ObjectiveTo investigate the triglyceride-glucose (TyG) index and the level of serum homocysteine (Hcy) in association with the incidence of stroke in type 2 diabetes mellitus (T2DM) patients. MethodsBased on the chronic disease risk factor surveillance cohort in Pudong New Area, Shanghai, excluding those with stroke in baseline survey, T2DM patients who joined the cohort from January 2016 to October 2020 were selected as the research subjects. During the follow-up period, a total of 318 new-onset ischemic stroke patients were selected as the case group, and a total of 318 individuals matched by gender without stroke were selected as the control group. The Cox proportional hazards regression model was used to adjust for confounding factors and explore the serum TyG index and the Hcy biochemical indicator in association with the risk of stroke. ResultsThe Cox proportional hazards regression results showed that after adjusting for confounding factors, the risk of stroke in T2DM patients with 10 μmol·L⁻¹-¹ and Hcy>15 μmol·L⁻¹ was 1.532 times (95%CI: 1.017‒2.309 times, P=0.041) and 1.738 times (95%CI: 1.119‒2.699 times, P=0.014) higher respectively, compared to T2DM patients with Hcy≤10 μmol·L⁻¹. T2DM patients with TyG>9.074 had 1.396 times higher risk of stroke (95%CI: 1.091‒1.787, P=0.008) compared to those with TyG≤9.074. The study found that urea and α1-antitrypsin (α1-AT) were independent risk factors for the incidence of stroke in T2DM patients. For every unit increase in urea andα1-AT, the risk of stroke in T2DM patients increased by 233.6% (HR=3.336, 95%CI: 1.588‒7.009, P=0.001) and 11.3% (HR=1.113, 95%CI: 1.028‒1.205, P=0.008), respectively. Cumulative risk curves showed that Hcy>10 μmol·L⁻¹ and TyG>9.074 accelerated the time to stroke occurrence in T2DM patients. ConclusionElevated levels of Hcy>10 μmol·L⁻¹ and a higher TyG index are risk factors for stroke in T2DM patients. Effective interventions for Hcy and TyG should be conducted for diabetic patients to reduce the incidence of stroke.

OBJECTIVE: To provide the experience and demonstration for the transformation of acupuncture-moxibustion techniques standards from Chinese national standards to international standards. METHODS: Questionnaire research, literature research, semi-structured interviews and expert consultation were used. RESULTS: The safety of acupuncture-moxibustion techniques was evaluated through literature research, and based on the results of the questionnaire survey, expert interviews, and expert consultation, 11 main bodies and structure of the former Chinese national standard, Technical Benchmark of Acupuncture and Moxibustion: General Rules for Drafting, were adjusted and optimized in accordance with the requirements of international standard (including the language, normative references, purpose, scope, applicable environment, target population, work team, terms and definitions, general principles and basic requirements, structural elements and text structure, and compilation process); and the first international standard, World Federation of Acupuncture-Moxibustion Societis (WFAS) Technical Benchmark of Acupuncture and Moxibustion: General Rules for Drafting was formulated to specify the general rules for drafting. CONCLUSION The 3 key questions, "international compatibility", "technical operability" and "safety" should be solved technically on the basis of explicit international requirements. It is the core technical issue during transforming the national standards of technical benchmark of acupuncture and moxibustion into international standards.
Moxibustion/methods* ; Acupuncture Therapy/methods* ; Humans ; Translational Research, Biomedical/standards* ; Surveys and Questionnaires ; China ; Benchmarking/standards*

