A concentration addition model for the activation of the constitutive androstane receptor by xenobiotic mixtures

The effects of contaminants are typically studied in individualexposures; however, environmental exposures are rarely froma single contaminant. Therefore, the study of chemical mixturesis important in determining the effects of xenobiotics. Theconstitutive androstane receptor (CAR) responds to endobioticsand xenobiotics, and in turn induces detoxification enzymesinvolved in their elimination. First, we compared several androgensas inverse agonists, including androgens allegedly used by BayArea Laboratory Co-operative to enhance athletic performance.CAR inverse agonists ranked in order of potency were dihydroandrosterone(DHA) > tetrahydrogestrinone (THG) > androstanol >norbolethone. Therefore, we used DHA as an inverse agonist duringtransactivation assays. Next, we examined the effects of severalpesticides, plasticizers, steroids, and bile acids on CAR activation.Our data demonstrates that several pesticides and plasticizers,including diethylhexylphthalate, nonylphenol, cypermethrin,and chlorpyrifos activate CAR. Both full and partial CAR activatorswere discovered, and EC₅₀ values and Hillslopes were determinedfor use in the concentration addition models. Concentrationaddition models with and without restraint values to accountfor partial activators were developed. Measured results fromtransactivation assays with a mixture of two to five chemicalsindicate that the concentration addition model without restraintscorrectly predicts activity unless all of the chemicals in themixture are partial activators, and then restraint values beconsidered. Overall, our data indicates that it is importantto consider that we are exposed to a milieu of chemicals, andthe efficacy of each individual chemical is not the sole factorin determining CAR's activity in mixture modeling.     

Use of multi-photon laser-scanning microscopy to describe the distribution of xenobiotic chemicals in fish early life stages

To better understand the mechanisms by which persistent bioaccumulative toxicants (PBTs) produce toxicity during fish early life stages (ELS), dose-response relationships need to be understood in relation to the dynamic distribution of chemicals in sensitive tissues. In this study, a multi-photon laser scanning microscope (MPLSM) was used to determine the multi-photon excitation spectra of several polyaromatic hydrocarbons (PAHs) and to describe chemical distribution among tissues during fish ELS. The multi-photon excitation spectra revealed intense fluorescent signal from the model fluorophore, pentamethyl-difluoro-boro-indacene (BODIPY), less signal from benzo[a]pyrene and fluoranthene, and no detectable signal from pyrene. The imaging method was tested by exposing newly fertilized medaka (Oryzias latipes) eggs to BODIPY or fluoranthene for 6 h, followed by transfer to clean media. Embryos and larvae were then imaged through 5 days post-hatch. The two test chemicals partitioned similarly throughout development and differences in fluorescence intensity among tissues were evident to a depth of several hundred microns. Initially, the most intense signal was observed in the oil droplet within the yolk, while a moderate signal was seen in the portion of the yolk containing the yolk-platelets. As embryonic development progressed, the liver biliary system, gall bladder, and intestinal tract accumulated strong fluorescent signal. After hatch, once the gastrointestinal tract was completely developed, most of the fluorescent signal was cleared. The MPLSM is a useful tool to describe the tissue distribution of fluorescent PBTs during fish ELS.     

Diesel exhaust as a model xenobiotic in allergic inflammation

We investigated the effects of diesel exhaust particulates on the human allergic response using in vivo human nasal challenges. Diesel particles and phenanthrene, one of their constituent polyaromatic hydrocarbons, were shown to enhance total allergic antibody (IgE) production, enhance allergen-specific IgE in the presence of allergen, and induce sensitization to a neoantigen.     

Prediction of the concentration of diphenylhydantoin in the brain using a physiological pharmacokinetic hybrid model

A physiological pharmacokinetic hybrid model was developed in order to predict the disposition kinetics of diphenylhydantoin (DPH) in the brain from the plasma concentration data of DPH. The model was constructed under the assumptions of well-stirred, plasma flow-limited and linear tissue disposition kinetics of DPH. DPH was administered intravenously to the rats at a dose of 10 mg/kg together with/without sodium salicylate (SA; 10 mg/kg) and the DPH concentrations in the plasma and brain were determined. Plasma protein binding of DPH was also determined using equilibrium dialysis technique. Then the model was tested for its predictability of DPH concentrations in the brian from the plasma data of DPH. It was found that the predicted values of DPH concentrations in the brian were in fair agreement with the experimental values in the rats of both treaments. The 2-fold increase in the brain concentrations of DPH by SA-coadministration was predicted well from the plasma concentration and plasma free fraction (f _p) data of DPH using the model. Therefore, the hybrid model was concluded to be very useful for the prediction of the concentrations of DPH in the brain from the plasma concentration data. Finally, DPH concentrations in the human brian was calculated using this model from plasma DPH data in the literature, yet the scale-up of this model to the human is not convinced.     

