Real‐time fluorescence‐based detection of furanocoumarin photoadducts of DNA
Bibliographic record
Abstract
Real-time fluorescence detection systems were adapted to identify DNA adducts formed by photogenotoxic phytochemicals. Two assays were developed: the first was based on quantitative polymerase chain reaction (qPCR) while the second used thermal denaturation and renaturation (D-R). Both assays employed yeast DNA, the fluorescent dye SYBR Green and a real-time PCR thermocycler. The furanocoumarins 8-methoxypsoralen (8-MOP), 5-methoxypsoralen (5-MOP), psoralen, angelicin and imperatorin, and the furanochrome khellin, were tested for adduct forming ability with up to 2 h of UVA light exposure (lambda = 320-400 nm). The known bifunctional compounds, 8-MOP, 5-MOP and psoralen, were inferred to form biadducts here based on both D-R and qPCR assays, as expected from previous research. The known monofunctional compound angelicin was used as a negative control and did not form biadducts based on either assay. Two compounds of unknown functional specificity, imperatorin and khellin, were determined to be positive and negative for biadduct activity, respectively. Detection of biadducts with 8-MOP, 5-MOP, psoralen and imperatorin, but not angelicin or khellin, was further verified by temperature gradient gel electrophoresis. The fluorescence methods improve and expand upon existing assays to monitor DNA adducts.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".