A novel colorimetric potassium sensor based on the substitution of lead from G-quadruplex
Bibliographic record
Abstract
Potassium ions play diverse roles in biological processes, and abnormal K(+) levels are the hallmarks of diseases. However, the potential clinical application of the developed DNA-based K(+) sensors remains a challenge due to the presence of Pb(2+) in blood samples. In this contribution, a novel colorimetric potassium sensing assay that functions in the presence of Pb(2+) is reported. This approach is based on conformational switching of a hairpin DNA structure to a G-quadruplex. Specifically, the hairpin DNA containing G-rich aptamer T30695 is exposed to successive amounts of Na(+), Pb(2+) and K(+). These cations induce formation of the corresponding metal-stabilized G-quadruplex, which acts as DNAzyme (with hemin as a cofactor) for the catalytic oxidation of ABTS by H(2)O(2). Importantly, studies presented here show that K(+) replaces Pb(2+) from the G-quadruplex to form K(+)-stabilized G-quadruplex, which differ in the catalytic behavior. With Pb(2+)-stabilized G-quadruplex as a probe, a highly sensitive and selective colorimetric detection of K(+) is achieved in the presence of Pb(2+) and excessive Na(+) (140 mM) with the detection limit of 1.9 nM. This system represents the first known DNAzyme-based colorimetric K(+) sensor, which works in the presence of Pb(2+). Finally, the sensor is successfully applied for K(+) detection in a real human serum sample containing Pb(2+).
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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".