bluuebunny/crossref_metadata_2025_split huggingface dataset:
Medical Device–Related Pressure Injuries in Infants and Children
Authors: Stellar Judith J. , Hasbani Natalie R. , Kulik Lindyce A. , Shelley Stacey S. , Quigley Sandy , Wypij David , Curley Martha A. Q. 
Published: September 2020

PURPOSE:
The purpose of this study was to describe medical device–related pressure injuries (MDRPIs) in hospitalized pediatric patients.

DESIGN:
A prospective, descriptive study.

SAMPLE/SUBJECTS AND SETTING:
The sample comprised 625 patients cared for in 8 US pediatric hospitals. Participants were aged preterm to 21 years, on bed rest for at least 24 hours, and had a medical device in place.

METHODS:
Two nursing teams, blinded to the other's assessments, worked in tandem to assess pressure injury risk, type of medical devices in use, and preventive interventions for each medical device. They also identified the presence, location, and stage of MDRPI. Subjects were observed up to 8 times over 4 weeks, or until discharge, whichever occurred first.

RESULTS:
Of 625 enrolled patients, 42 (7%) developed 1 or more MDRPIs. Two-thirds of patients with MDRPIs were younger than 8 years. Patients experiencing MDRPIs had higher acuity scores on hospital admission, were more frequently cognitively and/or functionally impaired, or were extreme in body mass index. Respiratory devices caused the most injuries (6.19/1000 device-days), followed by immobilizers (2.40/1000 device-days), gastric tubes (2.24/1000 device-days), and external monitoring devices (1.77/1000 device-days). Of the 6336 devices in place, 36% did not have an MDRPI preventive intervention in place. Clinical variables contributing to MDRPI development included intensive care unit care (odds ratio [OR] 8.9, 95% confidence interval [CI] 1.9-43.6), use of neuromuscular blockade (OR 3.7, 95% CI 1.7-7.8), and inotropic/vasopressor medications (OR 2.7, 95% CI 1.7-4.3). Multivariable analysis indicated that Braden QD scores alone predicted MDRPI development.

CONCLUSION:
Medical devices are common in hospitalized infants and children and these medical devices place patients at risk for MDRPI.
Gender-Related Variables for Health Research
Authors: Nielsen Mathias W. , Stefanick Marcia L. , Peragine Diana , Neilands Torsten B. , Ioannidis John P. A. , Pilote Louise , Prochaska Judith J. , Cullen Mark R. , Einstein Gillian , Klinge Ineke , LeBlanc Hannah , Paik Hee Y. , Schiebinger Londa 
Published: September 2020

AbstractThis study develops a gender assessment tool—the Stanford Gender-Related Variables for Health Research—for use in clinical and population research, including large-scale health surveys involving diverse Western populations. While analyzing sex as a biological variable is widely mandated, gender as a sociocultural variable is not, largely because the field lacks quantitative tools for analyzing the influence of gender on health outcomes. We conducted a comprehensive review of English-language measures of gender from 1975 to 2015 to identify variables across three domains: gender norms, gender-related traits, and gender relations. This yielded 11 variables tested with 44 items in three US cross-sectional survey populations: two internet-based (N= 2,051; N= 2,135) and a patient-research registry (N= 489), conducted between May 2017 and January 2018. Exploratory and confirmatory factor analyses distilled 11 constructs to 7 gender-related variables: caregiver strain, work strain, independence, risk-taking, emotional intelligence, social support, and discrimination. Regression analyses, adjusted for age, ethnicity, income, education, sex assigned at birth, and self-reported gender identity, identified associations between these gender-related variables and self-rated general health, physical and mental health, and health-risk behaviors. Our new instrument can be used to develop health interventions based on a fuller understanding of gender associations with health.
The Causal Effects of Blood Iron and Copper on Lipid Metabolism Disease: Evidence from Phenome-wide Mendelian Randomization Study
Authors: Zhou Jingqi , Liu Chang , Francis Michael , Sun Yitang , Ryu Moon-Suhn , Grider Arthur , Ye Kaixiong 
Published: September 2020

