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Record W2800545870 · doi:10.3389/fimmu.2018.01105

Mechanisms of Fish Macrophage Antimicrobial Immunity

2018· review· en· W2800545870 on OpenAlexafffund
Leon Grayfer, Barış Kerimoğlu, Amulya Yaparla, Jordan W. Hodgkinson, Jiasong Xie, Miodrag Belosevic

Bibliographic record

VenueFrontiers in Immunology · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesChina Scholarship CouncilGeorge Washington University
KeywordsBiologyMacrophageImmunityFish <Actinopterygii>AquacultureImmune systemAntimicrobialMacrophage polarizationInnate immune systemOvercrowdingImmunologyZoologyEcologyMicrobiologyFisheryGenetics

Abstract

fetched live from OpenAlex

Overcrowding conditions and temperatures shifts regularly manifest in large-scale infections of farmed fish, resulting in economic losses for the global aquaculture industries. Increased understanding of the functional mechanisms of fish antimicrobial host defenses is an important step forward in prevention of pathogen-induced morbidity and mortality in aquaculture setting. Like other vertebrates, macrophage-lineage cells are integral to fish immune responses and for this reason, much of the recent fish immunology research has focused on fish macrophage biology. These studies have revealed notable similarities as well as striking differences in the molecular strategies by which fish and higher vertebrates control their respective macrophage polarization and functionality. In this review, we address the current understanding of the biological mechanisms of teleost macrophage functional heterogeneity and immunity, focusing on the key cytokine regulators that control fish macrophage development and their antimicrobial armamentarium.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations176
Published2018
Admission routes2
Has abstractyes

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