An <scp>MMP</scp>‐degraded and cross‐linked fragment of type <scp>III</scp> collagen as a non‐invasive biomarker of hepatic fibrosis resolution
Bibliographic record
Abstract
BACKGROUND AND AIMS: Liver fibrosis results from a prolonged wound healing response to continued injury with excessive production of extracellular proteins. In patients with chronic liver disease, the monitoring of liver fibrosis dynamics is of high interest. Whilst markers of fibrogenesis exist, markers of hepatic fibrosis resolution remain an unmet clinical need. Thus, we sought to develop an assay quantifying a circulating proteolytic fragment of cross-linked type III collagen as a biomarker of fibrolysis, testing its utility in two clinical cohorts of liver fibrosis of distinct aetiology and regressing endotype METHODS: We used a monoclonal antibody targeting the C-telopeptide of type III collagen following C-proteinase cleavage to develop and validate a neo-epitope-specific enzyme-linked immunosorbent assay (CTX-III). A potential fibrosis resolution marker, CTX-III, was measured in two clinical cohorts of patients with obesity-associated non-alcoholic fatty liver disease undergoing bariatric surgery or hepatitis C virus infection from a clinical trial study evaluating the anti-fibrotic effect of farglitazar. RESULTS: CTX-III was robust and specific for the targeted neo-epitope with good reproducibility in EDTA plasma. We assessed type III collagen remodelling using a panel of biomarkers, including a type III collagen formation marker (PRO-C3), degradation (C3M), and CTX-III (fibrolysis). Net fibrolysis was increased in patients with non-alcoholic fatty liver disease following bariatric surgery (p < .001). Moreover, net fibrolysis identified spontaneous fibrotic regressors from stable and progressors (p < .05 and p < .001) among hepatitis C virus infection patients. CONCLUSION: Circulating CTX-III as a marker of fibrolysis indicates the biomarker's beneficial use in assessing hepatic fibrosis resolution.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".