Components of the Cultivated Red Seaweed Chondrus crispus Enhance the Immune Response of Caenorhabditis elegans to Pseudomonas aeruginosa through the <i>pmk-1</i> , <i>daf-2/daf-16</i> , and <i>skn-1</i> Pathways
Bibliographic record
Abstract
Marine macroalgae are rich in bioactive compounds that can, when consumed, impart beneficial effects on animal and human health. The red seaweed Chondrus crispus has been reported to have a wide range of health-promoting activities, such as antitumor and antiviral activities. Using a Caenorhabditis elegans infection model, we show that C. crispus water extract (CCWE) enhances host immunity and suppresses the expression of quorum sensing (QS) and the virulence factors of Pseudomonas aeruginosa (strain PA14). Supplementation of nematode growth medium with CCWE induced the expression of C. elegans innate immune genes, such as irg-1, irg-2, F49F1.6, hsf-1, K05D8.5, F56D6.2, C29F3.7, F28D1.3, F38A1.5 ZK6.7, lys-1, spp-1, and abf-1, by more than 2-fold, while T20G5.7 was not affected. Additionally, CCWE suppressed the expression of PA14 QS genes and virulence factors, although it did not affect the growth of the bacteria. These effects correlated with a 28% reduction in the PA14-inflicted killing of C. elegans. Kappa-carrageenan (K-CGN), a major component of CCWE, was shown to play an important role in the enhancement of host immunity. Using C. elegans mutants, we identified that pmk-1, daf-2/daf-16, and skn-1 are essential in the K-CGN-induced host immune response. In view of the conservation of innate immune pathways between C. elegans and humans, the results of this study suggest that water-soluble components of C. crispus may also play a health-promoting role in higher animals and humans.
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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) | 0.001 | 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".