Broccoli Leaf Phenolics Ameliorate NAFLD via Regulation of EGFR/AKT/SREBP Signaling Pathways and Gut Microbiota

Broccoli Leaf Phenolics Ameliorate NAFLD via Regulation of EGFR/AKT/SREBP Signaling Pathways and Gut Microbiota | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Broccoli Leaf Phenolics Ameliorate NAFLD via Regulation of EGFR/AKT/SREBP Signaling Pathways and Gut Microbiota Yaqi Zhao, Wenyuan Zhang, Yuanshou Zhao, Yue Li, Qian Wang, Zhanquan Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9194529/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Graphical Abstract Abstract Broccoli leaves are commonly discarded during industrial processing despite being rich in bioactive phytochemicals, resulting in substantial resource waste. This study investigated the protective effects and underlying mechanisms of a microwave-assisted green extract of broccoli leaf phenolics (BLP) against high-fat diet (HFD)-induced non-alcoholic fatty liver disease (NAFLD). The LC-MS/MS profiling revealed that BLP is predominantly composed of cinnamic acid derivatives and flavonoids, notably sinapic acid, ferulic acid, kaempferol, and luteolin. In HFD-fed C57BL/6J mice, BLP supplementation significantly ameliorated hepatic steatosis and liver injury, evidenced by reduced serum AST, ALT, and lipid profiles (TG, TC, LDL). Mechanistically, BLP suppressed hepatic lipogenesis via SREBP-1c downregulation, modulated the EGFR/AKT/SREBP signaling pathway, and attenuated inflammatory responses by inhibiting the TLR4/NF-κB pathway and reducing pro-inflammatory cytokines (IL-6, IL-1β, TNF-α). Furthermore, BLP reinforced intestinal barrier integrity by upregulating tight junction proteins () and restored gut microbiota homeostasis, enriching beneficial taxa (, ) while suppressing dysbiosis-associated genera. Overall, BLP could exert hepatoprotective effects via the gut-liver axis, highlighting its immense potential as a value-added, food-derived functional ingredient for NAFLD prevention. Biological sciences/Biochemistry Health sciences/Diseases Health sciences/Gastroenterology Biological sciences/Microbiology Broccoli leaf water extract Non-alcoholic fatty liver disease Network pharmacology EGFR/AKT/SREBP pathway Gut microbiota Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Non-alcoholic fatty liver disease (NAFLD) is a metabolic-related chronic liver disease characterized primarily by abnormal lipid deposition in the liver, also known as metabolic-associated fatty liver disease (MAFLD/MASLD) 1 . Its incidence has been steadily increasing due to the prevalence of obesity and metabolic syndrome, making it one of the most common chronic liver diseases worldwide 2–3 . Currently, clinical intervention for NAFLD mainly relies on lifestyle modifications (such as dietary control and exercise intervention) and drug treatments targeting metabolic disorders such as insulin resistance and dyslipidemia 4 . However, poor long-term adherence, significant individual variability in efficacy, and potential adverse reactions still limit its widespread application. Therefore, developing safe, effective, and suitable novel prevention and treatment strategies for long-term intervention has become an important direction for NAFLD. Plant extracts and concentrates have recently attracted increasing attention for their potential role in the prevention and treatment of NAFLD. Unlike single-target drugs, plant-derived bioactive compounds exert therapeutic effects through coordinated multi-target regulation, simultaneously modulating hepatic lipid metabolism, inflammatory responses, oxidative stress, and gut–liver axis homeostasis by activating metabolic pathways such as AMPK and PPAR, inhibiting NF-κB mediated chronic inflammation, and reshaping gut microbiota composition and its metabolites 5–7 . For example, flavonoid-rich mulberry leaf ( Morus ) extract has been shown to effectively alleviate hepatic lipid deposition and inflammatory response in a high-fat diet-induced mice model by improving lipid metabolism, enhancing antioxidant capacity, and regulating gut microbiota structure 8 . Conjugated polyphenols from millet ( Setaria italica ) have been reported to significantly improve NAFLD-related phenotypes by restoring gut microbiota balance, enhancing intestinal barrier function, and reducing hepatic lipid accumulation and inflammation levels 9 . These studies collectively demonstrate that plant extract concentrates can exert anti-NAFLD effects through the synergistic regulation of the gut-liver axis and multiple metabolic and inflammatory signaling pathways, highlighting their potential value as a safe, readily available, and suitable long-term intervention strategy for the prevention and treatment of metabolic diseases. Broccoli ( Brassica oleracea var. italica ), a member of the Cruciferae family, is widely consumed for its rich content of vitamin C, carotenoids, and glucosinolates, which exhibit antioxidant, anti-inflammatory, and potential anticancer activities 10–13 . However, large quantities of leaves and stalks generated during cultivation and processing are typically discarded, leading to substantial resource waste. Our previous study showed that broccoli leaves contain significantly higher levels of flavonoids than florets, while maintaining comparable levels of total phenolics and vitamin C 10 . Among these bioactive constituents, phenolic acids have attracted considerable attention due to their potent antioxidant and antimicrobial properties, conferring broad application potential in the food, pharmaceutical, and cosmetic industries 13 . Major phenolic acids in broccoli include caffeic acid, chlorogenic acid, neochlorogenic acid, ferulic acid, and sinapic acid 14 . Despite these advantages, the valorization of broccoli leaves remains underexplored. Therefore, the development of green and efficient extraction strategies, together with systematic evaluation of their bioactivities, is essential to unlock their full potential. Water is an ideal green solvent due to its safety, environmental compatibility, availability, and low cost 11 . However, aqueous extraction processes for broccoli leaves have not yet been systematically optimized for the recovery and characterization of bioactive compounds. In this study, broccoli leaf phenolics (BLP), a plant-derived natural product, were selected as the primary focus. The phytochemical profile of BLP was comprehensively characterized, and its potential effects on NAFLD were evaluated using multiple animal models combined with integrated data analysis approaches. The safety of BLP was first assessed in mice, followed by the establishment of preventive and therapeutic models of high-fat diet (HFD)-induced NAFLD to investigate its effects on serum and hepatic lipid levels, liver injury markers, histopathological changes, inflammatory cytokines, and gut microbiota composition. In addition, a network pharmacology approach was employed to identify potential molecular targets, followed by enrichment analysis and molecular docking to elucidate the underlying mechanisms. This integrated strategy provides a systematic evaluation of the efficacy and mechanistic basis of BLP in alleviating NAFLD. Results and Discussion BLP extraction and characterization The green extraction process of BLP is illustrated in Fig. 1 . A comprehensive LC-MS/MS analysis of broccoli leaf extract identified 24 phenolic compounds (Table 1 ), predominantly comprising cinnamic acids, flavonoids, and coumarins. Cinnamic acid derivatives constitute the primary phenolic group, with sinapic acid (14.45%) and ferulic acid (13.55%) accounting for over 28% of the total profile, accompanied by significant levels of valuable flavonoids, particularly kaempferol (9.86%) and luteolin (9.21%). These findings align with the typical phenolic profile of Brassica vegetables 15 . In addition, the total phenolic content of the extract, determined by the Folin–Ciocalteu method, was 10–14 mg GAE/g extract, providing quantitative support for the relative abundance observed in the LC–MS/MS analysis. Notably, the substantial accumulation of both free and conjugated sinapic acid in the foliage indicates highly conserved secondary metabolite biosynthetic pathways compared to the widely studied edible florets 16 . Furthermore, high-resolution profiling facilitated the precise detection of minor glycosylated flavonoids and anthocyanins 17 , reflecting adaptive defense mechanisms against environmental stressors 18 . While some literature identifies chlorogenic acid as the major broccoli phenolic 19 , the present dataset revealed a relatively higher abundance of coumarins, such as bergaptol (5.89%), which may be attributed to genotypic or environmental variation. Notably, the application of microwave-assisted green extraction enabled efficient recovery of phenolic compounds while minimizing solvent consumption and processing time, supporting sustainable sample preparation. Overall, these results provide a comprehensive characterization of the phenolic composition of broccoli leaves and suggest that this underutilized biomass may serve as a promising and sustainable source of bioactive compounds with potential for value-added applications 20–21 . Table 1 Phenolic compounds identified in broccoli leaf by LC-MS/MS. No. MS2.name Formula Class Peak area % 1 Sinapic acid C11H12O5 Cinnamic acids and derivatives 14.45 2 Ferulic acid C10H10O4 Cinnamic acids and derivatives 13.55 3 Kaempferol C15H10O6 Flavonoids 9.86 4 Caffeic acid C9H8O4 Cinnamic acids and derivatives 6.43 5 Bergaptol C11H6O4 Coumarins and derivatives 5.89 6 1-O-Sinapoyl-beta-D-glucose C17H22O10 Cinnamic acids and derivatives 5.11 7 Isoferulic acid C10H10O4 Cinnamic acids and derivatives 5.00 8 Astragalin C21H20O11 Flavonoids 4.35 9 4-Hydroxycinnamic acid C9H8O3 Cinnamic acids and derivatives 4.21 10 p-Coumaraldehyde C9H8O2 Cinnamaldehydes 4.08 11 Luteolin C15H10O6 Flavonoids 9.21 12 trans-Cinnamic acid C9H8O2 Cinnamic acids and derivatives 3.52 13 Cyanidin C15H11O6 Flavonoids 2.19 14 2-Hydroxycinnamic acid C9H8O3 Cinnamic acids and derivatives 2.18 15 Umbelliferone C9H6O3 Coumarins and derivatives 2.10 16 Kaempferol 3-gentiobioside C27H30O16 Flavonoids 1.25 17 6-Formylumbelliferone C10H6O4 Coumarins and derivatives 1.46 18 Cyanidin-3,5-diglucoside C27H31O16 Flavonoids 1.25 19 Cyanidin 3-galactoside C21H21O11 Flavonoids 1.07 20 Kaempferol 3-(2''-(E)-feruloylgalactosyl-(1->4)-glucoside) C37H38O19 Flavonoids 0.80 21 Aesculetin C9H6O4 Coumarins and derivatives 0.57 22 3-Hydroxyflavone C15H10O3 Flavonoids 0.58 23 3-(2-Hydroxyphenyl)propanoic acid C9H10O3 Phenylpropanoic acids 0.45 24 Scopoletin C10H8O4 Coumarins and derivatives 0.42 The Effect of BLP on NAFLD in Mice Assessing the Safety of BLP To confirm safety, natural plant extracts require comprehensive toxicological assessment before their biological effects on metabolic disorders can be evaluated 22 . BLP were evaluated for toxicity and obesity-preventive effects in C57BL/6J mice. In the toxicity study (Fig. 2 A), oral administration of BLP at 800 mg/kg caused no significant changes in body weight or in the weights of major organs (heart, spleen, lung, kidney, and brain) compared with the normal group ( p > 0.05) (Fig. 2 B and 2 C). Histological analysis further confirmed biocompatibility, as the liver, kidney, and spleen of treated mice showed intact structures, similar to the normal group, indicating no acute toxicity (Fig. 2 D). These results confirmed that BLP exhibited good biocompatibility, which is consistent with previously published studies. Previous investigations have shown that 21-day oral administration of broccoli by-product powder in mice does not induce physiological abnormalities or hepatotoxicity 23 . In addition, hydrophilic extracts derived from broccoli by-products have been reported to be safe and to possess functional potential, supporting their applicability as functional food ingredients 24 . Moreover, broccoli seed extracts have been demonstrated to cause neither acute nor sub-chronic toxicity, further reinforcing the low-toxicity profile of broccoli-derived bioactive fractions 25 . Taken together, these studies provide a solid toxicological basis for the subsequent evaluation of the therapeutic efficacy of BLP in metabolic disease models. The preventive effect of BLP on NAFLD in mice To further assess the preventive effects of BLP on NAFLD, mice were administered BLP concomitantly with a high-fat diet for 10 weeks (Fig. 2 E). In the HFD-induced NAFLD model, BLP produced a dose-dependent protective effect. All tested doses significantly reduced excessive body-weight gain compared with the Model group ( p < 0.05) (Fig. 2 F). Kidney and brain weight ratios were markedly altered in the Model group relative to the Normal group, whereas BLP treatment partially restored these indices ( p < 0.05) (Fig. 2 G and 2 H). Excessive weight gain and ectopic fat accumulation are major risk factors for NAFLD, primarily leading to increased hepatic lipid deposition 26 . For adipose tissue distribution (Fig. 2 I), the fat weight ratios of inguinal white adipose tissue (iWAT), epididymal white adipose tissue (eWAT), and retroperitoneal white adipose tissue (rWAT) were significantly increased in the model group compared with the normal group ( p < 0.05). BLP treatment reduced fat weight ratios in a dose-dependent manner, with the strongest effect observed in eWAT. Glucose metabolism disorders, particularly insulin resistance, are key drivers of NAFLD progression and exacerbate hepatic glucolipotoxicity 27 . Glucose homeostasis was evaluated using the oral glucose tolerance test (OGTT) and insulin tolerance test (ITT) (Fig. 2 J and 2 K). Compared with the model group, BLP-treated mice showed improved glucose tolerance and enhanced insulin sensitivity ( p < 0.05). OGTT and ITT curves showed smaller glycemic excursions, indicating better maintenance of glucose homeostasis. Dyslipidemia is closely linked to the onset and progression of NAFLD, and abnormal serum enzyme activities indicate liver injury 27 . As shown in Fig. 3 A–C, serum triglyceride (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels were significantly increased in the model group. However, serum HDL-C levels remained comparable between the Model group and all treatment groups (Fig. 3 D). Both BLP and simvastatin treatments reduced these lipid levels, with the high-dose BLP group showing the strongest effect ( p < 0.05). Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) activities were markedly elevated in the model group ( p < 0.05) (Fig. 3 E and 3 F), whereas BLP-treated groups significantly lowered ALT and AST, indicating improved liver function. Gross liver morphology revealed clear hepatomegaly and discoloration in the model group (Fig. 3 F). Histological analysis using H&E and Oil Red O staining showed severe hepatic steatosis in the model group, while BLP and simvastatin treatment markedly reduced lipid droplet accumulation. The liver weight radio (Fig. 3 G) and hepatic lipid contents (TC, TG, and LDL-C) were also significantly decreased by BLP treatment ( p < 0.05) (Fig. 3 H–J). During the development of NAFLD, pro-inflammatory factors are released simultaneously 28 . Indeed, we found the proinflammatory cytokines including interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) were strongly upregulated in the model group (Fig. 3 K), but were significantly suppressed by BLP treatment ( p < 0.05), confirming its anti-inflammatory and hepatoprotective effects 29 . Overall, these results indicate that BLP effectively alleviates HFD-induced NAFLD and associated metabolic disturbances. BLP reduces excessive weight gain and modulates adipose tissue distribution, lowering peripheral drivers of hepatic lipid accumulation. It improves glucose tolerance and insulin sensitivity, relieving metabolic stress on the liver, while correcting dyslipidemia and reducing hepatic enzyme leakage. Importantly, BLP downregulates proinflammatory cytokine expression, providing strong evidence for its anti-inflammatory and liver-protective properties. The therapeutic potential of BLP on NAFLD in mice To investigate the therapeutic potential of BLP in a high-fat diet–induced NAFLD model, mice were fed a high-fat diet for 14 weeks to establish NAFLD, followed by BLP treatment for an additional 14 weeks (Fig. 4 A). Compared with the normal group, the model group (HFD) exhibited significant body weight gain, whereas BLP-treated groups (Low and High) and the simvastatin group showed varying degrees of inhibition of weight gain ( p < 0.05), which was consistent with the results observed in the NAFLD prevention experiment (Fig. 4 B). Body weight regulation is crucial for metabolic health, as excessive weight gain is a key risk factor for NAFLD, and interventions that limit weight gain often improve metabolic homeostasis 30 . For glucose homeostasis, ITT results indicated that the model group developed insulin resistance, while treatment groups enhanced insulin sensitivity, as reflected by greater reductions in blood glucose following insulin injection (Fig. 4 C). OGTT results showed elevated blood glucose in the model group at all time points ( p < 0.05), whereas BLP treatment improved glucose tolerance, with lower glucose levels at 30, 60, 90, and 120 minutes ( p < 0.05) (Fig. 4 D). Impaired glucose tolerance and insulin resistance are central to NAFLD pathogenesis, promoting hepatic lipid accumulation and metabolic dysfunction 31 . The improvement in these parameters by BLP suggests its potential to target key metabolic defects in NAFLD. In serum lipid profiles, the model group showed significantly higher TG, TC, and LDL-C levels compared with the normal group ( p < 0.01), indicating HFD-induced dyslipidemia (Fig. 4 E–G). However, serum HDL-C levels did not differ significantly among the treatment groups. (Fig. 5 H). In addition, serum AST and ALT activities were markedly increased, suggesting hepatic injury (Fig. 4 I and 4 J). Both simvastatin and BLP treatments (Low and High doses) significantly reduced these indicators, with the high-dose BLP group approaching normal levels, indicating dose-dependent improvements in lipid metabolism and liver function. Gross liver morphology revealed severe hepatomegaly and pale coloration in HFD-fed mice, whereas BLP-treated mice showed visibly improved liver appearance (Fig. 4 K and 4 L). Histological analyses corroborated these findings that H&E staining revealed substantial lipid droplet accumulation and hepatocellular ballooning in the HFD group, which were alleviated by BLP, while Oil Red O staining demonstrated significant reductions in hepatic lipid deposition in BLP-treated mice (Fig. 4 K). Liver function assessments showed that the Model group had higher liver weight ratios ( p < 0.05) (Fig. 4 L) and elevated intrahepatic TG, TC, and LDL-C levels ( p < 0.05) (Fig. 4 M-O), consistent with the severe histological changes. Collectively, these results indicate that BLP supplementation effectively mitigates HFD-induced obesity, hyperlipidemia, hyperglycemia, and hepatic steatosis. The beneficial effects may be attributed to bioactive phytochemicals in broccoli leaves, which regulate lipid and glucose metabolism, enhance antioxidant defense, and suppress hepatic fat accumulation. These findings highlight the potential of BLP as a dietary intervention for the prevention and management of NAFLD and related metabolic disorders. Based on the evaluation of all the above animal test results, mice in the prevention group were selected for further mechanistic studies. Mechanistic Investigation of BLP in Improving NAFLD Investigate Potential Active Compounds Using Network Pharmacology To explore and predict the potential molecular targets underlying the effects of BLP on NAFLD, 22 phenolics metabolites identified through LC-MS/MS analysis were subjected to screening in the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). The possible targets of these compounds were then predicted using SwissTarget Prediction, yielding a total of 457 targets. In parallel, 3,142 NAFLD-related targets were collected from GeneCards, OMIM, and TTD databases (Fig. 5 A). To further investigate the potential mechanisms underlying the therapeutic effects of BLP, we performed bioinformatic analyses. A Venn diagram revealed 134 overlapping targets between BLP phytochemicals and NAFLD-related targets, suggesting potential key mediators of the extract's action (Fig. 5 A). Gene Ontology (GO) enrichment analysis (Fig. 5 B) showed that these overlapping targets were significantly enriched in biological processes such as signal transduction, protein phosphorylation, and positive regulation of transcription by RNA polymerase II; cellular components including plasma membrane, nucleus, and membrane; and molecular functions such as protein serine/threonine kinase activity, protein kinase activity, and enzyme binding. This pattern is consistent with previous NAFLD studies. Previous studies have shown that disease-relevant genes are enriched in signal transduction, membrane and nuclear compartments, and kinase-related functions, supporting the biological relevance of our findings 32 . KEGG pathway analysis (Fig. 5 C) indicated that these targets were involved in multiple signaling pathways, with the PI3K–AKT signaling pathway, lipid and atherosclerosis pathway, and Alzheimer disease pathway being the most significantly enriched. The protein–protein interaction (PPI) network (Fig. 5 D) further visualized interactions among key targets and highlighted core proteins that may play central roles in mediating the biological effects of BLP. These bioinformatic results provide insights into the potential molecular mechanisms of BLP in ameliorating HFD-induced NAFLD. The overlap between phytochemical targets and disease-related targets suggests that BLP acts by modulating specific molecular nodes involved in NAFLD pathogenesis. Enrichment in GO terms related to signal transduction and protein phosphorylation implies that BLP may regulate intracellular signaling cascades essential for metabolic control and cell function. Notably, the PI3K–AKT pathway, a central regulator of cell growth, survival, and metabolism, is closely linked to insulin resistance and hepatic lipid accumulation, key features of NAFLD 33–34 . Modulation of this pathway by BLP may improve insulin sensitivity and reduce hepatic steatosis. Furthermore, enrichment in the lipid and atherosclerosis pathway aligns with the observed reductions in serum lipid levels in vivo. The PPI network identifies core proteins that may serve as pivotal nodes in BLP-mediated molecular interactions, providing promising targets for further mechanistic studies. Research on the Mechanism of BLP Regulating the PI3K-AKT Pathway To clarify how BLP enhances HFD-induced NAFLD, we will perform analyze liver gene and protein expression levels associated with the PI3K-AKT signaling pathway. The transcription and protein levels of the EGFR–PI3K–AKT–SREBP-1c signaling cascade (Fig. 6 A) were measured by RT-qPCR and Western blotting. RT-qPCR analysis of mice liver tissue showed that the Model group had higher mRNA expression of EGFR and AKT1 than the Normal group (Fig. 6 B and 6 F). However, BLP and simvastatin treatment reduced their expression to near-normal levels. In addition, the transcripts of the EGFR–AKT cascade ( PI3K and IRS1 gene) were also upregulated in the model group (Fig. 6 D and 6 E). The expression of SREBP-1c and its adipogenic target genes was increased as well (Fig. 6 G and 6 H). These results were consistent with the activation of de novo lipogenesis at the early stage of pathology. Furthermore, Western blotting confirmed that the model group showed higher protein levels of phosphorylated EGFR (p-EGFR) and phosphorylated AKT (p-AKT) (Fig. 6 I). The PI3K and SREBP-1c protein levels were also elevated, indicating activation of the EGFR–PI3K–AKT–SREBP-1c pathway. In contrast, BLP intervention reduced p-EGFR, p-AKT, and SREBP-1c levels, while total AKT remained unchanged (Fig. 6 J-O). Thus, the regulatory effect of BLP was mainly achieved by blocking phosphorylation-dependent activation rather than by lowering AKT protein abundance. These molecular changes were associated with reduced hepatic lipid deposition, suggesting suppression of lipid production. Furthermore, it is noteworthy that AKT not only acts as a linker growth factor regulating lipid metabolism but also serves as a central signaling node in the inflammatory response 35 . TLR4 can activate HFD-induced liver inflammation, further enhancing PI3K/AKT signaling 36 . In mouse liver, the model group showed upregulation of TLR4 and p-p65/NF-κB expression ( p < 0.05), while simvastatin and BLP significantly inhibited these upregulations ( p < 0.05 and p < 0.01) (Fig. 6 P-R). This is similar to previous results, where many natural compounds often simultaneously regulate both hepatic lipid metabolism and inflammatory signaling pathways. For example, compounds such as berberine and flavanones from citrus extracts can simultaneously inhibit PI3K/AKT-related lipid metabolism signaling pathways and suppress TLR4/NF-κB activation to alleviate metabolic inflammation 35,37 . Overall, the data highlighted the specific molecular targets and regulatory pattern of potential bioactive components in BLP in NAFLD. BLP showed regulatory effects similar to simvastatin, supporting its potential as a natural treatment for NAFLD. Nevertheless, interactions among multiple phytochemicals in BLP and the network of NAFLD-related targets remain to be clarified. Future studies should examine possible synergistic actions among these compounds and conduct mechanistic experiments to verify the roles of AKT1 and EGFR. Effect of BLP on Gut Microbiota, Intestinal Barrier Function and Inflammation The role of gut microbiota in regulating NAFLD through the gut–liver axis has received increasing attention 38 . The gut microbiota plays a key role in the development and progression of NAFLD through multiple mechanisms, including increased energy harvesting, altered intestinal barrier function, and production of metabolites 39 . To investigate the impact of BLP treatments on microbial community composition and structure, 16S rRNA sequencing of fecal samples from three groups of mice was performed. Principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity (Fig. 7 A) revealed clear separation of the microbial communities among the normal, model, and high-dose groups, with PC1 and PC2 explaining 35.63% and 10.47% of the variation, respectively. Notably, the high-dose group was positioned between the normal and model groups, suggesting that BLP could partially reshape gut microbiota composition 40 . The Simpson index reflects the microbial diversity of the gut microbiota, describing how evenly species are distributed. The Chao1 index estimates species richness, indicating the total number of bacterial species. Together, these indices describe the overall structure of the gut microbial community 41 . As shown in Fig. 7 B, the Simpson index was significantly reduced in the model group compared with the normal group ( p < 0.01), whereas high-dose treatment restored microbial diversity ( p < 0.05). Similarly, the Chao1 index showed corresponding changes. At the genus level, 16S rRNA sequencing indicated that the fecal microbiota of mice fed with a normal diet was dominated by Bacteroides and Muribaculaceae (Fig. 7 C and 7 D), consistent with previous reports highlighting their abundance in healthy gut ecosystems and their protective role against metabolic disorders 42 . In contrast, HFD-induced NAFLD mice exhibited a marked increase in potentially pathogenic genera such as Rikenella, Alistipes , and Odoribacter , taxa that have been frequently associated with metabolic inflammation and NAFLD progression 43 .High-dose BLP reversed these changes, suppressing harmful taxa and promoting beneficial bacteria such as Lachnoclostridium , Lactobacillus , Parabacteroides , and Dubosiella , which have been reported to enhance gut barrier function, regulate bile acid metabolism, and reduce hepatic lipid accumulation (Fig. 7 E) 44–45 .Collectively, these findings suggest that the hepatoprotective effects of BLP are partially mediated through modulation of the gut microbiota and restoration of microbial balance disrupted by HFD. The correlation analysis further quantified the relationships between differential microbial taxa and individual samples (Fig. 7 F). The results revealed significant associations between specific gut microbial genera and metabolic parameters related to NAFLD, highlighting potential links between gut dysbiosis and disease progression. Rikenella , Alistipes , and Colidextribacter showed positive correlations with serum TC, TG, and liver TG, suggesting these taxa may exacerbate lipid dysregulation. For example, Colidextribacter can influence cholesterol metabolism in the gut, affecting absorption and systemic lipid balance, potentially promoting NAFLD 45 . In contrast, Faecalibaculum , Romboutsia , Blautia , and Odoribacter exhibited negative correlations, consistent with their protective roles. Faecalibaculum , in particular, is linked to improved lipid profiles and reduced metabolic disorder risk, likely via short-chain fatty acid production or immune modulation 46 . Romboutsia , Blautia , and Odoribacter may similarly limit lipid accumulation and inflammation 47 . Overall, these results indicate that BLP improves metabolic health, at least in part, by modulating gut microbiota diversity and composition. High-dose BLP treatment markedly reduced the abundance of pathogenic taxa linked to inflammation and metabolic