Characterization of ileal dendritic cell distribution in a rat model of acute and chronic inflammation
Bibliographic record
Abstract
We examined ileal dendritic cell (DC) subpopulations in a rat model of indomethacin-induced enteritis to determine changes in phenotype and distribution associated with increased mucosal permeability during acute and chronic stages of inflammation. Sprague-Dawley rats were treated with indomethacin (7.5 mg/kg subcutaneously, 2 injections 48 h apart). Animals were killed at day 4 (acute stage) or at day 15 or 30 (chronic stages); control rats were injected with saline. DC distribution was evaluated by immunohistochemistry for CD103, CD11b, CD83, and CD163; inflammation was assessed by light microscopy; and permeability was determined by flux of horseradish peroxidase in Ussing chambers. In controls, both immature DC subpopulations, CD103+CD11b+CD163-CD83- and CD103+CD11b-CD163-CD83-, were observed in the lamina propria, and the CD11b- population also was present in Peyer's patches. In acute inflammation, permeability was increased (P<0.01), and inflamed areas with or without ulcers were observed. CD103+ and CD11b+ (CD83-) DCs were absent from inflamed areas, reduced in noninflamed tissues, but present in Peyer's patches. In the chronic stage at day 15, CD103+ and CD11b+ cells were located in inflamed and noninflamed areas and in Peyer's patches. In addition, CD83+ DCs were detected in inflamed areas. At day 30, when we observed a complete microscopic resolution of inflammation, numbers of CD103+ and CD11b+ DCs were increased, and there were CD83+ DCs beneath the epithelial cell layer. We conclude that antigen uptake in acute inflammation may activate resident immature DCs, inducing their migration to lymphoid tissue where they mature and then return to the intestine to play a role in the local inflammatory response.
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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) | 0.001 | 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) | 0.001 | 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".