The effect of inflammation severity and of treatment on the production and release of TNFα by colonic explants in inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND: Despite its pivotal role in mucosal inflammation, data on TNFalpha levels in inflammatory bowel diseases have been contradictory. AIM: To examine TNFalpha production in relation to the type and severity of inflammation and therapy, using colonic explant cultures. MATERIALS AND METHODS: Rectal mucosal biopsies from 271 paediatric patients (178 inflammatory bowel disease, 27 inflammatory controls, 66 normal) were cultured for 4 or 18 h. Basal TNFalpha tissue content and release into the medium were measured by ELISA and compared to histological severity and clinical parameters. RESULTS: TNFalpha release as well as tissue-associated TNFalpha levels were significantly increased in rectal biopsies from involved inflammatory bowel disease tissue. The amount of TNFalpha correlated with inflammation severity scores. TNFalpha levels were higher at 18 compared to 4 h in all groups, whether inflamed or not. TNFalpha released from rectal biopsies was lower among treated patients at 18 h. The presence of proximal colonic involvement was associated with higher TNFalpha release by uninvolved Crohn's disease rectal biopsies compared to patients with ileitis alone. CONCLUSIONS: TNFalpha production and release is increased in involved rectal explants from inflammatory bowel disease. Anti-inflammatory treatment diminishes this response.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".