Population Pharmacokinetics of Lamotrigine and Its N2-Glucuronide Metabolite in Chinese Patients with Epilepsy.

BACKGROUND: Lamotrigine is a new antiepileptic drug with substantial interindividual variability in its pharmacokinetics and therapeutic responses. This study aimed to develop population pharmacokinetic (PPK) models of lamotrigine and its N2-glucuronide metabolites for model-informed individualized therapy. METHODS: A total of 353 plasma concentrations from Chinese patients with epilepsy receiving oral lamotrigine were used to develop a population PPK model using a nonlinear mixed effects modeling method. One- and two-compartment models were applied to the nonmetabolite and metabolite model, respectively. Forward addition and backward elimination were used to establish the final model. Model validation was performed using standard goodness-of-fit, bootstrap, visual predictive checks, and normalized prediction distribution errors. Finally, simulations were performed to propose lamotrigine dosages in different situations to achieve trough concentrations within the reference interval (2.5-15 mg/L). RESULTS: For both final population PPK models, coadministration with valproic acid (VPA) or enzyme inducer, and body weight significantly affected lamotrigine clearance. The final models for lamotrigine clearance were and for nonmetabolite and metabolite models, respectively. The precision of the PPK parameters was acceptable, and the models exhibited good predictability. Monte Carlo simulations revealed that the lamotrigine dosage administered to patients combined with an enzyme inducer must be tripled that administered with VPA to reach the target trough concentration. CONCLUSIONS: Variability in the pharmacokinetics of lamotrigine is large. Coadministration of VPA or an enzyme inducer and body weight are the most important factors in lamotrigine clearance in Chinese patients with epilepsy. The developed population PPK models might support further optimization of lamotrigine dosing regimens.

Risk factors associated with high-dose methotrexate induced toxicities.

INTRODUCTION: High-dose methotrexate (HDMTX) therapy poses challenges in various neoplasms due to individualized pharmacokinetics and associated adverse effects. Our purpose is to identify early risk factors associated with HDMTX-induced toxicities, paving the way for personalized treatment. AREAS COVERED: A systematic review of PubMed and Cochrane databases was conducted for articles from inception to July 2023. Eligible studies included reviews, clinical trials, and real-world analyses. Irrelevant studies were excluded, and manual searches and citation reviews were performed. Factors such as MTX exposure, drug interactions, demographics, serum albumin, urine pH, serum calcium, and genetic polymorphisms affecting MTX transport (e.g. SLCO1B1), intracellular folate metabolism (MTHFR), cell development (ARID5B), metabolic pathways (UGT1A1, PNPLA3), as well as epigenetics were identified. EXPERT OPINION: This comprehensive review aids researchers and clinicians in early identification of HDMTX toxicity risk factors. By understanding the multifaceted risk factors associated with hematologic malignancies, personalized treatment approaches can be tailored to optimize therapeutic outcomes.

UHPLC-MS/MS for plasma lamotrigine analysis and comparison with a homogenous enzyme immunoassay.

Aims: To develop and validate a UHPLC-MS/MS method for lamotrigine (LTG) analysis in human plasma and evaluate its agreement with a homogenous enzyme immunoassay (HEIA). Materials & methods: The UHPLC-MS/MS method was developed and validated according to the USFDA/EMA guidelines. A Bland-Altman plot was used to evaluate the agreement between UHPLC-MS/MS and HEIA. Results: Samples were pretreated with one-step protein precipitation and separated in 2.6 min. The intra- and inter-day bias and imprecisions were -15.8 to 15.0% and less than 11.17%, respectively. The recovery and matrix factor were 98.30 to 111.97%. The mean overestimation of UHPLC-MS/MS compared with HEIA was 21.57%. Conclusion: A rapid, sensitive and robust UHPLC-MS/MS method for plasma LTG analysis was developed and validated and was a 21.57% overestimation compared with HEIA.

UGT1A polymorphism rs4148324 associated with topiramate plasma concentration to dose ratio in children with epilepsy.

