bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Efficacy of IL-6 Inhibitor Tocilizumab in Reducing Severe COVID-19 Mortality: A Systematic Review
Authors: Kaye Avi , Siegel Robert 
Published: July 2020

AbstractIn the absence of highly effective antiviral therapies against SARS-CoV-2, it is crucial to counter the known pathophysiological causes of severe COVID-19. Evaluating the efficacy existing drugs may expedite the development of such therapeutics. Severe COVID-19 is largely the result of a dysregulated immune response characterized by lymphocytopenia, neutrophilia and critical hypercytokinemia, or “cytokine storm,” which is largely mediated by the cytokine interleukin-6 (IL-6). The IL-6 inhibitor tocilizumab (TCZ) could potentially suppress the effects of the pro-inflammatory cytokine and thereby lower mortality from the disease. This systematic analysis aimed to investigate and synthesize existing evidence for the efficacy of TCZ in reducing COVID-19 mortality. PubMed and SearchWorks searches were performed to locate clinical studies with primary data on TCZ treatment for severe COVID-19. Sixteen case-control studies comparing mortality between TCZ and standard of care (SOC) were identified for quantitative synthesis. Combined mortality for the TCZ-treated and SOC groups were 26.0% and 43.4% respectively. In all but one of the studies, the odds ratio of mortality from COVID-19 pointed towards lower fatality with TCZ versus the SOC. A combined random effects odds ratio calculation yielded an odds ratio of 0.453 (95% CI 0.376-0.547, p<0.001). Additionally, eighteen uncontrolled trials were identified for qualitative analysis producing a raw combined mortality rate of 16.0%. Important caveats to this research include the lack of prospective randomized control trials (RCTs) and the absence of data from the large COVATA study from the published literature. However, results from this systematic analysis of published research provide positive evidence for the potential efficacy of TCZ to treat severe COVID-19, validating the ethical basis and merit of ongoing randomized controlled clinical trials.
Impact of meteorological parameters on the Covid-19 incidence. The case of the city of Oran, Algeria
Authors: Rahal Farid , Rezak Salima , Baba Hamed Fatima Zohra 
Published: July 2020

AbstractSeveral studies have confirmed the impact of weather conditions on the evolution of the Covid-19 pandemic. We wanted to verify this phenomenon in the city of Oran in Algeria, which experienced its first case of Covid19 on March 19, 2020.The data studied are the new Covid19 cases, the average, minimum and maximum temperatures, as well as the relative humidity rate.A first analysis of the data with a Spearman rank correlation test did not yield significant results. Taking into account the average incubation period to adjust the data made it possible, during a second analysis, to show that the minimum temperature is significantly correlated with the new cases of Covid19 in Oran. This study can help establish prevention policies against Covid19, especially during fall in temperatures in autumn and winter.
Impact of COVID-19 Lockdown Policy on Homicide, Suicide, and Motor Vehicle Deaths in Peru
Authors: Calderon-Anyosa Renzo JC , Kaufman Jay S 
Published: July 2020

AbstractIntroductionAlthough lockdown measures to stop COVID-19 have direct effects on disease transmission, their impact on violent and accidental deaths remains unknown. Our study aims to assess the early impact of COVID-19 lockdown on violent and accidental deaths in Peru.MethodsBased on data from the Peruvian National Death Information System, an interrupted time series analysis was performed to assess the immediate impact and change in the trend of COVID-19 lockdown on external causes of death including homicide, suicide, and traffic accidents. The analysis was stratified by sex and the time unit was every 15 days.ResultsAll forms of deaths examined presented a sudden drop after the lockdown. The biggest drop was in deaths related to traffic accidents, with a reduction of 12.66 deaths per million men per month (95% CI: −15.56, −9.76) and 3.64 deaths per million women per month (95% CI:-5.25, −2.03). Homicide and suicide presented similar level drop in women, while the homicide reduction was twice the size of the suicide reduction in men. The slope in suicide in men during the lock-down period increased by 3.62 deaths per million men per year (95% CI:0.06, 7.18). No other change in slope was detected.ConclusionsViolent and accidental deaths presented a sudden drop after the lockdown was implemented and an increase in suicide in men was observed. Falls in mobility have a natural impact on traffic accidents, however, the patterns for suicide and homicide are less intuitive and reveal important characteristics of these events, although we expect all of these changes to be transient.
Effects of Smoking and Smoking Cessation on the Intestinal Microbiota
Authors: Sublette Marcus G. , Cross Tzu-Wen L. , Korcarz Claudia E. , Hansen Kristin M. , Murga-Garrido Sofia M. , Hazen Stanley L. , Wang Zeneng , Oguss Madeline K. , Rey Federico E. , Stein James H. 
Published: July 2020

