bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional modules from variable genes: Leveraging percolation to analyze noisy, high-dimensional data
Authors: Werner Steffen , Rozemuller W Mathijs , Ebbing Annabel , Alemany Anna , Traets Joleen , van Zon Jeroen S. , van Oudenaarden Alexander , Korswagen Hendrik C. , Stephens Greg J. , Shimizu Thomas S. 
Published: June 2020

While measurement advances now allow extensive surveys of gene activity (large numbers of genes across many samples), interpretation of these data is often confounded by noise — expression counts can differ strongly across samples due to variation of both biological and experimental origin. Complimentary to perturbation approaches, we extract functionally related groups of genes by analyzing the standing variation within a sampled population. To distinguish biologically meaningful patterns from uninterpretable noise, we focus on correlated variation and develop a novel density-based clustering approach that takes advantage of a percolation transition generically arising in random, uncorrelated data. We apply our approach to two contrasting RNA sequencing data sets that sample individual variation — across single cells of fission yeast and whole animals ofC. elegansworms — and demonstrate robust applicability and versatility in revealing correlated gene clusters of diverse biological origin, including cell cycle phase, development/reproduction, tissue-specific functions, and feeding history. Our technique exploits generic features of noisy high-dimensional data and is applicable, beyond gene expression, to feature-rich data that sample population-level variability in the presence of noise.Significance StatementGene expression largely determines the fate of each cell and ultimately the development and behavior of the whole organism. Whereas most of our knowledge on gene regulatory networks has been obtained from perturbation experiments (e.g. manipulating environmental conditions, genotype, or other physiological variables), here we develop an alternative approach based on the analysis of naturally occurring variations across individuals within a population. Using both single-cell and whole-animal RNA sequencing data, we demonstrate how a rich set of co-regulated gene modules can be uncovered from transcriptomic variability of individuals within unperturbed populations. To robustly extract interpretable clusters from the strong noise background, we devise a novel, versatile clustering approach based on network theory. With a foundation in the generic behavior of random networks near their percolation critical point, our method is broadly applicable, beyond gene expression, to any noisy, high-dimensional data that sample variation across individuals within a population.
FASTQuick: Rapid and comprehensive quality assessment of raw sequence reads
Authors: Zhang Fan , Kang Hyun Min 
Published: June 2020

AbstractBackgroundRapid and thorough quality assessment of sequenced genomes in an ultra-high-throughput scale is crucial for successful large-scale genomic studies. Comprehensive quality assessment typically requires full genome alignment, which costs a significant amount of computational resources and turnaround time. Existing tools are either computational expensive due to full alignment or lacking essential quality metrics by skipping read alignment.FindingsWe developed a set of rapid and accurate methods to produce comprehensive quality metrics directly from raw sequence reads without full genome alignment. Our methods offer orders of magnitude faster turnaround time than existing full alignment-based methods while providing comprehensive and sophisticated quality metrics, including estimates of genetic ancestry and contamination.ConclusionsBy rapidly and comprehensively performing the quality assessment, our tool will help investigators detect potential issues in ultra-high-throughput sequence reads in real-time within a low computational cost, ensuring high-quality downstream analysis and preventing unexpected loss in time, money, and invaluable specimens.
Anticipation of ventricular tachyarrhythmias by a novel mathematical method: Further insights towards an early warning system in implantable cardioverter defibrillators
Authors: Zamudio Gabriel S. , Márquez Manlio F. , José Marco V. 
Published: June 2020

