Intestinal epithelial cells express galectin-9 in patients with food allergy that plays a critical role in sustaining allergic status in mouse intestine
Bibliographic record
Abstract
To cite this article: Chen X, Song C-H, Liu Z-Q, Feng B-S, Zheng P-Y, Li P, In SH, Tang S-G, Yang P-C. Intestinal epithelial cells express galectin-9 in patients with food allergy that plays a critical role in sustaining allergic status in mouse intestine. Allergy 2011; 66: 1038–1046. Background and aims: Mechanisms in sustaining the allergic hypersensitivity status in the body are unclear. Galectin-9 (Gal-9) has strong immune regulatory capacity. The present study aims to elucidate the role of Gal-9 in sustaining allergic status in the intestine. Methods: Duodenal biopsies were obtained from 20 patients with peptic ulcer and food allergy (FA). The expression of Gal-9 in intestinal tissue was examined at both protein level and mRNA level. Two coculture systems with intestinal epithelial cells (IEC) and mast cells, or dendritic cells (DC) and T cells were established to investigate the source of Gal-9 in the intestine and the mechanism by which Gal-9 modulated DC’s phenotyping and sustained the T helper 2 polarization. Results: Normal IEC showed mild expression of Gal-9 that was markedly enhanced in patients with FA. Mast cells had the capability to induce IEC to produce Gal-9 via releasing tryptase that activated the proteinase-activated receptor 2 on IEC. Gal-9 activated DC to produce TIM4 (T-cell immunoglobulin mucin domain) via ligating TIM3 on DC via activating the cyclic guanosine monophosphate (cGMP) pathway. In a mouse FA model, blocking Gal-9 inhibited the allergic hypersensitivity status and the antigen-specific Th2 response in the intestine. Conclusions: IEC-derived Gal-9 contributes to sustaining the allergic status in the intestine.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".