The Role of Thymine DNA Glycosylase in Transcription, Active DNA Demethylation, and Cancer
Bibliographic record
Abstract
DNA methylation is an essential covalent modification that is required for growth and development. Once considered to be a relatively stable epigenetic mark, many studies have established that DNA methylation is dynamic. The 5-methylcytosine (5-mC) mark can be removed through active DNA demethylation in which 5-mC is converted to an unmodified cytosine through an oxidative pathway coupled to base excision repair (BER). The BER enzyme Thymine DNA Glycosylase (TDG) plays a key role in active DNA demethylation by excising intermediates of 5-mC generated by this process. TDG acts as a key player in transcriptional regulation through its interactions with various nuclear receptors and transcription factors, in addition to its involvement in classical BER and active DNA demethylation, which serve to protect the stability of the genome and epigenome, respectively. Recent animal studies have identified a connection between the loss of Tdg and the onset of tumorigenesis. In this review, we summarize the recent findings on TDG’s function as a transcriptional regulator as well as the physiological relevance of TDG and active DNA demethylation in cancer.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".