Proteomic comparison of two fractions derived from the transsynaptic scaffold
Bibliographic record
Abstract
A fraction derived from presynaptic specializations (presynaptic particle fraction; PPF) can be separated from postsynaptic densities (PSD) by adjusting the pH of Triton X-100 (TX-100) extraction of isolated transsynaptic scaffolds. Solubilization of the PPF corresponds to disruption of the presynaptic specialization. We show that the PPF is insoluble to repeated TX-100 extraction at pH 6.0 but becomes soluble in detergent at pH 8.0. By immunolocalization, we find that the major proteins of the PPF, clathrin and dynamin, are concentrated in the presynaptic compartment. By using multidimensional protein identification technology, we compared the protein compositions of the PPF and the PSD fraction. We identified a total of 341 proteins, 50 of which were uniquely found in the PPF, 231 in the PSD fraction, and 60 in both fractions. Comparison of the two fractions revealed a relatively low proportion of actin and associated proteins and a high proportion of vesicle or intracellular compartment proteins in the PPF. We conclude that the PPF consists of presynaptic proteins not connected to the actin-based synaptic framework; its insolubility in pH 6 and solubility in pH 8 buffered detergent suggests that clathrin might be an anchorage scaffold for many proteins in the PPF.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".