Characterization of the hepatic endothelial glycocalyx of sialidase deficient mice in response to TNFα
Bibliographic record
Abstract
Evidence exists that components of the venular glycocalyx are shed and sialic acid is cleaved during inflammation. The objective of this study was to examine the role of sialidase in altering the hepatic glycocalyx. Female C57Bl/6 (WT) or sialidase deficient (B6Sm −/− ) mice were injected with 500 ng of TNFα or saline and the hepatic microcirculation examined by intravital confocal microscopy at 4h. Sugars present on the vasculature were detected by IV injection of FITC‐labeled Bandeiraea simplicifolia (BS‐1) (detects α‐ N ‐acetylgalactosamine and α‐galactose residues) or Texas‐Red‐labeled Lycopersicon esculentum (TL) (detects N ‐acetylglucosamine residues). Both lectins labeled the sinusoidal endothelium with no significant difference between the groups in the mean fluorescence intensity of the BS‐1 or TLlabeled glycocalyx. However, the saline treated WT mice had a thicker glycocalyx as compared to the saline treated B6Sm −/− mice (876 ±37 nm and 777 ± 18 nm, respectively) and TNFα stimulation resulted in a decrease of the glycocalyx thickness (772 ± 45 nm and 658 ± 23 nm, respectively). Our data supports the idea that components of the glycocalyx are shed during inflammation resulting in loss of glycocalyx height. Surprisingly, these sugars were expressed primarily on the sinusoids rather than venules and in contrast to other vascular beds, were not removed during TNFα‐induced hepatic inflammation.
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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 | 0.001 |
| 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".