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Background: Early diagnosis and treatment of Crohn's Disease are associated with decreased risk of surgery and complications. However, diagnostic delay is frequently seen in clinical practice. To better understand Crohn's Disease risk factors and disease indicators, we identified, described, and predicted incident Crohn's Disease patients based on the Electronic Health Record data of the Mount Sinai Health System., Methods: We developed two phenotyping algorithms based on structured Electronic Health Record data (i.e., coded diagnosis, medication prescription, and healthcare utilization), and a more simple and advanced approach of information extraction from clinical notes, including data between 2011 and 2023. We conducted an ablation study for the classification task using different models, prediction time points, data inputs, text encoding methods, and case-control matching variables., Results: We identified 247 incident Crohn's Disease cases and 1221 matched controls and validated our cohorts through manual chart review. A second control cohort (n = 1235) was created without matching on race. Gastrointestinal symptoms were significantly overrepresented in cases at least 180 days before the first coded Crohn's Disease diagnosis. Adding text-based features to the clinical prediction models increased their overall performances. However, adding race as a matching variable had more effects on the model performance than the choice of modeling algorithm or input data, with an area under the receiver operating characteristic difference of 0.09 between the best-performing models., Conclusion: We demonstrate the feasibility of identifying newly diagnosed Crohn's Disease patients within a United States health system using Electronic Health Records. For the predictive modeling task, cases and controls were distinguished only with modest performance, even though various state-of-the-art methods were applied based on features from structured and unstructured data. Our findings suggest the benefit of adding information from clinical notes in a supervised or unsupervised manner for cohort creation and predictive modeling., Competing Interests: Declaration of competing interest RCU has served as a consultant and/or advisory board member for AbbVie, Bristol Myers Squibb, Celltrion, Inotrem, Lilly, Janssen, Pfizer, Roivant, Takeda. BYR has served as a consultant and/or holds intellectual property rights commercialized by Seqstant, Biontech, Genentech (Roche). The remaining authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The growing threat of viral infections requires innovative therapeutic approaches to safeguard human health. Nanomaterials emerge as a promising solution to overcome the limitations associated with conventional therapies. The eco-friendly synthesis of silver nanoparticles (AgNPs) currently represents a method that guarantees antimicrobial efficacy, safety, and cost-effectiveness. This study explores the use of AgNPs derived from the peel (Lp-AgNPs) and juice (Lj-AgNPs) Citrus limon "Ovale di Sorrento", cultivars of the Campania region. The antiviral potential was tested against viruses belonging to the Coronaviridae and Herpesviridae. AgNPs were synthesized by reduction method using silver nitrate solution mixed with aqueous extract of C. limon peel and juice. The formation of Lp-AgNPs and Lj-AgNPs was assessed using a UV-Vis spectrophotometer. The size, ζ-potential, concentration, and morphology of AgNPs were evaluated by dynamic light scattering (DLS), nanoparticle tracking analysis (NTA), and field emission-scanning electron microscopy (FE-SEM). Cytotoxicity was evaluated in a concentration range between 500 and 7.8 µg/mL on VERO-76 and HaCaT cells, with the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium test bromide (MTT). Antiviral activity consisted of virus pre-treatment, co-treatment, cellular pre-treatment, and post-infection tests versus HSV-1 and SARS-CoV-2 at a multiplicity of infections (MOI) of 0.01. Plaque reduction assays and real-time PCR provided data on the antiviral potential of tested compounds. Lp-AgNPs and Lj-AgNPs exhibited spherical morphology with respective diameters of 60 and 92 nm with concentrations of 4.22 and 4.84 × 10 10 particles/mL, respectively. The MTT data demonstrated minimal cytotoxicity, with 50 % cytotoxic concentrations (CC 50 ) of Lp-AgNPs and Lj-AgNPs against VERO cells of 754.6 and 486.7 µg/mL. Similarly, CC 50 values against HaCaT were 457.3 µg/mL for Lp-AgNPs and 339.6 µg/mL for Lj-AgNPs, respectively. In the virus pre-treatment assay, 90 % inhibitory concentrations of HSV-1 and SARS-CoV-2 were 8.54-135.04 µg/mL for Lp-AgNPs and 6.13-186.77 µg/mL for Lj-AgNPs, respectively. The molecular investigation confirmed the antiviral data, recording a reduction in the UL54 and UL27 genes for HSV-1 and in the Spike (S) gene for SARS-CoV-2, following AgNP exposure. The results of this study suggest that Lp-AgNPs and Lj-AgNPs derived from C. Limon could offer a valid ecological, natural, local and safe strategy against viral infections., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

The use of plastics in the manufacturing of food products is of concern as microplastics (MPs, 1 µm to 5 mm) find their way into food which poses risks to human health. This study is the first to report detection of MPs in selected staple food products in the Philippines, specifically sea salt, white and brown sugar, fish sauce, and rice. Raman microspectroscopy was used to identify the MPs and pigment additives. The mean MP concentration was 471 MPs kg -1 with 71% identified as polyvinyl chloride (PVC) for salt, 20 MPs kg -1 with 67% polyethylene terephthalate (PET) for white sugar, 67 MPs kg -1 with 77% polypropylene (PP) for brown sugar, 3 MPs L -1 for fish sauce, and 5 MPs kg -1 with 100% PET for cooked rice. For sea salt, the highest MP contamination found was PVC that is likely from the processing of this product. This implies the need for careful use of PVC materials in their manufacture. For sugar, rice, and fish sauce, the likely contamination is from plastic packaging. The present findings provide estimation of human consumption of MPs from food items and insights on the use of plastic materials in the manufacturing processes., Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-024-05978-2., Competing Interests: Conflict of interestThe authors declare that they have no competing interests that could have influenced the work reported in this paper., (© Association of Food Scientists & Technologists (India) 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Competing Interests: Declaration of Conflicting InterestsThe authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr. Balkhy is a proctor for Intuitive Surgical. All other authors have nothing to disclose.

Coral reefs are biodiverse ecosystems that rely on trophodynamic transfers from primary producers to consumers through the detrital pathway. The sponge loop hypothesis proposes that sponges consume dissolved organic carbon (DOC) and produce large quantities of detritus on coral reefs, with this turn-over approaching the daily gross primary production of the reef ecosystem. In this study, we collected samples of detritus in the epilithic algal matrix (EAM) and samples from potential sources of detritus over two seasons from the forereef at Carrie Bow Cay, Belize. We chose this location to maximize the likelihood of finding support for the sponge loop hypothesis because Caribbean reefs have higher sponge abundances than other tropical reefs worldwide and the Mesoamerican barrier reef is an archetypal coral reef ecosystem. We used stable isotope analyses and eDNA metabarcoding to determine the composition of the detritus. We determined that the EAM detritus was derived from a variety of benthic and pelagic sources, with primary producers (micro- and macroalgae) as major contributors and metazoans (Arthropoda, Porifera, Cnidaria, Mollusca) as minor contributors. None of the sponge species that reportedly produce detritus were present in EAM detritus. The cnidarian signature in EAM detritus was dominated by octocorals, with a scarcity of hard corals. The composition of detritus also varied seasonally. The negligible contribution of sponges to reef detritus contrasts with the detrital pathway originally proposed in the sponge loop hypothesis. The findings indicate a mix of pelagic and benthic sources in the calmer summer and primarily benthic sources in the more turbulent spring., Competing Interests: Beverly McClenaghan, Lesley Berghuis, Nicole Fahner and Hoda Rajabi are employees of eDNAtec Inc. Mehrdad Hajibabaei is the founder and Chief Scientific Officer of eDNAtec Inc., (©2024 Olinger et al.)

