B Cells and T Cells Abnormalities in Patients With Selective IgA Deficiency

BACKGROUND: Selective IgA deficiency (SIgAD) is the most prevalent inborn errors of immunity with almost unknown etiology. This study aimed to investigate the clinical diagnostic and prognostic values of lymphocyte subsets and function in symptomatic SIgAD patients. METHODS: A total of 30 available SIgAD patients from the Iranian registry and 30 age-sex-matched healthy controls were included in the present study. We analyzed B and T cell peripheral subsets and T cell proliferation assay by flow cytometry in SIgAD patients with mild and severe clinical phenotypes. RESULTS: Our results indicated a significant increase in naïve and transitional B cells and a strong decrease in marginal zone-like and switched memory B-cells in SIgAD patients. We found that naïve and central memory CD4 CONCLUSION: SIgAD patients have varied cellular and humoral deficiencies. Therefore, T cell and B cell assessment might help in better understanding the heterogeneous pathogenesis and prognosis estimation of the disease

Mechanical Strain Stabilizes Reconstituted Collagen Fibrils against Enzymatic Degradation by Mammalian Collagenase Matrix Metalloproteinase 8 (MMP-8)

Collagen, a triple-helical, self-organizing protein, is the predominant structural protein in mammals. It is found in bone, ligament, tendon, cartilage, intervertebral disc, skin, blood vessel, and cornea. We have recently postulated that fibrillar collagens (and their complementary enzymes) comprise the basis of a smart structural system which appears to support the retention of molecules in fibrils which are under tensile mechanical strain. The theory suggests that the mechanisms which drive the preferential accumulation of collagen in loaded tissue operate at the molecular level and are not solely cell-driven. The concept reduces control of matrix morphology to an interaction between molecules and the most relevant, physical, and persistent signal: mechanical strain.The investigation was carried out in an environmentally-controlled microbioreactor in which reconstituted type I collagen micronetworks were gently strained between micropipettes. The strained micronetworks were exposed to active matrix metalloproteinase 8 (MMP-8) and relative degradation rates for loaded and unloaded fibrils were tracked simultaneously using label-free differential interference contrast (DIC) imaging. It was found that applied tensile mechanical strain significantly increased degradation time of loaded fibrils compared to unloaded, paired controls. In many cases, strained fibrils were detectable long after unstrained fibrils were degraded.In this investigation we demonstrate for the first time that applied mechanical strain preferentially preserves collagen fibrils in the presence of a physiologically-important mammalian enzyme: MMP-8. These results have the potential to contribute to our understanding of many collagen matrix phenomena including development, adaptation, remodeling and disease. Additionally, tissue engineering could benefit from the ability to sculpt desired structures from physiologically compatible and mutable collagen

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

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 developm nt 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. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Rewiring of the Liver Transcriptome across Multiple Time-Scales Is Associated with the Weight Loss-Independent Resolution of NAFLD Following RYGB

Roux-en-Y gastric bypass (RYGB) surgery potently improves obesity and a myriad of obesity-associated co-morbidities including type 2 diabetes and non-alcoholic fatty liver disease (NAFLD). Time-series omics data are increasingly being utilized to provide insight into the mechanistic underpinnings that correspond to metabolic adaptations in RYGB. However, the conventional computational biology methods used to interpret these temporal multi-dimensional datasets have been generally limited to pathway enrichment analysis (PEA) of isolated pair-wise comparisons based on either experimental condition or time point, neither of which adequately capture responses to perturbations that span multiple time scales. To address this, we have developed a novel graph network-based analysis workflow designed to identify modules enriched with biomolecules that share common dynamic profiles, where the network is constructed from all known biological interactions available through the Kyoto Encyclopedia of Genes and Genomes (KEGG) resource. This methodology was applied to time-series RNAseq transcriptomics data collected on rodent liver samples following RYGB, and those of sham-operated and weight-matched control groups, to elucidate the molecular pathways involved in the improvement of as NAFLD. We report several network modules exhibiting a statistically significant enrichment of genes whose expression trends capture acute-phase as well as long term physiological responses to RYGB in a single analysis. Of note, we found the HIF1 and P53 signaling cascades to be associated with the immediate and the long-term response to RYGB, respectively. The discovery of less intuitive network modules that may have gone overlooked with conventional PEA techniques provides a framework for identifying novel drug targets for NAFLD and other metabolic syndrome co-morbidities

Rewiring of the Liver Transcriptome across Multiple Time-Scales Is Associated with the Weight Loss-Independent Resolution of NAFLD Following RYGB

Roux-en-Y gastric bypass (RYGB) surgery potently improves obesity and a myriad of obesity-associated co-morbidities including type 2 diabetes and non-alcoholic fatty liver disease (NAFLD). Time-series omics data are increasingly being utilized to provide insight into the mechanistic underpinnings that correspond to metabolic adaptations in RYGB. However, the conventional computational biology methods used to interpret these temporal multi-dimensional datasets have been generally limited to pathway enrichment analysis (PEA) of isolated pair-wise comparisons based on either experimental condition or time point, neither of which adequately capture responses to perturbations that span multiple time scales. To address this, we have developed a novel graph network-based analysis workflow designed to identify modules enriched with biomolecules that share common dynamic profiles, where the network is constructed from all known biological interactions available through the Kyoto Encyclopedia of Genes and Genomes (KEGG) resource. This methodology was applied to time-series RNAseq transcriptomics data collected on rodent liver samples following RYGB, and those of sham-operated and weight-matched control groups, to elucidate the molecular pathways involved in the improvement of as NAFLD. We report several network modules exhibiting a statistically significant enrichment of genes whose expression trends capture acute-phase as well as long term physiological responses to RYGB in a single analysis. Of note, we found the HIF1 and P53 signaling cascades to be associated with the immediate and the long-term response to RYGB, respectively. The discovery of less intuitive network modules that may have gone overlooked with conventional PEA techniques provides a framework for identifying novel drug targets for NAFLD and other metabolic syndrome co-morbidities

Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics

Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses

Design and Performance of an Optically Accessible, Low-Volume, Mechanobioreactor for Long-Term Study of Living Constructs

Currently available bioreactor systems used by tissue engineers permit either direct, high-magnification observation of cell behavior or application of mechanical loads to growing tissue constructs, but not both simultaneously. Further, in most loading bioreactors, the volume of the dead space is not minimized to reduce the cost associated with perfusion media, exogenous stimulatory/inhibitory agents, proteases, and label. We have designed, developed, and tested a bioreactor that simultaneously satisfies the combined requirements of providing (i) controlled tensile mechanical stimulation, (ii) direct high-magnification imaging capability, and (iii) low dead-space volume. This novel mechanostimulatory (uniaxial tensile loading) bioreactor operates on an inverted microscope and permits continuous optical access (up to 600×) to a loaded, growing construct for extended periods of time (weeks). The reactor employs an adjustable reaction chamber in which the dead space can be reduced to <2 mL. The device has been used to cultivate our human primary corneal fibroblast-derived, tissue-engineered system for up to 14 days. Using the instrument we have successfully recorded (i) the process of fibroblasts populating, growing to confluence, and stratifying on different substrates; (ii) recorded complex and organized cell sheet motions; and (iii) recorded the behavior of a subpopulation of what appear to be degradative/catabolic cells within our fibroblast culture. The device is capable of providing detailed, long-term, dynamic images of mechanically stimulated cell/matrix interaction that have not been observed previously