The expression of microRNA-199 - a new potential biomarker for immunomediated inflammation
Bibliographic record
Abstract
The etiology and pathogenesis of inflammatory bowel disease (IBD) remain undetermined but an interaction between environmental, genetic and immunological factors is most widely accepted. Recent studies examine the expression of miRNAs in peripheral blood and tissues in IBD patients. Our study aims to assess and correlate the serum expression of miR-199 in IBD patients with clinical parameters such as extent, activity, and severity of the disease. A total of 35 patients with ulcerative colitis (UC) and 35 patients with Crohn’s disease (CD) were included in the study. Serum miR-199 expression in both IBD diseases was assessed using reverse transcriptase quantitative real-time PCR (RT-qPCR). Circulating miR-199 levels were also correlated with disease extent, activity, and severity indices (CDAI, Montreal classification, Partial Mayo score). Serum expression of miR-199 in the 70 patients was also compared miR-199 serum levels in 30 healthy control subjects. The patients’ group showed mean serum miR-199 expression of 2.39 for CD, 1.08 for UC, and 1.26 for the control group with significant difference in the expression between groups. From the current study, we could conclude that there is a significant correlation between increased serum expression of miR-199 and disease activity (UC), extent (CD), and severity (CD and UC).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".