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New software is under development that doctors hope will help them identify brain tumours in children that will grow aggressively.
Some brain tumours in children remain benign and doctors choose not to operate. But a small percentage of those will suddenly start to grow aggressively.
Doctors have not identified what triggers that aggressive tumour growth, despite the vast array of data they hold on their child patients – demographic, environmental, genetic and clinical data, as well as images such as MRI and CAT scans of the developing tumours.
Read more: Software for Solving Life-Threatening Medical Problems
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Scientists at the University of North Carolina at Chapel Hill School of Medicine and the University of California, San Francisco have developed and experimentally tested a technique to predict new target diseases for existing drugs.
The researchers developed a computational method that compares how similar the structures of all known drugs are to the naturally occurring binding partners -- known as ligands -- of disease targets within the cell. In a study published this week in Nature, the scientists showed that the method predicts potential new uses as well as unexpected side effects of approved drugs.
Read more: Study points to new uses, unexpected side effects of already-existing drugs
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Mathematicians at Michigan Technological University have developed powerful new tools for winnowing out the genes behind some of humanity’s most intractable diseases.
With one, they can cast back through generations to pinpoint the genes behind inherited illness. With another, they have isolated 11 variations within genes—called single nucleotide polymorphisms, SNPs or "snips"—associated with type 2 diabetes.
Read more: Eleven Genetic Variations Linked To Type 2 Diabetes
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by Daniel J. Vargas
AUSTIN, Texas – A team of scientists, led by a biomedical engineer at The University of Texas at Austin, have demonstrated – for the first time – that mathematical models created from data obtained by a recently developed technology called DNA microarrays, can be used to correctly predict previously unknown cellular mechanisms. This brings biologists a step closer to one day being able to understand and control the inner workings of the cell as readily as NASA engineers plot the trajectories of spacecraft today.
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by Colin Poitras
Using a mathematical model to predict population trends based on ancient coin hoards, a UConn biologist and a Stanford University historian have concluded that the population of ancient Rome was smaller than sometimes suggested.
Although the first century BC in Italy has been extensively studied, and much is known about the great figures of the era, including Cicero, Caesar, Virgil, and Horace, some basic facts – such as the approximate population size of the late Roman Republic – remain the subject of intense debate.
Read more: Buried Coins May Help Solve Mystery of Ancient Roman Population
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The human brain is made up of 100 billion neurons — live wires that must be kept in delicate balance to stabilize the world’s most magnificent computing organ. Too much excitement and the network will slip into an apoplectic, uncomprehending chaos. Too much inhibition and it will flatline. A new mathematical model describes how the trillions of interconnections among neurons could maintain a stable but dynamic relationship that leaves the brain sensitive enough to respond to stimulation without veering into a blind seizure.
Read more: New model suggests how the brain might stay in balance