Chloroform inhalation exposure conditions necessary to initiate liver toxicity in female B6C3F1 mice

Organ wide toxicological assessment of common edible herbs and their mixtures as used in home remedies

The use of home remedies for medicinal purposes, most of which are edible plants has continued to be a practice in many homes. However, there has been an increasing report of chronic use with lethal effect. Among the commonly used herbal/ medicinal plants were ginger, garlic and lemon. These were seen to be prevalent across continents with brewing and crude extraction being the most means of consumption. This study investigated the organ wide toxicity of this extract following chronic consumption of crude extract. Twenty-five albino Wister rats, five in each group were used for this experiment. Each animal received 0.5ml/kg body weight of either ginger extract, garlic extract, lemon juice, or a mixture of equal volumes of all three extract (v/v) respectively twice daily for seven (7) days. Statistics were represented as ±SE; P≤0.05 was considered significant. Previous studies have shown that moderate consumption of these medicinal plants were beneficial and have shown no deleterious effect. This study observed no change in the weight of the experimental animals. The weight of the animals continued to increase except for the group that received lemon and the mixture, but these were not significant. It was observed that chronic consumption induced organ wide toxicity to include the liver, kidney, intestinal epithelium, stomach, and pancreas. These were shown to alter tissue architecture and the cell morphology. Packed cell volume was reduced in the lemon and the group that received a combination of all extracts (p=o.03). Blood differentials showed changes in levels. An elevated basophil level was observed in ginger and garlic (p<0.0001; p=0.0006). Monocyte levels increased progressively across each group when compared to the control with the most elevated level seen in the group that received the mixture (p<0.0001). Lymphocyte count was reduced across all the groups that received the extract except for animals that received ginger. This study suggests the application of caution among users of these medicinal plants and continues to draw attention to the need for harmonization and standardization of safe use doses.

Data-Driven Quantitative Structure-Activity Relationship Modeling for Human Carcinogenicity by Chronic Oral Exposure

Traditional methodologies for assessing chemical toxicity are expensive and time-consuming. Computational modeling approaches have emerged as low-cost alternatives, especially those used to develop quantitative structure-activity relationship (QSAR) models. However, conventional QSAR models have limited training data, leading to low predictivity for new compounds. We developed a data-driven modeling approach for constructing carcinogenicity-related models and used these models to identify potential new human carcinogens. To this goal, we used a probe carcinogen dataset from the US Environmental Protection Agency's Integrated Risk Information System (IRIS) to identify relevant PubChem bioassays. Responses of 25 PubChem assays were significantly relevant to carcinogenicity. Eight assays inferred carcinogenicity predictivity and were selected for QSAR model training. Using 5 machine learning algorithms and 3 types of chemical fingerprints, 15 QSAR models were developed for each PubChem assay dataset. These models showed acceptable predictivity during 5-fold cross-validation (average CCR = 0.71). Using our QSAR models, we can correctly predict and rank 342 IRIS compounds' carcinogenic potentials (PPV = 0.72). The models predicted potential new carcinogens, which were validated by a literature search. This study portends an automated technique that can be applied to prioritize potential toxicants using validated QSAR models based on extensive training sets from public data resources.

Influence of Sexual Dimorphism on Pulmonary Inflammatory Response in Adult Mice Exposed to Chloroform

Chloroform is an organic solvent used as an intermediate in the synthesis of various fluorocarbons. Despite its widespread use in industry and agriculture, exposure to chloroform can cause illnesses such as cancer, especially in the liver and kidneys. The aim of the study was to analyze the effects of chloroform on redox imbalance and pulmonary inflammatory response in adult C57BL/6 mice. Forty animals were divided into 4 groups (N = 10): female (FCG) and male (MCG) controls, and females (FEG) and males (MEG) exposed to chloroform (7.0 ppm) 3 times/d for 20 minutes for 5 days. Total and differential cell counts, oxidative damage analysis, and protein carbonyl and antioxidant enzyme catalase (CAT) activity measurements were performed. Morphometric analyses included alveolar area (Aa) and volume density of alveolar septa (Vv) measurements. Compared to FCG and MCG, inflammatory cell influx, oxidative damage to lipids and proteins, and CAT activity were higher in FEG and MEG, respectively. Oxidative damage and enzyme CAT activity were higher in FEG than in FCG. The Aa was higher in FEG and MEG than in FCG and MCG, respectively. The Vv was lower in FEG and MEG than in FCG and MCG, respectively. This study highlights the risks of occupational chloroform exposure at low concentrations and the intensity of oxidative damage related to gender. The results validate a model of acute exposure that provides cellular and biochemical data through short-term exposure to chloroform.

