bluuebunny/crossref_metadata_2025_split huggingface dataset:
Natural language processing for patient selection in phase I/II oncology clinical trials
Authors: Delorme Julie , Charvet Valentin , Wartelle Muriel , Lion François , Thuillier Bruno , Mercier Sandrine , Soria Jean-Charles , Azoulay Mikael , Besse Benjamin , Massard Christophe , Hollebecque Antoine , Verlingue Loic 
Published: February 2021

AbstractPurposeEarly discontinuation affects over one-third of patients enrolled in early-phase oncology clinical trials. Early discontinuation is deleterious both for the patient and for the study, by inflating its duration and associated costs. We aimed at predicting the successful screening and dose-limiting toxicity period completion (SSD) from automatic analysis of consultation reports.Materials and methodsWe retrieved the consultation reports of patients included in phase I and/or phase II oncology trials for any tumor type at Gustave Roussy, France. We designed a pre-processing pipeline that transformed free-text into numerical vectors and gathered them into semantic clusters. These document-based semantic vectors were then fed into a machine learning model that we trained to output a binary prediction of SSD status.ResultsBetween September, 2012 and July, 2020, 56,924 consultation reports were used to build the dictionary, and 1,858 phase I/II inclusion reports were used to train (75%), validate (15%) and test (15%) a Random Forest model. Pre-processing could efficiently cluster words with semantic proximity. On the unseen test cohort of 264 consultation reports, the performances of the model reached: F1 score 0.80, recall 0.81 and AUC 0.88. Using this model, we could have reduced the screen fail rate (including DLT period) from 39.8% to 12.8% (RR=0.322, 95%CI[0.209-0.498], p<0.0001) within the test cohort. Most important semantic clusters for predictions comprised words related to hematological malignancies, anatomo-pathological features and laboratory and imaging interpretation.ConclusionMachine learning with semantic conservation is a promising tool to assist physicians in selecting patients prone to achieve SSD in early-phase oncology clinical trials.
SplitStrains, a tool to identify and separate mixed Mycobacterium tuberculosis infections from WGS data
Authors: Gabbasov Einar , Moreno-Molina Miguel , Comas Iñaki , Libbrecht Maxwell , Chindelevitch Leonid 
Published: February 2021

AbstractThe occurrence of multiple strains of a bacterial pathogen such as M. tuberculosis or C. difficile within a single human host, referred to as a mixed infection, has important implications for both healthcare and public health. However, methods for detecting it, and especially determining the proportion and identities of the underlying strains, from WGS (whole-genome sequencing) data, have been limited.In this paper we introduce SplitStrains, a novel method for addressing these challenges. Grounded in a rigorous statistical model, SplitStrains not only demonstrates superior performance in proportion estimation to other existing methods on both simulated as well as real M. tuberculosis data, but also successfully determines the identity of the underlying strains.We conclude that SplitStrains is a powerful addition to the existing toolkit of analytical methods for data coming from bacterial pathogens, and holds the promise of enabling previously inaccessible conclusions to be drawn in the realm of public health microbiology.Author summaryWhen multiple strains of a pathogenic organism are present in a patient, it may be necessary to not only detect this, but also to identify the individual strains. However, this problem has not yet been solved for bacterial pathogens processed via whole-genome sequencing. In this paper, we propose the SplitStrains algorithm for detecting multiple strains in a sample, identifying their proportions, and inferring their sequences, in the case of Mycobacterium tuberculosis. We test it on both simulated and real data, with encouraging results. We believe that our work opens new horizons in public health microbiology by allowing a more precise detection, identification and quantification of multiple infecting strains within a sample.
The changing characteristics of COVID-19 presentations: A regional comparison of SARS-CoV-2 hospitalised patients during the first and second wave
Authors: Atkin Catherine , Kamwa Vicky , Reddy-Kolanu V , Parekh D , Evison Felicity , Nightingale Peter , Gallier Suzy , Ball Simon , Sapey Elizabeth 
Published: February 2021

