Recent studies hypothesized that vitamin D supplementation and subsequent higher 25(OH)D serum levels could protect against respiratory infections in children. This cross-sectional study, conducted from May 2022 to December 2023 in Timisoara, Romania, aimed to evaluate the potential influence of vitamin D supplementation on the incidence of respiratory infections among preschool-age children. This study examined 215 children over 18 months who were split into a group of patients with recurrent respiratory infections (n = 141) and another group of patients with only one respiratory tract infection in the past 12 months (n = 74). Patients were evaluated based on their serum vitamin D levels 25(OH)D, demographic characteristics, and health outcomes. The study identified that preschool-age children with recurrent infections had significantly lower mean vitamin D concentrations (24.5 ng/mL) compared to the control group (29.7 ng/mL, p < 0.001). Additionally, a higher proportion of vitamin D deficiency was observed among children with recurrent infections in the past 12 months. Notably, vitamin D supplementation above 600 IU/week significantly reduced the likelihood of respiratory infections, evidenced by an odds ratio of 0.523 (p < 0.001), indicating that preschool-age children receiving a dose of vitamin D higher than 600 IU/week were about half as likely to experience respiratory infections compared to those who did not. Furthermore, no significant associations were found between sun exposure, daily sunscreen use, and the incidence of respiratory infections. Conclusively, this study underscores the potential role of vitamin D in helping the immune system against respiratory infections in preschool-age children. The observed protective effect of vitamin D supplementation suggests a potential public health strategy to mitigate the incidence of respiratory infections in preschool children on top of the already known benefits.

The coronavirus disease 2019 (COVID-19) pandemic has necessitated the identification of biomarkers that can predict disease severity, particularly in vulnerable populations such as individuals with diabetes. This study aims to evaluate the predictive value of inflammatory and liver function markers, specifically derived Neutrophil to Lymphocyte Ratio (dNLR), aspartate aminotransferase (AST)-to-lymphocyte ratio (ALRI), AST to Platelet Ratio Index (APRI), and Systemic Inflammation Index (SII), in COVID-19 patients with and without diabetes. This cross-sectional study included 336 participants, comprising 168 patients with diabetes matched with 168 without, based on gender, body mass index (BMI), and COVID-19 severity at hospitalization. The study was conducted at Victor Babes Hospital for Infectious Diseases and Pulmonology from January 2021 to December 2023. All participants had a confirmed SARS-CoV-2 infection and met the inclusion criteria of being 18 years or older with type 1 or type 2 diabetes as per American Diabetes Association guidelines. At 3 days post symptom onset, significant differences in inflammatory and liver function markers were observed between the two groups. The dNLR, ALRI, APRI, and SII were notably higher in diabetic patients. At a dNLR cutoff of 2.685, the sensitivity and specificity were 70.312% and 65.978%, respectively, with an AUC of 0.624 (p < 0.001). The ALRI showed a cutoff of 0.812, with a sensitivity of 76.429% and specificity of 69.541% (AUC 0.752, p < 0.001). These markers demonstrated statistically significant hazard ratios at both 3 and 7 days, indicating their predictive relevance for severe COVID-19 outcomes. For instance, at 7 days, SII demonstrated a hazard ratio of 2.62 (CI: 1.29–5.04, p < 0.001), highlighting its strong prognostic capability. The study successfully identified significant differences in inflammatory and liver function markers between COVID-19 patients with and without diabetes, with these markers showing good predictive value for disease severity. The results underscore the potential of these biomarkers, particularly ALRI and SII, as valuable tools in managing COVID-19, aiding in the timely identification of patients at increased risk of severe outcomes.

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.

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.

Background. Essential hypertension (EH) is a complex, multifactorial and polygenic disease. Despite effective measures for control and modification of traditional risk factors, a significant amount of risk remains. The aim of the study was to evaluate changes in clinical parameters and to analyze the relationship of cholecalciferol, parathyroid hormone with anthropometric, metabolic parameters in patients with EH. Materials and methods. One hundred subjects with EH and target organ damage (stage 2), moderate, high, very high cardiovascular risk were enrolled in case-control study. Control group consisted of 60 healthy subjects matched for sex and age. Pearson’s test was used to determine the relationship between parameters in case of categorical variables; analysis of variance (ANOVA) when one of the variables is categorical and the other is numerical (interval); non-parametric Kruskal-Wallis test in case of abnormal array distribution. Results. Development and course of EH is characterized by clinical, hemodynamic, metabolic abnormalities that are nonlinearly exacerbated with the severity of hypertension. Correlation analysis showed a direct relationship between body weight and waist-to-hip ratio (r = 0.76–0.88; р < 0.001); systolic blood pressure is moderately directly correlated with waist circumference (WC) (r = 0.38; р < 0.05); total cholesterol is strongly associated with low-density lipoprotein cholesterol (r = 0.93; р < 0.001), high-density lipoprotein cholesterol (HDL-C) is inversely associated with WC (r = –0.40; р < 0.05) and triacylglycerol levels (r = –0.41; р < 0.001), and cholecalciferol concentration is negatively marginally associated with body mass index, waist-to-hip ratio (r = –0.41/–0.38; р < 0.05). ANOVA confirmed that plasma cholecalciferol was associated with body weight (F = 6.48; р = 0.013), height (F = 4.33; р = 0.04), WC (χ2 = 15.93; р < 0.001), blood glucose (χ2 = 10.66; р = 0.001) and HDL-С (F = 6.53; р = 0.012). Reliable relationship between parathyroid hormone and waist-to-hip ratio was found (χ2 = 6.86; р = 0.032). Conclusions. In EH patients, plasma cholecalciferol significantly correlates with body weight, height, WC, glucose level, HDL-С. Parathyroid hormone has a significant and direct relationship with waist-to-hip ratio.

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.