Objective To compare levels of glycosylated hemoglobin detected by 3 kinds of analytic instruments .Methods 75 samples were measured by D-10 glycosylated hemoglobin automatic analyzer(ionexchange chromatography) ,HA-8160 glycosylated hemoglobin automatic analyzer(affinity chromatography) and 7170A automatic analyzer(immune turbidimetry) .Results were tested by the homogeneity of variance ,the one-way analysis of variance and correlation analysis .Results There was a positive correlation between D-10 glycosylated hemoglobin automatic analyzer and HA-8160 glycosylated hemoglobin automatic analyzer(r2 =0 .996) , the linear equation was Y=0 .953X+0 .519 .There was a positive correlation between D-10 glycosylated hemoglobin automatic ana-lyzer and 7170A automatic analyzer(r2 =0 .996) ,the linear equation was Y=0 .925X+0 .576 .There was a positive correlation be-tween HA-8160 glycosylated hemoglobin automatic analyzer and 7170A automatic analyzer(r2 =0 .998) ,the linear equation was Y=0 .969 X+0 .081 .Conclusion In the premise of quality control in laboratory ,three different instrument can use to detect the level of glycosylated hemoglobin .

Objective To investigate the role and value of interleukin (IL)-17,receptor activator of nuclear factors κB-ligand (RANKL),osteoprotegerin (OPG) in the pathogenesis of AS by detecting the expression of IL-17,RANKL,OPG.Methods IL-17,RANKL,OPG in 44 AS and 15 healthy controls were measured by ELISA.HLA-B27 was measured by flow cytometry.T-test,Spearman's correlation analysis were used for statisical analysis.Results ① Serum IL-17 [(45±12) pg/ml],RANKL [(354±96) pg/ml] levels and RANKL/OPG [(6.5±3.4) pg/ml] ratio were significantly higher in AS patients than those in normal controls (t=11.18,P＜0.05; t=18.66,P＜0.05; t=15.48,P＜0.05),and the serum RANKL levels was higher in AS patients in middle and late period than that in AS patients in early stage (t=47.02,P＜0.05).The serum OPG levels was higher in AS patients in middle and late period than that in AS patients in early stage (t=15.48,P＜0.05).② There were positive linea correletion,respectively,between the serum levels of IL-17 and RANKL (r=0.532,P=O.021),and between serum levels of IL-17 and disease activities of BASDAI (r=0.625,P=0.023),between serum levels of RAN KL and disease activities of BASDAI (r=0.431,P=0.016).Conclusion The surem levels of IL-17 and RANKL are increased in AS patient.

Objective To detect the expression of T helper 17 (Th17) cells in the peripheral blood of patient with ankylosing spondylitis (AS),and discuss its role in thc pathogenesis of AS.Methods Twenty AS patients and fifteen healthy controls were enrolled in the study.Th17 (IL-17),Th1 (IFN-γ),Th2 (IL-4)cells and HLA-B27 of their peripheral blood were analyzed by flow cytometry,at the same time,the levels of ESR and CRP were also measured in order to analyze thc relation of Th17 and HLA-B27,ESR as well as the CRP level.The statistical analysis was carried out with single-sample t-test and Speraman's correlation test.Results The level of Th17 cells was significantly higher in the perpipheral blood of AS patients[(2.6±0.8 )%] than those in healthy controls[ (1.1±0.4)% ] (P＜0.01).The level of Th 1 cells was significantly lower in the peripheral blood of AS patients[(3.9±0.8)%] than those in healthy controls[(5.1±1.3)%] (P＜0.01)and the level of Th2 cells was not different in the peripheral blood of AS patients[(4.1±1.6)%] when compared to healthy controls[ (3.1±1.4)% ] (P＞0.05).Th 17 cells was not significantly correlated with the percentage and mean fluorescent intensity of HLA-B27,ESR,CRP(P＞0.05); but there was a tendency that increased expression level of Th17 cells was associated with elevated percentage and mean fluorescent intensity of HLA-B27.Conclusion The level of Th1 cells is decreased,but Th17 is increased in the peripheral blood of AS patients.Th cells are imbalance in AS,patients.The change of Th17 cells may be an important part of the pathogenesis of AS.

