ImageCAS: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images.

Cardiovascular disease (CVD) accounts for about half of non-communicable diseases. Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed tomography angiography (CTA) is one of the widely used noninvasive imaging modalities in coronary artery diagnosis due to its superior image resolution. Clinically, segmentation of coronary arteries is essential for the diagnosis and quantification of coronary artery disease. Recently, a variety of works have been proposed to address this problem. However, on one hand, most works rely on in-house datasets, and only a few works published their datasets to the public which only contain tens of images. On the other hand, their source code have not been published, and most follow-up works have not made comparison with existing works, which makes it difficult to judge the effectiveness of the methods and hinders the further exploration of this challenging yet critical problem in the community. In this paper, we propose a large-scale dataset for coronary artery segmentation on CTA images. In addition, we have implemented a benchmark in which we have tried our best to implement several typical existing methods. Furthermore, we propose a strong baseline method which combines multi-scale patch fusion and two-stage processing to extract the details of vessels. Comprehensive experiments show that the proposed method achieves better performance than existing works on the proposed large-scale dataset. The benchmark and the dataset are published at https://github.com/XiaoweiXu/ImageCAS-A-Large-Scale-Dataset-and-Benchmark-for-Coronary-Artery-Segmentation-based-on-CT.

The Association Between Child Maltreatment and Loneliness Across the Lifespan: A Systematic Review and Multilevel Meta-Analysis.

While there is evidence that child maltreatment is positively associated with loneliness, the strength of this association is not yet clear. It is also unclear whether the magnitude and statistical significance of this association varies across groups of individuals. Therefore, this meta-analysis examines whether there are differences in loneliness between individuals with and without maltreatment histories, and which factors may influence the association between child maltreatment and loneliness. A three-level meta-analysis was conducted on 52 studies reporting 116 effect sizes (N = 1,705,493; Mage = 30.93; 49.6% females). Results showed a medium overall effect (g = 0.45, p < .001, 95% CI [0.36, 0.53]), indicating that individuals with maltreatment histories, on average, feel lonelier than individuals without maltreatment histories. Moderator analyses showed that effect sizes were larger for emotional abuse and emotional neglect as compared to other types of child maltreatment and decreased when participants were older at the time of loneliness assessment. These findings suggest that individuals with maltreatment histories, especially those who have been emotionally abused and/or emotionally neglected, are vulnerable to experiencing loneliness across the lifespan. The results also suggest that feelings of loneliness warrant attention in prevention and intervention programs for individuals with maltreatment histories.

Perceived Social Support from Different Sources and Adolescent Life Satisfaction Across 42 Countries/Regions: The Moderating Role of National-Level Generalized Trust.

Although previous research established a positive association between perceived social support and adolescent life satisfaction, little is known about the relative importance of different sources of support for adolescent life satisfaction and cross-country variations in this respect. Using large-scale representative samples from the 2017/18 Health Behaviour in School-aged Children (HBSC) study, this study examined to what extent the association between social support and life satisfaction in early adolescence varied across different social sources and countries. Also, it examined whether cross-country variations are explained by national-level generalized trust, a sociocultural factor that shapes adolescent socialization. National-level data were linked to data from 183,918 early adolescents (Mage = 13.56, SD = 1.63, 52% girls) from 42 European and North American countries/regions obtained from HBSC. Multilevel regression analyses yielded a positive association between support from different sources and life satisfaction. The strongest associations were found for support from families, followed by teachers and classmates, and weakest for support from friends. Associations varied across different countries/regions. National-level trust amplified the association between perceived classmate support and adolescent life satisfaction. The revealed cross-country differences open avenues for future cross-cultural research on explanations for cross-cultural differences in the association between social support from different sources and life satisfaction in early adolescence.

Population pharmacokinetics of zonisamide after oral administration in healthy Chinese volunteers.

