Proliferating cell nuclear antigen (PCNA): a key factor in DNA replication and cell cycle regulation
Bibliographic record
Abstract
BACKGROUND: PCNA (proliferating cell nuclear antigen) has been found in the nuclei of yeast, plant and animal cells that undergo cell division, suggesting a function in cell cycle regulation and/or DNA replication. It subsequently became clear that PCNA also played a role in other processes involving the cell genome. SCOPE: This review discusses eukaryotic PCNA, with an emphasis on plant PCNA, in terms of the protein structure and its biochemical properties as well as gene structure, organization, expression and function. PCNA exerts a tripartite function by operating as (1) a sliding clamp during DNA synthesis, (2) a polymerase switch factor and (3) a recruitment factor. Most of its functions are mediated by its interactions with various proteins involved in DNA synthesis, repair and recombination as well as in regulation of the cell cycle and chromatid cohesion. Moreover, post-translational modifications of PCNA play a key role in regulation of its functions. Finally, a phylogenetic comparison of PCNA genes suggests that the multi-functionality observed in most species is a product of evolution. CONCLUSIONS: Most plant PCNAs exhibit features similar to those found for PCNAs of other eukaryotes. Similarities include: (1) a trimeric ring structure of the PCNA sliding clamp, (2) the involvement of PCNA in DNA replication and repair, (3) the ability to stimulate the activity of DNA polymerase δ and (4) the ability to interact with p21, a regulator of the cell cycle. However, many plant genomes seem to contain the second, probably functional, copy of the PCNA gene, in contrast to PCNA pseudogenes that are found in mammalian genomes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".