High UV Excitation Intensity Induces Photoconversion of DAPI During Wide-Field Microscopy
Bibliographic record
Abstract
Background: Multi-color fluorescence microscopy is dependent on the spectral specificity of the dyes and probes used for localization. One of the most commonly used fluorescent DNA dyes is DAPI, which is usually excited by UV light to emit in the blue visible light range. Herein, we describe a pattern of decreasing DAPI fluorescence upon extended UV exposure, closely followed by an increase in emission maxima in the green range.
 Methods: UV-induced photo-conversion of DAPI to green-fluorescing photoproducts was studied on Chinese hamster ovary cells using wide-field fluorescence microscopy, at different UV exposure times and intensities. Imaging was done in repetitive cycles, by alternating between a DAPI and FITC filter cube and following this with a 1 second UV excitation time. The effect of differing UV light intensities on the photo- conversion process was not previously described in the literature.
 Results: Upon image analysis from a large sample of cells, the rate of photo-conversion was shown to be dependent on both the duration of UV excitation and the intensity of the UV light source. Both the process of DAPI depletion and photo-product growth showed biphasic exponential patterns of change. Furthermore, the level of DAPI fluorescence intensity was found to be negatively correlated with the green fluorescence of the photo-product.
 Limitations: This study did not examine the effect of differing mounting media or a variation in DAPI concentration on the rate of DAPI photo-conversion. Also, the exact light dosage to the system was not measured from the 100W Hg bulb. Photo-bleaching of green fluorescence in cells not stained with DAPI was not measured to control for bleaching of endogenous cell molecules.
 Conclusion: Based on our findings, a set of recommendations was formulated in order to help reduce the effects of UV-induced DAPI photo-conversion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".