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. Using burgeoning single-cell sequencing data, we have constructed a foundation model for single-cell biology, scGPT, based on a generative pretrained transformer across a repository of over 33 million cells. Our findings illustrate that scGPT effectively distills critical biological insights concerning genes and cells. Through further adaptation of transfer learning, scGPT can be optimized to achieve superior performance across diverse downstream applications. This includes tasks such as cell type annotation, multi-batch integration, multi-omic integration, perturbation response prediction and gene network inference.

Community case management of malaria in Western Kenya: performance of community health volunteers in active malaria case surveillance.

BACKGROUND: In western Kenya, not all malaria cases are reported as stipulated in the community case management of malaria (CCMm) strategy. This underreporting affects the equity distribution of malaria commodities and the evaluation of interventions. The current study aimed to evaluate the effectiveness of community health volunteers' active case detection and management of malaria in western Kenya. METHODS: Cross-sectional active case detection (ACD) of malaria survey was carried out between May and August 2021 in three eco-epidemiologically distinct zones in Kisumu, western Kenya: Kano Plains, Lowland lakeshore and Highland Plateau. The CHVs conducted biweekly ACD of malaria household visits to interview and examine residents for febrile illness. The Community Health Volunteers (CHVs) performance during the ACD of malaria was observed and interviews done using structured questionnaires. RESULTS: Of the total 28,800 surveyed, 2597 (9%) had fever and associated malaria symptoms. Eco-epidemiological zones, gender, age group, axillary body temperature, bed net use, travel history, and survey month all had a significant association with malaria febrile illness (p < 0.05). The qualification of the CHV had a significant influence on the quality of their service. The number of health trainings received by the CHVs was significantly related to the correctness of using job aid (χ2 = 6.261, df = 1, p = 0.012) and safety procedures during the ACD activity (χ2 = 4.114, df = 1, p = 0.043). Male CHVs were more likely than female CHVs to correctly refer RDT-negative febrile residents to a health facility for further treatment (OR = 3.94, 95% CI = 1.85-5.44, p < 0.0001). Most of RDT-negative febrile residents who were correctly referred to the health facility came from the clusters with a CHV having 10 years of experience or more (OR = 1.29, 95% CI = 1.05-1.57, p = 0.016). Febrile residents in clusters managed by CHVs with more than 10 years of experience (OR = 1.82, 95% CI = 1.43-2.31, p < 0.0001), who had a secondary education (OR = 1.53, 95% CI = 1.27-1.85, p < 0.0001), and were over the age of 50 (OR = 1.44, 95% CI = 1.18-1.76, p < 0.0001), were more likely to seek malaria treatment in public hospitals. All RDT positive febrile residents were given anti-malarial by the CHVs, and RDT negatives were referred to the nearest health facility for further treatment. CONCLUSIONS: The CHV's years of experience, education level, and age had a significant influence on their service quality. Understanding the qualifications of CHVs can assist healthcare systems and policymakers in designing effective interventions that assist CHVs in providing high-quality services to their communities.