Nano-vesicular carriers are promising tissue-specific drug delivery platforms. Here, biomimetic proteolipid vesicles (BPLVs) were used for delivery of glycosylphosphatidylinositol (GPI)-anchored proteins to GPI deficient paroxysmal nocturnal hemoglobinuria (PNH) cells. BPLVs were assembled as single unilamellar monodispersed (polydispersity index, 0.1) negatively charged (ζ-potential, -28.6 ± 5.6 mV) system using microfluidic technique equipped with Y-shaped chip. GPI-anchored and not-GPI proteins on BPLV surface were detected by flow cytometry. Peripheral blood mononuclear cells (PBMCs) from healthy and PNH subjects were treated with BPLVs (final concentration, 0.5 mg/mL), and cells displayed an excellent protein uptake, documented by flow cytometry immunophenotyping and confocal microscopy. BPLV-treated cells stressed with complement components showed an increased resistance to complement-mediated lysis, both healthy and PNH PBMCs. In conclusion, BPLVs could be effective nanocarriers for protein transfer to targeted cells to revert protein deficiency, like in PNH disease. However, further in vivo studies are required to validate our preclinical in vitro results., Competing Interests: The Authors V.G., P.S., E.P.L., G.D.P., and C.S. disclose a patent no. 102023000015003 (18/07/2023)., (© 2024 The Author(s).)

Context: Chronic kidney disease (CKD) is a public health burden worldwide. Epidemiological studies observed an association between sex hormones, including estradiol, and kidney function., Objective: We conducted a Mendelian randomization (MR) study to assess a possible causal effect of estradiol levels on kidney function in males and females., Design: We performed a bidirectional two-sample MR using published genetic associations of serum levels of estradiol in men ( n = 206,927) and women ( n = 229,966), and of kidney traits represented by estimated glomerular filtration rate (eGFR, n = 567,460), urine albumin-to-creatinine ratio (UACR, n = 547,361), and CKD ( n = 41,395 cases and n = 439,303 controls) using data obtained from the CKDGen Consortium. Additionally, we conducted a genome-wide association study using UK Biobank cohort study data ( n = 11,798 men and n = 6,835 women) to identify novel genetic associations with levels of estradiol, and then used these variants as instruments in a one-sample MR., Results: The two-sample MR indicated that genetically predicted estradiol levels are significantly associated with eGFR in men (beta = 0.077; p = 5.2E-05). We identified a single locus at chromosome 14 associated with estradiol levels in men being significant in the one-sample MR on eGFR (beta = 0.199; p = 0.017). We revealed significant results with eGFR in postmenopausal women and with UACR in premenopausal women, which did not reach statistical significance in the sensitivity MR analyses. No causal effect of eGFR or UACR on estradiol levels was found., Conclusions: We conclude that serum estradiol levels may have a causal effect on kidney function. Our MR results provide starting points for studies to develop therapeutic strategies to reduce kidney disease., Competing Interests: CS is currently an employee of Bayer AG, Pharmaceuticals. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Nasr, Schurmann, Böttinger and Teumer.)

Because of its simplicity, pulse oximetry plays a ubiquitous role in neonatology. Its measurements are based on the absorption of light by hemoglobin. Ambient light can affect these values, therefore algorithms are designed to compensate for constant ambient light. Modern light-emitting diodes often flicker at a very high frequency. Such flickering ambient light can lead to significant measurement errors in saturation. To present a novel way in which light-emitting diodes influence the function of pulse oximeters and to demonstrate mathematically that a stroboscopic effect may well be responsible for this disturbance. Using publicly available data, a mathematical model of a pulse oximeter with a calibration curve and a proprietary measurement algorithm was created. This was used to simulate saturation measurements in flickering ambient light. To do this, photopletysmograms for red and infrared light at 98% oxygen saturation were mathematically superimposed on the light emission from an examination lamp used in the intensive care unit. From these results, presumable saturation measurements from a pulse oximeter were extrapolated. The light-emitting diodes in the examination lamp flicker at 207 Hz. The pulsating light from the light-emitting diodes causes superimposition of the photoplethysmogram due to the stroboscopic effect. With increasing brightness, the saturation dropped to 85% and the pulse rate to 108 bpm. The pulsed light of light-emitting diodes can distort pulse oximetry measurements. The stroboscopic effect leads to low saturation values, which can lead to the risk of blindness in premature infants due to excessive oxygenation., (© 2023. The Author(s).)

Background: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways., Methods: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses., Results: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology., Conclusions: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries., Competing Interests: Competing interests: Rebecca S. Fine: Rebecca S. Fine is currently employed by Vertex Pharmaceuticals Incorporated. Audrey Y Chu: Currently employed by GlaxoSmithkline. Dennis O. Mook-Kanamori: Dennis Mook-Kanamori is working as a part-time clinical research consultant for Metabolon, Inc. Paul W. Franks: PWF has been a paid consultant for Eli Lilly and Sanofi Aventis and has received research support from several pharmaceutical companies as part of a European Union Innovative Medicines Initiative (IMI) project. Mike A. Nalls: Dr. Mike A. Nalls is supported by a consulting contract between Data Tecnica International LLC and the National Institute on Aging (NIA), National Institutes of Health (NIH), Bethesda, MD, USA. Dr. Nalls also consults for Illumina Inc., the Michael J. Fox Foundation, and the University of California Healthcare. Mark J. Caulfield: MJC is Chief Scientist for Genomics England, a UK government company. Joel N. Hirschhorn: JHN is on the scientific advisory board of Camp4 Therapeutics. Erik Ingelsson: Erik Ingelsson is now an employee of GlaxoSmithKline. Anubha Mahajan: Anubha Mahajan is an employee of Genentech since January 2020, and a holder of Roche stock. Mark I McCarthy: The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. MMcC has served on advisory panels for Pfizer, NovoNordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly, and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, MMcC is an employee of Genentech, and a holder of Roche stock. Inês Barroso: IB and spouse declare stock ownership in GlaxoSmithkline and Incyte Ltd. James B. Meigs: JBM serves as an Academic Associate for Quest Diagnostics R&D Bruce M Psaty serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Dr. Sander W. van der Laan has received Roche funding for unrelated work. Matthias Blüher received honoraria as a consultant and speaker from Amgen, AstraZeneca, Bayer, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis, Pfizer and Sanofi. Vinicius Tragante: VT became an employee of deCODE genetics/Amgen Inc. after the conclusion of this work Dr Franco is employed by ErasmusAGE, a center for aging research across the life course funded by Nestlé Nutrition (Nestec Ltd.) and Metagenics., (Copyright: © 2023 Willems SM et al.)

