Skeletal muscle regeneration is attenuated with repression of the cytoskeletal protein, Xin
Bibliographic record
Abstract
Xin, an actin binding protein, has been implicated in the regulation of satellite cell function and is hypothesized to be essential for skeletal muscle regeneration following injury. To investigate the role of Xin during skeletal muscle regeneration, we inhibited Xin expression using a Xin shRNA adenoviral (XinAd) injection into the right tibialis anterior (TA) of 6 week old male mice, while the left TA served as a control receiving an injection of the virus lacking Xin shRNA. Injury was induced in both TAs 4 days later via cardiotoxin injection. At 5 days post‐injury, muscle fiber area was significantly smaller (Control: 1007 ± 62 μm 2 ; Xin Ad: 785± 73 μm 2 ) and the number of centrally located nuclei per muscle fiber was significantly increased (134 ± 9%) in XinAd regenerating muscle compared to control. These deficits in fiber area (Control: 3136±278 μm 2 ;Xin Ad: 2273 ±167 μm 2 ) and centrally located nuclei (137 ± 9% of control) in the XinAd muscles persisted to 14 days regeneration suggesting that the regenerating muscle injected with XinAd is less mature at 5 and 14 days of regeneration. A significant increase in apoptosis (TUNEL) at 5 and 14 days of regeneration (126±6%; 141±12% of control) was observed in the XinAd TA compared to control. These data support the hypothesis that Xin is important for muscle regeneration and future work will investigate the roles of Xin on satellite cell activation and maturation.
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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 | 0.001 |
| 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".