bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gut microbiota affects prostate cancer risk through steroid hormone biosynthesis
Authors: Kalinen Sofia , Kallonen Teemu , Gunell Marianne , Ettala Otto , Jambor Ivan , Knaapila Juha , Syvänen Kari T. , Taimen Pekka , Poutanen Matti , Ohlsson Claes , Aronen Hannu J. , Ollila Helena , Pietilä Sami , Elo Laura L. , Lamminen Tarja , Hakanen Antti J. , Munukka Eveliina , Boström Peter J. ,   the Multi-IMPROD Study group
Published: August 2021

ABSTRACTPurposeAlthough prostate cancer is the most common cancer in men in Western countries, there is significant variability in geographical incidence. This might result from genetic factors, discrepancies in screening policies or differences in lifestyle. Gut microbiota has been recently associated with cancer progression, but its role in prostate cancer is unclear.MethodsIn a prospective multicenter clinical trial (NCT02241122), the gut microbiota profiles of 181 men with a clinical suspicion of prostate cancer were assessed utilizing 16S rRNA gene sequencing. Sequences were assigned to operational taxonomic units, and differential abundance analysis, α- and β-diversities, and predictive functional (PICRUSt) analyses were performed. Additionally, plasma steroid hormone levels were correlated with the predicted microbiota functions.ResultsSeveral differences in the gut microbiota between the subjects with and without prostate cancer were noted. Prevotella 9, members of the Erysipelotrichaceae family and Escherichia-Shigella were higher, and Jonquetella, Moryella, Anaeroglobus, Corynebacterium and CAG-352 were lower in the cancer group. Predictive functional analyses revealed higher 5-α-reductase, copper absorption, and retinal metabolism in the prostate cancer associated microbiome. Plasma testosterone associated negatively with the microbial 5-α-reductase activity (p=0.030). In a subgroup of men taking 5-α-reductase inhibitors (n=17), plasma estrone (p=0.027) and estradiol (p=0.059) levels were lower in men with predicted elevation of the microbial 5-α-reductase function.ConclusionsGut microbiota of the prostate cancer patients differed significantly compared to benign subjects. Microbial 5-α-reductase, copper absorption and retinol metabolism are potential mechanisms of action. These findings could explain the observed association of lifestyle, geography, and prostate cancer incidence.
SARS-CoV-2 specific T cells and antibodies in COVID-19 protection: a prospective study
Authors: Molodtsov Ivan A. , Kegeles Evgenii , Mitin Alexander N. , Mityaeva Olga , Musatova Oksana E. , Panova Anna E. , Pashenkov Mikhail V. , Peshkova Iuliia O. , Almaqdad Alsalloum , Asaad Walaa , Budikhina Anna S. , Deryabin Aleksander S. , Dolzhikova Inna V. , Filimonova Ioanna N. , Gracheva Alexandra N. , Ivanova Oxana I. , Kizilova Anastasia , Komogorova Viktoria V. , Komova Anastasia , Kompantseva Natalia I. , Lagutkin Denis A. , Lomakin Yakov A. , Maleeva Alexandra V. , Maryukhnich Elena V. , Mohammad Afraa , Murugin Vladimir V. , Murugina Nina E. , Navoikova Anna , Nikonova Margarita F. , Ovchinnikova Leyla A. , Pinegina Natalia V. , Potashnikova Daria M. , Romanova Elizaveta V. , Saidova Aleena A. , Sakr Nawar , Samoilova Anastasia G. , Serdyuk Yana , Shakirova Naina T. , Sharova Nina I. , Sheetikov Savely A. , Shemetova Anastasia F. , Shevkova Liudmila , Shpektor Alexander V. , Trufanova Anna , Tvorogova Anna V. , Ukrainskaya Valeria M. , Vinokurov Anatoliy S. , Vorobyeva Daria A. , Zornikova Ksenia V. , Efimov Grigory A. , Khaitov Musa R. , Kofiadi Ilya A. , Komissarov Alexey A. , Logunov Denis Y. , Naigovzina Nelli B. , Rubtsov Yury P. , Vasilyeva Irina A. , Volchkov Pavel , Vasilieva Elena 
Published: August 2021

