bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epigenetic contributions to clinical risk prediction of cardiovascular disease
Authors: Chybowska Aleksandra D , Gadd Danni A , Cheng Yipeng , Bernabeu Elena , Campbell Archie , Walker Rosie M , McIntosh Andrew M , Wrobel Nicola , Murphy Lee , Welsh Paul , Sattar Naveed , Price Jackie F , McCartney Daniel L , Evans Kathryn L , Marioni Riccardo E 
Published: October 2022

AbstractBackground and AimsCardiovascular disease (CVD) is among the leading causes of death worldwide. Discovery of new omics biomarkers could help to improve risk stratification algorithms and expand our understanding of molecular pathways contributing to the disease. Here, ASSIGN – a cardiovascular risk prediction tool recommended for use in Scotland – was examined in tandem with epigenetic and proteomic features in risk prediction models in ý12,657 participants from the Generation Scotland cohort.MethodsPreviously generated DNA methylation-derived epigenetic scores (EpiScores) for 109 protein levels were considered, in addition to both measured levels and an EpiScore for cardiac troponin I (cTnI). The associations between individual protein EpiScores and the CVD risk were examined using Cox regression (ncasesý1,274; ncontrolsý11,383) and visualised in a tailored R application. Splitting the cohort into independent training (n=6,880) and test (n=3,659) subsets, a composite CVD EpiScore was then developed.ResultsSixty-five protein EpiScores were associated with incident CVD independently of ASSIGN and the measured concentration of cTnI (P<0.05), over a follow up of up to 16 years of electronic health record linkage. The most significant EpiScores were for proteins involved in metabolic, immune response and tissue development/regeneration pathways. A composite CVD EpiScore (based on 45 protein EpiScores) was a significant predictor of CVD risk independent of ASSIGN and the concentration of cTnI (Hazard Ratio HR=1.32, P=3.7×10-3, 0.3% increase in C-statistic).ConclusionsEpiScores for circulating protein levels are associated with CVD risk independent of traditional risk factors and may increase our understanding of the aetiology of the disease.Graphical abstractStructural graphical abstractASSIGN – a cardiovascular risk prediction tool recommended for use in Scotland – was examined in tandem with epigenetic and proteomic features in risk prediction models in ζ12,657 participants from the Generation Scotland cohort. Cox regression was used to model the association between individual predictors and CVD hospitalisation events ascertained over 16 years of follow-up. Finally, a composite protein EpiScore was developed (based on the protein EpiScores) and its predictive performance was tested. CVD – Cardiovascular Disease, EpiScore – Epigenetic Score, Cox PH – Cox Proportional Hazards Regression, DNAm – DNA methylation.
Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 infection (PASC) in a Large Academic Medical Center in the US
Authors: Fritsche Lars G. , Jin Weijia , Admon Andrew J. , Mukherjee Bhramar 
Published: October 2022

AbstractObjectiveA growing number of Coronavirus Disease-2019 (COVID-19) survivors are affected by Post-Acute Sequelae of SARS CoV-2 infection (PACS). Using electronic health records data, we aimed to characterize PASC-associated diagnoses and to develop risk prediction models.MethodsIn our cohort of 63,675 COVID-19 positive patients, 1,724 (2.7 %) had a recorded PASC diagnosis. We used a case control study design and phenome-wide scans to characterize PASC-associated phenotypes of the pre-, acute-, and post-COVID-19 periods. We also integrated PASC-associated phenotypes into Phenotype Risk Scores (PheRSs) and evaluated their predictive performance.ResultsIn the post-COVID-19 period, known PASC symptoms (e.g., shortness of breath, malaise/fatigue) and musculoskeletal, infectious, and digestive disorders were enriched among PASC cases. We found seven phenotypes in the pre-COVID-19 period (e.g., irritable bowel syndrome, concussion, nausea/vomiting) and 69 phenotypes in the acute-COVID-19 period (predominantly respiratory, circulatory, neurological) associated with PASC. The derived pre- and acute-COVID-19 PheRSs stratified risk well, e.g., the combined PheRSs identified a quarter of the COVID-19 positive cohort with an at least 2.9-fold increased risk for PASC.ConclusionsThe uncovered PASC-associated diagnoses across categories highlighted a complex arrangement of presenting and likely predisposing features, some with a potential for risk stratification approaches.Graphical Abstract
Gene-vegetarianism interactions in calcium, testosterone, and eGFR identified in genome-wide analysis across 30 biomarkers
Authors: Francis Michael , Ye Kaixiong 
Published: October 2022

