title: A model that predicts the attachment behavior of Ulva linza zoospores on surface topography.
abstract: A predictive model for the attachment of spores of the green alga Ulva on patterned topographical surfaces was developed using a constant refinement approach. This 'attachment model' incorporated two historical data sets and a modified version of the previously-described Engineered Roughness Index. Two sets of newly-designed surfaces were used to evaluate the effect of two components of the model on spore settlement. Spores attached in fewer numbers when the area fraction of feature tops increased or when the number of distinct features in the design increased, as predicted by the model. The model correctly predicted the spore attachment density on three previously-untested surfaces relative to a smooth surface. The two historical data sets and two new data sets showed high correlation (R(2) = 0.88) with the model. This model may be useful for designing new antifouling topographies.
authors.affiliation: Department of Materials Science and Engineering, University of Florida, Gainsville, FL, USA.
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Long
authors.forename: James F
authors.initials: JF
authors.lastname: Schumacher
authors.forename: Paul A C
authors.initials: PA
authors.lastname: Robinson
authors.forename: John A
authors.initials: JA
authors.lastname: Finlay
authors.forename: Maureen E
authors.initials: ME
authors.lastname: Callow
authors.forename: James A
authors.initials: JA
authors.lastname: Callow
authors.forename: Anthony B
authors.initials: AB
authors.lastname: Brennan
mesh_terms: D018441:Biofilms / Q000254:growth & development; D057219:Biofouling; D002448:Cell Adhesion; D000460:Chlorophyta / Q000502:physiology; D008386:Marine Biology; D008855:Microscopy, Electron, Scanning / Q000379:methods; D008954:Models, Biological; D012044:Regression Analysis; D013170:Spores / Q000378:metabolism*; D013499:Surface Properties; D044445:Ulva / Q000378:metabolism*; D014871:Water Microbiology