Targeting Host Cell Surface Nucleolin for RSV Therapy: Challenges and Opportunities
Bibliographic record
Abstract
Nucleolin (NCL) has been reported as a cellular receptor for the human respiratory syncytial virus (RSV). We studied the effects of re-purposing AS1411, an anti-cancer compound that binds cell surface NCL, as a possible novel strategy for RSV therapy in vitro and in vivo. AS1411 was administered to RSV-infected cultures of non-polarized (HEp-2) and polarized (MDCK) epithelial cells and to virus-infected mice and cotton rats. Results of in vitro experiments showed that AS1411, used in micromolar concentrations, was associated with decreases in the number of virus-positive cells. Intranasal administration of AS1411 (50 mg/kg) to RSV-infected mice and cotton rats was associated with partial reductions in lung viral titers, decreased virus-associated airway inflammation, and decreased IL-4/IFN-γ ratios when compared to untreated, infected animals. In conclusion, our findings indicate that therapeutic use of AS1411 has modest effects on RSV replication and host response. While the results underscore the challenges of targeting cell surface NCL as a potential novel strategy for RSV therapy, they also highlight the potential of cell surface NCL as a therapeutic target.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".