. Both the approaches harness extensive computer algorithms and in silico modelling to summarise gene encoded (or putative) functions. H. pylori has been the first prokaryote wherein full genome sequence of two different patient isolates [J99 and 26995] were characterized and compared [ 27 , 28 ]. As H. pylori is a freely recombining or panmictic organism [ 11 ] the question of whether the two genome sequences would accurately represent the myriad of genetic diversity found among the strains was posed. Since the 2 sequenced strains were obtained a decade apart from the two different continents and cultured from the lesions of different gastric disorders, it has been widely assumed that their genome sequences will more likely portray the genetic diversity exhibited by clinical isolates. Comparative genomic analysis of the two completely sequenced strains revealed a significant amount of genetic variation between their genomes. For instance, the J99 genome is shorter (1,643,831 bp) than that of strain 26695 (1,667,867 bp) and has 57 less predicted ORF's [ 27 , 28 ]. Strains 26695 and J99 contain 110 and 52 strain specific genes, respectively [ 29 , 30 ], in which more than a half reside within a locus termed the plasticity cluster. A recent approach helped revised annotation and comparison of the two sequenced H. pylori genomes [ 31 ] and reclassified the coding sequences. Based on this study the total number of hypothetical proteins was reduced from 40% to 33%. A large amount of size variation was also discovered between orthologous genes mostly due to natural polymorphisms arising as a result of natural transformation and free recombination within H. pylori chromosome. Recombinational events including the presence of insertion elements, pathogenicity islands, horizontally acquired genes (restriction recombination genes), mosaics and chromosomal rearrangements were frequently annotated in subsequent bioinformatics based attempts. It has been argued that such diversity is a result of a lack of direct competition between strains, even when resident within different individuals within the same community [ 32 ]. However, a recent study has demonstrated that integration of foreign gene fragments acquired via natural transformation is often prevented by the well-developed restriction-modification systems in H. pylori genome [ 33 ]. It has been demonstrated that H. pylori has extensive, non-randomly distributed repetitive chromosomal sequences, and that recombination between identical repeats contributes to the variation within individual hosts [ 34 ]. That H. pylori is representative of prokaryotes, especially those with smaller (<2 megabases) genomes, that have similarly extensive direct repeats, suggests that recombination between such direct DNA repeats is a widely conserved mechanism to promote genome diversification [ 33 ]. In addition, although H. pylori has been termed as a panmictic organism [ 11 , 35 ], it is surprising that clonal lineages within H. pylori populations exist [ 36 - 39 ]. Recent reports demonstrated that H. pylori in some populations shows a clonal descent and suggest that a large array of H. pylori clonal lineages co-exist, which evolve in isolation from on another [ 14 ]. Moreover, in certain parts of the world H. pylori isolates have been shown to exhibit little genetic heterogeneity, based on fingerprint profiles [ 17 , 40 ]. Functional genomics, utilising microarray technology, has provided researchers with a powerful tool to investigate the genetic diversity of clinical isolates [ 41 ], the transcriptional profiles of isolates grown under different conditions [ 42 ], the identification of strain-specific and species-specific genes [ 29 , 30 ] and the diversity between strains giving rise to differing clinical illnesses [ 43 ]. One of the interesting findings using microarray based genotyping has been the discovery that H. pylori isolates undergo 'microevolution' and give rise to sub-species during prolonged colonisation of a single host [ 44 - 46 ]. The presence of stable sub-species within a single individual suggests an adaptation of a H. pylori population to specific host niches, facilitated by unknown advantages conferred to them by select plasticity region genes. Bjorkholm et al . [ 45 ] demonstrated that several loci differed within two genetically related isolates from the same host, one major difference being the presence of the cag pathogenicity island ( cag PAI) in one isolate and not the other. As the cagA gene and cag PAI are principle virulence factors within the strains, the excision or abrogation of the cag PAI within a strain may indicate that attenuating the virulence of a strain could be a favourable adaptation. The conundrum of strain diversity: How many more genome sequences do we need to understand this bug? Within the bacterial populations, genome content may not be fixed, as changing selective forces favour particular phenotypes; however, organisms well adapted to particular niches may have evolved mechanisms to facilitate such plasticity. The highly diverse H. pylori is a model for studying genome plasticity in the colonization of individual hosts. For H. pylori , neither point mutation, nor intergenic recombination requiring the presence of multiple colonizing strains, is sufficient to fully explain the observed diversity. The two H. pylori genomes sequenced to date are each from ethnic Europeans, and genomic comparisons modelled on these data are sufficient to identify novel loci from new strains, especially from understudied Asian populations. However, these genome sequences may not be fully representative of the entire diversity of the gene pool. Identification and characterization of such loci which are more abundant in the Asian gene pool may lead to newer insights into the mechanisms of H. pylori colonization, carriage and virulence in the countries of Asia which are more seriously under threat from H. pylori . Therefore, future high throughput efforts involving a large number of strains are clearly needed. Taking the Indian example for instance, according to the Ethnologue database , there are about 1683 languages and dialects ('mother tongues') in this country and H. pylori diversity therefore can be assumed to coincide with this figure. So one has to roughly look at the inter-strain genomic diversity contributed by approximately 1683 different strains representing each dialect and or a community. Nonetheless, genotypic data from each geographic area or a community is extremely vital and might constitute a missing piece of a large, biologic jigsaw puzzle. Natural competence and transformation Independent of the other two pathogenesis associated type IV systems, H. pylori harbours a dedicated type IV apparatus, the comB gene cluster [ 47 ] linked to the natural transformation and competence. The comB gene cluster is essential for the bacterium to take up plasmid and chromosomal DNA during natural transformation. To identify the genes essential for natural transformation competence in H. pylori , genetic approach of transposon shuttle mutagenesis has been used and the comB locus was located, consisting of orf2 and comB1-comB3 [ 48 , 49 ]. This cluster contains four tandemly arranged genes, ORF2, comB1, comB2 and comB3 as a single transcriptional unit. Subsequently, the components of comB cluster namely Orf2, comB1, comB2 and comB3 were renamed (according to homology with the Agrobacterium tumifaciens type IV secretory apparatus) as comB7, comB8, comB9 and comB10 respectively (Figure 1 ). Another ORF in HP26695, HP0017 was found to be homologous to the virB4 gene in Agrobacterium tumifaciens type IV secretory apparatus and was named as comB4 [ 50 ]. From this study it also appeared that each of the gene products of ORFs comB8 to comB10 were absolutely essential for the development of natural transformation competence. It appears that the comB transformation apparatus has evolved conservatively and is typically present in all the strains. This conservation is interestingly in agreement with the need for genomic fluidity in H. pylori where deletions and rearrangements due to natural transformation and transposition are the norm. This is therefore necessary for the pathogen to keep the gene content flexible and as diverse as possible to probably acclimatise itself to diverse host niches during the process of infection. Both these systems, the cag -PAI encoded type IV export system and the transformation-associated type IV system seem to act completely independently, since the deletion of one system from the chromosome does apparently not affect the function of the other system. Figure 1 Different outcomes of H. pylori infection. Some studies argue that eradication of H. pylori might trigger some of the worst forms of heart burns and increased acidity, leading ultimately to oesophageal cancer and or GERD. Pathogenic apparatuses The cag pathogenicity island Molecular analysis of bacterial transport has been attempted in several bacterial pathogens. Among such transport systems, Type IV secretion systems have been described in greater detail in diverse bacteria. In H. pylori , 3 different kinds of type IV secretion apparatuses have been identified. The first such secretion system identified in H. pylori was the one comprised of 29 genes encoding the cag pathogenicity island (cag-PAI). One of the principal virulence factors of H. pylori , the cagA antigen is contained in the 40 kb cag-PAI. The tyrosine-phosphorylated cagA protein is translocated to the epithelial cells by the type IV secretion system (forming a sort of syringe like structure) [ 51 - 53 ]. Upon tyrosine phosphorylation, the cagA protein elicits growth factor like stimuli in epithelial cells (hummingbird phenotype) coupled with interleukin-8 induction for the recruitment of neutrophils. Mutations in several genes of the cag -PAI interfere with tyrosine phosphorylation and induction of interleukin-8 secretion [ 54 ]. In recent studies, in order to analyse which genes of the cag -PAI are essential for cagA translocation and/or interleukin 8 induction, a complete mutagenesis of the cag -PAI was performed [ 55 ]. In general, it appears that most of the cag genes are involved in assembly and arrangement of the secretory apparatus. Five of these genes namely HP0524 (virD4), HP0525 (virB11), HP0527 (virB10), HP0528 (virB9) and HP0544 (virB4/cagE) constitute the main apparatus of the type IV secretory system of H. pylori [ 56 ]. All these genes except HP0524 are associated with IL8 production [ 55 ]. However, the presence of strains eliciting IL 8 responses irrespective of intactness of the cag-PAI underlines the fact that it's 'not' the only factor linked to IL8 secretion [ 57 ]. Very recently, and for the first time, ultrastructure analysis of the surface of H. pylori 26695 has revealed a sheathed, surface organelle, coded by the cag-PAI genes, HP0527 (forms sheath around the pilus needle) and HP0532/ cagT (forms the base of the pilus) [ 58 ]. This structure, although uncommon, could be the special adaptation of H. pylori to the host niches and this might mediate biological as well as transport functions of the cag-PAI encoded proteins. Computational analyses to predict the macromolecular assemblies of such apparatuses are needed to have a more simplified understanding of the entire model of the H. pylori type IV secretion mechanism Link with cancer: the oncogenic cagA protein A large-scale prospective study revealed that the risk for development of gastric carcinoma was much greater in the H. pylori -infected population than in the H. pylori -uninfected population [ 59 ]. The cagA gene of H. pylori is assumed as partially responsible for eliciting signaling mechanisms that lead to the development of gastric adenocarcinoma. Based on the carriage of a functional cagA as a marker for the cag PAI, the H. pylori species is divided into cagA -positive and cagA -negative strains. The cagA -positive strains are associated with higher grades of gastric or duodenal ulceration and are more virulent than the cagA -negative strains [ 60 ]. Some epidemiological studies have demonstrated roles of cagA positive H. pylori in the development of atrophic gastritis, peptic-ulcer disease and gastric carcinoma [ 61 , 62 ]. The cagA gene product, cagA, is translocated to the gastric epithelial cells to undergo tyrosine phosphorylation by SRC family kinases [ 63 ]. Tyrosine phosphorylation is known to occur at the EPIYA motifs on the cagA. The cagA protein upon phosphorylation binds and activates a SHP2 phosphatase that acts as a human oncoprotein. As SHP2 transmits positive signals for cell growth and motility, deregulation of SHP2 by cagA is an important mechanism by which cagA -positive H. pylori promotes gastric carcinogenesis. Cag A is noted for its variation at the SHP2 binding site and, based on the sequence variation, it is sub- classified into two main types – East-Asian cagA and Western cagA. East-Asian cagA shows stronger SHP2 binding and greater biological activity than Western cagA. In East-Asian countries, endemic circulation of H. pylori strains that carry biologically active forms of cagA might underlie the high incidence of gastric carcinoma. One puzzling attribute of H. pylori infection is why some populations with high incidences of H. pylori infection, such as those in Japan and Korea, have high incidences of gastric carcinoma, whereas other highly infected populations, such as populations in central Africa, do not. Possible reasons could be the differences in genetic susceptibility among populations, environmental factors such as dietary habits, and strain differences of H. pylori . Among these, diversity of cagA in H. pylori strains might be involved in determination of the type and severity of disease. As discussed above, East-Asian and Western forms of cagA possess the distinctly structured tyrosine phosphorylation/ SHP2-binding sites – EPIYA-D and EPIYA-C, respectively [ 64 ]. Notably, the grades of inflammation, activity of gastritis, and atrophy are significantly higher in patients with gastritis who were infected with the East-Asian cagA-positive strain than in patients infected with the cagA-negative or Western cagA-positive strain [ 65 ]. Furthermore, the prevalence of the East-Asian cagA -positive strain is associated with the mortality rate of gastric cancer in Asia. Therefore, populations infected with East-Asian cagA positive H. pylori are at greater risk for gastric cancer than those infected with Western cagA -positive strains. Among Western CagA species, the number of EPIYA-C sites directly correlates with levels of tyrosine phosphorylation, SHP2-binding activity and morphological transformation [ 64 ]. Furthermore, molecular epidemiological studies have shown that the number of EPIYA-C sites is associated with the severity of atrophic gastritis and gastric carcinoma in patients infected with Western CagA-positive strains of H. pylori [ 66 ]. The number-2 virulence determinant: vacuolating cytotoxin ( Vac A) of H. pylori H. pylori has a single copy of the vacA gene. Screening of H. pylori chromosomal fragments permitted the identification of a 3864-base pair open reading frame ( vacA ) that encoded the vacuolating cytotoxin [ 67 ]. The sequence of the vacA gene includes a 33 amino acid signal sequence. With the exception of a hydrophobic region at the N terminus, the mature 90-kDa protein (amino acids 34 to 842) is mainly hydrophilic [ 67 ]. The cytotoxic activity of VacA has been shown to increase substantially under acidic conditions. VacA protein, a secreted 95 kD peptide, varies in the signal sequence (alleles s1a, s1b, s1c, s2) and/or its middle region (alleles m1, m2) between different H. pylori strains. The different combinations of s and m regions determine the production of cytotoxic activity. Strains with the genotype s1 m1 produce high levels of vacuolating cytotoxin in vitro. Strains with the genotype s2 produce an inactive toxin. Whereas, strains with the genotype m2 produce toxic activity with a different target cell specificity from those of m1 genotype. Genotypic variations in the vacA gene structure specific to a geographic locale have been recognised. While the vacA m1a allele is specific for the European strains [ 16 ], the vacA m1b genotype is typical of the Asian strains [ 68 ]. Yet another signal region genotype, s1c is also characteristic of the East Asians [ 69 ]. Among other functions, VacA selectively inhibits the invariant chain (Ii)-dependent pathway of antigen presentation mediated by the MHC class II and might induce apoptosis in epithelial cells. VacA, so far mainly regarded as a cytotoxin of the gastric epithelial cell layer, now turns out to be a potent immunomodulatory toxin, targeting the adapted immune system. Thus, in addition to the well-known vacuolating activity, VacA has been reported to induce apoptosis in epithelial cells, to affect B lymphocyte antigen presentation, to inhibit the activation and proliferation of T lymphocytes, and to modulate the T cell-mediated cytokine response. The plasticity region cluster The fascinating genomic landmark discovered post genomic era in both the sequenced strains is the one where 48% and 46% of the strain specific genes are located in J99 and 26695 respectively. This region is called as the 'plasticity zone' [ 28 ]. Genome sequence comparisons have revealed that nearly half of the strain specific genes fall in this zone. Recently, a new type IV secretion apparatus has been located in this plasticity zone [ 70 ]. This type IV cluster is comprised of 7 genes, homologous to the vir B operon of A. tumifaciens carried in a 16.3 kb genomic fragment called tfs3 (Figure 1 ). This cluster was discovered by Kersulyte et al . as a result of subtractive hybridization and chromosome walking and sequence homology. They also tested conservation of this island in clinical isolates and found that full length and partially disrupted tfs3 occur in 20% and19% of the strains respectively, from Spain, Peru, India and Japan. Although there is no correct role assigned to this cluster, it might be an unusual transposon linked to many deletion events occuring in the plasticity region that contribute to bacterial fitness in diverse host populations via exercising flexibility in gene content and gene order. The plastic nature of H. pylori and the evidence of horizontal transfer of genes from other H. pylori isolates and bacterial species could explain the ability of this organism to persist in a changing environment and why only a subset of clinical isolates exert an adverse effect on patients. Link with cancer: are plasticity region genes involved? The plasticity region as a whole displays certain characteristics of pathogenicity islands [ 71 ] with relatively low G+C content (35%) compared to the rest of the genome (39%). This region is about 45 kb long in J99 and 68 kb long in strain 26695. Genomic analysis revealed the region to be highly mosaic with a majority of the genes being transcribed suggesting their functional role. They also express protein level homology to various other recombinases, integrases and topoisomerases [ 72 ] accounting to natural transformation and recombination. In addition to these, many ORFs were identified as differentially expressed (JHP0927-JHP0928-JHP0931 and JHP-042-JHP0944-JHP0945-JHP0947-JHP0960). They share same chromosomal orientation and therefore they potentially represent a bacterial operon. It is interesting to study the expression or suppression of these ORFs in strains linked to different clinical conditions. Recent studies have posed a possibility to explore the presence of any new pathogenicity markers in the plasticity zone, although the functions of most of the putatively encoded proteins in this cluster are unknown. But they are thought to play a role in increasing the virulence capacity of H. pylori strains either directly or by encoding factors that could lead to variance in the clinical out come of the infection. More interestingly, it is also noted that some of the genes of the plasticity regions were co-inherited along with cagA . However their co-association with the disease status or with the severity of gastric inflammation was not established either due to small sample size or lack of clinical information [ 73 ]. Interestingly, a novel pathogenicity marker, JHP947 has been detected within the plasticity zone [ 74 ]. Many genes putatively linked to the development of gastric cancer have been assigned to the plasticity zone [ 72 ]. Researchers have looked for genetic markers in H pylori strains isolated from patients with gastric extranodal marginal zone B cell lymphoma (MZBL) of the mucosa-associated lymphoid tissue (MALT)-type and strains from age matched patients with gastritis only [ 75 ]. Two ORFs were significantly linked with gastric MZBL over gastritis strains: JHP950 (74% v 49%) and JHP1462 (26% v 3%). JHP950 proved specific for gastric MZBL when tested against a group of strains from patients with duodenal ulcer and patients with adenocarcinoma, with significant prevalence (49% and 39%, respectively), and is therefore the candidate marker for gastric MZBL. Interestingly, the candidate ORF JHP950 is located in the plasticity region of the J99 genome [ 75 , 76 ]. In view of such findings it can be speculated that some members of the plasticity region cluster provide selective advantage to some of the strains to adapt to changing host niches and become more and more invasive. In what way such advantage is gained? This needs to be discovered. Do we need to eradicate H. pylori from this earth? How long humans carried H. pylori is still controversial. However, it is accepted that this organism has colonized humans possibly for many thousands of years, and the successful persistence of H. pylori in human stomach for such a long period may be because this organism offers some advantages to the host. Unfortunately, the H. pylori infection is on steep decline in the western world. This is mainly due to the success rate of combination therapies and subsequent prevention of re-infection due to improvement in sanitation and personal hygiene. This may seem good news to many gastro-enterologists around the world, but having a H. pylori infection may be advantageous. A study has shown that H. pylori produces a cecropin-like peptide (antibacterial peptide) with high antimicrobial properties [ 77 ]. A German study revealed that children infected with H. pylori were less likely to have diarrhoea than children without an infection [ 78 ], implying that H. pylori may have beneficial properties to human hosts. Interestingly, there has been a marked decline in the instances of peptic ulcer disease and gastric cancer in the 20 th century. Concurrent with this is a dramatic increase in the incidences of gastro-oesophageal reflux disease (GERD), Barrett's oesophagus and adenocarcinoma of the oesophagus in Western countries [ 79 ]. This observation led to the speculation that H. pylori may in some way be associated with these diseases and perhaps capable of preventing their onset. Studies have also shown that cagA + H. pylori strains have a more protective effect than cagA - strains [ 80 ]. The presence of cagA + H. pylori strains can reduce the acidity of the stomach, and it is believed that the raising of the pH by H. pylori prevents GERD, Barrett's oesophagus and adenocarcinoma of the oesophagus (Figure). Conversely, arguments have been made that, although H. pylori may prevent these reflux-associated diseases, the risks of acquiring gastric cancer via H. pylori infection far outweigh any possible benefits it may provide [ 81 ]. However, it has been stated that, if H. pylori does provide protection from GERD, the notion of restriction of anti- H. pylori treatment to only a few cases (peptic ulcer disease and MALT lymphoma) could be justified [ 82 ]. In spite of this controversy, recent reports have demonstrated a protective role for H. pylori in erosive reflux oesophagitis [ 83 - 85 ]. However, as safe and potent anitsecretory drugs to prevent gastro-oesophageal reflux are available [ 86 ] it seems unjustified to use a dangerous organism that has been associated with extremely dangerous outcomes such as a carcinoma. On the other hand, eradication also is not an ultimate choice. Some ulcers recur even after successful eradication of H. pylori in non-users of non-steroidal anti-inflammatory drug (NSAID). In addition, the incidence of H. pylori -negative, non-NSAID peptic ulcer disease (PUD) (idiopathic PUD) is reported to increase with time. Moreover, it appears that H. pylori -positive ulcers are not always H. pylori -induced ulcers because there are two paradoxes of the H. pylori myth, first the existence of H. pylori -positive non-recurring ulcer and secondly, recurring ulcer after cure of H. pylori infection. To summarise, H. pylori is not the only cause of peptic ulcer disease. Therefore, it is still necessary to seriously consider the need for eradication in all cases of PUD, which may exist even after the elimination of H. pylori . Conclusion and expert opinion In our opinion, the intricacies of the role of H. pylori in health and disease may be fully ascertained only if we analyze genetic diversity of the pathogen as juxtaposed to the host diversity and the environment (food and dietary habits). A possible working hypothesis (that we are currently nurturing) may be that among the ocean of molecular host-pathogen interactions that could potentially occur with micro-evolution of this bacterium during long term colonization, some could prove advantageous where the bacterium and the host negotiate nearly a 'symbiotic' and balanced relationship. Such a 'friendship' might have taken thousands of years to develop. If so, why has this bacterium survived for such a long time? Microbes that have long been persisted in humans may be less harmful than recently emerged microbes, such as the human immunodeficiency viruses (HIV). This suggests that the colonization may either be beneficial or of low biological cost to the host. In addition to characterization of bacterial virulence apparatuses that are for sure linked to disease outcome, host responses to such factors must also be examined hand in hand, to completely ascertain mechanisms that lead to gastroduodenal disease. For instance polymorphisms linked to the host immune apparatus, such as IL-1β , TNF-α , and IL-10 , which are responsible for elevated proinflammatory potential of the strains. These polymorphisms increase the risk for atrophic gastritis and distal gastric adenocarcinoma among H. pylori -infected persons. Cancer of stomach is a highly lethal disease and establishment of H. pylori as a risk factor for this malignancy deserves an approach to identify persons at increased risk; however, infection with this organism is extremely common and most colonized persons never develop cancer. Thus, screens to identify high-risk subpopulations must use high-resolution biological markers. Fortunately, this task appears to be highly simplified due to the availability of biological tools, which were never thought in the past. Genome sequences ( H. pylori , human, C. elegans ), quantitative phenotypes (cagA phosphorylation, oip A frame status, vac Aallele status), and practical animal models (Mongolian gerbils) can be harnessed to decipher the molecular basis of H. pylori -associated malignancies, which should have direct clinical applications. It is important to gain more insight into the pathogenesis of H. pylori -induced gastric adenocarcinoma, not only to develop more effective diagnostics and treatment for this common cancer, but also to validate the role of chronic inflammation in the genesis of other tumours of the alimentary tract.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544872.xml
545946	Systems validation: application to statistical programs	Background In 2003, the United States Food and Drug Administration (FDA) released a guidance document on the scope of "Part 11" enforcement. In this guidance document, the FDA indicates an expectation of a risk-based approach to determining which systems should undergo validation. Since statistical programs manage and manipulate raw data, their implementation should be critically reviewed to determine whether or not they should undergo validation. However, the concepts of validation are not often discussed in biostatistics curriculum. Discussion This paper summarizes a "Plan, Do, Say" approach to validation that can be incorporated into statistical training so that biostatisticians can understand and implement validation principles in their research. Summary Validation is a process that requires dedicated attention. The process of validation can be easily understood in the context of the scientific method.	Background The United States Food and Drug Administration (FDA) has defined validation as "confirmation by examination and provision of objective evidence that computer system specifications conform to user needs and intended uses, and that all requirements can be consistently fulfilled" [ 1 ]. Validation is a process that begins with defining the requirements and ends with ensuring that the needs are being fulfilled consistently. Structured testing is only a part of the validation process. Interaction with researchers emphasized the notion that many people use validation and testing synonymously. To better illustrate the concepts of validation to these same researchers, the following mantra was developed: Plan what you are going to do, Do what you planned, And Say what you did. As an introduction to the application of this mantra, consider the following. Clinical trial operations are detailed in numerous manuals and procedural documents with the protocol being the most notable. A clinical trial protocol serves as the master research plan. Great efforts will be employed, both by researchers and by external advisory boards, to ensure that the protocol is sound and is designed to support the clinical hypothesis. Conducting the protocol at clinical sites allows for the execution of the research methodology in a reproducible and orchestrated manner, and in the end, the final report or manuscript summarizes the work performed. If any one of these components is missing from the research plan, the scientific integrity of the research would be questioned or directly refuted. Associating systems validation to this well developed paradigm is at the heart of the "Plan, Do, Say" approach to validation. There are many good references available that detail the process of validation. Stokes' two books are excellent resources for investigators new to validation [ 2 , 3 ]. The FDA provides additional guidance to industry by publishing guidance documents that aid in the interpretation of federal regulations. National organizations such as the Drug Information Association routinely host short sessions addressing validation. Still, for many practicing biostatisticians or other researchers, the concepts of validation may not be clearly understood. Therefore, the intent of this manuscript is to offer guidance on what is a validated computerized system to these individuals and provide a common framework that will enable effective communication. When revisiting the FDA definition of validation in the context of the scientific method, it becomes clear that "confirmation by examination and provision of objective evidence that the computer system specifications conform to user needs and intended uses, and that all requirements can be consistently fulfilled" is essentially applying the scientific method to the life cycle of computerized systems. The definition implies that a validated system is one in which processes are specific and clearly defined, reproducible and consistently applied, and result in a measurable and observable level of quality in the delivered product. Validation of applicable systems is viewed as the best way to ensure that research objectives can be consistently met. All clinical trials need to collect and deliver results in an efficient and accurate manner while ensuring the integrity of the data. The CONSORT Statement provides guidance to researchers on the format and content of clinical trial reporting [ 4 ]. Computerized systems validation is integral to the fulfillment of the CONSORT Statement since a validation process for statistical programs will make the analysis understandable and reproducible by external reviewers. It is the responsibility of the computer system owner to ensure that the system is properly validated. For statistical reporting of biomedical data, the computer system owner is the senior trial biostatistician in consultation with sponsor and principal investigators. In addition, validation should be considered as a part of the complete life cycle of a computerized system [ 2 ]. This life cycle includes the stages of planning, specifying, programming or purchasing, testing, documenting, operating, monitoring and modifying as necessary. The primary focus of regulatory inspection for computerized system validation is to obtain documented evidence to assure that any system is currently operating properly. Discussion Just as the "Plan, Do, Say" mantra illustrates, there are three main validation deliverables [ 5 ]. First, a validation plan must be developed. The validation plan should include the general scope of the system including high-level design features, the personnel responsible for the validation, a timeline, and a summary of other supporting documentation that need to be addressed in order to use the system. The whole deliverable must be approved by management prior to its deployment [ 5 ]. Second, there should be documentation that the system has been designed as envisioned in the validation plan [ 5 ]. There should be at a minimum complete system specifications / requirements, a traceability matrix and test scripts included in this set of documentation. A test script should be written to ensure that the system requirements function as desired by measuring whether the system produces the expected result, and a traceability matrix cross references the system requirements to individual test script items. Finally, a report should be included with the validation deliverables. The whole deliverable must be approved by management and indicate that the system functions as required [ 5 ]. A report also is a place to discuss how deviations to the plan were addressed. The scope and magnitude of the delieverable will vary from computerized system to computerized system, and it is the responsibility of the management team to decide upon the level. The following section provides an outline to serve as an aid to assembling the validation deliverables for statistical programs. Statistical program checklist 1. Planning activities (a) Develop a validation plan State how the validation process will be conducted, including personnel roles, test parameters, and decision points on what constitutes acceptable test results. Management prior to the development of the detailed specifications should approve the validation plan. The plan may be amended with time. (b) Utilize standard operating procedures (SOPs) SOPs should be available to formalize the procedures used in the validation process as well as establish statistical programming standards. Incorporation of standards will aid in producing reproducible deliverables. The following is a partial list of applicable SOPs: i. Validation of statistical programs ii. Statistical programming standards iii. Statistical program archival: Outlines the necessary steps to archive the analysis program, data sets, and, if necessary, computer hardware so that the results may be reconfirmed at a future date. (c) Document training on SOPs Written SOPs are not useful unless they are incorporated into practice. In order to do this, applicable individuals need to be orientated to the procedures. This orientation session should be documented for regulatory inspection. (d) Develop detailed specifications i. Data management plan A. Annotated database structure B. List of coding conventions for data C. List of procedures used to process the data D. Merging criteria (database keys) E. System environment: analysis package (with version), system hardware, input data structure, output data structure, long-term storage environment ii. Analysis objectives The analysis objectives may vary according to the application; however, for the primary clinical trial report, the protocol or a statistical analysis plan may be sufficient to detail the requirements of the analysis. (e) Develop a test plan and/or test script i. Mock tables ii. Expected results of tests iii. Programming standards iv. Testing procedures 2. Execution of the plan (a) Retain raw test results Record individual pass/fail for each step outlined in the test script. A pass occurs when the observed result matches the expected result. (b) Note variances and deviations to the test plan (c) Document location, time and individuals involved in the testing process 3. Summary report (a) Summarize validation process (b) Summarize the variances and deviations (c) Summarize test results and provide interpretation when necessary (d) Approve by management Application to statistical programs The definition of a computerized system encompasses both the hardware and software. For analytical applications, the key components of the system also will include the individual programs written to perform the analysis. The use of validated macros aides in reducing the burden introduced by the validation process for an individual system. For example, suppose for the clinical reporting of a trial's results, a table is desired that reports the mean and standard deviation or count and percentage for all putative covariates. A SAS macro [ 6 ] could be written to compile and export the data from SAS to a word-processing compatible format. This macro would be a candidate for validation since it manipulates raw data, performs calculations, and modifies output from standard SAS output. However, once this macro has been developed, a significant savings in the time required to produce (and verify) publication-ready tables could be possible. The remainder of the discussion highlights some of the key steps in validating this macro. The validation of the macro begins in the planning stage. For the macro to "conform to user needs", the needs need to be clearly identified. The following may describe its user requirements: 1. Export a word-processing compatible table consisting of three columns; 2. The table columns must be appropriately labeled; 3. Column 1 must be the labeled "Characteristic"; 4. Column 2 must be the labeled "Control Group"; 5. Column 3 must be the labeled "Intervention Group"; 6. For categorical covariates, calculate the count and percentage for each level of the variable; 7. For levels of a categorical variable, the table should indent the formatted description; and 8. For interval-scaled continuous covariates, calculate the mean and standard deviation. This set of requirements would then be discussed from a technical perspective. Issues such has how to best calculate the summary statistics could be a topic of discussion. The use of PROC TABULATE and the Output Delivery System (ODS) [ 6 ] could be a likely candidate for the summary. Next, discussion pertaining to the specification of covariates and the concatenation of the results is needed. In the process, potential macro parameters would need to be identified. All key decisions are incorporated into the validation plan. This plan is reviewed by the computer system owner and the validation system sponsor. Once this plan has been approved, a revision log should be kept to ensure traceability of changes that may occur during development. Once the macro has been developed, the validation system sponsor should work either independently or in conjunction with appropriate staff to review the programming and develop test cases. The test cases are assembled into a test that specifies the system input and expected output. To ensure all user requirements are addressed, a traceability matrix can be utilized. A simple traceability matrix for this validation exercise would list each of the requirements and cross reference the applicable test. The test script is then implemented under the direction of the validation system sponsor. Documentation of the event should be recorded so that it can be compiled into the validation report. Any discrepancies between the observed and expected results need to be addressed, and, if applicable, documentation on the corrective actions employed to resolve the issue(s) needs to be compiled into the validation deliverables. A revision log of programming changes is desirable; however, in practice, this may prove difficult to document completely. Once the testing has been completed, the computer system owner and validation system sponsor can determine what additional steps are required prior to release. For SAS macros, it is critical to document the parameters, default values of the parameters and system dependencies, then, perhaps include illustrative examples of the macro's use. Finally, a written statement by the computer system owner and the validation system sponsor should be issued stating that the macro has been validated and has been deemed acceptable for use. The above example illustrates a full-scale implementation of a validation process. However, it is acknowledged that individuals and organizations must decide the level of validation that is required. In many cases, more traditional approaches of program verification (code review, double programming, etc.) may be sufficient. The importance of the "Plan, Do, Say" mantra is that procedures used for validation are specified and operated on. Summary The "Plan, Do, Say" approach presented addresses the key deliverables an auditor expects to see in validated systems. By organizing validation activities into a plan, an action or a summary, one begins to gain efficiencies through proper planning. However, individual researchers and support organizations need to evaluate their particular needs for validation and develop a set of procedures to support their needs. The intent of this article is not to provide an ironclad approach to validation that will ultimately meet all needs. However, this design for validation has been conveyed successfully to a variety of audiences. The analogy of the scientific method helps break the technology and nomenclature barrier associated with a more computer science-driven approach to systems validation by associating the importance of validation to the process of designing a research plan. Competing interests The author(s) declare that they have no competing interests. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545946.xml
555572	Reliability and validity of the AGREE instrument used by physical therapists in assessment of clinical practice guidelines	Background The AGREE instrument has been validated for evaluating Clinical Practice Guidelines (CPG) pertaining to medical care. This study evaluated the reliability and validity of physical therapists using the AGREE to assess quality of CPGs relevant to physical therapy practice. Methods A total of 69 physical therapists participated and were classified as generalists, specialist or researchers. Pairs of appraisers within each category evaluated independently, a set of 6 CPG selected at random from a pool of 55 CPGs. Results Reliability between pairs of appraisers indicated low to high reliability depending on the domain and number of appraisers (0.17–0.81 for single appraiser; 0.30–0.96 when score averaged across a pair of appraisers). The highest reliability was achieved for Rigour of Development, which exceeded ICC> 0.79, if scores from pairs of appraisers were pooled. Adding more than 3 appraisers did not consistently improve reliability. Appraiser type did not determine reliability scores. End-users, including study participants and a separate sample of 102 physical therapy students, found the AGREE useful to guide critical appraisal. The construct validity of the AGREE was supported in that expected differences on Rigour of Development domains were observed between expert panels versus those with no/uncertain expertise (differences of 10–21% p = 0.09–0.001). Factor analysis with varimax rotation, produced a 4-factor solution that was similar, although not in exact agreement with the AGREE Domains. Validity was also supported by the correlation observed (Kendall-tao = 0.69) between Overall Assessment and the Rigour of Development domain. Conclusion These findings suggest that the AGREE instrument is reliable and valid when used by physiotherapists to assess the quality of CPG pertaining to physical therapy health services.	Background Clinical practice guidelines (CPGs) are one option for promotion of quality in health services [ 1 - 6 ] Many countries are faced with common challenges in delivering high-quality health care with available resources and have pursued the development of CPGs as a means to optimize effective and efficient care. As a result there is a need to evaluate CPGs guidelines to assess their quality and their impact on practice. The Appraisal of Guidelines for Research and Evaluation (AGREE) instrument was developed by a group of researchers from 13 countries to provide a systematic framework for assessing guideline quality[ 7 , 8 ] This instrument was thoroughly evaluated and refined and is now a commonly used assessment instrument for CPGs[ 2 , 3 , 9 - 13 ] A large-scale validation study focussing primarily on medical (i.e. physician) guidelines, was conducted supporting the reliability and validity of this instrument[ 14 ]. The AGREE Collaboration published the development process and associated reliability and validity data in 2003[ 14 ] This report outlined the rigorous process undertaken to develop the AGREE instrument which included item generation, selection and scaling followed by field-testing and refinement. This process resulted in the final instrument with 23 items distributed across six subscales termed "domains", for which reliability and validity data were presented. Reliability was determined by calculating the internal consistency of each domain within the final instrument and assessing the agreement between different appraisers. A total of 33 guidelines were evaluated by the four appraisers. Internal consistency ranged from 0.64–0.88. 'Scope of Purpose' and 'Rigour of Development' were the most homogeneous domains. The inter-rater reliability exhibited a wide range from 0.25–0.91. Reliability was higher with four appraisers and the most reliable domain was 'Rigor of Development'. Higher reliability within the domain of 'Rigor of Development' is a positive finding, as this domain should contain items that are more objective than items contained on other subscales of the AGREE instrument. That is, because the 'Rigor of Development' questions relate to the methodology of developing a CPG and thus there are optimal criteria that would be expected regardless of the content of the CPG. In measurement terms, it is more likely that a "true" score exists for elements within this domain. Therefore, variability observed on repeated assessments of the same CPG should reflect measurement error between appraisers. Other scales such as stakeholder involvement and applicability might reasonably have different criteria depending on clinical expertise or application. In measurement terms, no single true score may exist for these items. Therefore, variability observed between appraisers on these domains might reflect a combination of measurement error, as well as true variations in perspective. This concept is important when assessing and interpreting the reliability of evaluation instruments like the AGREE. The AGREE Collaboration also assessed face, construct and criterion validity of the AGREE Instrument. Face validity was determined by surveying appraisers attitudes and opinions about the instrument and its associated user guide. Construct validity was determined by comparing scores of guidelines in different subgroups to determine whether they fit three specific constructs. The constructs tested included whether established quality guideline programs produced guidelines with higher domain scores than those developed outside of established systems; whether guidelines supported by well-documented technical information had higher domain scores than those without such documentation; and finally whether guidelines developed as national policies were higher quality than regional or local CPGs. The first hypothesis was supported with respect to editorial independence, but not other domains. The second and third hypotheses were supported with respect to the domain Rigor of Development, but not other domains. Finally, criterion validity was determined by assessing the rank correlation between appraisers domain scores and their overall assessment scores (final item on the AGREE instrument). These correlations were all highly significant (range Kendall's Tau-b = 0.67 – 0.88). Physical therapy and other health care disciplines shares common challenges in providing effective care within limited resources. While many disciplines currently use the AGREE the validation paper emphasized medical practice and practitioners. The nature of physical therapy practice differs substantively from medical practice in a number of ways including access, funding, the nature of interventions, research systems and professional associations; all of these might affect the type of CPGs, developed. Differences in training between disciplines might also cause variations in how the AGREE was interpreted. Additional validation with other settings or users would strengthen the validation of the AGREE across a variety of applications. CPGs have arisen within the field of physical therapy from a variety of sources[ 15 , 16 ] Professional associations have assisted physical therapy practitioners in becoming aware of the existence of such guidelines through websites and newsletters. Ideally, information on the quality of such guidelines should also be available to assist practitioners in selecting between available guidelines. Currently, this is not the case in physical therapy. While professional associations may help co-ordinate the evaluation of CPGs, they must inevitably must make decisions about this process including which members of the profession are able to evaluate CPGs, how many appraisers should be selected and which instrument should be used. For this reason, our purpose was to determine whether the AGREE instrument is a reliable and valid tool when used by physical therapists to assess CPGs that pertain to physical therapy practice. Our hypothesis was that the AGREE instrument would be a valid tool when used by physical therapists to evaluate CPGs. Our secondary question was whether an ideal number or type of physical therapist appraiser would be evident from reliability data. We hypothesized that 4 appraisers might be best, as the AGREE Collaboration recommends " al least two appraisers and preferably four as this will increase the reliability of the assessment". [ 7 ] Methods This study was a cross-sectional study conducted to evaluate inter-appraiser reliability and validity of quality appraisal of CPGs performed by physical therapists using the AGREE instrument Permission to use the AGREE instrument was obtained from the AGREE Collaboration. Ethics approval for this study was received from the University of Toronto, Office of Research Services. Clinical practice guidelines Clinical practice guidelines (CPGs) are "systematically developed statements to assist practitioner and patient decisions about appropriate healthcare for specific clinical circumstances"[ 17 ]. The CPGs evaluated during this study were identified through an inventory that was created by the study authors from a series of systematic searches that included electronic databases, websites, contact of professional associations and guideline developers. The inventory included all located documents that were identified by authors as Clinical Practice Guidelines. This inventory was completed in 2002 and updated yearly and subsequently posted on the website for the Canadian and Ontario Physiotherapy Associations (members only access). Within this database, guidelines were categorized according to the area of physical therapy practice (e.g., musculoskeletal, neurological, cardiorespiratory). Sixty guidelines published in the last five years were selected from this database for inclusion in the present study. Four of these CPGs were excluded because they were not actually CPGs (e.g. systematic reviews included in error) and one CPG was excluded because it was not relevant to physical therapy. Thus in total, a sample of fifty-five guidelines were evaluated in the present study. Participants/training All participants were physical therapists who were recruited through advertisements in professional newsletters. A total of 72 therapists responded to advertisements and agreed to participate, 69 actually participated in training and study evaluations – two others had personal circumstances that prevented them from attending training and one failed to respond further. The participants were classified according to the following criteria: 1. Clinical Specialists were Physical Therapists who were currently practicing in a specific area, had a minimum of three years experience and had participated in at least one post-graduate course per year in their area of clinical expertise. 2. Generalists were Physical Therapists practicing in a variety of areas of physical therapy or an ongoing general practice, which covered a broad-spectrum of neurological, orthopaedic and cardiorespiratory health problems. 3. Researchers were Physical Therapists with or approaching completion of a graduate research degree (M.Sc. and/or PhD) with experience in conducting clinical trials or outcomes research and experience in formal critical appraisal of clinical research. Demographic data was collected on all participants. Eligible participants were provided with training materials which included the AGREE instrument (form and associated interpretation guidelines)[ 7 , 18 ] as well as a multiple-choice test that required participants to answer questions on the content and structure of the AGREE (see Additional file 1 ). In addition, a sample guideline was provided to participants with instructions to read the guideline (on management of lymphedema following treatment for breast cancer[ 19 ]) and appraise it using the AGREE instrument and associated documentation. Subsequently, all participants met by teleconference for one hour with a subgroup (4–8) of study participants. The sessions (a total of 6 teleconferences conducted) were led by a single facilitator (first author). During this session participants reviewed their responses to each question and discussed their rationale or concerns regarding scoring. The facilitator did not indicate a correct score for any individual item. Participants were instructed that the group facilitator would not indicate whether a given score was correct, as this was not possible for many of the items. Participants were directed to appreciate the difference between items that had clear answers because they inquired about specific factual information versus those that had a subjective element where responses might vary according to context. Participants were corrected if they incorrectly interpreted the meaning of a given item on the AGREE instrument. Although consensus was not the objective of the training sessions, participants tended to come to consensus after discussing items with colleagues and a facilitator. In total, 69 appraisers attended the training sessions. Appraisal instrument The appraisal instrument used to evaluate the CPGs was the AGREE [ 18 ]. This instrument consists of 23 items organized in six domains ; each domain is intended to capture a separate dimension of guideline quality. The following domains are included: 1. Scope And Purpose: 3 items that address the overall aim of the guideline, the clinical question and the target population 2. Stakeholder Involvement: 4 items that address the composition, expertise and representation of the development group 3. Rigor Of Development: 7 items that evaluate the process used to locate and synthesize the evidence and to formulate and update the recommendations, 4. Clarity And Presentation: 4 items that address language and format 5. Applicability: 3 items that address the potential organizational, behavioural and cost implications of implementation and 6. Editorial Independence: 2 items that address potential conflicts of interest. Items are rated on a 4-point scale with endpoints of 4 'strongly agree' and 1 'strongly disagree'; the two midpoints are 3 'agree' and 2 'disagree'. A section for overall assessment is included at the end of the instrument that requires the appraiser to make a judgment about the overall quality of the CPG. Appraisers are asked whether they would 'strongly recommend', 'recommend (with provisos or alterations)', 'would not recommend' or are 'unsure' if they would recommend the CPG for practice. Evaluation process All participants completed the training program and proceeded to evaluate a set of 6 CPGs. These CPGs, six copies of the AGREE instrument, and a pre-paid return were provided by mail. Each guideline was evaluated independently by three pairs of appraisers who were randomly picked from the three pools of Physical Therapists (i.e. two clinical specialists in the area of the CPG, two generalists and two researchers). All appraisers returned their packages, although up to 3 reminders calls were required for late returns. Participants who completed the study were provided with an honorarium ($100). Data analysis Data analysis was conducted to verify the quality of data, assess instrument reliability and determine the validity of the AGREE instrument for physical therapy practice. SPSS statistical software for Windows (Version 11.0; SPSS Inc, Chicago, Illinois) was used for all statistical analyses. P-values of 0.05 or less were considered significant. Data Entry/Quality Data entry was completed by a single research assistant who inspected data for errors once the data file was complete. The first author conducted random checks of data entry against original data sheets. Descriptive statistics were conducted to identify outliers or unusual values. Domain scores of each CPG were calculated as recommended by the AGREE Collaboration. The scores of the individual items in the domain were summed and standardized as a percentage of the maximum possible score for that domain (AGREE Collaboration, 2001). Reliability analyses The internal consistency of each domain was evaluated using Cronbach's Alpha. The reliability between appraisers was determined for each question and each domain of the AGREE. Intraclass correlation coefficients (ICC 1,1) were calculated within each pair of appraisers and across the pool of appraisers. A one-way random effects model was used as pairs of appraisers were randomly selected from our pool of physical therapist appraisers. An unweighted and quadratic weighted kappa were calculated to indicate the agreement within pairs of appraisers on whether a CPG was appropriate for clinical utilization. ICCs or kappa values above 0.75 were considered to represent good, 0.40–0.75 moderate and <0.40 poor reliability[ 20 ] Validity analyses Face validity The face validity of the instrument for physical therapy practice was determined from feedback provided on the instrument from two sources. Participants (experienced physical therapists) in the study were invited to provide feedback at the training sessions (open-ended questions regarding the training session and the AGREE itself -verbal response). They were also asked to add comments about any items, any issues with clarity or concerns directly on their AGREE form when they were using the AGREE on their assigned CPGs. These were returned, by mail, with their ratings. In addition, over the course of two years, a sample of 102 entry-level-masters trainees at McMaster University were provided the training materials (except for multiple-choice questionnaire) and were required to complete an assignment where they evaluated the same CPG[ 19 ] used during the study training session. This assignment consisted of a facilitated group component where students worked in groups of 4–6 to complete the AGREE evaluation for the assigned CPG. The individual component of this assignment required each student to write a 1–2 page essay evaluating the instrument itself in terms of its relevance to clinical practice, validity and their personal preference about whether they would use it again. This information was summarized by the course instructor (first author) and the percentage of students who responded that they would use the instrument again was tabulated. Factor (domain) validity The validity of the domain structure was evaluated using a principal components, varimax rotated factor analysis. Item means across all 6 appraisers were entered into the analysis. Coefficients were evaluated to determine whether they supported the domain structure and followed a similar pattern as to that reported for a previous factor analysis published by the AGREE Collaboration. Construct Validity Construct validity was assessed by evaluating 2 hypotheses. The first hypothesis was selected to match the hypothesis tested by the AGREE Collaboration guidelines[ 14 ] and supported by others[ 21 , 22 ], that CPGs developed by established guideline developers should have higher quality scores than those created outside of established system. All guidelines in the database were classified as having been developed by established guideline developers if it could be identified that an experienced guideline developer or development group was responsible for a specific guideline. A CPG was classified as having "Experienced Guideline Developers" if it 1) had more than 3 authors (also fulfilled by an agency) and 2) at least one team member could be identified an a methodologist experienced in CPG development – either by descriptions contained within the body or the CPG or after a review of listed authors (conducted by JM and DB). If this could not be verified the CPG was classified as " No or Uncertain Methodology Expertise". Our second hypothesis was that physical therapists would be more likely to recommend a guideline that was rated as having higher Rigor of Development scores. An independent t-test was used to evaluate the scores obtained for Rigor of Development for guidelines judged as acceptable versus those that were not. This hypothesis test is not ideal, as we are testing whether this subscale contributes to the overall rating within the same instrument. Nevertheless, in the absence of an external criterion, we choose to use this analysis given that it was also conducted in the original validation paper and there was an advantage to having a comparable analysis. Criterion validity Finally, criterion validity was assessed in the same manner as reported by the AGREE Collaboration in their validation study. Again we recognize we did not have an external criterion. Kendall Tau B Rank correlation coefficients were calculated between the appraisers domain scores and the overall assessment score. Results Participants Sixty-nine physical therapists were recruited and were categorized as clinical specialists (n = 29), generalists (n = 21) or researchers (n = 19) (Table 1 ). Generalists and specialists reported similar years of clinical experience with generalists ranging from 3–33 (mean ± SD,16 ± 11) years and specialists 3–35 (15 ± 8) years. Researchers reported 3–21 (7 ± 6) years of research experience. Table 1 Demographic description of physical therapy evaluators Group Age Mean (SD) Gender % Highest Degree % Female Male Diploma Bachelors Masters Doctorate Overall (n = 69) 40 (8) 96 4 9 58 32 1 Generalists (n = 21) 39 (9) 86 14 19 71 10 0 Specialists (n = 29) 39 (7) 100 0 7 79 14 0 Researchers (n = 19) 41 (9) 100 0 0 11* 84 5 * these two participants had significant research experience and were close to completion of Masters degree The majority of specialists were orthopaedic physical therapists (55%), followed by neurological (24%) and cardiorespiratory (10%). One participant reported to specialize in paediatric physical therapy. Two participants did not specify their area of specialization. Reliability Analysis of reliability of individual items indicates a trend for higher reliability in items within the domain from Rigor of Development (See Table 2 ). Intraclass correlation coefficients (ICCs) for each domain of the AGREE instrument for pairs of appraisers are presented in Table 3 . No systematic differences were observed that would indicate that type of appraisers had any substantial impact on the reliability obtained. Variation in reliability was observed across domains with Rigor of Development demonstrating the highest level of reliability. Few ICCs reached the excellent benchmark of 0.75, if a single appraiser performed the evaluation. ICC models that estimate the reliability when appraisers were averaged using models (1,2) for pairs or (1,6) across all six appraisers indicated substantial improvement in reliability if appraisals were averaged across appraisers. When comparing the reliability across different numbers of appraisers (Table 4 ) the improvement in reliability was most notable when going from two to three appraisers, with the exception of editorial independence). Additional benefit for adding additional appraisers was inconsistent. Agreement on the overall assessment of the CPG had low reliability for generalists and specialists and moderate reliability for researchers. Quadratic weighting demonstrated some improvement in reliability coefficients for generalists and researchers, but not for specialists. (Table 5 ) Table 2 Inter-rater reliability of AGREE instrument – individual items Generalists Clinical Specialists Researchers Overall Single Rater ICC Average of Raters ICC Single Rater ICC Average of Raters ICC Single Rater ICC Average of Raters ICC Single Rater ICC Average of Raters ICC Item 1 0.34 0.51 0.50 0.66 0.58 0.73 0.46 0.84 Item 2 0.28 0.44 0.03 0.05 -0.09 -0.19 0.25 0.67 Item 3 0.45 0.62 0.23 0.37 0.19 0.31 0.22 0.63 Item 4 0.58 0.74 0.65 0.79 0.75 0.86 0.67 0.92 Item 5 0.57 0.73 0.37 0.54 0.55 0.71 0.45 0.83 Item 6 0.43 0.60 0.62 0.76 0.69 0.82 0.55 0.88 Item 7 0.48 0.65 0.18 0.30 0.36 0.53 0.36 0.77 Item 8 0.88 0.93 0.77 0.87 0.78 0.88 0.83 0.97 Item 9 0.72 0.84 0.84 0.91 0.69 0.82 0.72 0.94 Item 10 0.61 0.76 0.54 0.70 0.66 0.80 0.62 0.91 Item 11 0.45 0.63 0.13 0.23 0.32 0.49 0.39 0.79 Item 12 0.61 0.75 0.46 0.63 0.55 0.71 0.63 0.91 Item 13 0.74 0.85 0.66 0.79 0.56 0.72 0.64 0.92 Item 14 0.57 0.73 0.61 0.76 0.70 0.82 0.65 0.92 Item 15 0.31 0.47 0.30 0.46 0.25 0.40 0.38 0.79 Item 16 0.39 0.56 0.49 0.66 0.46 0.63 0.43 0.82 Item 17 0.31 0.48 0.31 0.48 0.41 0.58 0.35 0.76 Item 18 0.32 0.48 0.60 0.75 0.42 0.59 0.52 0.87 Item 19 0.53 0.69 0.50 0.67 0.45 0.62 0.43 0.82 Item 20 0.48 0.65 0.40 0.57 0.49 0.66 0.43 0.82 Item 21 0.34 0.51 0.37 0.54 0.20 0.34 0.28 0.70 Item 22 0.53 0.69 0.15 0.27 0.42 0.60 0.26 0.68 Item 23 0.58 0.73 0.53 0.69 0.72 0.84 0.40 0.80 ICC – Intraclass correlation coefficient Results statistically significant at the p < 0.05 level except where indicated by bold. Table 3 Inter-rater reliability of AGREE instrument domain scores Scope & Purpose Stakeholder Involvement Rigor of Development Clarity & Presentation Applicability Editorial Independence Single Rater ICC (95% CI) Average of Raters ICC- all 6 raters or 3 pairs of 2 raters? (95% CI) Single Rater ICC (95% CI) Average of Raters ICC (95% CI) Single Rater ICC (95% CI) Average of Raters ICC (95% CI) Single Rater ICC (95% CI) Average of Raters ICC (95% CI) Single Rater ICC (95% CI) Average of Raters ICC (95% CI) Single Rater ICC (95% CI) Average of Raters ICC (95% CI) Generalists 0.37 (0.11–0.59) 0.54 (0.19–0.74) 0.71 (0.54–0.83) 0.83 (0.70–0.90) 0.81 (0.68–0.89) 0.89 (0.81–0.94) 0.41 (0.15–0.62) 0.58 (0.26–0.76) 0.65 (0.46–0.79) 0.79 (0.63–0.88) 0.60 (0.39–0.75) 0.75 (0.56–0.86) Clinical Specialists 0.35 (0.10–0.56) 0.52 (0.18–0.72) 0.59 (0.39–0.74) 0.74 (0.56–0.85) 0.65 (0.47–0.78) 0.79 (0.64–0.88) 0.51 (0.29–0.69) 0.68 (0.45–0.81) 0.43 (0.19–0.63) 0.61 (0.32–0.77) 0.32 (0.06–0.54) 0.49 (0.11–0.70) Researchers 0.17 (0.14–0.46) 0.30 (-0.32–0.63) 0.73 (0.54–0.85) 0.84 (0.70–0.92) 0.77 (0.61–0.87) 0.87 (0.76–0.93) 0.47 (0.18–0.69) 0.64 (0.31–0.81) 0.47 (0.19–0.68) 0.64 (0.32–0.81) 0.59 (0.34–0.77) 0.75 (0.51–0.87) Overall 0.40 (0.25–0.58) 0.80 (0.66–0.89) 0.67 (0.54–0.80) 0.93 (0.87–0.96) 0.79 (0.68–0.88) 0.96 (0.93–0.98) 0.55 (0.40–0.72) 0.88 (0.80–0.94) 0.50 (0.35–0.68) 0.86 (0.76–0.93) 0.35 (0.19–0.54) 0.76 (0.59–0.88) CI – confidence interval; ICC – intraclass correlation coefficient Results statistically significant at the p < 0.5 level except where indicated by bold. Table 4 Intraclass correlations for each AGREE instrument domain as a function of the number of raters Scope & Purpose Stakeholder Involvement Rigor of Development Clarity & Presentation Applicability Editorial Independence Single Rater ICC Average of Raters ICC Single Rater ICC Average of Raters ICC Single Rater ICC Average of Raters ICC Single Rater ICC Average of Raters ICC Single Rater ICC Average of Raters ICC Single Rater ICC Average of Raters ICC 2 Raters 0.37 0.54 0.71 0.83 0.81 0.89 0.41 0.58 0.65 0.79 0.60 0.75 3 Raters 0.38 0.64 0.71 0.88 0.82 0.93 0.54 0.78 0.66 0.85 0.38 0.65 4 Raters 0.41 0.73 0.64 0.88 0.77 0.93 0.51 0.80 0.54 0.82 0.35 0.69 5 Raters 0.42 0.78 0.69 0.92 0.79 0.95 0.51 0.84 0.57 0.87 0.38 0.76 6 Raters 0.40 0.80 0.67 0.93 0.79 0.96 0.55 0.88 0.51 0.86 0.35 0.76 ICC = Intraclass correlation coefficient Table 5 Agreement on whether a CPG would be recommended or not Pair of Raters Kappa (unweighted) Kappa (quadratic weights) Generalists 0.20 0.34 Specialists 0.25 0.22 Researchers 0.39 0.47 A Kappa was calculated on the final overall rating question whether or not a CPG should be using with the data dichotomized as YES (strongly recommend or recommend with provisos) or NO (Would not recommend or unsure) or by using quadratic weighting to compare the strength of recommendation (Strongly, with provisos, would not, unsure). Validity Face Validity/ User Feedback Study participants provided feedback during training sessions primarily with respect to the training session itself. They found the opportunity to discuss the results with others to be useful as a means of understanding the intent of individual items. Only three participants had previously been exposed to the AGREE instrument and that majority expressed positive comments about the value of learning about the AGREE instrument. Some clinicians expressed some anxiety about the role for CPGs and how they might be used. None of the study participants provided any feedback when returning their mail packages. The entry-level physical therapists (students) uniformly agreed that the AGREE instrument provided a useful structure and guidance in the evaluation of the CPG. Students compared the AGREE instrument to evaluation instruments they had used for critical appraisal of different study designs, such as clinical trials and systematic reviews. Students frequently commented that these previous instruments had a more open-ended format and expected the reviewer to understand issues in critical appraisal with little direction as to expectations or scoring criteria. Thus, they found the concrete nature of the AGREE instrument and the clear instruction on interpretation to be a useful framework for the evaluation process. Students stated that this direction increased their confidence that they had addressed all important issues. Although students differed on their ratings for individual questions, as well as the overall usefulness of the CPG evaluated, the majority of students understood and correctly interpreted the intent of the items from all of the AGREE domains. The majority of the students, 96 %, stated that they would use the AGREE instrument in other situations. A concern raised by the remaining 4% and other students who would continue to use the instrument was the length of the form and the amount of time required to complete the evaluation, given the busy nature of clinical practice. Factor analysis The factor analysis supported a 4-factor solution. The first factor explained 45% of the variance and contained items primarily from the Scope and Purpose or Rigor of Development domains. The second component explained 12% of the variance and contained items primarily from the Clarity and Presentation or Applicability domains. The third factor explained 7.7% of the variance and contained all of the items from the Stakeholder Involvement domain, all of the Editorial Independence items and question 13 from Rigor of Development, which pertains to whether the guideline has been externally reviewed by experts. The fourth component explained 5.6 percent of the variance and contained item 11 regarding health benefits/side effects and item 15 regarding whether recommendations were specific and unambiguous. Item means and their loadings are presented in Table 6 . Table 6 Results of factor analysis (principal components with varimax rotation) Item Mean Std. Deviation Components 1 2 3 4 Scope and Purpose Q1 3.4003 .72614 .690 .339 .271 .217 Q2 2.9681 .68948 .803 .213 .129 .296 Q3 3.3961 .51941 .393 .489 .016 .430 Stakeholder Involvement Q4 2.6814 1.07262 .336 .422 .661 .093 Q5 1.7517 .89553 .179 .173 .739 .058 Q6 2.8331 .89717 .195 .294 .726 .259 Q7 1.6664 .75710 .255 .290 .675 .175 Rigour of development Q8 2.7344 1.21287 .902 .096 .247 -.087 Q9 2.6533 1.20139 .913 .112 .229 -.123 Q10 2.6314 1.05247 .800 .132 .384 .066 Q11 2.9492 .76769 .059 .339 .302 .682 Q12 2.9811 1.00409 .626 -.058 .223 .514 Q13 2.3556 1.16306 .422 .273 .617 .213 Q14 1.9425 .99370 .323 .668 .090 .044 Clarity and presentation Q15 3.2250 .73262 .132 .200 .149 .864 Q16 3.2269 .77070 .022 .607 .241 .322 Q17 3.1631 .71880 .093 .606 .453 .400 Q18 2.3342 .98180 .091 .671 .449 .273 Applicability Q19 2.2072 .94797 .158 .830 .231 .005 Q20 1.9500 .83211 .172 .818 .176 -.073 Q21 2.2336 .80322 -.017 .775 .299 .237 Editorial Independence Q22 2.1453 .90158 .451 .108 .669 .045 Q23 1.7575 .92802 .178 .305 .452 -.436 This table presents the results of the final 4 factor solution to factor analysis. Bolded cells shown the factor for which each item loaded most strongly. Results are grouped according to the Domains of the AGREE. Construct validity The construct that the CPGs developed by expert guideline development groups would have a higher score on the domain Rigor of Development was supported (See Table 7 ). The construct that therapists would be more likely to recommend for usage a CPG with a higher quality on the domain Rigor of Development was also supported (mean of 76 vs. 58 p <0.001). Table 7 Hypothesis test: rigour of development is greater where panel is known to have methodology expertise Rater Expert Panel No or Uncertain Expertise p Generalist #1 79 58 0.002 Generalist #2 79 57 0.001 Specialist #1 73 58 0.015 Specialist #2 75 65 0.09 Researcher #1 72 57 0.02 Research #2 80 61 0.014 All 6 appraisers combined 78 59 <0.001 This table contains the scores for the Agree Domain on Rigour of Development. CPGs were classified as having an expert panel if 1) there were more than 3 authors listed (or an agency) and 2) there was an experienced CPG methodologist clearly identified as a panel member or if one of the study investigators was recognized as such. All others were classified as "No or Uncertain Expertise". The p value for the independent samples t-test is shown. Criterion validity The correlation between overall assessment and the domain scores ranged from low (0.38) to moderate (0.64), with the highest correlation being observed for the Rigor Of Development domain. (Table 8 ) Table 8 Correlation of domain scores with overall assessment of AGREE Domain Correlation with Overall Rating Stakeholder Involvement 0.59 Scope and Purpose 0.52 Rigour of Development 0.64 Clarity and Presentation 0.62 Applicability 0.49 Editorial Independence 0.38 Kendall's Tau-b correlations were conducted between the mean rating of the over assessment of the CPG across all raters as compared to the mean of each Domain score. As hypothesized the correlation was highest with Rigour of development. Discussion The study findings suggest that the AGREE instrument is reliable and valid when used by physical therapists to evaluate CPGs. While some differences exist between the results reported in the original validation study authored by the AGREE Collaboration, the similarities far outweigh the differences. This would suggest that the process of evaluating CPGs using the AGREE instrument can be transferred to physical therapy practice to support the translation of higher quality CPGs into physical therapy health services. Typically, individual item reliability is of little relevance when evaluating the properties of a measurement scale, as items are not intended to be used in isolation. However, it may be useful from a practical point of view to form hypotheses about were further training might be necessary, if it appears that appraisers have particular difficulty with certain items. As discussed above, one must be careful in interpreting reliability coefficients in isolation, particularly for instruments like the AGREE where some items have "relatively true" scores and others have a spectrum of true scores. For the AGREE this spectrum might exist on application items. Thus, we would expect low item reliability might result from items where there is large measurement error, but also from items where there is substantial variability in how the item might apply in different circumstances. Our data support this. Low reliability was evident on items such as whether the guideline was editorially independent (2/8 ICCs were not greater than 0) and whether key review criteria for monitoring or audit had been provided (2/8 ICCs were not greater than 0). Study participants also appeared to have difficulty interpreting these items during the training session and thus these disagreements may reflect a lack of consensus about the meaning of these items. In some CPGs information on Editorial Independence is contained in footnotes and was missed by some evaluators. Improvements in reliability on these items might be anticipated with further training. Other items where low reliability was observed included whether the clinical question was specifically described (6/8 ICCs were not greater than 0) and whether the patients to whom the guideline applied were specifically described (2/8 ICCs were not greater than 0). During training, participants appeared to understand these questions, although expectations about what constituted an appropriate description of the clinical question or patient population tended to vary according to the participant's level of expertise in that given clinical area. Thus, disagreements on these items may partially relate to differences in priorities or familiarity with relevant issues between participants. Further training is unlikely to enhance reliability in this case, but raises the question about the importance and specificity of relevant clinical expertise when selecting evaluators. Although our intent was to evaluate the importance of clinical expertise, we classified participants quite broadly. Participants classified as clinical specialists were provided CPGs within their broad area of practice; but, we did not ascertain whether in fact the specific topic of the CPG was an area in which they actually did have knowledge or experience. For example, a clinician with expertise in musculoskeletal practice might practice primarily in a narrower area within the field, such as, rheumatology, upper extremity, lower extremity, joint replacements etc. In such cases, their familiarity with the salient features of the specific conditions might be less detailed and result in a differential evaluation regarding whether the clinical population had been appropriately defined. Future investigations should focus on content knowledge in a more specific sense to determine the importance of this issue when selecting evaluators. It is not uncommon for the policy developers to use reliability data to set standards for the number of appraisers required when establishing guideline evaluation processes. Our data provide little direction in this regard, except to suggest that more than two appraisers are advisable. This is consistent with the minimum recommendation of 2 made by the AGREE Collaboration. [ 7 ] Measurement theory suggest that additional appraisers/ratings should produces higher levels of reliability[ 20 ] as do the AGREE Collaboration when stating that 4 appraisers is preferable. Our data did not follow this trend, beyond three appraisers. Our study evaluated the reliability of appraisers performing their assessment in isolation. This process replicates that which might be used by a working committee independently assessing quality scores. However, individual therapists might also need to evaluate CPG when no committee has been established to do so. In these cases, we would recommend three or more appraisers should still be recruited. We recognize that when evaluating CPGs, it is not just the score, but the process that is important. Adding additional appraisers with different perspectives may increase the variability/disagreements. In fact, our data support this, as quadratic weighting of disagreements improved reliability coefficients in generalists and researchers, but not specialists. Specialists tended to disagree on whether a CPG should be used are not, but were less uncertain about that recommendation. We suggest the ideal approach to evaluation of CPGs is one where a group of potential end-users with clinical and guideline expertise work together to review a potential CPG by using the AGREE to facilitate a consensus process to determine both the quality and relevance to practice. These quality ratings should be disseminated to the relevant clinical communities. We recognize that the ideal process will not always be possible. Individual clinicians who must make decisions about utilization of CPGs should recruit colleagues to assist with the evaluation process before modifying their clinical practice based on CPGs with unknown validity. Although interpretation of validity analyses is complex and requires some subjective decisions, overall our validity analyses are supportive of the AGREE instrument and are substantively similar to that reported by the AGREE Collaboration for 33 medically based CPGs[ 14 ] A factor analysis structure which suggests that the concepts measured by the AGREE are similar to the Domains described by the AGREE underlies the content and structural validity of the scale. The factor analysis was strongly supportive of the domains of Stakeholder Involvement and Editorial Independence. This would support uniqueness of items within these domains. The largest factor contained items from the domain Rigor of Development as well as the first two items in Scope and Purpose. Conceptually these two items, which require specific objectives and a well-defined clinical question, fit well with a process of rigorous development. That the largest factor relates to methodological issues supports the AGREE as an evaluative tool. The second factor contained the items regarding whether the patients were specifically described, whether procedures for updating the guideline were provided, all of the items from the applicability domain and 3/4 items from the clarity and presentation. Clarity of presentation, applicability and a defined patient population may all relate to the ability to implement CPGs and thus all retain a conceptual relationship to the domains Applicability or Clarity of Presentation described by the AGREE Collaboration. The third factor contained all items of the stakeholder involvement as well as the additional question in rigor of development addressing whether experts had externally reviewed the guideline. In general, these results support stakeholder involvement as a subscale and include external involvement within this distinct domain. The fourth factor contained only two items, one the item on health benefits/ side effects and a second whether recommendations were specific and unambiguous. This factor explained a small percentage of the variance and contained only two items, making it difficult to relate these results to the factor analysis presented by the AGREE Collaboration. While the results vary somewhat from those reported by the AGREE Collaboration, there is substantial similarity, particularly when one examines the concepts that are represented by the items that clumped together. We view our factor analysis results with caution given the small sample sizes. The AGREE Collaboration study use 100 guidelines and conducted this analysis during the field-testing prior to inclusion of item 23. Our analysis included only 56 guidelines. We did not conduct formal sample size calculations, as practical limitations on guideline availability determined our sample size. Rules of thumb suggest ten "subjects" per item for factor analysis, requiring 230 CPGs for a well-powered analysis. Thus, some inherent instability should be expected in the factor analyses conducted to date. With the proliferation of CPG, we expect that larger samples might be evaluated in future studies and provide more definitive results on the factor validity of the AGREE instrument. Construct validity tests also supported the validity of the AGREE instrument. Constructs were developed to replicate those used in the previous validation of the AGREE[ 14 ] and provided similar findings. Despite our inability to be confident about whether some CPGs had a methodologist, we still found large differences between the Rigour of Development Domain score obtained where we could identify a team containing a methodologist as compared to where this was not present or unclear (21 point difference). The AGREE Collaboration found a 9 point advantage in this domain for guidelines developed within a guideline development program and 19 points for those developed as national initiatives. Similarly, our correlations between overall assessment scores and those reported for Rigor of Development (0.64) concurred with those reported by AGREE Collaboration data (0.87) in that both suggest a substantive relationship. Overall, our findings were remarkably consistent with those reported by the AGREE collaboration when validating the AGREE as used by medical practitioners[ 14 ] Validation by independent groups in different settings provides a stronger foundation for any instrument. These findings can be used to increase confidence in the current practice of different health care disciplines to use the AGREE to facilitate the evaluation of CPGs. Conclusion 1. The AGREE instrument is reliable and valid when used by physical therapists to assess the quality of clinical practice guidelines 2. A minimum of three appraisers should be used to optimise reliability, although issues on effecting knowledge transfer or maximizing validity might increase these requirements. 3. There is no evidence that specific types of physical therapists provide more reliable scores. As this study did not address whether familiarity with the actual content of the CPG influenced reliability, this should be studied in the future. 4. There is evidence that guidelines developed with the assistance of experienced guideline developers are more rigorous. 5. The AGREE instrument was found to be useful in assisting both novice and experienced therapists in evaluation of clinical practice guidelines. The majority of therapists would continue to use the instrument. 6. Validity analysis supported the majority of results reported by the AGREE Collaboration)[ 14 ] The type of CPGs and evaluators were different in the current study supporting the validity of this instrument across a spectrum of circumstances. Competing interests IG is an associate member of the AGREE Collaboration. Authors' contributions JM, DB, SS, SSW formed the original study team which conceived of the research question, obtained the ethics approval and obtained grant funding. JM developed the research design, conducted statistical analyses, developed and facilitated the training sessions, developed and evaluated the student evaluations and drafted the manuscript. DB managed grant funds, selection of clinical practice guidelines, appraiser recruitment and data collection. All authors approved the final study protocol, contributed to interpretation of the study results and participated in revisions of the manuscript. IG provided consultation with respect to CPG research and health care policy. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 The training test Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555572.xml