AbstractBackgroundImplantable cardioverter defibrillators (ICD) are the most effective therapy to terminate malignant ventricular arrhythmias (VA) and therefore to prevent sudden cardiac death. Until today, there is no way to predict the onset of such VA. Our aim was to develop a mathematical model that could predict VA in a timely fashion.MethodsWe analyzed the time series of R-R intervals from 3 groups. Two groups from the Spontaneous Ventricular Tachyarrhythmia Database (v 1.0) were analyzed from a set of 81 pairs of R-R interval time series records from patients, each pair containing one record before the VT episode (Dataset 1A) and one control record which was obtained during the follow up visit (Dataset 1B). A third data set was composed of the RR interval time series of 54 subjects without a significant arrhythmia heart disease (Dataset 2). We developed a new method to transform a time series into a network for its analysis, theε−regular graphs. This novel approach transforms a time series into a network which is sensitive to the quantitative properties of the time series, it has a single parameter (ε) to be adjusted, and it can trace long-range correlations. This procedure allows to use graph theory to extract the dynamics of any time series.ResultsThe average of the difference between the VT and the control record graph degree of each patient, at each time window, reached a global minimum value of −2.12 followed by a drastic increase of the average graph until reaching a local maximum of 5.59. The global minimum and the following local maxima occur at the windows 276 and 393, respectively. This change in the connectivity of the graphs distinguishes two distinct dynamics occurring during the VA, while the states in between the 276 and 393, determine a transitional state. We propose this change in the dynamic of the R-R intervals as a measurable and detectable “early warning” of the VT event, occurring an average of 514.625 seconds (8 : 30 minutes) before the onset of the VT episode.ConclusionsIt is feasible to detect retrospectively early warnings of the VA episode using their correspondingε−regular graphs, with an average of 8 : 30 minutes before the ICD terminates the VA event.
Age-dependent progression of SARS-CoV-2 infection in Syrian hamsters
Authors: Osterrieder Nikolaus , Bertzbach Luca D. , Dietert Kristina , Abdelgawad Azza , Vladimirova Daria , Kunec Dusan , Hoffmann Donata , Beer Martin , Gruber Achim D. , Trimpert Jakob 
Published: June 2020

AbstractIn late 2019, an outbreak of a severe respiratory disease caused by an emerging coronavirus, SARS-CoV-2, resulted in high morbidity and mortality in infected humans1. Complete understanding of COVID-19, the multi-faceted disease caused by SARS-CoV-2, requires suitable small animal models, as does the development and evaluation of vaccines and antivirals2. Because age-dependent differences of COVID-19 were identified in humans3, we compared the course of SARS-CoV-2 infection in young and aged Syrian hamsters. We show that virus replication in the upper and lower respiratory tract was independent of the age of the animals. However, older hamsters exhibited more pronounced and consistent weight loss.In situhybridization in the lungs identified viral RNA in bronchial epithelium, alveolar epithelial cells type I and II, and macrophages. Histopathology revealed clear age-dependent differences, with young hamsters launching earlier and stronger immune cell influx than aged hamsters. The latter developed conspicuous alveolar and perivascular edema, indicating vascular leakage. In contrast, we observed rapid lung recovery at day 14 after infection only in young hamsters. We propose that comparative assessment in young versus aged hamsters of SARS-CoV-2 vaccines and treatments may yield valuable information as this small-animal model appears to mirror age-dependent differences in human patients.
A steady-state algebraic model for the time course of covalent enzyme inhibition
Authors: Kuzmič Petr 
Published: June 2020

AbstractThis report describes a double-exponential algebraic equation for the time course of irreversible enzyme inhibition following the two-step mechanismE+I⇌E·I→EI, under the steady-state approximation. Under the previously invoked rapid-equilibrium approximation [Kitz & Wilson (1962)J. Biol. Chem.237, 3245] it was assumed that the rate constant for the reversible dissociation of the initial noncovalent complex is very much faster than the rate constant for the irreversible inactivation step. The steady-state algebraic equation reported here removes any restrictions on the relative magnitude of microscopic rate constants. The resulting formula was used in heuristic simulations designed to test the performance of the standard rapid-equilibrium kinetic model. The results show that if the inactivation rate constant is significantly higher than the dissociation rate constant, the conventional “kobs” method is incapable of correctly distinguishing between the two-step inhibition mechanism and a simpler one-step variant,E+I→EI, even for inhibitors that have very high binding affinity in the reversible noncovalent step.
Discovery of a molecular glue promoting CDK12-DDB1 interaction to trigger Cyclin K degradation
Authors: Lv Lu , Chen Peihao , Cao Longzhi , Li Yamei , Zeng Zhi , Cui Yue , Wu Qingcui , Li Jiaojiao , Wang Jian-Hua , Dong Meng-Qiu , Qi Xiangbing , Han Ting 
Published: June 2020

