ObjectiveBiochemistry and Molecular Biology, a discipline that elucidates life phenomena at the molecular level, serves as a core foundational course in medical education. It provides the theoretical basis for studying other basic and clinical medical subjects, as well as for understanding pathogenesis, disease diagnosis, and treatment. However, its complex content and highly abstract concepts have posed a dual challenge to traditional teaching models: “inefficient instruction” and “inadequate learning outcomes”. Within limited classroom hours, how to engage students and stimulate their intrinsic motivation, and how to help them recognize, understand, and develop a passion for biochemistry from the perspective of the discipline’s essence, have long been key focuses of curriculum research. MethodsUsing the lipid metabolism chapter as an example, this study employs “Rain Classroom”, a generative artificial intelligence (AI)-assisted platform, to support education in four dimensions: teaching, learning, evaluation, and research. In teaching, it assists instructors through virtual experiments, lesson preparation support, knowledge mapping, and assignment design. For learning, it serves as an intelligent study assistant for students, providing automated assignment review, enabling educational resource sharing, and facilitating personalized learning pathways. In evaluation, the platform automates assignment grading, analyzes student performance data, and offers diagnostic feedback and teaching recommendations. In research, it aids educators in collecting and analyzing teaching data, as well as searching for and summarizing relevant literature. ResultsThe results indicate that an educational model integrating teacher-led instruction, student-centered learning, and generative AI assistance significantly enhances teaching quality, students’ self-directed learning abilities, and knowledge mastery. Furthermore, with the support of generative AI, curriculum-based ideological education—focusing on cutting-edge disciplinary advances and topical medical issues—helps cultivate students’ medical spirit of “honoring life and healing the wounded”, thereby fostering the establishment of appropriate professional values. Finally, while generative AI presents both opportunities and challenges for higher education, this study also analyzes potential risks in its teaching applications, emphasizing the need for both instructors and students to avoid over-reliance and to ensure that technological tools consistently serve the fundamental goals of education. ConclusionThis study demonstrates that integrating generative AI, specifically via the “Rain Classroom” platform, can effectively enhance biochemistry education. By supporting teaching, learning, evaluation, and research, this approach improves both educational effectiveness and student outcomes. It also facilitates the incorporation of cutting-edge knowledge and professional ethics, nurturing a patient-centered mindset. Additionally, the study addresses potential implementation risks to ensure that such technological tools remain aligned with the core purpose of education.

Background: and Purpose Vertebrobasilar fusiform aneurysms (VBFAs) carry substantial morbidity and mortality, but optimal management for unruptured VBFAs remains unclear. We compared the safety and efficacy of conservative management (CM), stent-assisted coiling (SAC), and flow diverters (FDs) in patients with unruptured VBFAs, focusing on long-term prognosis. Methods: This study included data from a nationwide Chinese cohort of patients with vertebrobasilar dissecting aneurysms. Inverse probability of treatment weighting (IPTW) balanced confounders across groups. The primary outcome was poor prognosis (modified Rankin Scale score >2). Secondary outcomes included aneurysm rupture, ischemic stroke, compression symptoms, and VBFA-related deaths. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup and sensitivity analyses were performed. Results: Among 1,115 patients with unruptured VBFAs, 838 (median age, 54 years; 655 men) were included. After IPTW, baseline characteristics were balanced. Median follow-up was 54 months. FD was associated with a lower risk of poor prognosis than CM (OR, 0.48 [95% CI, 0.30 to 0.77]; p=0.002), with no difference between CM and SAC. FD also reduced aneurysm rupture (OR, 0.20 [95% CI, 0.07 to 0.60]; p=0.004) and compression symptoms (OR, 0.30 [95% CI, 0.13 to 0.68]; p=0.004) versus CM. Time-to-event analyses further revealed significant differences in vertebral artery lesions and Type I–II VBFAs, whereas no significant differences were observed in basilar or vertebrobasilar junction lesions or in Type III–IV VBFAs. Conclusions Compared with CM, FD was associated with improved long-term outcomes in unruptured VBFAs, particularly in vertebral artery lesions and Type I–II VBFAs, although residual confounding cannot be excluded.

With the rapid development of social economy and the continuous improvement of human living standard, the incidence, fatality and recurrence rates of cardiovascular disease (CVD) are increasing year by year, which seriously affects people's life and health. Conventional therapeutic drugs have limited improvement on the disability rate, so the search for new therapeutic drugs and action targets has become one of the hotspots of current research. In recent years, the therapeutic role of the natural compound rosmarinic acid (RA) in CVD has attracted much attention, which is capable of preventing CVD by modulating multiple signalling pathways and exerting physiological activities such as antioxidant, anti-apoptotic, anti-inflammatory, anti-platelet aggregation, as well as anti-coagulation and endothelial function protection. In this paper, the role of RA in the prevention of CVD is systematically sorted out, and its mechanism of action is summarised and analysed, with a view to providing a scientific basis and important support for the in-depth exploration of the prevention value of RA in CVD and its further development as a prevention drug.

