bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mortality reduction in 46 severe Covid-19 patients treated with hyperimmune plasma. A proof of concept single arm multicenter interventional trial
Authors: Perotti Cesare , Baldanti Fausto , Bruno Raffaele , Del Fante Claudia , Seminari Elena , Casari Salvatore , Percivalle Elena , Glingani Claudia , Musella Valeria , Belliato Mirko , Garuti Martina , Meloni Federica , Frigato Marilena , Di Sabatino Antonio , Klersy Catherine , De Donno Giuseppe , Franchini Massimo 
Published: May 2020

AbstractBACKGROUNDHyperimmune plasma from Covid-19 convalescent is a potential treatment for severe Covid-19.METHODSWe conducted a multicenter one arm proof of concept interventional study. Patients with Covid-19 disease with moderate-to-severe Acute Respiratory Distress Syndrome, elevated C-reactive Protein and need for mechanical ventilation and/or CPAP were enrolled. One to three 250-300 ml unit of hyperimmune plasma (neutralizing antibodies titer ≥1:160) were administered. Primary outcome was 7-days hospital mortality. Secondary outcomes were PaO2/FiO2, laboratory and radiologic changes, as well as weaning from mechanical ventilation and safety.RESULTSThe study observed 46 patients from March, 25 to April, 21 2020. Patients were aged 63, 61% male, 30 on CPAP and 7 intubated. PaO2/FiO2 was 128 (SD 47). Symptoms and ARDS duration were 14 (SD 7) and 6 days (SD 3). Three patients (6.5%) died within 7 days. The upper one-sided 90%CI was 13.9%, allowing to reject the null hypothesis of a 15% mortality. PaO2/FiO2 increased by 112 units (95%CI 82 to142) in survivors, the chest radiogram severity decreased in 23% (95%CI 5% to 42%); CRP, Ferritin and LDH decreased by 60, 36 and 20% respectively. Weaning from CPAP was obtained in 26/30 patients and 3/7 were extubated. Five serious adverse events occurred in 4 patients (2 likely, 2 possible treatment related).CONCLUSIONSHyperimmune plasma in Covid-19 shows promising benefits, to be confirmed in a randomized controlled trial. This proof of concept study could open to future developments including hyperimmune plasma banking, development of standardized pharmaceutical products and monoclonal antibodies.
New models of transmission of COVID-19 with time under the influence of meteorological determinants
Authors: Adhikari Atin , Ghosh Shilpi , Sen Moon M. , Adhikari Rathin 
Published: May 2020

AbstractObjectivesThis work aimed at modeling the progressions of COVID-19 cases in time in relation to meteorological factors in large cities of Brazil, Italy, Spain, and USA, and finding the viability of SARS-CoV-2 virus in different weather conditions based on models.MethodsNew models constructed showing the relationship of the I′ (the number of infected individuals divided by the total population of a city) with the independent variables -time, temperature, relative humidity, and wind velocity. The regression models fitting in the data were statistically validated by: 1) plot of observed and predicted response; 2) standardized residual plots showing the characteristics of errors; 3) adjusted value; 4) the p value for the parameters associated with the various independent variables; and 5) the predictive power of the model beyond data points.ResultsModels indicate that 1) the transmission of COVID-19 could be relatively high either for elevated temperatures with lower relative humidity or for lower temperatures with higher relative humidity conditions; 2) disease transmission is expected to be reduced more with higher wind velocity; 3) the rate of increase in the number of COVID-19 cases increases in one model with a constant rate and in the other two with varying rates in time. These transmission features seem to have connections with the structural components of the SARS-CoV-2 virus. Under suitable meteorological conditions, the partial natural disappearance of COVID-19 pandemic could be possible.ConclusionNew models for I′ may be considered to understand the viability of the virus in the environment and future transmission of COVID-19.
ComplementaryIn VivoApproaches Reveal Quiescent Melanocytes in Anagen Outside the Hair Follicle Bulge
Authors: Tandukar Bishal , Joshi Sandeep S. , Pan Li , Hornyak Thomas J. 
Published: May 2020

