Vesicular glutamate (VGlut), GABA (VGAT), and acetylcholine (VACht) transporters in basal forebrain axon terminals innervating the lateral hypothalamus
Bibliographic record
Abstract
The basal forebrain (BF) is known to play important roles in cortical activation and sleep, which are likely mediated by chemically differentiated cell groups including cholinergic, gamma-aminobutyric acid (GABA)ergic and other unidentified neurons. One important target of these cells is the lateral hypothalamus (LH), which is critical for arousal and the maintenance of wakefulness. To determine whether chemically specific BF neurons provide an innervation to the LH, we employed anterograde transport of 10,000 MW biotinylated dextran amine (BDA) together with immunohistochemical staining of the vesicular transporter proteins (VTPs) for glutamate (VGluT1, -2, and -3), GABA (VGAT), or acetylcholine (ACh, VAChT). In addition, we applied triple staining for the postsynaptic proteins (PSPs), PSD-95 with VGluT or Gephyrin (Geph) with VGAT, to examine whether the BDA-labeled varicosities may form excitatory or inhibitory synapses in the LH. Axons originating from BDA-labeled neurons in the magnocellular preoptic nucleus (MCPO) and substantia innominata (SI) descended within the medial forebrain bundle and extended collateral varicose fibers to contact LH neurons. In the LH, the BDA-labeled varicosities were immunopositive (+) for VAChT ( approximately 10%), VGluT2 ( approximately 25%), or VGAT ( approximately 50%), revealing an important influence of newly identified glutamatergic together with GABAergic BF inputs. Moreover, in confocal microscopy, VGluT2+ and VGAT+ terminals were apposed to PSD-95+ and Geph+ profiles respectively, indicating that they formed synaptic contacts with LH neurons. The important inputs from glutamatergic and GABAergic BF cells could thus regulate LH neurons in an opposing manner to stimulate vs. suppress cortical activation and behavioral arousal reciprocally.
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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 | 0.000 |
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".