Immunohistochemical Detection of Nestin in Pediatric Brain Tumors
Bibliographic record
Abstract
Nestin is an intermediate filament protein (IFP) expressed in undifferentiated cells during CNS development and in CNS tumors. Previous studies have arrived at different conclusions in terms of which types of CNS tumors express nestin. In this report we establish an immunohistochemical protocol using antigen retrieval, which significantly enhances staining with two polyclonal anti-nestin antisera, #130 and #4350. The staining pattern was identical for the two nestin antisera and very similar to that of vimentin, while glial fibrillary acidic protein (GFAP), immunoreactivity was absent from 9.5-week-old forebrain. The current study of 20 primary CNS tumors from pediatric patients included seven ependymomas, seven primitive neuroectodermal tumors (PNETs), five pilocytic astrocytomas, and one glioblastoma multiforme (GBM). All these tumors expressed nestin to various extents, in contrast to five brain metastases tested. Strong nestin immunoreactivity was found in malignant primary CNS tumors, whereas benign pilocytic astrocytomas showed low but consistent nestin expression. In all tumors nestin immunoreactivity was confined to the cytoplasm of tumor cells and was co-expressed with astrocyte markers vimentin, GFAP, and S-100. Vascular endothelial cells of all neoplasms also showed marked immunoreactivity for nestin and vimentin, whereas they were negative for GFAP and S-100. In conclusion, antiserum #4350 detected nestin in formalin-fixed, paraffin-embedded tissue sections by heat-induced antigen retrieval immunohistochemistry. Nestin was expressed in both highly malignant and low malignant gliomas, indicating the potential use of nestin as a diagnostic tumor marker in surgical pathology.
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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 | 0.000 | 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".