bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors of characteristics associated with negative first SARS-CoV-2 PCR testing despite final diagnosis of COVID-19, and association with treatment and outcomes. The COVID-19 RT-PCR Study
Authors: Lascarrou Jean-Baptiste , Colin Gwenhael , Le Thuaut Aurélie , Serck Nicolas , Ohana Mickael , Sauneuf Bertrand , Geri Guillaume , Mesland Jean-Baptiste , Ribeyre Gaetane , Hussenet Claire , Sophie Boureau Anne , Gille Thomas 
Published: September 2020

AbstractBackgroundReverse transcriptase-polymerase chain reaction (RT-PCR) testing is an important tool for the diagnosis of coronavirus disease 2019 (COVID-19). However, performance concerns have recently emerged, especially about its sensitivity.. We hypothesized that clinical, biological and radiological characteristics of patients with false negative first RT-PCR testing, despite final diagnosis of COVID-19, might differ from patients with positive first RT-PCR.MethodsCase – control, multicenter study in which COVID-19 patients with negative first RT-PCR testing were matched to patients with positive first RT-PCR on age, gender and initial admission unit (ward or intensive care).ResultsBetween March 30, and June 22, 2020, 80 cases and 80 controls were included. Neither proportion of death at hospital discharge, nor duration of hospital length stay differed between “case” and “control” patients (P = 0.80 and P = 0.54, respectively). In multivariate analysis, headache (adjusted OR: 0.07 [0.01; 0.49]; P = 0.007) and fatigue/malaise (aOR: 0.16 [0.03; 0.81]; P = 0.027) were associated with lower risk of false negative, whereas platelets > 207.103.mm−3 (aOR: 3.81 [1.10; 13.16]; P = 0.034) and CRP > 79.8 mg.L−1 (aOR: 4.00 [1.21; 13.19]; P = 0.023) were associated with higher risk of false negative.InterpretationPatients with suspected COVID-19 and higher inflammatory biological signs expected higher risk of false negative RT-PCR testing. Strategy of serial RT-PCR testings must be rigorously evaluated before adoption by clinicians.
Containment to outbreak tipping points in COVID-19
Authors: Arim Matías , Herrera-Esposito Daniel , Bermolen Paola , Cabana Álvaro , Fariello María Inés , Lima Mauricio , Romero Hector 
Published: September 2020

AbstractNon-pharmaceutical interventions (NPIs) have been a cornerstone in managing emergent diseases such as COVID-191–4. However, despite their potential to contain or attenuate the epidemic, the effects of NPIs on disease dynamics are not well understood1,5–7. We show that saturation of NPIs with the increase in infected individuals, an expected consequence of limited contact tracing and healthcare capacities, produces a positive feedback in the disease growth rate and a threshold between two alternative states--containment and outbreak8. These alternative states were previously related with the strength of NPIs but not with the infection number2,9–11. Furthermore, the transition between these states involves an abrupt acceleration in disease dynamics, which we report here for several COVID-19 outbreaks around the world. The consequences of a positive feedback in population dynamics at low numbers is a phenomenon widely studied in ecology--the Allee effect. This effect is a determinant of extinction-outbreak states, geographic synchronization, spatial spread, and the effect of exogenous variables, as vaccination12–15. As countries are relaxing containing measures, recognizing an NPI-induced Allee effect may be essential for deploying containment strategies within and among countries16 and acknowledges the need for early warning indicators of approaching epidemic tipping points17.
Cryo-EM structure ofHelicobacter pyloriurease with a novel inhibitor in the active site at 2.0 Å resolution
Authors: Cunha Eva S. , Chen Xiaorui , Gaitero Marta Sanz , Mills Deryck J. , Luecke Hartmut 
Published: September 2020

