Objective To evaluate the efficacy and safety of 450 nm blue laser vaporization enucleation of the prostate in the treatment of benign prostatic hyperplasia(BPH)complicated with urinary retention, so as to promote its clinical application. Methods A retrospective analysis was conducted on the clinical data of 60 patients with BPH and urinary retention who underwent 450 nm blue laser vaporization enucleation of the prostate in our hospital during Feb. 2023 and Apr. 2024. All patients had urinary catheters indwelt preoperatively due to urinary retention. The perioperative indicators and complications were recorded. The maximum urinary flow rate(Qmax), postvoid residual(PVR), international prostate symptom score(IPSS), and quality of life score(QoL)were compared before surgery and 3 months after surgery. Results All procedures were completed successfully without conversion to transurethral resection of the prostate(TURP). No cases of severe intraoperative bleeding or transfusion were reported. The average operation time was(60.5±21.5)min, postoperative hemoglobin reduction(3.2±0.8)g/L, catheterization time(3.1±0.4)days, and hospital stay(3.2±0.4)days. No bladder perforation or urethral injury occurred. At 3 months postoperatively, Qmax [(19.2±4.9)mL/s vs.(3.5±2.3)mL/s], PVR [(50.8±20.1)mL vs.(369.2±163.2)mL], IPSS [(9.7±0.9)vs.(21.8±3.2)], and QoL [(1.4±0.5)vs.(4.9±0.1)]were significantly improved compared with preoperative values(P＜0.001). Urinary retention occurred in 2 patients after catheter removal on postoperative day 3, which was resolved one week after re-catheterization. Conclusion The 450 nm blue laser vaporization enucleation of the prostate is a safe and effective treatment for BPH complicated with urinary retention. It can significantly improve the short-term voiding function and quality of life with a low incidence of postoperative complications, demonstrating promising potential for clinical adoption.

ObjectiveTo construct a risk prediction model for carotid artery plaques in high-risk populations of stroke based on five machine learning methods. MethodsThe clinical information of the high-risk population of stroke was collected. Factor analysis and statistical analysis of syndrome elements were conducted on their traditional Chinese medicine （TCM） symptoms and tongue and pulse manifestations. On the basis of the results of factor analysis and variable screening， five machine learning methods-classification and regression tree （CART） decision tree， support vector machine （SVM）， back propagation（BP） neural network， logistic regression， and random forest-were used to construct the risk prediction model for carotid artery plaques. ResultsThe most common TCM syndrome elements in the high-risk population of stroke was Qi deficiency. The scores of Qi deficiency， Yin deficiency， and Yang deficiency in the population with carotid artery plaques were higher than those without carotid artery plaques （P<0.05）. The CART decision tree， SVM， logistic regression， BP neural network， and random forest models showed the areas under the receiver operating characteristic （ROC） curves of 0.71， 0.75， 0.76， 0.76， and 0.75， the accuracy rates of 68.94%， 69.27%， 69.44%， 70.10%， and 69.60%， the precision rates of 68.56%， 68.53%， 68.75%， 69.74%， and 69.42%， the recall rates of 68.91%， 67.93%， 67.92%， 68.10%， and 67.31%， and the F₁ values of 0.69， 0.68， 0.68， 0.68， and 0.68， respectively. ConclusionAmong the high-risk population of stroke， the most frequently distributed TCM syndrome element is Qi deficiency， with the rest mainly being fire heat， Yin deficiency， Yang deficiency， phlegm dampness， blood stasis， and Qi stagnation. Deficiency syndrome may be a major factor leading to carotid artery plaques in the high-risk population of stroke. The BP neural network model demonstrates better performance in predicting the risk of carotid artery plaques in the high-risk population of stroke. People with carotid artery plaques are more likely to present with symptoms such as a heavy head， dizziness， headache， and thready pulse. The primary community benefits more widely when the BP neural network model is adopted to predict the risk of carotid artery plaques in the high-risk population of stroke over 40 years old.

