Agrin plays an organizing role in the formation of sympathetic synapses
Bibliographic record
Abstract
Agrin is a nerve-derived factor that directs neuromuscular synapse formation, however its role in regulating interneuronal synaptogenesis is less clear. Here, we examine agrin's role in synapse formation between cholinergic preganglionic axons and sympathetic neurons in the superior cervical ganglion (SCG) using agrin-deficient mice. In dissociated cultures of SCG neurons, we found a significant decrease in the number of synapses with aggregates of presynaptic synaptophysin and postsynaptic neuronal acetylcholine receptor among agrin-deficient neurons as compared to wild-type neurons. Moreover, the levels of pre- and postsynaptic markers at the residual synapses in agrin-deficient SCG cultures were also reduced, and these defects were rescued by adding recombinant neural agrin to the cultures. Similarly, we observed a decreased matching of pre- and postsynaptic markers in SCG of agrin-deficient embryos, reflecting a decrease in the number of differentiated synapses in vivo. Finally, in electrophysiological experiments, we found that paired-pulse depression was more pronounced and posttetanic potentiation was significantly greater in agrin-deficient ganglia, indicating that synaptic transmission is also defective. Together, these findings indicate that neural agrin plays an organizing role in the formation and/or differentiation of interneuronal, cholinergic synapses.
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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) | 0.000 | 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".