Panx1b Modulates the Luminance Response and Direction of Locomotion in the Zebrafish
Bibliographic record
Abstract
Pannexin1 (Panx1) can form ATP-permeable channels that play roles in the physiology of the visual system. In the zebrafish two ohnologs of Panx1, Panx1a and Panx1b, have unique and shared channel properties and tissue expression patterns. Panx1a channels are located in horizontal cells of the outer retina and modulate light decrement detection through an ATP/pH-dependent mechanisms and adenosine/dopamine signaling. Here, we decipher how the strategic localization of Panx1b channels in the inner retina and ganglion cell layer modulates visually evoked motor behavior. We describe a panx1b knockout model generated by TALEN technology. The RNA-seq analysis of 6 days post-fertilization larvae is confirmed by real-time PCR and paired with testing of locomotion behaviors by visual motor and optomotor response tests. We show that the loss of Panx1b channels disrupts the retinal response to an abrupt loss of illumination and it decreases the larval ability to follow leftward direction of locomotion in low light conditions. We concluded that the loss of Panx1b channels compromises the final output of luminance as well as motion detection. The Panx1b protein also emerges as a modulator of the circadian clock system. The disruption of the circadian clock system in mutants suggests that Panx1b could participate in non-image forming processes in the inner retina.
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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) | 0.002 | 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".