The relationship between UHRF1 and DNMT1 and the process of DNA methylation
Bibliographic record
Abstract
The maintenance of normal epigenetic growth and development is crucial for various biological processes, with DNA methylation playing a significant role. The UHRF1-DNMT1 complex regulates DNA methylation, particularly in mammalian cells. This review paper explores the relationship between UHRF1, DNMT1, and DNA methylation homeostasis in cancer cells. Studies have primarily focused on human colorectal cell lines HCT116 and DLD1, shedding light on the protein stabilization of UHRF1 and DNMT1 through methylation-mediated ubiquitination. The impact of UHRF1 on DNA methylation in cancer cells is evaluated by controlling growth hormones. Furthermore, the study reveals that UHRF1 down-regulation influences DNMT1-mediated methylation on DNA and highlights the non-canonical functions of UHRF1 that significantly contribute to DNA methylation homeostasis. This review paper delves into the intricate relationship between the UHRF1-DNMT1 complex and DNA methylation homeostasis, particularly in the context of cancer cells. By examining the protein stabilization mechanisms of UHRF1 and DNMT1, as well as the regulatory role of UHRF1 in DNA methylation, this study provides valuable insights into the molecular mechanisms underlying epigenetic regulation. The findings presented in this review contribute to a better understanding of the role of UHRF1 and DNMT1 in maintaining DNA methylation patterns and highlight their potential implications in cancer biology.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".