bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hypertension and Atrial Fibrillation: An Intimate Association of Epidemiology, Pathophysiology, and Outcomes
Authors: Dzeshka Mikhail S. , Shahid Farhan , Shantsila Alena , Lip Gregory Y.H. 
Published: January 2017

AbstractAtrial fibrillation (AF) is the most prevalent sustained arrhythmia found in clinical practice. AF rarely exists as a single entity but rather as part of a diverse clinical spectrum of cardiovascular diseases, related to structural and electrical remodeling within the left atrium, leading to AF onset, perpetuation, and progression. Due to the high overall prevalence within the AF population arterial hypertension plays a significant role in the pathogenesis of AF and its complications. Fibroblast proliferation, apoptosis of cardiomyocytes, gap junction remodeling, accumulation of collagen both in atrial and ventricular myocardium all accompany ageing-related structural remodeling with impact on electrical activity. The presence of hypertension also stimulates oxidative stress, systemic inflammation, rennin–angiotensin–aldosterone and sympathetic activation, which further drives the remodeling process in AF. Importantly, both hypertension and AF independently increase the risk of cardiovascular and cerebrovascular events, e.g., stroke and myocardial infarction. Given that both AF and hypertension often present with limited on patient wellbeing, treatment may be delayed resulting in development of complications as the first clinical manifestation of the disease. Antithrombotic prevention in AF combined with strict blood pressure control is of primary importance, since stroke risk and bleeding risk are both greater with underlying hypertension.
Cigarette Smoking and Subtypes of Uncontrolled Blood Pressure Among Diagnosed Hypertensive Patients: Paradoxical Associations and Implications
Authors: Liu Xuefeng , Byrd James Brian 
Published: January 2017

Abstract

BACKGROUND
Isolated uncontrolled systolic blood pressure (SBP), uncontrolled systolic-diastolic blood pressure (BP), and isolated uncontrolled diastolic blood pressure (DBP) are subtypes of uncontrolled BP. The associations of smoking with uncontrolled BP subtypes among diagnosed hypertensive patients are unknown.

METHODS
Seven thousand eight hundred twenty-nine subjects aged 18 years or over with diagnosed hypertension were selected from the National Health and Nutrition Examination Survey with stratified multistage clustered sampling design. Weighted logistic regressions were conducted to estimate odds ratios (ORs) with 95% confidence intervals (CIs) of uncontrolled BP subtypes related to smoking status. Weighted multiple regression models were used to examine the association of smoking with levels of SBP, DBP, and pulse pressure.

RESULTS
The average age of the study sample was 60.3 ± 0.3 years. 54.2% ± 0.7% were females. Compared to nonsmokers, current smokers were 22% less likely to have uncontrolled BP (OR: 0.78, 95% CI: 0.64–0.94, P = 0.01), and 21% less likely to have isolated uncontrolled SBP (OR: 0.79, 95% CI: 0.64–0.97, P = 0.02). Average DBP was 1.5 mm Hg lower (95% CI: −2.8 to −0.2 mm Hg, P = 0.02) in current smokers than in nonsmokers. Average DBP was 0.9 mm Hg lower (95% CI: −1.7 to −0.03 mm Hg, P = 0.04) in former smokers than in nonsmokers. Current smoking and former smoking were not associated with risk of uncontrolled systolic–diastolic BP and isolated uncontrolled DBP.

CONCLUSIONS
Paradoxical associations between current smoking and SBP, uncontrolled BP and isolated uncontrolled SBP were shown among hypertensive patients. The explanation for these associations is currently unknown. No cause–effect relationships should be assumed.
Blood Pressure Control During Chronic Kidney Disease Progression
Authors: Lee Seulbi , Oh Hyung Jung , Lee Eun-Kyung , Lee Oesook , Ha Eunhee , Kim Seung-Jung , Kang Duk-Hee , Choi Kyu Bok , Ryu Dong-Ryeol 
Published: January 2017

Abstract

BACKGROUND
Hypertension is a major cause of end-stage renal disease, and blood pressure (BP) control is crucial in patients with chronic kidney disease (CKD). However, it is generally inadequately controlled in CKD patients. We investigated the prevalence of CKD patients with inadequate BP control and its related factors, based on the CKD stage.

