Glycemic State Regulates Brain Derived Neurotrophic Factor Responsiveness of Neurons in the Paraventrucular Nucleus
Bibliographic record
Abstract
Brain derived neurotrophic factor (BDNF) is a chemical messenger that has been implicated in the central control of food intake and regulation of the stress axis. Consistent with a role in feeding behavior, TrkB, the receptor through which BDNF exerts its effects, is expressed in the paraventricular nucleus (PVN). The PVN is a complex integrative autonomic centre with critical roles in the coordinated control of food intake. Recently, studies have shown that glucose‐sensing neurons in areas of the hypothalamus, including PVN, exhibit altered excitability in response to changes in extracellular glucose. Here, whole cell current‐clamp recordings were employed on rat PVN neurons in slice preparation to evaluate the ability of these cells to integrate multiple metabolically relevant signals. BDNF (2nM) was bath applied in both high (10mM) and low (0.2mM) extracellular glucose concentrations. BDNF applied to PVN neurons (N=48) in 10mM glucose elicited varying responses with 50% depolarizing (mean change in membrane potential ± standard error: 9.0 ± 1.2 mV), 23% hyperpolarizing (mean: ‐6.7 ± 1.4 mV), and 27% showing no response to BDNF treatment. However, BDNF's effects were profoundly altered in hypoglycemic conditions. BDNF application to PVN neurons in 0.2mM glucose (N=15) elicited primarily hyperpolarizing effects (73%, mean: ‐6.4 ± 0.9 mV) apart from one cell that depolarized (7%, mean: 4.8 mV). Our findings demonstrate the potential role of BDNF in feeding through its impact on the excitability of PVN neurons and how these responses are altered by glycemic state.
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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".