bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lots of movement, little progress: A review of reptile home range literature
Authors: Crane Matt , Silva Inês , Marshall Benjamin Michael , Strine Colin Thomas 
Published: December 2020

AbstractReptiles are the most species-rich vertebrate group with a broad diversity of life history traits. Biotelemetry is an essential methodology for reptiles as it compensates for several limitations when studying their natural history. We evaluated trends in reptile spatial ecology studies focusing upon quantifying home ranges for the past twenty years. We assessed 290 English-language reptile home range studies published from 2000-2019 via a structured literature review investigating publications’ study location, taxonomic group, methodology, reporting, and analytical techniques. Substantial biases remain in both location and taxonomic groups in the literature, with nearly half of all studies (45%) originating from the USA. Snakes were most often studied, and crocodiles were least often studied, while testudines tended to have the greatest within study sample sizes. More than half of all studies lacked critical methodological details, limiting the number of studies for inclusion in future meta-analyses (55% of studies lacked information on individual tracking durations, and 51% lacked sufficient information on the number of times researchers recorded positions). Studies continue to rely on outdated methods to quantify space-use (including Minimum Convex Polygons and Kernel Density Estimators), often failing to report subtleties on decisions that have substantial impact on home range area estimates. Moving forward researchers can select a suite of appropriate analytical techniques tailored to their research question (dynamic Brownian Bridge Movement Models for within sample interpolation, and autocorrelated Kernel Density Estimators for beyond sample extrapolation). Only 1.4% of all evaluated studies linked to available and usable telemetry data, further hindering scientific consensus. We ultimately implore herpetologists to adopt transparent reporting practices and make liberal use of open data platforms to maximize progress in the field of reptile spatial ecology.
Minimal information for Chemosensitivity assays (MICHA): A next-generation pipeline to enable the FAIRification of drug screening experiments
Authors: Tanoli Ziaurrehman , Aldahdooh Jehad , Alam Farhan , Wang Yinyin , Seemab Umair , Fratelli Maddalena , Pavlis Petr , Hajduch Marian , Bietrix Florence , Gribbon Philip , Zaliani Andrea , Hall Matthew D. , Shen Min , Brimacombe Kyle , Kulesskiy Evgeny , Saarela Jani , Wennerberg Krister , Vähä-Koskela Markus , Tang Jing 
Published: December 2020

ABSTRACTChemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of MICHA (Minimal Information for Chemosensitivity Assays), accessed viahttps://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents, and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets, and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provideFAIRifiedprotocols from five major cancer drug screening studies, as well as six recently conducted COVID-19 studies. With the MICHA webserver and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.
Spatial distribution of local patch extinctions drives recovery dynamics in metacommunities
Authors: Saade Camille , Kéfi Sonia , Gougat-Barbera Claire , Rosenbaum Benjamin , Fronhofer Emanuel A. 
Published: December 2020

AbstractHuman activities lead more and more to the disturbance of plant and animal communities with local extinctions as a consequence. While these negative effects are clearly visible at a local scale, it is less clear how such local patch extinctions affect regional processes, such as metacommunity dynamics and the distribution of diversity in space. Since local extinctions may not be isolated events in space but rather cluster together, it is crucial to investigate their effects in a spatially explicit framework.Here, we use experimental microcosms and numerical simulations to understand the relationship between local patch extinctions and metacommunity dynamics. More specifically, we investigate the effects of the amount and spatial autocorrelation of extinctions in a full factorial design. Experimentally, we found that local patch extinctions increased inter-patch (β-) diversity by creating differences between perturbed and unperturbed patches and at the same time increased local (α-) diversity by delaying the competitive exclusion of inferior competitors. Most importantly, recolonization dynamics depended more strongly on the spatial distribution of patch extinctions than on the amount of extinctions per se. Clustered local patch extinctions reduced mixing between perturbed and unperturbed patches which led to slower recovery, lowerα-diversity in unperturbed patches and higherβ-diversity. Results from a metacommunity model matched the experimental observations qualitatively when the model included ranked competitive interactions, giving a hint at the underlying mechanisms.Our results highlight that local patch extinctions can increase the diversity within and between communities, that the strength of these effects depends on the spatial distribution of extinctions and that the effects of local patch extinctions can spread regionally, throughout a landscape. These findings are highly relevant for conservation and management of spatially structured communities under global change.
Roles of hostplant availability and quality for the distribution and climate change response of a dietary specialist herbivore
Authors: Carvajal Acosta A. Nalleli , Mooney Kailen 
Published: December 2020

