bluuebunny/crossref_metadata_2025_split huggingface dataset:
THE ASSOCIATION OF OPENING K-12 SCHOOLS WITH THE SPREAD OF COVID-19 IN THE UNITED STATES: COUNTY-LEVEL PANEL DATA ANALYSIS
Authors: Chernozhukov Victor , Kasahara Hiroyuki , Schrimpf Paul 
Published: February 2021

AbstractThis paper empirically examines how the opening of K-12 schools and colleges is associated with the spread of COVID-19 using county-level panel data in the United States. Using data on foot traffic and K-12 school opening plans, we analyze how an increase in visits to schools and opening schools with different teaching methods (in-person, hybrid, and remote) is related to the 2-weeks forward growth rate of confirmed COVID-19 cases. Our debiased panel data regression analysis with a set of county dummies, interactions of state and week dummies, and other controls shows that an increase in visits to both K-12 schools and colleges is associated with a subsequent increase in case growth rates. The estimates indicate that fully opening K-12 schools with in-person learning is associated with a 5 (SE = 2) percentage points increase in the growth rate of cases. We also find that the positive association of K-12 school visits or in-person school openings with case growth is stronger for counties that do not require staff to wear masks at schools. These results have a causal interpretation in a structural model with unobserved county and time confounders. Sensitivity analysis shows that the baseline results are robust to timing assumptions and alternative specifications.
Self-testing for the detection of SARS-CoV-2 infection with rapid antigen tests
Authors: Stohr J. J.J.M. , Zwart V. F. , Goderski G. , Meijer A. , Nagel-Imming C. R.S. , Kluytmans-van den Bergh M.F.Q. , Pas S. D. , van den Oetelaar F. , Hellwich M. , Gan K. H. , Rietveld A. , Verweij J.J. , Murk J. L. , van den Bijllaardt W. , Kluytmans J. A. J. W. 
Published: February 2021

AbstractIntroductionSelf-testing for COVID-19 infection with lateral flow assay SARS-CoV-2 rapid antigen detection tests (RDT), provides rapid results and could enable frequent and extensive testing in the community, thereby improving the control of SARS-CoV-2. The objective of this study is to evaluate the performance of self-testing using RDT without assistance.MethodsParticipants visiting a municipal SARS-CoV-2 testing centre, received self-testing kits containing either the BD Veritor System (BD RDT) or Roche SARS-CoV-2 antigen detection test (Roche RDT). Oro-nasopharyngeal swabs were collected from the participants for qRT-PCR testing. As a proxy for contagiousness, viral culture was performed on a selection of qRT-PCR positive samples to determine the Ct-value at which the chance of a positive culture was dropping below 0.5 (Ct-value cut-off). Sensitivity and specificity of self-testing were compared to qRT-PCR with a Ct-value below the Ct value cut-off. Determinants independently associated with a false-negative self-test result were determined.ResultsA total of 3,215 participants were included (BD RDT n=1604; Roche RDT n=1611). Sensitivity and specificity of self-testing compared to the qRT-PCR results with Ct-value below the Ct-value cut-off was 78.0% (95% CI:72.5-82.8) and 99.4% (95%CI: 99.0-99.6) respectively. Determinants independently associated with a false-negative self-testing results were: higher age, low viral load and finding self-testing difficult.DiscussionSelf-testing using currently available RDT’s has a high specificity and relatively high sensitivity to identify individuals with a high probability of contagiousness. The performance of two tests were comparable. This application has the potential for frequent and extensive testing which may be an aid to lift restrictions to society while controlling the spread of SARS-CoV-2.
The spatio-temporal distribution of COVID-19 infection in England between January and June 2020
Authors: Elson Richard , Davies Tilman M. , Lake Iain R. , Vivancos Roberto , Blomquist Paula B. , Charlett Andre , Dabrera Gavin 
Published: February 2021

AbstractThe spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed.A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk.Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first six months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on the 23rdMarch 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout.In terms of controlling transmission, the most important practical application is the accurate identification of areaswithinregions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.
Prognostic value and peripheral immunologic correlates of early FDG PET response imaging in a phase II trial of risk-adaptive chemoradiation for unresectable non-small cell lung cancer
Authors: Bowen Stephen R. , Hippe Daniel S. , Thomas Hannah M. , Sasidharan Balukrishna , Lampe Paul D. , Baik Christina S. , Eaton Keith D. , Lee Sylvia , Martins Renato G. , Santana-Davila Rafael , Chen Delphine , Kinahan Paul E. , Miyaoka Robert S. , Vesselle Hubert J. , Houghton A. McGarry , Rengan Ramesh , Zeng Jing 
Published: February 2021