SummaryRapid spread of COVID-19 pandemic made a substantial share of the world population immunised by SARS-CoV-2 antigens. Infection induces the development of virus-specific antibodies and T cells. Ample evidence on the antibody-mediated protection is contrasted by the elusive role of T cells in preventing infection. To explore the impact of T cells and to quantify the protective levels of the immune responses we conducted a large prospective study: 5,340 Moscow residents were evaluated for the antibody and cellular immune responses to SARS-CoV-2 and monitored for COVID-19 up to 300 days. The antibody and cellular responses were tightly interconnected, their magnitude inversely correlated with infection probability. Similar maximal level of protection was reached by individuals positive for both types of responses and by individuals with antibodies alone. Meanwhile, T cells in the absence of antibodies provided an intermediate level of protection. The real-world data on the protective effects of T cells have important implications for T cell immunology and development of the strategies to fight the pandemic.
Anticipating the hospital burden of future COVID-19 epidemic waves
Authors: Boennec Corentin , Alizon Samuel , Sofonea Mircea T 
Published: August 2021

AbstractForecasting SARS-CoV-2 epidemic trends with confidence more than a few weeks ahead is almost impossible as these entirely depend on political decisions. We address this problem by investigating the consequences for the health system of an epidemic wave of a given size. This approach yields semi-quantitative results that depend on the proportion of the population already infected and vaccinated. We introduce the COVimpact software, which allows users to visualise estimated numbers of ICU admissions, deaths, and infections stratified by age class at the French departmental, regional, or national level caused by the wave. We illustrate the usefulness of our approach by showing that for France, even with a 95% vaccination coverage, the current vaccine efficiency against the delta variant would make a large epidemic wave infecting 25% of the population difficult to sustain for the current hospital bed occupancy capacity. Overall, using the final epidemic wave size and ignoring detailed epidemiological dynamics yields valuable and practical insights to optimise public health response to epidemics.
The social media response to twice-weekly mass asymptomatic testing in England
Authors: Dennis Amelia , Robin Charlotte , Carter Holly 
Published: August 2021

AbstractBackgroundFrom 9th April 2021, everyone in England has been encouraged to take two COVID-19 tests per week. This is the first time that national mass asymptomatic testing has been introduced in the UK and the effectiveness of the policy depends on uptake with testing and willingness to self-isolate following a positive test result. This paper examines attitudes towards twice-weekly testing, as well as barriers and facilitators to engaging in testing.MethodsBetween 5th April and 28th May 2021 we searched Twitter, Facebook, and online news articles with publicly available comment sections to identify comments relating to twice-weekly testing. We identified 5783 comments which were then analysed using a framework analysis.ResultsWe identified nine main themes. Five themes related to barriers to engaging in testing: low perceived risk from COVID-19; mistrust in the government; concern about taking a test; perceived ineffectiveness of twice-weekly testing policy; and perceived negative impact of twice-weekly testing policy. Four themes related to facilitators to engaging in testing: wanting to protect others; positive perceptions of tests; a desire to return to normal; and perceived efficacy for reducing asymptomatic transmission.ConclusionsOverall, the comments identified indicated predominately negative attitudes towards the twice weekly testing policy. Several recommendations can be made to improve engagement with twice weekly testing, including: 1) communicate openly and honestly about the purpose of testing; 2) provide information about the accuracy of tests; 3) provide financial support for those required to self-isolate, and; 4) emphasise accessibility of testing.
Seroresponse to SARS-CoV-2 vaccines among maintenance dialysis patients
Authors: Hsu Caroline M. , Weiner Daniel E. , Aweh Gideon N. , Manley Harold J. , Ladik Vladimir , Frament Jill , Miskulin Dana , Agyropoulos Christos , Abreo Kenneth , Chin Andrew , Gladish Reginald , Salman Loay , Johnson Doug , Lacson Eduardo K. 
Published: August 2021

