The Amyloid Precursor Protein Intracellular Domain Is an Effector Molecule of Metaplasticity
Bibliographic record
Abstract
BACKGROUND: Human studies and mouse models of Alzheimer's disease suggest that the amyloid precursor protein (APP) can cause changes in synaptic plasticity and is contributing to the memory deficits seen in Alzheimer's disease. While most of these studies attribute these changes to the APP cleavage product Aβ, in recent years it became apparent that the APP intracellular domain (APP-ICD) might play a role in regulating synaptic plasticity. METHODS: To separate the effects of APP-ICD on synaptic plasticity from Aβ-dependent effects, we created a chimeric APP in which the Aβ domain is exchanged for its homologous domain from the amyloid precursor-like protein 2. RESULTS: We show that the expression of this chimeric APP has no effect on basal synaptic transmission or synaptic plasticity. However, a synaptic priming protocol, which in control cells has no effect on synaptic plasticity, leads to a complete block of subsequent long-term potentiation induction and a facilitation of long-term depression induction in neurons expressing chimeric APP. We show that the underlying mechanism for this effect on metaplasticity is caused by caspase cleavage of the APP-ICD and involves activation of ryanodine receptors. Our results shed light on the controversially discussed role of APP-ICD in regulating transcription. Because of the short timespan between synaptic priming and the effect on synaptic plasticity, it is unlikely that APP-ICD-dependent transcription is an underlying mechanism for the regulation of metaplasticity during this time period. CONCLUSIONS: Our finding that the APP-ICD affects metaplasticity provides new insights into the altered regulation of synaptic plasticity during Alzheimer's disease.
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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 | 0.001 |
| 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".