Population density regulates <i>Drosophila</i> synaptic morphology in a Fasciclin‐II‐dependent manner
Bibliographic record
Abstract
Genetic analysis of the Drosophila larval neuromuscular junction has identified some of the key molecules that regulate synaptic plasticity. Among these molecules, the expression level of Fasciclin II (FasII), a homophilic cell adhesion molecule, is critically important for determining the final form of the neuromuscular junction. Genetic reduction of FasII expression by 50% yields more elaborate nerve terminals, while a greater reduction in expression, to 10% of wild-type, yields a substantial reduction in the nerve terminal morphology. Importantly, regulation of FasII expression seems to be the final output for several genetic manipulations that transform NMJ morphology. In an effort to understand the importance of this regulatory pathway in the normal animal, we have undertaken studies to identify environmental cues that might be important for initiating FasII-dependent changes in synaptic plasticity. Here we report on the relationship between larval population density and synaptic morphology, synaptic strength, and FasII levels. We raised Drosophila larvae under conditions of increasing population density and found an inverse exponential relationship between population density and the number of synaptic boutons, the number of branches, and the length of branches. We also observed population-dependent alteration in FasII levels, with lower densities having less FasII at the synapse. The correlation between density and morphological change was abrogated in larvae constitutively expressing FasII, and in wild-type larvae grown on soft culture medium. Together these data show that environmental cues can induce regulation of FasII. Interestingly, however, the quantal content of synaptic transmission was not different among the different population densities, suggesting that other factors contribute to maintaining synaptic strength at a defined level.
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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".