Angiotensin II Activates a Nitric-Oxide-Driven Inhibitory Feedback in the Rat Paraventricular Nucleus
Bibliographic record
Abstract
The hypothalamic paraventricular nucleus (PVN) has been shown to play major obligatory roles in autonomic and neuroendocrine regulation. Angiotensin II (ANG) acts as a neurotransmitter regulating the excitability of magnocellular neurons in this nucleus. We report here that ANG also activates a nitric-oxide-mediated negative feedback loop in the PVN that acts to regulate the functional output of magnocellular neurons. Thus in addition to its depolarizing actions on magnocellular neurons, ANG application results in an increase in the frequency of inhibitory postsynaptic potentials in a population of these neurons without effect on the amplitude of these events. ANG was also without significant effect on the mean frequency or amplitude of mini synaptic currents analyzed in voltage-clamp experiments. This increase in inhibitory input after ANG can be abolished by the nitric oxide synthase inhibitor Nomega-nitro-l-arginine methylester, demonstrating a requisite role for nitric oxide in the activation of this pathway. The depolarization of magnocellular neurons that show increased inhibitory postsynaptic potential (IPSP) frequency in response to ANG is significantly smaller than that observed in neurons in which IPSPs frequency was unaffected (3.2 +/- 1.1 vs. 8.0 +/- 0.5 mV, P < 0.05). Correspondingly, after nitric oxide synthase inhibition, the depolarizing effects of ANG on magnocellular neurons are augmented (2.0 +/- 0.7 vs. 6.7 +/- 0.7 mV, P < 0.05). The depolarization was also enhanced in the presence of the GABAergic antagonist bicuculline (1.9 +/- 1.2 vs. 11.9 +/- 2.3, P < 0.001). These data demonstrate that there exists within the PVN an intrinsic negative feedback loop that modulates neuronal excitability in response to peptidergic excitation.
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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".