Herpes zoster (HZ) is an acute infectious disease caused by varicella-zoster virus (VZV) reactivation, and zoster-associated pain (ZAP), including acute HZ pain and postherpetic neuralgia (PHN), severely impairs patients’ quality of life. The Chinese Guidelines (2025) define PHN as pain persisting over 1 month after lesion healing and advocate integrated ZAP management. ZAP’s pathogenesis is complex, involving VZV replication, neuronal sensitization, neuro-immune-inflammatory interactions, abnormal ion channels, genetic variations, and sympathetic dysfunction. Clarifying these mechanisms is crucial for optimizing treatment and developing targeted interventions, to further elucidate its pathogenic mechanisms.

The growing volume of electronic medical record (EMR) data in dermatology presents significant opportunities for research and clinical innovation. However, the field faces a paradox: while data generation increases exponentially, actionable knowledge remains limited due to structural and semantic heterogeneity. This challenge is especially pronounced in integrated Chinese and Western medicine settings, where clinical documentation must incorporate both biomedical constructs and traditional Chinese medicine (TCM) frameworks, including syndrome differentiation, diagnostic methods, and herbal prescriptions. This review highlights data standardization as a critical step in transforming heterogeneous clinical data into analyzable research resources, using integrated psoriasis treatment as an illustrative example. Key approaches to integrating diverse data sources, establishing governance frameworks, and implementing quality control mechanisms are reviewed. Core data elements are identified for both Western medicine (diagnostic codes, laboratory indicators, medications, and severity measures) and TCM (syndrome patterns, tongue and pulse characteristics, symptom descriptions, and herbal prescriptions). Advances in natural language processing for classical Chinese medical terminology, machine learning for syndrome recognition, and federated learning for multi-center collaboration are discussed as transformative tools for integrated medicine research. Applications of standardized data include the creation of specialized databases, generation of real-world evidence for mechanistic insights, and development of artificial intelligence (AI)-assisted clinical decision support tools. Current limitations, such as incomplete historical data, diagnostic subjectivity, underdeveloped TCM-specific computational methods, and the lack of validated reference standards, are critically examined. In conclusion, comprehensive data standardization is essential for advancing integrated medicine research. It facilitates evidence-based validation of TCM approaches, discovery of therapeutic targets, and optimization of patient outcomes through precision treatment strategies. The methods outlined here offer broader applicability across dermatology and other medical specialties, paving the way for data-driven integrative healthcare.

The application of artificial intelligence (AI) in dermatology is undergoing a fundamental transition from perceptive intelligence toward cognitive and actionable intelligence, signaling the emergence of “AI Dermatology 2.0”. This paradigm shift aims to restructure disease comprehension, predictive modeling, and clinical collaboration frameworks. Central to this evolution is the integration of causal inference methodologies, such as Structural Causal Models (SCMs), which enable AI to transcend superficial explainability and perform counterfactual reasoning, thereby achieving expert-level performance in deciphering complex pathological mechanisms. Furthermore, the development of high-fidelity skin digital twins—synthesizing multi-scale omics data with real-time physiological parameters—provides a virtual platform for simulating individualized drug responses. This capability facilitates a transition in clinical focus from reactive management to proactive, predictive intervention aimed at risk interception. Ultimately, a distributed intelligence network driven by autonomous AI agents, including closed-loop monitoring patches and large language model (LLM)-powered virtual assistants, is expected to establish a comprehensive management system spanning the entire life cycle. While the realization of this vision faces substantial challenges—including the integration of multi-source heterogeneous data, validation of model robustness, and the establishment of ethico-legal frameworks—AI 2.0 is not intended to replace clinicians. Instead, it seeks to automate redundant tasks, enabling physicians to transition into roles as supervisors of intelligent systems and final decision-makers for complex cases, ultimately advancing the field from symptom-based treatment toward holistic life-cycle skin homeostasis management.

Background: Viral skin diseases, particularly those caused by human papillomavirus (HPV), represent a major component of the global burden of infectious dermatoses. However, long-term global trends and socioeconomic inequalities remain insufficiently characterized.

Methods: Data were obtained from the Global Burden of Disease Study 2021, covering approximately 7.97 billion individuals. Incidence, prevalence, disability-adjusted life years (DALYs), and years lived with disability (YLDs) were analyzed. Age-standardized rates were calculated, and temporal trends were assessed using Joinpoint regression to estimate average annual percentage changes (AAPCs). Socioeconomic inequality was evaluated using the Slope Index of Inequality (SII) and Concentration Index (CI). Analyses were stratified by age, sex, country, region, and Socio-Demographic Index (SDI).

Results: Between 1990 and 2021, the global incidence, prevalence, and DALYs of viral skin diseases increased by 32.27%, 36.29%, and 35.81%, respectively. The age-standardized incidence rate declined slightly from 1134.3 to 1126.3 per 100,000. Increased age-specific incidence was observed among children < 15 years and adults aged 50–65 years and 85–95 years, with consistently higher rates in males. Geographically, incidence and prevalence were highest in Germany and lowest in Israel. Burden indicators were generally greater in high-SDI regions, whereas lower-middle SDI regions showed continued growth. Projections indicate stable age-standardized incidence through 2046, with case numbers rising until around 2030 before plateauing.

Discussion: The increasing absolute burden despite stable standardized rates reflects population growth and aging. Disparities across SDI regions highlight the roles of socioeconomic factors and healthcare access. Although vaccination and antiviral advances have improved viral disease control in high-SDI regions, limited resources and healthcare disruptions constrain progress in low- and middle-SDI regions, underscoring the need for targeted, equitable interventions.

Conclusions: Viral skin diseases remain a substantial and evolving global health burden. Persistent age-, sex-, and socioeconomic-related disparities highlight the need for targeted prevention strategies and strengthened public health policies.

Alopecia areata (AA) is an autoimmune, non-scarring hair loss disorder caused by collapse of hair follicle immune privilege and T cell-mediated inflammation. It affects individuals of all ages and carries substantial psychological and social burden. The condition shows marked heterogeneity in presentation and prognosis, influenced by genetic, immune, and environmental factors. The 2026 Chinese Guidelines for AA provide updated, evidence-based recommendations spanning diagnosis, severity assessment, and management. It endorses a multidimensional evaluation that integrates scalp involvement, extra-scalp features, treatment response, and psychosocial impact to guide individualized care. Therapeutic pathways cover topical, intralesional, and systemic options, including corticosteroids, Janus kinase (JAK) inhibitors, and selected biologics, with adjunctive modalities such as light-based therapies, microneedling, platelet-rich plasma, and oral minoxidil. For children, topical corticosteroids remain first-line; JAK inhibitors or biologics may be considered in carefully selected severe cases with appropriate monitoring. The guideline emphasizes long-term follow-up, screening and management of comorbidities, and shared decision-making to improve quality of life. It further highlights the need for research into biomarkers and novel therapeutic targets to fuel continued iterations on treatments for AA.