AbstractIntroductionWe hypothesized that FDG PET imaging during chemoradiation for unresectable non-small cell lung cancer (NSCLC) is prognostic for survival, and that tumor PET response is correlated with peripheral T-cell function.Methods45 patients with AJCCv7 stage IIB-IIIB NSCLC enrolled on the phase II FLARE-RT trial and received platinum-doublet chemotherapy concurrent with 6 weeks of radiation (NCT02773238). FDG PET imaging was performed prior to treatment start and after 24 Gy of radiation (week 3). PET response status was prospectively defined by multifactorial radiologic interpretation. PET responders received 60 Gy in 30 fractions, while non-responders received concomitant boosts to 74 Gy in 30 fractions. Peripheral blood was drawn synchronously with PET imaging, from which germline DNA sequencing, T-cell receptor (TCR) sequencing, and plasma cytokines analysis were performed.ResultsMedian follow-up was 18.8 months, 1-year overall survival (OS) 82%, 1-year progression-free survival (PFS) 53%, and 1-year locoregional control (LRC) 88%. Higher mid-treatment PET total lesion glycolysis was detrimental to OS (1-yr 87% vs. 63%, p<0.001), PFS (1-yr 60% vs. 26%, p=0.044) and LRC (1-yr 94% vs. 65%, p=0.012), even after adjustment for clinical/treatment factors. Higher PD-L1 tumor proportion score (TPS) was correlated with PET response (p=0.017): 6/6 patients with high PD-L1 (TPS>50%) were classified as PET responders, while 4/5 patients classified as PET non-responders had negative PD-L1 (TPS<1%). Higher TCR richness and clone distribution slope was associated with improved OS (p=0.018-0.035); clone distribution slope was correlated with PET response (p=0.031). Germline DNA alterations in immunologic pathways had an outsized effect on OS and PET response; of the top 30 SNPs ranked by association with PET response status (p<0.016), a plurality (13/30) came from immunologic pathways.ConclusionsMid-chemoradiation PET imaging is prognostic for survival; PET response may be linked to tumor and peripheral T-cell biomarkers.
Simple Scoring Tool to Estimate Risk of Hospitalization and Mortality in Ambulatory and Emergency Department Patients with COVID-19
Authors: Webb Brandon J. , Levin Nicholas M. , Grisel Nancy , Brown Samuel M. , Peltan Ithan D. , Spivak Emily S. , Shah Mark , Stenehjem Eddie , Bledsoe Joseph 
Published: February 2021

AbstractBackgroundAccurate methods of identifying patients with COVID-19 who are at high risk of poor outcomes has become especially important with the advent of limited-availability therapies such as monoclonal antibodies. Here we describe development and validation of a simple but accurate scoring tool to classify risk of hospitalization and mortality.MethodsAll consecutive patients testing positive for SARS-CoV-2 from March 25-October 1, 2020 within the Intermountain Healthcare system were included. The cohort was randomly divided into 70% derivation and 30% validation cohorts. A multivariable logistic regression model was fitted for 14-day hospitalization. The optimal model was then adapted to a simple, probabilistic score and applied to the validation cohort and evaluated for prediction of hospitalization and 28-day mortality.Results22,816 patients were included; mean age was 40 years, 50.1% were female and 44% identified as non-white race or Hispanic/Latinx ethnicity. 6.2% required hospitalization and 0.4% died. Criteria in the simple model included: age (0.5 points per decade); high-risk comorbidities (2 points each): diabetes mellitus, severe immunocompromised status and obesity (body mass index≥30); non-white race/Hispanic or Latinx ethnicity (2 points), and 1 point each for: male sex, dyspnea, hypertension, coronary artery disease, cardiac arrythmia, congestive heart failure, chronic kidney disease, chronic pulmonary disease, chronic liver disease, cerebrovascular disease, and chronic neurologic disease. In the derivation cohort (n=16,030) area under the receiver-operator characteristic curve (AUROC) was 0.82 (95% CI 0.81-0.84) for hospitalization and 0.91 (0.83-0.94) for 28-day mortality; in the validation cohort (n=6,786) AUROC for hospitalization was 0.8 (CI 0.78-0.82) and for mortality 0.8 (CI 0.69-0.9).ConclusionA prediction score based on widely available patient attributes accurately risk stratifies patients with COVID-19 at the time of testing. Applications include patient selection for therapies targeted at preventing disease progression in non-hospitalized patients, including monoclonal antibodies. External validation in independent healthcare environments is needed.
A rapid review of equity considerations in large-scale testing campaigns during infectious disease epidemics
Authors: Ost Katarina , Duquesne Louise , Duguay Claudia , Traverson Lola , Mathevet Isadora , Ridde Valéry , Zinszer Kate 
Published: February 2021

