Jose Figueres (1906-): A Study in Latin American Politics

It is the purpose of this study to examine this modern Latin American leader, investigating the conditions which produced the man and his movement, the cause which motivated him, his ideals, methods, actions and achievements. Finally, an attempt will be made to determine the significance of his thought and his contributions-- in his own country and in international affairs--- and to place him in the recent history of Latin America

Improving Gene-finding in Chlamydomonas reinhardtii:GreenGenie2

<p>Abstract</p> <p>Background</p> <p>The availability of whole-genome sequences allows for the identification of the entire set of protein coding genes as well as their regulatory regions. This can be accomplished using multiple complementary methods that include ESTs, homology searches and <it>ab initio </it>gene predictions. Previously, the Genie gene-finding algorithm was trained on a small set of <it>Chlamydomonas </it>genes and shown to improve the accuracy of gene prediction in this species compared to other available programs. To improve <it>ab initio </it>gene finding in <it>Chlamydomonas</it>, we assemble a new training set consisting of over 2,300 cDNAs by assembling over 167,000 <it>Chlamydomonas </it>EST entries in GenBank using the EST assembly tool PASA.</p> <p>Results</p> <p>The prediction accuracy of our cDNA-trained gene-finder, GreenGenie2, attains 83% sensitivity and 83% specificity for exons on short-sequence predictions. We predict about 12,000 genes in the version <it>v3 Chlamydomonas </it>genome assembly, most of which (78%) are either identical to or significantly overlap the published catalog of <it>Chlamydomonas </it>genes <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. 22% of the published catalog is absent from the GreenGenie2 predictions; there is also a fraction (23%) of GreenGenie2 predictions that are absent from the published gene catalog. Randomly chosen gene models were tested by RT-PCR and most support the GreenGenie2 predictions.</p> <p>Conclusion</p> <p>These data suggest that training with EST assemblies is highly effective and that GreenGenie2 is a valuable, complementary tool for predicting genes in <it>Chlamydomonas reinhardtii</it>.</p

Computational Characterization and Prediction of Estrogen Receptor Coactivator Binding Site Inhibitors

Many carcinogens have been shown to cause tissue specific tumors in animal models. The mechanism for this specificity has not been fully elucidated and is usually attributed to differences in organ metabolism. For heterocyclic amines, potent carcinogens that are formed in well-done meat, the ability to either bind to the estrogen receptor and activate or inhibit an estrogenic response will have a major impact on carcinogenicity. Here we describe our work with the human estrogen receptor alpha (hERa) and the mutagenic/carcinogenic heterocyclic amines PhIP, MeIQx, IFP, and the hydroxylated metabolite of PhIP, N2-hydroxy-PhIP. We found that PhIP, in contrast to the other heterocyclic amines, increased cell-proliferation in MCF-7 human breast cancer cells and activated the hERa receptor. We show mechanistic data supporting this activation both computationally by homology modeling and docking, and by NMR confirmation that PhIP binds with the ligand binding domain (LBD). This binding competes with estradiol (E2) in the native E2 binding cavity of the receptor. We also find that other heterocyclic amines and N2-hydroxy-PhIP inhibit ER activation presumably by binding into another cavity on the LBD. Moreover, molecular dynamics simulations of inhibitory heterocyclic amines reveal a disruption of the surface of the receptor protein involved with protein-protein signaling. We therefore propose that the mechanism for the tissue specific carcinogenicity seen in the rat breast tumors and the presumptive human breast cancer associated with the consumption of well-done meat maybe mediated by this receptor activation

Predictive Assay For Cancer Targets

Early detection of cancer is a key element in successful treatment of the disease. Understanding the particular type of cancer involved, its origins and probable course, is also important. PhIP (2-amino-1-methyl-6 phenylimidazo [4,5-b]pyridine), a heterocyclic amine produced during the cooking of meat at elevated temperatures, has been shown to induce mammary cancer in female, Sprague-Dawley rats. Tumors induced by PhIP have been shown to contain discreet cytogenetic signature patterns of gains and losses using comparative genomic hybridization (CGH). To determine if a protein signature exists for these tumors, we are analyzing expression levels of the protein products of the above-mentioned tumors in combination with a new bulk protein subtractive assay. This assay produces a panel of antibodies against proteins that are either on or off in the tumor. Hybridization of the antibody panel onto a 2-D gel of tumor or control protein will allow for identification of a distinct protein signature in the tumor. Analysis of several gene databases has identified a number of rat homologs of human cancer genes located in these regions of gain and loss. These genes include the oncogenes c-MYK, ERBB2/NEU, THRA and tumor suppressor genes EGR1 and HDAC3. The listed genes have been shown to be estrogen-responsive, suggesting a possible link between delivery of bio-activated PhIP to the cell nucleus via estrogen receptors and gene-specific PhIP-induced DNA damage, leading to cell transformation. All three tumors showed similar silver staining patterns compared to each other, while they all were different than the control tissue. Subsequent screening of these genes against those from tumors know to be caused by other agents may produce a protein signature unique to PhIP, which can be used as a diagnostic to augment optical and radiation-based detection schemes