Characterization and ligand binding properties of a fatty acid- and retinol- binding protein (Hp-FAR-2) from Heligmosomoides polygyrus
Bibliographic record
Abstract
Parasitic nematodes are major pathogens of humans, animals, and plants, contributing to global health challenges and substantial agricultural losses. Fatty acid- and retinol-binding proteins (FARs), secreted by parasitic nematodes, are believed to play key roles in host-pathogen interactions, including immune modulation and nutrient acquisition. In this study, we characterize a FAR protein from the gastrointestinal nematode Heligmosomoides polygyrus, Hp-FAR-2. Hp-FAR-2, unlike FARs from Caenorhabditis elegans, Steinernema carpocapsae, and Ancylostoma ceylanicum, did not influence immunity or survival in a Drosophila melanogaster infection model, suggesting functional divergence within the FAR family. Competitive lipid-binding assays revealed a preference for omega-3 and omega-6 polyunsaturated fatty acids, indicating selective binding to bioactive lipids that may modulate immunity. Using RAW 264.7 macrophages, we found that Hp-FAR-2 suppresses the expression of both M1-associated (TNF-α, IL-6) and M2-associated (Chil3) markers during polarization, implicating it as a broad immunomodulator that may inhibit inflammatory responses and tissue repair mechanisms to promote chronic infection. Our findings support a model in which Hp-FAR-2 disrupts host lipid signaling and immune function to favor parasite persistence, suggesting its potential role in the excretory/secretory products of H. polygyrus. These findings enhance our understanding of FAR-mediated host manipulation and may inform the development of novel anthelmintic or immunoregulatory therapies.
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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 | 0.000 |
| 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) | 0.000 | 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".