Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

OBJECTIVE To investigate the effect and mechanism of bumetanide on lung injury in chronic obstructive pulmonary disease （COPD） model rats. METHODS COPD rat model was induced by lipopolysaccharide， and they were randomly divided into model group （COPD group）， bumetanide low-dose and high-dose groups （Bumetanide-L group， Bumetanide-H group）， bumetanide high-dose+Yes-associated protein/transcriptional coactivator containing PDZ-binding motif （YAP/TAZ） signaling pathway activator group （Bumetanide-H+PY-60 group）， with 12 rats in each group. Another 12 normal rats were selected as normal control group （Control group）. Thirty minutes before modeling， bumetanide/normal saline was inhaled or/and PY-60/ normal saline was injected into the tail vein. On the next day after the completion of modeling and drug administration， the pulmonary function index of the rats in each group was measured [forced expiratory volume in 0.3 seconds （FEV0.3）， forced vital capacity （FVC）， peak expiratory flow （PEF）， FEV0.3/FVC]. The levels of tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6） and IL-1β in bronchoalveolar lavage fluid （BALF） were determined； the pathological morphology of lung tissue and degree of pulmonary fibrosis were observed. The expression levels of transforming growth factor- β （TGF- β）， α -smooth muscle actin （α-SMA） and TAZ protein as well as the phosphorylation of YAP protein in lung tissues were detected. RESULTS Compared with COPD group， the pathological injury of lung tissue in Bumetanide-L and Bumetanide-H groups was alleviated； the exfoliation of lung epithelial cells， tube wall thickening and the degree of pulmonary fibrosis were alleviated； inflammatory cell infiltration was reduced， and blue collagen deposition was reduced； FEV0.3， FVC， FEV0.3/FVC and PEF were significantly increased， while the lung injury score， levels of TNF-α， IL-6， IL-1β， expression levels of TGF-β， α-SMA and TAZ protein and the phosphorylation of YAP protein were significantly decreased （P＜0.05）. PY-60 could significantly reverse the improvement effects of bumetanide on above indexes （P＜0.05）. CONCLUSIONS Bumetanide can alleviate lung injury， inflammatory response and pulmonary fibrosis in COPD rats， and its mechanism is related to inhibiting YAP/TAZ signaling pathway.

The AP2/ERF transcription factor family is a class of transcription factors widely present in plants, playing a crucial role in regulating flowering, flower development, flower opening, and flower senescence. Based on transcriptome data from flower, leaf, and stem samples of two Lonicera macranthoides varieties, 117 L. macranthoides AP2/ERF family members were identified, including 14 AP2 subfamily members, 61 ERF subfamily members, 40 DREB subfamily members, and 2 RAV subfamily members. Bioinformatics and differential gene expression analyses were performed using NCBI, ExPASy, SOMPA, and other platforms, and the expression patterns of L. macranthoides AP2/ERF transcription factors were validated via qRT-PCR. The results indicated that the 117 LmAP2/ERF members exhibited both similarities and variations in protein physicochemical properties, AP2 domains, family evolution, and protein functions. Differential gene expression analysis revealed that AP2/ERF transcription factors were primarily differentially expressed in the flowers of the two L. macranthoides varieties, with the differentially expressed genes mainly belonging to the ERF and DREB subfamilies. Further analysis identified three AP2 subfamily genes and two ERF subfamily genes as potential regulators of flower development, two ERF subfamily genes involved in flower opening, and two ERF subfamily genes along with one DREB subfamily gene involved in flower senescence. Based on family evolution and expression analyses, it is speculated that AP2/ERF transcription factors can regulate flower development, opening, and senescence in L. macranthoides, with ERF subfamily genes potentially serving as key regulators of flowering duration. These findings provide a theoretical foundation for further research into the specific functions of the AP2/ERF transcription factor family in L. macranthoides and offer important theoretical insights into the molecular mechanisms underlying floral phenotypic differences among its varieties.
Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Transcription Factors/chemistry* ; Lonicera/classification* ; Flowers/metabolism* ; Phylogeny ; Gene Expression Profiling ; Multigene Family

