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.

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.

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

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*

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.