Population Pharmacokinetics of Caspofungin and Dose Simulations in Heart Transplant Recipients.

The effect of heart transplantation (HTx) on the pharmacokinetics (PK) of caspofungin is not well-characterized. The aim of this study was to investigate the population PK of caspofungin in HTx and non-HTx patients and to identify covariates that may affect the PK of caspofungin. Seven successive blood samples were collected before administration and at 1, 2, 6, 10, 16, and 24 h after the administration of caspofungin for at least 3 days. This study recruited 27 HTx recipients and 31 non-HTx patients with 414 plasma concentrations in total. A nonlinear mixed-effects model was used to describe the population PK of caspofungin. The PK of caspofungin was best described by a two-compartment model. The clearance (CL) and volume of the central compartment (Vc) of caspofungin were 0.385 liter/h and 4.27 liters, respectively. The intercompartmental clearance (Q) and the volume of the peripheral compartment (Vp) were 2.85 liters/h and 6.01 liters, respectively. In the final model, we found that albumin (ALB) affected the CL of caspofungin with an adjustment factor of -1.01, and no other covariates were identified. In this study, HTx was not found to affect the PK of caspofungin. Based on the simulations, the dose of caspofungin should be proportionately increased in patients with decreased ALB levels.

Pharmacokinetics and Pharmacodynamics of Sacubitril/Valsartan in Maintenance Hemodialysis Patients with Heart Failure.

BACKGROUND: Heart failure (HF) is one of the main comorbidities in patients receiving maintenance hemodialysis (HD). Sacubitril/valsartan (SAC/VAL) is widely used in HF patients with reduced ejection fraction (HFrEF) or HF mid-range ejection fraction (HFmrEF). However, the pharmacokinetic (PK) and pharmacodynamic properties of SAC/VAL in HD patients with HF remain uncertain. OBJECTIVES: This study aimed to analyze the efficacy and PK properties of SAC/VAL in HD patients with HFrEF or HFmrEF. METHODS: HD patients with HFrEF or HFmrEF were treated with SAC/VAL 50 or 100 mg twice a day (BID) and the concentrations of valsartan and LBQ657 (active metabolite of SAC) were determined by high-performance liquid chromatography-tandem mass spectrometry during HD and on the days between HD sessions (interval days). N-terminal-pro B-type natriuretic peptide and high-sensitivity troponin T were measured, and left ventricular ejection fraction (LVEF) was evaluated by echocardiography. RESULTS: The mean maximum plasma concentrations (Cmax) of LBQ657 and VAL on the interval days were 15.46 ± 6.01 and 2.57 ± 1.23 mg/L, respectively. Compared with previous values in patients with severe renal impairment and healthy volunteers, these levels both remained within the safe concentration ranges during treatment with SAC/VAL 100 mg BID. Moreover, SAC/VAL significantly improved LVEF in HD patients with HFrEF or HFmrEF (p < 0.05). CONCLUSIONS: HD did not remove the SAC metabolite LBQ657 or VAL in patients with HF. However, SAC/VAL 100 mg BID was safe and effective in patients undergoing HD.

Effect of Hemodialysis on Efficacy and Pharmacokinetics of Sofosbuvir Coformulated with Either Daclatasvir or Ledipasvir in Patients with End-Stage Renal Disease.

BACKGROUND/AIMS: Direct-acting antivirals (DAAs) play a key role in the eradication of hepatitis C virus (HCV) infection. However, limited data are available on DAA for treating HCV infection in hemodialysis (HD) patients. This study was to evaluate the pharmacokinetic characteristics and effectiveness of daclatasvir/sofosbuvir (DAC/SOF) and ledipasvir/SOF (LDV/SOF) in HD patients. METHODS: Seven patients were given SOF coadministered with DAC or LDV once daily for 12 weeks. The plasma concentrations of SOF007, DAC, and LDV were determined by high-performance liquid chromatography-electrospray ionization tandem mass spectrometry. RESULTS: A sustained virologic response in week 12 (SVR12) was achieved in 6 (100%) patients, except for 1 patient dying due to severe cerebral hemorrhage not related to antiviral therapy. The extraction ratio of SOF007 was 66.67%, and the estimated HD clearance of SOF007 was 5.65 L/h. CONCLUSION: The combination of SOF with either DAC or LDV is well tolerated and offers high SVR12 in HD patients.

