Ligase-catalyzed transcription and reverse-transcription of XNA-containing nucleic acid polymers using T3 DNA ligase
Bibliographic record
Abstract
A method to enable the transliteration between various XNA-continaing nucleic acids and canonical DNA is described. Using Ligase-catalysed oligonucleotide polymerisation (LOOPER), we show that DNA can be used as a template to generate nucleic acids polymers comprising various levels of 2’-fluoro (2’-F), 2'-Fluoro-arabinonucleic Acid (FANA), 2’-O-methyl (2’-OMe), and Locked Nucleic Acids (LNA) in moderate yields. The fidelity and biases of the LOOPER process was studied in detail for the 2’-F system by developing a hairpin-based sequecing method, which showed fidelities exceeeding 95% along with positional and sequence dependencies within the polymerised XNA-containing anticondons. Lastly, we show the ability of LOOPER to regenerate DNA from 2’-F, FANA, 2’-OMe, and LNA in moderate yield and in fidelities over 95%. Taken together, this study demonstrates the potential of LOOPER to serve as a platform for applications where the transliteration between XNA and DNA is needed, such as the in vitro evolution of XNA-containing nucleic acid polymers.
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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) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".