Objective To explore the correlation of MET status in patients with advanced prostatic acinar adenocarcinoma with the clinical pathological parameters and prognosis. Methods The specimen from 135 patients with advanced prostatic acinar adenocarcinoma was included. The expression of c-MET protein was detected via immunohistochemistry, and MET gene amplification was assessed by fluorescence in situ hybridization. The relationships of c-MET expression and gene amplification with clinicopathological features and prognosis were analyzed. Results The positive expression rate of c-MET was 52.60% (71/135). Compared with the c-MET expression in adjacent tissues, that in tumor tissues showed lower heterogeneous expression. Among the cases, 1.71% (2/117) exhibited MET gene polyploidy, but no gene amplification was detected. Positive c-MET expression was significantly correlated with high Gleason scores and grade groups (P=0.0073). However, no significant relationship was found between c-MET expression and progression-free survival or post-treatment t-PSA levels. Conclusion c-MET protein is expressed at a relatively low level in advanced prostatic acinar adenocarcinoma, suggesting that c-MET may not be a viable target for ADC drug development in prostatic acinar adenocarcinoma.

OBJECTIVE: Several epidemiological observational studies have related particulate matter (PM) exposure to Inflammatory bowel disease (IBD), but many confounding factors make it difficult to draw causal links from observational studies. The objective of this study was to explore the causal association between PM _2.5 exposure, its absorbance, and IBD. METHODS: We assessed the association of PM _2.5 and PM _2.5 absorbance with the two primary forms of IBD (Crohn's disease [CD] and ulcerative colitis [UC]) using Mendelian randomization (MR) to explore the causal relationship. We conducted two-sample MR analyses with aggregated data from the UK Biobank genome-wide association study. Single-nucleotide polymorphisms linked with PM _2.5 concentrations or their absorbance were used as instrumental variables (IVs). We used inverse variance weighting (IVW) as the primary analytical approach and four other standard methods as supplementary analyses for quality control. RESULTS: The results of MR demonstrated that PM _2.5 had an adverse influence on UC risk (odds ratio [ OR] = 1.010; 95% confidence interval [ CI] = 1.001-1.019, P = 0.020). Meanwhile, the results of IVW showed that PM _2.5 absorbance was also causally associated with UC ( OR = 1.012; 95% CI = 1.004-1.019, P = 0.002). We observed no causal relationship between PM _2.5, PM _2.5 absorbance, and CD. The results of sensitivity analysis indicated the absence of heterogeneity or pleiotropy, ensuring the reliability of MR results. CONCLUSION Based on two-sample MR analyses, there are potential positive causal relationships between PM _2.5, PM _2.5 absorbance, and UC.
Humans ; Mendelian Randomization Analysis ; Particulate Matter/analysis* ; Polymorphism, Single Nucleotide ; Inflammatory Bowel Diseases/genetics* ; Air Pollutants/analysis* ; Crohn Disease/genetics* ; Colitis, Ulcerative/genetics* ; Genome-Wide Association Study ; Risk Factors ; Environmental Exposure

Cooling system of low temperature is a key component of superconducting magnetic resonance equipment in maintaining the superconducting state.This paper investigated the contents and methods of routine and systematic maintenance of superconducting magnetic resonance equipment through analyzed the principle of structure and composition of cryogenic refrigeration system,and ordered the work flow of water refrigeration and helium refrigeration.In view of the phenomenon of cold head fault,water circulation fault and helium circulation fault in the operation of cryogenic refrigeration system,this paper analyzed,troubleshot and dealt the fault causes,and investigated the maintenance path on the perspective from structure to function,which effectively solved the occurred faults in the operation of equipment.Managers of superconducting magnetic resonance equipment should strengthen the accumulation for theoretical knowledge of cryogenic refrigeration systems,and summarize management experience of daily maintenance,and improve capabilities of analyzing and processing fault,and provide technical support for operation quality and security guarantee of equipment.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Diabetic nephropathy (DN) is one of the complications of diabetes mellitus,which is accom-panied by severe microvascular lesions.and is also the most common inducing factor of end-stage chronic kid-ney disease.The traditional treatment of DN cannot fundamentally cure diabetes and its complications,and new treatment methods need to be explored urgently.At present,the diagnosis and treatment strategy of using mesenchymal stem cells-derived exosomes (MSCs-exo) has become a research hotspot in the early diagnosis and clinical treatment of DN.A number of studies have confirmed that MSCs-exo has high efficacy and safety in the treatment of DN,and MSCs-exo plays a renoprotective role in diabetic nephropathy models by transfer-ring its own contents to the damaged tissue.This article focuses on the research progress and therapeutic po-tential of mesenchymal stem cell-derived exosomes in regulating autophagy in diabetic nephropathy,in order to provide new ideas and methods for the treatment of DN.

This study retrospectively analyzed the clinical data of four patients with malignant tumor-induced ureteral strictures admitted to our hospital. All patients successfully underwent ureteroscopic metal stent placement surgery under real-time ultrasound guidance, with a surgical duration of (64±33) minutes. Postoperatively, there was a creatinine decrease of (74±127) mmol/L. Only two cases experienced Clavien-Dindo grade I complications postoperatively. The stents were well positioned in all patients, with a postoperative hospital stay of (2.5±0.6) days. This surgical approach for malignant tumor-induced ureteral obstruction can compensate for the limitations of endoscopic visualization.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Although geriatric diseases are complicated due to the coexistence of many diseases,they often have a common pathological basis and are closely related to the pathogenesis of deficiency and excess in traditional Chinese medicine.Exploring the characteristics of the pathogenesis of deficiency and excess diseases in the elderly is helpful to keep simplicity and restrain complexity,grasp the law of occurrence and development of diseases in the elderly as a whole,and give full play to the advantages of traditional Chinese medicine in the prevention and treatment of chronic diseases.Based on the fundamental characteristics of deficiency and excess in senile diseases,researcher Hu Jingqing further summarized that"essence deficiency,Yin deficiency,Yang deficiency,qi deficiency,blood deficiency"and"qi stagnation,phlegm dampness,blood stasis,fire and heat,and latent wind"are the most common pathogenesis in the occurrence and development of senile diseases.Among them,deficiency is the basic pathogenesis of senile diseases,especially deficiency of kidney essence.Excess disease is the key pathogenesis of the development and changes of senile diseases.Qi stagnation is often the initial step in the development of senile diseases.Phlegm dampness and blood stasis are the pathological products of"excess due to deficiency"and are also the main secondary pathogenesis of senile diseases.In clinical identification of senile diseases,attention should be paid to grasping the pathogenesis of deficiency and excess and its concurrent changes.