PURPOSE: The objective of this study is to evaluate the association between genetic polymorphisms and the concentration to dose ratio of topiramate in children with epilepsy. METHODS: A cohort of 163 pediatric patients with epilepsy receiving topiramate therapy were enrolled. The ultra-performance liquid chromatography-tandem mass spectrometry method was employed to measure the trough plasma concentration of topiramate at steady-state. These concentrations were normalized by dividing them by the ratio of total daily dose to body weight, yielding the concentration to dose ratio (CDR) of topiramate. MassArray system identified 30 single nucleotide polymorphisms associated with the pharmacokinetics and pharmacodynamics of topiramate. The CDR values were logarithmic transformed (lnCDR) for normal distribution. The association between the identified genetic polymorphisms and lnCDR was assessed using the PLINK software, employing linear regression analysis with adjustments by epilepsy types, estimated glomerular filtration rate, alanine aminotransferase, valproic acid, phenobarbital, and oxcarbazepine. RESULTS: Variant rs4148324 (UGT1A1/3/4/5/6/7/8/9/10, BETA = 0.182, P = 0.010) was significantly associated with lnCDR of topiramate. Patients carrying the G allele exhibited higher normalized topiramate plasma concentrations. No other significant associations were found. CONCLUSIONS: In pediatric patients receiving topiramate therapy, rs4148324 was associated with normalized topiramate plasma concentration. Further studies are warranted to validate and confirm the findings.

An ultrahigh-performance liquid chromatography-tandem mass spectrometry method for quantification of methotrexate and 7-hydroxy-methotrexate and application for therapeutic drug monitoring in patients with central nervous system lymphoma.

A method using ultrahigh-performance liquid chromatography-tandem mass spectrometry was developed, validated, and applied to simultaneously determine plasma methotrexate (MTX) and 7-hydroxy-methotrexate (7-OH-MTX) in 117 patients with central nervous system (CNS) lymphoma. The ion transitions utilized were m/z 455.2 > 308.2 for MTX and m/z 471.2 > 324.1 for 7-OH-MTX. Samples were prepared through protein precipitation using methanol. Chromatographic separation was achieved within 3.0 min on a CMS9030 column (Ruixi, 2.1 × 50 mm, 3 µm) through a gradient elution of methanol and a 10% ammonium acetate solution at a flow rate of 0.4 mL/min. The method demonstrated linearity in the concentration range of 0.05-10 µM for MTX and 0.25-50 µM for 7-OH-MTX. The intra- and inter-day inaccuracy ranged from -7.38% to 7.83%, and the imprecision was less than 6.00% for both analytes. The recovery and matrix effect normalized by the internal standard (MTX-D3 ) remained consistent. Both analytes remained stable under nine different storage conditions. In patients with CNS lymphoma, MTX levels at 12 h and 7-OH-MTX levels at 12, 36, and 60 h after dosing in individuals with impaired renal function were significantly higher compared with those with normal renal function. 7-OH-MTX could potentially serve as a superior indicator for nephrotoxicity compared with MTX.

Causal relationship between spondylarthritis and stroke in a European population: a two sample Mendelian randomization study.

Background: Observational studies have found an increased risk of stroke in patients with spondyloarthritis, but the results are susceptible to reverse causality and confounders. Therefore, the study aimed to further explore the association between spondyloarthritis and different subtypes of stroke by using a two sample Mendelian randomization (MR) analysis. Methods: Genetic instrumental variables for spondyloarthritis were identified using summary level data from a genome-wide association study involving 201,581 people. Summary statistics from the Multiancestry Genome-wide Association Study of Stroke Consortium were used to obtain genetic data on stroke. There was no sample overlap between the exposure and outcome datasets. Inverse-variance weighted was considered the primary MR method for causal analysis. Heterogeneity, pleiotropy and sensitivity analyses were performed to ensure robustness, and single nucleotide polymorphism (SNP) with potential confounders was further screened in the PhenoScanner database to better evaluate the stability of our study. Results: One SNP (rs1065045) was excluded due to schizophrenia. After excluding SNP (rs1065045), results of the second MR analysis were slightly different from the first, which were considered as the final result: a significant positive causality between spondyloarthritis and cardioembolic stroke (OR=1.296, 95% CI:1.094-1.534, p=0.003); a possible positive causality between spondyloarthritis and any stroke (OR=1.082, 95% CI:1.016-1.152, p=0.013)/any ischemic stroke (OR=1.086, 95% CI:1.013-1.163, p=0.020); no significant/possible causality between spondyloarthritis and small vessel stroke (OR=1.168, 95% CI:0.993-1.375, p=0.061). Insufficient power may be one possible reason why a causality was not observed between spondyloarthritis in our study. Conclusions: This study suggests that the possible causative effects of spondyloarthritis predicted by genetics on stroke may be limited to any stroke, any ischemic stroke, and cardioembolic stroke, especially the last.

