UC Irvine

Background

Adipose tissue is an easily accessible source of stem and progenitor cells that offers exciting promise as an injectable autologous therapeutic for regenerative applications. Mechanical processing is preferred over enzymatic digestion, and the most common method involves shuffling lipoaspirate between syringes and filtering to produce nanofat. Although nanofat has shown exciting clinical results, the authors hypothesized that new device designs could enhance recovery of stem/progenitor cells through optimization of fluid dynamics principles, integration, and automation.

Methods

The authors designed and fabricated the emulsification and micronization device (EMD) and the filtration device (FD) to replace the manual nanofat procedures. Using human lipoaspirate samples, the EMD and the FD were optimized and compared to traditional nanofat using ex vivo measurements of cell number, viability, and percentage of mesenchymal stem cells and endothelial progenitor cells.

Results

The EMD produced results statistically similar to nanofat, and these findings were confirmed for a cohort of diabetic patients. Combining the FD with the EMD was superior to manually filtered nanofat in terms of both recovered cell percentages (>1.5-fold) and numbers (two- to three-fold). Differences were statistically significant for total mesenchymal stem cells and a DPP4 + /CD55 + subpopulation linked to improved wound healing in diabetes.

Conclusions

The new EMD and the FD improved mechanical processing of human lipoaspirate in terms of mesenchymal stem cell enrichment and number compared to traditional nanofat. Future work will seek to investigate the wound healing response both in vitro and in vivo, and to refine the technology for automated operation within clinical settings.

Clinical relevance statement

The new devices improved mechanical processing of human lipoaspirate in terms of stem cell enrichment and number compared to traditional methods. Future work will seek to validate wound healing response and refine the technology for automated operation within clinical settings.