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. Blood smears from febrile patients were examined by hospital laboratory technicians and re-examined by an expert microscopists thereafter subjected to real-time polymerase chain reaction (RT-PCR) for quality assurance. In addition, blood smears from patients diagnosed with malaria rapid diagnostic tests (RDT) and presumptively treated with anti-malarial were re-examined by an expert microscopist. RESULTS: A total of 1131 febrile outpatients were assessed for slide positivity (936), RDT (126) and presumptive diagnosis (69). The overall positivity rate for Plasmodium falciparum was 28% (257/936). The odds of slide positivity was higher in public hospitals, 30% (186/624, OR:1.44, 95% CI = 1.05-1.98, p < 0.05) than the private hospital 23% (71/312, OR:0.69, 95% CI = 0.51-0.95, p < 0.05). Anti-malarial treatment was dispensed more at public hospitals (95.2%, 177/186) than the private hospital (78.9%, 56/71, p < 0.0001). Inappropriate anti-malarial treatment, i.e. artemether-lumefantrine given to blood smear negative patients was higher at public hospitals (14.6%, 64/438) than the private hospital (7.1%, 17/241) (p = 0.004). RDT was the most sensitive (73.8%, 95% CI = 39.5-57.4) and specific (89.2%, 95% CI = 78.5-95.2) followed by hospital microscopy (sensitivity 47.6%, 95% CI = 38.2-57.1) and specificity (86.7%, 95% CI = 80.8-91.0). Presumptive diagnosis had the lowest sensitivity (25.7%, 95% CI = 13.1-43.6) and specificity (75.0%, 95% CI = 50.6-90.4). RDT had the highest non-treatment of negatives [98.3% (57/58)] while hospital microscopy had the lowest [77.3% (116/150)]. Health facilities misdiagnosis was at 27.9% (77/276). PCR confirmed 5.2% (4/23) of the 77 misdiagnosed cases as false positive and 68.5% (37/54) as false negative. CONCLUSIONS: The disparity in malaria diagnosis at health facilities with many slide positives reported as negatives and high presumptive treatment of slide negative cases, necessitates augmenting microscopic with RDTs and calls for Ministry of Health strengthening supportive infrastructure to be in compliance with treatment guidelines of Test, Treat, and Track to improve malaria case management.

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. METHODS: Active case detection of malaria was carried out in three eco-epidemiologically distinct zones topologically characterized as lakeshore, hillside, and highland plateau in Kisumu County, western Kenya, from March 2020 to March 2021. Community Health Volunteers (CHVs) conducted biweekly visits to residents in their households to interview and examine for febrile illness. A febrile case was defined as an individual having fever (axillary temperature ≥ 37.5 °C) during examination or complaints of fever and other nonspecific malaria related symptoms 1-2 days before examination. Prior to the biweekly malaria testing by the CHVs, the participants' treatment seeking methods were based on their behaviors in response to febrile illness. In suspected malaria cases, finger-prick blood samples were taken and tested for malaria parasites with ultra-sensitive Alere® malaria rapid diagnostic tests (RDT) and subjected to real-time polymerase chain reaction (RT-PCR) for quality control examination. RESULTS: Of the total 5838 residents interviewed, 2205 residents had high temperature or reported febrile illness in the previous two days before the visit. Clinical malaria incidence (cases/1000people/month) was highest in the lakeshore zone (24.3), followed by the hillside (18.7) and the highland plateau zone (10.3). Clinical malaria incidence showed significant difference across gender (χ2 = 7.57; df = 2, p = 0.0227) and age group (χ2 = 58.34; df = 4, p < 0.0001). Treatment seeking patterns of malaria febrile cases showed significant difference with doing nothing (48.7%) and purchasing antimalarials from drug shops (38.1%) being the most common health-seeking pattern among the 2205 febrile residents (χ2 = 21.875; df = 4, p < 0.0001). Caregivers of 802 school-aged children aged 5-14 years with fever primarily sought treatment from drug shops (28.9%) and public hospitals (14.0%), with significant lower proportions of children receiving treatment from traditional medication (2.9%) and private hospital (4.4%) (p < 0.0001). There was no significant difference in care givers' treatment seeking patterns for feverish children under the age of five (p = 0.086). Residents with clinical malaria cases in the lakeshore and hillside zones sought treatment primarily from public hospitals (61.9%, 60/97) traditional medication (51.1%, 23/45) respectively (p < 0.0001). However, there was no significant difference in the treatment seeking patterns of highland plateau residents with clinical malaria (p = 0.431).The main factors associated with the decision to seek treatment were the travel distance to the health facility, the severity of the disease, confidence in the treatment, and affordability. CONCLUSION: Clinical malaria incidence remains highest in the Lakeshore (24.3cases/1000 people/month) despite high LLINs coverage (90%). The travel distance to the health facility, severity of disease and affordability were mainly associated with 80% of residents either self-medicating or doing nothing to alleviate their illness. The findings of this study suggest that the Ministry of Health should strengthen community case management of malaria by providing supportive supervision of community health volunteers to advocate for community awareness, early diagnosis, and treatment of malaria.

