bluuebunny/crossref_metadata_2025 huggingface dataset:
An Explainable Deep Learning Approach for Multimodal Electrophysiology Classification
Authors: Ellis Charles A. , Carbajal Darwin A. , Zhang Rongen , Miller Robyn L. , Calhoun Vince D. , Wang May D.
Published: May 2021

In recent years, more biomedical studies have begun to use multimodal data to improve model performance. As such, there is a need for improved multimodal explainability methods. Many studies involving multimodal explainability have used ablation approaches. Ablation requires the modification of input data, which may create out-of-distribution samples and may not always offer a correct explanation. We propose using an alternative gradient-based feature attribution approach, called layer-wise relevance propagation (LRP), to help explain multimodal models. To demonstrate the feasibility of the approach, we selected automated sleep stage classification as our use-case and trained a 1-D convolutional neural network (CNN) with electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) data. We applied LRP to explain the relative importance of each modality to the classification of different sleep stages. Our results showed that across all samples, EEG was most important, followed by EOG, and EMG. For individual sleep stages, EEG and EOG had higher relevance for classifying awake and non-rapid eye movement 1 (NREM1). EOG was most important for classifying REM, and EEG was most relevant for classifying NREM2-NREM3. Also, LRP gave consistent levels of importance to each modality for correctly classified samples across folds and inconsistent levels of importance for incorrectly classified samples. Our results demonstrate the additional insight that gradient-based approaches can provide relative to ablation methods and highlight their feasibility for explaining multimodal electrophysiology classifiers.
WASP integrates substrate topology and cell polarity to guide neutrophil migration
Authors: Brunetti Rachel M. , Kockelkoren Gabriele , Raghavan Preethi , Bell George R. R. , Britain Derek , Puri Natasha , Collins Sean R. , Leonetti Manuel D. , Stamou Dimitrios , Weiner Orion D.
Published: May 2021

To control their shape and movement, cells leverage nucleation promoting factors (NPFs) to regulate when and where they polymerize actin. Here we investigate the role of the immune-specific NPF WASP during neutrophil migration. Endogenously-tagged WASP localizes to substrate-induced plasma membrane deformations. Super-resolution imaging of live cells reveals that WASP preferentially enriches to the necks of these substrate-induced membrane invaginations, a distribution that could support substrate pinching. Unlike other curvature-sensitive proteins, WASP only enriches to membrane deformations at the cell front, where it controls Arp2/3 complex recruitment and actin polymerization. Despite relatively normal migration on flat substrates, WASP depletion causes defects in topology sensing and directed migration on textured substrates. WASP therefore both responds to and reinforces cell polarity during migration. Surprisingly, front-biased WASP puncta continue to form in the absence of Cdc42. We propose that WASP integrates substrate topology with cell polarity for 3D guidance by selectively polymerizing actin around substrate-induced membrane deformations at the leading edge. A misregulation of WASP-mediated contact guidance could provide insight into the immune disorder Wiskott-Aldrich syndrome.
Quantitative proteomics identifies the universally conserved ATPase Ola1p as a positive regulator of heat shock response in Saccharomyces cerevisiae
Authors: Dannenmaier Stefan , Altamirano Christine Desroches , Schüler Lisa , Zhang Ying , Hummel Johannes , Oeljeklaus Silke , Koch Hans-Georg , Rospert Sabine , Alberti Simon , Warscheid Bettina
Published: May 2021

The universally conserved P-loop ATPase Ola1 is implicated in various cellular stress response pathways, as well as in cancer and tumor progression. However, Ola1p functions are divergent between species and the involved mechanisms are only poorly understood. Here, we studied the role of Ola1p in the heat shock response of the yeast Saccharomyces cerevisiae using a combination of quantitative and pulse labeling-based proteomics approaches, in vitro studies and cell-based assays. Our data show that when heat stress is applied to cells lacking Ola1p, the expression of stress-protective proteins is enhanced. During heat stress Ola1p associates with detergent-resistant protein aggregates and rapidly forms assemblies that localize to stress granules. The assembly of Ola1p was also observed in vitro using purified protein and conditions, which resembled those in living cells. We show that loss of Ola1p results in increased protein ubiquitination of detergent-insoluble aggregates recovered from heat-shocked cells. When subsequently cells lacking Ola1p were relieved from heat stress, reinitiation of translation was delayed, whereas, at the same time, de novo synthesis of central factors required for protein refolding and the clearance of aggregates was enhanced when compared to wildtype cells. The combined data suggest that upon acute heat stress, Ola1p is involved in the stabilization of misfolded proteins, which become sequestered in cytoplasmic stress granules. This function of Ola1p enables cells to resume translation in a timely manner as soon as heat stress is relieved.
CsoDIAq Software for Direct Infusion Shotgun Proteome Analysis (DISPA)
Authors: Cranney Caleb W. , Meyer Jesse G.
Published: May 2021