AbstractBackgroundBlood levels of iron and copper, even within their normal ranges, have been associated with a wide range of clinical outcomes. Available epidemiological evidence on blood iron and copper association with potential clinical effects, such as lipid metabolism disorder, is inconsistent and scarce. This study aims to examine and disentangle the causal clinical effects of iron and copper.MethodsGenetic instruments for the blood level of iron and copper were curated from existing genome-wide association studies. Candidate clinical outcomes were identified based on a phenome-wide association study (PheWAS) between these genetic instruments and multiple phenotypes in 310,999 unrelated individuals of European ancestry from the UK Biobank. All signals passing stringent correction for multiple testing were followed by Mendelian randomization (MR) analyses, with replication in independent data sources where possible.ResultsGenetically predicted higher blood levels of iron and copper are both associated with lower risks of iron deficiency anemia (OR = 0.75, 95% CI:0.67-0.85,p=1.90×10−06for iron; OR= 0.88, 95% CI: 0.78-0.98,p=0.03 for cooper), lipid metabolism disorders and its two subcategories, hyperlipidemia (OR = 0.90, 95% CI:0.85-0.96,p=6.44×10−04for iron; OR = 0.92, 95% CI:0.87-0.98,p= 5.51×10−03for cooper) and hypercholesterolemia (OR = 0.90, 95% CI:0.84-0.95,p= 5.34×10−04for iron; OR = 0.93, 95% CI:0.89–0.99,p=0.02 for cooper). Consistently, they are also associated with lower blood levels of total cholesterol and low-density lipoprotein cholesterol. Multiple sensitivity tests were applied to assess the pleiotropy and stability of the estimation, and consistent evidence across different approaches was obtained. Additionally, unique clinical effects of each blood mineral were also pinpointed, and sex-stratified MR analysis further revealed the clinical implication of iron and copper exhibits some degree of sex differences.ConclusionsOur comparative PheWAS-MR study of iron and copper comprehensively characterized their shared and unique clinical effects, highlighting their novel causal roles in hyperlipidemia and hypercholesterolemia. Given the modifiable and variable nature of blood mineral status, these findings warrant further investigation.
Multiple measures of depression to enhance validity of Major Depressive Disorder in the UK Biobank
Authors: Glanville Kylie P , Coleman Jonathan R I , Howard David M , Pain Oliver , Hanscombe Ken B , Jermy Bradley , Arathimos Ryan , Hübel Christopher , Breen Gerome , O’Reilly Paul F , Lewis Cathryn M 
Published: September 2020

AbstractBackgroundThe UK Biobank (UKB) contains data with varying degrees of reliability and completeness for assessing depression. A third of participants completed a Mental Health Questionnaire (MHQ) containing the gold-standard Composite International Diagnostic Interview (CIDI) criteria for assessing mental health disorders.AimsTo investigate whether multiple observations of depression from sources other than the MHQ can enhance the validity of Major Depressive Disorder.MethodsIn participants who did not complete the MHQ (n = 325k), we calculated the number of other depression measures endorsed, e.g. from hospital episode statistics and interview data. We compared the strength of the genetic contribution in cases defined this way, to CIDI-defined cases. We compared the variance explained by polygenic risk scores (PRS), area under the curve attributable to PRS, SNP-based heritability, and genetic correlations with summary statistics from the Psychiatric Genomics Consortium Major Depressive Disorder (PGC MDD) GWAS.ResultsThe strength of the genetic contribution increased with the number of measures endorsed. For example, SNP-based heritability increased from 7% with one measure of depression to 21% with four or five. The strength of the genetic contribution to cases defined by at least two measures approximated that for CIDI-defined cases. Most genetic correlations between UKB and PGC MDD exceeded 0.7, but there was variability between pairwise comparisons.ConclusionsMultiple measures of depression can serve as a reliable approximation for case-status where the CIDI measure is not available, with the implication that sample size can be optimised using the full suite of UKB data.
Cancer Diagnosis, Polygenic Risk, and Longevity-Associated Variants
Authors: Goetz Laura H. , Don Janith , Schork Andrew J. , Duggan David , Price Nathan D. , Evans Daniel S. , Cummings Steve , Perls Thomas , Sebastiani Paola , Schork Nicholas J. 
Published: September 2020