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. Metabolites associated with psychosis based on evidence in HMBD were then searched using PubMed to explore the availability of further evidence. Almost all of the studies which underwent full review involved patients with schizophrenia. Ten biomarkers were identified. Six of them were reported in two or more independent metabolomics studies: N-acetyl aspartate, lactate, tryptophan, kynurenine, glutamate, and creatine. Four additional metabolites were encountered in a single metabolomics study but had significant evidence (two supporting articles or more) for a link to psychosis based on PubMed: linoleic acid, D-serine, glutathione, and 3-hydroxybutyrate. The pathways affected are discussed as they may be relevant to the pathophysiology of psychosis, and specifically of schizophrenia, as well as, constitute new drug targets for treatment of related conditions. Based on the biomarkers identified, early diagnosis of schizophrenia and/or monitoring may be possible.

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. Unexpectedly, PSCs transduced with a CD19-targeted CAR resulted in diversion of T cell differentiation to the innate lymphoid cell 2 (ILC2) lineage in ATOs. T cells and ILC2s are closely related lymphoid lineages with shared developmental and transcriptional programs. Mechanistically, we show that antigen-independent CAR signaling during lymphoid development enriched for ILC2-primed precursors at the expense of T cell precursors. We applied this understanding to modulate CAR signaling strength through expression level, structure, and presentation of cognate antigen to demonstrate that the T cell-versus-ILC lineage decision can be rationally controlled in either direction, providing a framework for achieving CAR-T cell development from PSCs.

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. We demonstrate that OCAT efficiently integrates multiple scRNA-seq datasets and achieves the state-of-the-art performance in cell type clustering, especially in challenging scenarios of non-overlapping cell types. In addition, OCAT can efficaciously facilitate a variety of downstream analyses.

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. ML approaches, including neural networks, random forest, XGBoost, and the Lasso, were compared with a validated logistic regression model for discrimination and calibration. RESULTS: Among 12,608 patients in our analysis, lasso regression (c-statistic 0.774; 95% CI, 0.743, 0.806) performed better than other ML models for 7-day mortality but did not outperform the baseline logistic regression model (0.794; 95% CI, 0.789, 0.800). For 30-day mortality, XGBoost performed better than other ML models (c-statistic 0.759; 95% CI; 0.740, 0.779), but was not significantly better than logistic regression (c-statistic 0.755; 95% CI, 0.750, 0.762). Logistic regression demonstrated better calibration at 7 days (calibration-in-the-large 0.017; 95% CI, -0.657, 0.692, and calibration slope 0.954; 95% CI, 0.769, 1.139), and at 30 days (-0.026; 95% CI, -0.374, 0.322, and 0.964; 95% CI, 0.831, 1.098), and best Brier scores, compared to ML approaches. CONCLUSIONS: Logistic regression was comparable to ML in discrimination, but was superior to ML algorithms in calibration overall. ML algorithms for prognosis should routinely report calibration metrics in addition to discrimination.

