Cardiovascular disease in retired NFL players: a systematic review.

Objective: Despite robust research endeavors exploring post-play health implications in former NFL players, the impact of former-player status on long-term cardiovascular health has not yet been elucidated. The purpose of this systematic review is to describe the available research on the cardiovascular health in former NFL players.

Methods: Relevant studies were included from the PubMed, Scopus, and Embase databases.

Patients with operative gluteus medius tears often present with a concomitant history of lumbar pathology.

Background: Studies have indicated a correlation between patients presenting with decreased gluteus medius function and a history of lumbar pathology (LP). However, literature investigating the relationship between the prevalence of lumbar pathology in patients with gluteus medius tears is lacking. The purpose of this study is to determine if patients undergoing repair for gluteus medius tears have concomitant lumbar pathology.

Orthopedic consequences of modern gladiators: a systematic review of lower extremity musculoskeletal issues in retired NFL players.

Objectives: The stressors that National Football League (NFL) athletes face are well-described and documented with regard to multisystem afflictions and injury prevalence. However, the majority of literature discusses the short-term effects rather than long-term outcomes of playing professional football. The purpose of this study was to characterize the long-term musculoskeletal issues in the retired NFL population.

TMT One-Stop Shop: From Reliable Sample Preparation to Computational Analysis Platform.

In this chapter we describe the workflow we use for labeled quantitative proteomics analysis using tandem mass tags (TMT) starting with the sample preparation and ending with the multivariate analysis of the resulting data. We detail the step-by-step process from sample processing, labeling, fractionation, and data processing using Proteome Discoverer through to data analysis and interpretation in the context of a multi-run experiment. The final analysis and data interpretation rely on an R package we call TMTPrepPro, which are deployed on a local GenePattern server, and used for generating various outputs which are also outlined herein.

Label-free quantitative shotgun proteomics using normalized spectral abundance factors.

In this chapter we describe the workflow used in our laboratory for label-free quantitative shotgun proteomics based on spectral counting. The main tools used are a series of R modules known collectively as the Scrappy program. We describe how to go from peptide to spectrum matching in a shotgun proteomics experiment using the XTandem algorithm, to simultaneous quantification of up to thousands of proteins, using normalized spectral abundance factors.

PloGO: plotting gene ontology annotation and abundance in multi-condition proteomics experiments.

We describe the PloGO R package, a simple open-source tool for plotting gene ontology (GO) annotation and abundance information, which was developed to aid with the bioinformatics analysis of multi-condition label-free proteomics experiments using quantitation based on spectral counting. PloGO can incorporate abundance (raw spectral counts) or normalized spectral abundance factors (NSAF) data in addition to the GO annotation, as well as handle multiple files and allow for a targeted collection of GO categories of interest. Our main aims were to help identify interesting subsets of proteins for further analysis such as those arising from a protein data set partition based on the presence and absence or multiple pair-wise comparisons, as well as provide GO summaries that can be easily used in subsequent analyses.