Effects of electrical stimulation in C2C12 muscle constructs
Bibliographic record
Abstract
Electrical stimulation affects the deposition of extracellular matrices and cellular differentiation. Type I collagen is one of the most abundant extracellular matrix proteins; however, not much is known about the effects of electrical stimulation on collagen type I deposition in C2C12 cells. Thus, we studied the effects of electrical voltage and stimulation frequency in 3D cultured C2C12 muscle cells in terms of metabolic activity, type I collagen deposition and cell morphology. Electrically excitable C2C12 muscle cells were seeded in collagen scaffolds and stimulated with rectangular signals of voltage (2, 5, 7 V) and frequency (1, 2 Hz), using parallel carbon electrodes spaced 1 cm apart. Metabolic activity was quantified by the glucose:lactate concentration ratio in the medium. Apoptotic activity was assessed by TUNEL staining and changes in collagen deposition were identified by immunohistology. The ultrastructure of the tissue was examined by TEM. Glucose and lactate analysis indicated that all groups had similar metabolic activity. TUNEL stain showed no significant difference in apoptotic damage induced by electrical stimulation compared to the control. Samples stimulated at 2 Hz exhibited reduced collagen deposition compared to the control and 1 Hz stimulated samples. Muscle-protein marker desmin was highly expressed in constructs stimulated with 1 Hz/5 V sample. TEM revealed that the stimulated samples developed highly organized sarcomeres, which coincided with improved contractile properties in the 1 Hz/5 V- and 2 Hz/5 V-stimulated groups. Our data implicate that a specific electrical frequency may modulate type I collagen accumulation and a specific voltage may affect the differentiation of muscle sarcomeres in excitable cells.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| 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".