Population pharmacokinetics of topiramate in Chinese children with epilepsy.

OBJECTIVE: Topiramate, a broad-spectrum antiepileptic drug, exhibits substantial inter-individual variability in both its pharmacokinetics and therapeutic response. The aim of this study was to investigate the influence of patient characteristics and genetic variants on topiramate clearance using population pharmacokinetic (PPK) models in a cohort of Chinese pediatric patients with epilepsy. METHOD: The PPK model was constructed using a nonlinear mixed-effects modeling approach, utilizing a dataset comprising 236 plasma concentrations of topiramate obtained from 181 pediatric patients with epilepsy. A one-compartment model combined with a proportional residual model was employed to characterize the pharmacokinetics of topiramate. Covariate analysis was performed using forward addition and backward elimination to assess the influence of covariates on the model parameters. The model was thoroughly evaluated through goodness-of-fit analysis, bootstrap, visual predictive checks, and normalized prediction distribution errors. Monte Carlo simulations were utilized to devise topiramate dosing strategies. RESULT: In the final PPK models of topiramate, body weight, co-administration with oxcarbazepine, and a combined genotype of GKIR1-UGT (GRIK1 rs2832407, UGT2B7 rs7439366, and UGT1A1 rs4148324) were identified as significant covariates affecting the clearance (CL). The clearance was estimated using the formulas CL (L/h) = 0.44 × (BW/11.7)0.82 × eOXC for the model without genetic variants and CL (L/h) = 0.49 × (BW/11.7)0.81 × eOXC × eGRIK1-UGT for the model incorporating genetic variants. The volume of distribution (Vd) was estimated using the formulas Vd (L) = 6.6 × (BW/11.7). The precision of all estimated parameters was acceptable. Furthermore, the model demonstrated good predictability, exhibiting stability and effectiveness in describing the pharmacokinetics of topiramate. CONCLUSION: The clearance of topiramate in pediatric patients with epilepsy may be subject to the influence of factors such as body weight, co-administration with oxcarbazepine, and genetic polymorphism. In this study, PPK models were developed to better understand and account for these factors, thereby improving the precision and individualization of topiramate therapy in children with epilepsy.

Population pharmacokinetics of oxcarbazepine active metabolite in Chinese children with epilepsy.

Oxcarbazepine (OXC) is an antiepileptic drug whose efficacy is largely attributed to its monohydroxy derivative metabolite (MHD). Nevertheless, there exists significant inter-individual variability in both the pharmacokinetics and therapeutic response of this drug. The objective of this study is to explore the impact of patients' characteristics and genetic variants on MHD clearance in a population pharmacokinetic (PPK) model of Chinese pediatric patients with epilepsy. The PPK model was developed using a nonlinear mixed effects modeling method based on 231 MHD plasma concentrations obtained from 185 children with epilepsy. The one-compartment model and combined residual model were established to describe the pharmacokinetics of MHD. Forward addition and backward elimination were employed to evaluate the impact of covariates on the model parameters. The model was evaluated using goodness-of-fit, bootstrap, visual predictive checks, and normalized prediction distribution errors. In the two final PPK models, age, estimated glomerular filtration rate (eGFR), and a combined genotype of six variants (rs1045642, rs2032582, rs7668282, rs2396185, rs2304016, rs1128503) were found to significantly reduce inter-individual variability for MHD clearance. The inter-individual clearance equals to 1.38 × (Age/4.74)0.29 × (eGFR/128.66)0.25 × eθABCB-UGT-SCN-INSR for genetic variants included model and 1.30 × (Age/4.74)0.30 × (eGFR/128.66)0.23 for model without genetic variants. The precision of all parameters was deemed acceptable, and the model exhibited good predictability while remaining stable and effective.    Conclusion: Age, eGFR, and genotype may play a significant role in MHD clearance in children with epilepsy. The developed PPK models hold potential utility in facilitating oxcarbazepine dose adjustment in pediatric patients. What is Known: • The adjustment of the oxcarbazepine regimen remains difficult due to the considerable inter- and intra-individual variability of oxcarbazepine pharmacokinetics. • Body weight and co-administration with enzyme-inducing antiepileptic drugs emerge as the most influential factors contributing to the pharmacokinetics of MHD. What is New: • A positive correlation was observed between eGFR and the clearance of MHD in pediatric patients with epilepsy. • We explored the influence of genetic polymorphisms on MHD clearance and identified a combined genotype (ABCB-UGT-SCN-INSR) that exhibited a significant association with MHD concentration.

