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.

BACKGROUND:Cannabidiol is effective in ameliorating the body's inflammatory response,but no clear mechanistic studies have been conducted to ameliorate skeletal muscle inflammation induced by exhaustive exercise. OBJECTIVE:To explore the mechanism by which cannabidiol improves skeletal muscle inflammation during exhaustive exercise by using transcriptome sequencing technology. METHODS:Thirty-six Sprague-Dawley rats were randomly divided into six groups:blank control group,exercise coconut oil group,exercise control group,50 mg/kg cannabidiol group,60 mg/kg cannabidiol group,and 70 mg/kg cannabidiol group,with six rats in each group.Except for rats in the blank control group,rats in each group were subjected to swimming exercise for 9 days to produce the exhaustive exercise model.At the end of each swimming exercise,rats in the cannabidiol groups were given 2 mL of fat-soluble cannabidiol at different concentrations(50,60,and 70 mg/kg)by gavage;rats in the exercise coconut oil group were given the same volume of coconut oil by gavage until the end of the exercise on the 9th day;and rats in the blank control group and the exercise control group were not given any special treatment.The levels of inflammatory factors and differentially expressed genes in the skeletal muscle of rats in each group were determined using ELISA and transcriptome sequencing techniques.Differentially expressed genes obtained were subjected to KEGG analysis,and the accuracy of the sequencing data was verified by fluorescence quantitative PCR. RESULTS AND CONCLUSION:The results of ELISA showed that the contents of interleukin-6(P<0.05),tumor necrosis factor-α(P<0.01),interleukin-10 and other inflammatory factors in the exercise group increased significantly compared with the blank control group and the coconut oil group.After cannabidiol intervention,the mass concentrations of interleukin-6 and tumor necrosis factor-α showed a sequential decrease with increasing cannabidiol concentration.By comparing GO and KEGG databases,the functional properties of differentially expressed genes were analyzed,and the results showed that the differentially expressed genes were mainly involved in the tumor necrosis factor signaling pathway and the Toll-like receptor signaling pathway.RT-qPCR results showed that the trends of five randomly selected differentially expressed genes were in agreement with the transcriptome sequencing results.To conclude,cannabidiol can improve skeletal muscle inflammation caused by exhaustive exercise.

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.

ObjectiveTo investigate the mechanism of Huangqi Gegentang （HGT） in the treatment of type 2 diabetes mellitus （T2DM） through the application of proteomic techniques. MethodsThe rat model of T2DM was established by streptozotocin combined with a high-fat， high-sugar diet. Thirty-two male SD rats were randomized into four groups： blank， model， HGT （8.10 g·kg^-1·d^-1）， and positive control （metformin hydrochloride， 76.5 mg·kg^-1·d^-1）. After 6 weeks of drug intervention， the fasting blood glucose level was measured， and an oral glucose tolerance test （OGTT） was performed. The area under the curve （AUC） was calculated. Enzyme-linked immunosorbent assay was performed to assess the level of glycated hemoglobin （GHbA1c） in the serum. The limulus amebocyte lysate assay was employed to measure the serum level of lipopolysaccharide （LPS）. Pathological changes in the colon were observed by hematoxylin-eosin staining. The mRNA levels of pro-inflammatory cytokines including tumor necrosis factor （TNF）-α， interleukin （IL）-6， and IL-1β in the colon tissue were quantified via Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. Additionally， the protein and mRNA levels of zonula occludens-1 （ZO-1）， Occludin， and Claudin-1 in the colon tissue were assessed by Western blot and Real-time PCR， respectively. Label-free quantitative proteomics was employed to identify the differentially expressed proteins between the colon tissue samples from the blank， model， and HGT groups. Key proteins identified were subsequently validated by Western blot and Real-time PCR. Finally， bioinformatics analysis was conducted on the differentially expressed proteins. ResultsCompared with the blank group， the model group exhibited increased fasting blood glucose， AUC， and GHbA1c levels （P<0.01）， damaged colonic mucosal epithelial structure and inflammatory cell infiltration， up-regulated mRNA levels of TNF-α， IL-6， and IL-1β in the colon and an increase in serum LPS content （P<0.05， P<0.01）， and down-regulated protein and mRNA levels of ZO-1， Occludin， and Claudin-1 in the colon （P<0.01）. Compared with the model group， the HGT group showed reductions in fasting blood glucose， AUC， and GHbA1c （P<0.01）， alleviated damage to the colonic mucosal epithelium， down-regulated mRNA levels of TNF-α， IL-6， and IL-1β in the colon， a reduction in serum LPS content （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of ZO-1， Occludin， and Claudin-1 in the colon （P<0.05， P<0.01）. Proteomics analysis identified 70 differentially expressed proteins that exhibited a downward trend in the model group relative to the blank group and an upward trend in the HGT group relative to the model group. These findings were corroborated by Western blot and Real-time PCR， which confirmed that the protein and mRNA levels of mucin 2 （Muc2） and transforming growth factor （TGF）-beta receptor 1 （Tgfbr1） in the colon tissue were consistent with the proteomic data. Bioinformatics analysis showed that these 70 differentially expressed proteins identified were significantly enriched in multiple signaling pathways， among which the TGF-β and advanced glycation endproduct （AGE）/receptor for advanced glycation endproduct （RAGE） signaling pathways were closely associated with damage to the intestinal mucosal barrier. This suggests that HGT may ameliorate intestinal mucosal barrier damage by regulating these pathways. ConclusionHGT potentially exerts anti-T2DM effects by influencing AGE/RAGE and TGF-β signaling pathways， thereby contributing to the restoration of the intestinal mucosal barrier.

