Neha Rawat Rawat

This current study focuses on the impact of Artificial Intelligence (AI) on the rapid identification of new molecules to suppress aging processes, which increases the proportion of healthspan relative to lifespan. The research approach taken involved a quantitative method, where artificial intelligence-based machine learning, bioinformatics, and statistical analysis were used alongside computational molecular docking. Biochemical information from databases such as PubChem, DrugBank, and ChEMBL was leveraged to screen and analyze molecular data. It was observed that AI-assisted predictive models, especially Deep Learning Neural Networks, offered highly accurate predictions concerning the biological activity of anti-aging compounds. The selected molecules showed considerable decreases in oxidative stress, inflammation, and cellular senescence markers, coupled with improved mitochondrial function and cell repair. Moreover, quantitative results showed that the use of AI for predicting the efficacy of anti-aging agents led to more significant healthspan enhancements than lifespan increases.

The modern repair of hernia disease has undergone tremendous transitions in the past where open surgeries are still used to repair the hernia, to sophisticated minimally invasive and robotic assisted techniques through animal-based research being very essential in the understanding of the structure of the anatomy, biomaterials functions and the healing process. This review is a systematic analysis of the existing literature performed on animal models like rodents, rabbits, pigs, and canines to indicate the efficacy of various types of mesh, surgical methods and new technologies in enhancing clinical outcomes and recurrence. The results suggest that, biologic and composite mesh stimulates tissue integration, neovascularisation and organized collagen deposition and less inflammatory response and adhesion formation in comparison with synthetic mesh. As well, less invasive and robotic-assisted surgery methods enhance surgical accuracy, less tissue trauma, and outcome reproducibility. Nevertheless, interspecies variability, absence of standardized models, and inadequate long-term data are also limitations to direct translational applicability. The review notes the significance of the incorporation of advanced technologies including bioengineered meshes, artificial intelligence, and 3D bio printing and the necessity of standardized and long-term and interdisciplinary research to enhance the safety and efficacy of hernia repair approaches