Serotonin mediates a learned increase in attraction to high concentrations of benzaldehyde in aged <i>C. elegans</i>
Bibliographic record
Abstract
We utilized olfactory-mediated chemotaxis in Caenorhabditis elegans to examine the effect of aging on information processing and animal behavior. Wild-type (N2) young adults (day 4) initially approach and eventually avoid a point source of benzaldehyde. Aged adult animals (day 7) showed a stronger initial approach and a delayed avoidance to benzaldehyde compared with young adults. This delayed avoidance is due to an increased attraction rather than a decreased avoidance to benzaldehyde because (1) aged odr-3 mutants that are defective in odor attraction showed no delayed benzaldehyde avoidance, and (2) the delay in avoidance was also observed with another attractant diacetyl, but not the repellent octanol. Interestingly, the stronger expression of attractive behavior was only observed at benzaldehyde concentrations of 1% or higher. When worms were grown on nonbacterial growth media instead of Escherichia coli, thus removing the contingency between odors released from the food and the food itself, the increase in attraction to benzaldehyde disappeared. The increased attraction recovered after reinitiating the odor-food contingency by returning animals to E. coli food or supplementing axenic media with benzaldehyde. Moreover, serotonin-deficient mutants showed a deficit in the age-enhanced attraction. These results suggest that the increased attraction to benzaldehyde in aged worms is (1) serotonin mediated, (2) specific to high concentration of odorants, and (3) dependent on a learned association of odor metabolites with the presence of food. We propose that associative learning may selectively modify pathways at or downstream from a low-affinity olfactory receptor.
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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".