Xenobiotica最新文献

Statins, which inhibit HMG-CoA reductase, are widely prescribed for cardiovascular disease prevention, while the gut microbiota plays a key role in host metabolism, immune regulation, and drug response.This narrative review examines how statins modulate the composition and function of the gut microbiota and, conversely, how the gut microbiota influences the pharmacokinetics, efficacy, and adverse effects of statins.Preclinical and clinical studies indicate that individual statins exert distinct effects; however, detailed understanding remains limited because these drugs are frequently evaluated collectively as a class rather than as separate compounds.Statins have been shown to alter microbial diversity and their metabolite profiles, which may enhance lipid-lowering effects and confer additional benefits such as anticancer activity, but may also contribute to adverse effects such as increased risk of type 2 diabetes. On the other hand, gut microbes modulate the bioavailability of statins by metabolizing the active compounds, which affects the therapeutic response.These results highlight the clinical importance of the gut microbiota in shaping the efficacy and safety profiles of statins and support the development of personalized, microbiome-informed treatment strategies.

Exploring the molecular mechanism underlying the pathogenesis and treatment of ischaemic cardiomyopathy (ICM) is crucial for its precise management.In this study, an ICM cell model was constructed, treated with sacubitril/valsartan, and subjected to exogenous modulation of EP300 expression. RT-qPCR and Western blot were employed to detect the expression of E1A-associated protein P300 (EP300), Hypoxia-Inducible Factor-1 (HIF-1) α, and HIF-1β. Additionally, the CCK-8 assay, flow cytometry, lactic acid detection, and ROS activity detection were used to examine changes in cell conditions. The aim was to verify the molecular mechanism of sacubitril/valsartan in treating ICM and explore the mechanism of targeting EP300 in ICM treatment.Results showed that sacubitril/valsartan upregulated EP300 expression, activated the EP300/HIF-1 signalling pathway, inhibited lactate secretion and ROS production, increased cell viability, and decreased the apoptosis rate in the ICM cell model. Direct upregulation of EP300 expression produced similar effects on the ICM cell model as sacubitril/valsartan.The mechanism by which sacubitril/valsartan reduces myocardial hypoxic injury by upregulating the EP300/HIF-1 signalling pathway suggests that targeting the EP300/HIF-1 signalling pathway may become a new approach for the treatment of ICM.

The main objective of this study is to investigate whether the CYP3A4/5 and ABC transporter genetic polymorphisms could affect the pharmacokinetics (PK) of rivaroxaban in Chinese healthy subjects.Forty-two healthy subjects in China were recruited and given a single dose of 2.5 mg rivaroxaban tablets. Plasma concentration of rivaroxaban was determined by UPLC-MS/MS, the CYP3A4 20230 G > A(*1G)), CYP3A5 6986 A > G(*3), ABCB1 1236 C > T, ABCB1 3435 C > T, ABCB1 2677 G > T/A, ABCG2 34 G > A, ABCC2 1249 G > A, ABCC2 3972 C > T, ABCC2 - 24 C > T, ABCG2 421 C > A, SLC22A8 715 C > T, SLC22A8 445 C > A, SLC22A8 779 T > G, SLC22A8 829 C > T, and SLC22A8 913 A > T genotypes were determined by SnapShot Technique.In the study, compared with the subjects with C/C of ABCG2 421 C > A genotype, individuals with C/A and A/A genotype showed higher the area under the concentration-time curve AUC_0-t (289.17 vs. 358.56 vs. 439.26 ng/h/mL) (p < 0.05 and p < 0.01, respectively), AUC_0-∞ (293.92 vs. 362.80 vs. 442.25 ng/h/mL) (p < 0.05 and p < 0.01, respectively) and the maximum plasma concentration C_max (56.58 vs. 70.36 vs. 83.90 ng/mL) (p < 0.05 and p < 0.01, respectively), but lower apparent clearance CL/F (9114.00 vs. 7493.82 vs. 6017.75 mL/h) (p < 0.05). Following Bonferroni correction, subjects carrying the A/A genotype continued to exhibit statistically significant differences in PK parameters C_max, AUC_0-t, and AUC_0-∞ compared to C/C allele carriers.Data in the article proved that the ABCG2 421 C > A polymorphism was significantly related to the PK variability of rivaroxaban.

