Folia medica最新文献

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Introduction: Apical periodontitis (AP) is a chronic inflammatory condition resulting from microbial infection of the dental pulp. The host immune response and microbial interactions play a significant role in the disease's progression. Gingival crevicular fluid (GCF) provides a valuable, non-invasive source for detecting inflammatory biomarkers involved in AP, such as IL-1β, IL-10, and IL-23.

Introduction: Infections such as Chlamydiatrachomatis and Yersiniaenterocolitica are recognized triggers of reactive arthritis, but their role in chronic spondyloarthritis (SpA)-including ankylosing spondylitis (AS) and psoriatic arthritis (PsA)-remains incompletely defined.

Heart failure (HF) poses a major global health burden due to its high prevalence, complexity, and poor prognosis. Although biomarkers such as B-type natriuretic peptides (BNP, NT-proBNP) are widely used for diagnosis and risk stratification, additional biomarkers are needed to refine prognostication. Copeptin, a stable fragment of pre-provasopressin, reflects vasopressin system activity and has emerged as a promising prognostic tool. Elevated copeptin levels correlate with increased mortality, hospitalizations, and disease progression in both acute and chronic HF. It offers early detection of hemodynamic stress and complements traditional markers, especially in multimarker strategies. This review explores copeptin's physiological role, its predictive value in various HF phenotypes, and its integration into clinical risk models. Evidence supports its utility in identifying high-risk patients, guiding therapy, and monitoring disease evolution. Challenges to clinical adoption include assay standardization, cost-effectiveness, and establishing universally accepted cutoffs. Future directions focus on copeptin-guided therapies, AI-driven predictive models, and its role in precision medicine. Continued research may solidify copeptin's role in optimizing heart failure management through individualized risk assessment and tailored interventions.

This review explores how two cutting-edge technologies-telemedicine and artificial intelligence (AI)-are reshaping diabetes care. Diabetes remains one of healthcare's toughest challenges, demanding round-the-clock monitoring and treatments that adapt to each patient's needs. During COVID-19, telemedicine proved its worth as a vital tool for maintaining patient care and improving health outcomes. Meanwhile, AI-through machine learning (ML) and deep learning (DL)-brings fresh capabilities for catching diabetes early, assessing patient risk, and spotting complications like eye and nerve damage before they become serious. We examined recent research on these technologies, particularly their roles in predicting who might develop diabetes, using Natural Language Processing (NLP) to decode messy patient records, and supporting doctors through clinical decision support systems (CDSS). Our findings reveal that telemedicine works-it helps patients control their blood sugar better and keeps them satisfied with their care. However, not everyone has equal access to technology, and some healthcare providers remain skeptical. AI diagnostic tools, especially for eye screening, now match human doctors in accuracy. Though merging these technologies could revolutionize personalized diabetes care, we first need to tackle real-world obstacles: ensuring fair access for all patients, protecting sensitive health data, and making different systems work together seamlessly.

Introduction: Chemotherapy is one of the modalities of systemic therapy. It is not tumor-specific and is linked to the occurrence of toxicities in healthy tissues. Chemotherapy also impairs the immune system, reducing the number of immune cells and weakening its function.

Non-invasive prenatal testing (NIPT) has transformed prenatal screening, offering high sensitivity and specificity in the detection of common fetal aneuploidies. However, discordant results-where NIPT findings do not align with those of confirmatory diagnostics-pose challenges for clinical interpretation and patient counseling.