ABSTRACTBackgroundPolygenic risk scores (PRS) have been developed to predict individual cancer risk and their potential clinical utility is receiving a great deal of attention. However, the degree to which the predictive utility of individual cancer-specific PRS may be augmented or refined by the incorporation of other cancer PRS, non-cancer disease PRS, or the protective effects of health and longevity-associated variants, is largely unexplored.MethodsWe constructed PRS for different cancers from public domain data as well as genetic scores for longevity (‘Polygenic Longevity Scores’ or ‘PLS’) for individuals in the UK Biobank. We then explored the relationships of these multiple PRS and PLS among those with and without various cancers.ResultsWe found statistically significant associations between some PLS and individual cancers, even after accounting for cancer-specific PRS. None of the PLS in their current form had an effect pronounced enough to motivate clinical cancer risk stratification based on its combined use with cancer PRS. A few variants at loci used in the PLS had known associations with Alzheimer’s disease and other diseases.ConclusionUnderlying heterogeneity behind cancer susceptibility in the population at large is not captured by PRS derived from analytical models that only consider marginal associations of individual variants with cancer diagnoses. Our results have implications for the derivation and calculation of PRS and their use in clinical and biomedical research settings.ImpactExtensions of analyses like ours could result in a more refined understanding of cancer biology and how to construct PRS for cancer.
Reporting quality of trend analyses in leading medicine and oncology journals
Authors: Yuan Xiaoling , Lin Yong , Wang Yating , Zhang Lanjing 
Published: September 2020

AbstractTrend analyses are critical for assessing changes and predicting future of epidemiological parameters. Recent trend-analysis guidelines recommended reporting slopes or beta/coefficient if possible. American Statistical Association and others recommended reporting effect-size. However, reporting of these statistics in trend analyses was largely unclear. We searched the Pubmed for the articles published during Jan. 1, 2008 to Dec. 31, 2018, whose titles included “trend” or “trends” among the following medicine and oncology journals:Ann Intern Med, Ann Oncol, BMJ, J Clin Oncol, J Natl Cancer Inst, JAMA Oncol, JAMA, Lancet, Lancet OncolandN Engl J Med. We examined proportions of the trend analyses in leading medicine and oncology journals, that reported p-value, effect-size or beta/coefficient/Annual percent change (APC), and identified associated factors. Among the 398 identified reports of trend analysis published during 2008-2018, there were 297 qualified reports, including 38 (12.8%) analyses using non-parametric model, 226 (76.1%) analyses using (piece-wise) linear model, 32 (10.8%) analyses using non-linear parametric model and 1 (0.3%) analyses using semi-parametric model (Cox regression). In these analyses, 193 (66.0%) and 216 (72,7%) analyses reportedP-value and effect-size, respectively. Among the 226 trend analyses using linear model, 169 (74.8%) reported p-value, 183 (81.0%) reported effect-size, 94 (41.6%) reported APC and 34 (15.0%) reported Beta/coefficient. Only 13 (5.8%) analyses reported neither p-value/effect size nor beta/coefficient/APC. In multivariable regression models, author affiliation with epidemiology department or statistics department was associated with reporting effect-size, and U.S. senior-authors (versus non-U.S.) more likely reported p-value. No factors were linked to reporting APC. In summary, reporting quality of the included trend analyses was overall good. However, reporting p-value or effect-size did not change with publication years, and reporting APC or Beta/coefficient was uncommon. Additional works and training appear warranted to improve reporting quality of trend analyses.
Estimation and Interactive Visualization of the Time-Varying Reproduction NumberRtand the Time-Delay from Infection to Estimation
Authors: Valka Fabian , Schuler Carla 
Published: September 2020

AbstractRtplays a key role in the development of the COVID-19 pandemic. The methods used for building an interactive website for the visualization of the time-varying reproduction numberRtand a novel way to visualize the time delay from infection to estimation overlayed with theRtestimate are described and analyzed with regards to the influence of parameters chosen and compared to published estimates for Austria. Visualizing the time delays enables the interactive exploration of suspected changes in transmission and their effect on theRtestimate.
Detection of oncometabolites 1-methylnicotinamide, nicotine imine and N-Methylnicotinium in nails of oral cancer patients and prediction of them as modulators of DNMT1
Authors: Dutta Anwesha Deep , Kumar Ajay , Lokhande Kiran , Mitruka Manmohan , Pal Jayanta K. , Sarode Sachin C. , Sharma Nilesh Kumar 
Published: September 2020

