Aim: To identify intestinal microbiota compositions in elderly functional constipation (FC) patients. Materials & methods: Fecal samples from 61 FC patients and 48 healthy age-matched volunteers we...

Blockage of autophagy pathway enhances Salmonella tumor-targeting Blockage of autophagy pathway enhances Salmonella tumor-targeting

Background: Urinary tract infections (UTIs) are one the most common infections. The rapid and accurate identification of uropathogens, and the determination of antimicrobial susceptibility, are essential aspects of the management of UTIs. However, existing detection methods are associated with certain limitations. In this study, a new urinary tract infection high-throughput multiplex genetic detection system (UTI-HMGS) was developed for the semi-quantitative detection of 18 pathogens and the simultaneously screening of nine resistance genes directly from the clinical urine sample within 4 hours. Methods: We designed and optimized a multiplex polymerase chain reaction (PCR) involving fluorescent dye-labeled specific primers to detect 18 pathogens and nine resistance genes. The specificity of the UTI-HMGS was tested using standard strains or plasmids for each gene target. The sensitivity of the UTI-HMGS assay was tested by the detection of serial tenfold dilutions of plasmids or simulated positive urine samples. We also collected clinical urine samples and used these to perform urine culture and antimicrobial susceptibility testing (AST). Finally, all urine samples were detected by UTI-HMGS and the results were compared with both urine culture and Sanger sequencing. Results: UTI-HMGS showed high levels of sensitivity and specificity for the detection of uropathogens when compared with culture and sequencing. In addition, ten species of bacteria and three species of fungi were detected semi-quantitatively to allow accurate discrimination of significant bacteriuria and candiduria. The sensitivity of the UTI-HMGS for the all the target genes could reach 50 copies per reaction. In total, 531 urine samples were collected and analyzed by UTI-HMGS, which exhibited high levels of sensitivity and specificity for the detection of uropathogens and resistance genes when compared with Sanger sequencing. The results from UTI-HMGS showed that the detection rates of 15 pathogens were significantly higher (P<0.05) than that of the culture method. In addition, there were 41(7.72%, 41/531) urine samples were positive for difficult-to-culture pathogens, which were missed detected by routine culture method. Conclusions: UTI-HMGS proved to be an efficient method for the direct semi-quantitative detection of 18 uropathogens and the simultaneously screening of nine antibiotic resistance genes in urine samples. The UTI-HMGS could represent an alternative method for the clinical detection and monitoring of antibiotic resistance.

Purpose: The prevalence of primary liver cancer (PLC) is rising, yet strategies for its early diagnosis remain inadequate. This study aims to identify novel biomarkers to improve the diagnostic ability of PLC. Patients and Methods: This study included 94 patients with PLC, 128 patients with benign liver disease (BLD), and 79 normal controls (NC) were included. Among the PLC group, there were 39 patients with hepatocellular carcinoma (HCC), 14 patients with intrahepatic cholangiocarcinoma (ICC), 4 patients with combined hepatocellular-cholangiocarcinoma (CHC) and 37 patients with imaging-diagnosed HCC, respectively. Serum biomarkers and other laboratory parameters were collected and analyzed. Diagnostic values of individual and combined biomarkers for PLC were assessed using receiver operating characteristic (ROC) curve analysis. Univariate and multivariate logistic regression identified predictors of PLC, and a nomogram model was developed based on the independent predictors. Results: AFP and DCP levels were significantly higher in the HCC patients compared to those with the BLD. AFP-L3 and CA199 levels were markedly elevated in patients with HCC, ICC, and CHC compared with the other groups. Combining AFP, AFP-L3, DCP, and CA199 increased the AUC to 0.8492 for the PLC group versus the BLD group. Multivariate logistic regression analysis identified sex, AFP-L3, DCP, and CA199 as independent predictors of PLC, and a reliable nomogram model was developed based on these predictors. Conclusion: The combined use of AFP, AFP-L3, DCP, and CA199 significantly enhanced the diagnostic performance of PLC compared with existing models like GALAD (gender, age, AFP, AFP-L3, and DCP), and ASAP (age, sex, AFP, DCP), as well as individual biomarkers.