bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting cause of death from free-text health summaries: development of an interpretable machine learning tool
Authors: McWilliams Chris , Walsh Eleanor I. , Huxor Avon , Turner Emma L. , Santos-Rodriguez Raul 
Published: July 2021

Structured AbstractPurposeAccurately assigning cause of death is vital to understanding health outcomes in the population and improving health care provision. Cancer-specific cause of death is a key outcome in clinical trials, but assignment of cause of death from death certification is prone to misattribution, therefore can have an impact on cancer-specific trial mortality outcome measures.MethodsWe developed an interpretable machine learning classifier to predict prostate cancer death from free-text summaries of medical history for prostate cancer patients (CAP). We developed visualisations to highlight the predictive elements of the free-text summaries. These were used by the project analysts to gain an insight of how the predictions were made.ResultsCompared to independent human expert assignment, the classifier showed >90% accuracy in predicting prostate cancer death in test subset of the CAP dataset. Informal feedback suggested that these visualisations would require adaptation to be useful to clinical experts when assessing the appropriateness of these ML predictions in a clinical setting. Notably, key features used by the classifier to predict prostate cancer death and emphasised in the visualisations, were considered to be clinically important signs of progressing prostate cancer based on prior knowledge of the dataset.ConclusionThe results suggest that our interpretability approach improve analyst confidence in the tool, and reveal how the approach could be developed to produce a decision-support tool that would be useful to health care reviewers. As such, we have published the code on GitHub to allow others to apply our methodology to their data (https://zenodo.org/badge/latestdoi/294910364).
Mmp-13 deletion in cells of the mesenchymal lineage increases bone mass, decreases endocortical osteoclast number, and attenuates the cortical bone loss caused by estrogen deficiency in mice
Authors: Ponte Filipa , Kim Ha-Neui , Warren Aaron , Iyer Srividhya , Han Li , Mannen Erin , Gomez-Acevedo Horacio , Nookaew Intawat , Almeida Maria , Manolagas Stavros C. 
Published: July 2021

AbstractThe protective effect of estrogens against cortical bone loss is mediated via direct actions on mesenchymal lineage cells, but functional evidence for the precise molecular mechanism(s) and the mediators of these effects has only recently began to emerge. We report that the matrix metalloproteinase 13 (MMP-13) is the highest up-regulated gene in calvaria or bone marrow cells from mice lacking the estrogen receptor (ER) alpha in osteoprogenitors. We, therefore, generated mice with conditional Mmp-13 deletion in Prrx1 expressing cells (Mmp-13ΔPrrx1) and compared the effect of estrogen deficiency on their bone phenotype to that of control littermates (Mmp-13f/f). Femur and tibia length was decreased in sham-operated Mmp-13ΔPrrx1 mice as compared to Mmp-13f/f. Cortical thickness and trabecular bone volume in the femur and tibia were increased and osteoclast number at the endocortical surfaces was decreased in the sham-operated female Mmp-13ΔPrrx1 mice; whereas bone formation rate was unaffected. Ovariectomy (OVX) caused a decrease of cortical thickness in the femur and tibia of Mmp-13f/f control mice. This effect was attenuated in the Mmp-13ΔPrrx1 mice; but the decrease of trabecular bone caused by OVX was not affected. These results reveal that mesenchymal cell–derived MMP-13 regulates osteoclast number, bone resorption, and bone mass. We have recently reported that the loss of cortical, but not trabecular bone, caused by OVX is also attenuated in Cxcl12ΔPrrx1 mice. Together with the present report, this functional genetic evidence provides proof of principle that increased production of mesenchymal cell-derived factors, such as CXCL12 and MMP-13, are important mediators of the adverse effect of estrogen deficiency on cortical, but not trabecular, bone. Therefore, the mechanisms responsible for the protective effect of estrogens on these two major bone compartments are different.
Hypersensitivity of MAIT cells to Leukocidin ED indicates a Staphylococcus aureus immune evasion mechanism targeting the innate effector cell response
Authors: Boulouis Caroline , Leeansyah Edwin , Shambat Srikanth Mairpady , Norrby-Teglund Anna , Sandberg Johan K. 
Published: July 2021

