Innervation of cranial muscles requires Mllt11/Af1q/Tcf7c function during trigeminal ganglion development
Bibliographic record
Abstract
The development of cranial nerves, including the trigeminal nerve, and the formation of neuromuscular junctions (NMJs) are crucial processes for craniofacial motor function. Mllt11/Af1q/Tcf7c (henceforth Mllt11), a novel type of cytoskeletal-interacting protein, has been implicated in neuronal migration and neuritogenesis during central nervous system development. However, its role in peripheral nerve development and NMJ formation remains poorly understood. This study investigates the function of Mllt11 during trigeminal ganglion development and its impact on motor innervation of the masseter muscle. We report Mllt11 expression in the developing trigeminal ganglia, suggesting a potential role in cranial nerve development. Using a conditional knockout mouse model to delete Mllt11 in Wnt1-expressing neural crest cells, we assessed trigeminal ganglion development and innervation of the masseter muscle in the jaw. Surprisingly, we find that Mllt11 loss does not affect the initial formation of the trigeminal ganglion but disrupts its cellular composition, with a reduction in the ratio of neural crest-derived Sox10+ cells relative to placode-derived Isl1/2+ cells. Furthermore, our study demonstrates that conditional Mllt11 knockout leads to reduction of neurofilament density and NMJs within the masseter muscle, indicating altered trigeminal motor innervation. Our findings show that Mllt11 regulates the cellular composition of the trigeminal ganglion and is essential for proper trigeminal motor innervation in the masseter muscle.
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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 | 0.001 | 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".