The most important socially significant disease is pulmonary tuberculosis, which is based on the development of granulomatous inflammation with the formation of fibrosis. In the elderly, it occurs with the features of pathomorphosis, due to the presence of comorbid pathology. The processes of development of coarse-fibrous connective tissue, sclerosis-fibrosis occur according to the general patterns with the involvement of the organ stroma, vessels and remodeling of the connective-tissue matrix, the study of which is impossible without the study of the relevant molecular markers. On the other hand, diagnosis and treatment are impossible without understanding the dynamics of the pathological process. Therefore, research aimed at predicting the development of pulmonary tuberculosis (especially in elderly patients) is undoubtedly relevant. The aim of the study - to create a prognostic model of the severity of the course of pulmonary tuberculosis in elderly patients. In the course of the study, the outcomes of treatment of 45 patients treated in Saint-Petersburg Research Institute of Phthisiopulmonology were analyzed. Based on the degree of activity of the tuberculous process by B.M.Ariel (1998), groups with pulmonary tuberculosis without progression and active inflammatory changes with progression were allocated. Quantitative assessment of the expression of signaling molecules (TIMP-1, NGF, CD44, CD51, CD68, CD83, Vit D) was performed using immunohistochemical morphometry and computer analysis of microscopic images. The prediction model was constructed using logistic regression. In the course of the study, the activity of monoclonal antibodies for the corresponding signaling molecules was studied: TIMP-1, NGF, CD44, CD51, CD68, CD83, Vit D, statistically significant differences in the relative area of expression of the following biological markers were established: NGF, CD68, CD83 depending on the degree of tuberculosis activity. Logistic regression was used to create a model for predicting the course of the tuberculosis process. Based on the numerical values of molecular markers (NGF, CD-68, and CD-83), a logistic regression equation was obtained that allows for the association of the severity of the disease with the levels of the markers. The sensitivity of the model was 85,7%, and the specificity was 87,5%. Thus, the obtained regression model based on the expression of molecular markers NGF, CD-68, and CD-83 allows for the prediction of the severity of pulmonary tuberculosis in elderly patients, which will enable the control of treatment in these patients.
One of the hallmarks of skin aging is the accumulation of senescent cells, which drives the process of inflammaging. The senescence-associated secretory phenotype (SASP), which characterizes senescent cells, can induce dysfunction in both neighboring skin cells and cells of distant organs. In this study, distant negative effects of senescent dermal fibroblasts on target cells (B-lymphocytes, hepatocytes, and alveolar epithelial cells) were demonstrated. The expression of Klotho, Parkin, SIRT6, VDR, Ki-67, CCN1, p16, and p65 proteins was assessed. The effects of an extract from a plant native to Russia, Hippophae rhamnoides (Sea buckthorn, S), extracts from plants of the African ecosystem Aspalathus linearis (Rooibos, R), Moringa oleifera (Moringa, M), Kigelia Africana (Kigelia, Kg), and an injectable hyaluronic acid gel (HA-gel) on the formation of the senescent phenotype in dermal fibroblasts were evaluated. The studied extracts and HA-gel protected cells from the negative processes induced by genotoxic stress. Moreover, extracts R, S, and HA-gel suppressed the adverse distant effects of damaged fibroblasts, normalizing marker expression in recipient cells, suggesting an influence on signaling pathways involved in the senescent transformation of distant cells. These results suggest considering cosmetic products based on the studied extracts and the injectable preparation as potential agents capable of delaying the aging of not only the skin but also the whole organism, which may be a component of the healthy aging concept.
