Can Zonulin level be a new diagnosis and follow-up criterion in active ulcerative colitis?
Bibliographic record
Abstract
Objective: In this study, we compared the serum zonulin levels in patients diagnosed for the first time with active ulcerative colitis with those in healthy cases and attempted to determine whether serum zonulin levels were different in the active ulcerative colitis. Material and Methods: A total of 53 naive patients admitted to our hospital between 2019 and 2020 and diagnosed with active ulcerative colitis by colonoscopy were included as a group of cases and 37 patients with no acute or chronic diseases whose colonoscopy was normal as the control group. Results: The study was conducted on 90 cases, 65.5% male and 34.5% female. The patients with ulcerative colitis were compared with the control group in terms of serum zonulin levels. Average serum zonulin levels of the patients with ulcerative colitis (16.73 ± 5.49 ng/ml) were not significantly different than those in the control group 17.48 ± 8.31 ng/ml). Serum zonulin levels of the patients were also compared according to location and severity of disease and did not differ statistically significantly between the groups in terms of the Montreal Classification. When serum zonulin levels were grouped according to the Truelove and Witts criteria, there was no statistically significant difference between the patient groups themselves and the control group. Conclusion: Serum zonulin levels were not greater in the patients with naive active ulcerative colitis compared to the healthy controls. Several previous studies have shown that serum zonulin levels are elevated in patients with ulcerative colitis, but more studies are needed on this subject.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".