Activation of the TrkB Neurotrophin Receptor Is Induced by Antidepressant Drugs and Is Required for Antidepressant-Induced Behavioral Effects
Bibliographic record
Abstract
Recent studies have indicated that exogenously administered neurotrophins produce antidepressant-like behavioral effects. We have here investigated the role of endogenous brain-derived neurotrophic factor (BDNF) and its receptor trkB in the mechanism of action of antidepressant drugs. We found that trkB.T1-overexpressing transgenic mice, which show reduced trkB activation in brain, as well as heterozygous BDNF null (BDNF(+/)-) mice, were resistant to the effects of antidepressants in the forced swim test, indicating that normal trkB signaling is required for the behavioral effects typically produced by antidepressants. In contrast, neurotrophin-3(+/)- mice showed a normal behavioral response to antidepressants. Furthermore, acute as well as chronic antidepressant treatment induced autophosphorylation and activation of trkB in cerebral cortex, particularly in the prefrontal and anterior cingulate cortex and hippocampus. Tyrosines in the trkB autophosphorylation site were phosphorylated in response to antidepressants, but phosphorylation of the shc binding site was not observed. Nevertheless, phosphorylation of cAMP response element-binding protein was increased by antidepressants in the prefrontal cortex concomitantly with trkB phosphorylation and this response was reduced in trkB.T1-overexpressing mice. Our data suggest that antidepressants acutely increase trkB signaling in a BDNF-dependent manner in cerebral cortex and that this signaling is required for the behavioral effects typical of antidepressant drugs. Neurotrophin signaling increased by antidepressants may induce formation and stabilization of synaptic connectivity, which gradually leads to the clinical antidepressive effects and mood recovery.
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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 | 0.000 |
| 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".