Physioxic human cell culture improves viability, metabolism, and mitochondrial morphology while reducing DNA damage
Bibliographic record
Abstract
ABSTRACT Multicellular organisms balance oxygen delivery and toxicity by having oxygen pass through several barriers before cellular delivery. In human cell culture, these physiologic barriers are removed, exposing cells to higher oxygen levels. Human cells cultured in ambient air may appear normal, but this is difficult to assess without a comparison at physiologic oxygen. Here, we examined the effects of culturing human cells throughout the spectrum of oxygen availability on oxidative damage to macromolecules, viability, proliferation, the antioxidant and DNA damage responses, metabolism, and mitochondrial fusion and morphology. We surveyed 4 human cell lines cultured for 3 d at 7 oxygen conditions between 1 and 21% O 2 . We show that oxygen levels and cellular benefit are not inversely proportional, but the benefit peaks within the physioxic range. Normoxic cells are in a perpetual state of responding to damaged macromolecules and mitochondrial networks relative to physioxic cells, which could compromise an investigation. These data contribute to the concept of an optimal oxygen availability for cell culture in the physioxic range where the oxygen is not too high to reduce oxidative damage, and not too low for efficient oxidative metabolism, but just right: the Goldiloxygen zone.—Timpano, S., Guild, B. D., Specker, E. J., Melanson, G., Medeiros, P. J., Sproul, S. L. J., Uniacke, J. Physioxic human cell culture improves viability, metabolism, and mitochondrial morphology while reducing DNA damage. FASEB J. 33, 5716–5728 (2019). www.fasebj.org
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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) | 0.003 | 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".