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

OBJECTIVES: Recent evidence suggests that the gut may be a primary site of metformin action. However, studies on the effects of metformin on gut microbiota remain limited, and its impact on gut microbial metabolites such as short-/medium-chain fatty acids is unclear. This study aims to investigate the effects of metformin on gut microbiota, short-/medium-chain fatty acids, and associated metabolic benefits in high-fat diet rats. METHODS: Twenty-four Sprague-Dawley rats were randomly divided into 3 groups: 1) Normal diet group (ND group), fed standard chow; 2) high-fat diet group (HFD group), fed a high-fat diet; 3) high-fat diet + metformin treatment group (HFD+Met group), fed a high-fat diet for 8 weeks, followed by daily intragastric administration of metformin solution (150 mg/kg body weight) starting in week 9. At the end of the experiment, all rats were sacrificed, and serum, liver, and colonic contents were collected for assessment of glucose and lipid metabolism, liver pathology, gut microbiota composition, and the concentrations of short-/medium-chain fatty acids. RESULTS: Metformin significantly improved HFD-induced glucose and lipid metabolic disorders and liver injury. Compared with the HFD group, the HFD+Met group showed reduced abundance of Blautia, Romboutsia, Bilophila, and Bacteroides, while Lactobacillus abundance significantly increased (all P<0.05). Colonic contents of butyric acid, 2-methyl butyric acid, valeric acid, octanoic acid, and lauric acid were significantly elevated (all P<0.05), whereas acetic acid, isoheptanoic acid, and nonanoic acid levels were significantly decreased (all P<0.05). Spearman correlation analysis revealed that Lactobacillus abundance was negatively correlated with body weight gain and insulin resistance, while butyrate and valerate levels were negatively correlated with insulin resistance and liver injury (all P<0.05). CONCLUSIONS Metformin significantly increases the abundance of beneficial bacteria such as Lactobacillus and promotes the production of short-/medium-chain fatty acids including butyric, valeric, and lauric acid in the colonic contents of HFD rats, suggesting that metformin may regulate host metabolism through modulation of the gut microbiota.
Animals ; Metformin/pharmacology* ; Rats, Sprague-Dawley ; Diet, High-Fat/adverse effects* ; Rats ; Gastrointestinal Microbiome/drug effects* ; Male ; Fatty Acids, Volatile/metabolism* ; Fatty Acids/metabolism*

Treatment based on meridian differentiation is a characteristic method in clinical acupuncture diagnosis and treatment. Accurately defining and explaining its main content and core concepts is essential for effective clinical guidance. This paper reviews the historical and contemporary understanding, concepts, and primary content of treatment based on meridian differentiation. It proposes a four-step process for clinical application: meridian examination, treatment based on meridian differentiation, acupoint selection, and appropriate treatment methods, with TCM syndrome differentiation applied throughout. Constructing a diagnostic and treatment system which is based on meridian differentiation and suited to clinical acupuncture is significant for enhancing therapeutic efficacy and maximizing the benefits of acupuncture in disease treatment.
Humans ; Meridians ; Acupuncture Therapy/methods* ; Acupuncture Points ; Medicine, Chinese Traditional

OBJECTIVE: To observe the clinical efficacy of heat-sensitive moxibustion robot for improving the depressive state of methamphetamine addicts during withdrawal period. METHODS: A total of 60 patients with methamphetamine addiction accompanied with depressive state were randomly divided into an observation group (40 cases, 4 cases dropped out) and a control group (20 cases, 2 cases dropped out). The control group received routine health education and addiction treatment in compulsory isolation drug rehabilitation center. On the basis of the treatment in the control group, in the observation group, the heat-sensitive moxibustion robot was used to locate sensitive points at the Shenque (CV8) and Danzhong (CV17), and dual-point sparrow-pecking moxibustion was delivered for 60 min per session. The moxibustion therapy was performed 4 times in the 1st week, 3 times in the 2nd and 3rd weeks respectively, and 2 times in the 4th week, for 12 times totally. The scores of Hamilton depression scale (HAMD), self-rating depression scale (SDS), visual analogue scale (VAS) for drug craving, Hamilton anxiety scale (HAMA), self-rating anxiety scale (SAS), and Pittsburgh sleep quality index (PSQI) were observed before treatment, at the end of the 2nd and 4th weeks of treatment, and 4 weeks after the treatment completion (follow-up) in the two groups. RESULTS: At each time point after treatment, in the observation group, the HAMD, VAS, HAMA and PSQI scores were decreased compared with those before treatment (P<0.01, P<0.001); at the end of the 4th week of treatment and in follow-up, the SDS and SAS scores were decreased compared with those before treatment (P<0.001, P<0.01). Compared before treatment, there were no significant differences in the above scores at each time point after treatment in the control group (P>0.05). In the observation group, at each time point after treatment, the HAMD and VAS scores were lower than those in the control group (P<0.01, P<0.001, P<0.05); at the end of the 4th week of treatment and in follow-up, the SDS and HAMA scores were lower than those in the control group (P<0.05, P<0.001); at the end of the 4th week of treatment, the PSQI score was lower than that in the control group (P<0.01). CONCLUSION Heat-sensitive moxibustion robot effectively improves depression, anxiety and sleep quality, and reduces drug craving in methamphetamine addicts during withdrawal period.
Humans ; Moxibustion/methods* ; Male ; Adult ; Female ; Methamphetamine/adverse effects* ; Depression/therapy* ; Middle Aged ; Robotics ; Young Adult ; Amphetamine-Related Disorders/psychology* ; Acupuncture Points ; Substance Withdrawal Syndrome/psychology*

