Simulation of neuroplasticity in a CNN-based in-silico model of neurodegeneration of the visual system

The aim of this work was to enhance the biological feasibility of a deep convolutional neural network-based in-silico model of neurodegeneration of the visual system by equipping it with a mechanism to simulate neuroplasticity. Therefore, deep convolutional networks of multiple sizes were trained for object recognition tasks and progressively lesioned to simulate neurodegeneration of the visual cortex. More specifically, the injured parts of the network remained injured while we investigated how the added retraining steps were able to recover some of the model’s object recognition baseline performance. The results showed with retraining, model object recognition abilities are subject to a smoother and more gradual decline with increasing injury levels than without retraining and, therefore, more similar to the longitudinal cognition impairments of patients diagnosed with Alzheimer’s disease (AD). Moreover, with retraining, the injured model exhibits internal activation patterns similar to those of the healthy baseline model when compared to the injured model without retraining. Furthermore, we conducted this analysis on a network that had been extensively pruned, resulting in an optimized number of parameters or synapses. Our findings show that this network exhibited remarkably similar capability to recover task performance with decreasingly viable pathways through the network. In conclusion, adding a retraining step to the in-silico setup that simulates neuroplasticity improves the model’s biological feasibility considerably and could prove valuable to test different rehabilitation approaches in-silico

Caste Matters: Perceived Discrimination among Women in Rural India

Purpose: To examine the relationship of caste and class with perceived discrimination among pregnant women from rural western India. Methods: A cross-sectional survey was administered to 170 pregnant women in rural Gujarat, India, who were enrolled in a longitudinal cohort study. Everyday Discrimination Scale and Experiences of Discrimination questionnaires were used to assess perceived discrimination and response to discrimination. Based on self-reported caste, women were classified to three categories with increasing historical disadvantage: General, Other Backward Castes (OBC), and Scheduled Caste or Tribes (SC/ST). Socioeconomic class was determined using standardized Kuppuswamy scale. Regression models for count and binomial data were used to examine association of caste and class with experience of discrimination and response to discrimination. Results: 68% of women experienced discrimination. After adjusting for confounders, there was a consistent trend and association of discrimination with caste but not class. In comparison to General Caste, lower caste (OBC, SC/ST) women were more likely to 1) experience discrimination (OBC OR: 2.2, SC/ST: 4.1; p-trend: 0.01), 2) have a greater perceived discrimination score (OBC IRR: 1.3, SC/ST: 1.5; p-trend: 0.07), 3) accept discrimination (OBC OR: 6.4, SC/ST: 7.6; p-trend: \u3c 0.01), and 4) keep to herself about discrimination (OBC OR: 2.7, SC/ST: 3.6; p-trend: 0.04). Conclusion: The differential experience of discrimination by lower caste women in comparison to upper caste women and their response to such experiences highlight the importance of studying discrimination to understand existing caste-based disparities

Addressing and Inspiring Vaccine Confidence in Black, Indigenous, and People of Color During the Coronavirus Disease 2019 Pandemic

During the coronavirus disease 2019 (COVID-19) pandemic, we have witnessed profound health inequities suffered by Black, Indigenous, and People of Color (BIPOC). These manifested as differential access to testing early in the pandemic, rates of severe disease and death 2-3 times higher than white Americans, and, now, significantly lower vaccine uptake compared with their share of the population affected by COVID-19. This article explores the impact of these COVID-19 inequities (and the underlying cause, structural racism) on vaccine acceptance in BIPOC populations, ways to establish trustworthiness of healthcare institutions, increase vaccine access for BIPOC communities, and inspire confidence in COVID-19 vaccines

RAHI-SATHI Indo-U.S. Collaboration: The Evolution of a Trainee-Led Twinning Model in Global Health Into a Multidisciplinary Collaborative Program

