A novel toll-like receptor from Crassostrea gigas is involved in innate immune response to Vibrio alginolyticus
Bibliographic record
Abstract
Based on previous reports，toll-like receptors (TLRs) are recognition molecules common in various aquatic animals and play a vital role in innate immunity. In this study, a novel TLR CgToll-3 with leucine-rich repeats (LRRs) and a TIR (Toll-interleukin 1-resistance) domain was cloned in Crassostrea gigas. CgToll-3 with sixteen potential extracellular N-linked glycosylation sites and shares the closest phylogenic relationship with molluscan TLRs. Alignment of LRRs and TIR domains indicated that CgToll-3 was highly conserved compared to other LRRs of mollusks which could respond against Vibrio or other bacterial molecules, and contained three conserved functionally important motifs (Box 1, Box 2, and Box 3). The Hex Molecular Docking result showed that CgToll-3 could interact with CgMyd88 via the TIR domain. Subcellular Co-localization and BiFC Assay confirmed this interaction, and they could induce NF-κB activation. CgToll-3 was moderately expressed in the digestive gland, and its expression level was significantly up-regulated after Vibrio alginolyticus challenge. Taken together, CgToll-3 might be involved in the innate immune response to V. alginolyticus for C. gigas through a MyD88-dependent TLR mediated signaling pathway.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".