bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling COVID-19 Growing Trends to Reveal the Differences in the Effectiveness of Non-Pharmaceutical Interventions among Countries in the World
Authors: Chen You , Feng Yubo , Yan Chao , Zhang Xinmeng , Gao Cheng 
Published: April 2020

ABSTRACTObjectiveWe hypothesize that COVID-19 case growth data reveals the efficacy of NPIs. In this study, we conduct a secondary analysis of COVID-19 case growth data to compare the differences in the effectiveness of NPIs among 16 representative countries in the world.MethodsThis study leverages publicly available data to learn patterns of dynamic changes in the reproduction rate for sixteen countries covering Asia, Europe, North America, South America, Australia, and Africa. Furthermore, we model the relationships between the cumulative number of cases and the dynamic reproduction rate to characterize the effectiveness of the NPIs. We learn four levels of NPIs according to their effects in the control of COVID-19 growth and categorize the 16 countries into the corresponding groups.ResultsThe dynamic changes of the reproduction rate are learned via linear regression models for all of the studied countries, with the average adjusted R-squared at 0.96 and the 95% confidence interval as [0.94 0.98]. China, South Korea, Argentina, and Australia are at the first level of NPIs, which are the most effective. Japan and Egypt are at the second level of NPIs, and Italy, Germany, France, Netherlands, and Spain, are at the third level. The US and UK have the most inefficient NPIs, and they are at the fourth level of NPIs.ConclusionsCOVID-19 case growth data provides evidence to demonstrate the effectiveness of the NPIs. Understanding the differences in the efficacy of the NPIs among countries in the world can give guidance for emergent public health events.
Association between environmental pollution and prevalence of coronavirus disease 2019 (COVID-19) in Italy
Authors: Lippi Giuseppe , Sanchis-Gomar Fabian , Henry Brandon M. 
Published: April 2020

AbstractThe novel coronavirus disease 2019 (COVID-19) has recently been upgraded to a pandemic by the World Health Organization due to the alarming levels of spread and severity. Since several lines of evidence also attest that Lombardy region has an extraordinarily high level of environmental pollution, we aimed to explore the potential epidemiological association between the number of cases of COVID-19 and environmental pollution in Italy. Data on environmental pollution in Italy were retrieved from the 2019 annual report of the organization Legambiente (League for the Ambient). The adjusted correlation between the number of days in which environmental pollutants exceeded established limits and the overall number of COVID-19 cases reveals the existence of a highly significant positive association (r=0.66; 95% CI, 0.48-0.79; p<0.001). The association remained statistically significant even when the number of days above pollutant limits was correlated with the number of COVID-19 cases per 1000 inhabitants (r=0.43; 95% CI, 0.18-0.62; p=0.001). Living in a province with over 100 days per year in which environmental pollutants were exceeded was found to be associated with a nearly 3-fold higher risk of being positive for COVID-19 (0.014 vs. 0.005 COVID-19 cases per 1000 inhabitants; OR, 2.96; 95% 2.12-4.13; p<0.001). Reinforced restrictive measures shall be considered in areas with higher air pollution, where the virus is more likely to find a fertile biological or environmental setting.
GC-MS Analysis of Smokeless tobacco (Shamma): Toxicological Evaluation
Authors: Alzahrani Hamzah S. , Alamoudi Tariq S. , Aloudah Khaled S. , Alghamdi Fahad S. , Alghamdi Khalel S. , Ali Haytham A. 
Published: April 2020

