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Reef-building crustose coralline algae (CCA) are known to facilitate the settlement and metamorphosis of scleractinian coral larvae. In recent decades, CCA coverage has fallen globally and degrading environmental conditions continue to reduce coral survivorship, spurring new restoration interventions to rebuild coral reef health. In this study, naturally produced chemical compounds (metabolites) were collected from two pantropical CCA genera to isolate and classify those that induce coral settlement. In experiments using four ecologically important Caribbean coral species, we demonstrate the applicability of extracted, CCA-derived metabolites to improve larval settlement success in coral breeding and restoration efforts. Tissue-associated CCA metabolites induced settlement of one coral species,Orbicella faveolata, while metabolites exuded by CCA (exometabolites) induced settlement of three species:Acropora palmata,Colpophyllia natansandOrbicella faveolata. In a follow-up experiment, CCA exometabolites fractionated and preserved using two different extraction resins induced the same level of larval settlement as the unfractionated positive control exometabolites. The fractionated CCA exometabolite pools were characterized using liquid chromatography tandem mass spectrometry, yielding 145 distinct molecular subnetworks that were statistically defined as CCA-derived and could be classified into 10 broad chemical classes. Identifying these compounds can reveal their natural prevalence in coral reef habitats and facilitate the development of new applications to enhance larval settlement and the survival of coral juveniles. 

Abstract This work introduces a computational method for designing bone scaffolds for maximum bone growth. A mechanobiological model of bone adaptation is used to compute the bone growth, taking into account the shape of the defect, the applied loading, and the existing density distribution of the bone in which the scaffold has been implanted. Numerical homogenization and a geometry projection technique are used to efficiently obtain surrogates of the effective elastic and diffusive properties of the scaffold as a function of the scaffold design and the bone density. These property surrogates are in turn used to perform bone adaptation simulations of the scaffold–bone system for a sampling of scaffold designs. Surrogates of the bone growth in the scaffold at the end of the simulated time and of the strain energy of the scaffold at implantation time are subsequently constructed from these simulations. Using these surrogates, we optimize the design of a scaffold implanted in a rabbit femur to maximize volume bone growth into the scaffold while ensuring a minimum stiffness at implantation. The results of the optimization demonstrate the effectiveness of the proposed method by showing that maximizing bone growth with a constraint on structural compliance renders scaffold designs with better bone growth than what would be obtained by only minimizing compliance.