Maturation of metastases in peripheral neuroblastic tumors (neuroblastoma) of children
Bibliographic record
Abstract
Peripheral neuroblastic tumors of childhood exhibit 3 principal neural crest lineages: primitive neuroblastoma, ganglioneuroblastoma, and ganglioneuroma. They are unique in undergoing maturation of neurons (ganglion cells) and Schwann cells, thereby recapitulating normal fetal neuronal development in the brain. Precision in estimating neurogenesis is enhanced by immunoreactivities of markers of neuronal maturation. Whether organ tissue factors in different sites of metastases influence rates of maturation and whether metastases are similar to their primary neuroblastic tumor are incompletely documented. Four young children, 1 with a mixed primary adrenal tumor and 3 with metastases were studied at surgery or autopsy. Immunocytochemical reactivities included microtubule-associated protein-2, synaptophysin, chromogranin-A, somatostatin, keratan sulfate, vimentin, S-100β protein, and PHOX2B. Primary tumors were non-uniform with regions of either poor or enhanced maturation. Both neuronal and Schwannian lineages were represented in each tumor type but differed in proportions. Bi- or multi-nucleated ganglion cells matured equal to mononuclear forms. Ganglion cell maturation was similar in metastases regardless of the target organ. Metastases resembled primary tumors. Immunocytochemical markers of neuronal and of Schwann cell maturation provide greater diagnostic precision to supplement histological criteria. Interval between diagnosis of primary tumor and metastases, metastatic target tissues, and chemotherapy over an interval of time do not appear to influence neuroblastic or Schwann cell differentiation.
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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 | 0.001 |
| 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) | 0.001 | 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".