Analysis of NAD(P)H fluorescence components in cardiac myocytes from human biopsies: a new tool to improve diagnostics of rejection of transplanted patients
Bibliographic record
Abstract
Tissue autofluorescence is one of the most versatile non-invasive tools for mapping the metabolic state in living tissues. Increasing interest in the imaging and diagnosis of living cells and tissues, based on their intrinsic fluorescence rather than fluorescence labeling, is closely connected to the latest developments in high-performance spectroscopic and microscopic techniques. We investigate metabolic state of cardiac cells isolated from one additional human biopsy from transplanted pediatric patients presenting either no rejection (R0) or mild rejection (R1). Two different approaches for isolation of human cardiac myocytes are also compared. Spectrally-resolved fluorescence lifetime detection of NAD(P)H fluorescence (excitation by pulsed 375 nm picosecond laser) is tested as a promising new tool for quantitative analysis of intrinsic cellular autofluorescence signals in living cardiomyocytes. This work opens new horizons in the evaluation of cardiac transplant rejection using latest fluorescence imaging approaches.
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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 | 0.000 |
| 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".