Search Results (576)

Background/Objectives: Long-term hospitalization in cardiac patients is associated with significant metabolic and microbial alterations that may influence disease progression and prognosis. Although lipid imbalances, metabolomic shifts, and gut microbiome dysbiosis have each been linked individually to cardiovascular outcomes, their integrated evaluation in long-term-hospitalized patients remains underexplored. Methods: We conducted a retrospective observational study including 51 cardiac patients hospitalized for more than 25 days, compared with a control group of 41 patients hospitalized for short and intermediate durations (3–24 days). Clinical and demographic data were collected, alongside lipid profiling, metabolomic assessment through liquid chromatography–mass spectrometry (LC-MS), and gut microbiome analysis using GI360™ sequencing. Ethical approval was obtained, and all data were anonymized. Lipid-related findings are exploratory due to the small number of complete measurements. Results: Preliminary lipid trends were characterized by higher levels of LDL, triglycerides, and Lp(a), and lower HDL, in the long-term group. Metabolomic analyses revealed decreased energy-related metabolites (ATP, phosphocreatine ratio), altered amino acid patterns, and increased ketone utilization. Gut microbiome evaluation demonstrated a significant increase in dysbiosis index, with reduced diversity and dominance of potentially pathogenic taxa. These findings were correlated with clinical severity scores. Cross-domain relationships are exploratory and based on associative profiling rather than deep integrative modelling. Conclusions: Long-term hospitalization in cardiac patients is associated with distinct lipid, metabolomic, and gut microbiome profiles that may serve as predictive biomarkers of adverse outcomes. Future studies should validate these findings in larger cohorts and explore their integration into personalized management strategies. Full article

While short-term faba bean feeding is known to improve fish texture, its long-term systemic effects and the underlying molecular mechanisms in Nile tilapia remain rarely explored. This knowledge gap is critical, given the potential for extended feeding to induce distinct metabolic reprogramming and trade-offs. Here, we present the first comprehensive study investigating the 180-day impact of a 60% FB-based diet (FBD) on Nile tilapia through an integrated analysis of phenotypic traits, muscle histology, metabolome, and transcriptome. Our results revealed a fundamental trade-off: FBD feeding induced hyperplasia-driven muscle remodeling, significantly enhancing textural properties (hardness, gumminess, chewiness) and increasing intramuscular fat and collagen content, but at the cost of suppressed growth and hepatosomatic index. Metabolomics identified 243 significantly altered metabolites, outlining a systemic metabolic shift characterized by activated lipid synthesis but inhibited amino acid and energy metabolism. This multi-omics integration nominated the chac1 gene as a novel key regulator for FB-induced muscle hyperplasia, a finding not previously reported in this context. We propose a mechanistic model wherein long-term FBD feeding coordinates lipid deposition, collagen accumulation, and chac1-mediated hyperplastic growth to remodel muscle texture. Our work provides new insights into the long-term metabolic trade-offs and molecular drivers of FB-induced flesh quality improvement, offering a theoretical foundation for developing optimized aquafeeds. Full article

Background: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options, prompting extensive research into novel therapeutics. This study presents a comprehensive molecular characterization of usnic acid in TNBC using transcriptomic, proteomic, and in vivo analyses. Results: Transcriptome profiling identified 974 differentially expressed genes (201 upregulated, 773 downregulated; p ≤ 0.05, FC ≥ 2) between control and usnic acid-treated MDA-MB-231 cells, while 4956 DEGs were detected between usnic acid-treated normal epithelial and TNBC cells. Proteomic analysis revealed significant changes in 372 proteins (50 upregulated and 322 downregulated). Functional enrichment analyses indicated that usnic acid modulates key oncogenic pathways, including gonadotropin, CCKR, integrin–ECM signaling, and lipid/energy metabolism. Flow cytometry confirmed increased apoptosis, evidenced by upregulation of pro-apoptotic genes and suppression of anti-apoptotic genes. In vivo xenograft models further validated the tumor-suppressive effects of usnic acid. Conclusions: In light of the findings, this study constitutes the first comprehensive integrated transcriptomic and proteomic evaluation of usnic acid in TNBC, supported by functional and in vivo validation. Collectively, the results position usnic acid as a compelling therapeutic candidate that has successfully passed key in vitro and in vivo preclinical evaluations, warranting further investigation in advanced preclinical models and potential translation toward clinical development for TNBC. Full article

