Imaging EGFR distribution using surface-enhanced Raman spectroscopy
Bibliographic record
Abstract
The purpose of this study is to explore the feasibility of using Surface Enhanced Raman Spectroscopy (SERS) to image the distribution of Epidermal Growth Factor Receptor (EGFR) in cells. To accomplish this task, 30 nm gold nanoparticles (AuNPs) tagged with antibodies to EGFR (1012 per ml) are incubated with cells (106 per ml) of the A431 human epidermoid carcinoma cell line and normal human bronchial epithelial (NHBE) cells. Using the 632.8 nm excitation line of a He-Ne laser, Raman spectroscopy measurements are performed using a point mapping scheme. SERS signals are observed with an overall enhancement of 4-7 orders of magnitude. Raman intensity maps of the 1480 and 1583 cm-1 peaks correlate well with the expected distribution of AuNPs and EGFR. Normal cells show little to no enhancement. The results therefore present a simple yet effective means to image EGFR over-expression.
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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 | 0.000 | 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) | 0.001 | 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 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".