This review briefs the anti-hyperuricemia(HUA)mechanism of nutrition targeting the gut,such as the gut microbiota promoting the catabolism of purine and uric acid(UA),and increased its metabolites like uric acid.The review also summarizes the probiotics and prebiotics that have the effect of lowering uric acid targeting at the gut,providing reference and guidance for further research.In addition,this paper reviews the effects of various di-ets,such as the dietary approaches to stop hypertension(DASH)diet,the Mediterranean diet,and the low-purine diet,as well as the effects of individual foods including alcohol,coffee and tea,cherries,dairy products,fructose,and vitamin C on hyperuricemia and gout outcomes.

Objective To investigate the diagnostic value of magnetic resonance imaging(MRI)-based intratumoral and peritumoral radiomics of prostate cancer(PCa)for bone metastases.Methods A total of 211 patients diagnosed with PCa by biopsy pathology at Gansu Provincial People's Hospital from January 2018 to January 2023 were retrospectively analyzed.These patients were randomly divided into a training set(n=147)and a validation set(n=64)in a 7:3 ratio.Regions of interest(ROIs)were delineated from the patients'T2-weighted imaging(T2WI),diffusion-weighted imaging(DWI),and apparent diffusion coefficient imaging(ADC)sequences to extract radiomic features.Z-score(normalization)and the LASSO algorithm were used for feature dimensionality reduction,selection,and construction.A predictive model was then built using a logistic regression(LR)machine learning classifier.The receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to assess the model's performance.Calibration curves and decision curves(DCA)were plotted to evaluate the model's fit and clinical net benefit.Results Radiomic features were extracted from the tumor and peritumoral regions in each patient's T2WI,DWI,and ADC images,with a total of 312 features from each region.The LASSO regression model ultimately identified 10 intratumoral radiomic features closely related to bone metastasis,including 2 T2 sequence features,7 DWI features,and 1 ADC sequence feature;and 9 peritumoral radiomic features,including 4 T2 sequence features,3 DWI features,and 2 ADC sequence features.The predictive model based on intratumoral radiomic features achieved an AUC of 0.845(95%CI 0.747-0.943),while the predictive model based on peritumoral radiomic features had an AUC of 0.818(95%CI 0.716-0.919).A combined nomogram model incorporating intratumoral features,peritumoral radiomic features,and clinical features(including Gleason score,total prostate specific antigen,and body mass index)yielded an AUC of 0.936(95%CI 0.902-0.970).Calibration curves indicated that the combined model had good fit,and DCA demonstrated that the combined model provided better clinical net benefit.Conclusions Peritumoral radiomics has excellent predictive value for bone metastasis in newly diagnosed PCa.Combining with intratumoral radiomics features and clinical features,it significantly enhances the predictive capability of the model.

