bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global projections of lives saved from COVID-19 with universal mask use
Authors: Gakidou Emmanuela , Pigott David M. , Troeger Christopher E. , Hulland Erin N. , Reiner Robert C. , Adolph Christopher , Aravkin Aleksandr Y. , Bachmeier Steven D. , Bang-Jensen Bree , Barber Ryan M. , Bisignano Catherine , Bloom Sabina , Carter Austin , Castro Emma , Chakrabarti Suman , Chattopadhyay Jhilik , Chen Christine , Cogen Rebecca M. , Collins James K. , Combs Emily , Cormier Natalie Maria , Dai Xiaochen , Dangel William James , Deen Amanda , Ewald Samuel B. , Flaxman Abraham D. , Fullman Nancy , Guo Gaorui , Hackman Kathryn , He Jiawei , Henry Nathaniel J. , Johanns Casey , Larson Samantha Leigh , Lazzar-Atwood Alice , LeGrand Kate E. , Lescinsky Haley , Lim Stephen S. , Linebarger Emily , Lozano Rafael , Ma Rui , Magistro Beatrice , Månsson Johan C. , Marczak Laurie B. , Miller-Petrie Molly K. , Mokdad Ali H. , Mooney Meghan D. , Odell Christopher M. , O’Halloran James K. , Ostroff Samuel M. , Pasovic Maja , Patel Disha J. , Penberthy Louise , Ramshaw Rebecca E. , Roth Gregory A. , Shaw David H. , Sheena Brittney S. , Sholokhov Aleksei , Sorensen Reed J. D. , Sparks Gianna , Spurlock Emma Elizabeth , Subart Michelle L. , Walker Ally , Watson Alexandrea , Welgan Catherine A. , Wiens Kirsten E. , Woyczynski Lauren , Xu Liming , Hay Simon I. , Brauer Michael , Vos Theo , Murray Christopher J. L. ,   IHME COVID-19 Forecasting Team
Published: October 2020

ABSTRACTBACKGROUNDSocial distancing mandates (SDM) have reduced health impacts from COVID-19 but also resulted in economic downturns that have led many nations to relax SDM. Until deployment of an efficacious and equitable vaccine, intervention options to reduce COVID-19 mortality and minimize restrictive SDM are sought by society.METHODSA susceptible-exposed-infectious-recovered (SEIR) deterministic transmission model was parameterized with data on reported deaths, cases, and select covariates to predict infections and deaths from COVID-19 through March 01, 2021. We explore three scenarios: a “non-adaptive” scenario where neither mask use or SDM adapt to changing conditions, a “reference” where current national levels of mask use are maintained and SDM reintroduced when deaths rise, and an increase in mask use to 95% coverage levels (“universal mask”). We reviewed published studies to set priors on the magnitude of reduction in transmission through increasing mask use.RESULTSMask use was estimated at 59.0% of people globally on October 19, 2020. Universal mask use could avert 733,310 deaths (95% UI 385,981 to 1,107,759) between October 27, 2020 and March 01, 2021, the difference between the predicted 2.95 million deaths (95% UI 2.70 to 3.35) in the reference scenario and 2.22 million deaths (95% UI 2.00 to 2.45) in the universal mask scenario over this time period.CONCLUSIONSThe cumulative toll of the COVID-19 pandemic could be substantially reduced by the universal adoption of masks before the availability of a vaccine. This low-cost, low-barrier policy, whether customary or mandated, has enormous health benefits with presumed marginal economic costs.
Absence of SARS-CoV-2 neutralizing activity in pre-pandemic sera from individuals with recent seasonal coronavirus infection
Authors: Poston Daniel , Weisblum Yiska , Wise Helen , Templeton Kate , Jenks Sara , Hatziioannou Theodora , Bieniasz Paul 
Published: October 2020

