Altered response to the selective serotonin reuptake inhibitor escitalopram in mice heterozygous for the serotonin transporter: an electrophysiological and neurochemical study
Bibliographic record
Abstract
A serotonin (5-HT) transporter (5-HTT; SERT) polymorphism has been associated with depressive states and poor responses to selective serotonin reuptake inhibitors (SSRIs). Given the similar attenuation of SERT activity in SERT+/- mice and in humans with short allele(s) of SERT in its promoter region, it is conceivable that SERT+/- mice offer an adequate model to mimic the human subpopulation with respect to their altered response to SSRIs. This study investigated the effects of the most selective SSRI escitalopram, in heterozygous SERT+/- mice using a combined electrophysiological and neurochemical approach. Results indicated that administration of escitalopram for 2 d resulted in a 72% and 63% decrease in dorsal raphe 5-HT neuronal firing rate in SERT+/+ and SERT+/- mice, respectively. In contrast, administration of escitalopram for 21 d produced a gradual recovery of 5-HT neuronal firing rate to basal level in SERT+/+, but not in SERT+/- mice. In the hippocampus, microdialysis revealed that sustained administration of escitalopram produced a greater increase in extracellular 5-HT ([5-HT]ext) outflow in SERT+/- than in the wild-types with or without a washout of the SSRI. Nevertheless, the ability of microiontophoretically applied 5-HT to inhibit the firing rate of CA3 pyramidal neurons was not different between SERT+/+ and SERT+/- mice given escitalopram for 21 d. The data indicate that the poor response to SSRIs of depressive patients with short allele(s) of SERT is not attributable to a lesser increase in 5-HT transmission in the hippocampus.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".