Objective To explore the effects of different glucose concentrations on the synthesis and secretion of bone collagen in osteoblasts and the impact of diabetes on bone quality in mice.Methods(1)Primary osteoblasts were extracted from the skulls of neonatal mice via collagenase digestion and cultured in four groups under different glucose concentrations:normal glucose(5.5 mmol/L),moderate glucose(11.5 mmol/L),moderate-high glucose(16.5 mmol/L),and high glucose(25 mmol/L).EdU staining was performed to evaluate cell proliferation,while the Transwell assay was used to assess cell migration.Immunofluorescence and Western blotting were performed to detect and quantitatively analyze the content of type Ⅰ collagen(Col-1).Alizarin red S(ARS)staining and alkaline phosphatase(ALP)staining were applied to assess the effects of different glucose concentrations on osteogenic differentiation.(2)Six-week-old male C57BL/6 mice were randomly divided into control group and model group(5 in each group).The model group was fed a high-fat diet for 4 weeks followed by streptozotocin(STZ)injection to establish a diabetic mouse model.The osteogenic differentiation capacity of primary osteoblasts from both groups was assessed.(3)Micro-computed tomography(Micro-CT)was employed to analyze femoral bone mineral density(BMD),bone volume/tissue volume(BV/TV),trabecular number(Tb.N),and trabecular separation(Tb.Sp).Three-point bending test was conducted to evaluate mechanical parameters including maximum load,Young's modulus,fracture energy,and stiffness.RT-qPCR was employed to assess the expression of osteogenic differentiation genes(Alp,Opn,Col1a1,and Lox).Masson staining and Mallory staining were used to evaluate Col-1 content in trabecular bone.Results(1)EdU and Transwell assay results demonstrated that with the gradual increase in glucose concentration,the proliferation and migration abilities of osteoblasts were significantly decreased(P<0.001),and the protein expression levels of Col-1 and lysyl oxidase(LOX)were significantly reduced(P<0.01 or P<0.001).ARS and ALP staining revealed that calcium salt deposition and ALP activity in osteoblasts were significantly decreased with increasing glucose concentration(P<0.05 or P<0.001).(2)Compared with control group,mice in model group exhibited typical"three polies and one weight loss"symptoms(polyuria,polydipsia,polyphagia,and weight loss)of diabetes,and ARS and ALP staining showed a significant reduction in osteoblasts(P<0.001).(3)Micro-CT and three-point bending test results indicated that,compared with control group,mice in model group showed microarchitectural deterioration of bone,decreased Tb.N,increased Tb.Sp,and significantly reduced maximum load,Young's modulus,fracture energy,and stiffness(P<0.05).RT-qPCR results showed that the relative mRNA expression levels of osteogenic differentiation genes(Alp,Opn,Col1a1,and Lox)were significantly decreased in model group compared with control group(P<0.01 or P<0.001).Masson and Mallory staining indicated a significant reduction in collagen content in model group compared with control group(P<0.01).Conclusions High-glucose environment inhibits osteoblast proliferation,differentiation,and migration.Diabetic mice exhibit reduced bone quality and increased bone fragility,potentially mediated by decreased lysyl oxidase and collagen levels.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

Total knee arthroplasty(TKA)is mainly used for the treatment of advanced knee osteoarthritis.Accurate preoperative planning and rapid prosthesis recognition are essential for smooth operation and postoperative rehabilitation.However,manual prosthesis recognition rely on doctors'experience,easily leading to misdiagnosis or missed diagnosis.Recent years,artificial intelligence(AI)had been integrated with medical imaging,represented by machine learning(ML)and its branch deep learning(DL),and displayed relatively powerful auxiliary functions in TKA.The research status and application progresses of AI combined with imaging in TKA were reviewed in this article.

AIM To establish a GC-MS/MS method for the analysis of volatile components in Yinhu Ganmao Powder,and to determine the contents of α-pinene,camphene,sabinene,β-pinene,α-terpinene,(+)-limonene,p-cymene,1,8-cineole,linalool,L-menthol,terpinen-4-ol,DL-menthol,α-terpineol,tridecane,pulegone,caryophyllene,humulene,n-hexadecane and patchouli alcohol.METHODS The analysis was performed on a DB-624 UI capillary column(30 m×0.25 mm×1.40 μm ),and electron ionization source was adopted with multiple reaction monitoring mode.RESULTS Fifty volatile components and twenty-five liposoluble components were identified in volatile oils and medicinal material powder,respectively.Nineteen constituents showed good linear relationships within their own ranges(r ≥ 0.999 0),whose average recoveries were 84.43％-113.31％with the RSDs of less than 9.15％.CONCLUSION This stable,accurate and reproducible method can provide a reference for the quality evaluation of Yinhu Ganmao Powder.

Acute symptomatic osteoporotic thoracolumbar compression fracture (ASOTLF) can lead to chronic low back pain, kyphosis deformity, pulmonary dysfunction, loss of mobility, and even life-threatening complications. Vertebral augmentation is currently the mainstream treatment method for this condition. In 2019, the Editorial Board of Chinese Journal of Trauma and the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association collaboratively led the development of Clinical guideline for vertebral augmentation for acute symptomatic osteoporotic thoracolumbar compression fractures. Six years later, with advances in clinical diagnosis and treatment techniques as well as accumulating evidence in related fields, the 2019 guideline requires updating. To this end, the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association, the Spinal Health Professional Committee of China Human Health Science and Technology Promotion Association, and the Minimally Invasive Orthopedics Professional Committee of Shaanxi Medical Doctor Association have organized experts in the field to develop the Clinical guideline for vertebral augmentation of acute symptomatic osteoporotic thoracolumbar compression fractures ( version 2025) , based on the latest evidence-based medical researches. This guideline incorporates 3 recommendations retained from the 2019 version with updated strength of evidence, along with 12 new recommendations. It provides recommendations from six aspects of diagnosis, pain management, treatment option selection, prevention of postoperative complications, anti-osteoporosis therapy, and postoperative rehabilitation, aiming to provide a reference for standard treatment of vertebral augmentation for ASOTLF in hospitals at all levels.