AbstractExisting vegetarian cohort studies have not considered the effects of genetic differences on health outcomes. First, we reduced inconsistencies among self-identified vegetarians in UK Biobank by utilizing two dietary surveys. Vegetarians were matched 1:4 with nonvegetarians for traditional association analyses, revealing significant effects of vegetarianism in 15/30 biomarkers. Cholesterol measures plus Vitamin D were significantly lower in vegetarians, while triglycerides were higher. A genome-wide association study revealed no genome-wide significant (GWS) associations with vegetarianism status. We performed genome-wide gene-vegetarianism interaction analyses for 30 biomarker traits (N=147,253). We detected a GWS interaction in calcium at rs72952628 (P=4.47×10−8). rs72952628 is inMMAA, a B12metabolism gene; B12has high deficiency potential in vegetarians. Gene-based interaction tests revealed two significant genes,RNF168in testosterone (P=1.45×10−6) andDOCK4in eGFR (P=6.76×10−7), which have previously been associated with testicular and renal traits, respectively. These findings indicate genotype can influence biomarker levels across vegetarians.
The Antidepressant Advisor (ADeSS): A Decision Support System for Antidepressant Treatment for Depression in UK primary care – a feasibility study
Authors: Harrison Phillippa , Carr Ewan , Goldsmith Kimberley , Young Allan H. , Ashworth Mark , Fennema Diede , Duan Suqian , Barrett Barbara , Zahn Roland 
Published: October 2022

AbstractObjectivesTo develop and probe the first computerised decision-support tool to provide antidepressant treatment guidance to GPs in UK primary care.DesignA parallel group, cluster-randomised controlled feasibility trial, where individual participants were blind to treatment allocation.SettingSouth London NHS GP practices.ParticipantsTen practices and eighteen patients with treatment-resistant current major depressive disorder (MDD).InterventionsPractices were randomised to two treatment arms: 1) treatment-as-usual, 2) computerised decision support tool.ResultsTen GP practices participated in the trial, which was within our target range (8-20). However, practice and patient recruitment were slower than anticipated and only 18 of 86 intended patients were recruited. This was due to fewer than expected patients being eligible for the study, as well as disruption resulting from the Covid-19 pandemic. Only one patient was lost to follow-up. There were no serious or medically important adverse events during the trial. GPs in the ‘Decision tool’ arm indicated moderate support for the tool. A minority of patients fully engaged with the mobile app-based tracking of symptoms, medication adherence and side effects.ConclusionsOverall, the trial is not feasible in the current form and would need to be modified as follows to overcome its limitations: 1) inclusion of patients who have only tried one SSRI, rather than two, to improve recruitment and pragmatic relevance of the study, 2) approaching community pharmacists to implement tool recommendations rather than GPs, 3) further funding to directly interface between the decision support tool and self-reported symptom app, 4) increasing the geographic reach by not requiring detailed diagnostic assessments and replacing this with supported remote self-report.Ethics and disseminationThe study has received NHS ethical approval from the London - Camberwell St Giles Research Ethics Committee (ref:17/LO/2074).Trial registration numberClinicalTrials.govIdentifier:NCT03628027Strengths and limitations of this studyThe Antidepressant Advisor tool was incorporated into an existing GP healthcare record system for ease of use by GPsWe were unable to recruit a sufficient number of participants to estimate effect sizes for future trialsThe eligibility criteria for participants to have tried two antidepressants before entering the study limited the number of eligible participants
Stochastic Spatiotemporal Simulation of a General Reaction System
Authors: Loza Andrew J. , Sherman Marc S. 
Published: October 2022

