Automated Author ProfileM., Boldyreva
M., Boldyreva
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Objectives: This study aims to compare the urinary microbiota of healthy women, women with a predisposition to UTIs and patients with chronic recurrent cystitis using real-time PCR as well as identify diagnostic markers for urinary diseases. Patients and methods: The study enrolled three groups of patients: healthy control group, patients with chronic recurrent cystitis and patients with a risk of developing UTIs. Urine samples were analyzed by multiplex real-time PCR reagent kits Femoflor®16 and BacScreen OM. Results: Chronic recurrent cystitis is associated with an increase in total bacterial mass (TBM), genomic DNA and relative predominance of facultative anaerobic microorganisms. The most prevalent bacterial species found in chronic cystitis was E. coli in conjunction with other Enterobacteriaceae, most commonly, Serratia marcescens. An increased amount of genomic DNA and both facultative and obligate anaerobic microorganisms was observed in patients with a risk of developing UTIs. A relative decrease in Lactobacillus spp. was noted in both groups, with the chronic cystitis group showing a more pronounced reduction. Conclusion: In summary, the levels of genomic DNA, TBM and relative values of Lactobacillus spp. can be used as molecular diagnostics markers for chronic cystitis and a variety of other conditions, including micronephrolithiasis and bacterial vaginosis.
Authors
- karger, figshare admin ;
- M., Boldyreva ;
- M., Petrunicheva ;
- A., Ivanova ;
- A., Morozov ;
- S., Koroleva ;
- Z., Moskvina ;
- S., Rossolovskaya ;
- L., Spivak
Objectives: This study aims to compare the urinary microbiota of healthy women, women with a predisposition to UTIs and patients with chronic recurrent cystitis using real-time PCR as well as identify diagnostic markers for urinary diseases. Patients and methods: The study enrolled three groups of patients: healthy control group, patients with chronic recurrent cystitis and patients with a risk of developing UTIs. Urine samples were analyzed by multiplex real-time PCR reagent kits Femoflor®16 and BacScreen OM. Results: Chronic recurrent cystitis is associated with an increase in total bacterial mass (TBM), genomic DNA and relative predominance of facultative anaerobic microorganisms. The most prevalent bacterial species found in chronic cystitis was E. coli in conjunction with other Enterobacteriaceae, most commonly, Serratia marcescens. An increased amount of genomic DNA and both facultative and obligate anaerobic microorganisms was observed in patients with a risk of developing UTIs. A relative decrease in Lactobacillus spp. was noted in both groups, with the chronic cystitis group showing a more pronounced reduction. Conclusion: In summary, the levels of genomic DNA, TBM and relative values of Lactobacillus spp. can be used as molecular diagnostics markers for chronic cystitis and a variety of other conditions, including micronephrolithiasis and bacterial vaginosis.
Authors
- karger, figshare admin ;
- M., Boldyreva ;
- M., Petrunicheva ;
- A., Ivanova ;
- A., Morozov ;
- S., Koroleva ;
- Z., Moskvina ;
- S., Rossolovskaya ;
- L., Spivak