Bovine adipose-derived neural crest stem cells (baNCSCs) are an ideal model for studying the mechanism of adipogenesis. Lipidomics provides a powerful technical means to comprehensively analyze the dynamic changes in lipid metabolism during cell differentiation. However, the lipidomic remodeling throughout the adipogenic differentiation of baNCSCs is still lacking in-depth research. This study used ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) to perform non-targeted lipidomic analysis on baNCSCs on day 0 (CON0) and day 9 (DIF9) of adipogenic induction and differentiation. Differential lipid metabolites were screened through multivariate statistical analysis and univariate analysis. A total of 1639 lipid molecules were identified. Compared with the CON0 group, 568 lipids were significantly altered in the DIF9 group, involving 6 major categories and 20 subclasses. The relative content and types of triacylglycerols (TAG) and diacylglycerols (DAG) increased significantly, becoming the most important markers of successful differentiation. Glycerophospholipids (GP) underwent complex remodeling, with subclasses such as phosphatidylethanolamine (PE), phosphatidylserine (PS), and cardiolipin (CL) significantly increased, indicating extensive restructuring of the cell and organelle membranes to adapt to lipid storage and energy metabolism. Sphingolipids (SP) such as ceramides (Cer) and sphingomyelins (SM) were generally downregulated. The content of acylcarnitines (ACar) and hydroxy fatty acids (FAHFA) increased, suggesting enhanced fatty acid β-oxidation and metabolic health. This study systematically reveals the comprehensive lipidome reprogramming during the adipogenic differentiation of baNCSCs, which involves not only the accumulation of storage lipids but also the precise coordination of membrane lipid remodeling, signaling lipid regulation, and metabolic adaptation. These findings provide a valuable lipidomic perspective for understanding the molecular mechanism of bovine adipogenesis. Full article

In this study, we constructed an extraction process for bovine lung peptide-1 (BLP-1) derived from bovine lung tissue utilizing single-factor optimization combined with response surface methodology. We systematically analyzed its antioxidant activity, biological safety, and therapeutic mechanisms against alcoholic liver disease (ALD). In vitro experiments demonstrated that BLP-1 exhibits excellent scavenging activity against various free radicals, while exhibiting no significant cytotoxicity or hemolytic activity. In a model of H₂O₂-induced oxidative damage in HepG2 cells, BLP-1 significantly alleviated oxidative stress injury by upregulating the activities of intracellular antioxidant enzymes. Animal experiments further confirmed that BLP-1 significantly reduced serum levels of transaminase, inhibited the release of inflammatory factors, enhanced antioxidant enzyme activity, and ameliorated lipid peroxidation and pathological injury in ALD mice. By combining liquid chromatography-tandem mass spectrometry (LC-MS/MS) with bioinformatics, we screened 12 novel antioxidant peptides. Among these, the binding energies of GP9, FG6, and WG6 to Keap1 were −10.2, −9.7, and −8.7 kcal/mol, respectively, indicating their potential to modulate the antioxidant defense system through competitive inhibition of Keap1-Nrf2 interactions. This study provides a novel approach for the high-value utilization of bovine lung and the treatment of ALD, as well as a new source for the extraction of natural antioxidant peptides. Full article

Lameness remains a significant welfare and productivity challenge in dairy farming, often underdiagnosed due to the limitations of conventional detection methods. Unlike most previous approaches to lameness detection that rely on a single-sensor or gait-based measurement, this study integrates four complementary data domains—behavioural, physiological, biochemical, and milk composition parameters—collected from 272 dairy cows during early lactation to enhance diagnostic accuracy and biological interpretability. The main objective of this study was to evaluate and compare the diagnostic classification performance of multiple machine learning (ML) algorithms trained on multimodal data collected at the time of clinical lameness diagnosis during early lactation, and to identify the most influential physiological and biochemical traits contributing to classification accuracy. Specifically, six algorithms—random forest (RF), neural network (NN), Ensemble, support vector machine (SVM), k-nearest neighbors (KNN), and logistic regression (LR)—were assessed. The input dataset integrated physiological parameters (e.g., water intake, body temperature), behavioural indicators (rumination time, activity), blood biochemical biomarkers (non-esterified fatty acids (NEFA), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), gamma-glutamyl transferase (GGT)), and milk quality traits (fat, protein, lactose, temperature). Among all models, RF achieved the highest validation accuracy (97.04%), perfect validation specificity (100%), and the highest normalized Matthews correlation coefficient (nMCC = 0.94), as determined through Monte Carlo cross-validation on independent validation sets. Lame cows showed significantly elevated NEFA and body temperatures, reflecting enhanced lipid mobilization and inflammatory stress, alongside reduced water intake, milk protein, and lactose content, indicative of systemic energy imbalance and impaired mammary function. These physiological and biochemical deviations emphasize the multifactorial nature of lameness. Linear models like LR underperformed, likely due to their inability to capture the non-linear and interactive relationships among physiological, biochemical, and milk composition features, which were better represented by tree-based and neural models. Overall, the study demonstrates that combining sensor data with blood biomarkers and milk traits using advanced ML models provides a powerful, objective tool for the clinical classification of lameness, offering practical applications for precision livestock management by supporting early, data-driven decision-making to improve welfare and productivity on dairy farms. Full article

