OBJECTIVE To investigate the potential mechanism by which Juanxiao decoction improves bronchial asthma （hereinafter referred to as “asthma”） based on the nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 （NLRP3） inflammasome signaling pathway. METHODS Female SD rats were randomly assigned to normal group， model group and Juanxiao decoction low-， medium- and high-dose groups （0.36， 0.72 and 1.44 g/kg， calculated based on crude drug weight）， as well as positive control group （Dexamethasone acetate tablets， 0.2 mg/kg）， with 10 rats in each group. Except for the normal group， asthma models were established in the remaining groups via intraperitoneal injection of ovalbumin combined with aluminum hydroxide， followed by nebulized inhalation of ovalbumin. On day 14 of the experiment， rats in each group received intragastric administration of the corresponding solution or normal saline， once a day， for 7 consecutive days. Following the final administration， the following parameters were measured in each group： lung function indexes （forced vital capacity， forced expiratory volume in 0.3 second， peak expiratory flow）， serum levels of inflammatory markers （interleukin-1β， interleukin- 18）， and the percentages of inflammatory cells （lymphocytes， eosinophils， neutrophils） in bronchoalveolar lavage fluid. Histopathological changes in lung tissue were observed， and the protein and mRNA expressions of nuclear factor-kappa B （NF- κB）， NLRP3 and caspase-1 in lung tissue were detected. RESULTS Compared with the normal group， pathological changes such as alveolar wall thickening and inflammatory cell infiltration were observed in rats in the model group. All pulmonary function indicators were significantly reduced in rats in the model group and the administration groups. The levels of inflammatory markers， the percentages of inflammatory cells， and the protein and mRNA expressions of NF-κB， NLRP3 and caspase-1 were significantly elevated or up-regulated （P＜0.05）. Compared with the model group， pathological changes in rats in each dosage group of Juanxiao decoction were significantly alleviated， and all quantitative indicators showed dose-dependent improvements （P＜0.05）. CONCLUSIONS Juanxiao decoction can reduce airway inflammatory responses in asthmatic rats， alleviate lung function impairment， and improve pathological changes such as inflammatory cell infiltration. Those effects may be related to the inhibition of the NLRP3 inflammasome signaling pathway.

ObjectiveTo investigate the effects of Huanglian Jiedutang （HLJDT） on cognitive function in mice with ischemic stroke （IS） and to elucidate whether its neuroprotective effects are mediated by inhibition of the nuclear factor-κB （NF-κB） signaling pathway and subsequent suppression of NF-κB-regulated neuronal apoptosis. MethodsAn IS model was established using middle cerebral artery occlusion （MCAO）. Sixty C57BL/6J mice were randomly assigned to five groups （n =12 per group）， i.e.， sham operation， model， HLJDT low-dose （3.9 g·kg^-1·d^-1）， HLJDT high-dose （7.8 g·kg^-1·d^-1）， and Ginkgo biloba extract （GBE， 31.2 mg·kg^-1·d^-1）. Post-operatively， neurological deficit scores （Longa score）， cerebral infarct volume assessed by 2，3，5-triphenyltetrazolium chloride （TTC） staining， and brain water content were evaluated. Learning and memory were assessed using new object recognition （NOR） and fear conditioning （FC） tests. Hippocampal pathology was examined via hematoxylin and eosin （HE） staining. Immunofluorescence detected expression of glial fibrillary acidic protein （GFAP， astrocyte marker）， cellular oncogene Fos （c-Fos， neuronal activation marker）， and glutamate decarboxylase 65 （GAD65）. Western blot measured nuclear factor-κB inhibitor protein α （IκBα）， phosphorylated IκBα （p-IκBα）， NF-κB p65， phosphorylated NF-κB p65 （p-NF-κB p65）， ionic calcium binding adapter molecule 1 （Iba-1）， tumor necrosis factor （TNF）-α， interleukin （IL）-1β， and apoptosis-related proteins， such as cleaved cysteinyl aspartate-specific protease 3 （Caspase-3）， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. Real-time quantitative PCR （Real-time PCR） was used to assess mRNA levels of Iba-1， TNF-α， IL-1β， NF-κB p65， cleaved Caspase-3， Bax， and Bcl-2. ResultsCompared with the sham group， the model group exhibited significantly increased neurological deficit scores， brain water content， and cerebral infarct volume （P<0.01）. Hippocampal CA1 neurons were disorganized， showing nuclear pyknosis and karyolysis. NOR exploration time and FC freezing time were significantly reduced （P<0.01）. GFAP and c-Fos expression were increased， while GAD65 expression was decreased （P<0.01）. Cleaved Caspase-3 and Bax were upregulated， Bcl-2 was downregulated， and the Bax/Bcl-2 ratio was elevated （P<0.01）. Expression levels of p-IκBα， p-NF-κB p65， IL-1β， TNF-α， and Iba-1 were significantly increased （P<0.01）. Compared with the model group， HLJDT high-dose， low-dose， and GBE groups showed significant improvements in all parameters （P<0.01）. Among them， the HLJDT high-dose group showed the most pronounced neuronal structural recovery and superior performance in NOR and FC tests （P<0.01）. In this group， GFAP and c-Fos decreased， GAD65 increased （P<0.01）， apoptosis-related protein expression was reversed， and NF-κB signaling and related inflammatory factor expression were suppressed （P<0.01）. ConclusionHLJDT ameliorates cognitive dysfunction in mice after IS， potentially by inhibiting the NF-κB signaling pathway， thereby reducing neuroinflammation and hippocampal neuronal apoptosis.

