Distributions of hypothalamic neuron populations coexpressing tyrosine hydroxylase and the vesicular GABA transporter in the mouse
Bibliographic record
Abstract
Abstract The hypothalamus contains catecholaminergic neurons marked by the expression of tyrosine hydroxylase (TH). As multiple chemical messengers coexist in each neuron, we determined if hypothalamic TH‐immunoreactive (ir) neurons express vesicular glutamate or GABA transporters. We used Cre/loxP recombination to express enhanced GFP (EGFP) in neurons expressing the vesicular glutamate (vGLUT2) or GABA transporter (vGAT), then determined whether TH‐ir neurons colocalized with native EGFP Vglut2 ‐ or EGFP Vgat ‐fluorescence, respectively. EGFP Vglut2 neurons were not TH‐ir. However, discrete TH‐ir signals colocalized with EGFP Vgat neurons, which we validated by in situ hybridization for Vgat mRNA. To contextualize the observed pattern of colocalization between TH‐ir and EGFP Vgat , we first performed Nissl‐based parcellation and plane‐of‐section analysis, and then mapped the distribution of TH‐ir EGFP Vgat neurons onto atlas templates from the Allen Reference Atlas ( ARA ) for the mouse brain. TH‐ir EGFP Vgat neurons were distributed throughout the rostrocaudal extent of the hypothalamus. Within the ARA ontology of gray matter regions, TH‐ir neurons localized primarily to the periventricular hypothalamic zone, periventricular hypothalamic region, and lateral hypothalamic zone. There was a strong presence of EGFP Vgat fluorescence in TH‐ir neurons across all brain regions, but the most striking colocalization was found in a circumscribed portion of the zona incerta (ZI)—a region assigned to the hypothalamus in the ARA —where every TH‐ir neuron expressed EGFP Vgat . Neurochemical characterization of these ZI neurons revealed that they display immunoreactivity for dopamine but not dopamine β‐hydroxylase. Collectively, these findings indicate the existence of a novel mouse hypothalamic population that may signal through the release of GABA and/or dopamine.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".