Highly Multiplexed Confocal Fluorescence Lifetime Microscope Designed for Screening Applications
Bibliographic record
Abstract
Protein-protein interactions can be measured in live cells, at nanometer scale, using Fluorescence Lifetime Imaging Microscopy (FLIM) enabled Forster Resonance Energy Transfer (FRET). There are growing interests in exploring protein-protein interactions in drug discovery applications. Traditional single point confocal microscopes, however, are slow and unsuited to small molecule screening, especially when combined with FLIM-FRET. We developed a 32 × 32 multiplexed confocal microscope, which employs a single-photon avalanche photodiode array with time gating capabilities for rapid FLIM acquisition. It has been demonstrated that such multiplexing technique can capture a 960 × 960 pixel multi-channel confocal fluorescence lifetime images in less than 1.5 seconds. Binding curves of two Bcl-2 family proteins: Bcl-XL and Bad were generated in live cells imaging experiments. The results show that the small molecule inhibitor A-1131852 is a more effective compound for disrupting Bcl-XL binding to Bad than ABT-263, which demonstrated the feasibility of screening of protein-protein interactions in high density well-plates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".