Synaptic proteasome is inhibited in Alzheimer’s disease models and is associated with memory impairment in mice
Bibliographic record
Abstract
Abstract Background The proteasome plays key roles in neuronal function by regulating protein turnover, quality control, and elimination of oxidized and misfolded proteins. Recent evidence indicates that proteasome activity is required for synaptic plasticity and memory, and may be altered in Alzheimer’s disease (AD). Method Here, we investigate proteasome function and localization at synapses in AD post‐mortem brain tissue and in experimental models of AD by using western blotting, immunocytochemistry and proteasome activity assay. We also evaluated core AD‐related features upon proteasome inhibition by using DCFDA measurement, phaloidin staining, SUnSET and mice memory tasks. Result We found a marked increase in ubiquitinylated proteins in post‐mortem AD hippocampi compared to controls. Using human ex vivo adult cortical tissue, primary neuronal cultures, isolated synaptosomes and in vivo experiments in mice, we show that amyloid‐b oligomers (AbOs) inhibit synaptic proteasome activity and trigger a reduction in synaptic proteasome content. We further show proteasome inhibition specifically in hippocampal synaptic fractions derived from APPswePS1DE9 mice. Treatment with the proteasome inhibitor, lactacystin, induces reactive oxygen species formation and loss of dendritic spines in hippocampal neurons, inhibits hippocampal mRNA translation, and causes memory impairment in mice. Conclusion These findings demonstrate that synaptic proteasome activity is inhibited in post‐mortem AD brain tissue and in experimental models of AD. Results further show that proteasome inhibition is associated with spine loss and memory impairment in mice, suggesting that proteasome inhibition may contribute to synaptic and memory deficits in AD.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".