524374	Perceptions of first and third year medical students on self-study and reporting processes of problem-based learning	Background The objective of this study is to investigate the perceptions of first and third year medical students on self-study and reporting processes of Problem-based Learning (PBL) sessions and their usage of learning resources. Methods The questionnaire applied to the students consisted of; questions about students' perceptions on searching and preparing phases of the self-study process, the breadth and depth of discussion during reporting phase and the usage of learning resources. Results First-year students spent more time for self-study and more highly rated the depth of discussion compared to third-year students. The searching and preparing phases of the self-study process were considered as statistically important factors strongly influencing the breadth and depth of discussion during the reporting phase. The effect of extensiveness of searching on the depth of discussion was negative among the first-year students, and positive among third-year students. Conclusions The relative shortness of third-year students' self-study periods can be related to their mental weariness, decreased motivation or first-year students' slowness in accessing appropriate resources. The third-year students' more frequent use of textbooks may be due to the improvement of their abilities in reaching relevant learning resources. The findings implied that the increase in students' PBL experience paralleled the development of their discussion skills using different learning resources.	Background The institution of the present study, Dokuz Eylul University School of Medicine (DEUSM), has been implementing Problem-based Learning (PBL) in its undergraduate curriculum since the 1997–1998 academic year. The duration of undergraduate medical education is six years. PBL is the principal educational strategy in the first three years. Task-based learning strategy was adopted as an educational strategy for clerkships in the 2000–2001 academic year. During the first three years of undergraduate education, PBL sessions are the main focus of a modular structure. The three objectives of PBL are; acquisition of essential knowledge, use of knowledge in clinical contexts and self-directed learning [ 1 ]. In a PBL programme, the students use a seven-step procedure to structure their activities. This procedure consists of clarifying vague phrases and concepts in the problem, defining the problem, analysing the problem on the basis of prior knowledge, arranging the proposed explanations, formulating learning objectives, trying to fill in the knowledge gaps by means of self study and reporting the findings in the group [ 2 ]. Individual study is an essential step of information processing approach to learning. The group members individually collect information with respect to the objectives [ 3 ]. PBL curriculum emphasises the development of self-regulating skills. Rather than being passive recipients of information, students are expected to be actively involved [ 4 ]. The diversification of learning resources and their access routes had a considerable impact on professional skills development. Due to the fact that medicine requires lifelong learning, it has become important for students to discover learning resources on their own and to interpret their findings. The use of a variety of resources necessitates the processing of information through critical self-directed inquiry. Important components of a PBL curriculum are self-directed learning and students' investigation of learning objectives. They support deep approaches to learning. Compared to traditional lecture-based curriculum, students in a PBL curriculum use a greater number and variety of resources [ 5 ]. In PBL, students are encouraged to take substantial responsibility for their learning. Small group discussions stimulate independent and active learning. They guide the students during their independent and self-directed learning. During a PBL group session, limited only by the boundaries of their prior knowledge, students try to clarify the issues being discussed. The issues that cannot be explained thoroughly are formulated as student-generated learning objectives which will guide the students during their independent and self-directed learning. During the searching phase of individual study, students are expected to refer to different learning resources and search for literature relevant to their learning issues. The findings are evaluated and prepared for the group discussion. The extensiveness of different learning resources used is an indicator of students' self-directed learning skill. The consultation of diverse information sources influences the breadth and depth of discussion of the tutorial group during the reporting phase [ 6 ]. The iteration of self-directed learning periods leads the students to organise and review the learning resources critically. Through this critical approach, a major educational objective of PBL, the learning resources can be efficiently and effectively accessed and relevant information can be elaborated to form the theoretical basis leading to the solution of the problem [ 1 ]. Students learn most effectively when using a variety of information resources. Therefore, the provision of adequate resources meeting the needs of different learning styles is important. Students' accessibility to these learning resources may be limited if they are preserved at different locations under the management of different departments [ 7 ]. Since the beginning of the curriculum change process in Dokuz Eylul University School of Medicine (DEUSM), a special emphasis has been given to the diversification and improvement of learning resources, and facilities have been improved to meet the learning needs of PBL students. During the first three academic years of DEUSM, approximately 30–35% of the weekly schedule is allocated to students' self-study periods. Several types of learning resources such as the library, the Learning Resources Centre and a computer laboratory with Internet access are available to students. In addition, the staff teachers provide appointment-based scientific counselling upon request. The library, offering a wide variety of printed material like textbooks and periodicals is open on office days and weekends between 8:30 a.m.–11:00 p.m. The Learning Resources Centre, an interactive learning environment inaugurated in the 2001–2002 academic year, is open on office days between 8:30 a.m.–7:00 p.m. The learning resources of the centre are; CD-ROMs, video-tapes, microscopes, histology and pathology slides, models & mannequins, posters and computers with Internet access. The centre's exhibitions of learning material are synchronous with the PBL modules being implemented. During the first week of their medical education, first-year students attend a PBL orientation course. This course consists of basic principles of PBL, student and tutor roles and presentation of available learning resources in DEUSM. All tutors are initially required to take a PBL course and regularly attend weekly tutor meetings [ 8 ]. The tutor profile of the first three years is similar. Faculty members from all existing preclinical and clinical departments fulfil tutor role in PBL groups for determined periods of time during an academic year. Some alterations observed by tutors in preparing and reporting processes between novice and experienced PBL students led us to plan the present study. The research questions of this study are; √ What were the differences between first and third-year students' perceptions with respect to self-study and reporting processes of PBL? √ What were the length of students' self-study times and their usage of learning resources? √ What was the overall and year-specific impact of self-study process on the breadth and depth of discussion during the reporting phase? The objective of the present study is to investigate and compare the perceptions of first and third-year PBL students on self-study and reporting processes and their usage of learning resources. Methods The first-year students of DEUSM who were recently introduced to PBL programme and completed their first semester and the third-year students who had a two and a half year experience in the PBL programme were included in this study. The questionnaire consisted of questions about students' perceptions on searching and preparing phases of the self-study process, the breadth and depth of discussion during reporting phase and the usage of learning resources. The questionnaire implemented and tested for validity and reliability in Maastricht University [ 6 ] was translated into Turkish, using expressions appropriate for our study group. Two questions, one on self-study time and the other on the usage of learning resources were added (Appendix 1). The participants reflected their perceptions of 22 questionnaire items, grouped under the headings of searching and preparing phases of self-study process, breadth and depth of discussion during the reporting phase, on a five-point scale ranging from 1 = totally disagree to 5 = totally agree. The points attributed to the items of the scale were evaluated between 1 to 5 points (1 = minimum, 5 = maximum). The pilot study of the questionnaire was applied to 10 medical students and favourable results were obtained. At the beginning of a PBL session in February 2002, the questionnaire was distributed to first and third-year students and collected 15 minutes later. Before the application of the questionnaire, the purpose of the study was briefly explained to the students and their oral consents were obtained. The response rate was 78.8% (115/146) for first-year students and 85.5% (142/166) for third-year students. SPSS 10.0 for Windows was used and the reliability coefficient was calculated (Cronbach alpha: 0.81). Chi-Square Test was used to investigate students' frequency of use of learning resources. Independent Samples T Test was used to compare the scores of self-study and reporting processes of both classes. The effects of independent variables on the breadth and depth of discussion were analysed with Multiple Regression Analysis Test. Results The weekly self-study times of the first and third-year students during a two-week module were 15.00 ± 8.83 and 11.57 ± 7.04 hours respectively (p = 0.001). The first and third-year students' percentages of learning resources usage and statistical difference between them were respectively as follows; textbooks 24.3% and 44.4% (χ 2 = 11.1, p = 0.01), educational CDs 14.8% and 6.3% (χ 2 = 4.983, p = 0.026), lecture handouts 95.7% and 95.8% (χ 2 = 0.002, p = 0.962) and medical journals 8.7% and 9.9% (χ 2 = 0.102, p = 0.750). Lecture handouts were used very frequently. It was found that third-year students referred more frequently to textbooks than first-year students. The scores reflecting students' perceptions of statements regarding learning issue driven searching and extensiveness of searching ranged between 3.4–3.7 out of five (Table 1 ). Third-year students' scores for the same statements were higher than those of first-year students' (p = 0.034, p = 0.009). First-year students' average scores on explanation-oriented preparing of learning issues were higher than those of third-year students' (p = 0.015). Table 1 First and third-year students' average scores regarding self-study process Titles First-year students average score* ± SD Third-year students average score* ± SD Statistical analysis** Learning issue driven preparing 3.5 ± 0.8 3.7 ± 0.8 P = 0.034 Extensiveness of searching 3.4 ± 0.9 3.7 ± 0.9 P = 0.009 Explanation-oriented preparing 3.5 ± 0.6 3.3 ± 0.7 P = 0.015 * (1 = minimum, 5 = maximum) ** Independent samples T test. The scores reflecting students' perceptions on statements regarding the discussion of learning objectives during the reporting phase of a PBL session, ranged between 3.2–3.7 out of five. First-year students' average scores on the depth of discussion were higher than those of third-year students' (p = 0. 000) (Table 2 ). Table 2 First and third-year students' average scores on discussion during reporting phase Titles First-year students' average score* ± SD Third-year students' average score* ± SD Statistical analysis** Breadth of discussion 3.3 ± 0.8 3.2 ± 0.9 P = 0.345 Depth of discussion 3.7 ± 0.7 3.4 ± 0.8 P = 0.000 * (1 = minimum, 5 = maximum) ** Independent samples T test. The effects of learning issue driven searching, extensiveness of searching and explanation oriented preparing on the breadth and depth of discussion were analysed with regression analysis (Table 3 ). Table 3 The effects of the independent variables on the breadth and depth of discussion (Multiple Regression Analysis) R 2 β t F Dependent variable: Breadth of discussion Searching process Learning issue driven searching 0.21 2.97* Extensiveness of searching 0.07 0.96 Preparing process 0.09 6.976* Explanation-oriented preparing 0.14 1.89* Dependent variable: Depth of discussion Searching process Learning issue driven searching 0.26 3.87* Extensiveness of searching -0.07 -1.08 Preparing process 0.15 12.377* Explanation-oriented preparing 0.26 3.87* *p < 0.05 The 9% change in the breadth of discussion was explained with searching and preparing phases. Learning issue driven searching with the highest β value was the most important and statistically significant factor influencing the breadth of discussion. The impact of explanation oriented preparing on the breadth of discussion was also statistically significant (Table 3 ). The 15% change in the depth of discussion was explained with searching and preparing phases. It was found that learning issue driven searching and explanation oriented preparing were the most important and statistically significant factors influencing the depth of discussion. The extensiveness of searching had a statistically insignificant negative effect on the depth of discussion (Table 3 ). Regression analysis was separately carried out for both classes. Excluding the extensiveness of searching, other findings were similar. Extensiveness of searching had a statistically negative effect on the depth of discussion among first-year students (β = -0.28, t = -2.680, p = 0.009), but a positive effect among third-year students (β = 136, t = 2.198, p = 0.030). Discussion A probable explanation for the relative shortness of third-year students' self-study times compared with those of first-year students' was third-year students' mental weariness due to continuous and intensive effort in reaching learning objectives. Another probable explanation was first-year students' slowness in accessing appropriate resources due to their lack of familiarity with self-directed learning. It was found that first and third-year students frequently used lecture handouts. The reasons for the high frequency of use of handouts were considered as their wide availability due to their provision at the end of lectures that are limited to one hour a day. In order not to hinder the curiosity of students and their motivation for self-directed learning, handouts are designed as brief outlines prepared by lecturers and include topic titles, schemata, algorithms and tables. Since the Learning Resources Centre was inaugurated in 2001, third year students could only use it during their second and third years, whereas first-year students started using it since the beginning of their medical education. More frequent use of Learning Resources Centre CDs by first-year students may be related to their early encounter with these learning facilities. Third-year students' more frequent use of textbooks may reflect the development of their ability in reaching essential resources. Third-year students' higher ratings for learning issue driven searching and extensiveness of searching are consistent with the general expectation stating that experienced students can search more learning resources [ 4 ] The first-year students attributed higher scores to statements regarding explanation oriented preparing (Table 1 ). This finding may be explained with third-year students' mental weariness due to continuous and intensive efforts since the beginning of their medical education or first-year students' eagerness to adapt to a new educational system. In the Maastricht study, first-year students' average scores for learning issue driven searching, extensiveness of searching and explanation oriented searching were 3.1 ± 0.3, 2.8 ± 0.4 and 3.2 ± 0.3 respectively [ 6 ]. The scores of the entire study group attributed to breadth and depth of discussion during the reporting phase varied between 3.2 ± 0.9 and 3.7 ± 0.7. Although third-year students were expected to become more competent in PBL discussions, third-year students' scores, especially the ones attributed to the depth of discussion, were lower than those of first-year students' (Table 2 ). This finding is consistent with Cohen's view that the students who gain experience in cooperative study are inclined to limit their efforts to share and explain the information they gather [ 9 ]. Higher scores of first-year students on the depth of discussion may also be interpreted as a reflection of their adaptation to the PBL system. In the Maastricht study, average scores attributed by first-year students to the breadth and depth of discussion were 3.0 ± 0.4 and 3.4 ± 0.5 respectively [ 6 ] The results of this study showed that the breadth of discussion during reporting phase was affected by the searching and preparing phases of the self-study process. Similarly, it was understood that the depth of discussion during the reporting phase was affected by the searching and preparing phases of self-study process. Learning issue driven searching " using learning objectives as study references " and explanation oriented preparing " studying and summarising learning resources at an appropriate level to be shared with other students during PBL session ", directly influenced the breadth and depth of discussion. It was observed that students' searching of different resources (extensiveness of searching), though not statistically significant, negatively affected the depth of discussion. During a PBL session, in the presence of different resources, in-depth understanding of newly acquired information requires a well-structured discussion. This may be difficult for first-year students due to their lack of familiarity with PBL and self-directed learning. In the group session, first-year students may encounter difficulties while tutoring a discussion based on several resources [ 6 ]. When regression analysis was separately carried out for both classes, it was observed that extensiveness of searching had a statistically negative effect on the depth of discussion among first-year students, but a positive effect among third-year students. These findings imply that the increase in students' PBL experience paralleled the development of their discussion skills using different learning resources. The design of the present study based on students' perceptions was its main limitation. The assumptions regarding the causes of differences between first and third-year students' perceptions were based on the PBL experience of authors. Conclusions First-year students' longer self-study times, higher explanation oriented preparing scores, and higher depth of discussion scores compared with the scores of third-year students were considered as research questions which need to be investigated in future studies. Competing interests None declared. Authors' contributions BM carried out research design, statistical data analysis, data evaluation, research report, YG carried out research design, data evaluation, research report, HCT carried out data evaluation and research report, SO carried out data evaluation and contributed to the research report, AT contributed to research design, data collection and data evaluation. All authors read and approved the final manuscript. List of abbreviations DEUSM: Dokuz Eylul School of Medicine PBL: Problem-based Learning Appendix Self-study and Reporting Processes Questionnaire Year: 1 □ 3 □ • What is your weekly average study time in a two-week module? (..............) hours. • What kind of resources do you use during your self-study process? () Textbook () Lecture handouts () Others ..................... () Educational CDs () Medical journals • Please indicate your level of agreement with the following statements about self-study process, by rating them between 1-to-5. (1 = totally disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = totally agree) 1 2 3 4 5 Search Phase Learning Issue Driven Searching 1. I use the learning issues as a starting point for my search and search the resources accordingly. During studying 2. I always check the learning issues to decide whether I study deep enough. 3. I remain attached to the learning issues. 4. I check the learning issues to decide whether the resources I study fully cover the learning issues. 5. I use the learning issues as a guide while studying the resources step by step. Extensiveness of searching 6. When searching the resources, I try to evaluate the relevancy of different books with the subject to be studied. 7. When searching the resources, I try to compare different resources about the same subject. 8. I spent a lot of time and effort on searching the resources before I start studying Preparing phase Explanation Oriented 9. I study the subjects such that I can explain them without looking at the resources. 10. I study the subjects such that I can comment about the theories being discussed 11. I study such that I can explain the content of the resource in my own words. 12. I study such that I know what needs to be discussed in each learning issue. 13. I study by making summaries of the selected resources. 14. I study by making notes and algorithms. Reporting Phase Breadth of Discussion 15. Many different issues/findings are discussed. 16. When a student from the group reaches an information not included in the learning issues explains it to others. 17. The members of the group question different aspects of the resources. 18. Different/contradicting resources are compared. Depth of Discussion 19. During discussions new concepts are discussed and explained in detail. 20. The issues are discussed in depth. 21. The problems of the scenario are questioned and clarified using the newly learned knowledge. 22. The discussion in the reporting makes very useful contributions to newly learned knowledge in the self-study process. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524374.xml
527872	Melanoma-restricted genes	Human metastatic cutaneous melanoma has gained a well deserved reputation for its immune responsiveness. The reason(s) remain(s) unknown. We attempted previously to characterize several variables that may affect the relationship between tumor and host immune cells but, taken one at the time, none yielded a convincing explanation. With explorative purposes, high-throughput technology was applied here to portray transcriptional characteristics unique to metastatic cutaneous melanoma that may or may not be relevant to its immunogenic potential. Several functional signatures could be identified descriptive of immune or other biological functions. In addition, the transcriptional profile of metastatic melanoma was compared with that of primary renal cell cancers (RCC) identifying several genes co-coordinately expressed by the two tumor types. Since RCC is another immune responsive tumor, commonalities between RCC and melanoma may help untangle the enigma of their potential immune responsiveness. This purely descriptive study provides, therefore, a map for the investigation of metastatic melanoma in future clinical trials and at the same time may invite consideration of novel therapeutic targets.	Background Human metastatic cutaneous melanoma relative to other common solid tumors shares with renal cell cancer (RCC) the well deserved reputation of being responsive to immune manipulation [ 1 , 2 ]. However, the reason(s) for this phenomenon remain(s) largely unknown [ 3 ]. Possibly, metastatic cutaneous melanoma is endowed compared to other tumors with a wealth of "tumor rejection" antigens of unique immunogenic potential. Indeed, the ease in which tumor infiltrating lymphocytes recognizing autologous tumor cells can be isolated from melanoma metastases suggests an extraordinary ability of melanoma cells to elicit cognitive T cell responses [ 4 ]. In addition, the broad repertoire of melanoma-associated antigens so far discovered largely outnumbers that of other tumors suggesting a stronger immunogenicity of this cancer [ 5 - 7 ]. This explanation, however, contrasts with the paucity of RCC-specific antigens described and the relative difficulty of expanding tumor infiltrating lymphocytes from RCC that can recognize autologous cancer cells. Yet, RCC is somehow also responsive to immune therapy [ 2 , 8 ]. suggesting that explanations other than solely the identity of T cell epitopes should be considered. We have previously shown that the microenvironment of a subgroup of melanoma metastases expresses at the transcriptional level an array of biologically active factors that may influence both the innate and the adaptive arm of the immune system [ 9 ]. We have also observed that subcutaneous melanoma metastases likely to respond to immunotherapy have a different genetic profile than those unlikely to respond to therapy [ 10 ]. This genetic profile differs particularly in expression of immunologically relevant genes suggesting that melanoma metastases that respond to therapy are conditioned to respond even before therapy by an immunologically active environment. These pilot studies encouraged us to collect a large series of melanoma metastases and analyze their genetic profile to search for molecular signatures specific for this tumor entity compared with other less immunogenic cancers. The lack of clinical information limited this study to a descriptive analysis of the molecular signatures characteristic of melanoma that could serve as a map for future studies on this subject. In addition, the application of high-throughput technology to identify transcriptional characteristics unique to metastatic cutaneous melanoma may define novel targets which can be employed for further analysis. . Several signatures were identified descriptive of immune or other biological functions that might be relevant to immune responsiveness. Furthermore, a comparison of the transcriptional profile of metastatic melanoma with that of a library of available primary RCC identified several genes co-coordinately expressed by the two tumor types. Since RCC represents another immune responsive human tumor it is possible that commonalities with melanoma may reveal, in the future, the secret of immune responsiveness. This purely descriptive study provides, therefore, a map of markers for the investigation of metastatic melanoma in novel clinical trials and may invite consideration of novel therapeutic targets. Results and Discussion Differences between the transcriptional profile of melanoma metastases and other solid tumors We first identified genes differentially expressed between 69 melanoma samples and 87 samples obtained from available primary or metastatic solid tumors (Table I ). RCC samples were excluded from the statistical comparison because this tumors share immune responsiveness with metastatic melanoma and, therefore, were considered separately from non-immunogenic tumors. Differential expression was defined significant at a p 2 -value ≤ 0.001 (unpaired two-tailed Student t test). This test identified 4,658 cDNA clones differentially expressed between melanoma metastases and tumors of other histology (see Additional file 1 ). Non parametric Wilcoxon test yielded comparable results in terms of number and identity of differentially expressed genes (data not shown). Permutation analysis strongly supported the significance of these findings. Approximately half of the differentially expressed clones (2,044) were up-regulated in melanoma metastases relative to other tumors and the remaining 2,614 clones were down-regulated. Up-regulation was defined as a positive value after subtracting the average ratio of other tumors from that of melanoma lesions (Figure 1 ). Down-regulation was considered a negative value resulting from the same formula. A large proportion of the genes down-regulated in melanoma relative to other tumor were lineage specific and reflected its unique ontogeny from the neuroectoderm while the tumors studied were mostly of epithelial origin. We have previously described the weight that ontogeny may play in balancing the transcriptional profile of RCC [ 11 ]. Unfortunately, for this type of analysis to be conclusive availability of matched normal tissues is required which is not as readily achievable in the case of melanoma due to the scattered distribution of normal epithelial melanocytes within the skin layers. The complete list of the 4,658 genes differentially expressed by melanomas is available at Table 1 Samples used for the analysis presented in the same ordered displayed in the supervised analyses. Histology Location # of Specimens Source RCC Primary 14 Mainz University, Germany Melanoma Primary 1 Padua University, Italy Melanoma In Transit Metastases 3 Padua University, Italy Melanoma Cutaneous Metastases 7 Padua University, Italy Melanoma Lymph Node Metastasis 35 Padua University, Italy Melanoma Visceral Metastases 2 Padua University, Italy Melanoma Cutaneous Metastases (FNA) 21 NCI, NIH, Bethesda, USA EOC Primary 15 MD Anderson CC, Houston, TX, USA Soft Tissue Sarcoma Primary 3 Tissue Network, Philadelphia, PA, USA Endometrial Cancer Primary 1 Tissue Network, Philadelphia, PA, USA Laryngeal Cancer Primary 1 Tissue Network, Philadelphia, PA, USA Breast Cancer Primary 2 Tissue Network, Philadelphia, PA, USA Colon Adeno-Carcinoma Primary 1 Tissue Network, Philadelphia, PA, USA Esophageal Carcinoma Primary 12 NCI, NIH, Bethesda, USA, Colorectal Carcinoma Primary 35 University of Pisa, Italy Colorectal Carcinoma Lymph Node Metastasis 16 University of Pisa, Italy Colorectal Carcinoma Hepatic Metastasis 1 University of Pisa, Italy Total Specimens 180 RCC = Renal Cell Carcinoma; FNA = Fine Needle Aspirates; EOC = Epithelial Ovarian Cancer; Figure 1 Eisen's clustering based on 2,044 genes up-regulated in metastatic melanoma lesions compared with all other tumors. Signatures include growth regulation (maroon vertical bar); a signature of genes similarly expressed by melanoma and RCC (blue vertical bar) including a sub-cluster of genes predominantly expressed by RCC (double vertical blue bar and blue arrow); an immunological signature (orange vertical bar); a signature specific for genes predominantly expressed by cutaneous and subcutaneous melanoma metastases (green vertical bar); gene related to blood contamination in fine needle aspirates (FNA; red arrow) and a signature specific for melanoma differentiation antigens (MDA; blue arrow). Genes were identified by a two-tailed Student's t test comparing all melanoma lesions with other tumors (with the exception of RCC) applying as cut off of significance a p 2 -value < 0.001. Up-regulation was defined as a positive value after subtracting the average of other tumor samples Cy5/Cy3 ratios from that of melanoma samples. Signature-specific genes Several signatures representing genes preferentially expressed by melanomas were identified that could be partially linked to specific gene functions. Those signatures were segregated according to unsupervised gene rearrangement based on the Eisen's clustering method. The first cluster ( cluster a , Figure 1 ) included 76 clones of which 63 were named corresponding to 53 genes. A subset of genes in this cluster were commonly up-regulated in melanoma and RCC including enolase 2 ( neuronal γ-enolase ) which is a previously described serum marker of RCC also associated with renal carcinogenesis [ 11 - 13 ]. Differential expression of enolase-2 between melanoma and other cancers with the exception of RCC reached a significance of 5 × 10 -7 and 1 × 10 -6 for two clones representing this gene (Student's t -test p 2 value). Overall, this cluster was enriched of genes associated with active cellular metabolism and included only few genes of previous known relevance to melanoma with the exception of a member of the melanoma antigen family D ( MAGED2 , Table 2 and Figure 2 ). Cluster b included 91 clones (72 named representing 65 distinct genes) predominantly associated with growth regulation and apoptosis. Among the genes included in this cluster was BNIP3L (BCL2/Adenovirus E1B interacting protein like-3, t -test p 2 -value = 2 × 10 -7 for both cDNA clones representing this gene) that we have previously reported to be associated with the immune responsiveness of melanoma metastases [ 10 ]. Two large and related clusters ( cluster c and d ) included 262 and 613 clones, respectively (112 and 296 named corresponding respectively to 110 and 289 genes). These clusters were characterized by a high density of unnamed clones and by relatively low Cy5/Cy3 ratios. However, it should be noted that these clusters may be of particular interest because the gene expression profile was similar between melanoma and RCC tumors suggesting that some of these genes may conceal the enigma of immune responsiveness. In particular, a relatively sizable sub-cluster was noted with genes predominantly up-regulated in RCC but also expressed by melanoma lesions compared with other tumors ( Blue arrow and double vertical bar , Figure 1 ). Genes concomitantly up-regulated in melanoma and RCC will be separately discussed later, however, it is important to note that this cluster included JAK-1 ( t -test p 2 -value = 2 × 10 -5 ) that was previously also reported in association with melanoma immune responsiveness to interleukin-2-based immunotherapy [ 10 ]. JAK-1 was recently linked to the apoptotic role that interleukin-24 (melanoma differentiation associated gene-7: MDA 7 ) may exert on melanoma cells [ 14 ]. The following cluster ( cluster e ) included 208 clones (151 named representing 143 different genes) predominantly associated with immune function. This immune signature was underlined by the high prevalence of expression of these genes in samples obtained from lymph node metastases whether from melanoma or colorectal primaries. Cluster f integrated 129 clones (91 named representing 87 distinct genes) including a mixture of genes with disparate functions difficult to categorize into a predominant pattern. This group also included APPBP1 (amyloid β precursor protein; t -test p 2 -value = 1 × 10 -4 ) which was previously reported in association with melanoma immune responsiveness [ 10 ]. APPBP1 is a recently discovered epidermal growth factor that regulates dendrite motility and melanin release in epidermal melanocytes and melanoma cells [ 15 ]. It is possible that some of its functions may have an indirect effect in modulating the immunological profile of subcutaneous metastases. Cluster g included genes preferentially up-regulated in subcutaneous melanoma metastases known to be more responsive to immunotherapy with interleukin-2 [ 16 ]. This cluster included 201 clones (142 named representing 132 genes). Among the genes representative of this cluster were two classic melanoma associated genes ( PRAME and tyrosine-related protein-1; TRP-1 ). In a small proportion, this cluster included a group of genes only over-expressed in fine needle aspirates (FNA) and generally expressed by circulating cells revealing blood contamination of FNA material ( red arrow , Figure 1 ). Cluster h included 131 clones (102 named representing 99 genes). Cluster I included 222 clones (171 named identifying 155 genes) with most of the melanoma differentiation antigens (MDA) clustering in close proximity with the exception of the TRP-1 already discussed in cluster g . Interestingly, this cluster was also highly enriched of genes associated with ribosomal function and active translation. Furthermore, it included the melanocyte master regulator MITF ( t -test p 2 -value for two respective cDNA clones = 2 × 10 -15 and 8 × 10 -14 ) which has been shown to modulate lineage survival and melanoma cell viability through interaction with the anti-apoptotic protein BCL2 [ 17 ]. MITF was coordinately expressed with several genes associated with calcium and other solute metabolism including cytochrome p450 ( t -test p 2 -value for two respective cDNA clones = 3 × 10 -12 and 7 × 10 -13 ) solute carrier family 7 ( t -test p 2 -value for two respective cDNA clones = 2 × 10 -10 and 2 × 10 -6 ), G protein coupled receptor 56 ( t -test p 2 -value = 2 × 10 -7 ) and calpain 3 ( t -test p 2 -value = 6 × 10 -15 ), a calcium-regulated gene found to be highly expressed in melanoma cells [ 18 ]. Finally, cluster J included 88 clones of which the 62 named identified 58 genes. Table 2 Genes of known association with melanoma Clone ID Chromosomal Location Name AVERAGE t -test (p 2 -value) RCC MEL Other RCC vs MEL MEL vs Other Cluster a 2569910 Xp11.2 MAGED2 -0.22 0.4 -0.28 7.10E-03 8.00E-07 316397 Xp11.2 MAGED2 -0.24 0.41 -0.29 5.60E-04 3.00E-07 P24478 Xp11.2 MAGED2 -0.21 0.31 -0.22 5.10E-03 1.00E-06 Cluster d 1735474 Xq26 MAGEC1 0.03 0.25 -0.26 3.40E-02 6.80E-06 131595 Xq28 MAGEA10 -0.03 0.28 -0.24 6.20E-02 1.80E-04 1505360 Xq28 MAGEA2 -0.88 0.94 -0.76 6.00E-12 2.00E-10 Cluster e 781233 2p23.3 POMC -0.03 0.17 -0.15 2.20E-01 1.40E-05 Cluster g 897956 22q11.22 PRAME -0.62 1.33 -1.05 1.60E-06 1.00E-18 853789 9p23 TYRP1 -0.82 0.59 -0.3 7.70E-06 8.00E-04 768344 9p23 TYRP1 -0.7 0.8 -0.61 1.60E-07 1.80E-06 40056 15q23 CSPG4 -0.32 0.69 -0.53 2.20E-04 2.70E-09 P07338 n.a. CSPG4 -0.63 0.78 -0.61 8.50E-05 5.70E-09 2447688 11q23.3 MCAM 0.21 0.69 -0.6 8.70E-02 3.40E-09 1585510 3q28-q29 MFI2 (p97) -0.48 0.59 -0.44 1.10E-03 5.70E-07 Cluster i P30563 n.a. CD63 -0.66 0.7 -0.44 8.20E-08 1.90E-09 1631546 Xq28 MAGEA6 -0.55 0.35 -0.22 1.30E-08 5.60E-04 291448 12q13-q1 SILV (gp100) -1.31 1.55 -1.16 4.90E-16 5.00E-15 271985 11q14-q2 \|\| TYR Tyrosinase -1.37 1.73 -1.38 6.30E-18 2.90E-18 272327 9p24.1 Melan-A -0.76 1.19 -0.95 2.40E-08 1.80E-16 269124 9p24.1 Melan-A -0.65 1.21 -0.99 5.30E-09 2.70E-16 Figure 2 Eisen's clustering of genes already reported to be preferentially expressed by melanomas. The analysis was performed on 180 cancer samples as described in the Results section and ordered according to Table 1. In particular, renal cell cancer (RCC, orange), melanoma (blue), Epithelial Ovarian Cancer (EOC, yellow), Esophageal Cancer (green), Primary Colorectal Cancer (CRC, dark brown) and lymph nodal metastases of CRC (light brown) are shown. Melanoma samples are further subdivided in cutaneous metastases (CM, light blue) from frozen sections (continuous line) or fine needle aspirates (FNA, dashed line) and lymph nodal metastases (LN, darker blue line). Below is the distance among the various genes based on Eisen's clustering. Genes previously recognized to be associated with melanoma Genes previously described to be preferentially expressed by melanoma lesions were confirmed to be so at a very high level of significance (Figure 2 ). Exceptions included AIM-1, CXCL-1 (GRO-α), D2S448 and MAGEA1 which are all significantly more expressed by tumors other than melanomas. Interestingly, different types of melanoma associated genes displayed a different pattern of expression with MDA (tyrosinase, gp100/PMel17 and MART-1/MelanA) being co-coordinately expressed in close proximity to each other in cluster I and MAGE family genes preferentially expressed in cluster d (Table II ). Cluster g included a number of genes whose expression had been previously associated with melanoma including preferentially expressed antigen in melanoma ( PRAME ) and the tyrosine-related protein-1 ( TRP-1 ). When the melanoma associated genes were studied alone, PRAME clustered close to the other MDA believe to be involved in the pigmentation process (tyrosinase, MART-1/Melan and gp100/PMel17). This is of particular interest because PRAME has been also reported to be highly expressed in other cancers of ectodermic origin such as medulloblastoma and neuroblastoma suggesting a link between ectoderm and pigmentation [ 19 , 20 ]. The coordinated expression of MDA suggests that their down-regulation or loss of expression during melanoma progression may be related to a central regulatory pathway not as yet identified. Indeed in previous studies [ 21 - 25 ], we noted that loss of expression of MART-1/Melan A paralleled that of gp100/PMel17 ( SILV ) in melanoma metastases while genes of the MAGE family manifested an independent behavior [ 25 ]. This finding may have important repercussions in the design of antigen-specific immunization protocols and at the same time may complicate the interpretation of tumor antigen loss variant analysis by broadening loss of expression to antigens other than those targeted by a given therapy. Immunological Signature The large majority of genes associated with immune function were included in cluster e . These genes appeared up-regulated in lymph node metastases of melanoma as well as those from colorectal primaries suggesting that their expression results from lymphoid cell infiltration (Figure 3 ). The same genes were up-regulated in a significant proportion of subcutaneous melanoma metastases suggesting that a strong and active infiltrate of immune cells is present in these tissues. In fact, most of the genes included in cluster e were significantly up-regulated in 10 cutaneous/subcutaneous melanoma lesions compared to 70 primary cancers of other histology (Table III shows a selection of the most significantly up-regulated genes in cutaneous/subcutaneous melanomas). Of interest is the observation that several of the genes up-regulated in these lesions are clustered in specific chromosomal locations with a high predominance of genes located in position 6p21.3, 11p11.2, 19p13 and 19q13. Among the immunologically-related genes specifically up-regulated in subcutaneous melanoma metastases, some are of particular interest because of their known relationship with effector T cell function. In particular, we find interesting that NK4 , an anti-angiogenic factor released by natural killer cells [ 26 ], was constitutively expressed by cutaneous melanomas. We found this gene to be associated with regression of a melanoma metastasis during interleukin-2 therapy [ 27 ] and to be one of the genes most frequently up-regulated during activation of antigen-specific T cells in vitro [ 28 , 29 ]. Of interest was also the constitutive expression of CD27 a co-stimulatory member of the TNF receptor family strongly associated with cell activation [ 30 , 31 ]. The expression of CX3CR1 a gene constitutively expressed by natural killer cells that makes them sensitive to chemo-attraction by CXCL12 and CXC3L1 [ 32 ] may be an explanation for a preferential localization of these effector cells in melanoma lesions. In particular, this finding suggests that the microenvironment of melanoma metastases is rich of fractalkine (CX3CL1) which is a potent chemo-attractant released by endothelial cells stimulated by interferons [ 33 ]. Overall, the presence of these and other ( KLRG1 ; killer cell lectin like receptor subfamily G, member 1 and KLRK1 ; killer cell lectin like receptor subfamily K, member 1 and the interleukin-21 receptor) natural killer cell-related genes suggests potent chemo-attraction toward natural killer cells by the tumor micro-environment of subcutaneous and cutaneous melanoma metastases. This is also emphasized by the high expression of interleukin-21 receptor which is usually expressed by natural killer cells and stimulates their cytolytic activity upon ligation with interleukin-21 produced by activated T cells [ 34 , 35 ]. The constitutive expression of interferon regulatory factor ( IRF )-7 implicated in the amplification of the innate immune response [ 36 ] through interactions with the NF-κB pathway [ 37 ] may lead to the activation of various types of type I interferons [ 38 ]. More puzzling is the constitutive expression of interleukin-16, a pleiotropic cytokine with predominant chemo-attractant activity for CD4+ T cells [ 39 ] and CD4+ eosinophils [ 40 ]; a relationship between this cytokine and melanoma metastases has never been observed before. In summary, the immunological signature portrayed by subcutaneous melanoma metastases is that of an active innate immune response centered on natural killer cells. More broadly, the preferential expression of genes with immune function in melanoma lesions compared with other tumors suggests that this cancer is constitutively immunologically active and this status may predispose metastatic melanoma to respond to general or antigen-specific immune manipulation. Figure 3 Eisen's clustering of immunologically relevant genes selected from clusters e and f-j . To the right the identity of the genes included in cluster e is shown. Table 3 Immune-relevant genes specifically up-regulated by sub-cutaneous melanomas Clone ID Location Gene AVERAGE t -test (p 2 -value) SQ Other SQ vs Oth Me vs Oth 295868 1p34 LAPTM5 0.43 -0.68 2.00E-04 3.00E-04 P37265 1p34.3 LCK 0.55 -0.58 1.00E-04 6.00E-06 2563224 1p36.2 PIK3CD 0.8 -0.88 3.00E-07 5.00E-15 842871 1q12 PDE4DIP 0.58 -0.21 5.00E-04 9.00E-05 773509 1q21.3 SNX27 1.05 -0.88 9.00E-11 7.00E-16 701332 1q22 IFI16 0.25 -0.39 2.00E-04 1.00E-05 472009 1q42.1 DISC1 0.35 -0.26 1.00E-07 9.00E-08 746229 2q11.2-q MAP4K4 0.15 -0.24 7.00E-04 6.00E-05 840466 2q12-q13 MARCO 0.34 -0.28 3.00E-05 2.00E-04 328542 2q24-q3 GALNT3 0.51 -0.4 4.00E-04 1.00E-03 825715 2q37.1 SP110 0.71 -0.59 9.00E-07 3.00E-09 283023 3p21 CX3CR1 0.31 -0.34 2.00E-05 4.00E-10 1605539 4p16.3 IDUA 0.27 -0.29 4.00E-06 6.00E-06 724932 5q35 GRK6 0.43 -0.19 4.00E-05 3.00E-05 753587 6p21.3 BTN3A3 0.49 -0.43 2.00E-05 5.00E-06 753236 6p21.3 TAP2 0.31 -0.42 2.00E-04 1.00E-07 752557 6p21.3 GPSM3 0.42 -0.42 1.00E-04 3.00E-06 2549448 6q21 FYN 0.6 -0.45 1.00E-07 2.00E-07 2306953 8q13.3 LY96 1.01 -0.32 3.00E-06 2.00E-08 645332 10p12 NEBL 0.23 -0.23 6.00E-04 2.00E-04 1631391 11p11.2 BHC80 0.35 -0.29 8.00E-04 4.00E-04 686164 11p11.2 DGKZ 0.44 -0.21 2.00E-04 4.00E-04 487115 11p11.2 PTPRJ 0.78 -0.4 3.00E-09 5.00E-07 151430 11p13 CD44 0.71 -0.22 1.00E-03 2.00E-05 740117 11p15.5 IRF-7 0.53 -0.3 4.00E-05 3.00E-04 P33303 11p15.5 LSP1 0.55 -0.4 1.00E-03 2.00E-05 1850690 11q23.3 BLR1 0.36 -0.36 6.00E-05 2.00E-04 2120815 12p12-p1 KLRG1 0.51 -0.44 1.00E-04 5.00E-04 34637 12p13 CD27 0.72 -0.54 4.00E-04 1.00E-04 1517162 12p13.2- KLRK1 0.55 -0.53 5.00E-04 6.00E-04 1569551 12q13.11 CSAD 0.37 -0.45 2.00E-04 6.00E-06 429186 13q21.33 LMO7 0.41 -0.37 5.00E-06 4.00E-19 P41256 15q26.3 IL-16 0.64 -0.58 4.00E-05 2.00E-06 P14913 16p11 IL-21R1 0.48 -0.43 6.00E-06 6.00E-04 P07382 16p11.2 ITGAL 0.55 -0.48 2.00E-05 3.00E-06 P12753 16p13.3 NK4; 0.32 -0.3 4.00E-05 3.00E-06 206795 17p ASGR2 0.57 -0.53 8.00E-05 6.00E-06 488575 17p11.2 ULK2 0.35 -0.17 3.00E-06 1.00E-04 155717 17q23 CD79B 0.44 -0.41 3.00E-05 2.00E-11 156343 17q24.2 MAP3K3 0.62 -0.46 4.00E-06 7.00E-11 P38436 17q25 CARD14 0.54 -0.33 4.00E-08 2.00E-08 1551273 19p12 MEF2B 0.19 -0.21 7.00E-05 1.00E-09 814377 19p13.1 BRD4 0.9 -0.7 6.00E-06 2.00E-16 2010562 19p13.3 MYO1F 0.55 -0.62 9.00E-04 7.00E-05 824384 19p13-q1 CD37 0.64 -0.74 1.00E-03 7.00E-04 788272 19q13.1 CLC 0.61 -0.64 7.00E-06 3.00E-06 815239 19q13.13 ARHGEF1 0.38 -0.42 3.00E-05 1.00E-04 683276 19q13.33 CARD8 0.86 -0.64 1.00E-08 3.00E-05 277906 19q13.4 LILRB1 0.89 -0.51 4.00E-04 5.00E-04 202897 19q13.4 LILRB2 0.72 -0.61 4.00E-04 1.00E-06 2072768 20q12 NCOA3 0.69 -0.36 4.00E-06 2.00E-05 SQ = Average Cy5/Cy3 ratios of10 frozen samples from cutaneous and subcutaneous metastases as described in Table I. Oth = Sample from 80 primary tumors other than melanoma and RCC with the exclusion, in this table of lymph nodal metastases from colorectal cancer (see Table I). Complete and extended gene name is available at A second and smaller group of immunologically-related genes was identified and included genes that segregated separately in clusters f to j . These genes had an expression profile opposite to the immune-related genes seen included in cluster e and appeared over-expressed in subcutaneous compared to lymph node metastases. Two granzyme-related genes were found strongly up-regulated in cluster e including granzyme A and M. This observation contrasted with the increased expression of cathepsin F and L in cluster f to j suggesting an opposite regulation of these genes involved in cell death or survival. Subcutaneous metastases-associated genes It has been reported that subcutaneous metastases of melanoma are more responsive to immunotherapy with interleukin-2 than lymph nodal and visceral metastases [ 16 ]. Therefore, we identified genes differentially expressed in the former compared with the latter. Since no material from visceral metastases was available, we limited the comparison to subcutaneous versus lymph nodal metastases. Overall, clusters g - j appeared to demonstrate a preferential expression of genes in subcutaneous metastases independent of the technique used for biopsy (excision versus FNA). In particular, cluster g contained a small node of 47 clones highly expressed in subcutaneous metastases that included PRAME and TRP-1 . This cluster also included the renal tumor antigen RAGE which has been previously shown to be highly expressed by melanomas [ 41 ] and melanophilin and the s100 protein often associated with clinical parameters in melanoma [ 42 ]. Interestingly, closely linked to PRAME was the pattern of expression of the serine/threonine-specific protein kinase B-RAF . This gene is mutated in approximately 70 % of melanomas and it is often over-expressed [ 43 ]. Although several of these genes had been associated with melanoma their co-ordinate expression has never been previously appreciated. Overall, the identity of the genes over-expressed in subcutaneous metastases did not offer an obvious explanation for the increased immune responsiveness of these lesions and more extensive understanding of their relationship will be necessary in the future. Genes differential expressed by melanoma and RCC samples compared with other solid tumors We then pooled together melanoma and RCC samples data to identify genes commonly expressed by these tumors and not by tumors of other histology. Significance was assessed by a two-tailed unpaired student's t test and identified 4,221 genes at a cut off p 2 -value of ≤ 0.001. The data set was then filtered using the Cluster Program (Stanford, CA) selecting genes that were expressed in at least 80 % of the experiments and for which a Cy5/Cy3 log 2 ratio ≥ 2 was present in at least one experiment. Two-thousand eight hundred and forty-three genes resulted from this filter. Because of the predominance of melanoma lesions (69 melanoma lesions compared to 14 RCC) the genes identified strongly represent differences between melanomas and other tumors. Therefore, we identified among them those that were not differentially expressed between melanoma and RCC samples to identify those genes that are truly uniquely expressed by the two immune responsive cancers. Two-thousand three hundred and fifty-eight genes were expressed similarly between the two types of cancer (at a t test p 2 -value > 0.05). A significant number of genes commonly expressed by melanoma and RCC and not by other tumors had no known function (681 genes). The remaining 1, 677 genes were further analyzed by separating those up-regulated from those down-regulated in melanoma and RCC compared with other tumors. The genes up-regulated in RCC and melanoma were considered those with a median Log Ratio above 0.3 in either RCC or melanomas ( a selection of these genes is shown in Table IV ). This analysis selected 199 genes. A proportion of genes appeared to be specifically related to lymph nodal and immune infiltration as they were particularly up-regulated in melanoma metastases to lymph nodes and in lymph node metastases obtained from patients with CRC ( orange vertical bar , Figure 4 ). These genes included annotations related to immunological function. A set of genes was specifically expressed in cutaneous metastases of melanoma and in RCC and not other tumor samples ( dark blue vertical bar , Figure 4 ). These genes included microphtalmia transcription factor MITF [ 17 , 44 ]. that has been shown previously to exert a central role in the regulation of transcriptional activity of melanoma cells. Similarly, enolase-2 (previously known to be up-regulated in RCC) [ 11 ] was found to be over-expressed in common between the two histologies. This is somewhat surprising since immunohistochemical analysis has used lack of staining for enolase-2 as a reliable method to differentiate malignant melanoma (enolase-2 negative) from Merkel cell carcinoma [ 45 ]. It is possible, that although identifiable at the transcriptional level, enolase-2 is not processed into a protein in melanomas. On the other hand, enolase-2 has been shown to be expressed in approximately 90 % of canine oral melanomas [ 46 ]. In addition, the macrophage migration inhibiting factor ( MIF ) which is a modulator of cell cycle progression and angiogenesis in melanoma [ 47 , 48 ]. was found co-expressed by melanoma and RCC lesions. MIF has modulatory properties on natural killer cell mediated lysis of cancer cells contributing, therefore, to an immune privileged microenvironment in uveal melanoma [ 49 ]. Two genes coding for adhesion molecules; L1 cell adhesion molecule ( LCAM ) and melanoma cell adhesion molecule ( MCAM ) were also up-regulated in both lesions and may play an important role in mediating migration of immune cells to the tumor deposits [ 50 ]. Finally, it is remarkable that serologically defined colon cancer antigen 8 was specifically expressed by melanoma and RCC while was completely absent in colon cancers underlying the need for a better nomenclature of newly identified genes. Table 4 Selected genes constitutively expressed by RCC and melanoma metastases. UNIQID NAME Extended Name Median log2 Cy5/Cy3 Average log2 Cy5/Cy3 t -test* RCC MEL OTH RCC MEL OTH p 2 -value 274276 IFIT2 interferon-induced protein with tetratricopeptide repeats 2 0.74 0.30 -0.28 0.54 0.18 -0.23 0.06 191173 ITGB7 integrin, beta 7 0.17 0.33 -0.26 0.14 0.30 -0.26 0.51 191169 FLT3LG fms-related tyrosine kinase 3 ligand 0.18 0.32 -0.27 0.31 0.19 -0.20 0.53 187264 CORO1A coronin-like protein p57=actin binding protein p57 0.38 0.13 -0.19 0.47 0.12 -0.17 0.16 189684 SP110 SP110 nuclear body protein 0.22 0.60 -0.56 0.26 0.44 -0.42 0.27 279561 TNFRSF7 CD27 -0.06 0.65 -0.39 -0.09 0.45 -0.35 0.07 279871 CD37 CD37 antigen 0.09 0.56 -0.56 0.33 0.47 -0.38 0.72 276143 TAP2 transporter 2 0.23 0.33 -0.21 0.27 0.31 -0.24 0.86 281103 sialic acid binding Ig-like lectin 7=D-siglec=expressed in dendritic cells 0.33 0.26 -0.34 0.27 0.24 -0.24 0.86 279699 BTK btk = Bruton agammaglobulinemia tyrosine kinase \|\| -0.04 0.45 -0.28 -0.09 0.34 -0.26 0.05 274604 CST7 cystatin F (leukocystatin) \|\| -0.14 0.37 -0.29 -0.07 0.45 -0.34 0.06 281440 ITGB7 CD103 beta=Integrin beta 7 \|\| 0.36 0.39 -0.25 0.31 0.38 -0.35 0.67 191157 KLRG1 killer cell lectin-like receptor subfamily G, member 1 \|\| 0.32 0.40 -0.17 0.35 0.23 -0.25 0.39 274016 RASGRP1 RAS guanyl releasing protein 1 (calcium and DAG-regulated) \|\| 0.48 0.38 -0.29 0.36 0.30 -0.29 0.78 274444 ITGAL integrin, alpha L (antigen CD11A (p180)\| 0.34 0.57 -0.43 0.30 0.33 -0.31 0.88 282504 CX3CR1 chemokine (C-X3-C motif) receptor 1 0.84 0.66 -0.53 0.62 0.51 -0.50 0.76 274267 KLRK1 killer cell lectin-like receptor subfamily K, member 1 0.80 0.33 -0.20 0.71 0.34 -0.38 0.14 187290 LILRB1 LIR-7=PIR homologue\| 0.11 0.67 -0.15 0.12 0.49 -0.41 0.20 186380 SLC2A3 solute carrier family 2 (facilitated glucose transporter), member 3 0.14 0.34 -0.21 0.34 0.36 -0.34 0.94 188111 CD3Z CD3Z antigen, zeta polypeptide (TiT3 complex) 0.09 0.42 -0.30 -0.01 0.35 -0.27 0.10 186528 SLA SLAP=src-like adapter protein 0.38 0.31 -0.24 0.32 0.33 -0.31 0.98 185279 ASGR2 asialoglycoprotein receptor 2\| 0.28 0.61 -0.33 0.17 0.45 -0.40 0.16 187450 LILRB2 leukocyte immunoglobulin-like receptor, subfamily B, member 2 0.10 0.65 -0.45 0.13 0.54 -0.44 0.07 184382 FGR Gardner-Rasheed feline sarcoma viral (v-fgr) oncogene homolog\| 0.57 0.23 -0.29 0.40 0.27 -0.28 0.49 190623 MYO1F myosin IF\| 0.18 0.50 -0.22 0.16 0.46 -0.38 0.24 188800 PILRA paired immunoglobin-like type 2 receptor alpha 0.16 0.56 -0.08 0.07 0.31 -0.27 0.17 188004 CLC Charcot-Leyden crystal protein\| 0.08 0.51 -0.33 0.08 0.53 -0.44 0.08 186399 PPP3CC protein phosphatase 3, catalytic subunit, gamma isoform (calcineurin A gamma)\| 0.07 0.36 -0.15 0.05 0.21 -0.18 0.17 278997 XLHSRF-1 heat shock regulated 1 -0.12 0.32 -0.09 0.10 0.28 -0.20 0.33 281827 LLT1 lectin-like NK cell receptor 0.46 0.26 -0.33 0.53 0.22 -0.26 0.08 282466 LLT1 lectin-like NK cell receptor 0.22 0.38 -0.23 0.23 0.32 -0.32 0.66 189527 FMNL1 formin-like 1 0.46 0.43 -0.25 0.44 0.24 -0.26 0.32 282550 natural killer cell transcript 4 -0.20 0.41 -0.29 0.00 0.30 -0.24 0.15 282534 B-cell CLL/lymphoma 2 0.05 0.38 -0.38 -0.05 0.33 -0.34 0.05 282477 ICOS inducible T-cell co-stimulator\| -0.07 0.37 -0.18 -0.07 0.28 -0.26 0.07 282624 granzyme A granzyme A (granzyme 1, cytotoxic T-lymphocyte-associated serine esterase 3)\| -0.10 0.58 -0.33 -0.16 0.43 -0.31 0.06 * Two-tailed un-paired t test between RCC and MEL samples. RCC = Renal cell carcinoma; Mel = melanoma lesions; Oth = all other tumors in the study (see Table I). Figure 4 Eisen's clustering of genes similarly expressed by RCC and melanoma lesion. To the right the identity of genes most prominently expressed by RCC lesions and cutaneous or subcutaneous melanoma lesions is shown. This is a descriptive study where genes specifically expressed by melanoma metastases were identified comparing a large collection of samples from patients with metastatic cutaneous melanoma with other primary tumors and lymph nodal metastases. A limitation of the study is the lack of other samples including visceral metastases of melanoma and metastases from tumors of other histology. Nevertheless, we considered useful to compile a list of genes characteristically expressed by subcutaneous and lymph nodal lesions of melanoma for reference purposes and we are willing to provide full information about these genes upon request. In spite of the limitations of this study, few general conclusions could be drawn. Materials and Methods Tissue procurement Fourteen primary renal cell carcinoma (RCC) specimens were collected at the Department of Urology of The Johannes Gutenberg-University, Mainz, Germany; one primary melanoma, three in transit metastases, seven cutaneous metastases, thirty-five lymph nodal metastases and two visceral metastases of cutaneous melanoma were collected at the Department of Surgical Sciences, University of Padua, Italy; twenty-one fine needle aspirates of cutaneous melanoma metastases were obtained at the Surgery Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD; seventeen primary epithelial ovarian cancer (EOC) specimens were obtained at the Department of Gynecologic Oncology, MD Anderson Cancer Center, TX; three primary sarcoma, one primary endometrial cancer, one primary laryngeal cancer, two primary breast cancers and one primary colon adeno-carcinoma were obtained from the Tissue Network (Philadelphia, PA); twelve primary carcinomas of the esophageal junction were obtained from the NCI (Division of Cancer Treatment and Diagnosis); thirty-five primary, 16 lymph node metastases and one hepatic metastasis from colorectal adeno-carcinomas were obtained from the Department of Pathology of the University of Pisa, Italy. Specimens were collected as the result of routine operative procedures and portions were frozen for subsequent analysis while the remnant tissue was used for pathological confirmation. Tissue procurement followed standard ethical procedure according to institutional policy. A summary of the specimens studied is presented in Table 1 with their order reflecting their distribution in figures where supervised analyses are shown. RNA preparation, amplification and labeling Total RNA was extracted from frozen material using Trizol reagent according to manufacturer's instructions (Invitrogen, CA) and amplified into anti-sense RNA (aRNA) as previously described [ 10 , 27 , 51 , 52 ]. Although the quantity of starting total RNA was in most cases sufficient for cDNA array hybridization, we have shown repeatedly that the fidelity of aRNA hybridization is at least equal and likely superior to total RNA for transcriptional profiling due to lack of contaminant ribosomal and transfer RNA [ 51 , 53 ]. Therefore, we used aRNA to increase consistency of results particularly when low quality total RNA was documented by Agilent Bioanalyzer 2000 (Agilent Technologies, Palo Alto, CA). After amplification the quality of aRNA was tested with the Agilent Bioanalyzer as previously described [ 52 ]. Total RNA from peripheral blood mononuclear cells pooled from six normal donor was extracted and amplified to serve as constant reference as previously described [ 10 , 27 , 51 , 52 ]. Test and reference RNA were labeled with Cy5 (red) and Cy3 (green) and co-hybridized to a costum-made17.5 K cDNA micro-array . Micro-arrays were printed at the Immunogenetics Section, DTM, CC, NIH with a configuration of 32 × 24 × 23 and contained 17,500 elements. Clones used for printing included a combination of the Research Genetics RG_HsKG_031901 8 k clone set and 9,000 clones selected from the RG_Hs_seq_ver_070700 40 k clone set. The 17,500 spots included 12,072 uniquely named genes, 875 duplicated genes and about 4,000 expression sequence tags. Data analysis All statistical analyses were performed using the log 2 -based ratios normalizing the medial log 2 ratio value across the array equal to zero. Validation and reproducibility were performed using our internal reference concordance system as previously described [ 54 ]. Unsupervised clustering was performed according to the Eisen's Pearson correlation method [ 55 ] and visualized with Tree-View software (Stanford University, CA). Genomic portraits were depicted according to the central method for display using a normalization factor as suggested by Ross et al. [ 56 ]. Details about different tests are discussed in the respective results section. Identification of tumor-specific genes was performed using un-paired 2-tailed Student's t test. The same analyses were performed using un-paired Wilcoxon's non-parametric assessment and provided the same conclusions (not shown). Details of each analysis are presented in the results section. Supplementary Material Additional file 1 AVE Ratio = average Log2 CY5/Cy3 ratio between test and reference sample. The t test p2-value refers to a two-tailed unpaired analysis between the samples mentioned below. RCC = renal cell cancer; MEL = melanoma; Other = tumors other than RCC and melanoma. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC527872.xml
