Long-term memory of configural learning is enhanced via CREB upregulation by the flavonoid quercetin in<i>Lymnaea stagnalis</i>
Bibliographic record
Abstract
Animals respond to acute stressors by modifying their behaviour and physiology. The pond snail Lymnaea stagnalis exhibits configural learning (CL), a form of higher order associative learning. In CL snails develop a landscape of fear when they experience a predatory cue along with a taste of food. This experience results in a suppression of the food response; but the memory only persists for 3 h. Lymnaea has also been found to upregulate heat shock proteins (HSPs) as a result of acute heat stress, which leads to the enhancement of memory formation. A plant flavonoid quercetin blocks the upregulation of HSPs when experienced prior to heat stress. Here, we used this blocking mechanism to test the hypothesis that HSP upregulation plays a critical role in CL. Snails experienced quercetin prior to CL training and surprisingly instead of blocking memory formation it enhanced the memory such that it now persisted for at least 24 h. Quercetin exposure either prior to or after CL enhanced long-term memory (LTM) up to 48 h. We quantified mRNA levels of the transcription factor CREB1 in the Lymnaea central nervous system and found LymCREB1 to be upregulated following quercetin exposure. The enhanced LTM phenotype in L. stagnalis was most pronounced when quercetin was experienced during the consolidation phase. Additionally, quercetin exposure during the memory reconsolidation phase also led to memory enhancement. Thus, we found no support of our original hypothesis but found that quercetin exposure upregulated LymCREB1 leading to LTM formation for CL.
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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".