ABSTRACTContextLarge-scale testing is an intervention that is instrumental for infectious disease control and a central tool for the COVID-19 pandemic. Our rapid review aimed to identify if and how equity has been considered in large-scale testing initiatives.MethodsWe searched Web of Science and PubMed in November 2020 and followed PRISMA recommendations for scoping reviews. Articles were analyzed using descriptive and thematic analysis.ResultsOur search resulted in 291 studies of which 41 were included for data extraction after full article screening. Most of the included articles (83%) reported on HIV-related screening programs, while the remaining programs focused on other sexually transmitted infections (n=3) or COVID-19 (n=4). None of the studies presented a formal definition of (in)equity in testing, however, 23 articles did indirectly include elements of equity in the program or intervention design, largely through the justification of their target population.ConclusionThe studies included in our rapid review did not explicitly consider equity in their design or evaluation. It is imperative that equity is incorporated into the design of infectious disease testing programs and serves as an important reminder of how equity considerations are needed for SARS-CoV-2 testing and vaccination programs.
High-resolution longitudinal serum proteome trajectories in COVID-19 reveal patients-specific seroconversion
Authors: Geyer Philipp E. , Arend Florian M. , Doll Sophia , Louiset Marie-Luise , Winter Sebastian Virreira , Müller-Reif Johannes B. , Torun Furkan M. , Weigand Michael , Eichhorn Peter , Bruegel Mathias , Strauss Maximilian T. , Holdt Lesca M. , Mann Matthias , Teupser Daniel 
Published: February 2021

AbstractBiomarkers for COVID-19 are urgently needed. Here we bring the powerful technology of mass spectrometry (MS)-based proteomics to bear on this challenge. We measured serum proteomes of COVID-19 patients and symptomatic, but PCR-negative controls, in a time-resolved manner. In 262 controls and 458 longitudinal samples (average of 31 days) of 31 patients, hospitalized for COVID-19, a remarkable 26% of proteins changed significantly. Bioinformatics analyses revealed co-regulated groups and shared biological functions. Proteins of the innate immune system such as CRP, SAA1, CD14, LBP and LGALS3BP decreased early in the time course. In contrast, regulators of coagulation (APOH, FN1, HRG, KNG1, PLG) and lipid homeostasis (APOA1, APOC1, APOC2, APOC3, PON1) increased over the course of the disease. A global correlation map provides a systems-wide functional association between proteins, biological processes and clinical chemistry parameters. Importantly, five SARS-CoV-2 immunoassays against antibodies revealed excellent correlations with an extensive range of immunoglobulin regions, which were quantified by MS-based proteomics. The high-resolution profile of all immunoglobulin regions showed individual-specific differences and commonalities of potential pathophysiological relevance.Graphical AbstractHighlightsA total of 720 proteomes of 262 symptomatic controls and 458 longitudinal samples (average 31 days) of hospitalized COVID-19 cases were analyzed26% of the 502 quantified proteins significantly changed in COVID-19 patientsThe innate immune and the coagulation system were strongly regulatedMS-based profiles of immunoglobulin regions allow the detection of seroconversion in a highly detailed fashion on the patient levelITIH4 may be a prospective marker of COVID-19 mortality
Estimating DNA methylation potential energy landscapes from nanopore sequencing data
Authors: Abante Jordi , Kambhampati Sandeep , Feinberg Andrew P. , Goutsias John 
Published: February 2021

