bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross-sectional and longitudinal associations of threat and deprivation on cognition, emotional processing and psychopathology in children and adolescents
Authors: Schäfer Julia Luiza , McLaughlin Katie A. , Manfro Gisele Gus , Pan Pedro , Rohde Luis Augusto , Miguel Eurípedes Constantino , Salum Giovanni Abrahão 
Published: February 2020

AbstractBackgroundExposure to childhood adversity has been consistently associated with poor developmental outcomes, but it is unclear whether these associations vary across different forms of adversity. We examined cross-sectional and longitudinal associations between two types of adversity—threat and deprivation—with cognition, emotional processing, and psychopathology in a middle-income country.MethodsThe sample consisted of 2,511 children and adolescents (6-17 years old) from the Brazilian High-Risk Cohort for Psychiatric Disorders. Parent reports on childhood adversity were used to construct threat and deprivation latent constructs. Psychopathology was measured by the CBCL which generated a measure of general psychopathology (the “p” factor). Executive function (EF) and attention orienting toward angry faces were assessed using cognitive tasks. All measures were acquired at two time-points 3-years apart. Cross-lagged panel models were estimated to evaluate longitudinal associations.ResultsPsychopathology was associated with threat and deprivation cross-sectionally, and higher levels of threat and deprivation predicted increases in general psychopathology at follow-up. For EF, worse performance was more strongly associated with deprivation than threat at baseline, and only with deprivation at follow-up. Deprivation was associated with attention orienting away from angry faces cross-sectionally, but neither form of adversity was associated with changes over time in attention bias.ConclusionBoth types of adversity are associated with current and future psychopathology and with current, but not future, EF. Threat was more strongly linked to higher psychopathology, whereas deprivation was more strongly linked to lower EF. Lack of longitudinal associations between deprivation and EF mean reverse causality cannot be excluded.
Interfruit : Deep Learning Network for Classifying Fruit Images
Authors: Liu Wenzhong 
Published: February 2020

AbstractFruit classification is conductive to improving the self-checkout and packaging systems. The convolutional neural networks automatically extract features through the direct processing of original images, which has attracted extensive attention from researchers in fruit classification. However, due to the similarity of fruit color, it is difficult to recognize at a higher accuracy. In the present study, a deep learning network, Interfruit, was built to classify various types of fruit images. A fruit dataset involving 40 categories was also constructed to train the network model and to assess its performance. According to the evaluation results, the overall accuracy of Interfruit reached 93.17% in the test set, which was superior to that of several advanced methods. According to the findings, the classification system, Interfruit, recognizes fruits with high accuracy, which has a broad application prospect.
Delta Oscillations Are a Robust Biomarker of Dopamine Depletion Severity and Motor Dysfunction in Awake Mice
Authors: Whalen Timothy C. , Willard Amanda M. , Rubin Jonathan E. , Gittis Aryn H. 
Published: February 2020

AbstractDelta oscillations (0.5–4 Hz) are a robust but often overlooked feature of basal ganglia pathophysiology in Parkinson’s disease and their relationship to parkinsonian akinesia has not been investigated. Here, we establish a novel approach to detect spike oscillations embedded in noise to provide the first study of delta oscillations in awake, dopamine depleted mice. We find that approximately half of neurons in the substantia nigra reticulata exhibit delta oscillations in dopamine depletion and that these oscillations are a strong indicator of dopamine loss and akinesia, outperforming measures such as changes in firing rate, irregularity, bursting and synchrony. We further establish that these oscillations are caused by the loss of D2 receptor activation and do not require motor cortex, contrary to previous findings in anesthetized animals. These results give insight into how dopamine loss leads to dysfunction and suggest a reappraisal of delta oscillations as a biomarker in Parkinson’s disease.
Axonal mechanisms mediating GABA-A receptor inhibition of striatal dopamine release
Authors: Kramer Paul F. , Twedell Emily L. , Shin Jung Hoon , Zhang Renshu , Khaliq Zayd M. 
Published: February 2020

