PSS25 COST-EFFECTIVENESS OF ETANERCEPT AND EFALIZUMAB IN THE MANAGEMENT OF MODERATE AND SEVERE PLAQUE PSORIASIS

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Support Vector Machine based method to distinguish proteobacterial proteins from eukaryotic plant proteins

Background: Members of the phylum Proteobacteria are most prominent among bacteria causing plant diseases that result in a diminution of the quantity and quality of food produced by agriculture. To ameliorate these losses, there is a need to identify infections in early stages. Recent developments in next generation nucleic acid sequencing and mass spectrometry open the door to screening plants by the sequences of their macromolecules. Such an approach requires the ability to recognize the organismal origin of unknown DNA or peptide fragments. There are many ways to approach this problem but none have emerged as the best protocol. Here we attempt a systematic way to determine organismal origins of peptides by using a machine learning algorithm. The algorithm that we implement is a Support Vector Machine (SVM).Result: The amino acid compositions of proteobacterial proteins were found to be different from those of plant proteins. We developed an SVM model based on amino acid and dipeptide compositions to distinguish between a proteobacterial protein and a plant protein. The amino acid composition (AAC) based SVM model had an accuracy of 92.44% with 0.85 Matthews correlation coefficient (MCC) while the dipeptide composition (DC) based SVM model had a maximum accuracy of 94.67% and 0.89 MCC. We also developed SVM models based on a hybrid approach (AAC and DC), which gave a maximum accuracy 94.86% and a 0.90 MCC. The models were tested on unseen or untrained datasets to assess their validity.Conclusion: The results indicate that the SVM based on the AAC and DC hybrid approach can be used to distinguish proteobacterial from plant protein sequences.Peer reviewedBiochemistry and Molecular Biolog

A literature-based approach to evaluate the predictive capacity of a marker using time-dependent summary receiver operating characteristics

Meta-analyses are popular tools to summarize the results of publications. Prognostic performances of a marker are usually summarized by meta-analyses of survival curves or hazard ratios. These approaches may detect a difference in survival according to the marker but do not allow evaluation of its prognostic capacity. Time-dependent receiver operating characteristic curves evaluate the ability of a marker to predict time-to-event. In this article, we describe an adaptation of time-dependent summary receiver operating characteristic curves from published survival curves. To achieve this goal, we modeled the marker and the time-to-event distributions using non-linear mixed models. First, we applied this methodology to individual data in kidney transplantation presented as aggregated data, in order to validate the method. Second, we re-analyzed a published meta-analysis, which focused on the capacity of KI-67 to predict the overall survival of patients with breast cancer

Skeletal age assessment from the olecranon for idiopathic scoliosis at Risser grade 0

Background: Themain progression of idiopathic scoliosis occurs during peak height growth velocity, which is between the ages of eleven and thirteen years in girls and thirteen and fifteen years in boys and corresponds to the accelerating phase of pubertal growth. The Risser sign remains at grade 0 during this stage of growth. Triradiate cartilage closure occurs at approximately twelve years of age in girls and fourteen years in boys, which is in the middle of this phase. In addition to regular height measurements, a more detailed evaluation of skeletal maturity would be desirable prior to the identification of Risser grade 1. From the method of Sauvegrain et al., Dim ́eglio derived a simplified method based on the radiographic appearance of the olecranon, which allows skeletal age to be assessed in six-month intervals. The purpose of this study was to determine the accuracy and the value of this simple method for the follow-up of patients with scoliosis. Methods: Five radiographic images demonstrate the typical characteristics of the olecranon during pubertal growth: two ossification nuclei, a half-moon image, a rectangular shape, the beginning of fusion, and complete fusion. This classificationmethodwasevaluated by three experienced and independent observers fromlateral radiographs of the elbow in 100 boys and 100 girls with idiopathic scoliosis during the time of peak height velocity. Skeletal ages were correlated with the integral Sauvegrainmethod. The degree of interobserver concordance was determined, and skeletal age was compared with chronological age and the time of triradiate cartilage closure. Results: For the three observers, the average concordance between the Sauvegrain and olecranon methods was excellent (r = 0.977 for boys and r = 0.938 for girls). The interobserver agreement was also excellent (r = 0.987 for the olecranon method and r = 0.958 for the Sauvegrain method for boys, and r = 0.992 and r = 0.985, respectively, for girls). Skeletal and chronological age were considered to correspond to each other within a six-month range for 49% of the boys and 51% of the girls, while 25% of the boys and 26% of the girls had an advanced skeletal age and 26% of boys and 23% of girls had a delayed skeletal age. Triradiate cartilage closure occurred at the same time as the appearance of the rectangular shape of the olecranon in 65%of the boys and61%of the girls, corresponding to skeletal ages of fourteen and twelve years, respectively. In 91% of the boys and 88% of the girls, the triradiate cartilage fused within six months before to six months after the appearance of the rectangular shape of the olecranon, which occurred between the half-moon image and the beginning of fusion of the olecranon. Conclusions: Themethod of assessing skeletal age fromthe olecranon allowsskeletalmaturity to be evaluated in regular six-month intervals during the phase of peak height velocity. This method is simple, precise, and reliable. It complements the Risser grade-0 and the triradiate cartilage evaluation. Level of Evidence: Prognostic Level II