Gene Expression Profiling in Mouse Embryonic Stem Cells Reveals Glycogen Synthase Kinase-3-Dependent Targets of Phosphatidylinositol 3-Kinase and Wnt/β-Catenin Signaling Pathways
Bibliographic record
Abstract
Glycogen synthase kinase-3 (Gsk-3) activity is an important regulator of numerous signal transduction pathways. Gsk-3 activity is the sum of two largely redundant proteins, Gsk-3α and Gsk-3β, and in general, Gsk-3 is a negative regulator of cellular signaling. Genetic deletion of both Gsk-3α and Gsk-3β in mouse embryonic stem cells (ESCs) has previously been shown to lead to the constitutive activation of the Wnt/β-catenin signaling pathway. However, in addition to Wnt signaling, all Gsk-3-regulated pathways, such as insulin signaling, are also affected simultaneously in Gsk-3α(-) (/) (-); Gsk-3β(-) (/) (-)ESCs. In an effort to better understand how specific signaling pathways contribute to the global pattern of gene expression in Gsk-3α(-) (/) (-); Gsk-3β(-) (/) (-)ESCs, we compared the gene expression profiles in Gsk-3α(-) (/) (-); Gsk-3β(-) (/) (-) ESCs to mouse ESCs in which either Wnt/β-catenin signaling or phosphatidylinositol 3-kinase (PI3K)-dependent insulin signaling are constitutively active. Our results show that Wnt signaling has a greater effect on up-regulated genes in the Gsk-3α(-) (/) (-); Gsk-3β(-) (/) (-)ESCs, whereas PI3K-dependent insulin signaling is more responsible for the down-regulation of genes in the same cells. These data show the importance of Gsk-3 activity on gene expression in mouse ESCs, and that these effects are due to the combined effects of multiple signaling pathways.
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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) | 0.001 | 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".