Localization pattern of dPNA:GFP at the Drosophila larval neuromuscular junctions
Bibliographic record
Abstract
Panels A-C: The D42-Gal4 driver transgene conducting the expression of UAS-dPNA:GFP transgene in larval motor neurons. The confocal images show the motorneuron boutons loaded with dPNA:GFP, in dissected-fixed preparations. Arrowheads indicate the distribution of GFP puncta from the motor neuron presynapse to adjacent areas, most likely the skeletal muscles, supporting previous observations that dPNA:GFP can migrate from the presynapse to post-synaptic partners. Marking the terminal with an anti-Fasciclin-II MAb (Helt G. 1997*) for example, will help delineate the bouton-boundaries more accurately. Similarly, immunolabeling the muscles and colocalization will help confirm the anterograde dPNA:GFP transfer at the larval NMJ. Scale bar in A is approximately 8 microns. Panels D-F: Expression of UAS-dPNA:GFP transgene by the dMEF2-Gal4 driver in the larval skeletal muscles (m). The filleted-preparations were immunlabled with an anti-BruchPilot (BRP) monoclonal antibody and AlexaFluor594 secondary antibody to localize the motor neuron presynaptic terminals. dPNA:GFP appears to migrate (arrow) from the post-synaptic muscle compartment to the segmental nerves innervating the muscle. GFP-puncta within the boutons (arrowheads) is almost absent. Is it the peripheral glial cells that ensheath the segmental nerves (but not the bouton terminals), that show preferential retrograde uptake of dPNA:GFP from the muscle? Colocalization of dPNA:GFP with a glia-specific marker, such as anti-gliotactin MAb (Auld et al. 1995), will be required to test this possibility. *Helt, G. (1997) Data visualization and gene discovery in Drosophila melanogaster, Appendix A. PhD thesis, University of California at Berkeley. Acknowledgements Thanks to Drs. Milton Charlton, Jeffrey Dason (Dept. of Physiology, Univ. of Toronto) and Dr. Greg Macleod (Dept. of Physiology, UTHSCSA, San Antonio) for the support and discussions.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".