ABSTRACTBackgroundThe prominent among various existing views on the role of nicotine and nicotine-metabolized products in Oral squamous cell carcinoma (OSSC) is metabolic adaptation that allows the use of methyl-donor S-adenosylmethionine (SAM) for non-epigenetic purpose including the methylation of nicotinamide and nicotine. In fact, channeling of SAM for generation of 1-methylnicotinamide (1-MNA) and methylated nicotine products is seen as a key event in cancer cells that allows favorable epigenetic states by forcing DNA hypomethylation. A better perception of such events can be appreciated by analyzing samples like nail, which represents a perfect biological material for studying long-term metabolic reflections of the body.MethodsPotential nicotine-metabolized products and 1-MNA in nails of OSCC patients were analyzed by using a novel approach of Vertical tube gel electrophoresis (VTGE)- assisted purification followed by their identification by LC-HRMS. Further, these identified nicotine metabolized products and 1-MNA were evaluated for their molecular interactions with known methyltransferases including cytosolic nicotinamide methyltransferase (NNMT), DNA methyltransferase (DNMT)1 and histone methyltransferases by molecular docking and molecular dynamics simulation (MDS) analyses.ResultsOur data suggests the presence of N-methylnicotinium ion and nicotine imine in the nail samples of OSCC patients. Further, 1-MNA is also detected in the nails as a major enzymatic product of a known detoxifying enzyme NNMT. Molecular docking of all nicotine and nicotine metabolized products with DNMT1revealed a specific binding affinity of nicotine imine only with a -6.2 Kcal/Mol docking energy. Importantly, binding of nicotine imine is within the CXCC regulatory domain of DNMT1 and it displays molecular interactions with the key amino acid residues, namely ARG690, PRO574, VAL658, PRO692 and ALA695. Furthermore, MDS data corroborated well with the specific binding affinity of nicotine imine to DNMT1 obtained by docking analysis.ConclusionIdentification of N-methylnicotinium ion, nicotine imine and 1-MNA in nail samples indicates their potential as predictive and detectable biomarkers for OSCC. Molecular docking and MDS data lead us to propose a role of nicotine imine in modulating the activity of DNMT1. These data further suggest a novel understanding on the role of nicotine metabolized products in modulating DNA methylation that may contribute to tumorigenicity in oral cancer patients.
Comparative analysis reveals the species-specific genetic determinants of ACE2 required for SARS-CoV-2 entry
Authors: Ren Wenlin , Hu Gaowei , Zhao Xiaomin , Wang Yuyan , Shi Hongyang , Lan Jun , Zhu Yunkai , Wu Jianping , Kenney Devin J. , Florian Douam , Tong Yimin , Zhong Jin , Xie Youhua , Wang Xinquan , Yuan Zhenghong , Zhou Dongming , Zhang Rong , Ding Qiang 
Published: September 2020

ABSTRACTCoronavirus interaction with its viral receptor is a primary genetic determinant of host range and tissue tropism. SARS-CoV-2 utilizes ACE2 as the receptor to enter host cell in a species-specific manner. We and others have previously shown that ACE2 orthologs from New World monkey, koala and mouse cannot interact with SARS-CoV-2 to mediate viral entry, and this defect can be restored by humanization of the restrictive residues in New World monkey ACE2. To better understand the genetic determinants behind the ability of ACE2 orthologs to support viral entry, we compared koala and mouse ACE2 sequences with that of human and identified the key residues in koala and mouse ACE2 that restrict viral receptor activity. Humanization of these critical residues rendered both koala and mouse ACE2 capable of binding the spike protein and facilitating viral entry. The single mutation that allowed for mouse ACE2 to serve as a viral receptor provides a potential avenue for the development of SARS-CoV-2 mouse model.
Default Mode and Salience Network Alterations in Suicidal and Non-Suicidal Self-Injurious Thoughts and Behaviors in Adolescents with Depression
Authors: Ho Tiffany C. , Walker Johanna C. , Teresi Giana I. , Kulla Artenisa , Kirshenbaum Jaclyn S. , Gifuni Anthony J. , Singh Manpreet K. , Gotlib Ian H. 
Published: September 2020

