Effects of Fluoxetine and Visual Experience on Glutamatergic and GABAergic Synaptic Proteins in Adult Rat Visual Cortex
Bibliographic record
Abstract
Fluoxetine has emerged as a novel treatment for persistent amblyopia because in adult animals it reinstates critical period-like ocular dominance plasticity and promotes recovery of visual acuity. Translation of these results from animal models to the clinic, however, has been challenging because of the lack of understanding of how this selective serotonin reuptake inhibitor affects glutamatergic and GABAergic synaptic mechanisms that are essential for experience-dependent plasticity. An appealing hypothesis is that fluoxetine recreates a critical period (CP)-like state by shifting synaptic mechanisms to be more juvenile. To test this we studied the effect of fluoxetine treatment in adult rats, alone or in combination with visual deprivation [monocular deprivation (MD)], on a set of highly conserved presynaptic and postsynaptic proteins (synapsin, synaptophysin, VGLUT1, VGAT, PSD-95, gephyrin, GluN1, GluA2, GluN2B, GluN2A, GABAAα1, GABAAα3). We did not find evidence that fluoxetine shifted the protein amounts or balances to a CP-like state. Instead, it drove the balances in favor of the more mature subunits (GluN2A, GABAAα1). In addition, when fluoxetine was paired with MD it created a neuroprotective-like environment by normalizing the glutamatergic gain found in adult MDs. Together, our results suggest that fluoxetine treatment creates a novel synaptic environment dominated by GluN2A- and GABAAα1-dependent plasticity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".