bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cardiovascular Disease Risk Prediction Models in Haiti: Implications for Primary Prevention in Low-Middle Income Countries
Authors: Yan Lily D , Pierre Jean Lookens , Rouzier Vanessa , Théard Michel , Apollon Alexandra , St-Preux Stephano , Kingery Justin R , Jamerson Kenneth A , Deschamps Marie , Pape Jean W , Safford Monika M , McNairy Margaret L 
Published: August 2021

AbstractBackgroundCardiovascular diseases (CVD) are rapidly increasing in low-middle income countries (LMICs). Accurate risk assessment is essential to reduce premature CVD by targeting primary prevention and risk factor treatment among high-risk groups. Available CVD risk prediction models are built on predominantly Caucasian, high-income country populations, and have not been evaluated in LMIC populations.ObjectiveTo compare the predicted 10-year risk of CVD and identify high-risk groups for targeted prevention and treatment in Haiti.MethodsWe used cross-sectional data within the Haiti CVD Cohort Study, including 653 adults ≥ 40 years without known history of CVD and with complete data. Six CVD risk prediction models were compared: pooled cohort equations (PCE), adjusted PCE with updated cohorts, Framingham CVD Lipids, Framingham CVD Body Mass Index (BMI), WHO Lipids, and WHO BMI. Risk factors were measured during clinical exams. Primary outcome was continuous and categorical predicted 10-year CVD risk. Secondary outcome was statin eligibility.ResultsSeventy percent were female, 65.5% lived on a daily income of ≤1 USD, 57.0% had hypertension, 14.5% had hypercholesterolemia, 9.3% had diabetes mellitus, 5.5% were current smokers, and 2.0% had HIV. Predicted 10-year CVD risk ranged from 3.9% in adjusted PCE (IQR 1.7-8.4) to 9.8% in Framingham-BMI (IQR 5.0-17.8), and Spearman rank correlation coefficients ranged from 0.87 to 0.98. The percent of the cohort categorized as high risk using the uniform threshold of 10-year CVD risk ≥ 7.5% ranged from 28.8% in the adjusted PCE model to 62.0% in the Framingham-BMI model (χ2= 331, p value < 0.001). Statin eligibility also varied widely.ConclusionsIn the Haiti CVD Cohort, there was substantial variation in the proportion identified as high-risk and statin eligible using existing models, leading to very different treatment recommendations and public health implications depending on which prediction model is chosen. There is a need to design and validate CVD risk prediction tools for low-middle income countries that include locally relevant risk factors.Trial registrationclinicaltrials.govNCT03892265
Fractality of tics as a quantitative assessment tool for Tourette syndrome
Authors: Beeler Payton , Jensen Nicholas O. , Kim Soyoung , Robichaux-Viehoever Amy , Schlaggar Bradley L. , Greene Deanna J. , Black Kevin J. , Chakrabarty Rajan 
Published: August 2021

AbstractTics manifest as brief, purposeless, and unintentional movements or noises that, for many individuals, can be suppressed temporarily with effort. Peterson and Leckman (1998) hypothesized that the chaotic temporal nature of tics could possess an inherent fractality, that is, have neighbor-to-neighbor correlation at all levels of time scale. However, demonstrating this phenomenon has eluded researchers for more than two decades, primarily because of the challenges associated with estimating the scale-invariant, power law exponent – called the fractal dimension Df– from fractional Brownian noise. Here, we confirm this hypothesis and establish the fractality of tics by examining two tic time series datasets collected 6-12 months apart in children with tics, using one-dimensional random walk models. We find that Dfincreases from ∼1.4 to 1.75 in order of decreasing tic severity, and is correlated with tic severity as measured by the YGTTS total tic score. We demonstrate Dfto be a sensitive parameter in examining the effect of several tic suppression conditions on the tic time series. We confirm the fractal nature of tics in Tourette syndrome (TS) and extend the finding to Provisional Tic Disorder. Our findings pave the way for utilizing the fractal nature of tics as a robust quantitative tool for estimating tic severity and treatment effectiveness, as well as a marker for differentiating typical from functional tics.
Human gene function publications that describe wrongly identified nucleotide sequence reagents are unacceptably frequent within the genetics literature
Authors: Park Yasunori , West Rachael A , Pathmendra Pranujan , Favier Bertrand , Stoeger Thomas , Capes-Davis Amanda , Cabanac Guillaume , Labbé Cyril , Byrne Jennifer A 
Published: August 2021

