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.

With the continuous advancement of internet technology and the improvement of internet literacy among the general population, the concept of online-offline integration in internet hospitals has gradually gained acceptance and has been applied and developed both domestically and internationally. In thoracic surgery, the applicability of this model lies in enhancing efficiency and delivering comprehensive, diversified, and personalized medical services to address complex and severe conditions. However, challenges such as hardware limitations and diagnostic/treatment risks persist during the implementation of internet hospitals. Through future in-depth and localized research, the online-offline integration of internet hospitals is expected to undergo further development and refinement. This progress will facilitate its integration into clinical practice in thoracic surgery, ultimately providing patients with improved medical care services.

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.

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*

INTRODUCTION: The primary objective of this guideline is to establish evidence-based recommendations for the clinical use of parenteral nutrition (PN) in adult patients within the acute hospital setting in Singapore. METHOD: An expert workgroup, consisting of healthcare practitioners actively involved in clinical nutrition support across all public health institutions, systematically evaluated existing evidence and addressed clinical questions relating to PN therapy. RESULTS: This clinical practice guideline developed 30 recommendations for PN therapy, which cover these key aspects related to PN use: indications, patient assess-ment, titration and formulation of PN bags, access routes and devices, and monitoring and management of PN-related complications. CONCLUSION This guideline provides recommendations to ensure appropriate and safe clinical practice of PN therapy in adult patients within the acute hospital setting.
Humans ; Singapore ; Parenteral Nutrition/adverse effects* ; Adult

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