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A primer of statistical methods for correlating parameters and properties of electrospun poly( l ‐lactide) scaffolds for tissue engineering—PART 2: Regression
Author(s) -
Seyedmahmoud Rasoul,
Mozetic Pamela,
Rainer Alberto,
Giannitelli Sara Maria,
Basoli Francesco,
Trombetta Marcella,
Traversa Enrico,
Licoccia Silvia,
Rinaldi Antonio
Publication year - 2015
Publication title -
journal of biomedical materials research part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.849
H-Index - 150
eISSN - 1552-4965
pISSN - 1549-3296
DOI - 10.1002/jbm.a.35183
Subject(s) - tissue engineering , scaffold , electrospinning , materials science , regression analysis , biomedical engineering , biological system , computer science , composite material , biology , engineering , machine learning , polymer
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. Y 1–4 ), 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 ( Y 1–3 ) 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 ( Y 1–4 ). 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 ( Y 1–4 ), 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. © 2014 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 103A: 103–114, 2015.