Visualization of synaptic markers in the optic neuropils ofDrosophila using a new constrained deconvolution method
Bibliographic record
Abstract
The fruitfly Drosophila melanogaster offers compelling genetic advantages for the analysis of its nervous system, but cell size precludes immunocytochemical analysis of wild-type structure and mutant phenotypes beyond the level of neuronal arborizations. For many antibodies, especially when immunoelectron microscopy is not feasible, it would therefore be desirable to extend the resolution limit of confocal microscopy as far as possible. Because high-resolution confocal microscopy suffers from considerable blurring, so-called deconvolution algorithms are needed to remove, at least partially, the blur introduced by the microscope and by the specimen itself. Here, we present the establishment and application of a new deconvolution method to visualize synaptic markers in Drosophila optic neuropils at the resolution limit of light. We ascertained all necessary parameters experimentally and verified them by deconvolving injected fluorescent microspheres in immunostained optic lobe tissue. The resulting deconvolution method was used to analyze colocalization between the synaptic vesicle marker neuronal synaptobrevin and synaptic and putative synaptic markers in photoreceptor terminals. We report differential localization of these near the resolution limit of light, which could not be distinguished without deconvolution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".