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LLM - Digital Humanities 16

ERROR: type should be string, got "https://doi.org/10.1016/j.fpsl.2020.100551 \nReceived 23 March 2020; Received in revised form 26 July 2020; Accepted 31 July 2020 \n2214-2894/ ©\n 2020 Published by Elsevier Ltd. Hossein Haghighia, Fabio Licciardelloa,b,*, Patrizia Favaa,b, Heinz Wilhelm Sieslerc, \nAndrea Pulvirentia,b Hossein Haghighia, Fabio Licciardelloa,b,*, Patrizia Favaa,b, Heinz Wilhelm Sieslerc, \nAndrea Pulvirentia,b a Department of Life Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy \nb Interdepartmental Research Centre BIOGEST-SITEIA, University of Modena and Reggio Emilia, Reggio Emilia, Italy \nc Department of Physical Chemistry, University of Duisburg-Essen, Essen, Germany ⁎ Corresponding author. \nE-mail address: fabio.licciardello@unimore.it (F. Licciardello). A B S T R A C T Keywords: \nBiopolymer \nBlend \nFilm \nFood packaging \nMechanical properties \nPermeability The recent sharp increase of sensitivity towards environmental issues arising from plastic packaging has boosted \ninterest towards alternative sustainable packaging materials. This new trend promotes the industrial exploitation \nof knowledge on chitosan-based films. Chitosan has been extensively investigated and used due to its unique \nbiological and functional properties. However, inherent drawbacks including low mechanical properties and \nhigh sensitivity to humidity represent major limitations to its industrial applications, including food packaging. In the present study, the scientific literature of the last five years has been extensively reviewed (source: Web of \nScience) addressing chitosan-based films for their potential application in the food packaging industry. The \ncontribution summarizes the various strategies adopted to overcome inherent drawbacks and improve the \nproperties of chitosan-based films, with special regards for blending with natural and synthetic biopolymers. biodegradable materials are produced from renewable resources \n(Rujnić-Sokele & Pilipović, 2017). A schematic classification of biode­\ngradable polymers according to their source is presented in Fig. 1. Food Packaging and Shelf Life 26 (2020) 100551 Food Packaging and Shelf Life 26 (2020) 100551 1. Introduction Fig. 1. Schematic classification of biodegradable polymers. Fig. 1. Schematic classification of biodegradable polymers. Bioplastics, whether biobased, biodegradable, or both, have unique \nadvantages over conventional plastics to reduce reliance on fossil re­\nsources and to mitigate carbon footprint and greenhouse gas emissions. Besides, they promote resource efficiency and offer extra waste man­\nagement options such as organic recovery (Arikan & Ozsoy, 2015; \nKumar & Thakur, 2017). interrogation of the Web of Science database was performed searching \n“chitosan, film, blend, food packaging” within title, abstract and key­\nwords in the timeframe 2015–2020. Nevertheless, among the very large \nnumber of papers available dealing with a wide range of characteristics \nand functionalities, only the most significant studies and achievements \nwill be analyzed and discussed. ,\n)\nRecently, biodegradable polymers derived from renewable re­\nsources have been proposed as the future generation of packaging \nmaterials (Lei et al., 2014). The basic material employed to form bio­\nbased films are polysaccharides, proteins, lipids, and their derivatives \n(De Leo et al., 2018; Ramos, Valdés, Beltrán, & Garrigós, 2016). Pro­\nteins and polysaccharides have acceptable mechanical and gas barrier \nproperties, but they show high moisture sensitivity (Rhim & Ng, 2007). On the contrary, lipid films exhibit acceptable water vapor barrier \nproperty and high oxygen permeability, but they have poor mechanical \nproperties (Vodnar, Pop, Dulf, & Socaciu, 2015). Among poly­\nsaccharides, chitosan has received considerable attention from aca­\ndemics and industry for food packaging applications due to its parti­\ncular \nphysicochemical \nfeatures, \nbiodegradability, \nnon-toxicity, \nbiocompatibility, good film-forming properties, chemical stability, high \nreactivity (Dutta, Tripathi, & Dutta, 2012; Lago et al., 2014; Mujtaba \net al., 2019). General values for the parameters of interest for food \npackaging applications are reported in Table 1. The reader should \nconsider these values as merely representative since they could dar­\namatically change upon addition of additives such as plasticizers or \ncrosslinker. Chitoasan has also intrinsic antioxidant and antimicrobial \nactivities against fungi, molds, yeasts, and bacteria (Aider, 2010; \nLeceta, Guerrero, & de la Caba, 2013). However, inherent drawbacks of \nchitosan including low mechanical and thermal stability and high \nsensitivity to humidity are causing a major restriction for its industrial \napplications (Elsabee & Abdou, 2013). One strategy to overcome these \ndrawbacks is blending chitosan with other biopolymers to combine \ntheir advantages as well as minimize their disadvantages. 1. Introduction Annually, more than 350 million tons of plastics are produced in the \nworld (Ritchie & Roser, 2018). It is expected that plastics will account \nfor 20 % of total oil consumption by 2050 (Newell, Qian, & Raimi, \n2016; Cui, Borgemenke, Qin, Liu, & Li, 2019). Packaging, particularly \nfood packaging, is one of the largest application fields for plastics (Cui, \nSurendhiran, Li, & Lin, 2020). Food packaging is represented as a co­\nordinated system for processing, transporting, distributing, retailing, \nprotecting and preserving food to satisfy the industry demands and \nconsumer desires, to retain food safety and to protect food from ex­\nternal contamination with optimal cost (Marsh & Bugusu, 2007; Shin & \nSelke, 2014; Yam & Lee, 2012). However, accumulation of huge \namounts of plastic waste in the environment, and also rapid depletion \nof fossil reserves and increases in the cost of petroleum, are pushing the \nfood packaging industry toward the development and application of \neco-friendly materials, such as bioplastics (Arikan & Ozsoy, 2015; Philp, \nBartsev, Ritchie, Baucher, & Guy, 2013). The term “biobased” refers to the derivation of material from bio­\nmass (Soroudi & Jakubowicz, 2013). The term “biodegradable” in­\ndicates materials that can disintegrate or break down naturally into \nCO2, CH4, H2O, and inorganic compounds, or biomass in which the \nprevalent process is the enzymatic function of microorganisms \n(Peelman et al., 2013), that can be measured by standardized tests \n(ASTM Standard D-5488-94d). Some of these polymers can also be \ncompostable, which means disintegration occurs in a compost site at a \nrate consistent with known compostable materials and without re­\nleasing toxic substances (Siracusa, Rocculi, Romani, & Dalla Rosa, \n2008). As stated by the European Bioplastic Organization, bioplastics \nconstitute approximately 1 % of the total global plastics production \nannually (Rujnić-Sokele & Pilipović, 2017). Packaging, as one of the \nlargest application fields for bioplastics, shares almost 65 % of the total \nbioplastics market. This number is predicted to rise continuously in the \nupcoming years mainly due to the increasing consumer requirements \nfor sustainable products and growing awareness over environmental \nissues (van den Oever, Molenveld, van der Zee, & Bos, 2017). Bioplastics can be referred to as plastics obtained from renewable \nresources (biobased), plastics that are biodegradable and/or compo­\nstable, or materials that feature both properties (Kumar & Thakur, \n2017). Hence, not all biobased materials are biodegradable and not all Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. 1. Introduction Therefore, \nthe objective of the present paper is to provide a comprehensive lit­\nerature review of the last five years addressing chitosan-based films and \nstrategies adopted for the improvement of their performances for po­\ntential food packaging applications. To get an idea of the complexity of \nthe theme and of the work that has been done in the last years, an 2. History, features, and potential of chitosan Molecular weight \nMoisture content (%) \nTransparency value (A600/T) \nL* \na* \nb* \nΔE* \nWVP \n(× 10-13 g cm-1 s-1 Pa-1) \nOP \n(cm3 μm m-2 day-1 KPa-1) \nTS \n(MPa) \nE \n(%) \nHigh molecular weight chitosan \n15.70 \n0.754 \n96.39 \n−0.23 \n3.15 \n1.68 \n8.07 \n6.65 \n61.82 \n4.59 \nLow molecular weight chitosan \n19.43 \n0.760 \n96.54 \n−0.57 \n4.74 \n5.29 \n9.21 \n7.70 \n55.83 \n4.58 \n. Haghighi, et al. hydrolyzed chitin in several ways and extracted chitosan from marine \narthropods (e.g., crab, shrimp, and lobster). In the 1940s, both chitin \nand chitosan attracted considerable attention as evidenced by about 50 \npatents. In 1950, the structure of chitosan was discovered using X-ray \n(Darmon & Rudall, 1950). The first book about chitosan was published \nby Albert Glenn Richards in 1951 (Richards, 1951). Nowadays, chitin and chitosan are simply described as copolymers \nof N-acetyl-D-glucosamine and D-glucosamine units linked with β-(1–4)- \nglycosidic bonds (Hosseinnejad & Jafari, 2016). They attract consider­\nable attention and are employed worldwide for a broad range of ap­\nplications. In the food industry, they are applied as antimicrobial agents \n(bactericidal and fungicidal), edible films and coating (e.g., post-har­\nvest deterioration control in fruits), additives (e.g., natural flavor ex­\ntender, emulsifying agents, thickeners, stabilizing agents, and color \nstabilizers), integrators (e.g., dietary fiber), enzyme immobilization, \nencapsulation of nutraceuticals, and purification of water (e.g. removal \nof dyes) (Ahmed & Ikram, 2017; Dutta, Tripathi, Mehrotra, & Dutta, \n2009; López-Caballero, Gómez-Guillén, Pérez-Mateos, & Montero, \n2005; Zargar et al., 2015; Zhang, Li, & Liu, 2011). g\ng\nChitosan exhibits antioxidant (Ngo & Kim, 2014; Ojagh, Rezaei, \nRazavi, & Hosseini, 2010) and antimicrobial activity against a broad \nrange of pathogenic and spoilage microorganisms, including fungi \n(yeasts and molds), Gram-positive and Gram-negative bacteria \n(Friedman & Juneja, 2010; Kong, Chen, Xing, & Park, 2010; van den \nBroek, Knoop, Kappen, & Boeriu, 2015). The antimicrobial activity of \nchitosan has drawn attention as a potential natural food preservative \n(Del Nobile et al., 2009; No, Meyers, Prinyawiwatkul, & Xu, 2007). Several hypotheses have been suggested to elucidate the mechanism of \nantimicrobial activity of chitosan: the most reasonable hypothesis is \nelectro statistic interaction between protonated amino groups (NH3\n+) \nof glucosamine in the chitosan backbone and microbial negative cell \nmembrane constituents such as phosphoryl groups of the phospholipid \ncomponents, proteins, amino acids, and various lipopolysaccharides \n(Elsabee & Abdou, 2013; Mousavi Khaneghah, Hashemi, & Limbo, \n2018). 2. History, features, and potential of chitosan This interaction affects the membrane integrity and perme­\nability, interfering with energy metabolism, nutrient transport, pro­\nvoking the permeation of proteinaceous and other intracellular com­\nponents, and causing disruptions that lead to cell death of \nmicroorganisms (Goy, de Britto, & Assis, 2009). Another possible me­\nchanism is the interaction of chitosan with cellular DNA of micro­\norganisms, thus preventing DNA transcription, RNA translation, and \nprotein synthesis (Raafat & Sahl, 2009; Sharif et al., 2018; Verlee et al., \n2017). Moreover, chitosan acts as a chelating agent that selectively \nbinds essential trace metals, spores, prevents the production of toxins \nand microbial growth (Hosseinnejad & Jafari, 2016; Vodnar et al., \n2015). Several researchers also suggested that microbial growth in­\nhibition occurs by blocking the supply of essential nutrients into the cell \n(No et al., 2007; Raafat & Sahl, 2009). Chitosan exhibits antioxidant (Ngo & Kim, 2014; Ojagh, Rezaei, \nRazavi, & Hosseini, 2010) and antimicrobial activity against a broad \nrange of pathogenic and spoilage microorganisms, including fungi \n(yeasts and molds), Gram-positive and Gram-negative bacteria \n(Friedman & Juneja, 2010; Kong, Chen, Xing, & Park, 2010; van den \nBroek, Knoop, Kappen, & Boeriu, 2015). The antimicrobial activity of \nchitosan has drawn attention as a potential natural food preservative \n(Del Nobile et al., 2009; No, Meyers, Prinyawiwatkul, & Xu, 2007). l h\nh\nh\nb\nd\nl\nd\nh\nh\nf 2. History, features, and potential of chitosan Chitosan is a unique natural biopolymer, commercially originated \nfrom the deacetylation (to varying degrees) of chitin (Verlee, Mincke, & \nStevens, 2017). It is the second most abundant natural polysaccharide \nbehind \ncellulose \n(Salari, \nSowti \nKhiabani, \nRezaei \nMokarram, \nGhanbarzadeh, & Samadi Kafil, 2018) and the most abundant biopo­\nlymer of animal origin (Priyadarshi & Rhim, 2020). Chitin can be ob­\ntained from terrestrial arthropods (e.g., spiders, scorpions, beetles, \ncockroaches, and brachiopods), marine crustaceans (e.g., crab, lobster, \nprawn, and krill), Mollusca (e.g., squid) and microorganisms (e.g., fungi \ncell walls) (Zargar, Asghari, & Dashti, 2015). The waste of marine food \nproduction (particularly exoskeleton of crabs, lobsters, and shrimps) is \ncurrently the main industrial source of biomass for chitin production \n(Gutiérrez, 2017). i The first report on chitin traces back to 1811 by French Professor of \nnatural history Henri Braconnot. He found out the alkaline-insoluble \nfraction from mushrooms and named it “fungine”. In 1823, Antoine \nOdier extracted this alkaline-insoluble fraction from the cuticle of in­\nsects and named it “chitine”, originated from the Greek word “khiton” \nmeaning “tunic” or “envelope”. Twenty years later, Jean Louis \nLassaigne proved the presence of nitrogen in chitin. In 1859, Prof. C. Rouget discovered the deacylated form of chitin. He treated chitin with \nconcentrated potassium hydroxide solution and heat to become soluble \nin dilute organic acids and named it “modified chitin” (Rouget, 1859). In 1878, Ledderhose identified that chitin was made of glucosamine and \nacetic acid. In 1894, Hoppe-Seyler treated the shells of crabs, scorpions, \nand spiders with potassium hydroxide solution at 180 °C and dissolved \nthe product in dilute acid solution and named it “chitosan”. In 1894, \nGilson proved the presence of glucosamine in chitin. In 1930, Ram­\nmelberg found more chitin sources apart from insects and fungi. He 2 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. Table 1 \nMoisture content, transparency value, color parameters including L* (lightness), a* (redness/greenness) and b*(yellowness/blueness), ΔE* (total color difference), water vapor permeability (WVP), oxygen permeability \n(OP), tensile strength (TS) and elongation at break (E) of low and high molecular weight chitosan films. Adapted from Leceta, Guerrero, & de la Caba (2013). 