Artificial Intelligence (AI) has revolutionized multiple domains, including healthcare, by enhancing the capabilities of Machine Learning (ML) models for disease detection and diagnosis. Among these, early joint disease detection has significantly benefited from AI-powered technologies such as deep learning (DL) algorithms, medical image analysis, pattern recognition, and predictive analytics. Joint disorders, such as osteoarthritis (OA), rheumatoid arthritis (RA), and other inflammatory musculoskeletal conditions, are among the leading causes of disability worldwide. The early diagnosis of these diseases is critical for effective intervention, reducing disease progression, and improving patient outcomes. Traditional diagnostic methods rely heavily on clinical symptoms, imaging techniques, and laboratory tests. However, these approaches often detect diseases at an advanced stage when significant joint damage has already occurred. Recent advances in AI and ML have transformed the field of medical diagnostics, providing early and accurate detection methods for joint disorders. AI-driven diagnostic tools, including ML models, leverage large datasets of medical images, biomarkers, and patient records to identify patterns and predict disease onset with high precision. This editorial article explores the current state of AI in joint disease diagnostics, discusses the benefits and challenges of these technologies, and highlights future directions in AI-driven healthcare innovations.

Objectives: Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder that adversely affects pregnant women and their growing fetuses. Evidence suggests that genetic and epigenetic modifications, such as DNA methylation, may contribute to the disease phenotype. This study aimed to identify GDM-related hub-methylated genes involved in GDM pathogenesis. Methods: RNA-seq transcriptomic-wide data (GSE203346) and microarray epigenomic-wide data (GSE106099) were obtained from the Gene Expression Omnibus. Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression (DEGs) analysis were performed on the RNA-seq data using the “R” packages “WGCNA” and “DESeq2,” respectively. Differentially methylated genes (DMGs) were identified using the “limma” package. Results: WGCNA identified 18 modules, with only two modules [MEyellow r = −0.32; P = 0.042 and MEmagenta r = −0.32; P = 0.041] showing significant inverse correlations with GDM and one module [MEblue r = 0.35; P = 0.026], showing a direct correlation. Following intersecting the hub genes from WGCNA, DEGs and DMGs, six hub genes were identified as hypomethylated and highly expressed (UCKL1, SHANK2, GDPD5, CMYA5, ESRRG, NOS3), while two genes (DPYSL3 and FTH1) were hypermethylated and showed low expression. Gene set enrichment analysis revealed that the GDM-related hub DMGs were mainly enriched in pathways related to ferroptosis, VEGF signaling, and arginine and proline metabolism. Conclusion: This multi-omics study identified eight novel GDM-related hub DMGs in placental tissue from GDM cases, suggesting their potential involvement in GDM pathogenesis. Further study is needed.

Objectives: In utero, exposure to maternal high-fat diet (HFD) has been identified to predispose the offspring to obesity and other metabolic dysfunctions later in life. Zingerone, a bioactive phytochemical found in ginger has potential for the treatment of metabolic diseases due to its antioxidant properties. This study investigated its potential reprogramming effect on some metabolic indices and pro-opiomelanocortin (POMC) gene in young adult offspring of Wistar rat models exposed to maternal HFD. Methods: 30 pregnant Wistar rats were divided into five groups: Normal control group, an HFD control, and three experimental groups treated with 50, 100, or 200 mg/kg of zingerone, respectively. The treatment commenced from day 1 of pregnancy until postnatal day (PND) 21, after which the offsprings were weaned and placed on a standard diet until PND 42. On PND 42, the biochemical assays were performed on the offsprings using enzyme-linked immunosorbent assay kits and the hypothalamic POMC gene expression using reverse transcription polymerase chain reaction. Data were analyzed using analysis of variance. Values of P < 0.05 were taken as statistically significant. Results: Offsprings in the zingerone-treated groups showed significant (P < 0.05) decrease in body weight, glucose, insulin, cholesterol, triglycerides, and leptin levels compared to the HFD control group. Food intake and ghrelin levels increased, while POMC gene expression was inhibited with 100 and 200 mg/kg of zingerone. Conclusion: Maternal zingerone administration may mitigate the risk of metabolic disorders in the offspring, possibly by its influence on the anorexigenic genetic makeup of the offspring.

Objectives: This study aims to evaluate the synergistic effects of doxorubicin (DOX) and the natural phenolic alkaloid avenanthramide C (AVC) on enhancing apoptosis in MCF-7 breast cancer (BC) cells, with a specific focus on the expression of mitochondrial proteins voltage-dependent anion channel 2 (VDAC2) and mitochondrial carrier homolog 1 (MTCH1) involved in apoptosis pathways. Methods: MCF-7 cells were treated with various concentrations of DOX and AVC. The 50% inhibitory concentration (IC50) of DOX combined with AVC was evaluated in the MCF-7 cells using an MTT assay, while gene expression levels of Ki-67, MTCH1, and VDAC2 were assessed through real-time polymerase chain reaction. Apoptotic rates were measured using flow cytometry. Results: DOX and AVC combination reduced the IC50 value by 2.1-fold compared to DOX alone, indicating enhanced cytotoxicity. Co-treatment significantly downregulated Ki-67 expression and increased apoptosis by 76% in cells treated with 3 μM DOX and 160 μM AVC. Gene expression analysis revealed a 4.8-fold increase in MTCH1 and a 15-fold increase in VDAC2 compared to DOX treatment alone. Conclusion: The DOX-AVC combination demonstrated a potent synergistic effect, enhancing apoptosis in BC cells by modulating mitochondrial pathways. This approach may provide a promising strategy for reducing chemotherapy side effects in BC treatment. Further studies in pre-clinical models are warranted to explore its therapeutic potential.

