bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance evaluation of the BD SARS-CoV-2 reagents for the BD MAX™ system
Authors: Yanson Karen , Laviers William , Neely Lori , Lockamy Elizabeth , Castillo-Hernandez Luis Carlos , Oldfied Christopher , Ackerman Ronald , Ackerman Jamie , Ortiz Daniel A , Pacheco Sixto , Simner Patricia J , Young Stephen , McElvania Erin , Cooper Charles K 
Published: May 2021

ABSTRACTBackgroundThe RT-qPCR assay for detecting SARS-CoV-2 virus is the favorable approach to test suspected COVID-19 cases. However, discordant results can occur when two or more assays are compared. Variability in analytical sensitivities between assays, among other factors, may account for these differences in reporting.MethodsThe limits of detection (LOD) for the BD SARS-CoV-2 Reagents for BD MAX™ System (“MAX SARS-CoV-2 assay”), the Biomerieux BioFire® Respiratory Panel 2.1 (“BioFire SARS-CoV-2 assay”), the Roche cobas SARS-CoV-2 assay (“cobas SARS-CoV-2 assay”), and the Hologic Aptima® SARS-CoV-2 assay Panther® (“Aptima SARS-CoV-2 assay”) RT-qPCR systems were determined using a total of 84 contrived nasopharyngeal specimens with seven target levels for each comparator. The positive and negative percent agreement (PPA and NPA, respectively) for the MAX SARS-CoV-2 assay were compared to the Aptima SARS-CoV-2 assay in a post-market clinical study utilizing 708 paired nasopharyngeal specimens collected from suspected COVID-19 cases. Discordant results were further tested by the cobas and BioFire SARS-CoV-2 assays.ResultsThe measured LOD for the MAX SARS-CoV-2 assay (251 copies/mL) was comparable to the cobas SARS-CoV-2 assay (298 copies/mL) and the BioFire SARS-CoV-2 assay (302 copies/mL); the Aptima SARS-CoV-2 assay had a LOD of 612 copies/mL. The MAX SARS-CoV-2 assay had a PPA of 100% (95%CI: [97.3%-100.0%]) and a NPA of 96.7% (95%CI: [94.9%-97.9%]) when compared to the Aptima SARS-CoV-2 assay.ConclusionsThe MAX SARS-CoV-2 assay exhibited a high analytical sensitivity and specificity for SARS-CoV-2 detection. The clinical performance of the MAX SARS-CoV-2 assay agreed with another sensitive EUA cleared assay.
SPARSEMODr: Rapid simulations of spatially explicit and stochastic models infectious diseases, including COVID-19
Authors: Mihaljevic Joseph R , Borkovec Seth , Ratnavale Saikanth , Hocking Toby D , Banister Kelsey E , Eppinger Joseph E , Hepp Crystal , Doerry Eck 
Published: May 2021

AbstractBuilding realistically complex models of infectious disease transmission that are relevant for informing public health is conceptually challenging and requires knowledge of coding architecture that can implement key modeling conventions. For example, many of the models built to understand COVID-19 dynamics have included stochasticity, transmission dynamics that change throughout the epidemic due to changes in host behavior or public health interventions, and spatial structures that account for important spatio-temporal heterogeneities. Here we introduce an R package, SPARSEMODr, that allows users to simulate disease models that are stochastic and spatially explicit, including a model for COVID-19 that was useful in the early phases of the epidemic. SPARSEMOD stands for SPAtial Resolution-SEnsitive Models of Outbreak Dynamics, and our goal is to demonstrate particular conventions for rapidly simulating the dynamics of more complex, spatial models of infectious disease. In this report, we outline the features and workflows of our software package that allow for user-customized simulations. We believe the example models provided in our package will be useful in educational settings, as the coding conventions are adaptable, and will help new modelers to better understand important assumptions that were built into sophisticated COVID-19 models.
Model-M: An agent-based epidemic model of a middle-sized municipality
Authors: Berec Luděk , Diviák Tomáš , Kuběna Aleš , Levínský René , Neruda Roman , Suchopárová Gabriela , Šlerka Josef , Šmíd Martin , Trnka Jan , Tuček Vít , Vidnerová Petra , Zajíček Milan , Zapletal František 
Published: May 2021