AbstractBiological systems frequently contain biochemical species present as small numbers of slowly diffusing molecules, leading to fluctuations that invalidate deterministic analyses of system dynamics. The development of mathematical tools that account for the spatial distribution and discrete number of reacting molecules is vital for understanding cellular behavior and engineering biological circuits. Here we present an algorithm for an event-driven stochastic spatiotemporal simulation of a general reaction process that bridges well-mixed and unmixed systems. The algorithm is based on time-varying particle probability density functions whose overlap in time and space is proportional to reactive propensity. We show this to be mathematically equivalent to the Gillespie algorithm in the specific case of fast diffusion. We develop a computational implementation of this algorithm and provide a Fourier transformation-based approach which allows for near constant computational complexity with respect to the number of individual particles of a given species. To test this simulation method, we examine reaction and diffusion limited regimes of a bimolecular association-dissociation reaction. In the reaction limited regime where mixing occurs between individual reactions, equilibrium numbers of components match the expected values from mean field methods. In the diffusion limited regime, however, spatial correlations between newly dissociated species persist, leading to rebinding events and a shift the in the observed molecular counts. In the final part of this work, we examine how changes in enzyme efficiency can emerge from changes in diffusive mobility alone, as may result from protein complex formation.
Impact evaluation of score classes and annotation regions in deep learning-based dairy cow body condition prediction
Authors: Nagy Sára Ágnes , Kilim Oz , Csabai István , Gábor György , Solymosi Norbert 
Published: October 2022

AbstractBody condition scoring is a simple method to estimate the energy supply of dairy cattle. Our study aimed to investigate the accuracy with which supervised machine learning, a deep convolutional neural network, can be used to retrieve body condition score (BCS) classes estimated by an expert. Using a simple action camera, we recorded images of animals’ rumps in three large-scale farms. The images were annotated with three different-sized boxes by an expert. A Faster-RCNN pre-trained model was trained on 12 and 3 BCS classes. Training in 12 classes, with a 0 error range, the Cohen’s kappa value yielded minimal agreement. Allowing an error range of 0.25, we obtained a minimum or week agreement. With an error range of 0.5, we had strong or almost perfect agreements. The kappa values of the approach trained on 3 classes show that we can classify all animals into BCS categories with at least moderate agreement. Furthermore, CNNs trained in 3 BCS classes show a remarkably higher proportion of strong agreement than those trained in 12 classes. The prediction precision based on training with various annotation regions showed no meaningful differences.
Atypical cortical encoding of speech identifies children with Dyslexia versus Developmental Language Disorder
Authors: Araújo João , Simons Benjamin D , Peter Varghese , Mandke Kanad , Kalashnikova Marina , Macfarlane Annabel , Gabrielczyk Fiona , Wilson Angela , Di Liberto Giovanni M. , Burnham Denis , Goswami Usha 
Published: October 2022

AbstractSlow cortical oscillations play a crucial role in processing the speech envelope, which is perceived atypically by children with Developmental Language Disorder (DLD) and developmental dyslexia. Here we use electroencephalography (EEG) and natural speech listening paradigms to identify neural processing patterns that characterize dyslexic versus DLD children. Using a story listening paradigm, we show that atypical power dynamics and phase-amplitude coupling between delta and theta oscillations characterize dyslexic and DLD children groups, respectively. We further identify EEG common spatial patterns (CSP) during speech listening across delta, theta and beta oscillations describing dyslexic versus DLD children. A linear classifier using four deltaband CSP variables predicted dyslexia status (0.77 AUC). Crucially, these spatial patterns also identified children with dyslexia in a rhythmic syllable task EEG, suggesting a core developmental deficit in neural processing of speech rhythm. These findings suggest that there are distinct atypical neurocognitive mechanisms underlying dyslexia and DLD.
SiPhyNetwork: An R package for Simulating Phylogenetic Networks
Authors: Justison Joshua A. , Solis-Lemus Claudia , Heath Tracy A. 
Published: October 2022

AbstractGene flow is increasingly recognized as an important macroevolutionary process. The many mechanisms that contribute to gene flow (e.g., introgression, hybridization, lateral gene transfer) uniquely affect the diversification of dynamics of species, making it important to be able to account for these idiosyncrasies when constructing phylogenetic models. Existing phylogenetic-network simulators for macroevolution are limited in the ways they model gene flow.We present SiPhyNetwork, an R package for simulating phylogenetic networks under a birth-death-hybridization process.Our package unifies the existing birth-death-hybridization models while also extending the toolkit for modeling gene flow. This tool can create patterns of reticulation such as hybridization, lateral gene transfer, and introgression.Specifically, we model different reticulate events by allowing events to either add, remove, or keep constant the number of lineages. Additionally, we allow reticulation events to be trait-dependent, creating the ability to model the expanse of isolating mechanisms that prevent gene flow. This tool makes it possible for researchers to model many of the complex biological factors associated with gene flow in a phylogenetic context.
How Does White Matter Registration Affect Tractography Alignment?
Authors: Amorosino Gabriele , Olivetti Emanuele , Jovicich Jorge , Avesani Paolo 
Published: October 2022