METHODS
We analyzed the health examination sample cohort database, which consisted of the randomly selected participants among all the citizens who received the health examination provided by National Health Insurance Service of Korea in 2012 and 2013.

RESULTS
There were 27,350 CKD patients (7.9%) out of a total of 345,044 participants. As CKD stage progressed, there were more patients with poorly controlled hypertension compared to those with well-controlled hypertension. In addition, systolic BP increased with CKD stage progression, while diastolic BP was not significantly different. Age, female, body mass index, increased pulse pressure, CKD stage, and levels of fasting glucose, total cholesterol, hemoglobin, and proteinuria were significant factors associated with poor control of BP in hypertensive CKD patients.

CONCLUSION
The proportion of CKD patients with poorly controlled hypertension significantly increased as CKD progressed, mainly associated with the increase in pulse pressure. However, future investigation for causal relationship between poorly controlled hypertension and its related factors is needed.
The Effects of Trivialization of Workplace Violence on Its Victims: Profession and Sex Differences in a Cross-Sectional Study among Healthcare and Law Enforcement Workers
Authors: Geoffrion Steve , Goncalves Jane , Boyer Richard , Marchand André , Guay Stéphane 
Published: January 2017

Abstract

Background:
Workers from the law enforcement and healthcare sectors tend to normalize or mute their victimization from workplace violence (WPV).

Objectives:
This study aims to assess the impact of the trivialization of WPV on psychological consequences for workers who have been affected by a WPV incident. The second aim is to assess the moderating effect of sex on the trivialization of WPV. The third and overarching aim is to assess the moderating effect of professional identity on the relations between individual and organizational factors and psychological consequences following a WPV incident.

Methods:
The findings are based on a convenience sample of 377 (204 female and 173 male) workers from the law enforcement and healthcare sectors. Individual factors (sex, age, professional identity, prior victimization, witnessing WPV, injuries, and trivialization of violence) and perceived support factors (colleagues’ support and employer’s support) were used as predictor variables of psychological consequences in hierarchical linear regression models. Sex was used as a moderator of trivialization while professional identity was used as a moderator of all predictors.

Findings:
When individual and social support factors were controlled for, normalizing violence was negatively associated with psychological consequences while perceiving a taboo associated with complaining about WPV was positively associated for all participants. When these relations were moderated by the sex of the participants and then by their professional identity, normalization was found to decrease psychological consequences only for male healthcare workers.

Implications:
To help employees cope with WPV, organizations should promote strategies adapted to profession and sex differences. For male healthcare workers, normalization as a cognitive coping strategy should be formally recognized. For both professions and sexes, organizational strategies that counter the perceived taboo of complaining about violence should be reinforced.
Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data
Authors: Basu Sumanta , Duren William , Evans Charles R , Burant Charles F , Michailidis George , Karnovsky Alla 
Published: January 2017

Abstract

Motivation
Recent technological advances in mass spectrometry, development of richer mass spectral libraries and data processing tools have enabled large scale metabolic profiling. Biological interpretation of metabolomics studies heavily relies on knowledge-based tools that contain information about metabolic pathways. Incomplete coverage of different areas of metabolism and lack of information about non-canonical connections between metabolites limits the scope of applications of such tools. Furthermore, the presence of a large number of unknown features, which cannot be readily identified, but nonetheless can represent bona fide compounds, also considerably complicates biological interpretation of the data.

Results
Leveraging recent developments in the statistical analysis of high-dimensional data, we developed a new Debiased Sparse Partial Correlation algorithm (DSPC) for estimating partial correlation networks and implemented it as a Java-based CorrelationCalculator program. We also introduce a new version of our previously developed tool Metscape that enables building and visualization of correlation networks. We demonstrate the utility of these tools by constructing biologically relevant networks and in aiding identification of unknown compounds.

