bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID-19 could cause long term peripheral nerve demyelination and axonal loss: A One Year Prospective Cohort Study
Authors: Yang Qian , Zhang Meng , Lai Yanhui , Liu Xuzhao , Liu Fengshuang , Zang Hongmin , Song Jinzhong , Li Na , Cui Shuhua , Shao Wei , Ma Jiang , Wang Zhibo , Cui Ling , Sun Feng , Zhao Yubin 
Published: July 2022

AbstractBackgroundThere is a lack of studies on large-sample, medium-, or long-term follow-up data of peripheral neuropathy (PNP) in the COVID-19 survivors. This study evaluated the characteristics and related risk factors of PNP in the medium- and long-term rehabilitation, which provided real-world study data for the complete recovery of COVID-19 patients.MethodsThis study was a prospective cohort study of the COVID-19 survivors. We collected data on baseline characteristics, symptoms at onset and after discharge during the 6-month and 12-month follow-up. Peripheral nerves were measured by electromyography and inducible potentiometer. We used multivariable logistic regression to analyze the influencing factors of PNP. Additionally, we compared the difference between the two measurements among the population who completed both measurements.Results313 patients were included in the study and all of them underwent nerve conduction study. 67 patients completed two measurements at 6-month and 12-month follow-up. Commonly reported symptoms contained memory loss (86%), hair loss (28%), anxiety (24%), and sleep difficulties (24%). 232 patients (74%) were found with PNP, including 51 (16%) with mononeuropathy and 181 (58%) with generalized PNP. Patients with measurement at 12-month follow-up had a higher prevalence of generalized PNP (p=0.006). For pathological types, 64 (20%) patients had only axonal loss, 67 (21%) had only demyelination, and 101 (32%) had a mixed type. There was no significant difference in the prevalence of accompanying symptoms after discharge between the two groups with or without PNP. After adjustment, age was positively associated with PNP (OR=1.22 per 10-year increase of age, 95% CI, 1.05-1.41). Compared with less than the median amount of IgG at discharge, higher amount of IgG was associated with decreased risk of F-wave abnormality (OR=0.32, 95%CI, 0.11-0.82), but no significant difference in other types of PNP.Conclusions and RelevanceSARS-CoV-2 could cause PNP in hospital survivors with COVID-19, which persisted and was associated with age, education, and IgG antibody at discharge, but had no significant correlation with symptoms after discharge.
MiniVess: A dataset of rodent cerebrovasculature from in vivo multiphoton fluorescence microscopy imaging
Authors: Poon Charissa , Teikari Petteri , Rachmadi Muhammad Febrian , Skibbe Henrik , Hynynen Kullervo 
Published: July 2022

ABSTRACTWe present MiniVess, the first annotated dataset of rodent cerebrovasculature, acquired using two-photon fluorescence microscopy. MiniVess consists of 70 3D image volumes with segmented ground truths. Segmentations were created using traditional image processing operations, a U-Net, and manual proofreading. Code for image preprocessing steps and the U-Net are provided. Supervised machine learning methods have been widely used for automated image processing of biomedical images. While much emphasis has been placed on the development of new network architectures and loss functions, there has been an increased emphasis on the need for publicly available annotated, or segmented, datasets. Annotated datasets are necessary during model training and validation. In particular, datasets that are collected from different labs are necessary to test the generalizability of models. We hope this dataset will be helpful in testing the reliability of machine learning tools for analyzing biomedical images.
Single-cell level temporal profiling of tumour-reactive T cells under immune checkpoint blockade
Authors: Hassan Jehanne , Appleton Elizabeth , Kalfaoglu Bahire , Pedersen Malin , Almeida-Santos José , Kanemaru Hisashi , Irie Nobuko , Foo Shane , Reda Omnia , Tan Benjy J.Y. , Okazaki Il-mi , Okazaki Taku , Satou Yorifumi , Harrington Kevin , Melcher Alan , Ono Masahiro 
Published: July 2022