AbstractAxons of midbrain dopaminergic neurons innervate the striatum where they contribute to movement and reinforcement learning. Past work has shown that striatal GABA tonically inhibits dopamine release, but whether GABA-A receptors directly modulate transmission or act indirectly through circuit elements is unresolved. Here, we use whole-cell and perforated-patch recordings to test for GABA-A receptors on the main dopaminergic neuron axons and branching processes within striatum. Application of GABA depolarized axons, but also decreased the amplitude of axonal spikes, limited propagation and reduced striatal dopamine release. The mechanism of inhibition involved sodium channel inactivation and shunting. Lastly, we show that the positive allosteric modulator diazepam enhanced GABA-A currents on dopaminergic neuron axons and directly inhibited release, but also likely acts by reducing excitatory drive from cholinergic interneurons. Thus, we reveal the mechanisms of GABA-A receptor modulation of dopamine release and provide new insight into the actions of benzodiazepines within the striatum.
High-throughput multivariable Mendelian randomization analysis prioritizes apolipoprotein B as key lipid risk factor for coronary artery disease
Authors: Zuber Verena , Gill Dipender , Ala-Korpela Mika , Langenberg Claudia , Butterworth Adam , Bottolo Leonardo , Burgess Stephen 
Published: February 2020

BackgroundGenetic variants can be used to prioritize risk factors as potential therapeutic targets via Mendelian randomization (MR). An agnostic statistical framework using Bayesian model averaging (MR-BMA) can disentangle the causal role of correlated risk factors with shared genetic predictors. Here, our objective is to identify lipoprotein measures as mediators between lipid-associated genetic variants and coronary artery disease (CAD) for the purpose of detecting therapeutic targets for CAD.MethodsAs risk factors we consider 30 lipoprotein measures and metabolites derived from a high-throughput metabolomics study including 24,925 participants. We fit multivariable MR models of genetic associations with CAD estimated in 453,595 participants (including 113,937 cases) regressed on genetic associations with the risk factors. MR-BMA assigns to each combination of risk factors a model score quantifying how well the genetic associations with CAD are explained. Risk factors are ranked by their marginal score and selected using false discovery rate (FDR) criteria. We perform sensitivity and replication analyses varying the dataset for genetic associations with CAD.ResultsIn the main analysis, the top combination of risk factors ranked by the model score contains apolipoprotein B (ApoB) only. ApoB is also the highest ranked risk factor with respect to the marginal score (FDR< 0.005). Additionally, ApoB is selected in all replication analyses. No other measure of cholesterol or triglyceride is consistently selected otherwise.ConclusionsOur agnostic genetic investigation prioritizes ApoB across all datasets considered, suggesting that ApoB, representing the total number of hepatic-derived lipoprotein particles, is the primary lipid determinant of CAD.Key messagesIt is a common consensus that lipoproteins increase cardiovascular disease risk, yet little is known about the exact mechanisms.We use genetic associations with high-throughput metabolomics features to draw a detailed picture of lipid traits and characteristics allowing for an unprecedented resolution when considering lipids as risk factors for cardiovascular disease.This study integrates genetic data from a large scale metabolomics study including 25,000 samples and the largest study on cardiovascular disease risk including 113,937 cases and 339,658 controls.MR-BMA, a novel algorithm for multivariable MR (Zuber and Burgess, Nature Communications 2020; 11(1):29) is used to identify the most likely causal lipid determinants of cardiovascular disease from a large set of candidate risk factors with shared genetic predictors.Our agnostic genetic investigation prioritizes apolipoprotein B across all datasets considered, suggesting that apolipoprotein B, representing the total number of hepatic-derived lipoprotein particles, is the primary lipid determinant of cardiovascular disease risk.
The Omics Discovery REST interface
Authors: Dass Gaurhari , Vu Manh-Tu , Xu Pan , Audain Enrique , Hitz Marc-Phillip , Hermjakob Henning , Perez-Riverol Yasset 
Published: February 2020

AbstractThe Omics Discovery Index is an open source platform that can be used to access, discover and disseminate omics datasets. OmicsDI integrates proteomics, genomics, metabolomics, models and transcriptomics datasets. Using an efficient indexing system, OmicsDI integrates different biological entities including genes, transcripts, proteins, metabolites and the corresponding publications from PubMed. In addition, it implements a group of pipelines to estimate the impact of each dataset by tracing the number of citations, reanalysis and biological entities reported by each dataset. Here, we present the OmicsDI REST interface to enable programmatic access to any dataset in OmicsDI or all the datasets for a specific provider (database). Clients can perform queries on the API using different metadata information such as sample details (species, tissues, etc), instrumentation (mass spectrometer, sequencer), keywords and other provided annotations. In addition, we present two different libraries in R and Python to facilitate the development of tools that can programmatically interact with the OmicsDI REST interface.
Association of gut microbiota with metabolism in juvenile Atlantic Salmon
Authors: Dvergedal H. , Sandve S.R. , Angell I.L. , Klemetsdal G. , Rudi K. 
Published: February 2020

