Non-alcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease and is closely associated with metabolic diseases such as obesity, type 2 diabetes mellitus (T2DM), and metabolic syndrome. However, effective treatment strategies for NAFLD are still lacking. In recent years, progress has been made in understanding the pathogenesis of NAFLD, identifying multiple therapeutic targets and providing new directions for drug development. This review summarizes the recent advances in the treatment of NAFLD, focusing on the mechanisms of action of natural products, small-synthetic-molecule drugs, and combination therapy strategies. This review aims to provide new insights and strategies in treating NAFLD.

Diacylglycerol kinases (DGKs) are crucial lipid-signaling enzymes that convert diacylglycerol (DAG) into phosphatidic acid (PA) through phosphorylation. This reaction modulates the DAG–PA axis, which is central to signal transduction, metabolic homeostasis, and immune responses. Mammals express ten DGK isoforms, classified into five subtypes on the basis of their structural features. These isoforms exhibit subtype-specific characteristics and distinct subcellular localization patterns, underpinning their diverse physiological functions. Accumulating evidence implicates DGKs in the pathogenesis of metabolic disorders, cancer, and cardiovascular and neurological diseases, where they may play either pathogenic or protective roles depending on the cellular context. This isoform-specific functionality renders DGKs promising yet underexploited therapeutic targets. Notably, one DGKζ inhibitor (ASP1570) has entered clinical trials, while other candidates, such as DGKα inhibitors (e.g., CU-3), remain at the preclinical stage. This review systematically summarizes the structural classification, catalytic mechanisms, and pathological roles of DGKs, with a particular emphasis on therapeutic targeting strategies and the associated technical challenges.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease associated with disrupted lipid metabolism. This study aimed to uncover novel molecular subtypes and biomarkers by integrating sphingolipid metabolism-related genes (SMGs) with machine learning approaches. Using data from the GEO and GeneCards databases, 29 UC-related SMGs were identified. Consensus clustering was employed to define distinct molecular subtypes of UC, and a diagnostic model was developed through various machine learning algorithms. Further analyses—including functional enrichment, transcription factor prediction, single-cell localization, potential drug screening, molecular docking, and molecular dynamics simulations—were conducted to investigate the underlying mechanisms and therapeutic prospects of the identified genes in UC. The analysis revealed two molecular subtypes of UC: C1 (metabolically dysregulated) and C2 (immune-enriched). A diagnostic model based on three key genes demonstrated high accuracy in both the training and validation cohorts. Moreover, the transcription factor FOXA2 was predicted to regulate the expression of all three genes simultaneously. Notably, mebendazole and NVP-TAE226 emerged as promising therapeutic agents for UC. In conclusion, SMGs are integral to UC molecular subtyping and immune microenvironment modulation, presenting a novel framework for precision diagnosis and targeted treatment of UC.

Acute pancreatitis (AP) can be mild and self-limited, but it can also become severe acute pancreatitis (SAP) and lead to multi-organ dysfunction. It is still difficult to identify patients who may develop severe disease at an early stage. Lactate was once viewed only as a metabolic byproduct, but recent work shows that it also acts as a signaling molecule that links cellular energy status with immune control. Its role in the progression of AP is still not clear. Transcriptomic analysis showed clear differences in metabolism and immune features between SAP and non-severe AP (NSAP). Among lactate-related genes (LRGs), 24 were expressed at different levels. Three machine-learning methods identified CCNA2 and H2BC5 as possible diagnostic markers. Both genes had higher expression in SAP clinical samples. In vitro experiments showed that adding lactate increased CCNA2 and H2BC5 expression and raised inflammatory cytokine production. When these genes were knocked down, the inflammatory response decreased. This suggests that both genes are involved in lactate-driven inflammatory signaling. Molecular docking and simulation showed that the MDM2 inhibitor AMG-232 binds strongly to CCNA2, and the mTOR inhibitor Torin-1 binds strongly to H2BC5. Functional tests showed that Torin-1 reduced inflammation and oxidative stress in a sodium-taurocholate–induced cell model. This study shows that CCNA2 and H2BC5 are candidate biomarkers for SAP. They are involved in important immune and metabolic pathways. AMG-232 and Torin-1 are possible therapeutic drugs. These findings give a molecular framework for early risk detection in AP and point to new options for targeted treatment. The online version contains supplementary material available at 10.1186/s13036-025-00605-w.

Environmental cadmium (Cd) pollution poses a severe threat to human health due to its strong bioaccumulation and high carcinogenicity. Although Cd exposure has been linked to various cancers, its specific role in pancreatic cancer (PC) remains unclear. This study aimed to explore the molecular mechanisms underlying Cd-associated PC and identify potential diagnostic and therapeutic targets. Transcriptomic data of PC were obtained from the GEO database to screen differentially expressed genes (DEGs), which were then intersected with Cd-related genes retrieved from the Comparative Toxicogenomics Database (CTD). Functional enrichment analyses, including GO and KEGG, were conducted to identify key biological processes and pathways. Multiple machine learning algorithms were used to construct a diagnostic model and identify hub genes. Furthermore, molecular docking and molecular dynamics simulations were performed to evaluate drug-target interactions, and in vitro experiments were used to validate the effects of Cd exposure on PC cell proliferation and invasiveness. A total of five key genes-FN1, COL5A1, AHR, COL3A1, and TIMP1-were identified as core regulators of Cd-associated PC. Functional analyses indicated that Cd primarily affects the extracellular matrix (ECM) metabolic and collagen remodeling pathways. Experimental results confirmed that Cd exposure significantly enhanced the proliferation and invasiveness of PC cells. Molecular docking and dynamics simulations revealed that the EGFR inhibitor dacomitinib exhibited favorable predicted binding affinity to FN1, suggesting its potential as a therapeutic agent. This study reveals that Cd may promote the malignant progression of PC by regulating ECM remodeling through key genes such as FN1. Dacomitinib shows promise as an FN1-associated therapy, offering new insights for the precise prevention and treatment of Cd-associated PC.