Widespread immunoreactivity for neuronal nuclei in cultured human and rodent astrocytes
Bibliographic record
Abstract
The monoclonal antibody (mAb) neuronal nuclei (NeuN) labels the nuclei of mature neurons in vivo in vertebrates. NeuN has also been used to define post-mitotic neurons or differentiating neuronal precursors in vitro. In this study, we demonstrate that the NeuN mAb labels the nuclei of astrocytes cultured from fetal and adult human, newborn rat, and embryonic mouse brain tissue. A non-neuronal fibroblast cell line (3T3) also displayed NeuN immunoreactivity. We confirmed that NeuN labels neurons but not astrocytes in sections of P10 rat brain. Western blot analysis of NeuN immunoreactive species revealed a distribution of bands in nucleus-enriched fractions derived from the different cell lines that was similar, but not identical to adult rat brain homogenates. We then examined the hypothesis that the glial fibrillary acidic protein/NeuN-double positive population of cells might correspond to neuronal precursors. Although the NeuN-positive astrocytes were proliferating, no evidence of neurogenesis was detected. Furthermore, expression of additional neuronal precursor markers was not detected. Our results indicate that primary astrocytes derived from mouse, rat, and human brain express NeuN. Our findings are consistent with NeuN being a selective marker of neurons in vivo, but indicate that studies utilizing NeuN-immunoreactivity as a definitive marker of post-mitotic neurons in vitro should be interpreted with caution.
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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) | 0.001 | 0.001 |
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".