From: To: "jeevacationcrOmnail.corn" Subject: Real Press topics: thoughts? Date: Tue, 28 May 2013 16:11:35 +0000 Attachments: Mount sinai alzheimers.docx > Hi Jeffrey, as said: There is a hierarchy of listing permancy on google: 1. Wikipedia 2. Personal websites 3. Foundation Center. 3. Real press (not press releases) I need the Foundation Center 990 form and I would like to create some real press . (National Review, the Republic or NY Observer-- or whoever you know). Real Press should sit well on the 1st page, just like Huffington. To do this, to get you into the headline, I need something newsworthy. It's not enough to provide partial funding for something. Two things I can think of: • the 10th Anniversary of the Program for Evolutionary Dynamics. • a math model of late Alzheimer's. (Mount Sinai, Harvard) Late Alzheimer's. See rough draft of attached press release that I am sending out. I think there's an opportunity if you are interested, to get Martin Nowak on board with this project? He might already know of it. I could then get you in the headline as being the instigator: the idea would be to get the Program of Evolutionary Dynamics to review Mount Sinai's math model, revise and enhance it. What it is: Mount Sinai, Sage Bionetworks, in collaboration with Harvard, have created a mathematical model of the prevailing genes, gene expression and emanating biological pathways from the DNA of 376 deceased patients with late Alzheimer's. Eric Schadt, PhD, an author of the study and Director of the Icahn Institute for Genomics and \1ultiscale Biology and Chair of the Department of Genetics and Genomic Sciences at Mount Sinai, said "Creating a predictive model of Alzheimer's disease is a landmark achievement, yielding valuable insights into the complex mechanism of the disease." Christopher Gaiteri, PhD, a co-lead author of the study and Senior Scientist at Sage Bionetworks, said, "In the same way that sophisticated predictive mathematical models drive decision making in the global financial markets (what stocks to buy, when to sell, etc.), the field of medical research has begun to rely on network models such as this to derive meaning from vast amounts of patient data, enabling better understanding and treatment of human disease." See full article here: http://www.prweb.com/releases/2013/4/prweb10669467.hun EFTA00655619

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