Publications by authors named "Yuguan Wen"

Chronic ketamine administration causes cognitive impairments similar to those observed in schizophrenia. Growing evidence suggests that patients with schizophrenia show alterations in gut microbiota, which is associated with cognitive impairments. Inulin could regulate gut microbiota.

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Background: The aim of this study was to determine the therapeutic reference range of lurasidone, and to analyze the factors influencing the dose-corrected concentration of lurasidone in Chinese psychiatric patients, thereby providing a basis for the development of individualized dosing of lurasidone.

Methods: A retrospective analysis was conducted for hospitalized patients who had received lurasidone and undergone blood concentration monitoring from May 2022 to September 2023 at the Affiliated Brain Hospital of Guangzhou Medical University. Analyses were based on patient demographic data, treatment regimens, and administered drug concentrations.

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  • This study investigated cardiovascular adverse events (AEs) linked to venlafaxine (VEN) therapy by analyzing data from the FDA Adverse Event Reporting System between January 2004 and December 2023.
  • It revealed that higher doses of VEN increased the risk of various cardiovascular issues, especially in older adults, males, and those with other medical conditions or taking certain medications.
  • The findings suggest close monitoring of cardiovascular health in elderly patients on VEN and highlight the need for further prospective research to confirm these results.
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  • - The study investigates the cardiovascular risks associated with 37 commonly prescribed antidepressants, focusing on the link between depression and heart-related issues.
  • - Data from the FDA Adverse Event Reporting System (FAERS) from 2004 to 2023 was analyzed to identify cardiovascular adverse events (AEs) related to these medications, highlighting that monoamine oxidase inhibitors pose the highest risk.
  • - Factors like age, gender, and specific antidepressants significantly influenced the occurrence of cardiovascular deaths, with amoxapine showing the greatest risk of serious heart-related events.
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  • Sertraline is a commonly used SSRI for depression, noted for its effectiveness and favorable safety compared to other medications, but there’s limited data on its pharmacokinetics in the Chinese population.
  • A study analyzed data from 140 Chinese patients to identify factors influencing sertraline drug exposure, using advanced modeling techniques to assess the impact of covariates like age on drug clearance.
  • The research concluded that sertraline clearance decreases with age, highlighting an optimal daily dose for adolescents and recommending specific dosage regimens to manage serum concentration effectively.
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Objectives: To analyze the factors affecting the concentrations of the active moiety of risperidone (RIS) and its active metabolite 9-hydroxyrisperidone (9-OH-RIS) in psychiatric outpatients taking immediate-release formulations.

Methods: This is a retrospective study on the therapeutic drug monitoring (TDM) data regarding RIS and 9-OH-RIS in adult psychiatric outpatients. TDM data with simultaneous RIS and 9-OH-RIS monitoring from March 2018 to February 2020 and relevant medical records (including dosage, dosage form, sex, age, diagnosis, combined medication, and comorbid disease) from 399 adult psychiatric outpatients (223 males and 176 females) were included in this study.

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Danzhi-xiaoyao-San (DZXYS), a Traditional Chinese Medicine, plays an essential role in the clinical treatment of depression, but its mechanisms in humans remain unclear. To investigate its pharmacological effects and mechanisms as an add-on therapy for depression, we conducted a double-blind, placebo-controlled trial with depressed patients receiving selective serotonin reuptake inhibitors (SSRIs). Serum and fecal samples were collected for metabolomic and microbiome analysis using UHPLC-QTRAP-MS/MS and 16S rRNA gene sequencing technologies, respectively.

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Background: Genetic polymorphism has been proven to have an important association with depression, which can influence the risk of developing depression, the efficacy of medications, and adverse effects metabolic and neurological pathways. Nonetheless, aspects of the association between single nucleotide polymorphisms and depression have not been systematically investigated by bibliometric analysis.

Objective: The aim of this study was to analyze the current status and trends of single nucleotide polymorphism research on depression through bibliometric and visual analysis.

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Alzheimer's disease (AD) has attracted considerable attention from the public and scientific researchers, leading to a rapid growth in relevant research on this disorder in the last 10 years. The present study aimed to conduct a bibliometric analysis to elucidate the trends of global research on the role of apolipoprotein E in AD in the past decade. Three bibliometric software (CiteSpace, VOSviewer, and R Bibliometrix) were used to analyze the active journals, countries/regions, institutes, authors, co-cited references, and keywords in this field.

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A sensitive, convenient, rapid and economic liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to determine cinacalcet concentration in human plasma. A stable isotope cinacalcet (cinacalcet-D) was selected as internal standard and the analytes were extracted from plasma samples by a one-step precipitation procedure. Chromatography separation was conducted on an Eclipse Plus C18 column by gradient elution with mobile phase of methanol-water-ammonium formate system at a constant flow rate of 0.

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Objective: Growing evidence suggests an abnormal metabolism of kynurenine in individuals with alcohol use disorder (AUD). This systematic review and meta-analysis was aimed at assessing the possible differences in kynurenine metabolites between individuals with AUD and controls.

Methods: We searched PubMed, Embase, and Web of Science databases and included any clinical studies comparing the peripheral blood levels of at least one metabolite, between individuals with AUD and controls without AUD.

