Effects of the antidepressant fluoxetine on the subcellular localization of 5-HT <sub>1A</sub> receptors and SERT
Bibliographic record
Abstract
Serotonin (5-HT) 5-HT(1A) autoreceptors (5-HT(1A)autoR) and the plasmalemmal 5-HT transporter (SERT) are key elements in the regulation of central 5-HT function and its responsiveness to antidepressant drugs. Previous immuno-electron microscopic studies in rats have demonstrated an internalization of 5-HT(1A)autoR upon acute administration of the selective agonist 8-OH-DPAT or the selective serotonin reuptake inhibitor antidepressant fluoxetine. Interestingly, it was subsequently shown in cats as well as in humans that this internalization is detectable by positron emission tomography (PET) imaging with the 5-HT(1A) radioligand [(18)F]MPPF. Further immunocytochemical studies also revealed that, after chronic fluoxetine treatment, the 5-HT(1A)autoR, although present in normal density on the plasma membrane of 5-HT cell bodies and dendrites, do not internalize when challenged with 8-OH-DPAT. Resensitization requires several weeks after discontinuation of the chronic fluoxetine treatment. In contrast, the SERT internalizes in both the cell bodies and axon terminals of 5-HT neurons after chronic but not acute fluoxetine treatment. Moreover, the total amount of SERT immunoreactivity is then reduced, suggesting that SERT is not only internalized, but also degraded in the course of the treatment. Ongoing and future investigations prompted by these finding are briefly outlined by way of conclusion.
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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) | 0.003 | 0.001 |
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".