Background: Gastric cancer is a leading cause of cancer-related mortality worldwide, with approximately one million new cases diagnosed annually. While Helicobacter pylori infection remains a primary etiological factor, mounting evidence implicates obesity and lipid metabolic dysregulation, particularly in hypercholesterolemia, as emerging drivers of gastric tumorigenesis. This study investigates the molecular intersections between gastric cancer, obesity, and hypercholesterolemia through a comprehensive multi-omics and systems biology approach. Methods: We conducted integrative transcriptomic analysis of gastric adenocarcinoma using The Cancer Genome Atlas (TCGA) RNA-sequencing dataset (n = 623, 8863 genes), matched with standardized clinical metadata (n = 413). Differential gene expression between survival groups was assessed using Welch’s t-test with Benjamini–Hochberg correction (FDR < 0.05, |log₂FC| ≥ 1). High-confidence gene sets for obesity (n = 128) and hypercholesterolemia (n = 97) were curated from the OMIM, STRING (confidence ≥ 0.7), and KEGG databases using hierarchical evidence-based prioritization. Overlapping gene signatures were identified, followed by pathway enrichment via Enrichr (KEGG 2021 Human) and protein–protein interaction (PPI) analysis using STRING v11.5 and Cytoscape v3.9.0. CD36’s prognostic value was evaluated via Kaplan–Meier and log-rank testing alongside clinicopathological correlations. Results: We identified 36 genes shared between obesity and gastric cancer, and 31 genes shared between hypercholesterolemia and gastric cancer. CD36 emerged as the only gene intersecting all three conditions, marking it as a unique molecular integrator. Enrichment analyses implicated dysregulated fatty acid uptake, adipocytokine signaling, cholesterol metabolism, and NF-κB-mediated inflammation as key pathways. Elevated CD36 expression was significantly correlated with higher tumor stage (p = 0.016), reduced overall survival (p = 0.001), and race-specific expression differences (p = 0.007). No sex-based differences in CD36 expression or survival were observed. Conclusions: CD36 is a central metabolic–oncogenic node linking obesity, hypercholesterolemia, and gastric cancer. It functions as both a mechanistic driver of tumor progression and a clinically actionable biomarker, particularly in metabolically comorbid patients. These findings provide a rationale for targeting CD36-driven pathways as part of a precision oncology strategy and highlight the need to incorporate metabolic profiling into gastric cancer risk assessment and treatment paradigms.

Electrophysiological implants enable exploration of the relationship between neuronal activity and behavior. These technologies evolve rapidly, with multiple iterations of recording systems developed and utilized. Chronic implants must address a litany of complications, including retention of high signal-to-noise ratio in probes and the ability to withstand excess force over the experimental period. To overcome these issues, we designed a chronic implant for rats. Our comprehensive protocol optimizes the entire implant process, from assembling and testing the probes (Neuropixels) to implantation. In addition to addressing the complications previously mentioned, our implant can vertically adjust probes with micron precision and is constructed using modular components, allowing it to be easily modified for various research contexts, electrophysiological recording systems, headstages, and probe types.