Availability and Implementation
http://metscape.med.umich.edu

Supplementary information
Supplementary data are available at Bioinformatics online.
Genotyping inversions and tandem duplications
Authors: Ebler Jana , Schönhuth Alexander , Marschall Tobias 
Published: January 2017

Abstract

Motivation
Next Generation Sequencing (NGS) has enabled studying structural genomic variants (SVs) such as duplications and inversions in large cohorts. SVs have been shown to play important roles in multiple diseases, including cancer. As costs for NGS continue to decline and variant databases become ever more complete, the relevance of genotyping also SVs from NGS data increases steadily, which is in stark contrast to the lack of tools to do so.

Results
We introduce a novel statistical approach, called DIGTYPER (Duplication and Inversion GenoTYPER), which computes genotype likelihoods for a given inversion or duplication and reports the maximum likelihood genotype. In contrast to purely coverage-based approaches, DIGTYPER uses breakpoint-spanning read pairs as well as split alignments for genotyping, enabling typing also of small events. We tested our approach on simulated and on real data and compared the genotype predictions to those made by DELLY, which discovers SVs and computes genotypes, and SVTyper, a genotyping program used to genotype variants detected by LUMPY. DIGTYPER compares favorable especially for duplications (of all lengths) and for shorter inversions (up to 300 bp). In contrast to DELLY, our approach can genotype SVs from data bases without having to rediscover them.

Availability and Implementation
https://bitbucket.org/jana_ebler/digtyper.git.

Supplementary information
Supplementary data are available at Bioinformatics online.
PALADIN: protein alignment for functional profiling whole metagenome shotgun data
Authors: Westbrook Anthony , Ramsdell Jordan , Schuelke Taruna , Normington Louisa , Bergeron R Daniel , Thomas W Kelley , MacManes Matthew D 
Published: January 2017

Abstract

Motivation
Whole metagenome shotgun sequencing is a powerful approach for assaying the functional potential of microbial communities. We currently lack tools that efficiently and accurately align DNA reads against protein references, the technique necessary for constructing a functional profile. Here, we present PALADIN—a novel modification of the Burrows-Wheeler Aligner that provides accurate alignment, robust reporting capabilities and orders-of-magnitude improved efficiency by directly mapping in protein space.

Results
We compared the accuracy and efficiency of PALADIN against existing tools that employ nucleotide or protein alignment algorithms. Using simulated reads, PALADIN consistently outperformed the popular DNA read mappers BWA and NovoAlign in detected proteins, percentage of reads mapped and ontological similarity. We also compared PALADIN against four existing protein alignment tools: BLASTX, RAPSearch2, DIAMOND and Lambda, using empirically obtained reads. PALADIN yielded results seven times faster than the best performing alternative, DIAMOND and nearly 8000 times faster than BLASTX. PALADIN's accuracy was comparable to all tested solutions.

Availability and Implementation
PALADIN was implemented in C, and its source code and documentation are available at https://github.com/twestbrookunh/paladin

Supplementary information
Supplementary data are available at Bioinformatics online.
Supporting precision medicine by data mining across multi-disciplines: an integrative approach for generating comprehensive linkages between single nucleotide variants (SNVs) and drug-binding sites
Authors: Roy Choudhury Amrita , Cheng Tiejun , Phan Lon , Bryant Stephen H , Wang Yanli 
Published: January 2017

Abstract

Motivation
Genetic variants in drug targets and metabolizing enzymes often have important functional implications, including altering the efficacy and toxicity of drugs. Identifying single nucleotide variants (SNVs) that contribute to differences in drug response and understanding their underlying mechanisms are fundamental to successful implementation of the precision medicine model. This work reports an effort to collect, classify and analyze SNVs that may affect the optimal response to currently approved drugs.

Results
An integrated approach was taken involving data mining across multiple information resources including databases containing drugs, drug targets, chemical structures, protein–ligand structure complexes, genetic and clinical variations as well as protein sequence alignment tools. We obtained 2640 SNVs of interest, most of which occur rarely in populations (minor allele frequency &lt; 0.01). Clinical significance of only 9.56% of the SNVs is known in ClinVar, although 79.02% are predicted as deleterious. The examples here demonstrate that even if the mapped SNVs predicted as deleterious may not result in significant structural modifications, they can plausibly modify the protein–drug interactions, affecting selectivity and drug-binding affinity. Our analysis identifies potentially deleterious SNVs present on drug-binding residues that are relevant for further studies in the context of precision medicine.