Obesity, a major risk factor for cardiometabolic diseases, arises from chronic energy imbalance and ectopic lipid deposition. This study investigated the anti-obesity potential of Coral dealbatus crude polysaccharides (CDP), a previously uncharacterized bioactive fraction from a hybrid vegetable cultivar developed by the Chinese Academy of Agricultural Sciences. CDP, obtained via hydroalcoholic extraction, was structurally characterized as amorphous with heterogeneous molecular weights (87,813 Da, 4158 Da, and 728 Da) and glucose-dominant monosaccharide composition (FT-IR, XRD, and HPLC). In a high-fat diet (HFD)-induced murine obesity model, oral CDP administration significantly attenuated body weight gain (p < 0.05) and reduced ectopic lipid deposition. Histopathological analysis confirmed CDP’s efficacy in ameliorating hepatic steatosis, evidenced by diminished lipid droplet accumulation. Furthermore, CDP reversed HFD-induced gut microbiota dysbiosis, modulating beneficial bacterial taxa. These findings demonstrate CDP’s therapeutic potential against diet-induced metabolic disorders, likely mediated through lipid metabolism regulation and intestinal microbiota modulation, supporting its development as a novel functional food ingredient for dietary intervention. Full article

Background/Objectives: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating complex disease with an elusive etiology, lacking objective diagnostic biomarkers. This study leverages advanced Automated Machine Learning (AutoML) to analyze plasma metabolomic and lipidomic profiles for the purpose of ME/CFS detection. Methods: We utilized a publicly available dataset comprising 888 metabolic features from 106 ME/CFS patients and 91 matched controls. Three AutoML frameworks—TPOT, Auto-Sklearn, and H2O AutoML—were benchmarked under identical time constraints. Univariate ROC and PLS-DA analyses with cross-validation, permutation testing, and VIP-based feature selection were applied to standardized, log-transformed omics data to identify significant discriminatory metabolites/lipids and assess their intercorrelations. Results: TPOT significantly outperformed its counterparts, achieving an area under the curve (AUC) of 92.1%, accuracy of 87.3%, sensitivity of 85.8%, and specificity of 89.0%. The PLS-DA model revealed a moderate but statistically significant discrimination between ME/CFS and controls. Explainable artificial intelligence (XAI) via SHAP analysis of the optimal TPOT model identified key metabolites implicating dysregulated pathways in mitochondrial energy metabolism (succinic acid, pyruvic acid, leucine), chronic inflammation (prostaglandin D₂, 11,12-EET), gut–brain axis communication (glycocholic acid), and cell membrane integrity (pc(35:2)a). Conclusions: Our results demonstrate that TPOT-derived models not only provide a highly accurate and robust diagnostic tool but also yield biologically interpretable insights into the pathophysiology of ME/CFS, highlighting its potential for clinical decision support and elucidating novel therapeutic targets. Full article

