@article {19622, title = {Personalized advanced therapies for skeletal tissue regeneration}, journal = {Ci{\^e}ncia 2018 - Encontro com a Ci{\^e}ncia e Tecnologia em Portugal}, year = {2018}, month = {2018-07-02 00:00:00}, address = {Lisbon, Portugal}, abstract = {

Tissue and organ repair still represents a clinical challenge. Tissue engineering and regenerative medicine (TERM) is an emerging field focused on the development of alternative therapies for tissue/organ repair. Regeneration of skeletal tissues is among the most promising research areas, providing a broad spectrum of potential clinical applications.

In bone and cartilage, irreversible tissue defects are caused by aging, trauma, tumors, or developmental abnormalities. Most of the currently available therapies for recovering the tissues affected by those diseases are not effective in recovering totally the function of these tissues [1]. As a result, those conditions result in significantly reduced patient quality-of-life and high socio-economical costs. Therefore, there is the urgent need for developing new strategies capable to efficiently repair bone and cartilage tissues. For that, nanofibrous meshes biofunctionalized by the immobilization of autologous bioactive molecules will induce the chondrogenic and osteogenic differentiation of human bone marrow mesenchymal stem cells (hBM-MSCs), enabling designing highly effective regenerative therapies.

Herein, it is demonstrated that immobilized antibodies (single or multiple) allows for an efficient binding of the corresponding proteins. Our biological results indicate that the biofunctional systems are able to promote the chondrogenesis or osteogenesis\  of hBMSCs, being more effective than other common differentiation methods.

The proposed biofunctional systems can act as skeletal tissue engineering devices, operating as a synthetic support for hBMSCs growth, differentiation and delivery at injury sites.

}, keywords = {Biofunctionalization; Skeletal Tissue Regeneration, Nanofibrous substrate}, author = {Casanova, M. R. and Reis, R. L. and Martins, A. and Neves, N. M.} }