Availability and Implementation
Data are available from Supplementary information file.

Supplementary information
Supplementary Tables S1–S5 are available at Bioinformatics online.
Riborex: fast and flexible identification of differential translation from Ribo-seq data
Authors: Li Wenzheng , Wang Weili , Uren Philip J , Penalva Luiz O F , Smith Andrew D 
Published: January 2017

Abstract

Motivation
Global analysis of translation regulation has recently been enabled by the development of Ribosome Profiling, or Ribo-seq, technology. This approach provides maps of ribosome activity for each expressed gene in a given biological sample. Measurements of translation efficiency are generated when Ribo-seq data is analyzed in combination with matched RNA-seq gene expression profiles. Existing computational methods for identifying genes with differential translation across samples are based on sound principles, but require users to choose between accuracy and speed.

Results
We present Riborex, a computational tool for mapping genome-wide differences in translation efficiency. Riborex shares a similar mathematical structure with existing methods, but has a simplified implementation. Riborex directly leverages established RNA-seq analysis frameworks for all parameter estimation, providing users with a choice among robust engines for these computations. The result is a method that is dramatically faster than available methods without sacrificing accuracy.

Availability and Implementation
https://github.com/smithlabcode/riborex

Supplementary information
Supplementary data are available at Bioinformatics online.
Accurate prediction of human essential genes using only nucleotide composition and association information
Authors: Guo Feng-Biao , Dong Chuan , Hua Hong-Li , Liu Shuo , Luo Hao , Zhang Hong-Wan , Jin Yan-Ting , Zhang Kai-Yue 
Published: January 2017

Abstract

Motivation
Previously constructed classifiers in predicting eukaryotic essential genes integrated a variety of features including experimental ones. If we can obtain satisfactory prediction using only nucleotide (sequence) information, it would be more promising. Three groups recently identified essential genes in human cancer cell lines using wet experiments and it provided wonderful opportunity to accomplish our idea. Here we improved the Z curve method into the λ-interval form to denote nucleotide composition and association information and used it to construct the SVM classifying model.

Results
Our model accurately predicted human gene essentiality with an AUC higher than 0.88 both for 5-fold cross-validation and jackknife tests. These results demonstrated that the essentiality of human genes could be reliably reflected by only sequence information. We re-predicted the negative dataset by our Pheg server and 118 genes were additionally predicted as essential. Among them, 20 were found to be homologues in mouse essential genes, indicating that some of the 118 genes were indeed essential, however previous experiments overlooked them. As the first available server, Pheg could predict essentiality for anonymous gene sequences of human. It is also hoped the λ-interval Z curve method could be effectively extended to classification issues of other DNA elements.

Availability and Implementation
http://cefg.uestc.edu.cn/Pheg

Supplementary information
Supplementary data are available at Bioinformatics online.
PatternMarkers & GWCoGAPS for novel data-driven biomarkers via whole transcriptome NMF
Authors: Stein-O’Brien Genevieve L , Carey Jacob L , Lee Wai Shing , Considine Michael , Favorov Alexander V , Flam Emily , Guo Theresa , Li Sijia , Marchionni Luigi , Sherman Thomas , Sivy Shawn , Gaykalova Daria A , McKay Ronald D , Ochs Michael F , Colantuoni Carlo , Fertig Elana J 
Published: January 2017

