The impact of CYP3A4 genetic polymorphism on crizotinib metabolism and drug-drug interactions.

To elucidate the impact of CYP3A4 activity inhibition and genetic polymorphism on the metabolism of crizotinib. Enzymatic incubation systems for crizotinib were established, and Sprague-Dawley rats were utilized for in vivo experiments. Analytes were quantified using LC-MS/MS. Upon screening 122 drugs and natural compounds, proanthocyanidins emerged as inhibitor of crizotinib metabolism, exhibiting a relative inhibition rate of 93.7%. The IC50 values were 24.53 ± 0.32 µM in rat liver microsomes and 18.24 ± 0.12 µM in human liver microsomes. In vivo studies revealed that proanthocyanidins markedly affected the pharmacokinetic parameters of crizotinib. Co-administration led to a significant reduction in the AUC(0-t), Cmax of PF-06260182 (the primary metabolite of crizotinib), and the urinary metabolic ratio. This interaction is attributed to the mixed-type inhibition of liver microsome activity by proanthocyanidins. CYP3A4, being the principal metabolic enzyme for crizotinib, has its genetic polymorphisms significantly influencing crizotinib's pharmacokinetics. Kinetic data showed that the relative metabolic rates of crizotinib across 26 CYP3A4 variants ranged from 13.14% (CYP3A4.12, 13) to 188.57% (CYP3A4.33) when compared to the wild-type CYP3A4.1. Additionally, the inhibitory effects of proanthocyanidins varied between CYP3A4.12 and CYP3A4.33, when compared to the wild type. Our findings indicate that proanthocyanidins coadministration and CYP3A4 genetic polymorphism can significantly influence crizotinib metabolism.

A dynamic nomogram for predicting in-hospital major adverse cardiovascular and cerebrovascular events in patients with both coronary artery disease and atrial fibrillation: a multicenter retrospective study.

BACKGROUND AND OBJECTIVE: Patients with both coronary artery disease (CAD) and atrial fibrillation (AF) are at a high risk of major adverse cardiovascular and cerebrovascular events (MACCE) during hospitalization. Accurate prediction of MACCE can help identify high-risk patients and guide treatment decisions. This study was to elaborate and validate a dynamic nomogram for predicting the occurrence of MACCE during hospitalization in Patients with CAD combined with AF. METHODS: A total of 3550 patients with AF and CAD were collected. They were randomly assigned to a training group and a validation group in a ratio of 7 : 3. Univariate and multivariate analyses were utilized to identify risk factors (P < 0.05). To avoid multicollinearity and overfit of the model, the least absolute shrinkage and selection operator was conducted to further screen the risk factors. Calibration curves, receiver operating characteristic curves, and decision curve analyses are employed to assess the nomogram. For external validation, a cohort consisting of 249 patients was utilized from the Medical Information Mart for Intensive Care IV Clinical Database, version 2.2. RESULTS: Eight indicators with statistical differences were screened by univariate analysis, multivariate analysis, and the least absolute shrinkage and selection operator method (P < 0.05). The prediction model based on eight risk factors demonstrated good prediction performance in the training group, with an area under the curve (AUC) of 0.838. This performance was also maintained in the internal validation group (AUC = 0.835) and the external validation group (AUC = 0.806). Meanwhile, the calibration curve indicates that the nomogram was well-calibrated, and decision curve analysis revealed that the nomogram exhibited good clinical utility. CONCLUSION: The nomogram we constructed may aid in stratifying the risk and predicting the prognosis for patients with CAD and AF.

Genetic variants, haplotype determination, and function of novel alleles of CYP2B6 in a Han Chinese population.