Population pharmacokinetics and safety of eptifibatide in healthy Chinese volunteers and simulations on the dose regimens approved for a Western population.

OBJECTIVE: This study was designed to evaluate the pharmacokinetics (PK) and safety of eptifibatide in healthy Chinese volunteers and provide information for the further study in the Chinese population. METHODS: 30 healthy volunteers (15 male) were enrolled in the study and divided into three dose groups (45 µg x kg⁻¹, 90 µg x kg⁻¹, and 180 µg x kg⁻¹). Plasma and urine samples were drawn after one single-bolus administration and measured by LC-MS/MS. The plasma and urine data were analyzed simultaneously by the population approach using the NONMEM software and evaluated by the visual predicted check (VPC) and bootstraping. The PK profiles of dose regimens approved for a Western population in the Chinese population were simulated. RESULTS: A two-compartment model adequately described the PK profiles of eptifibatide. The clearance (CL) and the distribution volume (V1) of the central compartment were 0.128 L x h⁻¹ x kg⁻¹ and 0.175 L x kg⁻¹, respectively. The clearance (Q) and V2of the peripheral compartment were 0.0988 L x h⁻¹ x kg⁻¹ and 0.147 L x kg⁻¹, respectively. The elimination fraction from plasma to urine (F0) was 17.2%. No covariates were found to have a significant effect. Inter-individual variabilites were all within 33.9%. The VPC plots and bootstrap results indicated good precision and prediction of the model. The simulations of the approved regimens in the Chinese population showed much lower steady-state concentrations than the target concentration obtained from the Western clinical trials. No severe safety events were found in this study. CONCLUSIONS: The PK model of eptifibatide was established and could provide PK information for further studies in the Chinese population.

Population pharmacokinetic/pharmacodynamic model of clozapine for characterizing the relationship between accumulated exposure and PANSS scores in patients with schizophrenia.

BACKGROUND: The aim of this study was to characterize the relationship between accumulated exposure of clozapine and changes in Positive and Negative Syndrome Scale (PANSS) score in Chinese patients with schizophrenia by pharmacokinetic/pharmacodynamic (PK/PD) modeling. METHODS: Sparse clozapine PK data and PANSS scores were collected from 2 clinical studies of Chinese inpatients with schizophrenia. Two other rich PK data sets were included for more accurate assessment of clozapine PK characteristics. The relationship between clozapine-accumulated exposure and PANSS score was investigated using linear, log-linear, E(max), and sigmoid models, and each model was evaluated using visual predictive condition and normalized prediction distribution error methods. Simulations based on the final PK/PD model were preformed to investigate the effect of clozapine on PANSS scores under different dose regimens. RESULTS: A total of 1391 blood clozapine concentrations from 198 subjects (180 patients and 18 healthy volunteers) and 576 PANSS scores from 137 patients were included for PK and PK/PD analysis. A first-order 2-compartment PK model with covariates gender and smoking status influencing systemic clearance adequately described the PK profile of clozapine. The decrease in total PANSS score during treatment was best characterized using cumulated clozapine area under the curve (AUC) data in the E(max) model. The maximum decrease in PANSS during clozapine treatment (Emax) was 55.4%, and the cumulated AUC(50) (cAUC(50)) required to attain half of E(max) was 296 mg·L(-1)·h(-1)·d(-1). The simulations demonstrated that the accelerated dose titration and constant dose regimens achieved a similar maximum drug response but with a slower relief of symptoms in dose titration regimen. CONCLUSIONS: The PK/PD model can describe the clinical response as measured by decreasing PANSS score during treatment and may be useful for optimizing the dose regimen for individual patients.

Sex differences in the association between the muscle quality index and the incidence of depression: A cross-sectional study.