ABSTRACTMelanocyte stem cells (McSCs) are key components of the hair follicle (HF) stem cell system that are derived from neural crest during embryogenesis and are responsible for regeneration of differentiated melanocytes during successive HF cycles. Our previous research has shown presence of two subsets of phenotypically and functionally distinct McSCs exist in murine telogen HFs, CD34+ McSCs in the bulge/lower permanent portion (LPP) and CD34− McSCs in the secondary hair germ (SHG). Whether these subsets are maintained independently or exist in a developmental hierarchy is not yet known. UsingDct-H2BGFP mice, we analyzed the quiescent and proliferative properties of McSCs and melanocytes in anagen and telogen. We found unexpectedly that Kit+Nestin− quiescent melanocytes are maintained outside of the bulge/LPP region throughout anagen in addition to the Kit+Nestin+ quiescent melanocytes of the bulge/LPP. Both subpopulations express lower levels of melanocyte differentiation markers Mitf, Pax3, Dct, Tyrp1 and Tyr compared to differentiated melanocytes of the HF bulb/matrix. These results suggest that quiescent melanocytes localized in the outer root sheath, both in and below the bulge/LPP) retain the stem cell phenotype observed in quiescent McSCs during telogen. This finding has implications for maintenance of distinct subsets of McSCs throughout successive HF cycles.
Proteoform Identification by Combining RNA-Seq and Top-down Mass Spectrometry
Authors: Chen Wenrong , Liu Xiaowen 
Published: May 2020

ABSTRACTIn proteogenomic studies, genomic and transcriptomic variants are incorporated into customized protein databases for the identification of proteoforms, especially proteoforms with sample-specific variants. Most proteogenomic research has been focused on combining genomic or transcriptomic data with bottom-up mass spectrometry data. In the last decade, top-down mass spectrometry has attracted increasing attention because of its capacity to identify various proteoforms with alterations. However, top-down proteogenomics, in which genomic or transcriptomic data are combined with top-down mass spectrometry data, has not been widely adopted, and there still lack of software tools for top-down proteogenomic data analysis. In this paper, we introduce TopPG, a proteogenomic tool for identifying proteoforms with genetic alterations and alternative splicing events. Experiments on top-down proteogenomic data of DLD-1 colorectal cancer cells showed that TopPG can confidently identify proteoforms with sample-specific alterations.
Efficacy of a novel SARS-CoV-2 detection kit without RNA extraction and purification
Authors: Fukumoto Tatsuya , Iwasaki Sumio , Fujisawa Shinichi , Hayasaka Kasumi , Sato Kaori , Oguri Satoshi , Taki Keisuke , Nakakubo Sho , Kamada Keisuke , Yamashita Yu , Konno Satoshi , Nishida Mutsumi , Sugita Junichi , Teshima Takanori 
Published: May 2020

AbstractRapid detection of SARS-CoV-2 is critical for the diagnosis of coronavirus disease 2019 (COVID-19) and preventing the spread of the virus. A novel “2019 Novel Coronavirus Detection Kit (nCoV-DK)” halves detection time by eliminating the steps of RNA extraction and purification. We evaluated concordance between the nCoV-DK and direct PCR. The virus was detected in 53/71 fresh samples by the direct method and 55/71 corresponding frozen samples by the nCoV-DK. The overall concordance rate of the virus detection between the two methods was 94.4% (95% CI, 86.2-98.4). Concordance rates were 95.2% (95% CI, 83.8-99.4), 95.5% (95% CI, 77.2-99.9), 85.7% (95% CI, 42.1-99.6) in nasopharyngeal swab, saliva, and sputum samples, respectively. These results indicate that the nCoV-DK effectively detects SARS-CoV-2 in all types of the samples including saliva, while reducing time required for detection, labor, and risk of human error.
HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population
Authors: Sasso Ariane M. , Datta Suparno , Jeitler Michael , Steckhan Nico , Kessler Christian S. , Michalsen Andreas , Arnrich Bert , Böttinger Erwin 
Published: May 2020

