Insecticide resistance and its intensity in urban Anopheles arabiensis in Kisumu City, Western Kenya: Implications for malaria control in urban areas.

Background: The rise of insecticide resistance poses a growing challenge to the effectiveness of vector control tools, particularly in rural areas. However, the urban setting has received comparatively less focus despite its significance in attracting rural to urban migration. Unplanned urbanization, often overlooked, exacerbates insecticide resistance as Anopheles mosquitoes adapt to the polluted environments of rapidly expanding cities.

Bionomics and distribution of malaria vectors in Kisumu city, Western Kenya: Implications for urban malaria transmission.

Background: Increasing urbanization in tropical Africa may create new niches for malaria vectors, potentially leading to higher disease transmission rates. Vector control efforts remain largely targeted at ecologically rural bio-complexities with multiple hosts. Understanding mosquito species composition, ecology, host diversity and biting behavior in urban areas is crucial for planning effective control.

CryoEM structure of an MHC-I/TAPBPR peptide bound intermediate reveals the mechanism of antigen proofreading.

Class I major histocompatibility complex (MHC-I) proteins play a pivotal role in adaptive immunity by displaying epitopic peptides to CD8+ T cells. The chaperones tapasin and TAPBPR promote the selection of immunogenic antigens from a large pool of intracellular peptides. Interactions of chaperoned MHC-I molecules with incoming peptides are transient in nature, and as a result, the precise antigen proofreading mechanism remains elusive.

Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization.

Introduction: Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical models (CSM), but the calibration of such models is unclear.

Objectives: To compare models developed using ML with those developed using CSM to predict 30-day readmission for cardiovascular and noncardiovascular causes in HF patients.

scGPT: toward building a foundation model for single-cell multi-omics using generative AI.

Generative pretrained models have achieved remarkable success in various domains such as language and computer vision. Specifically, the combination of large-scale diverse datasets and pretrained transformers has emerged as a promising approach for developing foundation models. Drawing parallels between language and cellular biology (in which texts comprise words; similarly, cells are defined by genes), our study probes the applicability of foundation models to advance cellular biology and genetic research.

Strength of CAR signaling determines T cell versus ILC differentiation from pluripotent stem cells.

Generation of chimeric antigen receptor (CAR) T cells from pluripotent stem cells (PSCs) will enable advances in cancer immunotherapy. Understanding how CARs affect T cell differentiation from PSCs is important for this effort. The recently described artificial thymic organoid (ATO) system supports in vitro differentiation of PSCs to T cells.

Clinical malaria incidence and health seeking pattern in geographically heterogeneous landscape of western Kenya.

Background: Malaria remains a public health problem in Kenya despite sustained interventions deployed by the government. One of the major impediments to effective malaria control is a lack of accurate diagnosis and effective treatment. This study was conducted to assess clinical malaria incidence and treatment seeking profiles of febrile cases in western Kenya.

Influence of landscape heterogeneity on entomological and parasitological indices of malaria in Kisumu, Western Kenya.

Background: Identification and characterization of larval habitats, documentation of Anopheles spp. composition and abundance, and Plasmodium spp. infection burden are critical components of integrated vector management.

Comparison of machine learning and the regression-based EHMRG model for predicting early mortality in acute heart failure.

Background: Although risk stratification of patients with acute decompensated heart failure (HF) is important, it is unknown whether machine learning (ML) or conventional statistical models are optimal. We developed ML algorithms to predict 7-day and 30-day mortality in patients with acute HF and compared these with an existing logistic regression model at the same timepoints.

Methods: Patients presenting to one of 86 hospitals, who were either admitted to hospital or discharged home directly from the emergency department, were randomly selected using stratified random sampling.

Risk associations of submicroscopic malaria infection in lakeshore, plateau and highland areas of Kisumu County in western Kenya.

Background: Persons with submicroscopic malaria infection are a major reservoir of gametocytes that sustain malaria transmission in sub-Saharan Africa. Despite recent decreases in the national malaria burden in Kenya due to vector control interventions, malaria transmission continues to be high in western regions of the country bordering Lake Victoria. The objective of this study was to advance knowledge of the topographical, demographic and behavioral risk factors associated with submicroscopic malaria infection in the Lake Victoria basin in Kisumu County.

Health care provider practices in diagnosis and treatment of malaria in rural communities in Kisumu County, Kenya.

Background: Accurate malaria diagnosis and appropriate treatment at local health facilities are critical to reducing morbidity and human reservoir of infectious gametocytes. The current study assessed the accuracy of malaria diagnosis and treatment practices in three health care facilities in rural western Kenya.

Methods: The accuracy of malaria detection and treatment recommended compliance was monitored in two public and one private hospital from November 2019 through March 2020.

One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data.

Integrative analysis of large-scale single-cell RNA sequencing (scRNA-seq) datasets can aggregate complementary biological information from different datasets. However, most existing methods fail to efficiently integrate multiple large-scale scRNA-seq datasets. We propose OCAT, One Cell At a Time, a machine learning method that sparsely encodes single-cell gene expression to integrate data from multiple sources without highly variable gene selection or explicit batch effect correction.

Factors associated with SARS-CoV-2 test positivity in long-term care homes: A population-based cohort analysis using machine learning.

Background: SARS-Cov-2 infection rates are high among residents of long-term care (LTC) homes. We used machine learning to identify resident and community characteristics predictive of SARS-Cov-2 infection.