AbstractBackgroundThis study assesses COVID-19 hospitalised patient demography and outcomes during wave 1 and wave 2, prior to new variants of the virus.MethodsAll patients with a positive SARS-CoV-2 swab between 10th March 2020 and 5th July 2020 (wave 1) and 1st September 2020 and 16th November 2020 (wave 2) admitted to University Hospitals Birmingham NHS Foundation Trust were included (n=4856), followed for 28 days.ResultsWave 2 patients were younger, more ethnically diverse, had less co-morbidities and disease presentation was milder on presentation. After matching for these factors, mortality was reduced, but without differences in intensive care admissions.ConclusionPrior to new SARS-CoV-2 variants, outcomes for hospitalised patients with COVID-19 were improving but with similar intensive care needs.
Limiting the loss of terrestrial ecosystems to safeguard nature for biodiversity and humanity
Authors: Simmonds Jeremy S. , Suarez-Castro Andres Felipe , Reside April E. , Watson James E.M. , Allan James R. , Borrelli Pasquale , Dudley Nigel , Edwards Stephen , Fuller Richard A. , Game Edward T. , Linke Simon , Maxwell Sean L. , Panagos Panos , Puydarrieux Philippe , Quétier Fabien , Runting Rebecca K. , Santini Talitha , Sonter Laura J. , Maron Martine 
Published: February 2021

ABSTRACTHumanity is on a pathway of unsustainable loss of the natural systems upon which we, and all life, rely. To date, global efforts to achieve internationally-agreed goals to reduce carbon emissions, halt biodiversity loss, and retain essential ecosystem services, have been poorly integrated. However, these different goals all rely on preserving natural ecosystems. Here, we show how to unify these goals by empirically deriving spatially-explicit, quantitative area-based targets for the retention of natural terrestrial ecosystems. We found that at least 67 million km2of Earth’s natural terrestrial ecosystems (~79% of the area remaining) require retention – via a combination of strict protection but more prominently through sustainably managed land use regimes complemented by restoration actions – to contribute to biodiversity, climate, soil and freshwater objectives under four United Nations’ Resolutions. This equates to retaining natural ecosystems across ~50% of the total terrestrial (excluding Antarctica) surface of Earth. Our results show where retention efforts could be focussed to contribute to multiple goals simultaneously. The retention targets concept that we present explicitly recognises that such management can and should co-occur alongside and be driven by the people who live in and rely on places where natural and semi-natural ecosystems remain on Earth.
Two distinct types of nodes of Ranvier support auditory nerve function in the mouse cochlea
Authors: Panganiban Clarisse H. , Barth Jeremy L. , Tan Junying , Noble Kenyaria V. , McClaskey Carolyn M. , Dias James W. , Harris Kelly C. , Lang Hainan 
Published: February 2021

AbstractGlial cells of the auditory nerve regulate formation of the nodes of Ranvier that are needed for regeneration of action potentials and proper hearing function. Here we identify and describe the distinct features of two novel types of Ranvier nodes—the axonal node and the ganglion node—in the mouse auditory nerve that change across the lifespan, including during myelination and postnatal development, and degenerate during aging. Cellular, molecular, and structure-function correlation evaluations revealed that nodal types are critical for different aspects of auditory nerve function. Specifically, the length of the axonal node is associated with neural processing speed and neural synchrony, whereas ganglion node development is associated with amplitude growth of the action potential. Moreover, our data indicate that dysregulation of glial cells and associated degeneration of the ganglion node structure are an important and new mechanism of auditory nerve dysfunction in age-related hearing loss.
Resolving the conflict between antibiotic production and rapid growth by recognition of peptidoglycan of susceptible competitors
Authors: Maan Harsh , Friedman Jonathan , Kolodkin-Gal Ilana 
Published: February 2021