Amino acid variants in protein may result in deleterious effects on enzymatic activity. In this study we investigate the DNA variants on activity of CYP2B6 gene in a Chinese Han population for potential use in precision medicine. All exons in CYP2B6 gene from 1483 Chinese Han adults (Zhejiang province) were sequenced using Sanger sequencing. The effects of nonsynonymous variants on recombinant protein catalytic activity were investigated in vitro with Sf12 system. The haplotype of novel nonsynonymous variants with other single nucleotide variants in the same allele was determined using Nanopore sequencing. Of 38 alleles listed on the Pharmacogene Variation Consortium, we detected 7 previously reported alleles and 18 novel variants, of which 11 nonsynonymous variants showed lower catalytic activity (0.00-0.60) on bupropion compared to CYP2B6*1. Further, these 11 novel star-alleles (CYP2B6*39-49) were assigned by the Pharmacogene Variation Consortium, which may be valuable for pharmacogenetic research and personalized medicine.

Using new indices to predict metabolism dysfunction-associated fatty liver disease (MAFLD): analysis of the national health and nutrition examination survey database.

BACKGROUND: Metabolism dysfunction-associated fatty liver disease (MAFLD), is the most common chronic liver disease. Few MAFLD predictions are simple and accurate. We examined the predictive performance of the albumin-to-glutamyl transpeptidase ratio (AGTR), plasma atherogenicity index (AIP), and serum uric acid to high-density lipoprotein cholesterol ratio (UHR) for MAFLD to design practical, inexpensive, and reliable models. METHODS: The National Health and Nutrition Examination Survey (NHANES) 2007-2016 cycle dataset, which contained 12,654 participants, was filtered and randomly separated into internal validation and training sets. This study examined the relationships of the AGTR and AIP with MAFLD using binary multifactor logistic regression. We then created a MAFLD predictive model using the training dataset and validated the predictive model performance with the 2017-2018 NHANES and internal datasets. RESULTS: In the total population, the predictive ability (AUC) of the AIP, AGTR, UHR, and the combination of all three for MAFLD showed in the following order: 0.749, 0.773, 0.728 and 0.824. Further subgroup analysis showed that the AGTR (AUC1 = 0.796; AUC2 = 0.690) and the combination of the three measures (AUC1 = 0.863; AUC2 = 0.766) better predicted MAFLD in nondiabetic patients. Joint prediction outperformed the individual measures in predicting MAFLD in the subgroups. Additionally, the model better predicted female MAFLD. Adding waist circumference and or BMI to this model improves predictive performance. CONCLUSION: Our study showed that the AGTR, AIP, and UHR had strong MAFLD predictive value, and their combination can increase MAFLD predictive performance. They also performed better in females.

Effect of Interfacial Modification on the Low-Temperature Fatigue Properties of Polymer/MXene Flexible Pressure Sensors.

Maintaining an excellent force-electric response under cyclic bending at low temperatures is still challenging for resistive-type electrically conductive polymer composite-based pressure sensors. In this study, the effect of low temperature on the fatigue failure of flexible MXene/polymer pressure sensors was systematically investigated through the silane functionalization of MXene nanosheets embedded with different polymer matrixes. The results show that the MXene/polymer interfaces are the primary factors affecting the temperature-dependent bending fatigue of the Cu/MXene/polymer/Cu sensor. Using finite element analysis and theoretical calculations, we reveal that the MXene/polymer interfaces are affected by free volume changes and the molecular chain motion under different temperatures. At room temperature, the well-distributed free volume in the polydimethylsiloxane (PDMS) matrix permits local segmental mobility that promotes the affinity between the polymer and MXene. As the temperature decreases, the free volume in the matrix shrinks with less space left for molecular chains to slide relatively, weakening the polymer/MXene interfacial bonding strength. However, for PDMS/MXene sensors with the interface modified using the silane coupling agent KH550, the nanoconstrained structure formed by strong hydrogen bonds and covalent bonds at the PDMS/MXene interface can hinder the mobility of polymer chains, which greatly helps to dissipate the inter/intrachain friction. It thus alleviates the debonding energy dissipation during cyclic bending at subzero temperatures.

Epstein-Barr virus-based prognostic model in nodular sclerosis classic Hodgkin lymphoma.

