Role of Serum Interleukin-6, Interleukin-1β and Interleukin-10 in Assessment of Disease Activity and Nutritional Status in Patients with Inflammatory Bowel Disease
Bibliographic record
Abstract
Inflammatory bowel diseases (IBD) are characterised by multifactorial and chronic inflammation. Much attention has been paid to immune dysfunction in inflammatory bowel diseases. The aim of this study was to assess the usefulness of serum IL-6, IL-1β and IL-10 in determining the activity and nutritional status in IBD patients. The case-control study was carried out on 82 patients with IBD; the control group consisted of 25 clinically healthy subjects. The serum concentrations of IL-6, IL-1 β and IL-10 were determined by the quantitative sandwich enzyme-linked immunosorbent assay. There were no significant differences in IL-6 and IL-1β levels in UC and CD patients according to disease activity as assessed by the Montreal classification, Partial Mayo Score and CDAI. Significantly higher IL-6 levels were found in patients with low body fat in comparison to patients with normal body fat. Furthermore, significantly higher mean IL-6 levels were observed in patients with excess body fat in comparison to patients with normal body fat, and also in comparison to patients with deficient body fat. IL-6 and IL-1β may provide extra information regarding the nutritional status of IBD patients. IL-10 can be considered a non-invasive biomarker of IBD activity.
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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 | 0.000 |
| 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".