To develop a population-based pharmacokinetic model for the oral antiepileptic drug zonisamide using a cohort of healthy (nonepileptic) subjects and evaluate the effect of individual factors on the pharmacokinetics of zonisamide. 30 young adults (21-39 years) in good health were randomly assigned to 3 equal groups (1:1 sex ratio) for single-dose administration of zonisamide at 200 mg, 300 mg, or 400 mg. An additional 9 subjects (22-24 years) were administered once daily zonisamide at 300 mg for 14 days, and comprised the multiple dosing group. Venous blood samples were collected for analysis prior to (baseline, 0 hours) and after (1-300 hours) drug administration, providing 607 total samples used to build the pharmacokinetic model. The population pharmacokinetic analysis was performed by ICON's nonlinear mixed-effect modeling (NONMEM) software. Validation of the final model was carried out by nonparametric bootstrapping and visual predictive check. The zonisamide pharmacokinetics was best described by a two-compartment model with first-order elimination. In the final model, the estimated value of clearance (CL) was 23.25 L/h, the volume of distribution of the central compartment (Vc) was 34.50 L, the intercompartmental clearance (Q) was 20.22 L/h, and the Ka was 0.026 h(-1). The peripheral volume of distribution (Vp) was 1,429 L for single dose and 1,003 L for multiple doses. Body weight was the significant covariate affecting CL, Vc, Vp, and Q. Otherwise, female subjects had a lower Q than male subjects. The pharmacokinetics of zonisamide after oral administration could be described using a linear first-order elimination two-compartment model, which may provide a reference for clinical use of zonisamide in Chinese adults.

Population pharmacokinetic study of cyclosporine in the hematopoietic stem cell transplant recipients.

OBJECTIVES: The aim of this study is to investigate the population pharmacokinetics (PopPK) of cyclosporine (CsA) in the Chinese hematopoietic stem cell transplantation (HSCT) recipients for promoting the individualization of CsA administration. METHODS: A total of 887 retrospective drug monitoring data points were collected from 58 HSCT recipients. Whole blood samples were collected at predose (C0) and 2 hours (C2) post dose. The administration of CsA was intermittent intravenous infusion, continuous intravenous infusion and oral. Population modeling was performed using the NONMEM (nonlinear mixedeffect modeling) program. A one compartment pharmacokinetic model was used to fit the data. RESULTS: Body surface area (BSA), administration route and postoperative days were identified as significant covariates for clearance (CL) according to the final model: CL = 31.0 × (BSA/1.59)0.761 × (ROUT) × (POD), where ROUT was 1.91 if the administration route was intravenous infusion, otherwise it is equal to 1. The POD was 0.818, 0.753, 0.539, and 0.509 for posttransplant Days 0 - 10, 11 - 20, 21 - 30 and more than 30 days, respectively. Administration route was a significant covariate for volume (V) according to the final model: V = 192 × (ROUT), where ROUT was 4.10, 3.63 and 1 when the administration route was continuous intravenous infusion, intermittent intravenous infusion and oral. The other covariates were not identified as a significant effect on CsA pharmacokinetic parameters. CONCLUSION: Body surface area, administration route and postoperative days should be considered in individual pharmacotherapy of cyclosporine for HSCT patient to achieve the desired therapeutic target.

Response surface analysis of sevoflurane-remifentanil interactions on consciousness during anesthesia.