AbstractCross-reactive immune responses elicited by seasonal coronaviruses might impact SARS-CoV-2 susceptibility and disease outcomes. We measured neutralizing activity against SARS-CoV-2 in pre-pandemic sera from patients with prior PCR-confirmed seasonal coronavirus infection. While neutralizing activity against seasonal coronaviruses was detected in nearly all sera, cross-reactive neutralizing activity against SARS-CoV-2 was undetectable.
Exclusion of bacterial co-infection in COVID-19 using baseline inflammatory markers and their response to antibiotics
Authors: Mason Claire Y , Kanitkar Tanmay , Richardson Charlotte J , Lanzman Marisa , Stone Zak , Mahungu Tabitha , Mack Damien , Wey Emmanuel Q , Lamb Lucy , Balakrishnan Indran , Pollara Gabriele 
Published: October 2020

AbstractBackgroundCOVID-19 is infrequently complicated by secondary bacterial infection, but nevertheless antibiotic prescriptions are common. We used community-acquired pneumonia (CAP) as a benchmark to define the processes that occur in a bacterial pulmonary infection, and tested the hypothesis that baseline inflammatory markers and their response to antibiotic therapy could distinguish CAP from COVID-19.MethodsIn patients admitted to Royal Free Hospital (RFH) and Barnet Hospital (BH) we defined CAP by lobar consolidation on chest radiograph, and COVID-19 by SARS-CoV-2 detection by PCR. Data were derived from routine laboratory investigations.ResultsOn admission all CAP and >90% COVID-19 patients received antibiotics. We identified 106 CAP and 619 COVID-19 patients at RFH. CAP was characterised by elevated white cell count (WCC) and C-reactive protein (CRP) compared to COVID-19 (median WCC 12.48 (IQR 8.2-15.3) vs 6.78 (IQR 5.2-9.5) x106cells/ml and median CRP CRP 133.5 (IQR 65-221) vs 86 (IQR 42-160) mg/L). Blood samples collected 48-72 hours into admission revealed decreasing CRP in CAP but not COVID-19 (CRP difference −33 (IQR −112 to +3.5) vs +15 (IQR −15 to +70) mg/L respectively). In the independent validation cohort (BH) consisting of 169 CAP and 181 COVID-19 patients, admission WCC >8.2×106cells/ml or falling CRP during admission identified 95% of CAP cases, and predicted the absence of bacterial co-infection in 45% of COVID-19 patients.ConclusionsWe propose that in COVID-19 the absence of both elevated baseline WCC and antibiotic-related decrease in CRP can exclude bacterial co-infection and facilitate antibiotic stewardship efforts.
Prediction of immunotherapy response using deep learning of PET/CT images
Authors: Mu Wei , Jiang Lei , Shi Yu , Tunali Ilke , Gray Jhanelle E. , Katsoulakis Evangelia , Tian Jie , Gillies Robert J. , Schabath Matthew B. 
Published: October 2020