3. Strategies for the improvement of properties of chitosan-based \nfilms Inherent drawbacks of chitosan such as high sensitivity to water, \nlow mechanical and thermal stability lead to a shorter food shelf life \ncompared to the conventional food packaging material and conse­\nquently limited its applications in food packaging (Al-Tayyar, Youssef, \n& Al-hindi, 2020; Elsabee & Abdou, 2013). Therefore, different strate­\ngies have been proposed to tackle these issues and to improve the \nproperties of chitosan-based materials, such as cross-linking (Jahan, \nMathad, & Farheen, 2016; Khouri, Penlidis, & Moresoli, 2019; Liang, \nWang, & Chen, 2019; Yeamsuksawat & Liang, 2019), enzyme treatment \n(Águila-Almanza, Salgado-Delgado, Vargas-Galarza, García-Hernández, \n& Hernández-Cocoletzi, 2019), graft copolymerization (Argüelles- \nMonal, Lizardi-Mendoza, Fernández-Quiroz, Recillas-Mota, & Montiel- \nHerrera, 2018; Wang, Yu et al., 2016; Wang et al., 2019), complexation \n(Wang, Wang, & Heuzey, 2016), surface coating (Khwaldia, Basta, 3 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. plications. Improvement of the parameters investigated in each contribution is reported as \nantimicrobial activity\nHaghig (continued on next page) Table 2 \nSynopsis of research published between 2015 – 2020 addressing chitosan-polysaccharide blend films for food packaging applications. Improvement of the parameters investigated in each contribution is reported as\nfollows. M: mechanical properties, WB: water barrier properties, GB: gas barrier permeability, AO: antioxidant activity, AM: antimicrobial activity. Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Pectin (2 % w/v) \n• Nano chitosan (2 % w/v) \n• Films with different ratios of pectin/nano chitosan (100:0, 75:25, \n50:50, 25:75, and 0:100 w/w) were developed. • Blending pectin with nano chitosan at proportions of 50:50 \nincreased the tensile strength while water solubility, water vapor \npermeability, and oxygen permeability decreased. • Developed films showed antimicrobial activity against C. gloeosporioides, S. cerevisiae, A. niger, and E. coli. ✓ \n✓ \n✓ \n✓ \nNgo, Nguyen, Dang, Tran, and \nRachtanapun (2020) \n• Cassava starch (2 % w/w) \n• Chitosan (1 % w/w) \n• Pitanga leaf extract (2.25 % w/w of film forming \nsolution) \n• Natamycin (1 % w/w of film forming solution) \n• Pitanga leaf extract /Natamycin mixture \n• Addition of natamycin into the biopolymers blend caused an \nincrease in tensile strength while water vapor permeability \ndecreased. • Films containing additive showed excellent barrier to UV light. • Addition of pitanga leaf extract caused an increase in antioxidant \nactivity while a combination of pitanga leaf extract and natamycin \nled to the reduction of antioxidant activity. 3. Strategies for the improvement of properties of chitosan-based \nfilms • Addition of natamycin showed positive anti-fungal activity against \nAspergillus flavus and Aspergillus parasiticus. ✓ \n✓ \n✓ \n✓ \nSirisha Nallan Chakravartula et al. (2020) \n• Purple yam starch (2 % w/v) \n• Chitosan (0.5 and 1 % w/v) \n• Increasing concentration of chitosan in the biopolymers blend \ncaused an increase in water vapor permeability while moisture \ncontent was reduced. • Application of a purple yam starch/chitosan blend film on apple \nfruits for 4 weeks preserved the fruit quality compared to \nuntreated apple samples. Martins da Costa, Lima Miki, da \nSilva Ramos, and Teixeira-Costa \n(2020) \n• Bacterial cellulose (0.5 % w/v) \n• Chitosan (2 % w/v) \n• Borate (4 %) \n• Tripolyphosphate (4 %) \n• Borate/Tripolyphosphate mixture \n• Films with different proportion of bacterial cellulose/chitosan 0, \n1/64, 1/32, 1/16, 1/8, and 1/4 were developed. • Addition of borate and tripolyphosphate into the biopolymers \nblend (1/32) showed an improvement in tensile strength and \nelasticity values mainly. • Antimicrobial activity of composite film against E. coli, B. cinerea, \nand S. cerevisiae reduced by addition of cross-linking agent. ✓ \n✓ \nLiang et al. (2019) \n• Potato starch (4 % w/v) \n• Chitosan (1.5 % w/v) \n• Citric acid (5, 10, 15, and 20 % w/w based on a dry \nbiopolymer basis) \n• Addition of citric acid into the biopolymers blend improved tensile \nstrength and elasticity. • Active films containing citric acid showed a homogenous and \ncompact structure. • Moisture content and water solubility reduced while water vapor \npermeability, mechanical and antimicrobial properties improved \nby addition of citric acid to the biopolymers blend. • Both control and films containing citric acid showed antibacterial \nactivity against E. coli and S. aureus. ✓ \n✓ \n✓ \nWu et al. (2019) \n• Hemicellulose (2 % w/v) \n• Chitosan (2 % w/v) \n• Cellulose nanofiber (5, 10, 15, and 20 % w/w based on \nbiopolymers \n• Glycerol, xylitol, sorbitol (10, 20, 30, and 40 % v/w on a \ndry biopolymer basis) \n• Adding 5 % cellulose nanofiber to the biopolymers blend \nincreased tensile strength. Films containing glycerol showed \nbetter mechanical properties than films containing xylitol and \nsorbitol. • Films containing glycerol, xylitol and sorbitol showed higher \nwater solubility, barrier properties to water vapor and oxygen, \nlower contact angle and opacity. 3. Strategies for the improvement of properties of chitosan-based \nfilms ✓ \nXu, Xia, Zheng, Yuan, and Sun \n(2019) \n• Xylan (20, 30, and 40 % w/w \nbased on chitosan) \n• Chitosan (1 % w/v) \n• Carvacrol (10 % w/w based on dry chitosan weight) \n• Addition of xylan into the biopolymers blend caused an increase in \nelasticity and samples with 20 and 25 wt.% xylan showed higher \ntensile strength and elastic modulus. • Thermal analysis showed that addition of xylan to chitosan moved \nthe degradation peak to a lower temperature with a lower rate of \ndegradation. • Addition of carvacrol into the biopolymer blend did not show \nantibacterial activity against E. coli and L. innocua. ✓ \nKamdem, Shen, Nabinejad, and \nShu (2019) \n(continued on next page\n4 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. H. Haghighi, et al. (continued on next page) Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Carboxy methyl chitosan (1 % w/ \nv) \n• Chitosan (2 % w/v) \n• Nisin (1000 and 6000 IU/mL of film forming solution) \n• Blending carboxymethyl chitosan with chitosan increased \nelasticity while it reduced thermal stability. • Incorporation of nisin into the biopolymers blend showed \nantibacterial activity against L. monocytogenes. ✓ \n✓ \nZimet et al. (2019) \n• Starch (1.5 % w/v) \n• Chitosan (1.5 % w/v) \n• Clove essential oil (3, 6, 9, and 12 % w/w) \n• Nano titanium dioxide (1, 3, 5, and 7 % w/w) \n• Addition of nano titanium dioxide into the biopolymers blend \ncaused an increase in tensile strength and antioxidant activity \nwhile water vapor permeability and elasticity decreased. • Addition of clove essential oil into the biopolymers blend reduced \ntensile strength, water content, and water vapor permeability \nwhile antioxidant and antibacterial activity against E. coli and S. aureus improved. ✓ \n✓ \n✓ \n✓ \nLi et al. (2019) \n• Carboxymethyl cellulose (2 % w/ \nv) \n• Chitosan (1 % w/v) \n• Cinnamon essential oil (1.5 % v/v) \n• Oleic acid (1 % w/v) \n• Glutaraldehyde (0.01 % w/v) \n• Addition of glutaraldehyde into the biopolymers blend caused an \nimprovement in mechanical property, water solubility, and water \nvapor permeability. • Addition of cinnamon essential oil into the biopolymers blend \nshowed antioxidant and antimicrobial activities against L. monocytogenes and P. aeruginosa. • Addition of cinnamon essential oil and glutaraldehyde at the same \ntime into the biopolymers blend increased the antioxidant and \nantibacterial activities. 3. Strategies for the improvement of properties of chitosan-based \nfilms • Addition of oleic acid into the biopolymers blend reduced water \nsolubility, tensile strength, antioxidant and antimicrobial \nactivities while elasticity, and water vapor permeability increased. ✓ \n✓ \n✓ \n✓ \nValizadeh et al. (2019) \n• Gum arabic (1.5 % w/v) \n• Chitosan (1.5 %w/v) \n• Cinnamon essential oil (8 % w/w of total solid) \n• Increasing gum arabic proportion into the biopolymers blend (1:0, \n1:0.25, 1:0.5, 1:1, 1:2, 1:4) reduced thickness, water content, \ntensile strength, elasticity, and water vapor permeability. • Addition of cinnamon essential oil into the biopolymers blend \nshowed antioxidant activity. Antioxidant activity enhanced when \nthe ratio of chitosan/gum arabic changed from 1:0 to 1:2. Antioxidant activity quickly reduced by further increasing of gum \narabic proportions in biopolymers blend to 1:4. ✓ \n✓ \nXu, Gao, Feng, Yang, Shen and\nTang et al. (2019) \n• Gum arabic (1.5 % w/v) \n• Chitosan (1.5 %w/v) \n• Cinnamon essential oil (5, 10, and 15 % w/w based on \ngum arabic) \n• Clove essential oil (10 % w/w based on gum arabic) \n• cinnamon and clove essential oil combination (5 % w/w \nbased on gum arabic) \n• Addition of essential oils into the biopolymers blend decreased the \nζ-potential and viscosity, while particle size increased. • Addition of essential oils (in particular cinnamon essential oil) \ncaused an increase in elasticity while tensile strength and water \nbarrier properties were reduced \n• Films containing cinnamon essential oils or a combination of \ncinnamon and clove showed better water barrier properties \ncompared to films containing clove. • Films containing cinnamon and clove essential oils combinations \nexhibited better antimicrobial activity against E. coli and S. aureus. Besides, films containing cinnamon essential oil showed better \nantibacterial activity compared to the clove essential oil. ✓ \n✓ \n✓ \nXu, Gao, Feng, Huang, Yang et \n(2019) \n• Corn starch (3 % w/v) \n• Cassava starch (3 % w/v) \n• Chitosan (0.5 % w/v) \n• Glutaraldehyde(10 % w/v based on a dry biopolymer \nbasis) \n• Composite films showed antibacterial activity against aerobic \nmesophilic bacteria. ✓ \nLuchese et al. (2018) \n• Hardleaf oatchestnut starch (0.5, 2, \nand 8 % w/v) \n• Chitosan (2 % w/v) \n• Litsea cubeba oil (4, 8, 12, and 16 % w/w, based on \nbiopolymers total weight) \n• Blending chitosan and hardleaf oatchestnut (ratio 1:1) caused an \nincrease in tensile strength and an improvement in water vapor \npermeability. 3. Strategies for the improvement of properties of chitosan-based \nfilms • The incorporation of Litsea cubeba oil into the biopolymers blend \n(ratio 1:1) decreased tensile strength, elasticity, water vapor \npermeability, water content, and water solubility while contact \nangle values increased. • Addition of Litsea cubeba oil into the biopolymers blend showed \nantimicrobial activity against E. coli and S. aureus. ✓ \n✓ \n✓ \nZheng et al. (2018) \n(continued on next p\n5 5 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. H. Haghighi, et al. (\n)\nBiopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Cassava starch \n• Chitosan (0, 25, 50, 75, 100, and \n150 mg chitosan/g starch ratios) \n• Gallic acid \n• Increasing chitosan proportion in biopolymers blend decreased \nmoisture content, water activity, water vapor permeability, total \nphenolic contents, and antioxidant activities. • Blending chitosan and cassava starch reduced the growth of \nspoilage microorganisms and prolonged the shelf life of cooked \nham. ✓ \n✓ \nZhao, Teixeira, Gänzle, and \nSaldaña (2018) \n• Burdock root inulin (4 % w/v) \n• Chitosan (2.5 % w/v) \n• Water vapor permeability, water solubility, water content, tensile \nstrength, and lightness value of inulin-chitosan films were reduced \nwith increasing oregano-thyme essential oils blend. • Addition of oregano-thyme essential oils blend into the \nbiopolymers blend increased elasticity, opacity, a*, and b* values. • Active films containing oregano-thyme essential oils blend showed \nantioxidant and antibacterial activity against E. coli, L. monocytogenes, S. aureus, and S. typhimurium. ✓ \n✓ \n✓ \nCao, Yang, and Song (2018) \n• TEMPO cellulose nanofiber (0, 15, \n25 and 100 wt.%) \n• Chitosan (0, 75, 85 and 100 wt.%) \n• Increasing proportion of chitosan in biopolymers blend showed a \nsignificant reduction in the growth of S. enterica, E. coli O157:H7, \nand L. monocytogenes and also had a significant increase in the \nantioxidant activity. ✓ \n✓ \nSoni, Mahmoud, Chang, El-Giar, \nand Hassan (2018) \n• Corn starch (5 % w/v) \n• Chitosan (1, 2, 3 and 4 % w/v) \n• Blending chitosan and corn starch showed an increase in water \nsolubility, total color differences, tensile strength and elasticity, \nand a reduction in crystallinity, elastic modulus, and water vapor \npermeability. • Increasing concentration of chitosan in biopolymers blend caused \nan increase in water vapor permeability and water content values. ✓ \n✓ \nRen et al. 3. Strategies for the improvement of properties of chitosan-based \nfilms (2017) \n• Rice starch (2 % w/v) \n• Chitosan (2 % w/v) \n• Cranberry, blueberry, beetroot, pomegranate, oregano, \npitaya, and resveratrol extract (0.5, 2, and 5 % w/w \nbased on dry biopolymers weight) \n• Addition of plant extracts into the biopolymers blend improved \nUV-Vis light barrier properties. • Active films containing beetroot, cranberry, and blueberry \nextracts showed higher antibacterial activity against E. coli, \naerobic mesophilic bacteria, and fungi (P. notatum, A. niger, and A. fumigatus). ✓ \nLozano-Navarro et al. (2017) \n• Pectin (2 % w/v) \n• Chitosan (2 % w/v) \n• Increasing pectin proportion in biopolymers blend caused an \nincrease in water solubility, water content, and swelling index. • Increasing chitosan proportion in biopolymers blend increased \ntensile strength and reduced elasticity values. ✓ \nBaron et al. (2017) \n• Xanthan gum (1.5 % w/v) \n• Chitosan (1.5 % w/v) \n• Addition of xanthan gum into the biopolymers blend did not affect \nthe water vapor permeability, solubility, and moisture content. • Increasing xanthan gum proportion in biopolymers blend caused \nan increase in tensile strength while it reduced elasticity values. ✓ \nde Morais Lima et al. (2017) \n• Tapioca starch (3 % w/w) \n• Chitosan (20, 40, 60, 80 % w/w of \ndry starch solid weight) \n• Increasing chitosan proportion in biopolymers blend up to 60 % \n(w/w) caused an increase in tensile strength and elastic modulus \nwhile elasticity values reduced. ✓ \nShapi’i and Othman (2016) \n• Carboxymethyl cellulose (1 % w/ \nv) \n• Chitosan (2 % w/v) \n• Zinc oxide nanoparticles (2, 4, and 8 % w/w) \n• Incorporation of zinc oxide nanoparticles into the biopolymers \nblend showed antimicrobial activity against S. aureus, P. aeruginosa, E. coli, C. albicans and prolonged the shelf life of white \nsoft cheese. ✓ \nYoussef, El-Sayed, El-Sayed, \nSalama, and Dufresne (2016) \n(continued on next page\n6 (\n)\nBiopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Cassava starch \n• Chitosan (0, 25, 50, 75, 100, and \n150 mg chitosan/g starch ratios) \n• Gallic acid \n• Increasing chitosan proportion in biopolymers blend decreased \nmoisture content, water activity, water vapor permeability, total \nphenolic contents, and antioxidant activities. • Blending chitosan and cassava starch reduced the growth of \nspoilage microorganisms and prolonged the shelf life of cooked \nham. 3. Strategies for the improvement of properties of chitosan-based \nfilms ✓ \n✓ \nZhao, Teixeira, Gänzle, and \nSaldaña (2018) \n• Burdock root inulin (4 % w/v) \n• Chitosan (2.5 % w/v) \n• Water vapor permeability, water solubility, water content, tensile \nstrength, and lightness value of inulin-chitosan films were reduced \nwith increasing oregano-thyme essential oils blend. • Addition of oregano-thyme essential oils blend into the \nbiopolymers blend increased elasticity, opacity, a*, and b* values. • Active films containing oregano-thyme essential oils blend showed \nantioxidant and antibacterial activity against E. coli, L. monocytogenes, S. aureus, and S. typhimurium. ✓ \n✓ \n✓ \nCao, Yang, and Song (2018) \n• TEMPO cellulose nanofiber (0, 15, \n25 and 100 wt.