bluuebunny/crossref_metadata_2025_split huggingface dataset:
Failure to replicate the association of rare loss-of-function variants in type I IFN immunity genes with severe COVID-19
Authors: Povysil Gundula , Butler-Laporte Guillaume , Shang Ning , Weng Chen , Khan Atlas , Alaamery Manal , Nakanishi Tomoko , Zhou Sirui , Forgetta Vincenzo , Eveleigh Robert , Bourgey Mathieu , Aziz Naveed , Jones Steven , Knoppers Bartha , Scherer Stephen , Strug Lisa , Lepage Pierre , Ragoussis Jiannis , Bourque Guillaume , Alghamdi Jahad , Aljawini Nora , Albes Nour , Al-Afghani Hani M. , Alghamdi Bader , Almutair Mansour , Mahmoud Ebrahim Sabri , Safie Leen Abu , Bardisy Hadeel El , Harthi Fawz S. Al , Alshareef Abdulraheem , Suliman Bandar Ali , Alqahtani Saleh , AlMalik Abdulaziz , Alrashed May M. , Massadeh Salam , Mooser Vincent , Lathrop Mark , Arabi Yaseen , Mbarek Hamdi , Saad Chadi , Al-Muftah Wadha , Badji Radja , Thani Asma Al , Ismail Said I. , Gharavi Ali G. , Abedalthagafi Malak S. , Richards J Brent , Goldstein David B. , Kiryluk Krzysztof 
Published: December 2020

AbstractA recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,934 COVID-19 cases (713 with severe and 1,221 with mild disease) and 15,251 ancestry-matched population controls across four independent COVID-19 biobanks. We then tested if rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only one rare pLOF mutation across these genes amongst 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We find no evidence of association of rare loss-of-function variants in the proposed 13 candidate genes with severe COVID-19 outcomes.
Consensus based framework for digital mobility monitoring
Authors: Kluge Felix , Din Silvia Del , Cereatti Andrea , Gaßner Heiko , Hansen Clint , Helbostad Jorunn L , Klucken Jochen , Küderle Arne , Müller Arne , Rochester Lynn , Ullrich Martin , Eskofier Bjoern M , Mazzà Claudia ,   Mobilise-D consortium
Published: December 2020

AbstractDigital mobility assessment using wearable sensor systems has the potential to capture walking performance in a patient’s natural environment. It enables the monitoring of health status and disease progression and the evaluation of interventions in real-world situations. In contrast to laboratory settings, real-world walking occurs in non-conventional environments and under unconstrained and uncontrolled conditions. Despite the general understanding, there is a lack of agreed definitions about what constitutes real-world walking, impeding the comparison and interpretation of the acquired data across systems and studies. Hence, there is a need for a terminological framework guiding further implementation of digital measures for gait assessment. We used an objective methodology based on an adapted Delphi process to obtain consensus on specific terminology related to real-world walking by asking a diverse panel of clinical, scientific, and industrial stakeholders. Six constituents (‘real-world’, ‘walking’, ‘purposeful’, ‘walking bout’, ‘walking speed’, ‘turning’) have successfully been defined in two feedback rounds. The identification of a consented set of real-world walking definitions has important implications for the development of assessment and analysis protocols, as well as for the reporting and comparison of digital mobility outcomes across studies and systems. The definitions will serve as a common framework for implementing digital and mobile technologies for gait assessment.
SIGLEC1 (CD169): a marker of active neuroinflammation in the brain but not in the blood of MS patients
Authors: Ostendorf Lennard , Dittert Philipp , Biesen Robert , Duchow Ankelien , Stiglbauer Victoria , Ruprecht Klemens , Seelow Dominik , Niesner Raluca A. , Hauser Anja E. , Paul Friedemann , Radbruch Helena 
Published: December 2020