dysfunction, while promoting beneficial bacteria, thereby contributing to the restoration of gut microbial balance and overall intestinal homeostasis. Alterations in gut microbiota have been implicated in intestinal barrier dysfunction along the gut–liver axis. Therefore, intestinal barrier integrity and permeability were evaluated in mice from the different treatment groups. H&E staining results showed that, compared with the normal group, the model group mice exhibited significant mucosal structural damage and inflammatory cell infiltration in the intestine (Fig. 7 G). BLP showed a similar effect to simvastatin, inhibiting intestinal damage. The mRNA expression levels of tight junction genes and pro-inflammatory cytokines related to intestinal barrier integrity also showed a similar trend. Compared with the Model group, BLP significantly inhibited TLR4 expression in the intestine and promoted the expression of ZO-1, Claudin-1, and Occludin (Fig. 7 H). Simultaneously, BLP treatment significantly reduced the mRNA levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α), indicating that BLP not only improved intestinal barrier function damaged by HFD but also inhibited intestinal inflammation (Fig. 7 I). Collectively, these results demonstrate that BLP alleviates HFD-induced gut microbiota dysbiosis by restoring microbial diversity and favorably reshaping microbial composition. Concomitantly, BLP preserves intestinal barrier integrity and suppresses intestinal inflammation, thereby potentially interrupting the pathological gut–liver axis that contributes to hepatic lipid accumulation and NAFLD progression. Conclusions In this study, broccoli leaf phenolics (BLP) were obtained using a green extraction approach, incorporating microwave-assisted technology, and their chemical composition was characterized by LC–MS/MS-based analysis. The results demonstrated that BLP is rich in diverse phenolic compounds, particularly cinnamic acid derivatives and flavonoids. In vivo experiments further showed that BLP alleviated high-fat diet (HFD)-induced NAFLD, as evidenced by improved metabolic parameters, reduced hepatic steatosis and inflammation, and no observable toxicity to major organs. In addition, BLP mitigated intestinal inflammation and barrier dysfunction and modulated the gut microbiota by increasing the relative abundance of beneficial genera, including Romboutsia , Blautia , and Odoribacter . Integrated bioinformatics analysis, together with RT-qPCR and Western blot validation, suggested that these effects may be associated with the regulation of PI3K–AKT signaling, lipid metabolism, and inflammatory pathways. Notably, the application of green extraction technology, particularly microwave-assisted processing, enabled efficient recovery of phenolic compounds while reducing solvent consumption and extraction time. Collectively, these findings indicate that BLP represents a promising and sustainable source of bioactive compounds with potential for NAFLD intervention, while also providing a feasible strategy for the value-added utilization of broccoli leaf by-products in the context of green and sustainable food processing. Materials and methods Materials Fresh ‘Youxiu’ broccoli by-product leaves were collected in June 2024 from the SanJiaoCheng Township, Yuzhong County, Lanzhou City, Gansu Province (China). All chemicals used in this study were UPLC grade. Sample Preparation The green extraction process of broccoli leaf phenolics (BLP) is illustrated in Fig. 1 . Fresh broccoli leaves were washed, dried, and pulverized. After cleaning, the leaves were cut into small pieces and evenly distributed on drying trays (Changsheng Machinery Co., Ltd., CS-6CHZ-9), followed by drying at 45°C for 60 h until the moisture content was below 6%. The Vornoli et al. 48 technique was used to make the water extract. A wall-breaking machine (Zhongshan Huiren Electric Appliance Co., Ltd., 919E) was used to crush the dried leaves before they were put through an 80-mesh sieve. The powder was completely dissolved in 200 mg/mL of distilled water and ultrasonicated for one hour at room temperature (KQ-30L, Zhengzhou Yuhua Instrument Manufacturing Co., Ltd.), and then stirred on a magnetic stirrer (IKA C-MAG HS7) at 600 rpm for 1 h. The mixture was centrifuged at 4000 rpm, and the supernatant was collected, stored at − 80°C, and freeze-dried using a vacuum dryer (Boyikang, Pilot2–4 m, China). For in vivo experiments, the freeze-dried powder was resuspended in water at the required concentration. Phenolics concentration measurement The total phenolic content (TPC) of the freeze-dried extract was determined using the Folin–Ciocalteu method. Briefly, the sample was dissolved in distilled water and centrifuged, and 100 µL of the supernatant was mixed with 500 µL of 10-fold diluted Folin–Ciocalteu reagent. After 5 min, 400 µL of sodium carbonate solution (7.5%, w/v) was added, followed by incubation in the dark for 30 min at room temperature. The absorbance was measured at 765 nm. Gallic acid was used to generate the calibration curve (R² > 0.99), and the results were expressed as mg gallic acid equivalents per gram of extract (mg GAE/g extract). All measurements were performed in triplicate. Animal experiments All animal experiments were approved by the Animal Care and Use Committee of China Agricultural University (AW12106202-5-02). (1) Safety assessment : Male C57BL/6J mice that were eight weeks old were kept in controlled environments with free access to food and water (22 ± 2°C, 40–60% humidity, and a 12-hour light/dark cycle). Following a week of acclimatization, mice were divided into two groups at random: BLP-treated (800 mg/kg/day BLP, by oral gavage) and control (normal chow). Body weight and food consumption were monitored every day for the duration of the treatment 49 . (2) Preventive experiments : Thirty 6-week-old male C57BL/6J mice were randomly assigned to five groups (n = 6 per group) after being acclimated to the same conditions: normal (standard chow), model (high-fat diet, HFD), simvastatin (HFD + 10 mg/kg/day simvastatin), low-dose BLP (HFD + 300 mg/kg/day BLP), and high-dose BLP (HFD + 600 mg/kg/day BLP). Treatment lasted 10 weeks. Body weight was recorded weekly, and food and water intake were measured every 2–3 days 50 . (3) Therapeutic experiments : Another group of thirty 6-week-old male C57BL/6J mice was housed under the same conditions, acclimated for 1 week, and randomly assigned to five groups: normal (standard chow), model (HFD), simvastatin (HFD), low-dose BLP (HFD), and high-dose BLP (HFD). After 14 weeks on their diets, simvastatin and BLP treatments were started at 10, 300, and 600 mg/kg/day, respectively, by oral gavage and continued for another 14 weeks 51 . At the end of each experiment, mice were fasted for 8 h with free access to water, weighed, and euthanized by retro-orbital blood collection followed by cervical dislocation. Tissues were collected and weighed for further analysis. Biochemical Analysis As directed by the manufacturer, commercial test kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) were used to assess biochemical parameters in the liver and serum of mice. Aspartate aminotransferase (AST, No. C010-2-1), alanine aminotransferase (ALT, No. C009-2-1), total cholesterol (TC, No. A111-1-1), low-density lipoprotein cholesterol (LDL-C, No. A113-1-1), high-density lipoprotein cholesterol (HDL-C, No. A112-1-1). Detection of histopathology in mice After euthanasia, the liver and other tissues were quickly removed and fixed in 4% paraformaldehyde for 24 h. Samples were then embedded in paraffin and cut into 5 µm sections. Hematoxylin and eosin (H&E) staining was used to examine tissue structure. Additional liver samples were embedded in OCT compound, cryosectioned, and stained with Oil Red O to assess lipid accumulation. All sections were examined and imaged with a light microscope. Histological scoring was performed based on steatosis (micro- and macrovesicular), lobular inflammation, hepatocyte ballooning, and fibrosis. Oral Glucose Tolerance Test (OGTT) and Insulin Tolerance Test (ITT) To evaluate glucose homeostasis, OGTT and ITT were performed at weeks 12 and 13 of the KSP intervention, respectively. For the OGTT, mice were fasted for 8 h with free access to water. Baseline blood glucose (0 min) was measured from tail vein blood using a standard glucometer. Mice were then orally administered glucose (2 g/kg body weight), and blood glucose levels were recorded at 30, 60, 90, and 120 min post-gavage. For the ITT, following a 6 h fast, mice received an intraperitoneal injection of insulin (1 U/kg body weight), with blood glucose monitored at the same time intervals. The area under the curve (AUC) for both tests was calculated using the standard trapezoidal rule. 16S rRNA gene sequencing and data analysis The DNeasy PowerSoil Kit was used to extract total DNA from culture or fecal samples (Qiagen, Hilden, Germany). On a Bio-Rad PCR system, the V3–V4 region of the 16S rRNA gene was amplified using universal primers in 25 µL PCR reactions. Agencourt AMPure XP magnetic beads (Beckman Coulter, USA) were used to purify the PCR products after they were separated by agarose gel electrophoresis. A Qubit dsDNA test kit was then used to quantify the results. OE Biotech Co., Ltd. (Shanghai, China) used an Illumina MiSeq platform (Illumina Inc., San Diego, CA) to pool and sequence equimolar amplicons. Cutadapt was used to eliminate adapters from raw sequencing data (FASTQ). DADA2 in QIIME2 (version 2020.11) was used for filtering, denoising, merging, and chimera elimination. The Silva v138 database was used to create amplicon sequence variations (ASVs) and assign taxonomy to representative sequences using the q2-feature-classifier plugin. QIIME2 was used for principal coordinates analysis (PCoA), phylogenetic tree building, alpha diversity (Chao1, Shannon), and UniFrac distance matrices. LC-MS/MS analysis 80% methanol was used to extract tissue metabolites 52 . 50 mg of tissue was homogenized in 0.5 mL of pre-chilled 80% methanol, incubated for 30 minutes at -20°C, and then centrifuged at 20,000 × g for 15 minutes at 4°C. The supernatants were moved, vacuum-dried, reconstituted in 100 µL of 80% methanol, and kept at -80°C. Ten microliters of each extract were combined to create quality control (QC) samples. An UltiMate 3000 UPLC system (Thermo Fisher) with a T3 column (100 mm × 2.1 mm, 1.8 µm; Waters) was used for the LC-MS analysis at 40°C. Solvent A (5 mM ammonium acetate and 5 mM acetic acid in water) and solvent B (acetonitrile) were used as mobile phases at a rate of 0.3 mL/min. 0–0.8 min, 2% B; 8.0–8.1 min, 100–2% B; 8.1–10.0 min, 2% B. Metabolites were found in both positive and negative ion modes using a Q-Exactive high-resolution mass spectrometer (Thermo Scientific). At 70,000 resolutions (AGC 3e6, 100 ms), precursor spectra (70–1050 m/z) were obtained. At 17,500 resolutions (AGC 1e5, 80 ms), the top three DDA modes gathered fragment spectra. To guarantee stability, QC samples were conducted every ten injections. Network pharmacology We estimated the active components and important targets of BLP using previously reported methods 53 . Potential active molecules of BLP were found using SwissTargetPrediction ( https://www.swisstargetprediction.ch/ ) and the TCMSP database ( https://old.tcmsp-e.com/tcmsp.php ). The SMILES structures required for SwissTargetPrediction were supplied by PubChem ( https://pubchem.ncbi.nlm.nih.gov/ ). Using the phrase "NAFLD," GeneCards ( https://www.genecards.org/ ), OMIM ( https://omim.org/ ), and TTD ( https://idrblab.net/ttd/ ) provided illness-related targets for nonalcoholic fatty liver disease (NAFLD). After gathering all of the targets, duplicates were removed. The overlapping targets between BLP and NAFLD were visualized using Venny ( https://www.liuxiaoyuyuan.cn/ ). The DAVID database ( https://davidbioinformatics.nih.gov/summary.jsp ) was used for the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment studies. A compound–target–pathway network was constructed using the active compounds, relevant targets, and enriched pathways.Overlapping targets were further investigated by building a protein–protein interaction (PPI) network using STRING 11.5 ( https://string-db.org/ ). The CentiScape 2.2 plugin in Cytoscape 3.9.1 was used to perform topological analysis of the PPI network in order to identify key genes. RNA Extraction and Real-Time Quantitative PCR (RT-qPCR) The TRIzol reagent (TIANGEN, Beijing, China) was used to extract total RNA from colon tissue. Using a first-strand cDNA synthesis kit (TIANGEN, Beijing, China), 1 µg of RNA was converted into first-strand cDNA. The 2 −ΔΔCt technique was used to calculate the levels of gene expression. Table S1 lists the sequences of the primers that were acquired from Qingke Company. Western blot In accordance with previously published procedures, liver tissue was separated 54 . In ice-cold RIPA lysis solution supplemented with a 1% phosphatase and protease inhibitor cocktail, the obtained liver tissue was homogenized. On 4–20% SDS–PAGE gels, equal volumes of total protein (30 µg per lane) were separated before being deposited onto 0.22 µm PVDF membranes (Millipore, Billerica, MA, USA). Following blocking, primary antibodies against EGFR (1:750), p-EGFR (1:750), AKT (1:1500), p-AKT (1:1500), PI3K (1:1000), SREBP1 (1:750), GAPDH (1:4000), NK-κB (1:750), p-p65 (1:400), and TLR4 (1:750) were used as a loading control. The membranes were then exposed to an HRP-conjugated goat anti-rabbit IgG secondary antibody (1:5000) for 45 minutes at room temperature. An enhanced chemiluminescence (ECL) detection kit (Wuhan Aibotek Biotechnology Co., Ltd.) was used to observe protein bands, and a Bio-OI imaging system (OI600, Guangzhou Guangyi Biotechnology Co., Ltd.) was used to take pictures. ImageJ software (NIH, Bethesda, MD, USA) was used to quantify band intensities. Statistical Analysis R software (version 4.2.2) was used to conduct bioinformatics studies. SPSS 23.0 (IBM, Armonk, NY, USA) was used for statistical analysis, and Origin Pro 2021 (OriginLab, Northampton, MA, USA) was used for data visualization. Every outcome is displayed as mean ± standard deviation (SD). One-way analysis of variance (ANOVA) was used to examine group differences. Statistical significance was defined as a p-value<0.05. Author Contributions Statement Yaqi Zhao: Data curation, Methodology, Software, Writing-Original draft; Wenyuan Zhang: Writing-Reviewing and Editing, Methodology, Software; Yuanshou Zhao: Data curation, Methodology; Yue Li: Writing – review & editing; Qian Wang: Methodology; Zhanquan Zhang: Writing – review & editing. Haixia Yang: Writing-Reviewing and Editing; Liwang Liu: Writing – review & editing; Jianjun Deng: Conceptualization, Writing- Reviewing and Editing, Supervision, Project administration. Data availability statement The data supporting the findings of this study are available from the corresponding author upon request. Research funding This work was supported by the Innovation Program of the Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2024-IVF) and Central Public-interest Scientific Institution Basal Research Fund (IVF-BRF2024005, IVF-BRF2024003). Declarations Conflict of interest: The authors declare no conflict of interest. Supporting Information description Table S1 . The primers for RT-qPCR. Author Contribution Yaqi Zhao: Data curation, Methodology, Software, Writing-Original draft; Wenyuan Zhang: Writing-Reviewing and Editing, Methodology, Software; Yuanshou Zhao: Data curation, Methodology; Yue Li: Writing – review & editing; Qian Wang: Methodology; Zhanquan Zhang: Writing – review & editing. Haixia Yang: Writing-Reviewing and Editing; Liwang Liu: Writing – review & editing; Jianjun Deng: Conceptualization, Writing- Reviewing and Editing, Supervision, Project administration. Acknowledgement Yaqi Zhao: Data curation, Methodology, Software, Writing-Original draft; Wenyuan Zhang: Writing-Reviewing and Editing, Methodology, Software; Yuanshou Zhao: Data curation, Methodology; Yue Li: Writing – review & editing; Qian Wang: Methodology; Zhanquan Zhang: Writing – review & editing. 