Relationship Between Psychophysiological Responses to Aversive Odors and Nutritional Status During Normal Aging
Bibliographic record
Abstract
Psychophysiological responses to disgusting and pleasant smells are one of the most important aspects of olfaction. These emotional signals can constitute an alert against toxic substances, and they may play a major role in food selection and nutritional intake. The aim of this study was to test this hypothesis by examining whether individual physiological responses to odors could predict the subject's nutritional status. Because aging is associated with changes in emotional response to smells, we also examined how aging affects the relationship between olfaction and nutrition. Twenty young and 20 old participants perceived a series of odorants while their psychophysiological responses were simultaneously measured, and completed the Mini-Nutritional Assessment (MNA) questionnaire. Regression between individual correlation coefficients (r-values between odor perceptual ratings and physiological parameters) and individual MNA scores revealed that appropriateness of the physiological responses to aversive odors predicted nutritional status (R2 = 0.22, P < 0.007): participants with higher electromyogram corrugator activity in response to aversive smells had better nutritional status. Furthermore, this relationship was significant in old (R2 = 0.45, P < 0.005) but not young participants (R2 = 0.04, P > 0.44). Taken together, preserved functioning of somatic markers in response to odors during normal aging is associated with better nutritional status, and may facilitate healthier food selection.
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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".