Scanning Electron Microscopy of Elastic Networks from the Bifurcation Region of Guinea Pig Carotid Arteries
Bibliographic record
Abstract
We isolated the elastic network from the bifurcation region of guinea pig carotid arteries by treatment with hot alkali and examined its adventitial and adluminal components by SEM. The thickness of networks from common and external carotid arteries averaged 87.5 µm (±6.9 SD) and from the carotid sinus averaged 46.8 µm (±2.4 SD). The networks consisted of a mesh of elastic tissue that became a continuous sheet, 2 µm thick, which formed the internal elastic lamina (IEL). The IEL was fenestrated; the perforations varied in number among the vessels (occipital > carotid sinus > common = external carotid), and some were spanned by delicate elastic fibers. The IEL’s adluminal surface was a smooth membranous sheet, which in some specimens bore unidirectional loose fibers, or was composed of tightly fused bundles of uni- or multidirectional fibers. The interior region of the cranial carotid sinus contained unique blister-like structures and dense clusters of fenestrations, together with a honeycomb-like mesh near the ascending pharyngeal artery. The outer, adventitial elastic layer consisted of a network of loose elastic fibers that were fused with the inner layers. We conclude that the structural differences noted among the common and external carotid arteries and carotid sinus are related to the sinus’s unique pressure-sensing functions.
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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) | 0.002 | 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".