Enkephalin co‐expression with classic neurotransmitters in the amygdaloid complex of the rat
Bibliographic record
Abstract
This study aimed at characterizing the neurotransmitter phenotype of enkephalin neurons in the rat amygdaloid complex. We first established the detailed distribution of vesicular glutamate transporters 1 and 2 (VGLUT1 and -2) and glutamate decarboxylase 65 (GAD65) in the amygdala by using in situ hybridization. In the amygdaloid complex, GAD65 is strongly expressed in striatal-like divisions, namely, the anterior amygdaloid area, the central nucleus (CEA), the intercalated nuclei, and the dorsal part of the medial nucleus (MEA). VGLUT1 and -2 expression is mostly segregated to specific divisions of the amygdale, with VGLUT2 being expressed only in the MEA, the anterior cortical nucleus (COAa), and the anterior basomedial nucleus (BMAa), whereas VGLUT1 is expressed in all other divisions of the amygdala. Second, we assessed the co-expression of preproenkephalin (ppENK) with GAD65, VGLUT1, or VGLUT2 by using double fluorescent in situ hybridization. We found that ppENK mRNA co-localized exclusively with GAD65 in all striatal-like structures of the amygdaloid complex with the exception of the MEA, where ENK also co-localized with VGLUT2 mRNA. This co-localization is most apparent in the posteroventral part of the MEA, where 70% of ENKergic cells expressed VGLUT2. In addition, ppENK also co-localized with VGLUT1 because more than 95% of ENK cells in the basolateral amygdala expressed VGLUT1. In contrast, less than 25% of ENKergic cells expressed VGLUT1 in the lateral nucleus of the amygdale, with the majority of ENK cells expressing GAD65 mRNA in this nucleus. These results have broad implications for understanding the functional roles of enkephalinergic neurotransmission in the amygdaloid complex.
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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".