Subfornical organ neurons integrate cardiovascular and metabolic signals
Bibliographic record
Abstract
The subfornical organ (SFO) is a critical circumventricular organ involved in the control of cardiovascular and metabolic homeostasis. Despite the plethora of circulating signals continuously sensed by the SFO, studies investigating how these signals are integrated are lacking. In this study, we use patch-clamp techniques to investigate how the traditionally classified “cardiovascular” hormone ANG II, “metabolic” hormone CCK and “metabolic” signal glucose interact and are integrated in the SFO. Sequential bath application of CCK (10 nM) and ANG (10 nM) onto dissociated SFO neurons revealed that 63% of responsive SFO neurons depolarized to both CCK and ANG; 25% depolarized to ANG only; and 12% hyperpolarized to CCK only. We next investigated the effects of glucose by incubating and recording neurons in either hypoglycemic, normoglycemic, or hyperglycemic conditions and comparing the proportions of responses to ANG ( n = 55) or CCK ( n = 83) application in each condition. A hyperglycemic environment was associated with a larger proportion of depolarizing responses to ANG ( χ2, P < 0.05), and a smaller proportion of depolarizing responses along with a larger proportion of hyperpolarizing responses to CCK ( χ2, P < 0.01). Our data demonstrate that SFO neurons excited by CCK are also excited by ANG and that glucose environment affects the responsiveness of neurons to both of these hormones, highlighting the ability of SFO neurons to integrate multiple metabolic and cardiovascular signals. These findings have important implications for this structure’s role in the control of various autonomic functions during hyperglycemia.
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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 | 0.001 |
| 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".