AbstractMicrobial communities employ a variety of complex strategies to compete successfully against competitors sharing their niche, with antibiotic production being a common strategy of aggression. Here, by systematic evaluation of all non-ribosomal peptides (NRP) produced byB. subtilisclade, we revealed that they acted either synergistically or additively to effectively eliminate phylogenetically distinct competitors. All four major NRP biosynthetic clusters were also imperative for the survival ofB. subtilisin a complex community extracted from the rhizosphere. The production of NRP came with a fitness cost manifested in growth inhibition, rendering NRP synthesis uneconomical when growing in proximity to a phylogenetically close species, carrying resistance against the same antibiotics. To resolve this conflict and ease the fitness cost, NRP production was only induced by the presence of peptidoglycan cue from a sensitive competitor. These results experimentally demonstrate a general ecological concept – closely related communities (“self”) are favoured during competition, due to compatibility in attack and defence mechanisms.
Ethanol-guided behavior inDrosophilalarvae
Authors: Schumann Isabell , Berger Michael , Nowag Nadine , Schäfer Yannick , Saumweber Juliane , Scholz Henrike , Thum Andreas S. 
Published: February 2021

AbstractChemosensory signals allow vertebrates and invertebrates not only to orient in its environment toward energy-rich food sources to maintain nutrition but also to avoid unpleasant or even poisonous substrates. Ethanol is a substance found in the natural environment ofDrosophila melanogaster. Accordingly,D. melanogasterhas evolved specific sensory systems, physiological adaptations, and associated behaviors at its larval and adult stage to perceive and process ethanol.To systematically analyze howD. melanogasterlarvae respond to naturally occurring ethanol, we examined ethanol-induced behavior in great detail by parametrically reevaluating existing approaches and comparing them with new experiments. Using behavioral assays, we confirm that larvae are attracted to different concentrations of ethanol in their environment. This behavior is controlled both by olfactory and contact cues. It is independent of previous exposure to ethanol in their food. Moreover, moderate, naturally occurring ethanol concentration of 4% results in increased larval fitness. On the contrary, higher concentrations of 10% and 20% ethanol, which rarely or never appear in nature, increase larval mortality. Finally, ethanol also serves as a positive teaching signal in learning and memory and updates valence associated with simultaneously processed odor information.Since information on how larvae perceive and process ethanol at the genetic and neuronal level is limited, the establishment of standardized assays described here is an important step towards their discovery.
Selection and structural characterisation of anti-TREM2 scFvs that reduce levels of shed ectodomain
Authors: Szykowska Aleksandra , Chen Yu , Smith Thomas B , Preger Charlotta , Yang Jingjing , Qian Dongming , Mukhopadhyay Shubhashish M , Wigren Edvard , Neame Stephen J , Gräslund Susanne , Persson Helena , Atkinson Peter J , Di Daniel Elena , Mead Emma , Wang John , Davis John B , Burgess-Brown Nicola A , Bullock Alex N 
Published: February 2021

SummarySingle point mutations in TREM2, a receptor expressed by microglia in the brain, are associated with an increased risk of neurodegeneration including Alzheimer’s disease. Numerous studies support a role for TREM2 in sensing damaging stimuli and triggering signalling cascades necessary for neuroprotection. Despite its significant role, ligands and regulators of TREM2 activation, and the mechanisms governing TREM2-dependent responses and its cleavage from the membrane, remain poorly characterised. Here, we present phage display generated scFv antibody binders to human TREM2 ectodomain. Cocrystal structures revealed the binding of two scFvs to an epitope on the globular TREM2 domain distal to the putative ligand-binding site. Enhanced functional activity was observed for oligomeric scFv species which inhibited the production of soluble TREM2 in a HEK293 cell model. We hope that detailed characterisation of their epitopes and properties will facilitate the use of these renewable binders as structural and functional biology tools for TREM2 research.
Unsupervised selection of optimal single-molecule time series idealization criterion
Authors: Bandyopadhyay Argha , Goldschen-Ohm Marcel P. 
Published: February 2021