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Pomegranate peel extract alleviates diabetic retinopathy by suppressing the PI3K/AKT/HIF-1α/VEGF pathway and gut microbiota modulation. J. Adv. Res. 2025, in press. https://doi.org/10.1016/j.jare.2025.10.048. Additional Declarations No competing interests reported. Supplementary Files supplementaryfilesupportingdata.docx SupplementaryfileuncroppedBlotsimages.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9194529","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":615133966,"identity":"e60b173c-2e21-4f27-ae31-c87e601c29f5","order_by":0,"name":"Yaqi Zhao","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yaqi","middleName":"","lastName":"Zhao","suffix":""},{"id":615133967,"identity":"d4d5c83f-8c7b-49af-b4f5-497f57dcddc2","order_by":1,"name":"Wenyuan Zhang","email":"","orcid":"","institution":"Chinese Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Wenyuan","middleName":"","lastName":"Zhang","suffix":""},{"id":615133969,"identity":"490450fa-f684-44a9-a62a-f043fca8b1fc","order_by":2,"name":"Yuanshou Zhao","email":"","orcid":"","institution":"Lanzhou Industry Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Yuanshou","middleName":"","lastName":"Zhao","suffix":""},{"id":615133970,"identity":"b55a7b18-431a-40b1-938a-4d05e0ce677c","order_by":3,"name":"Yue Li","email":"","orcid":"","institution":"Ocean University of China","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Li","suffix":""},{"id":615133972,"identity":"f7dbeeae-a16f-4692-aab9-59ce71a81fde","order_by":4,"name":"Qian Wang","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Wang","suffix":""},{"id":615133973,"identity":"a8480527-ea72-434c-968d-3c72b14e3162","order_by":5,"name":"Zhanquan Zhang","email":"","orcid":"","institution":"Chinese Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Zhanquan","middleName":"","lastName":"Zhang","suffix":""},{"id":615133974,"identity":"9e1582b3-cfdd-45b2-8090-e7d0d5d7c26f","order_by":6,"name":"Haixia Yang","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Haixia","middleName":"","lastName":"Yang","suffix":""},{"id":615133975,"identity":"0279d5a6-e57d-4427-b3df-dd48d13cab21","order_by":7,"name":"Liwang Liu","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Liwang","middleName":"","lastName":"Liu","suffix":""},{"id":615133976,"identity":"cc6634b4-c390-443f-b484-56df017cb0bb","order_by":8,"name":"Jianjun Deng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDCCA0AsYcDAwNjAwPgAIpRAvBZmA+K1QAGbBFFa+I73Hn5hUWCXxzwj91h1YdthBn72HAOGnztwa5E8cy7NQsIguZhxRl7a7ZlALZI9bwwYe8/g1mJwI8fMQMKAObFxRo7Zbd5th0EiBsyMbXi03H8D0lIP1lIM0mJPUMsNHuMHEgaHwVqYwbZIENAieSbHDBjIxxMbe94YS/P+S+eROPOs4GAvHi18x88Yf5b4U524sT3H8DPPGWs5/vbkjQ9+4tECBGzSoPgwbIDweEDEAbwaGBiYP34AkvIEVI2CUTAKRsEIBgCZ/lFr2MF9/wAAAABJRU5ErkJggg==","orcid":"","institution":"Chinese Academy of Agricultural Sciences","correspondingAuthor":true,"prefix":"","firstName":"Jianjun","middleName":"","lastName":"Deng","suffix":""}],"badges":[],"createdAt":"2026-03-23 02:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9194529/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9194529/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106030090,"identity":"4c989987-df32-4d0d-bd5f-29f377e9f22a","added_by":"auto","created_at":"2026-04-02 15:11:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":8881077,"visible":true,"origin":"","legend":"\u003cp\u003eThe green extraction process of broccoli water extract.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/42abace4c96b511aff4ffca4.png"},{"id":106030081,"identity":"8906e519-f500-4b75-b431-f52e0dfae7e0","added_by":"auto","created_at":"2026-04-02 15:11:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":14210006,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental design, safety assessment, and preventive effects of BLP in mice. (A) Schematic illustration of the experimental design for safety assessment. (B) The change of body weight. (C) Organ weight percentages. (D) H\u0026amp;E staining of liver, kidney, and spleen tissues, and the scale bar at the lower right corner is 100 μm. (E) Schematic of the experimental design for preventive experiments. (F) Body weight changes over 10 weeks, and ** indicates a significant difference (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01) compared with all groups and the model group in the 10th week. (G) Kidney and brain (H) weight ratios. (I) Fat weight ratios of iWAT, eWAT, rWAT, and BAT. (J) OGTT results and area under the curve (AUC). (K) ITT results and AUC. Data are presented as mean ± SD or median with interquartile range (n = 6) and analyzed by two-tailed Student’s t-test or Mann–Whitney t-test. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01. iWAT, inguinal white adipose tissue; eWAT, epididymal white adipose tissue; rWAT, retroperitoneal white adipose tissue; BAT, brown adipose tissue. OGTT, oral glucose tolerance test; ITT, insulin tolerance test.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/fea83a7363b06aad88a28301.png"},{"id":106030094,"identity":"5f0bbc06-b24b-4ebc-b71f-7a5ef015a5b0","added_by":"auto","created_at":"2026-04-02 15:11:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17128007,"visible":true,"origin":"","legend":"\u003cp\u003eBLP regulates serum and hepatic lipid profiles and reduces liver inflammation in HFD - induced NAFLD mice. (A–D) Serum levels of TG, TC, LDL-C and HDL-C. (E, F) Serum AST and ALT activities. (G) Representative images of livers and H\u0026amp;E/Oil red O staining. The scale bar at the lower right corner is 100 μm. (H) Liver weight ratio. (I–K) Hepatic TG, TC, and LDL - C levels. (L) Relative mRNA expression of pro - inflammatory cytokines (\u003cem\u003eIL - 1β, TNF-α, IL-6 \u003c/em\u003egene) in the liver. Data are presented as mean ± SD or median with interquartile range (n = 6) and analyzed by two-tailed Student’s t-test or Mann–Whitney t-test. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01. TG, triglyceride; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; \u003cem\u003eIL-1β\u003c/em\u003e, interleukin-1 beta; \u003cem\u003eTNF-α\u003c/em\u003e, tumor necrosis factor alpha; \u003cem\u003eIL-6\u003c/em\u003e, interleukin-6.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/8e03cff6bed557af38284608.png"},{"id":106030096,"identity":"2f44b911-2ea4-4dcd-bd91-a1645a1d2130","added_by":"auto","created_at":"2026-04-02 15:11:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":17829210,"visible":true,"origin":"","legend":"\u003cp\u003eTherapeutic effects of BLP on body weight, glucose metabolism and therapeutic regulation in HFD-induced NAFLD mice. (A) Schematic of the therapeutic experimental design. (B) Percentage change in body weight over 12 weeks. (C) ITT and AUC results. (D) OGTT and AUC results.\u003cstrong\u003e \u003c/strong\u003e(E–H) Serum TG, TC, LDL-C and HDL-C levels. (I, J) Serum ALT and AST activities. (K) Representative liver images and H\u0026amp;E/Oil red O staining. and the scale bar at the lower right corner is 100 μm. (L) Liver weight ratio. (M–O) Hepatic TG, TC, and LDL - C levels.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/7b98001ef56c19ca7499fc29.png"},{"id":106030115,"identity":"4db038f8-4f31-46cb-992b-dd9032a48571","added_by":"auto","created_at":"2026-04-02 15:11:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5379623,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrated bioinformatic and molecular docking analyses reveal key targets of BLP in NAFLD. (A) Venn diagram showing overlapping targets between BLP phytochemicals and NAFLD-associated genes. (B) GO enrichment analysis highlighting biological processes (signal transduction, protein phosphorylation), cellular components (plasma membrane, nucleus), and molecular functions (protein kinase activity, enzyme binding). (C) KEGG pathway analysis showing significant enrichment in PI3K-AKT signaling, lipid metabolism, and other NAFLD-related pathways. (D) PPI network of core targets, illustrating key molecular interactions.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/b5c67de9ebd38cd949952282.png"},{"id":106030138,"identity":"e18fec44-57e9-4593-83e9-fe1a8a1dbbf0","added_by":"auto","created_at":"2026-04-02 15:11:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":742147,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Schematic diagram of the EGFR/PI3K/AKT/SREBP-1c signaling axis regulating hepatic lipid synthesis. (B–G) Relative mRNA levels of \u003cem\u003eEGFR\u003c/em\u003e (B), \u003cem\u003eIRSI\u003c/em\u003e (C), \u003cem\u003ePI3K\u003c/em\u003e (D), \u003cem\u003ePDK1\u003c/em\u003e(E), \u003cem\u003eAKT1\u003c/em\u003e (F), and \u003cem\u003eSREBP-1c\u003c/em\u003e (G) in mice liver tissues. (H) Relative mRNA levels of lipogenic genes in liver tissues. (I) Representative Western blot bands of tEGFR, p-EGFR, tAKT, p-AKT, PI3K, SREBP1, GAPDH and proteins related to inflammation (NF-κB，p-p65 and TLR4) in liver tissues. tEGFR, total EGFR; p-EGFR, Phosphorylated EGFR; tAKT, total AKT; p-AKT, Phosphorylated AKT; (J–Q) Relative protein expression (or phosphorylation ratio) of EGFR (J), p-EGFR/EGFR (K), AKT (L), p-AKT/AKT (M), PI3K (N), and SREBP-1c (O) in liver tissues. (P–R) Relative protein expression (or phosphorylation ratio) of TLR4 (Q) and p-p65/NF-κB (R) in liver tissues. Normal, chow diet; Model, HFD-induced NAFLD, Simvastatin: positive control, High, high-dose BLP. Data are presented as mean ± SEM (n = 6 per group). *\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, (vs. Model group; Mann–Whitney t-test).\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/899b0484b57e20f782d5f6f4.png"},{"id":106030092,"identity":"15dc2d5d-ac39-4baa-91ec-7ba0fe050760","added_by":"auto","created_at":"2026-04-02 15:11:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":18520351,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of BLP on gut microbiota composition in HFD-induced NAFLD mice. (A) PCoA plot showing microbial community separation. (B) Alpha diversity indices (Simpson and Chao1). (C) Circos plot illustrating taxonomic relationships and abundance changes. (D) Relative abundance of gut microbiota at the genus level. (E) LEfSe analysis identifying differentially abundant taxa among groups. (F) Spearman correlations (two-tailed Spearman’s rank test) of key genera with metabolic parameters. (G) Representative H\u0026amp;E-stained images of gut tissue from each group at 5× and 20× magnifications. The scale bar at the lower right corner is 250 μm. (H) The relative expression levels of \u003cem\u003eTLR4\u003c/em\u003e, ZO-1, \u003cem\u003eclaudin-1\u003c/em\u003e and \u003cem\u003eoccludin\u003c/em\u003egenes in the colon. (I) The relative expression levels of \u003cem\u003eIL-1β,\u003c/em\u003e \u003cem\u003eIL-6\u003c/em\u003e, and \u003cem\u003eTNF-α\u003c/em\u003e genes in the colon. Data are presented as mean ± SD or median with interquartile range (n = 6) and analyzed by two-tailed Student’s t-test or Mann–Whitney t-test. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01. PCoA, principal coordinate analysis; LEfSe, linear discriminant analysis effect size.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/b25aa412c753f733ac934456.png"},{"id":106030135,"identity":"3fe5faa4-e700-4ec8-aae5-ca172f4eab44","added_by":"auto","created_at":"2026-04-02 15:11:48","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"graphical-abstract","size":1273678,"visible":true,"origin":"","legend":"Broccoli leaves are commonly discarded during industrial processing despite being rich in bioactive phytochemicals, resulting in substantial resource waste. This study investigated the protective effects and underlying mechanisms of a microwave-assisted green extract of broccoli leaf phenolics (BLP) against high-fat diet (HFD)-induced non-alcoholic fatty liver disease (NAFLD). The LC-MS/MS profiling revealed that BLP is predominantly composed of cinnamic acid derivatives and flavonoids, notably sinapic acid, ferulic acid, kaempferol, and luteolin. In HFD-fed C57BL/6J mice, BLP supplementation significantly ameliorated hepatic steatosis and liver injury, evidenced by reduced serum AST, ALT, and lipid profiles (TG, TC, LDL). Mechanistically, BLP suppressed hepatic lipogenesis via SREBP-1c downregulation, modulated the EGFR/AKT/SREBP signaling pathway, and attenuated inflammatory responses by inhibiting the TLR4/NF-κB pathway and reducing pro-inflammatory cytokines (IL-6, IL-1β, TNF-α). Furthermore, BLP reinforced intestinal barrier integrity by upregulating tight junction proteins () and restored gut microbiota homeostasis, enriching beneficial taxa (, ) while suppressing dysbiosis-associated genera. Overall, BLP could exert hepatoprotective effects via the gut-liver axis, highlighting its immense potential as a value-added, food-derived functional ingredient for NAFLD prevention.","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/68197fb5cd76f356b607c148.png"},{"id":107485621,"identity":"0bf9cca6-a0ee-4fd5-9b5d-e299f72881c0","added_by":"auto","created_at":"2026-04-22 02:35:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":83142385,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/51d81f7c-3d6f-41d3-92d3-2f854eca6968.pdf"},{"id":106030098,"identity":"fd06062f-cc42-4621-a479-0432daa90aef","added_by":"auto","created_at":"2026-04-02 15:11:44","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":26992,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfilesupportingdata.docx","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/332336d65ca0d15b7a6218f6.docx"},{"id":106030136,"identity":"d306a487-7bcd-43b1-88f5-f6d5d61e866f","added_by":"auto","created_at":"2026-04-02 15:11:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":885521,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryfileuncroppedBlotsimages.docx","url":"https://assets-eu.researchsquare.com/files/rs-9194529/v1/06fba15b5e38ff13a8aafefb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Broccoli Leaf Phenolics Ameliorate NAFLD via Regulation of EGFR/AKT/SREBP Signaling Pathways and Gut Microbiota","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNon-alcoholic fatty liver disease (NAFLD) is a metabolic-related chronic liver disease characterized primarily by abnormal lipid deposition in the liver, also known as metabolic-associated fatty liver disease (MAFLD/MASLD) \u003csup\u003e1\u003c/sup\u003e. Its incidence has been steadily increasing due to the prevalence of obesity and metabolic syndrome, making it one of the most common chronic liver diseases worldwide \u003csup\u003e2\u0026ndash;3\u003c/sup\u003e. Currently, clinical intervention for NAFLD mainly relies on lifestyle modifications (such as dietary control and exercise intervention) and drug treatments targeting metabolic disorders such as insulin resistance and dyslipidemia \u003csup\u003e4\u003c/sup\u003e. However, poor long-term adherence, significant individual variability in efficacy, and potential adverse reactions still limit its widespread application. Therefore, developing safe, effective, and suitable novel prevention and treatment strategies for long-term intervention has become an important direction for NAFLD.