AbstractCurrently only a fraction of patients with non-small cell lung cancer (NSCLC) experience durable clinical benefit (DCB) from immunotherapy, robust biomarkers to predict response prior to initiation of therapy are an emerging clinical need. PD-L1 expression status from immunohistochemistry is the only clinically approved biomarker, but a non-invasive complimentary approach that could be used when tissues are not available or when the IHC fails and can be assessed longitudinally would have important implications for clinical decision support. In this study, 18F-FDG-PET/CT images and clinical data were curated from 697 NSCLC patients from three institutions. Utilizing PET/CT images, a deeply-learned-score (DLS) was developed by training a small-residual-convolutional-network model to predict the PD-L1 expression status, which was further used to predict DCB, progression-free survival (PFS), and overall survival (OS) in both retrospective and prospective test cohorts of immunotherapy-treated patients with advanced stage NSCLC. This PD-L1 DLS significantly discriminated PD-L1 positive and negative patients (AUC≥0.82 in all cohorts). Further, higher PD-L1 DLS was significantly associated with higher probability of DCB, longer PFS, and longer OS. The DLS combined with clinical characteristics achieved C-indices of 0.86, 0.83 and 0.81 for DCB prediction, 0.73, 0.72 and 0.70 for PFS prediction, and 0.78, 0.72 and 0.75 for OS prediction in the retrospective, prospective and external cohorts, respectively. The DLS provides a non-invasive and promising approach to predict PD-L1 expression and to infer clinical outcomes for immunotherapy-treated NSCLC patients. Additionally, the multivariable models have the potential to guide individual pre-therapy decisions pending in larger prospective trials.Statement of SignificancePD-L1 expression status by immunohistochemistry (IHC) is the only clinically-approved biomarker to trigger immunotherapy treatment decisions, but a non-invasive complimentary approach that could be used when tissues are not available or when the IHC fails and can be assessed longitudinally would have important implications for clinical decision support. Utilizing PET/CT images, we developed and tested a convolutional neural network model to predict PD-L1 expression status with high accuracy in cohorts from different institutions. And the generated signature may serve as a prognostic biomarker for immunotherapy response in patients with NSCLC, and outperforms the clinical characteristics.
Factors associated with progression to critical illness in 28 days among COVID-19 patients: results from a tertiary care hospital in Istanbul, Turkey
Authors: Sili Uluhan , Ay Pinar , Topuzoglu Ahmet , Bilgin Huseyin , Tigen Elif Tukenmez , Sengel Buket Erturk , Caglayik Dilek Yagci , Balcan Baran , Kocakaya Derya , Yildizeli Sehnaz Olgun , Gul Fethi , Bilgili Beliz , Sarinoglu Rabia Can , Yagci Aysegul Karahasan , Durmusoglu Lutfiye Mulazimoglu , Eryuksel Emel , Odabasi Zekaver , Direskeneli Haner , Karakurt Sait , Cinel Ismail , Korten Volkan 
Published: October 2020

ABSTRACTBackgroundCoronavirus disease 2019 (COVID-19) quickly spread worldwide to become a pandemic. This study aimed to define the predictors of critical illness development within 28 days postadmission.MethodsWe conducted a prospective cohort study including 477 PCR-positive COVID-19 patients admitted to a tertiary care hospital in Istanbul from March 12 to May 12, 2020. The development of critical illness, e.g., invasive mechanical ventilation and/or death, was followed for a period of 28 days postadmission. Demographic characteristics, number of comorbidities, illness severity at admission defined by the WHO scale, vital signs, laboratory findings and period of admission to the hospital were independent variables. Cox proportional hazards analysis was performed, and the C-index was calculated.ResultsThe median (IQR) age of the cohort was 55.0 (44.0-67.0) years, and 50.1% were male. The most common presenting symptoms were cough, dyspnea and fatigue. Overall, 65.2% of the patients had at least one comorbidity. Hydroxychloroquine was given to 99.2% of the patients. Critical illness developed in 45 (9.4%; 95% CI: 7.0%-12.4%) patients. In the multivariable analysis, age (HR: 1.05, p<0.001), number of comorbidities (HR: 1.33, p=0.02), procalcitonin ≥0.25 µg/L (HR: 2.12, p=0.03) and LDH ≥350 U/L (HR: 2.04, p=0.03) were independently associated with critical illness development. The WHO scale on admission was the strongest predictor of critical illness (HR: 4.15, p<0.001). Prognosis improved within the study period (p<0.05). The C-index of the model was 0.92.ConclusionsAge, comorbidity number, WHO scale, LDH and procalcitonin were independently associated with critical illness development. Mortality from COVID-19 seems to be decreasing as the pandemic advances.summaryWe analyzed 477 confirmed COVID-19 patients for the development of critical illness, e.g., invasive mechanical ventilation and/or death within 28 days postadmission. Age, comorbidity number, WHO scale, LDH and procalcitonin were independently associated with critical illness development.
Development and Validation of a Highly Generalizable Deep Learning Pulmonary Embolism Detection Algorithm
Authors: Schmid Ryan , Johnson Jacob , Ngo Jennifer , Lamoureux Christine , Baker Brian , Ngo Lawrence 
Published: October 2020