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 compare the effects of leuprorelin and mifepristone on sex hormone levels， ovarian function， adverse reactions， and recurrence in patients with endometriosis （EMs） after surgery. METHODS A total of 178 patients who underwent surgical treatment for EMs in Ji’an Central People’s Hospital from September 2021 to September 2023 were randomly divided into the leuprorelin group and the mifepristone group， with 92 cases in each group. Medication was initiated on days 1 to 5 of the first menstrual cycle following surgery. Patients in the leuprorelin group received subcutaneous injections of Leuprorelin acetate microspheres， 3.75 mg per time， once every four weeks， for a total of 6 injections. Patients in the mifepristone group took 12.5 mg of Mifepristone capsules orally once daily for six consecutive months. Visual analog scale （VAS）， serum sex hormone levels [follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， and estradiol （E2）]， ovarian function indicators [anti- Müllerian hormone （AMH）， antral follicle count （AFC）]， and T helper 1 cell （Th1）/Th2 shift markers [interferon-γ （IFN-γ）， interleukin 2 （IL-2）， IL-4， and IL-10] were compared between the two groups before surgery and after treatment. Incidence and outcome of adverse reactions and recurrence within one year were also compared between the two groups. RESULTS There were no statistically significant differences in baseline indicators between the two groups before surgery （P＞0.05）. After treatment， both groups showed significantly lower VAS scores for chronic pelvic pain， dysmenorrhea and dyspareunia， and significantly reduced serum FSH， LH， E2， IL-4 and IL-10 levels compared to before surgery （P＜0.05）， while serum IFN-γ and IL-2 levels were significantly increased （P＜0.05）； the leuprorelin group showed significantly greater improvements than the mifepristone group in all these indicators （P＜0.05）. After treatment， serum AMH levels in both groups were significantly lower than before surgery levels， while AFC was significantly increased （P＜0.05）； the leuprorelin group had significantly higher serum AMH levels and more AFC compared to the mifepristone group （P＜0.05）. There were no significant differences in the incidence of adverse reactions and outcome rates between the two groups （P＞0.05）. During one year of follow-up after discontinuation， the recurrence rate in the leuprorelin group was significantly lower than in the mifepristone group （1.15% vs. 10.99%， P＜0.05）. CONCLUSIONS Both leuprorelin and mifepristone are effective therapeutic drugs for EMs， but the former has advantages in alleviating pain， regulating serum sex hormone levels， protecting ovarian function， regulating immune function and reducing recurrence rates.