New mass spectrometry data collection methods require new computational tools. Direct Infusion Shotgun Proteome Analysis (DISPA) is a new paradigm for expedited mass spectrometry-based proteomics, but the original data analysis workflow was onerous. Here we introduce CsoDIAq, a user-friendly software package for the identification and quantification of peptides and proteins from DISPA data. In addition to establishing a complete and automated analysis workflow with a graphical user interface, CsoDIAq introduces algorithmic concepts to improve peptide identification speed and sensitivity. These include spectra pooling to reduce search time complexity, and a new spectrum-spectrum match score called match count and cosine (MaCC), which improves target discrimination in a target-decoy analysis. We further show that reanalysis after fragment mass tolerance correction increased the number of peptide identifications. Finally, we adapt CsoDIAq to standard LC-MS DIA, and show that it outperforms other spectrum-spectrum matching software.
Universal amyloidogenicity of patient-derived immunoglobulin light chains
Authors: Sternke-Hoffmann Rebecca , Pauly Thomas , Norrild Rasmus K. , Hansen Jan , Dupré Mathieu , Tucholski Florian , Duchateau Magalie , Rey Martial , Metzger Sabine , Boquoi Amelie , Platten Florian , Egelhaaf Stefan U. , Chamot-Rooke Julia , Fenk Roland , Nagel-Steger Luitgard , Haas Rainer , Buell Alexander K.
Published: May 2021

The deposition of immunoglobulin light chains (IgLCs) in the form of amorphous aggregates or amyloid fibrils in different tissues of patients can lead to severe and potentially fatal organ damage, requiring transplantation in some cases. There has been great interest in recent years to elucidate the origin of the very differentin vivosolubilities of IgLCs, as well as the molecular determinants that drive either the formation of ordered amyloid fibrils or disordered amorphous aggregates. It is commonly thought that the reason of this differential aggregation behaviour is to be found in the amino acid sequences of the respective IgLCs, i.e. that some sequences display higher intrinsic tendencies to form amyloid fibrils. Here we perform in depth Thermodynamic and Aggregation Fingerprinting (ThAgg-Fip) of 9 multiple myeloma patient-derived IgLCs, the amino acid sequences of all of which we have solved byde novoprotein sequencing with mass spectrometry. The latter technique was also used for one IgLc from a patient with AL amyloidosis. We find that all samples also contain proteases that fragment the proteins under physiologically relevant mildly acidic pH conditions, leading to amyloid fibril formation in all cases. Our results suggest that while every pathogenic IgLC has a unique ThAgg fingerprint, all sequences have comparable amyloidogenic potential. Therefore, extrinsic factors, in particular presence of, and susceptibility to, proteolytic cleavage is likely to be a strong determinant ofin vivoaggregation behaviour. The important conclusion, which is corroborated by systematic analysis of our sequences, as well as many sequences of IgLCs from amyloidosis patients reported in the literature, challenges the current paradigm of the link between sequence and amyloid fibril formation of pathogenic light chains.
A catalog of transcription start sites across 115 human tissue and cell types
Authors: Moore Jill E. , Zhang Xiao-Ou , Elhajjajy Shaimae I. , Fan Kaili , Reese Fairlie , Mortazavi Ali , Weng Zhiping
Published: May 2021

Accurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated nor do they contain information on cell type-specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks were primarily proximal to GENCODE-annotated TSSs and were concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3’ ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations were supported by epigenomic and other transcriptomic datasets. To demonstrate the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI GWAS catalog and identified new candidate GWAS genes. Overall, our work demonstrates the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.
Inferring kinetic parameters of oscillatory gene regulation from single cell time series data
Authors: Burton Joshua , Manning Cerys S. , Rattray Magnus , Papalopulu Nancy , Kursawe Jochen
Published: May 2021

