Pannexin1 (Panx1) is a hemichannel-forming protein that participates in the communication of cells with the extracellular space. To characterize the role of osteoclastic Panx1 on bone, Panx1 fl/fl ;TRAP-Cre (Panx1 ΔOc ) mice were generated, and compared to Panx1 fl/fl littermates at 6 weeks of age. Total and femoral BMD was ~20% lower in females and males whereas spinal BMD was lower only in female Panx1 ΔOc mice. μCT analyses showed that cortical bone of the femoral mid-diaphysis was not altered in Panx1 ΔOc mice. In contrast, cancellous bone in the distal femur and lumbar vertebra was significantly decreased in both female and male Panx1 ΔOc mice compared to Panx1 fl/fl controls and was associated with higher osteoclast activity in female Panx1 ΔOc mice, with no changes in the males. On the other hand, vertebral bone formation was decreased for both sexes, resulting from lower mineral apposition rate in the females and lower mineralizing surface in the males. Consistent with an osteoclastic effect in female Panx1 ΔOc mice, osteoclast differentiation with RANKL/M-CSF and osteoclast bone resorbing activity in vitro were higher in female, but not male, Panx1 ΔOc mice, compared to Panx1 fl/fl littermates. Surprisingly, although Panx1 expression was normal in bone marrow stromal-derived osteoblasts from male and female Panx1 ΔOc mice, mineral deposition by male (but not female) Panx1 ΔOc osteoblasts was lower than controls, and it was reduced in male Panx1 fl/fl osteoblasts when conditioned media prepared from male Panx1 ΔOc osteoclast cultures was added to the cell culture media. Thus, deletion of Panx1 in TRAP-expressing cells in female mice leads to low bone mass primarily through a cell autonomous effect in osteoclast activity. In contrast, our evidence suggests that changes in the osteoclast secretome drive reduced osteoblast function in male Panx1 ΔOc mice, resulting in low bone mass.

This paper explores a new class of measures for the detection of changes in images, specially for images acquired from different classes of sensors such as synthetic aperture radar (SAR) systems or computerized axial tomography (CAT) systems, monitoring patients. The problems become very challenging as the local statistics may be different even though the observations in the images may be similar. By exploiting this similarity new approaches are proposed for change detection. Based on the assumption that some form of dependence exists between the images, this dependence can be modeled by copulas. By using the conditional copula and the second image to simulate the distribution of first image, the dependence between the two images may be more closely modeled by the ensuing joint distribution. As a follow on, the symmetrical Kullback-Leibler distance can be used to obtain the change indicator between the distributions associated with the two images. In this paper the conditional copula is used as a change detector and applied to scenes from two distinct and different image families -SAR and CAT, and its performance compared with that of conventional change detection algorithms, based on a pixel based difference measure and on local pixel statistics