AbstractInfection of the human stomach byHelicobacter pyloriremains a worldwide problem and greatly contributes to peptic ulcer disease and gastric cancer. Without active intervention approximately 50% of the world population will continue to be infected with this gastric pathogen. Current eradication, called triple therapy, entails a proton-pump inhibitor and two broadband antibiotics, however resistance to either clarithromycin or metronidazole is greater than 25% and rising. Therefore, there is an urgent need for a targeted, high-specificity eradication drug. Gastric infection byH. pyloridepends on the expression of a nickeldependent urease in the cytoplasm of the bacteria. Here, we report the 2.01 Å resolution structure of the 1.1 MDa urease in complex with a novel inhibitor by cryo-electron microscopy and compare it to a β-mercaptoethanol-inhibited structure at 2.45 Å resolution. The structural information is of sufficient detail to aid in the development of inhibitors with high specificity and affinity.
Oncogenic KRAS engages an RSK1/NF1 complex in pancreatic cancer
Authors: Cheng Derek K. , Oni Tobiloba E. , Park Youngkyu , Thalappillil Jennifer S. , Ting Hsiu-Chi , Alagesan Brinda , Prasad Nadia , Rivera Keith D. , Pappin Darryl J. , Van Aelst Linda , Tuveson David A. 
Published: September 2020

AbstractPancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with limited treatment options. Although activating mutations of the KRAS GTPase are the predominant dependency present in >90% of PDAC patients, targeting KRAS mutants directly has been challenging in PDAC.Similarly, strategies targeting known KRAS downstream effectors have had limited clinical success due to feedback mechanisms, alternate pathways and toxicity due to the targeting of normal tissues. Therefore, identifying additional functionally relevant KRAS interactions in PDAC may allow for a better understanding of feedback mechanisms and unveil new potential therapeutic targets. Here, we used proximity labelling to identify protein interactors of active KRAS in PDAC cells. Fusions of wildtype (BirA-KRAS4B), mutant (BirA-KRAS4BG12D) and non-transforming and cytosolic double mutant (BirA-KRAS4BG12D/C185S) KRAS with the BirA biotin ligase were expressed in murine PDAC cells. Mass spectrometry analysis revealed that RSK1 was enriched among proteins that selectively interacted with membrane-bound KRASG12D. RSK1 required the NF1 and SPRED proteins to interact with KRAS-GTP at the membrane. In both murine and human PDAC lines, membrane-targeted RSK1 was tolerated but inhibited cell proliferation following oncogenic KRAS abrogation to reveal a negative feedback role for membrane-localized RSK1 on wild-type KRAS. Inhibition of the wild-type KRAS, which has been previously proposed to suppress KRAS oncogenesis, may partially explain how RSK1 has been identified as a dependency in some KRAS mutant cells and may provide an additional function for NF1 in tumorigenesis.Significance StatementFor decades, KRAS interactors have been sought after as potential therapeutic targets in KRAS mutant cancers, especially pancreatic adenocarcinoma (PDAC). Our proximity labeling screen with KRAS in PDAC cells highlight RSK1 as a notable mutant-specific interactor. Functionally, we show that RSK1 mediates negative feedback on wild-type KRAS in PDAC cells.
Low hatching success in the critically endangered kākāpō (Strigops habroptilus) is driven by early embryo mortality not infertility
Authors: Savage James L. , Crane Jodie M. S. ,   Kākāpō Recovery Team, Hemmings Nicola 
Published: September 2020

