ExPRSweb: An online repository with polygenic risk scores for common health-related exposures.

Complex traits are influenced by genetic risk factors, lifestyle, and environmental variables, so-called exposures. Some exposures, e.g., smoking or lipid levels, have common genetic modifiers identified in genome-wide association studies. Because measurements are often unfeasible, exposure polygenic risk scores (ExPRSs) offer an alternative to study the influence of exposures on various phenotypes. Here, we collected publicly available summary statistics for 28 exposures and applied four common PRS methods to generate ExPRSs in two large biobanks: the Michigan Genomics Initiative and the UK Biobank. We established ExPRSs for 27 exposures and demonstrated their applicability in phenome-wide association studies and as predictors for common chronic conditions. Especially the addition of multiple ExPRSs showed, for several chronic conditions, an improvement compared to prediction models that only included traditional, disease-focused PRSs. To facilitate follow-up studies, we share all ExPRS constructs and generated results via an online repository called ExPRSweb.

Major Genetic Risk Factors for Dupuytren's Disease Are Inherited From Neandertals.

Dupuytren's disease is characterized by fingers becoming permanently bent in a flexed position. Whereas people of African ancestry are rarely afflicted by Dupuytren's disease, up to ∼30% of men over 60 years suffer from this condition in northern Europe. Here, we meta-analyze 3 biobanks comprising 7,871 cases and 645,880 controls and find 61 genome-wide significant variants associated with Dupuytren's disease. We show that 3 of the 61 loci harbor alleles of Neandertal origin, including the second and third most strongly associated ones (P = 6.4 × 10-132 and P = 9.2 × 10-69, respectively). For the most strongly associated Neandertal variant, we identify EPDR1 as the causal gene. Dupuytren's disease is an example of how admixture with Neandertals has shaped regional differences in disease prevalence.

Changing diagnostic criteria for gestational diabetes (CDC4G) in Sweden: A stepped wedge cluster randomised trial.

BACKGROUND: The World Health Organisation (WHO) 2013 diagnostic criteria for gestational diabetes mellitus (GDM) has been criticised due to the limited evidence of benefits on pregnancy outcomes in different populations when switching from previously higher glycemic thresholds to the lower WHO-2013 diagnostic criteria. The aim of this study was to determine whether the switch from previous Swedish (SWE-GDM) to the WHO-2013 GDM criteria in Sweden following risk factor-based screening improves pregnancy outcomes. METHODS AND FINDINGS: A stepped wedge cluster randomised trial was performed between January 1 and December 31, 2018 in 11 clusters (17 delivery units) across Sweden, including all pregnancies under care and excluding preexisting diabetes, gastric bypass surgery, or multifetal pregnancies from the analysis. After implementation of uniform clinical and laboratory guidelines, a number of clusters were randomised to intervention (switch to WHO-2013 GDM criteria) each month from February to November 2018. The primary outcome was large for gestational age (LGA, defined as birth weight >90th percentile). Other secondary and prespecified outcomes included maternal and neonatal birth complications. Primary analysis was by modified intention to treat (mITT), excluding 3 clusters that were randomised before study start but were unable to implement the intervention. Prespecified subgroup analysis was undertaken among those discordant for the definition of GDM. Multilevel mixed regression models were used to compare outcome LGA between WHO-2013 and SWE-GDM groups adjusted for clusters, time periods, and potential confounders. Multiple imputation was used for missing potential confounding variables. In the mITT analysis, 47 080 pregnancies were included with 6 882 (14.6%) oral glucose tolerance tests (OGTTs) performed. The GDM prevalence increased from 595/22 797 (2.6%) to 1 591/24 283 (6.6%) after the intervention. In the mITT population, the switch was associated with no change in primary outcome LGA (2 790/24 209 (11.5%) versus 2 584/22 707 (11.4%)) producing an adjusted risk ratio (aRR) of 0.97 (95% confidence interval 0.91 to 1.02, p = 0.26). In the subgroup, the prevalence of LGA was 273/956 (28.8%) before and 278/1 239 (22.5%) after the switch, aRR 0.87 (95% CI 0.75 to 1.01, p = 0.076). No serious events were reported. Potential limitations of this trial are mainly due to the trial design, including failure to adhere to guidelines within and between the clusters and influences of unidentified temporal variations. CONCLUSIONS: In this study, implementing the WHO-2013 criteria in Sweden with risk factor-based screening did not significantly reduce LGA prevalence defined as birth weight >90th percentile, in the total population, or in the subgroup discordant for the definition of GDM. Future studies are needed to evaluate the effects of treating different glucose thresholds during pregnancy in different populations, with different screening strategies and clinical management guidelines, to optimise women's and children's health in the short and long term. TRIAL REGISTRATION: The trial is registered with ISRCTN (41918550).