The uptake and accumulation of nanoplastics by plants have emerged as a major research focus. Exogenous selenium nanoparticles (SeNPs) are widely used to mitigate the toxicity of abiotic stresses, such as nanoplastics (NPs) and polyethylene (PE—NPs) nanoplastics, and represent a feasible strategy to enhance plant performance. However, the molecular mechanisms by which SeNPs alleviate the phytotoxicity of microplastics and nanoplastics remain poorly defined. To address this gap, we used Pistia stratiotes L. (P. stratiotes) as a model and silicon dioxide nanoparticles (SiO₂NPs) as a comparator, integrating physiological assays, ultrastructural observations, and proteomic analyses. We found that NP stress caused ultrastructural damage in root tips, exacerbated oxidative stress, and intensified membrane lipid peroxidation. SeNPs treatment significantly mitigated NP-induced oxidative injury and metabolic suppression. Compared to the NPs group, SeNPs increased T-AOC by 38.2% while reducing MDA and ·OH by 33.3% and 89.6%, respectively. Antioxidant enzymes were also elevated, with CAT and POD rising by 47.1% and 39.2%. SeNPs further enhanced the photosynthetic capacity and osmotic adjustment, reflected by increases in chlorophyll a, chlorophyll b, and soluble sugar by 49.7%, 43.8%, and 27.0%, respectively. In contrast, proline decreased by 17.4%, indicating stress alleviation rather than an osmotic compensation response. Overall, SeNPs outperformed SiO₂NPs. These results indicate that SeNPs broadly strengthen anti-oxidative defenses and metabolic regulation in P. stratiotes, effectively alleviating NP-induced oxidative damage. Proteomics further showed that SeNPs specifically activated the MAPK signaling cascade, phenylpropanoid biosynthesis, and energy metabolic pathways, enhancing cell-wall lignification to improve the mechanical barrier and limiting NPs translocation via a phytochelatin-mediated vacuolar sequestration mechanism. SiO₂NPs produced similar but weaker alleviative effects. Collectively, these findings elucidate the molecular basis by which SeNPs mitigate NPs’ phytotoxicity and provide a theoretical foundation and practical outlook for using nanomaterials to enhance phytoremediation in aquatic systems. Full article

Sesame seed oil is a bioactive-rich lipid source, notable for lignans, tocopherols, and unsaturated fatty acids that underpin its antioxidant and cardioprotective properties. This study optimized two innovative, non-thermal extraction techniques—pulsed electric field (PEF) and ultrasound bath-assisted extraction (UBAE)—to maximize yield and preserve oil quality for functional food applications. A blocked definitive screening design combined with response surface methodology modeled the effects of energy power (X₁, 60–100%), liquid-to-solid ratio (X₂, 10–20 mL/g), and extraction time (X₃, 10–30 min) on fat content, DPPH antiradical activity, and oxidative stability indices (Conjugated Dienes, CDs/Conjugated Trienes, CTs). UBAE achieved the highest fat yield—59.0% at low energy (60%), high X₂ (20 mL/g), and short X₃ (10 min)—while PEF maximized DPPH to 36.0 μmol TEAC/kg oil at high energy (100%), moderate X₂ (17 mL/g), and short X₃ (10 min). CDs were minimized to 19.78 mmol/kg (UBAE, 60%, 10 mL/g, 10 min) and CTs to 3.34 mmol/kg (UBAE, 60%, 12 mL/g, 10 min). Partial least squares analysis identified X₂ and X₃ as the most influential variables (VIP > 0.8), with energy–time interplay (X₁ × X₃) being critical for antioxidant capacity. Compared to cold-pressing and Soxhlet extraction, PEF and cold-pressing retained higher antioxidant activity (~19 μmol TEAC/kg) and oxidative stability (TBARS ≤ 0.30 mmol MDAE/kg), while Soxhlet—though yielding 55.65% fat—showed the poorest quality profile (Totox value > 560). Both non-thermal techniques can deliver bioactive-rich sesame oil with lower oxidative degradation, supporting their application in functional foods aimed at improving dietary antioxidant intake and mitigating lipid oxidation burden. PEF at high energy/short time and UBAE at low energy/short time present complementary, scalable options for producing high-value edible oils aligned with human health priorities. As a limitation, we did not directly quantify lignans or tocopherols in this study, and future work will address their measurement and bioaccessibility. Full article

