Kahn Coates (mosquestory1)

Chevron osteotomy for the treatment of mild and moderate hallux valgus obtain good effects. The procedure is suitable for a variety of cases, thereby allowing for a significant degree of correction. This study aimed to investigate Chevron osteotomy procedures for the correction of hallux valgus in the medium-term (2010-2016) by podiatrists surgeons. It takes into account clinical and radiological findings as well as patient perspectives and level of satisfaction. All patients were assessed preoperatively, postoperatively and at a final follow-up. Fifty feet (forty five patients). The mean age was 59.43 (range 32 to 80) years. All of the participants signed an informed consent form to take part in the study. The protocols include chart review, clinical and radiological. Anterior-posterior weight-bearing radiographs were analyzed preoperatively and at final follow-up. All radiological data were assessed by two observers blinded. check details Clinical and functional measurements as well as evaluation of the satisfaction howed that radiological results at final follow-up weren´t compatible with relapse of the deformity. The definitive clinical results, and the degree of patient satisfaction achieved with this technique were favorable from the patients' point of view. Many diseases have a metabolic background, which is increasingly investigated due to improved measurement techniques allowing high-throughput assessment of metabolic features in several body fluids. Integrating data from multiple cohorts is of high importance to obtain robust and reproducible results. However, considerable variability across studies due to differences in sampling, measurement techniques and study populations needs to be accounted for. We present Metabolite-Investigator, a scalable analysis workflow for quantitative metabolomics data from multiple studies. Our tool supports all aspects of data pre-processing including data integration, cleaning, transformation, batch analysis as well as multiple analysis methods including uni- and multivariable factor-metabolite associations, network analysis and factor prioritization in one or more cohorts. Moreover, it allows identifying critical interactions between cohorts and factors affecting metabolite levels and inferring a common covariate model, all via a graphical user interface. We constructed Metabolite-Investigator as a free and open web-tool and stand-alone Shiny-app. It is hosted at https//apps.health-atlas.de/metabolite-investigator/, the source code is freely available at https//github.com/cfbeuchel/Metabolite-Investigator. Supplementary data are available at Bioinformatics online. Supplementary data are available at Bioinformatics online. Although genome-wide association studies (GWASs) have identified thousands of variants for various traits, the causal variants and the mechanisms underlying the significant loci are largely unknown. In this study, we aim to predict noncoding variants that may functionally affect translation initiation through long-range chromatin interaction. By incorporating the Hi-C data, we propose a novel and powerful deep learning model (DeepHiC) of artificial intelligence to classify interacting and non-interacting fragment pairs and predict the functional effects of sequence alteration of single nucleotide on chromatin interaction and thus on gene expression. The changes in chromatin interaction probability between the reference sequence and the altered sequence reflect the degree of functional impact for the variant. The model was effective and efficient with the classification of interacting and non-interacting fragment pairs. The predicted causal SNPs that had a larger impact on chromatin interaction were more likely to be identified by GWAS and eQTL analyses. We demonstrate that an integrative approach combining artificial intelligence - deep learning with high throughput experimental eviden