Lab-on-a-chip multiplexed electrochemical sensor enables simultaneous detection of SARS-CoV-2 RNA and host antibodies
Bibliographic record
Abstract
Abstract The current COVID-19 pandemic highlights the continued need for rapid, accurate, and cost-effective point-of-care (POC) diagnostics that can accurately assess an individual’s infection and immunity status for SARS-CoV-2. As the virus continues to spread and vaccines become more widely available, detecting viral RNA and serological biomarkers can provide critical insights into the status of infectious, previously infectious, and vaccinated individuals over time. Here, we describe an integrated, low-cost, 3D printed, lab-on-a-chip device that extracts, concentrates, and amplifies viral RNA from unprocessed patient saliva and simultaneously detects RNA and multiple host anti-SARS-CoV-2 antibodies via multiplexed electrochemical (EC) outputs in two hours. The EC sensor platform enables single-molecule CRISPR/Cas-based molecular detection of SARS-CoV-2 viral RNA as well as serological detection of antibodies against the three immunodominant SARS-CoV-2 viral antigens. This study demonstrates that microfluidic EC sensors can enable multiplexed POC diagnostics that perform on par with traditional laboratory-based techniques, enabling cheaper and more widespread monitoring of infection and immunity over time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".