AbstractObjectiveWe aimed to evaluate SIGLEC1 (CD169) as a biomarker in Multiple Sclerosis (MS) and Neuromyelitis optica spectrum disorder (NMOSD) and to evaluate the specificity of SIGLEC1+ myeloid cells for demyelinating diseasesMethodsWe performed flow cytometry-based measurements of SIGLEC1 expression on monocytes in 86 MS patients, 41 NMOSD patients and 31 healthy controls. Additionally, we histologically evaluated the presence of SIGLEC1+ myeloid cells in acute and chronic MS brain lesions as well as other neurological diseases.ResultsWe found elevated SIGLEC1 expression in 16/86 (18.6%) MS patients and 4/41 (9.8%) NMOSD patients. Almost all MS patients with high SIGLEC1 levels received exogenous interferon beta as an immunomodulatory treatment and only a small fraction of MS patients without interferon treatment had increased SIGLEC1 expression. SIGLEC1+ myeloid cells were abundantly present in active MS lesions as well as in a range of acute infectious and malignant diseases of the central nervous system, but not chronic MS lesions.ConclusionIn our cohort, SIGLEC1 expression on monocytes was – apart from those patients receiving interferon treatment – not significantly increased in patients with MS and NMOSD, nor were levels associated with more severe disease. The presence of SIGLEC1+ myeloid cells in brain lesions could be used to investigate the activity in an inflammatory CNS lesion.
Signatures of Discriminative Copy Number Aberrations in 31 Cancer Subtypes
Authors: Gao Bo , Baudis Michael 
Published: December 2020

AbstractCopy number aberrations (CNA) are one of the most important classes of genomic mutations related to oncogenetic effects. In the past three decades, a vast amount of CNA data has been generated by molecular-cytogenetic and genome sequencing based methods. While this data has been instrumental in the identification of cancer-related genes and promoted research into the relation between CNA and histo-pathologically defined cancer types, the heterogeneity of source data and derived CNV profiles pose great challenges for data integration and comparative analysis. Furthermore, a majority of existing studies have been focused on the association of CNA to pre-selected “driver” genes with limited application to rare drivers and other genomic elements.In this study, we developed a bioinformatics pipeline to integrate a collection of 44,988 high-quality CNA profiles of high diversity. Using a hybrid model of neural networks and attention algorithm, we generated the CNA signatures of 31 cancer subtypes, depicting the uniqueness of their respective CNA landscapes. Finally, we constructed a multi-label classifier to identify the cancer type and the organ of origin from copy number profiling data. The investigation of the signatures suggested common patterns, not only of physiologically related cancer types but also of clinico-pathologically distant cancer types such as different cancers originating from the neural crest. Further experiments of classification models confirmed the effectiveness of the signatures in distinguishing different cancer types and demonstrated their potential in tumor classification.
Antibody-drug conjugates with dual payloads for combating breast tumor heterogeneity and drug resistance
Authors: Yamazaki Chisato M. , Yamaguchi Aiko , Anami Yasuaki , Xiong Wei , Otani Yoshihiro , Lee Jangsoon , Ueno Naoto T. , Zhang Ningyan , An Zhiqiang , Tsuchikama Kyoji 
Published: December 2020

ABSTRACTBreast tumors generally consist of a diverse population of cells with varying gene expression profiles. Breast tumor heterogeneity is a major factor contributing to drug resistance, recurrence, and metastasis after chemotherapy. Antibody-drug conjugates (ADCs) are emerging chemotherapeutic agents with striking clinical success, including T-DM1 for HER2-positive breast cancer. However, these ADCs often suffer from issues associated with intratumor heterogeneity. Here, we show that homogeneous ADCs containing two distinct payloads are a promising drug class for addressing this clinical challenge. Our conjugates show HER2-specific cell killing potency, desirable pharmacokinetic profiles, minimal immunogenicity, and marginal toxicity at therapeutic doses. Notably, a dual-drug ADC exerts greater treatment effect and survival benefit than does co-administration of two single-drug variants in a xenograft mouse model representing intratumor HER2 heterogeneity and elevated drug resistance. Our findings highlight the therapeutic potential of the dual-drug ADC format for treating refractory breast cancer and perhaps other cancers.
Inferring brain-wide interactions using data-constrained recurrent neural network models
Authors: Perich Matthew G. , Arlt Charlotte , Soares Sofia , Young Megan E. , Mosher Clayton P. , Minxha Juri , Carter Eugene , Rutishauser Ueli , Rudebeck Peter H. , Harvey Christopher D. , Rajan Kanaka 
Published: December 2020

