Masculinized and feminized physiological cell culture media
Bibliographic record
Abstract
Cell culture is an important tool in molecular and cellular physiology. Recently, culture media (e.g. HPLM, Plasmax) modeled after the human blood plasma metabolome have been developed. However, these media are agnostic to biological sex. Generally, sex is often ignored as a variable in cell biology. To effectively include biological sex as a variable in cell culture, media could be developed to reproduce male-like or female-like blood plasma. To address this, we gathered data on the concentrations of 86 plasma metabolites, measured in healthy human adults of both sexes. A meta-analysis of the data indicated that mean concentrations of many amino acids, and a number of other metabolically significant metabolites, are significantly different between males and females. Similarly, a range of steroid hormones also differend significantly. We formulated a ‘masculinized’ and a ‘feminized’ cell culture media based on these values and use these media to culture Molt-4 and Loucy cell lines, which are male and female T-lymphoblast lines, respectively. These experiments are ongoing and will include RNAseq analyses to identify gene expression differences, as well as metabolic assays. Nonetheless, we already have sufficient insight into the male and female plasma metabolomes to understand that, as we move forward with more physiological cell culture approaches, the impact of biological sex must be considered. Natural Science and Engineering Research Council of Canada This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".