bluuebunny/crossref_metadata_2025_split huggingface dataset:
Context- and scale-dependent effects of thymol bioactivity on biological networks: contributions from quail under heat stress
Authors: Fernandez Maria Emilia , Bonansea Rocío Inés , Mas Agustin Lucini , Baroni María Verónica , Marin Raul Hector , Labaque Maria Carla , Kembro Jackelyn M. 
Published: June 2022

AbstractA defining feature of healthy function is adaptability, the capacity to dynamically respond to novel and/or unpredictable factors, such as exposition to environmental challenges. Here we explore the role of context (i.e., order in which factors are applied) on the configuration of networks of behavioral and physiological traits from Japanese quail that were supplemented dietary thymol prior, jointly or after onset of a chronic heat stress protocol (i.e., supplementation strategies). Basal diet and standard environmental temperature were used as controls. We begin by showing that each supplementation strategy evolved differently over the 5-week experimental period in regard to body weight and feed- intake. At the end of this experimental period, context-dependency was also observed in the non- trivial functional relationships among 27 traits from 4 subsystems from distinct spatial-temporal scales. When considered separately, whole-organism level subsystems (i.e. somatic maintenance and egg production traits), are predominantly functionally related to environmental temperature. Conversely, at the molecular level, the liveŕs antioxidant system response is fundamentally dominated by the supplementation strategy. Interestingly, the serum’s antioxidant system shows an intermediate response, not dominated by a given factor. Overall, network configurations were highly dependent on context, and could be associated with specific induced physiological states. Our work constitutes the first study that includes network, integrative, and experimentally comparative analyses applied to the field of dietary supplementation under environmental challenges. This perspective could help understand complex biological responses important for developing efficient and welfare orientated supplementation protocols for farm animals and for interpreting the background in this field.
Exome-wide association studies discover germline mutation patterns and identify high-risk populations in human cancers
Authors: Shen Sipeng , Jiang Yunke , Wang Guanrong , Li Hongru , You Dongfang , Duan Weiwei , Zhang Ruyang , Wei Yongyue , Shen Hongbing , Hu Zhibin , Christiani David C. , Zhao Yang , Chen Feng 
Published: June 2022

AbstractGenome-wide association studies have discovered numerous common variants associated with human cancers. However, the contribution of exome-wide rare variants to cancers remains largely unexplored, especially for the protein-coding variants. The UK Biobank provides detailed cancer follow-up information linked to whole-exome sequencing (WES) for approximately 450,000 participants, offering an unprecedented opportunity to evaluate the effect of exome variation on pan-cancer. Here, we performed exome-wide association studies (ExWAS) based on single variant levels and gene levels to detect their associations across 20 primary cancer types in the discovery set (WES-300k, N = 284,456) and replication set (WES-150k, N = 143,478), separately. The ExWAS detected 143 independent variants at variant-level and 49 genes at gene-level, while nine variants and eight genes were shared across cancers. In the cross-trait meta-analysis, we identified 239 additional independent pleiotropic variants, mapping to the genes which were functional through trans-omics analyses in transcriptomics and proteomics. Further, we developed exome-wide risk scores (ERS) to identify high-risk populations based on rare variants with minor allele frequency (MAF) < 0.05. The ERS had satisfactory performance in cancer risk stratification, especially for the extremely high-risk persons (top 5% ERS) that were frequently risk allele carriers. The ERS (median C-index (IQR): 0.655 (0.636-0.667)) outperforms the traditional polygenic risk score (PRS) (median C-index (IQR): 0.585 (0.572-0.614)) for discrimination in the replication set. Our findings offer further insight into the genetic architecture of human exomes for cancer susceptibility.
Genetic risk, parental history, and suicide attempts in a diverse sample of US adolescents
Authors: Barzilay Ran , Visoki Elina , Schultz Laura M , Warrier Varun , Daskalakis Nikolaos P , Almasy Laura 
Published: June 2022