BACKGROUND: Recently, the combination of sevoflurane and remifentanil has been widely used in general anesthesia. In this study, we investigated the sevoflurane-remifentanil pharmacodynamic interactions at clinical concentrations using the observer's assessment of alertness/sedation (OAA/S) and the bispectral index (BIS) by response surface analysis. METHODS: Totally 65 American Society of Anesthesiologists (ASA) I patients age 20 to 50 years old were included in this study. Patients were randomly assigned to be anesthetized with different target end-tidal sevoflurane concentrations that ranged from 0.2% to 3.4% in increments of 0.2%. The end-tidal sevoflurane concentration was maintained constant throughout the study. Remifentanil was infused with a target controlled infusion (TCI) system at increasing step-wise concentrations from 1 ng/ml to 10 ng/ml. The values of OAA/S and BIS at different sevoflurane-remifentanil concentration combinations were measured. The pharmacodynamic interactions between sevoflurane and remifentanil were analyzed by a response surface method. The three-dimensional response surfaces were constructed with Minitab Software. Model parameters were estimated with NONMEM program. RESULTS: Sevoflurane and remifentanil acted synergistically on OAA/S. Sevoflurane alone could produce OAA/S ≤ 1 at a minimal alveolar concentration (MAC) of 0.93%. When used in combination with remifentanil at 1, 3, 6, and 10 ng/ml, the corresponding sevoflurane MACs were reduced to 0.79%, 0.58%, 0.48%, and 0.38%, with reductions of 17.2%, 37.6%, 48.4%, and 62.0% from baseline, respectively. In patients administered remifentanil alone, the OAA/S score was ≥ 3 even when the remifentanil concentration reached 10 ng/ml. BIS was closely associated with the sevoflurane concentration and the remifentanil concentration did not noticeably influence the relationship between the sevoflurane concentration and BIS. A sevoflurane concentration of (1.04 ± 0.19)% to (1.81 ± 0.21)% could maintain a BIS between 60 and 40. CONCLUSIONS: The response surface method can analyze the pharmacodynamic interactions between remifentanil and sevoflurane qualitatively and quantitatively. Within the range of our study (remifentanil ≤ 10 ng/ml, sevoflurane ≤ 3.4%), the two drugs produced synergistic effects on OAA/S but had no interactive effect on BIS. A guideline of BIS between 40 and 60 may cause excessive anesthesia when opioids are used to maintain anesthesia.

A mechanism-based pharmacokinetic/pharmacodynamic model for CYP3A1/2 induction by dexamethasone in rats.

AIM: To develop a pharmacokinetic/pharmacodynamic (PK/PD) model describing the receptor/gene-mediated induction of CYP3A1/2 by dexamethasone (DEX) in rats. METHODS: A group of male Sprague-Dawley rats receiving DEX (100 mg/kg, ip) were sacrificed at various time points up to 60 h post-treatment. Their blood sample and liver were collected. The plasma concentration of DEX was determined with a reverse phase HPLC method. CYP3A1/2 mRNA, protein levels and enzyme activity were measured using RT-PCR, ELISA and the testosterone substrate assay, respectively. Data analyses were performed using a first-order conditional estimate (FOCE) with INTERACTION method in NONMEM version 7.1.2. RESULTS: A two-compartment model with zero-order absorption was applied to describe the pharmacokinetic characteristics of DEX. Systemic clearance, the apparent volume of distribution and the duration of zero-order absorption were calculated to be 172.7 mL·kg(-1)·h(-1), 657.4 mL/kg and 10.47 h, respectively. An indirect response model with a series of transit compartments was developed to describe the induction of CYP3A1/2 via PXR transactivation by DEX. The maximum induction of CYP3A1 and CYP3A2 mRNA levels was achieved, showing nearly 21.29- and 8.67-fold increases relative to the basal levels, respectively. The CYP3A1 and CYP3A2 protein levels were increased by 8.02-fold and 2.49-fold, respectively. The total enzyme activities of CYP3A1/2 were shown to increase by up to 2.79-fold, with a lag time of 40 h from the Tmax of the DEX plasma concentration. The final PK/PD model was able to recapitulate the delayed induction of CYP3A1/2 mRNA, protein and enzyme activity by DEX. CONCLUSION: A mechanism-based PK/PD model was developed to characterize the complex concentration-induction response relationship between DEX and CYP3A1/2 and to resolve the drug- and system-specific PK/PD parameters for the course of induction.

[The therapeutic drug monitoring network server of tacrolimus for Chinese renal transplant patients].

