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.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

AIM To investigate the tumor-suppressive mechanism of Guiqi Yiyuan Extract combined with cisplatin in Lewis lung cancer mice.METHODS Ten intact C57BL/6J mice were assigned to the blank group.Sixty additional mice were developed into Lewis lung cancer models bearing transplanted tumor and subsequently allocated into the model group,the cisplatin group(5 mg/kg),the high-dose Guiqi Yiyuan Extract group(6.6 g/kg),and the low-dose,medium-dose and high-dose Guiqi Yiyuan Extract combined with cisplatin group(1.6,3.3,6.6 g/kg+5 mg/kg),with 10 mice in each group.Mice in the blank and model groups received saline via daily gavage,while treatment groups were administered Guiqi Yiyuan Extract orally(once daily),and cisplatin injection intraperitoneally(once every other day).After 14 days of drug administration,mice were euthanized for endpoint analysis.The following assessments were conducted:general health status and body weight changes monitored throughout the study period;tumor excision and weighing for inhibition rate calculation;histopathological examination of tumors via hematoxylin-eosin(HE)staining;serum quantification of IL-1 β,IL-18 and HMGB1 by ELISA;ultrastructural analysis of tumor cell death using transmission electron microscopy(TEM);spatial localization of TXNIP and GSDMD-N in tumor sections via immunofluorescence(IF);and Western blot detection of TXNIP,NLRP3,Caspase-1,cleaved Caspase-1,GSDMD,GSDMD-N protein expressions in tumor tissues.RESULTS Compared to the model group,the cisplatin group and all combination therapy groups exhibited significant reduction in tumor weight(P＜0.05)and increased tumor suppression rate;enhanced tumor tissue necrosis with characteristic pyroptotic morphology;elevated serum levels of IL-1β,IL-18 and HMGB1(P＜0.05);and upregulated expressions of pyroptosis-associated proteins TXNIP,NLRP3,Caspase-1,cleaved Caspase-1,GSDMD and GSDMD-N(P＜0.05).The high dose combination group demonstrated optimal therapeutic efficacy(P＜0.05).CONCLUSION Guiqi Yiyuan Extract enhances cisplatin sensitivity,demonstrating synergistic anti-tumor effects in Lewis lung carcinoma-bearing mice.This combinatorial therapeutic effect likely involves modulation of the TXNIP/NLRP3/Caspase-1/GSDMD pathway.

Objective:To construct a framework for evaluating the quality of health economic evaluation methodology based on the pragmatic clinical trial.Methods:An evaluation framework was constructed based on existing quality evaluation tools for health economic evaluation other quality evaluation tools.The weights of each item in the framework were determined by the Delphi method,and the weighted average was calculated using the expert authority coefficient.Results:A total of 23 experts were consulted,and the expert authority coefficients were 0.88 and 0.90,respectively.The results of the Wilcoxon signed-rank test showed no statistically signifi-cant differences among the expert opinions in two rounds(P＞0.05).Finally,a framework with 3 dimensions and 8 items was estab-lished.Conclusion:The evaluation framework has high scientificity and reliability.

To investigate the in vitro inhibitory mechanism of Nymphaea candida total flavonoids(NCTF)against Staphylococcus aureus(S.aureus)and its safety in mice,this study first deter-mined the antibacterial effect of NCTF on the clinically isolated strain S.aureus-C1.Subsequently,the inhibitory mechanism of NCTF on S.aureus-C1 was explored by measuring its effects on bac-terial growth curves,microstructure,intracellular AKP and LDH levels,and biofilm formation.Safety evaluation included determination of LD50 and MDT in mice,as well as analysis of serum biochemical parameters,organ indices,and histopathological observations.Results showed that NCTF effectively inhibited S.aureus-C1 proliferation,with an inhibition zone diameter of(18.98±0.67)mm and a MIC of 6.25 g/L.A concentration of 2×MIC nearly completely suppressed bacte-rial growth.Scanning electron microscopy revealed structural damage to bacterial cells,including collapse and shrinkage.AKP and LDH assays indicated significantly increased AKP activity(P＜0.05)and decreased intracellular LDH activity(P＜0.05)in the supernatant of drug-treated groups,demonstrating NCTF-induced disruption of cell walls and membranes leading to leakage of AKP and LDH.Crystal violet staining of biofilms showed significant inhibition rates of(43.77±9.16)％and(61.71±9.82)％at 2 × MIC and 4 × MIC concentrations,respectively(P＜0.05).Safe-ty assessments indicated low toxicity of NCTF in mice,with transient effects that returned to nor-mal levels within a short period.These findings demonstrate that NCTF exhibits potent antibacte-rial activity against S.aureus-C1 by damaging bacterial cell structures,increasing cell wall/mem-brane permeability,reducing biofilm formation,and displaying low toxicity.This study provides scientific evidence for clinical drug screening against bovine mastitis and the development of Nym-phaea candida resources.

Objective:To construct a framework for evaluating the quality of health economic evaluation methodology based on the pragmatic clinical trial.Methods:An evaluation framework was constructed based on existing quality evaluation tools for health economic evaluation other quality evaluation tools.The weights of each item in the framework were determined by the Delphi method,and the weighted average was calculated using the expert authority coefficient.Results:A total of 23 experts were consulted,and the expert authority coefficients were 0.88 and 0.90,respectively.The results of the Wilcoxon signed-rank test showed no statistically signifi-cant differences among the expert opinions in two rounds(P＞0.05).Finally,a framework with 3 dimensions and 8 items was estab-lished.Conclusion:The evaluation framework has high scientificity and reliability.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

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.