Identification of Serum Biomarkers in End Stage Liver Disease
Bibliographic record
Abstract
Background: Progressive fibrosis and cirrhosis, clinically presenting as end-stage liver disease are common outcomes in alcoholic hepatitis as well as non-alcoholic fatty liver disease(NAFLD). In these processes, a series of changes occurs in liver tissues leading to cell death, remodeling, fibrosis and regeneration. The aim of this study is to identify potential novel biomarkers for non-invasive diagnosis of cirrhosis due to alcoholic etiology or NAFLD. Methods: Serum from patients with biopsy proven end-stage liver disease of various etiologies, namely NAFLD(n=9), alcohol( n=5), and other end-stage liver diseases(n=6), who underwent liver transplant during the first six months of 2007 were utilized for retrospective analysis. Serum samples were also collected from a group of healthy volunteers (n=7). The samples were analysed using Luminex technology or ELISA for 27 biomarkers that are known to be involved in pathologic processes such as cell death, regeneration and fibrosis. Results: Of the 27 serum markers examined, 16 were elevated in the serum in all groups with end-stage liver diseases compared with the control group. They include adipokines, apoptosis and inflammatory mediators and growth factors. Interestingly, the serum of NAFLD patients showed significantly elevated HGF levels and trend towards increase in sFAS, TGF1, TNFR-1, TNFR-2 and leptin. The level of serum markers showed excellent correlation with each other indicating a complex interdependent pathogenetic mechanism. Conclusions: The data from this study indicate that a large number of serum markers are altered in end-stage liver diseases. A panel of such markers may potentially be useful in assessing advanced fibrosis and cirrhosis in patients with chronic end stage liver diseases.
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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 | 0.001 | 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) | 0.002 | 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".