AbstractIn many endangered species, reproductive failure is a major barrier to recovery. The critically endangered kākāpō (Strigops habroptilus) exemplifies this challenge: 61% of their eggs fail to hatch, and of these 73% show no sign of development. Undeveloped eggs have previously been attributed to male infertility, but recent studies of non-threatened bird species suggest fertilisation failure is rare in the wild. The underlying causes of fertilisation failure and embryo death differ, so distinguishing between them is essential for effective conservation management. Here we show that the majority (72%, n=124) of undeveloped kākāpō eggs are fertilised, and combine this with conservation programme data on natural copulations, artificial inseminations, and paternity of developed eggs, to generate the most precise estimate to date of fertility in a wild population. We also demonstrate, for the first time in a wild bird, that artificial insemination results in greater numbers of sperm reaching the egg.
Peptide location fingerprinting reveals modification-associated biomarkers of ageing in human tissue proteomes
Authors: Ozols Matiss , Eckersley Alexander , Mellody Kieran T , Mallikarjun Venkatesh , Warwood Stacey , O’Cualain Ronan , Knight David , Watson Rachel EB , Griffiths Christopher EM , Swift Joe , Sherratt Michael J 
Published: September 2020

AbstractAlthough dysfunctional protein homeostasis (proteostasis) is a key factor in many age-related diseases, the untargeted identification of structural modifications in proteins remains challenging. Peptide location fingerprinting is a proteomic analysis technique capable of identifying structural modification-associated differences in mass spectrometry (MS) datasets of complex biological samples. A new webtool (Manchester Peptide Location Fingerprinter), applied to photoaged and intrinsically aged skin proteomes, can relatively quantify peptides (spectral counting) and map statistically significant differences to regions within protein structures. New photoageing biomarkers were identified in multiple proteins including matrix components (collagens and proteoglycans), oxidation and protease modulators (peroxiredoxins and SERPINs) and cytoskeletal proteins (keratins). Crucially, for many extracellular biomarkers, structural modification-associated differences were not correlated with relative abundance (by ion intensity). By applying peptide location fingerprinting to published MS datasets, (identifying biomarkers including collagen V and versican in ageing tendon) we demonstrate the potential of the MPLF webtool to discover novel biomarkers.
A high-affinity calmodulin-binding site in the CyaA toxin translocation domain is essential for invasion into eukaryotic cells
Authors: Voegele Alexis , Sadi Mirko , O’Brien Darragh P , Gehan Pauline , Raoux-Barbot Dorothée , Davi Maryline , Hoos Sylviane , Brûlé Sébastien , Raynal Bertrand , Weber Patrick , Mechaly Ariel , Haouz Ahmed , Rodriguez Nicolas , Vachette Patrice , Durand Dominique , Brier Sébastien , Ladant Daniel , Chenal Alexandre 
Published: September 2020

AbstractThe molecular mechanisms and forces involved in the translocation of bacterial toxins into host cells have thus far remained elusive. The adenylate cyclase (CyaA) toxin fromBordetella pertussisdisplays a unique intoxication pathway in which its catalytic domain is directly translocated across target cell membranes. We have previously identified a translocation region in CyaA that contains a segment, P454 (residues 454–484), exhibiting membrane-active properties related to antimicrobial peptides. Herein, we show that this peptide is able to translocate across membranes and interact with calmodulin. Structural and biophysical analyses have revealed the key residues of P454 involved in membrane destabilization and calmodulin binding. Mutational analysis demonstrated that these residues play a crucial role in CyaA translocation into target cells. We have also shown that calmidazolium, a calmodulin inhibitor, efficiently blocks CyaA internalization. We propose that after CyaA binding to target cells, the P454 segment destabilizes the plasma membrane, translocates across the lipid bilayer and binds calmodulin. Trapping of the CyaA polypeptide chain by the CaM:P454 interaction in the cytosol may assist the entry of the N-terminal catalytic domain by converting the stochastic process of protein translocation into an efficient vectorial chain transfer into host cells.
Deep learning for supervised classification of temporal data in ecology
Authors: Capinha César , Ceia-Hasse Ana , Kramer Andrew M. , Meijer Christiaan 
Published: September 2020