AbstractIntroductionWe evaluated associations of smoking heaviness markers and the effects of smoking cessation on the intestinal microbiota and cardiovascular disease risk factors in current smokers undertaking a quit attempt.Methods and ResultsParticipants were current smokers enrolled in a randomized clinical trial of smoking cessation therapies with visits, risk factor measurements, and fecal collections at baseline, 2, and 12 weeks after starting a quit attempt. Genomic DNA was extracted from fecal samples followed by 16S rRNA gene sequencing and analysis using the QIIME2 software workflow. Relative abundances of bacterial taxa and alpha- and beta-diversity measures were compared.Longitudinal changes in bacterial taxa abundances were compared using analysis of covariance (ANCOVA). The 36 smokers were (mean [standard deviation]) 51.5 (11.1) years old (42% male) and smoked 15.1 (6.4) cigarettes per day for 22.7 (11.9) pack-years. Their exhaled carbon monoxide (CO) levels were 17.6 (9.3) ppm. At baseline, relative abundances of the phylum Actinobacteria were correlated inversely with pack-years (rho=-0.44, p=0.008) and Cyanobacteria were correlated positively with CO levels (rho=0.39, p=0.021). After 12 weeks, abundances of the phylaBacteroidetes increased (pANCOVA=0.048) and Firmicutes decreased (pANCOVA=0.036) among abstainers compared to continuing smokers. Increases in alpha-diversity were associated with lower heart rates (rho=-0.59, p=0.037), systolic blood pressures (rho=-0.58, p=0.043), and C-reactive protein levels (rho=-0.60, p=0.034).ConclusionsSmoking cessation leads to minor changes in the intestinal microbiota. It is unclear if the proven health benefits of smoking cessation lead to salutary changes in the intestinal microbiota and if such changes affect cardiovascular disease risk.ImplicationsIn the largest prospective study of current smokers making a quit attempt to date, we showed that smoking cessation has minor effects on the composition of the gut microbiome. In successful abstainers, relative abundances of the phyla Bacteroidetes increased and Firmicutes decreased, a pattern of uncertain clinical significance. We did not observe significant changes in alpha- or beta-diversity with smoking cessation. It is unclear if the proven health benefits of smoking cessation lead to salutary changes in the intestinal microbiota and if such changes affect cardiovascular disease risk.
Social Disadvantage, Politics, and SARS-CoV-2 Trends: A County-Level Analysis of United States Data
Authors: Mourad Ahmad , Turner Nicholas A. , Baker Arthur W. , Okeke Nwora Lance , Narayanasamy Shanti , Rolfe Robert , Engemann John J. , Cox Gary M. , Stout Jason E. 
Published: July 2020

