ObjectiveTo clarify the graded quantitative diagnostic characteristics of lung qi deficiency syndrome in chronic obstructive pulmonary disease （COPD） based on latent class analysis combined with a hidden structure model. MethodsClinical data， including the four diagnostic methods of traditional Chinese medicine （TCM）， were collected from 745 COPD patients with lung qi deficiency syndrome. Latent class modeling was performed using R 4.1.2 software， and each patient was classified into one of three severity categories （mild， moderate， or severe） based on probabilistic parameterization， parameter estimation， and model fitting. A database was established for different severity levels of lung qi deficiency syndrome. Based on this， Lantern 5.0 software was used to construct hidden structure models for mild， moderate， and severe lung qi deficiency syndrome， and syndrome differentiation rules were developed through comprehensive clustering. ResultsA latent class model was constructed using 28 symptoms and signs with a frequency greater than 10%. Considering TCM theory and model simplicity， the optimal model was determined when the number of latent classes was three， categorizing lung qi deficiency syndrome into mild （298 cases）， moderate （164 cases）， and severe （283 cases）. Hidden structure models were separately developed for each severity level， and syndrome differentiation rules were established. A comparison of common symptoms in the syndrome differentiation rules for mild and moderate lung qi deficiency syndrome showed no statistically significant differences in diagnostic values and weights （P＞0.05）， leading to their combined analysis and the development of a unified syndrome differentiation rule. Value and weight of quantitative diagnosis of mild-to-moderate lung qi deficiency syndrome were as followed： shortness of breath （diagnostic value 9.3， diagnostic weight 86.92%）， dyspnea on exertion （8.2， 76.64%）， low voice and reluctance to speak （6.7， 62.62%）， poor appetite （4.0， 37.38%）， loose stools （4.0， 37.38%）， weak cough sound （2.9， 27.10%）， wheezing （2.3， 21.50%）， fatigue （1.8， 16.82%）， spontaneous sweating （1.7， 15.89%）， susceptibility to colds （1.6， 14.95%）， swollen tongue （1.4， 13.08%）， teeth marks on the tongue edge （1.2， 11.21%）， deep pulse （1.6， 14.95%）， with a diagnostic threshold of 10.3. Value and weight of quantitative diagnosis of severe lung qi deficiency syndrome were as followed： weak cough sound （15.1， 61.13%）， soreness and weakness of the waist and knees （12.6， 51.01%）， shortness of breath （11.1， 44.94%）， low voice and reluctance to speak （8.3， 33.60%）， frequent nocturia （6.1， 24.70%）， spontaneous sweating （3.7， 14.98%）， susceptibility to colds （3.5， 14.17%）， teeth marks on the tongue edge （7.8， 31.58%）， pale tongue body （1.9， 7.69%）， white tongue coating （5.5， 22.27%）， thin pulse （1.5， 6.07%）， with a diagnostic threshold of 23.7. ConclusionThe combination of latent class analysis and a hideen structure model effectively clarified the graded quantitative diagnostic characteristics of lung qi deficiency syndrome， providing a reference for the quantitative diagnosis of other fundamental syndromes in TCM.