This study is to develop a therapeutic drug monitoring (TDM) network server of tacrolimus for Chinese renal transplant patients, which can facilitate doctor to manage patients' information and provide three levels of predictions. Database management system MySQL was employed to build and manage the database of patients and doctors' information, and hypertext mark-up language (HTML) and Java server pages (JSP) technology were employed to construct network server for database management. Based on the population pharmacokinetic model of tacrolimus for Chinese renal transplant patients, above program languages were used to construct the population prediction and subpopulation prediction modules. Based on Bayesian principle and maximization of the posterior probability function, an objective function was established, and minimized by an optimization algorithm to estimate patient's individual pharmacokinetic parameters. It is proved that the network server has the basic functions for database management and three levels of prediction to aid doctor to optimize the regimen of tacrolimus for Chinese renal transplant patients.

Population pharmacokinetics of rocuronium delivered by target-controlled infusion in adult patients.

BACKGROUND: Target-controlled infusion (TCI) has been recently developed and successfully implemented in clinical practice. The current study was to estimate the population pharmacokinetics of rocuronium TCI in adult patients using nonlinear mixed-effects model (NONMEM), and to investigate the influence of relevant factors in adult patients. METHODS: Fourteen ASA I-II patients undergoing elective laparoscopy operation with general anesthesia were included. After induction, all patients received rocuronium by TCI system. The beginning target plasma concentration (Cpt) was 2.0 µg/ml, then increased Cpt according to the neuromuscular transmission monitoring. The endpoint of Cpt was determined when the T1 scale was blocked by 90% - 95%. TCI rocuronium was stopped 30 minutes before the end of the operation. Arterial blood was drawn before anesthesia at 0, 2, 4, 6, 8, 10, 15, 20, 30, 45, 60, 120, 180, 240 and 360 minutes after the infusion of rocuronium was stopped for the analysis of plasma concentrations of rocuronium by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS). The population pharmacokinetics analysis was performed using NONMEM program. RESULTS: The pharmacokinetics of TCI rocuronium in adult patients was best described by a three-compartment model. Pharmacokinetic parameters were clearance (CL)1 = 0.205 L/min, CL2 = 0.324 L/min, CL3 = 0.0292 L/min, volumes of distribution (V)1 = 4.00 L, V2 = 2.28 L, V3 = 4.26 L, Vdss = 10.54 L. Both age and weight as covariates affected the pharmacokinetic parameters. V1 and CL1 were negatively correlated with patient age. CL1 was positively correlated with weight. CONCLUSIONS: No pharmacokinetic change was noted when rocuronium was administered via TCI. Both age and weight as covariates affected the pharmacokinetic parameters.

[Pharmacodynamic interaction between propofol and remifentanil on the tolerance response to electrical tetanus stimuli].

OBJECTIVE: To describe the pharmacodynamic interaction between propofol and remifentanil in suppressing somatic and hemodynamic responses to electrical tetanus stimuli (ETS) during induction of intravenous anesthesia with response surface method. METHODS: Seventy patients of ASA I or II, aged 18-65 years, scheduled for elective surgery were anesthetized by propofol and remifentanil. Propofol was administered with a target-controlled infusion (TCI) device at a target concentration that remained constant throughout the study, and remifentanil was administered with a TCI device at increasing staircase target concentrations. The somatic and hemodynamic responses to electrical tetanus stimuli were assessed multiple times after allowing for plasma effect site equilibration. The pharmacodynamic interaction between propofol and remifentanil was analyzed by response surface method. The three-dimensional response surfaces were constructed with Minitab Software. Model parameters were estimated with NONMEM. RESULTS: Response surface method characterized the pharmacodynamic interactions between propofol (0-9 mg/L) and remifentanil (0-10 µg/L) qualitatively and quantitatively. The three-dimensional response surfaces showed considerable synergy between propofol and remifentani for blunting somatic and hemodynamic responses to ETS. When the target concentration of remifentani was 1 µg/L, 2 µg/L and 3 µg/L, the C50 of propofol for blunting somatic responses to ETS decreased by 40.1%, 71.5% and 82.1% respectively; and the C50 of propofol for blunting hemodynamic responses to ETS decreased by 45.0%, 72.8% and 83.7% respectively. However, further increases in remifentanil only modestly reduced the C50 of propofol associated with loss of response to ETS. Ceiling effect was seen. CONCLUSION: Response surface method can analyze the pharmacodynamic interactions qualitatively and quantitatively. The response surface models revealed the significant synergy between propofol (≤9 mg/L) and remifentanil (≤10 µg/L) for blunting somatic and hemodynamic responses to electrical tetanus stimuli. The ceiling effects of remifentanil were demonstrated in the reduction of propofol C50 regarding tolerance of responses to ETS.

