Insulin Production in a Neuroectodermal Tumor that Expresses Islet Factor-1, But Not Pancreatic-Duodenal Homeobox 1
Bibliographic record
Abstract
We studied a 60-yr-old female with a brain tumor who showed severe symptoms of hypoglycemia (plasma glucose, 2.2 mmol/L) and hyperinsulinemia (1.28 nmol/L) after radiotherapy. The cystic brain tumor contained proinsulin and insulin at concentrations of 13.6 and 1.22 nmol/L, respectively. Immunohistochemical studies showed the tumor cells were ectodermal in origin but not endodermal, based on three diagnostic features of neuroectodermal tumors 1) pseudorosette formation noted under light microscopy, 2) finding of a small number of dense core neurosecretory granules on electron microscopy, and 3) positive immunostaining for both neuronal specific enolase and protein gene product 9.5. These cells also expressed the transcription factor, neurogenin-3, NeuroD/beta 2, and islet factor I, which are believed to be transcription factors in neuroectoderm as well as in pancreatic islet cells, but not pancreatic-duodenal homeobox 1, Pax4, or Nkx2.2. In addition, they did not express glucagon, somatostatin, or glucagon-like peptide-1. Our results show the presence of proinsulin in an ectoderm cell brain tumor that does not express the homeobox gene, pancreatic-duodenal homeobox 1, but expresses other transcription factors, i.e. neurogenin3, NeuroD/beta 2, and islet factor-1, which are related to insulin gene expression in the brain tumor.
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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) | 0.000 | 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".