High-Density Au Anchored to Ti<sub>3</sub>C<sub>2</sub>-Based Colorimetric-Fluorescence Dual-Mode Lateral Flow Immunoassay for All-Domain-Enhanced Performance and Signal Intercalibration
Bibliographic record
Abstract
In this work, a novel MXene-Au nanoparticle (Ti 3 C 2 @Au) was synthesized with a high molar extinction coefficient, strong fluorescence quenching ability, ultrahigh antibody affinity, high stability, and good dispersibility, and it was used to develop a colorimetric-fluorescence dual-mode lateral flow immunoassay (LFIA). The detection limits of this method for the detection of dexamethasone in milk, beef, and pork were 0.0018, 0.12, and 0.084 μg/kg in the “turn-off” mode (colorimetric signal), and 0.0013, 0.080, and 0.070 μg/kg in the “turn-on” mode (fluorescent signal), respectively, which was up to 231-fold more sensitive compared with that of the reported LFIAs. The recovery rates ranged from 81.1–113.7%, and 89.2–115.4%, with the coefficients of variation ranging from 1.4–15.0%, and 1.9–14.8%, respectively. The results of the LC-MS/MS confirmation test on 30 real samples had a good correlation with that of our established method ( R 2 > 0.97). This work not only developed novel nanocarriers for antibody-based LFIA but also ensured high-performance 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".