As metabolomics is widely used in the study of disease mechanisms, an increasing number of studies have found that metabolites play an important role in the occurrence of diseases. The aim of this study is to investigate the effects and mechanisms of quercetin in high-fat-sucrose diet (HFD)-induced nonalcoholic fatty liver disease (NAFLD) development using nontargeted metabolomics. A rat model of NAFLD was established by feeding with an HFD for 30 and 50 days. The results indicated quercetin exhibited hepatoprotective activity in 30-day HFD-induced NAFLD rats by regulating fatty acid related metabolites (adrenic acid, etc.), inflammation-related metabolites (arachidonic acid, etc.), oxidative stress-related metabolites (2-hydroxybutyric acid) and other differential metabolites (citric acid, etc.). However, quercetin did not improve NAFLD in the 50-day HFD; perhaps quercetin was unable to reverse the inflammation induced by a long-term high-fat diet. These data indicate that dietary quercetin may be beneficial to NAFLD in early stages. Furthermore, combining metabolomics and experimental approaches opens avenues to study the effects and mechanisms of drugs for complex diseases.

As metabolomics is widely used in the study of disease mechanisms, more and more studies have found that metabolites play an important role in the occurrence of diseases. The aim of this study is to investigate the effects and mechanisms of quercetin in high-fat-sucrose diet (HFD)-induced nonalcoholic fatty liver disease (NAFLD) development using nontargeted metabolomics. A rat model of NAFLD was established by feeding with a HFD for 30 and 50 days. Results indicated quercetin exhibited hepatoprotective activity in HFD-induced NAFLD rats in 30 days by regulating fatty acids related metabolites (adrenic acid, etc.), inflammation related metabolites (arachidonic acid, etc.), oxidative stress related metabolites (2-hydroxybutyric acid) and other differential metabolites (citric acid, etc.). However, quercetin couldn’t improve NAFLD in 50 days maybe it couldn’t reverse the inflammation condition induced by long-term high-fat diet. These data indicate that dietary quercetin may be beneficial to NAFLD at early stages. Furthermore, combining metabolomics and experimental approaches opens up avenues of effects and mechanisms of drugs for complex diseases.

Multiple myeloma (MM) is a hematological tumor characterized by the malignant proliferation of plasma cells in bone marrow (BM). Despite the prolonged survival of MM patients, a significant amount of patients relapse or become drug resistant. This underlines the importance of the development and investigation of novel targets to improve MM therapy. Increasing evidences have shed light on the emerging roles of E3 ubiquitin ligases in MM. E3 ubiquitin ligases play an essential role in protein ubiquitination, which is involved in the regulation of protein degradation, protein-protein interactions and signal transduction. In this comprehensive review, we will summarize the current understanding of E3 ubiquitin ligases in MM and their contribution to MM therapy, which could help explore the molecular mechanisms in MM and provide potential therapeutic targets for the treatment of MM.

Because of the absence of the time course of histological nonalcoholic fatty hepatitis with subsequent fibrotic progression, the effective approaches available for controlling the onset and progression of non-alcoholic steatohepatitis (NASH) remain limited. Therefore, we detected the serum and liver tissue related lipid metabolism disorder, liver pathology and relative molecular makers alteration dynamically in a high fat-sucrose diet during different time points. High fat-sucrose diet significantly increased the serum lipid level on day 10. The excess lipid accumulation in liver was referred to as simple steatosis after the feeding of a high fat-sucrose diet for 20 days. The high fat-sucrose diet induced a hepatic inflammation response on day 30. Similarly, hepatic fibrosis was also initiated on day 30 and gradually formed from the 30th to the 50th day. Oxidative stress may be related with the process from NASH to liver fibrosis. Insulin resistance was involved in the progression from hepatic steatosis to NASH with hepatic fibrosis from the 20th to the 50th day. In conclusion, we established a high fat-sucrose diet induced nonalcoholic fatty hepatitis with liver fibrosis rat model, which presented the time course of histological nonalcoholic steatohepatitis and the initiation and progression change of characteristic molecular makers in the process from steatosis to hepatic fibrosis.

Introduction Infection is a common and potentially fatal complication during the treatment of hematological diseases, particularly in the context of chemotherapy-induced immunosuppression. The nonselective use of antibiotic prophylaxis in patients with neutropenia in China has persistently accelerated antimicrobial resistance. Early identification of patients at high risk for infection before clinical symptom onset could enable targeted preventive strategies; however, reliable and biologically informed screening approaches remain limited. Methods We developed a prediction model for infection risk stratification in newly diagnosed patients with hematological conditions. Plasma metagenomic next-generation sequencing was performed in a prospective cohort of 230 patients. Among them, 116 patients provided prechemotherapy, non-neutropenic plasma samples (cohort A), and 114 patients provided postchemotherapy, neutropenic samples (cohort B). Microbial community profiles were analyzed, and machine learning approaches were applied to construct classifiers for neutropenia status and subsequent infection risk. Results Plasma metagenomic profiling revealed a complex microecological landscape in patients with hematological conditions and identified distinct microbial features associated with neutropenia. A trained random forest classifier successfully distinguished patients without neutropenia from patients with neutropenia, achieving an area under the receiver operating characteristic curve of 0.8324. Importantly, a microorganism-based random forest model was established to predict patients at high risk of infection, yielding an area under the curve of 0.942. Nested cross-validation demonstrated high classification accuracy, correctly identifying 99.1% of patients who subsequently developed infections and 72.7% of patients who remained infection-free. Furthermore, integration of microbial features with clinical metrics improved predictive performance, resulting in an area under the curve of 0.953. Conclusions This microorganism-based prediction model provides an effective tool for infection risk stratification in patients with hematological conditions. By enabling early identification of high-risk individuals, the model has potential clinical utility for guiding precise preventive interventions and optimizing infection management strategies, which can significantly reduce the use of prophylactic antibiotics, thereby mitigating the development of resistance. Registration number: ChiCTR2100042992.