Thermodynamics of lipid interactions with cell-penetrating peptides

Cationic peptides are efficiently taken up by biological cells through different pathways, which can be exploited for delivery of intracellular drugs. For example, their endocytosis is known since 1967, and this typically produces entrapment of the peptides in endocytotic vesicles. The resulting peptide (and cargo) degradation in lysosomes is of little therapeutic interest. Beside endocytosis (and various subtypes thereof), cationic cell-penetrating peptides (CPPs) may also gain access to cytosol and nucleus of livings cells. This process is known since 1988, but it is poorly understood whether the cytosolic CPP appearance requires an active cellular machinery with membrane proteins and signaling molecules, or whether this translocation occurs by passive diffusion and thus can be mimicked with model membranes devoid of proteins or glycans. In the present chapter, protocols are presented that allow for testing the membrane binding and disturbance of CPPs on model membranes with special focus on particular CPP properties. Protocols include vesicle preparation, lipid quantification, and analysis of membrane leakage, lipid polymorphism ((31)P NMR), and membrane binding (isothermal titration calorimetry). Using these protocols, a major difference among CPPs is observed: At low micromolar concentration, nonamphipathic CPPs, such as nona-arginine (WR(9)) and penetratin, have only a poor affinity for model membranes with a lipid composition typical of eukaryotic membranes. No membrane leakage is induced by these compounds at low micromolar concentration. In contrast, their amphipathic derivatives, such as acylated WR(9) (C(14), C(16), C(18)) or amphipathic penetratin mutant p2AL (Drin et al., Biochemistry 40:1824-1834, 2001), bind and disturb lipid model membranes already at low micromolar peptide concentration. This suggests that the mechanism for cytosolic CPP delivery (and potential toxicity) differs among CPPs despite their common name.

Toxicogenetics: population-based testing of drug and chemical safety in mouse models

The rapid decline in the cost of dense genotyping is paving the way for new DNA sequence-based laboratory tests to move quickly into clinical practice, and to ultimately help realize the promise of 'personalized' therapies. These advances are based on the growing appreciation of genetics as an important dimension in science and the practice of investigative pharmacology and toxicology. On the clinical side, both the regulators and the pharmaceutical industry hope that the early identification of individuals prone to adverse drug effects will keep advantageous medicines on the market for the benefit of the vast majority of prospective patients. On the environmental health protection side, there is a clear need for better science to define the range and causes of susceptibility to adverse effects of chemicals in the population, so that the appropriate regulatory limits are established. In both cases, most of the research effort is focused on genome-wide association studies in humans where de novo genotyping of each subject is required. At the same time, the power of population-based preclinical safety testing in rodent models (e.g., mouse) remains to be fully exploited. Here, we highlight the approaches available to utilize the knowledge of DNA sequence and genetic diversity of the mouse as a species in mechanistic toxicology research. We posit that appropriate genetically defined mouse models may be combined with the limited data from human studies to not only discover the genetic determinants of susceptibility, but to also understand the molecular underpinnings of toxicity.

Development of a quantitative model incorporating key events in a hepatotoxic mode of action to predict tumor incidence

Biologically based dose-response (BBDR) modeling of environmental pollutants can be utilized to inform the mode of action (MOA) by which compounds elicit adverse health effects. Chemicals that produce tumors are typically labeled as either genotoxic or nongenotoxic. Though both the genotoxic and the nongenotoxic MOA may be operative as a function of dose, it is important to note that the label informs but does not define a MOA. One commonly proposed MOA for nongenotoxic carcinogens is characterized by the key events cytotoxicity and regenerative proliferation. The increased division rate associated with such proliferation can cause an increase in the probability of mutations, which may result in tumor formation. We included these steps in a generalized computational pharmacodynamic (PD) model incorporating cytotoxicity as a MOA for three carcinogens (chloroform, CHCl(3); carbon tetrachloride, CCL(4); and N,N-dimethylformamide, DMF). For each compound, the BBDR model is composed of a chemical-specific physiologically based pharmacokinetic model linked to a PD model of cytotoxicity and cellular proliferation. The rate of proliferation is then linked to a clonal growth model to predict tumor incidences. Comparisons of the BBDR simulations and parameterizations across chemicals suggested that significant variation among the models for the three chemicals arises in a few parameters expected to be chemical specific (such as metabolism and cellular injury rate constants). Optimization of model parameters to tumor data for CCL(4) and DMF resulted in similar estimates for all parameters related to cytotoxicity and tumor incidences. However, optimization of the CHCl(3) data resulted in a higher estimate for one parameter (BD) related to death of initiated cells. This implies that additional steps beyond cytotoxicity leading to induced cellular proliferation can be quantitatively different among chemicals that share cytotoxicity as a hypothesized carcinogenic MOA.

A preliminary operational classification system for nonmutagenic modes of action for carcinogenesis

This article proposes a system of categories for nonmutagenic modes of action for carcinogenesis. The classification is of modes of action rather than individual carcinogens, because the same compound can affect carcinogenesis in more than one way. Basically, we categorize modes of action as: (1) co-initiation (facilitating the original mutagenic changes in stem and progenitor cells that start the cancer process) (e.g. induction of activating enzymes for other carcinogens); (2) promotion (enhancing the relative growth vs differentiation/death of initiated clones (e.g. inhibition of growth-suppressing cell-cell communication); (3) progression (enhancing the growth, malignancy, or spread of already developed tumors) (e.g. suppression of immune surveillance, hormonally mediated growth stimulation for tumors with appropriate receptors by estrogens); and (4) multiphase (e.g., "epigenetic" silencing of tumor suppressor genes). A priori, agents that act at relatively early stages in the process are expected to manifest greater relative susceptibility in early life, whereas agents that act via later stage modes will tend to show greater susceptibility for exposures later in life.

