Quantitative hepatic phosphorus-31 magnetic resonance spectroscopy in compensated and decompensated cirrhosis
Bibliographic record
Abstract
Few studies have examined the physiological/biochemical status of hepatocytes in patients with compensated and decompensated cirrhosis in situ. Phosphorus-31 magnetic resonance spectroscopy ((31)P MRS) is a noninvasive technique that permits direct assessments of tissue bioenergetics and phospholipid metabolism. Quantitative (31)P MRS was employed to document differences in the hepatic metabolite concentrations among patients with compensated and decompensated cirrhosis as well as healthy controls. All MRS examinations were performed on a 1.5-T General Electric Signa whole body scanner. The concentration of hepatic phosphorylated metabolites among patients with compensated cirrhosis (n = 7) was similar to that among healthy controls (n = 8). However, patients with decompensated cirrhosis (n = 6) had significantly lower levels of hepatic ATP compared with patients with compensated cirrhosis and healthy controls (P < 0.02 and P < 0.009, respectively) and a higher phosphomonoester/phosphodiester ratio than controls (P < 0.003). The results of this study indicate that metabolic disturbances in hepatic energy and phospholipid metabolism exist in patients with decompensated cirrhosis that are not present in patients with compensated cirrhosis or healthy controls. These findings provide new insights into the pathophysiology of hepatic decompensation.
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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 | 0.002 |
| 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".