ObjectiveTo construct a risk prediction model for carotid artery plaques in high-risk populations of stroke based on five machine learning methods. MethodsThe clinical information of the high-risk population of stroke was collected. Factor analysis and statistical analysis of syndrome elements were conducted on their traditional Chinese medicine （TCM） symptoms and tongue and pulse manifestations. On the basis of the results of factor analysis and variable screening， five machine learning methods-classification and regression tree （CART） decision tree， support vector machine （SVM）， back propagation（BP） neural network， logistic regression， and random forest-were used to construct the risk prediction model for carotid artery plaques. ResultsThe most common TCM syndrome elements in the high-risk population of stroke was Qi deficiency. The scores of Qi deficiency， Yin deficiency， and Yang deficiency in the population with carotid artery plaques were higher than those without carotid artery plaques （P<0.05）. The CART decision tree， SVM， logistic regression， BP neural network， and random forest models showed the areas under the receiver operating characteristic （ROC） curves of 0.71， 0.75， 0.76， 0.76， and 0.75， the accuracy rates of 68.94%， 69.27%， 69.44%， 70.10%， and 69.60%， the precision rates of 68.56%， 68.53%， 68.75%， 69.74%， and 69.42%， the recall rates of 68.91%， 67.93%， 67.92%， 68.10%， and 67.31%， and the F₁ values of 0.69， 0.68， 0.68， 0.68， and 0.68， respectively. ConclusionAmong the high-risk population of stroke， the most frequently distributed TCM syndrome element is Qi deficiency， with the rest mainly being fire heat， Yin deficiency， Yang deficiency， phlegm dampness， blood stasis， and Qi stagnation. Deficiency syndrome may be a major factor leading to carotid artery plaques in the high-risk population of stroke. The BP neural network model demonstrates better performance in predicting the risk of carotid artery plaques in the high-risk population of stroke. People with carotid artery plaques are more likely to present with symptoms such as a heavy head， dizziness， headache， and thready pulse. The primary community benefits more widely when the BP neural network model is adopted to predict the risk of carotid artery plaques in the high-risk population of stroke over 40 years old.

Objective To explore the alteration and function of TIMM8A during gefitinib-induced growth inhibition of lung cancer cell line PC-9.Methods TIMM8A siRNA transfection experiment was used to inhibit the expression of TIMM8A in PC-9 and gefitinib resistant PC-9 cells(PC-9-MTAC).CCK-8 assay was carried out to assess PC-9 and PC-9-MTAC cell viability after gefitinib treatment or TIMM8A siRNA transfection.qPCR was used to determine TIMM8A expression in PC-9 or PC-9-MTAC cells.Results Gefitinib inhibited PC-9 cell growth in a dose-depend-ent manner.The expression of TIMM8 A was inhibited during this process,and more than 50％TIMM8 A expression had been inhibited by 25 nmol/L gefitinib,while knockdown of TIMM8 A enhanced inhibitory effects of gefitinib on PC-9 cell proliferation(P＜0.05).Compared with the sensitive cells,treatment of the gefitinib-resistant PC-9-MTAC with 100 nmol/L gefitinib for 48 h only inhibited approximately 30％of TIMM8A expression.Furthermore,inhibition of TIMM8A expression enhanced the sensitivity of PC-9-MTAC cells to gefitinib(P＜0.05).Conclusions Low expression of TIMM8A improves anti-tumor effects of gefitinib in lung cancer cell line PC-9.

Objective To construct nucleotide-binding oligomerization domain-like receptor protein 3(NLRP3)knockout mice in order to investigate the effects of NLRP3 knockout on radiation-induced acute pneumonitis and pulmonary fibrosis.Methods Nlrp3+/+and Nlrp3-/-mice were randomly divided into the control group and irradiation group.To induce radiation-caused acute pneumonitis,the control group was exposed to sham irradiation while the irradiation group was exposed to 60Co γ-rays at a dose of 22 Gy at a dose rate of 184.30 R/min.At 14 days post-irradiation,the body weight of each mouse and the wet weight of its lung tissue were measured separately using an analytical balance to calculate the lung coefficient.Quantitative real-time PCR(qPCR)and cytometric bead array(CBA)were used to detect inflammatory responses in lung tissues and serum.Hematoxylin-eosin(HE)staining and F4/80 immunohistochemical staining were used to assess pathological changes and inflammatory cell infiltration in lung tissues.Cysteinyl aspartate specific proteinase-1(caspase-1)activation was analyzed by Western blotting.To establish a model of radiation-induced pulmonary fibrosis,mice were irradiated with 60Co γ-rays at a dose of 18 Gy at a dose rate of 174.67 R/min.At 24 weeks post-irradiation,HE staining and Masson staining were performed to evaluate pulmonary fibrosis.Results NLRP3 knockout inhibited caspase-1 activation,reduced inflammatory responses in lung tissues and serum,suppressed macrophage infiltration,alleviated pulmonary edema,and thereby protected against acute radiation-induced lung injury.Additionally,NLRP3 knockout significantly ameliorated late-stage radiation-induced pulmonary fibrosis.Conclusion NLRP3 knockout can mitigate both early radiation-induced pneumonia and lateradiation-induced pulmonary fibrosis.