Background& Aims: Tumor necrosis factor (TNF) antagonists often are used as first-line medications to treat moderate to severe inflammatory bowel disease (IBD), but many patients do not achieve or maintain response. Our aim was to compare the effectiveness of second-line treatments (ustekinumab, vedolizumab, or a second TNF antagonist) after TNF antagonist exposure in patients with Crohn's disease (CD) and ulcerative colitis (UC) from 2 electronic health records-based cohorts., Methods: We identified patients with prior TNF antagonist exposure who switched to a different biologic in the Mount Sinai Health System (MSHS) electronic health records (CD, n = 527; UC, n = 165) and the Study of a Prospective Adult Research Cohort (SPARC) from the Inflammatory Bowel Disease Plexus Program of the Crohn's & Colitis Foundation (CD, n = 412; UC, n = 129). Treatment failure was defined as the composite of any IBD-related surgery, IBD-related hospitalization, new prescription of oral/intravenous corticosteroids, or need to switch to a third biologic agent. Time-to-event analysis was conducted with inverse probability of treatment-weighted data., Results: Overall, treatment failure occurred in 85% of MSHS and 72% of SPARC CD patients. In SPARC, the likelihood of treatment failure was significantly lower with ustekinumab compared with vedolizumab as second-line treatment (adjusted hazard ratio, 0.66; 95% CI, 0.54-0.82; P < .001), a trend confirmed in MSHS (adjusted hazard ratio, 0.89; 95% CI, 0.77-1.04; P = .15). In both cohorts, the superiority of ustekinumab compared with vedolizumab was shown when considering treatment failure as prescription of steroids or a third biologic agent. In UC, no differences between second-line treatment groups were identified., Conclusions: In 2 independent real-world cohort settings, second-line therapy in CD with ustekinumab after TNF antagonist treatment failure was associated with a lower likelihood of treatment failure than second-line vedolizumab., (Copyright © 2023 AGA Institute. Published by Elsevier Inc. All rights reserved.)

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development., (© 2023. The Author(s).)

Objective: To assess whether an individual's degree of psychological resilience can be determined from physiological metrics passively collected from a wearable device., Materials and Methods: Data were analyzed in this secondary analysis of the Warrior Watch Study dataset, a prospective cohort of healthcare workers enrolled across 7 hospitals in New York City. Subjects wore an Apple Watch for the duration of their participation. Surveys were collected measuring resilience, optimism, and emotional support at baseline., Results: We evaluated data from 329 subjects (mean age 37.4 years, 37.1% male). Across all testing sets, gradient-boosting machines (GBM) and extreme gradient-boosting models performed best for high- versus low-resilience prediction, stratified on a median Connor-Davidson Resilience Scale-2 score of 6 (interquartile range = 5-7), with an AUC of 0.60. When predicting resilience as a continuous variable, multivariate linear models had a correlation of 0.24 ( P  = .029) and RMSE of 1.37 in the testing data. A positive psychological construct, comprised of resilience, optimism, and emotional support was also evaluated. The oblique random forest method performed best in estimating high- versus low-composite scores stratified on a median of 32.5, with an AUC of 0.65, a sensitivity of 0.60, and a specificity of 0.70., Discussion: In a post hoc analysis, machine learning models applied to physiological metrics collected from wearable devices had some predictive ability in identifying resilience states and a positive psychological construct., Conclusions: These findings support the further assessment of psychological characteristics from passively collected wearable data in dedicated studies., Competing Interests: DC is a coinventor on patents filed by the Icahn School of Medicine at Mount Sinai (ISMMS) relating to the treatment for treatment-resistant depression, suicidal ideation, and other disorders. ISMMS has entered into a licensing agreement with Janssen Pharmaceuticals, Inc, and it has received and will receive payments from Janssen under the license agreement related to these patents for the treatment of treatment-resistant depression and suicidal ideation. Consistent with the ISMMS Faculty Handbook (the medical school policy), DC is entitled to a portion of the payments received by the ISMMS. Because SPRAVATO has received regulatory approval for treatment-resistant depression, through the ISMMS, DC will be entitled to additional payments beyond those already received under the license agreement. DC is a named coinventor on several patents filed by ISMMS for a cognitive training intervention to treat depression and related psychiatric disorders. The ISMMS has entered into a licensing agreement with Click Therapeutics, Inc and has received and will receive payments related to the use of this cognitive training intervention for the treatment of psychiatric disorders. In accordance with the ISMMS Faculty Handbook, DC has received a portion of these payments and is entitled to a portion of any additional payments that the medical school may receive from this license with Click Therapeutics. DC is a named coinventor on a patent application filed by the ISMMS for the use of intranasally administered Neuropeptide Y for the treatment of mood and anxiety disorders. This intellectual property has not been licensed. DC is a named coinventor on a patent application in the United States and several issued patents outside the United States filed by the ISMMS related to the use of ketamine for the treatment of posttraumatic stress disorder. This intellectual property has not been licensed. EPB reports consultancy agreements with Deloitte and Roland Berger; ownership interest in Digital Medicine E. Böttinger GmbH, EBCW GmbH, and Ontomics, Inc; receiving honoraria from Bayer, Bosch Health Campus, Sanofi, and Siemens; and serving as a scientific advisor or member of Bosch Health Campus and Seer Biosciences Inc. LK declares research funding from Abbvie and Pfizer, consulting for Abbvie and Pfizer, and equity ownership/stock options in MetaMe Health and Trellus Health. MS-F declares research support from Novartis and Allergenis. GNN reports employment with, consultancy agreements with, and ownership interest in Pensieve Health and Renalytix AI; receiving consulting fees from AstraZeneca, BioVie, GLG Consulting, and Reata; and serving as a scientific advisor or member of Pensieve Health and Renalytix AI. ZAF discloses consulting fees from Alexion, GlaxoSmithKline, and Trained Therapeutix Discovery and research funding from Daiichi Sankyo, Amgen, Bristol Myers Squibb, and Siemens Healthineers. ZAF receives financial compensation as a board member and advisor to Trained Therapeutix Discovery and owns equity in Trained Therapeutix Discovery as a cofounder. The remaining authors declare no conflicts of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Anaplastic thyroid carcinoma is a rare but aggressive neoplasm that often presents as advanced inoperable disease. Patients with B-Raf proto-oncogene (BRAF) v600e mutated anaplastic thyroid carcinoma who receive neoadjuvant dabrafenib/trametinib have improved rates of microscopically margin-negative resection and durable locoregional control. However this has not been evaluated in the setting of tracheal resection and primary reconstruction. Here we demonstrate the safety and efficacy of laryngotracheal resection and reconstruction after dabrafenib/trametinib for locoregionally advanced BRAF v600e mutated anaplastic thyroid carcinoma., (Copyright © 2023 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Purpose: Due to the increasing application of genome analysis and interpretation in medical disciplines, professionals require adequate education. Here, we present the implementation of personal genotyping as an educational tool in two genomics courses targeting Digital Health students at the Hasso Plattner Institute (HPI) and medical students at the Technical University of Munich (TUM)., Methods: We compared and evaluated the courses and the students' perceptions on the course setup using questionnaires., Results: During the course, students changed their attitudes towards genotyping (HPI: 79% [15 of 19], TUM: 47% [25 of 53]). Predominantly, students became more critical of personal genotyping (HPI: 73% [11 of 15], TUM: 72% [18 of 25]) and most students stated that genetic analyses should not be allowed without genetic counseling (HPI: 79% [15 of 19], TUM: 70% [37 of 53]). Students found the personal genotyping component useful (HPI: 89% [17 of 19], TUM: 92% [49 of 53]) and recommended its inclusion in future courses (HPI: 95% [18 of 19], TUM: 98% [52 of 53])., Conclusion: Students perceived the personal genotyping component as valuable in the described genomics courses. The implementation described here can serve as an example for future courses in Europe., (© 2023. The Author(s).)

