miR-34a is a tumor suppressor in zebrafish and its expression levels impact metabolism, hematopoiesis and DNA damage
Bibliographic record
Abstract
Li-Fraumeni syndrome is caused by inherited TP53 tumor suppressor gene mutations. MicroRNA miR-34a is a p53 target and modifier gene. Interestingly, miR-34 triple-null mice exhibit normal p53 responses and no overt cancer development, but the lack of miR-34 promotes tumorigenesis in cancer-susceptible backgrounds. miR-34 genes are highly conserved and syntenic between zebrafish and humans. Zebrafish miR-34a and miR-34b/c have similar expression timing in development, but miR-34a is more abundant. DNA damage by camptothecin led to p53-dependent induction of miR-34 genes, while miR-34a mutants were adult-viable and had normal DNA damage-induced apoptosis. Nevertheless, miR-34a-/- compound mutants with a gain-of-function tp53R217H/ R217H or tp53-/- mutants were more cancer-prone than tp53 mutants alone, confirming the tumor-suppressive function of miR-34a. Through transcriptomic comparisons at 28 hours post-fertilization (hpf), we characterized DNA damage-induced transcription, and at 8, 28 and 72 hpf we determined potential miR-34a-regulated genes. At 72 hpf, loss of miR-34a enhanced erythrocyte levels and up-regulated myb-positive hematopoietic stem cells. Overexpression of miR-34a suppressed its reporter mRNA, but not p53 target induction, and sensitized injected embryos to camptothecin but not to γ-irradiation.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".