Gene expression dynamics, such as stochastic oscillations and aperiodic fluctuations, have been associated with cell fate changes in multiple contexts, including development and cancer. Single cell live imaging of protein expression with endogenous reporters is widely used to observe such gene expression dynamics. However, the experimental investigation of regulatory mechanisms underlying the observed dynamics is challenging, since these mechanisms include complex interactions of multiple processes, including transcription, translation, and protein degradation. Here, we present a Bayesian method to infer kinetic parameters of oscillatory gene expression regulation using an auto-negative feedback motif with delay. Specifically, we use a delay-adapted nonlinear Kalman filter within a Metropolis-adjusted Langevin algorithm to identify posterior probability distributions. Our method can be applied to time series data on gene expression from single cells and is able to infer multiple parameters simultaneously. We apply it to published data on murine neural progenitor cells and show that it outperforms alternative methods. We further analyse how parameter uncertainty depends on the duration and time resolution of an imaging experiment, to make experimental design recommendations. This work demonstrates the utility of parameter inference on time course data from single cells and enables new studies on cell fate changes and population heterogeneity.
HASTER is a transcriptional stabilizer of HNF1A
Authors: Beucher Anthony , Miguel-Escalada Irene , Balboa Diego , De Vas Matías G. , Maestro Miguel Angel , Garcia-Hurtado Javier , Bernal Aina , Gonzalez-Franco Roser , Vargiu Pierfrancesco , Heyn Holger , Ravassard Philippe , Ortega Sagrario , Ferrer Jorge
Published: May 2021

The biological purpose and disease relevance of long noncoding RNAs (lncRNAs) is poorly understood. We examined HASTER, a lncRNA antisense to HNF1A. Haploinsufficient mutations in HNF1A, encoding a homeodomain transcription factor, cause diabetes mellitus. Using mouse and human models, we show that HASTER maintains HNF1A at cell-specific physiological concentrations through positive and negative feedback loops. Haster mutant pancreatic β cells thus showed variegated HNF1A overexpression or silencing, causing insulin-deficiency and diabetes. We demonstrate that the HASTER promoter acts in cis to prevent HNF1A overexpression and silencing, and link HASTER-dependent inhibition to local remodelling of 3D chromatin architecture. We further show that HASTER negative feedback ensures that HNF1A creates open chromatin at appropriate cell-specific genome regions. Our studies expose a cis-regulatory element that is unlike enhancers or silencers, and instead stabilizes expression levels of a pioneer transcription factor. They also show that disruption of a mammalian lncRNA can cause diabetes mellitus.
Single-Cell Stochastic Modeling of the Action of Antimicrobial Peptides on Bacteria
Authors: Teimouri Hamid , Nguyen Thao N. , Kolomeisky Anatoly B.
Published: May 2021

Antimicrobial peptides (AMPs) produced by multi-cellular organisms as their immune system’s defense against microbes are actively considered as natural alternatives to conventional antibiotics. Although a substantial progress has been achieved in studying the AMPs, the microscopic mechanisms of their functioning remain not well understood. Here, we develop a new theoretical framework to investigate how the AMPs are able to efficiently neutralize the bacteria. In our minimal theoretical model, the most relevant processes, AMPs entering into and the following inhibition of the single bacterial cell, are described stochastically. Using complementary master equations approaches, all relevant features of bacteria clearance dynamics by AMPs, such as the probability of inhibition and the mean times before the clearance, are explicitly evaluated. It is found that both processes, entering and inhibition, are equally important for the efficient functioning of AMPs. Our theoretical method naturally explains a wide spectrum of efficiencies of existing AMPs and their heterogeneity at the single-cell level. Theoretical calculations are also consistent with existing single-cell measurements. Thus, the presented theoretical approach clarifies some microscopic aspects of the action of AMPs on bacteria.
Direct Reconstruction of Gene Regulatory Networks underlying Cellular state Transitions without Pseudo-time Inference
Authors: Wan Ruosi , Zhang Yuhao , Peng Yongli , Tian Feng , Gao Ge , Tang Fuchou , Xie Xiaoliang S. , Jia Jinzhu , Ge Hao
Published: May 2021

