Magnetic Resonance Imaging of Chondrocytes Labeled with Superparamagnetic Iron Oxide Nanoparticles in Tissue-Engineered Cartilage

The distribution of cells within tissue-engineered constructs is difficult to study through nondestructive means, such as would be required after implantation. However, cell labeling with iron-containing particles may prove to be a useful approach to this problem, because regions containing such labeled cells have been shown to be readily detectable using magnetic resonance imaging (MRI). In this study, we used the Food and Drug Administration–approved superparamagnetic iron oxide (SPIO) contrast agent Feridex in combination with transfection agents to label chondrocytes and visualize them with MRI in two different tissue-engineered cartilage constructs. Correspondence between labeled cell spatial location as determined using MRI and histology was established. The SPIO-labeling process was found not to affect the phenotype or viability of the chondrocytes or the production of major cartilage matrix constituents. We believe that this method of visualizing and tracking chondrocytes may be useful in the further development of tissue engineered cartilage therapeutics

What is the "golden standard" for assessing population-based interventions?—problems of dilution bias

OBJECTIVES—To identify different types of dilution bias in population-based interventions and to suggest measures for handling these methodological problems.
DESIGN—Literature review plus analysis of data from a population-based intervention against cardiovascular disease in a Swedish municipality.
MAIN RESULTS—The effects of an intervention on mortality and morbidity were much more diluted by non-intervening factors, dissemination to areas outside the intervention area, social diffusion, population mobility and time than by using intermediate outcome measures.
CONCLUSIONS—Theoretically, changes in scientifically well documented risk factors, for example, intermediate outcome measures, should be preferred to using morbidity or mortality as outcome measures.


Keywords: population-based intervention