Cancer PRSweb: An Online Repository with Polygenic Risk Scores for Major Cancer Traits and Their Evaluation in Two Independent Biobanks.

To facilitate scientific collaboration on polygenic risk scores (PRSs) research, we created an extensive PRS online repository for 35 common cancer traits integrating freely available genome-wide association studies (GWASs) summary statistics from three sources: published GWASs, the NHGRI-EBI GWAS Catalog, and UK Biobank-based GWASs. Our framework condenses these summary statistics into PRSs using various approaches such as linkage disequilibrium pruning/p value thresholding (fixed or data-adaptively optimized thresholds) and penalized, genome-wide effect size weighting. We evaluated the PRSs in two biobanks: the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort at Michigan Medicine, and the population-based UK Biobank (UKB). For each PRS construct, we provide measures on predictive performance and discrimination. Besides PRS evaluation, the Cancer-PRSweb platform features construct downloads and phenome-wide PRS association study results (PRS-PheWAS) for predictive PRSs. We expect this integrated platform to accelerate PRS-related cancer research.

The association of smoking, use of snuff, and preconception alcohol consumption with spontaneous abortion: A population-based cohort study.

INTRODUCTION: It is unclear whether tobacco in early pregnancy and alcohol use preceding pregnancy are associated with spontaneous abortion. The purpose was to investigate if use of tobacco and/or alcohol is associated with spontaneous abortion among women attending antenatal care, and if age and body mass index (BMI) attenuate the risk. MATERIAL AND METHODS: A population-based cohort study based on data from the Swedish Pregnancy Register. All pregnant women having had the first antenatal visit from January 2014 to July 2018 were included (n = 525 604). The register had information about smoking and use of snuff before and in early pregnancy, as well as data on alcohol habits before pregnancy, measured by the Alcohol Use Disorders Identification Test (AUDIT), a validated questionnaire. Logistic regression analysis was used to estimate the association between lifestyle factors and spontaneous abortion, and multiple imputation was used to impute missing data. RESULTS: In total, 34 867 (6.6%) pregnancies ended in a spontaneous abortion after the first visit to maternal health care. At the first maternal healthcare visit, daily smoking was reported by 24 214 (5.1%), and 6403 (1.2%) used snuff. For 19 837 (4.2%) women, a high alcohol score was reported for the year preceding pregnancy. After adjusting for potential confounders and multiple imputation, use of tobacco was associated with spontaneous abortion; smoking 1-9 cigarettes/day (adjusted odds ratio [aOR] 1.11, 95% confidence interval [CI] 1.04-1.18), smoking 10 or more cigarettes/day (aOR 1.12, 95% CI 1.-1.26), and use of snuff (aOR 1.20, 95% CI 1.06-1.37). Higher AUDIT scores were not significantly associated with spontaneous abortion (AUDIT 6-9: aOR 1.03, 95% CI 0.97-1.10 and AUDIT 10 or more: aOR 1.07, 95% CI 0.94-1.22). Increasing maternal age showed the highest risk of spontaneous abortion from the age of 35, and BMI of 30 kg/m2 or more increased the risk. There were interactions between different lifestyle factors associated with spontaneous abortion that could either increase or decrease the risk of spontaneous abortion. CONCLUSIONS: Smoking and use of snuff were associated with an increased risk of spontaneous abortion. The AUDIT scores preceding pregnancy were not associated with an increased risk of spontaneous abortion, which contradicts the results from previous studies.

