The Impact of Estrogen Deficiency on Liver Metabolism: Implications for Hormone Replacement Therapy
Bibliographic record
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD; previously nonalcoholic fatty liver disease) is the most common chronic liver condition globally. It affects 1 in 3 individuals and is associated with increased liver and cardiovascular mortality. MASLD is a sexually dimorphic condition, and in women the prevalence and severity of MASLD rises significantly following menopause. Preclinical data shows that lack of estrogen promotes multisystem metabolic dysfunction that is characteristic of MASLD. This not only includes hepatic lipid accumulation, insulin resistance, and fibrosis but also extra-hepatic metabolic processes in adipose and skeletal muscle. There are currently no available MASLD treatments tailored to women. The uptake of estrogen-based menopausal hormone replacement therapy (HRT) has seen a dramatic increase in recent years. Despite the changing attitudes toward HRT and the strong evidence base implicating estrogen deficiency in the development of MASLD, the impact of HRT on MASLD in postmenopausal women is poorly studied. In this review, we discuss the burden of MASLD in women, the effect of estrogen deficiency on the processes that drive MASLD development and progression, and the potential sex-specific therapeutic strategies that may prevent or limit MASLD development after menopause.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".