To assess the current status of early surgical site infections following prosthetic implantation in plastic surgery across four provincial-level administrative regions in China, and to explore the effectiveness of standardized training for infection prevention and control.

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:To explore the value of dual-layer spectral CT virtual monoenergetic images (VMI) in contrast-enhanced abdominal CT scans with reduced contrast medium volume in pediatric tumor patients.Methods:The study is a self-matched case-control study. From January to October 2024, pediatric patients admitted to Shandong Cancer Hospital with abdominal tumors who underwent low contrast dose spectral CT contrast-enhanced scans during follow-up were prospectively included. A total of 47 patients aged (6.2±2.2) years (4-14 years) were enrolled. Usual contrast dose enhanced CT served as the conventional-dose group, while the follow-up low-dose spectral CT scans employed a protocol with half the contrast agent dose (low-dose group). Images were reconstructed as conventional CT images and VMI at 45, 55, and 65 keV. Using muscle as the reference background, differences in CT values and contrast-to-noise ratio (CNR) in the aorta, kidneys, liver, and spleen were compared between the low-dose group and conventional-dose group. Multi-group comparisons were performed using the Friedman test. Post-hoc pairwise comparisons were conducted with Bonferroni correction for P-values. Results:CT values and CNRs for all measured regions progressively increased with decreasing keV levels in spectral CT VMI. Significant overall differences were found in CT values and CNRs for the aorta, kidneys, liver, and spleen among the low-dose group (all VMIs) and the conventional-dose group (all P<0.001). At 65 keV VMI in the low-dose group, both CT values and CNRs (except for the liver CNR) were significantly lower than those in the conventional-dose group (all adjusted P<0.05). At 55 keV VMI in the low-dose group, CT values and CNRs for all regions did not show statistically significant differences compared to the conventional-dose group (all adjusted P>0.05). At 45 keV VMI in the low-dose group, CT values for all structures and CNR for the spleen were significantly higher than those in the conventional-dose group (all adjusted P<0.05). However, no statistically significant difference was found in CNRs for the aorta, kidneys, and liver (adjusted P=1.000, 0.313, and 0.503, respectively). Conclusion:When the contrast dose is halved, spectral CT 45 keV VMI enhances CT attenuation values and CNR in the abdomen of pediatric tumor patients, while 55 keV VMI provides image quality comparable to that of conventional-dose CT.

Objective:To explore the characteristics of the brain functional networks in children with spastic cerebral palsy (SCP) while at rest and to correlate them with motor functioning.Methods:Thirty-six children with SCP were enrolled as the SCP group, while thirty-four age-matched healthy children were recruited as the control group (the HC group). Functional near-infrared spectroscopy was used to detect changes in the concentration of oxygenated hemoglobin in the children′s cerebral cortex while at rest. The left prefrontal cortex (LPFC), right prefrontal cortex (RPFC), left motor cortex (LMC), and right motor cortex (RMC) were selected as regions of interest. Phase locking values (PLVs) were used to evaluate the strength of functional connectivity (FC) among these brain regions, and graph theory methods were applied to analyze the topological properties of the brain networks. Motor functioning was assessed using the gross motor function measure (GMFM).Results:The analyses of FC strength revealed that the SCP group had significantly weaker FC among all of the regions of interest while at rest compared to the HC group. Their PLVs for LPFC-RPFC, LPFC-RMC, RPFC-RMC and LMC-RMC connectivity were all significantly smaller. Graph theory analysis showed that the SCP group had significantly lower global efficiency (GE) and smaller clustering coefficients (CCs) and network density (D), while their characteristic path lengths were significantly longer. According to the correlation analysis, the PLVs for LMC-RMC connections in the SCP group were positively correlated with their scores on dimensions D and E of the GMFM ( r=0.496 and r=0.579 respectively). GE ( r=0.587 and r=0.642) and CC ( r=0.318 and r=0.759) showed similar significant positive correlations with GMFM dimensions D and E. Conclusions:At rest, the functional networks in the brains of children with SCP exhibit abnormalities closely associated with their motor dysfunction.

OBJECTIVE To develop a long-acting light-protective nanogel with both physical barrier and chemical clearance functions， and evaluate its performance. METHODS The photoprotective nanogel composed of mussel mucin and sodium hyaluronate was constructed based on a fullerenol-cerium oxide composite nano system， namely fullerenol-cerium oxide nanogel （FCN）， and was characterized. The antioxidant capacity of FCN was evaluated using in vitro free radical scavenging experiments； its UV shielding ability was assessed by using an SPF value detector； its biosafety was assessed according to the requirements of the Guidelines for Drug Safety Evaluation； skin adhesion was assessed using small animal 3D live imaging technology； its sun protection ability was assessed through skin sunscreen detection and histopathological observation. RESULTS The average particle sizes of cerium oxide and fullerenol nanoparticles in FCN were about 20 and 10 nm， respectively， and FCN exhibited good UV absorption and free radical scavenging abilities. SPF value of FCN was 58.95±0.82， and the ultraviolet A protection level value was 6.21±0.15. No pathogenic colonies such as Staphylococcus aureus， were detected in the nanogel， and the contents of lead， arsenic， mercury and cadmium all met the standards for pharmaceutical excipients； FCN group did not show any irritating reactions such as erythema， edema， or desquamation； blood biochemical indicators of the FCN group were within the normal reference range. The material clearance rate of mice in the artificial sweat flushing group was less than 30%， while the material clearance rate of mice in the dry cleaning group reached about 92%. The mice in the protective group did not show obvious erythema or ulcer formation throughout the experiment. Histopathology showed that the fibers were arranged in an orderly manner， and the number of collagen fibers was close to that of the control group. CONCLUSIONS The FCN formulation constructed in this study meets the relevant requirements of the Chinese Pharmacopoeia， has good safety and skin compatibility， and achieves dual synergistic protection of UV shielding and free radical scavenging.

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: 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.