Smad4 deficiency in T cells leads to the Th17-associated development of premalignant gastroduodenal lesions in mice
Bibliographic record
Abstract
While there is evidence that specific T cell populations can promote the growth of established tumors, instances where T cell activity causes neoplasms to arise de novo are infrequent. Here, we employed two conditional mutagenesis systems to delete the TGF-β signaling pathway component Smad4 in T cells and observed the spontaneous development of massive polyps within the gastroduodenal regions of mice. The epithelial lesions contained increased levels of transcripts encoding IL-11, IL-6, TGF-β, IL-1β, and TNF-α, and lamina propria cells isolated from lesions contained abundant IL-17A+CD4+ T cells. Furthermore, we found that Smad4 deficiency attenuated TGF-β-mediated in vitro polarization of FoxP3+CD4+ T cells, but not IL-17A+CD4+ T cells, suggesting that the epithelial lesions may have arisen as a consequence of unchecked Th17 cell activity. Proinflammatory cytokine production likely accounted for the raised levels of IL-11, a cytokine known to promote gastric epithelial cell survival and hyperplasia. Consistent with IL-11 having a pathogenic role in this model, we found evidence of Stat3 activation in the gastric polyps. Thus, our data indicate that a chronic increase in gut Th17 cell activity can be associated with the development of premalignant lesions of the gastroduodenal region.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".