Cellular mechanisms of orexin actions on paraventricular nucleus neurones in rat hypothalamus
Bibliographic record
Abstract
Using whole-cell patch clamp techniques we have examined the cellular mechanisms underlying the effects of orexin A (OX-A) on electrophysiologically identified magnocellular and parvocellular neurones in the rat hypothalamic paraventricular nucleus (PVN). The majority of magnocellular neurones (67 %) showed concentration-dependent, reversible depolarizations in response to OX-A. These effects were abolished in tetrodotoxin (TTX), suggesting them to be indirect effects on this population of neurones. OX-A also caused increases in excitatory postsynaptic current (EPSC) frequency and amplitude in magnocellular neurones. The former effects were again blocked in TTX while increases in mini-EPSC amplitude remained. Depolarizing effects of OX-A on magnocellular neurones were also found to be abolished by kynurenic acid, supporting the conclusion that these effects were the result of activation of a glutamate interneurone. Parvocellular neurones (73 % of those tested) also showed concentration-dependent, reversible depolarizations in response to OX-A. In contrast to magnocellular neurones, these effects were maintained in TTX, indicating direct effects of OX-A on this population of neurones. Voltage clamp analysis using slow voltage ramps demonstrated that OX-A enhanced a non-selective cationic conductance with a reversal potential of -40 mV in parvocellular neurones, effects which probably explain the depolarizing effects of this peptide in this subpopulation of PVN neurones. These studies have identified separate cellular mechanisms through which OX-A influences the excitability of magnocellular and parvocellular PVN neurones.
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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".