Universal concept signature analysis: genome-wide quantification of new biological and pathological functions of genes and pathways.

Identifying new gene functions and pathways underlying diseases and biological processes are major challenges in genomics research. Particularly, most methods for interpreting the pathways characteristic of an experimental gene list defined by genomic data are limited by their dependence on assessing the overlapping genes or their interactome topology, which cannot account for the variety of functional relations. This is particularly problematic for pathway discovery from single-cell genomics with low gene coverage or interpreting complex pathway changes such as during change of cell states. Here, we exploited the comprehensive sets of molecular concepts that combine ontologies, pathways, interactions and domains to help inform the functional relations. We first developed a universal concept signature (uniConSig) analysis for genome-wide quantification of new gene functions underlying biological or pathological processes based on the signature molecular concepts computed from known functional gene lists. We then further developed a novel concept signature enrichment analysis (CSEA) for deep functional assessment of the pathways enriched in an experimental gene list. This method is grounded on the framework of shared concept signatures between gene sets at multiple functional levels, thus overcoming the limitations of the current methods. Through meta-analysis of transcriptomic data sets of cancer cell line models and single hematopoietic stem cells, we demonstrate the broad applications of CSEA on pathway discovery from gene expression and single-cell transcriptomic data sets for genetic perturbations and change of cell states, which complements the current modalities. The R modules for uniConSig analysis and CSEA are available through https://github.com/wangxlab/uniConSig.

Interleaflet Decoupling in a Lipid Bilayer at Excess Cholesterol Probed by Spectroscopic Ellipsometry and Simulations.

Artificial lipid membranes are often investigated as a replica of the cell membrane in the form of supported lipid bilayers (SLBs). In SLBs, the phase state of a lipid bilayer strongly depends on the presence of molecules such as cholesterol, ceramide, and physical parameters such as temperature. Cholesterol is a key molecule of biological membranes and it exerts condensing effect on lipid bilayers. In this paper, we demonstrate the influence of excess cholesterol content on a supported lipid bilayer of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) (fluid-phase) using spectroscopic ellipsometry (SE) and coarse-grained (CG) molecular dynamics (MD) simulations. The results show the condensation effect due to cholesterol addition up to 30% and interleaflet decoupling at excess cholesterol beyond 30%. SE results show the separation of individual leaflets of the bilayer and influence of cholesterol on the biophysical properties such as thickness and optical index. CG simulations were performed at different ratios of DOPC:cholesterol mixtures to explore cholesterol-driven bilayer properties and stability. The simulations displayed the accumulation of cholesterol molecules at the interface of the lower and upper leaflets of the bilayer, thus leading to undulations in the bilayer. This work reports the successful application of SE technique to study lipid-cholesterol interactions for the first time.

p.Arg69Trp in RNASEH2C is a founder variant in three Indian families with Aicardi-Goutières syndrome.

Aicardi-Goutières syndrome is an early-onset severe neurological disorder characterized by intracranial calcification, white matter abnormalities, hepatosplenomegaly, cerebrospinal fluid lymphocytosis, and elevated interferon-α levels, thus mimicking congenital viral infections. It is a genetically heterogeneous condition and autosomal recessive and autosomal dominant forms with variations in seven genes known till date. Variations in RNASEH2C cause an autosomal recessive form of AGS. Here we report three Indian families with variant, c.205C>T (NM_032193.3, p.Arg69Trp) in RNASEH2C gene identified by whole-exome sequencing and targeted molecular testing of the variant. Review of literature and our data suggest this is likely to be a founder variant in Asians and it would be a good initial variant to screen in patients with Aicardi-Goutières syndrome in Indians.

RNA-Enrich: a cut-off free functional enrichment testing method for RNA-seq with improved detection power.