BACKGROUND:Traditional treatments for corneal alkali burns are limited,especially in controlling inflammation,preventing neovascularization,and inhibiting corneal scarring.Natural,synthetic,or composite materials provide a wide range of treatment options.However,the mechanism by which biomaterials promote corneal alkali burn repair has not yet been systematically understood. OBJECTIVE:To summarize the current research on biomaterials in promoting corneal alkali burn repair in and outside China,and review the mechanism and application of biomaterials in repairing corneal alkali burn. METHODS:The first author searched"cornea,alkali burn,amniotic membrane,hyaluronic acid,collagen,chitosan,polymer materials"as Chinese keywords and"amniotic membrane,hyaluronic acid,collagen,chitosan,polymer,cornea,alkali burn"as English keywords in PubMed,Web of Science,CNKI,and WanFang databases.According to inclusion and exclusion criteria,76 eligible articles were finally included for review. RESULTS AND CONCLUSION:(1)In the field of corneal alkali burn repair,biomaterials such as amniotic membrane,hyaluronic acid,collagen,chitosan,and degradable polymer materials have been widely studied and applied.Each of these biomaterials has its own characteristics,advantages,and disadvantages,and stands out in different aspects.(2)First and foremost,amniotic membranes are considered one of the most promising biomaterials due to their abundance of bioactive factors.They are biocompatible and can regulate the corneal inflammatory response.However,there are issues with donor shortages and susceptibility to infectious diseases.(3)Hyaluronic acid has good moisturizing properties and biocompatibility,and is able to improve the survival rate of corneal cells and increase corneal transparency.(4)The good biocompatibility and scaffold structure of collagen enable the promotion of corneal cell adhesion and proliferation,as well as the reconstruction of corneal tissue structure.(5)Chitosan is recognized for its good biocompatibility and degradability,making it suitable as a carrier for drug delivery and cell transplantation.(6)Degradable polymer materials have good controllability over degradation and can provide a good support and delivery platform for the repair of corneal alkali burns,but further research is needed on their stability and biocompatibility.(7)Overall,there is currently no single biomaterial that can completely address the repair problem of corneal alkali burns,and each biomaterial has its own specific application scenarios and limitations.(8)Future research directions should focus on further improving the properties and structure of biomaterials,exploring more effective combination applications,and deeply understanding the interaction mechanism between biomaterials and corneal tissue,in order to enhance the therapeutic effect of corneal alkali burns and the quality of life of patients.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

BACKGROUND: The American Heart Association (AHA) introduced the concept of cardiovascular-kidney-metabolic (CKM) health and stage, reflecting the interaction among metabolism, chronic kidney disease (CKD), and the cardiovascular system. However, the association between CKM stage and the long-term risk of cardiovascular disease (CVD) has not been validated. This study aimed to evaluate the long-term CVD risk associated with CKM health metrics and CKM stage using data from a population-based cohort study. METHODS: In total, 5293 CVD-free participants were followed up to around 13 years in the Chinese Multi-provincial Cohort Study (CMCS). Considering the pathophysiologic progression of CKM health metrics abnormalities (comprising obesity, central adiposity, prediabetes, diabetes, hypertriglyceridemia, CKD, and metabolic syndrome), participants were divided into CKM stages 0, 1, and 2. The time-dependent Cox regression models were used to estimate the cardiovascular risk associated with CKM health metrics and stage. Additionally, broader CVD outcomes were examined, with a specific assessment of the impact of stage 3 in 2581 participants from the CMCS-Beijing subcohort. RESULTS: Among participants, 91.2% (4825/5293) had at least one abnormal CKM health metric, 8.8% (468/5293), 13.3% (704/5293), and 77.9% (4121/5293) were in CKM stages 0, 1, and 2, respectively; and 710 incident CVD cases occurred during a median follow-up time of 13.3 years (interquartile range: 12.1 to 13.6 years). Participants with each poor CKM health metric exhibited significantly higher CVD risk. Compared with stage 0, the hazard ratio (HR) (95% confidence interval [CI]) for CVD incidence was 1.31 (0.84-2.04) in stage 1 and 2.27 (1.57-3.28) in stage 2. Significant interactive impacts existed between CKM stage and age or sex, with higher CVD risk related to increased CKM stages in participants aged <60 years or females. CONCLUSION These findings highlight the contribution of CKM health metrics and CKM stage to the long-term risk of CVD, suggesting the importance of multi-component recognition and management of poor CKM health in CVD prevention.
Humans ; Female ; Male ; Cardiovascular Diseases/etiology* ; Middle Aged ; Adult ; Cohort Studies ; Renal Insufficiency, Chronic/metabolism* ; Aged ; Risk Factors ; Metabolic Syndrome/metabolism* ; China ; East Asian People

