Bibliographic record
Abstract
N-Myc is a member of the myc family of proto-oncogenes involved in initiation and progression of tumors. While c-MYC, the most characterized member of the family, is well known for its role in cellular proliferation and apoptosis, the function of N-MYC in differentiation and proliferation remains unclear. N-Myc mutant mice present a phenotype more consistent with a role of N-MYC protein in proliferation of precursor populations than in differentiation per se. Recent studies have also shown that N-MYC can enhance apoptosis and shorten the G1 phase of the cell cycle. However, the role of N-MYC in instigating cell-cycle progression has not been clearly demonstrated. Here, we demonstrate that overexpression of N-myc or activation of inducible N-MYC proteins is sufficient to induce apoptosis in serum-starved fibroblast cells, an effect that can be counteracted by overexpression of Bcl-2. Moreover, N-MYC can induce the reentry of quiescent cells into the cell cycle even in the absence of external stimuli. These results indicate that N-MYC and c-MYC share many properties, supporting the model that MYC-specific roles during embryonic development are mediated, at least in part, via their specific profile of expression rather than by their different protein functions.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".