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Record W4410799731 · doi:10.1016/j.jbc.2025.110304

Mannose-modified hemocyanin enhances pathogen endocytosis by crustacean hemocytes

2025· article· en· W4410799731 on OpenAlexaff
Jiaxi Li, Jude Juventus Aweya, Mingming Zhao, Yongzhen Zhao, Zhongyang Lin, Xiuli Chen, Zhihong Zheng, Peifeng Li, Defu Yao, Yueling Zhang

Bibliographic record

VenueJournal of Biological Chemistry · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicInvertebrate Immune Response Mechanisms
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersScience and Technology Major Project of GuangxiNational Natural Science Foundation of China
KeywordsHemocyaninEndocytosisMannoseCrustaceanPathogenBiologyCell biologyBiochemistryChemistryMicrobiologyEcologyReceptorImmunologyAntibody

Abstract

fetched live from OpenAlex

In crustaceans, hemolymph plasma contains more than 90% hemocyanin, whereas hemocytes have minimal levels, suggesting a regulated uptake mechanism. Here, we demonstrate that in Penaeus vannamei, hemocytes internalize plasma hemocyanin under normal conditions via phagocytosis, clathrin-mediated endocytosis, and micropinocytosis. This uptake is significantly enhanced during bacterial (Vibrio parahaemolyticus, Vibrio alginolyticus, Staphylococcus aureus, Streptococcus iniae) and viral (White spot syndrome virus) infections or upon stimulation with pathogen-associated molecular patterns. While post-translational modifications (PTMs) such as dephosphorylation, deacetylation, and mannosylation enhance hemocyanin's pathogen-binding affinity, only mannosylation promotes mannose receptor-mediated endocytosis for intracellular clearance, whereas dephosphorylation and deacetylation facilitate extracellular pathogen elimination. These findings reveal that hemocyanin functions beyond oxygen transport, acting as an immune effector that undergoes PTMs to enhance intracellular pathogen clearance.

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 categoriesInsufficient payload (model declined to judge)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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.

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

Citations3
Published2025
Admission routes1
Has abstractyes

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