The role of Epstein-Barr virus (EBV) in lymphoma cells of nodular sclerosis classic Hodgkin lymphoma (NScHL) is controversial. Our aim was to explore this and establish a clinically feasible model for risk stratification. We interrogated data from 542 consecutive subjects with NScHL receiving ABVD therapy and demonstrated EBV-infection in their lymphoma cells with EBV-encoded small RNAs (EBERs) in situ hybridization. Subjects were divided into training and validation datasets. As data from the training dataset suggested EBERs-positivity was the only independent prognostic factor for both progression-free survival (PFS) and overall survival (OS), we developed corresponding prognostic models based on it. Our models showed excellent performance in both training and validation cohort. These data indicate the close association of EBV infection and the outcomes of persons with NScHL receiving ABVD. Additionally, our newly developed models should help physicians estimate prognosis and select individualized therapy.

A modified nucleoside O6-methyl-2'-deoxyguanosine-5'-triphosphate exhibits anti-glioblastoma activity in a caspase-independent manner.

Resistance to temozolomide (TMZ), the frontline chemotherapeutic agent for glioblastoma (GBM), has emerged as a formidable obstacle, underscoring the imperative to identify alternative therapeutic strategies to improve patient outcomes. In this study, we comprehensively evaluated a novel agent, O6-methyl-2'-deoxyguanosine-5'-triphosphate (O6-methyl-dGTP) for its anti-GBM activity both in vitro and in vivo. Notably, O6-methyl-dGTP exhibited pronounced cytotoxicity against GBM cells, including those resistant to TMZ and overexpressing O6-methylguanine-DNA methyltransferase (MGMT). Mechanistic investigations revealed that O6-methyl-dGTP could be incorporated into genomic DNA, disrupting nucleotide pools balance, and inducing replication stress, resulting in S-phase arrest and DNA damage. The compound exerted its anti-tumor properties through the activation of AIF-mediated apoptosis and the parthanatos pathway. In vivo studies using U251 and Ln229 cell xenografts supported the robust tumor-inhibitory capacity of O6-methyl-dGTP. In an orthotopic transplantation model with U87MG cells, O6-methyl-dGTP showcased marginally superior tumor-suppressive activity compared to TMZ. In summary, our research, for the first time, underscores the potential of O6-methyl-dGTP as an effective candidate against GBM, laying a robust scientific groundwork for its potential clinical adoption in GBM treatment regimens.

Widely targeted metabolomics reveals the effect of different raw materials and drying methods on the quality of instant tea.

Introduction: Instant teas are particularly rich in tea polyphenols and caffeine and have great potential as food ingredients or additives to improve the quality of food and enhance their nutritional and commercial value. Methods: To determine the relationships between raw material, drying method, and sensory and other quality attributes, instant teas were prepared from three tea varieties, namely black, green and jasmine tea, using two drying methods, namely spray-drying (SD) and freeze-drying (FD). Results: Both the raw tea material and drying method influenced the quality of the finished instant teas. Black tea was quality stable under two drying, while green tea taste deteriorated much after SD. Jasmine tea must be produced from FD due to huge aroma deterioration after SD. FD produced instant tea with higher sensory quality, which was attributed to the lower processing temperature. Chemical compositional analysis and widely targeted metabolomics revealed that SD caused greater degradation of tea biochemical components. The flavonoids content changed markedly after drying, and metabolomics, combined with OPLS-DA, was able to differentiate the three varieties of tea. Instant tea preparations via SD often lost a large proportion of the original tea aroma compounds, but FD minimized the loss of floral and fruity aroma compounds. Changes in the tea flavonoids composition, especially during drying, contributed to the flavor development of instant tea. Discussion: These results will provide an practicle method for high-quality instant tea production through choosing proper raw tea material and lowering down drying temperature with non-thermal technologies like FD.

Effect of apatinib on the pharmacokinetics of tramadol and O-desmethyltramadol in rats.

