Quantitative and Multiplexed Chopper-Based Time-Gated Imaging for Bioanalysis on a Smartphone
Bibliographic record
Abstract
Smartphones are emerging platforms for point-of-care diagnostics (POCDs), where the on-board camera is, for example, used to image fluorescence. Many laboratory instruments are capable of time-gated (TG) photoluminescence (PL) measurements─an analytical method leveraged by multiple commercial assay kits. When paired with long-lived PL emitters such as luminescent lanthanide complexes (LLCs), time-gating eliminates background from sample autofluorescence and many other sources. This capability is amenable to minimally processed samples and would thus be useful for POCDs on a smartphone-based platform. Here, we report a double-chopper design for TG PL imaging using a portable, 3D-printed, smartphone-based device. The rotation speed, dimensions, and overlap of the chopper blades and gaps set the timing parameters, with delay times on the order of hundreds of microseconds to milliseconds. The device was capable of quantitative TG imaging of PL from terbium(III) and europium(III) LLCs, including rejection of short-lived PL background from serum and tissue phantoms, spectral and temporal multiplexing, a model time-gated Förster resonance energy transfer (TG-FRET) assay, and imaging of cells. As the first smartphone-based demonstrations of these important analytical capabilities, this work is an important foundation for developing POCD methods based on TG PL imaging.
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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 | 0.001 |
| 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".