[Novel integrative multi-omics strategies of human's biological age computation.]

Multi-omics methods for analysing postgenomic data have become firmly established in the tools of molecular gerontology only in recent years, since previously there were no comprehensive integrative approaches adequate to the task of calculating biological age. This paper provides an overview of existing papers on multi-omics integrative approaches in calculating the biological age of a human. An analysis of the most common options for integrating methylomic, transcriptomic, proteomic, microbiomic and metabolomic datasets was carried out. We defined (1) concatenation (machine learning), in which models are developed using a concatenated data matrix, formed by combining multiple omics data sets; (2) fusion model approaches that create multiple intermediate submodels for different omics data to then build a final integrated model from the various intermediate submodels; and (3) transformation methods (via artificial intelligence) that first transform each of the single omics data sets into core plots or matrices, and then combine them all into one graph before building an integral complex model. It is unlikely that multi-omics approaches will find application in anti-aging personalized medicine, but they will undoubtedly deepen and expand the understanding of the fundamental processes standing behind the phenomenon of the biological aging clocks.

[Artificial intelligence in pathological anatomy]. / Iskusstvennyi intellekt v patologicheskoi anatomii.

The review presents key concepts and global developments in the field of artificial intelligence used in pathological anatomy. The work examines two types of artificial intelligence (AI): weak and strong ones. A review of experimental algorithms using both deep machine learning and computer vision technologies to work with WSI images of preparations, diagnose and make a prognosis for various malignant neoplasms is carried out. It has been established that weak artificial intelligence at this stage of development of computer (digital) pathological anatomy shows significantly better results in speeding up and refining diagnostic procedures than strong artificial intelligence having signs of general intelligence. The article also discusses three options for the further development of AI assistants for pathologists based on the technologies of large language models (strong AI) ChatGPT (PathAsst), Flan-PaLM2 and LIMA. As a result of the analysis of the literature, key problems in the field were identified: the equipment of pathology institutions, the lack of experts in training neural networks, the lack of strict criteria for the clinical viability of AI diagnostic technologies.

[Drosophila melanogaster Lifespan Is Regulated by nejire Gene Expression in Peripheral Tissues and Nervous System].

Histone acetyltransferases of the CBP/p300 family are involved in transcriptional regulation and many biological processes (cell proliferation and differentiation, development, and regulation of the stress response and metabolism). Overexpression and knockdown of the nejire (nej) gene (codes for an ortholog of human CBP/p300 proteins) in various tissues (the fat body, intestine, and nervous system) and at various stages of the life cycle (throughout all developmental stages or in adulthood only) were tested for effect on lifespan in the fruit fly Drosophila melanogaster. The activation of nej exerted a positive or a negative effect on the lifespan, depending on the induction mode and the sex. A 6-15% greater lifespan was observed in females with conditional overexpression of nej in the intestine and constitutive overexpression of nej in the nervous system. A decrease (to 44%) or lack of significant changes in lifespan was detected in all other cases observed. In addition, stress response genes (Sod1, Gadd45, Hsp27, Hsp68, and Hif1) were regulated by nej activation. nej knockdown caused a pronounced negative effect on the D. melanogaster lifespan in most variants of the experiment.

[Key Molecular Mechanisms of Aging, Biomarkers, and Potential Interventions].

The mechanisms of aging are described at the molecular, cell, tissue, and systemic levels. Primary age-dependent molecular lesions activate the cell stress response to compensate for the resulting defects, but the mechanisms that recover and maintain homeostasis are gradually deteriorated. When the amount of errors reaches a critical threshold in regulatory networks, a phase transition from health to disease occurs at the systemic level. The review considers the approaches to quantitative assessment of the aging process (biomarkers of aging) and promising interventions to slow down the aging process and to reduce the risk of age-dependent diseases.