Highlights d Multi-omics analysis and techniques with NASA's GeneLab platform d The largest cohort of astronaut data to date utilized for analysis d Mitochondrial dysregulation driving spaceflight health risks d NASA Twin Study data validates mitochondrial dysfunction during space missions

Mounting evidence suggests that inflammation is important in epileptogenesis. Particularly Interesting New Cysteine Histidine-rich (PINCH) protein is a highly conserved, LIM-domain protein known to interact with hyperphosphorylated Tau. We assessed PINCH expression in resected epileptogenic human hippocampi and further explored the relationships among PINCH, hpTau and associated kinases. Resected hippocampal tissue from 7 patients with mesial temporal lobe epilepsy (MTLE) was assessed by Western analyses to measure levels of PINCH and hyperphosphorylated Tau, as well as changes in phosphorylation levels of associated kinases AKT and GSK3β in comparison to normal control tissue. Immunolabeling was also conducted to evaluate PINCH and hpTau patterns of expression, co-localization and cell-type specific expression. Hippocampal PINCH was increased by 2.6 fold in the epilepsy cases over controls and hpTau was increased 10 fold over control. Decreased phospho-AKT and phospho-GSK3β in epilepsy tissue suggested involvement of this pathway in MTLE. PINCH and hpTau co-localized in some neurons in MTLE tissue. While PINCH was expressed by both neurons and astrocytes in MTLE tissue, hpTau was extracellular or associated with neurons. PINCH was absent from the serum of control subjects but readily detectable from the serum of patients with chronic epilepsy. Our study describes the expression of PINCH and points to AKT/GSK3β signaling dysregulation as a possible pathway in hpTau formation in MTLE. In view of the interactions between hpTau and PINCH, understanding the role of PINCH in MTLE may provide increased understanding of mechanisms leading to inflammation and MTLE epileptogenesis and a potential biomarker for drug-resistant epilepsy.

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1 Supplementary methods 1.1 scedar package development Scedar is built upon various high-performance scientific computing and visualization packages.Scedar is also extensively benchmarked and tested by unit testing, with comprehensive coverage on statements and branches.Scedar uses the following packages:• numpy (Travis E. Oliphant, 2006) for matrix representation and operations. • scipy (Virtanen et al., 2018) for fast Gaussian kernel density estimation, hierarchical clustering and sparse matrix. * yuanchao.zhang@rutgers.edu †

The use of biomedical knowledge graphs (BMKG) for knowledge representation and data integration has increased drastically in the past several years due to the size, diversity, and complexity of biomedical datasets and databases. Data extraction from a single dataset or database is usually not particularly challenging. However, if a scientific question must rely on analysis across multiple databases or datasets, it can often take many hours to correctly and reproducibly extract and integrate data towards effective analysis. To overcome this issue, we created Petagraph, a large-scale BMKG that integrates biomolecular data into a schema incorporating the Unified Medical Language System (UMLS). Petagraph is instantiated on the Neo4j graph platform, and to date, has fifteen integrated biomolecular datasets. The majority of the data consists of entities or relationships related to genes, animal models, human phenotypes, drugs, and chemicals. Quantitative data sets containing values from gene expression analyses, chromatin organization, and genetic analyses have also been included. By incorporating models of biomolecular data types, the datasets can be traversed with hundreds of ontologies and controlled vocabularies native to the UMLS, effectively bringing the data to the ontologies. Petagraph allows users to analyze relationships between complex multi-omics data quickly and efficiently.