This study aimed to reveal whether blood hydrogen sulfide (H₂S) reduction could result in attenuated platelet inhibition of clopidogrel and whether replenishing blood H₂S would reverse such attenuation in mice with diabetes mellitus (DM).Control (non-diabetic) versus DM mice were treated with vehicle control or GYY4137 (a synthetic H₂S donor) alone or in combination with clopidogrel. Body weight gain, blood glucose, glucose tolerance, insulin tolerance, blood H₂S, adenosine diphosphate (ADP)-induced whole-blood platelet aggregation, main clopidogrel metabolites (active thiol metabolite H4 and inactive clopidogrel carboxylate) in plasma, and the expression of main clopidogrel-metabolizing enzymes and interleukin-1β as well as their genes in the liver were measured, respectively.Compared with control mice, DM mice exhibited significant decreases in plasma H₂S and H4 levels, glucose tolerance, insulin sensitivity, and clopidogrel-metabolizing enzyme expression, but significant increases in blood glucose, ADP-induced whole-blood platelet aggregation, and hepatic interleukin-1β expression, respectively. After use of GYY4137, boosting blood H₂S levels ameliorated or reversed all other changes observed in DM mice, except for blood glucose elevation.Blood H₂S reduction may contribute to impaired platelet inhibition of clopidogrel in DM mice, suggesting that replenishing blood H₂S may benefit DM patients more when taking clopidogrel concomitantly.

The escalating threat of methicillin-resistant Staphylococcus aureus (MRSA) infections, coupled with the dwindling efficacy of current antibiotics, highlights the urgent need for novel antimicrobial agents.In this study, we demonstrate that sanguinarine - a plant-derived benzophenanthridine alkaloid - exerts potent antibacterial activity against MRSA, with a minimum inhibitory concentration (MIC) of 20 mg/L. To elucidate the molecular mechanisms underlying its antibacterial effects, we conducted a comprehensive, time-resolved proteomic analysis of MRSA upon sanguinarine exposure, quantifying a total of 1,037 proteins, among which significant alterations were observed at each time point over a 120-min treatment period. Proteomic profiling combined with fuzzy C-means clustering revealed distinct temporal response patterns. Upregulated proteins were enriched in pathways related to nucleotide excision repair and central metabolism, suggesting adaptive responses to DNA damage and metabolic stress. In contrast, downregulated proteins were primarily involved in critical cellular processes such as cell division, iron acquisition, RNA turnover, and protein synthesis, indicating a disruption of bacterial growth and homeostasis.These findings provide systems-level insights into the multifaceted antibacterial actions of sanguinarine and support its potential as a promising lead compound for the development of novel therapeutics targeting drug-resistant bacterial infections.

Bioequivalence (BE) studies have made significant advancements, particularly with the introduction of the ICH M13 guidances. This review examines the historical aspects leading to the harmonisation efforts of the latest ICH M13A, the draft of ICH M13B, and the anticipated ICH M13C.The primary focus of this article is on ICH M13A, highlighting the significant changes over previous guidelines of USFDA and EMA. It outlines the stringent requirements for high-risk products as per ICH M13A and emphasises the necessity for both fasting and fed studies. This review highlights the high-risk complex formulations, such as amorphous solid dispersions, microemulsions, and nanotechnology-based formulations, which often exhibit different food effects compared to conventional formulations.Additionally, the role of PBPK/PBBM modelling in predicting food effects and fed bioequivalence for high-risk products is discussed. Furthermore, the potential of modelling based methodologies as 'alternative BE' approaches for securing waivers for fed BE studies is discussed in depth.Furthermore, the latest ICH M13B guidance is reviewed, focusing on differences from previous guidelines on dissolution similarity and bracketing approaches. The review also discusses the anticipated directions for ICH M13C and its potential impact on future BE studies for HVDs, NTIs, and complex designs.

Soticlestat (TAK-935) is a selective cholesterol 24S-hydroxylase inhibitor and represents a potential adjunctive treatment for Dravet and Lennox-Gastaut syndromes. The direct glucuronide metabolite of soticlestat TAK-935-G is the primary circulating drug-related material in humans. Thus, the potential of TAK-935-G as a perpetrator for drug-drug interactions (DDIs) was evaluated according to the current regulatory guideline. The DDI risk between soticlestat/TAK-935-G and representative anti-seizure medications (ASMs) was also investigated using various in vitro assays.TAK-935-G was not a perpetrator of cytochrome P450 enzymes (CYPs), uridine diphosphate glucuronosyl-transferase enzymes (UGTs) or transporters, except for CYP1A2 induction, where it demonstrated an induction with an E_max of 2.06- to 3.56-fold change and EC₅₀ of 53.7-78.8 µM. Two ASMs are known to be substrates of CYP1A2; however, no serious DDI through CYP1A2 induction has been reported. The examined ASMs did not inhibit soticlestat glucuronidation. Moreover, soticlestat and TAK-935-G did not inhibit glucuronidation of the examined ASMs.Collectively, no notable concern exists regarding the clinical perpetrator risk of CYP, UGT and transporters with TAK-935-G, despite its high unbound plasma concentrations. The combined analysis of in vitro and clinical DDI results, alongside physiologically based pharmacokinetic modelling, exhibited a low DDI risk for soticlestat and TAK-935-G.