Development and use of a single-animal whole-body system for inhalation exposure

Inhalation exposure studies, in which test subjects are fully or partially immersed in an atmosphere containing a compound of interest, are usually carried out using one of two possible exposure systems: large whole-body chambers or systems that expose only the animal's nose or head. Whole-body chambers may require large quantities of test compound, which can pose a problem if the chemical is expensive or available in limited quantities. Nose- or head-only systems can help conserve test compound but may cause stress or injury to animals. To address these concerns, the authors developed an exposure system consisting of small single-animal whole-body chambers. They exposed 80 mice and 80 rats to five test compounds at various concentrations. Though the system was labor-intensive for animal care technicians, it effectively exposed animals to precise chemical doses without causing adverse effects, using less test compound than would have been required in a conventional whole-body chamber.

A classification framework and practical guidance for establishing a mode of action for chemical carcinogens

The recently released U.S. Environmental Protection Agency (U.S. EPA) Supplemental Guidance for Assessing Risk from Early Life Exposure to Carcinogens (SGAC) provides guidance to account for potential increased early life susceptibility to carcinogens that are acting via a mutagenic mode of action. While determination of the mode of carcinogenic action is central to the SGAC procedures and other regulatory risk assessments, little guidance is given as to the approaches, criteria, and nature of the evidence required to define a mutagenic mode of action. The purpose of this paper is to provide a framework along with practical guidance for the process of assigning a mode of action. Strengths, weaknesses, reliability, and choice of a test battery are discussed for select bacterial, cell culture, whole animal and human cell assays. Common confounding factors of induced pathology, cytolethality, and regenerative cell proliferation in rodent cancer bioassays are discussed along with approaches to account for these effects in assigning a mode of action and in risk assessments. Specific examples are given to illustrate the complexity in generating a data set sufficient to move from the default regulatory position of assuming a genotoxic mode of action to actually assigning a nongenotoxic mode of action. A two-part framework is proposed for assigning a mode of action. First, a weight of evidence approach is used to assess mutagenic potential based on results of genetic toxicology test systems. Second, a descriptor is assigned to classify the degree to which mutagenic activity likely played a role in the mode of action of tumor formation. This option provides a more realistic way of describing the mode of action instead of being bound by the strict genotoxic vs. nongenotoxic choices.

Universality of J-shaped and U-shaped dose-response relations as emergent properties of stochastic transition systems

Dose-response data for many chemical carcinogens exhibit multiple apparent concentration thresholds. A relatively small increase in exposure concentration near such a threshold disproportionately increases incidence of a specific tumor type. Yet, many common mathematical models of carcinogenesis do not predict such threshold-like behavior when model parameters (e.g., describing cell transition rates) increase smoothly with dose, as often seems biologically plausible. For example, commonly used forms of both the traditional Armitage-Doll and multistage (MS) models of carcinogenesis and the Moolgavkar-Venzon-Knudson (MVK) two-stage stochastic model of carcinogenesis typically yield smooth dose-response curves without sudden jumps or thresholds when exposure is assumed to increase cell transition rates in proportion to exposure concentration.This paper introduces a general mathematical modeling framework that includes the MVK and MS model families as special cases, but that shows how abrupt transitions in cancer hazard rates, considered as functions of exposure concentrations and durations, can emerge naturally in large cell populations even when the rates of cell-level events increase smoothly (e.g., proportionally) with concentration. In this framework, stochastic transitions of stem cells among successive events represent exposure-related damage. Cell proliferation, cell killing and apoptosis can occur at different stages. Key components include: An effective number of stem cells undergoing active cycling and hence vulnerable to stochastic transitions representing somatically heritable transformations. (These need not occur in any special linear order, as in the MS model.)A random time until the first malignant stem cell is formed. This is the first order-statistic, T = min{T1, T2, ..., Tn} of n random variables, interpreted as the random times at which each of n initial stem cells or their progeny first become malignant.A random time for a normal stem cell to complete a full set of transformations converting it to a malignant one. This is interpreted very generally as the first passage time through a network of stochastic transitions, possibly with very many possible paths and unknown topology.In this very general family of models, threshold-like (J-shaped or multi-threshold) dose-response nonlinearities naturally emerge even without cytotoxicity, as consequences of stochastic phase transition laws for traversals of random transition networks. With cytotoxicity present, U-shaped as well as J-shaped dose-response curves can emerge. These results are universal, i.e., independent of specific biological details represented by the stochastic transition networks.