Featured Research

from universities, journals, and other organizations

Small step towards growing tissue in the lab

Date:
March 19, 2014
Source:
University of Adelaide
Summary:
Mathematicians have devised a method for identifying how cell clusters have formed by analyzing an image of the cluster. Their modelling tool will be useful in helping biologists and tissue engineers to move towards growing human tissue such as liver in the laboratory.

University of Adelaide mathematicians have devised a method for identifying how cell clusters have formed by analysing an image of the cluster.

Published in the Journal of Theoretical Biology, their mathematical modelling tool will be useful in helping biologists and tissue engineers to move towards growing human tissue such as liver in the laboratory.

"When any tissue or organ develops, the cells have to organise themselves into the correct structure," says Dr Edward Green, researcher in the University's School of Mathematical Sciences. "This self-organisation process is important in regenerative medicine where scientists are trying to grow tissues in the laboratory. Getting the right structure is key to ensuring the tissue is viable and functional.

"We know that the control of the organisation process is very complex, and it's still not well understood, which is why we're using modelling to explore simple examples like cluster formation. We looked at two main ways of producing cell clusters -- by attraction through chemical and other signals and by proliferation (cells dividing).

"The idea behind our research is that, for any particular cell type, if you are trying to get cells to organise in certain ways, you need to know how they are behaving. We show how you might be able to analyse this using a combination of models and image analysis."

The paper introduces a quantitative measure of the pattern of clustering from an image, producing a statistic called the 'pair correlation function' which shows the relationship between cells.

"The two clustering mechanisms produce different patterns. In some cases you can spot the differences simply by looking, but the pair correlation function allows you to distinguish them, even when you can't see any obvious differences between the pictures by eye," says Dr Green.

They validated their mathematical model experimentally using cells with known clustering mechanisms in collaboration with Queensland University of Technology.

"Our tool gives a basic understanding of the process in clustering," says co-author Dr Ben Binder, Senior Lecturer in the School of Mathematical Sciences. "It will be useful in assessing what factors may be used to enhance the process of growing cells.

"Next steps will be feeding experimental data back into the model to simulate biological processes. Instead of running lengthy and expensive experiments, we can look at the potential effects of different factors through the computer."


Story Source:

The above story is based on materials provided by University of Adelaide. Note: Materials may be edited for content and length.


Journal Reference:

  1. D.J.G. Agnew, J.E.F. Green, T.M. Brown, M.J. Simpson, B.J. Binder. Distinguishing between mechanisms of cell aggregation using pair-correlation functions. Journal of Theoretical Biology, 2014; DOI: 10.1016/j.jtbi.2014.02.033

Cite This Page:

University of Adelaide. "Small step towards growing tissue in the lab." ScienceDaily. ScienceDaily, 19 March 2014. <www.sciencedaily.com/releases/2014/03/140319093830.htm>.
University of Adelaide. (2014, March 19). Small step towards growing tissue in the lab. ScienceDaily. Retrieved July 28, 2014 from www.sciencedaily.com/releases/2014/03/140319093830.htm
University of Adelaide. "Small step towards growing tissue in the lab." ScienceDaily. www.sciencedaily.com/releases/2014/03/140319093830.htm (accessed July 28, 2014).

Share This




More Health & Medicine News

Monday, July 28, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Trees Could Save More Than 850 Lives Each Year

Trees Could Save More Than 850 Lives Each Year

Newsy (July 27, 2014) A national study conducted by the USDA Forest Service found that trees collectively save more than 850 lives on an annual basis. Video provided by Newsy
Powered by NewsLook.com
Google's Next Frontier: The Human Body

Google's Next Frontier: The Human Body

Newsy (July 27, 2014) Google is collecting genetic and molecular information to paint a picture of the perfectly healthy human. Video provided by Newsy
Powered by NewsLook.com
What's To Blame For Worst Ebola Outbreak In History?

What's To Blame For Worst Ebola Outbreak In History?

Newsy (July 27, 2014) A U.S. doctor has tested positive for the deadly Ebola virus, as the worst-ever outbreak continues to grow. Video provided by Newsy
Powered by NewsLook.com
Losing Sleep Leaves You Vulnerable To 'False Memories'

Losing Sleep Leaves You Vulnerable To 'False Memories'

Newsy (July 27, 2014) A new study shows sleep deprivation can make it harder for people to remember specific details of an event. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:
from the past week

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins