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Record W2755566208 · doi:10.3390/vaccines5030027

Targeting Host Cell Surface Nucleolin for RSV Therapy: Challenges and Opportunities

2017· article· en· W2755566208 on OpenAlexafffund
Peter Mastrangelo, Michael Norris, Wenming Duan, Edward G. Barrett, Theo J. Moraes, Richard G. Hegele

Bibliographic record

VenueVaccines · 2017
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersConnaught FundUniversity of Toronto
KeywordsNucleolinIn vivoVirusIn vitroBiologyVirologyNasal administrationCellViral replicationRespiratory systemImmunologyCancer researchCell biology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.198
GPT teacher head0.380
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2017
Admission routes2
Has abstractyes

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