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Record W1977455608 · doi:10.3354/dao072093

Identification of a WSSV neutralizing scFv antibody by phage display technology and in vitro screening

2006· article· en· W1977455608 on OpenAlexaff
Yuan Li, Xuan Zhang, Nan Xiao, L.H. Dai, Wen Chen, Chao Jia, Rui Zhao, Sean M. Hemmingsen, Huanqin Dai

Bibliographic record

VenueDiseases of Aquatic Organisms · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicInvertebrate Immune Response Mechanisms
Canadian institutionsPlant Biotechnology Institute
FundersChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsWhite spot syndromeBiologyVirologyAntibodyShrimpPhage displayVirusNeutralizing antibodyIn vitroNeutralizationMicrobiologyImmunologyGenetics

Abstract

fetched live from OpenAlex

White spot syndrome virus (WSSV) is one of the most significant viral pathogens causing high mortality and economic damage in shrimp aquaculture. Although intensive efforts were undertaken to detect and characterize WSSV infection in shrimp during the last decade, we still lack methods either to prevent or cure white spot disease. Most of the studies on neutralizing antibodies from sera have been performed using in vivo assays. For the first time, we report use of an in vitro screening method to obtain a neutralizing scFv antibody against WSSV from a previously constructed anti-WSSV single chain fragment variable region (scFv) antibody phage display library. From clones that were positive for WSSV by ELISA, 1 neutralizing scFv antibody was identified using an in vitro screening method based on shrimp primary lymphoid cell cultures. The availability of a neutralizing antibody against the virus should accelerate identification of infection-related genes and the host cell receptor, and may also enable new approaches to the prevention and cure of white spot disease.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.227
Teacher spread0.223 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

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