bluuebunny/crossref_metadata_2025_split huggingface dataset:
Communicating Regulatory High Throughput Sequencing Data Using BioCompute Objects
Authors: King Charles Hadley S. , Keeney Jonathon , Guimera Nuria , Das Souvik , Fochtman Brian , Walderhaug Mark O , Talwar Sneh , Patel Janisha , Mazumder Raja , Donaldson Eric 
Published: December 2020

AbstractFor regulatory submissions of next generation sequencing (NGS) data it is vital for the analysis workflow to be robust, reproducible, and understandable. This project demonstrates that the use of the IEEE 2791-2020 Standard, (BioCompute objects [BCO]) enables complete and concise communication of NGS data analysis results. One arm of a clinical trial was replicated using synthetically generated data made to resemble real biological data. Two separate, independent analyses were then carried out using BCOs as the tool for communication of analysis: one to simulate a pharmaceutical regulatory submission to the FDA, and another to simulate the FDA review. The two results were compared and tabulated for concordance analysis: of the 118 simulated patient samples generated, the final results of 117 (99.15%) were in agreement. This high concordance rate demonstrates the ability of a BCO, when a verification kit is included, to effectively capture and clearly communicate NGS analyses within regulatory submissions. BCO promotes transparency and induces reproducibility, thereby reinforcing trust in the regulatory submission process.
Pervasive low-frequency vocal modulation during territorial contests in Eurasian Scops Owls (Otus scops)
Authors: Grieco Fabrizio 
Published: December 2020

AbstractIn several animal species, including birds, individuals are known to produce low-frequency vocalizations during aggressive interactions with conspecifics. In this study, I investigated territorial interactions between male Eurasian Scops Owls that occupy territories in a densely-packed area. The single-note hoot of the Scops Owl is generally assumed to be highly repeatable, however extensive recording of male-male interactions identified previously unrecognized variation in the hoots’ structure. Male Scops Owls gave hoots at a frequency lower than usual when engaging in short-distance contests with neighbouring males. Within-subject analysis revealed that the caller’s average hoot frequency was positively correlated with the distance from its rival. During contests, males gradually reduced their hoot frequency as they approached one another, perhaps reflecting changes in the degree of escalation. Male Scops Owls reduced their hoot frequency immediately after the rival initiated countersinging, and returned to their usual frequency range at the end of the contest. These findings demonstrate that vocal modulation is pervasive in social contexts in the Scops Owl, and suggests that individuals have full voluntary control of the structure of their vocalizations. This study confirms in part the findings of other authors’ experimental work, where male owls adjusted their vocal frequency when challenged by an opponent. However, that study suggested that vocal frequency would encode information about the caller’s body weight. In contrast, the present study revealed context-dependent fluctuations in hoot frequency, which may suggest that the hoot of the Scops Owl dynamically reflects the current motivational state of the caller during the contest.
Misalignment of selection, plasticity, and among-individual variation: A test of theoretical predictions withPeromyscus maniculatus
Authors: Berdal Monica Anderson , Dochtermann Ned A. 
Published: December 2020

AbstractGenetic variation and phenotypic plasticity are predicted to align with selection surfaces, a prediction that has rarely been empirically tested. Understanding the relationship between sources of phenotypic variation, i.e. genetic variation and plasticity, with selection surfaces improves our ability to predict a population’s ability to adapt to a changing environment and our understanding of how selection has shaped phenotypes. Here, we estimated the (co)variances among three different behaviors (activity, aggression, and anti-predator response) in a natural population of deer mice (Peromyscus maniculatus). Using multi-response generalized mixed effects models, we divided the phenotypic covariance matrix into among- and within-individual matrices. The among-individual covariances includes genetic and permanent environmental covariances (e.g. developmental plasticity) and is predicted to align with selection. Simultaneously, we estimated the within-individual (co)variances, which include reversible phenotypic plasticity. To determine whether genetic variation, plasticity and selection align in multivariate space we calculated the dimensions containing the greatest among-individual variation and the dimension in which most plasticity was expressed (i.e. the dominant eigenvector for the among- and within-individual covariance matrices respectively). We estimated selection coefficients based on survival estimates from a mark-recapture model. Alignment between the dominant eigenvectors of behavioural variation and the selection gradient was estimated by calculating the angle between them, with an angle of 0 indicating perfect alignment. The angle between vectors ranged from 68° to 89°, indicating that genetic variation, phenotypic plasticity, and selection are misaligned in this population. This misalignment could be due to the behaviors being close to their fitness optima, which is supported by low evolvabilities, or because of low selection pressure on these behaviors.
Injectable prevascularized mature adipose tissues (iPAT) to achieve long-term survival in soft tissues regeneration
Authors: Louis Fiona , Sowa Yoshihiro , Irie Shinji , Kitano Shiro , Mazda Osam , Matsusaki Michiya 
Published: December 2020

