A primer of statistical methods for correlating parameters and properties of electrospun poly(L-lactide) scaffolds for tissue engineering-PART 2: Regression

This two-articles series presents an in-depth discussion of electrospun poly-l-lactide scaffolds for tissue engineering by means of statistical methodologies that can be used, in general, to gain a quantitative and systematic insight about effects and interactions between a handful of key scaffold properties (Ys) and a set of process parameters (Xs) in electrospinning. While Part-1 dealt with the DOE methods to unveil the interactions between Xs in determining the morphomechanical properties (ref. Y1-4), this Part-2 article continues and refocuses the discussion on the interdependence of scaffold properties investigated by standard regression methods. The discussion first explores the connection between mechanical properties (Y-4) and morphological descriptors of the scaffolds (Y1-3) in 32 types of scaffolds, finding that the mean fiber diameter (Y-1) plays a predominant role which is nonetheless and crucially modulated by the molecular weight (MW) of PLLA. The second part examines the biological performance (Y-5) (i.e. the cell proliferation of seeded bone marrow-derived mesenchymal stromal cells) on a random subset of eight scaffolds vs. the mechanomorphological properties (Y1-4). In this case, the featured regression analysis on such an incomplete set was not conclusive, though, indirectly suggesting in quantitative terms that cell proliferation could not fully be explained as a function of considered mechanomorphological properties (Y1-4), but in the early stage seeding, and that a randomization effects occurs over time such that the differences in initial cell proliferation performance (at day 1) is smeared over time. The findings may be the cornerstone of a novel route to accrue sufficient understanding and establish design rules for scaffold biofunctional vs. architecture, mechanical properties, and process parameters. (c) 2014 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 103A: 103-114, 2015.