External validation of population pharmacokinetic models of vancomycin in postoperative neurosurgical patients.

OBJECTIVE: Vancomycin is commonly used in the prevention and treatment of intracranial infections in postoperative neurosurgical patients with narrow therapeutic window and large pharmacokinetic variations. Several population pharmacokinetic (PPK) models of vancomycin have been established for neurosurgical patients. But comprehensive external evaluation has not been performed for almost all models. The objective of this study was to evaluate the predictive ability of published vancomycin PPK models in adult postoperative neurosurgical patients using an independent dataset. METHOD: PubMed, Embase and China National Knowledge Internet databases were searched to identify published vancomycin PPK models in adult postoperative neurosurgical patients. Prediction-based and simulation-based diagnostics were used to evaluate model predictability. Bayesian forecasting was used to assess the influence of prior concentration on model prediction performance. RESULT: A total of 763 vancomycin plasma concentrations from 493 postoperative neurosurgical patients were included in the external dataset. Eight population pharmacokinetic models of vancomycin in postoperative neurosurgical patients were included and evaluated. The model by Zhang et al. exhibited the best predictive performance in prediction-based diagnostics and prediction-corrected visual predictive checks, followed by the model by Shen et al. The predictive performance of other models was not satisfactory. The normalized predictive distribution error test shows that none of the models is suitable to describe our data. The predictive performance of vancomycin models was obviously improved by maximum a posteriori Bayesian forecasting. CONCLUSION: The published PPK models for adult postoperative neurosurgical patients show extensive variation in predictive performance in our patients. Although it is challenging to recommend initial doses of vancomycin from these predictive models, the combination of model-based prediction and therapeutic drug monitoring can be used for dose optimization.

Trends in research on acute lung injury/acute respiratory distress syndrome associated with viral pneumonia from 1992 to 2022: a 31-year bibliometric analysis.

Purpose: Acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is a dangerous symptom in patients with severe viral pneumonia. This study aims to comprehensively review the cooperation and influence of countries, institutions, authors and co-cited journals/authors/references and keywords in the field of ALI/ARDS associated with viral pneumonia from the perspective of bibliometrics, evaluate the clustering evolution of knowledge structure, and find hot trends and emerging topics. Methods: Publications on ALI/ARDS associated with viral pneumonia published from January 1, 1992 to December 31, 2022 were extracted from the Web of Science core collection. The document type was limited to original article or review, with the language set to English. Citespace was used to conduct the bibliometric analysis. Results: A total of 929 articles were included, and the number of them generally increased over time. The countries with the most published articles in this field are the United States (320 papers) and Fudan University is the institution (15 papers) with the most research results. The New England Journal of Medicine was the most frequently co-cited journal, while the most influential co-cited journal was American Journal of Clinical Pathology. Reinout A Bem and Cao Bin were the most prolific author, but there was no leader in this field. The keywords with both high frequency and high centrality were "pneumonia" (Freq = 169, Central = 0.15), "infection" (Freq = 133, Central = 0.15), "acute lung injury" (Freq = 112, Central = 0.18), "respiratory distress syndrome" (Freq = 108, Central = 0.24), and "disease" (Freq = 61, Central = 0.17). "Failure" was the first keyword with citation bursts. Meanwhile, "coronavirus," "cytokine storm" and "respiratory syndrome coronavirus" continue to burst. Conclusion: Although there was a surge in literature since 2020, attentions to ALI/ARDS associated with viral pneumonia were still insufficient over last three decades. The communication and cooperation among countries, institutions and authors need to be further strengthened.