AbstractNucleotide sequence reagents underpin a range of molecular genetics techniques that have been applied across hundreds of thousands of research publications. We have previously reported wrongly identified nucleotide sequence reagents in human gene function publications and described a semi-automated screening tool Seek & Blastn to fact-check the targeting or non-targeting status of nucleotide sequence reagents. We applied Seek & Blastn to screen 11,799 publications across 5 literature corpora, which included all original publications inGenefrom 2007-2018 and all original open-access publications inOncology Reportsfrom 2014-2018. After manually checking the Seek & Blastn screening outputs for over 3,400 human research papers, we identified 712 papers across 78 journals that described at least one wrongly identified nucleotide sequence. Verifying the claimed identities of over 13,700 nucleotide sequences highlighted 1,535 wrongly identified sequences, most of which were claimed targeting reagents for the analysis of 365 human protein-coding genes and 120 non-coding RNAs, respectively. The 712 problematic papers have received over 17,000 citations, which include citations by human clinical trials. Given our estimate that approximately one quarter of problematic papers are likely to misinform or distract the future development of therapies against human disease, urgent measures are required to address the problem of unreliable gene function papers within the literature.Author summaryThis is the first study to have screened the gene function literature for nucleotide sequence errors at the scale that we describe. The unacceptably high rates of human gene function papers with incorrect nucleotide sequences that we have discovered represent a major challenge to the research fields that aim to translate genomics investments to patients, and that commonly rely upon reliable descriptions of gene function. Indeed, wrongly identified nucleotide sequence reagents represent a double concern, as both the incorrect reagents themselves and their associated results can mislead future research, both in terms of the research directions that are chosen and the experiments that are undertaken. We hope that our research will inspire researchers and journals to seek out other problematic human gene function papers, as we are unfortunately concerned that our results represent the tip of a much larger problem within the literature. We hope that our research will encourage more rigorous reporting and peer review of gene function results, and we propose a series of responses for the research and publishing communities.
Internet of Things Architecture for Cellular Biology
Authors: Parks David F. , Voitiuk Kateryna , Geng Jinghui , Elliott Matthew A. T. , Keefe Matthew G. , Jung Erik A. , Robbins Ash , Baudin Pierre V. , Ly Victoria T. , Hawthorne Nico , Yong Dylan , Sanso Sebastian E. , Rezaee Nick , Sevetson Jess , Seiler Spencer T. , Currie Rob , Pollen Alex A. , Hengen Keith B. , Nowakowski Tomasz J. , Mostajo-Radji Mohammed A. , Salama Sofie R. , Teodorescu Mircea , Haussler David 
Published: August 2021

AbstractThe Internet of Things (IoT) provides a simple framework to easily control online devices. IoT is now a commonplace tool used by technology companies, but it is rarely used in biology experiments. IoT can benefit research through alarm notifications, automation, and the real-time monitoring of experiments. We developed and implemented an IoT architecture to control biological devices used in experiments. We developed our own electrophysiology, microscopy, and microfluidic devices so that may be controlled through a unified IoT architecture. The system allows each device to be monitored and controlled through an online web tool. We present our IoT architecture so other labs may replicate it for their own experiments.
Design and quality control of large-scale two-sample Mendelian randomisation studies
Authors: Haycock Philip C. , Borges Maria Carolina , Burrows Kimberly , Lemaitre Rozenn N. , Harrison Sean , Burgess Stephen , Chang Xuling , Westra Jason , Khankari Nikhil K. , Tsilidis Kostas , Gaunt Tom , Hemani Gib , Zheng Jie , Truong Therese , OMara Tracy , Spurdle Amanda B. , Law Matthew H. , Slager Susan L. , Birmann Brenda M. , Hosnijeh Fatemeh Saberi , Mariosa Daniela ,   ACCC,   CCFR-CORECT-GECCO,   EPITHYR,   InterLymph,   ECAC,   ILCCO,   KIDRISK,   PRACTICAL,   PanScan,   PanC4, Amos Chris I. , Hung Rayjean J. , Zheng Wei , Gunter Marc J. , Smith George Davey , Relton Caroline , Martin Richard M 
Published: August 2021