AbstractImportanceVaccines against SARS-CoV-2 are highly effective in the general population; however, their efficacy may be diminished in maintenance dialysis patients, a population particularly vulnerable to COVID-19 infection and morbidity.ObjectiveWe assessed vaccine response in a national sample of maintenance dialysis patients and identified predictors of response.DesignRetrospective cohort studySetting130 Dialysis Clinic, Inc (DCI) facilitiesParticipantsMaintenance dialysis patients without known prior COVID-19 or a positive baseline antibody titerExposure(s)Vaccine type and clinical characteristicsMain Outcome(s)Using a semi-quantitative assay for antibodies against SARS-CoV-2 spike antigen, vaccine response was defined as at least one titer ≥1 U/L between 14 and 74 days after completion of a SARS-CoV-2 vaccine series. Regression analysis was used to identify characteristics associated with response.ResultsAmong 1528 patients, 437 received BNT162b2/Pfizer vaccine, 766 received mRNA-1273/Moderna, and 325 received Ad26.COV2.S/Janssen. Serologic response differed significantly by vaccine type: 381/437 (87%) among BNT162b2/Pfizer recipients, 736/766 (96%) among mRNA-1273/Moderna recipients, and 119/325 (37%) among Ad26.COV2.S/Janssen recipients. Vaccine type, older age, immune-modulating medication, history of transplantation, and lower serum albumin were associated with vaccine non-response.Conclusions and RelevanceSerologic response to mRNA vaccines is robust among maintenance dialysis patients. Future research should evaluate durability of this response, correlation between seroresponse and protection from COVID-19, and the role of the AD26.COV2.S/Janssen vaccine in this vulnerable population.
Assessment of inter-laboratory differences in SARS-CoV-2 consensus genome assemblies between public health laboratories in Australia
Authors: Foster Charles S.P. , Stelzer-Braid Sacha , Deveson Ira W. , Bull Rowena A. , Yeang Malinna , Phan-Au Jane , Silva Mariana Ruiz , van Hal Sebastiaan J. , Rockett Rebecca J. , Sintchenko Vitali , Kim Ki Wook , Rawlinson William D. 
Published: August 2021

AbstractWhole-genome sequencing of viral isolates is critical for informing transmission patterns and ongoing evolution of pathogens, especially during a pandemic. However, when genomes have low variability in the early stages of a pandemic, the impact of technical and/or sequencing errors increases. We quantitatively assessed inter-laboratory differences in consensus genome assemblies of 72 matched SARS-CoV-2-positive specimens sequenced at different laboratories in Sydney, Australia. Raw sequence data were assembled using two different bioinformatics pipelines in parallel, and resulting consensus genomes were compared to detect laboratory-specific differences. Matched genome sequences were predominantly concordant, with a median pairwise identity of 99.997%. Identified differences were predominantly driven by ambiguous site content. Ignoring these produced differences in only 2.3% (5/216) of pairwise comparisons, each differing by a single nucleotide. Matched samples were assigned the same Pango lineage in 98.2% (212/216) of pairwise comparisons, and were mostly assigned to the same phylogenetic clade. However, epidemiological inference based only on single nucleotide variant distances may lead to significant differences in the number of defined clusters if variant allele frequency thresholds for consensus genome generation differ between laboratories. These results underscore the need for a unified, best-practices approach to bioinformatics between laboratories working on a common outbreak problem.
Using routine emergency department data for syndromic surveillance of acute respiratory illness in Germany, week 10-2017 to 10-2021
Authors: Boender T. Sonia , Cai Wei , Schranz Madlen , Kocher Theresa , Wagner Birte , Ullrich Alexander , Buda Silke , Zöllner Rebecca , Greiner Felix , Diercke Michaela , Grabenhenrich Linus 
Published: August 2021

AbstractBackgroundThe Coronavirus disease 2019 (COVID-19) pandemic expanded the need for timely information on acute respiratory illness on the population level.AimWe explored the potential of routine emergency department data for syndromic surveillance of acute respiratory illness in Germany.MethodsWe included routine attendance data from emergency departments who continuously transferred data between week 10-2017 and 10-2021, with ICD-10 codes available for >75% of the attendances. Case definitions for acute respiratory illness (ARI), severe ARI (SARI), influenza-like illness (ILI), respiratory syncytial virus disease (RSV) and COVID-19 were based on a combination of ICD-10 codes, and/or chief complaints, sometimes combined with information on hospitalisation and age.ResultsWe included 1,372,958 attendances from eight emergency departments. The number of attendances dropped in March 2020, increased during summer, and declined again during the resurge of COVID-19 cases in autumn and winter of 2020/2021. A pattern of seasonality of acute respiratory infections could be observed. By using different case definitions (i.e. for ARI, SARI, ILI, RSV) both the annual influenza seasons in the years 2017-2020 and the dynamics of the COVID-19 pandemic in 2020-2021 were apparent. The absence of the 2020/2021 flu season was visible, parallel to the resurge of COVID-19 cases. The percentage SARI among ARI cases peaked in April-May 2020 (17%) and November 2020-January 2021 (14%).ConclusionSyndromic surveillance using routine emergency department data has the potential to monitor the trends, timing, duration, magnitude and severity of illness caused by respiratory viruses, including both influenza and SARS-CoV-2.
Bias as a source of inconsistency in ivermectin trials for COVID-19: A systematic review
Authors: Izcovich Ariel , Peiris Sasha , Ragusa Martín , Tortosa Fernando , Rada Gabriel , Aldighieri Sylvain , Reveiz Ludovic 
Published: August 2021

