Presynaptic plasticity and associative learning are impaired in a <i>Drosophila presenilin</i> null mutant
Bibliographic record
Abstract
Alzheimer's disease is a neurodegenerative disorder characterized by progressive memory and cognitive decline that is associated with changes in synaptic plasticity and neuronal cell loss. Recent evidence suggests that some of these defects may be due to a loss of normal presenilin activity. Here, we have examined the effect of loss of Drosophila presenilin (psn) function on synaptic plasticity and learning. Basal transmitter release was elevated in psn mutants while both paired pulse synaptic plasticity and post-tetanic potentiation were impaired. These defects in synaptic strength and plasticity were not due to developmental defects in NMJ morphology. We also found that psn null terminals take up significantly less FM 4-64 than control terminals when loaded with high frequency stimulation, suggesting a defect in synaptic vesicle availability or mobilization. To determine whether these reductions in synaptic plasticity had any impact on learning, we tested the larvae for defects in associative learning. Using both olfactory and visual learning assays, we found that associative learning is impaired in psn mutants compared with controls. Both the learning and synaptic defects could be rescued by expression of a full length psn transgene suggesting the defects are specifically due to a loss of psn function. Taken together, these results provide the first evidence of learning and synaptic defects in a Drosophila psn mutant and strongly suggest a presynaptic role for presenilin in normal neuronal function.
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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) | 0.001 | 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".