bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phenome-Wide Association Study of Actigraphy in the UK Biobank
Authors: Brooks Thomas G. , Lahens Nicholas F. , Grant Gregory R. , Sheline Yvette I. , FitzGerald Garret A. , Skarke Carsten 
Published: December 2021

AbstractWrist-worn accelerometer actigraphy devices present the opportunity for large-scale data collection from people during their daily lives. Using data from approximately 100,000 participants in the UK Biobank, actigraphy-derived measures of physical activity, sleep, and diurnal rhythms were associated in exploration and validation cohorts with a full phenome-wide set of diagnoses, biomarkers and metadata. Rhythmicity was captured by two independent models based on accelerometer and skin temperature harnessing behavioral (diurnal) and molecular (circadian) components. We found that robust rhythms significantly with biomarkers, survival, and phenotypes including diabetes, hypertension, mood disorders, and chronic airway obstruction; these associations were comparable to those with physical activity and sleep. Surprisingly, associations were mostly consistent between the sexes, while modulation by age was significant. More importantly, rhythms were found to be powerful predictors of future diseases: a two standard deviation difference in wrist temperature rhythms corresponded to increases in rate of diagnosis of 61% in diabetes, 38% in chronic airway obstruction, 27% in anxiety disorders, and 22% in hypertension. Our PheWAS of actigraphy data in the UK Biobank establishes that rhythmicity is fundamental to modeling disease trajectories, as are physical activity and sleep. Integration of long-term remote biosensing into patient care could thus afford an individualized approach to risk management.
Disruption in structural-functional network repertoire and time-resolved subcortical-frontoparietal connectivity in disorders of consciousness
Authors: Panda Rajanikant , Thibaut Aurore , Lopez-Gonzalez Ane , Escrichs Anira , Bahri Mohamed Ali , Hillebrand Arjan , Deco Gustavo , Laureys Steven , Gosseries Olivia , Annen Jitka , Tewarie Prejaas 
Published: December 2021

AbstractUnderstanding recovery of consciousness and elucidating its underlying mechanism is believed to be crucial in the field of basic neuroscience and medicine. Ideas such as the global neuronal workspace and the mesocircuit theory hypothesize that failure of recovery in conscious states coincide with loss of connectivity between subcortical and frontoparietal areas, a loss of the repertoire of functional networks states and metastable brain activation. We adopted a time-resolved functional connectivity framework to explore these ideas and assessed the repertoire of functional network states as a potential marker of consciousness and its potential ability to tell apart patients in the unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). In addition, prediction of these functional network states by underlying hidden spatial patterns in the anatomical network, i.e. so-called eigenmodes, were supplemented as potential markers. By analysing time-resolved functional connectivity from fMRI data, we demonstrated a reduction of metastability and functional network repertoire in UWS compared to MCS patients. This was expressed in terms of diminished dwell times and loss of nonstationarity in the default mode network and fronto-parietal subcortical network in UWS compared to MCS patients. We further demonstrated that these findings co-occurred with a loss of dynamic interplay between structural eigenmodes and emerging time-resolved functional connectivity in UWS. These results are, amongst others, in support of the global neuronal workspace theory and the mesocircuit hypothesis, underpinning the role of time-resolved thalamo-cortical connections and metastability in the recovery of consciousness.
A quantum-enhanced precision medicine application to support data-driven clinical decisions for the personalized treatment of advanced knee osteoarthritis: development and preliminary validation of precisionKNEE_QNN
Authors: Heidari Nima , Olgiati Stefano , Meloni Davide , Pirovano Federico , Noorani Ali , Slevin Mark , Azamfirei Leonard 
Published: December 2021