AbstractSpecies distributions are recognized to be driven by abiotic factors, but the importance of biotic interactions that provide critical resources is less well understood, especially with respect to variation in critical resource quality. Disentangling the relative importance of these factors – abiotic environment, presence of critical resources and their quality-may be critical to predicting species response to climate change. We used species distribution models (SDMs) to address these questions for the western monarch butterfly (Danaus plexippus), a species that obligately feeds upon plants in the genusAsclepias, and for which hostplant quality in this region varies among species by an order of magnitude. We modeled the distribution of 24Asclepiasspecies to develop and compare three monarch distribution models with increasing levels of ecological complexity: (i) a null model using only environmental factors (a climate envelope model), (ii) a model using environmental factors andAsclepiasspp. distribution, (iii) and a model using environmental factors andAsclepiasspp. distribution weighted by hostplant quality assessed through a greenhouse bioassays of larval performance.Asclepiasmodels predicted that half of theAsclepiasspp. will both expand their ranges and shift their distribution towards higher latitudes while half will contract within the study region. Our performance analysis of monarch models revealed that the climate envelope model was the poorest performing. Adding hostplant distribution produced the best performing model, while accounting for hostplant quality did not improved model performance. The climate envelope model estimated more restrictive contemporary and future monarch ranges compared to both hostplants models. Although all three models predicted future monarch range expansions, the projected future distributions varied among models. The climate envelope model predicted range expansions along the Pacific coast and contractions inland while hostplants models predicted range expansions in both of these regions and, as a result, estimated 14 and19% increases in distribution relative to the climate envelope model, respectively. These results suggest that information on biotic interactions that provide critical resources is needed to predict future species distributions, but that variation in the quality of those critical resources may be of secondary importance.
Manifold learning analysis suggests novel strategies for aligning single-cell multi-modalities and revealing functional genomics for neuronal electrophysiology
Authors: Huang Jiawei , Sheng Jie , Wang Daifeng 
Published: December 2020

AbstractRecent single-cell multi-modal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, our understanding of functional genomics and gene regulation leading to various cellular characteristics remains elusive. To address this, we applied multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain. We found that nonlinear manifold learning outperforms other methods. After manifold alignment, the cell clusters highly correspond to transcriptomic and morphological cell-types, suggesting a strong nonlinear relationship between gene expression and electrophysiology at the cell-type level. The aligned cells form developmental trajectories and show continuous changes of electrophysiological features, implying the underlying developmental process. We also found that the manifold-aligned cell clusters’ differentially expressed genes can predict many electrophysiological features. Functional enrichment and gene regulatory network analyses for those cell clusters revealed potential genome functions and molecular mechanisms from gene expression to neuronal electrophysiology.
Zika Virus Infection Prevents Host mRNA Nuclear Export by Disrupting UPF1 Function
Authors: Leon Kristoffer , Flynn Ryan , Khalid Mir M. , Fontaine Krystal A. , Nguyen Tom , Kumar G. Renuka , Simoneau Camille R , Tomar Sakshi , Jimenez-Morales David , Dunlap Mariah , Kaye Julia , Shah Priya S , Finkbeiner Steven , Krogan Nevan J , Bertozzi Carolyn , Carette Jan E. , Ott Melanie 
Published: December 2020

AbstractZika virus (ZIKV) is a mosquito-borne RNA virus that can infect fetusesin uterocausing characteristic neurodevelopmental disorders including microcephaly. We previously showed that ZIKV infection downregulates expression of up-frameshift protein 1 (UPF1), a helicase/ATPase and central regulator of the nonsense-mediated mRNA decay pathway. Here, we identify a novel function of nuclear UPF1 in mRNA export. Using crosslinking immunoprecipitation of UPF1 followed by sequencing of associated transcripts as well as fluorescence in situ hybridization experiments, we find widespread mRNA accumulation in the nucleus of human neural progenitor cells (NPCs) upon ZIKV infection or UPF1 knockdown. Knockdown ofFREM2, a top UPF1 target transcript encoding an extra-cellular matrix protein critical in fetal development, decreased expression of pluripotency markers and increased expressed neuronal differentiation in NPCs, consistent with the model that trappingFREM2mRNA in the nucleus perturbs proper NPC function. Collectively, our data uncover a new posttranscriptional mechanism by which ZIKV “shuts off” host mRNA export via UPF1. As we find UPF1 linked to many neurodevelopment pathways, we propose that the lack of host mRNA export contributes to the neurodevelopmental defects associated with ZIKV infection.
The Impact of Digital Histopathology Batch Effect on Deep Learning Model Accuracy and Bias
Authors: Howard Frederick M. , Dolezal James , Kochanny Sara , Schulte Jefree , Chen Heather , Heij Lara , Huo Dezheng , Nanda Rita , Olopade Olufunmilayo I. , Kather Jakob N. , Cipriani Nicole , Grossman Robert , Pearson Alexander T. 
Published: December 2020

