Improving fluorescence diagnosis of cancer by SLIM
Bibliographic record
Abstract
Although during the last years, significant progress was made in cancer diagnosis, using either intrinsic or specially designed fluorophores, still problems exist, due to difficulties in spectral separation of highly overlapping probes or in lack of specificity. Many of the problems could be circumvented by focusing on time-resolved methods. In combination with spectral resolved detection (spectral fluorescence lifetime imaging, SLIM) highly sophisticated fluorescence lifetime imaging can be performed which might improve specificity of cell diagnosis. To record lifetime images (τ-mapping) with spectral resolution a setup was realized consisting of a laser scanning microscope equipped with a 16 channel array for time-correlated single photon counting (TCSPC) and a spectrograph in front of the array. A Ti:Saphir laser can be used for excitation or alternatively ps diode lasers. With this system the time- and spectral-resolved fluorescence characteristics of different fluorophores were investigated in solution and in cell culture. As an example, not only the mitochondria staining dye rhodamine 123 could be easily distinguished from DAPI, which intercalates into nucleic acids, but also different binding sites of DAPI. This was proved by the appearance of different lifetime components within different spectral channels. Another example is Photofrin, a photosensitizer which is approved for bladder cancer and for palliative lung and esophageal cancer in 20 countries, including the United States, Canada and many European countries. Photofrin is a complex mixture of different monomeric and aggregated porphyrins. The phototoxic efficiency during photodynamic therapy (PDT) seems to be correlated with the relative amounts of monomers and aggregates. With SLIM different lifetimes could be attributed to various, spectrally highly overlapping compounds. In addition, a detailed analysis of the autofluorescence by SLIM could explain changes of mitochondrial metabolism during Photofrin-PDT.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".