Rapid ratiometric biomarker detection with topically applied SERS nanoparticles
Bibliographic record
Abstract
Multiplexed surface-enhanced Raman scattering (SERS) nanoparticles (NPs) offer the potential for rapid molecular phenotyping of tissues, thereby enabling accurate disease detection as well as patient stratification to guide personalized therapies or to monitor treatment outcomes. The clinical success of molecular diagnostics based on SERS NPs would be facilitated by the ability to accurately identify tissue biomarkers under time-constrained staining and detection conditions with a portable device. In vitro, ex vivo and in vivo experiments were performed to optimize the technology and protocols for the rapid detection (0.1-s integration time) of multiple cell-surface biomarkers with a miniature fiber-optic spectral-detection probe following a brief (5 min) topical application of SERS NPs on tissues. Furthermore, we demonstrate that the simultaneous detection and ratiometric quantification of targeted and nontargeted NPs allows for an unambiguous assessment of molecular expression that is insensitive to nonspecific variations in NP concentrations.
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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".