The growing demand for sustainable bioprocesses highlights microalgae as a promising source of renewable feedstock. However, high energy use for artificial lighting limits the commercial viability of photobioreactor systems. This study proposes an energy-optimized framework for cultivating Mychonastes homosphaera using LED illumination. The optimization was performed using Response Surface Methodology (RSM) with a Face-Centered Central Composite Design (FCCCD) to assess the interactive effects of light intensity, duration, airflow rate, and nitrogen concentration on biomass and lipid productivity. The performance of LED wavelengths was compared for biomass, lipid productivity, and energy consumption. RSM models were statistically significant (p < 0.01), and ANOVA had a high coefficient of determination (R²) for all LEDs. Maximum biomass productivity was 512.0 ± 12.23 mg L⁻¹ day⁻¹ with cool-white, followed by pink (401.33 ± 10.48), blue (342.66 ± 3.53), and red (189.6 ± 1.36). Cool-white consumed the least energy (228.6 Wh day⁻¹) to produce the maximum biomass, compared to blue (235.05 Wh day⁻¹), pink (240.0 Wh day⁻¹), and red (240.0 Wh day⁻¹). Lipid content was highest under red (22.84%), followed by pink (17.39%), blue (15.82%), and cool-white (8.96%). However, lipid productivity was highest under pink (69.8 mg L⁻¹ day⁻¹), followed by blue (54.2 mg L⁻¹ day⁻¹), cool-white (45.86 mg L⁻¹ day⁻¹), and red (43.3 mg L⁻¹ day⁻¹). Full article

Left ventricular hypertrophy (LVH) refers to the pathological thickening of the myocardial wall and is strongly associated with several adverse cardiac outcomes and sudden cardiac death. While the biomechanical drivers of LVH are well established, growing evidence points to a critical role for cardiac and systemic metabolism in modulating hypertrophic remodeling and disease pathogenesis. Despite the efficiency of fatty acid oxidation (FAO), LVH hearts preferentially increase glucose uptake and catabolism to drive glycolysis and oxidative phosphorylation (OXPHOS). The development of therapies to increase and enhance LFCA FAO is underway, with promising results. However, the mechanisms of systemic metabolic states and LCFA dynamics in the context of cardiac hypertrophy remain incompletely understood. Further, it is unknown to what extent cardiac metabolism is influenced by whole-body energy balance and lipid profiles, despite the common occurrence of lipotoxicity in LVH. In this study, we measured whole-body and cellular respiration along with analysis of lipid and glycogen stores in a mouse model of LVH. We found that loss of the cardiac-specific gene, myosin-binding protein C3 (Mybpc3), resulted in depletion of adipose tissue, decreased mitochondrial function in skeletal muscle, increased lipid accumulation in both the heart and liver, and loss of whole-body metabolic flux. We found that supplementation of exogenous LCFAs boosted LVH mitochondrial function and reversed cardiac lipid accumulation but did not fully reverse the hypertrophied heart nor systemic metabolic phenotypes. This study indicates that the LVH phenotype caused systemic metabolic rewiring in Mybpc3^−/− mice and that exogenous LCFA supplementation boosted mitochondrial function in both cardiac and skeletal muscle. Full article

Neurotransmitters play a pivotal role not only in central nervous system signaling but also in the regulation of systemic energy metabolism, insulin sensitivity, and cardiovascular function. The contribution of neuroendocrine dysregulation to the development of type 2 diabetes mellitus (T2DM) is increasingly being recognized; however, the interplay between neurotransmitter levels and lipid/insulin resistance profiles in T2DM and prediabetes (PreDM) remains poorly characterized. We evaluated serum dopamine (DA), norepinephrine (NE), epinephrine (EPI), and serotonin (ST) in 110 individuals with PreDM (n = 40) or newly diagnosed T2DM (n = 70). Extended metabolic profiling included HbA1c, lipid panels, and insulin resistance indices (triglyceride-to-glucose index (TyG), TyG-derived indices). Neurotransmitter levels were compared across body mass index (BMI) categories, gender, and glycosylated hemoglobin A1c (HbA1c) quartiles. We applied multivariable linear regression (MLR) adjusted for body mass index (BMI), age, sex, lipids, penalized logistic regression (predicting T2DM status), and exploratory Spearman correlations with False Discovery Rate (FDR) correction. All four neurotransmitters were significantly higher in T2DM versus PreDM (p < 0.001). In T2DM patients, DA and NE levels increased across HbA1c quartiles, and NE levels were significantly higher in quartile 3 compared to quartile 2 (p = 0.045). In multivariable models, T2DM status was the only consistent predictor of neurotransmitter elevations. Logistic regression identified ST (OR = 8.70) and NE (OR = 3.76) as key discriminators of T2DM status, in addition to HbA1c. Exploratory correlation analyses in T2DM showed trends between EPI and insulin resistance indices (TyG adjusted for waist circumference (TyG-WC), TyG adjusted for waist-to-height ratio (TyG-WHtR)) and between DA and low-density lipoprotein cholesterol (LDL-C), although these did not survive to FDR correction. Neurotransmitter levels are elevated in T2DM and correlate with glycemic and metabolic profiles, suggesting early neuroendocrine involvement in the pathogenesis of diabetes. Serotonin and norepinephrine may serve as adjunctive biomarkers for disease stratification, meriting further prospective and mechanistic investigation. Full article

