From MIT’s Labs

Engineering Tissue with Blood Vessels
Lab-grown muscle gets nourishment

Results: Researchers in Robert Langer’s lab have coaxed skeletal-muscle tissue growing in a lab dish to develop its own network of blood vessels. When the researchers inserted the small piece of tissue into the abdominal muscle of a mouse, they found that 41 percent of the engineered tissue’s blood vessels connected with the mouse’s vascular system. After two weeks, twice as much of the engineered vascularized tissue survived as did control tissue without blood vessels.

Why It Matters: One of the biggest problems in tissue engineering is keeping cells alive after they’ve been implanted in the body. Researchers have had success implanting very thin layers of engineered tissue like skin, because they can use blood vessels from underlying tissue to deliver oxygen and nutrients and get rid of waste. Thicker engineered tissues like muscle, however, tend not to live long because they lack their own sets of vessels that deliver nourishment. Langer and his colleagues have taken an important step toward solving this problem: for the first time, they have gotten blood vessels to grow in a patch of engineered tissue before implanting it in the body. While the researchers focused on muscle tissue, a similar approach could work for other tissues that have a lot of blood vessels, such as liver or heart tissue.

Methods: Langer and his colleagues grew vascularized muscle tissue on a biodegradable polymer scaffold, which measured 25 square millimeters by one millimeter thick, by seeding it with three different types of cells: mouse muscle stem cells; human endothelial cells, which form blood vessels; and mouse fibroblasts, which give rise to connective tissue and smooth-muscle cells (the researchers hypothesized that these cells would stabilize the vessels). The researchers let the cells grow for several weeks. In one experiment, they removed part of a mouse’s abdominal muscle and replaced it with the tissue-covered scaffold. After two weeks, they removed the tissue and analyzed it. – By Lisa Scanlon

Source: Levenberg, S., et al. 2005. Engineered vascu- larized skeletal muscle tissue. Nature Biotechnology 23:879-884.

Virtual Expressions
Computer graphics technique transfers facial expressions

Results: Researchers from MIT and Mitsubishi Electric Research Laboratories have created a computer model that allows them to capture from video the facial expression, speech-related mouth shapes, and other key identifying features of one person’s face and digitally transfer a select combination of those attributes to video of another person’s face. In one example, the researchers took a surprised look from one person and the mouth position from a second person and placed those two features on the face of a third person filmed with a blank expression; in the resulting image, she looked surprised.

Why It Matters: Making digital facial movements look natural is a major challenge in computer animation. These new tools could be used to give computer-generated characters in films and video games more-realistic faces, based on the movements made by live actors. Existing techniques, such as those used in movies like The Polar Express, typically capture the motion of a live actor using reflective markers stuck to the actor’s body and face. The MIT method can capture motion and expressions from a video recording of the actor without the need for markers, making this kind of computer animation potentially simpler and cheaper.

Methods: Daniel Vlasic of MIT and his colleagues created their model using data from 3-D scans of 31 subjects making different facial expressions and mouthing different sounds. They then filmed subjects performing–singing, for instance. They tracked the facial movements of the subjects and fed that data into the model. The model used that data to change the expressions or mouth movements of a second person, and the researchers imposed those changes on video of the person. The model allowed the researchers to manipulate a subject’s attributes, such as a smile or identifying features, independently of one another, so that they could transfer, say, a smile to a person without changing that person’s identity. – By Corie Lok

Source: Vlasic, D., et al. 2005. Face transfer with multilinear models. ACM Transactions on Graphics 24:426-433.