Noradrenaline Triggers GABA<sub>A</sub>Inhibition of Bed Nucleus of the Stria Terminalis Neurons Projecting to the Ventral Tegmental Area
Bibliographic record
Abstract
The lateral part of the ventral bed nucleus of the stria terminalis (vlBNST) is a critical site for the antiaversive effects of noradrenergic drugs during opioid withdrawal. The objective of the present study is to identify the cellular action(s) of noradrenaline in the vlBNST after withdrawal from a 5d treatment with morphine. The vlBNST is a heterogeneous cell group with multiple efferent projections. Therefore, neurons projecting to the midbrain were identified by retrograde transport of fluorescent microspheres injected in the ventral tegmental area (VTA). Whole-cell voltage clamp recordings of these neurons and of those sharing physiological properties were done in brain slices. Noradrenaline activated alpha1-adrenergic receptors to increase GABA(A)-IPSC frequency. Noradrenaline produced a similar increase in GABA(A)-IPSCs during acute opioid withdrawal, but this increase resulted from activation of beta-adrenergic receptors, adenylyl cyclase, and protein kinase A, as well as alpha1-adrenergic receptors. Given that neurons in the vlBNST send an excitatory projection to the VTA, noradrenaline may reduce excitatory drive to mesolimbic dopamine cells. This mechanism might contribute to the withdrawal-induced inhibition of dopamine neurons and explain how noradrenergic drugs microinjected into the vlBNST reduce aversive aspects of opioid withdrawal.
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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".