Since the combination of anticancer drugs and opioids is very common, apatinib and tramadol are likely to be used in combination clinically. This study evaluated the effects of apatinib on the pharmacokinetics of tramadol and its main metabolite O-desmethyltramadol in Sprague-Dawley (SD) rats and the inhibitory effects of apatinib on tramadol in rat liver microsomes (RLMs), human liver microsomes (HLMs) and recombinant human CYP2D6.1. The samples were determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The in vivo results showed that compared with the control group, apatinib increased the AUC(0-t), AUC(0-∞) and Cmax values of tramadol and O-desmethyltramadol, and decreased the values of VZ/F and CLz/F. In addition, the MRT(0-t), MRT(0-∞) values of O-desmethyltramadol were increased. In vitro, apatinib inhibited the metabolism of tramadol by a mixed way with IC50 of 1.927 µM in RLMs, 2.039 µM in HLMs and 15.32 µM in CYP2D6.1. In summary, according to our findings, apatinib has a strong in vitro inhibitory effect on tramadol, and apatinib can increase the analgesic effect of tramadol and O-desmethyltramadol in rats.

Comparison analysis of full-spectrum metabolomics revealed on the variation of potential metabolites of unscented, Chloranthus spicatus scented, and Osmanthus fragrans (Thunb.) Lour. scented Congou black teas.

Introduction: In recent years, scented black tea has attracted much attention due to its pleasant floral aroma and mellow flavor, but little research has been carried out on its flavor metabolic profile. Methods: In this study, the flavor metabolic profiles of unscented, Chloranthus spicatus scented, and Osmanthus fragrans (Thunb.) Lour. scented Congou black teas were investigated using full-spectrum metabolomics analysis method, the first time that the flavor profiles of scented black tea were characterized in detail. Results and Discussion: The results revealed that a total of 3,128 metabolites were detected in the three teas. Based on the criteria of variable importance in the project >1 and fold change ≥2 or ≤ 0.5, 761 non-volatile metabolites and 509 volatile metabolites were filtered as differential metabolites. Many differential non-volatile metabolites belonged to flavonoids, phenolic acids, and terpenoids. Floral, fruity and herbaceous volatile metabolites were significantly up-regulated in Chloranthus spicatus scented Congou black tea while sweet and fruity volatile metabolites were significantly down-regulated in Osmanthus fragrans (Thunb.) Lour. scented Congou black tea. The results contribute to a better understanding of the scenting techniques on the flavor quality of scented black teas and provide some information on the flavor chemistry theory of scented black teas.

Predicting delayed methotrexate elimination in pediatric acute lymphoblastic leukemia patients: an innovative web-based machine learning tool developed through a multicenter, retrospective analysis.

BACKGROUND: High-dose methotrexate (HD-MTX) is a potent chemotherapeutic agent used to treat pediatric acute lymphoblastic leukemia (ALL). HD-MTX is known for cause delayed elimination and drug-related adverse events. Therefore, close monitoring of delayed MTX elimination in ALL patients is essential. OBJECTIVE: This study aimed to identify the risk factors associated with delayed MTX elimination and to develop a predictive tool for its occurrence. METHODS: Patients who received MTX chemotherapy during hospitalization were selected for inclusion in our study. Univariate and least absolute shrinkage and selection operator (LASSO) methods were used to screen for relevant features. Then four machine learning (ML) algorithms were used to construct prediction model in different sampling method. Furthermore, the performance of the model was evaluated using several indicators. Finally, the optimal model was deployed on a web page to create a visual prediction tool. RESULTS: The study included 329 patients with delayed MTX elimination and 1400 patients without delayed MTX elimination who met the inclusion criteria. Univariate and LASSO regression analysis identified eleven predictors, including age, weight, creatinine, uric acid, total bilirubin, albumin, white blood cell count, hemoglobin, prothrombin time, immunological classification, and co-medication with omeprazole. The XGBoost algorithm with SMOTE exhibited AUROC of 0.897, AUPR of 0.729, sensitivity of 0.808, specificity of 0.847, outperforming the other models. And had AUROC of 0.788 in external validation. CONCLUSION: The XGBoost algorithm provides superior performance in predicting the delayed elimination of MTX. We have created a prediction tool to assist medical professionals in predicting MTX metabolic delay.

