GSK3β‐Regulated Lipolysis is Required for Histone Acetylation and Decidualization in Early Pregnancy
Bibliographic record
Abstract
Decidualization, a highly programmed differentiation process of the uterine stroma, is characterized by significant biochemical remodeling and is essential for pregnancy. However, the functions and molecular mechanisms of lipid metabolism during decidualization remain poorly understood. In this study, a dynamic process of lipid droplet synthesis and degradation is observed during decidual progression, and GSK3 is identified as a potential regulator for lipolysis. Specifically, lipolysis is inhibited in uterine Gsk3b knockout mice, leading to impaired terminal differentiation of decidual cells. Mechanistically, GSK3β promots phosphorylation-dependent lysosomal degradation of RNF213, which permits the localization of adipose triglyceride lipase (ATGL) on lipid droplets, thereby facilitating lipolysis. Furthermore, fatty acids released from lipolysis enter the mitochondria to undergo β-oxidation and produce acetyl-CoA. The inhibition of lipolysis caused by GSK3β deficiency leads to a reduction in acetyl-CoA levels, which in turn epigenetically affects gene transcription through histone acetylation. This study provided evidence for the regulation of dynamic lipid metabolism in vivo, and its influences on gene transcription for decidualization, which emphasized the critical role of metabolic modulation in uteri during early pregnancy.
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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".