AbstractTemporal data is ubiquitous in ecology and ecologists often face the challenge of accurately differentiating these data into predefined classes, such as biological entities or ecological states. The usual approach consists of transforming the time series into user-defined features and then using these features as predictors in conventional statistical or machine learning models. Here we suggest the use of deep learning models as an alternative to this approach. Recent deep learning techniques can perform the classification directly from the time series, eliminating subjective and resource-consuming data transformation steps, and potentially improving classification results. We describe some of the deep learning architectures relevant for time series classification and show how these architectures and their hyper-parameters can be tested and used for the classification problems at hand. We illustrate the approach using three case studies from distinct ecological subdisciplines:i) insect species identification from wingbeat spectrograms;ii) species distribution modelling from climate time series andiii) the classification of phenological phases from continuous meteorological data. The deep learning approach delivered ecologically sensible and accurate classifications demonstrating its potential for wide applicability across subfields of ecology.
Minimal detection and low biological fluctuation of mitochondrial CpG methylation at the single-molecule level
Authors: Goldsmith Chloe , Rodríguez-Aguilera Jesús Rafael , El-Rifai Ines , Jarretier Adrien , Hervieu Valérie , de Sánchez Victoria Chagoya , Dante Robert , Ichim Gabriel , Hernandez-Vargas Hector 
Published: September 2020

AbstractCytosine DNA methylation in the CpG context (5mCpG) is associated with the transcriptional status of nuclear DNA. Due to technical limitations, it has been less clear if mitochondrial DNA (mtDNA) is methylated and whether 5mCpG has a regulatory role in this context. The main aim of this work was to develop and validate a novel tool for determining methylation of mtDNA and to corroborate its existence across different biological contexts. Using long-read nanopore sequencing we found low levels of CpG methylation (with few exceptions) and little variation across biological processes: differentiation, oxidative stress, and cancer. 5mCpG was overall higher in tissues compared to cell lines, with small additional variation between cell lines of different origin. Although we do show several significant changes in all these conditions, 5mCpG is unlikely to play a major role in defining the transcriptional status of mitochondrial genes.
Microfluidic Antibody Affinity Profiling for In-Solution Characterisation of Alloantibody - HLA Interactions in Human Serum
Authors: Schneider Matthias M. , Scheidt Tom , Priddey Ashley J. , Xu Catherine K. , Hu Mengsha , Devenish Sean R. A. , Meisl Georg , Dobson Christopher M. , Kosmoliaptsis Vasilis , Knowles Tuomas P. J. 
Published: September 2020

AbstractThe detection and characterisation of antibodies in human blood is a key for clinical diagnostics and risk assessment for autoimmunity, infectious diseases and transplanta-tion. Antibody titre derived from immunoassays is a commonly used measure for anti-body response, but this metric does not resolve readily the two fundamental properties of antibodies in solution, namely their affinity and concentration. This difficulty originates from the fact that the fundamental parameters describing the binding interaction, affinity and ligand concentration, are convoluted into the titre measurement; moreover, the difficulty of controlling the surface concentration and activity of the immobilised ligand can make it challenging to distinguish between avidity and affinity. To address these challenges, we developed microfluidic antibody affinity profiling, an assay which allows the simultaneous determination of both affinity and antibody concentration, directly in solution, without surface immobilisation or antibody purification. We demonstrate these measurements in the context of alloantibody characterisation in organ transplantation, using complex patient sera, and quantify the concentration and affinity of alloantibodies against donor Human Leukocyte Antigens (HLA), an extensively used clinical biomarker to access the risk of allograft rejection. These results outline a path towards detection and in depth profiling of antibody response in patient sera.
Transcriptional alterations in opioid use disorder reveal an interplay between neuroinflammation and synaptic remodeling
Authors: Seney Marianne L. , Kim Sam-Moon , Glausier Jill R. , Hildebrand Mariah A. , Xue Xiangning , Zong Wei , Wang Jiebiao , Shelton Micah A. , Phan BaDoi N. , Srinivasan Chaitanya , Pfenning Andreas R. , Tseng George C. , Lewis David A. , Freyberg Zachary , Logan Ryan W. 
Published: September 2020