AbstractBackgroundAdolescent suicide is a major health problem in the US marked by a recent increase in Black/African American youth suicide trends. While genetic factors partly account for familial transmission of suicidal behavior, it is not clear whether polygenic risk scores of suicide attempt have clinical utility in youth suicide risk classification.ObjectivesTo evaluate the contribution of a polygenic risk score for suicide attempt (PRS-SA) in explaining variance in suicide attempt by early adolescence.MethodsWe studied N=5,214 non-related Black and White youth from the Adolescent Brain Cognitive Development (ABCD) Study (ages 8.9-13.8 years) who were evaluated between 2016 and 2021. Regression models tested associations between PRS-SA and parental history of suicide attempt/death with youth-reported suicide attempt. Covariates included age, sex, and race.ResultsOver three waves of assessments, 182 youth (3.5%) reported a past suicide attempt, with Black youth reporting significantly more suicide attempts than their White counterparts (6.1% vs 2.8%, P<.001). PRS-SA was associated with suicide attempt (odds ratio [OR]=1.3, 95% confidence interval [CI] 1.1-1.5, P=.001). Inclusion of PRS-SA explained 2.7% of the variance in suicide attempts, significantly more than the base model including only age, sex and race, which explained 1.9% of the variance (P=.001). Parental history of suicide attempt/death was also associated with youth suicide attempt (OR=2.9, 95%CI 1.9-4.4, P<.001). Addition of PRS-SA to the model that included parental history significantly increased the variance explained from 3.3% to 4% (P=.002).ConclusionsFindings suggest that PRS-SA may be useful for suicide risk classification in diverse youth.Contribution to the Field StatementAdolescent suicidal behavior is a major health problem, with suicide being the 2nd leading cause of death in youth. Research that improves our understanding regarding drivers of suicide risk in youth can inform youth suicide prevention strategies. Family history of suicide is an established risk factor for youth suicidal behavior. Current methods in psychiatric genetics allow calculation of polygenic risk scores that represent genetic liability to specific conditions. It is not clear whether polygenic risk score of suicide attempt can assist in risk classification, beyond family history. In this work, we show that in a sample of 5,214 youth ages 9-13, of which 3.5% reported past suicide attempt, polygenic score of suicide attempt was associated with youth suicide attempt. This association additively explained variance over and above parental history of suicide attempt/death. Findings make a case for the potential utility of incorporating polygenic risk scores as part of suicide attempt risk classification in youth, and suggest that polygenic scores may reveal genetic liability that is not captured by family history of suicide.
Rapid Response for Notification of Monkeypox Exposure, Exposure Risk Assessment and Stratification, and Symptom Monitoring
Authors: Simpson Lynn A. , Macdonald Kaitlin , Searle Eileen F. , Shearer Jennifer A. , Dimitrov Dimitar , Foley Daniel , Morales Eduardo , Shenoy Erica S. 
Published: June 2022

ABSTRACTObjectivePublic health authorities recommend symptom monitoring of healthcare personnel (HCP) after defined exposures to Monkeypox (MPX). We report on the rapid development and implementation of mobile responsive survey solutions for notification of possible exposure, exposure risk assessment and stratification, and symptom monitoring.SettingAcademic health center in Boston, Massachusetts, after admission of first diagnosed case of MPX in the United States during the current global outbreak.ParticipantsResearch Electronic Data Capture (REDCap) design and programmers, Infection Control, Occupational Health, and Emergency Preparedness specialists, and HCP with possible exposure to MPX.InterventionsDesign and deployment of Research Electronic Data Capture (REDCap) tools to identify HCP with possible exposure to MPX, perform exposure risk assessment and stratification for post-exposure prophylaxis (PEP), and conduct symptom monitoring during the exposure window. Project enhancements included dashboards for HCP tracking and SMS text reminders for symptom monitoring.ResultsTools to support the contact tracing and exposure investigation were deployed within 24 hours of identification of a patient with suspected MPX, with the full suite in production within 4 days of confirmation of the diagnosis of MPX. Clinical follow up of HCP was integrated into the design, and real-time versioning allowed for adjustments leading to improvements in HCP symptom monitoring compliance and enhanced tracking.ConclusionsDuring the current MPX outbreak, timely and comprehensive evaluation of potential HCP exposures is necessary but presents logistical challenges. Rapid development of MPX-specific solutions using REDCap enabled flexibility in design and approach, and integration of targeted clinical support enhanced functionality.
Prevalence of COVID-19 and Long COVID in Collegiate Student Athletes from Spring 2020 to Fall 2021: A Retrospective Survey
Authors: Massey Daisy , Saydah Sharon , Adamson Blythe , Lincoln Andrew , Aukerman Douglas F. , Berke Ethan M. , Sikka Robby , Krumholz Harlan M. 
Published: June 2022

