The Arsenic-Binding Aptamer Cannot Bind Arsenic: Critical Evaluation of Aptamer Selection and Binding
Why this work is in the frame
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Bibliographic record
Abstract
An arsenic-binding aptamer named Ars-3 was reported in 2009, and it has been used for detection of As(III) in more than two dozen papers. In this work, we performed extensive binding assays using isothermal titration calorimetry, various DNA-staining dyes, and gold nanoparticles. By carefully comparing Ars-3 and a few random control DNA sequences, no specific binding of As(III) was observed in each case. Therefore, we conclude that Ars-3 cannot bind As(III). Possible reasons for some of the previously reported binding and detection were speculated to be related to the adsorption of As(III) onto gold surfaces, which were used in many related sensor designs, and As(III)/Au interactions were not considered before. The selection data in the original paper were then analyzed in terms of sequence alignment, secondary structure prediction, and dissociation constant measurement. These steps need rigorous testing before confirming specific binding of newly selected aptamers. This study calls for attention to the gap between aptamer selection and biosensor design, and the gap needs to be filled by careful binding assays to further the growth of the aptamer field.
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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 | 0.001 | 0.001 |
| 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 it