Background  The clinical results of conservative treatment options for ulnar compression at the elbow have not been clearly determined. The aim of this review was to evaluate available conservative treatment options and their effectiveness for ulnar nerve compression at the elbow. Methods  In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations, a systematic review and meta-analysis of studies was performed. Literature search was performed using Ovid MEDLINE, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL). Results  Of the 1,079 retrieved studies, 20 were eligible for analysis and included 687 cases of ulnar neuropathy at the elbow. Improvement of symptoms was reported in 54% of the cases receiving a steroid/lidocaine injection (95% confidence interval [CI], 41-67) and in 89% of the cases using a splint device (95% CI, 69-99). Conclusions  Conservative management seems to be effective. Both lidocaine/steroid injections and splint devices gave a statistically significant improvement of symptoms and are suitable options for patients who refuse an operative procedure or need a bridge to their surgery. Splinting is preferred over injections, as it shows a higher rate of improvement., Competing Interests: Conflict of Interest None declared., (The Korean Society of Plastic and Reconstructive Surgeons. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

Pharmacogenetic implementation programs are increasingly feasible due to the availability of clinical guidelines for implementation research. The utilization of these resources has been reported with selected drug-gene pairs; however, little is known about how prescribers respond to pharmacogenetic recommendations for statin therapy. We prospectively assessed prescriber interaction with point-of-care clinical decision support (CDS) to guide simvastatin therapy for a diverse cohort of primary care patients enrolled in a clinical pharmacogenetics program. Of the 1,639 preemptively genotyped patients, 298 (18.2%) had an intermediate function (IF) OATP1B1 phenotype and 25 (1.53%) had a poor function (PF) phenotype, predicted by a common single nucleotide variant in the SLCO1B1 gene (c.521T>C; rs4149056). Clinicians were presented with CDS when simvastatin was prescribed for patients with IF or PF through the electronic health record. Importantly, 64.2% of the CDS deployed at the point-of-care was accepted by the prescribers and resulted in prescription changes. Statin intensity was found to significantly influence prescriber adoption of the pharmacogenetic-guided CDS, whereas patient gender or race, prescriber type, or pharmacogenetic training status did not significantly influence adoption. This study demonstrates that primary care providers readily adopt pharmacogenetic information to guide statin therapy for the majority of patients with preemptive genotype data., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

Microplastics (MPs), <5 mm in size, are a concerning pollutant in bodies of water because they can be ingested by biological organisms, posing risks to humans and the environment. This study assessed the extent of MPs contamination in various fish species (Oreochromis niloticus, Arius manillensis, and Pterygoplichthys spp.) in selected sites along two major river systems in the Philippines - Pasig and Marikina Rivers. An optimized Raman microspectroscopy technique was used for imaging and identification of MPs using a mean laser spot size of about 1 μm, which is advantageous in the identification of fibers which have small diameters (<50 μm). It also allowed the simultaneous identification of MPs and their pigment additives, which in turn enabled the tracing of possible sources of these MPs. This is important because the fate and accumulation of MPs in rivers systems, as well as its toxicity is dependent on various factors including polymer type and surface chemistry. Majority of the MPs identified from all the fish species were composed of polypropylene and polyethylene in the form of fragments, which reflects both the widespread use of these polymers for packaging and their environmental fate as riverine plastic debris. Moreover, the detection of MPs in the fish species may affect the food chain and eventually pose health risks for humans. The study could provide guidance on waste and environmental water management in the surrounding region., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Emilyn Q. Espiritu reports financial support was provided by Republic of the Philippines Department of Science and Technology., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Objective: High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach., Methods: This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank., Results: Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux., Conclusions: This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes., (© 2022 The Obesity Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Water is essential for survival, but one in three individuals worldwide (2.2 billion people) lacks access to safe drinking water. Water intake requirements largely reflect water turnover (WT), the water used by the body each day. We investigated the determinants of human WT in 5604 people from the ages of 8 days to 96 years from 23 countries using isotope-tracking ( 2 H) methods. Age, body size, and composition were significantly associated with WT, as were physical activity, athletic status, pregnancy, socioeconomic status, and environmental characteristics (latitude, altitude, air temperature, and humidity). People who lived in countries with a low human development index (HDI) had higher WT than people in high-HDI countries. On the basis of this extensive dataset, we provide equations to predict human WT in relation to anthropometric, economic, and environmental factors.

