Age of Collagen in Intracranial Saccular Aneurysms
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The chronological development and natural history of cerebral aneurysms (CAs) remain incompletely understood. We used (14)C birth dating of a main constituent of CAs, that is, collagen type I, as an indicator for biosynthesis and turnover of collagen in CAs in relation to human cerebral arteries to investigate this further. METHODS: Forty-six ruptured and unruptured CA samples from 43 patients and 10 cadaveric human cerebral arteries were obtained. The age of collagen, extracted and purified from excised CAs, was estimated using (14)C birth dating and correlated with CA and patient characteristics, including the history of risk factors associated with atherosclerosis and potentially aneurysm growth and rupture. RESULTS: Nearly all CA samples contained collagen type I, which was <5 years old, irrespective of patient age, aneurysm size, morphology, or rupture status. However, CAs from patients with a history of risk factors (smoking or hypertension) contained significantly younger collagen than CAs from patients with no risk factors (mean, 1.6±1.2 versus 3.9±3.3 years, respectively; P=0.012). CAs and cerebral arteries did not share a dominant structural protein, such as collagen type I, which would allow comparison of their collagen turnover. CONCLUSIONS: The abundant amount of relatively young collagen type I in CAs suggests that there is an ongoing collagen remodeling in aneurysms, which is significantly more rapid in patients with risk factors. These findings challenge the concept that CAs are present for decades and that they undergo only sporadic episodes of structural change.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".