Nowadays the advanced technology for single-cell transcriptional profiling enables people to routinely generate thousands of single-cell expression data, in which data from different cell states or time points are derived from different samples. Without transferring such time-stamped cross-sectional data into pseudo-time series, we propose COSLIR (COvariance restricted Sparse LInear Regression) for directly reconstructing the gene regulatory networks (GRN) that drives the cell-state transition. The differential gene expression between adjacent cell states is modeled as a linear combination of gene expressions in the previous cell state, and the GRN is reconstructed through solving an optimization problem only based on the first and second moments of the sample distributions. We apply the bootstrap strategy as well as the clip threshold method to increase the precision and stability of the estimation. Simulations indicate the perfect accuracy of COSLIR in the oracle case as well as its good performance and stability in the sample case. We apply COSLIR separately to two cell lineages in a published single-cell qPCR dataset during mouse early embryo development. Nearly half of the inferred gene-gene interactions have already been experimentally reported and some of them were even discovered during the past decade after the dataset was published, indicating the power of COSLIR. Furthermore, COSLIR is also evaluated on several single-cell RNA-seq datasets, and the performance is comparable with other methods relying on the pseudo-time reconstruction.
SMCHD1 has separable roles in chromatin architecture and gene silencing that could be targeted in disease
Authors: Tapia del Fierro Andres , den Hamer Bianca , Jansz Natasha , Chen Kelan , Beck Tamara , Vanyai Hannah , Benetti Natalia , Gurzau Alexandra D , Daxinger Lucia , Xue Shifeng , Ly Thanh Thao Nguyen , Wanigasuriya Iromi , Breslin Kelsey , Oey Harald , Krom Yvonne , van der Hoorn Dinja , Bouwman Linde F , Ritchie Matthew E. , Reversade Bruno , Prin Fabrice , Mohun Timothy , van der Maarel Silvère M , McGlinn Edwina , Murphy James M , Keniry Andrew , de Greef Jessica C , Blewitt Marnie E
Published: May 2021

The interplay between 3D chromatin architecture and gene silencing is incompletely understood. Here, we report a novel point mutation in the non-canonical SMC protein SMCHD1 that enhances its silencing capacity at endogenous developmental targets and at the facioscapulohumeral muscular dystrophy associated macro-array, D4Z4. Heightened SMCHD1 silencing perturbs developmental Hox gene activation, causing a homeotic transformation in mice. Paradoxically, the mutant SMCHD1 appears to enhance insulation against another epigenetic regulator complex, PRC2, while depleting long range chromatin interactions akin to what is observed in the absence of SMCHD1. These data suggest that SMCHD1’s role in long range chromatin interactions is not directly linked to gene silencing or insulating the chromatin, refining the model for how the different levels of SMCHD1-mediated chromatin regulation interact to bring about gene silencing in normal development and disease.
Efficacy of the NVX-CoV2373 Covid-19 Vaccine Against the B.1.1.7 Variant
Authors: Heath Paul T. , Galiza Eva P. , Baxter David Neil , Boffito Marta , Browne Duncan , Burns Fiona , Chadwick David R. , Clark Rebecca , Cosgrove Catherine , Galloway James , Goodman Anna L. , Heer Amardeep , Higham Andrew , Iyengar Shalini , Jamal Arham , Jeanes Christopher , Kalra Philip A. , Kyriakidou Christina , McAuley Daniel F. , Meyrick Agnieszka , Minassian Angela M. , Minton Jane , Moore Patrick , Munsoor Imrozia , Nicholls Helen , Osanlou Orod , Packham Jonathan , Pretswell Carol H. , Francisco Ramos Alberto San , Saralaya Dinesh , Sheridan Ray P. , Smith Richard , Soiza Roy L. , Swift Pauline A. , Thomson Emma C. , Turner Jeremy , Viljoen Marianne Elizabeth , Albert Gary , Cho Iksung , Dubovsky Filip , Glenn Greg , Rivers Joy , Robertson Andreana , Smith Kathy , Toback Seth
Published: May 2021

Background

Covid-19 vaccines are urgently needed, especially against emerging variants. NVX-CoV2373 is a recombinant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 rS) nanoparticle vaccine containing trimeric full-length SARS-CoV-2 spike glycoprotein and Matrix-M adjuvant.

Methods

A phase 3, randomized, observer-blinded, placebo-controlled trial was conducted in adults 18-84 years old who received two intramuscular 5-µg doses, 21 days apart, of NVX-CoV2373 or placebo (1:1) across 33 sites in the United Kingdom. The primary efficacy endpoint was virologically confirmed symptomatic Covid-19 with onset 7 days after second vaccination in serologically negative participants.

Results

A total of 15,187 participants were randomized, of whom 7569 received NVX-CoV2373 and 7570 received placebo; 27.2% were 65 years or older, 44.7% had comorbidities and 4.2% had baseline serological evidence of SARS-CoV-2. There were 10 cases of Covid-19 among NVX-CoV2373 recipients and 96 cases among placebo recipients, with symptom onset at least 7 days after second vaccination; NVX-CoV2373 was 89.7% (95% confidence interval, 80.2 to 94.6) effective in preventing Covid-19, with no hospitalizations or deaths reported. There were five cases of severe Covid-19, all in the placebo group. Post hoc analysis revealed efficacies of 96.4% (73.8 to 99.5) and 86.3% (71.3 to 93.5) against the prototype strain and B.1.1.7 variant, respectively. Vaccine efficacy was similar across subgroups, including participants with comorbidities and those ≥65 years old. Reactogenicity was generally mild and transient. The incidence of serious adverse events was low and similar in the two groups.

