bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patterns of Multimorbidity
Authors: Siah Kien Wei , Wong Chi Heem , Gupta Jerry , Lo Andrew W. 
Published: May 2021

AbstractBackgroundWith multimorbidity becoming the norm rather than the exception, the management of multiple chronic diseases is a major challenge facing healthcare systems worldwide.MethodsUsing a large, nationally representative database of electronic medical records from the United Kingdom spanning the years 2005 to 2016 and consisting over 4.5 million patients, we apply statistical methods and network analysis to identify comorbid pairs and triads of diseases and identify clusters of chronic conditions across different demographic groups. Unlike many previous studies, which generally adopt cross-sectional designs, we examine temporal changes in the patterns of multimorbidity. In addition, we perform survival analysis to examine the impact of multimorbidity on mortality.ResultsThe proportion of the population with multimorbidity has increased by approximately 2.5 percentage points over the last decade, with more than 17% having at least two chronic morbidities. We find that the prevalence and the severity of multimorbidity increase progressively with age. Stratifying by socioeconomic status, we find that people living in more deprived areas are more likely to be multimorbid compared to those living in more affluent areas at all ages. The same trend holds consistently for all years in our data. In addition to a number of strongly associated comorbid pairs (e.g., cardiac-vascular and cardiac-metabolic disorders), we identify three principal clusters: a respiratory cluster, a cardiovascular cluster, and a mixed cardiovascular-renal-metabolic cluster. These are supported by established pathophysiological mechanisms and shared risk factors, and are largely consistent with existing studies in the medical literature.ConclusionsIn this paper, we use data-driven methods to characterize multimorbidity patterns in different demographic groups and their evolution over the past decade. Our findings contribute to the better understanding of the epidemiology of multimorbidity that is needed to develop more effective primary care for multimorbid patients.
STING mediates immune responses in the closest living relatives of animals
Authors: Woznica Arielle , Kumar Ashwani , Sturge Carolyn R. , Xing Chao , King Nicole , Pfeiffer Julie K. 
Published: May 2021

AbstractAnimals have evolved unique repertoires of innate immune genes and pathways that provide their first line of defense against pathogens. To reconstruct the ancestry of animal innate immunity, we have developed the choanoflagellate Monosiga brevicollis, one of the closest living relatives of animals, as a model for studying mechanisms underlying pathogen recognition and immune response. We found that M. brevicollis is killed by exposure to Pseudomonas aeruginosa bacteria. Moreover, M. brevicollis expresses STING, which, in animals, activates innate immune pathways in response to cyclic dinucleotides during pathogen sensing. M. brevicollis STING increases the susceptibility of M. brevicollis to P. aeruginosa-induced cell death and is required for responding to the cyclic dinucleotide 2’3’ cGAMP. Furthermore, similar to animals, autophagic signaling in M. brevicollis is induced by 2’3’ cGAMP in a STING-dependent manner. This study provides evidence for a pre-animal role for STING in antibacterial immunity and establishes M. brevicollis as a model system for the study of immune responses.
Regulators of the secretory pathway have distinct inputs into single-celled branching morphogenesis and seamless tube formation in the Drosophila trachea
Authors: Bourne Christopher M. , Lai Daniel C. , Schottenfeld-Roames Jodi 
Published: May 2021