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. METHODS: Cross-sectional community surveys for malaria infection were undertaken in three eco-epidemiologically distinct zones in Nyakach sub-County, Kisumu. Adjacent regions were topologically characterized as lakeshore, hillside and highland plateau. Surveys were conducted during the 2019 and 2020 wet and dry seasons. Finger prick blood smears and dry blood spots (DBS) on filter paper were collected from 1,777 healthy volunteers for microscopic inspection and real time-PCR (RT-PCR) diagnosis of Plasmodium infection. Persons who were PCR positive but blood smear negative were considered to harbor submicroscopic infections. Topographical, demographic and behavioral risk factors were correlated with community prevalence of submicroscopic infections. RESULTS: Out of a total of 1,777 blood samples collected, 14.2% (253/1,777) were diagnosed as submicroscopic infections. Blood smear microscopy and RT-PCR, respectively, detected 3.7% (66/1,777) and 18% (319/1,777) infections. Blood smears results were exclusively positive for P. falciparum, whereas RT-PCR also detected P. malariae and P. ovale mono- and co-infections. Submicroscopic infection prevalence was associated with topographical variation (χ2 = 39.344, df = 2, p<0.0001). The highest prevalence was observed in the lakeshore zone (20.6%, n = 622) followed by the hillside (13.6%, n = 595) and highland plateau zones (7.9%, n = 560). Infection prevalence varied significantly according to season (χ2 = 17.374, df = 3, p<0.0001). The highest prevalence was observed in residents of the lakeshore zone in the 2019 dry season (29.9%, n = 167) and 2020 and 2019 rainy seasons (21.5%, n = 144 and 18.1%, n = 155, respectively). In both the rainy and dry seasons the likelihood of submicroscopic infection was higher in the lakeshore (AOR: 2.71, 95% CI = 1.85-3.95; p<0.0001) and hillside (AOR: 1.74, 95% CI = 1.17-2.61, p = 0.007) than in the highland plateau zones. Residence in the lakeshore zone (p<0.0001), male sex (p = 0.025), school age (p = 0.002), and living in mud houses (p = 0.044) increased the risk of submicroscopic malaria infection. Bed net use (p = 0.112) and occupation (p = 0.116) were not associated with submicroscopic infection prevalence. CONCLUSION: Topographic features of the local landscape and seasonality are major correlates of submicroscopic malaria infection in the Lake Victoria area of western Kenya. Diagnostic tests more sensitive than blood smear microscopy will allow for monitoring and targeting geographic sites where additional vector interventions are needed to reduce malaria transmission.

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. The present study aimed to investigate the effect of landscape heterogeneity on entomological and parasitological indices of malaria in western Kenya. METHODS: A cross-sectional entomological and parasitological survey was conducted along an altitudinal transect in three eco-epidemiological zones: lakeshore along the lakeside, hillside, and highland plateau during the wet and dry seasons in 2020 in Kisumu County, Kenya. Larval habitats for Anopheles mosquitoes were identified and characterized. Adult mosquitoes were sampled using pyrethrum spray catches (PSC). Finger prick blood samples were taken from residents and examined for malaria parasites by real-time PCR (RT-PCR). RESULTS: Increased risk of Plasmodium falciparum infection was associated with residency in the lakeshore zone, school-age children, rainy season, and no ITNs (χ2 = 41.201, df = 9, P < 0.0001). Similarly, lakeshore zone and the rainy season significantly increased Anopheles spp. abundance. However, house structures such as wall type and whether the eave spaces were closed or open, as well as the use of ITNs, did not affect Anopheles spp. densities in the homes (χ2 = 38.695, df = 7, P < 0.0001). Anopheles funestus (41.8%) and An. arabiensis (29.1%) were the most abundant vectors in all zones. Sporozoite prevalence was 5.6% and 3.2% in the two species respectively. The lakeshore zone had the highest sporozoite prevalence (4.4%, 7/160) and inoculation rates (135.2 infective bites/person/year). High larval densities were significantly associated with lakeshore zone and hillside zones, animal hoof prints and tire truck larval habitats, wetland and pasture land, and the wet season. The larval habitat types differed significantly across the landscape zones and seasonality (χ2 = 1453.044, df = 298, P < 0.0001). CONCLUSION: The empirical evidence on the impact of landscape heterogeneity and seasonality on vector densities, parasite transmission, and Plasmodium infections in humans emphasizes the importance of tailoring specific adaptive environmental management interventions to specific landscape attributes to have a significant impact on transmission reduction.

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. The results from studies of 62 solid dosage form drug products were compiled.  A total of 387 degradation products were reported as being observed in stress testing studies, along with 173 degradation products observed in accelerated and/or long-term stability studies for the 62 drug products.  Among these, 25 of the stress testing degradation products were unique to the solution phase stress testing of the drug products; however, none of these unique degradation products were relevant to the formal stability data. The relevant degradation products were sufficiently accounted for by stress testing studies that included only drug substance stressing (in solution and in the solid state) and drug product stressing (in the solid state). Based on these results, it is the opinion of the authors that for solid dosage form drug products, well-designed stress testing studies need not include solution phase stress testing of the drug product in order to be comprehensive.

