Magnetically Retrievable Platinum Nanoreporters for Efficient Lateral Flow Immunoassay in Complex Bio‐Samples
Bibliographic record
Abstract
Abstract Lateral flow immunoassays (LFIAs) are widely used for point‐of‐care diagnostics, but their development is challenged by the complexity and variability of patient samples. In particular, LFIAs often exhibit reduced sensitivity and specificity when used with patient samples, compared to their performance with analyte‐spiked idealized matrices. Patient samples are inherently complex, with variations in physical and biochemical properties between patients. This complexity has consequences for the performance of LFIAs, and can result in non‐specific binding on the test line, discoloration of the nitrocellulose membrane, and incomplete sample flow along the test strip. To address these challenges, a magnetically retrievable platinum nanoreporter (termed Pt@Fe 3 O 4 ) is developed for LFIAs. Leveraging the magnetic properties of the Fe 3 O 4 core, magnetic separation is utilized to enable the purification and concentration of target antigens from complex human matrices, including serum, saliva, and even stool samples. This also eliminates assay inconsistencies caused by inter‐sample variability. Further, the suitability of Pt@Fe 3 O 4 nanoreporters has been explored for use as detection probes in LFIAs. Signal enhancement is demonstrated by the utilization of the magnetic and enzyme‐mimicking activity of the nanoreporter, resulting in a marked improvement in sensitivity, as evidenced by a 2‐ to 4‐fold decrease in the visual limit of detection.
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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 | 0.000 |
| 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".