Integrating variability in half-lives and dietary intakes to predict mercury concentration in hair

Methylmercury (MeHg) is a bioaccumulative environmental toxin that exerts its effect on fetal and infant neurodevelopment. Mercury concentration in hair is a good biomarker of MeHg accumulation in the body, with seafood being the main source of MeHg in humans. Therefore, modeling the link between food intake and mercury concentration in hair is a key step in assessing the risk of MeHg exposure. Using repeated measurements of diet and mercury concentration in hair, we studied 125 French pregnant women who consumed seafood (e.g., fish, mollusks and crustaceans) and compared their individual estimated dietary MeHg intakes with their hair mercury concentrations. We used a one-compartment toxicokinetic model for these comparisons. We integrated and estimated the between-person variability in MeHg half-life into the model. In a second model, we took into account an intra-individual MeHg intake variability to improve the performance of the toxicokinetic model.     

Toxic effect and adaptation in Scenedesmus intermedius to anthropogenic chloramphenicol contamination: genetic versus physiological mechanisms to rapid acquisition of xenobiotic resistance

Anthropogenic water pollution is producing a challenge to the survival of phytoplankton populations. From an ecological point of view, the tolerance of these microorganisms to water pollution is of paramount importance since they are the principal primary producers of aquatic ecosystems. The adaptation of a common chlorophyta species (Scenedesmus intermedius) exposed to selected dose-response chloramphenicol (CAP) concentrations has been analyzed. A fluctuation analysis demonstrated that CAP-resistant cells arise due to spontaneous mutation which occurs randomly prior to the antibiotic exposure. CAP-inhibited growth and photosynthetic performance of algal cells at 0.28 mg/l, and the IC₅₀₍₇₂₎ value was established in 0.10 mg/l for both parameters. The mutation rate from CAP sensitivity to resistance was 1.01 × 10⁻⁵ mutations per cell division, while the frequency of CAP-resistant allele in non-polluted environment was estimated to be 5.5 CAP-resistant mutants per 10³ sensitive-cells. These results demonstrate that resistant mutants exhibit a diminished fitness until 5 mg/l of CAP, thus enabling the survival of microalgae population.     

Leveraging mammalian pharmaceutical toxicology and pharmacology data to predict chronic fish responses to pharmaceuticals

Comparative pharmacology and toxicology approaches with fish models provide important linkages between the biomedical and environmental sciences. Because chronic fish responses to select pharmaceuticals are observed at very low (e.g., ng/L) concentrations, approaches are needed to identify therapeutics for robust environmental hazard and risk assessments. Whereas we observed no obvious relationship between acute toxicity data for rodent (LD₅₀) and fish (LC₅₀) models, using a probabilistic hazard evaluation approach, rodent and fish acute toxicity distributions predicted limited potential for acute toxicity at low concentrations, which is consistent with the peer-reviewed literature. Similar probabilistic distributions were developed to examine mammalian C_max and an Acute to Therapeutic Ratio (ATR), a surrogate for mammalian therapeutic index that is similar to an Acute to Chronic Ratios (ACRs) commonly calculated for fish models. Probabilistic distributions of ATRs for fifteen drug classes were also examined, which showed specific groups with higher (e.g., reproductive hormones, corticosteroids, antihistamines) and lower (e.g., antibiotics, NSAIDs) ATR values than the distribution for all available pharmaceutical ATRs. A statistically significant relationship (r² = 0.846, p < 0.001) was determined between mammalian ATR and fish ACR values, which may support a screening approach to examine chronic pharmaceutical effects in fish based on the magnitude of mammalian ATR values.     

