Obesity is characterized by a chronic inflammation driven primarily by sustained activation of the canonical NF-κB signaling pathway. This persistent inflammatory state originates in hypertrophic adipose tissue and progressively affects multiple organ systems, contributing to systemic metabolic dysfunction. This review explores the molecular architecture and regulatory components of the canonical NF-κB pathway and outline how metabolic stressors, cytokines, chemokines, adhesion molecules, and dysregulated microRNAs influence its activity in obesity. Clinically relevant NF-κB linked biomarkers are characterized, those that reflect the degree of inflammation and may support risk stratification in metabolic disease. Finally, we discuss emerging therapeutic strategies, including small-molecule inhibitors, monoclonal antibodies, and miRNA-based approaches designed to modulate NF-κB activity while preserving its essential physiological roles. Together, these insights emphasize the central involvement of NF-κB in obesity-associated inflammation and highlight potential targets for selective intervention.

Background: Chronic venous disease (CVD) represents a significant health challenge, particularly in obese individuals. This study focuses on the interplay between inflammation, obesity, and CVD, by analyzing the role of inflammatory markers in the disease progression. Methods: Clinical and paraclinical data of 619 patients hospitalized and treated in the Phlebology Department (1stSurgical Department, “Pius Brînzeu” Emergency County Hospital Timișoara, Romania) between 2018 and 2024 were analyzed. Results: The statistical analysis revealed that age, C-reactive protein (CRP), fibrinogen, and absolute neutrophil count (ANC) were key predictors of CVD progression. Specifically, elevated CRP and fibrinogen levels correlated strongly with increased CVD severity, particularly in patients with higher body-mass index (BMI). BMI, while not an independent predictor, contributed indirectly to the disease severity through its association with these inflammatory markers. The logistic regression model incorporating age, BMI, CRP, fibrinogen, and ANC demonstrated a high predictive accuracy, with an area under the curve (AUC) of 0.902, highlighting the models reliability in stratifying patients at risk for severe CVD. Conclusions: This predictive model not only aids in identifying high-risk patients but also reinforces inflammation as a critical therapeutic target in CVD management.

Background/Objectives: Artificial intelligence (AI) is rapidly transforming the landscape of modern medicine, offering advanced tools for diagnosing complex conditions. In the realm of venous pathologies such as chronic venous disease (CVD), venous reflux, and deep venous thrombosis (DVT), AI has shown tremendous potential to improve diagnostic accuracy, streamline workflows, and enhance clinical decision-making. This study aims to evaluate the efficacy and feasibility of AI algorithms in diagnosing venous diseases and explore their potential impact on clinical practice. Methods: This paper provides a comprehensive review of key studies documenting the use of AI in venous pathology diagnostics, with different electronic databases being searched, including MEDLINE/Pub Med, Web of Science, Scopus, Embase, ResearchGate, and Google Scholar. Results: Out of 52 reports assessed for eligibility, 43 were excluded according to the preset criteria; therefore, findings from nine major studies involving more than 1000 patients were analyzed. The evaluation shows that AI utilization in the diagnosis of venous pathologies has demonstrated significant improvements. Notably, AI algorithms have achieved an accuracy exceeding 90%, significantly reducing inter-observer variability and ensuring consistent interpretation of ultrasonographic images across different clinicians and settings. Additionally, AI has accelerated diagnostic workflows, decreasing the time required for image analysis by more than 50%. Furthermore, AI has proven capable of detecting subtle abnormalities, such as minor venous reflux or early-stage thrombi, which may be overlooked during manual evaluations. Conclusions: Artificial intelligence represents a transformative innovation in the diagnosis and management of venous diseases. By enhancing diagnostic accuracy, streamlining workflows, and enabling personalized care, AI has the potential to address current challenges in venous diagnostics and improve patient outcomes. The future of AI in venous diagnostics is promising, and several areas of development were noted, including AI algorithms embedding directly into ultrasound devices to provide instantaneous diagnostic insights during patient evaluations; combining AI-processed Doppler data with other imaging modalities, such as computed tomography or MRI, for comprehensive assessments; AI usage in order to predict disease progression and tailor treatment strategies based on individual patient profiles; and constructing large-scale, multicenter datasets to improve the robustness and generalizability of AI algorithms.

Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) play an important role in the pathophysiology of chronic glaucoma, as they are involved in extracellular matrix (ECM) remodeling in the trabecular meshwork (TM), affecting its ability to efficiently regulate intraocular pressure (IOP). Ensuring the balance between MMPs and TIMPs helps to maintain homeostasis in ocular tissues, which is essential to avoid glaucomatous lesions. Elevated levels of MMPs and increased degradation of the ECM, ultimately affecting aqueous humor outflow and increasing IOP, characterize glaucoma. In the current literature review, the impact and interactions of MMPs and TIMPs in chronic glaucoma have been emphasized, with multiple but still unelucidated roles in the mentioned pathology including their clinical implications, future research directions, and therapeutic approaches. Research to date indicates that the expression of TIMPs is altered in patients with chronic glaucoma, suggesting a compensatory response to increased MMPs activity. Certain drugs can influence the expression levels of MMPs and TIMPs, therefore therapeutic strategies can be developed to restore the balance between tissue enzymes and their inhibitors. Therefore, understanding the relationship between MMPs and TIMPs is a key factor in the pathogenesis of chronic glaucoma. Understanding the interplay between the two provides interesting insights into ECM remodeling in ocular tissues, highlighting the potential of targeted therapies to restore the balance between proteolytic enzymes and their inhibitors.

Background and Objectives: The prevalence of thyroid nodules and type 2 diabetes mellitus (T2D) has increased. This study firstly aims to assess the prevalence of T2DM among thyroid nodules patients who underwent total thyroidectomy in the Western Romanian population. By focusing on the biochemical and hormonal parameters, it also aims to provide insights into possible connections between T2D and different types (benignant or malignant) of thyroid nodules. Materials and Methods: A total of 926 patients who underwent total thyroidectomy were analysed, comprising 99 (10.7%) T2D patients and 827 (89.3%) non-diabetic patients (non-T2D). Results: This study’s results revealed an increased prevalence of T2D among thyroid nodules patients. Among these patients, higher values of FT4 and inflammatory markers and a higher prevalence of malignant nodules (55%, p = 0.001) were noted. Conclusions: Our study revealed an increased prevalence of T2D among thyroid nodules patients. The biochemical profile of thyroid nodules in T2D patients presents aspects, like elevated FT4 and inflammatory markers, which should be considered in their clinical management. Furthermore, a T2D patient seems to be more likely to develop thyroid malignancies. Thyroid screening strategies in diabetic patients should be considered.

Cataract is among the most common ocular complications in diabetes mellitus (DM). While microRNA (miRNA) dysregulations in DM have been previously reported, consensus is still lacking concerning miRNA expression in cataract. Furthermore, the miRNA profile in diabetic cataract patients remains largely unexplored, and data on plasma expression levels are limited. Our study aimed to assess the plasma levels of three distinct miRNA species (hsa-miR-19b, hsa-miR-34a, and hsa-miR-146a) implicated in the development of cataract and/or DM.We investigated the circulating miRNA expression in DM patients diagnosed with cataract, compared to a non-DM cataract group. We employed qRT-PCR for relative quantification experiments and subsequently conducted a correlation analysis between miRNA expression levels and clinical characteristics. Our findings reveal that hsa-miR-34a and hsa-miR-146a are differentially expressed in the two cohorts. However, no significant correlation was observed between the clinical variables and miRNA levels. In summary, our results suggest a potential role for hsa-miR-34a and hsa-miR-146a in the biology of diabetic cataract.