AbstractBackgroundThe clinical problem of knee osteoarthritis is that, although some novel therapies are safe and effective, the response is variable, and defining the features that predict individual response remains a challenge. Variational quantum-classical and quantum machine learning (QML) algorithms based on parameterized quantum circuits (PQC) are promising experimental technologies which can improve the efficiency of precision medicine clinical decision support systems (CDSS) based on real-world data stored in large unstructured databases. In this paper we tested a quantum neural network (QNN) application to support precision data-driven clinical decisions to select personalized treatments for advanced knee osteoarthritis.MethodsFollowing patients’ consent and Research Ethics Committee approval, we collected clinico-demographic data before and after the treatment from 170 patients eligible for knee arthroplasty (Kellgren-Lawrence grade ≥ 3, OKS ≤ 27, Age ≥ 64 and idiopathic aetiology of arthritis) treated over a 2 year period with a single injection of microfragmented fat. Gender classes were balanced (76 M, 94 F) to mitigate gender bias. A patient with an improvement ≥ 7 OKS has been considered a Responder. We trained our QNN Classifier on a randomly selected training subset of 113 patients to classify responders from non-responders (73 R, 40 NR) in pain and function at 1 year. Outliers were hidden from the training dataset but not from the validation set. We ran our QNN Classifier on a IBM quantum simulator to reduce the error due to noise.ResultsWe tested our QNN Classifier on a randomly selected test subset of 57 patients (34 R, 23 NR) including outliers. The No Information Rate was equal to 0.59. Our application correctly classified 28 Responders out of 34 and 6 non-Responders out of 23 (Sensitivity = 0.82, Specificity = 0.26, F1 Statistic= 0.71). The Positive (LR+) and Negative (LR-) Likelihood Ratios were respectively 1.11 and 0.68. The Diagnostic Odds Ratio (DOR) was equal to 2.ConclusionsPreliminary clinical and technical results of a QNN Classifier tested on a relatively small knee osteoarthritis dataset show that quantum machine learning applied to data-driven clinical decisions is a promising technology. Our results need further research validation with larger, real-world unstructured datasets, and clinical validation with an AI Clinical Trial to test model efficacy, safety, clinical significance and relevance at a public health level.
Residual insecticide surface treatment for preventing malaria: a systematic review protocol
Authors: Munn Zachary , Stone Jennifer C. , Barker Timothy Hugh , Price Carrie , Pollock Danielle , Kabaghe Alinune Nathanael , Gimnig John E. , Stevenson Jennifer C. 
Published: December 2021

AbstractIntroductionMalaria presents a significant global public health burden, although substantial progress has been made, with vector control initiatives such as indoor residual surface spraying with insecticides and insecticide treated nets. There now exists many different approaches to apply residual insecticide to indoor and outdoor surfaces in malaria endemic settings. This review aims to synthesise the best available evidence regarding full or partial indoor or outdoor residual insecticide surface treatment for preventing malaria.Methods and AnalysisThis review will comprehensively search the literature (both published and unpublished) for any studies investigating the effectiveness of residual insecticide surface treatment for malaria. Studies will be screened to meet the inclusion criteria by a minimum of two authors, followed by assessment of risk of bias (using appropriate risk of bias tools for randomised and non-randomised studies) and extraction of relevant information using structured forms by two independent authors. Meta-analysis will be carried out where possible for epidemiological outcomes such as malaria, anaemia, malaria related mortality, all-cause mortality and adverse effects. Certainty in the evidence will be established with GRADE assessments.Ethics and DisseminationA full review report will be submitted to the Vector Control & Insecticide Resistance Unit, Global Malaria Program, WHO. A version of this report will be submitted for publication in an open access peer-reviewed journal. The report will inform the development of WHO recommendations regarding residual insecticide treatment for malaria. This systematic review does not require ethics approval as it is a review of primary studies.RegistrationPROSPERO, ID 293194 (in progress as of 24thNovember, 2021)
Genuine Selective Caspase-2 Inhibition with new Irreversible Small Peptidomimetics
Authors: Bosc Elodie , Anastasie Julie , Soualmia Feryel , Coric Pascale , Kim Ju Youn , Lacin Gullen , Duplus Eric , Tixador Philippe , Brugg Bernard , Reboud-Ravaux Michelle , Bouaziz Serge , Karin Michael , El Amri Chahrazade , Jacotot Etienne 
Published: December 2021