Objective: Hypertension has long been recognized as one of the most important predisposing factors for cardiovascular diseases and mortality. In recent years, machine learning methods have shown potential in diagnostic and predictive approaches in chronic diseases. Electronic health records (EHRs) have emerged as a reliable source of longitudinal data. The aim of this study is to predict the onset of hypertension using modern deep learning (DL) architectures, specifically long short-term memory (LSTM) networks, and longitudinal EHRs., Materials and Methods: We compare this approach to the best performing models reported from previous works, particularly XGboost, applied to aggregated features. Our work is based on data from 233 895 adult patients from a large health system in the United States. We divided our population into 2 distinct longitudinal datasets based on the diagnosis date. To ensure generalization to unseen data, we trained our models on the first dataset (dataset A "train and validation") using cross-validation, and then applied the models to a second dataset (dataset B "test") to assess their performance. We also experimented with 2 different time-windows before the onset of hypertension and evaluated the impact on model performance., Results: With the LSTM network, we were able to achieve an area under the receiver operating characteristic curve value of 0.98 in the "train and validation" dataset A and 0.94 in the "test" dataset B for a prediction time window of 1 year. Lipid disorders, type 2 diabetes, and renal disorders are found to be associated with incident hypertension., Conclusion: These findings show that DL models based on temporal EHR data can improve the identification of patients at high risk of hypertension and corresponding driving factors. In the long term, this work may support identifying individuals who are at high risk for developing hypertension and facilitate earlier intervention to prevent the future development of hypertension., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether humans have evolved sex differences in the degree of interindividual variation in energy expenditure. We found that, even when statistically comparing males and females of the same age, height, and body composition, there is much more variation in total, activity, and basal energy expenditure among males. However, with aging, variation in total energy expenditure decreases, and because this happens more rapidly in males, the magnitude of greater male variation, though still large, is attenuated in older age groups. Considerably greater male variation in both total and activity energy expenditure could be explained by greater male variation in levels of daily activity. The considerably greater male variation in basal energy expenditure is remarkable and may be explained, at least in part, by greater male variation in the size of energy-demanding organs. If energy expenditure is a trait that is of indirect interest to females when choosing a sexual partner, this would suggest that energy expenditure is under sexual selection. However, we present a novel energetics model demonstrating that it is also possible that females have been under stabilizing selection pressure for an intermediate basal energy expenditure to maximize energy available for reproduction., Competing Interests: Conflicts of interest The authors have no conflicts of interest to declare., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The median nerve can be compressed due to a tumor along the course of the median nerve, causing typical compression symptoms or even persistence or recurrence after an operation. The aim of this review is to provide a comprehensive overview of rare tumors described in recent publications that cause median nerve compression and to evaluate treatment options. The PubMed, Embase, and Web of Science databases were searched for studies describing median nerve compression due to a tumor in adults, published from the year 2000 and written in English. From 94 studies, information of approximately 100 patients have been obtained. Results  The rare tumors causing compression were in 32 patients located at the carpal tunnel, in 21 cases in the palm of the hand, and 28 proximal from the carpal tunnel. In the other cases the compression site extended over a longer trajectory. There were 37 different histological types of lesions. Complete resection of the tumor was possible in 58 cases. A total of 8 patients presented for the second time after receiving initial therapy. During follow-up, three cases of recurrence were reported with a mean follow-up period of 11 months. The most common published cause of median nerve compression is the lipofibromatous hamartoma. Besides the typical sensory and motor symptoms of median nerve compression, a thorough physical examination of the complete upper extremity is necessary to find any swelling or triggering that might raise suspicion of the presence of a tumor., Competing Interests: Conflict of Interest None of the authors is an Editorial Board member. No other potential conflicts of interest relevant to this article were reported., (The Korean Society of Plastic and Reconstructive Surgeons. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics., (Copyright © 2022 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

The protection mediated by the bioactive sphingolipid sphingosine-1-phosphate (S1P) declines during Alzheimer's disease (AD) progression, especially in patients carrying the apolipoprotein E ε4 (APOE4) isoform. The drug FTY720 mimics S1P bioactivity, but its efficacy in treating AD is unclear. Two doses of FTY720 (0.1 mg / kg and 0.5 mg / kg daily) were given by oral gavage for 15 weeks to transgenic mouse models of familial AD carrying human apolipoprotein E (APOE) APOE3 (E3FAD) or APOE4 (E4FAD). After 12 weeks of treatment, animals were subjected to behavioral tests for memory, locomotion, and anxiety. Blood was withdrawn at different time points and brains were collected for sphingolipids analysis by mass spectrometry, gene expression by RT-PCR and Aβ quantification by ELISA. We discovered that low levels of S1P in the plasma is associated with a higher probability of failing the memory test and that FTY720 prevents memory impairments in E4FAD. The beneficial effect of FTY720 was induced by a shift of the sphingolipid metabolism in the brain towards a lower production of toxic metabolites, like ceramide d18:1/16:0 and d18:1/22:0, and reduction of amyloid-β burden and inflammation. In conclusion, we provide further evidence of the druggability of the sphingolipid system in AD., (Copyright © 2022. Published by Elsevier Masson SAS.)

Background: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure., Methods: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants., Results: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings ( P <5×10 -8 ). Among them, a rare intergenic variant at novel locus, LOC100506274 , was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; P =4.99×10 -8 ) but not stage-2 analysis ( P =0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; P =4.18×10 -7 ) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; P =7.28×10 -23 ). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings ( P <1×10 -6 and P <1×10 -4 , respectively)., Discussion: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

Lower ambient temperature (T a ) requires greater energy expenditure to sustain body temperature. However, effects of T a on human energetics may be buffered by environmental modification and behavioral compensation. We used the IAEA DLW database for adults in the USA (n = 3213) to determine the effect of T a (-10 to +30°C) on TEE, basal (BEE) and activity energy expenditure (AEE) and physical activity level (PAL). There were no significant relationships (p > 0.05) between maximum, minimum and average T a and TEE, BEE, AEE and PAL. After adjustment for fat-free mass, fat mass and age, statistically significant (p < 0.01) relationships between TEE, BEE and T a emerged in females but the effect sizes were not biologically meaningful. Temperatures inside buildings are regulated at 18-25°C independent of latitude. Hence, adults in the US modify their environments to keep TEE constant across a wide range of external ambient temperatures., Competing Interests: The authors declare no conflicts of interest., (© 2022 The Authors.)

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (n DM  = 178,691, n noDM  = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM., (© 2022. The Author(s).)

Objective: To determine whether a machine learning model can detect SARS-CoV-2 infection from physiological metrics collected from wearable devices., Materials and Methods: Health care workers from 7 hospitals were enrolled and prospectively followed in a multicenter observational study. Subjects downloaded a custom smart phone app and wore Apple Watches for the duration of the study period. Daily surveys related to symptoms and the diagnosis of Coronavirus Disease 2019 were answered in the app., Results: We enrolled 407 participants with 49 (12%) having a positive nasal SARS-CoV-2 polymerase chain reaction test during follow-up. We examined 5 machine-learning approaches and found that gradient-boosting machines (GBM) had the most favorable validation performance. Across all testing sets, our GBM model predicted SARS-CoV-2 infection with an average area under the receiver operating characteristic (auROC) = 86.4% (confidence interval [CI] 84-89%). The model was calibrated to value sensitivity over specificity, achieving an average sensitivity of 82% (CI ±∼4%) and specificity of 77% (CI ±∼1%). The most important predictors included parameters describing the circadian heart rate variability mean (MESOR) and peak-timing (acrophase), and age., Discussion: We show that a tree-based ML algorithm applied to physiological metrics passively collected from a wearable device can identify and predict SARS-CoV-2 infection., Conclusion: Applying machine learning models to the passively collected physiological metrics from wearable devices may improve SARS-CoV-2 screening methods and infection tracking., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10 -9 ), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Objective: Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed., Research Design and Methods: Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD)., Results: Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway., Conclusions: Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes., (© 2022 by the American Diabetes Association.)

