In vivo <sup>1</sup>H MRS of human gallbladder bile in understanding the pathophysiology of primary sclerosing cholangitis (PSC): Immune‐mediated disease versus bile acid‐induced injury
Bibliographic record
Abstract
Primary sclerosing cholangitis (PSC) has been considered to be either an “autoimmune disease” or a “bile acid‐induced injury.” In vitro MRS studies on PSC patients have limitations due to the contamination of bile with contrast agent (commonly administered during endoscopic retrograde cholangiopancreatography) and/or the use of patient cohorts with other diseases as controls. The objective of this study was to quantify biliary metabolites using in vivo 1H MRS and gain insight into the pathogenesis of PSC. Biliary metabolites in 10 PSC patients and 14 healthy controls were quantified in vivo using 1H MRS on a 3 T MR scanner. The concentrations of total bile acids plus cholesterol, glycine‐conjugated bile acids, taurine‐conjugated bile acids, and choline‐containing phospholipids (chol‐PLs) were compared between the two groups. There were statistically significant decreases in the levels of the above mentioned biliary metabolites in the PSC patients compared with controls. The reduction in bile acid secretion in bile of PSC patients indicates accumulation of bile acids in hepatocytes. Moreover, reduction in the levels of chol‐PLs in bile may increase the toxic effects of bile acids. Our findings suggest that the bile duct injury in PSC patients is most likely due to “bile acid‐induced injury.”
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".