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New Human Neural Stem Cells Could Boost Tissue Engineering

Article-New Human Neural Stem Cells Could Boost Tissue Engineering

The new technique can generate rapidly-differentiating human neural stem cells that could be used to build three-dimensional models of human tissue and other tissue engineering applications.

Kristopher Sturgis

This photo shows human induced neural stem cell lines (red) grown in co-culture with skeletal muscle (green) and cell nuclei visualized by blue DAPI staining.

A new technique for tissue engineering has been developed by researchers out of Tufts University in Massachusetts that could pave the way for the development of three dimensional models of the human brain and other organs. David Kaplan, PhD, professor in the department of biomedical engineering at Tufts University and one of the lead authors on the work, said that the technique could be used to develop models for future drug studies.

"Because these neural stem cells differentiate quite rapidly and maintain their neuronal characteristics, even when cultured with other cell types, they can be utilized for applications like drug screens and to generate complex innervated tissues," Kaplan said. "We hope to utilize this human 3-D brain model for various applications including the development of disease models, as well as future drug studies."

The technique involves converting human fibroblasts and adipose-derived stem cells into human induced neural stem cell lines that eventually acquire the features of active neurons, all in as little as four days time. While their research isn't the first to generate neural stem cell lines from fibroblasts and adipose-derived stem cells, their new technique does accomplish the feat faster and more efficiently, as all other previous methods typically take around four weeks.

"Basically you use a starting cell type that is easy to harvest from humans," Kaplan said. "In this case we used cells derived from either skin or fat tissue, and then we genetically modify them and culture them using a very specific technique. The procedure results in the generation of induced neural stem cells, which can then be utilized for multiple downstream applications."

Tissue engineering techniques continue to evolve as researchers explore new avenues that could unlock innovative and potentially game changing discoveries. Earlier this year researchers from Harvard created a mathematical model for 4-D printed objects that could have a significant impact on tissue engineering and bioprinting techniques. Elsewhere, last fall researchers from Penn State University created promising new citrate-based biomaterials that could serve as biodegradable materials for nerve and blood vessel regeneration.

Both projects represent the growing focus on new methods and materials for bioprinting and tissue engineering research. In their latest study, Kaplan and his colleagues were able to create a working three-dimensional model of the human brain and actually observed neurons firing back and forth. However, the truly novel element of the research is the ability to generate cells more quickly, which could lead to the development of larger, more sustainable three dimensional models of other organs.

"In general, 3-D models for human organs are specifically designed to mimic their in vivo counterparts," Kaplan said. "While our specific brain design may not necessarily be useful for other organ models, our group can generate other 3-D models of tissue and organs."

As the group moves forward with their research, Kaplan said they hope the research can be used as a tool to better understand the brain and its surrounding tissue, and eventually generate models of other human organs for similar research.

"Moving forward, we hope to utilize this technology as a tool to understand various disorders of both the brain and innervated peripheral tissues," he said. "We think that this technique could greatly impact future research in that it will allow for the generation of relevant human models of multiple innervated tissue types."

Kristopher Sturgis is a contributor to Qmed.


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