\u003c/p\u003e \u003cp\u003ePlant extracts and concentrates have recently attracted increasing attention for their potential role in the prevention and treatment of NAFLD. Unlike single-target drugs, plant-derived bioactive compounds exert therapeutic effects through coordinated multi-target regulation, simultaneously modulating hepatic lipid metabolism, inflammatory responses, oxidative stress, and gut\u0026ndash;liver axis homeostasis by activating metabolic pathways such as AMPK and PPAR, inhibiting NF-κB mediated chronic inflammation, and reshaping gut microbiota composition and its metabolites \u003csup\u003e5\u0026ndash;7\u003c/sup\u003e. For example, flavonoid-rich mulberry leaf (\u003cem\u003eMorus\u003c/em\u003e) extract has been shown to effectively alleviate hepatic lipid deposition and inflammatory response in a high-fat diet-induced mice model by improving lipid metabolism, enhancing antioxidant capacity, and regulating gut microbiota structure \u003csup\u003e8\u003c/sup\u003e. Conjugated polyphenols from millet (\u003cem\u003eSetaria italica\u003c/em\u003e) have been reported to significantly improve NAFLD-related phenotypes by restoring gut microbiota balance, enhancing intestinal barrier function, and reducing hepatic lipid accumulation and inflammation levels \u003csup\u003e9\u003c/sup\u003e. These studies collectively demonstrate that plant extract concentrates can exert anti-NAFLD effects through the synergistic regulation of the gut-liver axis and multiple metabolic and inflammatory signaling pathways, highlighting their potential value as a safe, readily available, and suitable long-term intervention strategy for the prevention and treatment of metabolic diseases.\u003c/p\u003e \u003cp\u003eBroccoli (\u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eitalica\u003c/em\u003e), a member of the Cruciferae family, is widely consumed for its rich content of vitamin C, carotenoids, and glucosinolates, which exhibit antioxidant, anti-inflammatory, and potential anticancer activities \u003csup\u003e10\u0026ndash;13\u003c/sup\u003e. However, large quantities of leaves and stalks generated during cultivation and processing are typically discarded, leading to substantial resource waste. Our previous study showed that broccoli leaves contain significantly higher levels of flavonoids than florets, while maintaining comparable levels of total phenolics and vitamin C \u003csup\u003e10\u003c/sup\u003e. Among these bioactive constituents, phenolic acids have attracted considerable attention due to their potent antioxidant and antimicrobial properties, conferring broad application potential in the food, pharmaceutical, and cosmetic industries\u003csup\u003e13\u003c/sup\u003e. Major phenolic acids in broccoli include caffeic acid, chlorogenic acid, neochlorogenic acid, ferulic acid, and sinapic acid \u003csup\u003e14\u003c/sup\u003e. Despite these advantages, the valorization of broccoli leaves remains underexplored. Therefore, the development of green and efficient extraction strategies, together with systematic evaluation of their bioactivities, is essential to unlock their full potential. Water is an ideal green solvent due to its safety, environmental compatibility, availability, and low cost \u003csup\u003e11\u003c/sup\u003e. However, aqueous extraction processes for broccoli leaves have not yet been systematically optimized for the recovery and characterization of bioactive compounds.\u003c/p\u003e \u003cp\u003eIn this study, broccoli leaf phenolics (BLP), a plant-derived natural product, were selected as the primary focus. The phytochemical profile of BLP was comprehensively characterized, and its potential effects on NAFLD were evaluated using multiple animal models combined with integrated data analysis approaches. The safety of BLP was first assessed in mice, followed by the establishment of preventive and therapeutic models of high-fat diet (HFD)-induced NAFLD to investigate its effects on serum and hepatic lipid levels, liver injury markers, histopathological changes, inflammatory cytokines, and gut microbiota composition. In addition, a network pharmacology approach was employed to identify potential molecular targets, followed by enrichment analysis and molecular docking to elucidate the underlying mechanisms. This integrated strategy provides a systematic evaluation of the efficacy and mechanistic basis of BLP in alleviating NAFLD.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eBLP extraction and characterization\u003c/h2\u003e \u003cp\u003eThe green extraction process of BLP is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A comprehensive LC-MS/MS analysis of broccoli leaf extract identified 24 phenolic compounds (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), predominantly comprising cinnamic acids, flavonoids, and coumarins. Cinnamic acid derivatives constitute the primary phenolic group, with sinapic acid (14.45%) and ferulic acid (13.55%) accounting for over 28% of the total profile, accompanied by significant levels of valuable flavonoids, particularly kaempferol (9.86%) and luteolin (9.21%). These findings align with the typical phenolic profile of Brassica vegetables \u003csup\u003e15\u003c/sup\u003e. In addition, the total phenolic content of the extract, determined by the Folin\u0026ndash;Ciocalteu method, was 10\u0026ndash;14 mg GAE/g extract, providing quantitative support for the relative abundance observed in the LC\u0026ndash;MS/MS analysis. Notably, the substantial accumulation of both free and conjugated sinapic acid in the foliage indicates highly conserved secondary metabolite biosynthetic pathways compared to the widely studied edible florets \u003csup\u003e16\u003c/sup\u003e. Furthermore, high-resolution profiling facilitated the precise detection of minor glycosylated flavonoids and anthocyanins \u003csup\u003e17\u003c/sup\u003e, reflecting adaptive defense mechanisms against environmental stressors \u003csup\u003e18\u003c/sup\u003e. While some literature identifies chlorogenic acid as the major broccoli phenolic \u003csup\u003e19\u003c/sup\u003e, the present dataset revealed a relatively higher abundance of coumarins, such as bergaptol (5.89%), which may be attributed to genotypic or environmental variation. Notably, the application of microwave-assisted green extraction enabled efficient recovery of phenolic compounds while minimizing solvent consumption and processing time, supporting sustainable sample preparation. Overall, these results provide a comprehensive characterization of the phenolic composition of broccoli leaves and suggest that this underutilized biomass may serve as a promising and sustainable source of bioactive compounds with potential for value-added applications \u003csup\u003e20\u0026ndash;21\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhenolic compounds identified in broccoli leaf by LC-MS/MS.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMS2.name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFormula\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePeak area %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSinapic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC11H12O5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFerulic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC10H10O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaempferol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC15H10O6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaffeic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9H8O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBergaptol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC11H6O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoumarins and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-O-Sinapoyl-beta-D-glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC17H22O10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsoferulic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC10H10O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAstragalin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC21H20O11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4-Hydroxycinnamic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9H8O3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-Coumaraldehyde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9H8O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamaldehydes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLuteolin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC15H10O6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etrans-Cinnamic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9H8O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCyanidin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC15H11O6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2-Hydroxycinnamic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9H8O3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCinnamic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmbelliferone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9H6O3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoumarins and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaempferol 3-gentiobioside\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC27H30O16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6-Formylumbelliferone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC10H6O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoumarins and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCyanidin-3,5-diglucoside\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC27H31O16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCyanidin 3-galactoside\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC21H21O11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaempferol 3-(2''-(E)-feruloylgalactosyl-(1-\u0026amp;gt;4)-glucoside)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC37H38O19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAesculetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9H6O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoumarins and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-Hydroxyflavone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC15H10O3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlavonoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-(2-Hydroxyphenyl)propanoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9H10O3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhenylpropanoic acids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScopoletin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC10H8O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoumarins and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe Effect of BLP on NAFLD in Mice\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAssessing the Safety of BLP\u003c/h2\u003e \u003cp\u003eTo confirm safety, natural plant extracts require comprehensive toxicological assessment before their biological effects on metabolic disorders can be evaluated \u003csup\u003e22\u003c/sup\u003e. BLP were evaluated for toxicity and obesity-preventive effects in C57BL/6J mice. In the toxicity study (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), oral administration of BLP at 800 mg/kg caused no significant changes in body weight or in the weights of major organs (heart, spleen, lung, kidney, and brain) compared with the normal group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Histological analysis further confirmed biocompatibility, as the liver, kidney, and spleen of treated mice showed intact structures, similar to the normal group, indicating no acute toxicity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). These results confirmed that BLP exhibited good biocompatibility, which is consistent with previously published studies. Previous investigations have shown that 21-day oral administration of broccoli by-product powder in mice does not induce physiological abnormalities or hepatotoxicity \u003csup\u003e23\u003c/sup\u003e. In addition, hydrophilic extracts derived from broccoli by-products have been reported to be safe and to possess functional potential, supporting their applicability as functional food ingredients \u003csup\u003e24\u003c/sup\u003e. Moreover, broccoli seed extracts have been demonstrated to cause neither acute nor sub-chronic toxicity, further reinforcing the low-toxicity profile of broccoli-derived bioactive fractions \u003csup\u003e25\u003c/sup\u003e. Taken together, these studies provide a solid toxicological basis for the subsequent evaluation of the therapeutic efficacy of BLP in metabolic disease models.