The Effects of Acute Tryptophan Depletion and Psychological Traits on Cardiovascular and Mood Responses to Interpersonal Conflict
Bibliographic record
Abstract
The present study investigated the effects of serotonin and psychosocial factors including Cook-Medley hostility, Trait anger, Trait anxiety, and Beck depression scores on cardiovascular and mood responses to interpersonal stress. Eighty-five males and females participated in either an acute tryptophan depletion, a procedure that lowers brain serotonin levels, or a sham tryptophan depletion. They were subsequently exposed to an interpersonal conflict stressor. Cardiovascular and mood measures were recorded at baseline, post-depletion pre-stress, during the stressor, and during recovery. All participants exhibited heightened cardiovascular responses as well as increased anxious, hostile, and depressed mood to the interpersonal conflict. Effects of depletion on cardiovascular reactivity were observed exclusively during recovery. Effects of depletion on negative mood were found at rest and during stress with increased negative affect in the depleted versus balanced condition. Interactions between tryptophan depletion and psychological factors other than hostility were also observed. Greater negative mood responses were found in depleted individuals with high scores on anger, anxiety, and depression factors. Overall, these findings suggest that the effect of serotonin on the stress response may be modulated by psychological factors. Implications for future research on the interaction between serotonin, psychological factors, cardiovascular reactivity, and mood are discussed.
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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) | 0.001 | 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".