AbstractThe blockade of the immune checkpoints PD-1 and CTLA-4 enhances T cell response. However, it is largely unknown how antigen-reactive T cells regulate their checkpoint expression in vivo and whether and how the checkpoint blockade can change activation dynamics of tumour-reactive T cells. To address this, here we used Nr4a3-Timer-of-cell-kinetics-and-activity (Tocky), which allows analysis of temporal changes of activated T cells following TCR signalling in vivo. By analysing melanoma-bearing Nr4a3 Tocky mice, we elucidate hidden dynamics of tumour-reactive T cells in the steady-state. Checkpoint blockade depleted highly activated effector Treg, while promoting unique effector T cell populations, and thus differentially modulating activation of tumour-reactive T cell populations. Furthermore, multidimensional analysis and seamless analysis of Tocky and scRNA-seq revealed a full spectrum of T cell dynamics in response to tumour burden and treatment with checkpoint blockade. Lastly, we propose a rational design of combinatorial therapy to further enhance T cell activities.
Prior-guided Individualized Thalamic Parcellation based on Local Diffusion Characteristics using Deep Learning
Authors: Gao Chaohong , Wu Xia , Wang Yaping , Li Gang , Chu Congying , Madsen Kristoffer Hougaard , Fan Lingzhong 
Published: July 2022

AbstractAs a gateway for projections entering and exiting the cerebral cortex, the human thalamus processes information from sensory to cognition relevant to various neuropsychiatric disorders. It is composed of dozens of nuclei, which have been difficult to identify with clinical MR sequences. However, delineating thalamic nuclei accurately at an individual level is essential for precise neuromodulation treatment. Here, we not only identified the fine-grained thalamic nuclei using local diffusion properties in vivo but also employed a deep learning strategy to achieve highly reproducible individual-level parcellation. Using High-quality diffusion MRI (dMRI), we first constructed a fine-grained group thalamus atlas based on thalamic local diffusion features. Then, the high-probability core area of the group thalamus atlas was wrapped into the native space as prior guidance for individualized thalamus construction. Finally, we trained the semi-supervised multiple classification models to accurately construct the individualized thalamus atlas with single-subject local diffusion characteristics. Compared to group atlas registration and single-subject clustering strategies, our individualized thalamus atlas combines population commonality and individual specificity and is superior in depicting the individual thalamic nuclei boundaries. Besides, our atlas provides a more conspicuous capacity to capture the individual specificity of thalamic nuclei. Through the evaluation by 3.0T\7.0T and test-retest dMRI datasets, the proposed high-probability group prior guided individualized thalamus construction pipeline is robust and repeatable in different magnetic field strengths and scanning batches. In addition, the individual parcellation of the thalamic nuclei has a good correspondence with the histological atlas and captured both higher group consistency and inter-subjects variations, which could be a valuable solution for precision clinical treatment.
Cross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for any atlas when raw data is not available
Authors: Dadashkarimi Javid , Karbasi Amin , Liang Qinghao , Rosenblatt Matthew , Noble Stephanie , Foster Maya , Rodriguez Raimundo , Adkinson Brendan , Ye Jean , Sun Huili , Camp Chris , Farruggia Michael , Tejavibulya Link , Dai Wei , Jiang Rongtao , Pollatou Angeliki , Scheinost Dustin 
Published: July 2022

AbstractOpen-source, publicly available neuroimaging datasets—whether from large-scale data collection efforts or pooled from multiple smaller studies—offer unprecedented sample sizes and promote generalization efforts. Releasing data can democratize science, increase the replicability of findings, and lead to discoveries. Due to patient privacy and data storage concerns, researchers typically release preprocessed data with the voxelwise time series parcellated into a map of predefined regions, known as an atlas. However, releasing preprocessed data also limits the choices available to the end-user. This is especially true for connectomics, as connectomes created from different atlases are not directly comparable. Since there exist several atlases with no gold standards, it is unrealistic to have processed, open-source data available from all atlases. Together, these limitations directly inhibit the potential benefits of open-source neuroimaging data. To address these limitations, we introduce Cross Atlas Remapping via Optimal Transport (CAROT) to find a mapping between two atlases. This approach allows data processed from one atlas to be directly transformed into a connectome based on another atlas without the need for raw data access. To validate CAROT, we compare reconstructed connectomes against their original counterparts (i.e., connectomes generated directly from an atlas), demonstrate the utility of transformed connectomes in downstream analyses, and show how a connectome-based predictive model can generalize to publicly available data that was processed with different atlases. Overall, CAROT can reconstruct connectomes from an extensive set of atlases—without ever needing the raw data—allowing already processed connectomes to be easily reused in a wide range of analyses while eliminating redundant processing efforts. We share this tool as both source code and as a stand-alone web application (http://carotproject.com/).
Towards Self-Describing and FAIR Bulk Formats for Biomedical Data
Authors: Lukowski Michael , Prokhorenkov Andrew , Grossman Robert L. 
Published: July 2022