AbstractBiological tubes serve as conduits through which gas, nutrients and other important fluids are delivered to tissues. Most biological tubes consist of multiple cells connected by epithelial junctions. Unlike these multicellular tubes, seamless tubes are unicellular and lack junctions. Seamless tubes are present in various organ systems, including the vertebrate vasculature,C.elegansexcretory system, andDrosophilatracheal system. TheDrosophilatracheal system is a network of air-filled tubes that delivers oxygen to all tissues. Specialized cells within the tracheal system, called terminal cells, branch extensively and form seamless tubes. Terminal tracheal tubes are polarized; the lumenal membrane has apical identity whereas the outer membrane exhibits basal characteristics. Although various aspects of membrane trafficking have been implicated in terminal cell morphogenesis, the precise secretory pathway requirements for basal and apical membrane growth have yet to be elucidated. In the present study, we demonstrate that anterograde trafficking, retrograde trafficking and Golgi-to-plasma membrane vesicle fusion are each required for the complex branched architecture of the terminal cell, but their inputs during seamless lumen formation are more varied. The COPII subunit, Sec 31, and ER exit site protein, Sec16, are critical for subcellular tube architecture, whereas the SNARE proteins Syntaxin 5, Syntaxin 1 and Syntaxin15 are required for seamless tube growth and maintenance. These data suggest that distinct components of the secretory pathway have differential contributions to basal and apical membrane growth and maintenance during terminal cell morphogenesis.
Predicting individual shelter dog behaviour after adoption using longitudinal behavioural assessment: a hierarchical Bayesian approach
Authors: Goold Conor , Newberry Ruth C. 
Published: May 2021

AbstractPredicting the behaviour of shelter dogs after adoption is an important, but difficult, endeavour. Differences between shelter and post-adoption environments, between- and within-individual heterogeneity in behaviour, uncertainty in behavioural predictions and measurement error all hinder the accurate assessment of future behaviour. This study integrates 1) a longitudinal behavioural assessment with 2) a novel joint hierarchical Bayesian mixture model that accounts for individual variation, missing data and measurement error to predict behaviour post-adoption. We analysed shelter observations (> 28,000 records) and post-adoption reports (from telephone surveys) on the behaviour of 241 dogs across eight contexts. Dog behaviour at the shelter correlated positively with behaviour post-adoption within contexts (r= 0.38; 95% highest density interval: [0.20, 0.55]), and behavioural repeatability was approximately 20% higher post-adoption than at the shelter for behaviour within contexts. Although measurement error was higher post-adoption than at the shelter, we found few differences in individual-level, latent probabilities of different behaviours post-adoption versus at the shelter. This good predictive ability was aided by accurate representation of uncertainty in individual-level predictions. We conclude that longitudinal assessment paired with a sufficient inferential framework to model latent behavioural profiles with uncertainty enables reasonably accurate estimation of post-adoption behaviour.
Priority-based transformations of stimulus representation in visual working memory
Authors: Wan Quan , Menendez Jorge A. , Postle Bradley R. 
Published: May 2021

AbstractHow does the brain prioritize among the contents of working memory (WM) to appropriately guide behavior? Using inverted encoding modeling (IEM), previous work (Wan et al., 2020) showed that unprioritized memory items (UMI) are actively represented in the brain but in a “flipped”, or opposite, format compared to prioritized memory items (PMI). To gain insight into the mechanisms underlying the UMI-to-PMI representational transformation, we trained recurrent neural networks (RNNs) with an LSTM (long short-term memory) architecture to perform a 2-back working memory task. Although visualization of LSTM hidden layer activity using Principal Component Analysis (PCA) suggested that stimulus representations undergo a smooth rotational transformation across the trial, demixed (d)PCA of the same data decomposed this pattern into a cascade of multiple trajectories, each with a different time course, unfolding within UMI and PMI subspaces. The application of the same analyses to the EEG dataset of Wan et al. (2020) indicated that an item’s trajectory through the UMI subspace closely mirrored that of the RNN, but that its trajectory through the PMI subspace differed markedly from the RNN. It may be a general principle that, at the level of the representational code, information held in WM undergoes priority-based transformations that allow for its retention while preventing it from interfering with concurrent behavior. Implementational details of this process may vary across model systems.Author SummaryHow is information held in working memory (WM) but outside the current focus of attention? Motivated by previous neuroimaging studies, we trained recurrent neural networks (RNNs) to perform a 2-back WM task that entails shifts of an item’s priority status. Dimensionality reduction of the resultant activity in the hidden layer of the RNN allowed us to characterize how a stimulus item’s representation follows a transformational trajectory through high-dimensional representational space as its priority status changes from memory probe to unprioritized to prioritized. This work illustrates the value of artificial neural networks for assessing and refining hypotheses about mechanisms for information processing in the brain.
Origami: Single-cell oriented 3D shape dynamics of folding epithelia from fluorescence microscopy images
Authors: Mendonca Tania , Jones Ana A. , Pozo Jose M. , Baxendale Sarah , Whitfield Tanya T. , Frangi Alejandro F. 
Published: May 2021

