Altered gene activity correlated with long‐term memory formation of conditioned taste aversion in <i>Lymnaea</i>
Bibliographic record
Abstract
The pond snail Lymnaea stagnalis is capable of learning conditioned taste aversion (CTA) and then consolidating that learning into long-term memory (LTM) that persists for at least 1 month. LTM requires de novo protein synthesis and altered gene activity. Changes in gene activity in Lymnaea that are correlated with, much less causative, memory formation have not yet been identified. As a first step toward rectifying this situation, we constructed a cDNA microarray with mRNAs extracted from the central nervous system (CNS) of Lymnaea. We then, using this microarray assay, identified genes whose activity either increased or decreased following CTA memory consolidation. We also identified genes whose expression levels were altered after inhibition of the cyclic AMP response element-binding protein (CREB) that is hypothesized to be a key transcription factor for CTA memory. We found that the molluscan insulin-related peptide II (MIP II) was up-regulated during CTA-LTM, whereas the gene encoding pedal peptide preprohormone (Pep) was down-regulated by CREB2 RNA interference. We next examined mRNAs of MIP II and Pep using real-time RT-PCR with SYBR Green. The MIP II mRNA level in the CNS of snails exhibiting "good" memory for CTA was confirmed to be significantly higher than that from the CNS of snails exhibiting "poor" memory. In contrast, there was no significant difference in expression levels of the Pep mRNA between "good" and "poor" performers. These data suggest that in Lymnaea MIP II may play a role in the consolidation process that forms LTM following CTA training.
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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".