bluuebunny/crossref_metadata_2025_split huggingface dataset:
Visualizing orientation-specific relaxation-diffusion features mapped onto orientation distribution functions estimated via nonparametric Monte Carlo MRI signal inversion
Authors: de Almeida Martins João P. , Tax Chantal M. W. , Reymbaut Alexis , Szczepankiewicz Filip , Jones Derek K. , Topgaard Daniel 
Published: May 2020

ABSTRACTDiffusion MRI techniques are widely used to studyin vivochanges in the human brain connectome. However, to resolve and characterise white matter fibres in heterogeneous diffusion MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and restrictive constraints. We have recently introduced a 5D relaxation-diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo-times in order to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation-diffusion distributions where contributions from different sub-voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre-specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins in order to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation-specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along distinct fibre bundles. If combined with fibre-tracking algorithms, the methodology presented in this work may be useful for investigating the microstructural properties along individual white matter pathways.
Bepridil is potent against SARS-CoV-2 In Vitro
Authors: Vatansever Erol C. , Yang Kai , Kratch Kaci C. , Drelich Aleksandra , Cho Chia-Chuan , Mellott Drake M. , Xu Shiqing , Tseng Chien-Te K. , Liu Wenshe Ray 
Published: May 2020

ABSTRACTGuided by a computational docking analysis, about 30 FDA/EMA-approved small molecule medicines were characterized on their inhibition of the SARS-CoV-2 main protease (MPro). Of these tested small molecule medicines, six displayed an IC50value in inhibiting MProbelow 100 μM. Three medicines pimozide, ebastine, and bepridil are basic small molecules. Their uses in COVID-19 patients potentiate dual functions by both raising endosomal pH to slow SARS-CoV-2 entry into the human cell host and inhibiting MProin infected cells. A live virus-based microneutralization assay showed that bepridil inhibited cytopathogenic effect induced by SARS-CoV-2 in Vero E6 cells completely at and dose-dependently below 5 μM and in A549 cells completely at and dose-dependently below 6.25 μM. Therefore, the current study urges serious considerations of using bepridil in COVID-19 clinical tests.
Evidence for prescribed NK cell Ly49 developmental pathways in mice
Authors: Millan Alberto J. , Hom Bryan A. , Libang Jeremy B. , Sindi Suzanne , Manilay Jennifer O. 
Published: May 2020

AbstractPrevious studies of NK cell inhibitory Ly49 receptors suggested their expression is stochastic. However, relatively few studies have examined this stochasticity in conjunction with activating Ly49 receptors. We hypothesized that the expression of activating Ly49 receptors is not stochastic and is influenced by inhibitory Ly49 receptors. We analyzed NK cell “clusters” defined by combinatorial expression of activating (Ly49H, Ly49D) and inhibitory (Ly49I, Ly49G2) receptors in C57BL/6 mice. Using the product rule to evaluate the interdependencies of the Ly49 receptors, we found evidence for a tightly regulated expression at the immature NK cell stage, with the highest interdependencies between clusters that express at least one activating receptor. Further analysis demonstrated that certain NK clusters predominated at the immature (CD27+CD11b−), transitional (CD27+CD11b+) and mature (CD27−CD11b−) NK cell stages. Using parallel in vitro culture and in vivo transplantation of sorted NK clusters, we discovered non-random upregulation of Ly49 receptors, suggesting that prescribed pathways of NK cluster differentiation exist. Our data infer that upregulation of Ly49I is an important step in NK cell maturation. Ki-67 expression and cell counts confirmed that immature NK cells proliferate more than mature NK cells. We found that MHC-I is particularly important for regulation of Ly49D and Ly49G2, even though no known MHC-I ligand for these receptors is present in B6 mice. Our data indicate that the regulatory systems controlling the expression of both activating and inhibitory Ly49 receptors are non-stochastic and support the idea that NK cell clusters develop in a non-random process correlated to their maturation stage.
The stringent stress response controls proteases and global regulators under optimal growth conditions inPseudomonas aeruginosa
Authors: Pletzer Daniel , Blimkie Travis M. , Wolfmeier Heidi , Li Yicong , Baghela Arjun , Lee Amy H. Y. , Falsafi Reza , Hancock Robert E. W. 
Published: May 2020