%) \n• Chitosan (0, 75, 85 and 100 wt.%) \n• Increasing proportion of chitosan in biopolymers blend showed a \nsignificant reduction in the growth of S. enterica, E. coli O157:H7, \nand L. monocytogenes and also had a significant increase in the \nantioxidant activity. ✓ \n✓ \nSoni, Mahmoud, Chang, El-G\nand Hassan (2018) \n• Corn starch (5 % w/v) \n• Chitosan (1, 2, 3 and 4 % w/v) \n• Blending chitosan and corn starch showed an increase in water \nsolubility, total color differences, tensile strength and elasticity, \nand a reduction in crystallinity, elastic modulus, and water vapor \npermeability. • Increasing concentration of chitosan in biopolymers blend caused \nan increase in water vapor permeability and water content values. ✓ \n✓ \nRen et al. (2017) \n• Rice starch (2 % w/v) \n• Chitosan (2 % w/v) \n• Cranberry, blueberry, beetroot, pomegranate, oregano, \npitaya, and resveratrol extract (0.5, 2, and 5 % w/w \nbased on dry biopolymers weight) \n• Addition of plant extracts into the biopolymers blend improved \nUV-Vis light barrier properties. • Active films containing beetroot, cranberry, and blueberry \nextracts showed higher antibacterial activity against E. coli, \naerobic mesophilic bacteria, and fungi (P. notatum, A. niger, and A. fumigatus). ✓ \nLozano-Navarro et al. (2017)\n• Pectin (2 % w/v) \n• Chitosan (2 % w/v) \n• Increasing pectin proportion in biopolymers blend caused an \nincrease in water solubility, water content, and swelling index. • Increasing chitosan proportion in biopolymers blend increased \ntensile strength and reduced elasticity values. ✓ \nBaron et al. (2017) \n• Xanthan gum (1.5 % w/v) \n• Chitosan (1.5 % w/v) \n• Addition of xanthan gum into the biopolymers blend did not affect \nthe water vapor permeability, solubility, and moisture content. • Increasing xanthan gum proportion in biopolymers blend caused \nan increase in tensile strength while it reduced elasticity values. 3. Strategies for the improvement of properties of chitosan-based \nfilms ✓ \nde Morais Lima et al. (2017)\n• Tapioca starch (3 % w/w) \n• Chitosan (20, 40, 60, 80 % w/w of \ndry starch solid weight) \n• Increasing chitosan proportion in biopolymers blend up to 60 % \n(w/w) caused an increase in tensile strength and elastic modulus \nwhile elasticity values reduced. ✓ \nShapi’i and Othman (2016) \n• Carboxymethyl cellulose (1 % w/ \nv) \n• Chitosan (2 % w/v) \n• Zinc oxide nanoparticles (2, 4, and 8 % w/w) \n• Incorporation of zinc oxide nanoparticles into the biopolymers \nblend showed antimicrobial activity against S. aureus, P. aeruginosa, E. coli, C. albicans and prolonged the shelf life of white \nsoft cheese. ✓ \nYoussef, El-Sayed, El-Sayed, \nSalama, and Dufresne (2016)\n(continued on nex\n6 6 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. H. Haghighi, et al. Table 2 (continued) \nBiopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Carboxymethyl cellulose (2 % w/ \nv) \n• Qaternized chitosan (5 % w/v) \n• Increasing carboxymethyl cellulose proportion in biopolymers \nblend caused an improvement in tensile strength, thermostability, \nand water vapor permeability values while oxygen permeability \nand opacity values increased. • Increasing carboxymethyl cellulose proportion in biopolymers \nblend caused a reduction in antibacterial activity against E. coli \nand S. aureus. • Higher proportion of quaternized chitosan in biopolymers blend \ndelayed the deterioration of banana fruit. • Quaternary ammonium chitosan was water soluble over a wide \nrange of pH values. The antibacterial activity of quaternized \nchitosan films was better than that of chitosan itself, but these \nfilms showed poor mechanical properties. ✓ \n✓ \n✓ \n✓ \nHu, Wang, and Wang (2016) \ng g , Aloui, & El-Saied, 2014), fillers incorporation (Abdelrazek, Elashmawi, \n& Labeeb, 2010), high-energy irradiation (Shahbazi, Rajabzadeh, & \nAhmadi, 2017) and blending with other biopolymers (Muxika, \nEtxabide, Uranga, Guerrero, & de la Caba, 2017; Wang, Qian, & Ding, \n2018). Blending chitosan with other polymers to form a composite film \ncould combine the advantages of the base polymers into a film with \nhigher performances compared with those of each constituent. A series \nof natural and synthetic polymers have been reported to blend with \nchitosan, such as pectin (Baron, Pérez, Salcedo, Córdoba, & do A. 3. Strategies for the improvement of properties of chitosan-based \nfilms Sobral, 2017; Younis & Zhao, 2019), cellulose and its derivatives \n(Noshirvani et al., 2017; Valizadeh, Naseri, Babaei, Hosseini, & Imani, \n2019), starch (Ren, Yan, Zhou, Tong, & Su, 2017; Suriyatem, Auras, & \nRachtanapun, 2018), gelatin (Bonilla, Poloni, Lourenço, & Sobral, \n2018; Guo et al., 2019), soy protein isolate (Li et al., 2017), polyvinyl \nalcohol (Do Yoon, Kim, Kim, & Je, 2017), polylactic acid (Liu, Wang, \nZhang, Lan, & Qin, 2017), etc. 4. Chitosan blends A polymer blend is a compatible or phase-separated mixture of at \nleast two polymers or copolymers, that is produced to enhance the \nphysical properties of each component (Cazón & Vázquez, 2020; Khan, \nMansha, & Mazumder, 2018). The objective of polymer blending is to \ndevelop composite materials in a simple and cost-effective route which \nwould combine the features of components, possibly enhancing their \nuseful attributes, and minimizing their drawbacks (Parameswaranpillai, \nThomas, & Grohens, 2015; Unger, Sedlmair, Siesler, & Hirschmugl, \n2014). The success of polymer blending as a strategy to improve packaging \nmaterials relies on the wide range of resulting physical, thermal, me­\nchanical, barrier, and optical properties. Therefore, studying these \nproperties plays a key factor in the suitable formulation of blends ad­\ndressed to specific applications. i\nThe growing interest towards chitosan for packaging applications \nhas resulted in many published studies focusing on the production and \ninvestigation of properties of films obtained from chitosan blended with \nother natural and synthetic polymers (Kumar, Mukherjee, & Dutta, \n2020). In this study, chitosan blends have been classified into two main \ngroups, respectively chitosan-natural biopolymers blends and chitosan- \nsynthetic polymers blends. A synopsis of the literature published in the \nlast five years is presented in each subsection considering: type of \npolymer and its concentration, active compounds, and other additives \nincorporated in the blend and the main properties of the blend films \naddressed for food packaging applications. 4.1. Chitosan-natural biopolymer blends The functional properties of chitosan-based films can be improved \nby blending with other natural biopolymers such as polysaccharides, \nproteins, and their derivatives (Aider, 2010; Cazón & Vázquez, 2020; \nElsabee & Abdou, 2013). Compatibility between chitosan and these \npolymers depends on the ability to associate through electrostatic in­\nteraction due to chitosan cationic character at appropriate pH condi­\ntions and the availability of high-polarity groups, such as NH/NH2, OH, \nC]O, C−O−Cee, in its backbone to form intermolecular hydrogen \nbonds or dipole association with the corresponding functional groups of \nother biopolymers (Bonilla et al., 2018). It has been reported that \npolysaccharides such as pectin, starch (from rice, corn, potato, cassava, \netc.), alginate, carrageenan, xanthan gum, xylan, glucose, kefiran, cel­\nlulose, and its derivatives can be blended with chitosan (Wang et al., \n2018). A synopsis of recent advances in chitosan-polysaccharide blend \nfilms for packaging applications is presented in Table 2. i i\nProtein-based films from animal sources (gelatin, collagen, casein, \nwhey protein, etc.) and plant source (soy protein isolate, corn zein, \nkidney bean protein isolate, quinoa protein, wheat gluten, etc.) have \nbeen studied for the development of biodegradable films due to their 7 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. . Improvement of the parameters investigated in each contribution is reported as follows. M: \nal activity\nHaghig (continued on next page) Table 3 \nSynopsis of research published between 2015 – 2020 addressing chitosan-protein blend films for food packaging applications. Improvement of the parameters investigated in each contribution is reported as follows\nmechanical properties, WB: water barrier property, GB: gas barrier permeability, AO: antioxidant activity, AM: antimicrobial activity. Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Sheep bone collagen (1.5 % w/v) \n• Skin gelatin (1.5 % w/v) \n• Chitosan (1.5 % w/v) \n• Addition of chitosan into bone collagen improved transparency and \ntensile strength of bone collagen film. • Increasing proportion of chitosan over 50 % in the biopolymers blend \nimproved the elasticity value. • Blending chitosan and bone collagen led to an improvement in UV barrier \nproperty, water solubility, and thermal stability while water vapor \npermeability increased. ✓ \nHou et al. 4.1. Chitosan-natural biopolymer blends (2020) \n• Hordein nanofiber (11 % w/v) \n• Chitosan (0.4 % w/v) \n• Quercetin (5 % w/w based on hordein) \n• Addition of quercetin into the nano biopolymers blend showed \nantioxidant activity and treating films with different temperatures (90, \n120, 150, and 180 °C) did not influence the antioxidant activity. • Heat treatment enhanced the water resistance of nano biopolymers blend. • Covering apple and potato samples with heat treated nano fiber films \ndelayed the rate of enzymatic browning and preserved their fresh color \nafter 6 and 12 h, respectively. ✓ \n✓ \nLi, Yan, Guan, and Huang (2020\n• Zein (2 % w/v) \n• Chitosan (2 % w/v) \n• α-tocopherol (50 % w/w based on the content \nof dry materials) \n• Active zein-chitosan films containing α-tocopherol reduced the \npostharvest deterioration of mushroom (Agaricus bisporus) at 4 °C for 12 \ndays. This was mainly due to the excellent gas barrier property and \nantioxidant activity of films. ✓ \n✓ \nZhang, Liu, Sun, Wang, and Li \n(2020) \n• Gelatin (2 % w/v) \n• Chitosan (2 % w/v) \n• Polyphenols from the fruits of Chinese \nhawthorn (2, 4, and 6 % w/w on the total \nbiopolymer weight) \n• Addition of the polyphenol extract into the biopolymers blend increased \nthickness, tensile strength, elasticity, opacity, and total color difference, \nwhile water content and water vapor permeability reduced. • Antioxidant activity of films significantly improved by increasing the \nconcentration of polyphenol extract. ✓ \n✓ \n✓ \nKan et al. (2019) \n• Gelatin (5 % w/v) \n• Chitosan (3, 6 and 9 % w/w based on \ngelatin) \n• Citric acid (10 and 20 % w/w based on gelatin \nweight) \n• Incorporation of citric acid into the biopolymer blend improved elasticity \nvalues. • Higher concentration of chitosan and citric acid in biopolymers blend led \nto better antibacterial activity against E. coli. ✓ \n✓ \nUranga et al. (2019) \n• Fish myofibrillar protein (0.45, 0.8, \n1.3, 1.8, and 2.14 % w/v) \n• Chitosan (13.18, 20, 30, 40, and \n46.81 % w/w) \n• The optimum formulation to produce biodegradable film contained 1.3 % \n(w/v) fish myofibrillar proteins, 30 % (w/w) chitosan, and 40 % (w/w) \nglycerol. • Adding chitosan in the biopolymers blend increased elasticity, thermal \nstability, UV barrier properties while solubility, swelling degree, and \nwater vapor permeability decreased. 