Effects of Exercise on the Isoelectric Patterns of Erythropoietin
Bibliographic record
Abstract
OBJECTIVES: Recombinant erythropoietin has a strong impact on aerobic power and is therefore one of the most potent doping agents in endurance sports. The anti-doping control of this synthetic hormone relies on the detection, in the urine, of its isoelectric pattern, which differs from that of the corresponding natural hormone, the latter being typically more acidic than the former. However, a small number of natural urinary patterns, referred to as "atypical patterns," are less acidic than the dominant form. Based on anecdotal evidence, the occurrence of such patterns seems to be related to particular strenuous exercises. This study aimed to demonstrate this relation using a strenuous exercise protocol. DESIGN: Seven athletes took part in a training protocol including a series of supramaximal short-duration exercises. Urine and blood samples were collected throughout the protocols. SETTINGS: World Cycling Center, Aigle, Switzerland, and research laboratories. PARTICIPANTS: Seven top-level athletes (cyclists) were involved in this study. MAIN OUTCOME MEASURES: Erythropoietin (EPO) isoelectric patterns were obtained by submitting blood and urine samples to isoelectric focusing. Additional protein dosages were performed. RESULTS: Supramaximal short-duration exercises induced the transformation of typical urinary natural EPO patterns into atypical ones. None of the obtained atypical patterns fulfilled the 3 criteria mandatory for reporting an adverse analytical finding. Serum EPO patterns were not affected by the exercises that caused the transformation of urinary patterns. CONCLUSION: An exercise-induced transient renal dysfunction is proposed as a hypothetic explanation for these observations that rely on parallel investigations of proteinuria in the same samples.
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 | 0.000 | 0.001 |
| 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".