A mathematical model to predict the release of water-soluble drugs from HPMC matrices

A mathematical model to predict the fraction of water-soluble drug released as a function of release time (t, h), HPMC concentration (CH, w/w), and volume of drug molecule (V, nm3) was derived with ranitidine hydrochloride, diltiazem hydrochloride, and ribavirin as model drugs. The model is log (M(t)/M(infinity)) = 0.5 log t-0.3322CH-0.2222V-0.2988 (n = 140, r = 0.9848), where M(t) is the amount of drug released at time t, M(infinity) is the amount of drug released over a very long time, which corresponds in principle to the initial loading, n is the number of samples, and r is the correlation coefficient. The model was validated using isoniazid and satisfactory results were obtained. The model can be used to predict the release fraction of various soluble drugs from HPMC matrices having different polymer levels.     

基于垂体腺瘤术后临床资料建立复发预测模型

目的 基于病人的临床资料建立一种易于实施的评分系统,对垂体腺瘤的复发做出预测。方法 回顾性选取2017年1月至2021年1月徐州医科大学附属医院垂体腺瘤病人作建模组,均接受经鼻内镜下垂体腺瘤切除术,平均随访时间大于1年。对可能引起术后复发的相关因素行统计学分析,依据已证相关特征建立评分系统,通过受试者操作特征曲线（ROC曲线）曲线下面积（AUC）评价该评分系统预测复发的能力,根据约登指数分析出评分临界值,另随访同期该院36例同种疾病病人作验证组,佐证评分系统的预测效能。结果 最终被纳入建模组病人157例。建模组中,28例（17.8%）的病人在>12个月的随访中出现复发;复发的可能性可通过Ki-67指数、改进后Knosp分级、大小及肿瘤残余进行预测（均P<0.05）;垂体腺瘤评分系统在预测肿瘤复发方面显示出良好的预测能力[AUC=0.92,95%CI:(0.85,0.98)],约登指数最大值为0.752,提示最佳预测临界分数为3分,当评分≥3分时,肿瘤复发可能性高;验证组评分≥3分有7例,复发4例,评分<3分有29例,复发1例（P=0.002）;评分系统作为预测指标,准...     

Metabolism in the rat of a model xenobiotic plant metabolite S-benzyl-N-malonyl-L-cysteine

1. The metabolism of a model xenobiotic plant metabolite S-benzyl-N-malonyl-L-cysteine (BMC) administered to rat at 10?mg/kg has been studied using a combination of radio-t.l.c. and?h.p.l.c.

2. The major route of excretion for the administered ¹⁴C was via the urine (79% in 3 days).

3. The major metabolite was hippuric acid. The extent of biotransformation of BMC indicated the lability of the N-malonyl bond whose hydrolytic removal initiated a metabolic sequence which involved the action of C-S lyase to produce benzyl thiol.

4. A comparison of the findings from this study with those from experiments with N-acetyl-S-benzyl-L-cysteine and S-benzyl-L-cysteine is made to support the metabolic pathway proposed.     

Metabolism in the rat of a model xenobiotic plant metabolite S-benzyl-N-malonyl-L-cysteine

1. The metabolism of a model xenobiotic plant metabolite S-benzyl-N-malonyl-L-cysteine (BMC) administered to rat at 10 mg/kg has been studied using a combination of radio-t.l.c. and h.p.l.c. 2. The major route of excretion for the administered 14C was via the urine (79% in 3 days). 3. The major metabolite was hippuric acid. The extent of biotransformation of BMC indicated the lability of the N-malonyl bond whose hydrolytic removal initiated a metabolic sequence which involved the action of C-S lyase to produce benzyl thiol. 4. A comparison of the findings from this study with those from experiments with N-acetyl-S-benzyl-L-cysteine and S-benzyl-L-cysteine is made to support the metabolic pathway proposed.     

A catalogue of polymorphisms related to xenobiotic metabolism and cancer susceptibility

High-throughput genotyping technology of multiple genes based on large samples of cases and controls are likely to be important in identifying common genes which have a moderate effect on the development of specific diseases. We present here a comprehensive list of 313 known experimentally confirmed polymorphisms in 54 genes which are particularly relevant for metabolism of drugs, alcohol, tobacco, and other potential carcinogens. We have compiled a catalog with a standardized format that summarizes the genetic and biochemical properties of the selected polymorphisms. We have also confirmed or redesigned experimental conditions for simplex or multiplex PCR amplification of a subset of 168 SNPs of particular interest, which will provide the basis for the design of assays compatible with high-throughput genotyping.     