AbstractThis report presents a technical description of our agent-based epidemic model of a particular middle-sized municipality. We have developed a realistic model with 56 thousand inhabitants and 2.7 millions of social contacts. These form a multi-layer social network that serves as a base of our epidemic simulation. The disease is modeled by our extended SEIR model with parameters fitted to real epidemics data for Czech Republic. The model is able to simulate a whole range of non-pharmaceutical interventions on individual level, such as protective measures and physical distancing, testing, contact tracing, isolation and quarantine. The effect of government-issued measures such as contact restrictions in different environments (schools, restaurants, vendors, etc.) can also be simulated.The model is implemented in Python and is available as open source at:www.github.com/epicity-cz/model-m/releases
Non-differential risk of SARS-CoV-2 infection for members of polling stations on Catalan parliament voting day
Authors: Medina-Peralta Manuel , Garcia-Eroles Luis , Hermosilla Eduardo , Fuentes Antonio , Méndez-Boo Leonardo , Fina Francesc , Fàbregas Mireia , Coma Ermengol , Lejardi Yolanda , Ramentol Marc , Peña-López Ismael 
Published: May 2021

AbstractWe aimed to assess the risk of SARS-CoV-2 infection for polling station members during the Catalan elections in February 2021. We compared the incidence 14 days after the elections between a cohort of polling station members (N= 18,304) and a control cohort paired by age, sex and place of residence. A total of 37 COVID-19 cases (0.2%) were confirmed in the members of the polling stations and 43 (0.23%) in the control group (p-value 0.576). Our study suggests that there was no greater risk of infection for the members of the polling stations.
Sensitive detection of Plasmodium vivax malaria by the rotating-crystal magneto-optical method in Thailand
Authors: Orbán Ágnes , Longley Rhea J. , Sripoorote Piyarat , Maneechai Nongnuj , Nguitragool Wang , Butykai Adam , Mueller Ivo , Sattabongkot Jetsumon , Karl Stephan , Kézsmárki István 
Published: May 2021

AbstractThe rotating-crystal magneto-optical detection (RMOD) method has been developed for the rapid and quantitative diagnosis of malaria and tested systematically on various malaria infection models. Very recently, an extended field trial in a high-transmission region of Papua New Guinea demonstrated its great potential for detecting malaria infections, in particular Plasmodium vivax. In the present small-scale field test, carried out in a low-transmission area of Thailand, RMOD confirmed malaria in all samples found to be infected with Plasmodium vivax by microscopy, our reference method. Moreover, the magneto-optical signal for this sample set was typically 1–3 orders of magnitude higher than the cut-off value of RMOD determined on uninfected samples. Based on the serial dilution of the original patient samples, we expect that the method can detect Plasmodium vivax malaria in blood samples with parasite densities as low as ∼ 5 − 10 parasites per microliter, a limit around the pyrogenic threshold of the infection. In addition, by investigating the correlation between the magnitude of the magneto-optical signal, the parasite density and the erythrocytic stage distribution, we estimate the relative hemozoin production rates of the ring and the trophozoite stages of in vivo Plasmodium vivax infections.
Pregnancy-induced changes in blood composition drive post-partum hemorrhage risk
Authors: Robinson Matthew R. , Patxot Marion , Stojanov Miloš , Blum Sabine , Baud David 
Published: May 2021

ABSTRACTThe extent to which women differ in the course of blood cell counts throughout pregnancy, and the importance of these changes to pregnancy outcomes has not been well defined. Here, we develop a series of statistical analyses of repeated measures data to reveal the degree to which women differ in the course of pregnancy, predict the changes that occur, and determine the importance of these changes for post-partum hemorrhage which is one of the leading causes of maternal mortality. We present a prospective cohort of 4,082 births recorded at the University Hospital, Lausanne, Switzerland between 2009 and 2014 where full labour records could be obtained, along with complete blood count data taken at hospital admission. We find significant differences, at a p < 0.001 level, among women in how blood count values change through pregnancy for mean corpuscular hemoglobin, mean corpuscular volume, mean platelet volume, platelet count and red cell distribution width. We find evidence that almost all complete blood count values show trimester-specific associations with postpartum hemorrhage and that tracking blood count value changes through pregnancy improves identification of women at increased risk, with increased area under the receiver operator curve in independent patient samples. Differences among women in the course of blood cell counts throughout pregnancy have an important role in shaping pregnancy outcome. Modelling trimester-specific associations with pregnancy outcomes, in a way that fully utilizes repeated measures data, provides greater understanding of the complex changes in blood count values that occur through pregnancy and provides indicators to guide the stratification of patients into risk groups.
Prediction of the effective reproduction number of COVID-19 in Greece. A machine learning approach using Google mobility data
Authors: Athanasios Arvanitis , Irini Furxhi , Tasioulis Thomas , Konstantinos Karatzas 
Published: May 2021