Importance: Risk variants in the apolipoprotein L1 (APOL1 [OMIM 603743]) gene on chromosome 22 are common in individuals of West African ancestry and confer increased risk of kidney failure for people with African ancestry and hypertension. Whether disclosing APOL1 genetic testing results to patients of African ancestry and their clinicians affects blood pressure, kidney disease screening, or patient behaviors is unknown., Objective: To determine the effects of testing and disclosing APOL1 genetic results to patients of African ancestry with hypertension and their clinicians., Design, Setting, and Participants: This pragmatic randomized clinical trial randomly assigned 2050 adults of African ancestry with hypertension and without existing chronic kidney disease in 2 US health care systems from November 1, 2014, through November 28, 2016; the final date of follow-up was January 16, 2018. Patients were randomly assigned to undergo immediate (intervention) or delayed (waiting list control group) APOL1 testing in a 7:1 ratio. Statistical analysis was performed from May 1, 2018, to July 31, 2020., Interventions: Patients randomly assigned to the intervention group received APOL1 genetic testing results from trained staff; their clinicians received results through clinical decision support in electronic health records. Waiting list control patients received the results after their 12-month follow-up visit., Main Outcomes and Measures: Coprimary outcomes were the change in 3-month systolic blood pressure and 12-month urine kidney disease screening comparing intervention patients with high-risk APOL1 genotypes and those with low-risk APOL1 genotypes. Secondary outcomes compared these outcomes between intervention group patients with high-risk APOL1 genotypes and controls. Exploratory analyses included psychobehavioral factors., Results: Among 2050 randomly assigned patients (1360 women [66%]; mean [SD] age, 53 [10] years), the baseline mean (SD) systolic blood pressure was significantly higher in patients with high-risk APOL1 genotypes vs those with low-risk APOL1 genotypes and controls (137 [21] vs 134 [19] vs 133 [19] mm Hg; P = .003 for high-risk vs low-risk APOL1 genotypes; P = .001 for high-risk APOL1 genotypes vs controls). At 3 months, the mean (SD) change in systolic blood pressure was significantly greater in patients with high-risk APOL1 genotypes vs those with low-risk APOL1 genotypes (6 [18] vs 3 [18] mm Hg; P = .004) and controls (6 [18] vs 3 [19] mm Hg; P = .01). At 12 months, there was a 12% increase in urine kidney disease testing among patients with high-risk APOL1 genotypes (from 39 of 234 [17%] to 68 of 234 [29%]) vs a 6% increase among those with low-risk APOL1 genotypes (from 278 of 1561 [18%] to 377 of 1561 [24%]; P = .10) and a 7% increase among controls (from 33 of 255 [13%] to 50 of 255 [20%]; P = .01). In response to testing, patients with high-risk APOL1 genotypes reported more changes in lifestyle (a subjective measure that included better dietary and exercise habits; 129 of 218 [59%] vs 547 of 1468 [37%]; P < .001) and increased blood pressure medication use (21 of 218 [10%] vs 68 of 1468 [5%]; P = .005) vs those with low-risk APOL1 genotypes; 1631 of 1686 (97%) declared they would get tested again., Conclusions and Relevance: In this randomized clinical trial, disclosing APOL1 genetic testing results to patients of African ancestry with hypertension and their clinicians was associated with a greater reduction in systolic blood pressure, increased kidney disease screening, and positive self-reported behavior changes in those with high-risk genotypes., Trial Registration: ClinicalTrials.gov Identifier: NCT02234063.

Objective: The median nerve can become compressed at multiple points in the arm, causing carpal tunnel-, pronator-, anterior interosseous-, or lacertus syndrome. Anatomical variations are potential reasons of persisting or recurrent symptoms of median nerve compression and are often recognized late. The objective of this study is to provide a comprehensive list of rare anatomical variations and malformations causing median nerve compression., Methods: A total of 62 studies describing median nerve compression due to an anatomical structure in adults published from 2000 in English were included. The findings were: 35 tenomuscular, 16 vascular causes, and 4 cases with nerve involvement. Only 1 osseous and 18 combined anomalies caused compression. In 18 cases, the anomaly was found in the proximal forearm., Results: In 44 cases, the median nerve was surgical released and 35 anomalies were completely resected. Persistent or recurrent symptoms were present in 13 cases. During follow-up, 1 case of recurrence was reported.Standard operative option for median nerve compression consists of an open median nerve release., Conclusions: In case of persistent or recurrent carpal tunnel syndrome, unilateral symptoms, the presence of a palpable mass, manifestation of symptoms at young age and pain in the forearm or upper arm, the surgeon has to rule out the presence of an anatomical anomaly. Complete resection of the anomaly is not always necessary. The surgeon should be aware of potential anomalies to avoid inadvertent damage at surgery., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Low total energy expenditure (TEE, MJ/d) has been a hypothesized risk factor for weight gain, but repeatability of TEE, a critical variable in longitudinal studies of energy balance, is understudied. We examine repeated doubly labeled water (DLW) measurements of TEE in 348 adults and 47 children from the IAEA DLW Database (mean ± SD time interval: 1.9 ± 2.9 y) to assess repeatability of TEE, and to examine if TEE adjusted for age, sex, fat-free mass, and fat mass is associated with changes in weight or body composition. Here, we report that repeatability of TEE is high for adults, but not children. Bivariate Bayesian mixed models show no among or within-individual correlation between body composition (fat mass or percentage) and unadjusted TEE in adults. For adults aged 20-60 y (N = 267; time interval: 7.4 ± 12.2 weeks), increases in adjusted TEE are associated with weight gain but not with changes in body composition; results are similar for subjects with intervals >4 weeks (N = 53; 29.1 ± 12.8 weeks). This suggests low TEE is not a risk factor for, and high TEE is not protective against, weight or body fat gain over the time intervals tested., (© 2022. The Author(s).)

In this study, we present a non-invasive solution to identify patients with coronary artery disease (CAD) defined as ⩾50% stenosis in at least one coronary artery. The solution is based on the analysis of linear acceleration (seismocardiogram, SCG) and angular velocity (gyrocardiogram, GCG) of the heart recorded in the x, y, and z directional axes from an accelerometer/gyroscope sensor mounted on the sternum. The database was collected from 310 individuals through a multicenter study. The time-frequency features extracted from each SCG and GCG data channel were fed to a one-dimensional Convolutional Neural Network (1D CNN) to train six separate classifiers. The results from different classifiers were later fused to estimate the CAD risk for each participant. The predicted CAD risk was validated against related results from angiography. The SCG z and SCG y classifiers showed better performance relative to the other models ( p < 0.05) with the area under the curve (AUC) of 91%. The sensitivity range for CAD detection was 92-94% for the SCG models and 73-87% for the GCG models. Based on our findings, the SCG models achieved better performance in predicting the CAD risk compared to the GCG models; the model based on the combination of all SCG and GCG classifiers did not achieve higher performance relative to the other models. Moreover, these findings showed that the performance of the proposed 3-axial SCG/GCG solution based on recordings obtained during rest was comparable, or better than stress ECG. These data may indicate that 3-axial SCG/GCG could be used as a portable at-home CAD screening tool., Competing Interests: PD and ZX are employed by Heart Force Medical Inc., Vancouver, Canada. EB is on the Board of Directors at Heart Force Medical, Inc. Vancouver, Canada. FK-K is the CTO of Heart Force Medical Inc., Vancouver, Canada. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Dehkordi, Bauer, Tavakolian, Xiao, Blaber and Khosrow-Khavar.)