BACKGROUND: Depression presents significant challenges to mental health care. Although physical activity is highly beneficial to mental and physical health, relatively few studies have conducted on the relationship between them. AIM: To investigate the association between muscle quality index (MQI) and incidence of depression. METHODS: The data used in this cross-sectional study were obtained from the 2011-2014 National Health and Nutritional Examination Survey, which included information on MQI, depression, and confounding factors. Multivariable logistic regression models were employed, while taking into account the complex multi-stage sampling design. A restricted cubic spline model was utilized to investigate the non-linear relationship between the MQI and depression. Additionally, subgroup analyses were performed to identify influential factors. RESULTS: The prevalence of depression in this population was 8.44%. With the adjusted model, the MQI was associated with depression in females (odds ratio = 0.68, 95% confidence interval: 0.49-0.95) but not in males (odds ratio = 1.08, 95% confidence interval: 0.77-1.52). Restricted cubic spline adjustment of all covariates showed a significant negative non-linear relationship between depression and the MQI in females. The observed trend indicated an 80% decrease in the risk of depression for each unit increase in MQI, until a value of 2.2. Subsequently, when the MQI exceeded 2.2, the prevalence of depression increased by 20% for every unit increase in the MQI. Subgroup analyses further confirmed that the MQI was negatively associated with depression. CONCLUSION: The MQI was inversely correlated with depression in females but not males, suggesting that females with a higher MQI might decrease the risk of depression.

Preclinical pharmacokinetic/pharmacodynamic models to predict schedule-dependent interaction between erlotinib and gemcitabine.

PURPOSE: To investigate the pharmacological effects of different erlotinib (ER) and gemcitabine (GM) combination schedules by in vitro and in vivo experiments and PK/PD models in non-small cell lung cancer cells. METHODS: H1299 cells were exposed to different ER combined with GM schedules. Cell growth inhibition was analyzed to evaluate these schedules. A preclinical in vivo study was then conducted to compare tumor suppression effects of different schedules in H1299 xenografts. PK/PD models were developed to quantify the anti-tumor interaction of ER and GM. RESULTS: Synergism was observed when ER preceded GM, but other sequences showed antagonism. The optimal in vitro schedule, or interval schedule, was applied to the animal study, which showed greater anti-tumor effect than simultaneous group. PK/PD models implied that interaction of the two drugs was additive in simultaneous treatment but synergistic in interval schedule. The simulation results showed that interval schedule can delay tumor growth for a longer time, and demonstrated more evident anti-tumor effect compared with simultaneous group if the treatment duration was longer. CONCLUSIONS: Interval schedule of the two drugs can achieve synergistic anti-tumor effect, and is superior to simultaneous treatment.

Population pharmacokinetics of blonanserin in Chinese healthy volunteers and the effect of the food intake.

OBJECTIVE: The aim of the study was to better understand blonanserin population pharmacokinetic (PK) characteristics in Chinese healthy subjects. METHODS: Data from two studies with 50 subjects were analyzed to investigate the population PK characteristics of blonanserin at single dose (4, 8, and 12 mg) under fasting, multidose (4 mg bid or 8 mg qd for 7 days) and under food intake condition (single dose, 8 mg). Blonanserin plasma concentrations were detected using the high performance liquid chromatography tandem mass spectrometry (LC/MS/MS). A nonlinear mixed-effects model was developed to describe the blonanserin concentration-time profiles. RESULTS: A two compartment model with first-order absorption was built to describe the time-course of blonanserin. The population-predicted system apparent clearance (CL/F), volume of apparent distribution in center (V(1)/F), and the first-order absorption rate constant (Ka) of blonanserin under fasting was 1230 L/h, 9500 L, and 3.02 h(-1), respectively. Food intake decreased Ka of blonanserin to 0.78 h(-1). The relative bioavailability between fasting and food intake estimated by the final model was 55%. No clinically significant safety issues were identified. CONCLUSION: This is the first study assessing the PK profile of blonanserin with population PKs method. The results can be used for simulation in further clinical trial and optimize individual dosage regimens using a Bayesian methodology in patients.

Exploring the causal effects of the gut microbiome on serum lipid levels: A two-sample Mendelian randomization analysis.

Background: The gut microbiome was reported to be associated with dyslipidemia in previous observational studies. However, whether the composition of the gut microbiome has a causal effect on serum lipid levels remains unclear. Objective: A two-sample Mendelian randomization (MR) analysis was conducted to investigate the potential causal relationships between gut microbial taxa and serum lipid levels, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and log-transformed triglyceride (TG) levels. Materials and methods: Summary statistics of genome-wide association studies (GWASs) for the gut microbiome and four blood lipid traits were obtained from public datasets. Five recognized MR methods were applied to assess the causal estimates, among which, the inverse-variance weighted (IVW) regression was used as the primary MR method. A series of sensitivity analyses were performed to test the robustness of the causal estimates. Results: The combined results from the five MR methods and sensitivity analysis showed 59 suggestive causal associations and four significant causal associations. In particular, genus Terrisporobacter was associated with higher LDL-C (P IVW = 3.01 × 10-6) and TC levels (P IVW = 2.11 × 10-4), phylum Actinobacteria was correlated with higher LDL-C level (P IVW = 4.10 × 10-4), and genus Oscillospira was associated with lower TG level (P IVW = 2.19 × 10-6). Conclusion: This research may provide novel insights into the causal relationships of the gut microbiome on serum lipid levels and new therapeutic or prevention strategies for dyslipidemia.