A UHPLC-MS/MS method for the simultaneous determination of vancomycin, norvancomycin, meropenem, and moxalactam in human plasma and its clinical application.

We developed an ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method to determine four antibacterial drugs in human plasma for clinical usage. Samples were prepared using protein precipitation with methanol. Chromatographic separation was accomplished in 4.5 min on a BEH C18 column (2.1 × 50 mm, 1.7 µm) using a gradient elution of methanol and water (containing 7.71 g/L concentrated ammonium acetate, adjusted to pH 6.5 with acetic acid) at a flow rate of 0.4 mL/min. Positive electrospray was used for ionization. The method was linear in the concentration range 1-100 µg/mL for vancomycin, norvoncomycin, and meropenem; and 0.5-50 µg/mL for R-isomer of moxalactam and S-isomer of moxalactam. For all analytes, the intra- and inter-day accuracies and precisions were -8.47%-10.13% and less than 12%, respectively. The internal standard normalized recoveries and matrix effect were 62.72%-105.78% and 96.67%-114.20%, respectively. All analytes were stable at six storage conditions, with variations of less than 15.0%. The method was applied in three patients with central nervous system infection. The validated method might be useful for routine therapeutic drug monitoring and pharmacokinetic study.

Trends in research related to vaccine and cancer prevention from 1992 to 2022: A 30-years bibliometric analysis.

Vaccines may play an important role in cancer prevention. This bibliometric study in the field of vaccine and cancer prevention is designed to evaluate key research advances, identify existing deficiencies, and provide reference for future investigations. A total of 2916 original articles published in English from 1992 to 2022 were extracted from the Web of Science core collection. America (1,277) and the National Cancer Institute (82) were the most productive country and institution in this field, respectively. Vaccine was not only the most co-cited journal but also the most influential. Garland SM was the most prolific author, and Bosch FX was the most influential co-cited author. The keywords "cervical cancer" had the highest frequency. "Nanovaccines," "vaccine acceptance" and "coverage" were the new research hotspots in this field. Currently, although an increasing number of publications involve vaccine and cancer prevention studies, most of them are related to cervical cancer, and few other cancers, suggesting the need to investigate other cancer prevention vaccines. The promising research hotspots, such as nanovaccines, vaccine acceptance, and vaccine coverage should be the focus of investigation. The study provides the current status and trends in clinical research on vaccine and cancer prevention, enabling researchers to identify hotspots and explore new study directions. In the future, vaccines are expected to play a key role in multiple cancer prevention.

What is the context? Currently, cancer is the leading cause of death worldwide and poses a significant burden due to increasing incidence, high mortality, and heavy economic costs. One effective way to prevent cancers is by using cancer prevention vaccines such as the human papillomavirus (HPV) vaccine. By preventing an infection that can progress to cancer and reducing the morbidity and economic burden, HPV vaccines have played a positive role in the fight against cervical cancer. The potential of vaccines as a cancer prevention strategy is significant. However, the shortcomings, progress, hotspots and frontiers of global research in the field of vaccine and cancer prevention remain unclear.What is new? In this study, a bibliometric analysis was conducted from multiple aspects such as countries, institutions, authors, co-cited authors/journals/references and keywords. The analysis was designed to evaluate the important research progress in vaccine and cancer prevention, to explore the research hotspots and frontiers, and to identify existing problems and deficiencies. It provides a valuable reference for future research directions.What is the impact? Excluding cervical and liver cancer, few other cancers have been investigated in the field of vaccine and cancer prevention, suggesting the need for intensive studies focusing on other cancer prevention vaccines. Key areas for investigation include nanovaccines, vaccine acceptance, and vaccine coverage. In the future, vaccines are expected to play a more important role in prevention of cancers beyond cervical cancer prevention.

Simultaneous determination of 24 antiepileptic drugs and their active metabolites in human plasma by UHPLC-MS/MS.