AbstractCaspase-2 (Casp2) is a promising therapeutic target in several human diseases including nonalcoholic steatohepatitis (NASH) and Alzheimer’s disease (AD). However, the design of active-site-directed inhibitor selective to individual caspase family members is challenging because caspases have extremely similar active sites. Here we present new peptidomimetics derived from the VDVAD pentapeptide structure, harboring non-natural modifications at the P2 position and an irreversible warhead. Enzyme kinetics shows that these new compounds, such as LJ2 or its specific isomer LJ2a, and LJ3a, strongly and irreversibly inhibit Casp2 with genuine selectivity. According to Casp2 role in cellular stress responses, LJ2 inhibits cell death induced by microtubule destabilization or hydroxamic acid-based deacetylase inhibition. The most potent peptidomimetic, LJ2a, inhibits human Casp2 with a remarkably high inactivation rate (k3/Ki ~ 5 500 000 M−1s−1) and the most selective inhibitor, LJ3a, has a near to 1000 times higher inactivation rate on Casp2 as compared to Casp3. Structural analysis of LJ3a shows that spatial configuration of Cα at the P2 position determines inhibitor efficacy. In transfected human cell lines overexpressing site-1 protease (S1P), sterol regulatory element-binding protein 2 (SREBP2) and Casp2, LJ2a and LJ3a fully inhibit SREBP2 activation, suggesting a potential to prevent NASH development. Furthermore, in primary hippocampal neurons treated with β-amyloid oligomers, submicromolar concentrations of LJ2a and of LJ3a prevent synapse loss, indicating a potential for further investigations in AD treatment.
A novel framework for analysis of the shared genetic background of correlated traits
Authors: Svishcheva Gulnara R. , Tiys Evgeny S. , Elgaeva Elizaveta E. , Feoktistova Sofia G. , Timmers Paul R. H. J. , Sharapov Sodbo Zh. , Axenovich Tatiana I. , Tsepilov Yakov A. 
Published: December 2021

AbstractWe propose a novel effective framework for analysis of the shared genetic background for a set of genetically correlated traits using SNP-level GWAS summary statistics. This framework called SHAHER is based on the construction of a linear combination of traits by maximizing the proportion of its genetic variance explained by the shared genetic factors. SHAHER requires only full GWAS summary statistics and matrices of genetic and phenotypic correlations between traits as inputs. Our framework allows both shared and unshared genetic factors to be to effectively analyzed. We tested our framework using simulation studies, compared it with previous developments, and assessed its performance using three real datasets: anthropometric traits, psychiatric conditions and lipid concentrations. SHAHER is versatile and applicable to summary statistics from GWASs with arbitrary sample sizes and sample overlaps, allows incorporation of different GWAS models (Cox, linear and logistic) and is computationally fast.
Introduction ofloxPsites by electroporation in the mouse genome; a simple approach for conditional allele generation in complex targeting loci
Authors: Bernas Guillaume , Ouellet Mariette , Barrios Andréa , Jamann Hélène , Larochelle Catherine , Lévy Émile , Schmouth Jean-François 
Published: December 2021

AbstractBackgroundThe discovery of the CRISPR-Cas9 system and its applicability in mammalian embryos has revolutionized the way we generate genetically engineered animal models. To date, models harbouring conditional alleles (i.e.: twoloxPsites flanking an exon or a critical DNA sequence of interest) remain the most challenging to generate as they require simultaneous cleavage of the genome using two guides in order to properly integrate the repair template. In the current manuscript, we describe a modification of the sequential electroporation procedure described by Horiiet al(2017). We demonstrate production of conditional allele mouse models for eight different genes via one of two alternative strategies: either by consecutive sequential electroporation (strategy A) or non-consecutive sequential electroporation (strategy B).ResultsBy using strategy A, we demonstrated successful generation of conditional allele models for three different genes (Icam1, Lox, andSar1b), with targeting efficiencies varying between 5 to 13%. By using strategy B, we generated five conditional allele models (Loxl1, Pard6a, Pard6g, Clcf1, andMapkapk5), with targeting efficiencies varying between 3 to 25%.ConclusionOur modified electroporation-based approach, involving one of the two alternative strategies, allowed the production of conditional allele models for eight different genes via two different possible paths. This reproducible method will serve as another reliable approach in addition to other well-established methodologies in the literature for conditional allele mouse model generation.
In silico evidence of superantigenic features in ORF8 protein from COVID-19
Authors: Gómez-Icazbalceta Guillermo , Hussain Zubair , Vélez-Alavez Marcela 
Published: December 2021