526205	Fear of nuclear war increases the risk of common mental disorders among young adults: a five-year follow-up study	Background Evidence on the relation between fear of war and mental health is insufficient. We carried out a prospective cohort study to find out whether fear of nuclear war is related to increased risk of common mental disorders. Methods Within two months preceding the outbreak of Persian Gulf War in January 1991, 1518 adolescents [mean age 16.8 years, SD 0.9] filled in a self-administered questionnaire. Of the 1493 respondents, 47% gave their written informed consent to participate in the follow-up study. There were no material differences between those who chose to respond anonymously and those who volunteered to give their name and address for the follow-up study. In 1995, the response to the follow-up questionnaire was 92%. Common mental disorders were assessed by 36-item version of the General Health Questionnaire [GHQ]. A score 5 or higher was considered to indicate caseness. We excluded 23 cases which had used mental health services in the year 1991 or earlier and two cases with deficient responses to GHQ. This left 626 subjects for analysis [400 women]. Results After adjusting for significant mental health risk factors in logistic regression analysis, the risk for common mental disorders was found to be significantly related to the increasing frequency of fear for nuclear war, high scores of trait anxiety and high scores of immature defense style. Elevated risk was confined to the group reporting fear of nuclear war once a week or more often [odds ratio 2.05; 95% confidence interval 1.29–3.27]. Conclusion Frequent fear of nuclear war in adolescents seems to be an indicator for an increased risk for common mental disorders and deserves serious attention.	Background Risks of war and terrorism are threatening our health, both directly in actual life and also indirectly by the increasingly violent content of video games and other forms of entertainment. How does this affect mental health? Earlier during the cold war period, fear of war was found to be common among adolescents, and more prevalent among girls than boys [ 1 - 5 ]. Little is known about the influence of fear of war on mental health of adolescents. On one hand, it has been argued that worrying about nuclear war is related to positive aspects of mental health [ 6 ]. On the other, fear of nuclear war has been found to associate with several measures of psychological distress in cross-sectional studies [ 4 , 7 - 9 ]. To our knowledge, no follow-up studies have been published. However, high perceived risk of nuclear war might be related not only to transient psychological distress but also to more long-term mental disorder among vulnerable adolescents. We have followed up a cohort of adolescents first studied during the period of increasing international tension before the outbreak of the Persian Gulf War in January 17, 1991, and report here on the relation between fear of nuclear war at that time and incident common mental disorders five years later. Methods Design Between December 4, 1990, and January 16, 1991, 1518 adolescents from five high schools in Helsinki and five in Jyväskylä, Finland, representing a cross-section of school entrance requirement levels filled in a self-administered questionnaire during an ordinary classroom hour. Of the 1493 respondents, 709 (47%) gave their written informed consent to participate in the follow-up study. There were no significant differences between those who chose to respond anonymously and those who volunteered to give their name and address for the follow-up study with respect to baseline predominance of mature, immature or neurotic defence styles, trait anxiety, trait depression, the number of positive and that of negative life-events, self-esteem, coherence of future, or availability of social support. Anonymous respondents reported less somatic symptoms than those who gave informed consent to follow up. The absolute difference in the symptom score was not very large, however. The mean scores (SE) were 21.8 (0.22) and 22.8 (0.29) for men, 24.2 (0.23) and 25.0 (0.23) for females, respectively [ 10 ]. Of the 709 subjects who gave signed consent, two were excluded from the follow-up due to deficient completion of the baseline questionnaire, and one died. The sample eligible for follow-up comprised 706 subjects. In 1995, the response to the follow-up questionnaire was 92%. Design and sample has been described earlier in more detail [ 10 ]. Participants We excluded 23 cases who reported having used mental health services in the year 1991 or earlier and two cases with deficient responses to GHQ. This left 626 subjects for analysis, of whom 400 were women. At the baseline, the age range was 15 to 19 years (mean 16.8, SD 0.9). Measures Baseline examination in 1990 Frequency of fearing nuclear war during past four weeks (scores in parentheses) was assessed by a question with six options: not at all (0), less than once a week (0.5), 1–2 times a week (6), 3–5 times a week (16), almost daily (22) and daily (28). The Defence Style Questionnaire (DSQ) consisted of 72 statements assessing possible conscious derivatives of 20 defences. It is based on the 88-item version of the Bond's Defense Style Questionnaire [ 11 ]. Andrews et al. [ 12 ] reviewed the items to make the labelling consistent with the Diagnostic and Statistical Manual of Mental Disorders (3rd ed. revised, DSM-III-R) by the American Psychiatric Association [ 13 ]. The defence styles were grouped into three levels: mature, neurotic, and immature defence styles. Individual defences are (mature:) sublimation, humour, anticipation, suppression, (neurotic:) undoing, altruism, idealisation, reaction formation, (immature:) projection, passive aggression, acting out, isolation, devaluation, autistic fantasy, denial, displacement, dissociation, splitting, rationalisation and somatization [ 14 ]. The Trait Anxiety Inventory was used to measure trait anxiety as a general tendency of feeling [ 15 ]. Trait anxiety is used to screen neurotic anxiety problems and vulnerability for anxiety disorders. Depressive trait [ 16 ] was assessed by questions following the style, scoring and response options of the Trait Anxiety Inventory. The questions dealt with a general tendency to have obvious depressive mood. An abbreviated version of the Life Event Checklist [ 17 ] consisted of 20 defined life events considered to be the most common ones among Finnish adolescents and of four open items. Number of negative and that of positive life events was analysed. The Somatic Symptom Score is an abbreviated 14-item version of an original 18-item score used earlier in Finnish studies on adults and adolescents [ 18 ]. The 14 items comprised physical symptoms common in adolescence but only rarely associated with a physical disease, such as headache, abdominal pains, fatigue or weakness, lack of energy, diarrhoea or irregular bowel function. Respondents were asked "Have any of the following symptoms bothered you, and how often during the last six months?" The response options were never, sometimes, quite often, and often or continuously. The self-esteem scale by Rosenberg [ 19 ] consists of ten items measuring the self acceptance aspect of self-esteem. Rosenberg relates positive self-esteem to many social and interpersonal consequences such as less shyness and depression, more assertiveness, and more extra-curricular activities. The response scorings were inverted so that a high total score indicated high self-esteem. Coherence of future was measured by three items (no. 11, 22 and 27) from the Sense of Coherence Scale [ 20 ] relating to the meaningfulness and manageability of one's own personal future. Social support was ascertained by asking "Do you have a significant other person with whom you may discuss your personal activities and problems?". Social class assessment was based on father's occupation or on mother's occupation when the father was not living in the family of the adolescent. Use of the City of Helsinki Social Group Classification divided the sample into four categories: (i) professionals, managers and higher administrative or clerical employees, (ii) lower clerical employees, (iii) skilled workers, and (iv) unskilled workers. Follow-up examination in 1995 The General Health Questionnaire (GHQ) [ 21 , 22 ] is a measure for common mental disorders [ 23 ]. It is a widely used and well-validated self-administered test. The GHQ focuses on discontinuities in normal functioning and the experience of new phenomena of a distressing nature. It covers feelings of strain, depression, inability to cope, anxiety-based insomnia, lack of confidence and other psychological problems [ 24 ]. GHQ has been found to be very accurate at detecting anxiety and depression with anxiety [ 25 ]. We employed the 36-item version, which is derived from the original 60-item questionnaire by excluding items measuring somatic symptoms [ 26 ]. We applied the standard scoring method, counting the two highest response options as pathological. As commonly done earlier [ 27 , 28 ], a score 5 or higher was considered to indicate common mental disorders. Treatment contacts with mental health professionals before the follow-up examination were ascertained in 1995. Statistical analysis Data were analysed with SPSS 11. Logistic regression was used to model the relationship between assumed risk factors and high GHQ score [5 or more]. Initial models included sex, social class, availability of social support [dichotomous variables], age, self-esteem, coherence of future, number of positive and that of negative life-events, neurotic, immature and mature defence styles, trait anxiety, trait depression, somatic symptom score [continuous variables]. Second-level interactions were studied by adding product terms to the models. Because of missing values, the number of cases was lower than 626 in some analyses. Only significant [p < 0.05] confounders remained in the final models. To evaluate relative risk, fear of nuclear war and the significant confounders were categorised and odds ratios with their 95% confidence interval were estimated. Results Of the 400 women, 27.5% reported having feared nuclear war once a week or more often in 1990. The respective figures for men were 226 and 13.7%. Thirty-six per cent of the women and 22.1 % of the men scored 5 or higher on GHQ. The initial full model included all putative confounders under study (Table 1 ). There were no interactions. Significant and almost significant explaining variables were retained in the final model with continuous variables. The risk for common mental disorders was found to be significantly related to high frequency of fear for nuclear war, high scores of trait anxiety and high scores of immature defense style (Table 2 ). While the odds ratios suggested a dose-response relation between fear of nuclear war and common mental disorders, significantly elevated risk was confined to the group reporting fear of nuclear war once a week or more often. This group showed a 2-fold risk compared to subjects that did not report fear of nuclear war (Table 3 ). High immature defense style and high trait anxiety were also related to higher risk for common mental disorders. Applying a GHQ cut-off score 6 did not materially change the results. Table 1 Logistic regression analysis, General Health Questionnaire score on unit change in all potential explanatory variables (n = 607) Explanatory variable Odds ratio Regression coefficient SD p-value Frequency of fearing nuclear war 1.04 0.039 0.015 0.007 Sex 0.75 -0.287 0.231 0.2 Age 1.10 0.093 0.114 0.4 Social class II 1.05 0.052 0.240 0.8 Social class III 0.64 -0.439 0.263 0.095 Social class IV 1.40 0.336 0.559 0.5 Number of positive life events 1.01 0.005 0.041 0.9 Number of negative life events 1.05 0.052 0.056 0.4 Social support 1.07 0.063 0.426 0.9 Self esteem 0.97 -0.029 0.030 0.3 Coherence of future 1.00 -0.005 0.159 0.98 Trait anxiety 1.04 0.042 0.019 0.03 Trait depression 1.10 0.091 0.108 0.4 Mature defense style 0.94 -0.065 0.116 0.6 Neurotic defense style 1.10 0.096 0.120 0.4 Immature defense style 1.32 0.274 0.163 0.09 Somatic symptom score 1.02 0.021 0.025 0.4 Table 2 Logistic regression analysis, General Health Questionnaire score on unit change in significant explanatory variables (n = 621) Explanatory variable Odds ratio Regression coefficient SD p-value Frequency of fearing nuclear war 1.04 0.04 0.014 0.004 Trait anxiety 1.07 0.069 0.014 <0.001 Immature defense style 1.43 0.359 0.143 0.012 Table 3 Logistic regression analysis, General Health Questionnaire (GHQ) score on categorized significant explanatory variables (n = 626) Explanatory variable Number of cases Odds ratio (95% confidence interval) GHQ ≥ 5 GHQ <5 Unadjusted Adjusted Fear of nuclear war never 63 199 1 (reference) 1 (reference) less than once a week 72 151 1.51 (1.01–2.24) 1.35 (0.88–2.05) once a week or more 59 82 2.27 (1.47–3.52) 2.01 (1.26–3.21) Trait anxiety <32 26 167 1 (reference) 1 (reference) ≥ 32 < 38 95 195 3.13 (1.94–5.06) 2.58 (1.58–4.23) ≥ 38 73 70 6.70 (3.95–11.4) 4.48 (2.53–7.91) Immature defense style <3.3 40 159 1 (reference) 1 (reference) ≥ 3.3 < 4.0 56 148 1.50 (0.95–2.39) 1.24 (0.76–2.01) ≥ 4.0 98 125 3.12 (2.02–4.82) 2.01 (1.24–3.25) Discussion A positive association was found between frequent fear of nuclear war at baseline examination and common mental disorders among adolescents in a five-year follow up. The temporal order of exposure and response suggest that this relation could be causal. Our measure for common mental disorders, the GHQ, rates recent change (within the past month) in mental health at follow-up examination, i.e. incident problems. False positives might have included individuals with mild or transient psychological disturbance, which should have biased the association towards the null. Still, the relation was significant. However, some caveats should be discussed. Could the association be due to some confounding factors? We controlled for several potential confounders. Those, known to increase or decrease the risk of mental disorders, included neurotic, immature and mature defence styles [ 29 - 31 ], trait anxiety [ 32 , 33 ], trait depression [ 34 , 35 ], life-events [ 36 , 37 ], somatic symptom score [ 38 ], self-esteem [ 39 ], coherence of future [ 40 , 41 ] and social support [ 42 , 43 ]. Nevertheless, on one hand there always remains the possibility of bias due to some unknown or otherwise not controlled variable, and, on the other, one cannot be sure that such a variable would also be an actual confounder in the data set at hand. In our data, the close correspondences of unadjusted and adjusted risk ratios suggest that no material residual confounding remained [ 44 ]. Adolescents not willing to answer a mental health questionnaire may have more mental health risk factors and problems than participants. However, we found no significant differences between the anonymous and identifiable respondents in possible mental health risk factors analysed except that anonymous respondents reported slightly more somatic symptoms than those who identified themselves. The difference was, however, small in absolute terms (data presented above in section on design). This suggests that subjects with high risk were not underrepresented in the present sample. The degree of perceived threat of nuclear war may depend on several factors, such as (i) actual presence and size of the nuclear weapon arsenal, (ii) actual political tensions and threats, (iii) media coverage of the former, (iv) mental, conscious and unconscious processing of information, and (v) psychological developmental influences specific to adolescence. Part of the fear may be based on realistic evaluation of the threat. Our baseline examination was carried out within two months before the outbreak of the Persian Gulf War in January 1991 and before the reductions in nuclear weapon arsenals in the United States and in Russia started. A quote from a novel describing the life experience of one teen-age girl during the pre- detente period may be illustrative: "One was obliged to think about something important. One was obliged to think about the crisis between China and Soviet Union. A war could break out, the World War III and nuclear fallout would burn everything. The familiar fear for war pressed me inside so that it was difficult to breathe." Laura Honkasalo. Sinun lapsesi eivät ole sinun. Jyväskylä: Gummerus, 2001, p. 132. But similar experiences were not unknown among boys either, as witnessed by a seasoned cook from New York: "I grew up thinking the Big One could come at any moment, and this country – or fear of it, the way my country reacted to the threat – radicalized, marginalized, and alienated me in ways that still affect me." Alan Bourdain. A cook's tour in search of the perfect meal. London: Bloomsbury, 2001. p. 80. Widespread media coverage on any potential danger may bring about considerable increase in perceived fear [ 45 ]. Mass media have been found to be the most important source of information about the issue of nuclear war among adolescents in Finland [ 5 ]. Perceptions of the threat of nuclear war as well as other dangers are processed mentally. Conscious or unconscious intentions are often projected to or mixed with dangerous external events, and they may distort the association between the actual threat of war and perceived fear. There is growing evidence that violent films and video games may trigger fear, aggression and violence among adolescents vulnerable to such content [ 46 ], and perceived fear of nuclear war might cause mental distress in vulnerable adolescents in similar vein. Studies on the prevalence of fearing or worrying about nuclear war during periods of low political tension suggest that this phenomenon is common in adolescence and disappears or at least diminishes later in life [ 47 ]. Cognitive maturation and lessening of egocentrism seem to explain why fears with a major irrational component decrease from early adolescence to adulthood [ 48 ]. Global threats may vary in time as well as in their appraisal. In addition to old risks of nuclear war and aircraft hijacking, international terrorism and biological warfare loom at present. How should we handle these risks? We might inquire into the fears of our patients, appraise the risks realistically, point out that widespread media coverage tends to exaggerate the risks, and, as Durodié and Wessely [ 49 ] point out, suggest that we should not become victims of our fears. Conclusions A clear positive association was found between fear of nuclear war and common mental disorders among adolescents. Fear of nuclear war may either be a risk indicator produced by an underlying vulnerability to psychopathological process or have a more direct causal role in the onset of mental disorder among adolescents. In either case, frequent fear of nuclear war in adolescence seems to be an indicator for an increased risk for common mental disorders that deserves serious attention. Competing interests The authors declare that they have no competing interests. Authors' contributions KP and JL planned and designed the study. KP wrote the study proposal and received funding. KP, TA-S, AT-H, MM and JL designed the follow-up, supervised the data collection, and interpreted data. KP analysed data and drafted the paper. KP revised it with contributions from all authors. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526205.xml
548290	An online operational rainfall-monitoring resource for epidemic malaria early warning systems in Africa	Periodic epidemics of malaria are a major public health problem for many sub-Saharan African countries. Populations in epidemic prone areas have a poorly developed immunity to malaria and the disease remains life threatening to all age groups. The impact of epidemics could be minimized by prediction and improved prevention through timely vector control and deployment of appropriate drugs. Malaria Early Warning Systems are advocated as a means of improving the opportunity for preparedness and timely response. Rainfall is one of the major factors triggering epidemics in warm semi-arid and desert-fringe areas. Explosive epidemics often occur in these regions after excessive rains and, where these follow periods of drought and poor food security, can be especially severe. Consequently, rainfall monitoring forms one of the essential elements for the development of integrated Malaria Early Warning Systems for sub-Saharan Africa, as outlined by the World Health Organization. The Roll Back Malaria Technical Resource Network on Prevention and Control of Epidemics recommended that a simple indicator of changes in epidemic risk in regions of marginal transmission, consisting primarily of rainfall anomaly maps, could provide immediate benefit to early warning efforts. In response to these recommendations, the Famine Early Warning Systems Network produced maps that combine information about dekadal rainfall anomalies, and epidemic malaria risk, available via their Africa Data Dissemination Service. These maps were later made available in a format that is directly compatible with HealthMapper, the mapping and surveillance software developed by the WHO's Communicable Disease Surveillance and Response Department. A new monitoring interface has recently been developed at the International Research Institute for Climate Prediction (IRI) that enables the user to gain a more contextual perspective of the current rainfall estimates by comparing them to previous seasons and climatological averages. These resources are available at no cost to the user and are updated on a routine basis.	Introduction It is estimated that more than 110 million Africans live in areas prone to epidemics of malaria. Populations in these areas are infrequently challenged by malaria and, therefore, do not fully develop acquired immunity. As a result, the disease remains life threatening to all age groups. The impact of malaria epidemics could be greatly reduced by timely detection or, ideally, by prediction and prevention through vector control and deployment of appropriate drugs [ 1 ]. Rainfall is recognized as one of the major factors influencing variability in malaria transmission in warm semi-arid and desert-fringe areas of the Sahel, the Greater Horn and Southern Africa. Explosive epidemics may occur in these regions after excessive rains, usually with a lag-time of several weeks during which time mosquito vector populations and malaria infections increase rapidly. Epidemics can be especially severe among communities stressed by recent periods of drought and poor food security. Recent research has found that rainfall estimates would be able to provide useful epidemic early warning information, even in highland-fringe settings, such as those in Kenya and Ethiopia, where temperature is also an important limiting factor for the development of the malaria parasite [ 2 - 4 ]. Consequently, rainfall monitoring forms one of the essential elements for the development of integrated Malaria Early Warning Systems for sub-Saharan Africa, as outlined by the World Health Organization [ 5 , 6 ]. During a meeting of the Roll Back Malaria Technical Resource Network on Prevention and Control of Epidemics (RBM-TSN) it was decided that immediate benefit could be realized from the routine availability of a simple indicator of changes in epidemic risk in these regions of marginal transmission [ 7 ]. The indicator was to be based on the difference between current rainfall (derived from meteorological satellite estimates) and the expected (average) for the particular time of the year; results were to be made available on the internet in a frequently updated format. The purpose was to provide timely alerts to malaria control programme staff and RBM partners working in areas of increased epidemic risk [ 8 ]. The following article provides an update on existing online rainfall monitoring resources and a description of a new tool that has been developed to address remaining needs of the malaria control community Discussion Following discussion among members of the RBM-TSN a consensus map of epidemic risk zones was produced [ 7 ]. The map, shown in Figure 1 , was used as a mask to exclude areas where malaria transmission is considered absent or endemic, as opposed to epidemic. This mask is based purely on climatic constraints to malaria transmission, and does not yet account for areas in the northern and southern margins of the continent where control has eliminated malaria risk. Figure 1 Epidemic risk zones in Africa (adapted from [1]). The epidemic risk map was then combined with rainfall anomaly data (i.e., the difference between observed rainfall and the expected, i.e. average, rainfall for a particular time of the year) to provide a simple indicator of changes in risk in epidemic prone areas. Figure 2 illustrates the resulting dekadal (i.e., ~10-daily) rainfall anomaly maps, which are updated approximately every 10 days, and have been available in experimental form through the Africa Data Dissemination Service (ADDS) since June 2002. The ADDS is an operational part of the Famine Early Warning Systems Network (FEWS NET) which is maintained by the United States Geological Survey (USGS) and supported by the U. S. Agency for International Development (USAID). The maps can be accessed at: under "RFE Anomaly – Malaria", where the anomaly map for the most recent dekad is displayed along with documentation on how the map is produced. The existence of this online monitoring resource was publicized and their use and validation by control services and researchers was encouraged [ 8 ]. The rainfall estimate data underlying these maps was tested against laboratory-confirmed malaria incidence figures for selected districts in Southern Africa, where they showed a good association [ 9 ]. Figure 2 Rainfall Anomalies in Zones with Malaria Epidemic Potential: 21–31 December 2004 In the year following the launch of the ADDS dekadal rainfall anomaly maps, WHO commissioned field visits to a number of epidemic prone countries to evaluate whether the National Malaria Control Programmes were aware of this resource and how useful they considered it may be for their efforts. Sudan, Uganda, Niger, Mali and Burkina Faso received field visits. In general, all of the control programmes had been aware of the rainfall anomaly maps, but only those in Uganda and Sudan had monitored them regularly during the previous year. The control programmes in the Sahelian countries did not agree with the epidemic risk zone used in the mask because their recent experience was that epidemic outbreaks had occurred beyond the northern boundary of the epidemic risk zone. This was also partly true in Sudan where epidemic outbreaks have been known to occur along the Nile River margins in the northern half of the country. Uganda's malaria control programme, however, had found the maps to be reasonably accurate and a useful monitoring resource. Further dialogue with malaria control programmes in West Africa and Southern Africa also raised the point that a single dekadal rainfall anomaly map could raise an alert; when in fact the rainfall levels were not abnormally high – but just 10 days earlier than 'normal'. This suggested that additional information about the temporal distribution of rainfall was necessary. In order to respond to these issues, USGS and WHO-HealthMapper agreed to collaborate on the development of the dekadal anomaly maps in a format which could be downloaded, viewed and archived by surveillance staff directly in HealthMapper, a basic mapping and surveillance software developed by WHO's Communicable Disease Surveillance and Response Department . In addition to the most recent map, it is possible to download the dekadal maps for the previous six months and begin to construct a seasonal time series. The integration of the rainfall anomalies maps within HealthMapper also allowed the users to improve their analyses by combining ancillary data related to malaria directly on top of the rainfall anomalies maps for their country. Figure 3 provides an example for Niger. Figure 3 10 daily rainfall anomaly map for Niger viewed in the HealthMapper Staff working at the International Research Institute for Climate Prediction (IRI) have since developed a web-based Malaria Early Warning System (MEWS) interface that enables the user to gain a broader contextual perspective of the current rainfall season by comparing it to previous seasons and climatological averages. The interface is in the IRI Data Library and takes the form of an online 'clickable map' of Africa: . It displays the most recent dekadal rainfall map (Figure 4 ) over which national and district administrative boundaries and the epidemic risk zone can be overlaid (in this case as a guide rather than an absolute mask which may have excluded districts of local interest). These visual features can be toggled on or off and the user can zoom in to any region for more clarity. The user can 'zoom' into a more localized region of interest. Dekadal rainfall can be spatially-averaged over a variety of user-selected areas, including administrative districts and 11 × 11 km, 33 × 33 km, 55 × 55 km and 111 × 111 km boxes. Upon the selection of this sampling area and a specific location of interest (by a click on map at the location of interest), four time-series graphs are generated (Figure 5 ). These time-series provide an analysis of recent rainfall with respect to that of recent seasons and the overall climatology. A description of the time-series figures, the data used and its source is also provided. Figure 4 MEWS 'Clickable Map' for Rainfall Monitoring: 21–31 December 2004 Figure 5 Summary information on current rainfall/seasonal development and expected rainfall for location of interest. Conclusions Access to frequently-updated rainfall information is an important requirement for the development of integrated early warning systems for malaria and other climate sensitive diseases [ 6 , 10 ]. These operational rainfall monitoring tools have been developed primarily for application in warm semi-arid regions where rainfall anomalies are the main determinant of epidemic outbreaks, however they may also be an important information source for highland-fringe epidemic settings. They are offered as an experimental resource for testing within MEWS applications in Africa – and may be modified in future in response to user feedback and further evaluation. While it is recognized that much of Africa does not (yet) have easy access to the internet, email is becoming more prevalent and it is now relatively easy for regional support centres, such as the WHO-Intercountry Programme for Malaria Control in Southern Africa, to prepare bulletins with malaria relevant climate data for distribution by email and courier to district health teams in epidemic prone areas as part of an overall MEWS process [ 11 ].	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548290.xml
526211	Feeding of soy protein isolate to rats during pregnancy and lactation suppresses formation of aberrant crypt foci in their progeny's colons: interaction of diet with fetal alcohol exposure	Soy protein isolate (SPI) in the diet may inhibit colon tumorigenesis. We examined azoxymethane (AOM)-induced aberrant crypt foci (ACF) in male rats in relation to lifetime, pre-weaning, or post-weaning dietary exposure to SPI and also within the context of fetal alcohol exposure. Pregnant Sprague Dawley rats were fed AIN-93G diets containing casein (20%, the control diet) or SPI (20%) as the sole protein source starting on gestation day 4 (GD 4). Progeny were weaned on postnatal day (PND) 21 to the same diet as their dams and were fed this diet until termination of the experiment at PND 138. Rats received AOM on PND 89 and 96. Lifetime (GD 4 to PND 138) feeding of SPI led to reduced frequency of ACF with 4 or more crypts in the distal colon. Progeny of dams fed SPI only during pregnancy and lactation or progeny fed SPI only after weaning exhibited similarly reduced frequency of large ACF in distal colon. Number of epithelial cells, in the distal colon, undergoing apoptosis was unaffected by diet. SPI reduced weight gain and adiposity, but these were not correlated with fewer numbers of large ACF. Lifetime SPI exposure similarly inhibited development of large ACF in Sprague Dawley rats whose dams were exposed to ethanol during pregnancy. In summary, feeding of SPI to rat dams during pregnancy and lactation suppresses numbers of large ACF in their progeny, implying a long-term or permanent change elicited by the maternal diet. Moreover, results support the use of ACF as an intermediate endpoint for elucidating effects of SPI and its biochemical constituents in colon cancer prevention in rats.	Background Colorectal cancer is the third leading cause of cancer-related deaths in the U.S.; an estimated 147,500 new cases of this disease will have occurred in the U.S. during 2003 [ 1 ]. Globally, this cancer is a significant health problem as its incidence is increasing with the burgeoning of the aged population and with 'Westernization' of diets. Most recently, the cancer incidence rates for the ascending colon have increased whereas those for all other colon subsites (transverse, descending, sigmoid and rectum) have stabilized or declined slightly [ 2 , 3 ]. The incidence of colorectal cancer, like that for breast and prostate cancers, is lower in Asian than American and European populations [ 4 ]. This has implied a possible protective effect of the Asian diet and of soy foods in particular, on colon cancer incidence. Epidemiological studies are generally supportive of the postulated protection against colorectal cancer incidence by consumption of soy components and soy foods [ 4 - 6 ]. However, these studies were not designed to decipher possible effects of lifetime vs. developmental stage-specific dietary exposure to soy. In this regard, soy consumption during adolescence may preferentially reduce subsequent risks for breast cancer in later adults [ 7 , 8 ]. Soy foods are the main dietary sources of isoflavones, which are implicated in cancer prevention [ 4 , 5 , 9 ]. Soy foods are a source of other potentially cancer-preventive substances as well, including saponins, protease inhibitors, and other bio-active peptides and proteins [ 9 - 13 ]. However, the literature concerning effects of pure isoflavones or processed soy products (soy flour, soy protein) in animal models of colon cancer is mixed. Many investigators utilized the rat and administered a chemical carcinogen, either dimethylhydrazine (DMH) or azoxymethane (AOM). Both agents rapidly induce formation of aberrant crypt foci (ACF) and subsequent development of colon adenomas and adenocarcinomas. Investigators have utilized ACF number and type, tumor number and type, or the combination, as endpoints to examine effects of soy and soy constituents on colon cancer. Dietary genistein (the predominant soy isoflavone) was inhibitory to ACF formation in AOM-treated rats [ 14 , 15 ]. Order of protection (measured as ACF number) was genistein > defatted soy flour > full-fat soy flakes > soy concentrate (isoflavone-depleted) [ 16 ]. Similarly, soy bean saponins inhibited ACF incidence in AOM-treated mice at 14 weeks post-initiation [ 11 ]. However, in the study of Gee et al ., [ 17 ], feeding of isoflavone-containing soy protein isolate or of genistein (with casein) for 7 days prior to DMH treatment (and switching to casein diet thereafter) actually promoted ACF numbers in the distal colon; whereas, feeding of these same diets for 42 days immediately after carcinogen administration had no effect. Davies et al . [ 18 ] formulated diets to mimic the Western type (i.e., high fat, low calcium) diet supplemented with low or high isoflavone-containing soy protein isolates, and ACF and tumors were subsequently measured in AOM-rats. Increased numbers of small ACFs were found at 12 weeks, post-carcinogen administration in the isoflavone-enhanced group. Therefore, there is a lack of consensus for effects of soy or soy components on chemically-induced ACFs in rodents and the underlying basis of these discrepancies is unknown. The picture is also unclear when tumors rather than ACFs are used as the end point. In an early study, soybean protein did not differ from beef protein in terms of relative numbers of colon tumors in DMH-treated rats [ 19 ]. Defatted soybean meal was not protective in the same model [ 20 ]. However, we previously reported the protection afforded by lifetime-feeding of a soy protein isolate, against colon carcinoma in AOM-treated male Sprague Dawley rats [ 21 ]. Dietary genistein, on the other hand, had no effect on colon adenocarcinoma incidence or multiplicity of invasive colon carcinoma, yet actually increased noninvasive and total adenocarcinoma multiplicity [ 22 ]. In contrast, soy protein isolates with two levels of total isoflavones did not elicit differences in colon tumorigenesis in the Min mouse model of intestinal cancer [ 23 ]. However, feeding of a high molecular weight insoluble fraction from proteinase-treated soybean protein isolate suppressed colon tumor numbers in rats [ 24 , 25 ]. The above studies used diets made with soy protein isolates or soy components prepared in different ways and supplemented to varying levels. Furthermore, diets usually were fed just prior to or concurrent with the chemical carcinogen in order to focus on initiation or progression of tumorigenesis. Some studies did not account for the fact that commercial rodent diets can include soy protein; moreover there is significant maternal-fetal transfer of isoflavones in rats fed soy-containing diets [ 26 ]. Thus, pre-exposure to soy constituents during various stages of an animal's life cycle potentially complicates interpretation of the reported results. With the single exception of the study from our group [ 21 ], no studies examined the effects of lifetime (including gestational) exposure, by feeding of soy or purified soy components, on colon tumor or ACF incidence. In view of the significant use of soy-based infant formulae, which accounts for greater than 25% of the infant formula currently sold in the United States [ 9 , 27 ], it is important to examine potential SPI effects on colon tissue pre-disposition to cancer. Here, we utilize male Sprague Dawley rats fed AIN-96G diets formulated with casein or SPI to examine dietary effects on AOM-induced ACF incidence and multiplicity. We also examine effects of dietary SPI at pre- and post-weaning vs. lifetime consumption. Lastly, we confirm the SPI effect on colon ACF biogenesis in a second model, namely, AOM-treated rats whose dams were exposed to ethanol during their pregnancy. Methods Solid Diets Diets contained either casein or SPI as the sole protein source (200 g/Kg diet) and their formulation has been previously described [ 21 , 28 ]. Casein (ALACID 741) was from New Zealand Milk Products (North America) Inc. (Santa Rosa, CA). SPI was a gift from DuPont Protein Technologies (St. Louis, MO). Total isoflavone content was 3.70–3.98 mg/g protein and total aglycone equivalents were 2.13–2.32 mg/g protein for the SPI. Corn oil replaced soybean oil and essential amino acid content was maintained at levels for that of the AIN-93G diet [ 29 ]. Diets were prepared by Harlan Teklad (Madison, WI). Animals Animals were housed in an AAALAC-approved animal facility at the Arkansas Children's Hospital Research Institute; animal use protocols were approved by the University of Arkansas for Medical Sciences Institutional Animal Care and Use Committee. Animals were housed in polycarbonate cages and allowed ad libitum access to diet and water. Animal rooms had constant humidity and a 12-h light-dark cycle. Expt. I. Lifetime, Pre-weaning and Post-weaning Diets Pregnant Sprague Dawley dams from Harlan, Inc. (Indianapolis, IN) were received at gestation day (GD) 4 and immediately assigned in random fashion to casein or SPI diet. At postnatal day (PND) 2, each litter was culled to 5 males and 5 females (females were used in an unrelated experiment). At weaning, animals were divided into four diet groups: lifetime (GD 4 to PND 138) casein, n = 25; lifetime SPI, n = 25; casein to SPI, n = 25; and SPI to casein, n = 25. Diet switchovers were performed at PND 21 and all rats were given AOM on PND 89 and 96. Rats were injected subcutaneously with AOM (Midwest Research Institute) in saline, 15 mg/kg body weight. Animals were weighed weekly from birth and were euthanized at PND 138 for ACF determination or TUNEL assay. Expt. II. Intra-gastric Infusion of Ethanol-containing CAS and SPI Liquid Diets during Pregnancy Pregnant rats at GD 5 were surgically implanted with an intra-gastric cannula as previously described [ 30 ]. Dams were fed casein plus ethanol (n = 5) or SPI plus ethanol (n = 7) by total enteral nutrition (TEN) from GD 6 – GD 19 [ 30 ]. TEN diets were isocaloric and met NRC requirements for normal pregnancy [ 30 ]. Amounts of casein hydrolysate (MPH 955; New Zealand Milk Products) and SPI (Soy Clinical Blend IB1.2; total isoflavone content was 3.98 mg/g protein, total aglycone equivalents were 2.32 mg/g protein; DuPont Protein Technologies) added to liquid TEN diets were 31.5 and 31 g/l, respectively. Ethanol was infused at increasing amounts to reach a maximum of 10 g/Kg body weight. At GD 19, ethanol was no longer fed, however, the TEN diets were infused until parturition and simultaneously, corresponding solid diet was added to cages. After parturition, only water was infused (25 ml/23 h) and solid diets were continued ad libitum . At PND 2, each litter was culled to 5 males and 5 females (females were used in an unrelated experiment). Progeny were weaned to the same diet as for their dam. Number of male progeny allocated to casein and SPI diets was 24 and 29, respectively. Visualization of ACF Fifteen animals of each diet group in Experiments I and II were used for ACF determination. Colon contents were removed by flushing from the cecal end with ~20 ml of PBS via syringe. Each colon was slid onto a 2 ml pipette and was fixed in this position for 10 min in 10% neutral buffered-formalin. The colon was opened, laid flat and placed between sheets of labeled filter paper in fixative in the cold. Tissue was removed from formalin, divided into proximal and distal halves, and stained in 0.2% methylene blue in PBS for 5–7 min or until the tissue had a uniform blue appearance. Tissues were rinsed with PBS for ~1 min and stored in 0.4% formalin-PBS at 4°C. Aberrant crypt foci were viewed immediately after staining using a Nikon AMZ800 stereoscope at 40× magnification with side illumination. Proximal and distal colon halves were reviewed along their entire lengths and all ACF were counted. Aberrant crypt foci were categorized according to crypt complexity (1, 2, 3, 4, 5, etc., crypts per ACF). All colons were scored in blinded fashion by a single observer. Colons that failed to yield useable data due to poor fixation and/or staining were excluded from statistical analysis. TUNEL Colons not used for ACF determination (i.e., whole-mount fixation) were divided into proximal and distal halves and the midpoints of each half taken for fixation. Tissue was fixed in 10% neutral buffered-formalin, processed through a graded series of ethanol and xylene washes, embedded in paraffin, 4 μm sections obtained, and these were subjected to TUNEL assay. The TdT-FragEL DNA Fragmentation Detection kit (Oncogene Research Products, San Diego, CA) was used for this purpose. Approximately 200 crypt columns were examined from each of 4–5 animals in each diet group. Adiposity Body composition data were obtained on anesthetized rats by dual energy x-ray absorptiometry (DXA) using a Hologic QDR 4500A instrument (Bedford, MA). Five rats (at 33 days post-AOM treatment) were randomly chosen from casein and SPI diet groups ( Expt. I ) for DXA analysis. Percentage of global fat (% fat) was determined. Statistical Analyses The ACF endpoints were discrete variables (numbers of crypts, numbers of ACF, etc.) and hence were not normally distributed. We took the natural logarithm of all data points since log-transformed values were less skewed than the original data and more amenable to analysis. However, for simplicity, figures and tables present the original (not log-transformed) data. To examine diet effects, we used the SAS System's (SAS, SAS Institute, Inc., Cary, NC) PROC GLM procedure. Unpaired t tests were also used to examine differences between proximal and distal colon for several endpoints. Incidence of large ACF (with 5 or more crypts per focus) was analyzed using Fisher's Exact Test (SigmaStat for Windows Version 2.03, SPSS Inc.). For all analyses, a P value less than 0.05 was considered significant, while 0.05 < P < 0.1 was deemed marginal. Body weights and body fat content were compared by t-test (SigmaStat). Results Effects of Lifetime Consumption of Casein and SPI on Colonic ACF Frequency In casein-fed animals, the distal half of the colon had 2–3 fold more ACF of each size class than did the proximal half (Fig. 1 ). In rats lifetime-fed casein or SPI, differences in ACF content were observed for distal colon (Table 1 ). SPI feeding led to fewer numbers of ACF with 4, 5 and >5 crypts and as a consequence, a reduced overall ACF crypt multiplicity for distal colon. Crypts/focus was slightly reduced (by ~8%) by SPI in the proximal colon (P = 0.01). SPI did not differ from the casein group in the frequencies of ACF containing 1, 2 or 3 aberrant crypts in either colon region. Figure 1 ACF occurrence in proximal and distal colon of Sprague Dawley rats (n = 12) lifetime-fed casein. Shown are means ± SEM of ACF (per rat) containing: 1, 2, 3, 4, 5 or greater than 5 crypts (5+) per ACF; crypt multiplicity (number of aberrant crypts/focus); total number of ACF; and total number of aberrant crypts (no. ACF × crypts/focus). P values indicate all statistically significant differences between proximal and distal colon. Table 1 Effect of diet on ACF distribution by colon region* Proximal Colon Distal Colon CAS SPI CAS SPI ACF – 1 Crypt 5.50 ± 1.03 6.55 ± 1.35 10.58 ± 1.77 12.55 ± 2.45 ACF – 2 Crypts 9.92 ± 2.28 8.65 ± 1.61 18.33 ± 2.36 16.27 ± 2.81 ACF – 3 Crypts 4.67 ± 0.96 5.18 ± 1.17 11.42 ± 1.57 8.18 ± 1.91 ACF – 4 Crypts 1.50 ± 0.40 a 0.82 ± 0.38 5.83 ± 0.99 b 2.45 ± 0.73 ACF – 5 Crypts 0.42 ± 0.26 0.27 ± 0.20 1.67 ± 0.33 c 0.64 ± 0.47 ACF – 5+ Crypts 0.08 ± 0.08 0.09 ± 0.09 0.42 ± 0.19 d 0.09 ± 0.09 Crypts/Focus 2.17 ± 0.05 a 2.00 ± 0.09 2.38 ± 0.07 c 2.02 ± 0.04 ACF Total 22.08 ± 4.29 21.54 ± 4.08 48.25 ± 5.98 40.18 ± 6.93 Crypt Total 47.92 ± 9.47 44.55 ± 8.98 115.67 ± 14.83 e 83.18 ± 15.55 * CAS, n = 12; SPI, n = 11; shown are means ± SEM per animal for ACF of differing sizes; 5+ = no. ACFs containing 6 or more aberrant crypts; crypt total = sum of ACF × crypts/focus. a P = 0.01, b P = 0.005, c P = 0.001, d P = 0.091, e P = 0.044; P values for differences between diets within each region; SAS. Dietary Switchovers at Weaning and Subsequent ACF Formation To examine the possibility that dietary exposure to SPI over the period encompassing fetal and neonatal development could mimic effects of lifetime SPI, we performed diet switchovers of Sprague Dawley rats at weaning and surveyed their colons six weeks after AOM administration, relative to animal's lifetime-fed SPI diet concurrently. The opposite switchover, from casein to SPI at weaning, was carried out in parallel to examine effects of SPI, from post-weaning through to adulthood. ACF frequency for each diet switchover generally mimicked that for lifetime SPI (Fig. 2 ). Analysis for the relative incidence rather than the mean number (per animal) of the largest ACF (those containing 5 or >5 crypts) for all diet groups is shown in Table 2 . These data further support a protective role for dietary SPI (lifetime, CAS/SPI or SPI/CAS regimens) on appearance of large ACF. Figure 2 Frequency distribution of ACF in Sprague Dawley rats lifetime-fed SPI or switched, at weaning, from CAS to SPI or from SPI to CAS. Analysis of proximal and distal colon halves is shown. Shown are means ± SEM, per rat, of ACF containing: 1, 2, 3, 4, 5 or greater than 5 crypts (5+) per ACF; crypt multiplicity (number of aberrant crypts/focus); total number of ACF; and total number of aberrant crypts. P value indicates the only statistically significant difference between switchover diets and SPI. Table 2 Relative incidence of largest ACFs (5 or >5 Crypts/ACF)* CAS SPI CAS/SPI SPI/CAS % rats with ACF(s) containing 5 crypts Proximal 25 18 0 38 Distal 83 18 a 57 54 Entire 83 36 b 57 69 % rats with ACF(s) containing >5 crypts Proximal 8 9 0 0 Distal 33 9 0 15 Entire 42 18 0 15 * CAS, n = 12; SPI, n = 11; CAS/SPI, n = 7; SPI/CAS, n = 13. a, b Compared to CAS: a P = 0.003; b P = 0.036; Fisher's Exact Test. Apoptosis At six weeks, post-AOM, there were no observable differences in the relative apoptotic state of total colonic epithelium in distal colons of CAS, SPI, CAS/SPI and SPI/CAS groups (Table 3 ). However, the upper third crypt region of the CAS/SPI group had ~2-fold more apoptotic cells than did the lifetime SPI or SPI/CAS groups. Table 3 Effect of diet regimen on TUNEL positive cells in the distal colon a CAS b SPI CAS/SPI SPI/CAS Total c 18.0 ± 2.55 13.8 ± 3.20 24.6 ± 5.80 16.0 ± 3.89 Upper d, e 6.8 ± 3.02 3.2 ± 1.07 11.4 ± 2.02 2.25 ± 0.48 Middle 4.6 ± 0.93 3.2 ± 1.02 9.2 ± 4.68 9.5 ± 3.12 Lower 6.8 ± 2.63 7.2 ± 1.93 4.4 ± 1.29 4.75 ± 0.75 a CAS, n = 5; SPI, n = 5; CAS/SPI, n = 5; SPI/CAS, n = 4 animals; PND 138. b Mean values are expressed as the number of positive cells per 200 crypt columns ± SEM. c Data are for entire crypts. d Data represent upper one-third, middle one-third or lower one-third regions of crypts, respectively. e Overall diet effect (P = 0.024); CAS/SPI > SPI and >SPI/CAS, P < 0.05; One-way ANOVA and Student-Newman-Keuls method. Growth and Body Composition SPI-fed animals weighed less than corresponding casein-fed counterparts (Fig. 3 ). The body weight differences between the casein and SPI groups were evident as early as PND 10 postnatal and prior to weaning (Fig. 3 ). Administration of AOM resulted in temporary cessation of growth and a small amount of weight loss in all groups (Fig. 3 ); however after a short lag period, all animals resumed growth. Growth curves of casein/SPI and SPI/casein switch-over groups were intermediate between those for lifetime casein and SPI groups (data not shown). Analysis of body composition (at 33 days post-AOM treatment) by DXA revealed significant differences in global % fat between groups (CAS > SPI, difference of ~3.3 percentage points; Fig. 4 ) and this somewhat mimicked the observed final differences in body weight. Regression analysis did not identify any significant associations between final body weight and proximal or distal ACF numbers or crypts/focus (Fig. 5 and data not shown). Figure 3 Feeding of casein or SPI to pregnant dams and their progeny elicits differential growth rates. Top panel shows body weight (mean ± SEM) gain in relation to postnatal day (PND) and time of administration of azoxymethane (AOM) for progeny of Sprague Dawley dams. Bottom panel shows divergence in body weights during early postnatal development. P values indicating differences between CAS and SPI groups (t-test) are shown in lower panel. Figure 4 Dietary protein type influences body fat content. DXA was performed on five animals per group (CAS: casein; SPI: soy protein isolate) at 33 days after the second AOM administration. Means (±SEM) are statistically different for the two diets. Figure 5 Lack of association of final body weight with ACF size. ACF in AOM-treated Adult Rats Previously Exposed to Ethanol as Fetuses We confirmed the inhibitory effect of SPI on occurrence of large ACF in a second model, namely, progeny of Sprague Dawley dams that received ethanol + casein or ethanol + SPI by total enteral nutrition (TEN) during gestation and which were weaned to the same diet as their dams (paradigm shown in Fig. 6 ). We chose this model since we were interested in examining how diet, in combination with ethanol, might affect ACF distribution in progeny. As is evident from Fig. 7 , SPI inhibited the occurrence of large ACF relative to the casein diet in animals exposed to ethanol as fetuses. Unlike the results from Expt. I. however, SPI-fed animals exhibited reduced ACF numbers in both proximal and distal colons and these ACF now included those with 3 aberrant crypts (Fig. 7 ). Moreover, there was an increased occurrence of ACF with three or more crypts in the proximal colons of casein-fed rats in Expt. II vs. those in Expt. I. In the absence of a true no-ethanol control for Expt. II, we cannot make any final conclusions about the specific effect of fetal alcohol exposure on ACF frequency in the later adult stage. However, these data do suggest that fetal alcohol exposure favors the development of large ACF which was inhibited by SPI in the diet. Figure 6 Experimental design used for evaluation of diet effects on ACF in progeny of dams exposed to ethanol during pregnancy. Figure 7 Frequency distribution of ACF in rat progeny lifetime fed casein (n = 10) or SPI (n = 14) and whose dams were exposed to ethanol during pregnancy (Fig. 6). Analysis of proximal and distal colon halves is presented. Shown are mean ± SEM, per rat, of ACF containing: 1, 2, 3, 4, 5 or greater than 5 crypts (5+) per ACF; crypt multiplicity (number of aberrant crypts/focus); total number of ACF; and total number of aberrant crypts. P values indicate statistically significant differences between diets. Discussion The objectives of this study were to: a) elucidate effects of SPI on colon ACF frequency in rat models, b) study effects of dietary SPI on somatic growth and adiposity in view of their potential interactions with colon ACF incidence, c) examine developmental and lifetime 'exposures' to dietary SPI and consequent effects on ACF indices, and d) correlate ACF data with our previously published colon tumor data obtained with animals lifetime fed SPI [ 21 ]. ACF may provide a more time- and cost-effective means to study SPI effects on colon cancer prevention in animal models and we sought to further explore this possibility in the current study. We report that SPI reduced the incidence of the largest size classes of ACF in AOM-treated, adult Sprague Dawley male rats and, regardless of whether SPI was fed during GD 4 – PND 21, only after PND 21, or from GD 4 to PND 138. This effect of SPI also was manifested in animals whose dams were exposed to ethanol during pregnancy; thereby suggesting the generality of the SPI effect. ACF have been identified on the colon luminal surface in rats and mice treated with chemical carcinogens (AOM, DMH, and NMU) and in humans with and without overt colon carcinoma [ 31 , 32 ]. AOM stimulates both proliferation and apoptosis in the colonic mucosa [ 33 ] and ACF are thought to be the earliest observable pre-neoplastic lesions to arise in this tissue [ 34 , 35 ]. The validity of ACF as an intermediate biomarker for colon cancer is however, controversial. Larger multi-cryptal ACF are generally correlated with tumor incidence in rodents and humans [ 32 , 36 - 42 ]. Feeding a Western-type diet can induce ACF as well as adenomas and carcinomas in normal mouse colon [ 43 ]. Thiagarajan et al . [ 16 ] reported a trend for diets that promoted ACF numbers to also increase colon tumor numbers. In other studies, however, DMH or AOM induced the occurrence of adenomas and adenocarcinomas in the distal colon which were correlated with ACF number; whereas the proximal colon developed signet-ring type carcinomas which were not correlated with ACF [ 44 - 46 ]. Moreover, there may be discrete subset(s) of ACF, not easily recognized by the standard assay, that progress to microadenomas and which are characterized by increased dysplasia, altered oncoprotein and tumor suppressor expression and/or genomic instability [ 37 , 47 - 51 ]. Previously, we reported that Sprague Dawley rats, lifetime fed casein-AIN-93G diet had a 50% incidence, whereas those fed SPI-AIN-93 G diet had a 12% incidence of colon tumors, at 40 weeks post-AOM [ 21 ]. In our previous study, tumor incidence was similarly reduced for proximal and distal regions by SPI. However, in the present study, we found that SPI reduced crypt multiplicity and frequency of large ACF (those containing 4 or more crypts) mainly in the distal colon, which at six weeks post-AOM had more ACF of each size than did the proximal region. Therefore, the present ACF data are in general concordance with our previous tumor data but only for the distal colon. The basis for the discordance of ACF and tumor data for the proximal colon is unknown but is in general agreement with other studies showing correlations of larger ACFs with distal but not proximal colon tumors [ 44 - 46 ]. A diet switching paradigm examined whether the suppressive effect of SPI on larger ACF required lifetime exposure or could be mimicked with a shorter developmental period of SPI feeding. We also questioned if 'protective' effects could be transferred maternally to the offspring. The results of this experiment are of interest for a number of reasons. The observation that SPI elicited reduced growth by day 10, postnatal, may point to a 'maternal effect' of SPI, during gestation or lactation or both that is transmitted to progeny to affect their growth. The exact nature of this effect awaits further clarification. Both diet switchovers generally mimicked the effects of lifetime SPI on ACF incidence, although the casein/SPI regimen appeared to be slightly more effective than the SPI/casein dietary treatment in this regard. We therefore surmise that SPI can manifest long lasting effects on ACF incidence and that at least some of these effects can be transmitted to the offspring through feeding of SPI to pregnant and/or lactating dams. Obesity is considered by some to be a promoter of oncogenesis in rat models of chemically induced colon cancer [ 52 , 53 ] and of colon cancer in humans [ 54 ]. Positive interactions of soyfoods with increasing body mass index to reduce breast cancer risk in humans have been suggested [ 55 ]. In the current study, DXA analysis identified differences in global % fat that could account for the differences between final body weights of casein and SPI animals; although we examined only a limited number of animals in this regard. However, we were unable to find any statistically significant associations of final body weight and ACF for the diet groups. Therefore, our results do not indicate any obvious positive relationship between relative fat content and ACF incidence. Kállay et al. [ 56 ] observed that the feeding of soy protein isolate selectively suppressed or enhanced colonic gene expression (relative to casein). Their work as well as the present results underscores the need for further elucidating direct and indirect actions of dietary SPI and its protein and non-protein constituents on colonic mucosal growth and differentiation during development through to adulthood. The somewhat conflicting literature regarding effects of soy on colon carcinoma in the rat may derive in part from differences in the nature of the dietary casein and SPI used, and the relative developmental timing of SPI feeding. Studies that used commercial diets containing soy constituents for propagation of rat colonies for subsequent experiments may also have been confounded by pre-exposure to soy. It may be important to standardize this developmental soy exposure in future studies so as to reach consensus on the colon cancer-preventive actions of soy and its constituent(s). Conclusions SPI inhibited the development of large ACF, some of which may be tumor precursors. Feeding of SPI to rat dams during pregnancy and lactation led to a suppression in numbers of large ACF in their progeny, implying a long-term or permanent anti-carcinogenic effect elicited by the SPI-based diet. Body weight and body composition were differentially affected by soy protein isolate or casein in the diet. ACF may be a valid intermediate endpoint for elucidating effects of SPI and its biochemical constituents in tumor prevention in the colons of Sprague Dawley rats. Author's contributions ALL performed the whole-mount and TUNEL assays, performed data analysis, and assisted with tissue collection. RX performed data analysis, assisted with tissue collection, and prepared the final figures. JGP and PMS performed statistical analyses. TMB participated in the design of the study and oversaw the animal and diet manipulations. FAS conceived of the study, participated in its design, interpreted the data and prepared the manuscript. All authors read, modified and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526211.xml
539325	A Model of the Statistical Power of Comparative Genome Sequence Analysis	Comparative genome sequence analysis is powerful, but sequencing genomes is expensive. It is desirable to be able to predict how many genomes are needed for comparative genomics, and at what evolutionary distances. Here I describe a simple mathematical model for the common problem of identifying conserved sequences. The model leads to some useful rules of thumb. For a given evolutionary distance, the number of comparative genomes needed for a constant level of statistical stringency in identifying conserved regions scales inversely with the size of the conserved feature to be detected. At short evolutionary distances, the number of comparative genomes required also scales inversely with distance. These scaling behaviors provide some intuition for future comparative genome sequencing needs, such as the proposed use of “phylogenetic shadowing” methods using closely related comparative genomes, and the feasibility of high-resolution detection of small conserved features.	Introduction Comparative genome sequence analysis is a powerful means of identifying functional DNA sequences by their evolutionary conservation [ 1 , 2 , 3 ]. It will be instrumental for achieving the goal of the Human Genome Project to comprehensively identify functional elements in the human genome [ 4 ]. How many comparative genome sequences do we need? Where is the point of diminishing returns, after which sequencing another koala or bat does not contribute significant information to human genome analysis? Since sequencing is expensive and capacity remains limited, one would like to address this issue as rigorously as possible. Empirical evaluations of candidate comparative genomes have become important in allocating sequencing resources. Pilot sequencing and analysis in Saccharomyces and Drosophila species were done to choose appropriate species for comparative genome sequencing [ 5 , 6 ]. A pilot sequencing effort is underway for a number of mammalian genomes to evaluate their utility for human genome analysis [ 4 ]. Given the complexity of genomes, empirical studies are necessary. However, one would also like to complement this with higher-level, general insights that are independent of the details of particular analysis programs, organisms, and genomic features. Cooper et al. proposed a mathematical model of one important type of comparative genome analysis [ 7 ]. They framed a question amenable to quantitative modeling: how many comparative genomes, and at what distances, are required to detect that an individual base in a target genome is “neutral” (inferred to be evolving at the neutral rate) as opposed to “conserved” (inferred to be under purifying selection)? Their model infers a nucleotide site to be conserved if it is 100% identical to homologous sites in N comparative genomes. The key parameters are the independent branch lengths (d i ) contributed to a phylogeny by each new comparative genome (i), measured in neutral substitutions per site. More neutral evolutionary distance makes it more likely that neutral sites will have one or more substitutions in the alignment. Analytical strength increases as a function of the total neutral branch length in the phylogeny (Σ i d i ), because the probability that a neutral site has no changes in any branch of the phylogeny (and thus would be misclassified as conserved) is taken to be approximately e −Σ i d i . Based on the model, they concluded that 5.0 neutral substitutions/site of total branch length (about 10–20 well-chosen mammalian genomes) would approach “single nucleotide resolution” for human genome analysis, with a false positive probability (FP) of less than e −5.0 per invariant site. This model has some limitations that seem serious enough to question the proposed target of 10–20 mammalian genomes. Most importantly, it assumes that conserved sites are invariant. Few conserved features are absolutely invariant. If invariance is required to infer conservation, the fraction of truly conserved sites that are wrongly inferred to be neutral (because a substitution is seen in one of the comparative genomes) asymptotically approaches one as the number of comparative genomes or their evolutionary distance increases. We want to consider not just our FP, but our statistical power—our ability to successfully detect features that are conserved. Additionally, single nucleotide resolution may not be the most relevant goal. It is useful to consider single nucleotide resolution as an ultimate limit on comparative analyses—one can imagine plausible analyses of single bases, and certainly individual codons—but we are mostly concerned with identifying conserved features of greater length, such as exons or transcription factor binding sites. Nonetheless, the level of abstraction introduced by Cooper et al. is attractive. There is a need for better intuitions for planning comparative genome sequencing. How many more comparative genomes are needed as one looks for smaller and smaller conserved features—from exons to regulatory sites to single codons or even single nucleotides? How many more genomes are needed as one uses more and more closely related comparative genomes, in order to improve the chances that homologous lineage-specific features are found and correctly aligned [ 8 , 9 ]? Precise answers will be elusive, because genome biology is complex, but perhaps there are rough, useful scaling relationships amongst comparative genome number, evolutionary distance, and feature size. To explore this, I have extended the ideas introduced by Cooper et al. and developed an abstract model that seems to capture the essential flavor of comparative genome analysis. Results/Discussion Description of the Model A “feature” is a sequence of L nucleotide sites in the target genome. We assume we have a correct, ungapped multiple sequence alignment of this sequence to N homologous features from N additional comparative genomes, and that the L sites are independent. In the NL nucleotides in the aligned comparative sequences, we count how many changes are observed relative to the target feature sequence; call this c . If c is greater than some threshold C, we infer the feature is evolving at the neutral rate. If, on the other hand, c is less than or equal to C, we infer the feature is conserved. We assume that each comparative genome is independently related to the target genome by a branch length of D neutral substitutions per site, that is, a uniform star topology, with the target at the root, and equal length branches to the comparative genomes at the leaves. A uniform star topology allows us to model how evolutionary distance affects comparative analysis at an abstract level, as a single variable D, independent of the details of real phylogenies. The biologically unrealistic placement of the known target at the root simplifies the mathematics, and does not significantly affect the results compared to making the more realistic assumption of an unknown ancestor at the root of a tree with N + 1 leaves, including the target. We assume that the only difference between conserved features and neutral features is that conserved features evolve more slowly, by a relative rate coefficient ω . A conserved site accumulates an average of ωD substitutions, whereas a neutral site accumulates an average of D substitutions. ω = 0 for an absolutely conserved feature; ω = 1 for a neutrally evolving feature. At short evolutionary distances, we expect about c = DNL changes in neutral features, and c = ωDNL changes in conserved features, with binomial densities for P ( c ) around those values. To model the probability that two nucleotides diverged by D or ωD substitutions will be observed to be identical (to deal with multiple substitutions at one site), we assume a Jukes-Cantor process in which all types of base substitution occur at the same rate [ 10 ]. Under a Jukes-Cantor model, the probability that two sites that have diverged by D substitution events are identical is , which approaches 25% at infinite divergence. Given these assumptions, the FP in a comparative analysis (the probability that we erroneously infer that a neutral feature is conserved) is the probability that a neutral feature happens to have C or fewer observed changes (a cumulative binomial distribution): and the false negative probability (FN; the probability that we erroneously infer that a conserved feature is neutral) is the probability that a conserved feature happens to have more than C observed changes: The model therefore depends on four parameters: the size of the conserved feature, L, the relative rate of evolution of the conserved feature, ω, the number of comparative genomes, N, and the neutral distance of the comparative genomes from the target genome, D . The threshold C is usually not an input parameter (except in the special case of invariance; C = 0). Rather, we find the minimum genome number N (or feature size L ) at which there exists any cutoff C that can satisfy specified FN and FP thresholds. The Cooper et al. model is essentially a special case where L = 1 (single nucleotide resolution), ω = 0 (conserved sites are always invariant), C = 0 (only invariant sites are inferred to be conserved), and FN = 0 by definition (if all conserved sites are invariant, and all invariant sites are inferred to be conserved, then all conserved sites are detected). Also, instead of using an evolutionary model to account for multiple substitutions at one site (saturation), Cooper et al. make a Poisson assumption that the probability of observing no change at a comparative site is e −D , which is only valid for small D . The model discriminates features based on their relative rate of evolution. The same equations could be used to detect features evolving faster than the neutral rate (positively selected features), or to detect highly conserved features on a background of less strongly conserved sequence, as, for instance, transcription factor binding sites in an upstream region often appear [ 11 , 12 ]. For simplicity, I will only talk about discriminating “conserved” from “neutral” features here. Reasonable Parameter Values The feature length L and conservation coefficient ω abstractly model the type of feature one is looking for. I use L = 50, L = 8, and L =1 as examples of detecting small coding exons, transcription factor binding sites, and single nucleotides, respectively, solely by sequence conservation. On average, conserved exons and regulatory sites appear to evolve about 2- to 7-fold slower than neutral sequences ( ω = 0.5–0.15) [ 7 , 8 , 13 , 14 , 15 ]. I use 5-fold slower ( ω = 0.2) in most cases discussed below. Typically, one doesn't know L or ω when looking for novel features. These two parameters behave as bounds: if one can detect a specified feature, larger and/or more conserved features are also detected. The model's single distance parameter, D, abstractly represents the independent neutral branch length contributed by each comparative genome [ 7 ]. In a phylogenetic tree of the target with N > 1 comparative genomes that are as independent from each other as possible, we can roughly consider the independent branch length contributed by each comparative genome to be one-half its pairwise distance to the target genome, because in a real tree (with unknown common ancestors, as opposed to placing the target at the root of a uniform star topology) all comparative genomes share at least one branch leading to the target. Thus the figures highlight D = 0.03, 0.19, and 0.31 as “baboon-like,” “dog-like,” and “mouse-like” distances from human, 50% of one set of pairwise neutral distance estimates of 0.06, 0.38, and 0.62, respectively, arbitrarily chosen from the literature [ 7 ]. These labels are solely to give some intuition for what the model's D parameter means. The correspondence between D and real branch lengths is crude. Real neutral distance estimates are a subject of substantial (up to about 2-fold) uncertainty in the literature, and there are regional variations and strong context effects on neutral substitution rates in mammalian genomes [ 16 , 17 ]. More importantly, the model's uniform star topology, though it allows a high-level analysis in terms of just two parameters, D and N, makes direct comparison to real phylogenies difficult. Large numbers of equidistant, independently evolved mammalian genomes do not occur in reality. Real genomes are not independent, and will generally contribute an independent neutral branch length of less than one-half of their pairwise distance to the target genome. Critically, the model assumes that homologous features are present, correctly detected, and correctly aligned. In reality, with increasing evolutionary distance, features can be gained, lost, or transposed [ 14 , 18 , 19 , 20 , 21 ], the ability to detect homology by significant sequence similarity decreases, and alignments become less reliable [ 22 ]. The frequency of effects like loss, gain, and transposition depend on the biology of particular types of features, so departures from the model's “alignment assumptions” are difficult to model abstractly. However, minimally, we can posit a maximum neutral distance, D max , beyond which the alignment assumptions will not hold, based just on the ability of alignment programs to recognize and align homologous DNA sequences. Roughly speaking, reliability of DNA sequence alignments begins to break down at about 70% pairwise identity. For alignments of conserved features evolving 5-fold slower than neutral, this suggests D max ∼ 0.15/0.2 = 0.75; Figures 1 and 2 show results out a little further, to D max = 1.0. Figure 1 Number of Genomes Required for Single Nucleotide Resolution The red line plots genome number required for identifying invariant sites ( ω = 0) with a FP of 0.006, essentially corresponding to the Cooper model [ 7 ]. Black lines show three more parameter sets: identifying 50% (FN < 0.5) of conserved sites evolving 5-fold slower than neutral ( ω = 0.2) with FP < 0.006, doing likewise but with a more-stringent FP of 0.0001, and identifying 99% of conserved sites instead of just half of them. Values of N at baboon-like, dog-like, and mouse-like neutral distances are indicated with diamonds, squares, and circles, respectively. Jaggedness of the lines here and in subsequent figures is an artifact of using discrete N, L, and cutoff threshold C to satisfy continuous FP and FN thresholds. Figure 2 Number of Genomes Required for 8-nt or 50-nt Resolution Top: identifying 8-nt conserved features (“transcription factor binding sites”; L = 8); bottom: identifying 50-nt conserved features (“exons”; L = 50). Parameter settings are indicated at top right, in same order as the plotted lines. The parameters are the same as those used in Figure 1 . Two different FP settings are used as illustrative examples: 0.006 (the e −5 threshold used by Cooper et al. [ 7 ]) and the more stringent 10 −4 . For consistency, the same two FP thresholds are used to illustrate scaling behaviors for all three feature sizes ( L = 1, L = 8, and L = 50). However, for a real analysis, one wants to consider the appropriate choice of FP carefully. In a genome sequence of length M, the total number of false positive feature predictions in all overlapping possible windows of length L is M − L + 1, multiplied by FP per feature. In most analyses, we would probably merge overlapping predicted features into a single predicted conserved region, resulting in a lower number of false positive regions in a genome. This overlap correction (from the number of false features to the number of false regions) depends on the parameters, but for the parameters in Figures 1 and 2 it varies from 1.5- to 2-fold less for L = 8 sites and 4- to 8-fold less for L = 50 sites, based on simulations. Thus, for example, FP = 10 −4 corresponds to one false positive feature per 10 kb, and (for the parameters here) somewhere between one false positive conserved region per 20–100 kb, depending on the feature. For “small exon” detection, this means 40,000–300,000 false region/feature predictions in the 3-Gb human genome; for “transcription factor binding sites,” this means one false positive feature or region per 10–20 kb. FP = 10 −4 therefore seems a reasonable stringency for L = 8 or L = 50 feature analyses. If one carried out a single nucleotide resolution analysis on a genome-wide scale, FP = 10 −4 would mean that 99.8% of the predictions for conserved bases in the 3-Gb human genome would be correct, assuming about 5% of the bases are truly conserved and detected with high sensitivity. However, it is likely that one would actually carry out single nucleotide resolution analyses on a subset of conserved features that had already been identified (exons, for example), so a less stringent FP might be required. The setting of FP = 0.006 might therefore be more appropriate for evaluating single nucleotide resolution, where FP is closer to the traditional statistical choices of a 0.01 or 0.05 significance level. Single Nucleotide Resolution Requires Many Genomes The Cooper model concluded that for invariant conserved sites, sequencing comparative genomes to achieve a total branch length of five neutral substitutions per site would give single nucleotide resolution, with a FP of e −5 (0.006) [ 7 ]. Under my model, detection of invariant nucleotides takes about 17 genomes at mouse-like distances, essentially as predicted by Cooper et al. ( Figure 1 ). However, the picture changes when one considers comprehensive detection of features that are conserved but not invariant ( Figure 1 ). To detect 50% of sites evolving 5-fold slower than neutral, we need 25 comparative genomes at mouse-like distances at the same (arbitrary) false positive threshold of less than 0.006. For a comprehensive screen that would detect 99% of conserved single nucleotides with a FP of less than one per 10 kb, the model predicts about 120 comparative genomes at mouse-like distances are needed. Detectable Feature Size Scales Inversely with Genome Number The large genome numbers in Figure 1 might appear to conflict with the known power of comparing just two genomes, such as human and mouse. This is because recognizing conserved sequences is easier than recognizing conserved single nucleotides; the size of the conserved feature matters. Figure 2 shows how many genomes are required to detect small features like transcription factor binding sites ( L ∼ 8) or larger features like short coding exons ( L ∼ 50). One genome at about human/mouse distance is sufficient for reasonable strength in coding exon detection. For a range of reasonable sensitivity and specificity stringencies, three to 15 genomes at human/mouse distance are sufficient for detecting transcription factor binding sites. There is a general, intuitive explanation for this. The strength of an analysis will depend on the difference in the expected number of substitutions in neutral features versus conserved features. This difference will be proportional to NL, the total number of aligned sites. Thus, for a constant stringency, the required number of comparative genomes is expected to scale inversely with the size of the feature to be detected ( N ∝ 1 /L ): to detect conserved features ten times smaller, it takes ten times as many comparative genomes. (This scaling behavior is seen directly later.) No Clear Optimum for Evolutionary Distance, but Close Distances Disfavored Figures 1 and 2 show two other notable behaviors. First, there is no sharp optimum for the neutral distance D . The number of genomes required is relatively flat for a wide range, from about 0.4 to well beyond 1.0. Within a broad range, the exact choice of one comparative genome versus another has little impact. This is shown more directly in Figure 3 , in which a measure of overall statistical strength is plotted against neutral distance over an unrealistically long range of D, out to 4.0 substitutions/site. For conserved features evolving 5-fold slower than neutrality, assuming that alignment assumptions hold, the optimum distance according to the model is about 1.4 neutral substitutions/site, four to five times the mouse-like distance. However, for many kinds of features, at such long evolutionary distances the alignment assumptions are likely to break down. Because the mathematically optimal distance for discriminating idealized conserved and neutral features lies outside the range where the alignment assumptions are likely to hold, it may not be particularly meaningful to imagine a uniquely optimal choice of evolutionary distance for comparative genome analysis; optimal choices will be problem-dependent. (This is not surprising, of course, but perhaps useful to see clearly in a simple model.) Figure 3 A Measure of Statistical Strength As a Function of Neutral Evolutionary Distance One convenient threshold-independent measure of the strength of a comparative analysis is an expected Z score, the expected difference Δ c in the number of substitutions in a neutral feature alignment versus a conserved feature alignment, normalized to units of standard deviations. E ( Z ) is readily calculated for the binomial distribution: where p n and p c are the probabilities of observing a change at one aligned comparative nucleotide according to the Jukes-Cantor equation. The plots here are for N = 5 and L = 8. The shape of the curve is independent of N and L, while the absolute magnitude of Z scales as √ NL . The x-axis is shown from D = 0 to D = 4, beyond the more realistic range of Figures 1 and 2 , to show the mathematically optimum D if homologous conserved features were present, recognized, and accurately aligned at any D . The second behavior worth noting in Figures 1 and 2 is that at close evolutionary distances, the necessary number of comparative genomes needed ramps up steeply. For instance, at human/baboon distances of 0.03, achieving equivalent statistical strength requires about seven times as many comparative genomes as when using human/mouse distances (see Figure 2 ). There is another general intuition behind these results. For D ≪ 1, the expected number of substitutions is DNL in a neutral feature and ωDNL in a conserved feature. So, for a constant statistical stringency, the number of genomes required will scale inversely with evolutionary distance, when the distance is small. At larger distances, this scaling ceases as the number of observed changes saturates. The strong scaling of N at small distances D has implications for the use of “phylogenetic shadowing” using closely related genomes [ 8 , 9 ]. It is clear that the use of closely related genomes is advantageous in several ways: alignments are more accurate, one can accurately align a surrounding neutral region to detect small embedded conserved regions, and homologous features are more likely to be present (for instance, primate-specific features in human analyses). However, the model illustrates how these advantages are accompanied by a significant cost in statistical strength (see Figure 3 ). When using comparative species at short evolutionary distances, species choice matters a lot. Within primates, for example, divergence times from human vary about 10-fold (∼6 to ∼65 million years); if one aims to use “primate sequences” for human genome analysis, there is a large difference between using distant primates (lemurs or New World monkeys) versus close primates (great apes). Resolution and Stringency as a Function of Genome Number How much additional information does each new comparative genome sequence give us? The top panel in Figure 4 plots sensitivity and specificity as the number of comparative genomes increases, for an analysis of transcription factor binding site–like features. The scaling behavior is expected to be (roughly speaking) log(FP or FN) ∝ − N , based on the cumulative binomial expressions for FP and FN. That is, each additional genome reduces FP or FN by a roughly constant multiplier; for the parameters used here, every three or four more comparative genomes reduces FP by 10-fold. The bottom