17β‐estradiol attenuates excitatory neurotransmission and enhances the excitability of rat parabrachial neurons in vitro
Bibliographic record
Abstract
The steroid hormone 17beta-estradiol and its respective receptors have been found in several cardiovascular nuclei in the central nervous system including the parabrachial nucleus. In a previous study, we provided evidence that 17beta-estradiol attenuated an outward potassium conductance in parabrachial neurons of male rats, using an in vitro slice preparation. In this study we sought to enhance the comprehensive information provided previously on estradiol's postsynaptic effects in the parabrachial nucleus by directly examining whether 17beta-estradiol application will modulate excitatory synaptic neurotransmission. Using a pontine slice preparation and whole-cell patch-clamp recording, bath application of either 17beta-estradiol (20-100 muM) or BSA-17beta-estradiol (50 muM) decreased the amplitude of evoked excitatory postsynaptic currents (from 30-60% of control) recorded from neurons in the parabrachial nucleus. The paired pulse ratio was not significantly affected and suggests a post-synaptic site of action. The inhibitory effect on the synaptic current was relatively long-lasting (non-reversible) and was blocked by the selective estrogen receptor antagonist, ICI 182,780. Furthermore, 17beta-estradiol reduced the maximum current elicited by a ramp protocol, increased the input resistance measured between resting membrane potential and action potential threshold and caused an increase in the firing frequency of the cells under current-clamp. In summary, 17beta-estradiol caused 3 effects: first, a depolarization; second, a reduction in evoked excitatory postsynaptic potentials; and third, an enhancement of action potential firing frequency in neurons of the parabrachial nucleus. These observations are consistent with our previous findings and support a role for estrogen in modulating neurotransmission in this nucleus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".