AbstractSymptomatic COVID-19 and post-COVID conditions, also referred to as post-acute sequelae of SARS-CoV-2 (PASC) or Long COVID, have been widely reported in young, healthy people, but their prevalence has not yet been determined in student athletes. We surveyed a convenience sample of 18 collegiate school administrators, representing about 7,000 student athletes. According to their survey responses, 9.8% of student athletes tested positive for COVID-19 in spring 2020 and 25.4% tested positive in the academic year of fall 2020 to spring 2021. About 4% of student athletes who tested positive from spring 2020 to spring 2021 developed Long COVID, defined as new, recurring, or ongoing physical or mental health consequences occurring 4 or more weeks after SARS-CoV-2 infection. This study highlights that Long COVID occurs in healthy collegiate athletes and merits a larger study to determine population-wide prevalence.
A nomogram to predict failure rate in immediate implant-based breast reconstruction
Authors: Zhu Meizhen , Zhang Fanrong , Mao Jiefei , Fang Jun , Chen Daobao 
Published: June 2022

AbstractControversies on risk factors affecting immediate implant-based breast reconstruction (IBBR) still exist. We aimed to evaluate risk factors of reconstruction failure (RF) in immediate IBBR. We retrospectively reviewed 239 patients (241 breasts) who underwent immediate IBBR from 2011 to 2019. A nomogram was established to predict RF rate in stage I operation and logistic regression model was created for stage II operation. 14 (5.81%) and 7 (5.51%) reconstructive breasts experienced RF in stage I and II operation, respectively. Body mass index (BMI) [odds ratio (OR)=1.569, 95% confidence interval (CI): 1.087-2.263, p=0.016], implant/tissue expander (TE) volume>86.30% (OR=5.711, 95% CI: 1.067-30.583, p=0.042), adjuvant chemotherapy (ACT) (OR=30.094, 95% CI: 2.030-446.084, p=0.013) were independent risk factors for RF in stage I operation. The nomogram to predict RF rate in stage I operation revealed area under the curve (AUC) was 0.920 (95% CI: 0.844-0.995). Logistic regression demonstrated that mesh use was the independent predictor of RF in stage II operation (OR=47.326, 95% CI: 3.11-720.081, p=0.005). The nomogram exhibited satisfied predictive ability. Present findings enhanced our understanding of the risk factors contributing to RF and might lead us clinical decision to improve the outcome of immediate IBBR.
High-Coverage Four-Dimensional Data-Independent Acquisition Proteomics and Phosphoproteomics Enabled by Deep Learning-Driven Multi-Dimensional Prediction
Authors: Chen Moran , Zhu Pujia , Wu Pengfei , Hao Yanhong , Zhang Zhourui , Sun Jian , Nie Wenjing , Chen Suming 
Published: June 2022

AbstractFour-dimensional (4D) data-independent acquisition (DIA)-based proteomics is an emerging technology that has been proven to have high precursor ion sampling efficiency and higher precursor identification specificity. However, the current 4D DIA proteomics is still dependent on the building of project-specific experimental library which is time-consuming and limits the coverage for identification/quantification. Herein, a workflow of 4D DIA proteomics by using the predicted multi-dimensional in silico library was established. A deep learning model Deep4D that could high-accurately predict the CCS and RT of both the unmodified and phosphorylated peptides was developed. By using an integrated 4D in silico library containing millions of peptides, we have identified 25% more protein than using experimental libraries in the DIA proteomics analysis of HeLa cells. We further demonstrate that the introduction of in silico prediction library can greatly complement the experimental library of directly obtained phosphorylated peptides, resulting in a greater increase in the identification of phosphorylated peptides and phosphorylated proteins.
Lowering of circulating sclerostin may increase risk of atherosclerosis and its risk factors: evidence from a genome-wide association meta-analysis followed by Mendelian randomization
Authors: Zheng Jie , Wheeler Eleanor , Pietzner Maik , Andlauer Till , Yau Michelle , Hartley April E. , Brumpton Ben Michael , Rasheed Humaira , Kemp John P , Frysz Monika , Robinson Jamie , Reppe Sjur , Prijatel Vid , Gautvik Kaare M , Falk Louise , Maerz Winfried , Gergei Ingrid , Peyser Patricia A , Kavousi Maryam , de Vries Paul S. , Miller Clint L. , Bos Maxime , van der Laan Sander W. , Malhotra Rajeev , Herrmann Markus , Scharnagl Hubert , Kleber Marcus , Dedoussis George , Zeggini Eleftheria , Nethander Maria , Ohlsson Claes , Lorentzon Mattias , Wareham Nick , Langenberg Claudia , Holmes Michael V. , Smith George Davey , Tobias Jonathan H. 
Published: June 2022

