bluuebunny/crossref_metadata_2025_split huggingface dataset:
Routine laboratory blood tests predict SARS-CoV-2 infection using machine learning
Authors: Yang He S. , Hou Yu , Vasovic Ljiljana V. , Steel Peter , Chadburn Amy , Racine-Brzostek Sabrina E. , Velu Priya , Cushing Melissa M. , Loda Massimo , Kaushal Rainu , Zhao Zhen , Wang Fei 
Published: June 2020

AbstractBackgroundAccurate diagnostic strategies to rapidly identify SARS-CoV-2 positive individuals for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PCR from nasopharyngeal swabs specimens, however the results are not promptly obtainable in all patient care locations. Routine laboratory testing, in contrast, is readily available with a turn-around time (TAT) usually within 1-2 hours.MethodWe developed a machine learning model incorporating patient demographic features (age, sex, race) with 27 routine laboratory tests to predict an individual’s SARS-CoV-2 infection status. Laboratory test results obtained within two days before the release of SARS-CoV-2-RT-PCR result were used to train a gradient boosted decision tree (GBDT) model from 3,356 SARS-CoV-2 RT-PCR tested patients (1,402 positive and 1,954 negative) evaluated at a metropolitan hospital.ResultsThe model achieved an area under the receiver operating characteristic curve (AUC) of 0.854 (95% CI: 0.829-0.878). Application of this model to an independent patient dataset from a separate hospital resulted in a comparable AUC (0.838), validating the generalization of its use. Moreover, our model predicted initial SARS-CoV-2 RT-PCR positivity in 66% individuals whose RT-PCR result changed from negative to positive within two days.ConclusionThis model employing routine laboratory test results offers opportunities for early and rapid identification of high-risk SARS-CoV-2 infected patients before their RT-PCR results are available. It may play an important role in assisting the identification of SARS-COV-2 infected patients in areas where RT-PCR testing is not accessible due to financial or supply constraints.
Higher risk of COVID-19 hospitalization for unemployed: an analysis of 1,298,416 health insured individuals in Germany
Authors: Dragano Nico , Rupprecht Christoph J. , Dortmann Olga , Scheider Maria , Wahrendorf Morten 
Published: June 2020

AbstractBackgroundPrevious research on infectious disease has revealed that infection risk as well as the severity of diseases is related to income and poverty. In this study we investigate if unemployed persons have a higher risk to become hospitalized with a COVID-19 diagnosis compared with employed persons.MethodsWe used routine data on hospitalizations in a study population of 1,298,416persons between the ages 18 and 65 who were enrolled in a German health insurance and who were active on the labour market (either employed or unemployed). Hospital diagnosis of COVID-19 (ICD-10-GM U07.1 and U07.2) were reported on a daily basis from 01.01.2020 to 04.06.2020. We studied if the rate of persons hospitalized with a COVID-19 diagnoses differed by employment situation. Logistic regression models comparing employed with short- and long-term unemployed were calculated adjusting for age and sex.ResultsIn total, we observed 1,311 persons who were hospitalized, corresponding to a rate of 100.98 cases per 100.000 in our study population. Rates varied between the groups in different employment situations with lowest rates for employed and highest for long-term unemployed. Odds ratio for a hospitalization was 1.84 (1.64 - 2.07) for long-term and 1.18 (0.75 - 1.85) for short-term unemployed compared with employed persons.ConclusionThe results are in line with earlier (mainly ecological) studies from the USA and Great Britain which found social inequalities in hospitalization risk. The fact that differences exist in Germany, a country with a universal health care system, indicates socioeconomic differences in the COVID-19 pandemic exists across countries.
Genetic architecture of four smoking behaviors using partitioned h2SNP
Authors: Evans Luke M. , Jang Seonkyeong , Ehringer Marissa A. , Otto Jacqueline M. , Vrieze Scott I. , Keller Matthew C. 
Published: June 2020

