NanoLC-MS/MS Analyses of Urinary Desmosine, Hydroxylysylpyridinoline and Lysylpyridinoline as Biomarkers for Chronic Graft-versus-Host Disease
Bibliographic record
Abstract
Chronic graft-versus-host disease (cGVHD) is a common and potentially lethal complication of allogeneic hematopoietic stem cell transplantation (HSCT). cGVHD as well as the transplant procedure itself (chemotherapy with or without radiotherapy) can lead to the degradation of connective tissue components such as elastin and collagen. The catabolism of these structural proteins releases desmosine (DES), lysylpyridinoline (LP), hydroxylysylpyridonoline (HP), and related pyridinium-based cross-linkers analogues that could represent potential biomarkers for cGVHD. This study reports the development of a sensitive liquid chromatography/tandem mass spectrometry method for the simultaneous analysis of N-propyl derivatives of DES, HP, and LP. The concentrations of free and total forms of urinary DES, HP, and LP were determined using synthetic deuterated internal standards. This method enabled accurate quantitation of these pyridinium-based cross-linkers from as little as 100 microL of urine with detection limits of 0.03-0.10 ng/mL. These compounds were analyzed in urine samples from three groups of patients: (1) Healthy volunteers, (2) Autologous HSCT recipients (who cannot develop cGVHD), and (3) Allogeneic HSCT recipients at onset of cGHVD. These analyses revealed that the urinary concentrations of DES, HP, and LP in the autologous recipients were greater or equal to the cGVHD group although both groups showed marked increase in the levels of these compounds compared to healthy individuals. These results suggest that the chemotherapy treatment has significant effects on the turnover of elastin and collagen, and that these biomarkers could be effective during prospective analyses to determine the onset of cGVHD.
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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 | 0.000 |
| 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".