NPY presynaptic actions are reduced in the hypothalamic mpPVN of obese (<i>fa/fa</i>), but not lean, Zucker rats <i>in vitro</i>
Bibliographic record
Abstract
1. Neuropeptide Y (NPY) profoundly enhances feeding when injected intracerebroventricularly, or directly into hypothalamic nuclei, such as the paraventricular nucleus (PVN). Paradoxically, NPY has a reduced action on feeding in obese Zucker rats relative to lean Zucker rats, although the obese rats have much higher levels of hypothalamic NPY expression. GABAergic inputs to a subpopulation of medial parvocellular PVN (mpPVN) neurons are sensitive to NPY. Here, we tested the hypothesis that the blunted eating response to NPY observed in obese Zucker rats will be reflected in a reduced NPY action at mpPVN GABAergic synapses. 2. 'Blind' whole-cell patch-clamp recordings made from mpPVN neurons in acute brain slices of lean and obese Zucker rats revealed GABAergic inhibitory postsynaptic currents (IPSC) responses which were inhibited by NPY. While the maximum response in the obese Zucker rats was significantly less than in lean Zucker or Sprague-Dawley rats, there was no difference in the EC(50). 3. Experiments using blocking concentrations of Y(1)- or Y(5)-receptor antagonists revealed no differences between lean and obese Zucker rats in the contributions of either of these receptors to the total NPY response in mpPVN. 4. NPY is less effective at the mpPVN GABA synapse in obese than in lean Zucker rats. This is not associated with a change in the proportion of Y(1) or Y(5) receptors mediating the NPY response, and is consistent with the downregulation of NPY receptors or a reduction in receptor-effector coupling, and with the reduced sensitivity of obese rats to NPY.
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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 | 0.001 |
| 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".