Multispectral multiplexed confocal FLIM for live cell imaging
Bibliographic record
Abstract
Abstract Spectrally resolved fluorescence lifetime imaging (FLIM) with high spatial precision offers comprehensive information on species localization and behavior. It is challenging to resolve weak fluorescence signals in multiple dimensions (spatial, spectral, and temporal) at high frame rates, especially in dynamic live cell processes, as photobleaching and phototoxicity limit acceptable photon count rates. We developed a multiplexed confocal FLIM technique, which uses a prism-based imaging spectrometer to separate a 10 × 10 array of confocal foci into their spectral components. This allows the sampling of the spectra by a time-resolved image sensor to produce a multispectral time-resolved data set used for generating multispectral lifetime images. This system captures 300 × 300 pixel FLIM containing 12 unique spectral bands covering a 450–700 nm spectral range in 1.8 s of exposure. Its performance was demonstrated in fixed stained samples and in multispectral imaging of FLIM-FRET in live cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".