AbstractBackground and purposeThe objective of this systematic review is to summarize the effects of ivermectin for the prevention and treatment of patients with COVID-19 and to assess inconsistencies in results from individual studies with focus on risk of bias due to methodological limitations.Evidence reviewWe searched the L.OVE platform through July 6, 2021 and included randomized trials (RCTs) comparing ivermectin to standard or other active treatments. We conducted random-effects pairwise meta-analysis, assessed the certainty of evidence using the GRADE approach and performed sensitivity analysis excluding trials with risk of bias.ResultsWe included 29 RCTs which enrolled 5592 cases. Overall, the certainty of the evidence was very low to low. Compared to standard of care, ivermectin may reduce mortality, may increase symptom resolution or improvement, may increase viral clearance, may reduce infections in exposed individuals and may decrease hospitalizations (Risk difference (RD) 21 fewer per 1000, 95%CI: 35 fewer to 4 more). However, after excluding trials classified as “high risk” or “some concerns” in the risk of bias assessment, most estimates of effect changed substantially: Compared to standard of care, low certainty evidence suggests that ivermectin may not significantly reduce mortality (RD 7 fewer per 1000, 95%CI: 77 fewer to 108 more) nor mechanical ventilation (RD 6 more per 1000, 95%CI: 43 fewer to 86 more), and moderate certainty evidence shows that it probably does not significantly increase symptom resolution or improvement (RD 14 more per 1000, 95%CI: 29 fewer to 71 more) nor viral clearance (RD 12 fewer per 1000, 95%CI: 84 fewer to 76 more). It is uncertain if ivermectin increases or decreases severe adverse events and symptomatic infections in exposed individuals.Conclusions and RelevanceIvermectin may not improve clinically important outcomes in patients with COVID-19 and its effects as a prophylactic intervention in exposed individuals are uncertain. Previous reports concluding significant benefits associated with ivermectin are based on potentially biased results reported by studies with substantial methodological limitations. Further research is needed.
Feasibility of Continuous Distal Body Temperature for Passive, Early Pregnancy Detection
Authors: Grant Azure , Smarr Benjamin 
Published: August 2021

AbstractThe majority of American women become aware of pregnancy ~3-7 weeks after conception, and all must seek testing to confirm their pregnant status. The delay between conception and awareness is often a time in which contraindicated behaviors take place. However, there is long standing evidence that passive, early pregnancy detection may be possible using body temperature. To address this possibility, we analyzed 30 individuals’ continuous distal body temperature (DBT) in the 180 days surrounding self-reported conception in comparison to self-reported pregnancy confirmation. Features of DBT nightly maxima changed rapidly following self-reported conception, reaching uniquely elevated values after a median of 5.5 ± 3.5 days, whereas individuals reported a positive pregnancy test result at a median of 14.5 ± 4.2 days. Together, we were able to generate a retrospective, hypothetical alert a median of 9 ± 3.9 days prior to the date at which individuals received a positive pregnancy test. Continuous temperature-derived features can provide early, passive indication of pregnancy onset. We propose these features for testing and refinement in clinical settings, and for exploration in large, diverse cohorts. The development of pregnancy detection using DBT may reduce the delay from conception to awareness and increase the agency of pregnant individuals.
Linking Free Text Documentation of Functioning and Disability to the ICF with Natural Language Processing
Authors: Newman-Griffis Denis , Maldonado Jonathan Camacho , Ho Pei-Shu , Sacco Maryanne , Silva Rafael Jimenez , Porcino Julia , Chan Leighton 
Published: August 2021