AbstractBackground and AimsSmoking is a leading cause of premature death. Although genome-wide association studies have identified many loci that influence smoking behaviors, much of the genetic variance in these traits remains unexplained. We sought to characterize the genetic architecture of four smoking behaviors through SNP-based heritability (h2SNP) analyses.DesignWe applied recently-developed partitioned h2SNP approaches to smoking behavior traits assessed in the UK Biobank.SettingUK Biobank.ParticipantsUK Biobank participants of European ancestry. The number of participants varied depending on the trait, from 54,792 to 323,068.MeasurementsSmoking initiation, age of initiation, cigarettes per day (CPD; count, log-transformed, binned, and dichotomized into heavy versus light), and smoking cessation. Imputed genome-wide SNPs.FindingsWe estimated h2SNP(SE)=0.18(0.01) for smoking initiation and 0.12(0.02) for smoking cessation, which were more than twice the previously reported estimates. Estimated age of initiation h2SNP=0.05(0.01) and binned CPD h2SNP=0.1(0.01) were similar to previous reports. These estimates remained substantially below published twin-based h2 of roughly 50%. CPD encoding strongly influenced estimates, with dichotomized CPD h2SNP=0.28. We found significant contributions of low-frequency variants and variants in low linkage-disequilibrium (LD) with surrounding genomic regions. Functional annotations related to LD, allele frequency, sequence conservation, and selective constraint also contributed significantly to the partitioned heritability. We found no evidence of dominance genetic variance for any trait.Conclusionh2SNP of these four specific smoking behaviors is modest overall. The patterns of partitioned h2SNP for these highly polygenic traits is consistent with negative selection. We found a predominant contribution of common variants, and our results suggest a role of low-frequency or rare variants, poorly tagged by surrounding regions. Deep sequencing of large samples and/or improved imputation will be required to fully assess the role of rare variants.
Anti-phospholipid antibodies in COVID-19 are different from those detectable in the anti-phospholipid syndrome
Authors: Borghi Maria Orietta , Beltagy Asmaa , Garrafa Emirena , Curreli Daniele , Cecchini Germana , Bodio Caterina , Grossi Claudia , Blengino Simonetta , Tincani Angela , Franceschini Franco , Andreoli Laura , Lazzaroni Maria Grazia , Piantoni Silvia , Masneri Stefania , Crisafulli Francesca , Brugnoni Duilio , Muiesan Maria Lorenza , Salvetti Massimo , Parati Gianfranco , Torresani Erminio , Mahler Michael , Heilbron Francesca , Pregnolato Francesca , Pengo Martino , Tedesco Francesco , Pozzi Nicola , Meroni Pier Luigi 
Published: June 2020

AbstractBackgroundCritically ill patients with coronavirus disease 2019 (COVID-19) have a profound hypercoagulable state and often develop coagulopathy which leads to organ failure and death. Because of a prolonged activated partial-thromboplastin time (aPTT), a relationship with anti-phospholipid antibodies (aPL) has been proposed, but results are controversial. Functional assays for aPL (i.e., lupus anticoagulant) can be influenced by concomitant anticoagulation and/or high levels of C reactive protein. The presence of anti-cardiolipin (aCL), anti-beta2-glycoprotein I (anti-β2GPI) and anti-phosphatidylserine/prothrombin (aPS/PT) antibodies was not investigated systematically. Epitope specificity of anti-β2GPI antibodies was not reported.ObjectiveTo evaluate the prevalence and the clinical association of aPL in a large cohort of COVID-19 patients, and to characterize the epitope specificity of anti-β2GPI antibodies.MethodsELISA and chemiluminescence assays were used to test 122 sera of patients suffering from severe COVID-19. Of them, 16 displayed major thrombotic events.ResultsAnti-β2GPI IgG/IgA/IgM were the most frequent in 15.6/6.6/9.0% of patients, while aCL IgG/IgM were detected in 5.7/6.6% by ELISA. Comparable values were found by chemiluminescence. aPS/PT IgG/IgM were detectable in 2.5 and 9.8% by ELISA. No association between thrombosis and aPL was found. Reactivity against domain 1 and 4-5 of β2GPI was limited to 3/58 (5.2%) tested sera for each domain and did not correlate with aCL/anti-β2GPI nor with thrombosis.ConclusionsaPL show a low prevalence in COVID-19 patients and are not associated with major thrombotic events. aPL in COVID-19 patients are mainly directed against β2GPI but display an epitope specificity different from antibodies in antiphospholipid syndrome.
Extrapolation of Infection Data for the CoVid-19 Virus in 21 Countries and States and Estimate of the Efficiency of Lock Down
Authors: Langel Walter 
Published: June 2020