AbstractSuicidal ideation (SI) and non-suicidal self-injury (NSSI) are two distinct yet often co-occurring risk factors for suicide in adolescents. Elucidating the neurobiological patterns that specifically characterize SI and NSSI in adolescents is needed to inform the use of these markers in intervention studies and to develop brain-based treatment targets. Here, we clinically assessed 70 adolescents—49 adolescents with depression and 21 healthy controls—to determine SI and NSSI history. Twenty-eight of the depressed adolescents had a history of SI and 29 had a history of NSSI (20 overlapping). All participants underwent a resting-state fMRI scan. We compared groups in network coherence of subdivisions of the central executive network (CEN), default mode network (DMN), and salience network (SN). We also examined group differences in between-network connectivity and explored brain-behavior correlations. Depressed adolescents with SI and with NSSI had lower coherence in the ventral DMN compared to those without SI or NSSI, respectively, and healthy controls (allps<0.043). Depressed adolescents with NSSI had lower coherence in the anterior DMN and in insula-SN (allps<0.030), and higher CEN–DMN connectivity compared to those without NSSI and healthy controls (allps<0.030). Lower network coherence in all DMN subnetworks and insula-SN were associated with higher SI and NSSI (allps<0.001). Thus, SI and NSSI are related to brain networks associated with difficulties in self-referential processing and future planning, while NSSI specifically is related to brain networks associated with disruptions in interoceptive awareness. Intrinsic network patterns may be reliable biomarkers of SI and NSSI in adolescents.
A Multi-center Cross-platform Single-cell RNA Sequencing Reference Dataset
Authors: Chen Xin , Yang Zhaowei , Chen Wanqiu , Zhao Yongmei , Farmer Andrew , Tran Bao , Furtak Vyacheslav , Moos Malcolm , Xiao Wenming , Wang Charles 
Published: September 2020

AbstractSingle-cell RNA sequencing (scRNA-seq) is developing rapidly, and investigators seeking to use this technology are left with a variety of options for both experimental platform and bioinformatics methods. There is an urgent need for scRNA-seq reference datasets for benchmarking of different scRNA-seq platforms and bioinformatics methods. To be broadly applicable, these should be generated from renewable, well characterized reference samples and processed in multiple centers across different platforms. Here we present a benchmarking scRNA-seq dataset that includes 20 scRNA-seq datasets acquired either as a mixtures or as individual samples from two biologically distinct cell lines for which a large amount of multi-platform whole genome sequencing data are also available. These scRNA-seq datasets were generated from multiple popular platforms across four sequencing centers. Our benchmark datasets provide a resource that we believe will have great value for the single-cell community by serving as a reference dataset for evaluating various bioinformatics methods for scRNA-seq analyses, including but not limited to data preprocessing, imputation, normalization, clustering, batch correction, and differential analysis.
The Dynamic Influence of Linker Histone Saturation within the Poly-Nucleosome Array
Authors: Woods Dustin C. , Rodríguez-Ropero Francisco , Wereszczynski Jeff 
Published: September 2020

AbstractLinker histones bind to nucleosomes and modify chromatin structure and dynamics as a means of epigenetic regulation. Biophysical studies have shown that chromatin fibers can adopt a plethora of conformations with varying levels of compaction. Linker histone condensation, and its specific binding disposition, has been associated with directly tuning this ensemble of states. However, the atomistic dynamics and quantification of this mechanism remains poorly understood. Here, we present molecular dynamics simulations of octa-nucleosome arrays, based on a cryo-EM structure of the 30-nm chromatin fiber, with and without the globular domains of the H1 linker histone to determine how they influence fiber structures and dynamics. Results show that when bound, linker histones inhibit DNA flexibility and stabilize repeating tetra-nucleosomal units, giving rise to increased chromatin compaction. Furthermore, upon the removal of H1, there is a significant destabilization of this compact structure as the fiber adopts less strained and untwisted states. Interestingly, linker DNA sampling in the octa-nucleosome is exaggerated compared to its mono-nucleosome counterparts, suggesting that chromatin architecture plays a significant role in DNA strain even in the absence of linker histones. Moreover, H1-bound states are shown to have increased stiffness within tetra-nucleosomes, but not between them. This increased stiffness leads to stronger long-range correlations within the fiber, which may result in the propagation of epigenetic signals over longer spatial ranges. These simulations highlight the effects of linker histone binding on the internal dynamics and global structure of poly-nucleosome arrays, while providing physical insight into a mechanism of chromatin compaction.SignificanceLinker histones dynamically bind to DNA in chromatin fibers and serve as epigentic regulators. However, the extent to which they influence the gamut of chromatin architecture is still not well understood. Using molecular dynamics simulations, we studied compact octa-nucleosome arrays with and without the H1 linker histone to better understand the mechanisms dictating the structure of the chromatin fiber. Inclusion of H1 results in stabilization of the compact chromatin structure, while its removal results in a major conformational change towards an untwisted ladder-like state. The increased rigidity and correlations within the H1-bound array suggests that H1-saturated chromatin fibers are better suited to transferring long-range epigentic information.