Analysis of Potential Gene Doping Preparations for Transgenic DNA in the Context of Sports Drug Testing Programs
Bibliographic record
Abstract
Gene doping has been classified as a prohibited method by the World Anti-Doping Agency (WADA) and the International Olympic Committee (IOC) for over two decades. As gene therapeutic approaches improve and, concomitantly, safety concerns regarding clinical applications decline, apprehensions about their illicit use in elite sports continue to grow. Two products available via Internet-based providers and advertised as EPO-gene- and IGF1-gene-containing materials were analyzed for the presence of potential gene doping agents using a newly developed analytical approach, allowing for the detection of transgenic DNA corresponding to seven potential targets (EPO, FST, GH1, MSTN (Propeptide), IGF1, VEGFA, and VEGFD). Panel detection was based on a 20-plex polymerase chain reaction (PCR) followed by a single base extension (SBE) reaction and subsequent SBE product analyses via matrix-assisted time-of-flight laser desorption/ionization mass spectrometry (MALDI-TOF MS). Extracts of both products were found to contain transgenic EPO-DNA, while transgenic DNA for IGF-1 was not detected. The results were confirmed using SYBR Green qPCR with primer sets directed against EPO and IGF1 cDNA, and the CMV promotor sequence. In this case study, the detection of authentic (whilst low concentrated) transgenes, potentially intended for gene doping practices in readily available products, is reported for the first time.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".