AbstractThe bacterial stringent stress response, mediated by the signaling molecule guanosine tetra-phosphate, ppGpp, has recently gained attention as being important during normal cellular growth and as potential new therapeutic target, which warrants detailed mechanistic understanding. Here, we used intracellular protein tracking inPseudomonas aeruginosaPAO1, which indicated that RelA was bound to the ribosome, while SpoT localized at the cell poles. RNA-Seq was used to investigate the transcriptome of a ppGpp-deficient strain under non-stressful nutrient-rich broth conditions where the mutant grew at the same rate as the parent strain. In exponential growth phase, the lack of ppGpp led to >1,600 transcriptional changes (fold-change cut-off ±1.5), providing further novel insights into the normal physiological role of ppGpp. The stringent response was linked to gene expression of various proteases and secretion systems includingaprA, PA0277,impA, andclpP2. The previously observed reduction in cytotoxicity towards red blood cells, in a stringent response mutant, appeared to be due toaprA. Investigation of anaprAmutant in a murine skin infection model, showed increased survival rates of theaprAmutant consistent with previous observations that stringent-response mutants have reduced virulence. In addition, the overexpression ofrelA, but not induction of ppGpp with serine hydroxamate, dysregulated global transcriptional regulators as well as >30% of the regulatory networks controlled by AlgR, OxyR, LasR, and AmrZ. Together these data expand our knowledge about ppGpp and its regulatory network and role in environmental adaptation. It also confirms its important role throughout the normal growth cycle of bacteria.Significance StatementMicroorganisms need to adapt rapidly to survive harsh environmental changes. Here, we showed the broad influence of the highly studied bacterial stringent stress response under non-stressful conditions that indicate its general physiological importance and might reflect the readiness of bacteria to respond to and activate acute stress responses. Using RNA-Seq to investigate the transcriptional network ofPseudomonas aeruginosacells revealed that >30% of all genes changed expression in a stringent-response mutant under optimal growth conditions. This included genes regulated by global transcriptional regulators and novel downstream effectors. Our results help to understand the importance of this stress regulator in bacterial lifestyle under relatively unstressed conditions. As such it draws attention to the consequences of targeting this ubiquitous bacterial signaling molecule.
COVID-19 impact on consecutive neurological patients admitted to the emergency department
Authors: Pilotto Andrea , Benussi Alberto , Libri Ilenia , Masciocchi Stefano , Poli Loris , Premi Enrico , Alberici Antonella , Baldelli Enrico , Bonacina Sonia , Brambilla Laura , Benini Matteo , Caratozzolo Salvatore , Cortinovis Matteo , Costa Angelo , Piccinelli Stefano Cotti , Cottini Elisabetta , Cristillo Viviana , Delrio Ilenia , Filosto Massimiliano , Gamba Massimo , Gazzina Stefano , Gilberti Nicola , Gipponi Stefano , Giunta Marcello , Imarisio Alberto , Liberini Paolo , Locatelli Martina , Cola Francesca Schiano di , Rao Renata , Risi Barbara , Rozzini Luca , Scalvini Andrea , Vergani Veronica , Volonghi Irene , Zoppi Nicola , Borroni Barbara , Magoni Mauro , Leonardi Matilde , Zanusso Gianluigi , Ferrari Sergio , Mariotto Sara , Pezzini Alessandro , Gasparotti Roberto , Paolillo Ciro , Padovani Alessandro 
Published: May 2020

AbstractObjectiveAim of this study was to analyse the impact of COVID-19 on clinical and laboratory findings and outcome of neurological patients consecutively admitted to the emergency department (ED) of a tertiary hub center.MethodsAll adult patients consecutively admitted to the ED for neurological manifestations from February 20th through April 30th 2020 at Spedali Civili of Brescia entered the study. Demographic, clinical, and laboratory data were extracted from medical records and compared between patients with and without COVID-19.ResultsOut of 505 consecutively patients evaluated at ED with neurological symptoms, 147 (29.1%) tested positive for SARS-CoV-2. These patients displayed at triage higher values of CRP, AST, ALT, and fibrinogen but not lymphopenia (p<0.05). They were older (73.1 ± 12.4 vs 65.1 ± 18.9 years, p=0.001) had higher frequency of stroke (34.7% vs 29.3%), encephalitis/meningitis (9.5% vs 1.9%) and delirium (16.3% vs 5.0%). Compared to patients without COVID, they were more frequently hospitalized (91.2% vs 69.3%, p<0.0001) and showed higher mortality rates (29.7% vs 1.8%, p<0.0.001) and discharge disability, independently from age.ConclusionsCOVID-19 impacts on clinical presentation of neurological disorders, with higher frequency of stroke, encephalitis and delirium, and was strongly associated with increased hospitalisation, mortality and disability.
A Consensus Transcriptional Landscape of Human End-Stage Heart Failure
Authors: Flores Ricardo O. Ramirez , Lanzer Jan D. , Holland Christian H. , Leuschner Florian , Most Patrick , Schultz Jobst-Hendrik , Levinson Rebecca T. , Saez-Rodriguez Julio 
Published: May 2020

