Objective To investigate the expression of insulin-like growth factor Ⅱ mRNA-binding protein 3( IMP3 ) in transitional cell carcinoma of bladder( TCCB ) and its clinical significance. Methods The IMP3 expressions in 6 normal bladder tissues and 48 TCCB tissues were determined by immunohistochemistry staining, and the relationships between IMP3 expression and gender, age, pathological grading and staging were analyzed statistically. Results The positive expression rate of IMP3 was 62.5% ( 30/48 ) in bladder cancer,which were significantly higher than that in normal control ( 0/6 ) ( P ＜ 0. 05 ). The positive rate of IMP3 expression were significantly lower in superficial TCCB ( 46. 15%, 12/22 ) or early TCCB [ Grade Ⅰ 12. 5%(1/8) ,Grade Ⅱ 60. 0% (12/20) ] than that in invasive TCCB [T2 or above,81.8% (18/22) ] or advanced TCCB [ Grade Ⅲ ,85% ( 17/20 ) ] ( Ps ＜ 0. 05 ). Conclusion IMP3 is a promising biomarker for eraly detection and assessment of the malignancy degree in TCCB.

OBJECTIVETo investigate the effect of transperineal puncture drug injection in the treatment of chronic prostatitis.

METHODSForty cases of chronic prostatitis underwent transperineal puncture drug injection. Bacterial culture and antimicrobial agent sensitivity tests were conducted on the prostatic fluid of the patients. A sensitive antimicrobial agent was selected, mixed with lidocaine and dexamethasone, and injected transperineally into the prostate at intervals of 7 days and 4 times as one course. After one month, the effect was evaluated and the patients were followed up for 6 months.

RESULTSAmong the 40 cases, the cure rate was 52.5% (21/ 40), the alleviation rate 40% (16/40), the nullify rate 7.5% (3/40) and the total effectivity rate 92.5%. No relapse was found in the 28 followed-up cases.

CONCLUSIONTransperineal puncture drug injection is a safe and effective way in the treatment of chronic prostatitis.

Adult ; Anti-Bacterial Agents ; administration & dosage ; Chronic Disease ; Follow-Up Studies ; Humans ; Injections ; methods ; Male ; Middle Aged ; Perineum ; Prostate ; Prostatitis ; drug therapy

Objective To construct N6-methyladenosine related long non-coding RNA(LncRNA)pairing model for renal cell carcinoma based on bioinformatics analysis of the cancer ganome atlas(TCGA)database and to explore its prognosis value.Methods Transcriptome data of RNA-sep for renal cell carcinoma and its related clinical information were downloaded from the TCGA database.Perl software was used to organize and separate LncRNA and messenger RNA(mRNA)from the transcriptome data.A total of 564 tissues from renal cell carcinoma cases and 72 normal tissues were obtained,and thus 540 renal cancer patients were eventually included.Random data table method was used to divide 540 patients with renal cancer into a training group(n=275)and a validation group(n=265)by caret.M6A related LncRNA pairing models were established based on the single factor and multivariate COX regression analysis.The risk assessment equation was obtained using the LASSO regression algorithm.The risk scores were calculated based on this equation,and the optimal critical point of the median risk value was applied to divide all patients into high-risk and low-risk groups.Kaplan-Meier survival analysis was used to make a survival curve for the differences between high and low risk groups in the overall sample.The gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analyses were conducted using the Cluster Profiler software package.The relationship between N6-methyladenosine related LncRNA pairing model and immune cell infiltration was analyzed by R software.Results Kaplan-Meier survival analysis showed the total survival time of patients in the low-risk group was significantly higher than that of patients in the high-risk group of the training group(P<0.05).Compared with high risk group,the overall survival time of patients(G1～2,G3～4,Ⅰ～Ⅱ,or Ⅲ～Ⅳ,age≤65 years,or patients>65 years old)in low risk group was higher(P<0.05).Differential gene enrichment analysis was obtained for high and low risk groups,which mainly enriched with many differential genes such as muscle contraction,rhabdomytic cell differentiation,myofibril,receptor activation activity,and vascular smooth muscle contraction.The highest driver genes in high risk group and low risk group exhibited mutation frequency and mutation information,and their risk score was positively correlated with the degree of T cell and plasma cell infiltration(r=0.638,P=0.001).Conclusion Bioinformatics-based analysis of the N6-methyladenosine related LncRNA pairing models can be helpful to predict the prognosis of patients with renal cancer.It provides new ideas for the prognosis evaluation and optimal treatment strategy of renal cancer,and contributes to further analyzing the molecular mechanism of the occurrence and development of gastric cancer in the future.