Fluorescence spectroscopy as a biomarker in a cell culture and in a nonhuman primate model for ovarian cancer chemopreventive agents
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to compare the effects of chemopreventive agents on natural fluorescence emission of ovarian cells in a cell culture and in a primate model as a feasibility trial to monitor drug activity. METHODS: Fluorescence emission spectra were collected from normal (NOE) and immortalized ovarian surface epithelial cells at 290, 360, and 450 nm excitation. Redox potentials were calculated and compared to % apoptosis and cell survival. Fluorescence emission spectra were collected from 18 female rhesus macaques receiving fenretinide [N-(-hydroxyphenyl)retinamide (4-HPR)] orally and/or oral contraceptive pills (OCP) or no medication. Fluorescence intensities and redox ratios were compared using a two-tailed Student's t test. RESULTS: Apoptosis and cell survival correlated with fluorescence emission consistent with metabolically active proteins [flavin adenine dinucleotide (FAD) and nicotinamide adenine dinucleotide (NAD(P)H)] and the resulting redox ratio in cells grown with 4-HPR. The 4-HPR consistently inhibited cell survival in a dose dependent manner. Degree of correlation varied between different cell lines. In primates receiving 4-HPR, fluorescence emission was increased at 450 nm excitation, 550 nm emission consistent with FAD presence, whereas those receiving OCP showed decreased emission at 350 nm excitation, 450 nm emission consistent with decreased NAD(P)H presence. Redox ratios were increased by both drugs. CONCLUSIONS: Fluorescence intensity and redox ratio appear to be altered by 4-HPR treatment in vivo and in cell culture and by OCP in vivo. Fluorescence intensity may be useful to monitor chemopreventive agents in clinical trials.
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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 | 0.000 |
| 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".