Effect of Phosphothioate Modification on the Anti-L-Tyrosinamide Aptamer
Bibliographic record
Abstract
Aptamers are short, single-stranded RNA or DNA molecules that can bind to targets with high affinity and selectivity.Aptamers are versatile for their flexibility to be chemically modified, which can increase their stability against nucleases and positively affect their binding affinities.Many chemical modifications can be applied to aptamers, however for this study, phosphothioate modification (PS) is of interest.In antisense oligonucleotides, PS modifications seem to enhance the oligonucleotide's stability and resistance to nuclease degradation.To our knowledge, there were no studies documenting the effect of PS modification on aptamers, specifically anti-L-Tyrosinamide aptamers.Thus, the aim of this study is to understand the effect PS modifications have on aptamer binding and recognition to the target, L-Tyrosinamide, to exploit the modification to make an assay that is innovative and universally adaptable for small molecule KD determination.In this study, BSA yielded the best assay design using fluorescence anisotropy, at a concentration of 1.5x10 -7 M with an LOD of 3.04 µM and a spike recovery of 95.5% in urine.The findings of this study, mentioned above, will not only shed light on the effects of PS modifications on anti-L-Tyrosinamide aptamer, but possibly on other aptamers in general.Understanding the potential impact of the phosphothioate modification on the aptamer's functionality can contribute to valuable insights into the potential applications of aptamers and their optimization for various biomedical and biotechnological applications.
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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 | 0.001 |
| 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) | 0.001 | 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 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".