Radioprotective Effect of Vitamin C as an Antioxidant

Vitamin C is known as a potent antioxidant. We studied vitamin C as a radioprotective agent, focusing on its antioxidative effect. When the body is exposed to radiation, free radicals and reactive oxygen species (ROS) are produced and oxidize cell components, resulting in cell damage. Vitamin C has the potential to scavenge these radical products, thereby protecting against radiation-induced cell damage. We investigated the effects of vitamin C on radiation-induced gastrointestinal (GI) syndrome in mice. The mice received whole-body irradiation followed by bone marrow transplantation 24 h after exposure. Despite avoiding bone marrow failure, the mice eventually died of GI syndrome. Pretreatment with per os administration of high-dose vitamin C effectively mitigated radiation-induced GI syndrome and improved mouse survivals, while per os post-treatment with vitamin C was ineffective, presumably due to impaired absorption from the radiation-damaged intestine. We also investigated the effect of post-exposure treatment with intraperitoneal administration of vitamin C on radiation-induced bone marrow dysfunction in mice. Intraperitoneal administration with high-dose vitamin C, even at 24 h after whole-body irradiation, was still effective in avoiding bone marrow dysfunction, thereby increasing mouse survival after radiation. In conclusion, administration of high-dose vitamin C effectively reduced the radiation lethality in mice

Reliability checks on the Indo-US Stellar Spectral Library using Artificial Neural Networks and Principal Component Analysis

The Indo-US coud\'{e} feed stellar spectral library (CFLIB) made available to the astronomical community recently by Valdes et al. (2004) contains spectra of 1273 stars in the spectral region 3460 to 9464 \AA at a high resolution of 1 \AA FWHM and a wide range of spectral types. Cross-checking the reliability of this database is an important and desirable exercise since a number of stars in this database have no known spectral types and a considerable fraction of stars has not so complete coverage in the full wavelength region of 3460-9464 \AA resulting in gaps ranging from a few \AA to several tens of \AA. In this paper, we use an automated classification scheme based on Artificial Neural Networks (ANN) to classify all 1273 stars in the database. In addition, principal component analysis (PCA) is carried out to reduce the dimensionality of the data set before the spectra are classified by the ANN. Most importantly, we have successfully demonstrated employment of a variation of the PCA technique to restore the missing data in a sample of 300 stars out of the CFLIB.Comment: 17 pages, 8 figures PASJ Vol.58, No1 (it will be issued on February 25, 2006