AbstractSeveral algorithms have been developed for the detection of pulmonary embolism, though generalizability and bias remain potential weaknesses due to small sample size and sample homogeneity. We developed and validated a highly generalizable deep-learning algorithm, Emboleye, for the detection of PE by using a large and diverse dataset, which included 30,574 computed tomography (CT) exams sourced from over 2,000 hospital sites. On angiography exams, Emboleye demonstrates an AUROC of 0.79 with a specificity of 0.99 while maintaining a sensitivity of 0.37 and PPV of 0.77. On non-angiography CT exams, Emboleye demonstrates an AUROC of 0.77 with a specificity of 0.99 while maintaining a sensitivity of 0.18 and PPV of 0.35.
Risk of death among people with rare autoimmune diseases compared to the general population in England during the 2020 COVID-19 pandemic
Authors: Peach Emily , Rutter Megan , Lanyon Peter , Grainge Matthew J , Hubbard Richard , Aston Jeanette , Bythell Mary , Stevens Sarah , Pearce Fiona 
Published: October 2020

AbstractObjectivesTo quantify the risk of death among people with rare autoimmune rheumatic diseases (RAIRD) during the UK 2020 COVID-19 pandemic compared to the general population, and compared to their pre-COVID risk.MethodsWe conducted a cohort study in Hospital Episode Statistics for England 2003 onwards, and linked data from the NHS Personal Demographics Service. We used ONS published data for general population mortality rates.ResultsWe included 168,691 people with a recorded diagnosis of RAIRD alive on 01/03/2020. Their median age was 61.7 (IQR 41.5-75.4) years, and 118,379 (70.2%) were female. Our case ascertainment methods had a positive predictive value of 85%. 1,815 (1.1%) participants died during March and April 2020. The age-standardised mortality rate (ASMR) among people with RAIRD (3669.3, 95% CI 3500.4-3838.1 per 100,000 person-years) was 1.44 (95% CI 1.42-1.45) times higher than the average ASMR during the same months of the previous 5 years, whereas in the general population of England it was 1.38 times higher. Age-specific mortality rates in people with RAIRD compared to the pre-COVID rates were higher from the age of 35 upwards, whereas in the general population the increased risk began from age 55 upwards. Women had a greater increase in mortality rates during COVID-19 compared to men.ConclusionThe risk of all-cause death is more prominently raised during COVID-19 among people with RAIRD than among the general population. We urgently need to quantify how much risk is due to COVID-19 infection and how much is due to disruption to healthcare services.Key messagesPeople with RAIRD had an increased risk of dying during COVID-19 from age 35 years onwards, whereas in the general population it increased from the age of 55 onwards.Women had a greater increase in their risk of death during COVID-19 compared to men.The risk of working age people with RAIRD dying during COVID-19 was similar to that of someone 20 years older in the general population.
Polyester Nasal Swabs Collected in a Dry Tube are a Robust and Inexpensive, Minimal Self-Collection Kit for SARS-CoV-2 Testing
Authors: Padgett Leah R. , Kennington Lauren A. , Ahls Charlotte L. , Samarasinghe Delini K. , Tu Yuan-Po , Wallander Michelle L. , Elliott James S. , Rains Douglas 
Published: October 2020