UNLABELLED: Tests for differential gene expression with RNA-seq data have a tendency to identify certain types of transcripts as significant, e.g. longer and highly-expressed transcripts. This tendency has been shown to bias gene set enrichment (GSE) testing, which is used to find over- or under-represented biological functions in the data. Yet, there remains a surprising lack of tools for GSE testing specific for RNA-seq. We present a new GSE method for RNA-seq data, RNA-Enrich, that accounts for the above tendency empirically by adjusting for average read count per gene. RNA-Enrich is a quick, flexible method and web-based tool, with 16 available gene annotation databases. It does not require a P-value cut-off to define differential expression, and works well even with small sample-sized experiments. We show that adjusting for read counts per gene improves both the type I error rate and detection power of the test. AVAILABILITY AND IMPLEMENTATION: RNA-Enrich is available at http://lrpath.ncibi.org or from supplemental material as R code. CONTACT: sartorma@umich.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ConceptMetab: exploring relationships among metabolite sets to identify links among biomedical concepts.

MOTIVATION: Capabilities in the field of metabolomics have grown tremendously in recent years. Many existing resources contain the chemical properties and classifications of commonly identified metabolites. However, the annotation of small molecules (both endogenous and synthetic) to meaningful biological pathways and concepts still lags behind the analytical capabilities and the chemistry-based annotations. Furthermore, no tools are available to visually explore relationships and networks among functionally related groups of metabolites (biomedical concepts). Such a tool would provide the ability to establish testable hypotheses regarding links among metabolic pathways, cellular processes, phenotypes and diseases. RESULTS: Here we present ConceptMetab, an interactive web-based tool for mapping and exploring the relationships among 16 069 biologically defined metabolite sets developed from Gene Ontology, KEGG and Medical Subject Headings, using both KEGG and PubChem compound identifiers, and based on statistical tests for association. We demonstrate the utility of ConceptMetab with multiple scenarios, showing it can be used to identify known and potentially novel relationships among metabolic pathways, cellular processes, phenotypes and diseases, and provides an intuitive interface for linking compounds to their molecular functions and higher level biological effects. AVAILABILITY AND IMPLEMENTATION: http://conceptmetab.med.umich.edu CONTACTS: akarnovsky@umich.edu or sartorma@umich.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ChIP-Enrich: gene set enrichment testing for ChIP-seq data.

Gene set enrichment testing can enhance the biological interpretation of ChIP-seq data. Here, we develop a method, ChIP-Enrich, for this analysis which empirically adjusts for gene locus length (the length of the gene body and its surrounding non-coding sequence). Adjustment for gene locus length is necessary because it is often positively associated with the presence of one or more peaks and because many biologically defined gene sets have an excess of genes with longer or shorter gene locus lengths. Unlike alternative methods, ChIP-Enrich can account for the wide range of gene locus length-to-peak presence relationships (observed in ENCODE ChIP-seq data sets). We show that ChIP-Enrich has a well-calibrated type I error rate using permuted ENCODE ChIP-seq data sets; in contrast, two commonly used gene set enrichment methods, Fisher's exact test and the binomial test implemented in Genomic Regions Enrichment of Annotations Tool (GREAT), can have highly inflated type I error rates and biases in ranking. We identify DNA-binding proteins, including CTCF, JunD and glucocorticoid receptor α (GRα), that show different enrichment patterns for peaks closer to versus further from transcription start sites. We also identify known and potential new biological functions of GRα. ChIP-Enrich is available as a web interface (http://chip-enrich.med.umich.edu) and Bioconductor package.

Broad-Enrich: functional interpretation of large sets of broad genomic regions.

MOTIVATION: Functional enrichment testing facilitates the interpretation of Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) data in terms of pathways and other biological contexts. Previous methods developed and used to test for key gene sets affected in ChIP-seq experiments treat peaks as points, and are based on the number of peaks associated with a gene or a binary score for each gene. These approaches work well for transcription factors, but histone modifications often occur over broad domains, and across multiple genes. RESULTS: To incorporate the unique properties of broad domains into functional enrichment testing, we developed Broad-Enrich, a method that uses the proportion of each gene's locus covered by a peak. We show that our method has a well-calibrated false-positive rate, performing well with ChIP-seq data having broad domains compared with alternative approaches. We illustrate Broad-Enrich with 55 ENCODE ChIP-seq datasets using different methods to define gene loci. Broad-Enrich can also be applied to other datasets consisting of broad genomic domains such as copy number variations. AVAILABILITY AND IMPLEMENTATION: http://broad-enrich.med.umich.edu for Web version and R package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tumor Subtype Classification Tool for HPV-associated Head and Neck Cancers.