In recent years, researchers have found that patients with nonalcoholic fatty liver disease (NAFLD) often have urolithiasis, and the incidence of urolithiasis increases gradually with the severity of NAFLD. Meanwhile, the detection rate of NAFLD was higher in patients with urolithiasis than in normal controls. In this paper, we reviewed the domestic and international studies on the correlation between urolithiasis and NAFLD and described the related pathogenesis, such as insulin resistance, oxidative stress, abnormal lipid metabolism and impaired glyoxalate detoxification. Meanwhile, this paper proposed preventive measures to reduce the risk of development and recurrence of NAFLD-associated urolithiasis by addressing the common risk factors of both diseases, including metabolism-related diseases, lifestyle and diet.

Objective To explore clinical characteristics,diagnosis and treatment method after Peutz-Jeghers Syndrome (PJS) secondary malignant.Methods The clinical date of five cases with malignant tumors associated with Peutz-Jeghers syndrome from June 2014 to January 2017 were analyzed retrospectively in Beijing Friendship Hospital,Capital Medical University.The patients were followed up by phone,outpatient service,and hospitalization.The starting point of the follow-up was the visit date.The patient's death was the end point.The clinical and pathological features,therapy,and postoperative survival were observed.The follow-up deadline was May 2018.Results PJS secondary malignant patients lack clinical specificity.Two cases of five patients accepted endoscopic resection,three cases accepted surgery,and were treated with chemotherapy postoperatively,including 1 case died from tumor progression of 6 months after operation.Tumor recurrence was not found in the rest 4 cases till May 2018.Conclusions Part of the malignant polyp,endoscopic resection is feasible.When endoscopic resection is not feasible,operation treatment is needed;and postoperative adjuvant chemotherapy is needed to improve the long-term prognosis.

Objective:To classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer.Methods:The transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas(TCGA)database.Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells.The classification of breast cancer patients was achieved by unsupervised clustering,and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed.The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis(WGCNA),and the key genes in the modules were identified.A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified.Results:B cells,mast cells,neutrophils,T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer.The patients were clustered into two groups(Cluster 1′ and Custer 2)based on immune cell infiltration scores.Compared with patients with Cluster 1′,patients with Cluster 2 were more likely to benefit from immunotherapy(P<0.05),and patients with Cluster 2 were more sensitive to Enbeaten,Docetaxel,Cyclopamine,and Akadixin(P<0.05).35 genes related to key immune cells were screened out by WGCNA and 4 genes(GPR171,HOXB3,HOXB5 and HOXB6)related to the prognosis of bladder cancer were further screened by LASSO Cox regression.The areas under the ROC curve(AUC)of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-,3-and 5-year survival of patients were 0.735,0.765 and 0.799,respectively.The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-,3-,and 5-year overall survival of bladder cancer patients.Conclusions:According to the immune cell infiltration score,bladder cancer patients can be classified.Furthermore,bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.

Objective:To investigate the risk factors for hemorrhagic transformation (HT) after intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS), and the predictive value of Neutrophil to lymphocyte ratio (NLR).Methods:Consecutive patients with AIS received IVT in Zhengzhou People’s Hospital from January 2021 to December 2022 were retrospectively enrolled. HT was defined as no intracranial hemorrhage was found on the first imaging examination after admission, and new intracranial hemorrhage was found on the imaging examination 24 h after IVT or when symptoms worsened. sHT was defined as HT and the National Institutes of Health Stroke Scale (NIHSS) score increased by ≥4 compared to admission or required surgical treatment such as intubation and decompressive craniectomy. The baseline clinical and laboratory data of the patients were collected, and NLR, lymphocyte to monocyte ratio (LMR), and platelet to neutrophil ratio (PNR) were calculated. Multivariate logistic regression analysis was used to identify the independent predictors of HT and sHT, and receiver operating characteristic (ROC) curve was used to analyze the predictive value of NLR for HT and sHT after IVT. Results:A total of 196 patients were included (age 65.37±13.10 years, 124 males [63.3%]). The median baseline NIHSS score was 4 (interquartile range: 2-10). Twenty patients (10.2%) developed HT, and 12 (6.1%) developed sHT. Univariate analysis showed that there were statistically significant differences in age, baseline NIHSS score, creatinine, NLR, and stroke etiology type between the HT group and the non-HT group (all P<0.05); there were statistically significant differences in age, NLR, PNR, creatinine, baseline NIHSS score, and stroke etiological type between the sHT group and the non-sHT group (all P<0.05). Multivariate logistic regression analysis showed that NLR was an independent predictor of HT (odds ratio [ OR] 1.375, 95% confidence interval [ CI] 1.132-1.670; P=0.001) and sHT ( OR 1.647, 95% CI 1.177-2.304; P=0.004) after IVT. The ROC curve analysis showed that the area under the curve for predicting HT by NLR was 0.683 (95% CI 0.533-0.833; P=0.007), the optimal cutoff value was 5.78, the sensitivity and specificity were 55.0% and 84.1%, respectively. The area under the curve for predicting sHT by NLR was 0.784 (95% CI 0.720-0.839; P=0.001), the optimal cutoff value was 5.94, the sensitivity and specificity were 66.67% and 84.24%, respectively. Conclusions:A higher baseline NLR is associated with an increased risk of HT and sHT after IVT in patients with AIS, and can serve as a biomarker for predicting HT and sHT after IVT.