ABSTRACTSclerostin inhibition is a new therapeutic approach for increasing bone mineral density (BMD) but its cardiovascular safety is unclear. We conducted a genome-wide association study (GWAS) meta-analysis of circulating sclerostin in 33,961 Europeans followed by Mendelian randomization (MR) to estimate the causal effects of sclerostin on 15 atherosclerosis-related diseases and risk factors. GWAS meta-analysis identified 18 variants independently associated with sclerostin, which including a novel cis signal in the SOST region and three trans signals in B4GALNT3, RIN3 and SERPINA1 regions that were associated with opposite effects on circulating sclerostin and eBMD. MR combining these four SNPs suggested lower sclerostin increased hypertension risk (odds ratio [OR]=1.09, 95%CI=1.04 to 1.15), whereas bi-directional analyses revealed little evidence for an effect of genetic liability to hypertension on sclerostin levels. MR restricted to cis (SOST) SNPs additionally suggested sclerostin inhibition increased risk of type 2 diabetes (T2DM) (OR=1.26; 95%CI=1.08 to 1.48) and myocardial infarction (MI) (OR=1.31, 95% CI=1.183 to 1.45). Furthermore, these analyses suggested sclerostin inhibition increased coronary artery calcification (CAC) (β=0.74, 95%CI=0.33 to 1.15), levels of apoB (β=0.07; 95%CI=0.04 to 0.10; this result was driven by rs4793023) and triglycerides (β=0.18; 95%CI=0.13 to 0.24), and reduced HDL-C (β=-0.14; 95%CI=-0.17 to -0.10). This study provides genetic evidence to support a causal effect of sclerostin inhibition on increased hypertension risk. Cis-only analyses suggested that sclerostin inhibition additionally increases the risk of T2DM, MI, CAC, and an atherogenic lipid profile. Together, our findings reinforce the requirement for strategies to mitigate against adverse effects of sclerostin inhibitors like romosozumab on atherosclerosis and its related risk factors.
Managing the evidence infodemic: Automation approaches used for developing NICE COVID-19 living guidelines
Authors: Sood Mariam , Sharp Steve , McFarlane Emma , Willans Robert , Hopkins Kathryn , Karpusheff Justine , Glen Fiona 
Published: June 2022

AbstractBackground and ObjectivesThe National Institute for Health and Care Excellence (NICE) produces evidence-based guidance and advice for health, public health and social care practitioners in England and Wales. Between March 2020 and March 2022, NICE produced 24 COVID-19 guidelines to support healthcare workers during the COVID-19 pandemic. This article outlines three automation strategies NICE utilised to facilitate faster processing of evidence on COVID-19 and describes the value of those approaches when there is an increasing volume of evidence and demand on resources.Study Design and SettingText classification using machine learning, and regular expression-based pattern matching were used to automate screening of literature search results. Relevant clinical trials were tracked by automated monitoring of clinical trial databases and Pubmed.ResultsThe strategies discussed here brought considerable efficiencies in the processing time without impacting on quality compared to equivalent manual efforts. Additionally, the paper illustrates how to incorporate automation into established processes of the evidence management pipeline.ConclusionsWe have demonstrated through testing and use in live guideline development and surveillance that these are effective and low risk approaches at managing high volumes of evidence.Highlights-To illustrate how NICE utilised automation to handle the Covid-19 ‘infodemic’-managing the ‘infodemic’ of evidence surveillance is a shared global issue.-To outline automation strategies to facilitate faster processing of evidence, especially when there is an increasing volume of evidence and demand on resources.-How automation can be included in established processes without disrupting business as usual operations.-Automation can take many forms, and depending on risk appetite, can be supplemented with manual checking.-Automation can be adopted easily with the right tools and techniques.
Variable-Selection ANOVA Simultaneous Component Analysis (VASCA)
Authors: Camacho José , Vitale Raffaele , Morales-Jimenez David , Gómez-Llorente Carolina 
Published: June 2022