AbstractBackgroundMendelian randomization studies are susceptible to meta-data errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors.MethodsWe invited cancer GWAS to share summary association statistics with the FAMRC and subjected the collated data to a comprehensive QC pipeline. We identified meta data errors through comparison of study-specific statistics to external reference datasets (the NHGRI-EBI GWAS catalog and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants:1) GWAS hits for fatty acids, 2) GWAS hits for cancer and 3) a 1000 genomes reference set.ResultsWe collated summary data from six fatty acid and 49 cancer GWAS. Meta data errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (13%). After resolving analytical issues and excluding unreliable data, we created a dataset of 219,842 genetic associations with 87 cancer types.ConclusionIn this large MR collaboration, 13% of included studies were affected by a substantial meta data error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of post-GWAS analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).
Measuring vaccine efficacy against infection and disease in clinical trials: sources and magnitude of bias in COVID-19 vaccine efficacy estimates
Authors: Williams Lucy R. , Ferguson Neil M. , Donnelly Christl A. , Grassly Nicholas C. 
Published: August 2021

AbstractBackgroundPhase III trials have estimated COVID-19 vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections.MethodsWe developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic and any SARS-CoV-2 infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections.ResultsVE against asymptomatic infection measured by PCR or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias towards underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4 to 77.1) and 70.9% (95% UI 49.8 to 80.7) respectively.ConclusionMultiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.
Preterm birth increases placental expression of multidrug resistance (MDR) transporters irrespective of prepregnancy body mass index (BMI)
Authors: Scott Hailey , Martinelli Lilian M , Bloise Enrrico , Connor Kristin L 
Published: August 2021

AbstractContextPreterm birth (PTB) and suboptimal prepregnancy body mass index (BMI) operate through inflammatory pathways to impair fetoplacental development. Placental efflux transporters mediate fetal protection and nutrition, however few studies consider the effect of both PTB and BMI on fetal protection. We hypothesized that PTB would alter the expression of placental multidrug resistance (MDR) transporters and selected pro-inflammatory cytokines, and that maternal underweight and obesity would further impair placental phenotype.ObjectiveTo determine whether placental MDR transporters P-glycoprotein (P-gp, encoded by ABCB1) and breast cancer resistance protein (BCRP/ABCG2), and pro-inflammatory cytokine levels are altered by PTB and maternal BMI.Design and OutcomesA cross-sectional study was conducted to assess the effect of PTB (+/- chorioamnionitis), or the effect of maternal prepregnancy BMI on placental MDR transporter and interleukin [IL]-6 and 8 expression in 60 preterm and 36 term pregnancies.ResultsABCB1 expression was increased in preterm compared to term placentae (p=0.04). P-gp (p=0.008) and BCRP (p=0.01) immunolabeling was increased among all preterm compared to term placentae, with P-gp expression further increased in preterm pregnancies with chorioamnionitis (PTC, p=0.007). Placental IL-6 mRNA expression was decreased in PTC compared to term placentae (p=0.0005), and PTC was associated with the greatest proportion of anti-inflammatory medications administered during pregnancy. Maternal BMI group did not influence placental outcomes.ConclusionsPTB and infection, but not prepregnancy BMI, alter placental expression of MDR transporters and IL-6. This may have implications for fetal exposure to xenobiotics that may be present in the maternal circulation in pregnancies complicated by PTB.
COVID-19 in hospitalized patients in 4 hospitals in San Isidro, Buenos Aires, Argentina
Authors: Barra María Ana , Carlos Medinacelli Nelson Adolfo , Meza Padilla Camilo Andres , Di Rocco Lucrecia , Larrea Ramiro Manuel , Gaudenzi Giuliano , Mastrovincenzo Verónica Vanesa , Raña Elisa , Moreno Inés , Sörvik Dagmar Ana , Sarlingo Andrea , Dadomo Florencia , Torrilla Miguel 
Published: August 2021

