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Record W7029034776

Hemagglutinin-esterase (HE) from Infectious Salmon Anemia virus (ISAv): Characteristics and attempted expression

2015· dissertation· en· W7029034776 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2015
Typedissertation
Languageen
FieldEngineering
TopicArtificial Immune Systems Applications
Canadian institutionsnot available
Fundersnot available
KeywordsVirusVirulencePathogenCloning (programming)Host (biology)EsteraseInfectious hematopoietic necrosis virusEquine infectious anemiaImmune system
DOInot available

Abstract

fetched live from OpenAlex

Infectious salmon anemia virus (ISAv) is a pathogen that mainly affects Atlantic salmon (Salmo salar), which are commonly grown in the aquaculture industry. The resulting disease, infectious salmon anemia, has caused large financial losses for this industry. ISAv is a member of the Orthomyxoviridae family, as are the influenza type A, B and C viruses, and it belongs to the genus Isavirus. ISAv has a single dual-functional surface protein that is involved in the interaction with the host cells, namely: a hemagglutinin-esterase (HE). The HE protein binds preferentially to 4-O,5-N-diacetylneuraminic acid residues that are present on the target cells, which in this case are salmon erythrocytes. As is the case for influenza, the binding of HE protein to 4-O-acetylsialosides (receptor function) triggers infection in salmon, whereas the esterase active site, which possesses the 'receptor destroying' activity hydrolyzes the 4-O-acetyl groups, aiding the release of the viral progeny to infect neighbouring cells. This thesis reports the cloning and the attempted expression of the haemagglutinin-esterase from two different ISAv strains, that is a Canadian and a Norwegian strain, using baculovirus expression systems.

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 score0.003

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.011
GPT teacher head0.218
Teacher spread0.207 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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