AbstractBackgroundPolyester nasal swabs stored in saline or in a dry tube were evaluated as an alternative to foam nasal swabs for SARS-CoV-2 testing by reverse transcription quantitative polymerase chain reaction (RT-qPCR) since they may be inexpensively manufactured at high capacity.MethodsSurrogate clinical specimens were prepared by inoculating foam and polyester nasal swabs with residual SARS-CoV-2 positive clinical specimens diluted in porcine or human matrix. Dry swab elution with phosphate buffered saline (PBS) was evaluated by vortex, swab swirling, and passive methodologies. Surrogate and clinical nasal specimen stability were evaluated at refrigerated (4°C) and elevated temperatures (40°C for 12 hours, 32°C hold) through 72 hours.ResultsPolyester swabs demonstrated equivalent performance to foam swabs for detection of low and high SARS-CoV-2 viral loads. Dry swab elution performed with PBS and mechanical disruption by vortex resulted in nearly complete quantitative recovery of virus. Dry polyester and foam surrogate specimens were stable through 72 hours both when refrigerated and after high temperature excursion, which simulated specimen transport without cold chain. Similarly, clinical specimens collected with polyester swabs and stored dry were stable through 72 hours in the presence and absence of cold chain. Polyester surrogate specimens stored in saline were stable through 72 hours refrigerated but only through 48 hours at elevated temperatures.ConclusionsPolyester nasal swabs stored in dry collection tubes comprise a robust and inexpensive self-collection method for SARS-CoV-2 viral load testing, which is stable under conditions required for home collection and shipment to the laboratory.
Holocephali From the Irati Formation (Paraná Basin), Brazil: Origin, Paleogographical and Paleoenvironmental Considerations
Authors: Chahud Artur 
Published: October 2020

AbstractThe Permian (Cisuralian) Irati Formation, from the Brazilian southeastern Paraná Basin bears, at some levels, Chondrichthyes, besides other vertebrates. Outcrops of this unit are frequent at the state of São Paulo eastern belt. Two members of the Irati are recognized at this state, Assistência, the upper, and Taquaral. A sandy facies, mostly at the base of the Taquaral, is noteworthy by the richness of the Chondrichthyes, mainly Holocephali. The Petalodontiformes are the Chondrichthyes most abundant, so far referred toItapyrodus punctatus. Recent studies of several specimens revealed that some morphotypes must belong to different species of the genusItapyrodus. Others are akin to this genus, justifying a proposition of an endemic family Itapyrodidae. The presence of this endemic family is an argument, among others, for a proposed isolation of two Brazilan Basins northeast Parnaíba and southeast Paraná, during the time of deposition of the Irati, inasmuch as Itapyrodidae are present in both basins.
Kidney injury molecule-1 is a potential receptor for SARS-CoV-2
Authors: Yang Chen , Zhang Yu , Chen Hong , Chen Yuchen , Yang Dong , Shen Ziwei , Wang Xiaomu , Liu Xinran , Xiong Mingrui , Huang Kun 
Published: October 2020

AbstractCOVID-19 patients present high incidence of kidney abnormalities, which are associated with poor prognosis and high mortality. Identification of SARS-CoV-2 in kidney of COVID-19 patients suggests renal tropism and direct infection. Presently, it is generally recognized that SARS-CoV-2 initiates invasion through binding of receptor-binding domain (RBD) of spike protein to host cell-membrane receptor ACE2, however, whether there is additional target of SARS-CoV-2 in kidney remains unclear. Kidney injury molecule-1 (KIM1) is a transmembrane protein that drastically up-regulated after renal injury. Here, binding between SARS-CoV2-RBD and the extracellular Ig V domain of KIM1 was identified by molecular simulations and co-immunoprecipitation, which was comparable in affinity to that of ACE2 to SARS-CoV-2. Moreover, KIM1 facilitated cell entry of SARS-CoV2-RBD, which was potently blockaded by a rationally designed KIM1-derived polypeptide. Together, the findings suggest KIM1 may mediate and exacerbate SARS-CoV-2 infection in a ‘vicious cycle’, and KIM1 could be further explored as a therapeutic target.
Functional Context Affects Scene Processing
Authors: Aminoff Elissa M. , Tarr Michael J. 
Published: October 2020