Objective:To investigate the effect of decarbromodiphenyl ether(BDE-209)exposure on the migration ability of triple-negative breast cancer(TNBC)cells and to explore the underlying mechanism.Methods:Human TNBC MDA-MB-231 cells were divided into blank control group and BDE-209 exposure groups(treated with 0.02,0.20,2.00,20.00 and 200.00 ng/mL BDE-209 in high glucose DMEM).Extracellular vehicles(EVs)secreted by MDA-MB-231 cells were isolated by differential ultracentrifugation.Transmission electron microscopy(SEM),nanoparticle tracking analysis(NTA)and Western blotting were performed to characterize the EVs.The effect of the EVs induced by BDE-209 exposure(EVs-BDE-209)on the migration and invasion of MDA-MB-231 cells was detected by wound-healing assay and Transwell test.qRT-PCR was used to measure the miR-221 level in EVs-BDE-209.The expression of MMP9 in MDA-MB-231 cells was determined by Western blotting.Results:Compared with the blank control,BDE-209 exposure increased the tumor cell-derived EVs in dose-dependent manner.The MDA-MB-231 cells co-cultured with EVs released by 200.00 ng/mL BDE-209 exposure showed an 86%increase in cell migration rate,a 1.32-fold higher number of membrane-penetrating cells,a 2.71-fold higher expression level of miR-221,and a 1.62-fold higher expression level of MMP9 compared with the blank control group(all P<0.05).While transfection with anti-miR-221 antibody to decrease miR-221 level in EVs significantly reversed the increased invasion ability of the MDA-MB-231 cells treated with EVs-BDE-209.Conclusion:BDE-209 exposure may promote metastasis potential of MDA-MB-231 cells via EVs-BDE-209 transmitted miR-221.

Objective To explore the comparison of the predictive value of three risk assessment tools on the chemotherapy-induced nausea and vomiting(CINV)in cancer patients.Methods From January 2022 to December 2022,convenience sampling was used to select 626 cancer patients with Intravenous chemotherapy in the Department of Hepatobiliary Pancreatic Oncology of Zhejiang Cancer Hospital as the research object.CINV risk assessment of patients was performed using George teams acute CINV prediction tool,Dranitsari's CINV risk assessment and CINV nomogram model.Area under curve(AUC),sensitivity,specificity and Youden index were used to compare the predictive value of the three tools.Results Totally 622 patients were ultimately included in the study,with an overall effective rate of 99.36%.There were 51.13%(318/622)patients who experienced CINV.Specifically,patients with grade 2 or higher acute CINV accounted for 18.17%(113/622).When using the three tools for acute CINV risk assessment,the AUC was respectively 0.591,0.616 and 0.558.And Dranitsari's CINV risk assessment has the highest sensitivity,acute and delayed chemotherapy-induced nausea and vomiting prediction tool has the highest specificity.Comparatively,Dranitsari's CINV risk assessment on the Yorden index is better.Conclusion The incidence of CINV in cancer patients is at a high level.The three tools can not effectively predict the risk of acute CINV.We need to develop a localized,multi-disease,standardized CINV risk assessment model for hospital.