AbstractBackgroundUnderstanding the epidemiology of SARS-CoV-2 is essential for public health control efforts. Social, demographic, and political characteristics at the US county level might be associated with the trajectories of SARS-CoV-2 case incidence.ObjectiveTo understand how underlying social, demographic, and political characteristics at the US county level might be associated with the trajectories of SARS-CoV-2 case incidence.DesignRetrospective analysis of the trajectory of reported SARS-CoV-2 case counts at the US county level during June 1, 2020 – June 30,2020 and social, demographic, and political characteristics of the county.SettingUnited States.ParticipantsReported SARS-CoV-2 cases.ExposuresMetropolitan designation, Social Deprivation Index (SDI), 2016 Republican Presidential Candidate Victory.Main Outcomes and MeasuresSARS-CoV-2 case incidence.Results1023/3142 US counties were included in the analysis. 678 (66.3%) had increasing SARS-CoV-2 case counts between June 1 – June 30, 2020. In univariate analysis, counties with increasing case counts had a significantly higher SDI (median 48, IQR 24 – 72) than counties with non-increasing case counts (median 40, IQR 19 – 66; p=0.009). In the multivariable model, metropolitan areas of 250,000 – 1 million population, higher percentage of Black residents and a 10-point or greater Republican victory were independently associated with increasing case counts.LimitationsThe data examines county-level voting patterns and does not account for individual voting behavior, subjecting this work to the potential for ecologic fallacy.ConclusionIncreasing case counts of SARS-CoV-2 in the US are likely driven by a combination of social disadvantage, social networks, and behavioral factors. Addressing social disadvantage and differential belief systems that may correspond with political alignment will be essential for pandemic control.
Efficient Sequencing, Assembly, and Annotation of Human KIR Haplotypes
Authors: Roe David , Williams Jonathan , Ivery Keyton , Brouckaert Jenny , Downey Nick , Locklear Chad , Kuang Rui , Maiers Martin 
Published: July 2020

AbstractThe homology, recombination, variation, and repetitive elements in the natural killer-cell immunoglobulin-like receptor (KIR) region has made full haplotype DNA interpretation impossible without physical separation of chromosomes. Here, we present a new approach using long-read sequencing to efficiently capture, sequence, and assemble diploid human KIR haplotypes. Sequences for capture probe design were derived from public full-length gene and haplotype sequences. IDT xGen® Lockdown probes were used to capture 2-8 kb of sheared DNA fragments followed by sequencing on a PacBio Sequel. The sequences were error corrected, binned, and then assembled using the Canu assembler. The assembly was evaluated on 16 individuals (8 African American and 8 Europeans) from whom ground truth was known via long-range sequencing on fosmid-isolated chromosomes. Using only 18 capture probes, the results show that the assemblies cover 97% of the GenBank reference, are 99.97% concordant, and it takes only 1.8 contigs to cover 75% of the reference. We also report the first assembly of diploid KIR haplotypes from long-read WGS, including the first sequencing of cB05∼tB01, which pairs aKIR2DS2/KIR2DS3fusion with the tB01 region. Our targeted hybridization probe capture and sequencing approach is the first of its kind to fully sequence and phase all diploid human KIR haplotypes, and it is efficient enough for population-scale studies and clinical use.
Modulating the transcriptional landscape of SARS-CoV-2 as an effective method for developing antiviral compounds
Authors: Hoagland Daisy A. , Clarke Daniel J.B. , Møller Rasmus , Han Yuling , Yang Liuliu , Wojciechowicz Megan L. , Lachmann Alexander , Oguntuyo Kasopefoluwa Y. , Stevens Christian , Lee Benhur , Chen Shuibing , Ma’ayan Avi , tenOever Benjamin R 
Published: July 2020

AbstractTo interfere with the biology of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, we focused on restoring the transcriptional response induced by infection. Utilizing expression patterns of SARS-CoV-2-infected cells, we identified a region in gene expression space that was unique to virus infection and inversely proportional to the transcriptional footprint of known compounds characterized in the Library of Integrated Network-based Cellular Signatures. Here we demonstrate the successful identification of compounds that display efficacy in blocking SARS-CoV-2 replication based on their ability to counteract the virus-induced transcriptional landscape. These compounds were found to potently reduce viral load despite having no impact on viral entry or modulation of the host antiviral response in the absence of virus. RNA-Seq profiling implicated the induction of the cholesterol biosynthesis pathway as the underlying mechanism of inhibition and suggested that targeting this aspect of host biology may significantly reduce SARS-CoV-2 viral load.
Endosomal trafficking is required for glycosylation and normal maturation of the Alzheimer’s-associated protein sorLA
Authors: Christensen Sofie K. , Narimatsu Yoshiki , Simoes Sabrina , Goth Christoffer K. , Vægter Christian B. , Small Scott A. , Clausen Henrik , Andersen Olav M. 
Published: July 2020