ABSTRACTBehavior arises from the coordinated activity of numerous anatomically and functionally distinct brain regions. Modern experimental tools allow unprecedented access to large neural populations spanning many interacting regions brain-wide. Yet, understanding such large-scale datasets necessitates both scalable computational models to extract meaningful features of inter-region communication and principled theories to interpret those features. Here, we introduce Current-Based Decomposition (CURBD), an approach for inferring brain-wide interactions using data-constrained recurrent neural network models that directly reproduce experimentally-obtained neural data. CURBD leverages the functional interactions inferred by such models to reveal directional currents between multiple brain regions. We first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. We then apply CURBD to multi-region neural recordings obtained from mice during running, macaques during Pavlovian conditioning, and humans during memory retrieval to demonstrate the widespread applicability of CURBD to untangle brain-wide interactions underlying behavior from a variety of neural datasets.
Emergence and global spread ofListeria monocytogenesmain clinical clonal complex
Authors: Moura Alexandra , Lefrancq Noémie , Leclercq Alexandre , Wirth Thierry , Borges Vítor , Gilpin Brent , Dallman Timothy J. , Frey Joachim , Franz Eelco , Nielsen Eva M. , Thomas Juno , Pightling Arthur , Howden Benjamin P. , Tarr Cheryl L. , Gerner-Smidt Peter , Cauchemez Simon , Salje Henrik , Brisse Sylvain , Lecuit Marc ,   for the Listeria CC1 Study Group
Published: December 2020

AbstractRetracing microbial emergence and spread is essential to understanding the evolution and dynamics of pathogens. The bacterial foodborne pathogenListeria monocytogenesclonal complex 1 (Lm-CC1) is the most prevalent clonal group associated with listeriosis, and is strongly associated with cattle and dairy products. Here we analysed 2,021Lm-CC1 isolates collected from 40 countries, since the firstLmisolation to the present day, to define its evolutionary history and population dynamics. Our results suggest thatLm-CC1 spread worldwide from North America following the Industrial Revolution through two waves of expansion, coinciding with the transatlantic livestock trade in the second half of the 19thcentury and the rapid growth of cattle farming in the 20thcentury.Lm-CC1 then firmly established at a local level, with limited inter-country spread. This study provides an unprecedented insight intoLm-CC1 phylogeography and dynamics and can contribute to effective disease surveillance to reduce the burden of listeriosis.
Glycan remodeled erythrocytes facilitate antigenic characterization of recent A/H3N2 influenza viruses
Authors: Broszeit Frederik , van Beek Rosanne J. , Unione Luca , Bestebroer Theo M. , Chapla Digantkumar , Yang Jeong-Yeh , Moremen Kelley W. , Herfst Sander , Fouchier Ron A.M. , de Vries Robert P. , Boons Geert-Jan 
Published: December 2020

AbstractDuring circulation in humans and natural selection to escape antibody recognition for decades, A/H3N2 influenza viruses emerged with altered receptor specificities. These viruses lost the ability to agglutinate erythrocytes critical for antigenic characterization and give low yields and acquire adaptive mutations when cultured in eggs and cells, contributing to recent vaccine challenges. We examined receptor specificities of A/H3N2 viruses, revealing that recent viruses compensated for decreased binding of the prototypic human receptor by recognizing 2,6-sialosides on extended LacNAc moieties. Erythrocyte glycomics showed an absence of extended glycans, providing a rationale for lack of agglutination by recent A/H3N2 viruses. A glycan remodeling approach installed functional receptors on erythrocytes, allowing antigenic characterization of recent A/H3N2 viruses and confirming the cocirculation of several antigenically different viruses in humans. Computational studies of HAs in complex with a sialoside having an extended LacNAc moiety revealed that mutations distal to the RBD reoriented the Y159 side chain, resulting in an extended receptor binding site.
Multi-color fluorescence fluctuation spectroscopy in living cells via spectral detection
Authors: Dunsing Valentin , Petrich Annett , Chiantia Salvatore 
Published: December 2020

