Insulation of tumor suppressor genes by the nuclear factor CTCF
Bibliographic record
Abstract
One of the most outstanding nuclear factors, which has chromatin insulator and transcriptional properties and also contribute to genomic organization, is the zinc-finger protein CCCTC-binding factor (CTCF). Among its multiple functions, a growing amount of evidence implicates CTCF in the epigenetic regulation of genes responsible for the control of the cell cycle, and its mis-regulation can lead to aberrant epigenetic silencing of genes involved in cancer development. Detailed studies are now revealing that CTCF can serve as a barrier against the spread of DNA methylation and histone repressive marks over promoter regions of tumor suppressor genes. Moreover, new evidences points out to the capacity of CTCF to be covalently modified, in particular, through poly(ADP-ribosyl)ation with regulatory consequences. An unexplored aspect of CTCF is its intergenic and intragenic distribution in certain loci. Such distribution seems to facilitate the formation of an optimal chromatin structure and the recruitment of chromatin remodelers with the possible incorporation of RNA polymerase II. Therefore, in the context of tumor suppressor genes and cancer development, CTCF appears to play a relevant role by incorporating a combination of mechanisms involved in the protection against epigenetic silencing components and the maintenance of optimal higher-order organization of the corresponding loci.
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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 | 0.000 |
| 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".