Spatial and spectral resolution of photosensitizer fluorescence in cells and tissues
Bibliographic record
Abstract
Spatial and temporal distribution patterns of photosensitizers or their photoproducts is an important observation when attempting to understand the cellular and molecular effects of a particular photochemotherapeutic compound on cells and tissues. While fluorescence microscopy can be readily used to determine the spatial distribution of specific fluorophores within cells, certain limitations arise with this commonly used technique. These limitations include spectral overlap between probes and the fluorophore of interest, endogenous autofluorescence of various intracellular components, and artifactual signals derived from exogenous dyes, all of which interfere with the fluorescent signals emitted from the molecules of interest in a study. The most significant artifactual fluorescent signals given off by intracellular molecules include fluorescence emitted from certain aromatic amino acids, collagen, elastin, pyridoxine, nicotinamide adenine dinucleotides, flavins, and several different porphyrins. In addition to these obstacles, the intercellular environment may influence some fluorophores when macroscopic analysis of tissues is performed. Different fluorophores have different photodynamic activities, photobleaching characteristics, emission wavelength maxima and bandwidths, and fluorescence quantum yields, all of which may lead to a shift in a particular emission signal by a certain fluorophore in a given tissue environment.
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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 | 0.000 | 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) | 0.000 | 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".