AbstractBackgroundSmoking is a badly addictive habit due to nicotine contents in tobacco. Shammah is one way of smokeless tobacco that is homely made and it use resulting in multiple medical issues.AimThe aim of the present study were to chemically analyze the content of various types of Shammah using GC-MS analysis with clinical biochemical investigation of some cases usually used shamma in Makkah region, Saudi Arabia.MethodsThree samples from two main different types ofshamma (black and yellow)were collected from local providers and analyzed by Gas Chromatography Mass Spectrometry (GC/MS). Eighteen blood samples were also collected from apparently healthy male peoples (30-45 years) classified into 3 groups; group 1 (control) people who doesn’t smoke or use any type of shamma, second and third groups were people who usually used black and yellow shamma respectively; CBC and biochemical analysis were performed.ResultsIn GC-MS Analysis, the nicotine represents the major constituent in all samples. Total RBCs count, Hemoglobin (HGB) Conc., eosinophil % and iron, total cholesterol, HDL-c concentrations were significantly decreased in peoples using either black or yellow shamma whereas serum levels of ALT, AST and ALP enzyme activities, BUN and creatinine levels were significantly increases.ConclusionDifferent shamma samples contains different concentrations of various toxic compounds that can produced a serious health problems as hypochromic anemia due to iron deficiency, decrease in eosinophil %, with hepatic and renal cell injuries detected as increase ALT, AST, ALP, BUN, and creatinine levels.
Small-sample estimation of the mutational support and the distribution of mutations in the SARS-Cov-2 genome
Authors: Rana Vishal , Chien Eli , Peng Jianhao , Milenkovic Olgica 
Published: April 2020

AbstractThe problem of estimating unknown features of viral species using a limited collection of observations is of great relevance in computational biology. We consider one such particular problem, concerned with determining the mutational support and distribution of the SARS-Cov-2 viral genome and its open reading frames (ORFs). The mutational support refers to the unknown number of sites that is expected to be eventually mutated in the SARS-Cov-2 genome. It may be used to assess the virulence of the virus or guide primer selection for real-time RT-PCR tests during the early stages of an outbreak. Estimating the unknown distribution of mutations in the genome of different subpopulations while accounting for the unseen may aid in discovering adaptation mechanisms used by the virus to evade the immune system. To estimate the mutational support in the small-sample regime, we use GISAID sequencing data and new state-of-the-art polynomial estimation techniques based on weighted and regularized Chebyshev approximations. For distribution estimation, we adapt the well-known Good-Turing estimator. We also perform a differential analysis of mutations and their sites across different populations. Our analysis reveals several findings: First, the mutational supports exhibit significant differences in the ORF6 and ORF7a regions (older vs younger patients), ORF1b and ORF10 regions (females vs males) and as may be expected, in almost all ORFs (for Asia versus Europe and North America). Second, despite the fact that the N region of SARS-Cov-2 has a predicted 10% mutational support, almost all observed mutations fall outside of the two regions of paired primers recommended for testing by the CDC.Author SummaryWe introduce the new problem of small-sample estimation of the number of mutations and the distribution of mutations in viral and bacterial genomes, and in particular, in the SARS-Cov-2 genome. The approach is of interest due to the fact that it aims to predict which regions in the genome will mutate in the future and with what frequency, given only a very limited number of complete viral sequences. This setting is usually encountered during the early stages of an outbreak when it is critical to assess the potential of the virus to gain mutations advantageous for its spreading. The results may also be used to guide the selection of genomic (primer) regions that are not subject to mutational pressure and can consequently be used as identifiers in the process of testing for the disease. They can also highlight differences in the mutation rates and locations of the SARS-Cov-2 virus affecting diverse subpopulations and therefore potentially suggest the role of certain mutations in evading the immune system. Our approach uses a new class of estimation methods that may find other applications in bioinformatics.
ICU and ventilator mortality among critically ill adults with COVID-19
Authors: Auld Sara C. , Caridi-Scheible Mark , Blum James M. , Robichaux Chad , Kraft Colleen , Jacob Jesse T. , Jabaley Craig S. , Carpenter David , Kaplow Roberta , Hernandez-Romieu Alfonso C. , Adelman Max W. , Martin Greg S. , Coopersmith Craig M. , Murphy David J. ,   the Emory COVID-19 Quality and Clinical Research Collaborative
Published: April 2020

SummaryWe report preliminary data from a cohort of adults admitted to COVID-designated intensive care units from March 6 through April 17, 2020 across an academic healthcare system. Among 217 critically ill patients, mortality for those who required mechanical ventilation was 29.7% (49/165), with 8.5% (14/165) of patients still on the ventilator at the time of this report. Overall mortality to date in this critically ill cohort is 25.8% (56/217), and 40.1% (87/217) patients have survived to hospital discharge. Despite multiple reports of mortality rates exceeding 50% among critically ill adults with COVID-19, particularly among those requiring mechanical ventilation, our early experience indicates that many patients survive their critical illness.
Joint antibiotic and phage therapy: addressing the limitations of a seemingly ideal phage for treatingStaphylococcus aureusinfections
Authors: Berryhill Brandon A. , Huseby Douglas L. , McCall Ingrid C. , Hughes Diarmaid , Levin Bruce R. 
Published: April 2020

