Bibliographic record
Abstract
Preservation of vascular glycocalyx has proven problematic. Complex carbohydrates that constitute most of glycocalyx are disrupted by physiological stresses and aqueous fixatives. This study found that a non‐aqueous, osmium‐based fixative was superior to aqueous alternatives. Buffered aqueous fixative (2.5% glutaraldehyde in 0.05M sodium cacodylate, pH=7.3) was compared with a non‐aqueous fixative composed of 0.05% osmium tetroxide dissolved in fluorocarbon (FC‐72, 3M Co.). Samples of perfused rat aortas were processed for ultrastructural analysis immediately after initial fixation, or after various periods of time in non‐aqueous solvent, non‐aqueous fixative, buffered glutaraldehyde or aqueous buffer. Glycocalyx composed of mildly electron‐dense branching materials up to 600 nm tall was best preserved by non‐aqueous fixation followed by immediate processing. Post‐fixation delays for up to 24 hours in either non‐aqueous solvent or the solvent mixed with osmium did not substantially alter its appearance. However, the same samples, if post‐fixation‐treated with buffer solution or buffered glutaraldehyde for 30 minutes had no appreciable glycocalyx remaining. Non‐aqueous fixation offered the further advantage of exerting no osmotic forces, so there was no appreciable shrinking of cells or separation from connective tissues.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".