Germline <i>DICER1</i> mutation and associated loss of heterozygosity in a pineoblastoma: Figure 1
Bibliographic record
Abstract
Pineoblastomas occur in RB-1 mutation carriers,1 but are rarely seen in association with other hereditary syndromes.2 Germline DICER1 mutations are associated with embryonal tumours such as pleuropulmonary blastoma (PPB),3 ,4 so we hypothesised that such mutations might also occur in children with pineoblastoma. Here we describe a novel deleterious germline DICER1 mutation in a young child with a highly aggressive pineoblastoma. In addition, we observed loss of heterozygosity (LOH) of the wild-type allele, an event not previously reported in DICER1 associated tumours.5 ,6 Our observations suggest: (1) pineoblastomas are associated with germline DICER1 mutations; and (2) unexpectedly, tumour cells can thrive in the absence of functional DICER1 . The pineal gland, so named by Galen because of its resemblance to a pine nut, is a ∼175 mg midline structure situated on the posterior wall of the third ventricle, deep between the cerebral hemispheres. Pineal gland tumours are often derived from ectopic germ cell tissue, but pineocytomas and pineoblastomas also occur. A pineoblastoma is a supratentorial primitive neuroectodermal tumour arising in the pineal gland. Germline mutations in tumour suppressor genes have rarely been associated with pineoblastomas,1 ,2 but mutations in RB-1 can result in so-called ‘trilateral retinoblastoma’.1 We obtained …
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".