Purpose Preclinical evaluation of PCA3 and AMACR transcript simultaneous detection in urine to diagnose clinical significant prostate cancer (prostate cancer with Gleason score ≥7) in a Russian cohort. Patients and Methods We analyzed urine samples of patients with a total serum PSA ≥2 ng/mL: 31 men with prostate cancer scheduled for radical prostatectomy, 128 men scheduled for first diagnostic biopsy (prebiopsy cohort). PCA3 , AMACR , PSA and GPI transcripts were detected by multiplex reverse transcription quantitative polymerase chain reaction, and the results were used for scores for calculation and statistical analysis. Results There was no significant difference between clinically significant and nonsignificant prostate cancer PCA3 scores. However, there was a significant difference in the AMACR score (patients scheduled for radical prostatectomy p =0.0088, prebiopsy cohort p =0.029). We estimated AUCs, optimal cutoffs, sensitivities and specificities for PCa and csPCa detection in the prebiopsy cohort by tPSA, PCA3 score, PCPT Risk Calculator and classification models based on tPSA, PCA3 score and AMACR score. In the clinically significant prostate cancer ROC analysis, the PCA3 score AUC was 0.632 (95%CI: 0.511–0.752), the AMACR score AUC was 0.711 (95%CI: 0.617–0.806) and AUC of classification model based on the PCA3 score, the AMACR score and total PSA was 0.72 (95%CI: 0.58–0.83). In addition, the correlation of the AMACR score with the ratio of total RNA and RNA of prostate cells in urine was shown (tau=0.347, p =6.542e–09). Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Conclusion The AMACR score is a good predictor of clinically significant prostate cancer. Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Evaluation of the AMACR score and classification models based on it for clinically significant prostate cancer detection with larger samples and a follow-up analysis is promising.
The structural udp gene encoding uridine phosphorylase (UPh) was cloned from the Salmonella typhimurium chromosome and overexpressed in Escherichia coli cells. S. typhimurium UPh (StUPh) was purified to apparent homogeneity and crystallized. The primary structure of StUPh has high homology to the UPh from E. coli, but the enzymes differ substantially in substrate specificity and sensitivity to the polarity of the medium. Single crystals of StUPh were grown using hanging-drop vapor diffusion with PEG 8000 as the precipitant. X-ray diffraction data were collected to 2.9 A resolution. Preliminary analysis of the diffraction data indicated that the crystal belonged to space group P6(1(5)), with unit-cell parameters a = 92.3, c = 267.5 A. The solvent content is 37.7% assuming the presence of one StUPh hexamer per asymmetric unit.
Analysis of genomic variability of pathogens associated with heightened public health concerns is an opportunity to track transmission routes of the disease and helps to develop more effective vaccines and specific diagnostic tests. We present the findings of a detailed genomic analysis of the genomic variability of the SARS-CoV-2 Omicron variant that spread in Russia between 8 December 2021 and 30 January 2022. We performed phylogenetic analysis of Omicron viral isolates collected in Moscow (n = 589) and downloaded from GISAID (n = 397), and identified that the BA.1 lineage was predominant in Russia during this period. The BA.2 lineage was also identified early in December 2021. We identified three cases of BA.1/BA.2 coinfections and one case of Delta/Omicron coinfection. A comparative genomic analysis of SARS-CoV-2 viral variants that spread in other countries allowed us to identify possible cases of transmission. We also found that some mutations that are quite rare in the Global Omicron dataset have a higher incidence rate, and identified genetic markers that could be associated with ways of Omicron transmission in Russia. We give the genomic variability of single nucleotide variations across the genome and give a characteristic of haplotype variability of Omicron strains in both Russia and around the world, and we also identify them.
Introduction. Urinary tract infections are the most common infections in obstetrics and gynecology. Bacteriological method to investigate urine is laborious and time-consuming, therefore development of accurate and rapid methods for the detection of significant bacteriuria is important. Objective. Evaluation of quantitative real-time PCR based approach for the detection of significant bacteriuria in pregnant women. Material and methods. A retrospective investigation of mid-stream urine samples obtained from pregnant women was performed. Urine culture was performed using quantitative method, and a case was considered as significant bacteriuria if ≥ 105 CFU/ml were detected. Urine samples were analyzed for main uropathogens / groups of uropathogens using quantitative multiplex real-time PCR. Diagnostic characteristics of PCR were computed relative to the results of urine culture. Results. In total, 896 urine samples were tested. Of them, significant bacteriuria was found in 28 cases (3%). The frequency of detection of Escherichia coli was 50%, Enterococcus spp. — 25%, Klebsiella spp. — 7%, Proteus spp. and S. saprophyticus 4% each, Streptococcus spp. — 14%. Sensitivity and specificity of the detection of significant bacteriuria using quantitative real-time PCR for the majority of bacterial species / groups were 99% to 100%. Sensitivity and specificity of the quantitative real-time PCR based method were 96% and 98%, respectively. Conclusions. Prevalence of significant bacteriuria among pregnant women is 3%. Half of the uropathogens isolated from pregnant women with bacteriuria are E. coli. Sensitivity and specificity of quantitative PCR for the detection of significant bacteriuria are 96% and 98%, respectively.
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