Efficient Transfer of Intact Oligonucleotides into the Nucleus of Ligament Scar Fibroblasts by HVJ-Cationic Liposomes Is Correlated with Effective Antisense Gene Inhibition
Bibliographic record
Abstract
The efficacy of two different cationic liposomes, Lipofectin and hemagglutinating virus of Japan (HVJ)-cationic liposomes, on nuclear uptake of fluorescence-labeled phosphorothioate oligodeoxyribonucleotide (S-ODN) by ligament scar fibroblasts and suppression of decorin mRNA expression when antisense decorin S-ODN was transferred was investigated. There was no significant difference in nuclear uptake of fluorescent ODN between the two methods. However, only HVJ-cationic liposomes had a significant effect on suppression of decorin mRNA expression levels. To address the discrepancy, the molecular integrity of the transferred ODN in the cells was assessed by analysis of fluorescence resonance energy transfer (FRET) within double-fluorescence-labeled S-ODN. More than 70% of the ODN transfected by HVJ-cationic liposomes remained intact within the nucleus at 20 h after transfection, while the majority of the ODN transferred by Lipofectin was degraded at this point. These results suggest a strong relationship between the nuclear integrity of transfected antisense ODN and its suppression of target mRNA expression.
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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) | 0.000 | 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".