Acid-Triggered Self-Assembled Egg White Protein-Coated Gold Nanoclusters for Selective Fluorescent Detection of Fe<sup>3+</sup>, NO<sub>2</sub><sup>–</sup>, and Cysteine
Why this work is in the frame
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Bibliographic record
Abstract
Herein, we present a simple and economical synthesis for the first multianalyte probe able to selectively quantify the concentrations of Fe3+, NO2–, and cysteine. It comprises H+-triggered self-assembled gold nanoclusters (AuNCs@EW/H+, AuEHs), showing enhanced red fluorescence at 640 nm. The AuEH is a good fluorescent nanosensor for Fe3+ and NO2– with detection limits of 1.40 and 2.82 nM, respectively. Iron detection, through fluorescence quenching, occurs because of nanocluster aggregation elicited by the complexation of Fe3+ with amino acids on the surface of AuEH; nitrite detection likely proceeds through fluorescence quenching via the disassembly of the nanoclusters following irreversible oxidation by nitrite. This selectivity is good enough that it can be used to quantify the nitrite concentration in commercially available processed meat. Cysteine detection occurs through the restoration of fluorescence of iron-quenched samples; similar molecules including homocysteine and glutathione are unable to restore fluorescence, showing the specificity of the interaction. Applications, including as a detecting ink and as a biocompatible probe, show promise because of the lack of observable toxicity of the AuEHs, demonstrating their promise as specific and sensitive biosensors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it