AbstractRapid visual perception is often viewed as a bottom-up process. Category-preferred neural regions are often characterized as automatic, default processing mechanisms for visual inputs of their categorical preference. To explore the sensitivity of such regions to top-down information, we examined three scene-preferring brain regions, the occipital place area (OPA), the parahippocampal place area (PPA), and the retrosplenial complex (RSC), and tested whether the processing of outdoor scenes is influenced by the functional contexts in which they are seen. Context was manipulated by presenting real-world landscape images as if being viewed through a window or within a picture frame; manipulations that do not affect scene content but do affect one’s functional knowledge regarding the scene. This manipulation influences neural scene processing (as measured by fMRI): the OPA and PPA exhibited greater neural activity when participants viewed images as if through a window as compared to within a picture frame, while the RSC did not show this difference. In a separate behavioral experiment, functional context affected scene memory in predictable directions (boundary extension). Our interpretation is that the window context denotes three-dimensionality, therefore rendering the perceptual experience of viewing landscapes as more realistic. Conversely, the frame context denotes a two-dimensional image. As such, more spatially-biased scene representations in the OPA and the PPA are influenced by differences in top-down, perceptual expectations generated from context. In contrast, more semantically-biased scene representations in the RSC are likely to be less affected by top-down signals that carry information about the physical layout of a scene.
A novel density-based neural mass model for simulating neuronal network dynamics with conductance-based synapses and membrane current adaptation
Authors: Huang Chih-Hsu , Lin Chou-Ching K. 
Published: October 2020

AbstractNowadays, building low-dimensional mean-field models of neuronal populations is still a critical issue in the computational neuroscience community, because their derivation is difficult for realistic networks of neurons with conductance-based interactions and spike-frequency adaptation that generate nonlinear properties of neurons. Here, based on a colored-noise population density method, we derived a novel neural mass model, termed density-based neural mass model (dNMM), as the mean-field description of network dynamics of adaptive exponential integrate-and-fire neurons. Our results showed that the dNMM was capable of correctly estimating firing rate responses under both steady- and dynamic-input conditions. Finally, it was also able to quantitatively describe the effect of spike-frequency adaptation on the generation of asynchronous irregular activity of excitatory-inhibitory cortical networks. We conclude that in terms of its biological reality and calculation efficiency, the dNMM is a suitable candidate to build very large-scale network models involving multiple brain areas.
SARS-CoV-2 infections in Italian schools: preliminary findings after one month of school opening during the second wave of the pandemic
Authors: Buonsenso Danilo , De Rose Cristina , Moroni Rossana , Valentini Piero 
Published: October 2020

ABSTRACTIntroductionThe impact of school opening on the SARS-CoV-2 pandemic is still unknown. This study aims to provide preliminary information about the number of SARS-CoV-2 cases among students attending Italian schools.MethodsData are extracted and analysed from an open access, online dataset that monitor, on a daily basis, media news about SARS-CoV-2 infections of students attending Italian schoolsResultsAs of 5 October 2020, a total of 1350 cases of SARS-CoV-2 infections have been registered in the Italian territory schools (involving 1059 students, 145 teachers and 146 other school members), for a total of 1212 out of 65104 (1.8%) Italian schools involved. National schools reported only 1 case of SARS-CoV-2 infection in more than 90% of cases, and only in one high school a cluster of more than 10 cases have been described (P 0.015). The detection of one or more SARS-CoV-2 infections leaded to the closure of 192 (14.2%) entire schools, more frequently nursery/kindergartens (P<0.0005).DiscussionOur preliminary data support low transmission of SARS-CoV-2 within schools, at least among younger students. However, entire schools are frequently closed in the fear of larger outbreaks. Continuous monitoring of school settings, hopefully through daily updated open access datasets, are needed to better understand the impact of schools on the pandemic, and provide guidelines that better consider different risks within different age groups.