Objectives: Osteoporosis is a silent disease with low screening rates in many developing countries. This study aimed to evaluate the feasibility of using an artificial intelligence (AI)-based system to screen osteoporosis from pelvic and hip radiographs in Vietnam. Methods: We conducted a cross-sectional study at a tertiary medical center in Central Vietnam in 2023. A total of 2000 consecutive pelvic and hip radiographs from patients aged ≥ 40 years were collected. After excluding poorquality images, 1987 radiographs were analyzed using an AI-based software designed to estimate bone mineral density (BMD) from plain radiographs and derive T-scores. Osteoporosis was defined as a T-score ≤ − 2.5. Patient characteristics, radiographic findings, and risk factors for osteoporosis were analyzed. Results: Among 1987 patients (mean age 66.4 ± 15.1 years; 41.3% men), osteoporosis was identified in 872 patients (43.9%). The prevalence increased with age and was higher in women than in men (58.7% vs 22.8%, P < 0.001). Osteoporosis was associated with femoral neck (OR = 3.8, 95% CI: 2.7–5.2) and intertrochanteric fractures (OR = 7.0, 95% CI: 4.5–11.0). Patients with lower T-scores had a higher risk of hip fractures, especially those with T-scores ≤ − 3.0 (OR = 11.5, 95% CI: 5.5–24.5). Conclusions AI-based analysis of pelvic and hip radiographs is a feasible and effective tool for osteoporosis screening in Vietnam. The prevalence of osteoporosis in this hospital-based setting was high, particularly among elderly women.AI-assisted screening may offer an accessible strategy for early detection of osteoporosis in resource-limited settings.

Autophagy is a conserved catabolic process that degrades proteins and damaged organelles to maintain cellular homeostasis, and its role in cancer depends on stage and context. Farnesyl-diphosphate farnesyltransferase 1 (FDFT1) is an essential enzyme in the sterol branch of the mevalonate pathway, but its functions in hepatocellular carcinoma (HCC) and in the regulation of autophagy remain poorly understood. In this study, we show that FDFT1 acts as a negative regulator of autophagy in HCC cells. Loss of FDFT1 led to increased autophagosome formation and fusion with lysosomes, whereas its overexpression suppressed both basal and induced autophagy. These changes were associated with AMPK–ULK1 signaling, suggesting that FDFT1 influences a central pathway controlling autophagy. Our findings connect cholesterol metabolism with autophagy regulation and tumor growth, highlighting FDFT1 as a potential prognostic marker and therapeutic target in liver cancer.

Background: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, largely because of challenges in early diagnosis and the limited sensitivity of conventional biomarkers. Therefore, reliable molecular tools for early detection, prognostic stratification, and individualized treatment predictions are urgently required. Methods: This retrospective study analyzed publicly available gene expression datasets. Candidate biomarkers were identified from the GSE14520 cohort using a multistep screening workflow that integrated differential expression analysis, diagnostic performance, and prognostic relevance. A 10-gene diagnostic model was constructed using least absolute shrinkage and selection operator logistic regression and subsequently validated across multiple independent cohorts. Survival outcomes were evaluated using the Kaplan-Meier analysis and treatment responses to sorafenib and transarterial chemoembolization (TACE) were assessed using receiver operating characteristic analysis. Results: A 10-gene signature (TOP2A, CDK1, CYP3A4, MASP2, EPHX2, HAO1, RACGAP1, GLYAT, ADH1B, and CYP4A11) was established. The model demonstrated robust internal performance and consistent accuracy across external validation cohorts (area under the curve [AUC], >0.9). This signature effectively identified early-stage HCC and distinguished malignancy from cirrhosis. High-risk scores were significantly associated with poor overall survival and recurrence-free survival (p<0.05). Furthermore, the model could predict treatment sensitivity, with higher risk scores associated with better outcomes for sorafenib (AUC, 0.791), whereas lower risk scores correlated with an improved response to TACE (AUC, 0.768). Conclusion Our gene expression-based machine learning model provides a robust tool for HCC diagnosis, prognosis, and treatment response prediction, with potential as a supportive system for personalized clinical decision-making.