panel in Figure 4 plots resolution L as a function of N, showing the expected L ∝ 1/ N scaling. Each doubling of the number of comparative genomes increases resolution about 2-fold. Figure 4 Increase in Stringency and Resolution with Increasing Genome Number Top: black line shows improvement in specificity (FP) for transcription factor (TF) binding site–like features ( L = 8, ω = 0.2) as comparative genome number increases, for FN = 0.01 (99% of sites detected), and genomes of D = 0.31 (mouse/human-like distance). Red line shows improvement in sensitivity (FN) for the same parameters and a FP threshold of 0.0001. Shown as a log-linear plot to show the expected rough log(FP or FN) proportional to − N scaling. Bottom: resolution (size of detectable feature, L ) as a function of comparative genome number, plotted on log-log axes to show the fit to the expected L ∝ 1/ N scaling. All four lines assume goals of FN < 0.01 and FP < 0.0001. Black lines are for identifying conserved features evolving 5-fold slower than neutral ( ω = 0.2), using baboon-like ( D = 0.03), dog-like ( D = 0.19), or mouse-like ( D = 0.31) genomes. Red line is for identifying invariant features with mouse-like genomes. Good Agreement with More Realistic Simulations The model's simplicity is useful. By just counting the number of substitutions in conserved versus neutral features, the reasons for the scaling behaviors are more intuitively obvious. However, the assumptions required for this level of simplicity are questionable. In real DNA sequences, the Jukes-Cantor model's simple assumptions are violated in many ways; transitions are more frequent than transversions, base composition is not uniform, and mutation rates show strong context dependence [ 17 ]. In a real analysis, we would use probabilistic methods to compare the log likelihood ratio (LLR) of a phylogenetic tree under competing hypotheses of two different rates [ 8 , 23 , 24 ], so we can deal with real phylogenies and different expected rates of substitutions at different bases. The relative predicted scaling behaviors are unlikely to change under more realistic simulations. However, for the model to be useful as a rough guide for required genome number under different comparative analysis scenarios, at a minimum we want to know whether the absolute predicted numbers would be substantially different for features evolving under a more realistic evolutionary model, such as the Hasegawa-Kishino-Yano (HKY) model [ 25 ], which models nonuniform base composition and transition/tranversion rate bias, and if we analyzed those data with LLR statistics instead of simply counting substitutions. Therefore, I performed the following computational simulation study. Synthetic “neutral” and “conserved” feature alignments were generated using two HKY models that differed in evolutionary rate by a factor of ω . The rates in the HKY models were parameterized with an AT-biased base composition of 33% A, 17% C, 17% G, and 33% T, and a biased transition/transversion rate ratio of 4.0. A feature alignment was simulated by choosing a random L -mer (using the specified base composition) as the target feature, then generating N homologous features from it with substitutions according to an HKY conditional substitution matrix at distance D . For each dataset, 10 3 conserved feature alignments and 10 6 neutral feature alignments were generated. These alignments were then scored under the two HKY models and ranked by LLR score. This was repeated for increasing N until an LLR score threshold existed that could satisfy the chosen FP and FN thresholds. I then reproduced the analyses in Figures 1 and 2 using the HKY/LLR simulation for the 27 highlighted points with ω = 0.2. That is, for the 27 combinations of D = 0.03, 0.19, or 0.31; L = 1, 8, or 50; and (FP, FN) = (0.0001, 0.01), (0.0001, 0.5), or (0.006, 0.5), I determined the minimum number of genomes required to achieve the chosen thresholds. This analysis showed that the predictions of the simple model's equations and the results of the HKY/LLR simulations are in close agreement. The maximum deviation was 15%. For example, for the [ D = 0.19, L = 1] points where the model predicts needing N = 183, 89, and 40 for the different values of FP and FN, the HKY/LLR simulation predicts needing N = 210, 80, and 35; for the [ D = 0.19, L = 8] points, the model predicts N = 23, 12, and 5, and the simulation predicts N = 24, 11, and 5; and for the [ D = 0.19, L = 50] points the model and simulation both predict N = 4, 2, and 1. More significant discrepancies appear at larger distances. A simple Jukes-Cantor model has only one substitution rate, so all types of substitutions saturate equally fast. In an HKY model, some substitution rates are faster than others. Intuitively, one expects an HKY model to be able to extract information from slower, less quickly saturated substitutions at longer distances, resulting in more discrimination at large D than the simple model predicts. This effect appears at distances of D > 2.0–3.0 or so: for instance, for [ ω = 0.2, L = 8] features, to achieve FP < 0.0001 and FN < 0.01 for distances of D = 1, 2, 3, 4, 5, and 10, the simple model predicts needing N = 8, 8, 11, 17, 26, and 335 genomes, respectively, whereas HKY/LLR simulations predict needing N = 8, 9, 9, 13, 17, and 82 genomes. Thus, the simple model's approximation breaks down somewhat at larger distances, beyond the D < 1 range that is considered here to be reasonable for comparative genomics. Additionally, nonuniform base composition causes some composition-dependent spreading around the mean N that is not predicted by the simple model. For instance, GC-rich features are more easily detected than AT-rich features when substitution rates are biased towards high AT composition. Additional HKY/LLR simulations, using the same HKY matrices as above but specifically looking at poly-A features versus poly-C target features, show this effect; for instance, for [ ω = 0.2, L = 8] features at D = 0.19, to achieve FP < 0.0001 and FN < 0.01, we need at least N = 24 genomes to detect features on average, but specifically we need N = 19 for poly-C/G features and N = 29 for poly-A/T features. Reasonable Agreement with Available Data One also wants to see that the model's predictions do not disagree with published results, at least to the extent that it is possible to crudely compare real phylogenies to the abstracted uniform star topology of the model. Three examples follow. Cooper et al. estimated that the mouse and rat genomes suffice for about 50-nt resolution of human conserved features [ 26 ]. The independent branch lengths to human, mouse, and rat are roughly 0.3, 0.3, and 0.1 neutral substitutions/site; the rat is close to the mouse, so this situation is difficult to fit with a single D . However, using either N = 1 and D = 0.6 (pairwise comparison to one rodent using one full pairwise distance for D ), or N =2 and D = 0.23 (approximating D as an average of three independent branch lengths), or N = 2 and D = 0.35 (approximating D as one-half the average pairwise distances from human to mouse and rat), the model predicts that 90% of 50-nt features with ω = 0.2 can be detected with a reasonable FP of between 0.0003 and 10 −5 ; but for features just half that size ( L = 25), FP collapses to between 0.02 and 0.006 (one false prediction every 50–150 nt). Boffelli et al., in introducing “phylogenetic shadowing,” used 13–17 primate sequences with a total independent branch length of about 0.6 neutral substitutions/site to analyze conserved sequences smoothed in 50-nt windows, and conserved regions down to 40–70 nt were detected effectively [ 8 ]. The model predicts that for N = 15 and D = 0.04 (average independent branch length of 0.6/15), one can detect 90% of 50-nt, ω = 0.2 features with a FP of 10 −5 ; but for 25-nt features, FP collapses to 0.003 (one false prediction per 300 bp). Kellis et al. and Cliften et al. reported comparative analyses to identify transcription factor binding sites in Saccharomyces cerevisiae using alignments of intergenic regions to three comparative Saccharomyces genomes, with a total independent branch length of about 0.8–0.9 [ 11 , 12 ]. For N = 3 and D = 0.27–0.30 (average independent branch length of 0.8/3 to 0.9/3), the model predicts that binding site–like features ( L = 8, ω = 0.2) would be detected with a FP of 0.001–0.002 (about one false prediction per upstream region) and a sensitivity of about 25%, suggesting that these data are barely sufficient to identify individual short conserved features. Indeed, though both research groups showed examples of highly conserved individual sites, both groups analyzed their data primarily at the level of detecting motif consenses, rather than attempting to detect individual features genome-wide. That is, they required that the same motif be found conserved in multiple places upstream of multiple genes. This is a data aggregation strategy, multiplying the effective L by the number of copies of the feature. In this way, even when only a fraction of individual features are identified, the existence of a conserved consensus motif may be inferred from the average conservation of the aggregated data. Limitations on the Generality of These Conclusions The model assumes a pure, brute force detection of individual conserved features by comparative analysis. For many particular problems, one can leverage additional information and reduce the number of comparative genomes needed. Data aggregation strategies are one example (for instance, detecting that a particular consensus motif is conserved more often than expected, averaged across all individual occurrences [ 27 ]). Another strategy is to combine sequence conservation data with other experimental data (for instance, using microarray data to detect that a marginally conserved motif is also statistically associated with a coordinately regulated set of genes [ 28 ]). Some features are not just conserved, but also show informative patterns of substitution, insertion, and deletion, so we can gain power by using feature-specific evolutionary models instead of a general conservation screen. For instance, coding regions predominately show substitutions in wobble positions and strong selection against insertions/deletions, and those insertions/deletions that remain will generally preserve frame [ 11 ]. Conserved structural RNAs reveal their basepaired secondary structure interactions by compensatory basepair mutations [ 29 ]. In such analyses it becomes important to see enough evolutionary events to distinguish one kind of conserved feature from other kinds of conserved features, not just to discriminate conserved from neutral. Because different conserved features evolve at different rates, one would generally want to have a range of comparative genomes at different distances, so that for any given conserved feature with its particular relative rate of evolution, one can find alignments in a “sweet spot” with the right amount of divergence. Finally, there are other important uses of comparative genomics in addition to DNA sequence analysis of conserved elements. For example, evolutionary/developmental studies choose species based on phylogenetic position, and population genetics studies choose multiple individuals within the same species. Concluding Remarks The principal results here are two inverse scaling behaviors that provide useful intuitions for planning comparative genome sequencing. All other things being constant, the required number of comparative genomes is inversely proportional to detectable feature size, and at small evolutionary distances, required genome number becomes inversely proportional to the neutral distance to the comparative genomes. Neither behavior is entirely surprising; the contribution of an abstract model is to see them more clearly. Obviously, it takes more comparative genomes to recognize smaller features, though one may not have predicted a simple inverse relationship between L and N . And it is already common to use total independent neutral branch length as a measure of the strength of a comparative dataset [ 7 , 8 , 9 , 30 ], which implies an inverse relationship between genome number and evolutionary distance, a relationship made explicit in a simplified model where total independent branch length is ND . The model also shows clearly that for two analysis scenarios—identification of small conserved features and the identification of lineage-specific conserved features in closely related genomes—it will be useful to obtain large numbers of comparative genome sequences. Since a small number of comparative genome sequences are already enabling powerful analyses, this may be surprising. Even for simple conservation analyses, we have not begun to exhaust the power of comparative genome analysis. Materials and Methods The model was implemented in several ANSI C programs, which can be downloaded at http://www.genetics.wustl.edu/eddy/publications/Eddy05 .	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539325.xml
548286	Experimental study of the function of the excreted/secreted Leishmania LmSIR2 protein by heterologous expression in eukaryotic cell line	Background In yeast and Caenorhabditis elegans , Silent Information Regulator (SIR2) proteins have been shown to be involved in ageing regulation. In Leishmania , the LmSIR2rp was originally isolated from the excreted/secreted material of the Leishmania parasites. Among the function(s) of this protein in Leishmania biology, we have documented its implication in parasite survival, and in particular in Leishmania amastigotes. In this paper we question the role of the excreted/secreted form of the protein. In particular we wonder if the Leishmania Sir2 homologue is involved in some aspect of its biological function(s), in various components and pathways, which could promote the host cell survival. To test this hypothesis we have mimicked an intracellular release of the protein through constitutive expression in mouse L929 fibrosarcoma cells. Results Our results demonstrate that the LmSIR2 protein was properly expressed by fibroblasts and that LmSIR2 is localized both in the cytoplasm and the nucleus of all the transformed cell clones. Unexpectedly, we found that cells expressing LmSIR2 presents reduced saturation cell density ranging from 40% to 60% and expressed an acidic (pH6.0) β-galactosidase activity, which is known to be a senescence biomarker. As a consequence, we observed that LmSIR2 positive fibroblasts were more permissive towards Leihmania infection. Conclusions LmSIR2 is able to substantially interfere with the host cell physiology. Thus, it is tempting to speculate that these modifications could help Leishmania to survive for a long period in a cell with reduced capacity to multiply or respond to immunologic stimuli. The potential implications of our finding during the in vivo infection process are discussed.	Background Leishmania is an intracellular pathogen that causes Leishmaniasis, which remain an important medical problem in several countries. Protozoan parasites of the genus Leishmania result in a spectrum of human disease that range from self-healing cutaneous ulcers to potentially fatal visceral infection, depending primarily upon the species of parasite involved [ 1 , 2 ]. Leishmania live as either extracellular flagellated promastigotes in the digestive tracts of their sand fly vectors or as nonflagellated amastigotes within macrophages where they survive and replicate within phagolysosome. Leishmania are known to export large range of proteins and glycoconjugates including lipophosphoglycan [ 3 ]. In a previous paper we have characterized a Leishmania major gene encoding a protein carrying extensive homology to SIR2 of yeast that we consequently termed LmSIR2rp [ 4 ]. It belongs to a large family of closely related NAD-dependent deacetylase named Hst proteins (Homologous of Sir two) or sirTuins, present in both prokaryotic and eukaryotic species [ 5 ]. Post-translational modifications of histones, like acetylation by histone acetylase (HAT) and deacetylation by histone deacetylase (HDAC), within the context of chromatin has been shown to regulate gene expression [ 6 , 7 ]. To date, three classes of HDACs are characterized in eukaryotes, the class I and II HDACs, and the class III defined by the sir2 family. In eukaryotic species some members of the Sir2 family are much more closely related to the core domain of the yHst2p protein than to the core domain of ySir2p itself [ 8 ]. These are: the SIR2 family members from Schizosaccharomyces pombe , C albicans , Leishmania , chicken, human (hSirT2p, hSirT3p) and the closely related mouse protein (MmSirT2p and MmSirT3p) [ 8 ]. This group has been designated Hst2-like, as it forms an independent branch within the Sir2 family tree. Five members of this group (LmSIR2rp), like it yeast (yHst2) human (SIR2L) and mouse (MmSIR2L2 and MmSIR2L3), are cytoplasmic [ 4 , 9 , 8 , 11 ]. The implication of SIR2 proteins bearing nuclear localization, in aging process has been extensively studied. In yeast, the deletion of SIR2 shortens lifespan and over expression extends lifespan [ 12 ]. This phenotype of life extension has been also observed in Caenorhabditis elegans carrying extra copies of the SIR2 orthologue, Sir-2.1 [review in [ 13 ]]. In mammalian cell, SIRT1 promote cell survival [ 14 ]. SIRT1 is able to deacetylate FOXO3 and/or FOXO4, thus attenuating FOXO-induced apoptosis and potentiating FOXO-induced cell-cycle arrest. Thus SIRT1 might increase longevity by shifting FOXO dependent responses away from cell death and toward cell survival [ 15 ]. Also, the unusual NAD-requirement for the Sir2 deacetylase may link metabolic rate to silencing and life span [ 16 ]. We have shown that the cytosolic LmSIR2rp protein, when over expressed in Leishmania amastigotes, was able to promote parasite survival in in vitro culture systems [ 9 ]. Further, we also observed that LmSIR2rp can be detected in the excreted/secreted material of Leishmania parasites when using radiolabelled immunoprecipitation technique, suggesting therefore that fraction of LmSIR2 is actively excreted by parasite (personal observations). We then initially surmised that this protein could also be involved in some aspect of host cell-parasite interplay, particularly in pathways that could contribute to cell survival. To test this hypothesis, the leishmania LmSIR2 gene was cloned in a mammalian shuttle vector and the expression of the protein was performed in fibroblasts. Unexpectedly, expression of the Leishmania Sir2 protein leads to a cell growth arrest phenotypes, which correlates, with the expression by the cells of an acidic (pH 6.0) β-galactosidase activity, known to be a senescence biomarker. Furthermore, fibroblasts expressing LmSIR2 were more permissive towards Leishmania infection than control ones. Altogether our results may suggest that the excreted forms of LmSIR2 could participate in the perturbation observed during chronic disease. Materials and Methods Molecular construct and transfection procedure LmSIR2 was amplified using sense GAA TTC GAT ATG ACA GGG TCT CCG and antisense CTC GAG CAG TCA CCA TGT TGG CAG primers. The 1119 bp PCR amplified genomic fragment subcloned into pCR2.1 was digested with Eco RI and inserted into the Eco RI digested and dephosphorylated pcDNA3.1 shuttle vector (Amersham). Restriction analysis of the recombinant plasmids using Eco RI and Xho I allowed the identification of recombinant vector carrying the LmSIR2 gene in sense orientation. Large-scale preparations of pcDNA- LmSIR2 and pcDNA empty vectors were performed using the QIAGEN plasmid maxi kit. Transfected cells were selected in RPMI 1640 medium containing 10% FBS and 400 μg/ml G418. Each G418-resistant clone, isolated by limiting dilution, were propagated and screened by immunofluorescence. Four clones were isolated and named Cl2, Cl9, Cl10 and Cl11. Production of monoclonal antibodies (mAb) against the fusion protein LmSIR2 recombinant protein containing 6 X histidine residues at its N-terminal (hisLmSIR2) was previously obtained after having subcloned the encoding gene in the pQE-expression vector [ 17 ]. Mice of BALB/c strain were injected intraperitoneally with 50 mg of hisLmSIR2 in saline solution emulsified with 0.1 ml of Freud's Complete Adjuvant. After 2 weeks, a booster injection of the same preparation was given. The antibody response of the animals was tested 1 month later. The same dose of antigen was injected intravenously 3 days before the hybridization experiment. The fusion procedure and the screening of mAb were carried out as previously described [ 18 ]. The class of mAb was determined by agarose double diffusion of supernatants against antisera specific for immunoglobulin subclasses obtained from cliniscience (Montrouge, France). Several hybridoma clones producing mAb reacting in an ELISA test with LmSIR2 protein were obtained; only one mAb of the IgG1 isotype (IIIG4) reacted in Western blot against the fusion as well as the native LmSIR2 protein. Growth kinetic and 3 H-thymidine incorporation L929 cells were inoculated at 400 cells/cm 2 , after various period of incubation they were collected by using Trypsin-EDTA (0.025%). The mean number of viable cells was determined at 100-× magnification after staining with trypan blue. In order to evaluate the rate of 3 H-thymidine incorporation, cells were seeded in 96 wells plates at 1000 cells/cm2, after various periods of incubation 1 μCi of 3 H-thymidine was added to each well. Cells were further incubated for 4 hours before reading the level of incorporated radioactivity. Giemsa staining and Immunofluorescence analysis L929 cells were seeded in 16-well Labteck chambers for 48 hrs. Cells were then washed with PBS and fixed for 30 minutes with 4% paraformaldehyde at 4°C. After two washes with PBS, cells were permeabilized with 0.01 M PBS containing 0.5% TritonX-100 and 2% BSA for 30 min at 4°C. Slides were then washed and incubated for 1 hour with mAb IIIG4 in 0.01 M PBS containing 2% BSA. After two washes, slides were incubated for 45 min with fluoresceine-conjugated rabbit anti-mouse IgG (Diagnostic Pasteur, Marnes la Coquette, France) diluted 1:100 in PBS containing Evan's blue (final dilution in PBS: 1: 10.000) and mounted in glycerol PBS (1:1). Giemsa staining of the cell culture was performed as follows: cells were inoculated at 400 cells/cm 2 in 25 cm 2 flasks, after 7 days of growth they were fixed with methanol and stained with Giemsa and examined observed on inverted microscope (40× magnification) after adding a solution of PBS 0,01 M-Glycerol (1/1). RT-PCR analysis Total RNA was isolated from wild type and transformed cells using the Rneasy Mini Kit following the manufacturer's instructions. One microgram of RNA was reverse transcribed to cDNA with an oligonucleotide [poly (dT) 12–18 ] using the Superscript II RNase H-reverse transcriptase. PCR amplifications were performed using 1–2 μl of reverse-transcription of each product and 20 pmol of each primer, using Taq DNA polymerase. Each PCR cycle consisted of a denaturation step (94°C, 1 min), an annealing step (55°C, 1 min) and an elongation step (72°C 1 min). For the last cycle, the elongation step was extended to 10 min at 72°C. Reactions were carried out for 25–35 cycles in a thermocycler (PTC-100™, MJ Research, Inc.). PCR products were analyzed on 1.5% agarose gel and visualized with ethidium bromide. As an internal control, a housekeeping gene, the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) transcript, was amplified. LmSIR2 primers were: Sense GAA TTC GAT ATG ACA GGG TCT CCG and antisense CTC GAG CAG TCA CCA TGT TGG CAG. GAPDH primers were: Sense GTC TTC ACC ACC ATG GAG and antisense CCA AAG TTG TCA TGG ATG ACC. β-galactosidase pH6 analysis Acidic (pH 6.0) β-galactosidase was assayed according to Dimri et al. [ 19 ]. Briefly, stationary-phase cells were washed three times in phosphate buffered saline (0.1 M PBS, pH 7.4), fixed in 2% formaldehyde/0,2% glutaraldehyde for 5 min at room temperature, washed three times with PBS, then incubated at 37°C without CO 2 for 12 h with freshly prepared β-Gal staining solution pH 6.0, containing the 5-bromo-4-chloro-3-indoyl-b-D-galactosidase (X-Gal) chromogenic substrate which produces blue 5-bromo-4-chloro-3-indole upon hydrolysis. Cell preparation was stored at 4°C in 70% glycerol upon analysis. Results and Discussion Expression of LmSIR2 by L929 fibroblasts The Level of the LmSIR2 gene transcription was evaluated by RT-PCR analysis. As shown in Figure 1 , an amplification product of around 1.2 Kb was observed only in recombinant L929 cells transformed with the pcDNA carrying LmSIR2 gene (Fig 1 lane 2), No amplification could be detected in Wild-type fibroblasts or in fibroblasts carrying the empty pcDNA vector (Lane 1 and 3 respectively). Accordingly, Western blot analysis of cellular extracts derived from the clones 2 and 11 reacted with with the mAb IIIG4 showed a polypeptide of 50 kDa (Fig 2 lanes 3 and 5), which is slightly higher than the molecular size of the pcDNA encoded protein (≈ 43 kDa). However, it is noteworthy that this molecular size is similar to that of the parasite native protein shown in previous studies [ 9 ]. It is therefore likely that the transfected gene product is submitted to posttranslational modifications that occur during its processing. No cross reactivity was observed on cell extract derived from Wild-type cell or fibroblast carrying the empty vector (Fig 2 Lane 1 and 2). Thus, these results confirm that mouse L929 fibroblast cell line properly expressed the LmSIR2 gene. Figure 1 Expression of LmSIR2 gene in L-929 cells. RT-PCR analysis of total RNA from various L-929 clones was carried out using LmSIR2 or GAPDH primers. The lanes correspond to the following samples: standard size marker (PM); WT L929 cells (1); L929 clone 2 (Cl2) (2); L929 carrying an empty pcDNA plasmid (3). Figure 2 Detection of the LmSIR2 protein in L929 cell extracts. The lanes correspond to the following samples: WT L929 cells (1); L929 carrying an empty pcDNA plasmid (2), L929 Cl2 (3); Molecular weight markers (4); L-929 Clone 9 (5). The LmSIR2 gene was originally isolated via immunoscreening of a cDNA library, using polyclonal antibodies raised against excreted factors which could bind to glutathione [ 4 ]. The presence of such protein in the leishmania 's excreted material as previously demonstrated raised the question of its function during the infection process. Thus, heterologous expression in eukaryotic cells could represent a useful approach to give some insight into the biological activity of secreted parasite material. Immunolocalization of LmSIR2 shows that cells expressing LmSIR2 (Figure 3B ) react with the monoclonal antibody as compared to cells carrying the empty pcDNA vector (Figure 3A ). Interestingly, high number of cells positive for LmSIR2 bears abnormal morphology i.e. giant multinucleated cells (Figure 3B ). In these cells, the protein is localized both in the cytosol and the nucleus. Functional studies of several mammalian SIR2 related proteins have been carried out including those who are mainly localized in the cytosol. Nevertheless, similar cellular localization pattern has never been reported nor such modification of cell physiology. Our observations suggest that LmSIR2 possesses unrelated specificity that can strongly affect the biological properties of the host cell. Interestingly, LmSIR2 protein presents a NES (the nuclear export signal or NES)-like motif LX 3 L X LX 3 L at its carboxy-terminal region, where L represents Leucine and X any amino acid [ 20 ]. The intracellular localization of key regulatory proteins tagged with a short Leucine-rich motif (nuclear export signal) is controlled by CRM1/exportin1, which is involved in the export of these proteins from the nucleus [reviewed in [ 21 ]]. However, the ability of the Leishmania SIR2 to shuttle between the cytoplasm and nucleus of the host cell through the NES putative sequence, await further investigations. Figure 3 Indirect immunofluorescence analysis and morphology of transgenic cells . Localisation of LmSIR2 using immunofluorescence analysis (A) L929 cells carrying an empty pcDNA vector (B) L929 (Cl2) expressing LmSIR2 protein. Morphology of cells in culture: (C) L929 cells carrying an empty pcDNA vector and (D) L929 Cl2. Note the reduced cell density and the presence of cells bearing abnormal morphology (arrow). When L929 cell culture, of either clone 1, clone 2, clone 9 or clone 10, were stained with Giemsa, a high rate of cells with unusual shape and size associated with the presence of multiple nuclei was revealed (Figure 3 D ) as compared to cells carrying the empty pcDNA vector (Figure 3C ). The rate of multinucleated cells was determined by counting the number of cells bearing more than 2 nucleus per 10 champs at 10-× magnification. In fact all the clone cultures present a 10 to 15-fold increase in giant multinucleated cells as compared to cultures of L-929 fibroblast transformed with the empty vector (Figure 3 C ). Moreover, majority of the cells if not all, present an enlarged and flattened morphology (Figure 3 D ). Growth kinetic parameters of L929 cell expressing LmSIR2 In order to investigate the potential functions of LmSIR2 protein, when delivered intracellularly in L929 fibroblasts, we have determined the growth kinetic parameters of cells via two different methodologies. Using a counting method, we observed a high reduction in the saturation density of cells expressing LmSIR2 (Figure 4A ). The reduction observed in this experiment was as high as 40% as compared to cells carrying the empty pcDNA vector. These preliminary observations were further confirmed using 3 H thymidine. Indeed, as shown in figure ( 4B ), expression of LmSIR2 strongly reduced the thymidine incorporation over the time course of the experiment. The most dramatic reduction of 3H-thymidine incorporation was observed a day 7 which correspond to the maximal cell density observed for both Wild type control and the four clones studied (reduction in 3 H-thymidine incorporation of about 61% for clone 2, 60% for clone 9, 52% for clone 10 and 42% for clone 11). Figure 4 Growth kinetics analysis. Cell proliferation was determined using two methods: cell counting (A), the results are given as a mean value of a triplicate experiment ; and 3 H-thymidine incorporation (B), the results are given as mean value of a sextuplate experiment Expression of senescence biomarker Parameters of senescence include increased cell size, reduced saturation density as well as altered expression of some gene products that have been proposed to serve as biomarkers of aging. Reduction in the final cell yield or saturation density is known to occur in human diploid fibroblast senescence and is considered as a criterion of the onset of senescence [ 22 ]. With respect to biomarkers, pH 6 β-galactosidase is particularly useful, since this activity has been found to distinguish senescent from quiescent cells both in vivo and in vitro [ 19 ]. We found that L929 cells expressing LmSIR2 exhibit reduced saturation densities (40% to 60%) and altered cell morphology. We have thus evaluated the occurrence of the pH 6 β-glactosidase activity. As shown on Figure 5 (B and C), a strong pH-6 β-glactosidase was detected in L929 cells expressing the LmSIR2 gene but was not detected in wild-type cells or cells transformed with the empty pcDNA vector (Figure 5A ). Figure 5 Expression of a senescence biomarker. (pH6.0) β-galactosidase activity detected in L929 cells expressing LmSIR2 (Cl2) (B and C) but not in L929 carrying an empty pcDNA plasmid (A). Cells were seeded at 40 cells/mm 2 in 25 cm 2 flasks and after 13 days of growth, the presence of pH6-galactosidase activity (Arrow) was determined as described in the Materials and Methods section. N nucleus, note the perinuclear galactosidase activity. Permissivity of fibroblast expressing LmSIR2 towards Leishmania amazoensis Fibroblasts at the lymph are used as safe target for long lasting residual parasite population [ 23 ]. However, only few reports deal with in vitro infection of fibroblast. In 1978, Chang [ 24 ] demonstrated that promastigotes of L. amazonsensis but not L. donovani were able to infect human skin fibroblasts. However, once differentiated into amastigotes the parasites were unable to multiply inside the cell. Dedet and co-workers further confirmed these observations [ 25 ]. Thus, we decided to test the capacity of L. amazonensis to infect L929 cell lines. When L. amazonensis promastigotes were incubated with Wild-type fibroblasts the proportion of infected cells reached a peak of about 50% after 24 hours of contact, after what the proportion of infected fibroblasts decreased quickly. On day 2, only few parasites could be seen and after 3 days of incubation less that 1% of fibroblasts remain infected (data not shown). As shown in Figure 6 , fibroblasts expressing LmSIR2 were more permissive toward Leishmania infection since the mean percentage of infected fibroblast reach 70% after 24 hours of contact. However, once inside fibroblasts no differences in the capacity of parasites to survive and/or multiply was observed and the intracellular amastigote population was eliminated after three days of contact (data not shown). Figure 6 Permissivity of L929 cells toward Leishmania amazonensis infection. L929 cells were seeded in 25 cm2 flasks and treated with mitomycin. They were then infected, at different parasite/fibroblast ratio, with freshly differentiated stationary phase L. amazonensis promastigotes. After 24 hours of contact cells were washed and the percentage of fibroblats bearing attached or internalized parasites was determined. Results are expressed as a mean value of a triplicate experiment. Conclusions Our study demonstrates that LmSIR2 is able to down regulate the proliferation of fibroblasts and to induce a senescence-like state in L929 fibroblast cell line. The most interesting finding is that a parasitic protein is able to modify the physiology of the host cell making them more permissive toward Leishmania infection. These results suggest that LmSIR2 has dual function according to the cell type in which it acts: in Leishmania parasites, LmSIR2 is able to promote cell survival while in the host fibroblast it induces a senescence phenotype. This effect could be beneficial for Leishmania since senescent cells are no longer capable of dividing yet remaining metabolically active. They could thus represent safe target for parasite. It is documented that senescent fibroblasts present an inherent higher capacity to resist to apoptotic death [ 26 ]. In this view, it will be of interest to determine if fibroblasts that express LmSIR2 were more resistant to apoptotic stimuli. It is known that infected macrophages are usually more resistant to apoptosis, however it is not know if such mechanism operate in infected fibroblast. Thus, the implication of LmSIR2 in a general mechanism leading to apoptosis resistance of both macrophages and fibroblasts await further investigations. The in vivo relevance of our observation is rather difficult to appreciate because; (1) the level of the protein produced in fibroblasts transformed with the pcDNA is certainly far higher than the level achievable in vivo , and (2) the presence of excreted parasite material inside the fibroblast cytosol has yet not been reported. However, an action of the excreted form of LmSIR2 on he host cell could no be ruled out. Two series of observations support this possibility: (1) it has been shown that the Leishmania EF1-a could be translocated from the parasitophorous vesicle into the macrophage cytosol [ 27 ]; (2) the ultrastructural examinations of skin biopsies obtained from patients with cutaneous leishmaniasis showed that intracellular amastigotes could be frequently identified in vacuoles and in the cytosol of the host cell [ 28 ]. In conclusion, although the effect of the protein, when delivered extracellularly, on the host cells have not being examined in the present study, our data support the notion that the excreted form of LmSIR2 is able to interfere with the host cell physiology, when delivered intracellularly. Unexpectedly the expression of the protein is associated with the appearance of a senescence biomarker. Relevance of such finding during the in vivo infection process awaits further investigations	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548286.xml
549198	Dysregulation of Na+/K+ ATPase by amyloid in APP+PS1 transgenic mice	Background The pathology of Alzheimer's disease (AD) is comprised of extracellular amyloid plaques, intracellular tau tangles, dystrophic neurites and neurodegeneration. The mechanisms by which these various pathological features arise are under intense investigation. Here, expanding upon pilot gene expression studies, we have further analyzed the relationship between Na+/K+ ATPase and amyloid using APP+PS1 transgenic mice, a model that develops amyloid plaques and memory deficits in the absence of tangle formation and neuronal or synaptic loss. Results We report that in addition to decreased mRNA expression, there was decreased overall Na+/K+ ATPase enzyme activity in the amyloid-containing hippocampi of the APP+PS1 mice (although not in the amyloid-free cerebellum). In addition, dual immunolabeling revealed an absence of Na+/K+ ATPase staining in a zone surrounding congophilic plaques that was occupied by dystrophic neurites. We also demonstrate that cerebral Na+/K+ ATPase activity can be directly inhibited by high concentrations of soluble Aβ. Conclusions The data suggest that the reductions in Na+/K+ ATPase activity in Alzheimer tissue may not be purely secondary to neuronal loss, but may results from direct effects of amyloid on this enzyme. This disruption of ion homeostasis and osmotic balance may interfere with normal electrotonic properties of dendrites, blocking intraneuronal signal processing, and contribute to neuritic dystrophia. These results suggest that therapies aimed at enhancing Na+/K+ ATPase activity in AD may improve symptoms and/or delay disease progression.	Background Alzheimer's disease (AD) has several well-characterized post-mortem pathological markers that include both gliosis and dystrophic neurites surrounding extracellular amyloid plaques. In addition, intracellular tangles of hyper-phosphorylated tau and massive neurodegeneration are seen later in the disease process. Mutated forms of both amyloid precursor protein (APP) and presenilin 1 (PS1) lead to an increased rate of amyloid deposition and therefore an earlier onset of the dementia associated with AD [ 1 ]. Doubly transgenic mice expressing these human mutants of the APP [ 2 ] and PS1 [ 3 ] genes (APP+PS1 mice; [ 4 ] exhibit a large amount of amyloid deposition and gliosis without the formation of tangles or neuron loss, and yet they still develop anterograde amnesia as they age, similar to what is seen in the early stages of AD [ 5 ]. Memory deficits without the loss of neurons indicate that amyloid-associated disruption of some step in neural processing can result in memory deficits. Previously we have described decreased expression of genes critical for learning and memory and impaired induction of several immediate early genes (IEGs) in aged, memory deficient APP+PS1 mice [ 6 , 7 ]. Increased neural activity during learning is argued to be a primary inducing stimulus for these IEGs [ 8 ]. One possible mechanism to describe this phenomenon would be that amyloid is diminishing the ability of neurons to facilitate sufficient electrical signaling to induce changes in synaptic plasticity essential for memory consolidation. Here we present evidence that in addition to decreased expression of Na+/K+ ATPase mRNA as previously described [ 6 , 7 ], the activity of this enzyme is significantly decreased in the APP+PS1 hippocampus but not in the amyloid-free cerebellum. Perhaps not surprisingly ouabain, an Na+/K+ ATPase inhibitor, has been shown to impair memory consolidation [ 9 , 10 ]. We decided to investigate further the interactions of Aβ and Na+/K+ ATPase activity to understand better the potential role of this enzyme in AD and memory dysfunction. Results We used the APP+PS1 transgenic mouse model to better understand how the deposition of amyloid contributes to the consistent memory loss seen in these animals [ 11 - 14 ]. Specifically, we have found that Na+/K+ ATPase, a protein critical for not only brain function, but survival, is adversely affected by the presence of amyloid and this interaction may be driving a major pathological event in the progression of amyloid-associated dementia. In order to determine if our early observation regarding reduced mRNA for Na+/K+ ATPase was functionally meaningful, we measured total and ouabain-sensitive ATPase activity in APP+PS1 brain homogenates compared to those from non-transgenic littermates using a standard colorimetric assay. Using ouabain as a selective inhibitor of Na+/K+ ATPase, we demonstrated that the specific enzymatic activity was significantly reduced by ~25% in the hippocampi of aged, memory-deficient APP+PS1 mice compared with non-transgenic littermates (Figure 1B ). The percent reduction in total ATPase activity was similar to that of specific Na+/K+ ATPase activity, suggesting that inhibition of is selective for Na+/K+ ATPase (Figure 1A & 1B ). In addition, approximately 40% of all the ATP hydrolysis found in the homogenate was ouabain sensitive, confirming that this enzyme is likely the largest single site of ATP hydrolysis in brain. The specific activity values measured here were consistent with those reported 3 decades ago by Stefanovic et al. [ 15 ], testifying to the robustness of the assay method. Upon analysis of the cerebellum of these mice, we found that the specific enzyme activity in APP+PS1 transgenics remained equivalent to that in non-transgenic littermates (Figure 1B ); however the overall activity of Na+/K+ ATPase in this region was only one fifth of that in the hippocampus (Figure 1A & 1B ). Western blot analyses of cortical homogenates demonstrated a trend for reduced protein expression, a finding that would be expected based upon the mRNA analyses (Figure 1C ). Immunohistochemical staining for the Na+/K+ ATPase αIII subunit was performed using saggital sections from non-transgenic and APP+PS1 mice. Specific staining was observed throughout the forebrain. The specificity of the Na+/K+ ATPase α subunit antibody used for immunochemistry was determined by pre-incubation of the antibody with purified Na+/K+ ATPase protein, which dramatically reduced apparent immunostaining (Figure 2B ) compared with normal staining (Figure 2A ; amyloid plaques stained with Congo red dye appear red). Positive reaction product appeared to be localized to the periphery of cellular profiles in CA3 of the hippocampus (Figure 3A ) and the insular cortex (Figure 3B ), consistent with the enzyme's membrane-association. Throughout the brain, the white matter regions appeared to have less intense staining, than the neuropil, consistent with the larger numbers of ions crossing the membrane in post-synaptic potentials than action potentials (thus requiring more ionic pumping to maintain ionic equilibrium). Additionally, regions with high densities of neuronal somata also appeared to have less dense staining, reflecting the greater density of membrane area in dendritic than somatic regions of neuropil. Similar observations have been made using [3H] ouabain to mark Na+/K+ ATPase distribution in brain [ 16 ] Another striking observation from images of the hippocampus in non-transgenic mice (Figure 3C ) demonstrate a decreased intensity of staining along the dentate granule cell projection pathways within the hilus and along the mossy fiber projections to CA3 (Figure 3A ). This can also be observed at higher magnification in figure 3A , where there is reduced staining to the left of the somatic staining in the inner molecular layer. Although not commented upon, this too can be observed in micrographs of [3H] ouabain autoradiography [ 17 ]. Cortical staining (Figure 3D ) revealed a fairly uniform pattern, with the exclusion of white matter. The difference in Na+/K+ ATPase staining between non-transgenic and APP+PS1 forebrain areas is the absence of staining where amyloid plaques are present in the APP+PS1 mice (Figure 3E & 3F ). Subsequent Congo red staining of these amyloid plaques confirmed that the loss of Na+/K+ ATPase staining was not only present in the center of the plaque, but also in a penumbral zone immediately surrounding the congophilic material, resulting in a "halo" (Figure 2A , 3G , 3H & 4A ). Higher power magnification clearly demonstrated the lack of Na+/K+ ATPase staining surrounding the congophilic plaques (Figure 4A and 4B ). These findings led us to postulate that the osmotic imbalance brought on by an absence or inhibition of Na+/K+ ATPase may contribute to the swelling associated with dystrophic neurites found in the vicinity of congophilic plaques in APP+PS1 mice and AD patients. We designed a dual immunostain utilizing immunohistochemical methods for Na+/K+ ATPase and immunofluorescence methods for phosphorylated neurofilament, a dystrophic neurite marker we evaluated earlier [ 12 ]. Using this assay, we were able to demonstrate that the dystrophic neurites were almost exclusively present within the zone surrounding the congophilic plaque that lacked Na+/K+ ATPase staining. This is represented in a triple staining overlay of the fluorescent neurites from figure 4C onto the bright field image of Na+/K+ ATPase and Congo red staining from figure 4B (Figure 4D ). The arrows in figure 4C demarcate where dystrophic neurites are present. Finally, to determine whether amyloid could inactivate Na+/K+ ATPase activity, we measured the activity of purified cerebral Na+/K+ ATPase after exposure to various concentrations of Aβ 1–42 peptide in a DMSO+water suspension or a DMSO+neutralized HCl suspension. Figure 5 demonstrates that increasing concentrations of the DMSO+water Aβ soluble preparation dose-dependently reduced Na+/K+ ATPase activity, whereas the fibrillar Aβ preparation suspended in DMSO+neutralized HCl did not demonstrate the same effect. There were significant reductions in Na+/K+ ATPase activity at the lower concentrations of 112 and 225 μg/ml compared to vehicle, but maximal reductions were at the highest concentration of the DMSO+water Aβ suspension (450 μg/ml). Discussion Over the past 6 years, our group has characterized various aspects of the APP+PS1 transgenic mice including their pathology, behavior, and gene expression. With age, these mice progressively develop more amyloid plaques surrounded by dystrophic neurites, activated microglia and astrocytes [ 12 ]. With increasing amyloid burden, aged animals consistently develop memory deficits in the radial arm water maze (RAWM; [ 13 , 18 , 19 ], and, there is as yet no evidence for neuronal or synaptic loss. [ 6 , 20 , 21 ]. We have also demonstrated that several genes critical for synaptic plasticity and memory consolidation are down-regulated in these mice exclusively in those brain regions which accumulate amyloid [ 6 ] and the induction of a subset of immediate-early genes is impaired when the transgenic mice are introduced to a novel environment [ 7 ]. Here, we show that Na+/K+ ATPase has decreased enzyme activity in the amyloid-containing hippocampus of APP+PS1 transgenic mice. We have also demonstrated by immunohistology that Na+/K+ ATPase protein expression is reduced in the immediate vicinity of congophilic plaques, a zone where dystrophic neurites are most prevalent, suggesting that disrupted ionic homeostasis may contribute to their formation. Additionally, high concentrations of Aβ 1–42 directly inhibit the activity of Na+/K+ ATPase. This suggests that in the area surrounding amyloid plaques, where the local Aβ concentration is likely high, Na+/K+ ATPase activity may be locally inhibited. From previous gene expression studies, we found that the mRNA for the Na+/K+ ATPase αIII subunit was consistently down-regulated ~30% in the hippocampi of APP+PS1 mice compared to non-transgenic littermates and to the amyloid-free cerebella [ 6 ]. These reductions were also demonstrated in human Alzheimer's disease samples, consistent with data from previous investigations [ 6 , 22 ]. Using a sensitive colorimetric assay to measure activity of Na+/K+ ATPase modified from Ellis et al. [ 23 ], we were able to demonstrate that in the APP+PS1 hippocampus, the specific activity of ouabain-sensitive ATPase was significantly reduced (figure 1B ) while Na+/K+ ATPase activity in the amyloid-free cerebellum remained unperturbed with respect to genotype. Cerebellar activity was substantially lower than that seen in the non-transgenic hippocampal tissue, perhaps indicative of the abundant white matter found in this region, where Na+/K+ ATPase activity is low. These data demonstrate that the function of Na+/K+ ATPase is perturbed in a brain region that contains high overall concentrations of Aβ. Previous investigations have shown that Na+/K+ ATPase protein levels are decreased in AD tissue but not in normal aged tissue [ 24 , 25 ], but it is difficult to dissociate the loss due to neuronal death from any loss caused directly by Aβ inhibition. This demonstration that reduced activity along with a trend for reduced protein levels can be determined in homogenates from animal models of amyloid deposition argues that at least some of this loss in AD brain is associated with direct actions of Aβ. In vitro data suggests that Na+/K+ ATPase activity can be blocked directly by various Aβ peptide fragments in cultured neurons [ 26 ] and that even the purified enzyme can be inhibited by high concentrations of Aβ (Figure 5 ). When we immunostained transgenic mouse tissue to visualize the distribution of Na+/K+ ATPase alpha III subunits we found that in areas where congophilic plaque staining was apparent, Na+/K+ ATPase staining was absent, and more specifically, there appeared to be no or little Na+/K+ ATPase staining in a penumbral zone surrounding the plaques stained with Congo red (Figures 3E–H and 4A–B ). While most immunostaining protocols detect voids at the sites where congophilic plaques are located, these areas appeared somewhat larger in the Na+/K+ ATPase immunostained sections. This led us to speculate about that a reduction in the activity of this extremely important enzyme may have severe impacts on the functions of neurons in the vicinity of the deposits. We knew from previous studies that dystrophic neurites could be visualized surrounding amyloid plaques in the APP+PS1 mice. And we have demonstrated previously that proteins such as synaptophysin and APP are in fact increased in dystrophic neurites [ 12 ]. Therefore, we decided to stain sections for Na+/K+ ATPase and dystrophic neurites, along with amyloid plaques using Congo red, to determine whether Na+/K+ ATPase was absent from these neurites and in their immediate vicinity. We found empirically that staining the ATPase with a peroxidase label and the phosphorylated neurofilament with a fluorescein label to detect dystrophic neurites was the most effective way to see both markers on the same section along with the Congo red stained plaques. Imaging of these sections revealed that dystrophic neurites are in the circumferential area surrounding the congophilic amyloid plaques where Na+/K+ ATPase staining is absent (Figure 4D ). One possible explanation for this putative relationship would be that Aβ associated inhibition of Na+/K+ ATPase activity would result in osmotic imbalance and cause the neurites to begin swelling. In addition to the loss of electronic properties and accompanying dysregulation of neuronal signaling, these changes might even feedback to influence gene expression. Indeed, Huang et al. demonstrated that cells exposed to ouabain have reduced Na+/K+ ATPase αIII subunit mRNA expression [ 27 ]. An alternative pathway may involve interactions of Aβ with surface proteins, such as integrins [ 28 , 29 ]. and focal adhesion proteins [ 30 ] leading to activation of signal transduction cascades that mediate tyrosine phosphorylation [ 31 ]. Bozulic et al. reported that the tyrosine kinase, Lyn, can phosphorylate Na+/K+ ATPase resulting in its removal from the membrane [ 32 ]. These findings suggest that either direct inhibition of Na+/K+ ATPase by amyloid or its removal due to amyloid-mediated activation of a signaling cascade, could contribute to the formation of dystrophic neurites due to osmotic and/or ionic imbalances. Aβ has been shown to bind various cell surface proteins [ 26 , 33 , 34 ]. and induce neuro-toxicity in vitro [ 35 - 37 ]. To determine the effect of Aβ 1–42 on Na+/K+ ATPase activity, we pre-incubated purified Na+/K+ ATPase with Aβ then colorimetrically measured enzyme activity. Although both preparations of Aβ did suppress activity at 112 μg/ml (~10 μM) and 225 μg/ml (~50 μM), it was the highest concentration (450 μg/ml or ~100 μM) of the soluble Aβ suspension that precipitated the largest reduction in activity compared to vehicle, nearly rendering it completely inactive (Figure 5 ). The fibrillar Aβ preparation did not exact the same precipitous decline in activity, demonstrating that it is not simply an artifact caused by high concentrations of a peptide that reduced activity. Further investigations will be required to determine which physicochemical form of Aβ is causing the reduced activity. This suggests that the Aβ can directly bind to the Na+/K+ ATPase and decrease its activity. Mark et al. suggests that the 25–35 amino acid region of the Aβ peptide induces oxidative stress thereby impairing Na+/K+ ATPase activity [ 26 ], and the findings presented herein are consistent with this earlier work. Conclusions These data indicate that Aβ deposition in transgenic mice is associated with reduced activity of Na+/K+ ATPase. In vitro studies suggest that high concentrations of Aβ can quickly inactivate the enzyme activity. One area in the brain that might harbor Aβ concentrations sufficient to suppress the activity of Na+/K+ ATPase would be the micro-domain near and immediately around the plaques. This is the area demonstrated to have reduced immunostaining for Na+/K+ ATPase, while exhibiting increased phosphorylated neurofilament staining consistent with dystrophic neurites. These results lead to the possibility that one factor contributing to the formation of dystrophic neurites is loss of ionic homeostasis. Such changes might explain the "swollen" nature of these neuronal processes in the vicinity of plaques. It might also lead to sufficient disruption of electro-chemical properties as to disrupt normal information processing and lead to memory dysfunction. If these suggestions are correct, drugs targeted at activating Na+/K+ ATPase and maintaining ionic balance in these neurons may benefit Alzheimer's patients by delaying the onset of neuritic dystrophia and memory dysfunction. Methods Tissue preparation Mice were bred in our facility and genotyped using previously described methods [ 19 ] The working memory performance of the APP+PS1 mice used in these studies was impaired when compared to non-transgenic littermates as published previously [ 14 ]; untreated groups were studied here). For tissue collection, 17–18 month old mice were deeply anesthetized with pentobarbital (100 mg/kg) and perfused transcardially with phosphate buffered saline. Brains were removed and bisected into right and left hemispheres. The right hemisphere was immediately dissected into regions that were immediately frozen on dry ice, while the left hemisphere was post-fixed in 4% para-formaldehyde for 24 hours and subsequently processed through a cryo-protection schedule of 10, 20 and 30% sucrose. Frozen brains were sectioned horizontally on a sliding microtome at 25 μm and stored in Dulbecco's phosphate buffered saline plus azide at 4°C. Na+/K+ ATPase activity assay and amyloid preparation An assay to detect specific activity of Na+/K+ ATPase by measuring the release of phosphate was developed using a variation of the method described by Ellis et al. [ 23 ]. Freshly frozen dissected hippocampi, cortex and cerebella (20–30 mg tissue weight) from APP+PS1 and non-transgenic littermates were homogenized using a rotor-stator homogenizer in 1 ml of cold suspension buffer containing 85 mM sodium chloride (NaCl), 20 mM potassium chloride (KCl), 4 mM magnesium chloride (MgCl), 0.2 mM EGTA and 30 mM histidine pH 7.2. Saponin was added to the samples to a final concentration of 20 μg/ml. They were then incubated at 37°C for 15 minutes. Protein concentration was measured by Bradford assay and concentrations were adjusted to 10 mg/ml. In a 96-well plate, 60 μl of ATP buffer containing 140 mM NaCl, 20 mM KCl, 3 mM MgCl, 30 mM histidine and 3 mM ATP were added to wells. Two sets of samples were included, one with ATP buffer only and the other with 100 μM of the Na+/K+ ATPase selective inhibitor ouabain added to the ATP buffer. Subsequently, 10 μl of protein homogenates were added to the ATP buffer ± ouabain, which were then mixed by pipetting and incubated at 37°C for 30 minutes. The reaction was stopped by adding 120 μl of an acid molybdate solution consisting of 0.5 g ammonium molybdate (Sigma, St. Louis, MO) in 0.5 M sulfuric acid. After mixing, 10 μl of Fiske Subbarow Reducer (Sigma, St. Louis, MO) was added and wells were mixed again. The plate was allowed to incubate covered at room temperature for 10 minutes and then measured spectrophotometrically at 660 nm. A standard curve of phosphoric acid dilutions was used to calculate the specific activity of the ouabain sensitive ATP hydrolysis and converted to μmols of inorganic phosphate (Pi) liberated/mg protein/ hour. All reactions were performed in triplicate, which were then averaged to produce the single value for the sample. Differences between APP+PS1 and non-transgenic mice were analyzed for significance using one-way ANOVA. Aβ used for these studies was generated by resuspending 1 mg of commercially available recombinant Aβ 1–42 peptide (rPeptide, Athens, GA) in 221 μl of 1,1,1,3,3,3-Hexafluoro-2-propanol (HFIP, Sigma, St. Louis, MO) to generate 45 μg Aβ 1–42 films. These films were resuspended in 2 μl of anhydrous DMSO, followed by agitation and subsequent addition of either 48 μl of cold water followed by overnight incubation at 4°C (for soluble Aβ preparation) or 10 mM HCl followed by overnight incubation at 37°C (for fibrillar Aβ preparation). The acid was neutralized the following day by the addition of NaOH. These preparations yielded approximately 900 μg/ml suspensions of Aβ. For analysis of activity inhibition by both preparations of Aβ, purified Na+/K+ ATPase (from brain; Sigma, St. Louis, MO) was pre-incubated for 2 hours in a 37°C orbital shaker separately with 112.5, 225 and 450 μg/ml of either a DMSO+water Aβ suspension or a DMSO+neutralized HCl Aβ suspension. Vehicle alone was also used for each preparation and sample values are indicated as a percentage of the "vehicle only" values. Activity was then measured using the same activity assay as above and significance was measured using one-way ANOVA comparing activity between vehicle treated and Aβ treated. Western blot Brain homogenate from cortical tissue was equilibrated to 10 μg of total protein. This homogenate, along with 1 μg of purified cerebral Na+/K+ ATPase, was diluted 1:1 with loading buffer containing 4% SDS and 5% β-mercaptoethanol, heated to 95°C for 5 minutes and loaded onto a 7.5% Tris-glycine gel which was electrophoresed at 100 mV for one hour in the presence of SDS. The protein was subsequently transferred onto an Immobilon membrane (Millipore, Billerica, MA) for one hour at 100 mV. The blot was rinsed with borate saline + 0.05% Tween-20 (BST) and blocked overnight at 4°C in 5% non-fat dry milk (NFDM). The following day, a 1:2000 dilution of rabbit anti-rat Na+/K+ ATPase αIII antibody (Upstate Biotech, Lake Placid, NY) in 0.5% NFDM+BST was applied to the blot for 1 hour, followed by washing and a subsequent 1 hour incubation with a 1:5000 dilution of hrp-labeled anti-rabbit IgG (Sigma, St. Louis, MO) in 0.5% NFDM+BST. After washing, the blot was developed for chemiluminescence using a luminol substrate kit (Santa Cruz Biotech, Santa Cruz, CA). Band density was quantified using the SoftMax Pro program and one-way ANOVA was used to determine significance. Histology Immunohistochemical and immunofluorescence analyses for Na+/K+ ATPase αIII and phosphorylated neurofilament, respectively, were performed on the same 25 μm free-floating hippocampal sections. Sections were treated 15 minutes with 10% methanol, 3% hydrogen peroxide and 80% phosphate buffered saline (PBS) to block endogenous peroxidase activity, and then washed 3 times with PBS. Sections were subsequently treated with sodium borohydride for 15 minutes to reduce background auto-fluorescence [ 38 ] followed by washing with PBS. Sections were then permeabilized for 30 minutes with 100 mM lysine, 0.2% triton x-100, 2% goat serum and 2% horse serum in PBS, and washed 3 times with PBS. Because one antibody was murine being used on mouse tissue, endogenous mouse IgG was first blocked with a 1:300 dilution of goat F (ab') 2 anti-mouse IgG (overnight; Protos Immunoresearch, Burlingame, CA). Sections were washed the following day and co-incubated with a 1:5000 dilution of a rabbit anti-rat Na+/K+ ATPase αIII IgG (Upstate Biotech, Lake Placid, NY) and a 1:10,000 dilution of a mouse monoclonal IgG1 ascites pool specific for phosphorylated forms of neurofilament (SMI-312; Sternberger Monoclonals, Lutherville, MD) in 2% goat serum and 2% horse serum in PBS. The following day, sections were washed, and then co-incubated in both a 1:3000 dilution of anti-rabbit biotinylated secondary antibody (Vector Laboratories, Burlingame, CA) and a 1:100 dilution of anti-mouse fluorescein conjugated secondary antibody (Vector Labs, Burlingame, CA) for 2 hours. After washing, the tissue was incubated with Vectastain ® Elite ® ABC kit (Vector Labs, Burlingame, CA). The tissue was then washed and stained with a diaminobenzidine: peroxide system plus nickel enhancement (DAB/Ni 2+ ), followed by final washes. Compact amyloid plaques were visualized using Congo red staining after sections were slide mounted and dried [ 19 ]. Briefly, slides were incubated in alkaline alcoholic saturated sodium chloride (AASSC), followed by 0.2% Congo red in AASSC, then dehydrated and cover-slipped with xylene-free Vectamount (Vector Labs, Burlingame, CA). Other mounting media were tested, but only Vectamount was suitable for combined immunohistochemistry, immunofluorescence and Congo red staining. The extent of nonspecific binding was assessed in the absence of primary antibodies for all assays. Specificity of the Na+/K+ ATPase antibody was confirmed by reduced staining following a 2 hour pre-incubation of the antibody with purified cerebral Na+/K+ ATPase at a 1 antibody to 4 enzyme molecule ratio. Both immunostains were characterized individually before the co-incubation procedure was implemented. Authors' contributions C D contributed to the design the study, developed the activity assay, generated the Aβ preparations, performed the histology and western blotting, and drafted the article. M G was responsible for maintenance of the animals used in the study, prepared the tissue for subsequent analysis, and assisted in the design. Both D W and D H participated in the histology and contributed to the coordination of the study. M B facilitated the investigations and assisted with histology. M F performed the genotyping of the mice. D M conceived of the study, and contributed to its design and coordination, along with helping to draft the manuscript. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC549198.xml
535535	In vivo gene targeting of IL-3 into immature hematopoietic cells through CD117 receptor mediated antibody gene delivery	Background Targeted gene transfection remains a crucial issue to permit the real development of genetic therapy. As such, in vivo targeted transfection of specific subsets of hematopoietic stem cells might help to sustain hematopoietic recovery from bone marrow aplasia by providing local production of growth factors. Methods Balb/C mice were injected intravenously, with an anti-mouse c-kit (CD117) monoclonal antibody chemically coupled to a human IL-3 gene-containing plasmid DNA. Mice were sacrificed for tissue analyses at various days after injection of the conjugates. Results By ELISA, the production of human IL-3 was evidenced in the sera of animals 5 days after treatment. Cytofluorometric analysis after in vivo transfection of a reporter gene eGFP demonstrated transfection of CD117+/Sca1+ hematopoietic immature cells. By PCR analysis of genomic DNA and RNA using primer specific pIL3 sequences, presence and expression of the human IL-3-transgene were detected in the bone marrow up to 10 days in transfected mice but not in control animals. Conclusions These data clearly indicate that antibody-mediated endocytosis gene transfer allows the expression of the IL-3 transgene into hematopoietic immature cells, in vivo . While availability of marketed recombinant growth factors is restricted, this targeting strategy should permit delivery of therapeutic genes to tissues of interest through systemic delivery. In particular, the ability to specifically target growth factor expression into repopulating hematopoietic stem cells may create new opportunities for the treatment of primary or radiation-induced marrow failures.	Introduction In vivo gene targeting of highly specific cell subsets remains the main challenge for gene therapy of a broad range of conditions associated with acquired diseases, including infectious disorders, cancer and failure of the hematopoietic system [ 1 , 2 ]. In vivo gene transfection is more appealing than in vitro transfection of an aliquot of cells or tissue that would be then reinfused to the patients, because it potentially concerns the total population of targeted cells disseminated in the whole body; this is particularly relevant to patients with primary or secondary failures of the hematopoietic system, since, in most instances, residual foci of hematopoiesis exist that cannot be easily located and cannot be collected by a marrow harvest procedure. In vivo targeted transfection of specific subsets of hematopoietic stem cells (HSC) might help to sustain hematopoietic recovery from bone marrow aplasia by providing local production of growth factors. Systemic gene delivery systems are needed for therapeutic applications in which the target cells are not directly accessible [ 3 ]. However, for several reasons including lack of cell specificity and safety, in vivo targeted gene transfer cannot use current viral vectors. Although cationic liposomes have been promising systems in transfecting cells in tissue culture, it has been recognised that their in vitro efficiency does not correlate with their ability to deliver DNA after in vivo administration [ 4 - 10 ]. Tissue-specific targeting can be achieved through ligand receptor interactions [ 11 , 12 ]. We have already described a technique of antibody-mediated targeted gene transfection termed antibody delivery system [ 11 , 12 ]: a ligand (capable of binding to the surface of the targeted cells) conjugated with plasmid DNA retains its ability to specifically interact with cognate receptors on the cell surface. In previous studies, antibodies directed against internalised cell surface antigens such as the T lymphocyte-related CD3 molecule or the B lymphocyte-related surface IgD were chemically coupled to purified plasmid DNA encoding various reporter genes. This approach was validated both in vitro by the transfer of G418 resistance (neo r ) into human T-cell lines [ 13 ] or human hematopoietic immature cells [ 14 ] and in vivo by the transfer of β-galactosidase activity into mouse splenocytes [ 13 ]. We have reported that this strategy can be applied to targeted gene delivery to human renal carcinoma cells [ 15 ]. More recently, in vivo , we have shown a specific tumor targeting after a single intravenous injection in mice bearing tumour expressing the renal carcinoma – related G250 tumor associated antigen [ 16 ]. We have previously reported that the method is suitable for the production of a functional growth factor in specifically CD117+ targeted cells, mediating an in vitro biological effect on hematopoiesis [ 14 ]. As our previous report evidenced interaction of the conjugate with hematopoietic cells in vitro , this study was focused on specific in vivo targeting of hematopoietic tissues. In the present study, we used anti-CD117 (c-kit) mAb covalently coupled to human IL-3 -encoding plasmid DNA. CD117 antigen is expressed on a CD34+ hematopoietic subpopulation and is readily internalised upon binding to its ligand [ 17 ]. Thus, targeted-gene transfer through CD117 may be achieved in this cell subset. We indeed demonstrated an in vivo targeting of hematopoietic immature cells via a systemic route, mediating an efficient in vivo transgene expression. Methods Ab-DNA conjugation The human IL-3 coding sequence (R&D Systems, Minneapolis, Minnesota) was ligated to synthetic fragments containing the natural leader sequence of human IL-3 and was subcloned into pCEP4 vector (Invitrogen Corporation). Transgene expression was controlled by the cytomegalovirus (CMV) enhancer-promoter sequence. The Epstein-Barr Virus replication (oriP) and nuclear antigen (encoded by the EBNA-1 gene) were carried by this plasmid to permit extrachromosomal replication in human, primate and canine cells [ 18 ]. pCEP4 also carries the hygromycin B resistance gene for stable selection of transfected cells. The resulting vector was named pIL3. IgG mAbs were chemically coupled to plasmid DNA as previously described [ 13 ]. Briefly, purified IgG (3 mg/ml) in borate buffer (pH 8.2) (100 mM boric acid, 25 mM sodium tetraborate, and 75 mM NaCl) were activated using 3 mg/ml (final concentration) of benzoquinone (Sigma-Aldrich, St Louis, Missouri, USA). After gel filtration through a G25 column (Roche Diagnostics, Mannheim Germany) activated IgG were then covalently linked to pIL3 24 hours, in 0.1 M carbonate buffer (pH 8.7), in a ratio of 100 μg of plasmid DNA for 10 μg of IgG antibody. IgG-plasmid conjugates were then purified by HPLC. Antibodies used was clone 2B8 a monoclonal rat anti mouse IgG reacting with the mouse p145 c-kit protein (CD117) (BD Biosciences Pharmingen Tullastrasse, Heidelberg, Germany). The negative control was the mouse G250 IgG1 mAb reacting with human renal cell carcinoma (kindly provided by Dr A. Gorter, The Netherlands) [ 19 ]. The quantities of conjugates were expressed as the quantities of plasmid initially used for reaction. In vivo transfection assessment We have previously shown that in vitro transfection of HSC may be observed in a dose-dependent effect for up to 100 μg of conjugate [ 14 ]. BalbC mice (6 weeks) were intravenously injected with a dose of up to 400μg of monoclonal 2B8 (BD Biosciences Pharmingen) covalently coupled to the pIL3 plasmid (named conjugate) and as negative control the monoclonal 2B8 and plasmid DNA uncoupled (named unconjugate) or irrelevant human monoclonal antibody (G250) covalently coupled to the pIL3 plasmid (named control conjugate) or physiological serum (named control serum). In a set of experiments, two intraperitoneal injections of chloroquine (32.5 mg/kg) were performed 2 hours and just a few minutes before intravenous injection of conjugates. The tolerance of chloroquine (used to prevent the degradation of the plasmid for transfection assays, 20) was in the range reported in mice for the study of malaria treatment [ 21 ]. Monoclonal antibody (mAb) 2B8 (BD Biosciences Pharmingen) was covalently coupled to 100 μg of the enhanced green fluorescent protein encoding plasmid pEGFP-1 provided from Clontech and was named eGFP conjugate. Mice were intravenously injected twice (day 0 and day 2) and euthanasied 5, 7 or 10 days after the first injection of the conjugate, after proper anaesthesia. Human IL-3 production in serum was assayed by High Sensitivity ELISA (R & D Systems). Controls were sera or cell culture supernatants of control mice (unconjugate, control conjugate, control serum). After euthanasia, the presence of the transgene was investigated in blood, brain, lungs, liver, spleen, kidneys, adrenal glands and bone marrow. In order, to observe toxicity the weight of mice and their organs were measured (brain, lungs, liver, spleen, kidneys). In mice injected with eGFP conjugate, a MACS magnetic cell separation systems (Miltenyi Biotec, Sunnyvale, CA) was used to enrich cells expressing CD117 and Sca1 from mononuclear bone marrow cells. Negative and positive cells were collected for experimental use. To achieve a purity greater than 50%, it was necessary to perform two sequential passes through magnetic columns. The overall recovery of CD117 was about 30% and enrichment 40 fold, as assessed by the fraction of CD117/Sca1 positive population before and after separation. Cells were analysed by flow cytometry to determine the purity of cell fractions. Then the presence of eGFP positive cells was investigated by flow cytometry into negative fraction (CD117/Sca1 negative populations) and positive cell fractions (CD117/Sca1 positive populations). All experiments were conducted according to French regulation for animal experimentation (Ministry of agriculture Act No.87848, 1987). Long-term cultures Long-term cultures of bone marrow cells were performed, as previously described [ 22 ]. At one week, 50 μg/ml of hygromycin were added to the long-term culture, in order to select for stably transfected cells (plasmid conferred hygromycin resistance to stably transfected cells). After 1-week selection, these cells were cultured 2 weeks in long-term culture medium. Viable cells were numbered using trypan blue exclusion assay. Clonogenic hematopoietic progenitor assay 5 × 10 5 cells from bone marrow were assayed for clonogenic hematopoietic immature cells [ 23 ]. Briefly, cells were plated in triplicate in 35-mm dishes at a concentration of 5 × 10 5 cells/ml in complete methylcellulose M3434 from Stem Cell Technologies (West Broadway, Vancouver, Canada). Cultures were incubated at 37°C in 5% CO 2 and removed at 14 days. Colonies were defined as containing more than 40 cells using an inverted microscope. Cells were then harvested and studied for IL-3 gene expression. Two weeks post-transfection, semi-solid colonies were removed from methylcellulose culture for PCR analysis of the presence of the pIL3 plasmid. DNA and RNA analyses The simultaneous isolation of total cellular RNA and DNA from tissues or cells was performed using TriPure Isolation Reagent Kit (Roche Diagnostics) [ 24 ]. Total cellular RNA was incubated 30 min in the presence of RNAse-free DNAse (Invitrogen), heated at 90°C for 5 min and promptly cooled at 4°C. The RT-PCR was then carried out as previously described [ 25 ]. Briefly, total cellular RNA was first annealed with 1 mM of oligo-dT15 (Sigma-Aldrich) and then incubated at 42°C for 1 hour in the presence of 100 units of Moloney murine leukemia virus reverse transcriptase (Invitrogen) in a final volume of 20 μl. DNA or the reverse transcriptase reaction mixtures were then subjected to PCR amplification using sense primer (GTGGTTTGTCCAAACTCATC) and anti-sense primer (AGAGCTCGTTTAGTGAACCG) located on both sides of the IL-3 gene (into the multiple cloning site of pCEP4), which resulted in a PCR product specific of the gene inserted in the pCEP4. Nested PCR was performed using sense (CCAAACTCAATGTATCTTATCATGTCT) and anti-sense (TCAGATTCTAGAAGCTTGGGT) primers localized in the multiple site of clonage of pCEP4 plasmid. These pairs of primers allow for detection of a 542 bp fragment when electrophoresed on a 2% agarose gel and visualization with ethidium bromide. Specificity of PCR products was controlled using an internal 33 P-5'-end labeled oligo-probe specific of human IL3 coding sequence (ACGGCCGCACCCACGCGACA), in Southern blot analysis as previously described [ 26 ]. To detect a false positive due to plasmid contamination, we have tested RNA samples by direct amplification of RNA (without the reverse transcription step). Indeed in the absence of plasmid, Taq pol will be unable to amplified RNA whereas a PCR product would be observed if the RNA sample was contaminated with plasmid DNA. No DNA plasmid contamination was observed for all the assayed RNA samples. As internal control a 590 bp region of the endogenous mouse RAP-SYN gene was also amplified using a second set of unique 30 bp primers (sense: AGGACTGGGTGGCTTCCAACTCCCAGACAC, anti-sense: AGCTTCTCATTGCTGCGCGCCAGGTTCAGG), which allows the detection of a 590 bp fragment [ 27 ]. Results Assessment of transgene product secretion Balb/C mice were intravenously injected twice (day 0 and day 3), with the anti-mouse CD117 (c-kit) 2B8 mAb conjugated to pIL3 expression vector. Control animals received unconjugated pIL3 expression vector and 2B8 mAb (named control unconjugate) or irrelevant G250 mouse mAb covalently coupled to the pIL3 plasmid (named control conjugate) or physiological serum (named control serum). To increase the transgene processing into cells, mice were injected with the conjugate up to a dose of 400μg in the presence or not of chloroquine known to diminish endosomal DNA degradation [ 20 ]. Mice were euthanasied 5, 7 or 10 days after the first injection of the conjugate. The presence of human IL-3 in serum was measured by a human IL3 specific ELISA, from 5 to 10 days. Using 400μg of conjugate in the presence of chloroquine, we detected human IL-3 in the serum of mice at 50 pg/ml at day 5 (table 1 ). No human IL-3 was observed in the serum of mice sacrificed at days 7 and 10 nor in mice injected with lower dose of conjugate, with control unconjugate or control conjugate (data not shown). Table 1 Detection of circulating human IL-3 in mouse serum at day 5 post injection of pIL3 conjugate Treatment (IP injection) Quantity of conjugate pg/ml of human IL-3 in mice Chloroquine unconjugate conjugate mean sd mean Sd 0 100μg 0 0 0 0 0 400μg 0 0 0 0 2 × 32.5 mg/kg 100μg 0 0 0 0 2 × 32.5 mg/kg 400μg 0 0 50* 17 The presence of human IL-3 in serum was investigated by ELISA. The data are representative of three independent experiments and are the mean of triplicate determinations ± S.D. * indicates statistically significant differences by Student's t -test analysis; p < 0.007 as compared to 400μg of unconjugate. Assessment of transfection cell specificity Gene targeting was then evaluated by injecting mice with eGFP conjugated or unconjugated to either 2B8 mAb or to G250 control mAb. At day 5, the presence of transfected cells into bone marrow mononucleated cells was analysed into the purified CD117- and CD117+ subpopulations, by flow cytometry using anti-CD117 and anti-Sca1 Abs. As shown in Table 2 , 4.7% cells from the CD117+/Sca1- and 2.8% cells from the CD117+/Sca1+ subpopulations collected from mice injected with the eGFP-2B8 conjugate were positive. All controls were negative. Table 2 Detection of transfected cells in bone marrow mononucleated cells at 5 day postinjection of eGFP conjugate plasmid eGFP Cell population Control serum Unconjugate Control conjugate Conjugate MNC 0 0 0 0 CD117- 0 0 0 0 CD117-/Sca1- 0 0 0 0 CD117+/Sca1- 0 0 0 4.7% CD117+/Sca1+ 0 0 0 2.8% The presence of transfected cells (eGFP positives) in bone marrow was investigated 5 days postinjection among mononucleated cells (MNC): CD117 negative cell population (CD117-), CD117/Sca1 negative cell population (CD117-/Sca1-), CD117 positive/Sca1 negative (CD117+/Sca1-) and CD117/Sca1 positive cell population (CD117+/Sca1+). In all cases no transfected cells were observed in the controls. Assessment of transfection tissue specificity To assess the tissue specificity of the targeting, presence of pIL3 plasmid was investigated in bone marrow, blood cells, liver, spleen, lungs, kidneys, adrenal glands, and brain. PCR analysis of genomic DNA and RNA isolated from bone marrow and blood (or serum) was performed using primer specific pIL3 sequences. Specificity of the PCR and RT-PCR products was assessed by a Southern blot hybridised with a specific radiolabelled human IL3 probe. The expected 542 bp band of the PCR product corresponding to the IL3-transgene presence (both DNA and RNA) were was specifically detected in the bone marrow of transfected mice up to 7 days for RNA and 10 days for DNA, post transfection (figure 1 ). Nested PCR also was positive for the IL3 transgene DNA in the spleen of transfected animals up to day 7 (not shown). In control animals (control serum, unconjugate, control conjugate), pIL3 DNA but no RNA was detected in peripheral blood but not in serum until day 5 after the first injection and then disappeared (figure 2 ); there was no detection of DNA or RNA in bone marrow (figure 1 ). Aside from this, all other tissues were negative when assayed by nested PCR on day 5, 7, 10 in transfected animals. IL3 transgene DNA was only found in the kidney of control animals receiving an unconjugated mixture of Ab and DNA or the control conjugate, on day 5 only (not shown). The measurement of the weight of the mice and their organs (liver, kidneys spleen, brain, adrenal glands, lungs), did not reveal any change, suggesting the lack of toxicity detected in mice receiving the conjugate (data not shown). Furthermore, since no IL3 transgene was evidenced in these organs, further investigation of potential toxicity of conjugate might not be relevant. Figure 1 Nested PCR detection of pIL3 plasmid in bone marrow 5, 7, and 10 days after injection of the conjugate. Mice were intravenously injected twice with 100μg of anti-CD117-pIL3 conjugate (at day 0 and at day 2). Control groups corresponded to bone marrow of mice treated with unconjugated pIL3 and anti-CD117 Abs or control conjugate (G250-pIL3). IL3 DNA and RNA were detected in the bone marrow of animals receiving the pIL3-anti CD117 conjugate up to day 10. The data are representative of three independent experiments. Figure 2 Nested PCR detection of pIL3 plasmid in mononuclear peripheral blood cells 5, 7, and 10 days after injection of the conjugate. Mice were intravenously injected twice with 100μg of anti-CD117-pIL3 conjugate (at day 0 and at day 2). Control group corresponded to mononuclear peripheral blood cells or serum of mice treated with unconjugated pIL3 and anti-CD117 Abs. pIL3 DNA was only detected in peripheral blood of control animals until day 5 after the first injection. The data are representative of three independent experiments. Finally, clonogenic assay hematopoietic immature cells were performed on cells removed from sacrificed animals. As shown in Table 3 , their was no differences in mice receiving the conjugate, control unconjugate, control conjugate and mice receiving physiological control serum. These data clearly demonstrated that our approach did not alter the hematopoiesis. Table 3 Frequencies of colonies in bone marrow following transfection anti-CD117-pIL3 conjugate Days Control serum Unconjugate Control conjugate Conjugate mean sd mean sd mean sd mean sd 5 191 10 183 8 192 10 185 25 7 157 55 152 50 192 12 197 16 10 187 23 173 11 182 22 187 26 Number of colonies was measured 5, 7 and 10 days following in vivo transfection with 100μg of anti-CD117-pIL3 conjugate. Control groups corresponded to mice injected with unconjugated pIL3 and anti-CD117 mAb or with the control conjugate (G250-pIL3). 5 × 10 5 cells from bone marrow were cultured in complete methylcellulose. Colony (aggregates of more than 40 cells) numbers were evaluated under inverted light microscope. The data are representative of three independent experiments and are the mean of triplicate determinations ± S.D. Lack of transgene integration Long-term cultures of bone marrow cells from mice receiving the conjugate or the controls were performed. After 1 week of selection in hygromycin-containing medium (plasmid conferred hygromycin resistance), cells were cultured for another 2 weeks and then viable cells were quantified using trypan blue exclusion assay. As illustrated on Figure 3 , upon hygromycin selection, no viable cell was found in mice transfected with anti-CD117-pIL3 conjugate, suggesting that there was no integration of pIL3 into host DNA. Figure 3 Morphology of survival long-term bone marrow cells. (a) Long-term bone marrow cells were cultured 7 days. (b) After a 1-week culture, 50μg/ml of hygromycin was added in order to select for stably transfected cells. After 1 week of selection, these cells were cultured 2 weeks in long-term culture medium. Cells observed in controls or in long-term culture in mice injected with the conjugate were viable (original magnification ×400). Discussion Although much progress has been accomplished in the field of gene therapy over the last years, there is still a need to develop more effective vectors and new strategies [ 28 ]. Using a non-viral gene delivery system, targeting primary hematopoietic stem/progenitor cells in vitro can be especially useful for studying the biological effects of various growth factors [ 29 ]. Our conjugate linking an anti-CD117 mAb to a pIL3 plasmid should be a good candidate to target specifically hematopoietic stem cells. We have previously reported that the method is suitable for the production of a functional growth factor in specifically CD117+ targeted cells, mediating an in vitro biological effect on hematopoiesis [ 14 ]. Since our previous report evidenced interaction of the conjugate with hematopoietic cells in vitro , the present study focus on specific targeting of hematopoietic tissues, in vivo . We first demonstrated the efficacy of our approach since the transgene and its product (RNA and circulating human IL3) were found in mice injected with anti-CD117/pIL3 conjugate. It is of note that although human IL3 was only detected in plasma of chloroquine-treated mice injected with high quantity of conjugate (400μg); human IL3 encoding RNA were evidenced in treated mice injected with lower quantity of conjugate (100μg). These results were in accordance with the design of these experiments aiming at observing even a transitory and local effect (within the bone marrow). PCR analyses of tissues evidenced the specific targeting of the hematopoietic system since brain, liver and lungs were negative. Only the spleen of mice transfected with the conjugate and kidneys of control animals (transfected with unconjugate mixture of Ab and DNA or with the control conjugate) displayed a positive PCR signal. Observed shortly after the last plasmid injection in blood, the presence of plasmid might be due to the intravenous administration route used and in kidney, to a progressive elimination of the plasmid in this organ of refinement. These results correspond to kinetic of plasmid availability when not using the specific vector (conjugate) to carry plasmid into progenitor cells. In the latter case, CD117+ cells were specifically transfected, and among them, Sca1+ cells were positive, suggesting a targeting of hematopietic progenitor cells via the systemic route. Several parameters contribute to the efficiency and specificity of our system such as the internalisation of the antigen targeted, the choice of the transgene used, the tissues targeted, the conformation of the conjugate. Bone marrow was a good candidate for gene targeting as it is a highly proliferative tissue, as opposed to tissues which possess terminally differentiated cells such as hepatocytes or adipocytes, which are more resistant to transfection [ 30 ]. Factors affecting the bioavailabilty of the administered conjugates strongly determine their in vivo performance. These include avid interaction with serum components, resulting in colloidal instability, including both aggregation and dissociation of the conjugates and rapid elimination from blood circulation [ 31 , 32 ]. Therefore, the gene delivery carrier should function as a protector of DNA during in vivo administration. Protamine has been shown to cause condensation of DNA, which promotes cellular entry [ 33 , 34 ]. Our complex of plasmid and antibody may have been sufficiently compacted to resist nuclease degradation and non-specific interaction with plasma proteins. Furthermore the reduced dimensions of the conjugate may have been sufficient to allow its diffusibility through the extracellular space to reach bone marrow cells. Conclusions Our gene delivery system is specific and leads to transient gene delivery and expression. It may prove useful and safe for numerous clinical applications of gene transfer in hemato-oncology and radiopathology, whereby a stable genetic modification is not required, in contrast to the gene therapy approaches for genetic diseases. For example, it may be of interest to facilitate the long-term reconstitution of hematopoiesis through transient gene delivery into progenitor cells of patients after therapeutic and /or accidental exposure to chemo/radiotherapy. Whether our approach could be used to potentate hematopoietic reconstitution following irradiation remains to be studied. List of Non-Standard Abbreviations Used HSC Hematopoietic Stem Cells Competing Interests The author(s) declare that they have no competing interests. Authors' contributions AC, OD, AD, MB, SF, MM, PP carried out the studies. FH, DT participated to the designed of the study and its coordination. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535535.xml
