bluuebunny/crossref_metadata_2025_split huggingface dataset:
treeheatr: an R package for interpretable decision tree visualizations
Authors: Le Trang T. , Moore Jason H. 
Published: July 2020

AbstractSummarytreeheatris an R package for creating interpretable decision tree visualizations with the data represented as a heatmap at the tree’s leaf nodes. The integrated presentation of the tree structure along with an overview of the data efficiently illustrates how the tree nodes split up the feature space and how well the tree model performs. This visualization can also be examined in depth to uncover the correlation structure in the data and importance of each feature in predicting the outcome. Implemented in an easily installed package with a detailed vignette,treeheatrcan be a useful teaching tool to enhance students’ understanding of a simple decision tree model before diving into more complex tree-based machine learning methods.AvailabilityThetreeheatrpackage is freely available under the permissive MIT license athttps://trang1618.github.io/treeheatrandhttps://cran.r-project.org/package=treeheatr. It comes with a detailed vignette that is automatically built with GitHub Actions continuous integration.Contactttle@pennmedicine.upenn.edu
A coarse-grained methodology identifies intrinsic mechanisms that dissociate interacting protein pairs
Authors: Abdizadeh Haleh , Jalalypour Farzaneh , Atilgan Ali Rana , Atilgan Canan 
Published: July 2020

AbstractWe address the problem of triggering dissociation events between proteins that have formed a complex. We have collected a set of 25 non-redundant, functionally diverse protein complexes having high-resolution three-dimensional structures in both the unbound and bound forms. We unify elastic network models with perturbation response scanning (PRS) methodology as an efficient approach for predicting residues that have the propensity to trigger dissociation of an interacting protein pair, using the three-dimensional structures of the bound and unbound proteins as input. PRS reveals that while for a group of protein pairs, residues involved in the conformational shifts are confined to regions with large motions, there are others where they originate from parts of the protein unaffected structurally by binding. Strikingly, only a few of the complexes have interface residues responsible for dissociation. We find two main modes of response: In one mode, remote control of disassociation in which disruption of the electrostatic potential distribution along protein surfaces play the major role; in the alternative mode, mechanical control of dissociation by remote residues prevail. In the former, dissociation is triggered by changes in the local environment of the protein e.g. pH or ionic strength, while in the latter, specific perturbations arriving at the controlling residues, e.g. via binding to a third interacting partner is required for decomplexation. We resolve the observations by relying on an electromechanical coupling model which reduces to the usual elastic network result in the limit of the lack of coupling. We validate the approach by illustrating the biological significance of top residues selected by PRS on select cases where we show that the residues whose perturbation leads to the observed conformational changes correspond to either functionally important or highly conserved residues in the complex.
scMET: Bayesian modelling of DNA methylation heterogeneity at single-cell resolution
Authors: Kapourani Chantriolnt-Andreas , Argelaguet Ricard , Sanguinetti Guido , Vallejos Catalina A. 
Published: July 2020

AbstractHigh throughput measurements of DNA methylomes at single-cell resolution are a promising resource to quantify the heterogeneity of DNA methylation and uncover its role in gene regulation. However, limitations of the technology result in sparse CpG coverage, effectively posing challenges to robustly quantify genuine DNA methylation heterogeneity. Here we tackle these issues by introducing scMET, a hierarchical Bayesian model which overcomes data sparsity by sharing information across cells and genomic features, resulting in a robust and biologically interpretable quantification of variability. scMET can be used to both identify highly variable features that drive epigenetic heterogeneity and perform differential methylation and differential variability analysis between pre-specified groups of cells. We demonstrate scMET’s effectiveness on some recent large scale single cell methylation datasets, showing that the scMET feature selection approach facilitates the characterisation of epigenetically distinct cell populations. Moreover, we illustrate how scMET variability estimates enable the formulation of novel biological hypotheses on the epigenetic regulation of gene expression in early development. An R package implementation of scMET is publicly available athttps://github.com/andreaskapou/scMET.
Intrinsic growth heterogeneity of mouse leukemia cells underlies differential susceptibility to a growth-inhibiting anticancer drug
Authors: Seita Akihisa , Nakaoka Hidenori , Okura Reiko , Wakamoto Yuichi 
Published: July 2020

