Multiplexed in vivo photoacoustic imaging of photoswitchable chromoproteins GAF2 and BphP1 with difference spectra differentiation (Conference Presentation)
Bibliographic record
Abstract
Photoswitchable chromoproteins allow for molecular photoacoustic images with reduced hemoglobin background signal. We have previously introduced GAF2 a far-red photoswitchable chromoprotein similar to BphP1 [Yao et al., Nat. Meth. 13, 67–73 (2016)], but one-tenth the size. We introduce a new strategy for differentiating between spectrally similar photoswitchable chromoproteins. This strategy is based on exploiting relative spectral differences between two photoswitchable absorption states. We present in vivo photoacoustic images of GAF2 and BphP1 with differentiation based on their relative intensity change. We imaged using a custom photoswitchable photoacoustic imaging system that allows simultaneous background-free photoacoustic signal acquisition and difference spectra differentiation. E.coli expressing BphP1 and GAF2 are injected at various depths in hairless SCID mice. Background-free photoacoustic images are obtained and the chromoproteins are differentiated based on their relative intensity change. We photoconvert GAF2 and BphP1 using 607.5nm (5.2mJ/cm2) and 710nm (8.3mJ/cm2) light. The cycle of imaging and photoconversion is 20s. We are able to obtain background-free photoacoustic images 1.2cm deep in vivo and clearly differentiate between GAF2 and BphP1 via relative intensity changes despite similar imaging spectra. Photoswtichable chromoproteins and difference spectra differentiation could prove promising for deep multiplexed molecular background-free photoacoustic imaging.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".