AbstractSignaling pathways in biological systems rely on specific interactions between multiple biomolecules. Fluorescence fluctuation spectroscopy provides a powerful toolbox to quantify such interactions directly in living cells. Cross-correlation analysis of spectrally separated fluctuations provides information about inter-molecular interactions but is usually limited to two fluorophore species. Here, we present scanning fluorescence spectral correlation spectroscopy (SFSCS), a versatile approach that can be implemented on commercial confocal microscopes, allowing the investigation of interactions between multiple protein species at the plasma membrane. We demonstrate that SFSCS enables cross-talk-free cross-correlation, diffusion and oligomerization analysis of up to four protein species labeled with strongly overlapping fluorophores. As an example, we investigate the interactions of influenza A virus (IAV) matrix protein 2 with two cellular host factors simultaneously. We furthermore apply raster spectral image correlation spectroscopy for the simultaneous analysis of up to four species and determine the stoichiometry of ternary IAV polymerase complexes in the cell nucleus.
Compressed sensing-based super-resolution ultrasound imaging for faster acquisition and high quality images
Authors: Kim Jihun , Wang Qingfei , Zhang Siyuan , Yoon Sangpil 
Published: December 2020

AbstractSuper-resolution ultrasound (SRUS) imaging technique has overcome the diffraction limit of conventional ultrasound imaging, resulting in an improved spatial resolution while preserving imaging depth. Typical SRUS images are reconstructed by localizing ultrasound microbubbles (MBs) injected in a vessel using normalized 2-dimensional cross-correlation (2DCC) between MBs signals and the point spread function of the system. However, current techniques require isolated MBs in a confined area due to inaccurate localization of densely populated MBs. To overcome this limitation, we developed the ℓ1-homotopy based compressed sensing (L1H-CS) based SRUS imaging technique which localizes densely populated MBs to visualize microvasculature in vivo. To evaluate the performance of L1H-CS, we compared the performance of 2DCC, interior-point method based compressed sensing (CVX-CS), and L1H-CS algorithms. Localization efficiency was compared using axially and laterally aligned point targets (PTs) with known distances and randomly distributed PTs generated by simulation. We developed post-processing techniques including clutter reduction, noise equalization, motion compensation, and spatiotemporal noise filtering for in vivo imaging. We then validated the capabilities of L1H-CS based SRUS imaging technique with high-density MBs in a mouse tumor model, kidney, and zebrafish dorsal trunk, and brain. Compared to 2DCC, and CVX-CS algorithm, L1H-CS algorithm, considerable improvement in SRUS image quality and data acquisition time was achieved. These results demonstrate that the L1H-CS based SRUS imaging technique has the potential to examine the microvasculature with reduced acquisition and reconstruction time of SRUS image with enhanced image quality, which may be necessary to translate it into the clinics.
assayM: a web application to monitor mutations in COVID-19 diagnostic assays
Authors: Naeem Raeece , Pain Arnab 
Published: December 2020

AbstractSummaryReverse Transcriptase – Polymerase Chain Reaction (RT-PCR) is the gold standard as diagnostic assays for the detection of COVID-19 and the specificity and sensitivity of these assays depend on the complementarity of the RT-PCR primers to the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the virus mutates over time during replication cycles, there is an urgent need to continuously monitor the virus genome for appearances of mutations and mismatches in the PCR primers used in these assays. Here we present assayM, a web application to explore and monitor mutations introduced in the primer and probe sequences published by the World Health Organisation (WHO) or in any custom-designed assay primers for SARS-CoV-2 detection assays in globally available SARS-CoV-2 genome datasets.Availability and implementationassayM is available onhttps://grafnet.kaust.edu.sa/assayMas a web application and also as an open-source R shiny application, downloadable fromhttps://github.com/raeece/assayMContactarnab.pain@kaust.edu.sa
Learning a non-neutral conditioned stimulus: place preference in the crabNeohelice granulata
Authors: Klappenbach Martín , Medina Candela , Freudenthal Ramiro 
Published: December 2020

