Objectives: The objective of the study was to investigate the mRNA expression of critical gene patterns, including IL-6, CCL2, IL-10, MAPK1, MAPK8, MMP9, COL1A1, COL3A1, and TGFB1, and their associations with adverse postoperative outcomes in reconstructive and plastic surgery patients, depending on age. Methods: A total of 95 women participated in this prospective longitudinal cohort study and underwent reconstructive/plastic surgery. The mean age was 35.48 ± 6.61 years (range: 19–57). mRNA expression of IL-6, CCL2, IL-10, MAPK1, MAPK8, MMP9, COL1A1, COL3A1, and TGFB1 genes was evaluated in peripheral blood leukocytes using a PCR-based method with reverse transcription of cDNA. Results: The risk of postoperative complications significantly increased with elevated expression levels of IL-6 and COL3A1 (7.5-fold, p = 0.007), CCL2 (6.2-fold, p = 0.012), and MAPK1 (25.5-fold, p < 0.001). Increased expression of MAPK8, IL-10, and MMP9 was associated with a 13.2-fold higher risk (p < 0.001). The strongest association was observed for COL1A1 overexpression, which increased complication risk by 58.33-fold (p < 0.001). Risk stratification using the Molecular Complication Risk Index (MCRI), incorporating weighted gene contributions, identified an unfavorable molecular profile predominantly among women aged ≥ 40 years. Receiver operating characteristic analysis confirmed the model’s discriminative ability (AUC = 0.78; 95% CI 0.68–0.87), with an optimal cut-off value of MCRI ≥ 8.5 (sensitivity 76%, specificity 71%, p < 0.05). Conclusions: The transcriptional activity of IL-6, CCL2, IL-10, MAPK1, MAPK8, MMP9, COL1A1, COL3A1, and TGFB1 is associated with postoperative wound healing risk. Women aged over 40 years are at the highest risk of complications. Implementation of the MCRI model may enable early identification of high-risk patients, support targeted preventive strategies, and improve personalized surgical planning.

Postoperative wound healing complications present a major challenge in plastic and reconstructive surgery, prolonging recovery and impairing outcomes. Early risk identification is difficult due to complex interactions among clinical, laboratory, and molecular factors. This study developed and evaluated machine-learning (ML) models to predict wound healing outcomes and identify key complication predictors. Utilizing a dataset of 95 women and 76 variables (including hematological, biochemical, coagulation, and gene expression profiles), we evaluated several ML approaches, including Decision Tree, Extra Trees, Gaussian/Bernoulli Naive Bayes, Logistic Regression, and Support Vector Machine. Model performance was assessed via k-fold cross-validation, ROC analysis, and SHAP feature importance. Molecular markers (COL1A1, MMP9, MAPK1, MAPK8, IL10, and CCL2) emerged as the strongest predictors, whereas conventional clinical variables showed limited value. The models achieved high discriminative performance, with validation ROC–AUC values ranging from 0.903 to 0.913. Extra Trees and Gaussian Naive Bayes demonstrated the highest sensitivity for detecting complications (Recall = 0.820 ± 0.238 and 0.807 ± 0.246, respectively). These findings highlight the value of integrating molecular-genetic biomarkers with ML for personalized risk stratification and preventive care in reconstructive surgery.

Introduction. Over the past decades, scientists have been trying to trace and substantiate the correlation between periodontitis and pathology of the cardiovascular, respiratory, digestive systems, rheumatic diseases, metabolic disorders, etc. Periodontitis and a number of common chronic inflammatory diseases have several risk factors: psychological stress and depression, alcohol and tobacco use, obesity, diabetes, metabolic syndrome and osteoporosis, etc. The condition of periodontal tissues depends on both local and general factors. The key importance belongs to the functioning of the antioxidant defense system, which regulates free radical processes in cells and tissues, which contributes to ensuring homeostasis in the body as a whole and in the oral cavity, in particular. For a long time, metabolic disorders were considered an aggravating factor in periodontal diseases. In modern professional literature, there is a significant number of studies indicating a correlation between metabolic syndrome and generalized periodontitis. The aim of the study was to assess the effectiveness of comprehensive treatment and prevention of generalized periodontitis in patients with metabolic syndrome based on clinical examination data. Participants and methods. To investigate the prevalence and features of the clinical course of periodontal diseases on the background of metabolic disorders, 190 people with metabolic syndrome registered in the endocrinological dispensary of Chernivtsi were examined, forming the main group. The comparison group included 90 people without metabolic disorders. The study groups were standardized by age and sex. Analyzing the periodontal status of patients in the main and comparison groups revealed characteristic features of the clinical course of periodontal diseases in individuals with metabolic syndrome. These included increased gingival bleeding, a high prevalence of diffuse gingivitis, and predominance of generalized periodontitis of grades II–III with a severe clinical course. Common findings also included profuse serous-purulent or purulent exudate, frequent exacerbations, deep periodontal pocket formation, and low effectiveness of conventional treatment regimens. The prevalence of periodontal diseases in patients with metabolic syndrome was found to be 81.58 ± 2.82%. Within this cohort, generalized periodontitis was the most frequently diagnosed condition. Moreover, during long-term follow-up, a significant proportion of patients demonstrated advanced forms of periodontal destruction, with disease progression correlating with increasing age.

