Impact of acute tryptophan depletion on mood and eating-related urges in bulimic and nonbulimic women
Bibliographic record
Abstract
Background: Previous research has shown that many people experience a temporary worsening of mood following acute tryptophan depletion (ATD) and that concurrent use of serotonergic medications may influence such mood responses. We investigated mood and other consequences of ATD in women with bulimia nervosa who were or were not using concurrent serotonergic medications compared with women without bulimia. Methods: Women self-referred for treatment of bulimia who were either not currently using psychoactive medications ( n = 26) or who were using serotonin reuptake inhibitor medications exclusively ( n = 13), as well as medication-free normal-eater control women ( n = 25) completed interviews and questionnaires assessing eating and comorbid psychopathology and then participated in an ATD procedure involving balanced and tryptophan-depleted conditions. Results: In the tryptophan-depleted condition, the groups displayed similar and significant decrements in plasma tryptophan levels and mood. Women with bulimia who were using serotonin reuptake inhibitors, but not the other groups, also reported an increased urge to binge eat in the tryptophan-depleted condition. Limitations: Application of medication in participants with bulimia was not random. Conclusion: Acute reductions in serotonin availability produced similar mood-reducing effects in bulimic and nonbulimic women. To the extent that ATD affected subjective experiences pertinent to eating (i.e., urge to binge eat), such effects appeared to depend upon ATD-induced competition with the therapeutic effects of serotonergic medications.
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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) | 0.000 | 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".