The TGF-β/Smad Repressor TG-Interacting Factor 1 (TGIF1) Plays a Role in Radiation-Induced Intestinal Injury Independently of a Smad Signaling Pathway
Bibliographic record
Abstract
Despite advances in radiation delivery protocols, exposure of normal tissues during the course of radiation therapy remains a limiting factor of cancer treatment. If the canonical TGF-β/Smad pathway has been extensively studied and implicated in the development of radiation damage in various organs, the precise modalities of its activation following radiation exposure remain elusive. In the present study, we hypothesized that TGF-β1 signaling and target genes expression may depend on radiation-induced modifications in Smad transcriptional co-repressors/inhibitors expressions (TGIF1, SnoN, Ski and Smad7). In endothelial cells (HUVECs) and in a model of experimental radiation enteropathy in mice, radiation exposure increases expression of TGF-β/Smad pathway and of its target gene PAI-1, together with the overexpression of Smad co-repressor TGIF1. In mice, TGIF1 deficiency is not associated with changes in the expression of radiation-induced TGF-β pathway-related transcripts following localized small intestinal irradiation. In HUVECs, TGIF1 overexpression or silencing has no influence either on the radiation-induced Smad activation or the Smad3-dependent PAI-1 overexpression. However, TGIF1 genetic deficiency sensitizes mice to radiation-induced intestinal damage after total body or localized small intestinal radiation exposure, demonstrating that TGIF1 plays a role in radiation-induced intestinal injury. In conclusion, the TGF-β/Smad co-repressor TGIF1 plays a role in radiation-induced normal tissue damage by a Smad-independent mechanism.
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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 | 0.001 |
| 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".