BACKGROUND: In recent years there has been a surge in the number of global health programs operated by academic institutions. However, most of the existing programs describe partnerships that are primarily faculty-driven and supported by extramural funding. PROGRAM DESCRIPTION: Research and Advocacy for Health in India (RAHI, or pathfinder in Hindi) and Support and Action Towards Health-Equity in India (SATHI, or partnership in Hindi) are 2 interconnected, collaborative efforts between the University of Massachusetts Medical School (UMMS) and Charutar Arogya Mandal (CAM), a medical college and a tertiary care center in rural western India. The RAHI-SATHI program is the culmination of a series of student/trainee-led research and capacity strengthening initiatives that received institutional support in the form of faculty mentorship and seed funding. RAHI-SATHI\u27s trainee-led twinning approach overcomes traditional barriers faced by global health programs. Trainees help mitigate geographical barriers by acting as a bridge between members from different institutions, garner cultural insight through their ability to immerse themselves in a community, and overcome expertise limitations through pre-planned structured mentorship from faculty of both institutions. Trainees play a central role in cultivating trust among the team members and, in the process, they acquire personal leadership skills that may benefit them in their future careers. CONCLUSION: This paradigm of trainee-led twinning partnership promotes sustainability in an uncertain funding climate and provides a roadmap for conducting foundational work that is essential for the development of a broad, university-wide global health program

Building capacity for injury prevention: a process evaluation of a replication of the Cardiff Violence Prevention Programme in the Southeastern USA

Objectives Violence is a major public health problem in the USA. In 2016, more than 1.6 million assault-related injuries were treated in US emergency departments (EDs). Unfortunately, information about the magnitude and patterns of violent incidents is often incomplete and underreported to law enforcement (LE). In an effort to identify more complete information on violence for the development of prevention programme, a cross-sectoral Cardiff Violence Prevention Programme (Cardiff Model) partnership was established at a large, urban ED with a level I trauma designation and local metropolitan LE agency in the Atlanta, Georgia metropolitan area. The Cardiff Model is a promising violence prevention approach that promotes combining injury data from hospitals and LE. The objective was to describe the Cardiff Model implementation and collaboration between hospital and LE partners. Methods The Cardiff Model was replicated in the USA. A process evaluation was conducted by reviewing project materials, nurse surveys and interviews and ED–LE records. Results Cardiff Model replication centred around four activities: (1) collaboration between the hospital and LE to form a community safety partnership locally called the US Injury Prevention Partnership; (2) building hospital capacity for data collection; (3) data aggregation and analysis and (4) developing and implementing violence prevention interventions based on the data. Conclusions The Cardiff Model can be implemented in the USA for sustainable violent injury data surveillance and sharing. Key components include building a strong ED–LE partnership, communicating with each other and hospital staff, engaging in capacity building and sustainability planning

Demonstration of surface electron rejection with interleaved germanium detectors for dark matter searches

The following article appeared in Applied Physics Letters 103.16 (2013): 164105 and may be found at http://scitation.aip.org/content/aip/journal/apl/100/26/10.1063/1.4729825The SuperCDMS experiment in the Soudan Underground Laboratory searches for dark matter with a 9-kg array of cryogenic germanium detectors. Symmetric sensors on opposite sides measure both charge and phonons from each particle interaction, providing excellent discrimination between electron and nuclear recoils, and between surface and interior events. Surface event rejection capabilities were tested with two 210 Pb sources producing ∼130 beta decays/hr. In ∼800 live hours, no events leaked into the 8–115 keV signal region, giving upper limit leakage fraction 1.7 × 10−5 at 90% C.L., corresponding to < 0.6 surface event background in the future 200-kg SuperCDMS SNOLAB experiment.This work is supported in part by the National Science Foundation (Grant Nos. AST-9978911, NSF-0847342, PHY-1102795,NSF-1151869, PHY-0542066, PHY-0503729, PHY-0503629, PHY-0503641, PHY-0504224, PHY-0705052,PHY-0801708, PHY-0801712, PHY-0802575, PHY-0847342, PHY-0855299, PHY-0855525, and PHY-1205898), by the Department of Energy (Contract Nos. DE-AC03-76SF00098, DE-FG02-92ER40701, DE-FG02-94ER40823,DE-FG03-90ER40569, DE-FG03-91ER40618, and DESC0004022),by NSERC Canada (Grant Nos. SAPIN 341314 and SAPPJ 386399), and by MULTIDARK CSD2009-00064 and FPA2012-34694. Fermilab is operated by Fermi Research Alliance, LLC under Contract No. De-AC02-07CH11359, while SLAC is operated under Contract No. DE-AC02-76SF00515 with the United States Department of Energy

