Objective To investigate the value and diagnostic efficiency of the quantitative dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) and intravoxel incoherent motion (IVIM) parameters using three dimention (3D)-histogram analysis for discriminating the Gleason score (GS) of prostate cancer. Methods A total of 53 patients pathologically confirmed as prostate cancer by systemic prostate biopsy who had routine , DCE and DWI-MRI scans were retrospectively analyzed. There were 15 cases for low-risk and 38 cases for intermediate/high-risk prostate cancer. The 3D ROI of all lesions based on T2WI was achieved by image registration to get the quantitative parameters of DCE-MRI and DWI-IVIM. The parameters of DCE-MRI contains: transfer constant (Ktrans), rate constant (Kep) and extracellular-extravascular volume fraction (Ve).The DWI-IVIM related quantitative parameters were ADC, diffusion coefficient (D), diffusion coefficient related to perfusion (D*) and perfusion fraction (f). Then the histogram analysis of these quantitative parameters was performed to get the mean, median, 25th percentile, 75th percentile, Skewness and Kurtosis. Using the Spearman rank correlation analysis to evaluate the correlation of these parameters and GS of prostate cancer. The diagnostic performance of these quantitative histogram parameters related to the GS in identifying low-risk and intermediate/high-risk of prostate cancer was carried by ROC. Results The Kep and Ktrans (mean, median, 25th, 75th) of DCE-MRI were positively correlated with GS (r value was 0.346 to 0.696, P<0.05). The ADC (mean, median, 25th, 75th), D (mean, median, 25th, 75th, Skewness, Kurtosis) and D*(25th) of DWI-IVIM were correlated with GS (r value was-0.544 to 0.428, P<0.05). The DCE-MRI quantitative parameters Kep (25th) had the highest area under curve (AUC, 0.961); The ADC (median) and D (25th) had higher AUC( 0.832, 0.888) in the quantitative parameters of DWI-IVIM, the difference between Kep(25th) and ADC (median) was statistically significant (Z value was 2.212, P value was 0.027). The difference of AUC between Kep (25th) and D (25th), D (25th) and ADC (median) was not statistically significant (Z values were 1.027 and 1.398, P values were 0.162 and 0.304, respectively).Conclusion DCE and IVIM quantitative parameters (Kep, Ktrans, ADC, D) histogram analysis results are correlated with GS, and can be used for distinguishing low-risk from intermediate/high-risk prostate cancer.

Objective: To analyze the infection composition and drug resistance to Gram-negative (G^-) bacilli in children′s respiratory tract in Suzhou, in order to provide evidence for rational use of antibiotics clinically. Methods: G^- bacilli culture samples were collected from 21 561 cases of nasopharyngeal secretions from patients with respiratory tract infection admitted at the Department of Respiratory, Children′s Hospital of Soochow University from January 2007 to December 2016, including 21 246 cases in general wards, and 315 patients who were transferred to the respiratory department after treatment in the Intensive Care Unit(ICU), and the children were divided into the general ward group and the ICU group, and the pathogens were compared and the changes in bacterial susceptibility were dynamically observed between the 2 groups. Results: The primary G^-bacteria for respiratory infection was Haemophilus influenzae, followed by Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii.The detection rates of Klebsiella pneumoniae and Pseudomonas aeruginosa in the ICU group were 16.8% (21/125 strains)and 14.4%(18/125 strains), respectively, which were significantly higher than those in the general ward group [10.0%(208/2 071 strains), 9.2%(190/2 071 strains)]. The detection rates of G^-bacteria in the ICU group were 33.7%(106/315 cases), which were significantly higher than those in the general ward group [9.4%(1 997/21 246 cases)], and the difference was statistically significant(χ²=210.325, P<0.001). The rare G^-bacillus such as Stenotrophomonas maltophilia, Acinetobacter junii and Burkholderia onion were higher in the ICU group [17.6%(22/125 strains)] than that in the general ward group [6.4% (132/2 071 strains)]. The rate that of G^-bacteria with two or more mixed infection in ICU group [17.0% (18/106 cases)] was significantly higher than in the general ward group [3.4%(68/1 997 cases)], and the difference was statistically significant(χ²=47.3, P<0.05). For the mixed infection, the ICU group was mainly composed of Klebsiella pneumoniae mixed with Pseudomonas aeruginosa or Escherichia coli, while the general ward group was composed of Haemophilus influenzae mixed with Pseudomonas aeruginosa or Escherichia coli.The sensitivity of Haemophilus influenzae to Ampicillin, Sultamicillin, Cefuroxime, Cefaclor and Azithromycin decreased, and the sensitivity to Chloramphenicol, Tetracycline and Trimethoprim+ Sulfamethoxazole increased year by year, and there were statistically significant differences in different years (all P<0.05). The sensiti-vity to Escherichia coli to Ceftazidime decreased year by year, and the sensitivity to Ampicillin and Levofloxacin increased year by year, and there were statistically significant differences in different years (all P<0.05). The sensitivity to Klebsiella pneumoniae to Cefoperazone/Sulbactam and imipenem decreased, and the sensitivity to Ciprofloxacin and Levofloxacin increased, and there were statistically significant differences in different years (all P<0.05). The sensitivity to Pseudomonas aeruginosa, Cefoperazone/Sulbactam and Ceftriaxone decreased year by year, and the sensitivity to Levofloxacin increased, and there were statistically significant differences in different years (all P<0.05). The detection rate of carbapenem-resistant strains of Klebsiella pneumoniae and Pseudomonas aeruginosa showed an increasing trend, and there were statistically significant differences in different years (all P<0.05). Conclusions The primary G^-bacteria for respiratory infections is Haemophilus influenzae, G^-bacilli especially, the mixed infection of G^-bacilli, is more likely to cause severe and critical respiratory infections.The resistance rate of G^-bacteria infection in children′s respiratory tract to commonly used antibiotics is generally on the rise.

