Methods of phase reconstruction for time-averaging electronic speckle pattern interferometry

Electronic speckle pattern interferometry is useful for the qualitative depiction of the deformation profile of harmonically vibrating objects. However, extending the process to achieve quantitative results requires unwrapping the phase in the interferogram, which contains significant noise due to the speckle. Two methods to achieve accurate phase information from time-averaged speckle pattern interferograms are presented. The first is based on a direct inverse of the regions within corresponding phase intervals, and the second is based on optimization of four independent parameters. The optimization method requires less time than more commonly used algorithms and shows higher precision of the resulting surface displacement.

Identification of chemical modulators of the constitutive activated receptor (CAR) in a gene expression compendium

The nuclear receptor family member constitutive activated receptor (CAR) is activated by structurally diverse drugs and environmentally-relevant chemicals leading to transcriptional regulation of genes involved in xenobiotic metabolism and transport. Chronic activation of CAR increases liver cancer incidence in rodents, whereas suppression of CAR can lead to steatosis and insulin insensitivity. Here, analytical methods were developed to screen for chemical treatments in a gene expression compendium that lead to alteration of CAR activity. A gene expression biomarker signature of 83 CAR-dependent genes was identified using microarray profiles from the livers of wild-type and CAR-null mice after exposure to three structurally-diverse CAR activators (CITCO, phenobarbital, TCPOBOP). A rank-based algorithm (Running Fisher’s algorithm (p-value ≤ 10^-4)) was used to evaluate the similarity between the CAR biomarker signature and a test set of 28 and 32 comparisons positive or negative, respectively, for CAR activation; the test resulted in a balanced accuracy of 97%. The biomarker signature was used to identify chemicals that activate or suppress CAR in an annotated mouse liver/primary hepatocyte gene expression database of ~1850 comparisons. CAR was activated by 1) activators of the aryl hydrocarbon receptor (AhR) in wild-type but not AhR-null mice, 2) pregnane X receptor (PXR) activators in wild-type and to lesser extents in PXR-null mice, and 3) activators of PPARα in wild-type and PPARα-null mice. CAR was consistently activated by five conazole fungicides and four perfluorinated compounds. Comparison of effects in wild-type and CAR-null mice showed that the fungicide propiconazole increased liver weight and hepatocyte proliferation in a CAR-dependent manner, whereas the perfluorinated compound perfluorooctanoic acid (PFOA) increased these endpoints in a CAR-independent manner. A number of compounds suppressed CAR coincident with increases in markers of inflammation including acetaminophen, concanavalin A, lipopolysaccharide, and 300 nm silica particles. In conclusion, we have shown that a CAR biomarker signature coupled with a rank-based similarity method accurately predicts CAR activation. This analytical approach, when applied to a gene expression compendium, increased the universe of known chemicals that directly or indirectly activate CAR, highlighting the promiscuous nature of CAR activation and signaling through activation of other xenobiotic-activated receptors.

Pharmacokinetic and Genomic Effects of Arsenite in Drinking Water on Mouse Lung in a 30-Day Exposure

The 2 objectives of this subchronic study were to determine the arsenite drinking water exposure dependent increases in female C3H mouse liver and lung tissue arsenicals and to characterize the dose response (to 0, 0.05, 0.25, 1, 10, and 85 ppm arsenite in drinking water for 30 days and a purified AIN-93M diet) for genomic mouse lung expression patterns. Mouse lungs were analyzed for inorganic arsenic, monomethylated, and dimethylated arsenicals by hydride generation atomic absorption spectroscopy. The total lung mean arsenical levels were 1.4, 22.5, 30.1, 50.9, 105.3, and 316.4 ng/g lung tissue after 0, 0.05, 0.25, 1, 10, and 85 ppm, respectively. At 85 ppm, the total mean lung arsenical levels increased 14-fold and 131-fold when compared to either the lowest noncontrol dose (0.05 ppm) or the control dose, respectively. We found that arsenic exposure elicited minimal numbers of differentially expressed genes (DEGs; 77, 38, 90, 87, and 87 DEGs) after 0.05, 0.25, 1, 10, and 85 ppm, respectively, which were associated with cardiovascular disease, development, differentiation, apoptosis, proliferation, and stress response. After 30 days of arsenite exposure, this study showed monotonic increases in mouse lung arsenical (total arsenic and dimethylarsinic acid) concentrations but no clear dose-related increases in DEG numbers.