BACKGROUND:Tuberculous osteitis is a chronic, granulomatous bone infection that frequently results in impaired bone healing following surgery. Despite surgical intervention and prolonged anti-tuberculous therapy, complete bone regeneration often remains unachieved, contributing to subsequent orthopedic complications. AIM:To investigate the efficacy and safety of pamidronate in promoting bone regeneration following surgical treatment of experimental animal tuberculous osteitis. METHODS:A controlled randomized basic study of rabbit femoral tuberculosis induced by Mycobacterium tuberculosis strain H37Rv included surgical removal of infected tissue and implantation of osteoinductive bone grafts with the following animal allocation to one of three groups: (1) Bisphosphonates alone; (2) Bisphosphonates combined with anti-tuberculous therapy; and (3) Anti-tuberculous therapy alone. The control group consisted of animals that received no surgical or medical treatment. Clinical evaluations, biochemical markers, micro-computed tomography imaging, and histomorphometry analyses were conducted at 3 months and 6 months postoperatively. RESULTS:Pamidronate treatment significantly reduced early implant resorption, increased osteoblastic activity, improved trabecular bone regeneration, and maintained graft integrity compared to the anti-tuberculous therapy-only group. Histologically, pamidronate led to enhanced vascular remodeling and increased bone matrix formation. Crucially, bisphosphonate therapy demonstrated safety, compatibility with anti-tuberculous medications, and did not exacerbate tuberculous inflammation. Furthermore, micro-computed tomography analysis revealed a significant increase in trabecular thickness and density in pamidronate-treated groups, underscoring the anabolic effects of bisphosphonates. Morphometric evaluation confirmed a marked reduction in osteoclast number and activity at graft interfaces. These combined radiological, histological, and biochemical data collectively demonstrate the efficacy of pamidronate as an adjunctive agent in enhancing bone repair outcomes following surgical intervention for tuberculous osteitis. CONCLUSION:A single intravenous dose of pamidronate significantly enhances bone regeneration and prevents implant resorption following surgical treatment of tuberculous osteitis. The following prospective studies are needed.
OBJECTIVE:To develop and validate classification criteria for pediatric chronic nonbacterial osteomyelitis (CNO) jointly supported by EULAR and the American College of Rheumatology (ACR). METHODS:This international initiative had 4 phases: (1) candidate items were proposed in a survey of pediatric rheumatologists, (2) criteria definition and reduction by Delphi and nominal group technique exercises, (3) criteria weighting using multicriteria decision analysis, and (4) refinement of weights and threshold score in a development cohort of 441 patients and validation in another cohort of 514 patients. RESULTS:The new EULAR/ACR classification criteria for CNO require typical radiographic or magnetic resonance imaging findings and bone pain as an obligatory entry criterion and exclusion criteria of malignancy, infection, vitamin C deficiency, and hypophosphatasia, followed by additive weighted criteria in 5 clinical (site of bone lesions, pattern of bone lesions, age at onset, coexisting conditions, fever) and 4 pathology/laboratory domains (bone biopsy findings if done, anemia, C-reactive protein level, and erythrocyte sedimentation rate). A total score ≥55 is required for classification as CNO. The new criteria had a sensitivity of 82% and specificity of 98% in the validation cohort. CONCLUSION:These new classification criteria for pediatric CNO developed with international input reflect current views about CNO, have high specificity and good sensitivity, and provide a key foundation for future CNO research.
The accurate differentiation of pulmonary lesions (nodule/mass) is crucial for selecting appropriate treatment strategies, particularly for distinguishing benign lesions such as hamartoma and tuberculoma from malignancies like non-small cell lung cancer (NSCLC). This study investigates the use of machine learning (ML) models, including Decision Tree (DT), Random Forest (RF), and CatBoost (CB), to identify key predictors of nodules type based on computed tomography (CT) imaging features. We analyzed CT data from 363 patients with confirmed diagnoses of hamartoma, tuberculoma, or NSCLC to evaluate the models’ predictive performance and identify the most significant diagnostic features. The models demonstrated high accuracy, sensitivity, and specificity, with DT and CB models highlighting changes in surrounding tissue as primary indicators, whereas RF integrated additional predictors, providing a nuanced classification framework. These findings suggest that ML models can enhance diagnostic accuracy for lung lesions and reduce unnecessary invasive procedures, although further validation in larger cohorts is recommended.