AbstractIn response to increasing frequencies of antibiotic-resistant pathogens, there has been a resurrection of interest in the use of bacteriophage to treat bacterial infections: phage therapy. Here we explore the potential of a seemingly ideal phage, PYOSa, for combination phage and antibiotic treatment ofStaphylococcus aureusinfections. (i) This K-like phage has a broad host range; all 83 tested clinical isolates ofS.aureustested were susceptible to PYOSa. (ii) Because of the mode of action of PYOSaS. aureusis unlikely to generate classical receptor-site mutants resistant to PYOSa; none were observed in the 13 clinical isolates tested. (iii) PYOSakillsS. aureusat high rates. On the downside, the results of our experiments and tests of the joint action of PYOSaand antibiotics raise issues that must be addressed before PYOSais employed clinically. Despite the maintenance of the phage, PYOSadoes not clear the populations ofS. aureus. Due to the ascent of a phenotypically diverse array of small colony variants following an initial demise, the bacterial populations return to densities similar to that of phage-free controls. Using a combination of mathematical modeling andin vitroexperiments, we postulate and present evidence for a mechanism to account for the demise–resurrection dynamics of PYOSaandS. aureus. Critically for phage therapy, our experimental results suggest that treatment with PYOSafollowed by bactericidal antibiotics can clear populations ofS. aureusmore effectively than the antibiotics alone.Significance StatementThe increasing frequency of antibiotic-resistant pathogens has fostered a quest for alternative means to treat bacterial infections. Prominent in this quest is a therapy that predates antibiotics: bacteriophage. This study explores the potential of a phage, PYOSa, for treatingStaphylococcus aureusinfections in combination with antibiotics. On first consideration, this phage, isolated from a commercial therapeutic cocktail, seems ideal for this purpose. The results of this population dynamic and genomic analysis study identify a potential liability of using PYOSafor therapy. Due to the production of potentially pathogenic atypical small colony variants, PYOSaalone cannot eliminateS. aureuspopulations. However, we demonstrate that by following the administration of PYOSawith bactericidal antibiotics, this limitation and potential liability can be addressed.
Comparison of Commercially Available and Laboratory Developed Assays for in vitro Detection of SARS-CoV-2 in Clinical Laboratories
Authors: Lieberman Joshua A. , Pepper Gregory , Naccache Samia N. , Huang Meei-Li , Jerome Keith R. , Greninger Alexander L. 
Published: April 2020

AbstractMultiple laboratory developed tests and commercially available assays have emerged to meet diagnostic needs related to the SARS-CoV-2 pandemic. To date, there is limited comparison data for these different testing platforms. We compared the analytical performance of a laboratory developed test (LDT) developed in our clinical laboratory based on CDC primer sets and four commercially available, FDA emergency use authorized assays for SARS-CoV-2 (Cepheid, DiaSorin, Hologic Panther, and Roche Cobas) on a total of 169 nasopharyngeal swabs. The LDT and Cepheid Xpert Xpress SARS-CoV-2 assays were the most sensitive assays for SARS-CoV-2 with 100% agreement across specimens. The Hologic Panther Fusion, DiaSorin Simplexa, and Roche Cobas 6800 only failed to detect positive specimens near the limit of detection of our CDC-based LDT assay. All assays were 100% specific, using our CDC-based LDT as the gold standard. Our results provide initial test performance characteristics for SARS-CoV-2 RT-PCR and highlight the importance of having multiple viral detection testing platforms available in a public health emergency.
A computational network approach to identify predictive biomarkers and therapeutic combinations for anti-PD-1 immunotherapy in cancer
Authors: Wu Chia-Chin , Wang Y Alan , Livingston J Andrew , Zhang Jianhua , Futreal P. Andrew 
Published: April 2020