Background: Nonalcoholic fatty liver disease, a progressive condition caused by the accumulation of fat in the liver, begins with simple steatosis and can potentially progress to metabolic dysfunction-associated steatohepatitis (MASH) in the presence of inflammation and fibrosis, ultimately leading to cirrhosis or hepatocellular carcinoma. Increasing evidence indicates that sodiumglucose cotransporter 2 (SGLT2) inhibitors effectively alleviate MASH in mouse models. However, there is a lack of research on the effects of enavogliflozin on liver disease. In the present study, we investigated the effects of SGLT2 inhibitors on MASH induced by a high-fat, high-cholesterol (HFHC) diet in mice. Methods: Male C57BL/6 mice were fed a normal chow diet, HFHC diet, or HFHC diet with enavogliflozin for 12 weeks. LX-2 and HepG2 cells were treated with enavogliflozin in the presence of various pathological stimuli. Results: The HFHC diet induced excessive hepatic lipid accumulation, inflammation, and severe fibrosis. Administration of enavogliflozin not only ameliorated hepatic steatosis and fibrotic conditions but also suppressed the production of inflammatory cytokines. Positive outcomes were also observed in in vitro experiments, where enavogliflozin demonstrated the ability to impede the activation of hepatic stellate cells and alleviate lipid accumulation in hepatocytes. The potential pathway through which enavogliflozin attenuated liver fibrosis development may be associated with the transforming growth factor β1/Smad signaling pathway. Conclusion Our results suggest that enavogliflozin is effective in a mouse model of MASH by attenuating hepatic steatosis, suppressing inflammation, and improving liver fibrosis.

BACKGROUND: Acellular tubular artery scaffolds offer structural support for vascular regeneration but are inherently limited by poor anticoagulant properties, which increases the risk of thrombus formation following implantation. This thrombogenicity remains a major obstacle to their clinical application, particularly in small-diameter vascular grafts. METHODS: To address this challenge, the present study investigates the use of the Layer-by-Layer (LbL) assembly technique for heparin immobilization under low-speed rotation. Utilizing a roller tube system, heparin was immobilized onto decellularized scaffolds through electrostatic interactions facilitated by a DHI-based linker. This low-speed rotation LbL approach enhanced the uniformity and stability of heparin deposition compared to traditional static methods. One, 4, 7, 10, 13 deposition cycles were performed to achieve optimal heparin loading, resulting in scaffolds capable of sustained heparin release over 28 days. RESULTS: The heparinized scaffolds exhibited an initial burst release (approximately 80%), followed by a sustained phase with 18.24% ± 0.242 remaining to support prolonged anticoagulant activity. Importantly, the modified scaffolds significantly reduced thrombus formation and exhibited minimal hemolytic activity, indicating improved hemocompatibility. In addition to their antithrombotic properties, the scaffolds also promoted endothelial cell adhesion, which is critical for restoring vascular integrity, regulating vascular tone, and maintaining long-term patency. CONCLUSION These findings highlight the efficacy of roller-assisted LbL heparinization as a practical and scalable strategy to enhance the blood compatibility of acellular vascular grafts. This method holds considerable promise for addressing thrombogenicity in vascular tissue engineering and advancing the clinical translation of bioengineered vascular constructs.

Background: While advanced age is a known risk factor for postoperative complications following hip arthroplasty, its role as an independent predictor versus a surrogate for comorbidity remains unclear, particularly in developing countries. This study aimed to investigate the independent impact of age on postoperative outcomes and explore the mediating role of key comorbidities in a resource-limited setting. Methods: We retrospectively reviewed 769 adult patients undergoing hip arthroplasty at a Vietnamese tertiary hospital (2021–2024), categorized into three groups: younger adults (18–64 years), older adults (65–79 years), and oldest old (≥80 years). The primary outcome was a composite of major postoperative complications. Multivariable logistic regression and structural equation modeling were used to identify independent predictors and assess mediation effects. Results: Among 769 patients, 363 were younger (47.2%), 241 older adults (31.3%), and 165 oldest old (21.5%). Complication rates increased significantly with age (18.7%, 36.9%, and 60.0%, respectively; p<0.001). However, multivariable adjustment showed that age was not an independent predictor. Instead, heart failure (adjusted odds ratio [aOR]=5.49, 95% confidence interval [CI] 2.19–13.74) and preoperative anemia (aOR=1.77, 95% CI 1.21– 2.59) were identified as independent risk factors. Mediation analysis revealed that the effect of age on complications was significantly mediated through preoperative anemia. Conclusion Increased postoperative risk in older adults is driven by comorbidity burden rather than chronological age. Preoperative anemia and heart failure are critical, independent predictors, with anemia acting as a key mediator for the effects of age. Individualized correction of modifiable comorbidities may be more beneficial than using age alone to assess surgical risk.

