Skin cancer represents one of the most common and clinically significant malignancies worldwide, with rising incidence and substantial mortality, particularly melanoma, which accounts for approximately 75–80% of skin cancer-related deaths despite comprising < 5% of cases. Early detection and accurate prognostication remain essential for improving patient outcomes, yet subjectivity, resource constraints, and inter-observer variability often limit conventional diagnostic methods. Recent advances in artificial intelligence (AI), particularly deep learning, have demonstrated remarkable potential in enhancing diagnostic precision, risk stratification, and personalized treatment planning. Convolutional neural networks, vision transformers, and hybrid architectures have achieved dermatologist-level accuracy in classifying dermoscopic and clinical images, while multimodal approaches integrating histopathology, genomics, and patient metadata have improved prognostic assessments. Despite these advances, significant challenges remain, including dataset biases, lack of interpretability, regulatory barriers, and disparities in access to AI technologies. Addressing these challenges through explainable AI, federated learning, robust clinical validation, and equitable deployment strategies will be crucial for translation into routine practice. This review synthesizes current evidence on AI applications in skin cancer diagnosis and prognosis, highlights key technological innovations, and outlines the challenges and future directions necessary to ensure safe, effective, and globally accessible integration of AI into dermatological care..

Sex and gender represent critical yet underutilized precision biomarkers in oncology, influencing cancer incidence, progression, treatment response, and survival outcomes. Biological sex, characterized by chromosomal, hormonal, and anatomical factors, directly influences tumor biology, immune responses, and therapy-related toxicities. Gender, encompassing social norms and behaviors, further impacts cancer risk through lifestyle choices, health awareness, and access to healthcare. Nonetheless, the predominant portion of clinical research remains gender- and sex-neutral, hence limiting the efficacy of precision medicine. Artificial intelligence (AI) facilitates predictive modeling for diagnosis, therapy optimization, and prognosis by integrating sex- and gender-specific data, ranging from high-dimensional biological markers to actual clinical records. In conditions such as breast, prostate, and lung cancers, AI-driven patient stratification can discern sex-specific biological pathways, guide the formulation of targeted treatments, and improve therapy customization. Despite these advancements, challenges about data representation, annotation, and regulatory compliance persist. To attain equitable precision oncology, ethically governed AI frameworks must be integrated with extensive, longitudinal, and gender-balanced datasets. Consistently incorporating sex and gender across the cancer care continuum for diverse patient populations may enhance quality of life, augment therapeutic efficacy, and reduce disparities.

Poly(1-naphthylamine) (pNPA), similar to polyaniline, is a significant conducting polymer frequently synthesized through electrochemical methods in acidic or non-aqueous environments. Unlike conventional preparation, this work demonstrates the fabrication of pNPA via a neutral pH-assisted open-circuit potential technique on a multiwalled carbon nanotube modified glassy carbon electrode (GCE/CNT@pNPA). Electrochemical cycling of 1-naphthylamine (1-NPA) adsorbed GCE/CNT in pH 7 phosphate buffer solution (PBS) led to the formation of a redox active polymeric structure. Physicochemical characterization of CNT@pNPA by microscopic (SEM) and spectroscopic (Raman and FTIR) methods confirmed the electro-organic synthesis of pNPA on CNT. Notably, GCE/CNT@pNPA showed good Nernstian behavior with negligible electrocatalytic activity to various electroactive biochemicals. The stability of peak current and potential further highlighted the selective electrochemical pH sensing capability of GCE/CNT@pNPA. Under optimal differential pulse voltammetry conditions, the GCE/CNT@pNPA was extended for analysis of pH values in various food samples. In near future, GCE/CNT@pNPA can be further miniaturized and could be extended for online monitoring of pH in various samples.

Breast cancer, one of the leading cancer types, directly contributes to cancer‐related mortality, but new therapies are required to improve treatment efficiency. Nanoparticle‐based strategies have already introduced the most radical advances in this regard, from their first formulation through their development to the next generation as promising candidates. The present review provides an overview of nanoparticle‐based strategies in breast cancer, their development, and their state of the art. The review addresses the diverse formulation of nanoparticles, including liposomes, dendrimers, and metallic nanoparticles, as well as their respective roles in drug delivery: bioavailability, focused therapeutic intervention, and lower systemic toxicity. This review covers studies on the engineering of nanoparticles for improved drug delivery, including cancer‐targeted delivery to tumors and optimization within the tumor microenvironment. Additionally, new nanosized drugs may also be utilized for novel modification of nanoparticle composition for combination therapeutics, which allows pharmacological agents to enter the tumor microenvironment by combined treatment with diverse types of other agents, to provide a synergistic, effective treatment in real time, in addition to real‐time monitoring. Stimuli‐responsive nanoparticles, which release the drug according to the appropriate stimulus signal to provide greater accuracy and regulation in delivering the drug, are also under investigation. This review notes trends in personalized nanomedicine and nanoparticle‐mediated immunotherapy that target personalized patient and immune responses, among others. Other exciting areas for nanoparticle research include AI‐based optimal design and sustainable biodegradable materials aimed at maintaining nanoparticle safety. Nanoparticle‐based therapies are a unique new frontier in breast cancer therapy. They have considerable clinical potential, offer promise for patient‐specific treatment, and warrant further investigation in breast cancer, particularly in advanced targeting mechanisms, multifunctional approaches, and individualized interventions.

Peptic ulcer disease (PUD) is still a global health problem, and Helicobacter pylori infection is identified as the principal causative factor. While these are effective, the conventional pharmacological treatments are usually accompanied by side effects, the development of antibiotic resistance, and limited access in some cases. As a result, Complementary and Alternative Medicine (CAM) has become a promising complementary or alternative intervention for PUD. The objective of this systematic review was to assess the therapeutic value, safety, and constraints of CAM interventions for peptic ulcer disease. An extensive systematic review was performed using the PICO format and reported following guidelines, including Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Literature searches were conducted in multiple databases, including the Cochrane Library, Embase, MEDLINE, and the Complementary Medicine Database and included papers from 2000 to 2024. Herbal treatment, complementary medicine, and alternative medicine were the search terms. Available full-text studies had a focus primarily on CAM interventions for PUD. Data were tabulated and synthesized to summarize therapeutic mechanisms, safety profiles, and limitations of the studies. A total of 134 studies met the inclusion criteria, including randomized controlled trials ( n ≈ 45), observational studies ( n ≈ 30), systematic reviews and meta-analyses ( n ≈ 20), and preclinical experimental studies ( n ≈ 39). Herbal medicine was studied the most in CAM. There were agents such as Nigella sativa, licorice, turmeric, Aloe vera, and ginger, with gastroprotective, Antioxidant, and anti- H. Pylori effects. Probiotics and acupuncture were supportive, too. Compared to conventional therapies, CAM therapy caused fewer adverse effects. Some drawbacks included heterogeneity in herbal preparations, no standardized dosing, small patient populations, and limited large-scale clinical trials. In PUD management, CAM therapies, especially herbal medicines and probiotics, are of significant use as adjunctive drugs. Although both safety and affordability seem good, the overall evidence base is still moderate to low. Standardized preparations and good multicenter randomized controlled trials should be studied further to aid clinical utilization.