Synthesis, characterisation, and mass spectrometric detection of a pegylated EPO‐mimetic peptide for sports drug testing purposes
Bibliographic record
Abstract
Erythropoietin (EPO) and other erythropoiesis-stimulating agents possess a high misuse potential in elite sport due to their ability to increase the oxygen transport capacity, which plays a vital role in enhancing endurance performance. Currently, a new generation of EPO-mimetic peptides is under development from which peginesatide (also referred to as Hematide™), a pegylated homodimeric peptide of approximately 45 kDa with no structural relationship to erythropoietin, is the most advanced drug candidate undergoing phase-III clinical trials. Since preventive doping research aims at the development of detection methods before a drug receives clinical approval, a selective and sensitive assay has to be established knowing that conventional doping control assays for EPO will not succeed in detecting peginesatide. Thus, a pegylated EPO-mimetic peptide simulating the structure and properties of the lead drug candidate peginesatide was synthesised as a model compound for this new class of emerging drugs and characterised by means of gel electrophoresis, matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry, as well as liquid chromatography/electrospray ionisation tandem mass spectrometry (LC/ESI-MS/MS) after proteolytic digestion. Based on these results, a mass spectrometric detection method of the product in plasma was developed targeting a pentapeptide fragment after protein precipitation and subtilisin digestion. Its fitness for purpose was evaluated by the determination of selected method characteristics focusing particularly on specificity, recovery (ca. 60%), and limit of detection (1 ng/mL).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".