Metabolism-associated fatty liver disease (MAFLD), a growing health problem worldwide, is one of the major risks for the development of cirrhosis and liver cancer. Oral administration of nobiletin (NOB), a natural citrus flavonoid, modulates the gut microbes and their metabolites in mice. In the present study, we established a mouse model of MAFLD by subjecting mice to a high-fat diet (HFD) for 12 weeks. Throughout this timeframe, NOB was administered to investigate its potential benefits on gut microbial balance and bile acid (BA) metabolism using various techniques, including 16S rRNA sequencing, targeted metabolomics of BA, and biological assays. NOB effectively slowed the progression of MAFLD by reducing serum lipid levels, blood glucose levels, LPS levels, and hepatic IL-1β and TNF-α levels. Furthermore, NOB reinstated diversity within the gut microbial community, increasing the population of bacteria that produce bile salt hydrolase (BSH) to enhance BA excretion. By exploring further, we found NOB downregulated hepatic expression of the farnesoid X receptor (FXR) and its associated small heterodimer partner (SHP), and it increased the expression of downstream enzymes, including cholesterol 7α-hydroxylase (CYP7A1) and cytochrome P450 27A1 (CYP27A1). This acceleration in cholesterol conversion within the liver contributes to mitigating MAFLD. The present findings underscore the significant role of NOB in regulating gut microbial balance and BA metabolism, revealing that long-term intake of NOB plays beneficial roles in the prevention or intervention of MAFLD.

This study systematically evaluates the comparative performance of two mass spectrometry acquisition modes, data-dependent acquisition (DDA) and data-independent acquisition (DIA), coupled with ultra-high-performance liquid chromatography-quadrupole-orbitrap high-resolution mass spectrometry (UPLC-Q-Orbitrap HRMS) for comprehensive chemical profiling of complex traditional Chinese medicine (TCM) formulations. Huaihua Powder, a classical formulated prescription, was employed as a model system for empirical assessment. Optimized DDA and DIA acquisition methods were separately established: the DDA method incorporated a targeted precursor ion selection strategy with customized fragmentation parameters, while the DIA method employed a segmented variable window strategy to cover the target m/z range, performing unbiased fragmentation on all precursor ions. Compound identification was executed using Compound Discoverer software. The comparative evaluation specifically focused on the performance characteristics of the two acquisition modes, encompassing the number of identified compounds, reproducibility, MS/MS spectral quality, and detection sensitivity for low-abundance active constituents. Results demonstrated that the DDA mode yielded a higher total number of detected compounds, whereas the DIA mode generated a greater proportion of high-confidence identifications (10.63 % with spectral match scores >0.8). Notably, the DIA approach exhibited significantly superior reproducibility in retention time and peak area for six representative compounds, with rutin showing >3-fold difference in retention time RSD between the two acquisition modes. However, DDA produced cleaner MS/MS spectra with distinct fragment ions, whereas DIA spectra exhibited interference from contaminant ions. Concurrently, DIA effectively detected low-abundance active constituents whose ion chromatograms and MS/MS fragments could not be extracted in DDA mode. This study contributes critical experimental evidence and analytical datasets to inform the selection of high-resolution mass spectrometry acquisition modes for complex TCM formulation research. Subsequent researchers may integrate the complementary advantages of both approaches to achieve dual objectives in comprehensive compound characterization.

This study systematically evaluates the comparative performance of two mass spectrometry acquisition modes, data-dependent acquisition (DDA) and data-independent acquisition (DIA), coupled with ultra-high-performance liquid chromatography-quadrupole-orbitrap high-resolution mass spectrometry (UPLC-Q-Orbitrap HRMS) for comprehensive chemical profiling of complex traditional Chinese medicine (TCM) formulations. Huaihua Powder, a classical formulated prescription, was employed as a model system for empirical assessment. Optimized DDA and DIA acquisition methods were separately established: the DDA method incorporated a targeted precursor ion selection strategy with customized fragmentation parameters, while the DIA method employed a segmented variable window strategy to cover the target m/z range, performing unbiased fragmentation on all precursor ions. Compound identification was executed using Compound Discoverer software. The comparative evaluation specifically focused on the performance characteristics of the two acquisition modes, encompassing the number of identified compounds, reproducibility, MS/MS spectral quality, and detection sensitivity for low-abundance active constituents. Results demonstrated that the DDA mode yielded a higher total number of detected compounds, whereas the DIA mode generated a greater proportion of high-confidence identifications (10.63 % with spectral match scores >0.8). Notably, the DIA approach exhibited significantly superior reproducibility in retention time and peak area for six representative compounds, with rutin showing >3-fold difference in retention time RSD between the two acquisition modes. However, DDA produced cleaner MS/MS spectra with distinct fragment ions, whereas DIA spectra exhibited interference from contaminant ions. Concurrently, DIA effectively detected low-abundance active constituents whose ion chromatograms and MS/MS fragments could not be extracted in DDA mode. This study contributes critical experimental evidence and analytical datasets to inform the selection of high-resolution mass spectrometry acquisition modes for complex TCM formulation research. Subsequent researchers may integrate the complementary advantages of both approaches to achieve dual objectives in comprehensive compound characterization.