2‐( <scp> <i>N</i> ‐Morpholino </scp> )ethanesulphonic acid mediated facile and rapid one‐pot synthesis of gold nanoparticles and its application for colorimetric detection of heparin in human serum
Bibliographic record
Abstract
Abstract A facile and rapid method for one‐pot synthesis of gold nanoparticles (AuNPs) has been developed. It employed 2‐( N ‐morpholino)ethanesulphonic acid (MES) to act as reducing agent, buffering agent, and capping ligand to perform the reduction of the gold precursor (HAuCl 4 ) into AuNPs. The AuNPs were synthesized by a simple mixing of MES buffer (pH 6.0) and HAuCl 4 solution under a vortex at room temperature, and the process was completed within 1 min, which not only significantly simplifies the preparation procedure without heating or cooling but also greatly shortens the reaction time. Moreover, a novel colorimetric approach for sensitive detection of heparin was fabricated based on the prepared AuNPs. The detection limit was determined to be 3.1 μg/ml (i.e., 0.465 U/ml) with a linear response range of 3.25–130 μg/ml. Additionally, the sensor was also successfully applied for the detection of heparin in human blood serum samples, demonstrating its potential applicability for disease diagnosis in the future.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".