Abstract.The state of the art for monitoring hypertension relies on measuring blood pressure (BP) using uncomfortable cuff-based devices. Hence, for increased adherence in monitoring, a better way of measuring BP is needed. That could be achieved through comfortable wearables that contain photoplethysmography (PPG) sensors. There have been several studies showing the possibility of statistically estimating systolic and diastolic BP (SBP/DBP) from PPG signals. However, they are either based on measurements of healthy subjects or on patients on intensive care units (ICUs). Thus, there is a lack of studies with patients out of the normal range of BP and with daily life monitoring out of the ICUs. To address this, we created a dataset (HYPE) composed of data from hypertensive subjects that executed a stress test and had 24-hours monitoring. We then trained and compared machine learning (ML) models to predict BP. We evaluated handcrafted feature extraction approaches vs image representation ones and compared different ML algorithms for both. Moreover, in order to evaluate the models in a different scenario, we used an openly available set from a stress test with healthy subjects (EVAL). The best results for our HYPE dataset were in the stress test and had a mean absolute error (MAE) in mmHg of 8.79 (±3.17) for SBP and 6.37 (±2.62) for DBP; for our EVAL dataset it was 14.74 (±4.06) and 7.12 (±2.32) respectively. Although having tested a range of signal processing and ML techniques, we were not able to reproduce the small error ranges claimed in the literature. The mixed results suggest a need for more comparative studies with subjects out of the intensive care and across all ranges of blood pressure. Until then, the clinical relevance of PPG-based predictions in daily life should remain an open question.
Reliability of P3 Event-Related Potential during Working Memory Across the Spectrum of Cognitive Aging
Authors: Devos Hannes , Burns Jeffrey , Liao Ke , Ahmadnezhad Pedram , Mahnken Jonathan D. , Brooks William M. , Gustafson Kathleen 
Published: May 2020

AbstractEvent-related potentials (ERPs) offer unparalleled temporal resolution in tracing distinct electrophysiological processes related to normal and pathological cognitive aging. The stability of ERPs in older individuals, who inherently show more intraindividual variability in cognitive functions, has not been established. In this test-retest reliability study, 39 older individuals (age 74.10 (5.4) years; 23 (59%) women; 15 non β-amyloid elevated, 16 β-amyloid elevated, 8 cognitively impaired) with scores on the Montreal Cognitive Assessment (MOCA) ranging between 3 and 30 completed a working memory (n-back) test with three levels of difficulty at baseline and two-week follow-up. Stability of the ERP was evaluated on grand averaged task effects for both visits. P3 peak amplitude and latency were measured in frontal channels. P3 peak amplitude at Fz, our main outcome variable, showed excellent reliability in 0-back (intraclass correlation coefficient (ICC), 95% confidence interval = 0.82 (0.67 – 0.90) and 1-back (ICC = 0.87 (0.76 – 0.93), however, only fair reliability in 2-back (ICC = 0.53 (0.09 – 0.75). Reliability of P3 peak latencies was substantially lower, with ICCs ranging between 0.17 for 2-back and 0.54 for 0-back. Generalized linear mixed models showed no confounding effect of age, group, or task difficulty on stability of P3 amplitude and latency of Fz. By contrast, MOCA scores tended to negatively correlate with P3 amplitude of Fz (p=0.07). We conclude that P3 peak amplitude and latency provide a stable measure of electrophysiological processes in older individuals. However, impaired cognition may affect the stability of the ERP response.
Study protocol for COvid-19 Vascular sERvice (COVER) study: The impact of the COVID-19 pandemic on the provision, practice and outcomes of vascular surgery
Authors: Benson Ruth A 
Published: May 2020

ABSTRACTBackgroundThe novel Coronavirus Disease 2019 (COVID-19) pandemic is having a profound impact on global healthcare. Shortages in staff, operating theatre space and intensive care beds has led to a significant reduction in the provision of surgical care. Even vascular surgery, often insulated from resource scarcity due to its status as an urgent specialty, has limited capacity due to the pandemic. Furthermore, many vascular surgical patients are elderly with multiple comorbidities putting them at increased risk of COVID-19 and its complications. There is an urgent need to investigate the impact on patients presenting to vascular surgeons during the COVID-19 pandemic.Methods and AnalysisThe COvid-19 Vascular sERvice (COVER) study has been designed to investigate the worldwide impact of the COVID-19 pandemic on vascular surgery, at both service provision and individual patient level. COVER is running as a collaborative study through the Vascular and Endovascular Research Network (VERN) with the support of numerous national (Vascular Society of Great Britain and Ireland, British Society of Endovascular Therapy, British Society of Interventional Radiology, Rouleaux Club) and an evolving number of international organisations (Vascupedia, SingVasc, Audible Bleeding (USA), Australian and New Zealand Vascular Trials Network (ANZVTN)). The study has 3 ‘Tiers’: Tier 1 is a survey of vascular surgeons to capture longitudinal changes to the provision of vascular services within their hospital; Tier 2 captures data on vascular and endovascular procedures performed during the pandemic; and Tier 3 will capture any deviations to patient management strategies from prepandemic best practice. Data submission and collection will be electronic using online survey tools (Tier 1: SurveyMonkey® for service provision data) and encrypted data capture forms (Tiers 2 and 3: REDCap® for patient level data). Tier 1 data will undergo real-time serial analysis to determine longitudinal changes in practice, with country-specific analyses also performed. The analysis of Tier 2 and Tier 3 data will occur on completion of the study as per the prespecified statistical analysis plan.Ethical ApprovalEthical approval from the UK Health Research Authority has been obtained for Tiers 2 and 3 (20/NW/0196 Liverpool Central). Participating centres in the UK will be required to seek local research and development approval. Non-UK centres will need to obtain a research ethics committee or institutional review board approvals in accordance with national and/or local requirements.ISRCTN: 80453162 (https://doi.org/10.1186/ISRCTN80453162)Ethical Approval: 20/NW/0196 Liverpool Central, IRAS: 282224
Lessons from movement ecology for the return to work: modeling contacts and the spread of COVID-19
Authors: Shaw Allison K. , White Lauren A. , Michalska-Smith Matthew , Borer Elizabeth T. , Craft Meggan E. , Seabloom Eric W. , Snell-Rood Emilie , Travisano Michael 
Published: May 2020

