Pham Ngoc Thach University of Medicine

Osteoporosis is a major and growing health concern in the Asia-Pacific region, y et it remains widely underdiagnosed and undertreated due to limited access to dual-energy X-ray absorptiometry (DXA) in many areas. Artificial intelligence (AI) offers new opportunities to improve osteoporosis screening and management, but unvalidated tools pose risks of inconsistent care. This consensus was developed to provide regionally harmonized guidance on the safe, effective, and equitable use of AI in osteoporosis care. Purpose The aim of this work was to establish expert consensus recommendations on the role of AI in osteoporosis screening and management in the Asia-Pacific region. Key objectives were to define appropriate applications of AI (e.g., imaging-based bone assessment and fracture risk prediction) and specify minimum standards for validation and reporting, addressing region-specific implementation challenges and ensuring that AI use aligns with clinical guidelines and ethical principles. Methods This consensus was developed through multidisciplinary collaboration among experts across the Asia-Pacific region. Each participant reviewed draft statements, contributed feedback during virtual meetings, and provided insights based on clinical experience and current evidence. Consensus was reached iteratively until full agreement was achieved for all statements. The process integrated global best practices and regional adaptations, drawing from peer-reviewed studies, international AI guidelines, and local fracture registry data. The final recommendations emphasize the validation, transparency, and ethical implementation of AI within regional healthcare systems, ensuring compatibility with local regulations. Ultimately, twelve consensus statements were established to guide the responsible use of AI for osteoporosis screening and management in the Asia-Pacific region. Results The panel produced 12 consensus statements covering the role of AI as an adjunct for opportunistic osteoporosis screening rather than a diagnostic tool, requirements for imaging quality and AI model transparency, standards for validation and performance reporting, integration of AI with clinical risk stratification, demonstration of clinical utility in real-world settings, adherence to data protection laws and ethical AI principles, training of clinicians in AI use, strategies for implementation and monitoring (including post-market surveillance and feedback loops), and recognition of technical, clinical, and equity limitations of AI. All 12 statements give extensive recommendations for using AI to improve osteoporosis management while ensuring patient safety, accuracy, and equity. Conclusion This first Asia-Pacific consensus on AI in osteoporosis concludes that AI, when appropriately validated and implemented, can help bridge the osteoporosis care gap by identifying high-risk patients who would otherwise remain undiagnosed, thus facilitating earlier intervention. It emphasizes that AI should complement-not replace-standard diagnostic methods and clinical judgment. The guidance emphasizes validation, transparency, and ethical oversight to facilitate early intervention while minimizing risks associated with unvalidated or premature AI adoption.

Measles remains a highly infectious viral disease and continues to pose a major global public health concern, with recurrent outbreaks occurring despite the implementation of effective vaccination strategies. This review examines multifactorial drivers of current measles outbreaks, summarises current recommendations for the standard two-dose measles-containing vaccine schedule, and evaluates emerging immunological evidence regarding the administration of a third dose. Some studies indicate that a third measles-containing vaccine dose can result in an enhanced response for both humoral and cellular immune responses among individuals with declining antibody levels. However, existing evidence is largely derived from small, context-specific studies and does not yet demonstrate durable clinical protection or population-level impact on measles transmission. Consequently, the role of a routine third dose remains uncertain. In conclusion, addressing the multifactorial drivers of measles resurgence, including strengthening two-dose vaccination coverage, reducing vaccine hesitancy, improving surveillance, and closing immunity gaps, remains the primary priority for measles control. A third dose may be considered as an investigational strategy, but further large-scale epidemiologic and effectiveness data are needed before any policy implementation can be considered.

Alcoholic beverages have been concerned not only for gastronomic delight but also for certain impacts on health, such as obesity, diabetes, and cardiovascular diseases. In this study, we assessed the bioactive functions of 1,1-Diethoxyethane (1,1-DEE), a flavoring compound formed during the aging process of wine by flor yeast, using both cultured cell lines and a high-fat diet (HFD) mouse model. 1,1-DEE was identified in the batches of ethanol that induced oxidation of phosphatase and tensin homolog deleted on chromosome 10 (PTEN) using gel mobility shift assay and gas chromatography-mass spectrometry. PTEN was reversibly oxidized when exposed to 1,1-DEE, but 1,2-DEE did not induce PTEN oxidation. Mechanistically, 1,1-DEE treatment enhanced the production of mitochondrial reactive oxygen species, accompanying by oxidation of PTEN and subsequent activation of Akt signaling. 1,1-DEE treatment elevated Akt activation when combined with insulin, compared with insulin alone, and alleviated palmitate-induced insulin resistance in C2C12 myoblasts. Moreover, the oral administration of 1,1-DEE alleviated glucose intolerance and insulin resistance in HFD-fed mice. 1,1-DEE also mitigated HFD-induced body weight gain and hepatic dyslipidemia without reduction of food intake. Transcriptome analysis revealed significant genes involved in the improvement of insulin sensitivity and dyslipidemia. Thus, 1,1-DEE may serve as a promising therapeutic agent for the intervention of obesity, diabetes, and dyslipidemia.