AbstractThis paper demonstrates how a short-term prediction of the effective reproduction number (Rt) of COVID-19 in regions of Greece is achieved based on online mobility data. Various machine learning methods are applied to predict Rt and attribute importance analysis is performed to reveal the most important variables that affect the accurate prediction of Rt. Our results are based on an ensemble of diverse Rt methodologies to provide non-precautious and non-indulgent predictions. The model demonstrates robust results and the methodology overall represents a promising approach towards COVID-19 outbreak prediction. This paper can help health related authorities when deciding non-nosocomial interventions to prevent the spread of COVID-19.
Functional Brain Networks in Focal Dystonia and their Associations with Dystonic Behavior
Authors: Bukhari-Parlakturk Noreen , Fei Michael , Voyvodic James , Davis Simon , Michael Andrew 
Published: May 2021

ABSTRACTMultiple neuroimaging studies suggest that dystonia is a network-level brain disorder, but the key networks to target for brain therapy in dystonia remain poorly understood. This study identified impaired functional networks (FNs) in writer’s cramp (WC) dystonia while participants performed hand motor tasks in the scanner. Task-fMRI images were acquired from twelve WC and twelve healthy volunteers (HV) while they performed writing, tapping, and flexion-extension motor tasks. Group independent component analysis was used to derive FNs, and functional network connectivity (FNC) between the FNs was computed to evaluate their associations with dystonic behavior. Our approach revealed three novel findings: First, we found that the basal ganglia, orbitofrontal, and superior parietal FNs were aberrant during the on-block of the task and, interestingly, also during the off-block period reminiscent of the loss of network inhibitory response during writing in WC. Second, we found multiple impaired FNC patterns in WC primarily in these three FNs these results were further validated through non-parametric testing via Monte Carlo simulations. Third, using FNC deficits and FNC-writing legibility correlations, we characterized these FNC patterns as primary or secondary associations with the motor program for writing. Findings from our data-driven whole-brain analysis approach reveal new FNs disrupted in dystonia and they may serve as key targets for the treatment of this disorder.Impact StatementDystonia is a rare and disabling brain disorder affecting motor function. In this study, novel functional network differences in dystonia were identified. Associations between functional network connectivity and dystonic behavior were found. Through a data-driven approach, this study reveals new targets for dystonia treatment.
CAR-T cells Targeting Thyroid-stimulating Hormone Receptor (TSHR) Demonstrate Safety and Potent Preclinical Activity Against Differentiated Thyroid Cancer
Authors: Li Hanning , Zhou Xiang , Wang Ge , Hua Dongyu , Li Shuyu , Xu Tao , Dong Menglu , Cui Xiaoqing , Yang Xue , Wu Yonglin , Cai Miaomiao , Liao Xinghua , Zhang Tongcun , Yang Zhifang , Du Yaying , Li Xingrui 
Published: May 2021

AbstractBackgroundDifferentiated thyroid cancer (DTC) is usually very treatable and is often cured with surgery and, if indicated, follow with radioactive iodine (RAI) and long-term thyroid-stimulating hormone (TSH) suppression with levothyroxine. Unfortunately, locoregional relapse and distant metastases occur in up to 20% at ten years; those relapsed or distant metastatic thyroid cancer is relatively uncommon compare to other cancers, cytotoxic chemotherapies provided low response rates, and two-thirds of cases became RAI refractory (RAI-R). New therapy options for local-regional relapsed or distant metastases thyroid cancer are desperately needed. Chimeric antigen receptor T cells (CAR-T) have been demonstrated remarkable efficacy in hematological cancers but have not yet translated in treating solid tumors. The significant hurdles limiting CAR-T therapy were due to a paucity of differentially expressed cell surface molecules on solid tumors that can be safely targeted. Here, we present thyroid-stimulating hormone receptor (TSHR) as a putative target for CAR-T therapy of DTC.MethodsWe undertook a large-scale screen on thyroid cancer tissues and multiple internal organs through bioinformatical analysis and immunohistochemistry to date TSHR expression. Using three previously described mAb, we generate three third-generation CAR-Ts. We tested anti-TSHR CAR-T in vitro activity by T-cell function assay and killing assay. Then we tested pre-clinical therapeutical efficacy in a xenograft mouse model of DTC and analyzed mice’s physical conditions and histological abnormalities to evaluate anti-TSHR CAR-T’s safety.ResultsTSHR is highly and homogeneously expressed on 90.8%(138/152) of papillary thyroid cancer, 89.2% (33/37) of follicular thyroid cancer, 78.2% (18/23) of the cervical lymph node metastases, and 86.7% of locally recurrent or metastasis lesions with RAI-R disease. We develop three novel anti-TSHR CAR-T from mAb M22, K1-18, and K1-70, all three CAR-Ts mediate significant anti-tumor activity in vitro. Among these, we demonstrate that K1-70 CAR-T can have therapeutical efficacy in vivo, and no apparent toxicity has been observed.ConclusionTSHR is a latent target antigen of CAR-T therapy for DTC. Anti-TSHR CAR-T has strong therapeutical efficacy in vivo while without prominent adverse events. Anti-TSHR CAR-T could represent an exciting therapeutic option for patients with specific local-regional relapsed or distant metastases thyroid cancer and should be tested in carefully designed clinical trials.
Co-establishing an infrastructure for routine data collection to address disparities in infant mortality: Planning and implementation
Authors: Fareed Naleef , Swoboda Christine , Griesenbrock Tyler , Lawrence John , Huerta Timothy R. 
Published: May 2021