This research investigated the impact of Ganoderma lucidum polysaccharides(GLP) on hepatoblastoma HepG2 and Huh6 cell models, as well as KM mouse model with in situ transplanted tumors, so as to provide a theoretical basis for the clinical application of GLP. Cell viability was assessed through the CCK-8 assay, whereas cell proliferation was evaluated by using the BeyoClick~(TM)EdU-488 test. Cell apoptosis was visualized via Hochest 33258 staining, and autophagy was detected through Mrfp-GFP-LC3 dual fluorescence staining. An in situ tumor transplantation model was created by using HepG2 cells in mice, and mice were treated with normal saline and GLP of 100, 200, and 300 mg·kg~(-1) for tumor count calculation and size assessment. Hematoxylin-eosin(HE) staining was used to observe pathological changes in tumor tissue and vital organs(liver, kidney, lung, spleen, and heart). Western blot analysis was conducted to measure the protein expressions of tumor protein P53(P53), B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), cleaved-caspase-3, Beclin-1, autophagy related protein-5(Atg-5), microtubule-associated protein-light chain-3Ⅰ(LC3Ⅰ)/LC3Ⅱ, autophagy adapter protein 62(P62), protein kinase B(Akt), p-Akt, mammalian target of rapamycin(mTOR), and p-mTOR. The in vitro experiment revealed that compared with the control group, after GLP treatment, tumor cell viability decreased significantly; apoptosis rate increased in a dose-dependent manner, and autophagic flux was inhibited. The in vivo experiments showed that compared with the model group, mice treated with GLP exhibited significantly fewer and smaller tumors. Western blot results showed that compared with the control group or model group, levels of P53, Bax, cleaved-caspase-3, Beclin-1, Atg-5, and LC3-Ⅱ/LC3-Ⅰ were significantly increased after GLP treatment, and the levels of Bcl-2, P62, p-Akt/Akt, and p-mTOR/mTOR were significantly decreased. These outcomes suggest that GLP promotes apoptosis and autophagy in hepatoblastoma cells by regulating the Akt/mTOR pathway.
Animals ; Humans ; Autophagy/drug effects* ; Reishi/chemistry* ; Mice ; Apoptosis/drug effects* ; TOR Serine-Threonine Kinases/genetics* ; Proto-Oncogene Proteins c-akt/genetics* ; Liver Neoplasms/genetics* ; Hepatoblastoma/genetics* ; Polysaccharides/pharmacology* ; Cell Line, Tumor ; Signal Transduction/drug effects* ; Male ; Cell Proliferation/drug effects* ; Hep G2 Cells

The innate immune sensor NLRP3 inflammasome overactivation is involved in the pathogenesis of ulcerative colitis. PGAM5 is a mitochondrial phosphatase involved in NLRP3 inflammasome activation in macrophages. However, the role of PGAM5 in ulcerative colitis and the mechanisms underlying PGAM5 regulating NLRP3 activity remain unknown. Here, we show that PGAM5 deficiency ameliorates dextran sodium sulfate (DSS)-induced colitis in mice via suppressing NLRP3 inflammasome activation. By combining APEX2-based proximity labeling focused on PGAM5 with quantitative proteomics, we identify NEK7 as the new binding partner of PGAM5 to promote NLRP3 inflammasome assembly and activation in a PGAM5 phosphatase activity-independent manner upon inflammasome induction. Interfering with PGAM5-NEK7 interaction by punicalagin inhibits the activation of the NLRP3 inflammasome in macrophages and ameliorates DSS-induced colitis in mice. Altogether, our data demonstrate the PGAM5-NEK7 interaction in macrophages for NLRP3 inflammasome activation and further provide a promising therapeutic strategy for ulcerative colitis by blocking the PGAM5-NEK7 interaction.

Peptide-based radiopharmaceuticals targeting integrin α5β1 show promise for precise tumor diagnosis and treatment. However, current peptide-based radioligands that target α5β1 demonstrate inadequate in vivo performance owing to limited tumor retention. The use of PEGylation to enhance the tumor retention of radiopharmaceuticals by prolonging blood circulation time poses a risk of increased blood toxicity. Therefore, a PEGylation strategy that boosts tumor retention while minimizing blood circulation time is urgently needed. Here, we developed a PEGylation-enabled peptide multidisplay platform (PEGibody) for PR_b, an α5β1 targeting peptide. PEGibody generation involved PEGylation and self-assembly. [⁶⁴Cu]QM-2303 PEGibodies displayed spherical nanoparticles ranging from 100 to 200 nm in diameter. Compared with non-PEGylated radioligands, [⁶⁴Cu]QM-2303 demonstrated enhanced tumor retention time due to increased binding affinity and stability. Importantly, the biodistribution analysis confirmed rapid clearance of [⁶⁴Cu]QM-2303 from the bloodstream. Administration of a single dose of [¹⁷⁷Lu]QM-2303 led to robust antitumor efficacy. Furthermore, [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 exhibited low hematological and organ toxicity in both healthy and tumor-bearing mice. Therefore, this study presents a PEGibody-based radiotheranostic approach that enhances tumor retention time and provides long-lasting antitumor effects without prolonging blood circulation lifetime. The PEGibody-based radiopharmaceutical [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 shows great potential for positron emission tomography imaging-guided targeted radionuclide therapy for α5β1-overexpressing tumors.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