AbstractCancer cell populations consist of phenotypically heterogeneous cells. Growing evidence suggests that pre-existing phenotypic differences among cancer cells correlate with differential susceptibility to anticancer drugs and eventually lead to a relapse. Such phenotypic differences can arise not only externally driven by the environmental heterogeneity around individual cells but also internally by the intrinsic fluctuation of cells. However, the quantitative characteristics of intrinsic phenotypic heterogeneity emerging even under constant environments and their relevance to drug susceptibility remain elusive. Here we employed a microfluidic device, mammalian mother machine, for studying the intrinsic heterogeneity of growth dynamics of mouse lymphocytic leukemia cells (L1210) across tens of generations. The generation time of this cancer cell line had a distribution with a long tail and a heritability across generations. We determined that a minority of cell lineages exist in a slow-cycling state for multiple generations. These slow-cycling cell lineages had a higher chance of survival than the fast-cycling lineages under continuous exposure to the anticancer drug Mitomycin C. This result suggests that heritable heterogeneity in cancer cells’ growth in a population influences their susceptibility to anticancer drugs.
Temperature triggers provide quantitative predictions of multi-species fish spawning peaks
Authors: Choi Emma S. , Saberski Erik T. , Lorimer Tom , Smith Cameron , Kandage-don Unduwap , Burton Ronald S. , Sugihara George 
Published: July 2020

AbstractWe find a startling correlation (Pearson ρ > 0.97) between a single event in daily sea surface temperatures each spring, and peak fish egg abundance measurements the following summer, in 7 years of approximately weekly fish egg abundance data collected at Scripps Pier in La Jolla California. Even more surprising is that this event-based result persists despite the large and variable number of fish species involved (up to 46), and the large and variable time interval between trigger and response (up to ~3 months). To mitigate against potential over-fitting, we make a true out-of-sample prediction for the peak summer egg abundance that will be observed at Scripps Pier this year.
Comprehensive in-vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms
Authors: Huston Nicholas C. , Wan Han , Araujo Tavares Rafael de Cesaris , Wilen Craig , Pyle Anna Marie 
Published: July 2020

SummarySARS-CoV-2 is the positive-sense RNA virus that causes COVID-19, a disease that has triggered a major human health and economic crisis. The genome of SARS-CoV-2 is unique among viral RNAs in its vast potential to form stable RNA structures and yet, as much as 97% of its 30 kilobases have not been structurally explored in the context of a viral infection. Our limited knowledge of SARS-CoV-2 genomic architecture is a fundamental limitation to both our mechanistic understanding of coronavirus life cycle and the development of COVID-19 RNA-based therapeutics. Here, we apply a novel long amplicon strategy to determine for the first time the secondary structure of the SARS-CoV-2 RNA genome probed in infected cells. In addition to the conserved structural motifs at the viral termini, we report new structural features like a conformationally flexible programmed ribosomal frameshifting pseudoknot, and a host of novel RNA structures, each of which highlights the importance of studying viral structures in their native genomic context. Our in-depth structural analysis reveals extensive networks of well-folded RNA structures throughout Orf1ab and reveals new aspects of SARS-CoV-2 genome architecture that distinguish it from other single-stranded, positive-sense RNA viruses. Evolutionary analysis of RNA structures in SARS-CoV-2 shows that several features of its genomic structure are conserved across beta coronaviruses and we pinpoint individual regions of well-folded RNA structure that merit downstream functional analysis. The native, complete secondary structure of SAR-CoV-2 presented here is a roadmap that will facilitate focused studies on mechanisms of replication, translation and packaging, and guide the identification of new RNA drug targets against COVID-19.
Quantum aspects of evolution: a contribution toward evolutionary explorations of genotype networks via quantum walks
Authors: Santiago-Alarcon Diego , Tapia-McClung Horacio , Lerma-Hernández Sergio , Venegas-Andraca Salvador E. 
Published: July 2020