AbstractBackgroundEfforts to address infant mortality disparities in Ohio have historically been adversely affected by the lack of consistent data collection and infrastructure across the community-based organizations performing front-line work with expectant mothers, and there is no established template for implementing such systems in the context of diverse technological capacities and varying data collection magnitude among participating organizations.MethodsTaking into account both the needs and limitations of participating community-based organizations, we created a data collection infrastructure that was refined by feedback from sponsors and the organizations to serve as both a solution to their existing needs and a template for future efforts in other settings.ResultsBy standardizing the collected data elements across participating organizations, integration on a scale large enough to detect changes in a rare outcome such as infant mortality was made possible. Datasets generated through the use of the established infrastructure were robust enough to be matched with other records, such as Medicaid and birth records, to allow more extensive analysis.ConclusionWhile a consistent data collection infrastructure across multiple organizations does require buy-in at the organizational level, especially among participants with little to no existing data collection experience, an approach that relies on an understanding of existing barriers, iterative development, and feedback from sponsors and participants can lead to better coordination and sharing of information when addressing health concerns that individual organizations may struggle to quantify alone.
The effect of smaller classes on infection-related school absence: Evidence from the Project STAR randomized controlled trial
Authors: von Hippel Paul T. 
Published: May 2021

ABSTRACTIn an effort to reduce viral transmission, many schools are planning to reduce class size if they have not reduced it already. Yet the effect of class size on transmission is unknown. To determine whether smaller classes reduce school absence, especially when community disease prevalence is high, we merge data from the Project STAR randomized class size trial with influenza and pneumonia data from the 122 Cities Mortality Reporting System on deaths from pneumonia and influenza.Project STAR was a block-randomized trial that followed 10,816 Tennessee schoolchildren from kindergarten in 1985-86 through third grade in 1988-89. Children were assigned at random to small classes (13 to 17 students), regular-sized classes (22 to 26 students), and regular-sized class with a teacher’s aide.Mixed effects regression showed that small classes reduced absence, but not necessarily by reducing infection. In particular, small classes reduced absence by 0.43 days/year (95% CI -0.06 to -0.80,p<0.05), but had no significant interaction with pneumonia and influenza mortality (95% CI -0.27 to +0.30,p>0.90). Small classes, by themselves, may not suffice to reduce the spread of viruses.
Epigenetic predictors of maximum lifespan and other life history traits in mammals
Authors: Li C.Z. , Haghani A. , Robeck T.R. , Villar D. , Lu A.T. , Zhang J. , Faulkes C.G. , Vu H. , Ablaeva J. , Adams D.M. , Ardehali R. , Arneson A. , Baker C.S. , Belov K. , Blumstein D.T. , Bors E.K. , Breeze C.E. , Brooke R.T. , Brown J.L. , Caulton A. , Cavin J.M. , Chatzistamou I. , Chen H. , Chiavellini P. , Choi O.W. , Clarke S. , DeYoung J. , Emmons C.K. , Emmrich S. , Fei Z. , Ferguson S.H. , Finno C.J. , Flower J.E. , Gaillard J.M. , Garde E. , Gladyshev V.N. , Goya R.G. , Hanson M.B. , Haulena M. , Herrick K. , Hogan A.N. , Hogg C.J. , Hore T.A. , Jasinska A.J. , Jones G. , Jourdain E. , Kashpur O. , Katcher H. , Katsumata E. , Kaza V. , Kiaris H. , Kobor M.S. , Kordowitzki P. , Koski W.R. , Larison B. , Lee S.G. , Lehmann M. , Lemaitre J.F. , Levine A.J. , Li C. , Li X. , Lin D.T.S. , Lindemann D.M. , Macoretta