Antiepileptic drugs (AEDs) have narrow therapeutic ranges with large individual variability. Routine therapeutic drug monitoring of AEDs was useful for dose optimization, but the common immunoassays could not meet the detection requirements of AEDs, especially for new generation AEDs. The aim of this study was to validate an ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method for simultaneously quantification of 24 AEDs and their active metabolites in human plasma and comparison with a chemiluminescent immunoassay (Simens ADVIA Centaur). The method validation was performed according to FDA and EMEA guidelines. A one-step protein precipitation by acetonitrile followed a five-fold dilution was performed for sample pretreatment. A 5.2 min gradient separation by methanol and 10 mM ammonium acetate was used for separation at 0.6 mL/min under 45 °C. Both positive and negative electrospray ionization were used. Isotopic internal standard was used for all analytes. The inter-day (36 days) accuracy and precision of quality control samples were - 1.07-13.69% and < 6.70% for all analytes. The stability was acceptable for all analytes under routine storing conditions. A total of 436 valproic acid, 118 carbamazepine, and 65 phenobarbital samples were determined twice by each of the UHPLC-MS/MS and immunoassay. Evaluated by Bland-Altman plot, the mean overestimation of the immunoassay compared to UHPLC-MS/MS was 16.5% for valproic acid, 5.6% for carbamazepine, and 40.3% for phenobarbital.

Trends in metabolic signaling pathways of tumor drug resistance: A scientometric analysis.

Background: Cancer chemotherapy resistance is one of the most critical obstacles in cancer therapy. Since Warburg O first observed alterations in cancer metabolism in the 1950s, people gradually found tumor metabolism pathways play a fundamental role in regulating the response to chemotherapeutic drugs, and the attempts of targeting tumor energetics have shown promising preclinical outcomes in recent years. This study aimed to summarize the knowledge structure and identify emerging trends and potential hotspots in metabolic signaling pathways of tumor drug resistance research. Methods: Publications related to metabolic signaling pathways of tumor drug resistance published from 1992 to 2022 were retrieved from the Web of Science Core Collection database. The document type was set to articles or reviews with language restriction to English. Two different scientometric software including Citespace and VOS viewer were used to conduct this scientometric analysis. Results: A total of 2,537 publications including 1,704 articles and 833 reviews were retrieved in the final analysis. The USA made the most contributions to this field. The leading institution was the University of Texas MD Anderson Cancer Center. Avan A was the most productive author, and Hanahan D was the key researcher with the most co-citations, but there is no leader in this field yet. Cancers was the most influential academic journal, and Oncology was the most popular research field. Based on keywords occurrence analysis, these selected keywords could be roughly divided into five main topics: cluster 1 (study of cancer cell apoptosis pathway); cluster 2 (study of resistance mechanisms of different cancer types); cluster 3 (study of cancer stem cells); cluster 4 (study of tumor oxidative stress and inflammation signaling pathways); and cluster 5 (study of autophagy). The keywords burst detection identified several keywords as new research hotspots, including "tumor microenvironment," "invasion," and "target". Conclusion: Tumor metabolic reprogramming of drug resistance research is advancing rapidly. This study serves as a starting point, providing a thorough overview, the development landscape, and future opportunities in this field.

Population pharmacokinetic model of vancomycin in postoperative neurosurgical patients.