526213	Current practices in the spatial analysis of cancer: flies in the ointment	While many lessons have been learned from the spatial analysis of cancer, there are several caveats that apply to many, if not all such analyses. As "flies in the ointment", these can substantially detract from a spatial analysis, and if not accounted for, can lead to weakened and erroneous conclusions. This paper discusses several assumptions and limitations of spatial analysis, identifies problems of scientific inference, and concludes with potential solutions and future directions.	Introduction 'Dead flies cause the ointment of the apothecary to send forth a stinking savor; so doth a little folly him that is in reputation for wisdom and honour.' Ecclesiastes 10:1 The term "flies in the ointment" is occasionally used to describe minor defects in some endeavor. But this quote from Ecclesiastes has a much wider scope than a few dead flies – it is the ointment itself that stinks, and the entire endeavor is thereby ruined. By analogy, there are several caveats that apply to many, if not all spatial analyses of cancer data. As "flies in the ointment", these caveats can substantially detract from a spatial analysis, and if not accounted or otherwise controlled for, can lead to weakened or erroneous conclusions. Several of these caveats have been identified in the papers in this collection; others have yet to be described. This paper brings them together in one location, where they are discussed under three broad headings. • Problems of inference; • Assumptions and limitations; and • Potential solutions and future directions. Problems of inference: what can we learn from spatial analysis? This section provides an overview of the scientific method as applied to spatial data, limitations inherent in the study of spatial systems, including those on inference, spatial methods and data, and finally, limitations imposed on spatial analyses of human health data by society and the context from which health data arise. Overview of the scientific method The Classic Paradigm of Karl Popper . Popper [ 1 ] posed an approach to gaining knowledge from bodies of data that has come to be known as the "Scientific Method". Although his approach has been criticized as not necessarily being applicable to how scientific knowledge advances in practice, with fortuitous circumstance and flashes of insight (as occurred in the discovery of penicillin) receiving no mention, Popper's philosophy is useful because it incorporates inductive and deductive reasoning, and uses falsifiable predictions based on clearly stated hypotheses. The useful lessons from Popper are first, that hypotheses and theories emerge from patterns and relationships in a set of observations; second, that the validity of the hypotheses is evaluated by distilling falsifiable predictions from them; third, that experiments designed to test these falsifiable predictions result in new data collected specifically to evaluate the predictions (these are designed experiments); and fourth, in order to avoid a tautology predictions cannot be tested on the data that gave rise to them. It is important to realize that useful predictions are falsifiable ones. Popper's approach can never prove a theory or hypothesis to be true. Rather, a body of evidence is collected from a series of experiments designed to test specific predictions, thereby increasing confidence that the hypothesis on which the predictions are based is true. Popper thus saw science as advancing much in the way used by Sir Arthur Conan Doyle's fictitious character Sherlock Holmes: If the alternative explanations are disproven, then the remaining explanation, no matter how unlikely, must be true. Recognizing this, Platt [ 2 ], proposed what he called "Strong Inference". Strong Inference begins with a set of hypotheses regarding observed phenomenon. The researcher then designs a series of critical experiments to systematically test each hypothesis. Platt recognized that the set of alternative hypotheses may change during the course of the experimental process, and Strong Inference is thus more closely aligned with the experimental process as it is used in practice. Limitations inherent in the study of spatial systems Spatial systems typically are large, and the spatial phenomena of interest in public health (e.g. cancer mortality rates, risk behaviors, demographic characteristics, and environmental exposures) are often difficult to observe directly and/or change slowly through time. This makes it difficult, if not impossible, to conduct designed experiments, and in any event there are substantial ethical considerations with experimentation on human populations. The spatial health researcher must often work with encountered data that have been collected for some purpose other than her specific study. In some instances the data are sampled in a systematic way from a spatially distributed population. But in each of these instances spatial analysis plays a critical role in identifying spatial and temporal relationships in population-level data, giving rise to hypotheses that can then be evaluated on additional data to be collected from the same system or on data from analogous spatial systems (spatial controls). Under both Popper's and Platt's inference frameworks, study designs that attempt to confirm rather than reject hypotheses are not particularly useful. Repeating spatial studies to search for confirmation is less useful than undertaking analyses that are designed specifically to reject scientifically meaningful alternative hypotheses. But because it is so difficult to manipulate spatial systems, it can be difficult to design and undertake the critical analytical experiments that test falsifiable predictions. Limitations on inference The spatial analyst's tool box includes techniques for quantifying spatial patterns, modeling risk surfaces, and assessing relationships between cancer outcomes and potential exposures. These techniques allow researchers to determine whether observed spatial patterns are statistically significant, to identify the locations of clusters, hotspots and cool spots, to construct maps showing excesses and deficits relative to a risk model, and to quantify association between two spatial variables (such as cancer incidence and putative environmental exposures). Although these techniques can be quantitatively powerful, the inferences that can be drawn from them have attendant limitations. We now consider three limitations on the inferences that can be reached from analyses (1) of spatial patterns, (2) of spatial associations, and (3) by using randomization (Monte Carlo)-based techniques. Pattern does not demonstrate causation . As noted by Waller and Jacquez [ 3 ] tests for spatial pattern employ alternative hypotheses of two types; the omnibus "not the null hypothesis" or more specific alternatives. Tests with specific alternatives include focused tests [ 4 ] that are sensitive to monotonically decreasing risk as distance from a putative exposure source (the focus) increases. Acceptance of either of these types (the omnibus or a more specific alternative) only demonstrates that some spatial pattern exists, and does not implicate a cause. When the alternative hypothesis is highly specific, as for a focused test, it may correspond to a potential causal mechanism. For example, Waller et al [ 5 ] employed focused tests to explore a possible association between leukemia and lymphoma in New York State and exposure to TCE injected into ground water at industrial sites. While the score test employed was highly significant, demonstrating increased risk near several ground water injection wells, this finding did not demonstrate a causal relationship, or even that persons close to the injection wells had increased exposure to TCE. The existence of a spatial pattern alone cannot demonstrate nor prove a causal mechanism. Association is not causation . The spatial analyst has an increasingly diverse suite of tools for documenting and quantifying associations between the spatial patterns of two or more variables. These techniques include cross-correlograms and related measures [ 6 , 7 ]., the bivariate LISA [ 8 , 9 ]., boundary overlap [ 10 ], polygon area overlap [ 11 ], as well as other approaches. Not intended to replace traditional statistical methods for association (such as the Pearson product-moment correlation), these methods assess the extent to which the spatial patterns in two variables (such as lung cancer incidence and ambient air toxic concentrations, see for example Jacquez and Greiling 2003) [ 12 ] coincide or "match up". But, as for traditional correlation techniques, a demonstration of spatial association does not demonstrate causality. Randomization limits inference to the data set . Many disease cluster techniques and approaches to spatial modeling employ randomization, either based on sampling algorithms from spatial models (e.g. the Bernoulli model for the locations of cases and controls; the heterogeneous Poisson model for area-based cluster tests, and so on) or on distributional assumptions of randomization (e.g. the randomization hypothesis for Moran's I). Traditional statistics based on distribution theory (e.g. student's test, ANOVA etc) are able to make inferences regarding the "Universe" from which the population sample was drawn. Inferences for methods based on randomization, however, are limited only to the data set to which they were applied. This is one of the critical distinctions between methods based on distribution theory and "distribution free" techniques based on re-sampling a data set to construct empirical distributions [ 13 ]. Limitations imposed by methods All methods have attendant limitations, and this is true as well for techniques in the spatial analyst's toolbox. We now consider limitations imposed by spatial methods including the amount of knowledge required to use them, the selection and specification of spatial weights, and the subjectivity of the methods themselves. Amount of knowledge Different analysis approaches require different amounts of knowledge. A distinction often is made between exploratory analysis, models of data, and models of process. When working with spatial data, a corresponding distinction can be made between Exploratory Spatial Data Analysis (ESDA), spatial data models, and spatial process models. Each of these (ESDA, models of data, and models of process) has different inferential/predictive abilities, and requires different amounts of data and knowledge of the spatial system itself. ESDA quantifies spatial pattern, models of data are used for interpolation and prediction, and models of process are used for prediction and the assessment of proposed perturbations to the spatial system. ESDA (including techniques such as autocorrelation analysis and disease clustering) aims to identify spatial patterns and to generate hypotheses that might explain those patterns. It requires relatively little knowledge of the system being studied. In fact, the objective of exploratory techniques is to explore and quantify relationships in order to increase the analyst's knowledge of the spatial system. Models of data (such as spatial regression, geostatistical models, risk surface models, and Bayesian techniques) require data of sufficient quality to estimate model parameters, and that the researcher possesses sufficient knowledge to be able to identify dependent and independent variables, and their relevant parameters. However the forms of these models do not convey any information regarding causal relationships. Models of process require a detailed understanding of the mechanics of the system being studied, and incorporate this understanding directly into the model itself. Spatial compartmental models that incorporate population and disease processes such as birth, death, migration and risk have been applied to model infectious diseases [ 14 , 15 ]. This kind of model has also been used to model the transport and fate of mutagenic compounds that are known carcinogens (e.g. [ 16 ]). But to date there are few if any process models that link population-level cancer outcomes to environmental exposures. Spatial weights Each of the 3 types of approaches outlined above require the use and specification of spatial relationships among the objects (e.g. individuals, places of residence, areas of spatial support) being studied. In ESDA these are referred to as spatial weights. In models of data these may be called kriging weights (in geostatistics), autoregressive parameters (in spatial regression), or spatial filters (in Bayesian smoothing). In models of process spatial relationships are quantified to correspond to the underlying mechanics of the system, for example in an infection model, by how likely pairs of nearby susceptible and infectious individuals are to contact one another. As one moves from ESDA to models of process, the methods used for quantifying spatial relationships become increasingly meaningful in terms of the spatial system being studied. For ESDA spatial weights model the spatial disease pattern (the alternative hypothesis). The selection and specification of spatial weights in ESDA is undertaken in the most "knowledge poor" circumstance, yet is critical since these weights quantify the alternative hypothesis of the pattern recognition statistic. For area-based data, commonly used spatial weights include first and higher order adjacencies, and functions of common border length. Some techniques evaluate nearest-neighbor and adjacency relationships on the centroids of areas, an approach that disposes of highly relevant geographic information (such as common borders) readily obtainable from polygon geometry. More advanced and realistic techniques are now being developed that account, not only for geographic relationships, but also for co-information such as population size [ 17 ]. But in general many of the spatial weights in common use are geographically crude (e.g. employ area centroids) and based entirely on Euclidean spatial relationships that ignore relevant co-information such as population size. Later in this paper we discuss the use of spatial weights to represent exposure mechanisms. Subjectivity Most researchers recognize that all analytical methods impose a model, of one type or another, on the data and are therefore subjective. For example, the product-moment correlation coefficient imposes a linear model and is thus sensitive to linear relationships in bivariate data. Similarly, all techniques for spatial pattern analysis and modeling are founded on assumptions and are sensitive to or descriptive of different aspects of spatial pattern. For example, reliance on a single cluster statistic can only reveal those disease patterns that are consistent with that test's alternative hypothesis (e.g. circular or elliptical clusters for spatial scan statistics). This has prompted some researchers to employ a battery of spatial pattern methods to better describe different aspects of the morphology of geographic patterns in cancer incidence [ 12 ]. While employing a variety of techniques doesn't remove subjectivity, it does illuminate different aspects of spatial patterns, thereby providing a richer and more accurate description of geographic variation. Limitations imposed by data The spatial data used in many geographic studies of cancer have inherent limitations attributable to granularity, spatial and temporal mismatch, under-reporting, misdiagnosis, the use of location as an exposure surrogate, human mobility, location and attribute uncertainty, static representation, as well as topological errors that result in erroneous spatial weights. Granularity has to do with the spatial resolution of the data. For human health applications, death certificates are often georeferenced to location of place of residence at time of diagnosis or death. Point-based methods then use these coordinates directly. Area-based methods require the point locations to be aggregated to provide raw or adjusted rates within areas, and these areas might be census units, metropolitan statistical areas, counties, states and so forth. Because of the need to protect patient privacy, publicly available data are often aggregated to a sufficient extent to prevent the disclosure or reconstruction of patient identity. So, for example, point maps displaying patient place-of-residence typically cannot be disclosed by researchers and public health agencies. But due to the Modifiable Areal Unit Problem (MAUP) how these data are aggregated can dramatically impact analysis results, and incompatible geographies (e.g. census vs. ZIP Code) make tests for association problematic [ 18 ]. The ability to detect and model spatial pattern depends on granularity. One cannot, for example, detect clusters of counties using health data that is aggregated at the state-level. It is worth noting, however, that methods of spatial unmixing for raster-based data have been developed that support the construction of higher resolution maps from lower resolution information [ 19 ]. Unmixing approaches for disaggregating census and spatially aggregated health data that will allow spatial analyses using a common spatial support across variables are now available [ 20 ]. Spatial and temporal mismatch Cancer data, information on covariates and on environmental exposures typically do not "match up" in space or in time. For example, Jacquez and Greiling [ 12 ] analyzed lung cancer data on Long Island, and contrasted spatial patterns (geographic boundaries) with data on airborne toxics from EPA's (Environmental Protection Agency) National Air Toxics Assessment (NATA) program. Mismatch occurred between the cancer and air toxics data both in space (lung cancer incidence was reported at ZIP+4 level; air toxics data for census block groups) and in time (lung cancer incidence was reported for 1994–97; the air toxics data was based on emissions reported during 1996). The problem of spatial mismatch was solved by using spatial tests for association (boundary overlap) that account for the differing geographies within the randomization procedure. Temporal mismatch was problematic because latency for lung cancer is on the order of 15–20 years, and air toxics information could not be reconstructed over that time span. Thus while they found a positive geographic association between the air toxics and lung cancer incidence, the substantial temporal mismatch means a more detailed exposure reconstruction is required before any conclusions can be reached. Location and attribute uncertainty Uncertainty in spatial health data occurs in two data components: the locations (e.g. coordinates of place of residence) and attributes (the values recorded at the locations). Also referred to as positional uncertainty, the impacts of location uncertainty on spatial pattern analysis and modeling have been well documented in the geographical and natural resource sciences [ 21 , 22 ]. In the health sciences, Jacquez and Waller [ 23 ] evaluated the impacts of location uncertainty on three tests for space-time interaction, and found the Mantel, Knox and k-nn tests to differ in their sensitivity to location uncertainty, with the k-nn test less likely to report false negatives as uncertainty increased. Location uncertainty can be modeled using several approaches, including lists of alternative locations for point-based data, and polygon, population, and risk-based models for area-based data [ 24 ]. Nonetheless, many spatial analyses of cancer assume locations are known with 100% certainty and that the spatial weights calculated from those locations are precise and without error in either representation (e.g. is it reasonable to use place of residence to represent human activity patterns?) or measurement. Location as an exposure surrogate Location uncertainty has different sources, one of which is human mobility. Attempts at describing such mobility that transcend the use of place-of-residence to represent location include daily activity spaces[ 25 , 26 ], and constructs such as time geography and pathogenic paths [ 27 - 29 ]. But while almost all researchers acknowledge that many causative exposures occur outside of the home, most spatial analyses still rely on place-of-residence to georeference locations of health events. When might place of residence reasonably be used to georeference health data? For infectious diseases exposure events require contact between infected and susceptible individuals of sufficient duration to allow the pathogen to pass from one to the other. The exposure route varies from one type of pathogen to another, and a given pathogen may have several exposure mechanisms. These includes fecal-oral (e.g. the Norberg virus that recently has been the bane of cruise ships), intimate sexual contact (e.g. STD's and HIV), air-borne droplets (e.g. tuberculosis), and contaminated foods (e.g. hepatitis), among other mechanisms. Zoonotic and vector-borne diseases involve an animal host or reservoir, and exposure mechanisms may include animal-human as well as human to human routes. Spatial weights for such exposure routes may incorporate measures of geographic proximity, but also should be constructed to reflect the probability of exposure between pairs of individuals (for individual-based models) and for groups (for population-based models). Although exposure routes for infectious diseases are numerous and often quite complex, exposure reconstruction for cancers with long latency and for which mechanisms of carcinogenesis are only partially known is even more problematic. Use of place-of-residence in spatial analyses of cancer, and calculating purely spatial weights from those locations, seems appropriate only when individuals have resided at that location for as long or longer than the latency period, and when potential causative exposures occur either in the household or in the surrounding neighborhood . For what cancers might causative exposures occur in the home? Lung cancers attributable to household radon are a good example, as well as cancers caused by combustion by-products from cooking and second-hand smoke. Cancers of childhood reasonably may use place-of-residence as an exposure surrogate since the latency period is short and children tend to stay near the home. For other cancers and at larger scales of aggregation, such as census and ZIP Code geography, human mobility, especially in commuter communities, poses a substantial challenge to spatial analysis of cancer, and the finding of a geographic cluster can thus be difficult to interpret when place of residence is used to represent locations of individuals. Recently, Meliker et al [ 30 ] used the constructs of time geography within a space-time information system to undertake the space-time modeling of individual-level exposure to arsenic. They were able to reconstruct individual arsenic exposure based on specific assumptions regarding occupational exposures and the ingestion of arsenic in drinking water. The time-geographic approach appears to provide a robust quantitative foundation for exposure reconstruction that is not possible when a single location is used to represent an individual's location in space-time. Under reporting and misdiagnosis : Uncertainty in the attributes (e.g. case identifiers and the numerators in incidence and mortality rates) arises from under reporting and misdiagnosis. Under reporting is especially an issue when working with data that encompasses health districts with different recording and reporting practices. Because states maintain their own cancer registries, differences in reporting practices can pose a special problem for data sets that cross state boundaries. For most cancers, diagnostic accuracy decreases as one works with retrospective data when the physician's diagnostic arsenal was not as robust. In addition, classifications of disease change through time, as when the International Classification of Disease (ICD) code is updated. When either differences in reporting and diagnosis are present, once cannot preclude the possibility that observed spatial variation in cancer rates is attributable to these causes. Static view : GIS typically represent the world as "snapshots" in time and do not effectively represent temporal change [ 31 ]. The importance of time in health geography is well recognized, since almost all geographic disease patterns are the result of space-time processes [ 32 ]. There thus are substantial limitations that arise from using conventional GIS technology, especially for the mapping, representation, and analysis of health, socioeconomic, and environmental information for populations that are dispersed or mobile and in which space-time relationships are dynamic. Advances in space-time information system technology address this deficiency using space-time coordinates and object representations that include motion and morphing, as well as attribute change models [ 30 ]. Polygons, Topology and computational geometry : The spatial analysis of area-based data requires the calculation of statistics such as polygon contiguity, length of common boundaries, areas and centroids. Calculation of these statistics employs methods of computational geometry that assume the polygons are correctly represented in the Euclidean plane. These assumptions usually are that polygons are closed (e.g. Jordan curves), and are not folded or joined together at single points to form "bow ties". When these assumptions are not met, techniques such as polygon triangulation will either fail or yield incorrect results, and resulting statistics, including placement of area centroids and spatial weights, will be wrong. Despite the importance of this problem, most spatial analysis software does not check shapefiles (which lack topological information) to determine whether the polygons are topologically well-conditioned. While this may seem an arcane problem, we have discovered in practice that a substantial proportion of the shapefiles shared among researchers for use in spatial analysis are flawed to a sufficient extent so that the resulting spatial weights are incorrect. One example is the primary care service area file that has 60 of 6000 polygons self intersecting, a 1% error rate. Limitations imposed by society and context Limitations on inference in cluster investigations . Many disease cluster investigations are initiated by reports from concerned citizens, and the attendant increase in the probability of false positives due to such preselection bias is well known [ 33 , 44 ]. Others have pointed out that the investigation of preselected clusters is not a scientifically valid endeavor [ 34 ], because of the tautology of testing hypotheses on the data from which they emerged, as well as other reasons. Several authors [ 35 ] have noted limitations of the hypothesis-testing framework relative to a more flexible spatial modeling approach. Nonetheless, it is the mission of public health departments to respond to public health concerns [ 36 ], and cluster investigations are likely to continue to be undertaken within a hypothesis testing framework such as that advocated by the Centers for Disease Control [ 37 ]. Limitations arising from lack of communication with community stakeholders Within public health departments spatial analyses of cancer data are best undertaken by teams comprised of a community stakeholder (e.g. community end-user of the study results), a political decision maker whose constituency is the subject of analysis, a public health practitioner capable of putting in place an intervention should the results be positive, a spatial analyst with a detailed understanding of the spatial analytic methods, and a GIS specialist to manage data and undertake mapping tasks. Such a team effort is most likely to translate analytical results into community action [ 43 ]. Information democracy vs. protection of privacy Efforts such as the National Spatial Data Infrastructure project are leading to the advent of data portals designed specifically to facilitate sharing and dissemination of spatial information. The DataWeb is a network of online data libraries created in a collaboration between the CDC and the US Census Bureau. The libraries consist of both microdata and aggregate data, and include census, economic, health, income and unemployment, population, labor, cancer, crime, transportation, family dynamics, vital statistics, and other georeferenced data. Information in DataWeb is accessed through DataFerret, an application that prepares data sets for the user to download. It allows users to select a databasket of variables and then recode those variables as needed. Users develop and customize data tables and download them to their desktop (download formats include ASCII, SAS, SPSS, and Excel/Access). Launched on June 30th, 2003, the Geospatial One Stop program is a web-based portal for one-stop access to maps, data and other geospatial services that simplifies access to geospatial data collected by government agencies and other organizations. Geodata.gov is accelerating development and implementation of the National Spatial Data Infrastructure (NSDI) and includes state, local and tribal governments along with the private sector and academia as data providers. Geodata.gov offers access to thousands of data bases in 17 categories. The promise of these and like efforts is an information democracy in which all citizens have ready access to information describing health, the environment, services, resources, the economy and other data, both for their immediate neighborhood as well as larger areas. While freedom of information is arguably one of the pillars of a democratic society, the need to protect individual privacy is a substantial countervailing consideration. There are other important ethical considerations with the sharing of spatial data of very high resolution. For example, satellite imagery is now publicly available at 1 m and sub 1 meter spatial resolution, and hyperspectral imagery at comparable resolution will soon be available. From such imagery it will be possible to identify and classify microhabitat for disease vectors [ 38 ], and even to map the transport and fate of heavy metals in rivers and streams [ 39 ]. But such information also will allow even small pockets of microhabitat of economically valuable species to be targeted for exploitation (for example, in the U.S. there is a black market in native endangered frogs, turtles, snakes and lizards). How will the need for spatial data sharing consistent with an information democracy be balanced with individual rights to privacy and related ethical considerations? Assumptions and limitations of spatial analysis of cancer data Every study is based on assumptions, and ideally these are made explicit when the results are reported. This section describes several assumptions and considerations typical of spatial analyses of cancer, including ability to infer causality, the ecologic fallacy, and the role of higher-order interactions. This section concludes with a discussion of the lack of utility of the word "cluster" as a spatial pattern descriptor. Power to disprove but not confirm causality Earlier we pointed out than an important limitation of spatial analyses of cancer data is that demonstration of significant geographic patterns and associations is never sufficient to demonstrate causality. This is particularly true of cancers because of long latencies, the substantial difficulties posed by exposure reconstruction, and because of our lack of a full our understanding of the environmental bases of carcinogenesis. However, the exploration and modeling of spatial cancer patterns can disprove predictions based on causal hypotheses that are expressed in spatial terms. For example, hypothesized exposure mechanisms that involve proximity to point sources, or for which attributed risks vary geographically, can be evaluated systematically using spatial analytic approaches. Ecologic fallacy, and arbitrary spatial partitions Studies of geographic clusters and cancer data must include consideration of the potentially misleading aspects of ecologic studies. Even ZIP Codes and census tracts can be considered coarse spatial units for aggregating cancer cases and for estimating exposures, and exposure and health data often are not available at the same resolution. Exposure data often are reported at spatial levels, such as census tracts, that partition the geography in a manner inappropriate for the exposure process. Other spatial divisions may be better descriptors of environmental exposure, including, for example, watersheds, aquifers, local public water systems for water-borne substances, or "windsheds" for airborne substances. But because of privacy concerns for the patients and the limitations on existing environmental data, the data used often are simply the data that are available. Every data collection protocol has a design. Is it appropriate to use data for purposes other than for which they were collected? ZIP Code, census tract or place of residence at diagnosis is an inadequate descriptor of an individual's location during the development of cancer. For example, using the ZIP Code of residence assumes the patient lived within that ZIP Code area during the period of time required to develop cancer following exposure to an environmental compound that influenced cancer risk. Hence the degree of exposure to the potential risk factors over a multi-year period has been estimated for each study subject based on their place of residence, aggregated at the census tract level. This assumption is clearly tenuous given the mobility of human populations and the arbitrariness of the spatial partition for the environmental data [ 45 ]. In the 1980's many epidemiologists considered ecologic studies likely to lead to erroneous conclusions, and that the most accurate findings arise from individual-level data. Since the late 1990's, however, the potential of adding "contextual variables" to multi-level analyses has provided a sound methodological mechanism for combining individual-level data with higher geographical contextual data. Nonetheless, issues regarding the definition of spatial partitions, patient privacy, and the appropriate use of data still pertain. Higher order interactions Especially for complex relationships (such as those between environment, genetics and cancer), apparent bivariate associations may be driven by multivariate interactions that are not directly quantified by the two variables under scrutiny. For example, elevated air pollution may be associated with lower housing prices (because of proximity to industrial sites), which in turn attracts poorer households with higher smoking rates. In this instance, an observed bivariate correlation between air pollution and cancer would actually overestimate the degree of association between these two variables. But because of their complexity, higher order multivariate interactions are difficult to quantify in spatial cancer studies. The term "cluster" has little meaning The term "cluster" by and of itself is so generic as to be almost meaningless for describing spatial variation in cancers. What is a cluster? Is it an excess of cancer, and, if so, how much extra is considered an excess? Do we use likelihood statistics to find an excess, or should we use some other statistical framework? Are we looking globally to identify clusters anywhere in the study area, or do we define patterns locally, or relative to a putative source? These kinds of questions suggest that the declaration of a "cluster" is meaningless without a precise description of the statistical test being employed and the patterns to which the test it is sensitive. Because different clustering techniques are sensitive to different aspects of cluster morphology, analytic approaches that employ several pattern recognition methods can be more informative, especially in the ESDA phase of an analysis, with the caveat that the multiple tests will need to be accounted for should accurate estimates of P-values be required. Analyses that rely on just one kind of cluster test are incomplete in the sense that they will have power to detect only one type of cluster. Cancer morbidity and mortality evinces rich geographic variation, and it thus can make sense to employ a variety of techniques to more fully describe relevant aspects of spatial pattern. The future This last section discusses salient trends and methodological challenges in the changing landscape of the spatial analysis of cancer. It summarizes expected improvements in cancer data, exposure measures, and genetic information, and concludes with some anticipated methodological and technological challenges for the next decade. Improved availability of cancer data Recent trends in cancer registries are resulting in improved reporting and linking of spatially referenced data, although there is substantial variation in quality from state to state. There is a trend towards increased availability of aggregated cancer statistics over the World Wide Web. Not withstanding the inherent limitations of ZIP Code data, a good exemplar of improved availability is New York State, which is publishing online atlases of cancer incidence at ZIP Code level geography. A second example is the National Cancer Mortality Atlas published by the National Cancer Institute. New York State also makes available findings from spatial analyses of the cancer incidence data using the spatial scan statistic [ 40 ], and the National Cancer Atlas provides a narrative interpretation of the cancer mortality patterns and their potential causes. In coming months and years the quality of and speed with which cancer incidence and mortality data are made available is expected to improve, with some of these benefits attributable to improved Public Health Surveillance infrastructure currently being funded by bioterrorism and first responder initiatives. Improved exposure and population data Efforts cited earlier in this paper such as the CDC's dataweb and geospatial onestop are making georeferenced information on socioeconomic, census, environmental, remote sensing and other data readily available for downloading over the web. In remote sensing, the trend is towards higher spatial, spectral and temporal resolutions which together hold great promise for improving environmental risk assessment, habitat classification, and change detection [ 41 ]. Modeling efforts by organizations such as the Environmental Protection Agency are integrating exposure models with spatial models of air-borne and other toxins, incorporating both point and non-point source information. Coupled with improved data on cancer health outcomes, enhanced exposure estimates, along with detailed descriptions of the affected populations, hold the promise of more detailed, accurate and predictive spatial modeling of cancer outcomes. However, this promise can only be realized when the data obtained from disparate sources is temporally matched, aggregated in an appropriate fashion, and collected at compatible geographic granularities. Improved genetic data The recent revolution in gene sequencing, bioinformatics and proteomics is making possible a detailed understanding of genetic predispositions as well as the cascade of genetic changes that cause normal cells to turn into cancer cells. Research currently underway at the NCI is seeking to elucidate gene-environment interactions and how these interactions can lead to cancer, but in general spatial analysis has contributed little to the study of gene-environment interactions. In fact, such studies would require population-level information on genetic profiles and biomarkers sufficient to calculate human genetic distances, and this kind of data are not yet available. Some research has conducted on European populations to explore relationships between genetic distances calculated from blood polymorphisms and differences in cancer mortality [ 42 ]. But to fully exploit the potential of spatial analysis for the study of gene-environment interactions, more detailed data on the genetic profiles of human populations in the United States is needed. Improved technology As noted earlier, the static view of GIS makes it difficult to represent human mobility and temporal change in cancer, environmental and socioeconomic data. GIS typically are based on spatial data models that apply to static spatial systems such as those found in geology, forestry, and physical geography. However, this purely spatial data model inadequately characterizes the "what, where, when" needed to effectively analyze cancer data and health-environment relationships. GIS built on spatial, rather than space-time data structures, cannot deal readily with space-time georeferencing nor space-time queries [ 31 ], and instead are best suited for analyzing static systems. Loytonen [ 32 ] and others have called for a "higher-dimensional GIS" (a Space-Time Information System or STIS) to better represent space-time dynamics. STIS provide a rich framework for the generation and evaluation of epidemiologic hypotheses founded on the exploration of space-time disease patterns in relation to their putative causes and covariates [ 9 ]. The advent of mobile computing and location-based services provide substantial opportunities for increasing our understanding of human activity patterns, and an important challenge for the spatial analysis of cancer will be to more fully exploit the temporal dimension as this information becomes more readily available. The methodological challenge In the near future we will need techniques and methods that take full advantage of the burgeoning data stream while maintaining the values and ethos of an open, democratic society. Information detailing place of death, genetic makeup, socioeconomic status, product use, and lifestyle indicators will be available at unprecedented spatial and temporal resolution. Using these data, substantial benefits to society are expected to accrue from the rapid identification of cancers and other health risks. Syndromic and health surveillance systems are now being deployed that could make it possible to rapidly identify local increases in cancer risk, and even relate them to spatial patterns and changes in environmental data thought linked to causative exposures. But the benefits of analyzing such high spatial and temporal resolution data must be balanced against the need to maintain individual privacy, while at the same time providing equitable information access to all strata of society. Certain aspects of this problem can be met by the development of appropriate analysis techniques. Coming up with these techniques and applying them in a responsible fashion is a substantial challenge that will require the cooperation of researchers, funding agency program managers, and legislators. Note The author is President of a commercial company (BioMedware) that develops software for the exploratory spatial and temporal analysis of health and environmental data.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526213.xml
514538	A Skeletal Muscle Protein That Regulates Endurance	null	It's a common runner's complaint. Just when you've built up enough strength and endurance to make running fun, those niggling aches and pains won't go away. Every time your foot hits the ground, a force equal to about twice your weight shoots through your body, eventually chipping away at bones, cartilage, muscles, tendons, ligaments, and joints. For those lucky souls who can take the pounding, the main limitation to running performance stems from muscle fatigue. Now, Randall Johnson and colleagues report that a protein found in skeletal muscle profoundly influences muscle endurance. Running, like any sustained skeletal muscle activity, consumes large quantities of adenosine triphosphate (ATP), a molecule that fuels many essential cell processes. A number of metabolic pathways supply muscle tissue with the ATP needed to power muscle contraction and sustain ongoing exercise. Which pathway predominates depends on factors like speed, duration, and type of activity, as well as on the availability of oxygen, which fluctuates during activity. (For more on muscle cell type and endurance, see the synopsis titled “Gene Targeting Turns Mice Into Long-Distance Runners.”) Say you start a half-hour run with a sprint. Within a few seconds, your body uses up the oxygen in its muscles and has to switch to anaerobic pathways, which metabolize sugars and fats to regenerate ATP. Aerobic pathways operate inside mitochondria, the cell's major power generators. Anaerobic pathways like glycolysis function in the cytoplasm. Hypoxia (the physiological state that occurs when oxygen levels drop below normal levels) governs how ATP is recycled and which energy-producing substrates (for example, glucose or fatty acids) are used; it also generates metabolic by-products, like lactic acid, during strenuous exercise. (Runners know the “lactic acid burn” associated with reduced blood pH.) Glycolysis—the primary source of anaerobic energy in animals—uses glucose, stored as glycogen in muscle cells, to produce ATP. When blood oxygen levels drop, the gene transcription factor hypoxia-inducible factor 1α (HIF-1α) triggers the glycolytic pathway. To understand how HIF-1α regulates skeletal muscle function, Johnson's team generated mice that couldn't express HIF-1α in skeletal muscle. Normal and mutant mice went through exercise routines that included swimming and running on treadmills. After exercise, the normal mice had increased levels of gene transcripts and enzymes involved in glucose transport and metabolism. In the mutant mice, expression of these glycolysis-associated genes and enzymes was significantly lower. The mutants' ATP levels, however, were normal. Without the molecular machinery to engage anaerobic metabolism, their muscles switched to aerobic pathways. The presence of enzymes that respond to reduced ATP levels by increasing mitochondrial ATP production, combined with low levels of lactic acid, confirmed the switch. During endurance tests, the mutants could swim and run uphill (on treadmills tilted upward) longer than the normal mice, but when it came to running downhill, the normal mice prevailed. Downhill running, it turns out, favors glycolytic metabolism; uphill running and swimming favor oxidative pathways, which the mutants were predisposed toward. But their inappropriate use of this pathway came at a cost. By the final day of a four-day exercise routine, the mutants' run time was significantly shorter and their muscles were clearly damaged. The mutants displayed a number of the trademark muscle defects seen in human patients with glycolytic processing disorders. These patients often have reduced lactate levels and elevated levels of mitochondrial enzymes, which apparently can cause a second wind and enhance endurance. This inappropriate use of oxidative pathways—which compensates for the inability to trigger glycolysis—may account for the exercise-induced muscle damage associated with these diseases. These results demonstrate that losing the molecular wherewithal to engage hypoxia response pathways has serious consequences for muscle function during exercise; it can give increased endurance, but at a high price. The mouse model presented here will help researchers explore how muscles normally function in response to low oxygen and how metabolic deficiencies cause debilitating muscle disease.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514538.xml
548284	Epimorphin expression in interstitial pneumonia	Epimorphin modulates epithelial morphogenesis in embryonic mouse organs. We previously suggested that epimorphin contributes to repair of bleomycin-induced pulmonary fibrosis in mice via epithelium-mesenchyme interactions. To clarify the role of epimorphin in human lungs, we evaluated epimorphin expression and localization in normal lungs, lungs with nonspecific interstitial pneumonia (NSIP), and lungs with usual interstitial pneumonia (UIP); we also studied the effect of recombinant epimorphin on cultured human alveolar epithelial cells in vitro . Northern and Western blotting analyses revealed that epimorphin expression in NSIP samples were significantly higher than those in control lungs and lungs with UIP. Immunohistochemistry showed strong epimorphin expression in mesenchymal cells of early fibrotic lesions and localization of epimorphin protein on mesenchymal cells and extracellular matrix of early fibrotic lesions in the nonspecific interstitial pneumonia group. Double-labeled fluorescent images revealed expression of matrix metalloproteinase 2 in re-epithelialized cells overlying epimorphin-positive early fibrotic lesions. Immunohistochemistry and metalloproteinase activity assay demonstrated augmented expression of metalloproteinase induced by recombinant epimorphin in human alveolar epithelial cells. These findings suggest that epimorphin contributes to repair of pulmonary fibrosis in nonspecific interstitial pneumonia, perhaps partly by inducing expression of matrix metalloproteinase 2, which is an important proteolytic factor in lung remodeling.	Introduction Fetal development and morphogenesis of various tissues and organs such as hair follicles, teeth, salivary glands, mammary glands, kidneys, liver, pancreas, and lungs depend on epithelium-mesenchyme interactions [ 1 , 2 ]. Such interactions are believed to be important for the tissue regeneration necessary for wound healing in adults [ 3 ]. Pulmonary fibrosis is thought to be a result of wound healing or regeneration after lung injury [ 4 - 11 ]. Lung injury causes the epithelial basement membrane to be destroyed, which enables migration of interstitial cells into intra-alveolar spaces where they produce and deposit extracellular matrix (ECM). Regenerated epithelial cells then cover the surface of the intra-alveolar fibrotic area. If the injury is mild and focal and re-epithelialization has occurred, these epithelial cells appear widespread over early intraluminal fibrotic lesions and form intra-alveolar buds, which later become small collagen globules and do not contribute to alveolar structural remodeling [ 5 - 7 , 9 - 13 ]. For example, intra-alveolar buds, in a so-called organizing pneumonia pattern, are frequently observed in nonspecific interstitial pneumonia (NSIP); NSIP usually has a better prognosis than does usual interstitial pneumonia (UIP), which has fibroblastic foci without good re-epithelialization [ 8 - 10 , 13 , 14 ] as early fibrotic lesions. The re-epithelialization around early fibrotic lesions is similar to the process of fetal epithelial development [ 4 - 7 ], which suggests that epithelium-mesenchyme interactions may play a key role in repair of pulmonary fibrosis. Epimorphin is a mesenchymal cell surface-associated protein that modulates epithelial morphogenesis in embryonic mouse organs including lungs and skin [ 15 ]. Epimorphin expression was found in fetal lungs and skin rudimentary cells, at the mesenchyme-epithelium interface. Epimorphin also directs epithelial morphogenetic processes in other gastrointestinal organs and mammary glands [ 15 - 21 ]. For example, primary cultured rat hepatocytes (an epithelial cell) were used to show that epimorphin induces formation of hepatocyte spheroids with a bile canaliculi-like structure, which maintained albumin production even without growth factors [ 16 ]. Epimorphin mediated mammary luminal morphogenesis by controlling expression of CCAAT/enhancer binding protein Î² [ 22 ], which is essential for proper mammary morphogenesis and for determination of the fate of mammary epithelial cells [ 23 ]. In cultured mammary epithelial cells, epimorphin augmented expression of matrix metalloproteinase 2 (MMP-2), an important proteinase in matrix degradation, and both epimorphin and MMP-2 were required for mammary gland morphogenesis [ 24 ]. During fetal rabbit lung development, MMP-2 and MT1-MMP (an activator of MMP-2) were detected in epithelial cells, and expression of active MMP-2 and MT1-MMP increased dramatically; MMP-2 and MT1-MMP were especially predominant during late development, in which there was an extremely wide alveolar surface, which indicated an important role for MMP-2 in alveoli formation [ 25 ]. MMP-2 was also up-regulated and activated in regenerated alveolar epithelial cells, which may lead to elongation and migration of these cells for repair of pulmonary fibrosis [ 26 , 27 ]. The epimorphin gene is highly conserved among mouse, rat, and human [ 15 , 28 ]: the 289 amino acid sequence of rat epimorphin/syntaxin 2 exhibits 86% homology to human epimorphin [ 29 ]. However, the distribution and function of epimorphin in human lungs, including during fibrosis, are unknown. To clarify the role of epimorphin in human lungs, especially in fibrosis, we evaluated epimorphin expression and localization in normal control lungs and in lungs affected by NSIP or UIP, especially in early intra-alveolar fibrotic lesions. We also used cultured human alveolar epithelial cells to assess the effect of recombinant epimorphin on MMP-2 expression. Materials and Methods Patients All histologic slides from open or thoracoscopic lung biopsies in the files of the Department of Pathology, Kumamoto University Hospital, from 2000 to 2003, were evaluated. From among these samples, 17 patients were selected, with 8 fulfilling the histologic and clinical criteria for NSIP and 9 showing UIP. To confirm the histologic diagnosis, two pulmonary pathologists reviewed the slides; they were informed only of the age and sex of each patient and the presence of bilateral pulmonary disease determined by chest posteroanterior radiography and high-resolution computed tomography. All patients had had no steroid therapy before the biopsy. Normal control lung tissues were obtained from the normal areas of lungs that had been surgically removed from eight patients because of cancer. Table 1 shows the characteristics of the nine patients with UIP, eight patients with NSIP, and eight normal control subjects. In addition to the histologic diagnosis, we confirmed that the clinical data, pulmonary function test results, bronchoalveolar lavage findings, chest radiographic findings, and follow-up information obtained from the patients were consistent with the diagnoses. Diagnostic criteria of the American Thoracic Society/European Respiratory Society consensus classification system were applied [ 30 ]. We also verified that none of the patients with UIP had a connective tissue disease. In the group of patients with NSIP, two with SjÃ¶gren's syndrome and one with rheumatoid arthritis were included. In all other cases, no etiologic agent was found. These tissue samples were used for microscopic immunohistochemistry, Western blotting, and Northern blotting assays. The procedures used in this study were in accordance with those recommended by the regional ethical committee on human experimentation. Northern Blotting Studies Human epimorphin DNA fragments were isolated by reverse transcriptase-polymerase chain reaction. Strand cDNA was synthesized with random primers from human lung total RNA. Polymerase chain reaction assays were carried out at 95Â°C for 1 minute, 64Â°C for 1 minute, and 72Â°C for 1 minute for 35 cycles. The following primer pairs were used: human epimorphin forward 5'-GGA ACC GGA CTT CAG TGG ATC-3' and reverse 5'-CAGC CAA TGA TTA GAG CCA GGA-3'. Polymerase chain reaction products were subcloned into the Nco I and Spe I sites of the pGEM-T Vector (Promega, Madison, WI), and authenticity was confirmed by sequencing. Total cellular RNA was isolated from lung tissues from each case by using the acid guanidinium-isothiocyanate-phenol-chloroform method. The RNA samples (10 Î¼g/lane) were fractionated by electrophoresis on 1% agarose-formaldehyde gels under denaturing conditions and were transferred to Nytran by capillary action. The blots were then probed with the 339-bp Nco I/ Spe I fragment of the human epimorphin cDNA labeled with [ 32 P]dCTP (3000 Ci/mmol) by means of the Nick Translation System kit (GIBCO/BRL, Grand Island, NY). After hybridization, blots were washed and were processed by autoradiography. Washed blots were analyzed by using a Fujix BAS2000 Bio-Imaging analyzer system (BASTM, Fuji Photo Film Co., Ltd., Tokyo, Japan) and were visualized on Kodak X-OMAT AR film (Eastman Kodak, Rochester, NY). Signal intensity was quantified in digital images via BASTM analysis (FUJIX BAStation, Fuji Photo Film Co., Ltd.). To control for differences in gel loading, for each sample the RNA hybridized with the epimorphin probe was normalized to the expression of Î²-actin mRNA in the same sample. Western Blotting Studies Although the monoclonal antibody to mouse epimorphin (MC-1) has been reported to cross-react with human epimorphin [ 31 , 32 ], we performed Western blotting to confirm whether the anti-epimorphin antibody (MC-1, a gift from Dr. Hirai, Osaka R&D Laboratory (Yokohama-lab), Sumitomo Electric Industries, Yokohama, Japan) cross-reacted with the human epimorphin in our lung samples and to make comparisons of epimorphin peptide expression between normal and fibrotic groups. For immunoblotting, lung tissues from each case were dissolved in sample buffer containing 2% sodium dodecyl sulfate in 8 M urea and were kept at 4Â°C overnight; the same protein concentration (30 Î¼g) in samples from each lung extract was ensured by using Protein Assay (Bio-Rad Laboratories, Hercules, CA). Lung tissues from normal adult mice were also dissolved in sample buffer as above and served as positive controls. Those samples were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis according to the method of Laemmli (1970), and proteins in the gels were transferred onto nitrocellulose filters and were incubated sequentially with 5% skim milk in 0.5% Tween 20 overnight. Blots were then incubated at 4Â°C overnight with 10 Î¼g/ml rat anti-mouse epimorphin primary monoclonal antibody MC-1 used at a dilution of 1:1000 in 1% bovine serum albumin. Samples were then stained by incubation with horseradish peroxidase-conjugated anti-rat goat IgG F(ab') 2 antibody (Biosource International Inc., Camarillo, CA) used at a dilution of 1:1000 in Tris-buffered saline with 0.05% Tween 20 for 2 hours at room temperature. The bound antibody was detected by using the enhanced chemiluminescence method (Amersham Pharmacia Biotech UK Limited, Little Chalfont, Buckinghamshire, England) according to the manufacturer's protocol. Light Microscopic Immunohistochemistry A portion of each lung specimen was fixed immediately in a solution of 4% paraformaldehyde in 0.1 M phosphate buffer (pH 7.4), after which samples were sequentially washed for 4 hours in 10% sucrose in 0.01 M phosphate-buffered saline (pH 7.4, 4Â°C), 4 hours in 20% sucrose in phosphate-buffered saline, and overnight in 30% sucrose in phosphate-buffered saline. They were then snap-frozen in OCT embedding medium and stored at -80Â°C. Frozen tissues were cut into 4-Î¼m sections, which were incubated for 30 minutes with a biotin blocking system (Dako Corporation, Carpinteria, CA) and for 30 minutes with 0.3% hydrogen peroxide in methanol to eliminate endogenous peroxidase activity. After treatment with normal goat serum, tissues were incubated overnight at 4Â°C with 10 Î¼g/ml rat anti-mouse monoclonal epimorphin antibody and were then incubated for 1.5 hours at 37Â°C with 1 Î¼g/ml biotinylated goat anti-rat IgG (ZYMED, San Francisco, CA) and streptavidin-biotin-horseradish peroxidase complex (Dakopatts, Glostrup, Denmark). Bound antibody was visualized after incubation for 10 minutes in a Coplin jar with 100 ml of Tris-HCl buffer (pH 7.6) containing 20 mg of diaminobenzidine and 17 ml of 30% H 2 O 2 . Counterstaining was with Mayer's hematoxylin. Lung tissue of normal adult mice was stained as a positive control. Nonspecific labeling of primary antibody was evaluated with normal rat serum. Each tissue sample was also stained for keratin (rabbit anti-bovine antibody raised against the 58-, 56-, and 52-kd subunits of muzzle epidermal keratin; Dakopatts, Santa Barbara, CA), Î±-smooth muscle actin (mouse anti-human Î±-smooth muscle actin monoclonal antibody; Dakopatts, Santa Barbara, CA), and MMP-2 (mouse anti-human MMP-2 monoclonal antibody; clone 42-5D11, IgG1 isotype, purified antibody; Daiichi Fine Chemical Co., Ltd., Takaoka, Japan). Serial sections were also stained with hematoxylin-eosin (H&E) and Alcian blue-periodic acid-Schiff (AB-PAS). Confocal Microscopy To localize epimorphin as precisely as possible, epithelial and stromal cells were double labeled by means of immunofluorescent probes, and the distribution of epimorphin was compared with that of keratin and vimentin (mouse monoclonal anti-vimentin [V9] antibody; Dakopatts, Glostrup, Denmark). Briefly, after sections were exposed to primary antibodies, they were exposed to secondary antibodies: for the first analysis: fluorescein isothiocyanate-conjugated goat anti-rat IgG (American Qualex, San Clemente, CA) or Texas Red-conjugated goat anti-rabbit IgG (Molecular Probes, Inc., Eugene, OR); for the second analysis: fluorescein isothiocyanate-conjugated goat anti-rat IgG (American Qualex) or Texas Red-conjugated goat anti-mouse IgG (Molecular Probes). The nuclei were counterstained with 4,6-diamidino-2-phenylindole dihydrochloride (Vector Laboratories, Inc., Burlingame, CA). Specimens were examined under a confocal laser scanning microscope (TCS-SP; Leica Lasertechnik, Heidelberg, Germany), based on an upright microscope (DMRB, Leica Lasertechnik) equipped with a krypton/argon laser [ 33 ]. The excitation wavelengths for fluorescein isothiocyanate and Texas Red were 498 nm and 568 nm, respectively. Green fluorescein isothiocyanate emission was selected and recorded by using a 500- to 550-nm bandpass filter; red Texas Red emission was selected and recorded by using a 581- to 631-nm bandpass filter. In addition, 4,6-diamidino-2-phenylindole dihydrochloride was excited at 350-nm by using a UV laser, and its blue emission was recorded via a 401- to 551-nm bandpass filter. Localization of MMP-2 and Epimorphin in Lungs with NSIP To compare the precise localization of MMP-2 and epimorphin in NSIP, a confocal microscope was used for immunohistochemical study of lung tissues from patients with NSIP, by means of the same technical immunohistochemical staining and analysis method as that described previously for epimorphin and keratin detection [ 34 ]. Mouse anti-human MMP-2 monoclonal antibody and rat anti-mouse monoclonal epimorphin antibody served as primary antibodies. Secondary antibodies for double-labeling immunohistochemistry studies via confocal microscopy were goat anti-mouse IgG antibody (Alexa Fluor 546; Molecular Probes) and goat anti-rat IgG antibody (Alexa Fluor 488; Molecular Probes). Cell Culture and Treatment Conditions Human lung-derived alveolar epithelial cells (A549), an epithelial cell line derived from lung adenocarcinoma (Cell Resource Center for Biomedical Research, Institute of Development, Aging and Cancer, Tohoku University), were cultured in RPMI (GIBCO/BRL) supplemented with 10% fetal bovine serum, 2 mM l-glutamine, 50 U/ml penicillin, and 50 Î¼g/ml streptomycin. All cells were maintained at 37Â°C in a humidified incubator containing 5% CO 2 and 95% air. Detection of MMP-2 Expression in A549 Cells Four-well chamber slides (Lab-Tek II, Nalge Nunc International, Naperville, IL) were coated with human recombinant epimorphin fragment (H12; 20 Î¼g/well, dissolved in 1.5 mM HCl; a gift from Dr. Hirai), negative control solution prepared from non-transfected Escherichia coli strain BL21 (BL; 20 Î¼g/well, dissolved in 1.5 mM HCl; a gift from Dr. Hirai), or Type IV collagen from human placenta collagen (20 Î¼g/well, dissolved in 0.4% glacial acetic acid; Sigma Chemical Co., St. Louis, MO), after which samples were dried at room temperature. After A549 cells were washed two times with phosphate-buffered saline, the cells (5 Ã— 10 5 ) were suspended in RPMI medium with 2% fetal calf serum and were incubated at 37Â°C on the chamber slides coated with recombinant epimorphin, BL, or Type IV collagen. After incubation for 9 h, culture dishes were placed on ice, medium from each dish was collected, and cells were washed twice with phosphate-buffered saline. Cells were fixed in 4% paraformaldehyde in phosphate-buffered saline for 5 minutes at -20Â°C and then were washed in phosphate-buffered saline and permeabilized in acetone for 5 minutes at -20Â°C. Cells were again washed in phosphate-buffered saline and incubated with a blocking solution containing 1% bovine serum albumin/phosphate-buffered saline for 1 hour at room temperature. Immunohistochemistry was performed via the same technical method described above for epimorphin detection. The primary antibody was 5 Î¼g/ml mouse anti-human MMP-2 monoclonal antibody, and the secondary antibody was horseradish peroxidase-conjugated goat anti-mouse IgG antibody (Amersham Pharmacia Biotech UK Limited). The A549 culture supernatant collected after incubation for 9 hours on the chamber slides coated with recombinant epimorphin, BL, and Type IV collagen was used to determine the amount of MMP-2 activity by means of the MMP-2 Biotrack Activity Assay System (Amersham Pharmacia Biotech UK Limited), according to the manufacturer's instructions. All samples were assayed in triplicate, and assays were repeated three times. Statistical Analysis Densitometric analysis of the bands of Northern and Western blotting was performed with Macintosh G4 computer (Apple Japan, Inc., Tokyo, Japan) using high-resolution scanner and NIH image software (version 1.62, National Institutes of Health, Bethesda, Maryland). The data are expressed as a ratio of a standard normal control subject to each case's band density units (arbitrary units) and reported as mean Â± standard error of the mean (SEM). Statistical significance was established using the one-way analysis of variance test followed by Tukey-Kramer multiple intergroup comparison test. Probabilities less than 0.05 were considered significant. Results Expression of Epimorphin mRNA in Normal Human Lungs and Lungs of Patients with NSIP or UIP Expression of 3.2-kb epimorphin mRNA was revealed in all lung samples from patients with NSIP, UIP and normal control subjects by Northern blotting (Figure 1A ). To confirm that the blots reflected samples of equal size, they were reprobed for expression of Î²-actin mRNA. Compared with corresponding densities of Î²-actin, the densities of epimorphin expression in NSIP samples were significantly higher than those in control lungs and lungs with UIP, as determined by NIH Image analysis ( P < 0.05) (Figure 1B ). Figure 1 (A) Representative Northern blots of epimorphin mRNA and Î²-actin mRNA. Epimorphin mRNA (3.2-kb) was expressed in samples of normal lung (Control: lanes 1â€“3 ) and lungs from patients with UIP ( lanes 4â€“6 ) and patients with NSIP (lanes 7â€“9) ( upper blot ). To confirm that the blots reflected samples of equal size, they were reprobed for expression of Î²-actin mRNA ( lower blot ). (B) The data are expressed as a ratio of epimorphin to Î²-actin band density units (arbitrary units) and reported as mean Â± SEM measured by means of NIH Image analysis. In NSIP samples, the density of epimorphin expression was significantly higher than that in control and UIP samples (* P < 0.05). Tissue Localization of Epimorphin in Normal Human Lungs Western blotting showed that rat anti-mouse epimorphin monoclonal antibody (MC-1) recognized the 150-kd bands in the extracted samples from both mouse lung and normal human lung (Figure 2A ), similar to results reported elsewhere [ 31 , 32 ]. We thus confirmed that anti-mouse epimorphin antibody demonstrated specificity and cross-reactivity with the human epimorphin of our lung samples. Normal lung tissues of the human samples had normally opened alveoli with infiltration of a few inflammatory cells. In immunohistochemical studies of the human samples, as with normal mouse lung specimens [ 34 ], epimorphin was weakly stained in vascular and alveolar walls (Figure 2B ). Negative control staining with normal rat serum showed no positive findings in the serial section (data not shown). Figure 2 Representative Western blots for epimorphin in normal mouse and human lung samples (A), and representative epimorphin immunohistochemistry (B) in normal mouse lung. (A) Recognition of the 150-kd bands by rat anti-mouse epimorphin monoclonal antibody (MC-1) in extracted