Methods: We linked 26 population-based health and administrative databases to identify the population of all LTC residents tested for SARS-Cov-2 infection in Ontario, Canada.

Predictors of mortality among long-term care residents with SARS-CoV-2 infection.

Background: While individuals living in long-term care (LTC) homes have experienced adverse outcomes of SARS-CoV-2 infection, few studies have examined a broad range of predictors of 30-day mortality in this population.

Methods: We studied residents living in LTC homes in Ontario, Canada, who underwent PCR testing for SARS-CoV-2 infection from January 1 to August 31, 2020, and examined predictors of all-cause death within 30 days after a positive test for SARS-CoV-2. We examined a broad range of risk factor categories including demographics, comorbidities, functional status, laboratory tests, and characteristics of the LTC facility and surrounding community were examined.

Assessing the Relevance of Solution Phase Stress Testing of Solid Dosage Form Drug Products: A Cross-Industry Benchmarking Study.

Stress testing (also known as forced degradation) of pharmaceutical products has long been recognized as a critical part of the drug development process, providing foundational information related to intrinsic stability characteristics and to the development of stability-indicating analytical methods. A benchmarking study was undertaken by nine pharmaceutical companies and the Brazilian Health Regulatory Agency (Agência Nacional de Vigilância Sanitária, or ANVISA) with a goal of understanding the utility of various stress testing conditions for producing pharmaceutically-relevant chemical degradation of drugs. Special consideration was given to determining whether solution phase stress testing of solid drug products produced degradation products that were both unique when compared to other stress conditions and relevant to the formal drug product stability data.

Hepatitis C and Racial Disparity in Liver Transplant Waitlist Additions : Separate Not Equal.

Background: In 2014, direct-acting antivirals (DAAs) became available for hepatitis C virus (HCV) with successful results. Since their implementation, the rate of HCV waitlist (WL) for liver transplantation (LT) has decreased, but significant ethnic disparities exist. We hypothesized that the rate of decline for HCV WL for LT is different across the various racial groups.

Silicone Wristbands as Passive Samplers in Honey Bee Hives.

The recent decline of European honey bees ( ) has prompted a surge in research into their chemical environment, including chemicals produced by bees, as well as chemicals produced by plants and derived from human activity that bees also interact with. This study sought to develop a novel approach to passively sampling honey bee hives using silicone wristbands. Wristbands placed in hives for 24 h captured various compounds, including long-chain hydrocarbons, fatty acids, fatty alcohols, sugars, and sterols with wide ranging octanol-water partition coefficients (K) that varied by up to 19 orders of magnitude.

Microbial colonization of metal sulfide minerals at a diffuse-flow deep-sea hydrothermal vent at 9°50'N on the East Pacific Rise.

Metal sulfide minerals, including mercury sulfides (HgS), are widespread in hydrothermal vent systems where sulfur-oxidizing microbes are prevalent. Questions remain as to the impact of mineral composition and structure on sulfur-oxidizing microbial populations at deep-sea hydrothermal vents, including the possible role of microbial activity in remobilizing elemental Hg from HgS. In the present study, metal sulfides varying in metal composition, structure, and surface area were incubated for 13 days on and near a diffuse-flow hydrothermal vent at 9°50'N on the East Pacific Rise.

Symptomatic, Radiological, and Quality of Life Outcome of Paraesophageal Hernia Repair With Urinary Bladder Extracellular Surgical Matrix: Comparison With Primary Repair.

Introduction: Paraesophageal hernia repairs are prone to recurrence and mesh reinforcement is common. Both biologic and prosthetic meshes have been used. We report a comparison of a new type of biologically derived graft, Gentrix Surgical Urinary Bladder Matrix (UBM).

Metabolomics in patients with psychosis: A systematic review.

The purpose of this article is to provide a comprehensive review of metabolomics studies for psychosis, as a means of biomarker discovery. Manuscripts were selected for review if they involved discovery of metabolites using high-throughput analysis in human subjects and were published in the last decade. The metabolites identified were searched in Human Metabolome Data Base (HMDB) for a link to psychosis.

Long-term weathering and continued oxidation of oil residues from the Deepwater Horizon spill.

To investigate the long-term weathering of oil from the Deepwater Horizon (DWH) incident, oil-soaked sand patties were collected from Gulf of Mexico beaches from Florida to Alabama over a three-year period from 2012 to 2014. Analysis of oil residues by gas chromatography with flame ionization detection (GC-FID), thin-layer chromatography with flame ionization detection (TLC-FID), and Fourier transform infrared spectroscopy (FT-IR) indicated uniformity in their chemical composition. Some variability within and between samples was observed, arising from differences in exposure to light and water, which increase the amount of weathering.

Perception about transplant of rural and urban patients with chronic kidney disease; a qualitative study.

Background: Chronic kidney disease (CKD) is a worldwide public health problem with increasing incidence and prevalence and associated expenses.

Objectives: To explore different perceptions of rural and urban patients with chronic kidney disease (CKD) about kidney transplant.

Patients And Methods: We conducted four focus groups, each including 5 or 6 patients with stage 5 CKD or end stage renal disease living in a rural or urban area.

Perceptions of patient candidacy for kidney transplant in the United States: a qualitative study comparing rural and urban nephrologists.

Objectives: To explore different perceptions of urban and rural nephrologists regarding patient suitability for transplant.

Materials And Methods: We conducted 4 focus groups, each consisting of 4 to 6 nephrologists practicing in either a rural (n=9) or an urban setting (n=11). A topic guide was developed and modified according to pilot testing.