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Per- and polyfluoroalkyl substances (PFASs) are a family of "forever chemicals" including perfluorooctane sulfonate (PFOS). These toxic chemicals do not break down in the environment or in our bodies. In the human body, PFOS and perfluoroctanoic acid (PFOA) have a half-life (T1/2) of about 4–5 yr so low daily consumption of these chemicals can accumulate in the human body to a harmful level over a long period. Although the use of PFOS in consumer products was banned in the United States in 2022/2023, this forever chemical remains detectable in our tap water and food products. Every American tested has a high level of PFAS in their blood (https://cleanwater.org/pfas-forever-chemicals). In this report, we used a Sertoli cell blood-testis barrier (BTB) model with primary Sertoli cells cultured in vitro with an established functional tight junction (TJ)-permeability barrier that mimicked the BTB in vivo. Treatment of Sertoli cells with PFOS was found to perturb the TJ-barrier, which was the result of cytoskeletal disruption across the cell cytoplasm, disrupting actin and microtubule polymerization. These changes thus affected the proper localization of BTB-associated proteins at the BTB. Using RNA-Seq transcriptome profiling, bioinformatics analysis, and pertinent biochemical and cell biology techniques, it was discovered that PFOS -induced Sertoli cell toxicity through the c-Jun N-terminal kinase (JNK; also known as stress-activated protein kinase, SAPK) and its phosphorylated/active form p-JNK signaling pathway. More importantly, KB-R7943 mesylate (KB), a JNK/p-JNK activator, was capable of blocking PFOS-induced Sertoli cell injury, supporting the notion that PFOS-induced cell injury can possibly be therapeutically managed. NEW & NOTEWORTHY: PFOS induces Sertoli cell injury, including disruption of the 1) blood-testis barrier function and 2) cytoskeletal organization, which, in turn, impedes male reproductive function. These changes are mediated by JNK/p-JNK signaling pathway. However, the use of KB-R7943, a JNK/p-JNK activator was capable of blocking PFOS-induced Sertoli cell injury, supporting the possibility of therapeutically managing PFOS-induced reproductive dysfunction. [ABSTRACT FROM AUTHOR]

Objective: Somatic variants in UBA1 cause VEXAS, a recently described, systemic autoinflammatory disease. Research on VEXAS has largely focused on highly symptomatic patients. We sought to determine the prevalence of canonical, VEXAS‐associated somatic variants and their disease penetrance in a diverse, unselected population. Methods: We analyzed clinical‐grade whole genome sequencing data from 245,368 participants in the All of Us Research Program. We compared persons carrying a canonical VEXAS‐associated somatic variant to age, sex, and ancestry matched controls across the domains of diagnoses, medications, and laboratory values. Results: 74 participants were identified who carry one VEXAS‐defining somatic variant, UBA1 c.121A>C, p.Met41Leu. The variant allele fraction ranged from 4.5% to 33%. No other canonical VEXAS‐associated variants were identified. Of the 74 carriers, 62 (84%) were women, 20 (27%) were African American, and 14 (19%) were American Admixed/Latino. There was no statistically significant association between case/control status and any VEXAS‐associated diagnosis code, medication prescription, or laboratory value. Conclusion: We report the largest cohort to date of persons with the VEXAS‐associated p.Met41Leu somatic variant. This cohort differed substantially from reported cohorts of patients with clinical VEXAS, having a higher proportion of persons who were young, female, and of diverse ancestry. Variant allele fractions were lower than reported in clinical VEXAS cohorts, and bioinformatic analysis detected no clinical manifestations of VEXAS. Thus, the UBA1 p.Met41Leu somatic variant displayed incomplete penetrance for VEXAS. Further study is needed to determine the natural history of VEXAS‐associated somatic variants in the predisease phase. [ABSTRACT FROM AUTHOR]

Long-term immunity against severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) requires the identification of T-cell epitopes affecting host immunogenicity. In this computational study, we explored the CD8+ epitope diversity estimated in 27 of the most common HLA-A and HLA-B alleles, representing most of the United States population. Analysis of 16 SARS-CoV-2 variants [B.1, Alpha (B.1.1.7), five Delta (AY.100, AY.25, AY.3, AY.3.1, AY.44), and nine Omicron (BA.1, BA.1.1, BA.2, BA.4, BA.5, BQ.1, BQ.1.1, XBB.1, XBB.1.5)] in analyzedMHC class I alleles revealed that SARS-CoV-2 CD8+ epitope conservation was estimated at 87.6%-96.5% in spike (S), 92.5%-99.6% in membrane (M), and 94.6%-99% in nucleocapsid (N). As the virus mutated, an increasing proportion of S epitopes experienced reduced predicted binding affinity: 70% of Omicron BQ.1-XBB.1.5 S epitopes experienced decreased predicted binding, as compared with ~3% and ~15% in the earlier strains Delta AY.100-AY.44 and Omicron BA.1-BA.5, respectively. Additionally, we identified several novel candidate HLA alleles thatmay be more susceptible to severe disease, notably HLA-A*32:01, HLA-A*26:01, and HLA-B*53:01, and relatively protected from disease, such as HLA-A*31:01, HLAB* 40:01, HLA-B*44:03, and HLA-B*57:01. Our findings support the hypothesis that viral genetic variation affecting CD8 T-cell epitope immunogenicity contributes to determining the clinical severity of acute COVID-19. Achieving long-term COVID-19 immunity will require an understanding of the relationship between T cells, SARS-CoV-2 variants, and host MHC class I genetics. This project is one of the first to explore the SARS-CoV-2 CD8+ epitope diversity that putatively impacts much of the United States population. [ABSTRACT FROM AUTHOR]

Introduction: The goal of this study is to explore the pharmacological potential of the amyloid-reducing vasodilator fasudil, a selective Ras homolog (Rho)- associated kinases (ROCK) inhibitor, in the P301S tau transgenic mouse model (Line PS19) of neurodegenerative tauopathy and Alzheimer's disease (AD). Methods: We used LC-MS/MS, ELISA and bioinformatic approaches to investigate the effect of treatment with fasudil on the brain proteomic profile in PS19 tau transgenic mice. We also explored the efficacy of fasudil in reducing tau phosphorylation, and the potential beneficial and/or toxic effects of its administration in mice. Results: Proteomic profiling of mice brains exposed to fasudil revealed the activation of the mitochondrial tricarboxylic acid (TCA) cycle and blood-brain barrier (BBB) gap junction metabolic pathways. We also observed a significant negative correlation between the brain levels of phosphorylated tau (pTau) at residue 396 and both fasudil and its metabolite hydroxyfasudil. Conclusions: Our results provide evidence on the activation of proteins and pathways related to mitochondria and BBB functions by fasudil treatment and support its further development and therapeutic potential for AD. [ABSTRACT FROM AUTHOR]

