Universitätsbibliothek

Background Published models predicting nasal colonization with Methicillin-resistant Staphylococcus aureus among hospital admissions predominantly focus on separation of carriers from non-carriers and are frequently evaluated using measures of discrimination. In contrast, accurate estimation of carriage probability, which may inform decisions regarding treatment and infection control, is rarely assessed. Furthermore, no published models adjust for MRSA prevalence. Methods Using logistic regression, a scoring system (values from 0 to 200) predicting nasal carriage of MRSA was created using a derivation cohort of 3091 individuals admitted to a European tertiary referral center between July 2007 and March 2008. The expected positive predictive value of a rapid diagnostic test (GeneOhm, Becton & Dickinson Co.) was modeled using non-linear regression according to score. Models were validated on a second cohort from the same hospital consisting of 2043 patients admitted between August 2008 and January 2012. Our suggested correction score for prevalence was proportional to the log-transformed odds ratio between cohorts. Calibration before and after correction, i.e. accurate classification into arbitrary strata, was assessed with the Hosmer-Lemeshow-Test. Results Treating culture as reference, the rapid diagnostic test had positive predictive values of 64.8% and 54.0% in derivation and internal validation corhorts with prevalences of 2.3% and 1.7%, respectively. In addition to low prevalence, low positive predictive values were due to high proportion (> 66%) of mecA-negative Staphylococcus aureus among false positive results. Age, nursing home residence, admission through the medical emergency department, and ICD-10-GM admission diagnoses starting with “A” or “J” were associated with MRSA carriage and were thus included in the scoring system, which showed good calibration in predicting probability of carriage and the rapid diagnostic test’s expected positive predictive value. Calibration for both probability of carriage and expected positive predictive value in the internal validation cohort was improved by applying the correction score. Conclusions Given a set of patient parameters, the presented models accurately predict a) probability of nasal carriage of MRSA and b) a rapid diagnostic test’s expected positive predictive value. While the former can inform decisions regarding empiric antibiotic treatment and infection control, the latter can influence choice of screening method.

Early healing after myocardial infarction (MI) is characterized by a strong inflammatory reaction. Most leukotrienes are pro-inflammatory and are therefore potential mediators of healing and remodeling after myocardial ischemia. The enzyme 5-lipoxygenase (5-LOX) has a key role in the transformation of arachidonic acid in leukotrienes. Thus, we tested the effect of 5-LOX on healing after MI. After chronic coronary artery ligation, early mortality was significantly increased in 5-LOX\(^{−/−}\) when compared to matching wildtype (WT) mice due to left ventricular rupture. This effect could be reproduced in mice treated with the 5-LOX inhibitor Zileuton. A perfusion mismatch due to the vasoactive potential of leukotrienes is not responsible for left ventricular rupture since local blood flow assessed by magnetic resonance perfusion measurements was not different. However, after MI, there was an accentuation of the inflammatory reaction with an increase of pro-inflammatory macrophages. Yet, mortality was not changed in chimeric mice (WT vs. 5-LOX\(^{−/−}\) bone marrow in 5-LOX\(^{−/−}\) animals), indicating that an altered function of 5-LOX\(^{−/−}\) inflammatory cells is not responsible for the phenotype. Collagen production and accumulation of fibroblasts were significantly reduced in 5-LOX\(^{−/−}\) mice in vivo after MI. This might be due to an impaired migration of 5-LOX\(^{−/−}\) fibroblasts, as shown in vitro to serum. In conclusion, a lack or inhibition of 5-LOX increases mortality after MI because of healing defects. This is not mediated by a change in local blood flow, but through an altered inflammation and/or fibroblast function.

No abstract available

Background A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.