Objective To analyze the multi-target mechanism of Paeoniflorin in the intervention of oral submucosal fibrosis(OSF)systematically,based on molecular dynamics simulation and network pharmacology.Methods Identify potential targets of Paeoniflorin were predicted by using database.OSF-related disease targets and identified drug-disease intersecting targets were screened.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were conducted to validate the molecular binding capabilities between Paeoniflorin and core targets.Finally,molecular dynamics simulations were performed to verify binding stability.Results A total of 20 overlapping targets were identified,including key genes such as transforming growth factor(TGF)-β1,interleukin(IL)-6,and tumor necrosis factor(TNF)-α.TGF-β1,IL-6,and TNF formed the core hub.The enrichment analysis revealed that the target molecules were significantly enriched in the TGF-β1,phosphatidylinositol 3-kinease-actin(PI3K-Akt),and nuclear factor κB(NF-κB)signaling pathways.Molecular docking confirmed high affinity binding of Paeoniflorin to targets including TGF-β1,while molecular dynamics simulations verified stable interactions between Paeoniflorin and both TGF-β1 and B-cell lymphoma-2 targets.Conclusion This study revealed that Paeoniflorin inhibits the inflammatory-fibrotic cascade of OSF through synergistic regulation of TGF-β1/Smad,PI3K-Akt and NF-κB pathways.

Objective To understand the willingness to engage in the combine medical care with old-age care institutions of medical students in vocational colleges and analyze their influencing factors.Methods By convenient sampling method,1 266 medical students from 3 vocational colleges in Hunan Province were select-ed as the research objects,and their occupational cognition and occupational willingness were investigated and analyzed.Through objective sampling,20 medical students who were not willing to work in medical institu-tions were selected for semi-structured interviews.Results 62.1%of medical students intend to work in med-ical institutions after graduation;The results of multi-factor analysis showed that the experience of caring for the elderly,understanding of the nursing institution,participating in the volunteer service of the nursing insti-tution,and cognition score of the combination of medical care and nursing were the influencing factors of med-ical students'career intention(P＜0.05).The qualitative interview found that professional identity,job abili-ty,salary,social security and promotion were the main influencing factors.Conclusion Medical students in medical nursing institutions do not have strong willingness,so they should improve their professional cogni-tion of old-age service,enhance their professional identity and post competency,fully implement salary,social security and professional title promotion,attract more medical students to engage in the combined service in-dustry,and promote the combined development of medical care.

Objective To explore the effect of positive ruminative thinking training(PRT)on negative emotions during modified electroconvulsive therapy(MECT)in depression patients.Method A total of 80 patients with depression who received MECT at Ganzhou Third People's Hospital from February 2024 to February 2025 were selected as subjects.Using a random number table method,they were divided into control group(n=40)and observation group(n=40).The control group received standard interventions,while the observation group received PRT in addition to control group's interventions.Both groups continued treatment until the completion of MECT,with all patients receiving 8-12 sessions of MECT.Negative emotions,self-efficacy,and the positive and negative ruminative thinking(PNR)scale were compared between two groups.Before and after intervention,adverse reactions were evaluated in both groups post-treatment.Results After intervention,the scores of anxiety,depression scale,and negative factor rumination thinking in observation group were lower than those in control group.The scores of general self-efficacy scale and positive factor rumination thinking were higher than those in control group,and the differences were statistically significant(P＜0.05).The total incidence of adverse reactions in observation group was lower than that in control group(P＜0.05).Conclusion PRT can reduce negative emotions and negative rumination thinking in depression patients during MECT,improve positive rumination thinking and self-efficacy.

Resistant ovary syndrome(ROS)and premature ovarian insufficiency(POI)fall under the cat-egory of hypogonadotropic amenorrhea,sharing similar clinical features that often pose challenges in differentiation.ROS can be easily misdiagnosed as POI,which presents a significant obstacle to subsequent treatment.Therefore,it is crucial for patients with fertility requirements to have a clear understanding of the etiology,clinical features,and diagnostic criteria of ROS and POI in order to establish an early diagnosis and develop an appropriate treatment plan.This article provides a systematic and comprehensive discussion on the research progress regarding the eti-ology and pathogenesis,clinical features and diagnosis,as well as individualized management of ROS and POI.The aim is to offer reference for clinicians in achieving early clarification of diagnoses,avoiding misdiagnosis or mistreatment,while assisting patients in improving symptoms and realizing their fertility aspirations through person-alized management.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.