Aberration correction during real time in vivo imaging of bone marrow with sensorless adaptive optics confocal microscope

Quantitative analyses of matrices, osteoblasts, and osteoclasts during bone remodeling using an in vitro system

INTRODUCTION

Bone remodeling plays a central role in the maintenance of bone homeostasis. Our group has established an in vitro system by which the cellular events during bone remodeling can be observed longitudinally. This study used this system to quantitatively analyze osteoblasts, osteoclasts, and matrices to elucidate their temporal changes and correlations.

MATERIALS AND METHODS

Osteoblasts from EGFP mice were cultured to form calcified nodules, followed by co-culture with bone marrow macrophages from Tnfrsf11a^Cre/+ x Ai14 mice for 3 weeks (resorption phase). Then cells were cultured with osteoblast differentiation medium for 3 weeks (formation phase). The same sites were observed weekly using 2-photon microscopy. Matrices were detected using second harmonic generation. Parameters related to matrices, osteoblasts, and osteoclasts were quantified and statistically analyzed.

RESULTS

Resorption and replenishment of the matrix were observed at the same sites by 2 photon microscopy. Gross quantification revealed that matrix and osteoblast parameters decreased in the resorption phase and increased in the formation phase, while osteoclast parameters showed the opposite pattern. When one field of view was divided into 16 regions of interest (ROIs) and correlations between parameters were analyzed in each ROI, decreased and increased matrix volumes were moderately correlated. Parameters of matrices and osteoblasts, and those of matrices and osteoclasts exhibited moderate correlations, while those of osteoblasts and osteoclasts were only weakly correlated.

CONCLUSION

Several correlations between cells and matrix during remodeling were demonstrated quantitatively. This system may be a powerful tool for the research of bone remodeling.

Improving Retinal Image Quality Using Registration with an SIFT Algorithm in Quasi-Confocal Line Scanning Ophthalmoscope

When high-magnification images are taken with a quasi-confocal line scanning ophthalmoscope (LSO), the quality of images always suffers from Gaussian noise, and the signal to noise ratio (SNR) is very low for a safer laser illumination. In addition, motions of the retina severely affect the stabilization of the real-time video resulting in significant distortions or warped images. We describe a scale-invariant feature transform (SIFT) algorithm to automatically abstract corner points with subpixel resolution and match these points in sequential images using an affine transformation. Once n images are aligned and averaged, the noise level drops by a factor of [Formula: see text] and the image quality is improved. The improvement of image quality is independent of the acquisition method as long as the image is not warped, particularly severely during confocal scanning. Consequently, even better results can be expected by implementing this image processing technique on higher resolution images.

Podosomes revealed by advanced bioimaging: what did we learn?

Podosomes are micrometer-sized, circular adhesions formed by cells such as osteoclasts, macrophages, dendritic cells, and endothelial cells. Because of their small size and the lack of methods to visualize individual proteins and protein complexes, podosomes have long been considered a simple two-module structure with a protrusive actin core and a surrounding adhesive ring composed of integrins and cytoskeletal adaptor proteins such as vinculin and talin. In the past decade, the applications of fluorescence based techniques that circumvent the diffraction limit of conventional light microscopy took a major leap forward. Podosomes have been imaged by a variety of these super-resolution methods, and in this concise review we discuss how these super-resolution data have increased our understanding of the podosome ultra-structure and function.