AbstractVery early on COVID-19 pandemic outbreak, it was noted that the some of the virus-induced clinical conditions resembled features of toxaemia caused by the toxic shock syndrome toxin type 1, which is a soluble superantigen produced byStaphylococcus aureus. Among all SARS proteins, the ORF8 protein from SARS-2 virus is significantly different from other known SARS-like coronaviruses, and therefore could exhibit unique pathogenic properties. We assess if ORF8 protein bears super antigenic features usingin silicotools. We show that ORF8 has properties of an extracellular soluble protein and shares a significant degree of amino acid sequence identity with toxic shock syndrome toxin. Besides, docking and binding affinity analyses between monomeric and homodimeric ORF-8 with Vβ 2.1 and TRBV11-2 reveal strong interaction and high binding affinity. ORF8-TRBV11-2 strong interaction can contribute to the observed clonal expansion of that chain during COVID-19-associated multisystem inflammatory syndrome. Taken together, the evidence presented here supports the hypothesis that ORF8 protein from SARS-2 bears super antigenic properties.
Connectome-wide association analysis identified significant brain functional alteration in adults with attention-deficit/hyperactivity disorder
Authors: Liu Lu , Chen Di , Huang Fang , Jia Tianye , Pan Meirong , Zhao Mengjie , Bu Xuan , Wang Yufeng , Cao Miao , Qian Qiujin , Feng Jianfeng 
Published: December 2021

AbstractAdults with attention-deficit/hyperactivity disorder (ADHD), as an extreme-phenotype of ADHD, is still facing problems of inconsistency and undeciphered mechanisms for its neuropathology. To address this matter, our present study performed connecotome-wide voxel-based analyses with the resting-state fMRI data of 84 adults with ADHD and 89 healthy controls. We found that functional connectivity patterns of the left precuneus and the left middle temporal significantly altered in ADHD populations serving as potential neural biomarkers to distinguish ADHD with healthy controls, with subsequent seed-based analysis revealing the dysfunction of functional connections both intra- and inter-default mode and attention networks, among which middle temporal gyrus plays the key role of ‘bridge’ linking the default mode and attention networks. After cognitive behavioral therapy, two of these ADHD-altered functional connections ameliorated accompanied with improvement of ADHD core symptoms. Additionally, imaging genetic analyses also revealed close relationships between the observed brain functional alterations and ADHD-risk genes. Taken together, our findings suggested the interference of default mode on attention networks in adults with ADHD, which would be severing as a potential biomarker for both ADHD pathogenesis and treatment effects.
Potential inhibitors for blocking the interaction of the coronavirus SARS-CoV-2 spike protein and its host cell receptor ACE2
Authors: Li Changzhi , Zhou Hongjuan , Guo Lingling , Xie Dehuan , He Huiping , Zhang Hong , Liu Yixiu , Peng Lixia , Zheng Lisheng , Lu Wenhua , Mei Yan , Liu Zhijie , Huang Jie , Wang Mingdian , Shu Ditian , Ding Liuyan , Lang Yanhong , Luo Feifei , Wang Jing , Huang Bijun , Huang Peng , Gao Song , Chen Jindong , Qian Chao-Nan 
Published: December 2021