AbstractPredictions about the further development of the Corona pandemic are of great public interest but many approaches demand a large number of country specific parameters and are not easily transferable. A special interest of simulations on the pandemic is to trace the effect of politics for reducing the virus spread, since these measures have had an enormous impact on economy and daily life.Here a simple yet powerful algorithm is introduced for fitting the infection numbers by simple analytic functions. This way, the increase of the case numbers in periods with different regulations can be distinguished, and by extrapolating the fit functions, a forecast for the maximum numbers and time scales are possible. The effect of the restraints such as lock down are demonstrated by comparing the resulting infection history with the likely unconstrained virus spread, and it is shown that a delay of 1-4 weeks before imposing measures aiming at social distancing could have led to a complete infection of the respective populations.The approach is simply transferable to many different states. Here data from six E.U. countries, the UK, Russia, two Asian countries, the USA and ten states inside the USA with significant case numbers are analyzed, and striking qualitative similarities are found.Keywords: Covid-19, forecast, analytic fit, France, Germany, Italy, Spain South Korea, New York, Washington, Florida, Michigan, Poland, Sweden, USA, Pennsylvania, China, Russia, UK, California, Illinois, Indiana, Maryland, North Carolina.
Predicting walking response to ankle exoskeletons using data-driven models
Authors: Rosenberg Michael C. , Banjanin Bora S. , Burden Samuel A. , Steele Katherine M. 
Published: June 2020

IIAbstractDespite recent innovations in exoskeleton design and control, predicting subject-specific impacts of exoskeletons on gait remains challenging. We evaluated the ability of three classes of subject-specific phase-varying models to predict kinematic and myoelectric responses to ankle exoskeletons during walking, without requiring prior knowledge of specific user characteristics. Each model – phase-varying (PV), linear phase-varying (LPV), and nonlinear phase-varying (NPV) – leveraged Floquet Theory to predict deviations from a nominal gait cycle due to exoskeleton torque, though the models differed in complexity and expected prediction accuracy. For twelve unimpaired adults walking with bilateral passive ankle exoskeletons, we predicted kinematics and muscle activity in response to three exoskeleton torque conditions. The LPV model’s predictions were more accurate than the PV model when predicting less than 12.5% of a stride in the future and explained 49–70% of the variance in hip, knee, and ankle kinematic responses to torque. The LPV model also predicted kinematic responses with similar accuracy to the more-complex NPV model. Myoelectric responses were challenging to predict with all models, explaining at most 10% of the variance in responses. This work highlights the potential of data-driven phase-varying models to predict complex subject-specific responses to ankle exoskeletons and inform device design and control.
Phylogenetic Studies and Inhibitor Design Targeting Protein Interacting Interface of Nucleoid-Associated Protein HU
Authors: Dey Debayan , Ramakumar Suryanarayanarao 
Published: June 2020

AbstractThe formations of nucleoprotein structures by promiscuous DNA binding proteins like HU are assisted with their protein protein interaction capability with other proteins. InE. coliGal repressosome assembly, GalR piggybacks HU to the critical position on the DNA (hbs site) through a specific GalR–HU interaction using an interface at the bottom of alpha helical region, which we termed as HUpb interface. Similarly, MtbHU also interact with Topoisomerase I with the same interface to enhance its relaxation activity. In an earlier study, we determined the crystal structure of MtbHU, inhibited it using stilbene derivatives which inhibited the cell growth. It motivated us to understand the evolutionary and structural characteristics of the HUpb interface, which has not been investigated previously for HU or for any other NAPs. Our analyses found residue positions corresponding to MtbHU Thr11 to Gln20 form the interface while Ala23 serves the pocket lining residue. Due to ancestral mutations in the duplication event before the HU and IHF split, physicochemical properties of the interface vary among clades. Thus, this interface could engage different proteins in different HU oligomeric states inProteobacteria. Protein-protein interfaces are usually a challenging target due to its flatter surface. In case of MtbHUpb interface, we observed that due to the presence of a partially hydrophobic pocket, small molecule scaffolds could fit into it, while the ligand can be further designed to interact with D17, which is the crucial residue for Topoisomerase I interaction. We used a two-step virtual screening protocol with known drug like molecules as starting set to an aim to re-purpose drugs. Our docking results showed compounds like Maltotetraose, Valrubicin, Iodixanol, Enalkiren, indinavir, Carfilzomib, oxytetracycline, quinalizarin, Raltitrexed, Epigallocatechin and their analogues exhibit high scoring binding at MtbHUpb interface. Our present report gives a model example of an evolutionary study of an interface of nucleoid associated protein, which is used to computationally design inhibitors. This strategy could be in general useful for designing inhibitors for various types of protein-protein interfaces using evolutionary guided design.
Inhibiting actin polymerization does not prevent the fast block to polyspermy in the African clawed frog,Xenopus laevis
Authors: Tembo Maiwase , Sauer Monica L. , Wisner Bennett W. , Beleny David O. , Napolitano Marc A. , Carlson Anne E. 
Published: June 2020

