CRF signaling between neurons in the paraventricular nucleus of the hypothalamus (PVN) coordinates stress responses
Bibliographic record
Abstract
The importance of a precisely coordinated neuroendocrine, autonomic, and behavioral stress response was a primary theme at the Stress Neurobiology Workshop 2018, held in the beautiful setting of Banff Provincial Park in Alberta, Canada. Much of the research featured at this meeting reinforced the importance of appropriately responding to stress in order to avoid various neuropsychiatric pathologies, including Post-Traumatic Stress Disorder (PTSD), depression, and addiction. Corticotropin-Releasing Factor (CRF) neurons in the paraventricular nucleus of the hypothalamus (PVN) are central players in the stress response, integrating both external and visceral stress-relevant information, then directing neuroendocrine, autonomic and behavioral adaptations via endocrine and neural outputs of the PVN. The PVN contains a densely packed array of neuron types that respond to stress, including CRF neurons that activate the Hypothalamic-Pituitary-Adrenal (HPA) axis. Recently, identification of a new population of neurons in the PVN that express CRF Receptor 1 (CRFR1) has suggested that CRF release in the PVN signals to neighboring CRF responsive neurons, potentially functioning in HPA axis feedback, neuroendocrine coordination, and autonomic signaling. Here, we review our recent work characterizing an intra-PVN microcircuit in which locally released CRF release activates CRFR1+ neurons that make recurrent inhibitory GABAergic synapses onto CRF neurons to dampen excitability , therebylimiting HPA axis hyperactivity in response to stress and promoting stress recovery, which we presented in a poster session at the conference. We then discuss questions that have arisen following publication of our initial characterization of the microcircuit, regarding specific features of intra-PVN CRF signaling and its potential role in coordinating neuroendocrine, autonomic, and behavioral outputs of the PVN. Our presented work, as well as many of the presentations at the Stress Neurobiology Workshop 2018 together establish intra-PVN signaling as an important regulatory node in stress response pathways, which are central to the pathogenesis of neuropsychiatric disorders.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".