Racial Differences in Oxidative Stress and Inflammation: <i>In Vitro</i> and <i>In Vivo</i>
Bibliographic record
Abstract
African American race is an independent risk factor for enhanced oxidative stress and inflammation. We sought to examine whether oxidative-stress and inflammatory markers that are typically measured in humans also differ by race in cell culture. We compared levels between African American and Caucasian young adults and then separately in human umbilical vein endothelial cells (HUVECs) from both races. We found heightened oxidative stress and inflammation in the African Americans both in vitro and in vivo. African American HUVECs showed higher nitric oxide (NO) levels (10.8 ± 0.4 vs. 8.8 ± 0.7 μmol/L/mg, p = 0.03), Interleukin-6 (IL-6) levels (61.7 ± 4.2 vs. 23.9 ± 9.0 pg/mg, p = 0.02), and lower superoxide dismutase activity (15.6 ± 3.3 vs. 25.4 ± 2.8 U/mg, p = 0.04), and also higher protein expression (p < 0.05) of NADPH oxidase subunit p47phox, isoforms NOX2 and NOX4, endothelial nitric oxide synthase (NOS), inducible NOS, as well as IL-6. African American adults had higher plasma protein carbonyls (1.1 ± 0.1 vs. 0.8 ± 0.1 nmol/mg, p = 0.01) and antioxidant capacity (2.3 ± 0.2 vs. 1.1 ± 0.3 mM, p = 0.01). These preliminary translational data demonstrate a racial difference in HUVECs much like that in humans, but should be interpreted with caution given its preliminary nature. It is known that racial differences exist in how humans respond to development and progression of disease, therefore these data suggest that ethnicity of cell model may be important to consider with in vitro clinical research.
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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) | 0.002 | 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".