AbstractHuman behavior (movement, social contacts) plays a central role in the spread of pathogens like SARS- CoV-2. The rapid spread of SARS-CoV-2 was driven by global human movement, and initial lockdown measures aimed to localize movement and contact in order to slow spread. Thus, movement and contact patterns need to be explicitly considered when making reopening decisions, especially regarding return to work. Here, as a case study, we consider the initial stages of resuming research at a large research university, using approaches from movement ecology and contact network epidemiology. First, we develop a dynamical pathogen model describing movement between home and work; we show that limiting social contact, via reduced people or reduced time in the workplace are fairly equivalent strategies to slow pathogen spread. Second, we develop a model based on spatial contact patterns within a specific office and lab building on campus; we show that restricting on-campus activities to labs (rather than labs and offices) could dramatically alter (modularize) contact network structure and thus, potentially reduce pathogen spread by providing a workplace mechanism to reduce contact. Here we argue that explicitly accounting for human movement and contact behavior in the workplace can provide additional strategies to slow pathogen spread that can be used in conjunction with ongoing public health efforts.
Modeling Plasmodium falciparum Diagnostic Test Sensitivity using Machine Learning with Histidine-Rich Protein 2 Variants
Authors: Ford Colby T. , Alemayehu Gezahegn , Blackburn Kayla , Lopez Karen , Dieng Cheikh Cambel , Lo Eugenia , Golassa Lemu , Janies Daniel 
Published: May 2020

AbstractMalaria, predominantly caused by Plasmodium falciparum, poses one of largest and most durable health threats in the world. Previously, simplistic regression-based models have been created to characterize malaria rapid diagnostic test performance, though these models often only include a couple genetic factors. Specifically, the Baker et al., 2005 model uses two types of particular repeats in histidine-rich protein 2 (PfHRP2) to describe a P. falciparum infection [1], though the efficacy of this model has waned over recent years due to genetic mutations in the parasite. In this work, we use a dataset of 102 P. falciparum PfHRP2 genetic sequences collected in Ethiopia and derived a larger set of motif repeat matches for use in generating a series of diagnostic machine learning models. Here we show that the usage of additional and different motif repeats proves effective in predicting infection. Furthermore, we use machine learning model explanability methods to highlight which of the repeat types are most important, thereby showcasing a novel methodology for identifying potential targets for future versions of rapid diagnostic tests.
Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea
Authors: Yu Xinhua , Duan Jiasong , Jiang Yu , Zhang Hongmei 
Published: May 2020

AbstractObjectivesElderly people had suffered disproportional burden of COVID-19. We hypothesized that males and females in different age groups might have different epidemic trajectories.MethodsUsing publicly available data from South Korea, daily new COVID-19 cases were fitted with generalized additive models, assuming Poisson and negative binomial distributions. Epidemic dynamics by age and gender groups were explored with interactions between smoothed time terms and age and gender.ResultsA negative binomial distribution fitted the daily case counts best. Interaction between the dynamic patterns of daily new cases and age groups was statistically significant (p<0.001), but not with gender group. People aged 20-39 years led the epidemic processes in the society with two peaks: one major peak around March 1 and a smaller peak around April 7, 2020. The epidemic process among people aged 60 or above was trailing behind that of younger people with smaller magnitude. After March 15, there was a consistent decline of daily new cases among elderly people, despite large fluctuations of case counts among young adults.ConclusionsAlthough young people drove the COVID-19 epidemic in the whole society with multiple rebounds, elderly people could still be protected from virus infection after the peak of epidemic.
ACE2 polymorphisms as potential players in COVID-19 outcome
Authors: Khayat André Salim , de Assumpção Paulo Pimentel , Khayat Bruna Claudia Meireles , Araújo Taíssa Maíra Thomaz , Batista-Gomes Jéssica Almeida , Imbiriba Luciana Carvalho , Ishak Geraldo , de Assumpção Paula Baraúna , Moreira Fabiano Cordeiro , Burbano Rommel Rodriguez , Ribeiro-dos-Santos André , Ribeiro-dos-Santos Ândrea Kelly , dos Santos Ney Pereira Carneiro , dos Santos Sidney Emmanuel Batista 
Published: May 2020