AbstractBackgroundInvaluable information on patient functioning and the complex interactions that define it is recorded in free text portions of the Electronic Health Record (EHR). Leveraging this information to improve clinical decision-making and conduct research requires natural language processing (NLP) technologies to identify and organize the information recorded in clinical documentation.MethodsWe used NLP methods to analyze information about patient functioning recorded in two collections of clinical documents pertaining to claims for federal disability benefits from the U.S. Social Security Administration (SSA). We grounded our analysis in the International Classification of Functioning, Disability and Health (ICF), and used the ICF’s Activities and Participation domain to classify information about functioning in three key areas: Mobility, Self-Care, and Domestic Life. After annotating functional status information in our datasets through expert clinical review, we trained machine learning-based NLP models to automatically assign ICF categories to mentions of functional activity.ResultsWe found that rich and diverse information on patient functioning was documented in the free text records. Annotation of 289 documents for Mobility information yielded 2,455 mentions of Mobility activities and 3,176 specific actions corresponding to 13 ICF-based categories. Annotation of 329 documents for Self-Care and Domestic Life information yielded 3,990 activity mentions and 4,665 specific actions corresponding to 16 ICF-based categories. NLP systems for automated ICF coding achieved over 80% macro-averaged F-measure on both datasets, indicating strong performance across all ICF categories used.ConclusionsNLP can help to navigate the tradeoff between flexible and expressive clinical documentation of functioning and standardizable data for comparability and learning. The ICF has practical limitations for classifying functional status information in clinical documentation, but presents a valuable framework for organizing the information recorded in health records about patient functioning. This study advances the development of robust, ICF-based NLP technologies to analyze information on patient functioning, and has significant implications for NLP-powered analysis of functional status information in disability benefits management, clinical care, and research.
StainedGlass: Interactive visualization of massive tandem repeat structures with identity heatmaps
Authors: Vollger Mitchell R. , Kerpedjiev Peter , Phillippy Adam M. , Eichler Evan E. 
Published: August 2021

AbstractSummaryVisualization and analysis of genomic repeats is typically accomplished through the use of dot plots; however, the emergence of telomere-to-telomere assemblies with multi-megabase repeats requires new visualization strategies. Here, we introduce StainedGlass which can generate publication quality figures and interactive visualizations that depict the identity and orientation of multi-megabase repeat structures at a genome-wide scale. The tool can rapidly reveal higher-order structures and improve the inference of evolutionary history for some of the most complex regions of genomes.Availability and implementationStainedGlass is implemented using Snakemake and is available open source under the MIT license athttps://mrvollger.github.io/StainedGlass/.Contactmvollger@uw.edu
Using Natural Language Processing to Classify Serious Illness Communication with Oncology Patients
Authors: Davoudi Anahita , Tissot Hegler , Doucette Abigail , Gabriel Peter E. , Parikh Ravi , Mowery Danielle L. , Miranda Stephen 
Published: August 2021

AbstractOne core measure of healthcare quality set forth by the Institute of Medicine is whether care decisions match patient goals. High-quality “serious illness communication” about patient goals and prognosis is required to support patient-centered decision-making, however current methods are not sensitive enough to measure the quality of this communication or determine whether care delivered matches patient priorities. Natural language processing (NLP) offers an efficient method for identification and evaluation of documented serious illness communication, which could serve as the basis for future quality metrics in oncology and other forms of serious illness. In this study, we trained NLP algorithms to identify and characterize serious illness communication with oncology patients.
Virological characteristics of SARS-CoV-2 vaccine breakthrough infections in health care workers
Authors: Shamier Marc C. , Tostmann Alma , Bogers Susanne , de Wilde Janet , IJpelaar Jeroen , van der Kleij Willemijn A. , de Jager Herbert , Haagmans Bart L. , Molenkamp Richard , Oude Munnink Bas. B. , van Rossum Carsten , Rahamat-Langendoen Janette , van der Geest Nannet , Bleeker-Rovers Chantal P. , Wertheim Heiman , Koopmans Marion P.G. , GeurtsvanKessel Corine H. 
Published: August 2021

AbstractBackgroundSARS-CoV-2 vaccines are highly effective at preventing COVID-19-related morbidity and mortality. As no vaccine is 100% effective, breakthrough infections are expected to occur.MethodsWe analyzed the virological characteristics of 161 vaccine breakthrough infections in a population of 24,706 vaccinated healthcare workers (HCWs), using RT-PCR and virus culture.ResultsThe delta variant (B.1.617.2) was identified in the majority of cases. Despite similar Ct-values, we demonstrate lower probability of infectious virus detection in respiratory samples of vaccinated HCWs with breakthrough infections compared to unvaccinated HCWs with primary SARS-CoV-2 infections. Nevertheless, infectious virus was found in 68.6% of breakthrough infections and Ct-values decreased throughout the first 3 days of illness.ConclusionsWe conclude that rare vaccine breakthrough infections occur, but infectious virus shedding is reduced in these cases.