AbstractSoft tissue regeneration remains a challenge in reconstructive surgery. Current autologous fat implantations lead to high fat absorption ratios, while artificial implants can be associated with lymphoma occurrence. To overcome these limitations, our aim was to reproduce adipose tissue vasculature structure before implantation. Here, we developed injectable prevascularized adipose tissues (iPAT), using physiological collagen microfibers (CMF) mixed with human mature adipocytes, adipose-derived stem cells (ADSC) and human umbilical vein endothelial cells (HUVEC). Following murine subcutaneous implantation, higher cell survival (84±6% viability) and volume maintenance were shown after 3 months for the iPAT (up to twice heavier than the non-prevascularized balls). This higher survival can be explained by the greater amount of blood vessels (up to 1.6 folds increase), with balanced host anastomosis (51±1% of human/mouse lumens), also involving infiltration by the lymphatic and neural vasculature networks. These iPAT tissues allowed non-invasive soft tissue reconstruction for long-term outcomes, and the ability to cryopreserve them with maintained viability and functionality also enables a later reinjection usually required before reaching the final patient desired graft volume.
Universal Spectrum Identifier for mass spectra
Authors: Deutsch Eric W. , Perez-Riverol Yasset , Carver Jeremy , Kawano Shin , Mendoza Luis , Van Den Bossche Tim , Gabriels Ralf , Binz Pierre-Alain , Pullman Benjamin , Sun Zhi , Shofstahl Jim , Bittremieux Wout , Mak Tytus D. , Klein Joshua , Zhu Yunping , Lam Henry , Vizcaíno Juan Antonio , Bandeira Nuno 
Published: December 2020

AbstractMass spectra provide the ultimate evidence for supporting the findings of mass spectrometry (MS) proteomics studies in publications, and it is therefore crucial to be able to trace the conclusions back to the spectra. The Universal Spectrum Identifier (USI) provides a standardized mechanism for encoding a virtual path to any mass spectrum contained in datasets deposited to public proteomics repositories. USIs enable greater transparency for providing spectral evidence in support of key findings in publications, with more than 1 billion USI identifications from over 3 billion spectra already available through ProteomeXchange repositories.
Investigating pleiotropy between depression and autoimmune diseases using the UK Biobank
Authors: Glanville Kylie P , Coleman Jonathan R I , O’Reilly Paul F , Galloway James , Lewis Cathryn M 
Published: December 2020

AbstractBackgroundEpidemiological studies have shown increased comorbidity between depression and autoimmune diseases. The mechanisms driving the comorbidity are poorly understood, and a highly powered investigation is needed to understand the relative importance of shared genetic influences. We investigated the evidence for pleiotropy from shared genetic risk alleles between these traits in the UK Biobank (UKB).MethodsWe defined autoimmune and depression cases using information from hospital episode statistics, self-reported conditions and medications, and mental health questionnaires. Pairwise comparisons of depression prevalence between autoimmune cases and controls, and vice-versa, were performed. Cross-trait polygenic risk score (PRS) analyses were performed to test for pleiotropy, i.e. testing whether PRS for depression could predict autoimmune disease status, and vice-versa.ResultsWe identified 28k cases of autoimmune diseases (pooling across 14 traits) and 324k autoimmune controls, and 65k cases of depression and 232k depression controls. The prevalence of depression was significantly higher in autoimmune cases compared to controls, and vice-versa. PRS for myasthenia gravis and psoriasis were significantly higher in depression cases compared to controls (p < 5.2×10−5, R2 <= 0.04%). PRS for depression were significantly higher in inflammatory bowel disease, psoriasis, psoriatic arthritis, rheumatoid arthritis and type 1 diabetes cases compared to controls (p < 5.8×10−5, R2 range 0.06% to 0.27%), and lower in coeliac disease cases compared to controls (p < 5.4×10−7, R2 range 0.11% to 0.15%).ConclusionsConsistent with the literature, depression was more common in individuals with autoimmune diseases compared to controls, and vice-versa, in the UKB. PRS showed some evidence for involvement of shared genetic factors, but the modest R2 values suggest that shared genetic architecture accounts for only a small proportion of the increased risk across traits.
Reproducible Correlations Of Corpus Callosum And Cingulum Generalized Fractional Anisotropy With Anxiety Ratings In Healthy Participants
Authors: Kartashov Sergey , Tetereva Alina , Martynova Olga 
Published: December 2020

