bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hammock: a hidden Markov model-based peptide clustering algorithm to identify protein-interaction consensus motifs in large datasets
Authors: Krejci Adam , Hupp Ted R. , Lexa Matej , Vojtesek Borivoj , Muller Petr 
Published: September 2015

Abstract
Motivation: Proteins often recognize their interaction partners on the basis of short linear motifs located in disordered regions on proteins’ surface. Experimental techniques that study such motifs use short peptides to mimic the structural properties of interacting proteins. Continued development of these methods allows for large-scale screening, resulting in vast amounts of peptide sequences, potentially containing information on multiple protein-protein interactions. Processing of such datasets is a complex but essential task for large-scale studies investigating protein-protein interactions.
Results: The software tool presented in this article is able to rapidly identify multiple clusters of sequences carrying shared specificity motifs in massive datasets from various sources and generate multiple sequence alignments of identified clusters. The method was applied on a previously published smaller dataset containing distinct classes of ligands for SH3 domains, as well as on a new, an order of magnitude larger dataset containing epitopes for several monoclonal antibodies. The software successfully identified clusters of sequences mimicking epitopes of antibody targets, as well as secondary clusters revealing that the antibodies accept some deviations from original epitope sequences. Another test indicates that processing of even much larger datasets is computationally feasible.
Availability and implementation: Hammock is published under GNU GPL v. 3 license and is freely available as a standalone program (from http://www.recamo.cz/en/software/hammock-cluster-peptides/) or as a tool for the Galaxy toolbox (from https://toolshed.g2.bx.psu.edu/view/hammock/hammock). The source code can be downloaded from https://github.com/hammock-dev/hammock/releases.
Contact: muller@mou.cz
Supplementary information: Supplementary data are available at Bioinformatics online.
ResiCon: a method for the identification of dynamic domains, hinges and interfacial regions in proteins
Authors: Dziubiński Maciej , Daniluk Paweł , Lesyng Bogdan 
Published: September 2015

AbstractMotivation: Structure of most proteins is flexible. Identification and analysis of intramolecular motions is a complex problem. Breaking a structure into relatively rigid parts, the so-called dynamic domains, may help comprehend the complexity of protein’s mobility. We propose a new approach called ResiCon (Residue Contacts analysis), which performs this task by applying a data-mining analysis of an ensemble of protein configurations and recognizes dynamic domains, hinges and interfacial regions, by considering contacts between residues.Results: Dynamic domains found by ResiCon are more compact than those identified by two other popular methods: PiSQRD and GeoStaS. The current analysis was carried out using a known reference set of 30 NMR protein structures, as well as molecular dynamics simulation data of flap opening events in HIV-1 protease. The more detailed analysis of HIV-1 protease dataset shows that ResiCon identified dynamic domains involved in structural changes of functional importance.Availability and implementation: The ResiCon server is available at URL: http://dworkowa.imdik.pan.pl/EP/ResiCon.Contact: pawel@bioexploratorium.plSupplementary information: Supplementary data are available at Bioinformatics online.
metaModules identifies key functional subnetworks in microbiome-related disease
Authors: May Ali , Brandt Bernd W. , El-Kebir Mohammed , Klau Gunnar W. , Zaura Egija , Crielaard Wim , Heringa Jaap , Abeln Sanne 
Published: September 2015

Abstract
Motivation: The human microbiome plays a key role in health and disease. Thanks to comparative metatranscriptomics, the cellular functions that are deregulated by the microbiome in disease can now be computationally explored. Unlike gene-centric approaches, pathway-based methods provide a systemic view of such functions; however, they typically consider each pathway in isolation and in its entirety. They can therefore overlook the key differences that (i) span multiple pathways, (ii) contain bidirectionally deregulated components, (iii) are confined to a pathway region. To capture these properties, computational methods that reach beyond the scope of predefined pathways are needed.
Results: By integrating an existing module discovery algorithm into comparative metatranscriptomic analysis, we developed metaModules, a novel computational framework for automated identification of the key functional differences between health- and disease-associated communities. Using this framework, we recovered significantly deregulated subnetworks that were indeed recognized to be involved in two well-studied, microbiome-mediated oral diseases, such as butanoate production in periodontal disease and metabolism of sugar alcohols in dental caries. More importantly, our results indicate that our method can be used for hypothesis generation based on automated discovery of novel, disease-related functional subnetworks, which would otherwise require extensive and laborious manual assessment.
Availability and implementation: metaModules is available at https://bitbucket.org/alimay/metamodules/
Contact: a.may@vu.nl or s.abeln@vu.nl
Supplementary information: Supplementary data are available at Bioinformatics online.
Desiderata for computable representations of electronic health records-driven phenotype algorithms
Authors: Mo Huan , Thompson William K , Rasmussen Luke V , Pacheco Jennifer A , Jiang Guoqian , Kiefer Richard , Zhu Qian , Xu Jie , Montague Enid , Carrell David S , Lingren Todd , Mentch Frank D , Ni Yizhao , Wehbe Firas H , Peissig Peggy L , Tromp Gerard , Larson Eric B , Chute Christopher G , Pathak Jyotishman , Denny Joshua C , Speltz Peter , Kho Abel N , Jarvik Gail P , Bejan Cosmin A , Williams Marc S , Borthwick Kenneth , Kitchner Terrie E , Roden Dan M , Harris Paul A 
Published: September 2015

