How Supraphysiological Oxygen Levels in Standard Cell Culture Affect Oxygen‐Consuming Reactions
Bibliographic record
Abstract
Most mammalian tissue cells experience oxygen partial pressures in vivo equivalent to 1–6% O 2 (i.e., physioxia). In standard cell culture, however, headspace O 2 levels are usually not actively regulated and under these conditions are ~18%. This drives hyperoxia in cell culture media that can affect a wide variety of cellular activities and may compromise the ability of in vitro models to reproduce in vivo biology. Here, we review and discuss some specific O 2 ‐consuming organelles and enzymes, including mitochondria, NADPH oxidases, the transplasma membrane redox system, nitric oxide synthases, xanthine oxidase, and monoamine oxidase with respect to their sensitivities to O 2 levels. Many of these produce reactive oxygen and/or nitrogen species (ROS/RNS) as either primary end products or byproducts and are acutely sensitive to O 2 levels in the range from 1% to 18%. Interestingly, many of them are also transcriptional targets of hypoxia‐inducible factors (HIFs) and chronic cell growth at physioxia versus 18% O 2 may alter their expression. Aquaporins, which facilitate hydrogen peroxide diffusion into and out of cells, are also regulated by HIFs, indicating that O 2 levels may affect intercellular communication via hydrogen peroxide. The O 2 sensitivities of these important activities emphasize the importance of maintaining physioxia in culture.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".