Objective:To investigate the value of habitat radiomic features based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI in establishing a predictive model for cytokeratin 19 (CK19) expression in hepatocellular carcinoma (HCC) and to evaluate its role in prognostic risk stratification.Methods:This multicenter case-control study retrospectively enrolled 489 patients with pathologically confirmed HCC who underwent Gd-EOB-DTPA-enhanced MRI between June 2016 and June 2024. Among them, 346 patients from the First Affiliated Hospital of Soochow University were divided into a training cohort ( n=245) and an internal test cohort ( n=101) via stratified sampling at a 7∶3 ratio. And 143 patients from Nantong Third Hospital Affiliated to Nantong University served as an external validation cohort. The training cohort included 53 CK19-positive and 192 CK19-negative patients. The internal test cohort included 21 CK19-positive and 80 CK19-negative patients. The external validation cohort included 30 CK19-positive and 113 CK19-negative patients. Univariate logistic regression analysis was performed to identify potential factors associated with CK19 expression, and a clinical-radiologic model was constructed. The k-means clustering algorithm was applied to segment target HCC lesions into 3 subregions. Radiomic features were extracted and selected from these habitat subregions. Habitat radiomics models were constructed for the arterial phase (AP), portal venous phase, hepatobiliary phase (HBP), and combined phases (CP). Multivariate logistic regression analysis identified independent clinical and radiologic predictors of CK19 expression, and the optimal habitat model score was integrated to build a clinical-radiologic-habitat combined model. The area under the receiver operating characteristic curve (AUC) was used to evaluate model predictive performance. Recurrence-free survival (RFS) was analyzed using the Kaplan-Meier method and the differences in survival curves were compared with the log-rank test. Results:Univariate logistic regression analysis revealed that alpha-fetoprotein (AFP) ( OR=2.629, 95% CI 1.412-4.896, P=0.002), AP enhancement ( OR=3.636, 95% CI 1.642-8.052, P=0.001), AP peritumoral enhancement ( OR=2.219, 95% CI 1.084-4.542, P=0.029), and HBP peritumoral hypointensity ( OR=2.010, 95% CI 1.004-4.021, P=0.049) were potential factors associated with CK19 expression, which were incorporated into the clinical-radiologic model. In the internal and external validation cohorts, the AUC of the clinical-radiologic model was 0.690 (95% CI 0.590-0.778) and 0.650 (95% CI 0.565-0.727), respectively. The habitat radiomics model based on CP images demonstrated the highest performance. It achieved AUC of 0.729 (95% CI 0.622-0.836) and 0.725 (95% CI 0.607-0.842) in the internal and external validation cohorts, respectively. Multivariate analysis identified AFP ( OR=2.494, 95% CI 1.163-5.348, P=0.019), AP enhancement ( OR=5.230, 95% CI 1.868-14.643, P=0.002) and habitat radiomics model score ( OR=4.105, 95% CI 2.643-6.368, P<0.001) as independent predictors of CK19 positivity. Based on these factors, a combined clinical-radiologic-habitat combined model was established. The clinical-radiologic-habitat combined model achieved AUCs of 0.767 (95% CI 0.671-0.846) and 0.730 (95% CI 0.649-0.801) in the internal and external validation cohorts, respectively. Significant differences in RFS were observed between the CK19-positive group (25.1 month) and CK19-negative group (51.0 month) as predicted by the clinical-radiologic-habitat model ( χ2=4.17, P=0.041). Conclusion:The clinical-radiologic-habitat combined model based on Gd-EOB-DTPA-enhanced MRI habitat radiomics demonstrates good predictive performance for CK19 expression in HCC and offers valuable prognostic stratification for clinical practice.