2.AbstractAimsTranscriptomic studies have contributed to fundamental knowledge of myocardial remodeling in human heart failure (HF). However, the agreement on key regulated genes in HF is limited and systematic efforts to integrate evidence from multiple patient cohorts are lacking. Here we aimed to provide an unbiased consensus transcriptional signature of human end-stage HF by comprehensive comparison and analysis of publicly available datasets.Methods and ResultsWe curated and uniformly processed 16 public transcriptomic studies of left ventricular samples from 263 healthy and 653 failing human hearts. Transfer learning approaches revealed conserved disease patterns across all studies independent of technical differences. We meta-analyzed the dysregulation of 14041 genes to extract a consensus signature of HF. Estimation of the activities of 343 transcription factors, 14 signalling pathways, and 182 micro RNAs, as well as the enrichment of 5998 biological processes confirmed the established aspects of the functional landscape of the disease and revealed novel ones. We provide all results in a free public resource https://saezlab.shinyapps.io/reheat/ to facilitate further use and interpretation of the results. We exemplify usage by deciphering fetal gene reprogramming and tracing myocardial origin of the plasma proteome biomarkers in HF patients.ConclusionWe demonstrated the feasibility of combining transcriptional studies from different HF patient cohorts. This compendium provides a robust and consistent collection of molecular markers of end-stage HF that may guide the identification of novel targets with diagnostic or therapeutic relevance.
Incubation period of COVID-19 in the “live-house” cluster of accurately known infection events and delay time from symptom onset of public reporting observed in cases in Osaka, Japan
Authors: Tomie Toshihisa 
Published: May 2020

AbstractThe incubation period of an infectious disease is very important for control of the disease but estimating the period is not easy because the date of infection is not easy to identify. Accurate incubation period distribution by examining cases in the cluster generated in “live-houses” in Osaka, Japan with known infection events is reported. The distribution of the latent period is also estimated. The modes of incubation and latent periods of COVID-19 in Japan are 4.1 days and 3.3 days, respectively. The mode of the delay time from the onset to reporting is estimated to be 4.7 days, telling that the effects of interventions show up in the number of infections two weeks later after the measures.
Remdesivir use in patients with coronavirus COVID-19 disease: a systematic review and meta-analysis of the Chinese Lancet trial with the NIH trial
Authors: Alexander Paul Elias , Piticaru Joshua , Lewis Kimberley , Aryal Komal , Thomas Priya , Szczeklik Wojciech , Fronczek Jakub , Polok Kamil , Alhazzani Waleed , Mammen Manoj 
Published: May 2020

AbstractBackgroundCoronavirus disease 2019 (COVID-19), caused by the novel coronavirus SARS-CoV-2, has led to significant global mortality and morbidity. Until now, no treatment has proven to be effective in COVID-19. To explore whether the use of remdesivir, initially an experimental broad-spectrum antiviral, is effective in the treatment of hospitalized patients with COVID-19, we conducted a systematic review and meta-analysis of randomized, placebo-controlled trials investigating its use.MethodsA rapid search of the MEDLINE and EMBASE medical databases was conducted for randomized controlled trials. A systematic approach was used to screen, abstract, and critically appraise the studies. Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method was applied to rate the certainty and quality of the evidence reported per study.ResultsTwo RCTs studies were identified (n=1,299). A fixed-effects meta-analysis revealed reductions in mortality (RR=0.69, 0.49 to 0.99), time to clinical improvement (3.95 less days, from 3.86 days less to 4.05 less days), serious adverse events (RR=0.77, 0.63 to 0.94) and all adverse events (RR=0.87, 0.79 to 0.96).ConclusionIn this rapid systematic review, we present pooled evidence from the 2 included RCT studies that reveal that remdesivir has a modest yet significant reduction in mortality and significantly improves the time to recovery, as well as significantly reduced risk in adverse events and serious adverse events. It is more than likely that as an antiviral, remdesivir is not sufficient on its own and may be suitable in combination with other antivirals or treatments such as convalescent plasma. Research is ongoing to clarify and contextual these promising findings.
Modelling COVID-19 Transmission in the United States through Interstate and Foreign Travels and Evaluating Impact of Governmental Public Health Interventions
Authors: Shah Nita H. , Sheoran Nisha , Jayswal Ekta , Shukla Dhairya , Shukla Nehal , Shukla Jagdish , Shah Yash 
Published: May 2020