Objectives: Probiotic-enriched fermented turmeric-camel milk (FTCM) and unfermented (TCM) were examined on streptozotocin (STZ)-induced type 2 diabetes and oxidative stress in rats. Methods: High phenolics and antioxidant activity were found in TCM and FTCM. FTCM and TCM at 10 or 20 mL/kg were investigated for antidiabetic and hypolipidemic effects in an animal model. The positive group diabetic rats (DR) received 45 mg/kg STZ intraperitoneally; G3 DR (DR+Met) received 50 mg metformin kg−1. G4 (DR+TCM10), G5 (DR+TCM20), G6 (DR+FTCM10), and G7 (DR+FTCM20) received 10 or 20 mL/kg from either TCM or FTCM orally daily, respectively. Blood glucose, liver and kidney functions, antioxidant biomarkers, and histopathology were investigated. Results: TCM and FTCM had strong phenolics and antioxidant potential. High performance liquid chromatography analysis quantified ten phenolic acids and four flavonoids, with ferulic acid and resveratrol dominating. TCM and FTCM dramatically decreased random blood glucose and fasting blood glucose. The hypolipidemic effects of TCM and FTCM were more significant at 20 mL/kg than at 10 mL/kg, with substantial reductions in triglycerides, total cholesterol, high- and low-density lipoproteins cholesterol, and very-low-density lipoproteins cholesterol. TCM and FTCM at 20 mL/kg improved liver and kidney functions more than metformin or 10 mL/kg. FTCM and TCM dose-dependently increased antioxidant enzyme activity, glutathione, catalase, and superoxide dismutase, and decreased malondialdehyde. Histopathologically, TCM and FTCM showed typical Langerhans cell and acini structure, outperforming metformin. Conclusion: TCM and FTCM may help profitably manage diabetes complications and oxidative stress.

Objectives: The goal of this study was to estimate and compare the prospective therapeutic impacts of different types of bioflavonoids (flavonols, flavanones, and isoflavones) on acute kidney injury (AKI) induced by glycerol in male rats. Methods: Fifty adult male albino rats (Sprague-Dawley) were separated into five groups: G1, control; G2, rats injected (i.m.) by glycerol (50%) (10 mL/kg b. w.) to induce AKI; G3, G4, and G5, rats received quercetin (QUR), hesperidin (HSP), and genistein (GEN), respectively, after 24 h of glycerol injection for 42 successive days. Results: Treatment with bioflavonoids improved the renal tissue levels of antioxidant biomarkers (superoxide dismutase, glutathione, catalase, nitric oxide, inflammatory cytokines (interleukin-6, interleukin-1 βeta, nuclear factor kappa-B, tumor necrosis factor-alpha), kidney function markers (creatinine, urea, urine albumin creatinine ratio, albumin) as compared to nephrotoxic groups. QUR extract reduced the serum level of kidney function parameters in glycerol-injected rats more significantly (P ≤ 0.01) than HSP and GEN. Results demonstrated that the GEN as a therapeutic natural agent exhibited the greatest advancement in urine values, followed by the QUR and HSP respectively when compared to the AKI group. Conclusion: The study results demonstrated the therapeutic effect of bioflavonoids against AKI induced by glycerol. Different types of bioflavonoids could reduce oxidative stress, inhibit the production of inflammatory mediators and cytokines, and improve renal function.

Objective: This systematic review examines the development and clinical application of hybrid aortic valve interventions that integrate surgical and transcatheter techniques. It focuses on the efficacy, outcomes, and innovations of these procedures, particularly for patients at moderate-to-high surgical risk. Methods: A comprehensive database search (PubMed, Ovid, Web of Science, Cochrane, CINAHL, Embase, Scopus) was conducted from August 20 to October 10, 2024. Studies on aortic valve interventions combining surgical and transcatheter approaches were included, encompassing case studies, series, cohort studies, and reviews. Non-English articles, gray literature, cadaveric, and animal studies were excluded. Screening followed Preferred Reporting Items for Systematic Review and Meta-Analysis 2023 guidelines, with two rounds performed. Formal quality assessment was omitted due to study heterogeneity. Results: Out of 2046 initial articles, 495 unique studies remained after duplicate removal, and 65 articles were selected for analysis. Hybrid aortic valve procedures, blending surgical techniques with transcatheter aortic valve implantation, demonstrated improved outcomes, including shorter recovery times, reduced complications, and personalized treatment options for moderate-risk patients. Conclusion: Hybrid aortic valve interventions mark a significant advancement, enhancing patient-specific care and outcomes. Continued innovation in materials, techniques, and clinician training is crucial to improve durability, long-term outcomes, and broader adoption of these minimally invasive procedures. Future research should address these areas to further optimize cardiovascular care.

Granulomatous mycosis fungoides (GMF) is a rare subtype of T-cell cutaneous lymphoma. Due to the lack of distinct clinical features, GMF may pose a diagnostic challenge, which results in diagnostic delay. The diagnosis is based on histopathological and immunohistochemical findings. Herein, we present an 82-year-old male with itchy lesions over the scalp, face, forearms, trunk, and bilateral lower limbs for 6 months. Histologically, it was a CD8-positive GMF. GMF is a rare subtype of mycosis fungoides with <100 cases in the literature, and most of these cases showed a CD4-positive phenotype. CD8-positive GMF is extremely rare. We observed that it commonly affects elderly females. The patients often present with nodules and do not carry an adverse prognosis.