Objective: Vancomycin is commonly used in postoperative neurosurgical patients for empirical anti-infective treatment due to the low success rate of bacterial culture in cerebrospinal fluid (about 20%) and the high mortality of intracranial infection. At conventional doses, the rate of target achievement for vancomycin trough concentration is low and the pharmacokinetics of vancomycin varies greatly in these patients, which often leads to treatment failure. The objective of this study was to establish a population pharmacokinetic (PPK) model of vancomycin in postoperative neurosurgical patients for precision medicine. Method: A total of 895 vancomycin plasma concentrations from 560 patients (497 postoperative neurosurgical patients) were retrospectively collected. The model was analyzed by nonlinear mixed effects modeling method. One-compartment model and mixed residual model was employed. The influence of covariates on model parameters was tested by forward addition and backward elimination. Goodness-of-fit, bootstrap and visual predictive check were used for model evaluation. Monte Carlo simulations were employed for dosing strategies with AUC24 targets 400-600. Result: Estimated glomerular filtration rate (eGFR), body weight (BW) and mannitol had significant influence on vancomycin clearance (CL). e G F R ( m L / min ) = 144 × ( S c r / a ) b × 0.993 a g e , for female, a = 0.7, Scr ≤ 0.7 mg/dl, b = -0.329, Scr > 0.7 mg/dl, b = -1.209; for male, a = 0.9, Scr ≤ 0.9 mg/dl, b = -0.411, Scr > 0.9 mg/dl, b = -1.210. Vancomycin clearance was accelerated when co-medicated with mannitol and increased with eGFR and BW. In the final model, the population typical value is 7.98 L/h for CL and 60.2 L for apparent distribution volume, C L ( L / h ) = 7.98 × ( e G F R / 115.2 ) 0.8 × ( B W / 70 ) 0.3 × e A , where A = 0.13 when co-medicated with mannitol, otherwise A = 0. The model is stable and effective, with good predictability. Conclusion: In postoperative neurosurgical patients, a higher dose of vancomycin may be required due to the augmented renal function and the commonly used mannitol, especially in those with high body weight. Our vancomycin PPK model could be used for individualized treatment in postoperative neurosurgical patients.

Simultaneous determination of plasma lamotrigine, lamotrigine N2-glucuronide and lamotrigine N2-oxide by UHPLC-MS/MS in epileptic patients.

The plasma concentration of lamotrigine (LTG) and its metabolites has great interindividual variability. An UHPLC-MS/MS method for simultaneous determination of LTG and lamotrigine N2-glucuronide (LTG N2-GLUC), lamotrigine N2-oxide was developed, validated, and applied in 58 plasma samples. The ion transition was m/z 256.0 > 144.9 for LTG, 432.1 > 256.0 for LTG N2-GLUC, 272.2 > 241.9 for LTG N2-oxide, and 259.1 > 144.8 for LTG-13C3 (internal standard). The flow rate was 0.4 mL/min with a run time of 3 min. The calibration range was 0.025-2 mg/L for LTG and LTG N2-GLUC, and 0.000625-0.05 mg/L for LTG N2-oxide. For all analytes, the intra-day and inter-day bias and imprecision were -11.7-5.7 % and less than 14.3 %, and the internal standard normalized recovery and matrix factor were 91.7-101.5 % and 98.1-110.1 % with CV < 13. 7%. Ten- and twenty-fold dilution with blank plasma did not affect the analysis. All analytes were stable in plasma at room temperature for 8 h, at -80 °C for 80 days, and after 3 freeze-thaw cycles. The LTG N2-GLUC/LTG ratio was 0.44 in LTG monotherapy group. The ratio was reduced to 0.17 when co-administrated with valproic acid, while elevated to 0.82 when co-administrated with enzyme inducer. In conclusion, this method is suitable for simultaneous determination of LTG, LTG N2-GLUC and LTG N2-oxide in human plasma.

Leucovorin (folinic acid) rescue for high-dose methotrexate: A review.

High-dose methotrexate (HDMTX) is active against various malignancies; it possesses serious toxicities and is associated with patient characteristics, dosage regimens, comedications, and physiological status. There are many strategies to overcome HDMTX-induced toxicities, such as hydration, alkalization, leucovorin rescue, and haemodialysis. Leucovorin rescue is a cornerstone for toxicity prevention in HDMTX treatment. However, the leucovorin dose adjustment and the existence of leucovorin overrescue are still controversial. At present, various methods for calculating leucovorin doses in different tumour types have been proposed, including empirical calculations based on MTX plasma concentration, the Bleyer nomogram, and other methods. Nonetheless, leucovorin rescue protocols differ greatly across tumour types and medical institutions. Further studies are needed to investigate the optimal dosage regimen for leucovorin rescue in various tumours using HDMTX.

Determination of levodopa by chromatography-based methods in biological samples: a review.

