The Role of Genetics and Synergistic Effect of Targeting Common GeneticMutations in Acute Lymphoblastic Leukemia (ALL)
Bibliographic record
Abstract
Increasing concern regarding non-treatment and relapse in Acute Lymphoblastic Leukemia (ALL) among children and adults has attracted the attention of researchers to investigate the genetic factors of ALL and discover new treatments with a better prognosis. Nevertheless, the survival rate in children is more than in adults; therefore, it is necessary to find new potential molecular targets with better therapeutic results. Genomic analysis has enabled the detection of different genetic defects that are serious for driving leukemogenesis. The study of genetic translocation provides a better understanding of the function of genes involved in disease progression. This paper presents an overview of the main genetic translocations and dysregulations in the signaling pathways of ALL. We also report the inhibitors of these main translocations and evaluate the synergistic effect of chemical inhibitors and gamma-ray irradiation on ALL.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".