Neurobehavioral and Cardiovascular Effects of Potassium Cyanide Administered Orally to Mice.

The Food and Drug Administration Animal Rule requires evaluation of cardiovascular and central nervous system (CNS) effects of new therapeutics. To characterize an adult and juvenile mouse model, neurobehavioral and cardiovascular effects and pathology of a single sublethal but toxic, 8 mg/kg, oral dose of potassium cyanide (KCN) for up to 41 days postdosing were investigated. This study describes the short- and long-term sensory, motor, cognitive, and behavioral changes associated with oral dosing of a sublethal but toxic dose of KCN utilizing functional observation battery and Tier II CNS testing in adult and juvenile mice of both sexes. Selected tissues (histopathology) were evaluated for changes associated with KCN exposure with special attention to brain regions. Telemetry (adult mice only) was used to evaluate cardiovascular and temperature changes. Neurobehavioral capacity, sensorimotor responsivity or spontaneous locomotor activity, and rectal temperature were significantly reduced in adult and juvenile mice at 30 minutes post-8 mg/kg KCN dose. Immediate effects of cyanide included bradycardia, adverse electrocardiogram arrhythmic events, hypotension, and hypothermia with recovery by approximately 1 hour for blood pressure and heart rate effects and by 2 hours for body temperature. Lesions consistent with hypoxia, such as mild acute tubular necrosis in the kidneys corticomedullary junction, were the only histopathological findings and occurred at a very low incidence. The mouse KCN intoxication model indicates rapid and completely reversible effects in adult and juvenile mice following a single oral 8 mg/kg dose. Neurobehavioral and cardiovascular measurements can be used in this animal model as a trigger for treatment.

Effects of tyrosine kinase inhibitors on rat isolated heart function and protein biomarkers indicative of toxicity.

INTRODUCTION: Cardiac toxicity, manifested as diminished contractility, ischemic heart disease, and heart failure is a major issue in drug safety. Concerns revolve around targeted drugs (TKIs) where contractility effects were not anticipated. The ability to predict cardiac toxicity early would help to de-risk drugs in development and prepare physicians to manage risk in the clinic. Issues with current preclinical studies include insufficient testing with informative, translatable models, and predictive biomarkers. The isolated heart model is amenable to multiple assessments which can be combined with current technologies to assess toxicity on a multi-scale level. METHODS: Rat isolated heart model was used to assess changes in left ventricular (LV) contractility and protein biomarkers BNP, IL6, TNFα, and cardiac troponins T (TnT) and I (TnI). Responses were assessed during perfusion with modified Henseleit Krebs (MHK), and 20 min concentration escalations of verapamil, carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP), isoproterenol, or 20 min escalations bracketing clinical blood concentrations of sunitinib, sorafenib, and erlotinib. LV parameters and effluent for biomarkers were collected before and during escalating drug concentrations. RESULTS: Verapamil reduced inotropy with no change in biomarkers, FCCP and isoproterenol reduced and increased heart function respectively and increased TnT and TNFα. Erlotinib had no significant effects on function or biomarkers. Sunitinib diminished function, increased TNFα at 0.1 µM, and increased TnT at higher concentrations. Sorafenib dose dependently increased TNFα beginning at 0.1 µM, reducing contractility and flow rate at 0.6 µM. DISCUSSION: The ex-vivo assay is a sensitive and predictive model for assessing changes in heart function and biomarkers of toxicity and injury. This assay demonstrates the potential for sunitinib and sorafenib to cause cardiac toxicity in humans. Also, TNFα appears to be a biomarker in the heart prior to injury. Due to its versatility, the isolated heart assay has potential to fill gaps in cardiac safety testing early in drug development.

Evaluating sufficient similarity for disinfection by-product (DBP) mixtures: multivariate statistical procedures.

For evaluation of the adverse health effects associated with exposures to complex chemical mixtures in the environment, the U.S. Environmental Protection Agency (EPA) (2000) states, "if no data are available on the mixture of concern, but health effects data are available on a similar mixture ... a decision must be made whether the mixture on which health effects are available is 'sufficiently' similar to the mixture of concern to permit a risk assessment." This article provides a detailed discussion of statistical considerations for evaluation of the similarity of mixtures. Multivariate statistical procedures are suggested to determine whether individual samples of drinking-water disinfection by-products (DBPs) vary significantly from a group of samples that are considered to be similar. The application of principal components analysis to (1) reduce the dimensionality of the vectors of water samples and (2) permit visualization and statistical comparisons in lower dimensional space is suggested. Formal analysis of variance tests of homogeneity are illustrated. These multivariate statistical procedures are applied to a data set describing samples from multiple water treatment plants. Essential data required for carrying out sensitive analyses include (1) identification and measurement of toxicologically sensitive process input and output characteristics, and (2) estimates of variability within the data to construct statistically efficient estimates and tests.

Evaluating sufficient similarity for drinking-water disinfection by-product (DBP) mixtures with bootstrap hypothesis test procedures.

In chemical mixtures risk assessment, the use of dose-response data developed for one mixture to estimate risk posed by a second mixture depends on whether the two mixtures are sufficiently similar. While evaluations of similarity may be made using qualitative judgments, this article uses nonparametric statistical methods based on the "bootstrap" resampling technique to address the question of similarity among mixtures of chemical disinfectant by-products (DBP) in drinking water. The bootstrap resampling technique is a general-purpose, computer-intensive approach to statistical inference that substitutes empirical sampling for theoretically based parametric mathematical modeling. Nonparametric, bootstrap-based inference involves fewer assumptions than parametric normal theory based inference. The bootstrap procedure is appropriate, at least in an asymptotic sense, whether or not the parametric, distributional assumptions hold, even approximately. The statistical analysis procedures in this article are initially illustrated with data from 5 water treatment plants (Schenck et al., 2009), and then extended using data developed from a study of 35 drinking-water utilities (U.S. EPA/AMWA, 1989), which permits inclusion of a greater number of water constituents and increased structure in the statistical models.

Serial analysis of gene expression profiles of adult and aged mouse cerebellum.

Changes in specific cerebellar molecules contribute to impaired balance and motor coordination frequently observed in aged individuals. Serial analysis of gene expression (SAGE) was used to construct six libraries from adult and aged mouse cerebella. Combined unique tags for each group revealed 325 genes that were differentially expressed (p-chance

Comparisons of methods for linkage analysis and haplotype reconstruction using extended pedigree data.

We compare and contrast the performance of SIMPLE, a Monte Carlo based software, with that of several other methods for linkage and haplotype analyses, focusing on the simulated data from the New York City population. First, a whole-genome scan study based on the microsatellite markers was performed using GENEHUNTER. Because GENEHUNTER had to drop individuals for many of the pedigrees, we performed a follow-up study focusing on several regions of interest using SIMPLE, which can handle all pedigrees in their entirety. Second, 3 haplotyping programs, including that in SIMPLE, were used to reconstruct haplotypic configurations in pedigrees. SIMPLE emerges clearly as a preferred tool, as it can handle large pedigrees and produces haplotypic configurations without double recombinant haplotypes. For this study, we had knowledge of the simulating models at the time we performed the analysis.