Altered erythroid‐related miRNA levels as a possible novel biomarker for detection of autologous blood transfusion misuse in sport
Bibliographic record
Abstract
BACKGROUND: Autologous blood transfusion (ABT) is a performance-enhancing method prohibited in sport; its detection is a key issue in the field of anti-doping. Among novel markers enabling ABT detection, microRNAs (miRNAs) might be considered a promising analytical tool. STUDY DESIGN AND METHODS: We studied the changes of erythroid-related microRNAs following ABT, to identify novel biomarkers. Fifteen healthy trained males were studied from a population of 24 subjects, enrolled and randomized into a Transfusion (T) and a Control (C) group. Seriated blood samples were obtained in the T group before and after the two ABT procedures (withdrawal, with blood refrigerated or cryopreserved, and reinfusion), and in the C group at the same time points. Traditional hematological parameters were assessed. Samples were tested by microarray analysis of a pre-identified set of erythroid-related miRNAs. RESULTS: Hematological parameters showed moderate changes only in the T group, particularly following blood withdrawal. Among erythroid-related miRNAs tested, following ABT a pool of 7 miRNAs associated with fetal hemoglobin and regulating transcriptional repressors of gamma-globin gene was found stable in C and differently expressed in three out of six T subjects in the completed phase of ABT, independently from blood conservation. Particularly, two or more erythropoiesis-related miRNAs within the shortlist constituted of miR-126-3p, miR-144-3p, miR-191-3p, miR-197-3p, miR-486-3p, miR-486-5p, and miR-92a-3p were significantly upregulated in T subjects after reinfusion, with a person-to-person variability but with congruent changes. CONCLUSIONS: This study describes a signature of potential interest for ABT detection in sports, based on the analysis of miRNAs associated with erythroid features.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".