Aortic Dimensions, Biophysical Properties, and Plasma Biomarkers in Children and Adults with Marfan or Loeys-Dietz Syndrome
Bibliographic record
Abstract
BACKGROUND: Aortic dilation, stiffening, and dissection are common and potentially lethal complications of Marfan syndrome (MFS) and Loeys-Dietz syndrome (LDS), which involve abnormal transforming growth factor beta (TGF-β) signalling. The relation of aortic dimensions, stiffness, and biomarker levels is unknown. The objective of this study was to measure aortic dimensions, stiffness, TGF-β and matrix metalloproteinase (MMP) levels, and endothelial function in patients with MFS, and to compare TGF-β levels in patients with MFS receiving different therapeutic regimens. METHODS: This was a cohort study of 40 MFS and 4 LDS patients and 87 control participants. Aortic dimension and stiffness indexes, including pulse wave velocity (PWV), were measured using echocardiography and Doppler. Total and free TGF-β and MMP blood levels were measured using Quantikine (R&D Systems, Inc, Minneapolis, MN) and Quanterix (Billerica, MA) kits. Endothelial function was measured using brachial artery flow-mediated dilation. RESULTS: PWV was increased in patients with MFS. There were increased MMP-2 levels in those with MFS but no increase in free or total TGF-β or MMP-9 levels compared with control participants. There was no difference in TGF-β levels between MFS patients receiving no medications, angiotensin receptor blockers, and β-blockers. PWV correlated most strongly with age. Endothelial function showed premature gradual decline in patients with MFS. CONCLUSIONS: Despite the increased PWV, monitoring aortic stiffness or TGF-β levels would not be helpful in patients with MFS. TGF-β levels were not increased and the increased MMP-2 levels suggest consideration of a different therapeutic target.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".