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe preventive effect of BLP on NAFLD in mice\u003c/h3\u003e\n\u003cp\u003eTo further assess the preventive effects of BLP on NAFLD, mice were administered BLP concomitantly with a high-fat diet for 10 weeks (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). In the HFD-induced NAFLD model, BLP produced a dose-dependent protective effect. All tested doses significantly reduced excessive body-weight gain compared with the Model group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Kidney and brain weight ratios were markedly altered in the Model group relative to the Normal group, whereas BLP treatment partially restored these indices (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH). Excessive weight gain and ectopic fat accumulation are major risk factors for NAFLD, primarily leading to increased hepatic lipid deposition \u003csup\u003e26\u003c/sup\u003e. For adipose tissue distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI), the fat weight ratios of inguinal white adipose tissue (iWAT), epididymal white adipose tissue (eWAT), and retroperitoneal white adipose tissue (rWAT) were significantly increased in the model group compared with the normal group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). BLP treatment reduced fat weight ratios in a dose-dependent manner, with the strongest effect observed in eWAT. Glucose metabolism disorders, particularly insulin resistance, are key drivers of NAFLD progression and exacerbate hepatic glucolipotoxicity \u003csup\u003e27\u003c/sup\u003e. Glucose homeostasis was evaluated using the oral glucose tolerance test (OGTT) and insulin tolerance test (ITT) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eK). Compared with the model group, BLP-treated mice showed improved glucose tolerance and enhanced insulin sensitivity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). OGTT and ITT curves showed smaller glycemic excursions, indicating better maintenance of glucose homeostasis.\u003c/p\u003e \u003cp\u003eDyslipidemia is closely linked to the onset and progression of NAFLD, and abnormal serum enzyme activities indicate liver injury \u003csup\u003e27\u003c/sup\u003e. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u0026ndash;C, serum triglyceride (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels were significantly increased in the model group. However, serum HDL-C levels remained comparable between the Model group and all treatment groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Both BLP and simvastatin treatments reduced these lipid levels, with the high-dose BLP group showing the strongest effect (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) activities were markedly elevated in the model group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF), whereas BLP-treated groups significantly lowered ALT and AST, indicating improved liver function. Gross liver morphology revealed clear hepatomegaly and discoloration in the model group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Histological analysis using H\u0026amp;E and Oil Red O staining showed severe hepatic steatosis in the model group, while BLP and simvastatin treatment markedly reduced lipid droplet accumulation. The liver weight radio (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG) and hepatic lipid contents (TC, TG, and LDL-C) were also significantly decreased by BLP treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH\u0026ndash;J). During the development of NAFLD, pro-inflammatory factors are released simultaneously \u003csup\u003e28\u003c/sup\u003e. Indeed, we found the proinflammatory cytokines including interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) were strongly upregulated in the model group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eK), but were significantly suppressed by BLP treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), confirming its anti-inflammatory and hepatoprotective effects \u003csup\u003e29\u003c/sup\u003e. Overall, these results indicate that BLP effectively alleviates HFD-induced NAFLD and associated metabolic disturbances. BLP reduces excessive weight gain and modulates adipose tissue distribution, lowering peripheral drivers of hepatic lipid accumulation. It improves glucose tolerance and insulin sensitivity, relieving metabolic stress on the liver, while correcting dyslipidemia and reducing hepatic enzyme leakage. Importantly, BLP downregulates proinflammatory cytokine expression, providing strong evidence for its anti-inflammatory and liver-protective properties.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eThe therapeutic potential of BLP on NAFLD in mice\u003c/h3\u003e\n\u003cp\u003e To investigate the therapeutic potential of BLP in a high-fat diet\u0026ndash;induced NAFLD model, mice were fed a high-fat diet for 14 weeks to establish NAFLD, followed by BLP treatment for an additional 14 weeks (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Compared with the normal group, the model group (HFD) exhibited significant body weight gain, whereas BLP-treated groups (Low and High) and the simvastatin group showed varying degrees of inhibition of weight gain (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which was consistent with the results observed in the NAFLD prevention experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Body weight regulation is crucial for metabolic health, as excessive weight gain is a key risk factor for NAFLD, and interventions that limit weight gain often improve metabolic homeostasis \u003csup\u003e30\u003c/sup\u003e. For glucose homeostasis, ITT results indicated that the model group developed insulin resistance, while treatment groups enhanced insulin sensitivity, as reflected by greater reductions in blood glucose following insulin injection (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). OGTT results showed elevated blood glucose in the model group at all time points (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas BLP treatment improved glucose tolerance, with lower glucose levels at 30, 60, 90, and 120 minutes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Impaired glucose tolerance and insulin resistance are central to NAFLD pathogenesis, promoting hepatic lipid accumulation and metabolic dysfunction \u003csup\u003e31\u003c/sup\u003e. The improvement in these parameters by BLP suggests its potential to target key metabolic defects in NAFLD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn serum lipid profiles, the model group showed significantly higher TG, TC, and LDL-C levels compared with the normal group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating HFD-induced dyslipidemia (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u0026ndash;G). However, serum HDL-C levels did not differ significantly among the treatment groups. (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH). In addition, serum AST and ALT activities were markedly increased, suggesting hepatic injury (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ). Both simvastatin and BLP treatments (Low and High doses) significantly reduced these indicators, with the high-dose BLP group approaching normal levels, indicating dose-dependent improvements in lipid metabolism and liver function. Gross liver morphology revealed severe hepatomegaly and pale coloration in HFD-fed mice, whereas BLP-treated mice showed visibly improved liver appearance (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eL). Histological analyses corroborated these findings that H\u0026amp;E staining revealed substantial lipid droplet accumulation and hepatocellular ballooning in the HFD group, which were alleviated by BLP, while Oil Red O staining demonstrated significant reductions in hepatic lipid deposition in BLP-treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK). Liver function assessments showed that the Model group had higher liver weight ratios (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eL) and elevated intrahepatic TG, TC, and LDL-C levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eM-O), consistent with the severe histological changes. Collectively, these results indicate that BLP supplementation effectively mitigates HFD-induced obesity, hyperlipidemia, hyperglycemia, and hepatic steatosis. The beneficial effects may be attributed to bioactive phytochemicals in broccoli leaves, which regulate lipid and glucose metabolism, enhance antioxidant defense, and suppress hepatic fat accumulation. These findings highlight the potential of BLP as a dietary intervention for the prevention and management of NAFLD and related metabolic disorders. Based on the evaluation of all the above animal test results, mice in the prevention group were selected for further mechanistic studies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMechanistic Investigation of BLP in Improving NAFLD\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eInvestigate Potential Active Compounds Using Network Pharmacology\u003c/h2\u003e \u003cp\u003eTo explore and predict the potential molecular targets underlying the effects of BLP on NAFLD, 22 phenolics metabolites identified through LC-MS/MS analysis were subjected to screening in the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). The possible targets of these compounds were then predicted using SwissTarget Prediction, yielding a total of 457 targets. In parallel, 3,142 NAFLD-related targets were collected from GeneCards, OMIM, and TTD databases (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). To further investigate the potential mechanisms underlying the therapeutic effects of BLP, we performed bioinformatic analyses. A Venn diagram revealed 134 overlapping targets between BLP phytochemicals and NAFLD-related targets, suggesting potential key mediators of the extract's action (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Gene Ontology (GO) enrichment analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) showed that these overlapping targets were significantly enriched in biological processes such as signal transduction, protein phosphorylation, and positive regulation of transcription by RNA polymerase II; cellular components including plasma membrane, nucleus, and membrane; and molecular functions such as protein serine/threonine kinase activity, protein kinase activity, and enzyme binding. This pattern is consistent with previous NAFLD studies. Previous studies have shown that disease-relevant genes are enriched in signal transduction, membrane and nuclear compartments, and kinase-related functions, supporting the biological relevance of our findings \u003csup\u003e32\u003c/sup\u003e. KEGG pathway analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC) indicated that these targets were involved in multiple signaling pathways, with the PI3K\u0026ndash;AKT signaling pathway, lipid and atherosclerosis pathway, and Alzheimer disease pathway being the most significantly enriched. The protein\u0026ndash;protein interaction (PPI) network (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) further visualized interactions among key targets and highlighted core proteins that may play central roles in mediating the biological effects of BLP. These bioinformatic results provide insights into the potential molecular mechanisms of BLP in ameliorating HFD-induced NAFLD. The overlap between phytochemical targets and disease-related targets suggests that BLP acts by modulating specific molecular nodes involved in NAFLD pathogenesis. Enrichment in GO terms related to signal transduction and protein phosphorylation implies that BLP may regulate intracellular signaling cascades essential for metabolic control and cell function. Notably, the PI3K\u0026ndash;AKT pathway, a central regulator of cell growth, survival, and metabolism, is closely linked to insulin resistance and hepatic lipid accumulation, key features of NAFLD \u003csup\u003e33\u0026ndash;34\u003c/sup\u003e. Modulation of this pathway by BLP may improve insulin sensitivity and reduce hepatic steatosis. Furthermore, enrichment in the lipid and atherosclerosis pathway aligns with the observed reductions in serum lipid levels in vivo. The PPI network identifies core proteins that may serve as pivotal nodes in BLP-mediated molecular interactions, providing promising targets for further mechanistic studies.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eResearch on the Mechanism of BLP Regulating the PI3K-AKT Pathway\u003c/h3\u003e\n\u003cp\u003eTo clarify how BLP enhances HFD-induced NAFLD, we will perform analyze liver gene and protein expression levels associated with the PI3K-AKT signaling pathway. The transcription and protein levels of the EGFR\u0026ndash;PI3K\u0026ndash;AKT\u0026ndash;SREBP-1c signaling cascade (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA) were measured by RT-qPCR and Western blotting. RT-qPCR analysis of mice liver tissue showed that the Model group had higher mRNA expression of \u003cem\u003eEGFR\u003c/em\u003e and \u003cem\u003eAKT1\u003c/em\u003e than the Normal group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). However, BLP and simvastatin treatment reduced their expression to near-normal levels. In addition, the transcripts of the \u003cem\u003eEGFR\u0026ndash;AKT\u003c/em\u003e cascade (\u003cem\u003ePI3K\u003c/em\u003e and \u003cem\u003eIRS1\u003c/em\u003e gene) were also upregulated in the model group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). The expression of SREBP-1c and its adipogenic target genes was increased as well (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH). These results were consistent with the activation of de novo lipogenesis at the early stage of pathology. Furthermore, Western blotting confirmed that the model group showed higher protein levels of phosphorylated EGFR (p-EGFR) and phosphorylated AKT (p-AKT) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI). The PI3K and SREBP-1c protein levels were also elevated, indicating activation of the EGFR\u0026ndash;PI3K\u0026ndash;AKT\u0026ndash;SREBP-1c pathway. In contrast, BLP intervention reduced p-EGFR, p-AKT, and SREBP-1c levels, while total AKT remained unchanged (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ-O). Thus, the regulatory effect of BLP was mainly achieved by blocking phosphorylation-dependent activation rather than by lowering AKT protein abundance. These molecular changes were associated with reduced hepatic lipid deposition, suggesting suppression of lipid production. Furthermore, it is noteworthy that AKT not only acts as a linker growth factor regulating lipid metabolism but also serves as a central signaling node in the inflammatory response \u003csup\u003e35\u003c/sup\u003e. TLR4 can activate HFD-induced liver inflammation, further enhancing PI3K/AKT signaling\u003csup\u003e36\u003c/sup\u003e. In mouse liver, the model group showed upregulation of TLR4 and p-p65/NF-κB expression (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while simvastatin and BLP significantly inhibited these upregulations (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eP-R). This is similar to previous results, where many natural compounds often simultaneously regulate both hepatic lipid metabolism and inflammatory signaling pathways. For example, compounds such as berberine and flavanones from citrus extracts can simultaneously inhibit PI3K/AKT-related lipid metabolism signaling pathways and suppress TLR4/NF-κB activation to alleviate metabolic inflammation \u003csup\u003e35,37\u003c/sup\u003e. Overall, the data highlighted the specific molecular targets and regulatory pattern of potential bioactive components in BLP in NAFLD. BLP showed regulatory effects similar to simvastatin, supporting its potential as a natural treatment for NAFLD. Nevertheless, interactions among multiple phytochemicals in BLP and the network of NAFLD-related targets remain to be clarified. Future studies should examine possible synergistic actions among these compounds and conduct mechanistic experiments to verify the roles of AKT1 and EGFR.