AbstractQuantum biology seeks to explain biological phenomena via quantum mechanisms, such as enzyme reaction rates via tunneling and photosynthesis energy efficiency via coherent superposition of states. However, less effort has been devoted to study the role of quantum mechanisms in biological evolution. In this paper, we used transcription factor networks with two and four different phenotypes, and used classical random walks (CRW) and quantum walks (QW) to compare network search behavior and efficiency at finding novel phenotypes between CRW and QW. In the network with two phenotypes, at temporal scales comparable to decoherence time TD, QW are as efficient as CRW at finding new phenotypes. In the case of the network with four phenotypes, the QW had a higher probability of mutating to a novel phenotype than the CRW, regardless of the number of mutational steps (i.e., 1, 2 or 3) away from the new phenotype. Before quantum decoherence, the QW probabilities become higher turning the QW effectively more efficient than CRW at finding novel phenotypes under different starting conditions. Thus, our results warrant further exploration of the QW under more realistic network scenarios (i.e., larger genotype networks) in both closed and open systems (e.g., by considering Lindblad terms).
Early Repolarization Pattern and Suicidal Risks: A Single Center Case-Control Study
Authors: Kameyama Hiroshi , Sugimoto Kenichi , Itoh Kyoko , Nukariya Kazutaka , Kato Tomohiro , Shigeta Masahiro 
Published: July 2020

AbstractBackgroundEarly repolarization pattern was reported to be associated with mental illness. However, its role in patients with the suicidal risks remains unclear.ObjectiveThe aim of this study is to examine the frequency of Early repolarization pattern in patients with the suicidal risks compared with the age matched medical checkups.MethodA retrospective analysis of 27 patients with a history of suicide risks, including suicide attempt and nonsuicidal self-injury, and a family history of suicide. The presence of early repolarization pattern was compared in patients with suicidal risks and controls. Social and psychological factors were also compared among the patients with suicidal risks with or without Early repolarization pattern.ResultComparing the controls, Early repolarization pattern was significantly observed in the patients (14 patients: 52%, 7 controls: 9%, P<0.001). After logistic regression including the other clinical findings among the patients and controls, the presence of Early repolarization pattern was associated with the patients with the suicidal risks (p < 0.001). In the patients with suicide, there were no difference between the clinical factors compared with or without Early repolarization pattern.ConclusionThere could be association between Early repolarization pattern and the patients with the suicidal risks. Further studies are needed to confirm the association between suicidal risks and Early repolarization pattern.
ICU admissions and in-hospital deaths linked to covid-19 in the Paris region are correlated with previously observed ambient temperature
Authors: Mejdoubi Mehdi , Kyndt Xavier , Djennaoui Mehdi 
Published: July 2020

ABSTRACTOBJECTIVETo study the effect of weather on severity indicators of coronavirus disease 2019 (covid-19).DESIGNEcological study.SETTINGParis region.POPULATIONSeverely ill patients with covid-19.MAIN OUTCOME MEASURESDaily covid-19-related intensive care unit (ICU) admission and in-hospital deaths in the Paris region, and the daily weather characteristics of Paris midtown.RESULTSDaily ICU admissions and in-hospital deaths were strongly and negatively correlated to ambient temperatures, with a time lag. The highest Pearson correlation coefficients and statistically significant P values were found 8 days before occurrence of ICU admissions and 15 days before deaths.CONCLUSIONSThe study findings show a strong effect of previously observed ambient temperature that has an effect on severity indicators of covid-19.Strengths and limitations of this studyWe assessed the link between weather characteristics with a time lag and covid-19-related hospital severity indicators.This is the first study, with reliable data, to find a strong negative correlation between previously observed ambient temperature with covid-19-related iCU admissions and in-hospital deaths.It is compatible with the natural history (including hospitalisation) of covid-19 outbreak in a highly developed country.We also report the duration after which iCU admissions and in-Hospital deaths occurs following temperature variation (respectively median of 8 and 15 days).Our analyses are mainly valid for temperate climate countries.
Eurofins Covid-19 Sentinel™ Wastewater Test Provide Early Warning of a potential COVID-19 outbreak
Authors: Jørgensen Alissa Carina Udi , Gamst Jesper , Hansen Line Visby , Knudsen Ida Ingeborg Høgh , Jensen Søren Krohn Skovgaard 
Published: July 2020