As environmental opportunistic pathogens, nontuberculous mycobacteria (NTM) can cause severe and difficult to treat pulmonary disease. In the United States, Hawai'i has the highest prevalence of infection. Rapid growing mycobacteria (RGM) such as Mycobacterium abscessus and M. porcinum and the slow growing mycobacteria (SGM) including M. intracellulare subspecies chimaera are common environmental NTM species and subspecies in Hawai'i. Although iron acquisition is an essential process of many microorganisms, iron acquisition via siderophores among the NTM is not well-characterized. In this study, we apply genomic and microbiological methodologies to better understand iron acquisition via siderophores for environmental and respiratory isolates of M. abscessus, M. porcinum, and M. intracellulare subspecies chimaera from Hawai'i. Siderophore synthesis and transport genes, including mycobactin (mbt), mmpL/S, and esx-3 were compared among 47 reference isolates, 29 respiratory isolates, and 23 environmental Hawai'i isolates. Among all reference isolates examined, respiratory isolates showed significantly more siderophore pertinent genes compared to environmental isolates. Among the Hawai'i isolates, RGM M. abscessus and M. porcinum had significantly less esx-3 and mbt genes compared to SGM M. chimaera when stratified by growth classification. However, no significant differences were observed between the species when grown on low iron culture agar or siderophore production by the chrome azurol S (CAS) assay in vitro. These results indicate the complex mechanisms involved in iron sequestration and siderophore activity among diverse NTM species. [ABSTRACT FROM AUTHOR]

Simple Summary: Prostate cancer remains the most frequent cause of cancer morbidity, the second most frequent cause of cancer mortality in men in the developed world and is an exemplar of a heterogeneous disease. Stemness phenotypes and lineage plasticity have been highlighted as key drivers of heterogeneity observed both across patients and within the same patient. However, markers that indicate the presence or absence of these events remain to be identified. Next-generation sequencing has proven to be a beneficial approach to distinguish predictive and prognostic biomarkers in various diseases, including prostate cancer. This review explores measurable metrics that can reliably reflect lineage plasticity at the genomic, transcriptomic, and epigenomic levels, as well as bioinformatic tools that can be used to identify measures of lineage-plasticity in prostate cancer, in order to inform preclinical and clinical research. Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients. [ABSTRACT FROM AUTHOR]

Introduction: Medication errors, adverse events, and nonadherence in organ transplant recipients are common and can lead to suboptimal outcomes. A medication safety dashboard was developed to identify issues in medication therapy. Research Questions: Can a multicenter bioinformatics dashboard accurately identify clinically relevant medication safety issues in US military Veteran transplant recipients? Design: The dashboard was tested through a 24-month, prospective, cluster-randomized controlled multicenter study. Pharmacists used the dashboard to identify and address potential medication safety issues, which was compared with usual care. Results: Across the 10 sites (5 control sites and 5 intervention sites), 2012 patients were enrolled (1197 intervention vs 831 control). The mean age was 65 (10) years, 95% male, and 27% Black. The dashboard produced 18 132 alerts at a rate of 0.61(0.32) alerts per patient-month, ranging from 0.44 to 0.72 across the 5 intervention sites. Lab-based issues were most common (83.4%), followed by nonadherence (9.4%) and transitions in care (6.4%); 56% of alerts were addressed, taking an average of 43 (29) days. Common responses to alerts included those already resolved by another provider (N = 4431, 44%), the alert not clinically relevant (N = 3131, 31%), scheduling of follow-up labs (N = 591, 6%), and providing medication reconciliation/education (N = 99, 1%). Inaccurate flags significantly decreased over the study by a mean of −0.6% per month (95% CI −0.1 to −1.0; P =.0265), starting at 13.4% and ending at 2.6%. Conclusion: This multicenter cluster-randomized controlled trial demonstrated that a medication safety dashboard was feasibly deployable across the VA healthcare system, creating valid alerts. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 variant XBB.1.5 is of concern as it has high transmissibility. XBB.1.5 currently accounts for upwards of 30% of new infections in the United States. One year after our group published the predicted structure of the Omicron (B.1.1.529) variant's receptor binding domain (RBD) and antibody binding affinity, we return to investigate the new mutations seen in XBB.1.5 which is a descendant of Omicron. Using in silico modeling approaches against newer neutralizing antibodies that are shown effective against B.1.1.529, we predict the immune consequences of XBB.1.5's mutations and show that there is no statistically significant difference in overall antibody evasion when comparing to the B.1.1.529 and other related variants (e.g., BJ.1 andBM.1.1.1). However, noticeable changes in antibody binding affinity were seen due to specific amino acid changes of interest in the newer variants. [ABSTRACT FROM AUTHOR]

The use of electronic health records has expanded in the past decades, with healthcare entities storing terabytes of patient health data. In this study, we investigated how these databases can be utilized to generate clinically relevant information. We used the Office of Addiction Services and Supports Client Data Systems data merged with the NYS Medicaid Data Warehouse to study the relationship of certain antidepressants on alcohol withdrawal (AW) rates in patients with alcohol dependence (AD). We found that in patients with AD, bupropion was associated with a significantly reduced rate of AW compared to selective serotonin reuptake inhibitors (SSRIs). This may be due to the ability of bupropion to inhibit dopaminergic reuptake. This retrospective study provides the advantage of being faster and less expensive than randomized controlled trials (RCTs).

Despite over 41 million registered potential volunteer stem cell donors worldwide, many patients in need of a transplant do not find an HLA-matched unrelated donor or cord blood units, with the respective odds differing significantly between various populations. In this study, we analysed data of 2205 unsuccessful real-life donor searches sent to the DKMS Registry to identify populations in which further donor recruitment would be associated with particularly large patient benefits. For that purpose, we estimated haplotype frequencies of 67 donor populations at various sample sizes and entered them into two different mathematical models. These models assessed patient benefits from population-specific donor recruitment, operationalised by the number of originally unsuccessful searches that may become successful due to new donors. Consistently, across the different mathematical models and sample sizes, we obtained several countries from East and Southeast Asia (Thailand, Vietnam, China, and the Philippines) and the population of Asians in the USA as countries/populations where donor recruitment activities would be particularly beneficial for patients. We also identified various countries in Southeast and Central Europe as possible target regions for donor recruitment with above-average patient benefits. The results presented are registry-specific in the sense that they were obtained by optimising unsuccessful searches that had been sent to the DKMS Registry. Therefore, it would be desirable to apply the presented methods to a global data set that includes all unsuccessful stem cell donor searches worldwide and uses population-specific haplotype frequencies based on all donors available in the WMDA Search & Match Service., (© 2024 The Author(s). HLA: Immune Response Genetics published by John Wiley & Sons Ltd.)

SARS-CoV-2 is a newly discovered beta coronavirus at the end of 2019, which is highly pathogenic and poses a serious threat to human health. In this paper, 1875 SARS-CoV-2 whole genome sequences and the sequence coding spike protein (S gene) sampled from the United States were used for bioinformatics analysis to study the molecular evolutionary characteristics of its genome and spike protein. The MCMC method was used to calculate the evolution rate of the whole genome sequence and the nucleotide mutation rate of the S gene. The results showed that the nucleotide mutation rate of the whole genome was 6.677 × 10-4 substitution per site per year, and the nucleotide mutation rate of the S gene was 8.066 × 10-4 substitution per site per year, which was at a medium level compared with other RNA viruses. Our findings confirmed the scientific hypothesis that the rate of evolution of the virus gradually decreases over time. We also found 13 statistically significant positive selection sites in the SARS-CoV-2 genome. In addition, the results showed that there were 101 nonsynonymous mutation sites in the amino acid sequence of S protein, including seven putative harmful mutation sites. This paper has preliminarily clarified the evolutionary characteristics of SARS-CoV-2 in the United States, providing a scientific basis for future surveillance and prevention of virus variants. [ABSTRACT FROM AUTHOR]

