Nitin Kumar Singh

Pancreatic cancer remains one of the most lethal malignancies, characterised by aggressive progression, metabolic adaptation, and resistance to therapy. Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, has emerged as a critical mechanism influencing tumour survival and therapeutic response. However, the role of ferroptosis suppressor genes (FSGs) in pancreatic cancer remains incompletely understood. In this study, FSGs were systematically retrieved from FerrDb V2 and subjected to multi-step filtering to identify a curated set of 196 protein-coding genes. Genomic alteration analysis using cBioPortal across 21 pancreatic cancer studies (n = 5189 samples) identified seven recurrently altered genes (TP53, HSF1, PARP10, ZFP36, SIRT2, ECH1, and ENPP2) with alteration frequencies ≥ 3%. Co-occurrence analysis revealed predominantly cooperative alteration patterns among these genes, suggesting functional complementarity. Survival analysis demonstrated that alterations in FSGs were significantly associated with reduced overall survival in pancreatic cancer, with several genes (ECH1, ZFP36, SIRT2, and ENPP2) showing particularly strong adverse prognostic effects. In contrast, no significant survival associations were observed in oesophageal and gastric cancers, indicating a tumour-specific dependency on ferroptosis-related mechanisms. KEGG pathway enrichment analysis of the broader FSG set revealed significant involvement in pathways related to metabolic regulation (AMPK-mTOR signalling), autophagy, hypoxia response (HIF-1 signalling), and oncogenic signalling (PI3K-Akt pathway). Integration of these findings suggests that ferroptosis suppressor genes contribute to pancreatic cancer progression by promoting metabolic adaptation and resistance to oxidative stress. In conclusion, this study identifies key ferroptosis suppressor genes with prognostic relevance in pancreatic cancer and highlights their integration within critical metabolic and stress-response pathways. The tumour-specific nature of these associations underscores the importance of biological context and supports the potential of FSGs as prognostic biomarkers and potential therapeutic targets in ferroptosis-based strategies.

Heavy metal exposure in industrial environments constitutes a significant occupational health risk and can induce systemic oxidative and proteotoxic stress. In this study, in silico toxicogenomics was integrated with population-based validation to identify and confirm candidate biomarkers of heavy metal exposure. Publicly available PBMC microarray data (GSE37567; lead-related exposure model) were analyzed to identify significantly dysregulated genes and enriched biological pathways. Subsequent pathway and protein-protein interaction (PPI) network prioritization, along with toxicogenomics cross-evidence from the Comparative Toxicogenomics Database (CTD), further refined candidate selection. For human validation, PBMC gene expression was assessed by endpoint RT-PCR in a subgroup of four occupationally exposed tannery workers (S1–S4), an additional exposed group from the affected area (n = 10), and (5 + 2) seven controls. Transcriptomic analysis identified 319 significantly dysregulated genes (FDR < 0.05), with notable enrichment of metal homeostasis and cellular stress-response pathways. Metallothionein-related and heat-shock response genes emerged as key network modules, leading to the prioritization of MT1A and HSP70 as a complementary biomarker pair for metal sequestration and proteostasis protection. In the human cohort, MT1A demonstrated consistent induction in exposed individuals (approximately 2.1–2.6-fold, with a maximum of 2.63-fold), while HSP70 expression varied among exposed samples, reflecting heterogeneous exposure and stress-response dynamics. Water analysis from the industrial zone revealed polymetallic contamination, including Pb, Cd, and Cr, supporting the biological plausibility of combined metal-stress responses. Collectively, these findings indicate that MT1A functions as a reliable indicator of metal exposure, whereas HSP70 represents variable stress responses. Together, they offer a complementary framework for assessing stress associated with heavy metal exposure.

Introduction: Brain disorders, including Parkinson’s disease, epilepsy, traumatic brain injury, and psychiatric illnesses, continue to pose substantial clinical and societal burdens. Traditional treatment approaches are often limited by poor targeting efficiency and the complexity of neural networks. Neuroengineering combines principles of engineering, materials science, and neuroscience to develop innovative tools capable of monitoring and modulating brain activity. Advances in neural interfaces, neurostimulation technologies, and bioengineered therapeutic systems are enabling more precise and minimally invasive treatment strategies, offering new possibilities for restoring neurological function and improving patient outcomes. Short summary: Brain disorders represent one of the greatest challenges in modern medicine, demanding innovative approaches that integrate neuroscience, engineering, and technology. Neuroengineering has emerged as a transformative discipline that bridges these domains, offering new strategies for diagnosis, monitoring, and therapeutic intervention. This review discusses recent advances in neuroengineering technologies, including neural interfaces, neurostimulation systems, nanotechnology-based therapeutics, and tissue engineering approaches supported by artificial intelligence for precision brain disorder management. Conclusion: Neuroengineering represents a rapidly evolving field with the potential to transform brain healthcare through innovative diagnostic and therapeutic technologies. Continued interdisciplinary collaboration and technological refinement are essential to overcome translational challenges and achieve widespread clinical implementation.