The global integration of traditional medicine (TM) and modern medicine reflects a fundamental shift in healthcare aimed at delivering more holistic, culturally sensitive, and patient-centered care. With over 80% of the global population relying on some form of TM, especially in Asia, Africa, and Latin America, there is growing momentum to institutionalize TM alongside evidence-based biomedicine. Countries like India, China, and Korea have led integration through formal education, government-supported research, and clinical frameworks, while high-income countries are increasingly adopting complementary and integrative medicine models. However, this convergence faces substantial challenges, including differences in epistemology, regulatory standards, evidence hierarchies, and practitioner training. Limited clinical trials, quality assurance concerns, and issues related to intellectual property rights and biopiracy further complicate harmonization. Despite these barriers, the World Health Organization’s Traditional Medicine Strategy (2014–2023) and its newly established Global Centre for Traditional Medicine (India) underscore a growing international commitment to evidence-based integration. Opportunities lie in promoting collaborative research, strengthening regulatory frameworks, enhancing digital health platforms for TM documentation, and fostering intercultural dialogue between health systems. If guided ethically and scientifically, integration can improve access to care, reduce treatment costs, and offer personalized health solutions for chronic and lifestyle-related diseases. This review explored global integration models, evaluated emerging challenges, and identified strategies to support an inclusive, pluralistic, and sustainable healthcare future that respects both traditional wisdom and modern science.

Recent advancements in cancer immunotherapy have highlighted glypican-3 (GPC3) as a prominent target for treating hepatocellular carcinoma (HCC). However, approximately 10% to 30% of HCC patients exhibit low or absent GPC3 expression on the surface of tumor cells, which limits the feasibility of GPC3-targeted therapies. Consequently, it is essential for patients to undergo pre-diagnostic assessments of GPC3 expression in tumor cells to evaluate their suitability for GPC3-directed therapy. Although various methods have been developed to specifically detect GPC3 as a biomarker for treatment and prognosis, the diagnostic approaches currently employed in clinical studies remain relatively limited. Here, we provide a comprehensive overview of the clinical development of GPC3-targeted therapeutics, clinical trials in GPC3-positive HCC, and current methods for detecting GPC3 expression, highlighting their advantages and limitations. Furthermore, we explore the potential of integrating targeted therapy with various GPC3 detection modalities tailored to different pathological stages. This integration not only provides insights into the selection of effective methods for detecting GPC3 expression but also has the potential to significantly improve the clinical outcomes of patients with liver cancer. By simultaneously assessing the advantages and disadvantages of these methods, this review aims to establish a theoretical foundation for the clinical selection of appropriate GPC3 detection strategies for targeted therapy.

Artificial intelligence (AI) is profoundly transforming the paradigm of solid tumor drug development. By integrating multi-omics data, spatial transcriptomics, and advanced computational models, AI has significantly accelerated the discovery and validation of new targets, compressing the traditional ten-year research and development cycle to two to three years. Generative AI platforms have optimized small molecule inhibitors, biologics, and messenger RNA vaccines, achieving breakthroughs in overcoming tumor heterogeneity, improving efficacy, and predicting drug resistance. However, clinical translation still faces challenges such as data bias, algorithm transparency, and the validation gap between models and real-world human experience. This review aims to systematically elaborate on the transformative role of AI in solid tumor drug development and to promote interdisciplinary cooperation as well as the construction of ethical frameworks to enable the full realization of precision oncology.

With the widespread application of systemic treatments for hepatocellular carcinoma, liver injury caused by molecular targeted drugs and immune checkpoint inhibitors has become a common clinical problem. The Chinese Society of Hepatology, Chinese Medical Association, organized domestic experts to summarize and analyze adverse liver reactions, as well as advances in the diagnosis and treatment related to systemic therapy for liver cancer, both domestically and internationally. Based on this work, we formulated the “Consensus on the Management of Liver Injury Associated with Targeted Drugs and Immune Checkpoint Inhibitors for Hepatocellular Carcinoma”, aiming to provide practical recommendations and decision-making guidance for clinicians in hepatology and related specialties. This guidance focuses on the monitoring, diagnosis, prevention, and treatment of liver injury during targeted and immune checkpoint inhibitor therapy, ultimately helping more liver cancer patients benefit from targeted immunotherapy.

Macromolecular-based gene delivery systems have emerged as viable alternatives to non-viral vectors for gene therapy due to their versatility, biocompatibility, and capacity to efficiently deliver therapeutic cargo. These systems, primarily based on synthetic and natural polymers, offer significant advantages in terms of safety, controlled gene release, and targeted delivery. This review explores the design and synthesis of macromolecular carriers, focusing on their chemical and physical architectures, which play a key role in improving gene delivery. Catanionic polymers and their derivatives (comb, brush, and star polymers) have been extensively researched for their capacity to condense and protect genetic material. Furthermore, natural polymers like chitosan and hyaluronic acid have been modified to enhance gene delivery capabilities. These macromolecular carriers are engineered to boost circulation time, increase cellular uptake, and facilitate the controlled release of genetic material at the target site. Strategies such as incorporating targeting ligands, stimuli-responsive elements, and reducing cytotoxicity are being pursued to improve the overall efficiency and specificity of these systems. This review highlights the current state of macromolecular gene delivery systems, their applications, and the ongoing research aimed at overcoming existing challenges, paving the way for more effective non-viral gene therapies.