The RET gene point mutation is the main molecular alteration involved in medullary thyroid carcinoma (MTC) tumorigenesis. Previous studies in Vietnam mainly consisted of case reports, with limited data on larger sample sizes. In this study, we investigated RET gene mutations in exons 10, 11, and 16 and analyzed clinicopathological features of a series of Vietnamese MTC patients. Methods: We collected 33 tissue samples from patients with MTC and analyzed RET mutations using the Sanger sequencing method. The relationship between hotspot RET mutations (exons 10, 11, 16) and clinicopathological features were investigated. Results: Among the 33 analyzed cases, 17 tumors (52%) harbored RET mutations in exon 10, 11, or 16. A total of 10 distinct genetic alterations were identified, including eight missense mutations and two short indels. Of these, seven were classified as pathogenic mutations based on previous publications, with p.M918T being the most frequent (4 cases), followed by p.C634R (3 cases) and p.C618R (3 cases). Mutations were significantly associated with specific histological patterns, such as the nested/insular pattern (p=.026), giant cells (p=.007), nuclear pleomorphism (p=.018), stippled chromatin (p=.044), and amyloid deposits (p=.024). No mutations were found in germline analyses, suggesting these were somatic alterations. Conclusions: Our results provided the first comprehensive analysis of RET mutations in Vietnamese MTC patients. The most frequent mutation was p.M918T, followed by p.C634R and p.C618R. Mutations in these three exons were linked to specific histopathological features. Information on mutational profiles of patients with MTC will further aid in the development of targeted therapeutics to ensure effective disease management.

Objectives: Vertebral fractures are associated with disability and mortality, but most vertebral fractures are asymptomatic. The present study aimed to determine the incidence of and develop a predictive nomogram for asymptomatic vertebral fractures in Vietnamese adults. Methods: This cohort study as a part of the Vietnam Osteoporosis Study involved 168 men and 287 women aged 50 years and older without a clinically diagnosed vertebral fracture. Their spine x-rays were taken at the recruitment and subsequent 2-year visit. Vertebral fractures were ascertained using the Genant’s semiquantitative method. We employed the Bayesian Model Averaging method to search for the optimal model for predicting asymptomatic vertebral fractures. A predictive nomogram was also developed to facilitate risk prediction. Results: During a median of 2.38 years of follow-up, 13 men and 16 women developed an asymptomatic vertebral fracture, yielding the overall incidence rate of 28 fractures per 1000 person-years, or 33 fractures/1000 personyears in men and 24 fractures/1000 person-years in women, respectively. Most asymptomatic vertebral fractures were moderate, almost 1.5 times more common than mild fractures. The optimal model for predicting incident asymptomatic vertebral fractures included age, male sex and lower femoral neck T-score. The area under the receiver’s operating characteristic curve was 0.91, with 95% CI ranging from 0.86 to 0.96. Conclusions Asymptomatic vertebral fractures were relatively common among adults in Vietnam. A simple model with sex, age and femoral neck T-score is helpful for selective screening of asymptomatic vertebral fractures in Vietnamese individuals.

Alport syndrome (AS) is a hereditary nephropathy characterized by progressive kidney damage that commonly leads to endstage kidney disease. Early diagnosis is critical, as preemptive nephroprotective therapy, such as angiotensin-converting enzyme inhibitors, can significantly delay disease progression. However, the early diagnosis of AS remains challenging due to the lack of reliable preclinical or screening biomarkers, particularly before the onset of proteinuria. Although nonspecific microhematuria is often present, it is insufficient for definitive early detection. Recent studies have identified potential early cellular alterations as candidate biomarkers for the preclinical detection of AS, but none have been widely implemented in clinical practice. This review presents the current knowledge on early biomarkers of kidney damage for AS, highlights promising avenues for future research, and emphasizes the importance of developing effective diagnostic tools to enable timely intervention and improve patient outcomes.

Objective: This study aimed to develop a configurable clean room paradigm with low air pressure for assisted reproductive technology (ART) clinics and demonstrate the concept’s efficacy using in vitro fertilization (IVF) treatment. Methods: A high-standard clean room system with positive pressure (13 Pa) was built using accessible materials and equipment for ART laboratories. Methods for controlling and evaluating the clean room’s characteristics were developed and implemented for quality assessment and calibration to maximize efficiency. The feasibility of the flexible clean room concept was assessed by analyzing the key performance indicators of embryo culture and IVF treatment. Results: After 3 weeks of testing, the concentration of particles ≥0.5 μm was 6.04 times lower than the International Organization for Standardization (ISO) class 5 standard (3,520 particles/m3) in the IVF laboratory. Air pressure, noise, temperature, and humidity were controlled stably and appropriately. Five days after installation and handover, the volatile organic compound concentration dropped to 0.00 ppm. With blastocysts and a respectable blastocyst rate, embryonic culture with female patients younger than 40 matched the criteria (63.5% and 38.9%, respectively). After vitrified blastocysts were transferred, the pregnancy and implantation rates were 58.5% and 36.2%, respectively, demonstrating a high degree of treatment success. Conclusion Our customizable, high-quality, low-air-pressure clean room model can be implemented to achieve positive outcomes for infertility treatment.