ABSTRACTTractography is a powerful method to represent the structural connectivity of the brain white matter. Nevertheless, the comparison of these data structures between two individuals is still an open challenge because of their complexity, e.g. digital representation of millions of fibers as polylines. The scientific community spent a meaningful effort to develop new methods of white matter registration aiming to take advantage of diffusion MRI models. Despite the effort to improve the registration of the white matter, little is known about the effect of the registration on tractogram alignment. The main issue for an empirical evaluation is the lack of ground truth, e.g. a sample of data where the correct alignment is validated by experts. This work aims to overcome this drawback by proposing an evaluation framework based on the matching of homologous fiber structures, e.g. known neuroanatomical bundles. The contribution is a quantitative comparison of how the most representative methods of white matter registration affect tractogram alignment.
Membrane-active peptides escape drug-resistance in cancer
Authors: Benfield Aurélie H. , Vernen Felicitas , Young Reuben S.E. , Nadal-Bufí Ferran , Hammerlindl Heinz , Craik David J. , Schaider Helmut , Lawrence Nicole , Blanksby Stephen J. , Henriques Sónia Troeira 
Published: October 2022

AbstractAcquired drug-resistance is a recurring problem in cancer treatment, and this is particularly true for patients with metastatic melanoma that carry a BRAF V600E mutation. In the current study, we explored the use of membrane-active peptides as an alternative therapeutic modality to target drug-resistant melanoma cells. We produced slow-cycling and drug-resistant melanoma cells using dabrafenib, a small molecule drug that targets tumor cells with BRAF V600E mutation, and characterised their lipidome and proteome to investigate the role of membrane lipids in acquired drug-resistance. Despite some changes in the lipid composition, tested anti-melanoma membrane-active cyclic peptides (cTI and cGm) killed melanoma cells that are sensitive, tolerant, or resistant to dabrafenib. Importantly, melanoma cells did not develop resistance to cTI or cGm, nor changed their lipid composition with long-term peptide treatment. Therefore, these peptides are well suited as templates to design therapeutic leads to target drug-resistant metastatic melanoma cells and/or as co-treatment with small molecule drugs.
RecGraph: adding recombinations to sequence-to-graph alignments
Authors: Avila Jorge , Bonizzoni Paola , Ciccolella Simone , Della Vedova Gianluca , Denti Luca , Monti Davide , Pirola Yuri , Porto Francesco 
Published: October 2022

AbstractThe transition towards graph pangenomes is posing several new challenging questions, most notably how to extend the classical notion of read alignment from a sequence-to-sequence to a sequence-to-graph setting. Especially on variation graphs, where paths corresponding to individual genomes are labeled, notions of alignments that are strongly inspired by the classical ones are usually able to capture only variations that can be expressed by mismatches or gaps, such as SNPs or short insertions and deletions.On the other hand the recent investigation of pangenomes at bacterial scale (Colquhoun et al, 2021) shows that most tools are tailored for human pangenomes and are not suited to bacteria which exhibit, among other characteristics, a larger variability. Such variability leads to the need for incorporating a greater flexibility when computing an alignment.In this paper, we extend the usual notion of sequence-to-graph alignment by including recombinations among the variations that explicitly represented and evaluated in an alignment. From a computational modeling point of view, a recombination corresponds to identifying a new path of the variation graph which is a mosaic of two different paths, possibly joined by a new arc.We provide a dynamic programming algorithm for computing an optimal alignment that allows recombinations with an affine penalty. We have implemented our approach with the tool RecGraph and we have analyzed its accuracy over some over some bacterial pangenome graphs.
TLR7/8 stress response drives histiocytosis in SLC29A3 disorders
Authors: Shibata Takuma , Sato Ryota , Taoka Masato , Saitoh Shin-Ichiroh , Komine Mayumi , Yamaguchi Kiyoshi , Goyama Susumu , Motoi Yuji , Kitaura Jiro , Izawa Kumi , Yamauchi Yoshio , Tsukamoto Yumiko , Ichinohe Takeshi , Fujita Etsuko , Hiranuma Ryosuke , Fukui Ryutaro , Furukawa Yoichi , Kitamura Toshio , Takai Toshiyuki , Tojo Arinobu , Ohtsuki Mamitaro , Ohto Umeharu , Shimizu Toshiyuki , Ozawa Manabu , Yoshida Nobuaki , Isobe Toshiaki , Latz Eicke , Mukai Kojiro , Taguchi Tomohiko , Miyake Kensuke 
Published: October 2022