Conclusion

A two-dose regimen of NVX-CoV2373 conferred 89.7% protection against a blend of prototype and variant Covid-19, demonstrated high efficacy against the B.1.1.7 variant, and had a reassuring safety profile.

(Funded by Novavax, Inc. EudraCT number, 2020-004123-16).
Impact of the COVID-19 pandemic on the mental health and wellbeing of parents with young children: a qualitative interview study
Authors: Dawes Jo , May Tom , McKinlay Alison , Fancourt Daisy , Burton Alexandra
Published: May 2021

Background

Parents have faced unique challenges during the coronavirus disease 2019 (COVID-19) pandemic, including mobility constraints, isolation measures, working from home, and the closure of schools and childcare facilities. There is presently a lack of in-depth qualitative research exploring how these changes have affected parents’ mental health and wellbeing.

Methods

Semi-structured qualitative interviews with 29 parents of young children. Interviews were analysed using reflexive thematic analysis.

Results

We identified five superordinate themes affecting participant mental health and wellbeing: 1) navigation of multiple responsibilities and change inside the home; 2) disruption to home life; 3) changes to usual support networks; 4) changes in personal relationships; and 5) use of coping strategies. Participants described stress and exhaustion from navigating multiple pressures and conflicting responsibilities with home, schooling, and work, without their usual support networks and in the context of disrupted routines. Family roles and relationships were sometimes tested, however, many parents identified coping strategies that protected their wellbeing including access to outdoor space, spending time away from family, and avoiding conflict and pandemic-related media coverage.

Conclusions

Employers must be cognisant of the challenges that the pandemic has placed on parents, particularly women and lone parents. Flexible working arrangements and support might therefore relieve stress and increase productivity. Coping strategies identified by parents in this study could be harnessed and encouraged by employers and policymakers to promote positive wellbeing during times of stress throughout the pandemic and beyond.
Patterns of Multimorbidity
Authors: Siah Kien Wei , Wong Chi Heem , Gupta Jerry , Lo Andrew W.
Published: May 2021

Background

With multimorbidity becoming the norm rather than the exception, the management of multiple chronic diseases is a major challenge facing healthcare systems worldwide.

Methods

Using 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.

Results

The 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.

Conclusions

In 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

Animals 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

Biological 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

Predicting 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

How 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 Summary

How 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

A 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

Ectopic 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

We 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

Ducks 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

In 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.

Significance

To 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

Background

The 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.

Methods

The 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.

Results

In 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.

Conclusions

Despite 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

Loss 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.
Structural Basis for Membrane Recruitment of ATG16L1 by WIPI2 in Autophagy
Authors: Strong Lisa M. , Chang Chunmei , Alexander Boecker C. , Flower Thomas G. , Buffalo Cosmo Z. , Ren Xuefeng , Stavoe Andrea K. H. , Holzbaur Erika L. F. , Hurley James H.
Published: May 2021

Autophagy is a cellular process that degrades cytoplasmic cargo by engulfing it in a double membrane vesicle, known as the autophagosome, and delivering it to the lysosome. The ATG12–5-16L1 complex is responsible for conjugating members of the ubiquitin-like ATG8 protein family to phosphatidylethanolamine in the growing autophagosomal membrane, known as the phagophore. ATG12–5-16L1 is recruited to the phagophore by a subset of the phosphatidylinositol 3-phosphate-binding seven bladed β-propeller WIPI proteins. We determined the crystal structure of WIPI2d in complex with the WIPI2 interacting region (W2IR) of ATG16L1 comprising residues 207-230 at 1.85 Å resolution. The structure shows that the ATG16L1 W2IR adopts an alpha helical conformation and binds in an electropositive and hydrophobic groove between WIPI2 β-propeller blades 2 and 3. Mutation of residues at the interface reduces or blocks the recruitment of ATG12–5-16L1 and the conjugation of the ATG8 protein LC3B to synthetic membranes. Interface mutants show a decrease in starvation-induced autophagy. Comparisons across the four human WIPIs suggest that WIPI1 and 2 belong to a W2IR-binding subclass responsible for localizing ATG12–5-16L1 and driving ATG8 lipidation, whilst WIPI3 and 4 belong to a second W34IR-binding subclass responsible for localizing ATG2, and so directing lipid supply to the nascent phagophore. The structure provides a framework for understanding the regulatory node connecting two central events in autophagy initiation, the action of the autophagic PI 3-kinase complex on the one hand, and ATG8 lipidation on the other.