<i>DNMT3A</i>mutations and prognostic significance in childhood acute lymphoblastic leukemia
Bibliographic record
Abstract
Little is known about DNMT3A mutations in childhood acute lymphoblastic leukemia (ALL). We screened for DNMT3A mutations in exon 23 and its adjacent intron regions in diagnostic samples of 201 children with ALL. The cDNA samples from 82 patients were also sequenced to identify other mutations in the entire coding region. DNMT3A mutations were detected in exon 23 and its adjacent intron regions only in five patients (2.5%). There was only one mutation in exon 23 in two patients, respectively. In the other three patients, five intronic mutations were found. None of the mutations was found in the five corresponding complete remission samples. DNMT3A mutations were correlated with higher minimal residual disease at the end of remission induction (p = 0.078). Treatment outcome was obviously worse in patients with DNMT3A mutations than in other patients (p < 0.05). Thus, DNMT3A mutations can be found in a few children with ALL, and may have an adverse impact on prognosis.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".