Activated microglia promote invasion and barrier dysfunction of brain endothelial cells via regulating the CXCL13/CXCR5 axis.

The blood brain barrier (BBB) is a protective border that prevents noxious substances from gaining access to the central nervous system (CNS). CXCL13 is a chemokine from the CXC chemokine family, which has been shown to destroy the barrier function of umbilical vein endothelial cells with its receptor CXCR5. Here, we aimed to investigate the role of CXCL13/CXCR5 signaling axis in BBB. The invasive ability of bEnd.3 cells was determined by the Transwell invasion assay. The barrier integrity of bEnd.3 cells was assessed by detecting trans-endothelial electrical resistance, the permeability to fluorescein isothiocyanate-dextran, and the expression levels of the tight junction protein E-cadherin. Lipopolysaccharide (LPS)-activated microglia promoted invasion and barrier dysfunction, and upregulated CXCR5 and p-p38 expression levels in cocultured bEnd.3 cells. However, the effects of activated microglia were alleviated by knocking down CXCR5 in cocultured bEnd.3 cells. Furthermore, recombinant CXCL13 promoted invasion and barrier dysfunction, and upregulated the expression levels of p-p38 in bEnd.3 cells; however, its effects were abolished by treating bEnd.3 cells with the p38 inhibitor SB203580. Our data tentatively demonstrated that LPS-activated microglial cells may promote invasion and barrier dysfunction in bEnd.3 cells by regulating the CXCL13/CXCR5 axis and p38 signaling.

Population pharmacokinetics of the anti-PD-1 antibody camrelizumab in patients with multiple tumor types and model-informed dosing strategy.

Camrelizumab, a programmed cell death 1 (PD-1) inhibitor, has been approved for the treatment of patients with relapsed or refractory classical Hodgkin lymphoma, nasopharyngeal cancer and non-small cell lung cancer. The aim of this study was to perform a population pharmacokinetic (PK) analysis of camrelizumab to quantify the impact of patient characteristics and to investigate the appropriateness of a flat dose in the dosing regimen. A total of 3092 camrelizumab concentrations from 133 patients in four clinical trials with advanced melanoma, relapsed or refractory classical Hodgkin lymphoma and other solid tumor types were analyzed using nonlinear mixed effects modeling. The PKs of camrelizumab were properly described using a two-compartment model with parallel linear and nonlinear clearance. Then, covariate model building was conducted using stepwise forward addition and backward elimination. The results showed that baseline albumin had significant effects on linear clearance, while actual body weight affected intercompartmental clearance. However, their impacts were limited, and no dose adjustments were required. The final model was further evaluated by goodness-of-fit plots, bootstrap procedures, and visual predictive checks and showed satisfactory model performance. Moreover, dosing regimens of 200 mg every 2 weeks and 3 mg/kg every 2 weeks provided similar exposure distributions by model-based Monte Carlo simulation. The population analyses demonstrated that patient characteristics have no clinically meaningful impact on the PKs of camrelizumab and present evidence for no advantage of either the flat dose or weight-based dose regimen for most patients with advanced solid tumors.

Population Pharmacokinetics of Pregabalin Extended-Release in Healthy Volunteers and Patients With Postherpetic Neuralgia, Fibromyalgia, and Partial-Onset Seizures.

A population pharmacokinetic (PK) model was developed to characterize the properties of pregabalin extended-release (ER) in healthy volunteers and was subsequently applied to patient data from efficacy/safety studies investigating pregabalin ER for postherpetic neuralgia, fibromyalgia, and partial-onset seizures. The impact of demographic and other covariates on PK was assessed, and various dosing scenarios were simulated to inform pregabalin ER dosing/administration instructions. Phase 1 and 3 models were developed using data from 14 phase 1 studies (12 627 samples from 335 participants receiving pregabalin immediate-release [IR] or ER) and 3 phase 3 studies (2591 samples from 1235 patients receiving pregabalin ER), respectively. Final phase 1 and 3 models adequately characterized the data. Several covariates were statistically significant, but renal function (creatinine clearance) was considered the only clinically relevant covariate. The relationship between creatinine clearance and pregabalin clearance was reasonably consistent between phase 1 and 3 models and with that reported previously with pregabalin IR data alone. Patients with moderate renal impairment who received pregabalin ER 82.5 mg once daily (QD) had similar predicted area under the plasma concentration-time curve and peak plasma concentration values as patients with normal/mild renal impairment who received 165 mg QD. Ranges in predicted PK parameters after switching from pregabalin IR administered in the morning to ER after a meal at 3, 6, or 9 pm were similar. Administration of a missed evening dose at bedtime with food or the next morning with food did not result in clinically important changes in predicted PK parameters.

[Application of panoramic film in predicting orthodontic treatment time for impacted maxillary canine].

