Disruption of PTH Receptor 1 in T Cells Protects against PTH-Induced Bone Loss

Hyperparathyroidism in humans and continuous parathyroid hormone (cPTH) treatment in mice cause bone loss by regulating the production of RANKL and OPG by stromal cells (SCs) and osteoblasts (OBs). Recently, it has been reported that T cells are required for cPTH to induce bone loss as the binding of the T cell costimulatory molecule CD40L to SC receptor CD40 augments SC sensitivity to cPTH. However it is unknown whether direct PTH stimulation of T cells is required for cPTH to induce bone loss, and whether T cells contribute to the bone catabolic activity of PTH with mechanisms other than induction of CD40 signaling in SCs.Here we show that silencing of PTH receptor 1 (PPR) in T cells blocks the bone loss and the osteoclastic expansion induced by cPTH, thus demonstrating that PPR signaling in T cells is central for PTH-induced reduction of bone mass. Mechanistic studies revealed that PTH activation of the T cell PPR stimulates T cell production of the osteoclastogenic cytokine tumor necrosis factor alpha (TNF). Attesting to the relevance of this effect, disruption of T cell TNF production prevents PTH-induced bone loss. We also show that a novel mechanism by which TNF mediates PTH induced osteoclast formation is upregulation of CD40 expression in SCs, which increases their RANKL/OPG production ratio.These findings demonstrate that PPR signaling in T cells plays an essential role in PTH induced bone loss by promoting T cell production of TNF. A previously unknown effect of TNF is to increase SC expression of CD40, which in turn increases SC osteoclastogenic activity by upregulating their RANKL/OPG production ratio. PPR-dependent stimulation of TNF production by T cells and the resulting TNF regulation of CD40 signaling in SCs are potential new therapeutic targets for the bone loss of hyperparathyroidism

Masking of Time-Frequency Patterns in Applications of Passive Underwater Target Detection

Spectrogram analysis of acoustical sounds for underwater target classification is utilized when loud nonstationary interference sources overlap with a signal of interest in time but can be separated in time-frequency (TF) domain. We propose a signal masking method which in a TF plane combines local statistical and morphological features of the signal of interest. A dissimilarity measure D of adjacent TF cells is used for local estimation of entropy H, followed by estimation of ΔH=Htc−Hfc entropy difference, where Hfc is calculated along the time axis at a mean frequency fc and Htc is calculated along the frequency axis at a mean time tc of the TF window, respectively. Due to a limited number of points used in ΔH estimation, the number of possible ΔH values, which define a primary mask, is also limited. A secondary mask is defined using morphological operators applied to, for example, H and ΔH. We demonstrate how primary and secondary masks can be used for signal detection and discrimination, respectively. We also show that the proposed approach can be generalized within the framework of Genetic Programming