Immunoassay for LMP1 in nasopharyngeal tissue based on surface-enhanced Raman scattering
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Bibliographic record
Abstract
BACKGROUND: Previous studies have shown that Epstein-Barr virus (EBV)-encoded latent membrane protein 1 (LMP1) is closely associated with the occurrence and development of nasopharyngeal carcinoma, and can be used as a tumor marker in screening for the disease. Here we report a new methodology based on highly specific and sensitive surface-enhanced Raman scattering (SERS) technology to detect LMP1 in nasopharyngeal tissue sections directly with no need of tedious procedures as with conventional immunohistochemistry methods. METHODS: LMP1-functionalized 4-mercaptobenzoic acid (4-MBA)-labeled Au/Ag core-shell bimetallic nanoparticles were prepared first and then applied for analyzing LMP1 in formalin-fixed paraffin-embedded nasopharyngeal tissue sections obtained from 34 cancer patients and 20 healthy controls. SERS spectra were acquired from a 25 × 25 spot square area on each tissue section and used to generate SERS images. RESULTS: Data from SERS spectra and images show that this new SERS-based immunoassay detected LMP1 in formalin-fixed paraffin-embedded nasopharyngeal tissue sections with high sensitivity and specificity. The results from the new LMP1-SERS probe method are superior to those of conventional immunohistochemistry staining for LMP1, and in excellent agreement with those of in situ hybridization for EBV-encoded small RNA (EBER). CONCLUSION: This new SERS technique has the potential to be developed into a new clinical tool for detection and differential diagnosis of nasopharyngeal carcinoma as well as for predicting metastasis and immune-targeted treatment of nasopharyngeal carcinoma.
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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 it