The development of tissue fibrosis is a complex process involving the interaction of multiple cell types, which makes the search for antifibrotic agents rather challenging. So far, myofibroblasts have been considered the key cell type that mediated the development of fibrosis and thus was the main target for therapy. However, current strategies aimed at inhibiting myofibroblast function or eliminating them fail to demonstrate sufficient effectiveness in clinical practice. Therefore, today, there is an unmet need to search for more reliable cellular targets to contribute to fibrosis resolution or the inhibition of its progression. Activated stromal cells, capable of active proliferation and invasive growth into healthy tissue, appear to be such a target population due to their more accessible localization in the tissue and their high susceptibility to various regulatory signals. This subpopulation is marked by fibroblast activation protein alpha (FAPα). For a long time, FAPα was considered exclusively a marker of cancer-associated fibroblasts. However, accumulating data are emerging on the diverse functions of FAPα, which suggests that this protein is not only a marker but also plays an important role in fibrosis development and progression. This review aims to summarize the current data on the expression, regulation, and function of FAPα regarding fibrosis development and identify promising advances in the area.

Evaluation of the influence of primary and secondary aging on the manifestation of molecular and cellular hallmarks of aging is a challenging and currently unresolved issue. Our study represents the first demonstration of the distinct role of primary aging and chronic inflammation/physical inactivity – the most important drivers of secondary aging, in the regulation of transcriptomic and proteomic profiles in human skeletal muscle. To achieve this purpose, young healthy people ( n = 15), young ( n = 8) and older ( n = 37) patients with knee/hip osteoarthritis, a model to study the effect of long‐term inactivity and chronic inflammation on the vastus lateralis muscle, were included in the study. It was revealed that widespread and substantial age‐related changes in gene expression in older patients relative to young healthy people (~4000 genes regulating mitochondrial function, proteostasis, cell membrane, secretory and immune response) were related to the long‐term physical inactivity and chronic inflammation rather than primary aging. Primary aging contributed mainly to the regulation of genes (~200) encoding nuclear proteins (regulators of DNA repair, RNA processing, and transcription), mitochondrial proteins (genes encoding respiratory enzymes, mitochondrial complex assembly factors, regulators of cristae formation and mitochondrial reactive oxygen species production), as well as regulators of proteostasis. It was found that proteins associated with aging were regulated mainly at the post‐transcriptional level. The set of putative primary aging genes and their potential transcriptional regulators can be used as a resource for further targeted studies investigating the role of individual genes and related transcription factors in the emergence of a senescent cell phenotype.

The aim of the study was to investigate the relationship between established clinical systemic biomarkers of ageing and the development of age-associated diseases and senescent cell biomarkers at tissue and cellular levels. Thirty-eight patients (mean age 70 ± 4.9 years) who were assessed for traditional risk factors for cardiovascular diseases were included. From all patients we obtained biomaterials (peripheral blood, skin, subcutaneous fatty tissue) and isolated different cell types (peripheral blood mononuclear cells (PBMC), fibroblasts (FB) and mesenchymal stem/stromal cells (MSC)). Isolated cells were analyzed using several senescent cells biomarkers such as telomere length and telomerase activity, proliferation rate, cell cycle inhibitor expression (p16 and p21), b-galactosidase activity, gH2AX expression. CD34+ cell content in peripheral blood was determined by flow cytometry. Systemic senescent cell-associated factors (insulin-like growth factor 1 (IGF-1), fibroblast growth factor 21 (FGF-21), osteoprogerin, ferritin, soluble vascular cell adhesion molecule (VCAM-1), intercellular adhesion molecule 1 (ICAM-1)) in peripheral blood as well as senescence-associated secretory phenotype (SASP) components in MSC and FB secretome were evaluated by ELISA. Skin and adipose tissue biopsy samples were analyzed histologically to assess senescent cell markers. A strong significant association of tissue p16 expression with age (r = 0.600, p < 0.001), pulse wave velocity (PWV) (r = 0.394, p = 0.015), vascular cell adhesion molecule (VCAM-1) content (r = 0.312, p = 0.006) in the systemic blood stream and p16 mRNA level in the blood mononuclear cells (MNCs) (r = 0.380, p = 0.046) were confirmed by correlation analysis. Statistically significant correlations were found with indicators of FBs and MSCs proliferation in culture and acquisition of SASP by the cells. Thus, p16 expression in tissues correlated significantly with interleukin-6 (IL-6) (r = 0.485, p < 0.05) and monocyte chemoattractant protein type 1 (MCP-1) (r = 0.372, p < 0.05) secretion by isolated cells. The results of regression analysis confirmed that, regardless of age, the expression of p16 was associated with the proliferation of isolated cells and IL-6 within SASP. Based on these findings, two models have been proposed to predict the level of p16 expression in tissues from the levels of other markers of senescent cell accumulation determined by non-invasive methods and available in clinical practice.