AbstractThe Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. However, we demonstrate that these features vary substantially across tissue submitting sites in TCGA for over 3,000 patients with six cancer subtypes. Additionally, we show that histologic image differences between submitting sites can easily be identified with DL. This site detection remains possible despite commonly used color normalization and augmentation methods, and we quantify the digital image characteristics constituting this histologic batch effect. As an example, we show that patient ethnicity within the TCGA breast cancer cohort can be inferred from histology due to site-level batch effect, which must be accounted for to ensure equitable application of DL. Batch effect also leads to overoptimistic estimates of model performance, and we propose a quadratic programming method to guide validation that abrogates this bias.
Unscrambling cancer genomes via integrated analysis of structural variation and copy number
Authors: Shale Charles , Baber Jonathan , Cameron Daniel L. , Wong Marie , Cowley Mark J. , Papenfuss Anthony T. , Cuppen Edwin , Priestley Peter 
Published: December 2020

AbstractComplex somatic genomic rearrangement and copy number alterations (CNA) are hallmarks of nearly all cancers. Whilst whole genome sequencing (WGS) in principle allows comprehensive profiling of these events, biological and clinical interpretation remains challenging. We have developed LINX, a novel algorithm which allows interpretation of short-read paired-end WGS derived structural variant and CNA data by clustering raw structural variant calls into distinct events, predicting their impact on the local structure of the derivative chromosome, and annotating their functional impact on affected genes. Novel visualisations facilitate further investigation of complex genomic rearrangements. We show that LINX provides insights into a diverse range of structural variation events including single and double break-junction events, mobile element insertions, complex shattering and high amplification events. We demonstrate that LINX can reliably detect a wide range of pathogenic rearrangements including gene fusions, immunoglobulin enhancer rearrangements, intragenic deletions and duplications. Uniquely, LINX also predicts chained fusions which we demonstrate account for 13% of clinically relevant oncogenic fusions. LINX also reports a class of inactivation events we term homozygous disruptions which may be a driver mutation in up to 8.8% of tumors including frequently affectingPTEN,TP53andRB1, and are likely missed by many standard WGS analysis pipelines.
NOTCH-YAP1/TEAD-DNMT1 axis regulates hepatocyte reprogramming into intrahepatic cholangiocarcinoma
Authors: Hu Shikai , Molina Laura , Tao Junyan , Liu Silvia , Hassan Mohammed , Singh Sucha , Poddar Minakshi , Bell Aaron , Sia Daniela , Oertel Michael , Raeman Reben , Nejak-Bowen Kari , Singhi Aatur , Luo Jianhua , Monga Satdarshan P. , Ko Sungjin 
Published: December 2020

ABSTRACTIntrahepatic cholangiocarcinoma (ICC), a disease of poor prognosis, has increased in incidence. It is challenging to treat due to intra- and inter-tumoral heterogeneity, which in part is attributed to diverse cellular origin. Indeed, co-expression of AKT and NICD in hepatocytes (HCs) yielded ICC, with similarity to proliferative, Notch-activated, and stem cell-like subclasses of clinical ICC. NICD regulated SOX9 and YAP1 during ICC development.Yap1deletionor TEADinhibition impaired HC-to-biliary epithelial cell (BEC) reprogramming and ICC proliferation;Sox9loss repressed tumor growth; andYap1-Sox9combined loss abolished ICC development in AKT-NICD model. DNMT1 was discovered as a novel downstream effector of YAP1-TEAD complex that directed HC-to-BEC/ICC fate-switch. DNMT1 loss prevented Notch-dependent HC-to-ICC development, and DNMT1 re-expression restored ICC development following TEAD repression. Coexpression of DNMT1 with AKT was sufficient to induce hepatic tumor development including ICC. Thus, we have identified a novel NOTCH-YAP1/TEAD-DNMT1 axis essential for HC-driven ICC development.SIGNIFICANCEWe evaluated the clinical relevance of hepatocyte-driven ICC model and revealed critical but distinct roles of YAP1 and SOX9 in AKT-NICD-driven hepatocyte-derived ICC. We also identified NOTCH-YAP1/TEAD-DNMT1 axis as a critical driver for hepatocyte-to-ICC reprogramming, which might have biological and therapeutic implications in ICC subsets.
Dynamics of cell mass and size control in multicellular systems and the human body
Authors: Martinez-Martin David 
Published: December 2020

