To explore the correlation between MTHFR C677T gene polymorphism and hypertension, hyperhomocysteinemia(Hcy), and hyperlipidemia in the Tibetan population of Tibet.

Panvascular diseases represent systemic vascular disorders characterized by atherosclerosis as their core pathological feature. Their incidence rates continue to rise， posing significant challenges for clinical management. Based on Traditional Chinese Medicine （TCM） theory of ''positive deficiency phlegm stasis''， this study delved into the pivotal role of mitochondrial homeostasis dysregulation in the pathogenesis and progression of pan-vascular diseases， along with its intrinsic connection to TCM pathogenesis. Mitochondrial homeostasis dysregulation pervades the entire course of these diseases， with mitochondrial oxidative stress serving as the initiating factor. Excessive reactive oxygen species （ROS） trigger endothelial dysfunction， lipid accumulation， and inflammatory initiation. Additionally， the imbalance between mitochondrial autophagy and apoptosis constitutes a pivotal link in disease progression. Excessive or insufficient autophagy may lead to the accumulation of damaged mitochondria and excessive cellular apoptosis， thereby promoting plaque instability. Furthermore， mitochondrial metabolic reprogramming impairs energy supply and function in vascular wall cells， hindering subsequent vascular repair. These pathological processes constitute the microscopic manifestation of the core pathogenesis， which is characterized by ''the intermingle of phlegm and stasis and the deficiency of healthy Qi''. Specifically， the endogenous phlegm-turbidity drives mitochondrial oxidative stress injuries， the mutual entanglement of phlegm and stasis induces an imbalance between mitochondrial autophagy and apoptosis， while deficiency of healthy Qi propels mitochondrial energy metabolism disorders and reprogramming. In view of this， this study proposed to employ phlegm-resolving and turbidity-clearing methods to mitigate mitochondrial oxidative stress injuries， phlegm-resolving and blood-activating methods to regulate mitochondrial autophagy and apoptosis， and spleen-tonifying and kidney-nourishing methods to modulate mitochondrial metabolic reprogramming. This approach can prevent and treat panvascular diseases by multi-target regulation of mitochondrial homeostasis， providing a theoretical framework and therapeutic strategies for the prevention and treatment of panvascular diseases through integrated Chinese and Western medicine.

As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

OBJECTIVE To evaluate the effect of clinical pharmacists participating in the treatment of chronic heart failure （CHF） based on the clinical pharmacy pathway （CPP）. METHODS Totally 226 CHF patients recruited from August 24th， 2024 to March 14th， 2025， were divided into an observation group and a control group based on the random number table method， with 113 cases in each group. All patients were treated with conventional therapy. The observation group was additionally given CPP management （including pharmaceutical care during hospitalization， the formulation of individualized discharge medication regimens， and pharmaceutical follow-up after discharge）. The cardiac function parameters at admission， at discharge， at 3 and 6 months after discharge， drug use at 6 months after discharge， economic indicators， as well as the readmission rate and mortality rate at 6 months after discharge were compared between the two groups. Morisky Medication Adherence Scale-8 Items （MMAS-8）， Somatic Self-rating Scale （SSS） and Patient Health Questionnaire-9 （PHQ-9） scores were compared at admission， at discharge and at 3 and 6 months after discharge. RESULTS Six months after discharge， 24 patients dropped out. Eventually， 104 patients in the observation group and 98 patients in the control group completed the study. Compared with at admission， New York Heart Association （NYHA） cardiac functional classification， left ventricular ejection fraction （LVEF） and N -terminal pro-B-type natriuretic peptide （NT-proBNP） of both groups of patients at discharge as well as at 3 and 6 months after discharge were significantly improved； moreover， the improvements at 3 and 6 months after discharge were significantly better than those at discharge. Meanwhile， the above indexes （except for NYHA cardiac functional classification at discharge， NT-proBNP and NYHA cardiac functional classification at 3 months after discharge） of the observation group at discharge， at 3 and 6 months after discharge were significantly better than the control group （ P ＜0.05）. The utilization rates of angiotensin converting enzyme inhibitor （ACEI）/angiotensin Ⅱ receptor blocker （ARB）/angiotensin receptor neprilysin inhibitor （ARNI）， the proportion of β-blockers reaching the target dose， the utilization rate of sodium-glucose linked transporter 2 inhibitor （SGLT2i）， and the proportion of SGLT2i reaching the target dose in the observation group were significantly higher than the control group （ P ＜0.05）， and the proportion of drugs and readmission rate were significantly lower than the control group （ P ＜0.05）. Compared with at admission， MMAS-8 scores of the patients in the observation group at discharge， at 3 and 6 months after discharge were significantly increased， while SSS and PHQ-9 scores were significantly lowered （ P ＜0.05）. And all the above scores gradually decreas ed with the extension of discharge time （ P ＜0.05）. CONCLUSIONS Clinical pharmacists can utilize CPP to significantly improve patients’ cardiac function， medication adherence， somatic symptoms and depression. Additionally， they can significantly improve the utilization rates of ACEI/ARB/ARNI and SGLT2i， as well as the proportion of target doses of β-blockers and SGLT2i， while simultaneously reducing readmission rates.