Importance: Molecular subtypes of HPV-associated Head and Neck Squamous Cell Carcinoma (HNSCC), named IMU (immune strong) and KRT (highly keratinized), are well-recognized and have been shown to have distinct mechanisms of carcinogenesis, clinical outcomes, and potentially differing optimal treatment strategies. Currently, no standardized method exists to subtype a new HPV+ HNSCC tumor. Our paper introduces a machine learning-based classifier and webtool to reliably subtype HPV+ HNSCC tumors using the IMU/KRT paradigm and highlights the importance of subtype in HPV+ HNSCC. Objective: To develop a robust, accurate machine learning-based classification tool that standardizes the process of subtyping HPV+ HNSCC, and to investigate the clinical, demographic, and molecular features associated with subtype in a meta-analysis of four patient cohorts. Data Sources: We conducted RNA-seq on 67 HNSCC FFPE blocks from University of Michigan hospital. Combining this with three publicly available datasets, we utilized a total of 229 HPV+ HNSCC RNA-seq samples. All participants were HPV+ according to RNA expression. An ensemble machine learning approach with five algorithms and three different input training gene sets were developed, with final subtype determined by majority vote. Several additional steps were taken to ensure rigor and reproducibility throughout. Study Selection: The classifier was trained and tested using 84 subtype-labeled HPV+ RNA-seq samples from two cohorts: University of Michigan (UM; n=18) and TCGA-HNC (n=66). The classifier robustness was validated with two independent cohorts: 83 samples from the HPV Virome Consortium and 62 additional samples from UM. We revealed 24 of 39 tested clinicodemographic and molecular variables significantly associated with subtype. Results: The classifier achieved 100% accuracy in the test set. Validation on two additional cohorts demonstrated successful separation by known features of the subtypes. Investigating the relationship between subtype and 39 molecular and clinicodemographic variables revealed IMU is associated with epithelial-mesenchymal transition (p=2.25×10-4), various immune cell types, and lower radiation resistance (p=0.0050), while KRT is more highly keratinized (p=2.53×10-8), and more likely female than IMU (p=0.0082). Conclusions and Relevance: This study provides a reliable classifier for subtyping HPV+ HNSCC tumors as either IMU or KRT based on bulk RNA-seq data, and additionally, improves our understanding of the HPV+ HNSCC subtypes.

CogniFiber: Harnessing Biocompatible and Biodegradable 1D Collagen Nanofibers for Sustainable Nonvolatile Memory and Synaptic Learning Applications.

Here, resistive switching (RS) devices are fabricated using naturally abundant, nontoxic, biocompatible, and biodegradable biomaterials. For this purpose, 1D chitosan nanofibers (NFs), collagen NFs, and chitosan-collagen NFs are synthesized by using an electrospinning technique. Among different NFs, the collagen-NFs-based device shows promising RS characteristics. In particular, the optimized Ag/collagen NFs/fluorine-doped tin oxide RS device shows a voltage-tunable analog memory behavior and good nonvolatile memory properties. Moreover, it can also mimic various biological synaptic learning properties and can be used for pattern classification applications with the help of the spiking neural network. The time series analysis technique is employed to model and predict the switching variations of the RS device. Moreover, the collagen NFs have shown good cytotoxicity and anticancer properties, suggesting excellent biocompatibility as a switching layer. The biocompatibility of collagen NFs is explored with the help of NRK-52E (Normal Rat Kidney cell line) and MCF-7 (Michigan Cancer Foundation-7 cancer cell line). Additionally, the biodegradability of the device is evaluated through a physical transient test. This work provides a vital step toward developing a biocompatible and biodegradable switching material for sustainable nonvolatile memory and neuromorphic computing applications.

PNPLA3 risk allele is associated with risk of hepatocellular carcinoma but not decompensation in compensated cirrhosis.