AbstractCellular processes, in particular homeostasis and growth, require an intricate and complex exchange of matter between a cell and its surroundings. Yet experimental difficulties have prevented a detailed description of the dynamics of a cell’s mass and volume along different cellular processes, limiting our understanding of cell physiology in health and disease. It has been recently observed that single mammalian cells fluctuate their mass in a timescale of seconds. This result challenges central and long-standing cell growth models, according to which cells increase their mass either linearly or exponentially throughout the cell cycle. However, it remains unclear to what extent cell mass fluctuations may be sustained in multicellular organisms. Here I provide a mathematical model for cell mass fluctuations and explore how such fluctuations can be successfully sustained in multicellular organisms. I postulate that cells do not synchronise their mass fluctuations, but they are executed with their phases uniformly distributed. I derive a mathematical expression to estimate the resulting mass shift between fluid compartments in an organism due to cell mass fluctuations. Together with a new estimate of 4×1013human cells in the body, I demonstrate that my hypothesis leads to shifts of mass between the intracellular and extracellular fluid compartments in the human body that are approximately or smaller than 0.25 mg and, therefore, perfectly viable. The proposed model connects cell physiology with information theory and entropy.
The Full Database of Countries with Potential COVID-19 Data Misreport based on Benford’s Law
Authors: Kilani Ahmad , Georgiou Georgios P. 
Published: December 2020

AbstractThe aim of this database is to provide researchers and scholars a unified database for potential data misreport by 171 countries regarding their COVID-19 daily reported cases. The analysis employs three different tests (chi-square, Kuiper, and Mean Absolute Deviation) to determine if the data given by each country in the world fit Benford’s Law.
Minimal requirements for a neuron to co-regulate many properties and the implications for ion channel correlations and robustness
Authors: Yang Jane , Shakil Husain , Ratté Stéphanie , Prescott Steven A. 
Published: December 2020

ABSTRACTNeurons regulate their excitability by adjusting their ion channel levels. Degeneracy – achieving equivalent outcomes (excitability) using different solutions (channel combinations) – facilitates this regulation by enabling a disruptive change in one channel to be offset by compensatory changes in other channels. But neurons must co-regulate many properties. Pleiotropy – the impact of one channel on more than one property – complicates regulation because a compensatory ion channel change that restores one property to its target value often disrupts other properties. How then does a neuron simultaneously regulate multiple properties? Here we demonstrate that of the many channel combinations producing the target value for one property (the single-output solution set), few combinations produce the target value for other properties. Combinations producing the target value for two or more properties (the multi-output solution set) correspond to the intersection between single-output solution sets. Properties can be effectively co-regulated only if the number of adjustable channels (nin) exceeds the number of regulated properties (nout). Ion channel correlations emerge during homeostatic regulation when the dimensionality of solution space (nin–nout) is low. Even if each property can be regulated to its target value when considered in isolation, regulation as a whole fails if single-output solution sets do not intersect. Our results also highlight that ion channels must be co-adjusted with different ratios to regulate different properties, which suggests that each error signal drives modulatory changes independently, despite those changes ultimately affecting the same ion channels.
Elevated temperature inhibits SARS-CoV-2 replication in respiratory epithelium independently of the induction of IFN-mediated innate immune defences
Authors: Herder Vanessa , Dee Kieran , Wojtus Joanna K. , Goldfarb Daniel , Rozario Christoforos , Gu Quan , Jarrett Ruth F. , Epifano Ilaria , Stevenson Andrew , McFarlane Steven , Stewart Meredith E. , Szemiel Agnieszka M. , Pinto Rute M. , Garriga Andreu Masdefiol , Graham Sheila V. , Murcia Pablo R. , Boutell Chris 
Published: December 2020

AbstractThe pandemic spread of SARS-CoV-2, the etiological agent of COVID-19, represents a significant and ongoing international health crisis. A key symptom of SARS-CoV-2 infection is the onset of fever, with a hyperthermic temperature range of 38 to 41°C. Fever is an evolutionarily conserved host response to microbial infection and inflammation that can influence the outcome of viral pathogenicity and regulation of host innate and adaptive immune responses. However, it remains to be determined what effect elevated temperature has on SARS-CoV-2 tropism and replication. Utilizing a 3D air-liquid interface (ALI) model that closely mimics the natural tissue physiology and cellular tropism of SARS-CoV-2 infection in the respiratory airway, we identify tissue temperature to play an important role in the regulation of SARS-CoV-2 infection. We show that temperature elevation induces wide-spread transcriptome changes that impact upon the regulation of multiple pathways, including epigenetic regulation and lncRNA expression, without disruption of general cellular transcription or the induction of interferon (IFN)-mediated antiviral immune defences. Respiratory tissue incubated at temperatures >37°C remained permissive to SARS-CoV-2 infection but severely restricted the initiation of viral transcription, leading to significantly reduced levels of intraepithelial viral RNA accumulation and apical shedding of infectious virus. To our knowledge, we present the first evidence that febrile temperatures associated with COVID-19 inhibit SARS-CoV-2 replication. Our data identify an important role for temperature elevation in the epithelial restriction of SARS-CoV-2 that occurs independently of the induction of canonical IFN-mediated antiviral immune defences and interferon-stimulated gene (ISG) expression.