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      Recombinant Human Secretory IgA Induces Salmonella Typhimurium Agglutination and Limits Bacterial Invasion into Gut-Associated Lymphoid Tissues

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          Abstract

          As the predominant antibody type in mucosal secretions, human colostrum, and breast milk, secretory IgA (SIgA) plays a central role in safeguarding the intestinal epithelium of newborns from invasive enteric pathogens like the Gram-negative bacterium Salmonella enterica serovar Typhimurium (STm). SIgA is a complex molecule, consisting of an assemblage of two or more IgA monomers, joining (J)-chain, and secretory component (SC), whose exact functions in neutralizing pathogens are only beginning to be elucidated. In this study, we produced and characterized a recombinant human SIgA variant of Sal4, a well-characterized monoclonal antibody (mAb) specific for the O5-antigen of STm lipopolysaccharide (LPS). We demonstrate by flow cytometry, light microscopy, and fluorescence microscopy that Sal4 SIgA promotes the formation of large, densely packed bacterial aggregates in vitro. In a mouse model, passive oral administration of Sal4 SIgA was sufficient to entrap STm within the intestinal lumen and reduce bacterial invasion into gut-associated lymphoid tissues by several orders of magnitude. Bacterial aggregates induced by Sal4 SIgA treatment in the intestinal lumen were recalcitrant to immunohistochemical staining, suggesting the bacteria were encased in a protective capsule. Indeed, a crystal violet staining assay demonstrated that STm secretes an extracellular matrix enriched in cellulose following even short exposures to Sal4 SIgA. Collectively, these results demonstrate that recombinant human SIgA recapitulates key biological activities associated with mucosal immunity and raises the prospect of oral passive immunization to combat enteric diseases.

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

            Summary Background In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding Bill & Melinda Gates Foundation.
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              ImageJ2: ImageJ for the next generation of scientific image data

              Background ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software’s ability to handle the requirements of modern science. Results We rewrote the entire ImageJ codebase, engineering a redesigned plugin mechanism intended to facilitate extensibility at every level, with the goal of creating a more powerful tool that continues to serve the existing community while addressing a wider range of scientific requirements. This next-generation ImageJ, called “ImageJ2” in places where the distinction matters, provides a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. Conclusions Scientific imaging benefits from open-source programs that advance new method development and deployment to a diverse audience. ImageJ has continuously evolved with this idea in mind; however, new and emerging scientific requirements have posed corresponding challenges for ImageJ’s development. The described improvements provide a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs. Future efforts will focus on implementing new algorithms in this framework and expanding collaborations with other popular scientific software suites. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1934-z) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                ACS Infect Dis
                ACS Infect Dis
                id
                aidcbc
                ACS Infectious Diseases
                American Chemical Society
                2373-8227
                17 March 2021
                14 May 2021
                : 7
                : 5 , Gut Pathogens
                : 1221-1235
                Affiliations
                []Department of Biomedical Sciences, University at Albany School of Public Health , Albany, New York 12208, United States
                []Division of Infectious Diseases, Wadsworth Center, New York State Department of Health , Albany, New York 12208, United States
                []Humabs BioMed SA a Subsidiary of Vir Biotechnology Inc. , 6500 Bellinzona, Switzerland
                Author notes
                [* ]Phone: (518) 473-7487. Email: nicholas.mantis@ 123456health.ny.gov .
                Author information
                http://orcid.org/0000-0002-5083-8640
                Article
                10.1021/acsinfecdis.0c00842
                8154420
                33728898
                d8cedea4-601c-4fb1-87b8-ba128e0e0391
                © 2021 The Authors. Published by American Chemical Society

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 30 November 2020
                Funding
                Funded by: U.S. Department of Health and Human Services, doi 10.13039/100000060;
                Award ID: AI119647
                Funded by: Bill and Melinda Gates Foundation, doi 10.13039/100000865;
                Award ID: OPP1176017
                Funded by: Bill and Melinda Gates Foundation, doi 10.13039/100000865;
                Award ID: OPP1170883
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                id0c00842
                id0c00842

                immunity,antibody,secretory immunoglobulin a,salmonella enterica,peyer’s patch

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