AbstractMucosa-associated invariant T (MAIT) cells recognize bacterial riboflavin metabolite antigens presented by MR1 and play an important role in antimicrobial immune defense. Staphylococcus aureus is a pathobiont expressing a range of virulence factors including the secreted toxin Leukocidin ED (LukED), which binds to certain chemokine receptors and causes cell death by osmolysis. Here, we investigated the effect of LukED on subsets of human T cells and NK cells that are involved in the early innate response to infection. MAIT cells were strikingly hypersensitive to LukED-mediated lysis and rapidly lost from the peripheral blood T cell pool upon exposure to the toxin, leaving a T cell population devoid of MAIT cells. The cytolytic effect of LukED on MAIT cells was rapid, occurred at lower LukED concentration compared to effects on the overall T cell pool, and coincided with extraordinarily high and uniform expression of CCR5. Furthermore, loss of MAIT cells was efficiently inhibited by the CCR5 inhibitor Maraviroc. Interestingly, pre-activation of MAIT cells with IL-12 and IL-18 also partially rescued these cells from LukED toxicity. Among NK cells, LukED targeted the more mature and cytotoxic CD57+ NK cell subset in a CXCR1-dependent manner. Overall, these results indicate that LukED efficiently eliminates cells of the human immune system that have the capacity to respond rapidly to S. aureus in an innate fashion, and that MAIT cells are exceptionally vulnerable to this toxin. Thus, the findings support a model where LukED functions as a S. aureus immune evasion mechanism to avoid recognition by the rapid cell-mediated responses mediated by MAIT cells and NK cells.
The most comprehensive annotation of the Krill transcriptome provides new insights for the study of physiological processes and environmental adaptation
Authors: Urso Ilenia , Biscontin Alberto , Corso Davide , Bertolucci Cristiano , Romualdi Chiara , De Pittà Cristiano , Meyer Bettina , Sales Gabriele 
Published: July 2021

AbstractThe krill species Euphausia superba plays a critical role in the food chain of the Antarctic ecosystem, as the abundance of its biomass affects trophic levels both below it and above. Major changes in climate conditions observed in the Antarctic Peninsula region in the last decades have already altered the distribution of the krill population and its reproductive dynamics. A deeper understanding of the adaptation capabilities of this species, and of the molecular mechanisms behind it are urgently needed. The availability of a large body of RNA-seq assays gave us the opportunity to extend the current knowledge of the krill transcriptome, considerably reducing errors and redundancies. Our study covered the entire developmental process, from larval stages to adult individuals, providing information of central relevance for ecological studies. Here we describe the KrillDB2 database, a resource combining the latest annotation of the krill transcriptome with a series of analyses specifically targeting genes and molecular processes relevant to krill physiology. KrillDB2 provides in a single resource the most complete collection of experimental data and bioinformatic annotations: it includes an extended catalog of krill genes; an atlas of their expression profiles over all RNA-seq datasets publicly available; a study of differential expression across multiple conditions such as developmental stages, geographical regions, seasons, and sexes. Finally, it provides initial indications about non-coding RNAs, a class of molecules whose contribute to krill physiology has never been reported before.
An Ecological Approach to the Effects of Water-Source Locations and Time-Based Schedules on Entropy and Spatio-Temporal Behavioral Features
Authors: Hernández Varsovia , León Alejandro , Guzmán Isiris , Díaz Fryda , Avendaño Garrido Martha Lorena , Hernández Porfirio Toledo , Hernández Linares Carlos Alberto , Luna Itzel 
Published: July 2021

