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Record W2081262528 · doi:10.3354/dao069197

Immunogen-dependent quantitative and qualitative differences in phagocytic responses of the circulating hemocytes of the lobster Homarus americanus

2006· article· en· W2081262528 on OpenAlexaff
Keiichiro Mori, JE Stewart

Bibliographic record

VenueDiseases of Aquatic Organisms · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicInvertebrate Immune Response Mechanisms
Canadian institutionsFisheries and Oceans CanadaBedford Institute of Oceanography
Fundersnot available
KeywordsHomarusBiologyPathogenMicrobiologyImmunogenAmerican lobsterImmunologyCrustaceanZoologyAntibody

Abstract

fetched live from OpenAlex

Phagocytic responses in circulating hemocytes of the lobster Homarus americanus were measured before and after treatment of lobsters with 2 different immunogens: (1) lipolysaccharide (LPS) or endotoxin from a non-pathogenic Pseudomonas perolens, and (2) a vancomycin/live Gram-positive pathogen (Aerococcus viridans [var.] homari) combination, essentially attenuated cells, shown previously to induce a high degree of resistance to this pathogen. The responses elicited by each of the immunogens were markedly different. Hemocytes drawn from LPS-treated lobsters showed significant, largely non-specific, increases in phagocytic responses over baseline values against sheep red blood cells and an array of test bacteria, with the notable exception of the pathogen. In marked contrast, induction with the vancomycin/live pathogen combination resulted in highly significant and specific increases in phagocytic responses to the pathogen and to the related, (but avirulent) strains of the pathogen, as well as inducing in the lobsters the usual high degree of resistance to the pathogen. These results suggest that quantitative and qualitative variations in phagocytic and resistance levels induced in at least 1 crustacean genus are determined largely by the particular characteristics of the immunogen.

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)0.001
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 score0.273
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.016
GPT teacher head0.254
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 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

Citations23
Published2006
Admission routes1
Has abstractyes

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