AbstractThe gut microbiome plays a key role in animal health and metabolism through the intricate functional interconnection between the feed, gut microbes, and the host. Unfortunately, in aquaculture, the links between gut microbes and fish genetics and production phenotypes are not well understood.In this study, we investigate the associations between gut microbial communities, fish feed conversion, and fish genetics in the domestic Atlantic salmon. Microbial community composition was determined for 230 juvenile fish from 23 full-sib families and was then regressed on growth, carbon and nitrogen metabolism, and feed efficiency. We only found weak associations between host genetics and microbial composition. However, we did identify significant (p< 0.05) associations between the abundance of three microbial operational taxonomical units (OTUs) and fish metabolism phenotypes. Two OTUs were associated with both carbon metabolism in adipose tissue and feed efficiency, while a third OTU was associated with weight gain.In conclusion, this study demonstrates an intriguing association between host lipid metabolism and the gut microbiota composition in Atlantic salmon.
Spatiotemporal control of cell cycle acceleration during axolotl spinal cord regeneration
Authors: Costa Emanuel Cura , Otsuki Leo , Albors Aida Rodrigo , Tanaka Elly M. , Chara Osvaldo 
Published: February 2020

AbstractAxolotls are uniquely able to resolve spinal cord injuries, but little is known about the mechanisms underlying spinal cord regeneration. We previously found that tail amputation leads to reactivation of a developmental-like program in spinal cord ependymal cells (Rodrigo Alborset al., 2015), characterized by a high-proliferation zone emerging 4 days post-amputation (Rostet al., 2016). What underlies this spatiotemporal pattern of cell proliferation, however, remained unknown. Here, we use modelling, tightly linked to experimental data, to demonstrate that this regenerative response is consistent with a signal that recruits ependymal cells during 85 hours after amputation within~830□m of the injury. We adapted FUCCI technology to axolotls (AxFUCCI) to visualize cell cycles in vivo. AxFUCCI axolotls confirmed the predicted appearance time and size of the injury-induced recruitment zone and revealed cell cycle synchrony between ependymal cells. Our modeling and imaging move us closer to understanding bona fide spinal cord regeneration.
Unfolded protein response and scaffold independent pheromone MAP kinase signalling controlVerticillium dahliaegrowth, development and plant pathogenesis
Authors: Starke Jessica , Harting Rebekka , Maurus Isabel , Bremenkamp Rica , Kronstad James W. , Braus Gerhard H. 
Published: February 2020

SummaryDevelopment and virulence of the vascular plant pathogenVerticillium dahliaeare connected and depend on a complex interplay between the unfolded protein response, a Ham5 independent pheromone MAP kinase module and formation of precursors for oxylipin signal molecules.Genes coding for the unfolded protein response regulator Hac1, the Ham5 MAPK scaffold protein, and the oleate Δ12-fatty acid desaturase Ode1 were deleted and their functions in growth, differentiation, and virulence on plants were studied using genetic, cell biology, and plant infection experiments.The unfolded protein response transcription factor Hac1 is required for initial root colonization, fungal conidiation and propagation inside the host and is essential for resting structure formation. Microsclerotia development, growth and virulence require the pheromone response MAPK pathway, but without the Ham5 scaffold function. Single ER-associated enzymes for linoleic acid production make important contributions to fungal growth but have only a minor impact on the pathogenicity ofV. dahliae.Fungal growth, sporulation, dormant structure formation and plant infection require a network of the Hac1-regulated unfolded protein response, a scaffold-independent pheromone response MAPK pathway and formation of precursors for signalling. This network includes interesting targets for disease management of the vascular pathogenV. dahliae.
An Image-Based Data-Driven Analysis of Cellular Architecture in a Developing Tissue
Authors: Hartmann Jonas , Wong Mie , Gallo Elisa , Gilmour Darren 
Published: February 2020

