Inhibition of P53-mediated cell cycle control as the determinant in dedifferentiated liposarcomas development.
Bibliographic record
Abstract
genes, and harbor additional amplifications of chromosomes 6 and 1. Novel therapies targeted at the gene products of chromosome 12 are currently considered in clinical trials. Our work consisted in a genomic characterization of DDLS to draw up a complete picture of alterations, including genomic signatures, tumor mutation burden, gene mutations, copy number variations, translocations, gene fusions and methylation modifications. Analysis of translocations helped to understand the mechanisms underlying the amplification processes. Combination of mutations and loss of heterozygosity or homozygous deletions were detected and led to inactivate tumor suppressor genes (TSG). In contrast, methylation anomalies seemed not linked to any particular genomic profile. All identified anomalies, whether amplifications and/or TSG inactivation, involve genes playing a role in p53 regulation, that appears to be the epicenter of the initiation process in DDLS tumorigenesis, as is also known to be responsible for Li-Fraumeni syndrome, a family cancer syndrome highly predisposing to sarcomas.
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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) | 0.000 | 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) | 0.002 | 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".