Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Our previous research demonstrated that the Wenxia Changfu Formula (WCF), as a neoadjuvant therapy, inhibits M2 macrophage infiltration in the tumor microenvironment and prevents lung cancer metastasis. Given tumor-associated macrophages (TAMs) in epithelial-mesenchymal transition (EMT), this study investigated whether WCF impedes lung cancer metastasis by attenuating TAM-induced EMT in non-small cell lung cancer (NSCLC) cells. Utilizing a co-culture model treated with or without WCF, we observed that WCF downregulated cluster of differentiation 163 (CD163) expression in macrophages, reduced CCL18 levels in the conditioned medium, and inhibited the growth, invasion, and EMT of NSCLC cells induced by macrophage co-culture. Manipulation of CCL18 levels and Src overexpression in NSCLC cells revealed that WCF's effects are mediated through CCL18 and Src signaling. In vivo, WCF inhibited recombinant CCL18 (rCCL18)-induced tumor metastasis in nude mice by blocking Src signaling. These findings indicate that WCF inhibits NSCLC metastasis by impeding TAM-induced EMT via antagonistic modulation of CCL18, providing evidence for its potential development and clinical application in NSCLC patients.
Epithelial-Mesenchymal Transition/drug effects* ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Humans ; Animals ; Lung Neoplasms/metabolism* ; Chemokines, CC/antagonists & inhibitors* ; Mice ; Mice, Nude ; Drugs, Chinese Herbal/administration & dosage* ; Cell Line, Tumor ; Neoplasm Metastasis ; Tumor-Associated Macrophages/drug effects* ; Mice, Inbred BALB C ; Signal Transduction/drug effects*

Objective To investigate the characteristics of body fluid metabolic profile in patients with kidney stones based on surface-enhanced Raman spectroscopy,and to explore its application value and provide a reference for the screening of patients with kidney stones.Methods A total of 25 patients with kidney stones and 25 healthy controls were involved.Urine and blood samples were collected,whose spectra were measured with surface-enhanced Raman spectroscopy.The mean and difference spectra were plotted with origin software.The normalized data were processed with principal component analysis combined with linear discriminant analysis(PCA-LDA).Finally,the performance of the PCA-LDA method was evaluated with the receiver operating characteristic(ROC)curve.Results The levels of phosphatidylinositol,phenylalanine,palmitic acid/fatty acids,etc.in the urine of patients with kidney stones are higher than those in healthy controls,while the levels of components such as uracil and glycogen are lower.The content of methyl bands in the plasma of patients with kidney stones is higher than that of healthy controls,while the contents of glycogen,phosphatidylinositol,protein-tyrosine,phenylalanine,palmitic acid/fatty acid,hydroxyproline/tyrosine,and lipids are lower than those of healthy controls.Conclusion Surface-enhanced Raman spectroscopy can identify the changes in various metabolites in patients with kidney stones,and the combination of PCA-LDA and ROC analysis is helpful for the screening of patients.

Objective To explore the characteristics of myocardial injury in patients with acute myocardial infarction(AMI)complicated by pleural effusion and its effect on long-term prognosis.Methods It was a prospective single-center study.Patients with AMI who were admitted to hospital within 15 days from symptom onset and performed echocardiography and cardiac magnetic resonance imaging(CMR)during hospitalization were consecutively enrolled and assigned to the with-pleural effusion group and the without-pleural effusion group according to the echocardiography result.Baseline data,cardiac magnetic resonance myocardial injury index and echocardiography characteristics were compared between the two groups.The occurrence of major adverse cardiovascular and cerebrovascular events(MACCE)was recorded through outpatient follow-up and telephone follow-up,including all-cause death,re-infarction,revascularization,rehospitalization for congestive heart failure and stroke.Cox regression analysis was performed to analyze influencing factors of all-cause death.Results Among 211 patients,31(14.7%)patients had pleural effusion and 180(85.3%)had no pleural effusion.Compared with the group without pleural effusion,the left ventricular end-diastolic diameter was larger,and left ventricular ejection fraction assessed by echocardiography was lower in the group with pleural effusion(P＜0.05).There were no significant differences in infarct size,left ventricular end-diastolic volume,left ventricular end-systolic volume,left ventricular ejection fraction and the presence of microvascular obstruction and intramyocardial hemorrhage between the two groups in CMR(all P＞0.05).At a median follow-up of 31 months,MACCE occurred in 43(20.4%)patients,and there was no significant difference between the two groups(χ2=3.160,P=0.075).Six cases(2.8%)had all-cause death.The incidence of all-cause death was higher in the group with pleural effusion than that in the group without pleural effusion(9.7%vs.1.7%,P<0.05).There was no significant difference in the incidence of other adverse events between the two groups(P＞0.05).Multivariate Cox regression analysis showed that advanced age and presence of pleural effusion were independent risk factors of all-cause death during follow-up.Conclusion Patients with AMI combined with pleural effusion have more severe myocardial injury and higher all-cause mortality.

Objective To investigate the association between intraoperative hypotension and post-operative acute kidney injury(AKI)in patients undergoing brain tumor resections.Methods A total of 428 patients undergoing elective craniotomy for tumor resection were selected,276 males and 152 females,aged≥18 years,BMI 15-36 kg/m2,ASA physical statusⅡ orⅢ.Based on postoperative occurrence of AKI,the patients were divided into two groups:the AKI group and the control group.This study defined three thresholds for hypotension,including MAP during surgery below 65 mmHg,60 mmHg,and 55 mmHg.Multivariate logistic regression was used to analyze the correlation between intraoperative hypotension and postoperative AKI under three thresholds.Results A total of 107 patients had postoperative AKI.The re-sults of multivariable regression analysis indicated that intraoperative MAP＜65 mmHg(OR = 1.11,95%CI 1.03-1.20,P = 0.010)and intraoperative MAP＜60 mmHg(OR = 1.12,95%CI 1.02-1.23,P = 0.017)were associated with postoperative AKI.Conclusion Intraoperative MAP＜65 mmHg or 60 mmHg is associated with postoperative AKI in patients undergoing brain tumor resection.

Objective To understand the infectious pathogen characteristics and drug sensitivity of hospitalized patients in the respiratory intensive care unit (RICU) of Renmin Hospital of Wuhan University. Methods Bacterial culture samples sent to the RICU of our hospital from January 2020 to December 2022 were retrospectively analyzed. The bacterial types were identified by Bruker mass spectrometer, and the Phoenix 100 was used for drug sensitivity analysis. The antimicrobial susceptibility was analyzed by WHONET 5.6 software. Results A total of 1 157 strains of bacteria were isolated, including 878 strains of Gram-negative bacteria (75.89%) and 279 strains of Gram-positive bacteria (24.11%). The top five with the highest detection rate were Acinetobacter baumannii (25.50%), Pseudomonas aeruginosa (18.76%), Klebsiella pneumoniae (13.83%), Staphylococcus aureus (6.57%) and Escherichia coli (5.70%). Among them, Acinetobacter baumannii was extremely drug-resistant, only showing relatively high sensitivity to colistin, minocycline, and tigecycline. Staphylococcus aureus accounted for the highest proportion of Gram-positive bacteria (6.57%), with methicillin-resistant Staphylococcus (MRSA) showing a continuous increase. Conclusion In the past three years, Gram-negative bacteria have been the main pathogenic bacteria detected in the respiratory intensive care unit of our hospital. The main bacteria are Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae, which have a high resistance rate to various antibiotics. Therefore, clinical monitoring of resistant strains in RICU should be strengthened to facilitate rational use of antibiotics and improve antibacterial effect.