Transcriptomic biomarkers of altered erythropoiesis to detect autologous blood transfusion
Bibliographic record
Abstract
Autologous blood transfusion is a powerful means of improving performance and remains one of the most challenging methods to detect. Recent investigations have identified 3 candidate reticulocytes genes whose expression was significantly influenced by blood transfusion. Using quantitative reverse transcription polymerase chain reaction as an alternative quantitative method, the present study supports that delta-aminolevulinate synthase 2 (ALAS2), carbonic anhydrase (CA1), and solute carrier family 4 member 1 (SLC4A1) genes are down-regulated post-transfusion. The expression of these genes exhibited stronger correlation with immature reticulocyte fraction than with reticulocytes percentage. Moreover, the repression of reticulocytes' gene expression was more pronounced than the diminution of immature reticulocyte fraction and reticulocyte percentage following blood transfusion. It suggests that the 3 candidate genes are reliable predictors of bone marrow's response to blood transfusion and that they represent potential biomarkers for the detection of this method prohibited in sports.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".