Bacterial leaf spot disease caused by Xanthomonas cucurbitae has severely affected the pumpkin industries in the Midwestern region of United States, with the bacteria mainly infecting pumpkin leaves and fruits, and leading to significant yield losses. In this study, we utilized genomics and genetics approaches to elucidate X. cucurbitae molecular mechanisms of pathogenesis during interaction with its host. We generated the first reference-quality whole-genome sequence of the X. cucurbitae type isolate and compared with other Xanthomonas species, X. cucurbitae has a smaller genome size with fewer virulencerelated genes. RNA-seq analysis of X. cucurbitae under plantmimicking media conditions showed altered transcriptional responses, with upregulation of virulence genes and downregulation of cellular homeostasis genes. Additionally, characterization of key virulence genes using gene deletion methods revealed that both type II enzymes and type III effectors are necessary for X. cucurbitae to cause infection in the pumpkin host. [ABSTRACT FROM AUTHOR]

The National Heart, Lung, and Blood Institute and the Cardiovascular Medical Research and Education Fund held a workshop on the application of pulmonary vascular disease omics data to the understanding, prevention, and treatment of pulmonary vascular disease. Experts in pulmonary vascular disease, omics, and data analytics met to identify knowledge gaps and formulate ideas for future research priorities in pulmonary vascular disease in line with National Heart, Lung, and Blood Institute Strategic Vision goals. The group identified opportunities to develop analytic approaches to multiomic datasets, to identify molecular pathways in pulmonary vascular disease pathobiology, and to link novel phenotypes to meaningful clinical outcomes. The committee suggested support for interdisciplinary research teams to develop and validate analytic methods, a national effort to coordinate biosamples and data, a consortium of preclinical investigators to expedite target evaluation and drug development, longitudinal assessment of molecular biomarkers in clinical trials, and a task force to develop a master clinical trials protocol for pulmonary vascular disease. [ABSTRACT FROM AUTHOR]

Background Group B Streptococcus (GBS) is a leading cause of neonatal sepsis and meningitis and an important cause of invasive infections in pregnant and nonpregnant adults. Vaccines targeting capsule polysaccharides and common proteins are under development. Methods Using whole genome sequencing, a validated bioinformatics pipeline, and targeted antimicrobial susceptibility testing, we characterized 6340 invasive GBS isolates recovered during 2015–2017 through population-based Active Bacterial Core surveillance (ABCs) in 8 states. Results Six serotypes accounted for 98.4% of isolates (21.8% Ia, 17.6% V, 17.1% II, 15.6% III, 14.5% Ib, 11.8% IV). Most (94.2%) isolates were in 11 clonal complexes (CCs) comprised of multilocus sequence types identical or closely related to sequence types 1, 8, 12, 17, 19, 22, 23, 28, 88, 452, and 459. Fifty-four isolates (0.87%) had point mutations within pbp2x associated with nonsusceptibility to 1 or more β-lactam antibiotics. Genes conferring resistance to macrolides and/or lincosamides were found in 56% of isolates; 85.2% of isolates had tetracycline resistance genes. Two isolates carrying vanG were vancomycin nonsusceptible (minimum inhibitory concentration = 2 µg/mL). Nearly all isolates possessed capsule genes, 1–2 of the 3 main pilus gene clusters, and 1 of 4 homologous alpha/Rib family determinants. Presence of the hvgA virulence gene was primarily restricted to serotype III/CC17 isolates (465 isolates), but 8 exceptions (7 IV/CC452 and 1 IV/CC17) were observed. Conclusions This first comprehensive, population-based quantitation of strain features in the United States suggests that current vaccine candidates should have good coverage. The β-lactams remain appropriate for first-line treatment and prophylaxis, but emergence of nonsusceptibility warrants ongoing monitoring. [ABSTRACT FROM AUTHOR]

Background Antibiotic resistance is often spread through bacterial populations via conjugative plasmids. However, plasmid transfer is not well recognized in clinical settings because of technical limitations, and health care–associated infections are usually caused by clonal transmission of a single pathogen. In 2015, multiple species of carbapenem-resistant Enterobacteriaceae (CRE), all producing a rare carbapenemase, were identified among patients in an intensive care unit. This observation suggested a large, previously unrecognized plasmid transmission chain and prompted our investigation. Methods Electronic medical record reviews, infection control observations, and environmental sampling completed the epidemiologic outbreak investigation. A laboratory analysis, conducted on patient and environmental isolates, included long-read whole-genome sequencing to fully elucidate plasmid DNA structures. Bioinformatics analyses were applied to infer plasmid transmission chains and results were subsequently confirmed using plasmid conjugation experiments. Results We identified 14 Verona integron-encoded metallo-ß-lactamase (VIM)-producing CRE in 12 patients, and 1 additional isolate was obtained from a patient room sink drain. Whole-genome sequencing identified the horizontal transfer of bla VIM-1 , a rare carbapenem resistance mechanism in the United States, via a promiscuous incompatibility group A/C2 plasmid that spread among 5 bacterial species isolated from patients and the environment. Conclusions This investigation represents the largest known outbreak of VIM-producing CRE in the United States to date, which comprises numerous bacterial species and strains. We present evidence of in-hospital plasmid transmission, as well as environmental contamination. Our findings demonstrate the potential for 2 types of hospital-acquired infection outbreaks: those due to clonal expansion and those due to the spread of conjugative plasmids encoding antibiotic resistance across species. [ABSTRACT FROM AUTHOR]

Background: The global coronavirus disease 2019 (COVID-19) outbreak has significantly impacted public health. Moreover, there has been an association between the incidence and severity of osteoarthritis (OA) and the onset of COVID-19. However, the optimal diagnosis and treatment strategies for patients with both diseases remain uncertain. Bioinformatics is a novel approach that may help find the common pathology between COVID-19 and OA., Methods: Differentially expressed genes (DEGs) were screened by R package "limma." Functional enrichment analyses were performed to find key biological functions. Protein-protein interaction (PPI) network was constructed by STRING database and then Cytoscape was used to select hub genes. External data sets and OA mouse model validated and identified the hub genes in both mRNA and protein levels. Related transcriptional factors (TF) and microRNAs (miRNAs) were predicted with miRTarBase and JASPR database. Candidate drugs were obtained from Drug Signatures database. The immune infiltration levels of COVID-19 and OA were evaluated by CIBERSORT and scRNA-seq., Results: A total of 74 common DEGs were identified between COVID-19 and OA. Receiver operating characteristic curves validated the effective diagnostic values (area under curve > 0.7) of four hub genes (matrix metalloproteinases 9, ATF3, CCL4, and RELA) in both the training and validation data sets of COVID-19 and OA. Quantitative polymerase chain reaction and Western Blot showed significantly higher hub gene expression in OA mice than in healthy controls. A total of 84 miRNAs and 28 TFs were identified to regulate the process of hub gene expression. The top 10 potential drugs were screened including "Simvastatin," "Hydrocortisone," and "Troglitazone" which have been proven by Food and Drug Administration. Correlated with hub gene expression, Macrophage M0 was highly expressed while Natural killer cells and Mast cells were low in both COVID-19 and OA., Conclusion: Four hub genes, disease-related miRNAs, TFs, drugs, and immune infiltration help to understand the pathogenesis and perform further studies, providing a potential therapy target for COVID-19 and OA., (© 2023 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.)