Functional evaluation of CYP2C19 and CYP3A4 gene polymorphism on ibuprofen metabolism.

AIM: Ibuprofen is the most commonly used analgesic. CYP polymorphisms are mainly responsible for the differences in drug metabolism among individuals. Variations in the ability of populations to metabolize ibuprofen can lead to drug exposure events. The aim of this study was to evaluate the effects of CYP2C19 and CYP3A4 polymorphisms on ibuprofen metabolism in a Chinese population. METHODS: First, 31 CYP2C19 and 12 CYP3A4 microsomal enzymes were identified using an insect expression system. Then, variants were evaluated using a mature incubation system. Moreover, ibuprofen metabolite content was determined via ultra-performance liquid chromatography-tandem mass spectrometry analysis. Finally, kinetic parameters of CYP2C19 and CYP3A4 genotypes were determined via Michaelis-Menten curve fitting. RESULTS: Most variants exhibited significantly altered intrinsic clearance compared to the wild type. In the CYP2C19 metabolic pathway, seven variants exhibited no significant alterations in intrinsic clearance (CLint), six variants exhibited significantly high CLint (121-291%), and the remaining 15 variants exhibited substantially reduced CLint (1-71%). In the CYP3A4 metabolic pathway, CYP3A4*30 was not detected in the metabolite content due to the absence of activity, and 10 variants exhibited significantly reduced CLint. CONCLUSION: To the best of our knowledge, this is the first study to assess the kinetic characteristics of 31 CYP2C19 and 12 CYP3A4 genotypes on ibuprofen metabolism. However, further studies are needed on poor metabolizers as they are more susceptible to drug exposure. Our findings suggest that the kinetic characteristics in combination with artificial intelligence to predict the toxicity of ibuprofen and reduce any adverse drug reactions.

Development of a prediction model for the risk of 30-day unplanned readmission in older patients with heart failure: A multicenter retrospective study.

BACKGROUND AND AIM: Heart failure (HF) imposes significant global health costs due to its high incidence, readmission, and mortality rate. Accurate assessment of readmission risk and precise interventions have become important measures to improve health for patients with HF. Therefore, this study aimed to develop a machine learning (ML) model to predict 30-day unplanned readmissions in older patients with HF. METHODS AND RESULTS: This study collected data on hospitalized older patients with HF from the medical data platform of Chongqing Medical University from January 1, 2012, to December 31, 2021. A total of 5 candidate algorithms were selected from 15 ML algorithms with excellent performance, which was evaluated by area under the operating characteristic curve (AUC) and accuracy. Then, the 5 candidate algorithms were hyperparameter tuned by 5-fold cross-validation grid search, and performance was evaluated by AUC, accuracy, sensitivity, specificity, and recall. Finally, an optimal ML model was constructed, and the predictive results were explained using the SHapley Additive exPlanations (SHAP) framework. A total of 14,843 older patients with HF were consecutively enrolled. CatBoost model was selected as the best prediction model, and AUC was 0.732, with 0.712 accuracy, 0.619 sensitivity, and 0.722 specificity. NT.proBNP, length of stay (LOS), triglycerides, blood phosphorus, blood potassium, and lactate dehydrogenase had the greatest effect on 30-day unplanned readmission in older patients with HF, according to SHAP results. CONCLUSIONS: The study developed a CatBoost model to predict the risk of unplanned 30-day special-cause readmission in older patients with HF, which showed more significant performance compared with the traditional logistic regression model.

Ketamine exerts dual effects on the apoptosis of primary cultured hippocampal neurons from fetal rats in vitro.

