Balancing tonic and phasic inhibition in hypothalamic corticotropin‐releasing hormone neurons
Bibliographic record
Abstract
Key points GABA transporter (GAT) blockade recruits extrasynaptic GABAA receptors (GABAARs) and amplifies constitutive presynaptic GABABR activity. Extrasynaptic GABAARs contribute to a tonic current. Corticosteroids increase the tonic current mediated by extrasynaptic GABAARs. Abstract Corticotropin‐releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVN) are integratory hubs that regulate the endocrine response to stress. GABA inputs provide a basal inhibitory tone that constrains this system and circulating glucocorticoids (CORT) are important feedback controllers of CRH output. Surprisingly little is known about the direct effects of CORT on GABA synapses in PVN. Here we used whole‐cell patch clamp recordings from CRH neurons in mouse hypothalamic brain slices to examine the effects of CORT on synaptic and extrasynaptic GABA signalling. We show that GABA transporters (GATs) limit constitutive activation of presynaptic GABAB receptors and ensure high release probability at GABA synapses. GATs in combination with GABAB receptors also curtail extrasynaptic GABAAR signalling. CORT has no effect on synaptic GABA signalling, but increases extrasynaptic GABA tone through upregulation of postsynaptic GABAA receptors. These data show that efficient GABA clearance and autoinhibition control the balance between synaptic (phasic) and extrasynaptic (tonic) inhibition in PVN CRH neurons. This balance is shifted towards increased extrasynaptic inhibition by CORT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".