MP77-03 THE MICROBIOME OF HUNNER LESIONS IN INTERSTITIAL CYSTITIS/BLADDER PAIN SYNDROME (IC/BPS)
Bibliographic record
Abstract
You have accessJournal of UrologyInfections/Inflammation/Cystic Disease of the Genitourinary Tract: Kidney & Bladder II (MP77)1 Apr 2020MP77-03 THE MICROBIOME OF HUNNER LESIONS IN INTERSTITIAL CYSTITIS/BLADDER PAIN SYNDROME (IC/BPS) J. Curtis Nickel*, Garth Erhlich, R. Christopher Doiron, Kerri-Lynn Kelly, and Joshua Earl J. Curtis Nickel*J. Curtis Nickel* More articles by this author , Garth ErhlichGarth Erhlich More articles by this author , R. Christopher DoironR. Christopher Doiron More articles by this author , Kerri-Lynn KellyKerri-Lynn Kelly More articles by this author , and Joshua EarlJoshua Earl More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000963.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Hunner Lesions (HL) are distinct focal inflammatory areas in the bladder mucosa observed in a minority of patients diagnosed with IC/BPS. This is the first comprehensive evaluation of the microbiome of HL patients using a case-control design in an IC/BPS patient population. METHODS: The bacterial microbiota of mid-stream urine specimens from HL IC/BPS and age/gender matched IC/BPS subjects with no Hunner Lesions (NHL) were examined using state of the art next generation full-length 16S gene sequencing. The differential abundances and diversity of species were characterized and compared (R package DESeq2 v1.24.0) for HL and NHL as well as gender-specific HL and NHL subjects. RESULTS: IC/BPS subjects (total 59; 29 HL and 30 NHL; 43 female and 16 male) were analyzed as species grouped by HL/NHL and female/male designations. There were 10 (p < 0.05) significant species that differentiated HL from NHL urine specimens (though not significant after multiple testing correction). These included Streptococcus, Propionibacterium, Campylobacter, Atopobium, Anaerococcus, Actinomyces, Prevotella, Actinotignum, Gardnerella, and Peptoniphilus species. However, the difference between male and female subjects accounted for the majority of the variance observed in the total IC/BPS population. Similar findings were observed in respect to abundance analyses. In the female data set, there are 7 species abundances that significantly differ (p<0.05) between HL and NHL though only a single Lactobacillus species (L. crispatus) differed significantly after multiple testing correction. In the male subset, there were 11 species that were significantly different and the top 4 species were still significant after correction. The differences observed between HL and NHL species abundance appears to be driven, in part, by the male HL subjects. Diversity metrics (Shannon Diversity and Effective Number; see Figure) shows that both female HL and NHL are dominated by 5 different species and male HL by 10, while male NHL are less diverse at 6. CONCLUSIONS: There is a differential abundance of species in HL vs NHL, with the difference more pronounced in the male subset and much less clear between the female IC/BPS groups. Species differences between HL and NHL subjects are overshadowed by the strong differential clustering of species based on gender. Source of Funding: Canadian Research Chair Program © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e1163-e1164 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information J. Curtis Nickel* More articles by this author Garth Erhlich More articles by this author R. Christopher Doiron More articles by this author Kerri-Lynn Kelly More articles by this author Joshua Earl More articles by this author Expand All Advertisement PDF downloadLoading ...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.138 | 0.024 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".