AbstractIn behavior analysis, the modulation of the effect of time-based schedules by the spatial characteristics of the environment has been scarcely studied. Furthermore, the spatial organization of behavior, despite its ubiquity and ecological relevance, has not been widely addressed. The purpose of the present work was to analyze the effect of water delivery location (peripheral vs. central) on the spatial organization of water-feeding behavior under time-based schedules. One group of rats was exposed to a Fixed Time 30 s-water-delivery schedule and a second group to a Variable Time 30 s schedule. For both groups, in the first phase, the water dispenser was located in the perimetral zone. In the second condition, the water dispenser was located in the central zone. Each location was presented for 20 sessions. Rat’s trajectories, distance to the dispenser, accumulated time in regions, and entropy measures were analyzed. A differential effect of the location of water delivery in interaction with the time-based schedule was observed on all the analyzed spatial qualities of behavior. The findings are discussed in relation to the ecological proposal of Timberlake’s behavioral systems.
Mapping inter-individual functional connectivity variability in TMS targets for major depressive disorder
Authors: Harita Shreyas , Momi Davide , Mazza Frank , Griffiths John D. 
Published: July 2021

AbstractTranscranial magnetic stimulation (TMS) is an emerging alternative to existing treatments for major depressive disorder (MDD). The effects of TMS on both brain physiology and therapeutic outcomes are known to be highly variable from subject to subject, however. Proposed reasons for this variability include individual differences in neurophysiology, in cortical geometry, and in brain connectivity. Standard approaches to TMS target site definition tend to focus on coordinates or landmarks within the individual brain regions implicated in MDD, such as the dorsolateral prefrontal cortex (dlPFC) and orbitofrontal cortex (OFC). Additionally considering the network connectivity of these sites has the potential to improve subject-specificity of TMS targeting and, in turn, improve treatment outcomes. We looked at the functional connectivity (FC) of dlPFC and OFC TMS targets, based on induced electrical field (E-field) maps, estimated using the SimNIBS library. We generated individualized E-field maps on the cortical surface for 121 subjects from the Human Connectome Project database using tetrahedral head models generated from T1-weighted MR images. We analyzed inter-subject variability in the shape and location of these TMS target E-field patterns, their FC, and the major functional networks to which they belong. Our results revealed the key differences in TMS target FC between the dlPFC and OFC, and also how this connectivity varies across subjects. Three major functional networks were targeted across the dlPFC and OFC: the ventral attention, fronto-parietal and default-mode networks in the dlPFC, and the fronto-parietal and default mode networks in the OFC. Inter-subject variability in cortical geometry and in FC was high. Our results characterize the FC patterns of canonical therapeutic TMS targets, and the key dimensions of their variability across subjects. The high inter-individual variability in cortical geometry and FC, leading to high variability in distributions of targeted brain networks, may account for the high levels of variability in physiological and therapeutic TMS outcomes. These insights should, we hope, prove useful as part of the broader effort by the psychiatry, neurology, and neuroimaging communities to help improve and refine TMS therapy, through a better understanding of the technology and its neurophysiological effects.HighlightsE-field modelling and functional connectivity used to study TMS targets (dlPFC,OFC)Considerable variability in TMS target E-field patterns seen across subjectsLarge inter-subject differences in target connectivity observed and characterizedMajor functional networks targeted by dlPFC, OFC TMS were the VAN, FPN and DMNInsights can contribute to improved and more personalized TMS therapies in the future
GPR39 Localization in Aging Human Brain and Correlation of Expression and Polymorphism with Vascular Cognitive Impairment
Authors: Davis Catherine M , Bah Thierno M , Zhang Wenri H , Nelson Jonathan W , Golgotiu Kirsti , Nie Xiao , Alkayed Farah N , Young Jennifer M , Woltjer Randy L , Silbert Lisa C , Grafe Marjorie R , Alkayed Nabil J 
Published: July 2021

