Prediction and in vitro verification of potential CTL epitopes conserved among PRRSV-2 strains

Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) is the causative agent of one of the most important porcine diseases with a high impact on animal health, welfare, and production economy. PRRSV exhibits a multitude of immunoevasive strategies that, in combination with a very high mutation rate, has hampered the development of safe and broadly protective vaccines. Aiming at a vaccine inducing an effective cytotoxic T cell response, a bioinformatics approach was taken to identify conserved PRRSV-derived peptides predicted to react broadly with common swine leukocyte antigen (SLA) class I alleles. Briefly, all possible 9- and 10-mer peptides were generated from 104 complete PRRSV type 2 genomes of confirmed high quality, and peptides with high binding affinity to five common SLAs were identified combining the NetMHCpan and positional scanning combinatorial peptide libraries binding predictions. Predicted binders were prioritized according to genomic conservation and SLA coverage using the PopCover algorithm. From this, 53 peptides were acquired for further analysis. Binding affinity and stability of a subset of 101 peptide-SLA combinations were validated in vitro for 4 of the 5 SLAs. Eventually, 23% of the predicted peptide-SLA combinations showed to form complexes with a dissociation half-life ≥30 min. Additionally, combining the two prediction methods proved to be more robust across alleles than either method used alone in terms of predicted-to-observed correlations. In summary, our approach represents a finely tuned epitope prediction pipeline providing a rationally selected ensemble of peptides for future in vivo experiments with pigs expressing the included SLAs.Fil: Welner, Simon. Technical University of Denmark; DinamarcaFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Rasmussen, Michael. Universidad de Copenhagen; DinamarcaFil: Buus, Søren. Universidad de Copenhagen; DinamarcaFil: Jungersen, Gregers. Technical University of Denmark; DinamarcaFil: Larsen, Lars Erik. Technical University of Denmark; Dinamarc

The effect of MELatOnin on Depression, anxietY, cognitive function and sleep disturbances in patients with breast cancer. The MELODY trial: protocol for a randomised, placebo-controlled, double-blinded trial

This is a protocol article on the MELODY trial. The objective of this double-blind randomized, placebo-controlled trial is to investigate whether daily treatment with 6 mg oral melatonin has a prophylactic or ameliorating effect on depressive symptoms, anxiety, sleep disturbances and cognitive dysfunction in women with breast cancer. Furthermore to examine whether a specific clock-gene PER3 is correlated with an increased risk of depressive symptoms, sleep disturbances or cognitive dysfunction

Risk assessment models for potential use in the emergency department have lower predictive ability in older patients compared to the middle-aged for short-term mortality - a retrospective cohort study

Table S1. Comparison of Baseline characteristics of the TRIAGE II study and TRIAGE III study. Patients above 40 years were included in the current study Table S2. Comparison of AUCs of individual predictors in discriminating short-term mortality of ED patients, grouped according to age: 40–69 years (middle-aged), and 70+ years (older). Figure S1. Area under the Curve (AUC) for Receiver operating characteristics for all-cause mortality within 7 days for acutely admitted patients. Comparison of patients aged 40-69 (Middle-aged, blue colour), and patients aged 70+ (Older, red colour). The graph presents four different approaches of risk assessment of patients acutely presenting at the emergency department. Two different triage algorithms; Adaptive Process Triage (ADAPT) and Copenhagen Triage Algorithm (CTA), a predictive model using four vital signs (heart rate, arterial oxygen saturation, respiratory rate and systolic blood pressure), and a predictive model using levels of seven routine biomarkers (albumin, creatinine, c-reactive protein, haemoglobin, leucocytes, potassium, sodium). (DOCX 241 kb

Dimethyl fumarate is an allosteric covalent inhibitor of the p90 ribosomal S6 kinases

Dimethyl fumarate (DMF) has been applied for decades in the treatment of psoriasis and now also multiple sclerosis. However, the mechanism of action has remained obscure and involves high dose over long time of this small, reactive compound implicating many potential targets. Based on a 1.9 Å resolution crystal structure of the C-terminal kinase domain of the mouse p90 Ribosomal S6 Kinase 2 (RSK2) inhibited by DMF we describe a central binding site in RSKs and the closely related Mitogen and Stress-activated Kinases (MSKs). DMF reacts covalently as a Michael acceptor to a conserved cysteine residue in the αF-helix of RSK/MSKs. Binding of DMF prevents the activation loop of the kinase from engaging substrate, and stabilizes an auto-inhibitory αL-helix, thus pointing to an effective, allosteric mechanism of kinase inhibition. The biochemical and cell biological characteristics of DMF inhibition of RSK/MSKs are consistent with the clinical protocols of DMF treatment.</p

Quantification of Normal Cell Fraction and Copy Number Neutral LOH in Clinical Lung Cancer Samples Using SNP Array Data

Technologies based on DNA microarrays have the potential to provide detailed information on genomic aberrations in tumor cells. In practice a major obstacle for quantitative detection of aberrations is the heterogeneity of clinical tumor tissue. Since tumor tissue invariably contains genetically normal stromal cells, this may lead to a failure to detect aberrations in the tumor cells.Using SNP array data from 44 non-small cell lung cancer samples we have developed a bioinformatic algorithm that accurately models the fractions of normal and tumor cells in clinical tumor samples. The proportion of normal cells in combination with SNP array data can be used to detect and quantify copy number neutral loss-of-heterozygosity (CNNLOH) in the tumor cells both in crude tumor tissue and in samples enriched for tumor cells by laser capture microdissection.Genome-wide quantitative analysis of CNNLOH using the CNNLOH Quantifier method can help to identify recurrent aberrations contributing to tumor development in clinical tumor samples. In addition, SNP-array based analysis of CNNLOH may become important for detection of aberrations that can be used for diagnostic and prognostic purposes

Diagnostic performance of an acoustic-based system for coronary artery disease risk stratification

ObjectiveDiagnosing coronary artery disease (CAD) continues to require substantial healthcare resources. Acoustic analysis of transcutaneous heart sounds of cardiac movement and intracoronary turbulence due to obstructive coronary disease could potentially change this. The aim of this study was thus to test the diagnostic accuracy of a new portable acoustic device for detection of CAD.MethodsWe included 1675 patients consecutively with low to intermediate likelihood of CAD who had been referred for cardiac CT angiography. If significant obstruction was suspected in any coronary segment, patients were referred to invasive angiography and fractional flow reserve (FFR) assessment. Heart sound analysis was performed in all patients. A predefined acoustic CAD-score algorithm was evaluated; subsequently, we developed and validated an updated CAD-score algorithm that included both acoustic features and clinical risk factors. Low risk is indicated by a CAD-score value ≤20.ResultsHaemodynamically significant CAD assessed from FFR was present in 145 (10.0%) patients. In the entire cohort, the predefined CAD-score had a sensitivity of 63% and a specificity of 44%. In total, 50% had an updated CAD-score value ≤20. At this cut-off, sensitivity was 81% (95% CI 73% to 87%), specificity 53% (95% CI 50% to 56%), positive predictive value 16% (95% CI 13% to 18%) and negative predictive value 96% (95% CI 95% to 98%) for diagnosing haemodynamically significant CAD.ConclusionSound-based detection of CAD enables risk stratification superior to clinical risk scores. With a negative predictive value of 96%, this new acoustic rule-out system could potentially supplement clinical assessment to guide decisions on the need for further diagnostic investigation.Trial registration numberClinicalTrials.gov identifier NCT02264717; Results.</jats:sec