AbstractDiffusion tensor imaging revealed that trait anxiety predicts the microstructural properties of fiber tracts between the anterior cingulate cortex, prefrontal cortex, and amygdala. However, the whole-brain structural connectivity has been rarely reported in the non-clinical populations with marginal deviations in trait anxiety and substantial changes in state anxiety. This work is aimed to assess the correlation of state and trait anxiety inventory (STAI) scores and their one-day deviation with white matter connectivity at the whole-brain scale. 64-direction diffusion-weighted images were collected in 25 participants without prior complaints of excess anxiety and/or clinical history of anxiety disorders. The self-reported ranking of STAI was collected twice with 24-hour interval: one day before and several minutes before the MRI scanning. A correlation analysis between the generalized fractional anisotropy (GFA) and the STAI ratings was performed for all regions of the brain. According to the diffusion connectometry, the most reproducible positive correlation of GFA and anxiety scores was observed for corpus callosum. For both days of psychological assessment, the left cingulum GFA correlated negatively with State anxiety ratings, while the right cingulum GFA was strongly associated with Trait anxiety. Our results suggest that the density of the corpus callosum and bilateral cingulum tracts are associated with the individual level of anxiety.
A Machine Learning Model of Microscopic Agglutination Test for Diagnosis of Leptospirosis
Authors: Oyamada Yuji , Ozuru Ryo , Masuzawa Toshiyuki , Miyahara Satoshi , Nikaido Yasuhiko , Obata Fumiko , Saito Mitsumasa , Villanueva Sharon Yvette Angelina M. , Fujii Jun 
Published: December 2020

AbstractLeptospirosis is a zoonosis caused by the pathogenic bacteriumLeptospira. The Microscopic Agglutination Test (MAT) is widely used as the gold standard for diagnosis of leptospirosis. In this method, diluted patient serum is mixed with serotype-determined Leptospiras, and the presence or absence of aggregation is determined under a dark-field microscope to calculate the antibody titer. Problems of the current MAT method are 1) a requirement of examining many specimens per sample, and 2) a need of distinguishing contaminants from true aggregates to accurately identify positivity. Therefore, increasing efficiency and accuracy are the key to refine MAT. It is possible to achieve efficiency and standardize accuracy at the same time by automating the decision making process. In this study, we built an automatic identification algorithm of MAT using a machine learning method to determine aggregation within microscopic images. The machine learned the features from 316 positive and 230 negative MAT images created with sera of Leptospira- infected (positive) and non-infected (negative) hamsters, respectively. In addition to the acquired original images, wavelet-transformed images were also considered as features. We utilized a support vector machine (SVM) as a proposed decision method. We validated the trained SVMs with 210 positive and 154 negative images. When the features were obtained from original or wavelet-transformed images, all negative images were misjudged as positive, and the classification performance was very low with sensitivity of 1 and specificity of 0. In contrast, when the histograms of wavelet coefficients were used as features, the performance was greatly improved with sensitivity of 0.99 and specificity of 0.99. We confirmed that the current algorithm judges the positive or negative of agglutinations in MAT images and gives the further possibility of automatizing MAT procedure.
A connectome of theDrosophilacentral complex reveals network motifs suitable for flexible navigation and context-dependent action selection
Authors: Hulse Brad K. , Haberkern Hannah , Franconville Romain , Turner-Evans Daniel B. , Takemura Shinya , Wolff Tanya , Noorman Marcella , Dreher Marisa , Dan Chuntao , Parekh Ruchi , Hermundstad Ann M. , Rubin Gerald M. , Jayaraman Vivek 
Published: December 2020

ABSTRACTFlexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of theDrosophilaCX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly’s head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.
Workflow for Protein N-terminal Acetylation and C-terminal Amidation Application using CcpNmr Analysis v2.4 Platform and Aria2.3 Structure Calculation Software
Authors: de Paula Oliveira Santos Bruno , Silva Bruno Marques , de Magalhães Mariana Torquato Quezado 
Published: December 2020