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. Using ensemble-based algorithms, we examined 484 factors, including individual-level demographics, healthcare use, comorbidities, functional status, and laboratory results; and community-level characteristics to identify factors predictive of infection. Analyses were performed separately for January to April (early wave 1) and May to August (late wave 1). FINDINGS: Among 80,784 LTC residents, 64,757 (80.2%) were tested for SARS-Cov-2 (median age 86 (78-91) years, 30.6% male), of whom 10.2% of 33,519 and 5.2% of 31,238 tested positive in early and late wave 1, respectively. In the late phase (when restriction of visitors, closure of communal spaces, and universal masking in LTC were routine), regional-level characteristics comprised 33 of the top 50 factors associated with testing positive, while laboratory values and comorbidities were also predictive. The c-index of the final model was 0.934, and sensitivity was 0.887. In the highest versus lowest risk quartiles, the odds ratio for infection was 114.3 (95% CI 38.6-557.3). LTC-related geographic variations existed in the distribution of observed infection rates and the proportion of residents at highest risk. INTERPRETATION: Machine learning informed evaluation of predicted and observed risks of SARS-CoV-2 infection at the resident and LTC levels, and may inform initiatives to improve care quality in this setting. FUNDING: Funded by a Canadian Institutes of Health Research, COVID-19 Rapid Research Funding Opportunity grant (# VR4 172736) and a Peter Munk Cardiac Centre Innovation Grant. Dr. D. Lee is the Ted Rogers Chair in Heart Function Outcomes, University Health Network, University of Toronto. Dr. Austin is supported by a Mid-Career investigator award from the Heart and Stroke Foundation. Dr. McAlister is supported by an Alberta Health Services Chair in Cardiovascular Outcomes Research. Dr. Kaul is the CIHR Sex and Gender Science Chair and the Heart & Stroke Chair in Cardiovascular Research. Dr. Rochon holds the RTO/ERO Chair in Geriatric Medicine from the University of Toronto. Dr. B. Wang holds a CIFAR AI chair at the Vector Institute.

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. In total, 304 potential predictors were evaluated for their association with mortality using machine learning (Random Forest). RESULTS: A total of 64,733 residents of LTC, median age 86 (78, 91) years (31.8% men), underwent SARS-CoV-2 testing, of whom 5029 (7.8%) tested positive. Thirty-day mortality rates were 28.7% (1442 deaths) after a positive test. Of 59,702 residents who tested negative, 2652 (4.4%) died within 30 days of testing. Predictors of mortality after SARS-CoV-2 infection included age, functional status (e.g., activity of daily living score and pressure ulcer risk), male sex, undernutrition, dehydration risk, prior hospital contacts for respiratory illness, and duration of comorbidities (e.g., heart failure, COPD). Lower GFR, hemoglobin concentration, lymphocyte count, and serum albumin were associated with higher mortality. After combining all covariates to generate a risk index, mortality rate in the highest risk quartile was 48.3% compared with 7% in the first quartile (odds ratio 12.42, 95%CI: 6.67, 22.80, p < 0.001). Deaths continued to increase rapidly for 15 days after the positive test. CONCLUSIONS: LTC residents, particularly those with reduced functional status, comorbidities, and abnormalities on routine laboratory tests, are at high risk for mortality after SARS-CoV-2 infection. Recognizing high-risk residents in LTC may enhance institution of appropriate preventative measures.

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. METHODS: We conducted a retrospective cohort study using Organ Procurement and Transplantation Network data reports of adult LT candidates from 2014 to 2018. RESULTS: Overall, there was a decline in HCV WL rates for all ethnic groups (Caucasians, African Americans [AA], and Hispanics). However, the WL rates were significantly higher in AA compared with Caucasians each year, and this trend was continuous across the 5-year period. There were no differences in WL rates between Caucasians and Hispanics. DISCUSSION: The results show that health care disparities related to HCV disproportionately affect AA. The factors associated with this disparity need to be explored further to develop mechanisms to address these differences. By understanding the HCV treatment disparities across racial groups, modifications to HCV treatment nationwide can be adopted. Additional emphasis should be placed on AA to help reduce their WL rate, as well as redistributing resources to promote health care equity.