The small-molecule alkaloid halofuginone (HF) is obtained from febrifugine. Recent studies on HF have aroused widespread attention owing to its universal range of noteworthy biological activities and therapeutic functions, which range from parasite infections and fibrosis to autoimmune diseases. In particular, HF is believed to play an excellent anticancer role by suppressing the proliferation, adhesion, metastasis, and invasion of cancers. This review supports the goal of demonstrating various anticancer effects and molecular mechanisms of HF. In the studies covered in this review, the anticancer molecular mechanisms of HF mainly included transforming growth factor-β (TGF-β)/Smad-3/nuclear factor erythroid 2-related factor 2 (Nrf2), serine/threonine kinase proteins (Akt)/mechanistic target of rapamycin complex 1(mTORC1)/wingless/integrated (Wnt)/β-catenin, the exosomal microRNA-31 (miR-31)/histone deacetylase 2 (HDAC2) signaling pathway, and the interaction of the extracellular matrix (ECM) and immune cells. Notably, HF, as a novel type of adenosine triphosphate (ATP)-dependent inhibitor that is often combined with prolyl transfer RNA synthetase (ProRS) and amino acid starvation therapy (AAS) to suppress the formation of ribosome, further exerts a significant effect on the tumor microenvironment (TME). Additionally, the combination of HF with other drugs or therapies obtained universal attention. Our results showed that HF has significant potential for clinical cancer treatment.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

[Objective]To summarize and analyze the educational quality and problems of Traditional Chinese Medicine students in Zhejiang Chinese Medical University,and provide reference for improving the teaching quality and students'clinical knowledge and skills.[Methods]Taking the students of Traditional Chinese Medicine who participated in the step-1 medical licensing examination empirical research in Zhejiang Chinese Medical University from 2018 to 2020 as the research objects,the data was analyzed by variance analysis and χ2 test.[Results]Staged examination scores could reflect students'academic performance,the average passing rate of theoretical examination was 68.64%,and the average passing rate of skill assessment was 95.27%.The average total mastery rate of theoretical examination was 65.06%,including basic medicine(55.57%)and clinical medicine(52.12%),whose comparison with the total mastery rate of theoretical examination was statistically significant(P<0.05).The total mastery rate of skill assessment was 76.57%,and the average mastery rates of stations 3～4(physical examination)were 71.24%and 72.24%,whose comparison with the total mastery rate of skill assessment was statistically significant(P<0.05).It proposed improvement measures and strategies such as establishing exam incentive mechanisms to enhance students'internal motivation in exams,strengthening clinical medicine course training to improve staged examination pass rates of theoretical part,and repeatedly training clinical skills to fill the gaps in skill assessment.[Conclusion]Traditional Chinese medicine universities can improve the clinical knowledge and skills of students by establishing examination incentive mechanisms,strengthening clinical medicine course training and repeating clinical skill training,so as to improve the quality of training for students majoring in Traditional Chinese Medicine.

Objective:We aimed to develop a novel visualized model based on nomogram to predict postoperative overall survival.Methods:This was a multicenter, retrospective, observational cohort study, including participants with histologically confirmed gastric and colorectal cancer who underwent radical surgery from 11 medical centers in China from August 1, 2015 to June 30, 2018. Baseline characteristics, histopathological data and nutritional status, as assessed using Nutrition Risk Screening 2002 (NRS 2002) score and the scored Patient-Generated Subjective Global Assessment, were collected. The least absolute shrinkage and selection operator regression and Cox regression were used to identify variables to be included in the predictive model. Internal and external validations were performed.Results:There were 681 and 127 patients in the training and validation cohorts, respectively. A total of 188 deaths were observed over a median follow-up period of 59 (range: 58 to 60) months. Two independent predictors of NRS 2002 and Tumor-Node-Metastasis (TNM) stage were identified and incorporated into the prediction nomogram model together with the factor of age. The model's concordance index for 1-, 3- and 5-year overall survival was 0.696, 0.724, and 0.738 in the training cohort and 0.801, 0.812, and 0.793 in the validation cohort, respectively.Conclusions:In this study, a new nomogram prediction model based on NRS 2002 score was developed and validated for predicting the overall postoperative survival of patients with gastric colorectal cancer. This model has good differentiation, calibration and clinical practicability in predicting the long-term survival rate of patients with gastrointestinal cancer after radical surgery.