Background. Network pharmacology (NP) has become an increasingly important focus in the drug research field over the past decade. However, no study to date has mapped the current status of NP. Therefore, we performed a bibliometric study to evaluate the top 100 cited papers on NP. Methods. We searched the Web of Science Core Collection from its inception to February 25, 2019, using the terms "network pharmacology" and "systems pharmacology." Key data, including title, publication year, number of citations, authors, countries/regions, organizations, and journals, were retrieved and analyzed using Excel 2016 and VOSviewer 1.6.10. Results. The total number of citations for the 100 cited papers ranged from 21 to 1,238, published in 53 journals, from 2005 to 2017. The top three journals with the most publications on NP were Clinical Pharmacology & Therapeutics (n = 8, IF2017 = 6.544), Journal of Ethnopharmacology (n = 8, IF2017 = 3.115), and PLoS One (n = 7, IF2017 = 2.766). Most published articles were from the USA (n = 41) and China (n = 35). The most active author was Wang Yonghua from the Northwest A&F University, and of the 100 publications, 14 listing his name. The most frequently used substantive terms included "drug discovery," "traditional Chinese medicine (TCM)," "in-vitro," "cancer," and "cardiovascular disease." Conclusions. The USA and China made the greatest contribution to NP research. The current NP research mainly focused on NP methods (including experimental validation) and using them to explore the molecular mechanisms of TCM for some critical diseases such as cardiovascular diseases and cancers. Furthermore, we believe some guidelines should be developed to regulate NP studies. [ABSTRACT FROM AUTHOR]

Bioinformatics has become an indispensable part of life science over the past 2 decades. However, bioinformatics education is not well integrated at the undergraduate level, especially in liberal arts colleges and regional universities in the United States. One significant obstacle pointed out by the Network for Integrating Bioinformatics into Life Sciences Education is the lack of faculty in the bioinformatics area. Most current life science professors did not acquire bioinformatics analysis skills during their own training. Consequently, a great number of undergraduate and graduate students do not get the chance to learn bioinformatics or computational biology skills within a structured curriculum during their education. To address this gap, we developed a module-based, week-long short course to train small college and regional university professors with essential bioinformatics skills. The bioinformatics modules were built to be adapted by the professor-trainees afterward and used in their own classes. All the course materials can be accessed at . [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) has been categorized by the Centers for Disease Control and Prevention (CDC) as the 6th leading cause of death in the United States. AD is a significant health-care burden because of its increased occurrence (specifically in the elderly population), and the lack of effective treatments and preventive methods. With an increase in life expectancy, the CDC expects AD cases to rise to 15 million by 2060. Aging has been previously associated with susceptibility to AD, and there are ongoing efforts to effectively differentiate between normal and AD age-related brain degeneration and memory loss. AD targets neuronal function and can cause neuronal loss due to the buildup of amyloid-beta plaques and intracellular neurofibrillary tangles. Our study aims to identify temporal changes within gene expression profiles of healthy controls and AD subjects. We conducted a meta-analysis using publicly available microarray expression data from AD and healthy cohorts. For our meta-analysis, we selected datasets that reported donor age and gender, and used Affymetrix and Illumina microarray platforms (8 datasets, 2,088 samples). Raw microarray expression data were re-analyzed, and normalized across arrays. We then performed an analysis of variance, using a linear model that incorporated age, tissue type, sex, and disease state as effects, as well as study to account for batch effects, and included binary interactions between factors. Our results identified 3,735 statistically significant (Bonferroni adjusted p < 0.05) gene expression differences between AD and healthy controls, which we filtered for biological effect (10% two-tailed quantiles of mean differences between groups) to obtain 352 genes. Interesting pathways identified as enriched comprised of neurodegenerative diseases pathways (including AD), and also mitochondrial translation and dysfunction, synaptic vesicle cycle and GABAergic synapse, and gene ontology terms enrichment in neuronal system, transmission across chemical synapses and mitochondrial translation. Overall our approach allowed us to effectively combine multiple available microarray datasets and identify gene expression differences between AD and healthy individuals including full age and tissue type considerations. Our findings provide potential gene and pathway associations that can be targeted to improve AD diagnostics and potentially treatment or prevention. [ABSTRACT FROM AUTHOR]

The pathogenic fungus Sclerotinia sclerotiorum infects over 600 species of plant. It is present in numerous environments throughout the world and causes significant damage to many agricultural crops. Fragmentation and lack of gene flow between populations may lead to population sub-structure. Within discrete recombining populations, positive selection may lead to a ‘selective sweep’. This is characterised by an increase in frequency of a favourable allele leading to reduction in genotypic diversity in a localised genomic region due to the phenomenon of genetic hitchhiking. We aimed to assess whether isolates of S. sclerotiorum from around the world formed genotypic clusters associated with geographical origin and to determine whether signatures of population-specific positive selection could be detected. To do this, we sequenced the genomes of 25 isolates of S. sclerotiorum collected from four different continents–Australia, Africa (north and south), Europe and North America (Canada and the northen United States) and conducted SNP based analyses of population structure and selective sweeps. Among the 25 isolates, there was evidence for two major population clusters. One of these consisted of 11 isolates from Canada, the USA and France (population 1), and the other consisted of nine isolates from Australia and one from Morocco (population 2). The rest of the isolates were genotypic outliers. We found that there was evidence of outcrossing in these two populations based on linkage disequilibrium decay. However, only a single candidate selective sweep was observed, and it was present in population 2. This sweep was close to a Major Facilitator Superfamily transporter gene, and we speculate that this gene may have a role in nutrient uptake from the host. The low abundance of selective sweeps in the S. sclerotiorum genome contrasts the numerous examples in the genomes of other fungal pathogens. This may be a result of its slow rate of evolution and low effective recombination rate due to self-fertilisation and vegetative reproduction. [ABSTRACT FROM AUTHOR]

Herpes simplex virus 2 (HSV-2) is a large double-stranded DNA virus that causes genital sores when spread by sexual contact and is a principal cause of viral encephalitis in newborns and infants. Viral glycoproteins enable virion entry into and spread between cells, making glycoproteins a prime target for vaccine development. A truncated glycoprotein D2 (gD2) vaccine candidate, recently tested in the phase 3 Herpevac Trial for Women, did not prevent HSV-2 infection in initially seronegative women. Some women who became infected experienced multiple recurrences during the trial. The HSV US7, US8, and US9 genes encode glycoprotein I (gI), glycoprotein E (gE), and the US9 type II membrane protein, respectively. These proteins participate in viral spread across cell junctions and facilitate anterograde transport of virion components in neurons, prompting us to investigate whether sequence variants in these genes could be associated with frequent recurrence. The nucleotide sequences and dN/dS ratios of the US7-US9 region from viral isolates of individuals who experienced multiple recurrences were compared with those who had had a single episode of disease. No consistent polymorphism(s) distinguished the recurrent isolates. In frequently recurring isolates, the dN/dS ratio of US7 was low while greater variation (higher dN/dS ratio) occurred in US8, suggesting conserved function of the former during reactivation. Phylogenetic reconstruction of the US7-US9 region revealed eight strongly supported clusters within the 55 U.S. HSV-2 strains sampled, which were preserved in a second global phylogeny. Thus, although we have demonstrated evolutionary diversity in the US7-US9 complex, we found no molecular evidence of sequence variation in US7-US9 that distinguishes isolates from subjects with frequently recurrent episodes of disease. [ABSTRACT FROM AUTHOR]