Background. Perioperative care and postoperative complications, such as impaired wound healing, infection, flap or graft failure, pathological scarring, remain a significant clinical challenge, negatively affecting patient outcomes and satisfaction. The aim of the study is to evaluate the IL6, CCL2, MAPK1, MAPK8, IL10, MMP9, COL1A1 and COL3A1 genes’ transcriptional activity, functional networks, and major metabolic and immunogenetic pathways involved in the wound healing in plastic and reconstructive surgery. Materials and methods. Ninety-five women participated in the prospective longitudinal cohort study and underwent reconstructive/plastic surgery. Their mean age was 35.48 ± 6.61 years (from 19 to 57). All women underwent a set of clinical, demographic, laboratory and instrumental examinations. The study was conducted in accordance with the principles of the GCP, Council of European Convention on Human Rights and Biomedicine. Transcriptional activity of IL6, CCL2, MAPK1, MAPK8, IL10, MMP9, COL1A1 and COL3A1 genes in the peripheral blood was validated by pathway-specific PCR array. Functional linkage of the genes and protein-protein interaction were constructed using GeneMANIA software and the STRING Interaction Network program. Results. Two hundred and sixty-seven gene-gene interactions of the IL6, CCL2, MAPK1, MAPK8, IL10, MMP9, COL1A1, COL3A1 genes were established with the 20 most involved genes, which realize their activity mainly through the following functional linkage: co-expression (50.06 %) and co-localization (31.81 %) dominate, significantly less — common protein domains (8.63 %) and predicted (5.30 %) and physical interactions (2.49 %), additional signaling pathways (1.71 %). The central place in the gene-gene interaction network belongs to IL6, which acts as a key mediator of the pro-inflammatory response and connects immune (CCL2, IL10), signaling (MAPK1, MAPK8), and matrix (MMP9, COL1A1, COL3A1) components. IL10 gene shows the strongest expression (almost 3 times) in interaction with MAPK8 gene (М: 2.81 (р = 0.003)), the latter activates inflammation, remodeling, and with excess expression — fibrosis. Conclusions. The IL6, CCL2, MAPK1, MAPK8, IL10, MMP9, COL1A1 and COL3A1 genes’ transcriptional activity influence major metabolic and immunogenetic pathways involved in the wound healing in plastic and reconstructive surgery.

Summary. Periodontal diseases represent a significant issue in modern dentistry, with both medical and social implications. This is due to their high prevalence, the intensity of the disease process, the subsequent formation of chronic odontogenic foci of infection, tooth loss at a young age, and, consequently, a reduced quality of life. Aim: assess the condition of periodontal tissues in young individuals with chronic catarrhal gingivitis, based on the values of the papillary-marginal-alveolar (PMA) index. Material and methods. Two study groups were formed: Group I included 58 patients with chronic gingivitis whose PMA index was less than 30%; Group II consisted of 38 individuals with an inflammatory periodontal process and a PMA index greater than 30%. The following indices were determined: the papillary-marginal-alveolar (PMA) index, the Papillary Bleeding Index (PBI), and the Green-Vermillion Oral Hygiene Index. Results. In Group I, the PMA index was 20.12 ± 2.20%, indicating a mild degree of gingival inflammation. In Group II, the index reached the upper limit of a moderate degree of gingivitis (49.04 ± 4.16%), which was 2.4 times higher than in Group I (p < 0.01). The mean PBI index in Group I was 0.35 ± 0.04, reflecting a low level of gingival papilla bleeding. In Group II, this index was 2.7 times higher, indicating more pronounced gingival bleeding (0.94 ± 0.07, p < 0.01). The Green-Vermillion index in Group I fell within the range indicating satisfactory oral hygiene (1.54 ± 0.16), while in Group II, an unsatisfactory level of oral hygiene was observed (2.47 ± 0.22, p < 0.01). Conclusions. A direct relationship was observed between the papillary-marginal-alveolar index and the severity of periodontal disease in young individuals. Our findings also confirmed existing scientific data on the correlation between oral hygiene levels and the condition of periodontal tissues. An increase in gingival bleeding was observed in parallel with elevated hygienic and papillary-marginal-alveolar index values.

Acute otitis media (AOM) is the 2^nd most frequent ENT diagnosis in early childhood. The aim of the study was to evaluate the clinical, anamnestic and micro-social predictors of AOM in children and its association with heat-shock protein gene (HSP70-2, rs1061581) polymorphism. A total of 95 children with AOM (7-18 years old) participated in the study. HSP70-2 (rs1061581) gene genotyping was performed by qPCR method. Risk factors were analyzed. The A-allele of the HSP70-2 gene is a predictor of a more severe AOM course in children and increases its risk and purulent ear discharge almost 2.5 times (p < 0.05), otorrhea - twofold. In preadolescence chronic hypertrophic or vasomotor rhinitis, adenoid vegetations of II-III degrees and non-obstructive diseases of the lower respiratory tract cause an AOM increase risk 3-6 times (p < 0.05). In adolescence, the probability of AOM increases with chronic persistence of hemolytic streptococcus in the oropharynx and broncho-obstructive diseases almost 10 times (p < 0.05). Early daycare attendance before the age of 3 elevates AOM likelihood more than 3 times (p = 0.001). Clinical and social predictors affect the severity of AOM in children depending on age. A-allele (rs1061581) associates with a more severe AOM course in children.