lung samples. (B) Weak epimorphin staining in vascular walls ( arrowheads ) and alveolar walls ( inset ). Scale bar = 50 Î¼m. Amount of Epimorphin in Normal Human Lungs and Lungs of Patients with NSIP or UIP In the lung tissue homogenates of patients with NSIP, UIP and of control subjects, Western blotting with antibody for epimorphin also recognized the 150-kd bands (Figure 3A ) and the densities of the bands of patients with NSIP are relatively higher than those of UIP and control subjects by methods of NIH image analysis (p < 0.05) (Figure 3B ). Figure 3 (A) Representative Western blots for epimorphin in normal control subjects and fibrotic groups. Epimorphin protein (150-kd) was expressed in samples of normal lung (Control: lanes 1â€“3 ) and lungs from patients with UIP ( lanes 4â€“7 ) and patients with NSIP ( lanes 8â€“10 ). (B) The data are expressed as a ratio of a standard normal control subject to each case's band density units (arbitrary units) and reported as mean Â± SEM measured by means of NIH Image analysis. In NSIP samples, the density of epimorphin protein expression was significantly higher than that in control and UIP samples (* P < 0.05) Tissue Localization of Epimorphin in NSIP and UIP by Means of Immunohistochemical Analyses In lungs of all patients with NSIP, alveolar walls were thickened with edema, fibrosis, and inflammatory cell infiltration; the appearance was typically uniform (Figure 4A ). There was slight or no dense fibrosis; intra-alveolar organizing fibrosis was seen as pale eosinophilic fibrosis with H&E staining and as Alcian blue positive area with AB-PAS staining as early stage of fibrosis (Figure 4A and 4B ). Epimorphin immunostaining was strong in the early intra-alveolar fibrotic areas with a covering of regenerated alveolar epithelial cells (Figure 4C and 4E ), which contained a few Î±-smooth muscle actin-positive cells (Figure 4F ), in addition to immunostaining seen in vascular and alveolar walls. No positive findings was shown using normal rat serum as fist antibody for negative control (Figure 4D ). The epimorphin immunohistochemical staining patterns for all eight patients with NSIP were quite similar. Figure 4 Representative histology stained with hematoxylin-eosin (H&E)(A) and Alcian blue-periodic acid-Schiff (AB-PAS)(B) and immunohistochemistry for epimorphin (C), rat normal serum as negative control for epimorphin (D), keratin (E), and Î±-smooth muscle actin (F) for all patients with NSIP. (A) Thickened alveolar walls showed edema, fibrosis, and inflammatory cell infiltration. Dense fibrosis was inconspicuous or absent. (A and B) Intra-alveolar organizing fibrotic areas were seen as pale eosinophilic fibrosis with H&E staining and as Alcian blue positive area with AB-PAS staining as early stage of fibrosis ( asterisks ). (C) Positive epimorphin immunostaining appeared in areas of early fibrosis ( inset in C shows a close-up view; asterisks indicates early intra-alveolar fibrotic area) covered with regenerated alveolar epithelial cells ( arrowhead in E), in addition to the alveolar walls. A few Î±-smooth muscle actin-positive cells were noted in the fibrotic areas ( arrowhead in F). Scale bars = 60 Î¼m. In lungs of all patients with UIP, the fibrotic zones showed temporal heterogeneity, with dense acellular collagen and scattered fibroblastic foci with intervening nearly normal alveoli. Most fibrotic zones had honeycombing with complete destruction of the architecture (Figure 5A ). Though clear immunostaining in the vascular walls, only weak epimorphin immunostaining occurred in dense fibrotic lesions and scattered fibroblastic foci, as in areas of early fibrosis (Figure 5B and 5F ) with Alcian blue positive (Figure 5E ). The scattered fibroblastic foci contained many Î±-smooth muscle actin-positive cells (Figure 5D ) with the desquamative regenerated alveolar epithelial cells overlying these fibroblastic foci (Figure 5C ). Figure 5 Representative histology (A, C [close-up view]; H&E staining) and immunohistochemistry for epimorphin (B, F [close-up view]) and Î±-smooth muscle actin (D [close-up view]) of scattered fibroblastic foci in early fibrotic areas as Alcian blue positive area (E; AB-PAS staining) for patients with UIP. (A and C) Honeycombing with complete architectural destruction occurred in fibrotic zones. (C and E) Arrowheads indicate scattered fibroblastic foci. In addition to clear immunostaining in the vascular and alveolar walls ( arrows ), only weak epimorphin immunostaining was seen in scattered fibroblastic foci ( arrowheads ) (B and F); many Î±-smooth muscle actin-positive cells (D) and desquamative regenerated alveolar epithelial cells (C) were found. Scale bars = A, B: 200 Î¼m; Câ€“E: 80 Î¼m. Tissue Localization of Epimorphin in NSIP by Means of Double-labeled Immunohistochemical Analyses Double-labeled confocal fluorescent images confirmed the presence of epimorphin in early fibrotic lesions and keratin-positive epithelial cells overlying the lesions (Figure 6A and 6B ). Double-labeled confocal fluorescent images also verified the localization of epimorphin in vimentin-positive stromal cells and in surrounding ECM (Figure 6C, D , and 6E ) in early fibrotic lesions. Figure 6 Representative double-labeled confocal fluorescent images of staining for epimorphin plus keratin (A), epimorphin (C), vimentin (D), and epimorphin plus vimentin (E) in an early fibrotic lesion from the lung of a patient with NSIP. (A) The presence of epimorphin (green) in areas of early fibrosis and the presence of keratin (red) in epithelial cells overlying the lesions were confirmed. (B) The same image shown in part A but with Nomarski optics used. (Câ€“E) Epimorphin (C, green) localized in vimentin-positive (D, red) stromal cells (yellow-orange) and in surrounding ECM in early fibrotic areas (E). Nuclei were 4,6-diamidino-2-phenylindole dihydrochloride-positive (blue). Asterisks indicate early fibrotic areas. Scale bars = B: 20 Î¼m, E: 5 Î¼m. Localization of MMP-2 and Its Relation to Epimorphin in NSIP Areas of early fibrosis in lung tissues from patients with NSIP showed epimorphin immunoreactivity (Figure 7A ), and regenerating epithelial cells overlying these lesions demonstrated MMP-2 labeling (Figure 7B ). Furthermore, in tissues from patients with NSIP, double-labeled confocal fluorescent images confirmed the expression of MMP-2 (Figure 7C ) in re-epithelialized cells overlying fibrotic lesions in which epimorphin was also clearly expressed. Figure 7 Representative images of immunostaining for epimorphin (A) and MMP-2 (B) in NSIP; the double-labeled confocal fluorescent image of in an early fibrotic lesion from the lung of a patient with NSIP was stained for epimorphin plus MMP-2 (C). (A) Epimorphin immunoreactivity was observed in early fibrotic areas, with (B) MMP-2 labeled in regenerated epithelial cells overlying the fibrotic lesion. Asterisks indicate early fibrotic areas. (C) MMP-2 (red) was strongly expressed in re-epithelialized cells overlying early fibrotic lesions with clear epimorphin expression (green). Nuclei were 4,6-diamidino-2-phenylindole dihydrochloride-positive (blue). Asterisks indicate early fibrotic areas. Scale bars = 20 Î¼m. Increased Expression of MMP-2 Induced in A549 Cells by Epimorphin Nine hours after plating of BL or Type IV collagen-coated chamber slides with cells of the human lung-derived alveolar epithelial cell line A549, the cells had spread and formed a loose sheet (Figure 8A , left panel). However, during the same time period, in recombinant epimorphin-coated chamber slides, the A549 cells formed some monolayer cell islands in addition to the loose cellular sheet, in about 50% of the chamber slide area (Figure 8A , right panel). Moreover, the immunoperoxidase method revealed strong MMP-2 immunostaining in cells of these cell islands in epimorphin-coated slides after 9 hours of incubation (Figure 8A , right panel). The MMP-2 Biotrack Activity Assay System revealed significantly higher MMP-2 activity levels in the supernatants of cultures of A549 cells with recombinant epimorphin compared with those for cultures with BL or Type IV collagen after 9 hours of incubation (Figure 8B ). Figure 8 (A) Representative images of MMP-2 immunostaining in A549 cells cultured with recombinant epimorphin ( right panel ) or with BL ( left panel ) after 9 hours of incubation. In the epimorphin-coated slides, plated cells formed some monolayer cell islands in addition to loose sheets of cells, and cells in these cell islands showed strong MMP-2 immunostaining (by the immunoperoxidase method). Scale bars = 30 Î¼m. (B) Via the MMP-2 Biotrack Activity Assay System, MMP-2 activity in the supernatants of A549 cells cultured with recombinant epimorphin was higher than in supernatants of cells cultured with BL or Type IV collagen ( P = 0.01). Discussion This is the first study to examine in detail the distribution and magnitude of epimorphin expression in normal human lungs and lungs from patients with NSIP or UIP. We found clear expression of epimorphin mRNA and protein in lung samples from normal control subjects and patients with NSIP or UIP. Expression of Epimorphin in Normal Human Lungs Consistent with previous reports [ 32 ], epimorphin was expressed in connective tissue components of walls of the alveoli and blood vessels in normal lungs, as determined by immunohistochemistry. Epimorphin expression was also confirmed at the mRNA and protein levels by Northern and Western blotting assays, similar to results found previously for mice [ 15 , 32 ]. Although the specific function of epimorphin in normal lungs is not yet known, it may serve as an epithelial and endothelial cell morphogen to maintain the cell turnover necessary for normal structure and function. Alveolar epithelial cells are replaced at regular intervals under physiologic conditions. For example, the estimated turnover time for normal mouse alveolar epithelial cells ranges from 28 to 35 days [ 35 ], and daily endothelial cell turnover is reported to be about 1% [ 36 ]. Also, in the normal adult human kidney, similar to results for normal adult mouse kidney, low levels of epimorphin mRNA and protein were detected in the glomerular mesangium and peritubular interstitium (interstitial fibroblast-like cells), as revealed by reverse transcriptase -polymerase chain reaction and immunohistochemistry [ 37 ]. These findings are consistent with our result that epimorphin is expressed in the interstitium in human control lungs, as in normal adult mouse lungs [ 34 ]. Expression of Epimorphin in Lungs of Patients with NSIP or UIP We found, by means of Northern blotting assays, distinct expression of epimorphin mRNA and protein in normal lungs and lung samples of patients with NSIP or UIP, with significantly higher epimorphin expression in lungs of patients with NSIP than in other lung samples. Also, serial sections and double-labeled immunohistochemistry analyses of NSIP samples demonstrated strong expression of epimorphin in mesenchymal cells situated within active intra-alveolar fibrotic lesions and the presence of epimorphin in the ECM in the vicinity of these cells. These findings are consistent with our previous report that epimorphin was synthesized by mesenchymal cells and localized to these cells and the ECM of early intra-alveolar fibrotic lesions in a murine bleomycin-induced pulmonary fibrosis model [ 34 ]. They are also consistent with a report that epimorphin was synthesized by normal human skin fibroblasts [ 38 ]. It is well known that regeneration of alveolar and bronchiolar epithelial cells is crucial for repair of pulmonary fibrosis, and the ECM in early fibrotic lesions provides fibronectin and other adhesion molecules as ligands for regenerating epithelial cells to ensure successful repair [ 3 , 4 , 39 - 41 ]. In the murine bleomycin-induced pulmonary fibrosis model, we suggested that epimorphin in the early fibrotic lesions participated in adhesion of the regenerating alveolar epithelial cells. Involvement of epimorphin in the repair process was also reported for other organs including the gut during tissue repair in an isograft in rats [ 20 ] and the liver during regeneration after partial hepatectomy in mice [ 17 ]. Increased expression of epimorphin during epithelial cell regeneration was also reported in human skin ulcers and active ulcerative colitis [ 32 , 42 ]. We observed strong epimorphin immunostaining in early fibrotic areas with a few Î±-smooth muscle actin-positive cells in NSIP, as well as weak epimorphin immunostaining in fibroblastic foci with many Î±-smooth muscle actin-positive cells and desquamative regenerated alveolar epithelial cells in UIP. It is believed that in UIP, a failure of re-epithelialization of fibroblastic foci maintains fibroblast/myofibroblast activity and ECM synthesis [ 43 , 44 ]. We suggest that highly expressed epimorphin in the lungs of patients with NSIP may be necessary during wound healing, especially for regeneration of alveolar epithelial cells in early fibrotic lesions, and we also suggest that poorly expressed epimorphin in the lungs of patients with UIP may lead to failure of re-epithelialization of fibroblastic foci and the contraction of fibrotic lungs during the end stage of UIP. Role of Epimorphin Associated with MMP-2 in Lung Repair To understand the role of epimorphin in the repair process in the lungs of patients with NSIP, we evaluated whether epimorphin enhanced expression of MMP-2 (gelatinase A). Recombinant epimorphin induced formation of some monolayer cell islands in addition to a loose cellular sheet and augmented expression of MMP-2 in cultured human alveolar epithelial cells, as demonstrated by immunohistochemistry and the MMP-2 Activity Assay System. We suggest that epimorphin-induced monolayer cell islands are a type of formation of differentiated alveolar epithelial cells, like the epimorphin-induced spheroid formation of rat hepatocytes, and suggest that the augmented expression of MMP-2 may be similar to the increased albumin production of rat hepatocytes. We also demonstrated expression of MMP-2 in re-epithelialized cells overlying epimorphin-positive early fibrotic areas by means of double-labeled confocal fluorescent images. MMP-2, which is an important proteinase needed for matrix degradation, is secreted by type II alveolar epithelial cells in vitro [ 45 ]. Fukuda et al. [ 25 ] observed the localization of MMP-2 in fetal rabbit alveolar epithelial cells and gelatinolytic activities of MMP-2 in fetal rabbit lung, which indicated an important role for MMP-2 in formation of alveoli. These authors also observed the localization of MMP-2 in regenerating alveolar epithelial cells covering intra-alveolar fibrotic areas in a study of bronchiolitis obliterans organizing pneumonia, which is a reversible fibrotic human lung disease [ 13 ]. Yaguchi et al. [ 26 ] reported that MMP-2 was found in regenerating alveolar epithelial cells and that gelatinolytic activities of the active forms of MMP-2 increased in later repair stages in bleomycin-induced pulmonary fibrosis, during reconstruction of alveoli. Moreover, Fukuda et al. [ 46 ] reported that in bleomycin-induced pulmonary fibrosis, re-epithelialization on the surface of early intra-alveolar fibrotic lesions in gelatinase A -/- mice was markedly reduced compared with that of gelatinase A +/+ controls. Thus, MMP-2 was up-regulated and activated in regenerating alveolar epithelial cells, which may allow elongation and migration of these cells for successful repair of pulmonary fibrotic lesions [[ 26 , 27 ], 47]. We therefore suggest that epimorphin expression in early fibrotic lesions in the lungs of patients with NSIP may contribute to the repair process in pulmonary fibrosis, in part by inducing MMP-2 expression. What may follow this MMP-2 expression may be elongation and migration of regenerating epithelial cells and degradation of ECM in alveolar spaces. Thus, epimorphin, as a component of proteolytic systems, may contribute to cell migration and tissue remodeling during repair of human lung fibrosis. Although epimorphin receptors have not yet been identified, binding ECM molecules has been suggested as involved in establishing epithelial polarity, thus helping form an organized basement membrane and cell-ECM junctional complexes [ 21 ]. Our results are consistent with the idea [ 22 , 34 ] that epimorphin has a high affinity for ECM molecules and could modify functions of adhesion and migration of regenerating alveolar epithelial cells by altering signaling through MMP-2. In conclusion, epimorphin expressed in lungs may have important roles as a morphogen not only in mice but also in humans, and epimorphin may contribute to the repair process in human pulmonary fibrosis via epithelium-mesenchyme interactions. Supplementary Material Additional File 1 Table 1. Characteristics of subjects, including pulmonary function test results Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548284.xml
545950	Neural progenitor cells from an adult patient with fragile X syndrome	Background Currently, there is no adequate animal model to study the detailed molecular biochemistry of fragile X syndrome, the leading heritable form of mental impairment. In this study, we sought to establish the use of immature neural cells derived from adult tissues as a novel model of fragile X syndrome that could be used to more fully understand the pathology of this neurogenetic disease. Methods By modifying published methods for the harvest of neural progenitor cells from the post-mortem human brain, neural cells were successfully harvested and grown from post-mortem brain tissue of a 25-year-old adult male with fragile X syndrome, and from brain tissue of a patient with no neurological disease. Results The cultured fragile X cells displayed many of the characteristics of neural progenitor cells, including nestin and CD133 expression, as well as the biochemical hallmarks of fragile X syndrome, including CGG repeat expansion and a lack of FMRP expression. Conclusion The successful production of neural cells from an individual with fragile X syndrome opens a new avenue for the scientific study of the molecular basis of this disorder, as well as an approach for studying the efficacy of new therapeutic agents.	Background Fragile X syndrome, the leading heritable form of mental impairment [ 1 , 2 ], is generally caused by the expansion of a trinucleotide (CGG) repeat element in the fragile X mental retardation 1 ( FMR1 ) gene to greater than 200 repeats (full mutation) [ 3 ]. Such expansions generally lead to methylation-coupled gene silencing [ 4 , 5 ] and the consequent absence of the FMR1 protein (FMRP), an RNA-binding protein that is important for neural development and plasticity [ 6 , 7 ]. Although great strides have been made from animal models in our understanding of the neuropathology of fragile X syndrome [ 8 - 13 ], there is, at present, no adequate animal or cell model to study the detailed molecular biochemistry of the FMR1 gene. The absence of a suitable model system is a consequence of the inability to clone full mutation alleles, and because no animal system has been found that carries native, full mutation FMR1 alleles. Thus, all animal or cell model systems for fragile X syndrome are based on FMR1 (homolog) knock-out constructs. While these models qualitatively recapitulate some of the features of the fragile X syndrome phenotype, they do not address any of the potential consequences of the expanded methylated CGG repeat. As with most disorders of the human nervous system, it has been impossible to directly study the detailed cellular pathogenic mechanisms that underlie fragile X syndrome, due to the absence of a suitable (human) cell model. However, this barrier may be overcome through the use of neural progenitor cells, which comprise relatively undifferentiated populations of cells in the central nervous system (CNS) that give rise to the broad array of specialized cells, including neurons and glial cells. Long thought to be an exclusive component of the developing CNS, these cells have been shown to exist in the adult CNS [ 14 - 19 ]. Recent research, demonstrating that these cells can be isolated and cultured [ 14 , 18 , 20 - 22 ] has raised the prospect of using neural progenitor cells as a human cell-appropriate (neuronal and astrocytic) model system for the detailed study of the molecular biology of fragile X syndrome. Importantly, we have previously shown that neural progenitor cells can be harvested from adult post-mortem brain tissue [ 18 , 20 ], which represents a singular advantage over the use of neural stem cells from fetal sources. In particular, since there is a broad spectrum of clinical involvement in fragile X syndrome [ 2 ], the study of neural stem cells from individuals of known phenotype provides us with a closer coupling of the genotype with the clinical phenotype. In the current report, we describe the successful culturing of neural progenitor cells from an adult male with fragile X syndrome, and some of the characteristics of these cells. We further demonstrate initial efforts to differentiate these progenitor cells into both neuronal and astrocytic lineages. As expected, expression of FMRP is substantially reduced relative to its expression in neural cell culture from an unaffected control. Methods Autopsy, brain harvest, and tissue cryopreservation Prior to tissue acquisition by the authors, informed consent for the donation of tissues was obtained under the auspices of the protocol for the National Human Neural Stem Cell Resource. This protocol is approved by Institutional Review Board (IRB) of Children's Hospital of Orange County, and follows a protocol approved by the UC Davis School of Medicine IRB. All tissues were acquired in compliance with NIH and institutional guidelines. Two patients were used for the present study: a patient with fragile X syndrome and a patient with no neurogenetic disease. The autopsy followed standard procedures as described [ 20 ]. The periventricular zone in the area of the head of the caudate nucleus regions was identified and dissected from the appropriate brain sections. Brain region specimens were then placed in separate Petri dishes and rinsed three times with DGA (see below). Tissues were minced with sterile scalpel blades, triturated in DGF (see below) containing 10% DMSO, taken to -80°C overnight in controlled-rate freezing containers, and then transferred to liquid nitrogen Dewars for long term storage. Pathology Portions of fresh brain, heart, and testicular tissue were received, and fixed in 10% formalin for 10 days prior to sampling and processing for paraffin sections in standard fashion. All tissue sections were stained with hematoxylin and eosin, with cardiac valves and aorta additionally stained for elastin and mucin. All sections were examined by standard light microscopy. Cell culture The base medium was a high glucose 1:1 DMEM:F12 (Irvine Scientific). The basal medium (DGA) used for all other media was the base medium containing glutamine, penicillin, streptomycin, gentamicin, ciprofloxacin, and amphotericin as previously described [ 20 ]. Medium (DGF) used for all washes consisted of DGA containing 20% fetal bovine serum. All procedures were performed as previously described [ 20 ], with modifications. Tissues were quickly thawed, diluted by drop-wise addition and agitated in 10 volumes of DGF, then further dissociated by trituration and three washes in DGF with centrifugation – no enzymatic digestion was used. Whole tissue homogenates were plated directly on fibronectin-coated tissue culture plates (6-well, tissue culture treated, Falcon) in primary growth medium (PGM) composed of DGF containing 10% BIT 9500 (Stem Cell Technologies), 40 ng/mL basic fibroblast growth factor (FGF-2; InVitrogen), 20 ng/mL epidermal growth factor (EGF; InVitrogen), and 20 ng/mL platelet-derived growth factor-AB (PDGF-AB; Peprotech). Plates had been previously incubated with 200 uL/cm 2 of fibronectin (5 ug/mL; Sigma) overnight at 37°C, the fibronectin solution aspirated, and the plates allowed to air dry before the introduction of tissue homogenates. Approximately 300 mg fresh tissue was subjected to mincing and trituration, and the resulting crude tissue homogenate plated into six wells of a fibronectin-coated six-well tissue culture plastic plate (≈60 cm 2 total surface area). After plating, 50% of the medium was replaced, 3 times weekly. Non-adherent cells and debris from the removed supernatant were pelleted by centrifugation and re-introduced into the cultures together with the fresh medium. After 7 days in culture, plates were agitated by sharp rapping with a marking pen and 100% of the culture medium and non-adherent material was removed. Fifty percent of the volume removed was replaced with fresh medium, while the removed medium was centrifuged to pellet cell debris and non-adherent cells and to recover conditioned medium as supernatant. Fifty percent, by volume, of the conditioned medium was then returned to the original plates. The pellet, containing the non-adherent fraction, was resuspended in 50% conditioned medium and 50% fresh medium, by volume, and then transferred to a fresh fibronectin-coated 6-well plate. After one week, the procedure was repeated, except that the non-adherent fraction was discarded. In this way, an additional population of cells was recovered from the non-adherent fraction. All the cells were eventually combined to form a single population of cultured cells. At near confluence, cultures were passaged by lifting with a solution of Cell Dissociation Buffer (GIBCO) supplemented with trypsin. The cells were washed twice with DGF and plated in 1:1 (conditioned:fresh) medium into a fibronectin-coated T75 flask. Thereafter, and at approximately one week intervals, cells were lifted and similarly plated into twice the surface area from which they were removed. After the cells had reached a confluent surface area of 600 cm 2 , the medium from one T75 flask was exchanged with GM (PGM without serum), and these cells were cultured for two weeks before immunocytochemical analysis, or differentiation and immunocytochemical analysis, as previously described [ 20 ]. Immunocytochemistry Immunocytochemistry was performed as previously described [ 20 ]. Primary antibodies and dilutions were used as follows: nestin (1:100; mouse; Chemicon), type III β-tubulin (Tuj20; 1:100; mouse; Chemicon), MAP2ab (1:250; mouse; Sigma), GFAP (1:500, guinea pig; Advance Immuno), CD133-APC (1:100; mouse; Miltenyi), NCAM (1:100, rabbit, Chemicon), fusin (1:100, mouse, Chemicon), and FMRP (1:100; mouse; Chemicon). Coverslips were mounted with Prolong ® Antifade Kit (Molecular Probes, Eugene, OR). Some cells were stained with 4',6-diamidino-2-phenylindole (DAPI, Sigma) before being rinsed and mounted. Pictures were imaged on an Olympus IX70 Microscope and digitally photographed via a Microfire digital camera (Optronics, Goleta, CA) using Image Pro Plus 4.5 with AFA plugin 4.5 software. Molecular studies DNA analysis Genomic DNA was isolated from approximately 5 × 10 6 neural progenitor cells and from post-mortem sections of about 500 mg of brain tissue using standard methods (Puregene Kit; Gentra). For Southern blot analysis, 10 μg of isolated DNA were digested with Eco RI and Nru I. The FMR1 genomic probe StB12.3, labeled with Dig-11-dUTP by PCR (PCR dig synthesis Kit, Roche Diagnostics), was used in the hybridization, as described in Tassone et al. [ 31 ]. Genomic DNA was also amplified by PCR using primers c and f [ 32 ]; PCR products were detected using a digoxygenin-end-labeled oligonucleotide probe (CGG) 10 . Southern blot and PCR analyses were both carried out using an Alpha Innotech FluorChem 8800 Image Detection System. FMR1 mRNA expression levels Total RNA was isolated from approximately 1 × 10 6 neural progenitor cells and from post-mortem brain tissue using standard methods (Purescript, Gentra Inc. and Trizol). Reverse transcriptase reactions and quantitative fluorescence RT-PCR, using specific primers and probe set for the FMR1 gene and the control gene (β-glucoronidase; GUS ), were carried out as described in Tassone et al. [ 33 ]. Results Clinical history JS was a 25-year-old man with fragile X syndrome. His history included motor and language delays in childhood, with walking at 20 months, phrases at three years, and sentences at 6 years of age. He was diagnosed with fragile X syndrome at 11 years of age, by cytogenetic testing. His behavior included hyperactivity, anxiety, shyness, poor eye contact, hand flapping, finger biting, and perseverative speech. At age 24, cognitive testing with the WAIS III demonstrated a verbal IQ of 58, performance IQ of 51, and full scale IQ of 51. He did not have autism; childhood autism rating scale (CARS) score was 28.5 (below autism range). Previous medical history included severe mitral valve prolapse; echocardiography revealed moderate thickening and redundancy of both mitral leaflets, with central mitral regurgitation (grade 2 to 3+ by Doppler), mild tricuspid regurgitation, and moderate left ventricular and mild left atrial enlargement. Upon physical examination at age 24, JS had a long face, prominent ear pinna, high arched palate, and macroorchidism with testicular volume of 60 ml bilaterally. Blood pressure was 142/74, and a grade III/IV systolic and diastolic murmur with click was heard on examination. He died unexpectedly at age 25, presumably due to a cardiac arrhythmia secondary to mitral valve prolapse. Pathology A complete autopsy was performed 16 hours after death. Abnormal findings included increased brain weight (1600 gm; normal, 1440 ± 20 g), an enlarged heart, (400 gm; normal, 349 ± 40 g), with features of mitral valve prolapse (myxomatous thickening of both leaflets; "hooding" of the posterior leaflet), and increased testicular weight of 73 g (normal average, 25 g). Our laboratory did not receive the intact brain, but portions of it, therefore detailed gross and histological evaluation was not possible. In particular, neither the hippocampus nor the amygdala was available for histopathological examination. Evaluation of available brain sections showed diffuse, acute early ischemic damage corresponding to the manner of death; no intraneuronal inclusions were seen, nor was there spongiosis of white matter in the cerebrum, cerebellum, or middle cerebellar peduncles. Cerebellar folia showed moderate patchy absence of Purkinje cells; because of the manner of death, loss due to ischemic damage cannot be ruled out. However, the majority of Purkinje cells present appeared histologically normal. Cell culture Minced brain tissue, derived from the periventricular zone in the area of the head of the caudate nucleus and maintained under proliferation conditions in serum-containing medium with growth factors, yielded viable cells that formed an adherent monolayer on fibronectin-coated plates. When lifted and plated without serum or fibronectin substrate, the cells grew in suspended clusters/spheres (Figure 1 ), similar to previously described neurospheres [ 20 ]. The morphology within the adherent population was variable and included small, rounded profiles, medium-sized bipolar and spindle-shaped profiles, and larger cells with polygonal and multipolar morphologies. Once a robust primary culture had been established in the six-well plates (approximately one month after plating of tissue homogenates), the cultures were passaged into T75 flasks approximately once per week until 600 cm 2 of confluent adherent cells had been produced. Cells were then further expanded under serum-free conditions for immunocytochemical analysis, or under growth-factor-free conditions for biochemical analysis. Figure 1 Phase-contrast photomicrographs of fragile X progenitor cells The figure shows clusters/spheres during the initial stages (2–3 days after plating) of adherence to a fibronectin substrate. (A) 4×; (B) 10×; (C) 20×. Confluent serum- and growth factor-expanded cultures were serum deprived for one week in the presence of growth factors, then lifted with enzyme-free buffers and transferred to new plates with no fibronectin substrate. After growing the resulting clusters/spheres for two weeks, the clusters/spheres were transferred to new fibronectin-coated plates. Clusters/spheres (black arrows) are abundant and are seen adhering to the substrate. Cells (black arrowheads) can be seen streaming from the spheres and spreading out on the substrate. Although the methodology used was similar to that previously reported [ 20 ], four conditions employed in the current work are noteworthy. ( i ) The cells were grown from cryopreserved, rather than fresh, tissue. This modification allows pathologists with no local access to a stem cell culture laboratory to preserve tissues for later stem cell harvest at a remote collaborating laboratory. ( ii ) No enzymatic digestion, only trituration, was used to generate the crude tissue homogenates. Preliminary studies showed that enzymatic digestion, typically used with fresh tissue, adversely affected our ability to harvest living cells from cryopreserved tissues. ( iii ) Serum (20%) was maintained in the culture until it was expanded to 600 cm 2 of confluent adherent cells, after which the cells were cultured in serum-free medium. Preliminary studies indicated that, unlike cells harvested from fresh tissues, cells harvested from cryopreserved tissues required application of serum for a longer time in culture to sustain a sufficient rate of proliferation. ( iv ) The non-adherent fraction was transferred to new fibronectin-coated plates after one week. Preliminary studies showed that the non-adherent fraction from cryopreserved tissues retained a significant population of viable cells for a longer period of time than that from fresh tissue. These plates were cultured for an additional week before the remaining non-adherent fraction was finally discarded. Cells grown from both sets of plates were combined for expansion. Immunocytochemistry Immunocytochemical analysis of fragile X neural progenitor cells grown under expansion conditions demonstrated the expression of a range of developmental and mature neural markers (Figure 2 ). Many of the current results are similar to previous findings with control human neural progenitor cell cultures [ 20 ]. In particular, the distribution of the multipotential neural progenitor lineage marker, CD133, the neuroepithelial marker nestin, and the neural cell adhesion molecule, NCAM, are found to be widespread in these cultures, consistent with earlier observations of immunocytochemistry and flow cytometry in control human neural progenitor cells [ 20 , 23 , 24 ]. The CXCL12 (SDF-1) cytokine receptor, CXCR4 (fusin, CD184), and the glial neurofilament marker, glial fibrillary acidic protein (GFAP), are also widely expressed in the fragile X neural progenitor cell cultures, in agreement with a previous report [ 20 ]. The expression of β-III-tubulin, a mature neuronal marker, is restricted to subpopulations of cells, again consistent with control human neural progenitor cells [ 20 ]. Finally, the primitive neuroepithelial (intermediate filament) markers, nestin and CD133, seen in the proliferating neural progenitor cells (Figure 2 ), disappear under differentiation conditions (data not shown). Importantly, FMRP staining is markedly reduced in the fragile X neural progenitor cells (Figure 3 ) compared to control cultures. Figure 2 Staining of fragile X progenitor cells, grown under expansion conditions In all panels, nuclei are stained with DAPI (blue), while the second color represents antibody staining as follows: (A) multipotential neural progenitor lineage marker, CD133 (red); (B) neural cell adhesion molecule, NCAM (green); (C) CXCL12 (SDF-1) cytokine receptor, CXCR4 (fusin, CD184, red); (D) β-III-tubulin (green); (E) the glial fibrillary acidic protein, GFAP (green); (F) nestin. (100×). Figure 3 Markedly reduced staining with anti-FMRP antibody of neural progenitor cells from a fragile X patient FMRP staining (green) is greatly reduced in the fragile X derived cells (A) relative to progenitor cells from an unaffected control (B). Cell nuclei counterstained with DAPI (blue); both panels, 40×. Molecular studies Southern Blot analysis of DNA isolated from brain tissue (frontal cortex) showed the presence of a mosaic pattern. Specifically, full mutation alleles were present in 82% of the cells (435, 528, 652, 727, 847 CGG repeats) with the remaining 18% harboring a premutation allele. Sizing of the CGG repeat number by PCR analysis demonstrated the presence of a premutation allele of 90 CGG repeats and an allele with the deletion of the CGG element and the flanking region, the latter of which was not detected by Southern Blot analysis. Sequence analysis of this allele indicated the presence of a deletion extending from nucleotide 13742 to 13915 of the FMR1 gene (GenBank accession number L29074). Southern blot analysis of DNA isolated from neural progenitor cells revealed the presence only of hypermethylated full mutation alleles (536 and 591 CGG repeats). No premutation alleles were detected by PCR analysis. The brain FMR1 mRNA level (frontal cortex) relative to the reference gene (glucuronidase) was low (0.08 ± 0.009, relative value). In agreement with the observed lack of FMRP expression, no FMR1 message was detected after 40 cycles of PCR in total RNA isolated from the neural progenitor cells. Discussion In the current work, we have successfully isolated and cultured neural progenitor cells from post-mortem brain tissue of an adult male with fragile X syndrome, which, to our knowledge, is the first example of the production of adult, human neural progenitor cells for any neurodevelopmental disorder. This result is of particular importance for the study of fragile X syndrome, since the disease-causing CGG repeat expansions have thus far been refractory to cloning into any animal or human cell model. With these cells, we hope to better understand the mechanistic link between the CGG expansion and the disease phenotype, which is known for the donor of the cells. We have demonstrated the feasibility of generating neural progenitor cell cultures from post-mortem brains of patients with neurogenetic disease. Moreover, as the cultures were generated from cryopreserved tissue, our data suggest that cells can be harvested and processed from the required tissues in locations that are remote from the stem cell culture laboratory. This last point is of particular importance for the study of neurogenetic diseases, which generally affect only 1:20,000 to 1:200,000 live births; a technique that can be implemented at multiple institutions will be necessary to generate sufficient numbers of specimens for statistical analysis. A major determinant of the proliferative capacity of neural progenitor cells in culture is donor age, with younger donors (particularly fetuses and infants) having greater proliferative capacity than adults [ 18 ]. Although progenitor cells can be obtained from fetal or embryonic sources, there are advantages to obtaining cells from post-mortem adult tissue. In using cells derived from adult tissues, one avoids the serious ethical controversies surrounding the use of fetal samples [ 25 - 27 ]. Moreover, for research aimed at understanding the effects of identified genetic defects on neural development, the phenotypic expression of a particular neurogenetic disease can be ascertained with post-mortem specimens, thus making a correlation possible between in vitro and in vivo pathophysiology. Due to the broad variability in phenotypic expression in fragile X syndrome (as with many other neurodevelopmental disorders), any such correlations are problematic using tissue obtained at fetopsy. The method used to isolate the neural progenitor cells in the current study was adapted from the neuro-selective methods developed for culturing CNS stem cells from the brain [ 28 ], spinal cord [ 29 ], and retina [ 30 ] of rodents, as well as the brain of humans [ 18 , 20 ]. Passaged cells expressed a number of immature markers, including the neural stem cell markers CD133 and nestin [ 20 ]. Although the currently recognized method for establishing multipotency is clonal derivation followed by differentiation, these cells proliferated poorly when seeded at low density and, therefore, clonal derivation has not been fruitful thus far. Nevertheless, analysis of marker expression provides evidence that these cultures give rise to cells of neuronal lineage (β-III tubulin) and glial lineage (GFAP). Our data are thus most consistent with the interpretation that the immature, highly proliferative neuroepithelial cells in the present study were multipotent neural progenitor cells. Conclusions The successful production of neural cells from an individual with fragile X syndrome opens a new avenue for the scientific study of the molecular basis of this disorder, as well as an approach for studying the efficacy of new therapeutic agents. Competing interests The author(s) declare that they have no competing interests. Authors' contributions PHS conceived of the study, participated in its design and coordination, and drafted the manuscript. FT carried out the molecular genetic studies, participated in the design of the study, and helped to draft the manuscript. CMG performed the neuropathological analyses. HEN carried out the cell culture. BZ performed the immunocytochemical analyses and imaging. RJH performed the clinical evaluation. PJH participated in the design of the study and helped to draft the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545950.xml
548292	Individualized quality of life, standardized quality of life, and distress in patients undergoing a phase I trial of the novel therapeutic Reolysin (reovirus)	Background The purpose of this study was to evaluate the individualized and standardized quality of life (QL) and psychological distress of patients participating in a Phase I trial of the novel therapeutic reovirus (Reolysin). Methods 16 patients with incurable metastatic cancer were interviewed prior to being accepted into the phase I trial with a semi-structured expectations interview, the Schedule for the Evaluation of Individual Quality of Life – Direct Weighting (SEIQoL-DW), the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), the Brief Symptom Inventory (BSI), the Beck Depression Inventory (BDI), and the Spiritual Health Inventory (SHI). Results Patients were able to complete all measures. They felt hopeful and excited about the trial, with about two thirds hoping for disease regression and one third hoping for a cure. The most commonly spontaneously nominated areas of QL were family relationships, activities and friends, and the overall SEIQoL mean index score was 69. Health was nominated by only 38% of the sample. Scores on the SEIQoL were correlated with global QL on the EORTC QLQ C-30. Scores on the BDI and BSI were lower than reported for similar populations, and on the SHI scores were similar to other samples. Global QL on the EORTC QLQ C-30 and depression scores were associated with time to death in the nine patients who had died at the time of writing. Conclusions Individualized QL is easy to assess in seriously ill cancer patients, provides useful information relative to each individual, and is related to standard QL measures. Repeated assessment of individualized QL of patients in Phase I trials would be a useful addition to the research.	Background As health care professionals begin to understand the importance of quality of life (QL) and emotional and social well-being in the treatment and progression of cancer, it has become standard practice, and in fact has been described as a bioethical imperative, to include QL assessment in all oncology clinical trials [ 1 - 7 ]. This is particularly the case in Phase I trials for novel therapeutics, where in many cases the patients admitted have exhausted other treatment options and likely face death within months under best supportive care [ 8 ]. A Phase I trial is the first test of a new therapeutic in humans and aims to establish a maximum tolerated dose, to evaluate dose limiting toxicity, and to examine the drug's pharmacology. There is generally little chance of clinical disease response and relatively high potential risk of toxicity in this type of trial. For patients in this situation, quality of life remains perhaps the most important variable to consider in the evaluation of the new treatment [ 9 , 10 ]. We report here on the initial QL of patients enrolled in the Reolysin Phase I trial, the first clinical usage of the reovirus in humans with cancer. The reovirus as a possible treatment for cancer attracted a great deal of media attention when the journal Science, in 1998, published very encouraging results showing tumor regression in animal models [ 11 ]. Further work has established the reovirus as a potential therapeutic in the treatment of brain, colorectal, ovarian and breast cancer cell lines [ 12 , 13 ]. A small sample of patients with different types of primary cancers that had exhausted other treatment options, all of whom had subcutaneous tumors that were easily palpable and injectable with Reolysin, were enrolled in the current trial. Due to the nature of the population under study, it seemed especially important to use instrumentation that was flexible enough to allow these very ill patients to identify what was important to each of them as individuals, as well as to collect data from standardized instruments that would allow direct comparisons with other patient populations. Thus, a battery of tests to measure both individualized and standardized QL, distress levels, and spirituality was selected. Important aspects of QL were measured, including physical, psychological, emotional, social, and spiritual functioning, with emphasis on mood states and psychopathology. Expectations and hopes regarding participation in the trial were also elicited during a semi-structured interview. The specific instruments used included an interview-based subjective measure of QL, the Schedule for the Evaluation of Individual Quality of Life – Direct Weighting (SEIQoL – DW)[ 14 ]. The SEIQoL-DW is a relatively new measure and unique in QL measurement in that it elicits from patients their own self-generated list of the "five most important domains of QL" for them, rather than asking about pre-set areas. After patients identify their most important domains, they rate how well each domain is for them currently, and how important overall in their lives each domain is. This instrument and its predecessor, the SEIQoL [ 15 ], have been used in oncology in several published studies [ 16 - 18 ]. The SEIQoL differs from the SEIQoL-DW in that a procedure called judgement analysis is used in the SEIQoL to arrive at the relative importance of each of the domains for each patient. This process is much more time consuming, abstract and complicated than the direct weighting procedure used in the SEIQoL-DW. While the SEIQoL procedure has been deemed overly burdensome for some patients with both early and advanced cancer [ 16 , 17 ], primarily due to the judgement analysis portion of the procedure, the SEIQoL-DW has been found to be acceptable and practical to use in a validation study of patients on Phase I clinical trials [ 18 ]. Another study of the SEIQoL-DW found that patients with advanced cancer were good judges of their own QL, and able to complete the interview with little difficulty [ 17 ]. In past studies, the most important areas of QL that patients on Phase I clinical trials identified were equally health and family [ 18 ]. However, in a sample of advanced cancer patients family concerns were consistently identified as more important than health issues [ 17 ]. The patient population in the Campbell & White study [ 18 ] was not defined except by their participation in Phase I trials, whereas the Waldron & O'Boyle sample [ 17 ] all had advanced incurable cancer. It may be the case that as illness severity progresses, concerns are directed toward domains that offer more hope. Other studies that have used the SEIQoL found family, health and finances to be the top three areas in men with early stage prostate cancer [ 16 ], and similarly family, health, marriage and leisure/hobbies were most important to a group of cardiac patients [ 19 ]. Thus, although there does seem to be some consistency in the areas nominated by diverse patient groups, differences in the relative importance of the areas are commonly found. The other QL questionnaire used in this study is the very widely used European Organization of Research and Treatment of Cancer (EORTC) Quality of life Questionnaire (QLQ C-30), a 30 item standardized self-administered questionnaire that taps into important domains of QL, including physical, psychological, emotional and social functioning. This was included to allow comparisons with a well-known and validated standardized quality of life questionnaire with set domains and subscale scores. Another study at our Centre directly compared the SEIQoL to the EORTC QLQ C-30 in a sample of early stage prostate cancer patients [ 16 ]. The authors compared the domains nominated by the patients to those included on the EORTC QLQ C-30, and concluded that although there was substantial overlap on some items, many items identified by patients were not included on the standardized questionnaire. The area of spirituality was also of interest in this population of very ill people, as issues of death and dying are often accompanied by questioning in the realm of spirituality. The Spiritual Health Inventory [ 20 ] was used for this purpose, as it measures self-acceptance, relationships with others, and hope, which may be an important factor as patients participate in the trial. In terms of depression, anxiety and other psychiatric symptoms that are frequent in cancer patients, the Brief Symptom Inventory (BSI)[ 21 ] was used to broadly assess many areas of psychopathology, and the Beck Depression Inventory (BDI)[ 22 ] to focus in more detail on depressive symptomatology. Both of these instruments are widely used in the oncology literature and thus there are many published reports with values that can be used for comparison purposes. Previous work with patients in Phase I trials has found that patients' expectations going into trials are generally more optimistic than oncologists'. Patients with incurable malignancy in a Phase I trial estimated a greater potential for benefit from the experimental therapy than did oncologists [ 10 ]. They also estimated that the experimental therapy had less potential for toxicity than the standard treatment. The oncologists estimated the potential for toxicity on both treatments to be about equal, and lower, than did patients. Patients in Phase I trials for new drugs, when asked why they had agreed to try the new treatment, cited the potential for helping their disease to be the number one reason for participation [ 9 ]. Indeed, despite cautious words from the medical staff, it is not surprising that patients with a disease resistant to all other treatments might hope for at least a slowing of their disease progression with an experimental treatment. Thus, the preliminary QL of such patients, as measured in the current study, may be inflated by these hopes. Other studies looking at the effects of participation in Phase I trials on QL have found either no detrimental effects of participation [ 8 ], or enhancement of QL over the course of the trial compared to a control group that received supportive care [ 23 ]. The purpose of the current study was to investigate individualized QL in a group of patients with metastatic incurable cancer participating in a Phase I trial of a highly media lauded new therapeutic, and investigate their expectations regarding the trial. Areas of importance and SEIQoL Index scores for these patients will be compared with those of patients in other studies, and compared to their own scores on the standardized QL and psychological measures assessed. Relationships between the different measures will also be explored. Methods Subjects Patients were recruited as specified in the protocol: "A Phase I Clinical Trial to Evaluate Dose Limiting Toxicity and Maximum Tolerated Dose of Intralesional Administration of REOLYSIN for the Treatment of Histologically Confirmed Malignancies". All patients had histologically confirmed evaluable palpable tumors of any histological type that had failed to improve on existing standard therapy. The injectable lesion was required to be between 1 and 10 cm 2 , and accessible and measurable for delivery of an intralesional injection. Patients were required to have a life expectancy of at least 12 weeks and a ECOG performance status of ≤ 3 and must not have received active cancer treatment for least 21 days prior to entrance onto the trial. Adequate organ reserve in terms of bone marrow, hepatic, renal and cardiac functions was required. Patients on immunosuppressive therapy or alternative/complimentary/unproven systemic or local therapies were ineligible. Procedures After patients had been referred to the above mentioned trial, but prior to being definitively accepted (pending complete assessment of inclusion/exclusion criteria), patients met with a psychologist (LC) for the assessment protocol. At that time they were interviewed concerning their expectations about their health, both without any further conventional treatment and with the potential experimental treatment. They then completed the interview-based individualized QL interview, followed by the quantitative questionnaires as detailed below. All 16 patients followed the same procedures. Instruments Demographics Form Demographic information including age, education, marital status, occupation and current employment status was obtained on a form created for this study. Medical history including type of illness, dates of first diagnosis and subsequent relapses and site of metastases were collected, and later verified from patient charts. Expectations Interview Patients were asked three questions in a semi-structured interview: How do you feel about potentially being a part of this trial? How do you see your disease progressing without any further conventional treatment? Once on the trial, how do you see your disease progressing? Short answers to these questions were recorded verbatim at the time of the interview. Quality of Life Schedule for the Evaluation of Individual Quality of Life – Direct Weighting (SEIQoL – DW) [ 14 ] This schedule takes the form of a semi-structured interview, in which the investigator first describes quality of life as an individually defined construct, then elicits from the patient their own five most important domains of QL, rather than asking them about pre-set areas. Patients are asked to think of what areas of life determine their own happiness, or quality of life. After patients identify their most important domains ("cues"), they rate the quality of each domain currently in their lives by drawing a bar graph on a 100 mm scale from worst possible to best possible. This is called the "level" of the cue. Finally, they rate how important each domain is overall in their lives using a direct weighting disk. This disk consists of five overlapping different colored laminated disks that can be rotated around a central point to form a pie chart. Each piece represents one of the five chosen domains. The patient manipulates the disk until the proportion of each piece making up the pie represents the relative importance of that domain in their lives ("weight"). The weight value of each cue is calculated by determining the percentage of the overall pie that each piece covers by reading off a larger backing disk that is labeled with a 0–100 scale around the pie. Then by multiplying the level of each domain by its weight and summing the product for all five items, a summary score representing overall subjective quality of life can be calculated. This is called the SEIQoL Index Score. More detailed descriptions of the procedures are available in other publications [ 14 , 18 , 24 ]. The European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 Quality of Life Questionnaire [ 25 ] This 30-item questionnaire includes five functional domains of quality of life: physical function (5 items), emotional function (4 items), cognitive function (2 items), social function (2 items) and role function (2 items). There are also several symptom scales: fatigue (3 items), pain (2 items), nausea and vomiting (2 items), and one item each for dyspnea, sleep disturbance, appetite, constipation, diarrhea and financial difficulties. Finally, two items assess global quality of life. The questionnaire shows high internal consistency, and overall reliability and validity of the survey has been demonstrated in international clinical trials with cancer patients of heterogeneous diagnoses including lung cancer [ 26 ]. Distress Beck Depression Inventory (BDI) [ 22 ] This 21-item questionnaire gives a global score on depressive symptoms, and norms are available for many different populations, including cancer patients. Higher scores represent more depressive symptoms. Brief Symptom Inventory (BSI) [ 21 ] A general mental health measure of 58 questions which provides scores on nine dimensions of psychopathology or psychological distress: somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism. Three global scores can be calculated: the Global Severity Index (GSI), the Positive Symptom Total (PST) and the Positive Symptom Distress Index (PSDI). The GSI was used as the global score in this study. Spirituality Spiritual Health Inventory (SHI) [ 20 ] This instruments defines spiritual health as the capacity to transcend oneself and meet three basic needs; the need for self-acceptance, the need for relationships with others and/or a supreme being, and the need for hope. These three factors accounted for 71% of the variance in validity studies. A single total score is calculated by summing all items. The possible range of scores is 31–155, with higher scores indicating higher levels of spiritual health. The 31-item questionnaire takes very little time to complete. Results Subjects Demographic characteristics and disease variables of participants are presented in Table 1 . Patient #10 was registered in the trial but too ill to complete any of the questionnaires or the interview. Therefore no data for this patient is included in the study. The remaining 16 patients who provided data all had metastatic disease that was considered incurable, 6 men and 10 women. The largest patient group consisted of five women who had metastatic breast cancer, followed by three patients with malignant melanoma. Patients ranged in age from 32 to almost 76 years old, with a median age of 53 years. They had been diagnosed with cancer for a median of 3.3 years (range 0.5–26.9 years) before entrance to the study. They had on average 16 years of education (range 12–25), and therefore represented a highly educated group. At the time of analysis, nine of the patients had died, at a median of 136 days from the time of the interview (range 21–664 days). The remaining seven were still alive, a median of 242 days from the time of the interview (range 207–709 days). Table 1 Demographic and Disease Characteristics Patient Number Gender Age (Years) Cancer diagnosis Years since first diagnosis Location of metastases Days from interview to death 1 Female 45 Mucoepidermoid carcinoma (head and neck) 14.7 Lymph nodes 28 2 Male 50 Squamous carcinoma (head and neck) 0.7 Lymph nodes Alive-709 3 Female 54 Anaplastic thyroid carconoma 10.8 Lungs/liver/bone 21 4 Female 47 Malignant Melanoma 12.7 Eye/breast/liver/chest wall/lung 664 5 Female 47 Metastatic Breast carcinoma 6.6 Chest wall/bone 241 6 Female 60 Metastatic Breast carcinoma 2.7 Chest wall /lungs /retroperitoneum Alive-529 7 Male 32 Soft tissue sarcoma 0.5 Right lower extremity 96 8 Male 56 Neuroendocrine islet cell tumor 2.4 Liver/face/neck/ Scalp 44 9 Female 56 Metastatic Breast carcinoma 2.7 Chest wall/ left supraclavicular skin/ intrabdomen 142 11 Male 42 Malignant melanoma 6.4 Liver/lung/spleen Alive-368 12 Male 64 Klatskin's tumor 1.4 Abdomen 171 13 Female 76 Metastatic Breast carcinoma 26.9 Lung/bone/liver 136 14 Female 55 Malignant melanoma 1.8 Axilla /lung /liver Alive-242 15 Female 48 Metastatic breast carcinoma 2.8 Neck /Chest Wall /Brain Alive-242 16 Female 46 Soft tissue sarcoma 3.9 Lung/skin/breast/ retroperitoneal Alive-227 17 Male 70 Squamous carcinoma (head and neck) 9.7 Head/neck Alive-207 Expectations Interview Interviews were conducted with all of the 16 patients. To the question "How do you see your disease progressing without further conventional treatment?", nine of the patients indicated they felt it would get worse and they would eventually die of their disease. This was stated in different ways: Nothing else left...getting gradually worse...terminal – could be months, could be years...wouldn't go very well. The other seven patients offered more hopeful or neutral prognoses: don't think about it – stay positive...still hopeful and optimistic...other things available still...would still take chemo, hope it would work...wouldn't ever give up on hope...faith...not sure, unknown. When asked how they felt about being in the trial, most patients indicated feeling excited, fortunate, grateful and hopeful. One indicated that they felt scared as well as hopeful, not knowing what to expect, and one said they felt like a guinea pig. To the question "Once on the trial, how do you see your disease progressing?", ten of the patients mentioned hoping for the tumor to shrink, for a remission, or for some extension of life. Five patients mentioned hoping for a cure, to be cancer free. One patient just mentioned hoping to help others, and four others said that although they were hoping for personal benefit, if it didn't help them it might help others in the future. In general, patients were hopeful yet philosophical about the trial. The 54-year old woman with melanoma captured these sentiments with her comments: It feels hopeful. Maybe it won't help me – I won't be disappointed. It might help others down the road. It's on the frontier – exciting. If it works it's a bonus. I don't totally expect anything. It may extend life. Just day by day carry on. EORTC QLQ C-30 Quality of life scores on the EORTC QLQ C-30 are presented in Table 2 . All 16 patients completed the questionnaire. On the functional scales, where higher scores indicated better functioning, scores ranged from a low of 55 on social functioning, to a high of 76 for cognitive functioning, on a scale of 1–100. The overall global QL rating was 57. On the symptom scales, where higher scores indicate more symptomatology, scores ranged from a low of 14 (nausea and diarrhea) to a high of 42 on pain and fatigue. The next most prevalent symptoms were sleep problems and appetite loss. Table 2 EORTC Scores Functional Scales (Higher scores = higher function) Mean SD Physical Function 63.75 32.02 Role Function 62.50 38.73 Emotional Function 75.52 18.12 Cognitive Function 76.04 24.32 Social Function 55.21 32.04 Global Quality of Life 57.22 21.79 Symptom Scales (Higher scores = more symptomatic) Fatigue 41.67 25.82 Nausea 14.58 14.75 Pain 41.67 25.82 Dyspnea 22.92 26.44 Sleep 35.42 30.96 Appetite 33.33 32.20 Constipation 25.00 28.55 Diarrhea 14.58 17.78 Finances 29.17 26.87 Correlations between subscales are presented in Table 6 (additional file 1 ). The subscales of role function, cognitive function, global QL, fatigue and appetite loss were significantly related to seven other subscales each. Social functioning was associated with scores on six other subscales. Finances, diarrhea, and sleep were unassociated with any other subscales, and pain was associated only with dyspnea. All significant correlations were in the expected directions. Table 4 SEIQoL Items Patient Number Item 1 Item 2 Item 3 Item 4 Item 5 1 Children Spouse Religion Physical Fitness Finances 2 Family Exercise Nature Computer Work 3 Spouse Children Friends Activities Father 4 Family Friends Dog Gardening Fun 5 Pain Control Finances Health Energy Activities 6 Travel Health Family and Friends Spouse Activities 7 Children Family Mobility Hope Work 8 Work Family Finances Health Activities 9 Family Grandchildren Friends Travel with Spouse Finances 11 Family Friends Active at Home Work Finances 12 Spouse Friends Family Belief Art 13 Activity Grandchildren Sewing Gardening Travel 14 Family Faith Positivity Activities Friends 15 Work Recreation Mobility Family Friends 16 Spouse Children Family Faith Exercise 17 Family Spouse Work Family tree Religion Mean Level 70.9 68.4 64.6 56.9 62.5 SD 31.3 26.0 32.0 32.1 27.1 Mean Weight 0.25 0.23 0.19 0.20 0.16 SD 0.08 0.08 0.06 0.08 0.09 Psychological Scores Scores on the BDI, BSI and SHI are presented in Table 3 . Fifteen of the 16 patients completed the questionnaires. Scores on the BDI averaged 11, in the moderate range of depressive symptomatology. On the BSI, scores ranged from a low of 0.17 on paranoid ideation, to a high of 0.91 on the obsessive-compulsive subscale. The overall global severity index was 0.55. These scores are higher than those of the general population, but quite a bit lower than those of psychiatric outpatients [ 21 ]. Table 3 Psychological Scores Mean SD BSI Somatization 0.74 0.56 BSI Obsessive Compulsive 0.91 0.63 BSI Interpersonal Sensitivity 0.38 0.36 BSI Depression 0.76 0.62 BSI Anxiety 0.50 0.40 BSI Hostility 0.21 0.27 BSI Paranoid Ideation 0.17 0.17 BSI Psychoticism 0.16 0.17 BSI Global Severity Index 0.55 0.36 Beck Depression Inventory Total Score 11.40 9.46 Spiritual Health Inventory Total Score 118.33 16.02 Patients scored an average of 118 on the SHI. The most highly endorsed items on the scale of 1–5, where 1 corresponds with the heading "not at all", and 5 with "very much", were the following: "I believe other people accept me even with my faults" (4.5); "I actively participate in decisions concerning my health care" (4.5); "I believe my nurses and doctors care about me" (4.3); "My life has a purpose" (4.2); "I feel accepted and forgiven despite some past actions" (4.0). The lowest scores were on the following items: "I wonder if God is angry with me" (1.1); "I feel angry with others" (1.3); "I feel a need to be forgiven for some of my thoughts and feelings" (1.7); "I worry about life after death" (1.9); "I feel angry with myself" (1.9); and "I feel out of touch with my own feelings and with others" (1.9). SEIQoL All 16 patients completed the SEIQoL. The average time taken was 13.5 minutes, range 5–30 minutes. Areas identified by patients as the most important in determining their overall quality of life are presented in Table 4 by patient, along with average levels and weights associated with each cue by order of identification. As can bee seen, most patients identified family, children, or spouse as the single most important factor in determining their current quality of life. The average level of each of the five cues ranged from 57–71 on a scale of 0–100, where 100 was the best possible state for that cue. The weights assigned to the cues varied from 16% to 25%, a fairly narrow range, with those cues identified earlier in the process generally being assigned higher importance. The overall index scores, which take into account both the level of the cue and its weight, were an average of 69, SD 20.5 and ranged from 27–100. The frequency of nomination of different cues as any of the five domains is presented in Table 5 . All but one patient mentioned some family relationship as one of the five domains, while some patients nominated several different specific family relationships. This was followed by the general ability to participate in chosen activities (e.g. exercise, recreation, travel, gardening, sewing). Seventy-five percent of the patients nominated some type of activity in their top five. The next most frequent category was friends, endorsed by 44% of the patients. This was followed equally by health (mobility, fitness, energy), faith (religion, belief, hope), and work, with 38% of the patients nominating each category. Finances were nominated by 31% of the patients, followed by several items that were mentioned by only one person each and warranted separate categories. Table 5 Frequency of Cue Nomination Cue N (out of 16) % Family (Children, Spouse, Grandchildren, Parent, Family Tree) 15 93.8 Activities (exercise, gardening, sewing, recreation, travel) 12 75 Friends 7 43.8 Health (mobility, physical fitness, energy) 6 37.5 Faith (religion, belief, hope) 6 37.5 Work 6 37.5 Finances 5 31.3 Pet 1 6.3 Computer 1 6.3 Pain Control 1 6.3 Art 1 6.3 Fun 1 6.3 Positivity 1 6.3 Nature 1 6.3 The internal validity of each of the cues was assessed by performing regressions of the combination of each cue level and its weight onto the total index scores. The resulting R 2 values ranged from .19–.76, median .47, mean .50. The highest R 2 value was for the first cue generated, and the lowest value was associated with the fourth cue. This is much lower than in previous reports [ 16 , 17 ] and may constitute reason to pause before attributing high levels of credence to the validity of all of the cues in influencing overall QL. Two examples of cues, cue levels and cue weights are illustrated in Figures 1 and 2 . Figure 1 illustrates the responses of patient #1, a 45 year old woman with mucoepidermoid cancer of her head and neck region who died four weeks following the interview. The most important areas to her were health, followed by children, spouse, religion and finally finances. This profile is unusual for this group in that most patients, if they nominated health as a cue at all, did so later in the process. She indicated that the areas that were going the best were finances and religion, followed by children, spouse and health. This combination of things not rated as going very well in some important areas resulted in an index score of 59 on the SEIQoL This is quite a bit higher than her global QL score on the EORTC of just 25. Another example is patient #2 (figure 2 ), a 50 year-old male with head and neck cancer who, as of this writing, has been alive for 709 days following the interview. For him, things were going well in the areas most important to him; family, work and computers. This resulted in an index score of 81, consistent with his global QL score on the EORTC of 75. These examples illustrate that the SEIQoL scores are related to overall QL scores, and suggest that they may be related to health status as well. Figure 1 Patient #1: Cues, Levels and Weights Figure 2 Patient #2: Cues, Levels and Weights Correlations between measures Correlations between the SEIQoL index and scores on the other measures are presented in Table 6 (see additional file 1 – Carlson Table 6.doc). The index score was significantly positively correlated with the global QL score (r = .53, p < .05), and negatively associated with the symptoms of nausea (r = -.58, p < .05), pain (r = -.53, p < .05) and appetite loss (r = -.59, p < .05) on the EORTC QLQ C-30. Scores on the BDI were positively associated with appetite loss (r = 0.56, p < .05) and fatigue (r = 0.56, p < .05), not surprising since these are both symptoms of depression assessed by the BDI. Depression scores were also negatively related to social functioning (r = -.79, p < .01) and global quality of life (r = -.69, p < .01), indicating that people who endorsed more depressive symptoms also tended to report lower social functioning and lower overall QL. Higher scores on the Global Severity Index of the BSI were associated with worse emotional (r = -.55, p < .05), cognitive (r = -.58, p < .05) and social (r = -.69, p < .01) functioning, as well as worse global QL (r = -.70, p < .01) and more sleep disturbance on the EORTC. Higher scores on the spiritual health inventory were associated with lower scores on the global severity index of the GSI (r = -.54, p < .05) and less nausea (r = -.63, p < .05). Significant correlations between days to death and psychological scores were found on two instruments in the nine patients who had passed away at the time of writing. The BDI total score was negatively correlated (r = -.75, p < .05), and the EORTC global QL score was positively correlated (r = .77, p < .05) with time to death. This indicates an association between higher levels of depression and lower global QL at the time of the interview, and fewer days to death. Discussion This study is the first to use the SEIQoL-DW instrument to assess individualized QL in a population of patients with advanced cancer participating in a Phase I clinical trial. Of note is that the instrument was easy to use in this population and acceptable even to those patients who were quite ill. Replication of the wide range of individual differences in the cues chosen and the weights associated with each cue was seen in this group. The areas of QL that were nominated by patients as the most important factors in the determination of their overall QL were primarily family relationships, the ability to participate in pleasurable activities, and friendships. Only 38% of this sample mentioned health or health-related domains such as mobility, fitness and energy as one of the five cues. This is in contrast to other samples of cancer patients where over 70% of patients nominated health as an important domain. For example, health was nominated by 73% of cancer patients in phase I trials (not necessarily advanced cancer) [ 18 ], 87% of men with early stage prostate cancer [ 16 ], and 70% of patients with advanced incurable cancer (these patients were not on trials) [ 17 ]. The commonality between these studies is that family was consistently nominated as the most frequent domain. In terms of the index scores, our average of 69 was higher than that of the group of advance incurable cancer patients (mean = 58) and the patients participating in Phase I trials (mean = 61). It was comparable to the men with early stage prostate cancer (mean = 71), but the relatively small range of mean scores among these studies is notable. Construct validity is supported in that those patients whom one might expect to have higher QL (i.e. less ill patients), indeed reported higher QL. That the scores in the current sample were more comparable to the early stage prostate cancer patients than the incurable cancer patients may speak to the hope patients were feeling regarding the potential of the reovirus treatment. In terms of the index scores for other illness populations, patients prior to hip arthroplasty scored 59, after the surgery scores increased to 69 [ 27 ], on par with the cancer patients in this study (mean 69). Another study of hip replacement patients found scores of 62 prior to surgery, with improvements to 71 following surgery [ 28 ], a similar improvement pre- to post-surgery. Severely disabled multiple sclerosis patients scored 61 [ 29 ], patients with ALS had a higher mean index of 76 [ 30 ], and cardiac patients scored a high index of 82 after myocardial infarction or coronary artery bypass graft surgery and prior to beginning cardiac rehab [ 31 ];. Interestingly, only 24% of the ALS patients nominated health (disease progression) as a cue. Thus, although the areas of importance varied by individual in all these studies, the resultant index scores seem to demonstrate some consistency across similar populations. Another indication of the construct validity of the SEIQoL-DW is its high correlation to global QL scores on the EORTC QLQ C-30. This speaks to the validity of the self-generated items, as the sum of the products of their importance and current status was associated with the overall global assessment of QL on standardized domains. Predictably, our patients had a global QL on the EORTC of 57, much lower than the 77 reported in a large normative community sample [ 32 ]. Scores on all five functional scales and symptom scores were all also worse in this population, not surprising considering the extent of their disease status. However, they did have the same global QL scores compared to a large sample of patients with advanced malignancy from 12 institutions in 10 countries (both 57), but scored higher on most of the other functional scales than this group (Physical function: 64 vs. 60; Role function: 63 vs. 50; Emotional function: 76 vs. 50; Cognitive function: 76 vs. 63; Social Function: 55 vs. 50) [ 33 ]. The greatest differences in favor of the patients in this trial were seen on emotional, cognitive and role function. Interestingly, lower global QL scores on the EORTC and higher depression scores on the BDI were associated with a shorter time to death in those patients who had already passed away, an association that has been reported in other studies [ 33 - 35 ]. In fact, in an international sample of 411 patients with advanced malignancy, similar to the current group, the single-item global QL scale remained independently prognostic of death in a proportional hazards model stratified on diagnostic category, after allowing for performance status and age, and, among solid tumor patients, metastatic site [ 33 ]. Patients who were in terminal care from a large sample from 12 oncology outpatients departments around the United States scored an average BSI Global severity index score of .93. Those who were under symptom control scored .80, whereas lower scores were seen for patients in active therapy (.59), adjuvant therapy (.60) or no current therapy (.65)[ 36 ]. Our sample mean of .55 is quite low in comparison and most comparable to patients in active therapy. An even larger sample of over 4000 patients of all disease sites and stages of illness from Johns Hopkins Oncology Centre reported an average global severity index very similar to our patients, at .54 [37]. This seems to indicate that our sample is reporting less psychopathology than would be expected of patients in similar disease states, but comparable levels to cancer patients in general. They also scored an average of 11 on the BDI, which indicates mild depressive symptomatology. The spirituality scores of this group average 118. This is very similar to a group of lung cancer patients who had a mean of 120 [ 20 ]. Analysis of the individual items showed that these patients endorsed feeling well supported by the medical team and quite peaceful and accepting of themselves, and well accepted by others. They reported not feeling angry at themselves or others, or worried about life after death. The spirituality scores were correlated with the global severity index of the BSI, indicating that those who felt more spiritually at ease also endorsed fewer symptoms of psychopathology. In summary, these patients in a Phase I trial of a promising novel therapeutic were easily able to complete the SEIQoL-DW interview as well as a battery of other psychological questionnaires. They reported feeling excited and hopeful about the trial, with about two-thirds hoping for disease regression, and another third optimistically hoping for a cure. However, most acknowledged that although they hoped for the best they were realistic in their expectations. The individuality of QL as defined by each person was reinforced in this group, as many different cues were nominated as important and variable weights were assigned to the same cues. Consistent with reports from other seriously ill groups, health status received less focus than other aspects of life, primarily family relationships and activities. Overall QL on standardized measures and psychological status was generally better than other seriously ill patient groups, but comparable to cancer patients in general. QL and depression scores were related to time until death in those patients who had passed away. Authors' contributions LC wrote the research proposal and ethics applications, conducted the interviews with the patients, designed the database, conducted the statistical analysis, and wrote the first draft of the paper. BB is the department head for Psychosocial Resources, and in conjunction with LC conceived of and designed the study. He also made the linkages with medical oncology to facilitate the study. DM is the oncologist and principal investigator of the Phase I Reovirus trial, and recruited all the patients. All authors reviewed and edited the final manuscript. Supplementary Material Additional File 1 Table 6: Correlations between scores on the SEIQoL, BDI, BSI, SHI and EORTC QLQ C-30 Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548292.xml
