bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cardioprotection against ischaemia/reperfusion by vitamins C and E plus n−3 fatty acids: molecular mechanisms and potential clinical applications
Authors: Rodrigo Ramón , Prieto Juan C. , Castillo Rodrigo 
Published: September 2012

The role of oxidative stress in ischaemic heart disease has been thoroughly investigated in humans. Increased levels of ROS (reactive oxygen species) and RNS (reactive nitrogen species) have been demonstrated during ischaemia and post-ischaemic reperfusion in humans. Depending on their concentrations, these reactive species can act either as benevolent molecules that promote cell survival (at low-to-moderate concentrations) or can induce irreversible cellular damage and death (at high concentrations). Although high ROS levels can induce NF-κB (nuclear factor κB) activation, inflammation, apoptosis or necrosis, low-to-moderate levels can enhance the antioxidant response, via Nrf2 (nuclear factor-erythroid 2-related factor 2) activation. However, a clear definition of these concentration thresholds remains to be established. Although a number of experimental studies have demonstrated that oxidative stress plays a major role in heart ischaemia/reperfusion pathophysiology, controlled clinical trials have failed to prove the efficacy of antioxidants in acute or long-term treatments of ischaemic heart disease. Oral doses of vitamin C are not sufficient to promote ROS scavenging and only down-regulate their production via NADPH oxidase, a biological effect shared by vitamin E to abrogate oxidative stress. However, infusion of vitamin C at doses high enough to achieve plasma levels of 10 mmol/l should prevent superoxide production and the pathophysiological cascade of deleterious heart effects. In turn, n−3 PUFA (polyunsaturated fatty acid) exposure leads to enhanced activity of antioxidant enzymes. In the present review, we present evidence to support the molecular basis for a novel pharmacological strategy using these antioxidant vitamins plus n−3 PUFAs for cardioprotection in clinical settings, such as post-operative atrial fibrillation, percutaneous coronary intervention following acute myocardial infarction and other events that are associated with ischaemia/reperfusion.
An Outbreak of Scabies in Multiple Linked Healthcare Settings in the Netherlands
Authors: Ladbury Georgia , Morroy Gabriella , Hoeven-Dekkers Sandra van , Botermans Corine , Veelenturf Cees , Bastiaens Maarten , Abeelen Cees van , Wijkmans Clementine 
Published: September 2012

We report a large scabies outbreak occurring in Tilburg, Netherlands, which affected several different healthcare settings that provide care to the elderly and the mentally disabled. The outbreak demonstrated how the complex system of care provision to vulnerable groups facilitated extensive scabies transmission among multiple linked healthcare settings and the community.Infect Control Hosp Epidemiol 2012;33(10): 1047-1050
Outbreak of Carbapenem-Resistant Enterobacteriaceae at a Long-Term Acute Care Hospital: Sustained Reductions in Transmission through Active Surveillance and Targeted Interventions
Authors: Chitnis Amit S. , Caruthers Pam S. , Rao Agam K. , Lamb JoAnne , Lurvey Robert , De Rochars Valery Beau , Kitchel Brandon , Cancio Margarita , Török Thomas J. , Guh Alice Y. , Gould Carolyn V. , Wise Matthew E. 
Published: September 2012