Abstract

Summary
Non-negative Matrix Factorization (NMF) algorithms associate gene expression with biological processes (e.g. time-course dynamics or disease subtypes). Compared with univariate associations, the relative weights of NMF solutions can obscure biomarkers. Therefore, we developed a novel patternMarkers statistic to extract genes for biological validation and enhanced visualization of NMF results. Finding novel and unbiased gene markers with patternMarkers requires whole-genome data. Therefore, we also developed Genome-Wide CoGAPS Analysis in Parallel Sets (GWCoGAPS), the first robust whole genome Bayesian NMF using the sparse, MCMC algorithm, CoGAPS. Additionally, a manual version of the GWCoGAPS algorithm contains analytic and visualization tools including patternMatcher, a Shiny web application. The decomposition in the manual pipeline can be replaced with any NMF algorithm, for further generalization of the software. Using these tools, we find granular brain-region and cell-type specific signatures with corresponding biomarkers in GTEx data, illustrating GWCoGAPS and patternMarkers ascertainment of data-driven biomarkers from whole-genome data.

Availability and Implementation
PatternMarkers & GWCoGAPS are in the CoGAPS Bioconductor package (3.5) under the GPL license.

Supplementary information
Supplementary data are available at Bioinformatics online.
qPCR-based characterization of DNA fragmentation efficiency of Tn5 transposomes
Authors: Rykalina Vera , Shadrin Alexey , Lehrach Hans , Borodina Tatiana 
Published: January 2017

Abstract
Here, we describe an electrophoresis free assay for characterizing Tn5 transposomes fragmentation efficiency in a tagmentation reaction, in which double-stranded DNA is fragmented and tagged with adapter sequences. The assay uses plasmid DNA as a reference tagmentation substrate. Fragmentation efficiency is analyzed by comparative qPCR which measures the difference (ΔCt) in amplification of a specific plasmid region before and after tagmentation: more efficient fragmentation is characterized by a larger number of cleavage events within the amplified region, a delayed increase in the amplification curve and as a result, a larger ΔCt. Tagmentation reactions characterized with the same ΔCt exhibit the same fragment size distribution on an agarose gel. The ΔCt values measured can be used to quantitatively determine the relative performance of Tn5 transposome assemblies in optimization experiments and to standardize between batch variations in transposomes for use in next-generation sequencing library preparation. Moreover, the use of a reference tagmentation template added during next-generation sequencing library preparation enabled monitoring of the input DNA fragmentation. The presented qPCR-based assay is quick, contamination-safe, high-throughput and cost-efficient.
Osteopontin RNA aptamer can prevent and reverse pressure overload-induced heart failure
Authors: Li Jihe , Yousefi Keyvan , Ding Wen , Singh Jayanti , Shehadeh Lina A. 
Published: January 2017

Aims
Cardiac myocyte hypertrophy, the main compensatory response to chronic stress in the heart often progresses to a state of decompensation that can lead to heart failure. Osteopontin (OPN) is an effector for extracellular signalling that induces myocyte growth and fibrosis. Although increased OPN activity has been observed in stressed myocytes and fibroblasts, the detailed and long term effects of blocking OPN signalling on the heart remain poorly defined. Targeting cardiac OPN protein by an RNA aptamer may be beneficial for tuning down OPN pathologic signalling. We aimed to demonstrate the therapeutic effects of an OPN RNA aptamer on cardiac dysfunction.

Methods and results
In vivo, we show that in a mouse model of pressure overload, treating at the time of surgeries with an OPN aptamer prevented cardiomyocyte hypertrophy and cardiac fibrosis, blocked OPN downstream signalling (PI3K and Akt phosphorylation), reduced expression of extracellular matrix (Lum, Col3a1, Fn1) and hypertrophy (Nppa, Nppb) genes, and prevented cardiac dysfunction. Treating at two months post-surgeries with the OPN aptamer reversed cardiac dysfunction and fibrosis and myocyte hypertrophy. While genetic homozygous deletion of OPN reduced myocardial wall thickness, surprisingly cardiac function and myocardial fibrosis, specifically collagen deposition and myofibroblast infiltration, were worse compared with wild type mice at three months of pressure overload.

Conclusion
Taken together, these data demonstrate that tuning down cardiac OPN signalling by an OPN RNA aptamer is a novel and effective approach for preventing cardiac hypertrophy and fibrosis, improving cardiac function, and reversing pressure overload-induced heart failure.