AbstractBackgroundPrevalence rates of opioid use disorder (OUD) have increased dramatically, accompanied by a surge of overdose deaths. While opioid dependence has been extensively studied in preclinical models, an understanding of the biological alterations that occur in the brains of people who chronically use opioids and who are diagnosed with OUD remains limited. To address this limitation, RNA-sequencing (RNA-seq) was conducted on the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc), regions heavily implicated in OUD, from postmortem brains in subjects with OUD.MethodsWe performed RNA-seq on the DLPFC and NAc from unaffected comparison subjects (n=20) and subjects diagnosed with OUD (n=20). Our transcriptomic analyses identified differentially expressed (DE) transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric ordering (RRHO). Weighted gene co-expression analyses (WGCNA) also identified OUD-specific modules and gene networks. Integrative analyses between DE transcripts and GWAS datasets using linkage disequilibrium score (LDSC) assessed the genetic liability psychiatric-related phenotypes.ResultsRRHO analyses revealed extensive overlap in transcripts between DLPFC and NAc in OUD, primarily relating to synaptic remodeling and neuroinflammation. Identified transcripts were enriched for factors that control pro-inflammatory cytokine-mediated, chondroitin sulfate, and extracellular matrix signaling. Cell-type deconvolution implicated a role for microglia as a critical driver for opioid-induced neuroplasticity. Using LDSC, we discovered genetic liabilities for risky behavior, attention deficit hyperactivity disorder, and depression.ConclusionsOverall, our findings reveal new connections between the brain’s immune system and opioid dependence in the human brain.
Single-cell RNA Expression of SARS-CoV-2 Cell Entry Factors in Human Endometrium during Preconception
Authors: Vilella Felipe , Wang Wanxin , Moreno Inmaculada , Quake Stephen R. , Simon Carlos 
Published: September 2020

AbstractWe investigated potential SARS-CoV-2 tropism in human endometrium by single-cell RNA-sequencing of viral entry-associated genes in healthy women. Percentages of endometrial cells expressingACE2, TMPRSS2, CTSB, orCTSLwere <2%, 12%, 80%, and 80%, respectively, with 0.7% of cells expressing all four genes. Our findings imply low efficiency of SARS-CoV-2 infection in the endometrium before embryo implantation, providing information to assess preconception risk in asymptomatic carriers.
Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform
Authors: Freyman William A. , McManus Kimberly F. , Shringarpure Suyash S. , Jewett Ethan M. , Bryc Katarzyna ,   The 23 and Me Research Team, Auton Adam 
Published: September 2020

AbstractEstimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer (DTC) genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale datasets with millions of samples. Furthermore we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for non-commercial use in the code repositoryhttps://github.com/23andMe/phasedibd.
Ex vivotherapeutic base and prime editing using chemically derived hepatic progenitors in a mouse model of tyrosinemia type 1
Authors: Kim Yohan , Yu Jihyeon , Hong Sung-Ah , Eom Jeongyun , Jang Kiseok , Lee Seu-Na , Woo Jae-Sung , Jeong Jaemin , Bae Sangsu , Choi Dongho 
Published: September 2020

SummaryDNA base editors and prime editing technology capable of therapeutic base conversion enableex vivogene editing therapy for various genetic diseases. For such therapy, it is critical that the target cells survive well both outside the body and after transplantation. In this regard, chemically derived stem/progenitor cells are attracting attention as the most useful cell sources for clinical trials. Here, we generate chemically derived hepatic progenitors from the hereditary tyrosinemia type1 model mouse (HT1-mCdHs) and successfully correct the disease causing mutation using both adenosine base editors (ABEs) and prime editing tools. After transplantation into HT1 mice, ABE-corrected HT1-mCdHs repopulated the liver with fumarylacetoacetate hydrolase-positive cells and dramatically increased the survival rate of HT1 model mice, suggesting a safe and effectiveex vivogene editing therapy.