AbstractThe clinical condition COVID-19, caused by SARS-CoV-2, was declared a pandemic by the WHO in March 2020. Currently, there are more than 5 million cases worldwide, and the pandemic has increased exponentially in many countries, with different incidences and death rates among regions/ethnicities and, intriguingly, between sexes. In addition to the many factors that can influence these discrepancies, we suggest a biological aspect, the genetic variation at the viral S protein receptor in human cells, ACE2 (angiotensin I-converting enzyme 2), which may contribute to the worse clinical outcome in males and in some regions worldwide. We performed exomics analysis in native and admixed South American populations, and we also conducted in silico genomics databank investigations in populations from other continents. Interestingly, at least ten polymorphisms in coding, noncoding and regulatory sites were found that can shed light on this issue and offer a plausible biological explanation for these epidemiological differences. In conclusion, ACE2 polymorphisms should influence epidemiological discrepancies observed among ancestry and, moreover, between sexes.
Monitoring and forecasting the number of reported and unreported cases of the COVID-19 epidemic in Brazil using Particle Filter
Authors: Dutra J. C. S. , da Silva W. B. , da Costa J. M. J. 
Published: May 2020

AbstractIn this paper, we combine algorithm of Liu & West for the Particle Filter (PF) with SIRU-type epidemic model to monitor and forecast cases of Covid-19 in Brazil from February up to September. We filter the number of cumulative reported cases and estimate model parameters and more importantly unreported infectious cases (asymptomatic and symptomatic infectious individuals). The parameters under study are related to the attenuation factor of the transmission rate and the fraction of asymptomatic infectious becoming reported as symptomatic infectious. Initially, the problem is analysed through Particle Swarm Optimization (PSO) based simulations to provide initial guesses, which are then refined by means of PF simulations. Subsequently, two additional steps are performed to verify the capability of the adjusted model to predict and forecast new cases. According to the results, the pandemic peak is expected to take place in mid-June 2020 with about 25,000 news cases per day. As medical and hospital resources are limited, this result shows that public health interventions are essential and should not be relaxed prematurely, so that the coronavirus pandemic is controlled and conditions are available for the treatment of the most severe cases.
Integrated sample inactivation, amplification, and Cas13-based detection of SARS-CoV-2
Authors: Arizti-Sanz Jon , Freije Catherine A. , Stanton Alexandra C. , Boehm Chloe K. , Petros Brittany A. , Siddiqui Sameed , Shaw Bennett M. , Adams Gordon , Kosoko-Thoroddsen Tinna-Solveig F. , Kemball Molly E. , Gross Robin , Wronka Loni , Caviness Katie , Hensley Lisa E. , Bergman Nicholas H. , MacInnis Bronwyn L. , Lemieux Jacob E. , Sabeti Pardis C. , Myhrvold Cameron 
Published: May 2020

AbstractThe COVID-19 pandemic has highlighted that new diagnostic technologies are essential for controlling disease transmission. Here, we develop SHINE (SHERLOCK and HUDSON Integration to Navigate Epidemics), a sensitive and specific integrated diagnostic tool that can detect SARS-CoV-2 RNA from unextracted samples. We combine the steps of SHERLOCK into a single-step reaction and optimize HUDSON to accelerate viral inactivation in nasopharyngeal swabs and saliva. SHINE’s results can be visualized with an in-tube fluorescent readout — reducing contamination risk as amplification reaction tubes remain sealed — and interpreted by a companion smartphone application. We validate SHINE on 50 nasopharyngeal patient samples, demonstrating 90% sensitivity and 100% specificity compared to RT-PCR with a sample-to-answer time of 50 minutes. SHINE has the potential to be used outside of hospitals and clinical laboratories, greatly enhancing diagnostic capabilities.