545944	A remission spectroscopy system for in vivo monitoring of hemoglobin oxygen saturation in murine hepatic sinusoids, in early systemic inflammation	Background During the early stages of systemic inflammation, the liver integrity is compromised by microcirculatory disturbances and subsequent hepatocellular injury. Little is known about the relationship between the hemoglobin oxygen saturation (HbsO 2 ) in sinusoids and the hepatocellular mitochondrial redox state, in early systemic inflammation. In a murine model of early systemic inflammation, we have explored the association between the sinusoidal HbsO 2 detected with a remission spectroscopy system and 1.) the NAD(P)H autofluorescence (an indicator of the intracellular mitochondrial redox state) and 2.) the markers of hepatocellular injury. Results Animals submitted to 1 hour bilateral hindlimb ischemia (I) and 3 hours of reperfusion (R) (3.0 h I/R) exhibited lower HbsO 2 values when compared with sham. Six hours I/R (1 hour bilateral hindlimb ischemia and 6 hours of reperfusion) and the continuous infusion of endothelin-1 (ET-1) further aggravated the hypoxia in HbsO 2 . The detected NAD(P)H autofluorescence correlated with the detected HbsO 2 values and showed the same developing. Three hours I/R resulted in elevated NAD(P)H autofluorescence compared with sham animals. Animals after 6.0 h I/R and continuous infusion of ET-1 revealed higher NAD(P)H autofluorescence compared with 3.0 h I/R animals. Overall the analysed HbsO 2 values correlated with all markers of hepatocellular injury. Conclusion During the early stages of systemic inflammation, there is a significant decrease in hepatic sinusoidal HbsO 2 . In parallel, we detected an increasing NAD(P)H autofluorescence representing an intracellular inadequate oxygen supply. Both changes are accompanied by increasing markers of liver cell injury. Therefore, remission spectroscopy in combination with NAD(P)H autofluorescence provides information on the oxygen distribution, the metabolic state and the mitochondrial redox potential, within the mouse liver.	Background Hepatic microcirculatory failure is a major prerequisite for the development of hepatocellular dysfunction in a number of conditions like trauma/hemorrhage, liver transplantation and systemic inflammation. In various inflammatory states, the degree of lethal hepatocyte necrosis can be predicted from the extent of hepatic microcirculatory failure [ 1 ], possibly via alterations in the mitochondrial redox state of the liver [ 2 , 3 ]. Previously, our group has shown that the development of systemic inflammation was associated with a disturbance of the hepatic microcirculation, and a subsequent increase in hepatocellular damage [ 4 , 5 ]. The causal mechanisms are not completely understood, but accumulating evidence suggests a dysregulation of stress-inducible vasoactive mediators like endothelins, nitric oxide synthase or heme oxygenase [ 6 ]. Moreover, modifications in effector cell function may also alter the response to those mediators [ 7 ]. Hepatic microcirculatory failures during various stresses are typically characterized by alterations in the distribution of perfusion, thereby resulting in a disparity between oxygen supply and demand. This impaired nutritive blood flow, together with reduced oxygen availability, decreases cellular high-energy phosphates leading to an early hepatocellular injury and dysfunction. Studies of tissue oxygenation focusing on the relationship between microcirculatory disturbances and oxygen transport dynamics may help to better elucidate the pathophysiological mechanisms involved. Several methods have been reported in the past couple of years directly quantifying the oxygen distribution in tissues; however, their applicability in tissues, especially in small rodents like mice, is limited due to technical reasons. For instance, microelectrodes measure tissue pO 2 at specific points; but the technique is invasive and consumes oxygen. Electron paramagnetic resonance oximetry techniques or nuclear MRI approaches allow the detection of changes in tissue pO 2 ; however, their resolution is too low [ 8 ]. A fluorescent membrane, developed by Itoh et al . [ 9 ] on the basis of an oxygen-quenched fluorescent dye allows the in vivo visualization of the tissue pO 2 . This technique allows the visualization of oxygen distribution on tissue surfaces, but this method comprised some technical limitations. The oxygen-sensitive membrane has to be used under gastight and watertight conditions during microscopy and the fluorescent membrane shows a photobleaching effect. Paxian et al . [ 10 ] recently demonstrated that the intravenous infusion of a special oxygen quenching dye allowed the visualization of the oxygen distribution on the liver surface using intravital videomicroscopy. The fluorescence of the dye was directly dependent on the tissue pO 2 . A disadvantage of this method, especially when used in small rodents like mice, is that it requires changing the continuous intravenous infusion rates of the dye to provide stable plasma concentrations. With mice (increasingly used as laboratory animals) there is a growing need for a method able to reliably detect tissue oxygenation or, at least, hemoglobin oxygen saturation (HbsO 2 ) in capillaries of small animals. The aim of the present study was to investigate whether the utility of a new and simple remission spectroscopy system allows reliable in vivo detection of liver sinusoidal HbsO 2 . In a mouse model of early systemic inflammation, we examined whether the detected changes in hepatic HbsO 2 correlated with the established method of NAD(P)H autofluorescence and hepatocellular injury. Results Macrohemodynamics Consistent with previous reports [ 4 , 11 ], mean arterial pressure (MAP) was significantly lower in animals after ischemia (I) and reperfusion (R) (3.0 h I/R and 6.0 h I/R) compared to sham animals, but remained normotensive (> 80 mmHg) throughout the study. MAP did not differ between the I/R groups. Central venous pressure was not different (data not shown). Blood gas analysis The measurement of arterial blood gases carried out after the microscopy procedure showed normal oxygenation, a moderate acidosis, and adequate pCO 2 for all groups (Table 1 ). Table 1 Arterial blood gases. pO 2 (mmHg) pH pCO 2 (mmHg) Sham 128 (46) 7.29 (0.13) 35.8 (11.3) 3.0 h I/R 123 (49) 7.27 (0.15) 36.7 (10.8) 6.0 h I/R 116 (38) 7.26 (0.17) 36.8 (12.4) 6.0 h I/R+endothelin-1 119 (46) 7.26 (0.13) 36.9 (12.9) Data expressed as Mean (SD); n = 7 for each group Hepatic sinusoidal hemoglobin oxygen saturation (HbsO 2 ) Hepatic sinusoidal HbsO 2 of the different groups are shown in Figure 1 . Animals treated with 3.0 h I/R have significant lower hepatic HbsO 2 values (56.2 (13.1)) when compared with sham (68.4 (14.1); p < 0.01). No statistically significant differences were observed between 3.0 h I/R and 6.0 h I/R treated animals. However, an obvious shift of hepatic HbsO 2 towards a lower oxygenation was observed when compared with 3.0 h I/R treated animals. Animals treated with 6.0 h I/R and a continuous infusion of endothelin-1 (ET-1) showed significant reduced HbsO 2 values (44.8 (14.7)) when compared with 3.0 h I/R treated animals (56.2 (13.2); p < 0.006). More than half of the measured data from these animals revealed HbsO 2 values lower than 50%. There was no apparent difference in the local tissue hemoglobin (Hb) content detected (data not shown). Figure 1 Sinusoidal haemoglobin oxygen saturation (HbsO 2 ) . At least 35 different observation points of the left liver lobe per animal were examined. The frequency distributions of all examined HbsO 2 values per group are shown. Hepatic tissue redox status Animals subjected to 3.0 h I/R revealed significantly higher NAD(P)H autofluorescence (141.6 (12.8)); therefore, a significant decline in hepatic tissue oxygenation was observed when compared with sham (100.0 (6.7)) (Figure 2 ). Three hours I/R treated animals failed to show a significant difference in NAD(P)H autofluorescence when compared with the 6.0 h I/R treated animals. Animals treated with 6.0 h I/R and a continuous infusion of ET-1 demonstrated significantly higher NAD(P)H autofluorescence (161.1 (13.8)) when compared to the 3.0 h I/R treated animals (141.6 (12.8)). There was a highly significant correlation found between NAD(P)H autofluorescence and hepatic HbsO 2 detected in the same animal ( p < 0.005; r 2 = 0.94), as depicted in Figure 3 . Figure 2 Hepatic tissue redox status . NAD(P)H autofluorescence, as a marker of the intracellular mitochondrial redox state, was examined using fluorescence intravital videomicroscopy with a filter set consisting of a 365 nm excitation and a 397 nm emission bandpass filter. The complete left liver lobe was systematically scanned and at least 15 different fields of view have been analysed. Fluorescence was densitometrically assessed and expressed as average intensity/liver acinus. * p < 0.001 vs. sham; # p < 0.01 vs. 3.0 h I/R; Data expressed as Mean + 2SD; n = 7 for each group. Figure 3 Correlation between sinusoidal hemoglobin oxygen saturation (HbsO 2 ) and tissue redox status . The mean HbsO 2 values significantly correlated with the corresponding NAD(P)H autofluorescence ( p < 0.005; r 2 = 0.94). Data derived from 32 animals. Hepatic tissue injury Serum alanine aminotransferase (ALT) and serum aspartate aminotransferase (AST) levels are summarized in Table 2 . When compared with sham animals, mice treated with 3.0 h I/R exhibited significantly higher levels of ALT and AST. No significant changes between 3.0 h I/R and 6.0 h I/R animals were detectable. When compared with 3.0 h I/R, mice treated with 6.0 h I/R and a continuous infusion of ET-1 showed significant higher ALT and AST levels. The results of labelling lethally injured hepatocytes with propidium iodide (PI) are shown in Figure 4 . The 3.0 h I/R treated animals exhibited a significantly increase in lethally injured hepatocytes (120.4 (44.0)) compared with sham (25.7 (17.9)), whereas the 6.0 h I/R group had a significant higher number of dead hepatocytes (260.1 (52.7)) than the 3.0 h I/R treated animals. The treatment of 6.0 h I/R animals with a continuous ET-1 infusion further elevated the degree of lethally injured hepatocytes (361.8 (56.0)) when compared to the 6.0 h I/R treated animals. Regression analysis between lethally injured hepatocytes and hepatic HbsO 2 revealed a significant correlation ( p < 0.001; r 2 = 0.86), as shown in Figure 5 . Table 2 Serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Sham 3.0 h I/R 6.0 h I/R 6.0 h I/R+endothelin-1 ALT (U/L) 50.2 (16.6) 197.0 (40.4) * 226.2 (38.5) * 261.6 (37.8) ## AST (U/L) 177 (34) 1825 (410) # 2551 (616) * 2856 (320) ## Data expressed as Mean (SD); n = 7 for each group; p < 0.001 vs. sham; # p < 0.02 vs. 6.0 h I/R; ## p < 0.01 vs. 3.0 h I/R. Figure 4 Hepatic tissue injury . Nuclei of lethaly injured hepatocytes were labelled in vivo with propidium iodide (PI). PI-labelled nuclei were quantified using fluorescence intravital videomicroscopy with a 510 to 560 nm excitation and an emission barrier filter greater than 590 nm. PI-labelled hepatocytes were expressed as number of cells/10 -1 mm 3 . * p < 0.001 vs. sham; # p < 0.001 vs. 3.0 h I/R; ## p < 0.01 vs. 6.0 h I/R; Data expressed as Mean + 2SD; n = 7 for each group. Figure 5 Correlation between sinusoidal hemoglobin oxygen saturation (HbsO 2 ) and lethal hepatocyte injury . There is a significant correlation between the mean HbsO 2 values and the corresponding amount of PI-labelled nuclei ( p < 0.001; r 2 = 0.87). Data derived from 32 animals. Discussion In the present study, we demonstrate the utility of a remission spectroscopy system for the in vivo measurement of murine hepatic sinusoidal HbsO 2 that showed a significant correlation with the established method of NAD(P)H autofluorescence, as well as with the extent of hepatic tissue injury. Oximetry relies on the detection of the spectral properties of oxygenated and reduced Hb. In vitro bench analysis capabilities have spurred the desire to accomplish accurate in vivo measurement through various techniques. The 1930's and 1940's were a particularly active period for oximetry advances culminating in the development of pulse oximeters in the 1970's [ 12 ]. Remission spectroscopy is based on the same principles of those oximeters, namely because they rely on the emission of white light and measure the total intensity of the backscattered light returned from the tissue. The intensity of the backscattered light is dependant on the amount and absorbance of the Hb in the tissue under observation. Oxygenated Hb has a different absorbance from that of deoxygenated Hb. The analysis of the backscattered light spectrum allows the determination of the HbsO 2 in the tissue. Previously, it has been shown that bilateral hindlimb I/R results in the deterioration of liver microcirculation [ 13 ]. Since the hepatic Hb content was not found to be different between groups in this study, the differences in the backscattered light spectra only represent differences in the HbsO 2 . In the past, we have shown that bilateral hindlimb I/R results in a systemic inflammation with hepatic microcirculatory disturbances, in terms of reduced sinusoidal diameters and sinusoidal volumetric blood flow accompanied by elevated levels of sinusoidal leukocytes [ 4 , 5 ]. These disturbances may result in an imbalance between oxygen supply and oxygen demand. Since the spectra, extinction coefficient, and quantum yield of NADH and NADPH are the same [ 14 , 15 ], they are designated together as NAD(P)H – this naturally occurring fluorophore transfers electrons to oxygen by means of an electron transport chain located at the inner membrane of mitochondria [ 16 ]. Under hypoxic conditions, with no oxygen available to accept electrons from cytochrome a, intracellular NAD(P)H accumulates. Unlike the oxidized form NAD + , NAD(P)H is highly fluorescent [ 17 ]. Therefore, we compared the changes in NAD(P)H autofluorescence, which reflect the extent of tissue hypoxia, with that of hepatic HbsO 2 obtained by the remission spectroscopy system under pathophysiological conditions. Whether induced by I/R or by the combination of I/R and infusion of ET-1, both analytical methods showed a decrease in hepatic oxygen supply, either as an elevation in NAD(P)H autofluorescence or as a diminution in hepatic HbsO 2 . The significant correlation between remission spectroscopy and NAD(P)H fluorescence indicates that after 3.0 h I/R, 6.0 h I/R and 6.0 h I/R+ET-1, hepatic oxygen supply was compromised. This is further emphasized by the statistical relationship found between hepatic HbsO 2 and the extent of subsequent hepatocyte death. Both remission spectroscopy and NAD(P)H autofluorescence provide information on the metabolic state of the murine liver. Remission spectroscopy is directly dependent on the HbsO 2 in the sinusoids, whereas NAD(P)H autofluorescence depends upon the mitochondrial redox state and the activity of the mitochondrial electron transport chain. It was previously proposed that during systemic inflammation the NADH/NAD + redox potential may increase, and oxygen utilization may be altered [ 18 ]. The present study demonstrates a concomitant change in NAD(P)H autofluorescence and hepatic HbsO 2 . Obviously, the observed hypoxia did not occur through altered oxygen utilization, but rather through a reduced oxygen supply induced by sinusoidal microcirculatory disturbances. This corroborates our previous contention that the simultaneous use of remission spectroscopy, and that of NAD(P)H autofluorescence, provides additional information regarding the underlying pathophysiological mechanisms. That technical approach allows the correlation between disturbances in oxygen supply and those of oxygen utilization. Conclusions There is a significant reduction in hepatic sinusoidal HbsO 2 during the early stages of systemic inflammation. In parallel, we detected an increasing NAD(P)H autofluorescence representing an intracellular inadequate oxygen supply. Both changes are accompanied by increasing markers of liver cell injury. Future therapeutic interventions should focus on the amelioration of sinusoidal HbsO 2 followed by an improvement in mitochondrial redox state. Remission spectroscopy represents a simple and reliable method for hepatic sinusoidal HbsO 2 determination in small rodents. In combination with NAD(P)H autofluorescence, it provides information on the oxygen distribution, the metabolic state and the mitochondrial redox potential within the hepatic tissue. Methods Animals Male C57/BL6 mice (eight to ten weeks old, weighing 23.7 (11.1) g) were used for all experiments. The experimental protocols were in compliance with the guidelines of the Committee on the Care and Use of Laboratory Animals of the Institute of Laboratory Animal Resources, National Research Council as well as those of Germany. Animals were maintained under controlled conditions (22°C, 55% humidity and 12-hour day/night cycle) with free access to tap water and a standard laboratory chow. Experimental protocol Mice (n = 7, for each group) were randomly assigned to either a Sham or a hindlimb ischemia/reperfusion (I/R) group. Animals of the I/R groups were treated with 60 minutes bilateral hindlimb ischemia induced by tightening a tourniquet above the greater trochanter of each leg while under anaesthesia. Sham animals were not subjected to ischemia, but remained anaesthetized for the same period of time. Tourniquets were removed just prior to recovery from anaesthesia. The animals were awake during the 3 hours (3.0 h I/R) or the 6 hours (6.0 h I/R) reperfusion periods, and re-anaesthetized for the intravital microscopy procedure. To further induce liver microcirculatory disturbances and contribute towards a reduction in liver oxygen supply 6.0 h I/R, mice were further randomized to a group treated with a continuous infusion of ET-1 (70 pmol/min., i.v.) starting 15 minutes prior to microscopy. This dose of ET-1 was chosen because it produced alteration in the oxygen distribution, along with derangements in the hepatic tissue perfusion [ 19 ]. Surgical procedure Animals received anaesthesia, by inhalation, for all procedures. As previously described [ 20 ], anaesthesia was performed using isoflurane (Forene, Abbott, Wiesbaden, Germany) in spontaneously breathing animals. The left carotid artery and the left jugular vein were cannulated under sterile conditions. The carotid artery cannula was used for the continuous measurement of systemic arterial blood pressure and heart rate, while central venous pressure was assessed via the jugular vein cannula. Throughout the experiment, normal saline was administered at a rate of 0.4 ml/hr to maintain normal mean arterial pressure. As formerly described [ 4 ], and for the realization of the intravital microscopy procedure in anaesthetized animals, a transverse subcostal incision was performed. Briefly, the ligament attachments from the liver to the diaphragm and to the abdominal wall were carefully released. For the evaluation of the hepatic microcirculation by intravital fluorescence microscopy, the animals were positioned on left lateral decubitus and the left liver lobe was exteriorized onto an adjustable stage. The liver surface was covered with a thin transparent film to avoid tissue drying and exposure to ambient oxygen. For equilibrium purposes, a pause of 10 minutes was allowed before data from microscopy and remission spectroscopy was collected. After microscopy, animals were killed by exsanguination, via the insertion of a cannula in the left femoral artery for the collection of arterial blood samples or via cardiac puncture. Intravital microscopy Details of this technique have been described elsewhere [ 4 , 21 ]. For observations of the liver microcirculation, we used a modified inverted Zeiss microscope (Axiovert 200, Carl Zeiss, Göttingen, Germany) equipped with different lenses (Achroplan × 10 NA 0.25 / × 20 NA 0.4 / × 40 NA 0.6). The image was captured using a 2/3" charge-coupled device video camera (CV-M 300, Jai Corp., Kanagawa, Japan) and digitally recorded (JVC HM-DR10000EU D-VHS recorder) for off-line analysis. As previously described [ 22 ], NAD(P)H autofluorescence, as a marker of the mitochondrial redox state, was assessed using the 10x objective lens. The liver was examined using a filter set consisting of a 365 nm excitation and a 397 nm emission bandpass filter. NAD(P)H autofluorescence was recorded over the complete left liver lobe, allowing at least 15 different fields of view. Non-viable hepatocyte nuclei were labelled in vivo with an i.v. bolus of the vital dye PI (0.05 mg/100 g). As previously stated [ 21 ], PI-labelled nuclei were used to identify lethally injured hepatocytes. The fluorescent labelling of these nuclei was viewed using the 20x objective lens and a filter set with a 510 to 560 nm excitation and an emission barrier filter greater than 590 nm. Quantification of redox state and cell death was performed off-line by frame-by-frame analysis of the videotaped images using Meta Imaging Series Software (Ver. 6.1; Universal Imaging Corp., Downington, PA, USA). NAD(P)H fluorescence was densitometrically assessed and expressed as "average intensity/liver acinus". Gain, black level and enhancement settings were identical in all experiments. PI-labelled hepatocytes were expressed as number of cells/10 -1 mm 3 . Remission spectroscopy Hepatic sinusoidal HbsO 2 was measured using the remission spectroscopy system Oxygen-to-See (O2C-ATS) supplied with the micro probe VM-3 (Lea Medizintechnik GmbH, Gießen, Germany). White light was continuously emitted via one channel of the micro probe light-guide and was continuously detected via another channel (channel diameter 70 μm). The backscattered light was analyzed in steps of 1 nm (500–650 nm). Each HbsO 2 value was defined by specific Hb spectra. The local tissue light absorbance depends on the total local tissue content of Hb. The local content of Hb was calculated from the local light absorbance and emission. The flexible VM-3 micro probe allowed the detection of oxygen saturation of the left liver lobe placed on the glass slide of the inverted microscope. A special clamping system fixed the micro probe close to the surface of the glass slide and permitted contact-free systematic scanning of the liver lobe (Figure 6 ). At least 35 different observation points per animal were randomly chosen and examined. Before each experiment, the white standard of the micro probe was calibrated according to the technical instructions of the manufacturer. Figure 6 Illustration of the experimental setup . The flexible probe of the remission spectroscopy system was fixed on a special shaped clamp holder, which allowed the contact free scanning of the left liver lobe from the bottom side of the glass slide. The setup permitted systematic in vivo scanning of the liver sinusoidal HbsO 2 , without affecting the organ integrity. Measurement of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels Blood was collected immediately after the microscopy procedure, via cardiac puncture. Blood samples were centrifuged at 6500 g, for 5 min, and the remaining serum analyzed, at 37°C, by means of standard enzymatic techniques. Blood gas analyses Blood samples for blood gas analyses were collected in heparinized syringes, via the insertion of a cannula in the left femoral artery, at the end of the microscopy procedure. The samples were immediately analyzed using the automated blood gas analyzing system Radiometer ABL 700 (Radiometer Medical Aps., Bronshoj, Denmark). Statistical analysis Data in text and Tables is given as: Mean (SD). Statistical differences between groups and from baseline within each group were determined by ANOVA, followed by the Tukey post-hoc test. The Kolmogorov-Smirnov test was previously used to confirm the normal distribution of data. For checking the nature and extend of the relationship between two variables linear regression analysis was performed. All figures were generated with Sigma Plot (Ver. 8.0) and statistical analyses were performed using Sigma Stat software (Ver. 2.0; SPSS Inc.; München, Germany). Differences were considered significant for p < 0.05. Authors' contributions CW conceived the design of the study and conducted the laboratory experiments; RB drafted the manuscript and coordinated the study; AK assisted in technical questions. NR participated in design and coordination and OE participated in animal procedures and in drafting the paper. All authors approved and read the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545944.xml
524376	A Randomised, Double-Blind, Controlled Vaccine Efficacy Trial of DNA/MVA ME-TRAP Against Malaria Infection in Gambian Adults	Background Many malaria vaccines are currently in development, although very few have been evaluated for efficacy in the field. Plasmodium falciparum multiple epitope (ME)– thrombospondin-related adhesion protein (TRAP) candidate vaccines are designed to potently induce effector T cells and so are a departure from earlier malaria vaccines evaluated in the field in terms of their mechanism of action. ME-TRAP vaccines encode a polyepitope string and the TRAP sporozoite antigen. Two vaccine vectors encoding ME-TRAP, plasmid DNA and modified vaccinia virus Ankara (MVA), when used sequentially in a prime-boost immunisation regime, induce high frequencies of effector T cells and partial protection, manifest as delay in time to parasitaemia, in a clinical challenge model. Methods and Findings A total of 372 Gambian men aged 15–45 y were randomised to receive either DNA ME-TRAP followed by MVA ME-TRAP or rabies vaccine (control). Of these men, 296 received three doses of vaccine timed to coincide with the beginning of the transmission season (141 in the DNA/MVA group and 155 in the rabies group) and were followed up. Volunteers were given sulphadoxine/pyrimethamine 2 wk before the final vaccination. Blood smears were collected weekly for 11 wk and whenever a volunteer developed symptoms compatible with malaria during the transmission season. The primary endpoint was time to first infection with asexual P. falciparum . Analysis was per protocol. DNA ME-TRAP and MVA ME-TRAP were safe and well-tolerated. Effector T cell responses to a non-vaccine strain of TRAP were 50-fold higher postvaccination in the malaria vaccine group than in the rabies vaccine group. Vaccine efficacy, adjusted for confounding factors, was 10.3% (95% confidence interval, −22% to +34%; p = 0.49). Incidence of malaria infection decreased with increasing age and was associated with ethnicity. Conclusions DNA/MVA heterologous prime-boost vaccination is safe and highly immunogenic for effector T cell induction in a malaria-endemic area. But despite having produced a substantial reduction in liver-stage parasites in challenge studies of non-immune volunteers, this first generation T cell–inducing vaccine was ineffective at reducing the natural infection rate in semi-immune African adults.	Introduction The disease burden of malaria has increased in recent years partly because of the rise of drug-resistant Plasmodium falciparum parasites [ 1 ] and insecticide-resistant Anopheline spp. vectors [ 2 ]. There is an urgent need for effective malaria control methods to reduce mortality and morbidity from malaria in endemic countries. Detailed analysis of immunological mechanisms of immunity against malaria in humans and experimental animals has indicated a likely protective role for T cell responses against the liver stages of P. falciparum [ 3 , 4 , 5 , 6 , 7 , 8 , 9 ]. Comparison of a variety of means of immunisation to induce protective T cell responses in animal models has identified heterologous prime-boost immunisation, i.e., sequential immunisation with two different vaccines with the same recombinant DNA sequence, as a particularly effective approach [ 10 , 11 ]. DNA and viral vaccines recombinant for a malarial DNA sequence known as multiple epitope (ME)–thrombospondin-related adhesion protein (TRAP), which were designed to induce protective immunogenicity against liver-stage P. falciparum malaria, were manufactured to explore this approach [ 12 ]. γ-interferon T cell responses to ME and TRAP peptides were associated with protection from severe malarial anaemia in a prospective study of Kenyan children [ 13 ]. DNA and modified vaccinia virus Ankara (MVA)'s excellent safety profiles in malaria-naïve and semi-immune volunteers have been discussed previously [ 12 ]. In several studies, prime-boost immunisation (usually with DNA/MVA) has been highly immunogenic for CD4+ and CD8+ T cell induction against infectious pathogens and cancers in both murine and nonhuman primate studies [ 14 , 15 , 16 , 17 , 18 , 19 ]. DNA/MVA vaccination was protective 7 mo after vaccination in an HIV macaque model [ 20 ]. Priming with three 2-mg intramuscular DNA ME-TRAP vaccinations at 3-wk intervals, followed by boosting with one intradermal MVA ME-TRAP vaccination of 1.5 × 10 8 plaque-forming units, produced very strong vaccine-induced CD4+ and CD8+ T cell responses in previous phase I studies in the United Kingdom [ 21 ]. The immunogenicity of two DNA ME-TRAP primes followed by one MVA ME-TRAP boost at these doses is similarly high in both the United Kingdom (S. Dunachie and A. V. S. Hill, unpublished data) and Gambia [ 22 ]. DNA ME-TRAP/MVA ME-TRAP regimens led to a delay in time to parasitaemia compared to unvaccinated controls after high-dose heterologous sporozoite challenge of malaria-naïve individuals [ 21 ]. To follow up these encouraging findings in volunteers, we have conducted a randomised, controlled trial of DNA ME-TRAP/MVA ME-TRAP in a rural part of Gambia to explore whether this vaccine combination could provide protection against natural P. falciparum infection. We chose a two-DNA prime, one-MVA boost regimen with 3-wk between doses because this is a three-dose regimen that would be amenable to integration with the World Health Organization/United Nations Children's Fund Expanded Program on Immunization, with the necessary supporting safety and immunogenicity data both from adults in the United Kingdom and Gambia. We used 3-wk intervals because 4-wk intervals had not been evaluated in phase I trials previously, hence bridging studies would be necessary to bridge to the three-dose, 4-wk interval Expanded Program on Immunization schedule. Methods Vaccines The malarial DNA sequence is known as ME-TRAP. The ME string contains 14 CD8+ T cell epitopes, one CD4+ T cell epitope, and two B cell epitopes from six pre-erythrocytic P. falciparum antigens. It also contains two non-malarial CD4+ T cell epitopes [ 23 ]. The ME string is fused in frame to the entire T9/96 strain of P. falciparum TRAP [ 10 , 24 , 25 ]. The individual epitopes making up the ME string are described in detail elsewhere [ 23 ]. The strain of P. falciparum used to produce the vaccine construct is T9/96. The candidate malaria vaccines were manufactured to Good Manufacturing Practice by contract manufacturers (DNA ME-TRAP by Qiagen, Hilden, Germany; MVA ME-TRAP by IDT, Rosslau, Germany). DNA ME-TRAP was supplied as a single dose of2 mg in 2-ml vials. MVA ME-TRAP was supplied as two-dose vials, each containing 3 × 10 8 plaque-forming units in 0.8 ml. The rabies vaccine (Chiron Behring, Marburg, Germany) was supplied as a lyophilised single-dose vial with accompanying diluent and syringe. This vaccine was chosen because of its public health benefit in Gambia. Study Setting and Volunteers Approval was obtained from the Joint Gambian Government/Medical Research Council Ethics Committee, the Oxford Tropical Research Ethics Committee, and the London School of Hygiene and Tropical Medicine Ethics Committee. An independent Data and Safety Monitoring Board provided oversight for the trial. In addition, independent clinical trial monitors monitored the trial for adherence to International Committee on Harmonisation Good Clinical Practice guidelines. Malaria incidence is highly seasonal in Gambia. The climate is typical of sub-Sahelian Africa, with a long dry season followed by a relatively short rainy season from July to October. Rainfall averages about 600 mm per year. Morbidity and mortality from malaria both occur more frequently during the rainy season. However, in 2002, Gambia experienced a drought, and the malaria season was delayed, with few disease episodes before October. The entomological inoculation rate varies between less than 1 and greater than 100 in Gambia [ 26 ]. Based on previous years' data, we assumed that the average cumulative incidence over a number of years would be about 60% (interquartile range [IQR], 50%–70%), with very few years with incidence less than 40% or more than 90%. Allowing for 15% loss to follow-up, and using a significance level of 0.05, the median power of a study with 372 participants would be 90% (95% confidence interval [CI], 69%–98%) if the vaccine efficacy were 40%. Volunteers were recruited from 13 villages in the North Bank Division of Gambia in July 2002 with follow-up to December 2002 [ 26 ]. The villages were chosen for proximity to the alluvial flood plain. A strong association between proximity to the flood plain and entomological inoculation rate has been seen in this part of Gambia [ 27 ], and the entomological inoculation rate in the study area is likely to have been in the range of 10–20 infectious bites per year. Before recruitment, meetings were held with village heads and elders, followed by general village meetings at which the study was explained. Volunteers received information sheets and consent forms translated into the three local languages in Arabic script, as well as in English. After written informed consent was obtained by a study physician, age and identity were checked, pre-test HIV counselling occurred, and potential volunteers underwent clinical evaluation, including a full medical history and clinical examination. They were screened for haematological (full blood count), renal (plasma creatinine), and hepatic (plasma alanine aminotransferase [ALT]) dysfunction, and duplicate malaria smears were made. Exclusion criteria included any chronic illness detected by clinical evaluation, ALT greater than 42 (international units/litre), creatinine greater than 130 (micromoles/litre), packed cell volume less than 30%, positive antibody ELISA to HIV-1 or HIV-2, simultaneous participation in another clinical trial, blood transfusion in the month prior to vaccination, previous experimental malaria vaccination, administration of another vaccine within 2 wk of vaccination, previous rabies vaccination, allergy to any previous vaccine or to sulphadoxine/pyrimethamine, history of splenectomy, and any treatment with immunosuppressive drugs. Eligible volunteers were given a unique study number and a photographic identity card. Parental written informed consent was obtained for volunteers aged 15–17 y. Procedures A member of the Data and Safety Monitoring Board generated and held the randomisation code that associated each study number with a specific vaccine. A blocking procedure was used, and whole villages were enrolled with sequential study numbers to ensure balanced numbers in each group. During the course of the study investigators and volunteers did not know the size of the blocks, nor were they aware of which vaccine preparation was administered to a particular volunteer. Opaque sealed envelopes were used for vaccine allocation. Study numbers were not preprinted on vials but were written on vials at vaccination. Used vials were checked for correct allocation off-site. Vaccination was performed by nurses who played no other part in the trial. Volunteers were randomly assigned to receive either (1) two 2-mg doses of DNA ME-TRAP followed by a single 1.5 × 10 8 -plaque-forming-units dose of MVA ME-TRAP or (2) three doses of rabies vaccine; injections were given on days 0, 21, and 42, timed to coincide with the start of the rainy season. The first two doses of vaccine consisted of two intramuscular injections, one into each deltoid muscle. DNA ME-TRAP was given as 1 ml and rabies vaccine as 0.5 ml into each arm. The third dose of vaccine was given as four intradermal injections into the skin overlying the deltoid muscle, with two injections into each arm. The malaria vaccine group received MVA ME-TRAP as four 0.1-ml injections, whereas the control group received four 0.05-ml injections of rabies vaccine. Two weeks before administration of the third dose, all volunteers received three tablets of sulphadoxine/pyrimethamine to clear blood-stage P. falciparum infections [ 23 ]. After each vaccination volunteers were observed for 1 h and visited at home on the first, second, and seventh day postvaccination for assessment of local adverse events (discolouration, induration, blister formation, pain, or limitation of arm motion), systemic adverse events (headache, nausea, malaise, or elevated axillary temperature), and unsolicited adverse events. One week and 13 wk after the third vaccination, venous blood was collected for repeated measurement of full blood count, ALT, and creatinine. Since vaccination with MVA causes a characteristic local reactogenicity in some subjects, specific steps were taken to ensure that the participants were evaluated in a double-blinded manner. Field workers who assessed reactogenicity after the third dose were different from those who undertook surveillance during the parasitological follow-up period. During the surveillance period, starting 2 wk after the third dose of vaccine, volunteers were visited twice weekly and asked whether they had attended a health centre. At weekly visits blood smears and axillary temperatures were taken. At midweek visits, blood smears and temperature were taken if symptoms compatible with malaria were present. Investigators and field supervisors made random visits to ensure accurate data collection. This active case detection was supplemented by passive case detection by study nurses to whom volunteers had 24-h access at three of the study villages and by a clinic at Medical Research Council Farafenni (20 km from the study villages). Symptomatic malaria was defined as the presence of asexual P. falciparum parasites at any parasitaemia with either an axillary temperature of 37.5 °C or more or one or more of the following symptoms: headache, myalgia, arthralgia, malaise, nausea, dizziness, or abdominal pain. When blood smears were obtained, two sets of duplicate blood smears (four smears in total) were made. A Field's stain was performed on films obtained from subjects with possible clinical malaria and the films read immediately. Two further smears (“A” and “B” slides) were stained with Giemsa after overnight drying; 100 high-power fields were read by two slide readers before a film was declared negative. The presence of P. falciparum parasites was confirmed by a supervisor before a slide was declared positive. The arithmetic mean of the A and B slides was used to determine parasite density. If parasite densities for A and B slides were markedly discrepant, a third read was performed by the supervisor and this read was used for analysis. Parasite density was expressed per microlitre (assuming one parasite per high power field equals 500 parasites/μl). Full blood counts were performed and packed cell volumes were measured in a CA620 cell analyser (Medonic, Stockholm, Sweden). ALT (international units/litre) and creatinine (micromoles/litre) were measured in a Visual analyser (bioMérieux, Craponne, France). Effector T cell responses were assessed in ex vivo γ-interferon enzyme-linked immunospot (ELISPOT) assays for 98 volunteers randomly selected from a substudy list containing a 3:1 ratio of participants receiving malaria vaccines to participants receiving rabies (control) vaccines. For this assay, 4 × 10 5 peripheral blood mononuclear cells (PBMCs) were assayed as described [ 28 ], using Millipore (Billerica, Massachusetts, United States) MAIP S45 plates for 18–20 h before being developed. Mabtech (Stockholm, Sweden) antibodies were used, and counting of spots was performed blinded to vaccine allocation with the AutoImmun Diagnostika (Strassberg, Germany) computerised system. All peptides were at 25 μg/ml concentration. A single pool contained all ME peptides. Four pools each were used of 20-mer peptides, overlapping by ten amino acids, to span the entire TRAP antigen of the T9/96 and 3D7 strains of P. falciparum . Statistical Analysis An analysis plan, written before unblinding, specified exclusion criteria, statistical methods, and important covariates (age, village of residence, and bednet use [defined as sleeping nightly under an intact or impregnated bednet]). Ethnic group, though not specified as a covariate in the analysis plan, was found on analysis to be associated with the risk of infection, and was included as a covariate. The primary endpoint was time to first infection with asexual P. falciparum, defined as the number of days from the start of the surveillance period to the date of the first positive slide. Vaccine efficacy was calculated from the hazard ratio estimated by Cox's regression, adjusting for the effects of prognostic variables. Volunteers who received fewer than three doses or who were parasitaemic both prevaccination and at the beginning of surveillance without an intervening negative blood smear were excluded from the primary analysis but included in a secondary analysis. Observations on individuals who were lost to follow-up or were missing from trial data for 3 wk were censored. Analyses were done with Stata version 7 (Stata Corporation, College Station, Texas, United States). ELISPOT responses were analysed as follows. After subtraction of medium-alone values from each pooled peptide response, responses were summed across T9/96 and 3D7 pools. Geometric means were calculated for T9/96 TRAP, 3D7 TRAP, and ME string responses. Responses in the two groups were compared using the Mann-Whitney test. Results In total, 489 volunteers were screened ( Figure 1 ), of whom 117 were excluded for the following reasons: 46 could not be found on the day of vaccination, 44 were not eligible (anaemia, ALT, creatinine, HIV, various medical conditions, too young or too old), and 27 withdrew consent. Thus, 372 volunteers aged 15–45 y were enrolled. Of these, 335 men (90%) received their second dose of vaccine, and 320 of these received the third dose. Some 52 volunteers who were randomised did not receive three doses (two men received the wrong vaccine at the second dose, 26 left the study area, 23 withdrew consent, and one was withdrawn because he developed pneumonia between the first and second doses). In total, 296 volunteers (141 in the malaria group and 155 in the rabies group) received three doses and were followed up, 277 of whom completed 11 wk of surveillance. Additional data were available for 14 volunteers who did not receive all three vaccine doses (all 14 received the first and third doses), for two volunteers in the malaria vaccine group who received the wrong vaccine at the second dose, and for 18 volunteers who were parasitaemic both before vaccination and at the start of surveillance. These individuals were included in a secondary analysis. Losses to follow-up were similar in the two groups. Prognostic variables were similarly distributed in the two groups at the start of surveillance ( Table 1 ). This trial is reported in accordance with CONSORT guidelines ( Table S1 ). Figure 1 Trial Profile Table 1 Characteristics of the Trial Cohorts at the Start of Surveillance Table shows the 296 participants who received three doses of vaccine and were followed up a Village group 2 consisted of nine closely situated villages Vaccine Safety No clinically significant differences in packed cell volume, ALT, or creatinine were seen in either vaccine group. One volunteer who received rabies vaccine had a history of breathlessness and chest pain several years prior to enrolment, experienced a relapse of symptoms, and deteriorated and died, probably from heart disease, 3 mo after he received the last dose of vaccine. This event was regarded as unrelated to vaccination. There were no other serious adverse events. Adverse events were rare after first and second doses and were not increased in the DNA ME-TRAP group compared to the rabies vaccine group (data not shown). Injection site pain, limited arm motion, headache, and malaise in the first 24 h after vaccination (mild to moderate in intensity, i.e., not preventing activities of daily living, in all but one volunteer) were more common after MVA ME-TRAP vaccination than rabies vaccination ( Table 2 ). Some volunteers developed an injection site blister 1–2 d after MVA ME-TRAP vaccination, which healed over 1–3 wk without complications. Induration (for 1–2 d) and discolouration (faint, shiny macular appearance for several weeks) were common after MVA ME-TRAP vaccination. The frequency of short duration severe adverse events (i.e., preventing activities of daily living) of less than 2% seen with MVA ME-TRAP immunisations is less than that seen with some other licensed alum-formulated vaccines in widespread use. Table 2 Frequency of Solicited Symptoms during the 7 d after the Third Dose of Vaccine Table shows the number and percentage of participants who had at least one report of the symptom Immunogenicity In the study, 63 and 30 volunteers from the malaria and rabies vaccine groups, respectively, were assayed 7 d after final vaccination for T cell responses. In the rabies vaccine group, geometric mean effector T cell responses were 3.1, 3.9, and 1.4 spot-forming cells (SFCs) per million PBMCs for T9/96 and 3D7 strains of TRAP and the ME string, respectively. In the malaria vaccine group, the effector T cell frequency to the vaccine strain of the TRAP antigen, T9/96, was geometric mean 251.1 SFCs per million PBMCs (80-fold increase above control group, p <0.001, range 6.25–2148.75). A large cross-reactive T cell response to 3D7 TRAP, a strain with 6% amino acid variance to T9/96, and a weaker response to the ME string were also seen at this timepoint ( Table 3 ). Table 3 Effector T Cell Responses 1 wk after the Third Vaccination Of the 98 individuals identified for testing T cell responses, 80 received three doses of vaccine according to protocol and gave analysable responses Time to First P. falciparum Infection By the end of the study, 171 participants developed parasitaemia, 80/141 (57%) in the malaria vaccine group and 91/155 (59%) in the rabies vaccine group. The distribution of time to first infection was similar in the two groups ( Figure 2 ). Vaccine efficacy among participants who received three doses, adjusted for age, bednet use, ethnic group, and village of residence was 10.3% (95% CI, −22% to +34%; p = 0.49). Similar results were obtained when all participants who received at least one dose of vaccine were included in the analysis (efficacy, 1.0%; 95% CI, −32% to +25%; p = 0.95). Figure 2 Kaplan-Meier Survival Curves Showing the Probability of Remaining Free of P. falciparum Infection during the 11 wk of Surveillance Week 0 of surveillance began in October 2002, 14 d after the third dose of vaccine was administered. Geometric mean P. falciparum densities in first infections were similar in the two groups (31 parasites/μl [IQR, 5–154] in the malaria vaccine group compared to 24 parasites/μl [IQR, 5–69] in the rabies group; Mann-Whitney test, p = 0.79). During surveillance, there were ten episodes of symptomatic malaria in the malaria vaccine group and 13 in the rabies group. The risk of malaria-related symptoms during an episode of parasitaemia was similar in both vaccine groups. Percentage mean packed cell volume at the end of the trial was similar in both groups (41 [IQR, 37–44] for the malaria vaccine group and 40 [IQR, 37–43] for the rabies group). Within the ELISPOT substudy group, the risk of developing parasitaemia was not associated with effector T cell response to the 3D7 strain of TRAP. The 80 men from the substudy group who received three doses of either malaria vaccine (55 men) or rabies vaccine (25 men), completed 11 wk of surveillance, and had complete ELISPOT data after dose three were divided into four quartiles. Men with the highest effector T cell responses had hazard ratios for infection similar to those with the lowest after adjustment for age, bednet use, and village of residence. The incidence of parasitaemia decreased with increasing age, and was decreased in those of Fula ethnicity compared to those in the Mandinka and Wollof ethnic groups ( Table 4 ). The use of bednets was not associated with a significantly reduced risk of malaria infection ( Table 4 ). Table 4 Results of Cox Proportional Hazards Regression Analysis for the Risk of Developing Parasitaemia after Three Doses of Vaccine Discussion This trial demonstrated that vaccination with two doses of DNA ME-TRAP followed by a single dose of MVA ME-TRAP is safe and highly immunogenic for effector T cell induction but that it did not reduce the P. falciparum infection rate in a semi-immune adult African population. This provides a second comparison between protection in malaria-naïve and malaria-experienced adults. RTS,S/AS02, a circumsporozoite protein malaria vaccine based on a hepatitis B surface antigen virus-like particle formulated in a proprietary adjuvant, provided about 40% sterile protection in the artificial challenge model [ 29 ] and 71% short-term protection against natural infection [ 30 ]. The lack of field efficacy found in the present study despite evidence of partial protection in United Kingdom volunteers supports the use of complete, not partial, protection in the sporozoite challenge model as a predictor of likely field efficacy against malaria infection when screening pre-erythrocytic vaccine candidates. However, some vaccines are known to prevent disease but not infection, as is also the case for naturally acquired immunity to malaria. There was no effect of bednet use on parasitaemia in either this study or an earlier malaria vaccine trial in adults [ 30 ], whereas bednet use has been found to substantially reduce the incidence of clinical malaria and childhood mortality in Gambian children [ 31 ]. The present study does not exclude the possibility that the vaccination regimen tested could provide significant anti-disease immunity. Paediatric study designs are necessary to evaluate this possibility. The present study highlights an issue related to use of surrogate efficacy endpoints; whereas positive results can spur development, negative results may incorrectly lead to the cessation of development of a candidate vaccine. Another possible reason for the observed low efficacy is that the frequency of the effector T cell response declines from 7 d after boost, and so efficacy would be prevented if very high frequencies of circulating effectors are needed for protective efficacy. Alternatively, a suboptimal regional memory T cell pool in the liver may be responsible [ 32 ], or, less likely in view of the observed T cell strain cross-reactivity, TRAP polymorphisms may have impaired T cell recognition. In previous studies in East and West Africa, summed T cell responses to TRAP in unvaccinated semi-immune adults by ex vivo γ-interferon ELISPOT were geometric mean less than 20 SFCs per million PBMCs. The candidate regimen represents a new method for induction of unprecedented effector T cell frequencies, which are about 50-fold higher than those induced by lifelong natural exposure. Estimates of the reduction in liver-stage parasite burden induced by these vaccines in the human challenge model are of the order of 80%–90% of infected hepatocytes [ 21 , 33 ]. It is unclear whether a similar level of anti-parasite activity could have been achieved in this study without any significant change in infection rate. Another candidate malaria vaccine that reduced liver parasite burden by an estimated 95% in challenge studies [ 29 , 33 ] did have a substantial, if short-lived, impact on infection rates in a similar Gambian field study [ 30 ]. This suggests that a moderate increase in the efficacy of this first-generation prime-boost vaccination strategy in reducing liver parasite burden might have an important impact on overall efficacy. Second-generation prime-boost vaccine strategies for malaria currently in or near to clinical evaluation include the following: use of a different viral vector as the priming agent that may lead to proportionately greater CD8+ rather than CD4+ T cell induction (J. M. Vuola, S. Keating, D. P. Webster, T. Berthoud, S. Dunachie, et al., unpublished data), as is the case with fowlpox-MVA immunisation; the use of a different antigen, the circumsporozoite protein, or polyprotein constructs [ 34 ] to address the difficult issue of target antigen selection; and evaluation of regimes that seek to combine high-level T cell responses with strong anti-sporozoite antibody induction, e.g., protein/adjuvant and recombinant virus prime-boost immunisation. In the medium term, combination with protective blood-stage antigens is also desirable. Determining methods for the successful combination of different candidate vaccine regimens (whether within or between parasite stages) will be one of the important challenges of coming years. We were unable to obtain a useful estimate of the likely efficacy of the DNA ME-TRAP/MVA ME-TRAP vaccination regime against clinical disease. Even for an adult population, the incidence of clinical disease was lower than expected. Sulphadoxine/pyrimethamine was administered 4 wk before the start of surveillance in this study and in an RTS,S field efficacy study [ 30 ]. There is some evidence that pretreatment with this antimalarial reduces the incidence of clinical malaria for longer than 4 wk [ 35 , 36 ]. However, there was also less clinical disease than in recent years in paediatric cohorts recruited for other studies in 2002 at the study site, probably for climatic reasons. This study highlights North Bank Division in Gambia as an excellent malaria vaccine field trial site both for adults and, by extrapolation, for children. In a low-transmission year, cumulative incidence overall in men aged 15–45 y was 72% over 11 wk, which was higher than expected. Also, compliance was good despite a demanding study design, and migration from the study area was acceptably low. This paper adds to the body of data detailing the very gradual acquisition of anti-infection immunity in adults resident in sub-Saharan Africa [ 30 ]. While substantial immunity to severe malaria is acquired after only a few infections and anti-disease immunity is acquired in childhood, we saw statistically significant decreases in incidence of infection with increasing age in the 15–45 age range ( Table 4 ). The protection against infection for those with Fula ethnicity observed in this trial is consistent with a report from Burkina Faso [ 37 ]. The Fulani mostly reside in distinct villages in this part of Gambia. Immunological analysis of the high level of protection inducible by immunisation of humans and animals with irradiated sporozoites has encouraged attempts to generate protective immunity by subunit vaccines that induce strong cellular immune responses. To date the induction of high-level protective T cell responses against malaria and some other infectious pathogens has generally required two-component prime-boost vaccination approaches [ 38 ]. We report the first field efficacy trial of a subunit vaccine designed to induce protective immunity through effector T cell rather than antibody induction. Effector T cell induction 50-fold greater than that generated by natural malaria infection is now possible through DNA-based heterologous prime-boost vaccination of humans. However, further development of T cell–inducing vaccines will be required to evaluate the effects of altering the characteristics, target antigen specificities, and durability of the induced T cells in order to generate higher levels of protective immunity against malaria. Patient Summary Background Malaria kills 1–2 million people a year, mostly children under the age of five who live in sub-Saharan Africa. Scientists are trying to develop cheap, safe, and effective vaccines that could be given to people living in regions where malaria is very common to prevent them from developing the disease. What Did the Researchers Find? The researchers enrolled 372 Gambian men aged 15–45 years into the study. They injected half the men with two malaria vaccines, one after the other, and half the men with a rabies vaccine that does not protect against malaria (this vaccine was given so that “control” participants would have some benefit from being in the trial) just before the rainy season, when malaria is especially prevalent. The scientists took blood smears from the men once a week and checked to see if they had been infected with the parasite that causes malaria. They found that the men who had been vaccinated became infected just as quickly as those who had not. Although the two malaria vaccines in concert did not work, neither did they cause any serious side effects. The men given the malaria vaccines did produce an immune response to the vaccines, though not one that was clinically useful. What Does This Mean for Patients? It looks as though the combination of these two vaccines is not effective at preventing infection with Plasmodium falciparum, the parasite that causes malaria. However, there are other vaccines in development that have not been tested yet. Resources on the Web. Gates Malaria Partnership (which co-funded the study): http://www.lshtm.ac.uk/gmp/ Malaria Vaccine Initiative: http://www.malariavaccine.org/ Medicines for Malaria Venture: http://www.mmv.org/pages/page_main.htm Roll Back Malaria Partnership: http://rbm.who.int/partnership The Wellcome Trust (which co-funded the study): http://www.wellcome.ac.uk/en/malaria/ Supporting Information Trial Registration This trial has been submitted for registration in the International Standard Randomised Controlled Trial Number (ISRCTN) Register. The ISRCTN is ISRCTN05221133; Web site http://www.controlled-trials.com/isrctn/trial/1/0/05221133.html . Table S1 Consort Checklist (55 KB DOC). Click here for additional data file.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524376.xml
543460	Analysis of superfamily specific profile-profile recognition accuracy	Background Annotation of sequences that share little similarity to sequences of known function remains a major obstacle in genome annotation. Some of the best methods of detecting remote relationships between protein sequences are based on matching sequence profiles. We analyse the superfamily specific performance of sequence profile-profile matching. Our benchmark consists of a set of 16 protein superfamilies that are highly diverse at the sequence level. We relate the performance to the number of sequences in the profiles, the profile diversity and the extent of structural conservation in the superfamily. Results The performance varies greatly between superfamilies with the truncated receiver operating characteristic, ROC 10 , varying from 0.95 down to 0.01. These large differences persist even when the profiles are trimmed to approximately the same level of diversity. Conclusions Although the number of sequences in the profile (profile width) and degree of sequence variation within positions in the profile (profile diversity) contribute to accurate detection there are other superfamily specific factors.	Background Currently some of the best methods for detecting relationships between protein sequences below the so-called twilight zone of sequence similarity are offered by iterative search algorithms such as PSI-BLAST [ 1 ] which, in effect, compare sequences to a profile. More recently profile-profile matching protocols [ 2 - 5 ] have been shown to offer considerable benefits over sequence-profile matching. Here, we examine how the performance of remote homolog detection by profile-profile methods varies between particular superfamilies. Since superfamilies are believed to constitute sets of remote homologs, detection of same-superfamily relationships is an important task for bioinformatics, and with the increasing number of structures becoming available, improvement in this area will help build a complete structural map of sequence space. In this paper, we use a set of superfamilies that are very sequence diverse to benchmark profile-profile methods. By sequence diverse, we mean that the superfamily has many domains that show no detectable sequence similarity to each other; this lack of detectable sequence similarity means this set is a difficult benchmark for remote homolog detection methods. Previous work has shown that the performance of profile-profile methods is chiefly determined by the width and diversity of the profiles. By profile width , we mean the number of sequences in the profile, defined in contrast to profile length and by diversity we mean the degree of sequence variation within positions in the profile. In particular, Panchenko suggested that there may be an optimum level of profile diversity [ 6 ], whilst Grishin suggested that the inclusion of as many related sequences as possible gives maximum performance [ 7 ]. We examine the performance of profile-profile matching with regard to specific superfamilies with both the full profiles generated from a PSI-BLAST search, and with profiles that are trimmed to similar width and diversity. Significant differences in recognition performance exist between superfamilies for both the full and trimmed profiles. This suggests that performance of profile-profile matching is not simply a function of profile width and diversity. We examine how the performance relates to the structural diversity of superfamilies and find that structurally conserved superfamilies are recognised more successfully than structurally diverse superfamilies. Results Width and diversity of profiles Table 1 shows the width and diversity for the full and trimmed profiles. The table shows average profile width in for each superfamily in the dataset before and after trimming (as detailed in the Methods section). The table also shows average Neff (defined as the total number of different amino acids in a given column of a profile [ 1 , 6 , 7 ]) across all non-gapped columns for each profile in the superfamily. The full profiles show considerable variation in both size and diversity of the profiles. The trimmed profiles, however, are much more similar in both width and diversity, with values of Neff consistently around three. Superfamily specific performance of remote homolog detection Figure 1 shows the value of the performance measure ROC 10 (see Methods for definition) for each superfamily. The figure shows that there is a large variation in performance with respect to superfamily for both the full profiles and the trimmed profiles. For the full profiles, the alpha/beta-Hydrolases, Cytochrome c and S-adenosyl superfamilies perform well, all having with ROC 10 values ≥ 0.7, the fibronectin, thioredoxin-like, (trans)glycosidases, immunoglobulin and FAD/NAD(P)-binding have ROC 10 > 0.2 and the remaining 8 superfamilies all perform poorly, having a performance less than 0.1. After trimming, although performance is reduced, the overall pattern of performance still remains. All the well recognised superfamilies (with the exception of the (trans)glycosidases and thioredoxin-like) still show ROC 10 values greater than 0.2, while the rest are still less than 0.1. The fact that the performance varies greatly between superfamilies despite the trimming of the profiles indicates that the profile generation is not the only limiting step in the performance of profile-profile methods. One might have thought that, for instance, the bad recognition of 4-helical cytokines is due to the small number of homologs drawn from the profile-building stage. Whilst this still may be true, it is not necessarily true: the Cytochrome c superfamily still shows a ROC 10 of 0.7 when using trimmed profiles despite having, on average, less than 20 sequences in the profile. Structural diversity Figure 2 shows the average root mean square deviation (RMSD) across each superfamily in our dataset. As can be seen, there is a large range in the degree of structural diversity across the dataset: some superfamilies are highly structurally conserved showing a narrow range of small RMSDs whilst other show large mean RMSDs with large deviations from the mean. For example, the FAD-NAD(P)-binding SCOP super-family contains 21 domains in the astral_10 data set, and despite the low sequence identity there is high structural conservation with an average RMSd of 1.47Å. Furthermore, the range of RMSDs within this super-family is very small, generally within 0.5-2Å. By comparison, super-families such as the P-loop containing nucleotide triphosphate hydrolases, the (Trans)Glycosidases and the Viral-coat and capsid proteins are very structurally diverse, having high average RMSds with the distribution of RMSds generally higher than 1.5Å, and with a long tail. Relation between structural diversity, sequence conservation and recognition performance Figure 3 shows a scatter of mean RMSD against ROC 10 for each superfamily. The figure shows a correlation between the mean RMSD of each super-family and its ROC 10 value. The figure shows that superfamilies with a mean RMSD of less than 2 Å tend to be well recognised by profile-profile methods, whilst the structurally diverse superfamilies are not. It may be the case that despite the absence of any discernible global sequence similarity within our dataset some local patterns of conservation do exist. These patterns may be present more strongly in some superfamilies than in others. In order to examine this possibility we constructed multiple structure based sequence alignments for each of the 16 superfamilies and then looked down the columns of the multiple sequence alignments to examine the extent of conservation at each position (see Methods section). Figure 4 shows a plot of performance ( ROC 10 ) versus conservation. Apart from the cytochrome c superfamily (an outlier with a high ROC 10 of 0.7 despite a conservation score of 0.2 because the superfamily has a conserved CxxCH motif that facilitates detection), the well performing superfamilies (the alpha beta hydrolases, immunoglobulins, FAD/NAD(P)-binding and fibronectin with ROC 10 values for the trimmed profiles of at least 0.25) have conservation measures of greater than 0.25. This suggests that some superfamilies although highly sequence diverse, may retain some patterns of conservation that facilitate recognition. Further investigation of the functional implications of this variation would be a next step. Figure 5 shows a plot of mean RMSD versus performance ( ROC 10 ). The P-loop and Viral coat superfamilies have low conservation scores and and large structural diversity reflected by high RMSD values. In contrast, the fibronectin and immunoglobulin superfamilies have higher conservation values (both around 0.28) and lower RMSDs (around 1.5Å). However the figure does not show any clear correlation between conservation and RMSD. Discussion Our results suggest that profile profile methods can detect remotely related sequences for some superfamilies significantly better than for others. In our dataset the sequence identity between domains in all the superfamilies is low (not greater than 10% as defined by the ASTRAL). Although the mean width and diversity of the profiles varies across the superfamilies this does not appear to be the only factor contributing to the differences in detection. The effect of the trimming varied depending on superfamily. For the best performing profile (alpha/beta hydrolases) the trimming reduced the performance by about 50% (from 0.95 to 0.43) but the effect on the rank was small dropping from first place to second. Similarly the trimming impacted significantly on the performance of the S-adenosyl methyl transferases with ROC 10 dropping from 0.70 to 0.22. However trimming had no effect on performance for the FAD/NAD(P)-binding superfamily, and only resulted in a small reduction in performance for the immunoglobulins and the cytochrome c superfamilies. Importantly the membership of the top ranking superfamilies in terms of performance did not change after trimming. Although the overall level of sequence similarity within our dataset is low (not more than 10% identity) the different superfamilies exhibit different levels of conservation at positions within the multiple structure based alignments. These conserved positions may facilitate recognition. The extent to which they constrain the structures leading to less diverse alignments is unclear. We recognise also that our measure of conservation and also the use of RMSD as a measure of structural diversity both have their shortcomings. It would be interesting to identify and extract a conserved core and represent structural profiles as combination of core profiles separated by regions of variable length. Conclusions There exist large superfamily specific differences in the performance of profile profile matching for the detection of remote sequence relationships. Some superfamilies can be detected far more successfully than others. The width and diversity of the profiles are important factors in successful recognition. However these are not the only factors that contribute to these superfamily specific differences. Methods Dataset We took release 1.63 of ASTRAL [ 8 ] which provides a filtered version of the SCOP database [ 9 ] where no two sequences have a pairwise sequence identity of over 10%. From this, we chose the sequence diverse superfamilies by selecting all superfamilies with more than 20 domains. This resulted in a dataset of 543 domains which only show a random (not greater than 10%) level of sequence similarity. The particular superfamilies used and a summary of their properties is shown in Table 2 . Superfamily is a readable description of the superfamily, sunid is the SCOP unique identifier, families is the number of families in superfamily, domains is the number of domains in superfamily, length shows the average length of the domains in the superfamily and RMSD shows average RMSD between members of superfamily. Profile generation For each domain of each of the 16 superfamilies we executed a five round PSI-BLAST [ 1 ] run against the protein non redundant protein database nr (dated 5/2/04). We used the "-m6" option to output a multiple alignment and the "e 0.05" to only include hits with e-values less than 0.05 in the alignment. Positions in the multiple alignment that correspond to gaps in the query are removed. We use the resulting multiple alignment as the profile for the query domain. To produce trimmed profiles, we take the full profile and remove the bottom sequence (corresponding to the most remote homolog) until a stopping criterion is reached. The stopping criterion is based on Neff, a statistic previously used for this task [ 1 , 6 , 7 ]. Neff is defined as the total number of different amino acids in a given column of a profile. Our stopping criterion was that Neff must be less than 8 in all non-gapped positions in profile, where non-gapped positions are defined as those with a gap content of less than half. Profile-profile matching We use the program COMPASS [ 2 ] to perform the profile profile matching. COMPASS performs a local alignment of a query profile to each member of a database of profiles. COMPASS uses a generalisation of PSI-BLAST profile-sequence scoring to score similarities between profiles and estimate the statistical significance of the score of the local alignment. Assessing performance To assess the performance of profile-profile matching, each domain of each of the 16 superfamilies was used as a query and its sequence profile was matched against a library of sequence profiles representing the dataset. A profile database was then created using the 543 profiles. When matching the profile of domain i of superfamily j , ( ), the sequence profile corresponding to was not included in the sequence profile library. This procedure was carried out twice: firstly with the full profiles, and the again with the trimmed profiles. We use ROC 10 as a statistic that describes the performance of the profiles for a particular super-family. ROC n is defined as , where T is the total number of true hits possible and t i is the number of true positives with a score better than the ith false hit. Variance in the ROC 10 statistic was calculated using the method given in [ 10 ]. Structural diversity of superfamilies To evaluate the structural diversity within each superfamily, each member of a superfamily was structurally compared to every other member. For all the domains in a superfamily we perform pairwise structural alignments using the program SAP [ 11 ] to all other domains. Since these domains do not share more than about 10% sequence identity, we would expect that they effectively capture the extent of structural variation within the superfamily. We obtain an average measure of structural similarity (root mean square deviation, RMSD) for each of the 16 superfamilies. Structure based multiple alignments To create a structure based multiple alignment of a superfamily, we first made all pairwise structural comparisons between all pairs within a superfamily using SAP [ 11 , 12 ]. We then created a T-Coffee [ 13 ] library for each pairwise comparison, where the score between two equivalenced residues is i and j at positions x i , x j in the superposition, is defined to be ((1 + RMSD )(1 + \| x i - x j \|)) -1 . A detailed explanation and analysis of this method is given in [ 14 ]. Conservation measure We used the Taylor Venn diagram [ 15 ] to assign residues in a column of the multiple alignment to a given set. The sets are overlapping and they group together amino acids at differing levels of detail (eg the hydrophobic set includes aromatic [FYWH] as a subset). However, we adopted a fairly general measure of conservation and marked a position (column) as conserved if 80% of the residues at that position could be assigned to any one set. The conservation measure for a superfamily was the number of conserved positions divided by the average length of domains in our dataset belonging to that superfamily. Only those columns that contained at least 80% of positions ungapped were considered. Authors' contributions JAC carried out the benchmarking and wrote the necessary code and helped to prepare the manuscript. MASS conceived of the study, provided input into the design and refined the manuscript. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC543460.xml