AbstractSingle-molecule (SM) approaches have provided valuable mechanistic information on many biophysical systems. As technological advances lead to ever-larger datasets, tools for rapid analysis and identification of molecules exhibiting the behavior of interest are increasingly important. In many cases the underlying mechanism is unknown, making unsupervised techniques desirable. The Divisive Segmentation and Clustering (DISC) algorithm is one such unsupervised method that idealizes noisy SM time series much faster than computationally intensive approaches without sacrificing accuracy. However, DISC relies on a user selected objective criterion (OC) to guide its estimation of the ideal time series. Here, we explore how different OCs affect DISC’s performance for data typical of SM fluorescence imaging experiments. We find that OCs differing in their penalty for model complexity each optimize DISC’s performance for time series with different properties such as signal-to-noise and number of sample points. Using a machine learning approach, we generate a decision boundary that allows unsupervised selection of OC based on the input time series to maximize performance for different types of data. This is particularly relevant for SM fluorescence datasets which often have signal-to-noise near the derived decision boundary and include time series of nonuniform length due to stochastic bleaching. Our approach allows unsupervised per-molecule optimization of DISC, which will substantially assist rapid analysis of high-throughput single-molecule datasets with noisy samples and nonuniform time windows.
Strain dynamics of specific contaminant bacteria modulate the performance of ethanol biorefineries
Authors: Lino Felipe Senne de Oliveira , Misiakou Maria-Anna , Kang Kang , Li Simone S. , da Costa Bruno Labate Vale , Basso Thiago Olitta , Panagiotou Gianni , Sommer Morten Otto Alexander 
Published: February 2021

AbstractBioethanol is a viable alternative for fossil fuels, and its use has lowered CO2emissions by over 500 million tonnes in Brazil alone by replacing more than 40% of the national gasoline consumption. However, contaminant bacteria reduce yields during fermentation. Our understanding of these contaminants is limited to targeted studies, and the interplay of the microbial community and its impact on fermentation efficiency remains poorly understood. Comprehensive surveying and longitudinal analysis using shotgun metagenomics of two major biorefineries over a production season revealed similar patterns in microbial community structure and dynamics throughout the entire fermentation system. Strain resolution metagenomics identified specificLactobacillus fermentumstrains as strongly associated with poor industrial performance and laboratory-scale fermentations revealed yield reductions of up to 4.63±1.35% depending on the specific contaminating strains. Selective removal of these strains could reduce emissions from the bioethanol industry by more than 2×106tonnes per year. Using the large-scale Brazilian ethanol fermentations as a model system for studying microbiome-phenotype relationships this study further demonstrates how high-resolution metagenomics can identify culprits of large scale industrial biomanufacturing.
Non-linear Dimensionality Reduction on Extracellular Waveforms Reveals Cell Type Diversity in Premotor Cortex
Authors: Lee Eric Kenji , Balasubramanian Hymavathy , Tsolias Alexandra , Anakwe Stephanie , Medalla Maria , Shenoy Krishna V. , Chandrasekaran Chandramouli 
Published: February 2021

AbstractCortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Currentin vivomethods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We applyWaveMAPto extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. UsingWaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using feature-based approaches.WaveMAPtherefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.SignificanceHow different cell types sculpt activity patterns in brain areas associated with decision-making is a fundamentally unresolved problem in neuroscience. In monkeys, and other species where transgenic access is not yet possible, identifying physiological typesin vivorelies on only a few discrete user-specified features of extracellular waveforms to identify cell types. Here, we show that non-linear dimensionality reduction with graph clustering applied to the entire extracellular waveform can delineate many different putative cell types and does so in an interpretable manner. We show that this method reveals previously undocumented physiological, functional, and laminar diversity in the dorsal premotor cortex of monkeys, a key brain area implicated in decision-making.
Epstein-Barr virus long non-coding RNARPMS1full-length spliceome in transformed epithelial tissue
Authors: Holmqvist Isak , Bäckerholm Alan , Xie Guojiang , Tian Yarong , Thorell Kaisa , Tang Ka-Wei 
Published: February 2021