Objective:To prepare a novel 68Ga-labeled bicyclic peptide targeting poliovirus receptor related protein 4 (PVRL4, Nectin-4), and evaluate its feasibility for breast cancer imaging via in vitro and in vivo experiments. Methods:A Biotin-modified bicyclic peptide targeting Nectin-4, Biotin-BMIC, was synthesized, and its targeting properties were preliminarily evaluated by in vitro cell staining experiments. BMIC was modified by 1, 4, 7-triazonane-1, 4-diacetic acid (NODA) and the labeling precursor NODA-BMIC was prepared. A potential PET probe targeting Nectin-4, 68Ga-NODA-BMIC was prepared by one-step labeling strategy. The imaging properties of the probe were investigated by in vivo microPET imaging and in vitro experiments in mice bearing breast tumors. Data were analyzed by independent-sample t test and repeated measures analysis of variance. Results:Fluorescence staining of the cells showed that the fluorescently labeled bicyclic peptide, Biotin-BMIC, was highly aggregated in Nectin-4 positive BT474 breast cancer cells compared to those in Nectin-4 negative MDA-MB-231 cells. The uncorrected yield of 68Ga-NODA-BMIC was (71.5±2.2)% and the radiochemical purity was greater than 95%. The specific activity was greater than 3 GBq/μmol. After incubation 10, 30, 60 and 120 min, higher radioactivity uptakes were found in BT474 breast cancer cells compared to those in MDA-MB-231 breast cancer cells respectively ( F=1 302.00, P<0.001). MicroPET imaging showed that the BT474 xenograft tumors were clearly visible with favorable contrast. A significant statistical difference in uptakes between BT474 and MDA-MB-231 xenograft tumor uptake at 10, 30, 60, and 120 min after probe injection respectively was existed ( F=1 826.00, P<0.001). At 60 min postinjection, the uptake value of BT474 tumors was (5.03±0.14) percentage activity of injection dose per gram of tissue (%ID/g), which was significantly higher than that of MDA-MB-231 tumors ((0.19±0.04) %ID/g; t=79.40, P<0.001). Meanwhile, the tumor-to-muscle ratios in the former were also greater than those in the latter ( F=222.00, P<0.001). At 60 min postinjection, the tumor-to-muscle ratio in the former was significantly higher than that in the latter (24.75±3.10 vs 1.30±0.15; t=14.31, P=0.002). The results were consistent with the immunohistochemistry staining. Conclusions:A novel bicyclic peptide PET probe targeting Nectin-4, 68Ga-NODA-BMIC, is easy to be synthesized and owns satisfactory labeling yield and radiological purity. The imaging performance is good and the target tissues could be visualized. It may play a unique role in the diagnosis and treatment of breast cancer.

Essential oils (EOs) are natural, volatile substances derived from aromatic plants. They exhibit multiple pharmacological effects, including antibacterial, anticancer, anti-inflammatory, and antioxidant properties, with broad application prospects in health care, food, and agriculture. However, the instability of volatile components, which are susceptible to deterioration under light, heat, and oxygen exposure, as well as limited water solubility, have significantly impeded the development and application of EOs. Porous nanoclays are natural clay minerals with a layered structure. They possess unique structural characteristics such as large pore size, regular distribution, and tunable particle size, which are extensively utilized in drug delivery, adsorption separation, reaction catalysis, and other fields. Natural-derived porous nanoclays have garnered considerable attention for the encapsulation and delivery of EOs. This review comprehensively summarizes the structure, types, and properties of natural-derived porous nanoclays, focusing on the structural characteristics of porous nanoclays such as montmorillonite, palygorskite, halloysite, kaolinite, vermiculite, and natural zeolite. It also examines research advances in their delivery of EOs and explores engineering strategies to enhance the delivery of EOs by natural-derived porous nanoclays. Finally, various applications of natural-derived porous nanoclays for EOs in antibacterial, food preservation, repellent, and insecticide aspects are presented, providing a reference for the development and application of EOs.
Humans ; Nanoparticles/chemistry* ; Oils, Volatile/administration & dosage* ; Porosity ; Nanoparticle Drug Delivery System/chemistry*

There are a large number of individuals with HBV infection in China, which seriously endangers public health safety. As a first-line drug used in clinical practice, tenofovir alafenamide fumarate (TAF) has the characteristics of strong efficacy, low drug resistance, and bone and kidney safety. This article summarizes the role of TAF in patients with special types of chronic hepatitis B, such as low-level viremia, multidrug resistance, pregnancy, liver failure, and liver transplantation, and the analysis shows that TAF can reduce viral load in patients with low-level viremia to achieve virologic response, provide new regimens for patients with drug resistance, block mother-to-child transmission, reduce the mortality rate of patients with end-stage liver disease, and improve renal function in patients with chronic kidney disease.