Endothelial Glycocalyx Degradation in Critical Illness and Injury
Bibliographic record
Abstract
The endothelial glycocalyx is a gel-like layer on the luminal side of blood vessels that is composed of glycosaminoglycans and the proteins that tether them to the plasma membrane. Interest in its properties and function has grown, particularly in the last decade, as its importance to endothelial barrier function has come to light. Endothelial glycocalyx studies have revealed that many critical illnesses result in its degradation or removal, contributing to endothelial dysfunction and barrier break-down. Loss of the endothelial glycocalyx facilitates the direct access of immune cells and deleterious agents (e.g., proteases and reactive oxygen species) to the endothelium, that can then further endothelial cell injury and dysfunction leading to complications such as edema, and thrombosis. Here, we briefly describe the endothelial glycocalyx and the primary components thought to be directly responsible for its degradation. We review recent literature relevant to glycocalyx damage in several critical illnesses (sepsis, COVID-19, trauma and diabetes) that share inflammation as a common denominator with actions by several common agents (hyaluronidases, proteases, reactive oxygen species, etc.). Finally, we briefly cover strategies and therapies that show promise in protecting or helping to rebuild the endothelial glycocalyx such as steroids, protease inhibitors, anticoagulants and resuscitation strategies.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".