Investigating relationships between arterial stiffness and collagen turnover in humans
Bibliographic record
Abstract
Understanding the factors regulating changes in vascular structure may assist in designing strategies for decreasing the development and progression of cardiovascular disease. Previous research has shown links between various markers of collagen turnover and arterial stiffness in clinical populations (McNulty, 2006 & Chatzikyriakou, 2008). The purpose of this study was to investigate the relationship between functional assessments and blood markers of arterial wall structure. Arterial stiffness and markers of collagen turnover were assessed in 20 overweight women, 20 elderly healthy men, 23 individuals with coronary artery disease, 16 individuals with spinal cord injury and 10 young healthy men. Carotid artery stiffness was determined through assessment of common carotid artery distensibility with simultaneous B‐mode ultrasound imaging and applanation tonometry. Fasting venous blood samples were analyzed for serum levels of pro‐collagen type I (PIP) and cross‐linked telopeptide of collagen type I (CTX); markers of type I collagen synthesis and degradation, respectively. There was a significant positive relationship observed between CTX and carotid artery distensibility (R = 0.330, p = 0.001) and a weak but significant inverse relationship (R = −0.224, p = 0.034) observed between carotid artery distensibility and type I collagen turnover, expressed as a ratio of PIP to CTX. These findings suggest a link exists between type I collagen turnover and central arterial distensibility, however this relationship appears to be opposite to that previous observed in the literature in older hypertensive individuals (McNulty, 2006). Funded by Canadian Institute of Health Research, Natural Sciences and Engineering Research Council, Innovation Center for US Dairy, Dairy Farmers of Canada and the Ontario Neurotrauma Foundation.
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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 | 0.001 | 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 | 0.000 |
| 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".