Concentric FRET: a review of the emerging concept, theory, and applications
Bibliographic record
Abstract
Concentric Förster resonance energy transfer (cFRET) is an emerging concept for single-vector multiplexed bioanalysis and imaging. It features a network of competitive and sequential energy transfer pathways, which, to date, has been assembled with a central semiconductor quantum dot (QD) and biomolecular linkers to multiple copies of multiple types of concentrically-arranged fluorescent dyes. In this review, we provide a first-hand account of the concept and development of cFRET, starting from its place in the broader context of FRET probes and assemblies. Topics of discussion include materials for cFRET, with a focus on the enabling properties of QDs and the ideal properties of nominal acceptor dyes; characterization and analysis of cFRET configurations via photoluminescence intensity, emission ratio, lifetime, and photobleaching measurements; semi-empirical modeling to determine the rates and efficiencies of competitive and sequential FRET pathways from overall quenching efficiencies; and archetypical examples of cFRET configurations and their application in bioanalysis and imaging. Most of the latter examples demonstrate multiplexed detection of protease activity or nucleic acid targets. Examples of atypical and cFRET-like configurations are also discussed, including those that utilize time-gated FRET relays and charge-transfer quenching. We conclude with a perspective on challenges and directions for future research with cFRET. Although still emerging as a method, many exciting opportunities in bioanalysis, imaging, and beyond are envisioned for cFRET.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".