AbstractHigh-throughput third-generation sequencing devices, such as the Oxford Nanopore Technologies (ONT) MinION sequencer, can generate long reads that span thousands of bases. This new technology opens the possibility of considering a wide range of epigenetic modifications and provides the capability of interrogating previously inaccessible regions of the genome, such as highly repetitive regions, as well as of performing comprehensive allele-specific methylation analysis, among other applications. It is well-known, however, that detection of DNA methylation from nanopore data results in a substantially reduced per-read accuracy when comparing to WGBS, due to noise introduced by the sequencer and its underlying chemistry. It is therefore imperative that methods are developed for the reliable modeling and analysis of the DNA methylation landscape using nanopore data. Here we introduce such method that takes into account the presence of noise introduced by the ONT sequencer and, by using simulations, we provide evidence of its potential. The proposed approach establishes a solid foundation for the development of a comprehensive framework for the statistical analysis of DNA methylation, and possibly of other epigenetic marks, using third-generation sequencing.
The role of memory in non-genetic inheritance and its impact on cancer treatment resistance
Authors: Cassidy Tyler , Nichol Daniel , Robertson-Tessi Mark , Craig Morgan , Anderson Alexander R.A. 
Published: February 2021

AbstractIntra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.Author summaryWe propose a simple mathematical model to understand the role of phenotypic plasticity and non-genetic inheritance in driving therapy resistance in cancer. We identify the role of non-genetic inheritance on treatment resistance and use a variety of analytical and numerical techniques to understand the impact of phenotypic plasticity on population fitness and dynamics. We further use our model to study the role of phenotypic heterogeneity in therapeutic resistance in a genetically identical non-small cell lung cancer population. Finally, we combine analytical perspectives and techniques from the theory of structured populations, renewal equations and infinite dimensional dynamical systems to derive a model informed therapeutic strategy that both drives tumour eradication while avoiding competitive release of a drug-tolerant subpopulation. These results exemplify the potential of using mathematical techniques to identify therapeutic strategies to guide the evolution of a heterogeneous tumour.
The contribution of electrostatics to hydrogen exchange in the unfolded protein state
Authors: Dass Rupashree , Corlianò Enrico , Mulder Frans A. A. 
Published: February 2021

AbstractAlthough electrostatics have long been recognized to play an important role in hydrogen exchange (HX) with solvent, the quantitative assessment of its magnitude in the unfolded state has hitherto been lacking. This limits the utility of HX as a quantitative method to study protein stability, folding and dynamics. Using the intrinsically disordered human protein α-synuclein as a proxy for the unfolded state, we show that a hybrid mean-field approach can effectively compute the electrostatic potential at all backbone amide positions along the chain. From the electrochemical potential a fourfold reduction in hydroxide concentration near the protein backbone is predicted for the C-terminal domain, a prognosis that is in direct agreement with experimentally-derived protection factors from NMR spectroscopy. Thus, impeded HX for the C-terminal region of α-synuclein is not the result of intramolecular hydrogen bonding and/or structure formation.
Comparative analysis of host-associated variation in Phytophthora cactorum
Authors: Nellist Charlotte F. , Armitage Andrew D. , Bates Helen J. , Sobczyk Maria K. , Luberti Matteo , Lewis Laura A. , Harrison Richard J. 
Published: February 2021

ABSTRACTPhytophthora cactorum is often described as a generalist pathogen, with isolates causing disease in a range of plant species. It is the causative agent of two diseases in the cultivated strawberry, crown rot (CR; causing whole plant collapse) and leather rot (LR; affecting the fruit). In the cultivated apple, P. cactorum causes girdling bark rots on the scion (collar rot) and rootstock (crown rot), as well as necrosis of the fine root system (root rot) and fruit rots. We investigated evidence for host specialisation within P. cactorum through comparative genomic analysis of 18 isolates. Whole genome phylogenetic analysis provided genomic support for discrete lineages within P. cactorum, with well supported non-recombing clades for strawberry CR and apple infecting isolates specialised to strawberry crowns and apple tissue. Isolates of strawberry CR are genetically similar globally, while there is more diversity in apple-infecting isolates. We sought to identify the genetic basis of host specialisation, demonstrating gain and loss of effector complements within the P. cactorum phylogeny, representing putative determinants of host boundaries. Transcriptomic analysis highlighted that those effectors found to be specific to a single host or expanded in the strawberry lineage are amongst those most highly expressed during infection of strawberry and give a wider insight into the key effectors active during strawberry infection. Many effectors that had homologs in other Phytophthoras that have been characterised as avirulence genes were present but not expressed in our tested isolate. Our results highlight several RxLR-containing effectors that warrant further investigation to determine whether they are indeed virulence factors and host-specificity determinants for strawberry and apple. Furthermore, additional work is required to determine whether these effectors are suitable targets to focus attention on for future resistance breeding efforts.