N. , Maddox D. , Matkin C.O. , Mattison J.A. , Mergl J. , Meudt J.J. , Montano G.A. , Mozhui K. , Naderi A. , Nagy M. , Narayan P. , Nathanielsz P.W. , Nguyen N.B. , Niehrs C. , Odom D.T. , Ophir A.G. , Ostrander E.A. , O’Tierney Ginn P. , Parsons K.M. , Paul K.C. , Pellegrini M. , Pinho G.M. , Plassais J. , Prado N.A. , Rey B. , Ritz B.R. , Robbins J. , Rodriguez M. , Russell J. , Rydkina E. , Sailer L.L. , Salmon A.B. , Sanghavi A. , Schachtschneider K.M. , Schmitt D. , Schomacher L. , Schook L.B. , Sears K.E. , Seifert A.W. , Shindyapina A.V. , Singh K. , Sinha I. , Snell R.G. , Soltanmohammadi E. , Spangler M.L. , Spriggs M. , Steinman K.J. , Sugrue V.J. , Szladovits B. , Takasugi M. , Teeling E.C. , Van Bonn B. , Vernes S.C. , Vinters H.V. , Wallingford M.C. , Wang N. , Wilkinson G.S. , Williams R.W. , Yang X.W. , Young B.G. , Zhang B. , Zhang Z. , Zhao P. , Zhao Y. , Zhou W. , Zoller J.A. , Ernst J. , Seluanov A. , Raj K. , Gorbunova V. , Horvath S. ,   MAMMALIAN METHYLATION CONSORTIUM
Published: May 2021

AbstractMaximum lifespan of a species is the oldest that individuals can survive, reflecting the genetic limit of longevity in an ideal environment. Here we report methylation-based models that accurately predict maximum lifespan (r=0.89), gestational time (r=0.96), and age at sexual maturity (r=0.87), using cytosine methylation patterns collected from over 12,000 samples derived from 192 mammalian species. Our epigenetic maximum lifespan predictor corroborated the extended lifespan in growth hormone receptor knockout mice and rapamycin treated mice. Across dog breeds, epigenetic maximum lifespan correlates positively with breed lifespan but negatively with breed size. Lifespan-related cytosines are located in transcriptional regulatory regions, such as bivalent chromatin promoters and polycomb-repressed regions, which were hypomethylated in long-lived species. The epigenetic estimators of maximum lifespan and other life history traits will be useful for characterizing understudied species and for identifying interventions that extend lifespan.
Relationships between acute race-induced changes in creatine kinase activity and blood plasma myoglobin concentration and race performance in mountain bike and road cyclists
Authors: Hebisz Paulina , Borkowski Jacek , Hebisz Rafał 
Published: May 2021

AbstractThe aim of this study was to determine if the changes in plasma creatine kinase (CK) activity and myoglobin (MB) concentrations as markers of muscle damage differ between competitive road (n = 14) and mountain bike (n = 11) cyclists and if these biochemical markers show a relationship with real-world race performance. CK and MB were measured from blood samples collected 2 hours before race start and 1 hour after race completion and the change in pre- and post-race difference was calculated (ΔCK and ΔMB). An incremental exercise test was used to determine maximal oxygen uptake, maximal aerobic power, and power output at the second ventilatory threshold. Post-race CK and MB increased in the whole group of cyclists. Although the magnitude of change in CK was similar in both road and mountain bike cyclists, only the increase in road cyclists was significant. MB significantly increased only in mountain bike cyclists. Multiple regression analysis revealed a significant association between both road and mountain bike race performance and ΔCK and ΔMB. The other significant predictors for mountain bike race performance were maximal aerobic power (W·kg-1) and power output at the second ventilatory threshold (W·kg-1) and for road race performance both maximal oxygen uptake (l·min-1) and power output at the second ventilatory threshold (W). In conclusion, mountain bike racing was associated with an increase in MB whereas road racing with an increase in CK, with the post-race changes in CK and MB related to race performance as high ΔCK and low ΔMB were obtained by better-performing cyclists.