Objective.To describe a Klebsiella pneumoniae carbapenemase (KPC)–producing carbapenem-resistant Enterobacteriaceae (CRE) outbreak and interventions to prevent transmission.Design, Setting, and Patients.Epidemiologic investigation of a CRE outbreak among patients at a long-term acute care hospital (LTACH).Methods.Microbiology records at LTACH A from March 2009 through February 2011 were reviewed to identify CRE transmission cases and cases admitted with CRE. CRE bacteremia episodes were identified during March 2009–July 2011. Biweekly CRE prevalence surveys were conducted during July 2010–July 2011, and interventions to prevent transmission were implemented, including education and auditin? of staff and isolation and cohorting of CRE patients with dedicated nursing staff and shared medical equipment. Trends were evaluated using weighted linear or Poisson regression. CRE transmission cases were included in a case-control study to evaluate risk factors for acquisition. A real-time polymerase chain reaction assay was used to detect the blaKPC gene, and pulsed-field gel electrophoresis was performed to assess the genetic relatedness of isolates.Results.Ninety-nine CRE transmission cases, 16 admission cases (from 7 acute care hospitals), and 29 CRE bacteremia episodes were identified. Significant reductions were observed in CRE prevalence (49% vs 8%), percentage of patients screened with newly detected CRE (44% vs 0%), and CRE bacteremia episodes (2.5 vs 0.0 per 1,000 patient-days). Cases were more likely to have received β-lactams, have diabetes, and require mechanical ventilation. All tested isolates were KPC-producing K. pneumoniae, and nearly all isolates were genetically related.Conclusion.CRE transmission can be reduced in LTACHs through surveillance testing and targeted interventions. Sustainable reductions within and across healthcare facilities may require a regional public health approach.Infect Control Hosp Epidemiol 2012;33(10):984-992
Surveillance Definitions of Infections in Long-Term Care Facilities: Revisiting the McGeer Criteria
Authors: Stone Nimalie D. , Ashraf Muhammad S. , Calder Jennifer , Crnich Christopher J. , Crossley Kent , Drinka Paul J. , Gould Carolyn V. , Juthani-Mehta Manisha , Lautenbach Ebbing , Loeb Mark , MacCannell Taranisia , Malani Preeti N. , Mody Lona , Mylotte Joseph M. , Nicolle Lindsay E. , Roghmann Mary-Claire , Schweon Steven J. , Simor Andrew E. , Smith Philip W. , Stevenson Kurt B. , Bradley Suzanne F. ,   Society for Healthcare Epidemiology Long-Term Care Special Interest Group
Published: September 2012

Infection surveillance definitions for long-term care facilities (ie, the McGeer Criteria) have not been updated since 1991. An expert consensus panel modified these definitions on the basis of a structured review of the literature. Significant changes were made to the criteria defining urinary tract and respiratory tract infections. New definitions were added for norovirus gastroenteritis and Clostridum difficile infections.Infect Control Hosp Epidemiol 2012;33(10):965-977
Identifying functional modules in interaction networks through overlapping Markov clustering
Authors: Shih Yu-Keng , Parthasarathy Srinivasan 
Published: September 2012

Abstract
Motivation: In recent years, Markov clustering (MCL) has emerged as an effective algorithm for clustering biological networks—for instance clustering protein–protein interaction (PPI) networks to identify functional modules. However, a limitation of MCL and its variants (e.g. regularized MCL) is that it only supports hard clustering often leading to an impedance mismatch given that there is often a significant overlap of proteins across functional modules.
Results: In this article, we seek to redress this limitation. We propose a soft variation of Regularized MCL (R-MCL) based on the idea of iteratively (re-)executing R-MCL while ensuring that multiple executions do not always converge to the same clustering result thus allowing for highly overlapped clusters. The resulting algorithm, denoted soft regularized Markov clustering, is shown to outperform a range of extant state-of-the-art approaches in terms of accuracy of identifying functional modules on three real PPI networks.
Availability: All data and codes are freely available upon request.
Contact: srini@cse.ohio-state.edu
Supplementary Information: Supplementary data are available at Bioinformatics online.
Techniques to cope with missing data in host–pathogen protein interaction prediction
Authors: Kshirsagar Meghana , Carbonell Jaime , Klein-Seetharaman Judith 
Published: September 2012

Abstract
Motivation: Approaches that use supervised machine learning techniques for protein–protein interaction (PPI) prediction typically use features obtained by integrating several sources of data. Often certain attributes of the data are not available, resulting in missing values. In particular, our host–pathogen PPI datasets have a large fraction, in the range of 58–85% of missing values, which makes it challenging to apply machine learning algorithms.
Results: We show that specialized techniques for missing value imputation can improve the performance of the models significantly. We use cross species information in combination with machine learning techniques like Group lasso with ℓ1/ℓ2 regularization. We demonstrate the benefits of our approach on two PPI prediction problems. In our first example of Salmonella–human PPI prediction, we are able to obtain high prediction accuracies with 77.6% precision and 84% recall. Comparison with various other techniques shows an improvement of 9 in F1 score over the next best technique. We also apply our method to Yersinia–human PPI prediction successfully, demonstrating the generality of our approach.
Availability: Predicted interactions, datasets, features are available at: http://www.cs.cmu.edu/~mkshirsa/eccb2012_paper46.html.
Contact: judithks@cs.cmu.edu
Supplementary Information: Supplementary data are available at Bioinformatics online.
Indel-tolerant read mapping with trinucleotide frequencies using cache-oblivious kd-trees
Authors: Mahmud Md Pavel , Wiedenhoeft John , Schliep Alexander 
Published: September 2012

