Selection and Characterization of DNA Aptamers for Cytidine and Uridine
Bibliographic record
Abstract
Abstract Cytidine and uridine are two essential pyrimidine ribonucleotides, and accurate detection of these nucleosides holds significant biological importance. While many aptamers were reported to bind purines, little success was achieved for pyrimidine binding. This study employs the library‐immobilization capture‐SELEX technique to isolate aptamers capable of selectively binding to cytidine and uridine. First, a selection was performed using a mixture of cytidine and uridine as the target. This selection led to the isolation of a highly selective aptamer for cytidine with a dissociation constant ( K d ) of 0.9 μM as determined by isothermal titration calorimetry (ITC). In addition, a dual‐recognition aptamer was also discovered, which exhibited selective binding to both cytidine and uridine. Subsequently, a separate selection was carried out using uridine as the sole target, and the resulting uridine aptamer displayed a K d of 4 μM based on a thioflavin T fluorescence assay and a K d of 102 μM based on ITC. These aptamers do not have a strict requirement of metal ions for binding, and they showed excellent selectivity since no binding was observed with their nucleobases or nucleotides. This study has resulted three aptamers for pyrimidines, which can be employed in biosensors and DNA switches.
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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".