AbstractBackground Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.
Patient and physician predictors of patient receipt of therapies recommended by a computerized decision support system when initially prescribed broad-spectrum antibiotics: a cohort study
Authors: Chow Angela LP , Lye David C. , Arah Onyebuchi A 
Published: September 2015

AbstractObjective Antibiotic computerized decision support systems (CDSSs) were developed to guide antibiotic decisions, yet prescriptions of CDSS-recommended antibiotics have remained low. Our aim was to identify predictors of patients' receipt of empiric antibiotic therapies recommended by a CDSS when the prescribing physician had an initial preference for using broad-spectrum antibiotics.Methods We conducted a prospective cohort study in a 1 500-bed tertiary-care hospital in Singapore. We included all patients admitted from October 1, 2011 through September 30, 2012, who were prescribed piperacillin-tazobactam or carbapenem for empiric therapy and auto-triggered to receive antibiotic recommendations by the in-house antibiotic CDSS. Relevant data on the patient, prescribing and attending physicians were collected via electronic linkages of medical records and administrative databases. To account for clustering, we used multilevel logistic regression models to explore factors associated with receipt of CDSS-recommended antibiotic therapy.Results One-quarter of the 1 886 patients received CDSS-recommended antibiotics. More patients treated for pneumonia (33.2%) than sepsis (12.1%) and urinary tract infections (7.1%) received CDSS-recommended antibiotic therapies. The prescribing physician – but not the attending physician or clinical specialty – accounted for some (13.3%) of the variation. Prior hospitalization (odds ratio [OR] 1.32, 95% CI, 1.01-1.71), presumed pneumonia (OR 6.77, 95% CI, 3.28-13.99), intensive care unit (ICU) admission (OR 0.38, 95% CI, 0.21-0.66), and renal impairment (OR 0.70, 95% CI, 0.52-0.93) were factors associated with patients’ receipt of CDSS-recommended antibiotic therapies.Conclusions We observed that ICU admission and renal impairment were negative predictors of patients’ receipt of CDSS-recommended antibiotic therapies. Patients admitted to ICU and those with renal impairment might have more complex clinical conditions that require a physician's assessment in addition to antibiotic CDSS.
Cardiac catheterization laboratory inpatient forecast tool: a prospective evaluation
Authors: Toerper Matthew F , Flanagan Eleni , Siddiqui Sauleh , Appelbaum Jeff , Kasper Edward K , Levin Scott 
Published: September 2015

AbstractObjective To develop and prospectively evaluate a web-based tool that forecasts the daily bed need for admissions from the cardiac catheterization laboratory using routinely available clinical data within electronic medical records (EMRs).Methods The forecast model was derived using a 13-month retrospective cohort of 6384 catheterization patients. Predictor variables such as demographics, scheduled procedures, and clinical indicators mined from free-text notes were input to a multivariable logistic regression model that predicted the probability of inpatient admission. The model was embedded into a web-based application connected to the local EMR system and used to support bed management decisions. After implementation, the tool was prospectively evaluated for accuracy on a 13-month test cohort of 7029 catheterization patients.Results The forecast model predicted admission with an area under the receiver operating characteristic curve of 0.722. Daily aggregate forecasts were accurate to within one bed for 70.3% of days and within three beds for 97.5% of days during the prospective evaluation period. The web-based application housing the forecast model was used by cardiology providers in practice to estimate daily admissions from the catheterization laboratory.Discussion The forecast model identified older age, male gender, invasive procedures, coronary artery bypass grafts, and a history of congestive heart failure as qualities indicating a patient was at increased risk for admission. Diagnostic procedures and less acute clinical indicators decreased patients’ risk of admission. Despite the site-specific limitations of the model, these findings were supported by the literature.Conclusion Data-driven predictive analytics may be used to accurately forecast daily demand for inpatient beds for cardiac catheterization patients. Connecting these analytics to EMR data sources has the potential to provide advanced operational decision support.
Eggerthella lenta bacteraemia in a patient with Caroli disease
Authors: Miguel Sahuquillo-Arce José , Guitián-Deltell Jorge , Falomir-Salcedo Patricia , Galiana-Sastre María , López-Andujar Rafael , López-Hontangas José Luis 
Published: September 2015

