Talin, Vinculin and Nestin Expression in Orofacial Muscles of Dystrophin Deficient mdx Mice
Bibliographic record
Abstract
The activity of cytoskeletal proteins like talin, vinculin and nestin increases in muscle that regenerates. Little is known about their role or at least their expression in the process of regeneration in masticatory muscles of mdx mice, a model of Duchenne muscular dystrophy. To determine a potential role of cytoskeletal proteins in the regeneration process of mdx masticatory muscles, we examined the expression of talin 1, talin 2, vinculin and nestin in 100-day-old control and mdx mice using quantitative RT-PCR, Western blot analyses and histochemistry. The protein expression of talin 1, talin 2, nestin and vinculin in mdx muscles remained unchanged as compared with normal mice. However, in mdx masseter it was found a relative increase of nestin compared to controls. The protein expression of talin 1 and vinculin tended to be increased in mdx tongue and talin 2 to diminish in mdx masseter and temporal muscle. In mdx mice, we found significantly lower percentage of transcripts coding for nestin, talin 1, talin 2 and vinculin in masseter (p < 0.05) and temporal muscle (p < 0.001). In contrast, the mRNA expression of nestin was found to be increased in mdx tongue. Activated satellite cells, myoblasts and immature regenerated muscle fibres in mdx masseter and temporal revealed positive staining for nestin. The findings of the presented work suggest dystrophin-lack-associated changes in the expression of cytoskeletal proteins in mdx masticatory muscles could be compensatory for dystrophin absence. The expression of nestin may serve as an indicator for the regeneration in the orofacial muscles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".