Abstract
Motivation: Mapping billions of reads from next generation sequencing experiments to reference genomes is a crucial task, which can require hundreds of hours of running time on a single CPU even for the fastest known implementations. Traditional approaches have difficulties dealing with matches of large edit distance, particularly in the presence of frequent or large insertions and deletions (indels). This is a serious obstacle both in determining the spectrum and abundance of genetic variations and in personal genomics.
Results: For the first time, we adopt the approximate string matching paradigm of geometric embedding to read mapping, thus rephrasing it to nearest neighbor queries in a q-gram frequency vector space. Using the L1 distance between frequency vectors has the benefit of providing lower bounds for an edit distance with affine gap costs. Using a cache-oblivious kd-tree, we realize running times, which match the state-of-the-art. Additionally, running time and memory requirements are about constant for read lengths between 100 and 1000 bp. We provide a first proof-of-concept that geometric embedding is a promising paradigm for read mapping and that L1 distance might serve to detect structural variations. TreQ, our initial implementation of that concept, performs more accurate than many popular read mappers over a wide range of structural variants.
Availability and implementation: TreQ will be released under the GNU Public License (GPL), and precomputed genome indices will be provided for download at http://treq.sf.net.
Contact: pavelm@cs.rutgers.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Stoichiometric capacitance reveals the theoretical capabilities of metabolic networks
Authors: Larhlimi Abdelhalim , Basler Georg , Grimbs Sergio , Selbig Joachim , Nikoloski Zoran 
Published: September 2012

Abstract
Motivation: Metabolic engineering aims at modulating the capabilities of metabolic networks by changing the activity of biochemical reactions. The existing constraint-based approaches for metabolic engineering have proven useful, but are limited only to reactions catalogued in various pathway databases.
Results: We consider the alternative of designing synthetic strategies which can be used not only to characterize the maximum theoretically possible product yield but also to engineer networks with optimal conversion capability by using a suitable biochemically feasible reaction called ‘stoichiometric capacitance’. In addition, we provide a theoretical solution for decomposing a given stoichiometric capacitance over a set of known enzymatic reactions. We determine the stoichiometric capacitance for genome-scale metabolic networks of 10 organisms from different kingdoms of life and examine its implications for the alterations in flux variability patterns. Our empirical findings suggest that the theoretical capacity of metabolic networks comes at a cost of dramatic system's changes.
Contact: larhlimi@mpimp-golm.mpg.de, or nikoloski@mpimp-golm.mpg.de
Supplementary Information: Supplementary tables are available at Bioinformatics online.
Hybrid spatial Gillespie and particle tracking simulation
Authors: Klann Michael , Ganguly Arnab , Koeppl Heinz 
Published: September 2012

Abstract
Motivation: Cellular signal transduction involves spatial–temporal dynamics and often stochastic effects due to the low particle abundance of some molecular species. Others can, however, be of high abundances. Such a system can be simulated either with the spatial Gillespie/Stochastic Simulation Algorithm (SSA) or Brownian/Smoluchowski dynamics if space and stochasticity are important. To combine the accuracy of particle-based methods with the superior performance of the SSA, we suggest a hybrid simulation.
Results: The proposed simulation allows an interactive or automated switching for regions or species of interest in the cell. Especially we see an application if for instance receptor clustering at the membrane is modeled in detail and the transport through the cytoplasm is included as well. The results show the increase in performance of the overall simulation, and the limits of the approach if crowding is included. Future work will include the development of a GUI to improve control of the simulation.
Availability of Implementation: www.bison.ethz.ch/research/spatial_simulations.
Contact: mklann@ee.ethz.ch or koeppl@ethz.ch
Supplementary/Information: Supplementary data are available at Bioinformatics online.
Decoding properties of tRNA leave a detectable signal in codon usage bias
Authors: Roth Alexander C. 
Published: September 2012