AbstractMolecular glues are small molecules that exert their biologic or therapeutic activities by inducing gain-of-function interactions between pairs of proteins. In particular, molecular-glue degraders, which mediate interactions between target proteins and components of the ubiquitin proteasome system to cause targeted protein degradation, hold great promise as a unique modality for therapeutic targeting of proteins that are currently intractable. Here, we report a new molecular glue HQ461 discovered by high-throughput screening of small molecules that inhibited NRF2 activity. Using unbiased loss-of-function and gain-of-function genetic screening followed by biochemical reconstitution, we show that HQ461 acts by promoting interaction between CDK12 and DDB1-CUL4-RBX1 E3 ubiquitin ligase, leading to polyubiquitination and proteasomal degradation of CDK12’s interacting protein Cyclin K (CCNK). Degradation of CCNK mediated by HQ461 compromised CDK12 function, leading to reduced phosphorylation of CDK12 substrate, downregulation of DNA damage response genes, and cell death. Structure-activity relationship analysis of HQ461 revealed the importance of a 5-methylthiazol-2-amine pharmacophore and resulted in an HQ461 derivate with improved potency. Our studies reveal a new molecular glue that engages its target protein directly with DDB1 to bypass the requirement of a substrate-specific receptor, presenting a new strategy for targeted protein degradation.
Human Whole Genome Sequencing in South Africa
Authors: Glanzmann Brigitte , Jooste Tracey , Ghoor Samira , Gordon Richard , Mia Rizwana , Mao Jun , Li Hao , Charls Patrick , Douman Craig , Kotze Maritha J. , Peeters Armand V. , Loots Glaudina , Esser Monika , Tiemessen Caroline T. , Wilkinson Robert J , Louw Johan , Gray Glenda , Warren Robin M. , Möller Marlo , Kinnear Craig 
Published: June 2020

ABSTRACTThe advent and evolution of next generation sequencing has considerably impacted genomic research. Until recently, South African researchers were unable to access affordable platforms capable of human whole genome sequencing locally and DNA samples had to be exported. Here we report the whole genome sequences of the first six human DNA samples sequenced and analysed at the South African Medical Research Council’s Genomics Centre. We demonstrate that the data obtained is of high quality, with an average sequencing depth of 36.41, and that the output is comparable to data generated internationally on a similar platform. The Genomics Centre creates an environment where African researchers are able to access world class facilities, increasing local capacity to sequence whole genomes as well as store and analyse the data.
Single nuclei chromatin profiling of ventral midbrain reveals cell identity transcription factors and cell type-specific gene regulatory variation
Authors: Gui Yujuan , Grzyb Kamil , Thomas Mélanie H. , Ohnmacht Jochen , Garcia Pierre , Buttini Manuel , Skupin Alexander , Sauter Thomas , Sinkkonen Lasse 
Published: June 2020

ABSTRACTCell types in ventral midbrain are involved in diseases with variable genetic susceptibility such as Parkinson’s disease and schizophrenia. Many genetic variants affect regulatory regions and alter gene expression. We report 20 658 single nuclei chromatin accessibility profiles of ventral midbrain from two genetically and phenotypically distinct mouse strains. We distinguish ten cell types based on chromatin profiles and analysis of accessible regions controlling cell identity genes highlights cell type-specific key transcription factors. Regulatory variation segregating the mouse strains manifests more on transcriptome than chromatin level. However, cell type-level data reveals changes not captured at tissue level. To discover the scope and cell-type specificity ofcis-acting variation in midbrain gene expression, we identify putative regulatory variants and show them to be enriched at differentially expressed loci. Finally, we find TCF7L2 to mediatetrans-acting variation selectively in midbrain neurons. Our dataset provides an extensive resource to study gene regulation in mesencephalon.
Relating Bone Strain to Local Changes in Radius Microstructure Following 12 Months of Axial Forearm Loading in Women
Authors: Mancuso Megan E. , Troy Karen L. 
Published: June 2020

