Characterization of serotonin neurotransmission in knockout mice: implications for major depression
Bibliographic record
Abstract
The interaction between genes and environment plays a significant role in the pathogenesis of major depression and mood disorders. Preclinical and clinical studies have established that a dysfunction of serotonin (5-HT) neurotransmission is a common hallmark in major depression and drugs acting on the 5-HT system have antidepressant properties. In the past 15 years, the development of knockout mice showing a depressive-like or resilience-like phenotype have allowed us to better understand the complex relationship between genes, behaviour and the 5-HT system in mood disorders. The present review revises several knockout mice genotypes with 'mood' alteration and analyses how 5-HT firing activity, measured with electrophysiological techniques, is impaired after a gene manipulation. The behavior and electrophysiology data from 5-HT transporter (5HTT), 5-HT₁(A), 5-HT₄, the neurokinin 1 (NK₁) receptor, fatty acid amide hydrolase (FAAH) and the TWIK-1 related K+ (TREK-1) channel knockout mice are here analysed. Interestingly, a correlation between 5-HT firing rate and depressive/resilience phenotypes can be established in these different knockouts. Furthermore, findings in knockout mice have been successfully translated to humans, and findings from human studies have helped to design and generate knockout mice to explore new hypotheses of the etiology of human depression. The correlation of 5-HT activity and behavior could be a predictor factor for understanding the role of receptors, channels and enzymes in depression, and could be used also to assess the potential antidepressive effects of novel drugs.
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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 | 0.000 |
| 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".