A glycan-based plasmonic sensor for prostate cancer diagnosis
Bibliographic record
Abstract
Prostate cancer affects thousands of men who undergo clinical screening tests every year. The main biomarker used for the diagnosis of prostate cancer, prostate specific antigen (PSA), presents limitations that justify investigating new biomarkers to improve reliability. Antibodies against the tumor-associated carbohydrate antigen (Tn), or TACA, develop early in carcinogenesis, making them an interesting alternative as a target for prostate cancer diagnostics. In this work, the Tn antigen was synthesized and immobilized on a surface plasmon resonance sensor coated with a polydopamine/polyethylene oxide mixed layer used both as an anchoring surface for Tn capture moieties and to minimize surface fouling. The sensor could be regenerated and reused at least 60 times without any significant loss in sensitivity. Anti-Tn antibodies were detected in the 0-10 nM concentration range with detection limits of 0.1 and 0.3 nM in spiked buffer solutions and diluted human blood serum samples, respectively. Finally, as a proof-of-concept, this carbohydrate-based sensor was used to successfully discriminate blood serum samples from prostate cancer-free and prostate cancer patients.
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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".