Impedimetric Immobilized DNA-Based Sensor for Simultaneous Detection of Pb<sup>2+</sup>, Ag<sup>+</sup>, and Hg<sup>2+</sup>
Bibliographic record
Abstract
An unlabeled immobilized DNA-based sensor was reported for simultaneous detection of Pb(2+), Ag(+), and Hg(2+) by electrochemical impedance spectroscopy (EIS) with [Fe(CN)(6)](4-/3-) as redox probe, which consisted of three interaction sections: Pb(2+) interaction with G-rich DNA strands to form G-quadruplex, Ag(+) interaction with C-C mismatch to form C-Ag(+)-C complex, and Hg(2+) interaction with T-T mismatch to form T-Hg(2+)-T complex. Circular dichroism (CD) and UV-vis spectra indicated that the interactions between DNA and Pb(2+), Ag(+), or Hg(2+) occurred. Upon DNA interaction with Pb(2+), Ag(+), and Hg(2+), respectively, a decreased charge transfer resistance (R(CT)) was obtained. Taking advantage of the R(CT) difference (ΔR(CT)), Pb(2+), Ag(+), and Hg(2+) were selectively detected with the detection limit of 10 pM, 10 nM, and 0.1 nM, respectively. To simultaneously (or parallel) detect the three metal ions coexisting in a sample, EDTA was applied to mask Pb(2+) and Hg(2+) for detecting Ag(+); cysteine was applied to mask Ag(+) and Hg(2+) for detecting Pb(2+), and the mixture of G-rich and C-rich DNA strands were applied to mask Pb(2+) and Ag(+) for detecting Hg(2+). Finally, the simple and cost-effective sensor could be successfully applied for simultaneously detecting Pb(2+), Ag(+), and Hg(2+) in calf serum and lake water.
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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) | 0.001 | 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 | 0.001 |
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".