4.1. Chitosan-natural biopolymer blends ✓ \n✓ \nBatista, Araújo, Peixoto Joele, Sil\nJúnior, and Lourenço (2019) \n• Porcine plasma protein (3 % w/w) \n• Chitosan (1 % w/w) \n• The porcine plasma protein/chitosan blend film had lower transparency \nthan neat porcine plasma protein and chitosan film. • Blending porcine plasma protein and chitosan increased thermal stability. • Blend films (ratio 1:1) showed improvement in water resistance and \nwater vapor permeability, solubility, and mechanical properties \ncompared to the neat porcine plasma protein film. ✓ \n✓ \nSamsalee and Sothornvit (2019) \n• Gelatin (2 % w/v) \n• Chitosan (2 % w/v) \n• Cinnamon, citronella, pink clove, nutmeg and \nthyme essential oils (1 % w/w based on \nweight) \n• Addition of essential oils into the biopolymers blend improved UV barrier \nproperties and increased thickness, water content, water vapor \npermeability, opacity, and total color difference values. • Incorporation of essential oils into biopolymers blend showed \nantibacterial activity against C. jejuni, E. coli, L. monocytogenes, and S. typhimurium. ✓ \n✓ \nHaghighi, Biard et al. (2019) \n• Gelatin (1 % w/v) \n• Chitosan (1 % w/v) \n• Cinnamon essential oil (0.4 % w/w based on a \ndry biopolymer weight) \n• Addition of cinnamon essential oil into the biopolymer blend improved \nelasticity, thermal stability, water vapor permeability, UV barrier, and \ncontact angle values. • Active films containing cinnamon essential oils showed antibacterial \nactivity against E. coli and S. aureus. ✓ \n✓ \n✓ \nGuo et al. (2019) \n• Collagen (3.5 % w/v) \n• Chitosan (1 % w/v) \n• Pomegranate peel extract (1, 3, and 5 % v/v) • Addition of 5 % pomegranate peel extract into the biopolymers blend \ncaused a reduction in water solubility and enhanced antibacterial activity \nagainst B. saprophyticus, B. subtilis, S. typhi, and E. coli. ✓ \nBhuimbar, Bhagwat, and Dandge\n(2019) \n(continued on next p 8 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. H. Haghighi, et al. Table 3 (continued) \nBiopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Zein (10 % w/v) \n• Chitosan (6 wt%) \n• TiO2 nanoparticles (0.05, 0.1, 0.15, 0.2, and \n0.25 % w/w) \n• Addition of TiO2 nanoparticles up to 0.2 % into the biopolymers blend \nenhanced water absorption and water vapor permeability. • Biopolymers blend containing TiO2 nanoparticles showed antibacterial \nactivity against S. aureus, E. coli, and S. enteritidis. ✓ \n✓ \nQu et al. 4.1. Chitosan-natural biopolymer blends (2019) \n• Gelatin (2 % w/v) \n• Chitosan (2 % w/v) \n• Ethyl lauroyl arginate (0.1 % v/v) \n• Blending chitosan and gelatin caused an improvement in mechanical and \nwater barrier properties. • Incorporation of ethyl lauroyl arginate into the biopolymer blend \nconferred antibacterial activity against C. jejuni, E. coli, L. monocytogenes, \nand S. typhimurium. ✓ \n✓ \n✓ \nHaghighi, De Leo et al. (2019) \n• Gelatin (2 % w/v) \n• Chitosan (2 % w/v) \n• Silver nanoparticle (0.05 and 0.1 % w/w) \n• Addition of silver nanoparticles into the biopolymers blend enhanced \nelasticity values while tensile strength and light transmittance in the \nvisible light region were reduced. • Incorporation of silver nanoparticles into the biopolymers blend showed \nantimicrobial activity. • Shelf life of red grapes fruits wrapped with gelatin-chitosan blend \nenriched with silver nanoparticles was extended for additional two weeks. ✓ \n✓ \nKumar, Shukla, Baul, Mitra, and \nHalder (2018) \n• Gelatin (1 % w/v) \n• Chitosan (2 % w/v) \n• β-Carotene loaded starch nanocrystals (1mg/ \n1 mL) \n• Addition of β-carotene loaded starch nanocrystals into the biopolymers \nblend caused a significant reduction in water solubility while antioxidant \nactivity increased. ✓ \nHari, Francis, Rajendran Nair, and \nNair (2018) \n• Gelatin (3 % w/v) \n• Chitosan (1 % w/v) \n• Gallic acid (1 % w/w total dry weight of film) \n• Tween 80 (50 and 100 % w/w based on the \nweight of the gallic acid \n• β-cyclodextrin \n• Ethanol \n• Addition of gallic acid into the biopolymers blend increased opacity and \nelasticity. • Incorporation of β-cyclodextrin and gallic acid into the biopolymers blend \nreduced water barrier properties. ✓ \n✓ \nRezaee, Askari, EmamDjomeh, and\nSalami (2018) \n• Gelatin (4 % w/v) \n• Chitosan (1 % w/v) \n• Eugenol and ginger essential oils (0.5 % w/w \nbased on dry biopolymers weight) \n• Addition of essential oils into the biopolymers blend improved elasticity \nand UV barrier properties. • Incorporation of essential oils into biopolymers blend showed significant \nantioxidant activity. ✓ \n✓ \nBonilla et al. (2018) \n• Gelatin (3 % w/v) \n• Chitosan (1 % w/v) \n• Procyanidin (0.25, 0.5, 0.75, and 1 mg/mL) • Addition of procyanidin into the biopolymers blend improved elasticity, \nwater vapor permeability, water solubility, swelling index, and UV barrier \nproperties while tensile strength was reduced. • Incorporation of procyanidin into the biopolymers blend showed \nantioxidant activity and antibacterial activity against S. aureus and E. coli \nstrains. 4.1. Chitosan-natural biopolymer blends ✓ \n✓ \n✓ \n✓ \nRamziia, Ma, Yao, Wei, and Huang\n(2018) \n• Soy protein isolate (2 % w/w) \n• Chitosan (2 % w/w) \n• Elasticity, thermal stability, and homogeneity of chitosan film increased \nby blending with soy protein isolate. ✓ \nXing, Zhang, Li, Li, and Shi (2018)\n• Soy protein isolate \n• Chitosan (1 % w/w) \n• Cu nanoclusters (20 mmol/L) \n• Incorporation of copper nanoclusters into the biopolymers blend \nimproved tensile strength, elasticity, water vapor permeability, contact \nangle, and thermal stability. ✓ \n✓ \nLi et al. (2017) \n• Eggshell membrane gelatin (3 % w/v) \n• Chitosan (1.5 % w/v) \n• Blending chitosan and gelatin showed an improvement in elasticity, water \nsolubility, and water barrier property. ✓ \n✓ \nMohammadi et al. (2018) \n• Gelatin (4 %w/v) \n• Chitosan (1 % w/w) \n• Cinnamon, guarana, rosemary and boldo-do- \nchile ethanolic extract (1 % v/v) \n• Increasing chitosan proportion in biopolymers blend improved the \nmechanical properties and water vapor permeability. • Addition of ethanolic extracts into the biopolymers blend enhanced \nantioxidant and antibacterial activity against S. aureus and E. coli. ✓ \n✓ \n✓ \n✓ \nBonilla and Sobral (2016) \n• Gelatin (10 % w/v) \n• Chitosan (2 % w/v) \n• Boric acid (2, 3, 4 and 5 % w/w) \n• Polyethylene glycol (5, 10 and 20 % v/v) \n• Blending chitosan and gelatin showed UV barrier property. • Addition of boric acid into the biopolymer blend improved tensile \nstrength and water solubility, moisture content, and water vapor \npermeability. • Addition of polyethylene glycol into the biopolymers blend caused an \nincrease in elasticity, water content, and water solubility. ✓ \n✓ \nAhmed and Ikram (2016) \n• Corn starch (2 and 5 % w/v) \n• Gelatin (2 and 5 % w/v) \n• Chitosan (2 % w/v) \n• Glycerol and sorbitol (1, 2, 5, and 10 % w/w) • Addition of sorbitol into the chitosan-starch or chitosan-gelatin blend \nfilms enhanced water vapor permeability compared with films containing \nglycerol. ✓ \n✓ \nBadawy, Rabea, and El-Nouby \n(2016) 9 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. H. Haghighi, et al. high abundance, acceptable mechanical properties, excellent gas bar­\nrier properties to non-condensable gases (oxygen, carbon dioxide, and \nnitrogen) and aromas (Arfat, Ahmed, Hiremath, Auras, & Joseph, \n2017). 4.1. Chitosan-natural biopolymer blends The chitosan-protein blend film could render better functional \nproperties than single proteins and chitosan film, thus promoting their \napplication in food packaging (Basta, Khwaldia, Aloui, & El-Saied, \n2015; Ma et al., 2012; Wang et al., 2018). A synopsis of recent advances \nin chitosan-protein blend films for packaging applications is presented \nin Table 3. Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Addition of glycerol and sorbitol into the biopolymers blend showed \nantioxidant activity. • Quinoa protein (6.7 % w/v) \n• Chitosan (1.5 and 2 % w/v) \n• Chitosan-tripolyphosphate nano \nparticles (0.3 w/v) \n• Thymol nanoparticles (0.1 % w/v) \n• Addition of chitosan-tripolyphosphate nanoparticles into the biopolymers \nblend improved water vapor permeability. • Incorporation of chitosan-tripolyphosphate-thymol nanoparticles into the \nbiopolymers blend enhanced antibacterial activity against L. innocua, S. aureus, S. typhimurium, E. aerogenes, P. aeruginosa, and E. coli. ✓ \n✓ \nCaro et al. (2016) \n• Gelatin (3 % w/v) \n• Chitosan (2 % w/v) \n• Red grape seed extract (1 and 2 % w/w) \n• Ziziphora clinopodioides essential oil (1 and 2 \n% w/w) \n• Addition of red grape seed extract and Ziziphora clinopodioides into the \nbiopolymers blend showed antibacterial activity against L. monocytogenes, \ntotal mesophilic and psychrotrophic bacteria, Pseudomonas spp., P. fluorescens, S. putrefaciens, lactic acid bacteria and Enterobacteriaceae \nfamily. • Packing minced rainbow trout fillets with chitosan-gelatin blend enriched \nwith red grape seed extract and Ziziphora clinopodioides essential oil \nextended the shelf life at refrigerated condition due to the delay of lipid \noxidation and inhibition of bacterial growth. ✓ \n✓ \nKakaei and Shahbazi (2016) \n• Brewer’s spent grain protein (3 % w/ \nv) \n• Chitosan (2 % w/v) \n• Blending brewer’s spent grain protein with chitosan caused an \nimprovement in water vapor permeability and mechanical properties. • Blend films showed antioxidant and antibacterial activity against S. aureus, E. coli, L. monocytogenes, and S. typhimurium. ✓ \n✓ \n✓ \n✓ \nLee, Lee, Yang, and Song (2015) 4.2. Chitosan-synthetic polymers blends Blending chitosan with synthetic polymers (polyvinyl alcohol - PVA, \npolyvinyl pyrrolidone - PVP, polylactic acid - PLA, etc.) has been ex­\ntensively studied for the positive effects on the physical, mechanical, \nand biological features of composite films. The success of synthetic \npolymers as biodegradable materials depends on their diverse range of \nmechanical properties, chemical resistance, and low production costs \ncompared to natural polymers (Bourakadi et al., 2019). Chitosan is \npotentially miscible with some synthetic polymers mainly due to the \nformation of intermolecular hydrogen bonds between hydroxyl groups \nof synthetic polymer and hydroxyl and amine groups of chitosan \n(Bonilla, Fortunati, Atarés, Chiralt, & Kenny, 2014). Depending on the \ninteractions between polymer components, blending chitosan with \nsynthetic biopolymers can enhance the mechanical and water barrier \nproperties of films in some cases. A synopsis of recent advances in \nchitosan-synthetic polymer blend films for packaging applications is \npresented in Table 4. 5. Conclusions and future perspectives Packaging is an essential item responsible for the protection of the \nproduct and provides food safety assurance during marketing. Conventional plastic packaging material due to non-biodegradability \nand insufficient waste management system has labeled the food in­\ndustry as a source of pollution and social concerns. Therefore, bio- \nbased, and biodegradable materials have received considerable atten­\ntion to address these issues in recent years. The adoption of chitosan as \npackaging material could contribute to mitigating the environmental \nconcern, despite some drawbacks in terms of thermal stability, barrier \nand mechanical properties, and production costs. Blending chitosan \nwith other natural and synthetic polymers is an effective way to over­\ncome these limitations, making the films suitable for specific uses. This \napproach appears to have a bright future for innovative food packaging \ndesign since it will allow the partial replacement of the existing syn­\nthetic plastic packaging materials presently available in the market. Potential applications of chitosan blend-based films are for fresh pro­\nducts (vegetable, meat and fish) and foods with short to medium shelf \nlife. Such films may represent an interesting alternative to conventional \nplastic films especially when recycling is not possible or is compromised \ndue to presence of food residues: in these cases, the feature of biode­\ngradability/compostability offers a valid end-of-life alternative. Nanotechnologies certainly represent a promising complementary tool \nfor further improvement of mechanical and barrier properties of chit­\nosan-based films and for the addition of other functionalities (anti­\nmicrobial and antioxidant capacity), but their development and appli­\ncation faces resistance due to toxicological issues. In particular, \nnanocomposite materials based on the incorporation of biobased na­\nnomaterials such as nano-cellulose, emerge for their potential to pro­\nvide a barrier and mechanical strength maintaining the full biode­\ngradability of the material. Finally, despite contributions retrieved in \nliterature in the considered timeframe, the aspect of biodegradability \nremains mostly disregarded. This omission has two reasons: the first is \nlinked to the difficulty of applying a real holistic and multidisciplinary \napproach, necessary for the development of food packaging; the second \narises from the consideration that making a new material from 10 Food Packaging and Shelf Life 26 (2020) 100551 applications. Improvement of the parameters investigated in each contribution is reported as \n: antimicrobial activity\nHaghig H. Haghighi, et al. Table 4 \nSynopsis of research published between 2015 – 2020 addressing chitosan-synthetic biopolymer blend films for food packaging applications. 5. Conclusions and future perspectives Improvement of the parameters investigated in each contribution is reported as \nfollows. M: mechanical properties, WB: water barrier properties, GB: gas barrier permeability, AO: antioxidant activity, AM: antimicrobial activity. Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• PVA (0.5, 1, 1.5, and 2 % w/v) \n• Chitosan (0.5, 1, 1.5, and 2 % w/ \nv) \n• Ethyl vanillin (2 % w/v) \n• Addition of ethyl vanillin into the biopolymers blend caused an \nimprovement in the tensile strength, surface hydrophobicity, and UV barrier \nproperties while water vapor transmission rate and oxygen transmission rate \nwere reduced. • Blend films containing ethyl vanillin showed antimicrobial activity against \nS. aureus and E. coli. ✓ \n✓ \n✓ \n✓ \nNarasagoudr, Hegde, Vanjeri, \nChougale, and Masti (2020) \n• PVA (4 % w/w) \n• Chitosan (2 % w/w) \n• Glycerol \n• Polyethylene glycol \n• Glycerol/ Polyethylene glycol \n• Addition of glycerol showed an enhancement in the crystallinity of PVA/ \nchitosan blends while polyethylene glycol reduced the extent of \ncrystallization. • Combination of glycerol and polyethylene glycol led to the highest level of \ncompatibility. Flexibility of the blend plasticized with the combination of \npolyethylene glycol and glycerol was improved five-times of the blend \nplasticized with glycerol. However, the antibacterial activity of the \nchitosan/PVA blend plasticized with polyethylene glycol /glycerol was \nsignificantly reduced compared to that of glycerol or polyethylene glycol. ✓ \n✓ \nShojaee Kang Sofla, Mortazavi, \nand Seyfi (2020) \n• PVA (4 % w/w) \n• Liquefied chitin (1 % w/w) \n• Silica (0.1, 0.2, 0.4, 0.8, and 1.6 wt.%) \n• Addition of silica into the biopolymers blend up to 0.2 % (wt.) improved the \ntensile strength and elasticity values. • Addition of silica into the biopolymers blend up to 0.2 % (wt.) improved the \nbrowning index of fresh cherries. • Compared with synthetic food packaging materials, the blend films \ndegraded quickly in the soil while addition of silica slightly reduced the \nbiodegradability. ✓ \nZhang, Xu et al. (2020) \n• PVA (5 % w/v) \n• Chitosan (1 % w/v) \n• Ethyl lauroyl arginate (1, 2.5, 5, and 10 % w/w) • Addition of ethyl lauroyl arginate into the biopolymers blend negatively \ninfluenced elasticity, tensile strength, and water barrier properties while \nbarrier properties to UV light improved. • Chitosan-gelatin blend enriched with ethyl lauroyl arginate exhibited \nantibacterial activity against C. jejuni, E. coli, L. monocytogenes and S. typhimurium. ✓ \nHaghighi et al. 5. Conclusions and future perspectives ✓ \nCazón, Vázquez, and Velazquez \n(2018) \n• PVA (3 % w/v) \n• Chitosan (1.5 % w/v) \n• Cellulose nanocrystals from rice straw (1, 3, and 5 \n% w/w base on polyvinyl alcohol-chitosan blend) • Addition of cellulose nanocrystals into PVA-chitosan blend improved tensile \nstrength and thermal properties. • PVA-chitosan blend films enriched with cellulose nanocrystal from rice \nstraw showed antifungal activity against C. gloeosporioides and antibacterial \nactivity against S. mutans, S.aureus, E.coli, and P.aeruginosa. ✓ \n✓ \nPerumal, Sellamuthu, Nambiar, \nand Sadiku (2018) \n• PVA (1 % w/v) \n• Chitosan (2 % w/v) \n• SiO2 (0.3, 0.6, and 0.9 %w/w) \n• Addition of silicon dioxide into the biopolymers blend caused an \nenhancement in mechanical, water and oxygen barrier properties. ✓ \n✓ \nYu, Li, Chu, and Zhang (2018) \n• PVA (10 %w/v) \n• Chitosan (2, 2.5, 3, and 3.5 % w/ \nv) \n• In comparison to neat PVA film, blending PVA and chitosan caused an \nimprovement in elasticity and oxygen barrier properties while water barrier \npropertied decreased. Increasing proportion of chitosan in biopolymers \nblend showed better antibacterial activity against S. aureus and E. coli. ✓ \n✓ \n✓ \nLiu, Wang, and Lan (2018) \n• PVA (2 % w/v) \n• Chitosan (2 % w/v) \n• Sulfosuccinic acid \n• (5, 10, 15, 20, and 30 wt%) \n• Glycerol (0−60 wt%) \n• Xylitol (0−60 wt%)\n• Addition of sulfosuccinic acid into the biopolymers blend caused an \nenhancement in tensile strength, elasticity, swelling degree, water solubility, \nthermal stability, and optical properties. ✓ \nYun, Lee, Kim, and Yoon (2017) \naghighi, et al. Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Microcrystalline cellulose (3, 4 \nand 5 % w/w) \n• PVA (2 and 4 % w/w) \n• Chitosan (0.5 and 1 % w/w) \n• Addition of chitosan-PVA blend into the cellulose based films caused an \nimprovement in mechanical properties. • Blending chitosan and cellulose improved barrier properties to the UV light. • Addition of PVA into the biopolymers blend caused an improvement in light \ntransmittance values. ✓ \nCazón, Vázquez, and Velaz\n(2018) \n• PVA (3 % w/v) \n• Chitosan (1.5 % w/v) \n• Cellulose nanocrystals from rice straw (1, 3, and 5 \n% w/w base on polyvinyl alcohol-chitosan blend) • Addition of cellulose nanocrystals into PVA-chitosan blend improved tensile \nstrength and thermal properties. • PVA-chitosan blend films enriched with cellulose nanocrystal from rice \nstraw showed antifungal activity against C. gloeosporioides and antibacterial \nactivity against S. 5. Conclusions and future perspectives mutans, S.aureus, E.coli, and P.aeruginosa. ✓ \n✓ \nPerumal, Sellamuthu, Nam\nand Sadiku (2018) \n• PVA (1 % w/v) \n• Chitosan (2 % w/v) \n• SiO2 (0.3, 0.6, and 0.9 %w/w) \n• Addition of silicon dioxide into the biopolymers blend caused an \nenhancement in mechanical, water and oxygen barrier properties. ✓ \n✓ \nYu, Li, Chu, and Zhang (20\n• PVA (10 %w/v) \n• Chitosan (2, 2.5, 3, and 3.5 % w/ \nv) \n• In comparison to neat PVA film, blending PVA and chitosan caused an \nimprovement in elasticity and oxygen barrier properties while water barrier \npropertied decreased. Increasing proportion of chitosan in biopolymers \nblend showed better antibacterial activity against S. aureus and E. coli. ✓ \n✓ \n✓ \nLiu, Wang, and Lan (2018)\n• PVA (2 % w/v) \n• Chitosan (2 % w/v) \n• Sulfosuccinic acid \n• (5, 10, 15, 20, and 30 wt%) \n• Glycerol (0−60 wt%) \n• Xylitol (0−60 wt%) \n• Sorbitol (0−60 wt%) \n• Addition of sulfosuccinic acid into the biopolymers blend caused an \nenhancement in tensile strength, elasticity, swelling degree, water solubility, \nthermal stability, and optical properties. ✓ \nYun, Lee, Kim, and Yoon (2\n• PVA (1 % w/v) \n• Chitosan-gallic acid (0.1, 0.5, and \n1 % w/v) \n• Increasing chitosan-gallic acid concentration into the biopolymers blend and \ntreating with UV caused an increase in tensile strength while elasticity \nvalues were reduced. • Films containing chitosan-galic acid (1 % w/v) showed antibacterial activity \nagainst E. coli, S. typhimurium, S. aureus, and B. cereus. ✓ \n✓ \nDo Yoon et al. (2017) \n• PVA (5 % w/v) \n• Sodium lactate loaded chitosan \n(2 % w/v) \n• Montmorillonite (0, 5, 10, 15, and 20 % w/w, \nbased on the dry weight of CS/PVA) \n• Montmorillonite concentration up to 15 % in biopolymers blend improved \ntensile strength and elastic modulus while elasticity values decreased. • Addition of montmorillonite into the biopolymers blend enhanced barrier \nproperties to water vapor, oxygen, and carbon dioxide. Blend films showed \nantibacterial activity against E. coli. ✓ \n✓ \n✓ \n✓ \nZhang et al. (2017) \n• PVA (5 % w/v) \n• Chitosan (0.15 % w/w) \n• Carvacrol (5 % w/v) \n• Cellulose nanocrystals (3 % w/w) \n• Addition of carvacrol and cellulose nanocrystal into the biopolymer blend \ncaused an improvement in mechanical properties while color and \ntransparency were not affected. • Blend films showed antioxidant activity and antimicrobial activity against P. carotovorum subsp. Odoriferum, and X. axonopodis. 5. Conclusions and future perspectives (2020) \n• PVA (0.5 % w/v) \n• Xylan (0.5 % w/v) \n• Chitosan (1 % w/v) \n• Nano hydroxyapatite \n• (0.01 w/v) \n• Curcumin (0.01 w/v) \n• PVA-xylan-chitosan-nano hydroxyapatite-curcumin films were developed as \nintelligent packaging to assess the freshness of Indian oil sardine fish at \nroom temperature. • In vitro biodegradation test showed that incorporation of curcumin into the \nbiopolymers blend increased resistance to biodegradation and improved \nlongevity of these scaffolds for longer last. ✓ \nVadivel et al. (2019) \n• Poly(ε-capro-lactone) (6 % w/v) \n• Chitosan (1 % w/v) \n• Oregano essential oil (1, 3, and 5 % w/w) \n• Addition of oregano essential oil into the biopolymers blend caused a \nreduction in tensile strength and elastic modulus while water vapor \npermeability and elasticity values increased. • Poly(ε-caprlactone)-chitosan blend mats containing 5 % oregano essential \noil showed antibacterial activity against S. aureus, L. monocytogenes, S. enteritidis, and E. coli. ✓ \nHasanpour Ardekani-Zadeh and \nHosseini (2019) \n• PVA (2 % w/v) \n• Fish gelatin (2 % w/v) \n• Chitosan (1.5 % w/v) \n• Increasing fish gelatin proportion in biopolymers blend caused an increase \nin water vapor permeability, water absorption, and opacity values while \nwater solubility, tensile strength, and elasticity values reduced. Ghaderi, Hosseini, Keyvani, and \nGómez-Guillén (2019) \n• PVA (4% w/v) \n• Chitosan (1.25 % w/v) \n• Thiabendazol-ium-montmorillonite (5 % w/w) \n• Addition of thiabendazolium into the biopolymers blend caused an increase \nin tensile strength and elastic modulus values. Chitosan-PVA blend films \ncontaining thiabendazolium showed antibacterial activity against P, \naeruginosa, S. aureus, and E. coli. ✓ \n✓ \nBourakadi et al. (2019) \n• PVA (2 % w/v) \n• Chitosan (2 % w/v) \n• Increasing chitosan proportion in the biopolymer blend caused a reduction \nin tensile strength and elasticity values while UV barrier properties \nimproved. Wu, Ying, Liu, Zhang, and Huang \n(2018) \n(\nd\n)\n11 11 Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Microcrystalline cellulose (3, 4 \nand 5 % w/w) \n• PVA (2 and 4 % w/w) \n• Chitosan (0.5 and 1 % w/w) \n• Addition of chitosan-PVA blend into the cellulose based films caused an \nimprovement in mechanical properties. • Blending chitosan and cellulose improved barrier properties to the UV light. • Addition of PVA into the biopolymers blend caused an improvement in light \ntransmittance values. References Abdelrazek, E. M., Elashmawi, I. S., & Labeeb, S. (2010). Chitosan filler effects on the \nexperimental characterization, spectroscopic investigation and thermal studies of \nPVA / PVP blend films. Physica B: Physics of Condensed Matter, 405(8), 2021–2027. https://doi.org/10.1016/j.physb.2010.01.095. Águila-Almanza, E., Salgado-Delgado, R., Vargas-Galarza, Z., García-Hernández, E., & \nHernández-Cocoletzi, H. (2019). Enzymatic depolymerization of chitosan for the \npreparation of functional membranes. Journal of Chemistry, 2019, 1–8. https://doi. org/10.1155/2019/5416297. i Ahmed, S., & Ikram, S. (2016). Chitosan and gelatin based biodegradable packaging films \nwith UV-light protection. Journal of Photochemistry and Photobiology B, Biology, 163, \n115–124. https://doi.org/10.1016/j.jphotobiol.2016.08.023. Ahmed, S., & Ikram, S. (2017). Chitin and chitosan: History, composition and properties. In S. Ahmed, & S. Ikram (Eds.). Chitosan: Derivatives, composites and applications (pp. 1–24). Scrivener Publishing LLC. i g\nAider, M. (2010). Chitosan application for active bio-based films production and potential \nin the food industry: Review. LWT - Food Science and Technology, 43(6), 837–842. https://doi.org/10.1016/j.lwt.2010.01.021. g\nj\nAl-Tayyar, N. A., Youssef, A. M., & Al-hindi, R. (2020). Antimicrobial food packaging \nbased on sustainable bio-based materials for reducing foodborne pathogens: A re­\nview. Food Chemistry, 310, Article 125915. https://doi.org/10.1016/j.foodchem. 2019.125915. Arfat, Y. A., Ahmed, J., Hiremath, N., Auras, R., & Joseph, A. (2017). Thermo-mechanical, \nrheological, structural and antimicrobial properties of bionanocomposite films based \non fish skin gelatin and silver-copper nanoparticles. Food Hydrocolloids, 62, 191–202. https://doi.org/10.1016/j.foodhyd.2016.08.009. Argüelles-Monal, W. M., Lizardi-Mendoza, J., Fernández-Quiroz, D., Recillas-Mota, M. T., \n& Montiel-Herrera, M. (2018). Chitosan derivatives: Introducing new functionalities \nwith a controlled molecular architecture for innovative materials. Polymers, 10(3), \n342. https://doi.org/10.3390/polym10030342. g\ny\nArikan, E. B., & Ozsoy, H. D. (2015). A review: Investigation of bioplastics. Journal of Civil \nEngineering and Architecture, 9(2), 188–192. https://doi.org/10.17265/1934-7359/ \n2015.02.007. Badawy, M. E. I., Rabea, E. I., & El-Nouby, M. A. M. (2016). Preparation, physicochemical \ncharacterizations, and the antioxidant activity of the biopolymer films based on \nmodified chitosan with starch, gelatin, and plasticizers. Journal of Polymer Materials, \n33(1), 17–32. https://doi.org/10.1007/s10924-013-0621-z. Baron, R. D., Pérez, L. L., Salcedo, J. M., Córdoba, L. P., & do A. Sobral, P. J. (2017). Production and characterization of films based on blends of chitosan from blue crab \n(Callinectes sapidus) waste and pectin from Orange (Citrus sinensis Osbeck) peel. International Journal of Biological Macromolecules, 98, 676–683. https://doi.org/10. 1016/j.ijbiomac.2017.02.004. j j\nBasta, A. H., Khwaldia, K., Aloui, H., & El-Saied, H. (2015). Enhancing the performance of \ncarboxymethyl cellulose by chitosan in producing barrier coated paper sheets. 5. Conclusions and future perspectives (2016) \n• PLA (1 % w/v) \n• Chitosan (1 % w/v) \n• Methyldiphenyl diisocyanate (0.2,1, 2, and 3 % w/ \nw of the final PLA/chitosan solution) \n• Increasing concentration of methyldiphenyl diisocyanate in biopolymers \nblend improved tensile strength and contact angle values. ✓ \nGartner, Li, and Almenar (2015) Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• PVA \n• Chitosan (1 % w/v) \n• Potassium nitrate \n• (0.1, 0.2, 0.3, 0.4, and 0.5 % w/w) \n• Addition of potassium nitrate into the biopolymers blend caused an \nimprovement in tensile strength and elasticity due to its crosslinking effect. • The degradation behavior can be improved with addition of potassium \nnitrate. ✓ \nJahan et al. (2016) \n• PLA (1 % w/v) \n• Chitosan (1 % w/v) \n• Methyldiphenyl diisocyanate (0.2,1, 2, and 3 % w/ \nw of the final PLA/chitosan solution) \n• Increasing concentration of methyldiphenyl diisocyanate in biopolymers \nblend improved tensile strength and contact angle values. ✓ \nGartner, Li, and Almenar (2015) biodegradable components would result in a new biodegradable ma­\nterial. This should not be taken for granted and requires verification \nespecially in the case of film incorporation of antimicrobial compounds. Indeed, compounds which inhibit microbial food spoilage might also \ncause negative effects in the composting process. Hence, future research \non chitosan-based films and sustainable materials, in general, should \ninclude biodegradability among the targeted parameters. 5. Conclusions and future perspectives ✓ \n✓ \n✓ \nLuzi et al. (2017) \n• PVA (2 % w/v) \n• Chitosan (2 % w/v) \n• Increasing proportion of PVA in biopolymers blend caused an increase in \ntensile strength and elasticity. • Increasing proportion of chitosan in the blend improved antioxidant activity \nand antibacterial activity against S. aureus, B. cereus M. luteus, S. enterica, E. coli, and S. typhimurium. ✓ \n✓ \n✓ \nHajji et al. (2016) \n• PVA (10, 20, and 30 % w/w) \n• Montmorillonite (5 %w/v) \n• Chitosan (2 % w/v) \n• Addition of PVA into the biopolymers blend caused a plasticizing effect \nwhile tensile strength decreased. Also, barrier properties to water and \noxygen improved. • Incorporation of montmorillonite into the biopolymer blend enhanced the \nmechanical and antimicrobial activities while barrier properties to water \nand oxygen reduced. ✓ \n✓ \n✓ \n✓ \nGiannakas et al. (2016) \n• EVOH (4 % w/v) \n• Chitosan \n• Nano zinc oxide (1 and 2 %w/w) \n• Addition of nano zinc oxide into the biopolymers blend caused an \nimprovement in barrier properties against water vapor and oxygen. • Presence of chitosan and nano zinc oxide caused excellent antimicrobial \nactivity against A. niger and E.coli. Adding nano zinc oxide improved barrier, \nmechanical, and antimicrobial properties. ✓ \n✓ \n✓ \n✓ \nSadeghi and Shahedi (2016\n(continued on nex 12 Additives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• Potassium nitrate \n• (0.1, 0.2, 0.3, 0.4, and 0.5 % w/w) \n• Addition of potassium nitrate into the biopolymers blend caused an \nimprovement in tensile strength and elasticity due to its crosslinking effect. • The degradation behavior can be improved with addition of potassium \nnitrate. ✓ \nJahan et al. (2016) \n• Methyldiphenyl diisocyanate (0.2,1, 2, and 3 % w/ \nw of the final PLA/chitosan solution) \n• Increasing concentration of methyldiphenyl diisocyanate in biopolymers \nblend improved tensile strength and contact angle values. ✓ \nGartner, Li, and Almenar (2015) \nHaghighi, et al. Food Packaging and Shelf Life 26 (2020) 100551 H. Haghighi, et al. H. Haghighi, et al. Biopolymer \nAdditives \nKey findings \nM \nWB \nGB \nAO \nAM \nReference \n• PVA \n• Chitosan (1 % w/v) \n• Potassium nitrate \n• (0.1, 0.2, 0.3, 0.4, and 0.5 % w/w) \n• Addition of potassium nitrate into the biopolymers blend caused an \nimprovement in tensile strength and elasticity due to its crosslinking effect. • The degradation behavior can be improved with addition of potassium \nnitrate. ✓ \nJahan et al. References Nordic \nPulp and Paper Research Journal, 30(4), 617–625. https://doi.org/10.3183/npprj- \n2015-30-04-p617-625. p\nBatista, J. T. S., Araújo, C. S., Peixoto Joele, M. R. S., Silva Júnior, J. O. 