Population pharmacokinetics of remifentanil in patients undergoing orthotopic liver transplantation.

BACKGROUND: Little is known about the influence of liver transplantation on the pharmacokinetics of most anesthetic drugs. The goal of this study was to study the population pharmacokinetics of remifentanil in the different phases of orthotopic liver transplantation (OLT) and the influence of relevant factors. METHODS: Thirteen adult patients undergoing OLT were enrolled. A single bolus infusion of remifentanil 5 microg/kg was administered during the preanhepatic, anhepatic and neohepatic phases of OLT. Arterial blood samples of 1.5 ml were collected at 0 (baseline), 1, 2, 3, 5, 7, 10, 15, 20, 25, 30, 45, 60 and 90 minutes after drug administration. Remifentanil concentration was assayed by high-performance liquid chromatography/mass spectrometry/mass spectrometry (HPLC/MS/MS). Population pharmacokinetic modeling was performed using nonlinear mixed-effects modeling (NONMEM). RESULTS: The pharmacokinetics of remifentanil in patients undergoing OLT was best described by a two-compartment open model. The pharmacokinetic parameters were not influenced by age, gender, operative phase, blood temperature, rehydration volume, or blood loss volume during sampling. The volume of distribution in the central compartment (V(1)) and the volume of distribution in the peripheral compartment (V(2)) were influenced by body weight. CONCLUSIONS: The population pharmacokinetics of remifentanil in patients undergoing OLT can be well described by a two-compartment open model. The functional status of the liver does not significantly affect the pharmacokinetics of remifentanil, but the body weight is an influential factor of V(1) and V(2).

[Population pharmacokinetics of tacrolimus in Chinese renal transplant patients].

The goal of this study is to investigate the population pharmacokinetics of oral tacrolimus in Chinese renal transplant patients and to identify possible relationship between covariates and population parameters. Details of drug dosage history, sampling time and concentration of 802 data points in 58 patients were collected retrospectively. Before analysis, the 58 patients were randomly allocated to either the model building group (n=41) or the validation group (n=17). Population pharmacokinetic data analysis was performed using the nonlinear mixed-effects model (NONMEM) program on the model building group. The pharmacokinetics of tacrolimus was best described by a one compartment model with first-order absorption and elimination. Typical values of apparent clearance (CL/F), apparent volume of distribution (V/F) were estimated. A number of covariates including demographic index, clinical index and coadministration of other drugs were evaluated statistically for their influence on these parameters. The final population model related clearance with POD (post operative days), HCT (haematocrit), AST (aspartate aminotransferase) and coadministration of nicardipine and diltiazem. Predictive performance of the final model evaluated with the validation group showed insignificant bias between observed and model predicted concentrations. Typical value of CL/F and V/F was 21.7 L x h(-1) and 241 L, inter-patient variability (RSD) in CL/F and V/F was 41.6% and 49.7%, respectively. The residual variability (SD) between observed and model-predicted concentrations was 2.19 microg x L(-1). The population pharmacokinetic model of tacrolimus in Chinese renal transplant patients was established and significant covariates on the tacrolimus model were identified.

[Progress in the study of response surface modeling in investigation of drug-drug interaction in anesthetic drugs].

As a novel and effective approach, response surface model is used in the study of drug-drug interactions. When two drugs are used simultaneously, this model can be applied to estimate the key characters of the response surface, to find the desired response region by optimal drugs combination, to explore the mechanism of drug-drug interactions, and thus to guide sound clinical application and reduce the risk and cost. In this article, the model's basic mathematical and pharmacological concepts are introduced, and its research progresses are reviewed.