BACKGROUND:Osteosarcoma has a complex pathogenesis and a poor prognosis.While advancements in medical technology have led to some improvements in the 5-year survival rate,substantial progress in its treatment has not yet been achieved. OBJECTIVE:To screen key molecular markers in osteosarcoma,analyze their relationship with osteosarcoma treatment drugs,and explore the potential disease mechanisms of osteosarcoma at the molecular level. METHODS:GSE99671 and GSE284259(miRNA)datasets were obtained from the Gene Expression Omnibus database.Differential gene expression analysis and Weighted Gene Co-expression Network Analysis(WGCNA)on GSE99671 were performed.Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease.The intersection of these module genes and differentially expressed genes was taken as key genes.A Protein-Protein Interaction network was constructed,and correlation analysis on the key genes was performed using CytoScape software,and hub genes were identified.Hub genes were externally validated using the GSE28425 dataset and text validation was conducted.The drug sensitivity of hub genes was analyzed using the CellMiner database,with a threshold of absolute value of correlation coefficient|R|>0.3 and P<0.05. RESULTS AND CONCLUSION:(1)Differential gene expression analysis identified 529 differentially expressed genes,comprising 177 upregulated and 352 downregulated genes.WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma.(2)Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix,bone cell differentiation and development,human immune regulation,and collagen synthesis and degradation.Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway,focal adhesion signaling pathway,and immune response in the onset of osteosarcoma.(3)The intersection analysis revealed a total of 59 key genes.Through Protein-Protein Interaction network analysis,8 hub genes were selected,which were LUM,PLOD1,PLOD2,MMP14,COL11A1,THBS2,LEPRE1,and TGFB1,all of which were upregulated.(4)External validation revealed significantly downregulated miRNAs that regulate the hub genes,with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation.Text validation results demonstrated that the expression of hub genes was consistent with previous research.(5)Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate,6-mercaptopurine,and pazopanib with the mRNA expression of PLOD1,PLOD2,and MMP14.Moreover,zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1,LUM,MMP14,PLOD2,and TGFB1.This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma,but further validation is required through additional basic experiments and clinical studies.

Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

Laboratory animals are essential in scientific research and experimental teaching in colleges and universities. Disciplines such as life sciences, medicine, pharmacy, chemistry, and biomedical engineering heavily rely on animal experiments. The standardized barrier environmental facility for laboratory animals provides a fundamental platform for stable, scientific, and reliable animal experiment results. Rigorous access management for such facilities is a vital safeguard for maintaining standardized operations of facilities, controlling the quality and stability of laboratory animals, mitigating pathogen contamination risks among animals and laboratory staff, and preventing biosecurity incidents such as zoonotic disease outbreaks. Taking the small-scale barrier facilities for laboratory rats and mice at Nanjing University's Xianlin Campus, operational since 2019, as an example, this study focuses on the safety access management system of these facilities. Based on five years of operational data and accumulated experience in studying and optimizing the access management system, this study, from the perspectives of management system development and the formulation and implementation of standard operating procedures, reviews five aspects of access management: personnel access, animals access, material access, equipment access, and air circulation control. Furthermore, these aspects are systematically analyzed and summarized to serve as a reference for the construction and management of the laboratory animal facilities in universities, while also contributing to scientific research, public health security, and the well-being of experimental personnel.

BACKGROUND: Metabolic-associated fatty liver disease (MAFLD) is the predominant form of chronic liver disease worldwide. This study was designed to investigate the proportion and characteristics of MAFLD within the general Chinese population and to identify the contributory risk factors for liver fibrosis among MAFLD individuals. METHODS: The participants were recruited from a cohort undergoing routine health evaluations at the Third Hospital of Hebei Medical University between May 2019 and March 2023. The diagnosis of MAFLD was based on the established clinical practice guidelines. The fibrosis-4 index score (FIB-4) was employed to evaluate hepatic fibrosis, with a FIB-4 score of ≥1.3 indicating significant fibrosis. Binary logistic regression analyses were used to determine risk factors associated with significant hepatic fibrosis in MAFLD. RESULTS: A total of 22,970 participants who underwent comprehensive medical examinations were included in the analysis. The overall proportion of MAFLD was 28.77% (6608/22,970), with 16.87% (1115/6608) of these patients showing significant fibrosis as assessed using FIB-4. Independent risk factors for significant liver fibrosis in MAFLD patients were male (odds ratio [OR] = 0.676, 95% confidence interval [CI]: 0.558-0.821), hepatitis B surface antigen (HBsAg) positivity (OR = 2.611, 95% CI: 1.557-4.379), body mass index ≥23.00 kg/m 2 (OR = 0.632, 95% CI: 0.470-0.851), blood pressure ≥130/85 mmHg (OR = 1.885, 95% CI: 1.564-2.272), and plasma glucose ≥5.6 mmol/L (OR = 1.815, 95% CI: 1.507-2.186) (all P <0.001). CONCLUSIONS The proportion of MAFLD in an urban Chinese population is 28.77%. About 16.87% of MAFLD patients presented with significant liver fibrosis. Independent risk factors for significant liver fibrosis in MAFLD patients should be noticed.
Humans ; Male ; Female ; Liver Cirrhosis/pathology* ; Middle Aged ; Risk Factors ; Adult ; Fatty Liver/pathology* ; Aged ; China/epidemiology* ; Logistic Models ; Urban Population ; East Asian People

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*