Consolidation of long-term memory by insulin in<i>Lymnaea</i>is not brought about by changing the number of insulin receptors
Bibliographic record
Abstract
The pond snail Lymnaea stagnalis learns taste aversion and consolidates it into long-term memory (LTM). This is referred to as conditioned taste aversion (CTA). The superfusion of molluscan insulin-related peptides (MIPs) over the isolated snail brain causes a long-term enhancement of synaptic input between the cerebral giant cell and the B1 buccal motor neuron. This enhancement is hypothesized to underlie CTA. The synaptic enhancement caused by the superfusion of MIPs can be blocked by the application of human insulin receptor antibody, which recognizes the extracellular domain of human insulin receptor and acts as an antagonist even for MIP receptors. An injection of the human insulin receptor antibody into the abdominal cavity of trained snails blocks the consolidation process leading to LTM, even though the snails acquire taste aversion. Here, we examined whether or not taste-aversion training changes the mRNA expression level of MIP receptor in the snail brain and found that it does not. This result, taken together with previous findings, suggest that the MIPs' effect on synaptic function in the snail brain is attributable to a change in the MIP concentration, and not to a change in the mRNA expression level of MIP receptor, which is thought to reflect the number of MIP receptors.
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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".