Characterization of naïve immune cell subsets important in HIV/SIV pathogenesis as a baseline for RNASeq deconvolution

The human immunodeficiency virus-1 (HIV-1) currently infects 35 million people globally. HIV preferentially infects CD4+ T cells, a critical component of the host immune system, causing their rapid depletion, which has a broad negative impact on host immunity. Chronic HIV infection also results in increased expression of inhibitory immune regulatory proteins, which is associated with impaired functionality of a wide range of immune cells. This clinical phenomenon, referred to as "immune exhaustion," precludes the slow and eventual failure of host immunity against co-infecting pathogens and is the hallmark of AIDS-related disease. In Aim 1 of our studies, we used whole blood from Indian-origin rhesus monkeys to distinguish 12 discrete immune cell subsets utilizing antibody staining and flow cytometric cell sorting. The segregated "naïve" (uninfected) cell subsets will be characterized by RNASeq gene expression analysis, and will be used as the baseline population for a bioinformatics "deconvolution" method comparing the same cell subsets from simian immunodeficiency virus (SIV)-infected cell populations. We successfully developed an antibody panel that distinguishes activated and resting CD4+ T cells, activated and resting CD8+ T cells, activated and resting B cells, activated and resting NK cells, plasmacytoid dendritic cells, myeloid dendritic cells, and monocytes. We also developed a separate isolation protocol for neutrophils using different densities of Percoll. Finally, we optimized cell sorting of CD4+ and CD8+ T cells in order to obtain sufficient amounts of high quality RNA for future RNASeq gene expression analysis. As an adjunct to our above work, in Aim 2 of our experiments we sought to quantify the expression of immune inhibitory proteins that are increased upon the various cell subsets during SIV infection. We set out to optimize an antibody panel targeting three proteins of interest, PD-L1, LAG-3, and TIM-3, for the study of whole blood from SIV-infected rhesus monkeys. This data will be used to compliment our RNASeq dataset developed in Aim 1. By utilizing a biotinylated antibody specific for PD-L1 along with fluorescently conjugated streptavidin, we were able to detect PD-L1-positive cells and allow for amplification of positive fluorescence. We also performed multiple evaluations of monoclonal antibodies specific to either LAG-3 or TIM-3 and determined the concentrations at which detection was best for LAG-3+ and TIM-3+ cells

Childhood Obesity: United States

Childhood obesity, a noncommunicable disease usually caused by consuming more energy in meals than your body needs, is often due to hereditary causes and the structure of their communities. With the average weight of American children increasing in the past thirty years, parents should be more informed on how to improve their offspring’s development and reduce the likelihood of chronic diseases. The Body Mass Index is the scale used to determine whether or not the child is considered overweight for their height and age, based off of their extra body fat. After comparing the child to the CDC growth charts, being above the 85 percentile is considered a danger zone for healthy weight. Some signs that show the child is at risk for being obese includes shortness of breath during physical exercise and/or a dislocated hip. Children are becoming obese because of the lack of playgrounds and walking trails for physical activity, as well as the absence of education for food nutrition due to their low socioeconomic status. Solutions to these problems are currently in progress, varying from providing healthier food options for the children, to creating more parks in neighborhoods and communities. With never ending possible solutions towards childhood obesity, it is important to note that the risks of these children becoming obese can lead to further issues, such as developing asthma, type 2 diabetes, or even cardiovascular disease

Determining key research areas for healthier diets and sustainable food systems in Viet Nam

Vietnamese food systems are undergoing rapid transformation, with important implications for human and environmental health and economic development. Poverty has decreased, and diet quality and undernutrition have improved significantly since the end of the Doi Moi reform period (1986-1993) as a result of Viet Nam opening its economy and increasing its regional and global trade. Yet poor diet quality is still contributing the triple burden of malnutrition, with 25 percent stunting among children under age 5, 26 percent and 29 percent of women and children, respectively, anemic, and 21 percent of adults overweight. Agricultural production systems have shifted from predominantly diverse smallholder systems to larger more commercialized and specialized systems, especially for crops, while the ‘meatification’ of the Vietnamese diet is generating serious trade-offs between improved nutrition and sustainability of the Vietnamese food systems. The food processing industry has developed rapidly, together with food imports, resulting in new and processed food products penetrating the food retail outlets, trending towards an increase in the Westernized consumption patterns that are shifting nutrition-related problems towards overweight and obesity and, with it, an increase of non-communicable disease-related health risks. While regulatory policies exist across the food system, these are not systematically implemented, making food safety a major concern for consumers and policy makers alike. Where data exists, it is not easy to aggregate with data from across food system dimensions, making it difficult for Viet Nam to make an informed analysis of current and potential food system trade-offs. In our research, we reviewed existing literature and data, and applied a food systems framework to develop an initial food systems profile for Viet Nam and to identify a comprehensive set a of research questions to fill current data gaps identified through the review. Insights on these would provide the comprehensive evidence needed to inform policy makers on how to develop new food systems policies for Viet Nam, and further refine and improve existing policies to achieve better quality diets and more sustainable food systems in Viet Nam. Based on these, we then engaged with stakeholders to develop research priorities in the Viet Nam context and identified 25 priority research questions. This paper aims to stimulate such reflections by clearly outlining key areas for research, government policy, and development programs on priority investment to build the evidence base around inclusive food systems interventions that aim to result in healthier diets and more sustainable food systems for Viet Nam

Man vs. Machine: Comparing Machine Learning and Analysts\u27 Predictions for Earnings