AbstractThe Eurofins Covid-19 Sentinel™ program was developed to monitor the evolution of the pandemic and for early detection of outbreaks. The study objective was to develop a wastewater testing method to analyze SARS-CoV-2 as an indicator of community infection rate as of resurgence of COVID-19 in well-defined sites such as production facilities, hospitals or nursing homes. Eurofins performed >700 tests on 78 unique samples from 18 sites in Denmark, France and Belgium. Ten variant test protocols were trialed. Protocol variations trialed included centrifugation, precipitation of the SARS-CoV-2 RNA, agitation prior to precipitation, cooling, and pasteurization of the samples. A method was succesfully developed and reliability was supported by stability, reproducibility, and dilution & linearity studies. Results obtained showed a direct link to number of RNA copies in the sample using a calibration curve with synthetic SARS-CoV-2. Analysis was performed on both the liquid phase and solid phase of wastewater samples, with virus RNA detected in both phases but more frequently in the liquid phase. The virus was present in a sample from a Danish community wastewater treatment plant collected on February 24, 3 days before the first COVID-19 case was officially reported in the country. The greatest concentration of virus detected corresponded to when the COVID-19 crisis was at its peak in Denmark. Based on studies carried out in a Danish hospital, the wastewater testing method is expected to be able to detect a community COVID-19 prevalence rate as low as a 0,02%-0,1% (i.e. between 2 virus shedders per 10000 persons and 1 virus shedder per 1000). The wastewater testing method was used to monitor a Danish Community after a COVID-19 outbreak and it was shown that the method can be used as a semi-quantitative method to monitor the development of an outbreak.
Genomic Evidences Support an Independent History of Grapevine Domestication in the Levant
Authors: Sivan Aviad , Rahimi Oshrit , Salmon-Divon Mail , Weiss Ehud , Drori Elyashiv , Hübner Sariel 
Published: July 2020

AbstractThe ancient grapevines of the Levant have inspired beliefs and rituals in human societies which are still practiced today in religious and traditional ceremonies around the world. Despite their importance, the original Levantine wine-grapes varieties were lost due to cultural turnovers commencing in the 7thcentury CE, which lead to the collapse of a flourishing winemaking industry in this region. Recently, a comprehensive survey of feral grapevines was conducted in Israel in an attempt to identify local varieties, yet the origin of these domesticated accessions is unclear. Here we study the origin of Levantine grapevines using whole-genome sequence data generated for a diversity panel of wild and cultivated accessions. Comparison between Levantine and Eurasian grapevines indicated that the Levantine varieties represent a distinct lineage from the Eurasian varieties. Demographic models further supported this observation designating that domestication in the Caucasus region predated the emergence of the Levantine samples in circa 5000 years and that authentic descendants of ancient varieties are represented among the Levantine samples. We further explore the pedigree relationship among cultivated grapevines, identify footprints of selective sweeps, and estimate the extent of genetic load in each group. We conclude that the Levantine varieties are distinct from the Eurasian varieties and that resistance to disease and abiotic stress are key traits in the development of both Eurasian and Levantine varieties.
Pairwise Interactions in Adjuvant Combinations Dictate Immune Responses and Inform Cancer Immunotherapy Design
Authors: Pandey Surya , Gruenbaum Adam , Kanashova Tamara , Mertins Philipp , Cluzel Philippe , Chevrier Nicolas 
Published: July 2020

