BDNF Influences the Excitability of Subfornical Organ Neurons
Bibliographic record
Abstract
Brain‐derived neurotrophic factor (BDNF) is a peptide known to be involved in several mammalian physiological processes. Expression of BDNF transcripts has been identified in the subfornical organ (SFO), a circumventricular organ involved in fluid balance and energy homeostasis. Microarray analysis has demonstrated that levels of transcript expression in the SFO are differentially regulated by fluid and food deprivation, with levels of BDNF expression increasing significantly in response to dehydration, and decreasing in response to starvation (Hindmarch et al 2008). The current study was therefore undertaken in order to determine the effects of BDNF on the excitability of SFO neurons. We used the whole‐cell patch clamp technique to determine the influence of BDNF on the membrane potential of dissociated SFO neurons as well as that of SFO neurons in slice preparation. We found that 86% of dissociated neurons responded when treated with BDNF (2 nM), all of which depolarized (mean 14 mV). Additionally, 75% of neurons tested in the slice preparation responded when treated with BDNF (2 nM). Of these, 67% showed a depolarization (mean 12 mV) and 33% hyperpolarized (mean ‐18 mV). This study suggests the SFO as a potential central nervous system site at which BDNF may act directly to influence homeostatic regulation. Supported by the Canadian Institutes for Health Research
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".