Alignment of collagen matrices using magnetic nanowires and magnetic barcode readout using first order reversal curves (FORC) (invited)

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Journal of Magnetism and Magnetic Materials, ISSN: 0304-8853

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Anirudh Sharma, Michael D. DiVito, Daniel E. Shore, Andrew D. Block, Katie Pollock, Peter Solheid, Joshua M. Feinberg, Jaime Modiano, Cornelius H. Lam, Allison Hubel, Bethanie J.H. Stadler Show More Hide
Elsevier BV
Materials Science, Physics and Astronomy
article description
Collagen matrices are one form of artificial tissue that has applications in biomimetic organs or tumors, and in fundamental biology. Anatomical organs and tissues are often composed of aligned collagen, and in this study cross-linking nickel magnetic nanowires (MNWs) to collagen allowed a one-step bi-directional alignment of the collagen matrices when processed in a uniform magnetic field. These matrices were analyzed by differential interference contrast (DIC) microscopy, scanning electron microscopy (SEM) and polarized transmittance. The bi-directional alignment was also confirmed by plated, stained arachnoid cells from the blood-brain-barrier (BBB). Arachnoid cells are morphologically sensitive to their extracellular matrix (ECM) environment, and in this study, they were observed to spider out in two distinct directions as predicted by microscopy and transmittance. In fact, MNW-collagen matrices plated with arachnoid-cells are promising for future studies of artificial BBBs. Other cells (here osteosarcoma) have been observed to internalize MNWs, which leads to the possibility of barcoding matrices and cells with distinct signatures, pending a magnetic readout technique. To this aim, mixtures of two different MNW populations were analyzed using first order reversal curves (FORC), and the relative concentrations of the two populations were correctly estimated with negligible error for ratios of 1: 23 and only 7% error for ratios of 1: 115. Together, these studies open a path for magnetic identification of artificial tissues where distinct magnetic labels on matrices and in cells combine for a unique fingerprint.

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