AbstractFertilization of an egg by more than one sperm presents one of the earliest and most prevalent obstacles to successful reproduction. As such, eggs employ multiple mechanisms to prevent sperm entry into the nascent zygote. The fast block to polyspermy is a depolarization of the egg membrane initiated by sperm entry and is employed by diverse external fertilizers including frogs and sea urchins. For some external fertilizers, sperm entry is associated with actin polymerization during the initiation of the fast block. We therefore sought to determine whether the fast block to polyspermy in the African clawed frog,Xenopus laevis, requires actin polymerization. Although actin polymerization is required for sperm entry into eggs from diverse external fertilizers, including sea urchins and zebrafish, here we demonstrate that actin polymerization is not required for the fast block to polyspermy inX. laevis.
Pretreatment with LCK Inhibitors Chemosensitizes Cisplatin-Resistant Endometrioid Ovarian Tumors
Authors: Crean-Tate Katie K. , Braley Chad , Dey Goutam , Esakov Emily , Saygin Caner , Trestan Alexandria , Silver Daniel J. , Turaga Soumya M. , Connor Elizabeth , DeBernardo Robert , Michener Chad M. , Rose Peter G. , Lathia Justin , Reizes Ofer 
Published: June 2020

AbstractObjectiveTo evaluate LCK inhibitors (LCKi) as chemosensitizing agents for platinum-resistant endometrioid ovarian carcinoma.MethodsKM Plotter survival data was obtained for endometrioid ovarian cancer based on LCK mRNA expression. Cisplatin resistant endometrioid ovarian carcinoma cell lines were cultured and treated first with LCKi or vehicle, then combination LCKi-cisplatin. Cell viability was assessed via CellTiter-Glo, and apoptosis with Caspase 3/7 Assay. Protein lysates were isolated from treated cells, withγ-H2Ax, a DNA adduct marker, assessed.In vivostudy compared mice treated with vehicle or LCK inhibitor followed by LCK inhibitor, cisplatin, or combination therapy. One-way ANOVA and two sample t-test were used to assess statistical significance with GraphPad Prism.ResultsKM plotter data indicated LCK expression is associated with significantly worse median progression-free survival (HR 3.19, p=0.02), and a trend toward decreased overall survival in endometrioid ovarian tumors with elevated LCK expression (HR 2.45, p=0.41).In vitro, cisplatin resistant ovarian endometrioid cells treated first with LCKi followed by combination LCKi-cisplatin treatment showed decreased cell viability and increased apoptosis. Immunoblot studies revealed inhibition of LCK led to increased expression ofγ-H2AX.In vivoresults demonstrate treatment with LCKi followed by LCKi-cisplatin leads to significantly slowed tumor growth.ConclusionsWe identified a targetable pathway for chemosensitization of platinum resistant endometrioid ovarian cancer with initial treatment of LCKi followed by co-treatment with LCKi-cisplatin.
The validation of new phase-dependent gait stability measures: a modeling approach
Authors: Jin Jian , Kistemaker Dinant , van Dieën Jaap H. , Daffertshofer Andreas , Bruijn Sjoerd M. 
Published: June 2020