The Determination of Polymyxin B in Critically Ill Patients by the HPLC-MS/MS Method.

Polymyxin B (PB) is a dose-dependent drug used to treat multidrug-resistantgram-negative bacteria, for which a suitable method is needed to determine clinical samples. A simple, economical, and efficient high-performance liquid chromatography-mass spectrometry (HPLC-MS/MS) method was developed and validated for polymyxin B1 (PB1), polymyxin B1-Ile (PB1-I), polymyxin B2 (PB2), and polymyxin B3 (PB3) in human plasma. Chromatographic column was Waters BEH C18 column (2.1 × 50 mm, 1.7 µm). Phase A was water with 0.2% formic acid (FA), and phase B was acetonitrile containing 0.2% FA. The elution method is gradient elutio. The total analysis time was 5 min. The pretreatment method involved protein precipitation using acetonitrile containing 0.2% trifluoroacetic acid and 0.1% FA as the precipitant. The recovery rate was 92-99%. The total quantity of PB1 and PB1-I was measured in the linear range of 100-8000 ng/mL. Simultaneously, the total amounts of PB2 and PB3 were measured in the linear range of 11.9-948.5 ng/mL. This validated method was successfully applied to the pharmacokinetics of PB in critically ill patients.

Optimal Teicoplanin Dosage Regimens in Critically Ill Patients: Population Pharmacokinetics and Dosing Simulations Based on Renal Function and Infection Type.

Purpose: To develop a population pharmacokinetic model describing teicoplanin concentrations in patients hospitalized in intensive care unit (ICU) and to perform Monte Carlo simulations to provide detailed dosing regimens of teicoplanin. Methods: This single-center, prospective, observational study was conducted on 151 patients in ICU with 347 plasma samples. The population pharmacokinetics model was established and various covariates were evaluated. The probability of target attainment (PTA) of various proposal dosing regimens was calculated by Monte Carlo simulations. Results: The two-compartment model adequately described teicoplanin concentration-time data. The estimated glomerular filtration rate (eGFR) associated with systemic clearance (CL) was the only covariate included in the final model. The estimate of CL was 0.838 L/h, with the eGFR adjustment factor of 0.00823. The volume of the central compartment (Vc), inter-compartmental clearance (Q) and volumes of the peripheral compartments (Vp) were 14.4 L, 3.08 L/h and 51.6 L, respectively. The simulations revealed that the standard dosage regimen was only sufficient for the patients with severe renal dysfunction (eGFR ≤ 30 mL/min/1.73 m2) to attain target trough concentration (Cmin, PTA 52.8%). When eGFR > 30 mL/min/1.73 m2, increasing dose and the administration times of loading doses were the preferred options to achieve target Cmin based on the renal function and types of infection. Conclusion: The most commonly used standard dosage regimen was insufficient for all ICU patients. Our study provided detailed dosing regimens of teicoplanin stratified by eGFR and types of infection for ICU patients.

Placebo effect model in asthma clinical studies: longitudinal meta-analysis of forced expiratory volume in 1 second.

OBJECTIVE: Our objective was to describe the time course of the placebo effect in asthma and quantitatively investigate the affective factors of the placebo effect for the placebo response simulation during the asthma clinical study design. METHODS: We conducted a systemic search of public data sources for the study-level forced expiratory volume in 1 second (FEV(1)) to build the placebo effect model for studies by oral or inhaled administrations simultaneously. The administration routes, types of inhalation device, mean patient age, mean male proportion, baseline FEV(1), disease severity, year of publication, inhaled corticosteroid status during the treatment, and dropout rate were tested as covariates. RESULTS: There are 34 literature sources containing 178 mean values for FEV(1) presenting the individual observations from about 3,703 patients. The exponential models adequately described the time course of placebo effect with the typical value of the maximum placebo effect (P(max)) of 0.060 L. Dropout rate incorporated in the residual error model and the disease severity (mild to moderate and moderate to severe) at baseline were covariates that remained in the final model. CONCLUSIONS: The placebo effect is adequately described by an exponential model over time. By incorporating the dropout rate in the residual error model, the estimation precision was improved. The model could predict the placebo response profile in mild to severe asthmatic patients for the asthma clinical study design and could also be a structure model of the placebo effect for the pure drug effect evaluation in the asthma clinical trials.