ABSTRACTWork in animal models suggest that bone structure adapts to local bone strain, but this relationship has not been comprehensively studied in humans. Here, we quantified the influence of strain magnitude and gradient on bone adaptation in the forearm of premenopausal women performing compressive forearm loading (n=11) and non-loading controls (n=10). High resolution peripheral quantitative computed tomography (HRpQCT) scans of the distal radius acquired at baseline and 12 months of a randomized controlled experiment were used to identify local sites of bone formation and resorption. Bone strain was estimated using validated finite element (FE) models. Trabecular strain magnitude and gradient were higher near (within 200 µm) formation versus resorption (p<0.05). Trabecular formation and resorption occurred preferentially near very high (>95th percentile) versus low (<5th percentile) strain magnitude and gradient elements, and very low strain elements were more likely to be near resorption than formation (p<0.05). In the cortical compartment, strain gradient was higher near formation versus resorption (p<0.05), and both formation and resorption occurred preferentially near very high versus low strain gradient elements (p<0.05). At most, 54% of very high and low strain elements were near formation or resorption only, and similar trends were observed in the control and load groups. These findings suggest that strain, likely in combination with other physiological factors, influences adaptation under normal loads and in response to a novel loading intervention, and represents an important step toward defining exercise interventions to maximize bone strength.
Assessment of metagenomic sequencing and qPCR for detection of influenza D virus in bovine respiratory tract samples
Authors: Zhang Maodong , Huang Yanyun , Godson Dale L. , Fernando Champika , Alexander Trevor W. , Hill Janet E. 
Published: June 2020

AbstractHigh throughput sequencing is currently revolutionizing the genomics field and providing new approaches to the detection and characterization of microorganisms. The objective of this study was to assess the detection of influenza D virus (IDV) in bovine respiratory tract samples using two sequencing platforms (MiSeq and Nanopore (GridION)), and species-specific qPCR. An IDV-specific qPCR was performed on 232 samples (116 nasal swabs and 116 tracheal washes) that had been previously subject to virome sequencing using MiSeq. Nanopore sequencing was performed on 19 samples positive for IDV by either MiSeq or qPCR. Nanopore sequence data was analyzed by two bioinformatics methods: What’s In My Pot (WIMP, on the EPI2ME platform), and an in-house developed analysis pipeline. The agreement of IDV detection between qPCR and MiSeq was 82.3%, between qPCR and Nanopore was 57.9% (in-house) and 84.2% (WIMP), and between MiSeq and Nanopore was 89.5% (in-house) and 73.7% (WIMP). IDV was detected by MiSeq in 14 of 17 IDV qPCR-positive samples with Cq (cycle quantification) values below 31, despite multiplexing 50 samples for sequencing. When qPCR was regarded as the gold standard, the sensitivity and specificity of MiSeq sequence detection were 28.3% and 98.9%, respectively. We conclude that both MiSeq and Nanopore sequencing are capable of detecting IDV in clinical specimens with a range of Cq values. Sensitivity may be further improved by optimizing sequence data analysis, improving virus enrichment, or reducing the degree of multiplexing.
Knowledge, attitudes, and practices among the general population during COVID-19 outbreak in Iran: A national cross-sectional survey
Authors: Kakemam Edris , Ghoddoosi-Nejad Djavad , Chegini Zahra , Momeni Khalil , Salehinia Hamid , Hassanipour Soheil , Ameri Hosein , Arab-Zozani Morteza 
Published: June 2020

