Metabolic mapping with plasmonic nanoparticle assemblies
Bibliographic record
Abstract
A rapid and simple methodology for the biomolecular analysis of single cells and microenvironments via a stick-and-peel plasmonic sensing platform is reported. Substrate-bound assemblies of plasmonic gold nanoparticles linked by reconfigurable oligonucleotides undergo disassembly upon target binding. Changes in the light scattering intensity of thousands of discrete nanoparticle assemblies are extrapolated concomitantly to yield the mapping of local target concentrations. The methodology is completely free of labelling, purification and separation steps. We quantified the intracellular ATP levels for two ovarian cancer cell lines to elucidate the differences and cellular distribution, and demonstrated the potential of the stick-and-peel platform for mapping the microenvironment of a 2D heterogeneous surface. The portable and economical analytical platform may broaden the affordability and applicability of single-cell based analyses and enable new opportunities in clinical care such as on-site molecular pathology.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".