AbstractA common feature of morphogenesis is the formation of three-dimensional structures from the folding of two-dimensional epithelial sheets aided by spatio-temporal cell shape changes at the cellular-level. Studying cell shape dynamics and polarised processes that underpin them, requires orienting cells within the epithelial sheet. In epithelia with highly curved surfaces, assigning cell orientation can be difficult to automate in silico. We present ‘Origami’, a MATLAB-based image analysis pipeline to compute oriented cell shape-features. Our automated method accurately computed cell orientation in regions with opposing curvature in synthetic epithelia and fluorescence images of zebrafish embryos. As proof of concept, we identified different cell shape signatures in the developing zebrafish inner ear, where the epithelium deforms in opposite orientations to form different structures. Origami is designed to be user-friendly and is generally applicable to fluorescence images of curved epithelia.
Microtubule inhibitors identified through non-biased screening enhance DNA transfection efficiency by delaying p62-dependent ubiquitin recruitment
Authors: Tsuchiya Megumi , Ogawa Hidesato , Watanabe Kento , Koujin Takako , Mori Chie , Nunomura Kazuto , Lin Bangzhong , Tani Akiyoshi , Hiraoka Yasushi , Haraguchi Tokuko 
Published: May 2021

AbstractEctopic gene expression is an indispensable tool in biology and medicine, but is often limited by the low efficiency of DNA transfection. We previously reported that depletion of the autophagy receptor p62/SQSTM1 enhances DNA transfection efficiency by preventing the degradation of transfected DNA. Therefore, p62 is a potential target for drugs to increase transfection efficiency. To identify such drugs, a non-biased high-throughput screening was applied to over 4,000 compounds from the Osaka University compound library, and their p62-dependency was evaluated. The top-scoring drugs were mostly microtubule inhibitors, such as colchicine and vinblastine, and all of them showed positive effects only in the presence of p62. To understand the p62-dependent mechanisms, the time required for p62-dependent ubiquitination, which is required for autophagosome formation, was examined using polystyrene beads that were introduced into cells as materials that mimicked transfected DNA. Microtubule inhibitors caused a delay in ubiquitination. Furthermore, the level of phosphorylated p62 at S405 was markedly decreased in the drug-treated cells. These results suggest that microtubule inhibitors inhibit p62-dependent autophagosome formation. Our findings demonstrate for the first time that microtubule inhibitors suppress p62 activation as a mechanism for increasing DNA transfection efficiency and provide solutions to increase efficiency.
DeLUCS: Deep Learning for Unsupervised Clustering of DNA Sequences
Authors: Arias Pablo Millán , Alipour Fatemeh , Hill Kathleen A. , Kari Lila 
Published: May 2021

AbstractWe present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of primary DNA sequences, and generates “mimic” sequence FCGRs to self-learn data patterns (genomic signatures) through the optimization of multiple neural networks. A majority voting scheme is then used to determine the final cluster assignment for each sequence. The clusters learned by DeLUCS match true taxonomic groups for large and diverse datasets, with accuracies ranging from 77% to 100%: 2,500 complete vertebrate mitochondrial genomes, at taxonomic levels from sub-phylum to genera; 3,200 randomly selected 400 kbp-long bacterial genome segments, into clusters corresponding to bacterial families; three viral genome and gene datasets, averaging 1,300 sequences each, into clusters corresponding to virus subtypes. DeLUCS significantly outperforms two classic clustering methods (K-means++ and Gaussian Mixture Models) for unlabelled data, by as much as 47%. DeLUCS is highly effective, it is able to cluster datasets of unlabelled primary DNA sequences totalling over 1 billion bp of data, and it bypasses common limitations to classification resulting from the lack of sequence homology, variation in sequence length, and the absence or instability of sequence annotations and taxonomic identifiers. Thus, DeLUCS offers fast and accurate DNA sequence clustering for previously intractable datasets.
RNA-seq and differential expression analysis of the duck transcriptome: The effect of short-term cage-rearing
Authors: Chen Biao , Fang Wenjie , Li Yankai , Xiong Ting , Zhou Mingfang , Wan Lei , Liu Qiuhong , Zhang Wenyan , Hu Xiaolong , Mao Huirong , Liu Sanfeng 
Published: May 2021