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEffect of BLP on Gut Microbiota, Intestinal Barrier Function and Inflammation\u003c/h2\u003e \u003cp\u003eThe role of gut microbiota in regulating NAFLD through the gut\u0026ndash;liver axis has received increasing attention \u003csup\u003e38\u003c/sup\u003e. The gut microbiota plays a key role in the development and progression of NAFLD through multiple mechanisms, including increased energy harvesting, altered intestinal barrier function, and production of metabolites \u003csup\u003e39\u003c/sup\u003e. To investigate the impact of BLP treatments on microbial community composition and structure, 16S rRNA sequencing of fecal samples from three groups of mice was performed. Principal coordinate analysis (PCoA) based on Bray\u0026ndash;Curtis dissimilarity (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA) revealed clear separation of the microbial communities among the normal, model, and high-dose groups, with PC1 and PC2 explaining 35.63% and 10.47% of the variation, respectively. Notably, the high-dose group was positioned between the normal and model groups, suggesting that BLP could partially reshape gut microbiota composition \u003csup\u003e40\u003c/sup\u003e. The Simpson index reflects the microbial diversity of the gut microbiota, describing how evenly species are distributed. The Chao1 index estimates species richness, indicating the total number of bacterial species. Together, these indices describe the overall structure of the gut microbial community \u003csup\u003e41\u003c/sup\u003e. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, the Simpson index was significantly reduced in the model group compared with the normal group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereas high-dose treatment restored microbial diversity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Similarly, the Chao1 index showed corresponding changes. At the genus level, 16S rRNA sequencing indicated that the fecal microbiota of mice fed with a normal diet was dominated by \u003cem\u003eBacteroides\u003c/em\u003e and \u003cem\u003eMuribaculaceae\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD), consistent with previous reports highlighting their abundance in healthy gut ecosystems and their protective role against metabolic disorders \u003csup\u003e42\u003c/sup\u003e. In contrast, HFD-induced NAFLD mice exhibited a marked increase in potentially pathogenic genera such as \u003cem\u003eRikenella, Alistipes\u003c/em\u003e, and \u003cem\u003eOdoribacter\u003c/em\u003e, taxa that have been frequently associated with metabolic inflammation and NAFLD progression \u003csup\u003e43\u003c/sup\u003e.High-dose BLP reversed these changes, suppressing harmful taxa and promoting beneficial bacteria such as \u003cem\u003eLachnoclostridium\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, and \u003cem\u003eDubosiella\u003c/em\u003e, which have been reported to enhance gut barrier function, regulate bile acid metabolism, and reduce hepatic lipid accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE) \u003csup\u003e44\u0026ndash;45\u003c/sup\u003e.Collectively, these findings suggest that the hepatoprotective effects of BLP are partially mediated through modulation of the gut microbiota and restoration of microbial balance disrupted by HFD. The correlation analysis further quantified the relationships between differential microbial taxa and individual samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF). The results revealed significant associations between specific gut microbial genera and metabolic parameters related to NAFLD, highlighting potential links between gut dysbiosis and disease progression. \u003cem\u003eRikenella\u003c/em\u003e, \u003cem\u003eAlistipes\u003c/em\u003e, and \u003cem\u003eColidextribacter\u003c/em\u003e showed positive correlations with serum TC, TG, and liver TG, suggesting these taxa may exacerbate lipid dysregulation. For example, \u003cem\u003eColidextribacter\u003c/em\u003e can influence cholesterol metabolism in the gut, affecting absorption and systemic lipid balance, potentially promoting NAFLD \u003csup\u003e45\u003c/sup\u003e. In contrast, \u003cem\u003eFaecalibaculum\u003c/em\u003e, \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eBlautia\u003c/em\u003e, and \u003cem\u003eOdoribacter\u003c/em\u003e exhibited negative correlations, consistent with their protective roles. \u003cem\u003eFaecalibaculum\u003c/em\u003e, in particular, is linked to improved lipid profiles and reduced metabolic disorder risk, likely via short-chain fatty acid production or immune modulation \u003csup\u003e46\u003c/sup\u003e. \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eBlautia\u003c/em\u003e, and \u003cem\u003eOdoribacter\u003c/em\u003e may similarly limit lipid accumulation and inflammation \u003csup\u003e47\u003c/sup\u003e. Overall, these results indicate that BLP improves metabolic health, at least in part, by modulating gut microbiota diversity and composition. High-dose BLP treatment markedly reduced the abundance of pathogenic taxa linked to inflammation and metabolic dysfunction, while promoting beneficial bacteria, thereby contributing to the restoration of gut microbial balance and overall intestinal homeostasis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlterations in gut microbiota have been implicated in intestinal barrier dysfunction along the gut\u0026ndash;liver axis. Therefore, intestinal barrier integrity and permeability were evaluated in mice from the different treatment groups. H\u0026amp;E staining results showed that, compared with the normal group, the model group mice exhibited significant mucosal structural damage and inflammatory cell infiltration in the intestine (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG). BLP showed a similar effect to simvastatin, inhibiting intestinal damage. The mRNA expression levels of tight junction genes and pro-inflammatory cytokines related to intestinal barrier integrity also showed a similar trend. Compared with the Model group, BLP significantly inhibited TLR4 expression in the intestine and promoted the expression of ZO-1, Claudin-1, and Occludin (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH). Simultaneously, BLP treatment significantly reduced the mRNA levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α), indicating that BLP not only improved intestinal barrier function damaged by HFD but also inhibited intestinal inflammation (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eI). Collectively, these results demonstrate that BLP alleviates HFD-induced gut microbiota dysbiosis by restoring microbial diversity and favorably reshaping microbial composition. Concomitantly, BLP preserves intestinal barrier integrity and suppresses intestinal inflammation, thereby potentially interrupting the pathological gut\u0026ndash;liver axis that contributes to hepatic lipid accumulation and NAFLD progression.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, broccoli leaf phenolics (BLP) were obtained using a green extraction approach, incorporating microwave-assisted technology, and their chemical composition was characterized by LC\u0026ndash;MS/MS-based analysis. The results demonstrated that BLP is rich in diverse phenolic compounds, particularly cinnamic acid derivatives and flavonoids. In vivo experiments further showed that BLP alleviated high-fat diet (HFD)-induced NAFLD, as evidenced by improved metabolic parameters, reduced hepatic steatosis and inflammation, and no observable toxicity to major organs. In addition, BLP mitigated intestinal inflammation and barrier dysfunction and modulated the gut microbiota by increasing the relative abundance of beneficial genera, including \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eBlautia\u003c/em\u003e, and \u003cem\u003eOdoribacter\u003c/em\u003e. Integrated bioinformatics analysis, together with RT-qPCR and Western blot validation, suggested that these effects may be associated with the regulation of PI3K\u0026ndash;AKT signaling, lipid metabolism, and inflammatory pathways. Notably, the application of green extraction technology, particularly microwave-assisted processing, enabled efficient recovery of phenolic compounds while reducing solvent consumption and extraction time. Collectively, these findings indicate that BLP represents a promising and sustainable source of bioactive compounds with potential for NAFLD intervention, while also providing a feasible strategy for the value-added utilization of broccoli leaf by-products in the context of green and sustainable food processing.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eFresh \u0026lsquo;Youxiu\u0026rsquo; broccoli by-product leaves were collected in June 2024 from the SanJiaoCheng Township, Yuzhong County, Lanzhou City, Gansu Province (China). All chemicals used in this study were UPLC grade.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSample Preparation\u003c/h2\u003e \u003cp\u003eThe green extraction process of broccoli leaf phenolics (BLP) is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Fresh broccoli leaves were washed, dried, and pulverized. After cleaning, the leaves were cut into small pieces and evenly distributed on drying trays (Changsheng Machinery Co., Ltd., CS-6CHZ-9), followed by drying at 45\u0026deg;C for 60 h until the moisture content was below 6%. The Vornoli et al. \u003csup\u003e48\u003c/sup\u003e technique was used to make the water extract. A wall-breaking machine (Zhongshan Huiren Electric Appliance Co., Ltd., 919E) was used to crush the dried leaves before they were put through an 80-mesh sieve. The powder was completely dissolved in 200 mg/mL of distilled water and ultrasonicated for one hour at room temperature (KQ-30L, Zhengzhou Yuhua Instrument Manufacturing Co., Ltd.), and then stirred on a magnetic stirrer (IKA C-MAG HS7) at 600 rpm for 1 h. The mixture was centrifuged at 4000 rpm, and the supernatant was collected, stored at \u0026minus;\u0026thinsp;80\u0026deg;C, and freeze-dried using a vacuum dryer (Boyikang, Pilot2\u0026ndash;4 m, China). For in vivo experiments, the freeze-dried powder was resuspended in water at the required concentration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePhenolics concentration measurement\u003c/h2\u003e \u003cp\u003eThe total phenolic content (TPC) of the freeze-dried extract was determined using the Folin\u0026ndash;Ciocalteu method. Briefly, the sample was dissolved in distilled water and centrifuged, and 100 \u0026micro;L of the supernatant was mixed with 500 \u0026micro;L of 10-fold diluted Folin\u0026ndash;Ciocalteu reagent. After 5 min, 400 \u0026micro;L of sodium carbonate solution (7.5%, w/v) was added, followed by incubation in the dark for 30 min at room temperature. The absorbance was measured at 765 nm. Gallic acid was used to generate the calibration curve (R\u0026sup2; \u0026gt; 0.99), and the results were expressed as mg gallic acid equivalents per gram of extract (mg GAE/g extract). All measurements were performed in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAnimal experiments\u003c/h2\u003e \u003cp\u003e All animal experiments were approved by the Animal Care and Use Committee of China Agricultural University (AW12106202-5-02). \u003cb\u003e(1) Safety assessment\u003c/b\u003e: Male C57BL/6J mice that were eight weeks old were kept in controlled environments with free access to food and water (22\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C, 40\u0026ndash;60% humidity, and a 12-hour light/dark cycle). Following a week of acclimatization, mice were divided into two groups at random: BLP-treated (800 mg/kg/day BLP, by oral gavage) and control (normal chow). Body weight and food consumption were monitored every day for the duration of the treatment \u003csup\u003e49\u003c/sup\u003e. \u003cb\u003e(2) Preventive experiments\u003c/b\u003e: Thirty 6-week-old male C57BL/6J mice were randomly assigned to five groups (n\u0026thinsp;=\u0026thinsp;6 per group) after being acclimated to the same conditions: normal (standard chow), model (high-fat diet, HFD), simvastatin (HFD\u0026thinsp;+\u0026thinsp;10 mg/kg/day simvastatin), low-dose BLP (HFD\u0026thinsp;+\u0026thinsp;300 mg/kg/day BLP), and high-dose BLP (HFD\u0026thinsp;+\u0026thinsp;600 mg/kg/day BLP). Treatment lasted 10 weeks. Body weight was recorded weekly, and food and water intake were measured every 2\u0026ndash;3 days \u003csup\u003e50\u003c/sup\u003e. \u003cb\u003e(3) Therapeutic experiments\u003c/b\u003e: Another group of thirty 6-week-old male C57BL/6J mice was housed under the same conditions, acclimated for 1 week, and randomly assigned to five groups: normal (standard chow), model (HFD), simvastatin (HFD), low-dose BLP (HFD), and high-dose BLP (HFD). After 14 weeks on their diets, simvastatin and BLP treatments were started at 10, 300, and 600 mg/kg/day, respectively, by oral gavage and continued for another 14 weeks \u003csup\u003e51\u003c/sup\u003e. At the end of each experiment, mice were fasted for 8 h with free access to water, weighed, and euthanized by retro-orbital blood collection followed by cervical dislocation. Tissues were collected and weighed for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eBiochemical Analysis\u003c/h2\u003e \u003cp\u003eAs directed by the manufacturer, commercial test kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) were used to assess biochemical parameters in the liver and serum of mice. Aspartate aminotransferase (AST, No. C010-2-1), alanine aminotransferase (ALT, No. C009-2-1), total cholesterol (TC, No. A111-1-1), low-density lipoprotein cholesterol (LDL-C, No. A113-1-1), high-density lipoprotein cholesterol (HDL-C, No. A112-1-1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eDetection of histopathology in mice\u003c/h2\u003e \u003cp\u003eAfter euthanasia, the liver and other tissues were quickly removed and fixed in 4% paraformaldehyde for 24 h. Samples were then embedded in paraffin and cut into 5 \u0026micro;m sections. Hematoxylin and eosin (H\u0026amp;E) staining was used to examine tissue structure. Additional liver samples were embedded in OCT compound, cryosectioned, and stained with Oil Red O to assess lipid accumulation. All sections were examined and imaged with a light microscope. Histological scoring was performed based on steatosis (micro- and macrovesicular), lobular inflammation, hepatocyte ballooning, and fibrosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eOral Glucose Tolerance Test (OGTT) and Insulin Tolerance Test (ITT)\u003c/h2\u003e \u003cp\u003eTo evaluate glucose homeostasis, OGTT and ITT were performed at weeks 12 and 13 of the KSP intervention, respectively. For the OGTT, mice were fasted for 8 h with free access to water. Baseline blood glucose (0 min) was measured from tail vein blood using a standard glucometer. Mice were then orally administered glucose (2 g/kg body weight), and blood glucose levels were recorded at 30, 60, 90, and 120 min post-gavage. For the ITT, following a 6 h fast, mice received an intraperitoneal injection of insulin (1 U/kg body weight), with blood glucose monitored at the same time intervals. The area under the curve (AUC) for both tests was calculated using the standard trapezoidal rule.