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Record W2292281348 · doi:10.11575/prism/26508

Induction of Antiviral Response Against Avian Infectious Laryngotracheitis Virus Infection

2015· dissertation· en· W2292281348 on OpenAlexfundno aff
Simrika Thapa

Bibliographic record

VenuePRISM (University of Calgary) · 2015
Typedissertation
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsnot available
FundersFaculty of Veterinary Medicine, University of Calgary
KeywordsVirologyVirusBiology

Abstract

fetched live from OpenAlex

Toll-like receptors (TLRs) recognize pathogen associated molecular patterns (PAMPs). The PAMPs that act as ligands for TLRs prompt downstream signalling leading to antimicrobial effects. However, the details of antiviral responses of lipotechoic acid (LTA) and CpG DNA, which act as ligands for TLR-2 and -21 respectively, elicited against avian viruses are scarce. We investigated whether in ovo delivery of LTA and CpG DNA induces antiviral responses against infectious laryngotracheitis virus (ILTV) infection in chickens. We found that in ovo delivery of these two ligands reduces ILTV infections in lungs pre- and post-hatch. However, only CpG DNA could reduce mortality and morbidity due to ILTV infection encountered post-hatch. The expression of IL-1β mRNA and increase of macrophage numbers in lungs were found to be correlates of observed antiviral responses. Thus, LTA and CpG DNA can be candidate TLR ligands worthy of further investigation for the control of ILTV infection in chickens.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.001

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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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