ABSTRACTThe sorting receptor sorLA encoded by theSORL1gene is implicated in Alzheimer’s disease (AD) pathogenesis. Genetic studies have identified AD-associatedSORL1mutations and the expression of sorLA in AD brains is reported to be reduced. SorLA is a receptor of the retromer trafficking complex and functions at the endosome, and deficiency in sorLA phenocopies the endosomal pathologies found in AD. SorLA undergoes posttranslational modifications and maturation with ultimate ectodomain shedding, however knowledge of these processes remains limited. Here we demonstrate that sorLA exists at the cell membrane in two forms, an immature and a mature form, characterized by distinctN-glycosylation profiles. The mature sorLA form has acquired complex typeN-glycans and is shed from the cell surface by the TACE juxtmembrane cleavage. The immature form of sorLA present at the cell surface is shown to have immature ER-typeN-glycans (high-mannose type susceptible to endo H) and does not undergo shedding, however, upon endocytosis and recycling to the cell surface via endosomal trafficking pathways the immature sorLA form acquires complex-typeN-glycans. These results suggest an unusual secretion model for sorLA whereby that immature sorLA first traffics to the cell membrane without acquiring Golgi processing ofN-glycans, and only upon retrograde trafficking does sorLA acquire normal Golgi maturation ofN-glycans and become susceptible to TACE regulated shedding. Supportive evidence for this model include a sorLA mutant with deficient endosomal trafficking andin vivostudies demonstrating requirement of retromer for sorLA trafficking in the brain of retromer VPS26 deficient mice. Collectively, our study establishes the role endosomal trafficking plays in sorLA’s normal maturation, and point to impaired maturation as a signature of AD-associated sorLA dysfunction.
Causal influence of dietary habits on the risk of major depressive disorder: A diet-wide Mendelian randomization analysis
Authors: Chen Tzu-Ting , Chen Chia-Yen , Fang Chiu-Ping , Cheng Ying-Chih , Lin Yen-Feng 
Published: July 2020

AbstractBackground & aimsSome evidence suggests that diet may potentially increase or decrease the risk of major depressive disorder (MDD). However, the association between dietary habits and MDD remains controversial. The aim of this study is to systemically investigate the causal influence of dietary habits on the risk of MDD by Mendelian randomization (MR) using diet- and genome-wide summary data.MethodsTo perform two-sample MR, we collected publicly available genome-wide association studies’ summary statistics for dietary habits from Benjamin Neale’s lab (n= 361,194) and MDD from the Psychiatric Genomics Consortium(n =142,646). We used a weighted median approach to synthesize MR estimates across genetic instruments. For the robustness of our results, we compared weighted median results with results from the inverse-variance weighted method, the weighted mode method, and MR-PRESSO.ResultsBeef intake showed a significant protective effect against MDD (β = -1.25; p-value = 0.002; Bonferroni-corrected p-value = 0.034; 9 single nucleotide polymorphisms [SNPs]); and cereal intake was nominally significantly protective (β = -0.52; p-value = 0.011; 21 SNPs). In contrast, non-oily fish intake showed a nominally significantly effect on the risk of MDD (β = 0.84; p-value = 0.030; 6 SNPs). We obtained similar results by using an inverse-variance weighted method and weighted mode approach, although some results were non-significant. On the other hand, we did not observe any significant causal effect of MDD on dietary habits.ConclusionsIn this two-sample MR analysis, we observed that higher beef and cereal intake may be protective factors for MDD, and that higher non-oily fish intake might increase the risk for MDD. However, MDD did not appear to affect dietary habits. Potential mechanisms need to be further investigated to support our novel findings.
Locating cephalometric landmarks with multi-phase deep learning
Authors: Nishimoto Soh , Kawai Kenichiro , Fujiwara Toshihiro , Ishise Hisako , Kakibuchi Masao 
Published: July 2020

