Liver Sinusoidal Endothelial Cells and Their Regulation of Immunology, Collagenization, and Bioreactivity in Fatty Liver: A Narrative Review
Bibliographic record
Abstract
Liver sinusoidal endothelial cells (LSECs) are essential for preserving liver homeostasis. Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses a category of hepatic disorders characterized by excessive fat accumulation in the liver, known as steatosis. Over time, accumulated hepatic fat can induce inflammation of the liver (hepatitis). MASLD is among the most prevalent types of chronic liver disease. Obesity and Type 2 diabetes mellitus (T2DM) are frequent etiological factors of MASLD. In the absence of therapy, MASLD can lead to more severe hepatic conditions, which can be life-threatening. MASLD is noteworthy due to its potential progression to MASH and further severe liver impairment, including cirrhosis and hepatocellular carcinoma (HCC), a neoplastic progression. This narrative review examines the distinctive functions of LSECs in regulating immunologic responses, collagenization, and drug-sensitive bioreactivity in healthy livers, MASLD, and metabolic dysfunction-associated steatohepatitis (MASH), as well as in a human primary 3D model. We found that LSECs serve as crucial regulators of immunological equilibrium in the liver by inhibiting disproportionate immunologic activation, concurrently filtering tissue antigens, and engaging with immunologic cells, such as Kupffer cells (KCs) and T lymphocytes. In chronic diseases of the liver, LSECs experience cellular dysfunction, resulting in capillarization (focal to diffuse), loss of fenestrations (fenestrae), and the activation of pro-fibrotic signaling pathways, including transforming growth factor-beta (TGF-β). Indeed, TGF-β is crucial in activating hepatic stellate cells (HSCs), a process that facilitates the progression of liver disease toward fibrosis. In addition to examining the dynamic interplay between LSECs, specifically HSCs, and other liver cells throughout the progression of fatty liver–MASH, we suggest that LSECs may become a potential therapeutic target for modifying immune responses and averting fibrosis in hepatic disorders. The limitations of animal models are also highlighted and discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".