AbstractBackgroundCOVID-19, which emerged in December 2019, is the largest pandemic ever to occur. During the early phase, little was known about public awareness relating to Coronavirus disease. This study was designed to determine knowledge, attitudes and practices (KAP) among the Iranian public towards COVID-19.MethodsA cross-sectional online survey was carried out in Iran from 2 March to 8 April 2020 using a self-administered questionnaire on 1,480 people. COVID-19-related KAP questions were adapted from other internationally validated questionnaires specific to infectious diseases.ResultsAll participants were aware of COVID-19. When asked unprompted, 80% of respondents could correctly cite fever, difficulty breathing and cough as signs/symptoms of COVID-19. Most of our sample population knew that by staying at home and staying isolated (95.3%, 95 % CI: 94.2-96.3) as well as constant hand washing and using disinfectants (92.5%, 95 % CI: 91.1-93.8) could prevent COVID-19. However, there was also widespread misconceptions such as the belief that COVID-19 can be transmitted by wild animals (58%, 95 % CI: 55.5-60.5) and by air (48.3%, 95 % CI: 45.7-50.8). Unprompted, self-reported actions taken to avoid COVID-19 infection included hand washing with soap and water (95.4%, 95 % CI: 94.3-96.4), avoiding crowded places (93%, 95 % CI: 91.7-94.3), cleaning hands with other disinfectants (80.9 %, 95 % CI: 78.9-82.9), and covering mouths and noses when coughing and sneezing (76.1 %, 95 % CI: 73.9-78.2). The internet and social media (94.5%, 95 % CI: 93.3-95.6) were the main Coronavirus information sources. However, the most trusted information sources on Coronavirus were health and medical professionals (79.3%, 95 % CI: 77.2-81.3). The majority of participants (77.0%, 95 % CI: 74.8-79.1) wanted more information about Coronavirus to be available.ConclusionOur findings suggest that people’s knowledge and attitude towards COVID-19 at the time of its outbreak was of a high level. Therefore, health systems should use multiple ways, such as mass media, phone applications, electronic, print, and tele-education to increase KAP related to COVID-19.
Intangibles and innovation-labor-biased technical change
Authors: Piekkola Hannu 
Published: June 2020

PurposeThis paper analyzes the productivity effects of structural capital such as research and development (R&D) and organizational capital (OC). Innovation work also produces innovation-labor-biased technical change (IBTC) and knowledge spillovers. Analyses use full register-based dataset of Finnish firms for the period 1994–2014 from Statistics Finland.Design/methodology/approachIntangibles are derived from the labor costs of innovation-type occupations using linked employer-employee data. The approach is consistent with National Accounting and offered as one method in OECD (2010) and applied in statistical offices, e.g. in measuring software. The EU 7th framework Innodrive project 2008–2011 extended this method to cover R&D and OC.FindingsMethodology is implementable at firm-level and offers way to link personnel reporting to intangible assets. The OC-IBTC as well as total resources allocated to OC are relevant for productivity growth. The R&D stock is relatively higher but R&D-IBTC is smaller than OC-IBTC. Public policy should, besides technology policy, account for OC and OC-IBTC and related knowledge spillovers in the industries that are most important among the SMEs (low market-share-firms).Research limitations/implicationsThe data are based on remote access to Statistics Finland; the data cannot be disseminated.Originality/valueIntangible assets are measured from innovation work that encompasses not only R&D work. IBTC is proxied in production function estimation by relative compensations on IA work. The non-competing nature of IAs is captured by IA knowledge spillovers. The sample sizes are much higher than in earlier studies on horizontal knowledge spillovers (such as for SMEs,) thus bringing additional generality to the results.
Interdependency in coordinating networked maintenance and modification operations
Authors: Engelseth Per , Törnroos Jan-Åke , Zhang Yufeng 
Published: June 2020

PurposeThe purpose of this research is to detect, through applying a process-based view, how to manage economisation of the maintenance and modification operations in offshore petroleum logistics operations.Design/methodology/approachA single case study of engineering services, more specifically, maintenance and modification service operations, on a Norwegian Sea oil platform reveals the dynamics of building network capabilities in a consistent network structure. Two layers of coordination are studied: the engineering process and its context, represented by its network of interconnected firms. This case study empirically grounds how engineering service involves managing reciprocally interdependent exchange processes in the network structure.FindingsPooled interdependencies are vital in understanding the nature of service provision and use, and sequential interdependencies are vital in narrating the timing of processes to reveal the nature of process emergence to coordinate strings of production events. Furthermore, the network structure, when characterised by multiple interdependent projects, is also dynamic but at a slower pace.Originality/valueThrough the case study, operations management is revealed to be associated with project emergence at two levels: the core process level regarding daily continuous change, including the changing interaction of multiple different and interdependent projects, and the contextual level, where features of interdependency and integration change, affecting engineering service production. This provides guidance as to the economisation of engineering services. They change not only interactions in the flow of production but also its context.