Population pharmacokinetics of clozapine and its primary metabolite norclozapine in Chinese patients with schizophrenia.

AIM: To develop a combined population pharmacokinetic model (PPK) to assess the magnitude and variability of exposure to both clozapine and its primary metabolite norclozapine in Chinese patients with refractory schizophrenia via sparse sampling with a focus on the effects of covariates on the pharmacokinetic parameters. METHODS: Relevant patient concentration data (eg, demographic data, medication history, dosage regimen, time of last dose, sampling time, concentrations of clozapine and norclozapine, etc) were collected using a standardized data collection form. The demographic characteristics of the patients, including sex, age, weight, body surface area, smoking status, and information on concomitant medications as well as biochemical and hematological test results were recorded. Persons who had smoked 5 or more cigarettes per day within the last week were defined as smokers. The concentrations of clozapine and norclozapine were measured using a HPLC system equipped with a UV detector. PPK analysis was performed using NONMEM. Age, weight, sex, and smoking status were evaluated as main covariates. The model was internally validated using normalized prediction distribution errors. RESULTS: A total of 809 clozapine concentration data sets and 808 norclozapine concentration data sets from 162 inpatients (74 males, 88 females) at multiple mental health sites in China were included. The one-compartment pharmacokinetic model with mixture error could best describe the concentration-time profiles of clozapine and norclozapine. The population-predicted clearance of clozapine and norclozapine in female nonsmokers were 21.9 and 32.7 L/h, respectively. The population-predicted volumes of distribution for clozapine and norclozapine were 526 and 624 L, respectively. Smoking was significantly associated with increases in the clearance (clozapine by 45%; norclozapine by 54.3%). The clearance was significantly greater in males than in females (clozapine by 20.8%; norclozapine by 24.2%). The clearance of clozapine and norclozapine did not differ significantly between Chinese patients and American patients. CONCLUSION: Smoking and male were significantly associated with a lower exposure to clozapine and norclozapine due to higher clearance. This model can be used in individualized drug dosing and therapeutic drug monitoring.

Population Pharmacokinetics Analysis and Dosing Simulations Of Meropenem in Critically Ill Patients with Pulmonary Infection.

PURPOSE: This study aimed to develop a population pharmacokinetic (PPK) model for meropenem to optimize dosing regimens for critically ill patients with pulmonary infection. PATIENTS AND METHODS: This prospective PPK study of meropenem was conducted on a pooled dataset of 236 blood samples obtained from 48 patients with pulmonary infection in the intensive care unit. Meropenem plasma concentrations were measured by a validated high-performance liquid chromatography-tandem mass spectrometry method, and the data were analyzed using NONMEM. The effect of covariates on meropenem pharmacokinetics was investigated. The probability of target attainment (PTA) to achieve the target of 100% fT>MIC at the proposed dosage regimens were investigated by Monte Carlo simulations. RESULTS: A two-compartment model adequately described the data with estimated glomerular filtration rate (eGFR) as a covariate significantly associated with the clearance (CL) from the central compartment. The typical value of CL was 7.48 L/h, with an eGFR adjustment factor of 0.0103 mL•1.73 m2/min, and the typical values of volume of the central compartment (V1), peripheral compartmental clearance (Q), and volume of the peripheral compartment (V2) were 15.9 L, 15.8 L/h, and 14.8 L, respectively. The goodness-of-fit plots, normalized prediction distribution error, and visual predictive checks showed good fitting and predictability of the final PPK model. When eGFR was >90 mL/min/1.73 m2, and there was a short duration of infusion (<60min), it was difficult for the probability target attainment (PTA) to reach >90% for MIC ≥ 2. Continuous infusion and frequent administration were necessary to achieve the target of 100% fT>MIC for critically ill patients with pulmonary infection. CONCLUSION: To achieve the optimal PTA, meropenem must be administered by frequent administration or continuously by an intravenous infusion. Our findings provide important information to optimize the meropenem regime in critically ill patients with pulmonary infection depending on eGFR values.

