Comparison of Fenestrations in Internal Elastic Laminae of Canine Thoracic and Abdominal Aortas
Bibliographic record
Abstract
All non-elastin tissue was removed from canine aortas by placing them in 0.1 N NaOH at 75 degrees C for varying periods of time. The segments of aorta were weighed in a Mettler Chemical Balance at intervals. In 10 dogs the average weight of the thoracic aorta was 5.01 +/- 0.388 (SE) g while that of the abdominal aorta was 3.08 +/- 0.346 g. After digestion, the thoracic aorta weighed 3.34 +/- 0.0275 g and the abdominal aorta 0.85 +/- 0.085 g. Thus, the elastin makes up 67% of the thoracic aorta but only 28% of the abdominal aorta. These are equivalent to 0.334 g/kg body weight for the thoracic aorta and 0.224 g/kg body weight for the abdominal aorta. The values were always stable between 5 and 7 h and usually between 3 and 12 h. Aortic elastin was obtained from 5 dogs after 5-7 h of digestion and prepared for analysis by scanning electron microscopy. The dimensions of the fenestrations in the internal elastic laminae were quantified as described previously. The lower abdominal aorta had the largest holes (2.227 +/- 0.048 micron), and the upper thoracic aorta the smallest holes (0.954 +/- 0.032 micron). There was no significant difference in the size of the fenestrations along the thoracic aorta, but those in the lower abdominal aorta were larger than those in the upper abdominal aorta. The possible significance of the fenestrations in the genesis of aortic disease is discussed briefly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".