Ketamine, a noncompetitive N-methyl D-aspartate (NMDA) receptor antagonist, is widely used in pediatric clinical practice. The neuroprotective and neurotoxic effects of ketamine on brain neurons during development remain controversial. The reason may be related to the different concentrations of ketamine used in practice and the small range of concentrations used in previous studies. In this study, cultured hippocampal neurons were treated with ketamine in a wide range of concentrations to comprehensively observe the effects of different concentrations of ketamine on neurons. We demonstrated that low concentrations of ketamine (10 µM, 100 µM and 1000 µM) promoted neuronal survival (p < 0.05) and reduced neuronal apoptosis (p < 0.05) compared with those of the control group. High concentrations of ketamine (2000 µM, 2500 µM and 3000 µM) reduced neuronal survival (p < 0.05) and promoted neuronal apoptosis (p < 0.05). The p38 MAPK inhibitor SB203580 reduced neuronal apoptosis induced by high concentrations of ketamine (2500 µM) (p < 0.05). Our findings indicate that ketamine exerts a dual effect on the apoptosis of primary cultured fetal rat hippocampal neurons in vitro and that the neurotoxic effects of ketamine are related to activation of the p38 MAPK signaling pathway.

Bioequivalence Study of Miglitol Orally Disintegrating Tablets in Healthy Chinese Volunteers Under Fasting Condition Based on Pharmacodynamic and Pharmacokinetic Parameters.

To investigate the bioequivalence of miglitol orally disintegrating tablets in healthy Chinese volunteers based on pharmacodynamic (PD) and pharmacokinetic (PK) parameters. Additionally, the safety profile was estimated. Two randomized, open-label, single-dose, crossover trials were conducted under fasting conditions. In the PD trial (CTR20191811), 45 healthy volunteers were randomly divided into 3 groups in a 1:1:1 ratio and administered sucrose alone or coadministered with 50 mg of miglitol orally disintegrating tablet test or reference formulation/sucrose. In the PK trial (CTR20191696), 24 healthy volunteers were randomized (1:1) to receive the test or reference formulation (50 mg). Blood samples were collected at 15 and 17 sampling points per cycle in the PD and PK trials, respectively. Plasma miglitol and serum glucose concentrations were analyzed using a validated liquid chromatography-tandem mass spectrometry method. Serum insulin concentrations were measured using electrochemiluminescent immunoassay. Statistical analyses for the PD and PK parameters were subsequently performed. The volunteers' physical indicators were monitored and documented during the entire study to estimate drug safety. The PD and PK parameters of the two formulations were similar. The main PD and PK end points were both within the prespecified range of 80%-125%. The incidences of treatment-emergent adverse events (TEAEs) and drug-related TEAEs were similar between the test and reference formulation groups, and no serious TEAEs or deaths occurred during the 2 trials. These 2 formulations were demonstrated to be bioequivalent and well tolerated in healthy Chinese volunteers under fasting condition.

Effect of flavonoids and CYP3A4 variants on midostaurin metabolism.

The objective of this study was to determine the effect of flavonoids on midostaurin disposition considering co-administration and metabolic enzyme gene polymorphism. Enzymatic incubation assays were performed in vitro, while in vivo experiments were conducted in Sprague-Dawley rats. The analytes were determined via UPLC-MS/MS. We found that myricetin was the most potent among the investigated 10 flavonoids in suppressing the metabolism of midostaurin, with an IC50 at a low µM level. After co-administration of midostaurin and myricetin, the plasma concentration of midostaurin's primary metabolite CGP62221 was reduced corresponding to myricetin exposure. Furthermore, CYP3A4 homologous rat protein CYP3A2 was reduced significantly in the co-administration group. Thereafter, the kinetic parameters of 23 recombinant human CYP3A4 variants were determined using midostaurin. The relative intrinsic clearance varied from 269.63% in CYP3A4.29-8.95% in CYP3A4.17. In addition, the inhibitory potency of myricetin was substantially different for CYP3A4.29 and CYP3A4.17 compared with wild type, with IC50 values of 9.85 ± 0.27 µM and 90.99 ± 16.13 µM, respectively. Collectively, our data demonstrated that flavonoids, particularly myricetin, can inhibit the metabolism of midostaurin. Additionally, CYP3A4 genetic polymorphism may contribute to stratification of midostaurin blood exposure.

