Medical Research Award Goes to Adult Stem Cell Scientists at a Kansas Not-for-Profit Organization
News Mar 21, 2008
Scientists at the Bio-Communications Research Institute (BCRI), a division of The Center for the Improvement of Human Functioning International (CIHFI), received a prestigious award for a scientific article about its recent stem cell discovery.
The scientific journal article entitled "Endometrial regenerative cells: A novel stem cell population" received BioMed Central's Research Article of the Year in Medicine Award sponsored by Microsoft Research.
Dr. Xiaolong Meng, the lead author of the article and Associate Director of BCRI was in London, England yesterday to receive the award at the Royal Society of Medicine alongside Tom Ichim, co-author and CEO of MediStem Laboratories, Inc. The paper was published in November 2007 in the Journal of Translational Medicine.
The award recognizes excellence in research that has been made universally accessible through open access publication in one of BioMed Central's peer reviewed scientific journals. The article is freely available at http://www.translational-medicine.com/content/5/1/57.
BCRI led the research team, composed of U.S. and Canadian scientists who identified and characterized a new type of stem cell that can be reproducibly isolated from menstrual blood collected from healthy women.
"We are extremely proud of the international recognition our scientists and collaborators are receiving for the discovery of this new type of stem cell," said Dr. Neil Riordan, co-author and President of MediStem. "We believe that these adult stem cells, which we have termed endometrial regenerative cells (ERC), offer a novel alternative to embryonic stem cells which are fraught with scientific and ethical issues."
"The ERC population appears to be superior to other stem cell types. These cells do not require matching with the recipient, they home to areas of injury or tissue damage, and they can differentiate into most of the tissue types found in the body," said Dr. Xiaolong Meng.
Scientists have used machine learning to train computers to see parts of the cell the human eye cannot easily distinguish. Using 3D images of fluorescently labeled cells, the research team taught computers to find structures inside living cells without fluorescent labels, using only black and white images generated by an inexpensive technique known as brightfield microscopy.READ MORE
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