THE EFFECT OF RESVERATROL AND ZINC ON INTRACELLULAR ZINC STATUS IN NHPrE CELLS
Bibliographic record
Abstract
To evaluate the influence of resveratrol on cellular zinc status, normal human prostate epithelial (NHPrE) cells were treated in 6 levels of resveratrol (0, 0.5, 1, 2.5, 5 and 10 µM) and 4 levels of zinc [0, 4, 16 and 32 µM or zinc deficient (ZD), zinc normal (ZN), zinc adequate (ZA) and zinc supplemented (ZS), respectively]. Among each zinc treatment, a progressive reduction in cell growth or increase in cellular total zinc was observed with increases of resveratrol from 2.5, 5 and 10 µM or from 5 and 10 µM, respectively. In ZS cells, a much higher increase in cellular total zinc was observed as early as 1 µM resveratrol. A flow cytometry study revealed that the resveratrol (10 µM) induced G2/M arrest was responsible for the depressed cell growth. Data from an in vitro experiment using zinquin, as an indicator of intracellular free Zn(II) status, demonstrated complex formation between resveratrol and zinc ion. Zinquin ethyl ester fluorescence spectrofluorimetry and microscope imaging revealed that intracellular labile free zinc decreased in ZD and ZN NHPrE cells but increased in high zinc (ZA and ZS) cells. Furthermore, increases in cellular zinc status induced enhanced levels of reactive oxygen species (ROS) as well as senescence detected by morphological and histochemical changes in cells treated with 2.5 or 10 µM resveratrol, especially in ZA and ZS cells. Thus, increases in free labile zinc may induce ROS and senescence. Grant Funding Source UNIV. MARYLAND
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".