Background: A large number of SCN5A variants have been reported to underlie Brugada syndrome (BrS). However, the evidence supporting individual variants is highly heterogeneous. Objective: We systematically re‐evaluated all SCN5A variants reported in BrS using the 2015 American college of medical genetics and genomics and the association for molecular pathology (ACMG‐AMP) guidelines. Methods: A PubMed/Embase search was performed to identify all reported SCN5A variants in BrS. Standardized bioinformatic re‐analysis (SIFT, PolyPhen, Mutation Taster, Mutation assessor, FATHMM, GERP, PhyloP, and SiPhy) and re‐evaluation of frequency in the gnomAD database were performed. Fourteen ACMG‐AMP rules were deemed applicable for SCN5A variant analysis. Results: Four hundred and eighty unique SCN5A variants were identified, the majority of which 425 (88%) were coding variants. One hundred and fifty‐six of 425 (37%) variants were classified as pathogenic/likely pathogenic. Two hundred and fifty‐eight (60%) were classified as variants of uncertain significance, while a further 11 (3%) were classified as benign/likely benign. When considering the subset of variants that were considered "null" variants separately, 95% fulfilled criteria for pathogenicity/likely pathogenicity. In contrast, only 17% of missense variants fulfilled criteria for pathogenicity/likely pathogenicity. Importantly, however, only 25% of missense variants had available functional data, which was a major score driver for pathogenic classification. Conclusion: Based on contemporary ACMG‐AMP guidelines, only a minority of SCN5A variants implicated in BrS fulfill the criteria for pathogenicity or likely pathogenicity. [ABSTRACT FROM AUTHOR]

High-throughput, "next-generation" sequencing methods are now being broadly applied across all fields of biomedical research, including respiratory disease, critical care, and sleep medicine. Although there are numerous review articles and best practice guidelines related to sequencing methods and data analysis, there are fewer resources summarizing issues related to study design and interpretation, especially as applied to common, complex, nonmalignant diseases. To address these gaps, a single-day workshop was held at the American Thoracic Society meeting in May 2017, led by the American Thoracic Society Section on Genetics and Genomics. The aim of this workshop was to review the design, analysis, interpretation, and functional follow-up of high-throughput sequencing studies in respiratory, critical care, and sleep medicine research. This workshop brought together experts in multiple fields, including genetic epidemiology, biobanking, bioinformatics, and research ethics, along with physician-scientists with expertise in a range of relevant diseases. The workshop focused on application of DNA and RNA sequencing research in common chronic diseases and did not cover sequencing studies in lung cancer, monogenic diseases (e.g., cystic fibrosis), or microbiome sequencing. Participants reviewed and discussed study design, data analysis and presentation, interpretation, functional follow-up, and reporting of results. This report summarizes the main conclusions of the workshop, specifically addressing the application of these methods in respiratory, critical care, and sleep medicine research. This workshop report may serve as a resource for our research community as well as for journal editors and reviewers of sequencing-based manuscript submissions in our research field. [ABSTRACT FROM AUTHOR]

The Sturgeon chub (Macrhybopsis gelida) is a cyprinid fish native to the Missouri and Mississippi River basins of the U.S. Suspected long-term declines in the size of its distribution have prompted a review of its conservation status by the U.S. Fish and Wildlife Service, a process which depends on reliable methods to delineate the distribution and status of extant populations. To facilitate monitoring of Sturgeon chub populations, we developed a quantitative PCR assay to detect Sturgeon chub DNA in environmental samples. The assay consistently detected Sturgeon chub DNA in concentrations as low as 2 copies per reaction, and did not amplify DNA from non-target fish species that are sympatric in the upper Missouri River basin. Field tests of this assay with environmental samples successfully detected Sturgeon chub from sites known to be occupied. This assay offers an extremely sensitive methodology that can be applied to determine the range of Sturgeon chub, regardless of variation in habitat characteristics. [ABSTRACT FROM AUTHOR]

Comparative genomics is the comparison of genetic information within and across organisms to understand the evolution, structure, and function of genes, proteins, and non-coding regions (Sivashankari and Shanmughavel, Bioinformation 1:376-8, 2007). Advances in sequencing technology and assembly algorithms have resulted in the ability to sequence large genomes and provided a wealth of data that are being used in comparative genomic analyses. Comparative analysis can be leveraged to systematically explore and evaluate the biological relationships and evolution between species, aid in understanding the structure and function of genes, and gain a better understanding of disease and potential drug targets. As our knowledge of genetics expands, comparative genomics can help identify emerging model organisms among a broader span of the tree of life, positively impacting human health. This impact includes, but is not limited to, zoonotic disease research, therapeutics development, microbiome research, xenotransplantation, oncology, and toxicology. Despite advancements in comparative genomics, new challenges have arisen around the quantity, quality assurance, annotation, and interoperability of genomic data and metadata. New tools and approaches are required to meet these challenges and fulfill the needs of researchers. This paper focuses on how the National Institutes of Health (NIH) Comparative Genomics Resource (CGR) can address both the opportunities for comparative genomics to further impact human health and confront an increasingly complex set of challenges facing researchers., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Contagious equine metritis is a disease of worldwide concern in equids. The United States is considered to be free of the disease although sporadic outbreaks have occurred over the last few decades that were thought to be associated with the importation of horses. The objective of this study was to create finished, reference quality genomes that characterize the diversity of Taylorella equigenitalis isolates introduced into the USA, and identify their differences. Five isolates of T. equigenitalis associated with introductions into the USA from unique sources were sequenced using both short and long read chemistries allowing for complete assembly and annotation. These sequences were compared to previously published genomes as well as the short read sequences of the 200 isolates in the National Veterinary Services Laboratories’ diagnostic repository to identify unique regions and genes, potential virulence factors, and characterize diversity. The 5 genomes varied in size by up to 100,000 base pairs, but averaged 1.68 megabases. The majority of that diversity in size can be explained by repeat regions and 4 main regions of difference, which ranged in size from 15,000 to 45,000 base pairs. The first region of difference contained mostly hypothetical proteins, the second contained the CRISPR, the third contained primarily hemagglutinin proteins, and the fourth contained primarily segments of a type IV secretion system. As expected and previously reported, little evidence of recombination was found within these genomes. Several additional areas of interest were also observed including a mechanism for streptomycin resistance and other virulence factors. A SNP distance comparison of the T. equigenitalis isolates and Mycobacterium tuberculosis complex (MTBC) showed that relatively, T. equigenitalis was a more diverse species than the entirety of MTBC. [ABSTRACT FROM AUTHOR]