Objective: To investigate the effects of Zuogui Jiangtang Yishen Formula (左归降糖益肾方, ZGJTYSF) in regulating the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3)/caspase-1/gasdermin D (GSDMD) signaling axis on pyroptosis in rats with diabetic kidney disease (DKD). Methods: Fifty male specific pathogen-free (SPF) grade Goto-Kakizaki (GK) rats (12 weeks old) were fed a high-fat diet for one month to establish an early DKD model. Model establishment was confirmed when fasting blood glucose (FBG) ≥ 11.1 mmol/L and urinary albumin-to-creatinine ratio (uACR) ≥ 30 mg/g. The successfully modeled early DKD rats were randomly divided by random number table into five groups (n = 10 per group): model group; dapagliflozin group (1.0 mg/kg, by gavage, served as positive control); and low-, medium-, and high-dose of ZGJTYSF groups (4.9, 9.9, and 19.9 g/kg, respectively, by gavage). Age-matched male SPF Wistar rats (n = 10) served as control group. Rats in control and model groups were gavaged with equivalent volumes of distilled water. Treatment lasted 12 weeks. Changes in uACR, FBG, and renal function were observed in all groups. Hematoxylin-eosin (HE), periodic acid-Schiff (PAS), and Masson staining were used to observe renal histopathological changes. Immunohistochemistry was performed to detect the localization and expression of caspase-1, GSDMD, and NLRP3 in rat renal tissues. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL) was utilized to detect pyroptosis in renal tissues. Quantitative real-time polymerase chain reaction (qPCR) and Western blot were applied to detect mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, interleukin (IL)-1β, and IL-18. Results: Compared with model group, all doses of ZGJTYSF showed reductions in FBG, with medium- and high-dose of ZGJTYSF groups demonstrating significant decreases at week 8 and 12 (P < 0.05). For uACR, all doses of ZGJTYSF groups exhibited a decreasing trend, with high-dose of ZGJTYSF group being significantly lower than low- and medium-dose of ZGJTYSF groups at week 12 (P < 0.05) and showing no significant difference from dapagliflozin group (P > 0.05). No significant differences in renal function parameters (serum creatinine, blood urea nitrogen, and uric acid) were observed among groups (P > 0.05). Histopathological examination revealed milder glomerular and tubular lesions in both ZGJTYSF groups and dapagliflozin group, with renal pathological changes in high-dose of ZGJTYSF group resembling those in dapagliflozin group. Immunohistochemistry demonstrated significantly reduced expression of caspase-1, GSDMD, and NLRP3 in renal tissues of dapagliflozin group and high-dose of ZGJTYSF group compared with model group (P < 0.05 or P < 0.01), while the differences in low- and medium-dose of ZGJTYSF groups were not statistically significant (P > 0.05). TUNEL assay showed significantly fewer TUNEL-positive cells in renal tissues of dapagliflozin and high-dose of ZGJTYSF groups (P < 0.01), indicating a marked reduction in pyroptotic cells. Molecular analysis revealed that compared with model group, both dapagliflozin and high-dose of ZGJTYSF groups showed significantly downregulated mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, IL-1β, and IL-18 in renal tissues (P < 0.01), while low- and medium-dose of ZGJTYSF groups showed downward trends without statistical significance (P > 0.05). Conclusion ZGJTYSF may inhibit renal pyroptosis by regulating the NLRP3/caspase-1/GSDMD signaling axis, thereby preventing and treating early renal injury in DKD and delaying the onset and progression of DKD.

Objective:To investigate the effect of "simulated Chinese medicine nursing clinic" teaching on syndrome differentiation ability among nursing students and the teaching effect of this method.Methods:A total of 325 students were randomly divided into conventional teaching group with 163 students (receiving conventional nursing teaching) and real situational teaching group with 162 students (receiving "simulated Chinese medicine nursing nursing clinic" teaching at the same time). A self-made questionnaire for syndrome differentiation-based nursing ability, assessment scores of traditional Chinese medicine nursing theories and skills, and a teaching satisfaction questionnaire were used for evaluation.Results:After intervention, the real situational teaching group (the treatment group and the experience group) had significantly higher socres of syndrome differentiation-based nursing ability (mastery of four diagnostic methods, diagnosis of syndromes, analysis of syndromes, determination of nursing principles, and development of nursing regimens) than the conventional teaching group (the treatment group and the conventional teaching group: 8.97±1.00/8.47±1.20/8.33±1.06/8.30±1.26/7.89±1.13 and 7.96±1.14/7.29±1.36/7.14±1.18/7.39±1.30/7.26±1.18, P<0.05; the experience group and the conventional teaching group: 8.39±1.10/8.17±1.15/8.07±1.06/7.97±1.26/7.73±1.38 and 7.96±1.14/7.29±1.36/7.14±1.18/7.39±1.30/7.26±1.18, P<0.05). The real situational teaching group had a significantly higher overall degree of satisfaction with teaching than the conventional teaching group [160 (97.6%) and 150 (92.0%), P<0.05]. Conclusions:The "simulated Chinese medicine nursing clinic" teaching program effectively enhances the thinking of syndrome differientiation and related abilities for nursing, improves the learning effect of traditional Chinese medicine nursing theories and skills, and increases the learning interest in traditional Chinese medicine nursing among nursing students.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.