\u003c/p\u003e \u003cp\u003e \u003cb\u003e16S rRNA gene sequencing and data analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe DNeasy PowerSoil Kit was used to extract total DNA from culture or fecal samples (Qiagen, Hilden, Germany). On a Bio-Rad PCR system, the V3\u0026ndash;V4 region of the 16S rRNA gene was amplified using universal primers in 25 \u0026micro;L PCR reactions. Agencourt AMPure XP magnetic beads (Beckman Coulter, USA) were used to purify the PCR products after they were separated by agarose gel electrophoresis. A Qubit dsDNA test kit was then used to quantify the results. OE Biotech Co., Ltd. (Shanghai, China) used an Illumina MiSeq platform (Illumina Inc., San Diego, CA) to pool and sequence equimolar amplicons.\u003c/p\u003e \u003cp\u003eCutadapt was used to eliminate adapters from raw sequencing data (FASTQ). DADA2 in QIIME2 (version 2020.11) was used for filtering, denoising, merging, and chimera elimination. The Silva v138 database was used to create amplicon sequence variations (ASVs) and assign taxonomy to representative sequences using the q2-feature-classifier plugin. QIIME2 was used for principal coordinates analysis (PCoA), phylogenetic tree building, alpha diversity (Chao1, Shannon), and UniFrac distance matrices.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eLC-MS/MS analysis\u003c/h2\u003e \u003cp\u003e80% methanol was used to extract tissue metabolites \u003csup\u003e52\u003c/sup\u003e. 50 mg of tissue was homogenized in 0.5 mL of pre-chilled 80% methanol, incubated for 30 minutes at -20\u0026deg;C, and then centrifuged at 20,000 \u0026times; g for 15 minutes at 4\u0026deg;C. The supernatants were moved, vacuum-dried, reconstituted in 100 \u0026micro;L of 80% methanol, and kept at -80\u0026deg;C. Ten microliters of each extract were combined to create quality control (QC) samples. An UltiMate 3000 UPLC system (Thermo Fisher) with a T3 column (100 mm \u0026times; 2.1 mm, 1.8 \u0026micro;m; Waters) was used for the LC-MS analysis at 40\u0026deg;C. Solvent A (5 mM ammonium acetate and 5 mM acetic acid in water) and solvent B (acetonitrile) were used as mobile phases at a rate of 0.3 mL/min. 0\u0026ndash;0.8 min, 2% B; 8.0\u0026ndash;8.1 min, 100\u0026ndash;2% B; 8.1\u0026ndash;10.0 min, 2% B. Metabolites were found in both positive and negative ion modes using a Q-Exactive high-resolution mass spectrometer (Thermo Scientific). At 70,000 resolutions (AGC 3e6, 100 ms), precursor spectra (70\u0026ndash;1050 m/z) were obtained. At 17,500 resolutions (AGC 1e5, 80 ms), the top three DDA modes gathered fragment spectra. To guarantee stability, QC samples were conducted every ten injections.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eNetwork pharmacology\u003c/h2\u003e \u003cp\u003eWe estimated the active components and important targets of BLP using previously reported methods \u003csup\u003e53\u003c/sup\u003e. Potential active molecules of BLP were found using SwissTargetPrediction (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.swisstargetprediction.ch/\u003c/span\u003e\u003cspan address=\"https://www.swisstargetprediction.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the TCMSP database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://old.tcmsp-e.com/tcmsp.php\u003c/span\u003e\u003cspan address=\"https://old.tcmsp-e.com/tcmsp.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The SMILES structures required for SwissTargetPrediction were supplied by PubChem (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Using the phrase \"NAFLD,\" GeneCards (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), OMIM (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://omim.org/\u003c/span\u003e\u003cspan address=\"https://omim.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and TTD (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://idrblab.net/ttd/\u003c/span\u003e\u003cspan address=\"https://idrblab.net/ttd/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) provided illness-related targets for nonalcoholic fatty liver disease (NAFLD). After gathering all of the targets, duplicates were removed. The overlapping targets between BLP and NAFLD were visualized using Venny (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.liuxiaoyuyuan.cn/\u003c/span\u003e\u003cspan address=\"https://www.liuxiaoyuyuan.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The DAVID database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://davidbioinformatics.nih.gov/summary.jsp\u003c/span\u003e\u003cspan address=\"https://davidbioinformatics.nih.gov/summary.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used for the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment studies. A compound\u0026ndash;target\u0026ndash;pathway network was constructed using the active compounds, relevant targets, and enriched pathways.Overlapping targets were further investigated by building a protein\u0026ndash;protein interaction (PPI) network using STRING 11.5 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The CentiScape 2.2 plugin in Cytoscape 3.9.1 was used to perform topological analysis of the PPI network in order to identify key genes.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eRNA Extraction and Real-Time Quantitative PCR (RT-qPCR)\u003c/h2\u003e \u003cp\u003eThe TRIzol reagent (TIANGEN, Beijing, China) was used to extract total RNA from colon tissue. Using a first-strand cDNA synthesis kit (TIANGEN, Beijing, China), 1 \u0026micro;g of RNA was converted into first-strand cDNA. The 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e technique was used to calculate the levels of gene expression. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e lists the sequences of the primers that were acquired from Qingke Company.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot\u003c/h2\u003e \u003cp\u003eIn accordance with previously published procedures, liver tissue was separated \u003csup\u003e54\u003c/sup\u003e. In ice-cold RIPA lysis solution supplemented with a 1% phosphatase and protease inhibitor cocktail, the obtained liver tissue was homogenized. On 4\u0026ndash;20% SDS\u0026ndash;PAGE gels, equal volumes of total protein (30 \u0026micro;g per lane) were separated before being deposited onto 0.22 \u0026micro;m PVDF membranes (Millipore, Billerica, MA, USA). Following blocking, primary antibodies against EGFR (1:750), p-EGFR (1:750), AKT (1:1500), p-AKT (1:1500), PI3K (1:1000), SREBP1 (1:750), GAPDH (1:4000), NK-κB (1:750), p-p65 (1:400), and TLR4 (1:750) were used as a loading control. The membranes were then exposed to an HRP-conjugated goat anti-rabbit IgG secondary antibody (1:5000) for 45 minutes at room temperature. An enhanced chemiluminescence (ECL) detection kit (Wuhan Aibotek Biotechnology Co., Ltd.) was used to observe protein bands, and a Bio-OI imaging system (OI600, Guangzhou Guangyi Biotechnology Co., Ltd.) was used to take pictures. ImageJ software (NIH, Bethesda, MD, USA) was used to quantify band intensities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eR software (version 4.2.2) was used to conduct bioinformatics studies. SPSS 23.0 (IBM, Armonk, NY, USA) was used for statistical analysis, and Origin Pro 2021 (OriginLab, Northampton, MA, USA) was used for data visualization. Every outcome is displayed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). One-way analysis of variance (ANOVA) was used to examine group differences. Statistical significance was defined as a p-value\u0026lt;0.05.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAuthor Contributions Statement\u003c/b\u003e \u003c/p\u003e \u003cp\u003eYaqi Zhao: Data curation, Methodology, Software, Writing-Original draft; Wenyuan Zhang: Writing-Reviewing and Editing, Methodology, Software; Yuanshou Zhao: Data curation, Methodology; Yue Li: Writing \u0026ndash; review \u0026amp; editing; Qian Wang: Methodology; Zhanquan Zhang: Writing \u0026ndash; review \u0026amp; editing. Haixia Yang: Writing-Reviewing and Editing; Liwang Liu: Writing \u0026ndash; review \u0026amp; editing; Jianjun Deng: Conceptualization, Writing- Reviewing and Editing, Supervision, Project administration.\u003c/p\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eData availability statement\u003c/h2\u003e \u003cp\u003eThe data supporting the findings of this study are available from the corresponding author upon request.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eResearch funding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Innovation Program of the Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2024-IVF) and Central Public-interest Scientific Institution Basal Research Fund (IVF-BRF2024005, IVF-BRF2024003).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest:\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eSupporting Information description\u003c/h2\u003e \u003cp\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The primers for RT-qPCR.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYaqi Zhao: Data curation, Methodology, Software, Writing-Original draft; Wenyuan Zhang: Writing-Reviewing and Editing, Methodology, Software; Yuanshou Zhao: Data curation, Methodology; Yue Li: Writing \u0026ndash; review \u0026amp; editing; Qian Wang: Methodology; Zhanquan Zhang: Writing \u0026ndash; review \u0026amp; editing. Haixia Yang: Writing-Reviewing and Editing; Liwang Liu: Writing \u0026ndash; review \u0026amp; editing; Jianjun Deng: Conceptualization, Writing- Reviewing and Editing, Supervision, Project administration.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eYaqi Zhao: Data curation, Methodology, Software, Writing-Original draft; Wenyuan Zhang: Writing-Reviewing and Editing, Methodology, Software; Yuanshou Zhao: Data curation, Methodology; Yue Li: Writing \u0026ndash; review \u0026amp; editing; Qian Wang: Methodology; Zhanquan Zhang: Writing \u0026ndash; review \u0026amp; editing. Haixia Yang: Writing-Reviewing and Editing; Liwang Liu: Writing \u0026ndash; review \u0026amp; editing; Jianjun Deng: Conceptualization, Writing- Reviewing and Editing, Supervision, Project administration\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVancells Lujan, P., Vinas Esmel, E., Sacanella Meseguer, E. Overview of non-alcoholic fatty liver disease (NAFLD) and the role of sugary food consumption and other dietary components in its development. \u003cem\u003eNutrients\u003c/em\u003e 2021, 13, 1442. https://doi.org/10.3390/nu13051442.\u003c/li\u003e\n\u003cli\u003eChen, J. F., Wu, Z. Q., Liu, H. S., Yan, S., Wang, Y. X., Xing, M., Dong, X. Q., Ding, S. Y. 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A., Liu, D., Liu, H.R., Sun, J. Y., Li, N. Y., Liu, C. Pomegranate peel extract alleviates diabetic retinopathy by suppressing the PI3K/AKT/HIF-1α/VEGF pathway and gut microbiota modulation. \u003cem\u003eJ. Adv. Res.\u003c/em\u003e 2025, in press. https://doi.org/10.1016/j.jare.2025.10.048.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Broccoli leaf water extract, Non-alcoholic fatty liver disease, Network pharmacology, EGFR/AKT/SREBP pathway, Gut microbiota","lastPublishedDoi":"10.21203/rs.3.rs-9194529/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9194529/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Broccoli leaves are commonly discarded during industrial processing despite being rich in bioactive phytochemicals, resulting in substantial resource waste. This study investigated the protective effects and underlying mechanisms of a microwave-assisted green extract of broccoli leaf phenolics (BLP) against high-fat diet (HFD)-induced non-alcoholic fatty liver disease (NAFLD). The LC-MS/MS profiling revealed that BLP is predominantly composed of cinnamic acid derivatives and flavonoids, notably sinapic acid, ferulic acid, kaempferol, and luteolin. In HFD-fed C57BL/6J mice, BLP supplementation significantly ameliorated hepatic steatosis and liver injury, evidenced by reduced serum AST, ALT, and lipid profiles (TG, TC, LDL). Mechanistically, BLP suppressed hepatic lipogenesis via SREBP-1c downregulation, modulated the EGFR/AKT/SREBP signaling pathway, and attenuated inflammatory responses by inhibiting the TLR4/NF-κB pathway and reducing pro-inflammatory cytokines (IL-6, IL-1β, TNF-α). Furthermore, BLP reinforced intestinal barrier integrity by upregulating tight junction proteins () and restored gut microbiota homeostasis, enriching beneficial taxa (, ) while suppressing dysbiosis-associated genera. Overall, BLP could exert hepatoprotective effects via the gut-liver axis, highlighting its immense potential as a value-added, food-derived functional ingredient for NAFLD prevention.","manuscriptTitle":"Broccoli Leaf Phenolics Ameliorate NAFLD via Regulation of EGFR/AKT/SREBP Signaling Pathways and Gut Microbiota","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-02 15:10:00","doi":"10.21203/rs.3.rs-9194529/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"17f98476-35d5-4f7d-99ff-dbe3281b1a1b","owner":[],"postedDate":"April 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":65453777,"name":"Biological sciences/Biochemistry"},{"id":65453778,"name":"Health sciences/Diseases"},{"id":65453779,"name":"Health sciences/Gastroenterology"},{"id":65453780,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-04-17T13:57:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-02 15:10:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9194529","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9194529","identity":"rs-9194529","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}