AbstractINTRODUCTIONThe pathogenesis of vascular cognitive impairment (VCI) is not fully understood. GPR39, an orphan G-protein coupled receptor, is implicated in neurological disorders but its role in VCI is unknown.METHODSWe performed GPR39 immunohistochemical analysis in postmortem brain samples from mild cognitive impairment (MCI) and control subjects. DNA was analyzed for GPR39 SNPs, and correlated with white matter hyperintensity (WMH) burden on premortem MRI.RESULTSGPR39 is expressed in aged human dorsolateral prefrontal cortex, localized to microglia and peri-capillary cells resembling pericytes. GPR39-capillary colocalization, and density of GPR39-expressing microglia was increased in aged brains compared to young. SNP distribution was equivalent between groups; however, homozygous SNP carriers were present only in the MCI group, and had higher WMH volume than WT or heterozygous SNP carriers.DISCUSSIONGPR39 may play a role in aging-related VCI, and may serve as a therapeutic target and biomarker for the risk of developing VCI.
Modeling transcriptional profiles of gene perturbation with deep neural network
Authors: Liu Wenke , Wang Xuya , Mani D R , Fenyö David 
Published: July 2021

AbstractBackgroundCell line perturbation data could be utilized as a reference for inferring underlying molecular processes in new gene expression profiles. It is important to develop accurate and computationally efficient algorithms to exploit biological knowledge in the growing compendium of existing perturbation data and harness these for new predictions.ResultsWe reframed the problem of inferring possible gene perturbation based on a reference perturbation database into a classification task and evaluated the application of deep neural network models to address this problem. Our results showed that a fully-connected multi-layer neural network was able to achieve up to 74.9% accuracy in a holdout test set, but the model generalizability was limited by consistency between training and testing data.ConclusionCapacity and flexibility enables neural network models to efficiently represent transcriptomic features associated with single gene knockdown perturbations. With consistent signals between training and testing sets, neural networks may be trained to classify new samples to experimentally confirmed molecular phenotypes.
Crosstalk between Flavonoids and the Plant Circadian Clock
Authors: Hildreth Sherry B. , Littleton Evan S. , Clark Leor C. , Puller Gabrielle C. , Kojima Shihoko , Winkel Brenda S.J. 
Published: July 2021

AbstractFlavonoids are a well-known class of specialized metabolites that play key roles in plant development, reproduction, and survival. Flavonoids are also of considerable interest from the perspective of human health, both as phytonutrients and pharmaceuticals. RNA-Seq analysis of an Arabidopsis null allele for chalcone synthase (CHS), which catalyzes the first step in flavonoid biosynthesis, has uncovered evidence that these compounds influence the expression of circadian clock genes in plants. Analysis of promoter-luciferase constructs showed that the transcriptional activity of genes encoding two components of the central clock,CCA1andTOC1, across the day/night cycle is altered in CHS-deficient seedlings. The effect of flavonoids on circadian function was furthermore reflected in photosynthetic activity, with chlorophyll cycling abolished in the mutant line. Analysis of a mutant lacking flavonoid 3’-hydroxylase (F3’H) activity, and thus able to synthesize mono- but not di-hydroxylated B-ring flavonoids, suggests that the latter are at least partially responsible, as further supported by the effects of quercetin onCCA1promoter activity in wild-type seedlings. Collectively, these experiments point to a previously-unknown connection between flavonoids and circadian cycling in plants and open the way to better understanding of the molecular basis of flavonoid action.
GuPPy, a Python toolbox for the analysis of fiber photometry data
Authors: Sherathiya Venus N. , Schaid Michael D. , Seiler Jillian L. , Lopez Gabriela C. , Lerner Talia N. 
Published: July 2021

ABSTRACTFiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages. However, analysis of FP data can be a challenge for new users, especially those with a limited programming background. Here, we present Guided Photometry Analysis in Python (GuPPy), a free and open-source FP analysis tool. GuPPy is provided as a Jupyter notebook, a well-commented interactive development environment (IDE) designed to operate across platforms. GuPPy presents the user with a set of graphic user interfaces (GUIs) to load data and provide input parameters. Graphs produced by GuPPy can be exported into various image formats for integration into scientific figures. As an open-source tool, GuPPy can be modified by users with knowledge of Python to fit their specific needs.
Data-independent acquisition protease-multiplexing enables increased proteome sequence coverage across multiple fragmentation modes
Authors: Richards Alicia L. , Chen Kuei-Ho , Wilburn Damien B. , Stevenson Erica , Polacco Benjamin J. , Searle Brian C. , Swaney Danielle L. 
Published: July 2021

