Improvements in siRNA properties mediated by 2'-deoxy-2'-fluoro- -D-arabinonucleic acid (FANA)
Bibliographic record
Abstract
RNA interference (RNAi) has emerged recently as an efficient mechanism for specific gene silencing. Short double-stranded small interfering RNAs (siRNAs) are now widely used for cellular or drug target validation; however, their use for silencing clinically relevant genes in a therapeutic setting remains problematic because of their unfavourable metabolic stability and pharmacokinetic properties. To address some of these concerns, we have investigated the properties of siRNA modified with 2'-deoxy-2'-fluoro-beta-d-arabinonucleotide units (araF-N or FANA units). Here we provide evidence that these modified siRNAs are compatible with the intracellular RNAi machinery and can mediate specific degradation of target mRNA. We also show that the incorporation of FANA units into siRNA duplexes increases activity and substantially enhances serum stability of the siRNA. A fully modified sense 2'-deoxy-2'-fluoro-beta-D-arabinonucleic acid (FANA) strand when hybridized to an antisense RNA (i.e. FANA/RNA hybrid) was shown to be 4-fold more potent and had longer half-life in serum (approximately 6 h) compared with an unmodified siRNA (<15 min). While incorporation of FANA units is well tolerated throughout the sense strand of the duplex, modifications can also be included at the 5' or 3' ends of the antisense strand, in striking contrast to other commonly used chemical modifications. Taken together, these results offer preliminary evidence of the therapeutic potential of FANA modified siRNAs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".