Frequent coexpression of the vesicular glutamate transporter 1 and 2 genes, as well as coexpression with genes for choline acetyltransferase or glutamic acid decarboxylase in neurons of rat brain
Bibliographic record
Abstract
It is widely believed that expression of the vesicular glutamate transporter genes VGLUT1 and VGLUT2 is restricted to glutamatergic neurons and that the two transporters segregate in different sets of neurons. Using single-cell multiplex RT-PCR (sc-RT-mPCR), we show that VGLUT1 and VGLUT2 mRNAs were coexpressed in most of the sampled neurons from the rat hippocampus, cortex, and cerebellum at postnatal Day (P)14 but not P60. In accordance, changes in VGLUT1 and VGLUT2 mRNA concentrations were found to occur in these and other brain areas between P14 and P60, as revealed by semiquantitative RT-PCR and quantitated by ribonuclease protection assay. VGLUT1 and -2 coexpression in the hippocampal formation is supported further by in situ hybridization data showing that virtually all cells in the CA1-CA3 pyramidal and granule cell layers were highly positive for both transcripts until P14. It was revealed using sc-RT-mPCR that transcripts for VGLUT1 and VGLUT2 were also present in neurons of the cerebellum, striatum, and septum that expressed markers for gamma-aminobutyric acid (GABA)ergic or cholinergic phenotypes, as well as in hippocampal cells containing transcripts for the glial fibrillary acidic protein. Our study suggests that VGLUT1 and VGLUT2 proteins may often transport glutamate into vesicles within the same neuron, especially during early postnatal development, and that they are expressed widely in presumed glutamatergic, GABAergic, and cholinergic neurons, as well as in astrocytes. Furthermore, our study shows that such coexpressing neurons remain in the adult brain and identifies several areas that contain them in both young and adult rats.
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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".