AbstractBackgroundThe first case of COVID-19 was reported in Wuhan, China in December 2019. The disease has spread to 210 countries and has been labelled as pandemic by WHO. Modelling, evaluating, and predicting the rate of disease transmission is crucial for epidemic prevention and control. Our aim is to assess the impact of interstate and foreign travel and public health interventions implemented by the United States government in response to the Covid-19 pandemic.MethodsA disjoint mutually exclusive compartmental model is developed to study transmission dynamics of the novel coronavirus. A system of non-linear differential equations was formulated and the basic reproduction number R0 was computed. Stability of the model was evaluated at the equilibrium points. Optimal controls were applied in the form of travel restrictions and quarantine. Numerical simulations were conducted.ResultsAnalysis shows that the model is locally asymptomatically stable, at endemic and foreigners free equilibrium points. Without any mitigation measures, infectivity and subsequent hospitalization of the population increases while placing interstates individuals and foreigners under quarantine, decreases the chances of exposure and subsequent infection, leading to an increase in the recovery rate.ConclusionInterstate and foreign travel restrictions, in addition to quarantine, help in effectively controlling the epidemic.
Reproductive number of COVID-19: A systematic review and meta-analysis based on global level evidence
Authors: Billah Md. Arif , Miah Md. Mamun , Khan Md. Nuruzzaman 
Published: May 2020

AbstractBackgroundThe coronavirus (COVID-19) is now a global concern because of its higher transmission capacity and associated adverse consequences including death. The reproductive number of COVID-19 provides an estimate on possible extent of the transmission. This study aims to provide the average reproductive number of COVID-19 based on available global level evidence.MethodsWe searched three databases (PubMed, Web of Science, and Science Direct) to find studies reported the reproductive number of COVID-19. The searches were conducted using a pre-specified search strategy that includes keywords of COVID-19 and its reproductive number related terms, which were combined using the Boolean operators. We used meta-analysis to provide average reproduction number of COVID-19.ResultsTotal of 30 studies included in this review whereas 24 of them were included in the meta-analysis. The average estimated reproductive number was 2.70 (95% CI, 2.21-3.30). We found evidence of very high heterogeneity (99.5%) of the reproductive number reported in the included studies. The highest reproductive number was reported for Diamond Princes Cruise Ship, Japan (14.8). In the country-level, higher reproductive number was reported for France (R, 6.32, 95% CI, 5.72-6.98) following Germany (R, 6.07, 95% CI, 5.51-6.69) and Spain (R, 5.08, 95% CI, 4.50-5.73). We also found estimation models, methods, and the number of cases considered to estimate reproductive number were played a role in arising the heterogeneity of the estimated reproductive number.ConclusionThe estimated reproductive number indicates an exponential increase of COVID-19 infection in coming days. Comprehensive policies and programs are important to reduce new infections as well as the associated adverse consequences including death.
Worldwide and Regional Forecasting of Coronavirus (Covid-19) Spread using a Deep Learning Model
Authors: Direkoglu Cem , Sah Melike 
Published: May 2020

AbstractIn December 2019, Covid-19 epidemic was identified in Wuhan, China. Covid-19 may cause fatality especially among elderly, and people with chronic health problems. After human to human transmissions of the disease, it has rapidly spread throughout China, and then the outbreak has reached to neighboring countries in Asia. Now, the spread of the virus is accelerating in the world, and increasing number of new cases has been reported daily in Europe, Middle East, Africa and America regions. Recently, World Health Organization (WHO) also announced Covid-19 as a Pandemic. As of 3 April, worldwide around more than 1 million cases and around 60,000 fatalities are reported. Thus, forecasting regional and worldwide outbreak size of Covid-19 is important in order to take necessary actions regarding to preparedness plans and mitigation interventions. In this work, we design a deep learning model, which is an effective artificial intelligence method, to provide regional and worldwide forecasts. Particularly for worldwide, our approach predicts the cumulative number of cases, cumulative number of deaths and daily new cases. For Europe and Middle East regions, we predict the cumulative number of cases, and for Mainland China we predict daily new cases and the cumulative number of deaths. We predict the next 10 days based on the previously reported actual time series data of Covid-19. For worldwide forecasts, we use the data provided by Worldometers. For Europe and Middle East forecasts, we use the data provided by World Health Organization, and for China Mainland forecasts, the data is obtained from Chinese Centre for Disease Control and Prevention. This is the first time that a deep learning model has been employed for Covid-19 spread prediction, solely based on the known reported cases of Covid-19. The proposed deep learning architecture consists of Long Short Term Memory (LSTM) layer, dropout layer, and fully connected layers to predict regional and worldwide forecasts. We evaluate our approach with Root Mean Square Error (RMSE) metric. For forecasting, we use the network models that give the minimum RMSE on the last 3 days of actual data. Networks, which achieves the minimum RMSE on the last 3 days, are used to predict the next 10 days. Every day, the spread and situations are changing. Our approach can take into account these realtime changes; the deep learning model can be re-trained with new daily data and perform real-time forecasting. Results show that the proposed deep learning model is promising, it can predict possible scenarios regionally and globally for the spread of Covid-19.