Acoustic Wave Sensor Detection of an Ovarian Cancer Biomarker with Antifouling Surface Chemistry
Bibliographic record
Abstract
Ovarian cancer (OC) must be detected in its early stages when the mortality rate is the lowest to provide patients with the best chance of survival. Lysophosphatidic acid (LPA) is a critical OC biomarker since its levels are elevated across all stages and increase with disease progression. This paper presents an LPA assay based on a thickness shear mode acoustic sensor with dissipation monitoring that involves a new thiol molecule 3-(2-mercaptoethanoxy)propanoic acid (HS-MEG-COOH). HS-MEG-COOH is an antifouling linker that provides (a) antifouling properties for gold substrates and (b) linking ability via its terminal carboxylic acid functional group. The antifouling ability of HS-MEG-COOH was tested in whole human serum. The new molecule was applied to the LPA assay in conjunction with a spacer molecule, 2-(2-mercaptoethoxy)ethan-1-ol (HS-MEG-OH), in a 1:1 v/v ratio. HS-MEG-COOH was covalently linked to gelsolin–actin, a protein complex probe that dissociates due to LPA-binding. LPA was detected in phosphate-buffered saline and undiluted human serum and achieved a low limit of detection (1.0 and 0.7 μM, respectively) which was below the concentration of LPA in healthy individuals. The antifouling properties of HS-MEG-COOH and the detection of LPA demonstrate the ability of the sensor to successfully identify the early-stage OC biomarker in undiluted human serum.
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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".