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Record W4386505072 · doi:10.1111/jfd.13851

Immune response induced by coinfection of the sea louse <i>Caligus rogercresseyi</i> and the intracellular bacteria <i>Piscirickettsia salmonis</i> in vaccinated Atlantic salmon

2023· article· en· W4386505072 on OpenAlexaff
Paulina Bustos, Carolina Figueroa, Bárbara Cádiz, Tamara Santander, Brian Dixon, José Gallardo, Pablo Conejeros

Bibliographic record

VenueJournal of Fish Diseases · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCoinfectionImmune systemBiologyVaccinationVirologyImmunologyMicrobiologyZoologyHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

Recently, we showed that Atlantic salmon vaccinated against Piscirickettsia salmonis lose their protection upon coinfection with Caligus rogercresseyi (sea lice). However, the causes of the overriding effect of C. rogercresseyi infection have not been elucidated, and the molecular basis of the cellular and humoral immune responses upon C. rogercresseyi infection has not been described for vaccinated salmon. Therefore, we studied changes in the transcription of immune genes in vaccinated Atlantic salmon that were experimentally challenged by co-infecting them with C. rogercresseyi and P. salmonis. In general, coinfection treatments showed immune gene expression similar to treatments with a single P. salmonis infection, showing a decreased cellular response. However, a high variance was found between individual fish in the case of crucial cellular immune genes, with a few fish reacting overwhelmingly highly compared to the majority. This supports our previous findings on vaccination response variation and reinforces the idea that vaccination failures in the field might be caused by an overwhelming amount of vaccinated fish that display a deficient immune response to the infection.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.260
Teacher spread0.252 · 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 designObservational
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

Citations7
Published2023
Admission routes1
Has abstractyes

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