Immobilization of DNA on Magnetic Microparticles for Mercury Enrichment and Detection with Flow Cytometry
Bibliographic record
Abstract
Mercury detection in water has attracted a lot of research interest due to its highly toxic nature and adverse environmental impact. In particular, the recent discovery of specific binding of Hg(II) to thymine-rich (T-rich) DNA resulting in T-Hg(II)-T base pairs has led to the development of a number of sensors with different signaling mechanisms. However, the majority of such sensors were non-immobilized. Immobilization, on the other hand, allows active mercury adsorption, signal amplification, and sensor regeneration. In this work, we immobilized a thymine-rich DNA on a magnetic microparticle (MMP) surface through biotin-streptavidin interactions. In the presence of Hg(II), the DNA changes from a random coil structure into a hairpin, upon which SYBR Green I binds to emit green fluorescence. Detection was carried out by using flow cytometry where the fluorescence intensity increased ≈9-fold in the presence of mercury and the binding of mercury reached equilibrium in less than 2 min. The sensor showed a unique sample-volume-dependent fluorescence signal change where a higher fluorescence was obtained with a larger sample volume, suggesting that the particles can actively adsorb Hg(II). Detection limits of 5 nM (1 ppb) and 14 nM (2.8 ppb) were achieved in pure buffer and in mercury-spiked Lake Ontario water samples, respectively.
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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".