Metabolomic Profiling of Equine Cord Blood Mesenchymal Stromal Cells in Both Early and Late Stages of Culture
Bibliographic record
Abstract
Abstract Introduction: Equine Mesenchymal Stromal Cells (MSC) hold great potential as a future form of cellular therapy. Fetal Bovine Serum (FBS) is used as a supplement MSC culture, but challenges with its use have initiated a desire to create a defined media to expand these cells. MSCs have shown great variability in species, tissue source and passage number. Due to this, to effectively create a replacement for FBS we must better understand how it meets the metabolic needs for each type of MSC. Objectives: The goal of this study is to determine key pathways and differences in pathways between the early and late passages of equine cord blood MSCs. Methods: This study utilized metabolomics to give a snapshot of the metabolism in the long-term culture of equine cord blood MSCs (eCB-MSC) by comparing the profile of plain culture media to spend media. Results: We found two significantly different metabolites between the early and late passage of eCB-MSC, alpha-ketoglutaric acid (p = 0.019) and creatine (p = 0.012). As well, the metabolic results allowed us to perform an enrichment analysis to assess which pathway(s) were most relevant. Conclusion: The two metabolites suggest a difference in metabolism between the early and late passage reflecting different cellular priorities. Insights into the unique metabolism of these cells and how the requirement of the cell differs between the early and late passage may allow the formulation a serum free media tailored to the metabolic needs of eCB-MSC.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".