AbstractSLC29A3, also known as ENT3, is a lysosomal transmembrane protein that transports nucleosides from the lysosomes to the cytoplasm1. Loss-of-function mutations inSLC29A3cause lysosomal nucleoside storage and histiocytosis: phagocyte accumulation in multiple organs2,3. However, little is known about the mechanism through which lysosomal nucleoside storage drives histiocytosis. Herein, histiocytosis inSlc29a3−/−mice was demonstrated to depend on TLR7, which senses a combination of nucleosides and oligoribonucleotides4,5. TLR7 responded to lysosomal nucleoside storage and enhanced proliferation of Ly6ChiCX3CR1lowimmature monocytes and their maturation into Ly6Clowphagocytes inSlc29a3−/−mice. Because accumulated nucleosides primarily originated from cell corpse phagocytosis, TLR7 in immature monocytes recognized nucleoside storage as lysosomal stress and increased phagocyte numbers. This non-inflammatory compensatory response is referred to as the TLR7 stress response where Syk, GSK3β, β-catenin, and mTORC1 serve as downstream signalling molecules. In SLC29A3 disorders, histiocytosis accompanies inflammation6,7. Nucleoside storage failed to induce pro-inflammatory cytokine production inSlc29a3−/−mice, but enhanced ssRNA-dependent pro-inflammatory cytokine production in Ly6Chiclassical monocytes and peripheral macrophages, not proliferating immature monocytes. Patient-derived monocytes harbouring G208RSLC29A3mutation showed higher survival and proliferation in the presence of M-CSF and produced larger amounts of IL-6 upon ssRNA stimulation than did those derived from healthy subjects. A TLR8 antagonist inhibited the survival/proliferation of patient-derived macrophages. These results demonstrated that TLR7/8 responses to lysosomal nucleoside stress drive SLC29A3 disorders.
Within-animal comparison of microdialysis and fiber photometry in amphetamine-exposed mice
Authors: Ejdrup Aske L. , Wellbourne-Wood Joel , Dreyer Jakob K. , Guldhammer Nina , Lycas Matthew D. , Gether Ulrik , Hall Benjamin J. , Sørensen Gunnar 
Published: October 2022

AbstractA fundamental concept in neuroscience is the transmission of information between neurons via neurotransmitters, -modulators, and – peptides. For the past decades the gold standard for measuring neurochemicals in awake animals has been microdialysis (MD). The emergence of genetically encoded fluorescence-based biosensors, as well as in vivo optical techniques such as fiber photometry (FP), have introduced technologically distinct means of measuring neurotransmission. To directly compare MD and FP, we performed concurrent within-animal recordings of extracellular dopamine (DA) in the dorsal striatum (DS) before and after administration of amphetamine in awake, freely behaving mice expressing the dopamine sensor dLight1.3b. We show that despite temporal differences, MD- and FP-based readouts of DA correlate well within mice. Down-sampling of FP data showed temporal correlation to MD data, with less variance observed using FP. We also present evidence that DA fluctuations periodically reach low levels and naïve animals have rapid, pre-drug DA dynamics measured with FP that correlate to the subsequent pharmacodynamics of amphetamine as measured with MD and FP.
The endogenous modulation of visual plasticity in human adults
Authors: Chen Yiya , Gao Yige , He Zhifen , Sun Zhouyuan , Mao Yu , Hess Robert F. , Zhang Peng , Zhou Jiawei 
Published: October 2022

AbstractThe adult human visual system can exhibit a degree of neuroplastic change under the right conditions which has implications for future treatments to recover vision loss that have occurred in infancy. The exogenous factors that promote neuroplastic change have been the focus of human psychophysical, electrophysiological and neuroimaging research over the last decade. What has not been considered is the importance of endogenous factors. In this study we modulate the neural oscillations that determines the internal neural state to demonstrate that endogenous factors play a critical role in not only baseline contrast sensitivity but also the extent to which the adult visual system can undergo neuroplastic change in binocular balance.