AbstractBackgroundDespite remarkable success, only a subset of cancer patients have shown benefit from the anti-PD1 therapy. Therefore, there is a growing need to identify predictive biomarkers and therapeutic combinations for improving the clinical efficacy.ResultsBased upon the hypothesis that aberrations of any gene that are close to MHC class I genes in the gene network are likely to deregulate MHC I pathway and affect tumor response to anti-PD1, we developed a network approach to infer genes, pathway, and potential therapeutic target genes associated with response to PD-1/PD-L1 checkpoint immunotherapies in cancer. Our approach successfully identified genes (e.g. B2M and PTEN) and pathways (e.g. JAK/STAT and WNT) known to be associated with anti-PD1 response. Our prediction was further validated by 5 CRISPR gene sets associated with tumor resistance to cytotoxic T cells. Our results also showed that many cancer genes that act as hubs in the gene network may drive immune evasion through indirectly deregulating the MHC I pathway. The integration analysis of transcriptomic data of the 34 TCGA cancer types and our prediction reveals that MHC I-immunoregulations may be tissue-specific. The signature-based score, the MHC I association immunoscore (MIAS), calculated by integration of our prediction and TCGA melanoma transcriptomic data also showed a good correlation with patient response to anti-PD1 for 354 melanoma samples complied from 5 cohorts. In addition, most targets of the 36 compounds that have been tested in clinical trials or used for combination treatments with anti-PD1 are in the top list of our prediction (AUC=0.833). Integration of drug target data with our top prediction further identified compounds that were recently shown to enhance tumor response to anti-PD1, such as inhibitors of GSK3B, CDK, and PTK2.ConclusionOur approach is effective to identify candidate genes and pathways associated with response to anti-PD-1 therapy, and can also be employed forin silicoscreening of potential compounds to enhances the efficacy of anti-PD1 agents against cancer.
Molecular dynamics simulations of protein aggregation: protocols for simulation setup and analysis with Markov state models and transition networks
Authors: Samantray Suman , Schumann Wibke , Illig Alexander-Maurice , Carballo-Pacheco Martin , Paul Arghadwip , Barz Bogdan , Strodel Birgit 
Published: April 2020

AbstractProtein disorder and aggregation play significant roles in the pathogenesis of numerous neuro-degenerative diseases, such as Alzheimer’s and Parkinson’s disease. The end products of the aggregation process in these diseases are β-sheet rich amyloid fibrils. Though in most cases small, soluble oligomers formed during amyloid aggregation are the toxic species. A full understanding of the physicochemical forces behind the protein aggregation process is required if one aims to reveal the molecular basis of the various amyloid diseases. Among a multitude of biophysical and biochemical techniques that are employed for studying protein aggregation, molecular dynamics (MD) simulations at the atomic level provide the highest temporal and spatial resolution of this process, capturing key steps during the formation of amyloid oligomers. Here we provide a step-by-step guide for setting up, running, and analyzing MD simulations of aggregating peptides using GROMACS. For the analysis we provide the scripts that were developed in our lab, which allow to determine the oligomer size and inter-peptide contacts that drive the aggregation process. Moreover, we explain and provide the tools to derive Markov state models and transition networks from MD data of peptide aggregation.
The perfect condition for the rising of superbugs: person-to-person contagion and antibiotic use are the key factors responsible for the positive correlation between antibiotic resistance gene diversity and virulence gene diversity in human metagenomes
Authors: Domingues Célia P. F. , Rebelo João S. , Nogueira Teresa , Pothier Joël , Monteiro Francisca , Dionisio Francisco 
Published: April 2020

