3D pore measurements to improve wound healing

Biomedical engineers at Duke University have developed a method to identify and characterize the voids between particles in any packed structure. By mapping these empty spaces, researchers can better understand how cells and other phenomena respond to their surroundings.

The research content is published Diary of November 21st natural computational science.

This is a common party game. Jelly beans, candy corn, gumballs, and other small objects are packed into containers and people try to guess how many objects are in the jar, with the most accurate guess winning a prize. There are many ways to count objects to get the closest guess, but Tatiana Segura, a professor of biomedical engineering at Duke University, Lindsey Riley, a postdoctoral researcher in Segura’s lab, and founder of Ninjabite Computing Peter Chen has devised a new method. An approach that turned the game on its head.

“We weren’t interested in counting objects. Instead, we were interested in how many open pockets of empty space there were between objects,” Riley explained. “For many systems, understanding that empty space, what we call void space, is actually more important than the object itself.”

Segura’s lab is developing a hydrogel called microparticle annealed particle (MAP) gel. This gel is made up of microparticles that can be injected into a wound to create a scaffold that promotes wound healing. When these particles are packed into a wound or culture dish, they leave empty spaces between the particles where cells can grow. Because cells respond to the microstructures of their surroundings, the researchers wanted a tool that could better understand the shape of the voids in which these cells grow, such as healing wounds or Petri dishes.

“To better understand the factors that drive cell behavior within MAP gels, we needed to find a way to precisely separate the interconnected voids of the scaffold into pockets that could be studied individually,” Segura said. states.

Using techniques from mathematical fields such as graph theory and computational geometry, the team developed LOVAMAP (abbreviation, or local void analysis) using internal axes by particle configuration. LOVAMAP identifies all distinct open pockets (i.e. 3D pores) between particles, and its approach focuses on accuracy by using information embedded in the particle composition itself. These pores contain continuous spaces in which objects can move around, both inside and outside the scaffold.

“Now that we can precisely identify the 3D pores of packed particles, we can understand what is responsible for their shape and connectivity, and which 3D pore shapes are responsible for different cell behaviors. “We can start to understand what’s going on,” Segura said.

“We can do this for any type of packed particle and study how differences in particle shape lead to different 3D pore structures. For example, filled rods are more elongated We find that packed spheres yield the most open structures, resulting in 3D pores.” Because there is more space and ellipsoids are more tightly packed than spheres, they have a higher number of 3D pores per volume. Become. LOVAMAP also tells you how many particles surround each open space. ”

In addition to extending the software to further elucidate patterns between particle types and voids, such as 3D pore-to-pore connectivity, Segura and her lab are using LOVAMAP to discover how cells behave. We will advance research on wound healing by comparing how it is affected by various 3D pores. mapped by software. This knowledge will help optimize materials to promote healing of skin and brain wounds, Segura says.

Although Segura and Riley have no plans to use LOVAMAP to win party games, they are willing to use the software to study the system.

“If you tell us the average diameter of the gumballs and how tightly packed they are, we can tell you with a fair amount of confidence how many 3D pores there are in the bottle,” Riley said. Ta. “You can also tell me the average pore size.”