Glutamine metabolism plays an essential role in cell growth, and glutamate dehydrogenase (GDH) is a key enzyme. GDH promotes the metabolism of glutamate and glutamine to generate ATP, which is profoundly increased in multiple human cancers. Through in vitro and in vivo experiments, we verified that the small-molecule GDH inhibitor EGCG slowed the progression of fibrosis by inhibiting GDH enzyme activity and glutamine metabolism. SIRT4 is a mitochondrial enzyme with NAD that promotes ADP ribosylation and downregulates GDH activity. The role of SIRT4 in liver fibrosis and the related mechanisms are unknown. In this study, we measured the expression of SIRT4 and found that it was downregulated in liver fibrosis. Modest overexpression of SIRT4 protected the liver from fibrosis by inhibiting the transformation of glutamate to 2-ketoglutaric acid (α-KG) in the tricarboxylic acid cycle (TCA), thereby reducing the proliferative activity of hepatic stellate cells (HSCs). Collectively, our study reveals that SIRT4 controls GDH enzyme activity and expression, targeting glutamine metabolism in HSCs and alleviating liver fibrosis.

Liver fibrosis is a reversible disease course caused by various liver injury etiologies, and it can lead to severe complications, such as liver cirrhosis, liver failure, and even liver cancer. Traditional pharmacotherapy has several limitations, such as inadequate therapeutic effect and side effects. Nanotechnology in drug delivery for liver fibrosis has exhibited great potential. Nanomedicine improves the internalization and penetration, which facilitates targeted drug delivery, combination therapy, and theranostics. Here, we focus on new targets and new mechanisms in liver fibrosis, as well as recent designs and development work of nanotechnology in delivery systems for liver fibrosis treatment.

Senescence of activated hepatic stellate cells (HSCs) is crucial for the regression of liver fibrosis. However, impaired immune clearance can result in the accumulation of senescent HSCs, exacerbating liver fibrosis. The activation of the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway is essential for both senescence and the innate immune response. Additionally, the specific delivery to activated HSCs is hindered by their inaccessible anatomical location, capillarization of liver sinusoidal endothelial cells (LSECs), and loss of substance exchange. Herein, we propose an antifibrotic strategy that combines prosenescence with enhanced immune clearance through targeted delivery of manganese (a cGAS-STING stimulator) via albumin-mediated transcytosis, specifically aimed at inducing senescence and eliminating activated HSCs in liver fibrosis. Our findings demonstrate that only albumin efficiently transfers manganese to activated HSCs from LSECs via transcytosis compared to liposomes, resulting in significant antifibrotic effects in vivo while exhibiting negligible toxicity.

Background and aims: There has been no reliable severity system based on the prognosis to guide therapeutic strategies for patients with pyrrolizidine alkaloid (PA)-induced hepatic sinusoidal obstruction syndrome (HSOS). We aimed to create a novel Drum Tower Severity Scoring (DTSS) system for these patients to guide therapy. Methods: 172 Patients with PA-HSOS who received supportive care and anticoagulation therapy in Nanjing Drum Tower Hospital from January 2008 to December 2020 were enrolled and analyzed retrospectively. These patients were randomized into a training or validation set in a 3:1 ratio. Next, we established and validated the newly developed DTSS system. Results: Analysis identified a predictive formula: logit (P) = 0.004 × aspartate aminotransferase (AST, U/L) + 0.019 × total bilirubin (TB, μmol/L) − 0.571 × fibrinogen (FIB, g/L) − 0.093 × peak portal vein velocity (PVV, cm/s) + 1.122. Next, we quantified the above variables to establish the DTSS system. For the training set, the area under the ROC curve (AUC) (n = 127) was 0.787 [95% confidence interval (CI) 0.706–0.868; p < 0.001]. With a lower cut-off value of 6.5, the sensitivity and negative predictive value for predicting no response to supportive care and anticoagulation therapy were 94.7% and 88.0%, respectively. When applying a high cut-off value of 10.5, the specificity was 92.9% and the positive predictive value was 78.3%. For the validation set, the system performed stable with an AUC of 0.808. Conclusions: The DTSS system can predict the outcome of supportive care and anticoagulation in PA-HSOS patients with satisfactory accuracy by evaluating severity, and may have potential significance for guiding therapy.