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Posts Tagged ‘cancer’

Arthur Lander on modeling normal versus rampant cell growth

How do the basics of what goes on in our tissues during normal development give us a better understanding of what happens when things go awry in the malignant disease state? In this clip, Arthur Lander of the University of California, Irvine, speaks about how biological systems use control and regulation to achieve or maintain desired outcomes in growth and development. Controlled growth is not only essential for biological development, but also plays an important role in preventing the kinds of out-of-control growth we see in certain cancers.  Lander’s group builds mathematical models that mimic real tissues in order to understand normal growth control. Using such models, his lab is determining how morphogenesis is achieved by turning growth on and off in certain desired locations via regulated feedback between growing cells and those that produce tissues.

Watch the video to learn more!

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Using math to analyze movement of cells, organisms, and disease

Philadelphia, PA—A few recent SIAM journal papers you should know about:

  Traveling waves model tumor invasion

Cell migration, which is involved in wound healing, cancer and tumor growth, and embryonic growth and development, has been a topic of interest to mathematicians and biologists for decades.

In a paper published recently in the SIAM Journal on Applied Dynamical Systems, authors Kristen Harley, Peter van Heijster, Robert Marangell, Graeme Pettet, and Martin Wechselberger study a model describing cell invasion through directional outgrowth or movement in the context of malignant tumors, in particular, melanoma or skin cancer. Tumor cells move up a gradient, based on the presence of a chemical or chemoattractant – this process is called haptotaxis. Receptors on the exterior of cell walls detect and allow passing of the chemoattractant. Based on the locations of these receptors, cells determine the most favorable migration direction. Read the rest of this entry »

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ICIAM video: math modeling in disease dynamics

At ICIAM 2011, speakers from varying backgrounds, including Professors Patrick Nelson, Kerry Landman, and Avner Friedman, and graduate student Irina Kareva, outlined the many aspects of mathematical modeling in disease progression and dynamics, emphasizing the connections between mathematics and medical science.

Watch a video that highlights the applications of math modeling in diabetes, cancer and wound healing:

You can also read about Avner Friedman’s other research—on math modeling for cancer treatments here.

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Mathematical Models for Breast Cancer Detection with Microwave Tomography

The most popular method of breast cancer detection today is X-ray mammography, which takes images of a compressed breast by low-dose ionizing radiation. However, there are several disadvantages to using X-rays for breast cancer screening, chief among them being the invasivity of radiation and the high costs, which limit their wide use and can deter women from getting them. In addition, depending on the age of the patient and tissue density, X-ray mammograms often result in false positives and negatives.

Microwave tomography can provide a cheaper and less risky alternative to X-ray mammography. In a paper published today in the SIAM Journal on Applied Mathematics, the authors describe a mathematical model for imaging tumors in the breast using microwave tomography. Read the rest of this entry »

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