Adiponectin Modulates Excitability of Rat Paraventricular Nucleus Neurons by Differential Modulation of Potassium Currents
Bibliographic record
Abstract
The adipocyte-derived hormone adiponectin acts at two seven-transmembrane domain receptors, adiponectin receptor 1 and adiponectin receptor 2, present in the paraventricular nucleus of the hypothalamus to regulate neuronal excitability and endocrine function. Adiponectin depolarizes rat parvocellular preautonomic neurons that secrete either thyrotropin releasing hormone or oxytocin and parvocellular neuroendocrine corticotropin releasing hormone neurons, leading to an increase in plasma adrenocorticotropin hormone concentrations while also hyperpolarizing a subgroup of neurons. In the present study, we investigate the ionic mechanisms responsible for these changes in excitability in parvocellular paraventricular nucleus neurons. Patch clamp recordings of currents elicited from slow voltage ramps and voltage steps indicate that adiponectin inhibits noninactivating delayed rectifier potassium current (I(K)) in a majority of neurons. This inhibition produced a broadening of the action potential in cells that depolarized in the presence of adiponectin. The depolarizing effects of adiponectin were abolished in cells pretreated with tetraethyl ammonium (0/15 cells depolarize). Slow voltage ramps performed during adiponectin-induced hyperpolarization indicate the activation of voltage-independent potassium current. These hyperpolarizing responses were abolished in the presence of glibenclamide [an ATP-sensitive potassium (K(ATP)) channel blocker] (0/12 cells hyperpolarize). The results presented in this study suggest that adiponectin controls neuronal excitability through the modulation of different potassium conductances, effects which contribute to changes in excitability and action potential profiles responsible for peptidergic release into the circulation.
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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".