A9 LOSS OF INTESTINAL EPITHELIAL NCOR1 INCREASES OXIDATIVE METABOLISM
Bibliographic record
Abstract
Abstract Background The nuclear co-repressor NCOR1 acts as a central platform of a complex that represses gene expression associated with inflammatory response. Literature also recently uncovered its possible role in oxidative metabolism in some tissues and organs. Although intestinal epithelial NCOR1 is crucial to restrict IBD symptoms during experimental colitis, its precise role in controlling intestinal epithelial cell biology has not been established. Aims We aimed to investigate the role of intestinal epithelial NCOR1 in oxidative metabolism. Methods Crossing Villin-Cre and Ncor1loxP/loxP mice was performed to delete Ncor1 in the whole intestinal epithelium conditionally. Crypts from control and NCOR1ΔIEC littermates were isolated to generate colonoids 3D cultures. Phenotypic, genotypic, and transcriptomic analyses were performed on those colonoids. Results Colonoids from NCOR1ΔIEC mice were phenotypically smaller but were found to display drastic higher intestinal stem cell propagation features during organoid clonogenic assays. A Gene Set Enrichment Analysis from RNA sequencing predicted an increase in oxidative metabolism in NCOR1ΔIEC colonoids. Several genes associated with oxidative metabolism were confirmed to be modulated in both NCOR1ΔIEC colonoids and the colon of NCOR1ΔIEC mice. Mitochondrial mass was also significantly increased in colonoids when NCOR1 was absent. Loss of the co-repressor did not affect the expression of PGC1-α, a known antagonist of NCOR1. However, transcripts of cytochrome c somatic (Cycs), a target gene of PGC1-α, were found higher in NCOR1ΔIEC colonoids, suggesting that the coactivator activity is increased in the absence of NCOR1. Conclusions Our results highlight a new role for NCOR1 in the oxidative metabolism of intestinal epithelial cells. Its action via PGC1-α activity could potentially be targeted as a therapeutic measure during inflammatory bowel diseases. Funding Agencies CIHR
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 | 0.000 | 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) | 0.005 | 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".