ABSTRACTQuantitative microscopy is becoming increasingly crucial in efforts to disentangle the complexity of organogenesis, yet adoption of the potent and ever-growing toolbox provided by modern data science has been slow, primarily because data-driven tools focus on “big data” whereas microscopy produces “rich data”. We tackle this issue using a newly developed algorithm for point cloud-based morphometry to unpack the rich information encoded in high-resolution 3D image data into a straightforward numerical representation. This allowed us to employ machine learning for multi-modal data integration of cell morphology, intracellular organization, gene expression and annotated contextual knowledge that facilitates data exploration. We apply these techniques to construct and explore a quantitative atlas of cellular architecture for the zebrafish posterior lateral line primordium, an experimentally tractable model of complex self-organized organogenesis. In doing so, we are able to retrieve both previously established and novel biologically relevant patterns, demonstrating the potential of our data-driven approach.
DYRK3-Controlled Phase Separation Organizes the Early Secretory Pathway
Authors: Gallo Raffaella , Rai Arpan , Pelkmans Lucas 
Published: February 2020

SummaryThe dual-specificity kinase DYRK3 controls formation and dissolution of several intracellular condensates thereby regulating various cell physiological processes. Here we report that DYRK3 establishes a dynamic equilibrium between condensation and dissolution of proteins associated with membranous structures of the early secretory pathway to organize membrane traffic between the ER and the Golgi complex in mammalian cells. This depends on the peripheral membrane protein Sec16A, whose N-terminal disordered region forms DYRK3-controlled liquid-like condensates on the surface of the ER and co-phase separates with multiple ER exit site components and a subset of matrix proteins specifically associated with ERGIC and cis-Golgi. Our findings support a mechanism whereby multiple interacting and differentially regulated intracellular condensates create favorable environments for directional membrane traffic in eukaryotic cells.
Repurposing of KLF5 activates a cell cycle signature during the progression from a precursor state to Oesophageal Adenocarcinoma
Authors: Rogerson Connor , Ogden Samuel , Britton Edward ,   the OCCAMS consortium, Ang Yeng , Sharrocks Andrew D. 
Published: February 2020

AbstractOesophageal adenocarcinoma (OAC) is one of the most common causes of cancer deaths and yet compared to other common cancers, we know relatively little about the underlying molecular mechanisms. Barrett’s oesophagus (BO) is the only known precancerous precursor to OAC, but our understanding about the specific events leading to OAC development is limited. Here, we have integrated gene expression and chromatin accessibility profiles of human biopsies of BO and OAC and identified a strong cell cycle gene expression signature in OAC compared to BO. Through analysing associated chromatin accessibility changes, we have implicated the transcription factor KLF5 in the transition from BO to OAC. Importantly, we show that KLF5 expression is unchanged during this transition, but instead, KLF5 is redistributed across chromatin in OAC cells to directly regulate cell cycle genes specifically in OAC. Our findings have potential prognostic significance as the survival of patients with high expression of KLF5 target genes is significantly lower. We have provided new insights into the gene expression networks in OAC and the mechanisms behind progression to OAC, chiefly the repurposing of KLF5 for novel regulatory activity in OAC.
Metrics for Public Health Perspective Surveillance of Bacterial Antibiotic Resistance in Low- and Middle-Income Countries
Authors: Auguet Olga Tosas , Niehus Rene , Gweon Hyun Soon , Berkley James A. , Waichungo Joseph , Njim Tsi , Edgeworth Jonathan D. , Batra Rahul , Chau Kevin , Swann Jeremy , Walker Sarah A. , Peto Tim E. A. , Crook Derrick W. , Lamble Sarah , Turner Paul , Cooper Ben S. , Stoesser Nicole 
Published: February 2020

