No abstract

The Wnt antagonist Dickkopf-1 (Dkk1) is a negative regulator of osteoblast function and bone mass. However, because of the lack of appropriate models, many aspects of its role in the regulation of postnatal bone turnover and its cellular source have remained unknown. In this study, we deleted Dkk1 postnatally and in different cell types using various Cre-drivers (Rosa26-ERT2-Cre, Osx-cre, Dmp1-Cre) and assessed to which extent cells of the osteoblastic lineage contribute to the effects of Dkk1 on bone turnover and homeostasis. Female and male mice were examined at 12 weeks of age. Mice with a global or cell type-specific deletion of Dkk1 showed a two- to threefold higher bone volume compared with their Cre-negative littermates. The mineral apposition rate and the bone formation rate were increased two- to fourfold in all three mouse lines, despite a significant increase in systemic and skeletal levels of sclerostin. Dkk1 deletion further reduced the number of osteoclasts about twofold, which was accompanied by a strong decrease in the receptor activator of nuclear factor-κB ligand/osteoprotegerin mRNA ratio in femoral bone. Despite similar increases in bone mass, the deletion of Dkk1 in osterix-expressing cells reduced circulating Dkk1 significantly (males, -79%; females, -77%), whereas they were not changed in Dkk1 ;Dmp1-Cre mice. However, both lines showed significantly reduced Dkk1 mRNA levels in bone. In summary, we show that lack of Dkk1 in cells of the osteoblastic lineage leads to high bone mass with increased bone formation, despite increased levels of sclerostin. Moreover, the majority of systemic Dkk1 appears to originate from osteoprogenitors but not from mature osteoblasts or osteocytes. Nevertheless, the amount of Dkk1 produced locally by more mature osteogenic cells is sufficient to modulate bone mass. Thus, this study highlights the importance of local Wnt signaling on postnatal bone homeostasis. © 2018 American Society for Bone and Mineral Research.

Dickkopf‐1 (Dkk1) is a negative regulator of bone formation and bone mass and is deregulated in bone loss induced by arthritis and glucocorticoid (GC) exposure. However, the role of Dkk1 in these pathological processes is still unknown. Here, we used conditional Dkk1 knock‐out mice to determine the role of Dkk1 produced by osteolineage cells in the development of arthritis and GC‐induced bone loss. Osteoprogenitor (Osx‐Cre)‐ and osteocyte (Dmp1‐Cre)‐specific knock‐out mice and their Cre‐negative controls were subjected to two arthritis models, K/BxN and antigen‐induced arthritis. Disease induction and progression were assessed. GC‐induced bone loss was induced in 25‐week‐old female mice by implanting prednisolone (7.5 mg) slow‐release pellets for 4 weeks. Dkk1fl/fl;Osx‐Cre mice subjected to K/BxN arthritis showed mildly reduced disease severity with reduced infiltration of neutrophils and T cells into affected joints and reduced bone erosions compared with Cre‐negative controls. Osteocyte‐specific Dkk1 deletion did not affect disease severity or local bone erosions. However, systemic bone loss at the spine was less severe in both mouse lines. In contrast to arthritis, both lines were protected from GC‐induced bone loss. Although the Cre‐negative controls lost about 26% and 31% bone volume potentially caused by decreased bone formation, Cre‐positive mice did not exhibit such alterations. Dkk‐1 deficiency in osteolineage cells protects against GC‐induced bone loss, whereas it had only minor effects in arthritis. Therefore, Dkk1 may be a promising therapeutic target especially for bone diseases in which inhibition of bone formation represents the predominant mechanism. © 2019 American Society for Bone and Mineral Research.

We realize an ultracompact nanocytometer for real-time impedimetric detection and classification of subpopulations of living cells. Nanoscopic nanowires in a microfluidic channel act as nanocapacitors and measure in real time the change of the amplitude and phase of the output voltage and, thus, the electrical properties of living cells. We perform the cell classification in the human peripheral blood (PBMC) and demonstrate for the first time the possibility to discriminate monocytes and subpopulations of lymphocytes in a label-free format. Further, we demonstrate that the PBMC of acute myeloid leukemia and healthy samples grant the label free identification of the disease. Using the algorithm based on machine learning, we generated specific data patterns to discriminate healthy donors and leukemia patients. Such a solution has the potential to improve the traditional diagnostics approaches with respect to the overall cost and time effort, in a label-free format, and restrictions of the complex data analysis.