PURPOSE: To evaluate the influence of pretreatment radiographic features (angle, distance, and location) on the duration of active orthodontic traction. METHODS: Sixty maxillary unilateral impacted canines were selected to analyze the panoramic features(angle, line spacing, and location) in pre-treatment patients， the results were evaluated using SPSS19.0 software package for multivariate regression analysis. RESULTS: Pretreatment radiographic variables (angle, line spacing, and location) were significantly associated with the duration of orthodontic traction. The sex and site of impaction did not significantly affect the duration of traction. CONCLUSIONS: Impacted canine angle, distance and position can predict the orthodontic traction time.

Pharmacokinetic Characteristics of Tofacitinib in Adult Patients With Moderate to Severe Chronic Plaque Psoriasis.

Tofacitinib is an oral Janus kinase (JAK) inhibitor. This study characterized the pharmacokinetics of tofacitinib in patients with psoriasis and evaluated the impact of patient factors on disposition. Pooled phase 2/3 data (2981 patients: 9735 concentrations, dose range: 2-15 mg twice daily) up to 56 weeks were used for modeling. A one-compartment model parameterized in terms of apparent oral clearance (CL/F), apparent volume of distribution, zero-order absorption (duration, D), with interindividual variability and inter-occasion variability terms, described tofacitinib pharmacokinetics. A full covariate model incorporated effects for age, sex, race, ethnicity, and baseline variables (body weight, Psoriasis Area Severity Index [PASI], C-reactive protein [CRP], creatinine clearance [CrCl]). The parameter estimates (95%CI) for CL/F, Vd/F, and D in a typical individual (white, male, 86 kg, 46 years, CrCl 121 mL/min, PASI 19.8, and CRP 0.267 mg/dL) were 26.7 (25.9, 27.5) L/h, 125 (120.8, 128.3) liters, and 0.69 (0.646, 0.735) hours, respectively. Only CrCl led to clinically relevant changes in exposure. The analysis suggested no dosing modifications for age, body weight, sex, race, ethnicity, baseline PASI, or CRP based on the magnitude of exposure change. Dosing adjustments for renal impairment were derived from a separate phase 1 study.

Aidi injection combined with CHOP chemotherapy regimen in the treatment of malignant lymphoma: A meta-analysis based on randomized controlled trials.

OBJECTIVE: The aim of this study was to evaluate the clinical efficacy of Aidi injection combined with CHOP chemotherapy regimen in the treatment of malignant lymphoma. METHODS: We made an electronic search in the database of Wanfang, CNKI, and PubMed. All the clinical studies related to Aidi injection combined with CHOP chemotherapy regimen in the treatment of malignant lymphoma were screened and reviewed. The combined objective response rate (ORR), life quality improvement, and hematological toxicity were pooled by random- or fixed-effect model according to the heterogeneity across the included study. Moreover, the publication bias was evaluated by Begg's funnel plot and Egger's line regression test. RESULTS: Eight prospective clinical trials with 513 subjects (273 in the Aidi injection plus CHOP group and 240 in the CHOP group) were included in this meta-analysis. The pooled results showed that Aidi injection combined with CHOP chemotherapy regimen can significantly improve the ORR (odds ratio [OR] =1.68, 95% confidence interval [CI]: 1.09-2.60, P < 0.05), improve the life quality (OR = 3.32, 95% CI: 1.97-5.58, P < 0.05), and decrease the risk of developing leukopenia (OR = 0.25, 95% CI: 0.17-0.39, P < 0.05) and thrombocytopenia (OR = 0.34, 95% CI: 0.22-0.53, P < 0.05). CONCLUSION: With the present evidence, Aidi injection combined with CHOP chemotherapy regimen can improve the treatment response and quality of life and decrease the risk of developing severe leukopenia or thrombocytopenia.

A Case of Primary Hepatic Lymphoma and Related Literature Review.

Objective. Primary hepatic lymphoma is a rare disease. And the clinical manifestations of this disease are nonspecific. The objective of this paper is to improve clinicians' understanding of this disease. Methods. We analyzed the clinical characteristics of a case of primary hepatic lymphoma in association with hepatitis B virus infection and reviewed the literature. Conclusion. The clinical manifestations of primary hepatic lymphoma are nonspecific. And it is easily misdiagnosed. Postoperative radiotherapy of patients with early stage was previously speculated to achieve favorable improvement. The application of targeted therapeutic drugs, chemotherapy, or combined local radiotherapy has become the first-line treatment strategy.

Prediction of human clearance based on animal data and molecular properties.

Human clearance is often predicted prior to clinical study from in vivo preclinical data by virtue of interspecies allometric scaling methods. The aims of this study were to determine the important molecular descriptors for the extrapolation of animal data to human clearance and further to build a model to predict human clearance by combination of animal data and the selected molecular descriptors. These important molecular descriptors selected by genetic algorithm (GA) were from five classes: quantum mechanical, shadow indices, E-state keys, molecular properties, and molecular property counts. Although the data set contained many outliers determined by the conventional Mahmood method, the variation of most outliers was reduced significantly by our final support vector machine (SVM) model. The values of cross-validated correlation coefficient and root-mean-squared error (RMSE) for leave-one-out cross-validation (LOOCV) of the final SVM model were 0.783 and 0.305, respectively. Meanwhile, the reliability and consistency of the final model were also validated by an external test set. In conclusion, the SVM model based on the molecular descriptors selected by GA and animal data achieved better prediction performance than the Mahmood method. This approach can be applied as an improved interspecies allometric scaling method in drug research and development.

