Defining Exposures in Professional Football: Professional American-Style Football Players as an Occupational Cohort.

Studies of professional American football players have shown that football-related activities lead to acute injuries and may have long-term adverse health outcomes including osteoarthritis, neurocognitive impairment, and cardiovascular disease. However, the full complement of what constitutes professional football exposure has yet to be effectively articulated. Most likely, professional football exposure encompasses a multifaceted array of experiences including head impacts and joint stresses, long-term pain medication use, dietary restrictions, and strenuous training regimens. To study the health of professional American football players, characterizing the group as an occupational cohort and taking advantage of methods established within the discipline of occupational epidemiology may be beneficial. We conducted a narrative review of existing football research, occupational epidemiological methods papers, and occupational medicine studies. Here we describe the traditional occupational epidemiological approach to assessing exposure in a novel cohort and show how this framework could be implemented in studies of professional football players. In addition, we identify the specific challenges associated with studying an elite athletic occupational group, including the healthy worker effect and other types of selection and information biases, and explore these in the context of existing studies of football-related health. The application of well-established occupational epidemiological methods to professional football players may yield new insights into the effects of playing exposure and may provide opportunities for interventions to reduce harm.

BCScreen: A gene panel to test for breast carcinogenesis in chemical safety screening.

Targeted gene lists have been used in clinical settings to specify breast tumor type, and to predict breast cancer prognosis and response to treatment. Separately, panels have been curated to predict systemic toxicity and xenoestrogen activity as a part of chemical screening strategies. However, currently available panels do not specifically target biological processes relevant to breast development and carcinogenesis. We have developed a gene panel called the Breast Carcinogen Screen (BCScreen) as a tool to identify potential breast carcinogens and characterize mechanisms of toxicity. First, we used four seminal reviews to identify 14 key characteristics of breast carcinogenesis, such as apoptosis, immunomodulation, and genotoxicity. Then, using a hybrid data and knowledge-driven framework, we systematically combined information from whole transcriptome data from genomic databases, biomedical literature, the CTD chemical-gene interaction database, and primary literature review to generate a panel of 500 genes relevant to breast carcinogenesis. We used normalized pointwise mutual information (NPMI) to rank genes that frequently co-occurred with key characteristics in biomedical literature. We found that many genes identified for BCScreen were not included in prognostic breast cancer or systemic toxicity panels. For example, more than half of BCScreen genes were not included in the Tox21 S1500+ general toxicity gene list. Of the 230 that did overlap between the two panels, representation varied across characteristics of carcinogenesis ranging from 21% for genes associated with epigenetics to 82% for genes associated with xenobiotic metabolism. Enrichment analysis of BCScreen identified pathways and processes including response to steroid hormones, cancer, cell cycle, apoptosis, DNA damage and breast cancer. The biologically-based systematic approach to gene prioritization demonstrated here provides a flexible framework for creating disease-focused gene panels to support discovery related to etiology. With validation, BCScreen may also be useful for toxicological screening relevant to breast carcinogenesis.

Novel application of normalized pointwise mutual information (NPMI) to mine biomedical literature for gene sets associated with disease: use case in breast carcinogenesis.

Advances in technology within biomedical sciences have led to an inundation of data across many fields, raising new challenges in how best to integrate and analyze these resources. For example, rapid chemical screening programs like the US Environmental Protection Agency's ToxCast and the collaborative effort, Tox21, have produced massive amounts of information on putative chemical mechanisms where assay targets are identified as genes; however, systematically linking these hypothesized mechanisms with in vivo toxicity endpoints like disease outcomes remains problematic. Herein we present a novel use of normalized pointwise mutual information (NPMI) to mine biomedical literature for gene associations with biological concepts as represented by Medical Subject Headings (MeSH terms) in PubMed. Resources that tag genes to articles were integrated, then cross-species orthologs were identified using UniRef50 clusters. MeSH term frequency was normalized to reflect the MeSH tree structure, and then the resulting GeneID-MeSH associations were ranked using NPMI. The resulting network, called Entity MeSH Co-occurrence Network (EMCON), is a scalable resource for the identification and ranking of genes for a given topic of interest. The utility of EMCON was evaluated with the use case of breast carcinogenesis. Topics relevant to breast carcinogenesis were used to query EMCON and retrieve genes important to each topic. A breast cancer gene set was compiled through expert literature review (ELR) to assess performance of the search results. We found that the results from EMCON ranked the breast cancer genes from ELR higher than randomly selected genes with a recall of 0.98. Precision of the top five genes for selected topics was calculated as 0.87. This work demonstrates that EMCON can be used to link in vitro results to possible biological outcomes, thus aiding in generation of testable hypotheses for furthering understanding of biological function and the contribution of chemical exposures to disease.

Cancer borealis stomatogastric nervous system dissection.

The stomatogastric ganglion (STG) is an excellent model for studying cellular and network interactions because it contains a relatively small number of cells (approximately 25 in C. borealis) which are well characterized. The cells in the STG exhibit a broad range of outputs and are responsible for the motor actions of the stomach. The stomach contains the gastric mill which breaks down food with three internal teeth, and the pylorus which filters the food before it reaches the midgut. The STG produces two rhythmic outputs to control the gastric mill and pylorus known as central pattern generators (CPGs). Each cell in the STG can participate in one or both of these rhythms. These CPGs allow for the study of neuromodulation, homeostasis, cellular and network variability, network development, and network recovery. The dissection of the stomatogastric nervous system (STNS) from the Jonah crab (Cancer borealis) is done in two parts; the gross and fine dissection. In the gross dissection the entire stomach is dissected from the crab. During the fine dissection the STNS is extracted from the stomach using a dissection microscope and micro-dissection tools (see figure 1). The STNS includes the STG, the oesophageal ganglion (OG), and the commissural ganglia (CoG) as well as the nerves that innervate the stomach muscles. Here, we show how to perform a complete dissection of the STNS in preparation for an electrophysiology experiment where the cells in the STG would be recorded from intracellularly and the peripheral nerves would be used for extracellular recordings. The proper technique for finding the desired nerves is shown as well as our technique of desheathing the ganglion to reveal the somata and neuropil.