AbstractThe use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments, however due to the additional analysis time required, it has not been widely adapted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing approach that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize data acquisition conditions for each protease individually with both the canonical DIA fragmentation mode (beam type CID), as well as resonance excitation CID, to determine optimal consensus conditions across proteases. Next, we demonstrate that application of these conditions to a protease-multiplexed sample of human peptides results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, and a 27% increase non-redundant amino acid detections. Importantly, this resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as proteoform analysis.
Cellular signaling beyond the Wiener-Kolmogorov limit
Authors: Weisenberger Casey , Hathcock David , Hinczewski Michael 
Published: July 2021

ABSTRACTAccurate propagation of signals through stochastic biochemical networks involves significant expenditure of cellular resources. The same is true for regulatory mechanisms that suppress fluctuations in biomolecular populations. Wiener-Kolmogorov (WK) optimal noise filter theory, originally developed for engineering problems, has recently emerged as a valuable tool to estimate the maximum performance achievable in such biological systems for a given metabolic cost. However, WK theory has one assumption that potentially limits its applicability: it relies on a linear, continuum description of the reaction dynamics. Despite this, up to now no explicit test of the theory in nonlinear signaling systems with discrete molecular populations has ever seen performance beyond the WK bound. Here we report the first direct evidence the bound being broken. To accomplish this, we develop a theoretical framework for multi-level signaling cascades, including the possibility of feedback interactions between input and output. In the absence of feedback, we introduce an analytical approach that allows us to calculate exact moments of the stationary distribution for a nonlinear system. With feedback, we rely on numerical solutions of the system’s master equation. The results show WK violations in two common network motifs: a two-level signaling cascade and a negative feedback loop. However the magnitude of the violation is biologically negligible, particularly in the parameter regime where signaling is most effective. The results demonstrate that while WK theory does not provide strict bounds, its predictions for performance limits are excellent approximations, even for nonlinear systems.
Functional analyses of phosphatidylserine/PI(4)P exchangers with diverse lipid species and membrane contexts set unanticipated rules on lipid transfer
Authors: Ikhlef Souade , Lipp Nicolas-Frédéric , Delfosse Vanessa , Fuggetta Nicolas , Bourguet William , Magdeleine Maud , Drin Guillaume 
Published: July 2021

AbstractSeveral members of the oxysterol-binding protein-related proteins (ORPs)/oxysterol-binding homology (Osh) family exchange phosphatidylserine (PS) and phosphatidylinositol 4-phosphate (PI(4)P) at the endoplasmic reticulum/plasma membrane (PM) interface. It is unclear whether they preferentially exchange PS and PI(4)P with specific acyl chains to tune the features of the PM, whether they use phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) instead of PI(4)P for exchange processes and whether their activity is influenced by the association of PS with sterol in the PM. Here, we measured in vitro how the yeast Osh6p and human ORP8 transported diverse PS and PI(4)P subspecies, including major cellular species, between membranes. We established how their activity is impacted by the length and unsaturation degree of these lipids. Surprisingly, the speed at which they individually transfer these ligands inversely depends on their affinity for them. To be fast, the transfer of high-affinity ligands requires their exchange for a counterligand of equivalent affinity. Besides, we determined that Osh6p and ORP8 cannot use PI(4,5)P2 for intracellular lipid exchange, as they have a low affinity for this lipid compared to PI(4)P, and do not transfer more PS into sterol-rich membranes. This study provides insights into PS/PI(4)P exchangers and sets unanticipated rules on how the activity of lipid transfer proteins relates to their affinity for ligands.