Phenolic Compounds from Haskap Berries Have Structure, Combination, and Cell Line-Dependent Impacts on the Longevity-Associated Deacetylase Sirtuin 1
Bibliographic record
Abstract
It is well established that phenolic compounds from plant sources impact readouts of cell health such as reduced radical and reactive oxygen species. However, it is unclear if specific phenolic structures impact other cellular processes or proteins, such as the evolutionary conserved deacetylase Sirtuin 1 (SIRT1), and if phenolic combinations interact synergistically to do so. We observed that structurally diverse haskap berry phenolics (caffeic acid, cyanidin, kaempferol-3-O-glucoside, and gentisic acid) differentially impacted normal primary human fibroblast growth, which has been linked to SIRT1. These results were consistent with previous work from our lab indicating that haskap phenolic extracts/fractions impact human cell growth via SIRT1-dependent mechanisms. Therefore, we furthered the investigation into SIRT1 and phenolic structure and observed that the individual phenolics or their combinations had no observable impact on SIRT1 transcript abundance or cellular localization. We also observed that select phenolics decreased SIRT1 protein abundance and increased SIRT1 activity. The catechol-containing phenolics outperformed those that lack a catechol group, indicating potential structure-dependent impact(s). Potential synergy between the specific phenolics analyzed was observed in Western blot, and potential antagonism was identified in the SIRT1 activity assay. Results were concomitant with the presence of different phenolic structures, phenolic combinations, and cell type (sex and/or individual differences). These results highlight the possible significance of the catechol structure and indicate that phenolics have the potential to impact cell processes, which the authors hypothesize to be due to mechanisms that are independent of antioxidant activity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".