A Genome-Wide Study of Cytogenetic Changes in Colorectal Cancer Using SNP Microarrays: Opportunities for Future Personalized Treatment

In colorectal cancer (CRC), chromosomal instability (CIN) is typically studied using comparative-genomic hybridization (CGH) arrays. We studied paired (tumor and surrounding healthy) fresh frozen tissue from 86 CRC patients using Illumina's Infinium-based SNP array. This method allowed us to study CIN in CRC, with simultaneous analysis of copy number (CN) and B-allele frequency (BAF) - a representation of allelic composition. These data helped us to detect mono-allelic and bi-allelic amplifications/deletion, copy neutral loss of heterozygosity, and levels of mosaicism for mixed cell populations, some of which can not be assessed with other methods that do not measure BAF. We identified associations between CN abnormalities and different CRC phenotypes (histological diagnosis, location, tumor grade, stage, MSI and presence of lymph node metastasis). We showed commonalities between regions of CN change observed in CRC and the regions reported in previous studies of other solid cancers (e.g. amplifications of 20q, 13q, 8q, 5p and deletions of 18q, 17p and 8p). From Therapeutic Target Database, we identified relevant drugs, targeted to the genes located in these regions with CN changes, approved or in trials for other cancers and common diseases. These drugs may be considered for future therapeutic trials in CRC, based on personalized cytogenetic diagnosis. We also found many regions, harboring genes, which are not currently targeted by any relevant drugs that may be considered for future drug discovery studies. Our study shows the application of high density SNP arrays for cytogenetic study in CRC and its potential utility for personalized treatment

Variation in carbon and nitrogen concentrations among peatland categories at the global scale

Publisher Copyright: © 2022 This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.Peatlands account for 15 to 30% of the world's soil carbon (C) stock and are important controls over global nitrogen (N) cycles. However, C and N concentrations are known to vary among peatlands contributing to the uncertainty of global C inventories, but there are few global studies that relate peatland classification to peat chemistry. We analyzed 436 peat cores sampled in 24 countries across six continents and measured C, N, and organic matter (OM) content at three depths down to 70 cm. Sites were distinguished between northern (387) and tropical (49) peatlands and assigned to one of six distinct broadly recognized peatland categories that vary primarily along a pH gradient. Peat C and N concentrations, OM content, and C:N ratios differed significantly among peatland categories, but few differences in chemistry with depth were found within each category. Across all peatlands C and N concentrations in the 10-20 cm layer, were 440 ± 85.1 g kg-1 and 13.9 ± 7.4 g kg-1, with an average C:N ratio of 30.1 ± 20.8. Among peatland categories, median C concentrations were highest in bogs, poor fens and tropical swamps (446-532 g kg-1) and lowest in intermediate and extremely rich fens (375-414 g kg-1). The C:OM ratio in peat was similar across most peatland categories, except in deeper samples from ombrotrophic tropical peat swamps that were higher than other peatlands categories. Peat N concentrations and C:N ratios varied approximately two-fold among peatland categories and N concentrations tended to be higher (and C:N lower) in intermediate fens compared with other peatland types. This study reports on a unique data set and demonstrates that differences in peat C and OM concentrations among broadly classified peatland categories are predictable, which can aid future studies that use land cover assessments to refine global peatland C and N stocks.Peer reviewe