Properties of RNA Polymerases from B16 Melanoma

Some of the properties of RNA polymerases from melanotic and amelanotic B16 melanomas have been studied. Chromatin-bound RNA polymerase is activated by Mg++ more the Mn++. Addition of ammonium sulfate was found to activate the enzyme. Preincubation with phospholipase A or phospholipase C as well as extraction with ether or iso-octane decreased the RNA polymerase activity in the presence of Mg++ but not that in the presence of Mn++. The polymerase activity in the presence of high salt concentration (ammonium sulfate) was not affected by the phospholipases or by solvent extraction. Preincubation in the presence of trypsin was found to activate enzymatic activity in the presence of Mn++ to a greater extent than in the presence of Mg++. RNA polymerase activity of melanoma mitochondria was decreased by treatment with phospholopase A or phosholopase C as well as by extraction with ether or iso-octane. Phospholipase D as well as wheat-germ lipase did not have any effect on the RNA polymerase activities of nuclei or mitochondria. α-amanitin was found to inhibit the nuclear RNA polymerase activity in the presence of Mn++ at high salt concentration but not in the presence of Mg++. The RNA polymerase activity of melanoma mitochondria was not inhibited by alpha;-amanitin. The RNA polymerase activity in melanoma nuclei and mitochondria was inhibited by actinomycin D but rifamycin and rifampicin did not have any inhibitory action. Of the various tissues studied, the properties of the RNA polymerase from melanoma closely resembled those of the RNA polymerases from liver

High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature

Although the Bock–Aitkin likelihood-based estimation method for factor analysis of dichotomous item response data has important advantages over classical analysis of item tetrachoric correlations, a serious limitation of the method is its reliance on fixed-point Gauss-Hermite (G-H) quadrature in the solution of the likelihood equations and likelihood-ratio tests. When the number of latent dimensions is large, computational considerations require that the number of quadrature points per dimension be few. But with large numbers of items, the dispersion of the likelihood, given the response pattern, becomes so small that the likelihood cannot be accurately evaluated with the sparse fixed points in the latent space. In this paper, we demonstrate that substantial improvement in accuracy can be obtained by adapting the quadrature points to the location and dispersion of the likelihood surfaces corresponding to each distinct pattern in the data. In particular, we show that adaptive G-H quadrature, combined with mean and covariance adjustments at each iteration of an EM algorithm, produces an accurate fast-converging solution with as few as two points per dimension. Evaluations of this method with simulated data are shown to yield accurate recovery of the generating factor loadings for models of upto eight dimensions. Unlike an earlier application of adaptive Gibbs sampling to this problem by Meng and Schilling, the simulations also confirm the validity of the present method in calculating likelihood-ratio chi-square statistics for determining the number of factors required in the model. Finally, we apply the method to a sample of real data from a test of teacher qualifications.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43596/1/11336_2003_Article_1141.pd