Recent trials of two classes of glucose-lowering drugs (SGLT2 inhibitors and GLP1RAs) have shown consistent cardiovascular and renal benefits that appear independent of glycaemic control. These results have prompted the Dutch College of General Practitioners (NHG) together with the Dutch Society of Internal Medicine (NIV) to update the treatment algorithm in patients with type 2 diabetes mellitus (T2D) at very high CVD risk. The use of SGLT2 inhibitors or GLP1RAs is now recommended in 3 groups of people with T2D. 1. patients with established CVD; 2. Patients with chronic kidney disease and a moderately to high CVD risk according to KDIGO; 3. patients with heart failure with reduced ejection fraction (HFrEF). Treatment algorithms differ for drug-naïve and drug-treated patients with T2D. In both drug-naïve and drug-treated patients the use of a SGLT2 inhibitor respectively as monotherapy or add-on is recommended as first step. If HbA1c is above the individual target, metformin will be added in drug-naive patients whereas GLP1-RAs could be considered in drug-treated patients. GLP1-RAs should also be considered when SGLT2-inhibitors are contraindicated.

Background: Physical activity may be a way to increase and maintain fat-free mass (FFM) in later life, similar to the prevention of fractures by increasing peak bone mass., Objectives: A study is presented of the association between FFM and physical activity in relation to age., Methods: In a cross-sectional study, FFM was analyzed in relation to physical activity in a large participant group as compiled in the International Atomic Energy Agency Doubly Labeled Water database. The database included 2000 participants, age 3-96 y, with measurements of total energy expenditure (TEE) and resting energy expenditure (REE) to allow calculation of physical activity level (PAL = TEE/REE), and calculation of FFM from isotope dilution., Results: PAL was a main determinant of body composition at all ages. Models with age, fat mass (FM), and PAL explained 76% and 85% of the variation in FFM in females and males < 18 y old, and 32% and 47% of the variation in FFM in females and males ≥ 18 y old, respectively. In participants < 18 y old, mean FM-adjusted FFM was 1.7 kg (95% CI: 0.1, 3.2 kg) and 3.4 kg (95% CI: 1.0, 5.6 kg) higher in a very active participant with PAL = 2.0 than in a sedentary participant with PAL = 1.5, for females and males, respectively. At age 18 y, height and FM-adjusted FFM was 3.6 kg (95% CI: 2.8, 4.4 kg) and 4.4 kg (95% CI: 3.2, 5.7 kg) higher, and at age 80 y 0.7 kg (95% CI: -0.2, 1.7 kg) and 1.0 kg (95% CI: -0.1, 2.1 kg) higher, in a participant with PAL = 2.0 than in a participant with PAL = 1.5, for females and males, respectively., Conclusions: If these associations are causal, they suggest physical activity is a major determinant of body composition as reflected in peak FFM, and that a physically active lifestyle can only partly protect against loss of FFM in aging adults., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Understanding the impacts of activity on energy balance is crucial. Increasing levels of activity may bring diminishing returns in energy expenditure because of compensatory responses in non-activity energy expenditures. 1-3 This suggestion has profound implications for both the evolution of metabolism and human health. It implies that a long-term increase in activity does not directly translate into an increase in total energy expenditure (TEE) because other components of TEE may decrease in response-energy compensation. We used the largest dataset compiled on adult TEE and basal energy expenditure (BEE) (n = 1,754) of people living normal lives to find that energy compensation by a typical human averages 28% due to reduced BEE; this suggests that only 72% of the extra calories we burn from additional activity translates into extra calories burned that day. Moreover, the degree of energy compensation varied considerably between people of different body compositions. This association between compensation and adiposity could be due to among-individual differences in compensation: people who compensate more may be more likely to accumulate body fat. Alternatively, the process might occur within individuals: as we get fatter, our body might compensate more strongly for the calories burned during activity, making losing fat progressively more difficult. Determining the causality of the relationship between energy compensation and adiposity will be key to improving public health strategies regarding obesity., Competing Interests: Declaration of interests The authors have no conflicts of interest to declare., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Polygenic risk scores (PRS) aggregating results from genome-wide association studies are the state of the art in the prediction of susceptibility to complex traits or diseases, yet their predictive performance is limited for various reasons, not least of which is their failure to incorporate the effects of gene-gene interactions. Novel machine learning algorithms that use large amounts of data promise to find gene-gene interactions in order to build models with better predictive performance than PRS. Here, we present a data preprocessing step by using data-mining of contextual information to reduce the number of features, enabling machine learning algorithms to identify gene-gene interactions. We applied our approach to the Parkinson's Progression Markers Initiative (PPMI) dataset, an observational clinical study of 471 genotyped subjects (368 cases and 152 controls). With an AUC of 0.85 (95% CI = [0.72; 0.96]), the interaction-based prediction model outperforms the PRS (AUC of 0.58 (95% CI = [0.42; 0.81])). Furthermore, feature importance analysis of the model provided insights into the mechanism of Parkinson's disease. For instance, the model revealed an interaction of previously described drug target candidate genes TMEM175 and GAPDHP25 . These results demonstrate that interaction-based machine learning models can improve genetic prediction models and might provide an answer to the missing heritability problem., Competing Interests: JC, HB, JK, CR, and MS are employed by biotx.ai GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Cope, Baukmann, Klinger, Ravarani, Böttinger, Konigorski and Schmidt.)

Background: The COVID-19 pandemic has resulted in a high degree of psychological distress among health care workers (HCWs). There is a need to characterize which HCWs are at an increased risk of developing psychological effects from the pandemic. Given the differences in the response of individuals to stress, an analysis of both the perceived and physiological consequences of stressors can provide a comprehensive evaluation of its impact., Objective: This study aimed to determine characteristics associated with longitudinal perceived stress in HCWs and to assess whether changes in heart rate variability (HRV), a marker of autonomic nervous system function, are associated with features protective against longitudinal stress., Methods: HCWs across 7 hospitals in New York City, NY, were prospectively followed in an ongoing observational digital study using the custom Warrior Watch Study app. Participants wore an Apple Watch for the duration of the study to measure HRV throughout the follow-up period. Surveys measuring perceived stress, resilience, emotional support, quality of life, and optimism were collected at baseline and longitudinally., Results: A total of 361 participants (mean age 36.8, SD 10.1 years; female: n=246, 69.3%) were enrolled. Multivariate analysis found New York City's COVID-19 case count to be associated with increased longitudinal stress (P=.008). Baseline emotional support, quality of life, and resilience were associated with decreased longitudinal stress (P<.001). A significant reduction in stress during the 4-week period after COVID-19 diagnosis was observed in the highest tertial of emotional support (P=.03) and resilience (P=.006). Participants in the highest tertial of baseline emotional support and resilience had a significantly different circadian pattern of longitudinally collected HRV compared to subjects in the low or medium tertial., Conclusions: High resilience, emotional support, and quality of life place HCWs at reduced risk of longitudinal perceived stress and have a distinct physiological stress profile. Our findings support the use of these characteristics to identify HCWs at risk of the psychological and physiological stress effects of the pandemic., (©Robert P Hirten, Matteo Danieletto, Lewis Tomalin, Katie Hyewon Choi, Micol Zweig, Eddye Golden, Sparshdeep Kaur, Drew Helmus, Anthony Biello, Renata Pyzik, Claudia Calcagno, Robert Freeman, Bruce E Sands, Dennis Charney, Erwin P Bottinger, James W Murrough, Laurie Keefer, Mayte Suarez-Farinas, Girish N Nadkarni, Zahi A Fayad. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.09.2021.)

