Conjugated bile acids are elevated in severe calcific aortic valve stenosis
Bibliographic record
Abstract
Calcific aortic valve (AV) stenosis (CAVS) is a disease associated with significant morbidity and mortality in the aging population. Recently, bile acids have been shown to play a significant role in many disease processes, and untargeted metabolomic analyses of CAVS patient valves have shown a disrupted bile acid pathway. We aimed to understand the changes in human valvular bile acids in relation to CAVS severity. A total of 100 human AVs were collected from patients undergoing AV replacement surgery. Bile acids were quantified by ultrahigh performance liquid chromatography coupled to MS/MS. Patients with mild aortic stenosis (AS) showed a distinct valvular bile acid composition compared with moderate and severe AS groups, with five bile acids being significantly elevated in patients with moderate and severe AS. These included norcholic, nordeoxycholic, glycodeoxycholic, glycocholic, and taurodeoxycholic acid. When classified by calcification score, five species were significantly different between mild and severe AS groups; four bile acids were similar when stratified based on AS severity. Using K-means clustering, we were able to distinguish valve severity by their bile acid composition. Grouping bile acids by conjugation and by primary versus secondary revealed that conjugated primary and secondary bile acids were significantly increased in stenotic valves compared with the mild AS group. Conjugated bile acids are significantly elevated in the valvular tissue of patients with severe calcific AS. These findings suggest a potential link between liver and gut microbiome physiology and bile acid pathways in contributing to the pathophysiology of valvular stenosis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".