Quantitative Immunoblotting Analyses Reveal that the Abundance of Actin, Tubulin, Synaptophysin and EEA1 Proteins is Altered in the Brains of Aged Mice
Bibliographic record
Abstract
Optimal synaptic activity is essential for cognitive function, including memory and learning. Evidence indicates that cognitive decline in elderly individuals is associated with altered synaptic function. However, the impact of aging on the expression of neurotransmitter receptors and accessory proteins in brain synapses remains unclear. To fill this knowledge gap, we investigated the effect of aging on the mouse brain by utilizing a subcellular brain tissue fractionation procedure to measure protein abundance using quantitative Western Blotting. Comparing 7-month- (control) and 22-month- (aged) old mouse tissue, no significant differences were identified in the levels of AMPA receptor subunits between the experimental groups. The abundance of GluN2B NMDA receptor subunits decreased in aged mice, whereas the levels of GluN2A did not change. The analysis of cytoskeletal proteins showed an altered level of actin and tubulin in aged mice while PSD-95 protein did not change. Vesicle protein analysis revealed that synaptophysin abundance is decreased in older brains whereas EEA1 was significantly increased. Thus, our results suggest that physiological aging profoundly impacts the abundance of molecules associated with neurotransmitter release and vesicle cycling, proteins implicated in cognitive 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 | 0.001 | 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) | 0.002 | 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".