MicroRNA-21 (miRNA-21) expression is increased in patients with kidney disease, and polysaccharides provide the structural scaffolding of the glomerular and tubular basement membranes.We investigated whether the induction of renal injury by the industrial toxic chemical thioacetamide (TAA) can dysregulate the kidney miRNA-21/SIRT1/NF-κB axis as well as the structural polysaccharide content of the kidney tissue, and whether treatment with the polyphenolic compound resveratrol can inhibit these adverse effects.Kidney injury was induced in rats by TAA (200 mg/kg) injections. The protective group of rats was pre-treated with resveratrol (20 mg/kg) prior to kidney injury and subsequently kept on resveratrol until culled.TAA intoxication caused a significant (p < 0.0001) modulation in kidney and blood levels of miRNA-21, the tissue renoprotective molecule SIRT1, NF-κB p65, kidney structural polysaccharides, the macrophage biomarker cluster of differentiation 68 (CD68), tissue inhibitor of metalloproteinases-1 (TIMP-1) mRNA, hypernatremia, urea, and creatinine, as well as albuminuria that were significantly (p ≤ 0.0187) protected by resveratrol. Furthermore, a significant correlation between the miRNA-21/SIRT1/NF-κB axis, structural polysaccharides, renal fibrosis, and renal injury biomarkers was observed.These findings demonstrate an association between renal injury induced by TAA intoxication and the dysregulation of the kidney miRNA-21/SIRT1/NF-κB axis and polysaccharide levels while being protected by resveratrol.

Arachidonic acid (ArA) is an essential omega-6 polyunsaturated fatty acid is crucial in various physiological processes and disease conditions. Nevertheless, the effects of arachidonic acid on liver and kidney damage are not well understood. Therefore, this study aimed to explore the beneficial role of ArA on liver and kidney injuries caused by thioacetamide (TAA) in rats, focusing on the associated hematological changes.The six groups, each consisting of 10 rats, are as follows; Control, 30 mg/kg ArA-treated, 20 mg/kg TAA-induced liver injury, ArA (10, 20, and 30 mg/kg)-pre-treated liver injury groups.The pre-treatment of ArA ameliorated histopathological injuries of hepatic and kidney tissues and hepatic dysfunction in TAA-treated rats. TAA increased hepatic and kidney injury serum biomarkers, otherwise, ArA significantly suppressed increased levels of these parameters and inhibited metabolic acidosis and dehydration due to TAA treatment. Besides, ArA effectively preserved protein and cholesterol metabolism against TAA-induced hepatic injury. ArA suppressed TAA caused ionic imbalance. Notably, the highest AA dosage (30 mg/kg) provided the most protective effects against TAA-induced liver and kidney damage.This study demonstrated that ArA effectively reduces liver and kidney injuries caused by TAA, indicating its potential as a promising preventive or therapeutic approach.

Bioavailability prediction remains a significant challenge in early-stage drug development, where conventional experimental approaches are time-consuming and resource-intensive. This study explores the application of machine learning techniques to enhance the efficiency of bioavailability prediction. By leveraging computational workflows within the KNIME Analytics Platform, we aim to automate bioavailability assessment and reduce dependence on costly in vitro and in vivo studies.

A dataset comprising 475 drug-like compounds characterised by key molecular descriptors was analysed using multiple machine learning models, including Random Forest, Gradient Boosting, Decision Trees, k-Nearest Neighbours, and neural networks. Model performance was assessed through 5-fold cross-validation, with ensemble models outperforming linear and neural network-based approaches. Random Forest demonstrated the highest predictive performance (R² = 0.87, RMSE = 0.08). Feature importance analysis identified topological polar surface area and solubility as the most influential factors in bioavailability prediction.

The findings underscore the potential of integrating open-source tools and machine learning methodologies in pharmaceutical research, improving workflow efficiency while adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. This approach facilitates rapid and cost-effective bioavailability assessment, supporting AI-driven predictive modelling and digital health applications in drug development.