Population pharmacokinetics of posaconazole in Chinese pediatric patients with acute leukaemia: Effect of food on bioavailability and dose optimization.

This study aimed to investigate the effect of food on the pharmacokinetics of posaconazole suspension in pediatric patients with acute leukaemia and to recommend optimal dosing strategies. This single-site, prospective, open-label, observational study was conducted in 42 patients and included 186 plasma concentrations of posaconazole. Sparse data were analyzed using population pharmacokinetic modeling. Monte Carlo simulations were conducted to predict the morning trough concentrations at steady-state with the proposed dose of 2-7 mg/kg three times daily (tid) or four times daily (qid) for bodyweights of 10-36 kg. The target concentrations were 700 ng/mL for prophylaxis and 1000 ng/mL for treatment. Dosage regimens with percentage of target attainment (PTA) ≥70% were recommended. A one-compartment model with allometric scaling adequately described the pharmacokinetic profile. The apparent clearance was 9.05 L/h (95% confidence interval [CI] 7.14-11.09) and the apparent volume of distribution was 283 L (95% CI 168-491) for a typical individual of 17.5 kg. The relative bioavailability with high-fat diet was as high as 1.95-fold compared with regular food. Following the intake of regular meals, 4 mg/kg qid was adequate with a PTA ≥ 71.8% for prophylaxis. A dosage of 6 mg/kg qid under a regular diet reached a PTA ≥ 73.4% for treatment. The recommended dosage of posaconazole for prophylaxis and treatment could be predicted by the pharmacokinetic model based on bodyweight and diet type in pediatric patients.

Joint population pharmacokinetic modeling of venlafaxine and O-desmethyl venlafaxine in healthy volunteers and patients to evaluate the impact of morbidity and concomitant medication.

Introduction: Venlafaxine (VEN) is a widely used dual selective serotonin/noradrenaline reuptake inhibitor indicated for depression and anxiety. It undergoes first-pass metabolism to its active metabolite, O-desmethyl venlafaxine (ODV). The aim of the present study was to develop a joint population pharmacokinetic (PPK) model to characterize their pharmacokinetic characters simultaneously. Methods: Plasma concentrations with demographic and clinical data were derived from a bioequivalence study in 24 healthy subjects and a naturalistic TDM setting containing 127 psychiatric patients. A parent-metabolite PPK modeling was performed with NONMEM software using a non-linear mixed effect modeling approach. Goodness of fit plots and normalized prediction distribution error method were used for model validation. Results and conclusion: Concentrations of VEN and ODV were well described with a one-compartment model incorporating first-pass metabolism. The first-pass metabolism was modeled as a first-order conversion. The morbid state and concomitant amisulpride were identified as two significant covariates affecting the clearance of VEN and ODV, which may account for some of the variations in exposure. This model may contribute to the precision medication in clinical practice and may inspire other drugs with pre-system metabolism.

Perfluorooctane sulfonate induces suppression of testosterone biosynthesis via Sertoli cell-derived exosomal/miR-9-3p downregulating StAR expression in Leydig cells.

Perfluorooctane sulfonate (PFOS) is associated with male reproductive disorder, but the related mechanisms are still unclear. In this study, we used in vivo and in vitro models to explore the role of Sertoli cell-derived exosomes (SC-Exo)/miR-9-3p/StAR signaling pathway on PFOS-induced suppression of testosterone biosynthesis. Forty male ICR mice were orally administrated PFOS (0.5-10 mg/kg/bw) for 4 weeks. Bodyweight, organ index, sperm count, reproductive hormones were evaluated. Primary Sertoli cells and Leydig cells were used to delineate the molecular mechanisms that mediate the effects of PFOS on testosterone biosynthesis. Our results demonstrated that PFOS dose-dependently induced a decrease in sperm count, low levels of testosterone, and damage in testicular interstitium morphology. In vitro models, PFOS significantly increased miR-9-3p levels in Sertoli cells and SC-Exo, accompanied by a decrease in testosterone secretion and StAR expression in Leydig cells when Leydig cells were exposed to SC-Exo. Meanwhile, inhibition of SC-Exo or miR-9-3p by their inhibitors significantly rescued PFOS-induced decreases in testosterone secretion and the mRNA and protein expression of the StAR gene in Leydig cells. In summary, the present study highlights the role of the SC-Exo/miR-9-3p/StAR signaling pathway in PFOS-induced suppression of testosterone biosynthesis, advancing our understanding of molecular mechanisms for PFOS-induced male reproductive disorders.