Convolution method to predict drug concentration profiles of 2,3,5,6-tetramethylpyrazine following transdermal application

The objective of this work is to predict the systemic drug concentration of 2,3,5,6-tetramethylpyrazine (TMP) following transdermal application in rabbits from the in vitro skin permeation data. The in vitro skin permeation was studied in Franz diffusion cells. Pharmacokinetic evaluation of TMP following transdermal application and bolus intravenous administration were carried out in New Zealand White (NZW) rabbits. Drug concentration-time curve following transdermal application was predicted via the convolution procedure using an in vitro skin permeation data as a weighting function, and the intravenous data as an unit impulse response. The results showed that the predicted drug concentration following transdermal application by convolution method was in good agreement with the observed drug absorption profiles. These findings indicated that in vitro skin permeation tests could be useful to predict in vivo drug absorption profiles following transdermal application.     

A physiological pharmacokinetic model for morphine disposition in the pregnant rat

A physiological model was used to examine the disposition of morphine in the pregnant rat. In the model was incorporated an expression of both a linear and a nonlinear binding term of morphine to the maternal muscular tissue. Furthermore, the experimental data suggested that a diffusion-limited transport of morphine occurred across the placenta. Morphine showed a relatively high partition into the maternal kidney and muscle tissues. The concentration of morphine in the foetus was about 1.5 times higher than that of the maternal plasma, whereas the foetal brain concentration was about 4 times higher than that of the maternal plasma. The influence on morphine disposition by changes in both the tissue binding of the maternal muscle and the placental plasma flow was explored by model simulations. Due to the diffusionlimited transport of morphine across the placenta, a change in the placental plasma flow would only have an effect on the concentration-time profile of morphine in the foetal tissues if the plasma flow approached and became less than the diffusion clearance across the placenta. An increase in the partition of morphine into the maternal muscle produced an increase in the terminal half-life in all tissues including the foetus.     

Continuous medication monitoring: A clinical model to predict adherence to medications among chronic kidney disease patients

BackgroundAn adherence model is required to optimise medication management among chronic kidney disease (CKD) patients, as current assessment methods overestimate the true adherence of CKD patients with complex regimens. An approach to assess adherence to individual medications is required to assist pharmacists in addressing non-adherence.ObjectiveTo develop an adherence prediction model for CKD patients.MethodsThis multi-centre, cross-sectional study was conducted in 10 tertiary hospitals in Malaysia using simple random sampling of CKD patients with ≥1 medication (sample size = 1012). A questionnaire-based collection of patient characteristics, adherence (defined as ≥80% consumption of each medication for the past one month), and knowledge of each medication (dose, frequency, indication, and administration) was performed. Continuous data were converted to categorical data, based on the median values, and then stratified and analysed. An adherence prediction model was developed through multiple logistic regression in the development group (n = 677) and validated on the remaining one-third of the sample (n = 335). Beta-coefficient values were then used to determine adherence scores (ranging from 0 to 7) based on the predictors identified, with lower scores indicating poorer medication adherence.ResultsMost of the 1012 patients had poor medication adherence (n = 715, 70.6%) and half had good medication knowledge (n = 506, 50%). Multiple logistic regression analysis determined 4 significant predictors of adherence: ≤7 medications (constructed score = 2, p < 0.001), ≤3 co-morbidities (constructed score = 1, p = 0.015), absence of complementary/alternative medicine use (constructed score = 1, p = 0.003), and knowledge score ≥80% (constructed score = 3, p < 0.001). A higher total constructed score from the prediction model indicated a higher likelihood of adherence (odds ratio [OR]: 2.41; 95% confidence interval [CI]: 2.112–2.744; p < 0.001). The area under the receiver operating characteristic (ROC) curve of the developed model (n = 677) had good accuracy (ROC: 0.867, 95% CI: 0.840–0.896; p < 0.001). The validated model (n = 335) also had good accuracy (ROC: 0.812, 95% CI: 0.765–0.859; p < 0.001). There was no significant difference between the development and validation groups (p = 0.11, Z-value:1.62, standard error: 0.034).ConclusionThe score constructed from the medication adherence prediction model for CKD patients had good accuracy and could be useful for identifying patients with a higher risk of non-adherence, to ensure optimised adherence management.