Detection of black market follistatin 344
Bibliographic record
Abstract
Follistatin, a myostatin-inhibiting protein, is prohibited according to chapter S4 of the "WADA 2019 List of Prohibited Substances and Methods". While currently no approved pharmaceutical formulations of follistatin are available, follistatin can be bought on the black market. Most of the products are labeled "follistatin 344" (FS344), a few "follistatin 315". A study on FS344 black market products was performed and an electrophoretic detection method for serum and urine developed. While only nine of the 17 tested products actually contained follistatin, in some of the others growth promoting peptides were found (e.g. MGF, GHRP-2). Surprisingly, all nine products contained His-tagged FS344 and a high degree of its oligomers. The detection method is based on immunomagnetic purification followed by SDS-PAGE and Western blotting with a monoclonal anti-His antibody. Alternatively, a monoclonal anti-follistatin antibody can be used. For immunoprecipitation (IP), a polyclonal anti-follistatin antibody is applied. An evaluation of suitable antibodies for IP and immunoblotting is also presented. Furthermore, practically all currently available follistatin standards were investigated. The detection limit of the method for black market FS344 in urine is ca 0.1 ng/mL for 10 mL. For a sample volume of 100 μL, an LOD of 5 ng/mL could be achieved for serum. Due to the presence of His-tags an unambiguous differentiation from endogenous follistatin is possible.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".