AbstractWe introduce a self-describing serialized format for bulk biomedical data called the Portable Format for Biomedical (PFB) data. The Portable Format for Biomedical data is based upon Avro and encapsulates a data model, a data dictionary, the data itself, and pointers to third party controlled vocabularies. In general, each data element in the data dictionary is associated with a third party controlled vocabulary to make it easier for applications to harmonize two or more PFB files. We describe experimental studies showing the performance improvements when importing and exporting bulk biomedical data in the PFB format versus using JSON and SQL formats.
Dynamic mitochondrial transcription and translation in B cells control germinal centre entry and lymphomagenesis
Authors: Yazicioglu Yavuz F , Marin Eros M , Sandhu Ciaran , Galiani Silvia , Raza Iwan G A , Ali Mohammad , Kronsteiner Barbara , Compeer Ewoud B , Attar Moustafa , Dunachie Susanna J , Dustin Michael L , Clarke Alexander J 
Published: July 2022

AbstractGerminal centre (GC) B cells undergo proliferation at very high rates in a hypoxic microenvironment, but the cellular processes driving this are incompletely understood. Here we show that the mitochondria of GC B cells are highly dynamic, with significantly upregulated transcription and translation rates associated with the activity of transcription factor mitochondrial A (TFAM). TFAM, whilst also necessary for normal B cell development, is required for entry of activated GC-precursor B cells into the germinal centre reaction, and deletion ofTfamsignificantly impairs GC formation, function, and output. Loss of TFAM in B cells compromises the actin cytoskeleton and impairs cellular motility of GC B cells in response to chemokine signalling, leading to their spatial disorganisation. We show that B cell lymphoma substantially increases mitochondrial translation, and deletion ofTfamin B cells is protective against the development of lymphoma in a c-Myc transgenic model. Finally, we show that pharmacologic inhibition of mitochondrial transcription and translation inhibits growth of GC-derived human lymphoma cells, and induces similar defects in the actin cytoskeleton.
A Quantitative Evaluation of Topological Motifs and Their Coupling in Gene Circuit State Distributions
Authors: Clauss Benjamin , Lu Mingyang 
Published: July 2022

AbstractOne of the major challenges in biology is to understand how gene interactions collaborate to determine overall functions of biological systems. Here, we present a new computational framework that enables systematic, high-throughput, and quantitative evaluation of how small transcriptional regulatory circuit motifs, and their coupling, contribute to functions of a dynamical biological system. We illustrate how this approach can be applied to identify four- node gene circuits, circuit motifs, and motif coupling responsible for various gene expression state distributions, including those derived from single-cell RNA sequencing data. We also identify seven major classes of four-node circuits from clustering analysis of state distributions. The method is applied to establish phenomenological models of gene circuits driving human neuron differentiation, revealing important biologically relevant regulatory interactions. Our study will shed light on a better understanding of gene regulatory mechanisms in creating and maintaining cellular states.
Long range allostery mediates the regulation of plasminogen activator inhibitor-1 by vitronectin
Authors: Kihn Kyle , Marchiori Elisa , Spagnolli Giovanni , Boldrini Alberto , Terruzzi Luca , Lawrence Daniel A. , Gershenson Anne , Faccioli Pietro , Wintrode Patrick L. 
Published: July 2022