Transient lower esophageal sphincter relaxation pharmacokinetic-pharmacodynamic modeling: count model and repeated time-to-event model.

Transient lower esophageal sphincter relaxation (TLESR) is the major mechanism for gastroesophageal reflux. Characterizations of candidate compounds for reduction of TLESRs are traditionally done through summary exposure and response measures and would benefit from model-based analyses of exposure-TLESR events relationships. Pharmacokinetic (PK)-pharmacodynamic (PD) modeling approaches treating TLESRs either as count data or repeated time-to-event (RTTE) data were developed and compared in terms of their ability to characterize system and drug characteristics. Vehicle data comprising 294 TLESR events were collected from nine dogs. Compound [(R)-(+)-[2,3-dihydro-5-methyl-3-(4-morpholinylmethyl)pyrrolo[1,2,3-de]-1,4-benzoxazin-6-yl]-1-naphthalenylmethanone mesylate (WIN55212-2)] data containing 66 TLESR events, as well as plasma concentrations, were obtained from four dogs. Each experiment lasted for 45 min and was initiated with a meal. Counts in equispaced 5- and 1-min intervals were modeled based on a Poisson probability distribution model. TLESR events were analyzed with the RTTE model. The PK was connected to the PD with a one-compartment model. Vehicle data were described by a baseline and a surge function; the surge peak was determined to be approximately 9.69 min by all approaches, and its width in time at half-maximal intensity was 5 min (1-min count and RTTE) or 10 min (5-min count). TLESR inhibition by WIN55212-2 was described by an I(max) model, with an IC(50) of on average 2.39 nmol · l(-1). Modeling approaches using count or RTTE data linked to a dynamic PK-PD representation of exposure are superior to using summary PK and PD measures and are associated with a higher power for detecting a statistically significant drug effect.

Comparison of the agonist-antagonist interaction model and the pool model for the effect of remoxipride on prolactin.

AIMS: The tolerance to the prolactin response following administration of antipsychotic drugs has been modelled as a depletion of a prolactin pool (pool model) and a model where the tolerance is explained by a feedback loop including the dopamine interaction of prolactin release (agonist-antagonist interaction model, (AAI model)). The AAI model was superior to the pool model when analyzing data from clinical trials of risperidone and paliperidone. Here we evaluated the two models using the remoxipride data, designed to challenge the short-term prolactin response, from which the original pool model was built. METHODS: The remoxipride data were collected from a study where eight healthy male subjects received two remoxipride infusions on five occasions. The intervals between the first and second dose on each occasion were 2, 8, 12, 24 and 48 h, respectively. The pool and AAI models were fitted using NONMEM. RESULTS: According to the objective function values the pool model with a circadian rhythm function fitted the data slightly better, while the AAI model was better in describing the circadian rhythm of prolactin. Visual predictive checks revealed that the models predicted the prolactin profiles equally well. CONCLUSIONS: According to the analysis performed here, a previous analysis of several clinical studies and literature reports on prolactin concentrations, it appears that the dopamine feedback mechanism included in the AAI model is better than the storage depletion mechanism in the pool model to estimate the bio-rhythm of prolactin time-course and the tolerance development across different populations, drugs, treatment schedules and time.

Identifying P-glycoprotein substrates using a support vector machine optimized by a particle swarm.

P-Glycoprotein (P-gp) contributes to extruding a structurally, chemically, and pharmacologically diverse range of substrates out of cells. This function may result in the failure of chemotherapy in cancer and influence pharmacokinetic properties of many drugs. Although a great deal of research has been devoted to the investigation of P-gp and its substrate specificity, still we do not have a clear understanding of the resolution of the three-dimensional structure of P-gp and its working role as a drug efflux pump at a molecular level. Hence to identify whether a compound is a P-gp substrate or not, computational methods are promising both in cancer treatment and the drug discovery processes. We have established more effective models for prediction of P-gp substrates with an average accuracy of >90% using a Particle Swarm (PS) algorithm and a Support Vector Machine (SVM) approach. The applied models yielded higher accuracies and contained fewer variables in comparison with previous studies. An analysis of P-gp substrate specificity based on the data set is also presented by a PS and a SVM. The aim of this study is 3-fold: (i) presentation of a modified PS algorithm that is applicable for selection of molecular descriptors in quantitative structure-activity relationship (QSAR) model construction, (ii) application of this modified PS algorithm as a wrapper to undertake feature selection in construction of a QSAR model to predict P-gp substrates with a multiple linear (ML) and SVM approach, and (iii) also finding factors (molecular descriptors) that most likely are associated with P-gp substrate specificity by using a PS and a SVM from the data set.