Objective To assess the use of human albumin (ALB) after hepatectomy in hepatocellular carcinoma patients in our hospital .Methods 150 hospital medical records from June 2012 to June 2013 were analyzed ,which used the human ser-um albumin during the perioperative period of hepatectomy at hepatocellular carcinoma (preoperative Child-Pugh A or B) retro-spectively ,the rationality of human blood albumin use was evaluated .Results Among the 150 medical records ,the total appli-cation amount of albumin was 11 212 .5 g (897 bottles) ,the total cost was 527 ,744 yuan ,nearly 20 percent of total drug costs ,accounting for nearly 10% of the total cost of hospitalization .By using human serum albumin after surgery ,the patients'liver function was significantly improved (P<0 .05) ,there was a positive correlation between the Child-Pugh score and dosage of human albumin (P<0 .05) .Conclusion The use of human serum albumin was rational during the perioperative period of hepatectomy in hepatocellular carcinoma patients in our hospital ,which had achieved the desired therapeutic effect .

ObjectiveTo investigate the expression of Midkine （MDK） in cholangiocarcinoma （CCA） and its value in predicting the prognosis of CCA， as well as the potential mechanism of the effect of MDK on the progression of CCA. MethodsThe data of CCA samples were obtained from TCGA database to analyze the difference in the expression of MDK between cancer tissue and paracancerous tissue and its association with clinical features， and the data collected from GEO database and 11 CCA patients who underwent surgical resection in The Fifth Medical Center of Chinese PLA General Hospital from June 2018 to September 2021 were used for validation. STRING and Cytoscape were used to construct a protein-protein interaction network， and gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analyses were used to investigate the biological functions and tumor-related pathways involving MDK-related genes. In addition， TIMER and TISIDB databases were used to analyze the correlation between MDK expression and immune cell infiltration in CCA tissue. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the Fisher’s exact test was used for comparison of categorical data between two groups. The Kaplan-Meier method was used to plot survival curves， and the Log-rank test was used for comparison between groups. The Spearman correlation analysis was used to investigate the correlation between two variables. ResultsThe expression level of MDK in cancer tissue and paracancerous tissue of CCA patients was compared based on TCGA database， and the results of the non-paired and paired analyses showed that the expression level of MDK in CCA tumor tissue was significantly higher than that in paracancerous tissue （P<0.001）. Transcriptome sequencing was performed for the tumor tissue and its corresponding paracancerous tissue from 11 CCA patients， and the results showed that the expression level of MDK in CCA tumor tissue was significantly higher than that in corresponding paracancerous tissue （P<0.01）. High expression of MDK was associated with lymph node metastasis （P=0.045） and vascular invasion （P=0.044）. Survival analysis showed that compared with the CCA patients with low MDK expression， the CCA patients with high MDK expression had significantly shorter overall survival time （χ²=5.30， P=0.028） and disease-specific survival time （χ²=6.25， P=0.019）. The GO and KEGG enrichment analyses showed that the 30 MDK-related genes were closely associated with ubiquitin-mediated proteolysis and affected the prognosis of CCA patients. The TIMER analysis showed that the expression level of MDK was positively correlated with the infiltration of B cells （r=0.356， P=0.035 6） and dendritic cells （r=0.409， P=0.014 7） in tumor microenvironment of CCA； the TISIDB analysis showed that the expression level of MDK was positively correlated with CXCL16 （r=0.465， P=0.004 67） and was negatively correlated with CXCL12 （r=-0.389， P=0.019 7） and CXCR5 （r=-0.393， P=0.018 5）， and it was also negatively correlated with the immune checkpoint regulators VTCN1 （r=-0.393， P=0.018 3）， LTA （r=-0.380， P=0.022 7）， and PVR （r=-0.350， P=0.037 3）. ConclusionHigh expression of MDK is associated with poor prognosis in CCA patients， and MDK has the potential of being used as a molecular marker for predicting the prognosis of CCA. MDK may promote the development and progression of CCA by regulating ubiquitin-mediated proteolysis and the infiltration of B cells and dendritic cells.