Media composition and O<sub>2</sub> levels determine effects of 17β-estradiol and selective estrogen receptor modulators on mitochondrial bioenergetics and cellular reactive oxygen species
Bibliographic record
Abstract
Estradiol (E2) and selective estrogen receptor modulators (SERMs) have broad-ranging cellular effects that include mitochondrial respiration and reactive oxygen species (ROS) metabolism. Many of these effects have been studied using cell culture models. Recent advances have revealed the extent to which cellular metabolism is affected by the culture environment. Cell culture media with metabolite composition similar to blood plasma [e.g., Plasmax, Human Plasma-Like Medium (HPLM)] alter cellular behaviors including responses to drugs. Similar effects have been observed with respect to O2 levels in cell culture. Given these observations, we investigated whether the effects of E2 and SERMs are also influenced by media composition and O2 level during cell culture experiments. We analyzed mitochondrial network characteristics, cellular oxidative metabolism, and H2O2 production in C2C12 myoblasts growing in physiological (5%) or standard cell culture (18%)O2 and in physiological (Plasmax) or standard cell culture [Dulbecco’s modified Eagle’s medium (DMEM)] media. Although E2 significantly lowered H2O2 production from cells growing in 18% O2/DMEM (standard cell culture), it had no effect on cells growing in Plasmax. Moreover, culture conditions significantly altered the effects of E2 and SERMs on mitochondrial abundance and network characteristics. These results indicate that the effects of E2 and SERMs on various aspects of cell physiology strongly depends on growth conditions, which in turn emphasizes the need to consider this carefully in cell culture experiments.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".