AbstractStructural biology is a field that enables a better understanding of proteins from scratch. From the available techniques, solution NMR is one well established that provides structure, dynamics and protein-molecules interaction. In a NMR lab routine, from data acquisition until protein/mechanisms elucidation comes a process that can undergo months. During the past decades, different tools were developed for NMR data processing, peaks assignment, structure elucidation and data submission. Since many of these programs demand great computational skills, a few groups have tried to combine those programs and make them more friendly and useful, what can possibilite a faster process. Here we highlight CCPNMR2.4 analysis and ARIA2.3, responsible for peak assignment and structure calculation, respectively, and can work associated. Although being academic free and the possibility of working with a GUI interface, the common N-terminal acetylation and C-terminal amidation modifications are not implemented in a way that possibilities to work with them in combination, what results in a dilemma. This work brings visual data that evidences the low usability of CCPN and ARIA with N-terminal acetylated and C-terminal amidated proteins and propose a workflow to overcome this problem, which may improve the usage of both software in the mentioned versions and facilitate the lab users already used to these programs. As a proof of concept, we have chosen a N-terminal amidated peptide, L-Phenylseptin, whose structure has already been solved with other programs. Statistical data shows that no significant difference was found with the structure obtained with the new protocol. In conclusion, we exhibit a new protocol that can be used in combination with CCPNMR2.4 and ARIA2.3 for protein with the mentioned modifications and it successfully works and manipulates these molecules.
Highly multiplexed quantitative phosphosite assay for biology and preclinical studies
Authors: Keshishian Hasmik , McDonald E. Robert , Melanson Randy , Porter Dale A. , Mundt Filip , Krug Karsten , Wallace Luke , Forestier Dominique , Rabasha Bokang , Marlow Sara E , Jane-Valbuena Judit , Todres Ellen , Specht Harrison , Golji Javad , Kuhn Eric , Burgess Michael , MacMullan Melanie , Satpathy Shankha , Mani D.R. , Gillette Michael , Clauser Karl , Rejtar Tomas , Wang Karen , Garraway Levi A. , Sellers William R. , Carr Steven A. 
Published: December 2020

AbstractReliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug-treatment in cells and tissues but are presently lacking. Here we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response and resistance to therapy.
A protease-initiated model of wound detection
Authors: O’Connor James T. , Stevens Aaron C. , Shannon Erica K. , Akbar Fabiha Bushra , LaFever Kimberly S. , Narayanan Neil , Hutson M. Shane , Page-McCaw Andrea 
Published: December 2020

AbstractWounds trigger surrounding cells to initiate repair, but it is unclear how cells detect wounds. The first known wound response of epithelial cells is a dramatic increase in cytosolic calcium, which occurs within seconds, but it is not known what initiates this calcium response. Specifically, is there an instructive signal detected by cells surrounding wounds? Here we identify a signal transduction pathway in epithelial cells initiated by the G-protein coupled receptor Methuselah-like 10 (Mthl10) activated around wounds by its cytokine ligands, Growth-blocking peptides (Gbps). Gbps are present in unwounded tissue in latent form, requiring proteolytic activation for signaling. Multiple protease families can activate Gbps, suggesting it acts as a detector to signal the presence of several proteases. We present experimental and computational evidence that proteases released during cell lysis serve as the instructive signal from wounds, liberating Gbp ligands to diffuse to the Mthl10 receptors on epithelial cells and activate downstream release of calcium. Thus, the presence of a nearby wound is signaled by the activation of a Gbp protease detector, sensitive to multiple proteases released after cellular damage.
Does arsenic contamination affect DNA methylation patterns in a wild bird population? An experimental approach
Authors: Laine Veronika N. , Verschuuren Mark , van Oers Kees , Espín Silvia , Sánchez-Virosta Pablo , Eeva Tapio , Ruuskanen Suvi 
Published: December 2020

AbstractPollutants, such as toxic metals, negatively influence organismal health and performance, even leading to population collapses. Studies in model organisms have shown that epigenetic marks, such as DNA methylation, can be modulated by various environmental factors, including pollutants, influencing gene expression and various organismal traits. Yet experimental data on the effects of pollution on DNA methylation from wild animal populations is largely lacking. We here experimentally investigated for the first time the effects of early-life exposure to environmentally relevant levels of a key pollutant, arsenic (As), on genome-wide DNA methylation in a wild bird population. We experimentally exposed nestlings of great tits (Parus major) to arsenic during their post-natal developmental period (3 to 14 days post-hatching) and compared their erythrocyte DNA methylation levels to those of respective controls. In contrast to predictions, we found no overall hypomethylation in the arsenic group. We found evidence for loci to be differentially methylated between the treatment groups, but for five CpG sites only. Three of the sites were located in gene bodies of zinc finger and BTB domain containing 47 (ZBTB47), HIVEP zinc finger 3 (HIVEP3) and insulin like growth factor 2 mRNA binding protein 1 (IGF2BP1). Further studies are needed to evaluate whether epigenetic dysregulation is a commonly observed phenomena in polluted populations, and what the consequences are for organism functioning and for population dynamics.