Uterine fibroids represent the most common benign gynecological tumors globally, yet management pathways differ substantially across health systems. Observational evidence demonstrates marked divergence between the United Kingdom (UK) and Sub-Saharan Africa (SSA), particularly Nigeria, in treatment access, surgical thresholds, and fertility-preserving strategies. To synthesize biological, structural, and health-system determinants underpinning divergent fibroid management pathways between the UK and SSA, and to construct a multi-domain explanatory framework with equity implications. A comparative narrative analysis was conducted using SANRA quality standards to guide critical appraisal and reporting. Elements of the PRISMA 2020 checklist informed transparent reporting of the search strategy. Databases were searched for epidemiological, clinical, policy, and systems-level literature comparing fibroid prevalence, genetic predisposition, treatment modalities, and institutional frameworks across regions. SSA populations demonstrate earlier age of onset, larger tumor burden at presentation, and higher surgical rates. In contrast, UK management is characterized by guideline-directed conservative pathways, wider access to MRI, uterine artery embolization, minimally invasive surgery, and fertility-preserving pharmacotherapy. Determinants of divergence include genetic susceptibility, delayed presentation, financing constraints, imaging availability, workforce distribution, and national guideline enforcement. The review identifies an emerging pattern of reverse reproductive medical tourism, wherein UK-resident African-ancestry women seek cross-border surgical intervention due to system-level unmet need. Divergent fibroid management reflects not merely biological variation but structural inequities embedded within health systems. Addressing disparities requires integrated policy reform, workforce investment, patient-stratified clinical decision-making, and context-adapted guideline implementation. Future prospective comparative studies are warranted to quantify outcome differentials and inform equity-driven global gynecological practice.
Magnetic nanoparticles (NPs), particularly magnetite (Fe₃O₄), are of increasing interest for biomedical and nanotechnological applications due to their unique magnetic and biocompatible properties. This study presents the gamma radiation-induced biomineralization of Fe₃O₄ NPs in the thermophilic bacterium, Bacillus sp. KA2, isolated from the “Ashagi Istisu” hot spring (Kelbajar, Azerbaijan). The bacterium was exposed to gamma radiation at doses of 500 Gy and 2000 Gy, with non-irradiated cells serving as controls. Electron Paramagnetic Resonance (EPR) spectroscopy revealed Fe₃O₄-specific signatures (g = 2.32, ∆H = 320 G) exclusively in irradiated samples, indicating radiation-assisted nanoparticle formation. A notable 30
BACKGROUND:Atherosclerotic cardiovascular disease is a leading cause of morbidity and mortality worldwide, and an urgent need exists to discover new therapeutic strategies. Isolinderalactone (ISO) is a sesquiterpene compound derived from the Lindera aggregata root with significant anti-inflammatory effects. Given that atherosclerosis (AS) is a chronic inflammatory condition, the efficacy and mechanism of ISO on atherosclerotic disease are still unclear. PURPOSE:The study aims to evaluate the therapeutic potential of ISO as an NLRP3 inhibitor in the management of AS. METHODS:For in vivo study, ApoE-/- mice were fed a high-fat diet to induce an AS model to evaluate the therapeutic effect of ISO. For in vitro study, bone marrow-derived macrophages (BMDMs) were used to elucidate the specific molecular mechanism by which ISO inhibits NLRP3 inflammasome activation. Mass spectrometry and molecular docking analyses were conducted to identify active sites. RESULTS:Our data show that ISO reduced atherosclerotic plaque formation by inhibiting NLRP3 inflammasome activation and inflammatory responses. Network pharmacology analyses showed that ISO might alleviate AS by suppressing the NOD-like receptor (NLR) pathway, leading to reduced inflammatory mediators. ISO dose-dependently suppressed IL-1β secretion through inhibiting NLRP3 inflammasome activation, displaying an IC50 value of 2.882 μM. In addition, ISO selectively blocked ASC oligomer formation and disrupted NLRP3 inflammasome complex assembly. Mass spectrometry and docking simulations revealed that ISO formed covalent bonds with the NLRP3 protein, specifically targeting Cys470 within its NACHT domain. CONCLUSION:Collectively, ISO emerges as a novel NLRP3 inhibitor and a potential therapeutic candidate for atherosclerotic disease.
Renal cell carcinoma (RCC) is a prevalent and heterogeneous malignancy with clear cell RCC (ccRCC) as the most common subtype. Despite advances in surgical, targeted, and immunotherapeutic approaches, prognosis for advanced and metastatic RCC remains poor, and the effectiveness of current immunotherapies is limited by immune tolerance, tumor heterogeneity, and adverse effects. The identification of tumor-associated antigens (TAAs) and tumor-specific antigens (TSAs) is crucial for the development of personalized and effective antigen-directed therapies, including vaccines, antibodies and adoptive cell therapies. This review summarizes epidemiological data, molecular features of RCC, and the role of the von Hippel Lindau – Hypoxia Inducible Factor (VHL-HIF) signaling pathway in pathogenesis, alongside recent progress in characterizing possible antigen targets for vaccination such as TOP2A, NCF4, FMNL1, DOK3, MUC1, CAIX, CD70, and 5T4. Preclinical models, including genetically engineered mouse models, zebrafish, and various patient-derived xenograft (PDX) systems, are discussed as tools for studying tumor biology and testing immunotherapeutic strategies. Clinical trial data on RCC vaccines, including autologous renal tumor cell vaccination, peptide-based, dendritic cell-based, and viral vector platforms, demonstrate immunogenicity but have not yet yielded clear survival benefits in phase III trials. Future directions emphasize integrating antigen discovery with immune profiling, refining preclinical modeling, and developing personalized vaccines to enhance therapeutic efficacy, particularly for immunologically favorable patient subtypes and for certain applications such as reducing metastasis after surgery. In particular, we discuss carrier-based vaccine approaches for overcoming tolerance and increasing the immunogenicity of vaccines.
The paper focuses on automated diagnosis of retinal diseases, particularly Age-related Macular Degeneration (AMD) and diabetic retinopathy (DR), using optical coherence tomography (OCT), while addressing three key challenges: disease comorbidity, severe class imbalance, and the lack of strictly paired OCT and fundus data. We propose a hierarchical modular deep learning system designed for multi-label OCT screening with conditional routing to specialized staging modules. To enable DR staging when fundus images are unavailable, we use cross-modal alignment between OCT and fundus representations. This approach involves training a latent bridge that projects OCT embeddings into the fundus feature space. We enhance clinical reliability through per-class threshold calibration and implement quality control checks for OCT-only DR staging. Experiments demonstrate robust multi-label performance (macro-F1 =0.989±0.006 after per-class threshold calibration) and reliable calibration (ECE =2.1±0.4%), and OCT-only DR staging is feasible in 96.1% of cases that meet the quality control criterion.
