Pleural mesothelioma (PM) is an aggressive tumor with few therapeutic options. Although patients with epithelioid PM (ePM) survive longer than non-epithelioid PM (non-ePM), heterogeneity of tumor response in ePM is observed. The role of the tumor immune microenvironment (TIME) in the development and progression of PM is currently considered a promising biomarker. A few studies have used high-throughput technologies correlated with TIME evaluation and morphologic and clinical data. This study aimed to identify different morphological, immunohistochemical, and transcriptional profiles that could potentially predict the outcome. A retrospective multicenter cohort of 129 chemonaive PM patients was recruited. Tissue slides were reviewed by dedicated pathologists for histotype classification and immunophenotype of tumor-infiltrating lymphocytes (TILs) and lymphoid aggregates or tertiary lymphoid structures (TLS). ePM (n = 99) survivors were further classified into long (>36 months) or short (<12 months) survivors. RNAseq was performed on a subset of 69 samples. Distinct transcriptional profiling in long and short ePM survivors was found. An inflammatory background with a higher number of B lymphocytes and a prevalence of TLS formations were detected in long compared to short ePM survivors. These results suggest that B cell infiltration could be important in modulating disease aggressiveness, opening a pathway for novel immunotherapeutic approaches.

The tumor microenvironment (TME) influences cancer progression. Therefore, engineered TME models are being developed for fundamental research and anti-cancer drug screening. This paper reports the biofabrication of 3D-printed avascular structures that recapitulate several features of the TME. The tumor is represented by a hydrogel droplet uniformly loaded with breast cancer cells (10⁶ cells/mL); it is embedded in the same type of hydrogel containing primary cells—tumor-associated fibroblasts isolated from the peritumoral environment and peripheral blood mononuclear cells. Hoechst staining of cryosectioned tissue constructs demonstrated that cells remodeled the hydrogel and remained viable for weeks. Histological sections revealed heterotypic aggregates of malignant and peritumoral cells; moreover, the constituent cells proliferated in vitro. To investigate the interactions responsible for the experimentally observed cellular rearrangements, we built lattice models of the bioprinted constructs and simulated their evolution using Metropolis Monte Carlo methods. Although unable to replicate the complexity of the TME, the approach presented here enables the self-assembly and co-culture of several cell types of the TME. Further studies will evaluate whether the bioprinted constructs can evolve in vivo in animal models. If they become connected to the host vasculature, they may turn into a fully organized TME.

Origanum vulgare var. vulgare essential oil (OEO) is known as a natural product with multiple beneficial effects with application in dermatology. Oregano essential oil represents a potential natural therapeutic alternative for fibroepithelial polyps (FPs), commonly known as skin tags. Innovative formulations have been developed to improve the bioavailability and stability of essential oils. In this study, we aimed to evaluate the morphology of a polymeric-micelles-based hydrogel (OEO-PbH), the release and permeation profile of oregano essential oil, as well as to assess in vivo the potential effects on the degree of biocompatibility and the impact on angiogenesis in ovo, using a chick chorioallantoic membrane (CAM). Scanning electron microscopy (SEM) analysis indicated a regular aspect after the encapsulation process, while in vitro release studies showed a sustained release of the essential oil. None of the tested samples induced any irritation on the CAM and the limitation of the angiogenic process was noted. OEO-PbH, with a sustained release of OEO, potentially enhances the anti-angiogenic effect while being well tolerated and non-irritative by the vascularized CAM, especially on the blood vessels (BVs) in the presence of leptin treatment. This is the first evidence of in vivo antiangiogenic effects of a polymeric-micelle-loaded oregano essential oil, with further mechanistic insights for OEO-PbH formulation, involving leptin as a possible target. The findings suggest that the OEO-containing polymeric micelle hydrogel represents a potential future approach in the pathology of cutaneous FP and other angiogenesis-related conditions.

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.

Aim: This study evaluates the comparative effectiveness of pathologists versus artificial intelligence (AI) algorithms in scoring PD‐L1 expression in non‐small cell lung carcinoma (NSCLC). Immune‐checkpoint inhibitors have revolutionized NSCLC treatment, with PD‐L1 expression, measured as the tumour proportion score (TPS), serving as a critical predictive biomarker for therapeutic response.Methods and Results: In our analysis, 51 SP263‐stained NSCLC cases were scored by six pathologists using light microscopy and whole‐slide images (WSI), alongside evaluations by two commercially available software tools: uPath software (Roche) and the PD‐L1 Lung Cancer TME application (Visiopharm). The study examined intra‐ and interobserver agreement among pathologists at TPS cutoffs of 1% and 50%, revealing moderate interobserver agreement (Fleiss' kappa 0.558) for TPS <1% and almost perfect agreement (Fleiss' kappa 0.873) for TPS ≥50%. Intraobserver consistency was high, with Cohen's kappa ranging from 0.726 to 1.0. Comparisons between the AI algorithms and the median pathologist scores showed fair agreement for uPath (Fleiss' kappa 0.354) and substantial agreement for the Visiopharm application (Fleiss' kappa 0.672) at the 50% TPS cutoff.Conclusion: These results indicate that while there is strong interobserver concordance among pathologists at higher TPS levels, the performance of AI algorithms is less consistent. The study underscores the need for further refinement of AI tools to match the reliability of expert human evaluation, particularly in critical clinical decision‐making contexts.

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.