Levodopa (L-DOPA) is the most effective drug for Parkinson's disease; however, various side effects occur during therapy. L-DOPA metabolites and the high cumulative dose of L-DOPA were responsible for its side effects. It is necessary to monitor the concentration of L-DOPA and its metabolites for individualized therapy. This review focuses on L-DOPA analysis by chromatography-based methods in biological matrices. Literature published up to September 2021 was collected in the PubMed, Web of Science, and Embase by using search strategy ("levodopa" OR "L-DOPA") AND ("chromatography"). A total of 1249 articles were identified and 32 articles were included. The contents for method development and validation were summarized and analyzed. Due to the instability of catecholamines (L-DOPA, dopamine, and 3-O-methyldopa) and carbidopa, antioxidation (0.5 mg sodium metabisulfite for 100 µL sample) and environment temperature control were used alone or in combination to enhance stability. Sample was mainly pretreated by protein precipitation (0.4-0.7 M perchloric acid). Separation was usually achieved using methanol or acetonitrile:water (with formic acid) on C18 columns. Mass spectrometry, electrochemical detector, ultraviolet-visible detector and fluorescence detector were used for detection. For L-DOPA, the calibration range was 2.5-10,000 ng/mL, the matrix effect and its coefficient of variation was 85-115 and -9.0-8.5%, and the recovery was 66.8-127.0%. Without stabilization strategy, L-DOPA was stable in plasma at room temperature for 1-7 h (4-6 h for most studies), at - 70 °C to - 80 °C for 10-20 days and after 3-5 freeze-thaw cycles. With stabilization strategies, the stability of L-DOPA in plasma was significantly improved. Metabolites of L-DOPA and enzyme inhibitors (carbidopa, entacapone, tolcapone and benserazide) were all stable in biological matrix. This study might be useful for researchers to develop their methods for individualized therapy of patients with Parkinson.

CTLA-4 Facilitates DNA Damage-Induced Apoptosis by Interacting With PP2A.

Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) plays a pivotal role in regulating immune responses. It accumulates in intracellular compartments, translocates to the cell surface, and is rapidly internalized. However, the cytoplasmic function of CTLA-4 remains largely unknown. Here, we describe the role of CTLA-4 as an immunomodulator in the DNA damage response to genotoxic stress. Using isogenic models of murine T cells with either sufficient or deficient CTLA-4 expression and performing a variety of assays, including cell apoptosis, cell cycle, comet, western blotting, co-immunoprecipitation, and immunofluorescence staining analyses, we show that CTLA-4 activates ataxia-telangiectasia mutated (ATM) by binding to the ATM inhibitor protein phosphatase 2A into the cytoplasm of T cells following transient treatment with zeocin, exacerbating the DNA damage response and inducing apoptosis. These findings provide new insights into how T cells maintain their immune function under high-stress conditions, which is clinically important for patients with tumors undergoing immunotherapy combined with chemoradiotherapy.

Review of HPLC-MS methods for the analysis of nicotine and its active metabolite cotinine in various biological matrices.

In recent years, tobacco smoking is a risk factor for a series of diseases, including cardiovascular diseases, cerebrovascular diseases, and cancers. Nicotine, the primary component of tobacco smoke, is mainly transformed to its active metabolite cotinine, which is often used as a biomarker for tobacco exposure for its higher blood concentration and longer residence time than nicotine. Various analytical methods have been developed for the determination of nicotine and cotinine in biological matrices. This article reviewed the HPLC-MS based methods for nicotine and/or cotinine analysis in various biological matrices. The sample preparation, mass and chromatographic conditions, and method validation results of these methods have been summarized and analyzed. The sample was mainly pretreated by protein precipitation and/or extraction. Separation was achieved using methanol and/or acetonitrile:water (with or without ammonium acetate) on C18 columns and acetonitrile:water (with formic acid, ammonium acetate/formate) on HILIC columns. Nicotine-d3, nicotine-d4, and cotinine-d3 were commonly used internal standards (ISs). Other non-deuterated ISs such as ritonavir, N-ethylnorcotinine, and milrinone were also used. For both nicotine and cotinine, the calibration range was 0.005-35,000 ng/mL, the matrix effect was 75.96-126.8%, and the recovery was 53-124.5%. The two analytes were stable at room temperature for 1-10 days, at -80°C for up to 6 months, and after three to six freeze-thaw cycles. Comedications did not affect nicotine and cotinine analyses.