SynPull: An advanced method for studying neurodegeneration-related aggregates in synaptosomes using super-resolution microscopy
Bibliographic record
Abstract
Synaptic dysfunction is a primary hallmark of both Alzheimer's and Parkinson's disease, leading to cognitive and behavioral decline. While alpha-synuclein, beta-amyloid, and tau are involved in the physiological functioning of synapses, their pathological aggregation has been linked to synaptopathology. The methodology for studying the small-soluble protein aggregates formed by these proteins is limited. Here we describe SynPull, a method combining single-molecule pull-down, super-resolution microscopy, and advanced computational analyses to characterize the protein aggregates in human and mouse synaptosomes. We show that AT8-positive tau aggregates are the predominant aggregate type in synaptosomes from postmortem Alzheimer's disease brain, although the aggregate size does not change in disease. Meanwhile, the relatively smaller amount of alpha-synuclein and beta-amyloid aggregates found in the synapses are larger than the extra-synaptic ones. Collectively, these results show the utility of SynPull to study pathological aggregates in neurodegeneration, elucidating the disease mechanisms causing synaptic dysfunction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".