Background: Quantitative estimation of the extent to which the immune system's protective effect against one herpes simplex virus type 2 (HSV-2) infection protects against infection with additional HSV-2 strains is important for understanding the potential for HSV-2 vaccine development. Using viral genotyping, we estimated the prevalence of HSV-2 dual-strain infection and identified risk factors.Methods and Findings: People with and without HIV infection participating in HSV-2 natural history studies (University of Washington Virology Research Clinic) and HIV prevention trials (HIV Prevention Trials Network 039 and Partners in Prevention HSV/HIV Transmission Study) in the US, Africa, and Peru with 2 genital specimens each containing ≥105 copies herpes simplex virus DNA/ml collected a median of 5 months apart (IQR: 2-11 months) were included. It is unlikely that 2 strains would be detected in the same sample simultaneously; therefore, 2 samples were required to detect dual-strain infection. We identified 85 HSV-2 SNPs that, in aggregate, could determine whether paired HSV-2 strains were the same or different with >90% probability. These SNPs were then used to create a customized high-throughput array-based genotyping assay. Participants were considered to be infected with more than 1 strain of HSV-2 if their samples differed by ≥5 SNPs between the paired samples, and dual-strain infection was confirmed using high-throughput sequencing (HTS). We genotyped pairs of genital specimens from 459 people; 213 (46%) were men, the median age was 34 years (IQR: 27-44), and 130 (28%) were HIV seropositive. Overall, 272 (59%) people were from the US, 59 (13%) were from Peru, and 128 (28%) were from 8 countries in Africa. Of the 459 people, 18 (3.9%) met the criteria for dual-strain infection. HTS and phylogenetic analysis of paired specimens confirmed shedding of 2 distinct HSV-2 strains collected at different times in 17 pairs, giving an estimated dual-strain infection prevalence of 3.7% (95% CI = 2.0%-5.4%). Paired samples with dual-strain infection differed by a median of 274 SNPs in the UL_US region (range 129-413). Matching our observed dual-strain infection frequency to simulated data of varying prevalences and allowing only 2 samples per person, we inferred the true prevalence of dual-strain infection to be 7%. In multivariable analysis, controlling for HIV status and continent of origin, people from Africa had a higher risk for dual-strain infection (risk ratio [RR] = 9.20, 95% CI = 2.05-41.32), as did people who were HIV seropositive (RR = 4.06, 95% CI = 1.42-11.56).Conclusions: HSV-2 dual-strain infection was detected in 3.7% of paired samples from individual participants, and was more frequent among people with HIV infection. Simulations suggest that the true prevalence of dual-strain infection is 7%. Our data indicate that naturally occurring immunity to HSV-2 may be protective against infection with a second strain. This study is limited by the inability to determine the timing of acquisition of the second strain. [ABSTRACT FROM AUTHOR]

Introduction: This pilot study was conducted to examine, for the first time, the ongoing systems biology research and development projects within the laboratories and centers of the U.S. Army Medical Research and Materiel Command (USAMRMC). The analysis has provided an understanding of the breadth of systems biology activities, resources, and collaborations across all USAMRMC subordinate laboratories.Methods: The Systems Biology Collaboration Center at USAMRMC issued a survey regarding systems biology research projects to the eight U.S.-based USAMRMC laboratories and centers in August 2016. This survey included a data call worksheet to gather self-identified project and programmatic information. The general topics focused on the investigators and their projects, on the project's research areas, on omics and other large data types being collected and stored, on the analytical or computational tools being used, and on identifying intramural (i.e., USAMRMC) and extramural collaborations.Results: Among seven of the eight laboratories, 62 unique systems biology studies were funded and active during the final quarter of fiscal year 2016. Of 29 preselected medical Research Task Areas, 20 were associated with these studies, some of which were applicable to two or more Research Task Areas. Overall, studies were categorized among six general types of objectives: biological mechanisms of disease, risk of/susceptibility to injury or disease, innate mechanisms of healing, diagnostic and prognostic biomarkers, and host/patient responses to vaccines, and therapeutic strategies including host responses to therapies. We identified eight types of omics studies and four types of study subjects. Studies were categorized on a scale of increasing complexity from single study subject/single omics technology studies (23/62) to studies integrating results across two study subject types and two or more omics technologies (13/62). Investigators at seven USAMRMC laboratories had collaborations with systems biology experts from 18 extramural organizations and three other USAMRMC laboratories. Collaborators from six USAMRMC laboratories and 58 extramural organizations were identified who provided additional research expertise to these systems biology studies.Conclusions: At the end of fiscal year 2016, USAMRMC laboratories self-reported 66 systems biology/computational biology studies (62 of which were unique) with 25 intramural and 81 extramural collaborators. Nearly two-thirds were led by or in collaboration with the U.S. Army Telemedicine and Advanced Technology Research Center/Department of Defense Biotechnology High-Performance Computing Software Applications Institute and U.S. Army Center for Environmental Health Research. The most common study objective addressed biological mechanisms of disease. The most common types of Research Task Areas addressed infectious diseases (viral and bacterial) and chemical agents (environmental toxicant exposures, and traditional and emerging chemical threats). More than 40% of the studies (27/62) involved collaborations between the reporting USAMRMC laboratory and one other organization. Nearly half of the studies (30/62) involved collaborations between the reporting USAMRMC laboratory and at least two other organizations. These survey results indicate that USAMRMC laboratories are compliant with data-centric policy and guidance documents whose goals are to prevent redundancy and promote collaborations by sharing data and leveraging capabilities. These results also serve as a foundation to make recommendations for future systems biology research efforts. [ABSTRACT FROM AUTHOR]

Environmental or social challenges can stimulate a cascade of coordinated physiological changes in stress response systems. Unfortunately, chronic activation of these adaptations under conditions such as low socioeconomic status (SES) can have negative consequences for long-term health. While there is substantial evidence tying low SES to increased disease risk and reduced life expectancy, the underlying biology remains poorly understood. Using pilot data on 120 older adults from the Health and Retirement Study (United States, 2002-2010), we examined the associations between SES and gene expression levels in adulthood, with particular focus on a gene expression program known as the conserved transcriptional response to adversity. We also used a bioinformatics-based approach to assess the activity of specific gene regulation pathways involved in inflammation, antiviral responses, and stress-related neuroendocrine signaling. We found that low SES was related to increased expression of conserved transcriptional response to adversity genes and distinct patterns of proinflammatory, antiviral, and stress signaling (e.g., sympathetic nervous system and hypothalamic-pituitary-adrenal axis) transcription factor activation. [ABSTRACT FROM AUTHOR]

Scientific inquiry and discovery are the fuel for education, research, technology, and health care in all the health professions: dentistry, medicine, nursing, pharmacy, and allied health sciences. The progression of discoveries from basic or fundamental to clinical research is followed by the progression from clinical to implementation and improved health outcomes and processes. Generally, implementation science is the scientific study of methods to promote the systematic uptake of research findings (e.g., basic, translational, behavioral, socioeconomic, and clinical) as well as other related evidence-based practices into standards of care, thereby improving the quality, effectiveness, and cost benefits of health care services. There is little doubt that science has and will continue to provide the essential fuel for innovations that lead to new and improved technologies for risk assessment, prevention, diagnosis, treatments and therapeutics, and implementation for addressing oral and craniofacial diseases and disorders. The history of the U.S. dental profession reviewed in this article gives testimony to the continued need for investments in scientific inquiry that accelerate progress in comprehensive health care for all people. This article was written as part of the project "Advancing Dental Education in the 21st Century." [ABSTRACT FROM AUTHOR]

New drugs are urgently needed to cure tuberculosis (TB) in a short period of time without causing any adverse effects since currently used drugs for the treatment of multi drug-resistant TB cause several adverse effects with poor success rate. Therefore, we aimed to prioritize known drugs towards repurposing for TB by employing bioinformatics approach in the present study. A total of 1554 FDA approved drugs were obtained from DrugBank. Serine/threonine-protein kinase, pknB (Rv0014c) of Mycobacterium tuberculosis (Mtb) was selected as the drug target since it involves in several vital functions of the Mtb. All of the 1554 drugs were subjected to molecular docking with pknB. Glide and AutoDock Vina were employed using rigid docking followed by induced fit docking protocol for prioritization of drugs. Out of 14 drugs prioritized, six are suggested as high-confident drugs towards repurposing for TB as they were consistently found within top 10 ranks of both methods, and strongly binding in the active site of the pknB. We also found atorvastatin as one of the high-confident drugs, which has already been demonstrated to be active against Mtb under in vitro conditions by other researchers. Therefore, we propose that the prioritized six high-confident drugs as potential candidates for repurposing for TB and suggest for further experimental studies. We also suggest that the bioinformatics procedure we have employed in this study could be effectively applied for prioritization of drugs for other diseases. [ABSTRACT FROM AUTHOR]