AbstractIn the wild, being able to recognize and remember specific locations related to food sources and the associated attributes of landmarks is a cognitive trait important for survival. In the present work we show that the crab Neohelice granulata can be trained to associate a specific environment with an appetitive reward in a conditioned place preference task. After a single training trial, when the crabs were presented with a food pellet in the target quadrant of the training arena, they were able to form a long-term memory related to the event. This memory was evident at least 24 h after training and was protein-synthesis dependent. Importantly, the target area of the arena proved to be a non-neutral environment, given that animals initially avoided the target quadrant. In the present work we introduce for the first time an associative one-trial memory paradigm including a conditioned stimulus with a clear valence performed in a crustacean.
Analysis of PPI networks of transcriptomic expression identifies hub genes associated with Newcastle disease virus persistent infection in bladder cancer
Authors: Ahmad Umar , Chau De Ming , Chia Suet Lin , Yusoff Khatijah , Abdullah Syahril , Chan Soon Choy , Veerakumarasivam Abhi 
Published: December 2020

AbstractMotivationBladder cancer cells acquire persistent infection associated with oncolytic Newcastle disease virus (NDV) in which its molecular events are still unclear. This poses a potential problem for oncolytic virus application for cancer therapy. To unravel the molecular mechanism underlying the development of NDV persistent infection in bladder cancer, we used mRNA expression profile of the persistently infected bladder cancer cells to construct PPI network.ResultsBased on path and module exploring in the PPI network, the bridges were found mainly from pathways of p53 signalling, ECM-receptor interaction, and TGF-beta signalling by the upregulated mRNAs, to the antigen processing and presentation, protein processing in endoplasmic reticulum, completement and coagulation cascades by the downregulated mRNAs in NDV persistent TCCSUPPi cells. In persistent EJ28Pi cells comparatively, connections were identified mainly from pathways of renal carcinoma, viral carcinogenesis, Ras signalling and cell cycle by the upregulated mRNAs, to the Wnt signalling, HTLV-I infection and pathways in cancer by the downregulated mRNAs. This connection was mainly dependent on ofRPL8- HSPA1A/HSPA4in TCCSUPPi cells andEP300, PTPN11, RAC1-TP53, SP1, CCND1andXPO1in EJ28Pi cells. Oncomine validation showed that the top hub genes identified in the network that includesRPL8, THBS1, F2from TCCSUPPi andTP53andRAC1from EJ28Pi are involved in the development and progression of bladder cancer. Protein-drug interaction network, have identified several drugs targets that could be used to disconnect the linkages between modules and prevent bladder cancer cells from acquiring NDV persistent infection. This is the first time reporting the PPI network analysis of differentially expressed mRNAs of the NDV persistently infected bladder cancer cell lines which provide an insight into screening drugs that could be used together with NDV to manage bladder cancer resistance to therapy and progression.
Evidence for distinct genetic and environmental influences on fear acquisition and extinction
Authors: Purves K. L. , Krebs G. , McGregor T. , Constantinou E. , Lester K.J. , Barry T.J. , Craske M.G. , Young K. S. , Breen G. , Eley T. C. 
Published: December 2020

AbstractBackgroundAnxiety disorders are highly prevalent with an early age of onset. Understanding the aetiology of disorder emergence and recovery is important for establishing preventative measures and optimising treatment. Experimental approaches can serve as a useful model for disorder and recovery relevant processes. One such model is fear conditioning. We conducted a remote fear conditioning paradigm in monozygotic and dizygotic twins to determine the degree and extent of overlap between genetic and environmental influences on fear acquisition and extinction.Methods1937 twins aged 22-25 years, including 538 complete pairs from the Twins Early Development Study (TEDS) took part in a fear conditioning experiment delivered remotely via the Fear Learning and Anxiety Response (FLARe) smartphone app.In the fear acquisition phase participants were exposed to two neutral shape stimuli, one of which was repeatedly paired with a loud aversive noise, while the other was never paired with anything aversive. In the extinction phase the shapes were repeatedly presented again, this time without the aversive noise. Outcomes were participant ratings of how much they expected the aversive noise to occur when they saw either shape, throughout each phase.ResultsTwin analyses indicated a significant contribution of genetic effects to the initial acquisition and consolidation of fear, and the extinction of fear (15%, 30% and 15% respectively) with the remainder of variance due to the non-shared environment. Multivariate analyses revealed that the development of fear and fear extinction show moderate genetic overlap (genetic correlations .4-.5).ConclusionsFear acquisition and extinction are heritable, and share some, but not all of the same genetic influences.