Abstract 5099: Adiponectin inhibits oxidative stress in prostate cancer cells
Bibliographic record
Abstract
Abstract INTRODUCTION AND OBJECTIVES: Emerging data suggest that obesity increases the risk of aggressive prostate cancer (PC) but the mechanisms underlying this relationship remain to be fully elucidated. Adiponectin, an adipocyte-specific hormone, circulates at relatively high levels in healthy human but its levels are reduced in obesity. Case control studies have documented an association between lower adiponectin blood levels and PC implying that obese individuals with low adiponectin levels are more susceptible in developing PC. In this study we examined the effect of adiponectin on the generation and reduction of oxidative stress (OS) in PC cells, a process that intimately relates to the initiation and development of PC. METHOD: As models we used two human PC cell lines (22rv1 and DU145) expressing the adiponectin receptors AdipoR1, AdipoR2 and T-cadherin. Cells were treated with increasing doses of human recombinant adiponectin (0-40μg/ml) and were subjected to the following tests: Quantification of cellular OS (NBT reduction assay), expression of catalase and MnSOD (Western blot analysis), comparison of transcript levels of NADPH oxidases (NOX) enzymes- a major source of reactive oxygen species in PC cells (RT-PCR) and determination of the global cellular anti-oxidative capacity and catalase activity (colorimetric assays). RESULT: Adiponectin significantly inhibited OS in both cell types in a dose dependent manner by inducing the expression of the two key anti-oxidative enzymes; catalase and MnSOD, leading to an increase in the anti-oxidative capacity of the cells. Treatment with adiponectin reduced Nox 2,4 mRNA expression in Du145 cells but increased it in 22RV1 cells. CONCLUSIONS: These results suggest a protective role for adiponectin against the initiation and development of PC, through OS inhibition. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 5099.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".