SUMMARYThe immune system makes decisions in response to complex combinations of microbial inputs. We do not understand the combinatorial logic that governs how the interplay between higher-order combinations of microbial or adjuvant signals shape immune responses, which hampers the rational design of vaccines and immunotherapies. Here, usingin vitrococulture experiments and statistical analyses, we discover a general property for the combinatorial sensing of microbial signals, whereby the effects of triplet combinations of adjuvants on immune responses can be explained by the effects of single and pairwise stimulations. Mechanistically, we find that adjuvant singles and pairs dictate the information signaled by triplets in mouse and human DCs at the levels of transcription, chromatin and protein secretion. Furthermore, we exploit this simplifying property to develop and characterize cell-based immunotherapies using adjuvant combinations with anti-tumor properties in mouse models. We conclude that the processing of complex mixtures of microbial or adjuvant inputs by immune cells is governed by pairwise effects, which will inform the rationale combination of immunomodulatory agents such as adjuvants to manipulate immunity.
Deconvolution of ears’ activity (DEA): A new experimental paradigm to investigate central auditory processing
Authors: Bardy Fabrice 
Published: July 2020

AbstractA novel experimental paradigm, “deconvolution of ears’ activity” (DEA), is presented which allows to disentangle overlapping neural activity from both auditory cortices when two auditory stimuli are presented closely together in time in each ear.Pairs of multi-tone complexes were presented either binaurally, or sequentially by alternating presentation order in each ear (i.e., first tone complex of the pair presented to one ear and second tone complex to the other ear), using stimulus onset asynchronies (SOAs) shorter than the neural response length. This timing strategy creates overlapping responses, which can be mathematically separated using least-squares deconvolution.The DEA paradigm allowed the evaluation of the neural representation in the auditory cortex of responses to stimuli presented at syllabic rates (i.e., SOAs between 120 and 260 ms). Analysis of the neuromagnetic responses in each cortex offered a sensitive technique to study hemispheric lateralization, ear representation (right versus left), pathway advantage (contra- versus ipsi-lateral) and cortical binaural interaction.To provide a proof-of-concept of the DEA paradigm, data was recorded from three normal-hearing adults. Results showed good test-retest reliability, and indicated that the difference score between hemispheres can potentially be used to assess central auditory processing. This suggests that the method could be a potentially valuable tool for generating an objective “auditory profile” by assessing individual fine-grained auditory processing using a non-invasive recording method.
Wide spectrum of neuronal and network phenotypes in human stem cell-derived excitatory neurons with Rett syndrome-associatedMECP2mutations
Authors: Mok Rebecca SF , Zhang Wenbo , Sheikh Taimoor I , Pradeepan Kartik , Fernandes Isabella R , DeJong Leah C , Benigno Gabriel , Hildebrandt Matthew R , Mufteev Marat , Rodrigues Deivid C , Wei Wei , Piekna Alina , Liu Jiajie , Muotri Alysson R , Vincent John B , Muller Lyle , Martinez-Trujillo Julio , Salter Michael W , Ellis James 
Published: July 2020

ABSTRACTRett syndrome (RTT) is a severe neurodevelopmental disorder primarily caused by heterozygous loss-of-function mutations in the X-linked geneMECP2that is a global transcriptional regulator. Mutations in the methyl-CpG binding domain (MBD) of MECP2 disrupt its interaction with methylated DNA. Here, we investigate the effect ofMECP2L124W missense mutation in the MBD of an atypical RTT patient in comparison to severeMECP2null mutations. L124W protein had a limited ability to disrupt heterochromatic chromocenters due to decreased binding dynamics. We isolated two pairs of isogenic WT and L124W induced pluripotent stem cells. L124W induced excitatory neurons expressed stable protein, exhibited increased input resistance and decreased voltage-gated Na+and K+currents, and their neuronal dysmorphology was limited to decreased dendritic complexity. Three isogenic pairs ofMECP2null neurons had the expected more extreme morphological and electrophysiological phenotypes. We examined development and maturation of L124W andMECP2null excitatory neural network activity using micro-electrode arrays. Relative to isogenic controls, L124W neurons had an increase in synchronous network burst frequency, in contrast toMECP2null neurons that suffered a significant decrease in synchronous network burst frequency and a transient extension of network burst duration. We capture these findings in a computational neural network model that shows the observed changes in network dynamics are best explained by changes in intrinsic adaptation currents in individual neurons. Our multilevel results demonstrate that RTT excitatory neurons show a wide spectrum of morphological, electrophysiological and circuitry phenotypes that are dependent on the severity of theMECP2mutation.