Effect of 15(R)-15-methyl-prostaglandin E2 on iron absorption in the rat

Summary The administration of 15(R)-15-methyl prostaglandin E₂ (15(R)-15-M-PGE₂) in vivo significantly diminished the uptake of⁵⁹Fe into blood, spleen, liver, femur and dried intestine of rats, whereas acetylsalicylic acid (ASA) increased the counts significantly. This effect of ASA was counteracted by 15(R)-15-M-PGE₂. It is suggested that prostaglandins (PGs) might play an important role in inhibiting iron absorption at the intestinal level.This work was supported by grant No.6638 from CONICET (Argentina). The technical assistance of Mrs María E. Castro and Norma Rizzo is gratefully acknowleged.     

Host cell reactivation of ozone-treated T3 bacteriophage by different strains ofEscherichia coli

Summary Host cell reactivation capacity for ozone T3 phage was determined for differentE. coli strains deficient in one or more of the DNA repair mechanisms. The results indicate that DNA polymerase I appears to play a key role in the repair of damage produced on the DNA by ozone while thelexA gene product seems to play a minor one.This research was sponsored by the National Sciences and Engineering Council of Canada. One of us (PLH) acknowledges a scholarship from the NSERCof Canada.     

Studies on the Dd antigen-antibody system. I. The nature of antigen Dd and its antibodies

Summary The nature of antigen Dd, an antigen present in the extracts of human dandruff which precipitates human sera selectively, and antibodies reacting with it are reported.This work was supported through U.G.C. Grant No. F.23-230/75/SR II. H.K. participated in this study, first as J.R.F. of U.G.C. and then as S.R.F. of I.C.M.R. We are grateful to Dr Baruch S. Blumberg for his invaluable suggestions and to Professor H. Walter for the gift of IgG, IgM and IgA immune sera.     

Accurate forecasting of the undecided population in a public opinion poll

The problem of pollsters is addressed which is to forecast accurately the final answers of the undecided respondents to the primary question in a public opinion poll. The task is viewed as a pattern‐recognition problem of correlating the answers of the respondents to the peripheral questions in the survey with their primary answers. The underlying pattern is determined with a supervised artificial neural network that is trained using the peripheral answers of the decided respondents whose primary answers are also known. With peripheral answers as inputs, the trained network outputs the most probable primary response of an undecided respondent. For a poll conducted to determine the approval rating of the (former) Philippine president, J. E. Estrada in December 1999 and March 2000, the trained network predicted with a 95% success rate the direct responses of a test population that consists of 24.57% of the decided population who were excluded in the network training set. For the undecided population (22.67% of December respondents; 23.67% of March respondents), the network predicted a final response distribution that is consistent with the approval/disapproval ratio of the decided population. Copyright © 2002 John Wiley & Sons, Ltd.     

Radar Imaging Based on Iterative Algorithms

It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.     

Subset threshold autoregression

We develop in this paper an efficient way to select the best subset threshold autoregressive model. The proposed method uses a stochastic search idea. Differing from most conventional approaches, our method does not require us to fix the delay or the threshold parameters in advance. By adopting the Markov chain Monte Carlo techniques, we can identify the best subset model from a very large of number of possible models, and at the same time estimate the unknown parameters. A simulation experiment shows that the method is very effective. In its application to the US unemployment rate, the stochastic search method successfully selects lag one as the time delay and five best models from more than 4000 choices. Copyright © 2003 John Wiley & Sons, Ltd.