BACKGROUND: The PNPLA3-rs738409-G, TM6SF2-rs58542926-T, and HSD17B13-rs6834314-A polymorphisms have been associated with cirrhosis, hepatic decompensation, and HCC. However, whether they remain associated with HCC and decompensation in people who already have cirrhosis remains unclear, which limits the clinical utility of genetics in risk stratification as HCC is uncommon in the absence of cirrhosis. We aimed to characterize the effects of PNPLA3, TM6SF2, and HSD17B13 genotype on hepatic decompensation, HCC, and liver-related mortality or liver transplant in patients with baseline compensated cirrhosis. METHODS: We conducted a single-center retrospective study of patients in the Michigan Genomics Initiative who underwent genotyping. The primary predictors were PNPLA3, TM6SF2, and HSD17B13 genotypes. Primary outcomes were either hepatic decompensation, HCC, or liver-related mortality/transplant. We conducted competing risk Fine-Gray analyses on our cohort. RESULTS: We identified 732 patients with baseline compensated cirrhosis. During follow-up, 50% of patients developed decompensation, 13% developed HCC, 24% underwent liver transplant, and 27% died. PNPLA3-rs738409-G genotype was associated with risk of incident HCC: adjusted subhazard hazard ratio 2.42 (1.40-4.17), p=0.0015 for PNPLA3-rs738409-GG vs. PNPLA3-rs738409-CC genotype. The 5-year cumulative incidence of HCC was higher in PNPLA3-rs738409-GG carriers than PNPLA3-rs738409-CC/-CG carriers: 15.6% (9.0%-24.0%) vs. 7.4% (5.2%-10.0%), p<0.001. PNPLA3 genotype was not associated with decompensation or the combined outcome of liver-related mortality or liver transplant. TM6SF2 and HSD17B13 genotypes were not associated with decompensation or HCC. CONCLUSIONS: The PNPLA3-rs738409-G allele is associated with an increased risk of HCC among patients with baseline compensated cirrhosis. People with cirrhosis and PNPLA3-rs738409-GG genotype may warrant more intensive HCC surveillance.

Comparative Analysis of Dentition and Periodontal Status in Patients With Unilateral Smokeless Tobacco Pouch Keratosis.

INTRODUCTION: The consumption of smokeless tobacco (SLT) and related products has become an epidemic worldwide, especially among young people, as they come into direct contact with the tissues of the oral cavity. Therefore, the present cross-sectional study was conducted to compare the status of dentition and periodontal health of teeth associated with the unilateral SLT pouch keratosis with the unaffected contralateral side. MATERIALS AND METHODS: In this study, 96 SLT users from north Maharashtra, India, with unilateral SLT pouch keratosis were studied. Demographic data, past and present SLT use history, features of SLT pouch keratosis, modified community periodontal index, dentition status index, and loss of tooth attachment were recorded. Data were collected and subjected to statistical analysis using the unpaired t-test and chi-square test. RESULTS: The results of the present study showed a significant difference (p≤0.05) in gingival bleeding, pocket depth, and attachment loss in teeth associated with smokeless tobacco keratosis (STK) compared to teeth at the contralateral sides of the arch. The duration of tobacco use had a significant effect on the severity of loss of attachment at SLT pouch keratosis sides. There was a significant difference (p≤0.05) in the mean scores of the sound crown, carious crown, and coronal caries status between the SLT pouch keratosis side and the contralateral side. CONCLUSION: The results of the study revealed that significant gingival bleeding, gingival recession, and attachment loss in the teeth are associated with SLT pouch keratosis compared with the teeth on the contralateral side without the lesion.

Limosilactobacillus reuteri DSM 17938 supplementation and SARS-CoV-2 specific antibody response in healthy adults: a randomized, triple-blinded, placebo-controlled trial.