Abstract
Motivation: The standard genetic code translates 61 codons into 20 amino acids using fewer than 61 transfer RNAs (tRNAs). This is possible because of the tRNA's ability to ‘wobble’ at the third base to decode more than one codon. Although the anticodon–codon mapping of tRNA to mRNA is a prerequisite for certain codon usage indices and can contribute to the understanding of the evolution of alternative genetic codes, it is usually not determined experimentally because such assays are prohibitively expensive and elaborate. Instead, the codon reading is approximated from theoretical inferences of nucleotide binding, the wobble rules. Unfortunately, these rules fail to capture all of the nuances of codon reading. This study addresses the codon reading properties of tRNAs and their evolutionary impact on codon usage bias.
Results: Using three different computational methods, the signal of tRNA decoding in codon usage bias is identified. The predictions by the methods generally agree with each other and compare well with experimental evidence of codon reading. This analysis suggests a revised codon reading for cytosolic tRNA in the yeast genome (Saccharomyces cerevisiae) that is more accurate than the common assignment by wobble rules. The results confirm the earlier observation that the wobble rules are not sufficient for a complete description of codon reading, because they depend on genome-specific factors. The computational methods presented here are applicable to any fully sequenced genome.
Availability: By request from the author.
Contact: alexander.roth@isb-sib.ch
Event extraction across multiple levels of biological organization
Authors: Pyysalo Sampo , Ohta Tomoko , Miwa Makoto , Cho Han-Cheol , Tsujii Jun'ichi , Ananiadou Sophia 
Published: September 2012

Abstract
Motivation: Event extraction using expressive structured representations has been a significant focus of recent efforts in biomedical information extraction. However, event extraction resources and methods have so far focused almost exclusively on molecular-level entities and processes, limiting their applicability.
Results: We extend the event extraction approach to biomedical information extraction to encompass all levels of biological organization from the molecular to the whole organism. We present the ontological foundations, target types and guidelines for entity and event annotation and introduce the new multi-level event extraction (MLEE) corpus, manually annotated using a structured representation for event extraction. We further adapt and evaluate named entity and event extraction methods for the new task, demonstrating that both can be achieved with performance broadly comparable with that for established molecular entity and event extraction tasks.
Availability: The resources and methods introduced in this study are available from http://nactem.ac.uk/MLEE/.
Contact: pyysalos@cs.man.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs
Authors: Wang Hua , Nie Feiping , Huang Heng , Yan Jingwen , Kim Sungeun , Nho Kwangsik , Risacher Shannon L. , Saykin Andrew J. , Shen Li ,   for the Alzheimer's Disease Neuroimaging Initiative
Published: September 2012

AbstractMotivation: Imaging genetic studies typically focus on identifying single-nucleotide polymorphism (SNP) markers associated with imaging phenotypes. Few studies perform regression of SNP values on phenotypic measures for examining how the SNP values change when phenotypic measures are varied. This alternative approach may have a potential to help us discover important imaging genetic associations from a different perspective. In addition, the imaging markers are often measured over time, and this longitudinal profile may provide increased power for differentiating genotype groups. How to identify the longitudinal phenotypic markers associated to disease sensitive SNPs is an important and challenging research topic.Results: Taking into account the temporal structure of the longitudinal imaging data and the interrelatedness among the SNPs, we propose a novel ‘task-correlated longitudinal sparse regression’ model to study the association between the phenotypic imaging markers and the genotypes encoded by SNPs. In our new association model, we extend the widely used ℓ2,1-norm for matrices to tensors to jointly select imaging markers that have common effects across all the regression tasks and time points, and meanwhile impose the trace-norm regularization onto the unfolded coefficient tensor to achieve low rank such that the interrelationship among SNPs can be addressed. The effectiveness of our method is demonstrated by both clearly improved prediction performance in empirical evaluations and a compact set of selected imaging predictors relevant to disease sensitive SNPs.Availability: Software is publicly available at: http://ranger.uta.edu/%7eheng/Longitudinal/Contact: heng@uta.edu or shenli@inpui.edu
Identification of chemogenomic features from drug–target interaction networks using interpretable classifiers
Authors: Tabei Yasuo , Pauwels Edouard , Stoven Véronique , Takemoto Kazuhiro , Yamanishi Yoshihiro 
Published: September 2012

