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The glycosylation sites in RBD of spike protein attenuate the immunogenicity of PEDV AH2012/12

2024· article· en· W4396229714 on OpenAlexaff
Gege Zhang, Qi Peng, Shiyu Liu, Baochao Fan, Chuanhong Wang, Song Xu, Qiuxia Cao, Chengcheng Li, Hong De Xu, Hongting Lu, Meiying Bao, Shanshan Yang, Yunchuan Li, Jiaxiang Wang, Bin Li

Bibliographic record

VenueVirus Research · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsMinistry of Agriculture
FundersNational Key Research and Development Program of ChinaJiangsu Agricultural Science and Technology Innovation FundGovernment of Jiangsu ProvinceNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of ChinaJiangsu Academy of Agricultural Sciences
KeywordsImmunogenicityBiologyGlycosylationSpike ProteinSpike (software development)VirologyComputational biologyCoronavirus disease 2019 (COVID-19)GeneticsAntibody

Abstract

fetched live from OpenAlex

Porcine epidemic diarrhea (PED) is a highly contagious swine intestinal disease caused by PED virus (PEDV). Vaccination is a promising strategy to prevent and control PED. Previous studies have confirmed that glycosylation could regulate the immunogenicity of viral antigens. In this study, we constructed three recombinant PEDVs which removed the glycosylation sites in RBD. Viral infection assays revealed that similar replication characteristics between the recombinant viruses and parental PEDV. Although animal challenging study demonstrated that the glycosylation sites in RBD do not affect the pathogenicity of PEDV, we found that removing the glycosylation sites on the RBD regions could promote the IgG and neutralization titer in vivo, suggesting deglycosylation in RBD could enhance the immunogenicity of PEDV. These findings demonstrated that removal of the glycosylation sites in RBD is a promising method to develop PEDV vaccines.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.138
GPT teacher head0.365
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2024
Admission routes1
Has abstractyes

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