Objective:To classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer.Methods:The transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas(TCGA)database.Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells.The classification of breast cancer patients was achieved by unsupervised clustering,and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed.The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis(WGCNA),and the key genes in the modules were identified.A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified.Results:B cells,mast cells,neutrophils,T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer.The patients were clustered into two groups(Cluster 1′ and Custer 2)based on immune cell infiltration scores.Compared with patients with Cluster 1′,patients with Cluster 2 were more likely to benefit from immunotherapy(P<0.05),and patients with Cluster 2 were more sensitive to Enbeaten,Docetaxel,Cyclopamine,and Akadixin(P<0.05).35 genes related to key immune cells were screened out by WGCNA and 4 genes(GPR171,HOXB3,HOXB5 and HOXB6)related to the prognosis of bladder cancer were further screened by LASSO Cox regression.The areas under the ROC curve(AUC)of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-,3-and 5-year survival of patients were 0.735,0.765 and 0.799,respectively.The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-,3-,and 5-year overall survival of bladder cancer patients.Conclusions:According to the immune cell infiltration score,bladder cancer patients can be classified.Furthermore,bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.

Objective:To classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer.Methods:The transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas(TCGA)database.Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells.The classification of breast cancer patients was achieved by unsupervised clustering,and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed.The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis(WGCNA),and the key genes in the modules were identified.A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified.Results:B cells,mast cells,neutrophils,T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer.The patients were clustered into two groups(Cluster 1′ and Custer 2)based on immune cell infiltration scores.Compared with patients with Cluster 1′,patients with Cluster 2 were more likely to benefit from immunotherapy(P<0.05),and patients with Cluster 2 were more sensitive to Enbeaten,Docetaxel,Cyclopamine,and Akadixin(P<0.05).35 genes related to key immune cells were screened out by WGCNA and 4 genes(GPR171,HOXB3,HOXB5 and HOXB6)related to the prognosis of bladder cancer were further screened by LASSO Cox regression.The areas under the ROC curve(AUC)of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-,3-and 5-year survival of patients were 0.735,0.765 and 0.799,respectively.The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-,3-,and 5-year overall survival of bladder cancer patients.Conclusions:According to the immune cell infiltration score,bladder cancer patients can be classified.Furthermore,bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.

Objective:To classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer.Methods:The transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas(TCGA)database.Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells.The classification of breast cancer patients was achieved by unsupervised clustering,and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed.The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis(WGCNA),and the key genes in the modules were identified.A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified.Results:B cells,mast cells,neutrophils,T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer.The patients were clustered into two groups(Cluster 1′ and Custer 2)based on immune cell infiltration scores.Compared with patients with Cluster 1′,patients with Cluster 2 were more likely to benefit from immunotherapy(P<0.05),and patients with Cluster 2 were more sensitive to Enbeaten,Docetaxel,Cyclopamine,and Akadixin(P<0.05).35 genes related to key immune cells were screened out by WGCNA and 4 genes(GPR171,HOXB3,HOXB5 and HOXB6)related to the prognosis of bladder cancer were further screened by LASSO Cox regression.The areas under the ROC curve(AUC)of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-,3-and 5-year survival of patients were 0.735,0.765 and 0.799,respectively.The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-,3-,and 5-year overall survival of bladder cancer patients.Conclusions:According to the immune cell infiltration score,bladder cancer patients can be classified.Furthermore,bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.