University of Kiel

About: University of Kiel is a education organization based out in Kiel, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 27816 authors who have published 57114 publications receiving 2061802 citations. The organization is also known as: Christian Albrechts University & Christian-Albrechts-Universität zu Kiel.

Assessing the biocompatibility of NiTi shape memory alloys used for medical applications.

Abstract: The present paper reviews aspects related to the biocompatibility of NiTi shape memory alloys used for medical applications. These smart metallic materials, which are characterised by outstanding mechanical properties, have been gaining increasing importance over the last two decades in many minimal invasive surgery and diagnostic applications, as well as for other uses, such as in orthodontic appliances. Due to the presence of high amounts of Ni, the cytotoxicity of such alloys is under scrutiny. In this review paper we analyse work published on the biocompatibility of NiTi alloys, considering aspects related to: (1) corrosion properties and the different methods used to test them, as well as specimen surface states; (2) biocompatibility tests in vitro and in vivo; (3) the release of Ni ions. It is shown that NiTi shape memory alloys are generally characterised by good corrosion properties, in most cases superior to those of conventional stainless steel or Co–Cr–Mo-based biomedical materials. The majority of biocompatibility studies suggest that these alloys have low cytotoxicity (both in vitro and in vivo) as well as low genotoxicity. The release of Ni ions depends on the surface state and the surface chemistry. Smooth surfaces with well-controlled structures and chemistries of the outermost protective TiO2 layer lead to negligible release of Ni ions, with concentrations below the normal human daily intake.

Genomic Selection Using Low-Density Marker Panels

Abstract: Genomic selection (GS) using high-density single-nucleotide polymorphisms (SNPs) is promising to improve response to selection in populations that are under artificial selection. High-density SNP genotyping of all selection candidates each generation, however, may not be cost effective. Smaller panels with SNPs that show strong associations with phenotype can be used, but this may require separate SNPs for each trait and each population. As an alternative, we propose to use a panel of evenly spaced low-density SNPs across the genome to estimate genome-assisted breeding values of selection candidates in pedigreed populations. The principle of this approach is to utilize cosegregation information from low-density SNPs to track effects of high-density SNP alleles within families. Simulations were used to analyze the loss of accuracy of estimated breeding values from using evenly spaced and selected SNP panels compared to using all high-density SNPs in a Bayesian analysis. Forward stepwise selection and a Bayesian approach were used to select SNPs. Loss of accuracy was nearly independent of the number of simulated quantitative trait loci (QTL) with evenly spaced SNPs, but increased with number of QTL for the selected SNP panels. Loss of accuracy with evenly spaced SNPs increased steadily over generations but was constant when the smaller number individuals that are selected for breeding each generation were also genotyped using the high-density SNP panel. With equal numbers of low-density SNPs, panels with SNPs selected on the basis of the Bayesian approach had the smallest loss in accuracy for a single trait, but a panel with evenly spaced SNPs at 10 cM was only slightly worse, whereas a panel with SNPs selected by forward stepwise selection was inferior. Panels with evenly spaced SNPs can, however, be used across traits and populations and their performance is independent of the number of QTL affecting the trait and of the methods used to estimate effects in the training data and are, therefore, preferred for broad applications in pedigreed populations under artificial selection.