Abstract
Motivation: Drug effects are mainly caused by the interactions between drug molecules and their target proteins including primary targets and off-targets. Identification of the molecular mechanisms behind overall drug–target interactions is crucial in the drug design process.
Results: We develop a classifier-based approach to identify chemogenomic features (the underlying associations between drug chemical substructures and protein domains) that are involved in drug–target interaction networks. We propose a novel algorithm for extracting informative chemogenomic features by using L1 regularized classifiers over the tensor product space of possible drug–target pairs. It is shown that the proposed method can extract a very limited number of chemogenomic features without loosing the performance of predicting drug–target interactions and the extracted features are biologically meaningful. The extracted substructure–domain association network enables us to suggest ligand chemical fragments specific for each protein domain and ligand core substructures important for a wide range of protein families.
Availability: Softwares are available at the supplemental website.
Contact: yamanishi@bioreg.kyushu-u.ac.jp
Supplementary Information: Datasets and all results are available at http://cbio.ensmp.fr/~yyamanishi/l1binary/ .
Multiple instance learning of Calmodulin binding sites
Authors: Minhas Fayyaz ul Amir Afsar , Ben-Hur Asa 
Published: September 2012

Abstract
Motivation: Calmodulin (CaM) is a ubiquitously conserved protein that acts as a calcium sensor, and interacts with a large number of proteins. Detection of CaM binding proteins and their interaction sites experimentally requires a significant effort, so accurate methods for their prediction are important.
Results: We present a novel algorithm (MI-1 SVM) for binding site prediction and evaluate its performance on a set of CaM-binding proteins extracted from the Calmodulin Target Database. Our approach directly models the problem of binding site prediction as a large-margin classification problem, and is able to take into account uncertainty in binding site location. We show that the proposed algorithm performs better than the standard SVM formulation, and illustrate its ability to recover known CaM binding motifs. A highly accurate cascaded classification approach using the proposed binding site prediction method to predict CaM binding proteins in Arabidopsis thaliana is also presented.
Availability: Matlab code for training MI-1 SVM and the cascaded classification approach is available on request.
Contact: fayyazafsar@gmail.com or asa@cs.colostate.edu
Chronic kidney disease and cardiac remodelling in patients with mild heart failure: results from the REsynchronization reVErses Remodeling in Systolic Left vEntricular Dysfunction (REVERSE) study
Authors: Mathew Jehu , Katz Ronit , St. Sutton Martin John , Dixit Sanjay , Gerstenfeld Edward P. , Ghio Stefano , Gold Michael R. , Linde Cecilia , Shlipak Michael G. , Deo Rajat 
Published: September 2012

AimsChronic kidney disease (CKD) is a risk factor for left ventricular hypertrophy (LVH) and heart failure. We evaluated the effect of CKD on left ventricular (LV) remodelling among patients with mild heart failure.Methods and resultsREVERSE was a randomized, controlled trial evaluating cardiac resynchronization therapy (CRT) in patients with New York Heart Association (NYHA) class I/II heart failure. CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. We compared changes in LV function and size over the course of 12 months by CKD status using linear mixed models adjusted for demographics, co‐morbidities, medications, cardiomyopathy aetiology, and CRT status. Finally, we evaluated the effect of CKD on cardiac remodelling among patients randomized to CRT on or off. CKD was associated with worsening LV function and dilation compared with the non‐CKD group {adjusted, 12‐month β coefficients for the CKD group compared with the non‐CKD referent group: LV ejection fraction (%) [–1.80, 95% confidence interval (CI) –3.36 to –0.24], LV end‐systolic volume (mL) (14.16, 95% CI 3.96–24.36), LV end‐diastolic volume (mL) (14.88, 95% CI 2.88–26.76), LV end‐systolic diameter (cm) (0.36, 95% CI 0.12–0.48), LV end‐diastolic diameter (cm) (0.24, 95% CI 0.012–0.36), mitral regurgitation (%) (3.12, 95% CI 0.48–5.76), and LV shape (0.036, 95% CI 0.012–0.060)}. In participants assigned to CRT, those without CKD had significantly greater improvements in LV structural parameters compared with the CKD group.ConclusionsIn comparison with participants with normal kidney function, CKD is an independent risk factor for ventricular dysfunction and dilation. CRT improves LV function and structure to a lesser extent in patients with CKD than in those with normal kidney function.