Ryanodine‐1‐Calstabin Complex Stabilizers in Antidoping Research: Synthesis, Metabolism, and Characterization
Bibliographic record
Abstract
Awareness of new potential doping agents and the proactive implementation of detection methods are key aspects of preventive antidoping research. Ryanodine receptor‐1‐calstabin complex stabilizers (RYR‐stabilizers) are a novel class of drug candidates for the treatment of various diseases associated with leaky Ca 2+ channels in the cardiac or skeletal muscle. Also, intense physical activity was shown to transiently cause leakage of skeletal muscle Ca 2+ channels, and RYR‐stabilizers have been shown to restore normal activity and, thus, increase endurance performance. Consequently, such compounds are relevant targets in doping controls, and to date, in particular, compounds S107, JTV‐519, ARM 036, and ARM 210 have been subject of antidoping research. In this study, ARM 036 and ARM 210 as well as the commercially available compounds S107 and JTV‐519 were synthesized using a multistep approach. Subsequently, all compounds were investigated concerning their in vitro metabolic behavior, and various metabolites were identified. Selected metabolites were then chemically synthesized for comprehensive structure confirmation. The findings of this study will contribute to routine doping control analytical programs and allow for improving existing detection methods.
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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 | 0.000 |
| 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".