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Record W4403157352 · doi:10.1016/j.celrep.2024.114809

The VLDLR entry receptor is required for the pathogenesis of multiple encephalitic alphaviruses

2024· article· en· W4403157352 on OpenAlexfundno aff
Sathvik Palakurty, Saravanan Raju, Alan Sariol, Zhenlu Chong, Ngan Wagoner, Hongming Ma, Ofer Zimmerman, Lucas J. Adams, Camille Carmona, Zhuoming Liu, Daved H. Fremont, Sean P. J. Whelan, William B. Klimstra, Michael S. Diamond

Bibliographic record

VenueCell Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersDivision of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious DiseasesNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesDefense Threat Reduction AgencyNational Cancer InstituteNational Institutes of HealthModernaMallinckrodt Pharmaceuticals
KeywordsPathogenesisVirologyAlphavirusReceptorImmunologyBiologyNeuroscienceMedicineGeneticsVirus

Abstract

fetched live from OpenAlex

The very-low-density lipoprotein receptor (VLDLR) has been reported as an entry receptor for Semliki Forest (SFV) and Eastern equine encephalitis (EEEV) alphaviruses in cell cultures. However, the role of VLDLR in alphavirus pathogenesis and the extent to which other alphaviruses can engage VLDLR remains unclear. Here, using a surface protein-targeted CRISPR-Cas9 screen, we identify VLDLR as a receptor for Western equine encephalitis virus (WEEV) and demonstrate that it promotes the infection of multiple viruses in the WEE antigenic complex. In vivo studies show that the pathogenicity of WEEV, EEEV, and SFV, but not the distantly related Venezuelan equine encephalitis virus, is markedly diminished in VLDLR-deficient mice and that mice treated with a soluble VLDLR-Fc decoy molecule are protected against disease. Overall, these results expand our understanding of the role of VLDLR in alphavirus pathogenesis and provide a potential path for developing countermeasures against alphaviruses from different antigenic complexes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.288

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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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 designNot applicable
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

Citations21
Published2024
Admission routes1
Has abstractyes

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