AbstractIn December 2019, a novel illness called coronavirus disease 2019 (COVID-19) was described in China and became pandemic in a few months. The first case was detected in Argentina on March 3, 2020.A multicentre prospective observational cohort study on hospitalized patients with COVID- 19 was conducted in 4 hospitals in San Isidro district from March 1, 2020 to October 31. Data was obtained by the attendant physician. 668 patients were included, the median age was 54 years, and 42.7% were female. Male sex and older age were associated with COVID-19 disease and more strongly with severity. Most frequent symptoms were fever and cough followed by dyspnoea, myalgia, odynophagia, headache, anosmia, and diarrhoea. Non-severe patients had more upper respiratory symptoms while severe patients had mainly lower respiratory symptoms on admission. Most common comorbidities were arterial hypertension, diabetes, and cardiovascular disease. A great proportion of patients had normal thorax X-ray and ground-glass opacity in tomography. In severe patients, radiography and tomography had a predominant ground – glass pattern, but normal radiography and tomography on presentation were present in 22% and 5.9%, respectively. The absence of fever and normal radiology on admission neither excluded the disease nor further severity. PCR elevation was related with COVID-19 disease and with severity, while lymphopenia was more related with the disease and leukocytosis and thrombocytopenia with severity. 8, 4% of patients were health care workers. The mortality rate was 12.4%, 32.7% in severe patients and 61.2% in ventilated patients. Mortality was higher in the public hospital, probably associated with patients with older age and more comorbidities. All these observations can contribute to the knowledge of this disease in terms of diagnosis and prognosis.
Binary toxin expression by Clostridioides difficile is associated with worse disease
Authors: Young Mary K. , Leslie Jhansi L. , Madden Gregory R. , Lyerly David M. , Carman Robert J. , Stewart David B. , Abhyankar Mayuresh M. , Petri William A. 
Published: August 2021

AbstractBackgroundThe incidence of Clostridioides difficile infection (CDI) has increased over the past two decades and is considered an urgent threat by the Centers for Disease Control. Hypervirulent strains such as ribotype 027, that possess genes for an additional toxin C. difficile binary toxin (CDT) are contributing to increased morbidity and mortality. In the mouse model, CDT activates Toll-like receptor 2 resulting in suppression of a protective type 2 innate immune response mediated by eosinophils.MethodsWe retrospectively tested stool from 215 CDI patients for CDT by enzyme-linked immunosorbent assay (ELISA). Stratifying patients by CDT status, we assessed if disease severity and clinical outcomes correlated with CDT positivity. Additionally, we performed 16 S rRNA gene sequencing to examine if CDT positive samples had an altered fecal microbiota.ResultsWe found that patients with CdtB, the pore forming component of CDT, detected in their stool were more likely to have severe disease and had higher 90-day mortality compared to CDT negative patients. CDT positive patients also had higher C. difficile bacterial burden and white blood cell counts. There was no significant difference in gut microbiome diversity between CDT positive and negative patients.ConclusionsPatients with fecal samples that were positive for CDT had increased disease severity and worse clinical outcomes. Utilization of PCR and C. difficile Toxins A and B testing may not reveal the entire picture when diagnosing CDI and the detection of CDT-expressing strains may be valuable during patient treatment.SummaryWe found that CDI patients with CDT detected in stool by immunoassay were more likely to have severe disease and had higher 90-day mortality.
TREATMENTS, RESOURCE UTILIZATION, AND OUTCOMES OF COVID-19 PATIENTS PRESENTING TO EMERGENCY DEPARTMENTS ACROSS PANDEMIC WAVES: AN OBSERVATIONAL STUDY BY THE CANADIAN COVID-19 EMERGENCY DEPARTMENT RAPID RESPONSE NETWORK (CCEDRRN)
Authors: Hohl Corinne M. , Rosychuk Rhonda J. , Hau Jeffrey P. , Hayward Jake , Landes Megan , Yan Justin W. , Ting Daniel K. , Welsford Michelle , Archambault Patrick M , Mercier Eric , Chandra Kavish , Davis Philip , Vaillancourt Samuel , Leeies Murdoch , Small Serena , Morrison Laurie J. 
Published: August 2021

