Application of Artificial Intelligence in Tissue Engineering

Tissue engineering, a crucial approach in medical research and clinical applications, aims to regenerate damaged organs. By combining stem cells, biochemical factors, and biomaterials, it encounters challenges in designing complex 3D structures. Artificial intelligence (AI) enhances tissue engineering through computational modeling, biomaterial design, cell culture optimization, and personalized medicine. This review explores AI applications in organ tissue engineering (bone, heart, nerve, skin, cartilage), employing various machine learning (ML) algorithms for data analysis, prediction, and optimization. Each section discusses common ML algorithms and specific applications, emphasizing the potential and challenges in advancing regenerative therapies.

Effect of maternal undernutrition on vascular expression of micro and messenger RNA in newborn and aging offspring

The aim of this study was to test the hypothesis that maternal undernutrition (MUN) alters offspring vascular expression of micro-RNAs (miRNAs), which, in turn, could regulate the expression of a host of genes involved with angiogenesis and extracellular matrix remodeling. The expression of miRNA and mRNA in the same aortic specimens in 1-day-old (P1) and 12-mo-old offspring aortas of dams, which had 50% food restriction from gestation day 10 to term, was determined by specific rat miRNA and DNA arrays. MUN significantly downregulated the expression of miRNAs 29c, 183, and 422b in the P1 group and 200a, 129, 215, and 200b in the 12-mo group, and upregulated the expression of miRNA 189 in the P1 group and 337 in the 12-mo group. The predicted target genes of the miRNAs altered in the two age groups fell into the categories of: 1) structural genes, such as collagen, elastin, and enzymes involved in ECM remodeling; and 2) angiogenic factors. MUN primarily altered the expression of mRNAs in the functional category of cell cycle/mitosis in the P1 group and anatomic structure and apoptosis in the 12-mo age group. Several of the predicted target genes of miRNAs altered in response to MUN were identified by the DNA array including integrin-beta(1) in the P1 aortas and stearoyl-CoA desaturase-1 in the 12-mo age groups. These results are consistent with the hypothesis that MUN modulation of offspring gene expression may be mediated in part by a miRNA mechanism.