Glycosaminoglycans and proteoglycans: Overlooked entities?
Bibliographic record
Abstract
Background: By virtue of their high net negative charge, glycosaminoglycans and proteoglycans play pivotal roles in biologic processes such as cell-cell and cell-matrix interactions, sequestration of growth factors, activation of chemokines and cytokines, and permselectivity of basement membranes. Methods: The present article reviews the putative roles of glycosaminoglycans and proteoglycans in the peritoneal cavity during normal peritoneal homeostasis and chronic inflammation, the latter induced by constant exposure of the peritoneum to non-physiologic peritoneal dialysis (PD) solutions. Results: Glycosaminoglycans have been identified in the mesothelial glycocalyx, a slippery, non-adhesive layer that protects the peritoneal membrane from abrasion and infection. Dermatan sulfate proteoglycans can neutralize the activity of transforming growth factor β1 and can thus play an essential role in modulating peritoneal fibrosis. Heparan sulfate proteoglycans play a crucial role in the sequestration of growth factors; they also modulate selective permeability of proteins across the peritoneal cavity. Reduced expression of perlecan, a heparan sulfate proteoglycan of the basement membrane, is observed in peritoneal biopsies obtained from established PD patients, consequent to prolonged exposure to the elevated glucose concentrations in conventional PD solutions. Supplementation of PD fluids with glycosaminoglycans has been shown to be beneficial to both the structural and functional integrity of the peritoneum. Conclusions: Recent advances in the field of glycobiology have revealed a multitude of biologic processes that are controlled or influenced by glycosaminoglycans and proteoglycans. Altered synthesis of these macromolecules during PD has serious implications for the peritoneal transport of proteins, host defense, wound healing, inflammation, and fibrosis. Copyright © 2007 International Society for Peritoneal Dialysis. Printed in Canada. All rights reserved.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".