Electrochemiluminescent magnetic biosensor for simultaneous microRNA and parathyroid hormone detection via resonance energy transfer
Bibliographic record
Abstract
• Dual-target ECL biosensor detects miR-222 and PTH for integrated thyroid malignancy diagnosis. • Uses CRET with luminol and dyes, requiring no external light and minimizing background noise. • Achieves ultrasensitive detection (0.38 fM & 0.22 pg/mL) in 30 minutes for point-of-care testing. Thyroid-related malignancies often involve both oncogenic alterations and endocrine imbalance, necessitating integrated biomarker monitoring. In this work, we report an electrochemiluminescent (ECL) magnetic biosensor for the simultaneous detection of microRNA (miR) and parathyroid hormone (PTH), two clinically relevant indicators of thyroid cancer and parathyroid dysfunction. The sensing platform leverages luminol as an ECL donor and organic dyes as energy acceptors within a chemiluminescence resonance energy transfer (CRET) framework, enabling excitation-free signal generation with low background interference. Surface-modified magnetic nanoparticles serve as dual-function carriers, facilitating efficient magnetic enrichment and high-affinity target recognition. The system achieves sensitive and specific dual-analyte detection in a single assay with broad linear ranges and rapid turnaround. Limits of detection in human serum were 0.38 fM for miR-222 and 0.22 pg/mL for PTH. This CRET-ECL magnetic biosensor offers a rapid, sensitive, and minimally invasive approach for point-of-care evaluation of thyroid malignancy and associated endocrine disorders.
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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".