Acute responsivity of the serotonergic system to S-citalopram and positive emotionality—the moderating role of the 5-HTTLPR
Bibliographic record
Abstract
According to the idea that the central serotonergic system has a modulatory function on behavior and personality in general, we aimed to highlight its association to habitual positive emotionality. In a placebo-controlled double-blind and randomized cross-over neuroendocrine challenge design (n = 72 healthy males) we investigated the association of the central serotonergic responsivity, 5-HTTLPR-genotype as well as their combined effects on positive emotionality. Regression analyses revealed an involvement of the serotonergic system in positive emotionality. There was, however, no direct association between positive emotionality and cortisol responses to S-citalopram; rather 5-HTTLPR-genotype showed an association (p < 0.05). That is, positive emotionality scores increased with the number of s-alleles carried by the individuals. Most notable was the moderating role of 5-HTTLPR-genotype (p < 0.05) on the association between acute serotonergic responsivity and positive emotionality. Indeed, this association was only found in ss-homozygotes, in which the acute responsivity of the serotonergic system additionally seems to contribute to the level of positive emotionality (r = 0.70, p < 0.05). The findings correspond to previous research demonstrating that the 5-HTTLPR is not only involved in the negative-emotional aspects of behavior and temperament, but is associated, moreover, with positive affectivity-supporting the assumption of its valence-neutrality. In addition, our data are in line with the idea of possible influences of the 5-HTTLPR-genotype on early neuronal development. They also indicate the need for further studies in order to clearly elucidate the role of the serotonergic system and its subcomponents in the regulation of positive emotionality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".