ABSTRACTThe outbreak of SARS-CoV-2 continues to pose a serious threat to human health and social and economic stability. In this study, we established an anti-coronavirus drug screening platform based on the Homogeneous Time Resolved Fluorescence (HTRF) technology and the interaction between the coronavirus S protein and its host receptor ACE2. This platform is a rapid, sensitive, specific, and high throughput system. With this platform, we screened two compound libraries of 2,864 molecules and identified three potential anti-coronavirus compounds: tannic acid (TA), TS-1276 (anthraquinone), and TS-984 (9-Methoxycanthin-6-one). Our in vitro validation experiments indicated that TS-984 strongly inhibits the interaction of the coronavirus S-protein and the human cell ACE2 receptor. This data suggests that TS-984 is a potent blocker of the interaction between the S-protein and ACE2, which might have the potential to be developed into an effective anti-coronavirus drug.SIGNIFICANCEThe ongoing pandemic of COVID-19 caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made a serious threat to public health worldwide. Given the urgency of the situation, researchers are attempting to repurpose existing drugs for treating COVID-19. In this present study, we screened two compound libraries of 2,864 molecules and identified a potent inhibitor (TS-984) for blocking the coronavirus S-protein and the human cell ACE2 receptor. TS-984 might have the potential to be developed into an effective anti-coronavirus drug for treating COVID-19.
A unified model for the biogenesis of mitochondrial outer membrane multi-span proteins
Authors: Zhou Jialin , Jung Martin , Dimmer Kai S. , Rapaport Doron 
Published: December 2021

AbstractThe mitochondrial outer membrane (MOM) harbors proteins that traverse the membrane via several helical segments, so-called multi-span proteins. Two contradicting mechanisms were suggested to describe their integration into the MOM. The first proposes that the mitochondrial import (MIM) complex facilitates this process and functions as an insertase, whereas the second suggests that such proteins can integrate into the lipid phase without the assistance of import factors in a process that is enhanced by phosphatidic acid. To resolve this discrepancy and obtain new insights on the biogenesis of these proteins, we addressed this issue using yeast mitochondria and the multi-span protein Om14. Testing different truncation variants, we show that only the full-length protein contains all the required information that assure targeting specificity. Employing a specific insertion assay and several single and double deletion strains, we show that neither the import receptor Tom70 nor any other protein with a cytosolically exposed domain have a crucial contribution to the biogenesis process. We further demonstrate that Mim1 and Porin are required for optimal membrane integration of Om14 but none of them is absolutely required. Unfolding of the newly synthesized protein, its optimal hydrophobicity, as well as higher fluidity of the membrane dramatically enhanced the import capacity of Om14. Collectively, our findings suggest that MOM multi-span proteins can follow different biogenesis pathways in which proteinaceous elements and membrane behavior contribute to a variable extent to the combined efficiency.SummaryZhou et al. provide new insights to the biogenesis of mitochondrial outer membrane proteins. They demonstrate that such proteins can follow various routes where both proteinaceous elements and membrane behavior regulate the efficiency and specificity of this process.
Institutional ethnoracial discrimination and microaggressions among a diverse sample of undergraduates at a minority-serving university: a gendered racism approach
Authors: Lui Florence , Anglin Deidre M. 
Published: December 2021

PurposeEthnoracial minorities report a variety of discriminatory experiences due to systemic racism. Yet, few studies have examined whether gender and race/ethnicity interact to predict institutional discrimination and racial microaggressions through an intersectional approach.Design/methodology/approachA predominantly female (60%), ethnoracial minority (20.8% Black, 31.6% Asian, 30.8% Latina/o, 8.2% White, 6.6% Middle Eastern) sample of 895 undergraduates attending a minority-serving public university in an urban setting completed self-report measures of sociodemographic characteristics, experiences of racial microaggressions and institutional discrimination.FindingsSignificant (p < 0.05) gender × race/ethnicity interaction effects were found in several institutional discrimination domains: Males reported more police/court discrimination overall, but gender differences in police/court discrimination were less pronounced for non-Black vs Black students. While males tended to report more institutional discrimination than females, the reverse was true for the Middle Eastern group: Middle Eastern females reported institutional discrimination in more domains and more discrimination getting hired than their male counterparts. There was a significant race/ethnicity × gender interaction effect for environmental microaggressions: White males reported more environmental microaggressions than White females, but gender differences were not found in the overall sample.Originality/valueThis study is the first to the authors’ knowledge to assess the interactive effects of gender and ethnicity on the type of microaggressions experienced in a diverse sample that includes individuals of Middle Eastern descent. The authors highlight the range of discriminatory events that ethnoracially minoritized undergraduates experience, even at a minority-serving institution.