Introduction:

Eggerthella lenta is an obligate anaerobic, non-spore-forming, Gram-positive rod found as a normal commensal of the human intestinal flora, which is capable of reducing digoxin into several metabolites. Disease caused by this micro-organism is unusual, although more frequent than reported.

Case presentation:
A 74-year-old man presented to the emergency room and was admitted with a mild acute cholangitis syndrome. One anaerobic blood culture became positive after 5 days of incubation. After an additional 5 days, the usual aerobic subcultures were negative, whereas anaerobically incubated Columbia blood agar presented tiny smooth colonies. The isolate was capable of reducing digoxin and was identified as Eggerthella lenta. Adequate antibiotic treatment with meropenem had been started and the patient recovered fully.

Conclusion:
We have described a patient with a potentially fatal bacteraemia with E. lenta that may have gone unnoticed. More case reports are necessary, not only to understand the pathogenicity and clinical course of infections by this neglected bacterium, but also to investigate its digoxin degradation and antimicrobial susceptibility variability.
Meningitis caused by Porphyromonas endodontalis detected by PCR amplification and sequencing of 16S rRNA genes direct from cerebrospinal fluid and cerebral tissue
Authors: New David W. , Pryce Todd M. 
Published: September 2015

Introduction:

Porphyromonas endodontalis (formerly Bacteroides endontalis) is a black-pigmented, non-motile, obligate anaerobe. It has an established role in endodontal infections and has rarely been isolated from other sites. To the best of our knowledge, this is the first time that this organism has been detected as the sole cause of meningitis. This was made possible by the use of direct-on-sample 16S rRNA gene amplification and sequencing.

Case presentation:
We present a case of meningitis that progressed to a cerebral abscess in an elderly but otherwise immunocompetent male. Despite broad-spectrum antibiotic therapy, the patient died.

Conclusion:
Although anaerobic meningitis is rarely described, it should be considered if there are clinical and biochemical features of meningitis but no organism isolated on standard aerobic culture.
Neisseria elongata prosthetic valve endocarditis: case report and literature review
Authors: Sawas Tarek , Hong-Nguyen Yugenia , Woods Christian J. 
Published: September 2015

Introduction:

Neisseria elongata, a Gram-variable, rod-shaped organism, was previously thought to be non-pathogenic. However, in recent years it has become increasingly recognized as a rare cause of infective endocarditis. Here, to the best of our knowledge, we describe the first case of bivalvular prosthetic valve endocarditis due to N. elongata.

Case Presentation:
A 55-year-old Taiwanese man with history of Streptococcus viridans endocarditis status post prosthetic mitral and aortic valve replacements presented with a 2-week history of progressive fatigue and altered mental status. He presented with fever, lethargy and shock. He was intubated and started on vasopressors. A systolic murmur was noted with leukocytosis and acute renal failure. He was started on broad-spectrum antibiotics. An initial trans-oesophageal echocardiogram (TOE) did not reveal vegetation, but showed an elevated aortic valve gradient of 70 mmHg consistent with severe aortic stenosis. A repeat TOE revealed multiple mobile and immobile mitral and aortic valve vegetations with an abscess extending toward the aortic valve. Three sets of positive blood cultures from admission identified N. elongata. Antibiotics were tailored to ceftriaxone. He underwent urgent aortic and mitral valve replacement. He completed a 6-week course of ceftriaxone. At discharge, two-dimensional echo revealed normal heart function with normal prosthetic mitral and aortic valves.