AbstractMotivationANOVA Simultaneous Component Analysis (ASCA) is a popular method for the analysis of multivariate data yielded by designed experiments. Meaningful associations between factors/interactions of the experimental design and measured variables in the data set are typically identified via significance testing, with permutation tests being the standard go-to choice. However, in settings with large numbers of variables, the “holistic” testing approach of ASCA (all variables considered) often overlooks statistically significant effects encoded by only a few variables.ResultsWe propose Variable-selection ASCA (VASCA), a method that generalizes ASCA through variable selection, augmenting its statistical power without inflating the Type-I error risk. The method is evaluated with simulations and with a real data set from a multi-omic clinical experiment. We show that VASCA is more powerful than both ASCA and the widely-adopted False Discovery Rate (FDR) controlling procedure; the latter is used as a benchmark for variable selection based on multiple significance testing. We further illustrate the usefulness of VASCA for exploratory data analysis in comparison to the popular Partial Least Squares Discriminant Analysis (PLS-DA) method and its sparse counterpart (sPLS-DA).AvailabilityThe code for VASCA is available in the MEDA Toolbox athttps://github.com/josecamachop/MEDA-ToolboxContactjosecamacho@ugr.esSupplementary informationSupplementary data are available atBioinformaticsonline.
Mitochondrial MICOS complex genes, implicated in hypoplastic left heart syndrome, maintain cardiac contractility and actomyosin integrity
Authors: Birker Katja , Kirkland Natalie J. , Theis Jeanne L. , Fogarty Zachary C. , Missinato Maria Azzurra , Kalvakuri Sreehari , Grossfeld Paul , Engler Adam J. , Ocorr Karen , Nelson Timothy J. , Colas Alexandre R. , Olson Timothy M. , Vogler Georg , Bodmer Rolf 
Published: June 2022

ABSTRACTHypoplastic left heart syndrome (HLHS) is a severe congenital heart disease (CHD) with a likely oligogenic etiology, but our understanding of the genetic complexities and pathogenic mechanisms leading to HLHS is limited. We therefore performed whole genome sequencing (WGS) on a large cohort of HLHS patients and their families to identify candidate genes that were then tested in Drosophila heart model for functional and structural requirements. Bioinformatic analysis of WGS data from an index family comprised of a HLHS proband born to consanguineous parents and postulated to have a homozygous recessive disease etiology, prioritized 9 candidate genes with rare, predicted damaging homozygous variants. Of the candidate HLHS gene homologs tested, cardiac-specific knockdown (KD) of mitochondrial MICOS complex subunit dCHCHD3/6 resulted in drastically compromised heart contractility, diminished levels of sarcomeric actin and myosin, reduced cardiac ATP levels, and mitochondrial fission-fusion defects. Interestingly, these heart defects were similar to those inflicted by cardiac KD of ATP synthase subunits of the electron transport chain (ETC), consistent with the MICOS complex’s role in maintaining cristae morphology and ETC complex assembly. Analysis of 183 genomes of HLHS patient-parent trios revealed five additional HLHS probands with rare, predicted damaging variants in CHCHD3 or CHCHD6. Hypothesizing an oligogenic basis for HLHS, we tested 60 additional prioritized candidate genes in these cases for genetic interactions with CHCHD3/6 in sensitized fly hearts. Moderate KD of CHCHD3/6 in combination with Cdk12 (activator of RNA polymerase II), RNF149 (E3 ubiquitin ligase), or SPTBN1 (scaffolding protein) caused synergistic heart defects, suggesting the potential involvement of a diverse set of pathways in HLHS. Further elucidation of novel candidate genes and genetic interactions of potentially disease-contributing pathways is expected to lead to a better understanding of HLHS and other CHDs.