AbstractDucks are an important source of meat and egg products for human beings. In China, duck breeding has gradually changed from the traditional floor-water combination system to multilayer cage breeding. Therefore, the present study collected the hypothalamus and pituitary of 113-day-old ducks after being caged for 3 days, in order to investigate the effect of cage-rearing on the birds. In addition, the same tissues (hypothalamus and pituitary) were collected from ducks raised in the floor-water combination system, for comparison. Thereafter, the transcriptomes were sequenced and the expression level of genes were compared. The results of sequencing analysis showed that a total of 506 and 342 genes were differentially expressed in the hypothalamus and pituitary, respectively. Additionally, the differentially expressed genes were mainly enriched in signaling pathways involved in processing environmental information, including ECM-receptor interaction, neuroactive ligand-receptor interaction and focal adhesion. The findings also showed that there was a change in the alternative splicing of genes when ducks were transferred into the cage rearing system. However, there was no difference in the expression of some genes although there was a change in the expression of the isoforms of these genes. The findings herein can therefore help in understanding the mechanisms underlying the effect of caging on waterfowl. The results also highlight the gene regulatory networks involved in animal responses to acute stress.
Mice exhibit stochastic and efficient action switching during probabilistic decision making
Authors: Beron Celia C. , Neufeld Shay Q. , Linderman Scott W. , Sabatini Bernardo L. 
Published: May 2021

AbstractIn probabilistic and nonstationary environments, individuals must use internal and external cues to flexibly make decisions that lead to desirable outcomes. To gain insight into the process by which animals choose between actions, we trained mice in a task with time-varying reward probabilities. In our implementation of such a “two-armed bandit” task, thirsty mice use information about recent action and action-outcome histories to choose between two ports that deliver water probabilistically. Here, we comprehensively modeled choice behavior in this task, including the trial-to-trial changes in port selection – i.e. action switching behavior. We find that mouse behavior is, at times, deterministic and, at others, apparently stochastic. The behavior deviates from that of a theoretically optimal agent performing Bayesian inference in a Hidden Markov Model (HMM). We formulate a set of models based on logistic regression, reinforcement learning, and ‘sticky’ Bayesian inference that we demonstrate are mathematically equivalent and that accurately describe mouse behavior. The switching behavior of mice in the task is captured in each model by a stochastic action policy, a history-dependent representation of action value, and a tendency to repeat actions despite incoming evidence. The models parsimoniously capture behavior across different environmental conditionals by varying the ‘stickiness’ parameter, and, like the mice, they achieve nearly maximal reward rates. These results indicate that mouse behavior reaches near-maximal performance with reduced action switching and can be described by a set of equivalent models with a small number of relatively fixed parameters.SignificanceTo obtain rewards in changing and uncertain environments, animals must adapt their behavior. We found that mouse choice and trial-to-trial switching behavior in a dynamic and probabilistic two-choice task could be modeled by equivalent theoretical, algorithmic, and descriptive models. These models capture components of evidence accumulation, choice history bias, and stochasticity in mouse behavior. Furthermore, they reveal that mice adapt their behavior in different environmental contexts by modulating their level of ‘stickiness’ to their previous choice. Despite deviating from the behavior of a theoretically ideal observer, the empirical models achieve comparable levels of near-maximal reward. These results make predictions to guide interrogation of the neural mechanisms underlying flexible decision-making strategies.
Aging metrics incorporating cognitive and physical function capture mortality risk: results from three prospective cohort studies
Authors: Cao Xingqi , Chen Chen , Zhang Jingyun , Xue Qian-Li , Hoogendijk Emiel O. , Liu Xiaoting , Li Shujuan , Wang Xiaofeng , Zhu Yiming , Liu Zuyun 
Published: May 2021

