Design of a universal biointerface for sensitive, selective, and multiplex detection of biomarkers using surface plasmon resonance imaging
Bibliographic record
Abstract
This paper reports on the sensitive, selective, and simultaneous detection of four protein biomarkers involved in metastasis of various cancers, namely Fas, angiopoietin-2 (Ang-2), human epidermal growth factor receptor 2 (HER2), and matrix metallopeptidase-9 (MMP-9) using an antibody-conjugated quantum dot (QD) chip and surface plasmon resonance imaging (SPRi) biosensors. Initially, a self-assembled monolayer film of l-cysteine, using glutaraldehyde as a linker and QDs as signal enhancement moieties, was employed to immobilize anti-Fas for the detection of Fas as a model protein in buffer. The biointerface was characterized using confocal microscopy, atomic force microscopy, and scanning electron microscopy to provide evidence of uniform surface coverage by the QDs. The SPRi signal was enhanced 100-fold to achieve a detection limit of 25 pg mL(-1) after applying biotinylated detection antibody-conjugate streptavidin-modified QDs. Secondly, this signal amplification strategy was applied to sequentially detect Fas, HER2, MMP-9, and Ang-2 at low concentrations on a protein-microprinted/gold-coated SPRi chip. The results showed the absence of cross-reactivity among these proteins and the feasibility of the approach for multiplex detection of biomarkers as required for the accurate diagnosis of various diseases.
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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".