INTRODUCTION: Lecanemab has shown promise in treating early Alzheimer's disease (AD), but its safety and efficacy in Chinese populations remain unexplored. This study aimed to evaluate the safety and 6-month clinical outcomes of lecanemab in Chinese patients with mild cognitive impairment (MCI) or mild AD. METHODS: In this single-arm, real-world study, participants with MCI due to AD or mild AD received biweekly intravenous lecanemab (10 mg/kg). The study was conducted at Hainan Branch, Ruijin Hospital Shanghai Jiao Tong University School of Medicine. Patient enrollment and baseline assessments commenced in November 2023. Safety assessments included monitoring for amyloid-related imaging abnormalities (ARIA) and other adverse events. Clinical and biomarker changes from baseline to 6 months were evaluated using cognitive scales (mini-mental state examination [MMSE], montreal cognitive assessment [MoCA], clinical dementia rating-sum of boxes [CDR-SB]), plasma biomarker analysis, and advanced neuroimaging. RESULTS: A total of 64 patients were enrolled in this ongoing real-world study. Safety analysis revealed predominantly mild adverse events, with infusion-related reactions (20.3%, 13/64) being the most common. Of these, 69.2% (9/13) occurred during the initial infusion and 84.6% (11/13) did not recur. ARIA-H (microhemorrhages/superficial siderosis) and ARIA-E (edema/effusion) were observed in 9.4% (6/64) and 3.1% (2/64) of participants, respectively, with only two symptomatic cases (one ARIA-E presenting with headache and one ARIA-H with visual disturbances). After 6 months of treatment, cognitive scores remained stable compared to baseline (MMSE: 22.33 ± 5.58 vs . 21.27 ± 4.30, P = 0.733; MoCA: 16.38 ± 6.67 vs . 15.90 ± 4.78, P = 0.785; CDR-SB: 2.30 ± 1.65 vs . 3.16 ± 1.72, P = 0.357), while significantly increasing plasma amyloid-β 42 (Aβ42) (+21.42%) and Aβ40 (+23.53%) levels compared to baseline. CONCLUSIONS: Lecanemab demonstrated a favorable safety profile in Chinese patients with early AD. Cognitive stability and biomarker changes over 6 months suggest potential efficacy, though high dropout rates and absence of a control group warrant cautious interpretation. These findings provide preliminary real-world evidence for lecanemab's use in China, supporting further investigation in larger controlled studies. REGISTRATION ClinicalTrials.gov , NCT07034222.
Humans ; Alzheimer Disease/drug therapy* ; Male ; Female ; Aged ; Middle Aged ; Cognitive Dysfunction/drug therapy* ; Aged, 80 and over ; Amyloid beta-Peptides/metabolism* ; Biomarkers ; East Asian People

Steroid-induced osteonecrosis of femoral head (SONFH) is a disease characterized by femoral head collapse and local pain caused by excessive use of glucocorticoids. Peroxisome proliferator-activated receptor-γ (PPARγ) is mainly expressed in adipose tissue. Wnt/β-catenin, AMPK and other related signaling pathways play an important role in regulating adipocyte differentiation, fatty acid uptake and storage. Bone marrow mesenchymal cells (BMSCs) have the ability to differentiate into adipocytes or osteoblasts, and the use of hormones upregulates PPARγ expression, resulting in BMSCs biased towards adipogenic differentiation. The increase of adipocytes affects the blood supply and metabolism of the femoral head, and the decrease of osteoblasts leads to the loss of trabecular bone, which eventually leads to partial or total ischemic necrosis and collapse of the femoral head. MicroRNAs (miRNAs) are a class of short non-coding RNAs that regulate gene expression by inhibiting the transcription or translation of target genes, thereby affecting cell function and disease progression. Studies have shown that miRNAs affect the progression of SONFH by regulating PPARγ lipid metabolism-related signaling pathways. Therefore, it may be an accurate and feasible SONFH treatment strategy to regulate adipogenic-osteoblast differentiation in BMSCs by targeted intervention of miRNA differential expression to improve lipid metabolism. In this paper, the miRNA-mediated PPARγ-related signaling pathways were classified and summarized to clarify their effects on lipid metabolism in SONFH, providing a theoretical reference for miRNA targeted therapy of SONFH, and then providing scientific evidence for SONFH precision medicine.
MicroRNAs/physiology* ; PPAR gamma/metabolism* ; Femur Head Necrosis/metabolism* ; Humans ; Signal Transduction/physiology* ; Lipid Metabolism/physiology* ; Animals ; Cell Differentiation ; Mesenchymal Stem Cells/cytology* ; Glucocorticoids/adverse effects*