An aptamer-based point-of-care diagnostic test strip for rapid diagnosis of surface spike proteins of SARS-CoV2 virus
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has been identified as the causative agent for the COVID-19 pandemic. Herein, we report the development of a point-of-care diagnostic (POC) test strip for rapid and specific diagnosis of surface spike protein (S-protein) of SARS-CoV2 virus, as a target analyte for the virus diagnosis. The test detects changes in the physicochemical properties of gold nanoparticles with the utility of a DNA aptamer that is specifically selected for binding to the receptor-binding domain (RBD) of S-protein of SARS-CoV-2. Structural changes in aptamer enables the aggregation/disaggregation of gold nanoparticles in the absence/presence of the target analyte, respectively. Lateral flow assays were utilized to visualize results and stratify positive samples (containing viral S-protein) from negative samples (blank) with high specificity and sensitivity (1–10 nM). The proposed sensing technology was successfully developed for rapid quantification of SARS-CoV2 S-protein; however, it can be further adapted to detect variants, viral DNA/RNA, and other targets, enabling the development of POC devices for multiplexing assays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".