The main goal of this study is to determine whether machine learning can outperform analysts in forecasting earnings. Using gradient boosted regression trees (a recursive regression tree-building method), this paper concludes that machine learning is unable to beat analysts’ predictions for earnings, when comparing median absolute percentage error. The model was trained on firms with Wall Street analyst coverage for earnings between years 2013 to 2016. Predictors from existing earnings forecasting literature were input for the model’s consideration. The model’s performance was compared to analysts’ forecasts on out-of-sample earnings for years 2017 to 2019. The results suggest that analysts hold some incremental information that is useful for forecasting earnings. This incremental information is either not contained in financial statements or has not been researched in existing literature

Collateral sensitivity in clinical Escherichia coli isolates

Background At present time, antimicrobial resistance is emerging more rapidly than the development of novel antimicrobials, presenting a serious threat to how we prevent and treat infectious diseases. Several treatment strategies to counteract this development have been proposed, among these is the use of collateral sensitivity in clinical treatment. The ability to predict collateral sensitivity and cross-resistance effects is essential to exploiting this concept. In this study, we aimed to investigate the patterns of collateral sensitivity and cross-resistance in ciprofloxacin resistant isolates carrying gyrA and parC mutations. Method Ciprofloxacin resistant isolates were evolved from three clinical E. coli strain using static and dynamic selection methods. Isolates were selected based on identified mutations and level of ciprofloxacin resistance measured with diffusion gradient strips. DNA sequencing was used to detect mutations in gyrA and parC. Resistant isolates carrying at least one gyrA and parC mutation were characterized by IC90 assays with micro-broth dilutions of six unrelated antimicrobial agents. The observed collateral sensitivity and cross-resistance effects were displayed in a heat map. Results Various non-synonymous point mutations in gyrA and parC were identified in several of the generated ciprofloxacin resistant isolates. These mutants displayed collateral sensitivity and cross-resistance to several unrelated antimicrobials. Collateral sensitivity to gentamicin and trimethoprim was observed in the majority isolates. Cross-resistance effects were found in several mutants, specifically to ceftazidime, chloramphenicol and colistin. Conclusion Our findings suggest that ciprofloxacin resistant mutants with gyrA and parC mutations display a clear tendency of collateral sensitivity to gentamicin, an effect which potentially can be exploited in future treatment. However, we propose further investigation into specific point mutations within these genes, to better understand the observed variations in collateral sensitivity and cross-resistance

Charting a new course. Leaders with purpose.

Flying without direction? Need a guide? Unsure of how to incorporate the Principles of Good Practice for Student Affairs at Catholic Colleges and Universities at your institution? Already use them but trying to think of how to use them as an assessment tool that connects to existing programs and community experiences? Come join us to learn about our newly created alignment guide. This guide provides a connection to our existing Learning Dimensions, our Mount Leads Core Principles and the Principles of Good Practice. Participants can all share the different ways they use the Principles of Good Practice at their institutions. We say we are mission-driven. We say we are guided by the spirit of our founders. Now we can prove it

Lifestyle and Dietary Modifications for Reducing Psoriatic Disease Activity: A Comprehensive Review

Abstract: Psoriasis is a prevalent, immune-medication disorder affecting millions of individuals in the United States, leading to substantial healthcare costs (Armstrong, 2021; Brenzinski, 2015). Psoriasis has an established correlation with comorbidities such as hypertension, coronary artery disease, obesity, dyslipidemia, and metabolic syndrome (Al-Mutairi, 2010). Due to the substantial socioeconomic burden psoriatic disease poses on modern day society, significant benefit could be derived from identifying nonprescription strategies for patients to adopt in order to reduce disease activity. This comprehensive review includes 33 publications from 2008 to 2023, evaluating non-prescription therapeutic strategies including lifestyle modification and anti-inflammatory dietary changes. The analysis suggests a positive correlation with reducing psoriatic disease activity by practicing weight loss, adherence to a Mediterranean diet, and gluten avoidance (Di Minno et al., 2014; Phan et al., 2018; Pietzrak, 2017). Further research is needed to provide more robust evidence to establish evidence based medical guidelines with respect to lifestyle and dietary modifications. Psoriatic patients, healthcare professionals, and healthcare systems would collectively benefit from research identifying and evaluating the impact of outside factors on disease severity, such as environmental/dietary exposures with respect to patients’ varied comorbidity status and other baseline demographics

Functional Genomics Profiling of Bladder Urothelial Carcinoma MicroRNAome as a Potential Biomarker.

Though bladder urothelial carcinoma is the most common form of bladder cancer, advances in its diagnosis and treatment have been modest in the past few decades. To evaluate miRNAs as putative disease markers for bladder urothelial carcinoma, this study develops a process to identify dysregulated miRNAs in cancer patients and potentially stratify patients based on the association of their microRNAome phenotype to genomic alterations. Using RNA sequencing data for 409 patients from the Cancer Genome Atlas, we examined miRNA differential expression between cancer and normal tissues and associated differentially expressed miRNAs with patient survival and clinical variables. We then correlated miRNA expressions with genomic alterations using the Wilcoxon test and REVEALER. We found a panel of six miRNAs dysregulated in bladder cancer and exhibited correlations to patient survival. We also performed differential expression analysis and clinical variable correlations to identify miRNAs associated with tobacco smoking, the most important risk factor for bladder cancer. Two miRNAs, miR-323a and miR-431, were differentially expressed in smoking patients compared to nonsmoking patients and were associated with primary tumor size. Functional studies of these miRNAs and the genomic features we identified for potential stratification may reveal underlying mechanisms of bladder cancer carcinogenesis and further diagnosis and treatment methods for urothelial bladder carcinoma