AbstractThe serpin plasminogen activator inhibitor 1 (PAI-1) spontaneously undergoes a massive structural change from a metastable, active conformation, with a solvent accessible reactive center loop (RCL), to a stable, inactive or latent conformation in which the RCL has inserted into the central β sheet. Physiologically, conversion to the latent state is regulated by the binding of vitronectin which retards the rate of this latency transition approximately 2-fold. We investigated the effects of vitronectin on the PAI-1 latency transition using all-atom path sampling simulations in explicit solvent. In simulated latency transitions of free PAI-1, the RCL is quite mobile as is the gate, the region that impedes RCL access to the central β sheet. This mobility allows the formation of a transient salt bridge that facilitates the transition, and this finding rationalizes existing mutagenesis results. Vitronectin binding reduces RCL and gate mobility by allosterically rigidifying structural elements over 40 Å away from the binding site thus blocking the transition to the latent conformation. The effects of vitronectin are propagated by a network of dynamically correlated residues including a number of conserved sites that have previously been identified as important for PAI-1 stability. Simulations also revealed a transient pocket populated only in the vitronectin bound state which corresponds to a cryptic drug binding site identified by crystallography. Overall, these results shed new light on regulation of the PAI-1 latency transition by vitronectin and illustrate the potential of path sampling simulations for understanding functional conformational changes in proteins and for facilitating drug discovery.
Discovery of malathion resistance QTL inDrosophila melanogasterusing a bulked phenotyping approach
Authors: Macdonald Stuart J , Long Anthony D 
Published: July 2022

ABSTRACTDrosophila melanogasterhas proven an effective system with which to understand the evolutionary genetics and molecular mechanisms of insecticide resistance. Insecticide use has left signatures of selection in the fly genome, and both functional and quantitative genetics studies in the system have identified genes and variants associated with resistance. Here, we useD. melanogasterand leverage a bulk phenotyping and pooled sequencing “extreme QTL” approach to genetically dissect variation in resistance to malathion, an organophosphate insecticide. We resolve two QTL (Quantitative Trait Loci), one of which implicates allelic variation at the cytochrome P450 geneCyp6g1, a strong candidate based on previous work. The second shows no overlap with hits from a previous genomewide association study (GWAS) for malathion resistance, recapitulating other studies showing that different strategies for complex trait dissection in flies can yield apparently different architectures. Notably, we see no genetic signal at theAcegene.Aceencodes the target of organophosphate insecticide inhibition, and GWAS have identified strongAce-linked associations with resistance. The absence of QTL implicatingAcehere is most likely because our mapping population does not segregate for several of the known functional polymorphisms impacting resistance atAce, perhaps because our population is derived from flies collected prior to the widespread use of organophosphate insecticides. Our fundamental approach can be an efficient, powerful strategy to dissect genetic variation in resistance traits. Nonetheless, studies seeking to interrogate contemporary insecticide resistance variation may benefit from deriving mapping populations from more recently collected strains.
How does the risk of bias influence the effect sizes of exercise therapy in chronic low back pain randomised controlled trials? A protocol for a meta-epidemiological study
Authors: Innocenti Tiziano , Hayden Jill A , Salvioli Stefano , Giagio Silvia , Piano Leonardo , Cosentino Carola , Brindisino Fabrizio , Feller Daniel , Ogilvie Rachel , Gianola Silvia , Castellini Greta , Bargeri Silvia , Twisk Jos WR , Ostelo Raymond , Chiarotto Alessandro 
Published: July 2022

ABSTRACTBackground and ObjectivesRisk of bias is a critical issue to consider when appraising studies. Generally, the higher the risk of bias of a study, the less confidence there will be that the results are valid. Considering that low back pain is recognized to have an extremely high disease burden; exercise therapy is one of the most frequently prescribed interventions for chronic low back pain (CLBP) and that most low back pain trials have methodological limitations that could bias treatment effect estimates; the objective of this study is to explore causal pathways between the sources of risk of bias and estimates of the treatment effect of exercise therapy interventions in CLBP trials.MethodsThe 249 RCTs included in the 2021 Cochrane review publication “Exercise therapy for chronic low back pain” will be included. The risk of bias will be evaluated with the Cochrane Risk of Bias 2 tool (ROB 2). Causal pathways between the exposure (risk of bias domains) and our outcomes of interest (effect sizes for pain and functional limitations) will be explored through univariable and multivariable meta-regression models. These models will be adjusted for potential confounders (sample size, trial registration, incomplete flow chart information and treatment comparisons), exploring relevant interactions within each model. Additional and sensitivity analyses will be performed to explore and test the robustness of the primary analyses.Ethics and disseminationA manuscript will be prepared and submitted for publication in an appropriate peer-reviewed journal upon study completion. We believe that the results of this investigation will be relevant to researchers paying more attention to the synthesis of the evidence to translate clinical implications to key stakeholders (healthcare providers and patients).
National and regional prevalence of SARS-CoV-2 antibodies in primary and secondary school children in England: the School Infection Survey, a national open cohort study, November 2021
Authors: Powell Annabel A , Ireland Georgina , Leeson Rebecca , Lacey Andrea , Ford Ben , Poh John , Ijaz Samreen , Shute Justin , Cherepanov Peter , Tedder Richard , Bottomley Christian , Dawe Fiona , Mangtani Punam , Jones Peter , Nguipdop-Djomo Patrick , Ladhani Shamez 
Published: July 2022