Acute lung injury (ALI) is a significant complication of sepsis, characterized by high morbidity, mortality, and poor prognosis. Neutrophils, as critical intrinsic immune cells in the lung, play a fundamental role in the development and progression of ALI. During ALI, neutrophils generate neutrophil extracellular traps (NETs), and excessive NETs can intensify inflammatory injury. Research indicates that Taohe Chengqi decoction (THCQD) can ameliorate sepsis-induced lung inflammation and modulate immune function. This study aimed to investigate the mechanisms by which THCQD improves ALI and its relationship with NETs in sepsis patients, seeking to provide novel perspectives and interventions for clinical treatment. The findings demonstrate that THCQD enhanced survival rates and reduced lung injury in the cecum ligation and puncture (CLP)-induced ALI mouse model. Furthermore, THCQD diminished neutrophil and macrophage infiltration, inflammatory responses, and the production of pro-inflammatory cytokines, including interleukin-1β (IL-1β), IL-6, and tumor necrosis factor α (TNF-α). Notably, subsequent experiments confirmed that THCQD inhibits NET formation both in vivo and in vitro. Moreover, THCQD significantly decreased the expression of peptidyl arginine deiminase 4 (PAD4) protein, and molecular docking predicted that certain active compounds in THCQD could bind tightly to PAD4. PAD4 overexpression partially reversed THCQD's inhibitory effects on PAD4. These findings strongly indicate that THCQD mitigates CLP-induced ALI by inhibiting PAD4-mediated NETs.
Extracellular Traps/immunology* ; Acute Lung Injury/immunology* ; Animals ; Sepsis/immunology* ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Neutrophils/immunology* ; Male ; Protein-Arginine Deiminase Type 4/genetics* ; Mice, Inbred C57BL ; Humans ; Disease Models, Animal ; Cytokines/metabolism*

The China Cardiovascular Health and Disease Report 2024 has recently been released,offering a comprehensive and detailed assessment of the current status of cardiovascular diseases(CVD)and their associated risk factors in China.The report reveals that the number of CVD cases,as well as the overall and age-standardized incidence rates,continue to increase.Among these conditions,atherosclerotic cardiovascular disease(ASCVD)constitutes a major contributor to CVD-related mortality.Although ASCVD is largely preventable and controllable,the management of key modifiable risk factors-such as smoking,obesity,hypertension,dyslipidemia,and diabetes-remains suboptimal.This article systematically summarizes the prevalence,current management practices,and evidence-based prevention strategies for each major ASCVD risk factor,aiming to reinforce for clinicians the impor-tance of not only treating established ASCVD but also proactively guiding patients in the prevention and control of its underlying risk factors,thereby reducing the overall burden of ASCVD in terms of both prevalence and mortality.

OBJECTIVES: To evaluate the clinical efficacy of hospital-prepared Chinese medicine Feigan granules for influenza patients. This study has been registered at the International Traditional Medicine Clinical Trial Registry platform (ITMCTR2025000162). METHODS: A prospective observational study was conducted on influenza patients who visited the Fever Clinic of the First Affiliated Hospital, Zhejiang University School of Medicine between February and March 2024. Patients were divided into the observation group (Feigan granules combined with conventional Western medicine) and the control group (conventional Western medicine). Main symptoms (including fever, cough and sore throat) and secondary symptoms (including chest tightness, poor appetite, muscle soreness and dry mouth) were evaluated with traditional Chinese medicine (TCM) symptom scale on the first day of the patient's visit and the third day after treatment. The degrees of improvement in the TCM symptom scores before and after treatment were compared using paired rank-sum test, and the differences in the overall symptom efficacy index between two groups were compared using the Wilcoxon test. RESULTS: A total of 217 influenza patients were included. After treatment, the TCM symptom scores of both groups were significantly improved compared with those before treatment (all P<0.01). The median differences in the main symptom score before and after treatment in the observation and the control groups were 7 points (95%CI: 6.0-8.0) and 6 points (95%CI: 6.0-8.0), respectively. The median difference in the secondary symptom score was 3 points (95%CI: 2.0-4.0) in both groups. The median differences in the total score were 9 points (95%CI: 8.0-10.5) and 8 points (95%CI: 7.0-10.0) in the observation and control groups, respectively. In the subgroup with an initial cough score >2, the improvement rates of total score (97.06% vs. 92.59%) and secondary symptoms (92.31% vs. 85.11%) in observation group were significantly higher than those in the control group (P<0.05); while there was no significant difference in the improvement rate of the main symptoms (95.59% vs. 90.74%, P>0.05). CONCLUSIONS Feigan granules can improve the TCM syndromes of influenza patients, especially for patients with more severe cough.
Humans ; Prospective Studies ; Influenza, Human/drug therapy* ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/therapeutic use* ; Female ; Male ; Middle Aged ; Adult ; Aged ; Adolescent ; Young Adult ; Treatment Outcome

BACKGROUND: The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories. METHODS: This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex. RESULTS: In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight. CONCLUSIONS Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Adipose Tissue ; Body Fat Distribution ; Body Mass Index ; China/epidemiology* ; Cross-Sectional Studies ; Health Surveys ; Phenotype