Connexin 39.9 Protein Is Necessary for Coordinated Activation of Slow-twitch Muscle and Normal Behavior in Zebrafish
Bibliographic record
Abstract
In many tissues and organs, connexin proteins assemble between neighboring cells to form gap junctions. These gap junctions facilitate direct intercellular communication between adjoining cells, allowing for the transmission of both chemical and electrical signals. In rodents, gap junctions are found in differentiating myoblasts and are important for myogenesis. Although gap junctions were once believed to be absent from differentiated skeletal muscle in mammals, recent studies in teleosts revealed that differentiated muscle does express connexins and is electrically coupled, at least at the larval stage. These findings raised questions regarding the functional significance of gap junctions in differentiated muscle. Our analysis of gap junctions in muscle began with the isolation of a zebrafish motor mutant that displayed weak coiling at day 1 of development, a behavior known to be driven by slow-twitch muscle (slow muscle). We identified a missense mutation in the gene encoding Connexin 39.9. In situ hybridization found connexin 39.9 to be expressed by slow muscle. Paired muscle recordings uncovered that wild-type slow muscles are electrically coupled, whereas mutant slow muscles are not. The further examination of cellular activity revealed aberrant, arrhythmic touch-evoked Ca(2+) transients in mutant slow muscle and a reduction in the number of muscle fibers contracting in response to touch in mutants. These results indicate that Connexin 39.9 facilitates the spreading of neuronal inputs, which is irregular during motor development, beyond the muscle cells and that gap junctions play an essential role in the efficient recruitment of slow muscle fibers.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".