Dectin-1 plays a deleterious role in high fat diet-induced NAFLD of mice through enhancing macrophage activation.

The innate immune response and inflammation contribute to hepatic steatosis and non-alcoholic fatty liver disease (NAFLD). Dectin-1 is a pathogen recognition receptor in innate immunity. In this study, we investigated the role of Dectin-1 in the pathogenesis of NAFLD. We first showed that Dectin-1 expression was significantly elevated in liver tissues of patients with NASH. NAFLD was induced in mice by feeding high fat diet (HFD) for 24 weeks. At the end of treatment, mice were sacrificed, and their blood and liver tissues were collected for analyses. We showed HFD feeding also increased liver Dectin-1 levels in mice, associated with macrophage infiltration. Either gene knockout or co-administration of a Dectin-1 antagonist laminarin (150 mg/kg twice a day, ip, from 16th week to 24th week) largely protected the livers from HFD-induced lipid accumulation, fibrosis, and elaboration of inflammatory responses. In primary mouse peritoneal macrophages (MPMs), challenge with palmitate (PA, 200 µM), an abundant saturated fatty acid found in NAFLD, significantly activated Dectin-1 signaling pathway, followed by transcriptionally regulated production of pro-inflammatory cytokines. Dectin-1 was required for hepatic macrophage activation and inflammatory factor induction. Condition media generated from Dectin-1 deficient macrophages failed to cause hepatocyte lipid accumulation and hepatic stellate activation. In conclusion, this study provides the primary evidence supporting a deleterious role for Dectin-1 in NAFLD through enhancing macrophage pro-inflammatory responses and suggests that it can be targeted to prevent inflammatory NAFLD.

Determination of CYP450 activities in diabetes mellitus rats by a UHPLC-MS/MS method.

In this study, we investigated the effect of type 1 diabetes mellitus on the modulation of the activities of CYP450s in dynamics by a UHPLC-MS/MS method. The diabetic rat model was constructed by an intraperitoneal single injection of streptozotocin. Fasting blood glucose levels > 16.7 mmol/L were considered as diabetic. The rats were given a cocktail of four probe drugs (10 mg/kg phenacetin, 1 mg/kg tolbutamide, 10 mg/kg metoprolol, and 10 mg/kg midazolam) by oral administration for the pharmacokinetic study. Thereafter, the metabolic ratio (MR) of the metabolites to probe substrates were determined. The results indicated that two weeks after diabetes was induced, diabetes increased the MRs of acetaminophen/phenacetin (CYP1A2) and 4-hydroxyl tolbutamide/tolbutamide (CYP2C9); however, it decreased the MRs of α-hydroxy metoprolol/metoprolol (CYP2D6) and 1-hydroxy midazolam/midazolam (CYP3A4). Two months after diabetes was induced, diabetes increased the MRs of acetaminophen/phenacetin and 4-hydroxyl tolbutamide/tolbutamide. The MR of α-hydroxy metoprolol/metoprolol was decreased and the MR of 1-hydroxy midazolam/midazolam was increased but the difference was not significant. According to the results, CYP1A2 and CYP2C9 activities were enhanced in the diabetic rats. and CYP2D6 activity was inhibited in a short period of diabetes; however, the decrease in CYP2D6 activity was not significant in the long period. CYP3A4 activity was decreased in a short period of diabetes and increased in a long period of diabetes but was not significant in the two periods. This study suggests the activity change rule of the CYP450 enzyme system in diabetes mellitus, which can provide a reference for precise clinical medication.