Multiplexed Surface Plasmon Resonance Imaging for Protein Biomarker Analysis
Bibliographic record
Abstract
The reliable detection of ligand and analyte binding is of significant importance for the field of medical diagnostics. Recent advances in proteomics and the rapid expansion in the number of identified protein biomarkers enhance the need for reliable techniques for their identification in complex samples. Surface plasmon resonance imaging (SPRi) provides label-free detection of this binding process in real-time. This chapter details the fabrication of an SPR imaging instrument and its use in analyzing molecular binding interactions with the use of a high-density microfluidic SPRi chip, capable of multiplexed analysis as well as various immobilization chemistries. Controlled recovery of bound biomarkers is demonstrated to enable their identification using mass spectrometry. Finally, activated leukocyte cell adhesion molecule (ALCAM), a protein biomarker associated with a variety of cancers, is identified from human crude cell lysates using the microfluidic surface plasmon resonance imaging (SPRi) instrument.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".