Chronic hepatitis B virus (HBV) infection remains a major cause of liver diseases, including cirrhosis and hepatocellular carcinoma. Reliable biomarkers for assessing viral replication, liver damage, and predicting clinical outcomes are essential for effective patient management. This review focuses on two promising biomarkers: serum HBV RNA and hepatitis B core-related antigen, both of which show strong correlations with viral replication and disease progression. Serum HBV RNA levels reflect the quantity and transcriptional activity of intrahepatic covalently closed circular DNA, providing insights into viral replication. They also correlate with other markers of replicative activity and have predictive value for key clinical outcomes, including hepatitis B e antigen and hepatitis B surface antigen seroconversion, relapse after therapy cessation, and liver fibrosis. Similarly, hepatitis B core-related antigen is closely associated with covalently closed circular DNA levels, correlates with markers of viral replication, and shows promise in predicting liver fibrosis, cirrhosis, and the risk of hepatocellular carcinoma. This review highlights the potential of both biomarkers for monitoring disease progression and guiding therapeutic decisions, particularly in the context of personalized treatment strategies and risk assessment for liver-related complications.

Acute liver failure (ALF) is a disorder with various etiologies. Although the causes leading to this disruptive condition are well documented in published ALF cohorts, there is significant concern among patients who experience ALF with indeterminate causes, an issue requiring thorough analysis. This review aimed to analyze cohort studies on ALF with a focus on unknown causes leading to classification as indeterminate ALF. The analysis revealed that, among 67 worldwide adult and pediatric ALF cohorts, indeterminate causes of ALF ranged from 2% to 100%, with an average of 30%. Among the 13 pediatric ALF cohorts, the corresponding range was 22% to 100%, with an average of 47%, while among the 55 adult ALF cohorts, the range was 2% to 78%, with an average of 26%. The percentage values were higher in pediatric cohorts due to the higher incidence of rare genetic causes compared to adult patients. Notably, higher rates of indeterminate causes were found in cohorts studied before the availability of diagnostic serologic screening parameters and polymerase chain reaction techniques for various hepatitis virus infections. Patients with indeterminate ALF may not have received a specific treatment that, if effective, could have helped prevent liver transplantation. It is concluded that, in future cases, all efforts must be undertaken to clearly establish the cause of severe liver injury, enabling effective therapy when available and helping reduce the risk of progression to ALF and the need for liver transplantation.

Celiac disease is a chronic, immune-mediated enteropathy precipitated by gluten exposure in genetically predisposed individuals, with a global prevalence of approximately 1%. Though diagnostic workflows incorporate serologic techniques with both histologic and genetic evaluation, each approach carries key pitfalls that contribute to diagnostic inaccuracy. Serology testing is limited by selective immunoglobulin A deficiency and low-titer antibodies, in addition to interlaboratory variability of calibration standards and specimen concentrations. While duodenal biopsy is considered the gold standard for celiac diagnosis, patchy villous atrophy (e.g., ultrashort celiac disease) mimics other enteropathies, and the inherent subjectivity of histologic interpretation can compromise accuracy. Furthermore, celiac predisposition is highly correlated with two human leukocyte antigen (HLA) alleles, HLA-DQ2 and HLA-DQ8. However, nearly 30–40% of the general population expresses one of these alleles, thus introducing the risk of overdiagnosis and limiting the practical implications of genetic testing. There exist special celiac presentations, such as seronegative or potential celiac disease, overlap syndromes, and enteropathy-associated T-cell lymphoma, that introduce additional challenges to diagnostic success. The serologic-histologic discordance and nonspecific symptoms associated with these cases may require divergence from the traditional workflow, as well as supplemental investigations, such as a gluten challenge or breath testing, to confirm a celiac diagnosis. These challenges in celiac diagnosis have driven research into novel biomarkers and molecular assays that can not only enable earlier, more accurate detection but also provide longitudinal disease monitoring. Such markers include intestinal fatty acid-binding proteins, specific microRNA expression, and microbiome signatures that are strongly linked to celiac disease, which may one day serve as adjunctive screening tools to optimize diagnostic yield. This narrative review identifies the key pitfalls in adult celiac disease diagnosis — from pre-analytic serology issues to patchy histology and overinterpretation of HLA — and proposes a guideline-aligned, stepwise algorithm (with emerging biomarkers) to enhance accuracy and reduce missed or delayed cases. Ultimately, continued refinement of a comprehensive, multimodal diagnostic strategy that can integrate with emerging molecular tools is necessary for overcoming the current limitations of individual approaches to celiac diagnosis.

Glioblastoma (GBM) is the most prevalent and aggressive form of primary brain malignancy in adults. Despite continuous advancements in standard treatment modalities, the prognosis for patients remains extremely poor, with a median survival of less than two years. In recent years, chimeric antigen receptor T-cell (CAR-T) therapy has achieved revolutionary success in hematologic malignancies, marking a significant breakthrough in the field of immunotherapy. However, the successful application of CAR-T therapy to GBM still faces dual challenges: antigen heterogeneity and the immunosuppressive tumor microenvironment. This review systematically summarizes these challenges encountered in CAR-T therapy for GBM and the innovative strategies currently under development to address these challenges, providing insights for the future clinical translation of CAR-T therapy in GBM.