AbstractBackgroundRisk factors for infection and, therefore, antibody positivity rates will be different in children compared to adults. We aim to estimate national and regional prevalence of SARS-CoV-2 antibodies in primary (4-11-year-olds) and secondary (11-15-year-olds) school children between 10 November and 10 December 2021.MethodsCross-sectional surveillance in England using two stage sampling, firstly stratifying into regions and selecting local authorities, then selecting schools according to a stratified sample within selected local authorities. Participants were sampled using a novel oral fluid validated assay for SARS-CoV-2 spike and nucleocapsid IgG antibodies.Results4,980 students from 117 state-funded schools (2,706 from 83 primary schools, 2,274 from 34 secondary schools) provided a valid sample. After weighting for age, sex and ethnicity, and adjusting for assay accuracy, the national prevalence of SARS-CoV-2 antibodies in primary school students, who were all unvaccinated, was 40.1% (95%CI; 37.3-43.0). Antibody prevalence increased with age (p<0.001) and were higher in urban than rural schools (p=0.01). In secondary school students, the adjusted, weighted national prevalence of SARS-CoV-2 antibodies was 82.4% (95%CI; 79.5-85.1); including 57.5% (95%CI; 53.9-61.1) in unvaccinated and 97.5% (95%CI; 96.1-98.5) in vaccinated students. Antibody prevalence increased with age (p<0.001), and was not significantly different in urban versus rural students (p=0.1).ConclusionsUsing a validated oral fluid assay, we estimated national and regional seroprevalence of SARS-CoV-2 antibodies in primary and secondary school students. In November 2021, 40% of primary school students and nearly all secondary school students in England had SARS-CoV2 antibodies through a combination of natural infection and vaccination.
Prevalence and Factors Associated with Mental Illness Symptoms among School Students Post Lockdown of the COVID-19 Pandemic in the United Arab Emirates: A Cross-Sectional National Study
Authors: Ghader Nariman Ali , Mheiri Noor Al , Fikri Asma , AbdulRazzak Hira , Saleheen Hassan , Saddik Basema , Aljawarneh Yousef , Dalky Heyam , Banna Ammar Al , Memari Shammah Al , Shehhi Budoor Al , Mazrouei Shereena Al , Hajeri Omniyat Al 
Published: July 2022

AbstractData from the United Arab Emirates about the mental health status of the younger population is limited. The current study aimed to assess the prevalence of anxiety, depression, and risk for PTSD among school students post lockdown of the current COVID-19 pandemic. A sample of 3745 students and their parents across the country answered a web-based survey. Parents provided bio-demographic data and students answered questions from the Mood and Feeling Questionnaire (MFQ-Child Self-report), Screen for Child Anxiety Related Disorders (SCARED-Child Version), and Children’s Revised Impact of Event Scale (CRIES-8). Findings showed that the risk for PTSD was the most prevalent (40.6%), followed by symptoms of anxiety (23.3%), and depression (17.1%). For gender differences, symptoms of the three conditions were higher in female students by 6.9%. Moreover, symptoms of depression and anxiety were found to be higher among late adolescents. Further analysis revealed that having medical problems (β = 2.0, p < 0.001) and witnessing the death of a close family member due to COVID-19 (β = 1.7, p < 0.001) were positive predictors associated with PTDS, depression, and anxiety. The study concluded that post COVID-19 lockdown, symptoms of anxiety, depression, and risk for PTSD are prevalent among students in the UAE. Researchers recommend the initiation of a national school mental health screening program and the provision of follow-up services for vulnerable students. Another must-have is the integration of a mental health support system in the emergency and disaster preparedness future plans.