AbstractCephalometric analysis has long been one of the most helpful approaches in evaluating cranio-maxillo-facial skeletal profile. To perform this, locating anatomical landmarks on an X-ray image is a crucial step, demanding time and expertise. An automated cephalogram analyzer, if developed, will be a great help for practitioners. Artificial intelligence, including machine learning is emerging these days. Deep learning is one of the most developing techniques in data science field. The authors attempted to enhance the accuracy of an automated landmark predicting system utilizing multi-phase deep learning and voting. To guarantee objectivity, an open-to-the-public dataset, cephalometric images accompanied with coordinate values of 19 landmarks, were used. A regressional system was developed, consisted with convolutional neural networks of three phases. First phase network was to determine approximate position of each landmark, inputting whole area of compressed original images. Five secondary networks were to narrow down the area, based on the first phase prediction. Third phase networks were trained by small areas around respective landmarks, with original resolution. Third phase prediction with voting was done inputting 81 shifted areas. Successful detection rates improved as the phase advances. Voting in third phase improved successful detection rate. In comparison with previously reported benchmarks, using the same dataset, proposed system marked better results. Within the physical limitation of memory and computation, multi-phase deep learning may be a solution to deal with large images.
Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys
Authors: Grantz Kyra H. , Cummings Derek A.T. , Zimmer Shanta , Vukotich Charles , Galloway David , Schweizer Mary Lou , Guclu Hasan , Cousins Jennifer , Lingle Carrie , Yearwood Gabby M.H. , Li Kan , Calderone Patti , Noble Eva , Gao Hongjiang , Rainey Jeanette , Uzicanin Amra , Read Jonathan M. 
Published: July 2020

AbstractComparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.
Covid19, 2020 - a tutorial of sorts on reading data
Authors: Meilijson Isaac 
Published: July 2020

AbstractThe SIR differential equations in Epidemiology are re-examined in the context of Covid19, 2020. The number of recovered cases is calibrated in time. Methods for estimating all pertinent parameters are described. A notion of implied susceptible population size ISPS is introduced, as the potential target population size for which the solution to the SIR equations would yield the current number of new affected cases. Analysis is applied to the Covid19 2020 data of a number of countries, as reported by the Johns Hopkins University data repository. It will be observed that some countries under-report consistently the number of recovered cases.
Power law behaviour in the saturation regime of fatality curves of the COVID-19 pandemic
Authors: Vasconcelos Giovani L. , Macêdo Antônio M. S. , Duarte-Filho Gerson C. , Brum Arthur A. , Ospina Raydonal , Almeida Francisco A. G. 
Published: July 2020

ABSTRACWe apply a versatile growth model, whose growth rate is given by a generalised beta distribution, to describe the complex behaviour of the fatality curves of the COVID-19 disease for several countries in Europe and North America. We show that the COVID-19 epidemic curves not only may present a subexponential early growth but can also exhibit a similar subexponential (power-law) behaviour in the saturation regime. We argue that the power-law exponent of the latter regime, which measures how quickly the curve approaches the plateau, is directly related to control measures, in the sense that the less strict the control, the smaller the exponent and hence the slower the diseases progresses to its end. The power-law saturation uncovered here is an important result, because it signals to policymakers and health authorities that it is important to keep control measures for as long as possible, so as to avoid a slow, power-law ending of the disease. The slower the approach to the plateau, the longer the virus lingers on in the population, and the greater not only the final death toll but also the risk of a resurgence of infections.
Outcomes and factors influencing care decisions in life-threatening fetal and neonatal anomalies
Authors: Lee Esther J. , Stenekes Simone , Harlos Michael 
Published: July 2020

AbstractObjectiveA retrospective chart review was undertaken to describe the outcomes following the diagnosis of a life-threatening fetal and neonatal anomaly.Study DesignCriteria for a life-threatening anomaly included genetic conditions, renal and pulmonary diseases, central nervous system anomalies (CNS), and cardiac defects. Information that could impact decision making was collected from provincial databasesResults176 patients met the inclusion criteria. The majority of the diagnoses were in the genetic and CNS categories. 58% (n=103) decided to terminate the pregnancy. When a live birth occurred (n=39), the mean length of survival was 13.5 days (range 1-156 days), with one death occurring at home.ConclusionsEthnicity and geographical factors were associated with the decision to terminate a pregnancy. The involvement of the palliative care service was associated with decreased interventions. Further research to determine the needs of families would be helpful in identifying program priorities in perinatal palliative care.