A fucose containing polymer-rich fraction from the brown alga Ascophyllum nodosum mediates lifespan increase and thermal-tolerance in Caenorhabditis elegans, by differential effects on gene and protein expression
Bibliographic record
Abstract
The extracts of the brown alga, Ascophyllum nodosum, which contains several bioactive compounds, have been shown to impart biotic and abiotic stress tolerance properties when consumed by animals. However, the physiological, biochemical and molecular mechanism underlying such effects remain elusive. We investigated the effect of A. nodosum fucose-containing polymer (FCP) on tolerance to thermally induced stress using the invertebrate animal model, Caenorhabditis elegans. FCP at a concentration of 150 μg mL(-1) significantly improved the life span and tolerance against thermally induced stress in C. elegans. The treatment increased the C. elegans survival by approximately 24%, when the animals were under severe thermally induced stress (i.e. 35 °C) and 27% under mild stress (i.e. 30 °C) conditions. The FCP induced differential expression of genes and proteins is associated with stress response pathways. Under thermal stress, FCP treatment significantly altered the expression of 65 proteins (54 up-regulated & 11 down-regulated). Putative functional analysis of FCP-induced differential proteins signified an association of altered proteins in stress-related molecular and biochemical pathways of the model worm.
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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".