Dual immunosensor based on methylene blue-electroadsorbed graphene oxide for rapid detection of influenza virus antigen
Bibliographic record
Abstract
ABSTRACT Rapid detection of influenza viral infections in the poultry farm is advantageous in several facts such as environmental/personal safety, food-security and socio-economy. Herein, we report the development of an electrochemical based dual sensor platform composed of methylene blue-electroadsorbed graphene oxide nanostructures modified with monoclonal antibodies, H5N1 and H1N1. Bio-functional layers comprised of chitosan and protein-A molecules were implemented at the interface of sensor element and antibodies, which synergistically enriched the bio-activity of immobilized antibodies for the immune complex formation. The differential pulse voltammetric signals resulted from the developed immunosensor platform exhibited a good correlation (R 2 = 0.9978 for H1N1 and R 2 =0.9997 for H5N1) for the wide range of target concentrations (25 to 500 pM). Chronoamperometric study also revealed the amplified current sensitivity of the immunoelectrodes even at the picomolar level. The proposed immunosensor design not only provide rapid analytical response time (<1 min) but also provide simplicity in fabrication and instrumentation which paves an attractive platform for on-farm monitoring of viral infections.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".