Examination of the anabolic activity and mechanisms of action of the combination of Diosgenin and Ecdysterone in C2C12 myotubes
Bibliographic record
Abstract
Plant steroids such as ecdysterone (ECDY) or diosgenin (DIO) have been associated with anabolic and performance-enhancing effects for years. However, the molecular mechanisms have not yet been extensively studied in skeletal muscle cells. Consequently, the anabolic activity and associated molecular mechanisms of ECDY and DIO alone and in combination were investigated in C2C12 myotubes. Dose-dependent effects of both compounds on myotube diameter, mRNA expression of IGF-1 and PI3KR1 as well as expression of myosin heavy chain (MHC) proteins were analyzed in differentiated C2C12 cells. In addition, the binding affinities to androgen and estrogen receptors were analyzed. Treatment with ECDY and DIO significantly induced hypertrophy of C2C12 myotubes. Partially additive effects were observed. This is supported by the mRNA expression of IGF-1 and PI3KR1 as well as in the expression of MHC. However, no clear statement can be made regarding which combination has the strongest additive effects. Besides the results suggest that, in contrast to ECDY, DIO has antiandrogenic effects and bind on AR. Consequently, it indicate that two different mechanisms of action are activated in ECDY and DIO combinations. However, this must be confirmed in further cell cultures studies and human interventions concerning anti-doping regulations.
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) | 0.001 | 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 | 0.000 |
| 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".