Lactate Accelerates Mouse ES Cell Differentiation Towards the XEN Lineage
Bibliographic record
Abstract
Summary Metabolism plays a crucial role for cell survival and function; however, recent evidence has implicated it in regulating embryonic development. The inner cell mass undergoes orchestrated cellular divisions resulting in the formation of embryonic stem cells and extraembryonic endoderm (XEN) cells. Concomitantly, changes in the metabolic profile occurs during development and are well-documented in the embryonic lineages. However, a comprehensive multi-omics analysis of these features in XEN cells remains lacking. We observed that feeder-free XEN cells exhibited high sensitivity to glycolytic inhibition in addition to maintaining elevated intra- and extracellular lactate levels. XEN cells maintain high lactate levels by increased LDHA activity and re-routing pyruvate away from the mitochondria. Importantly, exogenous lactate supplementation or promoting intracellular lactate accumulation enhances XEN differentiation in vitro . Our results highlight how lactate contributes to XEN differentiation in the mammalian embryo and may serve to enhance reprogramming efficiency of cells used for regenerative medicine. Highlights Feeder-free XEN cells exhibit high sensitivity to glycolytic inhibition Distinct transcriptomic, proteomic and metabolomic profile exists between feeder-free ES and XEN cells Elevated intracellular and extracellular lactate is observed in feeder-free XEN cells Lactate enhances feeder-free XEN differentiation in vitro
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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 | 0.001 |
| 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".