516449	Could a simple surgical intervention eliminate HIV infection?	Background Human Immunodeficiency Virus (HIV) infection is a dynamic interaction of the pathogen and the host uniquely defined by the preference of the pathogen for a major component of the immune defense of the host. Simple mathematical models of these interactions show that one of the possible outcomes is a chronic infection and much of the modelling work has focused on this state. Bifurcation However, the models also predict the existence of a virus-free equilibrium. Which one of the equilibrium states the system selects depends on its parameters. One of these is the net extinction rate of the preferred HIV target, the CD4+ lymphocyte. The theory predicts, somewhat counterintuitively, that above a critical extinction rate, the host could eliminate the virus. The question then is how to increase the extinction rate of lymphocytes over a period of several weeks to several months without affecting other parameters of the system. Testing the hypothesis Proposed here is the use of drainage, or filtration, of the thoracic duct lymph, a well-established surgical technique developed as an alternative for drug immunosuppression for organ transplantation. The performance of clinically tested thoracic duct lymphocyte depletion schemes matches theoretically predicted requirements for HIV elimination.	Dynamics of HIV infection and selection of equilibrium states Reports on the high turnover rates of HIV and its preferred target, CD4+ lymphocytes, during the latent phase of HIV infection [ 1 - 3 ] have established the virus as a prime suspect for direct demolition of the immune system. These clinical findings have also stimulated further efforts at modeling [ 4 , 5 ], and quantitative experimental observation [ 6 ]. Major journals have a preference for experimental or clinical data, and the results of mathematical modelling have not reached the broader AIDS research community. For example, the most interesting result of a simple dynamic model published several years ago [ 7 ], namely the existence of multiple equilibrium states, one of which is virus-free, has not been discussed in any of the recent publications on HIV response to anti-viral drugs. For a general medical audience it would be desirable to describe the basic features of the dynamics of HIV infection without recourse to any mathematical formulations. Dynamics implies change over time and the behavior of a dynamic system is defined by stating how the system variables affect each other during a unit of time. In the simplest model there are three system variables: (i) the number of uninfected lymphocytes, (ii) the number of infected lymphocytes and (iii) the number of free virions. The system equations describe how these populations interact. For HIV/CD4+, some of these interactions are understood and generally accepted; others are more speculative, and are subject to further study. However, even with different assumptions about these lesser known aspects, the most interesting result is little affected because it derives from the fact that the rate of infection, i.e. the number of newly infected cells in a unit of time, is proportional to the product of the number of uninfected cells and the number of free virions. This makes the resulting equations non-linear, and when the question of equilibrium is addressed, which is done by setting all rates (changes with time) equal to zero, there are two distinct solutions. One of these is free of virus, i.e. the number of virions (and infected cells) is equal to zero, whilst the other equilibrium state has non-zero values for all three populations and thus corresponds to a chronic infection. Which one of the two equilibrium states the system attains depends on the values of the system parameters. The most natural parameter to consider for switching the states is the difference between the rates at which uninfected cells are dying and proliferating. If this parameter, the net extinction rate of healthy lymphocytes, is increased above a critical value, the virus-free equilibrium is selected. This selection (bifurcation) is driven by the conditions of stability; the chronic infection state becomes unstable, i.e. any disturbance takes the system out of it, whilst the virus-free state becomes stable. Once the net extinction rate exceeds the critical value, the system finds its way out of infection. It just so happens that the amount by which the extinction rate needs to be changed, and this based on our current best estimates of other values, is quite modest – several percent of the total lymphocyte population needs to be removed daily. Depletion of lymphocytes as a therapy for AIDS, based on a population dynamic model, has been advocated by de Boer and Boucher [ 8 ]. They proposed that using a suitable immunosuppressant or CD4-killing drug in combination with an anti-viral therapy may eliminate the infection. This author has arrived at the same result independently using a population dynamics model (three populations, as described above), but also using an expanded model that includes the immune response and, in particular, Tat protein-induced apoptosis [ 9 ]. The intervention by lymphocyte depletion will work as predicted by modelling only if other parameters of the system remain substantially unaffected. This is an unlikely outcome with immunosuppressive drugs. Results from limited attempts to use them in HIV-positive patients [ 10 - 12 ] are interesting, but not very encouraging. In fact, the observed rise in CD4+ counts runs contrary to the expected effect of depletion. Activation of latent CD4+ by OKT3 and IL-2 with intention to purge the virus has also been attempted [ 13 ], but the outcome was a surprisingly prolonged depletion of CD4+ with little effect on the virus. Our knowledge of the immune system interactions seems inadequate to provide satisfactory explanations for such a response. As a further illustration of how complex different interventions with biological modifiers can be, treatments with depleting CD4 monoclonal antibody showed a preferential loss of naive T cells, but did not affect IFN-gamma secreting cells [ 14 ], providing a clue as to why such depletions did not meet expectations in treating autoimmune diseases. Depletion of lymphocytes from the lymphatic circulation The prediction of the theoretical model calls for the removal of 5 to 10 percent of the total lymphocyte pool per day. The critical value is subject to uncertain estimates of some parameters, and it does differ between the simple, three-parameter and the five-parameter, expanded model. Perhaps the best approach would be to begin depletion, monitor the response by the viral RNA, and then adjust the depletion rate. All of this suggests that some means of physical removal would be best suited. Extracorporeal blood cell separation is a possibility, but the estimate of several hours that the patient would have to spend on the machine daily for several weeks to months, is very discouraging. However, filtration of the thoracic duct lymph, where lymphocytes are present in high concentration, seems almost ideal. The technique of duct drainage for lymphocyte depletion was developed in the sixties and the seventies in order to reduce the risk of organ rejection [ 15 - 21 ]. It has found fairly broad acceptance in renal transplantation [ 22 - 25 ] where the patients would typically be treated for four weeks prior to receiving a transplant. With improved techniques of tissue matching and better immunosuppressive drugs, the thoracic duct drainage lost its appeal in transplant surgery, but it remains an interesting approach to treatments of autoimmune conditions such as rheumatoid arthritis (RA) [ 26 - 28 ]. Improvements in the biocompatibilty of implants could ostensibly even extend the impressive performance of access devices that have remained potent for hundreds of days [ 29 ]. The number of lymphocytes removed from RA patients by thoracic duct filtration [ 29 ] is in the range of modelling predictions for elimination of the virus (on the order of ten billion per day at the start of the treatment). An alternative to removal of lymphocytes by duct drainage or filtration is their diversion from the lymphatic system into the gastro-intestinal tract, which has been demonstrated in experimental animals [ 30 - 32 ]. Cells are killed while the precious protein is recycled, avoiding the problem of protein loss by drainage. There is no evidence that HIV could survive gastric passage. The drawback of such a procedure would be in the difficulty of controlling the number of lymphocytes removed. This may not be such a serious limitation, provided the critical value is exceeded. The rate of lymphocyte removal then simply determines the duration of the treatment and the reduction in the number of lymphocytes the patient will experience. This, of course, is an issue that needs careful consideration. Depletion of lymphocytes will cause a transient reduction of their pool (with counts predicted to drop to a few hundred CD4 lymphocytes/microliter), and thus affect the general immune competence. The intervention by depletion should be done as early as possible when the rates of removal necessary are lower and the total pool is less reduced. Concluding remarks Unfortunately, theoretical predictions of system dynamics are not very encouraging for the prospects of HIV vaccines. In principle, the vaccination primes the system for a faster, stronger response, including proliferation of the responding lymphocytes. As the same cells are targets for the virus, the system moves away from the stability condition for the virus-free equilibrium. Apoptosis of uninfected CD4+ lymphocytes in HIV infection is an appropriate response (for the host), albeit insufficient, since the cause of apoptosis is Tat protein produced by only the infected cells themselves. This prevents the system from eliminating the virus because the apoptotic signal weakens along with the infection. This suggests a possibility for a pharmacological intervention based on Tat protein that could sustain the apoptotic signal without introducing molecular modifiers with potentially broader effects. If vaccinations were to work, upon entry of the pathogen, they should provoke apoptosis of lymphocytes, not their proliferation. Until such discoveries are made, and to test perhaps their ultimate potential, a simple surgical intervention to allow for removal of lymphocytes merits further investigation. Dangers posed to the patient would be significant, both due to morbidity of the procedure itself, and the expected, but difficult to precisely predict cumulative effects on immunocompetence. An attractive aspect of using physical means of depletion is the possibility to terminate the treatment instantly and completely, as soon as any major deviations from the expected response would arise, indicating a failure of the model and alarming for unexpected risks. Competing interests None declared.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC516449.xml
519008	For Gene Activation, Location Matters	null	Multicellular organisms contain a complete set of genes in nearly all of their cells, each cell harboring the potential to make nearly any protein in their genome. The same holds true for a single-celled bacterium or yeast. Yet a cell activates only a fraction of its genes at any given time, calling on a number of different mechanisms to activate the right genes at the right time. To metabolize sugar, for example, a cell needs to synthesize proteins involved in sugar metabolism, not protein repair, and vice versa. In a new study, Jason Brickner and Peter Walter report a mechanism for gene activation that depends on shuttling DNA to a particular location within the nucleus. In organisms whose cells have nuclei (eukaryotes), genomes lie within the nucleus (called the nucleoplasm) but also interact with the inner nuclear membrane. Transcription factors activate gene expression by binding to a promoter sequence in the gene's DNA. The physical structure of DNA—which is packaged with proteins into chromatin—affects gene expression by controlling access to DNA. Where chromatin exists in the nucleus also influences gene expression. Heterochromatin—stretches of highly condensed chromatin—typically lines the nuclear periphery, and genes bundled into heterochromatin are typically silent. Active transcription generally occurs in the less condensed euchromatic regions. But since euchromatic regions are also silenced when they associate with heterochromatin along the membrane, it is thought that delivering chromatin to the nuclear periphery regulates transcriptional repression. Brickner and Walter, however, found evidence of the opposite effect—recruiting genes to the nuclear periphery can promote their activation—suggesting that nuclear membrane recruitment plays a much broader role than previously suspected in gene regulation. The INO1 gene (green) is recruited to the nuclear membrane (red) upon activation To explore the consequences of chromatin location, the authors focused on a yeast gene called INO1, which encodes inositol 1-phosphate synthase, an enzyme involved in phospholipid (fat) biosynthesis. INO1 is also a target gene of the “unfolded protein response,” which is triggered when unfolded proteins accumulate in the endoplasmic reticulum, a subcellular organelle where secreted proteins are folded. The INO1 gene contains a regulatory element (called UASINO) within its promoter region that responds to inositol availability. Genes under the control of this element are transcriptionally repressed by a repressor, Opi1, and activated by two transcription factors, Ino2 and Ino4. The presence of unfolded proteins sets off a chain of events to relieve Opi1 repression and allow activation of INO1 . Through a series of genetic and biochemical studies, Bricker and Walter show that Ino2 and Ino4 are always bound to the INO1 promoter. Opi1 associates with the chromatin, restricting the INO1 locus to the nucleoplasm and repressing transcription. Induction of the unfolded protein response bumps Opi1 off the chromatin and, with Opi1 out of the way, INO1 travels to the membrane and transcription proceeds. Crucially, the authors show that artificial recruitment of INO1 to the nuclear membrane can be enough to activate the gene. There are several mechanistic aspects of this model to figure out still, but Brickner and Walter argue that for INO1, gene recruitment to the nuclear membrane promotes its activation. In light of other recent work, this phenomenon may be emerging as a more general mechanism for regulating eukaryotic gene expression.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC519008.xml
555570	Patient preferences for notification of normal laboratory test results: A report from the ASIPS Collaborative	Background Many medical errors occur during the laboratory testing process, including lost test results. Patient inquiry concerning results often represents the final safety net for locating lost results. This qualitative study sought to identify, from a patient perspective, specific preferences and factors that influence the process of communicating normal (negative) laboratory test results to patients. Methods We conducted 30-minute guided interviews with 20 adult patients. Patients were recruited from two practice-based research networks in Colorado that were participating in a medical errors study. A semi-structured interview elicited the participant's experience with and preference for laboratory test result notification. Quantitative descriptive statistics were generated for demographic and preference data. Qualitative results were analyzed by a team of experienced qualitative researchers using multiple styles of qualitative analyses, including a template approach and an editing approach. Results Ninety percent of participants wanted to be notified of all tests results. Important issues related to notification included privacy, responsive and interactive feedback, convenience, timeliness, and provision of details. Telephone notification was preferred, followed by regular mail. Electronic notification was perceived as uncomfortable because it was not secure. While 65% preferred being notified by a provider, participants acknowledge that this may be impractical; thus, they wanted to be notified by someone knowledgeable enough to answer questions. Participants do not normally discuss their preferences for test result notification with their providers. Conclusion Privacy, responsive and interactive feedback, convenience, and timeliness with detailed information may be critical for patient satisfaction and for improving patient safety, and are features that may be incorporated into emerging communication channels.	Background Understanding how patients would like to be notified of laboratory test results is important for improving provider-patient communication, patient satisfaction, and patient safety. Data from Applied Strategies for Improving Patient Safety (ASIPS), a primary care practice-based study of medical errors, indicate a high frequency of errors in laboratory testing and patient notification[ 1 ]. Other studies in primary care show similar safety concerns with laboratory testing[ 2 , 3 ]. Preliminary ASIPS data show that laboratory errors were commonly discovered by patient-initiated requests for results. A study of patient notification of emergency department test results found that passive notification – the "no news is good news" approach – was ineffective and potentially dangerous[ 4 ]. Thus, ensuring that patients receive all lab results – even normal results – may be an important and last safety net for identifying missing or mishandled laboratory results. Patients want to be notified of all test results, regardless of whether the results are abnormal [ 4 - 8 ] A few studies have explored patient's preferences for being notified of specific test results, reporting that patients prefer to be notified by telephone for breast biopsy results[ 9 ] and normal mammograms[ 6 ], and wish to receive timely, detailed, written information for normal pap smear results[ 10 ]. We found no studies from primary care concerning notification procedures and patient preferences. To inform future interventions in this area, we elicited patients' thoughts, needs, and preferences regarding test result notification. Methods Sample This study was conducted within the Colorado Research Network (CaReNet) and High Plains Research Network (HPRN), two primary care practice-based research networks. CaReNet practices are located mostly in urban / suburban cities in Colorado; HPRN practices are in rural northeast Colorado. We intentionally used these settings as the most optimal example of the setting (primary care clinics) in which we would see the need for normal lab result notification. We purposively sampled study participants based on emerging themes from our analysis. Thus, we intentionally recruited participants who were 18 years of age or older, able to speak and understand English or Spanish, and who had at least one laboratory test at a participating practice within the last year. Laboratory tests were defined as blood or urine tests, pap smears, and biopsies. The aim of our strategy was not to maximize generalizability, but rather to understand the context and conditions under which normal lab result notification does or does not occur. We recruited to the point of saturation or replication of data[ 11 ]. All final 20 participants spoke English and gave verbal telephone consent. Procedures Patients were recruited via posters and business cards placed in 12 primary care practices participating in the ASIPS study. ASIPS was a multi-institutional, primary care practice-based project to collect, codify, and analyze data on medical errors[ 1 , 12 ]. Interested patients called an automated call center and left their names and telephone numbers. A research assistant called patients to determine eligibility, obtain consent, and schedule a 30–45 minute interview. An interview was completed by telephone (19 cases) or face-to-face (1 case) and was audio taped. This study was approved by the University of Colorado Health Sciences Center's institutional review board. Measures Demographic information We collected the patient's age, gender, race, ethnicity, highest level of education, if they had a permanent home address, and access to the Internet and e-mail. Patients were asked if they had personally received results of a test by message left on answering machine, through phone conversation, mail, e-mail, automated telephone call-up system, or via web-based system. Patients ranked these notification methods by their preference. Semi-structured interview The interview began with questions about the patient's most recent experiences with test result notification (who, what, when, etc.). The interview then shifted to preferences of notification and patient-doctor discussion about notification preferences. Inquiry also elicited patient factors that may affect test result notification. An in-depth interview provides a narrative understanding of how particular individuals arrive at their experience. Our purpose was to construct a meta-narrative of the interviewees' many stories. This on-going interpretive process informed each subsequent interview in an iterative fashion. For example, during early interviews it appeared that different preferences might be expressed by people with different educational levels. We then stratified our subsequent sample by educational level (more than a high school education vs. high school education or less). Data analysis We used mixed methodology to analyze the data. Quantitative descriptive statistics (frequencies, proportions, etc.) were generated for our demographic and preference variables. All coding and analysis was done by a three-member team that included a physician, a doctorate researcher experienced in qualitative methodology, and a professional research assistant. The use of a multidisciplinary team approach helped limit any personal biases, subjectivity, and preconceptions as well as enhanced our reflexivity process[ 11 ]. A commitment to reflexivity resulted in ongoing assessment of subjectivity by the team in all steps of the analyses[ 13 ]. Our qualitative analysis was initially guided by multiple styles of qualitative analyses including an initial template approach as outlined by Crabtree and Miller[ 11 ] using already published literature on lab result notification as guides. We created an initial a priori template of codes (code manual) and then applied it to the text data. This approach was then followed by editing approach, a technique derived from grounded theory, to identify emerging themes. Members of the research team independently coded a number of pages of the same text to test for both the utility and appropriateness of the codes and the intercoder reliability, which measures correspondence between two or more coders' assessments (84%)[ 14 ]. Achieving an acceptable level of intercoder reliability is important for providing basic validation of coding scheme. We modified the code manual to correct for discrepancies and deficiencies. Research team members then identified and sorted segments of text, which allowed further abstractions and emerging codes. ATLAS.ti software facilitated the iterative coding and sorting process[ 15 ]. We further sorted related text, producing connections and interpretations. Results In the end, we found no differences qualitatively or quantitatively across participants' educational levels. Thus, all results are reported as a single group. Most (75%) participants were female (see Table 1 ); 90% indicated they expected to be notified of all test results, regardless if normal or abnormal. Table 1 Demographics of participants Demographic Characteristics TOTAL % Female 15 75% Race White 15 75% Black 4 20% Asian 1 5% Age ≤ 30 4 20% 31–40 0 0% 41–50 8 40% 51–60 5 25% 61–70 2 10% ≥ 71 1 5% Education Some or graduate of high school 10 50% Some college 5 25% College graduate 1 5% Post graduate education 4 20% Have access to e-mail & Internet 19 95% Location of frequent access to e-mail & Internet Home 9 45% Library 4 20% Multiple sites 5 25% When exploring the possible modes of lab result notification (phone, message left on an answering machine, mail, e-mail, automated telephone call up system, and web-based systems) we found no differences in preferences by age groups, educational levels, or access to e-mail and the Internet (table 1 ). Many participants who had access to the Internet or e-mail were open to the idea of retrieving results via this medium only if the security was assured; however, most patients felt that web-based systems and e-mail are not secure. Only a minority of patients interviewed were willing to try an automated telephone call, e-mail, or web-based system. Patients' preferences seemed to reflect their most recently experienced method of notification. Table 2 shows total number of patients who experienced a particular method of notification within the past year and their preferred method of notification. Most patients experienced and preferred phone or mail notification. All interviewees stated that a message left on an answering machine was not appropriate. Table 2 Participants' experience with and preference for notification methods Selected Methods Experienced Method % (n = 20) Preferred Method % (n = 20) Message left on answering machine 9 45% 0 0% Telephone 16 80% 12 60% Mail 11 55% 3 15% Automated telephone call-up 0 0% 2 10% E-mail 0 0% 2 10% Web-based system 0 0% 1 5% We identified three emerging themes: (1) Important Characteristics of Notification: most notable factors influencing patient preferences in notification; (2) Patient/Provider Discussion: the lack of communication between patients and providers around notification preferences; and (3) Communication Frustration: challenges encountered during attempted communication between the patient and the practice regarding notification of their results. Below we briefly describe these themes with illustrative quotations from the participants. Important characteristics of notification Important factors that defined patients' concerns around notification were always being notified of results, timeliness, details of the results, responsive and interactive feedback, who should provide the notification, convenience, and assured security/confidentiality. Always notify Not surprising, almost all patients responded that they wanted to be notified of all results. The "no news is good news" approach is unacceptable to patients. "Obviously there was a reason to have that diagnostic test, so I'd at least like to know whether it was normal or what." "To me, no news is worrisome." Timeliness Patients wanted to receive their results in a timely manner – shortly after the physician or provider receives the results. "Let me know right away. Don't keep me hanging. Do the test on Friday and if I don't know till Tuesday, I want to know Monday morning. As soon as you find out the results, you let me know the results because this is my body." Details of test results The amount and detail of information is important in providing the context in which the patient can interpret the results. "I would like to know what normal means in relation to the general population, so I would certainly like some reference ranges...If there weren't any reference ranges, then I would certainly like to know that a test...came back negative and what negative meant." Responsiveness & interactive feedback The test result was only half of the information participants want. They also wished to discuss what the results mean for them. In some cases, patients are left wondering about the "next steps." A patient may feel confused if someone is not available during the notification process who can discuss what the test means. "Well, the information on what I can and what I can't do, you know. I mean I don't know what I can do at this point." "The thing I do like is that we can actually talk about the numbers and I can see where it's at because he just gives me, we just look at the sheet together...I like that." Who should notify Most patients recognize that providers are too busy to attend to all normal test results. They were comfortable having someone else notify them, but preferred that this person be knowledgeable enough to answer questions. Many patients indicated that notification by receptionists, who they felt were not knowledgeable enough to answer questions, is unacceptable. When asked specifically the preferred role of a notification person the responses were: 65% provider and 15% nurse; 20% were not concerned with who notifies. "Ok, this test result is normal but I still have this pain, what alternative do I have now. Where do I go from here and a physician would be the best person to be able to explain it to me, rather than a physician assistant or a nurse or an administrator or something like that." "Well, it doesn't have to be the actual doctor. It could be the RN...Somebody who knows about what is going on and if I have a question I could ask that person." Convenience Patients identified convenience as important to their satisfaction. Calling the office for results can mean long waits to reach a person who notifies them of their result and then longer waits when the results prompt a patient question that cannot be immediately answered. "That way (using web-based system) I could do it at anytime and it seems more personal and confidential to me because...you can draw up that information at any time when you're ready." "That's why the mail is so good because I always get the mail everyday." Security/confidentiality The most persistent issue we uncovered was a patient's privacy and assured confidentiality of test results and diagnoses. Participants seemed hesitant to experiment with alternative notification methods (i.e., web-based methods) if they perceived a possibility of a breach in this trust. "Who wants the public to read what their values are?...Even if it's normal, I'd rather have it personalized in a sealed envelope." Provider discussion Most patients assumed that their office used a specific system for notification; however, they were not aware of the details of this system. Often patients were told to call for results if not received within specified time, leaving the patients to close the feedback loop. Other patients were told to rely on "no news is good news," although they were uncomfortable with this policy. The majority of patients indicated that they had not discussed their notification preferences with their provider. "No, I haven't. I just assumed that was normal and customary procedure...That they only notify you if something is wrong." "I didn't know they were just going to send me a letter. In the past, I've had the doctors call me. Well, they automatically call [ed]." Communication frustration Two areas of frustration related to communication were identified: lack of follow-through and confusion within the office. Follow-through Communicating how the provider will notify the patient is important, but equally important is follow-through. Unmet expectations result in patient frustration. "I told him that he could call me, or the nurse. Either one would be ok, but...it doesn't happen. Even though I asked them face to face, it still hasn't happened." Office confusion Patients are also frustrated and worried when they try to complete the feedback loop, but find that the practice is unable to provide them the information they need. "I have to sometimes call in to find out about my results...I wasn't actually notified of the results...so obviously it was my responsibility. I felt it was my responsibility anyway. But...they [the results] seemed to have [been] misplaced. The parties concerned didn't seem to be aware that I had had a particular test and so they couldn't provide me with information...It wasn't until I went back recently and asked about that result, that I was told it was normal." Discussion Our results reinforce other literature suggesting patients want timely[ 9 ] and detailed[ 10 , 16 ] information, and want to be notified of all test results, even if normal[ 5 , 7 ]. These results also support the idea that patients prefer clinicians telephone them with lab results[ 6 ]. We, other researchers[ 17 , 18 ], and the patients in our study recognize that this plan is often too costly to be practical. A number of our findings, however, suggest that more than preferring a particular channel of communication, patients prefer a specific manner of communication, features of which could be incorporated into newer communication channels. For example, our participants overwhelmingly preferred a personal telephone call – but only from someone who was knowledgeable enough to answer their questions. They wanted responsive and interactive feedback, personalized to their situations. Many of the patient identified characteristics of notification could be more easily incorporated into a system that allowed for asynchronous communication (communication that doesn't rely on immediate person to person transfer of information.) Nonetheless, few of our participants were willing to try the computerized asynchronous communication methods we asked about: an automated telephone call, e-mail, or web-based system. This finding is similar to others[ 7 ], although Ridgeway and colleagues report that patients used and were generally satisfied with an automated phone call up system[ 19 ]. Our patients said they would be willing to try a web-based system if they were convinced of security and confidentiality, suggesting that concerns with web systems lie not with the technology, itself, but with the privacy of the information. Notably, privacy was one reason patients wanted a personal phone call. Thus, we suspect that their stated preferences for telephone calls are related to the perceived high level of privacy and interaction available through a synchronous telephone call, while their distrust of websites and e-mail indicate underlying discomfort with the perceived privacy of the technology. Recognizing these tradeoffs may be useful for those who are designing systems to provide test result notification to patients. Our patients emphasized the importance of receiving results in a timely fashion. Timeliness is a critical feature of notification systems that can significantly affect patient safety; timely recognition of mishandled or misplaced results will increase the practice's ability to correct or mitigate an error. However, timeliness is not an inherent feature of patients' preferred channel of communication: a telephone call. In our experience, providers' and patients' hectic schedules often mean it can take days for successful telephone contact between providers and patients. Again, our patients' focus on timeliness suggests that they are not wedded to the concept of telephone communication; rather, they prefer the perceived timeliness of communication by telephone. Similarly, our participants indicated that convenience was important to them. Again, waiting for a telephone call is not intuitively convenient, though the dramatic increase in cell phones may help alleviate this problem. Perhaps our study participants could not envision a convenient communication method other than phone calls that provide secure, personalized, interactive communication. A traditional mail-based system (a low-tech asynchronous communication system) was ranked second highest among preferences for notification. This finding detracts from our assumptions that patients focus on notification methods that are timely and interactive; however, it supports our idea that patients want convenient, private, personalized information. Perhaps the three patients who preferred mail notification were more concerned with privacy and convenience than with timeliness and interactivity. Further study is needed to elucidate these findings. Finally, we found that patients do not discuss with their provider their preferences for notification. Our patients indicated that it never occurred to them that their health care provider lacked a standard procedure for communicating test results to patients. Our findings may be a manifestation of poor communication between patients and providers, which has been shown to be a related to poor patient outcomes and safety issues[ 20 ]. More study is needed to explore this example of poor interpersonal communication. A potential limitation of this study relates to the recruitment, which was limited to patients who had access to call our research line after seeing an advertisement. However, qualitative inquiry rarely uses random sampling. Rather, samples are selected more purposefully and not by the need to generalize or predict but by a need to create deeper understanding or meaning[ 11 ]. Thus, studying the narratives of people who called our research line to talk about their experiences is appropriate and adequate. Additionally, we sampled to the point of redundancy; no new information was coming forth by the end of 20 interviews. A second limitation may be a gender bias. Most of our respondents were female. Male experiences may differ and may not be represented by our results. However, considering that the majority of health care utilizers are women, and women are critical in maintaining the health and health care consumption within families [ 21 - 23 ] their experience becomes crucial for primary care service delivery. Finally, the most significant limitation of this study relates to the participants' lack of experience using a web-based or automated telephone system to receive test results. While we could discuss how patients' preferences may possibly be met by such a system, we could not comment on how previous experiences might affect their preferences. Conclusion The results of this study provide us with a better understanding of how patients experience notification of laboratory tests within the primary care setting. Notifying patients of test results is important for laboratory information management, and ultimately, patient safety. We believe patients can play an important role in ensuring that laboratory tests results are obtained and reviewed by providers. Asking for all laboratory tests results is a recommended strategy[ 24 ] for improving patient safety that draws patients into the feedback loop and provides a last safety net for identifying misplaced or mishandled results. Learning patients' preferences for result notification is merely one step in this important patient safety area. Competing interests The author(s) declare that they have no competing interests. Authors' contributions All authors contributed to the study design and conceptualization, discussed the drafts of the paper, and read and approved the final manuscript. Additionally: DB developed the study idea and conducted the data analysis. JQ conducted the interviews. CD provided technical assistance in protocol development and data analyses, and contributed to the development of the manuscript. ES contributed to the development of the manuscript. WP obtained funding for the study, helped develop the study methods, and contributed to the development of the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555570.xml
524362	The vaa locus of Mycoplasma hominis contains a divergent genetic islet encoding a putative membrane protein	Background The Mycoplasma hominis vaa gene encodes a highly variable, surface antigen involved in the adhesion to host cells. We have analysed the structure of the vaa locus to elucidate the genetic basis for variation of vaa . Results Mapping of vaa on existing physical maps of five M. hominis isolates by pulsed field gel electrophoresis revealed that vaa is located in a genomic region containing the majority of other characterized membrane protein genes of M. hominis . Sequencing of an 11 kb region containing the vaa locus of M. hominis isolate 132 showed the presence of conserved housekeeping genes at the borders of the region, uvrA upstream and the hitABL operon downstream to vaa . Analysis of 20 M. hominis isolates revealed that the vaa upstream region was conserved whereas the downstream region was highly variable. In isolate 132 this region contained an open reading frame (ORF) encoding a putative 160 kDa membrane protein. Homologous ORFs were present in half of the isolates, whereas this ORF, termed vmp (variable membrane protein), was deleted from the locus in the remaining isolates. Compellingly, the conserved upstream region and variable downstream region of vaa correlates with the genetic structure of vaa itself which consists of a conserved 5' end and a variable 3' end containing a variable number of exchangeable sequence cassettes. Conclusion Our data demonstrate that the vaa locus contains a divergent genetic islet, and indicate pronounced intraspecies recombination. The high variability level of the locus indicate that it is a chromosomal 'hot spot', presumably important for sustaining diversity and a high adaptation potential of M. hominis .	Background The mycoplasmas are wall-less prokaryotes characterized by small genomes (580 – 2200 kb) and a low G+C content, generally below 30%. They are the smallest self-replicating organisms known with cell diameters normally in the range of 0.3–0.8 μm [ 1 ], and are observed as parasites of insects, plants, animals and humans with strict host specificities. As a consequence of the direct exposure of proteins located on the surface of the cytoplasmic membrane to the surrounding environment, antigenic variation of surface proteins is observed among mycoplasmas. The often chronic nature of mycoplasmal infections is thought to be a consequence of evasion of the humoral immune response by the variation displayed by these coat proteins [ 2 ]. Mycoplasma hominis is an opportunistic human pathogen observed as a commensal of the urogenital tract. Primarily, urogenital infections giving rise to spontaneous abortions, pelvic inflammatory disease, and acute pyelonephritis have been associated with M. hominis , but extragenital infections resulting in infant meningitis, arthritis, and septicemia have been reported [ 3 ]. M. hominis is a very heterogeneous species as measured by a pronounced antigenic variation [ 4 - 7 ]. The molecular basis for antigen variation of M. hominis surface proteins has been elucidated in some cases. The large membrane protein ( lmp ) gene family displays size variation by insertion/deletion of intragenic repeats of approximately 500 bp. The lmp genes are arranged in two clusters, lmp1-2 and lmp3-4 in the M. hominis genome of most analysed isolates with a distance between the clusters of more than 110 kb [ 8 ]. At least one member of the lmp family is expressed in each of the M. hominis isolates tested and decrease in the number of repeats were found to correlate to the amount of spontaneous agglutination of M. hominis cells [ 9 , 10 ]. The vaa (variable adherence-associated) gene encodes a size and phase variable M. hominis adhesin [ 11 - 14 ]. Phase variation is accomplished by variation in the number of bases in a poly-A tract situated in the 5'-end of the gene [ 12 ]. This is presumably achieved by slipped strand mispairing with a frequency of 10 -3 –10 -4 . In the ON-state 8 adenines are observed in the poly-A tract, whereas 7 or 9 results in the out-of-frame OFF-state [ 12 ]. A single vaa gene is present in each M. hominis isolate [ 15 ]. The size of Vaa observed in different isolates ranges from 28 kDa to 72 kDa. This size variation is the consequence of a variable number of homologous, exchangeable cassette sequences located in the 3' end of vaa [ 11 , 13 ]. Each cassette encodes approximately 110 aa containing a coiled-coil motif and 1 to 5 cassettes have been observed in different Vaa proteins. The Vaa protein is a rod-shaped, monomeric protein and the cassettes are presumed to form homologous, 'spike'-formed binding domains arranged in parallel in the three-dimensional structure [ 16 ]. Based on the cassette composition, 6 distinct vaa gene types have been observed in more than 100 analysed clinical isolates [ 13 , 14 ]. The mechanism behind this variation is unknown, but duplication/deletion of cassettes followed by divergence of cassette sequences has been suggested [ 14 ]. Comparison of the homology between cassettes showed that the cassette sequences could be divided arbitrarily into 5 cassette types based on sequence identity. Analysis of the cassette organization in different isolates revealed that intraspecies recombination resulting in the exchange of cassette sequences could be an alternative mechanism for variation of Vaa [ 13 ]. To obtain a better understanding of the genomic basis for variation of vaa and variation mechanisms in M. hominis in general, the vaa locus was characterized by mapping of the genomic position in five isolates and sequencing of a 11 kb region containing the vaa gene from isolate 132. Furthermore, the vaa locus of 20 M. hominis isolates was investigated by PCR and sequencing. In contrast to the more conserved vaa upstream region this analysis revealed that the downstream region also exhibits major variation caused by insertion/deletion and sequence variation of a large ORF encoding a putative membrane protein. Thus the vaa locus seems to constitute a 'hot spot' for variation in the M. hominis genome. Results Genomic localization of the vaa gene The vaa gene was mapped on exsisting physical and genetic maps of 5 M. hominis isolates: 132, 4195, 7488, PG21, and 93 (Fig. 1A ) [ 8 ]. Chromosomal DNA from the isolates was digested by the restriction endonucleases Sma I, Bam HI, Xho I, Sal I, and Apa I and the fragments were separated by pulsed field gel electrophoresis (Fig. 1B ). The fragments were transferred to nitrocellulose and hybridized with three (α- 32 P)dATP-labelled DNA fragments representing different parts of selected vaa genes (see materials and methods). All probes hybridized to a single fragment in all digests, corresponding to the same region of the genome for all 5 isolates (Fig. 1A and 1B ). The fragments were located in a genomic region near the gyrB gene (Fig. 1A ). A number of other M. hominis genes encoding membrane proteins ( p75 , p120 and p120' , see Fig. 1A ) were also positioned in this region of the genome [ 8 , 17 , 18 ]. To further analyse the variability of the vaa locus, restriction endonuclease analysis was performed. Southern blotting of Hin dIII and Eco RI cleaved genomic DNA separated with ordinary agarose gel electrophoresis from the 5 isolates using probe 2 was made (Fig. 2A and 2B ). The probe recognized a band of 6.0 kb in the isolates 132 and 4195 and a band of 6.3 kb in isolates 7488, PG21, and 93 in the Hin dIII digest (Fig. 2A ). The band size difference between the isolates could be attributed to the fact that the Hin dIII site relative to the ATG start codon in the vaa genes of isolates 7488, PG21, and 93 was located 243 bp further upstream compared to the Hin dIII site in isolates 132 and 4195. This indicates that the Hin dIII site upstream vaa is conserved. Bands of diverging size were observed in the isolates for the Eco RI digest using this probe (data not shown). The band differences observed could be explained by the presence or absence of an Eco RI site in the variable vaa gene. Using a probe comprising the cassette region of the vaa category 3 ( vaa- 3) gene (probe 4) band size variation was observed in the 5 isolates for both enzymes (Fig. 2B , data not shown). The results of the Southern blotting experiments confirmed that vaa is present as a single copy in the genome and indicated sequence variation in the vaa locus. Amplification and sequencing of the vaa locus of M. hominis 132 As the mapping and restriction endonuclease analysis of vaa indicated a variable locus, we decided to sequence this genomic region of the M. hominis genome to determine the cause of the variability. A Hin dIII/ Eco RI restriction map of the vaa locus of isolate 132 was made using the Southern blotting results (Fig. 3A ). The sizes of most of the Hin dIII and Eco RI fragments including the up- and downstream regions of vaa were 4.2 kb or below. These fragments were thus suitable for amplification by inverse PCR. The genomic DNA was cleaved by Hin dIII or Eco RI and religated. Outward pointing oligonucleotide primers located in the vaa gene were used in PCR on the religated template in order to amplify regions outside the gene (Fig. 3A ). PCR products of the expected sizes were observed and sequenced bidirectionally. A contig of approximately 8 kb was assembled. In order to expand the contig, a new round of inverse PCR was performed using new primer sets located in each end of the contig. The upstream region was expanded using the Hin dIII cleaved and religated template. To expand the downstream region, chromosomal DNA cleaved with Bgl II and religated was used as template. Sequencing of the expanded regions revealed that an ORF showing high similarity to the uvrA gene by database search was located approximately 5 kb upstream to vaa . The annotation of this ORF as uvrA , the gene encoding excinuclease ABC subunit A, was based on homology alone as this gene has not yet been characterized in mycoplasmas. Furthermore, the conserved hitB gene, part of the hitABL operon, was identified in the opposite end of the vaa locus (Fig. 3B ). The hitABL operon comprises three highly conserved genes. The hitAB genes encode the P60 and P80 proteins, respectively. P60 and P80 form a membrane associated complex that interacts by an unknown mechanism with the evolutionary conserved, cytoplasmic HinT (histidine triad nucleotide-binding) protein encoded by hitL . This system was previously characterized in M. hominis by Henrich and coworkers [ 19 - 21 ]. The hitABL operon was located almost 5 kb downstream to the vaa gene of M. hominis 132 (Fig. 3B ). Thus, the vaa locus is bordered by highly conserved housekeeping genes. A bidirectionally sequenced contig of 11.3 kb comprising the vaa locus was assembled (Fig. 3C ). Gene organization of the vaa locus of M. hominins 132 Analysis of the contig harboring the vaa locus revealed a number of open reading frames (Fig. 3B ). At the border of the sequenced upstream region the uvrA gene, represented by 878 bp of the 5' end of the gene, is located. Between uvrA and vaa five ORFs, numbered 1 to 5, were detected, ORF2 encoding a putative protein of only 6 kDa (Fig. 3B ). This ORF was included as proteins of similar size has been detected in other bacteria [ 22 ]. The transcriptional direction of these ORFs and uvrA was opposite that of vaa . The ORFs were positioned closely, ORFs 4 and 5 had a 16 bp intergenic region, and ORFs 2 and 3 had an intergenic region of 22 bp. ORFs 3 and 4 showed an overlap of 35 bp. Thus, ORFs 1 to 5 might constitute an operon. No obvious stem-loop structures with a putative rho-independent transcriptional termination function were observed immediately downstream to any of the ORFs. The hypothetical genes were employed in database searches. The ORF adjacent to uvrA , (ORF1), encoding a hypothetical 35 kDa protein, showed high similarity to a range of hypothetical proteins of similar size in the database. All of these proteins contained a HAD hydrolase superfamily motif. The highest similarity was to a hypothetical protein of Mycoplasma pulmonis (31% identity, 54% similarity in 268 aa). No significant homologues were found for ORFs 2 to 5. ORF5 was shown to encode a hypothetical protein containing an N-terminal signal peptide with a signal peptidase II cleavage site typical of prokaryotic prolipoproteins and may thus encode a lipoprotein having a size of 29 kDa and a pI of 9.6. Interestingly, a transmembrane helix was predicted in the C-terminal part of this putative lipoprotein using the program TMHMM (membrane probability of 1 for aa 243 to 252) [ 23 ]. The downstream region of vaa revealed the presence of a large open reading frame of 4 kb, ORF6, encoding a hypothetical protein with a molecular weight of 160 kDa (Fig. 3B ). A secretory signal peptide was identified in the N-terminal part of the putative protein using the program SignalP [ 24 ]. A signal peptidase I cleavage site was identified between A24 and S25 (mean S value of 0.956 for aa 1–27), but as no gene encoding signal peptidase I has been observed in most of the sequenced mycoplasma genomes, the protein is most likely not processed [ 2 , 17 ]. A homopolymeric tract of 16 thymidine residues (poly-T tract) was located 77 bp upstream to the ATG start codon of ORF6, and a putative rho-independent stem-loop terminator structure (ΔG = -16.2 kcal/mol) was observed 23 bp downstream of ORF6. The deduced aa sequence of ORF6 was used in a database search and intriguingly, high similarity to the Lmp-1 and Lmp-3 proteins of M. hominis was found, the highest similarity was to Lmp-1 (28% identity and 48% similarity in 1241 aa, see additional file 1 ). Surprisingly, homology was also found to the myosin heavy chain protein of the slime mold Dictyostelium discoideum (20% identity and 40% similarity in 1083 aa), and other myosin proteins in the database. In the region between ORF6 and the hitABL operon, a tRNA (His) gene was identified by database search (Fig. 3B ). The highest similarity observed was to the tRNA (His) of Bacillus subtilis . Intriguingly, the 5' end of the gene displayed a high similarity to the orthologue from Streptococcus pneumoniae (94% identity from bp 10 to 45), even higher than to the corresponding region in Bacillus subtilis (92% identity) and Mycoplasma pneumoniae (86% identity). The transcriptional direction of ORF6, tRNA (His) and the hitABL operon was opposite that of vaa in analogy to the ORFs of the vaa upstream region (Fig. 3B ). Variability of the vaa locus in 20 M. hominis isolates To examine the variability of the vaa locus, PCR was performed on 20 M. hominis isolates representing different vaa types. Using a primer located in the conserved region of vaa and a primer located in the uvrA gene, a PCR product of 5.5 kb was amplified (Figs. 3 and 4B ). All isolates gave rise to a band of identical size for the primer set (Fig. 4B ). Furthermore, PCR was performed using the primer located in the conserved region of vaa and a primer located in ORF3 or ORF5. This amplified fragments of 4 kb and 0.6 kb, respectively, in all analysed isolates (Fig. 4B ). The PCR results thus suggested that the upstream region is very conserved. Additionally, restriction endonuclease analysis of the 5.5 kb PCR fragment was made using the enzymes Alu I and Ase I, which cleaves at 5 and 8 sites, respectively, scattered over the entire fragment of isolate 132. This analysis revealed 13 and 3 digestion profiles, respectively, of the 20 isolates (data not shown). It was not possible to classify the profiles according to the vaa type or other known M. hominis groupings. Thus, despite a higly conserved organization and length of the ORFs in the vaa upstream region, there is an underlying sequence variation, presumably corresponding to the background variation level present in the M. hominis genome. In contrast, when primers located in the conserved region of vaa and hitB , respectively, were used in PCR, a pattern revealing different product sizes was observed (Fig. 4C ). The expected 5.5 kb PCR product was amplified in 5 isolates, 10 gave rise to bands of approximately 2 kb and 5 gave rise to larger bands of 7.5 and 8 kb (Fig. 4C ). The size of the 2 kb products corresponded to the deletion of ORF6. This was verified by sequencing of the products from M. hominis PG21 and 93 (Fig. 5 ). Sequencing of the 8 kb and 7.5 kb PCR products from M. hominis 7488 and 4195, respectively, revealed ORFs of 6.5 kb and 5.5 kb showing homology to ORF6 (Figs. 5 and 6 ). Because of the apparent variability of this protein, ORF6 and the corresponding ORFs of M. hominis 7488 and 4195 were named vmp (variable membrane protein). The isolates were divided into vmp groups based on the above PCR results according to the size of the vmp gene observed in the different sized downstream PCR products. The vmp gene having a size of 4 kb was named vmp category 1 or simply vmp -1, and the isolates (indicated with green numbers in Fig. 4 ) giving rise to a 5.5 kb downstream PCR product, containing the vmp-1 gene, were categorized as having a vmp-1 gene type (Fig. 4C ). Likewise, the vmp genes having a size of 5.5 kb and 6.5 kb were named vmp -2 and vmp -3, respectively, and the isolates giving rise to downstream PCR products of 7.5 and 8 kb (indicated in Fig. 4 by orange and magenta numbers, respectively) were categorized as having a vmp-2 and vmp-3 gene type, respectively (Fig. 4C ). It was not possible to design a universal vmp primer set that would amplify a fragment from all the sequenced vmp genes due to the high sequence variation observed between the genes. Instead, a primer set amplifying a 0.6 kb fragment of vmp-1 was used for PCR of the 20 isolates. Four of the five genes categorized as vmp-1 gave rise to a strong band of 0.6 kb (Fig. 4D ). The isolate 183 also categorized as having a vmp-1 gene type gave rise to a very faint band of 0.6 kb. A second primer set was designed that would amplify a 1.2 kb fragment from both vmp-2 and vmp-3 (Fig. 4E ). Again, only four of the five isolates expected gave a product. The isolate SC4 categorized as having a vmp-1 gene type also gave a faint band with the vmp-2/3 primer set. The isolate 1572B did not give a product with the primer set, but was categorized as having a vmp-2 gene type because it gave rise to a downstream PCR product of approximately 7.5 kb. Thorough examination revealed that the size of the 1572B downstream PCR product was slightly smaller than that of isolate 4195. Thus, isolate 1572B may harbor a fourth vmp type. The vmp-2 and vmp-3 genes were flanked by a poly-T tract and a stem-loop terminator structure (ΔGs of -16.7 and -15.6 kcal/mol, respectively) showing high homology of the stem regions to that observed for vmp-1 . The stem-loop structure was located approximately 500 bp downstream of the stop codon of vmp-2 but interestingly, the homology between vmp- 2 and vmp -3 extends beyond the stop codon in vmp -2. Careful analysis reveals that a poly-A tract in the 3'-end of the vmp genes has an extra (9 total) adenine in vmp -2 compared to vmp -3, which causes a premature termination of translation of the vmp -2 gene. If the extra adenine of the poly-A tract was deleted the ORF would continue for approximately 500 bp, corresponding to vmp -3, and the termination codon would be situated close the putative rho-independent transcriptional termination stem-loop structure. The remaining 10 isolates were divided into two groups based on a genetic fingerprint in the vaa - hitABL intergenic region of isolates lacking vmp (Fig. 5 ). The genetic fingerprint was an insertion/deletion in the intergenic regions downstream to vaa . The vaa-hitABL intergenic region of isolate 93 was nearly identical to the corresponding region of isolate PG21, except for a deletion of approximately 300 bp shortly after the vaa terminator stem-loop structure (Δ1, Fig. 5 ). Two isolates (PG21 and 1621) gave the 2.2 kb downstream PCR product, whereas the remaining 8 isolates gave the 2 kb downstream PCR product of isolate 93 (Fig. 4B ). The vmp type or absence of the vmp gene showed no correlation to the vaa type of the isolates. Surprisingly, the position of the vmp gene relative to the tRNA (His) gene was different for vmp -1 and vmp-2 , the latter positioned between tRNA (His) and hitABL , whereas the more similar vmp -2 and vmp -3 genes were positioned identically (Fig. 5 ). A careful sequence analysis was performed on the insertion/deletion sites of the vmp genes to try to deduce a mechanism of insertion/deletion. The vmp-2 and vmp-3 genes seemed to be inserted at the poly-T tract in the 5' end and stem-loop terminator structure at the 3' end. When compared to the vaa-hitABL intergenic region of isolate PG21, the sequences flanking the insertion sites were identical in isolates 7488/4195 and PG21 and insertion did not result in deletion of part of the intergenic sequence. The insertion site was A/T rich, and sequence identity was observed in a small 8 bp thymidine-rich ( vmp coding strand) sequence box between the insertion site in isolate PG21 and the stem region of the stem-loops of vmp-2 and vmp-3 . Furthermore, a 165 bp deletion (Δ2 in Fig. 5 ) was observed in the vaa-tRNA (His) intergenic region of isolate 7488 compared to isolate PG21. This deletion was located immediately downstream to the region deleted in isolate 93. In contrast, analysis of the vmp-1 insertion site did not show insertion at the stem-loop and poly-T structures when compared to the vaa-hitABL intergenic regions of isolates PG21 and 93. Sequence regions of 60 bp downstream to the stem-loop structure and 90 bp upstream to the poly-T tract which did not show any homology to the vaa-hitABL intergenic region of isolate PG21 were observed at the borders of the vmp-1 gene. Interestingly, comparison of the insertion site of the vmp-1 region including the 60 bp and 90 bp bordering sequences with the vaa-hitABL intergenic region of isolate PG21 revealed that insertion resulted in a deletion in the intergenic sequence corresponding to the 300 bp deletion (Δ1 in Fig. 5 ) observed for isolate 93. The sequences flanking this region in isolate PG21 was A/T rich but did not show high homology to each other or to the insertion site of the vmp-2 and vmp-3 genes. In conclusion, no obvious direct or inverted repeat structures were observed indicating a mechanism of insertion other than homologous recombination. Isolates PG21 and 4195 shared identical vaa-hitABL intergenic regions outside the vmp-2 insertion (Fig. 5 ). These isolates carry distinct vaa gene types, PG21 having a three cassette vaa -1 type and 4195 having a two cassette vaa -3 type [ 13 ]. The distal 3' end cassette of these vaa genes shows high mutual similarity, whereas the remaining exchangeable cassettes of both genes are distinct (Fig. 5B ). The 5' end including the first cassette of the vaa gene of isolate 4195 shows high similarity to the corresponding part of the vaa gene of isolate 132, harboring a different two cassette vaa gene type. The 3' end distal cassette of vaa from isolate 132 differs from that of isolates PG21 and 4195. Thus, the vaa type of isolate 4195 seems to be a chimera of the vaa types of isolates 132 and PG21 (Fig. 5B ). The GC content of the vaa and vmp genes of isolate 132 were 27% and 25% compared to a total of 25% for the 11.3 kb contig. Characterization and detection of the Vmp protein Alignments of the deduced Vmp-1 and Vmp-3 protein sequences revealed highest similarity in the C-terminal part (52% identity and 60% similarity in 382 aa). Half of this region was repeated once in Vmp-3 (Fig. 6B ). The N-terminal part showed a lower, but significant overall similarity (33% identity and 41% similarity in 660 aa). In contrast, Vmp-2 and Vmp-3 showed almost complete conservation of the N-terminal part (93% identity in 1552 aa), whereas the C-terminal part showed a similarity corresponding to that between the Vmp-1 and Vmp-3 (55% identity and 69% similarity in 276 aa). The repeated region of Vmp-3 was only present in one copy in Vmp-2. Sequence analysis revealed that the deduced Vmp proteins have a predominantly alpha-helical structure, and a coiled-coil region extending throughout almost the entire length of the proteins was identified (Fig. 6A and 6C ). In Vmp-1 the coiled-coil motif extended from residues 35 to 1328 out of a total of 1404 residues. Likewise, the coiled-coil region of Vmp-2 spanned residues 28 to 1631 out of 1829 and residues 29 to 1869 out of 2168 residues of Vmp-3. The coiled-coil region contained numerous short disruptions of the predicted coiled-coil and alpha-helical structure (Fig. 6A and 6C ). As this region showed high similarity to the Lmp proteins, the Lmp sequences were analysed for the presence of a coiled-coil region. Intriguingly, the Lmp proteins were shown to contain a coiled-coil region extending throughout most of the protein in analogy to the Vmps (data not shown). A polyclonal antibody was raised against the distal C-terminal part of Vmp-1 from isolate 132 (Fig. 6B ). This region shows low homology to the Vmp-2 and Vmp-3, and the antibody was applied in immunoblotting using antigen from 8 selected isolates (Fig. 7 ). The antibody reacted with a protein of 160 kDa from isolates 132, 5941, DC63 and SC4, in agreement with the predicted molecular weight of the protein encoded by the vmp -1 gene of these isolates. These data thus demonstrate that Vmp is expressed in M. hominis . Furthermore, the antibody reacted with a 100 kDa protein in all isolates except PG21. This is presumably a protein that has been shown previously to bind Ig-molecules unspecifically, and is not present in PG21 [ 25 ]. Apart from the 100 kDa protein the isolates PG21 and 93, having no vmp gene, and isolates 4195 and 7488 having a Vmp-2 and Vmp-3 type, respectively, did not react with the antibody, as expected from the low homology of the C-terminal region (Fig. 7 ). Discussion The presented analysis of the vaa locus reveals that it is a highly dynamic region of the M. hominis genome. The data indicate that variation in the 3' end of the vaa gene may be attributed recombinational events involving regions outside the gene. The insertion/deletion of the vmp gene downstream to vaa in different positions relative to the tRNA (His) gene, and the lack of correlation of vmp type and absence of vmp to vaa type suggests frequent recombination in this locus (Fig. 5 ). The finding that the two distinct vaa types of isolates PG21 and 4195 share 3' end cassettes and homologous downstream intergenic sequences, suggests that the vaa type of 4195 arose from intraspecies recombination (Fig. 5B ). This event might have taken place between a M. hominis cell carrying a vaa type with a 5'end analogous to the vaa type of isolate 132 and a cell harboring a vaa type with a 3' end similar to that of PG21. Another M. hominis gene encoding a surface exposed lipoprotein, P120, was shown to contain a hypervariable and two semivariable domains [ 26 ]. This gene maps in close proximity to the vaa locus in the M. hominis genome (Fig. 1A ). The groups of isolates carrying a specific hypervariable domain did not correlate with the vaa type [ 13 , 26 ]. Thus it is plausible that this region of the M. hominis genome harboring most of the characterized genes for membrane proteins is a genomic plasticity zone as previously suggested [ 18 ]. Based on these findings, recombination between different M. hominis subpopulations may be a general mechanism for the generation of antigen variation in this mycoplasma species. A necessity for intraspecies recombination is the transfer of DNA. No plasmids or phages have been observed for M. hominis , but the transfer of Tn 916 , presumably by conjugation, from a Streptococcus faecalis donor has been shown with low efficiency [ 27 , 28 ]. Conjugation between M. hominis cells has not been demonstrated. Chemically competent M. hominis were shown to be capable of uptake of homologous naked DNA. This was demonstrated by the transfer of tetracycline resistance from the DNA of a tetracycline resistant M. hominis isolate to a competent, sensitive isolate [ 29 ]. Thus, the knowledge regarding mechanisms of DNA uptake in M. hominis is sparse, and this subject needs to be addressed. The location of vmp in close proximity to a tRNA gene is analogous to genetic elements of other bacteria. These elements, often referred to as genetic islets (<10 kb) or genetic islands (>10 kb), are variable sites when comparing genomes of different isolates of a given species. Often, genetic islets/islands carry pathogenesis factors and are specific for virulent clones of the species. Such factors include adhesins, toxins and restriction/modification systems. Frequently, the genetic elements are inserted into tRNA genes, show a GC content diverging from the surrounding regions and are flanked by repeated elements [ 30 ]. Although the vmp gene was located on either side of the tRNA (His) gene in isolates 132 and 7488, respectively, the GC content of vmp was similar to the remaining part of the vaa locus analyzed and the M. hominis genome in general (28%) and despite a thorough analysis, no obvious flanking structures such as direct or inverted repeats were observed which could indicate a site specific mechanism of insertion. Thus, the vmp gene may be mycoplasma specific and insertion/deletion of vmp at the vaa locus seems mediated by homologous recombination. It was possible to amplify vmp fragments by PCR from four out of five isolates categorized as having a vmp-1 gene type and likewise for four out of five isolates having a vmp-2 or vmp-3 gene type. The pronounced heterogeneity observed between the vmp genes could explain the missing reaction of the remaining two isolates as being caused by sequence variation of the individual gene types as observed for a number of other M. hominis membrane protein genes, but it is also possible that additional vmp gene types exists. The size and predicted structure of Vmp is interesting. The coiled-coil motif extending through most of the protein, is a highly versatile motif involved in protein-protein interactions [ 31 ]. This motif is found in proteins carrying out diverse functions such as structural proteins, transcription factors, translation factors and extracellular proteins [ 32 ]. The coiled-coil domains often mediate the oligomerization of proteins forming di-, tri-, tetra- or even pentamers [ 31 ]. Additionally, coiled-coil motifs in some cases are involved in intramolecular interactions forming highly stable, ridgid and compact structures. The length of the coiled-coil region in the primary structure of Vmp is comparable to that of eukaryotic class II myosins, proteins involved in movement along actin filaments [ 33 ]. Furthermore, a coiled-coil region of similar length was observed for the cytadherence related HMW2 protein of Mycoplasma pneumoniae . This protein is cytoplasmic, part of the primitive cytoskeleton of this mycoplasma and truncation of the gene resulted in loss of cytadherence [ 34 ]. HMW2 is believed to form dimers due to the coiled-coil region [ 35 ]. In contrast to HMW2, Vmp contains a C-terminal region having no coiled-coil motifs. Furthermore, a signal sequence involved in transmembrane translocation of proteins was identified in the Vmps, but not in HMW2. Thus, it is highly likely that the Vmp protein is located on the cell surface of M. hominis in contrast to the cytoplasmic HMW2. The identification of a novel putative membrane protein displaying sequence variation is intriguing, and furthermore the remarkable size and structure displayed by the Vmp protein is interesting and should prompt investigations on the biological function of this protein in M. hominis . Conclusions We have demonstrated that in some isolates, the vaa locus of M. hominis contains a divergent genetic islet encoding a large, putative membrane protein called Variable membrane protein (Vmp). This genetic islet is only present in the locus of half of the 20 islolates tested, and three distinct, homologous Vmp types were observed. The composition of the locus was analysed and it was found that the vaa gene has a conserved upstream region and a highly variable downstream region, which contains the genetic islet. This locus organization corresponds to the organization of the vaa gene itself having a conserved 5' end and a variable 3' end. Thus, the mechanism underlying variation of the vaa gene seems to be intraspecies recombination exchanging variable regions of vaa and downstream regions of vaa , giving rise to a variable and dynamic 'hot spot' in the M. hominis genome. Methods Isolates and growth media Twenty M. hominis isolates were analysed (PG21, 4195, 132, 5941, 1621, 7488, 93, 3105, 1572B, 2032B, 2347B, 7808, 7357, 4712, V2785, DC63, SC4, P2, 183, and P71). The M. hominis isolates were cultivated in BEa medium (heart infusion broth (Difco), 2.2% (w/v); horse serum, 15% (v/v); fresh yeast extract, 1.9% (w/v); benzylpenicillin, 40 IU ml -1 ; L-arginine, 0.23% (w/v); phenol red 0.0023% (w/v)). The pH of the medium was adjusted to 7.2 and the medium was sterilized by filtration [ 36 ]. The M. hominis isolates were harvested by centrifugation at 15,000 rpm for 45 min at culture volumes greater than 1.5 ml or at 20,000 rpm for 15 min for culture volumes smaller than 1.5 ml. E. coli OneShot competent cells and the pCRII plasmid vectors were used for TA-cloning (Invitrogen). Pulsed field gel electrophoresis (PFGE) PFGE was performed on genomic DNA from the five M. hominis isolates PG21, 4195, 132, 93 and 7488. The M. hominis isolates were grown in BEa medium to log phase and harvested. The cell pellets were washed and resuspended in PBS buffer (20 mM sodium phosphate, 250 mM NaCl, pH 7.4). Melted NA agarose (Amersham Pharmacia Biotech) was mixed with the cell suspension in a plastic mold on ice. The agaroseblocks hereby formed were incubated overnight with 1 mg/ml Proteinase K (Roche) in lysis buffer (1% Sarcosyl, 0.5 M EDTA, 10 mM Tris HCl, pH 9.5). Subsequently, each block was washed twice in lysis buffer followed by one wash in TE buffer (10 mM Tris HCl, 1 mM EDTA, pH 8.0) and cut into eight blocks of identical size. The blocks were digested overnight with 40 units of one of five restriction enzymes ( Sma I, Bam HI, Xho I, Sal I, and Apa I) and 12 mg of BSA. Subsequently, the blocks were inserted into the slots of 1% NA agarose gels and the holes sealed with melted NA agarose. Hin dIII digested λ DNA and a λ DNA ladder (FMC) was used as molecular weight markers. The gels were used for PFGE using the CHEF-DRII separation system (Bio-Rad). Preparation of DNA DNA from the M. hominis isolates was isolated using the method described in [ 37 ]. Briefly, M. hominis cells were harvested and subsequently lysed on ice in a buffer containing 0.7% (w/v) N-laurylsarcocine, 10 mg RNase ml -1 (Sigma), 20 mM Tris pH 7.5 and 20 mM EDTA. Proteinase K (150 mg ml -1 ) was added and the cell lysate was incubated at 55°C for 2 hrs and 37°C for 1–2 hrs followed by phenol, phenol/chloroform and chloroform extractions [ 38 ]. DNA preparations from the isolates 1572B, 2032B and 2347B were made by Proteinase K (150 mg ml -1 ) treatment of harvested M. hominis at 55°C for 1 h. After the incubation the solution was heated to 100°C for 5 min to inactivate the enzyme. Plasmids from transformed E. coli were prepared as described in [ 38 ], for sequencing the phenol/chloroform extraction was omitted. Southern blotting PCR-products derived from different vaa types with sizes of 1220 bp (probe 1), 600 bp (probe 2), 800 bp (probe 3), and 660 bp (probe 4) were used for TA-cloning, performed according to manufacturers instructions (Invitrogen) [ 13 ]. Probe 1 contained most of the vaa-1 gene from M. hominis 7808, including the three cassettes III, IV and V [ 13 ]. Probe 2 contained the conserved 5' end and cassette III from the vaa-1 gene of M. hominis PG21 and probe 3 contained most of the vaa-3 gene of M. hominis V2785 including cassettes V and VII. TA-cloned PCR fragments or linear PCR fragments were used as DNA probes and labeled with radioactive (α- 32 P)dATP by nick-translation, performed as follows. 0.5–1 μg DNA was mixed with 1 × nick-translation buffer (50 mM Tris HCL (pH 7.2), 10 mM MgSO 4 , 0.1 mM DTT, 50 mg BSA, 60 mM of dTTP, dCTP, and dGTP respectively, 5 units of DNA polymerase I (Gibco), 0.5 ng DNase I (Roche), 20 mCi (α- 32 P)dATP (Du Pont) and ddH 2 O up to 50 μl. The reaction was incubated at 14–16°C for 1 h. Incorporation of radioactive nucleotides was verified by TLC and terminated by addition of TE-buffer with 0.5 M EDTA. The radioactive probes were denatured by heating to 100°C for 5 min and hybridization performed in 2 × SSC (1 × SSC is 0.15 M NaCl and 0.015 M sodium citrate), 0,5% SDS, 100 mg/ml yeast RNA, 5 × Denhardts solution (0.1% Ficoll, 0.1% BSA, 0.1% polyvinyl pyrollidone (Serva)) at 60°C in a hybridization oven. The membranes were washed in 6 × SSC and 0.5% SDS. The membranes were placed in sealed plastic bags and exposures of X-ray films were performed at room temperature or at -20°C. Genomic DNA samples of the isolates PG21, 4195, 132, 93 and 7488 were cleaved with either Hin dIII or Eco RI and separated on 0.7% agarose gels. The gels were stained with ethidium bromide and photographed under UV irradiation. Preceding the alkaline denaturation, partial hydrolysis of the DNA in the PFGE gels was performed by soaking in a 0.25 M HCl solution to enhance the transfer of large DNA fragments. DNA transfer to Hybond-N membranes (Amersham Biosciences) was carried out as described in [ 38 ]. PCR PCR was performed using the Expand™ High Fidelity PCR System from Roche according to the manufacturer's instructions, except for the amplification of the 1.2 kb vmp-2/3 PCR product where Taq polymerase was used (PE Biosystems). Custom oligonucleotide primers were purchased from DNA Technology (Aarhus, Denmark). PCR products were purified using the Wizard kit (Promega) according to manufacturers instructions. PCR conditions used for inverse PCR and amplification of downstream and upstream regions of the 20 isolates were as follows: 2 min at 92°C, 10 cycles of 10 s at 92°C, 30 s at 55°C, 8 min at 68°C, 20 cycles of 10 s at 92°C, 30 s at 55°C, 8 min at 68°C with 5 s added to the elongation time pr. cycle. Finally, an extension step of 7 min at 68°C was performed. The primers used for amplification of the 5.5 kb upstream product were F1 (CAGTACATGTTAATCCCAGAA GTATAGTTGG) and R1 (GCTGGATAATCGCCGTATGAACCTGC). The R1 primer was also used for amplification of the 4 kb and 0.6 kb PCR products in combination with the primers F2 (GGATCTTCTTTGTGGTCTTCC) and F3 (GGGATAGTTAGTAAAG TTGGAATAGCC), respectively. For amplification of the downstream region in the 20 isolates, the primers F4 (GCAGGTTCATACGGCGATTATCCAGC) and R4 (GCCACTTGCGGTTCTTCC) were used. For the amplification of the 0.6 kb vmp-1 PCR product, the primers F6 (CCACTGATACGTGATTTAAAAAGAAAAG) and R3 (GGTATTGTTTCTTTATCTAAGATGTTTTCAAATTC) were used with the following PCR conditions: 4 min at 94°C, 30 cycles of 15 s at 94°C, 30 s at 50°C, 1 min at 72°C and a final extension of 5 min at 72°C. For amplification of the 1.2 kb vmp-2/3 PCR product, similar conditions were used with an annealing temperature of 57°C and an elongation time of 2 min, and the primers were F5 (GAACAATTAAAAACATTAATTGGCTTAA GTGATG) and R2 (GTTTTATCTACATTGTTTTCGGATAAGG). Restriction endonuclease analysis The 5.5 kb upstream PCR products from the 20 analysed isolates were subjected to restriction endonuclease analysis employing the enzymes Alu I and Ase I (New England Biolabs) according to manufacturers instructions and analysed on 1 × TBE/2% agarose gels. Sequencing Sequencing reactions were carried out bidirectionally using the ABI PRISM Dye Terminator Cycle Sequencing Ready Reaction Kit (Perkin Elmer) on purified plasmid DNA (TA-cloned PCR products) or directly on the purified PCR products according to the instructions supplied by the manufacturer. Sequencing was performed on an ABI PRISM 377 DNA Sequencer from Perkin Elmer. Cloning, expression and generation of polyclonal antibodies to a Vmp-1 fragment Oligonucleotide primers (DNA technology, Aarhus, Denmark) were designed in order to amplify by PCR, the region of vmp -1 from isolate 132 encoding aa 1281 to 1404 of the Vmp-1 protein. Cloning and expression of the construct was performed using the pET-30 Ek/LIC vector according to manufacturers instructions (Novagen, Madison, USA). The His-tagged fusion protein was purified using a nickel chelated column (High Trap Sepharose, Amersham Pharmacia Biotech) under denaturing conditions as previously described [ 39 ]. Sera containing polyclonal antibody directed against the C-terminal Vmp-1 fragment was obtained by immunizing a rabbit three times intramuscularly with 20 mg of recombinant protein dissolved in Freunds complete adjuvant and three times intravenously with 20 mg protein dissolved in PBS. SDS-PAGE and immunoblotting were performed as previously described [ 13 ]. Computer analysis Computer analysis of the obtained DNA sequences was performed using the Wisconsin Package Version 9.0, Genetics Computer Group (GCG), Madison, Wisc., sequence analysis software package [ 40 ]. Data base searches were performed using both NetBlast and FastA. Furthermore, the programs SignalP and TMHMM, both found at the website , were used to predict signal sequences and transmembrane helices, respectively [ 23 , 24 ]. Energy of putative rho-independent stem-loop terminator structures was calculated using the RNA mfold server at [ 41 ]. Accession numbers The DNA sequences obtained in this study were deposited to the EMBL database under the following accession numbers: AJ416752, AJ545046 AJ629113, AJ629114 and AJ629115. Authors' contributions The individual parts of the work presented in the paper were conducted as follows: The ideas and designs of the experiments were developed by all the authors. Pulsed field gel electrophoresis and Southern blottings were performed by JE and TB. PCR, sequencing, and sequence analysis were performed by TB and AB. The fusion protein, polyclonal antisera and immunoblotting were made by TB. The manuscript was primarily written by TB and discussed with and approved by all authors. Supplementary Material Additional File 1 Multiple sequence alignment. Alignment of the three Vmp types and Lmp1 and Lmp3 from type strain PG21 using ClustalW. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524362.xml

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