ABSTRACTBackgroundTreatment strategies for coronavirus disease 2019 (COVID-19) evolved between pandemic waves. Our objective was to compare treatments, acute care resource utilization, and outcomes of COVID-19 patients presenting to Emergency Departments across two pandemic waves.MethodsThis observational study enrolled consecutive eligible COVID-19 patients presenting to 46 Emergency Departments participating in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) between March 1 and December 31, 2020. We collected data by retrospective chart review. Our primary outcome was in-hospital mortality. We used logistic regression modeling to assess the impact of pandemic wave on outcomes.ResultsWe enrolled 9,967 patients in 8 provinces, 3,336 from the first and 6,631 from the second wave. Patients in the second wave were younger, fewer met criteria for severe COVID-19, and more were discharged from the Emergency Department. Adjusted for patient characteristics and disease severity, steroid use increased (odds ratio [OR] 8.0; 95% confidence interval [CI] 6.4 – 10.0), while the use of invasive mechanical ventilation decreased (OR 0.5; 95%CI 0.4 – 0.6) in the second wave. After adjusting for differences in patient characteristics and disease severity, the odds of hospitalization (OR 0.7; 95%CI 0.6 – 0.8) and critical care admission (OR 0.6; 95%CI 0.4 – 0.7) decreased, while mortality remained unchanged (OR 1.0; 95%CI 0.7-1.4).InterpretationIn patients presenting to Canadian acute care facilities, rapid uptake of steroid therapy was evident. Mortality was stable despite lower critical care utilization in the second wave.Trial RegistrationClinicaltrials.gov, NCT04702945
Three-dimensional printing of patient-specific lung phantoms for CT imaging: emulating lung tissue with accurate attenuation profiles and textures
Authors: Mei Kai , Geagan Michael , Roshkovan Leonid , Litt Harold I. , Gang Grace J. , Shapira Nadav , Stayman J. Webster , Noël Peter B. 
Published: August 2021

AbstractPurposePhantoms are a basic tool for assessing and verifying performance in CT research and clinical practice. Patient-based realistic lung phantoms accurately representing textures and densities are essential in developing and evaluating novel CT hardware and software. This study introduces PixelPrint, a 3D printing solution to create patient-based lung phantoms with accurate attenuation profiles and textures.MethodsPixelPrint, a software tool, was developed to convert Patient DICOM images directly into printer instructions (G-code). The density was modeled as the ratio of filament to voxel volume to emulate attenuation profiles for each voxel. A calibration phantom was designed to determine the mapping between filament line width and Hounsfield Units (HU) within the range of human lungs. For evaluation of PixelPrint, a phantom based on a human lung slice was manufactured and scanned with the same CT scanner and protocol used for the patient scan. Density and geometrical accuracy between phantom and patient CT data was evaluated for various anatomical features in the lung.ResultsFor the calibration phantom, measured mean Hounsfield units show a very high level of linear correlation with respect to the utilized filament line widths, (r > 0.999). Qualitatively, the CT image of the patient-based phantom closely resembles the original CT image both in texture and contrast levels, with clearly visible vascular and parenchymal structures. Regions-of-interest (ROIs) comparing attenuation illustrated differences below 15 HU. Manual size measurements performed by an experienced thoracic radiologist reveal a high degree of geometrical correlation of details between identical patient and phantom features, with differences smaller than the intrinsic spatial resolution of the scans.ConclusionThe present study demonstrates the feasibility of 3D printed patient-based lung phantoms with accurate organ geometry, image texture, and attenuation profiles. PixelPrint will enable applications in the research and development of CT technology, including further development in radiomics.