Senecavirus A (SVA), previously known as Seneca Valley virus, was first isolated in the United States in 2002. SVA was associated with porcine idiopathic vesicular disease in Canada and the USA in 2007 and 2012, respectively. Recent increase in SVA outbreaks resulting in neonatal mortality of piglets and/or vesicular lesions in sows in Brazil, the USA and Canada point to the necessity to study the pathogenicity and molecular epidemiology of the virus. Here, we report the analysis of the complete coding sequences of SVA from 2 clinical cases and 9 assembly yard environmental samples collected in 2015 in Canada, along with 22 previously released complete genomes in the GenBank. With this combined data set, the evolution of the SVA over a 12-month period in 2015/2016 was evaluated. These SVA isolates were characterized by a rapid accumulation of genetic variations driven mainly by a high nucleotide substitution rate and purifying selection. The SVA sequences clustered in clearly defined geographical areas with reported cases of SVA infection. No transmission links were identified between assembly yards, suggesting that point source introductions may have occurred. In addition, 25 fixed non-synonymous mutations were identified across all analyzed strains when compared to the prototype SVA strain (SVV-001). This study highlights the importance of monitoring SVA mutations for their role in increased virulence and impact on SVA diagnostics. [ABSTRACT FROM AUTHOR]

Legionella longbeachae is the primary cause of legionellosis in Australasia and Southeast Asia and an emerging pathogen in Europe and the United States; however, our understanding of the population diversity of L. longbeachae from patient and environmental sources is limited. We analyzed the genomes of 64 L. longbeachae isolates, of which 29 were from a cluster of legionellosis cases linked to commercial growing media in Scotland in 2013 and 35 were non-outbreak-associated isolates from Scotland and other countries. We identified extensive genetic diversity across the L. longbeachae species, associated with intraspecies and interspecies gene flow, and a wide geographic distribution of closely related genotypes. Of note, we observed a highly diverse pool of L. longbeachae genotypes within compost samples that precluded the genetic establishment of an infection source. These data represent a view of the genomic diversity of L. longbeachae that will inform strategies for investigating future outbreaks. [ABSTRACT FROM AUTHOR]

For the last 500 years, the Americas have been a melting pot both for genetically diverse humans and for the pathogenic and commensal organisms associated with them. One such organism is the stomach-dwelling bacterium Helicobacter pylori, which is highly prevalent in Latin America where it is a major current public health challenge because of its strong association with gastric cancer. By analyzing the genome sequence of H. pylori isolated in North, Central and South America, we found evidence for admixture between H. pylori of European and African origin throughout the Americas, without substantial input from pre-Columbian (hspAmerind) bacteria. In the US, strains of African and European origin have remained genetically distinct, while in Colombia and Nicaragua, bottlenecks and rampant genetic exchange amongst isolates have led to the formation of national gene pools. We found three outer membrane proteins with atypical levels of Asian ancestry in American strains, as well as alleles that were nearly fixed specifically in South American isolates, suggesting a role for the ethnic makeup of hosts in the colonization of incoming strains. Our results show that new H. pylori subpopulations can rapidly arise, spread and adapt during times of demographic flux, and suggest that differences in transmission ecology between high and low prevalence areas may substantially affect the composition of bacterial populations. [ABSTRACT FROM AUTHOR]

Biomarkers are measurements of biological variables that can determine a state of health. They consist of measuring a single variable or a combination of variables related to the state of health that these variables represent. Biomarkers can provide an early warning of a health problem in relation to an individual patient or group of patients, and thus trigger actions and lead to interventions. Nutritional biomarkers measure the biological consequences of one's diet. In our recent work, we have used machine learning to predict weight, metabolic syndrome and blood pressure, using blood-exam-based biomarkers. In the current work, we use extreme value theory to examine the significance of outliers in health data, with a focus on diet and the standard biochemistry profile. Specifically, we show that, using extreme value analysis and by applying a systemisation of the process, health trends can be predicted, and thus, health interventions can be (at least partially) automated. For that purpose, public access datasets have been used, which were retrieved from the National Health and Nutrition Examination Survey. The NHANES is a program of studies designed to assess the health and nutritional status of the population in the United States. In total, about 70,000 datapoints were analysed, covering about a decade's worth of observations. [ABSTRACT FROM AUTHOR]

BACKGROUNDDespite guidelines promoting the prevention and aggressive treatment of ventilator-associated pneumonia (VAP), the importance of VAP as a driver of outcomes in mechanically ventilated patients, including patients with severe COVID-19, remains unclear. We aimed to determine the contribution of unsuccessful treatment of VAP to mortality for patients with severe pneumonia.METHODSWe performed a single-center, prospective cohort study of 585 mechanically ventilated patients with severe pneumonia and respiratory failure, 190 of whom had COVID-19, who underwent at least 1 bronchoalveolar lavage. A panel of intensive care unit (ICU) physicians adjudicated the pneumonia episodes and endpoints on the basis of clinical and microbiological data. Given the relatively long ICU length of stay (LOS) among patients with COVID-19, we developed a machine-learning approach called CarpeDiem, which grouped similar ICU patient-days into clinical states based on electronic health record data.RESULTSCarpeDiem revealed that the long ICU LOS among patients with COVID-19 was attributable to long stays in clinical states characterized primarily by respiratory failure. While VAP was not associated with mortality overall, the mortality rate was higher for patients with 1 episode of unsuccessfully treated VAP compared with those with successfully treated VAP (76.4% versus 17.6%, P < 0.001). For all patients, including those with COVID-19, CarpeDiem demonstrated that unresolving VAP was associated with a transitions to clinical states associated with higher mortality.CONCLUSIONSUnsuccessful treatment of VAP is associated with higher mortality. The relatively long LOS for patients with COVID-19 was primarily due to prolonged respiratory failure, placing them at higher risk of VAP.FUNDINGNational Institute of Allergy and Infectious Diseases (NIAID), NIH grant U19AI135964; National Heart, Lung, and Blood Institute (NHLBI), NIH grants R01HL147575, R01HL149883, R01HL153122, R01HL153312, R01HL154686, R01HL158139, P01HL071643, and P01HL154998; National Heart, Lung, and Blood Institute (NHLBI), NIH training grants T32HL076139 and F32HL162377; National Institute on Aging (NIA), NIH grants K99AG068544, R21AG075423, and P01AG049665; National Library of Medicine (NLM), NIH grant R01LM013337; National Center for Advancing Translational Sciences (NCATS), NIH grant U01TR003528; Veterans Affairs grant I01CX001777; Chicago Biomedical Consortium grant; Northwestern University Dixon Translational Science Award; Simpson Querrey Lung Institute for Translational Science (SQLIFTS); Canning Thoracic Institute of Northwestern Medicine.

