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Record W7117358660 · doi:10.1002/cplu.202500493

Ryanodine‐1‐Calstabin Complex Stabilizers in Antidoping Research: Synthesis, Metabolism, and Characterization

2025· article· en· W7117358660 on OpenAlexfundno aff
Tristan Möller, Thomas Piper, Mario Thevis

Bibliographic record

VenueChemPlusChem · 2025
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersUniversität zu KölnWorld Anti-Doping AgencyGross Foundation
KeywordsSkeletal muscleDrugDopingLeakage (economics)In vitro

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.114
GPT teacher head0.379
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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