Proteoglycan and ADAMTS expression during fibrogenic remodeling in the liver
Bibliographic record
Abstract
Liver fibrosis and end stage cirrhosis are leading causes of morbidity and mortality worldwide. Changes in the structure and composition of the proteoglycan rich extracellular matrix (ECM) are known to play a role in these processes, though these changes are incompletely understood and characterized. An increased understanding of these events may one day allow early recognition and targeted therapy, leading to the reversibility of liver fibrosis as a future clinical outcome. In other tissues, proteoglycans including versican are key components of fibrotic ECM that modulates cellular functions. The ADAMTS enzymes are now known to cleave versican and other proteoglycans in a manner previously ascribed to the MMPs. This work focuses on the role of the hepatic stellate cell in synthesizing a proteoglycan rich fibroproliferative ECM in vitro and in vivo. We have investigated several candidate proteoglycans, including versican, along with several candidate ADAMTS enzymes, in two models of liver fibrosis. Using qPCR and confocal microscopy, we report a more thorough expression profile for these important ECM constituents than has previously been described. These findings underscore the need to better characterize the fibroproliferative liver ECM. Grant Funding Source : Northern Medical Program
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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".