Immobilized cellulose nanospheres enable rapid antigen detection in lateral flow immunoassays
Bibliographic record
Abstract
Rapid diagnostic systems are essential in controlling the spread of viral pathogens and efficient patient management. The available technologies for low-cost viral antigen testing have several limitations, including a lack of accuracy and sensitivity. Here, we introduce a platform based on cellulose II nanoparticles (oppositely charged NPan and NPcat) for effective control of surface protein interactions, leading to rapid and sensitive antigen tests. Passivation against non-specific adsorption and augmented immobilization of sensing antibodies is achieved by adjusting the electrostatic charge of the nanoparticles. The interactions affecting the performance of the system are investigated by microgravimetry and confocal imaging. As a proof-of-concept test, SARS-CoV-2 nucleocapsid sensing was carried out by using saliva-wicking by channels that were stencil-printed on paper. We conclude that inkjet-printed NPcat elicits strong optical signals, visible after a few minutes, opening the opportunity for cost-effective and rapid diagnostic. Supplementary Information: The online version contains supplementary material available at 10.1007/s10570-022-05038-y.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
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 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".