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ERROR: type should be string, got "https://doi.org/10.1007/s10096-021-04211-8\nEuropean Journal of Clinical Microbiology & Infectious Diseases (2021) 40:1803–1813 https://doi.org/10.1007/s10096-021-04211-8\nEuropean Journal of Clinical Microbiology & Infectious Diseases (2021) 40:1803–1813 https://doi.org/10.1007/s10096-021-04211-8\nEuropean Journal of Clinical Microbiology & Infectious Diseases (2021) 40:1803–1813 ORIGINAL ARTICLE Abstract This study is to determine the incidence and outcome of neonatal gram-negative bacilli (GNB) sepsis in Stockholm, Sweden, and\ndescribe bacterial characteristics. This is a retrospective cohort study. All infants with GNB-sepsis between 2006 and 2016 were\nincluded and matched with two control groups, with suspected sepsis and uninfected neonates, respectively. Outcome was death\nbefore discharge, risk of death within 5 days after sepsis onset, and morbidity. The resistance pattern from all GNB was collected,\nand all available isolates were subjected to genome typing. All neonates with GNB-sepsis (n = 107) were included, and the\ncumulative GNB-sepsis incidence was 0.35/1000 live born. The in-hospital mortality was 30/107 (28%). GNB late-onset sepsis\n(LOS) was associated with an increase in mortality before discharge compared to uninfected controls (OR = 3.9; CI 1.6–9.4) but\nnot versus suspected sepsis. The suspected LOS cases did not statistically differ significantly from uninfected controls. The case\nfatality rate (CFR) at 5 days was 5/33 (15%) in GNB early-onset sepsis (EOS) and 25/74 (34%) in GNB-LOS. The adjusted\nhazard for 5 days CFR was higher in GNB-LOS versus uninfected controls (HR = 3.7; CI 1.2–11.2), but no significant difference\nwas seen in GNB-LOS versus suspected sepsis or in suspected sepsis versus controls. ESBL production was seen in 7/107 (6.5%)\nof the GNB isolates. GNB-LOS was associated with a higher 5 days CFR and in-hospital mortality compared to uninfected\ncontrols but not versus suspect sepsis. The incidence of both GNB-EOS and GNB-LOS was lower than previously reported from\ncomparable high-income settings. The occurrence of antibiotic resistance was low. Keywords Gram-negative bacilli . Sepsis . Neonatal . Antibiotic resistance . Mortality Viveka Nordberg1,2\n& Aina Iversen3,4 & Annika Tidell5 & Karolina Ininbergs3,4 & Christian G. Giske3,4 & Lars Navér1,2 Received: 20 September 2020 /Accepted: 23 February 2021\n# The Author(s) 2021\n/ Published online: 24 March 2021 Received: 20 September 2020 /Accepted: 23 February 2021\n# The Author(s) 2021\n/ Published online: 24 March 2021 * Viveka Nordberg\nviveka.nordberg@ki.se Keywords Gram-negative bacilli . Sepsis . Neonatal . Antibiotic resistance . Mortality A decade of neonatal sepsis caused by gram-negative\nbacilli—a retrospective matched cohort study Viveka Nordberg1,2\n& Aina Iversen3,4 & Annika Tidell5 & Karolina Ininbergs3,4 & Christian G. G Materials and methods There was no variability of GA in the matching groups, but\nthere was variability in closest birth date in the controls de-\npending on GA. The variability in closest birth date between\ncases in the three matching groups was 10 years, but on aver-\nage below 24 months. Identifying the cases and the controls To identify the sepsis cases, we used the ICD-10 codes for\nGNB-sepsis in the electronic medical record systems Take\nCare and Clinisoft and merged them with the Swedish\nNeonatal Quality Register (SNQ). Patient characteristics from\nthe total NICU-stay were collected. The two groups of controls, manually collected from the\nsame registries, were neonates with suspected sepsis and those\nuninfected during their NICU-stay. We chose controls with the\nsame gestational age (GA) and closest birth date. Suspected\nsepsis was defined as the ICD-10 code P36.9, clinical symp-\ntoms, a negative blood culture, and subsequent antibiotic ther-\napy for at least 5 days. Uninfected infants, alive at 72 h of age,\nwere defined as not fulfilling the ICD-10 criteria for sepsis or\nsuspect sepsis during the NICU-stay. The proportion of the case\nvs suspected sepsis vs uninfected was planned to be 1:1:3. The\nnumber of uninfected neonates in the same gestational ages as\nthe cases during 2006–2016 was insufficient; hence, the pro-\nportion of the cases to controls was 1:1:2.6. We aimed to analyze the incidence of neonatal GNB-\nsepsis and associated mortality and morbidity in neonates\nin our setting. We also wanted to determine whether there\nwere differences in outcome between patients with culture\nproven sepsis, suspected sepsis (negative blood culture)\nand uninfected patients. We characterized the invasive\nbacterial isolates as to clonality and presence of AMR\ngenes. Patients and study design deaths/year globally [13]. A reduction in inappropriate use of\nantibiotics would be the most important step to decrease AMR. The challenge is to reduce the use of antibiotics without an\nincrease in fatal outcome [14, 15]. A matched cohort study was undertaken where all neonates\nwith GNB-sepsis at Stockholm’s four NICUs between\nJanuary 2006 and December 2016 were included. We identi-\nfied all patients with a positive GNB blood culture, at least two\nclinical signs (fatigue, respiratory instability, temperature insta-\nbility, poor feeding, vomiting, cyanosis) and antibiotic therapy\nfor > 5 days. Patients with GPB-sepsis were not analyzed. EOS\nand LOS were defined according to age at onset of sepsis\nsymptoms before or after 72 h of age. Early diagnosis and treatment of neonatal sepsis are dif-\nficult, and the fact that a consensus definition of neonatal\nsepsis is lacking makes it even more challenging [16–18]. The neonatal immune defense, clinical symptoms, and\npathophysiologic responses to bacterial infection differ in\nterm and preterm neonates due to age-dependent maturity. Sepsis onset is most rapid in preterm neonates [19–21]. The\ncharacteristics of the infecting bacteria, such as virulence\nand resistance factors, play a role in the dynamics of\nthe infection. A positive blood culture is the gold stan-\ndard definition of sepsis. However, the difficulties in\ngetting adequate blood volumes for culture and bio-\nmarkers with low sensitivity and specificity complicate\nthe sepsis diagnosis [22]. The intestinal dysbiosis, fol-\nlowing antibiotic treatment, is associated with a higher\nrisk of LOS, necrotizing enterocolitis (NEC) and other\nlong-term morbidities [23–28]. Study population and setting There are six delivery units and four NICUs in the\nStockholm region. A total of 29,553 infants were born alive\nat these delivery units during 2016. The NICUs are\nKarolinska Danderyd (level 2), Karolinska Solna (level\n3), Karolinska Huddinge (level 3), and Södersjukhuset\n(level 2). From March 2014 to May 2016, a seventh small\ndelivery unit and levels 1–2 neonatal unit, BB Sophia,\noperated. Introduction neonatal mortality and accounts for more than one million\ndeaths/year worldwide [1, 2]. In high-income settings, the inci-\ndence of neonatal sepsis is reported to be 1–4/1000 live births\n[1, 3]. Among very low birth weight (VLBW) neonates, ap-\nproximately 30–40% suffer from late-onset sepsis (LOS) with a\nmortality rate between 10 and 36% depending on the infecting\norganism [4–6]. Infants with gram-negative bacilli (GNB)-LOS\nare associated with a higher mortality compared to gram-\npositive bacteria (GPB)-LOS [7, 8]. Studies from Sweden in\nthe last decade report an incidence of early-onset sepsis (EOS)\nof 0.9/1000 live births with a case fatality rate (CFR) of 7% and\nthe GNB-EOS incidence of 0.25/1000 live born with a CFR of\n13% [9]. There are no previous studies on the incidence or the\nCFR of neonatal GNB-LOS in Sweden. Neonatal infections account for more than one-third (36%) of\nall neonatal deaths globally. Sepsis is the leading cause of * Viveka Nordberg\nviveka.nordberg@ki.se * Viveka Nordberg\nviveka.nordberg@ki.se 1\nDepartment of Neonatology, Karolinska University Hospital,\nStockholm, Sweden 2\nDepartment of Clinical Science, Intervention and Technology\n(CLINTEC), Division of Paediatrics, Karolinska Institutet,\nStockholm, Sweden The growing challenge of antimicrobial resistance (AMR) in\nneonatal intensive care units (NICUs), especially with resistant\nGNB, is associated with a high mortality and poor long-term\noutcome [7, 10–12]. The spread of antibiotic resistant bacteria\nhas been a persisting clinical problem during the last decades\nand has resulted in approximately 214,000 attributable neonatal 3\nDepartment of Clinical Microbiology, Karolinska University\nHospital, Stockholm, Sweden 4\nDepartment of Laboratory Medicine, Division of Clinical\nMicrobiology, Karolinska Institutet, Stockholm, Sweden 5\nDepartment of Neonatology, Sachs’ Children’s Youth Hospital,\nSödersjukhuset, Stockholm, Sweden Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 1804 Outcomes and definition of sepsis-related mortality The primary outcome was death before discharge from NICU. The secondary outcomes were sepsis mortality 5 days after\nonset of GNB-LOS and major morbidities, such as retinopa-\nthy of prematurity (ROP), intraventricular hemorrhage (IVH),\nand bronchopulmonary dysplasia (BPD). The all-cause neonatal mortality before 28 days of life in\nthe Stockholm region was 0.7–1.8/1000 live born (mean 1.4/\n1000) (2006–2016). The recommended empiric antibiotic\ntherapy for unknown EOS was since 2012 benzylpenicillin/\namikacin and for LOS cloxacillin/amikacin or cefotaxime/\namikacin [29]. Between 2006-2012 the empiric aminoglyco-\nside was gentamicin or netilmicin, which during 2012 was\nchanged to amikacin due to local outbreaks with gentamicin\nresistant E.coli. Infection control routines were similar in\nall included hospitals. Death 5 days following a positive blood culture is present-\ned in the study as 5 days case fatality rate (CFR). The\nsuspected sepsis CFR was death 5 days after onset of therapy\nfor suspected sepsis. Repeated episodes of sepsis were docu-\nmented in a few numbers of patients, but survival was ana-\nlyzed from the first invasive GNB episode. Proportions of\nmultidrug-resistant GNB strains and the burden of AMR in\nclinical samples were determined. Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 1805 Statistical methods This was an open cohort design with varying lengths of time\nfrom onset of sepsis to discharge. Comparisons of continuous\nvariables were made with Wilcoxon rank-sum or two sample\nt-test and summarized using means and SDs if unimodal, sym-\nmetrically distributed variables. If the distribution was\nskewed, they were shown with median values and ranges. Pearson’s Chi-squared test was used to compare categorical\nvariables. Statistical significance was defined as p values <\n0.05, and confidence intervals of 95% were used. Selection of bacterial isolates steroid treatment. In the LOS group, we adjusted for gesta-\ntional age, gender, prenatal steroid treatment, mechanical ven-\ntilation, and necrotizing enterocolitis (NEC). We chose these\nvariables since mechanical ventilation is associated with a\nhigher mortality and prenatal steroids with a lower mortality\ngenerally. We also adjusted for NEC since we considered\nNEC to be a confounder in the association between GNB-\nsepsis and death. Because of the strong correlation between\nbirth weight (BW) and GA, the risk factor BW was excluded\nfrom the analysis. In the logistic regression for morbidities\n(ROP, IVH, BPD), we used composite binary variables for\ndeath and the specific morbidity. GNB in the study refers to the following species: Escherichia\ncoli, Klebsiella pneumoniae, K. oxytoca, K. aerogenes,\nEnterobacter cloacae, Citrobacter koseri, Serratia\nmarcescens, Proteus mirabilis, Pseudomonas aeruginosa,\nAcinetobacter baumannii, and Haemophilus influenzae. The\nNeisseria species were considered to be contaminants. Blood\ncultures with contaminants were not included. All isolates\nwere susceptibility tested for the following: gentamicin,\namikacin, trimethoprim-sulfamethoxazole, cefotaxime, cef-\ntazidime, ciprofloxacin, imipenem, meropenem, ertapenem,\nand piperacillin-tazobactam. We analyzed EOS and LOS separately in the survival anal-\nysis. The Kaplan-Meier method was used to visualize survival\nover time. In the survival analysis for 5-day mortality after\nindex day (GNB-sepsis date of the respective case), Cox pro-\nportional hazard regression was performed to measure the\nhazard ratio (HR) for dying between the cases and their\nmatched controls. The HR gives the time-dependent instanta-\nneous rate ratio of dying, but is in this study interpreted as a\nratio of risks of death occurring within 5 days, similar to the\ninterpretation of ORs in logistic regression. Results During the study period, 310,091 infants were born alive at the\nincluded delivery units. Of these, 31,878 (10.2%) neonates\nwere admitted to the neonatal units of Karolinska Danderyd\n(n = 10,418), Karolinska Solna (n = 5828), Karolinska\nHuddinge (n = 6904), and Södersjukhuset (n = 8728). These\nfour units are levels 2–3 NICUs with a total of 75–80in-patient\ncots. Characterization of gram-negative bacilli All GNB isolates were cultured, isolated, and identified ac-\ncording to routine validated clinical methods and guidelines\nused during the study period. Antibiotic susceptibility testing\nwas performed by the disk diffusion method and interpreted\naccording to the guidelines of the Swedish Reference Group\nof Antibiotics before 2011 and between 2011 and 2016 ac-\ncording to guidelines from the European Committee on\nAntimicrobial Susceptibility Testing (www.eucast.org). MDR was defined as resistance to at least one antibiotic\nagent in three or more antibiotic groups [30]. Covariates adjusted for in the Cox-regression model in the\nEOS and LOS cohort were the same as in the logistic regres-\nsion model. Stata Statistical Software version 16.0, StataCorp,\nTX, USA, and JMP 15.1.0. SAS Institute Inc., Cary, USA,\nwere used. Due to the retrospective design of the study, only 33/107\nisolates were available for the genetic analyzes. Whole ge-\nnome sequencing (WGS) was performed at the Science for\nLife Laboratory (SciLife, Solna, Sweden). Multi-locus se-\nquencing (MLST) was performed in silico as described previ-\nously [31]. All Enterobacterales were assigned to sequence\ntypes except S. marcescens. The isolates that were closely\nrelated in the MLST analysis were further analyzed with sin-\ngle nucleotide polymorphism (SNP) analysis in CLC\nWorkbench [31]. Mortality Among neonates with invasive GNB-sepsis (n = 111),\nmedical records were retrievable in 107 patients, of which\n33 were GNB-EOS and 74 were GNB-LOS. These cases were\nmatched with 107 patients with suspected sepsis (culture-\nnegative) and 295 uninfected controls. In total, data from\n509 patients were analyzed. The clinical characteristics of in-\ncluded patients are presented in Table 1. Thirty (30/107) neonates with GNB-sepsis died before dis-\ncharge (5/33 EOS and 25/74 LOS), with a case fatality rate\nof 28%. The median age at death was 28 days (IQR 14–52)\namong the infants with GNB-LOS that died during hospital\nstay. The mortality in the EOS group was too small to make\nunivariate comparisons between the groups relevant. Comparing GNB-LOS with the suspected sepsis and uninfect-\ned control groups, the proportion of deaths before discharge\nwas 33.7% (25/74), 18.9% (14/74), and 7.6% (15/196), re-\nspectively. The CFR of GNB-LOS in different gestational\nages were in GA ≤28 (18/52, 35 %), GA 29–32 (6/17,\n35%), GA 33–36 (1/3, 33%), and GA ≥37 (0/2, 0%). Proportions of deaths of GNB-EOS and GNB-LOS in differ-\nent gestational ages are presented in Online Resource 1. More than one LOS episode was seen in 35/107 (33%)\ncases where the causative pathogens were GNB and GPB,\nand 57% (20/35) of them had a GPB-sepsis episode before a\nGNB-sepsis. The 33 GNB-EOS cases were distributed as 4, 4,\n1, 3, 2, 4, 4, 5, 1, 2, and 3 per year during the years 2006–\n2016. There was no statistical difference in the trend of EOS\ncases per year during the study period. The 74 GNB-LOS\ncases were distributed as 4, 9, 12, 5, 11, 8, 5, 3, 4, 5, and 8\nwhich indicate a slight but not statistically significant decrease\nover the period. In the logistic regression of the relation between GNB-LOS\nand death, there was a 2.2 times higher odds (crude OR) of\ndying before discharge at NICU in the GNB-sepsis group\n(EOS and LOS combined) compared to the suspected sepsis\ngroup and 4.8 times higher odds compared to uninfected\ncases. There was no statistically significant difference in mor-\ntality before discharge between patients with GNB-EOS,\nsuspected EOS, and controls. Gestational age was the only\nfactor associated with death in GNB-EOS(Table 2). Mortality The pairwise analysis between groups showed that the me-\ndian age at diagnosis was 1 day for GNB-EOS, 0 for suspected\nEOS (p = 0.023), 19 days for GNB-LOS, and 9 for suspected\nLOS (p < 0.001). The administration of prenatal steroids did not differ be-\ntween culture proven GNB-EOS and suspected sepsis. The\nGNB-EOS group did not differ from the suspected EOS group\nregarding administration of antibiotics to mothers prenatally\n(p = 0.11), but the GNB-EOS group had a significantly higher\nuse compared to the uninfected group (52% vs 33 %). Similar\nresults were found in GNB-LOS (49%) where use of antenatal\nantibiotics differed from their uninfected control group (40%)\n(p < 0.01).’ Neonates with GNB-LOS were 6.5 (crude OR) and 3.9 (CI:\n1.6–9.4) (adjusted OR) more likely to die during hospital stay\ncompared to the uninfected matched control group. A higher\ngestational age was protective. The comparison between\nGNB-LOS and suspected LOS showed no significant differ-\nence in the odds of dying before discharge (OR 2.0; CI: 0.8–\n4.6) (Table 2). There were 43/74GNB-LOS cases vs 41/74 suspected LOS\ncases that received prophylactic antibiotics before the sepsis/\nsuspected sepsis episodes. Mode of delivery did not differ\nbetween the groups in the GNB-EOS analysis, but caesarean\nsection was significantly more common in GNB-LOS (42%)\ncompared to suspected LOS (15%) and uninfected controls\n(22%) (Table 1). The 5 days CFR was 15% (5/33) in GNB-EOS. All neo-\nnates with GNB-EOS that died died before 5 days after GNB-\nEOS onset. The 5 days CFR of GNB-LOS was 17.6% (13/74). The crude 5 days CFR differed significantly between GNB-\nLOS and the uninfected controls (p < 0.001) and between\nGNB-LOS and the suspected sepsis group (p = 0.039) but\nnot between the suspected sepsis group and uninfected con-\ntrols (p = 0.37). In a Cox-regression model, the adjusted haz-\nard ratio (HR) of dying 5 days after GNB-LOS onset vs unin-\nfected controls was 3.7 (CI: 1.2–11.2), but no increased hazard\nwas seen in GNB-LOS versus suspected LOS (Table 3). The\ncumulative survival rate, shown in the Kaplan-Meier curves\nfor 5 days survival, is illustrated in Fig. 2. Intensive care interventions The median days of mechanical ventilation differed between\nGNB-EOS cases (median 1 day, IQR 0–7 days) and uninfect-\ned cases (median 0, IQR 0–0 days). The days of total parental\nnutrition (TPN) in the GNB-EOS (median 8 days, IQR 2–13)\ndays were higher and differed significantly from the uninfect-\ned group (median 1 day, IQR 0–8 days). Incidence of GNB-sepsis and baseline characteristics A flowchart of included patients is depicted in Fig. 1 during\nthe period, a total of 804 admitted infants had a culture-\nconfirmed neonatal sepsis, which corresponds to a total inci-\ndence of 2.6/1,000 live born. GNB-sepsis counted for 111/804\n(14%) of all culture-confirmed sepsis cases. The proportion of GNB-sepsis for all admitted neonates\nwas 111/31,878 (0.36%), with a cumulative incidence of\n0.35 cases per 1000 live born during the study period. Among the infants admitted to the neonatal unit,\n1026/31,878 (3.2%) had suspected but not culture-verified\nsepsis with a cumulative incidence of 3.3/1,000 live born. We used logistic regression to measure odds ratios (OR) of\ndying, separately for EOS and LOS, and adjusted for different\nvariables in the regression model of EOS and LOS. Variables\nadjusted for in the EOS group were as follows: gestational\nage, gender, perinatal antibiotics, birth mode, and prenatal Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 1806 Flow chart of all included patients in the study Fig. 1 A Flow chart of all included patients in the study Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 1807 Mortality Morbidity GNB-LOS and suspected LOS had significantly more days\nof ventilatory support, umbilical artery catheter (UAC), pe-\nripheral central venous catheter (pCVC), and TPN than the\nuninfected group. Days of TPN and total days with pCVC\nwere significantly higher in the GNB-LOS group compared\nto the suspected sepsis and the uninfected group (Table 1). The GNB-EOS group differed in univariate analysis from the\nuninfected controls with a higher proportion of IVH grades 3–\n4 (15% vs 2%, p = 0.004) and ROP 3–4 (12% vs 1%, p =\n0.01). No difference was seen regarding BPD. Morbidity Verified\nGNB-LOS differed from uninfected controls regarding ROP 1808 Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 Table 1\nCharacteristics of 107 GNB cases (EOS and LOS) and pair-wise comparisons with suspected sepsis controls and uninfected controls\nGNB-EOS (n=33) Susp EOS (n=33)\nNo inf control (n=99) P*\nEOS\nP**\nEOS\nP***\nEOS\nGNB-LOS (n=74) Susp LOS (n=74)\nNo inf control (n=196) P*\nLOS\nP**\nLOS\nP***\nLOS\nGest age (w)\n34 (26–38)\n34 (26–38)\n34 (26–38)\n0.94\n0.97\n0.91\n27 (25–29)\n27 (25–29)\n27 (25–29)\n0.98\n0.60\n0.58\nGender, male\n16 (48)\n21 (64)\n57 (58)\n0.16\n0.36\n0.42\n45 (61)\n53 (72)\n99 (51)\n0.16\n0.13\n0.002\nBW (g)\n2225 (994–2950)\n2013 (686–3500)\n2087 (995–3325)\n0.88\n0.81\n0.89\n885 (750–1395)\n812 (627–1259)\n960 (747–1315)\n0.17\n0.69\n0.04\nApgar at 5 min<7\n13 (39)\n5 (15)\n26 (26)\n0.027\n0.16\n0.18\n23 (31)\n29 (39)\n63 (32)\n0.33\n0.83\n0.33\nCaesarean section\n16 (48)\n16 (48)\n50 (22)\n0.90\n0.96\n0.84\n31 (42)\n11 (15)\n44 (22)\n<0.001 <0.001\n0.17\nPrenatal steroids\n11 (33)\n14 (42)\n34 (34)\n0.72\n0.72\n0.40\n52 (70)\n64 (87)\n146 (75)\n0.17\n0.61\n0.034\nAntenatal antibiotics\n17 (52)\n11 (33)\n16 (16)\n0.11\n<0.001\n0.037\n36 (49)\n31 (42)\n79 (40)\n0.048 <0.01\n0.81\nOnset sepsis (d)\n1 (0–1)\n0 (0)\n0.023\n19 (11–31)\n9 (4–17)\n<0.001\nDays of MV\n1 (0–7)\n0 (0–6)\n0 (0)\n0.77\n<0.001\n0.57\n8 (2–24)\n9 (2–16)\n0 (0–7)\n0.43\n<0.001\n<0.001\nDays of CPAP\n2 (0–8)\n1 (0–4)\n3 (0–20)\n0.31\n0.048\n0.24\n16 (3–36)\n18 (2–38)\n6 (1–25)\n0.77\n0.003\n0.03\nDays of TPN\n8 (2–13)\n2 (0–10)\n1 (0–8)\n0.06\n0.001\n0.001\n22 (11–37)\n13 (8–24)\n9 (5–14)\n0.001 <0.001\n<0.001\nDays of UAC\n1 (0–6)\n0 (0–2)\n0 (0–4)\n0.038\n0.046\nNA\n6 (3–8)\n5 (0–7)\n3 (0–6)\n0.43\n<0.001\n0.036\nDays of UVC\n1 (0–5)\n0 (0–1)\n0 (0–0)\n0.062\n0.015\nNA\n1 (0–4)\n2 (0–5)\n0 (0–5)\n0.40\n0.72\n0.20\nDays of pCVC\n0 (0–9)\n0 (0–9)\n0 (0–0)\n0.39\n<0.001\n0.55\n15(8–28)\n7 (1–20)\n2 (0–8)\n0.009 <0.001\n<0.001\nBPD discharge\n4 (12)\n6 (18)\n13 (13)\n0.64\n0.67\n0.78\n32 (43)\n35 (47)\n64 (33)\n0.48\n0.12\n0.083\nROP 1–2 discharge\n4 (12)\n6 (18)\n2 (2)\n0.48\n0.004\n0.059\n9 (12)\n20 (27)\n26 (13)\n0.11\n0.99\n0.017\nROP 3–4 discharge\n4 (12)\n0 (0)\n1 (1)\n0.095\n0.01\n0.85\n10 (14)\n4 (5)\n9 (5)\n0.18\n0.019\n0.83\nIVH 1–2 discharge\n7 (21)\n4 (12)\n5 (5)\n0.32\n0.005\n0.059\n16 (22)\n14 (19)\n19 (10)\n0.55\n0.008\n0.039\nIVH 3–4 discharge\n5 (15)\n3 (9)\n2 (2)\n0.48\n0.004\n0.059\n6(8)\n6 (8)\n11 (6)\n0.60\n0.20\n0.45\nAll NEC\n27 (36)\n15 (20)\n5 (3)\n0.09\n0.059\n0.39\nSurgical NEC\n11 (15)\n5 (7)\n0 (0)\n0.11\n0.003\n0.78\nMortality\n5 (15)\n3 (9)\n7 (7)\n0.46\n0.24\n0.86\n25 (34)\n12 (16)\n15 (7.6)\n0.04\n<0.001\n0.008\n*Comparison between case and suspect sepsis, **comparison between case and uninfected control, ***comparison between suspected case and uninfected control. Discussion For GNB-LOS, the OR for the composite variable death/\nBPD was 3.8 (CI: 1.68–8.67) compared to uninfected con-\ntrols, but no difference was seen compared to suspect LOS. Gram-negative sepsis is an uncommon but serious disorder in\nthe neonate, especially in the premature born [4–6, 8, 32]. In\nthis 11-year retrospective study, we sought to describe GNB-\nsepsis by reporting the incidence, subsequent mortality, and\nmorbidity and to compare it to suspected sepsis and uninfected\ncontrols in neonates in our region. Morbidity Of all GNB strains, 7/107 were resistant\nto at least two groups of antimicrobials, and all were suscep-\ntible to carbapenems. 3–4 (14% vs 5%, p = 0.019), but not regarding IVH 3–4 and\nBPD (Table 1). Morbidity analyses with logistic regression for\nGNB-EOS showed an OR for the composite outcome mea-\nsure death/IVH3–4 of 7.5 (CI: 1.29–43.4) compared to sus-\npect EOS and 5.2 (CI: 1.17–23.4) compared to uninfected\ncontrols. For GNB-LOS OR was 3.0 (CI: 1.30–6.76) for\ndeath/ROP3–4 compared to suspect LOS and 6.3 (CI: 2.79–\n14.0) compared to uninfected controls. Morbidity Continuous variables are presented with\nmeans, SD, medians, and interquartile range. Categorical variables are presented with proportions and %. BW birth weight, MV mechanical ventilation, CPAP continuous positive airway pressure, TPN total\nparental nutrition, pCVC peripheral central venous catheter, UVC umbilical venous catheter, UAC umbilical arterial catheter, BPD bronchopulmonary dysplasia, ROP retinopathy of the newborn, IVH\nintraventricular hemorrhage *Comparison between case and suspect sepsis, **comparison between case and uninfected control, ***comparison between suspected case and uninfected control. Continuous variables are presented with\nmeans, SD, medians, and interquartile range. Categorical variables are presented with proportions and %. BW birth weight, MV mechanical ventilation, CPAP continuous positive airway pressure, TPN total\nparental nutrition, pCVC peripheral central venous catheter, UVC umbilical venous catheter, UAC umbilical arterial catheter, BPD bronchopulmonary dysplasia, ROP retinopathy of the newborn, IVH\nintraventricular hemorrhage Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 1809 Table 2\nLogistic regression with adjusted odds ratio of neonatal death after GNB-sepsis before discharge from NICU\nEOS\nAdjusted OR\n95% CI\np Value\nLOS\nAdjusted OR\n95% CI\np Value\nGNB-EOS: uninfected*\n2.5\n0.53–11.4\n0.25\nGNB-LOS: uninfected*\n3.9\n1.61–9.36\n0.003\nSuspected EOS: uninfected*\n0.92\n0.18–4.74\n0.92\nSuspected LOS: uninfected*\n2.0\n0.78–5.05\n0.15\nGNB-EOS: suspected EOS*\n2.7\n0.49–14.7\n0.26\nGNB-LOS: suspected LOS*\n2.0\n0.82–4.65\n0.13\nGestational week\n0.8\n0.67–0.95\n0.01\nGestational week\n0.8\n0.67–0.92\n0.002\nGender (male)\n0.9\n0.26–2.84\n0.81\nGender (male)\n1.8\n0.87–3.62\n0.12\nPrenatal steroids\n0.7\n0.13–3.79\n0.67\nMechanical ventilation\n3.8\n1.00–14.1\n0.049\nPrenatal antibiotics\n2.1\n0.50–8.56\n0.32\nPrenatal steroids\n0.4\n0.16–0.89\n0.26\nBirth mode (CS)\n1.4\n0.37–5.50\n0.60\nNecrotizing enterocolitis\n3.0\n1.34–6.48\n0.007\nAdjusted odds ratio of the comparisons between the sepsis group and the reference groups. GNB-EOS and GNB-LOS are reported separately. *Reference group ogistic regression with adjusted odds ratio of neonatal death after GNB-sepsis before discharge from NICU Adjusted odds ratio of the comparisons between the sepsis group and the reference groups. GNB-EOS and GNB-LOS are reported separately. *Reference group Table 4. The genomic characterization of the invasive isolates\nthat infected one-third of the neonates in the study can be seen\nin Online Resource 4. Of all GNB strains, 7/107 were resistant\nto at least two groups of antimicrobials, and all were suscep-\ntible to carbapenems. Table 4. The genomic characterization of the invasive isolates\nthat infected one-third of the neonates in the study can be seen\nin Online Resource 4. Bacterial characteristics and antibiotic resistance All 107 GNB from confirmed positive blood cultures are pre-\nsented in Online Resource 2. The majority belonged to the\norder Enterobacterales, comprising E. coli, K. pneumoniae,\nEnterobacter spp., and S. marcescens. Three other gram-\nnegative species were represented: A. baumannii,\nP. aeruginosa, and H. influenzae. Proportions of deaths from\nGNB-EOS and GNB-LOS and the causing pathogen can be\nseen in Online Resource 3. Multidrug resistance was observed\nin 3/47E. coli and 2/20K. pneumoniae and 2/14E. cloacae. The antibiotic resistance pattern of all isolates is presented in The incidence of neonatal GNB-sepsis in the region was\n0.35/1000 live born neonates and remained unchanged during\nthe study period. The incidence of GNB-EOS was 0.11/1000\nlive births which is about half of what recently has been re-\nported from the western part of Sweden, where the incidence\nof GNB-EOS was 0.25/1000 live births [9]. The difference is\nsubstantial but might be influenced by methodological differ-\nences. The incidence of GNB-LOS was 0.24/1000 live births\nand has not been previously described in a Swedish context. Table 3\nCox-regression survival analysis of hazard rate (HR) at 5 days after onset of LOS symptoms\nCase—uninfected*\nCase—suspected*\nSuspect—uninfected*\nGroup\nHR\n95% CI\np Value\nHR\n95% CI\np Value\nHR\n95% CI\np Value\n5 days ALL crude\n5.5\n2.4–12.8\n<0.001\n4.5\n1.9–10.7\n0.001\n1.2\n0.3–4.9\n0.76\n5 days LOS crude\n5.8\n2.2–15.2\n<0.001\n3.2\n1.0–10.0\n0.039\n1.8\n0.5–6.3\n0.37\n5 days LOS adjusted#\n3.7\n1.2–11.2\n0.019\n2.7\n0.8–8.8\n0.095\n1.4\n0.4–5.4\n0.65\n*Reference group\n# The analyses are adjusted for gestational age, gender, prenatal steroids, mechanical ventilation, and necrotizing enterocolitis (NEC)\nThe uninfected group is matched to the same days of life when the GNB-sepsis case was diagnosed Table 3\nCox-regression survival analysis of hazard rate (HR) at 5 days after onset of LOS symptoms g\np\n# The analyses are adjusted for gestational age, gender, prenatal steroids, mechanical ventilation, and necrotizing enterocolitis (NEC)\nThe uninfected group is matched to the same days of