AbstractEpstein-Barr virus is associated with two types of epithelial neoplasms, nasopharyngeal carcinoma and gastric adenocarcinoma. The viral long non-coding RNARPMS1is the most abundantly expressed poly-adenylated viral RNA in these malignant tissues. TheRPMS1gene is known to contain two cassette exons, exon Ia and Ib, and several alternative splicing variants have been described in low-throughput studies. To characterize the entireRPMS1spliceome we combined long-read sequencing data from the nasopharyngeal cell line C666-1 and a primary gastric adenocarcinoma, with complementary short-read sequencing datasets. We developed FLAME, a Python-based bioinformatics package that can generate complete high resolution characterization of RNA splicing at full-length. Using FLAME, we identified 32 novel exons in theRPMS1gene, primarily within the large constitutive exons III, V and VII. Two of the novel exons contained retention of the intron between exon III and exon IV, and a novel cassette exon was identified between VI and exon VII. All previously described transcript variants ofRPMS1containing putative ORFs were identified at various levels. Similarly, native transcripts with the potential to form previously reported circular RNA elements were detected. Our work illuminates the multifaceted nature of viral transcriptional repertoires. FLAME provides a comprehensive overview of the relative abundance of alternative splice variants and allows for a wealth of previously unknown splicing events to be unveiled.
Spray-induced gene silencing as a potential tool to control potato late blight disease
Authors: Kalyandurg Pruthvi B. , Sundararajan Poorva , Dubey Mukesh , Ghadamgahi Farideh , Zahid Muhammad Awais , Whisson Stephen C. , Vetukuri Ramesh R. 
Published: February 2021

AbstractPhytophthora infestanscauses late blight disease on potato and tomato and is currently controlled by resistant cultivars or intensive fungicide spraying. Here, we investigated an alternative means for late blight control by spraying potato leaves with double-stranded RNAs (dsRNA) that targetP. infestansgenes that are essential for infection. Through confocal microscopy, we show that the sporangia ofP. infestansexpressing Green Fluorescent Protein (GFP) can take upin vitrosynthesized dsRNAs homologous to GFP directly from their surroundings, including leaves, which leads to the reduced relative expression ofGFP. We further demonstrate the potential of spray induced gene silencing (SIGS) in controlling potato late blight disease by targeting developmentally important genes inP.infestanssuch as guanine-nucleotide binding (G) protein β-subunit (PiGPB1), haustorial membrane protein (PiHmp1), cutinase (PiCut3), and endo-1,3(4)-β-glucanase (PiEndo3). Our results demonstrate that SIGS can be potentially used to mitigate potato late blight; however, the degree of disease control is dependent on the selection of the target genes.
Chronic paternal morphine exposure increases sensitivity to morphine-derived antinociception
Authors: Toussaint Andre B. , Foster William , Jones Jessica M. , Kaufmann Samuel , Wachira Meghan , Hughes Robert , Bongiovanni Angela R. , Famularo Sydney T. , Dunham Benjamin P. , Schwark Ryan , Fried Nathan T. , Wimmer Mathieu E. , Abdus-Saboor Ishmail 
Published: February 2021

AbstractParental exposure to drugs of abuse such as opioids can have profound and long-lasting effects on reward processing and drug sensitivity across generations. However, little is known about the impact of long-term paternal exposure to morphine on offspring sensitivity to morphine-derived antinociception during painful experiences. To address this question, we constructed a rat pain scale at millisecond timescales to measure mechanical nociception in a multigenerational morphine exposure paradigm. Surprisingly, while developing the pain scale, we found that von Frey hair filaments (VFHs), the most common stimuli used in pain research, are not painful to rats and morphine did not change the touch-like responses elicited by VFHs. We next deployed this novel pain scale to determine whether chronic morphine exposure in sires impacted pain sensitivity in the next generation. Offspring produced from a cross of morphine-treated sires and drug-naïve dams, did not show any baseline changes in sensitivity to mechanical nociception. However, morphine-sired male progeny displayed a higher sensitivity to the antinociceptive properties of morphine, as measured by our pain scale. These findings demonstrate that long-term paternal exposure to morphine increases sensitivity to morphine-derived analgesia in the subsequent generation.