Robust phenotyping of patients from electronic health records (EHRs) at scale is a challenge in clinical informatics. Here, we introduce Phe2vec, an automated framework for disease phenotyping from EHRs based on unsupervised learning and assess its effectiveness against standard rule-based algorithms from Phenotype KnowledgeBase (PheKB). Phe2vec is based on pre-computing embeddings of medical concepts and patients' clinical history. Disease phenotypes are then derived from a seed concept and its neighbors in the embedding space. Patients are linked to a disease if their embedded representation is close to the disease phenotype. Comparing Phe2vec and PheKB cohorts head-to-head using chart review, Phe2vec performed on par or better in nine out of ten diseases. Differently from other approaches, it can scale to any condition and was validated against widely adopted expert-based standards. Phe2vec aims to optimize clinical informatics research by augmenting current frameworks to characterize patients by condition and derive reliable disease cohorts., Competing Interests: The authors declare no competing interests., (© 2021 The Authors.)

Total daily energy expenditure ("total expenditure") reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass-adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Background and Objectives: AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited., Design, Setting, Participants, & Measurements: Using data from adult patients hospitalized with COVID-19 from five hospitals from the Mount Sinai Health System who were admitted between March 10 and December 26, 2020, we developed and validated several models (logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme GradientBoosting [XGBoost; with and without imputation]) for predicting treatment with dialysis or death at various time horizons (1, 3, 5, and 7 days) after hospital admission. Patients admitted to the Mount Sinai Hospital were used for internal validation, whereas the other hospitals formed part of the external validation cohort. Features included demographics, comorbidities, and laboratory and vital signs within 12 hours of hospital admission., Results: A total of 6093 patients (2442 in training and 3651 in external validation) were included in the final cohort. Of the different modeling approaches used, XGBoost without imputation had the highest area under the receiver operating characteristic (AUROC) curve on internal validation (range of 0.93-0.98) and area under the precision-recall curve (AUPRC; range of 0.78-0.82) for all time points. XGBoost without imputation also had the highest test parameters on external validation (AUROC range of 0.85-0.87, and AUPRC range of 0.27-0.54) across all time windows. XGBoost without imputation outperformed all models with higher precision and recall (mean difference in AUROC of 0.04; mean difference in AUPRC of 0.15). Features of creatinine, BUN, and red cell distribution width were major drivers of the model's prediction., Conclusions: An XGBoost model without imputation for prediction of a composite outcome of either death or dialysis in patients positive for COVID-19 had the best performance, as compared with standard and other machine learning models., Podcast: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021&#95;07&#95;09&#95;CJN17311120.mp3., (Copyright © 2021 by the American Society of Nephrology.)

Thyroid disease is a very common condition that influences the entire human body, including cognitive function and mental health. As a result, thyroid disease has been associated with multiple neuropsychiatric conditions. However, the relationship between thyroid dysfunction and suicide is still controversial. We conducted a systematic review and meta-analysis to describe the association of thyroid function with suicidal behavior in adults. We searched four data bases (MEDLINE, EMBASE, PsycINFO, and Scopus) from their inception to 20 July 2018. Studies that reported mean values and standard deviation (SD) of thyroid hormone levels [Thyroid-stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), total thyroxine (TT4), and total triiodothyronine (TT3)] in patients with suicidal behavior compared with controls were included in this meta-analysis. The abstracts and papers retrieved with our search strategies were reviewed independently and in duplicate by four reviewers for assessment of inclusion criteria and data extraction, as well as for evaluation of risk of bias. Random-effects models were used in this meta-analysis to establish the mean difference on thyroid function tests between groups. Overall, 2278 articles were identified, and 13 studies met the inclusion criteria. These studies involved 2807 participants, including 826 participants identified with suicidal behavior. We found that patients with suicide behavior had lower levels of FT3 (-0.20 pg/mL; p = 0.02) and TT4 (-0.23 µg/dL; p = 0.045) compared to controls. We found no differences in either TSH, FT4, or TT3 levels among groups. With our search strategy, we did not identify studies with a comparison of overt/subclinical thyroid disease prevalence between patients with and without suicide behavior. The studies included in this meta-analysis had a low-to-moderate risk of bias. In the available literature, the evidence regarding the association of thyroid disorders and suicidal behavior is limited. We found that patients with suicidal behavior have significantly lower mean FT3 and TT4 levels when compared to patients without suicidal behavior. The clinical implications and pathophysiologic mechanisms of these differences remain unknown and further research is needed.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10 -8 ), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.

To address the need for low-cost analytical tools for on-site aquaculture water quality monitoring, miniaturized electrochemical sensor systems can be readily fabricated using additive manufacturing technologies such as 3D printing and inkjet printing. In this work, we report the design and fabrication of an additively manufactured electrochemical platform featuring a reusable 3D-printed electrochemical cell with integrated reference and counter electrodes, and a replaceable inkjet-printed Ag (IJP-Ag) working electrode. The electrochemical cell was 3D-printed with acrylonitrile butadiene styrene (ABS) filament and features a 3D-printed ABS-carbon counter electrode and a Ag|AgCl|gel-KCl reference electrode with a 3D-printed porous junction directly integrated along the sides of the sample compartment. The application of the integrated cell is demonstrated with the analysis of nitrate ions on the IJP-Ag electrode, which was modified with electrodeposited nanostructured Ag to enhance sensitivity to nitrate reduction. Linear sweep voltammetry (LSV) was successfully applied to detect nitrate with a LOD of 1.40 ppm and a sensitivity of 0.2086 μA ppm -1 in a background of artificial brackish aquaculture water (pH 8.0). The sensor response showed intra- and inter-electrode reproducibility and no significant interferences to most of the commonly encountered cations and anions in brackish water. The electrochemical sensor system was also applied to nitrate determination in real aquaculture water samples and demonstrated no significant differences with the results obtained using the standard spectrophotometric method at a 95% confidence level. Our results show how additive manufacturing is a promising approach to readily fabricate fit-for-purpose, low-cost miniaturized electrochemical sensor systems for point-of-use applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)