AbstractAntimicrobial resistance (AMR) is a global health threat, especially in low-/middle-income countries (LMICs), where there is limited surveillance to inform empiric antibiotic treatment guidelines. Enterobacterales are amongst the most important causes of drug-resistant bacterial infections. We developed a novel AMR surveillance approach for Enterobacterales by profiling pooled human faecal metagenomes from three sites (n=563 individuals; Cambodia, Kenya, UK) to derive a taxonomy-adjusted AMR metric (“resistance potential”) which could be used to predict the aggregate percentage of resistant invasive Enterobacterales infections within each setting. Samples were sequenced (Illumina); taxonomic and resistance gene profiling was performed using ResPipe. Data on organisms causing bacteraemia and meningitis and antibiotic susceptibility test results from 2010-2017 were collated for each site. Bayesian generalised linear models with a binomial likelihood were fitted to determine the capacity of the resistance potential to predict AMR in Enterobacterales infections in each setting. The most informative model accurately predicted the numbers of resistant infections in the target populations for 14/14 of antibiotics in the UK, 12/12 in Kenya, and 9/12 in Cambodia. Intermittent metagenomics of pooled human samples could represent a powerful pragmatic and economical approach for determining and monitoring AMR in clinical infections, especially in resource-limited settings.
Ursolic acid improves the bacterial community mapping of the intestinal tract in liver fibrosis mice
Authors: Wan Sizhe , Huang Chenkai 
Published: February 2020

ABSTRACTLiver fibrosis often appears in chronic liver disease, with extracellular matrix (ECM) deposition as the main feature. Due to the presence of the liver-gut axis, the destruction of intestinal homeostasis is often accompanied by the development of liver fibrosis. The inconsistent ecological environment of different intestinal sites may lead to differences in the microbiota. The traditional Chinese medicine Ursolic acid (UA) has been proven to protect the liver from fibrosis. We investigated the changes in the microbiota of different parts of the intestine during liver fibrosis and the effect of UA on these changes based on high-throughput sequencing technology. Sequencing results suggest that the diversity and abundance of intestinal microbiota decline and the composition of the microbiota is disordered, the potentially beneficial Firmicutes bacteria are reduced, and the pathways for functional prediction are changed in the ilea and anal faeces of liver fibrosis mice compared with normal mice. However, in UA-treated liver fibrosis mice, these disorders improved. It is worth noting that the bacterial changes in the ilea and anal faeces are not consistent. In conclusion, in liver fibrosis, the microbiota of different parts of the intestines have different degrees of disorder, and UA can improve this disorder. This may be a potential mechanism for UA to achieve anti-fibrosis. This study provides theoretical guidance for the UA targeting of intestinal microbiota for the treatment of liver fibrosis.
Astroglial FMRP modulates synaptic signaling and behavior phenotypes in FXS mouse model
Authors: Jin Shan-Xue , Higashimori Haruki , Schin Christina , Tamashiro Alessandra , Men Yuqin , Chiang Ming Sum R , Jarvis Rachel , Cox Dan , Feig Larry , Yang Yongjie 
Published: February 2020

AbstractFragile X syndrome (FXS) is one of the most common inherited intellectual disability (ID) disorders, in which the loss of FMRP protein induces a range of cellular signaling changes primarily through excess protein synthesis. Although neuron-centered molecular and cellular events underlying FXS have been characterized, how different CNS cell types are involved in typical FXS synaptic signaling changes and behavioral phenotypes is largely unknown. Recent evidence suggests that selective loss of astroglial FMRP is able to dysregulate glutamate uptake, increase spine density, and impair motor-skill learning. Here we investigated the effect of astroglial FMRP on synaptic signaling and FXS-related behavioral and learning phenotypes in astroglial Fmr1 cKO and cON mice in which FMRP expression is selectively diminished or restored in astroglia. We found that selective loss of astroglial FMRP contributes to cortical hyperexcitability by enhancing NMDAR-mediated evoked but not spontaneous miniEPSCs and elongating cortical UP state duration. Selective loss of astroglial FMRP is also sufficient to increase locomotor hyperactivity, significantly diminish social novelty preference, and induce memory acquisition and extinction deficits in astroglial Fmr1 cKO mice. Importantly, re-expression of astroglial FMRP is able to significantly rescue the hyperactivity (evoked NMDAR response, UP state duration, and open field test) and social novelty preference in astroglial Fmr1 cON mice. These results demonstrate a profound role of astroglial FMRP in the evoked synaptic signaling, spontaneously occurring cortical UP states, and FXS-related behavioral and learning phenotypes and provide important new insights in the cell type consideration for the FMRP reactivation strategy.