Background: Bibliometric analysis is an approach adopted by researchers to understand the various analytics such as year-wise publications, their citations, most impactful authors and their contributions, identification of emerging keywords, multiple themes (niche, motor, basic, and emerging or declining) etc. F1000Research is one of the Q1 category journals that publishes articles in various domains, but a detailed journal analysis is yet to be done. Methods: This study is an effort to extract the F1000Research journey information through bibliometric analysis using VOS-viewer and Biblioshiny (R-studio) interface. The F1000Research journal started its journey in 2012; since then, 5767 articles have been published until the end of 2022. Most of the published articles are from medical science, covering Biochemistry, Genetics & Molecular Biology, Immunology & Pharmacology, Toxicology & Pharmaceutics. To understand the research journey, various analyses such as publication & citation trends, leading authors, institutions, countries, most frequent keywords, bibliographic coupling between authors, countries and documents, emerging research themes, and trending keywords were performed. Results: The United States is the biggest contributor, and COVID-19 is the most commonly occurred keyword. Conclusions: The present study may help future researchers to understand the emerging medical science domain. It will also help the editors and journal to focus more on developing or emerging areas and to understand their importance towards society. Future researchers can contribute their quality research studies, focusing on emerging themes. These authors' research can guide future researchers to develop their research area around the most impacted articles. They can collaborate with them to bring that emerging theme forward., Competing Interests: No competing interests were disclosed., (Copyright: © 2023 Kumar D et al.)

Acute coronary syndrome (ACS) is a life-threatening disease that affects more than half a million people in United States. We currently lack molecular biomarkers to distinguish the unstable angina (UA) and acute myocardial infarction (AMI), which are the two subtypes of ACS. MicroRNAs play significant roles in biological processes and serve as good candidates for biomarkers. In this work, we collected microRNA datasets from the Gene Expression Omnibus database and identified specific microRNAs in different subtypes and universal microRNAs in all subtypes based on our novel network-based bioinformatics approach. These microRNAs were studied for ACS association by pathway enrichment analysis of their target genes. AMI and UA were associated with 27 and 26 microRNAs, respectively, nine of them were detected for both AMI and UA, and five from each subtype had been reported previously. The remaining 22 and 21 microRNAs are novel microRNA biomarkers for AMI and UA, respectively. The findings are then supported by pathway enrichment analysis of the targets of these microRNAs. These novel microRNAs deserve further validation and will be helpful for personalized ACS diagnosis. [ABSTRACT FROM AUTHOR]

BACKGROUND: Identifying cancer hazards is the first step towards cancer prevention. The International Agency for Research on Cancer (IARC) Monographs Programme, which has evaluated nearly 1,000 agents for their carcinogenic potential since 1971, typically selects agents for hazard identification on the basis of public nominations, expert advice, published data on carcinogenicity, and public health importance. OBJECTIVES: Here, we present a novel and complementary strategy for identifying agents for hazard evaluation using chemoinformatics, database integration, and automated text mining. DISCUSSION: To inform selection among a broad range of pesticides nominated for evaluation, we identified and screened nearly 6,000 relevant chemical structures, after which we systematically compiled information on 980 pesticides, creating network maps that allowed cluster visualization by chemical similarity, pesticide class, and publicly available information concerning cancer epidemiology, cancer bioassays, and carcinogenic mechanisms. For the IARC Monograph meetings that took place in March and June 2015, this approach supported high-priority evaluation of glyphosate, malathion, parathion, tetrachlorvinphos, diazinon, p,p-dichlorodiphenyltrichloroethane (DDT), lindane, and 2,4-dichlorophenoxyacetic acid (2,4-D). CONCLUSIONS: This systematic approach, accounting for chemical similarity and overlaying multiple data sources, can be used by risk assessors as well as by researchers to systematize, inform, and increase efficiency in selecting and prioritizing agents for hazard identification, risk assessment, regulation, or further investigation. This approach could be extended to an array of outcomes and agents, including occupational carcinogens, drugs, and foods. CITATION: Guha N, Guyton KZ, Loomis D, Barupal DK. 2016. Prioritizing chemicals for risk assessment using chemoinformatics: examples from the IARC Monographs on Pesticides. Environ Health Perspect 124:1823-1829; http://dx.doi.org/10.1289/EHP186 [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to test the utility of high-resolution metabolomics (HRM) for analysis of nutritional status and health indicators in military personnel. Methods: Serum samples from 400 military personnel were obtained from the Department of Defense Serum Repository (DoDSR) and analyzed for metabolites related to nutrition and health status. Metabolic profile organization was studied using modulated modularity clustering (MMC). Results: HRM provided quantitative measures of 61 metabolites across chemical classes for use as nutritional and clinical biomarkers. Levels were comparable to reported values except for arginine and glutamine. which were above and below reference ranges, respectively. MMC generated five clusters, three of which were associated and contained amino acids. The others contained lipids and mitochondria-related metabolites. Conclusions: HRM analysis of serum is suitable for real-time and/or retrospective evaluation of nutrition and health status of specific military cohorts. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to maximize detection of serum metabolites with high-resolution metabolomics (HRM). Methods: Department of Defense Serum Repository (DoDSR) samples were analyzed using ultrahigh resolution mass spectrometry with three complementary chromatographic phases and four ionization modes. Chemical coverage was evaluated by number of ions detected and accurate mass matches to a human metabolomics database. Results: Individual HRM platforms provided accurate mass matches for up to 58% of the KEGG metabolite database. Combining two analytical methods increased matches to 72% and included metabolites in most major human metabolic pathways and chemical classes. Detection and feature quality varied by analytical configuration. Conclusions: Dual chromatography HRM with positive and negative electrospray ionization provides an effective generalized method for metabolic assessment of military personnel. [ABSTRACT FROM AUTHOR]

This article summarizes the highlights of the expert technical consultation on bacterial vaginosis (BV), sponsored by the National Institute of Allergy and Infectious Disease and held in Washington, DC, on 8-9 April 2015. Many issues touched on in this article are discussed in much greater detail in the 6 preceding articles in this supplement to The Journal of Infectious Diseases There was a consensus among the meeting attendees concerning the most important research issues in the field: the pathogenesis of the syndrome, way to optimize treatment, and the relative roles of sexual transmission and endogenous infection in BV epidemiology. This article concludes with a listing of BV and genitourinary tract research priorities that were discussed and agreed on by attendees. The most important of these included better characterization of vaginal microbiome community state subtypes, application of advanced "-omic" technologies to improve understanding of BV pathogenesis, further investigation of the relationships between the male and female genitourinary tract microbiomes, and the development of new drugs for BV treatment. [ABSTRACT FROM AUTHOR]

BACKGROUND: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. OBJECTIVES: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. METHODS: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure--activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. RESULTS: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. CONCLUSION: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points. [ABSTRACT FROM AUTHOR]

Context.--Next-generation sequencing performed in a clinical environment must meet clinical standards, which requires reproducibility of all aspects of the testing. Clinical-grade genomic databases (CGGDs) are required to classify a variant and to assist in the professional interpretation of clinical next-generation sequencing. Applying quality laboratory standards to the reference databases used for sequence-variant interpretation presents a new challenge for validation and curation. Objectives.--To define CGGD and the categories of information contained in CGGDs and to frame recommendations for the structure and use of these databases in clinical patient care. Design.--Members of the College of American Pathologists Personalized Health Care Committee reviewed the literature and existing state of genomic databases and developed a framework for guiding CGGD development in the future. Results.--Clinical-grade genomic databases may provide different types of information. This work group defined 3 layers of information in CGGDs: clinical genomic variant repositories, genomic medical data repositories, and genomic medicine evidence databases. The layers are differentiated by the types of genomic and medical information contained and the utility in assisting with clinical interpretation of genomic variants. Clinical-grade genomic databases must meet specific standards regarding submission, curation, and retrieval of data, as well as the maintenance of privacy and security. Conclusion.--These organizing principles for CGGDs should serve as a foundation for future development of specific standards that support the use of such databases for patient care. [ABSTRACT FROM AUTHOR]