Determination of IGF-1 and IGF-2, their degradation products and synthetic analogues in urine by LC-MS/MS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Peptide analysis in doping controls by means of nano-UPLC coupled high resolution/high mass accuracy mass spectrometry provides the state-of-the-art technique in modern sports drug testing. The present study describes a recent application of this technique for the qualitative determination of different urinary insulin-like growth factor (IGF) related peptides. After simultaneous isolation by solid phase extraction and magnetic particle-based immunoaffinity purification, target analytes (IGF-1, IGF-2, Des1-3-IGF-1, R(3)-IGF-1 and longR(3)-IGF-1) were separated by nano-liquid chromatography prior to mass spectrometric detection. Endogenously produced IGF-1 and IGF-2, as well as the degradation product Des1-3-IGF-1, were frequently detected in urine samples from healthy volunteers in a concentration range of 20-400 pg mL(-1). The impact of IGF binding proteins (IGFBPs), being also present in urine, was potentially estimated by an additional ultrafiltration step in the sample preparation procedure. The synthetic analogue longR(3)-IGF-1, which is assumed to be subject to misuse by cheating athletes, was also analysed and detected in fortified urine samples. Besides the intact molecule, an N-terminally truncated degradation product Des1-10-longR(3)-IGF-1 was identified as the more stable target for doping controls using urine samples. The method was validated for qualitative purposes considering the parameters specificity, limit of detection (20-50 pg mL(-1)), recovery (10-35%), precision (<20%), linearity, robustness and stability.
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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) | 0.000 | 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) | 0.000 | 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 it