Microscopy is an essential method in modern biology, and brightfield microscopy methods (phase contrast, differential interference contrast, etc.) are being widely used and actively developed since they don’t require sample fixation and staining. But they produce low contrast images, where cells have similar intensity to the background. In this work we developed and tested a set of deep learning object detection YOLO models that detect cell nuclei in phase contrast images, which allows cell count and tracking without staining. We created a large dataset consisting of more than 100,000 640×640 pixels images with more than 3 million nuclei of 4 different cell cultures (CHO, HEK293, iPSCs, and MSCs). Using images from various microscopes and cameras, as well as full-scale augmentations, we developed a set of highly generalized models that can detect nuclei in images across different cell types and imaging conditions, including different microscopes and contrast methods. Combined with sliced inference methods, these algorithms can be applied to images of any size, allowing studies of large quantities of cells. Moreover, we developed a training-free calibration and testing algorithm based on confidence threshold optimization. It allows for fine-tuning of models for specific cell types and/or imaging options and evaluating the accuracy of the calibrated model. This provides a highly controllable and reliable method for studying cell proliferation rate, single cell tracking and other scenarios. Additionally, we developed a NuclePhaser plugin for Napari ( https://github.com/nikvo1/napari-nuclephaser ), which allows users to calibrate, test and apply our models in code-free manner. Given that the YOLO models are fast and can run at sufficient speeds even on CPUs, this makes our work highly accessible to a wide range of researchers.

Adipose tissue renewal requires precise coordination of stem/progenitor cell proliferation, preadipocyte commitment, and terminal adipocyte differentiation. T-cadherin (CDH13), an atypical GPI-anchored cadherin, is expressed in adipose tissue and functions as a receptor for high-molecular-weight (HMW) adiponectin—a key adipokine produced by adipose tissue and involved in metabolic regulation. While T-cadherin is implicated in cardiovascular and metabolic homeostasis, its role in adipogenesis still remains poorly understood. In this study, we used the 3T3-L1 preadipocyte model to investigate the function of T-cadherin in adipocyte differentiation. We analyzed T-cadherin expression dynamics during differentiation and assessed how T-cadherin overexpression or knockdown affects lipid accumulation, expression of adipogenic markers, and key signaling pathways including ERK, PI3K–AKT, AMPK, and mTOR. Our findings demonstrate that T-cadherin acts as a negative regulator of adipogenesis. T-cadherin overexpression ensured a proliferative, undifferentiated cell state, delaying early adipogenic differentiation and suppressing both lipid droplet accumulation and the expression of adipogenic markers. In contrast, T-cadherin downregulation accelerated differentiation, enhanced lipid accumulation, and increased insulin responsiveness, as indicated by PI3K–AKT pathway activation at specific stages of adipogenesis. These results position T-cadherin as a key modulator of adipose tissue plasticity, regulating the balance between progenitor expansion and terminal differentiation, with potential relevance to obesity and metabolic disease.