1.AbstractThis study aims to understand the cause of the recent observation that humans with a higher diversity of virulence genes in their metagenomes tend to be precisely those with higher diversity of antibiotic-resistance genes. We simulated the transferring of virulence and antibiotic-resistance genes in a community of interacting people where some take antibiotics. The diversities of the two genes types became positively correlated whenever the contagion probability between two people was higher than the probability of losing resistant genes. However, no such positive correlations arise if no one takes antibiotics. This finding holds even under changes of several simulations’ parameters, such as the relative or total diversity of virulence and resistance genes, the contagion probability between individuals, the loss rate of resistance genes, or the social network type. Because the loss rate of resistance genes may be shallow, we conclude that the contagion between people and antibiotic usage is the leading cause of establishing the positive correlation mentioned above. Therefore, antibiotic use and something as prosaic as the contagion between people may facilitate the emergence of virulent and multi-resistant bacteria in people’s metagenomes with a high diversity of both gene types. These superbugs may then circulate in the community.
A putative genomic map for resistance ofBos indicuscattle in Cameroon to bovine tuberculosis
Authors: Callaby Rebecca , Kelly Robert , Mazeri Stella , Egbe Franklyn , Benedictus Lindert , Clark Emily , Doeschl-Wilson Andrea , Bronsvoort Barend , Salavati Mazdak , Muwonge Adrian 
Published: April 2020

ABSTRACTBovine Tuberculosis (bTB) caused byMycobacterium bovisis a livestock disease of global economic and public health importance. There are currently no effective vaccines available for livestock and so control relies on animal level surveillance and pasteurisation of dairy products. A new alternative control approach is to exploit the genetic variability of the host; recent studies have demonstrated that breedingBos tauruscattle for increased resistance to bTB is feasible. The utility of such an approach is still unknown for theBos indicuscattle population. This study aims to assess genetic variation in bTB resistance and the underlying genomic architecture inBos indicusbreeds in Cameroon.We conducted a cross-sectional study of slaughter cattle in Cameroon and genotyped a sample of 213 cattle. Their genomic diversity was characterised using PCA, hierarchical clustering and admixture analysis. We assessed genetic variation in bTB resistance using heritability analysis and compared quantitative trait loci.Previous studies had found that breed was an important factor in explaining the epidemiology of bTB, with Fulani cattle appearing to be more susceptible than mixed breeds. However, we show that the apparent phenotypic differences in visual appearance between the breeds was not reflected by clear genomic differences. At the genetic level, cattle belonging to different hierarchical genomic clusters differed in their susceptibility to bTB. There was evidence of a genomic association betweenM. bovisinfection status with specific SNPs.We highlight the need to understand the challenges faced by livestock in specific settings both in terms of pathogens and the environment, in addition to their intended purpose and how they fit into a defined management system. It is only at this point livestock keepers can then make informed breeding choices, not only for resistance to disease but also for increasing production.
Microevolution of acquired colistin resistance in Enterobacteriaceae from ICU patients receiving selective decontamination of the digestive tract
Authors: Janssen Axel B. , van Hout Denise , Bonten Marc J.M. , Willems Rob J.L. , van Schaik Willem 
Published: April 2020

AbstractColistin is an antibiotic that targets the lipopolysaccharides present in the membranes of Gram-negative bacteria. It is used as last-resort drug to treat infections with multidrug-resistant strains. Colistin is also used in selective decontamination of the digestive tract (SDD), a prophylactic therapy used in patients hospitalised in intensive care units (ICUs) to selectively eradicate opportunistic pathogens in the oropharyngeal and gut microbiota. In this study, we aimed to unravel the mechanisms of acquired colistin resistance in Gram-negative opportunistic pathogens obtained from SDD-treated patients.Routine surveillance of 428 SDD-treated patients resulted in thirteen strains with acquired colistin resistance (Escherichia colin=9;Klebsiella aerogenes, n=3;Enterobacter asburiae, n=1) from five patients. Genome sequence analysis showed that these isolates represented multiple distinct colistin-resistant clones, but that within the same patients, colistin-resistant strains were clonally related. We identified previously described mechanisms that lead to colistin resistance, i.e. a G53 substitution in the response regulator PmrA/BasR, and the acquisition of the mobile colistin resistance genemcr-1.1, but we also observed novel variants ofbasRwith an 18-bp deletion, and a G19E substitution in the sensor histidine kinase BasS. We experimentally confirmed these variants to contribute to reduced colistin susceptibility. In a single patient, we observed that colistin resistance in a singleE. coliclone evolved through two unique variants inbasRS.We show that prophylactic use of colistin during SDD can select for colistin resistance in species that are not intrinsically colistin-resistant. This highlights the importance of continued surveillance for the emergence of colistin resistance in patients treated with SDD.