Intravital multiphoton microscopy can model uptake and excretion of fluorescein in hepatic ischemia-reperfusion injury
Bibliographic record
Abstract
The liver is important in the biotransformation of various drugs, where hepatic transporters facilitate uptake and excretion. Ischemia-reperfusion (I/R) injury is a common occurrence in liver surgery, and the developing oxidative stress can lead to graft failure. We used intravital multiphoton tomography, with fluorescence lifetime imaging, to characterize metabolic damage associated with hepatic I/R injury and to model the distribution of fluorescein as a measure of liver function. In addition to measuring a significant increase in serum alanine transaminase levels, characteristic of hepatic I/R injury, a decrease in the averaged weighted lifetime of reduced nicotinamide adenine dinucleotide phosphate was observed, which can be attributed to a changed metabolic redox state of the hepatocytes. I/R injury was associated with delayed uptake and excretion of fluorescein and elevated area-under-the-curve within the hepatocytes compared to sham (i.e., untreated control) as visualized and modeled using images recorded by intravital multiphoton tomography. High-performance liquid chromatography analysis showed no differences in plasma or bile concentrations of fluorescein. Finally, altered fluorescein distribution was associated with acute changes in the expression of liver transport proteins. In summary, multiphoton intravital imaging is an effective approach to measure liver function and is more sensitive in contrasting the impact of I/R injury than measuring plasma and bile concentrations of fluorescein.
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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 | 0.000 |
| 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 | 0.000 |
| 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".