Oxidative stress induces reactive oxygen species (ROS) accumulation, which compromises sperm DNA integrity, cellular homeostasis, and semen quality in Hainan black goats. This study aimed to mitigate ROS-mediated sperm damage by examining the protective effects of curcumin on metabolic regulation and sperm structural integrity. Semen samples were treated in vitro with varying concentrations of curcumin (5, 25, 50 μmol/L) under oxidative stress conditions. The intermediate concentration (25 μmol/L) was most effective at enhancing sperm quality. Following treatment, sperm motility, membrane integrity, and acrosome stability were significantly improved (p < 0.05), while ROS levels and apoptosis rates decreased. Antioxidant enzyme activities—glutathione peroxidase (GPX, p < 0.05), catalase (CAT, p < 0.05), and superoxide dismutase (SOD, p < 0.05)—were markedly elevated. Metabolomic analysis identified 48 differential metabolites (p < 0.05), including gluconic acid, 3-hydroxybutyric acid, and argininosuccinic acid, which were mainly involved in antioxidant defense, energy metabolism (e.g., the citrate cycle), and osmoregulatory pathways. Lipidomics revealed reduced lipid peroxidation and increased polyunsaturated fatty acid content, correlating with enhanced membrane stability. Transmission and scanning electron microscopy revealed preservation of sperm ultrastructure, with reduced mitochondrial and chromatin damage. Quantitative PCR further indicated curcumin-mediated downregulation of pro-apoptotic genes (BAX, Caspase3, and FAS) and upregulation of the anti-apoptotic gene BCL2 (p < 0.05). These findings demonstrate that Curcumin at 25 μM mitigated menadione-induced oxidative stress in goat sperm in vitro, improving antioxidant status, mitochondrial function and membrane integrity while reducing apoptosis. Multi-omic profiling supported redox and lipid homeostasis restoration. These findings establish proof-of-principle in an acute oxidative model. Full article

An integrative approach combining network pharmacology, molecular docking, and cellular assays was used to elucidate the potential mechanisms by which the n-butanol extract of Biebersteinia heterostemon ameliorates type 2 diabetes mellitus (T2DM). Chemical constituents of the n-butanol extract were identified via ultra-high-performance liquid chromatography coupled with Q-Exactive Orbitrap mass spectrometry. Active compounds and T2DM-related targets were retrieved from public databases, and intersecting targets were identified. Protein–protein interaction (PPI) networks were constructed using the STRING database, while Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed via the DAVID database. A comprehensive “drug–compound–target–disease–pathway” network was established, and molecular docking was conducted to evaluate binding affinities of key compounds to core targets. Functional validation was performed in insulin-resistant cell models. Network pharmacology analysis identified 37 active constituents within the extract and 222 overlapping targets associated with T2DM. GO enrichment indicated involvement in protein phosphorylation, MAPK cascade activation, and negative regulation of apoptosis. Key signaling pathways included PI3K/AKT and lipid and atherosclerosis pathways. Molecular docking revealed strong binding affinities (binding energies ≤ −9.3 kcal·mol⁻¹) between core compounds—such as cheilanthifoline, glabridin, acetylcorynoline, skullcapflavone II, liquiritigenin, and dinatin—and pivotal targets including GAPDH, AKT1, TNF, SRC, EGFR, and PPARγ. In vitro experiments demonstrated that the extract significantly enhanced glucose uptake and glycogen synthesis in insulin-resistant cells, while suppressing oxidative stress and the expression of pro-inflammatory mediators such as TNF-α, MMP9, and IL-6. Collectively, B. heterostemon shows potential as an effective intervention for T2DM by targeting key molecular pathways, improving insulin sensitivity, and mitigating oxidative stress and inflammation in insulin-resistant cells. Full article