ABSTRACTIdentification of individuals at risk of falling is important when designing fall prevention methods. Current measures that estimate gait stability and robustness appear limited in predicting falls in older adults. Inspired by recent findings on changes in phase-dependent local stability within a gait cycle, we devised several phase-dependent stability measures and tested for their usefulness to predict gait robustness in compass walker models. These measures are closely related to the often-employed maximum finite-time Lyapunov exponent and maximum Floquet multiplier that both assess a system’s response to infinitesimal perturbations. As such, they entail linearizing the system but this is realized in a rotating hypersurface orthogonal to the period-one solution followed by estimating the trajectory-normal divergence rate of the swing phases and the foot strikes. We correlated the measures with gait robustness, i.e. the largest perturbation a walker can handle, in two compass walker models with either point or circular feet to estimate their prediction accuracy. To also test for the dependence of the measures under state space transform, we represented the point-feet walker in both Euler-Lagrange and Hamiltonian canonical form. Our simulations revealed that for most of the measures their correlation with gait robustness differs between models and between different state space forms. In particular the latter may jeopardize many stability measures’ predictive capacity for gait robustness. The only exception that consistently displayed strong correlations is the divergence of foot strike. Our results admit challenges of using phase-dependent stability measures as objective means to estimate the risk of falling.
Characterization of nuclear pore complex targeting domains in Pom152 inSaccharomyces cerevisiae
Authors: Brown Jacqueline T. , Haraczy Alexandra J. , Wilhelm Christopher M. , Belanger Kenneth D. 
Published: June 2020

AbstractPom152 is a transmembrane protein within the nuclear pore complex (NPC) of fungi that is important for NPC assembly and structure. Pom152 is comprised of a short amino-terminal region that remains on the cytosolic side of the nuclear envelope (NE) and interacts with NPC proteins, a transmembrane domain, and a large, glycosylated carboxy-terminal domain within the NE lumen that self-assembles to form the NPC membrane ring. Here we show that the N-terminal 200 amino acids of Pom152 that include only the amino-terminal and transmembrane regions of the protein are sufficient for localization to the NPC. Full-length, glycosylation-deficient, and truncated Pom152-GFP chimeras expressed in cells containing endogenous Pom152 localize to both NPCs and cortical endoplasmic reticulum (ER). Expression of Pom152-GFP fusions in cells lacking endogenous Pom152 results in detectable localization at only the NE by full-length and amino-terminal Pom152-GFP fusions, but continued retention at both the NE and ER for a chimera lacking just the carboxy-terminal 377 amino acids. Targeted mutations in the amino-terminal and transmembrane domains did not alter Pom152 localization and neither deletion of Pom152 nor its carboxy-terminal glycosylation sites altered the nuclear protein export rate of an Msn5/Kap142 protein cargo. These data narrow the Pom152 region sufficient for NPC localization and provide evidence that alterations in other domains may impact Pom152 targeting or affinity for the NPC.
The structure of autocatalytic networks, with application to early biochemistry
Authors: Steel Mike , Xavier Joana C. , Huson Daniel H. 
Published: June 2020

AbstractMetabolism across all known living systems combines two key features. First, all of the molecules that are required are either available in the environment or can be built up from available resources via other reactions within the system. Second, the reactions proceed in a fast and synchronised fashion via catalysts that are also produced within the system. Building on early work by Stuart Kauffman, a precise mathematical model for describing such self-sustaining autocatalytic systems (RAF theory) has been developed to explore the origins and organisation of living systems within a general formal framework. In this paper, we develop this theory further by establishing new relationships between classes of RAFs and related classes of networks, and developing new algorithms to investigate and visualise RAF structures in detail. We illustrate our results by showing how it reveals further details into the structure of archaeal and bacterial metabolism near the origin of life, and provide techniques to study and visualise the core aspects of primitive biochemistry.
Microbial piggy-back: howStreptomycesspores are transported by motile soil bacteria
Authors: Muok Alise R. , Claessen Dennis , Briegel Ariane 
Published: June 2020

AbstractStreptomycetes are sessile, soil-dwelling bacteria that produce diverse metabolites that impact plant health and the behavior of microbial communities. Emerging studies have demonstrated thatStreptomycesspores are distributed through a variety of mechanisms, but it remains unclear how spores are transported to their preferred micro-environments, such as plant roots. Here, we show thatStreptomycesspores are capable of utilizing the motility machinery of other soil bacteria and are transported on the centimeter scale. Motility assays and microscopy studies reveal thatStreptomycesspores are transported to plant tissues by interacting directly with the flagella of both gram-positive and gram-negative bacteria. Genetics experiments demonstrate that this form of motility, called piggy-backing, is facilitated by conserved structural proteins present on the surface ofStreptomycesspores. These results demonstrate that non-motile bacteria are capable of utilizing the motility machinery of other microbes to complete necessary stages of their lifecycle, and that this mode of transport may be ubiquitous in nature.