Rapid Assembly of Functional Presynaptic Boutons Triggered by Adhesive Contacts
Bibliographic record
Abstract
CNS synapse assembly typically follows after stable contacts between "appropriate" axonal and dendritic membranes are made. We show that presynaptic boutons selectively form de novo following neuronal fiber adhesion to beads coated with poly-d-lysine (PDL), an artificial cationic polypeptide. As demonstrated by atomic force and live confocal microscopy, functional presynaptic boutons self-assemble as rapidly as 1 h after bead contact, and are found to contain a variety of proteins characteristic of presynaptic endings. Interestingly, presynaptic compartment assembly does not depend on the presence of a biological postsynaptic membrane surface. Rather, heparan sulfate proteoglycans, including syndecan-2, as well as others possibly adsorbed onto the bead matrix or expressed on the axon surface, are required for assembly to proceed by a mechanism dependent on the dynamic reorganization of F-actin. Our results indicate that certain (but not all) nonspecific cationic molecules like PDL, with presumably electrostatically mediated adhesive properties, can effectively bypass cognate and natural postsynaptic ligands to trigger presynaptic assembly in the absence of specific target recognition. In contrast, we find that postsynaptic compartment assembly depends on the prior presence of a mature presynaptic ending.
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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 | 0.000 |
| 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".