Electroporation as a Method to Induce Myofiber Regeneration and Increase the Engraftment of Myogenic Cells in Skeletal Muscles of Primates
Bibliographic record
Abstract
Engraftment of intramuscularly transplanted myogenic cells in mice can be optimized after induction of massive myofiber damage that triggers myofiber regeneration and recruitment of grafted cells; this generally involves either myotoxin injection or cryodamage. There are no effective methods to produce a similar process in the muscles of large mammals such as primates. In this study, we tested the use of intramuscular electroporation for this purpose in 11 macaques. The test sites were 1 cm of skeletal muscle. Each site was treated with 3 penetrations of a 2-needle electrode with 1 cm spacing, applying 3 pulses of 400 V/cm, for a duration of 5 milliseconds and a delay of 200 milliseconds during each penetration. Transplantation of β-galactosidase-labeled myoblasts was done in electroporated and nonelectroporated sites. Electroporation induced massive myofiber necrosis that was followed by efficient muscle regeneration. Myoblast engraftment was substantially increased in electroporated compared with nonelectroporated sites. This suggests that electroporation may be a useful tool to study muscle regeneration in primates and other large mammals and as a method for increasing the engraftment of myoblasts and other myogenic cells in intramuscular transplantation.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".