Enkephalinergic afferents of the centromedial amygdala in the rat
Bibliographic record
Abstract
The connectivity of the amygdaloid complex has been extensively explored with both anterograde and retrograde tracers. Even though the afferents of the centromedial amygdala [comprising the central (CEA) and medial (MEA) amygdaloid nuclei] are well established, relatively little is known about the neuropeptide phenotype of these connections. In this study, we first examined the distribution of mu-opioid receptor (MOR) and delta-opioid receptor (DOR) in the amygdala via in situ hybridization and immunohistochemistry. We then investigated the distribution of Met-enkephalin (ENK) and Leu-ENK fibers with immunohistochemistry and examined the distribution of preproenkephalin mRNA in the amygdala by using in situ hybridization. Finally, we examined the ENK projections to the CEA and MEA by using stereotaxic injections of the retrograde tracer cholera toxin subunit B or fluorogold revealed by immunohistochemistry combined with in situ hybridization to identify ENKergic neurons. Our results indicate that the centromedial amygdala receives ENK afferents, as indicated by the presence of MOR, DOR, and ENK fibers in the CEA and MEA, originating primarily from the bed nucleus of the stria terminalis (BST) and from other amygdaloid nuclei. The posterior BST, the basomedial nucleus (BMA), and the cortical nucleus of the amygdala (COA) were found to be the major ENK afferents of the MEA, whereas the anterolateral BST, the COA, the MEA, and the BMA provided the main ENKergic innervation of the CEA. In addition, we found that the ventromedial nucleus of the hypothalamus and the pontine parabrachial nucleus provide a moderate ENK input to the CEA and MEA. The functional implications of these connections in stress, anxiety, and nociception are discussed.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".