AbstractBackgroundThe aims of this study were to: 1) describe the proportions of vulnerable persons identified by three existing aging metrics that incorporate cognitive and physical function; 2) examine the associations of the three metrics with mortality; and 3) develop and validate a new simple functional score for mortality prediction.MethodsThe three aging metrics were the combined presence of cognitive impairment and physical frailty (CI-PF), the frailty index (FI), and the motoric cognitive risk syndrome (MCR). We operationalized them with data from two large cohort studies: the China Health and Retirement Longitudinal Study (CHARLS) and the US National Health and Nutrition Examination Survey (NHANES). Logistic regression models or Cox proportional hazard regression models, and receiver operating characteristic curves were used to examine the associations of the three metrics with mortality. A new functional score was developed and validated in the Rugao Ageing Study (RAS), an independent dataset.ResultsIn CHARLS, the proportions of vulnerable persons identified by CI-PF, FI, and MCR were 2.2%, 16.6%, and 19.6%, respectively. Each metric predicted mortality after adjustment for age and sex, with some variations in the strength of the associations (CI-PF, odds ratio (OR)=2.87, 95% confidence interval (CI)=1.74, 4.74; FI, OR=1.94, 95% CI=1.50, 2.50; MCR, OR=1.27, 95% CI=1.00, 1.62). CI-PF and FI had additional predictive utility beyond age and sex, as demonstrated by integrated discrimination improvement, and continuous net reclassification improvement (all P <0.001). These results were replicated in NHANES. Furthermore, we developed a new functional score by selecting six self-reported items from CI-PF and FI in CHARLS, and demonstrated that it predicted mortality risk. This functional score was further validated in RAS. To facilitate the quick screening of persons with deteriorations in cognitive and physical function, we introduced a publicly available online tool designed for this new functional score.ConclusionsDespite the inherent differences in the aging metrics incorporating cognitive and physical function, they consistently capture mortality risk. The findings support the incorporation of cognitive and physical function for risk stratification in both Chinese and US persons, but call for caution when applying them in specific study settings.
Elevated Neuropeptide Y1 Receptor Signaling Contributes to β-cell Dysfunction and Failure in Type 2 Diabetes
Authors: Yang Chieh-Hsin , Ann-Onda Danise , Lin Xuzhu , Fynch Stacey , Nadarajah Shaktypreya , Pappas Evan , Liu Xin , Scott John W. , Oakhill Jonathan S. , Galic Sandra , Shi Yanchuan , Moreno-Asso Alba , Smith Cassandra , Loudovaris Tom , Levinger Itamar , Eizirik Decio L. , Laybutt Ross D. , Herzog Herbert , Thomas Helen E. , Loh Kim 
Published: May 2021

ABSTRACTLoss of functional β-cell mass is a key factor contributing to the poor glycaemic control in type 2 diabetes. However, therapies that directly target these underlying processes remains lacking. Here we demonstrate that gene expression of neuropeptide Y1 receptor and its ligand, neuropeptide Y, was significantly upregulated in human islets from subjects with type 2 diabetes. Importantly, the reduced insulin secretion in type 2 diabetes was associated with increased neuropeptide Y and Y1 receptor expression in human islets. Consistently, pharmacological inhibition of Y1 receptors by BIBO3304 significantly protected β-cells from dysfunction and death under multiple diabetogenic conditions in islets. In a preclinical study, Y1 receptor antagonist BIBO3304 treatment improved β-cell function and preserved functional β-cell mass, thereby resulting in better glycaemic control in both high-fat-diet/multiple low-dose streptozotocin- and db/db type 2 diabetic mice. Collectively, our results uncovered a novel causal link of increased islet NPY-Y1 receptor signaling to β-cell dysfunction and failure in human type 2 diabetes. These results further demonstrate that inhibition of Y1 receptor by BIBO3304 represents a novel and effective β-cell protective therapy for improving functional β-cell mass and glycaemic control in type 2 diabetes.