Handheld Thermo-Photonic Device for Rapid, Low-Cost, and On-Site Detection and Quantification of Anti-SARS-CoV-2 Antibody
Bibliographic record
Abstract
With the emergence of vaccines and antibody therapeutics, rapid and scalable platforms are needed to quantify the antibody response of individuals. Lateral flow immunoassay (LFA) based test strips provide a rapid, low-cost, and point-of-care approach to antibody testing against the SARS-CoV-2 virus. These convenient and scalable tests, however, are qualitative in nature and cannot quantify the immune response of the infected and/or vaccinated individuals. This study reports on the development of a rapid, low cost and portable thermo-photonic device that enables sensitive detection and quantification of antibody levels using commercially available COVID-19 Antibody LFAs. Unlike conventional LFA readers, the developed technology is based on sensing the infrared thermal radiation of tag gold nanoparticles following laser excitation (aka photothermal response). Our proof-of-concept results with humanized monoclonal anti-SARS-CoV-2 Spike receptor-binding domain (RBD) IgG demonstrate that the thermo-photonic technology can detect and quantify antibody concentrations within the clinically relevant range and with a limit of detection of [Formula: see text]/ml. The reader in conjunction with antibody LFAs offers a low-cost, portable, and scalable solution for assessment of the degree of immunity in populations, quality control of convalescent plasma donations for antibody therapeutics, and monitoring the immune response of infected individuals and vaccine recipients.
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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 | 0.001 | 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".