Studies have shown that probiotics can decrease the symptoms of respiratory tract infections as well as increase antibody responses following certain vaccinations. We examined the effect of probiotic supplementation on anti-SARS-CoV-2 specific antibody responses upon SARS-CoV-2 infection as well as after COVID-19 vaccination. In this randomized, triple-blinded, placebo-controlled intervention study with a parallel design, 159 healthy adults without prior SARS-CoV-2 infection or COVID-19 vaccination and any known risk factors for severe COVID-19 were randomly allocated into two study arms. The active treatment arm consumed a probiotic product containing a minimum of 1 × 108 colony-forming units of Limosilactobacillus reuteri DSM 17938 + 10 µg vitamin D3 twice daily for 6 months. The placebo arm consumed identical tablets containing only 10 µg vitamin D3. Anti-SARS-CoV-2 specific antibodies and virus neutralizing antibody titers were analyzed from blood samples collected at baseline, after 3 months, and after 6 months. Differences in serum antibody titers between the two study arms were tested with independent t-test using log-transformed values. In the intention-to-treat (ITT) analysis, SARS-CoV-2 infected individuals in the active treatment arm (n = 6) tended to have higher serum anti-spike IgG (609 [168-1480] BAU/ml vs 111 [36.1-1210] BAU/ml, p = 0.080) and anti-receptor binding domain (RBD) IgG (928 [212-3449] BAU/ml vs (83.7 [22.8-2094] BAU/ml, p = 0.066) levels than individuals in the placebo arm (n = 6). Considering individuals who were fully vaccinated with mRNA-based COVID-19 vaccines, the active treatment arm (n = 10) exhibited significantly higher serum levels of anti-RBD IgA (135 [32.9-976] BAU/ml vs 61.3 [26.7-97.1] BAU/ml, p = 0.036) than the placebo arm (n = 7) >28 days postvaccination. Supplementation with specific probiotics might improve the long-term efficacy of mRNA-based COVID-19 vaccines via enhanced IgA response.

Review of Electrochemically Synthesized Resistive Switching Devices: Memory Storage, Neuromorphic Computing, and Sensing Applications.

Resistive-switching-based memory devices meet most of the requirements for use in next-generation information and communication technology applications, including standalone memory devices, neuromorphic hardware, and embedded sensing devices with on-chip storage, due to their low cost, excellent memory retention, compatibility with 3D integration, in-memory computing capabilities, and ease of fabrication. Electrochemical synthesis is the most widespread technique for the fabrication of state-of-the-art memory devices. The present review article summarizes the electrochemical approaches that have been proposed for the fabrication of switching, memristor, and memristive devices for memory storage, neuromorphic computing, and sensing applications, highlighting their various advantages and performance metrics. We also present the challenges and future research directions for this field in the concluding section.

Recent progress in energy, environment, and electronic applications of MXene nanomaterials.

Since the discovery of graphene, two-dimensional (2D) materials have gained widespread attention, owing to their appealing properties for various technological applications. Etched from their parent MAX phases, MXene is a newly emerged 2D material that was first reported in 2011. Since then, a lot of theoretical and experimental work has been done on more than 30 MXene structures for various applications. Given this, in the present review, we have tried to cover the multidisciplinary aspects of MXene including its structures, synthesis methods, and electronic, mechanical, optoelectronic, and magnetic properties. From an application point of view, we explore MXene-based supercapacitors, gas sensors, strain sensors, biosensors, electromagnetic interference shielding, microwave absorption, memristors, and artificial synaptic devices. Also, the impact of MXene-based materials on the characteristics of respective applications is systematically explored. This review provides the current status of MXene nanomaterials for various applications and possible future developments in this field.

The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients.

Biobanks of linked clinical patient histories and biological samples are an efficient strategy to generate large cohorts for modern genetics research. Biobank recruitment varies by factors such as geographic catchment and sampling strategy, which affect biobank demographics and research utility. Here, we describe the Michigan Genomics Initiative (MGI), a single-health-system biobank currently consisting of >91,000 participants recruited primarily during surgical encounters at Michigan Medicine. The surgical enrollment results in a biobank enriched for many diseases and ideally suited for a disease genetics cohort. Compared with the much larger population-based UK Biobank, MGI has higher prevalence for nearly all diagnosis-code-based phenotypes and larger absolute case counts for many phenotypes. Genome-wide association study (GWAS) results replicate known findings, thereby validating the genetic and clinical data. Our results illustrate that opportunistic biobank sampling within single health systems provides a unique and complementary resource for exploring the genetics of complex diseases.