Pharmacokinetics of immediate and sustained-release formulations of paroxetine: Population pharmacokinetic approach to guide paroxetine personalized therapy in chinese psychotic patients.

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. The study included 184 inpatients with psychosis (103 females and 81 males), with a total of 372 serum concentrations of paroxetine for PPK analyses. The total daily dosage ranged from 20 to 75 mg. One compartment model could fit the PKs characterize of paroxetine. Covariate analysis revealed that dose, formulation, and sex had a significant effect on the PK parameters of paroxetine; however, there was no evident genetic influence of CYP2D6 enzymes on paroxetine concentrations in Chinese patients. The study determined that the population's apparent distribution volume (V/F) and apparent clearance (CL/F), respectively, were 8850 and 21.2 L/h. The CL/F decreased 1-2-fold for each 10 mg dose increase, whereas the different formulations caused a decrease in V/F of 66.6%. Sex was found to affect bioavailability (F), which decreased F by 47.5%. Females had higher F values than males. This PPK model described data from patients with psychosis who received paroxetine immediate-release tablets (IR-T) and/or sustained-release tablets (SR-T). Paroxetine trough concentrations and relative bioavailability were different between formulations and sex. The altered serum concentrations of paroxetine resulting from individual variants and additive effects need to be considered, to optimize the dosage regimen for individual patients.

[Comparison study of model evaluation methods: normalized prediction distribution errors vs. visual predictive check].

The objective of this study is to compare the normalized prediction distribution errors (NPDE) and the visual predictive check (VPC) on model evaluation under different study designs. In this study, simulation method was utilized to investigate the capability of NPDE and VPC to evaluate the models. Data from the false models were generated by biased parameter typical value or inaccurate parameter inter-individual variability after single or multiple doses with the same sampling time or multiple doses with varied sampling time, respectively. The results showed that there was no clear statistic test for VPC and it was difficult to make sense of VPC under the multiple doses with varied sampling time. However, there were corresponding statistic tests for NPDE and the factor of study design did not affect NPDE significantly. It suggested that the clinical data and model which VPC was not fit for could be evaluated by NPDE.

Combining Metabolomics and Interpretable Machine Learning to Reveal Plasma Metabolic Profiling and Biological Correlates of Alcohol-Dependent Inpatients: What About Tryptophan Metabolism Regulation?

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. Plasma samples were obtained from healthy (n = 42) and AD-diagnosed individuals (n = 43). The plasma metabolic differences between them were investigated using liquid chromatography-tandem mass spectrometry (AB SCIEX® QTRAP 4500 system) in different electrospray ionization modes with scheduled multiple reaction monitoring scans. In total, 59 and 52 compounds were semi-quantitatively measured in positive and negative ionization modes, respectively. In addition, 39 metabolites were identified as important variables to contribute to the classifications using an orthogonal partial least squares-discriminant analysis (OPLS-DA) (VIP > 1) and also significantly different between healthy and AD-diagnosed individuals using univariate analysis (p-value < 0.05 and false discovery rate < 0.05). Among the identified metabolites, indole-3-carboxylic acid, quinolinic acid, hydroxy-tryptophan, and serotonin were involved in the tryptophan metabolism along the indole, kynurenine, and serotonin pathways. Metabolic pathway analysis revealed significant changes or imbalances in alanine, aspartate, glutamate metabolism, which was possibly the main altered pathway related to AD. Tryptophan metabolism interactively influenced other metabolic pathways, such as nicotinate and nicotinamide metabolism. Furthermore, among the OPLS-DA-identified metabolites, normetanephrine and ascorbic acid were demonstrated as suitable biological correlates of AD inpatients from our model using an interpretable, supervised decision tree classifier algorithm. These findings indicate that the discriminatory metabolic profiles between healthy and AD-diagnosed individuals may benefit researchers in illustrating the underlying molecular mechanisms of AD. This study also highlights the approach of combining metabolomics and interpretable machine learning as a valuable tool to uncover potential biological correlates. Future studies should focus on the global analysis of the possible roles of these differential metabolites and disordered metabolic pathways in the pathophysiology of AD.