A turn‐on fluorescence assay for heparin based on <scp>DNA</scp> ‐templated gold nanoclusters via <scp>ET</scp>
Bibliographic record
Abstract
Abstract A novel fluorescence turn‐on assay for heparin has been developed based on DNA‐templated gold nanoclusters (AuNCs) and Cytochrome c (Cyt c). In the design, poly A (A15) ssDNA was selected as a template for fabricating AuNCs. AuNCs possess strong fluorescence emission at 471 nm. Upon addition of Cyt c, the fluorescence of AuNCs was quenched effectively by electron transfer (ET) between AuNCs and the heme cofactor of Cyt c. In the presence of heparin, the much higher electrostatic binding of heparin to Cyt c caused Cyt c to be away from AuNCs, leading to a recovery of fluorescence intensity of AuNCs. The proposed method was found to be simple, fast, and sensitive for heparin detection, with a linear range from 0.5 μg/mL to 12 μg/mL, and a detection limit of 0.15 μg/mL. Furthermore, this work was successfully applied to detection of heparin in fetal bovine serum samples, with good recoveries from 93.53% to 103.6%.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".