life when the GNB-sepsis case was diagnosed Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 1810 Fig. 2 The Kaplan-Meier method visualizes survival over time in GNB-\nLOS. The figure depicts survival 5 days after sepsis onset parenteral nutrition, and central catheters, than the uninfected\ncontrols. Bacterial characteristics and antibiotic resistance The antenatal factors delivery by caesarean section and\nexposure to prenatal antibiotics occurred more frequently in\ninfants with GNB-LOS than in infants with suspected sepsis\nor in uninfected controls. A dysbiotic neonatal intestinal mi-\ncrobiota due to C-sectionand/or use of antibiotics has previ-\nously been associated as a risk factor for neonatal LOS. The\nsuggested biological rationale is that an altered first-\ncolonizing microbiota cannot confer protection against bacte-\nrial translocation in the neonatal intestine [33, 34]. We found GNB-sepsis to be a great risk factor for\nmortality and show the in-hospital mortality rate to be\n28% of all GNB-sepsis cases. The in-hospital mortality\nrate was more than 2.3 times higher among the infants\nwith GNB-LOS compared to those with GNB-EOS,\nwhich possibly reflects the fact that the LOS group\nwere more premature, had lower BW, had more co-\nmorbidities and a longer duration of hospital care. Prenatal steroids have been shown to be protective\nagainst a number of morbidities in preterm infants\n[35], and in this study it was protective against death\nfrom GNB-LOS but not from GNB-EOS. Fig. 2 The Kaplan-Meier method visualizes survival over time in GNB-\nLOS. The figure depicts survival 5 days after sepsis onset The incidence of 1.4 E.coli-LOS per 1000 NICU admissions\nwas about half that reported in studies from other high-income\ncountries [3, 5, 8]. We found that the need for intensive care interventions\ndiffered between the groups. The GNB-LOS group had sig-\nnificantly more days of supportive intensive care compared to\nuninfected controls, but not to suspected-LOS. These invasive\nmeasures could be risk factors for LOS but also the conse-\nquences of infection. As well neonates with suspected sepsis\nneeded more intensive care in terms of mechanical ventilation, When adjusted for confounders, the GNB-LOS group’s in-\nhospital mortality was 3.9 times higher compared to uninfect-\ned controls. We found no statistical differences in in-hospital\nmortality between the other control groups. Gram-negative bacteria\nNumber of isolates\nRatio of resistant isolates\nEnterobacterales\nE.coli\n47\n2/47 GEN\n3/47 TSU, CTX, CFZ\n7/47 TSU\nK. pneumoniae\n20\n2/20 TSU, CTX, CTZ, GEN, CIP\nK. aerogenes\n2\n1/2 TSU\nK. oxytoca\n4\n0\nE. cloacae\n14\n1/14 GEN\n2/14 CTX, CFZ\nS. marcescens\n10\n0\nC. koseri\n1\n0\nNon-Enterobacterales genera\nAcinetobacter\nA. baumannii\n3\n0\nPseudomonas\nP. aeruginosa\n4\n0\nHaemophilus\nH. Table 4 Summary of antibiogram\nof the 107 Gram-negative isolates\nfrom all neonates included in the\nstudy All isolates were susceptibility tested for the following: GEN gentamicin, AMI amikacin, TSU trimethoprim-\nsulfamethoxazole, CTX cefotaxime, CFZ ceftazidime, CIP ciprofloxacin, IMI imipenem, MER meropenem, ERT\nertapenem, and PT piperacillin-tazobactam Bacterial characteristics and antibiotic resistance influenzae\n2\n0\nAll isolates were susceptibility tested for the following: GEN gentamicin, AMI amikacin, TSU trimethoprim-\nsulfamethoxazole, CTX cefotaxime, CFZ ceftazidime, CIP ciprofloxacin, IMI imipenem, MER meropenem, ERT\nertapenem, and PT piperacillin-tazobactam 1811 Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 Many studies on neonatal sepsis present crude mortality after\na positive blood culture. However, autopsy completion is infre-\nquently performed. We have tried to relate the sepsis episode\nwith sepsis-related mortality and calculated the 5 days CFR. The 5 days CFR for GNB-EOS was 15% and for GNB-LOS\n17%. GNB-LOS was most common (70%) in the lower GA (≤\n28 weeks), and the CFR was as high as 35% in this group. repeatedly small outbreaks of gentamicin-resistantE.coli in the\nregion. After that, we could not see any high rates resistance to\namikacin or third generation cephalosporins that would lead to\nany change in the empiric therapy. One strength of the study is its population-based approach as\nit covers almost all 310,091 infants born in the Stockholm region\nduring the study period. Another strength of the study is that all\nmedical records from the patients with GNB-sepsis, suspected\nsepsis, and controls were validated against medical records. All\ndata was validated against medical records because between\n2006 and 2010, there were no predefined sepsis criteria and data\ncompleteness in SNQ regarding causative agents was low in the\nstudy region. Sepsis criteria have in later years been standardized,\nand reporting to SNQ has been changed from retrospective sum-\nmaries to web-based uploads on a daily basis. In later years, SNQ\nhas been shown to exhibit similar or higher completeness for\nneonatal sepsis as the Swedish Medical Birth register which is\nconsidered to be very high [41] . From the survival analysis, we concluded that the adjusted\nhazard for dying within 5 days from the GNB-LOS onset was\nfour times greater than if the neonate was uninfected. There\nwas no statistical significance in the adjusted Cox-regression\nanalysis in comparing the other groups with each other, which\npossibly might reflect a type II error and the small number of\nobservations. The Kaplan-Meier curve gives us the indication\nthat suspected-LOS is associated with a greater hazard of sur-\nviving than in uninfected, but we could not show that statisti-\ncally. Bacterial characteristics and antibiotic resistance Causal data on reasons for death in the suspected sepsis\nand uninfected group were not analyzed but could be ex-\nplained by the most common non-infectious causes of death\nin the NICU such as respiratory failure, asphyxia, IVH, met-\nabolic disease, and lethal genetic syndromes. The limitations of the study are related to the retrospective\ndesign and, despite covering all cases during an 11-year peri-\nod in an area with more than 2 million inhabitants, the small\nsample size. The procedure of matching the controls to each\nsepsis case has been done as accurately as possible. The phys-\niological vulnerability of the neonate in different gestational\nages is the most important variable for matching. The size of\nthe cohort makes it impossible to match for more morbidities\nand is therefore a limitation of the study. Without doubt, culture proven GNB-LOS is related to an\nincreased risk of mortality and morbidity, as previously reported\n[3, 6, 8, 32]. However, the power of this study is not sufficient to\nfind out whether suspect sepsis is an entity of its own or just\nsepsis not possible to detect by culture. Studies conducted in\nhigh-income countries report suspected sepsis to be 6–16 times\nas more common than culture proven sepsis [14, 18]. We could not draw conclusions about the association between\nGNB-sepsis and severe complications of preterm birth such as\nBPD and ROP 3–4, as the most severely ill patients died before\nthey could be validated for these conditions. IVH occurs early\nduring the same time frame as GNB-EOS and was also overrep-\nresented in GNB-EOS compared to neonates with suspected\nsepsis and the uninfected. As IVH often occurs before the onset\nof GNB-LOS, we did not analyze it in this context. Both ROP 3–\n4 and BPD was associated with GNB-LOS. Data availability The dataset is available on your request. 8. Stoll BJ, Hansen N, Fanaroff AA, Wright LL, Carlo WA,\nEhrenkranz RA, Lemons JA, Donovan EF, Stark AR, Tyson JE,\nOh W, Bauer CR, Korones SB, Shankaran S, Laptook AR,\nStevenson DK, Papile LA, Poole WK (2002)Late-onset sepsis in\nvery low birth weight neonates: the experience of the NICHD\nNeonatal Research Network. Pediatrics 110(2 Pt 1):285–291 Conflict of interest\nThe authors declare no competing interests. Open Access This article is licensed under a Creative Commons\nAttribution 4.0 International License, which permits use, sharing, adap-\ntation, distribution and reproduction in any medium or format, as long as\nyou give appropriate credit to the original author(s) and the source, pro-\nvide a link to the Creative Commons licence, and indicate if changes were\nmade. The images or other third party material in this article are included\nin the article's Creative Commons licence, unless indicated otherwise in a\ncredit line to the material. If material is not included in the article's\nCreative Commons licence and your intended use is not permitted by\nstatutory regulation or exceeds the permitted use, you will need to obtain\npermission directly from the copyright holder. To view a copy of this\nlicence, visit http://creativecommons.org/licenses/by/4.0/. 11. World Health Organisation (2014) Antimicrobial resistance: global\nreport on surveillance. www.who.int 12. Ting JY, Synnes A, Roberts A, Deshpandey A, Dow K, Yoon EW,\nLee KS, Dobson S, Lee SK, Shah PS, Canadian Neonatal Network\nI (2016) Association between antibiotic use and neonatal mortality\nand morbidities in very low-birth-weight infants without culture-\nproven sepsis or necrotizing enterocolitis. JAMA Pediatr 170(12):\n1181–1187. https://doi.org/10.1001/jamapediatrics.2016.2132 13. Laxminarayan R, Matsoso P, Pant S, Brower C, Rottingen JA,\nKlugman K, Davies S (2016) Access to effective antimicrobials: a\nworldwide challenge. Lancet 387(10014):168–175. https://doi.org/\n10.1016/S0140-6736(15)00474-2 Conclusion We conclude that GNB-sepsis is rare but it remains a serious\nthreat to neonatal patients in the region. GNB-sepsis is a risk\nfactor for neonatal mortality compared to suspect sepsis and\nuninfected controls. We found a lower incidence of GNB-\nEOS than previously described in Sweden and other high-\nincome settings, and for the first time, we present the inci-\ndence of GNB-LOS in Sweden. The GNB-EOS or GNB-\nLOS incidence did not change during the study period. The\nincidence of AMR was low, the AMR pattern did not reveal\nany highly resistant strains, and the incidence did not change\nover time. This is reassuring as the current empiric therapy\nagainst bacterial sepsis of unknown origin appears to be rele-\nvant despite its use over a long period of time. E.coli was the most common pathogen causing GNB-LOS\nwith a 5 days CFR of 9%. The highest 5 days CFR (33%) was\ncaused by the Enterobacter spp. We could not statistically\nrelate specific pathogens to mortality which is an important\nissue for the clinician. The rate of antibiotic resistant bacteria in our study was low\ncompared to studies from other settings [36, 37]. In a recent\nretrospective study between 2009 and 2017 from the USA, a\nmean of 5% ESBL-producingE.coli was seen in a large cohort\n(n = 733) of neonatal E-coli sepsis [38]. The proportion of all\nESBL-producingEnterobacterales in our study, with a smaller\nsample size, was 7/107 (6.5%) and is still considered low. The\nlow incidence of GNB-LOS and AMR could be the result of\nlong-standing efforts in infection control and antimicrobial\nstewardship [39, 40]. In 2012, we changed our empiric ami-\nnoglycoside from gentamicin or netilmicin to amikacin due to Supplementary Information The online version contains supplementary\nmaterial available at https://doi.org/10.1007/s10096-021-04211-8. Acknowledgements We like to thank Jessica Stenquist, Gabriella Lang,\nand Mikaela Winderud for their contribution to the data collection. Code availability\n“Not applicable.” Eur J Clin Microbiol Infect Dis (2021) 40:1803–1813 1812 5. Tsai MH, Hsu JF, Chu SM, Lien R, Huang HR, Chiang MC, Fu\nRH, Lee CW, Huang YC (2014) Incidence, clinical characteristics\nand risk factors for adverse outcome in neonates with late-onset\nsepsis. Pediatr Infect Dis J 33(1):e7–e13. https://doi.org/10.1097/\nINF.0b013e3182a72ee0 Authors’ contributions VN, LN, AI, and CG planned and designed the\nstudy. VN and AT acquired the data. VN, AI, KI, and CG performed the\nmicrobiological analyses. Declarations Ethics approval\nThe study is approved by the Regional Ethics Review\nboard in Stockholm (Dnr:2016/202-31/2). Ethics approval\nThe study is approved by the Regional Ethics Review\nboard in Stockholm (Dnr:2016/202-31/2). 9. Johansson Gudjonsdottir M, Elfvin A, Hentz E, Adlerberth I,\nTessin I, Trollfors B (2019) Changes in incidence and etiology of\nearly-onset neonatal infections 1997-2017 - a retrospective cohort\nstudy in western Sweden. BMC Pediatr 19(1):490. https://doi.org/\n10.1186/s12887-019-1866-z Consent to participate\n“Not applicable.” Consent for publication\nThis study has not been submitted for publica-\ntion or consideration in any other journal. Consent for publication\nThis study has not been submitted for publica-\ntion or consideration in any other journal. 10. Stoll BJ, Hansen NI, Adams-Chapman I, Fanaroff AA, Hintz SR,\nVohr B, Higgins RD, National Institute of Child H, Human\nDevelopment Neonatal Research N (2004) Neurodevelopmental\nand growth impairment among extremely low-birth-weight infants\nwith neonatal infection. Jama 292(19):2357–2365. https://doi.org/\n10.1001/jama.292.19.2357 Conflict of interest\nThe authors declare no competing interests. Conclusion VN and LN drafted the manuscript and the data\nanalysis. VN, LN, AI, CG, AT, and KI participated in the interpretation of\nthe data and critically revised the manuscript. All authors have read and\napproved the final manuscript. 6. Tsai MH, Chu SM, Lee CW, Hsu JF, Huang HR, Chiang MC, Fu\nRH, Lien R, Huang YC (2014) Recurrent late-onset sepsis in the\nneonatal intensive care unit: incidence, clinical characteristics and\nrisk factors. Clin Microbiol Infect 20(11):O928–O935. https://doi. org/10.1111/1469-0691.12661 Funding Open access funding provided by Karolinska Institute. The\nstudy was supported by grants from the Samariten Foundation for\nPediatric Research, Mjölkdroppen Foundation, Kronprinsessan Lovisas\nFoundation for pediatric healthcare, and Karolinska University Hospital\nresearch fund. 7. Benjamin DK, DeLong E, Cotten CM, Garges HP, Steinbach WJ,\nClark RH (2004) Mortality following blood culture in premature\ninfants: increased with Gram-negative bacteremia and candidemia,\nbut not gram-positive bacteremia. J Perinatol 24(3):175–180. https://doi.org/10.1038/sj.jp.7211068 Data availability The dataset is available on your request. References 14. Cantey JB, Wozniak PS, Pruszynski JE, Sanchez PJ (2016)\nReducing unnecessary antibiotic use in the neonatal intensive care\nunit (SCOUT): a prospective interrupted time-series study. Lancet\nInfect Dis 16(10):1178–1184. https://doi.org/10.1016/S1473-\n3099(16)30205-5 1. Shane AL, Sanchez PJ, Stoll BJ (2017) Neonatal sepsis. 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