Photoreceptor Neurons Find New Synaptic Targets When Misdirected by Overexpressing<i>runt</i>in<i>Drosophila</i>
Bibliographic record
Abstract
As a neuron differentiates, it adopts a suite of features specific to its particular type. Fly photoreceptors are of two types: R1-R6, which innervate the first optic neuropile, the lamina; and R7-R8, which innervate the second, the medulla. Photoreceptors R1-R6 normally have large light-absorbing rhabdomeres, express Rhodopsin1, and have synaptic terminals that innervate the lamina. In Drosophila melanogaster, we used the yeast GAL4/UAS system to drive exogenous expression of the transcription factor Runt in subsets of photoreceptors, resulting in aberrant axonal pathfinding and, ultimately, incorrect targeting of R1-R6 synaptic terminals to the medulla, normally occupied by terminals from R7 and R8. Even when subsets of their normal R1-R6 photoreceptor inputs penetrate the lamina, to terminate in the medulla, normal target cells within the lamina persist and maintain expression of cell-specific markers. Some R1-R6 photoreceptors form reciprocal synaptic inputs with their normal lamina targets, whereas supernumerary terminals targeted to the medulla also form synapses. At both sites, tetrad synapses form, with four postsynaptic elements at each release site, the usual number in the lamina. In addition, the terminals at both sites are invaginated by profiles of glia, at organelles called capitate projections, which in the lamina are photoreceptor sites of vesicle endocytosis. The size and shape of the capitate projection heads are identical at both lamina and medulla sites, although those in the medulla are ectopic and receive invaginations from foreign glia. This uniformity indicates the cell-autonomous determination of the architecture of its synaptic organelles by the presynaptic photoreceptor terminal.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".