Background:Chronic obstructive pulmonary disease (COPD) poses a significant health burden in Vietnam. The TNF-α rs1800629 (-308G/A) polymorphism is an influential factor in disease pathogenesis. However, its association is inconsistent across the studied populations. This study addresses this gap in Vietnam by examining allele frequencies and clinical associations in stable COPD patients. Methods:A cross-sectional study recruited 320 healthy controls and 266 stable COPD patients (per GOLD 2023 criteria) from October 2024 to August 2025. Clinical data were collected from medical records and direct interrogation. Genotyping was performed using PCR-RFLP. The dataset used for sensitivity analyses (2,660 observations) was created through multiple imputations to address missing clinical data. Associations of the rs1800629 with disease susceptibility and selected clinical management parameters were analyzed using Chi-square/Fisher's exact tests, multivariable logistic regression, and sensitivity analysis. Results:The A allele frequencies were 8.83% (COPD), 6.88% (controls), and 7.77% overall (p > 0.05). Patients were predominantly male smokers over 40 years, with moderate-severe symptoms (CAT ≥10, mMRC 3) and A/B severity groups. Under a recessive model, the AA genotype was associated with ~96% reduced susceptibility (adjusted OR 0.039, 95% CI 0.002-0.62, p=0.022). Regression identified smoking (OR 1.83-2.35), family history (OR 2.04), and onset ≥40 years (OR 2.88-3.36) as independent symptom influences. Sensitivity analysis further supported the protective effect of the AA genotype and revealed GA protective effects on symptomatic outcomes (OR<1, p<0.05). Conclusion:Our findings suggest a possible protective recessive association of the TNF-α rs1800629 (-308G/A) polymorphism with COPD susceptibility, symptom burden, and exacerbation risk. However, the wide confidence intervals arising from the rarity of the AA genotype and the use of multiply imputed data mean these signals are exploratory. Larger multi‑center studies with comprehensive exposure assessment are needed to confirm these observations.

Background:Acute heart failure (AHF) has high early mortality. The FIB-4 index indicates hepatic dysfunction in AHF, but its predictive power for short-term outcomes in developing countries is not well established. Methods:We conducted a prospective cohort study at Can Tho Central General Hospital, Vietnam, from May to December 2024 including adults aged ≥18, hospitalized with AHF and NT-proBNP levels ≥300 pg/mL. Exclusions were for those who died before blood sample collection, transferred, declined consent, or had chronic liver disease, active cancer, or end-stage renal disease. Survivors were followed up via phone for 30 days post-discharge. The primary endpoint was 30-day all-cause mortality. Results:The final analysis included 413 patients (mean age 70, 47.7% male). In-hospital mortality was 5.1% and did not associate to FIB-4. At 30 days post-discharge, 42(17%) of 247 patients with follow-up data died (37.3% loss to follow-up). Non-survivors had higher FIB-4 scores than survivors (3.3 vs. 2.3, p = 0.006). After adjusting for age, sex, comorbidities, LVEF, and NT-proBNP, each one-point increase in FIB-4 raised the 30-day mortality risk by 9% (RR 1.09; 95%CI: 1.01-1.17). A cut-off of 3.1 identified high-risk patients, with a RR of 1.82 (95%CI: 1.03-3.22). FIB-4 demonstrated an AUC of 0.634 (95%CI: 0.535-0.733) which was comparable to NT-proBNP (AUC 0.650; 95%CI: 0.559-0.742). Conclusion:In this exploratory single-center study of patients with AHF, FIB-4 demonstrated an independent association with 30-day mortality, with a threshold of 3.1 identifying high-risk individuals. These findings are hypothesis-generating, and external validation is warranted before FIB-4 can be recommended for risk stratification.