Interleukin-10 and nerve growth factor have reciprocal upregulatory effects on intestinal epithelial cells
Bibliographic record
Abstract
The intestinal mucosa is in a constant state of controlled inflammation, but the processes whereby this occurs are poorly understood. The aims of this study were to look at the role of IL-10 and nerve growth factor (NGF) in intestinal epithelial cell regulation. The human colon epithelial cell lines T84, HT-29, and CACO-2 were used. RT-PCR, flow cytometry analysis, and immunohistochemistry were applied to measure the cytokine changes in epithelial cells induced by recombinant cholera toxin and its B subunit, IL-10, and NGF. Cholera toxin B subunit caused selective dose-dependent increased mRNA for IL-10 in T84 cells and the protein in T84, HT-29, and CACO-2 cells. IL-10 dose dependently selectively increased NGF mRNA in T84 cells and intracellular protein synthesis in all three epithelial cell lines. The effect of NGF was reciprocal, selective, and dose dependent because it increased mRNA for IL-10 and IL-10 synthesis. Our results suggest that the epithelium may actively participate in downregulation through innate mechanisms involving IL-10 and NGF. The reciprocal interaction suggests for the first time that NGF may be involved in local downregulation by mucosal epithelium and thus may play a potent protective role in response to injury, by prevention of undue inflammation.
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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 | 0.000 | 0.000 |
| 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".