Conclusion:

N. elongata is an uncommon, but increasingly recognized, cause of infective endocarditis. It causes severe valvular destruction with systemic complications and often requires surgical intervention.
Development of EST-SSR annotated database in olive (Olea europaea)
Authors: Adawy Sami S. , Mokhtar Morad M. , Alsamman Alsamman M. , Sakr Mahmoud M. 
Published: September 2015

AbstractOlive tree (Olea europaeaL.) is one of the most important oil producing crops in the world and the genetic identification of several genotypes by using molecular markers is the first step in its breeding programs. A set of 1,801 well-informative EST-SSR primers targeting specific Olive genes included in different biological processes and pathways were generated using 11,215 Olive EST sequences acquired from the NCBI database. Our bioinformatics analytical procedure showed that 8295 SSR motifs were detected which belonged to different motif types with occurrences of 77.6%, 11.84%, 8.62%, 0.84%, 0.77% and 0.29% for Mononucleotide, trinucleotide, dinucleotide, hexanucleotide, pentanucleotide and tetranucleotide respectively. The appearance of the AAG/CTT repeat was highly represented in trinucleotide and the representation of AG/CT was high in dinucleotide repeats. Results obtained from functional annotation of olives EST sequences targeted with our primers set indicated that 78.5% of these sequences having homology with known proteins, while 4.2% was homologous to hypothetical, predicted, unnamed or uncharacterized proteins and the 17.3% sequences did not possess homology with any known proteins. Our EST-SSR primer set cover a total of 92 biological pathways such as carbohydrate metabolism pathway, energy metabolism& carbon fixation in photosynthetic organism pathway including 11 pathways associated with lipid metabolism. A twenty five randomly selected primers were applied to 9 Egyptian cultivated olive accessions to test its amplification and polymorphism detection efficacy. All tested primers were successfully amplified and only 10 exhibited detectable polymorphism.
Passenger DNA alterations reduce cancer fitness in cell culture and mouse models
Authors: McFarland Christopher D , Yaglom Julia A , Wojtkowiak Jonathan W , Scott Jacob G , Morse David L , Sherman Michael Y , Mirny Leonid A 
Published: September 2015

ABSTRACTGenomic instability causes cancers to acquire hundreds to thousands of mutations and chromosomal alterations during their somatic evolution. Most of these mutations and alterations are termed passengers because they do not confer cancer phenotypes. Evolutionary simulations and cancer genomic studies suggested that mildly-deleterious passengers accumulate, collectively slow cancer progression, reduce the fitness of cancer cells and enhance the effects of therapeutics. However, these effects of passengers and their impact on clinical variables remain limited to genomic analysis. Here, to assess passengers’ effect on cell fitness and cancer, we specifically introduced increasing passenger loads into human cell lines and mouse models. We found that passenger load dramatically reduced cancer cell’s fitness in every model investigated. Passengers’ average fitness cost of ∼3% per MB, indicates that genomic instability in cancer in patients can slow tumor growth and prevent metastatic progression. We conclude that genomic instability in cancer is a double-edged sword: it accelerates the accumulation of adaptive drivers, yet incurs a harmful passenger load that can outweigh drivers’ benefit. Passenger load could be a useful biomarker for tumor aggressiveness and response to mutagenic or passenger-exacerbating therapies, including anti-tumor immunity.
Corporate disclosure and foreign share ownership: empirical evidence from African countries
Authors: Bokpin Godfred A. , Isshaq Zangina , Nyarko Eunice  Stella 
Published: September 2015

Purpose
– The study aims to seeks to ascertain the impact of corporate disclosure on foreign equity ownership. Corporate disclosures are important to for stock markets because it is an activity that mitigates information differences between company insiders and outsiders.

Design/methodology/approach
– Corporate disclosures assume an even greater important when company outsiders are not domiciled in the same country as the company and the company insiders. In this study, the relation between foreign share ownership and corporate disclosures using data on Ghana, Kenya and Nigeria is examined.

Findings
– The consistent results in this study are that foreign share ownership is positively related to firm size. A negative relation, however, between foreign share ownership and corporate disclosure is found, but this turns out to be related to disclosures about ownership, while disclosures on financial reporting and board management have a positive and insignificant statistical relation taking into account unobserved country, time and firm effects. Further analysis shows that corporate disclosures are very persistent and negatively related to lag foreign share ownership. No consistent statistical relation is found between disclosure and market-to-book values as a proxy for investment opportunities. It is recommended to African-listed firms to pursue adoption of high-quality financial reporting standards and to increase their reporting on board management. The study also recommends that the African Government weighs the benefits of detailed ownership disclosures.

Originality/value
– The study utilises frontier market data to complement existing literature on how corporate disclosure and transparency influences foreign investors decision to invest in Africa.