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. Upon retrieval, incubated minerals were examined by scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), X-ray diffraction (XRD), and epifluorescence microscopy (EFM). DNA was extracted from mineral samples, and the 16S ribosomal RNA gene sequenced to characterize colonizing microbes. Sulfur-oxidizing genera common to newly exposed surfaces (Sulfurimonas, Sulfurovum, and Arcobacter) were present on all samples. Differences in their relative abundance between and within incubation sites point to constraining effects of the immediate environment and the minerals themselves. Greater variability in colonizing community composition on off-vent samples suggests that the bioavailability of mineral-derived sulfide (as influenced by surface area, crystal structure, and reactivity) exerted greater control on microbial colonization in the ambient environment than in the vent environment, where dissolved sulfide is more abundant. The availability of mineral-derived sulfide as an electron donor may thus be a key control on the activity and proliferation of deep-sea chemosynthetic communities, and this interpretation supports the potential for microbial dissolution of HgS at hydrothermal vents.

Silicone Wristbands as Passive Samplers in Honey Bee Hives.

The recent decline of European honey bees (Apis mellifera) 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 (Kow) that varied by up to 19 orders of magnitude. Most of the compounds identified from the wristbands are known to be produced by bees or plants. This study indicates that silicone wristbands provide a simple, affordable, and passive method for sampling the chemical environment of honey bees.

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). METHODS: The medical records of 65 patients who underwent paraesophageal hernia repair (PEHR) were reviewed. Primary data points included demographics, first-time or recurrent hernia, operative approach, graft or primary repair, operative time, and postoperative complications. Patients then underwent upper gastrointestinal series, completed the GERD-HRQL symptom severity questionnaire, and the SF-36 generic quality of life instrument. RESULTS: A total of 32 patients underwent graft-reinforced repair, 33 underwent primary repair. More patients in the UBM group were being treated for recurrent PEH. Demographic data and postoperative complications were similar. There was no difference in recurrence rates, size of recurrence, postoperative symptomatic or quality of life improvement. Patients who suffered recurrence in the primary repair group had more severe symptoms and a higher rate of dissatisfaction. Of the 3 patients with recurrences after Gentrix placement, reoperation demonstrated anterior failure where no reinforcement had occurred because of the posteriorly placed U-shaped graft. CONCLUSIONS: The use of UBM was not associated with an increased complications despite use in more difficult patients. Although there appeared to be no difference in recurrence rate or size, it was associated with less severe symptomatic recurrences. The U-shape configuration is prone to recurrence at the site of the repair not covered by the graft, suggesting that a keyhole configuration may be superior.

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. Oxygenated hydrocarbons (OxHC) produced by weathering processes dominate the majority of oil residues. These OxHC have continued recalcitrance in the environment, and increase in relative abundance over time. Analyses of the bulk characteristics of oil residues via TLC-FID and FT-IR should be continued as these techniques provide important insight into the weathering state of oil residues.

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. Broadly stated, open ended queries probed perceptions about the ideal or suboptimal candidates for transplant, perceived barriers to transplant, views regarding providing information to patients, and strategies that could improve transplant rates. At the sessions, all audio was recorded and professionally transcribed. Responses were pooled, de-identified, and analyzed using qualitative thematic content analysis. RESULTS: In considering candidacy, urban participants mentioned "age, " "compliance, " and "functional status "; "support " was a more-prevalent theme among rural nephrologists. Urban physicians discussed the expected effect of a transplant on a subject 's quality of life. As barriers to transplant, "evaluation time " was mentioned by urban groups only, and "distance to transplant center " was suggested by rural nephrologists only. To improve transplant rates, urban nephrologists suggested strategies that would increase the donor pool. Rural nephrologists, on the other hand, suggested a collaboration between nephrologists and the transplant center, "limiting listing eligibility " and "financial assistance. " Rural nephrologists suggested providing comparisons of modalities and information about selecting subjects. CONCLUSIONS: This qualitative study underscores geographic differences in perceptions of nephrologists regarding patient candidacy for kidney transplant, perceived barriers to kidney transplant, and proposed strategies to increase rates of kidney transplant. These differences are potential contributors to geographic variations in referring patients for kidney transplant.