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Article Synopsis
  • Alcohol use disorder (AUD) leads to chronic excessive drinking and withdrawal periods; diazepam is commonly used to treat alcohol withdrawal syndrome but the exact mechanisms of its effectiveness require further research.
  • An animal model was created to study the effects of chronic ethanol exposure using advanced proteomic analysis and network analysis techniques to map protein interactions in the brain.
  • Seven key hub proteins related to alcohol withdrawal and diazepam treatment were identified, with glutamatergic synapses emerging as a crucial pathway affected by alcohol use disorder and a potential target for new treatment strategies.
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The gene encodes the key aromatase for estrogen biosynthesis, and this study aimed to explore the relationship between rs6493497 and rs936306 polymorphisms and depression risk. rs6493497 and rs936306 genotyping was performed on 502 depression patients and 504 healthy controls. In the general population, no significant association was observed between the rs6493497 variant and depression, whereas that rs936306 variant significantly reduced depression risk in the recessive model.

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  • Venlafaxine (VEN) is a common medication for treating depression and anxiety and is metabolized into an active form called O-desmethyl venlafaxine (ODV) after it is processed in the liver.
  • The study aimed to create a population pharmacokinetic (PPK) model to analyze the characteristics of both VEN and ODV using data from a bioequivalence study involving healthy individuals and a larger group of psychiatric patients.
  • The PPK modeling, performed with NONMEM software, showed that the metabolism of VEN and ODV follows a one-compartment model, and identified factors like mental health status and the medication amisulpride as significant influences on how these drugs are processed in the body, potentially aiding in personalized
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Many studies associated with the combination of machine learning (ML) and pharmacometrics have appeared in recent years. ML can be used as an initial step for fast screening of covariates in population pharmacokinetic (popPK) models. The present study aimed to integrate covariates derived from different popPK models using ML.

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Background And Aim: Available evidence suggests elevated serum prolactin (PRL) levels in olanzapine (OLZ)-treated patients with schizophrenia. However, machine learning (ML)-based comprehensive evaluations of the influence of pathophysiological and pharmacological factors on PRL levels in OLZ-treated patients are rare. We aimed to forecast the PRL level in OLZ-treated patients and mine pharmacovigilance information on PRL-related adverse events by integrating ML and electronic health record (EHR) data.

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Therapeutic drug monitoring (TDM) has evolved over the years as an important tool for personalized medicine. Nevertheless, some limitations are associated with traditional TDM. Emerging data-driven model forecasting [e.

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Paroxetine is one of the most potent selective serotonin reuptake inhibitors (SSRIs) approved for treating depression, panic disorder, and obsessive-compulsive disorder. There is evidence linking genetic polymorphisms and nonlinear metabolism to the Paroxetine's pharmacokinetic (PK) variability. The purpose of the present study was to develop a population PK (PPK) model of paroxetine in Chinese patients, which was used to define the paroxetine's PK parameters and quantify the effect of clinical and baseline demographic factors on these PK characteristics.

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  • Olanzapine is an atypical antipsychotic used for mental disorders, but there's limited pharmacokinetic data for Chinese pediatric patients aged 10 to 17 years, which raises questions about dosage variability.
  • A study collected therapeutic drug monitoring data from 151 pediatric patients and developed a model using NONMEM software to simulate dosing regimens, targeting a concentration level of 20 ng/ml.
  • The final model identified sex and concomitant valproate as significant factors affecting olanzapine clearance, suggesting specific daily dosages for male and female patients, which can assist physicians in dosage adjustments.
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Introduction: Abnormal neurotransmission of glutamate and γ-aminobutyric acid (GABA) is a key characteristic of alcohol-related disorders. To track research output, we conducted a bibliometric analysis to explore the current status and trends in this field over the past decades.

Methods: Studies related to neurotransmitters and alcohol use disorder published in English from 2005-2021 were retrieved from the Web of Science Core Collection and Scopus databases.

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  • The study aimed to create a population pharmacokinetic model for escitalopram in Chinese psychiatric patients, focusing on factors affecting drug exposure.
  • Data from 106 inpatients, including demographic data, CYP2C19 genotypes, and liver/kidney function, were analyzed using nonlinear mixed-effects modeling.
  • Findings indicated that age and CYP2C19 genotype significantly influence escitalopram clearance, highlighting the need for individualized dosing, especially in older patients and poor metabolizers to avoid adverse effects.
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A high-performance liquid chromatographic method coupled with triple quadrupole mass spectrometry (LC-MS/MS) for the analysis of blonanserin and its active metabolite, -desethyl blonanserin, in rat plasma has been developed and validated. The biological samples were treated by simple direct protein precipitation before separation on an Agilent Eclipse Plus C column (4.6 × 100 mm, 3.

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Background: In recent years, there has been a significant worldwide increase in the use of generic drugs. China has committed to a consistency evaluation of generic drugs, with the aim to improve the rate of substitution. However, there is little research on physicians' perceptions of generic drugs in China.

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Alcohol dependence (AD) is a condition of alcohol use disorder in which the drinkers frequently develop emotional symptoms associated with a continuous alcohol intake. AD characterized by metabolic disturbances can be quantitatively analyzed by metabolomics to identify the alterations in metabolic pathways. This study aimed to: i) compare the plasma metabolic profiling between healthy and AD-diagnosed individuals to reveal the altered metabolic profiles in AD, and ii) identify potential biological correlates of alcohol-dependent inpatients based on metabolomics and interpretable machine learning.

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Purpose: To explain the high inter-individual variability (IIV) and the frequency of exceeding the therapeutic reference range and the laboratory alert level of amisulpride, a population pharmacokinetic (PPK) model in Chinese patients with schizophrenia was built based on therapeutic drug monitoring (TDM) data to guide individualized therapy.

Patients And Methods: Plasma concentration data (330 measurements from 121 patients) were analyzed using a nonlinear mixed-effects modeling (NONMEM) approach with first-order conditional estimation with interaction (FOCE I). The concentrations of amisulpride were detected by HPLC-MS/MS.

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